2015美赛预备
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Problem A Warmer Days or Sour Grapes ?The high quality of wines(葡萄酒)produced in the Finger Lakes Region(五指湖区)of upstate (北部)New York is widely known. Proximity(接近)to lakes tempers the climate and makes it more suitable for growing several varieties of premium(独特)grapes: R iesling(雷司令), G ewürztraminer(琼瑶浆),C hardonnay(霞多丽), M erlot(梅洛), P inot Noir(黑比诺), and CabernetF ranc(品丽珠). (There are many more, but we will restrict(限制)the discussion to these six to simplify(简化)the modeling.) Each variety has its own preferred “average temperature” range but is also different in its susceptibility(感受性)to diseases and ability to withstand(抵抗)short periods of unusually cold temperature.As our local climate changes, the relative suitability of these varieties will be changing as well. A forward-looking winery(酒厂)has hired your team to help with the long-term planning. You will need to recommenda) the proportion(比例)of the total vineyard(葡萄园)to be used for growing each of the above six varieties;b) and when should these changes be implemented (实施)(based on observed temperatures and/or current market prices for each type of wine).Naturally, the winery is interested in maximizing its annual profit. But since the latter (后者)is weather-dependent, it might vary a lot year-to-year. You are also asked to evaluate the trade-offs (权衡)between optimizing the expected/average case versus the worst(-realistic-)scenario(情景).Things to keep in mind:Climate modeling is complicated(复杂)and predicting the rate of “global warming” is a hotly debated area. For the purposes of this problem, assume that the annual average temperature in Ithaca(伊萨卡), NY will increase by no more than 4°C by the end of this century.It is not all about the average temperature – a short snap(临时)of sub- zero(零度)temperature in late Ferburay or early March (after the vines already started getting used to warmer weather) is far more damaging than the same low temperature would be in the middle of the winter.It takes at least 3 years for a newly planted vine to start producing grapes suitable for winemaking.Problem B Outlook of Car-to-Car TechSAN FRANCISCO -- After more than a decade of research into car-to-car communications, U.S. auto safety regulators took a step forward today by unveiling their plan for requiring cars to have wireless gear that will enable them to warn drivers of danger.These vehicle-to-vehicle (V2V) transmitters and software could save thousands of lives and prevent hundreds of thousands of crashes each year by providing cars with information they never will be able to gather simply from cameras and sensors. “Safety is our top priority, and V2V technology represents the next great advance in saving lives,” Transportation Secretary Anthony Foxx said in an announcement. “This technology could move us from helping people survive crashes to helping them avoid crashes altogether.”Requirement 1: Present a mathematical model to discuss the reduction of the number of traffic accidents and road fatalities/injuries in San Francisco by V2V technology. Requirement 2: Determine the maximum number of cars in San Francisco due to the V2V technology.Requirement 3: Discuss the benefits of V2V technology to alleviate road congestion. Requirement 4: Provide your recommendation to the government.Prblem C Forest FiresOne major environmental concern is the occurrence of forest fires (also called wildfires), which affect forest preservation, bring economical and ecological damage and endanger human lives. Such phenomenon is due to multiple causes (e.g. human negligence and lightnings). Despite an increasing of state expenses to control this disaster, each year millions of forest hectares (ha) are destroyed all around the world.Fast detection is an important element for successful firefighting. Traditional human surveillance is expensive and affected by subjective factors, there has been an emphasis to develop automatic solutions, such as satellite-based, infrared/smoke scanners and local sensors (e.g. meteorological). Propagation models try to describe the future evolution of the forest fire given an initial scenario and certain input parameters. Modeling the dynamical behavior of fire propagation in a forest is helpful for creating scheme to control and fight fire.Requirement 1 Describe several different metrics that could be used to evaluate the effectiveness of fire detection. Could you combine your metrics to make them even more useful for measuring quality?Requirement 2 Model the dynamical behavior of fire spread in a forest. Requirement 3 Discuss the factors to affect fire occurrence. Which factors are the most critical in causing fires. Build mathematical models to predict the burned area of fires using Meteorological Data.Requirement 4 Give y our suggestion for preventing from forest fire and fighting against it.Problem D Wearable Activity RecognitionThe percentage of EU citizens aged 65 years or over is projected to increase from 17.1% in 2008 to 30.0% in 2060. In particular, the number of 65 years old is projected to rise from 84.6 million to 151.5 million, while the number of people aged 80 or over is projected to almost triple from 21.8 million to 61.4 million (EUROSTAT: New European Population projections 2008–2060). It has been calculated that the purely demographic effect of an ageing population will push up health-care spending by between 1% and 2% of the gross domestic product (GDP) of most member states. At first sight this may not appear to be very much when extended over several decades, but on average it would in fact amount to approximately a 25% increase in spending on health care, as a share of GDP, in the next 50 years (European Economy Commission, 2006). The effective incorporation of technology into health-care systems could therefore be decisive in helping to decrease overall public spending on health. One of these emerging health-care systems is daily living physical activity recognition.Daily living physical activity recognition is currently being applied in chronic disease management (Amft & Troter, 2008; Zwartjes, Heida, van Vugt, Geelen, & Veltink, 2010), rehabilitation systems (Sazonov, Fulk, Sazonova, & Schuckers, 2009) and disease prevention (Sazonov, Fulk, Hill, Schutz, & Browning, 2011; Warren et al., 2010), as well as being a personal indicator to health status (Arcelus et al., 2009). One of the principal subjects of the health related applications being mooted is the monitoring of the elderly. For example, falls represent one of the major risks and obstacles to old people’s independence (Najafi, Aminian, Loew, Blanc, & Robert, 2002; Yu, 2008). This risk is increased when some kind of degenerative disease affects them. Most Alzheimer’s patients, for exa mple, spend a long time every day either sitting or lying down since they would otherwise need continuous vigilance and attention to avoid a fall.The registration of daily events, an important task in anticipating and/or detecting anomalous behavior patterns and a primary step towards carrying out proactive management and personalized treatment, is normally poorly accomplished by patients’ families, healthcare units or auxiliary assistants because of limitations in time and resources. Automatic activity-recognition systems could allow us to conduct a completely detailed monitoring and assessment of the individual, thus significantly reducing current human supervision requirements.Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements.Your task is as follows.(1) Build models to recognize daily living activities.(2) Explore the effects of sensor displacement induced by both the intentionalmisplacement of sensors and self-placement by the user.(3) Verify your recognition models’ toleranc e to sensor displacement.Data Set Information:The REALDISP (REAListic sensor DISPlacement) dataset has been originally collected to investigate the effects of sensor displacement in the activity recognition process in real-world settings. It builds on the concept of ideal-placement, self-placement and induced- displacement. The ideal and mutual-displacement conditions represent extreme displacement variants and thus could represent boundary conditions for recognition algorithms. In contrast, self-placement reflects a users perception of how sensors could be attached, e.g., in a sports or lifestyle application. The dataset includes a wide range of physical activities (warm up, cool down and fitness exercises), sensor modalities (acceleration, rate of turn, magnetic field and quaternions) and participants (17 subjects). Apart from investigating sensor displacement, the dataset lend itself for benchmarking activity recognition techniques in ideal conditions.Dataset summary:#Activities: 33#Sensors: 9#Subjects: 17#Scenarios: 3ACTIVITY SET:A1: WalkingA2: JoggingA3: RunningA4: Jump upA5: Jump front & backA6: Jump sidewaysA7: Jump leg/arms open/closedA8: Jump ropeA9: Trunk twist (arms outstretched)A10: Trunk twist (elbows bent)A11: Waist bends forwardA12: Waist rotationA13: Waist bends (reach foot with opposite hand)A14: Reach heels backwardsA15: Lateral bend (10_ to the left + 10_ to the right)A16: Lateral bend with arm up (10_ to the left + 10_ to the right)A17: Repetitive forward stretchingA18: Upper trunk and lower body opposite twistA19: Lateral elevation of armsA20: Frontal elevation of armsA21: Frontal hand clapsA22: Frontal crossing of armsA23: Shoulders high-amplitude rotationA24: Shoulders low-amplitude rotationA25: Arms inner rotationA26: Knees (alternating) to the breastA27: Heels (alternating) to the backsideA28: Knees bending (crouching)A29: Knees (alternating) bending forwardA30: Rotation on the kneesA31: RowingA32: Elliptical bikeA33: CyclingSENSOR SETUP:Each sensor provides 3D acceleration (accX,accY,accZ), 3D gyro (gyrX,gyrY,gyrZ), 3D magnetic field orientation (magX,magY,magZ) and 4D quaternions (Q1,Q2,Q3,Q4). The sensors are identified according to the body part on which is placed respectively:。
PROBLEM A: Eradicating(根除)EbolaThe world medical association has announced that their new medication could stop Ebola and cure patients whose disease is not advanced(晚期的). Build a realistic, sensible, and useful model that considers not only the spread of the disease, the quantity of the medicine needed, possible feasible (可行的)delivery systems, locations of delivery, speed of manufacturing of the vaccine or drug, but also any other critical factors your team considers necessary as part of the model to optimize the eradication of Ebola, or at least its current strain(压力). In addition to your modeling approach for the contest, prepare a 1-2 page non-technical letter for the world medical association to use in their announcement.PROBLEM B: Searching for a lost planeRecall the lost Malaysian flight MH370. Build a generic(一般的)mathematical model that could assist "searchers" in planning a useful search for a lost plane feared to(恐怕) have crashed in open water such as the Atlantic, Pacific, Indian, Southern, or Arctic Ocean while flying from Point A to Point B. Assume that there are no signals from the downed (坠落的) plane. Your model should recognize that there are many different types of planes for which we might be searching and that there are many different types of search planes, often using different electronics or sensors. Additionally, prepare a 1-2 page non-technical paper for the airlines to use in their press conferences concerning their plan for future searches.。
美赛参赛规则和注意事项比赛开始前:1、所有的参赛队必须在美国东部时间2014年2月6号(星期四)下午2点前完成注册。
此注册过程需要由指导老师完成。
2、缴费。
注册完成之后各个队伍需要缴纳100美元的报名费。
3、完成缴费后,每个参赛队伍会获得一个控制编号,获得控制编号意味着报名成功,同时控制编号是识别队伍的唯一标志。
4、在比赛前或比赛中希望更改参赛信息的,都需要通过指导老师进行更改。
5、指导老师需在完成注册和缴费之后确认队伍的相关资料,并打印含有队伍控制编号和摘要的页面,这会在准备邮包时用到。
选择参赛队成员:1、各队需要在美国东部时间2014年2月6日(星期四)晚上8点大赛开始以前选择好参赛队的队员。
一旦比赛开始,就不能增加或是改变任何一个参赛队队员。
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比赛开始之后:1、美国东部时间2014年2月6日(星期四)晚上8点竞赛开始时,可以通过竞赛网站得到题目。
美国东部时间2014年2月6日晚7点50分,比赛题目也会同步发布于一下镜像网站:/mcm/index.html/mcm/index.html/mcm/index.html/mcm/index.html2、每个参赛队伍可以从三道赛题中任选一道。
3、参赛队准备解决方案。
参赛队可以利用任何非生命提供的数据和资料——包括计算机,软件,参考书目,网站,书籍等,但是所有引用的资料必须注明出处,如有参赛队未注明引用的内容的出处,将被取消参赛资格。
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在评卷过程中,摘要占据了相当大的比重,以至于有的时候获奖论文之所以能在众多论文中脱颖而出是因为其高质量的摘要。
PROBLEM A: Eradicating EbolaThe world medical association has announced that their new medication could stop Ebola and cure patients whose diseases not advanced. Build a realistic, sensible, and useful model that considers not only the spread of the disease, the quantity of the medicine needed, possible feasible delivery systems, locations of delivery, speed of manufacturing of the vaccine or drug, but also any other critical factors your team considers necessary as part of the model to optimize the eradication of Ebola, or at least its current strain. In addition to your modeling approach for the contest, prepare a 1-2 page non-technical letter for the world medical association to use in their announcement.A消除埃博拉病毒世界医学协会已经宣布他们的新疗法可以阻止埃博拉疫情和治愈非晚期患者。
构建一个现实的、合理的和有用的模型,不仅要考虑疾病的传播,所需药物的数量,可能且可行的给药系统,给药地点,生产疫苗或药物的速度,而且还要考虑其他关键因素(你的团队认为有必要要考虑的)作为模型的一部分以优化消除埃博拉病毒,或至少是现行毒株。
2015年美国数学建模要求Your Paper's TitleStarts Here: Please Centeruse Helvetica(Arial) 14论文的题目从这里开始:用Helvetica (Arial)14号FULL First Author1, a, FULLSecond Author2,b and Last Author3,c第一第二第三作者的全名1Fulladdress of first author, including country第一作者的地址全名,包括国家2Fulladdress of second author, including country第二作者的地址全名,包括国家3Listall distinct addresses in the same way第三作者同上aemail,bemail, cemail第一第二第三作者的邮箱地址1.文章标题居中用宋体14 2.第一/第二/第三作者宋体143.第一作者详细地址,包括国家,电子邮件(宋体11),第二第三作者一样4.关键词:文章涵盖你论文中的关键词。
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美国(国际)大学生数学建模竞赛将于2015年2月5日-2月9日举行。
美国大学生数学建模竞赛(MCM/ICM),是唯一的国际性数学建模竞赛,也是世界范围内最具影响力的数学建模竞赛,为现今各类数学建模竞赛之鼻祖,目前我国已有清华大学、北京大学、浙江大学、上海交通大学、武汉大学等多所国内知名院校的学生参与了此项赛事的角逐。
2015年美国(国际)大学生数学建模竞赛比赛时间:美国东部时间:2015年2月5日(星期四)下午8点-2月9日下午8点(共4天)北京时间:2015年2月6日(星期五)上午9点-2月10日上午9点农历:十二月十八~十二月廿二重要说明:—COMAP是所有的规则和政策的最后仲裁者,对不遵循竞赛规则和程序的任何队伍,拥有唯一的自由裁量权,取消参赛资格或拒绝登记。
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2015 Contest ProblemsMCM PROBLEMSPROBLEM A: Eradicating EbolaThe world medical association has announced that their new medication could stop Ebola and cure patients whose disease is not advanced. Build a realistic, sensible, and useful model that considers not only the spread of the disease, the quantity of the medicine needed, possible feasible delivery systems, locations of delivery, speed of manufacturing of the vaccine or drug, but also any other critical factors your team considers necessary as part of the model to optimize the eradication of Ebola, or at least its current strain. In addition to your modeling approach for the contest, prepare a 1-2 page non-technical letter for the world medical association to use in their announcement.PROBLEM B: Searching for a lost planeRecall the lost Malaysian flight MH370. Build a generic mathematical model that could assist "searchers" in planning a useful search for a lost plane feared to have crashed in open water such as the Atlantic, Pacific, Indian, Southern, or Arctic Ocean while flying from Point A to Point B. Assume that there are no signals from the downed plane. Your model should recognize that there are many different types of planes for which we might be searching and that there are many different types of search planes, often using different electronics or sensors. Additionally, prepare a 1-2 page non-technical paper for the airlines to use in their press conferences concerning their plan for future searches.ICM PROBLEMSPROBLEM C: Managing Human Capital in OrganizationsClick the title below to download a PDF of the 2015 ICM Problem C.Your ICM submission should consist of a 1 page Summary Sheet and your solution cannot exceed 20 pages for a maximum of 21 pages.Managing Human Capital in OrganizationsPROBLEM D: Is it sustainable?Click the title below to download a PDF of the 2015 ICM Problem D.Your ICM submission should consist of a 1 page Summary Sheet and your solution cannot exceed 20 pages for a maximum of 21 pages.Is it sustainable?。