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Electrochemical performance of ZnxCo3-xO4/N-doped rGO nanocomposites for energy storage application
In this study, nanocomposites consisting of zinc-doped cobalt oxides with a spinel structure and nitrogen-doped reduced graphene oxide (ZnxCo3-xO4 (x = 0 and 1))/N-doped rGO) were synthesized using a solvothermal method. The synthesized materials were investigated using XRD, TEM, EDS, BET, Raman, and XPS for their phase formation, morphology, elemental composition, surface area, and chemical states. XRD analysis revealed that the metal oxides (Co3O4 and ZnCo2O4) present in the composites exhibited a single-phase cubic spinel structure, with a nanocrystalline nature and crystallite size ranging from 8 nm to 20 nm. Raman and TEM analyses revealed the co-existence of metal oxide nanoparticles and N-doped rGO phases in the composites. Electrodes were fabricated using the synthesized nanocomposite materials and subjected to electrochemical testing, including CV, GCD and EIS. The specific capacitiance (Cs) of samples determined to be 181 F/g and 234 F/g for CO/NrGO (Co3O4/N-doped rGO) and ZCO/NrGO (ZnCo2O4/N-doped rGO) nanocomposites, respectively, at lower current density (0.5 A/g). At all current densities, the CS of ZCO/NrGO nanocomposite electrode is observed to be higher than the CO/NrGO nanocomposite, probably due to structural defects and uniform anchoring of ZnCo2O4 particles over the layers of NrGO. The ZCO/NrGO composite electrode exhibits ?86 % capacitance retention after 3000 cycles. 2024 Elsevier B.V. -
Morphology-dependent supercapacitive properties of Co3O4 nanomaterials synthesized via coprecipitation and hydrothermal methods
The supercapacitive properties of Co3O4 nanocrystalline powders with two different morphologies synthesized by coprecipitation (referred to as Co3O4C) and hydrothermal (referred to as Co3O4-H) methods were compared and studied. The samples were analyzed for their phase purity, crystal structure, surface morphology, and surface area. Both samples were found to be single-phase nanostructures with a normal spinel-type cubic crystal structure (space group Fd3m), as indicated by Raman and XRD (X-ray diffraction) data analyses. TEM (Transmission electron microscopy) images clearly show that the Co3O4C sample exhibits spherical particles with a mean size of 10 nm. On the other hand, the Co3O4H sample shows a flower-like assembly of particles. The Co3O4C sample has a higher specific surface area than the Co3O4-H sample due to its smaller particle size. XPS (X-ray photoelectron spectroscopy) data were collected to analyze the chemical states and cation distribution of the samples, revealing a 2:1 ratio of Co3+ and Co2+ in both samples. Both samples displayed pseudocapacitive behaviour in CV (cyclic voltammetry) and GCD (galvanostatic chargedischarge) analyses. Despite having a smaller surface area, the Co3O4H electrode exhibited a higher CS (specific capacitance) compared to the Co3O4C electrode at all current densities when tested using 1 M KOH electrolyte. At a specific current density (0.5 A/g), the Cs values for Co3O4C and Co3O4H are found to be 366 F/g and 233 F/g, respectively. As the current density increases, the specific capacitance of both electrodes decreases, but this reduction is more prominent for Co3O4-C than Co3O4-H. The study indicates that besides surface area, the morphology of the sample also plays a crucial role in determining the capacitance of a material. 2023 Elsevier B.V. -
Hydrothermally synthesized mesoporous Co3O4 nanorods as effective supercapacitor material
Mesoporous Co3O4 nanomaterial in rod-shape morphology has been synthesized via a hydrothermal method, and heat treated at 350 C for 2 h to develop a phase. Phase purity, morphology, specific surface area and chemical composition of as-obtained Co3O4 material were studied using XRD, Raman, TEM, N2-adsoprtion/desorption and XPS techniques. XRD and Raman analyses indicate single phase material formation with nano-structure, and cubic normal spinel-type structure with a cell parameter of 8.123 The spinel particles are of rod-shape morphology and the specific surface area, estimated through BET studies, is obtained as 47 m2/g. Cyclic voltammogram (CV) recorded at different scan rates evidently demonstrate pseudocapacitance nature of the synthesized material. Maximum specific capacitance (CS) is computed and the value is 261 F/g at 0.25 A/g. These materials have shown longer cycle stability at lower KOH concentration and lower current density. Synthesized Co3O4 nanomaterial could be used as electrode material for energy storage applications. 2023 Elsevier B.V. -
The evaluation of the electrochemical properties of Co3O4 nanopowders synthesized by autocombustion and solgel methods
The present investigation involves two synthesis methods, autocombustion (Co3O4-AC) and solgel (Co3O4-SG), for producing nearly spherical-shaped and polygonal shaped nanomaterials of spinel cobalt oxide (Co3O4) respectively as electrode materials. TEM image analysis unveiled distinct particle morphologies for the two samples. The Co3O4-AC particles exhibited a nearly spherical shape, whereas the Co3O4-SG particles displayed a polygonal shape. The phase purity of the Co3O4 samples were confirmed via XRD patterns analysis and the crystallite size was calculated to be 44nm for Co3O4-AC and 36nm for Co3O4-SG. The surface area, estimated via BET experiments, of Co3O4-AC was found to be 15m2/g, while Co3O4-SG exhibited a slightly lower surface area of 11m2/g. Co3O4-AC exhibited a higher specific capacitance (Cs) of 162F/g at 0.25A/g, indicating its superior energy storage capability. On the other hand, Co3O4-SG shows a Cs of 98F/g, indicating slightly lower performance compared to Co3O4-AC. Both nanomaterials exhibited better stability, with more than 85% capacity retention after 5000 chargedischarge cycles. 2023, The Author(s), under exclusive licence to the Institute of Chemistry, Slovak Academy of Sciences. -
Relevance of backcasting as a strategic tool towards organisations' sustainable future ' A key to thrive in the VUCA world
Purpose: The business world has become more turbulent than ever. Organisations must be proactive to meet the challenges of the increasingly disruptive, dynamic, and unpredictable world. One technique that has supported leaders and organisations under challenging circumstances is 'backcasting', which works by envisioning a desirable future state and then working backwards to attain it. The current study aims to extend an understanding of the backcasting practices and strategic approaches that can be used by leadership teams in different industries in order to survive in turbulent times and can be adapted within and beyond any pandemic. Methodology: The research employs a desktop research method to review and compare the most commonly used strategies that leaders from different sectors can use for their respective organisations to thrive in the VUCA world. Findings: There needs to be more research on the applicability and relevance of backcasting that the leaders of different sectors can employ. The study would provide insights that would bridge the existing research gap and come up with suitable strategies that can be employed for dealing with VUCA challenges in the Indian context. Significance: The outcome of the study will be helpful to the leaders in designing and aligning 'out of the box' backcasting strategies to survive in the highly disruptive world. 2024 The authors. Published under exclusive licence by Emerald Publishing Limited. All rights reserved. -
Violence Prevention Climate and Turnover Intention: Mediating Role of Spirit at Work and Emotional Exhaustion
Workplace violence is a costly organizational problem. Violence prevention, incorporating employee perspectives on safe working policies, is crucial. A safe environment can enhance spirit at work, reducing burnout and turnover intention. This study investigates the relationship between violence prevention climate, emotional exhaustion, spirit at work, and turnover intention. Standardized tools were administered to 146 IT professionals aged 30-40 years. Results showed violence prevention climate positively correlated with spirit at work (r = 0.39; p < 0.001) and negatively with emotional exhaustion (r = -0.40; p < 0.001) and turnover intention (r = -0.35; p < 0.001). Emotional exhaustion mediated the relationship between violence prevention climate and turnover intention (b = -0.23; p < 0.001), while spirit at work did not show mediation. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Stakeholders' expressions of tech layoffs: A text mining analysis on the "Balance of Arguments"
The volume and nature of work undertaken by the tech employees is humongous, tech employees are known to manage those high tides because of attractive salary packages, perks, and other incentive options, which turn out to be a catastrophic collapse when such layoffs are levied, giving little or no room for a quick transfer to another job from the viewpoint of the affected employees. User-generated unstructured data content in the forms of either tweets, reviews, or comments from around seven major social media platforms were collected to understand the various expressions and discussions linked to layoffs. The collected data is further segregated into employee expressions, social media reviewers, news critiques views, etc., and their perspectives were further analysed. The overall analysis of sentiments on various stakeholders are formulated using Python (Juypter Notebook) package. The authors attempt to model out the viewpoints of various expressors and suggests various measures to be taken by the tech majors to better handle the phenomenon of layoffs. 2023, IGI Global. All rights reserved. -
Enhancement of Agriculture Feeder Performance by Optimal Sizing and Placing of Solar PV Tree through AEO-Based Optimization Technique
Electrical demand, which makes up a large share of the overall power market, agriculture at the top of the list of priorities. To provide end users with a dependable and high-quality supply via various feeders and renewable energy sources, distribution generations are now being developed. In recent years, solar PV systems have been used to meet the demands of numerous applications, including boosting the efficiency of distribution networks. This paper presents the system with effect ive optimization method like Artificial Eco-System based Optimization Technique for identification of the best location to install distribution generation and the optimum size to minimize feeder losses. To meet service expectations, the integration of a solar PV system is swapped out for a solar tree in this suggested work. A 28-bus Indian agriculture feeder is considered for better understanding the proposed algorithm. MATLAB software is used for implementing the proposed optimization technique and CREO-2.0 is used for designing the 3-dimensional solar PV tree. 2023 by the Kamal Kumar U and Varaprasad Janamala. -
Artificial Ecosystem-Based Optimization for Optimal Location and Sizing of Solar Photovoltaic Distribution Generation in Agriculture Feeders
In this paper, an efficient nature-inspired meta-heuristic algorithm called artificial ecosystem-based optimization (AEO) is proposed for solving optimal locations and sizes of solar photovoltaic (SPV) systems problem in radial distribution system (RDS) towards minimization of grid dependency and greenhouse gas (GHG) emission. Considering loss minimization as main objective function, the location and size of solar photovoltaic systems (SPV) are optimized using AEO algorithm. The results on Indian practical 22-bus agriculture feeder and 28-bus rural feeders are highlighted the need of optimally distributed SPV systems for maintaining minimal grid dependency and reduced GHG emission from conventional energy (CE) sources. Moreover, the results of AEO have been compared with different heuristic approaches and highlighted its superiority in terms of convergence characteristics and redundancy features in solving the complex, nonlinear, multi-variable optimization problems in real time. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Solar PV Tree Designed Smart Irrigation to Survive the Agriculture in Effective Methodology
The global economy benefits significantly from agriculture. However, there are significant issues and difficulties in the irrigation sector as a result of a significant regional imbalance in power supply, water availability, rainfall, and adoption of technology. The most economical approach to supporting agriculture in the modern day is through irrigation powered by renewable energy. Productivity is impacted by environmental issues, defective irrigation systems, and unknowable soil moisture content in agricultural fields. Traditional watering systems might lose up to 50% of the water used due to ineffective irrigation, evaporation, and overwatering. As a result, the proposed study will modify solar tree-based smart irrigation systems that use the most recent sensors for real-Time or old data to influence watering flows and change watering schedules to enhance the system efficiency. One application of a wireless sensor network is proposed for low-cost wireless controlled irrigation and real-Time monitoring of soil water levels using Arduino controllers. Data is gathered for drip irrigation control using wireless acquisition stations powered by renewable energy, which lowers the risk of electrocution and boosts output. 2022 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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
