基于Visual Basic的公差与配合精度设计

文章利用Visual Basic进行公差与配合精度设计,以理论设计和优化设计代替传统的经验设计和人工检索,计算配合参数,判断其配合的可行性,应用于对图样上公差与配合的分析计算.     

Knowledge and Belief: Some Clarifications

The notions of knowledge and belief play an important role in philosophy. Unfortunately, the literature is not very consistent about defining these notions. Is belief more fundamental than knowledge or is it the other way around? Many accounts rely on the widely accepted strategy of appealing to the intuition of the reader. Such an argumentative methodology is fundamentally flawed because it lets the problems of common sense reasoning in through the front door. Instead, I suggest that philosophical arguments should be based on formal-computational models to (a) reduce the ambiguities and uncertainties that come with intuitive arguments and reasoning, and (b) capture the dynamic nature of many philosophical concepts. I present a model of knowledge and belief that lends itself to being implemented on computers. Its purpose is to resolve terminological confusion in favor of a more transparent account. The position I defend is an antirealist naturalized one: knowledge is best conceived as arising from experience, and is fundamental to belief.     

Exploring the Belief Systems of Software Development Professionals

It is commonly accepted that an individual's beliefs and actions are based on his or her assessment and perceptions of the world. In order to determine what practices an individual is likely to follow at any given time, it is necessary to understand the individual's behavioral intention in a given circumstance. From an Information Technology perspective, a software development professional's belief systems are potentially the basis for the adoption and implementation of new and innovative work practices and processes. In this article, we explore the belief systems of software development professionals in order to understand the beliefs underlying intention and practice, and we seek answers about how they adopt or reject new and innovative software development processes and practices. The results point out a strong influence of past experiences, personality types, and repeated behavior on current software development processes and practices in industrial settings.     

Alternative Economics and Sustainable Future: Diverse Cultures/Beliefs/Values as Indispensable Factors

This article argues for a theoretical framework of alternative economics pertinent to Sustainable Development. The alternative economics requires an appropriate belief/value system based on a dynamic, sound and holistic society-specific culture (abbreviated as “Culture”). To represent the Culture-based belief/value system, a general framework for overarching Integral Harmony is introduced as an appropriate social value system for a paradigm shift toward sustainability. Such a social value system is now related to the value premises of the alternative economics. Then, the framework of alternative economics is explained in terms of basic theoretical construct that is simplified as a summary equation comprising value and real aspects. Finally, a typical working of the alternative economics is demonstrated diagrammatically as constant interactions of the value aspect and the real aspect (abbreviated as “Value-Real Interactions”).     

基于动态参数的按需可扩展地址分配算法

提出了一种基于动态参数的按需可扩展地址分配算法,根据分布式地址分配机制(DAAM)对16 bit地址空间进行分块,根据网络状况来动态调整参数以及进行地址一次或者多次扩展;同时改进路由算法,使其与Cluster-Tree协议兼容。仿真表明改进算法在地址分配成功率、平均分配耗时等方面优于DAAM以及它的改进方案EDAA-BA和RBAC。     

教育公共服务平台基础数据的采集与应用

基础数据是教育管理公共服务平台的核心与基础。提高基础数据的应用服务能力,数据采集是基础、数据整合是关键、数据安全是保障、智能分析是需要。结合云计算的应用,分析教育基础数据的组成、基础数据采集与应用中存在的问题与困难,探讨在教育云环境下,教育基础数据的采集与存储、交换与共享、应用与服务等过程中的挑战及其解决方案。     

多个水下机器人动态任务分配和路径规划的信度自组织算法

针对多个水下机器人(autonomous underwater vehicles,AUVs)动态任务分配和路径规划速度跳变问题,引入栅格信度函数概念,给出一种改进的栅格信度自组织(belief function self-organizing map,BFSOM)算法.目的是控制一组AUV有效地到达所有指定的目标位置,同时保证AUV能够自动的避开障碍物.首先,自组织神经网络(self-organizing map,SOM)算法对多AUV系统进行任务分配,使得每个目标位置都有一个AUV去访问.整个分配过程包括定义SOM神经网络的初始权值、获胜者选择、邻域函数的计算3个步骤;其次,根据栅格信度函数和环境信息更新SOM获胜神经元的权值,使得每个AUV在访问对应目标的过程中能够自动避障并且克服速度跳变,实现AUV自动有效路径规划.最后,通过仿真实验证明了本文提及算法的有效性.     

高效动态存储再分配方案与实现

为提高大小和数量都不确定的数据动态存储的空间利用率和处理速度,针对常规系统动态存储分配存在的问题,提出一种高效的动态存储再分配方案。通过减少系统动态存储分配的执行次数,在有效提高存储空间利用率的同时,提高存储空间动态分配的速度,给出动态存储再分配方案的具体实现算法,用实际数据对其性能进行测试。测试结果表明,该方案能节省36％至75％的系统存储空间,分配速度提高了20至50倍。     

深度信念网络在故障指示器检测中的应用

电子产品在生产过程中需进行产品检测,以故障指示器的检测为例,结合深度信念网络(DBN)技术实现了自动检测.深度信念网络由于其具有无监督预训练的优势,将其应用于实际系统,对现场的故障指示器视频图像的动作状态进行了分类实验.实验结果表明:深度信念网络分类算法相比于支持向量机(SVM)分类算法和BP分类算法有明显的优势,正确识别率达到了100％.该算法在产品检验的应用中满足生产测试的要求,且降低了人工测试的劳动强度,缓解了视觉疲劳问题.     

采用STRAIGHT模型和深度信念网络的语音转换方法

提出一种将STRAIGHT模型和深度信念网络DBN相结合实现语音转换的方式。首先,通过STRAIGHT模型提取出源说话人和目标说话人的语音频谱参数,用提取的频谱参数分别训练两个DBN得到语音高阶空间的个性特征信息;然后,用人工神经网络ANN将两个具有高阶特征的空间连接并进行特征转换;最后,用基于目标说话人数据训练出的DBN来对转换后的特征信息进行逆处理得到语音频谱参数,并用STRAIGHT模型合成具有目标说话人个性化特征的语音。实验结果表明,采用此种方式获得的语音转换效果要比传统的采用GMM实现语音转换更好,转换后的语音音质和相似度与目标语音更接近。