Search results for: semantic memory

Authors: Yu Ren Lin, Yu Hong Li

Abstract:

Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).

Keywords: blind-spot area, image, FPGA

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Authors: Chih-Hao Chen, Hsing-Chung Lee, Qingdong Ling, Hsiao-Jung Chen, Sun-Chong Wang, Li-Ching Wu, H.C. Lee

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Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Keywords: Cancer, pathogenesis, chromosomal aberration, copy number variation, segmentation analysis.

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Authors: Yu Ren Lin, Yi Feng Su

Abstract:

Using vision based solution in intelligent vehicle application often needs large memory to handle video stream and image process which increase complexity of hardware and software. In this paper, we present a FPGA implement of a vision based lane departure warning system. By taking frame of videos, the line gradient of line is estimated and the lane marks are found. By analysis the position of lane mark, departure of vehicle will be detected in time. This idea has been implemented in Xilinx Spartan6 FPGA. The lane departure warning system used 39% logic resources and no memory of the device. The average availability is 92.5%. The frame rate is more than 30 frames per second (fps).

Keywords: Lane departure warning system, image, FPGA.

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Authors: Thabet Slimani, Boutheina Ben Yaghlane, Khaled Mellouli

Abstract:

In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.

Keywords: Association extraction, query Language, relationships, knowledge base, multi-paradigm query.

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Authors: Yousef Daneshvar Rouyandozagh, Ece. K. Açikgöz

Abstract:

Conservation of historical urban patterns in the traditional neighborhoods is a part of creating integrated urban environments that are socially more sustainable. Urbanization reflects on life conditions and social, physical, economical characteristics of the society. In this regard, historical zones and traditional regions are affected by dramatic interventions on these characteristics. This article focuses on the Uch Dukkan neighborhood located in Ardabil City in Azarbaijani region of Iran, which has been up to such interventions that leaded its transformation from the past to the present. After introducing a brief inventory of the main elements of the historical zone and the neighborhood; this study explores the changes and transformations in different periods; and their impacts on the quality of the environment and its social sustainability. The survey conducted in the neighborhood as part of this research study revealed that the Uch Dukkan neighborhood and the unique architectural heritage that it possesses have become more inactive physically and functionally in a decade. This condition requires an exploration and comparison of the present and the expected transformations of the meaning of social space from the most private unit to the urban scale. From this token, it is argued that an architectural point of view that is based on space order; use and meaning of space as a social and cultural image, should not be ignored. Based on the interplay between social sustainability, collective memory, and the urban environment, study aims to make the invisible portion of ignorance clear, that ends up with a weakness in defining the collective meaning of the neighborhood as a historic urban district. It reveals that the spatial possessions of the neighborhood are valuable not only for their historical and physical characteristics, but also for their social memory that is to be remembered and constructed further.

Keywords: Urban integrity, social sustainability, collective memory, social decay.

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Authors: Xiang Li, Zhixian Chen, Zheng Fang, Aashit Kamath, Xinpeng Wang, Navab Singh, Guo-Qiang Lo, Dim-Lee Kwong

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We integrate TiN/Ni/HfO2/Si RRAM cell with a vertical gate-all-around (GAA) nanowire transistor to achieve compact 4F2 footprint in a 1T1R configuration. The tip of the Si nanowire (source of the transistor) serves as bottom electrode of the memory cell. Fabricated devices with nanowire diameter ~ 50nm demonstrate ultra-low current/power switching; unipolar switching with 10μA/30μW SET and 20μA/30μW RESET and bipolar switching with 20nA/85nW SET and 0.2nA/0.7nW RESET. Further, the switching current is found to scale with nanowire diameter making the architecture promising for future scaling.

Keywords: RRAM, 1T1R, gate-all-around FET, nanowire FET, vertical MOSFETs

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Authors: Mohamed Amine Ouddan, Hassane Essafi

Abstract:

Source code retrieval is of immense importance in the software engineering field. The complex tasks of retrieving and extracting information from source code documents is vital in the development cycle of the large software systems. The two main subtasks which result from these activities are code duplication prevention and plagiarism detection. In this paper, we propose a Mohamed Amine Ouddan, and Hassane Essafi source code retrieval system based on two-level fingerprint representation, respectively the structural and the semantic information within a source code. A sequence alignment technique is applied on these fingerprints in order to quantify the similarity between source code portions. The specific purpose of the system is to detect plagiarism and duplicated code between programs written in different programming languages belonging to the same class, such as C, Cµ, Java and CSharp. These four languages are supported by the actual version of the system which is designed such that it may be easily adapted for any programming language.

Keywords: Source code retrieval, plagiarism detection, clonedetection, sequence alignment.

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Authors: Lotfi Admane

Abstract:

This paper presents a model of case based corporate memory named ReCaRo (REsource, CAse, ROle). The approach suggested in ReCaRo decomposes the domain to model through a set of components. These components represent the objects developed by the company during its activity. They are reused, and sometimes, while bringing adaptations. These components are enriched by knowledge after each reuse. ReCaRo builds the corporate memory on the basis of these components. It models two types of knowledge: 1) Business Knowledge, which constitutes the main knowledge capital of the company, refers to its basic skill, thus, directly to the components and 2) the Experience Knowledge which is a specialised knowledge and represents the experience gained during the handling of business knowledge. ReCaRo builds corporate memories which are made up of five communicating ones.

Keywords: Corporate memories, meta-model, reuse, ReCaRo.

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Authors: Jiho Park, Yong-Gyu Lee, Gilwon Yoon

Abstract:

Data security in u-Health system can be an important issue because wireless network is vulnerable to hacking. However, it is not easy to implement a proper security algorithm in an embedded u-health monitoring because of hardware constraints such as low performance, power consumption and limited memory size and etc. To secure data that contain personal and biosignal information, we implemented several security algorithms such as Blowfish, data encryption standard (DES), advanced encryption standard (AES) and Rivest Cipher 4 (RC4) for our u-Health monitoring system and the results were successful. Under the same experimental conditions, we compared these algorithms. RC4 had the fastest execution time. Memory usage was the most efficient for DES. However, considering performance and safety capability, however, we concluded that AES was the most appropriate algorithm for a personal u-Health monitoring system.

Keywords: biosignal, data encryption, security measures, u-health

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Authors: Pichayut Peerasathien, Hiroshi Nagahashi

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Subdivision is a method to create a smooth surface from a coarse mesh by subdividing the entire mesh. The conventional ways to compute and render surfaces are inconvenient both in terms of memory and computational time as the number of meshes will increase exponentially. An adaptive subdivision is the way to reduce the computational time and memory by subdividing only certain selected areas. In this paper, a new adaptive subdivision method for triangle meshes is introduced. This method defines a new adaptive subdivision rules by considering the properties of each triangle's neighbors and is embedded in a traditional Loop's subdivision. It prevents some undesirable side effects that appear in the conventional adaptive ways. Models that were subdivided by our method are compared with other adaptive subdivision methods

Keywords: Subdivision, loop subdivision, handle cracks, smooth surface.

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Authors: Xiaomei Wang, Shouming Zhong

Abstract:

In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known results. One example is given to show the feasibility and effectiveness of our results.

Keywords: Bi-directional associative memory (BAM) neural networks, mixed delays, Lyapunov stability theory, contraction mapping theorem, existence, equilibrium, globally exponential stability.

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Authors: Muhammed Yousoof, Mohd Sapiyan, Khaja Kamaluddin

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Many difficulties are faced in the process of learning computer programming. This paper will propose a system framework intended to reduce cognitive load in learning programming. In first section focus is given on the process of learning and the shortcomings of the current approaches to learning programming. Finally the proposed prototype is suggested along with the justification of the prototype. In the proposed prototype the concept map is used as visualization metaphor. Concept maps are similar to the mental schema in long term memory and hence it can reduce cognitive load well. In addition other method such as part code method is also proposed in this framework to can reduce cognitive load.

Keywords: Cognitive load, concept maps, working memory, split attention effect, partial code programs.

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Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh

Abstract:

Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.

Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.

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Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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Authors: Sunitha Abburu, Golla Suresh Babu

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The issues that limit application interoperability is lack of common vocabulary, common structure, application domain knowledge ontology based semantic technology provides solutions that resolves application interoperability issues. Ontology is broadly used in diverse applications such as artificial intelligence, bioinformatics, biomedical, information integration, etc. Ontology can be used to interpret the knowledge of various domains. To reuse, enrich the available ontologies and reduce the duplication of ontologies of the same domain, there is a strong need to integrate the ontologies of the particular domain. The integrated ontology gives complete knowledge about the domain by sharing this comprehensive domain ontology among the groups. As per the literature survey there is no well-defined methodology to represent knowledge of a whole domain. The current research addresses a systematic methodology for knowledge representation using multiple sub-ontologies at different levels that addresses application interoperability and enables semantic information retrieval. The current method represents complete knowledge of a domain by importing concepts from multiple sub ontologies of same and relative domains that reduces ontology duplication, rework, implementation cost through ontology reusability.

Keywords: Knowledge acquisition, knowledge representation, knowledge transfer, ontologies, semantics.

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Authors: Jianhua Wang, Yan Yu

Abstract:

This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail.

Keywords: RBF, Elman, anomaly detection, misuse detection, hybrid neural network.

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Authors: Ilona Copik

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The aim of this study is to analyze the representation of memories of the forced displacement of Poles and Germans from the eastern territories in 1945 as depicted by Polish and German feature films between the years 1945-1960. The aftermath of World War II and the Allied agreements concluded at Yalta and Potsdam (1945) resulted in changes in national borders in Central and Eastern Europe and the large-scale transfer of civilians. The westward migration became a symbol of the new post-war division of Europe, new spheres of influence separated by the Iron Curtain. For years it was a controversial topic in both Poland and Germany due to the geopolitical alignment (the socialist East and capitalist West of Europe), as well as the unfinished debate between the victims and perpetrators of the war. The research premise is to take a comparative view of the conflicted cultures of Polish and German memory, to reflect on the possibility of an international dialogue about the past recorded in film images, and to discover the potential of film as a narrative warning against totalitarian inclinations. Until now, films made between 1945 and 1960 in Poland and the German occupation zones have been analyzed mainly in the context of artistic strategies subordinated to ideology and historical politics. In this study, the intention is to take a critical approach leading to the recognition of how films work as collective memory media, how they reveal the mechanisms of memory/ forgetting, and what settlement topoi and migration myths they contain. The main hypothesis is that feature films about forced displacement, in addition to the politics of history - separate in each country - reveal comparable transnational individual experiences: the chaos of migration, the trauma of losing one's home, the conflicts accompanying the familiar/foreign, the difficulty of cultural adaptation, the problem of lost identity, etc.

Keywords: Forced displacement, Polish and German cinema, war victims, World War II.

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: Building information modeling, elemental graph data model, geometric and topological data models, and graph theory.

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to gather information in unknown environments to achieve simultaneous localization and mapping of the environment. This technology has a wide range of applications in autonomous driving, virtual reality, and other related fields. Currently, the research advancements related to VSLAM can maintain high accuracy in static environments. But in dynamic environments, the presence of moving objects in the scene can reduce the stability of the VSLAM system, leading to inaccurate localization and mapping, or even system failure. In this paper, a robust VSLAM method was proposed to effectively address the challenges in dynamic environments. We proposed a dynamic region removal scheme based on a semantic segmentation neural network and geometric constraints. Firstly, a semantic segmentation neural network is used to extract the prior active motion region, prior static region, and prior passive motion region in the environment. Then, the lightweight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static regions and dynamic regions. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under a high dynamic environment.

Keywords: Dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM.

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Authors: Ákos Dudás, Sándor Juhász

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Various mechanisms providing mutual exclusion and thread synchronization can be used to support parallel processing within a single computer. Instead of using locks, semaphores, barriers or other traditional approaches in this paper we focus on alternative ways for making better use of modern multithreaded architectures and preparing hash tables for concurrent accesses. Hash structures will be used to demonstrate and compare two entirely different approaches (rule based cooperation and hardware synchronization support) to an efficient parallel implementation using traditional locks. Comparison includes implementation details, performance ranking and scalability issues. We aim at understanding the effects the parallelization schemes have on the execution environment with special focus on the memory system and memory access characteristics.

Keywords: Lock-free synchronization, mutual exclusion, parallel hash tables, parallel performance

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Authors: Francisco Guimarães, Mauro Figueiredo, José Rodrigues

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Cities are spaces of memory with several zones (parts of cities) with their own history and cultural events. Today, cities are also marked by a form of intangible cultural heritage like street art, which creates a visual culture based on the process of reflection about the city and the world. To link these realities and create a personal user interaction with this cultural heritage it is important to capture the story and aesthetics, and find alternatives to immerse the user in these spaces of memory. To that end, this article presents a project which combines Augmented Reality technologies and concepts of Transmedia Storytelling applied to Lisbon City, using Street Art artifacts as markers in a framework of digital media-art.

Keywords: Cultural heritage, urban art, street art, augmented reality, transmedia storytelling, digital media-art, socio-museology.

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Authors: John Mark Lampos, Virgilio Sison

Abstract:

Two constructions of unit-memory binary convolutional codes from linear block codes over the finite semi-local ring F2r +vF2r , where v2 = v, are presented. In both cases, if the linear block code is systematic, then the resulting convolutional encoder is systematic, minimal, basic and non-catastrophic. The Hamming free distance of the convolutional code is bounded below by the minimum Hamming distance of the block code. New examples of binary convolutional codes that meet the Heller upper bound for systematic codes are given.

Keywords: Convolutional codes, semi-local ring, free distance, Heller bound.

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Authors: Azleena Mohd Kassim, Muhamad Rashidi A. Rahman, Yu-N. Cheah

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Knowledge-based e-mail systems focus on incorporating knowledge management approach in order to enhance the traditional e-mail systems. In this paper, we present a knowledgebased e-mail system called KS-Mail where people do not only send and receive e-mail conventionally but are also able to create a sense of knowledge flow. We introduce semantic processing on the e-mail contents by automatically assigning categories and providing links to semantically related e-mails. This is done to enrich the knowledge value of each e-mail as well as to ease the organization of the e-mails and their contents. At the application level, we have also built components like the service manager, evaluation engine and search engine to handle the e-mail processes efficiently by providing the means to share and reuse knowledge. For this purpose, we present the KS-Mail architecture, and elaborate on the details of the e-mail server and the application server. We present the ontology mapping technique used to achieve the e-mail content-s categorization as well as the protocols that we have developed to handle the transactions in the e-mail system. Finally, we discuss further on the implementation of the modules presented in the KS-Mail architecture.

Keywords: E-mail rating, knowledge-based system, ontology mapping, text categorization.

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Authors: Amid Ranjkesh, Milan Ambrožič, Samo Kralj

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We study the typical domain size and configuration character of a randomly perturbed system exhibiting continuous symmetry breaking. As a model system we use rod-like objects within a cubic lattice interacting via a Lebwohl–Lasher-type interaction. We describe their local direction with a headless unit director field. An example of such systems represents nematic LC or nanotubes. We further introduce impurities of concentration p, which impose the random anisotropy field-type disorder to directors. We study the domain-type pattern of molecules as a function of p, anchoring strength w between a neighboring director and impurity, temperature, history of samples. In simulations we quenched the directors either from the random or homogeneous initial configuration. Our results show that a history of system strongly influences: i) the average domain coherence length; and ii) the range of ordering in the system. In the random case the obtained order is always short ranged (SR). On the contrary, in the homogeneous case, SR is obtained only for strong enough anchoring and large enough concentration p. In other cases, the ordering is either of quasi long range (QLR) or of long range (LR). We further studied memory effects for the random initial configuration. With increasing external ordering field B either QLR or LR is realized.

Keywords: Lebwohl-Lasher model, liquid crystals, disorder, memory effect, orientational order.

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Authors: E. Karoui Chaabane, S. Hadouaj, K. Ghedira

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Inter-organizational Workflow (IOW) is commonly used to support the collaboration between heterogeneous and distributed business processes of different autonomous organizations in order to achieve a common goal. E-government is considered as an application field of IOW. The coordination of the different organizations is the fundamental problem in IOW and remains the major cause of failure in e-government projects. In this paper, we introduce a new coordination model for IOW that improves the collaboration between government administrations and that respects IOW requirements applied to e-government. For this purpose, we adopt a Multi-Agent approach, which deals more easily with interorganizational digital government characteristics: distribution, heterogeneity and autonomy. Our model integrates also different technologies to deal with the semantic and technologic interoperability. Moreover, it conserves the existing systems of government administrations by offering a distributed coordination based on interfaces communication. This is especially applied in developing countries, where administrations are not necessary equipped with workflow systems. The use of our coordination techniques allows an easier migration for an e-government solution and with a lower cost. To illustrate the applicability of the proposed model, we present a case study of an identity card creation in Tunisia.

Keywords: E-government, Inter-organizational workflow, Multi-agent systems, Semantic web services.

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Authors: Mohamed Omar

Abstract:

Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Keywords: Finite element analysis, seismic response, shapesmemory alloy, steel frame, superelasticity

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Authors: Mario Mastriani, Marcelo Naiouf

Abstract:

This paper introduces a Quantum Correlation Matrix Memory (QCMM) and Enhanced QCMM (EQCMM), which are useful to work with quantum memories. A version of classical Gram-Schmidt orthogonalisation process in Dirac notation (called Quantum Orthogonalisation Process: QOP) is presented to convert a non-orthonormal quantum basis, i.e., a set of non-orthonormal quantum vectors (called qudits) to an orthonormal quantum basis, i.e., a set of orthonormal quantum qudits. This work shows that it is possible to improve the performance of QCMM thanks QOP algorithm. Besides, the EQCMM algorithm has a lot of additional fields of applications, e.g.: Steganography, as a replacement Hopfield Networks, Bilevel image processing, etc. Finally, it is important to mention that the EQCMM is an extremely easy to implement in any firmware.

Keywords: Quantum Algebra, correlation matrix memory, Dirac notation, orthogonalisation.

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Authors: Mandhapati P. Raju, Siddhartha Khaitan

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In-core memory requirement is a bottleneck in solving large three dimensional Navier-Stokes finite element problem formulations using sparse direct solvers. Out-of-core solution strategy is a viable alternative to reduce the in-core memory requirements while solving large scale problems. This study evaluates the performance of various out-of-core sequential solvers based on multifrontal or supernodal techniques in the context of finite element formulations for three dimensional problems on a Windows platform. Here three different solvers, HSL_MA78, MUMPS and PARDISO are compared. The performance of these solvers is evaluated on a 64-bit machine with 16GB RAM for finite element formulation of flow through a rectangular channel. It is observed that using out-of-core PARDISO solver, relatively large problems can be solved. The implementation of Newton and modified Newton's iteration is also discussed.

Keywords: Out-of-core, PARDISO, MUMPS, Newton.

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm.

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Authors: Pei. P. Tan, Don. U.A. Galagedera, Elizabeth A.Maharaj

Abstract:

This paper examines predictability in stock return in developed and emergingmarkets by testing long memory in stock returns using wavelet approach. Wavelet-based maximum likelihood estimator of the fractional integration estimator is superior to the conventional Hurst exponent and Geweke and Porter-Hudak estimator in terms of asymptotic properties and mean squared error. We use 4-year moving windows to estimate the fractional integration parameter. Evidence suggests that stock return may not be predictable indeveloped countries of the Asia-Pacificregion. However, predictability of stock return insome developing countries in this region such as Indonesia, Malaysia and Philippines may not be ruled out. Stock return in the Thailand stock market appears to be not predictable after the political crisis in 2008.

Keywords: Asia-Pacific stock market, long-memory, return predictability, wavelet

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