This article refers to:The design of an m-Health monitoring system based on a cloud computing platform

This article refers to:Analyzing manufacturer and the insurance-based risk mitigation policy with equipment service contracting

ABSTRACTThis paper proposes a trustable mold redesign knowledge-sharing platform, known as CKshare, based on private cloud and blockchain technology. Firstly, we use private cloud to store the mold redesign knowledge of each party to meet its own privacy and data format requirements. Secondly, a blockchain network is used for recording the knowledge and its transactions to ensure security and trustfulness. Thirdly, a simple retrieval mechanism is developed based on k-nearest neighbors for retrieving the codified knowledge on the platform. To realize CKshare, a prototype platform has been developed and explained based on real data from the case mold company.

ABSTRACTAs service-oriented computing is commonly used in industrial systems to deal with the continually changing business environment, matching processes with existing services becomes one of the most important phases in constructing, integrating and optimizing information systems. The precision of semantic service matching becomes a critical factor in ensuring the correctness of functionalities in system processes. However, the dependability of semantic service matching cannot be warranted in complex contexts. To improve semantic service matching for industrial systems, a context-based semantic service matching approach named ‘Process-Based service MatchMaker’(PBMM) is proposed in this paper. It selects the suitable services for the process from candidate services through taking the dependencies of related services process into consideration.

ABSTRACT In volunteer crowdsourcing, tasks are published via an open call and completed by many workers without reward. Under the traditional volunteer crowdsourcing paradigm, workers with diverse levels of reliabilities are chosen indiscriminately; moreover, each worker’s performance may change over the time. Thus, the quality of task completions is a key concern in volunteer crowdsourcing. To improve the task completion quality (i.e. the accuracy of task answers), we adopt an adaptive test task (with a true answer) insertion approach to detect a worker’s performance dynamically, thereby ensuring that normal tasks (with unknown true answers) are assigned when this worker is currently deemed reliable via testing. To decide when to route test tasks to detect a worker’s performance or assign normal tasks to be completed in a high quality state, we proposed a Partially Observable Markov Decision Processes (POMDP) based test mechanism without any complicated parameter estimation, which is more practical for real-world volunteer crowdsourcing applications. In addition, we also designed rejection strategies to reject malicious workers and dubious answers. Experiments on real datasets demonstrate that the proposed test mechanism performs better in the accuracy of task answers, compared with benchmark methods.

ABSTRACTThis paper presents an extension of the agent-oriented domain-specific language ALAS to support Distributed Non-Axiomatic Reasoning. ALAS is intended for the development of specific kind of intelligent agents. It is designed to support the Siebog Multi-Agent System (MAS) and implementation of the Siebog intelligent agents. Siebog is a distributed MAS based on the modern web and enterprise standards. Siebog offers support to reasoning based on the Distributed Non-Axiomatic Reasoning System (DNARS). DNARS is a reasoning system based on the Non-Axiomatic Logic (NAL). So far, DNARS-enabled agents could be written only in Java programming language. To solve the problem of interoperability and agent mobility within Siebog platforms, the ALAS language has been developed. The goal of such language is to allow programmers to develop intelligent agents easier by using domain specific constructs. The conversion process of ALAS code to Java code is also described in this paper.

ABSTRACTThe application of Industrial Internet of Things (IIoT) has brought a series of new challenges to the traditional Enterprise Information Systems (EIS). More and more networked manufacturing entities are combined with data sensing, collection, transmission, and actuation capabilities. EIS are now facing large amounts of heterogeneous data. To address this issue, this paper proposes a notification-oriented solution for the data-intensive EIS within a distributed, collaborative, and heterogeneous environment. The solution is then applied in terms of model to a cloud-based smart factory prototype. This work indicates the suitability of the proposition and discusses the existing drawbacks and perspectives that include the manual modelling process and the application on a prototype.

ABSTRACT Under the tendency of mass individualization demands, social manufacturing has been proposed as a new paradigm. This paper proposes a contextual process configuration model for realizing the mass individualized manufacturing. The Social Internet of Things (SIoT) strategy is introduced to boost sociality and narrow down the contextual computing complexity based on situational awareness in a cyber-physical-social connected space. SIoT monitors spatiotemporal situations in a spontaneous social network of relationships and interactions, and induces relevant smart machines depending on prosumers’ individual demands. Four key enabling techniques of SIoT are detailed, and then a demonstrative implementation together with a case study are presented to address the decentralized intelligence in proactive decision making for mass individualization. It is expected that this study can help readers to gain more understanding on the characteristics and configuration logics of contextual self-organizing of manufacturing process for mass individualization.

ABSTRACTIn the modern business world it is increasingly often that Enterprises opt to bring their business model online, in their effort to reach out to more end users and increase their customer base. While transitioning to the new model, enterprises consider securing their data of pivotal importance. In fact, many efforts have been introduced to automate this ‘webification’ process; however, they all fall short in some aspect: a) they either generate only the security infrastructure, assigning implementation to the developers, b) they embed mainstream, less powerful authorisation schemes, or c) they disregard the merits of the dominating REST architecture and adopt less suitable approaches. In this paper we present RESTsec, a Low-Code platform that supports rapid security requirements modelling for Enterprise Services, abiding by the state of the art ABAC authorisation scheme. RESTsec enables the developer to seamlessly embed the desired access control policy and generate the service, the security infrastructure and the code. Evaluation shows that our approach is valid and can help developers deliver secure by design enterprise services in a rapid and automated manner.

ABSTRACTThe era of system integration through service-oriented architecture is rapidly becoming a legacy. New systems increasingly rely on the successor microservice architecture. However, distributed applications can also play a significant role in the internet-of-things. In this paper, we gather evidence demonstrating cross-cutting issues in these areas and highlight how aspect-oriented programming addresses them. Specifically, the purpose of this paper is to provide a roadmap for using aspect-oriented programming to deal effectively with crosscuts in application design, systems interaction, and integration.