MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Computer Engineering & Technology

The idea of making everything readily available and universally has led to a revolution in the field of networks. In spite of the tremendous growth of technologies in the field of networks and information, we still lack in preventing our resources from cyber-attacks. This may not concern small organizations but it is a serious issue as far as industries, companies or national securities are concerned. Since many different mechanisms were opted by organizations in the form of intrusion detection and prevention systems to protect themselves from these kinds of attacks, there are many security breaches which go undetected. A host-based intrusion detection system (HIDS) is a system that monitors a computer system on which it is installed to detect an intrusion and/or misuse, and responds by logging the activity and notifying the designated authority. In this paper, we develop a HIDS using logs generated by services running on the systems. We will discuss about the client-server architecture used in HIDS.

Engineering and Technology

IOSR Journal of Computer Engineering (IOSR-JCE)

Log Based Intrusion Detection System

Non verbal communication has its own benefits and importance from the perspective of manyapplications. Facial expressions are one of the significant forms of non verbal communication amongst othermajor non verbal communication indicators like brain signals, body posture, gesture and actions etc. usedprominently to convey the emotional state/ mood of a person. Emotion recognition serve wide range ofapplications like healthcare, patient pain monitoring, driver alert system, cognitive assessment, e- learning,animation etc. Emotion classifier is modeled around the features fed to the model in the form of feature vectori.e. set of prominent features/attributes. The correctness in extracting the facial features has tremendous impacton classifier accuracy. The paper presents the study of various popular and unique techniques used so far forfacial feature extraction and emotion classification. Various techniques of facial expressions analysis arecompared over the performance parameters like recognition accuracy, number of emotions addressed, Databaseused for experimentation, classifier used etc

IOSR journal of Engineering

Facial Features Based Emotion Recognition

When owner stores his data on cloud that time for keeping his data confidential and to achieved access control, the owner can use encryption algorithm called attribute based encryption to encrypt his data. For achieving strongest form of access control, we are using to construct cipher text-policy attribute-based encryption in our work also we implemented Division and replication of Data in the Cloud for Optimal Performance and Security (DROPS) which secures data from threats and attacks in this DROP technique data is fragmented and stored using T-Coloring graph in cloud storage. Each node is able to store only one fragment of one file. Third Party Auditor will check integrity of stored data and inform the data owner

World University root node

International Journal of Science & Engineering Development Research

CPABE and Data Integrity on Cloud Storage

International Journal for Scientific Research & Development|

Conflict Solving with the Use of Driver Distraction

Recently there are a lot of advancements in healthcare technology. Amongst, Electronic Health Record (EHR) is an upcoming trend which stores patients’ demographics, lab tests & results, medical history, habits etc. collaborated in electronic form. EHR is huge data, which is difficult to maintain and retrieve. So the idea of health risk prediction is formulated in this work. To get the relevant data from EHR, feature selection technique is used. Feature selection is responsible to collect only important and needed data from the dataset. For feature selection regression method is used in which loss function is proposed due to which accuracy and performance of the model are increased. Further risk prediction is done using neural network model. Deep Neural Network (DNN) is best suited for pattern learning and prediction purpose. It consists of various layers which have their specific function. DNN uses transfer learning to avoid repeated training for the whole system. Dataset considered here is of hypertension. EHR data is also synthetically created for analysis.

International Journal of Advance Research, Ideas and Innovations in Technology

Automatic Feature Selection from EHR & DNN Modeling

Part of the renewed excitement about research in image and video captioning, which is a combination of Computer Vision, Natural Language Processing, and Knowledge Representation and Reasoning stems from a belief that it is a drastic step towards solving AI. The problems at the intersection of Computer Vision and the processing of natural language are of significant importance to challenging research questions and for the rich set of applications they enable. Given an input image and an open-ended question in natural language, it needs an understanding of visual elements contained in the image and common-sense knowledge to provide a useful response. In this review, we examine multiple approaches to this problem - where images and questions are mapped to a common feature space - along with the datasets available to train and evaluate these systems. We also discuss future scope and promising directions in which this field could be headed towards

International Research Journal of Engineering and Technology (IRJET)

Image Question answering :A Review

The rapid growth in the field of data analysis plays an important role in the healthcare research. Due to large amount of data growth in biomedical and healthcare field providing accurate analysis of medical data that has benefits from early detection, patient care, and community services. Previous system designed to analyze, manage and assimilate data produced by healthcare systems. Data analysis has been applied to help the disease-related information and treatment process. In this paper a decision tree is effectively used for predicting the outbreaks of diseases in society. The paper proposes to experiment with the modified predictive models with medical data which is related to the symptoms of the disease. For the disease prediction using unstructured data, we used a convolutional neural network which is based on multimodal disease risk prediction (CNN-MDRP) algorithm. Users can post their queries in order to seek information regarding diseases so that user get the proper answer to any kind of question and solving any problem related to the disease.

International journal of Computer Engineering and Aplication

DISEASE PREDICTION BY USING MACHINE LEARNING

With the fast progression of digital data exchange in electronic way, Information Security is becomingmuch more important in data storage and transmission. Information Confidentiality has a prominent significance in thestudy of ethics, law and most recently in Information Systems. With the evolution of human intelligence, the art ofcryptography has become more complex in order to make information more secure. In recent years, a lot of applicationsbased on internet are emerged such as on-line shopping, stock trading, internet banking and electronic bill payment etc.Such transactions, over wire or wireless public networks demand end-to-end secure connections, should beconfidential, to ensure data authentication, accountability and confidentiality, integrity and availability.

International Journal of Innovative Research in Computer and Communication Engineering

A Comparative Study on Various Encryption and Hashing Algorithms for Ranked Keyword Search over Encrypted Cloud Data

Computer system is widely used across the globefor several purposes in different fields and failure in thissystem is natural. It is not acceptable as it might lead to lossof important data. There are several reasons which cancause the computer system or an application to crash or fail,thus causing loss of important data lead to redo all theactivity or task, user was performing before the systemcrashed. Our system proposes a solution to this problem bybacking all the data to the cloud and thus can be restoredwhen the system recovers from the crash, allowing toresume the task which the user was initially performing.

Application Backup And Restore Across Multiple Devices

Tech-care is system designed and developed to monitor user’s health and give future disease risks prediction based on the collected data. The system is a four tier system which helps the user creates his own electronic health record with minimal daily efforts. Based on these records the system provides user with daily analysis as well as risk prediction based on the recorded data. The system also includes a front-end directly connected to the doctor to facilitate easy access of the records and provide doctor with intelligent insights. The overall aim of Tech-care is to develop a unique approach towards maintaining Health records and predict the future risks enabling better and user specific daily routine and daily health management.