Volume 9 | Issue 6

 Abstract

Data mining consists of various applications in financial and medical. Data Mining perform various tasks.Classification is one of the main task in data mining. In this paper classification is integrated in Cloud computing.Whenever the user created data in offload that can be encrypted and sent to the cloud.This paper uses classification technique for security in cloud. This paper implements KNN classification and prove its efficiency.

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 Keywords

Security, Classification ,KNN classifier, encryption, Security

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 Abstract

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 Keywords

Attendance, Curriculum, Semester

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Machine Learning has been exponentially growing in the past with applications in almost every field of science and engineering. It is a very useful and efficient technique to make sensible interpretations of the vast amount of data which is very difficult to carry out but the human mind. There are many fields in science where huge amounts of experimental data are systematically developed over several decades. It can be utilized to make new interpretations and understandings with the help of machine learning, which was otherwise not possible. This article reports advancements made in the fields of genetics, material science, and agriculture with the successful use of machine learning.

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Machine Learning, Material science, Genetics, Agriculture

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COVID-19 pandemic is the deadliest crisis the entire world is going through. There are many active cases and deaths that have been brought about by the infection. The main symptoms of the disease include fever, dry cough, sore throat, tiredness and difficulty in breathing. To prevent the spread of disease, infected people should maintain hygiene and to be kept in isolation. Masks, sanitiser, and physical distance are to be maintained to control the spread of disease. This disease mainly affects the respiratory system thereby affecting the oxygen intake which is essential for human survival. In the present paperwork, we estimated the probability of a patient being affected with COVID-19 and estimated whether they need oxygen or should be hospitalized or if home quarantine is enough based on the given patient's details.

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Logistic Regression, Django, Python, COVID-19, Symptoms, SPO2, Hospitalization

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Women domestic help, development, socio and economic conditions, exploitation.

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Diabetes has grown to be a severe problem now a days. So, we need to take severe precautions to eliminate this. To eradicate, we have to predict the occurrence of Diabetes. We predict the occurrence of diabetes with the usage of Random Forest which is Machine Learning Algorithm. Pima dataset is a data of real patients. Using these records, we are able to build accurate model that can predict the existence of diabetes. The factors which we are considering are pregnancies, glucose, blood pressure, skin thickness, insulin, body mass index, diabetes pedigree and age.

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Random Forest, PIMA dataset, Machine Learning.

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RP-HPLC, Dutasteride (DTS), Benign prostatic hyperplasia, ICH Revised Q2 (R1) guidelines.

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Surveillance systems play a crucial role in maintaining security and order in public places. Despite CCTV cameras installed at most of the locations, crimes that are captured in CCTVs not reported in an effective way. In this context, there has been an enhanced attention for increased surveillance in order to monitor crowd behaviour and to nab fugitives, suspects and criminals, especially in bus stations, railway stations and airports and other crowded locations. CCTV, in general, requires human supervision which may lead to missing some important crime events due to human error. The proposed project aims to help automate the process of monitoring the CCTV footage and supports in proactively detecting suspicious behaviour in real-time videos with alerts sent to higher authorities. The alert is generated and forwarded to designated authorities if suspicious events occur, which will help in preventing crimes, assisting in crime investigation, identification of suspects and also supports in automating some of the groundwork that is manual and time-consuming. Towards this, the paper attempts to incorporate two independently working machine learning models into one working model. To get the best results, transfer learning has been used for enhanced performance of each model and give better and faster results. The video feed from the CCTV will be taken as the input in our system and image frames will be extracted and fed into the two sub-systems of the project. For criminal/suspects face recognition, transfer learning on VGG16 model is used, for weapon detection, darknet framework is to be applied with YOLOv4 algorithm to get the desired object detection. These machine learning systems have been designed to work in parallel which in turn ensures faster output.

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CCTV surveillance, machine learning, transfer learning, face recognition, VGG16, YOLOv4.

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 Abstract

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HTML, CSS, Java Script, NetBeans IDE 7.1.2,MYSQL DBMS

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Cervical carcinoma, risk factors, genetic polymorphism, SNPs, genetic variants.

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ABSTRCT: The present study has explored about teaching aptitude of in-service teacher trainees in-service teacher trainees in relation to their intelligence, gender and locality. A representative sample of 200 in-service teacher trainees from B.Ed. colleges of Raichur district was randomly selected. Teaching aptitude scale (2002) by L.C. Singh and Dahiya and test of general intelligence (2012) by S.K.Pal & K.S.Mishra were used to measure teaching aptitude and general intelligence of in-service teacher trainees. The study depicts that there is significant difference in teaching aptitude between high intelligent and low intelligent in-service teacher trainees revealing that high intelligent group have high teaching aptitude than low intelligent group. While teaching aptitude has no relevance with the gender of the individual but on the other hand teaching his/her affect aptitude of an individual family background or his/her place of living.

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Key words: Teaching Aptitude, In-service teacher trainees, Intelligence, Gender and Locality

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Key words: Kendriaya Vidyalaya, Teaching effectiveness, teaching aptitude, relationship

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Creative Commons Attribution 4.0 and The Open Definition

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Education, Job Involvement, Professional development, Teachers, Teaching competency

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KEYWORDS: Antenatal care, Perceived stress, psychosocial stress, Pregnant women.

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9657396807

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Global warming, nuclear energy, sunlight, solar system, megatrend, mass to energy, carbon dioxide, petrochemical, greenhouse gas.

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Abstract : This study is to know the attitude of Teacher Educators who are prepare future teachers as their attitude can play a significant role in the character building and development of teachers in the future to whom they are going to teach and in the successful implementation of four years B.Ed. Programme. The investigator could not find any study about the attitude of Teacher Educators towards four years of integrated B.Ed. Programme. Hence, the present study is an attempt in this direction to investigate the attitude of teacher educators towards four years integrated B.Ed. Programme and teaching profession. The survey method was used for the present study. The researcher had constructed the five-point attitude scale to measure the attitude of Teacher Educators towards four years of integrated B.Ed. Programme. The Teacher Educators in Kalaburagi Education division comprised the population for the present study. Purposive sampling technique was employed to select the sample of 200 teacher educators covering Arts and Science streamlines from 100 TTI in Kalaburagi Education. The data were statistically analyzed and interpreted.

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Keywords: Teacher Education, Teacher Educators, Attitude, Four Year Integrated B.Ed. Programme.

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In this paper, we propose a novel semantic segmentation-based on the body pix module of the Tensor flow.js which can keep up with the accuracy of the state-of-the art approaches while running in real time. The solution follows the convolutional neural networks, each step in the workflow being enhanced by additional information from semantic segmentation. Therefore, we introduce several improvements to computation, aggregation, and optimization by adapting existing techniques to integrate additional surface information given by each semantic class. Using the body pix model which is trained using CNN, the ResNET50, this network can work with more than 150 layers, removing the problem of vanishing gradients. Using this network our body pix module, creates a more accurate and defined segmentation, and also supports multi-person segmentation.

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Semantic Segmentation, Convolutional Networks, Deep Learning.

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Tools of increasing sophistication have been developed to serve the human race over many centuries. Digital computers are, in many ways, just another tool. They are capable of performing the same numerical and symbolic manipulations as a normal person, but at a faster and more reliable rate. The purpose of this paper is to provide an overview of artificial intelligence. It provides a brief overview of artificial intelligence, its history, and future prospects.

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aritifical intelligence, tools,application

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Indian Cuisine consists of a variety of regional and traditional cuisines native to the Indian Subcontinent. Given the diversity in soil, climate, culture, ethnic groups, and occupations, these cuisines vary substantially and use locally available spices, herbs, vegetables, and fruits. Indian food is also heavily influenced by religion, cultural choices and traditions. The cuisine of India is one of the world's most diverse cuisines, characterized by its sophisticated and subtle use of the many spices, vegetables, grains and fruits grown across India. The cuisine of each geographical region includes a wide assortment of dishes and cooking techniques reflecting the varied demographics of the ethnically diverse Indian subcontinent. The project is based on exploratory data analysis on data set 'Indian Food 101'. The data set contains the information about famous Indian dishes. We plot some graphs to know the trends of food in different region and correlation between cooking time and food item, number of food items for each state veg-nonveg and recommendation of similar dishes using K-nearest neighbor.

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