Search results for: Heterogeneous Computing

Authors: Velid Demir, Mesut Akgün

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The lanthanum and zinc oxide were synthesized and then loaded with 6 wt% over γ-Al2O3 using the wet impregnation method. The samples were calcined at 900 °C to ensure a coherent structure with high catalytic performance. Characterization of the catalysts was verified by X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). The effect of catalysts on biodiesel content from jatropha oil was studied under supercritical conditions. The results showed that ZnO/γ-Al2O3 was the superior catalyst for jatropha oil with 98.05% biodiesel under reaction conditions of 7 min reaction time, 1:40 oil to methanol molar ratio, 6 wt% of catalyst loading, 90 bar of reaction pressure, and 300 °C of reaction temperature, compared to 95.50% with La2O3/γ-Al2O3 at the same parameters. For this study, ZnO/γ-Al2O3 was the most suitable catalyst due to performance and cost considerations.

Keywords: Biodiesel, heterogeneous catalyst, Jatropha oil, supercritical methanol, transesterification.

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Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: Social Network, link prediction, granular computing, Type-2 fuzzy sets.

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Authors: Nnamdi I. Nwulu, Shola G. Oroja

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It has become crucial over the years for nations to improve their credit scoring methods and techniques in light of the increasing volatility of the global economy. Statistical methods or tools have been the favoured means for this; however artificial intelligence or soft computing based techniques are becoming increasingly preferred due to their proficient and precise nature and relative simplicity. This work presents a comparison between Support Vector Machines and Artificial Neural Networks two popular soft computing models when applied to credit scoring. Amidst the different criteria-s that can be used for comparisons; accuracy, computational complexity and processing times are the selected criteria used to evaluate both models. Furthermore the German credit scoring dataset which is a real world dataset is used to train and test both developed models. Experimental results obtained from our study suggest that although both soft computing models could be used with a high degree of accuracy, Artificial Neural Networks deliver better results than Support Vector Machines.

Keywords: Artificial Neural Networks, Credit Scoring, SoftComputing Models, Support Vector Machines.

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Authors: José M. Cantera, Miguel Jiménez, Genoveva López, Javier Soriano

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With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation is exploited for either an individual element or a set of consecutive elements in a Web document and results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called SMC, enabling the development of mobility applications and services according to a channel model based on the principles of Services Oriented Architecture (SOA). It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation that prescribes a scheme for representing semantic markup files and a way of associating Web documents with these external annotations. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering. Semantic Web content adaptation is a way of adding value to Web contents and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).

Keywords: Semantic web, ubiquitous and mobile computing, web content transcoding. semantic mark-up, mobile computing, middleware and services.

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Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

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Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical generic sync middleware of low maintenance and operation costs is most wanted. To this demand, this paper presented a generic sync middleware system (GSMS), which has been developed, applied and optimized since 2006, holding the principles or advantages that it must be SyncML-compliant and transparent to data application layer logic without referring to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence of low cost. Regarding these hard commitments of developing GSMS, in this paper we stressed the significant optimization breakthrough of GSMS sync delay being well below a fraction of millisecond per record sync. A series of ultimate tests with GSMS sync performance were conducted for a persuasive example, in which the source relational database underwent a broad range of write loads (from one thousand to one million intensive writes within a few minutes). All these tests showed that the performance of GSMS is competent and smooth even under ultimate write loads.

Keywords: Heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization.

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Authors: Jeffrey A. Dunne, Kevin Ligozio

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In many applications there is a broad variety of information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color, and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion capabilities (such as the height, weight, and gender of a person). A service-oriented architecture has been designed and prototyped to support the fusion of information for such “object-centric" situations. It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of uncertainties, and minimize network bandwidth requirements.

Keywords: Data fusion, distributed computing, service-oriented architecture, SOA

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Authors: Yen-Cheng Chen, Fu-Chen Yang

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IETF defines mobility support in IPv6, i.e. MIPv6, to allow nodes to remain reachable while moving around in the IPv6 internet. When a node moves and visits a foreign network, it is still reachable through the indirect packet forwarding from its home network. This triangular routing feature provides node mobility but increases the communication latency between nodes. This deficiency can be overcome by using a Binding Update (BU) scheme, which let nodes keep up-to-date IP addresses and communicate with each other through direct IP routing. To further protect the security of BU, a Return Routability (RR) procedure was developed. However, it has been found that RR procedure is vulnerable to many attacks. In this paper, we will propose a lightweight RR procedure based on geometric computing. In consideration of the inherent limitation of computing resources in mobile node, the proposed scheme is developed to minimize the cost of computations and to eliminate the overhead of state maintenance during binding updates. Compared with other CGA-based BU schemes, our scheme is more efficient and doesn-t need nonce tables in nodes.

Keywords: Mobile IPv6, Binding update, Geometric computing.

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Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

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The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of a high performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice River catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: Flood prediction process, High performance computing, Online flood prediction system, Parallelization.

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Authors: Mohammad Ahmed Rehmatullah

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The aim of this paper is to discuss a low-cost methodology that can predict traffic flow conflicts and quantitatively rank crash expectancies (based on relative probability) for various traffic facilities. This paper focuses on the application of statistical distributions to model traffic flow and Monte Carlo techniques to simulate traffic and discusses how to create a tool in order to predict the possibility of a traffic crash. A low-cost data collection methodology has been discussed for the heterogeneous traffic flow that exists and a GIS platform has been proposed to thematically represent traffic flow from simulations and the probability of a crash. Furthermore, discussions have been made to reflect the dynamism of the model in reference to its adaptability, adequacy, economy, and efficiency to ensure adoption.

Keywords: Heterogeneous traffic data collection, Monte CarloSimulation, Traffic Flow Modeling, GIS.

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Authors: Stoyan Nedeltchev, Markus Schubert

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By means of the ultrafast X-ray tomography facility, data were obtained at different superficial gas velocities U_G in a bubble column (0.1 m in ID) operated with an air-deionized water system at ambient conditions. Raw reconstructed images were treated by both the information entropy (IE) and the reconstruction entropy (RE) algorithms in order to identify the main transition velocities in a bubble column. The IE values exhibited two well-pronounced minima at U_G=0.025 m/s and U_G=0.085 m/s identifying the boundaries of the homogeneous, transition and heterogeneous regimes. The RE extracted from the central region of the column’s cross-section exhibited only one characteristic peak at U_G=0.03 m/s, which was attributed to the transition from the homogeneous to the heterogeneous flow regime. This result implies that the transition regime is non-existent in the core of the column.

Keywords: Bubble column, ultrafast X-ray tomography, information entropy, reconstruction entropy.

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Authors: Sinnakkrishnan Perumal, Nitish Pandey

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Business transformation initiatives are required by any organization to jump from its normal mode of operation to the one that is suitable for the change in the environment such as competitive pressures, regulatory requirements, changes in labor market, etc., or internal such as changes in strategy/vision, changes in the capability, change in the management, etc. Recent advances in information technology in automating the business processes have the potential to transform an organization to provide it with a sustained competitive advantage. Process constitutes the skeleton of a business. Thus, for a business to exist and compete well, it is essential for the skeleton to be robust and agile. This paper details “transformation" from a business perspective, methodologies to bring about an effective transformation, process-based transformation, and the role of services computing in this. Further, it details the benefits that could be achieved through services computing.

Keywords: Business Transformation, Services Oriented Architecture, Business Processes, Process-based Transformation.

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Authors: Marinela Mircea

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The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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Authors: Toshinori Takabatake

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Recently, grid computing has been widely focused on the science, industry, and business fields, which are required a vast amount of computing. Grid computing is to provide the environment that many nodes (i.e., many computers) are connected with each other through a local/global network and it is available for many users. In the environment, to achieve data processing among nodes for any applications, each node executes mutual authentication by using certificates which published from the Certificate Authority (for short, CA). However, if a failure or fault has occurred in the CA, any new certificates cannot be published from the CA. As a result, a new node cannot participate in the gird environment. In this paper, an off-the-shelf scheme for dependable grid systems using virtualization techniques is proposed and its implementation is verified. The proposed approach using the virtualization techniques is to restart an application, e.g., the CA, if it has failed. The system can tolerate a failure or fault if it has occurred in the CA. Since the proposed scheme is implemented at the application level easily, the cost of its implementation by the system builder hardly takes compared it with other methods. Simulation results show that the CA in the system can recover from its failure or fault.

Keywords: grid computing, restarting application, certificate authority, virtualization, dependability.

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Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: Cloud Analyst, Cloud Computing, Join Idle Queue, Join Shortest Queue, Load balancing, Task Scheduling.

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: Handover, HetNets, interference, MADM, small cells, TOPSIS, weight.

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Authors: Jaimin Patel

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Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

Keywords: Cloud computing, encryption algorithm, secure hashing algorithm, brute force attack, birthday attack, plaintext attack, man-in-the-middle attack.

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Authors: Sajjad Hashemi, Seyyed Yasser Hashemi

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In today's world, success of most systems depend on the use of new technologies and information technology (IT) which aimed to increase efficiency and satisfaction of users. One of the most important systems that use information technology to deliver services is the education system. But for educational services in the form of E-learning systems, hardware and software equipment should be containing high quality, which requires substantial investment. Because the vast majority of educational establishments can not invest in this area so the best way for them is reducing the costs and providing the E-learning services by using cloud computing. But according to the novelty of the cloud technology, it can create challenges and concerns that the most noted among them are security issues. Security concerns about cloud-based E-learning products are critical and security measures essential to protect valuable data of users from security vulnerabilities in products. Thus, the success of these products happened if customers meet security requirements then can overcome security threats. In this paper tried to explore cloud computing and its positive impact on E- learning and put main focus to identify security issues that related to cloud-based E-learning efforts which have been improve security and provide solutions in management challenges.

Keywords: Cloud computing, E-Learning, Security.

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Authors: Karim Abouelmehdi, Loubna Dali, Elmoutaoukkil Abdelmajid, Hoda Elsayed Eladnani Fatiha, Benihssane Abderahim

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The security of cloud services is the concern of cloud service providers. In this paper, we will mention different classifications of cloud attacks referred by specialized organizations. Each agency has its classification of well-defined properties. The purpose is to present a high-level classification of current research in cloud computing security. This classification is organized around attack strategies and corresponding defenses.

Keywords: Cloud computing, security, classification, risk.

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Authors: Hyun-Ho Lee, Kee-Won Kim

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The arithmetic operations over GF(2m) have been extensively used in error correcting codes and public-key cryptography schemes. Finite field arithmetic includes addition, multiplication, division and inversion operations. Addition is very simple and can be implemented with an extremely simple circuit. The other operations are much more complex. The multiplication is the most important for cryptosystems, such as the elliptic curve cryptosystem, since computing exponentiation, division, and computing multiplicative inverse can be performed by computing multiplication iteratively. In this paper, we present a parallel computation algorithm that operates Montgomery multiplication over finite field using redundant basis. Also, based on the multiplication algorithm, we present an efficient semi-systolic multiplier over finite field. The multiplier has less space and time complexities compared to related multipliers. As compared to the corresponding existing structures, the multiplier saves at least 5% area, 50% time, and 53% area-time (AT) complexity. Accordingly, it is well suited for VLSI implementation and can be easily applied as a basic component for computing complex operations over finite field, such as inversion and division operation.

Keywords: Finite field, Montgomery multiplication, systolic array, cryptography.

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Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: Education, Information Technologies, IDT, awareness.

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Authors: M. Bohlouli, M. Analoui

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For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.

Keywords: Active Database, Grid Computing, ResourceRequirement Prediction, Scheduling,

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Authors: Drahoslava Janovska, Vladimir Janovsky, Kunio Tanabe

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A proof of convergence of a new continuation algorithm for computing the Analytic SVD for a large sparse parameter– dependent matrix is given. The algorithm itself was developed and numerically tested in [5].

Keywords: Analytic Singular Value Decomposition, large sparse parameter–dependent matrices, continuation algorithm of a predictorcorrector type.

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Authors: Marilyn Lim Chien Hui, Nabil Elmarzouqi, Chan Huah Yong

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This paper describes the authorization system architecture for Pervasive Grid environment. It discusses the characteristics of classical authorization system and requirements of the authorization system in pervasive grid environment as well. Based on our analysis of current systems and taking into account the main requirements of such pervasive environment, we propose new authorization system architecture as an extension of the existing grid authorization mechanisms. This architecture not only supports user attributes but also context attributes which act as a key concept for context-awareness thought. The architecture allows authorization of users dynamically when there are changes in the pervasive grid environment. For this, we opt for hybrid authorization method that integrates push and pull mechanisms to combine the existing grid authorization attributes with dynamic context assertions. We will investigate the proposed architecture using a real testing environment that includes heterogeneous pervasive grid infrastructures mapped over multiple virtual organizations. Various scenarios are described in the last section of the article to strengthen the proposed mechanism with different facilities for the authorization procedure.

Keywords: Pervasive Grid, Authorization System, Contextawareness, Ubiquity.

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Authors: Taehyun Yoon, Keechul Jung

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There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.

Keywords: Collision Detection, Computer Vision, Human Computer Interaction, Visual Hull

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Authors: T. Kjosmoen, T. Ryen, T. Eftestøl

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In biological and biomedical research motif finding tools are important in locating regulatory elements in DNA sequences. There are many such motif finding tools available, which often yield position weight matrices and significance indicators. These indicators, p-values and E-values, describe the likelihood that a motif alignment is generated by the background process, and the expected number of occurrences of the motif in the data set, respectively. The various tools often estimate these indicators differently, making them not directly comparable. One approach for comparing motifs from different tools, is computing the E-value as the product of the p-value and the number of possible alignments in the data set. In this paper we explore the combinatorics of the motif alignment models OOPS, ZOOPS, and ANR, and propose a generic algorithm for computing the number of possible combinations accurately. We also show that using the wrong alignment model can give E-values that significantly diverge from their true values.

Keywords: Motif alignment, combinatorics, p-value, E-value, OOPS, ZOOPS, ANR.

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Authors: Meenakshi Bheevgade, Rajendra M. Patrikar

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In today-s new technology era, cluster has become a necessity for the modern computing and data applications since many applications take more time (even days or months) for computation. Although after parallelization, computation speeds up, still time required for much application can be more. Thus, reliability of the cluster becomes very important issue and implementation of fault tolerant mechanism becomes essential. The difficulty in designing a fault tolerant cluster system increases with the difficulties of various failures. The most imperative obsession is that the algorithm, which avoids a simple failure in a system, must tolerate the more severe failures. In this paper, we implemented the theory of watchdog timer in a parallel environment, to take care of failures. Implementation of simple algorithm in our project helps us to take care of different types of failures; consequently, we found that the reliability of this cluster improves.

Keywords: Cluster, Fault tolerant, Grid, Grid ComputingSystem, Meta-computing.

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Authors: Daniel Gonzales, Zev Winkelman, Trung Tran, Ricardo Sanchez, Dulani Woods, John Hollywood

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We have developed a distributed computing capability, Digital Forensics Compute Cluster (DFORC2) to speed up the ingestion and processing of digital evidence that is resident on computer hard drives. DFORC2 parallelizes evidence ingestion and file processing steps. It can be run on a standalone computer cluster or in the Amazon Web Services (AWS) cloud. When running in a virtualized computing environment, its cluster resources can be dynamically scaled up or down using Kubernetes. DFORC2 is an open source project that uses Autopsy, Apache Spark and Kafka, and other open source software packages. It extends the proven open source digital forensics capabilities of Autopsy to compute clusters and cloud architectures, so digital forensics tasks can be accomplished efficiently by a scalable array of cluster compute nodes. In this paper, we describe DFORC2 and compare it with a standalone version of Autopsy when both are used to process evidence from hard drives of different sizes.

Keywords: Cloud computing, cybersecurity, digital forensics, Kafka, Kubernetes, Spark.

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Authors: Jefri Marzal, Hong Xie, Chun Che Fung

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Visibility problems are central to many computational geometry applications. One of the typical visibility problems is computing the view from a given point. In this paper, a linear time procedure is proposed to compute the visibility subsets from a corner of a rectangular prism in an orthogonal polyhedron. The proposed algorithm could be useful to solve classic 3D problems.

Keywords: Visibility, rectangular prism, orthogonal polyhedron.

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Authors: Belabbas Yagoubi, Yahya Slimani

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Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.

Keywords: Grid computing, load balancing, workload, tree based model.

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Authors: Hiroyuki Ohsaki, Makoto Imase

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In Grid computing, a data transfer protocol called GridFTP has been widely used for efficiently transferring a large volume of data. Currently, two versions of GridFTP protocols, GridFTP version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have been proposed in the GGF. GridFTP v2 supports several advanced features such as data streaming, dynamic resource allocation, and checksum transfer, by defining a transfer mode called X-block mode. However, in the literature, effectiveness of GridFTP v2 has not been fully investigated. In this paper, we therefore quantitatively evaluate performance of GridFTP v1 and GridFTP v2 using mathematical analysis and simulation experiments. We reveal the performance limitation of GridFTP v1, and quantitatively show effectiveness of GridFTP v2. Through several numerical examples, we show that by utilizing the data streaming feature, the average file transfer time of GridFTP v2 is significantly smaller than that of GridFTP v1.

Keywords: Grid Computing, GridFTP, Performance Evaluation, Queuing Theory.

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