882 resultados para parallel processing systems


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Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

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Animportant step in the residue number system(RNS) based signal processing is the conversion of signal into residue domain. Many implementations of this conversion have been proposed for various goals, and one of the implementations is by a direct conversion from an analogue input. A novel approach for analogue-to-residue conversion is proposed in this research using the most popular Sigma–Delta analogue-to-digital converter (SD-ADC). In this approach, the front end is the same as in traditional SD-ADC that uses Sigma–Delta (SD) modulator with appropriate dynamic range, but the filtering is doneby a filter implemented usingRNSarithmetic. Hence, the natural output of the filter is an RNS representation of the input signal. The resolution, conversion speed, hardware complexity and cost of implementation of the proposed SD based analogue-to-residue converter are compared with the existing analogue-to-residue converters based on Nyquist rate ADCs

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This paper describes JERIM-320, a new 320-bit hash function used for ensuring message integrity and details a comparison with popular hash functions of similar design. JERIM-320 and FORK -256 operate on four parallel lines of message processing while RIPEMD-320 operates on two parallel lines. Popular hash functions like MD5 and SHA-1 use serial successive iteration for designing compression functions and hence are less secure. The parallel branches help JERIM-320 to achieve higher level of security using multiple iterations and processing on the message blocks. The focus of this work is to prove the ability of JERIM 320 in ensuring the integrity of messages to a higher degree to suit the fast growing internet applications

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Cyber Physical systems (CPS) connect the physical world with cyber world. The events happening in the real world is enormous and most of it go unnoticed and information is lost. CPS enables to embed tiny smart devices to capture the data and send it to Internet for further processing. The entire set-up call for lots of challenges and open new research problems. This talk is a journey through the landscape of research problems in this emerging area.

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Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

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Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.

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This report gives a detailed discussion on the system, algorithms, and techniques that we have applied in order to solve the Web Service Challenges (WSC) of the years 2006 and 2007. These international contests are focused on semantic web service composition. In each challenge of the contests, a repository of web services is given. The input and output parameters of the services in the repository are annotated with semantic concepts. A query to a semantic composition engine contains a set of available input concepts and a set of wanted output concepts. In order to employ an offered service for a requested role, the concepts of the input parameters of the offered operations must be more general than requested (contravariance). In contrast, the concepts of the output parameters of the offered service must be more specific than requested (covariance). The engine should respond to a query by providing a valid composition as fast as possible. We discuss three different methods for web service composition: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multi-objective genetic algorithm.

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Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

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With this document, we provide a compilation of in-depth discussions on some of the most current security issues in distributed systems. The six contributions have been collected and presented at the 1st Kassel Student Workshop on Security in Distributed Systems (KaSWoSDS’08). We are pleased to present a collection of papers not only shedding light on the theoretical aspects of their topics, but also being accompanied with elaborate practical examples. In Chapter 1, Stephan Opfer discusses Viruses, one of the oldest threats to system security. For years there has been an arms race between virus producers and anti-virus software providers, with no end in sight. Stefan Triller demonstrates how malicious code can be injected in a target process using a buffer overflow in Chapter 2. Websites usually store their data and user information in data bases. Like buffer overflows, the possibilities of performing SQL injection attacks targeting such data bases are left open by unwary programmers. Stephan Scheuermann gives us a deeper insight into the mechanisms behind such attacks in Chapter 3. Cross-site scripting (XSS) is a method to insert malicious code into websites viewed by other users. Michael Blumenstein explains this issue in Chapter 4. Code can be injected in other websites via XSS attacks in order to spy out data of internet users, spoofing subsumes all methods that directly involve taking on a false identity. In Chapter 5, Till Amma shows us different ways how this can be done and how it is prevented. Last but not least, cryptographic methods are used to encode confidential data in a way that even if it got in the wrong hands, the culprits cannot decode it. Over the centuries, many different ciphers have been developed, applied, and finally broken. Ilhan Glogic sketches this history in Chapter 6.

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Die vorliegende Arbeit behandelt Restartautomaten und Erweiterungen von Restartautomaten. Restartautomaten sind ein Werkzeug zum Erkennen formaler Sprachen. Sie sind motiviert durch die linguistische Methode der Analyse durch Reduktion und wurden 1995 von Jancar, Mráz, Plátek und Vogel eingeführt. Restartautomaten bestehen aus einer endlichen Kontrolle, einem Lese/Schreibfenster fester Größe und einem flexiblen Band. Anfänglich enthält dieses sowohl die Eingabe als auch Bandbegrenzungssymbole. Die Berechnung eines Restartautomaten läuft in so genannten Zyklen ab. Diese beginnen am linken Rand im Startzustand, in ihnen wird eine lokale Ersetzung auf dem Band durchgeführt und sie enden mit einem Neustart, bei dem das Lese/Schreibfenster wieder an den linken Rand bewegt wird und der Startzustand wieder eingenommen wird. Die vorliegende Arbeit beschäftigt sich hauptsächlich mit zwei Erweiterungen der Restartautomaten: CD-Systeme von Restartautomaten und nichtvergessende Restartautomaten. Nichtvergessende Restartautomaten können einen Zyklus in einem beliebigen Zustand beenden und CD-Systeme von Restartautomaten bestehen aus einer Menge von Restartautomaten, die zusammen die Eingabe verarbeiten. Dabei wird ihre Zusammenarbeit durch einen Operationsmodus, ähnlich wie bei CD-Grammatik Systemen, geregelt. Für beide Erweiterungen zeigt sich, dass die deterministischen Modelle mächtiger sind als deterministische Standardrestartautomaten. Es wird gezeigt, dass CD-Systeme von Restartautomaten in vielen Fällen durch nichtvergessende Restartautomaten simuliert werden können und andererseits lassen sich auch nichtvergessende Restartautomaten durch CD-Systeme von Restartautomaten simulieren. Des Weiteren werden Restartautomaten und nichtvergessende Restartautomaten untersucht, die nichtdeterministisch sind, aber keine Fehler machen. Es zeigt sich, dass diese Automaten durch deterministische (nichtvergessende) Restartautomaten simuliert werden können, wenn sie direkt nach der Ersetzung einen neuen Zyklus beginnen, oder ihr Fenster nach links und rechts bewegen können. Außerdem gilt, dass alle (nichtvergessenden) Restartautomaten, die zwar Fehler machen dürfen, diese aber nach endlich vielen Zyklen erkennen, durch (nichtvergessende) Restartautomaten simuliert werden können, die keine Fehler machen. Ein weiteres wichtiges Resultat besagt, dass die deterministischen monotonen nichtvergessenden Restartautomaten mit Hilfssymbolen, die direkt nach dem Ersetzungsschritt den Zyklus beenden, genau die deterministischen kontextfreien Sprachen erkennen, wohingegen die deterministischen monotonen nichtvergessenden Restartautomaten mit Hilfssymbolen ohne diese Einschränkung echt mehr, nämlich die links-rechts regulären Sprachen, erkennen. Damit werden zum ersten Mal Restartautomaten mit Hilfssymbolen, die direkt nach dem Ersetzungsschritt ihren Zyklus beenden, von Restartautomaten desselben Typs ohne diese Einschränkung getrennt. Besonders erwähnenswert ist hierbei, dass beide Automatentypen wohlbekannte Sprachklassen beschreiben.

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The nonforgetting restarting automaton is a generalization of the restarting automaton that, when executing a restart operation, changes its internal state based on the current state and the actual contents of its read/write window instead of resetting it to the initial state. Another generalization of the restarting automaton is the cooperating distributed system (CD-system) of restarting automata. Here a finite system of restarting automata works together in analyzing a given sentence, where they interact based on a given mode of operation. As it turned out, CD-systems of restarting automata of some type X working in mode =1 are just as expressive as nonforgetting restarting automata of the same type X. Further, various types of determinism have been introduced for CD-systems of restarting automata called strict determinism, global determinism, and local determinism, and it has been shown that globally deterministic CD-systems working in mode =1 correspond to deterministic nonforgetting restarting automata. Here we derive some lower bound results for some types of nonforgetting restarting automata and for some types of CD-systems of restarting automata. In this way we establish separations between the corresponding language classes, thus providing detailed technical proofs for some of the separation results announced in the literature.

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In this report, we discuss the application of global optimization and Evolutionary Computation to distributed systems. We therefore selected and classified many publications, giving an insight into the wide variety of optimization problems which arise in distributed systems. Some interesting approaches from different areas will be discussed in greater detail with the use of illustrative examples.

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Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.

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