Aspect-Oriented Software Architecture (AOA) is a high-level abstraction and integration blueprint of aspectual component-based software.A semantic model of aspectual component-based software is proposed to provide behavior description and semantic foundation for the consistency verification of software architecture dynamic evolution.By using the semantic model of Pi-calculus,a set of the consistency verification methods of dynamic evolution from multiple aspects are introduced.Finally,a case study shows the effect of these methods.

关键词：软件体系结构；动态演化;行为一致性；电子信息

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关键词：地图界面;信息采集;递归聚类;信息可视化

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In this chapter, low-density parity-check (LDPC) codes, a class of powerful iteratively decodable error correcting codes, are introduced. The chapter first reviews some basic concepts and results in information theory such as Shannon's channel capacity and channel coding theorem. It then overviews the Flash memory channel model. Finally, it addresses LDPC codes describing both their structure and efficient implementation, and their decoding algorithms. Simulation results are also provided.

关键词：低密度奇偶校验码；迭代解码；仿真；电子信息

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The literature on intelligent systems was reviewed in relation to the following: efficient human supervision of multiple robots; appropriate human trust in the automated systems; maintenance of human operator s situation awareness; individual differences in human-agent (H-A) interaction; and retention of human decision authority. A number of approaches, from flexible automation to autonomous agents, were reviewed and their advantages and disadvantages were discussed. Also discussed were two key human performance issues (trust and situation awareness) related to H-A teaming for multi-robot control and some promising user interface design solutions to address these issues. Some key individual differences factors (operator spatial ability, attentional control ability, and gaming experience) were identified that may impact H-A teaming in the context of robotics control.

关键词：人类，机器人；自动化；保留（一般）；人类与机器人互动

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Contextual awareness refers to having autonomous robots reason about their capabilities and limitation and improve on those limitations through the help of others. This project explored three areas of contextual awareness detecting when anomalous behaviors occur, reacting to situations where plans are failing, and learning new plans through human demonstration. Each of these areas is important in achieving robust, reliable robot autonomy. The work on detecting anomalous behavior focused on finding subtle anomalies that could not be detected from single events; the work on reacting to failing plans focused on deciding when to switch between risk-neutral and risk-seeking policies, for domains in which the goal is to achieve above a certain threshold of reward; and the work on learning new plans focused on complex manipulator trajectories, where multiple human examples are combined so as to smooth out noise in the examples without losing important details. The first and third areas were demonstrated using actual robots; the second area was demonstrated using a video game simulator.

关键词：人工智能；机器人技术；机器人；自动操作

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关键词：Web应用程序；WebGL；HTML5；机器人仿真；COLLADA

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Using a multi-robot system in military operations poses many control problems. Thus, the ability to formulate clear and unambiguous commands for the robots is extremely desirable. To ensure that the operator expresses clearly what needs to be done, we use Battle Management Language (BML) to command multi- robot systems. BML was developed by the military research community to express short, unambiguous orders readable by both humans and machines. BML allows the operator to command the multi-robot system using a single controller on a mobile device (e.g., a tablet). We use BML reports to send information from the robots to the BML-Graphical User Interface (GUI). Position information, operational status, task status, and information about detected units are directly transformed into BML reports. The robots also report binary data such as images, video, or lidar data. These data cannot be translated into BML because BML is limited to textual messages. Instead, the data are converted into another XML format. After conversion, they are sent to the GUI and can be stored in a central database so that other (superordinate) C2 systems can make use of it. This article presents an overview of the BML communication architecture, the BML language and the commands that can be given to robots using BML, and the BML reports system.

关键词：指挥和控制系统；多智能体系统；机器人

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This paper discussed several methods to maximize the sum of the data rate.After the analysis of the graphic algorithm,we found the difficulty of the determination of the variables.To solve the problem,we propose a new idea to operate the variable and proved it to be efficient in the simulation results.

关键词：数据传输速率；蜂窝网络；图形算法；功率控制；电子信息

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Fuzzy clustering algorithms have been widely used for image segmentation,typically such as FCM algorithm.However,the FCM algorithm is parameter sensitive,and its results lack of availability.To improve the above problems,a novel fuzzy clustering method based on semantic color tree for image segmentation is proposed in this paper.The method is realized by modifying the membership function in the conventional FCM algorithm and by constructing the semantic color tree to achieve the semantic color extraction,which take human visual subjectivity into account in semantics.The proposed method is applied to real images.Experimental results show that the presented algorithm performs more effectively than the FCM algorithm.

关键词：模糊聚类;语义色彩;语义树;颜色提取;电子信息

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Multi-thresholding is an important step for automatic image analysis.In this paper,a multi-thresholding method based on symmetric Tsallis-cross entropy and uniform searching particle swarm optimization (UPSO) is proposed.The criterion function using symmetric Tsallis-cross entropy can make the grayscale within the background cluster and the object cluster uniform.Since the exhaustive multi-thresholding algorithm would be too time-consuming,UPSO algorithm is adopted to find the optimal thresholds quickly and accurately.A large number of experimental results show that,compared with related multi-thresholding methods based on Shannon entropy and Tsallis entropy,the proposed method is effective and rapid.It can obtain more accurate boundary shape and clearer details of object.

关键词：图像分割;多阈值;对称Tsallis交叉熵;均匀搜索粒子群优化

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