C. Renuka, N. Swapna, P. V. Bhavana, L. Prabha, Ajish K. Abraham
{"title":"Touch Screen: An interactive platform to learn arithmetic concepts for hearing impaired children attending preschool: Case Study","authors":"C. Renuka, N. Swapna, P. V. Bhavana, L. Prabha, Ajish K. Abraham","doi":"10.1109/ICAIT47043.2019.8987275","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987275","url":null,"abstract":"Technology is playing an important role in the field of education. The present study made an effort, to develop a mobile application and to explore the usefulness of technology in learning arithmetic skills on children with hearing impairment. Study included 10 participants in ages ranging from 2-6years, who were divided into 5 groups. Each group included 2 participants, one as experimental and another as control. The study was conducted across the groups using mobile application tool. Level 1 of the application tool included basic arithmetic concepts. It was designed, developed and validated before applying it on the children for field testing. The study revealed the positive impact of learning arithmetic concepts using touch screen mobile on children with bilateral severe hearing impairment. The activities attempted over a period of time kept on increasing, which was depicted by the scores obtained. Customer satisfaction was high and the caregivers of these children were happy to try this innovative technological intervention using touch screen mobile application.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128292544","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":"Smart Mirror Using Raspberry Pi for Human Monitoring and Intrusion Detection","authors":"Raju A. Nadaf, R. M, Sujata P, Vasudha M. Bonal","doi":"10.1109/ICAIT47043.2019.8987294","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987294","url":null,"abstract":"The demand for latest technology is rising and there by changing the way the world lives. The impact of technology is so heavy on our lives that, we are surrounded by technology filled equipments. Ranging from smart home to smart cities, everything is turning to smart. The ease of life and comfort zone also increasing with the advancement of technology. Hence, the proposed model, The Smart Mirror is a system in which the normal mirror will behave like a smart device. The Smart mirror is designed using Raspberry Pi-3 model and a touch enabled screen. The designed system is having two modes of operation namely regular mode and the triggered mode. In regular mode, it will act like a normal mirror and in triggered mode, the mirror will act like a smart mirror, which will capable of accepting commands and displays the results on the screen. There are three ways in which commands can be issued to the Smart mirror namely Voice, Touch and Mobile controlled commands. The system displays weather, temperature and latest news on the mirror. The system is primarily designed for the purpose of Human Monitoring and also Intrusion Detection. The proposed design is an interactive system and is made as a package bundled with maximum possible features, which not only just displays information over screen, but also can be used for providing security. The system is built using hardware units like Raspberry Pi-3 model, microphone, touch screen, mobile device, camera and PIR (Passive Infrared Sensor) sensors and programming coded in Python language. The Human Intrusion detection and Human Monitoring is implemented using Yolo Machine learning technique with OpenCV.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127218861","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}
N. Taranath, C. K. Subbaraya, L. M. Darshan, C. Gopalakrishna, Sourabh Saklecha, A. Varun, S. Sandesh
{"title":"Image Compression and Decompression using Fence Decimation","authors":"N. Taranath, C. K. Subbaraya, L. M. Darshan, C. Gopalakrishna, Sourabh Saklecha, A. Varun, S. Sandesh","doi":"10.1109/ICAIT47043.2019.8987423","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987423","url":null,"abstract":"Image Compression is a method of reducing the amount of data that we require to represent the image. Image Compression has been the most useful and very successful technologies in the field of digital image processing. Researchers have been using oversampling of images till recently. In the implementedsystem, architecture is implementedthat compresses the images using decimation of pixels. The image is prefiltered using a low-pass prefiltering process before pixel decimation to get redefined edges. In the resulting decimated image blocking artifacts are reduced, hence we can get an image that can be compressed and transmitted without any significant change to current image coding standards and systems.For the decompression procedure, the low resolution image is first decompressed then it is upscaled to its original resolution using image upscaling method and then applying edge enhancement operation. The implemented approach of pixel decimation outperforms JPEG in PSNR measure and achieves superior visual quality.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130341069","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}
S. J. F. G. Sathiaraj, Grishma S. Pingale, Souvik Majumdar, Saniya Shaikh, B. Thakare
{"title":"Secure Transfer of Image-Acquired Text Using a Combination of Cryptography and Steganography","authors":"S. J. F. G. Sathiaraj, Grishma S. Pingale, Souvik Majumdar, Saniya Shaikh, B. Thakare","doi":"10.1109/ICAIT47043.2019.8987361","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987361","url":null,"abstract":"Information security is a matter of growing concern. The threats to data being transmitted over networks is increasing day by day. The data being transmitted is thus vulnerable to different types of attacks. Cryptography is a technique used to protect the data by converting it into an unintelligible form of text known as cipher text. On the other hand, steganography based algorithms have proved to be an efficient way of hiding the existence of essential data during transfer. The proposed method uses a combination of cryptography and steganography for encryption thereby increasing the level of security provided. The text is recognized from images and documents using a deep learning model and further encrypted using an improved encryption method and then hidden into an image using image steganography.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"233 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113983489","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":"Analysis of Human Intelligence in Identifying Persons Native through the Features of Facial Image","authors":"Vani A. Hiremani, Kishore Kumar Senapati","doi":"10.1109/ICAIT47043.2019.8987298","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987298","url":null,"abstract":"Image object classification and detection are two important basic problems in the study of computer vision. Image classification is always a challenging task for computer scientist. Classification is a well-known supervised learning technique. This is always used to extract meaningful and vital information from a large dataset. It can also be effectively used for predicting unknown classes. At present image classification accuracy is not high enough because of large number of redundant information as well as features. Primary focus should be on how human intelligence works on image classification rather than training the machine for the image classification. In this research paper a theoretical and numerical analysis of human intelligence is outlined as how human intelligence works on an image through which features and in what way other they are deciding the category of image they have perceived.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"65 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114101851","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":"Evolutionary Approach based Scheduler for Speculative Task Execution","authors":"D. Vinutha, G. Raju","doi":"10.1109/ICAIT47043.2019.8987236","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987236","url":null,"abstract":"Hadoop is an open source framework to implement MapReduce. It stores and processes the data in distributed, highly scalable, parallel and fault tolerant environment. Job scheduling shows a significant role in optimizing the functioning of Hadoop. Hadoop default scheduler is not suitable for heterogeneous environment and not robust to identify the stragglers task which prolongs total execution time. Evolutionary approach based scheduler for speculative task execution is proposed in this paper. In this work we are proposing a new method to select the best nodes to run the speculative copy of the slow task. Two parameters such as network information and resource utilization are used to select the optimal nodes to execute the speculative copy of the stragglers task. Experiments have been conducted on web log file of academic website for obtaining the click count. Experimental results show that the execution time is reduced by 31% for 1 GB input data and 23% for 2 GB input data. On an average, the execution time is improved by 21% compared to conventional scheduler.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116025138","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}
S. K. Shashidhara, K. Sharath, M. Kavyashree, Basavaraj Basavaraj, Ibrahim B Aarif
{"title":"Intelligent Energy Meter for Smartcity","authors":"S. K. Shashidhara, K. Sharath, M. Kavyashree, Basavaraj Basavaraj, Ibrahim B Aarif","doi":"10.1109/ICAIT47043.2019.8987310","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987310","url":null,"abstract":"Efficient energy utilization is an important subject in the world that is filled with most of the non-renewable resources. In this paper, we are presenting Intelligent Energy meter, which is a smart Electricity measuring device that is connected to the internet via Wi-Fi that helps the direct communication with the Electricity consumers and the Electricity suppliers in terms of the number of units consumed, billing and control of the electricity flow. This electricity meter makes use of the BlynkIoT platform which provides free cloud and connectivity for the IoT devices. The proposed project is aimed at eliminating the human effort for the collection of the electricity bill from every consumer by automating the billing system through the Internet and online payment methods. This device is different from the existing systems not only in terms of the consumer authentication provided in the payment gateway and also in utilizing the industry grade online payment technology -paytm for the secured online payment.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114283174","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}
M. A. N., Swaroop L R, S. Hegde, Sourabh U, Rakshith Gowda G S
{"title":"Gender Identification for Kannada Names","authors":"M. A. N., Swaroop L R, S. Hegde, Sourabh U, Rakshith Gowda G S","doi":"10.1109/ICAIT47043.2019.8987346","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987346","url":null,"abstract":"Gender identification using the name of a person, specifically for Kannada names, is a challenging task. We present a classification approach for gender prediction of Kannada names represented in Kannada Unicode. We have determined various features derived from extensive morphological analysis of the names in Kannada. Some of the features identified are indigenous to Kannada Language. In this work we have developed three different classification models using Support Vector Machine (SVM), Random Forest and Naive Bayes machine learning algorithms. Our system reports a top accuracy of 90.1%, F1 score of 90.1% for male names and 90.0% for female names.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117236403","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}
B. Sujathakumari, M. Abhishek, D. S, A. N, Rakesh D S, B. S. Mahanand
{"title":"Detection of MCI from MRI using Gradient Boosting Classifier","authors":"B. Sujathakumari, M. Abhishek, D. S, A. N, Rakesh D S, B. S. Mahanand","doi":"10.1109/ICAIT47043.2019.8987413","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987413","url":null,"abstract":"This work presents a non-invasive approach for detection of Mild Cognitive Impairment (MCI) using Magnetic Resonance Imaging (MRI). The gray matter features of MRI along with the personal characteristics data are used as features for the Gradient Boosting classifier. The MRI and personal characteristics data of Cognitively Normal (CN) and MCI subjects are obtained from Alzheimer's Diseases Neuroimaging Initiative database. First, the MRI scans are subjected to segmentation from which the gray matter images are obtained. Then the resulting images are pre-processed using 2D Dual-Tree Complex Wavelet Transforms. The wavelets obtained are then combined with the personal characteristics data and is fed to the Gradient Boosting classifier. An accuracy of 97.25% is obtained for classifying CN and MCI subjects and the results are compared with other traditional machine learning approaches such as Logistic Regression, Naive Bayes, Support Vector Machine and Random Forest.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134496025","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":"Building a Data Mining Based Software Reliability Estimation Model","authors":"A. Visagan, M. Sumathi, G. Sujatha","doi":"10.1109/ICAIT47043.2019.8987354","DOIUrl":"https://doi.org/10.1109/ICAIT47043.2019.8987354","url":null,"abstract":"Development of quality software is the ultimate goal of any software development organization. But one of the most challenging aspects of quality is that it can typically be measured only post-delivery. There have been many attempts to estimate software quality during development. Such estimates are definitely likely to aid in the engineering of quality software by providing useful insights to the project manager who can make informed decisions on resource allocation. The present research is an attempt to apply data mining technique of classification to aid in such reliability estimation. While quality has many facets, the research focuses on reliability. Most organizations are typically equipped with data pertaining to their past software releases and this data can be put to use in building models that can aid in predicting the reliability of software under development. The research uses data metrics data collected from SonarCloud to build a model that can aid in predicting the reliability of software. The model is built using the popular data mining tool weka.","PeriodicalId":221994,"journal":{"name":"2019 1st International Conference on Advances in Information Technology (ICAIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131317998","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}