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智能家居室内感应定位系统中英文对照外文翻译文献(文档含英文原文和中文翻译)
A Pyroelectric Infrared Sensor-based Indoor Location-Aware
System for the Smart Home
Suk Lee, Member, IEEE, Kyoung Nam Ha, Kyung Chang Lee, Member, IEEE Abstract —Smart home is expected to offer various intelligent services by recognizing residents along with their life style and feelings. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based methods. The terminal -based method employs a type of device that should be carried by the resident while the non-terminal-based method requires no such device. This paper presents a novel non-terminal-based approach using
an array of pyroelectric infrared sensors (PIR sensors) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed
Index Terms— smart home, location-based service, pyroelectric infrared sensor (PIR sensor), location-recognition algorithm
I. INTRODUCTION
There is a growing interest in smart home as a way to offer a convenient, comfortable, and safe residential environment [1], [2]. In general, the smart home aims to offer appropriate intelligent services to actively assist i n the resident?s life such as housework, amusement, rest, and sleep. Hence, in order to enhance the resident?s convenience and safety, devices such as home appliances, multimedia appliances, and internet appliances should be connected via a home network system, as shown in Fig. 1, and they should be controlled or monitored remotely using a television (TV) or personal digital assistant (PDA) [3], [4].
Fig. 1. Architecture of the home network system for smart home Especially, attention has been focused on location-based services as a way to offer high-quality intelligent services, while considering human factors such as pattern of living, health, and feelings of a resident [5]-[7]. That is, if the smart home can recognize the resident?s pattern of living o r health, then home appliances should be able to anticipate the resident?s needs and offer appropriate intelligent service more actively. For example, in a passive service environment, the resident controls the operation of the HVAC (heating, ventilating, and air conditioning) system, while the smart home would control the temperature and humidity of a room according to the resident?s condition. Various indoor location-aware systems have been
developed to recognize the resident?s location in the smart home or smart office. In general, indoor location-aware systems have been classified into three types according to the measurement technology: triangulation, scene analysis, and proximity methods [8]. The triangulation method uses multiple distances from multiple known points. Examples include Active Badges [9], Active Bats [10], and Easy Living [11], which use infrared sensors, ultrasonic sensors, and vision sensors, respectively. The scene analysis method examines a view from a particular vantage point. Representative examples of the scene analysis method are MotionStar [12], which uses a DC magnetic tracker, and RADAR [13], which uses IEEE 802.11 wireless local area network (LAN). Finally, the proximity method measures nearness to a known set of points. An example of the proximity method is Smart Floor [14], which uses pressure sensors. Alternatively, indoor location-aware systems can be classified according to the need for a terminal that should be carried by the resident. Terminal-based methods, such as Active Bats, do not recognize the resident?s location directly, but perceive the location of a device carried by the resident, such as an infrared transceiver or radio frequency identification (RFID) tag. Therefore, it is impossible to recognize the resident?s location if he or she is not carrying the device. In contrast, non-terminal methods such as Easy Living and Smart Floor can find the resident?s location without such devices. However, Easy Living can be regarded to invade the resident?s privacy while the Smart Floor has difficulty with extendibility and maintenance. This paper presents a non-terminal based location-aware system that uses an array of pyroelectric infrared (PIR) sensors [15], [16]. The PIR sensors on the ceiling detect the presence of a resident and are laid out so that detection areas of adjacent sensors overlap. By combining the outputs of multiple PIR sensors, the system is able to locate a resident with a reasonable degree of accuracy. This system has inherent advantage of non-terminal based methods while avoiding privacy and extendibility, maintenance issues. In order to demonstrate its efficacy, an experimental test bed has been constructed, and the proposed system has been evaluated experimentally under various experimental conditions. This paper is organized into four sections, including this introduction. Section II presents the architecture of the PIR sensor-based indoor location-aware system (PILAS), and the location-recognition algorithm. Section III describes a resident-detection method using PIR sensors, and evaluates the performance of the system under various conditions using an experimental test bed. Finally, a summary and the conclusions are presented in Section IV.
II. ARCHITECTURE OF THE PIR SENSOR-BASED INDOOR
LOCATION-AWARE SYSTEM
A. Framework of the smart home
Given the indoor environment of the smart home, an indoor location-aware system must satisfy the following requirements. First, the location-aware system should be implemented at a relatively low cost because many sensors have to be installed in rooms of different sizes to detect the resident in the smart home. Second, sensor installation must be flexible because the shape of each room is different and there are obstacles such as home appliances and furniture, which prevent the normal operation of sensors. The third requirement is that the sensors for the location-aware system have to be robust to noise, and should not be affected by their surroundings. This is because the smart home can make use of various wireless communication methods such as wireless LAN or radio-frequency (RF) systems, which produce electromagnetic noise, or there may be significant changes in light or temperature that can affect sensor performance. Finally, it is desirable that the system?s accuracy is adjustable according to room types.
Among many systems that satisfy the requirement, the PIR sensor-based system has not attracted much attention even though the system has several advantages. The PIR sensors,which have been used to turn on a light when it detects human movement, are less expensive than many other sensors. In addition, because PIR sensors detect the infrared wavelengthemitted from humans between 9.4~10.4 μm, they are reasonably robust to their surroundings, in terms of temperature, humidity, and electromagnetic noise. Moreover, it ispossible to control the location accuracy of the system by adjusting the sensing radius of a PIR sensor, and PIR sensors are easily installed on the ceiling, where they are not affected by the structure of a room or any obstacles.
Figure 2 shows the framework for the PILAS in a smart home that offers location-based intelligent services to a resident. Within this framework, various devices are connected via a home network system, including PIR sensors, room terminals, a smart home server, and home appliances. Here, each room is regarded as a cell, and the appropriate number of PIR sensors is installed on the ceiling of each cell to provide sufficient location accuracy for the location-based services. Each PIR sensor attempts to detect the resident at a constant period, and transmits its sensing information to a room terminal via the home network system.
Fig. 2. Framework of smart home for the PILAS.
Consequently, the room terminal recognizes the resident?s l ocation by integrating the sensor information received from all of the sensors belonging to one cell, and transmits the resident?s location to the smart home server that controls the home appliances to offer location-based intelligent services to the resident.
Within this framework, the smart home server has the following functions. 1) The virtual map generator makes a virtual map of the smart home (generating a virtual map), and writes the location information of the resident, which is received from a room terminal, on the virtual map (writing the resident?s location). Then, it makes a moving trajectory of the resident by connecting the successive locations of the resident (tracking the resident?s movement). 2) The home appliance controller transmits control commands to home appliances via the home network system to provide intelligent services to the resident. 3) The moving pattern predictor saves the current movement trajectory of the resident, the current action of home appliances, and parameters reflecting the current home environment such as the time, temperature, humidity, and illumination. After storing sufficient information, it may be possible to offer human-oriented intelligent services in which the home appliances spontaneously provide services to satisfy human needs. For example, if the smart home server “knows” that the resident normally wakes up at 7:00 A.M. and takes a shower, it may be possible to turn on the lamps and some music. In addition, the temperature of the shower water can be set automatically for the resident.
B. Location-recognition algorithm
In order to determine the location of a resident within a room, an array of PIR sensors are used as shown in Fig. 3. In the figure, the sensing area of each PIR sensor is shown as a circle, and the sensing areas of two or more sensors overlap. Consequently, when a resident enters one of the sensing areas, the system decides whether he/she belongs to any sensing area by integrating the sensing information collected from all of the PIR sensors in the room. For example, when a resident enters the sensing area B, sensors a and b output …ON? signals, while sensor c outputs …OFF? signal. After collecting outputs, the algorithm can infer that the resident belongs to the sensing area B. According to the number of sensors and the arrangement of the sensors signaling …ON?, the resident?s location is deter-mined in the following manner. First, if only one sensor outputs …ON? signal, the resident is regarded to be at the center of the sensing area of the corre sponding sensor. If the outputs of two adjacent sensors are …ON?, the resident?s location is assumed to be at the point midway between the two sensors. Finally, if three or more sensors signal …ON?, the resident is located at the centroid of the centers of the corresponding sensors. For example, it is assumed that the resident is located at point 1 in the figure when only sensor a signals …ON?, while the resident is located at point 2 when sensors a and b both output …ON? signals.
The location accuracy of this system can be defined the maximum distance between the estimated points and the resident. For example, when a resident enters sensing area A, the resident is assumed to be at point 1. On the assumption that a resident can be represented by a point and the radius of the sensing area of a PIR sensor is 1 m, we know that the location accuracy is 1 m because the maximum error occurs when the resident is on the boundary of sensing area A. Alternatively, when the resident is in sensing area B, the resident is assumed to be at point 2, and the maximum location error occurs when the resident is actually at point 3. In this case, the error is 3 / 2 m which is the distance between points 2 and 3. Therefore, the location accuracy of the total system shown in Fig. 3 can be regarded as 1 m, which is the maximum value of the location accuracy of each area. Since the number of sensors and the size of their sensing areas determine the location accuracy of the PILAS, it is necessary to arrange the PIR sensors properly to guarantee the specified system accuracy.
Fig. 3. The location-recognition algorithm for PIR sensors.
In order to determine the resident?s location precisely and increase the accuracy of the system, it is desirable to have more sensing areas with given number of sensors and to have sensing areas of similar size. Fig. 4 shows some examples of sensor arrangements and sensing areas. Fig. 4(a) and 4(b) show the arrangements with nine sensors that produce 40 and 21 sensing areas, respectively. The arrangement in Fig. 4(a) is better than Fig. 4(b) in terms if the number of sensing areas. However, the arrangement in Fig. 4(a) has some areas where a resident can not be detected and lower location accuracy than that in Fig. 4(b). Fig. 4(c) shows an arrangement with twelve sensors that five 28 sensing areas without any blind spots.
Fig. 4. Location accuracy according to the sensor arrangement of PIR
sensors. (a) 40 sensing areas. (b) 21 sensing areas. (c) 28 sensing areas
with twelve sensors.
When PIR sensors are installed around the edge of a room, as shown in Fig. 4(c), it sometimes may give awkward results. One example is shown in Fig. 5. Fig. 5(a) shows the path of a resident. If we mark the estimated points by using the sensor location or the midpoint of adjacent sensors, it will be a zigzagging patterns as shown in Fig. 5(b). In order to alleviate this, we may regard the sensors on the edges to be located a little inwards, which give the result shown in Fig. 5(c).
Fig. 5. The effect of compensating for the center point of the outer sensors.
(a) Resident?s movement. (b) Before compensating for the outer sensors. (c)
After compensating for the outer sensors.
III. PERFORMANCE EVALUATION OF THE PILAS
A. Resident-detection method using PIR sensors
Since the PILAS recognizes the resident?s location by combining outputs from all the sensors belonging to one cell, determining whether a single sensor is …ON? or …OFF? directly influences location accuracy. In general, because the …ON/OFF? values can be determined by co mparing a predefined threshold and the digitized sensor output acquired by sampling the analog signal from a PIR sensor, it is necessary to choose an appropriate signal level for the threshold. For example, Smart Floor, which is another non-terminal method, can recognize a resident?s location exactly by comparing the appropriate threshold and a sensor value, because a pressure sensor outputs a constant voltage based on the resident?s weight when he remains at a specific point. However, because a PIR sensor measures the variation in the infrared signal produced by a moving human body, its output is in analog form, as shown in Fig. 6. That is, as the variation in the infrared
radiation from a resident increases when a resident enters a sensing area, the PIR sensor outputs an increasing voltage. Conversely, the voltage decreases as the resident leave the sensing area. If the resident does not move within the sensing area, the variation in the infrared radiation does not exist and the PIR sensor outputs zero voltage. Therefore, it is very difficult to deter-mine when a resident is staying resident within a specific sensing area using only the voltage or current threshold of a PIR sensor.
Fig. 6. Signal output of PIR sensor.
In order to guarantee the location accuracy of the system, the resident-detection method must meet several requirements. First, if no resident is present within a sensing area, the PIR sensor should not output …ON? signal. That is, the PIR sensor must not malfunction by other disturbances such as a moving pet, temperature change and sunlight. Second, it should be possible to precisely determine the point in time when a resident enters and leaves a sensing area. That is, in spite of variations in sensor characteristics, resident?s speed and heig ht, it should be possible to determine the time point exactly. Finally, because the output voltage of a PIR sensor does not exceed the threshold voltage when the resident does not move within a sensing area, it is necessary to know if a resident stays within the sensing area.
In order to satisfy these requirements, this paper introduces the following implementation method for the resident detection method for PIR sensors. First, in order to eliminate PIR sensor malfunctioning due to pets or temperature changes, a Fresnel lens, which allows human infrared waveforms to pass through it while rejecting other waveforms, is installed in front of the PIR sensors. Second, when the output of a PIR sensor exceeds the positive threshold voltage, and this state is maintained for several predefined sampling intervals, that the resident has entered a sensing area. Here, the threshold must be sufficient for the method to distinguish variation in the resident?s infrared from an environmental infrared signal caused by pets o r temperature change. Moreover, when the sensor?s output falls below a negative threshold voltage and this status is maintained for several sampling intervals, it is assumed that the resident has left the sensing area. Finally, when the output voltage remains between the two threshold voltages, for example when the resident is not moving inside the sensing area, the output of the corresponding PIR sensor is changed from …ON? to …OFF?. At this time, if other sensors installed near this sensor do not
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International Journal of Computer Networks & Communications (IJCNC) V ol.6, No.1, January 2014 基于Android应用的无处不在的智能家居系统 Shiu Kumar Department of Information Electronics Engineering, Mokpo National University, 534-729, Mokpo, South Korea 摘要 本文提出了一种灵活独立的，低成本的智能家居系统，它是基于Android应用与微web服务器通信，不仅仅提供交换功能。Arduino以太网的使用是为了避免使用个人电脑从而保证整个系统成本最低，语音激活时用来实现切换功能的。光开关，电源插头，温度传感器，湿度传感器，电流传感器，入侵检测传感器，烟雾/气体传感器和警报器等这些设备集成在系统中，表明了所提出的智能家居系统的有效性和可行性。经过检测，智能家居应用程序可以成功地进行智能家居操作，例如开关功能，自动环境监测，和入侵监测，在监测到有不法入侵后，系统会自动发送一个邮件，并响警笛。 关键字： Android智能手机，智能家居，物联网（loTs），远程控制 1.引言 随着移动设备受欢迎程度的不断增长和人们日常生活中对无处不在的先进的移动应用的功能需求不断增加，利用Web服务是提供远程访问服务的最开放和可互操作的方式，并且使应用程序能够彼此通信。一个有吸引力的市场产品自动化和网络化是忙碌的家庭和有生理缺陷的个人的代表。 loTs可以被描述为连接智能手机，网络电视，传感器等到互联网，实现人们之间沟通的新形势。过去几年中loTs的发展，创造了一个新层面的世界。这使得人们可以在任何时间，任何地点，联通任何期望的东西。物联网技术可用于为智能家居创建新的概念和广阔的空间，以提供智能，舒适的发展空间和完善生活质量。 智能家居是一个非常有前途的领域，其中有各种好处，如增加提供舒适性，更高安全性，更合理地使用能源和其他资源。这项研究的应用领域非常重要，未来它为帮助和支持有特殊需求老的人和残疾人士提供了强有力的手段。设计一个智能家居系统时需要考虑许多因素，该系统应该是经济实惠的，是可伸缩的，使得新的设备可以容易地集成到系统中，此外，它应该是用户友好的。 随着智能手机用户的急剧增加，智能手机已经逐渐变成了具备所有功能的便携式设备，为人们提供了日常使用。本文介绍了一种低成本的控制和监视家居环境控制的无线智能家居系统。利用Android设备，可以通过一个嵌入式微Web服务器与实际的IP连接，访问和控制电器和远程的其它设备，这可以利用任何支持Android的设备。Arduino Ethernet 用于微Web服务器从
Manufacturing Engineering and Technology(机械类英文文献+翻译)
Manufacturing Engineering and Technology—Machining Serope kalpakjian；Steven R.Schmid 机械工业出版社2004年3月第1版 20.9 MACHINABILITY The machinability of a material usually defined in terms of four factors: 1、Surface finish and integrity of the machined part; 2、Tool life obtained; 3、Force and power requirements; 4、Chip control. Thus, good machinability good surface finish and integrity, long tool life, and low force And power requirements. As for chip control, long and thin (stringy) cured chips, if not broken up, can severely interfere with the cutting operation by becoming entangled in the cutting zone. Because of the complex nature of cutting operations, it is difficult to establish relationships that quantitatively define the machinability of a material. In manufacturing plants, tool life and surface roughness are generally considered to be the most important factors in machinability. Although not used much any more, approximate machinability ratings are available in the example below. 20.9.1 Machinability Of Steels Because steels are among the most important engineering materials (as noted in Chapter 5), their machinability has been studied extensively. The machinability of steels has been mainly improved by adding lead and sulfur to obtain so-called free-machining steels. Resulfurized and Rephosphorized steels. Sulfur in steels forms manganese sulfide inclusions (second-phase particles), which act as stress raisers in the primary shear zone. As a result, the chips produced break up easily and are small; this improves machinability. The size, shape, distribution, and concentration of these inclusions significantly influence machinability. Elements such as tellurium and selenium, which are both chemically similar to sulfur, act as inclusion modifiers in
毕业设计_英语专业论文外文翻译
1. Introduction America is one of the countries that speak English. Because of the special North American culture, developing history and the social environment, American English has formed its certain unique forms and the meaning. Then it turned into American English that has the special features of the United States. American English which sometimes also called United English or U.S English is the form of the English language that used widely in the United States .As the rapid development of American economy, and its steady position and strong power in the world, American English has become more and more widely used. As in 2005, more than two-thirds of English native speakers use various forms of American English. The philologists of the United States had divided the English of the United States into four major types: “America n creating”; “Old words given the new meaning”; “Words that eliminated by English”;“The phonetic foreign phrases and the languages that are not from the English immigrates”[1]. Compared to the other languages, American English is much simple on word spelling, usage and grammar, and it is one of the reasons that American English is so popular in the world. The thesis analyzes the differences between American English and British English. With the main part, it deals with the development of American English, its peculiarities compared to that of British English, its causes and tendency. 2. Analyses the Differences As we English learners, when we learning English in our junior or senior school, we already came across some words that have different spellings, different pronunciations or different expressions, which can be represented by following contrasted words: spellings in "color" vs. "colour"; pronunciations in "sec-re-ta-ry" vs. "sec-re-try";
论文《人工智能》---文献检索结课作业
人工智能 【摘要】：人工智能是一门极富挑战性的科学，但也是一门边沿学科。它属于自然科学和社会科学的交叉。涉及的学科主要有哲学、认知科学、数学、神经生理学、心理学、计算机科学、信息论、控制论、不定性论、仿生学等。人工智能(Artificial Intelligence)，英文缩写为AI。它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学。人工智能是计算机科学的一个分支，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等1。 【关键词】：人工智能；应用领域；发展方向；人工检索。 1．人工智能描述 人工智能(Artificial Intelligence) ，英文缩写为AI。它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学2。人工智能是计 算机科学的一个分支，它企图了解智 能的实质，并生产出一种新的能以人 类智能相似的方式作出反应的智能 机器，该领域的研究包括机器人、语 言识别、图像识别、自然语言处理和 专家系统等。“人工智能”一词最初 是在1956 年Dartmouth学会上提出 的。从那以后,研究者们发展了众多 理论和原理,人工智能的概念也随之扩展。人工智能是一门极富挑战性的科学，从事这项工作的人必须懂得计算机知识，心理学和哲学。人工智能是包括十分广泛的科学，它由不同的领域组成，如机器学习，计算机视觉等等，总的说来，人工智能研究的一个主要目标是使机器能够胜任一些通常需要人类智能才能完成的复杂工作。但不同的时代、不同的人对这种“复杂工作”的理解是不同的。例如繁重的科学和工程计算本来是要人脑来承担的，现在计算机不但能完成这种计算, 而且能够比人脑做得更快、更准确，因之当代人已不再把这种计算看作是“需要人类智能才能完成的复 1.蔡自兴，徐光祐.人工智能及其应用.北京：清华大学出版社，2010 2元慧·议当人工智能的应用领域与发展状态〖Ｊ〗．2008
智能家居医疗保健中英文对照外文翻译文献
智能家居医疗保健中英文对照外文翻译文献 (文档含英文原文和中文翻译) 原文： Foreign Literature Increasing an individual’s quality of life via their intelligent home The hypothesis of this project is: can an individual’s quality of life be increased by integrating “intelligent technology”into their home environment. This hypothesis is very broad, and hence the researchers will investigate it with regard to various, potentially over-lapping, sub-sections of the population. In particular, the project will focus on sub-sections with health-care needs, because it is believed that these sub-sections will receive the greatest benefit from this enhanced approach to housing. Two research questions flow from this hypothesis: what are the health-care issues that could be improved via “intelligent housing”, and what are the technological issues needing to be solved to allow “intelligent housing”to be constructed?
机械专业中英文对照翻译大全.
机械专业英语词汇中英文对照翻译一览表 陶瓷ceramics 合成纤维synthetic fibre 电化学腐蚀electrochemical corrosion 车架automotive chassis 悬架suspension 转向器redirector 变速器speed changer 板料冲压sheet metal parts 孔加工spot facing machining 车间workshop 工程技术人员engineer 气动夹紧pneuma lock 数学模型mathematical model 画法几何descriptive geometry 机械制图Mechanical drawing 投影projection 视图view 剖视图profile chart 标准件standard component 零件图part drawing 装配图assembly drawing
尺寸标注size marking 技术要求technical requirements 刚度rigidity 内力internal force 位移displacement 截面section 疲劳极限fatigue limit 断裂fracture 塑性变形plastic distortion 脆性材料brittleness material 刚度准则rigidity criterion 垫圈washer 垫片spacer 直齿圆柱齿轮straight toothed spur gear 斜齿圆柱齿轮helical-spur gear 直齿锥齿轮straight bevel gear 运动简图kinematic sketch 齿轮齿条pinion and rack 蜗杆蜗轮worm and worm gear 虚约束passive constraint 曲柄crank 摇杆racker
无线数据采集和传输系统外文翻译文献
无线数据采集和传输系统外文翻译文献 (文档含中英文对照即英文原文和中文翻译) 译文： 一种无线数据采集和传输系统的设计【摘要】在现代无线通信领域主要有一些技术为无线传输网络提供解决方法，例如：GSM，CDMA，3G，Wi-Fi。这些方法使得网络能够高效率和高质量的工作，但是成本很高。因此要低成本和在没有基础设施或者基础设施被破坏的情况下推广它们是很困难的。根据这种情况，本论文中数据采集和无线传输网络里的信息终端和无线收发模块的关键部件，是依据nRF905收发模块和51系列单片机的原理设计而成作为核心硬件，此外，结合目前自组无线网络的技术，可以构建一个短距离无
线数据采集和传输网络，这个网络能够提供一个工作在ISM（工业科学医学）频段的低功率及高性能的数据通信系统。然后提出了一个对无线通信可行的解决方案，这个方案优势在于更强的实时响应，更高的可靠性要求和更小的数据量。通过软件和硬件的调试和实际测量，这个系统在我们的解决方案基础上运行良好，达到了预期的目标并且已经成功的应用到无线车辆系统。 【关键词】自组网络；数据采集；传输网络 1 简介 在现代无线通信里，GSM，CDMA，3G和Wi-Fi因为其高速和可靠的质量而逐渐成为无线数据传输网络的主流解决方案。它们也有高成本的缺点，因此如果广泛的应用，将会引起大量的资源浪费，也不能在小区域，低速率的数据通信中得到提升。多点短距离无线数据采集和传输网络将成为最佳解决方案。此系统支持点对点，点对多点和多点对多点通信系统的发展。 短距离无线通信可以适应各种不同的网络技术，例如蓝牙， IEEE802.11，家庭无线网和红外。与远距离无线通信网络相比，它们的不同之处在于基本结构，应用水平，服务范围和业务（数据，语音）。设计短距离无线通信网络的最初目的是为了提供短距离宽带无线接入到移动环境或者制定临时网络，这是在移动环境里互联网更深的发展。短距离无线通信网络最主要的优势是更低的成本和更灵活的应用。 本文介绍信息终端（单个器件）的硬件和软件以及多点短距离无线数据采集和传输网络的无线接收模块的设计建议，提供一个低功率高性
java毕业论文外文文献翻译
Advantages of Managed Code Microsoft intermediate language shares with Java byte code the idea that it is a low-level language witha simple syntax , which can be very quickly translated intonative machine code. Having this well-defined universal syntax for code has significant advantages. Platform independence First, it means that the same file containing byte code instructions can be placed on any platform; atruntime the final stage of compilation can then be easily accomplished so that the code will run on thatparticular platform. In other words, by compiling to IL we obtain platform independence for .NET, inmuch the same way as compiling to Java byte code gives Java platform independence. Performance improvement IL is actually a bit more ambitious than Java bytecode. IL is always Just-In-Time compiled (known as JIT), whereas Java byte code was ofteninterpreted. One of the disadvantages of Java was that, on execution, the process of translating from Javabyte code to native executable resulted in a loss of performance. Instead of compiling the entire application in one go (which could lead to a slow start-up time), the JITcompiler simply compiles each portion of code as it is called (just-in-time). When code has been compiled.once, the resultant native executable is stored until the application exits, so that it does not need to berecompiled the next time that portion of code is run. Microsoft argues that this process is more efficientthan compiling the entire application code at the start, because of the likelihood that large portions of anyapplication code will not actually be executed in any given run. Using the JIT compiler, such code willnever be compiled.
智能家居外文翻译文献
智能家居外文翻译文献 (文档含中英文对照即英文原文和中文翻译) 译文： 提高个人的生活质量，通过他们的智能家居 该项目的假设是：可以增加一个人的生活质量的“智能技术”集成到他们的家庭环境。这个假设是非常广泛的，因此，研究人员将调查它考虑到多方面的，潜在的过度研磨，分节的人口。特别是，该项目将重点放在与卫生保健需求的环节，因为它认为，这些子章节将获得最大的受益于这种增强的方法住房。两个研究问题流从这一假说：什么是保健，可以改善通过“智能住宅”的问题，什么是技术问题需要解决，让“智能住宅”建造？虽然存在少量的措施，在加拿大境外，据称这方面的调查，没有这方面的全球视野。工作往往是在小范围内的各个部分是如何有助于实现更大的目标只有有限的想法。这个项目有一
个非常强烈的责任感，并认为，如果没有这一全球性的方向，其他措施将失败，以解决各部分的重要问题，而且正确的全局方向的总和的部分会产生更大的回报比的各个组成部分。这个新的领域与业务流程工程领域，有许多相似之处，很多产品失败的原因只考虑一个子集的问题，通常是技术的子集。成功的项目和实施才开始启动，当人们开始认识到，一个全面的方法是至关重要的。这种整体性的要求也适用于领域的“聪明屋”，如果我们真的希望它有利益于社区，而不仅仅是技术的兴趣。话虽如此，下面列出的大部分工作是非常重要的，在其个人的主题包含了大量新奇的。 医疗保健和保障性住房： 至目前为止，很少有人协调，研究如何“聪明屋”的技术可以帮助体弱的老人留在家里，或降低成本所经历的非正式照顾者。因此，建议研究的目的是确定帮助老年人保持自己的独立性和帮助照顾者维持他们的爱心活动中的各种住宅技术的实用性。 整体设计的研究是集中在两个群体的老年人。首先是老人出院急性护理环境的潜在能力下降，保持独立。一个例子是有髋关节置换手术的老年人。本集团可能会受益于技术，这将有助于他们成为适应他们的行动不便。第二个是老年人有慢性健康问题，如老年痴呆症和接受援助的非正式护理员的生活在距离。关心的高级生活的距离是非正式照顾者在照顾者的职业倦怠的高风险。监测的关心，高级健康和安全是通过这样照顾者的重要任务之一。如地面传感器和访问控制来确保安全的入侵者或指示私奔与老年痴呆症的高级设备，可以减少护理