948 resultados para Computer Engineering|Computer science


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Relevance feature and ontology are two core components to learn personalized ontologies for concept-based retrievals. However, how to associate user native information with common knowledge is an urgent issue. This paper proposes a sound solution by matching relevance feature mined from local instances with concepts existing in a global knowledge base. The matched concepts and their relations are used to learn personalized ontologies. The proposed method is evaluated elaborately by comparing it against three benchmark models. The evaluation demonstrates the matching is successful by achieving remarkable improvements in information filtering measurements.

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This tutorial is designed to assist users who wish to use the LCD screen on the Spartan-3E board. In this tutorial, the PicoBlaze microcontroller is used to control the LCD. The tutorial is organised into three Parts. In Part A, code is written to display the message "Hello World" on the LCD. Part B demonstrates how to define and display custom characters. Finally, Part C shows how the display can be shifted and flashed. Shifting is done by using a delay in the main PicoBlaze program loop, while flashing is done using the PicoBlaze interrupt. The slider switches can be used to select the shifting direction, and to turn shifting and flashing on and off.

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A general electrical model of a piezoelectric transducer for ultrasound applications consists of a capacitor in parallel with RLC legs. A high power voltage source converter can however generate significant voltage stress across the transducer that creates high leakage currents. One solution is to reduce the voltage stress across the piezoelectric transducer by using an LC filter, however a main drawback is changing the piezoelectric resonant frequency and its characteristics. Thereby it reduces the efficiency of energy conversion through the transducer. This paper proposes that a high frequency current source converter is a suitable topology to drive high power piezoelectric transducers efficiently.

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Internet chatrooms are common means of interaction and communications, and they carry valuable information about formal or ad-hoc formation of groups with diverse objectives. This work presents a fully automated surveillance system for data collection and analysis in Internet chatrooms. The system has two components: First, it has an eavesdropping tool which collects statistics on individual (chatter) and chatroom behavior. This data can be used to profile a chatroom and its chatters. Second, it has a computational discovery algorithm based on Singular Value Decomposition (SVD) to locate hidden communities and communication patterns within a chatroom. The eavesdropping tool is used for fine tuning the SVD-based discovery algorithm which can be deployed in real-time and requires no semantic information processing. The evaluation of the system on real data shows that (i) statistical properties of different chatrooms vary significantly, thus profiling is possible, (ii) SVD-based algorithm has up to 70-80% accuracy to discover groups of chatters.

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Securing IT infrastructures of our modern lives is a challenging task because of their increasing complexity, scale and agile nature. Monolithic approaches such as using stand-alone firewalls and IDS devices for protecting the perimeter cannot cope with complex malwares and multistep attacks. Collaborative security emerges as a promising approach. But, research results in collaborative security are not mature, yet, and they require continuous evaluation and testing. In this work, we present CIDE, a Collaborative Intrusion Detection Extension for the network security simulation platform ( NeSSi 2 ). Built-in functionalities include dynamic group formation based on node preferences, group-internal communication, group management and an approach for handling the infection process for malware-based attacks. The CIDE simulation environment provides functionalities for easy implementation of collaborating nodes in large-scale setups. We evaluate the group communication mechanism on the one hand and provide a case study and evaluate our collaborative security evaluation platform in a signature exchange scenario on the other.

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Computer worms represent a serious threat for modern communication infrastructures. These epidemics can cause great damage such as financial losses or interruption of critical services which support lives of citizens. These worms can spread with a speed which prevents instant human intervention. Therefore automatic detection and mitigation techniques need to be developed. However, if these techniques are not designed and intensively tested in realistic environments, they may cause even more harm as they heavily interfere with high volume communication flows. We present a simulation model which allows studies of worm spread and counter measures in large scale multi-AS topologies with millions of IP addresses.

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We present a virtual test bed for network security evaluation in mid-scale telecommunication networks. Migration from simulation scenarios towards the test bed is supported and enables researchers to evaluate experiments in a more realistic environment. We provide a comprehensive interface to manage, run and evaluate experiments. On basis of a concrete example we show how the proposed test bed can be utilized.

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Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

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Driven by the rapid development of ubiquitous and pervasive computing, personalized services and applications are deployed to support our lives. Accordingly, the number of interfaces and devices (smartphone, tablet computer, etc.) provided to access and consume these services is growing continuously. To simplify the complexity of managing many accounts with different credentials, Single Sign-On (SSO) solutions have been introduced. However, a single password for many accounts represents a single-point-of-failure. Furthermore, once initiated SSO session is a high potential risk when the working station is left unlocked and unattended. In this paper, we present a conception of a Persistent Single Sign-On (PSSO) for ubiquitous home environments by involving the capabilities of Behavioral Biometrics to check the identity of the user continuously in an unobtrusive manner.

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An energy storage system (ESS) can provide ancillary services such as frequency regulation and reserves, as well as smooth the fluctuations of wind power outputs, and hence improve the security and economics of the power system concerned. The combined operation of a wind farm and an ESS has become a widely accepted operating mode. Hence, it appears necessary to consider this operating mode in transmission system expansion planning, and this is an issue to be systematically addressed in this work. Firstly, the relationship between the cost of the NaS based ESS and its discharging cycle life is analyzed. A strategy for the combined operation of a wind farm and an ESS is next presented, so as to have a good compromise between the operating cost of the ESS and the smoothing effect of the fluctuation of wind power outputs. Then, a transmission system expansion planning model is developed with the sum of the transmission investment costs, the investment and operating costs of ESSs and the punishment cost of lost wind energy as the objective function to be minimized. An improved particle swarm optimization algorithm is employed to solve the developed planning model. Finally, the essential features of the developed model and adopted algorithm are demonstrated by 18-bus and 46-bus test systems.

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Advances in solid-state switches and power electronics techniques have led to the development of compact, efficient and more reliable pulsed power systems. This paper proposes an efficient scheme that utilizes modular switch-capacitor units in obtaining high voltage levels with fast rise time (dv/dt) using low voltage solid-state switches. The proposed pulsed power supply has flexibility in terms of controlling energy and generating broad range of voltage levels. The energy flow can be controlled as the stored energy can be adjusted by a current source utilized at the first stage of the system. Desirable voltage level can be obtained by connecting adequate number of switch-capacitor units. Moreover, the proposed topology is load independent. Therefore it can easily supply wide range of applications especially the low impedance ones. The effectiveness of the proposed approach is verified by simulations

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A number of security models have been proposed for RFID systems. Recent studies show that current models tend to be limited in the number of properties they capture. Consequently, models are commonly unable to distinguish between protocols with regard to finer privacy properties. This paper proposes a privacy model that introduces previously unavailable expressions of privacy. Based on the well-studied notion of indistinguishability, the model also strives to be simpler, easier to use, and more intuitive compared to previous models.

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The GameFlow model strives to be a general model of player enjoyment, applicable to all game genres and platforms. Derived from a general set of heuristics for creating enjoyable player experiences, the GameFlow model has been widely used in evaluating many types of games, as well as non-game applications. However, we recognize that more specific, low-level, and implementable criteria are potentially more useful for designing and evaluating video games. Consequently, the research reported in this paper aims to provide detailed heuristics for designing and evaluating one specific game genre, real-time strategy games. In order to develop these heuristics, we conducted a grounded theoretical analysis on a set of professional game reviews and structured the resulting heuristics using the GameFlow model. A selection of the resulting 165 heuristics are presented in this paper and discussed with respect to key evaluations of the GameFlow model.

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The GameFlow model strives to be a general model of player enjoyment, applicable to all game genres and platforms. Derived from a general set of heuristics for creating enjoyable player experiences, the GameFlow model has been widely used in evaluating many types of games, as well as non-game applications. However, we recognize that more specific, low-level, and implementable criteria are potentially more useful for designing and evaluating video games. Consequently, the research reported in this paper aims to provide detailed heuristics for designing and evaluating one specific game genre, real-time strategy games. In order to develop these heuristics, we conducted a grounded theoretical analysis on a set of professional game reviews and structured the resulting heuristics using the GameFlow model. The resulting 165 heuristics for designing and evaluating real-time strategy games are presented and discussed in this paper.

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Piezoelectric transducers convert electrical energy to mechanical energy and play a great role in ultrasound systems. Ultrasound power transducer performance is strongly related to the applied electrical excitation. To have a suitable excitation for maximum energy conversion, it is required to analyze the effects of input signal waveform, medium and input signal distortion on the characteristic of a high power ultrasound system (including ultrasound transducer). In this research, different input voltage signals are generated using a single-phase power inverter and a linear power amplifier to excite a high power ultrasound transducer in different medium (water and oil) in order to study the characteristic of the system. We have also considered and analyzed the effect of power converter output voltage distortions on the performance of the high power ultrasound transducer using a passive filter.