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Synthesis, characterization and catalytic activity of oxovanadium(IV) complexes of heterocyclic acid hydrazones
Two acid hydrazones, furan-2-carbaldehyde nicotinic hydrazone (L1) and furan-2-carbaldehyde benzhydrazone (L2) have been synthesized and they are characterized by elemental analysis, IR, NMR and UV spectral analysis. Oxovanadium(IV) complexes of these two hydrazones were synthesized and characterized by elemental analysis, IR, UV, EPR, molar conductivity and magnetic susceptibility measurements. Conductivity measurements reveal that the complexes are non-electrolytes. Spectral data indicates the square pyramidal geometry for the monomeric five coordinated oxovanadium(IV) complexes with the general formula [VO(L)(OCH3)]. The complex was studied for its catalytic activity and was found to be a good catalyst in quinoxaline synthesis. -
RETAIL INVESTORS PARTICIPATION IN INDIAN CORPORATE BOND MARKET: A CRITICAL STUDY
A developed and vibrant corporate bond market provides an important means of financial resources to corporate, in addition to bank financing. It brings transparency and prudence into financial system and helps in minimizing risks in financial system through diversification. The main objective of this study is to find out the various issues and hurdles faced by retail investors and come out with appropriate suggestions in this regard. A modest attempt has also been made to understand the present status of the Indian corporate bond market in reference to retail investors participation. The study reveals that, in spite of sincere efforts of policymakers, the participation of retail investors in Indian corporate bond market are negligible. It has also been observed that the important issues of retail investors are related to safety of principal, returns, liquidity and tax benefits. It is expected that the suggestions made in this paper, if implemented, will definitely helpful in attracting retail investors to Indian corporate bond market. 2024 Published by Faculty of Engineering. -
The impact of audit committee independence and competence on investors investment decision making: A study in the Indian context
This study examined the impact of an independent and competent audit committee on the decision-making process of investors in the Indian capital market and adopted a quantitative approach in which cross-sectional data are gathered with the help of a self-administered questionnaire survey. The selection of participants involves a stratified random sample technique, specifically targeting 441 regular investors associated with nine prominent brokerage houses in the Delhi NCR engaged in equity market investments. Descriptive analysis is applied to discern respondent characteristics, whereas correlation and regression analyses are utilised to test and elucidate the relationships and influences among variables in the model. The findings of this study, which indicate a notable correlation between investors' investment decision-making in India and the independence and competence of the audit committee, are in line with the expectation that independence and competence are essential attributes that the audit committee must possess. These characteristics, in turn, have a notable influence on investors' investment decisions. The outcome of this paper fills a gap in the literature by offering insights into the vital attributes of audit committee independence and competence that notably contribute to investment decision-making in India. This research examined the impact of an independent and competent audit committee on the decision-making process of investors in the Indian capital market, which has never been examined before. Thus, the findings shed light on the influence of board independence and competence on the decision-making process of investors in the Indian capital market. 2025, Malque Publishing. All rights reserved. -
On l(T, 1)-colouring of certain classes of graphs
For a given set T of non-negative integers including zero and a positive integer k, the L(T, 1)-Colouring of a graph G = (V, E) is a function c: V(G) ? {0, 0, , k} such that |c(u) ? c(v)| ? T if the distance between u and v is 1 and |c(u) ? c(v)| ? 0 whenever u and v are at distance 2. The L(T,1)-span, ?T,1(G) is the smallest positive integer k such that G admits an L(T, 1)-Colouring. In this article we initiate a study of this concept of L(T, 1)-Colouring by determining the value of ?T,1(G) for some classes of graphs and present algorithms to obtain the L(T, 1)-Colouring of paths and stars. 2020 IJSTR. -
L(t, 1)-colouring of graphs
One of the most famous applications of Graph Theory is in the field of Channel Assignment Problems. There are varieties of graph colouring concepts that are used for different requirements of frequency assignments in communication channels. We introduce here L(t, 1)-colouring of graphs. This has its foundation in T-colouring and L(p, q)-colouring. For a given finite set T including zero, an L(t, 1)-colouring of a graph G is an assignment of non-negative integers to the vertices of G such that the difference between the colours of adjacent vertices must not belong to the set T and the colours of vertices that are at distance two must be distinct. The variable t in L(t, 1) denotes the elements of the set T. For a graph G, the L(t, 1)-span of G is the minimum of the highest colour used to colour the vertices of a graph out of all the possible L(t, 1)-colourings. It is denoted by ?t,1(G). We study some properties of L(t, 1)-colouring. We also find upper bounds of ?t,1(G) of stars and multipartite graphs. I??k University, Department of Mathematics, 2022; all rights reserved. -
Role of Need for Achievement on Decision making and Life Orientation of Young Adults
Purpose-To assess the role of need for achievement on decision making and life orientation of young adults. Design/methodology/approach-The data was collected from the participants using a questionnaire. The sample size is 100 young adults. The sampling technique used is convenience sampling, and the research design is a cross-sectional survey. It was hypothesised that individuals high in achievement motivation will also be high in life orientation level and there will be a positive correlation between achievement motivation and decision making. Findings The results of the study indicate that an individual high in achievement motivation will also be high in life orientation level and a positive correlation is found between achievement motivation and decision making. The other findings are that optimising decision-making styles is positively correlated with achievement motivation and a significant difference in achievement motivation between males and females is found, indicating a higher need for achievement in females as compared to males. Social Implications-The findings of the study are considerable with respect to the personal, professional, and educational development of young adults. As the research suggests, there is a positive relationship between decision-making styles, achievement motivation, and orientation towards life. Therefore, various decision-making styles can be introduced in the behavioural sciences subject domain. Higher achievement needs in females indicate their potential in various professional realms, and such platforms, if provided, can increase women's participation in the workforce, resulting in economic, social, and personal development for women as well as society. Originality/ Value The youth of a country are its greatest assets, and for an aspirational country, there is a need for a highly motivated task force. The research topic focuses on how motivated behaviour occupies a central position in personality and its relationship with decision-making style and orientation towards life. This study focuses on the need of the hour, which is harnessing our youth and exploring more about the achievement-oriented behaviour and optimistic outlook of young adults, which is the demographic dividend of the country. 2022 RESTORATIVE JUSTICE FOR ALL. -
Phishing attack detection using Machine Learning
Phishing is a type of digital assault, which adversely affects people where the client is coordinated to counterfeit sites and hoodwinked to screen their touchy and private data which integrates watchwords of records, monetary data, ATM pin-card data, etc. Recently safeguarding touchy records, it's fragile to cover yourself from malware or web phishing. AI is an investigation of information examination and logical investigation of calculations has demonstrated outcomes. Contradicting phishing sprinters with remarkable perception and felonious outcomes comparable as care shops, and custom against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against phishing apparatuses. We made a phishing section framework that extracts capacities that are expected to descry phishing. We likewise utilize numeric outline, as well as an overall investigation of customary Machine Learning methodologies comparable as Decision Tree, Random Forest, Multi-layer Perceptron's, XG Boost Classifier, SVM, Light BGM Classifier, Cat Boost Classifier, and covering grounded highlights choice, which contains the metadata of URLs and assists with deciding if a site is licit or not. 2022 The Authors -
An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders
Most low-voltage (LV) feeders have large distribution losses, poor voltage profiles, and inadequate voltage stability margins owing to their radial construction and high R/X ratio branches, and they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an extended pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the LV feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the LV feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time. The Author(s). -
Dynamic optimal network reconfiguration under photovoltaic generation and electric vehicle fleet load variability using self-adaptive butterfly optimization algorithm
Currently, electrical distribution networks (EDNs) have used modern technologies to operate and serve many types of consumers such as renewable energy, energy storage systems, electric vehicles, and demand response programs. Due to the variability and unpredictability of these technologies, all these technologies have brought various challenges to the operation and control of EDNs. In this case, in order to operate effectively, it is inevitable that effective power redistribution is required in the entire network. In this paper, a multi-objective based dynamic optimal network reconfiguration (DONR) problem is formulated using power loss and voltage deviation index considering the hourly variation of load, photovoltaic (PV) power, and electric vehicle (EV) fleet load in the network. This paper introduces recently introduced meta-heuristic butterfly optimization algorithm (BOA) and it's improve variant of self-adaptive method (SABOA) for solving the DONR problem. The simulation study of IEEE 33-bus EDN under different conditions has proved the effectiveness of DONR, and its adoptability for real-time applications. In addition, by comparing different performance indicators (such as mean, standard deviation, variance, and average calculation time) of 50 independently run simulations, the efficiency of SABOA can be evaluated compared with other heuristic methods (HMs). Comparative studies show that SABOA is better than PSO, TLBO, CSA and FPA in the frequent occurrence of global optimal values. 2021 Walter de Gruyter GmbH, Berlin/Boston 2021. -
Caste, Cricket, and Community Fraternal Intersections in Blue Star
[No abstract available] -
A study of consumers' attitude towards online private label brands using the Tri - Component model
Online private label products seem to be a promising and profitable deal for the Indian online retailers. The purpose of this paper was to understand the consumers' attitude and buying behaviour towards online private label brands. For this purpose, we empirically tested a model comprising of variables such as cognitive, affective, behavioural, purchase intention, and actual buying behaviour. Data were gathered by using a schedule. A sample of 400 respondents was gathered, and the hypotheses were tested by performing structural equation modelling. The findings highlighted that the cognitive, affective, and behavioural factors of attitude influenced each other strongly as well as the purchase intention. In addition, the results obtained revealed that purchase intention led to the buying of online private label brands. It is expected that the findings of this study will enable the marketers of online private label brands to be more informed about the consumers' attitude formation process. Furthermore, it will help them to understand the areas related to private label brands, which need their attention. 1964-2018 Associated Management Consultants. -
Sentiment analysis on social media data using intelligent techniques
Social media gives a simple method of communication technology for people to share their opinion, attraction and feeling. The aim of the paper is to extract various sentiment behaviour and will be used to make a strategic decision and also aids to categorize sentiment and affections of people as clear, contradictory or neutral. The data was preprocessed with the help of noise removal for removing the noise. The research work applied various techniques. After the noise removal, the popular classification methods were applied to extract the sentiment. The data were classified with the help of Multi-layer Perceptron (MLP), Convolutional Neural Networks (CNN). These two classification results were checked against the others classified such as Support Vector Machine (SVM), Random Forest, Decision tree, Nae Bayes, etc., based on the sentiment classification from twitter data and consumer affairs website. The proposed work found that Multi-layer Perceptron and Convolutional Neural Networks performs better than another Machine Learning Classifier. International Research Publication House. -
An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm
Cloud computing has rapidly emerged as a burgeoning research field in recent times. However, despite this growth, a comprehensive examination of this domain reveals persistent issues in the application of cloud-based systems concerning workload distribution. The abundance of resources and virtual machines (VMs) within cloud computing underscores the importance of efficient task allocation as a critical process. Within the infrastructure as a service (IaaS) architecture, load balancing (LB) remains a pivotal but challenging task. The occurrence of overloaded or underloaded hosts/servers during cloud access is undesirable, as it leads to operational delays and system performance degradation. To address LB issues effectively, it is imperative to deploy a proficient access scheduling algorithm capable of distributing tasks across the available resources. A novel approach was introduced by combining the Harris hawks optimization and cuckoo search algorithm (HHO-CSA), with a specific focus on critical service level agreement (SLA) parameters, particularly deadlines, to uphold LB in a cloud environment. The primary objective of the hybrid HHO-CSA methodology is to provide task attributes, resource allocation, VMs prioritization, and quality of service (QoS) to clients within cloud computing applications. The outcome analysis reveals that the proposed hybrid HHO-CSA algorithm results in a resource utilization reduction of 52%, with an execution time of 529.84 ms and a makespan of 638.88 ms. These values outperform those of existing SLA-based LB algorithms. Effective task scheduling plays a pivotal role in ensuring the seamless execution of tasks within a cloud system, while LB significantly aligns with the SLAs available to users. Drawing insights from the existing literature, the suggested hybrid HHO-CSA method addresses the research gap by effectively mitigating the challenges. 2023, Accent Social and Welfare Society. All rights reserved. -
Successful turnarounds: the role of appropriate entrepreneurial strategies
Purpose The purpose of this paper is to report on a research study aimed at comparing the causes of organisational decline and turnaround strategies involved in cases of successful and unsuccessful turnarounds, with a view to identifying the differences, if any, between the two groups, which in turn is expected to provide useful information to academics, practitioners and policy makers. Design/methodology/approach Since turnaround is a business phenomenon of general interest, their stories are often published in business periodicals, which are a rich source of data on them. In order to tap this data source, the present paper employed a method of content analysis for the proposed investigation on the cause of organisational decline and turnaround strategies used. In order to quantify the data, a three-point scale was developed, where the presence of a cause/strategy is rated as 3, its ambivalence as 2 and its absence as 1, whose validity was assessed through the inter-rater agreement indices. The data thus generated are amenable to statistical analyses, using which the more commonly prevalent causes of organisational decline and the strategies commonly employed for turnaround by the successful and unsuccessful companies are identified. Findings The findings of the present study have generated a few useful insights. First, the primary causes for organisational decline are the internal weaknesses of the organisation; in fact the external changes can adversely affect the organisation only if it is internally weak. Second, organisational decline caused by multiple factors (which is usually the case) can be managed effectively by adopting a variety of strategies; hence a single-pronged strategy is often found to be ineffective. Third, the more successful turnarounds had a diverse portfolio of strategies including those of institution-building, often employed in a phased manner, consistent with the stage theories of turnaround. Research limitations/implications The limitations of this research arise mainly from the generation of data from published sources and the consequent biases, which can be managed, to a large extent, by using multiple sources for the same case for reducing the publishers biases as well as by having multiple raters for identifying the researchers biases, if any. Originality/value The study has highlighted the need for addressing the internal causes of organisational decline on a priority-basis rather than blaming the external factors, besides pointing to the need for adopting a variety of strategies for dealing with the diversity of causes affecting the organisations health, particularly the need for institutionalising the changes. These findings can be of help especially to turnaround managers and policy-makers in dealing with organisational decline and thus contribute to the creation and enhancement of economic value. 2015, Emerald Group Publishing Limited. -
A Scoping Review on Integration of Electroencephalogram Neurofeedback Training for Alcohol Use Disorder: Clinical and Neurocognitive Outcomes
Background. The conventional treatment for alcohol use disorder (AUD) consists of dual treatment encompassing pharmacotherapy and psychotherapy. Nonetheless, the impact of these treatments on clinical and neurocognitive outcomes is only low to medium efficacy. Research studies substantiate the integration of electroencephalogram neurofeedback training (EEG-NFT) as an add-on tool with significant improvements in clinical and neurocognitive outcomes. Methods. A scoping review of the existing literature on EEG-NFT and AUD, which are open access, including review papers and empirical studies in the English language, and with human subjects are deemed worthy of the scope of this study. The keywords electroencephalogram neurofeedback training, alcohol use disorder, stress, neurocognition, and relapse were used. The primary sources of the literature search were Science Direct, Scopus, PubMed, and Google Scholar. A total of 35 articles have been included in the scoping review. Studies from the last 15 years were considered for the same. Results. This review revealed that EEG-NFT is a promising tool with significant improvements in stress levels, cognitive deficits, and relapse rates for individuals with AUD when used in integration with conventional treatments. Conclusion. Chronic alcohol use affects cognitive functions, escalates relapse rate, and increases stress experienced by the individual. The present study highlights the significance of NFT as a potent add-on treatment modality to improve clinical and cognitive outcomes, thereby facilitating abstinence and reducing relapse rates in individuals with AUD. Copyright: 2023. -
A Quasi-Experimental Study on the Effectiveness of Integrated Electroencephalogram Neurofeedback Training and Group Psychotherapy for Harmful Alcohol Use: Neurocognitive and Clinical Outcomes
Introduction. This study investigates the efficacy of integrating electroencephalogram (EEG) neurofeedback training and group psychotherapy for individuals with harmful alcohol use (AUDIT-10 scores 1013). Methods. Seventy-six participants were purposively sampled and divided into treatment (EEG neurofeedback training and group psychotherapy) and control groups. Baseline assessments measured alcohol consumption (AUDIT-10), stress (perceived stress scale [PSS]), neurocognition (NIMHANS neuropsychological battery), craving (PACS), and visual analog scale. The treatment group underwent 20 sessions of EEG neurofeedback (Peniston-Kulkosky and Scott-Kaiser modification protocols) and four sessions of group psychotherapy (motivational interviewing [MI], psychoeducation). Result/Discussion. A repeated measures ANOVA showed significant improvement in postcondition scores for the treatment group compared to controls, who exhibited deterioration over time. The study provides evidence supporting the efficacy of integrated EEG neurofeedback training and group psychotherapy in mitigating harmful alcohol use progression. Conclusion. By addressing stress, cognition, and cravings, this intervention offers crucial support to individuals with problematic drinking. 2024. Panicker et al. -
An Empirical Analysis of Turnaround and its Benefits to Stakeholders
International Journal of Applied Management Research, Vol-6 (1(3), pp. 470-473. ISSN-0974-8709 -
Correlation of temperature, velocity and perforation location in a flat unglazed transpired solar collector (Utc) due to air flow
An unglazed transpired solar collector is a system that can leverage the abundant solar energy for various purposes. The solar collector is available in flat or corrugated form and is seen to be installed as an exterior layer of building facades. The cladding thus made absorbs radiation from the sun and heats up air being sucked by fan and flowing through perforations. In this paper, the focus has been to understand the correlation of plate temperature, exit temperature, the velocity distribution in the chamber and perforation location when air flows past a flat unglazed transpired solar collector (UTC). The establishment of correlations was carried out in the dataset of flow variables obtained after solving the problem using Navier-Stokes (NS) equations along with the standard k-? turbulence model and shear stress transport (SST) k-? model. An attempt has also been made to compute Pearsons correlation coefficient of any two flow variables to understand their strong and weak correlations. A linear regression analysis has been done to predict the response variables against the response obtained in CFD solver by using an open source software Rstudio . A strong correlation among cavity vertical velocity, perforation location and temperature has been established. From the study, it is noted that the location of a perforation has a strong correlation with the cavity vertical velocity and a weak correlation exists with temperature and plate temperature. 2020, Pushpa Publishing House. All rights reserved. -
Numerical simulation of flow over a flat unglazed transpired solar collector (UTC) and its performance prediction
An unglazed transpired solar collector is a system that can leverage the abundant solar energy for various purposes. The solar collector is available in flat or corrugated form and is seen to be installed as an exterior layer of building facades. The cladding thus made absorbs radiation from the sun and heats up air being sucked by fan and flowing through perforations. In this research the focus has been to understand the correlation of plate temperature, exit temperature, the velocity distribution in the chamber and perforation location when air flows past an unglazed transpired solar collector (UTC). The establishment of correlations was carried out in the dataset of flow variables obtained after solving the problem using Navier-Stokes (NS) equations along with standard two-equation (k-?) turbulence models and Shear Stress Transport (SST ) k-? models for turbulent flow. The same problem was also solved using NS equation using laminar model. An attempt has also been made to compute Pearsons correlation coefficient of any two variables to understand their strong and weak correlations. A linear regression analysis was done through an open source software Rstudio for a dataset produced during the computational modeling using a commercial CFD solver, Ansys Fluent. At the end a Monte Carlo simulation has been done to predict the likelihood of using the flat UTC for drying as well as to understand the dependency of system efficiency on plate exit temperature, suction velocity and freestream temperature. BEIESP. -
Plano framework for graph indexing - A statistical analysis
Graph Mining is becoming one of the most dominant fields of research. There are plenty methods to index, re-index and to search the features throughout the index but still from the literature study there is no specific frame work which can sum up all three so that indexing and updating the index with new feature can be done in consistent intervals according to the arrival of new features. PLANO is the frame work which has the latest algorithms to look into the data and index. In this paper, Time and Memory efficiency of the proposed algorithms in the PLANO framework is tested statistically and compared with the existing algorithms memory and time usage. Research India Publications.