Search results for: computers with high memory.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6198

Search results for: computers with high memory.

6108 A Survey on Data-Centric and Data-Aware Techniques for Large Scale Infrastructures

Authors: Silvina Caíno-Lores, Jesús Carretero

Abstract:

Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: Co-scheduling, data-centric, data-intensive, data locality, in-memory storage, large scale.

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6107 Concurrent Approach to Data Parallel Model using Java

Authors: Bala Dhandayuthapani Veerasamy

Abstract:

Parallel programming models exist as an abstraction of hardware and memory architectures. There are several parallel programming models in commonly use; they are shared memory model, thread model, message passing model, data parallel model, hybrid model, Flynn-s models, embarrassingly parallel computations model, pipelined computations model. These models are not specific to a particular type of machine or memory architecture. This paper expresses the model program for concurrent approach to data parallel model through java programming.

Keywords: Concurrent, Data Parallel, JDK, Parallel, Thread

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6106 A Technique for Execution of Written Values on Shared Variables

Authors: Parvinder S. Sandhu, Vijay K. Banga, Prateek Gupta, Amit Verma

Abstract:

The current paper conceptualizes the technique of release consistency indispensable with the concept of synchronization that is user-defined. Programming model concreted with object and class is illustrated and demonstrated. The essence of the paper is phases, events and parallel computing execution .The technique by which the values are visible on shared variables is implemented. The second part of the paper consist of user defined high level synchronization primitives implementation and system architecture with memory protocols. There is a proposition of techniques which are core in deciding the validating and invalidating a stall page .

Keywords: synchronization objects, barrier, phases and events, shared memory

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6105 Attempt to Reuse Used-PCs as Distributed Storage

Authors: Toshiya Kawato, Shin-ichi Motomura, Masayuki Higashino, Takao Kawamura

Abstract:

Storage for storing data is indispensable. If a storage capacity becomes insufficient, we can increase its capacity by adding new disks. It is, however, difficult to add a new disk when a budget is not enough. On the other hand, there are many unused idle resources such as used personal computers despite those use value. In order to solve those problems, used personal computers can be reused as storage. In this paper, we attempt to reuse used-PCs as a distributed storage. First, we list up the characteristics of used-PCs and design a storage system that utilizes its characteristics. Next, we experimentally implement an auto-construction system that automatically constructs a distributed storage environment in used-PCs.

Keywords: Distributed storage, used personal computer, idle resource, auto construction.

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6104 In vivo Histomorphometric and Corrosion Analysis of Ti-Ni-Cr Shape Memory Alloys in Rabbits

Authors: T. Ahmed, Z. Butt, M. Ali, S. Attiq, M. Ali

Abstract:

A series of Ti based shape memory alloys with composition of Ti50Ni49Cr1, Ti50Ni47Cr3 and Ti50Ni45Cr5 were developed by vacuum arc-melting under a purified argon atmosphere. The histometric and corrosion evaluation of Ti-Ni-Cr shape memory alloys have been considered in this research work. The alloys were developed by vacuum arc melting and implanted subcutaneously in rabbits for 4, 8 and 12 weeks. Metallic implants were embedded in order to determine the outcome of implantation on histometric and corrosion evaluation of Ti-Ni-Cr metallic strips. Encapsulating membrane formation around the alloys was minimal in the case of all materials. After histomorphometric analyses it was possible to demonstrate that there were no statistically significant differences between the materials. Corrosion rate was also determined in this study which is within acceptable range. The results showed the Ti- Ni-Cr alloy was neither cytotoxic, nor have any systemic reaction on living system in any of the test performed. Implantation shows good compatibility and a potential of being used directly in vivo system.

Keywords: Shape memory alloy, Ti-Ni-Fe, histomorphometric, corrosion.

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6103 On Dialogue Systems Based on Deep Learning

Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: Dialogue management, response generation, reinforcement learning, deep learning, evaluation.

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6102 An Approach for a Bidding Process Knowledge Capitalization

Authors: R. Chalal, A. R. Ghomari

Abstract:

Preparation and negotiation of innovative and future projects can be characterized as a strategic-type decision situation, involving many uncertainties and an unpredictable environment. We will focus in this paper on the bidding process. It includes cooperative and strategic decisions. Our approach for bidding process knowledge capitalization is aimed at information management in project-oriented organizations, based on the MUSIC (Management and Use of Co-operative Information Systems) model. We will show how to capitalize the company strategic knowledge and also how to organize the corporate memory. The result of the adopted approach is improvement of corporate memory quality.

Keywords: Bidding process, corporate memory, Knowledge capitalization, knowledge acquisition, strategic decisions.

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6101 Performance Assessment of a Variable-Flux Permanent-Magnet Memory Motor

Authors: Michel Han, Christophe Besson, Alain Savary, Yvan Becher

Abstract:

The variable flux permanent magnet synchronous motor (VF-PMSM), also called "Memory Motor", is a new generation of motor capable of modifying the magnetization state with short pulses of current during operation or standstill. The impact of such operation is the expansion of the operating range in the torque-speed characteristic and an improvement in energy efficiency at high-speed in comparison to conventional permanent magnet synchronous machines (PMSMs). This paper reviews the operating principle and the unique features of the proposed memory motor. The benefits of this concept are highlighted by comparing the performance of the rotor of the VF-PMSM to that of two PM rotors that are typically found in the industry. The investigation emphasizes the properties of the variable magnetization and presents the comparison of the torque-speed characteristic with the capability of loss reduction in a VF-PMSM by means of experimental results, especially when tests are conducted under identical conditions for each rotor (same stator, same inverter and same experimental setup). The experimental results demonstrated that the VF-PMSM gives an additional degree of freedom to optimize the efficiency over a wide speed range. Thus, with a design easy to manufacture and with the possibility of controlling the magnetization and the demagnetization of the magnets during operations, the VF-PMSM can be interesting for various applications.

Keywords: Efficiency, magnetization state, memory motors, performances, permanent-magnet, synchronous machine, variable-flux, variable magnetization, wide speed application.

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6100 A Tabu Search Heuristic for Scratch-Pad Memory Management

Authors: Maha Idrissi Aouad, Rene Schott, Olivier Zendra

Abstract:

Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.

Keywords: Energy consumption, memory allocation management, optimization, tabu search heuristic.

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6099 Association of Sensory Processing and Cognitive Deficits in Children with Autism Spectrum Disorders – Pioneer Study in Saudi Arabia

Authors: Rana M. Zeina, Laila AL-Ayadhi, Shahid Bashir

Abstract:

The association between sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a Neuropsychological Test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/little circle (BLC), Simple Reaction Time (SRT) Intra /Extra dimensional set shift (IED), Spatial recognition memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. ASDs individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to a stimulus.

Keywords: Visual memory, Attention, Autism Spectrum Disorders (ASDs).

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6098 A Probabilistic View of the Spatial Pooler in Hierarchical Temporal Memory

Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

Abstract:

In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: Hierarchical Temporal Memory, HTM, Learning Algorithms, Machine Learning, Spatial Pooler.

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6097 Solving 94-bit ECDLP with 70 Computers in Parallel

Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

Abstract:

Elliptic curve discrete logarithm problem(ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard’s rho method to evaluate the security of ECDLP on Barreto-Naehrig(BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard’s rho method, BN curve, Montgomery multiplication.

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6096 An Enhanced Slicing Algorithm Using Nearest Distance Analysis for Layer Manufacturing

Authors: M. Vatani, A. R. Rahimi, F. Brazandeh, A. Sanati nezhad

Abstract:

Although the STL (stereo lithography) file format is widely used as a de facto industry standard in the rapid prototyping industry due to its simplicity and ability to tessellation of almost all surfaces, but there are always some defects and shortcoming in their usage, which many of them are difficult to correct manually. In processing the complex models, size of the file and its defects grow extremely, therefore, correcting STL files become difficult. In this paper through optimizing the exiting algorithms, size of the files and memory usage of computers to process them will be reduced. In spite of type and extent of the errors in STL files, the tail-to-head searching method and analysis of the nearest distance between tails and heads techniques were used. As a result STL models sliced rapidly, and fully closed contours produced effectively and errorless.

Keywords: Layer manufacturing, STL files, slicing algorithm, nearest distance analysis.

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6095 SC-LSH: An Efficient Indexing Method for Approximate Similarity Search in High Dimensional Space

Authors: Sanaa Chafik, ImaneDaoudi, Mounim A. El Yacoubi, Hamid El Ouardi

Abstract:

Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: Approximate Nearest Neighbor Search, Content based image retrieval (CBIR), Curse of dimensionality, Locality sensitive hashing, Multidimensional indexing, Scalability.

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6094 Mathematical Modeling of Current Harmonics Caused by Personal Computers

Authors: Rana Abdul Jabbar Khan, Muhammad Akmal

Abstract:

Personal computers draw non-sinusoidal current with odd harmonics more significantly. Power Quality of distribution networks is severely affected due to the flow of these generated harmonics during the operation of electronic loads. In this paper, mathematical modeling of odd harmonics in current like 3rd, 5th, 7th and 9th influencing the power quality has been presented. Live signals have been captured with the help of power quality analyzer for analysis purpose. The interesting feature is that Total Harmonic Distortion (THD) in current decreases with the increase of nonlinear loads has been verified theoretically. The results obtained using mathematical expressions have been compared with the practical results and exciting results have been found.

Keywords: Harmonic Distortion, Mathematical Modeling, Power Quality.

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6093 Switching Behaviors of TiN/HfOx/Pt Based RRAM

Authors: B. B. Weng, Z. Fang, Z. X. Chen, X. P. Wang, G. Q. Lo, D. L. Kwong

Abstract:

Resistive Random Access Memory (RRAM) had received great amount of attention from various research efforts in recent years, owing to its promising performance as a next generation memory device. In this paper, samples based on TiN/HfOx/Pt stack were prepared and its electrical switching behaviors were characterized and discussed in brief.

Keywords: HfOx, resistive switching, RRAM.

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6092 Crossover Memories and Code-Switching in the Narratives of Arabic-Hebrew and Hebrew-English Bilingual Adults in Israel

Authors: Amani Jaber-Awida

Abstract:

This study examines two bilingual phenomena in the narratives of Arabic Hebrew and Hebrew-English bilingual adults in Israel: CO memories and code-switching (CS). The study examined these phenomena in the context of autobiographical memory, using a cue word technique. Student experimenters held two sessions in the homes of the participants. In separate language sessions, the participant was asked to look first at each of 16 cue words and then to state a concrete memory. After stating the memory, participants reported whether their memories were in the same language of the experiment session or different. Memories were classified as ‘Crossovers’ (CO) or ‘Same Language’ (SL) according to participants' self-reports. Participants were also required to elaborate about the setting, interlocutors and other languages involved in the specific memory. Beyond replicating the procedure of cuing technique, one memory from a specific lifespan period was chosen per participant, and the participant was required to provide further details about it. For the more detailed memories, CS count was conducted. Both bilingual groups confirmed the Reminiscence Bump phenomenon, retrieving more memories in the 10-30 age period. CO memories prevailed in second language sessions (L2). Same language memories were more abundant in first language sessions (L1). Higher CS frequency was found in L2 sessions. Finally, as predicted, 'individual' CS was prevalent in L2 sessions, but 'community-based' CS was not higher in L1 sessions. The two bilingual measures in this study, crossovers, and CS came from different research traditions, the former from an experimental paradigm in the psychology of autobiographical memory based on self-reported judgments, the latter a behavioral measure from linguistics. This merger of approaches offers new insight into the field of bilingual autobiographical memory. In addition, the study attempted to shed light on the investigation of motivations for CS, beginning with Walters’ SPPL Model and concluding with a distinction between ‘community-based’ and individual motivations.

Keywords: Autobiographical memory, code-switching, crossover memories, reminiscence bump.

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6091 An Efficient Approach to Mining Frequent Itemsets on Data Streams

Authors: Sara Ansari, Mohammad Hadi Sadreddini

Abstract:

The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our approach SFIDS has been developed based on FIDS algorithm. The main attempts were to keep some advantages of the previous approach and resolve some of its drawbacks, and consequently to improve run time and memory consumption. Our approach has the following advantages: using a data structure similar to lattice for keeping frequent itemsets, separating regions from each other with deleting common nodes that results in a decrease in search space, memory consumption and run time; and Finally, considering CPU constraint, with increasing arrival rate of data that result in overloading system, SFIDS automatically detect this situation and discard some of unprocessing data. We guarantee that error of results is bounded to user pre-specified threshold, based on a probability technique. Final results show that SFIDS algorithm could attain about 50% run time improvement than FIDS approach.

Keywords: Data stream, frequent itemset, stream mining.

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6090 An E-learning System Architecture based on Cloud Computing

Authors: Md. Anwar Hossain Masud, Xiaodi Huang

Abstract:

The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.

Keywords: Architecture, Cloud Computing, E-learning, Information Technology

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6089 Analysis of Multilayer Neural Network Modeling and Long Short-Term Memory

Authors: Danilo López, Nelson Vera, Luis Pedraza

Abstract:

This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: Neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis.

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6088 ‘Memory Mate’ as Boundary Object in Cancer Treatment for Patients with Dementia

Authors: Rachel Hurdley, Jane Hopkinson

Abstract:

This article is based on observation of a cross-disciplinary, cross-institutional team that worked on an intervention called ‘Memory Mate’ for use in a UK Cancer Centre. This aimed to improve treatment outcomes for patients who had comorbid dementia or other memory impairment. Comorbid patients present ambiguous, spoiled identities, problematising the boundaries of health specialisms and frames of understanding. Memory Mate is theorised as a boundary object facilitating service transformation by changing relations between oncology and mental health care practice. It crosses the boundaries between oncology and mental health. Its introduction signifies an important step in reconfiguring relations between the specialisms. As a boundary object, it contains parallel, even contesting worlds, with potential to enable an eventual synthesis of the double stigma of cancer and dementia. Memory Mate comprises physical things, such as an animation, but its principal value is in the interaction it initiates across disciplines and services. It supports evolution of practices to address a newly emergent challenge for health service provision, namely the cancer patient with comorbid dementia/cognitive impairment. Getting clinicians from different disciplines working together on a practical solution generates a dialogue that can shift professional identity and change the culture of practice.

Keywords: Boundary object, cancer, dementia, interdisciplinary teams.

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6087 Small Sample Bootstrap Confidence Intervals for Long-Memory Parameter

Authors: Josu Arteche, Jesus Orbe

Abstract:

The log periodogram regression is widely used in empirical applications because of its simplicity, since only a least squares regression is required to estimate the memory parameter, d, its good asymptotic properties and its robustness to misspecification of the short term behavior of the series. However, the asymptotic distribution is a poor approximation of the (unknown) finite sample distribution if the sample size is small. Here the finite sample performance of different nonparametric residual bootstrap procedures is analyzed when applied to construct confidence intervals. In particular, in addition to the basic residual bootstrap, the local and block bootstrap that might adequately replicate the structure that may arise in the errors of the regression are considered when the series shows weak dependence in addition to the long memory component. Bias correcting bootstrap to adjust the bias caused by that structure is also considered. Finally, the performance of the bootstrap in log periodogram regression based confidence intervals is assessed in different type of models and how its performance changes as sample size increases.

Keywords: bootstrap, confidence interval, log periodogram regression, long memory.

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6086 Normalizing Logarithms of Realized Volatility in an ARFIMA Model

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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6085 Memristor: The Missing Circuit Element and its Application

Authors: Vishnu Pratap Singh Kirar

Abstract:

Memristor is also known as the fourth fundamental passive circuit element. When current flows in one direction through the device, the electrical resistance increases and when current flows in the opposite direction, the resistance decreases. When the current is stopped, the component retains the last resistance that it had, and when the flow of charge starts again, the resistance of the circuit will be what it was when it was last active. It behaves as a nonlinear resistor with memory. Recently memristors have generated wide research interest and have found many applications. In this paper we survey the various applications of memristors which include non volatile memory, nanoelectronic memories, computer logic, neuromorphic computer architectures low power remote sensing applications, crossbar latches as transistor replacements, analog computations and switches.

Keywords: Memristor, non-volatile memory, arithmatic operation, programmable resistor.

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6084 ALD HfO2 Based RRAM with Ti Capping

Authors: B. B. Weng, Z. Fang, Z. X. Chen, X. P. Wang, G. Q. Lo, D. L. Kwong

Abstract:

HfOx based Resistive Random Access Memory (RRAM) is one of the most widely studied material stack due to its promising performances as an emerging memory technology. In this work, we systematically investigated the effect of metal capping layer by preparing sample devices with varying thickness of Ti cap and comparing their operating parameters with the help of an Agilent-B1500A analyzer.

Keywords: HfOx, resistive switching, RRAM, metal capping.

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6083 An Interactive e-Learning Management System (e-LMS): A Solution to Tanzanian Secondary Schools' Education

Authors: A. Ellen Kalinga, R. B. Burchard Bagile, Lena Trojer

Abstract:

Information and Communications Technologies (ICT) has been integrated in education in many developing and developed countries alike, but the use of ICT in Tanzanian schools is dismal. Many Tanzanian secondary schools have no computers. The few schools with computers use them primarily for secretarial services and computer literacy training. The Tanzanian education system at other levels like secondary school level has to undergo substantial transformation, underscored by the growing application of new information and communication technology. This paper presents the e-readiness survey result from secondary schools in Tanzania. The paper also suggests how Tanzania can make use of the few present ICT resources to support and improve teaching and learning functions to improve performance and acquisition of knowledge by using e-Learning Management System (e-LMS).

Keywords: e-Learning, ICT, Object-Oriented, Participatorydesign.

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6082 Prospective Class Teachers- Computer Experiences and Computer Attitudes

Authors: L. Deniz

Abstract:

The main purpose of the research is to investigate the computer experiences and computer attitudes of prospective class teachers. The research also investigated the differences between computer attitudes and computer experiences, computer competencies and the influence of genders. Ninety prospective class teachers participated in the research. Computer Attitude Scale- Marmara (CAS-M), and a questionnaire, about their computer experiences, and opinions toward the use of computers in the classroom setting, were administrated. The major findings are as follows: (1) 62% of prospective class teachers have computer at home; (2) 50% of the computer owners have computers less than three years; (3) No significant differences were found between computer attitudes and gender; (4) Differences were found between general computer attitudes and computer liking attitudes of prospective class teachers based on their computer competencies in favor of more competent ones.

Keywords: Computer attitude, computer experience, prospective class teacher

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6081 Improving Worm Detection with Artificial Neural Networks through Feature Selection and Temporal Analysis Techniques

Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

Abstract:

Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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6080 Sustainable Renovation and Restoration of the Rural Based on the View Point of Psychology

Authors: Luo Jin, Jin Fang

Abstract:

Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it is failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: The rural, sustainable renovation, restoration, psychology, memory.

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6079 Hopfield Network as Associative Memory with Multiple Reference Points

Authors: Domingo López-Rodríguez, Enrique Mérida-Casermeiro, Juan M. Ortiz-de-Lazcano-Lobato

Abstract:

Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the retrieving phase. In this paper, a method to avoid spurious patterns is presented and studied, and an explanation of the previously mentioned effect is given. Another technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network with this technique is provided.

Keywords: Associative memory, Hopfield network, network capacity, spurious patterns.

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