National Conference
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Item HEALTH MONITORING USING WEARABLE DEVICE(Karpagam Academy of Higher Education, 2020-02) Selvanayaki M; Sheeba LThe Internet of Things (IoT) has the potential to transform health care by profoundly altering how hospitals, clinics and other care facilities gather and use data by bringing together the major technical and business trends of mobility, automation and data analytics to improve patient care delivery. IOT helps in connecting the people by empowering their health and wealth in a smart way through wearable gadgets. The main aim of this work is to provide an extensive research in capturing the sensor data's, analyzing the data and providing a feedback to patients based on different health parameters. This paper focuses on making the system affordable and user friendly for the mass people. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available.Item PREDICTING ENERGY CONSUMPTION USING LINEAR REGRESSION(Michael Job College of Arts and Science for Women, Coimbatore, 2020-02) Selvanayaki M; Sheeba LElectricity plays a very important role among energy sources. Electricity consumption is important for every national authority when making energy policy. An energy policy has a great impact on industrial development in a country. This paper predicting energy consumption to analyze the consumption of the electrical energy among the various industries.The machine learning technique namely pycharm is used to predict the electrical energy consumption by using the linear regression model. This paper presents a machine learning approach for predicting electrical energy consumption whether the electrical energy is increase or not. The electrical energy consumed by various industries during the year 2008 to 2018 was used for analysis. Using liner regressionmodelithaspredictedthatthe energy consumption will increase by 11 % in the year 2019 and 1% in the year 2020.Item MEDICARE EMERGENCY ALERT SYSTEM USING GEO – FENCE SENSOR(Sri Krishna Arts and Science College, Coimbatore, 2020-02) Selvanayaki MNowadays the usage of internet and online automation process is growing up like buying products in online from amazon or flip cart. This IOT sensor is implementation as a life science project that helps to find the nearby medical shop of user‘s emergency medicine using geo-fence senor. This application will helps to the location of the medical shops which was held the current location of the user. The user‘s location will be updated frequently once they are in travel or in the same situation. A Geo-fence is a virtual perimeter for a real-world geographic area. A geo-fence could be dynamically generated-as in a radius around a point location, or a geo-fence can be a predefined set of boundaries. The use of a geo-fence is called geo-fencing and one example of usage involves a location aware device of a location- based-service (LBS) user entering or exiting a geo-fence. This activity could trigger an alert to the device user as were as messaging to the geo-fence operator. The medical shop owner or user need to update their medicines, quantity and dosage along with their shop location. The registered user will need approve permission for location.Item CARDIO VASCULAR DISEASE PREDICITON ANALYSIS(Dr. NGP Arts and Science College, 2020-02) Selvanayaki MIn this paper, the user could predict the diseases of cardiovascular. It is the process in which the different types of retinal images are downloaded from the databases. The retina can be photographed relatively straight forwardly with a fundus camera and now with direct digital imaging there is much interest in computer analysis of retinal images for identifying and quantifying the effects of diseases. A retinal image provides a snapshot of what is happening inside the human body. In particular, the state of the retinal vessels has been shown to reflect the cardiovascular condition of the body. In this paper, the implementation of automate segmentation approach is carried out based on active contour method to provide regional information. It is developed in the web mode to access dynamically by using HTML as front-end tool, server side as Python script and client side as JavaScript. The retinal based disease prediction includes Retinal image acquisition, Pre-processing, Vessel Segmentation, Vessel classification, Disease diagnosis.Item CLOUD COMPUTING(PSGR Krishnammal College for Women, 2018-02) Selvanayaki MThe evolution of cloud computing over the past few years is potentially one of the major advantages in the History of computing. However, if cloud computing is to achieve its potential, there is an equally urgent need for understanding the business related issues surrounding cloud computing in this article we identify the strengths, weakness, opportunities and thread for the cloud computing industry. We then identify the various issues that will affect the different stakeholders of cloud computing. We also issue a set of recommendation for the Practitioners who will provide and manage this technology.Item STUDY ON TOOLS AND TECHNIQUES TO MANAGE THE TEXTILE QUALITY CONTROL(PSGR Krishnammal College for Women, 2017-02) Selvanayaki MIn recent years, the rapid development in IT applications like MIS, ERP, Network, Multimedia and Data Mining etc. are indispensable tools to boost productivity and drive maximum benefits that has ushered in a revolution in manufacturing and interactive marketing across the globe.The aim of this study is to elaborate how the textile industry can manage to improve their production capacity and resources to increase customer demands regarding individualized products with good quality using data mining tools and techniques. Data mining analysis offers many potential to improve the Quality control in manufacturing process and to enhance the usefulness of existing data.Item CLOUD COMPUTING FOR SMALL SIZED INDUSTRIES(Sri Ramakrishna Mission Vidyalaya College of Arts & science, 2015-09) Selvanayaki M; Anushya Devi T SCloud computing in Indian scenario has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is become attractive to small sized industries as it reduces the capital investment in IT over the year and to easily switch over the current technology. Also it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. This paper deals with the advantages and limitations of cloud computing for small sized industries and discuss the suitable model of cloud computing. The aim of this paper is to provide a better understanding of challenges of cloud computing and identify important research directions in this increasingly important areaItem PREDICTION OF COTTON QUALITY USING WEKA TOOL(PSGR Krishnammal College for Women, Coimbatore, 2014-02) Selvanayaki M; Anushya Devi TSCotton is a soft, staple fiber that grows in a form known as a boll around the seeds of the cotton plant, a shrub native to tropical and subtropical regions around the world, including the Americas, India and Africa. The fiber most often is spun into yarn or thread and used to make a soft, breathable textile, which is the most widely, used natural-fiber cloth in clothing today. Its widespread use is largely due to the ease with which its fibers are spun into yarns. Cotton's strength, absorbency, and capacity to be washed and dyed also make it adaptable to a considerable variety of textile products. Cotton It’s fashionable, natural and versatile. The physical characteristics such as fiber length, length distribution, trash value, color grade, strength, shape, tenacity, density, moisture absorption, dimensional stability, resistance, thermal reaction, count, etc., contributes to the quality of cotton. In this work, cotton quality prediction is modeled as classification task and implemented using supervised learning algorithms namely REP tree, Classificationviaclustering, Classificationviaregression and MulticlassClassifier in WEKA environment on the cotton quality assessment dataset. The classification models have been trained using the data collected from a spinning mill. The prediction accuracy of the classifiers is evaluated using 10-fold cross validation and the results are compared. It is observed that the model based on REP tree classifier produces high predictive accuracy compared to other models.Item GRID COMPUTING(Dr. SNS Rajalakshmi college of Arts & Science, Coimbatore, 2014-02) Selvanayaki M; JyothiSahiToday we are in the Internet world and everyone prefers to enjoy fast access to the Internet. But due to multiple downloading, there is a chance that the system hangs up or slows down the performance that leads to the restarting of the entire process from the beginning. This is one of the serious problems that need the attention of the researchers.So we have taken this problem for our research and in this paper we are providing a layout for implementing our proposed Grid Model that can access the Internet very fast. By using our Grid we can easily download any number of files very fast depending on the number of systems employed in the Grid. We have used the concept of Grid Computing for this purpose.Item STUDY ON TOOLS AND TECHNIQUES TO MANAGE THE TEXTILE QUALITY CONTROL(PSGR Krishnammal College for Women, 2017-04-02) Selvanayaki M; Anushya Devi T SIn recent years, the rapid development in IT applications like MIS, ERP, Network, Multimedia and Data Mining etc. are indispensable tools to boost productivity and drive maximum benefits that has ushered in a revolution in manufacturing and interactive marketing across the globe.The aim of this study is to elaborate how the textile industry can manage to improve their production capacity and resources to increase customer demands regarding individualized products with good quality using data mining tools and techniques. Data mining analysis offers many potential to improve the Quality control in manufacturing process and to enhance the usefulness of existing data.