物件

An object-oriented Petri Net will be built to model a flexible manufacturing cell. This cell includes a robot, three machines and a WIP buffer. The job enters the cell once the job volume is under capacity limit, therefore adynamic scheduling system is required to schedule operations for jobs in the cell. An algorithm will be developed for the scheduling system, which considers job's makespan as criteria.

在研究中，采用物件导向裴氏图模式，架构一个阶层式之弹性制造系统，其中包含机器群组主电脑物件、机器电脑物件以及机器手臂电脑物件，并规划系统的动态进出排程，以工作总完工时间为绩效评估指标来发展演算法，接著建立eM-Plant的模拟系统，以资料库建立之工件加工档，进行动态排程及模拟。

You can align objects vertically along the right edge, center, or left edge of the selected objects, or horizontally along the top edge, center, or bottom edge of the selected objects.

排成一排镶板使你能把沿着水平面或者垂直轴有选择的物件排成一排你能把垂直地沿着正确边缘，中心或者有选择的物件的左边边缘或者水平沿着最高边缘，中心或者有选择的物件的最底下边缘物件排成一排。

The Align panel enables you to align selected objects along the horizontal or vertical axis. You can align objects vertically along the right edge, center, or left edge of the selected objects, or horizontally along the top edge, center, or bottom edge of the selected objects.

排成一排镶板使你能把沿着水平面或者垂直轴有选择的物件排成一排你能把垂直地沿着正确边缘，中心或者有选择的物件的左边边缘或者水平沿着最高边缘，中心或者有选择的物件的最底下边缘物件排成一排。

The binary + operator performs string concatenation when one or both operands are of type string. If an operand of string concatenation is null, an empty string is substituted. Otherwise, any non-string argument is converted to its string representation by invoking the virtual ToString method inherited from type object.

由此可知 C#的加号运算子预设就支援字串串加的功能，只要一群字串串接的物件中只要有一个以上的物件型别是「字串」的话，就会全部变成「字串相加」，只要遇到「非字串」的物件，预设会使用继承至 object 物件的 ToString 方法进行转型，让所有物件都变成「字串」后进行相加动作。

In this thesis, we apply Coulomb's law and propose an external force to overcome the problem of traditional ACM that can not capture the cavities of an object. Assume that each node of a snake has its own electric charge, and the object boundary has opposite electric charge. Then object boundary will attract the nodes of the snake. This helps the contour easily to move to the object boundary.

本论文中，我们运用库仑定律的观念，提出了一个运用局部引力作为外力的方法，用以克服传统主动性轮廓模型在凹面处收敛不佳的缺点；假设物件边界带电，而主动性轮廓模型的结点带与物件边界相异之电荷，则物件边界会吸引著主动性轮廓模型各结点，使得模型曲线更容易靠近物件边界。

For the runtime system, objects can be allocated on demand by programmers, but there is no way that one can explicitly deallocate objects on the heap.

对Java执行时期而言，物件是依程式员的需求来配置，但是Java并没有提供任何方式来让程式员自行清除已配置的物件。

The best solution should be finding an effective method and technique to preserve digital objects in order to maintain the factuality and accuracy of digital objects.

解决之道应是找出有效的数位物件保存方法与技术，得以维持数位物件的真实性与正确性。

You can link any object or attachment to the parent object, no longer need to merge the object.

您可以附著或连结任何物件至父物件，不再需要合并物件。

The distance between the reactive sensor node and the target node is estimated by using the value of RSSI, since the strength of radiation signal and the square of distance is inversely proportional. We proposed a method to derive the position of the target node based on the theory of radical center. With data from three reactive nodes, the position of target node can be analytically estimated.

我们以讯号强度指标来推估节点与被追踪物件的距离，并利用圆之根轴的几何特性，提出一个位置的估算方法，可以简单地利用三个感测节点所回传的资讯计算出被追踪物件的位置，所提出的方法即使在距离值有误差的情况下，依然能够估算出被追踪物件的唯一位置。

Most of the e-learning research topics focus on metadata of learning object. These studies extract useful information from metadata, and use them to organize the LOs. However, to understand the metadata is not enough to organize the multimedia-style LO in meaningful manner. The comprehensive multimedia-style LO is especially useful for mobile learners to choose what they really demanded. In order to attack the problem, this project uses multi-agent technique to develop a personalized hyper-seamless learning environment for managing LOs comprehensibly. Following that, the proposed environment coordinates two agents: Content Reorganize Agent, and Zone Agent to provide mobile learners the efficient multimedia-style learning experience. The CRA is responsible for reorganizing the discovered critical multimedia content by analyzing learner』s behavior and the multimedia』s annotation. The ZA is designed for terminal devices to monitor the learning behavior, and it sends the collected behaviors to CRA for evaluating. Moreover, the ZAs can communicate with each other, and they can self-organize as a group for sharing learning resources. Due to the cooperation of the two agents, the learning environment can give the properly multimedia-style LO for learners without bandwidth squandering. Finally, we expect this project can construct a comprehensive multimedia-style LO map for efficient personalized seamless learning.

中文摘要大多数的数位学习研究著重於如何利用学习物件的Metadata来组织管理学习物件，然而只透过Metadata仍旧无法有效管理多媒体形态之学习物件，多媒体学习物件的内容若能被了解，则学习者能正确的选择所需的学习内容，尤其是行动学习，能正确选择行动内容不但能减少频宽的浪费，亦能有效利用行动装置有限的资源，有鉴於此，本研究计画拟利用多重代理人机制发展个人化超无缝学习环境来管理内容可被理解之多媒体形态学习物件，在超无缝学习环境中Content Reorganize Agent 与Zone Agent 这两支代理人程式负责协调作业以提供高品质之行动学习经验，其中CRA所负责的工作为分析学习行为与学习物件之注解找出多媒体关键内容来重组具备学习主题之多媒体学习内容，而ZA为安装於学习装置端的代理人程式，其负责监督学生在学习过程中产生的行为，并将该资讯传回CRA以供分析，此外ZA与ZA之间具备自我群聚组织的能力，同一群组下的ZA可彼此共享所需的学习资源，透过CRA与ZA的合作，个人化超无缝学习环境能在不浪费网路频宽的前提下，提供正确且合适的多媒体学习物件给行动学习者，最后我们预期透过本计画的执行能够建立具备内容理解能力之学习物件模型，并利用此模型提供有效率的个人化无缝学习。

On the other hand, the more important thing is because the urban housing is a kind of heterogeneity products.

另一方面，更重要的是由于城市住房是一种异质性产品。

Climate histogram is the fall that collects place measure calm value, cent serves as cross axle for a few equal interval, the area that the frequency that the value appears according to place is accumulated and becomes will be determined inside each interval, discharge the graph that rise with post, also be called histogram.

气候直方图是将所收集的降水量测定值，分为几个相等的区间作为横轴，并将各区间内所测定值依所出现的次数累积而成的面积，用柱子排起来的图形，也叫做柱状图。