VOLUME 11, ISSUE 3, MARCH 2022

Abstract: Fieldwork is an important task of lecturers in People’s Police University in order to raise awareness and professional skills, and help lecturers to combine theory and practice in a professional manner. During the teaching process, lecturers going on practical business trips are both rights, obligations and conditions for consideration and appointment of teaching titles. The field trip of the lecturer always plays an extremely important role, helping the lecturer gain a deeper understanding of professional activities in practice, collect documents and materials from which to bring "real breath". see" into his lecture.

Keywords: fieldwork, professional skills, theory and practice, teaching.

Abstract: An analysis is presented to investigate the effect of Hall current and heat absorption on MHD flow of an electrically conducting incompressible fluid along an infinite vertical porous plate with viscous dissipation. The governing partial differential equations are non-dimensionalized and transformed into a system of nonlinear partial differential similarity equations. The resulting nonlinear equations are solved under appropriate transformed boundary conditions by using Galerkin finite element method. Computations are performed for a wide range of the governing flow parameters viz. Grashof Number, Modified Grashof Number, Transpiration cooling parameter, Prandtl Number, Schmidt Number, Eckert number, Hartmann number, Heat absorption parameter and Hall parameter on the flow field. Numerical results for the dimensionless velocity, temperature and concentration profiles are obtained and displayed graphically for the above parameters. Key words: MHD flow, Hall current, Heat and mass transfer, heat absorption, viscous dissipation, finite element method.

Abstract: Payment wallet has many significant features like anytime transfers, mobile transfer, secure and convenient transfer of money.  It can also be considered as a bank for those who do not have approach to banks and do the banking activity like sending and receiving money. Digital wallets are gaining momentum in the Indian market due to increasing technology penetration and acceptance of new developments by the customers. By using E-Wallet payments can be made any time anywhere including receiving money, storing, sending. It works very closely with banks and telecom companies to offer banking services to its subscribers. Use of e-wallets helps in moving away from a cash base economy. In the process, all the transactions get accounted in the economy, which has the effect of reducing the size of the parallel economy It is an online platform which allows a user to keep money in it, just like a bank account. A user needs to make an account with a mobile wallet provider. This can be used in many different sectors of businesses, Shops, Malls. It will also capitalize the scope of India’s education market segments.

Keywords: E-Wallet, Payment, Transaction, Fraud detection.

Abstract: Grid synchronization failure can cause complete black out. So, there is always a need for a system that can sense any abnormalities and take actions accordingly to prevent black outs. A grid is connected with several power generating units like thermal, nuclear, wind etc. to deliver power to the load. In India, the generating units have to deliver power according to the Indian Electricity Grid Code, 2010 which states that the variation in voltage should be within the limit of ±5% and that for the frequency should be within ±3%. If any value higher/lower is detected, then that particular feeder should be disconnected from the grid temporarily in order to protect the grid. In this paper, we will be discussing about a system based on the microcontroller, that will be used to monitor the variation in voltage and frequency of the any external supply source, and automatically disconnects the supply source from the load.

Abstract: Biometrics which can be used for identification of individuals based on their physical or behavioral characteristics has gained importance in today's society where information security is essential. Face geometry based identification systems utilize the geometric features of the face like length and width of the face. The proposed system is a verification system which utilizes these face geometry features for user authentication. This project introduces an inexpensive, powerful and easy to use hand geometry based biometric person authentication system. One of the novelties of this work comprises on the introduction of face geometry's related, position independent, feature extraction and identification which can be useful in problems related to image processing.

Abstract: In this work we explore a deep learning and natural language processing (NLP) based dialog system that generates responses from a conversation design perspective. We trained a feed forward neural net model on a carefully curated dataset of normal query-based questions related to Ecommerce. We show that end-to-end systems learn patterns very quickly from small datasets and thus, are able to transfer simple linguistic structures representing abstract concepts. We also integrated this chatbot in a simple web application, where users can directly interact with our chatbot. As we are using NLP our chatbot model is getting familiar to user’s responses and training itself to respond with better responses.

Keywords: Chatbot, AI Chatbot, Natural Language Processing, Deep Learning.

Abstract: Our reality is transforming into an e-world. A great deal of information is made day to day. The computerized information that we share around should be safeguarded by the undesirable craps, the gate crashers who gets into the data set and make issues. Cryptography gives the strategies through which one can shield our information. Furthermore, in this paper, we are giving survey on the sorts of present day cryptography and its different phrasings.

Keywords: cryptography, modern cryptography, safeguard, database.

Abstract: Nowadays, Chronic diseases are turning out to be widespread. Treatment and observing of these diseases require going to hospitals regularly, which adds to the burdens of hospitals and patients. Present day's advancements in smart sensors and communication devices add to improving the medical care system such that will reshape medical services such as Remote Patient Monitoring (RPM) methods based on the collection of patient's body vital signs extricated using intrusive and non-invasive techniques, then sending them continuously to caretakers and doctors. This information might help doctors in taking the perfect decision at the right time. The objective of this paper is to design research headings on Remote Patient Monitoring (RPM), proposing a design of AI-based RPM, its benefits, its challenges, and its possible future bearings.

Keywords: Remote Patient Monitoring (RPM), Electronic Health Record (EHR), and Internet of Things (IoT)

Abstract: The project aims to provide the facility to manage the stock of medicines. It is designed for all the items that come inside the pharmacy. Management is the most important aspect of a pharmacy today, so this project demonstrates the design and implementation of that pharmacy. It makes it easy to manage the stocks and also provides sophistication to the user. It enriched the management of the pharmaceutical sector in India because, in our country, pharmaceutical management is a very essential thing to do for the safety of patients through pharmacy. The pharmaceutical supply system, for example, incorporates order placement, receiving, and storing of pharmaceutical products through inventory management software that is accessible on smartphones. The entire pharmacy data is analyzed, including medicine, pharmaceutical instruments, and inventory management software manages them. We need to consider a useful method to effectively manage your medical store by using an inventory system. A properly managed pharmacy can bring significant benefits to your business. Proper drug storage is crucial for ensuring you are always aware of your stock, which will help prevent any shortages. As a result, you can ensure that your pharmaceutical business is efficient and profitable in the long term.

Abstract: Due to increasing demand for data and connectivity, it has become necessary to enhance the data capacity of the existing 4G LTE network. In order to achieve this fit , the use of adaptive modulation and coding with involvement in finding the best combination of modulation scheme and code rate that best maximizes the throughput of the network momentarily for a given signal to noise ratio (SINR)available to the User equipment (UE). A method has been presented in this research work which is based on adaptive modulation and coding (AMC) switching which uses an algorithm that considers a certain given block error rate (BLER) requirement before deciding the best combination of modulation scheme, code rate and transmission mode that is most appropriate for a given available SINR from the UE. Field measurements were carried out to reveal the exact values of SINR values obtainable from a UE in a typical LTE cell. The SINR values were then simulated for different modulation schemes (QPSK, 16QAM, 64QAM and 256QAM, code rates ) varying from 0.13 to 0.92 depending on the modulation scheme and Transmission modes (TM7, TM8 and TM9) to generate the BLER and throughput performance for each unique combination of the stated parameters (modulation scheme, code rate and TM mode). The generated table served as a database to determine the best combination of modulation scheme, code rate and TM mode that best maximizes the throughput for a given input SINR and maximum BLER requirement.

Keywords: 4GLTE, BLER, SINR, Adaptive Modulation and Coding;

Abstract: -Wavelet-based image compression has been the subject of recent study. We suggest a compression method based on modifying the original EZW coding in it. We strive to eliminate less significant information in the image data in this lossy technique in order to achieve additional compression with little impact on output image quality. In each level, the algorithm calculates the weight of each sub-band and determines the sub-band with the least weight. Each level's smallest weight sub-band, which has the least effect during image reconstruction, passes through a threshold process to remove low-valued data. During the experiment, several threshold settings were used to determine how they affected the compression ratio and reconstructed image quality. As a result of the proposed strategy, the compression ratio is increased even more. The rapid advancement of computing technologies has resulted in a demand for digital photographs. The expense of manipulating, storing, and transmitting these photos in their raw form is prohibitively expensive, slowing transmission and increasing storage costs. A quick review of wavelet transform theory is given in this study, with filters used as examples to demonstrate multiresolution analysis. The advantages of the Fourier transform are studied, and numerous conclusions are drawn. The pyramid algorithm is also discussed, as well as several wavelet aspects in image data compression. image quality isn't harmed in the process.

Keywords: -Image compression, Wavelet image Compression, Embedded Zero coding, Sub band Coding.

Abstract: Now a days, the most active problem that affect both physically and mentally for the mob is the problems occurs when live vote happens. The problems created by political party leaders that sorrounded on different platforms of the booths, ineffective way of counting votes, the rude behaviour from the volunteers, and of the election officers in the booth. And a main problem is that old age peoples can’t vote because of their physical and both mental illness. Everyone has the right to vote, it is the fundamental right of a person. He /She have the right to vote. For that here we are implementing the Electronic voting system or E-voting. In our day to-day life, the implementation of electronic devices  are being increasing day by day. The knowledge of peoples that how to use smartphones and other digital devices are so efficient now. Here through web applications we can reveal our votes. The promotion of safe,serviceable and easy voting system are there.The group voting methodology and also the face recoginition and fingerprint are also implementing.

Keywords: face recoginition,voice recognition and finger print,Group voting,Blind and Deaf voting.

Abstract: An extensive review is conducted in the perspective of comprehending key strategies interested in creating diabetic retinopathy algorithms throughout this study. The research reveals indicated specialists use retina computer vision algorithms in conjunction with numerical learning techniques to identify abnormalities in eyes, and that they have used control criteria including such vascular areas to do so. We conducted a systematic review of approaches for mechanically identifying and classifying diabetic retinopathy throughout this work. This reviewed in the previous out though those writers use essentially three ways for diagnosing diabetic retinopathy, and a detailed look at methods for evaluating diabetic retinopathy is provided. Significantly the most frequent outcomes of diabetes are diabetic retinopathy. Unfortunately, many patients are unaware of any symptoms until it is too later to treat them efficiently. A pathway will be built for early retinal image analysis and prognosis during the field of counselling through analyzing the retina's, optical nerves, and optical brain Centre’s evoked applying suitable. Diabetic retinopathy is among the most devastating chronic diseases in the world, and is also one of the main causes of preventable vision. Timely identification of diabetic retinopathy allows for prompt treatment, and in order to achieve this, Screening programs will require a large amount of effort., particularly automated screening systems. A representative fundus picture database is essential for automated screening tools to function properly. We present a novel diabetic retinopathy database in this study, as well as a review of existing accessible datasets. Our database is the first and only database we are aware of that contains diabetic retinopathy abnormalities and significant fundus structures documented for every image in the database, making it ideal for the creation and assessment of existing and new diabetic retinopathy treatments.

Keywords: Big data in diabetic retinopathy, Diabetic retinopathy and big data, Healthcare and big data, diabetic retinopathy.

Abstract: Cancer is a common disease that has caused fatalities among all age groups worldwide causing thousands of deaths each year. It is, therefore, necessary to diagnose cancer at an early stage. Deep learning has been proven pivotal for the early detection of cancer. This project uses deep convolutional neural networks to classify cancer in medical images belonging to four common cancers. This project is an effort to apply deep learning for cancer detection using both custom made DCNN models and pre-trained models. Images are analyzed using various edge detection algorithms. Data augmentation has been employed on the images. The four cancers image datasets used for this project are breast cancer histopathological images, brain MRI images, lungs CT scan images and skin lesion images. The performance of the proposed models is compared based on classification accuracy, precision, recall and f-score. After a comparison of the performances of the model, the model with the best performance will be deployed using flask REST API. This is an attempt to make the use of deep learning practical for a medical professional to diagnose cancer. This project is an attempt to bolster the previous research and development in the field of cancer diagnosis using deep learning.

Keywords: BrecanNet, BrainNet, Classification Accuracy, Deep Convolution Neural Network, LungNet, MelNet

Abstract: The great use of the internet in cyberspace thoroughly changed the information environment for the development of artificial intelligence. Artificial intelligence (AI) 2.0 is a new stage of AI research. Internet crowd intelligence technologies are advanced. One of the most significant features of research in the AI 2.0 era is crowd-based intelligence and autonomous-intelligent systems. In the coming decades, it will attract and achieve remarkable progress in both the industrial and research communities. It will even advance our society as well. Specifically, crowd intelligence provides a problem-solving prototype by collecting the intelligence of hordes to focus on challenges. Due to the accelerated evolution of the sharing economy, crowd intelligence has not only become a new approach to resolving scientific challenges but has also been amalgamated into all variants of application scenarios in day-to-day routines, to cite an example, online-to-offline (O2O) applications, real-time traffic monitoring, and logistics management. In this research paper, we look at the existence of crowd intelligence. First and foremost, we describe the concept of crowd intelligence and its relationship to existing concepts, e.g., crowdsourcing and human computation. followed by presenting the four categories of representative crowd intelligence platforms. To recapitulate, three core research problems and the state-of-the-art techniques of crowd intelligence are analysed. Ultimately, we consider the promising future research directions of crowd intelligence.

Keywords: Artificial intelligence; Crowd intelligence; Crowdsourcing; Human Computation;

Abstract: On the internet, social networking sites (SNS) have become a common occurrence. Individuals use social networking sites (SNSs) like Facebook to present themselves and keep in touch with friends and family. The goal of this research paper is to give data from a variety of studies conducted by a variety of researchers in a variety of settings that clearly indicate the influence of social media on today's youth privacy.

Keywords: Social network, privacy, Facebook , security

Abstract: In this research paper as the title stated Cloud Computing Based on Predictive Acknowledgement System in which Cloud computing is operated to moderate Traffic. We have introduced PACK (Predictive Acknowledgement) which automatic Traffic Redundancy Elimination System (TRE), acquired from Cloud Computing customers. By using this Cloud Computing Based TRE use of reduction of the price in combination with the extra price of TRE Computation and storage will be improved. Cloud Computing Based on Predictive Acknowledgement has the advantage of its competency to reduce the load of the Cloud server. So that we have to Improve the Server productivity and minimize the amount of workload. To analyse prediction for Cloud users, the data transfer cost is a valuable issue when we have to minimize the costs consequently, by applying a well-judged use of cloud resources, cloud customers are motivated to use various TRE Systems, in Traffic Redundancy Elimination System (TRE). We recommend in this research new Calculations for the Lightweight Chunking Scheme. Lightweight Chunking Scheme is a fresh substitute for Rabin fingerprinting used in Traffic Redundancy Elimination System (TRE) . . So that we can So that I can develop the server efficiency and reduce the workload. This system can be applied in a very large area. Finally, we concluded Prediction Acknowledgement benefits for cloud users using traffic traces from various sources

Keywords: Traffic Redundancy Elimination, Cloud computing, Predictive Acknowledgement, Network Optimizing

Abstract: The use of the web has many positive effects on education. It overcame time and space limitations in traditional colleges teachers and students are now using the web to access vast amounts of information and resources in the cyber space. In our proposed work we aimed to ease the manual project work by developing web-based project management system. This system is an environment where all the process of the student in the institution is managed. It is done through the automated computerized method. This system saves the time of the student and of the faculty/students. As the system is online the information is globally present to everyone. As the system used in the institute is outdated as it requires paper, files and binders, which will require the human workforce to maintain them. To submit the project related material in the institute, a student in this system should come to the university. while standing in the queue which consumes a lot of the student’s time as well as of the management team. As the number of the student increases in the institute manually managing the strength becomes a hectic job for the faculty. This computerized system stores all the data in the database which makes it easy to fetch and update whenever needed.

Abstract: Although each individual human has a unique face, their expressions tell us the same tale and play an important role in determining an individual's emotions and behaviour. Music is the purest form of art and a medium of expression, and it is seen to have a stronger emotional connection. It has a unique capacity to make one feel better. This project system aims to create an effective music player that is based on the user's emotion and employs facial recognition algorithms to do so. The extracted facial traits will generate a system, minimising the effort and time required to accomplish so manually. A camera is used to record facial data. Deep learning algorithms are used by the emotion module to determine the exact mood associated with a given phrase. For real-time film, the mood detection module in the system has an accuracy of over 80%, while static images have an accuracy of 95 to 100%. As a result, it produces greater precision in terms of time and performance.

Keywords: Computer Vision, Deep Learning Techniques, Face Recognition, Emotion and Mood Detection, Mood Extraction Module, Computer Vision

Abstract: This kit will help the doctor and their staff to monitor their patient accurately and take decisions as fast as possible to help to improve their quality of service to patients. This system introduces a smart patient health tracking technique that utilize Sensors to track health of patience and uses wireless internet to inform their loved ones in case of any emergency or issues. Our system uses temperature as well as heartbeat sensing for monitoring the patient health. The sensors are bridge to a microcontroller to monitor the report which is in turn interfaced to an LCD display as well as WIFI connection in order to transmit issues in the particular range. If system detects any sudden changes in patient heartbeat or any sudden changes in body temperature, the system automatically alerts the end user about the patients status over IOT and also shows piece of information of heartbeat and temperature of patient live on the internet. Thus IOT based smart patient health tracking smart kit effectively uses internet to monitor health of patience stats using android platform and ardino and save lives on time.

Keywords: Smart Health care kit, Arduino, Android platform, monitoring system

Abstract: BookSwap is an online book exchange system which is used to exchange books and one can buy new books at a particular discount. In some cases, books are expensive and parents can’t afford new books. So, considering the problems, from the new emerging technologies we have chosen a web development domain to create a website which will be useful for the underprivileged as well as for the ordinary masses. The ‘BookSwap’ website would be an online platform where one can buy new books at reasonable prices with the exchange of pre-owned books if any. This platform would also provide the facility to acquire second-hand books at decent prices to the book lovers who cannot afford new books. The website has certain requirements for exchanging pre owned books.User’s pre-owned books should not be older than two years and can be directly purchased if the user is purchasing any fresh book from BookSwap. The adequate value in money for the pre-owned books will be given according to the condition of the book at the time of purchase. If the book is in good condition we will offer half of the original price of the book. If the book is in average condition then 40% of the original price of the book.If the book is in poor condition then one third of the original price of the book is offered.

Keywords: Book swapping, Book recommendation, Ecommerce, Online book system

Abstract: Opinions of the public and the sentiments originating thereby play a pivotal role in social procedures. Sentiment analysis deals with the resolution of the tone or polarity of the text- how positive or negative it is. When applied to news reports, it provides a wide range of applications. This study analyses news reports in real-time from reliable sources using a slightly modified Na¨ıve Bayes’ Algorithm. An article is fetched and then pre- processed to get rid of noisy words like English articles. After tokenization, the probability of each word being either positive or negative is determined. This is achieved by training a model using a dataset of brief news headlines, with their sentiment values labelled. The overall probability is summed using the well-known Bayes’ theorem, which gives the name to the algorithm.A slight modification is proposed to this algorithm by calculating sentiment value for the field ‘engineering,’ which separates or calculates how a particular report is related to engineering. Based on the relevance to engineering (defined herewith using the dataset), a system is developed that prompts the head of an organization or any competent authorities with the report through an email

Keywords: text analysis, natural language processing (NLP), machine learning, text polarity, opinion mining, Na¨ıve Bayes’.

Abstract: This paper utilizes a technology that is Real-time monitoring of welding parameters using IoT to transmit the data from the working environment to the monitoring station. Welding operations include several hazards like Suffocation, fumes poisoning, and gas explosions which are dangerous to both the worker and others in the territory. Welding helmets include several sensors to detect anomalies in temperature and fumes exceeding the threshold range to prevent this warning alarm system from being utilized. To boost wellbeing, the breaking point switch is utilized to effectively decide if the specialists had worn their caps appropriately or not.

Keywords: RFID, Arduino, Wifi-technology, IoT, Monitoring, and control system.

Abstract: The project involves preventing We as humans only have many things in common. We all eat, sleep, use the restroom and, usually, we all wake up after going to sleep. The alarm clock is a ubiquitous fixture in the bedroom and smartphones serve that purpose for a ton of people. Sometimes the stock alarm clock app just doesn’t cut and you need something better, although we need some extra features get us up and get consistent on our work.

Keywords: Visualizer, Data Structure, Algorithm, Sorting

Abstract: Plants and crops that are afflicted by pests or diseases have an impact on agricultural productivity. Generally, farmers and professionals examine plants with their naked eyes in order to discover and identify illness. However, this procedure is time-consuming and frequently wrong. Data augmentation and picture pre-processing techniques are used to detect plant diseases, resulting in faster and more reliable findings. The purpose of this study is to present a novel method to the construction of a disease recognition model using CNN, which supports plant leaf image classification utilising convolutional networks and the Deep Learning algorithm. Advances in technology allow for the expansion and enhancement of plant protection practises, as well as development in the computer vision sector and using machine learning applications in the world of agriculture and farming, making it easier and more successful with a completely unique training method. All of the necessary steps and modules for implementing the plants disease recognition model are fully described throughout the paper, beginning with image collection to create a database, which will be evaluated by agricultural experts, and a deep learning algorithm framework to perform CNN training. Using the deep convolutional neural network that we will train, test, and validate, this technique paper might be a novel strategy to detecting and identifying plant illnesses. The created CNN model's development and innovation are shown in its simplicity; healthy leaves and backdrop pictures are consistent with previous CNN models, Using CNN, the model is able to discriminate between damaged and healthy leaves. Plants are the world's primary food source. Plant infections and illnesses are a significant hazard, and the most frequent method of diagnosing plant diseases is to examine the plant body for visible signs and growth [1]. Different research efforts intend to identify realistic techniques to plant protection and support our farmers as an alternative to the old time-consuming process. In recent years, technological advancements have spawned a slew of new ways to complement old procedures [2]. In picture classification challenges, deep learning approaches are particularly powerful and successful.

Keywords: Plant's Leaf Disease, CNN model (Deep Learning Algorithm)

Abstract: Pet shop management system (PSMS) will handle the animal’s record, pet shop management e- commerce web application. The users can view various pets up for sale and can add to cart and checkout. Admin can manage the orders and the pets. it has many functionalities such as admin panel for management of pets and categories and orders and cart functionalities.

Abstract: India is a hotbed of electricity theft especially in rural areas and in the middle and upper populations. Electricity theft is increasing every year in the homes and industries that affect the state of the country's economy. Power theft is usually done in two ways by jumping or hooking. To see it, a proposed system (current measurement and comparison) is proposed in which the distribution of family power is done indirectly from the distribution box to each house. It is currently being rated from time to time in the distributor box and sent to the server of each used house server GSM / GPRS module It is currently being rated from time to time in the distributor box and sent to the server of each used house serve GSM / GPRS module It is currently being rated from time to time in the distributor box and sent to the server of each used house server GSM / GPRS module. The aim of this project is to design a system to monitor energy consumption and to detect and eliminate theft of electricity from transmission lines and electricity meters. This work also focuses on transmitting theft information to the Electricity Board (EB) via IoT. As the network of devices connected as sensors has the ability to exchange real-time information via the Internet. Power is periodically measured in the distributor box and sent to each house server website using a basic IoT dashboard. During the installation of electricity meter user information is stored in a database using a friendly mobile application that includes address, location. The power will be continuously measured in the distribution box and individual meters. Power values will be uploaded to the server on a distributed and one-sided server. This power will be monitored through an IoT dashboard that will be a "Blynk IoT dashboard". In this project, we will look at the power delivered from an AC source to a user and the power consumption by that user. We consider only one user for this project and one distribution box. On the basis of an effective comparison between the current values from the distribution box and the electric meter in the house, if we find the difference between the current from the distribution box and the user meter then theft is detected.

Keywords: Electricity Theft, Monitoring System, Algorithm, Power Line Communication, Power Theft, IoT, NodeMCU.

Abstract: With the advancement in technology and communication, everything can be done with much ease. In fact, any information can be accessed from anywhere at any time as per our own convenience. Facility Booking is one of its kind that can be used to book/reserve the facilities of Jigme Namgyel Engineering College (JNEC) through the use of web-based application. Those services can be made available to both the staff and students as well as to the guest/outsiders. In the current scenario, the JNEC family are governed with certain rules to get access to different types of facilities. In order to book any facilities, one has to call a concerned authority/person to get approval for the same. Only when one gets the approval, then only it can be shared as an information all to avoid clashes. This indeed is time consuming as well as tedious for someone who are busy with academic schedule. However, with the proposed system, booking process can be made easier and simpler for all to avail services without much hurdles. The paper mainly discusses the design process and its methodology used for the development of a system.

Keywords: Facility, Booking/Reservation, System, Web, Application

Abstract: Blockchain is a system of Tran scripting information in a way that makes it difficult or impossible to change, hack, or cheat the system. To make sure the money which is being allocated for the purpose of betterment reaches its source without being malpractice is challenging, particularly from the perspective of a large number of gateway it has to pass through. Blockchain provides one potential mechanism for solving this problem. Blockchain technology allows one to make the process of transactions of funds transparent. It is a public ledger to which everyone has access but control of ledger does not lie with a central authority. One can get transparency, accountability and trust by using blockchain technology to perform digital transactions. A single platform for tracking that will track all the allocated fund need to be developed. The paper survey’s the uses of blockchain technology in real-life commercial applications and proposes a method that shall be used to allocate and track public funds using blockchain technology. Keyword: Blockchain, Authority, Fund Tracking, Blockchain applications, Transparency

Abstract: More than 70 Million US Adults face Sleep disorders like Insomnia, Sleep apnea, Restless legs syndrome, Narcolepsy, Sleep walking and many more... Our main goal is to make people feel relaxed while they go asleep or prepare for short naps. Having such short naps at work or taking proper sleep can help a person focus, breathe, stay calm, and create more head space, the conditions for a better night’s sleep by practicing meditation and mindfulness. The perfect guide to health and happiness. To counter the issue we came up with this idea and successfully developed an app which would provide users a peaceful Sleep using Nature Sounds, Stories and Meditations

Keywords: Sleep App, Meditation, Sleeping disorder, Better Sleep, Sleep Stories

Abstract: Technology is beneficial to a mankind. Internet has become one of the daily basic needs and everything is just a click away where everyone can work with much ease. Moreover, the website has become most popular platforms which can be used in businesses. It helped to increase the sales opportunities and perform numerous functions for the individual to bring more comfort and convenience in their way of living. Support System is one of its kind which can help to support every individual inside the college campus. This was mainly developed to address the problems being faced by both the staff and student related to repair and maintenance of facilities in the college campus. The population has been increasing every year with the increased intake in each programme and this has helped in making the situation worst. Though the complaints are raised and informed to the concerned person, they tend lose the track due to no systematic way to keep records. In the worst case, they forget about it and the problem remain unsolved for a longer time. This happens due to the manual process being practiced in current scenario. With the system, all the resident of the college can be able to complain or raise their issue from system thereby bypassing unnecessary procedure like in manual process. Moreover, the concerned person can see the issue through the system which can help them to keep track of issues being solved and raised. The paper presents the technical aspect involved during the design and development of the application.

Keywords: Website, Application, System, Laravel, Complaints.

Abstract: The application manages the Sales & Return Invoices likewise as Payments, Purchase &Purchase return Invoices as well as Payments, Customers information(Customer Bulk Import) Suppliers information (suppliers bulk import), Expense information, Tax &Tax Grouping, Units Categories, Item(items bulk import), Brands and Business required Reports and far more. Very responsive template used, advanced reports for review like sales payment report, Purchase payment report, Profit & Loss reports, Expense Report, Customer reports, Supplier report, Stock report. Business Analyzer app which is useful for the companies stores, where storeowner keeps the records of sales and purchase. The central automatic data processing system then keeps track of this data. the acquisition order may include a listing of items that require to be pulled for packaging and shipping. Mismanaged inventory means disappointed customers, too much cash busy in warehouses and slower sales. This project eliminates the paper work, human faults, manual delay and speed up process . it'll Business Analyzer will have the flexibility to trace sales and available inventory, tells a store owner when it is time to reorder and the way much to buy. Business Analyzer could be a windows application developed for Windows operating systems which focused within the area of internal control and generates the assorted required reports report. Index Terms: Inventory Management System, Business analyzer, Point Of sales, ultimate inventory sales, Invoices, warehouse management, stock management, GST Billing.

Abstract: Cancer is one of the deadliest diseases and of all the cancers breast cancer is the prime reason of cancer death among women as compared to men, today 1 in 8 women are suffering from breast cancer according to the American Cancer Society (Information collected from cancer.org website https://bit.ly/3uc13B3). As of now breast cancer accounts for 41 % of cancer deaths in women and this number is likely to increase by 2030, according to the world health organization (Link: https://bit.ly/3ioT8eh) in 2020 there were 2.3 million women diagnosed with breast cancer and the death toll was 685 ,000. Some of the factors that are contributing to this disease are usage of alcohol, exposure to cigarette smoke, no or minimal breastfeeding, lack of physical activity, family history of breast cancer, obesity, gene change and exposure to radiation. Through this research paper we are trying to investigate breast cancer triggering factors and applying data mining models to work on early detection based on patients’ medical history and predicting where this disease will reoccur or not with accurate results. Our data mining model uses Recursive feature Elimination method with cross validation, Feature Selection and stacked with Artificial Neural Network to detect breast cancer. Furthermore, we have also compared the Artificial neural network classifier with other Machine learning algorithms to find the accuracy. To add some statistics into our model we have used concepts like Specificity, Sensitivity, ROC-AOC Score, Kappa-Cohen score, Wilcoxon Signed Rank test and other statistical parameters to check and compare the Artificial Neural Network model with other Machine Learning Classifier Algorithms. In our model we have represented other Machine learning classifier algorithms as Logistic Regression, Decision tree, Random Forest classifier, K-Nearest Neighbor, Support Vector Machine, Gradient Boosting and Naive-Bayes. In this Paper we have Proposed a stacked model which can outperform other Machine Learning Classifier Algorithm by calculating various statistical parameters and by conducting non-parametric test to prove our hypothesis. In this research Paper the authors observed 98 percent accuracy by using Artificial Neural Network Based Approach along with Recursive Elimination Feature Selection combined model with Hyperparameter Tuning so that we observed sensitivity being 100 percent and specificity 99 percent also the ROC-AUC Score is 100 percent and the kappa score is 99 percent.

Keywords: Machine Learning, Deep Learning, Breast Cancer, Feature Selection

Abstract: In ‘Sustainable Development of Little Andaman - Vision Document’ NITI Aayog proposed a development plan for Little Andaman of Andaman and Nicobar Island group to build a greenfield coastal megacity as a free trade zone to compete with Hong Kong and Singapore. The plan needs 240 sq km from the east and west coast of the island that is 30% of the total area out of 680 sq km of the island comprises of 95% forest area most of that is evergreen forest [1][2]. Due to the closeness of the island to the Malacca Strait, an important world shipping route, also having 53683.10 Sq km Exclusive Economic Zone ( EEZ ) and potentiality for medical and natural tourism the vision is very much significant for blue wealth of the nation [3]. Among the different environmental impact one of them will be carbon stock losses as more than 2 million trees will be uprooted from the pristine forest. This study aims to forecast the carbon stock losses that will be helpful for environment impact assessment, NITIAayog yet not published. For the study area land use and land cover (LU/LC) data set was created from Bhuvan thematic satellite data. LU/LC multi-temporal satellite data from Resourcesat-2, LISS-III sensor of 2015-16 with a scale of 1:50,000 have been used in this study. Another data set for carbon stock of four forest type groups viz. Tropical Wet Evergreen, Tropical Semi Evergreen, Tropical Moist Deciduous and Littoral & Swamp forests in Andaman and Nicobar Island was prepared from India State of Forest Report (ISFR) 2019. From this two data set total carbon stock loss for the study area was calculated. QGIS a open source s/w was used for various data operations.

Keywords: Carbon Stock, Little Andaman, Land use and Land Cover, Bhuvan -Indian Geo-platform

Abstract: Standing in the early 21st century, the world has experienced various regression analysis such as Simple Linear regression, Multiple Linear regression, Logistic regression, Multiple Logistic regression etc. Multiple Logistic regression (MLR) or we can say multiple regression is one of them. A widely used statistical technique that allow predictions of systems with multiple explanatory(independent) variables. In this paper, we collected the final year placement data of a university. Our main objective is to select the explanatory variables for predicting the placement results. Data that has been used in this research were taken from Kaggle website based on the college placements data compiled over 2 years. Then the data will be analysed by using step by step multiple regression techniques. Here, we used train_test_split and 10_fold_cross_validation in our model. Reference: - https://www.kaggle.com/tejashvi14/engineering-placements-prediction

Keywords: Multiple Logistic Regression, Placement predictor, Classification, Dataset, Machine Learning.

Abstract: Success and failure are part of human life. Some of us may achieve our target and some may not. Those who could not achieve their desired carrier, usually opt for a suitable alternative to settle in life. It has also been noticed that many students desired to study in their dream institutions, but on failing to fulfil the necessary admission criterion had to switch to institutions that are not so desired but available to them. This paper consists of the development of a methodology based on Multiple Regression Analysis (MRA) to predict the percentage of people who could not achieve their desired carrier/ academic institution and had to opt for suitable alternatives available to them. Mentioned outcome(s) would simultaneously generate the percentage of the people who could achieve their target and thereby appeared to be successful in society. Several samples of data were collected which have been used to carry out the above investigation. The first 66% of samples were used for analysis, the 34% samples were reserved for testing the accuracy of the analysis. Then 50% of samples were used for analysis and 50% samples were reserved for testing the accuracy of the analysis.

Keywords: MLR(Multiple Linear Regression), Target-career-goal, partially achieved, fully achieved, failed to achieve, Cross-fold validation, Confusion Matrix etc.

Abstract: Stock market price data is huge and it changes every second. As it is a complex system in which people either make money or lose all their savings, hence it is important to understand the stock market. In the era of big and dynamic data, machine learning for predicting stock market prices and trends has become even more popular than ever. In this paper, we tried to predict the trend of the stock market. A model with a supervised machine learning algorithm is used to predict prices. We collected data of every company from the beginning from Yahoo finance and proposed comprehensive customization of RNN Machine Learning based models which are known as LSTM for predicting price trends of stock markets. The proposed solution is comprehensive as it includes pre-processing of the stock market dataset, utilization of multiple feature engineering techniques, combined with an RNN based system for stock market price trend prediction. In the yearly forecasting model, historical prices have been trained and achieved an accuracy of 84.0%. We conducted comprehensive evaluations on frequently used machine learning models and concluded that our proposed solution outperforms due to the comprehensive feature engineering that we built. Through our detailed design and evaluated prediction term lengths, feature engineering and data pre-processing methods, this work will help investors to invest in the stock by comparing stocks of different enterprises periodically, hence resulting in less risk. Also, it will contribute to the financial and technical domains of the stock analysis research community.

Keywords: Stock Market, Machine Learning, LSTM, RNN, Forecast, Feature Engineering

Abstract: Poverty and unequal distribution of wealth is a monumental issue that still awaits a proper solution. Poverty is prevalent all over the world. If we talk about the US, one of the most developed countries in the world, we again find poverty. The ones mostly subjected to poverty are the ethnic group of African Americans and the Native Americans. According to the 2020 census, in 10 states of U.S[1] where the majority of the African American population are found, 19.5 percent of African Americans living in the United States were living below poverty level, Native Americans have the highest poverty rate in the U.S, with one in four people living below the poverty level [2]. This Article would thus chronicle the cause behind the penury of the African Americans and the Native Americans. The percentage of people living in penury has been highlighted here. The origin of the extreme poverty levels depends upon their literacy, violent crimes, self-employed income, and community population. Data has been analyzed through Multiple Regression Analysis(MRA). The proposed model is tested on the “Communities and Crime Data Set” from the UCI Machine Learning Repository: which is available at https://archive.ics.uci.edu/ml/datasets/communities+and+crime . We evaluate the model using 50–50%, 66–34% train-test splits and 10-fold cross-validation.

Abstract: The thyroid gland produces thyroid hormones levothyroxine (abbreviated T4) and triiodothyronine (abbreviated T3). These hormones play an important role in protein synthesis, body temperature regulation, and total energy generation and regulation. Many disorders affect the thyroid gland, some of which are very frequent, such as hypothyroidism and hyperthyroidism. Thyroid disorders (TD) impact 42 million individuals in India, with hypothyroidism being the most common, affecting one in every ten adults. According to a study report published in the journal Lancet in February 20221 type 1 diabetes among people under the age of 25 accounted for at least 73.7% of the overall 16,300 diabetes fatalities in this age group in 2019. This is even though this illness is largely treatable. To reduce such TD, early detection of the disease is essential. A fast, accurate, and interpretable machine learning model is a research subject. Fewer features reduce the computational effort and improve interpretation. A 3-Stage hybrid feature selection approach and several classification models are evaluated on the TD dataset obtained from the kaggle.com website with 29 features and one outcome variable. Stage-1 uses a Genetic Algorithm and Logistic Regression Architecture for Feature Selection and selects 13 features well correlated with the class but not among themselves. Stage-2 utilizes the same Genetic Algorithm and Logistic Regression Architecture for Feature Selection to select 11 features. In Stage-3, Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), Extra Trees (ET), Random Forest (RF), and Gradient Boosting (GDB) are used with the 11 features to identify patients with or without TD. Data splitting, several metrics, and statistical tests are used, along with 10-fold cross-validation, to do a comparative analysis. LR, NB, SVM, ET, RF, and GDB demonstrate improvement across performance measures by reducing the number of features to 11. When compared to prior research, many performance metrics such as accuracy, sensitivity, specificity, f-measure, AUC values, and kappa statistics showed superior outcomes with fewer features. Finally, with 100% classification results, the proposed ensemble model demonstrated its worth. The output findings were compared to those of previous research on the same dataset, and the proposed model was determined to be the most successful across all performance dimensions. 1. https://www.downtoearth.org.in/news/health/1-in-10-indians-have-hypothyroidism-61693

Keywords: Thyroid Disorders, Machine Learning Classifiers, Feature Selection, Genetic Algorithm(GA), Extra Trees(ET), Gradient Boosting(GDB), Random Forest(RF)

Abstract: Common perception is that America as a global leader in technology, employment opportunities, and living standards. But the shadow is darker just beneath the light. United States is also the global leader when it comes to incarcerations. One in every three US adults have criminal record. Statistical numbers clearly suggest a racial imbalance in terms of arrests and victim counts. While colored people only make up 37% of US population, they account for 67% of prison population. Among various factors behind this uncomfortable truth, major ones are poverty, lack of education, unemployment, improper family planning etc. Apart from the mentioned reason the relationship between race and crime has been the subject of controversy in the developed nations like United States. Correlation of crime with racial disparity is prominent to the extent to have its influence on social movements and even legislation. As for the purpose of prediction of expected criminal activity in a particular locality along with total population, proportions of colored people also make significant contribution. The proposed model is tested on the “Communities and Crime Data Set” from the UCI Machine Learning Repository[3]

Abstract: Lending Club (LC) is a Peer-to-Peer lending company acting as a loan originator and a web platform between borrowers and investors. Marketplace lending relies on large-scale loan screening and information production by investors, a major deviation from the traditional banking paradigm. Theoretically, the participation of sophisticated investors in marketplace lending increases volumes and improves screening outcomes, but also creates adverse selection to less sophisticated investors. In this project we will analyze the factors in relation with lending of various types of loans and reach conclusions based upon that.

Keywords: Exploratory Data Analysis, Python, Jupyter, Numpy and Pandas

Abstract: Lending Club (LC) is a Peer-to-Peer lending company acting as a loan originator and a web platform between borrowers and investors. Marketplace lending relies on large-scale loan screening and information production by investors, a major deviation from the traditional banking paradigm. Theoretically, the participation of sophisticated investors in marketplace lending increases volumes and improves screening outcomes, but also creates adverse selection to less sophisticated investors. In this project we will analyze the factors in relation with lending of various types of loans and reach conclusions based upon that.

Keywords: Exploratory Data Analysis, Python, Jupyter, Numpy and Pandas

Abstract: In recent times, health and wellness of the one has taken the centre stage and many programs have implemented in order to cater the lifestyle diseases, virus infections and many other health disorders. The disease fighting and improvement of oneself in the form of diet in order to develop immunity as well as prolong or cure the diseases are some of many areas that provides a scope for going in detailed analysis and research using Artificial Intelligence (AI) based on the data sets of different food formulations as well as patients’ history. It is proposed to study and research the data in the field of disease prediction and healthcare for prediction and early detection of celiac diseases (CD) by applying the artificial intelligence techniques. Machine Learning (ML) is one of the AI techniques that find high relevance in the medicine and health care. CD, a rare malabsorption syndrome of childhood and was limited to individuals of European ancestry. However, it is now identified as a common condition that may be diagnosed at any age and affects many organ systems in around 1% of the population. Currently symptomatic cases are diagnosed by physicians; however, this is not being effective in asymptomatic cases and it may remain undiagnosed. AI Techniques including Machine Learning can help in overcoming the existing limitations of diagnosis of CD. This review provides an overall peek of current practices and research outcomes of the application of the ML techniques in the healthcare and medical practices. It further describes ML techniques in CD prediction and its relevance is summarized.

Keywords: Artificial Intelligence, celiac disease, disease prediction, machine learning

Abstract: The trends in education are ever-transforming and gaining importance with the acquisition of skills and applying the learnings to real-life situations. There is a dire to need to change from learning in the classroom to expanding horizons in learning. Technology dependency is the main foresight to rethink, innovate or visualize solutions to bring a positive change in the process. Active interest in offline has taken a U-turn in compelling to learn through electronic resources and become self-empowered, and digitally literate. Being technologically involved in learning is crucial for well-round development. Adaptability, Problem-solving, team collaboration, communication, time management, creativity, and innovation are basic skills expected in the current scenario. The inclusion of technology is a redesigned learning experience that not only should be a replica of offline class but a virtual class with digital experience for cognitive skill enhancement. Though online education was an introduction during the pandemic, gradual growth is seen exponentially not leaving education at a standstill. Inclusion of lectures by global experts, conferences and webinars, and other online material has been a need of the hour in the Covid times. This paper mainly focuses on the e-learning strategies, upskilling, and reliability of the online sources that helped during the pandemic for career development.

Keywords: Acquisition of skills, Digitally literate, Problem-solving, Team collaboration, Communication, Time management, Creativity, Innovation, and Cognitive skill enhancement

Abstract: The main part of information gathering is to find out what other people think. In case of movies, the movie reviews can provide an in-depth and detailed understanding of the movie and can help decide whether it is worth watching or not. However, with the growing amount of data in reviews, it is quite prudent to automate the process, saving a lot of time. Sentiment analysis is an important field of study in machine learning that practically deals with extracting useful information of subjects from the textual reviews. The sentiment analysis is closely related to Natural Language Processing (NLP) and text mining. It is used to determine the sentiments of the reviewer in regard to various topics or the overall polarity of the review. In case of movie reviews, along with giving a rating in numeric to a movie, they can give us information on the approval or the disapproval of a movie quantitatively. A collection of those information then gives us a comprehensive qualitative understanding on different facets of the movie. Since human language is complex, we face many kinds of challenges during opinion mining from movie reviews which might leads us to situations where a positive word has a negative connotation and vice versa.

Keywords: Machine Learning, Natural Language Processing, Text Mining, Opinion Mining, Analysis of Sentiments, Extracting Information.

Abstract: Those who have permanent disabilities due to accidents, paralysis, or old age are frequently dependent on others assistance when it comes to movement. This Embedded system is created to assist individuals, giving them access to remote health services via a health monitoring system and increases their independence because their health is regularly recorded and monitored by the sensors without any effort. Because disabled patients cannot afford to travel, smart healthcare systems assist them in gaining access to healthcare. A feasible solution to monitor the patient’s health is by developing a health monitoring system with additional features since it is adequate for a wider range of audiences and it doesn't require tons of maintenance unlike the wearable systems. This project aims to develop a smart sensing embedded system for wheelchair by integrating sensors into its structure and developing an app that provides data visualization of all the monitored data along with automatic alerts when an anomaly is detected. With Internet of Things, sensors detect heart rate and sp02 levels, and embedded systems process them before sending them to the cloud that kicks off a trigger in case of any abnormalities. Depending on the user's preference, the trigger can be sent via SMS or e-mail.

Keywords: Healthcare, Embedded System, Sensors, Internet of Things, Smart assistance

Abstract: In this study, Machine Learning techniques are used to predict the winning team in the English Premier League (EPL). The goal is to predict a football match's full-time result (FTR) accurately, which determines the winning team. For training the data, we use algorithms like Support Vector Machines, XGBoost, and Logistic Regression, and the one with the highest and best accuracy is used to forecast the winning team. The data for previous seasons is obtained from [6].

Keywords: Football, Soccer Analytics, Prediction, Machine Learning, Support Vector Machine (SVM), XGBoost.

Abstract: To the climate change mitigation three blue carbon ecosystems (BCEs)- mangroves, sea grasses, meadows and salt marshes plays the important role by sequestrating blue carbon in their ecosystems. Mangroves, tidal marshes and seagrasses store more carbon per unit area than terrestrial forest such as tundra, taigas, deciduous forestland tropical rainforest. India is having nine coastal states and four coastal union territories, 7516.6 km coastline and total 2,305,143 sq km exclusive economic zone (EEZ) does not belong to the higher annual carbon sequestration potential countries. As total blue carbon wealth of India are generating from 4949 Sq km of mangroves , 193.09 Sq km of sea grasses and 301.5 Sq km of salt marshes but that is not equally distributed along the states and UTs as per their size of EEZs. This paper aims to present the status of different blue carbon ecosystem areas and their annual blue carbon sequestration potential states/UTs wise. Also we have shown here a management framework for the blue carbon wealth assessment and redistribution among the coastal states and UTs in India.

Keywords: Blue Carbon, Blue carbon wealth, Carbon Sequestration, Blue Carbon ecosystems (BCEs), Social cost of carbon (SCC), EEZ.

Abstract: In the international business sphere, English has become the lingua-franca of the business world irrespective of geographical, social, political, or religious differences. With jobs becoming more and more global, English as a global language has gained importance as a medium of communication, both at the international and intra-national levels. In the professional world, communication skills are very crucial. Being proficient in English means being able to communicate clearly and effectively. Enhanced communication skills in English can help attain better/ advanced education and consequently aid in availing better job opportunities in the future. In this paper, we explore two crucial aspects of the assimilation experience of colored Afro-Americans. It explores the determinants of their English language (speaking) fluency and the key role such skills play in their occupational success. We find that in a particular population enhanced level of fluency in English results in brighter job prospects. Advance education and better jobs help in keeping the population largely away from involvement in unlawful activities. Data has been analyzed through Multiple Regression Analysis (MRA). The proposed model is tested on the “Communities and Crime Data Set” from the UCI Machine Learning Repository: which is available at https://archive.ics.uci.edu/ml/datasets/communities+and+crime.

Abstract: This paper is based on an in-depth analysis of a gaming system and how it is beneficial to the young generation for solving different problems and uplifting Indian ethos. The system is a game application that utilizes the concept of the periodic table of chemistry. Keeping the interests of children in mind, we have designed this system that is based on the concept of the periodic table of chemistry. Each level represents an element of the periodic table and the properties of the elements are utilized to generate a solution for a given problem. The game has four steps: (i) Storytelling that emphasizes Indian ethos, (ii) Play and complete a specific level, (iii) Attempt and pass the MCQ. Thus, the objective of our research work is to enable the youth to gain knowledge in the specific field by playing this educational game.

Keywords: Game, Knowledge, Storytelling, MCQ, Ethos, Chemistry Periodic table.

Abstract: This paper offers a detailed explanation of a system that uses sentiment analysis and machine learning algorithms to classify and recommend products on Amazon. Using the idea of Machine Learning, we developed a system that can be used by many e-commerce sites for better product recommendations. This system employs a machine learning model in which similar and superior products are offered to the customers in order of best to worst based on the product utilized in the past. The computer will compile a shortlist of all relevant items or products based on user-generated product reviews that meet the user's criteria, taking into account the product's quality and rating. The approach we employed was to create a system model that would analyze customer reviews for various products in the same category and then use Natural Language Processing to arrive at a conclusion where the system (model) would be able to assess whether the review is positive or negative. We've also used the ratings offered on various items to create a technique to combine ratings and reviews to improve the accuracy of the system (model). We employed the Collaborative Algorithm to improve the accuracy of product recommendations. During the creation of the system, we used the Amazon e-commerce site and its products to simulate a real-world implementation scenario (model). Our system uses cosine similarity to find the similarities between items on basis of the multiple user’s ratings and form a matrix which helps to recommend items to other users.

Keywords: Review & Ratings, Machine Learning, Natural Language Processing, Collaborative Algorithm, Recommendation System, Accuracy.

Abstract: Maxima is a computer algebra system software which is Free Open Source Software (FOSS). In this paper, we solved statistics problems on correlation coefficient and Spearmn’s rank correlation using maxima where speed matters for numerical computation. With easy and simple commands it reduces the time taken for tedious calculations of lengthy problems and helps in obtaining quick solutions for similar statistical problems. Overall the maxima software is a friendly software which is easily accessible. In future, it will be definitely a stepping stone for students, teachers and for researchers in the field of statistics. We solved several examples to exploit the capability of maxima by its many commands for computations in statistics. Key words: Correlation coefficient, Spearman’s rank correlation coefficient, Maxima, FOSS.

Abstract: Artificial Intelligence is in every sphere in the globe now. Over many years, the environmental studies influences on the human mental, physical, social growth and development which focused on different factors such as family background, modernity, living style, nutrition, healthy food habits, socio economic status, also the environment such as temperature, climate etc. This kind of self created man-made traditional structure plays a key role that affect the human growth and development which in turn reflect the timing of sexual maturation, physical and mental imbalance and also cause of different diseases. The objective of the current study is to clearly examine the environmental influences on human growth and development in different aspects and stages of life from birth state to the end state. In this paper, we used artificial intelligence approach for the comparative analysis of human growth and development based on different real time environmental influential factors. Artificial Intelligence approach can be used as a tool for a new revolution in the field of medical science and education for human growth and development in this century. Keywords- Artificial Intelligence, Growth, Human Development, Random Effect

Abstract: The paper focused on online product reselling system. This system overcomes problem of searching pre-owned products by helping users to get their desired in terms of functions: products and customers. Online Products reselling application was devised to offer huge variety to customers, case of selling and buying. So, the customer's data is a variable in terms of payment or updating: customer id, name, address and phone number. For the product, it gives a large view of current events to customers, regarding different details of the products (tribal): name of products, model of products, year of manufacturing, product id calculate price (on market Price) of products, mileage and registration number of products. Furthermore, this application was designed to display detailed information about the products an seller can update or delete products details. The waterfall life cycle model was used to undertake the research and the development of a Android base online application that will aim for on product, and its details at a single place. This application is basically organized in bipartite customers in a specific order. The up grading option is used for the application, only by the line reselling of the products that draw out the middle man.

Keywords: Android, Request Products, Tracking, E-mail;

Abstract: The project aims to provide the facility to the small scale organization who has the leave management application in the form of ESS it does not help the project coordinators that much, they need to manage their own time sheet to track the leaves of the teammates in order to provide the deadline to the customer.This application allow team member to announce their leave Management is the most important aspect of a any sector today, so this project demonstrates the design and implementation of working module of office. It makes it easy to manage the groups and also provides sophistication to the user. It enriched the management of the office. The dividing of group and allocating the roles, dividing work, is done through office-work management software that is accessible on smartphones. We need to consider a useful method to effectively manage your projects by using an office-manager system. A properly managed group can bring significant benefits to your projects. As a result, you can ensure that your projects and office is efficiently managed and profitable in the long term.

Abstract: With the increasing population, the number of two-wheeler riders has increased rapidly. This causes an increase in accidents rates. Riders, being careless by not wearing helmets might lead to more health damage. Human involvement in monitoring the vehicles may be less effective and hard to catch every rider with no helmet, thus monitoring all these manually may be difficult if we consider the huge number of riders. Observers may not be able to capture everyone with no helmet. Thus to ensure that every single rider is monitored properly a Computerized Automatic Helmet Detection System is implemented. The system is trained with a dataset for better accuracy and prediction of results. The system will detect the rider with no helmet and will extract the number plate of the two-wheeler. The system uses GUI and various Python libraries such as sklearn, NumPy, TensorFlow, Keras, etc, also algorithms such as Yolo V3(You Look Only Once) and SSD (Single Shot Detector) has been used for object detection.

Keywords: Helmet, Number plate, Detection, Python Libraries, Machine Learning, Yolo V3, SSD.

Abstract: Currently, agriculture contributes to 20.19% of India's total GDP, yet this sector is most looked down upon when it comes to advancements, technologies, and providing benefits. As India is still a developing country, farming is done with traditional methods which are dependent upon the soil, climate, land condition, water facility, fertilizers, etc. It comes with its pitfalls like degrading soil quality, crop destruction due to unforeseen climatic conditions, and not enough/proper water supply. To prevail over these pitfalls of traditional farming, one such technique comes forward called Aquaponics. The term Aquaponics is coined from two words - Aquaculture (meaning raising aquatic animals such as fish, crayfish, snails, or prawns in tanks) + Hydroponics (cultivating plants crops in water was with no requirement of soil). Aquaponics is, therefore, a food production system that conjoins these two systems whereby the nutrient-rich aquaculture water bolsters the hydroponically grown plants using nitrifying bacteria to convert ammonia into nitrates. Thus, this technique will provide us with crops as well as fish and is soil-less and uses less water, and less space. In this era of technology, this system can make use of IoT (Internet of Things) for its management and control with the help of various sensors to keep in check the different parameters of the system like PTT level, water level, temperature, etc.

Keywords: Aquaponics, Aquaculture, Hydroponics, IoT

Abstract: With rapidly growing technology social media has now become a part of everyone’s daily life. From sharing the data like our personal information, text and many other things. We have also started sharing news articles and related pictures on social media platforms, different advertisements, marketing techniques, surveys, jokes, videos in the Entertainment domain. It provides a platform for users to connect with their family, friends, and other people globally. The information shared in social networks spread so fast, that makes it very comfortable for attackers to get access to the user’s information. While enjoying the content available on Social Media, secrecy and privacy of Social media need to be maintained from various possible areas. There are various security and privacy issues when a user shares his information like uploading personal data such as photos, videos, and audio. The information that is to be kept confidential, must be made private. To resolve these problems, we are writing this paper which reflects a thorough review of different security and privacy threats and the possible solutions that can be proved beneficial in providing full-fledged security to social network users. In addition to this, we have also discussed some other defensive approaches to Social media security.

Abstract: Data Security is a challenging issue of data communications today that touches many areas including secure communication channels, strong data encryption technique and trusted third party to maintain the database. The rapid development in information technology, the secure transmission of confidential data herewith gets a great deal of attention. The conventional methods of encryption can only maintain the data security. The information could be accessed by the unauthorized user for malicious purpose. Therefore, it is necessary to apply effective encryption/ decryption methods to enhance data security. This paper describes a new method of encrypting original data parts with different strong cryptographic encryption algorithms and LSB Image Steganography to hide the decryption keys in an image. This encryption technique enhances the complexity in encryption algorithm at large extent. This paper becomes very special in few aspects, all of them are explained in a detailed way in the chapters.

Keywords: Cryptographic, Data Security, Decryption, Decryption Keys, Encryption, Information Technology, LSB Image Steganography

Abstract: The government is unable to estimate the socio-economic status of a remote area and also they are unable to help them. Because the government only has their satellite image as a record and they can only see that area through a map but through this image they cannot get status about that area. So, considering this satellite image of an area, there is a profound need to detect the status of the remote area. In this project, we propose an advanced framework to identify socio-economic status of an area through satellite image. We are considering some major factors or attributes like water supply, rooftops and agriculture landfill and we are going to train some datasets through CNN technique then input satellite image is compare with train datasets and if there is presence of this factors in input image then we classify status of the area as poor, rich or medium.

Keywords: Machine Learning, Malnutrition, CNN, Poverty Prediction

Abstract: Text-summarization is one of the most challenging applications in the field of NLP where appropriate analysis is needed of given input text. Result of summarized text always may not identify by optimal functions, rather a better summarized result could be found by measuring sentence similarities. The current sentence similarity measuring methods only find out the similarity between words and sentences. There are two major problems to identify similarities between sentences. These problems were never addressed by previous strategies provided the ultimate meaning of the sentence and added the word order, approximately. In this project, main objective is to try to measure sentence similarities, which will help to summarize text of any language, but we considered English here. We have seen several text summarizing software, but the one we intend to develop will comprise of two factors summarization and translation. As English is one of the most popular languages around the globe, it is difficult for a lot of people to read long documents and lengthy texts hence summarization comes in to give a brief informative summary of the language. Not just that, we are also focusing on translation of the output into the simplest form of Hindi language.

Keywords: Text Summarizer, Translator, BERT, BART

Abstract: Ever since the internet was introduced fake news had also grab their hand around it, if we think carefully fake news being around since the old times but now only internet has expanded up the process.in the old times it took days for news to travel across lands but with the help of internet it happens within seconds we can share anything instantly. Social media also plays an important role in this it is a wide spreading and is a matter of serious concern due to ability to cause a lot of social and national damage. The credibility of social media networks is also at stack where the spreading of fake information is prevalent. Our paper review is tackling this by using machine learning and artificial intelligence to detect if the news is fake or not, we used more than 5 algorithms to get maximum accuracy towards our results, algorithms we used are decision tree, random forest, support vector machine (svm), naive bayes and KNN (k-nearest neighbours) which then show the credibility of news is later shown in percentage

Keywords: Support Vector Machine (SVM), Artificial Intelligence, Naive Based Classifier, Fuzzy Inference, Prediction, Recommendation, Machine Learning, Fuzzy Logic.

Abstract: Sharing not only means the involvement of cooperate providers, it can also be a peer-to-peer(P2P) sharing of people who match private providers and users. One such example of this is carpooling. The sharing of an automobile ride is known as carpooling. Quite often we have seen the markable and considerable research on various types of pooling techniques. Recent years have seen considerable research on why people use these sharing services. As is the trend worldwide, India is undergoing rapid urbanization; and using a private car as a transportation system has become very common in industrialized countries. The costs of increasing dependence of people on cars and other transport is becoming very expensive, building new roads and their maintenance, high level of energy consumption in addition to the economic and environmental costs, pollution, traffic accidents and social inequities that arises when the poor are unable to access the transportation services at an affordable price. To overcome these issues many strategies have been introduced. We have also created an android car-pooling application (Traveling Buddy) to tackle this problem. In this application we have also implemented some of the new features which would help the users for convenient journeys. Some of the feature like providing the real time images of the car to check the car condition, an efficient way to provide communication between the rider and passengers, Even if one does not owns a car , he/she can still post the trip’s details and a person who is willing to share the trip can communicate with him/her via calling and chat feature, Post initiator have to confirm the passenger of the trip before the actual day of trip after which he/she can’t cancel any passenger’s request. Carpooling would reduce the number of cars on streets hence providing worldwide environmental, economic and social benefits. Information and communication technology can aid in the matching of drivers and passengers [3].

Abstract: Power consumption has emerged as a primary design constraint for today VLSI integrated circuits (ICs). AS per reducing Technology, mostly Nanometre technology regime, leakage power has become a major component of total power. Full adder is the heart of any central processing unit that is a core component employed in all the processors. Full adder is the basic functional unit of an ALU. The power consumption of a processor is lowered by lowering the power consumption of an ALU. In this paper we introduced low power consume & Propagation Delay of one-bit full adders by using 10T. The analysis of the developed full adder design is done at room temperature CMOS 45nm,90nm and 180nm technologies using Cadence virtuoso tool. The result shows the comparison between different CMOS technologies in 45nm,90nm and180nm using Cadence virtuoso tool on the design in regards of power dissipation, propagation delay and power delay product. The simulation has been carried out on a Cadence environment virtuoso tool using a 45nm,90nm,180nm Technology.

Keywords: VLSI, CMOS, Full adder, Power, Delay, Transmission gate

Abstract: With the digital revolution around the world more and more number of users are now connecting to the internet, using digital platforms and preferring online or digital banking instead of using cash while making payments. But rise of online transaction have also given opportunity to hackers and fraudsters to fool people and harm them financially. Phishing attacks are type of cyber-crime in which scammers usually send malicious and spam emails, messages and SMS. Some people fall prey to these messages and they contact on the number mentioned or click on the link given in message by this way scammers loot them. The proposed Phishing Attacks Detection System uses Machine Learning Algorithms to identify malicious messages and alert the user. Proposed system uses Naive Bayes algorithm for classification of input data. This will reduce the chances of possible Phishing Attack, identity theft and user will be safe from the financial loss.

Keywords: Phishing Attacks, SMS, E-mail, Machine Learning, Naïve Bayes

Abstract: Roads are a major means of transportation and travelling hence it needs to be in proper conditions to reduce fatalities due to road accidents, decrease transportation delays due to surprising events, etc. The problem that we are trying to solve is to automate the analysis of road conditions using computer and cameras to generate data for maintenance and development of roads utilizing parameters such as potholes, cracks etc. The approach we are taking is to use still images of the roads to be surveyed or analyzed and then use image processing and computer vision for the required data. The data generated by the analysis and processing can then be used in various applications for development and maintenance of roads. This method of automating the process of surveying will drastically reduce the efforts, cost and time that was previously required manually.

Abstract: In the early days, if the user wanted to buy a piece of furniture without going to the store, it was possible, but not possible to check how the object actually looks in the structure of the apartment. Now, in our proposed system, it is possible for the user to buy the piece of furniture sitting at home without going to the stores. The main goal of "AR DEZINER" is to develop an Android application for virtual testing of various furniture using a mobile phone that supports AR camera. The app eliminates the human effort of physically visiting the furniture store, which is a very time-consuming activity. Also, it could be easier to use this technique when shopping online as an option for the user to try the furniture in their room that they want to buy and allow the user to visualize the space. what it will look like after furniture is placed on it. The user can try multiple combinations virtually without having to physically move the furniture. Our motivation here is to increase time efficiency and improve accessibility of furniture assembly by creating furniture augmented reality app. This system helps the customer see the object of the furniture. virtually in a real environment before purchasing the object. Thanks to this system, the customer knows what the structure of his house would look like after purchasing the furniture. This system would allow the user to try out multiple combinations of objects with virtually no physical movement of the furniture. These help the buyer determine how the furniture will fit into the structure of the home.

Keywords: Augmented Reality, Flutter, Android Studio, AR core

Abstract: Nowadays, almost every educational institution wants to boost its education and hence, productivity and quality education amongst its students. To achieve this goal, an institution need to have the necessary framework of centralized and secure educational services and resources. Rather than depending upon various available tools that are available in market, which are at times not secure or sometimes have more down time and are not privacy friendly. Due to unavailability of a single platform to solve these issues, we are left with no other option than to be dependent on these third part apps. To solve these array of issues, we have introduced a web application that can be a booster in an institution’s overall productivity and management. This web application have the major educational services covered in it that are centralized to the college or institution. It helps to maintain privacy and security. Integrates various services and provides a user friendly dashboard for keeping up with the studies and notifications. Also, students will be able to know the technological roadmaps of important domains that one must know beforehand. With the help of this application, student will be well equipped with all the necessary resources and pathways to explore and the teachers can effectively communicate and share knowledge with them in a more comfortable way

Abstract: Using the Appsheet application; a cloud based software provided by google, we are building up a mobile application using google sheets as a database. The sole purpose of this application is to maintain the records of sales, product, and its delivery details. The application allows us to make it easy to build multiple views of data in the table. It also allows UX designing. Further to add on, this application is lite in nature, allowing the developer and the user to ease their work. It needs a computer with internet connection and nothing more.

Keywords: mobile application, APK, cloud software, record management, no-code.

Abstract: In today’s generation, people write blogs, articles, record videos, audios, and upload it across the Internet for people across the globe to view. One of the benefits of this advancements is that now people can share their opinions directly and instantly with the artist. This large amount of feedback can be of great significance, when analyzed with necessary expertise and tools. This field is referred to as Sentiment Analysis which aims at identifying the sentiment of the text and also whether the writer has a positive opinion or a negative one. Categorization of these responses can help an artist to get insight of public review in order to take necessary steps in near future. In this paper we intend to use a lexicon based approach for sentiment analysis of comments on YouTube videos.

Keywords: Sentiment Analysis, Lexicon, YouTube and SentiWordNet

Abstract: The Paper Presents integrated health care web portal an emerging technology that provides the patients the all necessary healthcare services through one portal with 24 hours access. The challenge we faced so far is maintaining the confidentiality of patient’s health data, the integrity and correctness of diagnosis results. The e-health Portal can do many backend medical services efficiently. A major challenge in designing such a system is to meet critical security requirements, such as the confidentiality of patient data, the integrity of diagnosis results, and the availability of healthcare services. In this thesis I address the issue from the access control perspective. The address authentication for real time services provided by remote service providers.

Keywords: HealthCare, E-HealthCare, Doctors, Online.

Abstract: Mobile performs the important role in today’s lifestyle of human being. All the convenient things are done through the mobile applications and the development of different application has been increasing day by day. In existing system, a tourist visits famous city to know more about the place and hires a guide and tourist don’t know best hotel, restaurant and famous attraction of the preferred city. The proposed architecture of “Virtual Tourist Guide” system based on Web app which is able to provide tourism related information to the mobile users conveniently. By providing a geographic based information system, anyone can understand how to reach their preferred location like restaurants, hotels and other attractive places Mobile performs the important role in today’s lifestyle of human being. All the convenient things are done through the mobile applications and the development of different application has been increasing day by day. In such applications, location dependent systems have been detected as an important application.

Keywords: Web app, Places, Travel, Tourist guide.

Abstract: The main theme of this proposal was to develop a smart appointment booking system, that provides patients or any user an easy way of booking a doctor’s appointment online in health care. The purpose of doctor’s appointment system is to automate the existing manual system by the help of computerized equipment, so that their valuable data/information can be stored for a longer period with easy accessing and manipulation of the same. The required software and hardware are easily available and easy to work with. This system overcomes problem of searching doctors by helping users to get doctor according to their need, and other related health care details at a single place. Also solves issue of managing and booking appointments according to user’s choice or demands. This system provides the power of direct interaction between doctors of customer choice when required for your small problems. This application is basically organized in a bipartite in terms of functions: doctor can get the patients data to understand the history and users(patients) can get registered in few seconds at comfort of home. Online doctor’s appointment application was devised to offer huge variety in health care to users, case of registering and get verified doctor, view medical progress and all the data get stored in database.

Keywords: Online appointment system, Waterfall development methodology, Unified Modelling Language.

Abstract: The field of psychological treatment and counselling has grown greatly over time, and various platforms for providing mental health services have emerged. Professionals' usage of virtual therapy for offering mental support to individuals has expanded dramatically over the internet via emails, voice chat, audio platforms, or chat groups. Despite the fact that the world was exposed to specific triggers as a result of the unusual COVID-19 epidemic, therapeutic applications have helped ease mental health issues and maximise advantages to society's psychological well-being. However, it is critical to assess its effectiveness in really assisting people during a crisis. The purpose of this study is to (a) evaluate online counselling services and their effectiveness in providing the necessary emotional support during the pandemic, and (b) assess the effectiveness of online counselling services in providing the necessary emotional support during the pandemic. Counseling psychology is a sub-discipline of psychology that focuses on helping people. Attention on intact personalities; focus on human strengths; emphasis on relatively quick interventions; emphasis on person–environment interactions; and emphasis on education, career development, and environments are the five unifying characteristics that define the specialisation. Counseling psychology is a doctoral-level field that firmly supports the scientist-practitioner model and places a major emphasis on human variety. Counseling psychologists' typical duties and functions are described. Key research issues and themes are presented in terms of scientific inquiry: important research results and theories in counselling and psychotherapy; multicultural elements in counselling interventions; career development and intervention; research and theory on training in both practise and education

Abstract: There are two different cooling systems used in computer systems. One specifically used to maintain the temperature of processor and the second for maintaining the overall temperature and ventilation of computer system. To cool the processor variety of cooling systems are available in the market, but for ventilation and overall temperature of computer system only basic cooling is available in the market. So integrating the ventilation system with temperature sensors to regulate the speed of exhaust and intake fan can make computer systems more reliable with increased cooling & power efficiency.

Keywords: Temperature, Cooling, Ventilation, Sensor

Abstract: Heart disease is one of the most critical human diseases in the world and affects human life very badly. In heart disease, the heart is unable to push the required amount of blood to other parts of the body. The diagnosis of heart disease through traditional medical history has been considered as not reliable in many aspects. Accurate and on time diagnosis of heart disease is important for heart failure prevention and treatment. So, there is a need of reliable, accurate and feasible system to diagnose such diseases in time for proper treatment. Correct diagnosis and treatment at an early stage can save people from heart disease and its consequences. Machine learning is one of the fast-growing aspects in current world. Machine learning is helpful in detection and diagnosis of various heart disease. The heart disease consists of set of range of disorders affecting the heart. It includes blood vessels problem such as irregular heart beat issues, weak heart muscles, cardio vascular disease and coronary artery disease. It reduces the blood flow through the heart leading to the heart attack. For this kind of work large and authenticated observations related to patient’s health are required. This project proposes a prediction model to predict whether patient have a heart disease or not by using entered symptoms and to give an awareness on heart disease and some useful tips on heart disease. The proposed work predicts the chances of heart disease and classifies patient’s risk level by implementing K-Nearest Neighbour machine learning algorithm. These machine learning algorithms predicts the chances of heart failure with high accuracy.

Keywords: Heart Disease, Machine Learning, K-Nearest Neighbour

Abstract: As the internet is becoming more accessible and convenient, larger numbers of people and businesses are shifting towards digital transactions. Therefore, it’s not surprising that newer forms of digital payment systems and cryptocurrencies are rapidly being developed. When compared no other method comes even close to the giant that is cryptocurrency. Currently Cryptocurrencies like Bitcoin and Ethereum are among the most popular forms of digital payments. Cryptocurrencies could be popularized as a viable option for digital currency. Despite a huge demanding market, very few well developed platforms for exchange of cryptocurrencies are available. And there are a bunch of challenges are standing up in a growing and developing technology. The study suggests that all these obstacles can be eliminated and serving technology can be improved. this well developed platform will enhances the transaction efficiency, safety and security of cryptocurrencies.

Keywords: Waterfall development methodology.

Abstract: In recent years, the social media system has become one of the most popular online apps and has a large number of users. Nowadays, social networking sites are becoming more and more popular but also the need for new generations. "Lynked – An Educational Community" is another social networking site. This web application will enable the institution to build its own student community so that all activities can be run digitally in the event of this epidemic situation. Here, students can retain their profiles, become part of different communities, participate in activities, etc. It will also be beneficial when sending any official announcement of the various extra-curricular activities.

Keywords: MERN Technology, Lynked, Education, Community building, Social Networking

Abstract: Face anti-spoofing is widely used as a biometric approach. The face anti-spoofing systems are increasing due to their advantage of being convenient and contactless compared with other authentication systems. Unfortunately, the face anti-spoofing system is the most vulnerable to spoofing attacks. Hence, the need for the development of countermeasures against such presentation attacks. This paper provides detailed reviews of the different techniques available in face anti-spoofing systems. We give an outline of the research that has been accomplished in the field of face anti-spoofing.

Keywords: Face anti-spoofing, Face recognition, Presentation attack, Convolution neural network, Texture analysis, Information Security.

Abstract: Credit Card Fraud detection is a challenging task for researchers as fraudsters are innovative, quick-moving individuals. The credit card fraud detection system is challenging as the dataset provided for fraud detection is very imbalanced. In today’s economy, credit card (CC) plays a major role. It is an inevitable part of a household, business global business. While using CCs can of er huge advantages if used cautiously and safely, significant credit financial damage can be incurred by fraudulent activity. Several methods to deal with the rising credit card fraud (CCF) have been suggested. In this paper, an ensemble learningbased an intelligent approach for detecting fraud in credit card transactions using XGBoost classifier is used to detect credit card fraud, and it is a more regularized form of Gradient Boosting. XGBoost uses advanced regularization (L1 and L2), which increases model simplification abilities. Furthermore, XGBoost has an inherent ability to handle missing values. When XGBoost encounters node at lost value, it tries to split left right hands learn all ways to the highest loss.

Keywords: component, formatting, style, styling, insert

Abstract: There is a general tendency that effective police force has a significant protective effect on violent crimes. The effect of police on crime operates through both a deterrence and an incapacitation way.The deterrence theory is based on the fact that an increase in capacity of police force enhances a typical offender’s chance of being caught and thereby decreases crime particularly those which are violent in nature.The police departments actively focus their resources on the incapacitation of individuals posing the greatest risk to society, which make the incapacitation channel also an important factor. In this perspective adequate human resources (deployed police personnel) play a vital role. This article goes on to explore the relationship between population of a community of coloured (Afro-American) people, number police staff employed and violent crime occurrences in particular. The findings from this paper suggest that numbers of police recruited/ employed for maintaining law and order of a community/ area with coloured (Afro-American) inhabitation depend on population of that community/area and number of prevalent violent crimes. Our findings suggest that higher numbers of police not only reduce crime rates but also increase the share of crime, and in particular violent crime. This data will be analyzed using multiple linear regression in machine learning method using python programming language.

Keywords: Forecast; data Science, data analysis, Regression analyses; Stepwise multiple regression

Abstract: Many computer vision tasks have shown that deep convolutional neural networks perform exceptionally well. However, in order to avoid overfitting, these networks rely extensively on huge amounts of data. Many disciplines, such as medical image analysis, lack access to massive data sets. Data augmentation approaches enable applications with limited datasets to achieve higher accuracy. The process of creating samples by transforming training data is known as data augmentation, with the goal of increasing classifier accuracy and resilience. Geometric transformations, colour space augmentations, kernel filters, random erasing, feature space augmentation, adversarial training, generative adversarial networks, neural style transfer, and meta-learning are some of the image augmentation technologies explored in this review. Data Augmentation will help readers learn how to improve the performance of their models and expand their limited datasets in order to take advantage of big data.

Keywords: Machine learning, Deep learning, Data augmentation, GAN, Medical imaging.

Abstract: A mobile operating system, also called a mobile OS, is an operating system that is specifically designed to run on mobile devices such as mobile phones, smartphones, PDAs, tablet computers and other handheld devices. Android is an open source and Linux-based Operating System. Android was developed by the Open Handset Alliance, led by Google, and other companies. Android Studio is the IDE only used for android application development, contains design tools, flexible build system, and emulator. Android studio versions are available for windows, linux, and Mac Os, etc.

Keywords: Android operating system, android studio, IDE

Abstract: Artificial Intelligence (AI) has revolutionized healthcare, offering advanced solutions for diagnostics, treatment, and patient care. However, centralized AI systems face significant challenges, including data privacy concerns, high energy consumption, and a substantial carbon footprint. Federated learning (FL) presents a promising alternative, enabling collaborative model training while ensuring data privacy and reducing environmental impact. This paper explores the role of FL in addressing these challenges, its potential applications in healthcare, and future directions for sustainable and secure AI development.

Keywords: Federated learning, Deep Learning, Artificial Intelligence, Secure aggregation, Differential privacy

Abstract: AI has emerged as a promising tool in combating the COVID-19 pandemic, leading to widespread efforts to harness its capabilities. This paper explores AI’s role in six key areas: early warnings and alerts, tracking and prediction, data dashboards, diagnosis and prognosis, treatments and cures, and social control. While AI holds potential, its impact has been limited due to challenges such as data scarcity and overwhelming volumes of unstructured information. Addressing these issues requires a delicate balance between data privacy and public health, along with robust human-AI collaboration. Though these obstacles may not be fully resolved in time to significantly influence the current pandemic, systematic collection of diagnostic data remains crucial for saving lives, refining AI models, and mitigating economic consequences.