Volume 13 | Issue 5 |

 Abstract

Practically speaking, there is increasing use of electronic communication and availability of students in educational institutions, which has created a number of options for improving student-teacher interactions. One such solution is the Student-Teacher Booking Appointment System (STBAS), which offers scheduling, timeslot management, real-time information, and notifications on appointments. This paper explores current literature on students-teacher appointment systems, with an eye toward their functionalities, benefits, and challenges. Software for scheduling has evolved in recent years. Most scheduling-related issues are now addressed on a digital context that automates and streamlines appointment management. Functionalities including a userfriendly interface, flexible scheduling slots, real-time update notifications, and notifications for changes to reservations are discussed. The system increases decision support in terms of decisions regarding how to allocate students' time, and allows scheduling conflicts to be avoided. The paper also mentions various benefits associated with the use of the system accessibility, reduction of administrative overhead and personalization of interactions are highlighted. Issues such as technical limitations, scalability of the system and concerns for privacy also are considered. The paper synthesizes the findings from different studies.

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Practically speaking, there is increasing use of electronic communication and availability of students in educational institutions, which has created a number of options for improving student-teacher interactions. One such solution is the Student-Teacher Booking Appointment System (STBAS), which offers scheduling, timeslot management, real-time information, and notifications on appointments. This paper explores current literature on students-teacher appointment systems, with an eye toward their

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Creative Commons Attribution 4.0 and The Open Definition

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People who experience social inferiority complex consider Dalit literature as a symbol of self-respect. Whoever writes Dalit literature can consider it as Dalit literature as long as it does not deviate from its basic nature and objectives.Writing Dalit literature is a social act of consciousness and a responsible act of social transformation. All the social movements that have emerged in Telugu literature have tried to maintain their existence.As part of that, the Dalit movement also marked the beginning of the emergence of a struggle for existence.

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Dalit poetry of Nalgonda district - material diversity

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT Background: O'Donoghue's triad or the so-called "Unhappy Triad" is an extremely debilitating condition. It mainly affects athletes, excluding them for a long time from their sports activities. As sport participation increases globally, so will injury-related risks. The process used to determine return-to-sport following injury is vital to future sport participation and injury prevention. Early specialization along with poor management of sport participation causes an increase in injury risk and potential long-term health consequences for youth athletes. Dynamic instability of the knee joint is restored over a long period of time. For functional assessment and monitoring of the dynamics of recovery and rehabilitation intervention, it is necessary to make an analytical selection of a test battery from functional indicators and tests corresponding to the dysfunctions of the operated knee. Objective: The purpose of this study is to develop a diagnostic system for functional assessment of patients after surgical treatment of the O'Donoghue Triad for assess sport-specific functional performance. Previous injury is a common intrinsic risk factor for new injuries. Identifying functional performance deficits, defined by return-to-sport criteria, minimizes these risk factors and provides athletes with guidelines to return safely to sport. Methodology: A literature review was completed using numerous databases, where 22 articles were included in this commentary. Of the 22 articles using functional performance measures for return-to-sport criteria, 6 were specific to youth, 12 had mixed populations of adults and youth, and 4 were normative samples for specific youth populations. Conclusions: Due to the inconsistencies in terminology, definitions, and standardization of clinical assessment tools, it seems necessary to create a comprehensive functional performance test battery for the lower extremity that can be used as return-to-sport criteria.

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Keyword: unhappy triad; O'Donoghue's triad; sports injuries, agility, collegiate athlete, functional performance test, return-to-play

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid development of digital technology has changed the way data is communicated, worked and stored, as well as putting systems under more cyber threats. This research paper examines the developing landscape of cybersecurity and focuses on the most important threats, such as malware, phishing, ransomware, and advanced continuous threats (APTS). The complexity of ensuring a cloud environment, guarantees user awareness, and in today's interconnected world, individuals, organizations and government cybersecurity takes into account the weaknesses of zero-day sensitivity as well. By analyzing current trends and case studies, this article should highlight the importance of a proactive and adaptive approach to cybersecurity in the digital age.

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Cyber security, Cyber Threats, Network Security, Data Protection, Digital Forensics.

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Creative Commons Attribution 4.0 and The Open Definition

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Migraine is a Chronic Neurological Disorder Characterized by recurrent, Paroxysmal, Severe, incapacitating, Unilateral headaches, with vomiting and Preceded by the visual or sensory disturbances. It significantly affects the quality of life and requires a comprehensive approach for effective management. In Homeopathy, migraine treatment follows an individualized and holistic approach, addressing not only the symptoms but also the root cause. This article explores the etiology, pathophysiology, clinical presentation, and classification of migraine, along with this the Homoeopathic approach based on constitutional and acute remedies. Additionally, it highlights the Miasmatic Perspective and the importance of an integrative treatment plan, including lifestyle modifications, stress management, and counselling. By understanding the migraine through a homoeopathic and integrative lens, practitioners can provide long -term relief and improve patient outcomes.

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Migraine, Homeopathy, Homeopathic medicines, ICHD-3, 5-HT, Histamine and Serotonin, HIS

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Predicting employee performance is essential for organizations striving to improve productivity and align their workforce with long-term goals. Machine learning offers powerful tools to evaluate and forecast employee outcomes based on historical and behavioral data. In this implementation, a classification-based approach is adopted using the "INX Future Inc Employee Performance" dataset, which contains key employee attributes relevant to performance metrics. Various supervised learning algorithms were utilized, including Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest, and Naive Bayes classifiers. Data preprocessing and model serialization were handled using the Pickle module to facilitate deployment and reuse of trained models. Each algorithm was evaluated based on its predictive accuracy, with Naive Bayes emerging as the most effective, achieving an accuracy of 82%. This suggests that Naive Bayes, despite its simplicity, is well-suited for handling categorical and probabilistic data common in employee performance evaluations. The outcome demonstrates the potential of integrating machine learning into human resource management systems for efficient performance tracking and decision-making. By leveraging structured data and predictive analytics, organizations can enhance their talent management strategies and proactively address areas requiring improvement.

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Employee Performance Prediction, Machine Learning Classification, Naive Bayes Classifier, Predictive Analytics, Human Resource Optimization, Model Deployment Using Pickle.

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Creative Commons Attribution 4.0 and The Open Definition

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Campus Heaven is an AI-powered student accommodation and services hub built using Flask as its core web framework, SQLite as the backend storage engine, and lightweight, rule-based logic to implement natural language understanding and review analysis features. The platform supports student interaction with various service categories including Accommodations, Gyms, Libraries, and Meal Services. It provides user-friendly tools for students to browse and evaluate available listings, submit open-ended reviews, and receive AI-generated responses to their concerns through an integrated chatbot. All student reviews are logged and processed using a sentiment and sarcasm detection mechanism. Chat interactions are classified into defined support categories using a similarity-based intent-matching approach. Administrative users can view detailed analytics through dashboards that visualize user sentiments and support issues. These insights are also exportable via a downloadable PDF report, providing a complete and accessible summary of service performance and user engagement trends.

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AI Chatbot, Student Services, Sentiment Analysis, Accommodation System, Flask, SQLite

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid expansion of digital communication has made cyberspace a breeding ground for malicious activities. Detecting these threats in real-time is challenging due to the sheer volume and complexity of data. Natural Language Processing (NLP) offers a sophisticated approach to cyber threat detection by analyzing unstructured text from diverse sources, including social media, forums, and cybersecurity reports. This study presents an in-depth exploration of NLP techniques used for threat detection, covering data pre-processing, model selection, and evaluation. The results demonstrate the efficiency of NLP models in identifying potential threats, highlighting their critical role in enhancing cybersecurity.

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Natural Language Processing, Cyber Threat Detection, Machine Learning, Cyber Security, Text Analysis

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Creative Commons Attribution 4.0 and The Open Definition

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Lumpy skin disease (LSD) poses a significant threat to cattle farming, causing economic losses due to reduced productivity and hide damage. As of 2022, more than 67,000 cattle had died across the country. States like Rajasthan and Gujarat were heavily affected, with over 25,000 cases reported in Rajasthan alone and more than 37,000 cases in Gujarat. This viral disease, primarily transmitted by biting flies, necessitates early detection for effective management. In this project, we propose a novel approach for early detection of LSD in cattle using deep learning techniques applied to image analysis. Our methodology involves gathering a diverse dataset of cattle images, including both healthy and infected animals of various breeds, ages, and environmental conditions. The proposed healthcare system helps the farmers to check the early lumpy disease in cattle. Also, the AI based approach using multiple deep learning algorithms, including CNN, ResNet, and EfficientNet for disease detection can make the disease detection. Second stage we are providing the recommendation system for the treatment of cattle and providing the roadmap how the treatment will be and which hospital we can prefer based on the location. We are creating the system, where we employ advanced techniques for lumpy skin disease (LSD) management can involve a combination of traditional veterinary approaches and modern technologies. Here are some advanced techniques that can be employed. This proposed system will help farmer society who are suffering from the financial losses due to the diseases in cattle .The project provides the proper disease detection and recommendation system for the treatment by adopting the one health approach to lumpy skin disease management, involving collaboration between veterinary professionals, public health experts, and farmers.

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 Keywords

Lumpy Skin Disease (LSD), Deep Learning, Disease Detection, Rural Livelihoods, Convolutional Neural Network, EfficientNet V2B0, Farmer Recommendation System

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Creative Commons Attribution 4.0 and The Open Definition

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This study examines the skill gap in the Hazaribagh and Ramgarh districts of Jharkhand, India, focusing on the discrepancy between workforce capabilities and industry demands. The research utilizes secondary data from sources such as the National Skill Development Corporation (NSDC) and Census 2011, to assess current and projected skill requirements across 24 high-priority sectors for the period of 2012-2022. The analysis reveals significant demographic and economic differences between the two districts, with Hazaribagh showing a larger population and workforce, as well as stronger growth across all sectors, particularly the tertiary sector. Despite these positive indicators, both districts face critical deficits in skilled and semi-skilled labor, with Ramgarh exhibiting a higher shortfall. Conversely, there is a surplus of minimally skilled workers in both districts, potentially leading to underemployment. The study highlights the urgent need for targeted skill development programs and economic diversification, particularly in Ramgarh, to align workforce capabilities with industry needs. The findings underscore the importance of addressing skill gaps to foster long-term economic growth and competitiveness in these regions.

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A Comparative Study of Skill Gap between Hazaribagh and Ramgarh District of Jharkhand

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