Browse Items (14421 total)
Sort by:
-
Effect of substrate temperature on the properties of spray deposited Ga2O3 thin films, for solar blind UV detector applications
In this work, Ga2O3 thin films were deposited on glass substrates by chemical spray pyrolysis technique at three different substrate temperatures 350 C, 400 C, and 450 C. The structural, optical, morphological and electrical characteristics of the deposited sample thin films were investigated. From the studies, it is understood that by tuning substrate temperature, we can extensively change the properties of the film. Optimum temperature for coating Ga2O3 thin films was understood and the work was extended to demonstrate a simple deep UV detector, working in photoconductive mode. The fabricated device exhibit medium response to UV light at 254 nm. The present work report the fabrication of solar blind UV detector based on Ga2O3 thin film, grown using low cost, easily scalable spray deposition technique. 2022 Elsevier B.V. -
Synthesis of white emitting Dy-doped Ga?O? phosphors via hydrothermal method
Gallium oxide (Ga?O?), a wide band gap material, serves as an effective host for phosphors, with emission colour tunable through doping with suitable rare- earth elements. The present study investigates the influence of dysprosium doping on Ga?O?s luminescence characteristics. Samples were synthesized via a hydrothermal method and subjected to calcination at various temperatures 600C, 750C, 900C, 1050C. These samples were characterized using X-ray diffraction, UVvisible spectroscopy, Raman spectroscopy, and photoluminescence spectroscopy. The photoluminescence spectra of the samples were analysed to identify the defect states. The CIE (Commission Internationale de lEclairage) coordinates were calculated and chromaticity diagram was plotted to determine the overall luminescence colour emission. To assess potential phosphorescence properties, decay plot was analysed and average lifetime was calculated. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Empirical study on The Role of Machine Learning in Stress Assessment among Adolescents
Stress is a psychological condition that people who are experiencing difficulties in their social and environmental well-being face, and it can cause several health problems. Young individuals experience major changes during this crucial time, and they are expected to succeed in society. It's critical for people to master appropriate stress management techniques to ensure a smooth transition into adulthood. The transition to new settings, lifestyles, and interactions with a variety of people, things, and events occurs during adolescence. In this study, a dataset was utilized to classify 520 Indian individuals' stress levels into three categories: normal, moderate, and severe. Support Vector Machines, KNN, Decision Trees, Naive Bayes and CNN were among the different classification techniques that were taken into consideration. The CNN Algorithm was found to be the most reliable method for categorizing diseases linked to mental stress. The study's main goal is to create a classification model that can correctly classify a variety of samples into distinct levels of psychological discomfort. 2023 IEEE. -
Navigating the emotional maze: Understanding Adolescent suicidal ideation using CNN-LSTM model
Teenage suicidal ideation is on the rise, which emphasizes how crucial it is to recognize and comprehend the variables that contribute to this problem. Convolutional neural networks (CNNs), which are complex machine learning models capable of analysing intricate relationships within a network, are one possible strategy for addressing this issue. In our study, we employed a CNN-LSTM hybrid model to explore the complex relationships between teen suicide ideation and various risk variables, including depression, anxiety, and social support by analysing a substantial dataset of mental health surveys, seeking patterns and risk factors associated with suicidal thoughts. Our objective was clear: identify adolescents prone to suicidal ideation. With 24 parameters and a sample size of 3075 subjects, our model achieved an impressive F1-score of 97.8%. These findings provide valuable insights which helps in developing effective preventive interventions to address adolescent suicidal ideation, finding out the important patterns and risk variables related to suicidal thoughts. The study results offer important direction for developing preventive interventions that successfully address adolescent suicidal ideation. 2024 - IOS Press. All rights reserved. -
Computational Methods to Predict Suicide Ideation among Adolescents
Suicide has been a prominent cause of death worldwide, regardless of age, sex, geography, and so on, and predominantly suicide among teens, increased as the years have passed. Suicide ideation, suicide risk, suicide attempts have been studied extensively, and the most common cause has been identified as depression, followed by familial concerns, hereditary factors, stress, avoidance fear, and a variety of other variables. When visited by a doctor, most adolescents are unaware of their mental state and hence do not take action on their own or are not assisted by family or peer members to overcome their fear of social stigma or the treatment they must undergo. According to popular belief, early treatment and detection are the most effective ways to reduce the risk of suicide. As a result, the focus of this study is to illustrate some of the computational strategies utilized in deep learning and machine learning fields to detect kids at risk of suicide 2022 IEEE. -
Evaluating the Effectiveness of GraphSAGE with Reinforcement Learning in Suicide Risk Prediction
Suicide is considered to be a major mental health issue that has affected most individuals worldwide. According to World Health Organization, it shows the rise of suicidal rates among students has increased drastically. This vulnerability shows the rising need to encounter this issue with immediate effect. Therefore, proper detection methods have to be incorporated so that we can reduce the number of suicidal rates. Many computational models were implemented to address this issue. This study was conducted to compare various algorithms such as traditional machine learning models random forest and also various deep learning models like GraphSAGE, Graph Convolutional Network, Convolutional Neural Network, and Convolutional Neural Network with Long Short Term Memory with the proposed GraphSAGE Reinforcement Learning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
The potential of hydrolyzed chicken feather meal as a partial replacement for fish meal and its effects on the growth and health status of African catfish (Clarias gariepinus) fingerlings
The application of agricultural by-products as alternative feed has received tremendous interest from the aquaculture industry. The current study explored the potential of hydrolyzed chicken feather meal (CFM) at different percentages as fish meal (FM) replacement and the impacts on growth, feed stability, apparent protein digestibility, digestive enzyme, body amino acid profiling, body proximate analysis, hematology, and morphology of African catfish (Clarias gariepinus) fingerlings. Five isonitrogenous (32% crude protein) CFM diets were prepared [0% CFM (T1), 5% CFM (T2), 15% CFM (T3), and 30% CFM (T4)] and applied in a 70-day feeding trial. At the end of the experiment, fingerlings fed with the T2 diet exhibited the best final length, final weight, net weight gain, weight gain, specific growth rate, intraperitoneal fat, and condition factor than other treatment groups. Furthermore, the highest digestive enzyme activity and apparent protein digestibility (APD) were highest in the T2 diet. There were significant differences between the groups in the liver, muscle, and intestine amino acid profiles and proximate analysis. Moreover, the T2 group recorded the best villus length, width, and crypt depth in the anterior and posterior regions. The highest white blood cells, lymphocytosis, monocytes, red blood cells, hemoglobin, and hematocrit were also found in the T2 diet group. Meanwhile, albumin, globulin, and creatine levels were the lowest in the T4 diet group. Notably, fingerlings supplemented with the highest CFM percentage demonstrated the highest morphological deterioration in the liver and intestine. In conclusion, 5% CFM is a promising FM replacement to improve the growth, apparent protein digestibility, digestive enzyme, liver and intestine histology, and blood indices of African catfish fingerlings. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Artists' moving image: South Asian trajectories /
Moving Image Review & Art Journal (MIRAJ), Vol.7, Issue 2, pp.191-201, ISSN No: 2045-6298. -
Enhanced Data Security Architecture in Enterprise Networks
Encryption and storing important information is one of the risky and most challenging tasks. It is the need of the hour in todays fast growing technological transformations that the world is undergoing. A simple Enterprise network is the communication backbone of any organization. It mostly provides better information storage and efficient retrieval, which helps the organization to function smoothly, without having to think twice about their crucial datas security aspects. The information technology paradigm, cloud computing is used to help the organization to focus on its core business. In cloud computing is dealing with many services. That service is used for provide Platform service with infrastructure and software service. This paper, promotes the idea of combining various security and encryption algorithms to connect different enterprise networks using cloud computing, security layer concepts and giving no room for hackers to intrude into the confidential system of data. Springer Nature Switzerland AG 2020. -
Survey study on the methods of bird vocalization classification
The technologies holds the ability to change the world. Current digital era is a product of the evolutionary technologies. It created the necessity to increase the Human Computer Interaction (HCI) and it became one of the most emerging research areas of the decade. HCI is an interface between the users and the system to improve the interaction. HCI concept came into existence in early 1980's. One of the emerging new research area in HCI is Context Aware System (CAS). The technological advancements in HCI created a new outlook in the research of CAS. CAS is a system which understand the user, their surroundings, and location. CAS make this possible by processing the environmental and bio-acoustic. Sound is one of the important media for both humans and animals to communicate and understand information. Bird sound, vehicle sound, wind sound etc. are some of the environmental and bio acoustics. Processing these sounds or signals will help us to create a better performing CAS. This paper profiles a survey study on bird sound classification and identification. Automatic identification of bird sound is one among the difficult task in signal processing. Also, the paper will profile the previous research works on various phases in bird vocalization processing; such as preprocessing, feature selection and classification. 2016 IEEE. -
Re-evaluating Emperor Asoka a relational contract theory explanation for economic transformation
Emperor Asoka's rein is considered an important era in ancient Indian history because of the vastness of his empire and the Buddhist elements in his administration. We propose that in addition to these reasons for highlighting Asoka's rein, there is an important economic argument as well. It was during the century or two around Asoka's rule that the subcontinent's economy underwent a transformation from a simple pastoralagricultural economy to a more mature economy with large scale production, specialisation and trade. The element that Asoka introduced into the social relations in his empire is Buddha's Dhamma, which formed and strengthened relational contracts. A key feature of relational contracts is incompleteness of arrangements that is managed by social iterations and formal and informal enforcement mechanisms. Each of these is reflected in Asoka's edicts, the earliest surviving writing samples from the subcontinent. Asoka planned for these measures to ensure political and economic stability. In addition, he also laid the most important foundational material in a rather unique way for all future economic transformations. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Corporate social responsibility: Myth and reality
Companies nowadays strive to be socially conscious in the way they do business by taking up corporate social responsibility (CSR) activities besides maintaining profitability. Similarly consumers modulate their purchase choices to be made up of products that have been produced and marketed through socially responsible processes. But the congruence between achieving gain and being responsible to the community has ethical contradictions due to the presence of self interest. This paper proposes to examine the dimensions of this conflict and towards the end suggest a new orientation that foregrounds social responsibility relative to profit or gain. 2013 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (Dharmaram Vidya Kshetram, Bangalore). -
Rebuilding the Capabilities for Post COVID-19 Pandemic: Issues and Challenges of Bangalore Model of Development
The pace of urbanization has achieved considerable momentum in recent years with 34.93 per cent of India's population living in urban areas. However, the COVID - 19 pandemic has severely affected urban development with adverse effects on people's mobility, consumption level, health and poverty. Bangalore, the capital of Karnataka and the third largest city in India, has a population of 11 million and contributes more than one third of the state's GDP. The expansion of certain sectors including Information Technology, infrastructure and spread of educational institutions has fueled Bangalore's rapid growth in the past three decades which has made it a regional superpower in India, if not South Asia. This paper explores the unique features of the 'Bangalore Model of Development' as a regional development model and provides a systematic introspection of its capabilities. It discusses the impact of the pandemic on the key driving forces of Bangalore Model and assesses the current government measures. The situation analysis with the policy prescriptions would help to strengthen and sustain the urban system during the postpandemic times. 2022 IEEE. -
Flourishing and work flow among working adults: A positive investigation from India
The demands in today's organizations are only growing at peaking high levels where turnover and burnout sets out to be major factors that challenge productivity. This is supported by previous findings which have identified turnover and burnout as a consequence of job demands. In today's demanding era of workforce, capacity to work effectively is a key component of employee's health, well-being and growth. Positive emotional and mental state of employees is a predictor of positive organization which will result in high performance, wellbeing and a conducive environment to flourish. Present study deals with workflow and its relationship with employee`s flourishing. This paper aims to explore the relationship between flourishing and experiences of work flow among working adults (n=105). Relationship among variables was analyzed through correlation and regression analysis. Results indicate that there is significant positive correlation between flourishing and experience of work flow (r (105) = 0.49, p<.01) and experience of work flow predicts the flourishing among employees. 2021 Ecological Society of India. All rights reserved. -
A Study of Investment Behavior Of Economically Weaker Section (EWS) Investors
While investing, it is most important for an investor that he/she understand and follows the basic principles of investing to gain maximum advantages out of it. The present study analyzes the investment behavior of 190 economically weaker section (EWS) investors and rank their preferences and reasons using Garret ranking. The study observes that investors prefer to invest in traditional investment avenue over modern avenue due to lack of awareness and ease of investing across demographics. Results of ANOVA inform a small shift to mutual funds and change in perceived risk and return behavior in selected age, income and education category. The study recommends for opening of dedicated small financial planning centers/branches/kiosks etc to increase their awareness level and participation so that they can gain maximum advantages from their investment. The Electrochemical Society -
APPLYING SOLUTION-FOCUSED BRIEF THERAPY IN COGNITIVE REHABILITATION: Insights from Positive Neuropsychology
Neurocognitive rehabilitation refers to the procedure involved in helping patients recover or regain some of the lost functions of the brain after an internal and external injury. Specific psychotherapeutic procedures are also combined with these rehabilitation strategies for the maximum benefit of the patients. Solution-focused brief therapy (SFBT) is a psychotherapy that allows clients to focus their attention on the solution rather than exploring the origin of the problem and focusing on their strengths and resources. It is a brief therapy based on a positive psychology approach. The traditional cognitive rehabilitation techniques focus on deficit remediation, while SFBT offers a strength-based approach that focuses on the clients resources, exceptions to the problems, and goal-oriented behavior. The integration of these approaches will bring a shift in the paradigm of neurorehabilitation by providing a balance between cognitive challenges and preserved strengths. In the realm of cognitive rehabilitation, SFBT can empower individuals with neurological impairments by fostering resilience, adapting coping strategies, and self-efficacy. This chapter explores the innovative application of SFBT principles within cognitive rehabilitation settings, which can be viewed from the lens of positive neurorehabilitation. It will also propose a framework for integrating the CAPE model (Compensatory, Activity, Preventive & Enhancement) with salient principles of SFBT, emphasizing the potential role of positive neuropsychology in cognitive rehabilitation. 2026 selection and editorial matter, K. Jayasankara Reddy; individual chapters, the contributors. All rights reserved. -
Exploring ethical and cultural considerations in metaverse-based digital marketing
New opportunities for digital marketing have emerged with the emergence of the metaverse, a virtual setting where users can communicate with one another and other digital beings. This article tries to investigate the cultural and ethical issues of metaverse-based digital marketing. It is crucial to consider the ethical ramifications of these behaviours as marketers increasingly use the metaverse as a platform for connecting with and engaging with consumers. This cover concerns including consent, data security, and privacy. The massive collection of personal information in the metaverse raises questions regarding its use, storage, and security. It becomes crucial to provide openness, responsibility, and user control over their data in order to preserve consumer and marketer confidence. Cultural factors are as crucial for digital marketing that uses the metaverse. The metaverse is a worldwide network with participants from many racial and cultural origins. Marketing professionals must be aware of cultural conventions, beliefs, and sensitivities in order to prevent unintentionally offending people or feeding prejudices. Users may have a terrible user experience and react negatively to cultural appropriation, misrepresentation, and exclusionary practices. Therefore, it is essential for encouraging favourable brand perception and user engagement to include cultural diversity and inclusivity into marketing tactics within the metaverse. This article discusses several ethical and cultural issues that marketers in the metaverse face and suggests solutions. It highlights the requirement for unambiguous moral principles and business norms that are consistent with the principles of user empowerment, privacy, and inclusivity. Additionally, it emphasizes the significance of cultural sensitivity and localization in order to efficiently and politely customize marketing messages to various audiences inside the metaverse. Marketers can design meaningful and genuine user experiences while avoiding potential problems by taking the ethical and cultural aspects of metaverse-based digital marketing into account. This work will aid in the creation of ethical and culturally aware marketing techniques within the metaverse, encouraging consumer participation, trust, and beneficial brand-customer connections in this new digital environment. 2025, IGI Global Scientific Publishing. All rights reserved. -
Models for analyzing the impact of leadership and followership values on organizational outcomes
Followers have been the center of organizational focus in modern structure. The activation of followership could be a sign of successful leadership. Leaders must begin to understand the types of people they lead. Team members identify themselves as a unit and practically plan organizational development and progress to achieve similar strategies and objectives. The development of a leadermember exchange is based on characteristics of the working relationship as opposed to a personal or friendship relationship. Leaders create unity through demonstration of group-mindedness by making more references to the collective history, the collective identity and interests, and collective efficacy. The more leaders augment follower identification (through role modeling or group socialization), the more followers will likely experience higher feelings of ownership and responsibility. This paper is intended to characterize the types of followers that might exist in organizations and establish an integration of followers classification. 2026 selection and editorial matter, Mukesh Kumar Awasthi, Ashwani Kumar, Manoj Gupta; individual chapters, the contributors. -
Intelligent Smart Waste Management Using Regression Analysis: An Empirical Study
The term deep learning is seen as an important part of artificial intelligence that allows the system to understand and make decisions without special human intervention. In-depth learning uses a variety of statistical models and programs that allow different computational properties to reach the highest point. It is estimated that the market development of artificial intelligence and technology for deep learning will amount to USD 500 billion by 2026. The use of advanced technology, such as neural networks, enables better image recognition and the use of automated processes for deep operations. The main purpose of the study is to understand the critical determinants of Deep Learning in Creating a better City through Intelligent Smart Waste Management, the major determinants cover: System usability scale, Implementation of RFID sensors and Optimizing route selection. The proposed work is that implementation of advanced tools like deep learning methodologies and machine learning tools can support in managing the waste in a smart way, this will enable in creating better cities, enhance the environment and support sustainable living. Smart cities today need to use tools like deep learning and other artificial intelligence to effectively manage waste. Smart vessels are mainly controlled and implemented, which makes it easier for users to open vessels, it is also suitable for storing solid and dry waste, but provides information on the total degree of filling, can share data and information with central waste management service, you can collect waste quickly and avoid flooding. To achieve this, governments, administrators and communities are introducing sensors that transmit data and information to the waste management company in real-time and take appropriate action. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Multilingual Sentiment Analysis of YouTube Live Stream using Machine Translation and Transformer in NLP
YouTube has become one of the all-inclusive video streaming sources on the internet. Today, the news is streamed on YouTube, marketing of a product is done live on YouTube and it has become a platform for one of the biggest PR producers for companies. Various companies have proposed an optimized way of understanding and getting the opinions of the viewers from YouTube live chat and find the best possible way to provide relevant and informative content to boost the business strategy. This study uses Natural Language Processing (NLP) based approach along with NLP transformers to classify and analyses the sentiment. 2022 IEEE.