Location Service Information Supporting System Based on Ontology

In order to solve the problem of how to collect and manage large amount of location information and improve the accuracy of location service, interactive information supporting system based on ontology and location service is presented in this paper. It can transmit special information about users＇ location to front-end instantaneously, so it is very convenient for their daily life. It makes full use of the available wireless communication, which is easy to arrange and convenient for users.

Design of Distributed Authentication Mechanism for Equipment Support Information Network

Considering the secure authentication problem for equipment support information network,a clustering method based on the business information flow is proposed. Based on the proposed method,a cluster-based distributed authentication mechanism and an optimal design method for distributed certificate authority( CA)are designed. Compared with some conventional clustering methods for network,the proposed clustering method considers the business information flow of the network and the task of the network nodes,which can decrease the communication spending between the clusters and improve the network efficiency effectively. The identity authentication protocols between the nodes in the same cluster and in different clusters are designed. From the perspective of the security of network and the availability of distributed authentication service,the definition of the secure service success rate of distributed CA is given and it is taken as the aim of the optimal design for distributed CA. The efficiency of providing the distributed certificate service successfully by the distributed CA is taken as the constraint condition of the optimal design for distributed CA. The determination method for the optimal value of the threshold is investigated. The proposed method can provide references for the optimal design for distributed CA.

An Integrated Information Retrieval Support System for Campus Network

This paper presents a new integrated information retrieval support system （IIRSS） which can help Web search engines retrieve cross-lingual information from hereto geneous resources stored in multi-databases in Intranet. The IIRSS, with a three-layer architecture, can cooperate with other application servers running in Intranet. By using intelligent agents to collect information and to create indexes on the-fly, using an access control strategy to confine a user to browsing those accessible documents for him/her through a single portal, and using a new cross-lingual translation tool to help the search engine retrieve documents, the new system provides controllable information access with different authorizations, personalized services, and real-time information retrieval.

The Concept of Information Support for Bi-oresource and Ecosystem Research in the North-West Pacific: Theory and Practical Implementation

The first part of the article provides an overview of the theoretical evidence, the main provisions, and the implementation strategy of information support for bioresource and ecosystem research in the north-west Pacific, which has been conducted over the past 20 years in the Russian Far East Research Institute TINRO-Center. In short, the concept consists of a combination of the following four assertions: 1) For the steady and sustainable development of the Russian Far East, the entire Russian Federation and the Asia-Pacific Region in general, environmental, food, economic, and other security is required, which cannot be achieved without the rational use of bioresources based on the ecosystem approach to the management of aquatic bioresources. 2) For the inventory, appraisal, monitoring, forecasting of the state of and management the natural water resources when applying this approach, statistically relevant quantitative information is required on the greatest possible number of constituents of marine biocenosis of the north-western Pacific for the longest possible period of time, which is only available at the TINRO-Center. 3) This valuable data should be organized into databases, based on which geo-information and other electronic information systems are prepared, and based on these map atlases and reference books on natural water resources, using automated workplaces created especially for this. 4) The resulting unique information support will be of great value not only for practical purposes, but also for science, both applied and fundamental. Next comes a summary of the many years of work on the practical implementation of this concept and the key achievements in this field obtained by the TINRO-Center by the end of 2015 are reviewed. At the end, some plans for the near future are outlined.

Knowledge Creation Systems in Seven-Eleven Japan

Japanese convenience store chain Seven-Eleven Japan (hereinafter 'SEJ') has been profitable for 30 years by constantly anticipating changing trends regardless of the severe business environment. In this paper, the knowledge creation process and its supportive systems in SEJ to examine how information system can support knowledge creation are described. Using case study method, the knowledge creation theory is applied to SEJ, and the results show that facilitating 'dialogue' and reinforcing 'creative routine' might be the most important functions of information system to support knowledge creation.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.

AN EXTENDED BLOCK RESTRICTED ISOMETRY PROPERTY FOR SPARSE RECOVERY WITH NON-GAUSSIAN NOISE

We study the recovery conditions of weighted mixedl2/lp minimization for block sparse signal reconstruction from compressed measurements when partial block support information is available.We show theoretically that the extended block restricted isometry property can ensure robust recovery when the data fidelity constraint is expressed in terms of anlq norm of the residual error,thus establishing a setting wherein we are not restricted to Gaussian measurement noise.We illustrate the results with a series of numerical experiments.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.