IJACSA Volume 3 Issue 9 - thesai.org

IJACSA Volume 3 Issue 9

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: 3D Face Compression and Recognition using Spherical Wavelet Parametrization

Abstract: In this research an innovative fully automated 3D face compression and recognition system is presented. Several novelties are introduced to make the system performance robust and efficient. These novelties include: First, an automatic pose correction and normalization process by using curvature analysis for nose tip detection and iterative closest point (ICP) image registration. Second, the use of spherical based wavelet coefficients for efficient representation of the 3D face. The spherical wavelet transformation is used to decompose the face image into multi-resolution sub images characterizing the underlying functions in a local fashion in both spacial and frequency domains. Two representation features based on spherical wavelet parameterization of the face image were proposed for the 3D face compression and recognition. Principle component analysis (PCA) is used to project to a low resolution sub-band. To evaluate the performance of the proposed approach, experiments were performed on the GAVAB face database. Experimental results show that the spherical wavelet coefficients yield excellent compression capabilities with minimal set of features. Haar wavelet coefficients extracted from the face geometry image was found to generate good recognition results that outperform other methods working on the GAVAB database.

Author 1: Rabab M. Ramadan

Author 2: Rehab F. Abdel-Kader

Keywords: 3D Face Recognition; Face Compression; Geometry coding; Nose tip detection; Spherical Wavelets.

Paper 2: A Multi-Objective Optimization Approach Using Genetic Algorithms for Quick Response to Effects of Variability in Flow Manufacturing

Abstract: This paper exemplifies a framework for development of multi-objective genetic algorithm based job sequencing method by taking account of multiple resource constraints. Along this, Theory of Constraints based Drum-Buffer-Rope methodology has been combined with genetic algorithm to exploit the system constraints. This paper introduces the Drum-Buffer-Rope to exploit the system constraints, which may affect the lead times, throughput and higher inventory holding costs. Multi-Objective genetic algorithm is introduced for job sequence optimization to minimize the lead times and total inventory holding cost, which includes problem encoding, chromosome representation, selection, genetic operators and fitness measurements, where Queuing times and Throughput are used as fitness measures. Along this, paper provides a brief comparison of proposed approach with other optimisation approaches. The algorithm generates a sequence to maximize the throughput and minimize the queuing time on bottleneck/Capacity Constraint Resource (CCR). Finally, Results are analysed to show the improvement by using current research framework.

Author 1: Riham Khalil

Author 2: David Stockton

Author 3: Parminder Singh Kang

Author 4: Lawrence Manyonge Mukhongo

Keywords: Synchronous Manufacturing; Drum-Buffer-Rope; Flow Lines; Multi-Objective Optimisation; Job Sequence.

Paper 3: The Risk Management Strategy of Applying Cloud Computing

Abstract: It is inevitable that Cloud Computing will trigger off some loss exposures. Unfortunately, not much of scientific and objective researches had been focused on the identification and evaluation of loss exposures stemming from applications of Cloud Computing. In order to fill this research gap, this study attempts to identify and analyze loss exposures of Cloud Computing by scientific and objective methods which provide the necessary information to administrators in support of decisions of risk management. In conclusion, this study has identified “Social Engineering”, “Cross-Cloud Compatibility” and “Mistakes are made by employees intentionally or accidentally” are high priority risks to be treated. The findings also revealed that people who work in the field of information or Cloud Computing are somehow ignorant of where the risks in Cloud Computing lie due to its novelty and complication.

Author 1: Chiang Ku Fan

Author 2: Tien-Chun Chen

Keywords: Cloud Computing; Risk Assessment; Risk Management; Insurance.

Paper 4: A Survey on Models and Query Languages for Temporally Annotated RDF

Abstract: In this paper, we provide a survey on the models and query languages for temporally annotated RDF. In most of the works, a temporally annotated RDF ontology is essentially a set of RDF triples associated with temporal constraints, where, in the simplest case, a temporal constraint is a validity temporal interval. However, a temporally annotated RDF ontology may also be a set of triples connecting resources with a specific lifespan, where each of these triples is also associated with a validity temporal interval. Further, a temporal RDF ontology may be a set of triples connecting resources as they stand at specific time points. Several query languages for temporally annotated RDF have been proposed, where most of which extend SPARQL or translate to SPARQL. Some of the works provide experimental results while the rest are purely theoretical.

Author 1: Anastasia Analyti

Author 2: Ioannis Pachoulakis

Keywords: Temporal RDF; provenance; semantics; query languages.

Paper 5: An RGB Image Encryption Supported by Wavelet-based Lossless Compression

Abstract: In this paper we have proposed a method for an RGB image encryption supported by lifting scheme based lossless compression. Firstly we have compressed the input color image using a 2-D integer wavelet transform. Then we have applied lossless predictive coding to achieve additional compression. The compressed image is encrypted by using Secure Advanced Hill Cipher (SAHC) involving a pair of involutory matrices, a function called Mix() and an operation called XOR. Decryption followed by reconstruction shows that there is no difference between the output image and the input image. The proposed method can be used for efficient and secure transmission of image data.

Author 1: Ch. Samson

Author 2: V. U. K. Sastry

Keywords: Image compression; Wavelet Transform; image encryption; Lifting Wavelet ; Secure Advanced Hill Cipher.

Paper 6: Feature Subsumption for Sentiment Classification of Dynamic Data in Social Networks using SCDDF

Abstract: The analysis of opinions till now is done mostly on static data rather than on the dynamic data. Opinions may vary in time. Earlier methods concentrated on opinions expressed in an individual site. But on a given concept opinions may vary from site to site. Also the past works did not consider the opinions at aggregate level. This paper proposes a novel method for Sentiment Classification that uses Dynamic Data Features (SCDDF). Experiments were conducted on various product reviews collected from different sites using QTP. Opinions were aggregated using Bayesian networks and Natural Language Processing techniques. Bulk amount of dynamic data is considered rather than the static one. Our method takes as input a collection of comments from the social networks and outputs ranks to the comments within each site and finally classifies all comments irrespective of the site it belongs to. Thus the user is presented with overall evaluation of the product and its features.

Author 1: Jayanag. B

Author 2: Vineela. K

Author 3: Dr. Vasavi. S

Keywords: Sentiment classification; Natural language processing (NLP); opinions; features; Quick Test Professional (QTP); feature identification; sentiment prediction; summary generation.

Paper 7: Application of Relevance Vector Machines in Real Time Intrusion Detection

Abstract: In the recent years, there has been a growing interest in the development of change detection techniques for the analysis of Intrusion Detection. This interest stems from the wide range of applications in which change detection methods can be used. Detecting the changes by observing data collected at different times is one of the most important applications of network security because they can provide analysis of short interval on global scale. Research in exploring change detection techniques for medium/high network data can be found for the new generation of very high resolution data. The advent of these technologies has greatly increased the ability to monitor and resolve the details of changes and makes it possible to analyze. At the same time, they present a new challenge over other technologies in that a relatively large amount of data must be analyzed and corrected for registration and classification errors to identify frequently changing trend. In this research paper an approach for Intrusion Detection System (IDS) which embeds a Change Detection Algorithm with Relevance Vector Machine (RVM) is proposed. IDS are considered as a complex task that handles a huge amount of network related data with different parameters. Current research work has proved that kernel learning based methods are very effective in addressing these problems. In contrast to Support Vector Machines (SVM), the RVM provides a probabilistic output while preserving the accuracy. The focus of this paper is to model RVM that can work with large network data set in a real environment and develop RVM classifier for IDS. The new model consists of Change Point (CP) and RVM which is competitive in processing time and improve the classification performance compared to other known classification model like SVM. The goal is to make the system simple but efficient in detecting network intrusion in an actual real time environment. Results show that the model learns more effectively, automatically adjust to the changes and adjust the threshold while minimizing the false alarm rate with timely detection.

Author 1: Naveen N. C

Author 2: Dr Natarajan.S

Author 3: Dr Srinivasan.R

Keywords: Intrusion Detection; Change Point Detection; Relevance Vector Machine; Outlier Detection.

Paper 8: Convenience and Medical Patient Database Benefits and Elasticity for Accessibility Therapy in Different Locations

Abstract: When a patient comes to a hospital, clinic, physician practices or other clinics, the enrollment section will ask whether the patient in question had never come or not. If the patient in question said he had never come then the officer will ask you Medication Patient Identification Card (KiB), which will be used to search for patient records in question. In the conventional health care, then the officer will use a tracer to locate patient records at the storage warehouse in the form of stacks of paper. If a patient at a hospital is still a bit it will not be problematic, but if the patient sudha achieve large-scale number in the hundreds of thousands or even millions it will certainly cause problems. Database records are kept in hospital untapped to the maximum to be exchanged at another hospital when the patient arrives at another hospital for further treatment or research purposes. This study aims to produce a computerized model of inter Medical Information Systems Hospital. Facilitate the benefits of this research is in the medical records of patients get information, patient history properly stored in computerized medical records, patient data search can be found quicker resulting in faster unhandled The expected outcome of this research is rapidly tertanganinya patients coming to a clinic and when the patient comes to the clinic to another place then the patient's medical resume database and the analysis can be found immediately.

Author 1: Bambang Eka Purnama

Author 2: Sri Hartati

Keywords: Patient Medical Record.

Paper 9: A computational linguistic approach to natural language processing with applications to garden path sentences analysis

Abstract: This paper discusses the computational parsing of GP sentences. By an approach of combining computational linguistic methods, e.g. CFG, ATN and BNF, we analyze the various syntactic structures of pre-grammatical, common, ambiguous and GP sentences. The evidence shows both ambiguous and GP sentences have lexical or syntactic crossings. Any choice of the crossing in ambiguous sentences can bring a full-parsed structure. In GP sentences, the probability-based choice is the cognitive prototype of parsing. Once the part-parsed priority structure is replaced by the full-parsed structure of low probability, the distinctive feature of backtracking appears. The computational analysis supports Pritchett’s idea on processing breakdown of GP sentences.

Author 1: DU Jia-li

Author 2: YU Ping-fang

Keywords: Natural language processing; computational linguistics; context free grammar; Backus–Naur Form; garden path sentences.

Paper 10: Effect of Driver Strength on Crosstalk in Global Interconnects

Abstract: The Noise estimation and avoidance are becoming critical, in today’s high performance IC design. An accurate yet efficient crosstalk noise model which contains as many driver/interconnect parameters as possible, is necessary for any sensitivity based noise avoidance approach. In this paper, we present an analysis for crosstalk noise model which incorporates all physical properties including victim and aggressor drivers, distributed RC characteristics of interconnects and coupling locations in both victim and aggressor lines. Also shown that crosstalk can be minimized by driver sizing optimization technique. These models are verified for various deep submicron technologies.

Author 1: Kalpana. A. B

Author 2: P.V.Hunagund

Keywords: Coupling; crosstalk; Interconnect; noise; victim.

Paper 11: E-learning System Which Allows Students’ Confidence Level Evaluation with Their Voice When They Answer to the Questions During Achievement Tests

Abstract: E-learning system which allows students’ confidence level evaluation with their voice when they answer to the question during achievement tests is proposed. Through experiments of comparison of students’ confidence level between the conventional (without evaluation) and the proposed (with evaluation), 17-57% of improvement is confirmed for the proposed e-learning system.

Author 1: Kohei Arai

Keywords: learnng system; confidence level evaluation; emotion recognition with voice.

Paper 12: Error Analysis of Air Temperature Profile Retrievals with Microwave Sounder Data Based on Minimization of Covariance Matrix of Estimation Error

Abstract: Error analysis of air temperature profile retrievals with microwave sounder data based on minimization of covariance matrix of estimation error is conducted. Additive noise is taken into account in the observation data with microwave sounder onboard satellite. Method for air temperature profile retrievals based on minimization of difference of brightness temperature between model driven microwave sounder data and actual microwave sounder data is also proposed. The experimental results shows reasonable air temperature retrieval accuracy can be achieved by the proposed method.

Author 1: Kohei Arai

Keywords: Error analysis; leastsquare method; microwave sounder;air temperature profile.

Paper 13: Fast DC Mode Prediction Scheme For Intra 4x4 Block In H.264/AVC Video Coding Standard

Abstract: In this paper, the researchers proposed a new scheme for DC mode prediction in intra frame for 4X4 block. In this scheme, the upper and left neighboring pixels would be used to predict each of the pixels in the 4X4 block with different weight. The prediction equations for each position of the 4X4 block in DC mode would be static with fixed weighting coefficients. As a result, the computational time for intra frame would be decreased considerably with an increase in PSNR.

Author 1: Tajdid UI Alam

Author 2: Jafor Ikbal

Author 3: Touhid Ul Alam

Keywords: Intra; macroblock (MB); DC mode; luma; prediction.

Paper 14: Free Open Source Software: FOSS Based GIS for Spatial Retrievals of Appropriate Locations for Ocean Energy Utilizing Electric Power Generation Plants

Abstract: Free Open Source Software: FOSS based Geographic Information System: GIS for spatial retrievals of appropriate locations for ocean wind and tidal motion utilizing electric power generation plants is proposed. Using scatterometer onboard earth observation satellites, strong wind coastal areas are retrieved with FOSS/GIS of PostgreSQL/GIS. PostGIS has to be modified together with altimeter and scatterometer database. These modification and database creation would be a good reference to the users who would like to create GIS system together with database with FOSS.

Author 1: Kohei Arai

Keywords: free open source software; postgres SQL; GIS; spatial retrieval.

Paper 15: Knowledge Sharing Protocol for Smart Spaces

Abstract: In this paper we present a novel knowledge sharing protocol (KSP) for semantic technology empowered ubiquitous computing systems. In particular the protocol is designed for M3 which is a blackboard based semantic interoperability solution for smart spaces. The main difference between the KSP and existing work is that KSP provides SPARQL-like knowledge sharing mechanisms in compact binary format that is designed to be suitable also for resource restricted devices and networks. In order to evaluate the KSP in practice we implemented a case study in a prototype smart space, called Smart Greenhouse. In the case study the KSP messages were on average 70.09% and 87.08% shorter than the messages in existing M3 communication protocols. Because the KSP provides a mechanism for automating the interaction in smart spaces it was also possible to implement the case study with fewer messages than with other M3 communication protocols. This makes the KSP a better alternative for resource restricted devices in semantic technology empowered smart spaces.

Author 1: Jussi Kiljander

Author 2: Francesco Morandi

Author 3: Juha-Pekka Soininen

Keywords: Semantic Web; SPARQL; Ambient Intelligence; Ubiquitous Computing; embedded system; M3.

Paper 16: Localisation of Numerical Date Field in an Indian Handwritten Document

Abstract: This paper describes a method to localise all those areas which may constitute the date field in an Indian handwritten document. Spatial patterns of the date field are studied from various handwritten documents and an algorithm is developed through statistical analysis to identify those sets of connected components which may constitute the date. Common date patterns followed in India are considered to classify the date formats in different classes. Reported results demonstrate promising performance of the proposed approach.

Author 1: S Arunkumar

Author 2: Pallab Kumar Sahu

Author 3: Sudeep Gorai

Author 4: Kalyan Ghosh

Keywords: Connected Components; Feature Extraction; Spatial Arrangement; K-NN classifier.

Paper 17: Particle Swarm Optimization for Calibrating and Optimizing Xinanjiang Model Parameters

Abstract: The Xinanjiang model, a conceptual hydrological model is well known and widely used in China since 1970s. Therefore, most of the parameters in Xinanjiang model have been calibrated and pre-set according to different climate, dryness, wetness, humidity, topography for various catchment areas in China. However, Xinanjiang model is not applied in Malaysia yet and the optimal parameters are not known. The calibration of Xinanjiang model parameters through trial and error method required much time and effort to obtain better results. Therefore, Particle Swarm Optimization (PSO) is adopted to calibrate Xinanjiang model parameters automatically. In this paper, PSO algorithm is used to find the best set of parameters for both daily and hourly models. The selected study area is Bedup Basin, located at Samarahan Division, Sarawak, Malaysia. For daily model, input data used for model calibration was daily rainfall data Year 2001, and validated with data Year 1990, 1992, 2000, 2002 and 2003. A single storm event dated 9th to 12thOctober 2003 was used to calibrate hourly model and validated with 12 different storm events. The accuracy of the simulation results are measured using Coefficient of Correlation (R) and Nash-Sutcliffe Coefficient (E2). Results show that PSO is able to optimize the 12 parameters of Xinanjiang model accurately. For daily model, the best R and E2 for model calibration are found to be 0.775 and 0.715 respectively, and average R=0.622 and E2=0.579 for validation set. Meanwhile, R=0.859 and E2=0.892 are yielded when calibrating hourly model, and the average R and E2 obtained are 0.705 and 0.647 respectively for validation set.

Author 1: Kuok King Kuok

Author 2: Chiu Po Chan

Keywords: Conceptual rainfall-runoff model; Particle Swarm Optimization; Xinanjiang model calibration.

Paper 18: Probabilistic: A Fuzzy Logic-Based Distance Broadcasting Scheme For Mobile Ad Hoc Networks

Abstract: An on-demand route discovery method in mobile ad hoc networks (MANET) uses simple flooding method, whereas a mobile node blindly rebroadcasts received route request (RREQ) packets until a route to a particular destination is established. Thus, this leads to broadcast storm problem. This paper presents a novel algorithm for broadcasting scheme in wireless ad hoc networks using a fuzzy logic system at each node to determine its capability to broadcast route request packets, based on the node location. Our simulation analysis shows a significant improvement in performance in terms of routing overhead, MAC collisions and end-to-end delay while still achieving a good throughput compared to the traditional AODV.

Author 1: Tasneem Bano

Author 2: Jyoti Singhai

Keywords: Broadcasting; Distance based broadcasting; Fuzzy; Optimization Technique; AODV.

Paper 19: SAS: Implementation of scaled association rules on spatial multidimensional quantitative dataset

Abstract: Mining spatial association rules is one of the most important branches in the field of Spatial Data Mining (SDM). Because of the complexity of spatial data, a traditional method in extracting spatial association rules is to transform spatial database into general transaction database. The Apriori algorithm is one of the most commonly used methods in mining association rules at present. But a shortcoming of the algorithm is that its performance on the large database is inefficient. The present paper proposed a new algorithm by extracting maximum frequent itemsets based on spatial multidimensional quantitative dataset. Algorithms for mining spatial association rules are similar to association rule mining except consideration of special data, the predicates generation and rule generation processes are based on Apriori. The proposed method (SAS) Scaled Aprori on Spatial multidimensional quantitative dataset in the paper reduces the number of itemsets generated and also improves the execution time of the algorithm.

Author 1: M. N. Doja

Author 2: Sapna Jain

Author 3: M Afshar Alam

Keywords: association rules; spatial dataset; X tree.

Paper 20: Students’ Perceptions of the Effectiveness of Discussion Boards: What can we get from our students for a freebie point

Abstract: In this paper, we investigate how the students think of their experience in a junior (300 level) computer science course that uses blackboard as the underlying course management system. Blackboard’s discussion boards are heavily used for programming project support and to foster cooperation among students to answer their questions/concerns. A survey is conducted through blackboard as a voluntary quiz and the student who participated were given a participation point for their effort. The results and the participation were very interesting. We obtained statistics from the answers to the questions. The students also have given us feedback in the form of comments to all questions except for two only. The students have shown understanding, maturity and willingness to participate in pedagogy-enhancing endeavors with the premise that it might help their education and others’ education as well.

Author 1: Abdel-Hameed A. Badawy

Keywords: collaborative learning; cooperative learning; peer learning; teaching evaluation; pedagogy; discussion boards; Blackboard; pedagogy; survey; student feedback.1

Paper 21: The Impacts of ICTs on Banks

Abstract: ICT has taken the center stage in almost every aspect of human endeavor. ICT help banks improve the efficiency and effectiveness of services offered to customers, and enhances business processes, managerial decision making, and workgroup collaborations, which strengthens their competitive positions in rapidly changing and emerging economies. This paper considers the impacts and trends of ICTs on the banking industry of the 21st century. Four (4) parameters, namely: productivity, market structure, Innovation and value chain were used for benchmarking. Case studies of the IT platform employed by two Nigerian banks were included to for a more informed inference.

Author 1: Matthew K Luka

Author 2: Ibikunle A. Frank

Keywords: Banking industry; CBN; Customers; Economic growth; ICT; productivity.

Paper 22: Security Analysis of Image Cryptosystem Using Stream Cipher Algorithm with Nonlinear Filtering Function

Abstract: In this work a new algorithm for encryption image is introduced. This algorithm makes it possible to cipher and decipher images by guaranteeing a maximum security. The algorithm introduced is based on stream cipher with nonlinear filtering function. The Boolean function used in this algorithm is resilient function satisfying all the cryptographic criteria necessary carrying out the best possible compromises. In order to evaluate performance, the proposed algorithm was measured through a series of tests. Experimental results illustrate that the scheme is highly key sensitive, highly resistance to the noises and shows a good resistance against brute-force, Berlekamp-Massey Attack and algebraic attack.

Author 1: Belmeguenaï Aïssa

Author 2: Derouiche Nadir

Author 3: Mansouri Khaled

Keywords: cipherImage; cryptosystem; key-stream; nonlinear filtering function; stream cipher.

Paper 23: A Multi-Stage Optimization Model With Minimum Energy Consumption-Wireless Mesh Networks

Abstract: Optimization models related with routing, bandwidth utilization and power consumption are developed in the wireless mesh computing environment using the operations research techniques such as maximal flow model, transshipment model and minimax optimizing algorithm. The Path creation algorithm is used to find the multiple paths from source to destination.A multi-stage optimization model is developed by combining the multi-path optimization model, optimization model in capacity utilization and energy optimization model and minimax optimizing algorithm. The input to the multi-stage optimization model is a network with many source and destination. The optimal solution obtained from this model is a minimum energy consuming path from source to destination along with the maximum data rate over each link. The performance is evaluated by comparing the data rate values of superimposed algorithm and minimax optimizing algorithm. The main advantage of this model is the reduction of traffic congestion in the network.

Author 1: S. Krishnakumar

Author 2: Dr.R.Srinivasan

Keywords: optimization; breakthrough; transportation; aximization; superimposed; transshipment.

Paper 24: Time-Domain Large Signal Investigation on Dynamic Responses of the GDCC Quarterly Wavelength Shifted Distributed Feedback Semiconductor Laser

Abstract: A numerical investigation on the dynamic large-signal analysis using a time-domain traveling wave model of quarter wave-shifted distributed feedback semiconductor lasers diode with a Gaussian distribution of the coupling coefficient (GDCC) is presented. It is found that the single-mode behavior and the more hole-burning effect corrections of quarter wave-shifted distributed feedback laser with large coupling coefficient can be improved significantly by this new proposed light source.

Author 1: Abdelkarim Moumen

Author 2: Abdelkarim Zatni

Author 3: Abdenabi Elyamani

Author 4: Hamza Bousseta

Keywords: component; Distributed feedback laser; optical communication systems; Dynamic large signal analysis; Time domain model.

Paper 25: Mutual Exclusion Principle for Multithreaded Web Crawlers

Abstract: This paper describes mutual exclusion principle for multithreaded web crawlers. The existing web crawlers use data structures to hold frontier set in local address space. This space could be used to run more crawler threads for faster operation. All crawler threads fetch the URL to crawl from the centralized frontier. The mutual exclusion principle is used to provide access to frontier for each crawler thread in synchronized manner to avoid deadlock. The approach to utilize the waiting time on mutual exclusion lock in efficient manner has been discussed in detail.

Author 1: Kartik Kumar Perisetla

Keywords: Web Crawlers; Mutual Exclusion principle; Multithreading; Mutex locks.

Paper 26: A Novel Image Encryption Supported by Compression Using Multilevel Wavelet Transform

Abstract: In this paper we propose a novel approach for image encryption supported by lossy compression using multilevel wavelet transform. We first decompose the input image using multilevel 2-D wavelet transform, and thresholding is applied on the decomposed structure to get compressed image. Then we carry out encryption by decomposing the compressed image by multi-level 2-D Haar Wavelet Transform at the maximum allowed decomposition level. These results in the decomposition vector C and the corresponding bookkeeping matrix S. The decomposition vector C is reshaped into the size of the input image. The reshaped vector is rearranged by performing permutation to produce encrypted image. The vector C and the matrix S serve as key in the process of both encryption and decryption. In this analysis, we have noticed that the reconstructed image is a close replica of the input image.

Author 1: Ch. Samson

Author 2: V. U. K. Sastry

Keywords: Image compression; wavelet transform; thresholding; image encryption; compression ratio.

Paper 27: Ethernet Based Remote Monitoring And Control Of Temperature By Using Rabbit Processor

Abstract: Networking is a major component of the processes and control instrumentation systems as the network’s architecture solves many of the Industrial automation problems. There is a great deal of benefits in the process of industrial parameters to adopt the Ethernet control system. Hence an attempt has been made to develop an Ethernet based remote monitoring and control of temperature. In the present work the experimental result shows that remote monitoring and control system (RMACS) over the Ethernet.

Author 1: U. SUNEETHA

Author 2: K.TANVEER ALAM

Author 3: N.ANJU LATHA

Author 4: B.V.S.GOUD

Keywords: RMACS; Control system; Ethernet.

Paper 28: A study on Security within public transit vehicles

Abstract: In public transit vehicles, security is the major concern for the passengers. Surveillance Systems provide the security by providing surveillance cameras in the vehicles and a storage that maintains the data. The applications that allow monitoring the data in surveillance systems of public transit vehicles will provide different features to access the video and allow to perform number of operations like exporting video, generating snapshots at a particular time, viewing the live as well as playback videos. This paper studies automation process of video surveillance system that can also be applied in the surveillance system of public transit vehicles. A new feature that enhances the security to the passengers such as tracking of vehicle through the GPS (Global positioning system) tracking system and also capability of providing the vehicle information like acceleration, speed, on the user interface of application to the user.

Author 1: A. N. Seshukumar

Author 2: Dr.S.Vasavi

Author 3: Dr.V.Srinivasa Rao

Keywords: Surveillance Cameras; Global Positioning System; Automation; public transit vehicles.

Paper 29: Image Denoising using Adaptive Thresholding in Framelet Transform Domain

Abstract: Noise will be unavoidable during image acquisition process and denosing is an essential step to improve the image quality. Image denoising involves the manipulation of the image data to produce a visually high quality image. Finding efficient image denoising methods is still valid challenge in image processing. Wavelet denoising attempts to remove the noise present in the imagery while preserving the image characteristics, regardless of its frequency content. Many of the wavelet based denoising algorithms use DWT (Discrete Wavelet Transform) in the decomposition stage which is suffering from shift variance. To overcome this, in this paper we proposed the denoising method which uses Framelet transform to decompose the image and performed shrinkage operation to eliminate the noise .The framework describes a comparative study of different thresholding techniques for image denoising in Framelet transform domain. The idea is to transform the data into the Framelet basis, example shrinkage followed by the inverse transform. In this work different shrinkage rules such as universal shrink(US),Visu shrink (VS), Minmax shrink(MS), Sure shrink(SS) , Bayes shrink(BS) and Normal shrink(NS) were incorporated . Results based on different noise such as Gausssian noise, Poission noise , Salt and pepper noise and Speckle noise at (??=10,20) performed in this paper and peak signal to noise ratio (PSNR) and Structural similarity index measure(SSIM) as a measure of the quality of denoising was performed.

Author 1: S. Sulochana

Author 2: R.Vidhya

Keywords: Discrete Wavelet Transform(DWT); Framelet Transform(FT); Peak signal to noise ratio(PSNR); Structural similarity index measure(SSIM).

Paper 30: Improved Accuracy of PSO and DE using Normalization: an Application to Stock Price Prediction

Abstract: Data Mining is being actively applied to stock market since 1980s. It has been used to predict stock prices, stock indexes, for portfolio management, trend detection and for developing recommender systems. The various algorithms which have been used for the same include ANN, SVM, ARIMA, GARCH etc. Different hybrid models have been developed by combining these algorithms with other algorithms like roughest, fuzzy logic, GA, PSO, DE, ACO etc. to improve the efficiency. This paper proposes DE-SVM model (Differential Evolution- Support vector Machine) for stock price prediction. DE has been used to select best free parameters combination for SVM to improve results. The paper also compares the results of prediction with the outputs of SVM alone and PSO-SVM model (Particle Swarm Optimization). The effect of normalization of data on the accuracy of prediction has also been studied.

Author 1: Savinderjit Kaur

Author 2: Veenu Mangat

Keywords: Differential evolution; Parameter optimization; Stock price prediction; Support vector Machines; Normalization.

Paper 31: The Impact on Effectiveness and User Satisfaction of Menu Positioning on Web Pages

Abstract: The authors of this paper are conducting research into the usability of menu positioning on web pages. Other researchers have also done work in this area, but the results are not conclusive and therefore more work still needs to be done in this area. The design and results of an empirical experiment, investigating the usability of menu positioning on a supermarket web site, are presented in this paper. As a comparison, the authors tested a left vertical menu and a fisheye menu placed horizontally at the top of a page in a prototype supermarket web site against a real supermarket web site using a horizontal menu placed at the top of a page. Few significant results were observed, which gave rise to the conclusion that overall there were not many differences between the tested menu types. Furthermore, an explanation for the results observed is discussed in terms of cognitive, physical, functional and sensory affordances. It is suggested that observation of the affordances may be a more crucial aspect to menu design than the actual menu positioning.

Author 1: Dr Pietro Murano

Author 2: Kennedy K. Oenga

Keywords: Usability; menu design; menu positioning; affordances.

Paper 32: A New Automatic Method to Adjust Parameters for Object Recognition

Abstract: To recognize an object in an image, the user must apply a combination of operators, where each operator has a set of parameters. These parameters must be “well” adjusted in order to reach good results. Usually, this adjustment is made manually by the user. In this paper we propose a new method to automate the process of parameter adjustment for an object recognition task. Our method is based on reinforcement learning, we use two types of agents: User Agent that gives the necessary information and Parameter Agent that adjusts the parameters of each operator. Due to the nature of reinforcement learning the results do not depend only on the system characteristics but also the user’s favorite choices.

Author 1: Issam Qaffou

Author 2: Mohamed Sadgal

Author 3: Aziz Elfazziki

Keywords: component; Parameters adjustment; image segmentation; Q-learning; reinforcement learning.

Paper 33: An Emergency System for Succoring Children using Mobile GIS

Abstract: The large numbers of sick children in different diseases are very dreaded, and when there isn't succor at the proper time and in the type the sick child need it that makes us lose child. This paper suggested an emergency system for succoring sick child locally when he required that, and there isn't someone knows his disease. The proposed system is the first tracking system works online (24 hour in the day) but only when the sick children requiring the help using mobile GIS. In, this emergency system the child will send SMS (for easy he click one button) contains his ID and coordinates (Longitude and Latitude) via GPRS network to the web server (the child was registered previously on that server), in this step the server will locate the sick child on Google map and retrieve the child's information from the database which saved this information in registration stage, and base on these information will send succoring facility and at the same time informing the hospital, his parents, doctor, etc. about that emergency case of the child using the SMS mode through GPRS network again. The design and implement of the proposed system shows more effective cost than other systems because it used a minimum configuration (hardware and software) and works in economic mode.

Author 1: Ayad Ghany Ismaeel

Keywords: GPS; GPRS; Mobile GIS; SMS; Tracking device; Emergency System.

Paper 34: Billing System Design Based on Internet Environment

Abstract: This paper deals with the design of Internet billing system, in which it is possible pay invoices electronically. This approach is implemented via virtual banks, in which the process of money transfer can be implemented. In other hand many applications can be realize such as; deposit e-money, withdrawal e-money and determine account balance. A Gate way translator is used to apply authentication rules, security and privacy.

Author 1: Muzhir Shaban Al-Ani

Author 2: Rabah Noory

Author 3: Dua'a Yaseen Al-Ani

Keywords: Billing System; Internet Billing system; E-Commerce; E-bank; bill payment; Authentication; Security.

Paper 35: A Performance Evaluation of Multiple Input Queued (MIQ) Switch with Iterative Weighted Slip Algorithm

Abstract: Many researchers had evaluated the throughput and delay performance of virtual output queued (VOQ) packet switches using iterative weighted/un-weighted scheduling algorithms. Prof. Nick Mckeown from Stanford University had evolved with excellent iterative maximal matching (i-slip) scheme which provides throughput near to 100%. Prof. Kim had suggested multiple input queued architecture which also provide more than 90 % throughput for less number of input queues per port. (In VOQ N queues per port are used). Our attempt is to use MIQ architecture and evaluate delay, throughput performance with i-slip algorithm for scheduling. While evaluating performance we had used Bernoulli’s and Bursty (ON-OFF) traffic models.

Author 1: S N Kore

Author 2: Sayali Kore

Author 3: Ajinkya Biradar

Author 4: Dr. P J Kulkarni

Keywords: Network communications; Packet-switching networks;routing protocols; Sequencing and scheduling.

Paper 36: An integrated modular approach for Visual Analytic Systems in Electronic Health Records

Abstract: Latest visual analytic tools help physicians to visualize temporal data in regards to medical health records. Existing systems lack vast support in the generalized collaboration, a single user-centered and task based design for Electronic Health Records (EHR). Already existing frameworks are unable to mentor the interface gaps due to problems like complexity of data sets, increased temporal information density and no support to live databases. These are significant reasons for a single model to comply the end user requirements. We propose an integrated model termed as CARE 1.0 as a future Visual analytic process model for resolving these kinds of issues based on mix method studies. This will base on different disciplines of HCI, Statistics as well as Computer Sciences. This proposed model encompasses the cognitive behavioral requirements of its stake holder’s i.e. physicians, database administrators and visualization designers. It helps in presenting a more generalized and detailed visualization for desired medical data sets.

Author 1: Muhammad Sheraz Arshad Malik

Author 2: Dr.Suziah Sulaiman

Keywords: Visual analytic Systems; EHR; Information visualization; CARE 1.0.

Paper 37: Developing Backward Chaining Algorithm of Inference Engine in Ternary Grid Expert System

Abstract: The inference engine is one of main components of expert system that influences the performance of expert system. The task of inference engine is to give answers and reasons to users by inference the knowledge of expert system. Since the idea of ternary grid issued in 2004, there is only several developed method, technique or engine working on ternary grid knowledge model. The in 2010 developed inference engine is less efficient because it works based on iterative process. The in 2011 developed inference engine works statically and quite expensive to compute. In order to improve the previous inference methods, a new inference engine has been developed. It works based on backward chaining process in ternary grid expert system. This paper describes the development of inference engine of expert system that can work in ternary grid knowledge model. The strategy to inference knowledge uses backward chaining with recursive process. The design result is implemented in the form of software. The result of experiment shows that the inference process works properly, dynamically and more efficient to compute in comparison to the previous developed methods.

Author 1: Yuliadi Erdani

Keywords: expert systems; ternary grid; inference engine; backward chaining.

Paper 38: Comparison Study of Commit Protocols for Mobile Environment

Abstract: This paper presents a study of protocols to commit the transactions distributed over several mobile and fixed units and provides the method to handle mobility at the application layer. It describes the solutions to defeat the dilemma related to principle implementation of the Two Phase Commit (2PC) protocol which is essential to ensure the consistent commitment of distributed transactions. The paper surveys different approaches proposed for mobile transaction and outline how the conventional commitment are revisited in order to fit the needs of mobile environment. This approach deals with the frequency disconnections and the movement of mobile devices. This paper also proposes Single Phase Reliable Timeout Based Commit (SPRTBC) protocol that preserves the 2PC principle and it lessens the impact of unreliable wireless communications.

Author 1: Bharati Harsoor

Author 2: Dr.S.Ramachandram

Keywords: Mobile Transactions; Transaction Log; Transaction Recovery; Network disconnection; handoff; ACID properties.

Paper 39: Optimized Pessimistic Fibonacci Back-off Algorithm (PFB)

Abstract: MANET is a self-directed system consisting of mobile nodes, which can be either routers and/or hosts. Nodes in MANET are connected by wireless links without base stations. The Backoff algorithm considered as a main element of Media Access Control (MAC) protocol, which is used to avoid collision in MANET’s. The Fibonacci Backoff algorithm and the Pessimistic Fibonacci Backoff are proposed to improve network performance depending on contention window size. This research introduces a new hybrid Backoff algorithm called Pessimistic Fibonacci Backoff (PFB) Algorithm which merges the two previous algorithms in order to find the most proper contention window sizes that reduce collisions as much as possible. This research takes into consideration and evaluates each of the following main measurements: Packet delivery ratio, normalized routing load and end-to-end delay. Based on the extracted simulation results, PFB algorithm outperforms Pessimistic Linear-Exponential Backoff (PLEB) by up to 76%,40.41%, 31.88% in terms of Packet delivery ratio, end-to-end delay and normalized routing load respectively, especially in the sparse environments. All of the simulation results are obtained by the well-known NS-2 Simulator, version 2.34, without any distance or location measurements devices.

Author 1: Muneer Bani Yassein

Author 2: Mohammed Ahmed Alomari

Author 3: Constandinos X. Mavromoustakis

Keywords: Back-off; collision; end-to-end delay; normalized routing load; packet delivery Ratio; MANET’s; PLEB; PFB; and MAC.