Modelling Driver Behaviour at Urban Signalised Intersections Using Logistic Regression and Machine Learning

This study investigated several factors that may influence driver actions throughout the yellow interval at urban signalised intersections. The selected samples include 2,168 observations. Almost 33% of drivers stopped ahead of the stop line, 60% passed the intersection through the yellow interval, and 7% passed after the yellow interval was complete (red light running, RLR violations). Binary logistic regression models showed that the chance of passing went up as vehicle speed went up and down as the gap between the vehicle and the traffic light and green interval went up. The movement type and vehicle position influenced the passing probability, but the vehicle type did not. Moreover, multinomial logistic regression models showed that the legal passing probability declined with the growth in the green time and vehicle distance to the traffic signal. It also increased with the growth in the speed of approaching vehicles. Also, movement type directly affected the chance of legally passing, but vehicle position and type did not. Furthermore, the driver’s performance during the yellow phase was studied using the k-nearest neighbours algorithm (KNN), support vector machines (SVM), random forest (RF) and AdaBoost machine learning techniques. The driver’s action run prediction was the most accurate, and the run-on-red camera was the least accurate

Comparison of two methods for quantitative assessment of mandibular asymmetry using cone beam computed tomography image volumes

The aim of this study was to compare two methods of measuring mandibular asymmetry. The first method uses mirroring of the mandible in the midsagittal plane; the second uses mirroring of the mandible and registration on the cranial base

Assessment and Management of Atopic Dermatitis in Primary Care Settings

An increasingly common chronic inflammatory skin condition is atopic dermatitis (AD). It exhibits severe itching as well as recurring eczematous lesions. New difficulties for treatment selection and approach occur with the expansion of available therapy alternatives for healthcare professionals and patients.  The article highlights recent developments in scientific research on atopic dermatitis diagnosis and assessment that have led to the identification of novel therapeutic targets and the development of targeted therapies, both of which have the potential to completely change the way AD is treated, particularly in a primary care setting

Challenges and Risks Involved in Deploying 6G and NextGen Networks

Необходимо быть в курсе проблем, ожидающих нас в сетях следующего поколения (NextGen), чтобы предпринять надлежащие шаги для минимизации или устранения проблем по мере их возникновения. Этой цели послужит внедрение искусственного интеллекта в сетях NextGen для политики конфиденциальности и безопасности. Важно быть в курсе этих новых технологий и приложений, чтобы поддерживать безопасную связь в будущем.Проблемы и риски, связанные с развертыванием сетей 6G и NextGen исследуются стратегии проектирования и развертывания более защищенных и ориентированных на пользователя сетей NextGen с помощью искусственного интеллекта для улучшения пользовательского опыта. В нем дополнительно исследуются политические, социальные и географические проблемы, связанные с реализацией этих сетей 6G, и рассматриваются способы повышения безопасности будущих потенциальных приложений, а также защиты пользовательских данных от незаконного доступа. Этот крупный справочный труд, охватывающий такие темы, как алгоритмы глубокого обучения, свИспользуемые программы Adobe AcrobatThere is a need to be aware of the challenges awaiting us in next generation (NextGen) networks in order to take the proper steps to either minimize or eliminate issues as they present themselves. Incorporating artificial intelligence in NextGen networks for privacy and security policies will serve this purpose. It is essential to stay current with these emerging technologies and applications in order to maintain safe and secure communications in the future.Challenges and Risks Involved in Deploying 6G and NextGen Networks explores strategies for the design and deployment of more secured and user-centered NextGen networks through artificial intelligence to enrich user experience. It further investigates the political, social, and geographical challenges involved in realizing these 6G networks and explores ways to improve the security of future potential applications as well as protect user data from illegal access. Covering topics such as deep learning algorithms, aerial network communication, and edge comp

Challenges and risks involved in deploying 6G and NextGen networks Advances in wireless technologies and telecommunication (AWTT) book series./ A.M. Viswa Bharathy, Basim Alhadidi.

Includes bibliographical references and index."This book focuses on AI-enabled NextGen (6G and beyond) networks making readers aware of the challenges waiting in NextGen networks, so that proper steps could be taken to either minimize or eliminate issues on 6G and NextGen networks and incorporating AI in NextGen networks for privacy and security policies"--Chapter 1. Security and privacy policies in artificially intelligent 6G networks: risks and challenges -- Chapter 2. 6G and next gen networks with ultra-dense heterogeneous networks: system architecture, performance metrics -- Chapter 3. 6G-based undersea communication -- Chapter 4. AI-based wireless communication -- Chapter 5. AI-empowered 6G and next generation networks -- Chapter 6. Analysis of machine learning algorithms for efficient cloud and edge computing in the IoT -- Chapter 7. Augmentation of terahertz communication in 6G and its dependency for future state-of-the-art technology -- Chapter 8. Role of blockchain in security of 6G networks -- Chapter 9. Role of machine learning in 6G technologies: healthcare and education sectors -- Chapter 10. Security and privacy of unmanned aerial network communication systems in 6G networks -- Chapter 11. Technological and non-technical challenges associated with 6G networks -- Chapter 12. Defending IoT security infrastructure with the 6G network, and blockchain and intelligent learning models for the future research roadmap -- Chapter 13. Wireless brain-computer interface (WBCI) and 6G technology security issues, safety mechanisms -- Chapter 14. 6G: transformation of smart cities with blockchain and AI.1 online resource (xxii, 258 pages)

Donnan dialysis for tap-water softening

In this presentation, Abdusalam Alhadid, started by introducing the problem of hard water in both domestic and industrial applications,caused by an excess of calcium and magnesium ions. It significantly decreases thelifetime and efficiency of equipment which has negative technical and economic consequences. Existing water softening technologies have several disadvantages, such as a high chemical use (crystallization, ion exchange), water and energy consumption (nanofiltration