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2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)最新文献

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Indic SentiReview: Natural Language Processing based Sentiment Analysis on major Indian Languages 印度情感评论:基于自然语言处理的主要印度语言情感分析
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819786
Nidhi Hadiya, Nirali R. Nanavati
{"title":"Indic SentiReview: Natural Language Processing based Sentiment Analysis on major Indian Languages","authors":"Nidhi Hadiya, Nirali R. Nanavati","doi":"10.1109/ICCMC.2019.8819786","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819786","url":null,"abstract":"Sentiment Analysis(SA) can be a natural language processing(NLP) task that extracts opinions from the given text and classifies them as a negative or positive. Research works in SA is mostly conducted in English. Nowadays, the web indexes and other websites related to reviews also support non-English languages. It is therefore necessary to perform SA for these languages as well. There are numerous works found in the literature for SA in other languages worldwide. However, SA for Indian languages needs exploration. In this paper, we discuss various available lexicon resources and often used SA techniques in some Indian languages. Moreover, we present the theoretical parametric evaluation of our studied techniques and we also discuss challenges, which were identified during SA in Indian Languages.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124566174","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: 4
Fake Data Analysis and Detection Using Ensembled Hybrid Algorithm 基于集成混合算法的假数据分析与检测
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819741
Palagati Bhanu Prakash Reddy, M. K. Reddy, G. Reddy, K. Mehata
{"title":"Fake Data Analysis and Detection Using Ensembled Hybrid Algorithm","authors":"Palagati Bhanu Prakash Reddy, M. K. Reddy, G. Reddy, K. Mehata","doi":"10.1109/ICCMC.2019.8819741","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819741","url":null,"abstract":"Fake data detection is the most important problem to be addressed in the recent years, there is lot of research going on in this field. Because of its serious impacts on the readers. researchers, government and private agencies working together to solve the issue. This paper represents a hybrid approach for fake data detection using the multinomial voting algorithm. This algorithm was tested with multiple fake news dataset which resulted in an accuracy score of 94 percent which is a benchmark in the machine learning field where the other algorithms are at a range of 82 to 88 percent. The list of algorithms that have been used here is as follows Naive Bayes, Random Forest, Decision Tree, Support Vector Machine, K Nearest Neighbors. All these algorithms use training data as the bag of words model which was created using Count Vectorizer. Experimental data has collected from the Kaggle data world. Python is used as a language to verify and validate the results. Tableau is used as a visualization tool. Implementation is carried out using default algorithm values.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"58 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380212","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: 16
A Novel Optimized Classifier For the Loan Repayment Capability Prediction System 贷款偿还能力预测系统的一种新型优化分类器
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819772
Soni P M, V. Paul
{"title":"A Novel Optimized Classifier For the Loan Repayment Capability Prediction System","authors":"Soni P M, V. Paul","doi":"10.1109/ICCMC.2019.8819772","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819772","url":null,"abstract":"The most suitable predictive modelling technique to predict the loan repayment capability of a customer in a banking industry is classification. Classification is a supervised learning technique in data mining. The loan repayment capability of a customer can be predicted more accurately using random forest algorithm. The accuracy of the prediction depends on various parameters of the random forest algorithm. The main objective of this paper is to prove that optimization of parameters results in a better accuracy for the capability prediction of loan repayment by the customers. This paper illustrates the process of optimization that leads to an improved accuracy in classification. The comparative study explains that optimization can lead to a better accuracy and the experiments were done in weka and R.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131569099","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: 3
Expectation Maximization Segmentation Algorithm for Classification of Human Genome Image 人类基因组图像分类的期望最大化分割算法
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819686
D. Menaka, S. Vaidyanathan
{"title":"Expectation Maximization Segmentation Algorithm for Classification of Human Genome Image","authors":"D. Menaka, S. Vaidyanathan","doi":"10.1109/ICCMC.2019.8819686","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819686","url":null,"abstract":"Chromosomes are cellular structures which carry the genetic material. A chromosome is composed of a single circular or linear DNA molecule. The cell details of every individual is found in genome which contains the DNA genetic blueprint. The partitioning and categorization of chromosome has to be automated by standard algorithms for easy diagnosis of certain diseases. The structural and numerical anomalies in the genes that occur to the future generation can be predicted through the analysis of the various characteristics of the chromosomes. Karyotyping indicates the display of the chromosomes of a cell by arranging them in a specific and distinct fashion which will simplify the chromosome analysis. The multispectral staining techniques adopted in MFISH offers classification of human genome by assigning different colors to different chromosomes that ease the determination of structural and numerical aberrations. The important step in multispectral MFISH image karyotyping is segmentation of DAPI images. In this paper, Expectation maximization algorithm for M-FISH segmentation is presented. The Expectation Maximization segmentation algorithm reveals improved performance in segmentation when an analogy is made with watershed segmentation method for 30 sets of images taken from ADIR dataset of MFISH images. After segmentation, chromosomes ar classified using K means algorithm and an overall quality of 91.68% is reported.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114191496","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
Grading of quality in tomatoes using multi-class SVM 基于多类支持向量机的番茄品质分级
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819866
K. Meenakshi, K. Swaraja, U. Ch, Padmavathi Kora
{"title":"Grading of quality in tomatoes using multi-class SVM","authors":"K. Meenakshi, K. Swaraja, U. Ch, Padmavathi Kora","doi":"10.1109/ICCMC.2019.8819866","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819866","url":null,"abstract":"Tomato is one of the major crops cultivated across the globe. Despite the hype, the crop is also suffered from wide variety of diseases. Early detection of these disease will proportionally increase the crop yield and consequently improves the economic growth and food reserves of a nation. In particular the leaf part is more prone to diseases. Based on the leaves and by using mutli-class SVM we can even classify whether the plant is in healthy or unhealthy condition. An accuracy of 99.1 % is achieved on three classes of diseases-early and late blight and mosaic.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114791885","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: 4
Gas Leakage and Fire Detection using Raspberry Pi 气体泄漏和火灾检测使用树莓派
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819678
Sourabh Jamadagni, Priya R Sankpal, Shwetali Patil, N. Chougule, Shailesh S. Gurav
{"title":"Gas Leakage and Fire Detection using Raspberry Pi","authors":"Sourabh Jamadagni, Priya R Sankpal, Shwetali Patil, N. Chougule, Shailesh S. Gurav","doi":"10.1109/ICCMC.2019.8819678","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819678","url":null,"abstract":"This paper presents the growth in the industrial monitoring system’s design using Internet of Things (IoT). The sensor used for the development of this system is MQ-2 which detects the leakage of gas at any atmos pheric condition and fire sensor as a simple and compact device for protection against fire. In gas sensor system, Ras pberry pi plays an important role such that all the components are interfaced to it. This avails the observer to notice the changes from anywhere in the world. The requirement of a gas detection system is to monitor the surroundings continuously. When gas and smoke is detected then system will send short message service (SMS) to the user then user will take respective action.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115943438","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: 12
Design and Implementation of Inspection Model for knowledge Patterns Classification in Diabetic Retinal Images 糖尿病视网膜图像知识模式分类检测模型的设计与实现
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819647
Kajal Sanjay Kothare, Kalpana Malpe
{"title":"Design and Implementation of Inspection Model for knowledge Patterns Classification in Diabetic Retinal Images","authors":"Kajal Sanjay Kothare, Kalpana Malpe","doi":"10.1109/ICCMC.2019.8819647","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819647","url":null,"abstract":"Diabetes is one of the major health issues. In diabetes patient one serious problem experience is the Diabetic Retinopathy (DR) and visual deficiency and is vascular disease of retina. Hence prediction of DR from patient eye retina becomes very crucial at early stage to cure. We focuses on presenting an empirical method in this research to collect required data and then developing several models to predict the chance of diabetic retinopathy.Here we use diabetic eye retina image dataset as input for prediction and evaluation. There are many techniques and algorithms that help to diagnose DR in retinal fundus images. We utilized some data mining techniques such as Support vector machine (SVM), naïve bayes and Local binary pattern (LBP) to extract image features and analyze image dataset.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116669523","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
Review on LFSR for Low Power BIST 低功耗自适应技术LFSR研究进展
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819698
M. Mohan, Sunitha S Pillai
{"title":"Review on LFSR for Low Power BIST","authors":"M. Mohan, Sunitha S Pillai","doi":"10.1109/ICCMC.2019.8819698","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819698","url":null,"abstract":"While testing an integrated circuit, large chip size, and excess power dissipation are the major issues. As compared to its working mode, the testing mode power dissipation is very high. In addition to this, the inefficiency of ATE and its time-consuming nature makes the external testing much more difficult. LFSR is used for testing ASIC chips. The pseudo-random variable generated by the LFSR is used for the testing process. The pseudo-random variable testing has some advantages such that it uses simple hardware for the on-chip test generating process. BIST is one of the most efficient low power testing methods. LFSR is used in the BIST for the generation of test patterns. This paper compares the various architecture of the LFSR for BIST and its associated power dissipation","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116036580","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: 8
Novel Approaches to Identify and Prevent Cyber Attacks in Web 识别和预防网络攻击的新方法
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819822
S. Sodagudi, Sita Kumari Kotha, M. David Raju
{"title":"Novel Approaches to Identify and Prevent Cyber Attacks in Web","authors":"S. Sodagudi, Sita Kumari Kotha, M. David Raju","doi":"10.1109/ICCMC.2019.8819822","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819822","url":null,"abstract":"Security is the biggest challenging approach in today’s internet accessible technologies like, mobile phones, webmail, instant messaging services, and removable storage media. Internet access has given the ability to easily carry and handle the large amounts of data. With the growing technologies, the usage of internet increases along with the threats/data breaches like view or modify the confidential data by an unauthorized entities. Though the technology increases, there is no guarantee for the overall security. Every web application contains vulnerabilities and it is the most crucial area for the intruders to place cyber attacks on it. These attacks are very harmful for the society. They involve creating financial theft, data threats, blackmailing, resource upholding and many more. This paper provides the approaches to identify, detect and taking preventive measures for the eradication of attacks. For this available tools and scanners can also be used in the present world scenario. SQL injection, DNS attacks and DoS attacks are emphasized towards implementation since the risk encountered is more in such attacks.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115665049","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
Auto Adaptive Differential Evolution Algorithm 自适应差分进化算法
2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2019-03-01 DOI: 10.1109/ICCMC.2019.8819749
Vivek Sharma, Shalini Agarwal, Pawan Kumar Verma
{"title":"Auto Adaptive Differential Evolution Algorithm","authors":"Vivek Sharma, Shalini Agarwal, Pawan Kumar Verma","doi":"10.1109/ICCMC.2019.8819749","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819749","url":null,"abstract":"Differential Evolution algorithm has proved to be effective and best method for solving various optimization challenges. It has been proved to be rather cumbersome to manually set control parameters in DE. This paper sketch a new variant of the DE algorithm that provides an environment to auto-adjust the control parameters settings. For the past years, DE has captured the attention in many practical cases. It makes use of a few control parameters that are bound to the same value throughout the evolutionary process. Manual control parameters setting is a time-consuming process, so the proposed work provides a reliable, accurate and fast technique to optimize numerical function. This work is tested against various numerical set functions. Final results show that this proposed algorithm performs a cut above when compared with the classical Differential Evolution algorithm, and the other control parameter setting variant of DE considered in the literature.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121206279","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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