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Global Applications of Indian Psychology: Therapeutic and Strategic Models
Global Applications of Indian Psychology: Therapeutic and Strategic Models addresses a pressing problem in the field of psychology: the need for a fresh perspective that can effectively tackle the complex challenges of our modern world. While traditional Western psychology has its merits, it often fails to consider crucial aspects of human experience and well-being, limiting our understanding and hindering our ability to meet diverse global needs. This book offers a solution by presenting an interdisciplinary exploration of Indian psychology and its practical applications. Edited by Anuradha Sathiyaseelan and Sathiyaseelan Balasundaram, this comprehensive guide caters to academic scholars seeking a unique approach to understanding human psychology. It delves into the historical roots and philosophical foundations of Indian psychology, providing readers with a profound understanding of its principles and theories. The book highlights the multidisciplinary applications of Indian psychology, ranging from management and health to clinical practices, highlighting the significance of ancient Indian texts, ayurveda, yoga, and mindfulness meditation. By facilitating cross-cultural dialogue and collaboration, Global Applications of Indian Psychology: Therapeutic and Strategic Models bridges the gap between Indian and Western psychology, offering researchers and practitioners insights from both traditions. This fosters a more comprehensive understanding of human psychology and equips individuals with effective strategies to enhance well-being and flourishing worldwide. This invaluable resource fills a crucial gap in the field, offering a unique perspective and practical insights for teaching professionals, students, healthcare professionals, policymakers, researchers, and scholars in their quest for understanding and improving human psychology. 2024 by IGI Global. All rights reserved. -
Global and Indian Perspectives on Russia-Ukraine War using Sentiment Analysis
In today's world, social media has become a platform through which people express their opinions and thoughts regarding various topics. Twitter is one such platform wherein people resort to expressing their opinions or portraying sentiments to the world. Today it has become easier to analyze mass opinion by using sentiment analysis. This paper investigates the ongoing Russia-Ukraine war by analyzing opinionated tweets, and it seeks to understand the sentiments from a global and Indian perspective. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. Multinomial Naive Bayes classifier classified the tweets into positive, neutral, and negative categories. The paper employed NRCLex for emotion classification and aspect-based sentiment analysis to divide opinions into aspects and determine the sentiment associated with each element. For the study, 4,31,857 tweets were extracted, and the results of sentiment analysis depict that 44.09% users had negative sentiments followed by 33.378% users expressing positive sentiment and remaining 22.53% people were neutral in their tweets. Fear, anger and sadness were amongst the top emotions expressed in the negative tweets whereas the positive tweets expressed trust and anticipation that the war would end soon. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. An analysis was performed on 1542 tweets that were obtained for Operation Ganga. 74.5% of the users had positive sentiments about Operation Ganga, whereas 16.67% and 8.5% had negative and neutral sentiments respectively. The people trusted this evacuation process resulting in more positive sentiments. Fear of losing near and dear ones and fear of safety was the topmost concern for Indians and leadership was one of the topmost aspects tweeted in the positive sentiments. Thus, the overall results depict that the common man does not prefer war and is fearful of the outcomes. The government should hear the voice of the common man and plan strategies and decisions considering the common man's sentiments. 2022 ACM. -
Global Analysis of Quantum Technology Discourse
he study provides a thorough exploration of the global quantum technology landscape, offering valuable insights for researchers, policymakers, and industry stakeholders. It employs advanced analytical methods such as Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF) for topic modeling. The research focuses on understanding discussion intensity, geographical distribution, co-mentioning patterns among countries, prevalent topics, and keyword-based trends. Utilizing diverse datasets, the study employs heatmaps, network analysis, and thematic analysis to categorize textual data. Evaluation metrics like Topic Coherence and Network Centrality Measures contribute to a robust methodology.Key findings include dominant discussions on quantum computing and investment strategies, with focused attention on governmental roles in R&D and specific quantum computer research. Notably, there is a niche focus on quantum algorithmic risks in Australia. Document characteristics vary, with some blending multiple themes and others centered around a single topic. LDA topic modeling and network analysis identify key countries, showcasing global hotspots and potential collaborations in quantum technology discussions. 2024 IEEE. -
Glancing angle sputter deposited tungsten trioxide (WO3) thin films for electrochromic applications
The columnar growth angle-dependent tungsten oxide (WO3) thin films were grown by using the Glancing angle sputter deposition (GLAD) technique with varying different substrate angles (00, 700, 750, and 800) on Fluorine-doped tin oxide (FTO) and Corning glass (CG) corning glass substrates at room temperature. The surface morphology, crystallographic structure, optical, and electrochemical properties were determined using X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), UltravioletVisible(UVVis) spectrometer, and electrochemical analyzer, respectively. The structural properties reveal that the films are amorphous in nature. FE-SEM studies observed the columnar growth of the nano-rods and surface porosity. The optical transmittance of the deposited films was decreased from 83 to 78%, and the optical bandgap decreased from 3.08 to 2.88eV with increasing GLAD angle. The electrochemical studies reveal that the GLAD angle influenced the coloration efficiency (CE). The highest CE of 32cm2/C at 600nm and highest Diffusion coefficient (DC) of 6.529 109 cm2s?1 of the films was observed for the films deposited at an angle of 750. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature. -
GLANCEGuided Language Through Autoregression Establishing Natural and Classifier-Free Editing
In this study, researchers aimed to simplify text conversion into images using the latest text-to-image generation methods. While these methods have improved the quality and relevance of generated images, certain crucial questions remained unanswered, limiting their practicality and overall quality. To address these issues, the researchers introduced a novel text-to-image method. This method allows for better control of the scene depicted in the image through text, enhances the tokenization process by incorporating specific knowledge about key image regions such as faces and important objects, and provides guidance to the transformer model without needing a classifier. The outcome of this work was a model that achieved state-of-the-art results in terms of image quality and human evaluation, enabling the generation of high-fidelity 512?512-pixel images. Moreover, this method introduced new capabilities, including scene editing, text editing with reference scenes, handling out-of-distribution text prompts, and generating story illustrations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Getting Rid of Organizational Complacency in a Dynamic Environment
This case investigates the external consultants organizational diagnosis aimed at understanding the imperative for change within Infotics Solutions. It explores various concepts, including the nature of planned change and the resistance exhibited by employees. Emphasis is placed on the necessity of a comprehensive organizational diagnosis before embarking on the change process, highlighting the pitfalls of relying solely on a leaders intuition and experience to initiate change. Furthermore, the case underlines the implementation of human resource management interventions and their significance from both employee and organizational standpoints. It addresses the protagonists recognition of the need for external consultants expertise to grasp the problem and devise a strategic change process. The consultants methodical approach to planning change across different themes to achieve organizational objectives is elucidated, featuring the importance of employing the right diagnosis technique in situations where the problem is unclear. The case also showcases the consultants analytical approach to problem-solving, offering specific solutions tailored to the organizations needs. Ultimately, it illustrates the challenges faced by organizations that lean heavily on past successes and struggle to adapt to evolving environmental demands. Lastly, the case highlights the importance of analysing survey results and implementing theme-based interventions to address the issues confronting the organization and its employees at Infotics Solutions. 2024 Lahore University of Management Sciences. -
Getting Back to Work: Cognitive-Communicative Predictors for Work Re-entry Following Traumatic Brain Injury
Return to work following a Traumatic Brain Injury (TBI) is affected by deficits across the cognitive, psycho-social and physical domains. The specific role of cognitive -communicative abilities influencing work re-entry is understudied. This study aimed at identifying the cognitive-communicative predictors for work re-entry following TBI. Thirty patients with TBI employed pre morbidly were categorized into two groups- 14 employed and 16 unemployed post TBI. Those having sustained mild, moderate or severe head injury and in the post injury period of 648months were recruited and majority belonged to skilled/ professional type of premorbid occupational status. They underwent a detailed assessment of cognition, language and communication using NIMHANS Neuropsychology Battery, Indian adapted versions of Western Aphasia Battery and La Trobe Communication Questionnaire (LCQ) respectively. Patients employed post TBI had better Aphasia Quotient (AQ) and better performance on all the cognitive domains and few domains of LCQ than those who remained unemployed. On step-wise Discriminant Function Analysis (DFA), injury severity and AQ could significantly differentiate between the two groups with an overall accuracy of 80%. Severity of head injury is a significant predictor for employability post TBI and evaluation of language along with cognitive abilities is crucial for patients with TBI for work re-entry. The study highlights the importance of a multi-disciplinary team in the assessment and management of cognitive-communication impairments following a TBI. 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Gesture based Real-Time Sign Language Recognition System
Real-Time Sign Language Recognition (RTSLG) can help people express clearer thoughts, speak in shorter sentences, and be more expressive to use declarative language. Hand gestures provide a wealth of information that persons with disabilities can use to communicate in a fundamental way and to complement communication for others. Since the hand gesture information is based on movement sequences, accurately detecting hand gestures in real-time is difficult. Hearing-impaired persons have difficulty interacting with others, resulting in a communication gap. The only way for them to communicate their ideas and feelings is to use hand signals, which are not understood by many people. As a result, in recent days, the hand gesture detection system has gained prominence. In this paper, the proposed design is of a deep learning model using Python, TensorFlow, OpenCV and Histogram Equalization that can be accessed from the web browser. The proposed RTSLG system uses image detection, computer vision, and neural network methodologies i.e. Convolution Neural Network to recognise the characteristics of the hand in video filmed by a web camera. To enhance the details of the images, an image processing technique called Histogram Equalization is performed. The accuracy obtained by the proposed system is 87.8%. Once the gesture is recognized and text output is displayed, the proposed RTSLG system makes use of gTTS (Google Text-to-Speech) library in order to convert the displayed text to audio for assisting the communication of speech and hearing-impaired person. 2022 IEEE. -
Geraniol and Citral as potential therapeutic agents targeting the HSP90 activity: An in silico and experimental approach
Lemongrass essential oil has antifungal and anti-cancerous properties. Heat-shock protein (HSP90), an ATP-dependent molecular chaperone found in eukaryotes, is involved in protein folding, stability, and disease, making it a promising research topic. Both in silico and in vitro approaches were used to provide a clear insight into the HSP90-ATPase 3D structures, activity, and their interaction with the essential oil constituents among various species such as fungi (S. cerevisiae), parasites (P. falciparum), and humans. For in silico studies, sequence alignment, docking (AutoDock), and absorption, distribution, metabolism, and excretion (ADME) properties were evaluated to obtain hit compounds specifically against each HSP90-ATPase. The hit compounds obtained were evaluated for their efficacy in the in vitro studies of S. cerevisiae. In vitro studies were carried out targeting HSP90-ATPases via lemongrass essential oil components individually and in combination as a function of concentration and various salt concentrations. Results suggest that sequence alignment exists of over 75% among these three species. The best docking score was possessed by Geraniol and its constituent (geldanamycin ? ?4.93 kcal/mol) (a known antifungal and antitumor against HSP90) in all the above species. Lemongrass oil and the combination of Geraniol and Citral at concentrations of 80 ?g/mL showed the maximum inhibition of ATPase and HSP90-ATPase activity compared to their individual treatment. Therefore, both in silico and in vitro studies provide clear evidence of specific inhibitory action of lemongrass oil, Geraniol, and Citral against the ATPase and HSP90ATPase activities and might show potential as antifungal and antitumor drugs. 2021 -
Geospatial crime analysis to determine crime density using kernel density estimation for the indian context
Crime is the most common social problem faced in a developing country. Crime affects the reputation of a nation and the quality of life of its citizens. Crime also affects the economy of the country, increasing the financial burden of the government due to the need for expenditure in the police force and judicial system. Various initiatives are taken by law enforcement to reduce the crime rate. One such initiative, real-time accurate crime predictions can help reduce the occurrence of crime. In this paper, a crime analytics platform is developed, which processes newsfeed data analysis for different types of crimes and identify crime hotspots using Kernel Density Estimation method. This system enables criminologists to understand the hidden relationships between crime and geographical locations. Interactive visualization features are available that enable law enforcement agencies to predict crime. 2020 American Scientific Publishers. -
Geospatial crime analysis and forecasting with machine learning techniques
People use social media to engage, connect, and exchange ideas, for professional interests, and for sharing images, videos, and other contents. According to the investigation, social media allows researchers to examine individual behavior features and geographic and temporal interactions. According to studies, criminology has become a prominent subject of study globally, using data gathered from online social media sites such as Facebook, News feed articles, Twitter, and other sources. It is possible to obtain useful information for the analysis of criminal activity by using spatiotemporal linkages in user-generated content. The study refers to the application of text-based data science by gathering data from several news sources and visualizing it. This research is motivated by the abovementioned work from various social media crimes and government crime statistics. This chapter looks at 68 various crime keywords to help you figure out what kind of crime you are dealing with concerning geographical and temporal data. For categorizing crime into subgroups of categories with geographical and time aspects using news feeds, the Naive Bayes classification algorithm is used. For retrieving keywords from news feeds, the Mallet package is used. The hotspots in crime hotspots are identified using the K-means method. The KDE approach is utilized to address crime density and this methodology has solved the difficulties that the current KDE algorithm has. The study results demonstrated equivalence between the suggested crimes forecasting model as well as the ARIMA model. 2022 Elsevier Inc. All rights reserved. -
Geopolymer concrete paving blocks made with Recycled Asphalt Pavement (RAP) aggregates towards sustainable urban mobility development
Policy makers in India have realized the importance of facility for pedestrians and non- motorized vehicles in an urban infrastructure setup. This has resulted in increased utilization of construction materials like Portland cement and crushed stone, which are not environmentally friendly and sustainable. The current study presents the development of paver blocks for pedestrian facility using different wastes. Geopolymer concrete was synthesized by fly ash and recycled asphalt pavement aggregates for making of paver blocks. Paver blocks were produced in laboratory with recycled asphalt pavement aggregate replacement levels of 0%, 20%, 40%, 60% and 80% by weight of virgin coarse and fine aggregates. The developed paver blocks were tested for dimensions and tolerances, water absorption, compressive strength and abrasion resistance as per IS15658:2006 standard. The results of the laboratory study show that recycled asphalt pavement aggregates can be introduced into geopolymer matrix to produce paver blocks of desirable quality. Furthermore, its use in pedestrian facilities provides a new avenue for managing the excessive waste, which otherwise goes in landfills, incurring loss to the paving industry. Therefore, the proposed method can help decision makers to effectively utilize recycled asphalt pavement in paving industry with environment-friendly approach. 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Geometry of Variably Inclined Inviscid MHD Flows
A steady plane variably inclined magnetohydrodynamic flow of an inviscid incompressible fluid of infinite electrical conductivity studied. Introducing the vorticity, magnetic flux density, and energy functions along with the variable angle between magnetic field and velocity vector, governing equations are reformulated. The resulting equations are solved to analyze the geometry of the fluid flow. Considering streamlines to be parallel, stream function approach is applied to obtain the pattern for magnetic lines and the complete solution to the flow variables. Next considering parallel magnetic lines, magnetic flux function approach is applied to obtain streamlines and the complete solution of the flow. A graphical analysis of pressure variation is made in all the cases. 2020, Springer Nature Singapore Pte Ltd. -
Geometry of generalized Ricci-type solitons on a class of Riemannian manifolds
In this paper, the notion of generalized Ricci-type soliton is introduced and its geometrical relevance on Riemannian CR-manifold is established. Particularly, it is shown that a Riemannian CR-manifold is Einstein when its metric is a generalized Ricci-type soliton. Next, it has been proved that a Riemannian CR-manifold is Einstein-like, when its metric is a generalized gradient Ricci-type almost soliton (or generalized Ricci-type almost soliton for which the soliton vector field is collinear to the CR-vector field). Finally, we present an example of generalized Ricci-type solitons which illustrate our results. 2022 Elsevier B.V. -
Geographical and Gender Disparities in Financial Inclusion Diffusion in India
Financial inclusion is providing an opportunity to use essential banking and financial services to the less-privileged people and their businesses in order to accomplish an inclusive society and the inclusive economy. The efforts of policy makers towards achieving financial inclusion in India yielded fruitful results. Numbers of savings accounts, numbers of credit accounts, numbers of deposits, numbers of ATMs, and loan distribution to the micro and small enterprises have significantly improved in recent times. This study intends to provide answer to the question raised by examining the penetration of financial inclusion area wise, region wise and based on gender. This study has employed descriptive research design and has used secondary data for analysis. The study has found that there are geographical and gender disparities in financial inclusion penetration and financial inclusion penetration varies in terms of gender as well in India. Indian Institute of Finance. -
Geo-spatial crime density attribution using optimized machine learning algorithms
Law enforcement agencies use various crime analysis tools. A large amount of crime data has enabled crime analysis. In this paper, the proposed research methodology uses Kernel Density Estimation (KDE) in a Geographical Information System (GIS) to analyze crime-type data. Bangalore and India newsfeeds are considered for experimental purposes. The paper introduces an optimized KDE machine learning algorithm that detects hotspots, estimates a locations crime rate, and identifies point pattern lows and highs. As a result of the experiment, the proposed methodology identified that the bandwidth of the Geographical information system influences the visualization of crime density. The paper also aids in visually determining the appropriate bandwidth for the problem using an optimized KDE algorithm. We had identified a significant correlation between Newsfeed data and Official Government data, both overall Crime and by crime type. The proposed KDE model achieved a predictive performance of 77.49%. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Geo-spatial crime analysis using newsfeed data in indian context
Social media is the platforms where users communicate, interact, share ideas, career interest, pictures, video, etc. Social media gives an opportunity to analyze the human behavior. Crime analysis using data from social media such as Newsfeeds, Facebook, Twitter, etc., is becoming one of the emerging areas of research for law enforcement organizations across the world. The intelligence gathered through data is used for identifying future attacks and plan for reinforcements. This article focuses on the implementation of textual data analytics by collecting the data from different newsfeeds and provides an optimized visualization. This article establishes a framework for better prediction of 16 types of crime in India and the Bangalore area by providing the coordinates of the crime area, along with the crime which might happen there. 2019, IGI Global. -
Genuine handwriting variations in 10 years: a pilot study
Background: The present study aims to examine the extent of variation in genuine handwriting characteristics across 10years. One hundred samples (one admitted handwriting and three exemplars) were collected from 25 subjects (male and female, age ranging from 30 to 55) using purposive sampling technique. The admitted handwriting sample included documents like notebooks, wills, diaries, and record books that had been written 10years earlier, and 3 exemplars with the same information, written now in a similar kind of material. Both individual and class characteristics were analyzed in admitted as well as three exemplars which includes size of letters, slant, i-dot, t-bar (diacritics), humped letters (m, n, h), and formation of rounded letters (o, a, d, b, g, p, q). Results: Cohens kappa showed that there is a significant agreement between admitted and exemplars in the characteristics except for size. Conclusion: The results imply that once an adult has acquired a particular handwriting pattern, the master pattern of each letter, as well as both class and individual characteristics, remain unchanged. The size of the letters may change across age. 2019, The Author(s). -
Genotoxic repercussion of high-intensity radiation (x-rays) on hospital radiographers
Recent technological advances in the medical field have increased the plausibility of exposing humans to high-intensity wavelength radiations like x-rays and gamma rays while diagnosing or treating specific medical maladies. These radiations induce nucleotide changes and chromosomal alterations in the exposed population, intentionally or accidentally. A radiological investigation is regularly used in identifying the disease, especially by the technicians working in intensive care units. The current study observes the genetic damages like chromosomal abnormalities (CA) in clinicians who are occupationally exposed to high-intensity radiations (x-rays) at their workplaces using universal cytogenetic tools like micronucleus assay (MN), sister chromatid exchange and comet assay. The study was conducted between 100 exposed practitioners from the abdominal scanning, chest scanning, cranial and orthopedic or bone scanning department and age-matched healthy controls. We observed a slightly higher rate of MN and CA (p <.05) in orthopedic and chest department practitioners than in other departments concerning increasing age and duration of exposure at work. Our results emphasize taking extra precautionary measures in clinical and hospital radiation laboratories to protect the practitioners. 2022 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagen Society. -
Genome analysis for precision agriculture using artificial intelligence: a survey
Precision agriculture is a farm management technique which uses the help with the help of information technology to ensure that the crops and soil receive exactly what is required for optimum health and productivity. Genome analysis in plants helps to identify the plant structure and physiological traits. The identification of the right plant genome and the resulting traits help to optimize the cultivation of the plant for better productivity and adaptability. Genome analysis helps the biologist edit the plant genetic makeup structure to make the plant to adapt to the current conditions and thereby reducing the use of fertilizers. For precision agriculture, artificial intelligence techniques help to understand the relationships between plant genome and soil nutrient conditions that help in precision farming effectively reducing the usage of fertilizers by modifying the plants to adapt with the current soil characteristics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.