Pub Date : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508140
S. Shankar, Bishal Dey Sarkar, S. Sabitha, D. Mehrotra
The large volume of data in all fields across the globe has to be managed and is used by the decision makers to obtain something productive out of it. The big data of 14000×5 of Harvard University online course is analysed to find the performance metrics of registered students from different countries by means of K-mean clustering method. The performance of the student depends on number of factors and grades are not enough to represent the all-round knowledge of a student. The paper aims to analyse the performance of the students based on different attributes with respect to their country.
{"title":"Performance analysis of student learning metric using K-mean clustering approach K-mean cluster","authors":"S. Shankar, Bishal Dey Sarkar, S. Sabitha, D. Mehrotra","doi":"10.1109/CONFLUENCE.2016.7508140","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508140","url":null,"abstract":"The large volume of data in all fields across the globe has to be managed and is used by the decision makers to obtain something productive out of it. The big data of 14000×5 of Harvard University online course is analysed to find the performance metrics of registered students from different countries by means of K-mean clustering method. The performance of the student depends on number of factors and grades are not enough to represent the all-round knowledge of a student. The paper aims to analyse the performance of the students based on different attributes with respect to their country.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123611602","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508037
S. Rodzin, O. Rodzina
The article discusses the elements of the theory of population metaheuristics. Original and biogeographical memetic algorithms for solving transcomputational optimization problem are presented for the traveling salesman problem. Authors presented the method of biogeography and its modifications, as well as results of the comparative analysis of genetic, biogeographic and memetic algorithms. Experiments were carried out on certain benchmarks from the library TSPLIB. Efficiency, operating time and the diversity of the population were the criteria for comparison algorithms mentioned above.
{"title":"Metaheuristics memes and biogeography for transcomputational combinatorial optimization problems","authors":"S. Rodzin, O. Rodzina","doi":"10.1109/CONFLUENCE.2016.7508037","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508037","url":null,"abstract":"The article discusses the elements of the theory of population metaheuristics. Original and biogeographical memetic algorithms for solving transcomputational optimization problem are presented for the traveling salesman problem. Authors presented the method of biogeography and its modifications, as well as results of the comparative analysis of genetic, biogeographic and memetic algorithms. Experiments were carried out on certain benchmarks from the library TSPLIB. Efficiency, operating time and the diversity of the population were the criteria for comparison algorithms mentioned above.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127917889","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508146
Rashi Bansal, Nishant Gaur, S. Singh
Outlier Detection is one of the major issues in Data Mining; finding outliers from a collection of patterns is a popular problem in the field of data mining. An outlier is that pattern which is dissimilar with respect to all the remaining patterns in the data set. Outlier detection is quiet familiar area of research in mining of data set. It is a quiet important task in various application domains. Earlier outliers considered as noisy data, has now become severe difficulty which has been discovered in various domains of research. The discovery of outlier is useful in detection of unpredicted and unidentified data, in certain areas like fraud detection of credit cards, calling cards, discovering computer intrusion and criminal behaviors etc. A number of surveys, research and review articles cover outlier detection techniques in great details. Here in this review paper, my effort is to take as one several techniques of outlier detection. By this attempt, we wish to gain a improved perceptive of various research on outlier detection and analysis for our well-being as well as for those who are the beginners in this field, so that they can easily pickup the links in details.
{"title":"Outlier Detection: Applications and techniques in Data Mining","authors":"Rashi Bansal, Nishant Gaur, S. Singh","doi":"10.1109/CONFLUENCE.2016.7508146","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508146","url":null,"abstract":"Outlier Detection is one of the major issues in Data Mining; finding outliers from a collection of patterns is a popular problem in the field of data mining. An outlier is that pattern which is dissimilar with respect to all the remaining patterns in the data set. Outlier detection is quiet familiar area of research in mining of data set. It is a quiet important task in various application domains. Earlier outliers considered as noisy data, has now become severe difficulty which has been discovered in various domains of research. The discovery of outlier is useful in detection of unpredicted and unidentified data, in certain areas like fraud detection of credit cards, calling cards, discovering computer intrusion and criminal behaviors etc. A number of surveys, research and review articles cover outlier detection techniques in great details. Here in this review paper, my effort is to take as one several techniques of outlier detection. By this attempt, we wish to gain a improved perceptive of various research on outlier detection and analysis for our well-being as well as for those who are the beginners in this field, so that they can easily pickup the links in details.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114281840","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508168
Rajni, Kajal, Ankur Choudhary, A. Singhal
Harmony Search Algorithm is one of the best optimization algorithm known, due to its capability of escaping the local optima and divergence free behaviour. In this paper, an optimized audio watermarking technique based on harmony search algorithm is presented. The watermark is embedded using dither modulation of the host audio signal blocks. High imperceptibility is proved to be achieved by the proposed technique through subjective test. Moreover, the technique is quite robust against variety of attacks including resampling attack, low-pass filtering, requantization and cropping effect. To improve the robustness and imperceptibility, harmony search technique has been applied on user defined quantization parameter.
{"title":"Digital audio watermarking scheme using Harmony Search Algorithm","authors":"Rajni, Kajal, Ankur Choudhary, A. Singhal","doi":"10.1109/CONFLUENCE.2016.7508168","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508168","url":null,"abstract":"Harmony Search Algorithm is one of the best optimization algorithm known, due to its capability of escaping the local optima and divergence free behaviour. In this paper, an optimized audio watermarking technique based on harmony search algorithm is presented. The watermark is embedded using dither modulation of the host audio signal blocks. High imperceptibility is proved to be achieved by the proposed technique through subjective test. Moreover, the technique is quite robust against variety of attacks including resampling attack, low-pass filtering, requantization and cropping effect. To improve the robustness and imperceptibility, harmony search technique has been applied on user defined quantization parameter.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"38 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122509153","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 : 1900-01-01DOI: 10.1109/ofc.2008.4528175
The document that should appear here is not currently available.
这里应该出现的文档目前不可用。
{"title":"PDF Not Yet Available In IEEE Xplore","authors":"","doi":"10.1109/ofc.2008.4528175","DOIUrl":"https://doi.org/10.1109/ofc.2008.4528175","url":null,"abstract":"The document that should appear here is not currently available.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122866004","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508144
Rachana Sharma, Priyanka Sharma, P. Mishra, E. Pilli
The term Big Data is explosion of high frequency digital data encountering daily through various sources. Velocity, Volume, Variety, Veracity and Value is causing difficulty for processing, storing and analyzing the Data. Intrusion Detection System in Big Data environment is one of the research issue we addressed. Intrusion Detection is a security technique, used to monitor and analyze network traffic in order to detect network violation. We require a robust Intrusion Detection technique to classify between normal and anomalous data and predict security breaches. In this paper, we have analyzed Machine learning techniques to detect intrusion which can scale up to build such systems. There are many algorithms one can opt for depending upon the need of system. This paper deals with Naïve Bayes and K-Nearest Neighbor classifier in MapReduce framework and their performance comparison with WEKA implementations. Our preliminary analysis over NSL-KDD seems to be promising.
{"title":"Towards MapReduce based classification approaches for Intrusion Detection","authors":"Rachana Sharma, Priyanka Sharma, P. Mishra, E. Pilli","doi":"10.1109/CONFLUENCE.2016.7508144","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508144","url":null,"abstract":"The term Big Data is explosion of high frequency digital data encountering daily through various sources. Velocity, Volume, Variety, Veracity and Value is causing difficulty for processing, storing and analyzing the Data. Intrusion Detection System in Big Data environment is one of the research issue we addressed. Intrusion Detection is a security technique, used to monitor and analyze network traffic in order to detect network violation. We require a robust Intrusion Detection technique to classify between normal and anomalous data and predict security breaches. In this paper, we have analyzed Machine learning techniques to detect intrusion which can scale up to build such systems. There are many algorithms one can opt for depending upon the need of system. This paper deals with Naïve Bayes and K-Nearest Neighbor classifier in MapReduce framework and their performance comparison with WEKA implementations. Our preliminary analysis over NSL-KDD seems to be promising.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123825461","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508198
Ankur Choudhary, A. Baghel, O. Sangwan
Reliable softwares are the need of modern digital era. Failure nonlinearity makes software reliability a complicated task. Over past decades, many researchers have contributed many parametric / non parametric software reliability growth models and discussed their assumptions, applicability and predictability. It concluded that traditional parametric software reliability models have many shortcomings related to their unrealistic assumptions, environment-dependent applicability, and questionable predictability. In contrast to parametric software reliability growth models, the non-parametric software reliability growth models which use machine learning techniques or time series modeling have been proposed by researchers. This paper evaluates and compares the accuracy of 2 parametric and 2 non parametric software reliability growth models on 3 real-life data sets for software failures.
{"title":"Software reliability prediction modeling: A comparison of parametric and non-parametric modeling","authors":"Ankur Choudhary, A. Baghel, O. Sangwan","doi":"10.1109/CONFLUENCE.2016.7508198","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508198","url":null,"abstract":"Reliable softwares are the need of modern digital era. Failure nonlinearity makes software reliability a complicated task. Over past decades, many researchers have contributed many parametric / non parametric software reliability growth models and discussed their assumptions, applicability and predictability. It concluded that traditional parametric software reliability models have many shortcomings related to their unrealistic assumptions, environment-dependent applicability, and questionable predictability. In contrast to parametric software reliability growth models, the non-parametric software reliability growth models which use machine learning techniques or time series modeling have been proposed by researchers. This paper evaluates and compares the accuracy of 2 parametric and 2 non parametric software reliability growth models on 3 real-life data sets for software failures.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124063876","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508173
Anita Thakur, Adiba Kausar, Ariz Iqbal
Environment and circumstances are affected the visual quality of recorded images. As no devices are perfect so consequently imaging technology is recorded degrade image. Most of imaging system has a limited resolution and not crucial speed at which images can be recorded. So that, most of images are suffered by motion blur degradations and noise. Distortion in images are not same in whole image which depend on location of pixel in image that type of distortion are space variant type. This paper presenting comparative study of restoration method for space variant motion blurred images using Kalman and Wiener filter. The comparison of performance of method is verified using improvement in signal to noise ratio (ISNR).
{"title":"Comparison efficacy of restoration method for space variant motion blurred images using kalman & wiener filter","authors":"Anita Thakur, Adiba Kausar, Ariz Iqbal","doi":"10.1109/CONFLUENCE.2016.7508173","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508173","url":null,"abstract":"Environment and circumstances are affected the visual quality of recorded images. As no devices are perfect so consequently imaging technology is recorded degrade image. Most of imaging system has a limited resolution and not crucial speed at which images can be recorded. So that, most of images are suffered by motion blur degradations and noise. Distortion in images are not same in whole image which depend on location of pixel in image that type of distortion are space variant type. This paper presenting comparative study of restoration method for space variant motion blurred images using Kalman and Wiener filter. The comparison of performance of method is verified using improvement in signal to noise ratio (ISNR).","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117155380","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508218
A. Popli, Divya Upadhyay
Alzheimer is a kind of a disease that causes problems in thinking, behavior and memory. It is the most common form of Dementia (general term commonly used for the memory loss). This is a very dangerous disease as a victim does not realize that what action can cause harm to him or others too. He even tends to forget his friends, family and close relations. The victim also suffers from the problems like hallucinations, wandering, aggressiveness, eating as well as sleeping disorders. These kind of people are very difficult to handle and the major challenges faced while handling them is to cope up with their behavior and the personality changes that occur time to time. So, as a caregiver one cannot change the patient's behavior and their personality instead try to employ the strategies to change or accommodate with their issues. The main problem comes when the Alzheimer patient leaves home without a caregiver. Various methods have been adopted to prevent the patient from wandering. In this paper an comparative analysis is performed on the available software techniques for their protection. Most of the techniques are not cost efficient and difficult to install.
{"title":"Comparative analysis of the software techniques available for protecting Alzheimer patient","authors":"A. Popli, Divya Upadhyay","doi":"10.1109/CONFLUENCE.2016.7508218","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508218","url":null,"abstract":"Alzheimer is a kind of a disease that causes problems in thinking, behavior and memory. It is the most common form of Dementia (general term commonly used for the memory loss). This is a very dangerous disease as a victim does not realize that what action can cause harm to him or others too. He even tends to forget his friends, family and close relations. The victim also suffers from the problems like hallucinations, wandering, aggressiveness, eating as well as sleeping disorders. These kind of people are very difficult to handle and the major challenges faced while handling them is to cope up with their behavior and the personality changes that occur time to time. So, as a caregiver one cannot change the patient's behavior and their personality instead try to employ the strategies to change or accommodate with their issues. The main problem comes when the Alzheimer patient leaves home without a caregiver. Various methods have been adopted to prevent the patient from wandering. In this paper an comparative analysis is performed on the available software techniques for their protection. Most of the techniques are not cost efficient and difficult to install.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117282047","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 : 1900-01-01DOI: 10.1109/CONFLUENCE.2016.7508109
Ravi Khurana, R. K. Bawa
Cloud computing is an emerging trend of 21st century. From last few decades, IT industry and academic researchers are shifting to this paradigm very rapidly. Another side of this issue is they are confused while taking the decision of selecting the provider of cloud services. There are number of Cloud Service Providers (CSPs) in the market, who are providing different cloud services viz Software-as-a-Software, Platform-as-a-Service and Infrastructure-as-a-Service. CSPs are delivering their services to the user based on SLA (Service Level Agreement) document. In this document all the negotiations have been clearly defined, what quality of service will provider give and what the consumer will have to pay have been objectively defined. But unfortunately SLA is not properly followed; quality of service is not up to the mark, breaches in the services are there. In many occasions, availability of service is not there, reliability is compromised, response time is more than what is expected, throughput is not up to the mark and cost factor is fluctuating. In this paper, we will discuss quality of service issues while selecting any cloud services. Researchers and business agents will surely get benefits from the present study.
{"title":"QoS based Cloud Service Selection paradigms","authors":"Ravi Khurana, R. K. Bawa","doi":"10.1109/CONFLUENCE.2016.7508109","DOIUrl":"https://doi.org/10.1109/CONFLUENCE.2016.7508109","url":null,"abstract":"Cloud computing is an emerging trend of 21st century. From last few decades, IT industry and academic researchers are shifting to this paradigm very rapidly. Another side of this issue is they are confused while taking the decision of selecting the provider of cloud services. There are number of Cloud Service Providers (CSPs) in the market, who are providing different cloud services viz Software-as-a-Software, Platform-as-a-Service and Infrastructure-as-a-Service. CSPs are delivering their services to the user based on SLA (Service Level Agreement) document. In this document all the negotiations have been clearly defined, what quality of service will provider give and what the consumer will have to pay have been objectively defined. But unfortunately SLA is not properly followed; quality of service is not up to the mark, breaches in the services are there. In many occasions, availability of service is not there, reliability is compromised, response time is more than what is expected, throughput is not up to the mark and cost factor is fluctuating. In this paper, we will discuss quality of service issues while selecting any cloud services. Researchers and business agents will surely get benefits from the present study.","PeriodicalId":299044,"journal":{"name":"2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115173961","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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