International Journal of Integrative Studies (IJIS)
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Privacy Preserving E-Voting System Using Homomorphic Encryption
Get PDFWith the rise of digital governance, secure and private electronic voting systems are becoming increasingly important. Traditional e-voting platforms often suffer from vulnerabilities such as vote tampering, lack of transparency, and weak identity verification. To address these challenges, this project introduces a secure online voting system that integrates Paillier homomorphic encryption with deep-learning-based facial recognition technology. Homomorphic encryption enables the aggregation of votes while they remain encrypted, ensuring that individual ballots stay completely confidential throughout the counting process. Facial recognition provides real-time voter authentication, effectively preventing proxy and duplicate voting.Throughout the voting lifecycle, ballot data is encrypted during both transmission and storage, eliminating opportunities for third parties to intercept or manipulate information. An administrator can access results only after the voting period concludes, and the system reveals only the final aggregate tally without disclosing individual choices. The proposed model is implemented using Python, Flask, OpenCV, and SQLite, offering a secure, scalable, and user-friendly solution suitable for small-scale elections in academic institutions and local organizations.The system includes an intuitive web interface, encrypted data storage, and secure communication mechanisms to enhance usability and reliability. By combining biometric authentication with advanced cryptographic techniques, the project delivers a robust, tamper-resistant voting framework that strengthens voter trust and ensures endto-end privacy. Overall, this work demonstrates how modern cryptography and artificial intelligence can significantly improve the security and transparency of digital election systems, making it a strong foundation for future e-voting applications
Comparative Study of CNN and Transformer Models for Image Classification
Get PDFThe introduction of deep learning architectures has brought about a tremendous change in image classification. Although Convolutional Neural Networks (CNNs) has received widespread use over the last decade because they xhibit superior feature-extraction performance, during the last few years, transformer-based models have shown to be performing equally or even better in a variety of benchmarks. This paper is based on the main aim to compare CNN and transformer models in relation to image classification and their performance in terms of accuracy, computational cost, interpretability, and robustness. The experiment is performed using CIFAR-10 and a small group of ImageNet by evaluating a classical ResNet-50 and a Vision Transformer (ViT-Base). Findings indicate that CNNs are very efficient though it takes a shorter period to train and their generalization, but the transformer models perform better with a bigger dataset and they also tend to capture the global image dependence better. The results show that transformers have potential in large-scale classification, whereas CNNs have useful benefits in resource-limited settings
Antimicrobial Resistance: Mechanisms, Trends, and Future Directions
Get PDFAntimicrobial resistance (AMR) poses a worldwide health danger by rendering numerous antimicrobial treatments useless and leading to elevated healthcare costs and elevated mortality rates and increased morbidity standards as well as economic costs. The study explores antimicrobial resistance mechanisms by investigating enzymatic destruction alongside target alteration and cell pump activity and biofilm developmental capabilities of microorganisms for evading antimicrobial drug effects. This research investigates recent AMR developments by monitoring the increasing numbers of microbes that become resistant to multiple drugs known as MDR together with XDR strains and pan-drug-resistant bacteria. Resistive mechanisms have increased rapidly because of overuse of antibiotics in human medicine and its applications in animal farming as well as genetic exchange that allows microbes to travel among different regions. This paper outlines the importance of surveillance because it functions as an essential component fighting AMR alongside antimicrobial stewardship and infection control practices. Antimicrobial agents along with phage therapy options along with modern diagnostic methods make up the fundamental weapons against AMR. The proposed direction highlights the necessity for different organizations to collaborate because they should develop contemporary therapeutic approaches and strengthen antibiotic management systems worldwide
Effectiveness of Progressive Resistive Exercises on Gait Performance and Balance in Stroke
Get PDFStudy Design: Pre to post-test design- experimental study Background: There is a lack of clinical research regarding effectiveness of Progressive Resistive Exercises for improvement of Gait performance and Balance in Stroke. To our knowledge there are no prospective, randomized studies in the literature investigating the Progressive Resistive Exercises in improving Gait performance and Balance in Stroke. Purpose of the study: To determine the effect of Progressive Resistive Exercises for improvement of Gait performance and Balance in Stroke. Method: 30 subjects with 30-150 days post stroke having Spasticity 1+ or less than 1+ on modified Ashworth were randomly assigned to either control group or experimental group. Readings were taken for Time and Go Test (TUG) on 1st day and last day of 4th week. Results: The results of the study suggest that progressive resistive exercises are significantly effective in improving gait performance and balance than active exercises (same exercises without resistance) in stroke patients. There was a significant improvement in TUG score in group B in the end of 4th week (p<0.002) compared to that in group A. Conclusion: The results of the study revealed that low carb diet is more effective in decreasing pain in knee osteoarthritis patients
The Role of Microbial Communities in Bioremediation of Plastic Waste
Get PDFThe fast accumulation of plastic waste happens because insufficient recycling and proper disposal techniques allow only small quantities of plastic to be recycled thus releasing the vast majority into landfills and the environment. The research investigates how microbial collective organisms perform biological recovery of plastic waste. Plastic polymers undergo different enzymatic transformations through bacterial and fungal organisms before these microbes can break down the products to generate cellular metabolic energy. This study examines plasticbiodegrading microbial populations through enzyme research and environmental factor analysis and genetic modification studies focused on plastic degradation enhancement. This paper shows bioremediation operations need appropriate planning by explaining microbial technologies should be implemented during waste management activities. The research shows that plastic pollution management reaches success when applying microbial methods that combine bioplastics with modern biotechnological approaches to support environmental sustainability
Synergistic Toxicity of Airborne Pollutants and Their Effect on Rat Lung Cells
Get PDFAir pollutants or particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) have been identified to affect much on humanity especially the respiratory system. There is also an investigation on the increased or combined effect of such pollutants on the rat lung cell although the concern over the quality of air in both metropolitan and industrialized centres has been alleviated. The current manuscript is a review of synergistic toxicity of air pollutants and its effects on rat lung cells, or in other words cellular viability, oxidative stress, inflammation and cellular functioning. Additivity was determined due to the laboratory-based investigations involving human lung cell lines (e.g., A549, BEAS-2B) upon exposure to different concentrations of PM, NO2, SO2, and O3. These findings indicate that multi-pollutant exposure produced greater toxicological effect than single-pollutant exposures and that oxidative stress, inflammatory cytokine release and cell viability changes were significantly potentiated. The oxidative damage induction, the activation of the pro-inflammatory pathways, and the lung cells dysfunction are the mechanisms that stand behind these effects. The paper has raised concern on the potential health risk of colossal mixed airborne contaminants with long duration of exposure and short coming of the regulatory process in dealing with synergistic toxicity of the mixed air pollutants
The Evolution of E-commerce: How Artificial Intelligence is Reshaping Online Retail
Get PDFDue to the fast-growing e-commerce, the consumer behavior has changed, and business opportunities have been offered to personalize the experience and streamline operations. Recommendation systems, chatbots, predictive analytics, and computer vision are all examples of Artificial Intelligence (AI) technologies that are transforming online retail in a very critical way. This paper explores how AI can be applied to online shopping using actual online shopping data to conduct experimental research on how AI-based recommendation systems can change consumer behavior and online sales performance. An international e-commerce store consisting of more than 500,000 transactions in a Kaggle dataset were analyzed with the help of collaborative filtering and content-based AI recommendation algorithms. There were comparative experiments with a baseline of a non-personalized system of recommendations and an AI-enhanced one. The most important performance indicators were measured including the click-through rate (CTR), conversion rate (CR), and average order value (AOV). The results obtained showed that AI-based suggestions enhanced CTR (38), CR (24), and AOV (17) in comparison to baseline procedures. These findings show the real effects of AI technologies in enhancing user experience and contributing revenue to an online retail setup. In the end of the study, the methodological implications, limitations and future discussions of incorporating advanced AI methods in the e-commerce ecosystems are discusse
Sustainability Challenges in the Brassware Export Industry of Moradabad: A Policy Perspective
Get PDFThe export business of Moradabad brassware, also referred to as Peetal Nagri in the world and the largest in India, has always remained at the center of the Indian handicraft economy, bringing in foreign income, livelihoods of thousands of artisans and MSMEs. Although it is essential in terms of economic importance, the industry is experiencing pressures of sustainability due to environmental degradation, socio-economic weaknesses, and policy implementation loopholes. This research paper discusses these issues in the policy-level perspective through an analytical system constructed based on the secondary data of governmental reports, environmental reports, clusterlevel studies, and literature. The results indicate that the conventional production methods like casting, polishing, and electroplating have major pollution imprints that result in heavy-metal pollution of soil and water bodies, particularly the Ramganga River. Informal labour arrangements, health risks, lack of safety precautions and social security are other social issues that pose threats to long-term sustainability. The industry is threatened economically by the mechanized international production, increased cost of inputs, changeable demand of exports, and the lack of innovation of cleaner technologies. Although the ODOP, MSME schemes and cluster development programs are government policies aimed to empower the sector, the issue of sustainability is not well-planned. The paper highlights how policy reforms including the adoption of green technology, increased environmental regulation, enhanced worker protection and global sustainability compliances are necessary. The results can offer practical recommendations to policy makers who want to make the Moradabad brassware industry in line with sustainability and the changing face of trade in the world
Macroeconomic Variables and Stock Market Performance in Sri Lanka: An Ardl Bound Testing Approach
Get PDFThe aim of the study is to examine the impact of macroeconomic variables on stock market performance in Sri Lanka. This study uses yearly data collected from the annual report of the Central Bank of Sri Lanka for the period from 1990 to 2019. Macroeconomic variables used in this study are interest rate, inflation rate, real exchange rate, and money supply while All Share Price Index (ASPI) is used to measure the stock market performance. Inflation rate and interest rate are found stationary at zero levels while exchange rate, money supply and stock market performance are found stationary at levels one in the Augmented Dickey-Fuller (ADF) test. No serial correlation is found among variables by employing Breusch-Godfrey LM Test. The Auto-Regressive Distributed Lag (ARDL) bounds test is used to test the long-run and short-run relationships between variables. The empirical result reveals that there is a negative and significant impact of interest rate and inflation rate on stock market performance while exchange rate and money supply do not hold any significant impact on stock market performance in the long-run. Further, it is found that there is a negative and significant impact of interest rate on stock market performance in the short run
Effect of balance diet versus low carb diet in improving pain in knee Osteoarthritis
Get PDFKnee OA is one of the most standard arthritic maladies that affect the lives of most patients suffering from this ailment. Pain management and functional limitation in patients with knee OA poses a significant problem. Although there are many treatments for osteoporosis, dietary intervention is very important for patients suffering from the disease. It was, therefore, conducted with the objective of establishing the impact of an improved nutrient balanced diet (NBD) and an alternate low carbohydrate (low-carb) diet on the functional disability and pain perception in patients with knee OA. The participants consisted of 20 individuals within the age range of 30-60 years with the diagnosis of knee OA who complained of knee pain for at least six months. The subjects were divided into two groups on a completely random basis. Group A was given a low carbohydrate diet in addition to conventional treatment; IFT, hot pack and resistance exercises while Group B was given a normal diet in addition to the treatment modalities mentioned above. The Numeric Pain Rating Scale (NPRS) was applied to measure the baseline and post-intervention pain. So, it is has been found that there have been lessening of pain and increase in the functional range in both the groups, but the group which followed the low carbohydrate diet were slightly more benefited in terms of pain relief. Analysis of t-tests showed that both types of interventions were beneficial, and intra-group comparisons revealed a decrease of pain after the treatment. Thus, it is possible to argue that dietary measures, with an emphasis on low-carb diets, can be useful as an adjunct treatment for patients with knee OA and impaired functional mobility