利用相对坐标轻松完成网格袋布局

网格袋布局管理器是java布局中最有用、最灵活、最复杂、最难掌握的一种布局管理嚣，实际上，如果我们明白了在布局时它利用了单元格相对坐标定位这一点，以及各个约束条件在布局中的作用．网格袋布局也会变得很轻松。     

一种自制的JAVA布局管理器

在Java中,加入到容器中的组件是需要进行版面布局的.而AWT提供了边界布局Borderayout、卡片布局Card-Layout、流线布局FlowLayout、栅格布局Grid-Layout、栅格袋布局GridBagLayout五种布局管理程序类,用户可以选择其一使组件以不同形式布局.然而在这五种布局管理器中,前四种的布局形式虽然简单,但版面格式单调;栅格袋布局具有很好的灵活性,可以实现一些很漂亮的布局,却存在着组件布局过程复杂的缺点.可喜的是,除了这些预定义的布局管理之外,Java还为用户提供了建立自已的布局管理器的灵活性,这就意味着给了用户一个自由布局的小天地,用户可     

浅谈Qt中的布局管理

Qt布局管理的目标是将放置于窗体中的每一个部件都给定一个合适的位置和大小,常用的有QHBoxLayout水平布局管理器、QVBoxLayout垂直布局管理器、QgridLayout网格布局管理器。Qt程序员在完成窗体界面设计时,可通过可视化的方法搭建界面并布局;也可以纯粹手工编写C＋＋源代码来实现界面设计,编码的方式更适合较复杂的布局。     

浅谈Qt中的布局管理

Qt布局管理的目标是将放置于窗体中的每一个部件都给定一个合适的位置和大小,常用的有QHBoxLayout水平布局管理器、QVBoxLayout垂直布局管理器、QgridLayout网格布局管理器。Qt程序员在完成窗体界面设计时,可通过可视化的方法搭建界面并布局;也可以纯粹手工编写C++源代码来实现界面设计,编码的方式更适合较复杂的布局。     

自行设计JAVA布局管理器

利用Java自由布局功能,本文自行设计了一种Java布局管理器,并与AWT现有的五种布局管理器作了比较。     

JavaAWT布局管理器使用技巧

JavaAWT中的布局管理器以及对在何时使用何种布局管理器进行了详细地介绍。     

一个应用于中文信息处理的网格系统的设计

介绍了目前中文信息处理研究的不足和网格技术的发展.为了扩大计算和存储的共享规模,并充分复用各类技术和研究,提出了将中文信息处理的应用利用网格技术来实现的方案.描述了一个应用于中文信息处理的网格系统的整体框架,该框架分为四层:顶部是一个Web门户,中间是中文信息处理网格管理器和网格中间件,最下面是网格节点.另外,还分析了负责资源管理和作业分配的CIPG管理器的设计方案.     

自动布局布线程序

功述描述了用于规划芯片的自动布局布线程序。其特点是在单元电路版图实现之前进行布局布线以及布线是在单元内部进行，不存在专门的布线通道。这种布图模式，以多端网连接模型作为布局布线的连接模型，并以布线均匀作为主要的目标函数。 整个程序模块分为矩阵网格规划和布局，总体布线，端口分配三部分。在布局中采用最小切割算法。初始布线以布线均匀，连线长度最短为目标，并采用一个基于布线均匀的“重心“算法。通过再布线和通     

Java多文档界面类库的设计和实现

随着Java编程语言的发展，基于Java的多文档界面桌面应用程序日益普及。简要总结了JFC中的多文档界面机制，包括桌面窗格、内部帧和桌面管理器，说明了JFC中的多文档界面与Windows环境下多文档界面的差别，最后介绍了利用卡片布局管理器设计和实现传统多文档界面类库的思想。     

标注自动布局的网格化方法

针对自动标注过程中普遍存在且较难解决的标注自动布局问题,提出一种网格化方法:对布局空间进行网格划分,并采用矩阵表达布局空间的状态,结合标注文本区域的网格划分,将标注布局问题简化为在状态矩阵中寻找符合某种条件的小块矩阵问题,该方法实现了标注位置的快速搜索,避免了大量的干涉处理,显著地提高了布局的效率和质量,并已经在商品化的三维CAD系统中得到应用.     

基于RSSI方法的井下人员定位系统原理与设计

提出了一种基于RSSI方法的井下人员定位系统的设计方案,阐述了井下巷道数学建模方法和人员定位基本原理,重点介绍了该井下人员定位系统的硬件和软件实现方案。该系统通过在井下关键点布置无线传感器测点获取井下工作人员的RSSI信息,实现了实时追踪定位功能。     

遗传算法在土地利用优化中的应用

城市土地利用优化是从社会的长远与整体利益的角度,来规范一定时段内城市土地利用的结构、布局和方式,是一个典型的多目标优化问题.本文利用遗传算法的全局优化搜索能力,构建了一个城市土地利用的优化模型.该模型采用与土地利用现状图相对应的二维矩阵编码,利用层次分析法构建了顾及土地功能协调性、土地比例协调性、人口、交通4个方面的多目标适应度函数.应用该模型对某城市的城市土地利用空间结构进行了优化配置.结果表明,该模型能够反映城市土地利用的客观规律,优化后的方案能很好地符合城市规划上的各种需要.     

The Semantics of "Semantics"

Outside of computer science, semantics is the providence of philosophy, where we talk about what we mean when we talk, as well as ontology (what there is to know) and epistemology (how we know it). The nice thing about computer science is that, in contrast to philosophy, we can establish whether different representations make a computational difference. That's what makes what we do engineering/science. In this paper, the author distinguished the meaning of semantics (in programming) from ontologies and logics.     

Reasoning about reasoning in a meta-level architecture

In this paper we discuss reasoning about reasoning in a multiple agent scenario. We consider agents that are perfect reasoners, loyal, and that can take advantage of both the knowledge and ignorance of other agents. The knowledge representation formalism we use is (full) first order predicate calculus, where different agents are represented by different theories, and reasoning about reasoning is realized via a meta-level representation of knowledge and reasoning. The framework we provide is pretty general: we illustrate it by showing a machine checked solution to the three wisemen puzzle. The agents' knowledge is organized into units: the agent's own knowledge about the world and its knowledge about other agents are units containing object-level knowledge; a unit containing meta-level knowledge embodies the reasoning about reasoning and realizes the link among units. In the paper we illustrate the meta-level architecture we propose for problem solving in a multi-agent scenario; we discuss our approach in relation to the modal one and we compare it with other meta-level architectures based on logic. Finally, we look at a class of applications that can be effectively modeled by exploiting the meta-level approach to reasoning about knowledge and reasoning.     

The role of big data and cognitive computing in the learning process

In this paper, we investigate how the raise of big data and cognitive computing systems is going to redesign the labor market, also impacting on the learning processes. In this respect, we make reference to higher education and we depict a model of a smart university, which relies on the concepts that are at the basis of the novel smart-cities’ development trends. Thus, we regard education as a process so that we can find specific issues to solve to overcome existing criticisms, and provide some suggestions on how to enhance universities’ performances. We highlight inputs, outputs, and dependencies in a block diagram, and we propose a solution built on a new paradigm called smarter-university, in which knowledge grows rapidly, is easy to share, and is regarded as a common heritage of both teachers and students. Among the others, a paramount consequence is that there is a growing demand for competences and skills that recall the so called T-shape model and we observe that this is pushing the education system to include a blend of disciplines in the curriculums of their courses. In this overview, among the wide variety of recent innovations, we focus our attention on cognitive computing systems and on the exploitation of big data, that we expect to further accelerate the refurbishment process of the key components of the knowledge society and universities as well.     

Optimal location policy for three competitive facilities

Competitive facility location problems have been investigated in many papers. In most, authors have applied location models with two competitors. In this paper three companies, which are mutually competitive, intend to locate their facilities in a linear market. It is well-known that Nash equilibrium solution for location problem does not include three competitive facilities. In this paper we present the optimal location strategies for three facilities. In our model we assume that the demands are continuously distributed in a linear market and the facilities are locating according to a specific order of sequence, A, B and C. We apply the Stackelberg equilibrium solutions for competitive location problems with three facilities. In our model, we consider the decision problems in three stages. In the first stage, we decide the optimal location of facility A, which is located optimally in respect to the remaining two facilities B and C. In the second stage, we determine the optimal location of facility B which is optimally located in respect to facility C, by utilizing the information on the location of facility A. Finally in the third stage problem we decide the location of facility C, optimally located by utilizing the information on the location of A and B. In the first stage, we need the optimal solutions of the second and third stages. In the second stage we need the optimal solution of the third stage problem. Therefore, first we solve the third stage problem which is the simplest. After that, we solve the second stage problem utilizing the optimal solution strategy of the third stage problem. In this paper we present the optimal location strategies for three facilities.     

一个基于特征的图象变形算法

首先对图象变形算法的研究作了一个简要的概述，然后结合我们目前所进行的智能动画系统的开发工作，提出了一个图象空间中基于特征的变形算法。在文中第二节较为详细地介绍了该算法中所用到的散乱点插值算法，最后给邮了该变形算法的详细描述。