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A study on remote sensing image segmentation and classification
The image is a composition of many pixels. These pixels include two pieces of information: coordinate or position and intensity value. The image includes several objects; extracting the crucial objects from the image is critical. Based on the similarity of patterns, classes, groups, and segments of contained objects in the image can be created. Assigning the labels to the pixels is necessary to make the image more informative for analyzing features and decision-making. This study addresses segmentation techniques and classifying images pertaining to remote sensing images. Thereafter, Land Use Land Cover (LULC) mapping is discussed, which classifies the remote sensing images. 2025 Bentham Science Publishers. All rights reserved. -
Mental Health
[No abstract available] -
Machine Learning for Early Detection of Chronic Diseases: A Case Study in Diabetes Prediction
Early detection of chronic diseases like diabetes is very important for early treatment and effective management. This chapter describes a machine learning (ML) solution for predicting diabetes risk from clinical structured data and a case study is constructed on the PIMA Indian Diabetes dataset. The solution caters to the entire ML pipeline: problem formulation, preprocessing of data, feature selection (FS), model training, validation, and deployment issues. Different preprocessing techniques including missing value imputation, detection of outliers, and feature normalization were used for improving data quality. FS techniques like correlation analysis, recursive feature elimination, and selection based on domain knowledge were utilized to decrease the dimensionality of the data as well as model interpretability. Extensive comparison was conducted among widely used classification models like logistic regression (LR), random forest, support vector machine, and XGBoost. It was suggested to adopt a stacked ensemble model of LR, RF, SVM, and XGBoost that achieved better performance in terms of accuracy, precision, recall, and F1-score. The findings confirm the tremendous potential of ML to enable early diabetes diagnosis as an unobtrusive, data-driven, and scalable decision-making supporting system for physicians. This is the groundwork for the further development of clinically applicable artificial intelligence-based prediction models within real-world healthcare settings. 2026 Walter de Gruyter GmbH, Berlin/Boston, Genthiner Stra 13, 10785 Berlin. -
Adversarial networks in image generation: A detailed approach to manage datasets and to analyze discriminator and generator losses using GANs
Image production has been transformed by generative adversarial networks (GANs), which have made unprecedented realism and diversity possible. Still, there are significant hurdles in managing datasetsdatasets managing and analyzing lossesloss analysis. This book chapter focusses on dataset administration and loss analysis, while providing a thorough method for using adversarial networks for image production. A thorough approach for selecting and preparing datasets, while maintaining optimal GAN performance is put forth by researchers. The proposed research approach enables the effective training of GANs, resulting in high-quality image generationhigh-quality image generation. Experimental results demonstrate the efficacy of the current method, showcasing improved image realism and diversity. The suggested strategy also presents a fresh way to examine discriminator and generator lossesgenerator losses, offering new perspectives on the convergence and stability of GANs. This study advances the field of GAN-based image productionGAN-based image production and offers professionals and academics who wish to use adversarial networks a priceless tool. 2026 Walter de Gruyter GmbH, Berlin/Boston, Genthiner Stra 13, 10785 Berlin. -
A novel approach to optimize power utilization and scheduling in dynamic networks through generative adversarial network-based prediction of network parameters
The infrastructure-less network communication has been in an ever-increasing demand to cater to the needs of effective communication while the network dynamism exists. The quality of service (QoS)quality of service (QoS) demands increasing the efficiency of network by reducing the time taken for a data packet to reach the destination, increasing the probability of successful data transmissiondata transmission, minimizing packet loss,packet loss and optimizing power utilizationpower utilization. In this study, a generative adversarial network-based learning modelgenerative adversarial network-based learning model has been developed that considers the previous network statistics, as realized data, to predict future network patterns by the generatorgenerator to make such predictions, called as unrealized data, as near to the realized data. Further, the proposed model uses penalty-award criteria by the discriminatordiscriminator, to fine-tune the predicted network parameters. Now, having the set of realized and unrealized data, the model uses Markov decision processMarkov decision process to perform power scheduling and effective utilization of buffer space. The buffer utilization in the intermediate nodes necessitates the model to stochastically schedule the data transmission, depending on the percentage of utilization of buffer. Simulation results denote the effective utilization of buffer that makes continued transmission of data, whenever possible, without having data packet lossdata packet loss. Also, power scheduling, by the use of goodput function and increased transmission probability improves the power utilization that ultimately increases the lifetime of the network. 2026 Walter de Gruyter GmbH, Berlin/Boston, Genthiner Stra 13, 10785 Berlin. -
Future Possibilities for Integrating AI with Nano-Carrier Technology
The convergence of artificial intelligence (AI) and nanotechnology presents exciting prospects for advancing drug delivery systems. This review explores the potential synergies between AI and nanocarrier technology to enhance drug delivery efficiency and therapeutic outcomes. We examine current developments in both fields and propose future directions for integrating AI algorithms with nanocarrier design, optimization, and personalized medicine approaches. AI can play a pivotal role in guiding the rational design of nanocarriers, optimizing drug loading and release kinetics, predicting in vivo behavior, and tailoring treatments to individual patient needs. Challenges such as regulatory hurdles, data privacy concerns, and the need for interdisciplinary collaboration are also discussed. Overall, the integration of AI with nanocarrier technology offers unprecedented opportunities to revolutionize drug delivery and improve patient care in the years to come. 2026 by Apple Academic Press, Inc. -
The Road to Marketing Success: Drivers and Barriers in SME Strategy Implementation
Purpose: The paper seeks to present the drivers and barriers to implementing effective marketing strategies by SMEs in India. In this current research, a systematic literature review (SLR) was adopted to collect existing literature; after identifying relevant literature, topic modeling was used to identify significant research themes in the SME sector. Methodology: A semi-structured interview was conducted for data collection by interviewing SME owners and managers, which was analyzed via thematic analysis (TA) to identify different barriers and drivers of SMEs in implementing effective marketing strategies. Findings: The discussion of the study has collated and proposed a combined set of drivers and barriers from all three methodologies. The studys findings highlight that external and internal barriers and drivers impact SMEs implementation of effective marketing strategies in India. Originality: This paper combines three approaches, namely structured literature review, topic modeling, and TA, to identify SMEs different barriers and drivers in implementing effective marketing strategies. 2026 by Apple Academic Press, Inc. -
Navigating the Strategic Labyrinth: Bridging Gaps in Theory, Implementation, and Adaptation
The dynamic business landscape demands agile strategists, yet gaps remain between theory and practice. This study delves into five key areas for navigating the strategic maze: Tools are needed to translate theoretical frameworks into actionable strategies for diverse contexts. Factors enabling or hindering successful implementation across organizations, as explored by Haghighi et al. (2019), require a deeper understanding. Embracing Emerging Trends: Disruptive technologies like Eissas (2018) smart grid program necessitate strategic adaptation and exploration of their potential. Humanizing Strategy: Insights from behavioral economics and cognitive psychology can guide us in understanding the human factors influence on strategic decision-making. Context-Specific Strategies: Tailoring strategies to unique challenges and opportunities faced by different sectors and regions is key to sustainable success. By addressing these gaps, the study empowers organizations to navigate the strategic landscape with greater agility and effectiveness. This journey requires embracing a human-centered approach, fostering continuous learning, and bridging the theory-practice divide. Ultimately, equipping organizations with these tools will pave the way for a more resilient and sustainable future. 2026 by Apple Academic Press, Inc. -
Economic Insights: The Computational Intelligence Perspective on Finance
Using technological advancements and shifting risk landscapes as a driving force, this abstract investigates the revolutionary approaches that have reshaped risk mitigation in contemporary contexts. Introducing a new era of proactive risk management has been made possible by the combination of artificial intelligence (AI), machine learning (ML), and predictive analytics. Organizations are able to recognize patterns and anticipate potential risks with an accuracy that has never been seen before, thanks to these technologies, which analyze vast datasets. By extracting valuable insights from unstructured data sources, natural language processing (NLP) and sentiment analysis broaden the scope of risk assessment with their respective capabilities. Blockchain technology improves both transparency and security, particularly in the realm of financial transactions, thereby lowering the likelihood of fraudulent activity. Cloud computing makes dynamic risk modeling easier to accomplish, which in turn makes it possible to simulate real-time scenarios. The cumulative effect of these innovations not only improves the efficiency of risk reduction, but it also helps organizations develop risk management frameworks that are more agile and resilient. When navigating the complexities of a risk landscape that is constantly shifting, it is essential to strike a balance between technological advancements, ethical considerations, and transparency. 2026 by Apple Academic Press, Inc. -
The Road Ahead: Charting Future Research Directions in Computational Intelligence
The synergy between neuroscience and computational intelligence fosters a dynamic exchange that significantly advances both fields. At its core, this convergence focuses on emulating the brains intricate mechanisms to inspire and enhance machine learning (ML) models. Neural networks (NNs), foundational to computational intelligence, are modeled after biological neurons and drive artificial neural networks (ANNs) that excel in tasks simulating human cognition. Neuromorphic computing furthers this concept by designing hardware and software with braininspired architectures, enabling energy-efficient AI systems. A notable breakthrough is brain-computer interfaces (BCIs), which translate neural signals into actionable commands, offering transformative solutions for individuals with paralysis. Additionally, cognitive computing leverages neuroscience insights to emulate higher-order mental processes, enabling the development of intelligent, context-aware systems. Conversely, ML algorithms, especially in pattern recognition, empower neuroscience by analyzing large-scale brain imaging data to uncover hidden patterns and correlations. This bidirectional interaction accelerates discoveries in neurology and psychology while deepening our understanding of brain function. Together, neuroscience and computational intelligence form a powerful alliance, shaping the future of intelligent technologies and brain science. 2026 by Apple Academic Press, Inc. -
Financial Insights Unleashed: Computational Intelligence in Practice
This study explores how artificial intelligence (AI) is changing the banking sector and identifies important uses and consequences. Fintech is evolving, from AI-powered credit risk evaluations to the real-time effects of news and social media on markets. Customary financial procedures are being transformed by the incorporation of blockchain technology, smart contracts, and collaborative models that combine human and AI. It is important to balance risk and return while implementing computational intelligence (CI), and there are several obstacles associated with this technical advance, such as ethical issues and data privacy solutions. This 168changing financial story emphasizes the importance of finding a careful balance between innovation and responsibility. Financial decision-making will hopefully become data-driven, customer-focused, and morally based in the future thanks to the cooperative synergy between humans and AI. The development of a robust and thoughtful financial landscape depends critically on ongoing monitoring, adaptability, and dedication to ethical AI practices. 2026 by Apple Academic Press, Inc. -
Technology-Enabled Smart Healthcare toward Smart Society 5.0
The emerging technologies such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, 3D printing, and 5G networking (referred as AIB35) in the context of smart healthcare are being greatly explored by smart healthcare providers to move forward in an all-encompassing manner. The field of healthcare requires scientists to implement intelligent solutions into the daily routines of smart aging patients to improve the efficiency and precision of diagnostic and therapeutic procedures. The concept of smart aging refers to a program that makes it possible for elders to have a superior quality of life by embracing high-end technology solutions to diagnosis and disease. Healthcare technologies are a wide range of innovations, including connected devices, appliances, and procedures, as well as drugs, medicine, and vaccine that improve the level and quality of care provided at economic cost structures. The purpose of this study is to first present a listing of the principal technologies that underpin smart healthcare, and then to present it in several significant domains. After that, we elaborate on the issues that now exist with smart healthcare and attempt to provide potential solutions to these issues. In the final part of this chapter, we take a glance into the road ahead and assess the prospects of smart healthcare toward building a smart society 5.0. 2026 by Apple Academic Press, Inc. -
The Vital Role of Artificial Intelligence in the Dynamics of Human Resource Management
Human resources play a pivotal role in ensuring the growth of the organizations. Competency mapping, identifying skill gaps, and right talent identification are vital for enhancing the effective functioning of the organizations. As the organizations size increases, these functions become a challenge. In addition to managing the day-to-day operations, organizations are moving toward implementing effective processes for human resource development. Automating and adopting data-driven processes aids in transforming HR into an effective arm of the organization. The advent of artificial intelligence (AI) tools is becoming part of several organizations. These tools relieve HR personnel from spending time on routine tasks and drive them toward strategic decision-making. Organizations are finding AI is crucial in driving innovation in their business models. Thus, transforming processes and creating disruption are warranted to attain a competitive edge. The introduction of AI-driven systems in business organizations leads to significant changes in the demographic gambit of the workforce. It transforms the characteristics and significance of jobs and the relationship between employers and employees. The interaction between people and technology, and the customer experience in a rapidly changing market will be influenced by AI. The practices adopted by organizations in Middle East countries are also discussed. 2026 by Apple Academic Press, Inc. -
Navigating Prosperity: A Bibliometric Analysis of Financial Literacy and Sustainable Development Goals
The field of financial literacy and SDGs research has advanced significantly as countries place a greater emphasis on financial education and skill development. From 2017 to 2024, 1,017 SCOPUS papers were retrieved for this study. The study gives an overview of studies, trends, and future directions. The efficacy of financial literacy (FL), its impact on economic expansion, and its capacity to promote sustainable practices have all been extensively studied. Prospective pursuits involve advancing financial competencies and assessing their influence on income distribution, evaluating international cooperation initiatives, promoting environmentally friendly technologies, and designating green tax proceeds for environmental initiatives. The constantly growing corpus of research offers crucial direction for decision-makers dedicated to boosting FL and accomplishing Sustainable Development Goals (SDGs). 2026 by Apple Academic Press, Inc. -
Bibliometric Analysis on Multiobjective Optimization and Metaheuristic Algorithm
For difficult optimization issues, metaheuristic algorithms are effective methods for obtaining workable solutions quickly. In the past few years, continuous efforts have been put forward by researchers to develop new effective and robust metaheuristic algorithms for solving engineering optimization problems. The research aims to find the advancements made in multi-objective optimization and metaheuristic algorithms. Metadata of 4149 articles were extracted from Scopus from the year 2000 onward and bibliometric analysis was done with the help of the VOSviewer software. It was found that Mirjalili. S. has the highest number of citations (4011). IEEE Access has published the maximum number of documents (128), the University of Tehrans School of Industrial Engineering has contributed the most in this field of research (43 documents), and China has the most contribution among all the countries with 977 documents. In recent years, the terms optimization algorithms, exploration and exploitation, learning systems, decision-making, uncertainty analysis, sustainable development, supply chains, neural networks, forecasting, machine learning, and cloud computing are being mostly used by researchers. 2026 by Apple Academic Press, Inc. -
Unconventional Adjudication: Promise of Blockchain-Based Dispute Resolution
Blockchain technology is called disruptive technology. In the 1990s, the internet had the potential to revolutionize the entire industrial sector in the same way blockchain technology will change the face of society in the 2000s. Blockchain is the technology that also provides a platform for dispute resolution via smart contracts. The technology aims to create an anonymous and decentralized platform for transactions that do not require any state monitoring or intermediary. Blockchain is a decentralized network that generates an immutable record of transactions. A smart contract is a self-executing software application that executes a function automatically. When the prerequisites are met, the contract automatically takes effect. Blockchain-based dispute resolution (BDR) platforms provide services to resolve disputes resulting from blockchain and smart contract transactions, as well as traditional disputes unrelated to blockchain transactions. Blockchain-based DAO (decentralized autonomous organizations) are established, which are used to settle healthcare-related disputes between doctors, patients, insurance claims, etc. The blockchain platform offers unconventional processes for adjudication that are also distinct, unstructured, and unregulated. The platforms do not adhere to the accepted norms of alternative dispute resolution (ADR) and online dispute resolution (ODR) systems, raising concerns about the platforms authenticity and legitimacy, as well as the need for regulation. The purpose of this chapter is to examine the application of blockchain technology in dispute resolution and to comprehend regulatory issues. 2025 selection and editorial matter, Dr. Javaid Iqbal, Dr. Alwi M. Bamhdi, Dr. Bilal Ahmad Pandow, and Dr. Faheem Syeed Masoodi; individual chapters, the contributors. -
AI in Mechatronics Engineering
Robotic engineering, with a focus on the combination of artificial intelligence (AI) together with robotics, computers, electronics, and mechanical systems, as well as control system implementations, allows for many inventions. Key applications of AI in mechatronics engineering practice will be advanced production, intelligent robotics, predictive maintenance, and design optimization control. Robotics engineers are able to incorporate AI into their systems such that data can be collected, analyzed, and modeled, then used to enhance the dependability, flexibility, as well as performance of the systems. This chapter researches the engineering integration of AI along with mechatronics and the industries it is disrupting. Moreover, it addresses the basic definition of AI and its main application areas within mechatronics and its prospects toward enabling enhanced control systems, predictive maintenance, design optimization, intelligent robotics, and improved production in any contemporary industry. Such systems may be developed by mechatronics engineers due to the enriched capabilities of AI in data analysis, recognition, and decision-making. This study also addresses the limits and moral issues to the ethics of combining artificial and human power and suggests ideal steps for more study and advancement in the areas outlined. 2026 selection and editorial matter, Pushpalatha Naveenkumar, Vandana Sharma, Gunapriya Devarajan, Azween Abdullah, and Ahmed A. Elngar. -
Punishing poverty: The economic disparity of the poor in the criminal justice system
Equality before law is one of the most significant features of the Indian constitution. Anyone who seeks justice must be provided with legal support without any discrimination. An accused is also assured of penalization based on the tenets of equality irrespective of his ethnicity, religion, economic, social background, etc. Poor parity has led to discriminatory approaches in awarding punishments to offenders belonging to economically marginalised sections of society. The low paying capacity of the poor offenders gives an upper edge to the rich offenders who has better paying capacity of fines or damages and suffer less severe repercussions through the justice system. This paper will conduct a comprehensive study to identify the discrepancies in the penalization process and its implications in the dispensation of justice. It will also explore the factors such as social background, ethnicity, and economic status which play an integral part in influencing the legal and sociological perspectives of the stakeholders of the justice delivery system. It will analyze the judicial trend and legislative framework to ensure equitable justice. It will conclude with suggestions and recommendations for the formulation of robust policies to ensure a just penal administration. 2026 The Author(s). -
Smart Villages and Cities: A Sustainable Imperative for Emerging IndiaA Journey from Painful to Thoughtful
Smart cities and villages refer to making cities and villages more beautiful and fuller of all the requirements that can make the lives of the people living in the cities and villages more comfortable and satisfactory. On 25th June 2015, this initiative was launched by the Central government, and the time limit for completion was 5 years, but due to the pandemic situation, it was further extended by the central government, and this year, all the states are required to submit their respective report about the progress in this regard. In India, 70% of the total population lives in Villages and only 30% are part of urban areas. In India, villages should be a combination of smart and digital villages. If the work is done at the grassroots level, it will 436solve many problems, such as migration, employment, poverty, education, and medical facilities. Sustainability of the environment is one of the basic requirements for humankind globally. In 2015, the United Nations introduced Sustainable Development Goals (SDGs) to address environmental and economic issues and challenges and to provide and promote better and more sustainable pathways for the future generation globally. It is not a matter of concern for a group of countries, but every single species is affected by environmental issues. Owing to the dense population, infrastructure, buildings, and commercialization, cities are more prone and susceptible to the effects of climate change and natural disasters. while increasing the sustainability of urbanization processes is necessary to protect the environment, reduce the risk of disasters, and address climate change, building urban resilience is essential to preventing losses in terms of people, society, and the economy. Goal 11 of the SDGs deals with Sustainable Cities and Communities. Focusing more on urbanization in such a way that comprehensively controls and plans the development of cities and villages using different technologies and sciences to make them smart cities and villages. By ensuring that smart cities and villages will help us in many ways, they can control the migration of the human population from one city to another in search of employment and basic needs. In India, the government should focus on creating smart villages rather than smart cities. Around 69% of the population lives in the villages, and they do not have the basic amenities like electricity, clean drinking water, roads, transportation, and a source of employment. 2026 Jenny Stanford Publishing Pte. Ltd. -
Reengineering the Rural Economy by Leveraging the Use of Financial Services: A Lynchpin
Financial services form the bedrock of the economy, intricately woven into its fabric, exerting a profound influence on its dynamics and growth trajectory. Financial services play a momentous role in the complex web of global economies, delicately interlacing the strands of trade, capital accumulation, and risk mitigation. These services serve as an essential hub, linking people, companies, and governments in a complex web of exchanges and interactions, from the busy streets of big metropolises to the serene settings of rural villages. The chapter emphasizes the importance of financial services in promoting rural businesses by uplifting their stream of earnings by making use of emerging technologies. It also focuses on the challenges and opportunities faced by the rural population in obtaining financial assistance. The chapter also discusses the modern financial service schemes introduced so far for rural development and the suggestions for future implementation. The ways and means to mitigate shortcomings of the development of the rural business due to negligible awareness and restricted accessibility to financial services are also highlighted in the study. 2026 Jenny Stanford Publishing Pte. Ltd. All rights reserved.