Pub Date : 2013-09-16DOI: 10.18495/COMENGAPP.V2I2.24
M. Prasad, B. Kumar, Y.Naga Satish, K. Sriraman
Detecting and gaining clues from the crime scene plays a major role in the process of investigation. Now a days with increase of cybercrime and fraud on the internet, digital forensics gaining importance. It needs to collect information the events happened at crime place. This paper deals with event reconstruction process which is useful for digital crime scene. The process of reconstruction is based on crime event and event characteristics. It also furnishes crime rate guess using some semi-formal techniques. Keyword: Digital Investigation, Digital Forensics, Events, Attack Trees, Reconstruction
{"title":"Reconstruction of Events in Digital Forensics","authors":"M. Prasad, B. Kumar, Y.Naga Satish, K. Sriraman","doi":"10.18495/COMENGAPP.V2I2.24","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I2.24","url":null,"abstract":"Detecting and gaining clues from the crime scene plays a major role in the process of investigation. Now a days with increase of cybercrime and fraud on the internet, digital forensics gaining importance. It needs to collect information the events happened at crime place. This paper deals with event reconstruction process which is useful for digital crime scene. The process of reconstruction is based on crime event and event characteristics. It also furnishes crime rate guess using some semi-formal techniques. Keyword: Digital Investigation, Digital Forensics, Events, Attack Trees, Reconstruction","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134062444","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}
Pub Date : 2013-09-13DOI: 10.18495/COMENGAPP.V2I2.22
G. Vinodhini, R. Chandrasekaran
Online product reviews is considered as a major informative resource which is useful for both customers and manufacturers. The online reviews are unstructured-free-texts in natural language form. The task of manually scanning through huge volume of review is very tedious and time consuming. Therefore it is needed to automatically process the online reviews and provide the necessary information in a suitable form. In this paper, we dedicate our work to the task of classifying the reviews based on the opinion, i.e. positive or negative opinion. This paper mainly addresses using ensemble approach of Support Vector Machine (SVM) for opinion mining. Ensemble classifier was examined for feature based product review dataset for three different products. We showed that proposed ensemble of Support Vector Machine is superior to individual baseline approach for opinion mining in terms of error rate and Receiver operating characteristics Curve. Key words: Opinion, Classification, Machine Learning.
{"title":"Product Review Mining for Opinion Using Ensemble Classifier","authors":"G. Vinodhini, R. Chandrasekaran","doi":"10.18495/COMENGAPP.V2I2.22","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I2.22","url":null,"abstract":"Online product reviews is considered as a major informative resource which is useful for both customers and manufacturers. The online reviews are unstructured-free-texts in natural language form. The task of manually scanning through huge volume of review is very tedious and time consuming. Therefore it is needed to automatically process the online reviews and provide the necessary information in a suitable form. In this paper, we dedicate our work to the task of classifying the reviews based on the opinion, i.e. positive or negative opinion. This paper mainly addresses using ensemble approach of Support Vector Machine (SVM) for opinion mining. Ensemble classifier was examined for feature based product review dataset for three different products. We showed that proposed ensemble of Support Vector Machine is superior to individual baseline approach for opinion mining in terms of error rate and Receiver operating characteristics Curve. Key words: Opinion, Classification, Machine Learning.","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128423767","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}
Pub Date : 2013-09-13DOI: 10.18495/COMENGAPP.V2I2.21
R. F. Malik, Saparudin, Intan Septyliana
Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatos’s method. Gatos’s method is doing preprocessing, foreground estimation using Sauvola’s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvola’s method is final thresholding from Wiener filter image result and source image, and count F-Measure from both of these binary image results. By using optimum constant value on k value, n local window, K sw and K sw1, Gatos’s method can produced binary image better than Sauvola’s method based on F-Measure value. Sauvola’s method produces average value F=84,62%, Sauvola’s method with Wiener filter produces average value F=99.06% and Gatos’s method produces average value F=99,43%. Keyword : Degraded Document Image, Adaptive Approcah for Binarization, Gatos’s Method, Sauvola’s Method DOI: 10.18495/comengapp.22.185194
{"title":"An Analysis of Adaptive Approach for Document Binarization","authors":"R. F. Malik, Saparudin, Intan Septyliana","doi":"10.18495/COMENGAPP.V2I2.21","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I2.21","url":null,"abstract":"Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatos’s method. Gatos’s method is doing preprocessing, foreground estimation using Sauvola’s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvola’s method is final thresholding from Wiener filter image result and source image, and count F-Measure from both of these binary image results. By using optimum constant value on k value, n local window, K sw and K sw1, Gatos’s method can produced binary image better than Sauvola’s method based on F-Measure value. Sauvola’s method produces average value F=84,62%, Sauvola’s method with Wiener filter produces average value F=99.06% and Gatos’s method produces average value F=99,43%. Keyword : Degraded Document Image, Adaptive Approcah for Binarization, Gatos’s Method, Sauvola’s Method DOI: 10.18495/comengapp.22.185194","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115969467","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}
Pub Date : 2013-09-13DOI: 10.18495/COMENGAPP.V2I2.23
Amanpreet Kaur, Richa Sharma
Digital images are foremost source for information transfer. Due to advancement of the technology, images are now not treated as reliable source of information. Digital images can be edited according to the need. Adding and deleting content from an image is most easiest and popular way of creating image forgery, which is known as copy-move forgery. Digital Image Forensics is the field that deals with the authenticity of the images. Digital image forensics checks the integrity of the images by detecting various forgeries. In order to hide the traces of copy-move forgery there are editing operations like rotation, scaling, JPEG compression, Gaussian noise called as attacks, which are performed on the copied part of the image before pasting. Till now these attacks are not detected by the single method. The novel approach is proposed to detect image forgery by copy-move under above attacks by combining block-based and keypoint-based method. Keywords: Digital image forensics, copy-move forgery, passive blind approach, keypoint-based, block-based methods
{"title":"Optimization of Copy-Move Forgery Detection Technique","authors":"Amanpreet Kaur, Richa Sharma","doi":"10.18495/COMENGAPP.V2I2.23","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I2.23","url":null,"abstract":"Digital images are foremost source for information transfer. Due to advancement of the technology, images are now not treated as reliable source of information. Digital images can be edited according to the need. Adding and deleting content from an image is most easiest and popular way of creating image forgery, which is known as copy-move forgery. Digital Image Forensics is the field that deals with the authenticity of the images. Digital image forensics checks the integrity of the images by detecting various forgeries. In order to hide the traces of copy-move forgery there are editing operations like rotation, scaling, JPEG compression, Gaussian noise called as attacks, which are performed on the copied part of the image before pasting. Till now these attacks are not detected by the single method. The novel approach is proposed to detect image forgery by copy-move under above attacks by combining block-based and keypoint-based method. Keywords: Digital image forensics, copy-move forgery, passive blind approach, keypoint-based, block-based methods","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128539635","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}
Pub Date : 2013-05-07DOI: 10.18495/COMENGAPP.V2I1.16
E. Kinani, Fatima Amounas
In recent years, Elliptic Curve Cryptography (ECC) has attracted the attention of researchers due to its robust mathematical structure and highest security compared to other existing algorithm like RSA. Our main objective in this work was to provide a novel blind signature scheme based on ECC. The security of the proposed method results from the infeasibility to solve the discrete logarithm over an elliptic curve. In this paper we introduce a proposed to development the blind signature scheme with more complexity as compared to the existing schemes. Keyword: Cryptography, Blind Signature, Elliptic Curve, Blindness, Untraceability. DOI: 10.18495/comengapp.21.151160
{"title":"Proposed Developments of Blind Signature Scheme based on The Elliptic Curve Discrete Logarithm Problem","authors":"E. Kinani, Fatima Amounas","doi":"10.18495/COMENGAPP.V2I1.16","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.16","url":null,"abstract":"In recent years, Elliptic Curve Cryptography (ECC) has attracted the attention of researchers due to its robust mathematical structure and highest security compared to other existing algorithm like RSA. Our main objective in this work was to provide a novel blind signature scheme based on ECC. The security of the proposed method results from the infeasibility to solve the discrete logarithm over an elliptic curve. In this paper we introduce a proposed to development the blind signature scheme with more complexity as compared to the existing schemes. Keyword: Cryptography, Blind Signature, Elliptic Curve, Blindness, Untraceability. DOI: 10.18495/comengapp.21.151160","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114414392","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}
Pub Date : 2013-05-03DOI: 10.18495/COMENGAPP.V2I1.17
M. Aghaie, F. Shokri, M. Y. Tabari
There are far more cars on the road now than there used to be. Therefore, Controlling and managing the huge volume of traffic is virtually impossible without the use of computer technology. This paper represents design and implement of an intelligent system for license plate recognition based on three main steps. This process includes the detection of license plate location, character segmentation and character recognition. In this study, we used Classifier svm to detect the characters. According to the results, the performance of the proposed system is better compared to similar algorithms such as neural network. It is worth mentioning that Recognition Approach is tested in various conditions and results are described. Keyword - Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVM DOI: 10.18495/comengapp.21.161174
{"title":"Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms","authors":"M. Aghaie, F. Shokri, M. Y. Tabari","doi":"10.18495/COMENGAPP.V2I1.17","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.17","url":null,"abstract":"There are far more cars on the road now than there used to be. Therefore, Controlling and managing the huge volume of traffic is virtually impossible without the use of computer technology. This paper represents design and implement of an intelligent system for license plate recognition based on three main steps. This process includes the detection of license plate location, character segmentation and character recognition. In this study, we used Classifier svm to detect the characters. According to the results, the performance of the proposed system is better compared to similar algorithms such as neural network. It is worth mentioning that Recognition Approach is tested in various conditions and results are described. Keyword - Vehicle license plate recognition, Morphology Operations, Histogram, The edge detection, Classifier SVM DOI: 10.18495/comengapp.21.161174","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126204582","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}
Pub Date : 2013-03-31DOI: 10.18495/COMENGAPP.V2I1.13
S. Nurmaini
The ongoing research and development work in the field of robotics have resulted in so many new technological trends. There are revolution which are being achieved with the use of latest technology in robotics, giving birth to new possibilities for automating tasks and enriching human lives for better. One can easily witness the presence of robotics in every sphere of life from industrial robots, service robots to personal robots. It other words, robots have become a part of our world to meet new demands of a new society. DOI: 10.18495/comengapp.21.117120
{"title":"Robotics Current Issues and Trends","authors":"S. Nurmaini","doi":"10.18495/COMENGAPP.V2I1.13","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.13","url":null,"abstract":"The ongoing research and development work in the field of robotics have resulted in so many new technological trends. There are revolution which are being achieved with the use of latest technology in robotics, giving birth to new possibilities for automating tasks and enriching human lives for better. One can easily witness the presence of robotics in every sphere of life from industrial robots, service robots to personal robots. It other words, robots have become a part of our world to meet new demands of a new society. DOI: 10.18495/comengapp.21.117120","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"17 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133110457","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}
Pub Date : 2013-03-31DOI: 10.18495/COMENGAPP.V2I1.15
P. Das
Detecting and correcting errors is one of the main tasks in coding theory. The bounds are important in terms of error-detecting and -correcting capabilities of the codes. Solid Burst error is common in several communication channels. This paper obtains lower and upper bounds on the number of parity-check digits required for linear codes capable of correcting any solid burst error of length b or less and simultaneously detecting any solid burst error of length s (> b ) or less. Illustration of such a code is also provided. Keywords: Parity check matrix, Syndromes, Solid burst errors, Standard array DOI: 10.18495/comengapp.21.143150
{"title":"Codes correcting and simultaneously detecting solid burst errors","authors":"P. Das","doi":"10.18495/COMENGAPP.V2I1.15","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.15","url":null,"abstract":"Detecting and correcting errors is one of the main tasks in coding theory. The bounds are important in terms of error-detecting and -correcting capabilities of the codes. Solid Burst error is common in several communication channels. This paper obtains lower and upper bounds on the number of parity-check digits required for linear codes capable of correcting any solid burst error of length b or less and simultaneously detecting any solid burst error of length s (> b ) or less. Illustration of such a code is also provided. Keywords: Parity check matrix, Syndromes, Solid burst errors, Standard array DOI: 10.18495/comengapp.21.143150","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128767609","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}
Pub Date : 2013-03-26DOI: 10.18495/COMENGAPP.V2I1.14
S. Rosa, S. Shamsuddin, Evizal Evizal
Detecting of anomalies patients data are important to gives early alert to hospital, in this paper will explore on anomalies patient data detecting and processing using artificial computer intelligent system. Artificial Immune System (AIS) is an intelligent computational technique refers to human immunology system and has been used in many areas such as computer system, pattern recognition, stock market trading, etc. In this case, real value negative selection algorithm (RNSA) of artificial immune system used for detecting anomalies patient body parameters such as temperature. Patient data from monitoring system or database classified into real valued, real negative selection algorithm results is real values deduction by RNSA distance, the algorithm used is minimum distance and the value of detector generated for the algorithm. The real valued compared with the distance of data, if the distance is less than a RNSA detector distance then data classified into abnormal. To develop real time detecting and monitoring system, Radio Frequency Identification (RFID) technology has been used in this system. Keywords: AIS, RNSA, RFID, Abnormal DOI: 10.18495/comengapp.21.121142
{"title":"An Immune Based Patient Anomaly Detection using RFID Technology","authors":"S. Rosa, S. Shamsuddin, Evizal Evizal","doi":"10.18495/COMENGAPP.V2I1.14","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.14","url":null,"abstract":"Detecting of anomalies patients data are important to gives early alert to hospital, in this paper will explore on anomalies patient data detecting and processing using artificial computer intelligent system. Artificial Immune System (AIS) is an intelligent computational technique refers to human immunology system and has been used in many areas such as computer system, pattern recognition, stock market trading, etc. In this case, real value negative selection algorithm (RNSA) of artificial immune system used for detecting anomalies patient body parameters such as temperature. Patient data from monitoring system or database classified into real valued, real negative selection algorithm results is real values deduction by RNSA distance, the algorithm used is minimum distance and the value of detector generated for the algorithm. The real valued compared with the distance of data, if the distance is less than a RNSA detector distance then data classified into abnormal. To develop real time detecting and monitoring system, Radio Frequency Identification (RFID) technology has been used in this system. Keywords: AIS, RNSA, RFID, Abnormal DOI: 10.18495/comengapp.21.121142","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131408751","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}
Pub Date : 2013-03-18DOI: 10.18495/COMENGAPP.V2I1.18
Samuel Choi Ping Man
Programming computers to play board games against human players has long been used as a measure for the development of artificial intelligence. The standard approach for computer game playing is to search for the best move from a given game state by using minimax search with static evaluation function. The static evaluation function is critical to the game playing performance but its design often relies on human expert players. This paper discusses how temporal differences (TD) learning can be used to construct a static evaluation function through self-playing and evaluates the effects for various parameter settings. The game of Kalah, a non-chance game of moderate complexity, is chosen as a testbed. The empirical result shows that TD learning is particularly promising for constructing a good evaluation function for the end games and can substantially improve the overall game playing performance in learning the entire game. DOI: 10.18495/comengapp.21.175184
{"title":"On Constructing Static Evaluation Function using Temporal Difference Learning","authors":"Samuel Choi Ping Man","doi":"10.18495/COMENGAPP.V2I1.18","DOIUrl":"https://doi.org/10.18495/COMENGAPP.V2I1.18","url":null,"abstract":"Programming computers to play board games against human players has long been used as a measure for the development of artificial intelligence. The standard approach for computer game playing is to search for the best move from a given game state by using minimax search with static evaluation function. The static evaluation function is critical to the game playing performance but its design often relies on human expert players. This paper discusses how temporal differences (TD) learning can be used to construct a static evaluation function through self-playing and evaluates the effects for various parameter settings. The game of Kalah, a non-chance game of moderate complexity, is chosen as a testbed. The empirical result shows that TD learning is particularly promising for constructing a good evaluation function for the end games and can substantially improve the overall game playing performance in learning the entire game. DOI: 10.18495/comengapp.21.175184","PeriodicalId":120500,"journal":{"name":"Computer Engineering and Applications","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124931387","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}
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