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Advances in text steganography theory and research: A critical review and gaps
There is an immense advancement in science and technology, and computing systems with the highest degree of security are the present hot topic; however, the domination of hackers and espionage in terms of disclosing the sensitive information are steadily increasing. This chapter presents a theoretical view and critical examination of the few text steganography methods in the contemporary world. It tells the direction in which research has developed over the past few years. Cryptography, the encipherment to a certain extent, protects the data by making it unreadable but not safe. Improvisation of the same can be done using another layer of protection that is steganography in which the secret embedded inside the cover text will not be revealed. 2021, IGI Global. -
Advances in the use of ceramic catalysts in fine chemical synthesis
Ceramics are versatile materials that have been put to many different uses. Catalysis is one such area where they have been used, both as catalyst and as a robust support material for catalysts. Properties like porosity and thermal and mechanical stability make ceramics attractive in these applications. Oxidation, esterification, hydrogenation, reduction, condensation reaction, and FriedelCrafts reaction are important reactions, which have uses spanning a wide range of applications, most notably in energy and environment. This chapter gives the recent advancements in ceramic materials used in the synthetic applications of the abovementioned reactions. The type and class of the ceramic material used and its role have been mentioned for these reactions. 2023 Elsevier Ltd. All rights reserved. -
Advancing equity in digital classrooms: A personalized learning framework for higher education institutions
Since the introduction of technology-enabled education systems, personalizing the learning process has become more regarded as a promising methodology for revolutionizing the academe. Acknowledging the difference in the learning capability of students across various levels of the academic segment, a personalized learning approach is of paramount importance, especially when teachers cannot efficiently monitor each student (e.g., during emergency remote education). This chapter focused on the necessity for higher education institutions that offer courses from various streams to adopt a personalized learning initiative as a means of offering better online education services. For the successful creation of a personalized online learning experience, this chapter likewise developed a framework that provides a step-by-step guide to educational institutions in moving in this direction. As online education is a trend for future learning, this blueprint could be valuable as well in the post-pandemic era. 2022, IGI Global. All rights reserved. -
Advancing Nutrient Removal and Resource Recovery Through Artificial Intelligence: A Comprehensive Analysis and Future Perspectives
The increasing difficulties associated with effectively controlling wastewater treatment operations while simultaneously satisfying the imperatives of nutrient removal and resource recovery have necessitated the use of advanced technology. This book chapter provides a comprehensive analysis of the use of artificial intelligence (AI) methods within this complex context. Utilizing a vast array of scholarly investigations and real-world implementations, this study explores the intricate domain of wastewater treatment, providing a comprehensive understanding of how artificial intelligence algorithms are used to enhance the efficiency of nutrient removal procedures and expedite the recovery of valuable resources. This chapter presents a thorough examination of the impact of artificial intelligence (AI) on sustainable innovations in wastewater treatment facilities. It accomplishes this through a comprehensive analysis of relevant data and the inclusion of real-world case studies. The findings of this research highlight the transformative effect of AI on conventional approaches to wastewater treatment, enabling the adoption of environmentally friendly and resource-efficient practices. The integration of artificial intelligence (AI) with wastewater management offers a fascinating story that highlights the shifting paradigm in the field of environmental engineering and the efficient exploitation of resources. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Affecting computing in multimodal mobility
Computational models that simulate human emotions have witnessed a substantial development in recent years for widening the spectrum of applications. Emotional computation is becoming crucial in human-to-computer interactions with exponential growth of artificial intelligence. Normally referred to as emotion recognition, it is widely believed that the prospective detection of a person 's emotional state of mind should be computed from their facial expressions. Face-movement combinations may express many different emotion types, for instance, hate, anger, panic, joy, grief, surprise, shock, to name a few. The goal and emphasis of this manuscript is the deployment of different algorithms and computation models for emotions. Considerable advancements in this domain of emotion recognition can be made through AI model development that discusses the challenges of the system and Facial Action Coding as an integral part of the models. 2023, IGI Global. All rights reserved. -
Affiliate Marketing and the Symbiotic Relationship in the Pharma Industry
The objective of the study is to understand the dynamic relationship between customers and the healthcare industry giants in the Indian context. The purpose revolves around how the consumer is benefitting and at the same time, how the indirect third-party affiliates also earn marginal profits along with serving the customers. The study is backed by both primary and secondary data, which were collected from 173 individuals from various fields through a questionnaire. The convenience sampling method was used to select the respondents, and the Technology Acceptance Model (TAM) was used to propose the model for the study. There exists a parallel symbiotic relationship between consumers, pharmaceutical companies, and affiliates. The application of this research can be put to use for the startups, which want to explore and excel in this industry along with the future researchers who want to forecast and study the progress of the pharma companies in the long run. The empirical evidence of this paper highlights a unique relationship between affiliates, the pharma sector, and customers, which drives customer buying behavior and a combination that has not been explored yet. The study provides a unique understanding of how feedback from customers in third-party applications can benefit and produce huge profit margins down the line. 2025 Apple Academic Press, Inc. -
Agile HR "lite": Adapting agile principles to HR
This chapter explores how agile practices, called agile "Lite, " are evolving within human resources (HR) departments and how they may affect organizational agility. In addition to highlighting the benefits of agile HR principles, the study offers organizations self-assessment questions to gauge their readiness for implementing agile HR practices. The insights provided are designed to help leaders foster dialogue, address concerns, and facilitate a smooth transition to agile HR practices. The chapter examines gaps in the understanding of agile implementation in HR, raises critical questions, and provides organizations with a self-assessment tool to assist in the process. It emphasizes the importance of agile principles for transforming human resources and provides valuable insight for organizations grappling with agile approaches. Overall, it contributes to a better understanding of agile principles and offers a readiness assessment for implementing them in HR. 2024, IGI Global. -
Agricultural Crop-Yield Prediction: Comparative Analysis Using Machine Learning Models
Machine learning (ML) is a crucial decision-support tool for predicting agricultural crop yields, enabling choices about which crops to grow and what to do while they are in the growing season. The research on agricultural production prediction has been supported by the application of several ML techniques. We employed a comparative analysis in this study to synthesize using three ML models, including linear regression, polynomial regression, and K-nearest neighbors (KNN), and extracted the results for the prediction of yield. Crop yield depends on a variety of aspects such as temperature, pesticide usage, rainfall, and even year due to changing climatic conditions. It is in our best interest to find out the crop yield based on these factors, as it will help in advancing the farming sector. These collected data have gone through preprocessing - i.e., cleaning, to ensure that no redundant or error data is used to train the ML models. Before we train the models, the dataset is divided into training and testing to provide the performance metrics of each model we use. The experimental results on predictions indicate KNN performs slightly better in comparison with linear regression and polynomial regression models. 2024 Taylor & Francis Group, LLC. -
Agricultural Internet of Things (AIoT) Architecture, Applications, and Challenges
The internet of things (IoT) is a system that involves adding sensors, software, and network connectivity to physical devices, enabling them to collect and exchange data. This technology has the potential to bring significant advancements to various sectors, including agriculture. In farming, the agricultural internet of things (AIoT) utilizes IoT to improve efficiency, sustainability, and productivity. Through the real-time collection and analysis of data, AIoT can optimize growing conditions, prevent diseases and pests, and ultimately increase crop yields. By monitoring factors such as soil moisture, temperature, and nutrient levels, AIoT technology can effectively track crop health and detect potential issues in advance. In this way, AIoT technology is helping farmers to make more informed decisions and take more effective actions to improve crop yields, reduce waste, and lower costs. AIoT in agriculture finds practical applications in smart irrigation systems, precision agriculture, livestock monitoring systems, and climate control systems. Smart irrigation systems utilize weather data and soil moisture sensors to efficiently manage water consumption. Precision agriculture employs sensors and data analysis techniques to optimize planting, fertilization, and pest control practices. Livestock monitoring systems aid in monitoring and managing the well-being of farm animals. Climate control systems utilize AIoT to regulate and optimize environmental conditions for crops and livestock. Livestock monitoring systems use sensors to track the health and well-being of animals. Climate control systems for greenhouses and barns use AIoT devices to monitor temperature, humidity, and other environmental factors to optimize growing conditions. Sensors can be used to monitor various environmental factors in a farm, by connecting the sensors to a cloud-based platform for storing and analyzing data. The wireless sensor networks can be used to calculate the dew point on leaves and adjust the greenhouse environment to prevent and control plant diseases. Drones equipped with sensors, cameras, and other imaging technology can also be used to monitor crop conditions, as this allows farmers to take proactive measures to address these issues, preventing crop loss and reducing the need for pesticides and other chemicals. IoT/sensor nodes are vital components in precision agriculture as they gather real-time data. Integrating data analytics and machine learning into the agricultural system improves its practicality and efficiency. Real-time data availability enhances precision in agriculture, and combining data analytics with this information leads to notable progress in the field. However, AIoT technology is gradually advancing in agriculture, but there is a need for a more rigorous research approach in this area. Additionally, the current literature lacks coherence and solid research on the interconnectedness of technology and agriculture. 2024 selection and editorial matter, Alex Khang, Vugar Abdullayev, Vladimir Hahanov and Vrushank Shah; individual chapters, the contributors. -
Agricultural nanotechnologies: Future perspectives of bio-inspired materials
Bio-inspired designs have been used by humankind in understanding and modelling novel materials which have applications in diverse fields like disease diagnostics, drug delivery, agriculture, energy storage, industry, etc. Superhydrophobicity, directional adhesion, structural colour, self-cleaning, antireflection, etc. are some of the useful attributes for which we have relied a lot on nano level biomimetics. Bioinspired nanolevel designs have been explored in the field of agriculture too. Such nanomaterials and nanodesigns have been used to increase crop yields. They also find uses in fertilizer application and replacement of many harmful chemical pesticides, which are generally overused. Increasing population, increased longevity of people and the urgent need for sustainable environment have led to a dire need for exploration and adaptation of such novel technologies which can help in feeding the growing population. Nanoscale products and technologies can also help in reducing the accumulation of excess fertilizers, pesticides, etc. in soil, which can go a long way in cleaning up the environment. The current attempt is intended to portray the latest developments and future possibilities of bioinspired NT in diverse fields of agriculture like synthesis and delivery of novel pesticides and fertilizers, nanocarriers for gene delivery, sensors to monitor and assess soil conditions, plant pathogen detection and plant nanobionics to detect pollutants. 2023 Bentham Science Publishers. All rights reserved. -
Agriculture as a means of alleviating rural poverty: Pursuant to the sustainable development goal-1
Poverty is one of the worst problems prevailing in the world. The poorest in the world are often without food, have little or no access to education, basic amenities of life, and lack health facilities. Eradication of Global Poverty eradication is a herculean and complex task. The origination of 2030 Agenda to eradicate poverty was done after the successful completion of the anti-poverty Millennium Development Goal, but still, a vast number of people were living in poverty and a great number among them were living in extreme poverty. So, the 2030 Agenda for Sustainable Development called for the eradication of poverty in all poverty in forms from every corner of the world by almost half. In backward and developing nations, poverty is more rampant in rural areas. The economies of most of these nations are predominantly based on Agriculture and therefore progress in agriculture is viewed as a potent tool to eradicate rural poverty. However, there are serious issues that are required to be addressed in this regard. This chapter explores some vital issues related to agriculture which require the attention of the policymakers, to achieve the objective of reducing rural poverty through advancement in agriculture. 2023 Nova Science Publishers, Inc. All rights reserved. -
Agro-food traceability with efficient user interface using blockchain technology
Food traceability is crucial for food quality and safety to reduce vulnerabilities of product globalization. The traditional Agri-food production system does not offer easy traceability of the product at any point of the supply chain. Blockchain based production system resolves the challenges by reducing the complexity of traceability. Still no other study has presented Blockchain-based traceability platform with a lower impact on the environment and lower cost for each transaction sent by the supply chain. In the existing system, proof of work consensus protocol is used in blockchain which consumes more energy for transactions. The proposed traceability system is based on Ethereum Blockchain, which uses the Proof-of-Stake mechanism of consensus that requires minimal computational power, is highly scalable and environmentally sustainable. The user interface of consumer is specially designed that provides all the tracking information of the agro-food. The developed traceability platform digitizes the entire production chain making the data immutable and available in realtime. 2024 by IGI Global. -
AI and IoT for universal health and well-being across generations
Over the last several years, the confluence of AI and the Internet of Things (IoT) has caused tremendous changes in many areas of our life, including the healthcare industry. Because of this cooperation, new possibilities have emerged with the aim of enhancing the health and welfare of people across all different generations. The ability to efficiently gather, analyze, and derive insights from large volumes of real-time data has revolutionized healthcare, allowing for better patient treatment and community health management. This is made feasible by combining algorithms powered by artificial intelligence with IoT-connected devices. Examining the gamechanging possibilities of AI and the IoT in the healthcare industry is the goal of this introductory piece. The function of AI and the Internet of Things in advancing health equity and wellness across diverse age groups is the primary emphasis of this study. Countless and varied uses of AI and the internet of things may be found in the medical field. Some examples of these uses include remote patient monitoring and the development of predictive analytics tools for use in illness prevention.Health outcomes and quality of life for individuals of all ages can be improved via the development of individualized therapies and treatment programs that cater to each person's specific needs. It is feasible to create these opportunities with the help of these technologies. Healthcare issues may be effectively addressed in a variety of locations, from densely populated cities to more rural places, by implementing solutions that leverage the internet of things and artificial intelligence. Because these solutions are both accessible and scalable, this is the result. It is possible for healthcare systems to overcome barriers to service delivery and access by utilizing these technologies. As a result, people of all ages and from all over the world will be able to live the kind of healthy, fulfilling lives they deserve. 2024, IGI Global. All rights reserved. -
AI and IoT in Improving Resilience of Smart Energy Infrastructure
In todays world, we cant live without energy. Its essential for the growth and development of the economy. Changes in climate, sustainable growth, health, food security for the world, and environmental protection all require it if we are to make any headway. Governments around the world are looking for innovative ways to generate, control, supply, and save energy because of the rising cost and rising demand for it. Photovoltaic systems, hydropower, wind energy, tidal power, and geothermal energy are examples of traditional renewable energy sources that have advanced significantly in recent years. They, however, are unable to deal with environmental variations. It is critical to developing smart and cost-effective generators in order to meet the advanced worlds energy demands. In this chapter, we introduced the concept of smart energy, smart grid, and smart energy systems in a brief manner. Smart energy portfolio and smart energy management are introduced in the frst section. We also discuss how AI and IoT can be used to improve the different energy sources like wind power, solar power, geothermal power, etc. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
AI and Real-Time Business Intelligence
Timely and accurate knowledge that can be provided to different stakeholders in an enterprise improves the performance and decision-making capabilities with better insight. The information, be it qualitative or quantitative, when made available to decision makers becomes the basis of the business intelligence (BI) that improves functionality, scalability and reliability. The knowledge is managed by application of various data warehousing techniques, and artificial intelligence comes into play by providing an ample number of data mining and machine learning techniques. The chapter aims at analyzing the origin, evolution and development of BI systems and their relationship with artificial intelligence (AI). The chapter also aims to provide new research horizons in the scientific activities and advancements in BI, knowledge management and analysis. 2024 selection and editorial matter, Hemachandran K., Raul V. Rodriguez, Umashankar Subramaniam, and Valentina Emilia Balas; individual chapters, the contributors. -
AI Applications Computer Vision and Natural Language Processing
Artificial intelligence (AI) applications in computer vision and natural language processing (NLP) have made major advances in recent years, challenging a number of sectors and areas. This multidisciplinary topic combines NLP, which examines the study of human language, and computer vision, which concentrates on the understanding of visual data. This study examines the wide range of applications that are included within this convergence, highlighting the revolutionary potential of AI technology. AI has made it possible to make significant advances in autonomous systems, object identification, and image recognition in the field of computer vision. These developments have stimulated innovation and increased efficiency, revolutionizing sectors including healthcare, autonomous vehicles, and security. Meanwhile, AI-driven advances in NLP have produced strong language models that can produce, comprehend, and translate text. These approaches have been utilized to improve accessibility and efficiency of communication in chatbots, sentiment analysis, and language translation services. This chapter explores the basic ideas and advancements in these two fields, emphasizing the opportunities and novel challenges that arise from integrating computer vision and NLP. Additionally covered are data privacy, ethical issues, and the possibility of prejudice in AI applications. The study also highlights the ongoing need for these fields' advancement and investigation in order to solve real-world problems and fully utilize AI's potential in the computer vision and NLP industries. 2025 The Institute of Electrical and Electronics Engineers, Inc. -
AI applications at the scheduling and resource allocation schemes in web medium
Resources including business, informational, personal, and financial resources are required, with support from users, to maintain and implement the resource representations. Resource provisioning seeks to meet user needs by supplying the appropriate resources at the appropriate time at a lower cost. A service provider oversees supplying resources to all applications, and among the methods of resource management that they can employ are time-based, cost-based, on-demand, and bargain-based. These general approaches to resource provisioning and scheduling are based on recent developments in heterogeneity in 6G networks, including cloud computing, fog computing, and autonomic computing, to allocate and schedule resources while keeping an eye on service performance and adjusting as needed to meet the needs of cloud users. The proposed work increases resource allocation through cost reduction and, as a result, increases the availability of the services at the device levels without compromising performance parameters such as availability, efficiency, authentication, and authorization. The wide metropolitan area network (6G Networks) wireless heterogeneity is presented in this chapter's technological problems. Memory, network performance, and other factors were heterogeneous in fog nodes. Here, the Load balancing algorithm's Priority ordering is applied to make use of wireless model properties. This chapter focuses on various load balancing and scheduling strategies along with a few machine learning techniques applied to fog nodes and clustering techniques. 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors. -
AI as sustainable and eco-friendly environment for climate change
[No abstract available] -
AI Based Non-invasive Glucose Detection Using Urine
This proposed device uses urine to predict the glucose level present in the patient using non-invasive technique with a high level of accuracy for detection of diabetes. The paper presents a urine glucose level diagnosing and prediction using a computer-based polarimeter held in a portable device, to provide a fast and accurate on-field result. The instrument consists of an LCD screen, optical sensor, Benedicts reagent, a detachable tank, and an embedded system-on-chip (SoC). Springer Nature Singapore Pte Ltd 2020. -
AI Based Technologies for Digital and Banking Fraud During Covid-19
The only viral thing today is the Covid 19 virus, which has severely disrupted all the economic activity around globe because of which all the businesses are experiencing irrespective of its domain or country of origin. One such major paradigm shift is contactless business, which has increased digital transaction. This in turn has given hackers and fraudsters a lot of space to perform digital scams line phishing, spurious links, malware downloads etc. These frauds have become undesirable part of increased digital transactions, which needs immediate attention and eradication from the system with instant results. In this pandemic situation where, social distancing is key to restrict the spread of the virus, digital payments are the safest and most appropriate payment method, and it needs to be safe and secure for both the parties. Artificial intelligence can be a saviour in this situation, which can help combat the digital frauds. The present study will focus on the different kinds of frauds which customers and facing, and most possible ways Artificial intelligence can be incorporated to identify and eliminate such kind of frauds to make digital payments more secure. Findings of the study suggest that inclusion of AI did bring a change in the business environment. AI used for entertainment has become an essential part in business. Transfiguration from process to platform focused business. The primary requirement of AI is to study the customer experience and how to give a better response for improving the satisfaction. But recently AIs are used not only for customer support, but its been observed that businesses have taken it as marketing strategy to increase demand and sales. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.