Page 9
Page 9
Medical data processing and analysis
Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations.
Medical centers management system
The medical clinics management system (MCMS) is a system that manages a group of clinics distributed within different governorates and regions in Syria, as it manages data entry processes for each patient such as personal information, disease and accompanying symptoms in addition to doctors' information, and clinics through a web application. The system also performs mining algorithms on the current data for discovering new symptoms and diseases by analyzing patient, diseases and symptoms data available within the database, to subsequently notify the admins of the emergence of a new symptom or an increase in a disease in a given area. In addition to generating daily or weekly reports containing the number of visits and cases of recovery and other information.
MDATA : A New Knowledge Representation Model: Theory, Methods and Applications
This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis). By modifying the representation of entities and relations in knowledge graphs, dynamic knowledge can be efficiently described with temporal and spatial characteristics. The MDATA model can be regarded as a high-level temporal and spatial knowledge graph model, which has strong capabilities for knowledge representation. This book introduces some key technologies in the MDATA model, such as entity recognition, relation extraction, entity alignment, and knowledge reasoning with spatiotemporal factors. The MDATA model can be applied in many critical applications and this book introduces some typical examples, such as network attack detection, social network analysis, and epidemic assessment.
IP operations and management ; 8th IEEE International workshop, IPOM 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Constitutes the refereed proceedings of the 8th IEEE Workshop on IP Operations and Management, IPOM 2008, held on Samos Island, Greece, on September 22-26, 2008, as part of the 4th International Week on Management of Networks and Services, Manweek 2008. The 12 revised full papers presented in this volume were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on network anomaly detection; traffic engineering, protection, and recovery; network measurements and applications; and network management and security.
IP Networking over Next-Generation Satellite Systems ; International Workshop, Budapest, July 2007
Highlights the very latest research output of several EU satellite-related projects and addresses many unresolved issues in next-generation satellite systems, such as efficient deployment of IPv6 over satellites, working with WLAN and WiMax, QoS provisioning over multi-segment networks (including satellite networks), multicast networks and security.
IoT-enabled Smart Healthcare Systems, Services and Applications
In IoT-Enabled Smart Healthcare Systems, Services and Applications, an accomplished team of researchers delivers an insightful and comprehensive exploration of the roles played by cutting-edge technologies in modern healthcare delivery. The distinguished editors have included resources from a diverse array of learned experts in the field that combine to create a broad examination of a rapidly developing field.
IOT control and surveillance system
An automated system is a combination of both software and hardware which is designed and programmed to work automatically without the need of any human operator to provide inputs and instructions for each operation. The Internet of Things (IoT) is a network of connected things. These ‘things’ (devices) communicate with each other using machine to machine communication (M2M). Information is traversed between devices so that processes can be automated, without the need for human intervention. By reducing the number of people involved in a business process, several advantages arise, including improved accuracy and up-time. We will build an IoT automated system to control access of humans and vehicles to a warehouse based on biometrics and image recognition techniques.
IoT and AI Technologies for Sustainable Living : A Practical Handbook
Brings together all the latest methodologies, tools and techniques related to the Internet of Things and Artificial Intelligence in a single volume to build insight into their use in sustainable living. The areas of application include agriculture, smart farming, healthcare, bioinformatics, self-diagnosis systems, body sensor networks, multimedia mining, and multimedia in forensics and security. Provides a comprehensive discussion of modeling and implementation in water resource optimization, recognizing pest patterns, traffic scheduling, web mining, cyber security and cyber forensics. It will help develop an understanding of the need for AI and IoT to have a sustainable era of human living. The tools covered include genetic algorithms, cloud computing, water resource management, web mining, machine learning, block chaining, learning algorithms, sentimental analysis and Natural Language Processing (NLP).
Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets ; International Workshop, Dagstuhl Castle, Germany, March 1-5, 2004, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 2004 International Workshop on Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets, held in Dagstuhl Castle, Germany in March 2004. The 17 revised full papers presented together with an introductory overview have gone through two rounds of reviewing and revision. The papers are organized in topical sections on man-machine interface for intuitive knowledge access, intelligent pad and meme media, visualization and design of information access spaces, and semantics and narrative organization and access of knowledge.
Intrusion Detection Systems
Sٍheds new light on defense alert systems against computer and network intrusions. It also covers integrating intrusion alerts within security policy framework for intrusion response, related case studies and much more. This volume is presented in an easy-to-follow style while including a rigorous treatment of the issues, solutions, and technologies tied to the field.
Introduction to Video Search Engines
Their book has a practical emphasis with the goal of bringing readers up to date on the state of the art in multimedia search technologies and systems. It explains the overall process of video content acquisition, indexing and retrieval with browsing, it provides overviews of constituent technologies such as information retrieval, Internet video systems, video and multimedia processing to extract index data, and it gives examples of research prototypes and existing commercial systems and describes their features.
Introduction to the theory of computation
Gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs.
Introduction to Scientific Visualization
Scientific visualization is recognised as important for understanding data, whether measured, sensed remotely or calculated. Introduction to Scientific Visualization is aimed at readers who are new to the subject, either students taking an advanced option at undergraduate level or postgraduates wishing to visualize some specific data.
Introduction to robotics : Analysis, control, applications
Offers a guide to the fundamentals of robotics, robot components and subsystems and applications. The author—a noted expert on the topic—covers the mechanics and kinematics of serial and parallel robots, both with the Denavit-Hartenberg approach as well as screw-based mechanics. In addition, the text contains information on microprocessor applications, control systems, vision systems, sensors, and actuators.
Introduction to PHP for Scientists and Engineers : Beyond JavaScript
This text presents key information needed to write your own online science and engineering applications, including reading, creating and manipulating data files stored as text on a server, thereby overcoming the limitations of a client-side language.
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Introduction to information retrieval
Teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science.
Introduction to Cryptography : Principles and Applications
In the first part, this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators.
Introduction to C++ : 500+ Difficulty-Scaled Solved Programming Exercises
Includes more than 500 exercises and examples of progressive difficulty to aid the reader in understanding the C++ principles and to see how concepts can materialize in code. The examples are designed to be short, concrete, and substantial, quickly giving the reader the ability to understand how to apply correctly and efficiently the features of the C++ language and to get a solid programming know-how. Rest assured that if you are able to understand this book's examples and solve the exercises, you can safely go on to edit larger programs, you will be able to develop your own applications, and you will have certainly established a solid fundamental conceptual and practical background to expand your knowledge and skills
Introduction to Algorithms
Combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.
