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This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management. The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.
Mobile & handheld device programming / Apps programming --- WAP (wireless) technology --- Electrical engineering --- Computing & information technology --- Open Access --- mobile edge computing --- 5G beyond --- 6G --- edge caching --- Internet of Things --- UAV
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In this study, samples were selected with respect to their layer charge and morphology. Sixteen bulk materials were pre-selected, which contained either swellable clay minerals or non-swelling clay minerals. One topic of this work was a comprehensive determination of layer and edge charge and exchange properties of clay minerals. A further topic in this study concerned the modification of swellable and non-swelling clay minerals with mineral acids, e.g., HCl and H2SO4.
cay minerals --- acid treatment --- layer charge. edge charge --- layer charge reduction
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This work presents two image-based inspection approaches for the quality evaluation of cylinder bore surfaces. In the first algorithm, metal folds on plateau-honed surfaces are inspected with scanning electron microscopy. An edge-aware structure tensor is proposed for feature extraction and localization of surface defects. The second algorithm uses a morphgraphical method for detecting graphite grains in optical micrographs. Based on the inspection results, quality parameters are proposed.
image processing --- Bildverarbeitung --- Kantendetektion --- Mikrographhoning --- micrograph --- automated vision inspection --- Honung --- edge detection --- Automatische Sichtprüfung
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The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond.
hierarchical edge computing --- WSN --- rapid response strategy --- edge node --- fog access points --- cache memory --- convolutional neural network --- proactive caching --- fog computing --- Internet of Things --- service placement --- fog service orchestration --- spectral classification --- portable optical fiber spectrometers --- dew computing --- edge computing --- smartphone --- job scheduling --- scheduling heuristics --- mobile edge computing --- mobile edge server placement --- multiagent RL --- edge security --- offloading computation --- distributed collaboration --- data processing --- dynamic offloading --- IoT --- gateways --- Internet of Things (IoT) --- failure recovery --- FP-Growth algorithm --- association rules --- frequency pattern analysis --- computational offloading --- orchestration --- functional programming --- n/a
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In this work a new understanding of built-up edge formation was developed by applying new methods. For the first time built-up edge formation was examined in-situ in a relevant cutting parameter range by radiographic and optical methods with high temporal resolution. Additionally sophisticated analytical techniques were applied for the ex-situ examination of the microstructure in the built-up edge. A correlation between built-up edge formation and tool wear was deduced.
dry metal cutting --- in-situ Analyse --- Aufbauschneide --- tool wear --- Trockenzerspanung --- Werkzeugverschleiß --- microstructure analysis --- in-situ analysis --- Mikrostrukturanalysebuilt-up edge
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This open access book provides an overview of the work developed within the SODALITE project, which aims at facilitating the deployment and operation of distributed software on top of heterogeneous infrastructures, including cloud, HPC and edge resources. The experts participating in the project describe how SODALITE works and how it can be exploited by end users. While multiple languages and tools are available in the literature to support DevOps teams in the automation of deployment and operation steps, still these activities require specific know-how and skills that cannot be found in average teams. The SODALITE framework tackles this problem by offering modelling and smart editing features to allow those we call Application Ops Experts to work without knowing low level details about the adopted, potentially heterogeneous, infrastructures. The framework offers also mechanisms to verify the quality of the defined models, generate the corresponding executable infrastructural code, automatically wrap application components within proper execution containers, orchestrate all activities concerned with deployment and operation of all system components, and support on-the-fly self-adaptation and refactoring.
Computer software --- Software engineering. --- Development --- Management. --- Computer software engineering --- Engineering --- Heterogeneous Computing --- Cloud, Edge --- HPC --- IaC --- DevOps --- Semantic Reasoning
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This perspective of this book views Earth's various layers as a whole system, and tries to understand how to achieve harmony and sustainable development between human society and nature, with the theme of " habitability of the Earth." This book is one effort at providing an overview of some of the recent exciting advances Chinese geoscientists have made. It is the concerted team effort of a group of researchers from diverse backgrounds to generalize their vision for Earth science in the next 10 years. The book is intended for scholars, administrators of the Science and Technology policy department, and science research funding agencies. This is an open access book.
Geology & the lithosphere --- Earth sciences --- Geophysics --- Astronomy, space & time --- Earth System --- Deep Space --- Deep Earth --- Deep Sea --- Cutting-edge Technology on Earth Science
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The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies.
cloud computing --- container orchestration --- custom metrics --- Docker --- edge computing --- Horizontal Pod Autoscaling (HPA) --- Kubernetes --- Prometheus --- resource metrics --- fog computing --- task allocation --- multi-objective optimization --- evolutionary genetics --- hyper-angle --- crowding distance --- containers --- leader election --- load balancing --- stateful --- multi-access edge computing --- orchestrator --- task offloading --- fuzzy logic --- 5G --- fog/edge computing --- service provisioning --- service placement --- service offloading --- Internet of Things (IoT) --- task scheduling --- markov decision process (MDP) --- deep reinforcement learning (DRL) --- resource management --- algorithm classification --- evaluation framework --- web --- Web Assembly --- OpenCL --- LWC --- fast implementation --- Internet of things --- IoT actor --- data manager --- GDPR --- computing --- computational offloading --- dynamic offloading threshold --- minimizing delay --- minimizing energy consumption --- maximizing throughputs --- n/a
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The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems.
high-level synthesis --- HLS --- SDSoC --- support vector machines --- SVM --- code refactoring --- Zynq --- ZedBoard --- extreme edge --- embedded edge computing --- internet of things deployment --- hardware design --- IoT security --- Contiki-NG --- trustability --- embedded systems --- collaborative filtering --- recommender systems --- parallelism --- reconfigurable hardware --- neuroevolution --- block-based neural network --- dynamic and partial reconfiguration --- scalability --- reinforcement learning --- embedded system --- artificial intelligence --- hardware acceleration --- neuromorphic processor --- power consumption --- harsh environment --- fog computing --- edge computing --- cloud computing --- IoT gateway --- LoRa --- WiFi --- low power consumption --- low latency --- flexible --- smart port --- quantisation --- evolutionary algorithm --- neural network --- FPGA --- Movidius VPU --- 2D graphics accelerator --- line-drawing --- Bresenham’s algorithm --- alpha-blending --- anti-aliasing --- field-programmable gate array --- deep learning --- performance estimation --- Gaussian process
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Coastal environments are dynamic ecosystems, where erosion is influenced by meteorological/climatic, geological, biological, and anthropic factors. Erosion has worrying effects on the environment, infrastructure, lifelines, and buildings. Furthermore, climate change is exacerbating an already fragile situation. We are witnessing a high-risk situation and are convinced that this is the most appropriate time to focus on state-of-the-art remote sensing techniques for shoreline monitoring. The improvements in the spatial and spectral resolution of current and next generation satellite-based sensors and the significant progress in the spatial data processing identify remote sensing techniques that increase our knowledge of territory and coastline. This Special Issue aims to highlight an overview of all multiscale remote sensing techniques (e.g., high resolution images, photogrammetry, SAR, etc.) and a whole array of methods and techniques that process, analyse, and discuss multitemporal remotely sensed data. Thank you to all of our contributors and authors for their interesting and illuminating studies. Since this topic is complex and dynamic, we hope to develop this research with future works to form more cutting-edge studies.
DGPS measurements --- video camera observation --- shoreline position --- beach survey --- Sentinel-2 --- Remote Sensing --- habitat mapping --- mangroves --- coral reefs --- climate change --- vulnerable habitats --- side-scan sonar --- swath bathymetry --- habitat monitoring --- hurricane Sandy --- hurricane Joaquin --- shoreline detection --- remote sensing --- WorldView-2 --- Abruzzo --- multispectral classification --- shoreline --- coastline --- satellite images --- synthetic aperture radar (SAR) --- Sentinel-1 --- shoreline extraction --- coastline extraction --- active connection matrix (ACM) --- J-Net Dynamic --- edge detection --- canny edge detector --- coastline mapping --- geomatics --- SfM photogrammetry --- network RTK --- sea level rise --- coastlines --- 2100 --- storm surges --- heritage sites --- Pyrgi --- Mediterranean --- UAV --- DSM --- n/a
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