الصفحة 1
الصفحة 1
Obstructions in Security-Aware Business Processes : Analysis, Detection, and Handling
This book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software.
Obsessed by a Dream: The Physicist Rolf Widerøe – a Giant in the History of Accelerators
This biography chronicles the life and achievements of the Norwegian engineer and physicist Rolf Widerøe. Readers who meet him in the pages of this book will wonder why he isn't better known.
Object-Based Image Analysis and Treaty Verification : New Approaches in Remote Sensing – Applied to Nuclear Facilities in Iran
This book describes recent progress in object-based image interpretation, and also presents many new results in its application to verification of nuclear non-proliferation. A comprehensive workflow and newly developed algorithms for object-based high resolution image (pre-) processing, feature extraction, change detection, classification and interpretation are developed, applied and evaluated. The entire analysis chain is demonstrated with high resolution imagery acquired over Iranian nuclear facilities.
Object-Based Image Analysis : Spatial Concepts for Knowledge-Driven Remote Sensing Applications
This book discusses means, technologies and approaches related to the processing and analysis of multi-sensor, multi-resolution data with a focus on the generation, modelling and classification of objects. The applications also address the integration of Geographic Information and the concurrent developments of GIScience and vanquish limitations of pixelwise image processing by exploiting image information context-driven and "intelligently".
Object detection with deep learning models : Principles and applications
Discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval / A structured overview of deep learning in object detection / A diversified collection of applications of object detection using deep neural networks / Emphasize agriculture and remote sensing domains / Exclusive discussion on moving object detection
Nonlinear Observers and Applications
The problem of state reconstruction in dynamical systems, known as observer problem, is undoubtedly crucial for controlling or just monitoring processes. For linear systems, the corresponding theory has been quite well established for several years now, and the purpose of the present book is to propose an overview on possible tools in that respect for nonlinear systems. Basic observability notions and observer structures are first recalled, together with ingredients for advanced designs on this basis. A special attention is then paid to the well-known high gain techniques with a summary of various corresponding recent results. A focus on the celebrated Extended Kalman filter is also given, in the perspectives of both nonlinear filtering and high gain observers, leading to so-called adaptive-gain observers. The more specific immersion approach for observer design is then emphasized, while optimization-based methods are also presented as an alternative to analytic observers.
Next Generation Intelligent Optical Networks : From Access to Backbone
Next Generation Intelligent Optical Networks brings together two increasingly important topics: optical networks and network security. It provides a comprehensive treatment of the next generation optical network and a comprehensive treatment of cryptographic algorithms, the quantum optical network (including advanced topics such as teleportation), and how detection and countermeasure strategies may be used.
New pharmacological hypothesis for cancer therapy and treatment
Despite the considerable development of new cancer drugs the mortality remains high and the improvement in survival rate remains poor compared to the number of new concepts of cancer therapy in which we will review in our study and we will focus on two possible reasons for that delay in success such as the limitation of diagnostic tools to perform early detection for the tumor in a stage where it can be well treated or even cured as it is often a silent disease in the start phase of it...
New Methods of Concurrent Checking
New Methods of Concurrent Checking is the ultimate reference to answer the question as to how the best possible state-of-the-art error detection circuits can be designed. The most effective methods of concurrent checking for digital circuits are comprehensively described which were developed in the last 15 years. Some of the methods are published for the first time. How concurrent checking can be combined with soft error correction is also shown for the first time. This book is invaluable in considering the design of reliable systems in the emerging Nanotechnologies with an associated growing number of transient faults.
New insights in machine learning and deep neural networks
Gatheres ten exemplary papers, each delineating advancements within the spheres of machine learning and deep neural networks. Commencing with a thorough exploration by Figueira and Vaz, readers are introduced to the nuances of synthetic data generation and evaluation, followed closely by Silva and Pedroso's systematic approach to leveraging deep reinforcement learning within the intricate realm of delivery logistics. Kamran et al. contribute an astute methodology for camouflage object segmentation, whereas Pinheiro and collaborators offer a crafted semi-supervised strategy for predicting EGFR mutations via CT images. Subsequent contributions, such as Lee and Yoo's framework for portrait emotion recognition and Balakrishnan et al.'s analytical exploration of transformer models for Twitter disaster detection, further exemplify the depth of research contained herein.
New diagnostic method th detect peritoneal metastases in colorectal cancer
Colorectal cancer is the third common reason of death in population worldwide therefore we will focus in our study about description of this type of cancer and its symptoms to raise the public awareness to go to the right specialist as soon as the symptoms appear to improve early detection of this disease and the overall survival and we will highlight the best diet and life style to avoid this type of cancer hopefully beside that we will present all the most successful therapies of this disease from different classes of compounds such as chemotherapy or anti angiogenic and Metformin and other bacterial therapy however the major goal of the experimental part of this research is performed to establish a new promising diagnostic tool by Near Infra-red camera after injection of indyocine green to detection the peritoneal metastasis of colorectal in 15 patients since this kind of metastasis
New developments in nanosensors for pharmaceutical analysis ; 1st ed.
Presents an overview of developments in nanosensor usage in pharmaceutical analysis, thereby helping pharmaceutical companies attain reliable, precise, and accurate analysis of pharmaceuticals. This book presents very simple, precise, sensitive, selective, fast, and relatively inexpensive methods for pre-treatment, prior to analysis. These methods may be considered for further application in clinical studies and assays. The book includes the manufacturing of sensors for pharmaceutical analysis at nano- or smaller scales, and gives simple and relatable designs for the fabrication of sensors.
New approaches for security, privacy and trust in complex environments ; Proceedings of the IFIP TC 11 22nd International Information Security Conference (SEC 2007), 14-16 May 2007, Sandton, South Africa
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
New and emerging plant viruses : the threat to food security
Despite intensive efforts to manage and prevent plant viruses and their potential vectors in crop production processes, many crops are damaged each year. This new book reviews the progress made to date and the challenges ahead in the field of plant viruses and agricultural production. It sheds light on previously undiscovered plant viruses, bringing together information on the detection and tracking, host interaction, evolution, and management. The first section covers the various hidden sources of plant viruses such as from wild plants, weeds, and tobacco as well as other undetermined plant virus sources. The second section covers the implications of mixed infection on disease pathogenicity and epidemiology, provides an understanding of the virus and host relationship, and presents an overview of plant viruses from old to new.
New advances in audio signal processing
In the era of digitalization, audio signal processing is gaining peculiar relevance as an automation and remote analysis means, also considering its enhancement by novel artificial intelligence (AI) techniques. This Reprint aims to offer an overview of the current developments in all fields that revolve around audio processing: from advancements in the acoustic domain to deep learning architectures for the audio-based analysis of real-world problems such as pitch detection or pathology identification.
Neutrophil : Methods and Protocols
Neutrophils, the most abundant white cells in humans, serve as the primary cellular defense against infection. This volume provides a concise set of protocols for assessing basic neutrophil functions and investigating specialized areas in neutrophil biology. Each of the protocols is written by leading researchers in the field and includes hints for success, as well as guidance for troubleshooting. Part I contains overviews of neutrophil biology, function, and disorders. Part II describes commonly used methods to isolate neutrophils from humans and other animal species. Part III details methods for investigating chemotaxis, transmigration, phagocytosis, and bactericidal activity. Part IV includes protocols that measure neutrophil apoptosis, calcium signal transduction, degranulation and detection of cytoplasmic granules, gene expression, transcription factors, and apoptosis. Part V provides multiple assays for measuring production of intracellular and/or extracellular reactive oxygen species, and a method that details use of the cell-free NADPH oxidase assay, an iconic assay for studies of the neutrophil NADPH oxidase. Part VI provides chapters that describe how to analyze formation and function of neutrophil extracellular traps.
Neuroscribe = نيوروسكرايب
Neuroscribe is a cutting-edge deep learning framework designed to address the complexities and inefficiencies encountered in existing frameworks like PyTorch and TensorFlow. Aimed at streamlining model development and enhancing performance across diverse hardware environments, NeuroScribe offers a lightweight and flexible solution. The framework features a robust tensor library, an auto-differentiation engine, a comprehensive neural network module, and advanced optimization algorithms. With built-in visualization tools and a user-friendly interface, NeuroScribe simplifies both beginner and advanced workflows. Its cross-platform compatibility, supported by CUDA and Metal Performance Shaders (MPS), ensures optimal performance, and in some scenarios, NeuroScribe demonstrates superior speed compared to leading frameworks. Additionally, NeuroScribe introduces unique libraries and features not found in other frameworks, further enhancing its versatility and appeal. The modular architecture and automatic system detection further enhance its adaptability, making NeuroScribe a versatile and powerful tool for deep learning practitioners.
Networked Sensing Information and Control
In recent years, there has been significant interest and advances in developing systematic techniques to synthesize interactive and reconfigurable distributed sensing systems that are capable of performing effective inferencing and control tasks under overall resource constraints. Networked Sensing Information and Control is a collection of papers which present broad trends in the mathematical aspects of networked sensing, information, and control.
Network Classification For Traffic Management : Anomaly detection, feature selection, clustering and classification
Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks. Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. The authors explore novel methods for enhancing network statistics at the transport layer, helping to identify optimal feature selection through a global optimization approach and providing automatic labelling for raw traffic through a SemTra framework to maintain provable privacy on information disclosure properties.
Neonatal Cranial Ultrasonography
It provides important information on brain maturation in the (preterm) neonate and enables the detection of frequently occurring brain anomalies in both preterm and full term neonates. Furthermore, it can be repeated as often as is necessary. In this edition of Neonatal Cranial Ultrasonography, the focus is on the basics of the technique, from patient preparation through to screening strategies and the classification of abnormalities. Many new ultrasound images have been included to reflect the improvements in image quality since the first edition. Essential information is provided about both the procedure itself and the normal ultrasound anatomy. Standard technique using the anterior fontanelle as the acoustic window is described and illustrated, but emphasis is also placed on the value of supplementary acoustic windows.
