Vision and Robotics
Perception O f N o n -R i g i d M o t i o n :
Inference of Shape, M a t e r i a l and Force *
A l e x P e n t l a n d a n d J o h n W i l l i a m s Vision Sciences Group, E15-410
The M edia Lab, M .I.T.
20 Ames St., Cambridge M A 02138
A b s t r a c t
Most non-rigid motion is much simpler than is generally thought, having many fewer de-grees of freedom t h a n , for instance, 3-D shape. T h e relatively circumscribed nature of non-rigid motion can be seen by examining it f r o m the perspective of vibration modes. The fact t h a t a small number of parameters are suffi-cient to describe non-rigid motion mean that it is plausible to use sensory data to recover a nearly complete physical model of an ob-ject, so t h a t we can, for instance, predict its response to impinging forces. One perceptual task of considerable interest is estimating ma-terial properties such as stiffness, strength, and mass by watching, touching or listening to col-lisions. We derive equations which allow es-timates of these material properties to be ex-tracted f r o m visual and tactile data, and spec-ulate on the use of aural data.
1 I n t r o d u c t i o n
Non-rigid m o t i o n seems to be very complex. W h e n an object is struck so t h a t it moves in a non-rigid, elastic manner, each point on the surface goes off in a different direction. It seems, therefore, t h a t a full description of non-rigid m o t i o n must have even more degrees of free-d o m than a full description of shape. Despite this ap-parent complexity, however, people are often able to ac-curately predict the time course of objects experiencing non-rigid behavior, and are even able to infer material properties f r o m observing such m o t i o n.
For instance, people can watch a tree l i m b swaying in the w i n d and make a good estimate of its stiffness, strength and mass. M
ore commonly, when someone wants to determine the properties of an object they poke at it to see and feel it deform, and tap it to hear it res-onate. From these visual, tactile, and auditory cues we are somehow able to ascertain material properties.
In this paper we w i l l examine the finite element method of simulating the dynamics of collisions, and show t h a t it can be decomposed into simple, closed-form differential equations describing the object's vibration modes. We w i l l then show t h a t for most objects under *This research was made possible by National
Science Foundation Grant No. IRI-87-19920 and by ARO Grant No. DAAL03-87-K-0005
most conditions a relatively small number of modes are required to accurately describe how the object deforms as a function of time. Finally, we will show that for simple collisions we can estimate the object's material properties by observing these vibration modes using vi-sual, tactile or even auditory data.
2 B a c k g r o u n d : T h e F i n i t e
Element M e t h o d
T h e finite element method (F E M ) is a technique for sim-ulating the dynamic behavior of an object. In the F E M the continuous variation of displacements throughout an object is replaced by a finite number of displacements at so-called nodal points. Displacements between nodal points are interpolated using a smooth function. En-ergy equations (or functionals) can then be derived in terms of the nodal unknowns and the resulting set of simultaneous equations can be iterated to solve for dis-placements as a function of impinging forces. In the dynamical case these equations may be w r i t t e n :
Mu + D u + Ku = f (1)
where u is a 3n x 1 vector of the (x, y, z) displacements of the n nodal points relative to the objects' center of mass, M , D and K are 3n by 3n matrices describing the mass, damping, and material stiffness between each point w i t h i n the body, and f is a 3n x 1 vector describ-ing the (x ,y ,z ) components of the forces acting on the nodes. T h i s equation can be interpreted as assigning a certain mass to each nodal point and a certain mate-rial stiffness between nodal points, w i t h damping being accounted for by dashpots attached between the nodal points. The damping m a t r i x D is normally taken to be equal to s\M + s 2K for some scalars s 1, s 2. When S 1≠ 0 S 2 ≠ 0 this is called Raleigh damping, for s 2 = 0 it is called mass damping, and for s 1 = 0 stiffness damp-ing.
To calculate the result of applying some force f to the object one discretizes the equations in time, picking an appropriately small time step, solves this equation for the new u, and iterates u n t i l the system stabilizes. Direct (implicit) solution of the dynamic equations re-quires inversion the K m a t r i x , and is thus computation-ally expensive. Consequently explicit Euler methods (which are less stable, but require no m a t r i x inversion) are quite often applied.
Even the explicit Euler methods are quite expensive, because the matrices M , D, and K are quite large: for
Pentland and Williams 1565
1566 Vision and Robotics
Figure 1: (a) A cylinder, (b) a linear deformation mode in response to compression, (c) a linear deformation mode in response to acceleration, (d) a quadratic mode
in response to a bending force, (e) superposition of both
linear and quadratic modes in response to compression, (f) superposition of both linear and quadratic modes in response to acceleration.
To obtain an accurate simulation of the dynamics of an object one simply uses linear superposition of these modes to determine how the object responds to a given force. Because Equation 4 can be solved in closed form, we have the result that for objects composed of linearly-deforming materials the non-rigid behavior of the objec t in response to an impulse forc e c an be solved in c losed form for any time t. The solution is discussed in Section 4. In environments w i t h more complex forces, however, analytic solution becomes cumbersome and so numerical solution is preferred. Either explicit or implicit solution techniques may be used to calculate how each mode varies w i t h time.
Non-linear materials may be modeled by summing the modes at the end of each time step to f o r m the material stress state which can then be used to drive nonlinear plastic or viscous material behavior.
4 Number Of Modes Required
T h e modal representation decouples the degrees of free-dom w i t h i n the non-rigid dynamical system of Equation 1, but it does not reduced the t o t a l number of degrees of freedom. However once decoupled, we can separately analyze the various modes in order to determine which ones are required in order to obtain an accurate descrip-tion of an object's non-rigid dynamic behavior.
T h e most i m p o r t a n t observation is t h a t modes asso-ciated w i t h high resonance frequencies normally have little effect on object shape. This is because:
? The displacement amplitude for each mode is in-versely proportional to the square of the mode's resonance frequency. T h u s higher frequencies t y p i -cally have small amplitudes.
1. 2.
Figure 2: A ball coll ? D a m p i n g is proportional to the mode's resonance
frequency. T h u s higher frequency vibrations dissi-pate quickly. ? Frequencies are excited in proportion to the fre-quency content of the input force. T h e force gen-erated by simple collisions typically have a roughly Gaussian t i m e course, so that an individual reso-nance frequency / receives energy proportional to
e -J 1° T h u s low frequencies typically receive more
energy than high frequencies.
The combination of these effects is that high-frequency modes have very little amplitude, and even less effect, in simple collisions. As a consequence much more efficient (and still accurate) simulation of an ob-ject's dynamics can be accomplished by discarding the small, high-frequency modes, and considering only the large-amplitude, low-frequency modes [5,6]. Exactly which modes to discard can determined by examining their associated eigenvalue, which determines the reso-nance frequency.
Experimentally, we have found t h a t most common-place m u l t i -b o d y interactions can be adequately mod-eled by use of only rigid-body, linear, and quadratic strain modes. Figure 2, for instance, shows a example of a simulated non-rigid dynamic interaction: a ball col-liding w i t h a two-by-four. As can be seen, the interac-tion and resulting deformations look realistic despite the
use of only linear and quadratic modes.1
Figure 1 also illustrates how use of linear and quadratic modes can accurately simulate non-rigid m o t i o n. Note, however, higher-order modes are required to accurately model the objects whose dimensions differ more than an order of magnitude.
1
Perhaps the most impressive fact about this example, however, is the speed of computation: Using a SymboUcs 3600 (with a speed of roughly one MIP), it requires only one CPU second to compute each second of simulated time!
3. 4.
iding with a two-by-four
4.0.1 U s e o f F i x e d M o d e s
Normally, in either the finite element or modal meth-ods, the mass, damping, and stiffness matrices are not recomputed at each time step. The use of fixed M , D, and K (or, equivalently, fixed modes) is well-justified as long as the material displacements are small. The defi-nition of "s m a l l /' however, is quite different for different modes. Because the eigenvalue decomposition in Equa-tion 2 performs a sort of principal-components analysis, it is the gross object shape (e.g., its low-order moments of inertia) determine the low-frequency modes, which as a consequence are quite stable. High-frequency modes are much less stable because they are determined by the fine features of the object's shape.
In the standard finite element formulation the action of each mode is distributed across the entire set of equa-tions, so that one must recompute the mass and stiff-ness matrices as often as required by the very highest-frequency vibration modes. W h e n these high-frequency modes are discarded the mass, damping, and stiffness matrices need to be recomputed much less frequently. In most situations it is sufficient to use single, fixed set of low-frequency modes throughout an entire simulation.
5 Estimation of Material
Properties
Let us imagine that we have seen the image sequence shown in Figure 2, and have been able to compute a full 3-D description of the object's shape at each instant. How can we estimate the material properties of these objects? The first step is to compute for each object a description that decomposes the object motion into its low-order modes.
This can be accomplished by forming the vector p that describes each point on the object's surface, and then computing the matrices M, D, and K matrices using unit values for density and spring constant. Be-cause these matrices are determined by the vector p up to an overall constant, the eigenvectors found by solving
Pentland and Williams 1567
Equation 2 w i l l be identical regardless of the material properties (excepting, of course, non-linearly-behaving materials); only the eigenvalues depend upon the mate-rial properties. T h u s given the object's shape, we can directly determine Φ, the object's deformation modes.
In this straightforward approach the matrices M, D, and K can become quite large, so that solution to Equa-tion 2 becomes difficult. A more efficient method of de-termining Φ is be to fit either an eight or twenty point polygonal model to the sensed data (perhaps by use of the techniques described in reference [2]), and use the values of those points to construct a much smaller vector p. Given eight points we can form M, D, and K ma-trices that are 24 x 24 in size, and then solve Equation 2 to obtain the object's linear vibration modes. Given twenty points the matrices are 60 x 60, and produce both linear and quadratic vibration modes.
A still more efficient scheme can be obtained by not-ing that the axes of the object can allow us to directly disentangle the action of the various modes, so that by estimating axis shape and length we can avoid solving Equation 2. This approach is described in more detail below.
Given Φ and a description p(t) of the object's shape over time, we can directly decompose the object shape into a vector p(to) describing the object's shape at time / = t0a n d the amplitudes u(t) =Φl(p(t) —p(t0)) of each of the individual modes over time. The generic time behavior of each mode u i,(t) in response to an i m-pinging force is given by Equation 4. T h e solution to this equation is which is graphed in Figure 3(b).
Because the time behavior of u, is a function of M i,-, D i and K i, in simple situations we can recover the phys-ical parameters of the object's material by measuring u i over time. This is particularly straightforward when the mode is underdamped, as in Figure 3, so that several cy-cles of deformation occur, because in this case we need only measure the frequency and amplitude of the de-formation peaks. W h e n the mode is critically damped or overdamped only one peak occurs; however it is still possible to measure the material properties from peaks in the first derivative of the modal amplitude.
For example, in the sequence of Figure 2 we can ob-serve the bending of the two-by-four in response to the impact of the ball, as illustrated by Figure 4.
I
f we plot the amplitude of this deformation mode in response to
1568 Vision and Robotics
5.1 E s t i m a t i o n of Mass
By tracking geometry over time we can estimate the material properties up to an overall scale constant that depends upon the amount of mass involved in the par-ticular vibration mode. The obvious question, then, is how much information is required to estimate the ma-terial density? To answer this question we surveyed the CRC Handbook, which lists the density of several hun-dred materials. We found that the listed densities could be clustered into four categories: metals, stones, bio-logical materials, and woody (cellulose) materials. The range of densities for metals was roughly 7.0 to 10.0, for stone materials roughly 2.3 - 2.8, for biological ma-terials (gums, resins, soap, etc.) roughly 0.9 - 1.2, and for woody materials (e.g., common woods, plant stems, etc.) roughly 0.4 - 0.6.
Thus if the viewed material can be classified into one of these four categories, then it appears that the den-sity can be estimated w i t h an accuracy of roughly ±10 percent. Consequently it appears that the force, mass, damping, and spring constants can also be estimated w i t h similar accuracy.
5.2 Static L o a d i n g
When a static load is applied to an object, a fixed de-formation occurs. By examining Equation 4 we see that the amount of static deformation u i, is a function only of the loading force f i, and the stiffness constant K i as-sociated w i t h the particular mode. Thus if we know the modes (either from analysis of the static shape or by the methods described in the next section) and the imping-
ing force then we can determine the material stiffness
K i which is perhaps the most important of the basic material properties.
I
n many situations, particularly when using a tactile sensor, this method of estimating material properties is probably the most practical.
5.3 Speculation: E s t i m a t i o n f r o m
O t h e r M o d a l i t i e s
The same ideas can be applied to the tactile and audi-
tory senses: the modal vibration can be sensed either
by touch or by sound (via coupling between the air and
the object surface). The notion of using a tactile sensor
to produce a static measure of material stiffness has al-ready been mentioned above. However a much stronger result can be achieved by using either tactile or audi-
tory data given that we can apply a force f i so as to excite single mode i.
I
n this case, because we know
the force, we can measure the modal mass M, directly (from Equation 8), and thus obtain D, and K i, without knowledge of object geometry, modes, or density.
For instance, if we "poke" or "tap" an object - exert
a sharp blow normal to the surface - we can transfer most of the energy into a single, localized compression mode. To the extent that we are able to isolate a single mode, we need no knowledge of object geometry, modes,
or density in order to estimate the physical parameters.
In experiments where the sound spectrum produced by tapping has been measured it appears that most of the energy is indeed transferred into a single mode if the object's geometry is uniform in the area of the tap —
e.g., the object is not hollow, and the tap occurs far from any discontinuity.
6 Direct Observation of Modes
We have described a procedure of fitting data points, computing M, D, K. and then solving for Φ in order to obtain the object's vibration modes. Although mathe-matically sound, this procedure seems too complex and expensive to be useful in some applications. Similarly,
the procedure is complex to be an account of human ca-pabilities. Thus it is desirable to develop a theory that
is simpler even if less accurate.
6.1 E s t i m a t i o n v i a s y m m e t r y axes
The first approach to direct observation of the modes depends on the observation that the object's axes of symmetry have a special status in modal analysis: they
are the singular lines (and planes) of the various vibra-
tion modes, i.e., the places along which various vibra-
tion modes cause no deformation. Thus along the axes
of symmetry the actions of the different vibration modes become partially decoupled.
Thus one direct way to estimate material properties
is track the shape of symmetry axes over time. Time variation in the length of an axis is a function primarily
of linear compression modes, while the time variation
in axis curvature is primarily a function of quadratic bending modes. Either the axis length or curvature can
Pentland and Williams 1569
be tracked over time to produce a graph such as shown in Figure 3, and the material properties calculated by use of Equations 8. T h e simplicity of this method is its greatest virtue, however, in complex collisions the presence of many active vibration modes may destroy the accuracy of the approach.
6.2 D i r e c t e s t i m a t i o n of m o d a l
a m p l i t u d e s
A second approach is to fit the available shape data w i t h a simple volumetric model which can be parametrically deformed in any of the expected deformation modes. F i t t i n g the parameters of such a model to the sensor data provides a direct, simultaneous estimate of all of the modal amplitudes. Several variations on this ap-proach to extracting object geometry have been suc-cessfully demonstrated on range data [7,8,9,10]. As w i t h symmetry axes, the values of such a model's deforma-tion parameters can be tracked over time and material properties estimated by use of Equations 8. The advan-tage of this somewhat more computationally expensive approach is that is more likely to produce good esti-mates of modal amplitudes in relatively complex situa-tions.
6.3 E s t i m a t i o n f r o m static i m a g e r y
In recent years both Pentland [11] and Ley ton [12] have suggested that an object's static shape can be analyzed to produce an abstract c
ausal account of the object's history. T h a t is, t h a t a object's shape can be de-composed into a simple prototypical shape (a cube, a sphere) that has been modified by a sequence of forces or forming operations to achieve its present state. The advantage of this type of description is that produces a prototype-based representation t h a t can simplify object recognition [9] and which fits human psychological data
[13].
It can be seen, in retrospect, that both of these theo-ries were a t t e m p t i n g to capture the notion that objects have a limited repertoire of modal deformations. T h a t is, if one starts w i t h a fixed prototypical shape (a cylin-der, sphere, or cube for instance) an applies a series of forces to elastically deform that object, then in general the simplest possible description of the resulting shape is exactly the original shape plus the modal amplitudes that were produced by the impinging forces. Further, this description of object shape has considerable pre-dictive power, for it contains most of the information needed to estimate material properties, determine what forces were applied, and to predict the object's future dynamic behavior.
7 S u m m a r y
Non-rigid behavior is normally simpler than it appears from cursory examination of the F E M equations that describe such behavior. By breaking such motion into vibration modes, we can show that most of the degrees of freedom have very little energy or amplitude. Thus quite accurate descriptions of non-rigid behavior can be
obtained by knowing the amplitude and phase of rela-tively few vibration modes.
Using standard machine vision techniques the param-eters of these modes can be estimated f r o m sensory data. By tracking modal amplitudes across time (or, perhaps, even from analysis of static imagery!) we can then mea-sure material properties, predict future behavior, and perform other ecologically i m p o r t a n t tasks.
R E F E R E N C E S
[1]
[2]
[3]
[5]
[6]
[7] [8]
[9]
[10]
[11]
[12]
[13]
Williams, J ., Musto, G., and Hawking, G., (1987) The Theoretical Basis of the Discrete Element M e t h o d , Numeri c
al Methods in Engineering, The-ory, and Appli c
ation, R o t t e r d a m : Balkema Tub-ers
Terzopoulos, D., P i a t t , J ., Barr, A., and Fleis-cher, K., (1987) Elastically deformable models, Proceedings of S 1G G R A P I I '87, Computer Graph-ics, Vol. 21, No. 3, pp 205-214.
Williams, J. and Musto, G. (1987) Modal Methods for the Analysis of Discrete Systems, Computers and Geotec hnic s, Vol. 4, pp 1-19.
Pentland, A., and W i l l i a m s , J. (1988) V i r t u a l Con-struction, Construc tion, Vol. 3, No. 3, pp. 12-22 Pentland, A. and W i l l i a m s , J., (1989) Good Vibra-tions: Modal Analysis for Graphics and Anima-tion, Proceedings of S I G G R A P H '89, Computer Graphics, Vol. 23, No. 3.
Pentland, A., and W i l l i a m s , J . (1989) Fast Sim-ulation on Small Computers: Modal Dynamics Applied to Volumetric Models IEEE 20th Annual Conference on Simulation, May 4-5, Pittsburgh, PA.
Pentland, A., (1988) Part segmentation for object recognition, Neural Computation, Vol. 1, No. 1 Pentland, A., (1988) A u t o m a t i c extraction of de-formable part models, M.I.T. Media Lab Vision Sciences Tec hnic al Note 104, J uly 1, 1988.
Bajcsy, R. and Solina, F., (1987) Three-dimensional Object Representation Revisited, First International Conf. on Computer Vision, '87, J une 8-11, London, England.
Bolt, T., and Gross, A., (1987) Recovery of Su-perquadrics from Depth Information, Pro c
eedings of the AAA1 Workshop on Spatial Reasoning and Multi-Sensor Fusion, Oct. 1987, pp. 128-137
Pentland, A. (1986) Perceptual Organization and the Representation of Natural Form, Artific ial In-telligence Journal, Vol. 28, No. 2, pp. 1-38.
Ley ton, M. (1988) A Process-Grammar for Shape, Artificial Intelligen c
e Journal, No. 34, pp. 213-247.
Rosch, E. (1973) On the internal structure of per-ceptual and semantic categories. In Cognitive Development and the A c
quisition of Language. Moore, T.E. (Ed.) New York: Academic Press.
1570 Vision and Robotics
期刊影响因子的“含金量”是多少 这是一个以标准衡量的世界。既然吃饭都有米其林餐厅评级作为参考，更何况严谨的学术科研成果。 期刊影响因子长久以来被学术界视为一个重要的科研水平参考指标。在一本影响因子高的期刊发表论文，科研人员的科研能力和成果也更容易获得认同。然而，部分科学家已对这一指标能否真正反映单篇论文乃至作者学术水平提出质疑，加上每年发布这一指标的汤森路透公司在本月早些时候宣布把相关业务转售给两家投资公司，影响因子未来能否继续维持其「影响力」令人存疑。 广泛影响 根据汤森路透发布的信息，该公司已同意将旗下知识产权与科学业务作价３５．５亿美元出售给私募股权公司Ｏｎｅｘ和霸菱亚洲投资。这一业务包括了世界知名的科技文献检索系统「科学引文索引」（简称ＳＣＩ）以及定期发布的《期刊引证报告》，其中的期刊影响因子是一本学术期刊影响力的重要参考。 新华社记者就此事咨询了汤森路透，该公司一位发言人说，这一交易预计今年晚些时候完成，在此之前该公司还会继续拥有并运营这项业务，「我们将在不影响这项业务开展和质量的前提下完成交易」。 帝国理工学院教授史蒂芬·柯里接受记者采访时说，他对汤森路透用来计算期刊影响因子所使用的数据是否可靠本来就有一定顾虑，「我不确定汤森路透的这次交易是否产生影响，但这项业务的接盘方如果未来能够保证这方面的透明度也是一件好事」。 影响因子的计算方法通常是以某一刊物在前两年发表的论文在当年被引用的总次数，除以该刊物前两年发表论文的总数，得出该刊物当年的影响因子数值。理论上，一种刊物的影响因子越高，影响力越大，所发表论文传播范围也更广。鉴于全球每个科研领域中都有大量专业期刊，如果有一个可靠的指标能告诉研究人员哪个期刊影响力更大，他们就能更高效地选择在一个高质量平台上发表科研成果。 但这又引申出一个现象，即许多科研机构、高校甚至学术同行越来越依赖影响因子来评判一篇论文甚至作者本身的科研水平，进而影响他们的职称评定和获取科研项目资助等机会。 业内争议 这种过度依赖影响因子的做法引起不少业内争议。来自帝国理工学院、皇家学会等科研机构学者以及《自然》《科学》等期刊出版方的高级编辑，合作撰写了一份报告分析其中弊端，并提出相关改进方案。这篇报告已在近期被分享到一个公开的预印本服务器上供同行审阅。 报告分析了包括《自然》《科学》在内１１份学术期刊在２０１３年至２０１４年间所刊发论文被引用次数的分布情况，这些数据也您身边的论文好秘书：您的原始资料与构思,我按您的意思整理成优秀论文论著,并安排出版发表，企鹅1550116010自信我会是您人生路上不可或缺的论文好秘书被用来计算２０１５年相关刊物的影响因子。 报告作者发现，多数论文被引用次数都达不到发表它们的期刊的影响因子数值水平，比如《自然》在这期间所刊发论文中的７４．８% 在２０１５年获得的引用次数就低于这本期刊当年影响因子所显示的水平，《科学》的情况也类似。报告说，这主要是因为这些期刊中有一小部分论文被引用次数非常高，导致影响因子在均值计算过程中出现偏差。 报告详细描述了如何更准确地计算出期刊所刊发论文被引用次数的分布状况，并呼吁各家期刊将这些基础数据公布出来，减少学术界对影响因子的过度依赖。
毕业设计（论文）开题报告 题目电动汽车充电对配电系统的影响学院自动化学院 专业电气工程与自动化专业 姓名 班级 学号 指导教师
一、综述本课题选题的依据和意义 2015年9月，关于充电桩的好消息频频传出，如国务院常务会议上提出加快电动汽车充电基础设施、电动汽车充电接口国家标准修订稿通过审查，以及国务院办公厅日前发布《关于加快电动汽车充电基础设施建设的指导意见》，到2020年，我国将基本建成适度超前、车桩相随、智能高效的充电基础设施体系，满足超过500万辆电动汽车的充电需求。尤为引人关注的是，北京通信展举行期间，国务院副总理马凯称：国家准备将充电桩普及的任务交由铁塔公司负责。 随着时代的发展，汽车的普及，石油的消耗也日益增加，作为不可再生的石油资源，总有枯竭的一天，而且汽车尾气的排放对环境有很大的污染，所以利用电能替代石油，实现汽车尾气的零排放，将是未来汽车行业的发展趋势。截至2015年一月，从公开信息显示，目前杭州已经建成了70座充换电站、620个充电桩，其中杭州主城区投入运营的充换电站有27个。在杭州市区里，一辆新能源车要找到最近的充电站，只要开4.5公里。 国内外电动汽车在近几年的发展情况如下：经过2012和2013年的缓慢起步，全球电动汽车销量终于在2014年下半年爆发，全年销售已超过30万辆大关，中国新能源汽车品牌突飞猛进，比亚迪从2013年的第40名跃升至第七位，康迪电动车也挤进第十名。在2015年，全球电动汽车销售量达到40万辆左右。 随着电动汽车规模化应用,电网原有装机和线路容量是否能应对新增充电负荷需求,即在不扩大规模的情况下,如何提高原有电网利用率,增加容纳能力,同时最大限度降低充电负荷对电网的负面影响,在分析充电负荷特性基础上,针对电动汽车充电对电网各方面的影响,提出相应对策,将对电动汽车产业化进程具有重要的研究意义。 二、国内外研究动态 我国电动汽车起步较发达国家晚,但研究发展快。各汽车生产商进入研发电动汽车的行列,已经在促进电动汽车各方面技术发展方面取得有益的成见。由于配套设施等主要原因,家用电动汽车并没有广泛的推广开来，现有的电动汽车充电站主要对电动公交车和工程车辆进行充电。同时针对电动汽车充电站运行和电动汽车充电对配电网的研究仍然非常缺乏。电动汽车规模预测，用户充电行为的随机性,以及接入电网造成的影响和相应充电控制策略都没有一套成熟的模式和系统，以及对此的全面研究。 电动汽车对电网的影响，主要包括电网负荷特性影响、谐波影响、电压电流
2006年国内医学类核心期刊及影响因子列表 序号期刊名称被引频次影响因子预防医学、卫生学类 1、中国地方病学杂志1172 1.237 2、中华结核和呼吸杂志2829 1.228 3、中华流行病学杂志18750.904 4、中华传染病杂志9530.903 5、中华预防医学杂志9680.891 6、中国消毒学杂志4380.738 7、中国艾滋病性病5690.680 8、营养学报7730.632 9、中华实验和临床病毒学杂志5310.543 10、环境与健康杂志5620.490 11、卫生研究7510.465 12、中华劳动卫生职业病杂志6810.456 13、中国防痨杂志4730.414 14、中国卫生统计2930.393 15、中国食品卫生杂志2640.391 16、中国职业医学3860.341 17、中国学校卫生8520.312 18、中华卫生杀虫药械950.310 19、中国寄生虫病防治杂志4210.297 20、中国公共卫生16620.296 20、环境与职业医学2510.296 22、中国慢性病预防与控制4210.291 23、工业卫生与职业病3330.280 24、华南预防医学2300.236 25、疾病控制杂志2490.222 26、中国工业医学杂志3170.217 27、中国地方病防治杂志3510.210 28、解放军预防医学杂志2870.190 29、热带医学杂志1070.178 30、实用预防医学4420.158 31、现代预防医学4110.142 32、预防医学情报杂志2350.131 33、职业与健康3370.048 基础、医学综合类 1、中华医院管理杂志2015 1.556 2、中华病理学杂志1425 1.171 3、中华医学杂志3792 1.091 4、中国危重病急救医学16340.998 5、实用诊断与治疗杂志6900.997 6、中华麻醉学杂志14870.918 7、生理学报6970.851
F0/23B(C)、H3/36B、C7030电气系列 F0/23B(C)、H3/36B、C7030Electrical series 使 用 说 明 书 成都久和传动机械有限责任公司 地址:成都市双流县彭镇燃灯社区5组 电话(Phone):（028）67028807 传真(FAX):（028）85847360 邮编(ZIP code):610203
一．使用环境 1．周围空气温度 周围空气温度不超过+40℃,周围空气温度的下限为-25℃。且在24h周期内平均温度不超过+30℃。 2．海拔高度 安装地点的海拔不超过2000m。 3．大气条件 空气清洁，而其相对湿度在最高温度为+40℃，不超过50%，在较低温度时，亦允许有较大的相对湿度，如最湿月平均温度为+20℃，月平均最大相对湿度不超过90%，并注意因温度变化产生在产品表面的凝露。 4．供电电网质量 供电电网容量应保证满足塔机功耗，进线电压波动范围须保证不超过额定电压值的±10%。起升电控柜(L柜)适用于交流50Hz/380V、60Hz/440V三相电源。 5．安装条件 垂直安装倾斜度不超过5°；安装牢固，在主机工作过程中不会发生相对于主机的平移和垂直跳动；安装部位最高震动条件为：5～13Hz时,位移为1.5mm；13～15Hz时，震动加速度为1.0g。 二．阅读电气原理图的方法 1. 符号表示 各个部分字母表示见下列表格: a)操作,检测,指示
b) Ⅰ部分 c)Ⅱ或Ⅲ部分
d）方向或速度 2 . 工作顺序、工作原理及符号 不同的工作阶段用下面两种不同的形式表示： 在开关转换顺序中 A）在工作顺序示意图中，采用下面符号： 接触器或继电器进入“工作状态”：PV 接触器或继电器进入“停止状态”：PV PV表示两种工作状态。 B）在开关转换顺序中，采用下面符号： 接触器或继电器进入“工作状态”并通过同一机械或电气连锁保持：● 接触器或继电器进入“停止状态”：○ 3. 动作特性和各机构功能 F0/23B(C)、H3/36B、C7030等塔式起重机电气控制柜可工作在交流50Hz/380V、60Hz/440V的额定电压条件下。电气控制柜分A、L、HF柜，分别有供电，吊钩升降，小车变幅、回转几大系统。供电系统（A柜）供电源给塔机各机构的用电、并起电路的短路、过载保护作用。吊钩升降（L柜）控制塔机的吊钩起升、下降；小车变幅系统（HF柜）控制塔机的小车变幅（前后）；回转系统（HF柜）控制塔机的回转。
提高学术期刊影响因子的途径 作者：李勤来源：《今传媒》 美国科技信息研究所所长尤金?加菲尔德首先用论文的被引证频次来测度期刊的影响力，1963年美国科技信息研究所正式提出和使用影响因子这一术语。期刊在某年的影响因子是指该刊前两年发表论文在统计当年被引用的总次数除以该刊前两年发表论文的总数。由影响因子的定义可知，期刊的影响因子反映在一定时期内期刊论文的平均被引率。影响因子的三个基本要素是论文量、时间和被引次数，也就是说，期刊所刊发论文的被引情况决定了该期刊的影响因子。总的说来，一篇论文的被引次数越多，说明它的学术影响力越大，同样也表明它的学术质量较高、创新性较强。因为影响因子高的期刊具有较广泛的读者群和比较高的引用率。影响因子的高低客观地反映了期刊和编辑吸引高质量稿件的能力。所以，我们在评价期刊时，影响因子为重要的评价指标之一。许多作者在投稿时，也将影响因子高的期刊作为投稿首选。图书馆或研究院、资料室在选择订阅期刊或优化馆藏期刊时，也把期刊的影响因子作为重要的参考标准之一。而且影响因子也是筛选中文核心期刊的一项重要指标。因此，作为期刊工作者，努力提高期刊的影响因子十分必要。分析学术期刊的计量指标情况，决定影响因子高低的因素通常有这样几点： 一、影响因子的影响因素 一是论文发表时滞。论文发表时滞(DPA)是指期刊论文的出版日期与编辑部收到该文章的日期之时间差，以月为单位。它是衡量期刊时效性的重要指标，与期刊的影响因子和被引频次有密切关系。因为在计算影响因子时，期刊被引频次中两年的时间限制可导致不同刊物中论文的被引证次数有较大的差异。出版周期短的刊物更容易获得较高的影响因子。因而在同一学科领域的研究论文，特别是研究热点领域内的论文，首先被公开发表的论文更有可能引起较大的影响或者被别人引证。 二是论文学术水平。论文的学术质量直接制约着期刊影响因子的提高。学术质量较高的论文，容易被同行认可，引用率自然就高，影响因子也高。相反，学术质量较差的论文，不会被同行认可，得不到同行研究者的重视，引用率自然就低，影响因子也较低。在各类文章中，具有原创性的学术论文常常被研究人员参考和引用。同时有争议的学术讨论更容易获得同行的广泛关注，而普通的介绍性论文则不太被人们关注。 三是参考文献的数量和质量。由于影响因子是根据期刊的引文计算出来的，通常参考文献的内容越新颖，信息质量越高，影响因子就越高。准确的参考文献有助于作者在有限的篇幅中阐述论文的研究背景及其相关的观点和论据。同时可以方便读者追溯有关的参考资料进一步研究问题。统计分析表明，期刊的影响因子主要取决于论文的平均引文数、引证半衰期及论文的被引证率。所以，参考文献数量较多的论文它的平均引文数量就比较大，而且参考文献越准确，读者查阅参考文献就更方便，读者能分享文献信息资源就越多。 根据我们的分析研究，提高学术期刊影响因子，应该在以下几个方面用功夫： ⒈鼓励高质量论文在我国首先发表
11.6 疑难解答 危险： 严格遵守11.1章中“危险”一节的要求。 警告： 在（废料）切割器或者料盘分隔板附近工作时不论何时都必须戴厚度适度的保护手套。不论（废料）切割器及料盘分隔板刀片处于固定还是可动状态，甚至贴片机已经断电，都存在高风险的受伤可能性。 严禁从下方进入气压切割装置或者从上方进入空的皮带供料器，甚至是为了解决问题（如供料器卡住时）。 11.6.1 更换气压切割刀片 警告： 佩戴厚度适度的保护手套。 取出刀片时，只能捏住它的外面，左边和右边。 严禁将刀片放置身体上，例如，放到膝盖或者腿上。 不要将脚放到刀片上。你可能会重伤自己或者至少将衣服划破。 拆除刀片后确保没人会因踩到刀片伤到他们自己。 11.6.1.1 移除刀片 运行贴片机，开启压缩空气系统。 中断贴片机菜单中可动器件，然后将它取出。 停止运行贴片机，切断总电源，然后关闭压缩空气。开启位于压缩空气单元的针状阀以使压缩空气流动（查看11.1章中“危险”一节）。 松弛螺丝更换喷嘴，略微将它举起并保持它在这一位置。 拔下电缆和喷嘴气动软管 慢慢的拔出喷嘴。 拧下空供料器各个配件的螺丝（参考图11.4.1 -> 11, 9），然后将这些管道移出机器。 警告： 刀片的刀刃处始终可能伤到你自己。 基于这一原因，挡板、顶盖及保护罩（参见图11.4.3 -> 6,7, 2）必须安装到位。 打开连接电缆顶盖（见图11.6.6 -> 5） 拧下位于连接线缆（见图11.6.6 -> 5）处的气压连接阀（Y型插座：见图11.6.3 -> 9） 拔下电源和控制面板插头插座。（见图：see Fig. 11.6.5 -> 11, 10） 仔细解开外部控制面板箱内（见图11.6.5 -> 15）对应的接线头（向左或者向右）。在此期间不要损坏连线。 将顶盖放回控制面板及连接线缆处。 取出供料器斜槽（它只是扣住而已）。这使得取下刀片变得容易。 警告： 刀片下方必须保持干净。（例如，不要把脚放到下面） 在贴装元器件情况下松弛位于贴片机左右两个侧面的缓冲部件（2头M8六角头两边螺钉，见图 11.4.1 -> 15）。
中国学术期刊影响因子年报、国际引证报告发布 王保纯 2012年12月28日07:59 来源：光明日报 中国学术期刊电子杂志社、中国科学文献计量评价研究中心与清华大学图书馆26日共同发布了《中国学术期刊影响因子年报（2012版）》和《中国学术期刊国际引证报告（2012版）》，同时还首次发布了2012年度中国最具国际影响力学术期刊和中国国际影响力优秀期刊，科技界和社科界418个学术期刊分别入选两个名单。 此前，我国对于学术期刊国际影响力的评价，多以SCI（科学引文索引）、SSCI（社会科学引文索引）等国际权威检索机构收录与否作为唯一衡量标准，很多未被收录期刊往往不被看好。《中国学术期刊国际引证报告》的发布是我国学术期刊乃至学术评价领域的一个突破性进展，是我们国家，也是国际上第一次从文献计量的角度，全面、系统、深入地向社会揭示中国学术期刊走向世界取得的成果和存在的问题。此举标志着我国学术期刊有了统一的国际影响力认证标识。 中国科学文献计量评价中心主任杜文涛介绍了此次研究的有关情况。他说，中国最具国际影响力学术期刊和中国国际影响力优秀期刊，是依据《中国学术期刊国际引证报告（2012版）》，按2011年度中国学术期刊被SCI期刊、SSCI期刊引用的总被引频次和影响因子排序，经综合计算，并经40多位期刊界专家审议，最终遴选出的TOP5%期刊和TOP5%-10%期刊。在中国最具国际影响力学术期刊中，科技期刊备选3533种，由上述方法选出175种；人文社科类备选680种，选出34种，共计209种。同样，在中国国际影响力优秀期刊中，由上述方法选出科技类期刊和人文社科类期刊也分别为175种和34种，共计209种。参与报告研制的研究人员惊喜地发现，不少非SCI、SSCI收录期刊比SCI、SSCI收录期刊具有更高的被引用次数。在上榜的418个期刊中，中文期刊达312个。
电信学院毕业设计（论文）任务书 题目分布式发电并网系统潮流计算与分析 学生姓名张吉俊班级电气11级4班学号11230429 题目类型科学研究指导教师张晓英系主任 一、毕业设计（论文）的技术背景和设计依据： 分布式发电（DG-Distributed Generation）指的是直接接入配电网或用户侧的发电系统，功率等级一般在几十KW到几十MW之间，经济、高效、可靠地发电。根据使用的技术进行分类，DG主要可分为以下几类：（1）以天然气为常用燃料的燃气轮机、内燃机和微燃机等为基本核心的发电系统；（2）燃料电池发电系统；（3）太阳能光伏电池发电系统；（4）风力发电系统；（5）生物质能发电系统。分布式发电接入电网后，必然会改变电网的潮流分布，从而对节点电压，网络损耗产生重大的影响，其电压、潮流分布不仅取决于负荷，而且取决于分布式发电,而潮流计算是对其影响进行量化的主要手段。因此，研究分布式发电并网系统潮流计算与分析具有重要的实际意义。 1.原始资料 图1 20节点配电网络图 沿馈线将每一集中负荷视为一个节点并加以编号，从地区性变电站母线开始依次编为1，2，…，N（N=20），每一段线路的阻抗、各节点负荷大小如表1所示，配电网中节点1为平衡节点，电压取为1.02，基准值为10KV，功率基准值为100MV A。 节点电阻电抗有功无功 1 0.000 2 0.0005 0.0497 0.0261 2 0.0082 0.0246 0.0034 0.0065 3 0.0006 0.0017 0.0487 0.0002 4 0.0009 0.0027 0.0461 0.0163 5 0.0070 0.0209 0.0479 0.0180 6 0.0015 0.0044 0.0282 0.0497 7 0.0006 0.0017 0.0475 0.0217 8 0.0072 0.0219 0.0159 0.0217 9 0.0072 0.0217 0.0133 0.0468
四种中文核心期刊评价体系资料介 绍 对中国内地出版的期刊中核心期刊的认定，目前国内比较权威的有以下几种版本： 第一种是中国科技信息研究所（简称中信所）每年出一次的《中国科技期刊引证报告》（限理工科期刊，以下简称《引证报告》）。中信所每年第四季度面向全国大专院校和科研院所发布上一年的科研论文排名。排名包括SCI、Ei、ISTP 分别收录的论文量和中国期刊发表论文量等项指标。《引证报告》以1300多种中、外文科技类期刊作为统计源，报告的内容是对这些期刊进行多项指标的统计与分析，其中最重要的是按类进行“影响因子”排名。 第二种是北京大学图书馆与北京高校图书馆期刊工作研究会联合编辑出版的《中文核心期刊要目总览》（以下简称《要目总览》）。《要目总览》不定期出版，1996年出版了第一版，2000年出了第二版。《要目总览》收编包括社会科学和自然科学等各种学科类别的中文期刊。其中对核心期刊的认定通过五项指标综合评估。 《引证报告》统计源期刊的选取原则和《要目总览》核心期刊的认定各依据了不同的方法体系，所以二者界定的核心期刊（指科技类）不完全一致。 在《引证报告》和《要目总览》中每次都被评为核心期刊的期刊在其刊名前面加注了“#”，共597种。被《要目总览》1996年版，2000年版都定为核心期刊的社科类期刊，加注“=”，共434种。此外，被1999年EI和SCI收录的期刊，分别注以“+”(71种)或“ &”(28种)。 第三种是中国科学引文数据库(http://159.226.100.178/html/lyqkb.htm，限于理工科期刊)。它是由中国科学院文献情报中心建立的, 分为核心库和扩展库。核心库的来源期刊经过严格的评选,是各学科领域中具有权威性和代表性的核心期刊。我校在科研成果认定中把中国科学引文数据库核心库中的刊物均认定为核心期刊。 第四种是《中国人文社会科学核心期刊要览》。它是由中国社会科学院文献信息中心和社科文献计量评价中心共同建立的核心期刊库，我校在科研成果认定中均认定为核心期刊。 国内核心期刊，我院以最新版（目前以2004版）《中文核心期刊要目总览》为基础，在此基础上将核心期刊分为A、B、C、D四类。 国际国内重要检索系统简介
Sequence Analysis Software for Macintosh and Windows GETTING STARTED Introductory Tour of the LASERGENE System MAY 2001
DNASTAR, Inc. 1228 South Park Street Madison, Wisconsin 53715 (608) 258-7420 Copyright . 2001 by DNASTAR, Inc. All rights reserved. Reproduction, adaptation, or translation without prior written permission is prohibited,except as allowed under the copyright laws or with the permission of DNASTAR, Inc. Sixth Edition, May 2001 Printed in Madison, Wisconsin, USA Trademark Information DNASTAR, Lasergene, Lasergene99, SeqEasy, SeqMan, SeqMan II, EditSeq, MegAlign, GeneMan, Protean,MapDraw, PrimerSelect, GeneQuest, GeneFont , and the Method Curtain are trademarks or registered trademarks of DNASTAR, Inc. Macintosh is a trademark of Apple Computers, Inc. Windows is a trademark of Microsoft Corp. ABI Prism are registered trademarks of Pharmacopeia, Inc. Disclaimer & Liability DNASTAR, Inc. makes no warranties, expressed or implied, including without limitation the implied warranties of merchantability and fitness for a particular purpose, regarding the software. DNASTAR does not warrant, guaranty, or make any representation regarding the use or the results of the use of the software in terms of correctness, accuracy, reliability, currentness, or otherwise. The entire risk as to the results and performance of the software is assumed by you. The exclusion of implied warranties is not permitted by some states. The above exclusion may not apply to you. In no event will DNASTAR, Inc. and their directors, officers, employees, or agents (collectively DNASTAR) be liable to you for any consequential, incidental or indirect damages (including damages for loss of business profits, business interruption, loss of business information and the like) arising out of the use of, or the inability to use the software even if DNASTAR Inc. has been advised of the possibility of such damages. Because some states do not allow the exclusion or limitation of liability for consequential or incidental damages, the above limitations may not apply to you. DNASTAR, Inc. reserves the right to revise this publication and to make changes to it from time to time without obligation of DNASTAR, Inc. to notify any person or organization of such revision or changes. The screen and other illustrations in this publication are meant to be representative of those that appear on your monitor or printer.
经济学 排名期刊名称主办单位刊号2010年2011年2012年2013年（五年）四年平均值1经济研究中国社会科学院经济研究所CN11-1081/F9.838.60911.55514.45311.112 2会计研究中国会计学会CN11-1078/F8.983 5.9097.0849.0357.753 3经济学（季刊）北京大学中国经济研究中心CN 11-6010/F—— 4.703 4.267 5.386 4.785 4金融研究中国金融学会CN11-1268/F 5.003 3.423 4.669 5.902 4.749 5中国工业经济中国社会科学院工业经济研究所CN11-3536/F 4.797 4.073 3.814 5.644 4.582 6世界经济中国社会科学院世界经济与政治研究所CN11-1138/F 4.535 3.557 3.965 5.742 4.450 7数量经济技术经济研究数量经济与技术经济研究所CN11-1087/F 3.307 3.988 4.318 4.961 4.144 8国际金融研究中国国际金融学会CN11-1132/F 5.326 3.170 3.389 3.066 3.738 9审计研究中国审计学会CN11-1024/F 3.573 2.560 3.878 4.486 3.624 10中国农村经济中国社会科学院农村发展研究所CN11-1262/F 3.341 3.018 3.417 3.782 3.390 11中国农村观察中国社会科学院农村发展研究所CN11-3586/F 2.673 2.193 2.750 4.628 3.061 12财经研究上海财经大学CN31-1012/F 3.135 2.258 2.589 3.223 2.801 13农业经济问题中国农业经济学会CN11-1323/F 2.854 2.478 2.425 3.200 2.739 14中国土地科学中国土地学会、中国土地勘测规划院CN11-2640/F 2.402 2.675 2.518 2.999 2.649 15国际经济评论中国社会科学院世界经济与政治研究所CN11-3799/F 3.753 2.385 2.285 2.143 2.642 16世界经济研究上海社会科学院世界经济研究所CN31-1048/F 3.308 2.473 2.188 2.395 2.591 17国际贸易问题对外经济贸易大学CN11-1692/F 2.905 2.477 2.242 2.690 2.579 18经济科学北京大学CN11-1564/F 3.083 1.968 2.185 3.065 2.575 19南开经济研究南开大学经济学院CN12-1028/F 2.508 1.323 2.424 3.025 2.320 20农业技术经济中国农业技术经济研究会CN11-1883/S 2.221 1.798 1.901 2.549 2.117 21世界经济文汇复旦大学CN31-1139/F 2.143 1.453 2.245 2.596 2.109 22财贸经济中国社会科学院财经战略研究院CN11-1166/F 2.059 1.533 2.240 2.560 2.098 23经济学家西南财经大学CN51-1312/F 2.08 1.593 2.347 2.303 2.081 24经济理论与经济管理中国人民大学CN11-1517/F 2.272 1.718 2.075 2.172 2.059 25证券市场导报深圳证劵交易所综合研究所CN44-1343/F 2.641 1.602 1.687 2.142 2.018 26产业经济研究南京财经大学CN32-1683/F 1.783 1.763 2.153 2.283 1.996 27经济评论武汉大学CN42-1348/F 1.944 1.673 2.013 2.113 1.936 28国际贸易中国商务出版社CN11-1600/F 2.774 2.023 1.542 1.363 1.926 29财经科学西南财经大学CN51-1104/F 2.179 1.584 1.673 1.768 1.801 30当代经济科学西安交通大学CN61-1400/F 1.944 1.447 1.675 2.093 1.790 31现代日本经济吉林大学、全国日本经济学会CN22-1065/F 1.8 1.863 1.829 1.414 1.727 32财经问题研究东北财经大学CN21-1096/F 1.965 1.317 1.567 1.933 1.696 33财经理论与实践湖南大学CN43-1057/F 2.032 1.530 1.460 1.743 1.691 34城市发展研究中国城市科学研究会CN11-3504/TU 1.448 1.569 1.822 1.896 1.684 35审计与经济研究南京审计学院CN32-1317/F 1.42 1.413 1.859 2.002 1.674 36当代财经江西财经大学CN36-1030/F 1.774 1.468 1.685 1.747 1.669 37南方经济广东经济学会、广东省社会科学院CN44-1068/F 1.773 1.181 1.589 2.094 1.659 38上海财经大学学报上海财经大学CN31-1817/C 1.88 1.380 1.658 1.687 1.651 39宏观经济研究国家发展和改革委员会宏观经济研究院CN11-3952/F 1.915 1.535 1.625 1.460 1.634 40商业经济与管理浙江工商大学CN33-1336/F 1.738 1.235 1.458 1.803 1.559 41山西财经大学学报山西财经大学CN14-1221/F 1.594 1.277 1.602 1.724 1.549 42经济与管理研究首都经济贸易大学CN11-1384/F 1.769 1.287 1.382 1.617 1.514 43上海经济研究上海社会科学院经济研究所CN31-1163/F 1.357 1.424 1.658 1.554 1.498 44经济社会体制比较世界发展战略研究部CN11-1591/F 1.501 1.174 1.561 1.649 1.471 45税务研究中国税务杂志社CN11-1011/F 1.779 1.133 1.611 1.360 1.471 46世界经济与政治论坛江苏省社会科学院世界经济研究所CN32-1544/F 1.886 1.442 1.288 1.207 1.456 47中央财经大学学报中央财经大学CN11-3846/F 1.605 1.253 1.349 1.508 1.429 48城市问题北京市社会科学院CN11-1119/C 1.677 1.273 1.218 1.484 1.413 49中南财经政法大学学报中南财经政法大学CN42-1663/F 1.336 1.160 1.517 1.628 1.410 50财贸研究安徽财经大学CN34-1093/F 1.256 1.194 1.524 1.637 1.403 51经济问题探索云南省发展和改革委员会CN53-1006/F 1.433 1.108 1.320 1.294 1.289 52国际经贸探索广东外语外贸大学CN44-1302/F 1.5820.987 1.110 1.249 1.232 53财经论丛浙江财经大学CN33-1154/F0.759 1.147 1.376 1.614 1.224 54金融经济学研究广东金融学院CN44-1696/F 1.139 1.130 1.252 1.252 1.193 55国际商务(对外经济贸易大学学报)对外经济贸易大学CN11-3645/F 1.15 1.150 1.296 1.163 1.190 56农村经济四川省农业经济学会CN51-1029/F 1.2570.981 1.220 1.269 1.182 57江西财经大学学报江西财经大学CN36-1224/F0.9310.872 1.370 1.291 1.116 58财政研究中国财政学会CN11-1077/F 1.0950.994 1.185 1.173 1.112 59现代经济探讨江苏省社会科学院CN32-1566/F 1.0120.994 1.346 1.088 1.110 60经济学动态中国社会科学院经济研究所CN11-1057/F 1.1370.914 1.126 1.197 1.094 61经济经纬河南财经政法大学CN41-1421/F 1.0860.884 1.141 1.239 1.088 62改革重庆社会科学院CN50-1012/F——0.503 1.161 1.591 1.085 63亚太经济福建社会科学院CN35-1014/F 1.4530.9160.9550.990 1.079 64经济纵横吉林省社会科学院CN22-1054/F 1.1880.963 1.107 1.044 1.076 65经济问题山西省社会科学院CN14-1058/F 1.1690.8940.995 1.068 1.032 66云南财经大学学报云南财经大学CN53-1209/F 1.2010.8010.8660.9110.945 67当代经济研究吉林财经大学CN22-1232/F0.9570.8230.9940.9260.925 68广东财经大学学报广东财经大学CN44-1446/F0.8640.8000.9110.8420.854 69河北经贸大学学报河北经贸大学CN13-1207/F0.7510.7390.7760.8640.783 70中国经济问题厦门大学经济研究所CN35-1020/F0.7190.3330.5820.8530.622 71价格理论与实践中国价格协会CN11-1010/F0.6860.5130.6900.5610.613 72中国社会经济史研究厦门大学历史研究所CN35-1023/F0.4960.3950.5290.5020.481 73政治经济学评论中国人民大学CN11-5859/D—————————— 以下为CSSCI扩展版来源期刊 排名期刊名称主办单位刊号2010年2011年2012年2013年（五年）四年平均值1金融评论中国社会科学院金融研究所CN11-5865/F—————— 1.778 1.778 2金融论坛城市金融研究所、中国城市金融学会CN11-4613/F 2.348 1.083 1.000 1.504 1.484 3上海金融上海市金融学会CN31-1160/F 1.801 1.251 1.390 1.215 1.414 4技术经济中国技术经济学会CN11-1444/F 1.138 1.135 1.219 1.264 1.189 5现代城市研究南京城市科学研究会CN32-1612/TU 1.1680.916 1.295 1.333 1.178 6税务与经济吉林财经大学CN22-1210/F 1.225 1.113 1.212 1.001 1.138 7消费经济湘潭大学、湖南商学院、湖南师范大学CN43-1022/F 1.215 1.041 1.165 1.129 1.138 8保险研究中国保险学会CN11-1632/F0.839 1.069 1.408 1.152 1.117
《中国学术期刊影响因子年报》评价指标体系 1.期刊影响力综合评价指标——期刊影响力指数（CI ） 统计某个年度内出版的某些源文献引证期刊的次数，可以在统计学意义上反映期刊在该统计年度产生的影响力。简单而常用的计量指标有期刊的总被引频次（TC ，广延量，评价对象为期刊已发表的所有文献）、影响因子（IF ，强度量，评价对象为期刊在统计年之前两年发表的文献）、即年指标（强度量，评价对象为期刊在统计年发表的文献）等。 显然，上述指标的评价对象是期刊在不同时期发表的文献，且评价角度、计量方法各不相同，任一指标都不能全面反映期刊的影响力。期刊评价中片面强调其中某个指标，都会导致期刊出现片面发展倾向，甚至引发期刊的学术不端行为，干扰期刊正常发展。因此，人们一直在希望找到一个综合反映期刊影响力的计量指标。然而，过去这方面的工作总是试图将TC 、IF 等指标先验地假设为同一线性空间的可加标量，按一组人为设定的权重参数拟合为一个“综合指标”，而未注意区分这些指标的内禀属性，得到的期刊排序结果也难以给予合理的解释。 我们在2013年首次提出了一种综合评价学术期刊影响力的方法，连续三年应用于“中国最具国际影响力学术期刊”的遴选，基本原理、计算方法和结果得到了国内外学术界和期刊界的基本认可。 1.1期刊影响力指数（CI ）的基本定义 定义1：期刊影响力排序空间 在某种可比较大小的期刊范围内（同一学科内）将TC 、IF 分别归一化处理为tc 、if ，并按其大小进行期刊排序，即可在排序意义上将TC 、IF 映射到一个2维空间，称为“期刊影响力排序空间”。 定义2：期刊影响力等位线 在“期刊影响力排序空间”内，定义影响力最大的期刊为（1,1），各刊与之的距离为 22B -1)A 1(R ） （+-=，期刊影响力相等的点连成的线即为期刊影响力等位线。显然，等位线就是以（1,1）为圆心的圆弧，见图1。 定义3：期刊影响力指数（CI ） 学术期刊影响力指数（Academic Journal Clout Index ，简称CI ），是反映一组期刊中各刊影响力大小的综合指标，它是将期刊在统计年的总被引频次（TC ）和影响因子（IF ）双指标进行组内线性归一后向量平权计算所得的数值，用于对组内期刊排序。 CI 的计算公式为： [][]1,0B T C T C T C T C B 1,0A IF IF IF IF A 1)B 1()A 1(2CI 2 2∈--= ∈--=-+--=组内最小 组内最大组内最小个刊组内最小组内最大组内最小 个刊其中）（ CI 的几何意义如下：
MAXIDRIVER3.4数字音频处理器 ALTO MAXIDRIVER3.4数字处理器是集增益、噪声门、参数均衡、分频、压缩限 幅、延时为一体的全功能数字音频处理器，具有2个输入通道和6个输出通道，本机内设10种工厂预设的分频模式，64个用户程序数据库位置以及利用多媒体卡（MMC）进行128个用户程序外置储存的功能。MAXIDRIVER3.4是新一代全数字音 频处理器，采用分级菜单形式，操作非常方便。 功能键介绍 前面板 1、MODE---分级菜单选择，按动时循环选择PRESET（预设）、DELAY（延时）、EDIT（编辑）、UTILITY（系统设置）菜单功能。同时相对应的LED指示灯会被点亮。这时可以进入所选择的菜单进行参数编辑。 2、LED指示灯---当你用MODE键选择需要编辑的菜单时，相对应的LED指示 灯会被点亮。 3、2X16位LCD显示屏---显示正在编辑或查看的系统参数或系统状态。 4、数据轮---转动这个数据轮可以调节需要编辑的参数的数值，顺时针旋转提高数值，逆时针旋转减低数值。 5、PREV/NEXT---前翻/后翻键，每个主菜单下面都有若干个子菜单，通过按动这两个按键可以向前或向后选择所需要进行编辑的子菜单。 6、NAVIGATION CURSOR KEYS---光标移动键，每个子菜单中都有若干个可以 编辑的参数选择，按动这两个键，可以选择需要编辑的参数，选中的参数会闪烁。 7、CARD---储存卡插入口，在这个插口插入MMC储存卡，利用PRESET（预设） 菜单下，可以对该储存卡进行写入、读出等操作。 8、ENTER---确认键，按此键可以对所选择的菜单或编辑的参数数值进行确认。 9、ESC---取消键，按此键可以对所选择的菜单或编辑的参数数值进行取消操作，返回上一级菜单。 10、输入电平指示表，实时指示A/B两个输入通道输入电平的强弱数值。 11、MUTE---静音按键，按下后将关闭相应输出通道的输出信号，相对应的 红色LED指示灯将点亮。 12、输出电平指示表，显示每个输出通道输出电平大小数值，这里显示的数 值不是绝对的输出电平数值，而是与该列LED指示灯中的LIMIT（限幅）指示为基础相比较的数值。