الصفحة 33
الصفحة 33
Chance Discoveries in Real World Decision Making : Data-based Interaction of Human intelligence and Artificial Intelligence
For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc.
Challenges in Ad Hoc Networking ; 4th Annual Mediterranean Ad Hoc Networking Workshop, June 21-24, 2005, Île de Porquerolles, France
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research.
Challenges for Computational Intelligence
Computational Intelligence (CI) is used as a name to cover many existing branches of science, with artificial neural networks, fuzzy systems and evolutionary computation forming its core. In recent years CI has been extended by adding many other subdisciplines and it became quite obvious that this new field also requires a series of challenging problems that will give it a sense of direction. Without setting up clear goals and yardsticks to measure progress on the way many research efforts are wasted.The book written by top experts in CI provides such clear directions and the much-needed focus on the most important and challenging research issues, showing a roadmap how to achieve ambitious goals.
Cellular Automata and Discrete Complex Systems ; 26th IFIP WG 1.5 International Workshop, AUTOMATA 2020, Stockholm, Sweden, August 10–12, 2020, Proceedings
This volume constitutes the refereed post-conference proceedings of the 26th IFIP WG 1.5 International Workshop on Cellular Automata and Discrete Complex Systems, AUTOMATA 2020, held in Stockholm, Sweden, in August 2020. The workshop was held virtually. The 11 full papers presented in this book were carefully reviewed and selected from a total of 21 submissions. The topics of the conference include dynamical, topological, ergodic and algebraic aspects of CA and DCS, algorithmic and complexity issues, emergent properties, formal languages, symbolic dynamics, tilings, models of parallelism and distributed systems, timing schemes, synchronous versus asynchronous models, phenomenological descriptions, scientific modeling, and practical applications.
Case-Based Approximate Reasoning
Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'. Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.
Case based design : Applications in process engineering
The book by Professors is an impressive and in-depth treatment of the essence of the case–based reasoning strategy and case-based design dwelling upon the algorithmic facet of the paradigm, the authors provided an excellent applied research framework by showing how this development can be effectively utilized in real word complicated environment of process engineering.
Cartoony story app = تطبيق قصة كارتونية
The translation of textual narratives into immersive visual representations poses a significant challenge in the field of artificial intelligence. Traditional cartoon generation techniques face formidable technical challenges and require substantial resources. Research efforts towards direct video synthesis from text have encountered obstacles in developing efficient techniques. In parallel, researchers propose an alternative approach involving the generation of dynamic sequences of images portraying children's story narratives. This approach includes applying various visual effects to highlight motion, interaction, and excitement in storytelling. By dynamically generating a sequence of images reflecting the narrative's progression and applying diverse visual effects, this alternative method offers a flexible and practical solution to cartoon generation challenges, providing an efficient and effective experience akin to video while retaining the magical appeal of visual storytelling. ...
Carpooling optimization
The aim of this project is to collect and use the GPS data from mobile devices to get geolocations and translate this data to paths, starting points and destinations to detect patterns out of each individual trajectories that have stochastic nature on the close sight and find representations of those patterns. The second half of the artificial intelligence algorithms has the task of finding the optimal matching of the patterns that were detected in a computation efficient way that achieve the most efficient way of transportation.
Car deal : The ultimate used-cars marketplace
This is an effort to represents the design and implementation of a mobile application that serves as a marketplace for buying and selling used cars. The application is developed using Flutter, a popular cross-platform framework, and integrates an Artificial Intelligence (AI) model to predict the price of used cars based on various parameters, such as the car's model, age, mileage, and condition. The report provides a comprehensive overview of the project's development process, including the use of agile methodology and various technologies, such as Firebase, Python, and TensorFlow. The AI model's accuracy is evaluated using statistical metrics, such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE).
Canadian Semantic Web
This book covers a variety of well known topics of interest to practitioners in industry and research scientists. The range of topics includes languages, tools and methodologies for the semantic Web, semantic Web-based ontology management and engineering, semantic Web services, practical applications of the semantic Web techniques, artificial intelligence methods and tools for the semantic Web, software agents on the semantic Web, visualization and modeling of the semantic Web. The goal of this book is to provide a state-of-the-art review of the research as well as to introduce topics of interest to experts.
CADD and informatics in drug discovery
Updates knowledge on recent advances in computational and bioinformatics tools/techniques and their practical applications in modern drug design and discovery programme. Also it encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas / presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, RandD personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, De-novo drug design, Pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and system biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to different stakeholders working in the pharmaceutical and biotechnology industries (RandD), the academic as well as research sectors. .
Browning Agents and Active Particles : Collective Dynamics in the Natural and Social Sciences
Lays out a vision for a coherent framework for understanding complex systems'' (from the foreword by J. Doyne Farmer). By developing the genuine idea of Brownian agents, the author combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. This way, an efficient method for computer simulations of complex systems is developed which is also accessible to analytical investigations and quantitative predictions. The book demonstrates that Brownian agent models can be successfully applied in many different contexts, ranging from physicochemical pattern formation, to active motion and swarming in biological systems, to self-assembling of networks, evolutionary optimization, urban growth, economic agglomeration and even social systems.
Brilliantguard : AI-powered healthcare prototype for mobile & automotive integration
Brilliantguard is an AI-powered healthcare and safety prototype designed to support individuals with special needs, the elderly users, and patients with chronic conditions such as alzheimer’s disease. The system integrates augmented reality (AR), an AI based chatbot, and bitcoin-based payments into a unified platform combining mobile apps, smartwatches, and automotive sensors. It enables real-time health monitoring, predictive alerts with preliminary health suggestions, medication reminders, initial fault detection, and geofencing-based tracking for alzheimer’s patients. Emergency alerts are automatically triggered in response to abnormal health readings or car crashes.
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ; 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I
The content of thebook covers the current state-of-the-art literature on federated learning applications for cancer research and Vclinical oncology analysis, as well as an overview of the deep learning approaches improving the current standard of care for brain lesions and current neuroimaging challenges. It is also focusing on the accepted BrainLes workshop submissions, is to provide an overview of new advances of medical image analysis in all the aforementioned brain pathologies. It brings together researchers from the medical image analysis domain, neurologists, and radiologists working on at least one of these diseases. The aim is to consider neuroimaging biomarkers used for one disease applied to the other diseases.
Brain-inspired computing ; 4th International Workshop, BrainComp 2019, Cetraro, Italy, July 15–19, 2019, Revised Selected Papers
The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
Brain, vision, and artificial intelligence ; 1st International Symposium, BVAI 2005, Naples, Italy, October 19-21, 2005, Proceedings
This book constitutes the refereed proceedings of the First International Symposium on Brain, Vision and Artificial Intelligence, BVAI 2005, held in Naples, Italy in October 2005. The 48 revised papers presented together with 6 invited lectures were carefully reviewed and selected from more than 80 submissions for inclusion in the book. The papers are addressed to the following main topics and sub-topics: brain basics - neuroanatomy and physiology, development, plasticity and learning, synaptic, neuronic and neural network modelling; natural vision - visual neurosciences, mechanisms and model systems, visual perception, visual cognition; artificial vision - shape perception, shape analysis and recognition, shape understanding; artificial inteligence - hybrid intelligent systems, agents, and cognitive models.
Brain Dynamics : Synchronization and Activity Patterns in Pulse-Coupled Neural Nets with Delays and Noise
This book addresses a large variety of models in mathematical and computational neuroscience.He devotes the main part to the synchronization problem. He presents neural net models more realistic than the conventional ones by taking into account the detailed dynamics of axons, synapses and dendrites, allowing rather arbitrary couplings between neurons. He gives a complete stabile analysis that goes significantly beyond what has been known so far. He also derives pulse-averaged equations including those of the Wilson--Cowan and the Jirsa-Haken-Nunez types and discusses the formation of spatio-temporal neuronal activity pattems. An analysis of phase locking via sinusoidal couplings leading to various kinds of movement coordination is included.
Brain dynamics : An introduction to models and simualtions
Brain Dynamics serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. Some of the advanced chapters will also be of interest to the specialists. The book approaches the subject through pulse-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. Topics also include pulse-averaged equations and their application to movement coordination. The book closes with a short analysis of models versus the real neurophysiological system.
Boosting Collaborative Networks 4.0 ; 21st IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2020, Valencia, Spain, November 23–25, 2020, Proceedings
This book constitutes the refereed proceedings of the 21st IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2020, held in Valencia, Spain, in November 2020. The conference was held virtually. The 53 full papers were carefully reviewed and selected from 135 submissions. They provide a comprehensive overview of major challenges and recent advances in various domains related to the digital transformation and collaborative networks and their applications with a strong focus on the following areas related to the main theme of the conference: collaborative business ecosystems; collaborative business models; collaboration platform; data and knowledge services; blockchain and knowledge graphs; maintenance, compliance and liability; digital transformation; skills for organizations of the future
Bone remodeling and osseointegration of implants
Provides an insight into the latest advances in bone fracture healing and remodeling algorithm and their incorporation into patient-specific finite element models and the use of machine learning and artificial intelligence to predict the bone regeneration and osseointegration process with a certain degree of accuracy. It also examines the applications of numerical models to simulate the fracture healing process, which may prove to be advantageous in determining the optimal mechanical-based treatment or reconstruction after an accident or illness.
