A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies

The implementation of enterprise resource planning (ERP) is a complex process, and the failure rate remains very high. The literature has reported over 80 critical success factors for ERP implementation, but companies typically do not know to exploit them. In this article, a step-by-step assessment and improvement method for ERP implementation is proposed and applied in three companies. First, a five-stage ERP implementation model is proposed. Second, about 80 critical success factors (CSFs) from the literature are elaborated into key performance indices (KPIs), which are associated with each stage of ERP implementation by ten local ERP experts. Third, the weights of the KPIs are calculated using the Dumpster–Shafer method and the evaluation of ten experts. During the implementation process, performance is measured at each stage and remedial actions are identified if the performance is below expectation. An implementation flowchart is developed based on a five-stage model and the philosophy of continuous improvement. Three action cases in Chinese manufacturing companies are conducted to illustrate the effects of the assessment model, which is also currently being used by a consulting company specialising in ERP implementation. With further evaluation by local experts, the model has the potential to serve as a guideline for ERP implementation in other countries.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Goal-oriented dynamic test generation

ContextMemory safety errors such as buffer overflow vulnerabilities are one of the most serious classes of security threats. Detecting and removing such security errors are important tasks of software testing for improving the quality and reliability of software in practice.ObjectiveThis paper presents a goal-oriented testing approach for effectively and efficiently exploring security vulnerability errors. A goal is a potential safety violation and the testing approach is to automatically generate test inputs to uncover the violation.MethodWe use type inference analysis to diagnose potential safety violations and dynamic symbolic execution to perform test input generation. A major challenge facing dynamic symbolic execution in such application is the combinatorial explosion of the path space. To address this fundamental scalability issue, we employ data dependence analysis to identify a root cause leading to the execution of the goal and propose a path exploration algorithm to guide dynamic symbolic execution for effectively discovering the goal.ResultsTo evaluate the effectiveness of our proposed approach, we conducted experiments against 23 buffer overflow vulnerabilities. We observed a significant improvement of our proposed algorithm over two widely adopted search algorithms. Specifically, our algorithm discovered security vulnerability errors within a matter of a few seconds, whereas the two baseline algorithms failed even after 30 min of testing on a number of test subjects.ConclusionThe experimental results highlight the potential of utilizing data dependence analysis to address the combinatorial path space explosion issue faced by dynamic symbolic execution for effective security testing.     

A prediction-based dynamic file assignment strategy for parallel file systems

Nowadays, the rapid development of the internet calls for a high performance file system, and a lot of efforts have already been devoted to the issue of assigning nonpartitioned files in a parallel file system with the aim of pursuing a prompt response to requests. Yet most of the existing strategies still fail to bring about an optimal performance on system mean response time metrics, and new strategies which can achieve better performance in terms of mean response time become indispensable for parallel file systems. This paper, while addressing the issue of assigning nonpartitioned files in parallel file systems where the file accesses exhibit Poisson arrival rates and fixed service times, presents an on-line file assignment strategy, named prediction-based dynamic file assignment (PDFA), to minimize the mean response time among disks under different workload conditions, and a comparison of the PDFA with the well-known file assignment algorithms, such as HP and SOR. Comprehensive experimental results show that PDFA is able to improve the performance consistently in terms of mean response time among all algorithms for comparison.     

基于DSP的电子行走辅助系统的设计与实现

为帮助视障者独立行走，基于DSP设计一套电子行走辅助系统。介绍系统的功能和基本结构，详细描述各模块的硬件设计和系统软件工作流程。该系统以实时图像处理为基础，能够完全脱离 PC机实现视频图像的采集、处理和语音提示等功能，帮助视障碍者独立行走。该系统具有小巧、便携、使用方便的特点，与传统助盲设备相比提高了导盲精度，与大型电子盲道或全球定位系统相比节省了成本，实验验证了其有效性。     

控规"心结"之解

法定的控规在执行过程中屡遭调整,困扰着规划师.这是由于编制控规的"时间差"、"批零差"、"计划/市场契合"等问题导致.依据法理,创新编制控规的新机制,发挥政府主导,各利益相关者多方参与是解因之道.     

裂解态正癸烷点火延迟时间的理论研究（英）

在先进飞行器发动机中,吸热碳氢燃料在进入燃烧室之前会发生热裂解反应,生成未反应燃料和小分子裂解产物的混合物(称为裂解态燃料)。本工作研究了在1300~1800 K、0.1~3.0 MPa和当量比为1.0的条件下,不同的裂解转化率、裂解压力、点火压力和自由基对正癸烷裂解着火特性的影响。通过采用一种精确的组合机理,从理论上计算了流动反应器中3.0和5.0 MPa下正癸烷裂解组分,与文献中的实验结果吻合较好。结果表明,正癸烷在3 MPa和5 MPa下裂解的出口转化率分别为46.2%和58.8%,裂解产物分布一致,但乙烯的含量随着压力的升高明显的降低,而烷烃含量随着压力的增大而增加。尽管自由基总体含量很低,但在3 MPa条件下裂解产物中的自由基浓度依然高于5 MPa条件下。对于点火延迟时间的计算结果则表明,裂解态正癸烷的点火延迟时间随着转化率的增大而延长,且在5 MPa下随着转化率的变化更明显。相同转化率下,5 MPa下的裂解态正癸烷的点火延迟时间比3 MPa下更短。此外,与无自由基的裂解正癸烷相比,裂解正癸烷中自由基的存在可以加速着火过程,转化率小于40%时,着火延迟时间缩短15%以上。     

Quantile regression on the nonlinear relationship between land use and trip time

This study conceptually confirms and empirically tests the potential that the significance and magnitude of the compact land use–trip time relationship differ by the degree of compactness and trip time. Based on a quantile regression of about 25,000 commuters in Seoul, Korea, the empirical analysis suggests a significant level for each neighbourhood land use variable and a magnitude change within the level. Weekend trip and school densities are significant for shorter trip time commuters, population density is significant for longer trip time commuters, and pedestrian density is significant for all commuters. Wherever significant, the land use variables exert stronger effects as their values increase.     

Parameter identification for Wiener-finite impulse response system with output data of missing completely at random mechanism and time delay

In this paper, the parameter estimation issue of Wiener system with random time delay and missing output data is studied. The linear part of Wiener system is described by Finite Impulse Response (FIR) model. The mathematical formula of the Expectation Maximum algorithm to identify Wiener-FIR system that contains the random time delay and the nonlinear output data in missing completely at random mechanism is derived, which is never considered before. To obtain the unmeasurable intermediate variable in Wiener-FIR system, the idea of auxiliary model is adopted. The time delay and system parameters can be estimated simultaneously by this method. Numerical example and the identification of water tank system example are carried out, the effectiveness of the algorithm is proved.