International Journal of Innovations in Science, Engineering And Management
IJISEM International Journal of Innovations in Science, Engineering And Management A Peer-reviewed Scholarly Indexed Quarterly Journal International Journal of Innovations in Science, Engineering, and Management (IJISEM) is an open-access publication overseen by IJISEM Journals. It is dedicated to fostering the interests of emerging and promising writers. IJISEM endeavors to transcend geographical boundaries by welcoming contributions from professionals and academics worldwide, not limited to India. We thus adopted the term International as our motto and used it in the title of our journal. We are dedicated to fostering innovation and excellence across scientific, engineering, and management disciplines through our commitment to sharing knowledge. The publication focuses on research and intellectual viewpoints in order to achieve this goal. Realistic analysis, interdisciplinary/applied/methodological, empirical evidence production and utilization, critical viewpoint development and policy building work are all welcome in achieving this goal. IJISEM aims to provide a platform for doctoral researchers to showcase their investigations and disseminate their research findings and knowledge to a wider audience. IJISEM International Journal of Innovations in Science, Engineering and Management Title IJISEM International Journal of Innovations in Science, Engineering And Management Frequency Quarterly (July, October, January and April) ISSN 2583 – 7117 Publication Format Online Chief Editor Dr. Rajesh Gupta Publisher Yogesh Sharma, M.Tech (Industrial Design) Subject Multidisciplinary Published by IJISEM Journals Starting Year 2022 E-Mail editor@ijisem.com Mobile No (+91) 70893666889 Mobile No (+91) 9981622288 Publishing Body AG Publishing House Language Multiple Languages Copyright AG Publishing House Website http://www.ijisem.com/ Address IJISEM Journals 57-First Floor, Susheela Bhawan, Priyadarshini Phase-3, near Meenakshi Planet City, Bagmugaliya, Bhopal, Madhya Pradesh 462043
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A Comprehensive Review on Phytochemical and Pharmacological Properties of Alstonia scholaris
In traditional therapeutic systems, Alstonia scholaris is commonly employed. It is used to cure "diarrhoea, malaria, asthma, fever, epilepsy, skin disorders, snake bites", and other conditions in India, Thailand, China, Malaysia, the Philippines, Africa, Australia, and other places because of its abundant natural active components. This review highlights the phytochemical richness and pharmacological potential of Alstonia scholaris (“Saptaparni”), covering its traditional uses, bioactive constituents, and therapeutic activities including analgesic, anti-inflammatory, antibacterial, and anticancer effects. Despite promising in-vitro and in-vivo findings, limited clinical trials and mechanistic data remain major gaps. Further research is essential to validate safety, isolate active compounds, and advance its therapeutic applications.
Copyright (c) 2025 Nilesh Mohan Mishra, Khooshbu chouhan, Satkar Prasad, Shailesh Ghatuary, Priyanka More https://creativecommons.org/licenses/by-sa/4.0
A Comprehensive Review on Deep Learning Methods in Medical Image Analysis
Deep learning (DL) has transformed medical image analysis over the past decade, enabling automated, accurate, and scalable solutions for detection, classification, segmentation, and synthesis of medical images. This review synthesizes the evolution of major deep learning architectures including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), and Transformers and focuses on their specific applications in medical imaging modalities such as X-ray, CT, MRI, ultrasound, and histopathology. We discuss training strategies, data challenges, evaluation metrics, and clinical translation barriers. Finally, we present comparative tables, figure placeholders for common architectures, and an outlook on emerging directions including self-supervised learning, federated learning, and foundation models in medical imaging. The review includes key works from 2012–2025 to provide both foundational and contemporary context.
Copyright (c) 2025 Lalit Kumar Rawat, Anil Kumar https://creativecommons.org/licenses/by-sa/4.0
High-Frequency Interactions Between Market Volatility and Price Movements: Intraday Asymmetry Between India Vix and Nifty 50 Through Technical Lenses
This paper examines the intraday relationship between the Nifty 50 index and the India Volatility Index (India VIX) over a five-day trading period from 13th to 17th October 2025, using 15-minute OHLC data. Employing an integrated framework that combines technical candlestick analysis and statistical modelling, the study explores short-horizon volatility dynamics, sentiment behaviour, and market efficiency within the Indian equity market. The candlestick analysis reveals recurring reversal and continuation patterns—such as hammers, marubozu, and engulfing formations—closely associated with shifts in implied volatility. Regression and VAR results confirm a significant negative contemporaneous relationship between Nifty returns and VIX changes, with volatility responding almost instantaneously to price shocks. Evidence of asymmetric volatility behaviour demonstrates that India VIX reacts more sharply to market declines than to rallies, reflecting investor loss aversion. The findings validate the predictive value of traditional technical patterns in high-frequency contexts and underscore the role of India VIX as an effective intraday sentiment indicator. This research contributes to the literature on market microstructure and behavioural finance by linking visual market signals with econometric evidence in an emerging market setting.
Copyright (c) 2025 Dr. Tuhin Mukherjee, Subhrajyoti Mandal https://creativecommons.org/licenses/by-sa/4.0
Accurate PM2.5 Prediction Using Machine Learning Ensembles for Sustainable Smart Cities
Particularly in India, where cities like Delhi suffer from serious air quality problems, air pollution is a major obstacle to urban sustainability and requires precise prediction models to help smart city projects. Using the Central Pollution Control Board's Air Quality Data in India (2015–2020) dataset, this study, Air Quality Prediction for Sustainable Smart Cities using Machine Learning, creates a reliable framework for predicting PM2.5 concentrations across 26 Indian cities. The dataset was optimised for modelling by careful preparation, which included one-hot encoding of city variables, IQR-based outlier treatment, SimpleImputer for missing values, and exploratory data analysis to find trends. Support Vector Regressor, Gradient Boosting Regressor, Random Forest Regressor, and Extra Trees Regressor were the four machine learning models that were trained. A hybrid ensemble that combined Random Forest and Extra Trees through a voting mechanism performed better (R2 = 0.9818, RMSE = 11.8222 µg/m³). The model showed resilience in a variety of metropolitan settings, outperforming baseline models by 0.3 to 11.88% in R2 values for Hyderabad, Bengaluru, Kolkata, and Delhi. With the potential for worldwide use, this system facilitates real-time air quality management by providing precise AQI derivation and visualisation dashboards, improving environmental sustainability, urban planning, and public health in smart cities.
Copyright (c) 2025 Aesha Bhardwaj, Sanjay Silakar, Rajeev Pandey, Jashwant Samar https://creativecommons.org/licenses/by-sa/4.0
Exploring the role of Innovative Work Orientation in Healthcare Landscape through a narrative lens: A Glimpse
Background: Institutions around the globe are struggling with the inconsistent and unpredictable complexities of a microenvironment. It is essential to plan for uncertainty, adopt creative strategies to reduce risks. In recent years, healthcare system has become increasingly complex, necessitating creative approaches to enhance patient well-being and service provision. Healthcare organizations need to adopt innovative work practices to meet ongoing requirements of their clients. Innovative orientation is a key strategy to ensure excellence and maintaining the competitiveness for today's businesses. Therefore, employees play an important role to exhibit innovative orientation in the context of healthcare companies. Healthcare professionals engaged currently in health sector have often narrated issues related to lack of integration of objectives of various stakeholders including patients, healthcare providers, insurance companies, government and policymakers, pharmaceutical companies and research institutions as a challenge for effective delivery of healthcare services. Objective: The purpose of the current study is to provide a brief overview of all the prior studies on innovative work orientation especially in context of healthcare organization. Methods: The authors meticulously analyse the phenomenon by conducting a thorough review on innovative orientation among professionals derived from existing literature of journal articles, both published and unpublished reports, periodicals, books, theses, and pertinent publications gathered from varied worldwide information sources. Results: The findings of the research indicate that the fields of health care science services are somewhat unexplored and less studied especially in the domain of innovative behaviour. The research indicates a stronger association "innovative behaviour" and "innovation." Keywords: Innovation, Innovative work orientation, creativity, Support for creativity, healthcare, healthcare professionals
Copyright (c) 2025 Anjana gupta, Anshu Yadav https://creativecommons.org/licenses/by-sa/4.0
Understanding of Water Purification Methods through Chemistry among Urban Households
The chemistry-based water purification procedures commonly understood by urban households are the focus of this research. From 285 participants, we were able to compile demographic data and impressions assessed using a five-point Likert scale via a standardised questionnaire. Proper maintenance and operation of purification equipment, level of awareness of the chemistry involved, selecting a home purification technique, and chemical understanding of procedures were the four primary aspects evaluated in the study. Education considerably affects awareness, although results show that individuals have a reasonable level of chemical knowledge. The choice of purification processes was shown to be strongly correlated with chemical understanding, and the right maintenance practices were discovered to be impacted by chemical knowledge. The findings stress the need for more education and publicity to enhance water management in the home. The need of chemistry literacy in urban water safety procedures is further illuminated by this research.
Copyright (c) 2025 Jaidev Kumar https://creativecommons.org/licenses/by-sa/4.0
Phytochemical and wound healing potential of ethanolic extract of Nymphaea alba
The present study evaluates the effectiveness of the ethanolic extract of Nymphaea alba in wound healing and administers phytochemicals using "an excision and incision wound model on Wistar strain albino rats". Plant extracts have a higher phytoconstituent concentration, according to “phytochemical screening”. "Phenolic compounds, alkaloids, carbohydrates, flavonides, glycosides, and tannin" were all detected in the ethanolic extract of Nymphaea alba. "The tensile strength of the healed wounds" was assessed using the incision wound model, and the influence of wound healing was assessed using the excision wound model, which took into consideration the epithelialisation time and the percentage of wound closure. Wistar albino rats' dorsal surfaces were subjected to excision and incision wounds. Four groups of six rats each were randomly selected from among them. Group I served as the control group, receiving no treatment other than a basic ointment. Group II was used with framycetin sulphate cream (Soframycin, Aventis) and was regarded as the standard group. Group III was given EENA 2% (w/w), while Group IV was given EENA 5% (w/w). These were considered test groups. Compared to the usual control group, Nymphaea alba significantly rises the percentage of wound contraction, reduces its duration of epithelialisation, and increases the tensile strength of the skin in all forms. In view of the positive results, it may be feasible to conduct additional research to evaluate the efficacy of various wound models.
Copyright (c) 2025 Satkar Prasad, Shyam Bahadur, Sailesh Ghatuary https://creativecommons.org/licenses/by-sa/4.0
Traditional Herbal Medicine in the Management of Chronic Diseases
Traditional herbal medicines have been utilised for thousands of years to treat chronic ailments, but there are little scientific research on their knowledge, belief, and application. Participating participants' knowledge, belief in the efficacy, perceived safety, and use of herbal medicines for chronic illness management are the focus of this research. A total of 227 participants were asked to fill out a structured questionnaire that included questions about their demographics and statements that could be rated using a five-point Likert scale. Descriptive statistics showed a broad belief in the therapeutic effects of popular medicinal herbs and a reasonable level of knowledge with them. The frequency of herbal medicine use is significantly impacted by more knowledge and a larger belief in its efficacy, according to ANOVA and correlation studies. Perceived safety, on the other hand, greatly predicts the desire to continue using the medicine. The research results show that herbal medicines may be a useful supplementary intervention and call attention to the necessity of educational campaigns to promote informed use. The research sheds light on how to safely combine current methods of managing chronic diseases with traditional therapies.
Copyright (c) 2025 Madhu Dubey Swarnkar https://creativecommons.org/licenses/by-sa/4.0
Impact of GST on Household Expenditure in Madhya Pradesh
This study examines the multifaceted impact of the Goods and Services Tax (GST) on household expenditure in Madhya Pradesh through a primary, survey-based approach. Utilizing a structured questionnaire administered to a diverse sample of households across various income levels and geographical regions, this paper analyzes changes in consumer spending patterns before and after the implementation of GST. The findings reveal a significant, positive effect on household budgets due to the recent rationalization of GST rates, particularly on essential goods, personal care products, and consumer durables. While the reforms have made a wide range of products more affordable, the analysis also highlights the subtly regressive nature of the GST, where the tax burden on lower-income groups remains disproportionately high relative to their consumption. The study concludes that while GST has successfully streamlined the tax structure and stimulated domestic consumption, there is a continued need for targeted policy interventions to further enhance the system's progressivity and ensure a more equitable distribution of the tax burden across all segments of the population. The introduction of the Goods and Services Tax (GST) in India has significantly impacted household expenditure, primarily by altering the prices of a wide range of goods and services. A survey-based paper on this topic would investigate how the GST regime, particularly recent rationalization efforts, has affected consumer spending, focusing on different income groups and product categories.
Copyright (c) 2025 Sangita Deota, Saurabh Kumar Sahu https://creativecommons.org/licenses/by-sa/4.0
Software Bug Prediction Using Machine Learning Algorithms: An Empirical Study on Code Quality and Reliability
This study examines the effectiveness of a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model for predicting software bugs, with the objective of improving code quality and dependability. The research leverages the JM1 dataset from the PROMISE Software Engineering Repository and utilizes sophisticated preprocessing approaches, including Borderline-SMOTE, SMOTETomek, RobustScaler, Yeo-Johnson transformation, and Recursive Feature Elimination, to mitigate class imbalance and feature redundancy. The CNN-LSTM model attained a validation accuracy of 98.10%, a precision of 91.42%, and a recall of 99.53%, exhibiting a minimal false negative rate and indicating great sensitivity in detecting defect-prone modules. The results underscore the model's capacity to identify spatial and sequential patterns in software metrics, providing a reliable instrument for early fault identification. This work enhances software engineering by confirming deep learning's efficacy in defect prediction, offering practical insights for developers, and delineating future research avenues for cross-project generalization and model optimization.
Copyright (c) 2025 Elavarasi Kesavan https://creativecommons.org/licenses/by-sa/4.0
The Application of Artificial Intelligence in Human Resource Management: Evidence from Mid-to-Large Indian Enterprises
This survey-based study examines the adoption, use cases, benefits, and risks of artificial intelligence (AI) across human resource management (HRM) functions in India. Using responses from 412 HR leaders spanning mixed industries and mid-to-large enterprises, we find strong momentum in AI-augmented recruitment, HR analytics, and learning & development, alongside measured caution regarding data privacy, bias, and explainability. We provide descriptive statistics, two figures on adoption and perceived risks, and practical recommendations for Indian HR leaders to achieve responsible and value-accretive AI at scale.
Copyright (c) 2025 Sangita Deota, Rajesh Sahu https://creativecommons.org/licenses/by-sa/4.0
व्यावसायिक शिक्षा और कौशल विकास के लिए शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता पर एक तुलनात्मक अध्ययन
यह शोध पत्र भोपाल व्यावसायिक शिक्षा और कौशल विकास कार्यक्रमों की प्रभावशीलता निर्धारित करने में शिक्षक शिक्षा रणनीतिक रूप से महत्वपूर्ण है। वर्तमान अध्ययन का उद्देश्य भोपाल में बी.एड. विद्यार्थियों के बीच व्यावसायिक शिक्षा और कौशल विकास के लिए विकसित विभिन्न शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता की तुलना करना है। अध्ययन में भोपाल के 200 पुरुष और महिला बी.एड. विद्यार्थियों के नमूने ने भाग लिया। अध्ययन शैक्षणिक ज्ञान, व्यावहारिक कौशल और व्यावसायिक शिक्षण के लिए सामान्य तत्परता पर इन कार्यक्रमों के प्रभाव की सीमा का मूल्यांकन करता है। मात्रात्मक सर्वेक्षण को शामिल करते हुए सर्वेक्षण-पद्धति दृष्टिकोण को अपनाते हुए, अध्ययन ने पाठ्यक्रम डिजाइन, शिक्षण पद्धतियों और व्यावहारिक प्रशिक्षण पर प्रशिक्षु धारणाओं की जांच की। विभिन्न शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता की तुलना करने के लिए सांख्यिकीय उपकरणों का उपयोग करके डेटा का विश्लेषण किया गया। परिणाम बताते हैं कि भोपाल में बी.एड. छात्रों के बीच व्यावसायिक और कौशल विकास पर शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता की जांच की, जो पुरुष और महिला दोनों छात्रों द्वारा सामना की जाने वाली जागरूकता और चुनौतियों के संबंध में है। विश्लेषण ने जागरूकता के स्तर और कथित चुनौतियों के बीच कोई सांख्यिकीय रूप से महत्वपूर्ण अंतर नहीं दिखाया, जिसका अर्थ है कि वर्तमान शिक्षक शिक्षा कार्यक्रम छात्रों के लिए व्यावसायिक पहलुओं पर पर्याप्त रूप से विचार नहीं कर सकते हैं। इस प्रकार, भावी शिक्षकों को अपने छात्रों में व्यावसायिक कौशल और जागरूकता प्रदान करने के लिए प्रशिक्षित करने के लिए पाठ्यक्रम, व्यावहारिक प्रशिक्षण और सहायता प्रणालियों में सुधार की आवश्यकता अनिवार्य हो जाती है। लक्षित सुधारों के साथ, शैक्षणिक संस्थान इस प्रकार बी.एड. उत्तीर्ण छात्रों को संपन्न नौकरी बाजार के लिए तैयार करने में सक्षम होंगे, जिससे समग्र रूप से व्यावसायिक शिक्षा के सुधार में सहायता मिलेगी। वर्तमान अध्ययन के निष्कर्ष नीति निर्माताओं, शिक्षकों और व्यावसायिक शिक्षक शिक्षा की गुणवत्ता और प्रासंगिकता में सुधार करने में रुचि रखने वाले संस्थानों के लिए मूल्यवान हैं।
Copyright (c) 2025 नीलम सिंह https://creativecommons.org/licenses/by-sa/4.0
Thermal Comfort Analysis in Dormitory Room by Combined MVHR-Fan Coil
Low-energy-demand buildings are increasingly using "mechanical ventilation with heat recovery (MVHR)" applications to improve thermal comfort and reduce ventilation energy loss. MVHRs are often used in conjunction with an additional air heater to satisfy the need for room heating in retrofitted buildings. Therefore, it is crucial to assess how MVHR and heat emitters interact and how this affects the features of indoor airflow. In this study, the effects of a combination MVHR-fan-coil unit in the heating phase on thermal comfort parameters in a retrofitted room are investigated via "a computational fluid dynamic (CFD)" simulation. Numerical simulation results allow for the assessment of indoor thermal comfort as well as the resolution of the fan coil and MVHR interactions. Additionally, investigate the turbulent airflow characteristics in winter and summer season. The result indicate that relocate the fan coil position from left side to middle of the external wall increases the room temperature. Installing the inlet vent in ceiling shows a no changes in the room temperature. It observed that Case 2 exhibited the highest temperature inside the room at 23.3 ºC, while Case 1 and Case 3 both had a room temperature of 22.6 ºC and 22.5 ºC respectively. The average temperature across all six planes followed a similar pattern, Case 2 consistently showing higher temperatures.
Mechanical Ventilation with Heat Recovery
Copyright (c) 2025 Ashish Chourey, Piyush Kr. Verma, Pankaj Shrivastava https://creativecommons.org/licenses/by-sa/4.0
विद्यार्थियों की शैक्षणिक उपलब्धि पर सामाजिक - संवेगात्मक अधिगम (एसईएल ) के प्रभाव का तुलनात्मक अध्ययन
इस शोध पत्र का उद्देश्य विद्यार्थियों की शैक्षणिक उपलब्धि पर सामाजिक-संवेगात्मक अधिगम (एसईएल) के प्रभावों का विश्लेषण करना है। डेटा संग्रह के उद्देश्य से, 200 विद्यार्थियों को उनकी सामाजिक-संवेगात्मक अधिगम की क्षमताओं को मापने के लिए एक स्व-निर्मित प्रश्नावली द्वारा नमूना लिया गया था। शैक्षणिक उपलब्धि का मूल्यांकन करने के लिए, विद्यार्थियों का आकलन करने के लिए 10वीं कक्षा की परीक्षा और कुल अंकों का उपयोग किया गया। परिणाम इस अध्ययन में, सामाजिक-भावनात्मक शिक्षा (एसईएल) और विद्यार्थियों की शैक्षणिक उपलब्धि के बीच जटिल संबंध को रेखांकित किया गया है। अधिक विशेष रूप से, उच्च एसईएल दक्षताओं ने अंग्रेजी के क्षेत्र में छात्र के प्रदर्शन पर थोड़ा सकारात्मक प्रभाव डाला; अन्यथा अन्य विषयों में कोई महत्वपूर्ण अंतर नहीं पाया गया। ये परिणाम संकेत देते हैं कि एसईएल अच्छे परिणामों को बढ़ावा देता है, लेकिन यह शैक्षणिक सफलता को प्रभावित करने वाले कई कारकों में से एक है। एसईएल और किसी भी शैक्षिक परिणाम के बीच संबंध को स्पष्ट करने के लिए भविष्य में जांच की आवश्यकता है जो यह निर्धारित करने के लिए रुचिकर हो सकता है कि छात्र उपलब्धि को बढ़ावा देने में उनके साथ प्रभावी ढंग से कैसे काम किया जा सकता है। इस शोध का परिणाम भावनात्मक और शैक्षणिक विकास पर दोहरे ध्यान को आगे बढ़ाने के उद्देश्य से प्रभावी शैक्षिक प्रथाओं को बढ़ावा देने में शिक्षकों, नीति निर्माताओं और हितधारकों की बहुत मदद करता है।
Copyright (c) 2025 संजू शर्मा https://creativecommons.org/licenses/by-sa/4.0
Student Perceptions of E-Learning Tools in Chemistry Education
This research examines student perceptions of e-learning tools in chemistry education, concentrating on their usage, effectiveness, features, engagement, and overall impact. Two hundred students from various programs and levels of study were given a standardised questionnaire with five Likert scale items. The data was examined by using methods of correlation, regression, and descriptive statistics. According to the findings, using e-learning tools may greatly improve your ability to solve problems, study for exams, and do well in school generally. Findings indicate that multimedia and interactive aspects significantly contribute to higher levels of student engagement and motivation. While many students have faith in digital resources, others have doubts about their capacity to totally replace more conventional approaches, especially when it comes to grasping more advanced ideas. Another finding from the research is that people's perceptions are greatly impacted by demographic criteria such gender, age, academic level, institution type, and internet availability. These results emphasise the rising importance of online learning tools in chemistry education as useful adjuncts.
Lithium-Ion Battery Components and Its Recycling Methods – A Review
The increasing prevalence of lithium-ion batteries in electric vehicles, consumer electronics, and renewable energy systems has led to a pressing demand for efficient recycling methods. This review delves into the essential elements of lithium-ion batteries and examines the primary recycling techniques: pyrometallurgy, hydrometallurgy, and direct recycling. Every approach presents unique advantages and obstacles regarding expenses, energy consumption, efficiency of recovery, and ecological effects. Pyrometallurgy is frequently employed, yet it requires elevated temperatures and generates emissions. Hydrometallurgy provides enhanced material recovery, yet it involves a greater use of chemicals and intricate processes. Direct recycling, currently being explored, demonstrates promise in maintaining material value. Even with advancements in technology, obstacles like inconsistent regulations, inadequate collection systems, and limited public awareness continue to persist. Tackling these challenges is essential for establishing a sustainable and circular battery economy. This paper seeks to provide a comprehensive overview to aid in future research and policy formulation regarding battery waste management.
Copyright (c) 2025 Santosh Kumar Nathsharma https://creativecommons.org/licenses/by-sa/4.0
Impact of Stir Casting Parameter and Stirrer Blade Design on Mechanical Properties of Aluminium MMC: A Review
Among many other qualities, aluminium matrix composites provide reduced weight, increased strength, and increased resistance to wear. Comparing the stir casting technique to other manufacturing methods, it is simple to use, inexpensive, and appropriate for large quantities. Because it significantly affects the material's characteristics, distributing reinforcement evenly throughout the matrix is one of the main issues in producing aluminium MMCs. Review the many studies on the effects of stir casting parameters and stirrer blade design on the mechanical characteristics of aluminium MMC in order to fill this gap. The review highlights that both stir casting parameters and stirrer blade design significantly influence the mechanical properties and microstructure of Aluminium MMCs. Optimal stirring speed, time, and temperature promote uniform particle distribution, minimizing porosity and enhancing tensile strength and hardness. Stirrer blade design particularly blade shape, number, and angle affects vortex formation and reinforcement dispersion. Multi-blade and mixed blade designs yield more homogeneous composites with improved Brinell hardness and reduced clustering. Increased blade count and melting temperature enhance microstructural refinement and mechanical performance. Thus, the integration of optimized stir casting parameters and blade designs is crucial for superior AMMC properties.
Copyright (c) 2025 Arvinder Singh Channi, Manjot Kaur Channi https://creativecommons.org/licenses/by-sa/4.0
The Role of Social Work in Addressing Domestic Violence: Trends and Challenges
Regardless of a person's gender, age, socioeconomic class, or ethnocultural background, domestic violence is still a serious and complicated societal problem that has become worse all around the globe. Smart technology services, programs, and solutions that are digital, online, or AI-based provide innovative ways to combat intimate partner abuse and other forms of domestic violence. Examine the function of social work in combating domestic violence in this article. This review highlights that initial unreported cases of domestic violence often remain unnoticed, leading to re-victimization and negative impacts on children. Emerging ML/AI-based forecasting tools offer potential in predicting and preventing IPV but require human oversight and community collaboration. The findings emphasize trauma-informed approaches, effective practices, and tailored interventions for social workers. Resilience is fostered through clear communication, supervision, mentoring, and collaborative networks, which reduce stress and build trust. Multi-actor approaches and support systems are crucial in combating exclusion and fatigue, thereby strengthening survivor-centered practices and enhancing the overall role of social work in addressing domestic violence.
Copyright (c) 2025 Ashok Kumar B https://creativecommons.org/licenses/by-sa/4.0
The Role of Machine Learning in Enhancing Data Science Workflows: A Systematic Review
Big data is almost always the foundation of machine learning (ML) models, which have attracted a lot of interest in a range of applications, from computer vision to natural language processing. The intersection of data science, artificial intelligence, and software engineering is shown in the increasing number of products and applications that have integrated machine learning models. This review highlights that machine learning plays a pivotal role in enhancing data science workflows by automating complex tasks, improving predictive accuracy, and enabling data-driven decision-making. Proactive and reactive algorithms, supported by advanced computational power through GPUs and TPUs, allow better forecasting and response in real-world applications. Incorporating data engineering techniques with AI ensures scalability, efficiency, and reduced human errors. Furthermore, machine learning enables the discovery of hidden patterns, handling of massive datasets, and integration of smart computing for decision-making across domains such as business, healthcare, cybersecurity, and urban systems, thereby significantly advancing data science practices.
Copyright (c) 2025 Mudita Sharma https://creativecommons.org/licenses/by-sa/4.0
महिला सशक्तिकरण में शिक्षा और रोजगार की भूमिका: एक नीतिगत परिप्रेक्ष्य
यह अध्ययन "महिला सशक्तिकरण में शिक्षा और रोजगार की भूमिका: एक नीतिगत परिप्रेक्ष्य" के अंतर्गत महिला सशक्तिकरण के लिए शिक्षा और रोजगार की महत्वपूर्ण भूमिका का विश्लेषण करता है। महिला शिक्षा और रोजगार की बढ़ती भागीदारी ने महिला सशक्तिकरण की दिशा में महत्वपूर्ण बदलाव लाए हैं। सरकार द्वारा लागू की गई योजनाएं जैसे “बेटी बचाओ, बेटी पढ़ाओ”, “मुद्रा योजना” और स्टैंड-अप इंडिया” महिलाओं को शिक्षा और रोजगार के क्षेत्र में समान अवसर प्रदान करने में सहायक सिद्ध हुई हैं। अध्ययन में यह भी दिखाया गया है कि शिक्षा ने महिलाओं को आत्मनिर्भर बनाया है, और रोजगार नीतियों ने उनके आर्थिक सशक्तिकरण में सहायक भूमिका निभाई है। इस अध्ययन ने यह प्रदर्शित किया है कि नीति-निर्माण के प्रभावी प्रयासों से महिला सशक्तिकरण में अभूतपूर्व सुधार हुआ है। इस शोध ने महिला शिक्षा और रोजगार के समन्वय से महिलाओं के जीवन में सकारात्मक बदलाव और समाज में समानता की दिशा में हुए परिवर्तनों की जानकारी दी है।
Copyright (c) 2025 उमा शर्मा https://creativecommons.org/licenses/by-sa/4.0
Understanding Employee Attrition in Organised Retail: A Case Study from Bangalore
Employee attrition in organized retail business has become a considerable issue in operations, customer service and productivity carrier of an organization. This paper examines the major reasons which have led the employee turnover in the organized retail business in Bangalore based on secondary data analysis on 30 retail firms. The analysis depicts inadequate compensation, career progression blockades, work environment related issues and work-life imbalance as the major causes of attrition. Moreover, the success of the retention programs like attractive remuneration packages, career-enhancement schemes, better organizational culture and work-life balance schemes will be reviewed. The findings indicate that attrition rate is the highest in the early-stage employees showing the need of special retention efforts. The research can give practical recommendations to retail organizations to decrease employee turnover, to increase employee engagement, and to promote long-term stability of the workforce.
Copyright (c) 2025 Mallana Gouda S. Patil, M. Ganesh Babu https://creativecommons.org/licenses/by-sa/4.0
Review of Machine Learning Algorithms and Their Applications
A conceptual introduction is given to the topic of machine learning. Machine learning is primarily concerned with the process by which computers learn autonomously and modify their actions accordingly, without the need for human invention or assistance. Review the many viewpoints on machine learning algorithms and their uses found in the literature in this page. This review highlights that machine learning (ML) algorithms, including supervised, unsupervised, and reinforcement learning, have become integral to diverse real-world applications. From speech recognition, image classification, and medical diagnosis to fraud detection, self-driving cars, and online recommendations, ML demonstrates remarkable versatility. Findings indicate that supervised learning is effective with smaller labeled datasets, while unsupervised learning and deep learning perform better with large-scale data. Reinforcement learning adds value in dynamic environments requiring decision-making. In conclusion, ML continues to evolve as a transformative tool across domains, though challenges in scalability, interpretability, and ethical implementation remain critical areas for future research.
Copyright (c) 2024 Jaya Sharma https://creativecommons.org/licenses/by-sa/4.0
A Comprehensive Review of Artificial Intelligence Applications in Computer Science
Developing intelligent devices, particularly clever computer programs, is the goal of this field of science and engineering. Modern computer science has made artificial intelligence (AI) a pillar, and it has a significant impact on many facets of society. This article examines the perspectives of the diverse publications on computer science applications of artificial intelligence. This review highlights that Artificial Intelligence (AI) has become an indispensable tool in computer science, driving advancements across diverse domains such as healthcare, finance, cybersecurity, smart cities, robotics, and education. Speech recognition, image processing, and decision support systems are among the diverse applications of ten essential AI techniques, which include deep learning, machine learning, and natural language processing. Findings reveal that while AI enhances automation, efficiency, and intelligent computing, challenges remain in ethics, security, and large-scale implementation. In conclusion, AI continues to evolve as a transformative force, with future prospects pointing toward greater automation, intelligent decision-making, and sustainable societal integration.
Optimization Accuracy of Fake News Detection in social media using Multimodal Learning
The spread of false information in the digital age is a big problem because it changes how people think arounds, how politics works and how people behave on social media and the internet today. Standard detection methods that can rely on feature engineering, language indicators, or metadata often have problems with scalability and generalisability. Recent developments on natural language processing, such as Bidirectional Encoder Representations from Transformers (BERT), give a more effective method by summarize deep contextual and semantic relationships within text. In this study, BERT-based model is created to identify fake news using a dataset of news articles. The model was too though number of steps like as tokenization, embedding, and fine-tuning so it could learn patterns that distinguish between real and fake news. To measure its performance, by accuracy, precision, recall, F1-score, and AUC-ROC, and then compared the results with traditional machine learning methods. The results showed that BERT worked better than older models because it could capture subtle patterns in language, which improved detection accuracy. This also suggests that deep learning models perform more reliably when trained on large datasets. In this study, BERT proved to be an effective and practical method for detecting fake news. The work also sets a strong base for future research in automated misinformation detection.
Copyright (c) 2025 Priyal Verma, Nagesh Salimath https://creativecommons.org/licenses/by-sa/4.0
Informal Waste Sector in Urban India: A Review of Waste Management Policies and Their Impact
Nearly 70% of India's 62 million tonnes of municipal solid garbage are improperly handled, creating serious problems for the country's environment, public health, and socioeconomic standing. The present management systems are under a great deal of strain due to the fast urbanisation and economic expansion that increase waste creation. Notwithstanding the quick economic growth, efficient waste management has proven challenging, suggesting a weakness in development plans. In this article, discuss the effects of waste management regulations in metropolitan India. The analysis shows that there are many serious issues with India's solid waste management system, such as low public awareness, weak policy enforcement, inadequate infrastructure, and a lack of finance. Despite initiatives such as SBM, Smart Cities Mission, and SWM Rules (2016), gaps between policy and practice persist, leading to overflowing landfills, hazardous dumping, and severe public health risks. The informal sector, though under recognized, plays a vital role in recycling and waste reduction. Integrating this sector into formal systems, along with adopting decentralized composting, biogas, and modern waste-to-energy technologies, can enhance efficiency. Ultimately, sustainable MSWM demands inclusive governance, technological innovation, and collective participation.
Municipal Solid Waste, Informal Waste Sector, SWM Rules (2016), Swachh Bharat Mission, And Smart Cities Mission.
Copyright (c) 2025 Manisha Malik, Richa Chowdhary https://creativecommons.org/licenses/by-sa/4.0
Role of Community Participation in Solid Waste Management Systems
This study examines the role of community participation in improving solid waste management systems with a focus on reducing chemical hazards. A survey of 125 respondents was conducted to evaluate perceptions and practices related to participation, segregation, recycling efficiency, public awareness, and safe disposal of hazardous waste. Descriptive analysis revealed that while respondents strongly agreed on the importance of campaigns, collective efforts, and recycling in lowering toxic emissions and contamination, their active participation in household segregation and consistent practices remained moderate. Public awareness indicators scored high, showing that education, campaigns, and media play an important role in shaping attitudes toward waste management. Hypothesis testing provided further support: ANOVA results demonstrated that community participation significantly impacts the reduction of chemical hazards, and public awareness strongly influences safe handling and disposal of hazardous waste. Correlation analysis confirmed a strong positive relationship between segregation practices and recycling efficiency. The findings highlight that while knowledge and awareness are strong, gaps remain in individual practices and systemic recycling mechanisms. Strengthening household-level engagement and facilities for safe hazardous waste disposal can enhance the chemical safety and sustainability of solid waste management systems.
Copyright (c) 2024 Madhu Dubey Swarnkar https://creativecommons.org/licenses/by-sa/4.0
Molybdenum disulfide and its composites for Supercapacitor application: A Review
A transition metal dichalcogenide, molybdenum disulphide (MoS2) possesses unique properties, including a configurable bandgap, and a broad spectrum of potential applications in catalysis, electronics, and energy storage. It proved to be an effective electrode material for supercapacitors due to its high specific capacitance. Here electrochemical performances of MoS2 and its composites with different preparative methods and conditions have been summarized. The main advantages and disadvantages of MoS2-based electrodes are also covered in the review.
Copyright (c) 2025 Anil Dhawale, Sonali Raykar, Madhav Sarode, Y.B. Khollam, Vaibhav D. Patake https://creativecommons.org/licenses/by-sa/4.0
Investigating Customer Behaviour in the Digital Age: An Empirical Analysis of Online Buying Trends
This research examines customer behavior during the digital era using an empirical investigation of online purchasing patterns. From a study of secondary data equating to 100 cases of online purchases, the study identifies central features including preferred product categories, preferred devices used for shopping, frequency of purchase, and busiest shopping times. The research discovers that Electronics and Fashion are the leading online purchase items, with the smartphone proved to be the most frequently used device. This study notes that regular customers make up the bulk of customers and that customer activity is at its highest during festive and holiday seasons. With these observations, companies can get specific guidance on adjusting their online strategies to keep up. The study confirms that aligning with new consumer trends increases a company’s chances of succeeding in the growing online market.
Copyright (c) 2025 K.R. Nitinkrishna, Ganesh Babu. M. https://creativecommons.org/licenses/by-sa/4.0
A Comparative Study of Self-Confidence and Competitive Anxiety between Rural and Urban Cricket Players
In this study, urban and rural cricket players' levels of self-confidence and competitive anxiety are compared. Psychological qualities often determine performance under duress, and cricket is a sport that demands a high level of mental preparedness. The mental talents and limitations of players may vary among areas due to differences in coaching, exposure, and facilities. Measurements of these characteristics, effects of demographic and socioeconomic variables, and the link between anxiety and self-confidence were the goals of the research. The study included 420 players, evenly distributed between rural and urban locations. Data were collected using standardised methods, including the Sinha's Comprehensive Anxiety Test (SCAT) and the Self-Confidence Inventory (SCI). The analysis included descriptive statistics, t-tests, ANOVA, correlation, and regression. The findings indicated that players from rural areas exhibited greater self-confidence, whereas those from urban settings demonstrated a marginally better ability to manage anxiety. A significant positive relationship was observed, indicating that greater self-confidence may occasionally elevate performance pressure. Training exposure and facility availability substantially impacted confidence, while geography, income, and experience had lesser still significant impacts. The results underscore the need of integrating these features in the development of training and mental preparation programs.
Copyright (c) 2025 Sunil Shama, Changule Sheiba Bhima https://creativecommons.org/licenses/by-sa/4.0
Sperm DNA Fragmentation and Male Infertility: A Comprehensive Review
Male infertility remains a critical concern in reproductive medicine, with sperm DNA fragmentation (SDF) emerging as a key factor in impaired fertility potential. This review compiles and critically examines current literature on the biological mechanisms, diagnostic approaches, and clinical significance of SDF. The paper explores how oxidative stress, apoptosis, and defective chromatin packaging contribute to DNA damage in sperm cells. Various diagnostic tools such as TUNEL, SCSA, Comet assay, and SCD test are reviewed in terms of reliability and clinical relevance. The role of SDF in natural conception, intrauterine insemination (IUI), in vitro fertilization (IVF), and intracytoplasmic sperm injection (ICSI) is also discussed. Furthermore, the review addresses therapeutic interventions ranging from lifestyle modifications and antioxidant therapy to the application of advanced sperm selection techniques. It was observed that high levels of SDF are associated with lower fertilization rates, poor embryo quality, increased miscarriage risk, and reduced pregnancy outcomes. Recognizing and managing SDF could significantly enhance reproductive success and guide patient-specific fertility treatment.
Copyright (c) 2025 Shweta Dagar, Sandeep Verma https://creativecommons.org/licenses/by-sa/4.0