Qualitative Spatial Reasoning about Line Segments

cultivate aesthetic quality -回复如何培养审美品质。

第一步：了解审美品质的概念和重要性（150-200字）审美品质是指对于美的感觉和理解能力，以及对美学原则的应用能力。

它是个人对于美的主观感受与客观判断的综合体现。

培养审美品质对个人的成长和全面发展具有重要意义。

首先，它有助于提升个人对于艺术作品和自然景观的欣赏能力，能够让人更深入地体验和理解艺术创作的内涵。

其次，审美品质培养还能帮助个人鉴别真伪、区分高下，提高审美眼光，避免受伪劣产品的影响。

最后，审美品质的培养也有助于提高个人的创造力和想象力，对于各种领域的工作和生活有着积极的促进作用。

第二步：培养美的感受力（300-400字）培养美的感受力是培养审美品质的第一步。

而获得美的感受力的最佳方式就是通过参观艺术展览和博物馆。

艺术展览让人接触到各种形式的艺术作品，如绘画、雕塑和摄影等，有利于培养个人对于不同艺术形式的欣赏和理解能力。

博物馆则提供了与文化和历史相关的展品，通过与这些文化遗产接触，人们可以更好地理解艺术家的创作背景和时代背景，提升审美品质。

此外，观看电影、听音乐和参加舞台表演等也是培养美的感受力的重要途径。

电影是一种融合了音乐、摄影、绘画和文字等多种艺术形式的媒介，同时能够让观众通过影片剧情感受到导演的审美理念。

音乐是人类创作的一种高度抽象的艺术形式，通过欣赏音乐作品，人们可以培养对音乐的欣赏能力和审美品味。

而参加舞台表演则能够更直接地感受到演员的表演技巧和剧本的精彩。

批判性欣赏也是培养美的感受力的重要手段。

通过学习艺术史和文学理论等相关知识，人们能够进一步理解和分析艺术作品的内涵和创作意图，提高对作品的评判和欣赏能力。

第三步：学习美学原则和艺术技巧（400-500字）了解美学原则和艺术技巧是培养审美品质的另一个重要步骤。

美学原则是指古今中外对于美的规律和准则的总结，通过学习这些原则，人们可以更好地理解和应用美的规律。

个人素质英文作文英文：Personal qualities are essential for success in life, both personally and professionally. In my opinion, the most important personal qualities include self-discipline, adaptability, and communication skills.Self-discipline is crucial because it allows us to stay focused on our goals and achieve them. It means having the ability to control our impulses and resist temptation. For example, if I have a deadline for a project, I make sure to set aside time each day to work on it, even if I would rather do something else.Adaptability is also important because life is unpredictable, and we need to be able to adjust to changing circumstances. This means being open-minded and willing to try new things. For instance, if I am faced with a new challenge at work, I try to approach it with a positiveattitude and a willingness to learn.Finally, communication skills are essential forbuilding relationships and achieving success in both personal and professional settings. This means being ableto express oneself clearly and listen actively. For example, if I am working on a team project, I make sure to communicate my ideas clearly and listen to the ideas of my teammates.Overall, personal qualities are key to success in life, and self-discipline, adaptability, and communication skills are among the most important qualities to cultivate.中文：个人素质对于个人和职业生涯的成功至关重要。

Personal qualities are the essential characteristics that define an individuals behavior, attitude,and values.They play a crucial role in shaping ones life and interactions with others.Here are some key personal qualities that are often emphasized in English compositions:1.Integrity:This is the quality of being honest and having strong moral principles.It involves telling the truth,keeping promises,and maintaining a consistent set of values.2.Resilience:Resilience is the ability to bounce back from adversity and to cope with stress and challenges.It is important for personal growth and success.3.Empathy:Empathy is the capacity to understand and share the feelings of others.It fosters strong relationships and promotes a supportive community.4.Responsibility:Taking responsibility means being accountable for ones actions and decisions.It is a sign of maturity and is essential for building trust.5.Courage:Courage is the ability to face fear,danger,or adversity with confidence.It is often required to make difficult decisions and to stand up for what is right.6.Creativity:Creativity is the use of imagination to create something new or original.It is a valuable quality in various fields,from art to science.7.Selfdiscipline:Selfdiscipline involves controlling ones impulses and emotions to achieve goals.It is crucial for maintaining focus and achieving longterm objectives.8.Adaptability:Being adaptable means being able to adjust to new conditions or changes easily.It is important in a rapidly changing world.9.Curiosity:Curiosity is the desire to learn or know more about something.It drives exploration and the pursuit of knowledge.10.Teamwork:Teamwork is the collaborative effort of a group to achieve a common goal or to complete a task in the most effective and efficient way.11.Leadership:Leadership involves guiding,directing,and influencing others towards achieving a common goal.It requires a combination of skills,including communication, decisionmaking,and motivation.12.Perseverance:Perseverance is the ability to continue in a course of action despitedifficulty or opposition.It is often the key to achieving longterm goals.13.Humility:Humility is the quality of being modest and respectful.It involves recognizing ones limitations and being open to learning from others.14.Openmindedness:An openminded person is willing to consider new ideas and perspectives.It is important for personal growth and for fostering diversity of thought.munication Skills:Effective communication is the ability to express oneself clearly and listen to others with understanding.It is vital in both personal and professional settings.When writing an English composition about personal qualities,its important to provide examples or anecdotes that illustrate these qualities in action.This helps to make the essay more engaging and relatable to the reader.Additionally,discussing the importance of these qualities in various contexts,such as in education,the workplace,or in social interactions,can add depth to the composition.。

初二英语写作风格与文体特色判断练习题40题1.This story is full of vivid descriptions and exciting events. The writing style can be described as________.A.boringB.plainC.livelyD.dull答案：C。

本题考查记叙文写作风格判断。

A 选项boring 意为“无聊的”；B 选项plain 意为“平淡的”；C 选项lively 意为“生动活泼的”；D 选项dull 意为“枯燥的”。

题干中提到故事充满生动的描述和令人兴奋的事件，所以写作风格应是生动活泼的，答案是C。

2.The narrative has a simple plot and straightforward language. The writing style is________.plexB.confusingC.simplisticD.intricate答案：C。

本题考查记叙文写作风格判断。

A 选项complex 意为“复杂的”；B 选项confusing 意为“令人困惑的”；C 选项simplistic 意为“简单的”；D 选项intricate 意为“错综复杂的”。

题干中提到叙事有简单的情节和直白的语言，所以写作风格是简单的，答案是C。

3.The story is told in a slow-paced manner with detailed descriptions.The writing style is________.A.hurriedB.rushedC.leisurelyD.fast-paced答案：C。

本题考查记叙文写作风格判断。

A 选项hurried 意为“匆忙的”；B 选项rushed 意为“急促的”；C 选项leisurely 意为“悠闲的”；D 选项fast-paced 意为“快节奏的”。

Int. Joint Conf. on Artificial Intelligence (IJCAI 93), Chambéry, France, 1993 Orientation and Qualitative Angle for Spatial ReasoningLongin Jan Latecki Ralf RöhrigUniversity of HamburgDepartment of Computer ScienceBodenstedtstr. 162000 Hamburg 50, Germanye-mail: {latecki,roehrig}@informatik.uni-hamburg.deAbstractThough arrangement knowledge is well suitedfor qualitative representations of spatial situations, if we only use this kind of knowledge,we cannot do interesting inferences about relative positions of points in the plane. For example, if we know the orientation of two triangles over four points, we cannot say anything about the orientation of the other two triangles. In this paper, we show that the augmentation of arrangement knowledge by qualitative angles leads to interesting and useful inferences.IntroductionQualitative reasoning deals with reasoning on the conceptual level. Most approaches in the area of qualitative spatial reasoning define a set of spatial relations and show the connections of these relations in composition tables. Each entry in such a table is verified by informal considerations of some pictures showing the concepts, or by general quantitative considerations. This means there is an implicit quantitative semantics underlying the spatial relations. In this sense each qualitative inference is semantically verified in three steps: 1. definition of the qualitative concepts in quantitative terms, 2. quantitative reasoning, and 3. qualitative abstraction. Each of these steps has its inherent problems: The quantitative definition of spatial concepts is often context dependent, quantitative reasoning is a difficult problem in non-trivial domains, and the qualitative abstraction often entails a loss of information. For these reasons the underlying quantitative semantics is kept implicitly in most systems.Our approach takes two cognitively motivated spatial concepts, arrangement and angles, and offers a context independent well defined mapping of these concepts to quantitative regions which can be described by angle intervals. The quantitative reasoning process is fairly simple due to interval arithmetic, and the qualitative abstraction step performs without any loss of information due to the invertability of the well-defined mapping in the definition step.Problem descriptionReasoning about cognitive maps means explication of implicit relations among spatial objects of the domain. One of the possible formal descriptions of two dimensional cognitive maps is the abstraction of objects to points in the plane. Then spatial relations among objects can be represented by relative positions of the points. These relative positions are completely described by triangles among each triple of points. So, the reasoning task can be reduced to the problem of finding the descriptions of triangles. In this paper, we will concentrate on a basic version of this task: Given two triangles over four points in the plane, find the description of the other two. For example, in Figure 1 triangles ABC and CBD are given, and we are looking for a description of ABD and ACD.ABCDFigure 1. Triangles ABC and CBD are given, and we are looking for a description of ABD and ACD.It is a well known fact in classical geometry that the latter two triangles are completely determined by the first two. However, if we model reasoning processes in cognitive science, we usually do not deal with complete metric knowledge as is the case in classical geometry. Since people are able to do geometrical reasoning without complete metric knowledge, thequestion is which kind of knowledge they use. The simplest approach in cognitive science is to adopt arrangement information as described in [Schlieder, 1990]. There, relative positions are described in terms of the orientation of triangles, clockwise or counterclockwise. If, for example, a triangle ABC is oriented counterclockwise, then we know that point C is to the left of the straight line AB (see Figure 2). The distinction of a left and right hand side is clearly a cognitively motivated concept.Cright Figure 2. If triangle ABC is oriented counterclockwise, then weknow that C is to the left of the straight line AB. Arrangement knowledge has been successfully applied in Artificial Intelligence (see [Levitt andLawton, 1990; Schlieder, 1990]) and in Computational Geometry (see [Bokowski and Sturmfels, 1989]). Though arrangement knowledge is well suited for qualitative representations of spatial situations, if we only use this kind of knowledge, we cannot do inferences we are interested in, as the following example shows. Given the orientation of two triangles over four points, it is not possible to say anything about the orientation of the other two triangles. In bothFigures 3a and 3b, triangle ABC is oriented counterclockwise and BCD is oriented clockwise, but triangle ABD is oriented differently in Figures 3a and3b. Of course, the same situation can be constructed for triangle ACD.DBCADBCAa) b) Figure 3. Triangle ABC is oriented counterclockwise and BCD is oriented clockwise, but triangle ABD is oriented differently.Now the question is whether one can find another cognitively motivated concept for representing spatial situations without using metric information. There is psychological evidence that people are able to recognize the right angle (especially while treating the angle from the vertex perspective), and so are able to distinguish an acute angle from an obtuse angle. Therefore, it is straightforward to augment the concept of arrangement information by the qualitativedistinction of acute and obtuse angles. These two concepts of arrangement and qualitative angles fit together quite well, since both describe orientation information.NotationWhen introducing a system integrating arrangement and qualitative angles, for reasons of simplicity and transparency, we will treat neither the concept of collinearity of three points, nor the concept of right angles. This means that we will distinguish situations in which a point C is to the left or to the right of a straight line AB, but we will exclude situations where point C is on the line. In the same manner we willdistinguish situations where three points form an acute or an obtuse angle, but we will exclude situations where they form exactly the right angle. The augmentation of the system by these concepts is straightforward.Similar to the representation of arrangement information, the relative positions of triples of points will be described by triangles in our system. Each triangle will be represented by qualitative information about its three angles and its orientation. Orientation will be denoted by "+" for counterclockwise and "-" for clockwise. Qualitative angles will be abbreviated by "ac" for acute and "ob" for obtuse. For example, the representation of the triangle presented in Figure 4a isshown in Figure 4b. An obvious observation is the fact that if one angle is obtuse, the other two have to be acute. A CABC = + A = ac B = ac c = oba)b)Figure 4. Representation of triangle ABC.Since our inference processes are based on qualitativeangles, we will introduce a special notation for a single angle. We will denote an angle XYZ by an ordered pair consisting of the orientation of points XYZ and the qualitative angle in Y. For example, angle CAB of thetriangle presented in Figure 4 will be described as CAB(+, ac). As it is easy to note, if we know the orientation of one angle, we know the orientation of the whole triangle, so we can infer the orientation of the other angles. This simple fact together with the fact that every triangle can have only one obtuse angle forms some useful inference rules for reasoning about a single triangle.ReasoningInference RuleThe following examples show the profit in the reasoning process we get from combining arrangement and qualitative angle information. We have shown that given the orientation of two triangles over four points, it is not possible to infer anything about the orientation of a third triangle. However, the following example will demonstrate that when arrangement information is augmented with qualitative angles, we can conclude arrangement information about the third triangle. If we get the constellation presented in Figure 5, where ABC as well as CBD form counterclockwise oriented acute angles, then we know that D is to the left of line AB (i.e. triangle ABD is oriented counter-clockwise), though we do not know whether angle ABD is acute or obtuse, idicated by the dotted lineNow we present a rule that formalizes the above inferences. The general inference schema is to add two adjacent angles ABC and CBD in the vertex B to obtain a third angle ABD, as the following figure illustrates:ABC CBDABDFigure 8. The general inference schema is to add two adjacent angles ABC and CBD in the vertex B to obtain a third angle ABD.In the remainder of this section, we will show how arrangement and qualitative angle information will be passed through this schema. We are looking for a basic concept that underlies the above two concepts.As we mentioned above, arrangement information splits the plane into two disjoint regions, the left and the right hand side (of line AB in Figure 9a). Another observation is also that angle information splits the plane into two disjoint regions (at line perpendicular to line AB in Figure 9b). For any point C below the perpendicular line, angle ABC is acute, whereas for any point C above that line angle ABC is obtuse. If we combine these two observations, we obtain a division of the unit circle into four quadrants, which for computational reasons we name 0, 1, 2 and 3 as shown in Figure 9c.ABC(+, ac) CBD(+, ac)ABD(+, *)a)b)Figure 5. If ABC and CBD form counterclockwise oriented acute angles, then we know that D is to the left of line AB, though we do not know whether angle ABD is acute or obtuse.This inference is valid, because if we add two acute angles with the same orientation, we obtain an angle of less than 180o , which means that D stays to the left of line AB.left B Aright +-obright -left +As another example consider a configuration as depicted in Figure 6. Point C is to the right of line AB and angle ABC is acute.CABC(-, ac) CBD(+, ac)ABD(*, ac)a)b)c)a) b) Figure 9. a) Arrangement information splits the plane into the left and the right hand side of line AB. b) Angle information splits the plane into two disjoint regions at line perpendicular to line AB. c) If we combine these two observations, we obtain a division of theunit circle into four quadrants. Figure 6. If ABC is a negatively oriented acute angle and CBD is apositively oriented acute angle, then we can conclude that angleABD will be acute, though we do not know the orientation oftriangle ABD. Quadrant 0 corresponds to a position of point C forming a negatively oriented acute angle ABC, quadrant 1 to a negatively oriented obtuse angle,quadrant 2 to a positively oriented acute angle and quadrant 3 to a positively oriented obtuse angle.Now, if point D is to the left of line CB and angle CBD is acute, then we can conclude that angle ABD will be acute too. This is valid, because the difference of two acute angles is an acute angle itself. The dotted line shows that we cannot say anything about the position of D with respect to line AB, which will be denoted by "*".Now remember the example presented in Figure 6, where ABC was a negatively oriented acute angle and CBD a positively oriented acute angle. Using quadrants, we can express ABC(-, ac) as ABC(0) and CBD(+, ac) as CBD(3). The resulting angle ABD isacute, but without any orientation information, so either ABD(0) or ABD(3) holds, which we will denote ABD(0 | 3). This result can also be computed by the following general rule:If ABC(q1) and BCD(q2), then ABD(q3), whereq3 = ( (q1+q2 ) mod 4 | (q1+q2+1) mod 4 )and q1, q2 and q3 vary over quadrants 0, 1, 2 and 3. The correctness of this rule can easily be proved by simple angle interval addition, since the quadrants can be described as angle intervals of 90o magnitude. Because the quadrants of the resulting disjunction are always adjacent, the disjunction can be expressed in terms of either arrangement or qualitative angles. Therefore, we have the following correspondence:ABC(-, *) ABC(0 | 1)ABC(*, ob) ABC(1 | 2)ABC(+, *) ABC(2 | 3)ABC(*, ac) ABC(3 | 0)Figure 10. The correspondence between triangle description and adjacent quadrants.To demonstrate how to use this rule, we will go back to the example in Figure 5. Using quadrants, the two positively oriented acute angles ABC(+, ac) and CBD(+, ac) will be represented as ABC(3) and CBD(3). By our inference rule, the resulting angle will be ABD(2 | 3), which means that angle ABD is positively oriented and we do not know anything about the qualitative angle: ABD(+, *), as expected, due to the above example. The inference is illustrated in the following figure:ABC(+, ac) ABC(3)CBD(+, ac) CBD(3)_______ABD(+, *) ABD(2 | 3)Figure 11. Two positively oriented acute angles ABC and CBD result in a positively oriented triangle ABD.Problem SolutionIn this section, we will return to our original problem of finding the qualitative description in terms of arrangement and angles of the remaining triangles when given two triangles over four points in the plane. We will demonstrate that our inference rule provides a solution.The general problem is depicted in Figure 1. Knowing the orientation of a triangle ABC and the qualitative angles in A, B and C as well as the orientation and angles of a triangle BCD, we ask for the orientation and the angles of triangle ABD (the case for ACD will be treated analogously). The inference is based on the angle addition rule. Obviously, we can apply this rule only at point B, since this is the only point where two angles with one side in common are given, namely ABC and CBD. As an illustration, let us treat the situation presented in Figure 12.ABDCFigure 12. The angle addition is done at point B.Concerning the angles in point B, the situation is the same as in Figure 5. The resulting angle ABD can therefore be computed as shown in Figure 11. The obtained result ABD(+, *) will be interpreted as a counterclockwise orientation of triangle ABD. Let us note once more that knowing only orientation of triangles ABC and CBD, we could not make any inference, since a clockwise orientation of triangle ABD would be consistent with these orientation assumptions as well (cf. Figure 13).ABCDFigure 13. We would not know anything about the orientation of triangle ABD in Figure 12 if we only knew the orientation of triangles ABC and CBD.Another example where qualitative angles can be inferred is depicted in Figure 14: triangle ABC is oriented positively with an obtuse angle in B, whereas triangle CBD is oriented positively with an acute angle in B.ABCDFigure 14. The angle addition is done at point B.Again we can use our rule for angle addition in the vertex B, which leads to the following inference:ABC(+, ob) ABC(2) CBD(+, ac) CBD(3) _______ ABD(*, ob) ABD(1 | 2)Figure 15. Two positively oriented angles, an acute ABC and anobtuse CBD, result in an obtuse angle ABD. So, we obtain the qualitative angle information that angle ABD is obtuse. Knowing that one triangle canhave at most one obtuse angle, we can additionally infer that the other two angles in triangle ABD are acute. In this situation, we do not obtain any orientation information, as expected, because triangle ABD can be oriented positively (cf. Figure 14) as well as negatively (cf. Figure 16).AC DBFigure 16. We do not know anything about the orientation oftriangle ABD in Figure 14.ApplicationsIn the problem description we introduced triangles to describe relative positions of points in the plane. Now the question arises as to which relative positions of points can be described with arrangement and qualitative angle knowledge. Figure 17 shows the 8 possible positions of a point C with respect to a pair of points A and B that are distinguishable using ourFigure 17. Subdivision of the plane induced by arrangement andqualitative angle knowledge.The vertical line AB divides the plane into two regionswhich correspond to possible positions of point C withregard to arrangement knowledge (of course, we referto the line as "vertical" for purposes of illustrations, butit can in fact be oriented arbitrarily). If point C is to theleft of AB, then triangle ABC is orientedcounterclockwise, whereas if point C is to the right ofAB, then triangle ABC is in clockwise orientation. Thequalitative angle information provides furthersubdivision: If triangle ABC has an obtuse angle in B,then point C has to be above the horizontal line in B. In the same way, if the angle in A is obtuse, then C has to be below the horizontal line in A. In the case whereboth angles in A and B are acute, point C will be in the region between the horizontal lines. This region can be further subdivided into regions inside and outside of the circle, depending on whether the angle in C is obtuse or acute. Note that if point C were on one of thehorizontal lines or on the circle, then one of the angles in triangle ABC would be a right angle, but for reasons of simplicity we have not yet extended our representation to those singular cases. For the same reasons, we do not treat collinearity of A, B and C, which corresponds to the vertical line AB.The obtained subdivision of the plane can be interpreted as a refinement of the system of disjoint orientation relations used by Freksa [1992]. Freksa starts with a left/right and front/back dichotomy in a point B with respect to a reference vector AB. He endsup with 15 disjoint qualitative locations depicted inFigure 18.11Figure 18. Subdivision of the plane used by Freksa [1992].In Freksa´s system, the 15 locations have natural language correspondences, for example, straight-front of B (1), left-front of B (2), left-neutral of B (3), left-back ofB, and left-front of A (4), and so on. Spatial inferences are done through the same schema as in our representation (see Figure 8). Each inference step can be encoded in a table showing the composition of the15 qualitative locations. Freksa uses a neighborhoodrelation of the qualitative locations to reduce the size of the composition table. Since our inferences are based on an analytic calculus, we do not need any table look-ups.Freksa and Zimmermann [1992] use these qualitativedescriptions for route finding purposes. They illustratethe problems they treat by the following example:"Walk down the road (ab). You will see a church (c) inthe front of you on the left. Before you reach thechurch turn down the path that leads forward to theright (bd)." The question is where the church is withrespect to the path (bd):dFigure 19. Route finding scenario used in [Freksa and Zimmermann, 1992].To answer this question, Freksa and Zimmermann use special operations to transform the input information that (d) is right-front of vector (ab) to an expression based on vector (bd): (a) is right-back of (bd). Knowing this together with the input fact: (c) is left-front of (ab), we can infer that (c) is to the left of (bd), which answers the question.Due to the circle, our representation leads to a finer subdivision of the plane. If Freksa´s system is augmented by this circle, it turns out that the composition of the operations used to transform the input information is internal, and that these operations form an algebraic group. This is not the case in the original formalism of Freksa and Zimmermann. These algebraic properties simplify the route finding process. The description of these properties and their impact on the reasoning process will be the topic of a forthcoming paper.Arrangement knowledge is used successfully in [Levitt and Lawton, 1990] for qualitative navigation for mobile robots. Having augmented arrangement knowledge by qualitative angles, which leads to a finer subdivision of the plane, we expect further advantages in qualitative route finding.As the above example illustrates, our formalism can be used for performing inferences based on qualitative information treated from the observer´s perspective. Recently Jungert [1992] presented an extension of symbolic projections of [Chang et al., 1987] which is especially concerned with the observer´s point of view. We conjecture that combining these two formalisms would allow us to obtain a powerful system for qualitative spatial reasoning which could be used in motion planning and in building qualitative maps by autonomous systems. A big advantage of such a formalism is that it would not need any global coordinate system.It is also easy to incorporate arrangement and qualitative angle knowledge into a hybrid system for spatial reasoning which combines propositional and depictorial inferences, as presented in [Latecki and Pribbenow, 1992]. This is due to the propositional inference rule presented here and to the fact that using a finite grid as a representation frame for depictorial inferences, we can represent and retrieve arrangement and qualitative angle information in a simple way. AcknowledgementWe wish to thank Christian Freksa, whose work inspired us, and also Cao Yong, Rolf Sander, and Kai Zimmermann.References[Bokowski and Sturmfels, 1989] J. Bokowski and B. Sturmfels. Computational Synthetic Geometry. Springer-Verlag, Berlin, 1989.[Chang et al., 1987] S.-K. Chang, Q.Y. Shi, and C.W. Yan. Iconic indexing by 2D strings. IEEE transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 9, No. 3, 413-428, 1987.[Freksa, 1992] C. Freksa. Using Orientation Information for Qualitative Spatial Reasoning. Proceedings of the International Conference GIS - From Space to Territory. Theories and Methods of Spatio-Temporal Reasoning. Pisa, Italy, September 1992. [Freksa and Zimmermann, 1992] C. Freksa and K. Zimmermann. On the Utilization of Spatial Structures for Cognitively Plausible and Efficient Reasoning. Proceedings of SMC ’92 – 1992 IEEE International Conference on Systems Man and Cybernetics, Chicago, October 1992.[Jungert, 1992] E. Jungert. The Observer´s Point of View: An extension of Symbolic Projections. Proceedings of the International Conference GIS - From Space to Territory. Theories and Methods of Spatio-Temporal Reasoning., 179-195, Pisa, Italy, September 1992.[Latecki and Pribbenow, 1992] L. Latecki and S. Pribbenow. On Hybrid Reasoning for Processing Spatial Expressions. Proceedings of the European Conference on Artificial Intelligence (ECAI 92), Vienna, Austria, August 1992.[Levitt and Lawton, 1990] T.S. Levitt and D.T. Lawton. Qualitative Navigation for Mobile Robots. Artificial Intelligence 44, 305-360, 1992.[Schlieder 1990a] C. Schlieder. Anordnung. Eine Fallstudie zur Semantik bildhafter Repräsentationen. In Freksa, C. and Habel C. (eds.): Repräsentation und Verarbeitung räumlichen Wissens, Springer-Verlag, Berlin, 1990.[Schlieder 1990b] C. Schlieder. Hamburger Ansichten oder Ein Problem der Repräsentation räumlichen Wissens. Proceedings of the 14th German Workshop on Artificial Intelligence (GWAI 90), 29-37, Springer-Verlag, Berlin, 1990.。

When discussing the qualities of a person,there are several key attributes that are often regarded as essential for personal development and social interaction.Lets explore some of these qualities in detail:1.Integrity:This is the quality of being honest and having strong moral principles.A person with integrity is consistent in their actions,values,and methodsregardless of who is watching.2.Empathy:The ability to understand and share the feelings of others.Empathetic individuals are sensitive to the emotional states of those around them and can offer comfort and support.3.Resilience:This refers to the capacity to recover quickly from difficulties.Resilient people are able to bounce back from setbacks and maintain a positive outlook despite challenges.4.Humility:A humble person does not think of themselves as more important than others. They are willing to listen and learn from others,and they do not boast about their achievements.5.Courage:The ability to face fear,danger,or pain without shrinking.Courageous individuals are willing to stand up for what they believe in,even when it is difficult.6.Kindness:A kind person is considerate and caring towards others.They are willing to help and show compassion without expecting anything in return.7.Responsibility:This is the ability to be accountable for ones actions.Responsible individuals take ownership of their decisions and are reliable in fulfilling their commitments.8.Patience:The capacity to accept or tolerate delays,problems,or suffering without becoming annoyed or anxious.Patient people are able to remain calm and composed in difficult situations.9.Openmindedness:Being open to new ideas and willing to consider different perspectives.Openminded individuals are not rigid in their thinking and are receptive to change.10.Selfdiscipline:The ability to control ones feelings and overcome immediate temptations in order to achieve longterm goals.Selfdisciplined people are able toprioritize their tasks and manage their time effectively.11.Curiosity:A desire to learn more about the world and to explore new ideas.Curious individuals are always asking questions and seeking knowledge.12.Perseverance:The determination to continue in a course of action in spite of difficulty or opposition.Persevering people do not give up easily and are committed to seeing their goals through to completion.13.Honesty:The quality of being truthful and sincere.Honest people are transparent in their communication and do not deceive others.14.Fairness:Treating people equally and without bias.Fair individuals ensure that everyone is given an equal opportunity and is treated justly.15.Creativity:The ability to think of new and original ideas.Creative people are able to approach problems in unique ways and come up with innovative solutions.These qualities are not only important for personal growth but also for building strong relationships and contributing positively to society.Cultivating these attributes can lead to a more fulfilling and successful life.。

个人素质英文作文素材模板1. Personal qualities are essential for success in life. They include characteristics such as resilience, adaptability, and determination. These qualities help individuals navigate through challenges and setbacks, allowing them to achieve their goals and reach their full potential.2. Another important personal quality is empathy. Being able to understand and share the feelings of others is crucial for building strong relationships and fostering a sense of community. Empathy allows individuals to connect with others on a deeper level and offer support when needed.3. Creativity is also a valuable personal quality that can lead to innovation and problem-solving. Thinkingoutside the box and approaching situations from different perspectives can result in unique solutions andbreakthrough ideas. Creativity is a driving force behind progress and growth in various fields.4. Honesty and integrity are fundamental personal qualities that build trust and credibility. Being truthful and ethical in all interactions demonstrates a strong moral character and sets a positive example for others. Honesty and integrity are essential for maintaining strong relationships and upholding a sense of fairness and justice.5. Personal qualities such as humility and open-mindedness are important for personal growth and learning. Being willing to acknowledge one's limitations and being open to new ideas and perspectives can lead to self-improvement and a broader understanding of the world. Humility and open-mindedness foster a sense of curiosityand a willingness to embrace change and diversity.6. Lastly, resilience and perseverance are key personal qualities that enable individuals to overcome obstacles and achieve success. Facing challenges with a positive attitude and a determination to keep moving forward can lead to personal growth and accomplishment. Resilience andperseverance are essential for navigating through life's ups and downs and emerging stronger on the other side.。

Qualitative Spatial Representation andReasoning in the SparQ-Toolbox Jan Oliver Wallgr¨u n,Lutz Frommberger,Diedrich Wolter,Frank Dylla,and Christian FreksaSFB/TR8Spatial CognitionUniversit¨a t BremenBibliothekstr.1,28359Bremen,Germany{wallgruen,lutz,dwolter,dylla,freksa}@sfbtr8.uni-bremen.deAbstract.A multitude of calculi for qualitative spatial reasoning(QSR)have been proposed during the last two decades.The number of practicalapplications that make use of QSR techniques is,however,comparativelysmall.One reason for this may be seen in the difficulty for people fromoutside thefield to incorporate the required reasoning techniques intotheir software.Sometimes,proposed calculi are only partially specifiedand implementations are rarely available.With the SparQ toolbox pre-sented in this text,we seek to improve this situation by making commoncalculi and standard reasoning techniques accessible in a way that allowsfor easy integration into applications.We hope to turn this into a com-munity effort and encourage researchers to incorporate their calculi intoSparQ.This text is intended to present SparQ to potential users andcontributors and to provide an overview on its features and utilization.1IntroductionQualitative spatial reasoning(QSR)is an establishedfield of research pursued by investigators from many disciplines including geography,philosophy,computer science,and AI[1].The general goal is to model commonsense knowledge and reasoning about space as efficient representation and reasoning mechanisms that are still expressive enough to solve a given task.Qualitative spatial representa-tion techniques are especially suited for applications that involve interaction with humans as they provide an interface based on human spatial concepts.Following the approach taken in Allen’s seminal paper on qualitative tempo-ral reasoning[2],QSR is typically realized in form of calculi over sets of spatial relations(like‘left-of’or‘north-of’).These are called qualitative spatial calculi.A multitude of spatial calculi has been proposed during the last two decades, focusing on different aspects of space(mereotopology,orientation,distance,etc.) and dealing with different kinds of objects(points,line segments,extended ob-jects,etc.).Two main research directions in QSR are mereotopological reasoning about regions[3,4,5]and reasoning about positional information(distance and orientation)of point objects[6,7,8,9,10,11,12]or line segments[13,14,15].In T.Barkowsky et al.(Eds.):Spatial Cognition V,LNAI4387,pp.39–58,2007.c Springer-Verlag Berlin Heidelberg200740J.O.Wallgr¨u n et al.addition,some approaches are concerned with direction relations between ex-tended objects[16,17]or combine different aspects of space[18,19].Despite this large variety of qualitative spatial calculi,the amount of applica-tions employing qualitative spatial reasoning techniques is comparatively small. We believe that one important factor for this is the following:Choosing the right calculus for a particular application is a challenging task,especially for people not familiar with QSR.Calculi are often only partially specified and usually no implementation is made available—if the calculus is implemented at all and not only investigated theoretically.As a result,it is not possible to“quickly”eval-uate how different calculi perform in practice.Even if an application developer has decided on a particular calculus,he has to invest serious efforts to include the calculus and required reasoning techniques into the application.For many calculi this is a time-consuming and error-prone process(e.g.involving writing down large composition tables,which are often not even completely specified in the literature).We think that researchers involved in the investigation of QSR will also benefit from reference implementations of calculi that are available in a coherent framework.Tasks like comparing different calculi with respect to expressiveness or average computational properties in a certain context would clearly be simplified.To provide a platform for making the calculi and reasoning techniques de-veloped in the QSR community available,we have started the development of a qualitative spatial reasoning toolbox called SparQ1.The toolbox supports bi-nary and ternary spatial calculi.SparQ aims at supporting the most common tasks—qualification,computing with relations,constraint-based reasoning(cp. Section3)—for an extensible set of spatial calculi.Our focus is on providing an implementation of QSR techniques that is tailored towards the needs of appli-cation developers.A similar approach has recently been reported in[20]where calculi and reasoning techniques are provided in form of a programming library and focuses on algebraic and constraint-based reasoning.SparQ,on the other hand,is a application program that can be used directly and provides a broader range of services.A complementary approach aiming at the specification and investigation of the interrelations between calculi has been described in[21]. There,the calculi are defined in the algebraic specification language CASL.We believe that a toolbox like SparQ can provide a useful interface between the the-oretical specification framework and the application areas of spatial cognition, like cognitive modeling or GIS.In its current version,SparQ mainly focuses on calculi from the area of reason-ing about the orientation of point objects or line segments.However,specifying and adding other calculi is simple.We hope to encourage researchers from other groups to incorporate their calculi in a community effort of providing a rich spa-tial reasoning environment.SparQ is designed as an open framework of single program components with text-based communication.It therefore allows for in-tegrating code written in virtually any programming language,so that already existing code can easily be integrated into SparQ.1Spa tial R easoning done Q ualitatively.Qualitative Spatial Representation and Reasoning in the SparQ-Toolbox41 Specifically,the goals of SparQ are the following:–providing reference implementations for spatial calculi from the QSR com-munity–making it easy to specify and integrate new calculi–providing typical procedures required to apply QSR in a convenient way–offering a uniform interface that supports switching between calculi–being easily integrable into own applicationsThe current version of SparQ and further documentation will be made avail-able at the SparQ homepage2.In the present text,we will describe SparQ and its utilization.The next section briefly recapitulates the relevant terms concerningQSR and spatial calculi as needed for the remainder of the text.In Section3,we describe the services provided by SparQ.Section4explains how new cal-culi can be incorporated into SparQ,and Section5describes how SparQ can beintegrated into applications.Finally,Section6contains a case study in which SparQ is employed to compare different calculi with respect to their ability ofdetecting the inconsistency in the Indian Tent Problem[22].2Reasoning with Qualitative Spatial RelationsA qualitative spatial calculus defines operations on afinite set R of spatialrelations.The spatial relations are defined over a particular set of spatial objects, the domain D.In the rest of the text,we will encounter the sets of points in theplane,of oriented line segments in the plane,and of oriented points in the planeas domains.While a binary calculus deals with binary relations R⊆D×D,a ternary calculus operates with ternary relations R⊆D×D×D.The set of relations R of a spatial calculus is typically derived from a jointly exhaustive and pairwise disjoint(JEPD)set of base relations BR so that eachpair of objects from D is contained in exactly one relation from BR.Everyrelation in R is a union of base relations.Since spatial calculi are typically used for constraint reasoning and unions of relations correspond to disjunctions ofrelational constraints,it is common to speak of disjunctions of relations as welland write them as sets{B1,...,B n}of base ing this convention,R is either taken to be the powerset2BR of the base relations or a subset of thepowerset.In order to be usable for constraint reasoning,R should contain at least the base relations B i,the empty relation∅,the universal relation U,and the identity relation Id.R should also be closed under the operations defined in the following.As the relations are subsets of tuples from the same Cartesian product,theset operations union,intersection,and complement can be directly applied: Union:R∪S={t|t∈R∨t∈S}Intersection:R∩S={t|t∈R∧t∈S}Complement:R=U\R={t|t∈U∧t∈R}2http://www.sfbtr8.uni-bremen.de/project/r3/sparq/42J.O.Wallgr¨u n et al.where R and S are both n-ary relations on D and t is an n-tuple of elements from D.The other operations depend on the arity of the calculus.2.1Operations for Binary CalculiFor binary calculi the other two important operations are conversion and com-position:Converse:R ={(y,x)|(x,y)∈R}(Strong)composition:R◦S={(x,z)|∃y∈D:((x,y)∈R∧(y,z)∈S)}For some calculi,nofinite set of relations exists that includes the base re-lations and is closed under composition as defined above.In this case,a weak composition is defined instead that takes the union of all base relations that have a non-empty intersection with the result of the strong composition:Weak composition:R◦weak S={B i|B i∈BR∧B i∩(R◦S)=∅}2.2Operations for Ternary CalculiWhile there is only one possibility to permute the two objects of a binary relation which corresponds to the converse operation,there exist5such permutations for the three objects of a ternary relation3,namely[23]:Inverse:INV(R)={(y,x,z)|(x,y,z)∈R}Short cut:SC(R)={(x,z,y)|(x,y,z)∈R}Inverse short cut:SCI(R)={(z,x,y)|(x,y,z)∈R}Homing:HM(R)={(y,z,x)|(x,y,z)∈R}Inverse homing:HMI(R)={(z,y,x)|(x,y,z)∈R}Composition for ternary calculi is defined according to the binary case: (Strong)comp:R◦S={(w,x,z)|∃y∈D:((w,x,y)∈R∧(x,y,z)∈S)} Other ways of composing two ternary relations can be expressed as a combina-tion of the unary permutation operations and the composition[24]and thus do not have to be defined separately.The definition of weak composition is identical to the binary case.2.3Constraint Reasoning with Spatial CalculiSpatial calculi are often used to formulate constraints about the spatial con-figurations of a set of objects from the domain of the calculus as a constraint satisfaction problem(CSP):Such a spatial constraint satisfaction problem then consists of a set of variables X1,...,X n(one for each spatial object)and a set of constraints C1,...,C m which are relations from the calculus.Each variable X i 3In general,two operations(permutation and rotation)are sufficient to generate all permuations(cmp.[20]).Therefore,not all of these operations need to be specified.Qualitative Spatial Representation and Reasoning in the SparQ-Toolbox43 can take values from the domain of the utilized calculus.CSPs are often de-scribed as constraint networks which are complete labeled graphs with a node for each variable and each edge labeled with the corresponding relation from the calculus.A CSP is consistent,if an assignment for all variables to values of the domain can be found,that satisfies all the constraints.Spatial CSPs usually have infinite domains and thus backtracking over the domains can not be used to determine consistency.Besides consistency,weaker forms of consistency called local consistencies are of interest in QSR.On the one hand,they can be employed as a forward checking technique reducing the CSP to a smaller equivalent CSP(one that has the same set of solutions).Furthermore,in some cases a form of local consistency can be proven to be not only necessary but also sufficient for consistency.If this is only the case for a certain subset S⊂R and this subset exhaustively splits R (which means that every relation from R can be expressed as a disjunction of relations from S),this at least allows to formulate a backtracking algorithm to determine consistency by recursively splitting the constraints and using the local consistency as a decision procedure for the resulting CSPs with constraints from S[25].One important form of local consistency is path-consistency which(in binary CSPs)means that for every triple of variables each consistent evaluation of thefirst two variables can be extended to the third variable in such a way that all constraints are satisfied.Path-consistency can be enforced syntactically based on the composition operation(for instance with the algorithm by van Beek[26])in O(n3)time where n is the number of variables.However,this syntactic procedure does not necessarily yield the correct result with respect to path-consistency as defined above.The same holds for syntactic procedures that compute other kinds of consistency.Whether syntactic consistency coincides with semantic consistency with respect to the domain needs be investigated for each calculus individually(see[27,28]for an in-depth discussion).2.4Supported CalculiAs mentioned above,qualitative calculi are based on a certain domain of basic entities:time intervals in the case of Allen’s Interval Calculus[2],or objects like points,line segments,or regions in typical spatial calculi.In the following,we will briefly introduce those calculi that are currently included in SparQ and that will be used in the examples later on.A quick overview is given in Table1which also classifies the calculi according to their arity(binary,ternary),their domain (points,oriented points,line segments,regions),and the aspect of space modeled (orientation,distance,mereotopology).FlipFlop Calculus(FFC)and the LR refinement.The FlipFlop calculus proposed in[9]describes the position of a point C(the referent)in the plane with respect to two other points A(the origin)and B(the relatum)as illustrated in Fig.1.It can for instance be used to describe the spatial relation of C to B as seen from A.For configurations with A=B the following base relations are dis-tinguished:C can be to the l eft or to the r ight of the oriented line going through44J.O.Wallgr¨u n et al.Table 1.The calculi currently included in SparQarity domain aspect of spaceCalculus binary ternary point or.point line seg.region orient.dist.mereot.FFC/LR √√√SCC √√√DCC √√√DRA c √√√OPRA m √√√RCC-5/84√√√A and B ,or C can be placed on the line resulting in one of the five relations i nside,f ront,b ack,s tart (C =A )or e nd (C =B )(cp.Fig.1).Relations for the case where A and B coincide were not included in Ligozat’s original definition[9].This was done with the LR refinement [29]that introduces the relations dou (A =B =C )and tri (A =B =C )as additional relations,resulting in a total of 9base relations.A LR relation rel LR is written as A,B rel LR C ,e.g.A,B r C as depicted in Fig.1.r Fig.1.The reference frame for the LR calculus,an refined version of the FlipFlop CalculusSingle Cross Calculus (SCC).The Single Cross Calculus is a ternary calculus that describes the direction of a point C (the referent)wrt.a point B (the relatum)as seen from a third point A (the origin).It was originally proposed in[6].The plane is partitioned into regions by the line going through A and B and the perpendicular line through B .This results in eight distinct orientations as illustrated in Fig.2(a).We denote these base relations by numbers from 0to 7instead of using linguistic prepositions,e.g.2instead of left as in [6].Relations 0,2,4,6are linear ones,while relations 1,3,5,7are planar.In addition,three special relations exist for the cases A =B =C (bc ),A =B =C (dou ),and A =B =C (tri ).A Single Cross relation rel SCC is written as A,B rel SCC C ,e.g.A,B 4C or A,B dou C .The relation depicted in Fig.2(a)is the relation A,B 5C .4Currently only the relational specification is available for RCC,but no ‘qualify’module (cmp.Section 3.1).Qualitative Spatial Representation and Reasoning in the SparQ-Toolbox45(a)Single Cross Calculus reference frame(b)The two Single Cross reference frames result-ing in the overall Double Cross Calculus reference frameFig.2.The Single and Double Cross reference systemsDouble Cross Calculus(DCC).The Double Cross calculus[6]can be seen as an extension of the Single Cross calculus adding another perpendicular,this time at A(see Fig.2(b)(right)).It can also be interpreted as the combination of two Single Cross relations,thefirst describing the position of C wrt.B as seen from A and the second wrt.A as seen from B(cf.Fig.2(b)(left)).The resulting partition distinguishes13relations(7linear and6planar)denoted by tuples derived from the two underlying SCC reference frames and four special cases, A=C=B(4a),A=B=C(b4),A=B=C(dou),and A=B=C(tri), resulting in17base relations overall.Fig.2(b)depicts the relation A,B53C. Coarse-grained Dipole Relation Algebra(DRA c).A dipole is an oriented line segment,e.g.as determined by a start and an end point.We will write d AB for a dipole defined by start point A and end point B.The idea of using dipoles wasfirst introduced by Schlieder[13]and extended in[14].In the coarse-grained variant of the Dipole Calculus(DRA c)describes the orientation relation between two dipoles d AB and d CD with the preliminary that A,B,C,and D are in general position,i.e.no three disjoint points are collinear. Each base relation is a4-tuple(r1,r2,r3,r4)of FlipFlop relations relating a point from one of the dipoles with the other dipole.r1describes the relation of C wrt.the dipole d AB,r2of D wrt.d AB,r3of A wrt.d CD,and r4of B wrt.d CD.The distinguished FlipFlop relations are l eft,r ight,s tart,and e nd(see Fig.1).Dipole relations are usually written without commas and parentheses, e.g.rrll.Thus,the example in Fig.3shows the relation d AB rlll d CD.Since the underlying points for a DRA c relation need to be in general position the r i can only take the values l eft,r ight,s tart,or e nd resulting in24base relations. Oriented Point Relation Algebra OPRA m.The OPRA m calculus[11] operates on oriented points.An oriented point is a point in the plane with an additional direction parameter.OPRA m relates two oriented points A and B and describes their relative orientation towards each other.The granularity46J.O.Wallgr¨u n et al.Fig.3.A dipole configuration:d AB rlll d CD in the coarse-grained Dipole Relation Algebra (DRA c )factor m ∈N determines the number of distinguished relations.For each of the two oriented points,m lines are used to partition the plane into 2m planar and 2m linear regions.Fig.4shows the partitions for the cases m =2(Fig.4(a))and m =4(Fig.4(b)).The orientation of the two points is depicted by the arrows starting at A and B ,respectively.The regions are numbered from 0to (4m −1).Region 0always coincides with the orientation of the point.An OPRA m relation rel OPRA m consist of pairs (i,j )where i is the number of the region of A which contains B ,while j is the number of the region of B that contains A .Theserelations are usually written as A m ∠ji B with i,j ∈Z 4m 5.Thus,the examples inFig.4depict the relations A 2∠17B and A 4∠313B .Additional relations describesituations in which both oriented points coincide.In these cases,the relation is determined by the number s of the region of A into which the orientation arrow of B falls (as illustrated in Fig.4(c)).These relations are written as A 2∠s B (A 2∠1B in the example).(a)with granularity m =2:A 2∠17B (b)with granularity m =4:A 4∠313B(c)case where A and B co-incide:A 2∠1B Fig.4.Two oriented points related at different granularities3SparQSparQ consists of a set of modules that provide different services required for QSR that will be explained below.These modules are glued together by a central script that can either be used directly from the console or included into own applications via TCP/IP streams in a server/client fashion (see Section 5).The general architecture is visualized in Fig.5.5Z 4m defines a cyclic group with 4m elements.Qualitative Spatial Representation and Reasoning in the SparQ-Toolbox47Fig.5.Module architecture of the SparQ toolboxThe general syntax for using the SparQ main script is as follows:$./sparq<module><calculus identifier><module-specific parameters> Example:$./sparq compute-relation dra-24complement"(lrll llrr)"where‘compute-relation’is the name of the module to be utilized,in this case the module for conducting operations on relations,‘dra-24’is the SparQ identifier for the dipole calculus DRA c,and the rest are module-specific parameters,here the name of the operation that should be conducted(‘complement’)and a string parameter representing the disjunction of the two dipole base relations lrll and llrr6.The example call thus computes the complement of the disjunction of these two relations.Some calculi have calculus-specific parameters,for example the granularity parameter in OPRA m.These parameters are appended with a‘-’after the calculus’base identifier.opra-3for example refers to OPRA3.SparQ currently provides the following modules:qualify transforms a quantitative geometric description of a spatial configu-ration into a qualitative description based on one of the supported spatial calculicompute-relation applies the operations defined in the calculi specifications (intersection,union,complement,converse,composition,etc.)to a set of spatial relationsconstraint-reasoning performs computations on constraint networks Further modules are planned in future extensions.They comprise a quantifi-cation module for turning qualitative scene descriptions back into quantitative 6Disjunctions of base relations are always represented as a space-separated list of the base relations enclosed in parentheses in SparQ.48J.O.Wallgr¨u n et al.geometric descriptions and a module for neighborhood-based spatial reasoning. In the following section we will take a closer look at the three existing modules.3.1Scene Descriptions and QualificationThe purpose of the‘qualify’module is to turn a quantitative geometric scene description into a qualitative scene description with respect to a particular cal-culus.Calculi are specified via the calculus identifier that is passed with the call to SparQ.Qualification is required for applications in which one wants to perform qualitative computations over objects represented by their geometric parameters.xFig.6.An example configuration of three dipoles The‘qualify’module reads a quantitative scene description and generates a qualitative one.A quantitative scene description is a list of base object de-scriptions(separated by spaces and enclosed in parentheses).Each base object description is a tuple consisting of an object identifier and object parameters that depend on the type of the object.For instance,let us say we are working with dipoles,i.e.oriented line segments.The object description of a dipole has the form‘(name x s y s x e y e)’,where name is the identifier of this particular dipole object and the rest are the coordinates of start and end point of the dipole.Let us consider the example in Fig.6which shows three dipoles A,B, and C.The quantitative scene description for this situation is:((A-2080)(B7-225)(C1-14.54.5))The‘qualify’module has one module-specific parameter that needs to be speci-fied:mode:This parameter controls which relations are included into the qualitative scene description:If‘all’is passed as parameter,the relations between each pair of objects will be determined.If it is‘first2all’only the relations between thefirst and all other objects are computed.The resulting qualitative scene description is a list of relation tuples(again separated by spaces and enclosed in parentheses).A relation tuple consists of theobject identifier of the relatum followed by a relation and the object identifier of the referent,meaning that thefirst object stands in this particular relation with the second object.The command to produce the qualitative scene description followed by the result is7:$./sparq qualify dra-24all$((A-2080)(B7-225)(C1-14.54.5))>((A rllr B)(A rllr C)(B lrrl C))If we had chosen‘first2all’as mode parameter the relation between B and C would not have been included in the qualitative scene description.3.2Computing with RelationsThe‘compute-relation’module realizes computations with the operations defined in the calculus specification.The module-specific parameters are the operation that should be conducted and one or more input relations depending on the arity of the operation.Assume we want to compute the converse of the dipole relation llrl.The corresponding call to SparQ and the result are:$./sparq compute-relation dra-24converse llrl>(rlll)The result is always a list of relations as operations often yield a disjunction of base relations.In the example above,the list contains a single relation.The composition of two relations requires one more relation as parameter because it is a binary operation,e.g.:$./sparq compute-relation dra-24composition llrr rllr>(lrrr llrr rlrr slsr lllr rllr rlll ells llll lrll)Here the result is a disjunction of10base relations.It is also possible to have disjunctions of base relations as input parameters.For instance,the following call computes the intersection of two disjunctions:$./sparq compute-relation dra-24intersection"(rrrr rrll rllr)""(llll rrll)">(rrll)3.3Constraint ReasoningThe‘constraint-reasoning’module reads a description of a constraint network; this is a qualitative scene description that may include disjunctions and may be inconsistent and/or underspecified.It performs a particular kind of consistency check8.Which type of consistency check is executed depends on thefirst module specific parameter:7In all the examples,input lines start with‘$’.Output of SparQ is marked with‘>’. 8The‘constraint-reasoning’module also provides some basic actions to manipulate constraint networks that are not further explained in this text.One example is the ‘merge’operation that is used in the example in Section5(see the SparQ manual for details[30]).action:The two consistency checks currently provided are‘path-consistency’and‘scenario-consistency’;the parameter determines which kind of consis-tency check is performed.The action‘path-consistency’causes the module to enforce path-consistency on the constraint network using van Beek’s algorithm[26]or to detect an inconsis-tency of the network in the process.In case of a ternary calculus the canonical extension of van Beek’s algorithm described in[31]is used.For instance,we could check if the scene description generated by the‘qualify’module in Section3.1 is path-consistent—which of course it is.To make the test slightly more interest-ing we add the base relation ells to the constraint between A and C;this results in a constraint network that is not path-consistent:$./sparq constraint-reasoning dra-24path-consistency$((A rllr B)(A(ells rllr)C)(B lrrl C))>Modified network.>((B(lrrl)C)(A(rllr)C)(A(rllr)B))The result is a path-consistent constraint network in which ells has been re-moved.The output‘Modified network’indicates that the original network was not path-consistent and had to be changed.Otherwise,the result would have started with‘Unmodified network’.In the next example we remove the relation rllr from the disjunction.This results in a constraint network that cannot be made path-consistent;this implies that it is not consistent.$./sparq constraint-reasoning dra-24path-consistency$((A rllr B)(A ells C)(B lrrl C))>Not consistent.>((B(lrrl)C)(A()C)(A(rllr)B))SparQ correctly determines that the network is inconsistent and returns the constraint network in the state in which the inconsistency showed up(indicated by the empty relation()between A and C).In a last path-consistency example we use the ternary Double Cross Calculus: $./sparq constraint-reasoning dcc path-consistency$((A B(7_36_3)C)(B C(7_36_35_3)D)(A B(3_63_7)D))>Not consistent.>((A B()D)(A B(6_37_3)C)(B C(5_36_37_3)D)(D C(3_7)A)) If‘scenario-consistency’is provided as argument,the‘constraint-reasoning’module checks if a path-consistent scenario exists for the given network.It uses a backtracking algorithm to generate all possible scenarios and checks them for path-consistency as described above.A second module-specific parameter determines what is returned as the result of the search:return:This parameter determines what is to be returned in case of a constraint network for which path-consistent scenarios can be found.‘First’returns the first path-consistent scenario,‘all’returns all path-consistent scenarios,and ‘interactive’returns one solution and allows to ask for the next solution until all solutions have been generated.。

自动控制摘要：综述了自动控制理论的发展情况，指出自动控制理论所经历的三个发展阶段，即经典控制理论、现代控制理论和智能控制理论。

最后指出，各种控制理论的复合能够取长补短，是控制理论的发展方向。

自动控制理论是自动控制科学的核心。

自动控制理论自创立至今已经过了三代的发展：第一代为20世纪初开始形成并于50年代趋于成熟的经典反馈控制理论；第二代为50、60年代在线性代数的数学基础上发展起来的现代控制理论；第三代为60年代中期即已萌芽，在发展过程中综合了人工智能、自动控制、运筹学、信息论等多学科的最新成果并在此基础上形成的智能控制理论。

经典控制理论(本质上是频域方法)和现代控制理论(本质上是时域方法)都是建立在控制对象精确模型上的控制理论，而实际上的工业生产系统中的控制对象和过程大多具有非线性、时变性、变结构、不确定性、多层次、多因素等特点，难以建立精确的数学模型。

因此，自动控制专家和学者希望能从要解决问题领域的知识出发，利用熟练操作者的丰富经验、思维和判断能力，来实现对上述复杂系统的控制，这就是基于知识的不依赖于精确的数学模型的智能控制。

本文将对经典控制理论、现代控制理论和智能控制理论的发展情况及基本内容进行介绍。

1自动控制理论发展概述自动控制是指应用自动化仪器仪表或自动控制装置代替人自动地对仪器设备或工业生产过程进行控制，使之达到预期的状态或性能指标。

对传统的工业生产过程采用自动控制技术，可以有效提高产品的质量和企业的经济效益。

对一些恶劣环境下的控制操作，自动控制显得尤其重要。

自动控制理论是与人类社会发展密切联系的一门学科，是自动控制科学的核心。

自从19世纪Ma xw el l对具有调速器的蒸汽发动机系统进行线性常微分方程描述及稳定性分析以来，经过20世纪初Ny q ui s t，Bo de，H a rr is，E va ns，Wi e nn er，N ic ho l s等人的杰出贡献，终于形成了经典反馈控制理论基础，并于50年代趋于成熟。

定性研究与定量研究的联系与区别一、定性研究与定量研究的区别1、概念不同1定性研究是指研究者运用历史回顾、文献分析、访问、观察、参与经验等方法获得教育研究的资料,并用非量化的手段对其进行分析、获得研究结论的方法;2定量研究的结果通常是由大量的数据来表示的,研究设计是为了是使研究者通过对这些数据的比较和分析作出有效的解释;2、理论基础不同1定性研究主要是一种价值判断,它建立在解释学、现象学和建构主义理论等人文主义的方法论基础上;其主要观点是：社会现象不像自然现象那样受因果关系的支配,社会现象与自然现象有着本质的不同;2定量研究是一种事实判断,它是建立在实证主义的方法论基础上的;实证主义源于经验主义哲学,其主要观点是：社会现象是独立存在的客观现实,不以人的主观意志为转移;在评价过程中,主体与客体是相互孤立的实体,事物内部和事物之间必定存在内在的逻辑因果关系;量的评价就是要找到、确定和验证这些数量关系;3、特性不同4、在研究设计上的不同①研究环境：定性研究主要是在自然地环境下进行；定量研究多在实验室条件下进行;②研究工具和方法：定性研究主要是将研究者本身作为研究工具,运用观察、访谈等方法,或运用录音、录像设备获得描述性的资料；而定量研究则是用量表、调查表等工具进行测量,得到的资料可测量和统计;5,研究分析6,研究方法定量研究主要用观察、实验、调查、统计等方法研究社会现象,对研究的严密性、客观性、价值中立都提出了严格的要求,以求得到客观事实;定量研究通常采用数据的形式,对社会现象进行说明,通过演绎的方法来预见理论,然后通过收集资料和证据来评估或验证在研究之前预想的模型、假设或理论;定量研究是基于一种称为“先在理论”的基础研究,这种理论以研究者的先验想法为开端,这是一个自上而下的过程;定性研究大多是采用参与观察和深度访谈而获得第一手资料,具体的方法主要有参与观察、行动研究、历史研究法、人种志方法;其中参与观察,是定性研究中经常用到的一种方法;参与观察的优势在于,不仅能观察到被观察者采取行动的原因、态度、努力程序、行动决策依据;通过参与,研究者能获得一个特定社会情景中一员的感受,因而能更全面地理解行动;然后通过对观察和访谈法等所获得的资料,采用归纳法,使其逐步由具体向抽象转化,以至形成理论;与定量研究相反,定性研究是基于“有根据的理论”为基础的;这种方式形成的理论,是从收集到的许多不同的证据之间相互联系中产生的,这是一个自下而上的过程;Q1：什么促使工人加入“GIG经济”：对Deliveroo谢菲尔德分公司工作的人进行研究What motivates workers to join the 'gig economy': a study into individuals working for the Sheffield branch of Deliverooa定性方法qualitative approachb归纳推理inductive reasoningc解释主义哲学interpretivist philosophyd 方法：1.通过观察收集主要数据Collecting primary data through observation2.使用半结构化,深入和集体访谈收集主要数据Collecting primary data using semi-structured, in-depth and group interviewse 抽样策略7f 访问相关的答复者/组织Q2：灵活的工作方法是否能改善学术的工作与生活平衡和幸福感Do flexible working practices improve academic's work-life balance and well-beinga定量方法Quantitative approachb演绎推理deductive reasoningc实证主义哲学positivist philosophyd 方法：e 抽样策略7f 访问相关的答复者/组织演绎推理是从一般性的知识的前提推出一个特殊性的知识的结论,即从一般过渡到特殊;一个演绎推理只要前提真实并且推理形式正确,那么,其结论就必然真实;归纳推理则是从一些特殊性的知识的前提推出一个一般性的知识的结论,即从特殊过渡到一般;即使其前提都真也并不能保证结论是必然真实的;。

In Qualitative Reasoning in Decision Technologies, Proc. QUARDET ’93, N. Piera Carreté & M.G. Singh, eds., CIMNE Barcelona 1993, pp. 483-492. DIMENSIONS OF QUALITATIVE SPATIAL REASONINGChristian Freksa and Ralf RöhrigFachbereich InformatikUniversität HamburgBodenstedtstraße 162000 Hamburg 50, Germany{freksa, roehrig}@informatik.uni-hamburg.deAbstractQualitative knowledge can be viewed as that aspect of knowledge whichcritically influences decisions. Reasoning with qualitative knowledge hasbeen studied extensively for the temporal domain. It turns out that the spatialdomain is considerably richer than the temporal domain. The richness of thespatial domain is illustrated by showing the design choices for qualitativereasoning systems. After a general discussion of these dimensions of spatialknowledge nine research projects are presented for a comparison of theiradaptation of qualitative methods to the domain of space. A classificationwith respect to the dimensions of spatial knowledge is presented anddiscussed.1. QUALITATIVE REASONING IN ARTIFICIAL INTELLIGENCEQualitative reasoning is becoming increasingly popular in Artificial Intelligence (AI) and its areas of application. Various factors contribute to this development, including the following insights: 1) High-precision quantitative measurements are not as universally useful for the analysis of complex systems as was believed in the beginning of the computer age, when great advances in the natural sciences and in engineering were made as a result of the availability of high-precision measurement and computation equipment; 2) Much experience and confidence have been gained in AI regarding the representation and processing of non-numerical knowledge; 3) Although storage capacity is much less an issue today than it used to be, it has been recognized that decision making on the basis of large amounts of quantitative knowledge can be computationally expensive (see, for example, connectionist approaches); as a consequence, a reduction of data without loss of information remains an important goal;4) It has become apparent that higher cognitive mechanisms employ qualitative rather than quantitative mechanisms even if the knowledge originally is available in quantitative form through perception.Qualitative knowledge can be viewed as that aspect of knowledge which critically influences decisions. Which is the critical aspect of the available knowledge may depend much on the particular situation, of course. Thus, it is not surprising that different aspects are considered in different knowledge and/or application areas. On the other hand, there may be universal principles structuring a domain and its features. It is the purpose of this paper to look at dimensions and features which are universal to the domain of physical space.Qualitative reasoning has been studied extensively for the temporal domain. The representational primitives used are (time) points [McDermott 1982] or temporal intervals [Allen 1983]. Although Allen's approach has various deficiencies [Freksa 1992], it has become a paradigm for qualitative reasoning; several researchers have adapted this paradigm to the domain of spatial knowledge. It turns out that the spatial domain is considerably richer than the temporal domain; for this reason there is a variety of ways in which the adaptation from the temporal domain to the spatial domain can be done. In the present paper we analyze a selection of the resulting approaches and compare them with one another. We illustrate the richness of the spatial domain by showing the design choices for qualitative reasoning systems.2. DIMENSIONS OF SPATIAL KNOWLEDGEWe have selected nine research projects on qualitative spatial reasoning for this comparative study. Each of them approaches spatial reasoning from at least one of four areas of concern: the approaches of Cohn, Güsgen, and Schlieder1 are based upon formal concepts (logic-based, geometrical, topological, resp.); the approaches of Freksa, Hernández, and Mukerjee & Joe are largely motivated by cognitive considerations; the work of Egenhofer and Frank is driven by issues in geographical reasoning; and the work of Jungert has roots in data-base oriented research concerned with encoding pictorial information. Despite these differences of concern, the approaches converge remarkably with respect to some basic issues.Qualitative spatial representation systems can be compared with regards to the reference system used (Cartesian, polar), the scope of their reference system (local, global), the alignment of the reference system (internal, external), their representational primitives (point objects, spatially extended objects), the represented aspects (topology, arrangement, orientation, distance), the aspects represented qualitatively, the dimensionality of the represented space, their granularity (fine, coarse, flexible), the modularity of the aspects represented, their ability to represent incomplete and imprecise knowledge, the flexibility of integrating various kinds of spatial knowledge, their ability of incremental knowledge enrichment, among others. We will briefly introduce some of these notions in a general manner before we discuss how they are reflected in the nine approaches analyzed.In quantitative representations of space, the reference system is specified by 'rulers' which measure spatial objects and their locations. In a three-dimensional Cartesian reference system, for example, three rulers are arranged orthogonally; objects and locations are specified by a measurement on each of these rulers. Similarly, in a planar polar coordinate system, objects and locations are specified by a distance and angle measurement. In qualitative representations, we do not require scales on the rulers since they do not employ metrics; however, we still need a specification of the dimensions.Which scope does the reference system have? Is there one global reference system to which all descriptions refer or are there many local reference systems that are used in smaller vicinities? In quantitative representations, both approaches are used, dependent on possible advantages of having reference to local entities: comparisons across measurements may be carried out more easily in a global reference system, but the measurements themselves may be easier in local reference systems. Similarly, in qualitative representations, comparisons are carried out among entities; this can be done more easily if they are related to the same reference system; on the other hand, the1 Selected references to publications on the projects under study are given at the end of the article.entities themselves are described in terms of comparisons; these comparisons can be carried out directly, if the reference system is linked to the entities to be compared.What determines the alignment of the reference system? In quantitative representations, the scales are defined outside the problem space; the reference system containing the scales can be external to the problem space or it can be aligned to internal objects or structures of the problem space. In qualitative representations, features are typically compared within the problem space; but the feature dimensions may be aligned either to internal (e.g. egocentric or allocentric) or to external (e.g. geocentric) entities.Should we use points or spatially extended objects as representational primitives? Point locations are as non-spatial as time points are non-temporal since spatiality and temporality are due to spatial and temporal extension, respectively. This suggests that only extended entities should be used in these domains. On the other hand, abstraction from these fundamental aspects has proven useful for describing space and time in physics and geometry. The issue is related to the question how much abstraction is useful and how much abstraction misses the important properties of the respective domains. Practically speaking, the use of spatially extended objects limits the generality of spatial inferences, since there is a multitude of qualitatively different shapes; these result in a multitude of different spatial situations. The use of point objects, on the other hand, may miss crucial aspects of spatiality (for example: shape).Which are the important aspects of space which we have to consider? Do the interactions of spatial objects (as describable through topological relations) suffice or do we need more specific knowledge about relative arrangement, orientations, or distances? Topological relations completely abstract from aspects of shape and orientation; arrangement information adds some rudimentary aspects of orientation; full orientation knowledge constrains topology rather severely; and complete distance information hardly abstracts at all and leaves little or no freedom for a physical instantiation.These considerations raise a question - which is strongly linked to the external internal issue - should all aspects be represented qualitatively or can we profit from interactions with a quantitative approach?An issue which so far has been given little treatment in the AI literature is the question how the choice of approaches is affected by the dimensionalities of the problem domain and of its surrounding space. The more abstract approaches to representation appear to be less affected by the dimensionality than the more concrete approaches. The approaches considered in this paper are restricted to two or three spatial dimensions, respectively.Representational modularity concerns the question whether the treatment of different aspects of space is integrated within one approach or whether they are treated highly independently of one another.Granularity refers to the resolution of spatial features or decision criteria and to the transition between different levels of resolution: what can we infer from coarse spatial knowledge under consideration on a fine level of resolution and vice versa?Incomplete and imprecise knowledge has to be dealt with in all real-world situations. The notion 'incomplete' may refer to two distinguishable situations: it may mean that there is a 'hole' in the acquired knowledge (missing facts) or it may mean that the available knowledge does not have sufficient precision, i.e. each question about a situation can be answered but not necessarily with sufficient detail.Flexibility addresses the question how easily a given representation scheme can deal with spatial knowledge of different granularity, completeness, precision, etc.The ability of incremental knowledge enrichment, finally, refers to the ability of a representation and inference system to integrate new facts and procedures incrementally without requiring recomputation of already derived knowledge.In the following section we will look at specific approaches to qualitative spatial knowledge representation.3. QUALITATIVE REASONING IN THE DOMAIN OF SPACEQualitative reasoning is based on comparative knowledge rather than on metric information. The simplest comparison that can be performed in the spatial domain is the comparison of points in space with respect to their equality. Simple comparison of points in space can be extended in several ways: first, adopting the concept of orientation, space obtains a structure which can be used to further classify unequal locations of points; second, instead of points in space one might be interested in spatially extended objects. Many relations are conceivable for qualitative comparison of spatially extended objects.The following analysis of approaches to qualitative spatial representation will reflect the distinction between the comparison of spatially extended objects and the exploration of orientation. When examining systems for the representation of orientation, a major question is how the spatial axes described by the formalism are aligned to the domain. Reasons for a specific placement of the axes may be independent of the properties of the objects under consideration. We will call these kinds of decision factors external. On the other hand, internal properties of the domain may guide the alignment of the reference system.comparison of pointsspatially extendedobjects orientationspatially extendedobjects &orientation integratedEgenhofer Cohn, Cui, Randell Hernández (T)external internal external FrankHernández (O)Schlieder Freksa GüsgenJungertFigure 1:Classification of approaches to qualitative spatial reasoning.We classify the nine research projects under consideration into three coarse and five finer categories, depending on their use of spatially extended objects and/ororientation information and on the reference to external or internal entities, respectively. This classification is depicted in Figure l. Some of the approaches selected for this analysis of spatial reasoning cover both concepts, that of spatially extended objects and that of orientation. The approaches falling into the same class with regard to the distinctions described above will be further analyzed and differentiated with respect to other, more specific, features.3.1 From points to spatially extended objectsFor spatially extended objects in the domain of space we can qualitatively distinguish the interior, the boundary, and the exterior of the object, without bothering about the concrete shape or size of the object. Comparison of extended objects can then be reduced to the comparison of the parts of the objects. A set theoretical analysis of the possible relations between objects based on the above partition is provided by the work of Egenhofer and Franzosa. For the comparison of objects they examine the intersection of their parts. Most fundamental in this setting is the distinction of the values empty and non-empty for the intersection. Since there are three parts (including its exterior) for each object that are compared with three parts of another object, there are 29 = 512 set theoretically distinguishable relations. Egenhofer showed that only eight of them have a meaningful interpretation in physical space. These eight relations are labeled disjoint, meet, equal, inside, covered by, contains, covers, and overlap.Some variants of this theory were developed by Cohn and his coworkers. Cohn abandons the distinction of the interior and the boundary of an object. He defines the same eight topological relations that where provided by Egenhofer from the single binary relation 'is connected to'. Furthermore Cohn extends the theory to handle concave objects by distinguishing the regions inside and outside of the convex hull of objects. In this way many more relations can be defined, for example, an object may be inside, partially inside, or outside another object's convex hull.An application of the topological relations to two-dimensional layout plans for offices was done by Hemàndez. Describing qualitative positions of object in 2D, he distinguishes topological relations and orientation relations (cf. Figure 1, Hernández (T) and Hernández (O)). Since he is dealing with projections of objects, he can use the eight topological relations applicable to convex objects. He shows some important properties of these relations, for example, that there is a neighborhood structure among them, and how this structure influences the reasoning process. Another observation is that there are pairs of converse relations (covers / covered by and inside / contains), whereas the other relations are symmetric.3.2 From points to orientationsAn orientation can be viewed as a labeled axis, an orientation system as a system of labeled axes. Besides the questions, how many axes are to be used, whether the Cartesian or a polar system is preferred, or whether to define the axes globally or locally, it has to be stated how the axes are aligned to the domain, i.e., where the axes are to be located with respect to the objects under consideration.Externally aligned orientationsThere are different reasons for aligning an orientation system, which are independent of the properties of the objects in the domain, i.e. are external. For example, in large scale navigation often the system of cardinal points is used to describe orientation. This system is neither aligned with a moving object nor with a landmark in the scene. The north-south direction is always aligned with the North and South Poleand the east-west direction is always orthogonal to the north-south axis. Two examples of systems of cardinal directions are given by Frank. Instead of axes, he uses either cones or half-planes to define cardinal directions. Regardless of the shape of the regions and the number of directions used, either the four directions north, east, west, south, or at a finer level of granularity north, north-east, east, south-east, south, south-west, west, and north-west, the center of the northern region will always point to the North Pole and is not committed to any object of the domain.Another possible external reference for aligning an orientation system is the surrounding object or space. This kind of referencing is often used in small scale space or in in-door space descriptions. Specific properties of the room containing the scene are used to align a system of orientations. These properties can, for example, be the door through which a room was entered, or a black board at one side of the room. In his application of theoretical results in the domain of lay-out plans for offices Hernández uses the door of the office as a reference for his back orientation. Having fixed one orientation, he can define the other orientations with respect to the first one. For example, the orientation front is always opposite to the orientation back. Depending on the level of granularity, other orientations are defined at certain angles to the former ones. Since Hernández offers a representation that allows to explicitly state a reference frame for any orientation relation between two objects, he also provides a method for transforming the orientation information from one reference frame to another. Reasoning processes are always based on one global reference frame, the one aligned with the surrounding room.Internally aligned orientationsAlignment of the orientation system to the domain with regard to properties of the object in the domain, i.e. with regard to internal reasons, can be based on mainly two different considerations: first, there might be a deictic view, i.e., the relative orientation of two objects is given with respect to the position of another object; second, some non-spatial properties of the objects may be used to define a reference orientation for the alignment of the orientation system. Since this section is dedicated to the comparison of points, and points do not have non-spatial properties that could be used to define a reference orientation, the discussion of this kind of internal alignment is given in the next section, where the concept of orientation is analyzed in the light of spatially extended objects.To apply the deictic method to alignment of the orientation system means to take a third object or location into account. In natural language processing, this object is called a second reference object. For example, in the context of route descriptions, the actual or the imagined location of the speaker is taken as the second reference object to interpretate phrases like 'there is a church on the left'. In general, this way of aligning the orientation system results in orientation relations over three objects, the reference object of the relation, the entity to be related to the reference object, an the second reference object. The simplest way to qualitatively describe the arrangement of a set of points in two-dimensional space is to use the orientation of triangles, clockwise or counterclockwise. The orientation of triangles can be viewed as a relation over the three vertices of the triangle. Schlieder called the orientation of triangles global knowledge in his approach. Local knowledge is collected through perception processes and is therefore bound to a single point, in which perception takes place. Schlieder showed, that simply looking around and determining the order of visible landmarks in every point of the scene is not sufficient to reconstruct the global arrangement information. His idea was to augment the perceived landmarks by recording the opposite of each landmark as well. The resulting structure is called a panorama graph and consists of a cyclic list of the landmarks as well as their opposites, appearing in the order they occur when looking around in one point of the scene. Schlieder showed, that arrangement knowledge may be reconstructed from these panorama graphs. Determining the order oflandmarks in a point of perception can again be viewed as a set of orientation relations over three points, each relating two neighboring points with the point of perception.An approach that explicitly works with relations over three points is provided by Freksa. Relative orientation is described by relations between a point and a vector. Qualitatively different relations are left, right and on the line. These relations correspond to the orientation of triangles, clockwise and counter-clockwise, in Schlieder's approach. For a further differentiation of the left and right side of the vector, Freksa uses a biologically motivated concept of perception. People are not only able to distinguish their left hand side from their right hand side, but are definitely able to distinguish a front region from what is behind them. Freksa represents this front/back dichotomy by a bound orthogonal to the bound between the left and the right region. Placing this bound in each of the two end points of the vector being the reference for orientation relations, one obtains a structure (double cross) that separates the two dimensional plane into 15 disjoint regions.As shown by Latecki and Röhrig [1993], using the concept of oriented triangles for the description of arrangement of points in a two dimensional plane is not sufficient to get all interesting inferences, when only partial knowledge is available. Knowing that three points A, B, and C form a clockwise oriented triangle, and that points B, C, and a fourth point D form a clockwise oriented triangle, too, it is not possible to infer anything about the orientation of the points A, B, and D. But, augmenting the knowledge with the concept of qualitative angles, i.e., allowing a distinction of acute and obtuse angles, it is possible to define a composition of any two orientation relations that results in a new orientation relation. Latecki and Röhrig mention that the concept of qualitative angles is very similar to the front/back dichotomy introduced by Freksa. This concept leads to a finer subdivision of the plane again and has some nice algebraic properties that can improve the reasoning process.3.3 Combining extended objects with orientationAs mentioned above, Allen's approach to qualitative temporal reasoning has become a paradigm for several methods to qualitatively represent and reason about space. The primitives used by Allen are time intervals, i.e., temporally extended objects. Since intervals are convex by definition, the same eight topological relations are applicable to distinguish qualitatively different situations, as used by Cohn, Egenhofer and Hernández. Due to the inherent orientation of time five of the topological relations fall into two further distinguishable relations: disjoint becomes before and after; meets gets extended by met by; started by is separated into started by and finishes; and overlap is extended by overlapped by. Thus, the combination of (temporally) extended objects with the orientation of time results in 13 disjoint relations, which exhaustively describe the qualitatively distinguishable connections between two temporal intervals.There are two major problems in adapting this paradigm to the domain of spatial knowledge. First, space is of higher dimensionally than time. Therefore, all approaches that transfer the temporal structure to space use one dimensional projections of spatially extended, but connected objects. Second, space lacks an inherent orientation. This problem is the general problem of using orientation systems: the problem of alignment of a system of axes to the domain.Externally aligned orientationsA straightforward application of this qualitative reasoning paradigm to two-dimensional space was described by Güsgen. He uses a Cartesian system of three X-, Y- and Z- axes. Objects are projected to theses axes, and compared by means of eight qualitative relations (distinct from Cohn / Hernández / Egenhofer's) along each of theaxes separately. So, relative position of two objects is given by a tuple of qualitative relations.The same method of transferring temporal relations to the two dimensional spatial domain was used by Jungert. He uses the geo system with the cardinal directions north/south and east/west to align the orientation system in which the objects are to be compared. While in Güsgen's approach only such rectangular objects are compared, that are aligned to the system of X-, Y, and Z-axes, in the formalism of Jungert it is possible to split objects of arbitrary shape and to represent the relative position of the parts to other objects or object parts. The parts of a single object have a defined neighborhood relationship which is maintained by different methods than the 13 qualitative relations per axis.Internally aligned orientationWhen looking at internal reasons for alignment of an orientation system to the domain, beside the deictic method described in the section above, it is possible to make use of non-spatial properties of the objects. Several properties induce a front side of an object. For example, for moving objects it is easy to determine the front. The same holds for objects that have a visual apparatus, like a camera or an animal. Other objects get their fronts from functional considerations, like desk or a wardrobe.In the approach of Mukerjee and Joe, these non-spatial properties are used to predefine a special direction, called the front. This direction is used as a reference for the definition of the orthogonal directions left, back, and right. Relative orientation is given by the comparison of the reference frames of two objects. The front direction is also used to define a line of travel. This line serves as the axis to which all objects are projected. These projections can then be compared with the object at hand by means of the 13 qualitative relations provided by Allen. In order to describe relative position between two objects, the comparison of projections is done on the line of travel for each object separately. A spatial relation is then constructed from a relative orientation and a relative position.4. CONCLUSIONSWe have studied nine research projects on qualitative spatial reasoning which originated from rather different areas of concern. Nevertheless, these approaches converge remarkably with respect to some basic issues. This suggests that qualitative spatial reasoning has matured to a stage where we may develop a general theory of representing spatial knowledge which integrates a wide range of views. The development of such a theory first of all requires a clarification and unification of the applicable terminology.This includes a clarification of the question which kind of domains and dimensions are essential for describing spatial knowledge. Furthermore, a connection to the linguistic literature on spatial concepts should be drawn.For example, in the field of linguistic approaches to automated text understanding, there is a distinction of external and internal reference systems for the interpretation of spatial prepositions and within the internal ones there is a further distinction of deictic and intrinsic reference frames [Retz-Schmidt 88].。

Rationality is a cornerstone of quality,shaping the essence of our endeavors and the outcomes we achieve.It is through the lens of reason that we can discern the path to excellence,ensuring that our actions are guided by a clear understanding of our goals and the means to attain them.In the realm of education,rationality plays a pivotal role in fostering a learning environment that is conducive to intellectual growth.Teachers who approach their profession with a rational mindset are better equipped to identify the unique learning needs of their students,tailoring their teaching methods to suit these requirements.This not only enhances the learning experience but also ensures that students are able to reach their full potential.In the workplace,rationality is equally important.Employers who make decisions based on sound reasoning are more likely to create a productive and harmonious work environment.By setting clear expectations and providing employees with the necessary resources and support,these leaders can inspire their teams to perform at their best, leading to higher quality work and greater overall success.Innovation,too,is heavily influenced by rationality.When individuals approach problemsolving with a logical and methodical mindset,they are better positioned to develop creative and effective solutions.This is particularly true in the field of science and technology,where rational thinking is essential for the advancement of knowledge and the development of new technologies that improve our lives.Moreover,rationality is a key component of effective decisionmaking.Whether it is in our personal lives or in the broader context of society,making decisions based on reason rather than emotion can lead to more balanced and wellconsidered outcomes.This is especially important in areas such as politics and economics,where the stakes are high and the consequences of poor decisions can be farreaching.However,it is important to note that rationality alone is not enough.While it is a crucial element in the pursuit of quality,it must be complemented by other qualities such as empathy,creativity,and resilience.A truly rational approach to life involves the ability to balance logic with emotion,to consider multiple perspectives,and to adapt to changing circumstances.In conclusion,rationality is a vital force that shapes the quality of our actions and the outcomes we achieve.By embracing a rational mindset,we can make better decisions, foster a more conducive learning and working environment,and drive innovation andprogress.Yet,we must also remember to balance this with other essential human qualities to ensure a wellrounded and holistic approach to life.。

个人素质英文作文素材模板英文：Personal qualities are essential for success in both personal and professional life. One of the most important qualities is self-discipline. It means being able to control one's actions and emotions, and to stick to a plan or a goal. Without self-discipline, it is difficult to achieve anything meaningful.Another important quality is resilience. Life is full of challenges and setbacks, and it is important to be able to bounce back from them. Resilient people are able to learn from their mistakes, adapt to new situations, and keep moving forward.In addition, good communication skills are crucial in today's world. Being able to express oneself clearly and listen actively is important in both personal and professional relationships. It helps to avoidmisunderstandings and build trust.Finally, a positive attitude is essential for success. People with a positive outlook are more likely to be happy, motivated, and successful. They see challenges as opportunities and are able to find solutions to problems.中文：个人素质对于个人和职业生涯的成功至关重要。

Relation Variables inQualitative Spatial ReasoningSebastian BrandNational Research Institute for Mathematics and Computer Science(CWI) P.O.Box94079,1090GB,Amsterdam,The Netherlands Qualitative spatial representation and reasoning(QSR)[1]lends itself well to modelling by constraints.In the standard modelling approach,a spatial object, such as a region,is described by a variable,and the qualitative relation between spatial objects,such as the topological relation between two regions,contributes a constraint.We study here an alternative constraint-based formulation of QSR. In this approach,a spatial object is a constant,and the relation between spatial objects is a variable.We call this the relation-variable approach,in contrast to the conventional relation-constraint approach.Although modelling qualitative relations with variables is not original–see[2] for an application to qualitative temporal reasoning–it has practically been ignored in thefield of QSR so far.This fact surprises in view of the advantages of this approach.In particular,the following important issues are tackled.Aspect integration:Space has several aspects that can be characterised qualitatively, such as topology,size,shape,absolute and relative orientation.These aspects are interdependent,but no convenient canonical representation exists that provides a link.This is in contrast to temporal reasoning,in which the concepts can be defined in terms of time points.Context embedding:In practice,spatial reasoning problems are not likely to arise in pure form but embedded into a context.Systems:Knowledge in the relation-constraint approach is not stated declaratively but in algorithmic or at best in meta-constraint form.However, typical current constraint solving systems focus on domain reduction,and rarely provide facilities to easily access and modify the constraint network.The relation-variable approach to modelling QSR responds to these points.It results in a plain,single-level constraint satisfaction problem.Aspect integration is facilitated by stating inter-aspect constraints,and embedding means simply stating additional context constraints.The resulting problem can be solved by any constraint solver that supports extensionally defined constraints.We study diverse instances of QSR problems,such as aspect integration and evolution of spatial scenarios.The modelling task and the implementation is greatly simplified by using relation variables.References1. A.G.Cohn and S.M.Hazarika.Qualitative spatial representation and reasoning:An overview.Fundamenta Informaticae,46(1-2):1–29,2001.2. E.P.K.Tsang.The consistent labeling problem in temporal reasoning.InK.S.H.Forbus,editor,Proc.of6th National Conference on Artificial Intelligence (AAAI’87),pages251–255.AAAI Press,1987.。

如何做有质感的人英语作文To be a person of substance is to possess qualities that make one respected and valued by others. It involves a blend of character, integrity, and a genuine concern for the world around you. Here's how you can cultivate a life of substance:1. Develop a Strong Moral Compass: A person of substance hasa clear understanding of right and wrong. They stand firm in their principles and are not swayed by popular opinion or the lure of easy gains.2. Cultivate Integrity: Honesty and consistency in behavior are key. Always strive to do what you say you will do, and be someone others can rely on.3. Practice Empathy: Understanding and sharing the feelings of others builds deep connections and shows that you are not self-centered.4. Seek Knowledge: Continuously learning and being curious about the world around you makes you a well-rounded individual. It also opens your mind to new perspectives.5. Be Resilient: Life is full of challenges. A person of substance faces these with courage and learns from them, rather than shying away.6. Show Kindness: Small acts of kindness can have asignificant impact. Being kind to others, regardless of their status, shows a depth of character.7. Be Humble: Recognize that everyone has something to offer. Acknowledging your own limitations and learning from others is a sign of a mature and substantial person.8. Take Responsibility: Own your actions and their consequences. This shows maturity and integrity.9. Pursue Your Passions: Engage in activities that you love and are passionate about. This not only brings joy to your life but also makes you a more interesting person.10. Contribute to Society: Find ways to give back to your community. It could be through volunteering, mentoring, or simply being there for someone in need.11. Maintain a Healthy Lifestyle: Taking care of your physical health is also a sign of a person who values themselves and their well-being.12. Practice Gratitude: Appreciate what you have and the people in your life. Gratitude can transform your outlook on life and make you a more positive influence on others.13. Communicate Effectively: Being able to express your thoughts clearly and listen to others is a sign of an intelligent and thoughtful person.14. Be Patient: Good things take time. Patience is a virtuethat shows you are not easily frustrated and can handlelife's pace.15. Lead by Example: Actions speak louder than words. Lead by setting a positive example for others to follow.In conclusion, being a person of substance is not about wealth or status but about the quality of your character and your interactions with the world. It's a lifelong journey of self-improvement and contribution to the betterment of society.。

理性对待外界塑造英语作文English Answer:As we navigate the complexities of the 21st century, the ability to critically evaluate the information presented to us becomes paramount. The deluge of stimuli bombarding us daily, from social media to news outlets, demands a discerning eye to separate fact from fiction and shape our understanding of the world.Cultivating a rational approach to external influences requires a multifaceted strategy. Firstly, it entails an understanding of cognitive biases, the mental shortcutsthat can lead us astray in our judgments. These biases, such as confirmation bias or the tendency to seek information that confirms our existing beliefs, can cloud our objectivity.To mitigate these biases, we must actively seek out and consider opposing viewpoints. This involves engaging withdiverse sources, exploring alternative perspectives, and challenging our own assumptions. The ability to detach ourselves from our preconceptions and entertain the possibility of being wrong is essential for rational thinking.Beyond cognitive biases, critical thinking also requires a sound grasp of logic and evidence. We must be able to identify valid arguments, evaluate the credibility of sources, and distinguish between correlation and causation. By subjecting information to rigorous scrutiny, we can avoid falling prey to logical fallacies and make well-informed decisions.Furthermore, developing a foundation in digital literacy is crucial in navigating the vast expanse of online information. This includes understanding how search engines work, being able to assess the reliability of websites, and recognizing the potential for misinformation and propaganda. By empowering ourselves with these tools, we can make more informed choices about the information we consume.Rational thinking is not merely an academic pursuit; it is a vital skill for navigating the challenges of modern life. By embracing a critical approach to external influences, we empower ourselves to make sound judgments, avoid manipulation, and shape our world with informed decisions.中文回答：要理性地对待外界的塑造，需要一种多方面的策略。