A three-loop model-following control structure: theory and implementation

This article presents a novel three-loop control system, which supplements control structures known from the literature as model following control (MFC). The major advantage of the proposed system is its high robustness to process parameter variations; it is much higher than that offered by single-loop or two-loop control systems. Features of the new structure are revealed by a theoretical analysis that has been carried out from the viewpoint of requirements for a force/pose controller of a Stäubli RX60 manipulator. This article shows how the proposed control structure responds to such strong process parameter variations and makes a comparison to results yielded by single-loop control structures.     

Segmentation of unsorted cloud of points data from full field optical measurement for metrological validation

Modern industry requires the increase of quality of manufactured products with the simultaneous minimization of production time and cost. Therefore the development of faster, more precise measurement techniques is needed. There are many full field optical systems in use that offer multi directional measurement that meet these requirements. The raw output measurement data from these systems is in the form of unsorted clouds of points which may include millions of measurement points. This data has a different structure than data acquired by traditional contact methods. In addition phenomena connected with optical measurement such as reflection and occlusion result in various errors in the obtained cloud. Therefore a new method of analysis has to be developed to process the data and prepare it for metrological verification. This article presents an algorithm to manage measured data from full field optical systems. This includes segmentation of clouds of points so that each point is associated with its corresponding surface of the CAD model and then exported to certified metrological software for analysis.     

Improving the security level of the FUSION@ multi-agent architecture

The use of architectures based on services and multi-agent systems has become an increasingly important part of the solution set used for the development of distributed systems. Nevertheless, these models pose a variety of problems with regards to security. This article presents the Adaptive Intrusion Detection Multi-agent System (AIDeMaS), a mechanism that has been designed to detect and block malicious SOAP messages within distributed systems built by service based architectures. AIDeMaS has been implemented as part of FUSION@, a multi-agent architecture that facilitates the integration of distributed services and applications to optimize the construction of highly-dynamic multi-agent systems. One of the main features of AIDeMaS is that is employs case-based reasoning mechanisms, which provide it with great learning and adaptation capabilities that can be used for classifying SOAP messages. This research presents a case study that uses the ALZ-MAS system, a multi-agent system built around FUSION@, in order to confirm the effectiveness of AIDeMaS. The preliminary results are presented in this paper.     

基于Hadoop集群的日志分析系统的设计与实现

当前Internet上存在着海量的日志数据,他们中蕴藏着大量可用的信息。对海量数据的存储和分析都是一个艰巨而复杂的任务,单一主机已经无法满足要求,使用分布式存储和分布式计算来分析数据已经成为了必然的趋势。分布式计算框架Hadoop已经日趋成熟,被广泛的应用于很多领域。该文描述了一个针对大日志分析的分布式集群的构建与实现过程。介绍了日志分析的现状,使用vmware虚拟机搭建了Hadoop集群和日志分析系统的构建方法,并对实验结果进行了分析。     

Case-based reasoning for interpretation of data from non-destructive testing

Non-destructive testing (NDT) is a name for a range of methods and procedures used to determine fitness of industrial products for further use. The use of NDT testing techniques results in data in the form of signals, images, or sequences of these, which have to be analysed in order to determine if they contain any indications of defects in the inspected objects. This analysis is often quite complex. In the past, systems have been built which used neural networks (and other statistical classifiers) as well as expert systems to interpret NDT data; however, successful uses of these systems in inspection practice are rare. This article presents how the case-based reasoning methodology (where interpretation of new data is based on previous data-interpretation cases) can be used to tackle the problem of NDT data interpretation. The article presents the characteristics of CBR, which make it an interesting alternative to statistical classifiers and to expert systems. Suitability of CBR for NDT data interpretation is illustrated based on examples of two applications: a CBR system for ultrasonic rail inspection and a CBR system for eddy-current inspection of heat exchangers.     

Semi-Automated,Large-Scale Evaluation of Public Displays

This article presents a scalable, semi-automated process for studying the usage of public displays. The process consists of gathering anonymous interaction and skeletal data of passersby during public display deployment and programmatically analyzing the data. This article demonstrates the use of the process with the analysis of the Information Wall, a gesture-controlled public information display. Information Wall was deployed in a university campus for one year and collected an extensive data set of more than 100 000 passersby. The main benefits of the process include (1) gathering of large data sets without considerable use of resources, (2) fast, semi-automated data analysis, and (3) applicability to studying the effects of long-term public display deployments. In analyzing the usage and passersby data of the Information Wall in our validation study, the main findings uncovered using the method were (i) most users were first-time users exploring the system, and not many returned to use the system again, and (ii) many users were accompanied by passive users who observed interaction from further away, which could suggest a case of multi-user interaction blindness. In the past, logged data has mainly been used as a supporting method for in situ observations and interviews, and its use has required a considerable amount of manual work. In this article, we argue that logged data analysis can be automated to complement other methods, particularly in the evaluation of long-term deployments.     

Negotiating the Semantics of Agent Communication Languages

This article presents a formal framework and outlines a method that autonomous agents can use to negotiate the semantics of their communication language at run–time. Such an ability is needed in open multi–agent systems so that agents can ensure they understand the implications of the utterances that are being made and so that they can tailor the meaning of the primitives to best fit their prevailing circumstances. To this end, the semantic space framework provides a systematic means of classifying the primitives along multiple relevant dimensions. This classification can then be used by the agents to structure their negotiation (or semantic fixing ) process so that they converge to the mutually agreeable semantics that are necessary for coherent social interactions.     

Floridi's informational structural realist basis for info-computational modelling of cognizing agents

Informational structural realism, ISR (Floridi, 2008a), describes the reality as a complex informational structure for an epistemic agent interacting with the universe by the exchange of data as constraining affordances. In conjunction with naturalist computationalism – the view that the dynamics of the nature can be understood as computation – Floridi's ISR presents a basis for the construction of the unified framework of info-computationalism. In this framework, the fundamental mechanism of all natural computation is morphological computation, expressed as a process of information self-organisation, with information structure understood in the sense of Floridi's ISR. Recently, in robotics, morphological computing has been used for decentralised embodied control of robots. In this article, we describe how appropriate body morphology saves information-processing (computation) resources as well as enables learning through self-structuring of information in an epistemic, cognizing agent.     

A cloud approach to unified lifecycle data management in architecture,engineering, construction and facilities management: Integrating BIMs and SNS

The problem of data integration throughout the lifecycle of a construction project among multiple collaborative enterprises remains unsolved due to the dynamics and fragmented nature of the construction industry. This study presents a novel cloud approach that, focusing on China’s special construction requirements, proposes a series of as-built BIM (building information modeling) tools and a self-organised application model that correlates project engineering data and project management data through a seamless BIM and BSNS (business social networking services) federation. To achieve a logically centralised single-source data structure, a unified data model is constructed that integrates two categories of heterogeneous databases through the adoption of handlers. Based on these models, key technical mechanisms that are critical to the successful management of large amounts of data are proposed and implemented, including permission, data manipulation and file version control. Specifically, a dynamic Generalised List series is proposed to address the sophisticated construction file versioning issue. The proposed cloud has been successfully used in real applications in China. This research work can enable data sharing not only by individuals and project teams but also by enterprises in a consistent and sustainable way throughout the life of a construction project. This system will reduce costs for construction firms by providing effective and efficient means and guides to complex project management, and by facilitating the conversion of project data into enterprise-owned properties.     

Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction

This work presents a system for automatically evaluating the interaction that exists between the atmosphere and the ocean’s surface. Monitoring and evaluating the ocean’s carbon exchange process is a function that requires working with a great amount of data: satellite images and in situ vessel’s data. The system presented in this study focuses on computational intelligence. The study presents an intelligent system based on the use of case-based reasoning (CBR) systems and offers a distributed model for such an interaction. Moreover, the system takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve over time. In order to resolve this problem, an intelligent environment has been developed, based on the use of CBR systems, which are capable of handling several goals, by constructing plans from the data obtained through satellite images and research vessels, acquiring knowledge and adapting to environmental changes. The artificial intelligence system has been successfully tested in the North Atlantic Ocean, and the results obtained will be presented in this study.     

A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence

Digital twins and artificial intelligence have shown promise for improving the robustness, responsiveness, and productivity of industrial systems. However, traditional digital twin approaches are often only employed to augment single, static systems to optimise a particular process. This article presents a paradigm for combining digital twins and modular artificial intelligence algorithms to dynamically reconfigure manufacturing systems, including the layout, process parameters, and operation times of numerous assets to allow system decision-making in response to changing customer or market needs. A knowledge graph has been used as the enabler for this system-level decision-making. A simulation environment has been constructed to replicate the manufacturing process, with the example here of an industrial robotic manufacturing cell. The simulation environment is connected to a data pipeline and an application programming interface to assist the integration of multiple artificial intelligence methods. These methods are used to improve system decision-making and optimise the configuration of a manufacturing system to maximise user-selectable key performance indicators. In contrast to previous research, this framework incorporates artificial intelligence for decision-making and production line optimisation to provide a framework that can be used for a wide variety of manufacturing applications. The framework has been applied and validated in a real use case, with the automatic reconfiguration resulting in a process time improvement of approximately 10%.     

Web数据提取与发布工具的设计与实现

介绍一个Web数据提取与发布工具,内容包括系统结构、功能设计、数据组织、界面设计和实现技术。该工具已用于多个部门信息网站建设和信息系统开发之中。     

Information system development activities and inquiring systems: an integrating framework

This article presents a framework that maps information system development (ISD) activities on systems for the creation of knowledge. This work addresses the relevant and persisting problem of improving the chances of ISD success. The article builds upon previous research on knowledge aspects of ISD, abandoning the idea of a monolithic approach to knowledge and presenting a pluralistic approach based on the idea that different inquiring systems can support micro-level ISD activities. The article is divided into two parts. The first part presents the theoretical development of the framework based on ISD literature and on Churchman's (1971) inquiring systems. The second part presents the use of the framework in an ISD project. The case is used to show the applicability of the framework and to highlight the advantages of this approach. The main theoretical implication is that the framework provides a new way to see the development of a system in terms of the knowledge created in the process. The main practical implication of the framework is that it improves the managers' ability to guide ISD activities as knowledge activities embedded in a knowledge process, a crucial element in development projects.     

Bayesian computation for geometric process in maintenance problems

Geometric process modeling is a useful tool to study repairable deteriorating systems in maintenance problems. This model has been used in a variety of situations such as the determination of the optimal replacement policy and the optimal inspection-repair-replacement policy for standby systems, and the analysis of data with trend. In this article, Bayesian inference for the geometric process with several popular life distributions, for instance, the exponential distribution and the lognormal distribution, are studied. The Gibbs sampler and the Metropolis algorithm are used to compute the Bayes estimators of the parameters in the geometric process. Simulation results are presented to illustrate the use of our procedures.     

An integrated data collection and analysis framework for remote monitoring and planning of construction operations

Recent advances in data collection and operations analysis techniques have facilitated the process of designing, analyzing, planning, and controlling of engineering processes. Mathematical tools such as graphical models, scheduling techniques, operations research, and simulation have enabled engineers to create models that represent activities, resources, and the environment under which a project is taking place. Traditionally, most simulation paradigms use static or historical data to create computer interpretable representations of real engineering systems. The suitability of this approach for modeling construction operations, however, has always been a challenge since most construction projects are unique in nature as every project is different in design, specifications, methods, and standards. Due to the dynamic nature and complexity of most construction operations, there is a significant need for a methodology that combines the capabilities of traditional modeling of engineering systems and real time field data collection. This paper presents the requirements and applicability of a data-driven modeling framework capable of collecting and manipulating real time field data from construction equipment, creating dynamic 3D visualizations of ongoing engineering activities, and updating the contents of a discrete event simulation model representing the real engineering system. The developed framework can be adopted for use by project decision-makers for short-term project planning and control since the resulting simulation and visualization are completely based on the latest status of project entities.     

Guidance on Design of Internet-based Process Control Systems

Internet-based process control is becoming new generations of control systems, in which the Internet is used as a platform for global remote monitoring and control. The obvious benefit is to enable global collaboration between operators from geographically dispersed locations, data sharing and data provision for remote monitoring and control. However, connection to an open network and the use of universal technology present new problems that did not exist with the conventional design and construction of control systems, such as time delay and data loss in Internet transmission and security. This paper reviews the latest research results and presents design guidance of Internet based monitoring and control systems.     

大型城市一卡通系统线上应用方案

随着我国的信息化事业的迅猛发展,以Internet技术为基础的计算机网络已成为人们生活中最重要的基础设施之一,与此同时,智能卡（通常称为IC卡）也已在国民经济各部门、各行业以及各地区获得了广泛应用。我国电信、社会保障、交通、建设及公用事业、卫生、组织机构代码管理等领域应用的智能卡数量已经超过了40亿张,智能卡的广泛应用在促进政府与行业管理模式和工作方法的转变,推动国家经济与社会的协调发展,方便百姓生活,提高人民的信息化意识方面发挥了关键作用,做出了重大贡献。从Internet技术和智能卡技术入手,将两者相结合,提出了一个基于网络的大型城市一卡通系统线上交易与网上银行交互的应用方案。     

Context sharing in a ‘real world’ ubicomp deployment

While the application of ubicomp systems to explore context sharing has received a large amount of interest, only a very small number of studies have been carried out which involve “real world” use outside of the lab. This article presents an in-depth analysis of context sharing behaviours that built up around use of the Hermes interactive office door display system received during deployment. The Hermes system provided a groupware application supporting asynchronous messaging facilities, analogous to a digital form of Post-it notes, in order to explore the use of situated display systems to support awareness and coordination in an office environment. From this analysis we distil a set of issues relating to context sharing ranging from privacy concerns to ease of use; each supported through qualitative data from user interviews and questionnaires.