Artificial Intelligence And Online Engineering
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Artificial Intelligence and Online Engineering
Nowadays, online technologies are the core of most fields of engineering and the whole society and are inseparable connected for example with Internet of Things & Industrial Internet of Things (Industry 4.0), Online & Biomedical Engineering, Data Science, Machine Learning, and Artificial Intelligence, Cross & Mixed Reality, and Remote Working Environments. to name only a few. Since the first REV conference in 2004, we tried to focus on the upcoming use of the Internet for engineering tasks and the opportunities as well as challenges around it. Consequently, the motto of this year’s REV2022 was “Artificial Intelligence and Online Engineering”. In a globally connected world, the interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In response to that, the general objective of this conference is to contribute and discuss fundamentals, applications, and experiences in the field of Online and Remote Engineering, Virtual Instrumentation and other related new technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber-Security, and M2M & Smart Objects. Another objective of the conference is to discuss guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs & MOOLs, and Open Resources. REV2022 was the 19th in a series of annual events concerning the area of Online Engineering. It has been organized in cooperation with The British University in Egypt (BUE), Cairo, as a hybrid event from February 28 until March 02, 2022.
Artificial Intelligence Law
Author: Edward Swan
language: en
Publisher: Kluwer Law International B.V.
Release Date: 2024-03-18
It is inevitable, given the enormous media-driven concern generated by the recent application of artificial intelligence (AI) to an ever-expanding spectrum of day-to-day human experience, that the need for a clearly articulated legal response has become imperative. This book both clarifies the controversial issues surrounding the use of AI and explores in great detail how, far from being “unregulated,” the creation, distribution, and operation of AI systems currently is, and will remain, subject to a vast array of existing laws and regulations all over the world. Demonstrating beyond any doubt that the traditional concepts of legal responsibility, including duty of care, negligence, and compensation for damages, will always be applicable to those humans who create and/or use artificially intelligent things or systems, the author shows how AI systems are clearly implicated in numerous existing legal regimes, including the following: relevant provisions under international law and EU law; applicable provisions in the laws of the United States, the United Kingdom, France, China, India, Japan, South Korea, and Singapore; and numerous national provisions in the legal fields of health and safety, intellectual property, competition, privacy and data protection, and military engagement. However, given the lack of international consensus on this vitally important issue, the author suggests that any worldwide agreement on the legal responsibilities relating to the use of AI will need to be carefully defined, and that provisions will need to be reviewed to determine how they will apply to any new range of artificially intelligent creations. The purpose of this book is to review those legal concepts, throughout the world, that currently govern the application of AI and to comment on modifications or extensions of the rule of law that are being proposed as necessary to serve and protect humanity in relation to the expanding applications of AI. It is important that anyone who uses or is affected by AI products understands the relationship between existing laws and regulations in major markets around the world and those areas where initial regulations may be required. For them, for their counsel, and for the various policy and regulatory authorities confronted with AI issues, this book will prove an essential guide.
Algorithms in Advanced Artificial Intelligence
The most common form of severe dementia, Alzheimer’s disease (AD), is a cumulative neurological disorder because of the degradation and death of nerve cells in the brain tissue, intelligence steadily declines and most of its activities are compromised in AD. Before diving into the level of AD diagnosis, it is essential to highlight the fundamental differences between conventional machine learning (ML) and deep learning (DL). This work covers a number of photo-preprocessing approaches that aid in learning because image processing is essential for the diagnosis of AD. The most crucial kind of neural network for computer vision used in medical image processing is called a Convolutional Neural Network (CNN). The proposed study will consider facial characteristics, including expressions and eye movements using the diffusion model, as part of CNN’s meticulous approach to Alzheimer’s diagnosis. Convolutional neural networks were used in an effort to sense Alzheimer’s disease in its early stages using a big collection of pictures of facial expressions.