ICGEMT 2024 Proceeding

9 Oct

International Conference on Global Engineering & Management Trends

 

Web Page Recommendation Using KNN Model and Genetic Algorithm

Authors- Phd Scholar Sumit Sharma, Dr. Pritaj Yadav Associate Professor

Abstract- – Recommender systems are very helpful on the internet that suggest things personalized just for you. They’re great because they make it easier to find what you want without being overwhelmed by too much information. This paper is all about recommending web pages by looking at how people use websites and the content on those pages. They used a smart model called K-nearest neighbors to figure out which pages you might like based on what other people with similar interests have viewed. Then, they made these suggestions even better by using a clever algorithm called the elephant herd optimization. This work tested method on real website data to see if it actually works well. Since people’s internet habits are always changing, it’s important to have a recommendation system that can keep up. The results show that approach, called Elephant Herd-based Web page Recommendation (EHWPP), really makes things work better. In simpler terms, it’s like having a smarter system that helps you find the web pages visitor want in a way that suits their interests.

 

Credit Card Fraud Detection In Online Transactions Using Machine Learning Algorithms

Authors- M.Tech. Scholar Ramireddy Himabindu, Asst.Prof. N Surendra, Asst.Prof. V Subhasini

Abstract- – People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card holders and financial companies.In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm.Machine learning and deep learning algorithms have been used to detect frauds, but there is still a need to apply state-of-the-art deep learning algorithms to reduce fraud losses. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. The European card benchmark dataset was used to evaluate the proposed model, which outperformed the state-of-the-art machine learning and deep learning algorithms..

 

Prediction of Diabetes with Web-Application using Machine Learning Algorithms

Authors- M.Tech. Student Abbareddi Anjali, Asst. Prof. R Althaf,Asst. Prof. V Subhasini

Abstract- – Manufacturing decisions inherently face uncertainties and imprecision. Fuzzy logic, and tools based on fuzzy logic, allow for the inclusion of uncertainties and imperfect information in decision making models, making them well suited for manufacturing decisions. In this study, we first review the progression in the use of fuzzy tools in tackling different manufacturing issues during the past two decades. We then apply fuzzy linear programming to a less emphasized, but important issue in manufacturing, namely that of product mix prioritization. The proposed algorithm, based on linear programming with fuzzy constraints and integer variables, provides several advantages to existing algorithm as it carries increased ease in understanding, in use, and provides flexibility in its application.

Employees Stress Detection With Facial Expressions Using Machine Learning

Authors- M.Tech. Scholar G.V.Devi, Asst.Prof. V Dakshayani, Asst.Prof V Subhasini

Abstract- – The objective of this paper is to apply machine learning and visual processing to identify overworked IT employees. Our technology is an improved version of older stress detection systems that did not include live detection or personal counseling. Stress detection methods that don’t include real-time monitoring or individual counselling are being updated in this research. A survey is used to collect data on employees’ mental stress levels in order to provide effective stress management solutions. In order to get the most out of your employees, this paper will look at stress management and how to create a healthy, spontaneous work environment.

Effects of Dietary Sodium Restriction on Blood Pressure and Cardiovascular Disease Outcome: A Review

Authors- Paradis Honarvar

Abstract- – The effect of reduction of dietary sodium intake on blood pressure has been an important topic for discussion among physicians and researchers. In the past decades, the contribution of excessive sodium intake as a risk factor for developing cardiovascular diseases has remained controversial. The objective of this manuscript was to evaluate current epidemiological studies in order to determine what effects have been observed on the blood pressure of individuals with modest reduction of dietary sodium intake and what impact this dietary modification might have on the future of cardiovascular diseases. The search strategy was based on PubMed/MEDLINE database in order to gather information on the testing hypothesis, which is that a modest reduction of dietary sodium intake has no adverse effects on health and reduces the risk of developing future cardiovascular diseases in both normotensive and hypertensive adults. The search was not limited to the country of origin, however it was limited to only peer-reviewed publications written in English. The result of this review reveals that the majority of the current studies and public guidelines support giving 5-6 g of salt/day for lowering blood pressure in both normotensive and hypertensive adults in order to lower the risk of developing non-communicable diseases, including cardiovascular disease. In conclusion, the data collected from systematic reviews, randomized control clinical trials and prospective studies all suggest that modest reduction of dietary sodium intake has a positive outcome in lowering the risk of developing cardiovascular diseases and attenuating difficulties in both normotensive and hypertensive adult population. Word Count: 250 .

Integrating Blockchain and Cloud to Create Innovative IoT Architecture

Authors- Rishabh Rawat, Sarita, Associate Professor Dr Riya Sapra

Abstract- – The emergence of blockchain, cloud computing, and the Internet of Things (IoT) as a continuous worldview is transformational for the state-of-the-art computerized biological system. IoT systems with expanding reach are the generat massive amounts of data that appear to be properly managed if they are safe, adaptable, and skilled. Despite its versatility and abundance of resources, cloud computing frequently lacks the security that the Internet of Things demands, leaving the devices open to cyber threats. By enhancing the information intelligence, security, and dependability of IoT systems, blockchain technology, with its decentralized and impenetrable record, could close these security gaps. The goal of this research is to see how blockchain technology and cloud computing can be combined [2]. The main issues of scalability, latency, and security can be fully addressed by combining blockchain technology with cloud computing for Internet of Things applications. Blockchain’s decentralized management, transparency, and data immutability can greatly reduce the risks associated with single points of failure in centralized cloud systems. In the meantime, real-time processing of streams of Internet of Things data at scale can be made possible by cloud computing’s vast processing and storage capacity, which may exceed blockchain’s computational limits. Strong networks of IoT devices that can support vital applications in the management of supply chains, smart cities, healthcare, and other fields may result from this collaboration. In order to successfully balance cost, performance, and security, future study must concentrate on maximizing the integration of these technologies.

A Study to Observe the Use of Body Mechanic Practices among Nursing Students While Working in the Clinical Fields

Authors- Shally Sharma, Lecturer Dipak Sethi, Lecturer Jasmeet kaur

Abstract- – Mechanics is concerned with the analysis of the action of forces on object. Body mechanics is the term used to describe the efficient, coordinated and safe use of the body to move objects and carryout the activities of daily living. The major purpose of body mechanics is to facilitate the safe and efficient use of appropriate muscle groups to maintain balance, reduce the energy required, reduce fatigue and decrease the risk of injury. Good body mechanics is very much essential for the nurses. When a person moves, the balance of that person depends on the interrelationship of the centre of gravity and the base of the support. The closer the line of gravity is to the centre of base of support, the greater the person’s stability. Appropriate preparation prevents potential falls and injury and safeguards the person and equipment1.