Modularizing product extension services: An approach based on modified service blueprint and fuzzy graph

This study aims at modularizing product-extension service (PES). PES is high-value service solution (e.g., repair, maintenance, and energy management) based on product to help manufacturers to achieve sustainable growth and profitability. Modularization can help to realize customization, increase in flexibility, reusability of service modules, and simplification of complex PES systems, etc. However, compared with tangible product, the modularization of product-extension service has rarely been dealt with, despite its potential benefits. More specifically, the question of how to identify service components and partition modules in the practical context is still an unexplored subject. Thus, this paper proposes a PES modularization approach based on modified service blueprint and fuzzy graph. The PES blueprint is firstly used to represent the whole PES scenario and identify all relevant service components. Then, fuzzy graph theory is utilized to module partition based on correlation analysis results of the service components. Finally, an exemplified modular design of compressor rotor service demonstrates the potential of the proposed method.     

面向规模化产品族的数值规划方法

基于功能、物理特性的相似性形成零件之间的关系矩阵;应用模拟退火算法对产品模块进行合理、有效地划分,通过对目标函数、模块数量的并行优化得出了最优的模块设计方案．结合典型实例验证了文中提出的算法具有良好的适应性,并且通过与其他几种优化算法比较说明了该算法具有一定的简便性;为面向大规模定制的模块化构建提供了另一种数值计算、评价途径．     

Modularizing services: A modified HoQ approach

Compared with manufacturing, the modularization of services has rarely been dealt with, despite its potential benefits. More specifically, the question of how to modularize services in the practical context is still an unexplored subject. In response, this paper proposes a solid framework for service modularization, by employing and modifying the House of Quality (HoQ) structure in Quality Function Deployment (QFD) using two ways: driver-based approach and interrelationship-based approach. Firstly, module drivers representing the service characteristics are identified through a comprehensive literature review. In this step, twofold module drivers are identified: one for common and the other for service-specific. Secondly, by considering the interdependent nature of service offering, service is decomposed according to the three predefined dimensions: service process, service outcome, and prerequisites for the service. Service modularization is then conducted using HoQ structure; the relationships between module drivers and decomposed service components are analyzed in the Strategic Modularability Matrix (SMM), whereas the interrelationships among service components are identified in Interrelated Components Modularability Matrix (ICMM). Finally, a clustering analysis is conducted to identify the module candidates. In order to illustrate the utility of the proposed approach, a restaurant service is exemplified. This study contributes to the field by filling the void left by the service sector by applying the service-specific module drivers to modularize services, as well as analyzing the relationship among service components using three interrelated dimensions.     

A Benders decomposition for the location-allocation and scheduling model in a healthcare system regarding robust optimization

The hospital location and service allocation is one of the most important aspects of healthcare systems. Due to lack of studies on covering location-allocation and scheduling problems with respect to the uncertain budget, this paper develops a bi-objective hybrid model to locate hospitals and allocate machines and services scheduled. The costs of establishing facilities are assumed to be uncertain, while a robust counterpart model is employed to overcome the uncertainty. Covering the demand of each service is limited as well. Moreover, hospitals have a limited space to the specialized equipment like CT scan and MRI machines, while there is a cost constraint on hospitals and the specialized equipment. The aim of this paper is to find a near-optimal solution including the number of hospitals and the specialized equipment, the location of hospitals, the assignment of demand of each service and the specialized equipment to hospitals, the determination of allowable number of each service of hospitals, the determination of demand that should be transferred from one hospital to another (patient transfer), and schedule services. As the proposed model, minimizing the total costs and the completion time of demand simultaneously, is an NP-hard problem, it is impossible to solve its large-scale version with exact methods in a reasonable time. Thus, a hybrid algorithm including simulated annealing optimization and the Benders decomposition is employed to solve it. The CPLEX optimizer verifies the presented algorithm to solve the proposed model. The sensitivity analysis is performed to validate the proposed robust model against of uncertain situations while the Monte Carlo simulation is used to analyze the quality and the robustness of solutions under uncertain situations. The results show that the uncertainty used in the proposed model properly formulates real-world situations compared to the deterministic case. Finally, the contributions and the future research are presented.

     

A learning-based module extraction method for object-oriented systems

Developers apply object-oriented (OO) design principles to produce modular, reusable software. Therefore, service-specific groups of related software classes called modules arise in OO systems. Extracting the modules is critical for better software comprehension, efficient architecture recovery, determination of service candidates to migrate legacy software to a service-oriented architecture, and transportation of such services to cloud-based distributed systems. In this study, we propose a novel approach to automatic module extraction to identify services in OO software systems. In our approach, first we create a weighted and directed graph of the software system in which vertices and edges represent the classes and their relations, respectively. Then, we apply a clustering algorithm over the graph to extract the modules. We calculate the weight of an edge by considering its probability of being within a module or between modules. To estimate these positional probabilities, we propose a machine-learning-based classification system that we train with data gathered from a real-world OO reference system. We have implemented an automatic module extraction tool and evaluated the proposed approach on several open-source and industrial projects. The experimental results show that the proposed approach generates highly accurate decompositions that are close to authoritative module structures and outperforms existing methods.     

A design method for an intelligent manufacturing and service system for rehabilitation assistive devices and special groups

The maturity of Industrial 4.0 technologies (smart wearable sensors, Internet of things [IoT], cloud computing, etc.) has facilitated the iteration and digitization of rehabilitation assistive devices (RADs) and the innovative development of intelligent manufacturing systems of RADs, expanding the value-added component of smart healthcare services. The intelligent manufacturing service mode, based on the concept of the product life cycle, completes the multi-source data production process analysis and the optimization of manufacturing, operation, and maintenance through intelligent industrial Internet of things and other means and improves the product life cycle management and operation mechanism. The smart product-service system (PSS) realizes the value-added of products by providing users with personalized products and value-added services, service efficiency, and sustainable development and gradually forms an Internet-product-service ecosystem. However, research on the PSS of RADs for special populations is relatively limited. Thus, this paper provides an overview of an IoT-based production model for RADs and a smart PSS-based development method of multimodal healthcare value-added services for special people. Taking the hand rehabilitation training devices for autistic children as a case, this paper verifies the effectiveness and availability of the proposed method. Compared with the traditional framework, the method used in this paper primarily helps evaluate rehabilitation efficacy, personalizes schemes for patients, provides auxiliary intelligent manufacturing service data and digital rehabilitation data for RAD manufacturers, and optimizes the product iteration development procedures by combining user-centered product interaction, multimodal evaluation, and value-added design. This study incorporates the iterative design of RADs into the process of smart PSS to provide some guidance to the RADs design manufacturers.     

带时间约束的Louvain算法在动态脑功能网络模块化中的应用研究#br#

针对在动态脑功能网络的模块化属性研究中,Louvain算法因过度追求模块度值最大化而导致的动态脑功能网络模块辨识度不高的问题,提出了一种带时间约束的Louvain算法。该算法以整个数据采集区间上的模块度值分布为依据构建迭代结束条件,以时间约束来达到模块在规模和数量上的均衡,从而保证模块划分更加合理。将本文算法用于静息态脑功能的模块划分实验时,对比结果显示,与原Louvain算法相比,带时间约束的Louvain算法能够得到更为合理的模块化结果,并可以观测到动态脑功能网络中小规模的模块结构。而采用本文算法用于健康人和自闭症患者的动态脑功能网络模块度对比实验,能够揭示两者在模块化上存在显著差别,从而验证了本文算法的有效性。     

A comprehensive framework for the evaluation of ontology modularization

The Semantic Web and ontologies have received increased attention in recent years. The delivery of well-designed ontologies enhances the effect of Semantic Web services, but building ontologies from scratch requires considerable time and effort. Modularizing ontologies and integrating ontology modules to a given context help users effectively develop ontologies and revitalize ontology dissemination. Therefore, various tools for modularizing ontologies have been developed. However, selecting an appropriate tool to fit a given context is difficult because the assumptions for the approaches greatly vary. Therefore, a suitable framework is required to compare and help screen the most suitable modularization tool.In this research, we propose a new evaluation framework for selecting an appropriate ontology modularization tool. We present three aspects of tool evaluation as the main dimensions for the assessment of modularization tools: tool performance, data performance, and usability.This study provides an implicit evaluation and an empirical analysis of three modularization tools. It also provides an evaluation method for ontology modularization, enabling ontology engineers to compare different modularization tools and easily choose an appropriate one for the production of qualifying ontology modules.The experimental results indicate that the proposed evaluation criteria for ontology modularization tools are valid and effective. This research provides a useful method for assessing and selecting ontology modularization tools. Modularization performance, data performance, and usability are the three modularization aspects designed and applied to the context of ontology. We provide a new focus on the comprehensive framework to evaluate the performance and usability of ontology modularization tools. The proposed framework should be of value to both ontology engineers, who are interested in ontology modularization, and to practitioners, who need information on how to evaluate and select a specific type of ontology tool in accordance with the requirements of the individual environment.     

基于网关的ZigBee网络与Internet互联框架

针对如何将ZigBee网络与Internet紧密融合的问题,提出一种网关设计方案.介绍了工作在传输层的互联网关,在分析此网关不足的基础上,根据面向服务的网络中间件思想,提议网关的体系结构.包括服务注册、服务绑定、服务调用和取消服务4个模块,以实现为用户提供服务的透明性;同时,为了减少ZigBee网络节点占用的IP地址数目,服务调用模块中使用传输层网关的协议转换方式.该网关从网络协议和服务两个角度实现ZigBee网络和Internet网络的互联,通过分析和比较证明具有用户透明性、业务提供方便等特点.     

动态服务组合构造与最优组合服务算法研究

服务组合是将已有服务组合为一个新服务的过程,以增加服务的功能或／和性能。本文将组合方案表示为一个有向无环图,节。占、表示服务,边表示服务交互,以目标服务的输入为指标集,给出候选组合方案的构造算法。以服务费用为测度,并计入服务的计算、存储和通信费用。通过费用转移,提出了基于经典Dijkstra算法的最优组合服务算法。     

An effective monitoring framework and user interface design

A distributed environment requires a monitoring system to oversee the operation of various distributed nodes. A monitoring service is crucial because it ensures a high‐quality computing environment and a reliable service. The interface and framework determine the effectiveness of a monitoring system. This paper uses the concept of user‐adaptive visualization to design its interface and proposes a flexible modular framework. Designers can use the proposed modular framework to flexibly extend existing modules, design visual interfaces to satisfy user requirements, and improve system failover schemes. The implementation of such a monitoring system for monitoring data preservation nodes is also provided. The system including fault‐tolerance and notification functions supports full monitoring services for Storage Resource Broker (SRB) or integrated Rule‐Oriented Data System (iRODS) based systems. The experimental results show that the proposed framework is suitable for data preservation services and is robust and responsive when faced with system failures. Copyright © 2014 John Wiley & Sons, Ltd.     

Research on Circular Area Search algorithm of multi-robot service based on SOA cloud platform

Considering autonomous mobile robots with a variety of specific functions as a kind of service, when there are many types and quantities of services and the density of regional services is large, proposing an algorithm of Circular Area Search (CAS) because of the problem of multi-robot service scheduling in various areas. Firstly, Django is used as the web framework to build the Service-Oriented Architecture (SOA) multi-robot service cloud platform, which is the basic platform for multi-service combination. Then, the service type, the latitude and longitude and the scoring parameters of the service are selected as the service search metrics to design the CAS algorithm that based on the existing service information registered in MySQL and the Gaode Map for screening optimal service, and then providing the service applicant with the best service. Finally, the service applicant applies for the self-driving tour service as an example to perform performance simulation test on the proposed CAS algorithm. The results show that the CAS algorithm of the multi-robot service cloud platform proposed in this paper is practical compared to the global search. And compared with the Greedy Algorithm experiment, the service search time is reduced about 58% compared with the Greedy Algorithm, which verifies the efficiency of CAS algorithm.     

Healthcare service configuration based on project scheduling

Configuration has been recognized as an effective methodology to provide high product variety that caters to individual customer’s needs in the manufacturing industry. For healthcare service configuration, this decision-making process can be taken as service package creation and treated analogously as a project, which is defined as a collection of tasks. This research develops a decision support model to integrate individual patients into the healthcare service configuration process. The healthcare service configuration is formulated as a Resource Constrained Project Scheduling Problem (RCPSP), and a bi-level optimization algorithm based on Genetic Algorithm (GA) is developed for problem solving. The methodology and algorithm are implemented with a case study based on the data obtained from a general hospital in Singapore, which has demonstrated the applicability of healthcare service configuration.     

基于RFID的单件生产实验系统的监控系统设计

采用面向对象的模块化方式对基于RFID的单件生产实验系统的上位机监控系统进行了设计,目的是通过对于该上位机监控系统的设计,能够对于生产过程进行实时控制和监控。为此通过多线程技术的应用实现了各模块的并发异步运行与通讯。文中给出了上位机与PLC通信模块,共享内存区服务模块及其访问模块,上位机与机械手控制程序通信模块,生产过程调度模块以及监控结果显示模块等5个模块的具体实现方法。系统运行良好,能够完成对整个生产过程的实时监控,证明了采用多线程技术确实可以很好地解决对于生产过程的实时控制和监控。     

Quality-of-service oriented web service composition algorithm and planning architecture

In the next few decades, it is expected that web services will proliferate, many web services will offer the same services, and the clients will demand more value added and informative services rather than those offered by single, isolated web services. As the result, the problem of synthesizing web services of high quality will be raised as a prominent issue. The clients will face the trouble of choosing or creating composition plans, among numerous possible plans, that satisfy their quality-of-service (QoS) requirements. Typical QoS properties associated with a web service are the execution cost and time, availability, successful execution rate, reputation, and usage frequency. In engineering perspective, generating the composition plan that fulfills a client’s QoS requirement is a time-consuming optimization problem. To resolve the problem in a timely manner, we propose a constraint satisfaction based web service composition algorithm that combines tabu search and simulated annealing meta-heuristics. As an implementation framework of the algorithm, we suggest a QoS-oriented web service composition planning architecture. The architecture maintains expert made composition schemas in a service category and assists the client as pure user to choose the one he/she wants to use. The main modules of the architecture are composition broker and execution plan optimizer. With the aid of the UDDI server, the composition broker discovers candidate outsourced web services for each atomic process of the selected schema and gathers QoS information on the web services. After that, the execution plan optimizer runs the web service composition algorithm in order to generate a QoS-oriented composition plan. The performance of the algorithm was tested in a simulated environment.     

Profiting from business process outsourcing

Companies have successfully used outsourcing for decades to generate savings and allow greater focus on core (essential) business. Outsourcing traditionally noncore (nonessential) yet critical functions to larger service providers is one of the fastest-growing changes in the market today. We refer to this process as business process outsourcing (BPO). Two significant market forces are driving this practice: a growing low-cost white-collar labor pool and automation and codification of best practices. Although the BPO market has been around for more than 40 years, it is only now reaching many companies' radar screens because of the better service levels and cost-savings promise. The two opportunities behind the recent growth of this sector - process modules and offshoring - show enormous promise, and companies musty use them in conjunction to show sustainable savings and, hence, long-term profitability. Future work in this area would involve understanding the definitions, costs, benefits, and risks associated with various service delivery models that service providers deploy, such as a global services delivery model that uses on-site, on-shore and offshore locations and a pure offshore services delivery model.     

基于流程树的BPEL4WS中流程服务动态优化方法*

针对服务流程建模语言BPEL4WS难以满足用户个性化需求也无法适应动态环境变化的问题,提出了一种动态优化BPEL4WS中流程服务的方法。该方法给出了一种Web服务交互代价计算模型,用来评价用户对Web服务的偏好程度以及实时环境下Web服务交互的现实代价。将BPEL4WS描述的服务组合流程转换为服务组合流程树,并借助领域本体对流程树节点进行语义检查,消除流程树中不合法的流程组合。通过深度优先遍历流程树,利用单亲遗传算法对流程服务进行优化组合。最后给出应用算例,并对用来优化组合流程服务的单亲遗传算法的适用性与     

较小动态服务组合代价GLRA算法的设计与实现

针对动态服务组合的关键是优化组合后的服务代价这一问题,论文提出了较小动态服务组合代价GLRA算法,该算法首先对服务组合进行建模,针对动态服务组合中的Candidate Service模型,抽取出有向无环图,并根据服务代价动态性特点,使用基于贪心的局部修正算法,该算法每次都从当前值选取最小值,迭代次数和服务深度有关,循环次数有限.仿真结果表明算法能够高效的找到代价较小的组合方案,具有更好的时间复杂度.     

Ontology driven interactive healthcare with wearable sensors

Ubiquitous healthcare is the service that offers health-related information and contents to users without any limitations of time and space. Especially, to offer customized services to users, the technology of acquiring context information of users in real time is the most important consideration. In this paper, we researched wearable sensors. We proposed the ontology driven interactive healthcare with wearable sensors (OdIH_WS) to achieve customized healthcare service. For this purpose, wearable-sensor-based smart-wear and methods of data acquisition and processing are being developed. The proposed system has potential value in healthcare. A smart wear using wearable sensors is fabricated as a way of non-tight and comfortable style fitting for the curves of the human body based on clothes to wear in daily life. The design sample of the smart wear uses basic stretch materials and is designed to sustain its wearable property. To offer related information, it establishes an environment-information-based healthcare ontology model needed for inference, and it is composed of inside-outside context information models depending on the users’ context. The modeling of the proposed system involved combinations of information streams, focusing on service context information. With the proposed service inference rules, customized information and contents could be drawn by the inference engine. In the established OdIH_WS, real-time health information monitoring was achieved. The results of system performance and users’ satisfaction evaluations confirmed that the proposed system is superior to other existing systems.