Search results for: distributed algorithms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3865

Search results for: distributed algorithms

2515 Analysis of Exponential Nonuniform Transmission Line Parameters

Authors: Mounir Belattar

Abstract:

In this paper the Analysis of voltage waves that propagate along a lossless exponential nonuniform line is presented. For this analysis the parameters of this line are assumed to be varying function of the distance x along the line from the source end. The approach is based on the tow-port networks cascading presentation to derive the ABDC parameters of transmission using Picard-Carson Method which is a powerful method in getting a power series solution for distributed network because it is easy to calculate poles and zeros and solves differential equations such as telegrapher equations by an iterative sequence. So the impedance, admittance voltage and current along the line are expanded as a Taylor series in x/l where l is the total length of the line to obtain at the end, the main transmission line parameters such as voltage response and transmission and reflexion coefficients represented by scattering parameters in frequency domain.

Keywords: ABCD parameters, characteristic impedance exponential nonuniform transmission line, Picard-Carson's method, S parameters, Taylor's series

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2514 Seroprevalence of Cytomegalovirus among Pregnant Women in Islamabad, Pakistan

Authors: Hassan Waseem

Abstract:

Cytomegalovirus (CMV) is ubiquitously distributed viral agent responsible for different clinical manifestations that may vary according to the immunologic status of the patient. CMV can cause morbidity and mortality among fetuses and patients with compromised immune system. A cross-sectional study was carried out in Islamabad to investigate the prevalence and risk factors associated with CMV infection among pregnant women. Blood samples of 172 pregnant women visiting Mother and Child Healthcare, Pakistan Institute of Medical Sciences (PIMS) Islamabad were taken. In present study, serum samples of the women were checked for CMV-specific IgG and IgM antibodies by enzyme linked immunosorbent assay (ELISA). Clinical, obstetrical and socio-demographical characteristics of the women were collected by using structured questionnaires. Out of 172 pregnant women included in the study, 171 (99.4%) were CMV specific IgG positive and 30 (17.4%) were found positive for CMV-IgM antibodies. The CMV has taken an endemic form in Pakistan so, routine screening of CMV among pregnant women is recommended.

Keywords: Cytomegalovirus, blood transfusion, ELISA, seroprevalence

Procedia PDF Downloads 350
2513 Quality Fabric Optimization Using Genetic Algorithms

Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

Abstract:

Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

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2512 Context-Aware Recommender System Using Collaborative Filtering, Content-Based Algorithm and Fuzzy Rules

Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

Abstract:

Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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2511 Using Historical Data for Stock Prediction

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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2510 Soil Reinforcement by Fibers Using Triaxial Compression Test

Authors: Negadi Kheira, Arab Ahmed, Kamal Elbokl Mohamed, Setti Fatima

Abstract:

In order to evaluate influences of roots on soil shear strength, monotonic drained and undrained triaxial laboratory tests were carried out on reconstituted specimens at various confining pressure (σc’=50, 100, 200, 300, 400 kPa) and a constant relative density (Dr = 50%). Reinforcement of soil by fibrous roots is crucial for preventing soil erosion and degradation. Therefore, we investigated soil reinforcement by roots of acacia planted in the area of Chlef where shallow landslides and slope instability are frequent. These roots were distributed in soil in two forms: vertically and horizontally. The monotonic test results showed that roots have more impacts on the soil shear strength than the friction angle, and the presence of roots in soil substantially increased the soil shear strength. Also, the results showed that the contribution of roots on the shear strength mobilized increases with increase in the confining pressure.

Keywords: soil, monotonic, triaxial test, root fiber, undrained

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2509 Using Cooperation Approaches at Different Levels of Artificial Bee Colony Method

Authors: Vahid Zeighami, Mohsen Ghsemi, Reza Akbari

Abstract:

In this work, a Multi-Level Artificial Bee Colony (called MLABC) is presented. In MLABC two species are used. The first species employs n colonies in which each of the them optimizes the complete solution vector. The cooperation between these colonies is carried out by exchanging information through a leader colony, which contains a set of elite bees. The second species uses a cooperative approach in which the complete solution vector is divided to k sub-vectors, and each of these sub-vectors is optimized by a a colony. The cooperation between these colonies is carried out by compiling sub-vectors into the complete solution vector. Finally, the cooperation between two species is obtained by exchanging information between them. The proposed algorithm is tested on a set of well known test functions. The results show that MLABC algorithms provide efficiency and robustness to solve numerical functions.

Keywords: artificial bee colony, cooperative, multilevel cooperation, vector

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2508 Determination of the Botanical Origin of Honey by the Artificial Neural Network Processing of PARAFAC Scores of Fluorescence Data

Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

Abstract:

Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and artificial neural networks (ANN) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. Fluorescence spectra were described with a six-component PARAFAC model, and PARAFAC scores were further processed with two types of ANN’s (feed-forward network and self-organizing maps) to obtain algorithms for classification of honey on the basis of their botanical origin. Both ANN’s detected fake honey samples with 100% sensitivity and specificity.

Keywords: honey, fluorescence, PARAFAC, artificial neural networks

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2507 Study on the Efficient Routing Algorithms in Delay-Tolerant Networks

Authors: Si-Gwan Kim

Abstract:

In Delay Tolerant Networks (DTN), there may not exist an end-to-end path between source and destination at the time of message transmission. Employing ‘Store Carry and Forward’ delivery mechanism for message transmission in such networks usually incurs long message delays. In this paper, we present the modified Binary Spray and Wait (BSW) routing protocol that enhances the performance of the original one. Our proposed algorithm adjusts the number of forward messages depending on the number of neighbor nodes. By using beacon messages periodically, the number of neighbor nodes can be managed. The simulation using ONE simulator results shows that our modified version gives higher delivery ratio and less latency as compared to BSW.

Keywords: delay tolerant networks, store carry and forward, one simulator, binary spray and wait

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2506 Branding Destination for Major Event: A Case Study of Liverpool as the 2008 European Capital of Culture

Authors: Yi-De Liu

Abstract:

Destination branding is a popular practice adopted by many cities in the context of intensified tourism competition. However, branding for major event is a relatively new domain in the studies of destination marketing. Based on a case study of Liverpool as the 2008 European Capital of Culture, the aim of this paper is to explore the effectiveness of the key branding campaign - the ‘Look of the City’ programme. This study looks at quantitative data collected from on-street face-to-face survey. 611 questionnaires were distributed to and collected from local residents, visitors from the immediate hinterland, domestic tourists and overseas visitors. The analysis is done, first by investigating respondents’ impression on the Liverpool 08 brand and the branding campaign, and then by exploring the effects of campaign. The positioning of Liverpool compared with other similar cities is addressed in the end. The final section extracts lessons from this empirical investigation.

Keywords: destination branding, major event, European capital of culture, Liverpool

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2505 An Improvement of Multi-Label Image Classification Method Based on Histogram of Oriented Gradient

Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

Abstract:

Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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2504 Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

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2503 Inverted Diameter-Limit Thinning: A Promising Alternative for Mixed Populus tremuloides Stands Management

Authors: Ablo Paul Igor Hounzandji, Benoit Lafleur, Annie DesRochers

Abstract:

Introduction: Populus tremuloides [Michx] regenerates rapidly and abundantly by root suckering after harvest, creating stands with interconnected stems. Pre-commercial thinning can be used to concentrate growth on fewer stems to reach merchantability faster than un-thinned stands. However, conventional thinning methods are typically designed to reach even spacing between residual stems (1,100 stem ha⁻¹, evenly distributed), which can lead to treated stands consisting of weaker/smaller stems compared to the original stands. Considering the nature of P. tremuloides's regeneration, with large underground biomass of interconnected roots, aiming to keep the most vigorous and largest stems, regardless of their spatial distribution, inverted diameter-limit thinning could be more beneficial to post-thinning stand productivity because it would reduce the imbalance between roots and leaf area caused by thinning. Aims: This study aimed to compare stand and stem productivity of P. tremuloides stands thinned with a conventional thinning treatment (CT; 1,100 stem ha⁻¹, evenly distributed), two levels of inverted diameter-limit thinning (DL1 and DL2, keeping the largest 1100 or 2200 stems ha⁻¹, respectively, regardless of their spatial distribution) and a control unthinned treatment. Because DL treatments can create substantial or frequent gaps in the thinned stands, we also aimed to evaluate the potential of this treatment to recreate mixed conifer-broadleaf stands by fill-planting Picea glauca seedlings. Methods: Three replicate 21 year-old sucker-regenerated aspen stands were thinned in 2010 according to four treatments: CT, DL1, DL2, and un-thinned control. Picea glauca seedlings were underplanted in gaps created by the DL1 and DL2 treatments. Stand productivity per hectare, stem quality (diameter and height, volume stem⁻¹) and survival and height growth of fill-planted P. glauca seedlings were measured 8 year post-treatments. Results: Productivity, volume, diameter, and height were better in the treated stands (CT, DL1, and DL2) than in the un-thinned control. Productivity of CT and DL1 stands was similar 4.8 m³ ha⁻¹ year⁻¹. At the tree level, diameter and height of the trees in the DL1 treatment were 5% greater than those in the CT treatment. The average volume of trees in the DL1 treatment was 11% higher than the CT treatment. Survival after 8 years of fill planted P. glauca seedlings was 2% greater in the DL1 than in the DL2 treatment. DL1 treatment also produced taller seedlings (+20 cm). Discussion: Results showed that DL treatments were effective in producing post-thinned stands with larger stems without affecting stand productivity. In addition, we showed that these treatments were suitable to introduce slower growing conifer seedlings such as Picea glauca in order to re-create or maintain mixed stands despite the aggressive nature of P. tremuloides sucker regeneration.

Keywords: Aspen, inverted diameter-limit, mixed forest, populus tremuloides, silviculture, thinning

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2502 Software Quality Assurance in Network Security using Cryptographic Techniques

Authors: Sidra Shabbir, Ayesha Manzoor, Mehreen Sirshar

Abstract:

The use of the network communication has imposed serious threats to the security of assets over the network. Network security is getting more prone to active and passive attacks which may result in serious consequences to data integrity, confidentiality and availability. Various cryptographic techniques have been proposed in the past few years to combat with the concerned problem by ensuring quality but in order to have a fully secured network; a framework of new cryptosystem was needed. This paper discusses certain cryptographic techniques which have shown far better improvement in the network security with enhanced quality assurance. The scope of this research paper is to cover the security pitfalls in the current systems and their possible solutions based on the new cryptosystems. The development of new cryptosystem framework has paved a new way to the widespread network communications with enhanced quality in network security.

Keywords: cryptography, network security, encryption, decryption, integrity, confidentiality, security algorithms, elliptic curve cryptography

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2501 Free Vibration and Buckling of Rectangular Plates under Nonuniform In-Plane Edge Shear Loads

Authors: T. H. Young, Y. J. Tsai

Abstract:

A method for determining the stress distribution of a rectangular plate subjected to two pairs of arbitrarily distributed in-plane edge shear loads is proposed, and the free vibration and buckling of such a rectangular plate are investigated in this work.  The method utilizes two stress functions to synthesize the stress-resultant field of the plate with each of the stress functions satisfying the biharmonic compatibility equation. The sum of stress-resultant fields due to these two stress functions satisfies the boundary conditions at the edges of the plate, from which these two stress functions are determined. Then, the free vibration and buckling of the rectangular plate are investigated by the Galerkin method. Numerical results obtained by this work are compared with those appeared in the literature, and good agreements are observed.

Keywords: stress analysis, free vibration, plate buckling, nonuniform in-plane edge shear

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2500 A New Floating Point Implementation of Base 2 Logarithm

Authors: Ahmed M. Mansour, Ali M. El-Sawy, Ahmed T. Sayed

Abstract:

Logarithms reduce products to sums and powers to products; they play an important role in signal processing, communication and information theory. They are primarily used for hardware calculations, handling multiplications, divisions, powers, and roots effectively. There are three commonly used bases for logarithms; the logarithm with base-10 is called the common logarithm, the natural logarithm with base-e and the binary logarithm with base-2. This paper demonstrates different methods of calculation for log2 showing the complexity of each and finds out the most accurate and efficient besides giving in- sights to their hardware design. We present a new method called Floor Shift for fast calculation of log2, and then we combine this algorithm with Taylor series to improve the accuracy of the output, we illustrate that by using two examples. We finally compare the algorithms and conclude with our remarks.

Keywords: logarithms, log2, floor, iterative, CORDIC, Taylor series

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2499 Demand Forecasting Using Artificial Neural Networks Optimized by Particle Swarm Optimization

Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

Abstract:

Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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2498 Implementation of a Virtual Testbed for Secure IoT Firmware Update Using Blockchain

Authors: Tarun Chand, Michael Jurczyk

Abstract:

With the increasing need and popularity of IoT devices and how integrated they are becoming in our daily lives and industries, these devices make for a very lucrative target for malicious actors. And since these devices have such limited resources, the implementation of robust security features is a tradeoff to be made for the actual functionality the device was intended for. This makes them an easy target with high returns. Several frameworks for the secure firmware update of these devices have been recently proposed in the literature. They focus on methods such as blockchains and distributed file systems to secure firmware updates, but do not go into the details of the actual implementation of these frameworks and the lower-level interactions among these methods used. This work integrates some of these security measures into one overall framework and details the actual lower-level implementation of this framework in a virtual dockerized testbed running on AWS.

Keywords: blockchain, Ethereum, Geth, IPFS, secure IoT-firmware update, virtual testbed development

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2497 Signature Verification System for a Banking Business Process Management

Authors: A. Rahaf, S. Liyakathunsia

Abstract:

In today’s world, unprecedented operational pressure is faced by banks that test the efficiency, effectiveness, and agility of their business processes. In a typical banking process, a person’s authorization is usually based on his signature on most all of the transactions. Signature verification is considered as one of the highly significant information needed for any bank document processing. Banks usually use Signature Verification to authenticate the identity of individuals. In this paper, a business process model has been proposed in order to increase the quality of the verification process and to reduce time and needed resources. In order to understand the current process, a survey has been conducted and distributed among bank employees. After analyzing the survey, a process model has been created using Bizagi modeler which helps in simulating the process after assigning time and cost of it. The outcomes show that the automation of signature verification process is highly recommended for a banking business process.

Keywords: business process management, process modeling, quality, Signature Verification

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2496 Load Balancing and Resource Utilization in Cloud Computing

Authors: Gagandeep Kaur

Abstract:

Cloud computing uses various computing resources such as CPU, memory, processor etc. which is used to deliver service over the network and is one of the emerging fields for large scale distributed computing. In cloud computing, execution of large number of tasks with available resources to achieve high performance, minimal total time for completion, minimum response time, effective utilization of resources etc. are the major research areas. In the proposed research, an algorithm has been proposed to achieve high performance in load balancing and resource utilization. The proposed algorithm is used to reduce the makespan, increase the resource utilization and performance cost for independent tasks. Further scheduling metrics based on algorithm in cloud computing has been proposed.

Keywords: resource utilization, response time, load balancing, performance cost

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2495 Memetic Algorithm for Solving the One-To-One Shortest Path Problem

Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

Abstract:

The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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2494 Mathematical Modeling and Algorithms for the Capacitated Facility Location and Allocation Problem with Emission Restriction

Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

Abstract:

In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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2493 Channel Estimation for LTE Downlink

Authors: Rashi Jain

Abstract:

The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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2492 Impact of Workers’ Remittances on Poverty in Pakistan: A Time Series Analysis by Ardl

Authors: Syed Aziz Rasool, Ayesha Zaman

Abstract:

Poverty is one of the most important problems for any developing nation. Workers’ remittances and investment plays a crucial role in development of any country by reducing the poverty level in Pakistan. This research studies the relationship between workers’ remittances and poverty alleviation. It also focused the significant effect on poverty reduction. This study uses time series data for the period of 1972-2013. Autoregressive Distributed Lag (ARDL)Model and Error Correction (ECM)Model has been used in order to find out the long run and short run relationship between the worker’s remittances and poverty level respectively. Thus, inflow of remittances showed the significant and negative impact on poverty level. Moreover, coefficient of error correction model explains the adjustment towards convergence and it has highly significant and negative value. According to this research, Policy makers should strongly focus on positive and effective policies to attract more remittances. JELCODE: JEL: J61

Keywords: ECM, ARDL, AIC, SC

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2491 Motivations for Using Social Networking Sites by College Students for Educational Purposes

Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

Abstract:

Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social Networking Sites (SNSs), education, college students, motivations

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2490 An Earth Mover’s Distance Algorithm Based DDoS Detection Mechanism in SDN

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

Abstract:

Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

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2489 Research on ARQ Transmission Technique in Mars Detection Telecommunications System

Authors: Zhongfei Cai, Hui He, Changsheng Li

Abstract:

This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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2488 The Differential Role of Written Corrective Feedback in L2 Students’ Noticing and Its Impact on Writing Scores

Authors: Khaled ElEbyary, Ramy Shabara

Abstract:

L2 research has generally acknowledged the role of noticing in language learning. The role of teacher feedback is to trigger learners’ noticing of errors and direct the writing process. Recently L2 learners are seemingly using computerized applications which provide corrective feedback (CF) at different stages of writing (i.e., during and after writing). This study aimed principally to answer the question, “Is noticing likely to be maximized when feedback on erroneous output is electronically provided either during or after the composing stage, or does teacher annotated feedback have a stronger effect?”. Seventy-five participants were randomly distributed into four groups representing four conditions. These include receiving automated feedback at the composing stage, automated feedback after writing, teacher feedback, and no feedback. Findings demonstrate the impact of CF on writing and the intensity of noticing certain language areas at different writing stages and from different feedback sources.

Keywords: written corrective feedback, error correction, noticing, automated written corrective feedback, L2 acquisition

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2487 Image Compression Using Block Power Method for SVD Decomposition

Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

Abstract:

In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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2486 Analysis the Nexus among Ethnic Polarization, Globalization and Export Diversification of Pakistan

Authors: Naima Mubeen

Abstract:

Multi-ethnic societies play a crucial role in managing relevant policies and their implication. Pakistan is a classic case of multicultural identity, social evils and a wide-range of preferential ethnic policies. The major objectives of this study are to explore the relationship between ethnic diversity, globalization and export diversification of Pakistan. For empirical analysis of this underlying nexus by utilizing time series data from 1970 to 2016, this study used the autoregressive distributed lags (ARDL) technique. The empirical finding of this study reveals that ethnic diversity is an essential component for enhancing globalization and export diversification in the case of Pakistan. Regarding the promotion of globalization and export diversification at different forums of the country, this study suggested that government needs to take steps for the promotion of society towards more cohesiveness by fair justice-based system and awareness programs.

Keywords: ethnic diversity, social exclusion, globalization, export diversification

Procedia PDF Downloads 101