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

Fetal heart rate (FHR) monitoring is done for accessing fetal wellbeing during antepartum and intrapartum phases. Although noninvasive fetal electrocardiogram (NIfECG) is a potential data acquisition method for FHR, extraction of fetal electrocardiogram (ECG) from the abdominal ECG (aECG) is one of the major challenging research areas. This chapter proposed and assessed a method suitable for single channel based on principal component analysis (PCA) for extracting fetal ECG. Maternal R peaks and fetal R peaks were detected using Pan Tomkins algorithm (PTA) and improved Pan Tomkins algorithm (IPTA), respectively. Performance of fetal QRS detection is assessed using two open-access databases available online. The method shows satisfactory performance when compared with similar methods and makes it suitable for using a single channel system.

School of Computer Engineering & Technology

Engineering and Technology

Designing User Interfaces With a Data Science Approach

Fetal ECG Extraction: Principal Component Analysis Method for Extraction of Fetal ECG

Ambulance is a medically equipped vehicle that transports patients to treatment facilities that have tested to be a lifesaver throughout several emergency cases. One of the issues during transportation of patients is traffic related problems. We studied various approaches available for vehicle tracking systems. After going through various research papers we found these techniques, i.e. GPS based tracking, RFID device, Google API, RESTful API which were proposed earlier and hence we deduce that existing ambulance routing technique is not effective as a result of there is lack of help provided to them during the transparent passage through the traffic congestion. This issue arises due to outdated dedicated GPS systems, no proper communication between police and ambulance and difficulty in providing accurate location of the ambulance. To tackle this issue, we propose a system which will help the traffic police easily track any upcoming ambulance with its priority using a mobile application. This system will help in fast, economical and efficient traffic control providing safe, easy and quick passage to the ambulance.

International Journal of innovative Science and Research Technology

Survey Paper on Ambulance Tracking Systems

World University root node

International Journal of innovative Science and Research Technology 6 (Issue {\ldots}

Survey Paper on Ambulance Tracking Systems

Fetal monitoring usually refers to monitoring fetal heart rate (FHR) for detection fetal well-being. This is important activity carried out by doctors during prepartum, intrapartum phase as per health requirement of patient. Fetal monitoring is required to reduce chances of fetal to become hypoxic (when fetal is deprived from sufficient oxygen) that can cause fetal brain injury and even fetal death. Fetal monitoring plays important role in reducing mortality and morbidity rate. The most common noninvasive fetal monitoring device is cardiotocograph (CTG). CTG captures FHR based on Doppler ultrasound principle and uterine contractions (UC) based on pressure transducers. The present study highlights accuracy limitations of CTG and proposes more accurate noninvasive fetal ECG (NIfECG) as data acquisition methods to acquire FHR and electrohysterogram (EHG) to capture UC. CTG interpretation is one of the decision-making parameters used by doctors for early intervention like caesarian section. CTG interpretation often suffers from inter-observer and intra-observer agreement of CTG patterns which are non-reassuring. To overcome this limitation, computerized analysis can be useful. The present study also discusses usage of machine learning to detect fetal compromise. Further, in addition to FHR and UC analysis, we also propose to use ST waveform analysis to improve results. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Networks and Systems

Comprehensive Study of Fetal Monitoring Methods for Detection of Fetal Compromise

i-manager's Journal on Computer Science

Indian Sign Language Recognition System Using Openpose

Nowadays, there is a drastic increase in demand for data storage. Due to increasing demand for data storage, the concept of cloud computing is on the rise. This enormous amount of data can be backed-up on the cloud storage but, the problem is that it significantly increases the cost of the storage and its performance. Traditional storage process of data introduces redundancies and hence concept of Data deduplication is developed. Data deduplication is an effective solution for eliminating the redundancies. It uses the concepts of hash values and index tables which help in removal of duplicate data. With the use of Data deduplication process, an effective performance increase and reduction in cost of storage can be observed. In this paper, we have discussed different data deduplication methods considering their advantages and disadvantages. We have also proposed enhanced security method for generating data chunks by using standard encryption method.

International Journal of Computer Engineering and Applications

Secure Data Deduplication for Cloud Storage: A Survey

Machine learning has gained a lot of traction in the recent years, due to an increase in computing power of personal computers and the quick access to datasets, large enough to train highly accurate ML models. Recent studies have shown a lot of promise in the amalgamation of Machine Learning in the field of Biomedicine. The detection of dementia has also attracted a lot of attention given the increase in life expectancy. The aim of this survey article is to methodically study the various Machine Learning Techniques being used in the Biomedicine research. There is no definite diagnosis for Alzheimer’s Disease currently, the only conclusive diagnosis that can be made is during the autopsy conducted. The objective of this survey could help to develop a method for the conclusive detection of Dementia.

MACHINE LEARNING ALGORITHMS FOR THE PROGNOSIS OF DEMENTIA: A SURVEY

International Journal of Computer Applications

A Heuristic Approach for Encryption Policies in Data Outsourcing

Sign language is a visual language that uses hand gesture, change of hand shape and track information to express meaning, and is the main communication tool for people with hearing and language impairment. Recently, there has been an increase in research in the field of deep learning and creation of deep learning libraries like tensorflow, keras etc. have made it easy to make use of convolutional neural networks. It has made it easy to create different layers like convolutional layers, pooling layers, fully connected layers etc. Based on the recent developments and technology we are proposing a system for sign language recognition of alphabets and numbers based on CNN. We have used CNN because it increases the accuracy of the system by recognizing hidden patterns and correlation in raw data.