Browse Items (16488 total)
Sort by:
-
Betel leaf-mediated zinc oxide nanoparticle-coated silk fibres: a sustainable approach for biomedical applications
Clinical management of surgical site infections remains a challenge in biomedicine, where novel wound dressing materials are tested with a plethora of features. Here we describe a green and sustainable route to prepare biogenic zinc oxide nanoparticles (BZnONPs) using Piper betle leaf extract, which acts as a green reducing and stabilising agent. These biosynthesised nanoparticles were then used for the functional coating of degummed Bombyx mori silk fibers. Physico-chemical characterisation supports the efficient synthesis of crystalline, nanosized, and colloidal stable BZnONPs. The functionalization of silk fibers with BZnONPs resulted in the enhancement of the mechanical properties, tensile strength, and elasticity. Antibacterial testing proved the capability of the functional fibers against the strain Staphylococcus aureus. The as-synthesised fibers were biocompatible towards normal blood components, normal cells and exhibited slight toxicity toward cancer cells. Enhanced mechanical properties, antimicrobial action, and biocompatibility make BZnONP-coated silk fibers a leading player in various advanced biomedical devices, including sutures, wound dressings, tissue engineering scaffolds, and localised therapeutic platforms. Hence, this green nanotechnology approach opens up an alternative pathway toward the fabrication of multifunctional biomaterials with high translational value. 2025 The Royal Society of Chemistry. -
Enhancing Sustainable Urban Energy Management through Short-Term Wind Power Forecasting Using LSTM Neural Network
Integrating wind energy forecasting into urban city energy management systems offers significant potential for optimizing energy usage, reducing the carbon footprint, and improving overall energy efficiency. This article focuses on developing a wind power forecasting model using cutting-edge technologies to enhance urban city energy management systems. To effectively manage wind energy availability, a strategy is proposed to curtail energy consumption during periods of low wind energy availability and boost consumption during periods of high wind energy availability. For this purpose, an LSTM-based model is employed to forecast short-term wind power, leveraging a publicly available dataset. The LSTM model is trained with 27,310 instances and 10 wind energy system attributes, which were selected using the Pearson correlation feature selection method to identify crucial features. The evaluation of the LSTM-based forecasting model yields an impressive R2 score of 0.9107. The models performance metrics attest to its high accuracy, explaining a substantial proportion of the variance in the test data. This study not only contributes to advancing wind power forecasting, but also holds promise for sustainable urban energy management, enabling cities to make informed decisions in optimizing energy consumption and promoting a greener, more resilient future. 2023 by the authors. -
A Dynamic Anomaly Detection Approach for Fault Detection on Fire Alarm System Based on Fuzzy-PSO-CNN Approach
Early detection is crucial due to the catastrophic threats to life and property that are involved with fires. Sensory systems used in fire alarms are prone to false alerts and breakdowns, endangering lives and property. Therefore, it is essential to check the functionality of smoke detectors often. Traditional plans for such systems have included periodic maintenance; however, because they don't account for the condition of the fire alarm sensors, they are sometimes carried out not when necessary but rather on a predefined conservative timeframe. They describe a data-driven online anomaly detection of smoke detectors, which analyzes the behavior of these devices over time and looks for aberrant patterns that may imply a failure, to aid in the development of a predictive maintenance approach. The suggested procedure begins with three steps: preprocessing, segmentation, and model training. A pre-processing unit can enhance data quality by compensating for sensor drifts, sample-to-sample volatility, and disturbances (noise). The proposed approach normalizes the data in preparation. The smoke source can be detected by using segmentation to differentiate it from the background. Following segmentation, Fuzzy-PSO-CNN is used to train the models. CNN and PSO, two of the most used alternatives, are both outperformed by the proposed method. 2023 IEEE. -
-
Enhancement of resilience an quality of life using strength based counselling and the mediating role of parental bonding in adolescents with type 1 diabetes
The current study was an attempt to understand the socio-demographic profile of newlineadolescents with type 1diabetes, the relationship between variables such as resilience, quality of life, parental bonding and the mediating role of parental bonding. It was also aimed to understand parent s perception of the adolescent s resilience and quality of life and their newlineexperiences. In phase 1, 100 adolescents/ newlinechildren (M=40, F=60, Age 10-18years) with an newlineexisting diagnosis of type 1 diabetes and their parents were enrolled from two hospitals and one clinic in Bangalore. The adolescents were administered Paediatric Quality Of Life for Diabetics (PedsQL) (Child and Adolescent Form), The Resilience Scale for Youth (CYRM), The Parental Bonding Instrument PBI (Father and Mother Form ). Parents were administered the consent form, demographic data sheet and parent version of resilience and quality of life.All scales were translated and back translated. In Phase 2 of the study, an intervention model based on the principles of strength newlinebased counselling to enhance resilience and quality of life (SBCTD1) was developed and newlineused. Qualitative interviews were conducted to understand the experiences of parents of newlinechildren/adolescents having type 1 diabetes. These interviews were tape recorded. 50 newlineadolescents from Phase1, were randomly assigned to the intervention group (n=25) and the control group (n=25). For the intervention group after going through the sessions the Resilience Scales and The Paediatric Quality of Life scales were administered after one and three months respectively. HbA1c values were also collected again after three months of newlineintervention. Control group received regular care and treatment at the center and were not newlineexposed to the model developed for the study. -
Exploring the Effect of Work-Family Conflict on Burnout Among ICU Nurses in Indian Private Hospitals: The Influence of Perceived Organization Support
Nursing is demanding and often clashes with family responsibilities causing significant Work-Family Conflict (WFC). Nurses have long shifts, emotionally demanding workloads, and deep patient involvement which strains their work-life balance. This conflict blurs the lines between work and home and depletes emotional resources leading to burnout symptoms: emotional exhaustion, depersonalization, and reduced accomplishment. Burnout happens when nurses try to juggle work demands with personal responsibilities, hence organizational support is needed. ICU and emergency environments are known to be high-stress and deeply impact nurses personal lives through WFC. This affects nurse health and family well-being, especially in the ICU setting. Perceived Organizational Support (POS) which is how valued and supported nurses feel by their employers plays a big role in mitigating these challenges. This study will look into how WFC contributes to burnout among ICU nurses and the buffering effect of POS. The study had 449 ICU nurses from private hospitals in India through simple random sampling. Surveys showed that WFC did not affect ICU nurses accomplishment but affected emotional exhaustion and depersonalization. POS was found to moderate these effects hence it plays a role in buffering burnout risk among ICU nurses. The results emphasized the need for strong organizational support in nursing administration to mitigate WFC and burnout. The study had 449 ICU nurses from private hospitals in India through simple random sampling. Surveys showed that work-family conflict did not affect ICU nurses accomplishment but affected emotional exhaustion and depersonalization. Perceived Organizational Support (POS) was found to moderate these effects hence it plays a big role in buffering burnout risk among ICU nurses. The results emphasized the need for strong organizational support in nursing administration to mitigate work-family conflict and burnout. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Exploring the Impact of Disengagement on the Burnout Among ICU Nurses of Indian Private Hospitals: The Influence of Perceived Organization Support
Among healthcare workers, the nursing workforce has a high intensity of burnout which occurs as a response to the pressure they face at their workplace. Burnout in nursing professionalsis a widespread phenomenon characterized by a reduction in nurses energy that manifests in emotional exhaustion, lack of encouragement, and feelings of frustration and may lead to a decrease in work efficacy. This is a significant issue in human services that needs to be addressed.Several studies have been done on nurses; however, burnout in Indian ICU nurses has not received much attention. Intensive Care Units are specialized hospital areas requiring constant attention and vigorous patient care. Studies state that ICU nurses have to be more alert due to the severity of the illness in patients. Nurses in ICUs face many challenges at work which could lead to burnout. Disengagement is one such factor that might lead to burnout in nurses. When people experience disengagement, they feel detached from their workplace. Previous studies indicate that due to pandemic experiences, nurses are disengaging at a rate twice that of other healthcare staff. The challenging demands of their work have significantly affected the nurse's psychological wellness and overall health. Limited studies have been done on ICU nurse disengagement and its effect on burnout in Indian settings. Therefore, the study aims to examine how nurse disengagement affects the burnout they experience. Healthcare organizations must prioritize the support to be extended and care for the nurses well-being to prevent further disengagement. Nurses may become more committed to the organization when they feel supported by hospital administrators and have lighter workloads. This paper focuses on exploring the consequences of disengagement on burnout experienced by ICU nurses and the influence of Perceived Organizational Support (POS) between them. The sample used for the study was 449 nurses working in the ICU divisions of private hospitals in India. This study employed a simple random sampling technique. A survey was utilized and distributed to the nursing professionals working in the ICU divisions. The commonly recognized aspects of burnout are emotional exhaustion, depersonalization, and reduced personal achievement. The study results indicated that disengagement has no impact on the emotional exhaustion experienced by ICU nurses. However, it influences depersonalization and nurses achievement. The study results state that POS moderated the relationship between disengagement and the two burnout aspects: depersonalization and personal achievement. From the findings, it may be concluded that perceived organizational support is crucial in encouraging greater personal accomplishment, reduced depersonalization, and bringing about positive change for disengaged ICU nurses. Better organizational support for ICU nurses becomes a critical responsibility of nursing administration. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Exploring the Impact of Disengagement on the Burnout Among ICU Nurses of Indian Private Hospitals: The Influence of Perceived Organization Support
Among healthcare workers, the nursing workforce has a high intensity of burnout which occurs as a response to the pressure they face at their workplace. Burnout in nursing professionalsis a widespread phenomenon characterized by a reduction in nurses energy that manifests in emotional exhaustion, lack of encouragement, and feelings of frustration and may lead to a decrease in work efficacy. This is a significant issue in human services that needs to be addressed.Several studies have been done on nurses; however, burnout in Indian ICU nurses has not received much attention. Intensive Care Units are specialized hospital areas requiring constant attention and vigorous patient care. Studies state that ICU nurses have to be more alert due to the severity of the illness in patients. Nurses in ICUs face many challenges at work which could lead to burnout. Disengagement is one such factor that might lead to burnout in nurses. When people experience disengagement, they feel detached from their workplace. Previous studies indicate that due to pandemic experiences, nurses are disengaging at a rate twice that of other healthcare staff. The challenging demands of their work have significantly affected the nurse's psychological wellness and overall health. Limited studies have been done on ICU nurse disengagement and its effect on burnout in Indian settings. Therefore, the study aims to examine how nurse disengagement affects the burnout they experience. Healthcare organizations must prioritize the support to be extended and care for the nurses well-being to prevent further disengagement. Nurses may become more committed to the organization when they feel supported by hospital administrators and have lighter workloads. This paper focuses on exploring the consequences of disengagement on burnout experienced by ICU nurses and the influence of Perceived Organizational Support (POS) between them. The sample used for the study was 449 nurses working in the ICU divisions of private hospitals in India. This study employed a simple random sampling technique. A survey was utilized and distributed to the nursing professionals working in the ICU divisions. The commonly recognized aspects of burnout are emotional exhaustion, depersonalization, and reduced personal achievement. The study results indicated that disengagement has no impact on the emotional exhaustion experienced by ICU nurses. However, it influences depersonalization and nurses achievement. The study results state that POS moderated the relationship between disengagement and the two burnout aspects: depersonalization and personal achievement. From the findings, it may be concluded that perceived organizational support is crucial in encouraging greater personal accomplishment, reduced depersonalization, and bringing about positive change for disengaged ICU nurses. Better organizational support for ICU nurses becomes a critical responsibility of nursing administration. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Analysis of the Viscous Dissipation and Nonlinear Velocity Slip Effect on the Thin Film Nanofluid Flow
Abstract: In the contemporary study, the dynamics of the nanofluid thin film is investigated by considering the viscous dissipation and chemical reaction effects. Additionally, the surface is assumed to have a nonlinear slip rather than the conventional no-slip conditions. This helps in better flow and heat transfer characteristics. This nonlinear velocity slip at the boundary is modelled using the idea proposed by Thompson and Troian. Also, the presence of viscous dissipation in the energy equation, depicts the loss of energy due to the internal friction. Hence, the viscous dissipation turns out to be a critical factor in determining the thermal properties of the nanofluid thin film. The chemical reactions take place within the system because of the presence of nanoparticles, that in turn will have a significant impact on the mass transfer characteristics of the thin film nanofluid. The incorporation of the similarity transformation helps in converting the partial differential equations (PDEs) that govern the fluid flow into a system of nonlinear ordinary differential equations (ODEs). This resulting system is then solved using the BVP package in python whose accuracy is assessed through residual analysis. By this error analysis, convergence of residues was confirmed. Thus validating the method and the results obtained. The outcomes of the study are interpreted through the graphs which highlighted the intensification of heat transfer for the increase in the Eckert number while the magnetic field confirmed its flow controlling feature. Also, the streamlines and contours were plotted to understand and visulaise the flow, all these contours showed the significance of the presence of nonlinear velocity slip at the boundary. Pleiades Publishing, Ltd. 2025. -
Modeling and analysis of the bioconvective flow of nanofluid over a stretching sheet with ThompsonTroian slip condition
In the present study, the flow, heat, and mass transfer characteristics of a bioconvective nanofluid over a stretching plate subjected to an external magnetic field are analyzed. The nonlinear slip at the surface is modeled using the ThompsonTroian velocity slip condition, while convective boundary conditions are applied to account for heat and mass transfer in the thermal and concentration fields. To ensure uniform nanoparticle distribution, motile microorganisms are incorporated into the fluid. These microorganisms help counteract particle aggregation and prevent solidification within the medium. Their motion gives rise to the bioconvection phenomenon, enhancing overall fluid transport. The governing equations for momentum, energy, and species concentration are formulated as partial differential equations (PDEs), incorporating key effects such as viscous dissipation, magnetic field influence, and heat sources. Using similarity transformations, the PDEs are reduced to a system of ordinary differential equations (ODEs). This system is then numerically solved via Python solve_bvp function, which employs a collocation method for boundary value problems. The computed solutions are validated against existing literature, and residual analysis is conducted to ensure accuracy. The results reveal that an increase in magnetic field strength suppresses fluid velocity while simultaneously raising the nanofluid temperature. Additionally, higher critical shear stress associated with the ThompsonTroian slip model further reduces the flow velocity near the surface. Akadiai KiadZrt 2025. -
Exploring the Impact of Disengagement on the Burnout Among ICU Nurses of Indian Private Hospitals: The Influence of Perceived Organization Support
Among healthcare workers, the nursing workforce has a high intensity of burnout which occurs as a response to the pressure they face at their workplace. Burnout in nursing professionalsis a widespread phenomenon characterized by a reduction in nurses energy that manifests in emotional exhaustion, lack of encouragement, and feelings of frustration and may lead to a decrease in work efficacy. This is a significant issue in human services that needs to be addressed.Several studies have been done on nurses; however, burnout in Indian ICU nurses has not received much attention. Intensive Care Units are specialized hospital areas requiring constant attention and vigorous patient care. Studies state that ICU nurses have to be more alert due to the severity of the illness in patients. Nurses in ICUs face many challenges at work which could lead to burnout. Disengagement is one such factor that might lead to burnout in nurses. When people experience disengagement, they feel detached from their workplace. Previous studies indicate that due to pandemic experiences, nurses are disengaging at a rate twice that of other healthcare staff. The challenging demands of their work have significantly affected the nurse's psychological wellness and overall health. Limited studies have been done on ICU nurse disengagement and its effect on burnout in Indian settings. Therefore, the study aims to examine how nurse disengagement affects the burnout they experience. Healthcare organizations must prioritize the support to be extended and care for the nurses well-being to prevent further disengagement. Nurses may become more committed to the organization when they feel supported by hospital administrators and have lighter workloads. This paper focuses on exploring the consequences of disengagement on burnout experienced by ICU nurses and the influence of Perceived Organizational Support (POS) between them. The sample used for the study was 449 nurses working in the ICU divisions of private hospitals in India. This study employed a simple random sampling technique. A survey was utilized and distributed to the nursing professionals working in the ICU divisions. The commonly recognized aspects of burnout are emotional exhaustion, depersonalization, and reduced personal achievement. The study results indicated that disengagement has no impact on the emotional exhaustion experienced by ICU nurses. However, it influences depersonalization and nurses achievement. The study results state that POS moderated the relationship between disengagement and the two burnout aspects: depersonalization and personal achievement. From the findings, it may be concluded that perceived organizational support is crucial in encouraging greater personal accomplishment, reduced depersonalization, and bringing about positive change for disengaged ICU nurses. Better organizational support for ICU nurses becomes a critical responsibility of nursing administration. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Synthesis and Characterization of WO3 Nanostructures by the Solvothermal Method for Electrochromic Applications
In this study, a tungsten trioxide (WO3) thin film was deposited by direct current (DC) sputtering onto a fluorine-doped tin oxide (FTO) substrate as the seed layer at an oxygen partial pressure of 8 10?4mbar. A simple solvothermal method involving tungsten hexacarbonyl (W(CO)6), ethanol (C2H5OH), and hydrochloric acid (HCl) was used to synthesize vertically stacked nanoscale WO3 hierarchical structures on WO3 seed-layered FTO. After the deposition process, the FTO samples with nanostructures were subjected to annealing in air at 400C for 4 h. After annealing, the surface morphology, structural characteristics, and optical and electrochromic properties of the grown nanostructures were investigated using scanning electron microscopy (SEM), x-ray diffraction (XRD), Raman spectroscopy, UVvisible spectroscopy, and electrochemical analysis. From the XRD analysis, all the diffraction patterns were ascribed to a monoclinic phase. The SEM analysis showed that films grown with 5?L HCl had a nanoflower structure compared to the films grown with 0?L HCl and 20?L HCl. The nanoflower-structured films showed a higher cathodic peak current (?2.22mA), diffusion coefficient (5.43 10?9 cm2/s), and coloration efficiency (23.6 cm2/C). The increased electrochromic characteristics were attributed to the nanostructured films, which enhanced the diffusion of H+ ions by providing a large surface area during the charge transfer process. The Minerals, Metals & Materials Society 2024. -
Attitude of Parents Towards Various Behavior Management Techniques Utilized in Pediatric Dental Treatments
Dental experts are trusted to apply the knowledge and abilities they have acquired during their dental education to the diagnosis and effective treatment of any dental illness. When it comes to pediatric patients, however, the dentist's responsibility is different. However, without the right behavior management method (BMT), therapy outcomes would not be effective. Sometimes young children behave disruptively during dental visits, which makes it easier or harder for the dentist to perform dental work. Nonetheless, before being applied to children, behavior management strategies need the parents' acceptance and consent. This review's objective is to evaluate the dentists' use of effective behavior modification techniques (BMT) as well as the parents' attitudes regarding these techniques. RJPT All right reserved. -
Quasi Z-Source Inverter with Simple Boost and Maximum Boost Pulse Width Modulation Techniques for PV Grid Connection
The voltage-fed quasi Z-source inverter (qZSI) is emerged as a promising solution for photovoltaic (PV) applications. This paper proposes a novel high-gain partition input union output dual impedance quasi Z-source inverter (PUDL-qZSI) for PV grid-connected system. This advanced inverter design achieves exceptionally low shoot-through duty ratios and high modulation index, resulting in a superior output current with reduced total harmonic distortion (THD). To modulate three-phase qZSIs and other equivalent topologies, a variety of modulation schemes may be used, some of which involve two extra reference signals to generate shoot-through state. The simulation is carried out on the MATLAB/Simulink environment with PV-based grid-connected PUDL-qZSI to measure the harmonic distortion and power measurement. The proposed inverter is subjected to two different pulse width modulation (PWM) analysis are simulated and compared to validate the proposed system. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Detection of Lung Cancer with a Deep Learning Hybrid Classifier
This article presents a deep learning framework combining a convolutional neural network (CNN) and a support vector machine (SVM) for lung cancer diagnosis. The model uses data divided into six groups: 250 images in the training set and 150 images in the test set. The work includes preliminary data and development using the Keras image data generator, VGG-16 architecture, high-level rules, and SVM classifier training with labels and vectors. The model achieves 90% accuracy with 85% selection impact and 75% cross-validation flexibility using VGG-16 and SVM hybrid classifier. This study finally revealed the classification of the model by multi-class ROC curve analysis and confusion matrix. 2024 IEEE. -
Sentiment Analysis on Amazon Product Review
Users throughout the world may now access massive amounts of data thanks to the internet and social media platforms. [5] In every facet of human existence, electronic commerce (e-commerce) plays a crucial role. E-commerce is a marketing approach that enables businesses and consumers to buy and sell things via the internet. When buyers look for product information and compare alternatives online, they generally have access to dozens or hundreds of product reviews from alternative shoppers. Machine learning is the most appropriate approach to training a neural network in today's age of practical artificial intelligence. So implementing a model to polarize those reviews and learn from them would make passing hundreds of comments a lot easier. [24] The interpretation will be a very basic product with positive, neutral, and negative polarization. The product is checked. This study suggests a sentiment evaluation model for shopper reviews based on the object and emotive word mining for emotional level analysis using machine learning approaches. 2022 IEEE. -
Evaluating the usability of mhealth applications on type 2 diabetes mellitus using various mcdm models
The recent developments in the IT world have brought several changes in the medical industry. This research work focuses on few mHealth applications that work on the management of type 2 diabetes mellitus (T2DM) by the patients on their own. Looking into the present doctor-to?patient ratio in our country (1:1700 as per a Times of India report in 2021), it is very essential to develop self?management mHealth applications. Thus, there is a need to ensure simple and user-friendly mHealth applications to improve customer satisfaction. The goal of this study is to assess and appraise the usability and effectiveness of existing T2DM?focused mHealth applications. TOP? SIS, VIKOR, and PROMETHEE II are three multi?criteria decision?making (MCDM) approaches considered in the proposed work for the evaluation of the usability of five existing T2DM mHealth applications, which include Glucose Buddy, mySugr, Diabetes: M, Blood Glucose Tracker, and OneTouch Reveal. The methodology used in the research work is a questionnaire?based evaluation that focuses on certain attributes and sub?attributes, identified based on the features of mHealth applications. CRITIC methodology is used for obtaining the attribute weights, which give the pri-ority of the attributes. The resulting analysis signifies our proposed research by ranking the mHealth applications based on usability and customer satisfaction. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
TSM: A Cloud Computing Task Scheduling Model
Cloud offers online-based runtime computing services through virtualized resources, ensuring scalability and efficient resource utilization on demand. Resource allocation in the dynamic cloud environment poses challenges for providers due to fluctuating user demand and resource availability. Cloud service providers must dynamically and economically allocate substantial resources among dispersed users worldwide. Users, in turn, expect reliable and cost-effective computing services, requiring the establishment of Service Level Agreements (SLAs). Resource distribution uncertainty arises in view of the dynamicity of the cloud, where VMs, memory capacity requirement, processing power, and networking are allocated to user applications using virtualization technology. Resource allocation strategies must address issues such as insufficient provisioning, scarcity, competition, resources fragmentation. CPU scheduler plays a crucial role in task completion, by selecting job from queue considering specific requirements. The Task Scheduling Model (TSM) algorithm improves scheduling by considering expected execution time, standard deviation, and resource completion time, aiming to address resource imbalances and task waiting times. The research discusses previous work, presents experimental findings, describes the experimental setup and results, and concludes with future research directions. 2023 IEEE. -
Comparative Analysis of Maize Leaf Disease Detection using Convolutional Neural Networks
Worldwide, maize is a significant cereal crop for crop productivity, identifying diseases in the plant's leaves is essential to raise a good crop. Deep learning methods that have been used in recent years to precisely identify and categorize these serious diseases, offering a non-destructive and effective way to find maize leaf ailments. In order to detect maize leaf disease, this paper suggests using three well-liked deep learning models: VGG16, Inception V3, and EfficientNet. The models were trained and assessed using a datasets of 4000 images of three distinct maize leaf diseases and a healthy class. All three models had high accuracy rates, according to the results, though EfficientNet outperformed the other two models. The suggested method can detect and track diseases in maize crops with high accuracy and can be applied practically. It can accurately classify various diseases. The study also demonstrates that deep learning models can offer a trustworthy and effective solution for detecting crop diseases, which can aid in lowering crop losses, raising crop yields, and enhancing food security. 2023 IEEE. -
A Multi Objective Artificial Eco-System Based Optimization Technique Integrating Solar Photovoltaic System In Distribution Network
Agricultural sector contributes 6.4% of total economic generation across the world. Notably, the utilization of technology to improve the yield and economy is rapidly increasing. To provide continuous supply to the residential customers, the agricultural feeder grid-dependency has to be integrated with Solar Photo Voltaic (SPV) systems. In this paper, an Artificial Eco-System based Optimization (AEO) algorithm is proposed for simultaneously identifying the locations and quantifying the sizes of SPV systems. A practical distribution system feeder 'Racheruvu 11kV agricultural feeder' Andhra Pradesh, India is considered for simulation purpose and the performance is compared with the standard IEEE-33 radial distribution system. 2022 IEEE.