800 resultados para Intelligent environments
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The relation between the information/knowledge expression and the physical expression can be involved as one of items for an ambient intelligent computing [2],[3]. Moreover, because there are so many contexts around user/spaces during a user movement, all appplcation which are using AmI for users are based on the relation between user devices and environments. In these situations, it is possible that the AmI may output the wrong result from unreliable contexts by attackers. Recently, establishing a server have been utilizes, so finding secure contexts and make contexts of higher security level for save communication have been given importance. Attackers try to put their devices on the expected path of all users in order to obtain users informationillegally or they may try to broadcast their SPAMS to users. This paper is an extensionof [11] which studies the Security Grade Assignment Model (SGAM) to set Cyber-Society Organization (CSO).
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Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.
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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.
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Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.
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The current work can be seen as a starting point for the discussion of the problematic on risk acceptance criteria in occupational environments. Some obstacles to the quantitative acceptance criteria formulation and use were analyzed. A look to the long tradition of major hazards accidents was also performed. This work shows that organizations can have several difficulties in acceptance criteria formulation and that the use of pre-defined acceptance criteria in risk assessment methodologies can be inadequate in some cases. It is urgent to define guidelines that can help organizations in the formulation of risk acceptance criteria for occupational environments.
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Virtual Reality (VR) has grown to become state-of-theart technology in many business- and consumer oriented E-Commerce applications. One of the major design challenges of VR environments is the placement of the rendering process. The rendering process converts the abstract description of a scene as contained in an object database to an image. This process is usually done at the client side like in VRML [1] a technology that requires the client’s computational power for smooth rendering. The vision of VR is also strongly connected to the issue of Quality of Service (QoS) as the perceived realism is subject to an interactive frame rate ranging from 10 to 30 frames-per-second (fps), real-time feedback mechanisms and realistic image quality. These requirements overwhelm traditional home computers or even high sophisticated graphical workstations over their limits. Our work therefore introduces an approach for a distributed rendering architecture that gracefully balances the workload between the client and a clusterbased server. We believe that a distributed rendering approach as described in this paper has three major benefits: It reduces the clients workload, it decreases the network traffic and it allows to re-use already rendered scenes.
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In this paper we survey the most relevant results for the prioritybased schedulability analysis of real-time tasks, both for the fixed and dynamic priority assignment schemes. We give emphasis to the worst-case response time analysis in non-preemptive contexts, which is fundamental for the communication schedulability analysis. We define an architecture to support priority-based scheduling of messages at the application process level of a specific fieldbus communication network, the PROFIBUS. The proposed architecture improves the worst-case messages’ response time, overcoming the limitation of the first-come-first-served (FCFS) PROFIBUS queue implementations.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia
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The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.
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Indoor location systems cannot rely on technologies such as GPS (Global Positioning System) to determine the position of a mobile terminal, because its signals are blocked by obstacles such as walls, ceilings, roofs, etc. In such environments. The use of alternative techniques, such as the use of wireless networks, should be considered. The location estimation is made by measuring and analysing one of the parameters of the wireless signal, usually the received power. One of the techniques used to estimate the locations using wireless networks is fingerprinting. This technique comprises two phases: in the first phase data is collected from the scenario and stored in a database; the second phase consists in determining the location of the mobile node by comparing the data collected from the wireless transceiver with the data previously stored in the database. In this paper an approach for localisation using fingerprinting based on Fuzzy Logic and pattern searching is presented. The performance of the proposed approach is compared with the performance of classic methods, and it presents an improvement between 10.24% and 49.43%, depending on the mobile node and the Fuzzy Logic parameters.ł
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This paper presents the recent research results about the development of a Observed Time Difference (OTD) based geolocation algorithm based on network trace data, for a real Universal Mobile Telecommunication System (UMTS) Network. The initial results have been published in [1], the current paper focus on increasing the sample convergence rate, and introducing a new filtering approach based on a moving average spatial filter, to increase accuracy. Field tests have been carried out for two radio environments (urban and suburban) in the Lisbon area, Portugal. The new enhancements produced a geopositioning success rate of 47% and 31%, and a median accuracy of 151 m and 337 m, for the urban and suburban environments, respectively. The implemented filter produced a 16% and 20% increase on accuracy, when compared with the geopositioned raw data. The obtained results are rather promising in accuracy and geolocation success rate. OTD positioning smoothed by moving average spatial filtering reveals a strong approach for positioning trace extracted events, vital for boosting Self-Organizing Networks (SON) over a 3G network.
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In this paper a new simulation environment for a virtual laboratory to educational proposes is presented. The Logisim platform was adopted as the base digital simulation tool, since it has a modular implementation in Java. All the hardware devices used in the laboratory course was designed as components accessible by the simulation tool, and integrated as a library. Moreover, this new library allows the user to access an external interface. This work was motivated by the needed to achieve better learning times on co-design projects, based on hardware and software implementations, and to reduce the laboratory time, decreasing the operational costs of engineer teaching. Furthermore, the use of virtual laboratories in educational environments allows the students to perform functional tests, before they went to a real laboratory. Moreover, these functional tests allow to speed-up the learning when a problem based approach methodology is considered. © 2014 IEEE.
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With advancement in computer science and information technology, computing systems are becoming increasingly more complex with an increasing number of heterogeneous components. They are thus becoming more difficult to monitor, manage, and maintain. This process has been well known as labor intensive and error prone. In addition, traditional approaches for system management are difficult to keep up with the rapidly changing environments. There is a need for automatic and efficient approaches to monitor and manage complex computing systems. In this paper, we propose an innovative framework for scheduling system management by combining Autonomic Computing (AC) paradigm, Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems
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The aim of this study was to contribute to the assessment of exposure levels of ultrafine particles in the urban environment of Lisbon, Portugal, due to automobile traffic, by monitoring lung deposited alveolar surface area (resulting from exposure to ultrafine particles) in a major avenue leading to the town center during late spring, as well as in indoor buildings facing it. Data revealed differentiated patterns for week days and weekends, consistent with PM2.5 and PM10 patterns currently monitored by air quality stations in Lisbon. The observed ultrafine particulate levels may be directly correlated with fluxes in automobile traffic. During a typical week, amounts of ultrafine particles per alveolar deposited surface area varied between 35 and 89.2 mu m2/cm3, which are comparable with levels reported for other towns in Germany and the United States. The measured values allowed for determination of the number of ultrafine particles per cubic centimeter, which are comparable to levels reported for Madrid and Brisbane. In what concerns outdoor/indoor levels, we observed higher levels (32 to 63%) outdoors, which is somewhat lower than levels observed in houses in Ontario.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores