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A Proposal of smart hospital management using hybrid Cloud, IoT, ML, and AI
There has been a rapid shift in the medical industry from the service point of view. More importance is being given to patient care and customer satisfaction than ever before. The need to keep the customers happy with the hospital's service has increased rapidly and one way they can improve a patient's experience, even more is if they integrate cloud, IoT, ML, and AI into their system. This would help the medical sector to achieve customization which would enable them to address the needs of their customers more efficiently and offering personalized solutions. In this paper, we are proposing a novel model which focuses on a smart hospital information management system that runs by using hybrid cloud, IoT, ML, and AI. This system would be beneficial not only from the hospitals perspective but also from the patient's side as well. Patients and doctors unique ID would make the entire process a lot more efficient and easier. The advances happening in the field of AI and ML due to cloud-based computing is extremely beneficial for the medical industry. By integrating these components along with IoT it is possible for multi-specialty hospitals and super specialty hospital to be able to set up a smart hospital information management system. 2019 IEEE. -
A proposed framework for an appropriate governance system to develop smart cities in India
The Government of India has undertaken a novel step towards building new smart cities as well as transforming some of its existing cities into smart cities. However, tension relating to the governance of smart cities has emerged. Therefore, a mixed-methods approach was used based on a perception survey, case studies, and discussions with stakeholders and experts, to examine the current governance challenges in transforming existing cities into smart cities, and to explore various perspectives to propose a framework for an appropriate governance system for developing smart cities in India. The findings suggested that the current executive-led governance system, with special-purpose vehicles (SPVs) under the control of the state governments as the promoters of smart city development, might not lead to the smart governance system envisaged but, rather, add confusion and conflict, and undermine the constitutionally mandated, legislative-led urban local bodies. The argument in this article is for a people-centric, balanced governance approach with strengthened urban local bodies, enabled by advanced digital technology and the constructive participation of different social solidarities, in which the SPVs would act as the intellectual and executive wing of the urban local bodies. 2023 Regional Studies Association. -
A proposed framework for an appropriate governance system to develop smart cities in India
The Government of India has undertaken a novel step towards building new smart cities as well as transforming some of its existing cities into smart cities. However, tension relating to the governance of smart cities has emerged. Therefore, a mixed-methods approach was used based on a perception survey, case studies, and discussions with stakeholders and experts, to examine the current governance challenges in transforming existing cities into smart cities, and to explore various perspectives to propose a framework for an appropriate governance system for developing smart cities in India. The findings suggested that the current executive-led governance system, with special-purpose vehicles (SPVs) under the control of the state governments as the promoters of smart city development, might not lead to the smart governance system envisaged but, rather, add confusion and conflict, and undermine the constitutionally mandated, legislative-led urban local bodies. The argument in this article is for a people-centric, balanced governance approach with strengthened urban local bodies, enabled by advanced digital technology and the constructive participation of different social solidarities, in which the SPVs would act as the intellectual and executive wing of the urban local bodies. 2023 Regional Studies Association. -
A proposed framework for crop yield prediction using hybrid feature selection approach and optimized machine learning
Accurately predicting crop yield is essential for optimizing agricultural practices and ensuring food security. However, existing approaches often struggle to capture the complex interactions between various environmental factors and crop growth, leading to suboptimal predictions. Consequently, identifying the most important feature is vital when leveraging Support Vector Regressor (SVR) for crop yield prediction. In addition, the manual tuning of SVR hyperparameters may not always offer high accuracy. In this paper, we introduce a novel framework for predicting crop yields that address these challenges. Our framework integrates a new hybrid feature selection approach with an optimized SVR model to enhance prediction accuracy efficiently. The proposed framework comprises three phases: preprocessing, hybrid feature selection, and prediction phases. In preprocessing phase, data normalization is conducted, followed by an application of K-means clustering in conjunction with the correlation-based filter (CFS) to generate a reduced dataset. Subsequently, in the hybrid feature selection phase, a novel hybrid FMIG-RFE feature selection approach is proposed. Finally, the prediction phase introduces an improved variant of Crayfish Optimization Algorithm (COA), named ICOA, which is utilized to optimize the hyperparameters of SVR model thereby achieving superior prediction accuracy along with the novel hybrid feature selection approach. Several experiments are conducted to assess and evaluate the performance of the proposed framework. The results demonstrated the superior performance of the proposed framework over state-of-art approaches. Furthermore, experimental findings regarding the ICOA optimization algorithm affirm its efficacy in optimizing the hyperparameters of SVR model, thereby enhancing both prediction accuracy and computational efficiency, surpassing existing algorithms. The Author(s) 2024. -
A protoberberine alkaloid based ratiometric pH-responsive probe for the detection of diabetic ketoacidosis
Herein we report a ratiometric naturally occurring fluorescent pH probe, berberrubine (BBn) for the direct detection of diabetic ketoacidosis (DKA) conditions of patients having type I diabetes mellitus. The photophysical properties of the probe during pH titrations showed remarkable changes in absorption spectra where two absorption bands at 377 and 326 nm have disappeared followed by the emergence of an absorption maxima at 346 nm in highly acidic conditions. In addition, a fluorescence enhancement effect was observed in the alkaline pH, with a bathochromic shift of 33 nm. Moreover, the solution switches the color from light yellow to light pink with the change of pH from acidic to basic. A pKa value of 7.57 and a good linearity between pH 5.09.0 indicate that the probe can be used efficiently for the DKA condition, where pH variations are in the range of 67. The excellent water solubility, photostability, reversibility, and selectivity of BBn make it a potential pH sensing agent for acidic microenvironments. The reversible sensing of pH variations during DKA could be effective in primary detection and diagnosis which can assist in avoiding further complications of acidosis. 2021 Elsevier Ltd -
A Psychoanalytical Deconstruction of Surpanakha in Kavita Kane's Lanka's Princess
This paper endeavours to examine the character Surpanakha in Kavita Kane's novel Lanka's Princess. It attempts to critically follow her struggle in the androcentric space with the trapping of being a female. Breaking down her identity as a daughter, sister, wife and more specifically, as an individual, it tracks down the formulation of her own self-perception in order to reinterpret her femininity. Through the psychoanalytical lenses, this work also critically analyses her 'repression, rage and revenge' by connecting the dots in her journey that shape her personality. The giving of voice to the 'unvoiced' through revisionist myth making in the novel and the evolution of 'Surpanakha' from 'Meenakshi' due to her experiences in the oppressive and suffocating environment is the focal point of the paper. Keywords 2021 Copyright 2021 by Koninklijke Brill NV, Leiden, The Netherlands. -
A Psychological Analysis of the Structural, Socio-Cultural, And Legal Aspects of Women's Rights, their Societal Development & Superstition-Gender-Based Violence and their Eradication Alarming Practice
This comparative analysis examines the phenomenon of witch hunting as an organized crime against women in India. It explores the similarities between witch hunting and organized crime, shedding light on the structural, socio-cultural, and legal aspects of this alarming practice. The analysis delves into the systematic targeting of women, the role of patriarchal power dynamics, economic motivations, legal frameworks, and the profound impact on victims. This exploration aims to enhance understanding of the complex dynamics surrounding witch-hunting as an organized crime against women in the Indian context. Witch-hunting, a deeply rooted, superstition-based practice continues to plague several regions of India. This practice has fostered another category of gender-based violence, making women the primary victims of witch-hunts over time. The paper delves into the prevalent issue of witch-hunting, focusing on its organized nature and thus, drawing a synonymity between witch-hunts and organized crimes. The paper also aims to analyze the various factors contributing to the organization of witch-hunting and its implications on women's rights and societal development. By examining historical contexts, cultural beliefs, socio-economic factors, and legal frameworks, this research seeks to shed light on the complex nature of this crime and propose strategies for its eradication. 2023, Journal for ReAttach Therapy and Developmental Diversities. All Rights Reserved. -
A PV-Powered Single Phase Seven-Level Invertera's Photocurrent and Injected Power
The PV inverter in this study is linked to the grid and its performance analysis is evaluated using a PI controller. It is a single phase multi-level PV inverter. The major objective of this research is to increase efficiency and eliminate harmonics caused by DC link voltage fluctuations created by Maximum Power Point Tracking (MPPT) during foggy situations. PV inverters generate and inject actual power into the main grid. This study uses a transformer-less photovoltaic inverter to cut down on losses, cost, and size. A transformer-less multilayer inverter is described in this paper. There is no high-frequency leakage current since that inverter can distribute both actual and reactive electricity. MATLAB/Simulink software was used to analyze and assess the effects of various PV-based seven-level techniques on the devicea's Maximum Power Point Tracking (MPPT) performance. The Authors, published by EDP Sciences, 2024. -
A qualitative causal analysis on incremental behavioural complexities due to fomo (Fear of missing out) in indian youth
FOMO (Fear of Missing Out), a new threatening dampener of youth is prevalent across the world, and is shaping up as a wicked problem to Indian youth, especially in the category of Teens, Adolescents, including educated youth. The vulnerability is getting deeper and severe in terms of behavioural problems that turns as outcome. This qualitative paper contemplates on the human behavior with invasive nature of a newer and stronger, psychological stimulus to youth via, the digital connectivity, social media and mobile phones, called, or abbreviated as FOMO. Why FOMO has become a huge discomfort to almost all the organizations even, at times, separate teams are set to put things at control. This article qualitatively with the secondary statistics carried out across the world, and contemporary research outcome on the FOMO, tries to correlate, how the other countries are impacted, and tries to find a feasible practical moderating factors, that can wane down the impact or pull down the severity, the FOMO is causing in the life of youth. What are the strategies that can be adopted to bring down the level of damages, with suggestions for handling and managing the situation, rather than controlling, as most of the worlds work life balance is happening because of the FOM O. Also this study tries to validate the utilities of JOMO, and will it be possible in the Indian environment, since the youth are not in a position to bring d own the situation. Is NOMO too is growing up vividly across silently, is what the study concludes. 2019 ETA-Florence Renewable Energies. -
A Qualitative Enquiry of the Experience of Music Professionals during the COVID-19 Pandemic
Introduction: The COVID-19 pandemic became a new normal in todays world and has changed the consumption pattern and absorption of music and music apps in India. The music industry is relatively non-telecommutable, making working from home difficult during the imposed lockdown and social distancing norms. These conditions had adverse effects on the physical and mental health of music professionals. Therefore, it was crucial to understand the differential impact of COVID-19 on music professionals to find effective solutions and plan for future careers in a changed music industry. Method: The current paper qualitatively explored the experiences of the music professionals participating in this research during the COVID-19 pandemic in India. Twelve participants having 8 years of average professional experience (comprising singers, instrumentalists, music teachers, composers, YouTube content creators) were telephonically interviewed during the second wave of COVID-19 in India. The interviews were analysed using thematic content analysis. Results: The thematic content analysis resulted in the emergence of two major themes identified from the participants narratives were impact on participating music professionals and coping reactions. Conclusion: The themes emerged from analysis highlighted the impact of COVID-19 on these music professionals and the coping reactions utilized by them. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
A qualitative exploration of mental health experiences among IBDP students
The burgeoning concern surrounding mental health has become a prevailing issue. Considering the education sector, cut-throat competition among students has led them to experience concerns with their mental health. Although ample research exists on mental health awareness, escalating academic competition has impacted the holistic well-being of students. Research elucidates that the education sector beckons urgent attention to address the emerging mental health needs of the high school students. Thus, this study aims to probe the specific mental health requirements of students enrolled in the International Baccalaureate Diploma Program (IBDP) in Jaipur, Rajasthan. Conducted using a qualitative research paradigm, this study entailed in-depth interviews of 25 IBDP students. Subsequently, a thematic content analysis was deployed to interpret the emerging themes from the data gathered. The findings illustrated numerous themes such as mental health concerns, self-management, professional development, and other related themes discussed in the paper. This research seeks to enhance the awareness of the IBDP community regarding the mental health challenges experienced by the students. Additionally, it serves as an essential resource for educators, parents and students themselves, empowering them to acknowledge and address these challenges effectively. Furthermore, the results from this study can be utilized to develop a mental health framework tailor made to the needs of IBDP students. The Author(s) 2026. -
A Qualitative Exploration of the role of intersectionality in health disparities faced by Indian transgender persons
Transgender persons in India represent a minority and are subjected to varying levels of disparities, including those in health. These disparities for a transgender person are multi-axial and have a complex origin and manifestation that can only be assessed and explored through an intersectional lens where efforts are made to understand the collision of multiple and different identities and the role these identities play in a transgender person's life. This study aimed to explore the role of intersectionality in the health disparities as experienced by Indian transgender persons. Twelve transgender persons from rural, semi-rural, and urban residences were interviewed. The data was analysed through interpretative phenomenological inquiry. Following the same, five sub themes were emerged. 'Social and health disparities among Indian transgender persons' emerged as a group experiential theme in the analysis. The sub- themes were religion, place of residence, age, socio-economic status, and colour, which play a role in disparities of their physical as well as mental health treatment, henceforth resulting in the development of 'pervasive transphobia' in the Indian healthcare system as per the experiences lived by the participants. Following the findings of this study, we may assert that Indian transgender people perceive that they are disproportionately affected by health disparities. Henceforth, there is an urgency to unfold such disparities in health through the lens of intersectionality. 2024 Sapienza Universita Editrice. All rights reserved. -
A Qualitative Investigation of Adversities Experienced by Non-Alcoholic Adult Children of Alcoholics (ACOAs) in an Indigenous Community
This study explores the distinctive adversities encountered by non-alcoholic adult children of alcoholics (ACOAs) within the Mizo indigenous culture. Despite the abundance of literature on the adverse consequences of ACOAs, there is a dearth of global literature on the unique lived experiences of adversity among non-alcoholic ACOAs. Analysis of 13 in-depth interviews using the grounded theory approach identified that non-alcoholic ACOAs experienced a multitude of adversities across cognitive, affective, behavioral, and somatic domains. These adversities manifested as challenges in sustaining attention, lack of proficiency in problem-solving, distorted beliefs and negative emotions concerning relationships, skewed attachment styles, difficulty in managing oneself and adhering to rules, flawed relationship praxis, and somatic complaints such as fatigue, heightened psychomotor activity, and various aches and pains. These findings emphasize that parental alcohol misuse has lasting impacts on non-alcoholic ACOAs. Tailored early intervention and support programs are necessary to address these challenges. 2025, Institute for Human Rehabilitation. All rights reserved. -
A qualitative study on the reasons for online product
return in India /International Journal For Research In Engineering Application & Management, Vol.4, Issue 12, pp.152-154, ISSN No: 2454-9150. -
A Qualitative Study to Understand the Nature of Abuse Experienced by Persons with Severe Mental Illness
Persons with Severe Mental Illness (PwSMI) living in the community are considered high-risk groups for victimization. However, the nature of violence experienced by PwSMI is not well understood in India, which limits the effectiveness of clinical interventions to prevent revictimization. The Key Informant Interviews (KIIs) and Focused Group Discussion guides were developed, content validated, and pilot tested. A total of 27 KIIs and 5 focus groups were conducted with 14 PwSMIs, 19 experts, and 18 caregivers. Thematic analysis was done using Braun and Clarke's six stages of thematic analysis. The saturation of themes was determined using the Comparative Method for Themes Saturation (CoMeTS). Some of the themes and subthemes that emerged were (1) Physical Abuse (physical restraining, hitting, spitting), (2) Psychological Abuse (living in a controlling environment, criticized, neglected, scapegoated, symptomization of emotions and behavior),(3) Sexual Abuse (sexual assault, reproductive coercion, sexual exploitation), (4) Social Abuse (teased or labeled, social deprivation, abandonment, discrimination, and exclusion), and (5) Trauma in formal care (Coercive treatment practices, seclusion, negative attitude of staff, surreptitious prescribing of medicines, patronizing behavior). Abuse experienced by PwSMI has significant treatment and health care costs and an increased burden on families and society, so comprehensive psychosocial care and support are needed to prevent revictimization. Copyright 2023, Mary Ann Liebert, Inc., publishers 2023. -
A Quality of Service Study for Downlink Scheduling Algorithms in Mobile Networks
Internet usage and the number of applications/users growth is going in an unprecedented manner. In these days, lot of users are changed themselves to use internet-based applications rather than traditional voice service. The fundamental of voice-based communication is shifted to packet data access for satisfying the human needs through internet based mobile applications. 4G network is an IP supported rising technology for the past decade and at present also because of un availability service of 5G in all the places. Still, 4G is ruling the globe and the number of subscribers kept growing only. In these days, this remains on the list of latest research topics. Under 4G technology lot of research problems are exist like QoS, Uplink and Downlink Scheduling, Security, Mobility etc., Inspite of discussing that several issues, this paper mainly focusing the QoS in Downlink scheduling algorithms. Also, it presents the issues of various existing QoS downlink scheduling algorithms, names, QoS aware/unaware, parameters used/simulated, drawbacks of those algorithms and result verifications etc. Packet scheduling plays a crucial role for providing Quality of Service (QoS) to the mobile users. Ultimately, it gives some suggestions to explore more further about QoS based research work in Mobile Networks. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
A Quantitative Analysis of Trading Strategy Performance Over Ten Years
This study conducts a comparative analysis of two trading strategies over a ten-year period to assess their profitability and risk. Strategy 1 operates on a simple buy at close and sell at open principle, while Strategy 2 trades only when the closing price is above the 200-day moving average, introducing a conditional filter for market entry. Through the evaluation of performance metrics including total PNL, drawdown, standard deviation, and Sharpe ratio, the research highlights the differences in risk and return between the strategies. Results indicate Strategy 1 achieves higher profitability but at the cost of greater risk, as shown by larger drawdowns. Conversely, Strategy 2's conditional approach yields slightly lower returns but demonstrates a superior risk-adjusted performance. The findings emphasize the significance of risk management and the potential benefits of conditional filters in trading strategies, offering valuable insights for traders and investors in making informed strategy selections. 2024 IEEE. -
A Quantum-Enhanced Artificial Neural Network Model for Efficient Medical Image Compression
The ability to effectively store and transmit high-resolution images such as MRI and CT scans without losing quality is critical to modernizing medical imaging. Traditional compression methods risk losing essential medical image data, which requires perfect detail for diagnosis. Quantum algorithms use superposition and entanglement to compress faster while preserving important information. This research presents a Quantum-enhanced Artificial Neural Network (QANN) model that combines quantum feature extraction with classical neural network topologies to improve image compression. Our approach consists of converting standardized classical data into quantum states, controlling these states using parameterized quantum circuits, and measuring the resulting states to produce enhanced feature vectors. The quantum-enhanced features are fed into a traditional neural network for image compression. The experimental results clearly show that our QANN framework outperforms standard models in terms of accurate reconstructed images, reduced size, and increased space-saving percentage, especially when dealing with large and complicated datasets. The QANN model demonstrates how quantum computing can significantly enhance the effectiveness of medical image processing solutions. Kaggle brain CT and MRI datasets and COVID-CXNet chest x-ray images are used. The proposed QANN model improves peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Using quantum technology, the image size is reduced for MRI (73.3 %), X-ray (74.1%), and CT-SCAN (71.8%) to save space. 2025 IEEE. -
A Quantum-Inspired Self-Supervised Network model for automatic segmentation of brain MR images
The classical self-supervised neural network architectures suffer from slow convergence problem and incorporation of quantum computing in classical self-supervised networks is a potential solution towards it. In this article, a fully self-supervised novel quantum-inspired neural network model referred to as Quantum-Inspired Self-Supervised Network (QIS-Net) is proposed and tailored for fully automatic segmentation of brain MR images to obviate the challenges faced by deeply supervised Convolutional Neural Network (CNN) architectures. The proposed QIS-Net architecture is composed of three layers of quantum neuron (input, intermediate and output) expressed as qbits. The intermediate and output layers of the QIS-Net architecture are inter-linked through bi-directional propagation of quantum states, wherein the image pixel intensities (quantum bits) are self-organized in between these two layers without any external supervision or training. Quantum observation allows to obtain the true output once the superimposed quantum states interact with the external environment. The proposed self-supervised quantum-inspired network model has been tailored for and tested on Dynamic Susceptibility Contrast (DSC) brain MR images from Nature data sets for detecting complete tumor and reported promising accuracy and reasonable dice similarity scores in comparison with the unsupervised Fuzzy C-Means clustering, self-trained QIBDS Net, Opti-QIBDS Net, deeply supervised U-Net and Fully Convolutional Neural Networks (FCNNs). 2020 Elsevier B.V. -
A Quasi-Experimental Study on the Effectiveness of Integrated Electroencephalogram Neurofeedback Training and Group Psychotherapy for Harmful Alcohol Use: Neurocognitive and Clinical Outcomes
Introduction. This study investigates the efficacy of integrating electroencephalogram (EEG) neurofeedback training and group psychotherapy for individuals with harmful alcohol use (AUDIT-10 scores 1013). Methods. Seventy-six participants were purposively sampled and divided into treatment (EEG neurofeedback training and group psychotherapy) and control groups. Baseline assessments measured alcohol consumption (AUDIT-10), stress (perceived stress scale [PSS]), neurocognition (NIMHANS neuropsychological battery), craving (PACS), and visual analog scale. The treatment group underwent 20 sessions of EEG neurofeedback (Peniston-Kulkosky and Scott-Kaiser modification protocols) and four sessions of group psychotherapy (motivational interviewing [MI], psychoeducation). Result/Discussion. A repeated measures ANOVA showed significant improvement in postcondition scores for the treatment group compared to controls, who exhibited deterioration over time. The study provides evidence supporting the efficacy of integrated EEG neurofeedback training and group psychotherapy in mitigating harmful alcohol use progression. Conclusion. By addressing stress, cognition, and cravings, this intervention offers crucial support to individuals with problematic drinking. 2024. Panicker et al.