S. Saejung, A. Boondee, J. Preechasuk, C. Chantrapornchai
{"title":"On the comparison of digital image steganography algorithm based on DCT and wavelet","authors":"S. Saejung, A. Boondee, J. Preechasuk, C. Chantrapornchai","doi":"10.1109/ICSEC.2013.6694803","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694803","url":null,"abstract":"Steganography usually focuses on communicating secret data through a selected media such as image, audio, video etc. The goal of it is to hide the information in such a way that it is not prone to the detection while keeping the quality of the media. Also, other thing is also important about the algorithm itself such as robustness, capacity of hiding, computation time etc. In this work, we study the algorithms of steganography based on Discrete Cosine Transform (DCT) and Wavelet transform. We study the aspects of media quality after hiding the information in the digital images. Particularly, we compare the performance of the algorithms in [7] and [10] using Peak Signal-to-Noise Ration (PSNR). It is found that the algorithm using DCT has the PSNR value between 51-53dB while the algorithm using Wavelet has the PSNR value between 28-52dB on a test set of images. Also, considering the robustness, the DCT-based algorithm has a better PSNR when the image compression ratio increases.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125709257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The feature selection for classification by applying the Significant Matrix with SPEA2","authors":"Ekapong Chuasuwan, Narissara Eiamkanitchat","doi":"10.1109/ICSEC.2013.6694809","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694809","url":null,"abstract":"This paper presents a novel application of Genetic Algorithm for the feature selection. The main purpose is to provide proper subset features for decision tree construction in the classification task. New method with the use of “Significant Matrix” on genetic algorithm is presented. The main function is to calculate the relationship between the feature and class label assigned to a fitness value for the population. The algorithm presented important features selected by considering the class of the data and number of features for the least amount in the Significant Matrix. The next step will then update the feature number and the record number to repeat the process until a stop condition is met. Classification by decision tree is used to verify the importance of the features selected by the proposed method. The model tested with 11 different datasets. The results show that the method yields high accuracy of the classification and higher satisfaction compared to classification using artificial neural network. Experimental results show that the proposed method not only provides a higher accuracy, but also reduce the complexity by using less features of the dataset.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133094403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A web-based management system design for wireless sensor network monitoring","authors":"Wibhada Naruephiphat, Ridnarong Prom-Ya, Chalermpol Chansripinyo","doi":"10.1109/ICSEC.2013.6694794","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694794","url":null,"abstract":"In this paper, we formalize the main features of web-based management system for wireless sensor network monitoring. We design our web management framework using MVC (Model-View-Control) architecture, which encourages developers to partition the applications in the design phase. Our system design is scalable, flexible and reusable for wireless sensor network monitoring applications. We implemented and tested our web-based management system with two wireless sensor network applications, which are power monitoring and temperature/humidity monitoring. Based on our framework design, we can extend our web-based management system to support other sensor network applications in the future.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130780315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manik Sharma, Gurvinder Singh, R. Virk, Gurdev Singh
{"title":"Design and comparative analysis of DSS queries in distributed environment","authors":"Manik Sharma, Gurvinder Singh, R. Virk, Gurdev Singh","doi":"10.1109/ICSEC.2013.6694756","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694756","url":null,"abstract":"Query processing and its optimization is one of the major aspects of distributed database system. The research has exposed that the design of a query and its execution technique plays an important role in the optimization of a query. There are two major categories of distributed queries in distributed database system known as Decision Support system (DSS) queries and Online Transaction Processing (OLTP) queries. In this paper the prime focus is on design and analysis of DSS queries. The selected set of DSS queries are simulated by using exhaustive enumerative technique and genetic approach under serial and parallel processing environment. The simulation results show that an exhaustive enumeration approach provides optimized solution but takes huge time for complex DSS queries (Hours, Days, Month or even Years), hence it is infeasible to implement this approach for optimizing a set of DSS queries. On the other hand genetic algorithms optimize DSS Queries very quickly but show loss in accuracy and quality of solution as compare to exhaustive enumerative approach. Further the parallel execution of the different sub operations of a DSS query significantly reduces the total cost of system resources.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131880882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dimensionality reduction on slope one predictor in the food recommender system","authors":"Supaporn Bundasak, K. Chinnasarn","doi":"10.1109/ICSEC.2013.6694763","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694763","url":null,"abstract":"Slope One Predictor is one of the most successful approaches for predicting the online rating-base collaborative filtering. The researcher examined the use of dimensionality reduction to improve performance for a new data set analysis in the process Slope One prediction which is used for analyzing data related to persons' likes or interests in the menu of food that people do not want to eat similar dishes iteratively. This paper presents a method for extracting the user's relationally similar behavior by searching for best neighbors in computing deviations between varied pairs of items or deviation matrix used this matrix to make predictions. The goals of improving accuracy of recommender systems that the researchers consider the menu fit for the data; therefore, finding the best technique and using the recommended data as needed by the inquirer is essential and vital in the future.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128239559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kanok Hournkumnuard, B. Dolwithayakul, C. Chantrapornchai
{"title":"Parallel simulation of magnetic targeting of nano-carriers in capillary using OpenMP and MPI","authors":"Kanok Hournkumnuard, B. Dolwithayakul, C. Chantrapornchai","doi":"10.1109/ICSEC.2013.6694751","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694751","url":null,"abstract":"A parallel algorithm for simulating concentration distribution of nano-carriers in a capillary is developed by using the combination of OpenMP and MPI. The transport of the carriers under the influences of diffusion, blood flow and magnetic driving force is investigated in two dimensions on a plane that symmetrically slices through the capillary diameter and parallel to the capillary axis. The continuity equation governing carriers transport is solved numerically as initial and boundary values problem by using the finite difference method. The computing tasks of updating carrier concentration at each time step are distributed to a group of nodes and threads in the parallel simulation. The patterns of carrier concentration distribution, which are simulation results, show the progress of carrier accumulation within the considered region. These data can be visualized and are useful for biomedical researchers. The performance of parallel computing by OpenMP and MPI is also evaluated.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134081192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A dual-band wireless energy transfer protocol for heterogeneous sensor networks powered by RF energy harvesting","authors":"Prusayon Nintanavongsa, M. Naderi, K. Chowdhury","doi":"10.1109/ICSEC.2013.6694814","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694814","url":null,"abstract":"Radio frequency (RF) energy harvesting promises to realize battery-less sensor networks by converting energy contained in electromagnetic waves into useful electrical energy. We consider a network architecture that allows heterogeneous frequency harvesting. One class of sensors harvests RF energy on the DTV band (614 MHz) while another uses the 915 MHz ISM band. We study the effective energy transfer that is achieved under these circumstances, and then design a link layer protocol called RF-HSN that optimizes the energy delivery to energy-hungry sensors with the optimal duty cycle. To the best of our knowledge, this is the first wireless energy transfer protocol for heterogeneous frequency RF energy harvesting, and through a combination of experimentation and simulation studies, we demonstrate over 59% higher duty cycle and 66% average network throughput improvement over the classical CSMA MAC protocol.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130158730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data integration for phone users' mobility analysis","authors":"T. Niemi, M. Niinimaki","doi":"10.1109/ICSEC.2013.6694764","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694764","url":null,"abstract":"The aim of this paper is to develop methods for integrating external data with a mobile phone user data sample collected in Switzerland. The external data contains weather and stock price information, and the integration is done using locations and time stamps. We then analyze the resulting data using a multidimensional approach and statistical tools. Though the data is limited in scale, it indicates that weather or economic up/downturns does not affect the phone users' mobility very much.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114363662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Radius Particle Swarm Optimization","authors":"M. Anantathanavit, M. Munlin","doi":"10.1109/ICSEC.2013.6694765","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694765","url":null,"abstract":"Particle Swarm Optimization (PSO) is a swarm intelligence based and stochastic algorithm to solve the optimization problem. Nevertheless, the traditional PSO has disadvantage from the premature convergence when finding the global optimization. To prevent from falling into the local optimum, we propose the Radius particle swarm optimization (R-PSO) which extends the Particle Swarm Optimization by regrouping the agent particles within the given radius of the circle. It initializes the group of particles, calculates the fitness function, and finds the best particle in that group. The R-PSO employs the group-swarm to keep the swarm diversity and evolution by sharing information from the agent particles which successfully maintain the balance between the global exploration and the local exploitation. Therefore the agent particle guides the neighbour particles to jump out of the local optimum and achieve the global best. The proposed method is tested against the well-known benchmark dataset. The results show that the R-PSO performs better than the traditional PSO in solving the multimodal complex problems.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131573533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prefix filtering with data partitioning for similarity join","authors":"Methus Bhirakit, J. Chongstitvatana","doi":"10.1109/ICSEC.2013.6694772","DOIUrl":"https://doi.org/10.1109/ICSEC.2013.6694772","url":null,"abstract":"Many applications, such as data integration, and data preparation, use similarity join as an important operation. In real-world applications, the challenge of similarity joins arises when data sets are large. Filter and verify methods have been proposed to reduce the running time of similarity join. The prefix filtering algorithm, which is one of the filter and verify methods, filters out some dissimilar strings by examining only the prefix of strings, instead of the whole strings. In this paper, we propose the data partitioning for prefix filtering method using in similarity join. For our approach, the database is divided into partitions and prefix filtering is performed for each partition of data. This proposed algorithm supports parallelism because filtering can be done on each partition independently. Furthermore, when the dataset is partitioned into smaller sets, a proper prefix length can be determined for each data partition. This also improves the selection of candidate strings, and reduces the verify time. An experiment is performed to compare the proposed algorithm to state-of-the-art algorithms. The experiment shows that our method achieves higher performance by reducing in the number of candidate strings and parallel execution.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130208293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}