A multi-objective optimal approach to automated construction of sacrificial multi-piece molds

Sacrificial multi-piece molds can be used for producing complex parts. To obtain the optimal design of molds automatically, a multi-objective optimal approach is proposed. Mold pieces number, material utilization and partitioning area are taken as the objective functions, and the machinability of each mold piece is taken as constraint condition. Genetic algorithm (GA) is adopted to realize global optimization of partitioning process. Each mold piece in optimal scheme can be manufactured by milling and drilling operations, which reduce the tooling cost and shorten product cycle obviously. Using the proposed approach, mold design can be significantly automated for making complex parts.     

Keyword search encryption scheme resistant against keyword-guessing attack by the untrusted server

The user data stored in an untrusted server, such as the centralized data center or cloud computing server, may be dangerous of eavesdropping if the data format is a plaintext. However, the general ciphertext is difficult to search and thus limited for practical usage. The keyword search encryption is a helpful mechanism that provides a searchable ciphertext for some predefined keywords. The previous studies failed to consider the attack from the data storage server to guess the keyword. This kind of attack may cause some critical information revealed to the untrusted server. This paper proposes a new keyword search encryption model that can effectively resist the keyword-guessing attack performed by the untrusted data storage （testing） server. The testing （query） secret is divided into multiple shares so that the security can be guaranteed if the servers cannot conspire with each other to retrieve all shares of the secret.     

A data model applied to the knowledge-based ICAS

Image-guided computer aided surgery system (ICAS) contributes to safeness and success of surgery operations by means of displaying anatomical structures and showing correlative information to surgeons in the process of operation. Based on analysis of requirements for ICAS, a new concept of clinical knowledge-based ICAS was proposed. Designing a reasonable data structure model is essential for realizing this new concept. The traditional data structure is limited in expressing and reusing the clinical knowledge such as locating an anatomical object, topological relations of anatomical objects and correlative clinical attributes. A data structure model called mixed adjacency lists by octree-path-chain (MALOC) was outlined, which can combine patient's images with clinical knowledge, as well as efficiently locate the instrument and search the objects' information. The efficiency of data structures was analyzed and experimental results were given in comparison to other traditional data structures. The result of the nasal surgery experiment proves that MALOC is a proper model for clinical knowledge-based ICAS that has advantages in not only locating the operative instrument precisely but also proving surgeons with real-time operation-correlative information. It is shown that the clinical knowledge-based ICAS with MALOC model has advantages in terms of safety and success of surgical operations, and help in accurately locating the operative instrument and providing operation-correlative knowledge and information to surgeons in the process of operations.     

A Dynamic Job Scheduling Algorithm for Parallel System

One of the fundamental problems in parallel and distributed systems is deciding how to allocate jobs to processors. The goals of job scheduling in a parallel environment are to minimize the parallel execution time of a job and try to balance the user‘s desire with the system‘s desire. The users always want their jobs be completed as quickly as possible, while the system wants to service as many jobs as possible. In this paper, a dynamic job-scheduling algorithm was introduced. This algorithm tries to utilize the information of a practical system to allo-cate the jobs more evenly. The communication time between the processor and scheduler is overlapped with the computation time of the processor. So the communication overhead can he little. The principle of scheduling the job is based on the desirability of each processor. The scheduler would not allocate a new job to a processor that is already fully utilized. The execution efficiency of the system will he increased. This algorithm also can he reused in other complex algorithms.     

Secure and efficient digital rights management mechanisms with privacy protection

In the Internet or cloud computing environments, service providers provide more and more content services. Users can use these convenient content services in daily life. The major data of the user are maintained by the service providers except that some personal privacy data are stored at the client device. An attacker may try to invade the systems, and it will cause the damage of users and service providers. Also, users may lose their mobile devices and then it may cause the data disclosure problem. As a result, the data and privacy protection of users become an important issue in these environments. Besides, since many mobile devices are used in these environments, secure authentication and data protection methods must be efficient in these low resource environments. In this paper, we propose an efficient and privacy protection digital rights management （DRM） scheme that users can verify the valid service servers and the service servers can ensure the legal users. Since the key delegation center of the third party has the robust security protection, our proposed scheme stores the encrypted secret keys in the key delegation center. This approach not only can reduce the storage space of the user devices, but also can recover the encrypted secret keys in the key delegation center when a user loses her/his devices for solving the device losing problem.     

A bintree energy approach for colour image segmentation using adaptive channel selection

A new hierarchical approach called bintree energy segmentation was presented for color image segmentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images, from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the ＂best＂ channel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.     

Detecting the Resistivity Distribution of Carbon Fiber Reinforced Concrete by Electrical Resistance Tomography Method

According to the principle of electrical resistance tomography （ ERT）, the resistivity distribution of the carbon fiber reinforced concrete （CFRC） in the sensing field can be measured by injecting exciting current and measuring the voltage on the sensor electrode arrays installed on the surface of the object. Therefore, measurement of the resistivity distribution of CFRC is divided into first measuring the boundary conditions and then inversely computing the resistivity distribution. To reach this goal, an ERT system was constructed, which is composed of a sensor array unit, a data acquisition unit and an image reconstruction unit. Simulations of static ERT was performed on set-ups with many objects spread in a homogeneous background, and a simulation of dynamic ERT was also done on a rectangular board, the resistivity of which was changed within a small domain of it. Then, the resistivity distribution of a CFRC sample with a circlar hole as the target was detected by the ERT system. Simulation and experimental results show that the reconstructed ERT image reflects the resistivity distribution or the resistivity change of CFRC structure well. Especially, a small change in resistivity can be identified from the reconstructed images in the simulation of dynamic ERT images.     

Analytical Solution for Model-Based Dynamic Power Factor Measurement in AC Resistance Spot Welding

On the basis of welding transformer circuit model, a new measuring method was proposed. This method measures the peak angle of the welding current, and then calculates the dynamic power factor in each half-wave. An artificial neural network is trained and used to generate simulation data for the analytical solution, i.e. a high-order binary polynomial, which can be easily adopted to calculate the power factor online. The tailored sensing and computing system ensures that the method possesses a real-time computational capacity and satisfying accuracy. A DSP-based resistance spot welding monitoring system was developed to perform ANN computation. The experimental results suggest that this measuring method is feasible.     

Web Data Cube Construction in Multidimensional On-line Analytical Processing Environment

Introduction Using data warehousing and on-line analyticalprocessing (OLAP) technology, leaders of businessorganizations can gain insight into the global marketand make sound business decisions quickly to ensurethat the organization will excel in the ever…     

对多路数组聚集方法的研究及其优化

为了解决针对MOLAP服务器中的数据立方体的有效计算问题，对立方体全物化的多路数组聚集方法进行了研究与分析。在此基础上，提出了一种寻找最优聚集次序的方法，该方法克服了传统多路数组聚集需要计算所有扫描次序的缺陷，通过对各维数据的比较，找到一种特定的扫描方式，以方便、快捷地对以数据立方体形式存储于MOLAP服务器中的多维数据进行聚集操作，进而优化数据立方体的有效计算。     

开放式零件库TDB的一种实现方法

对零件库进行了介绍，主要研究了临时数据库(TDB)的功能，提出了在FORTRAN语言联编和UG／GRIP语言映射过程中，运用组结构实现TDB的功能，其具体操作是运用链表来实现对临时几何实体的操作，即实现临时几何实体的删除、组实体的转化等操作；将符合ISO13584．31标准的FORTRAN联编程序文件，通过用C语言编写的转换接口的编译，最终生成Unigraphics系统下的GRIP语言程序．     

社区卫生服务系统形式化规格说明

通过对社区卫生服务的功能需求出发,采用Z语言对系统规格进行了形式化说明,包括基础数据、系统状态以及系统操作等。采用形式化方法对社区卫生服务系统进行设计,能够得到一致的、精确的、简明的和无歧义的规格说明。     

Design and implementation of a data-driven dynamical reconfigurable cell array

The nature of dataflow computation demands the heavy flow of tokens amongst computation nodes. Traditional reduced instruction-set computer (RISC) processors are not suitable for such style computation. Devices that use long wire buses are not suitable for dataflow either. Reconfigurable computing devices (RCDs) consist of data transfer wires and computing resources. With minor modifications, reconfigurable cells can be adopted to perform dataflow computation. A reconfigurable cell array (RCA) is presented in this paper and it is suitable for dataflow computation. This cell array has a dynamic reconfigurable storage model. The distinctive features of the architecture include dataflow reconfigurable cells and reconfigurable storage. Dataflow applications can be mapped easily and effectively onto the cells. Reconfigurable storage is mainly used to manage data access and transmission. Furthermore, computation and data management are separated. Meanwhile, dynamical reconfiguration is accomplished, when some clusters of cells work in configuration mode and other clusters work in computation mode. The dataflow graphs of some algorithms are mapped onto our architecture, and the performance results are compared with those of CPU and GPU.     

基于启发性规则及关键路径调整的柔性作业调度优化算法

为克服传统进化算法求解较大型柔性作业调度问题计算时间长和结果不稳定的缺点,提出了一种启发性规则求解方法.该方法用一个启发性规则产生初始调度解,再利用一些启发式规则对初始调度过程中的关键工件及关键工序进行搜索,并对关键路径进行优化调整得到较优解,通过比较得到柔性调度问题的优化调度解.用本文方法对典型柔性调度问题进行求解,并与其他算法的求解结果进行比较,对于15×10问题,采用本文方法的计算结果与混合基因算法相同,计算时间为3.2 s,减少了42%;对于23×10及25×10的较大型问题,表明启发性规则的引入能提高求解效率,与传统进化算法相比,更适合求解较复杂的柔性作业调度问题.     

基于数据仓库和OLAP的民航灾害预警决策支持系统

为解决民航灾害预警管理中的多数据源和多目标决策的问题,构建了基于数据仓库和联机分析(OLAP)技术的民航灾害预警决策支持系统.该系统包括应用界面层、辅助决策功能层、库管理及接口层、信息库层和数据层。数据仓库的主题是航空公司、空管中心和机场的预警指标.设计了地域、机构、指标名称和时间4个维度,数据仓库雪花模型,以及年度、季度和月份3种粒度.数据仓库的分割方案是首先按地区维分割,再按机构维分割.#介绍了多维决策分析过程,包括切片、切块和旋转等操作.     

基于矩阵的多段支持度关联规则挖掘算法

为有效提高关联规则挖掘算法效率,提出了一种基于矩阵的多段支持度关联规则挖掘算法,该算法通过一次数据库扫描将事务数据存放在矩阵中,利用矩阵进行支持度的计算和频繁集的寻找,同时将项集支持度分段计算的思想应用其中,减少候选集生成,实验表明,算法效率得到了较大提高。     

背景知识在高职高专英语阅读教学中的应用

阅读是英语学习中一个重要的环节,传统英语阅读教学模式主要强调语言本身及其语法的作用,不注重读者及其背景知识。相关的图式理论和认知模式认为,学生的阅读效果会受其文化背景知识的影响。本文试图阐明文章背景知识介绍应用于高职高专英语阅读课堂教学中可以提高学生的阅读能力,更适合高职高专英语教学在新时代下的要求。     

英语阅读课多媒体教学模式探讨

多媒体在大学英语教学中的应用越来越广泛,然而在应用过程中出现了一些问题影响了教学效果。为了提高英语阅读课多媒体教学效果,本文通过教师访谈、学生问卷调查和随堂听课的方法来探索一个更有效的教学模式。研究结果表明交际法与多媒体结合的模式能调动学生的积极性,使英语学习朝自主学习的方向发展。