الصفحة 3
الصفحة 3
Agent-mediated electronic commerce : automated negotiation and strategy design for electronic markets : AAMAS 2006 workshop, TADA/AMEC 2006, Hakodate, Japan, May 9, 2006 : selected and revised papers
The design and an alysis of trading agents and electronic trading systems in which they are deployed involve finding solutions to a diverse set of problems, invo- ing individual behaviors, interaction, and collective behavior in the context of trade. A wide variety of trading scenarios and systems, and agent approaches to these, have been studied in recent years. The AMEC series of wo- shops presents interdisciplinary researchon both theoretical and practical issues of agent-mediated electronic commerce ranging from the design of electronic marketplaces and e?cient protocols to behavioral aspects of agents operating in suchenvironments.
Advances in Swarm Intelligence ; 11th International Conference, ICSI 2020, Belgrade, Serbia, July 14–20, 2020, Proceedings
Constitutes the proceedings of the 11th International Conference on Advances in Swarm Intelligence, ICSI 2020, held in July 2020 in Belgrade, Serbia. Due to the COVID-19 pandemic the conference was held virtually. The 63 papers included in this volume were carefully reviewed and selected from 127 submissions. The papers are organized in 12 cohesive topical sections as follows: Swarm intelligence and nature-inspired computing; swarm-based computing algorithms for optimization; particle swarm optimization; ant colony optimization; brain storm optimization algorithm; bacterial foraging optimization; genetic algorithm and evolutionary computation; multi-objective optimization; machine learning; data mining; multi-agent system and robotic swarm, and other applications.
Advanced technique and future perspective for next generation optical fiber communications
Optical fiber communication industry has gained unprecedented opportunities and achieved rapid progress in recent years. However, with the increase of data transmission volume and the enhancement of transmission demand, the optical communication field still needs to be upgraded to better meet the challenges in the future development. Artificial intelligence technology in optical communication and optical network is still in its infancy, but the existing achievements show great application potential. In the future, with the further development of artificial intelligence technology, AI algorithms combining channel characteristics and physical properties will shine in optical communication. This reprint introduces some recent advances in optical fiber communication and optical network, and provides alternative directions for the development of the next generation optical fiber communication technology.
Advanced parallel processing technologies ; 7th International Symposium, APPT 2007 Guangzhou, China, November 22-23, 2007 Proceedings
APPT was upgraded to the International Symposium on Advanced Parallel Processing Technologies. However, it kept its traditional flavor by sharing of the underlying theories and applications, and the establishment of new and long-term collaborative channels. And it will continue to provide a forum for researchers, professionals, and industrial practitioners from around the world to report on new advances in high-performance architecture and software, as well as to identify issues and directions for research and development in the new era of evolving technologies.
Ad-hoc Networks : Fundamental Properties and Network Topologies
This book clearly demonstrates how the Medium Access Control protocols impose a limit on the level of interference in ad-hoc networks. It has been shown that interference is upper bounded, and a new accurate method for the estimation of interference power statistics in ad-hoc and sensor networks is introduced here. Furthermore, this volume shows how multi-hop traffic affects the capacity of the network. In multi-hop and ad-hoc networks there is a trade-off between the network size and the maximum input bit rate possible per node. Large ad-hoc or sensor networks, consisting of thousands of nodes, can only support low bit-rate applications.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
3D Imaging, Analysis and Applications
This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops.
