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Prediction of Students Performance using Machine learning

IOP Conference Series: Materials Science and Engineering 2021年第1期1055卷

作者： J. Dhilipan N. Vijayalakshmi S. Suriya Arockiya Christopher Professor & Head Department of Computer Applications SRM IST Ramapuram Campus Assistant Professor Department of Computer Applications SRM IST Ramapuram Campus Student Department of Computer Applications SRM IST Ramapuram Campus

An enormous measure of computerized information is being produced over a wide assortment in the field of data mining strategies. The creation of student achievement prediction models to predict student performance in academic institutions is a key area of the development of Education Data Mining. A prediction system has been proposed by using their 10th, 12th and previous semester marks. The study is evaluated using Binomial logical regression, Decision tree, and Entropy and KNN classifier. In order to attain their higher score, this framework would assist the student to recognize their final grade and improve their academic conduct.

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A Novel IoT Based Power Monitoring System

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IOP Conference Series: Materials Science and Engineering 2021年第1期1055卷

作者： S. Suriya R Agusthiyar N.V Vijayalakshmi J. Shyamala Devi Assistant Professor Department of Computer Applications SRM IST Ramapuram Campus HoD Department of Computer Applications SRM IST Ramapuram Campus

The use of IoT is increasing day by day; the significance and utilization is on the increase with more sophistication. In real world situation the electricity board calculates the bill amount and passed to the user mail or EB card. Now an efficient power monitoring system is proposed which uses a sensor at the heap to ascertain current, a circuit is utilized to figure voltage and with these two, power can be computed. Control qualities are put away in cloud database. Noninvasive current transformer sensor which receives the input from the live power supply and transfer the value to Voltage sensor, Nodemcu gets the value from voltage sensor and stores it in cloud database. With the help of cloud database user can monitor the power consumption value. Home automation can be achieved with the help of Relay Module and separate Nodemcu. Devices can be controlled from cloud dashboard. EB bill is a big challenging expenditure on day to day life. To overcome this situation Power Monitoring System will be very useful for the Average Salary people and also it overcomes the Electricity theft, unwanted Power wastage, avoidance of high power consumption devices.

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Marketing decision making using sentiment score with co-extracting opinion target words from reviews

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IOP Conference Series: Materials Science and Engineering 2021年第1期1055卷

作者： T M Saravanan T Kavitha S Hemalatha Gourav Kumar Associate Professor Department of Computer Applications Assistant Professor (Sr.G) Department of Computer Applications PG Scholar Department of Computer Applications Kongu Engineering College Perundurai – 638 060 Tamil Nadu India

This paper proposes a broad-spectrum outline that utilizes natural language processing approaches counting sentiment analysis, web mining that uses clustering schemes to acquire fresh outcome elicited from reviews in support of diverse features of products. An ultimate part in the scheme is finding positive and negative sentiment scope for all features of a product in the given reviews. Massive figures of product reviews are crawling on the Web with the rapid development of Internet. Commencing these reviews, customers can get hold ofactualexamination of product rank and unswerving supervision of their acquisition actions. Withdrawal feelings from web reviews have developed into a gradually more fiery activity and haveengrossed a vastpact of considerationcommencingthe researchers. The key task for opinion mining is obtaining opinion emotions from reviews in online, the novelfactor involves in identifying relations between words. The project proposes a new scheme that contains graph based co-ranking scheme that is employed in finding poise of every word. Then, words with superiorpoise are withdrawn as opinion objects. Based on the nearest neighbor rule we compare with previous schemes, the scheme more preciselycaptures opinion relations, particularly for elongated cover relations. The investigationaloutcome shows that the schemesuccessfully outperforms all other methods and techniques.

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Multi stratagem analysis of sentiments on twitter data using partial phrase harmonizing

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IOP Conference Series: Materials Science and Engineering 2021年第1期1055卷

作者： T M Saravanan T Kavitha S Hemalatha Ankit Kumar Associate Professor Department of Computer Applications Assistant Professor (Sr.G) Department of Computer Applications PG Scholar Department of Computer Applications Kongu Engineering College Perundurai – 638 060 Tamil Nadu India

Sentiment analysis is constructive in the application environment for business intelligence and suggests systems because it is a very easy medium for the two ends of the availability to communicate. Numerous strategies and schemes have been worn inside the sentiment analysis, such as language processing, polarity lexicons, machine learning, and psychometric scales which establish diverse types of analyzing sentiments as assumptions ended, scheme reveals, and corroboration data set. Since the internet has to turn into a commanding resource of retrospect the sphere of sentiment is moreover referred to as Sentiment Analysis or Opinion Mining. It has seen an enormous boost in academia over the decades. Analyzing sentiment to extract sentiments in different levels like word, sentence, and document provides articles' feeling polarities. While well identified consumers' sentiments articulated in sentences by opinion. Customary machine learning schemes cannot virtuously mirror the views of writers. This paper proposes a scheme called multi-strategy sentiments with semantic resemblance to disentangle the topic with partial phrase matching. Additionally, the Naïve Bayes classification is applied to search for the probability of the distribution of knowledge in different categories of knowledge set.

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Automatic Plant Identification Using Transfer Learning

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IOP Conference Series: Materials Science and Engineering 2021年第1期1022卷

作者： S Sachar A Kumar Research Scholar Department of Computer Science and Applications Panjab University Chandigarh India Assistant Professor Department of Computer Science and Applications Panjab University Chandigarh India

Plant identification is a widely researched area in the field of computer vision. Many attempts have been made to automate the process of plant identification using an image of a part of plant including flower, leaf and bark. Leaf has proven be the most reliable source of information. After exhaustive experiments, we chose to apply transfer learning to compare the feature extraction capabilities of VGG-16, Xception, MobileNetV2 Convolutional Neural Network (CNN) and DenseNet121 architectures to freely available Swedish, Flavia and MalayaKew leaf image datasets. Random Forest is used as classifier to identify the species of given leaf. The evaluations and comparisons of the specified feature extractor models are provided. DenseNet121 achieved maximum accuracy of 100%, 99% and 92.4% respectively in the three datasets.

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Polynomial Equation Based Localization and Recognition Intelligent Vehicles Axis using Wireless Sensor in MANET

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Procedia computer Science 2020年 167卷 1281-1290页

作者： R. Ganesh Babu P. Karthika G. Manikandan Assistant Professor(SS)-Dept of ECE Rajalakshmi Institute of Technology Chennai-600124 TN India Research Scholar -Dept. of Computer Applications Kalasalingam Academy of Research and Education Krishnankoil Virudhunagar-626126 TN India Assistant Professor-Dept of ECE Dr. M.G.R Educational and Research Institute Maduravoyal Chennai-600095 TN India

Vehicle need for the image security is the present time. The task of security is being dangled as there is an assortment of information and vehicle to verify as the various dimensions of information security is required depending on the vehicle and picture information type. Encryption is the greatest catalyst way to deal with assuring the security of pictures and vehicles over open systems. The proposed another open cryptosystem key depends on the polynomial condition. In this methodology has been wanted due to their fight over the cryptanalysis assaults. Parameter, for example, relationship coefficient, entropy, 12 shape parameter, histogram investigation is utilized for the productivity of our planned strategy. The theoretic and reenactment outcome gives a high amount of security. Hence, it is reasonable for down to earth use in secure correspondence.

关键词： Encryption Decryption Polynomial Equation Parameter Analysis MANET

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Review on Crop Prediction Using Deep Learning Techniques

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Journal of Physics: Conference Series 2021年第1期1767卷

作者： M K Dharani R Thamilselvan P Natesan PCD Kalaivaani S Santhoshkumar Assistant Professor Department of Computer science and Engineering Kongu Engineering College Erode Professor and Head Master of Computer Applications Kongu Engineering college Erode Professor and Head Computer Technology (UG) Kongu Engineering college Erode Assistant Professor (SLG) Department of Computer science and Engineering Kongu Engineering College Erode Assistant Professor (SRG) Department of Computer science and Engineering Kongu Engineering College Erode

Agriculture is the very important sector of each country, where the gross domestic pay relies on it. The outcome of the agriculture or crop management was completely based on the end yield and the market rate. The complete factor of the crop yield depends on timely monitoring and suggestion. Artificial intelligence gives a way to monitor the crop and to predict the yield in an automatized outcome. The study has been made on the deep learning and its hybrid techniques such as Artificial neural network, deep neural network and Recurrent neural network. It helped to identify how the technology of artificial intelligence helps to improve the crop yield. The research study clearly gives the idea and need of recurrent neural network and hybrid network in the field of agriculture. It also shows how it outperforms the other networks such as artificial neural network and convolutional neural network. The results were analyzed and the future perspectives were drawn with the obtained outcome.

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A recurrent neural network forecasting technique for daily PM2.5 concentration level in Southern Kerala

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IOP Conference Series: Materials Science and Engineering 2021年第1期1085卷

作者： Sherin Babu Binu Thomas Assistant Professor Department of Computer Science Assumption College Autonomous Changanacherry Kottayam Kerala India Associate Professor Department of Computer Applications Marian College Autonomous Kuttikkanam Idukki Kerala India

The natural environment and public health are seriously impacted by air pollution. One of the most dominant contributors to air pollution around the world is particulate matter PM2.5. Predicting air pollution in advance has considerable importance for the regulation of people's health and to implement pollution control strategies for air quality management. The study was conducted for Thiruvananthapuram district, the southernmost region of Kerala. The data for the period from 1st July 2017 to 31st December 2019 were collected from the Central Pollution Control Board (CPCB) website. To predict the daily PM2.5 concentration, Recurrent Neural Network (RNN) based Long Short-Term Memory (LSTM) was used here. LSTM was built on the inputs of four meteorological parameters, namely average temperature, wind speed, wind direction and relative humidity and air pollutant parameter PM2.5 values. Performance evaluation of the prediction model has conducted, and the results showed that the model attained considerable prediction accuracy.

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Multiple Watermarking Scheme for Video & Image for Authentication & Copyright Protection

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IOP Conference Series: Materials Science and Engineering 2021年第1期1131卷

作者： Neha Janu Ankit Kumar Pankaj Dadheech Gajanand Sharma Ashutosh Kumar Linesh Raja Associate Professor Department of Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan Jaipur Rajasthan India Assistant Professor Department of Computer Science & Engineering Swami Keshvanand Institute of Technology Management & Gramothan Jaipur Rajasthan India Assistant Professor Department of Computer Science & Engineering JECRC University Jaipur Rajasthan India Assistant Professor Department of Computer Applications Manipal University Jaipur Rajasthan India

Watermarking has been used frequently to authenticate the accuracy and security of the image and video files. In the world of computer technology, several watermarking strategies have developed during the past 20 years. Integrate a picture of identity that is not always concealed, such that no detail is not possible to delete. A monitoring code can also be used to deter unauthorized recording equipment. Another application is the watermark copyright control, which works at stopping the creator of the image from stealing photos unlawfully. A watermark is a promising option for the copyright transcendence of multi-media files, as embedded messages are still included. Due to the limits of fidelity, a watermark may be implemented in a small multimedia data space. There is no proof that Automated Watermarking technologies will fulfil the ultimate purpose of the cleaners of all sorts of copyright security operations to gather knowledge from the data they obtain. Relevant situations may be deemed more fairly expected with the usage of automated copyright marking technologies. A perfect device will not be able to add a digital watermark without the limit, which does not supply the whole object with details. In this work, a modern technique for watermarking includes injecting two or more messages or photographs into a single picture for protection purposes and repeating a similar procedure for N-frames for authentication in the film.

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Biometric Based on Steganography Image Security in Wireless Sensor Networks

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Procedia computer Science 2020年 167卷 1291-1299页

作者： P. Karthika R. Ganesh Babu K. Jayaram Research Scholar -Dept. of Computer Applications Kalasalingam Academy of Research and Education Krishnankoil Virudhunagar-626126 TN India Assistant Professor(SS)-Dept. of ECE Rajalakshmi Institute of Technology Chennai-600124 TN India Associate Professor-Dept. of ECE Sri Ranganathar Institute of Engineering and Technology Coimbatore-641110 TN India

Wireless Sensor Network (WSN) is a rising the innovation that demonstrates incredible guarantees for the different complex applications for both mass open and the military. The detecting for innovation attached with the preparing energy and the remote correspondence the security of biometric data might be compromised by system assaults, showing person’s data without an appropriate insurance isn’t reasonable for approval. The concern of the remote correspondence of the innovation additionally causes different kind of security and dangers in the MANET. The expectation of this paper to examine of the security connected issues and difficulties in the remote sensor organizations utilizing MANET. It is distinguish the security and dangers of survey arranged security instruments for the remote sensor organization. Notwithstanding, encryption and decoding calculations are moderate and contain tedious activities for moving information in system. In this section, by considering remote sensor arranges and confirming server is present another idea called “review” and manages its productivity in managing the security issue in MANET. A “digest” can be gotten from any sort of data attribute through which no one can catch any data of essential biometric qualities. Here demonstrate that this idea prompts the expansion of the precision and availability of a biometric framework.

关键词： Wirelss Sensor Network Steganography Biometric MANET Remote Sensor

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