6,684 research outputs found

    A New Prototype for Intelligent Visual Fraud Detection in Agent-Based Auditing Framework

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    While US. Sarbanes Oxley act has been viewed by most as an onerous and expensive requirement; it is having a positive impact on driving appropriate levels of investment in IT security, controls, and transactional systems. This paper introduces a new secure solution for auditing and accounting based on artificial intelligence technology. These days, security is a big issue among regulatory firms. Big companies are concerned about their data to be disseminated to their competitors; this high risk prevents them to provide full information to the regulatory firms. This solution not only significantly reduces the risk of unauthorized access to the company’s information but also facilitate a framework for controlling the flow of disseminating information in a risk free method. Managing security is performed by a network of mobile agents in a pyramid structure among regulatory organization like securities and exchanges commissions, stock exchanges in top of this pyramid to the companies in the button. Because of security considerations, our strategy is to delegate all fraud detection algorithms to Intelligent Mobile Auditing Agent and web service undertake all inter communicational activity. Web services can follow auditing actives in predefined framework and they can act based on permitted security allowance to auditors. The current solution is designed based on Java-based mobile agents. Such design reaps strong mobility and security benefits. This new prototyped solution could be a framework for strengthening security for future development in this area. An insider trading case study is used to demonstrate and evaluate the approach

    Architecting system of systems: artificial life analysis of financial market behavior

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    This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as promoters or inhibitors of change in human systems. Computational intelligence tools have been successfully used in analysis of Complex Adaptive Systems. Since a System of Systems is a collection of Complex Adaptive Systems, a framework utilizing combination of these tools can be developed. Financial markets are selected to demonstrate the various architectures developed from the analysis framework --Introduction, page 3

    A Multi-Agent Energy Trading Competition

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    The energy sector will undergo fundamental changes over the next ten years. Prices for fossil energy resources are continuously increasing, there is an urgent need to reduce CO2 emissions, and the United States and European Union are strongly motivated to become more independent from foreign energy imports. These factors will lead to installation of large numbers of distributed renewable energy generators, which are often intermittent in nature. This trend conflicts with the current power grid control infrastructure and strategies, where a few centralized control centers manage a limited number of large power plants such that their output meets the energy demands in real time. As the proportion of distributed and intermittent generation capacity increases, this task becomes much harder, especially as the local and regional distribution grids where renewable energy generators are usually installed are currently virtually unmanaged, lack real time metering and are not built to cope with power flow inversions (yet). All this is about to change, and so the control strategies must be adapted accordingly. While the hierarchical command-and-control approach served well in a world with a few large scale generation facilities and many small consumers, a more flexible, decentralized, and self-organizing control infrastructure will have to be developed that can be actively managed to balance both the large grid as a whole, as well as the many lower voltage sub-grids. We propose a competitive simulation test bed to stimulate research and development of electronic agents that help manage these tasks. Participants in the competition will develop intelligent agents that are responsible to level energy supply from generators with energy demand from consumers. The competition is designed to closely model reality by bootstrapping the simulation environment with real historic load, generation, and weather data. The simulation environment will provide a low-risk platform that combines simulated markets and real-world data to develop solutions that can be applied to help building the self-organizing intelligent energy grid of the future

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Big data analytics:Computational intelligence techniques and application areas

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    Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

    SIMBA: a simulator for business education and research

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    Business simulators are used for decision-making since different scenarios can be evaluated without risk. They are also used in business management education. The main goal of this paper is to introduce SIMBA (SIMulator for Business Administration), a new simulator that serves as a web-based platform for business education, permitting both classroom and distance education. This paper also adds a research aspect in business intelligence because SIMBA can be used as a fieldwork tool for the development and evaluation of intelligent agents. The simulator creates a more complex competitive environment in which intelligent agents play the role of business decision makers.This work has been partially sponsored by a regional project CCG08-UC3M/TIC-4141 of the Comunidad de Madrid, a national project TIN2008-06701-C03-03 of the Ministerio de Ciencia e InnovaciĂłn of Spain and a contract with Simuladores Empresariales S.L.Publicad

    Managing smart cities with deepint.net

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    In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities
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