Journal of Scientific & Industrial Research (JSIR) <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 0.6 (JCR 2022).</strong></p> <p style="text-align: justify;"><strong><a href="" target="_blank" rel="noopener">Instructions to Author Guidelines</a></strong></p> en-US (Dr Narendra Kumar Sahoo) (Digital Information Resources Division) Tue, 06 Feb 2024 17:50:49 +0530 OJS 60 A Dynamic Nonlinear Autoregressive Exogenous Model to Analyze the Impact of Mobility during COVID-19 Pandemic on the Electricity Consumption Prediction in Jordan <p>Due to the global COVID-19 pandemic, governments have adopted regulations and restrictions to prevent spreading the disease. Changes in socioeconomic status, lifestyle, mobility and consumer consumption behavior have resulted due to these restrictions. These changes caused the amount and pattern of electricity consumption to be affected during and after the pandemic. In this study, we developed a data-driven model of electricity consumption based on machine learning techniques to analyze the effect of Mobility during and after the pandemic on electricity consumption prediction, which has been considered along with other factors that typically affect electricity consumption, including historical load profile, weather measurements, and timing information. The Nonlinear Auto Regressive Exogenous (NARX), a recurring dynamic neural network with feedback, establishes the model. The model performance results show improved prediction performance when considering the mobility factor; the error residuals between the actual and forecasted max load values were lower than when not considering the Mobility. The test dataset's least Mean Square Error (MSE) was decreased by 43%. In addition, the regression values between actual and predicted values have improved when considering the mobility factor. The same applies to the R-value and Root Mean Squared Error (RMSE), with an improvement of 6.0% and 7.6%, respectively. For comparison purposes, two additional models were developed to verify the results using the Auto-Regressive Integrated Moving Average (ARIMA) and Long-Short Term Memory (LSTM), as well known models. These models also demonstrated improved prediction performance when considering the mobility factor. However, the NARX model exhibited the best results, with lower MSE and higher R values. The models considered in this study can be used to predict the electricity consumption values of other pandemics or another wave of COVID-19 to assist decision-makers in having higher consumption visibility, thus better planning resources, capacity, and costs.</p> Mohammad A Shbool, Farah Altarazi, Wafa' H AlAlaween Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Application of Machine Learning Techniques on Multivariate Ocean Parameters <p>Locating potential fishing zones is a requirement for aquaculture. The existence of Potential Fishing Zones is dependent on several ocean parameters. The goal of this paper is to analyze the various techniques to identify the Potential and Non-Potential Fishing Zones based on multivariate parameters like Sea Surface Temperature, Chlorophyll and Salinity. Regression-based model, that is derived from Random Forest methodology has been developed in order to process the dependent parameters, and the outcome is compared with other methodologies namely Support Vector Method (SVM), k-Nearest Neighbor (k-NN), and Decision Trees. The data used for this analysis is the California Cooperative Oceanic Fisheries Investigations (CalCOFI) dataset, which represents the hydrographic data since 1949, of the Californian Current System. The overall efficiency of each method is captured using Accuracy, Prediction Precision, and Area under the ROC Curve (AUC), F1 Score and Recall values. The test accuracy of the proposed system based on Random Forest has been recorded as 96.21 as compared to other methodology. The SVM, k-NN and Decision Tree methods have recorded 79.21, 93.14 and 96.11, respectively. The evidence based on the prediction outcome has affirmed the relationship between chlorophyll and SST, as well as with the Salinity data.</p> Sivasankari M, R Anandan, G Rajesh Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Motor Insurance Policy Selection: A Joint Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Approach <p>Motor insurance policies play a crucial role in protecting vehicle owners against financial losses due to accidents, theft, or other unforeseen events. The selection of an appropriate motor insurance policy is a complex decision-making process that requires considering multiple criteria and their interrelationships. The motivation behind this study is to offer an advanced decision-making framework that addresses the complexities of motor insurance policy selection, improves risk management, fosters innovation in decision-making methodologies, enhances customer satisfaction, and increases the competitiveness of insurance providers. This research presents a joint approach, combining the SF-AHP (Spherical Fuzzy Analytic Hierarchy Process) and the CoCoSo (Combined Compromise Solution) method, to facilitate the selection of the most suitable motor insurance policy. The weights of the factors are estimated by SF-AHP method with experts’ advice. The rankings of the alternatives are calculated using CoCoSo method. The sensitivity analysis is also carried out to check the stability of results over different Eigen values (l). Premium amount is identified as the most influencing factor with factors weight as 0.178 and reputation of the insurance company is identified as least dominating out of other selected factors with factor weight as 0.10. The results are significantly stable over different l values ranging from zero to one. The research paper addresses a novel problem of motor insurance policy selection that has not been explored by any previous researchers in the existing literature.</p> Mangesh Joshi Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Simulative Investigation of MIMO-OFDM-FSOC System over Modified Malaga Distributed Composite Atmospheric Channel <p>In this research work, we propose a novel design for a multiple aperture based Free-Space Optical Communication (FSOC) system where the Low Density Parity Check (LDPC)-coded, M-independent parallel Quadrature Amplitude Modulation (QAM)-OFDM multiplexed data streams are transmitted over a composite Malaga atmospheric channel by selecting any one of the switching transmission schemes: diversity, hybrid, or spatial multiplexing based on channel conditions, to yield the maximum average channel capacity while satisfying the reliable Average Bit Error Rate (ABER). In diversity switching, the coded data stream is transmitted to extract diversity gains, whereas in hybrid switching, a compromise between diversity and multiplexing gains is sought to achieve the maximum outage capacity by maintaining the reliable ABER. The performance of each switching scheme is evaluated under the power-series represented Malaga distributed composite channel which comprise of losses due to turbulence-induced fading and pointing error. In this work, a closed loop approximated mathematical expressions for the Average Channel Capacity (ACC) and ABER for each transmission mode is also derived. Apart from this, a Look-Up Table (LUT) consists of threshold Signal-to-Noise Ratio (SNR) corresponding to different channel conditions is also constructed to select the optimal switching transmission scheme. The extensive simulation results clearly demonstrate that the proposed switched mode transmission based MIMO-OFDM-FSOC system has a significant improvement in ACC compared with each stand-alone system.</p> Shivaji Sinha, Chakresh Kumar Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Control Strategy for LVRT Enhancement in Photovoltaic Fuel Cell Hybrid Renewable Energy System <p>The present work describes a Low voltage ride through (LVRT) method for optimizing a photovoltaic fuel cell hybrid renewable energy system (HRES). The LVRT control approaches were previously studied to apply them to systems such as Wind Power Generation (WPG) and Solar Energy Generation (SEG), among other things. Photovoltaic (PV) power generation systems have recently drawn significant interest, with the building of large PV systems or groupings of systems related to the utility grid gaining a lot of traction. As a result of the significant penetration of photovoltaic electricity into the system, energy regulatory bodies enact increasingly strict grid rules to preserve grid stability. This paper demonstrates a large-scale grid-connected solar system along with the associated modeling and control approaches that can be utilized to improve DC-based voltage levels which can ride-through capabilities of solar power plants. The grid side inverter is essential for low-voltage driving. In case of overvoltage or under voltage the grid may trip inverter's DC link thereby such variation should be avoided as much as feasible. The purpose of this research is to incorporate DC-link over and under-voltage protection into the control loop without raising the cost of the protective device, which is a significant consideration. In the future, a study of the outcomes using a typical inverter system is also planned. Numerous fault scenarios with increasing severity are analyzed to show that the comprehensive control system is effective. The most recent grid code for the distributed generation system is considered.</p> Devvrat Tyagi, Ayushi Prakash, Amita Pal, Sonu Kumar Jha, Mayur Rahul, Vikash Yadav Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Characterization and Synthesis of Biocomposite Film with Coir and Polyvinyl Alcohol/Polyethylene Glycol <p style="margin: 0cm; text-align: justify;">This study explores the synthesis of biodegradable composite films by incorporation of different amounts of polyethylene glycol with polyvinyl alcohol, untreated coir and treated coir using the solution casting method. The effect of polyethylene glycol on the structure and properties of the synthesized biocomposite films was investigated. The increased ratio of polyvinyl alcohol/polyethylene glycol resulted in decreased tensile strength. This investigation revealed that the incorporation of 10 wt% polyethylene glycol with polyvinyl alcohol was sufficient to synthesize the biocomposite film and resulted in tensile strength of 28.14 MPa. It was observed that the incorporation of 30 wt% polyethylene glycol led to phase separation with the tensile strength of 18.33 MPa and hence, 10 wt% polyethylene glycol incorporation is best among the tested treatments for synthesizing biodegradable composite film.</p> Vandna, Devendra Kumar Gond, Brijesh Kumar Yadav, Shakti Priyadarshan, Vijay Laxmi Yadav Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Technology Transfers from Public-funded Research Organizations: A Systematic Literature Review <p>Public-funded Research Organizations (PROs) are a class of research organizations carrying out R&amp;D for the growth of industrial economy. These are distinct from University Research Organizations (UROs), despite both being publicly funded. While UROs are populated with student-faculty teams focused on academic research, PROs are populated with full-time professional researchers focusing largely on post-academic research. Technology transfers from PROs are important for national economic development and hence are worth a study. The objective of this paper is to study literature to (a) explore tech-transfer characteristics such as mechanisms, actors, success factors, stages, and models, and b) to gather any relevant insights. The method of Systematic Literature Review (SLR) was adopted for this study. Compared to conventional narrative review, SLR offers a replicable, scientific, and transparent process that aims to minimize bias and provides an audit trail of the reviewer’s decisions. Hence, SLR by itself is considered a research. Among the various methods for the literature-analysis such as bibliographic analysis, meta-analysis and thematic analysis, this paper adopts thematic analysis consistent with the objectives of research and the limited size of the literature on the topic. Focusing chiefly on recent literature on domestic technology transfers from PROs, this work provides useful insights.</p> Thyagaraju H Ponangi, Karuna Jain, R B Grover Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Microcontroller based Automatic Spot Granular Fertilizer Dispensing Machine for Orchards <p>A healthy orchard necessitates well-balanced nutrition. In order to achieve a high yield, fertilizer application in the proper amount and position is important. Existing fertilizer application methods (band placement, pellet application, and ring basin method) have limitations such as excessive fertilizer application, soil acidity, nutrient imbalance, soil structure damage, bulk density rise, and more. A spot fertilizer applicator that can dispense the proper amount of fertilizer at right site can reduce fertilizer waste, lowering pollution and input costs. As a result, a novel grooved belt type metering system was designed with an autonomous plant detection-based spot fertilizer application. The fertilizer placement and consistency of amount dispensed per plant of the applicator were assessed in the lab. The independent parameters were metering belt groove volume (50, 100 and 150 cm<sup>3</sup>), metering belt speed (8, 9 and 10 m.min<sup>−1</sup>), plant spacing (45, 60, 75 and 90 cm) and forward speed (2, 2.5 and 3 km.h<sup>−1</sup>). Forward speed had a considerable impact on the band length, whereas groove volume and belt speed had a substantial impact on the lateral placement parameters. Because plant spacing had no significant effect and the means of real and measured fertilizer application amounts were equal, the machine was found suitable for applying fertilizer with any plant spacing. Using a full factorial experimental design, the optimal values for independent parameters such as groove volume, plant spacing, belt speed, and forward speed were assessed 50 cm<sup>3</sup>, 78.4 cm, 8.74 m.min<sup>−1</sup>, and 2.72 km.h<sup>−1</sup>, respectively with a high desirability of 0.971. In comparison to mechanical sensing type available spot fertilizer applicators, the developed spot fertilizer applicator required half the sensing and actuation time and had three times less fluctuation in fertilizer dosing.</p> Aman Mahore, K P Singh, Bikram Jyoti, K N Agrawal, Manoj Kumar Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Development and Verification of Electrokinetic Injection Logical Control Mode in Microfluidic Device <p>This study presents a methodology for discretely injecting sample flows propelled by electroosmosis within a microfluidic device. The inquiry begins by analyzing the buffer distance required to hinder diffusion between successive distinct sample entities. Following this, a systematic formulation is developed to identify operational parameters that ensure the comprehensive deposition of the specimen segment into the assigned discharge reservoir. The results indicate that precise manipulation of voltages applied to the microfluidic device's various inlet and outlet channels enables the automatic and continuous delivery of samples with varying lengths to specified outlet reservoirs. Experimental evidence supports the claim that applying a voltage to the non-receiving reservoir during injection enhances the microfluidic device's injection performance by preventing sample leakage. Furthermore, findings from both experimental and numerical analyses suggest that optimizing the spatial configuration of the outlet channels enhances the overall efficiency of the injection process.</p> Yu-Jen Pan Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Volume Optimization of Two-Stage Helical Gear Train using Differential Evolution Algorithm <p>In high-performance power transmission systems like automotive and aerospace, the proper gear train design is essential because it requires minimum weight and high-efficiency gearboxes with maximum service life. An iterative design method that takes into account all viable design options is used to achieve the desired outcome. This procedure cannot be automated using the traditional methods utilized in its design. As a result, this paper makes an attempt to automate the gear train's preliminary design. This paper uses the Differential Evolution (DE) optimization technique and a dynamic penalty function to optimize the two-stage helical gear train's design parameters by minimising the objective function i.e., the gear train's overall geometrical volume (size). The objective function is constrained by bending force, surface fatigue strength, and interference equations of helical gear train with the design variables such as number of teeth, face width, module, and helix angle of each gear. Ranges of design parameters are taken from the manufacturer's catalogue. The optimised design parameters obtained from the proposed approach are compared and validated with the standard gear parameters (i.e., catalogue value) and with the results published in the literature applying other optimising approaches such as Genetic Algorithm (GA) and Fminsearch Solver (FS). The proposed approach shows a significant reduction i.e., 18.51% with GA and 18.14% with FS in the overall geometrical volume (size) of the two-stage helical gear train as compared to the published work. The presented approach enhances the design optimization problem of gear train which may be used in automobile, aircrafts, and robotics application for optimal performance.</p> Vikash Kumar, Sachin Kumar Singh Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530 Hybrid WCMFO Algorithm for Microhardness Improvement in Roller Burnishing of Brass (C3604) <p>Roller burnishing is a surface improvement technique that creates residual compressive stress in the workpiece surface layers. Compressive surface stress generation may increase surface hardness, which in turn enhances fatigue and corrosion resistance and overall surface quality. In order to optimize the process parameters in roller burnishing of brass, the present work unveils an application of Response Surface Methodology (RSM) and hybrid Water Cycle Moth Flame Algorithm (WCMFO) technique. Three input process parameters viz. burnishing speed, depth of penetration and feed rate have been investigated and modelled for Microhardness (HV) utilizing RSM based central composite design. In present experimentation, quadratic model has been suggested for surface hardness. Following validation of the model’s validity, the model was coupled with a new metaheuristic based hybrid WCMFO algorithm to optimize the burnishing parameters for maximum Microhardness. So as to prove the enhancement, the optimal burnishing parameters were tested. A substantial relationship was observed between the predicted micro hardness and the experimental values.</p> A Tamilarasan, A Renugambal Copyright (c) 2024 Journal of Scientific & Industrial Research (JSIR) Tue, 06 Feb 2024 00:00:00 +0530