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直接下载Microscopic traffic simulation: A tool for the design, analysis and evaluation of intelligent transport systemsJ Barcelo, E Codina, J Casas, JL Ferrer - Journal of Intelligent & , 2005 of possibilities and proposals of intelligent transport system (ITS) implementation in LithuaniaA Jarašūniene - Transport, 2006
CAN bus in the electric vehicle monitoring system of Abstract Now, CAN, high-performance and reliability has been recognized and was widely used in industrial automation, marine, medical equipment, industrial equipment, and so on. Field Bus is the development of automation technology One of the focuses of the area known as automated computer LAN. It is a distributed control system to achieve real-time between the nodes, reliable data communications providing strong technical support. CAN bus belonging to the scene of the areas, it is an effective support for real-time control of distributed control or serial communication network. Compared with many of the current RS-485 based on the R line Construction of the Distributed Control System, based on the CAN bus distributed control system has obvious advantages. In this paper, occupies a lot of relevant information based on the comprehensive use of various methods of the CAN bus in the electric vehicle monitoring system in the application of theory and an analysis of development issues, and some of the problems raised his own views. The full text is divided into four parts: The first part of the main topics on the background and content of the subjects studied in the context of topics to write on the CAN bus status and significance in the research described in the content of the object of measurement requirements and complete the task of this paper. The second part, write data acquisition module design, from the SJA1000 CAN-based communications port design, acquisition, the electric car design; electric car design capacity of the collection node consists of three parts. The third part, mainly to write the electric vehicle monitoring network design, the first Fieldbus awakened comparison and choice, selected after the introduction of the CAN bus, the last of the SJA1000 CAN bus controller is introduced. The fourth part is really on the reliability of the system design for discussion, data from the calibration, the anti-jamming software and hardware design of the anti-jamming design in three areas to address the reliability of the system problems. Key words :Fieldbus; CAN bus; SJA1000; nodes;
Along with the development of science and technology, intelligent and automation technology is more and more popular, all kinds of hi-tech also widely used in intelligent robot toy car and manufacturing field, make intelligent robot more and more diverse. Intelligent car is a variety of high-paying technology integration body, it incorporates mechanical, electronic, sensors, computer hardware, software, artificial intelligence and many other subject knowledge, can involves many of today's current areas of technology. This car design mainly by the single chip microcomputer control system module, manostat module, motor driver module, infrared inspection module and to the wireless digital module composition, system to C8051F340 microcontroller as the core, set to foreign control, use linear regulator chip to voltage stability of control for single chip microcomputer and other peripherals for the reliable power supply, using infrared to the module black and white signal detection, use L298N motor driver module to the dc speed-down motor stability control, use light coupling strength chips for electrical isolation of control, disappear
Along with the development of science and technology, intelligent and automation technology is more and more popular, all kinds of hi-tech also widely used in intelligent robot toy car and manufacturing field, make intelligent robot more and more diverse. Intelligent car is a variety of high-paying technology integration body, it incorporates mechanical, electronic, sensors, computer hardware, software, artificial intelligence and many other subject knowledge, can involves many of today's current areas of technology. This car design mainly by the single chip microcomputer control system module, manostat module, motor driver module, infrared inspection module and to the wireless digital module composition, system to C8051F340 microcontroller as the core, set to foreign control, use linear regulator chip to voltage stability of control for single chip microcomputer and other peripherals for the reliable power supply, using infrared to the module black and white signal detection, use L298N motor driver module to the dc speed-down motor stability control, use light coupling strength chips for electrical isolation of control, eliminate interference, the use of wireless digital module CC1101 for two car communication. The intelligent design two cars are from the start to car, overtaking alternately lead, lead a circle overtaking about 27 seconds. Key words: C8051F340 infrared to the dc speed-down wireless digital overtaking lead
直接下载Microscopic traffic simulation: A tool for the design, analysis and evaluation of intelligent transport systemsJ Barcelo, E Codina, J Casas, JL Ferrer - Journal of Intelligent & , 2005 of possibilities and proposals of intelligent transport system (ITS) implementation in LithuaniaA Jarašūniene - Transport, 2006
Artificial Intelligence (AI) is the intelligence of machines and the branch of computer science which aims to create it. Textbooks define the field as "the study and design of intelligent agents,"[1] where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.[2] John McCarthy, who coined the term in 1956,[3] defines it as "the science and engineering of making intelligent machines."[4]The field was founded on the claim that a central property of human beings, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.[5] This raises philosophical issues about the nature of the mind and limits of scientific hubris, issues which have been addressed by myth, fiction and philosophy since antiquity.[6] Artificial intelligence has been the subject of breathtaking optimism,[7] has suffered stunning setbacks[8] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.[9]AI research is highly technical and specialized, deeply divided into subfields that often fail to communicate with each other.[10] Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.[11] General intelligence (or "strong AI") is still a long-term goal of (some) research.[12]Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion's Galatea.[13] Human likenesses believed to have intelligence were built in every major civilization: animated statues were worshipped in Egypt and Greece[14] and humanoid automatons were built by Yan Shi,[15] Hero of Alexandria,[16] Al-Jazari[17] and Wolfgang von Kempelen.[18] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān,[19] Judah Loew[20] and Paracelsus.[21] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).[22] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods".[6] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.The problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention.[11][edit] Deduction, reasoning, problem solvingEarly AI researchers developed algorithms that imitated the step-by-step reasoning that human beings use when they solve puzzles, play board games or make logical deductions.[39] By the late 80s and 90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.[40]For difficult problems, most of these algorithms can require enormous computational resources — most experience a "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem solving algorithms is a high priority for AI research.[41]Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model.[42] AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that gives rise to this skill.General intelligenceMain articles: Strong AI and AI-completeMost researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.[12] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.[74]Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. For example, even a straightforward, specific task like machine translation requires that the machine follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's intention (social intelligence). Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it.[75][edit] ApproachesThere is no established unifying theory or paradigm that guides AI research. Researchers disagree about many issues.[76] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence, by studying psychology or neurology? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?[77] Can intelligent behavior be described using simple, elegant principles (such as logic or optimization)? Or does it necessarily require solving a large number of completely unrelated problems?[78] Can intelligence be reproduced using high-level symbols, similar to words and ideas? Or does it require "sub-symbolic" processing?[79][edit] Cybernetics and brain simulationMain articles: Cybernetics and Computational neuroscience There is no consensus on how closely the brain should be simulated.In the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.[24] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.How can one determine if an agent is intelligent? In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test. This procedure allows almost all the major problems of artificial intelligence to be tested. However, it is a very difficult challenge and at present all agents fail.Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing. Such tests have been termed subject matter expert Turing tests. Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.The broad classes of outcome for an AI test are:Optimal: it is not possible to perform better Strong super-human: performs better than all humans Super-human: performs better than most humans Sub-human: performs worse than most humans For example, performance at draughts is optimal,[143] performance at chess is super-human and nearing strong super-human,[144] and performance at many everyday tasks performed by humans is sub-human.A quite different approach is based on measuring machine intelligence through tests which are developed from mathematical definitions of intelligence. Examples of this kind of tests start in the late nineties devising intelligence tests using notions from Kolmogorov Complexity and compression [145] [146]. Similar definitions of machine intelligence have been put forward by Marcus Hutter in his book Universal Artificial Intelligence (Springer 2005), which was further developed by Legg and Hutter [147]. Mathematical definitions have, as one advantage, that they could be applied to nonhuman intelligences and in the absence of human testers.AI is a common topic in both science fiction and in projections about the future of technology and society. The existence of an artificial intelligence that rivals human intelligence raises difficult ethical issues and the potential power of the technology inspires both hopes and fears.Mary Shelley's Frankenstein,[160] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it also feel? If it can feel, does it have the same rights as a human being? The idea also appears in modern science fiction: the film Artificial Intelligence: A.I. considers a machine in the form of a small boy which has been given the ability to feel human emotions, including, tragically, the capacity to suffer. This issue, now known as "robot rights", is currently being considered by, for example, California's Institute for the Future,[161] although many critics believe that the discussion is premature.[162]Another issue explored by both science fiction writers and futurists is the impact of artificial intelligence on society. In fiction, AI has appeared as a servant (R2D2 in Star Wars), a law enforcer (K.I.T.T. "Knight Rider"), a comrade (Lt. Commander Data in Star Trek), a conqueror (The Matrix), a dictator (With Folded Hands), an exterminator (Terminator, Battlestar Galactica), an extension to human abilities (Ghost in the Shell) and the saviour of the human race (R. Daneel Olivaw in the Foundation Series). Academic sources have considered such consequences as: a decreased demand for human labor,[163] the enhancement of human ability or experience,[164] and a need for redefinition of human identity and basic values.[165]Several futurists argue that artificial intelligence will transcend the limits of progress and fundamentally transform humanity. Ray Kurzweil has used Moore's law (which describes the relentless exponential improvement in digital technology with uncanny accuracy) to calculate that desktop computers will have the same processing power as human brains by the year 2029, and that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction writer Vernor Vinge named the "technological singularity".[164] Edward Fredkin argues that "artificial intelligence is the next stage in evolution,"[166] an idea first proposed by Samuel Butler's "Darwin among the Machines" (1863), and expanded upon by George Dyson in his book of the same name in 1998. Several futurists and science fiction writers have predicted that human beings and machines will merge in the future into cyborgs that are more capable and powerful than either. This idea, called transhumanism, which has roots in Aldous Huxley and Robert Ettinger, is now associated with robot designer Hans Moravec, cyberneticist Kevin Warwick and inventor Ray Kurzweil.[164] Transhumanism has been illustrated in fiction as well, for example in the manga Ghost in the Shell and the science fiction series Dune. Pamela McCorduck writes that these scenarios are expressions of the ancient human desire to, as she calls it, "forge the gods."[6]
智能建筑停车场管理系统论文,我的建议：1.计算机毕业设计可不能马虎，最好还是自己动动脑筋，好好的写一写。 2.网上那种免费的毕业设计千万不能采用，要么是论文不完整，要么是程序运行不了，最重要的是到处都是，老师随时都可以知道你是在网上随便下载的一套3.如果没有时间写，可以在网上找找付费的，我们毕业的时候也是为这个头疼了很长时间，最后在网上找了很久，终于购买了一套毕业设计，还算不错，开题报告+论文+程序+答辩演示都有，主要的都是他们技术做好的成品，保证论文的完整和程序的独立运行，可以先看了作品满意以后再付款，而且同一学校不重复，不存在欺的性质，那个网站的域名我记的不是太清楚了，你可以在百度或者GOOGLE上搜索------七七论文，一定可以找到的这个智能建筑停车场管理系统论文的，祝您好运
一般网站里面买的是不全的，直接交肯定不会通过
论文开题报告基本要素
各部分撰写内容
论文标题应该简洁，且能让读者对论文所研究的主题一目了然。
摘要是对论文提纲的总结，通常不超过1或2页，摘要包含以下内容：
目录应该列出所有带有页码的标题和副标题， 副标题应缩进。
这部分应该从宏观的角度来解释研究背景，缩小研究问题的范围，适当列出相关的参考文献。
这一部分不只是你已经阅读过的相关文献的总结摘要，而是必须对其进行批判性评论，并能够将这些文献与你提出的研究联系起来。
这部分应该告诉读者你想在研究中发现什么。在这部分明确地陈述你的研究问题和假设。在大多数情况下，主要研究问题应该足够广泛，而次要研究问题和假设则更具体，每个问题都应该侧重于研究的某个方面。
模板背景千万不要太花哨 因为是学术论文字数尽可能少一些，自己准备演讲稿展开PPT不是最主要的 弄熟论文才是王道模板题目 答辩人 指导老师论文结构（目录）是否有创新之处论文研究 目的 方法 过程挑重点说出本论文的闪光点（切忌不要放太多，要熟悉内容，否则......）结论 感谢可行性研究类文章 最好字数少一些 配合图表 以及具体实例。最最重要的是熟悉论文 这是最根本的。还有一点是PPT是论文的缩影，重点突出自己会的，到时候就会的多讲点，要是有演示程序什么的就弄到最后边，讲完PPT就跑跑程序。答辩的老师不会细看所有论文的，主要就是听你的PPT，所以一定要扬长避短，还有，最好要突出你论文较新的东西，就算是讲和别人相似的题目有相同的地方也绝不说自己和谁的比较像，最后就是只要是你写在PPT上的就一定弄懂了，PPT前边的会比后边的更受答辩老师关注。我刚参加完答辩 以上是我的建议
点击下载：精美PPT各种风格模板
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谁有PPT模板网盘资源?很多朋友上网百度搜索。可是效果差强人意，下载来的不是拼凑版就是不清晰。不仅费时费力，还让人苦恼不已。可以说PPT模板需求是大的，在我们生产生活中的应用也是非常广泛。自己收集整理了各种风格的ppt模板合辑，现在分享给大家。希望可以帮到你，根据需要选择自己喜欢的下载就行了。
产品简介：PPT模板是指Powerpoint所用的模板,一套好的PPT模板可以让一篇PPT文稿的形象迅速提升,大大增加可观赏性。 同时又可以让PPT思路更清晰,逻辑更严谨,更方便处理图表、文字、图片等内容,ppt模板又分为动态模板和静态模板,动态模板是通过设置动作和各种动画展示达到表达思想同步的一种时尚式模板。
1、首先，PPT封面应该有：毕设来题目、答辩人、指导教师以及答辩日期；2、其次，需要有一个目录页来清楚的阐述本次答辩的主要内容有哪些；3、接下来，就到了答辩的主要内容了，第一块应该介绍课题的研究背景与意义；4、之后，是对于研究内容的理论源基础做一个介绍，这一部分简略清晰即可；5、重头戏自然是自己的研究内容，这一部分最好可以让不太了解相关方面的老师们也能听出个大概，知道到底都做出了哪些工作，研究成果有哪些，研究成果究竟怎么样；6、最后，是对工作的一个总结和展望。7、结束要感谢一下各位老师的指导与支持。下载精美的毕业论文答辩ppt模板，就到怪人网
点击下载：精美PPT各种风格模板（分类整理，持续更新）
收集整理：ppt模板高级感简约商务大学生答辩教师课件工作汇报总结素材模版
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幻灯片模板即已定义的幻灯片格式。PowerPoint和Word、Excel等应用软件一样，都是Microsoft公司推出的Office系列产品之一，主要用于设计制作广告宣传、产品演示的电子版幻灯片，制作的演示文稿可以通过计算机屏幕或者投影机播放；利用PowerPoint，不但可以创建演示文稿，还可以在互联网上召开面对面会议、远程会议或在Web上给观众展示演示文稿。随着办公自动化的普及，PowerPoint的应用越来越广。
飞思卡尔在中国多个城市有分支机构，销售分支遍布热点城市。 在苏州，上海，天津和北京有设计中心。并在天津有较大规模的工厂，主要从事封装和测试等。主要为汽车、网络、无线通信、工业控制和消费电子等行业提供产品。通过嵌入式处理器和辅助产品，为客户提供复杂多样的半导体和软件集成方案，即飞思卡尔所谓的“平台级产品”。飞思卡尔全球现有1万个终端客户，其中包括由公司自己的销售队伍服务的100多家知名的原始设备生产商，以及通过数千个代理商网络服务的其他终端客户。飞思卡尔在全球30多个国家拥有2.2万名全职员工。2004年，摩托罗拉半导体部成为飞思卡尔半导体。近年,飞思卡尔公司还协办全国大学生飞思卡尔杯智能汽车竞赛.
Flying think Carle Cup National College Students smart car race飞思卡尔杯全国大学生智能汽车竞赛
学硕可以联系导师，专硕没必要联系导师。导师的联系方式一般都能在学校官网找到，大多都是工作电子邮箱，一般都是由他带的学生帮忙管理。写下自己的本科学习经历，获得的奖项，参加的活动，发表的文章什么的。没东西可写就不要发了，更不要傻乎乎的直接问我能跟您读研吗。最好是过了初试在联系导师。初试都没过，联系了没毛用