Volume 14 | Issue 4

 Abstract

Offline signature verification is an effective biometric authentication method with widespread applications in areas including finance, law, and security. However, because of variations in the way that each person writes, as well as the existence of highly skilled forgeries, distinguishing real from false signatures can be very difficult. As a result, a number of researchers have proposed various methods for investigating the validity of signatures by applying principles of image processing and machine learning. Typically, researchers will preprocess the image of the signature, extract features related to it, and then classify these features to determine if a signature is either real or false. Historically, researchers have used many different methods to accomplish signature verification, including Support Vector Machines, Artificial Neural Networks, Hidden Markov Models, and Dynamic Time Warping, as well as more recently developing sophisticated detection models using deep learning architectures like Convolutional Neural Networks to improve accuracy. The purpose of this paper is to provide a survey of the current methods for offline signature verification to detail the advantages and disadvantages of each method. In addition, by comparing the strengths and weaknesses of their methodologies, researchers and practitioners can gain insight into what types of improvements can be made to signature verification systems in order to enhance their accuracy and dependability.

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 Keywords

Signature verification, Forgery detection, Biometrics, Image processing, Machine learning.

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Adolescents' psychological adjustment and overall well-being are influenced by attachment relationships and coping mechanisms. Due to being impacted by things such as parental deployment, frequent relocation, and parents being temporarily separated from them, children of defence personnel are more frequently thought to be at higher psychological risk than other children. Despite these assumptions, empirical research does not support this assumption with inconsistent findings. Therefore, the purpose of this study was to investigate attachment relationships, coping mechanisms, and psychological well-being among adolescents from both civilian and defence families. Quantitative cross-sectional data (comparing two groups of children) were collected. The sample included 30 children of defence personnel compared to 30 civilians (aged 14 - 18). The samples were compared using independent sample t-tests on the following standardized measures: Attachment Style, Brief COPE, and Psychological Well-Being (PWI) measures. No statistically significant differences were found between civilian versus defence personnel children regarding attachment, coping mechanisms, or psychological well-being. Thus, the findings suggest that a parent's occupational background does not solely determine the emotional adjustment of adolescents. This research highlights the role of familial and social supports in promoting adolescent well-being.

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attachment style, coping mechanisms, psychological well-being, adolescents, defence families.

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 Abstract

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Physical laws, Principles, Physical Expressions, Mathematical Formulation.

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UniAccess is a low-cost, multi-modal accessibility assistant that enhances digital interaction for users with physical, motor, and speech impairments. It integrates eye-tracking, voice commands, and hand gesture recognition into a single platform, enabling seamless mode switching. Using technologies like OpenCV, MediaPipe, and SpeechRecognition, it allows real-time, hands-free control, improving accessibility, flexibility, and user independence.

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eye-tracking, voice commands, and hand gestures

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Developing an effective model to identify uncertainties in real-world situations has been challenging due to incomplete, inconsistent, or ambiguous data. This research paper presents a new framework (FPNSM) basedon a five-component membership structure that extends current neutrosophic soft matrixes by enhancing and/or increasing uncertainty breakdown into levels of truth, contradiction, uncertainty, hesitation or falsity; enables users to create a more detailed and dynamic description of an undetermined (uncertain) piece of data. The FPNSM is developed by combining three theoretical components (fuzzy sets, neutrosophic sets and soft set theory). It systematically defines the matrix structure, fundamental operations, and applicable properties of the various algebraic structures associated with the FPNSM. It provides an evaluative basis through the establishment of score/accuracy functions that allow an evaluator to rank their alternatives in a variety of uncertain, dynamic environments. A decision algorithm based on the FPNSM is provided to assist in making decisions based on multiple criteria. In addition, the effectiveness of the FPNSM methodology has been demonstrated through a case study; therefore, this research demonstrates how using the FPNSM can enhance the precision of the output produced when evaluating alternative options relative to an objectively and systematically determined standard of performance compared with existing processes. Subsequently, this research represents an important advancement in uncertainty modeling and provides an avenue for further research into the fields of decision support systems, engineering applications, and data analysis under variable/complex conditions.

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 Keywords

soft set, Pentapartitioned neutrosophic soft set, fuzzy pentapartitioned neutrosophic soft set, fuzzy pentapartitioned neutrosophic soft matrix

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This work introduces the conceptual design of a RAG Based Learning Management System that harnesses semantic PDF analysis, vector-indexed storage, and intelligent module synthesis to offer each student a tailored study experience. Students supply two PDF inputs-- a set of Previous Year Questions (PYQ) and subject-specific study notes--which the system tokenises, chunks, and encodes into a persistent vector store through dense semantic embeddings. A Retrieval-Augmented Generation pipeline driven by the Gemini 2.5 large language model then cross-references retrieved chunks to produce cohesive study modules, each bundling curated YouTube video links, concise AI-drafted revision summaries, time-bounded MCQ assessments, and an interactive progress dashboard. A document-grounded conversational agent complements these modules by letting learners pose free-form questions against their own uploaded content. The overall stack pairs a FastAPI service layer with a React SPA presentation tier built with Vite and the YouTube Data API to yield a modular, scalable digital learning environment. Upon deployment, the system is anticipated to cut study-preparation overhead substantially while broadening syllabus coverage and sustaining higher learner engagement relative to conventional static platforms.

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Retrieval-Augmented Generation (RAG), Personalized Learning, Learning Management Systems (LMS), Vector Databases, Semantic Embeddings, PDF Analysis, Adaptive Learning, Large Language Models (LLMs), FastAPI, React.js, Gemini API.

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Object detection is an important issue in computer vision. It enables computers to find objects in images and video streams automatically. This capability is crucial for many applications, including surveillance systems, self-driving cars, medical imaging, and automation. Traditionally, object detection relies on complex processes that involve proposing objects, extracting features, and classifying them. These processes can be resource-intensive. Recently, the field has progressed with the introduction of single-stage object detectors like YOLO (You Only Look Once). These detectors have significantly increased the speed of object detection while keeping accuracy high. This paper introduces a new object detection framework called VisionX. VisionX is a web-based system that uses deep learning object detectors and modern web technologies. Its goal is to create a unified framework for various object detection applications. The framework uses YOLOv8 for object detection. It supports multiple input sources, including images, video streams, and webcam feeds. VisionX is built with React for the frontend and Flask for the backend. It includes key features such as object model selection, dataset management, real-time detection, filtering objects based on confidence levels, and identifying suspicious objects for security purposes. The system processes input data through a series of steps, including data preprocessing, object detection with YOLOv8, filtering results, and visualizing the objects. Experimental results indicate that this object detection framework is effective in terms of accuracy and speed. It effectively connects machine learning object detectors with user applications. VisionX can be applied in various scenarios, such as surveillance systems, smart object monitoring, and AI-driven automation.

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Object Detection, YOLOv8, Computer Vision, Deep Learning, Real-Time Detection, React, Flask, Web-Based System, Surveillance Systems, Machine Learning.

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This study aimed to compare the physical and physiological characteristics of youth football players aged 15-17 years from Kerala and Lakshadweep. A total of 200 male players (100 from each region) participated in this cross-sectional study. Anthropometric variables, body composition, physical performance (agility, sprint, power, and flexibility), and physiological capacities (intermittent endurance and aerobic fitness) were assessed using standardized field-based tests. Independent samples t-tests were used to determine differences between groups. The results revealed no significant differences in anthropometric characteristics between the groups. However, Kerala players demonstrated significantly better performance in agility, linear sprint, curve sprint, flexibility, and intermittent endurance. In contrast, Lakshadweep players exhibited significantly higher aerobic capacity (VO?max). These findings suggest that while body composition remains comparable, performance-related attributes are influenced by region-specific factors such as training exposure and environmental conditions. The study highlights the importance of targeted training interventions to optimize performance in youth football players.

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Football, Agility, Sprint, VO2max

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Abstract: Banaphul is a renowned figure in the landscape of 20th-century Bengali literature. Although he is primarily recognized for his contributions to fiction, he was equally a successful artist in the realm of dramatic literature. 'Dashabhan' (1944) is a collection comprising ten of his one-act plays. From this anthology, we have selected three plays--'ShikKabab', 'Lehya', and 'Jal'--for the purpose of this analysis. In the play 'ShikKabab', the playwright vividly portrays the inner anguish of women within the patriarchal social structure of that era. Through the character of Soudamini, the dramatist depicts the attitude of certain hedonistic men toward the women of that time. Employing the metaphor of the dish Shik Kabab, he successfully encapsulates--within the concise scope of a one-act play--the moral degradation of men who lust after the female body like predatory beasts. The characters--the Zamindar, his sycophant Pannalal, and Jibandhan--serve as representatives of that very society. In the second play, 'Lehya', he presents a tableau of a social reality where young people are not required to demonstrate their competence to secure employment; rather, mere sycophancy toward leaders occupying high positions is sufficient to achieve success. Job seekers manage to obtain appointments--specifically for the post of Private Secretary--by merely "licking the boots" of those in power, without offering any proof of their actual qualifications. Here, Banaphul highlights the plight of educated Bengali youths--both male and female--residing outside Bengal, specifically in the region of Bihar. In the third play, 'Jol', he depicts the communal conflicts prevalent in colonial India in a novel and unique style. Through a scientific lens, he portrays this dialectical backdrop using the metaphor of hydrogen and oxygen atoms. This conflict, in essence, serves as a microcosm of the discord between the Hindu and Muslim communities. At the conclusion of the play, the dramatist envisions a union between the two communities--a reconciliation akin to the scientific process wherein hydrogen and oxygen atoms combine to form the new compound: water. This research paper will explore how the multifaceted nature of contemporary social reality is reflected in these plays.

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Keywords: One-act play, social realism, 'Shikkabab', women's inner anguish, 'Lehya', unemployment problem, 'Jol', communal conflict.

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 Abstract

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 Keywords

Satire, Social Commentary, American culture, Conformity, Individuality

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In the contemporary educational system, a teacher is not merely a dispenser of knowledge; rather they serve as facilitators, a mentor and a psychologically influential figure. Consequently, a teacher's psychological well-being and job satisfaction directly impact the quality of their instruction. The present study aims to examine the relationship between job satisfaction and subjective well-being among private school teachers in Howrah district, West Bengal. It also investigates differences in job satisfaction and well-being with respect to selected variables such as gender and type of institution (government and private). A quantitative research design was adopted for the study. Samples of 150 teachers were selected using appropriate sampling techniques. Data were collected using standardized tools, namely the Job Satisfaction Scale, Teacher Effectiveness Scale and Well-being Scale were used. The formulated hypotheses were tested using statistical techniques such as t-test and correlation analysis. The findings of the study revealed that there is no significant relationship between overall job satisfaction and subjective well-being. Furthermore, no significant differences were found in job satisfaction and well-being with respect to gender and type of institution. The study concludes that job satisfaction and subjective well-being are complex constructs influenced by multiple factors. The findings suggest the need for improving institutional and psychological support systems to enhance teachers' overall well-being.

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Psychological Well-being, Teaching Effectiveness, Job Satisfaction, School Teachers

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 Abstract

Immune checkpoint inhibitors (ICIs), including agents targeting PD-1, PD-L1, and CTLA-4, have revolutionized cancer therapy by enhancing antitumor immunity. However, their use is frequently complicated by immune-related adverse events (irAEs), with thyroid dysfunction being the most common endocrine manifestation. Understanding the incidence, mechanisms, and clinical implications of ICI-induced thyroid disorders is essential for optimizing patient care. Studies were analyzed for incidence rates, mechanistic insights, clinical features, and therapeutic recommendations.

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Immune checkpoint inhibitors, thyroid dysfunction, hypothyroidism, thyrotoxicosis, immune-related adverse events.

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 Abstract

The gap between academic learning and industry requirements has become a major challenge in modern education systems. Students often work on projects without real-world exposure, while industries struggle to identify skilled candidates. This paper presents SYNERGY - Industrial Collaboration Portal, a web-based platform designed to enable seamless collaboration between students, developers, and industry professionals. The system allows users to create and share projects, form teams, assign tasks, and track progress through structured workflows. It integrates real-time communication, feedback systems, and performance tracking to ensure efficient project development. The platform transforms isolated academic work into a collaborative ecosystem, enhancing innovation, practical learning, and employability. The proposed solution improves knowledge sharing, bridges the academia-industry gap, and supports continuous skill development aligned with industry needs.

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Industrial Collaboration, Project Management, Knowledge Sharing, Team Collaboration, Innovation Platform, Web Application.

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 Abstract

This study explains the design and working of a domestic refrigerator based on the vapor compression refrigeration cycle. It focuses on main components like the compressor, condenser, capillary tube, and evaporator, and how they work together to produce cooling. The study also covers performance factors, energy efficiency, and eco-friendly refrigerants. It concludes that domestic refrigerators are efficient, reliable, and essential for food preservation in daily life.

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This study focuses on a domestic refrigerator operating on the vapor compression cycle, involving components like the compressor, condenser, and evaporator, while emphasizing energy efficiency and the use of eco-friendly refrigerants.

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Urban parking inefficiency remains one of the most persistent challenges in modern cities, driving traffic congestion, fuel wastage, rising emissions, and daily frustration for millions of drivers. Earlier research established the socio-economic cost of poor parking management and explored solutions ranging from camera-based detection and IoT sensor networks to edge computing and deep learning models -- each addressing parts of the problem but none delivering a complete, reliable, and deployable solution. Building on this foundation, a unified AI-Driven Smart Parking Framework was designed and developed, integrating ESP32-CAM based video capture, YOLO-based vehicle detection, Region of Interest matching, Django REST API backend with MySQL database, a Flutter mobile application for driver-facing slot availability, and a Streamlit-based monitoring dashboard for administrators. This paper presents the real-world experimental evaluation of that framework, implemented and tested on an open-air parking facility covering parking slots under daytime conditions. Performance evaluation focuses on three key dimensions -- system response latency, mobile application update speed, and dashboard refresh rate. Results confirm that the system achieves an average end-to-end response latency of 1 to 2 seconds, mobile application slot status updates within 1 to 3 seconds, and real-time dashboard refresh under 3 seconds -- validating the practical viability of the proposed framework for smart city deployment. The findings demonstrate that the convergence of computer vision, IoT sensing, and edge computing can successfully transform a conventional parking facility into an intelligent, data-driven, and user-friendly system.

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Computer Vision, Dashboard Performance, Django, ESP32-CAM, Flutter, IoT Sensing, Mobile Application, Real-Time Detection, Response Latency, YOLO.

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Syzygium cumini (L.) Skeels, commonly known as jamun, Indian blackberry, or black plum, is a tropical fruit tree belonging to the Myrtaceae family and is widely found in the Indian subcontinent. It has gained considerable attention for its potential role in managing hyperglycemia associated with diabetes mellitus, a metabolic disorder characterized by inadequate insulin production or impaired glucose regulation.This review focuses on the antihyperglycemic activity of S. cumini, particularly its seeds, which are an important by-product rich in various bioactive compounds. Phytochemical studies have identified the presence of several secondary metabolites such as flavonoids, polyphenols, terpenoids, and alkaloids including jambosine and jamboline, which are believed to contribute to its therapeutic effects.The antidiabetic action of S. cumini is associated with multiple mechanisms, including improvement of glucose homeostasis, stimulation of pancreatic ?-cell function, enhancement of insulin secretion, and inhibition of carbohydrate-digesting enzymes like ?-amylase and ?-glucosidase. Experimental studies in streptozotocin-induced diabetic animal models have demonstrated a dose-dependent reduction in blood glucose levels and HbA1c. Furthermore, computational studies suggest that compounds such as kaempferol and gallic acid exhibit strong interactions with key enzymes involved in carbohydrate metabolism.Clinical findings also indicate that the administration of standardized seed powder can significantly reduce fasting as well as postprandial blood glucose levels. Although S. cumini is generally considered safe, further research is needed to standardize extraction methods and develop advanced drug delivery systems to enhance its bioavailability and therapeutic effectiveness

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nutraceuticals, phytochemicals, antioxidants, jamun seed, Syzygium cumini, and antidiabetic.

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The purpose of the present study was to compare the level of achievement motivation between Kabaddi players and non Kabaddi players studying at Sri Guru Granth Sahib World University, Fatehgarh Sahib. A total sample of 40 male students was selected for the study. The subjects were divided into two groups: Kabaddi players (n = 20) and Non Kabaddi players (n = 20). Achievement motivation was measured using a standardized Achievement Motivation Test. Descriptive statistic, including mean and standard deviation, were calculated, and an independent samples t test was applied to examine differences between the groups. The findings revealed that Kabaddi players demonstrated significantly higher achievement motivation compared to non Kabaddi players. The results suggest that participation in competitive sports such as Kabaddi may enhance motivational traits among university students.

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Achievement Motivation, Kabaddi Players, Non-Kabaddi Players, Sports Psychology.

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The pursuit of happiness and psychological well-being has become a central theme in modern psychology, particularly within the framework of positive psychology. Constructs such as flow, emotional intelligence, and life satisfaction are increasingly recognized as vital determinants of subjective well-being. Flow, introduced by Csikszentmihalyi (1990), refers to a state of deep immersion in an activity, characterized by intrinsic motivation, concentration, and a loss of self-consciousness. Emotional intelligence, popularized by Goleman (1995), encompasses the ability to perceive, regulate, and utilize emotions effectively, thereby influencing interpersonal relationships, academic performance, and coping strategies. Life satisfaction, as defined by Diener et al. (1985), is a cognitive evaluation of one's overall quality of life and is influenced by both internal and external factors. Although these constructs have been studied extensively in Western contexts, their combined influence on young adults in collectivist societies such as India remains underexplored. This study investigates the relationships among flow, emotional intelligence, and life satisfaction in Indian college students. Results revealed significant positive correlations between flow and emotional intelligence, and between emotional intelligence and life satisfaction. Regression analysis confirmed that emotional intelligence and flow jointly predict life satisfaction, though flow alone did not significantly correlate with life satisfaction. These findings highlight the importance of emotional regulation and optimal experience in enhancing subjective well-being, while also emphasizing cultural nuances in collectivist societies. The study contributes to cross-cultural psychology by demonstrating that emotional intelligence is a stronger predictor of life satisfaction than flow alone, suggesting that interventions aimed at improving emotional intelligence may be particularly effective in Indian educational contexts.

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 Keywords

Flow, Emotional Intelligence, Life Satisfaction, Positive Psychology, Well-being, Indian College students, Psychological Engagement, Ex-post facto Research Design, Cros-Cultural Psychology

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 Abstract

Cataract is one of the top reasons people lose their eyesight worldwide, yet it can be easily treated if found early. The real problem is that most people -- especially in villages and small towns -- do not have easy access to eye doctors. To help solve this, we built Cataract Hub, a desktop application that uses artificial intelligence to check whether an uploaded eye photograph shows signs of cataract. The system uses five deep learning models -- AlexNet, VGG16, ResNet18, DeepCNN, and DeepANN -- that all examine the same image and vote on the result. The final answer is decided by the majority vote, which makes the system much more reliable than relying on one model alone. Before analysis, the image goes through a seven-layer validation check to make sure it is a proper eye photo. Along with the Cataract or Normal verdict, the system also measures four clinical eye features, provides a three-level explanation for patients, doctors, and data scientists, and generates a full medical report using the LLaMA 3.3-70B large language model through the Groq API. Users can also chat with the built-in Medical AI assistant in English, Telugu, or Hindi. The entire system runs as a native desktop application built with Electron JS, making it practical and easy to install in clinics, hospitals, and health camps.

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 Keywords

Cataract Detection, Deep Learning, Ensemble Learning, Convolutional Neural Network, Eye Screening, Electron JS, LLaMA, Groq API, Gradio, PyTorch, Medical AI, Rural Healthcare.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In pharmacology, the route of administration is the pathway by which a medication is introduced into the body to achieve a therapeutic effect, patient compliance, and safety of medications. The choice of a specific route depends on the physical and chemical properties of the drug, the desired site of action (local or systemic), the condition of the patient (e.g., unconscious or vomiting), and the rapidity of the response required. This review classifies these routes into systemic and local categories, detailing their specific advantages, disadvantages, and recent advancements in delivery systems. Drug can be administered through multiple routes such as oral, parenteral, topical, inhalation, and transdermal pathways, each having distinct advantages and limitations. Selection of an appropriate route depends on various factors including the physicochemical properties of the drug, desired onset and duration of action, patient condition, and clinical settings.

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Drug Administration Routes; Drug Delivery Systems; Pharmacokinetics; Bioavailability; First-Pass Effect; Administration, Oral; Administration, Sublingual; Administration, Buccal; Administration, Rectal; Injections, Intravenous; Injections, Intramuscular; Injections, Subcutaneous; Administration, Inhalation; Administration, Transdermal; Nanoparticles; Liposomes; Patient Compliance.

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Creative Commons Attribution 4.0 and The Open Definition