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Energy sector in India: Challenges and solutions
Energy plays a vital role in the socio-economic development and human welfare of a country. It is indeed a difficult task to meet the ever increasing demand with minimum environmental risks. Population explosion and economic growth are the two major facts that drives the energy demands. The economic growth rate of India has hit the decade low of 5% in 2012-13, which shows the challenges yet to come. India being a fast developing nation with second largest population in the world, faces a significant challenge to meet the desired economic growth rate and to provide adequate access to affordable and clean energy for a large population. With the growing concern about India's population, energy demands and climatic issues, it is difficult to formulate a sustainable energy plan for the country. At the same time energy plan should have minimal effects on the health of nature by reducing CO2 emissions. To cut down CO2 emissions, to reduce fossil fuel import bills and to reduce the dependence on a third country energy supplies, India has to increase the share of renewable energy sources in the country's final energy consumption to at least 18% by 2020. This paper provides a comprehensive overview of India's energy sector, discusses the current scenario, identifies the energy utilization, challenges and puts forward some effective solutions in meeting the increasing energy demands. 2013 IEEE. -
Us and India: Emerging offshore balancing in Asia
The US and India have become closer in recent times. Compared with the last century, the relationship between the two countries is in steady growth. Under both the Bush and Obama administrations, and now the Trump administration too, India is receiving significant importance in US strategic policy toward the IndoPacific. Indias emergence as a credible power in the Indian Ocean region has brought both countries much closer. The relationship has also steadily progressed as result of Chinas emergence as a potential hegemon in Asia. The US faces difficulty in maintaining its preponderant position across the IndoPacific and requires strong allies in the region to help share the burden. In this regard, India could be the offshore balancer in Asia to counter Chinas emergence as a potential hegemon in the region. 2019 Taylor & Francis Group, LLC. -
Paradigm shift from AI to XAI of Society 5.0: Machine-centric to human-centric
Artificial intelligence (AI), the Internet of things (IoT), and robotics have gained significant momentum to meet expectations in many applications. Data management has become a tedious job as businesses grow. The interruption of AI in business functions and a growing web-based service economy in the last decade have led the IoT to grow faster, reducing the tedious job. Timely interruption of eXplainable artificial intelligence (XAI) reduces the technical complexities. On the one hand, the AI of Industry 4.0 promises the easiness of business functions. On the other hand, XAI of Society 5.0 tends to ease people's social life. This chapter ascertains the impact of AI on significant business functions and tries to bring out challenges AI faces and ethical values that must be considered in business functions. This chapter also tries to shed some light on the evolution of XAI of Society 5.0 and reasons for the shift from AI to XAI or machine-centric to human-centric and concludes by highlighting the future of XAI. 2024 Elsevier Inc. All rights reserved. -
Exploring Mortality Salience and Pandemic Impact in the Context of COVID-19
Mortality salience refers to a state of conscious awareness of death and the inevitable conclusion of life, associated with psychological terror. The COVID-19 pandemic generated increased awareness of illness and death, and effectuated changes in death cognitions and peoples experiences around psychological or sociocognitive domains of media and life goals. To understand these changes, this study administered the Multidimensional Mortality Awareness Measure (Levasseur et al., 2015) to 103 emerging adults in India, post which 6 participants proceeded for a semi-structured interview exploring pandemic experiences, news consumption and goal prioritization, to examine specific areas in relation to death cognition. The thematic analysis demonstrates psychological effects, and discusses developments in health and death-related psychological processes. Focus on career goals and health maintenance, cautious news consumption and disadvantageous impacts on mental health are seen, significant in navigating healthcare measures for emerging adults, as we move forward into this new normal. The Author(s) 2021. -
Managing change, growth and transformation: Case studies of organizations in an emerging economy /
Journal of Management Development, Vol.38, Issue 4, pp. 298-311, ISSN No. 0262-1711. -
Factors of reintegration of children in conflict with law
Building an ethical society involves lifelong learning and training, individually and collectively. On many occasions, crime and offence happen in the life of children. Juvenile Justice Act 2015 of India covers two categories of children: Children Need Care and Protection (CNCP) and Children in Conflict with Law (CCL). The behaviour of CCL is one of the most complex areas of behavioural science. Recidivism proves that the present reintegration is insufficient to arrest crime. This study focuses on the factors that support the reintegration of the CCL who had undergone the procedures of the Juvenile Justice Board (JJB). This is an exploratory study conducted in Kerala, India, to find the significant factors that contribute to successful reintegration, making children part of an ethical society. The methodology of the study is qualitative in nature and using data collected from boy offenders who have undergone the procedure of JJB and their parents and officials through different individual case studies. All children who participated in the survey have been rehabilitated, but reintegration seems yet to be completed. 2020 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore),. -
Phytochemical fingerprinting and evaluation of in silico anti-thrombotic properties of Justicia adhatoda L. and Cordia dichotoma Frost
The study aimed to characterize hydro-methanolic (25%) extracts of Justicia adhatoda L. (stem and flower) and Cordia dichotoma Frost. (Stem and fruit) and evaluate the in silico thrombolytic properties of the major phytocompounds present in the plants. In the preliminary fluorescence imaging through treatment by different reagents, both plants were found to be pharmacologically active. Further qualitative screening of phytochemicals, spectroscopy-based techniques, namely, UV-Vis Spectroscopy and FTIR, revealed various classes of compounds such as polyacetylenes, aglycones, quercetin, anthocyanins, anthraquinones, alkaloids, chalcones and aurones, flavanols, carotenoids, and flavanones. Further, by the application of Thin Layer Chromatography, phenols and flavonoids, namely Catechol, Kaempferol, Quercetin, and Lutein, along with other compounds like Chlorophyll b, Glutamic Acid, and Tryptophan were identified from the extracts. Finally, in the molecular docking study, three compounds, Datiscoside and Robinin of C. dichotoma and Daucosterol of J. adhatoda showed high binding energies (-10.224,-9.547 and-9.262 kcal mol-1 respectively) towards the G-protein coupled thrombotic platelet aggregation receptor P2Y1 when compared to that of the control MRS2500 (-7.148 kcal mol-1). Articles by the authors; Licensee SMTCT, Cluj-Napoca, Romania. -
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) -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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.