Volume 14 | Issue 4

 Abstract

DR is one of the most prevalent diabetic retinopathy. preventable causes of vision loss, which cause an acute. requirement of effective and early detection means. The present review examines the joint implementation of EfficientNet, a current deep-learning. Gradient-weighted Class Activation Mapping, architecture, and Gradient-weighted Class Activation Mapping. (Grad-CAM) to enhance the classification and interpretability of DR. in medical imaging. The compound scaling strategy employed by EfficientNet makes it very accurate and calculationally efficient, which is why it is suitable with largescale retinal screening. Grad-CAM also enhances the diagnostic pipeline since it produces intuitive. visual descriptions to emphasize areas of clinical importance, Hence making it more transparent and practitioner-confident. Recent studies which used this combination to determine the severity of DR. grading is evaluated in terms of performance variables including accuracy, sensitivity and specificity. Key challenges--including Unequal size of data set, inconsistency in image quality, and scarcity. generalization in varied groups of patients- are also talked about. The review concludes that the combination of EfficientNet and GradCAM presents an effective direction of the creation of scalable, explainable, and clinically reliable automated DR screening.

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Federated Learning, Mental Health Monitoring, PHQ-9 Depression Assessment, Emotion Recognition, Privacy Preservation, Multimodal Behavioral Data, Secure AI Chatbot, Flower Framework

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Maha Kumbh 2027 at Nashik is expected to welcome hundred million of devotees from entire world. This presents significant challenges in managing transportation, parking, and emergency response. Traditional systems often fail to handle large crowds effectively, resulting in congestion, delays, and security problems. This paper introduces KumbhSahyogi, a GPS-based, AI-powered smart mobility and service management system designed to maximize parking allocation, optimize routes, and coordinate transportation for large events like the Kumbh Mela cordinate transportation for large events like the Kumbh Mela. The system includes various features such as real-time parking slot availability, AI-powered route optimization through Dijkstra's algorithm and congestion heatmaps, multimodal transport integration, and a smart chatbot for user support.

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 Keywords

Kumbh Mela 2027, Smart Transportation, Artificial Intelligence (AI), GPS Navigation, Smart Parking, Dijkstra's Algorithm, Crowd Management, AWS.

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The Travel Details Smart Logging Application is an intelligent mobile-based solution developed to modernize and streamline the process of capturing, managing, and storing travel-related information in a structured digital format. Traditional methods of recording travel details often depend on manual entry or paper-based documentation, which can lead to inaccuracies, data loss, and inefficiencies in managing travel records. This ap-plication addresses these challenges by providing an automated, user-friendly platform that allows users to record origin and destination locations using real-time GPS services, automatically capture date and time information, and manage additional travel parameters such as mode of transportation and number of travelers through an intuitive interface. The system enhances accuracy by minimizing manual intervention and ensures reliable data logging through automated location detection and time stamping. Designed with a focus on usability and efficiency, the application supports seamless data entry and retrieval, making it suitable for individuals, organizations, and institutions that require structured travel documentation for purposes such as expense tracking, travel monitoring, logistics management, and reporting. The lightweight architecture and scalable design allow easy deployment across devices while maintaining performance and accessibility. By integrating mobile technology with location-based services, the application demonstrates how digital solu-tions can significantly improve everyday travel documentation processes. The proposed solution promotes efficiency, reduces administrative overhead, and provides users with a convenient and dependable method to maintain organized travel records, thereby contributing to smarter and technology-driven travel management practices.

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Travel Monitoring, GPS Tracking, Mobile Ap-plication, Data Analysis, Smart Tourism

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Lalpur Chhedipara is a small village located in Dhuliyan town of Murshidabad district, West Bengal. This paper attempts to explore the cultural significance of Loko Utsab in this village. The study focuses on the active participation of villagers in preserving this tradition through performances. Gambhira is one type of Loko Utsab. It also highlights Gambhira's role as a medium of social awareness and cultural identity.

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Lalpur Chhedipara, Village, Tradition, Gambhira, Folk

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Abstract: The Spread of Christianity among the Bodos brought about different socio-cultural changes among them. The spread of Christianity among the Bodos of Borshijhora village began in about 1980 under Rev Fr. Joseph Zubizaretta and Fr. Edward D' Souza. The spread of the religion in the village, in due course of time, shaped the socio-cultural life of the villagers. This study aims to highlight the spread of Christianity in Borshijhora village, causes and impact of conversion to the faith.

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Christianity, Borshijhora, causes, impact, Social life.

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Ruskin Bond is one of the most celebrated Indian writers known for his sensitive portrayal of childhood and his deep engagement with nature. His writings are marked by simplicity, warmth, and an intimate understanding of the emotional world of children. Having spent much of his early life in the Himalayan regions, Bond developed a close and lasting bond with the natural landscape, which continues to shape his literary imagination. His stories often unfold in small towns and hill stations, where nature is not merely a setting but a living presence. This paper explores the representation of childhood sensibilities in Bond's fiction, with particular emphasis on the relationship between children and nature. Through close textual analysis of selected works, the study examines how natural elements such as seasons, trees, animals, insects and landscapes actively shape the emotional and psychological experiences of child protagonists. It further analyses themes of friendship, love, separation, and loneliness, showing how these experiences are closely intertwined with the rhythms of the natural world. The paper argues that Bond's depiction of childhood is rooted in simplicity and authenticity, where nature serves as both companion and guide in the process of growing up. Ultimately, his fiction presents a nuanced understanding of childhood as a period of deep sensitivity, where the external environment reflects and nurtures the inner emotional life of the child.

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Childhood, Nature, Childhood Sensibilities, Ruskin Bond, Human-Nature Relationship, Friendship, Coming of Age, Himalayan Landscape, Eco-criticism

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Investment advisory services are essential for helping investors make informed financial decisions in a complex and changing market. In India, the rapid growth of capital markets, regulatory changes by the Securities and Exchange Board of India (SEBI), and increased financial awareness among retail investors have greatly expanded the need for professional advisory services. This study offers a practical approach to investment advisory in India, focusing on ICICI Securities, a leading financial services provider in the country. The research looks at the advisory framework used by ICICI Securities. It covers client profiling, risk assessment, asset allocation strategies, portfolio diversification, and the use of technology-based platforms for investment recommendations. It also reviews the variety of products available, such as equity, mutual funds, derivatives, insurance, and wealth management solutions. The study shows how ICICI Securities combines research insights, digital tools, and personalized advisory services to meet the diverse needs of investors.

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Investment advisory services, Securities and Exchange Board of India (SEBI), ICICI Securities, portfolio diversification, Asset Allocation Strategy.

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This study examines the impact of group behaviour on employee productivity in manufacturing units, with special reference to Jeya Enterprises. Group behaviour, including communication, leadership, cooperation, trust, and conflict management, plays a significant role in shaping employee performance. The research adopts a descriptive and quantitative approach, collecting primary data through structured questionnaires from employees. Statistical tools such as percentage analysis, mean score, and correlation are used to analyze the data.

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Group behaviour, employee productivity, teamwork, communication, manufacturing units, cooperation, conflict management

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Deepfake technology has advanced rapidly in recent years, making it increasingly difficult to distinguish between real and manipulated media. This paper presents an efficient and explainable deepfake detection system that leverages facial artifact analysis and deep learning techniques. The proposed system integrates spatial feature extraction using a pretrained Xception Convolutional Neural Network (CNN) with fine-grained facial landmark analysis using MediaPipe FaceMesh. Video inputs are processed through an optimized frame extraction strategy, and facial regions are isolated using MTCNN. The model is trained on FaceForensics++ and Celeb-DF datasets and evaluated on the DFDC dataset to assess generalization capability. Experimental results demonstrate strong performance with high accuracy and robustness across datasets. Additionally, explainability is incorporated through probability-based outputs and visualization techniques such as Grad-CAM. The proposed approach effectively identifies deepfake content and provides interpretable results, making it suitable for real-world forensic applications.

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Deepfake Detection, Facial Artifact Analysis, Convolutional Neural Network, MediaPipe FaceMesh, Explainable AI, Grad-CAM, MTCNN, Video Forensics, FACEFORENSIC++, DFDC,CELEBP-DF,XECPTION NET.

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Now-a-days, there has been a significant increase in the use of fibres in concrete for improving its properties such as tensile strength and ductility. Now-a-days polypropylene fibre, etc. use while preparing concrete. polypropylene fibre has the advantages of having higher tensile strength and compressive strength, thus reducing the loss of damage during fire accident of concrete structures. In this investigation polypropylene fibre are added to the concrete by volume fraction to determine its strength characteristics. Determination of compressive, split tensile and flexural strength of concrete. Polypropylene is a synthetic hydrocarbon polymer, the fiber of which is made using extrusion processes by hot drawing the material through a die. Its use enables reliable and effective utilization of intrinsic tensile and flexural strength of the material along with significant reduction of plastic shrinkage cracking and minimizing of thermal cracking. Comparison of the strength performance of conventional concrete was made. This is experimental study done by using polypropylene fibres without flyash in concrete and conclusion from their various strength parameters finding out the optimum quantity of polypropylene fibers required to achieve the maximum compressive strength for M40 grade concrete. From the exhaustive and extensive experimental work it was found that with increase in polypropylene fiber content in concrete there was a tremendous increase in compressive strength. The effect of the addition of polypropylene fibers on the mechanical properties of normal strength concrete is studied. The polypropylene fibers were added at concentration of 0.3, 0.4, 0.5 and 0.6 % by volume. Compression, pullout and bending tests were carried out to determine the mechanical properties such as maximum compressive strength, splitting strength. On the basis of the experimental results, it can be concluded that, ductility of concrete significantly increased and maximum compressive strength slightly increased with increasing the content of polyproplylene fibers materials. Further increase of polypropylene fibers (higher values than 0.5 vol. %) did not increase the ultimate bond strength, but it provided much more ductile bond behaviour.

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Concrete, Strength, polypropylene fibre, durability

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 Abstract

The research field utilizes cancer cell lines that originate from tumors to investigate cancerous processes and test new treatment methods. The TP53 gene functions as a crucial genetic element because it governs three fundamental cellular processes, which include cell cycle management, genomic restoration, and programmed cell death. Researchers must establish the TP53 mutation status of their samples because it directly affects their ability to obtain trustworthy experimental results. Researchers propose a machine learning technique to predict and assess TP53 mutation status within human cancer cell lines. The UMD TP53 database provides data which undergoes preprocessing to maintain both consistency and accuracy. The Logistic Regression model functions as a supervised classification system, which enables researchers to distinguish between mutant and wild-type cell lines based on their mutation characteristics. The proposed system combines all necessary components for data preprocessing and feature extraction and model training and evaluation into a unified operational process. The experimental results demonstrate how the model successfully detects mutation patterns while the existing datasets contain verification errors. The study demonstrates that cancer research needs validated mutation data to conduct reliable research while machine learning methods improve this reliability.

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TP53, machine learning, cancer cell lines,

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Background and Objective: Chronic obstructive pulmonary disease is a diverse lung disease defined by chronic respiratory symptoms (dyspnea, cough, expectoration and /or excerbations) due to abnormalities of the airways (bronchitis, bronchiolitis) and/or alveoli (emphysema) that cause persistent, typically progressive, airflow obstruction There are airway clearance techniques like resistive respiratory device and threshold inspiratory muscle training techniques have been proposed as an adjunct to conventional therapy to treat COPD. Both the techniques have been proved in increasing inspiratory muscle strength and quality of life in COPD and the literature is limited on their comparison Hence need of the study arises. Methods: A quasi-experimental study design. 80 subject with FEV1/FVC<70% with clinical diagnosis of COPD were randomly allocated into two groups. In Group -A subjects (n=40) were treated with Resistive respiratory muscle trainer (breather) device and conventional physiotherapy training whereas in Group-B subjects (n=40) threshold inspiratory muscle training and conventional physiotherapy. The participants were given intervention thrice a week for 6 weeks. The Outcomes of this intervention was measured in terms of maximum inspiratory mouth pressure and st. George respiratory questionnaire. Results: Independent 't' test was used to compare the mean significance difference between continuous variables Paired 't' test was used to assess the Statistical significance difference between pre and post test scores. Statistical analysis of data revealed that within the group comparison both groups showed significant improvement in all parameters. Where as in between group comparison breather Device technique showed better improvement compared to threshold inspiratory muscle trainer. Conclusion: After 6 weeks of interventions both resistive respiratory muscle trainer and threshold inspiratory muscle trainer were shown statistically significant in improving inspiratory muscle strength and quality of life. However, resistive respiratory muscle trainer showed greater improvement in pi-max and SGRQ. Hence, we conclude that breather is a convenient, easy to use and Safe, in improving inspiratory muscle strength along with quality of life in subjects with COPD.

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 Keywords

Chronic obstructive pulmonary disease, inspiratory muscle strength, quality of life, maximum inspiratory mouth pressure, St. George respiratory questionnaire, breather device, threshold device.

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 Abstract

Students often face academic challenges and social isolation due to a lack of proficiency in the medium of instruction in multilingual education environments [1],[5]. In the existing model, there is a Traditional language support model where they separate such students into particular dedicated language classrooms, which results in a delay of subject learning and difficulty in inclusive participation .To address this problem, we propose this project, An AI-Based Real-Time multilingual Class room assistance System which enables instant translation of instructions said by the teacher within the mainstream classrooms. This proposed system of the project integrates Artificial Intelligence (AI), Automatic Speech Recognition (ASR), and Natural Language Processing (NLP) to give instant translation of the teacher's speech into live text, and it also translates into multiple target languages in real time. Here, in this proposed system, follows a client-server architecture with role-based access for students and teachers. The Teacher speaks through a microphone-enabled interface, while students register on the web page and select their preferred language. In this, we proposed an AI engine that processes the spoken input, does the speech-to-text conversion, and applies neural machine translation to generate multilingual outputs, and gets instantly displayed on the devices of students using real time communication protocols.

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Artificial Intelligence (AI), Inclusive Education, Multilingual Classrooms ,Natural Language Processing (NLP), Real-Time Translation, Speech Recognition (ASR).

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The study adopts a descriptive research design and is based on primary data collected from 135 respondents using a structured questionnaire through convenience sampling. Statistical tools such as percentage analysis, weighted average method, correlation, chi-square test, Kruskal-Wallis test, and Mann-Whitney U test are applied for analysis.

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 Keywords

Digital Platforms, Bio Bags, Consumer Behaviour, Sustainable Marketing, Awareness

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The rapid growth of digital banking systems has led to an increase in fraudulent financial transactions, posing a serious threat to both customers and financial institutions. This paper presents a machine learning-based approach for detecting fraudulent transactions in banking data. The system utilizes various classification algorithms to analyze transaction patterns and identify anomalies that indicate potential fraud. The dataset is preprocessed to handle missing values, normalize features, and improve model performance. Techniques such as Logistic Regression, Decision Trees, and Random Forest are used to classify transactions as legitimate or fraudulent. The proposed model achieves high accuracy and precision, enabling early detection and prevention of fraud. The system helps financial institutions minimize financial losses and enhance security by providing a reliable and automated fraud detection mechanism.

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Machine Learning, Fraud Detection, Banking Security, Classification Algorithms, Data Analysis

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Banking and financial institutions process thousands of customer complaints daily through multiple channels including emails, mobile applications, call centers, and web portals. Manual complaint handling is time-consuming, error-prone, and often leads to delayed resolution of critical customer issues. This paper presents an intelligent, automated complaint management system leveraging Natural Language Processing techniques for severity classification, sentiment analysis, and root cause iden-tification. The proposed system employs keyword-based NLP algorithms, duplicate detection using Gestalt pattern matching, and automated routing mechanisms to streamline complaint processing. Implementation results demonstrate a 60 percent reduction in processing time, 95 percent accuracy in duplicate detection, and 100 percent automation in severity classification. The system successfully identifies complaint patterns, enabling proactive problem-solving and data-driven decision-making, ulti-mately enhancing customer satisfaction and operational efficiency in banking services.

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Natural Language Processing, Banking Systems, Complaint Management, Sentiment Analysis, Severity Classifica-tion, Machine Learning, Customer Service Automation

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Air pollution is the major health and environmental hazard, but the majority of the systems available for this purpose are expensive and not easy to implement. This study will explain how to detect air pollution with the help of plants in a simple and low-cost way. As plants clearly indicate that they are not in a good condition when the atmosphere is polluted, as shown by the presence color, spots, and dust on the leaves, they can be used for this purpose. In this study, images of the selected plant will be taken on different days, and the presence of any visual changes will be detected by a CNN model. Before the plant images are used for this purpose, they will be adjusted for better clarity and visibility of the plant's condition. Then we will use the condition of the plants to figure out if the air is polluted or not. This system will help us detect air pollution using plants and artificial intelligence which make it easier and cheaper.

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Smart Environment, Air Pollution, Plant Health, AI, Image Processing, Climate Action.

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Keywords: Chronic bronchitis, educational intervention, self-care, prevention, adults.

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Iran's nuclear energy development programme is considered as one of the most controversial international issues in the contemporary world .The process of developing nuclear power in Iran resulted in a hostile relationship between the US and Iran, which is often characterised by the period of feud among the two that poses a constant threat to international security and peace in contemporary times. This article analyses the multilayered political and strategic dimensions of Iran's nuclear program and examines its impact across various interconnected lenses such as the diplomatic efforts, regional security , existing dynamics of various alliances in the gulf region, compliance with the Nuclear Non-Proliferation Treaty (NPT) and the framework of global nuclear governance. The theoretical basis of this study is realism, which believes that every actor in the international sphere acts to maximize power and security for their own state while influencing and dominating other weak states for their benefit.

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diplomatic efforts, hostile relations ,global peace, global nuclear framework, Iran,nuclear politics, Non-Proliferation Treaty (NPT), realism, regional power blocs, regional security, United States

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With the fast growth of digital technology and online connectivity has changed traditional marketing into more interactive and consumer - oriented process through e-marketing platforms. This study examines consumer perception towards personal care products in Erode District, marketed through e-marketing platforms. The research investigates awareness and attitudes of consumers towards e-marketed personal care products and also analyse consumers' expectation and perceived quality regarding product quality. Primary data is collected from the 110 respondents using questionnaire method, and statistical tools were used to analyse the relationship between awareness, attitudes, expectations and perceived product quality. The findings are expected to help how consumers reply to e-marketing practices for personal care products in Erode District. This study will support marketers, brand managers and online sellers in developing digital strategies that increase consumer trust, improve brand image and meet consumer expectations

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E-Marketing, Personal Care Products, Awareness, Attitudes, Consumer Perception, Expectations,etc.,

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