2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)最新文献

{"title":"Handling Structured Data Using Data Mining Clustering Techniques","authors":"Seema Maitrey, C. K. Jha","doi":"10.1109/ICICT46931.2019.8977647","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977647","url":null,"abstract":"In the new era, every organization has the capability to store the extremely large amount of data. The continuous rise in the capturing of data is turning it into a huge tomb of data. Such huge data is becoming difficult to get analysed. This constantly growing large data set is making the challenge to the researchers in discovering knowledge from it. Valuable information is buried under the huge collection of data which can be extracted by making the use of Data Mining technique, as it possess the ability to dig out the embedded precious information from the large datasets. Various application areas required this technique, thus, resulted into an evolution of many data mining methods. Though several data mining methods get evolved not all of them were capable to deal with high voluminous data. Numerous computation and data- intensive scientific data analyses are established to compete with the ongoing time. As today’s data has got converted to Big data, it now require large-scale data mining analyses to fulfil its scalability and performance requirements. To serve such data, several efficient parallel and concurrent algorithms got applied. The parallel algorithms used different parallelization techniques to manage the huge voluminous data and brought them into real action. Formerly, these techniques were : threads, MPI etc. which produce different performance and usability characteristics. The MPI model was efficient in computing rigorous problems but difficult to bring them into the practical use. Over coming years, Data mining is continuously spreading its root in business and in learning organizations. The new integrated clustering algorithm called CURE became more vigorous to outliers and recognizes those clusters that were having irregular shapes and are of variant size. CURE is formed with the combined features of random sampling and partitioning which assured that the quality of output clusters produced by it is much improved with respect to those clusters that are resulted from the prior algorithms. This paper put focus on CURE clustering technique which found suitable for working with large databases.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115763425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-Economic Analysis of 100 kW Rooftop Photovoltaic Grid - Type System Based on Actual Performance through Homer Software","authors":"Anam Khan, K. Rana","doi":"10.1109/ICICT46931.2019.8977701","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977701","url":null,"abstract":"As more consideration is being centered around the improvement of sustainable power source assets all-inclusive, specialized and economic evaluations of these assets are vital to learning their feasibility. These evaluations can be increasingly significant on the off chance that they depend on field and real execution of the renewable resources source conversion resources. The present investigation shows a technical as well as economical examination of a 100 kW rooftop pv lattice associated framework dependent on practical implementation through homer programming. Both the yearly vitality created and devoured by the system is resolved. The examination of a matrix associated PV framework incorporates; Total Net Present Cost, Levelized Cost of Energy (Rs/kWh), level of sustainable energy (solar) utilized in structure, decrease in bill cost with these presentation parameters. The general, specialized exhibition of the network tied PV framework can be assessed and, they can likewise be utilized to contrast the display of any structure and comparative establishments, independent of their area and introduced limit and correlation with real information. The rate contrast between the genuine and determined power yields is around 11.26 %. However, further research needs to be done by planning a PV based framework for any building structure utilizing homer programming.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124227539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ICICT 2019 Messages","authors":"","doi":"10.1109/icict46931.2019.8977702","DOIUrl":"https://doi.org/10.1109/icict46931.2019.8977702","url":null,"abstract":"","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116462835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Approach Web Services Based Long Tail Web Services Using Deep Neural Network","authors":"M. Meenakshi, Satpal","doi":"10.1109/ICICT46931.2019.8977655","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977655","url":null,"abstract":"As long-tail services are playing wider role in Web services, most of the developers are composing various web based services into mashups. Developers are increasing an interest for long-tail services, moreover, there are deep studies to address the recommendation problem using long-tail web services. The main Challenges for recommending long-tail services correctly includes unsatisfactory quality of description content and sparsity of historical data. Long term Web API Services are convenient, flexible and efficient way of interacting with customers, deliver businesses and sharing and exchange data over the web. They allow instant and complicated web services accessible to ubiquitous cell phone devices, such as tablets or smart phones. In the base paper, author proposed the DLSTR methodology using deep learning techniques, where author applied the feed forward neural network using Stack auto encoder denoising (SADE) to remove the data sparsity problem and achieved the 75% accuracy, which is unsatisfactory according to the traditional techniques. To overcome, this problem, we proposed the HDLSTTR technique, where we applied deep learning techniques with improved model of CNN (Convolutional Neural network) and GRU (Gated recurrent units) using the same dataset of Stack auto encoder denoising (SADE) to remove the data sparsity problem and achieved expected 95% accuracy with improved results. According to these improved results of long-term web services, the results are satisfactory and display the good results of keywords recommendation.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122301465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automation Of Use Case Transaction Methods In Terms Of Human Understanding","authors":"Mahima Sharma, R. Sharma","doi":"10.1109/ICICT46931.2019.8977653","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977653","url":null,"abstract":"In recent years the cost effecting became very useful feature in this era. The aim is to investigate the cost of transaction while finding the size of system. The industry lies between effective or general definitions for \"software productivity\" and \"software quality\" and uses a variety of differential definitions those are tough to predict before software is proposed or can say that live and tough to relate after that has been live or on production. The main aim of this study is: - (i) How to decide the weight of transaction. (ii) Calculating the total weight & cost. (iii) Implementation (iv) Abstract and Compare Differences will impact values of transaction identification cost effective method and other models those are available in market in the automated manner. This will tell the cost of the software how it is effecting the cost on the basis of other models those are already avail.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122847919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced key establishment technique for secure data access in cloud","authors":"Vidhisha Reddy, G. Prakash","doi":"10.1109/ICICT46931.2019.8977720","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977720","url":null,"abstract":"Today the IT environment concentrates on Cloud computing where the usage of cloud based applications poses various security threats. Many possible cloud applications fall victim to a tragedy of the generic approach such that a shared cloud service is becoming unstable and insecure based on the commercial demands by IT and other business organization. Companies should develop proper security guidelines for public and private cloud use and utilize an adequate cloud access model. Based on set of features in the three common cloud services, a set of security capabilities is identified which are needed to exercise those characteristic and the cryptographic dealing they entail. Random Number Generators can be used in cloud hosts especially for virtualized machines. Several purpose of Pseudo Random Number Generator (PRNG) exists in cloud which mainly can be used to authenticate users to the information stored on cloud, salts for the passwords or for statistical sampling. ANSI X9.31 is one standard pseudo random number generator used in many standard cryptographic algorithms like AES, RSA that are managed in securing data access in cloud applications. As ANSI X9.31 seed values are not secure they are directly used for generation. With brute force attack the seed values are exposed. On retrieval of seed values the key can be predicted which leads to insecurity of the information stored on the cloud. The proposed obfuscation technique protects from intruders. The proposed technique takes considerable minimum amount of time when compared with the existing method.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131728301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Fruit Recognition Approach for Refrigerator Inventory Management","authors":"Maithili Desai","doi":"10.1109/ICICT46931.2019.8977691","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977691","url":null,"abstract":"This study presents an image processing algorithm to identify four different classes and number of fruits. The proposed method recognizes fruits by extracting features (area, perimeter, color, eccentricity and shape) based upon the training dataset analysis. The aim is to manage refrigerator inventory by automating the process through image processing. This is done by first detecting which fruit it is and then keeping a count of it. The images have been pre-processed and used to extract features to be compared with our database. With this, an attempt has been made to avoid the hassle of last minute realization of shortage of food items. Furthermore, improvisation has been suggested based on the limitations of the proposed algorithm. It also talks about how it will be a useful aspect in the suggested application.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127967750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aphonic’s Voice: A Hand Gesture Based Approach to Convert Sign Language to Speech","authors":"Surendra Kumar Keshari, Shristi Tyagi, Niketa Tomar, Smiti Goel","doi":"10.1109/ICICT46931.2019.8977690","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977690","url":null,"abstract":"As everyone knows that language has always been a barrier in the path of communication for the people speaking different languages. A person going to some other country can learn a new language or carry a dictionary to communicate but, specially-abled people such as deaf or profoundly deaf person can only use sign language for communication. In a world where people barely understand this language it does not helps a lot in curbing the issue. So, the purpose of this proposed system is to develop a translation tool which can reduce the communication gap by converting the real-time gesture-based signs to text and finally to speech. This paper will first at discuss the design to recognize the hand gesture as it is one of the fastest way to communicate. And further the discussion will be about recognizing the digit and perform operations in addition to recognizing the English alphabets to form words. The paper reviewed the current study status of application aiming to recognize the hand gestures, symbols and movements to convert it into numbers and alphabets, and further into words and then sentences. According to the research the application will work as a medium in between an aphonic person and a normal person or vice versa. This paper shows the status of the application, customized hand gestures, the methods, analyzing the strength and week points and lists all the challenging problems in current research of hand gestures used for aphonic people school etc.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"33 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129150594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"To Detect Normal and Abnormal Neurological Disorder of MRI Image in Human using Convolutional Neural Netwok","authors":"Vaishali Tyagi, Anil.k. Ahlawat","doi":"10.1109/ICICT46931.2019.8977683","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977683","url":null,"abstract":"In todays world many numbers of people are affected with neurological disorder. Neurological disease is a brain abnormalities or brain dysfunction. It affects all age group of people. In past years, the detection of neurological disorder is a very difficult task but now, we are blessed with many medical technologies which are available such as MRI, CT scan and PET. Convolutional neural network is best classifier for image feature extraction without any image segment. In this paper, we detect neurological disorder for normal as well as abnormal brain using brain MRI dataset. To trace the MRI dataset, we select a convolutional neural network algorithm to classify the MRI data for normal and abnormal brain.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132057948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extractive Approach For Query Based Text Summarization","authors":"Gayathri Venu Madhuri Chandu, A. Premkumar, Sai Susmitha K, Nalini Sampath","doi":"10.1109/ICICT46931.2019.8977708","DOIUrl":"https://doi.org/10.1109/ICICT46931.2019.8977708","url":null,"abstract":"The last few years have seen a tremendous surge in the information that is being dumped online. In this digital world every organization have their respective website which gives a detailed knowledge about them to the public. Considering organizations like educational institutions, their official websites provide all the necessary information from admissions to research works carried out. Prospective students, parents, researchers and academicians refer the website to in order to get relevant answers to their query. In order to retrieve an answer for their query one to has to spend a lot of time searching through the website, reading through several subpages available and consolidating the relevant information. This paper presents a model to retrieve concise and irredundant answers to various questions / queries regarding an educational institution -Amrita School of Engineering. Our model uses various Natural Language Processing (NLP) based techniques for text summarization to give appropriate results. Hybrid similarity measure and clustering algorithm are used for retrieving relevant data and removing redundancy respectively. Our model was tested by many users and the results were accurate in 86% of the cases.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127515545","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}