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Classification of covid-19 in lung images
The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global economy. It is critical to detect the positive cases as early as possible so as to prevent the further spread of this epidemic and to quickly treat affected patients. The need for auxiliary diagnostic tools has increased as there are no accurate automated toolkits available. Recent findings obtained using radiology imaging techniques suggest that such images contain salient information about the COVID-19 virus. Application of advanced artificial intelligence (AI) techniques coupled with radiological imaging can be helpful for the accurate detection of this disease, and can also be assistive to overcome the problem of a lack of specialized physicians in remote villages.
Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.
Classification and Learning Using Genetic Algorithms : Applications in Bioinformatics and Web Intelligence
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries, and it demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains.
Chinese Computational Linguistics ; 19th China National Conference, CCL 2020, Hainan, China, October 30 – November 1, 2020, Proceedings
This book constitutes the proceedings of the 19th China National Conference on Computational Linguistics, CCL 2020, held in Hainan, China, in October/November 2020. The 32 full and 2 short papers presented in this volume were carefully reviewed and selected from 99 submissions. They were organized in topical sections named: fundamental theory and methods of computational linguistics; information retrieval, dialogue and question answering; text generation and summarization; knowledge graph and information extraction; machine translation and multilingual information processing; minority language information processing; language resource and evaluation; social computing and sentiment analysis; and NLP applications.
Charting a new course : Natural language processing and information retrieval : Essays in Honour of Karen Spärck Jones
This book celebrates the life and work of Karen Spärck Jones in her seventieth year. she is one of the major figures of 20th century and early 21st Century computing and information processing. It book consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.
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 and Solutions for Sustainable Smart City Development
Discusses advances in smart and sustainable development of smart environments. The authors discuss the challenges faced in developing sustainable smart applications and provide potential solutions. The solutions are aimed at improving reliability and security with the goal of affordability, safety, and durability. Topics include health care applications, sustainable smart transportation systems, intelligent sustainable wearable electronics, and sustainable smart building and alert systems. Authors are from both industry and academia and present research from around the world. Addresses problems and solutions for sustainable development of smart cities; Includes applications such as healthcare, transportation, wearables, security, and more ; Relevant for scientist and researchers working on real time smart city development.
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.
CASCOM : Intelligent service coordination in the semantic web
A general architecture for service delivery and coordination in intelligent agent-based peer-to-peer (IP2P) environments, that has been developed within the CASCOM research project, is presented in this book.
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.
Business Intelligence for the Real-Time Enterprises ; 1st International Workshop, BIRTE 2006, Seoul, Korea, September 11, 2006, Revised Selected Papers
The book includes different aspects in the lifecycle of business intelligence on very large enterprise-wide operational real-time data sets. In today’s competitive and highly dynamic environment, analyzing data to und- stand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become critical. The traditional approach to reporting is not longer adequate; users now - mand easy-to-use intelligent platforms and applications capable of analyzing real-time business data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, enabled by the availability of up-to-date, high-quality information.
Business Information Systems ; 11th International Conference, BIS 2008, Innsbruck, Austria, May 5-7, 2008. Proceedings
This book contains the refereed proceedings of the 11th International Conference on Business Information Systems, BIS 2008, held in Innsbruck, Austria, in May 2008.
Building a Data Warehouse : With Examples in SQL Server
The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation.
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.
