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Organizational culture, leadership styles, personal commitment and learning organization:An exploratory study
There is an accelerating change in the scope of all areas of human existence in this century. There are tidal waves of changes being felt by academicians also. To accept change that provides internal steadiness while moving ahead is one of the challenges academic institutions have to face. To improve an organization's quality there are many routes for organizational development through change. -
Brain Tumor Classification Using an Ensemble of Deep Learning Techniques
The article reflects on the classification of brain tumors where several deep learning (DL) approaches are used. Both primary and secondary brain tumors reduce the patient's quality of life, and therefore, any sign of the tumor should be treated immediately for adequate response and survival rates. DL, especially in the diagnosis of brain tumors using MRI and CT scans, has applied its abilities to identify excellent patterns. The proposed ensemble framework begins with the image preprocessing of the brain MRI to enhance the quality of images. These images are then utilized to train seven DL models and all of these models recognize the features related to the tumor. There are four models which are General, Glioma, Meningioma, and Pituitary tumors or No Tumor model, which helps in reaching a joint profitable prediction and concentrating solely on the strength of the estimation and outcome. This is a significant improvement over all the individual models, attaining a 99. 43% accuracy. The data used in this research was gotten from Kaggle website and comprised of 7023 images belonging to four classes. Future work will focus on increasing the dataset size, investigating additional DL architectures, and enhancing real-Time detection to improve the accuracy of diagnostic scans and their overall relevance to clinical practice. 2013 IEEE. -
Modeling a Logistic Regression based Sustained Approach for Cancer Detection
This assessment and treatment of cancer may be done using logistic regression. To properly forecast whether a tumour is malignant or benign, the likelihood of binary outcomes may be simulated based on input variables and taken into account for factors like volume, topology and texture. It aids in risk assessment by estimating an individual's likelihood of developing cancer using factors like age-group, relatives past data, life choices and gene based markers. Logistic regression plays an important role in early cancer detection and creating screening tools that identify high-risk individuals through patent characteristics, biomarkers, and medical imaging data. Prediction of the probability of survival based on age, tumor characteristics, treatment options and comorbidities is useful for survival analysis. In a comparative study, logistic regression achieved a high accuracy of 97.4%, along with random forest, in cancer detection and diagnosis. 2023 IEEE. -
Sustainable Climatic Metrics Determination with Ensemble Predictive Analytics
Sustainable features are dependent on vital climatic elements that has a prominent impact on the retention of sustainability provided its metrics are in desired domain. Regression analysis and ensemble learning models are some of the predictive analytics methods which were used to detect the association of every feature on sustainable criteria. Weather samples from Delhi during 1970-2020 is used in the research which considers features like humidity, pollutant level, temperature etc which are gathered from several authenticated sites like pollution management unit of India. After analyzing several elements affecting weather endurability, it is noticed that pollutant level and temperature exhibit the highest significance recording 30% and 44% respectively. Also the R-square metric of 86% and 82% was observed with implementation of analytics models. The major conclusion recorded that random forest outperformed regression model and it established the importance of predictive analytics in predicting sustainability results. The research validated the relevance of climatic tracking for regulating sustainability. 2023 IEEE. -
An Analysis of the Influence of Artificial Intelligence on Human Behaviour and Well-Being
Artificial intelligence is a phenomenon that has transformed the society and tends to have a strong impact on the human behavior and well-being. This is an empirical study which looks at and gauges on the various effects of AI on behavior and well being. It considers the interaction between AI and humanity in different walks through the wide literature review and a high number of empirical data collection. The research analyzes how personalization, recommendation systems and AI-led content curation change decision-making and interconnections of individuals. It also looks in to how AI is influencing health care, educational and mental wellbeing, ethical effects of AI e.g. infringing on privacy, biases in the algorithms and psychological effects of AI-based social media networks. The article gauges the influence of AI in employment systems and economic patterns, shedding light on the prospect of the workforce in possibilities and threats. It also speaks of how AI makes healthcare, education, and convenience improved. The research will be oriented to understanding how AI can influence the human behavior and well-being with the help of the comprehensive statistical processing of the research and data-driven analysis. The findings ought to assist students, professionals, and the society to ethically and safely negotiate AI technologies and concentrate on the necessity to create a measured strategy to utilize the advantages of AI and minimize the harm that could be inflicted on a person and society. Finding and reviewing the factors that influence the human behavior and well-being due to AI is the primary goal of the study. 2025, Green Publication. All rights reserved. -
Design and Realization of a Low-Cost 4 Butler Matrix Antenna Array for C-Band Beamforming
The article addresses the design and modelling of a beam-forming antenna array employing a 4 Butler Matrix Network (BMN) for C-band applications. The proposed low-cost antenna is designed and simulated using CST Microwave Studio Suite (V. 2024), and the prototype is fabricated using an in-house PCB manufacturing process. Simulated results demonstrate that the antenna can form beam patterns in four distinct directions (30, 190). The design achieves a wide -10-db bandwidth of 14.5% at 5.575 GHz, along with a narrow bandwidth of 2.5%, 1.07%, 1%, and 2.72% at 4.327, 4.677, 4.99, and 6.6 GHz, respectively. Also, it exhibits very good gain and considerable radiation efficiency. Furthermore, excellent agreement between simulated and experimental results confirms the validity and effectiveness of the proposed design. 2025 IEEE. -
Navigating the transition to preschool: Understanding the experience of parents in urban india
This qualitative study explores the experiences of parents in urban india as they navigate the process of selecting a preschool for their children, particularly in light of the challenges presented by the COVID-19 pandemic, which started in March 2020. In this study, preschool refers to formal early childhood education programs for children before entering primary school (typically serving children aged 35). This research examines the factors influencing parental decision-making, including the perceived importance of play-based learning, health and safety protocols, school proximity, and teacher qualifications. The study also explores the range of parental emotions experienced during this transition, from anxiety to excitement, as their children begin their preschool education. Using narrative analysis, the study involved interviews with 12 parents of children aged 37 who had recently enrolled their children in preschool. The findings highlight the significant influence of childrens perceived responses to the preschool environment on parental satisfaction and subsequent decision-making. The COVID-19 pandemic emerged as a key contextual factor shaping both the transition process and preschool selection criteria. This research highlights the active role parents play in seeking enriching early learning environments for their children. It also suggests the need for educational policymakers to support high-quality preschool education, particularly by fostering effective parental engagement, to facilitate smoother transitions for families and bridge the gap between quantitative educational targets and the qualitative dimensions of parental experience. The Author(s) 2026 -
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
This chapter elucidates the wage differential between male and female informal workers in urban labour market by using employment and unemployment survey 61st (2004-2005) round, 68th (2011-2012), and Periodic Labour Force Survey 2019-2020 data of National Sample Survey Office (NSSO) unit level data. This study found that gender inequality not only increased during getting job but also persists after getting job during wage distribution. Based on the Oaxaca-Blinder (OB) decomposition, it is revealed that gender wage inequality is more in the labour market due to the labour market discrimination, that is, unexplained components. Hence, this study helps researcher, policy makers and government to fix the gender wage discrimination issues exist in the Indian labour market. This will enhance economic growth through the rise of the women labour force participation. 2024 A. Vinodan, S. Mahalakshmi, and S. Rameshkumar. -
Drivers of Rural Non-farm Sector Employment in India, 19832019
Using the national-level employment and unemployment surveys (NSS and PLFS) and the macro-level data for the period 20052019, this article explores the trends and recent growth patterns of rural non-farm sector employment in India. It also examines the micro-level factors determining individuals preference towards non-farm sector jobs and the macro-level factors responsible for the growth of non-farm sector employment in rural India. The main findings of the study suggest that although rural non-farm sector employment is rising in absolute terms, its growth rate has slackened in recent years. While the level of education and skill training, market wage rates and socio-cultural setups are among the key micro-level factors determining farmnon-farm employment choices of rural folks, at the macro-level, the growth of investment in capital goods, the number of factories, investment in infrastructure development and the growth of the manufacturing sector are crucial for the growth of non-farm sector jobs in India. Based on these findings, it is argued that the improvement of human capabilities through increased investment in education and skill, and the growth of non-farm sector employment through the development of rural infrastructure and industrialization measures, are necessary to sustain the structural transformation and to harness the demographic dividend in India. JEL Codes: J01, J21, J43, J64 2024 Research and Information System for Developing Countries & Institute of Policy Studies of Sri Lanka. -
Feminization of hunger in climate change: linking rural womens health and wellbeing in India
The links between climate change, food security and womens wellbeing remain an under-investigated area. This paper contributes to this area through a thorough examination of how women experience food insecurity in farming households in rural India. The households are located in four agro-climatic regions in India. These regions experience varied climatic pressures, and this diversity allows us to explore a wider variety of womens experiences in their attempts to maintain household food security as the climate changes. The study finds that women, even in comparatively more food-secure households, suffer from food insecurity. One of the reasons for this is that womens food habits and mealtimes have altered in recent years due to the increase in their work pressures. The worst effects are to be found in drought-prone areas, and there are greater vulnerabilities among women-headed households, indicating that the impacts of climate change are exacerbated by cultural norms that further hinder the role of women in farm activities. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Heat transport of nano-micropolar fluid with an exponential heat source on a convectively heated elongated plate using numerical computation
Purpose: The study of novel exponential heat source phenomena across a flowing fluid with a suspension of microparticles and nanoparticles towards a convectively heated plate has been an open question. Therefore, the impact of the exponential heat source in the transport of nano micropolar fluid in the existence of magnetic dipole, Joule heating, viscous heating and convective condition effects has been analytically investigated. Influence of chemical reaction has also been exhibited in this discussion. Design/methodology/approach: The leading equations are constructed via conservation equations of transport, micro-rotation, energy and solute under the non-transient state situation. Suitable stretching transformations are used to transform the system of partial differential equations to ordinary. The transformed ODEs admit numerical solution via RungeKutta fourth order method along with shooting technique. Findings: The effects of pertinent physical parameters characterizing the flow phenomena are presented through graphs and discussed. The inclusion of microparticles and nanoparticles greatly affects the flow phenomena. The impact of the exponential heat source (EHS) advances the heat transfer characteristics significantly compared to usual thermal-based heat source (THS). The thermal performance can be improved through the effects of a magnetic dipole, viscous heating, Joule heating and convective condition. Originality/value: The effectiveness of EHS phenomena in the dynamics of nano micropolar fluid past an elongated plate which is convectively heated with regression analysis is for the first time investigated. 2019, Emerald Publishing Limited. -
Sodium alginate functionalized nickel ferrite nanocomposites: synthesis, physicochemical characterization, and evaluation of antibacterial, anticancer, and biocompatibility properties
The rise of multidrug-resistant bacteria and the need for effective therapies against breast cancer highlight the demand for multifunctional nanomaterials with high biocompatibility. In this study, Nickel ferrite (NiFe?O?) and sodium alginate functionalized NiFe?O? nanocomposites (NiFe?O?-SA) were synthesized via a green co-precipitation method. X-ray diffraction confirmed a cubic spinel structure, and transmission electron microscopy revealed quasi-spherical nanoparticles with sizes of 1525nm and uniform alginate coating. UVVis analysis showed a reduction in band gap from 4.44eV to 3.13eV, while photoluminescence spectra indicated enhanced charge carrier separation. NiFe?O?-SA exhibited strong antibacterial activity against Gram-negative pathogens (Klebsiella pneumoniae, Escherichia coli, Shigella dysenteriae, Pseudomonas aeruginosa, and Proteus vulgaris), with membrane disruption confirmed by microscopy. Cytotoxicity studies on MCF-7 breast cancer cells demonstrated dose-dependent inhibition with an IC?? of 11.9?g/mL, and zebrafish embryo assays confirmed excellent biocompatibility for NiFe?O?-SA. These findings highlight NiFe?O?-SA nanocomposites as promising multifunctional nanomaterials for therapeutic and biomedical applications. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Mental Health Data Analysis Using Cloud
In health care related research studies, there exists a need for retrieving patient's health record from multiple sites. So here comes the digitization of health records, which leads to a wide range of access to various users such as doctors, patients, psychiatrists and pharmacists. The sensitive nature of individual health care data pose a threat to security. Moreover, the increased access of health information by the users threatens the privacy and confidentiality of the stored data. Notwithstanding the existing privacy protection approaches used for mental health records, we suggest a privacy preserving data analysis methodology enabling protection of health records, once user access to records are granted. This paper mainly focuses on utilizing the data analysis approach in preserving privacy of personal health records to overcome the drawbacks of existing approaches. 2020 IEEE. -
A predictive model on post-earthquake infrastructure damage
Disaster management initiatives are employed to mitigate the effects of catastrophic events such as earthquakes. However, post-disaster expenses raise concern for both the government and the insurance companies. The paper provides insights about the key factors that add to the building damage such as the structural and building usage properties. It also sheds light on the best model that can be adopted in terms of both accuracy and ethical principles such as transparency and accountability. From the performance perspective, random forest model has been suggested. From the perspective of models with ethical principles, the decision tree model has been highlighted. Thus, the paper fulfills to propose the best predictive model to accurately predict the building damage caused by earthquake for incorporation by the insurance companies or government agency to minimize the post-disaster expenses involved in such catastrophic event. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Denial of Service Attacks in the Internet of Things
A DoS attack is the most severe attack on IoT and creates a crucial challenge for the detection and mitigation of such attacks. A DoS attack occurs at multiple layers of the IoT protocol stack and exploiting the protocol vulnerabilities disrupts communication. Traditional mechanisms employ single-layer detection of DoS attacks, which individually detect and mitigate attacks. However, it is essential to establish a general framework for detecting DoS attacks in a real-time environment and coping with diversified applications. This can be achieved by fetching attack features of multiple layers to create a pool of numerous attacks and then designing a system that detects the attack when fed with specific attack features. This chapter comprehensively analyzes the research gap in the DoS attack detection techniques proposed. Secondly, we offer a two-stage framework for DoS attack detection, comprising Fuzzy Rule Manager and Neural Network (NN), to detect cross-layer DoS attacks in real time. The Input Data Type (IDT) is derived using a fuzzy rule manager that can identify the type of input dataset as usual or attack in real time. This IDT is passed to the NN along with the real-time dataset to increase detection accuracy and decrease false alarms. 2024 selection and editorial matter, Vinay Chowdary, Abhinav Sharma, Naveen Kumar and Vivek Kaundal; individual chapters, the contributors. -
Overview of Cyber Security in Intelligent and Sustainable Manufacturing
With the advent of the Internet of Things (IoT), a new transformation is predominant in the manufacturing industry, termed Industry 4.0. The revolution of IoT with artificial intelligence, Web3, robotics, and automation has transformed the traditional manufacturing system into a smart manufacturing system (SMS) by adding an intelligent component capable of automatic data collection through using sensors, processing data autonomously, and controlling machines remotely. However, adding automated intelligence, autonomous systems, and real-time data processing presents an insecure surface to cyber attackers to penetrate these cyber-physical systems (CPSs) and cause physical damage. This chapter presents a detailed discussion of cyber threats and incidents in the intelligent manufacturing industry, along with the available acceptable mitigation strategies. A taxonomy of cyber attacks on intelligent manufacturing systems clearly shows the difference between information technology threats and smart manufacturing cyber-threats. A detailed discussion on the limitations of SMSs in implementing cyber security is presented. Finally, some innovative machine learningbased security mechanisms (ML-based intrusion detection systems) are discussed that promise to detect anomalies/intrusions in such systems. 2025 selection and editorial matter, Ajay Kumar, Parveen Kumar, Yang Liu, and Rakesh Kumar. -
Influence of HRM practices on organizational commitment: A study among software professionals in India
Although organizational commitment has been discussed frequently in organizational psychology for almost four decades, few studies have involved software professionals. A study in India reveals that HRM practices such as employee-friendly work environment, career development, developmentoriented appraisal, and comprehensive training show a significant positive relationship with organizational commitment. The study's results emphasize the role of such HRD variables as inculcating and enhancing organizational commitment, and suggest that HRD practitioners and researchers should further develop commitment-oriented organization policies. Copyright 2004 Wiley Periodicals, Inc. -
Impact of people management practices on organizational performance: Analysis of a causal model
Although researchers in strategic human resource management have established a relationship between HRM practices and organizational performance, the intervening process connecting HRM system and organizational performance remains unexplored. This paper, based on a study on Indian software companies, is an attempt to develop and test a causal model linking HRM with organizational performance through an intervening process. The study has found that not even a single HRM practice has direct causal connection with organizational financial performance. At the same time, it has been found that each and every HRM practice under study has an indirect influence on the operational and financial performance of the organization. Further, HRM practices such as training, job design, compensation and incentives directly affect the operational performance parameters, viz., employee retention, employee productivity, product quality, speed of delivery and operating cost. -
Antioxidant Phenolics of Justicia adhatoda L. and Cordia dichotoma Frost. Promote Thrombolytic Activity through Binding to a Serine Protease, Tissue Plasminogen Activator Protein
Background: The tissue plasminogen activator (tPA) protein dissolutes fibrin clots and prevents the disease like thrombosis. The current study aimed to study the tPA-promoting activity of bioactive molecules of Justicia adhatoda L (JA) and Cordia dichotoma Frost (CD). Methods: The phytochemical characterization of methanolic and aqueous extracts of JA and CD stems was performed through qualitative analysis, Fourier-transform infrared spectroscopy (FTIR), and biochemical tests (total phenolic and total flavonoid content [TPC and TFC]). The bioactivity of the extracts was studied through total antioxidant capacity (TAC) and ferric-reducing antioxidant potential (FRAP) assays. Finally, forty phytocompounds from JA and CD were identified from the literature, and in silico molecular docking study was performed to target tPA protein (PDB id 1A5H, Chain A, X-ray diffraction, resolution 2.90 . Results: Various phytochemical classes were identified from extracts, through qualitative and FTIR analysis. TPC and TFC were estimated from the JA and CD extracts within the range of 9.3428.67 mg gallic acid equivalent/100 g of extract weight (EW) and 2.4816.17 mg quercetin equivalent/100 g of EW, respectively. The aqueous extract of CD showed the highest TAC of 14.90 ascorbic acid equivalent (AAE)/100 g of EW, and the methanolic extract of JA had the highest FRAP activity of 27.77 mg AAE/100 g EW. The molecular docking study showed that apigenin 6,8-di-glucopyranoside had the highest binding potential toward the tPA (?9.380 kcal/mol). Conclusion: It can be concluded that antioxidant phytochemicals of JA and CD could promote the tPA activity, thereby promoting thrombolytic activity. Copyright: 2023 Biomedical and Biotechnology Research Journal (BBRJ)