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Adaptive optimization with reinforcement learning for high utility itemset extraction
Extraction of High Utility Itemsets (HUI) plays a vital role in data mining that comprises several techniques developed to address it efficiently. However, when dealing with large itemsets and diverse items in a dataset, the problem's search space becomes notably complex and expansive. This makes the task of identifying HUIs more computationally expensive and time-consuming. In this paper, a novel Optimized Coverage list unit utilities-based High Utility Itemset (OCHUI) extraction approach is introduced for High Utility Itemset extraction. The extraction of high utility patterns and the extraction of qualified high utility itemsets are the two main processes in the suggested method. In the first step, high utility patterns are identified by mining metrics such as Redefined transaction-weighted utility, positive and negative Unit profit, Purchase quantity, and Coverage (RUPC) from the dataset. In the second step, qualified high utility itemsets are obtained optimally using an adaptive optimization algorithm called Cuckoo search Assisted Ant colony Optimization with Reinforcement Learning (CAAO-RL) is proposed. The Reinforcement Learning (RL) uses the On and Off policy method to intelligently leverage the tuning parameter of optimization. The RUPC model obtained the pattern score of 13600, runtime rate of 10.256 s and memory usage of 198 MB, respectively. 2025 Elsevier B.V. -
Adaptive Risk-Aware Ride Assignment (ARARA) Algorithm to Improve Efficiency to Lower Cancellation Rates in Bengaluru
Ride cancellations on urban mobility platforms like Rapido, OLA, Uber and other service provide platforms are negatively impacting user experience, driver earnings, and platform efficiency due to high cancellation of rides. This study addresses the challenge by developing a machine learning based adaptive userride matching algorithm that is trained on real world ride dataset from Bengaluru. The dataset includes features such as ride time, source, destination, distance, fare, payment method, and ride status. Through data preprocessing and feature engineering, key patterns influencing ride cancellations are identified. A classification model is developed to predict the likelihood of cancellation before ride assignment by using few Machine learning models among various model XGBoost and Logistic Regression outperformed with nearly 9 0% accuracy. Later to enhance the performance in allocation based on cancellation prediction the ARARA algorithm suggests that reallocates rides dynamically based on cancellation risk using inference and assignment Algorithm. Experimental results shows that how to reduce cancellation rates and improved accuracy by choosing best allocation based on top three best captains for allocation to optimize chances of cancellation. This framework can be integrated by ride platforms to enhance service reliability and optimize fleet efficiency. 2025 IEEE. -
Adaptive uplink scheduling model for WiMAX network using evolutionary computing model
The increased usage of smart phones has led to increase usage an internet based application services. These application requires different quality of service (QoS) and bandwidth requirement. WiMAX is an efficient network to provision high bandwidth connectivity and coverage to end user. To meet QoS requirement the exiting model used adaptive model selection scheme. However, these model induce bandwidth wastage as it does not considers any feedback information for scheduling. This work present an Adaptive Uplink Scheduling (AUS) by optimizing MAC layer using Multi-Objective Genetic Algorithm (MOGA). The MAC scheduler use feedback information from both physical layer and application layer. Further, to meet QoS requirement of application and utilize bandwidth efficiently this paper presented an adaptive modulation selection scheme based on user application requirement using MOGA. Our model provides application level based QoS provisioning for WiMAX network. Experiment are conducted to evaluate performance of AUS over exiting model. The overall result attained shows AUS model attain good performance in term of throughput, successful packet transmission and packet collision. 2019 Institute of Advanced Engineering and Science. All rights reserved. -
AdaptiveNet: A Novel Architecture for Reducing Computation Complexity to Fake Review Classification
The exponential rise of e-commerce platforms has resulted in a dramatic increase in online reviews, which creates a challenge in distinguishing fake reviews that erode consumer confidence and harm commerce ecosystems. Traditional approaches for fake review detection employ computationally expensive deep learning networks which are resource-intensive and difficult to use in practice. In this paper, we describe AdaptiveNet, a new lightweight neural architecture that achieves fake review detection with much lower computational resources while maintaining a higher detection and classification precision. The model proposed in this paper is based on three original innovations: a Multi-Scale Semantic Fusion (MSSF) layer for hierarchical feature extraction, Dynamic Attention Scaling (DAS) with complexity measure attention, and Adaptive Parameter Sharing (APS) context-gated networks. With thorough evaluation on Amazon, Yelp, and TripAdvisor datasets of reviews totalling 1.2 million reviews, AdaptiveNet attains 94.8% accuracy while achieving 65% computational overhead in comparison to traditional models. The architecture outperformed all other state-of-the-art models, BERT-base (92.1%), RoBERTa (91.8%), and other more recent efficient models, requiring 70% lower parameters and 60% lower energy consumption. This work markedly advances the other efficient deep learning architectures for text classification and allows for the practical implementation of fake review detection systems in resource-limited settings as process innovation. 2026 by the authors. -
Addiction treatment in India: Legal, ethical and professional concerns reported in the media
As per the Magnitude of Substance Use in India 2019 survey report, over 57 million of the Indian population is in need of professional help for alcohol use disorders and around 7.7 million for opioid use disorders. The increasing demand for addiction treatment services in India calls for professionalising every aspect of the field. Frequent human rights violations and various unethical practices in Indian addiction treatment facilities have been reported in the mass media. This study is a content analysis of newspaper reports from January 1, 2016 to December 31, 2019 looking into legal, ethical and professional concerns regarding the treatment of substance use disorders in India. The content analysis revealed various human rights violations, the use of improper treatment modalities, the lack of basic facilities at treatment settings, and the presence of unqualified professionals in practice. Indian Journal of Medical Ethics 2021. -
Additively Composite Model Objective Function for Routing Protocol for Low-Power and Lossy Network Protocol
The Internet of Things (IoT) networks always operate within the context of diverse and constrained characteristics of the devices. Low-Power and Lossy Networks (LLNs) constitute a network architecture commonly utilized in IoT application deployments, facilitating networking and the establishment of paths for data transmission. The Routing Protocol for Low-Power and Lossy Networks (RPL) demonstrates promising capabilities for LLN network operations, supporting IPv4 and IPv6-enabled services. The RPL protocol constructs a Destination Oriented Directed Acyclic Graph (DODAG) logical routing topology based on defined Objective Function (OF) metrics. Routing operations within the DODAG utilize these metrics and constraints to select parent nodes and calculate optimal routes between two nodes. Standardized OFs have traditionally focused on either parent node selection or routing objectives within the DODAG, often treating load balancing and bottleneck optimization separately. However, their combined impact on RPL's effectiveness has been overlooked. This paper introduces an Adaptively Composite Objective Function (AC-OF) approach that considers the combined objectives of DODAG load balancing and optimized routing operations. Through simulation evidence, the paper presents improved network parameters. The AC-OF implementation brings out significant results in the form of a balanced DODAG topology and it has good impacts on data transmission, control overhead messages, parent switching, delay, energy consumption, and node lifetime. 2024 Totem Publisher, Inc. All rights reserved. -
Addressing B5G and 6G Network Connectivity Issues and Challenges in Rural Regions of India
The emerging technology of the fifth-generation broadband cellular network is already ruling the market with its efficiency, lower latency, higher connectivity, and many more features. In contrast, the sixthgeneration broadband cellular network is yet in its research and development stage. These technologies cannot only revolutionize the world with their features, such as high speed and enhanced cybersecurity but also empower it to reach greater heights. To understand the network requirements of the rural and under-developed areas, it is important to understand all those challenges in the way ahead.. Launching such efficient and effective technologies in rural areas would benefit the country as well as its economic growth. The large markets of these cellular networks are at constant growth and are expected to be booming in the future of the Telecom Regulatory Authority of India. (2023, September 29).. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Addressing B5G and 6G Network Connectivity Issues in Rural Regions
As regions move towards the next generation of wireless technology, addressing connectivity challenges in rural regions is critical for the development of Beyond 5G (B5G) and 6G networks. While urban areas may benefit from the advanced capabilities of these technologies, rural communities face significant barriers to accessing high-speed, reliable internet. These challenges, including limited infrastructure, geographical constraints, and financial obstacles, hinder economic development, education, and healthcare opportunities in rural areas. To bridge this digital divide, innovative solutions in network design, spectrum management, and infrastructure investment are essential. By addressing these connectivity issues, B5G and 6G networks have the potential to create inclusive, equitable access to new services and opportunities for rural populations. Addressing B5G and 6G Network Connectivity Issues in Rural Regions explores the transformative potential of advanced networking technologies in rural settings. It delves into the pressing issue of connectivity challenges faced by rural communities and outline how emerging B5G and 6G networks can address these obstacles. This book covers topics such as digital technology, policymaking, and social inclusion, and is a useful resource for communications professionals, business owners, engineers, economists, academicians, researchers, and scientists. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Addressing challenges and opportunities in enhancing water quality for irrigation
The rapidly changing quality of irrigation water is a pressing issue that needs to be addressed in order to understand and predict the long-term effects on soils and crops in a world that is facing increasing water stress. The use of irrigation in agriculture is becoming increasingly reliant on sources of water that are poorly understood and largely unmonitored. This trend has led to a decline in water and soil quality in many areas. While soil salinization and reduced crop productivity have traditionally been the main concerns when it comes to the quality of irrigation water, there is now evidence that geogenic contaminants, such as trace elements and an increase in the use of wastewater, are also affecting irrigation water quality. The ability to measure extremely small concentrations of biologically-active organic contaminants, including plasticizers, pharmaceuticals, personal care products, and steroid hormones, in various irrigation water sources allows us to evaluate their uptake and occurrence in crops. However, it does not address questions related to food safety or the potential health effects on humans. Additionally, natural and synthetic nanoparticles are now known to be present in many water sources, which may alter plant growth and impact food standards. 2023 Author(s). -
Addressing harassment against men through the lens of gender equality in India: A critical analysis /
Harassment refers to harassment derives from the English verb harass plus the suffixment. The verb harass, in turn, is a loan word from the French, which was already attested in meaning torment, annoyance, bother, trouble.1 It refers to when an individual continually performs undesirable behaviour against a victim. This may include offensive language, rude and cruel remarks, but it must continue over time in order then it is considered as harassment. Harassment has many types like sexual harassment, mental harassment; workplace harassment, domestic harassment and many more it cover wide range of offence Harassment. Harassment against men is a serious issue that needs to be addressed in India, just as harassment against women does. It is important to approach this issue through the lens of gender equality, as both men and women should have the right to live free from harassment and violence. To start with, it is important to acknowledge that men can be victims of harassment and violence, and that this issue is not limited to women alone. -
Addressing psychosocial problems associated with the COVID-19 lockdown
The lockdown imposed by the governments of various countries to contain the spread of the coronavirus disease (COVID-19) is associated with various psychosocial problems. The complications within the family and time management issues that can occur during this time period are explored. The stigma and anxiety associated with the coronavirus disease are also addressed. It is noted that the problems faced by vulnerable communities including individuals with substance use disorder (SUD) tend to be ignored. These crucial areas that psychologists and mental health professionals should consider before providing intervention are discussed. 2020 Elsevier B.V. -
Addressing quarter life crisis as a public health priority
The Quarter-Life Crisis (QLC), a period of intense self-doubt, anxiety, and identity confusion during early adulthood has become a widespread phenomenon affecting mental health and well-being globally. In the Indian context, this phase is further shaped by cultural expectations, economic uncertainty, and social transitions that shape young adults sense of purpose and stability. Although often discussed in psychological and sociological terms, the QLC remains under-addressed in public health discourse. This perspective paper argues for the recognition of QLC as a legitimate public health issue with cross-sector implications. Economic precarity, including unstable employment, student debt, and housing insecurity, plays a critical role in exacerbating this crisis, making it not only a psychological experience but also a condition influenced by broader socioeconomic and cultural forces. Drawing on developmental psychology, sociocultural theory, and the framework of the Sustainable Development Goals (SDGs), this paper situates the Quarter-Life Crisis within Indias evolving social landscape and examines it as a social determinant of mental health. It further highlights community-based and digital interventions, such as resilience and self-compassion apps, that can support young adults. Integrating QLC into public health frameworks particularly those focused on Good Health and Well-Being (SDG 3) can offer timely, systemic solutions to a rising mental health concern among Indias youth and the global young adult population. The Author(s) 2026. -
Addressing Security Challenges in AI-Driven Cyber Security: Enhancing Resilience While Fostering Sustainable Practices with Green Computing
The modern cyber security environment changed through increased sophistication and complexity of cyber threats that requires organizations to use artificial intelligence (AI) technologies for strengthened security frameworks. It also limits the adverse impact within the populace by a decrease in carbon dioxide emissions, energy conservation, decrease wastage of electronic gadgets and assistance to sustainability with renewable resources. Among the practices of creating the green environment are the measures of virtualization, improving the quality of the hardware to increase the energy efficiency and using the cooling technologies efficiently. The Sustainable Cyber security practices are examining the measures and innovation for minimizing energy usage by integrated cyber security tools/infrastructure, green data center/network, and practicing green software engineering. In this domain, Sustainability Cyber security employs energy conservative cryptographic algorithms and software architecture, low energy cryptographic physical devices, power-conscious security protocols; efficient virtualization by integrating these approaches, they can advance sustainability into higher security statures. Besides, the enforcement of those security practices will help to address green data center objectives like server virtualization, and other efficiency data storage products. Cyber Security algorithms will act to lessen the time construct of cryptographic operations to less computational power, and hence less energy consumption. It also looks at the direction that sustainability is likely to take in the future, which may include such policies and structures as are likely to promote green computing in cyber security. Also through this case study, we have been able to incorporate green computing into its cyber security programs for a better and environmentally friendly future. The advanced strategic planning through automation enables organizations to develop stronger defense capabilities as they adjust to security threats which keep evolving in the present-day landscape. 2026 Scrivener Publishing LLC. -
Addressing the complexities of postoperative brain MRI cavity segmentationa comprehensive review
Postoperative brain magnetic resonance images (MRI) is pivotal for evaluating tumor resection and monitoring post-surgical changes. The segmentation of surgical cavities in these images poses challenges due to artifacts, tissue reorganization, and heterogeneous appearances. This study explores challenges and advancements in postoperative brain MRI segmentation, examining publicly accessible datasets and the efficacy of various deep learning models. The analysis focuses on different U-Net models (U-Net, V-Net, ResU-Net, attention U-Net, dense U-Net, and dilated U-Net) using the EPISURG dataset. The training dice scores are as follows: U-Net 0.8150, attention U-Net 0.8534, V-Net 0.7602, ResU-Net 0.7945, dense U-Net 0.83, dilated U-Net 0.80. The study thoroughly assesses existing postoperative cavity segmentation models and proposes a fine-tuning approach to enhance the performance further, particularly for the best-performing model, attention U-Net. This fine-tuning involves introducing dilated convolutions and residual connections to the existing attention U-Net model, resulting in improved results. These improvements underscore the necessity for ongoing research to select and adapt efficient models, retrain specific layers with a comprehensive collection of postoperative images, and fine-tune model parameters to enhance feature extraction during the encoding phase. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Addressing the Problems of Forest and Biodiversity in Developing Nations: A Conservation Conundrum
Forests and biodiversity are essential for ecological stability and human well-being, but they confront unprecedented threats in developing countries. This chapter investigates the multifaceted interactions among environmental decline, socio-economic stresses, inadequate governance, and global market forces that drive biodiversity loss and deforestation. It underscores the difficulties of reconciling development with conservation in areas characterized by poverty, land tenure disputes, and weak institutions. The chapter emphasizes the necessity for methods that are integrated, participatory, andequitable throughan examination oflocaland global frameworks, such as community-based conservation, indigenous knowledge, and international agreements. Case studies demonstrate conservation initiatives that succeeded and others that did not, providing vital perspectives on the future of biodiversity governance. In conclusion, the chapter calls for global cooperation, inclusive policy frameworks, and context-specific strategies to ensure sustainable management of forests and biodiversity. Copyright 2026 by IGI Global Scientific Publishing. -
Addressing the psychiatric implications of AI-enabled non-consensual sexual imagery
[No abstract available] -
Addressing Violence Against Women as a Global Public Health Emergency
A major global public health concern, violence against women (VAW) is a widespread violation of human rights. VAW is framed as a worldwide public health issue that goes beyond personal injury to cause long-term physical, psychological and socioeconomic repercussions that jeopardize country development and community well-being. VAW increases their risk of harm, problems with their reproductive systems, mental health issues, and even death. These consequences put a burden on healthcare systems around the globe. Through the shadow pandemic, where lockdowns increased domestic abuse and limited survivors' access to necessary resources, the COVID-19 pandemic highlighted these vulnerabilities. An integrated, multisectoral strategy that incorporates community awareness, survivor-centered health care, legal reforms, and international collaboration is needed to address VAW as a public health emergency. Placing VAW within public health frameworks emphasizes the necessity of prevention, protection, and accountability measures for long-term social justice and gender equality. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Adherence to the WHO Guidelines on Suicide Reporting: A Content Analysis from Bengaluru, India
Background: Media, with its power to influence the masses, is found to have an impact on how the readers perceive suicide, and evidence suggest that suicidal behavior is contagious. However, studies have shown that it is possible to intervene by implementing media guidelines for suicide reporting. Unfortunately, the guidelines are mostly not being adhered to by the media. The current study attempts to assess if there has been any change in reporting after the Press Council of India issued guidelines on suicide reporting in 2019. Methodology: Content analysis of the newspaper articles reporting on suicide was done for 3 months (October 1, 2019, to December 31, 2019). Nineteen newspapers published in Bengaluru, Karnataka, were selected for the study based on the language and readership. These included six English, five Kannada, two Malayalam, two Hindi, two Tamil, and two Telugu newspapers. A total of 1198 reports were found and analyzed. Results: The study found that the majority of the reports did not adhere to the guidelines. It was observed that the news reports on suicide mostly resorted to sensationalization. Majority of the reports portrayed suicide in a harmful manner by mentioning the suicide method and the site in detail and focused on monocausal explanations. The significant connection between suicide and mental illness was also overlooked. Conclusion: Irresponsible reporting of suicide creates risks for the public and collaborative efforts should be designed to decrease the negative impact media can have on suicide prevention initiatives. 2025 Indian Journal of Social Psychiatry. -
Adhesion strength studies on zirconia based pyrochlore and functionally gradient thermal barrier coatings
Thermal Barrier Coating (TBC) plays a major role in the improvement of gas turbine and engine components in terms of their service life and performance. Generally, all coatings must possess certain primary properties to perform in the intended applications. However, regardless of applications, suitable adhesion strength is one major characteristic they must have to adequately protect the basic components on which they are applied upon. In TBCs, adhesion (or Bond) strength is a parameter that helps to illustrate the resistance of the ceramic top coat against spallation either from the bond coat (and component) or within the TBC layers itself. The performance of TBCs are reliant upon the adhesion between the coating and the metal substrate and also adhesion (or cohesion) between the bond coat and the overlying ceramic top coat layer. The de-bonding of the top coat layer or the inter-metallic bond coat layers are the main reasons of the failure of the overall TBC system. Some of the prominent problems associated with coatings applications are residual stresses, micro-cracks and pores etc. These and many other factors influence the adhesion of the coatings in addition to service environment conditions and pre coating substrate preparations such as substrate cleaning, grit blasting and very importantly plasma spray parameters. In the present work, results obtained from adhesion strength measurements carried out by following the ASTM C 633 standard test method, on various types of TBCs are being shared. Thermal barrier coatings (TBCs) were synthesized with NiCrAlY bond coat deposited on SS 304L substrate by using air plasma spray and different ceramic top coats (a) commercial 8%Yttria Stabilized Zirconia (8YSZ) (b) lab synthesized plasma spray powders of (i) Lanthanum Zirconate (La2Zr2O7) (ii) Lanthanum Ceria Zirconate (La2 (Zr0.7Ce0.3)2O7) and (iii) Lanthanum cerate (La2Ce2O7). The coating depositions were carried out in different configurations i.e. two layers, three layers and gradient layers (Functionally gradient materials). The evaluation of properties includes the studies of morphology of the strength (adhesive/cohesive failure mode) tested specimen as well. General conclusions drawn from the studies on several specimen in various configurations are that cohesive failures (between the ceramic top coat layers) is the predominant mechanisms followed by few adhesive failures in bond coat coat/ceramic interface. 2019 Elsevier Ltd. All rights reserved.