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Quality of work life and work motivation among garment sector executive employees /
The International journal Of Indian Psychology, Vol.3, Issue 1, pp.111-119, ISSN No: 2349-3429. -
QUALITY OF WORK LIFE IN RELATION TO PEOPLE CAPABILITY MATURITY MODEL IN IT AND ITES ORGANIZATIONS
The new found concern for Quality of Work Life in corporate life perhaps has been due to the realization that human resource is the most important asset which must be released and developed. Management viewed QWL programs as a way of reducing costs and improving productivity. The success of any organization depends on how it attracts recruits, motivates and retains its workforce. Human capital is clearly emerging as a key engine of economic growth, and it is evident that the skills and competencies of the workforce impact positively on productivity and competitiveness. In this regard investment in human capital would appear to be a prerequisite to economic success .In this new scenario People capability maturity model offers unlimited potential to develop and maximize human capital and organizational competence in the interest of the firm ,the employee ,the consumer ,the shareholder and not least the family. People capability maturity model is a maturity framework developed at the software engineering institute that guides the organizations in improving the ability to attract, develop, motivate, organize and retain talent.. Economies of the world over and companies facing tough domestic and international markets have been posing a serious challenge to all concerned. This coupled with every changing technology and increased access to information has necessitated studying organization with respect to productivity, efficiency and quality of service rendered. All this demands a new work culture, employee motivation, commitment to the job and organizational goals. Some organizations in the service sector have implemented PCMM to address all these organizational issues. However we have very little information at the grass root level to comprehend QWL, and very little research on QWL Life in relation to PCMM hence this study. Based on the objectives of the study a detailed questionnaire was constructed by the researcher. The questionnaire has three parts measuring demographics, implementation of PCMM and six dimensions of QWL. It was measured on a 5 point likert scale 1 indicating strongly disagree to 5 indicating strongly agree. The Cronbachs alpha reliability for the PCMM and the QWL for the present sample was .80 and above. The questionnaire was completed by 230 respondents using judgmental sampling technique from PCMM implemented and non implemented IT and ITES organizations. It was found that Quality of work life was not significantly higher in companies that implemented People capability maturity model as compared to other companies. Amongst all the dimensions of Quality of work life the only dimension influenced and affected by People capability maturity model was self evaluation of performance .It was found that there was a variation of 20.1% in the Quality of work life. In terms of correlation, the study indicated that there was significant intra relationship between the 6 dimensions of Quality of work Life; significant intra relationship between the People Capability Maturity Model related items and significant interrelationship between 6 dimensions of Quality of Work Life and the People capability maturity model related items. Amongst all the 6 dimensions of Quality of Work Life the only dimension that was significantly different across gender was self evaluation of performance. Females had higher self evaluation of performance as compared to the male counterparts. On the basis of the results attained from the current study we can clearly imply that Quality of work life dimensions is definitely positively influenced, affected and correlated with People Capability Maturity Model though there is no difference in Quality of Work Life among People Capability Maturity Model implemented and Non implemented IT and ITES organizations. The results from the study will have significant implications on the companies that have not implemented People Capability Maturity Model to join the group of People capability maturity model implemented companies as this will help the organizations to prepare the employees psychologically to meet the demands and challenges which otherwise may risk a poor Quality of work life program implementation. Key Words: Organizational behavior, Human Resource Management, People Capability Maturity Model, Quality of Work Life, General linear model. -
Quality of work life, emotional and physical well-being of police personnel in India
The job profile of police officers places exceptional demands on them leading to risks to life, personal discomfort and stress. This article aims to examine how the physical and emotional well-being of police personnel is affected by their perceived quality of work life (QWL). The study looked at the questionnaire responses of 234 police personnel. Emotional well-being is measured as the absence of depression, emotional hyperactivity, difficulty relaxing, irritability and anxiety, whereas physical well-being is measured as the presence of diabetes, thyroid problems, insomnia and obesity. The study assessed police perceptions of QWL as provided by the government. The study findings are segregated for QWL on the basis of dominant ill-being and dominant well-being. Factors such as career and development, working environment, safety, work load, compensation and fear of punishment should be carefully analysed and improved. Some 71.8% of the respondents suffered from two or more emotional ailments; 70% suffered from two or more physical ailments. Findings suggest that QWL dimensions that fall within dominant ill-being need to be addressed immediately by policy makers and management to improve police well-being. The Author(s) 2021. -
Quantifying the Impact: Assessing FPO Penetration in Indian Agriculture Through the Lens of the 2019 Situation Assessment Survey
In India, Farmer Producer Organisations (FPOs) are garnering significant attention as a potential solution to address the challenges faced by small-scale farmers. This research paper focuses on the engagement of farmers with more than 33,000 registered FPOs in India. It analyzes data from the Situation Assessment of Agricultural Households 2019 and the FPO dataset by the Tata Cornell Institute. The paper sheds light on how farmers are involved with FPOs to meet their agricultural needs, such as acquiring inputs, managing the sale of farm produce, and receiving technical support for farming activities. Despite the anticipated benefits for farmers through their engagement with FPOs, the actual achievements have not met initial expectations. The impact of FPOs on farmers remains minimal, with fewer than 1% of farmers in India utilizing FPO services. This emphasizes the crucial need for reassessment and targeted interventions to enhance the effectiveness of these organizations. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Quantifying the role of nanocarbon fillers on dielectric properties of poly(vinylidene fluoride) matrix
Development of polymers with excellent dielectric properties is a challenge for advanced electronic devices. Impregnating conducting fillers like carbon nanoparticles can enhance the dielectric constant, retaining low loss due to its compatibility and favorable polarization within the polymer matrix. The multifunctional characteristics of coal-derived nanocarbon can improve permittivity and facilitate large-scale production at a lower cost. The incorporation of coal-based nanocarbon in the polymer matrix and its dielectric response is seldom investigated. In this work, different ratios (10:90, 50:50, 90:10 by weight) of nanocarbon/PVDF composite are prepared via a simple solution casting technique. The dielectric measurements show that nanofillers addition significantly augments the dielectric constant value, which is ?3 times (50:50 composite) higher than pure PVDF. The uniform distribution of 50% filler within the polymer matrix impeded the seepage of charge at the interface and enhanced the permittivity via polarization of accumulated charges. The composite also exhibited balanced dielectric loss that is essential for energy storage applications. The Author(s) 2022. -
Quantitative assessment of blockchain applications for Industry 4.0 in manufacturing sector
Blockchain is one of the emerging digital technologies that will play a role in the breakthroughs of the fourth industrial revolution. The use of blockchain technology has the potential to greatly benefit businesses of all sizes by increasing their data's integrity, privacy, and openness. The term Industry 4.0? refers to the amalgamation of recent advances in manufacturing technology that have helped businesses cut production times significantly. The industrial and supply chain industries can benefit from these technological advancements in a number of ways. Increased efficiency in production and a more stable supply chain are just two of the many benefits that blockchain promises to bring to the manufacturing industry. The study focuses on Blockchain's huge potential in the context of Industry 4.0. Understanding the role of Blockchain technology in Industry 4.0 is examined, along with its various drivers, enablers, and associated capabilities. The several sub-domains of Industry 4.0 that can benefit from the implementation of Blockchain technology are also covered. The present research is primary and exploratory in nature. The sample size of the study is 256. The responses obtained from workers working in manufacturing sector in Delhi/NCR. The responses from workers obtained through structured questionnaire. The several sub-domains of Industry 4.0 found that can benefit from the implementation of Blockchain technology. At last, the existing study found the most important uses of Blockchain technology in the fourth industrial revolution. 2023 -
Quantitative Structure-Activity Relationship Modeling for the Prediction of Fish Toxicity Lethal Concentration on Fathead Minnow
As there has been a rise in the usage of in silico approaches, for assessing the risks of harmful chemicals upon animals, more researchers focus on the utilization of Quantitative Structure Activity Relationship models. A number of machine learning algorithms link molecular descriptors that can infer chemical structural properties associated with their corresponding biological activity. Efficient and comprehensive computational methods which can process huge set of heterogeneous chemical datasets are in demand. In this context, this study establishes the usage of various machine learning algorithms in predicting the acute aquatic toxicity of diverse chemicals on Fathead Minnow (Pimephales promelas). Sample drive approach is employed on the train set for binning the data so that they can be located in a domain space having more similar chemicals, instead of using the dataset that covers a wide range of chemicals at the entirety. Here, bin wise best learning model and subset of features that are minimally required for the classification are found for further ease. Several regression methods are employed to find the estimation of toxicity LC50 value by adopting several statistical measures and hence bin wise strategies are determined. Through experimentation, it is evident that the proposed model surpasses the other existing models by providing an R2 of 0.8473 with RMSE 0.3035 which is comparable. Hence, the proposed model is competent for estimating the toxicity in new and unseen chemical. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Quantitative Structure-Activity Relationship Modeling for the Prediction of Fish Toxicity Lethal Concentration on Fathead Minnow
As there has been a rise in the usage of in silico approaches, for assessing the risks of harmful chemicals upon animals, more researchers focus on the utilization of Quantitative Structure Activity Relationship models. A number of machine learning algorithms link molecular descriptors that can infer chemical structural properties associated with their corresponding biological activity. Efficient and comprehensive computational methods which can process huge set of heterogeneous chemical datasets are in demand. In this context, this study establishes the usage of various machine learning algorithms in predicting the acute aquatic toxicity of diverse chemicals on Fathead Minnow (Pimephales promelas). Sample drive approach is employed on the train set for binning the data so that they can be located in a domain space having more similar chemicals, instead of using the dataset that covers a wide range of chemicals at the entirety. Here, bin wise best learning model and subset of features that are minimally required for the classification are found for further ease. Several regression methods are employed to find the estimation of toxicity LC50 value by adopting several statistical measures and hence bin wise strategies are determined. Through experimentation, it is evident that the proposed model surpasses the other existing models by providing an R2 of 0.8473 with RMSE 0.3035 which is comparable. Hence, the proposed model is competent for estimating the toxicity in new and unseen chemical. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Quantitative X-ray and Spectroscopic Analysis of Nanocrystalline and Amorphous Carbon Materials
Carbon and its various allotropic forms is a blooming and extensively investigated field for the past few decades. The revolution which started with the discovery of fullerenes in 1985 continues with the newly discovered wonder material graphene and has never failed to amass the interest of scientific community. After all these years it still stays as a hot topic of research. This is primarily due to their unique physical and chemical properties which makes them suitable for a whole host of applications ranging from thin film technology to nano-medicine. But, the production cost of these novel materials is an issue which shadows its glory and hence it is essential to find out efficient and cost effective sources and production methods for these materials. Graphene oxide has attracted much interest because of its low cost, easy access and unique ability to get converted into graphene. Graphene oxide is basically, a graphene sheet which consists of either carboxyl or hydroxyl groups. Foreseeing the upcoming era of carbon nanomaterials on account of their revolutionary applications and the ever increasing demand for economical and viable sources, we have identified and explored the structural parameters of an efficient and cost effective precursor of the same. In the present investigation, wood charcoal and coconut shell charcoal, which is a superior source of activated carbon, is produced by a slow thermal decomposition method in a limited supply of oxygen. It is an impure form of carbon- is a black residue composed mainly of carbon, ash and char. Wood charcoal is transformed into Graphite oxide (GO) by a modified Hummers method. Spectroscopic analysis of the samples is carried out by various techniques such as X-ray diffraction (XRD), Raman Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), UV-Vis spectroscopy and Scanning Electron Microscopy (SEM). The various structural parameters are calculated from XRD and Raman data. -
Quantum AI in Finance: Predicting the Unpredictable
Navigating modern global financial markets becomes increasingly intricate, which makes the traditional approaches inadequate in processing large volumes of data in real time. This chapter presents Quantum Artificial Intelligence (QAI) and its capabilities in predicting and mitigating unanticipated financial shocks. With the integration of quantum computings parallel processing capabilities and AIs adaptive learning, QAI makes it possible for institutions to model market nonlinearities, scope large- scale simulations, and detect faint signals that are commonly overlooked by classical systems. The scope of this chapter illustrates the impact of QAI in real- time risk evaluation, fraud identification, portfolio management, and macroeconomic prediction and modeling. Focus is given to quantum- boosted machine learning models that are designed to simulate black swan events and other high- dimensional datasets. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Quantum Algorithm: A Classical Realization in High-Performance Computing Using MPI
Volume3, Special Issue3 ISSN: 23198753 -
Quantum Algorithms for Enhancing Cybersecurity in Computational Intelligence in Healthcare
This book explores the exciting field of quantum computing, which is changing how we approach computation. It covers the basics, cybersecurity aspects, advanced machine learning techniques, and the many ways quantum computing can be used. Quantum computing is much more powerful than traditional computing. The book starts by explaining the core concepts like qubits, quantum gates, superposition, entanglement, quantum memory, and quantum parallelism. One important area is how quantum computing can improve machine learning for cybersecurity. It can handle huge amounts of data and find complex patterns faster than regular computers. This is especially useful for finding cyber threats in real time, such as spotting unusual activity in healthcare networks that might mean a security breach. Quantum machine learning can help healthcare organizations better defend against advanced cyberattacks that try to steal patient data. The book also looks at how quantum computing is changing cybersecurity itself. It discusses quantum cryptography, post-quantum cryptography, and secure communication, explaining how quantum computing is leading to new ways of encrypting data, detecting threats, and protecting information. Beyond cybersecurity, the book shows how quantum computing impacts many other fields, such as medicine, finance, materials science, and logistics. It is poised to revolutionize artificial intelligence (AI) in healthcare and many other sectors. Because quantum computing is constantly developing, with discoveries and new applications happening all the time, this book brings together researchers from universities and industries to share their latest findings. It aims to help shape the future of this technology. The book offers a solid foundation, detailed explanations of advanced techniques, and a fascinating look at how quantum computing is being used in the real world. As quantum computing becomes easier to access through new tools and cloud platforms, this book hopes to inspire new research in AI and spark innovative applications that were previously thought impossible. 2026 selection and editorial matter, Prateek Singhal, Pramod Kumar Mishra, and Mokhtar Mohammed Hasan; individual chapters, the contributors. All rights reserved. -
Quantum approaches to sustainable resource management in supply chains
Quantum computing leverages the principles of quantum mechanics to process information in ways that classical computers cannot. This capability is particularly advantageous for solving complex optimization problems that are common in supply chain management. Quantum algorithms, such as the quantum approximate optimization algorithm (QAOA) and quantum annealing, have shown promise in efficiently solving these problems by exploring numerous potential solutions simultaneously and identifying optimal strategies. The purpose of this chapter is to investigate the rapidly developing topic of quantum computing and its potential applications in managing sustainable resources within supply chains. Traditional resource allocation methods often struggle to maximize efficiency while minimizing environmental impact. However, new developments in quantum computing have opened up potentially fruitful pathways for addressing these issues. This study aims to explore how quantum computing can revolutionize through an examination of quantum algorithms, optimization approaches, and case studies. 2024 by IGI Global. All rights reserved. -
Quantum computational, solvation and in-silico biological studies of a potential anti-cancer thiophene derivative
Heterocyclic molecules display a wide spectrum of properties that span both material and biological domains. Material properties stem from their interactions in the bulk, where a large number of molecules of the same type get together resulting in an enhancement of properties. However, biological properties emanate from the interaction of a single or a few molecules with a biologically functional macromolecule. Computational tools offer a particularly useful way of theoretically studying molecules to arrive at a conclusion regarding such properties, even though they may vary when experimentally evaluated. This study concerns itself with the theoretical investigation comprising density functional theory calculations, topological analyses and in-silico biological evaluation of a thiophene compound, i.e. the title compound. Density functional theory was used to compute properties of the title molecule and their variations in unsolvated and solvated phases using Gaussian 09. The molecule in solvent phases encompassing organic polar protic, organic polar aprotic and inorganic polar protic nature have been subjected to theoretical investigations. The suitability of the molecule for deployment as a modern optical material is examined with positive results. Topological characteristics of the molecule were evaluated using Multiwfn 3.8 to examine electron density distribution and the possible resulting covalent, non-covalent and weak interactions because of such distribution. The potency of the molecule towards brain cancer was evaluated by molecular docking with Auto Dock Tools against two brain cancer protein targets 6ETJ and 6YPE with a good docking score of ?6.63 and ?6.21 kcal mol?1 respectively and the resulting interactions visualized and its pharmacokinetic properties obtained using online tools. 2024 Elsevier B.V. -
Quantum Computing: Navigating The Technological Landscape for Future Advancements
Quantum Computing represents a transformative paradigm in information processing, leveraging principles of quantum mechanics to enable computations that transcend the limitations of classical computing. This research paper explores the cutting-edge technologies employed in Quantum Computing, examining the key components that facilitate quantum information processing.The purpose of this study is to provide a comprehensive exploration of the state-of-the-art technologies in Quantum Computing, laying the groundwork for future advancements and applications in this rapidly evolving field.The methodology employed in this study integrates three analytical approaches: sentiment analysis, topic modeling, and thematic analysis. Sentiment analysis is utilized to discern and quantify emotional tones within the content. Topic modeling is applied to identify latent themes and patterns within the data, revealing underlying structures. Thematic analysis, on the other hand, involves a systematic identification and exploration of recurrent themes to provide a nuanced understanding of the subject matter. This tripartite methodology ensures a comprehensive examination of the data, facilitating a robust and multifaceted analysis of quantum computing technologies. 2024 IEEE. -
Quantum Computings Path toSupremacy: Progress in the NISQ Epoch
Quantum computing leverages the principles of quantum mechanics for information processing, with qubits serving as the fundamental units of quantum information. Qubits are quantum states where information processing can be engineered. Qubits possess the unique ability to encode, manipulate and extract information, enabling remarkable parallelism in computation. This enhanced computational speed, called quantum supremacy, promises to transcend established complexity boundaries. Significant strides have been made in demonstrating quantum supremacy through various experiments, most notably Googles 2019 experiment utilizing the Sycamore quantum processor to solve a problem that would stymie classical supercomputers for millennia. Other research groups, such as the Chinese team employing Jiuzhang and Zuchongzhi quantum processors, have achieved similar feats, showcasing the profound computational capabilities of quantum computers. It is essential to underscore that quantum supremacy does not signify quantum computers superiority across all tasks; current quantum computers remain constrained in their applicability, excelling primarily in specific problem domains. Nevertheless, recent advancements in quantum computing are noteworthy and ongoing development promises to expand their problem-solving capacities. This paper offers an introductory overview of quantum computing and an assessment of three prominent quantum supremacy experiments. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Quantum Convolutional Neural Network for Medical Image Classification: A Hybrid Model
This study explores the application of Quantum Convolutional Neural Networks (QCNNs) in the realm of image classification, particularly focusing on datasets with a highly reduced number of features. We investigate the potential quantum computing holds in processing and classifying image data efficiently, even with limited feature availability. This research investigates QCNNs' application within a highly constrained feature environment, using chest X-ray images to distinguish between normal and pneumonia cases. Our findings demonstrate QCNNs' utility in classifying images from the dataset with drastically reduced feature dimensions, highlighting QCNNs' robustness and their promising future in machine learning and computer vision. Additionally, this study sheds light on the scalability of QCNNs and their adaptability across various training-test splits, emphasizing their potential to enhance computational efficiency in machine learning tasks. This suggests a possibility of paradigm shift in how we approach data-intensive challenges in the era of quantum computing. We are looking into quantum paradigms like Quantum Support Vector Machine (QSVM) going forward so that we can explore trade offs effectiveness of different classical and quantum computing techniques. 2024 IEEE. -
Quantum corrections in general relativity explored through a GUP-inspired maximal acceleration analysis
A maximun acceleration analysis by Pati dating back to 1992 is here improved by replacing the traditional Heisenberg Uncertainty Principle (HUP) with the Generalized Uncertainty Principle (GUP), which predicts the existence of a minimum length in Nature. This new approach allows one to find a numerical value for the maximum acceleration existing in Nature for a physical particle that turns out to be [Formula presented] that is, a function of two fundamental physical quantities such as the speed of light c and the Planck length lp. An application of this result to black hole (BH) physics allows one to estimate a new quantum limit to general relativity. It is indeed shown that, for every real Schwarzschild BH, the maximum gravitational acceleration occurs, without becoming infinite, when the Schwarzschild radial coordinate reaches the gravitational radius. This means that quantum corrections to general relativity become necessary not at the Planck scale, as the majority of researchers in the field think, but at the Schwarzschild scale, in agreement with recent interesting results in the literature. In other words, the quantum nature of physics, which in this case manifests itself through the GUP, appears to prohibit the existence of real singularities, in this current case forbiddiing the gravitational acceleration of a Schwarzschild BH from becoming infinite. 2025 The Authors -
Quantum cryptography: An in-depth exploration of principles and techniques
Quantum cryptography is evolving in the field of data security and cryptographic research, as it offers a high level of security based on the principles of quantum mechanics. This chapter provides an extensive understanding and in-depth explanation about the basic concepts of the techniques implemented in quantum cryptography. The exploration of the fundamental concepts begins with elaboration on the foundational concepts of quantum mechanics, such as no-cloning, entanglement, superposition, and quantum state measurement, which are crucial for the better understanding of quantum cryptography. Further, the chapter delves more into the quantum key distribution (QKD) protocols such as BB84, BBM92, and B92. All the QKD protocols are analysed and compared based on the underlying principles and techniques. Furthermore, the importance and benefits of the integration of quantum cryptography with the traditional algorithms are also discussed. The chapter also aims to provide thorough study of quantum cryptography principles, challenges, and future directions along with a detailed comprehensive review of quantum cryptographic techniques. 2025 selection and editorial matter, Keshav Kumar and Bishwajeet Kumar Pandey; individual chapters, the contributors. -
Quantum cryptography: An in-depth exploration of principles and techniques
Quantum cryptography is evolving in the field of data security and cryptographic research, as it offers a high level of security based on the principles of quantum mechanics. This chapter provides an extensive understanding and in-depth explanation about the basic concepts of the techniques implemented in quantum cryptography. The exploration of the fundamental concepts begins with elaboration on the foundational concepts of quantum mechanics, such as no-cloning, entanglement, superposition, and quantum state measurement, which are crucial for the better understanding of quantum cryptography. Further, the chapter delves more into the quantum key distribution (QKD) protocols such as BB84, BBM92, and B92. All the QKD protocols are analysed and compared based on the underlying principles and techniques. Furthermore, the importance and benefits of the integration of quantum cryptography with the traditional algorithms are also discussed. The chapter also aims to provide thorough study of quantum cryptography principles, challenges, and future directions along with a detailed comprehensive review of quantum cryptographic techniques. 2025 selection and editorial matter, Keshav Kumar and Bishwajeet Kumar Pandey; individual chapters, the contributors.