International Journal of Innovations in Science, Engineering And Management
type: channel
description: 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 …
language: en
publication name: International Journal of Innovations in Science, Engineering And Management
issn: 2583-7117
copyright: Re-users must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. This license allows for redistribution, commercial and non-commercial, as long as the original work is properly credited.
items: A Comprehensive Review on Phytochemical and Pharmacological Properties of Alstonia scholaris
items: A Comprehensive Review on Deep Learning Methods in Medical Image Analysis
items: High-Frequency Interactions Between Market Volatility and Price Movements: Intraday Asymmetry Between India Vix and Nifty 50 Through Technical Lenses
items: Accurate PM2.5 Prediction Using Machine Learning Ensembles for Sustainable Smart Cities
items: Exploring the role of Innovative Work Orientation in Healthcare Landscape through a narrative lens: A Glimpse
items: Understanding of Water Purification Methods through Chemistry among Urban Households
items: Phytochemical and wound healing potential of ethanolic extract of Nymphaea alba
items: Traditional Herbal Medicine in the Management of Chronic Diseases
items: Impact of GST on Household Expenditure in Madhya Pradesh
items: Software Bug Prediction Using Machine Learning Algorithms: An Empirical Study on Code Quality and Reliability
items: The Application of Artificial Intelligence in Human Resource Management: Evidence from Mid-to-Large Indian Enterprises
items: व्यावसायिक शिक्षा और कौशल विकास के लिए शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता पर एक तुलनात्मक अध्ययन
items: Thermal Comfort Analysis in Dormitory Room by Combined MVHR-Fan Coil
items: विद्यार्थियों की शैक्षणिक उपलब्धि पर सामाजिक - संवेगात्मक अधिगम (एसईएल ) के प्रभाव का तुलनात्मक अध्ययन
items: Student Perceptions of E-Learning Tools in Chemistry Education
items: Lithium-Ion Battery Components and Its Recycling Methods – A Review
items: Impact of Stir Casting Parameter and Stirrer Blade Design on Mechanical Properties of Aluminium MMC: A Review
items: The Role of Social Work in Addressing Domestic Violence: Trends and Challenges
items: The Role of Machine Learning in Enhancing Data Science Workflows: A Systematic Review
items: महिला सशक्तिकरण में शिक्षा और रोजगार की भूमिका: एक नीतिगत परिप्रेक्ष्य
items: Understanding Employee Attrition in Organised Retail: A Case Study from Bangalore
items: Review of Machine Learning Algorithms and Their Applications
items: A Comprehensive Review of Artificial Intelligence Applications in Computer Science
items: Optimization Accuracy of Fake News Detection in social media using Multimodal Learning
items: Informal Waste Sector in Urban India: A Review of Waste Management Policies and Their Impact
items: Role of Community Participation in Solid Waste Management Systems
items: Molybdenum disulfide and its composites for Supercapacitor application: A Review
items: Investigating Customer Behaviour in the Digital Age: An Empirical Analysis of Online Buying Trends
items: A Comparative Study of Self-Confidence and Competitive Anxiety between Rural and Urban Cricket Players
items: Sperm DNA Fragmentation and Male Infertility: A Comprehensive Review

A Comprehensive Review on Phytochemical and Pharmacological Properties of Alstonia scholaris
type: item
description: 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.
subject: Articles
  topic: section
subject: Alstonia Scholaris (Saptaparni)
  topic: keywords
subject: Analgesic
  topic: keywords
subject: Anti-Inflammatory
  topic: keywords
subject: Phytochemical Constituents
  topic: keywords
subject: Pharmacological Properties
  topic: keywords
creator: Nilesh Mohan Mishra
creator: Khooshbu chouhan
creator: Satkar Prasad
creator: Shailesh Ghatuary
creator: Priyanka More
rights: Copyright (c) 2025 Nilesh Mohan Mishra, Khooshbu chouhan, Satkar Prasad, Shailesh Ghatuary, Priyanka More https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-29
publication date: 2025-09-29
starting page: 401
ending page: 407
doi: 10.69968/

A Comprehensive Review on Deep Learning Methods in Medical Image Analysis
type: item
description: 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.
subject: Articles
  topic: section
subject: Deep learning
  topic: keywords
subject: medical image analysis
  topic: keywords
subject: convolutional neural networks
  topic: keywords
subject: transformers
  topic: keywords
subject: self-supervised learning
  topic: keywords
subject: GANs
  topic: keywords
creator: Lalit Kumar Rawat
creator: Anil Kumar
rights: Copyright (c) 2025 Lalit Kumar Rawat, Anil Kumar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-11-11
publication date: 2025-11-11
starting page: 38
ending page: 41
doi: 10.69968/ijisem.2025v4i438-41

High-Frequency Interactions Between Market Volatility and Price Movements: Intraday Asymmetry Between India Vix and Nifty 50 Through Technical Lenses
type: item
description: 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.
subject: Articles
  topic: section
subject: Technical analysis
  topic: keywords
subject: Candlestick patterns
  topic: keywords
subject: Intraday volatility
  topic: keywords
subject: India VIX
  topic: keywords
subject: Nifty 50
  topic: keywords
creator: Tuhin Mukherjee
creator: Subhrajyoti Mandal
rights: Copyright (c) 2025 Dr. Tuhin Mukherjee, Subhrajyoti Mandal https://creativecommons.org/licenses/by-sa/4.0
date: 2025-11-06
publication date: 2025-11-06
starting page: 25
ending page: 37
doi: 10.69968/ijisem.2025v4i410-14

Accurate PM2.5 Prediction Using Machine Learning Ensembles for Sustainable Smart Cities
type: item
description: 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.
subject: Articles
  topic: section
subject: Air quality prediction
  topic: keywords
subject: PM2.5
  topic: keywords
subject: machine learning
  topic: keywords
subject: hybrid ensemble
  topic: keywords
subject: Random Forest
  topic: keywords
subject: Extra Trees
  topic: keywords
subject: smart cities
  topic: keywords
subject: sustainability
  topic: keywords
subject: AQI
  topic: keywords
subject: India
  topic: keywords
creator: Aesha Bhardwaj
creator: Sanjay Silakar
creator: Rajeev Pandey
creator: Jashwant Samar
rights: Copyright (c) 2025 Aesha Bhardwaj, Sanjay Silakar, Rajeev Pandey, Jashwant Samar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-15
publication date: 2025-10-15
starting page: 10
ending page: 17
doi: 10.69968/ijisem.2025v4i410-17

Exploring the role of Innovative Work Orientation in Healthcare Landscape through a narrative lens: A Glimpse
type: item
description: 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
subject: Articles
  topic: section
subject: Innovation
  topic: keywords
subject: Innovative work orientation
  topic: keywords
subject: creativity
  topic: keywords
subject: Support for creativity
  topic: keywords
subject: healthcare
  topic: keywords
subject: healthcare professionals
  topic: keywords
creator: Anjana gupta
creator: Anshu Yadav
rights: Copyright (c) 2025 Anjana gupta, Anshu Yadav https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-31
publication date: 2025-10-31
starting page: 18
ending page: 24
doi: 10.69968/ijisem.2025v4i418-24

Understanding of Water Purification Methods through Chemistry among Urban Households
type: item
description: 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.
subject: Articles
  topic: section
subject: Water Purification
  topic: keywords
subject: Urban Households
  topic: keywords
subject: Chemical Understanding
  topic: keywords
subject: Household Practices
  topic: keywords
subject: Chemistry Education
  topic: keywords
creator: Jaidev Kumar
rights: Copyright (c) 2025 Jaidev Kumar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-10-08
publication date: 2025-10-08
starting page: 1
ending page: 9
doi: 10.69968/ijisem.2025v4i41-9

Phytochemical and wound healing potential of ethanolic extract of Nymphaea alba
type: item
description: 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.
subject: Articles
  topic: section
subject: Nymphaea alba
  topic: keywords
subject: Wound healing
  topic: keywords
subject: Incision
  topic: keywords
subject: Excision epithelialisation
  topic: keywords
subject: tensile strength
  topic: keywords
creator: Satkar Prasad
creator: Shyam Bahadur
creator: Sailesh Ghatuary
rights: Copyright (c) 2025 Satkar Prasad, Shyam Bahadur, Sailesh Ghatuary https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-27
publication date: 2025-09-27
starting page: 388
ending page: 400
doi: 10.69968/ijisem.2025v4i3388-400

Traditional Herbal Medicine in the Management of Chronic Diseases
type: item
description: 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.
subject: Articles
  topic: section
subject: Herbal medicine
  topic: keywords
subject: Chronic disease
  topic: keywords
subject: Knowledge
  topic: keywords
subject: Belief
  topic: keywords
subject: Perceived safety
  topic: keywords
creator: Madhu Dubey Swarnkar
rights: Copyright (c) 2025 Madhu Dubey Swarnkar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 392
ending page: 400
doi: 10.69968/ijisem.2025v4i1392-400

Impact of GST on Household Expenditure in Madhya Pradesh
type: item
description: 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.
subject: Articles
  topic: section
subject: GST
  topic: keywords
subject: Consumer spending
  topic: keywords
subject: household budget
  topic: keywords
creator: Sangita Deota
creator: Saurabh Kumar Sahu
rights: Copyright (c) 2025 Sangita Deota, Saurabh Kumar Sahu https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-22
publication date: 2025-09-22
starting page: 382
ending page: 387
doi: 10.69968/ijisem.2025v4i3382-387

Software Bug Prediction Using Machine Learning Algorithms: An Empirical Study on Code Quality and Reliability
type: item
description: 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.
subject: Articles
  topic: section
subject: Software Bug Prediction
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: CNN-LSTM
  topic: keywords
subject: Code Quality
  topic: keywords
subject: Software Reliability
  topic: keywords
subject: Feature Selection
  topic: keywords
subject: Class Imbalance
  topic: keywords
subject: Software Metrics
  topic: keywords
subject: Defect Detection
  topic: keywords
creator: Elavarasi Kesavan
rights: Copyright (c) 2025 Elavarasi Kesavan https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-15
publication date: 2025-09-15
starting page: 377
ending page: 381
doi: 10.69968/ijisem.2025v4i3377-381

The Application of Artificial Intelligence in Human Resource Management: Evidence from Mid-to-Large Indian Enterprises
type: item
description: 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.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: HRM
  topic: keywords
subject: India
  topic: keywords
subject: Recruitment
  topic: keywords
subject: Analytics
  topic: keywords
subject: Responsible AI
  topic: keywords
subject: Compliance
  topic: keywords
subject: L&D
  topic: keywords
subject: Workforce Planning
  topic: keywords
creator: Sangita Deota
creator: Rajesh Sahu
rights: Copyright (c) 2025 Sangita Deota, Rajesh Sahu https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-11
publication date: 2025-09-11
starting page: 372
ending page: 376
doi: 10.69968/ijisem.2025v4i3372-376

व्यावसायिक शिक्षा और कौशल विकास के लिए शिक्षक शिक्षा कार्यक्रमों की प्रभावशीलता पर एक तुलनात्मक अध्ययन
type: item
description: 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।
subject: Articles
  topic: section
subject: शिक्षक शिक्षा
  topic: keywords
subject: व्यावसायिक शिक्षा
  topic: keywords
subject: कौशल विकास
  topic: keywords
creator: नीलम सिंह
rights: Copyright (c) 2025 नीलम सिंह https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-10
publication date: 2025-09-10
starting page: 364
ending page: 371
doi: 10.69968/ijisem.2025v4i3364-371

Thermal Comfort Analysis in Dormitory Room by Combined MVHR-Fan Coil
type: item
description: 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.
subject: Articles
  topic: section
subject: Mechanical Ventilation with Heat Recovery
  topic: keywords
subject: Fan coil
  topic: keywords
subject: Thermal comfort
  topic: keywords
subject: computational fluid dynamic
  topic: keywords
creator: Ashish Chourey
creator: Piyush Kr. Verma
creator: Pankaj Shrivastava
rights: Copyright (c) 2025 Ashish Chourey, Piyush Kr. Verma, Pankaj Shrivastava https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-10
publication date: 2025-09-10
starting page: 351
ending page: 363
doi: 10.69968/ijisem.2025v4i3351-363

विद्यार्थियों की शैक्षणिक उपलब्धि पर सामाजिक - संवेगात्मक अधिगम (एसईएल ) के प्रभाव का तुलनात्मक अध्ययन
type: item
description: 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।
subject: Articles
  topic: section
subject: सामाजिक-संवेगात्मक अधिगम (एसईएल)
  topic: keywords
subject: शैक्षणिक उपलब्धि
  topic: keywords
subject: छात्र प्रदर्शन
  topic: keywords
creator: संजू शर्मा
rights: Copyright (c) 2025 संजू शर्मा https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-09
publication date: 2025-09-09
starting page: 344
ending page: 350
doi: 10.69968/ijisem.2025v4i3344-350

Student Perceptions of E-Learning Tools in Chemistry Education
type: item
description: 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.
subject: Articles
  topic: section
subject: e-learning tools
  topic: keywords
subject: chemistry education
  topic: keywords
subject: student engagement
  topic: keywords
subject: academic performance
  topic: keywords
subject: perceptions
  topic: keywords
creator: Jaidev Kumar
rights: Copyright (c) 2025 Jaidev Kumar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-09
publication date: 2025-09-09
starting page: 336
ending page: 343
doi: 10.69968/ijisem.2025v4i3336-343

Lithium-Ion Battery Components and Its Recycling Methods – A Review
type: item
description: 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.
subject: Articles
  topic: section
subject: Lithium-ion batteries
  topic: keywords
subject: Recycling methods
  topic: keywords
subject: Pyrometallurgy
  topic: keywords
subject: Hydrometallurgy
  topic: keywords
subject: Sustainability
  topic: keywords
creator: Santosh Kumar Nathsharma
rights: Copyright (c) 2025 Santosh Kumar Nathsharma https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-09
publication date: 2025-09-09
starting page: 322
ending page: 335
doi: 10.69968/ijisem.2025v4i3322-335

Impact of Stir Casting Parameter and Stirrer Blade Design on Mechanical Properties of Aluminium MMC: A Review
type: item
description: 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.
subject: Articles
  topic: section
subject: Stir Casting Parameter
  topic: keywords
subject: Stirrer Blade Design (Geometry)
  topic: keywords
subject: Aluminium Metal Matrix Composite (MMCs)
  topic: keywords
subject: Tensile Strength
  topic: keywords
subject: Hardness Stirring Speed and Time
  topic: keywords
creator: Arvinder Singh Channi
creator: Manjot Kaur Channi
rights: Copyright (c) 2025 Arvinder Singh Channi, Manjot Kaur Channi https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-08
publication date: 2025-09-08
starting page: 313
ending page: 321
doi: 10.69968/ijisem.2025v4i3313-321

The Role of Social Work in Addressing Domestic Violence: Trends and Challenges
type: item
description: 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.
subject: Articles
  topic: section
subject: Social Work
  topic: keywords
subject: Domestic Violence
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Education
  topic: keywords
subject: Prevention
  topic: keywords
subject: Intimate Partner Violence (IPV)
  topic: keywords
creator: Ashok Kumar B
rights: Copyright (c) 2025 Ashok Kumar B https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-05
publication date: 2025-09-05
starting page: 307
ending page: 312
doi: 10.69968/ijisem.2025v4i3307-312

The Role of Machine Learning in Enhancing Data Science Workflows: A Systematic Review
type: item
description: 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.
subject: Articles
  topic: section
subject: Machine Learning (ML)
  topic: keywords
subject: Data Science Workflows
  topic: keywords
subject: Natural Language Processing
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
subject: Internet of Things (Iot)
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Data Mining
  topic: keywords
creator: Mudita Sharma
rights: Copyright (c) 2025 Mudita Sharma https://creativecommons.org/licenses/by-sa/4.0
date: 2025-09-02
publication date: 2025-09-02
starting page: 301
ending page: 306
doi: 10.69968/ijisem.2025v4i1392-397

महिला सशक्तिकरण में शिक्षा और रोजगार की भूमिका: एक नीतिगत परिप्रेक्ष्य
type: item
description: 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।
subject: Articles
  topic: section
subject: महिला सशक्तिकरण
  topic: keywords
subject: शिक्षा
  topic: keywords
subject: रोजगार
  topic: keywords
subject: नीतिगत हस्तक्षेप
  topic: keywords
subject: सरकारी योजनाएँ
  topic: keywords
subject: सामाजिक परिवर्तन
  topic: keywords
subject: महिला उद्यमिता
  topic: keywords
subject: स्व-रोजगार
  topic: keywords
subject: महिला भागीदारी
  topic: keywords
creator: उमा शर्मा
rights: Copyright (c) 2025 उमा शर्मा https://creativecommons.org/licenses/by-sa/4.0
date: 2025-03-31
publication date: 2025-03-31
starting page: 384
ending page: 391
doi: 10.69968/ijisem.2025v4i1384-391

Understanding Employee Attrition in Organised Retail: A Case Study from Bangalore
type: item
description: 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.
subject: Articles
  topic: section
subject: Employee Attrition
  topic: keywords
subject: Organized Retail
  topic: keywords
subject: Retention Strategies
  topic: keywords
subject: Career Growth
  topic: keywords
subject: Compensation
  topic: keywords
subject: Work-Life Balance
  topic: keywords
subject: Employee Experience
  topic: keywords
subject: Bangalore
  topic: keywords
creator: Mallana Gouda S. Patil
creator: M. Ganesh Babu
rights: Copyright (c) 2025 Mallana Gouda S. Patil, M. Ganesh Babu https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-28
publication date: 2025-08-28
starting page: 296
ending page: 300
doi: 10.69968/ijisem.2025v4i3296-300

Review of Machine Learning Algorithms and Their Applications
type: item
description: 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.
subject: Articles
  topic: section
subject: Machine Learning Algorithms
  topic: keywords
subject: Machine Learning Applications
  topic: keywords
subject: Fraud Detection
  topic: keywords
subject: Self-Driving Cars
  topic: keywords
subject: Unsupervised Learning
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Decision-Making
  topic: keywords
creator: Jaya Sharma
rights: Copyright (c) 2024 Jaya Sharma https://creativecommons.org/licenses/by-sa/4.0
date: 2024-06-29
publication date: 2024-06-29
starting page: 113
ending page: 119
doi: 10.69968/ijisem.2024v3i2113-119

A Comprehensive Review of Artificial Intelligence Applications in Computer Science
type: item
description: 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.
subject: Articles
  topic: section
subject: Artificial Intelligence Applications
  topic: keywords
subject: Computer Science
  topic: keywords
subject: Decision-Making
  topic: keywords
subject: Data Security
  topic: keywords
subject: Automation
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Natural Language Processing
  topic: keywords
creator: Jaya Sharma
rights: Copyright (c) 2024 Jaya Sharma https://creativecommons.org/licenses/by-sa/4.0
date: 2024-03-30
publication date: 2024-03-30
starting page: 53
ending page: 59
doi: 10.69968/ijisem.2024v3i153-59

Optimization Accuracy of Fake News Detection in social media using Multimodal Learning
type: item
description: 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.
subject: Articles
  topic: section
subject: Fake news detection
  topic: keywords
subject: BERT
  topic: keywords
subject: Natural Language Processing
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Text classification
  topic: keywords
subject: Misinformation
  topic: keywords
subject: Social media analytics
  topic: keywords
subject: Contextual embeddings
  topic: keywords
creator: Priyal Verma
creator: Nagesh Salimath
rights: Copyright (c) 2025 Priyal Verma, Nagesh Salimath https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-23
publication date: 2025-08-23
starting page: 281
ending page: 287
doi: 10.69968/ijisem.2025v4i3281-287

Informal Waste Sector in Urban India: A Review of Waste Management Policies and Their Impact
type: item
description: 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.
subject: Articles
  topic: section
subject: Municipal Solid Waste, Informal Waste Sector, SWM Rules (2016), Swachh Bharat Mission, And Smart Cities Mission.
  topic: keywords
creator: Manisha Malik
creator: Richa Chowdhary
rights: Copyright (c) 2025 Manisha Malik, Richa Chowdhary https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-25
publication date: 2025-08-25
starting page: 288
ending page: 295
doi: 10.69968/ijisem.2025v4i3288-295

Role of Community Participation in Solid Waste Management Systems
type: item
description: 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.
subject: Articles
  topic: section
subject: community participation
  topic: keywords
subject: solid waste management
  topic: keywords
subject: chemical hazards
  topic: keywords
subject: recycling efficiency
  topic: keywords
subject: public awareness
  topic: keywords
creator: Madhu Dubey Swarnkar
rights: Copyright (c) 2024 Madhu Dubey Swarnkar https://creativecommons.org/licenses/by-sa/4.0
date: 2024-12-31
publication date: 2024-12-31
starting page: 100
ending page: 109
doi: 10.69968/ijisem.2024v3i4100-109

Molybdenum disulfide and its composites for Supercapacitor application: A Review
type: item
description: 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.
subject: Articles
  topic: section
subject: Electrochemical performance
  topic: keywords
subject: Molybdenum disulphide
  topic: keywords
subject: Specific capacitance Supercapacitor
  topic: keywords
creator: Anil Dhawale
creator: Sonali Raykar
creator: Madhav Sarode
creator: Y.B. Khollam
creator: Vaibhav D. Patake
rights: Copyright (c) 2025 Anil Dhawale, Sonali Raykar, Madhav Sarode, Y.B. Khollam, Vaibhav D. Patake https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-14
publication date: 2025-08-14
starting page: 255
ending page: 265
doi: 10.69968/ijisem.2025v4i3255-265

Investigating Customer Behaviour in the Digital Age: An Empirical Analysis of Online Buying Trends
type: item
description: 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.
subject: Articles
  topic: section
subject: Customer Behavior
  topic: keywords
subject: E-commerce
  topic: keywords
subject: Digital Shopping
  topic: keywords
subject: Consumer Preferences
  topic: keywords
subject: Purchase Frequency
  topic: keywords
subject: Online Buying Trends
  topic: keywords
creator: K.R. Nitinkrishna
creator: Ganesh Babu. M.
rights: Copyright (c) 2025 K.R. Nitinkrishna, Ganesh Babu. M. https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-12
publication date: 2025-08-12
starting page: 250
ending page: 254
doi: 10.69968/ijisem.2025v4i3250-254

A Comparative Study of Self-Confidence and Competitive Anxiety between Rural and Urban Cricket Players
type: item
description: 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.
subject: Articles
  topic: section
subject: self-confidence
  topic: keywords
subject: competitive anxiety
  topic: keywords
subject: rural and urban
  topic: keywords
subject: cricket
  topic: keywords
subject: sports psychology
  topic: keywords
creator: Sunil Sharma
creator: Chaugule Shetiba Bhima
rights: Copyright (c) 2025 Sunil Shama, Changule Sheiba Bhima https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-05
publication date: 2025-08-05
starting page: 230
ending page: 240
doi: 10.69968/ijisem.2025v4i3230-240

Sperm DNA Fragmentation and Male Infertility: A Comprehensive Review
type: item
description: 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.
subject: Articles
  topic: section
subject: Sperm DNA fragmentation
  topic: keywords
subject: male infertility
  topic: keywords
subject: oxidative stress
  topic: keywords
subject: assisted reproduction
  topic: keywords
subject: embryo quality
  topic: keywords
creator: Shweta Dagar
creator: Sandeep Verma
rights: Copyright (c) 2025 Shweta Dagar, Sandeep Verma https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 424
ending page: 431
doi: 10.69968/ijisem.2025v4i2424-431