Search results for: Shared Memory Parallel Computing

Authors: Yousef Daneshvar Rouyandozagh, Ece. K. Açikgöz

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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: Kuo-Yang Cheng, Yi-Lun Pan, Chang-Hsing Wu, His-En Yu, Hui-Shan Chen, Weicheng Huang

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The main mission of Ezilla is to provide a friendly interface to access the virtual machine and quickly deploy the high performance computing environment. Ezilla has been developed by Pervasive Computing Team at National Center for High-performance Computing (NCHC). Ezilla integrates the Cloud middleware, virtualization technology, and Web-based Operating System (WebOS) to form a virtual computer in distributed computing environment. In order to upgrade the dataset and speedup, we proposed the sensor observation system to deal with a huge amount of data in the Cassandra database. The sensor observation system is based on the Ezilla to store sensor raw data into distributed database. We adopt the Ezilla Cloud service to create virtual machines and login into virtual machine to deploy the sensor observation system. Integrating the sensor observation system with Ezilla is to quickly deploy experiment environment and access a huge amount of data with distributed database that support the replication mechanism to protect the data security.

Keywords: Cloud, Virtualization, Cassandra, WebOS

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Authors: Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress

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The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.

Keywords: Individual learning, collaborative knowledge building, systems theory, equilibration.

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: Analog circuits, digital circuits, memristors, neuromorphic computing systems.

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Authors: Sandeep Sharma, Sarabjit Singh, Meenakshi Sharma

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Load balancing is the process of improving the performance of a parallel and distributed system through a redistribution of load among the processors [1] [5]. In this paper we present the performance analysis of various load balancing algorithms based on different parameters, considering two typical load balancing approaches static and dynamic. The analysis indicates that static and dynamic both types of algorithm can have advancements as well as weaknesses over each other. Deciding type of algorithm to be implemented will be based on type of parallel applications to solve. The main purpose of this paper is to help in design of new algorithms in future by studying the behavior of various existing algorithms.

Keywords: Load balancing (LB), workload, distributed systems, Static Load balancing, Dynamic Load Balancing

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Authors: Lotfi Admane

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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: Aqeel S. Jaber, Abu Zaharin Ahmad, Ahmed N. Abdalla

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The artificial intelligent controller in power system plays as most important rule for many applications such as system operation and its control specially Load Frequency Controller (LFC). The main objective of LFC is to keep the frequency and tie-line power close to their decidable bounds in case of disturbance. In this paper, parallel fuzzy PI adaptive with conventional PD technique for Load Frequency Control system was proposed. PSO optimization method used to optimize both of scale fuzzy PI and tuning of PD. Two equal interconnected power system areas were used as a test system. Simulation results show the effectiveness of the proposed controller compared with different PID and classical fuzzy PI controllers in terms of speed response and damping frequency.

Keywords: Load frequency control, PSO, fuzzy control.

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Authors: K. Varesi, A. Radan

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In this paper, a new Genetic Algorithm (GA) based methodology is proposed to optimize the Degree of Hybridization (DOH) in a passenger parallel hybrid car. At first step, target parameters for the vehicle are decided and then using ADvanced VehIcle SimulatOR (ADVISOR) software, the variation pattern of these target parameters, across the different DOHs, is extracted. At the next step, a suitable cost function is defined and is optimized using GA. In this paper, also a new technique has been proposed for deciding the number of battery modules for each DOH, which leads to a great improvement in the vehicle performance. The proposed methodology is so simple, fast and at the same time, so efficient.

Keywords: Degree of Hybridization (DOH), Electric Motor, Emissions, Fuel Economy, Genetic Algorithm (GA), Hybrid ElectricVehicle (HEV), Vehicle Performance

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Authors: Khin Thida Latt, Mineo Kaneko, Yoichi Shinoda

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In Partitioned Optical Passive Stars POPS network,nodes and couplers become free after slot to slot in some computation.It is necessary to efficiently utilize free couplers and nodes to be cost effective. Improving parallelism, we present the fast data summation algorithm for multiple problem spaces on P OP S(g, g) with smaller number of nodes for the case of d =n = g. For the case of d >n > g, we simulate the calculation of large number of data items dedicated to larger system with many nodes on smaller system with smaller number of nodes. The algorithm is faster than the best know algorithm and using smaller number of nodes and groups make the system low cost and practical.

Keywords: Partitioned optical passive stars network, parallelcomputing, optical computing, data sum

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

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this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

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We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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Authors: César Camisón-Zornoza, Beatriz Forés-Julián, Alba Puig-Denia

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The literature has argued that firms based in industrial districts enjoy advantages for creating internal knowledge and absorbing external knowledge as a consequence of to the knowledge flows and spillovers that exist in the district. However, empirical evidence to show how belonging to an industrial district affects the business processes of creation and absorption of knowledge is scarce and, moreover, empirical research has not taken into account the influence of variations in the flows of knowledge circulating in each cluster. This study aims to extend empirical evidence on the effect that the stock of shared competencies in industrial districts has on the business processes of creation and absorption of knowledge, through data from an initial study on 952 firms and 35 industrial districts in Spain.

Keywords: Absorptive capacity, industrial district, knowledge creation, organisational learning

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Authors: Pedro M. A. Vitoriano, Tito. G. Amaral

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Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.

Keywords: AOI, automated optical inspection, SMD, surface mounting devices, pattern matching, parallel execution.

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Authors: Kewei Xu, Jens Friedrich, Kevin Dwinger, Wei Fan, Xijin Zhang

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Parallel Compressor Model (PCM) is a simplified approach to predict compressor performance with inlet distortions. In PCM calculation, it is assumed that the sub-compressors’ outlet static pressure is uniform and therefore simplifies PCM calculation procedure. However, if the compressor’s outlet duct is not long and straight, such assumption frequently induces error ranging from 10% to 15%. This paper provides a revised calculation method of PCM that can correct the error. The revised method employs energy equation, momentum equation and continuity equation to acquire needed parameters and replace the equal static pressure assumption. Based on the revised method, PCM is applied on two compression system with different blades types. The predictions of their performance in non-uniform inlet conditions are yielded through the revised calculation method and are employed to evaluate the method’s efficiency. Validating the results by experimental data, it is found that although little deviation occurs, calculated result agrees well with experiment data whose error ranges from 0.1% to 3%. Therefore, this proves the revised calculation method of PCM possesses great advantages in predicting the performance of the distorted compressor with limited exhaust duct.

Keywords: Parallel Compressor Model (PCM), Revised Calculation Method, Inlet Distortion, Outlet Unequal Pressure Distribution.

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

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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: Shuen-Tai Wang, Chin-Hung Li, Ying-Chuan Chen

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In recent years there has been renewal of interest in the relation between Green IT and Cloud Computing. The growing use of computers in cloud platform has caused marked energy consumption, putting negative pressure on electricity cost of cloud data center. This paper proposes an effective mechanism to reduce energy utilization in cloud computing environments. We present initial work on the integration of resource and power management that aims at reducing power consumption. Our mechanism relies on recalling virtualization services dynamically according to user-s virtualization request and temporarily shutting down the physical machines after finish in order to conserve energy. Given the estimated energy consumption, this proposed effort has the potential to positively impact power consumption. The results from the experiment concluded that energy indeed can be saved by powering off the idling physical machines in cloud platforms.

Keywords: Green IT, Cloud Computing, virtualization, power consumption.

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Authors: Tanuj Kumar, Rakesh Kumar Bajaj

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In the present paper, we analyze the vague reliability of k-out-of-n : G system (particularly, series and parallel system) with independent and non-identically distributed components, where the reliability of the components are unknown. The reliability of each component has been estimated using statistical confidence interval approach. Then we converted these statistical confidence interval into triangular intuitionistic fuzzy numbers. Based on these triangular intuitionistic fuzzy numbers, the reliability of the k-out-of-n : G system has been calculated. Further, in order to implement the proposed methodology and to analyze the results of k-out-of-n : G system, a numerical example has been provided.

Keywords: Vague set, vague reliability, triangular intuitionistic fuzzy number, k-out-of-n : G system, series and parallel system.

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Authors: Emilia Nercissians

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The paper attempts to contribute to the largely neglected social and anthropological discussion of technology development on the one hand, and to redirecting the emphasis in anthropology from primitive and exotic societies to problems of high relevance in contemporary era and how technology is used in everyday life. It draws upon multidimensional models of intelligence and ideal type formation. It is argued that the predominance of computational and cognitive cosmovisions have led to technology alienation. Injection of communicative competence in artificially intelligent systems and identity technologies in the coming information society are analyzed

Keywords: convergence, nomadic computing, solidarity, status.

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Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain

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One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.

Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread

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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: Hari Mohan Kushwaha, Santosh K. Sahu

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In the present study, analysis of heat transfer is carried out in the slip flow region for the fluid flowing between two parallel plates by employing the asymmetric heat fluxes at surface of the plates. The flow is assumed to be hydrodynamically and thermally fully developed for the analysis. The second order velocity slip and viscous dissipation effects are considered for the analysis. Closed form expressions are obtained for the Nusselt number as a function of Knudsen number and modified Brinkman number. The limiting condition of the present prediction for Kn = 0, Kn2 = 0, and Brq1 = 0 is considered and found to agree well with other analytical results.

Keywords: Knudsen Number, Modified Brinkman Number, Slip Flow, Velocity Slip.

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Authors: Mohammad Bsoul, Iain Phillips, Chris Hinde

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This paper is concerned with the design and implementation of MICOSim, an event-driven simulator written in Java for evaluating the performance of Grid entities (users, brokers and resources) under different scenarios such as varying the numbers of users, resources and brokers and varying their specifications and employed strategies.

Keywords: Grid computing, Economic Scheduling, Simulation, Event-Driven, Java.

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Authors: Xiaomei Wang, Shouming Zhong

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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: Imran Ihsan, Muhammad Abdul Qadir, Nadeem Iftikhar

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Mobile devices, which are progressively surrounded in our everyday life, have created a new paradigm where they interconnect, interact and collaborate with each other. This network can be used for flexible and secure coordinated sharing. On the other hand Grid computing provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In this paper, efforts are made to map the concepts of Grid on Ad-Hoc networks because both exhibit similar kind of characteristics like Scalability, Dynamism and Heterogeneity. In this context we propose “Mobile Ad-Hoc Services Grid – MASGRID".

Keywords: Mobile Ad-Hoc Networks, Grid Computing, Resource Discovery, Routing

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Authors: Weng Ming Chu

Abstract:

When faced with stochastic networks with an uncertain duration for their activities, the securing of network completion time becomes problematical, not only because of the non-identical pdf of duration for each node, but also because of the interdependence of network paths. As evidenced by Adlakha & Kulkarni [1], many methods and algorithms have been put forward in attempt to resolve this issue, but most have encountered this same large-size network problem. Therefore, in this research, we focus on network reduction through a Series/Parallel combined mechanism. Our suggested algorithm, named the Activity Network Reduction Algorithm (ANRA), can efficiently transfer a large-size network into an S/P Irreducible Network (SPIN). SPIN can enhance stochastic network analysis, as well as serve as the judgment of symmetry for the Graph Theory.

Keywords: Series/Parallel network, Stochastic network, Network reduction, Interdictive Graph, Complexity Index.

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Authors: S. Nagheli, N. Samani, D. A. Barry

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In this paper, the velocity potential and stream function of capture zone for a well field in an aquifer bounded by two parallel streams with or without a uniform regional flow of any directions are presented. The well field includes any number of extraction or injection wells or a combination of both types with any pumping rates. To delineate the capture envelope, the potential and streamlines equations are derived by conformal mapping method. This method can help us to release constrains of other methods. The equations can be applied as useful tools to design in-situ groundwater remediation systems, to evaluate the surface–subsurface water interaction and to manage the water resources.

Keywords: Complex potential, conformal mapping, groundwater remediation, image well theory, Laplace’s equation, superposition principle.

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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: Sana Hamdi, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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