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Poverty, globalization, and human security: A policy perspective
Poverty has been an ongoing insecurity to humanity. But it was mostly understood in relation to basic needs, income, and wealth. Bretton Woods Institutions and the World Trade Organization propagated globalization and its interconnectedness as capable mechanisms for poverty eradication. Although globalization takes the credit for alleviating poverty, many authors argue that it was the outcome of the successful welfare policies of China and India. Globalization is criticized for prioritizing the developed world's interests and its multinational and transnational corporations and equating development only with an increase in gross domestic product. However, together with interconnectedness, human insecurities like poverty and inequality also increased. The latest World Bank (2024) and World Inequality Lab (2022) data affirm this precarious situation. This chapter thus examines the feasibility of the United Nations Development Program's human security approach for a successful (national and international) poverty eradication program through its people- centered perspective. 2025, IGI Global Scientific Publishing. All rights reserved. -
Power and Area Efficient Decimation Filter Architectures of Wireless Receivers
This paper reports on the synthesis and implementation of a digital decimation filter suitable for multi-standard transceivers. Decimation filter architectures used in transceivers must be capable of providing low power and less area. In this paper, three different architecture designs namely Decimation Filter with Conventional MAC Unit, Cascaded Multi-Standard decimation Chain and Hybrid structure are proposed to meet the demand of low power and area efficient digital decimation filter. The filter architectures are implemented using FPGA and its performances are tested. The architectures are tested using conventional number system and with two different encoding schemes of filter coefficients called canonic signed digit and minimum signed digit. The implementation results reflect that considerable reduction in area of 47.9% and power reduction of 28.6% are achieved using hybrid architecture, when compared with conventional MAC and cascaded chain architectures. 2016, The National Academy of Sciences, India. -
Power Consumption Forecasting with AI and IOT
Electricity plays a fundamental and indispensable role in modern society, driving progress, development, and the overall quality of life. Electricity is profoundly ingrained in daily life. It powers homes, providing lighting, heating, cooling, and appliances that support, comfort, and convenience. From cooking meals to powering electronic devices and entertainment systems, electricity is vital for modern living, enhancing our quality of life and enabling various activities. Power forecasting is critical to the effective management and optimization of power generation, consumption, and distribution. Power consumption forecasting has evolved significantly with the introduction of advanced technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT). AI techniques, such as machine learning and deep learning, make use of the massive amounts of data produced by IoT devices like smart meters and energy monitoring devices. These devices continuously gather real-time data on power consumption, weather conditions, grid performance, and other relevant factors. AI algorithms can find patterns and correlations and provide accurate forecasts and important insights for power forecasting by processing and analyzing data. Machine learning algorithms, such as regression models, neural networks, and ensemble approaches, are trained using historical power consumption data and the features that have been chosen. The models discover the underlying patterns and correlations between input features and power consumption. These forecasts can be used for short-term load balancing, energy procurement planning, demand response management, and optimizing energy distribution. AI and IoT power usage projections give valuable data for decision-making and energy optimization techniques. These projections can be used by energy suppliers, grid operators, building managers, and consumers to plan energy usage, distribute resources efficiently, optimize demand response programs, and discover possibilities for energy saving. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Power Efficient e-Bike with Terrain Adaptive Intelligence
Electric bicycles or e-bikes are gaining momentum in the market as they are offering a smooth, noiseless and pollution free option for individual transportation in cities as well as in countryside. E-bikes are usually with a battery powered electric motor drive with an additional option for pedaling. In this work a low cost e-bike was designed and developed with a brushless DC hub motor with controllers. For smart control, smartphone was used a console and the e-bike can be controlled using a mobile application which was connected to the e-bike through Bluetooth. The controller will pick the gradient of the terrain and will control the power of the motor, which results in energy saving. Predicted range of the e-bike, speed, acceleration and total distance covered were displayed in the console along with the geographical position on the map and throttle control options. The bike with the proposed control tested and the results were giving a reduction in current drawn from the battery. 2019 IEEE. -
Power law coefficient effects on buoyant heat transfer in porous trapezoidal enclosures
The investigation of steady, incompressible, laminar mixed convective fluid flow within two different types of trapezoidal enclosures filled with saturated water and study explores how the power-law index governs buoyancy-driven heat transfer in a porous trapezoidal cavity filled with non-Newtonian fluids. Unlike Newtonian fluids, non-Newtonian fluids exhibit flow behavior that directly depends on the power-law index, which characterizes their shear-dependent viscosity. We formulate the governing equations in terms of the stream function and temperature and solve them using a validated, in-house MATLAB solver. Embedding a porous matrix within a trapezoidal enclosure creates intricate interactions between convective currents and conductive resistance. By performing numerical simulations across a range of Rayleigh numbers (Ra = 102 to 2 103) and boundary conditions, we systematically assess how variations in the power-law index alter local velocity fields, temperature distributions and overall heat-transfer rates. Our results reveal that increasing the power-law index strengthens convective flow and raises the average Nusselt number, whereas decreasing the index shifts the balance toward diffusion-dominated transport. These findings offer practical guidance for enhancing thermal management in industrial systems that employ both Newtonian and non-Newtonian fluids within porous structures. The study presents new empirical correlations linking Nu, Ra and power law co-efficients offering a practical tool for engineering design. Unlike previous works that focused primarily on Newtonian fluids or simplified geometries, this work provides a detailed analysis of non-Newtonian effects in realistic porous enclosures. These results contribute to a deeper understanding of convective mechanisms in complex therm-ofluid systems and offer guidance for optimizing thermal performance in engineering applications. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026. -
Power law in tails of bourse volatility evidence from India
Inverse cubic law has been an established Econophysics law. However, it has been only carried out on the distribution tails of the log returns of different asset classes (stocks, commodities, etc.). Financial Reynolds number, an Econophysics proxy for bourse volatility has been tested here with Hill estimator to find similar outcome. The Tail exponent or ? ? 3, is found to be well outside the Levy regime (0 < ? < 2). This confirms that asymptotic decay pattern for the cumulative distribution in fat tails following inverse cubic law. Hence, volatility like stock returns also follow inverse cubic law, thus stay way outside the Levy regime. This piece of work finds the volatility proxy (econophysical) to be following asymptotic decay with tail exponent or ? ? 3, or, in simple terms, inverse cubic law. Risk (volatility proxy) and return (log returns) being two inseparable components of quantitative finance have been found to follow the similar law as well. Hence, inverse cubic law truly becomes universal in quantitative finance. Bikramaditya Ghosh, M. C. Krishna, 2019. -
Power Line Communication Parameters in Smart Grid for Different Power Transmission Lines
In an electrical power system smart grid is a network that renewable energy sources along with smart devices. Communication capabilities of the conventional grid can be improved by the inclusion of superior sensing and computing abilities. Device control, remote management, information collection, intelligent power management is achievable by using communication networks. Wired communication technology is used because of its advantages like reliable connection, free from interference, and faster speed. In this paper, the data communication parameters have been analyzed using Power Line Communication (PLC) with various lengths of transmission lines. An orthogonal Frequency Modulation scheme is used to obtain the minimum BER.MATLAB Programming has been carried out and the results have been compared with the standards and found to be satisfactory. 2021 IEEE. -
Power quality disturbance mitigation in grid connected photovoltaic distributed generation with plug-in hybrid electric vehicle
In the last twenty years, electric vehicles have gained significant popularity in domestic transportation. The introduction of fast charging technology forecasts increased the use of plug-in hybrid electric vehicle and electric vehicles (PHEVs). Reduced total harmonic distortion (THD) is essential for a distributed power generation system during the electric vehicle (EV) power penetration. This paper develops a combined controller for synchronizing photovoltaic (PV) to the grid and bidirectional power transfer between EVs and the grid. With grid synchronization of PV power generation, this paper uses two control loops. One controls EV battery charging and the other mitigates power quality disturbances. On the grid connected converter, a multicarrier space vector pulse width modulation approach (12-switch, three-phase inverter) is used to mitigate power quality disturbances. A Simulink model for the PV-EV-grid setup has been developed, for evaluating voltage and current THD percentages under linear and non-linear and PHEV load conditions and finding that the THD values are well within the IEEE 519 standards. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Power quality enhancement of renewable energy systems using a hybrid orangutan optimization algorithm and continuous spiking graph neural network with series active power filter
Interconnected renewable energy systems (RES) often experience power quality (PQ) issues, such as harmonics and voltage disturbances. Nevertheless, conventional Series Active Power Filter (SAPF) control schemes have disadvantages, such as slow adaptation and reduced accuracy in a fluctuating renewable environment. To overcome these limitations, this work proposes a hybrid adaptive SAPF-based PQ optimization technique. The proposed method combines the Orangutan Optimization Algorithm (OOA) and Continuous Spiking Graph Neural Network (CSGNN), referred to as the OOA-CSGNN method. Reduction of total harmonic distortion (THD), increase of PQ, and stabilize of voltage profiles in interconnected RES are the goals of the proposed technique. The OOA offers the best SAPF control parameters to maximize convergence and dynamic tracking, and the CSGNN is effective to predict the compensation signals using graph-based spiking computations. The suggested technique is implemented in MATLAB and evaluated against existing approaches, such as the Gorilla Troops Algorithm (GTA), Genetic Algorithm (GA), Adaptive Bald Eagle Optimization Algorithm (ABE-OA), Artificial Neural Network (ANN), and Convolutional Neural Network (CNN). The proposed OOA-CSGNN approach achieves a load voltage THD of 0.11% under steady-state operating conditions after SAPF compensation, while maintaining voltage THD well within IEEE-519 limits during transient disturbances such as voltage sag, swell, and dip. These results demonstrate the efficiency and robustness of the proposed hybrid architecture for PQ optimization in renewable-integrated systems. 2026 Elsevier Ltd -
Power quality improvement strategy for non-linear load in single phase system
Widespread use of non-linear loads in today's world scenario, increased the harmonic current injection into the grid. The harmonic current play a vital role in deteriorating the power quality of the grid. The non-linear loads may be either, single phase or a Three phase loads. In this paper, a control strategy for single phase shunt active filter is discussed, in mitigating the harmonics flowing into the grid. The extraction of reference signal of shunt active filter is designed, using instantaneous reactive power theory. Here load is considered as diode rectifier which is feeding a resistive inductive load. A complete control strategy and analysis is done in MATLAB/Simulink environment. 2016 IEEE. -
Powering Ahead: Navigating Opportunities and Challenges in the Electric Vehicle Revolution
The technology is clearing ways for buzz in the market brimming with innovative items and new prospects. The government has planned to shift to electric vehicles by 2030, whether it is for personal or commercial use. As innovative improvements are developing quickly, it is blasting the market with the EVs industry which expected to transform the future (Rajkumar S, in Indian electric vehicle conundrum: a tale of opportunities amid uncertainties, 2020). Volvo company has also announced that it will be fully electric by 2030 (https://gadgets.ndtv.com, in Volvo to go all electric by 2030, sell exclusively online, 2021). It is expected that EVs will generate more demand for electricity and help in settling the focus on resources problem. It will also help in improving the financial feasibility of power sector projects. In India, there is more dependency on renewable energy so this is a chance to be independent and provide cheap power to the people. The EVs are more economical than petrol or diesel vehicles. The government is also giving incentives to the makers of electric vehicles. GST on electric vehicles is 12% as compared to petrol and diesel vehicles with 28% GST. As per the Electricity Act, 2003, a distribution license is needed to supply power from respective state electricity regulatory commissions. Another challenge is that charging the EVs will lead to a rise in the demand of electricity which is risky for the electricity distribution companies (www.livemint.com, in Indias electric vehicle drive: challenges and opportunities, 2017). Indians are very price conscious. A recent study revealed that Indians are ready to compromise on more charging time, but they are not ready to pay higher price for EVs (Gupta NS, in Electric vehicle adoption in India: study reveals three tipping points, 2020). From Fig.1, it can be seen that in 2014 investment in EVs was $2.2 billion which has increased to $406 billion in 2019 (Shanti S, in The road to green: what makes electric vehicle adoption a challenge for India. 2020). This shows that people are shifting toward EVs. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Powering the Future: The Role of Solar Energy in Indian Energy Transition
Energy has become one of the basic human needs, and the expanding population demands more energy for day-to-day needs. As the demand for energy increases, the easy solution for everyone to rely on is the employment of fuel-powered generation systems, which adversely affect the ecology and the environment. In order to address the energy needs of the time without harming the environment, we need considerable investments in the renewable energy sector. Government alone cannot perform this task. A collective effort from government, public, and private investors is required here. Energy conferences like Conferences of Parties (COP) focus on the transition of energy from non-renewable sources to renewable sources and on bringing down the loss of energy during transmission and distribution. This paper current Indian energy sector scenario, suggests solar energy as a solution to Indias energy crisis and discusses the reason behind the lack of motivation for people to invest in solar energy. Addressing these factors can attract more investors to the investment. The research in battery technology and solar panels can help the Indian energy sector focus on energy harvesting and the development of energy-independent systems which will solve the energy crisis to an extent. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Powerlessness in the moral self: a social cognitive perspective on drug users
Powerlessness resides in devalued self-images of drug users. This study, drawing on social and moral psychology, examined the moral functioning of drug users compared to non-drug users. Self-reported data concerning moral identity and moral judgment on drug use were assessed and compared between groups. Drug users appeared to have significantly weaker moral identity centrality and pro-drug moral judgment than non-drug users. They also showed dissociation in the relationship between moral identity and moral judgment. As a result, the study proposed a moral identity model of drug use to better approach social cognitive powerlessness in drug users moral self. 2021 Taylor & Francis Group, LLC. -
Prabhakar Anandrao Bhagwatwar (1934)
This chapter explores the initiatives undertaken by P.A. Bhagwatwar, a notable academic figure at the University of Mumbai, particularly in enhancing the practical application of psychology within the curriculum. It details the inception and development of a counselling centre, which began in 1988 and was officially established in 1995, under Bhagwatwars guidance. The centre provided comprehensive psychological services targeting a diverse range of demographics, from adults to the elderly, addressing issues such as family therapy and vocational guidance. Additionally, he is credited with authoring several influential books on psychology, including titles on general and organizational behaviour, as well as developing key assessment tools, such as aptitude tests and efficiency questionnaires, contributing significantly to the field of applied psychology. 2025 selection and editorial matter, Braj Bhushan; individual chapters, the contributors. -
Practical applications of self-service technologies across industries
Self-service technologies (SSTs) have practical applications across various industries, improving operational efficiency and customer satisfaction. In retail, self-checkout kiosks and mobile payment apps streamline the purchasing process, reducing waiting times and enhancing convenience. The hospitality industry utilizes SSTs through self-service check-in kiosks and digital concierge services. In healthcare, patients can use self-service portals to schedule appointments, access medical records, and complete pre-visit forms. In banking and finance, ATMs, mobile apps, and AI-powered chatbots offer access to essential services without the need for in-person assistance. These practical implementations demonstrate the versatility and importance of SSTs in modernizing service delivery across sectors. Practical Applications of Self-Service Technologies Across Industries explores self-service technology (SST) as a transformative force across industries. It examines practical applications of SST for improved customer service and business operations. This book covers topics such as smart technology, consumer behavior, and blockchain, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Practical Benefits of Using AI for More Accurate Forecasting in Mental Health Care
Artificial Intelligence (AI) is the general term for being able to make computers do things that require human-like intelligence. AI is the novel idea of the computer pioneers like Alan Turning and John von Neumann in the 1940s. Their novel intuition towards making machines think is the key start for this AI technology evolution. As shown in Fig. 1, the first milestone of AI happened in the year 1956 when it was proved by a group of researchers that a machine could solve any problem with the use of an unlimited amount of memory. Here they named this program General Problem Solver (GPS). 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Pratixa: A Cognitive Framework for Behavioral Decision-Making and Its Mathematical Formalization
The present study introduces pratixa, an internal cognitive structure that functions as a reference architecture guiding human decision-making. Pratixa is a dynamic, event-sensitive archive of anticipated outcomes of behavior, learned event-behavior-outcome associations, and adaptive behavioral responses, drawing on the theories from decision science, psychology, and behavioral adaptation. Past experiences shape pratixa, and iterative learning reinforces it. It supports predictive mental representations by enabling individuals to anticipate the outcomes of their own behavioral responses and adjust those responses when discrepancies arise between anticipated and actual outcomes. Pratixa supports anticipatory learning and real-time correction, making it a future-oriented cognitive structure for decision making. It matures in a spiral progression, from null pratixa, where no prior event-behavior-outcome associations exist, through quixotic pratixa, characterized by illusory or arbitrary associations, to realistic pratixa, where causal relationships are adequately approximated. This spiral maturation reflects how individuals adapt through experiential learning and reinforcement, transitioning from effortful reasoning to increasingly automatic and context-sensitive decision-making. By positioning decision-making within this evolving structure, pratixa offers a distinct perspective on predictive cognition in complex and ambiguous contexts, with implications for strategic foresight, behavioral economics, and adaptive behavioral decision making. The study also proposes a mathematical formulation to represent how this reference architecture evolves through reinforcement-based learning and guides decision-making, providing a computational basis for modeling human foresight and adaptation. 2025 John Wiley & Sons Ltd. -
Pre and Post Operative Brain Tumor Segmentation and Classification for Prolonged Survival
The aim of this research was to provide a detailed overview of the techniques in detecting and segmenting meningioma brain tumor in pre- and post-operative MRI images and classify for presence of meningioma thereby giving an early diagnosis to decrease the death rate. This study examines trending techniques for brain tumour segmentation and classification in Magnetic Resonance (MR) images of pre and post-surgery. For the segmentation and anomalies in the brain categorization, several approaches such as regular machine learning techniques (K-mean bunching, Fuzzy C mean grouping etc.), Deep Learning-based approaches (CNN, ResNET, Dense Net, VGG etc.), classical algorithms (Snake contour, watershed method etc.), and hybridization approaches were applied, according to the analysis. Information base, for example, BRATS, Fig-Share, EPISURG or TCIA can be taken to gather clinical pictures which principally contains of 2 classifications, pre and post pictures of Brain tumor. The multiple processes of brain tumour segmentation methodologies, such as preprocessing, feature extraction, segmentation, and classification, are also explained in this work. The task of segmenting residual and recurrent tumors differs greatly from that of segmenting tumors on baseline scans before surgery. This study shows that each approach has its own set of pros and limitations, as well as notable findings in terms of precision, sensitivity, and specificity, according to the comparison research. The use of segmentation approaches to determine success and reliability has been discovered. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Pre Packaged Insolvency - Exploring An Alternative Framework For Bankruptcy Resolution In India
This article is a review of literatures on the need for alternative bankruptcy resolution framework in India. The study explores the context & background to the recent initiation of limited Pre-Packaged Insolvency in India. The article makes a strong case for having a private & pre-negotiated mode of debt resolution along with the existing CIRP framework in India. The article provides a comparative perspective of CIRP and Pre-pack driven resolution model in India. The research paper also addresses some of the potential challenges & concerns related to initiation of pre-pack in India & accordingly discusses the relevant safeguards for the same. Lastly, the study also provide a brief view of pre-pack model currently practised in USA. The Electrochemical Society