bluuebunny/crossref_metadata_2025 huggingface dataset:
TheWorkQueue with Dynamic Replication-FaultTolerant Scheduler in Desktop Grid Environment
Authors: Bansal Jyoti , Rani Dr. Shaveta , Singh Dr. Paramjit
Published: May 2018

Desktop Grid is different from Grid in terms of the characteristics of resources as well as types of sharing. Particularly, resource providers in Desktop Grid are volatile, heterogeneous, faulty, and malicious. These distinct features make it difficult for a scheduler to allocate tasks. Moreover, they deteriorate reliability of computation and performance. Availability metrics can forecast unavailability & can provide schedulers with information about reliability which helps them to make better scheduling decision when combined them with information about speed. This paper using these metrics for deciding when to replicate jobs & how much to replicate. In particular our metrics forecast the probability that a job will complete uninterrupted & our schedulers replicate those jobs that are least likely to do so. Our policy outperforms other replication policies as measured by improved Total CPU Time & reduced Waiting Time & Failure count
Dynamic Fault Tolerance in Desktop Grids Based On Reliability
Authors: Arora Geeta , Rani Dr. Shaveta , Singh Dr. Paramjit
Published: May 2018

Fault tolerance is an important issue to guarantee reliable execution of tasks in computational desktop grid environment where execution failures are frequently expected, requires the availability of efficient fault tolerant strategies able to effectively deal with resource failures and/or unplanned periods of unavailability. In this paper we present a Dynamic Fault Tolerant strategy that, rather than just tolerating faults as done by traditional fault-tolerant schedulers, exploit the information concerning size of task, resource speed and resource reliability by maintaining resource history to improve application performance. The performance of this strategy has been compared via simulation with those attained by traditional fault-tolerant strategy. Our results, obtained by considering a set of realistic scenarios modeled after real Desktop Grids, show that our approach results in better application performance and resource utilization.
Air pollution monitoring By sensors embedded on mobile phone
Authors: Khozouie Nasim , Fotouhi-Ghazvini Faranak
Published: May 2018

Mobile technology has been available for at least a decade and is increasingly being used in developing countries as away of contacting and connecting citizens and helping them to organize for a better life.Mobile phones are not just for phone calls, but they can also be used to collect data in several different formats and send them to a central server. There the data can be aggregated and analyzed, with tables and visualizations automatically generated. What is new is the sheer number of observation points that are potentially available by using mobile phones. With over 4 billion phones in use worldwide, the mobile phone network is emerging as a form of “global brain” with sensors everywhere. In addition, there are companies such as Fourier Systems that provide purpose-built mobile devices that are specifically designed for science experiments in school sand for data logging in any science project.
Calcination and alkali metal modification of alumina as solid stationary phase in GC
Authors: El-Naggar Ashraf Yehia
Published: May 2018

Alumina has unique textural properties and functionalized surface. The single or multi-treatments of alumina with calcination and alkali metal treatment (NaCl) are of prime one importance not only for determining the structure, textural and surface chemistry of the phase but also to understand how modification is related to the changes in these properties and also to the change in its performance as solid stationary phase. Thermodynamic parameters (Î”H, Î”G and Î”S) were determined using n-hexane as a probe in order to show the adsorbate-adsorbent interaction. It was observed that the non-polar solutes could be separated independent of the reactivity and porosity of the alumina surfaces. Alkali metal modification of the calciened alumina is a selective stationary phase for eluting natural gas sample exhibiting good separation.
Implementation of Detachable Reversible Data Hiding in Image Encryption
Authors: Pradeep Musham , Srilatha D
Published: May 2018

This paper proposes a scheme for detachable reversible data hiding in image encryption. In which the sender encrypts an image using encryption key. Then, the data is appended to the encrypted image using a data-hiding key. With an encrypted image containing additional data, if a receiver has the data-hiding key, he can extract the additional data though he does not know the content of the image. If the receiver has the encryption key, he can decrypt the encrypted image and get an image similar to the original one, but he cannot extract the additional data. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original image without any error.
Performance Evaluation Study of Active Contour Models in Medical Imaging
Authors: Midha Sugandhi
Published: May 2018

Over the past years image segmentation has played an important role in medical imaging. Segmented images are used for a number of applications such as computer aided surgery, treatment planning, diagnosis, study of anatomical structures and many more. Deformable models provide a general method of performing non-rigid object segmentation. They offer an attractive approach to overcome the limitations of traditional low level segmentation approaches. A snake is a flexible deformable model which can be matched to an image contour by energy minimisation. Snakes are a powerful technique in segmenting formless shapes when little or no prior knowledge about the shape is available. Rather than handcrafting a prior knowledge into the model, the shape variation is extracted from a training set by applying PCA to PDM.Â  In this paper some familiar Active Contour models such as Snakes by Kass et al, Balloon model, Greedy snakes method, Gradient Vector Flow Snakes are compared on the basis of qualitative and quantitative measures. The GVF Snakes have the ability to move into boundary concavities whereas the Greedy Snakes, Original Snakes have problems trying to locate the contour of an object which has a boundary concavity.
Security Service for Wireless Sensor Network
Authors: Solairaju A. , Saravanan S.Vivek
Published: May 2018

Wireless Sensor Networks (WSNs) are gradually adopted in the industrial world due to their advantages over wired networks. In addition to saving cabling costs, WSNs widen the realm of environments feasible for monitoring. They thus add sensing and acting capabilities to objects in the physical world and allow for communication among these objects or with services in the future Internet. However, the acceptance of WSNs by theindustrial automation community is impeded by open issues, such as security guarantees. To examine both of these perspectives, we select and survey relevant WSN technologies dedicated to industrial automation. We determine to carry out a threat analysis, which act as basis of our evaluation of the current state-of-the-art. According to the results of this evaluation, we identify and discuss some research issues.
A Study on Existing Protocols and Energy-Balanced Routing Protocol for Data Gathering in Wireless Sensor Networks
Authors: Lalitha T. , Devi Jayanthila , Kadh Dr.G.M.
Published: May 2018

Energy is an extremely critical resource for battery-powered wireless sensor networks (WSN), thus making energy-efficient protocol design a key challenging problem. Most of the existing energy-efficient routing protocols always forward packets along the minimum energy path to the sink to merely minimize energy consumption, which causes an unbalanced distribution of forming residue energy among sensor nodes, and eventually results in a network partition. In this paper, with the help of the concept of potential in physics, we design an Energy-Balanced Routing Protocol (EBRP) by constructing a mixed virtual potential field in terms of depth, energy density, and residual energy. The goal of this basic approach is to force packets to move toward the sink through the dense energy area to protect the nodes with relatively low residual energy. To address the routing loop problem emerging in this basic algorithm, enhanced mechanisms are proposed to detect and eliminate loops. The basic algorithm and loop elimination mechanism are first validated through extensive simulation experiments.Â
Comparative Study of Three Imputation Methods to Treat Missing Values
Authors: Singhai Rahul
Published: May 2018

One relevant problem in data preprocessing is the presence of missing data that leads the poor quality of patterns, extracted after mining. Imputation is one of the widely used procedures that replace the missing values in a data set by some probable values. The advantage of this approach is that the missing data treatment is independent of the learning algorithm used. This allows the user to select the most suitable imputation method for each situation. This paper analyzes the various imputation methods proposed in the field of statistics with respect to data mining. A comparative analysis of three different imputation approaches which can be used to impute missing attribute values in data mining are given that shows the most promising method. An artificial input data (of numeric type) file of 1000 records is used to investigate the performance of these methods. For testing the significance of these methods Z-test approach were used.
Studying the Effect of Paracetamol Drug on the Conductivity of 0.5M Hydrochloric Acid Solution at Different Temperatures
Authors: Al-Sawaad Hadi.Z.
Published: May 2018

In this study paracetamol drug is used to reduce the conductivity of 0.5M hydrochloric acid at different concentrations for each one of them at different temperatures ranged (30-60)Â°C. Generally , increasing of the concentration of Â the inhibitor leads to reducing in conductivity of the acid at constant temperature. On the other hand, at constant concentration ofÂ  inhibitor, the conductivity is reduced as temperature increased i.e., paracetamol can adsorbed chemically on the metal or alloy. Furthermore the kinetic study of the molar conductance process reveal that in presence of paracetamol the activation energy and enthalpy of activation are negative compared with their values in absence of paracetamol where they are negative because the reducing the conductivity in presence of paracetamol where the non spontaneous property for the conductance of acid is increased as the paracetamol concentration increased in addition to increasing the negative value of entropy in presence of paracetamol that indicate to restrict for the mobility of hydrogen and chloride ions which correspond to 90.47% as efficiency of reducing the conductance of acid by paracetamol. On the other hand thermodynamic study is achieved which explained the adsorption of paracetamol obey to Freundlisch model.Â
Binary Quantum Communication using Squeezed Light: Theoretical and Experimental Frame Work
Authors: Fyath Raad Sami
Published: May 2018

The aim of this paper is to develop framework to generate squeezed light for binary quantum communication. Both theoretical and experimental models to generate squeezed state Â using optical parametric amplifier (OPO), which is implemented around He-Ne laser, are described in details.Â  The results will be used as a guide line to investigate the performance of squeezed light-based quantum communication over noisy channel and this issue will be presented in accompanying paper [1].Â  Â
Performance Evaluation System for Decision Tree Algorithms
Authors: Saini Deepali , Rajavat Prof. Anand
Published: May 2018

In the machine learning process, classification can be described by supervise learning algorithm. Classification techniques have properties that enable the representation of structures that reflect knowledge of the domain being classified. Industries, education, business and many other domains required knowledge for the growth.Â  Some of the common classification algorithms used in data mining and decision support systems is: Neural networks, Logistic regression, Decision trees etc. The decision regarding most suitable data mining algorithm cannot be made spontaneously. Selection of appropriate data mining algorithm for Business domain required comparative analysis of different algorithms based on several input parameters such as accuracy, build time and memory usage.To make analysis and comparative study, implementation of popular algorithm required on the basis of literature survey and frequency of algorithm used in present scenario. The performance of algorithms are enhanced and evaluated after applying boosting on the trees. We selected numerical and nominal types of dataset and apply on algorithms. Comparative analysis is perform on the result obtain by the system. Then we apply the new dataset in order to generate generate prediction outcome.
Semantic link-based Model for User Recommendation in Online community
Authors: Elkorany Abeer
Published: May 2018

Recommendation systems have been widely used to overcome the problem of information overloading and help people to make the right decision of needed items, such as: movies, books, products, or even people. This paper proposes a semantic model for people recommendation in online community. This model predicts significant links that would be established between community' members even they do not know each other using cascaded collaborative filtering (CF). Two major steps in this type of recommendation model are (i) the method used to compute the similarity between people, and (ii) the method used to combine these similarities in order to compute the overall similarity between target member and others. By utilizing local features of links and nodes, similarity measurements between members are calculated. Semantic relatedness between members is delivered from connection strength and trust score in order to identify the closeness between them. Extensive experimental of the proposed model using real dataset of scientific community was applied to recommend authors as possible coworkers for a target researcher. Experimental results on real dataset from publication network show that the proposed model for people recommendation outperforms other known techniques in ranking recommended collaborators.
A Novel LAS-Relief Feature Selection Algorithm for Enhancing Classification Accuracy in Data mining
Authors: Baskar S. S. , Arockiam Dr L.
Published: May 2018

Feature selection is an important task in data mining and machine learning domain. The main objective of feature selection is to find a relevant feature that predicts the knowledge better than the original set of features. This can be achieved by removing irrelevant or redundant features from original data sets. Feature selection involves a significant task of selecting relevant features from the feature space for data mining and pattern recognition. In this paper, the new approach has been introduced on feature selection on Relief based on Median Variance model. The new approach is named as LAS-Relief algorithm. This algorithm facilitates to stabilise the feature weights estimation compared to mean variance based Relief algorithm and is considered to be a better successful algorithm for feature selection. The random selection of instances in the data sets will lead to the fluctuation of weight estimation. This in turn leads to poor evaluation accuracy. This new approach removes the irrelevant features in the feature space. The novel LAS-Relief algorithm incorporates the median variance in the feature weight estimation. The feature weight is calculated by selection of the instances in random.  To overcome this issue, the novel feature selection algorithm called LAS-Relief algorithm is proposed based on median variance. This algorithm takes both the median and the variance of difference between instances. These are considered as the criterion of feature weight estimation in this LAS Relief algorithm.. This algorithm makes the result more stable and more accurate on classification. The relevant features are obtained from the original feature space using LAS-Relief algorithm, which outperforms well than Mean Variance Relief algorithm.
Effect of oral injection of tramadol, sildenafil and combined of tramadol and sildenafil on serum testosterone level for Wistar breed male rats
Authors: Farag Rabie Said , El Nawawy Mohamed Abdel , Fathy Wael Mohamed , Atiaa Hamada
Published: May 2018

Introduction:Testosterone is the main sexual hormone in human males, and has a pharmacological effect on the physiology of sexual function. It is known that suppression of testosterone in eugonadal adult males leads to reduced sexual desire and activity, and may result in erectile dysfunction. Tramadol is rapidly and almost completely absorbed after oral administration but its absolute bioavailability is only 65â€“70% due to first-pass metabolism. Sildenafil citrate is a water soluble citrate salt that was firstly synthesized by Pfizer in United Kingdom to treat hypertension and angina pectoris. Interestingly, this drug exhibited a different pharmacological effect, a marked penile erection, and became the first-line treatment option to erectile dysfunction. Aim of the work :the main work goal of this search was to measure and compare between mean serum testosterone concentrations after oral injection of tramadol, sildenafil , and combination of tramadol and sildenafil beside healthy subjects.Investigated Parameter: quantitative analysis of Free Testosterone ELISA Kit in serum by The Calbiotech, Inc. 10461 Austin Dr, Spring Valley, CA U.S.A., depending on McCann, D., et al 1985.Results In the present study, the results of GT group revealed that administration of tramadol 50 mg /Kg/day for 10, 20 days and 30 days indicated that the measured testosterone levels were lower than the (GC) control group, and the decrease in testosterone mean concentrations in GT3, than GT2, than GT1. In our research GS group administration of sildenafil 50 mg /Kg/day for 10, 20 and 30 days groups indicated that increase testosterone levels than that in control GC group, and there was an increase in testosterone mean concentrations in GS3, than GS2, than GS1. The present study reveled in GT&S administration of tramadol 50 mg /Kg/day combined with sildenafil 50 mg /Kg/day that the mean serum testosterone concentrations in (GT&S1), (GT&S2) and (GT&S3), were decrease than in the mean serum testosterone concentrations (GC), but this decrease in the mean serum testosterone concentrations in (GT&S1), (GT&S2) and (GT&S3), were quite higher than mean serum testosterone concentrations in GT1, GT2, and GT3, also and there were a decrease in mean testosterone mean concentrations in (GT&S3) than that in (GT&S2) and (GT&S1)conclusion: tramadol administration decrease testosterone levels, while sildenafil increase testosterone levels, while the combination between tramadol & sildenafil decrease testosterone levels.
Intuitionistic Fuzzy Modeling to Travelling Salesman Problem
Authors: Garai Arindam , Roy Tapan Kumar
Published: May 2018

This paper presents solution technique for travelling salesman problem (TSP) under intuitionistic fuzzy environment. Travelling salesman problemÂ is a non-deterministic polynomial-time (NP) hardÂ problem inÂ combinatorial optimization,Â studied inÂ graph theory, operations researchÂ andÂ theoretical computer science. It must be noted that a traveling sales man even face a situation in which he is not able to achieve his objectives completely. There must be a set of alternatives from which he can select one that best meets his aspiration level. For Multi-Objective Symmetric TSP, in fuzzy environment, it is converted into a Linear Program using Fuzzy Multi-Objective Linear Programming technique. A route cannot be simply chosen just as it will most minimize time or it will cover the least possible distance. Examples with requirements to consider the degree of rejection or hesitation (or both) are overflowing in our materialistic world. Here comes the need to consider TSP under intuitionistic fuzzy environment. The degree of rejection as well as the degree of hesitancy must be studied to find the solution in a truly optimum sense! Proposed technique is an extension as well as collaboration of ideas of fuzzy traveling salesperson problem and intuitionistic fuzzy (IF) optimization technique.
Hybrid Model based on unification of Technical Analysis and Sentiment Analysis for Stock Price Prediction
Authors: Wankhade Sunil B , Surana Divyesh , Mansatta Neel J , Shah Karan
Published: May 2018

Stock price forecasting phenomenon has been majorly made on the basis of quantitative information. Over the time, with the advent of technology, stock forecasting used technical analysis to get more accurate predictions. Until recently, studies have demonstrated that sentiment information hidden in corporate reports can be effectively incorporated to predict short-run stock price returns. Soft computing methods, like neural networks, fuzzy models and support vector regression, have shown great results in the forecasting of stock price due to their ability to model complex non-linear systems.In this paper we propose a hybrid method for stock price predication, which is combinational feature from technical analysis and sentiment analysis (SA). The features of sentiment analysis are based on a Point wise Mutual Information (PMI) and we applyÂ  neural network and Îµ-support vector regression models to predict the yearly change in the stock price.
Fangled Protocol for Black Hole Detection in Ad Hoc Networks
Authors: Mishra Reeta
Published: May 2018

Now a day, security in Mobile Ad hoc Network is very important issue. Due to dynamic topology and mobility of nodes, Mobile Ad hoc Networks are more vulnerable to security attacks than conventional wired and wireless network. Nodes of Mobile Ad hoc Network communicate directly without any central base station. That means in ad hoc network, infrastructure is not required for establishing communication. Therefore attacks in this are very frequent than other networks. In this research paper we are describing black hole attacks which are easy to launch in wireless ad hoc network. Black hole attack is referred to as a node dropping all packets and sending forged routing packets to route packets over itself. Ad hoc networks are vulnerable to different kinds of attacks such as: denial of services, impersonation, and eavesdropping.This paper discusses one of the security problems in ad hoc networks called the black hole problem. It occurs when a malicious node referred as black hole joins the network. The black hole conducts its malicious behaviour during the process of route discovery. For any received REQ, the black hole claims having a route and propagates a faked REP. The source node responds to these faked REPs and sends its data through the received routes. Once the data is received by the black hole, it is dropped instead of being sent to the desired destination.The proposed protocol is built on top of the original AODV. It extends the AODV to include the following functionalities: source node waits for a reliable route; each node has a table in which it adds the addresses of the reliable nodes; REP is overloaded with an extra field to indicate the reliability of the replying node.Â
Logistics Innovation in the Medico-Social Sector: An Optimized Workflow for an Efficient Patient Care
Authors: Zgaya Hayfa , Barras Thomas , Durocher Alain
Published: May 2018

The issue of care for the elderly is a real challenge for our society. The French government offers solutions to users, particularly through institutions hosting for dependent elderly people (nursing homes). We position ourselves in this study in the field of health logistics. We are particularly interested in the implementation of an innovative tool to provide, in real-time, the best possible organization of resources for an efficient patient care. For that, we propose a software solution in the form of a dynamic dashboard, in order to represent and optimize the overall behaviour of a nursing home and especially in terms of resource allocation. This allocation should be in accordance with the workload, patient needs and time constraints. The results show the effectiveness of our solution compared to an intuitive organization based on the experience and the organizational strategies of staff.
ON SOME DOUBLE INTEGRALS INVOLVING -FUNCTION OF TWO VARIABLES AND SPHEROIDAL FUNCTIONS
Authors: Singh Yashwant , Joshi Laxmi
Published: May 2018

The present paper evaluates certain double integrals involving -function of two variables [21] and Spherodial functions [23]. These double integrals are of most general character known so far and can be suitably specialized to yield a number of known or new integral formulae of much interest to mathematical analysis which are likely to prove quite useful to solve some typical boundary value problems.Â
Digital Fingerprinting In Encrypted Domain
Authors: Murala Kranthi Kumar , Kamaraju Dr.M. , Ramanjaneyulu Dr.K.
Published: May 2018

Digital fingerprinting is a method for protecting multimedia content from illegal redistribution and identified the colluders.In copy protection, a content seller embeds a unique identity as a watermark into the content before it is sold to a buyer. When an illegal copy is found, the seller can identify illegal users by extracting the fingerprint. In thisÂ  proposing an anonymous fingerprinting Â based on a homomorphic additive encryption scheme, it present a construction of anti-collision codes created using BIBD(Balanced incomplete block design) codes technique and dither technique which makes use of LFSR (linear feedback shift register) are used for improving the high robustness and Security.
Image Segmentation Using Signed Pressure Force Based Active Contour Model
Authors: Chouksey Sagar , Ghadle Mayur , Sharma Shreya , Puranik Rohan
Published: May 2018

A novel signed pressure force (SPF) based active contour model (ACM) is proposed in this work. It is implemented with help of Gaussian filtering regularized level set method, which first selectively penalizes the level set function to be binary, and then uses a Gaussian smoothing kernel to regularize it. The advantages of this method are as follows. First, a new region-based signed pressure force (SPF) function is proposed, which can efficiently stop the contours at weak or blurred edges. Second, the exterior and interior boundaries can be automatically detected with the initial contour being anywhere in the image. Third, the proposed SPF with ACM has the property of selective local or global segmentation. It can segment not only the desired object but also the other objects. Fourth, the level set function can be easily initialized with a binary function, which is more efficient. The computational cost for traditional re-initialization can also be reduced.
Estimation of Performance Improvement Derived from TCP/IP Offload Engine with Software Emulation
Authors: Nishijima Takamichi , Yokoi Nobuhiro , Nakamoto Yoichi , Ohsaki Hiroyuki
Published: May 2018

Many TOE (TCP/IP Offload Engine) devices have been developed and installed in high-end systems.Â  Although there have been many analysis of the effectiveness of TOE devices, there remain open issues related to them.Â  For example, it has not been clarified which part of TCP/IP processing should be performed with hardware and which with software, or how end-to-end TCP/IP performance is affected by the introduction of a TOE device.Â  In this paper, we propose VOSE (Virtual Offloading with Software Emulation), which is a technique for measuring TCP/IP performance improvements derived from different type of TOE devices without implementing TOE prototypes really.Â  VOSE enables virtual offloading without requiring a hardware TOE device by virtually emulating TOE processing on both source and destination end hosts.Â  For demonstrating the effectiveness of VOSE, we apply VOSE to the TCP checksum and IPsec protocol.Â  We extensively examine the accuracy of virtual offloading with VOSE, by comparing performance (i.e., end-to-end performance and CPU processing overhead) between VOSE and a dedicated TOE device.Â  Moreover, we estimate performance improvement that are derived from several TOE devices of IPsec and combinations of those devices, by applying VOSE to header authenticating and payload encryption in IPsec protocol.Â  Consequently, we show that performance improvements which are derived from TOE devices can be estimated correctly.
An Algorithm to reduce End to End Delay AND Enhance the Quality of Service in Mobile Adhoc Network
Authors: Ahirwal Ramratan , Chaurasiya Nitesh Kumar , Jain Yogendra Kumar
Published: May 2018

A mobile adhoc network (MANET) is formed by a group of wireless mobile hosts or nodes without any fixed infrastructure. As there is no inner control in a MANET, a mobile node itself acts as a router. Undoubtedly, MANETs plays a critical job in situations where a wired infrastructure is neither available nor easy to install. Wireless mesh networks have large round trip time variations and these variations are dependent on the number of hops. The end-to-end throughput degrades rapidly with increase in number of hops. This is one of the biggest problems in MANET.In this paper we introduce an algorithm for avoiding congestion in MANETs. The algorithm demonstrates fast response and superior stability with the controlled packet dropping rate, and reduces end-to-end delay in MANETs, while still fully utilizing the network resources. Analysis and simulation show the strength and robustness of the algorithm. This method is simple and easy to use. We also illustrate the advantages of our proposed approach by comparing its results with standard AODV with recommended parameter settings.
SAPMS; Student Assessment Process Management System Enriched with Quality Factors
Authors: Elsaid Abdelghafar Mohammed Elhady , Hassan Ahmed Elsayed
Published: May 2018

Computer's hardware and software development aided education field progresses more rapidly. Not only the computer is used in learning and assessment processes to add more attractiveness, but also it's used for better performance of educational system. But one of more defects was lacking in applying modern educational quality factors to both learning and assessment software. This paper presents a web based Student Assessment Process Management System (SAPMS). SAPMS provides a secured, attractive, easy to use and quality based assessment system. Our system is completely analyzed and designed using the Unified Modeling Language (UML). We also present the implementation of the core components of the SAPMS which performs the most important processes in the system. In addition to that a validation study for the system components is performed.
SOADM: A Design Architectural Method for Service-as-a-Software
Authors: Mcheick Hamid , Baghdadi Youcef
Published: May 2018

Service-Oriented Software Engineering is a new approach that concerns with methods to build software solutions as services and compositions with respect to service orientation and service-oriented architecture. Several methods from both academia and industry have been developed for service-oriented based systems. This work first questions â€œto what extent a solution provided by a method would conform to service orientation, particularly, how to examine the design decisions based on quality attributesâ€, and â€œto what extent the method would align solutions with problemsâ€. Next, it proposes a framework for shaping methods. The framework considers the perspectives. Then, it propose a SOADM, a method for developing Service-as-a Software (SaaS) in high level design based on functional requirements and quality attributes.
Numerical solution of system of two Nonlinear Volterra Integral equations
Authors: Maturi Dalal Adnan
Published: May 2018

In this paper, using the implicit trapezoidal rule in conjunction with Newton's method to solve nonlinear system.We have used a Maple 17 program to solve the System of two nonlinear Volterra integral equations. Finally, several illustrative examples are presented to show the effectiveness and accuracy of this method.
Effect of Weight Factor on The Performance of Hybrid Column Wavelet Transform used for Watermarking under Various Attacks.
Authors: Kekre H. B. , Sarode Tanuja , Natu Shachi
Published: May 2018

Digital image watermarking is aimed at copyright protection of digital images. Strength of embedded watermark plays an important role in robustness and invisibility of watermarking technique. In this paper, effect of two parameters namely, watermark strength and middle frequency coefficients of host image used for embedding watermark is studied. In the given watermarking technique, watermark is normalized before embedding. This reduces the strength of watermark so that there will be minimum possible distortion in watermarked image. However, it has been observed in our work proposed in previous paper that, such embedment responds poorly to various image processing attacks like compression, cropping, resizing, noise addition etc. Hence in this paper, an attempt has been made to increase the strength of embedded watermark by using suitable weight factor so that robustness of watermarking technique proposed in our previous paper is further increased with small acceptable decrease in imperceptibility. Also middle frequency elements of host image selected for embedding watermark are varied by selecting different rows of host such that slowly we move from middle frequency components towards high frequency components. For certain attacks like image cropping, selection of middle frequency coefficients affects the robustness achieved. Increase in weight factor significantly improves the performance of given watermarking technique by more than 50% as proposed in our previous paper where weight factor value was 25.
DIGITAL IMAGE ANALYSIS BASED ON AUTOMATED COUNTING CLUSTERED SOYBEAN SEEDS
Authors: Kaur Jasdeep
Published: May 2018

- Â This paper investigates the use of digital image analysis techniques for developing for counting clustered soya bean seeds. Images are extracted from source WWW.21food.com). As manual counting have several issues such as low accuracy and higher cost. Automated counting techniques give a fast and low cost of counting soya bean seeds. This paper follows 5 processing steps. First process converting the image into gray scale and thresholding is applied using CLAHE. Second dilation is applied to enhance the image. Third applied masking to enhance the image. Fourth edge detection algorithm is applied. Fifth step beans extracted with respect to bean shape.Â
Development and Simulation of Next Generation SDH Network Management System
Authors: Saeed Bilal , Shahid Khalil , Khan Zeeshan
Published: May 2018

In present scenario Network Management System of Next Generation SDH is not performing Offline reporting, offline analysis of alarms, offline performance management and Configurations of network like real time. Any offline configuration of a network when implemented on a real time environment leaves some shortcomings and wrong configuration attributes due to non-availability of Alarms and Performance Management in the presently available offline utility. A simulated platform is developed for implementation of a traffic matrix in an offline environment before implementing over a real time NG SDH Transmission network to reduce the chance of faults or any network disaster.
Fast Effective Deterministic Primality Test Using CUDA/GPGPU
Authors: Asaduzzaman Abu , Maiti Anindya , Yip Chok Meng
Published: May 2018

There are great interests in understanding the manner by which the prime numbers are distributed throughout the integers. Prime numbers are being used in secret codes for more than 60 years now. Computer security authorities use extremely large prime numbers when they devise cryptographs, like RSA (short for Rivest, Shamir, and Adleman) algorithm, for protecting vital information that is transmitted between computers. There are many primality testing algorithms including mathematical models and computer programs. However, they are very time consuming when the given number n is very big or nâ†’âˆž. In this paper, we propose a novel parallel computing model based on a deterministic algorithm using central processing unit (CPU) / general-purpose graphics processing unit (GPGPU) systems, which determines whether an input number is prime or composite much faster. We develop and implement the proposed algorithm using a system with a 8-core CPU and a 448-core GPGPU. Experimental results indicate that upto 94.35x speedup can be achieved for 21-digit decimal numbers.
A THEORETICAL APPROACH TO THE PROCESS OF INTERNATIONALIZATION OF SME's
Authors: Durmaz Dr. Yakup , Birlik Harun
Published: May 2018

In recent times, small and medium-sized enterprises (SMEs) have become a familiar form of business organization. They have a significant contribution on economic development creating significant number of jobs around the world. Elo (2005) mentions; SMEs are the largest source of employment which plays a considerable role at regional and international level enhancing innovativeness. According to the European commission the ratio of SMEs to the number of inhabitants are 58 SMEs per 1000 inhabitants (European commission 2011). Total workforce generated by SMEs was 33% on private sector in 2005 and it has increased to 59% (European Commission 2011). SMEs were struggling with economic and financial crises in 2008. Despite this fact, recent research has shown that most of the SMEs are in recovering phase. Nevertheless,SMEs have been contributing significant amount of growth in the economy. Therefore, the importance of SMEs cannot be neglected. Furthermore, SMEs are generating approximately 90 million jobs all around Europe with contribution on innovation and economic growth. (EU commission 2011).
Problems of Modern Networks
Authors: Al- Rababah Mohammad , E. Oweis Nour , Al-shredei Khaled Sadeq
Published: May 2018

Most of the modern computer networks encounter a lot of problems in order to use the new development of technologies with its needed and requirements, especially for data density, which affect to the large data Losses, this leading to the collapse of the economy . The spread ofsocial networking including thehuge connection between users led a positively effect to the economy in the word, while if there is a user'scut ofthe social network will led a big loss in all academic life and economic.
HYDROMAGNETIC STABILITY OF STREAMING COMPRESSIBLE CYLINDER PERVADED BY MAGNETIC FIELD
Authors: L. Azwz Shimaa
Published: May 2018

The Stability of MHD compressible streaming fluid cylinder of radius endowed with surface tension and pervaded by axial magnetic field has been developed. The stability criterion is established in general form. The model is capillary unstable only in the axisymmetric mode m=0, the electromagnetic forces acting interior and exterior the fluid cylinder are stabilizing and the MHD stability is destabilizing for small wave length. In the latter case the instability shrinks with increasing the magnetic intensity. However the compressibility has a stabilizing tendency.
Scene Oriented Classification of Blurry and Noisy Images Using SVM with Fuzzy C Mean Clustering
Authors: Nema Deepak
Published: May 2018

Image classification is a challenging task in image processing especially in the case of blurry and noisy images. In this work, we present an extension of scene oriented hierarchical classification of blurry and noisy images using Support Vector Machine (SVM) and Fuzzy C-Mean. Generally, a system for scene-oriented classification of blurry and noisy images attempts to simulate major features of the human visual observation. These approaches areÂ  based on three strategies such as Global pathway for extracting essential signature of image, local pathway for extracting local features, and then outcome of both global and local phase are combined and define feature vector and clustered using Monte Carlo approach. Afterwards, these clustered results are fed to a SOTA Algorithm (combination of self organizing map and hierarchical clustering) for final classification. But in these approaches, combination of self organizing map and hierarchical clustering has the problem in terms of accuracy and computation time of classification, especially when used large dataset for classification. To overcome this problem, we propose a combination of Support Vector Machine (SVM) and Fuzzy C-mean. Our proposed approach provides better result in terms of accuracy, especially when used with large dataset. The proposed method is computationally efficient because fuzzy c-mean clustering is faster and less time consuming as compared to hierarchical clustering.
Using Fuzzy Logic in Robot Navigation to Find Animals
Authors: Amiri Mahdi , Abbasi Zeinab , Tafreshi Fakhte Soltani
Published: May 2018

Â Fuzzy logic is a tool to use human expertise. The simplicity of fuzzy-rule based systems and its power to perform various tasks without accurate measurement and computation makes it very popular between sciences. One of these applications is using fuzzy logic in designing the controller for navigation of autonomous robots to move in various environments. This paper proposes a new method of robot navigation based on fuzzy logic. This method can be drawn upon to design robots which can find and catch different kind of animals, especially endangered species. It works based on a hierarchical set of behavior each of which acts by using a set of fuzzy rules. The proposed method is simulated and tested by MATLAB software.
EFFICIENT FPGA BASED MATRIX MULTIPLICATION USING MUX AND VEDIC MULTIPLIER
Authors: Bhairannawar Satish s , K B Raja , K R Venugopal , Patnaik L M
Published: May 2018

Most of the algorithms which are used in DSP, image and video processing, computer graphics, vision and high performance supercomputing applications require multiplication and matrix operation as the kernel operation.In this paper, we propose Efficient FPGA based matrix multiplication using MUX and Vedic multiplier. The 2x2, 3x2 and 3x3 MUX based multipliers are designed. The basic lower order MUX based multipliers are used to design higher order MxN multipliers with a concept of UrdhvaTiryakbyham Vedic approach. The proposed multiplier is used for image processing applications. It is observed that the device utilization and combinational delay are less in the proposed architecture compared to existing architectures.
A Biochemical Study to Estimate Malonaldehyde and Ceruloplasmin Oxidase Activity As Parameters Express Oxidation â€“ Antioxidation Balance for Patients With Acute Hepatitis Virus Type C
Authors: Hasan Jasim Rasha
Published: May 2018

Oxygen free radicals play an important role in the pathogenesis of tissue damage in many pathological conditions, including liver diseases. Aim of the present study focused on the investigation the possible relationship between serum malondialdehyde level, an index of lipid peroxidation, and ceruloplasmin levels, as protective agent against lipid peroxidation, in hepatitis C virus. A group of 31 hepatitis virus type C patients enrolled in the study, while; control group consisted of 25 healthy subjects. In the present study, total proteins (g/L), malondialdehyde (ÂµM), ceruloplasmin oxidase activity (U/L) and ceruloplasmin concentration (g/L) were measured in sera samples of patients with hepatitis C virus as well as in the healthy controls.
Method of Moving Region Detection for Static Camera
Authors: Goel Pravesh Kumar , Kotak Paresh P. , Gupta Amit
Published: May 2018

The moving object detection from a stationary video sequence is a primary task in various computer vision applications. In this proposed system; three processing levels are suppose to perform: detects moving objects region from the background image; reduce noise from the pixels of detected region and extract meaningful objects and their features (area of object, center point of area etc.). In this paper; background subtraction techniques is used for segments moving objects from the background image, which is capable for pixel level processing. Morphology operation (Erosion and dilation) are used to remove pixel to pixel noise. In last level, CCL algorithm is used for sorts out foregrounds pixels are grouped into meaningful connected regions and their features.
Skin Color detection Using Stepwise Neural Network and Color Mapping Co-occurrence Matrix
Authors: Osman Ghazali , Hitam Muhammad Suzuri
Published: May 2018

Skin color has been proven to be a useful and robust cue for face detection, human tracking, image content filtering, pornographic filtering, etc.Â  Most of skin classification researches are focused on using pixel-based method to classify skin and non-skin pixels.Â  This paper proposed a new technique for region-based skin color detection using texture information.Â  The texture information was extracted from the color mapping co-occurrence matrix (CMCM).Â  This technique is extension of gray level co-occurrence matrix (GLCM) which is introduced by Haralicket. al to compute second order statistical texture features.Â  The new color mapping matrix (CMM) between color bands have been developed for skin and non-skin area for each skin image and then, the CMCM were computed at four direction with distance, d = 1, and angle, Î¸ = 0o, 45o, 90o, and 135o.Â  The thirteen Haralickâ€™s textures have been computed and used for formulating a skin color classifiers using stepwise neural network (SNN).Â  The performance of each skin color classifier was measured based on true and false positive value.Â  Besides that, the benchmark datasets from Universidad de Chile and TDSD were also be employed to test the skin color classifiers ability.Â  The results shown that the skin color classifier formulated with [RGB] CMCM at direction (1, 0o) most superior as compared to other direction.Â  Its average of true positive and false positive are 98.38 percent and 3.67 percent, respectively.Â  Meanwhile, the classifier formulated with [RGB] CMCM at direction (1, 90o) is totally failed to classify skin and non-skin colors.Â  Meaning that, the texture features which are computed from [RGB] CMCM at direction (1, 90o) cannot represent skin and non-skin color at all.
A Content Based Approach to Medical X-Ray Image Retrieval using Texture Features
Authors: Ganesan Sumathi , Subashini T.S.
Published: May 2018

Of late, the amount of digital X-ray images that are produced in hospitals is increasing incredibly fast. Efficient storing, processing and retrieving of X-ray images have thus become an important research topic. With the exponential need that arises in the search for the clinically relevant and visually similar medical images over a vast database, the arena of digital imaging techniques is forced to provide a potential and path-breaking methodology in the midst of technical advancements so as to give the best match in accordance to the userâ€™s query image. CBIR helps doctors to compare X-rays of their current patients with images from similar cases and they could also use these images as queries to find the similar entries in the X-ray database. This paper focuses on six different classes of X-ray images, viz. chest, skull, foot, spine, pelvic and palm for efficient image retrieval. Initially the various X-rays are automatically classified into the six-different classes using BPNN and SVM as classifiers and GLCM co-efficient as features for classification. Indexing is done to make the retrieval fast and retrieval of similar images is based on the city block distance.Â Â