Volume 14 | Issue 3

 Abstract

Modern distributed systems demand proactive and intelligent incident management to maintain service reliability and reduce mean time to recovery (MTTR). This paper presents AgileCopilot, a proof-of-concept AI-powered Site Reliability Engineering (SRE) module that integrates Machine Learning (ML) anomaly detection with Generative AI root cause analysis (RCA). The system comprises four components: a Victim Service simulating a live web application with controllable fault injection, an ML-based Watchdog using the Isolation Forest algorithm, an AI Investigator powered by Gemini Generative AI, and a real-time Streamlit monitoring dashboard. The Watchdog monitors CPU utilization, memory consumption, and HTTP response latency; upon detecting an anomaly validated by a heuristic intensity filter, it triggers the AI Investigator to produce a structured JSON report containing the root cause and remediation steps. Experimental results demonstrate accurate detection of injected anomalies while suppressing false positives during normal operation, validating the effectiveness of combining unsupervised ML with rule-based filtering. AgileCopilot demonstrates the viability of embedding autonomous SRE intelligence into software engineering workflows.

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Site Reliability Engineering, Anomaly Detection, Isolation Forest, Generative AI, Root Cause Analysis, AIOps, Streamlit, Chaos Engineering, Incident Management, Machine Learning

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The present study aimed to compare explosive leg strength among students studying in rural, semi-urban, and urban schools. A total 275 of school students from the three different school were selected as participants. Explosive leg strength was assessed using the Vertical Jump Test, which is commonly used to evaluate the power of the lower limb muscles. Results: The calculated t-value as follow for boys (G1 = 0.838, G2 = 0.632, G3 = 0.837) and girls (G1 = 0.110, G2 = 0.047, G3 = 0.98) less than the table value at the 0.01 level. Conclusion: - There is no significant difference between the school students (girls and boys) in term of explosive leg strength (p < 0.01). The analysis of the study revealed no significance difference in explosive leg strength Among school students.

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physical fitness, explosive strength, vertical jump, school students, rural, semi-urban, urban, girls & boys.

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BACKGROUND: Knee osteoarthritis is common due to its weight-bearing function. Reduced hamstring and quadriceps flexibility impairs movement, increases injury risk, and limits mobility. Muscle Energy Technique (MET) improves range of motion and flexibility in a gentle manner. OBJECTIVE: To determine the efficacy of MET on hamstring flexibility and functional performance in patients with knee OA. METHODOLOGY: Thirty patients (40-60 years) were divided into Group A (MET + conventional, n=15) and Group B (conventional, n=15). Treatment was given 6 days/week for 3 weeks. Outcomes measured were Active Knee Extension (AKE), WOMAC, and NPRS. RESULTS: Both groups showed significant within-group improvement (p<=0.05). Between groups, Group A showed greater improvement: AKE (right) p=0.001, AKE (left) p=0.03, WOMAC p=0.03, and NPRS p=0.001. CONCLUSION: The result of the present study concluded that there was an effectiveness of the muscle energy technique on hamstring flexibility and functional performance in patients with OA knee, as well as there was also a reduction in pain in patients with OA knee.

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Hamstring, Muscle Energy Technique, Flexibility, AKE, WOMAC

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Due to the fast growth of automobiles and thescarcityofparkingspots,smartparking managementhasbecomeacrucialnecessity in contemporary urban settings. Conven- tional parking arrangements frequently re- sultintrafficjams,wastedtime,andtrouble locatingopenspaces.Thisprojectsuggests aDeepLearningBasedSmartParkingSys- tem that makes it simple for users to keep an eye on and reserve parking spaces in a variety of places, including shopping cen- ters,medicalfacilities,andofficebuildings. The system analyzes parking occupancy and dynamically initializes parking spaces for each zone using real-world parking da- tasets. The availability of slots can be shown by users, who can then choose and reservetheirchosentimeperiodfora certain amount of time. Additionally, the system automatically de- terminestheparkingpriceatasetrateof INR20perhourbasedonthedurationofpark- ing. In order to assist customers in finding appropriate parking spots quickly, the sys- tem also recommends the best available parkingspacesinsideeachzone.Thissmart parking management strategy increases userconvenience,decreasestrafficinpark- ing lots, and increases efficiency. The sug- gested method shows how automation and data-driven technology can help smart cit- ies manage parking more effectively.

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Smart Parking System, Deep Learning,ParkingSlotBooking,DataAna- lytics, Smart City, Parking Management

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Distributed Denial of Service (DDoS) attacks targeting UDP protocols continue to pose significant threats to network infrastructure, with traditional blocking-based defenses proving insufficient against sophisticated attack patterns. This paper presents a novel deception-based defense mechanism that employs dynamic destination mutation and decoy traffic diversion to protect servers from UDP flood attacks while gathering counter-intelligence on attackers. Unlike conventional approaches that rely solely on traffic filtering or rate limiting, our system operates at the gateway level to redirect malicious traffic to decoy systems, enabling continuous service availability while collecting valuable metadata about attack patterns. The proposed architecture implements real-time traffic monitoring, automated bot detection, and encrypted metadata collection without requiring payload inspection or endpoint trust assumptions. Experimental results demonstrate that our approach achieves 94% attack traffic diversion accuracy while maintaining legitimate service availability above 99.2%. This work contributes to the advancement of cyber deception techniques by introducing a practical, scalable solution for UDP DDoS mitigation that transforms passive defense into active intelligence gathering.

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DDoS, UDP Flood, Cyber Deception, Decoy Systems, Network Security, Traffic Diversion, Moving Target Defense

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Breast cancer, anxiety, fatigue, postmenopausal women, GAD-7, Fatigue Severity Scale

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In recent years, Artificial Intelligence (AI) and Blockchain have emerged as two of the most influential technologies transforming modern industries. AI focuses on enabling machines to mimic human intelligence and decision-making processes, while blockchain provides a decentralized and secure method for recording and storing digital information. When these two technologies are combined, they create new opportunities for improving transparency, security, and efficiency across various sectors. The integration of AI with blockchain allows organizations to process large datasets securely, automate decision-making, and improve trust in digital transactions. This paper examines the benefits of combining blockchain technology with artificial intelligence. It reviews existing research on how these technologies complement each other and highlights their applications in areas such as healthcare, finance, supply chain management, cybersecurity, and urban planning. In addition, the paper discusses technical challenges, privacy concerns, and future research opportunities associated with the integration of AI and blockchain technologies.

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Artificial Intelligence, Blockchain, Cybersecurity, Smart Contracts, Data Security

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Multi Commodity Exchange of India Ltd. (MCX) is the leading platform for commodity derivatives trading in India. Aluminium, with a great industrial demand in sectors such as construction and transportation, is actively traded on MCX. Analyzing the relationship between aluminium spot and related futures prices helps to understand how well futures prices reflect the underlying spot market. Thus, this study analyse the connection between the aluminium cash prices and related futures prices on MCX from 1st April, 2017 to 31st March, 2024. To achieve the objective, various techniques were applied including descriptive statistics, lag order selection criteria, unit root analysis, and the Johansen's co-integration. Findings from unit root analysis confirmed that the price series follow a first-order integration process, I(1) and the Johansen's co-integration analysis reveals a stable equilibrium link between the two aluminium price series in the long-term, suggesting that they move together over time despite short-term fluctuations.

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relationship, MCX, co-integration, aluminium, spot and related futures price.

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The rapid growth of e-commerce has transformed the way customers purchase products online. One of the most important features influencing customer satisfaction is the order tracking system. This study focuses on analyzing the customer perception of order tracking features in e-commerce applications with special reference to Tirupur City. The main objective of the study is to understand how customers view and use order tracking services provided by online shopping platforms. The research examines factors such as transparency, real-time updates, delivery status information, and reliability of tracking systems. Primary data were collected from customers through a structured questionnaire, and the responses were analyzed using statistical tools such as percentage analysis, ranking method, and chi-square test. The study aims to evaluate the effectiveness of order tracking features and their impact on customer satisfaction and trust. The findings reveal that most customers prefer applications that provide accurate and timely tracking updates. The study also highlights the importance of improving tracking transparency to enhance customer experience. Finally, the research provides suggestions for e-commerce companies to improve their tracking systems and strengthen customer relationships.

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Order Tracking, E-commerce Applications, Customer Perception, Delivery Status, Real-Time Tracking, Customer Satisfaction, Online Shopping, Tirupur City.

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Job and internship fraud is a growing concern on digital recruitment platforms, often leading to financial loss and exploitation of applicants. This paper presents an AI-based authenticity verification system designed to detect and flag suspicious job and internship postings. The proposed model leverages Natural Language Processing (NLP) techniques to analyze posting content, recruiter details, and linguistic cues, while machine learning classifiers are trained on datasets of genuine and fraudulent postings to identify anomalies. The system generates a reliability score and alerts users to potential risks, thereby ensuring a safer application process. Experimental results demonstrate that this approach significantly improves trust and security in online career ecosystems, providing a practical solution to the increasing problem of fraudulent employment opportunities.

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Job Authenticity Verification, Internship Fraud Detection, Machine Learning, Natural Language Processing, Online Career Platforms.

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As we all know investment is an immense concept. While this study will explore the investor perspective and awareness in choosing stock market as a main stream for their investment among various alternatives. In this prevalent locale there is numerous investment options are accessible to investors like investment in real estate, bullion, gold bars, fixed deposits etc., among these options stock market is an eye-catching path intended for investors to make their investment, owing to its massive augmentation over a period of time. The fundamental motive of this research seeks to scrutinize the inquisitiveness and comportment of working women professionals towards stock market. One of the considerable complications, we came across the survey is that there is an insufficient familiarity and practical knowledge among women professionals to take over their investment in stock market. This exploration assists us to realize ideology and views of working women professionals with respect to stock market.

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Stock market, Stock Exchange, Investment behavior, Awareness, Investor perception, Commerce Graduates

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Type 2 diabetes mellitus (T2DM) is a progressive metabolic disorder characterized by insulin resistance, impaired insulin secretion, and chronic hyperglycemia, leading to severe microvascular and macrovascular complications. Among the various pharmacological classes used for the management of T2DM, biguanides--particularly metformin--remain the cornerstone of first-line therapy due to their efficacy, safety, and cardiovascular benefits. Beyond metformin, increasing research interest has been directed toward the synthesis and development of novel biguanide derivatives with improved pharmacological profiles and reduced adverse effects. This comprehensive review summarizes recent advances in the synthesis, chemical characterization, and biological evaluation of biguanide derivatives developed for the treatment of T2DM. Emphasis is placed on synthetic strategies, physicochemical and spectroscopic characterization techniques, structure-activity relationship (SAR) insights, and mechanisms of antidiabetic action. In addition, emerging biguanide-based hybrids and multifunctional derivatives are discussed, along with current challenges and future perspectives in biguanide drug development. This review aims to provide a consolidated reference for researchers engaged in medicinal chemistry and antidiabetic drug discovery.

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Biguanide; Metformin; Type 2 diabetes mellitus; Synthesis; Characterization; Antidiabetic agents

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Clinically patient presents signs and symptoms to the physician. These are a part of Samprapti. Analyzing the samprapti becomes important to decide the treatment. Same clinical presentations can be a part of different samprapti as emphasized in Ayurveda. Frozen shoulder, which is a common condition with restricted movements of shoulder joint, which occur in later stages of Adhesive Capsulitis. The typical symptoms comprise passive and active range of motion restriction, depending on the stage and severity; the condition is self-limiting, interfering with activities of daily living, work, and leisure activities. Patients presenting with shoulder joint pain and restricted movements, on analyzing the clinical condition can belong to different samprapti. Apabahuka is one such clinical condition wherein there is pain and restricted movements of the upper limb. Sopham is another clinical entity which can also be considered as a part of any kind of inflammatory responses. Two different samprapti with the same clinical presentation are analyzed here to understand the applicability of nidana panchaka in understanding the disease. Clinically patient presents signs and symptoms to the physician. These are a part of Samprapti. Analyzing the samprapti becomes important to decide the treatment. Same clinical presentations can be a part of different samprapti as emphasized in Ayurveda. Frozen shoulder, which is a common condition with restricted movements of shoulder joint, which occur in later stages of Adhesive Capsulitis. The typical symptoms comprise passive and active range of motion restriction, depending on the stage and severity; the condition is self-limiting, interfering with activities of daily living, work, and leisure activities. Patients presenting with shoulder joint pain and restricted movements, on analyzing the clinical condition can belong to different samprapti. Apabahuka is one such clinical condition wherein there is pain and restricted movements of the upper limb. Sopham is another clinical entity which can also be considered as a part of any kind of inflammatory responses. Two different samprapti with the same clinical presentation are analyzed here to understand the applicability of nidana panchaka in understanding the disease.

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Frozen shoulder, Apabahuka, Samprapthi, Nidana Panchaka

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The present research paper is entitled as a study on the effect of family environment on the academic achievement of senior secondary boys and girls. Objectives: 1) to find the effect of family environment on the academic achievement of senior secondary boys and girls. Hypotheses: 1) there is no significant effect of family environment on the academic achievement of senior secondary boys and girls. Methodology: The researcher has employed descriptive survey method in this research. Academic achievement is taken the dependent variable while family environment is the independent variable in this study. For the present study, 600 senior secondary students from District Haridwar were selected using the random sampling technique. Family Environment Scale developed by Dr. Harpreet Bhatia and Dr. N.K. Chandra was used for the collection of data. Academic achievement has been measured in terms of the percentage of the marks obtained by the students in class-10. Collected data was analyzed using two-way analysis of variance. Findings: Gender had a significant impact on academic achievement, with girls achieving higher than boys. A cohesive environment significantly influenced achievement, as students with high cohesion performed best. An expressive environment also had a significant positive influence, with students from highly expressive families showing the highest achievement. A conflicting environment significantly affected achievement, with students from low-conflict environments performing better. Accepted and caring environments significantly enhanced achievement, with high levels showing better performance. Independent environments significantly influenced achievement, where low independence showed higher overall achievement. Active recreational-oriented, organized, and controlled environments all significantly influenced academic achievement, with high levels leading to better performance. Overall, family environment significantly influenced academic achievement, with students from good family environments performing best.

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Family Environment, Academic Achievement, Senior Secondary Boys and Girls.

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A Neuro fuzzy method for resolving Multi-level linear programming issues is presented in this work. This method typically solves a multilevel programming problem in fewer rounds without making the underlying difficulties more complex. The suggested method is compared with a number of methods in the literature using numerical examples in next paper.

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Computers, Multilevel linear and non linear , artificial intelligence, artificial neural networks, and neuro-fuzzy logic, multilayer, input output

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Healthcare businesses globally encounter escalating issues associated with personnel shortages, excessive workloads, and rising burnout among healthcare practitioners. These problems are especially significant in inpatient departments (IPDs), where ongoing monitoring and coordinated care are vital for patient safety. This initial study investigates workforce management strategies, burnout rates, and their perceived effects on patient safety within the inpatient departments of a multispecialty hospital. A descriptive research method was employed utilizing primary data gathered via a structured questionnaire from 300 inpatient department personnel. Percentage analysis was utilized to interpret the data. The initial data suggest that workload pressure, personnel shortages, and shift scheduling challenges substantially contribute to stress and burnout among healthcare professionals. Participants also saw a significant correlation between burnout and diminished patient safety. The study indicates that effective workforce management techniques, including optimal staffing, equitable shift scheduling, supportive work environments, and employee wellness initiatives, are crucial for mitigating burnout and improving patient safety.

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Managing the workforce, dealing with burnout, the inpatient department, patient safety, and healthcare staff.

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The socio-ecological and physical functions of public parks in urban areas are multifaceted and crucial to the livability of cities. The study assessed three public parks in Pune, based on a holistic evaluation framework covering eight key areas: Access and Linkages; Design and Site Plan; Environmental and Ecological Aspects; Social and Leisure Elements; Safety and Security; Maintenance and Administration; Financial and Cultural Relevance; and Inclusivity. A number of parameters and indicators were used in each category such as Entry Points, Connectivity, Inclusivity, Spatial Organization, Wayfinding, Biodiversity, Green Cover, Water Management, Community Participation, Lighting, Surveillance, Cleanliness, Infrastructure, Property Value, Local Economy Boost, Accessibility for All, etc. Visual research methodology along with spatial analysis and documentation was done to evaluate the parks. The comparative analysis technique facilitated the ascertainment of best practices. The study suggests that a holistic evaluation of public parks using multidimensional measures can be of practical help to city officials, planners and community residents. These types of analyses can contribute to better decision-making in the prioritization of investment, enhancement of park performance, promotion of equitable, sustainable and vibrant urban green spaces in the fast-growing urban scenario.

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public parks, spatial, urban

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Human beings are the most vital assets of any organization, and their effective management is essential for productivity and profitability. This study investigates the processes of manpower optimization and rightsizing within the steel industry, focusing on the Voluntary Retirement Scheme (VRS). It evaluates the organizational objectives behind these schemes, the factors influencing employee decisions to separate early, and the current status of their rehabilitation.

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Manpower optimization, Early separation, Rehabilitation, Effectiveness, Employment Programme, Getting them, Preparing them, Activating them and Keeping them

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Economic reform of most of the developing economies, particularly following the late twentieth century, involves trade liberalization on a large scale. Nations have attempted to stimulate economic growth, enhance exports and stimulate foreign investment by lowering tariffs, removing trade barriers and integrating into the global market. However, even though trade openness has contributed to the growth of the economy, its role in distributing incomes remains a controversial debate. Among the emerging economies, there have been rising cases of economic growth with the rising income inequality posing a question of whether globalization gains are equally shared with society.

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Economics and Trade

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Digital governance has emerged as a transformative force in India's public administration, reshaping the relationship between the state and citizens through technology-driven service delivery. Over the last two decades, India has adopted several digital initiatives such as the Digital India programme, Aadhaar-based digital identity, Unified Payments Interface (UPI), and digital platforms for welfare distribution. These initiatives have significantly improved the transparency, efficiency, and accessibility of government services. However, challenges such as the digital divide, cybersecurity risks, data privacy concerns, and institutional capacity constraints continue to hinder the full potential of digital governance. This article examines the evolution of digital governance in India, analyzes its current landscape and major initiatives, identifies key challenges, and explores prospects in the context of emerging technologies such as artificial intelligence, blockchain, and digital public infrastructure. The study highlights that while digital governance has transformed public service delivery, its success in the future will depend on inclusive digital infrastructure, robust data protection frameworks, and improved digital literacy among citizens and government officials.

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Digital Governance, DBT, Digital India, Digital Public Infrastructure, NeGP

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