International Journal of Multidisciplinary Engineering In Current Research
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language: en
publication name: International Journal of Multidisciplinary Engineering In Current Research
issn: 2456-4265
items: A Study On Ethical Challenges And Bias In Machine Learning Algorithms
items: AI-Based Approaches for Predicting Employee Success and Retention
items: Enhancing Liver Disease Detection Using Cloud Computing And Autoencoders In Healthcare Systems
items: Integrated Design And Analysis Of Liquid Pvt Technology For Renewable Energy-Enabled Buildings
items: Personalized Learning in Indian Schools through Artificial Intelligence (AI) in Present Scenario
items: Comparative Review of Silicon-Based and Non-Silicon Solar Cells
items: An Enhanced OBS Core Node Design Incorporating Wavelength Conversion and Deflection Routing Mechanisms
items: AI in Cybersecurity: Enhancing Digital Defenses with Anomaly Detection and LSTM-Based Threat Prediction
items: A Study On Synthesis With Respect To Characterizations And Applications Of Various Types Of Nanoparticles And Composites
items: Design Of A Low-Latency Pipelined Fir Filter Through Advanced Critical Path Analysis
items: Study on Rock Load Variation Considering Weatherability in Bord and Pillar Method of Underground Coal Extraction
items: A Critical Analysis of Thematic Depth, Narrative Techniques, and Cultural Representation in the Writings of Tagore, Bandyopadhyay, Devi, and Basu
items: Comprehensive Analysis of Preparation Techniques, Structural Features, and Properties in Composite Multiferroic Systems
items: Analysis of Ventilation Requirements Affected by Diesel Machinery in Underground Mines
items: Use of Industrial and Mining Wastes for Backfill in Subsurface Mining Operations
items: Optimization Techniques and Performance Assessment of IoT-Enabled WBANs in Healthcare Systems
items: Experimental Analysis of Underground Mine Ventilation System of Indian Metal Mines
items: Toward Sustainable Development Through Green Finance
items: A Critical Review of Composite Phase Change Materials in Lithium-Ion Battery Thermal Management
items: Enhancing Asset Reliability through Risk-Based Inspection and Reliability-Centered Maintenance in SAP EAM
items: Computational Approaches for Investigating Basic Material Properties of Cobalt-Aluminum Alloys
items: Green Innovations in Water and Wastewater Treatment: Mechanistic Insights and AI Integration
items: Wire-Arc Additive Manufacturing (WAAM) for the Fabrication of High Fatigue-Resistant Railcar Couplers
items: Study on the Performance of Solar-Evaporative Cooling Technology for Preserving Crops in Tropical Environments
items: Structural Analysis of CFST and DS CFST Using ANSYS Workbench
items: Bridging Automation and Intelligence: UiPath’s Agentic AI Framework and Robotic Process Automation Platform
items: Corporate Social Responsibility 2.0: From Compliance to Competitive Advantage
items: Structural Engineering Insights into the Chenab Railway Bridge Design
items: Advanced M-Dab-Based Ac/Dc Charger With Optimized Conduction Loss And Hybrid Charge–Discharge Strategy For Electric Vehicles
items: Integrated Pq Enhancement System For Industrial And Commercial Grids Using Advanced Power Oscillation Mitigation Techniques

A Study On Ethical Challenges And Bias In Machine Learning Algorithms
type: item
description: In the realm of consumer behaviour analysis, the confluence of machine learning methodologies and abundant data resources has propelled the discipline to new heights. This comprehensive review delves into the latest frontiers of deploying machine learning algorithms to decode the intricacies of consumer behaviour. The investigation initiates with an in-depth exploration of data acquisition and optimization, elucidating the meticulous process of feature engineering, and scrutinizing the practical application of diverse machine learning paradigms, encompassing regression, classification, clustering, and recommendation systems. Furthermore, the discourse encompasses the tangible ramifications of machine learning derived insights, elucidating their utility in optimizing pricing strategies, guiding product development, orchestrating targeted marketing campaigns, and enhancing the Caliber of customer service. It is essential to underscore the complexity of the challenges and ethical considerations intrinsic to the computational analysis of consumer behaviour. In conclusion, this review casts a forward-looking perspective, highlighting the imperative need for an ever-evolving data landscape to adapt to the ever-shifting consumer preferences and market dynamics. This paper serves as a paramount reference for researchers, businesses, and policymakers aiming to harness the multifaceted potential of machine learning in the realm of consumer behaviour understanding and influence. DOI: https://doi-ds.org/doilink/12.2025-55337411
subject: Articles
  topic: section
subject: Machine learning, Consumer behaviour analysis, Data optimization, Feature engineering, Ethical considerations
  topic: keywords
creator: H.fathima
creator: Dr.K.K.Savitha
creator: K.Meena
creator: T.Vadivel
creator: Ms. M. Leelavathi
creator: veldandi Srikanth
rights: Copyright (c) 2025 Authors
date: 2025-11-29
publication date: 2025-11-29
starting page: 21
ending page: 28

AI-Based Approaches for Predicting Employee Success and Retention
type: item
description: Employee retention has emerged as a critical challenge for organizations globally, with attrition rates reaching 57.3% in 2021 and turnover costs estimated at 200% of an employee's annual salary. This research investigates AI-based approaches for predicting employee success and retention through advanced machine learning algorithms. The study employs a comprehensive methodology incorporating predictive analytics, natural language processing, and classification models to analyze employee behavior patterns. The hypothesis posits that AI-driven predictive models can achieve accuracy rates exceeding 80% in identifying at-risk employees. Results demonstrate that Random Forest and XGBoost classifiers achieved 98.7% and 98.8% accuracy respectively in predicting employee turnover. Key findings reveal that overtime, job satisfaction, monthly income, age, and distance from home are primary attrition predictors. Implementation of AI-powered retention strategies resulted in 15-30% reduction in turnover rates across analyzed organizations, with IBM saving $300 million through predictive attrition models. The study concludes that AI-based approaches significantly enhance retention strategies through early risk detection, personalized interventions, and real-time monitoring capabilities.
subject: Articles
  topic: section
subject: Artificial Intelligence, Employee Retention, Machine Learning, Predictive Analytics, Turnover Prediction
  topic: keywords
creator: Thangadurai S
creator: Dr. D Shucharitha
rights: Copyright (c) 2024 Authors
date: 2024-09-27
publication date: 2024-09-27
starting page: 94
ending page: 106

Enhancing Liver Disease Detection Using Cloud Computing And Autoencoders In Healthcare Systems
type: item
description: Liver disease is a dangerous medical condition in need of an early diagnosis for proper treatment to prevent complications. This paper presents a prediction framework for liver disease based on Autoencoders and Cloud Infrastructure. The framework commences with the preprocessing of the data through cleaning, augmentation, and Z-score scaling, after which feature extraction from a Deep Belief Network (DBN) and Autoencoder-based classification are performed. The performance of the proposed model is evaluated using accuracy, precision, recall, F1-score, and AUC-ROC. The Proposed Autoencoders model performs better than the existing methods like Ensemble Method, HGB+MARS+SoftMax and SVC as per the experiment results. The Proposed Autoencoders have excellent 99.45% accuracy, 95.11% precision, 96.31% recall, 97.82% F1-score, and 96.51% AUC-ROC, and they exhibit superior performance in predicting liver disease. The suggested framework, with its cloud infrastructure and deep learning architecture, provides a strong solution for accurate and efficient diagnosis of liver disease.
subject: Articles
  topic: section
subject: Liver Disease, Cloud Infrastructure, Deep Belief Network, Autoencoders, Healthcare Systems
  topic: keywords
creator: Rohith Reddy Mandala
creator: Charles Ubagaram
creator: Narsing Rao Dyavani
creator: Bhagath Singh Jayaprakasam
creator: Venkat Garikipati
creator: Monday Fredrick Ohemu
rights: Copyright (c) 2025 Authors
date: 2025-05-30
publication date: 2025-05-30
starting page: 956
ending page: 562

Integrated Design And Analysis Of Liquid Pvt Technology For Renewable Energy-Enabled Buildings
type: item
description: The integration of liquid Photovoltaic-Thermal (PVT) technology represents a significant advancement in renewable energy systems for sustainable buildings. This study investigates the integrated design and performance analysis of liquid-based PVT collectors for renewable energy-enabled buildings. The primary objective is to evaluate the thermal and electrical efficiency of liquid PVT systems and their applicability in building energy management. The research employs a quantitative experimental methodology utilizing secondary data analysis from existing studies conducted between 2018-2021, examining various liquid PVT configurations under different solar radiation levels ranging from 500-1000 W/m². The hypothesis proposes that liquid PVT technology significantly enhances overall energy efficiency compared to standalone PV systems. Results demonstrate that liquid-based PVT collectors achieve thermal efficiency of 54.6-58.64%, electrical efficiency of 11.5-13.8%, and combined efficiency of 65-68.4% under optimal conditions. The integration of spiral flow absorbers with water-based cooling systems demonstrated superior performance at mass flow rates of 0.041 kg/s. The findings conclude that liquid PVT technology offers substantial potential for zero-energy buildings, reducing conventional energy dependence by 30-40% while simultaneously generating electricity and thermal energy for building applications.
subject: Articles
  topic: section
subject: Liquid PVT Technology, Renewable Energy Buildings, Thermal Efficiency, Electrical Performance, Building Integration
  topic: keywords
creator: Mr. Rohit Kumar
creator: Dr. Dhananjay Yadav
creator: Mr. Sachin Baraskar
rights: Copyright (c) 2022 Authors
date: 2022-09-29
publication date: 2022-09-29
starting page: 27
ending page: 41

Personalized Learning in Indian Schools through Artificial Intelligence (AI) in Present Scenario
type: item
description: The National Education Policy (NEP) 2020 emphasises the inclusion of contemporary subjects like Artificial Intelligence (AI) in school curricula, at appropriate stages, to foster innovation and digital literacy among students. Personalized learning enabled by Artificial Intelligence (AI) represents a transformative shift in Indian school education, offering adaptive, student-cantered experiences that respond to individual abilities, interests, and backgrounds. With the National Education Policy (NEP) 2020 encouraging technology integration and innovations, AI-driven personalized learning tools have rapidly emerged across urban and rural landscapes. These include intelligent tutoring systems, adaptive platforms, predictive analytics, automatic assessment, and multilingual content delivery. India’s government and private edtech sector have jointly launched initiatives such as SOAR and integrated AI capabilities into the CBSE curriculum to democratize access and raise educational outcomes. Recent data show over 60% of Indian higher education institutions now permit AI-based learning tools, and leading platforms have reached millions of students across diverse settings. Despite strong momentum and clear benefits in engagement, efficiency, and equity, challenges persist regarding infrastructure, teacher training, data privacy, and linguistic inclusivity. This article reviews theoretical foundations, case studies, current progress, and evolving challenges in AI-driven personalized learning in Indian schools. Recommendations emphasize a collaborative, ethical, and scalable approach to ensure inclusivity and maximize the impact of this technological revolution on future generations.
subject: Articles
  topic: section
subject: AI
  topic: keywords
subject: National Education Policy
  topic: keywords
creator: Dr. Rajendra Prasad Yadav
rights: Copyright (c) 2025 Author
date: 2025-03-28
publication date: 2025-03-28
starting page: 78
ending page: 81

Comparative Review of Silicon-Based and Non-Silicon Solar Cells
type: item
description: Solar photovoltaic (PV) technology has emerged as one of the most critical renewable energy solutions in combating climate change and ensuring long-term energy security. Over the past six decades, silicon-based solar cells have dominated the PV market due to their high efficiency, long-term stability, and well-established manufacturing processes. However, their relatively high manufacturing energy requirements, rigidity, and cost have prompted research into alternative non-silicon technologies such as cadmium telluride (CdTe), copper indium gallium selenide (CIGS), perovskites, organic photovoltaics (OPVs), dye-sensitised solar cells (DSSCs), and quantum dot solar cells (QDSCs). This chapter presents a comprehensive comparative review of these technologies, analysing their material properties, fabrication techniques, performance records, cost structures, environmental implications, and market prospects. The review also discusses the emergence of hybrid and tandem architectures that combine the advantages of different materials to achieve record efficiencies exceeding 33%. The chapter concludes with future research directions and strategies for large-scale sustainable deployment of both silicon-based and non-silicon PV technologies. DOI: https://doi-ds.org/doilink/12.2025-61124448
subject: Articles
  topic: section
subject: Silicon solar cells
  topic: keywords
subject: non-silicon photovoltaics
  topic: keywords
subject: perovskite solar cells
  topic: keywords
subject: thin-film photovoltaics
  topic: keywords
subject: organic photovoltaics
  topic: keywords
subject: dye-sensitised solar cells
  topic: keywords
subject: tandem photovoltaics
  topic: keywords
subject: photovoltaic efficiency
  topic: keywords
subject: renewable energy
  topic: keywords
creator: Naveen Kumar
creator: Dr Aloke Verma
rights: Copyright (c) 2025 Authors
date: 2025-11-29
publication date: 2025-11-29
starting page: 16
ending page: 20

An Enhanced OBS Core Node Design Incorporating Wavelength Conversion and Deflection Routing Mechanisms
type: item
description: The primary challenge in Optical Burst Switching (OBS) networks is the occurrence of burst contention. To address this issue, techniques such as wavelength conversion and deflection routing are widely used within switch fabrics. This study introduces a mathematical model for a newly proposed OBS core-node architecture. The system’s performance is evaluated by analyzing burst loss probability, relying on steady-state occupancy analysis and a Poisson arrival process. The results of the performance assessment are provided for various average burst arrival rates while considering key node parameters, including wavelength conversion capability and support for deflection routing. DOI: https://doi-ds.org/doilink/12.2025-27862832
subject: Articles
  topic: section
subject: Optical Burst Switching (OBS)
  topic: keywords
subject: wavelength conversion capability
  topic: keywords
subject: burst loss probability, deflection routing
  topic: keywords
creator: Waleed M. Gaballah
creator: Hani A. M. Harb
rights: Copyright (c) 2025 Authors
date: 2025-11-29
publication date: 2025-11-29
starting page: 11
ending page: 15

AI in Cybersecurity: Enhancing Digital Defenses with Anomaly Detection and LSTM-Based Threat Prediction
type: item
description: These are the key future areas of research in Applied Artificial Intelligence. In this era of increasingly fast, internet-connected systems, traditional defenses have become inefficient at detecting and responding to various types of sophisticated threats such as malware, phishing, ransomware, distributed denial of service attacks, and more. Such conventional security approaches are not effective with zero-day attacks or new-age evolving attacks. AI-based methods have developed into serious competitors through LSTM networks-an advanced adaptive technology-for continuous improvement of digital defense against anomalous access into network traffic patterns to provide maximum efficiency. To this end, the current research revolves around LSTM-based VAE anomaly detection methodology, utilizing onboard data from live network detection for prediction of future threats. The methodology involves necessary steps that include data pre-processing of Z-score normalization, encoding network traffic into latent representations and then reconstructing the pattern to realize anomaly detection through reconstruction loss and KL divergence. LSTM-based classifier with SoftMax activation is used for threat classification. Testing results indicated improvement in detection accuracy over 90% after 20 epochs of training. This is an AI-driven system that increases real-time monitoring in cybersecurity while reducing false positives associated with it. It future work concentrates on improving the efficiency of the models and embedding them within large-scale security frameworks.
subject: Articles
  topic: section
subject: Cybersecurity, Anomaly Detection, Long Short-term Memory - Variational Auto-Encoder, Threat Prediction, AI-Based Security, Network Traffic Analysis
  topic: keywords
creator: Guman Singh Chauhan
creator: Venkata Surya Teja Gollapalli
creator: Kannan Srinivasan
creator: Rahul Jadon
creator: Gamachis Ragasa Gutata,
rights: Copyright (c) 2025
date: 2025-05-20
publication date: 2025-05-20
starting page: 946
ending page: 955

A Study On Synthesis With Respect To Characterizations And Applications Of Various Types Of Nanoparticles And Composites
type: item
description: Nanoparticles and nanocomposites have emerged as transformative materials due to their superior physicochemical, mechanical, catalytic, and biological properties. This study presents a systematic investigation into the synthesis, characterization techniques, and multi-dimensional applications of metallic, metal oxide, polymeric, carbon-based nanoparticles, and hybrid nanocomposites. Emphasis is placed on green synthesis approaches, physiochemical modifications, and structure–property relationships. Characterization tools such as XRD, FTIR, UV-Vis, SEM, TEM, AFM, TGA, DLS, and Raman spectroscopy are examined in detail to understand morphological, structural, optical, and thermal behaviors. The study also reviews cutting-edge applications in catalysis, drug delivery, energy storage, environmental remediation, biosensing, antimicrobial activity, and smart materials. The findings underscore the tremendous potential of nanoparticles and composites in developing sustainable, efficient, and technologically advanced systems.
subject: Articles
  topic: section
subject: Nanoparticles; Nanocomposites; Green Synthesis; Chemical Reduction; Sol–Gel Method; Hydrothermal Synthesis; Metal Oxide Nanoparticles; Polymer Nanocomposites; Carbon-Based Nanomaterials etc.
  topic: keywords
creator: Urmila Meena
creator: Dr. Mukesh Kumar Bhimwal
rights: Copyright (c) 2025 Authors
date: 2025-09-29
publication date: 2025-09-29
starting page: 23
ending page: 28

Design Of A Low-Latency Pipelined Fir Filter Through Advanced Critical Path Analysis
type: item
description: A filter with a finite period impulse response that settles to zero in a finite amount of time is known as a FIR in digital signal processing. This is frequently contrasted with IIR filters, which may respond endlessly even if they have internal feedback. In this study, we use fine-grained seamless pipelining to propose a novel hardware design for a very high-speed finite impulse response (FIR) filter. By positioning the pipeline registers both across and in between components, the suggested full-parallel pipeline FIR filter may provide an output sample in a few gate delays. Depending on the throughput need, a suitable pipelining strategy may be created with the help of a detailed critical path analysis at the gate level. Two other designs are also shown in this project, each with a unique trade-off between throughput rate and area. The suggested FIR filters are created to measure the highest throughput while striking a compromise between speed and complexity. Model sim software is used for simulation, while Xilinx is used for implementation. DOI: https://doi-ds.org/doilink/11.2025-32813615
subject: Articles
  topic: section
subject: FIR filter, FFA, EKG, DSP, WRT, PP, Carry adder.
  topic: keywords
creator: Dr.K.Suresh Kumar
creator: Dr Md Ejaz Ahamed
creator: P.Rajalingam
rights: Copyright (c) 2024 Authors
date: 2024-12-30
publication date: 2024-12-30
starting page: 58
ending page: 67

Study on Rock Load Variation Considering Weatherability in Bord and Pillar Method of Underground Coal Extraction
type: item
description: In India, bord and pillar is the most commonly used method in the extraction of coal which contributes approximately 98% production from underground. Estimation of the rock load on the roof is important in providing sufficient support systems and mine safety. This research is carried out for the evaluation of rock load variation with weathering, which has been treated as a key parameter in CMRI-ISM RMR classification. A relationship was established between weather ability as determined by slake durability index (SDI) and rock load mobilization due to development drivages in Indian coalfields. The approach combined field technique and geotechnical characterization. Findings indicated that weather ability plays an important role in rock load estimation; for example, first-cycle SDIs are highly inversely correlated to the rock load magnitude. Strong coefficients of determination (R² > 0.85) were found between CMRI-ISM RMR and rock loads for galleries at various widths (3.6-4.8 m). Results have demonstrated that the bulk rock load under weather ability dependent is heavier than that of mechanically dependent, which should be taken into account for support design, especially in moisture-sensitive coal measure rocks, and provide reliable guidance on safety regulation of underground coal mining. DOI: https://doi-ds.org/doilink/11.2025-86468638
subject: Articles
  topic: section
subject: Rock loading effect, Weathering, Bord and pillar method, Slake durability index, CMRI-ISM RMR
  topic: keywords
creator: Suresh Chandra Dansena
creator: Dr. Ajay Kumar Gupta
rights: Copyright (c) 2025
date: 2025-11-15
publication date: 2025-11-15
starting page: 1
ending page: 10

A Critical Analysis of Thematic Depth, Narrative Techniques, and Cultural Representation in the Writings of Tagore, Bandyopadhyay, Devi, and Basu
type: item
description: This empirical study examines the thematic patterns, narrative techniques, and cultural representations in the works of four distinguished Bengali writers: Rabindranath Tagore, Bibhutibhushan Bandyopadhyay, Mahasweta Devi, and Buddhadeva Basu. Through systematic textual analysis of 120 literary works spanning 1890-1990, this research employs quantitative content analysis, thematic coding, and statistical correlation methods to identify distinctive literary characteristics and evolving cultural paradigms. The study analyzes 45,000 pages of text across multiple genres including poetry, novels, short stories, and essays. Data collection involved manual coding of thematic elements, narrative structure assessment, and cultural motif identification validated through inter-rater reliability testing (κ = 0.87). Results reveal significant variations in thematic focus: Tagore emphasizes philosophical humanism (42%), Bandyopadhyay foregrounds nature and rural life (51%), Devi concentrates on social marginalization (63%), and Basu explores psychological modernism (48%). Narrative style analysis demonstrates distinct temporal structures and point-of-view preferences across authors. Statistical tests including chi-square analysis and ANOVA confirm significant differences in cultural representation patterns (p < 0.001). The findings contribute to comparative literary studies by providing empirical evidence of stylistic evolution in Bengali literature and establishing quantifiable parameters for cross-cultural literary analysis.
subject: Articles
  topic: section
subject: Bengali literature, comparative textual analysis, thematic coding, narrative structure, cultural representation, quantitative literary studies, Indian regional literature
  topic: keywords
creator: Mukul Thakur
creator: Dr. Padmalochan Rout
rights: Copyright (c) 2024
date: 2024-03-13
publication date: 2024-03-13
starting page: 74
ending page: 89

Comprehensive Analysis of Preparation Techniques, Structural Features, and Properties in Composite Multiferroic Systems
type: item
description: This empirical study provides a comprehensive exploration of synthesis methodologies, characterization techniques, and fundamental properties in composite multiferroic materials. Multiferroics, exhibiting simultaneous ferroelectric and magnetic ordering, represent a frontier class of multifunctional materials with significant technological potential. Through systematic investigation of 127 distinct composite samples synthesized via solid-state reaction, sol-gel, and hydrothermal methods, we establish critical correlations between processing parameters and resultant multiferroic properties. X-ray diffraction, scanning electron microscopy, and vibrating sample magnetometry analyses reveal distinct phase formation behavior dependent on synthesis route, with optimal magnetoelectric coupling coefficients (up to 18.7 mV/cm·Oe) achieved in samples with controlled interfaces between ferroelectric and ferromagnetic components. Statistical analysis demonstrates significant variations in multiferroic performance across synthesis methods (p<0.001), with hydrothermal processing yielding superior magnetization (1.27±0.11 emu/g) while maintaining comparable ferroelectric properties to conventional techniques. These findings establish comprehensive synthesis-structure-property relationships in composite multiferroics, providing quantitative guidance for optimizing magnetoelectric coupling in next-generation multifunctional devices.
subject: Articles
  topic: section
subject: Composite multiferroics; magnetoelectric coupling; synthesis-structure-property relationship; hydrothermal synthesis; phase interface; ferroelectricity; ferromagnetism.
  topic: keywords
creator: Ashvan Kumar Sahu
creator: Dr. Nitta Kumar Swamy
rights: Copyright (c) 2025
date: 2025-01-13
publication date: 2025-01-13
starting page: 241
ending page: 255

Analysis of Ventilation Requirements Affected by Diesel Machinery in Underground Mines
type: item
description: Underground mines extensively utilize diesel-powered equipment for material handling and transportation, resulting in significant emissions of toxic gases and diesel particulate matter (DPM) that pose serious health risks to miners. This research analyzes ventilation requirements in underground mining operations with a focus on diesel machinery emissions and their control through optimized ventilation systems. The study examines current ventilation standards, emission characteristics, and airflow requirements across various mining jurisdictions. Through comprehensive literature review and data analysis, this research identifies that ventilation systems consume approximately 30-40% of total underground mine energy, with airflow requirements ranging from 0.047 to 0.067 m³/s per kilowatt of diesel engine power depending on regulatory frameworks. The study reveals that diesel equipment contributes over 50% of heat load in deep mines while emitting carcinogenic DPM, carbon monoxide, and nitrogen oxides. Results demonstrate that optimizing auxiliary ventilation systems through computational fluid dynamics modeling and implementing ventilation-on-demand strategies can reduce energy consumption by 31-53% while maintaining acceptable air quality standards. The research concludes that integrated approaches combining improved engine technologies, after-treatment devices, and advanced ventilation control systems are essential for ensuring miner safety and operational efficiency in modern underground mining operations. DOI: https://doi-ds.org/doilink/10.2025-53564516
subject: Articles
  topic: section
subject: Underground mine ventilation, Diesel particulate matter, Airflow requirements, Emission control, Computational fluid dynamics
  topic: keywords
creator: Nallamekala Ashok Kumar
creator: Dr. Imran Athar Beg
creator: Gopal Singh
rights: Copyright (c) 2025
date: 2025-10-13
publication date: 2025-10-13
starting page: 26
ending page: 38

Use of Industrial and Mining Wastes for Backfill in Subsurface Mining Operations
type: item
description: The escalating generation of industrial and mining wastes poses significant environmental challenges globally, necessitating sustainable disposal solutions. This research investigates the utilization of various industrial wastes including fly ash, slag, coal gangue, construction and demolition waste, and mine tailings as backfill materials in subsurface mining operations. The study aims to evaluate the mechanical properties, environmental sustainability, and economic feasibility of waste-based backfill composites. A comprehensive experimental methodology was employed involving laboratory testing of different waste combinations with varying cement ratios, curing periods, and compositional parameters. Results demonstrate that cemented paste backfill incorporating 30% fly ash with 8% cement content achieved uniaxial compressive strength of 4.95 MPa after 28 days curing, meeting mining industry requirements. Statistical analysis of five experimental datasets revealed significant correlations between waste content, binder ratio, and mechanical performance. The findings confirm that waste-based backfills effectively control ground subsidence while promoting circular economy principles. This research contributes to sustainable mining practices by transforming hazardous waste streams into functional engineering materials, simultaneously addressing environmental concerns and improving mine stability. DOI: https://doi-ds.org/doilink/10.2025-87317652
subject: Articles
  topic: section
subject: Backfill mining, Industrial waste, Fly ash, Mine tailings, Cemented paste backfill
  topic: keywords
creator: Mitul Karmoker
creator: Gopal Singh
creator: Dr. Imran Athar Beg
rights: Copyright (c) 2025
date: 2025-10-13
publication date: 2025-10-13
starting page: 14
ending page: 25

Optimization Techniques and Performance Assessment of IoT-Enabled WBANs in Healthcare Systems
type: item
description: Wireless Body Area Networks (WBANs) integrated with Internet of Things (IoT) technology have emerged as transformative solutions for continuous healthcare monitoring systems. This research investigates optimization techniques and performance assessment mechanisms for IoT-enabled WBANs in healthcare applications. The primary objective focuses on evaluating energy efficiency, quality of service parameters, and network reliability through advanced optimization algorithms. The methodology encompasses systematic analysis of IEEE 802.15.6 standard implementation, examining multiple performance metrics including throughput, packet delivery ratio, latency, and energy consumption across various network configurations. Experimental results demonstrate that optimized WBANs achieve 35% reduction in energy consumption, 97.5% packet delivery ratio, and latency below 92 milliseconds. The study employs machine learning algorithms, ant colony optimization, and particle swarm optimization techniques for cluster head selection and routing protocols. Statistical analysis reveals significant improvements in network lifetime extending up to 40% compared to traditional approaches. The findings confirm that integrated optimization strategies effectively balance energy efficiency with quality of service requirements, providing robust and scalable solutions for next-generation healthcare monitoring systems.
subject: Articles
  topic: section
subject: Wireless Body Area Networks, IoT Healthcare, Energy Optimization, Quality of Service, Performance Metrics
  topic: keywords
creator: Diwakara Vasuman M S
creator: Dr. Sridhara Archarya
rights: Copyright (c) 2025 Authors
date: 2025-07-29
publication date: 2025-07-29
starting page: 124
ending page: 130

Experimental Analysis of Underground Mine Ventilation System of Indian Metal Mines
type: item
description: Underground mine ventilation systems in Indian metal mines represent critical infrastructure for ensuring miner safety, productivity, and operational efficiency. This experimental study examines ventilation parameters across five major zinc-lead metal mining operations in India, specifically analyzing Rampura Agucha, Rajpura Dariba, Zawar, Sindesar Khurd, and Kayad mines in Rajasthan state. The research investigates airflow distribution, fan performance, air quality parameters, and energy consumption patterns in deep underground metal mining environments. Primary objectives include quantifying ventilation efficiency, assessing thermal comfort conditions, evaluating contaminant dilution effectiveness, and determining optimal fan operation strategies. Methodology employed field measurements, computational fluid dynamics simulations, and statistical analysis of ventilation data collected over twelve months during financial year 2023-24. Results demonstrate that Indian metal mines maintain airflow rates between 1450-2024 m³/sec, with primary ventilation consuming 32-34% of total mine electricity. Temperature regulation challenges persist at depths exceeding 600 meters, necessitating auxiliary cooling systems. Discussion reveals significant energy optimization potential through variable speed drives and ventilation-on-demand systems, achieving 25-31% energy reduction. The study concludes that modernization of ventilation infrastructure, implementation of intelligent monitoring systems, and adoption of international best practices can substantially enhance both safety parameters and operational economics in Indian underground metal mining sector. DOI: https://doi-ds.org/doilink/10.2025-74516576
subject: Articles
  topic: section
subject: Underground mine ventilation, metal mines India, airflow optimization, fan efficiency, thermal management
  topic: keywords
creator: Veerappa Savakar
creator: Ashit Datta
creator: Patitapaban Sahu
creator: Purnima Srivastava
rights: Copyright (c) 2025
date: 2025-10-07
publication date: 2025-10-07
starting page: 1
ending page: 13

Toward Sustainable Development Through Green Finance
type: item
description: Environmental change, energy constraints, and financial crisis are the three largest threats to the global economy in this era of fast technological advancement.. The reason for this is that governments incur costs associated with environmental deterioration as a result of financial development. To achieve a balance between the market and the natural world, green financing is the way to go. Financial backing for environmentally friendly development practices, sometimes known as "green finance," significantly cuts down on emissions of pollutants that deplete the ozone layer and other harmful air pollutants. If the country wants to enhance its finances, it should invest more in green gardening, green buildings, green security, and other green initiatives. The goal of this study is to survey what is been written on green finance and to speculate on its potential future development in India. DOI: https://doi-ds.org/doilink/10.2025-93865331
subject: Articles
  topic: section
subject: Environment; Green finance; Green building; Green projects; Renewableenergy.
  topic: keywords
creator: Dr. Sachin Ashok Deshmukh
rights: Copyright (c) 2023
date: 2023-06-01
publication date: 2023-06-01
starting page: 123
ending page: 132

A Critical Review of Composite Phase Change Materials in Lithium-Ion Battery Thermal Management
type: item
description: The rapid adoption of lithium-ion batteries in electric vehicles has heightened concerns over thermal safety and performance optimization, particularly the prevention of thermal runaway. Effective battery thermal management systems (BTMS) are therefore essential. This review focuses on composite phase change materials (CPCMs) as advanced solutions for BTMS, examining their thermal characteristics, modification strategies, and performance outcomes. The study evaluates key composite structures such as expanded graphite, metal foams, and nanoparticle-enhanced organic PCMs. Research objectives include assessing improvements in thermal conductivity, efficiency of temperature regulation, and effectiveness in mitigating thermal runaway. Methodologically, the review synthesizes experimental findings from peer-reviewed studies involving thermal property characterization, computational simulations, and performance testing under varied discharge rates. Results show expanded graphite composites deliver thermal conductivity enhancements of 400–1700%, while metal foam composites reduce cell temperature by 4–13 °C. Nanoparticle integration offers moderate improvements of 31–124% depending on concentration. Hybrid systems that couple CPCMs with active cooling provide superior thermal uniformity and safety. The findings confirm that multi-component CPCMs with three-dimensional thermal networks hold strong potential as next-generation BTMS for electric vehicles.
subject: Articles
  topic: section
subject: Composite phase change materials, Lithium-ion battery, Thermal management, Expanded graphite, Thermal conductivity, Thermal runaway
  topic: keywords
creator: Arpan Samanta
creator: Dr. Nilesh Diwakar
creator: Mr. Ritesh Khaterkar
rights: Copyright (c) 2025
date: 2025-08-01
publication date: 2025-08-01
starting page: 98
ending page: 104

Enhancing Asset Reliability through Risk-Based Inspection and Reliability-Centered Maintenance in SAP EAM
type: item
description: Risk-Based Inspection (RBI) and Reliability-Centered Maintenance (RCM) have emerged as critical methodologies for enhancing asset reliability in industrial operations. This research investigates the integration of RBI and RCM frameworks within SAP Enterprise Asset Management (EAM) systems to optimize maintenance strategies and improve asset performance. The study employed a mixed-method approach, combining quantitative analysis of maintenance data from manufacturing facilities and qualitative assessment of implementation practices. Data were collected from 150 industrial facilities across oil and gas, manufacturing, and utilities sectors implementing integrated RBI-RCM approaches through SAP EAM. Results demonstrate that integrated RBI-RCM implementation through SAP EAM reduces unplanned downtime by 45-50%, decreases maintenance costs by 25-30%, and improves asset availability by 35-40%. The hypothesis that synchronized RBI-RCM methodologies within SAP EAM significantly enhance asset reliability metrics compared to traditional maintenance approaches was confirmed. Discussion reveals that successful implementation requires organizational commitment, data quality management, and continuous improvement processes. The findings suggest that combining RBI's risk prioritization with RCM's systematic approach creates a comprehensive asset integrity framework. This research contributes to understanding how digital transformation through SAP EAM enables predictive maintenance capabilities and data-driven decision making in asset-intensive industries. DOI: https://doi-ds.org/doilink/10.2025-21618375
subject: Articles
  topic: section
subject: Risk-Based Inspection, Reliability-Centered Maintenance, SAP Enterprise Asset Management, Asset Reliability, Predictive Maintenance
  topic: keywords
creator: Akhilesh Kumar Aleti
rights: Copyright (c) 2025
date: 2025-09-29
publication date: 2025-09-29
starting page: 11
ending page: 22

Computational Approaches for Investigating Basic Material Properties of Cobalt-Aluminum Alloys
type: item
description: Cobalt-aluminum (Co-Al) alloys have garnered significant attention as potential high-temperature structural materials due to their exceptional thermal stability, mechanical properties, and oxidation resistance. This study employs comprehensive computational methodologies, primarily density functional theory (DFT) calculations and machine learning approaches, to investigate the fundamental material properties of Co-Al alloy systems. The research objectives encompass determining structural parameters, elastic properties, thermodynamic stability, and electronic characteristics of various Co-Al intermetallic phases including CoAl, Co3Al, and CoAl3. The methodology integrates first-principles calculations using DFT with generalized gradient approximation (GGA) functionals, complemented by high-throughput computational screening and machine learning models for property prediction. Results reveal that Co3Al exhibits superior mechanical stability with calculated elastic modulus values ranging from 180-220 GPa and bulk modulus of approximately 200 GPa. The formation energies demonstrate thermodynamic favorability with negative values between -0.45 to -0.65 eV/atom for stable phases. Electronic structure analysis indicates strong covalent-metallic bonding characteristics contributing to enhanced mechanical properties. The computational predictions show excellent agreement with available experimental data, validating the accuracy of employed methodologies. This comprehensive investigation provides crucial insights into structure-property relationships in Co-Al systems, facilitating accelerated alloy design for advanced high-temperature applications in aerospace and energy sectors.
subject: Articles
  topic: section
subject: Cobalt-Aluminum Alloys, Density Functional Theory, Elastic Properties, Computational Materials Science, Intermetallic Compounds
  topic: keywords
creator: Dr. Sachin Baraskar
creator: Saloni Singh
rights: Copyright (c) 2025
date: 2025-01-25
publication date: 2025-01-25
starting page: 225
ending page: 240

Green Innovations in Water and Wastewater Treatment: Mechanistic Insights and AI Integration
type: item
description: The pursuit of sustainable water purification technologies has catalyzed the emergence of green materials as high-performance alternatives to conventional synthetic agents. Sourced renewably and characterized by their biodegradability and low environmental toxicity, these advanced materials represent a paradigm shift in water treatment. This review highlights the exceptional potential of natural nanomaterials—including cellulose nanofibers, chitosan, alginate, and lignin—as well as their engineered composites, functionalized hydrogels, and aerogels for the highly efficient adsorption of heavy metals, dyes, and persistent organic contaminants. A critical analysis of contaminant removal mechanisms is presented, alongside the application of advanced modeling and optimization techniques. These computational tools are indispensable for predicting material properties, simulating molecular interactions, and tailoring bespoke solutions, thereby accelerating rational design. While challenges in scalability, synthesis cost, and real-world validation remain, this work concludes that the integration of green materials with cutting-edge computational models is pivotal for developing the next generation of efficient, sustainable, and environmentally benign water treatment systems, directly supporting global sustainable development and climate action goals.
subject: Articles
  topic: section
subject: Green materials; Sustainable water treatment; Natural polymers; Adsorption mechanisms; Computational modeling; Contaminant removal.
  topic: keywords
creator: Dr. Himanshu Sharma
creator: Dr. Priti Sharma
rights: Copyright (c) 2024
date: 2024-03-25
publication date: 2024-03-25
starting page: 48
ending page: 73

Wire-Arc Additive Manufacturing (WAAM) for the Fabrication of High Fatigue-Resistant Railcar Couplers
type: item
description: Wire-Arc Additive Manufacturing (WAAM) presents a revolutionary approach for fabricating high fatigue-resistant railcar couplers in the Indian railway sector. This study investigates the application of WAAM technology to enhance the fatigue life and structural integrity of railcar couplers compared to conventional casting methods. The primary objective was to evaluate the mechanical properties, fatigue resistance, and cost-effectiveness of WAAM-fabricated couplers. A comprehensive methodology involving experimental design, WAAM fabrication using ER110S-G high-strength steel wire, mechanical testing, and fatigue analysis was employed. The hypothesis proposed that WAAM-fabricated couplers would demonstrate superior fatigue resistance due to refined microstructure and absence of casting defects. Results demonstrated that WAAM couplers exhibited 35-40% improved fatigue life compared to cast steel equivalents, with ultimate tensile strength reaching 850-920 MPa and yield strength of 720-780 MPa. The refined grain structure and elimination of casting defects contributed to enhanced fatigue performance. Discussion reveals that WAAM offers significant advantages including reduced material waste, shorter production cycles, and improved mechanical properties. The study concludes that WAAM technology provides a viable and superior alternative to conventional casting for railcar coupler fabrication, offering enhanced safety, reliability, and economic benefits for Indian Railways.
subject: Articles
  topic: section
subject: Wire-Arc Additive Manufacturing, WAAM, Railcar Couplers, Fatigue Resistance, Indian Railways
  topic: keywords
creator: Mohammed Fahad Ismail Shaikh
creator: Dr. Priyanka Jhavar
rights: Copyright (c) 2025
date: 2025-01-25
publication date: 2025-01-25
starting page: 217
ending page: 224

Study on the Performance of Solar-Evaporative Cooling Technology for Preserving Crops in Tropical Environments
type: item
description: Solar-evaporative cooling technology represents a sustainable solution for reducing postharvest crop losses in tropical environments where conventional refrigeration systems are economically and logistically challenging. This study evaluates the performance of solar-powered evaporative cooling storage systems (SPECSS) for preserving various agricultural crops including tomatoes, mangoes, bananas, and carrots. The research involved comprehensive analysis of temperature reduction, humidity enhancement, and shelf-life extension capabilities under tropical conditions. Results demonstrated that SPECSS achieved temperature depressions of 7.8-15.4°C and relative humidity increases from 44% to 96.8% compared to ambient conditions. The shelf lives of tomatoes, mangoes, bananas, and carrots stored in SPECSS were extended to 21, 14, 17, and 28 days respectively, compared to 6, 5, 5, and 8 days under ambient storage. The cooling efficiency reached 84.7% with optimal pad thickness of 80mm, maintaining chamber temperatures at 25°C with 82.4% relative humidity. The system demonstrated significant potential for reducing the 25-30% postharvest losses typically experienced in tropical regions, providing an economically viable and environmentally sustainable solution for smallholder farmers and rural communities lacking grid electricity access.
subject: Articles
  topic: section
subject: Solar cooling, evaporative cooling, crop preservation, postharvest losses, tropical agriculture.
  topic: keywords
creator: Aditya Singh
creator: Dr. Sachin Baraskar
rights: Copyright (c) 2025
date: 2025-01-25
publication date: 2025-01-25
starting page: 205
ending page: 216

Structural Analysis of CFST and DS CFST Using ANSYS Workbench
type: item
description: Concrete-Filled Steel Tubes (CFSTs) have emerged as efficient structural members in modern construction due to their superior strength, stiffness, and ductility arising from the composite interaction between a steel tube and infilled concrete. However, the depletion of natural river sand, a primary component of conventional concrete, has raised sustainability concerns and prompted the search for alternative fine aggregates. In this context, dune sand, abundantly available in desert regions, offers potential as a sustainable replacement material. This thesis presents a comparative study of the structural performance of conventional CFST and Dune Sand Concrete-Filled Steel Tubes (DS CFST) through finite element analysis (FEA) conducted in ANSYS Workbench. Both CFST and DS CFST models were developed with identical geometry (1000 mm height, 150 mm diameter, 5 mm steel thickness), material definitions, meshing strategies, and boundary conditions to ensure direct comparability. Static structural analyses evaluated maximum deformation and equivalent elastic strain, while eigenvalue buckling analyses assessed critical load multipliers and mode shapes. Results indicated that DS CFST exhibited nearly identical deformation (9.37 × 10⁻⁹ m vs. 9.40 × 10⁻⁹ m for CFST) and slightly lower strain (2.63 × 10⁻⁸ m/m vs. 2.84 × 10⁻⁸ m/m). DS CFST showed a marginally higher buckling load multiplier (4.05 × 10⁵), suggesting improved global stability. The findings confirm that dune sand concrete can replace conventional concrete in CFSTs without compromising performance, while contributing to sustainable construction practices by reducing reliance on river sand. The study provides novel numerical evidence supporting DS CFST as a viable structural solution, particularly suited for sand-rich and desert regions. Limitations include the exclusive reliance on simulations and single geometry and future research should incorporate experimental validation, varied loading conditions, and extended g…
subject: Articles
  topic: section
subject: Concrete-Filled Steel Tubes, Dune Sand, Finite Element Analysis, ANSYS, Buckling, Sustainable Construction
  topic: keywords
creator: BHARATH GOWDAN
creator: ABDUL REHAMAN,
rights: Copyright (c) 2025
date: 2025-09-19
publication date: 2025-09-19
starting page: 1
ending page: 10

Bridging Automation and Intelligence: UiPath’s Agentic AI Framework and Robotic Process Automation Platform
type: item
description: UiPath Maestro introduces agentic automation, which goes beyond traditional RPA by handling complex, unstructured tasks with real-time decision-making. While conventional RPA is ideal for repetitive, rule-based tasks, Maestro integrates AI agents, BPM, and process intelligence to optimize dynamic workflows. Users can design processes using BPMN models or speed up creation with Autopilot. Business users build workflows visually, and developers can later integrate RPA bots. Real-time dashboards help monitor performance, fix issues, and reduce delays between teams. UiPath’s low-code platform makes automation accessible, improving speed, accuracy, and cost-efficiency. Maestro enhances this by enabling smarter, adaptive automation for modern business needs.
subject: Articles
  topic: section
subject: RPA, UiPath, Low-Code Automation, Business Process Automation, Drag-and-Drop.
  topic: keywords
creator: Sudheer reddy patlolla
rights: Copyright (c) 2025
date: 2025-08-27
publication date: 2025-08-27
starting page: 91
ending page: 97

Corporate Social Responsibility 2.0: From Compliance to Competitive Advantage
type: item
description: The landscape of corporate obligation is undergoing a profound and irreversible transformation. This paper delineates the critical evolution from traditional, reactive Corporate Social Responsibility—termed here as CSR 1.0—which treated social and environmental concerns as peripheral compliance issues or public relations exercises, to a transformative, strategic paradigm we define as CSR 2.0. We posit that CSR 2.0 is no longer an optional add-on or a charitable sideline but has emerged as a fundamental driver of competitive advantage and long-term, sustainable value creation. It represents a fundamental rewiring of corporate purpose, moving from "doing good" alongside business to "doing good through business." Our analysis begins by deconstructing the inherent limitations of the compliance-based model, illustrating how its siloed, often superficial nature fails to address the root of a corporation's societal impact and leaves it vulnerable to accusations of greenwashing. In contrast, we define the core tenets of CSR 2.0 as deep integration into corporate strategy and operations, a rigorous materiality assessment to focus efforts on the most impactful issues, and purpose-driven innovation that uses societal challenges as a catalyst for new products, services, and business models.
subject: Articles
  topic: section
subject:
  topic: keywords
  value: Corporate Social Responsibility (CSR), CSR 2.0, Competitive Advantage, Strategic Integration, ESG (Environmental, Social, and Governance), Creating Shared Value, Stakeholder Theory, Purpose-Driven Business, Sustainable Development, Triple Bottom Line, Brand Equity, Operational Efficiency, Talent Management.
creator: Dr. Preeti Gahlot
rights: Copyright (c) 2022 Authors
date: 2022-04-29
publication date: 2022-04-29
starting page: 79
ending page: 95

Structural Engineering Insights into the Chenab Railway Bridge Design
type: item
description: The Chenab Railway Bridge, standing at 359 meters above the Chenab River in Jammu and Kashmir, India, represents a remarkable achievement in structural engineering (Kumar et al., 2023). This paper presents comprehensive insights into the design, construction, and engineering challenges of the world's highest railway bridge. The bridge spans 1,315 meters with a main arch span of 467 meters, incorporating innovative steel-concrete composite construction (Singh & Sharma, 2022). The research objectives focused on analyzing structural design parameters, seismic resistance capabilities, and construction methodologies employed. Through detailed analysis of engineering drawings, material specifications, and construction reports, this study employed a mixed-method approach combining quantitative structural analysis with qualitative assessment of construction challenges. The bridge utilizes E410-grade steel with 63mm blast-proof specifications and concrete-filled steel box sections for enhanced structural integrity (Patel et al., 2024). Results demonstrate exceptional seismic resistance up to magnitude 8.0 earthquakes and wind load resistance up to 266 km/h. The innovative arch design with two-ribbed configuration provides optimal load distribution across the challenging Himalayan terrain. This engineering marvel not only connects Kashmir valley with the Indian mainland but also sets new benchmarks for high-altitude railway bridge construction, proving that extreme geographical challenges can be overcome through advanced engineering solutions and innovative construction techniques.
subject: Articles
  topic: section
subject: Chenab Bridge, Railway Engineering, Steel Arch Bridge, Seismic Design, Structural Analysis
  topic: keywords
creator: Shubham Chouhan
creator: Mr. Rajesh Chouhan
rights: Copyright (c) 2025
date: 2025-05-01
publication date: 2025-05-01
starting page: 936
ending page: 945

Advanced M-Dab-Based Ac/Dc Charger With Optimized Conduction Loss And Hybrid Charge–Discharge Strategy For Electric Vehicles
type: item
description: The rapid growth of electric vehicles (EVs) demands charging infrastructures that offer both high efficiency and reliability while addressing grid integration challenges. This work presents a novel high-power density and low conduction loss bidirectional AC/DC charging pile scheme with a hybrid charge–discharge control strategy. The proposed system leverages an optimized power conversion topology to minimize conduction and switching losses, thereby enhancing overall efficiency and reducing thermal stress on components. The bidirectional capability allows not only fast and efficient charging of EV batteries but also controlled discharge back to the grid, supporting vehicle-to-grid (V2G) applications and grid stability. A hybrid control strategy is implemented to balance constant current/constant voltage charging with dynamic discharge management, ensuring battery longevity and reliable energy exchange. Simulation and experimental results validate that the system achieves superior power density, high efficiency, and stable operation under varying load and grid conditions. This approach provides a scalable and practical solution for next-generation EV charging piles, promoting energy sustainability and smart grid integration. DOI: https://doi-ds.org/doilink/08.2025-98635245
subject: Articles
  topic: section
creator: Kanna Sai Moulikrishna
creator: B Jailsingh
rights: Copyright (c) 2025
date: 2025-08-21
publication date: 2025-08-21
starting page: 83
ending page: 90

Integrated Pq Enhancement System For Industrial And Commercial Grids Using Advanced Power Oscillation Mitigation Techniques
type: item
description: The increasing penetration of solar power in commercial and industrial facilities poses significant challenges to power quality due to intermittency, voltage fluctuations, and power oscillations. This work proposes an integrated approach that combines solar photovoltaic (PV) generation with a battery energy storage system (BESS) to mitigate power oscillations and enhance overall power quality. The BESS is strategically controlled to smooth out variations in solar output, regulate voltage, and maintain grid stability under dynamic load conditions. Simulation and performance analysis demonstrate that the proposed system not only improves power factor and reduces harmonic distortion but also ensures reliable and uninterrupted power supply for commercial and industrial applications. By effectively integrating renewable energy with advanced energy storage, the solution addresses both sustainability and operational efficiency, making it a practical model for modern smart grids. DOI: https://doi-ds.org/doilink/08.2025-33731528
subject: Articles
  topic: section
subject: Solar photovoltaic (PV), Battery energy storage system (BESS), Power quality improvement, Power oscillations mitigation, Voltage regulation, Harmonic distortion reductiony.
  topic: keywords
creator: Thatikonda Sruthi
creator: B.Kavya
rights: Copyright (c) 2025
date: 2025-08-21
publication date: 2025-08-21
starting page: 74
ending page: 82