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Harnessing technology for mitigating water woes in the city of Bengaluru
Industrialization has caused most of the world's environmental problems like climate change, water security issues, biodiversity issues among others. Water-related issues like water scarcity, lack of water quality, water sanitation issues, lack of proper water resources management are some of them. Urbanization, population increase, pollution has led to an increase in water demand. Water being the elixir of life, is essential for the day-to-day living of an individual. The Fourth Industrial Revolution technologies like AI, IoT, Blockchain, Machine Learning have the capability of bringing solutions to these issues. The current study focuses on the water woes of Bengaluru, a fast-growing urban city, due to its migrating population. The woes are also due to the irresponsible behaviour of builders converting lakes into real estate infrastructure leading to clogged drains, excess sewage creation and flooding. A huge mismatch between demand and supply of water is created due to these issues. Before the city hits the Day Zero - no water day, it is significant to set up water infrastructure along with technology implementation which will help resolve this burning issue at the earliest. Published under licence by IOP Publishing Ltd. -
Harnessing Technology for a Sustainable Future in Finance: The Role of Artificial Intelligence in Promoting Environmental Responsibility
The integration of artificial intelligence (AI) into sustainable finance has become a focal point in recent years, propelled by global concerns about the environment and the pressing need for sustainable development. AI technologies, equipped with advanced capabilities, offer significant opportunities to address challenges faced by financial institutions, investors, and policymakers, ushering in the prospect of a more sustainable and inclusive economy. AI's applications in sustainable finance cover diverse areas such as environmental risk assessment, green investment analysis, climate change modeling, and the integration of Environmental, Social, and Governance (ESG) factors. By leveraging advanced data analytics and machine learning algorithms, AI empowers financial institutions to assess environmental risks associated with investments and portfolios, identifying climate-related opportunities and seamlessly integrating ESG factors into decision-making processes. Furthermore, AI-driven technologies streamline the collection, processing, and analysis of extensive data from varied sources, facilitating precise and timely sustainability reporting. These technologies contribute to identifying sustainable investment trends and play a crucial role in monitoring the progress of sustainability initiatives. AI algorithms also aid in crafting predictive models for climate-related events, assisting investors and policymakers in evaluating the long-term financial implications of climate change and formulating effective mitigation strategies. While the adoption of AI in sustainable finance offers immense potential, it is not without challenges and risks. Ethical considerations, data quality and biases, transparency, and the interpretability of AI models are among the key concerns that require careful attention. Additionally, the establishment of regulatory frameworks and industry standards is essential to ensure the responsible and ethical use of AI technologies in finance. In spite of these challenges, the integration of AI in sustainable finance holds great promise for expediting the transition towards a greener and more sustainable future. It empowers stakeholders to make well-informed decisions, advocates for responsible investment practices, and contributes significantly to the attainment of global sustainability goals. By harnessing the capabilities of AI, financial institutions and policymakers can unlock new opportunities, mitigate risks, and cultivate a financial system that is not only sustainable but also resilient. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Harnessing nanotechnology applications and solutions for environmental and climate protection-an overview
Nanotechnology is an emerging technology that has drawn considerable interest from environmentalists. Numerous nano techniques identify Nanotechnology applications as having the potential for imperative advantages and innovation. This work offers a wide-overview of the main beliefs that strengthen s nanotechnology. We focus on the potential applications of nanotechnology for environmental protection and management by thoroughly reviewing past literature. To our understanding, this is an academic, peer-reviewed work to deliver a systematic review of nano-activities in the areas of environmental and climate protection. Our study has been systematically arranged into two different groups (1) Potential applications of nanotechnology in r environmental protection and (2) The best part of Nanotechnology that combats Climate Change. For each of these cases, our contribution is twofold: First, in identifying the technical ways by which nanotechnology can solve environmental risks, and secondly, in briefly presenting its potential advantages. The paper ends with deliberation of challenges and operational barriers that technology needs to overcome to prove its commercial viability and for being adopted for commercial use. 2021 Author(s). -
Harnessing Medical Databases and Data Mining in the Big Data Era: Advancements and Applications in Healthcare
In the contemporary period of Big Data, the healthcare industry is witnessing a transformative paradigm shift, propelled by the convergence of medical databases and data mining technology. This research paper delves into the multifaceted application of this synergy, offering a comprehensive overview of its implications and opportunities. With the exponential growth of healthcare data, the utilisation of medical databases serves as the bedrock for data mining techniques, fostering critical advancements in diagnosis, treatment, and patient care. Through this research, we explore the integration of electronic health records, genomic data, and clinical databases, unveiling new dimensions of predictive analytics, patient profiling, and disease monitoring. Moreover, we assess the ethical and privacy concerns entailed in this data-rich landscape, emphasising the need for robust governance and security measures. Our paper encapsulates the evolving landscape of health care, demonstrating the immense potential and the ethical responsibilities accompanying this groundbreaking merger of technology and medicine in the period of Big Data. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Harnessing Machine Learning for Mental Health: A Study on Classifying Depression-Related Social Media Posts
This study is of particular relevance in the way it identifies depression-related content on social media using a machine learning model to classify posts and comments. This dataset, encompassing around 6500 entries from various platforms including Facebook, was rigorously annotated by four proficient English-speaking undergraduate students together with the final label which is established via majority voting. Data Preprocessing, initial cleaning, normalization and TF-IDF feature creation through vectorization for the output of POS tags. The different machine learning models that were trained and tested are Logistic Regression, Random Forest, SVM (Support Vector Machine), Naive Bayes Gradient Boosting Algorithm K-NN (K nearest Neighbors) AdaBoost Decision Tree. Authors evaluated the models and measured their accuracy, precision score, recall rate (also known as sensitivity) in addition to F1-score. Gradient Boost, Random Forest, and SVM were top performers among which Gradient boosting was found to be an overall best one with almost 98.5%. They show that machine learning model can successfully predict the label of social media posts, as a way for accurately identifying depression from text data. This detailed model performance evaluation is useful in understanding what each approach does well and poorly, shedding light into whether they are / would be actually suitable for real-world applications. This study not only developed discriminative classifiers, but also included detailed analysis of their performance which should hopefully guide future work and help in practical implementations for real-time mental health monitoring. Through this work, this study aim to facilitate timely identification of depression-related posts, ultimately supporting mental health awareness and intervention efforts on social media platforms. 2024 IEEE. -
Harnessing digital innovation for inclusive tourism: Role of emerging technologies in creating accessibility and equity
The rapid advancement of digital technologies has ushered in a new era for the tourism industry, presenting unprecedented opportunities to enhance inclusivity, accessibility, and equity in travel experiences. This study investigates the transformative potential of emerging technologies in fostering a more inclusive tourism landscape. Specifically, it examines how selected digital innovations such as artificial intelligence (AI), augmented and virtual reality (AR/VR), mobile applications, and wearable devices are shaping the accessibility and equity of tourism for diverse populations. This chapter begins with a comprehensive literature review, highlighting current trends, challenges, and existing studies on inclusive practices in the tourism sector. The paper delves into a detailed analysis of each emerging technology, showcasing successful integration examples from real-world cases. It evaluates the benefits and potential challenges of adopting these technologies, especially in enhancing accessibility for travelers with disabilities. The examination addresses physical, sensory, and cognitive accessibility barriers, providing insights into how technology reshapes travel experiences for diverse individuals. This chapter delves into the role of emerging digital innovations in fostering equity within the tourism sector. By facilitating cross-cultural connections and enhancing access to tech-driven travel experiences, these technologies contribute to a more inclusive landscape. The study scrutinizes socioeconomic dimensions, shedding light on the holistic impact of tech integration. While acknowledging challenges and ethical concerns, responsible technology deployment is endorsed to counterbalance drawbacks and bridge the digital divide, enabling marginalized communities to leverage the benefits of this digital transformation. The implications of this study are relevant for businesses, policymakers, and tourism stakeholders. The chapter concludes by providing practical recommendations for the responsible incorporation of emerging technologies and emphasizing the long-term sustainability of inclusive digital innovations. By shedding light on the transformative potential of these technologies and outlining guidelines for their application, this research contributes to the evolution of a more accessible, equitable, and inclusive tourism industry. 2024 Nova Science Publishers, Inc. All rights reserved. -
Harmonizing human resource strategies navigating employer branding in sustainable organizations
In the framework of sustainable businesses, this chapter examines the synergies between employer branding and human resource (HR) strategies. In order to establish a harmonic organizational framework, this chapter thoroughly investigates how HR practices might be strategically aligned with sustainability goals. It explores the opportunities and challenges of managing employer branding within sustainable business practices. It sheds light on specific variables and practices that must be considered to develop an employer brand that reflects the organization's commitment to sustainability. In order to create an integrated, attractive, and socially responsible employer brand, it is important to align their human resources practices with sustainability initiatives. It provides insights into the strategic integration of employer branding and human resources, presenting a roadmap for businesses looking to match their HR procedures with sustainability programs. 2024, IGI Global. All rights reserved. -
Harmonizing financial systems for a greener future: Exploring sustainable finance strategies in India
Sustainable finance represents the next biggest transformation in the financial sector to aid the process of sustainable development. Sustainable finance comprises traditional investment which provides financial profits as well as financing the projects or investments that have social, economic and governance impact. The transition from traditional investment to sustainable finance is underway in different markets at different capacities. This study seeks to examine the performance of sustainability indices representing sustainable finance in the Indian and global markets by analysing returns. It was found that sustainable finance gained significant appreciation in the Indian market. In comparing the performance of sustainability indices in developing and developed markets, there was no development divide identified. In this path towards widespread adoption of sustainable finance, data science as a field also provides promising applications for facilitating this transformation. 2024, IGI Global. All rights reserved. -
Hardware in loop network simulators - An insight overview
Network simulation is a method of using software or a tool which can be used to mimic the network conditions that exist in pre-defined places. This kind of simulation allows the developers, designers, researchers and the network planners to intelligently plan, design, develop and test their applications or research work in changing network conditions. With varying network conditions either because of wireless nature or because of user mobility, it is very difficult to simulate the exact network conditions with the existing network simulators. These network simulators are flexible, re-usable and reliable. But they have a limitation of not being able to replicate the actual network conditions in the laboratories. This calls for a system in the loop or hardware in the loop concept to be extended to the network simulators. The idea of system in the loop is not new. In this paper, an overview with the fundamental understanding of the hardware-in-loop concept for network simulators, their applications and a review of the existing hardware-in-loop network simulators with their advantages and disadvantages is presented. 2024 World Scientific Publishing Company. -
Haptics: Prominence and Challenges
Derived from a Greek word meaning sense of touch, Haptic is a communication technology which applies tactile sensation for human-computer interaction with computers. Haptic technology, or haptics, is a tangible feedback technology that takes benefit of a users sense of touch by applying forces, sensations, or motions to the user. These objects are used to methodically probe human haptic capabilities, which would be complex to achieve without them. This innovative research tool gives an understanding of how touch and its core functions work. The article will provide a detailed insight into the working principles, uniqueness of the technology, its advantages and disadvantages along with some of its devices and notable applications. Future challenges and opportunities in the field will also be addressed. 2020, Springer Nature Switzerland AG. -
Happiness, Meaning, and Satisfaction in Life as Perceived by Indian University Students and Their Association with Spirituality
The present study aims to examine the association between various dimensions of psychological well-being (subjective happiness, satisfaction, and meaning in life), spirituality, and demographic and socioeconomic background of university students. A total of 414 postgraduate students were selected from three different schools, viz. science, management, and social sciences/humanities of Pondicherry University (A Central University), Puducherry, India, following multistage cluster sampling method. One semi-structured questionnaire and four standardized psychological scales, viz. subjective happiness scale, satisfaction with life scale, meaning in life questionnaire, and spirituality attitude inventory, were used for data collection after checking psychometric properties of the scales. The results show that a positive significant correlation between spirituality and subjective happiness exists. Spirituality is also correlated with meaning in life and satisfaction with life scale. Statistically, no significant gender difference was observed with respect to subjective happiness, meaning, and satisfaction in life as well as spirituality although the mean score of female students was more in all the four psychological domains. Non-integrated students are found to be happier than integrated students, and statistically it was significant. Positive interpersonal relationship and congenial family environment were probed to be facilitating factors for positive mental health of university students. There is a severe need to address students mental health by every educational institution through multiple programs. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
HAPPINESS INDEX OF HIGHER EDUCATION STUDENTS TOWARDS ONLINE LEARNING IN INDIA
World Happiness Index generally indicates the level of happiness and satisfaction among the residents in a given country. Since we all know that worldwide new ecosystem of online education has evolved there are many countries which have done pretty well with respect to adopting of technology in the education others have been lacking behind and hence causing more inequality in the online education space. To understand the students' perception and satisfaction regarding the online learning this study was conducted to assess the relationships of the happiness index (HI) and related parameters which were retrieved from existing literatures and self-prepared parameters. Accordingly, the world happiness index signifies a direct relationship with the social economic development factors leading to the general well-being of individuals and societies that include the full development of healthcare, politics, and higher employment. The question arises has the online learning lived up to its potential? The Indian Education System is heterogeneous comprising of private and public universities. The study was on conducted in the National Capital Region of India, (NCR). The data was collected from various types of universities' students irrespective of the gender, caste, creed and religion. The study aims to understand the perception of the students and challenges faced by them during the online learning. It is very important to know the views of the students along with teachers to get the true ground reality of online learning in India. Since the pandemic have hit overall the world education sector was hit too. All the educational institutions were closed for about nearly 1.5 years. There was drastic shift in the paradigm from traditional learning to the online learning. To understand the students' perception data is being collected from around 268 students of the Delhi NCR region. The study is quantitative. The questionnaire was distributed to the both Government and Private Universities to understand students' satisfaction regarding online learning. The data was being analyzed in the graph form. The study says the future of online learning is possible provided students have access to devices and better connectivity. 2022 Zeitschrift fur Psychologie / Journal of Psychology.All rights reserved. -
Happiness and resilience among young physically disadvantaged employees in India: A pilot study
Purpose: The study aimed to examine and compare the happiness and resilience of disadvantaged employees and non-disadvantaged employees. Method: The study sample included 37 young employees, between 20 and 30 years of age. Among them, 17 were with physical disadvantages of one type or the other, and 20 had no physical disadvantages. Results: Mann-Whitney U test showed that there is no difference in resilience and happiness between disadvantaged and non-disadvantaged employees. Among the non-disadvantaged employees, there is a relationship between happiness and resilience. However, among the disadvantaged employees, this relationship is not there. Conclusions: Disadvantaged employees in the present sample do not differ from the non-disadvantaged in their happiness and resilience. However, it cannot be assumed that happiness is a contributing factor to the resilience of the disadvantaged employees. Also, it is not possible to generalize the results of the study due to the small sample size. 2019, Action for Disability Regional Rehabilitation Centre. All rights reserved. -
Handwritten tibetan character recognition using hidden markov model
The Tibetan language which is one of the four oldest and most original languages of Asia is elemental to Tibetan identity, culture and religion and it convey very specific social and cultural behaviors, and ways of thinking. The annihilation of the Tibetan language will have tremendous consequences for the Tibetan culture and hence it is important to preserve it. Tibetan language is mainly used in Tibet, Bhutan, and also in parts of Nepal and India. Tibetan script is devised based on the Devanagari model and Sanskrit based grammars. In this paper, a method for Tibetan handwritten character recognition based on density and distance feature detection is presents. To get a better classification result, images are converted into binary and noise removal is done by using Otzsos method. Features are extracted by normalizing the image based on distance and density of the pixel in the image. Finally, Hidden Markov Model is used for character classification. BEIESP. -
Handwritten Telugu Character Recognition Using Machine Learning
The Telugu language is the most prominent representative within the Dravidian language family, predominantly spoken in the southeastern regions of India. Handwritten character recognition in Telugu has significant applications across diverse fields such as healthcare, administration, education, and paleography. Despite its importance, the Telugu script differs significantly from English, presenting distinct challenges in recognizing characters due to its complexity and diverse character shapes. This study explores the application of machine learning, particularly delving into deep learning techniques, to improve the accuracy of Telugu character recognition. This paper proposes a model to recognize handwritten Telugu characters using Convolutional Neural Network (CNN). The proposed study demonstrates the accuracy in identifying diverse handwritten Telugu characters. We assess the system's performance against conventional and machine learning methodologies and preprocess an extensive dataset to guarantee strong model training. The proposed model excels in accurately predicting visually similar but distinct characters, achieving an impressive accuracy rate of 96.96%. 2024 IEEE. -
Handwritten digit recognition using convolutional neural networks
Optical character recognition (OCR) systems have been used for extraction of text contained in scanned documents or images. This system consists of two steps: character detection and recognition. One classification algorithm is required for character recognition by their features. Character can be recognized using neural networks. The multilayer perceptron (MLP) provides acceptable recognition accuracy for character classification. Moreover, the convolutional neural network (CNN) and the recurrent neural network (RNN) are providing character recognition with high accuracy. MLP, RNN, and CNN may suffer from the large amount of computation in the training phase. MLP solves different types of problems with good accuracy but it takes huge amount of time due to its dense network connection. RNNs are suitable for sequence data, while CNNs are suitable for spatial data. In this chapter, a CNN is implemented for recognition of digits from MNIST database and a comparative study is established between MLP, RNN, and CNN. The CNN provides the higher accuracy for digit recognition and takes lowest amount of time for training the system with respect to MLP and RNN. The CNN gives better result with accuracy up to 98.92% as the MNIST digit dataset is used, which is spatial data. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Handwritten Character Recognition of MODI Script using Convolutional Neural Network Based Feature Extraction Method and Support Vector Machine Classifier
Deep learning based algorithms are used in various pattern recognition tasks, including character recognition. Convolutional Neural Network (CNN) is effectively implemented for character recognition and is one of the best performing deep learning models. CNN can be used for character recognition directly or it can be used for extracting features in the character recognition process. Implementation of a feature extraction method using CNN autoencoder for MODI script character recognition is discussed in the paper. The extracted features are then subjected to Support Vector Machine (SVM) for the purpose of classification. The On-the-fly data augmentation method is used to add variability and generalization of the data set. MODI Script is an ancient Indian script and was used for writing Marathi until 1950. Various libraries and temples in India and abroad have a large collection of MODI documents. Character recognition related research of MODI script is still in infancy and research and development is necessary to extract the information from MODI manuscripts stored in various libraries. The performance of the proposed method, which uses CNN autoencoder as a feature extractor and an SVM based classifier gives very high accuracy and is better compared to the most accurate MODI character recognition method reported so far. 2020 IEEE. -
Handoff schemes in mobile environments a comparative study
Vehicular ad-hoc networks are one of the most popular applications of Ad-hoc networks, where networks are formed without any sort of physical connecting medium and can be formed whenever required. It is an area in networks that has enjoyed a considerable amount of attention for quite some time. Due to the highly mobile environment where these networks find their usability, it can be understood that there are a lot of problems with respect to maintaining the communication links between the moving vehicular nodes and the static infrastructures which act as the access points (AP) for these moving vehicular mobile nodes (MN). The coverage area of each AP is limited and as such, the connections need to be re-established time and again between the MNs and the closest accessible AP. Handoff is the process involved here, which deals with selecting the optimal APs as well as the best network available for data transmission. In this article, the authors compare various handoff methods and categorize them based on the different approaches they follow. Copyright 2020 IGI Global. -
Handloom weavers and lockdown in Sualkuchi Cluster of Assam
After demonetisation in 2016, followed by imposition of the goods and services tax in the subsequent year, the COVID-19 lockdown has turned out to be a final nail in the coffin for the handloom sector in Assam. It has special importance in the informal economy of Assam since it is next to agriculture in creating employment opportunities. An examination of the Sualkuchi weaving cluster in Assam shows the many challenges the weavers, most of them women, face. 2020 Economic and Political Weekly. All rights reserved. -
Hand Sign Recognition to Structured Sentences
Computer vision is not just a concept of deep learning; it has wide applications such as motion recognition, object recognition, video indexing, video media understanding, and recognition-based intelligence. -However, vision-based systems are a challenging field for research and accurate results. Recent areas of interest are human action recognition or human hands gesture recognition techniques using video data set, still, an image data set, spatiotemporal methods, features in RGB, deep learning methods. Hand action recognition has applications such as communication systems to shorten the bridge gap for people with speech disabilities by using a vision-based system to recognize hand sign language and convert it to text, forming structured sentences which will be easy to understand and communicate. 2023 IEEE.