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2016 1st India International Conference on Information Processing (IICIP)最新文献

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A novel approach for the identification of writing traits on email database 一种新的电子邮件数据库写作特征识别方法
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975382
Pranjal S. Bogawar, K. Bhoyar
{"title":"A novel approach for the identification of writing traits on email database","authors":"Pranjal S. Bogawar, K. Bhoyar","doi":"10.1109/IICIP.2016.7975382","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975382","url":null,"abstract":"Trait is a particular characteristic that can produce a particular type of behavior. The email which is written communication medium among the people is the source, to identif1y the writing traits of the person. This paper proposes a novel approach to identify the writing traits of person from their email communication. The proposed technique is combination of an unsupervised k-means clustering algorithm and rule based system to classify the traits of email writer. We classified the email writers into three categories as perfect writer, average writer and casual writer. The experiment was carried out on Enron's email data set. This experiment is helpful to predict the writing behavior of a person which will be helpful in identifying an email writer or improve his/her writing style.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115023303","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}
引用次数: 0
A software component selection technique based on fuzzy clustering 一种基于模糊聚类的软件构件选择技术
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975350
J. Kaur, P. Tomar
{"title":"A software component selection technique based on fuzzy clustering","authors":"J. Kaur, P. Tomar","doi":"10.1109/IICIP.2016.7975350","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975350","url":null,"abstract":"The software component selection in component-based software development remains a challenging area for those who try to retrieve the optimal components from the existing component repository. The clustering techniques offer a solution for component selection problems but with major shortcomings like a prior specification of number of clusters, specifying the radius of clusters, finding appropriate representation for the feature vectors, choosing the correct distance metric, overlapping clusters and use of subjective judgment of application developers. This paper present a software component selection technique based on fuzzy clustering using the concept of fuzzy relations. The main contribution of the algorithm is that the components which are similar based on multi attributes are kept together, helping the decision maker to choose the right component set. The algorithm is validated with a help of a small case study.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123001203","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}
引用次数: 1
Application of iterated Hilbert transform for deriving respiratory signal from single-lead ECG 迭代希尔伯特变换在单导联心电图呼吸信号提取中的应用
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975307
H. Sharma, K. K. Sharma
{"title":"Application of iterated Hilbert transform for deriving respiratory signal from single-lead ECG","authors":"H. Sharma, K. K. Sharma","doi":"10.1109/IICIP.2016.7975307","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975307","url":null,"abstract":"This paper presents a methodology to extract the respiration from a single-lead ECG waveform using the iterated Hilbert transform (IHT) technique. It is proposed that the amplitude components (envelopes) obtained in the initial iterations of the ECG decomposition using the IHT technique contain the information about the respiration, and these amplitude components can be utilized to estimate the respiration using band-pass filtering. Performance of the proposed methodology is compared with the two well established ECG-derived respiration (EDR) methods (R-peak amplitude and respiratory sinus arrhythmia (RSA) based EDR method) based on three parameters: correlation coefficients, mean absolute error, and average percentage error. The experiments were performed with forty subjects (20 young and 20 elderly) of Fantasia dataset. The experimental results show that the proposed EDR technique provides improved results as compared to the other two methods used in this paper for comparison.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"74 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993327","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}
引用次数: 1
Contrast enchantment of CBCT images using Bi-Histogram method with soft plus activation function for dentistry 基于软+激活函数的牙科CBCT图像双直方图对比增强
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975377
Anita Thakur, M. Malik, Nishtha Phutela, P. Khare, Prashant Mor
{"title":"Contrast enchantment of CBCT images using Bi-Histogram method with soft plus activation function for dentistry","authors":"Anita Thakur, M. Malik, Nishtha Phutela, P. Khare, Prashant Mor","doi":"10.1109/IICIP.2016.7975377","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975377","url":null,"abstract":"The Cone Beam Computed Tomography (CBCT) imaging technique is widely used to visualise dental, oral and maxillofacial region. CBCT imaging techniques are low radiation exposure on the patients. Due do this it produces low contrast images. Therefore, there is a need to enhance the low contrast CBCT image to highlight the important information that may aid diagnostic assessment, suitable treatment for dentistry. This paper focuses on improvement of contrast and brightness of dental CBCT images by using Bi Histogram Equalization technique with transform creation using activation function. The output image has been analysed and evaluated using Peak Signal-to-Noise ratio (PSNR) and Structure Similarity Index (SSIM). From the experimental results, it has been found that the soft plus activation function has a better enhancement capability.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125493375","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}
引用次数: 0
Dual segment video watermarking using energy efficient technique 采用节能技术的双段视频水印
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975393
J. Panda, I. Kumari, Nitish Goel, Savita Kumari
{"title":"Dual segment video watermarking using energy efficient technique","authors":"J. Panda, I. Kumari, Nitish Goel, Savita Kumari","doi":"10.1109/IICIP.2016.7975393","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975393","url":null,"abstract":"Digital watermarking is a technique to employ copyright protection and ensure the authenticity of the owner using a proof of ownership embedded in a multimedia file. The objective of this paper is to present a novel digital video watermarking scheme using dual watermark. The binary watermark image is distributed over audio samples in which first four samples of each frame are watermarked with 4 bits of the image using multiple bit plane scheme. For the gray scale watermark, the FFT is taken and the samples are embedded in the FFT samples of video frames using Energy Efficient scheme. The watermarked video is subjected to different attacks and the efficiency of the technique is measured using Correlation Factor and PSNR. The algorithm presented is robust, secure and is energy efficient with decreased payload on the host signal.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134311722","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}
引用次数: 2
Improving classification in data mining using hybrid algorithm 利用混合算法改进数据挖掘中的分类
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975380
A. Ahlawat, Bharti Suri
{"title":"Improving classification in data mining using hybrid algorithm","authors":"A. Ahlawat, Bharti Suri","doi":"10.1109/IICIP.2016.7975380","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975380","url":null,"abstract":"Data mining is a powerful concept with great potential to predict future trends and behavior. It refers to the extraction of hidden knowledge from large datasets using techniques like statistical analysis, machine learning, clustering, neural networks and genetic algorithms. Hybrid algorithms for data mining are a logical combination of multiple pre-existing techniques to enhance performance and provide better results[11]. The hybrid algorithm proposed in this paper uses the concept of clustering and decision tree induction to classify the data samples. When the proposed approach is tested on real life datasets, the results obtained show improved accuracy in most cases.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131735913","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}
引用次数: 11
An analysis of machine learning techniques (J48 & AdaBoost)-for classification 机器学习技术分析(J48 & AdaBoost)-用于分类
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975394
Poonam Pandey, R. Prabhakar
{"title":"An analysis of machine learning techniques (J48 & AdaBoost)-for classification","authors":"Poonam Pandey, R. Prabhakar","doi":"10.1109/IICIP.2016.7975394","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975394","url":null,"abstract":"Extraction of relevant Information from data Is a challenging task. Many times an analyst may end up with an erroneous classifier because of huge, redundant, unreliable and noisy data. It may also be due to misinterpretation of results and usage of inappropriate techniques for a specific situation. In our study, we have investigated the two main approaches in data mining which are Decision Tree (J48 algorithm) and Ensemble Learning Technique (AdaBoost). We have also performed a comparative analysis of these two techniques. The tool which we have used is WEKA which is an open source's software. The datasets which we have used are supermarket.arff, labor.arff, soybean.arff, & segment.arff. Here. arff is an abbreviation of Attribute Relation file Format which is the standard format that is accepted by WEKA for the datasets. The sample size of training set is number of attributes and number of instances available in the dataset. Classification models are assessed on the basis of number of class labels in the dataset, accuracy, amount and length of the generated rules, error rate and standard deviation. Based on number of experiments which we have performed, results show that AdaBoost provides better accuracy than Decision Tree (J48 algorithm) when the number of class labels in the dataset are exactly two whereas the Decision Tree generate rules faster than the Adaboost and when number of class labels in the dataset are more than two then J48 algorithm performs better than Adaboost. The results show the tradeoff of using the two approaches for other researchers in finding the best model for a particular problem.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133041340","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}
引用次数: 27
A skillbased pairing scheme for effective collaborations 以技能为基础的结对计划，促进有效的合作
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975304
Sushma Hans, S. Chakraverty
{"title":"A skillbased pairing scheme for effective collaborations","authors":"Sushma Hans, S. Chakraverty","doi":"10.1109/IICIP.2016.7975304","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975304","url":null,"abstract":"We propose an innovative approach of pairing learners in competitive and complementary way based on the learner's learning skills. Students are assessed to determine their inherentlearning skills and after their assessment; students are paired up for collaborative learning. We employ two methods: (i) the Stable Marriages Problem and (ii) the recursive Kernighan-Lin partitioning algorithm to generate optimal collaborative pairs. Results reveal that both pairing algorithms generate high quality collaborative pairs. Further, it takes lesser time to discover all possible pairs.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117276100","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}
引用次数: 0
An energy efficient GA based routing algorithm for two-tiered sensor networks 基于遗传算法的两层传感器网络高效路由算法
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975318
Payal Khurana Batra, K. Kant
{"title":"An energy efficient GA based routing algorithm for two-tiered sensor networks","authors":"Payal Khurana Batra, K. Kant","doi":"10.1109/IICIP.2016.7975318","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975318","url":null,"abstract":"Routing plays a major role in increasing the energy efficiency of a wireless sensor network. In a cluster based wireless sensor network, cluster head can forward the data to the base station either directly or indirectly (multi-hoping). However, in multi-hop routing energy saving is more as compared to direct transmission. Further, the selection of energy efficient routing schedules helps in increasing the network lifetime. In this paper, we propose an Energy Efficient Genetic Algorithm based Routing (EEGAR) approach, which selects the next forwarding node on the basis of energy consumption in communication and forwarding node's current energy. Simulation results show that the proposed routing approach made network more energy efficient that the existing approaches in terms of network lifetime, energy consumption, throughput and the number of hops.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116143103","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}
引用次数: 6
Neuro-fuzzy based approach to event driven software testing: A new opportunity 基于神经模糊的事件驱动软件测试方法:一个新的机会
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975349
S. Chaudhury, A. Singhal, O. Sangwan
{"title":"Neuro-fuzzy based approach to event driven software testing: A new opportunity","authors":"S. Chaudhury, A. Singhal, O. Sangwan","doi":"10.1109/IICIP.2016.7975349","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975349","url":null,"abstract":"Event Driven Software (EDS) testing is a very challenging task as a large number of events can be invoked by users. So far it is difficult to test all the user inputs invoked, therefore, test case prioritization is essentially required for giving more priority to test cases which reveal higher faults comparatively. We have proposed test case prioritization for EDS: as the Event Type, Interaction of Event, and Coverage of Event. Priority assigned in the proposed model uses these factors in Adaptive Neuro-Fuzzy Inference System (ANFIS) MATLAB Toolbox based on Neuro-Fuzzy logic model. Evaluation and validation will be done using Average Percentage of Fault Detection (APFD). APFD rate for prioritized sequence using the proposed Neuro-Fuzzy logic model exhibited 81% rate, whereas, non-prioritized test sequences showed70% suggesting, thereby, that after prioritization; rate of fault detection has improved considerably. Data shows that proposed Neuro-Fuzzy logic model is apt for Test Case Prioritization of EDS Testing.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116581727","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}
引用次数: 1
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