https://or.niscpr.res.in/index.php/JSIR/issue/feed Journal of Scientific & Industrial Research (JSIR) 2025-02-13T17:34:17+0530 Dr Narendra Kumar Sahoo jsir@niscpr.res.in Open Journal Systems <p style="text-align: justify;">This oldest journal of NISCAIR (started in1942) carries comprehensive reviews in different fields of science &amp; technology (S&amp;T), including industry, original articles, short communications and case studies, on various facets of industrial development, industrial research, technology management, technology forecasting, instrumentation and analytical techniques, specially of direct relevance to industrial entrepreneurs, debates on key industrial issues, editorials/technical commentaries, reports on S&amp;T conferences, extensive book reviews and various industry related announcements.It covers all facets of industrial development.<strong> Impact Factor of JSIR is 0.7 (JCR 2023).</strong></p> <p style="text-align: justify;"><strong><a href="https://nopr.niscpr.res.in/jinfo/jsir/JSIR%2082(05)%20Instruction%20to%20Contributers.pdf" target="_blank" rel="noopener">Instructions to Author Guidelines</a></strong></p> https://or.niscpr.res.in/index.php/JSIR/article/view/8327 GAN-CNN based Structure-Preserving Mixed Noise Removal Model for Enhancing Medical Image 2024-10-14T12:01:04+0530 Vishal H Shah vishalhshah@bitmesra.ac.in Prajna Parimita Dash ppdash@bitmesra.ac.in <p>The current era of the Internet of Medical Things (IoMT) and Medical Artificial Intelligence (MAI) makes medical imaging a prominent mode of providing effective solutions in diagnosis and prognosis. The main issue with these images is the presence of noise that requires enhancement through effective edge preservation and noise reduction. The proposed work introduces a two-stage Deep Learning (DL) model, utilizing Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNN) for jointly reducing speckle, impulse, and Gaussian noise while preserving edge information in noisy medical images. The work also explores the probabilistic evaluation of generators and discriminators for compensating lossy patches to ensure image quality. The performance of the proposed model is investigated by considering three different performance metrics, namely, PSNR, FSIM, and SSIM. Moreover, non-parametric statistical tests like the Sign test, Wilcoxon Signed rank tests and Friedman tests are also conducted to assess the dominance of the proposed model over other state-of-the-art approaches. Two-stage GAN-based models generate realistic, high-quality images by effectively suppressing inherently present spurious noise in medical images and simultaneously preserving the edge information.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/9213 Simulative Performance Investigation of OFDM & f-OFDM for Optical Wireless Communication System 2024-04-19T12:36:31+0530 Kritika Upadhyay kritikaupadhyay@nitdelhi.ac.in Manisha Bharti manishabharti@nitdelhi.ac.in <p>Internet of Things (IoT) is a fast-growing technology that requires innovative solutions and technologies to realize its vision efficiently. Optical Wireless Communication (OWC) technology is one of the emerging connectivity technologies that could benefit this IoT deployment. Orthogonal Frequency Division Multiplexing (OFDM) is regarded as a technique of encoding data on multiple carriers as it promises high data rates and lays down the foundation for many standards of wireless communication such as 5G network. However, large OOBE (Out-Of-Band Emission) and large Peak to Average Power Ratio (PAPR) in OFDM makes it less potent to meet demand of high data rate. Therefore, Filtered-OFDM (f-OFDM) act as promising candidate for future wireless generation networks. The motivation of this paper is to analyze the applicative aspect of Multicarrier Modulation schemes (OFDM and f-OFDM) in implementation of OWC technology within the IoT. The parameters used for evaluating the robustness of the designed system are namely- Bit error Rate (BER), Signal to noise ratio (SNR) Peak to average power ratio (PAPR) and Power Spectral Density (PSD).The investigation reveals an increment of 25% SNR and decrement of 16% occurrences of error during transmission for f-OFDM. Further, Quadrature Amplitude Modulation (QAM) modulation scheme increase this SNR to 30% (approx.), thus promising the designed system as suitable contender for upcoming linked OWC and wireless networks like IoT.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/8130 MBO: A Novel Memory based Optimizer for Continuous and Discrete Optimization Problem 2024-09-19T12:03:13+0530 Rajesh Ranjan rajesh_61900059@nitkkr.ac.in Jitender Kumar Chhabra jitenderchhabra@gmail.com <p>This study introduces a novel metaheuristic approach called Memory Based Optimizer (MBO), which emulates the problem-solving process through multiple stages by utilizing the best solution obtained in terms of memory. Rooted in principles of human psychology, MBO reflects the tendency for individuals to solve problems incrementally, using previous learning to take small steps toward an optimal solution within a limited number of attempts. MBO is first evaluated on ten CEC 2019 Benchmark Functions, and its results are compared with ten other metaheuristic algorithms under similar execution conditions. In its binary form, MBO is also applied as a wrapper for feature selection in supervised machine learning using the K-NN classifier on twelve benchmark classification datasets. The findings indicate significant improvements in average accuracy and optimal feature selection compared to other metaheuristic approaches. As per the simulation results, MBO has outperformed other metaheuristics approaches in 5 out of 10 continuous benchmark functions. Further, the MBO has achieved higher average accuracy in 11 out of 12 datasets, along with better execution times in 9 out of 12 datasets when applied as a wrapper for feature selection tasks, the average improvement in accuracy and F1 score is reported as 2.8746% and 3.1643% when compared with other metaheuristic approaches under similar execution environment further validating its robustness and efficiency across multiple optimization tasks.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/8163 MCDM Approach Combining DEA and AHP Methods in Sustainable Tourism: Case of Serbia 2024-05-14T10:27:15+0530 Zlatko Langovic zlpitanja@gmail.com Brankica Pazun brankica.pazun@fim.rs Zeljko Grujcic zeljko.grujcic@fim.rs Magdalena Nikolic magdalena.nikolic@fim.rs Ana Langovic Milicevic ana.langovic@gef.bg.ac.rs Dragan Ugrinov dragan.ugrinov@gmail.com <p>This paper focuses on the workforce capable of implementing new trends through the application of environmental tourism and IT knowledge. Multi-criteria optimization methods such as Data Envelopment Analysis (DEA) and Analytical Hierarchy Process (AHP) were used to solve a particular and sensitive business decision problem. A unique questionnaire on five global trends - renewable energy growth, pollution, electrification, cloudification, data boom and smartization - was developed to assess the capabilities of potential candidates in relation to environmental issues in tourism and to determine whether they are able to solve tasks in a sustainable way. This paper proposes an approach for the selection of candidates for sustainable and green tourism. From 200 candidates, data collected in a northern region of Serbia in the fall of 2023, the model resulted in the 5 best alternatives under 5 criteria. The final solution was the alternative/candidate B with the consistency index 0.03. The intention was that by combining AHP and DEA methods to evaluate efficiency, the subjectivity of decision making in the selection of candidates would be minimized. The new value of this work could be that advanced technologies are integrated into sustainable tourism in a practical and scalable way, and that methods for evaluating and implementing the technologies in question are developed. This could form the basis for future research and practical applications.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/9675 Enhancing UI/UX Design for Children's Educational Gaming Platforms: An Integrated Multicriteria Decision Making Framework 2024-04-19T15:00:07+0530 Mangesh Joshi profmangeshjoshi@gmail.com Pranjali Deole profmangeshjoshi@gmail.com <p>This study aims to enhance the User Interface (UI) and User Experience (UX) design of children's educational gaming platforms by identifying key influential factors and providing actionable insights. Recognizing the importance of digital learning tools, the research employs an Integrated Multicriteria Decision Making Framework, utilizing the Spherical Fuzzy Analytical Hierarchy process to calculate factor weights and Interpretive Structural Modelling (ISM) to unravel complex interrelationships. The findings highlight the critical importance of age-appropriate content (weight 0.139) tailored to children's cognitive abilities and developmental stages, alongside crucial components like visual design (weight 0.102), and educational content (weight 0.101). MICMAC (Matrice d'impacts croisés multiplication appliquée á un classment) analysis is carried out to classify factors into autonomous, dependent, linkage, and driving groups. Practical implications emphasize cross-platform compatibility, background score optimization, and improvements in interactivity, accessibility, safety, privacy, engagement, and feedback mechanisms. The study offers valuable insights and actionable recommendations to enhance UI/UX design, creating immersive and impactful learning experiences tailored to young users. By integrating multiple decision-making methods, the research presents a novel, structured approach to comprehensively analyze and prioritize UI/UX factors, contributing to the discourse on optimizing digital learning environments for children.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/13919 Advancing Cardiac Disease Detection Using Feature Extraction, Feature Selection, and Ensemble Learning Approaches 2024-10-10T10:43:11+0530 S R Tripathy smitaranjan.tripathy@gmail.com Adyasha Rath adyasha.rath@cgu-odisha.ac.in Rohit Sharma rohithmr.21791@gmail.com Ganapati Panda ganapati.panda@gmail.com Meenakshi Sharma ms722530@gmail.com <p>Approximately 26 million individuals globally struggle with cardiac disease, and the incidence is increasing by 2% each year. To reduce the healthcare burden, the researchers propose various CAD models. Feature extraction and Feature selection are essential in reducing the model complexity and memory requirement. In the proposed research, we investigate the performance of different feature extraction and selection methods using two heart sound datasets. The features are extracted using MFCC and DWT methods from heart sounds. Four feature selection methods (Fisher’s Score, mRMR, ReliefF, and Gini Index) are analyzed and ranked using the D-CRITIC TOPSIS technique. The two best models based on feature selection are utilized in the weighted average ensemble. The weights in ensemble learning are optimized using the Dwarf Mongoose optimization algorithm. The feature fusion model combining DWT and MFCC with mRMR for feature selection achieved the highest performance on the PhysioNet dataset, with an accuracy of 82.70%, an F1-Score of 0.8369, and an AUC-ROC score of 0.9092. The best accuracy, F1-Score, and AUC-ROC score on the PASCAL CHSC dataset are 79.64%, 0.7826, and 0.8116, respectively. The study compared four feature selection methods. The mRMR-based model achieved the highest TOPSIS score and ranked first in the performance table. The findings demonstrate that the mRMR feature selection performed better than other feature selection for both feature extraction methods evaluated in this study. The ensemble model using mRMR and ReliefF outperformed all base models and achieved the highest performance metrics. This study highlighted the enhanced detection of cardiac disorders through the combined effectiveness of feature extraction, feature selection, classification models, and ensemble strategies.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/8882 Histopathological Studies on Liver, Kidney and Spleen of Staphylococcus aureus Infected BALB/c Mice 2024-05-16T14:58:43+0530 Dr. Anita Rana anitakadian23@gmail.com <p>Worker bees collect resin from tree buds, sap flows and other botanical sources mix it with salivary enzymes and wax to create propolis also referred as “bee glue”. They use it to seal gaps in the beehive, reinforce structural stability and protect against microorganisms. This study focuses on therapeutic effects of propolis on histology of liver, kidney and spleen of BALB/c mice infected with <em>Staphylococcus aureus</em>. In the experimental regimen, the <em>Staphylococcus aureus</em> infected mice group was compared with a normal control group and treatment groups, including those receiving propolis, antibiotics (ampicillin and amoxicillin) and a combination of propolis with antibiotics. Administration of <em>Staphylococcus aureus</em> caused notable histological changes in the organs. However, treatment with propolis extract at a dose of 250 mg/kg body weight successfully mitigated the histological alterations in liver, kidney and spleen of infected mice which demonstrate ameliorative efficacy of propolis against <em>Staphylococcus </em>mediated damage. Although propolis has been widely recognized for its antimicrobial properties, limited research has explored its histoprotective effects on internal organs in bacterial infections. Furthermore, studies investigating its synergistic potential with conventional antibiotics remain scarce. This study aims to address these gaps by assessing the impact of propolis both independently as well as in combination with antibiotics on organ histology in bacterial infections. This research provides novel insights into the protective role of propolis in mitigating <em>Staphylococcus aureus</em> induced histological damage. Additionally, it highlights the potential of propolis as an adjunct therapy to conventional antibiotics paving the way for alternative treatment strategies that could enhance antibiotic efficacy while minimizing resistance development. Future studies should focus on elucidating the precise molecular mechanisms underlying propolis's protective effects and clinical trials are also necessary to validate its therapeutic efficacy in humans.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/9253 A Topology of Multilevel Inverter for Tolerance against Single and Multiple Faults 2024-04-16T09:34:21+0530 Aquib Mehdi Naqvi aquibmn@gmail.com Pushkar Tripathi pushkartripathi@ietlucknow.ac.in S P Singh singh.surya12@gmail.com <p>Multilevel Inverter (MLI) offers numerous advantages, making them suitable for a wider range of application. However, the increased number of switches in MLIs raises the probability of faults. A fault in a switch may interrupt the complete power supply, which is a much-undesired condition for a critical load. In this paper, a fault-tolerant MLI topology is proposed for seven and higher voltage levels, capable of tolerating faults and ensuring the continuity of operation. The proposed MLI exhibits high redundancy in switching states, enabling it to produce all voltage levels even in the event of an open circuit fault in any switch. Fault detection and identification of the faulty switch are accomplished through the analysis of switching signals and measured output voltage. The proposed topology is implemented for 15-levels using the nearest level switching technique, operating under normal conditions as well as during different fault scenarios. Upon detection and identification of a fault by the fault detection unit, the switching sequence is updated to ensure the attainment of rated voltage magnitude and voltage levels. The fault-tolerant capability makes the MLI crucial for critical power supplies and renewable energy systems. The topology and its fault-tolerant operation under various fault cases are tested in the MATLAB Simulink environment and validated in real-time using the OPAL-RT Lab simulator.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/9598 Physicochemical Properties of Soil and Plant Geometry in Oil Yield, Quality and Economics of Lemongrass in Rainfed Bundelkhand Region, India 2024-06-21T14:27:24+0530 Sabha Jeet sabhajeet@iiim.res.in Ravindra Verma rv808130@gmail.com Sonali Bhagat sonalibhagat51@gmail.com Rajendra Bhanwaria rbhanwaria@iiim.res.in Shahina Tabassum shahina2044@gmail.com Gajendra Kumar Yadav yadavgajendra268@gmail.com <p>Keeping in mind the significance of sustainable production practices and greater resource use efficiency, a study was led to access five levels of Plant Geometry (PG)/spacing of lemongrass variety CKP–25 (<em>Cymbopogon khasianus × pendulous</em><strong>) </strong>tested with three levels of Soil Types (ST) on the performance of essential oil (EO) yield, secondary metabolites (SM) and economic returns (ER) in rainfed Bundelkhand region. The results of the analysis of variance data were recorded for two consecutive years (2020–21 and 2021–22). On an average EO content was found to be highest (0.77%) in Mar Soil (MS). The interaction MS along with PG1 [62,500 plants/ha (40<em>×</em>40 cm)] observed the highest EO content (0.79%). The highest EO yield (228.23, 319.92 kg/ha) was obtained in MS along with PG3 [76,923 plants/ha (45<em>×</em>30 cm)] in 1<sup>st</sup> and 2<sup>nd</sup> years, respectively. The lemongrass variety, showed excellent performance in terms of achieving higher net income and benefit˗cost (B:C) ratio, in respect of MS with PG3. The significantly highest Net Return (NR) (Rs. 1,70,995 and 3,02,984 /ha) and B:C ratio (2.66 and 4.74) were recorded in MS along with PG3 in the 1<sup>st</sup> and 2<sup>nd</sup> year, respectively. However, in terms of secondary metabolites, Neral (cis˗citral) or citral B (40.13 ± 3.92%, 37.36 ± 4.63) and trans citral or citral A (47.97 ± 5.51%, 45.83 ± 5.54%) was noted to be highest in MS in both the year. On average, the total citral was found to be highest in MS (84.95 ± 5.36%, 83.19 ± 4.85%) in 1<sup>st</sup> and 2<sup>nd</sup> years, respectively.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR) https://or.niscpr.res.in/index.php/JSIR/article/view/9775 Life Cycle Energy Assessment of Rajasthan’s Marble Processing Plant for Sustainable Environment Planning 2024-07-16T20:38:23+0530 Dharmanshu Sodha 2018rme9167@mnit.ac.in Harlal Singh Mali harlal.singh@gmail.com Amit Kumar Singh amitsingh@nitc.ac.in <p>The construction sector plays a vital role in achieving sustainability; therefore, monitoring and continuous improvement in energy and environmental performance in this sector are crucial. The Rajasthan state of India contains 64% of Indian marble resources, and approximately 90% of the marble is being processed in Rajasthan alone. In past decades, the production of marble stones has been in very high volume, leading to high energy consumption. Since the processing of marble worldwide is performed by Small-to-Medium Enterprises (SMEs), these industries lack technology, leading to low efficiency and more expensive production with significant waste generation. The objective of this study is to assess the energy consumption and environmental impacts of typical marble processing SMEs in Rajasthan and to propose strategies for enhancing production efficiency and reducing the ecological footprint. Through site surveys, power rating data were collected to quantify electrical energy usage across various operations of marble production, and further, each operating scenario's energy consumption was compiled. Environmental impacts, particularly CO<sub>2</sub> emissions, were quantified using the GaBi® sustainability software. This study presents a consolidate index for assessing the economic and environmental performance of different operating scenarios and for ranking processing lines for One Square Feet (ft<sup>2</sup>) of processed marble stone, providing a comprehensive sustainability performance assessment. The findings highlight the potential for substantial environmental advantages by implementing energy-efficient practices and critical technological advancements to improve the marble processing industries' sustainability and operational efficiency, potentially assisting broader regional environmental initiatives. Eventually, the findings aim to contribute to the development of greener production practices in the sector, promoting both economic and environmental sustainability.</p> 2025-02-13T00:00:00+0530 Copyright (c) 2025 Journal of Scientific & Industrial Research (JSIR)