物件導向軟體之架構(Object-Oriented Software Construction)探討

The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things.

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Internet of things: Vision, applications and research challenges

A mobile ad hoc network consists of wireless hosts that may move often. Movement of hosts results in a change in routes, requiring some mechanism for determining new routes. Several routing protocols have already been proposed for ad hoc networks. This report suggests an approach to utilize location information (for instance, obtained using the global positioning system) to improve performance of routing protocols for ad hoc networks.

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Location-aided routing (LAR) in mobile ad hoc networks

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

Parallel discrete event simulation (PDES), sometimes called distributed simulation, refers to the execution of a single discrete event simulation program on a parallel computer. PDES has attracted a considerable amount of interest in recent years. From a pragmatic standpoint, this interest arises from the fact that large simulations in engineering, computer science, economics, and military applications, to mention a few, consume enormous amounts of time on sequential machines. From an academic point of view, parallel simulation is interesting because it represents a problem domain that often contains substantial amounts of parallelism (e.g., see [59]), yet paradoxically, is surprisingly difficult to parallelize in practice. A sufficiently general solution to the PDES problem may lead to new insights in parallel computation as a whole. Historically, the irregular, data-dependent nature of PDES programs has identified it as an application where vectorization techniques using supercomputer hardware provide little benefit [14].A discrete event simulation model assumes the system being simulated only changes state at discrete points in simulated time. The simulation model jumps from one state to another upon the occurrence of an event. For example, a simulator of a store-and-forward communication network might include state variables to indicate the length of message queues, the status of communication links (busy or idle), etc. Typical events might include arrival of a message at some node in the network, forwarding a message to another network node, component failures, etc.We are especially concerned with the simulation of asynchronous systems where events are not synchronized by a global clock, but rather, occur at irregular time intervals. For these systems, few simulator events occur at any single point in simulated time; therefore parallelization techniques based on lock-step execution using a global simulation clock perform poorly or require assumptions in the timing model that may compromise the fidelity of the simulation. Concurrent execution of events at different points in simulated time is required, but as we shall soon see, this introduces interesting synchronization problems that are at the heart of the PDES problem.This article deals with the execution of a simulation program on a parallel computer by decomposing the simulation application into a set of concurrently executing processes. For completeness, we conclude this section by mentioning other approaches to exploiting parallelism in simulation problems.Comfort and Shepard et al. have proposed using dedicated functional units to implement specific sequential simulation functions, (e.g., event list manipulation and random number generation [20, 23, 47]). This method can provide only a limited amount of speedup, however. Zhang, Zeigler, and Concepcion use the hierarchical decomposition of the simulation model to allow an event consisting of several subevents to be processed concurrently [21, 98]. A third alternative is to execute independent, sequential simulation programs on different processors [11, 39]. This replicated trials approach is useful if the simulation is largely stochastic and one is performing long simulation runs to reduce variance, or if one is attempting to simulate a specific simulation problem across a large number of different parameter settings. However, one drawback with this approach is that each processor must contain sufficient memory to hold the entire simulation. Furthermore, this approach is less suitable in a design environment where results of one experiment are used to determine the experiment that should be performed next because one must wait for a sequential execution to be completed before results are obtained.

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Parallel discrete event simulation

All six papers in this special section engage in different streams but extremely relevant domain vectors of Cognitive Cyber-Physical Systems (CCPS) with artificial intelligence (AI) based solutions in medical informatics. Highlights recent trends in the scientific community and presents emergent technologies, implementations, applications concerning the CPSS. CPSS is witnessing rapid transformation as an interdisciplinary technology that blends physical components and computing devices to enable AI-based solutions. CCPS will be playing a significant role that integrates machine learning/AI techniques and resulting in dramatic improvements for medical informatics and the future of human-augmentation. CPHMS coordinates supervisory medical systems and medical resources everywhere; there is a great scope towards health consciousness and healthy society. Medical Cyber-Physical Systems (MCPS) in healthcare towards critical integration in network of medical devices. MCPS is the next generation computing that is comprised of tightly coupled computational and communication components of medical automation systems such as clinical decision, early detection of health infectious, disease prevention, rapid analysis of health hazards and so on. CCPS and MCPS research would be created new models, new design, and integration models for large scale systems in comprehensive, holistic medical automation systems. With recent enlargements in the big data processing, cognitive data science and AI, it is now possible to create even more realistic digital twins that properly model different operating situations and characteristics to process the medical intelligence systems. 

Guest Editorial Cognitive Cyber-Physical Systems With AI Based Solutions in Medical Informatics

1 Abstract —This paper proposes StrawberryTalk, an Internet of Things (IoT) platform for image-based strawberry disease detection. StrawberryTalk reuses the wall-mounted monitoring cameras without extra hardware cost. The contributions of StrawberryTalk are the utilization of IoT for automatic photo shoot and the wind detection mechanism to eliminate the obscure photos due to the wind effects. Also, the data preprocessing and the infection detection models are manipulated as IoT devices to simplify the implementation of the multi-cascade Artificial Intelligence (AI) models. We derive the relationship between the camera zoom factor and the distance between the camera and the strawberries for optimal disease detection. Accuracy of detection may be affected by obscure photos. In terms of eliminating obscure photos due to wind effect, we analytically derive the relationship between the wind alert delay and the number of obscure photos that must be retaken. For the greenhouses in the Bao Mountain, we only need to retake one photo. Based on the experiments, the mean average precision (mAP) of StrawberryTalk (to detect exact spots in a leaf) can be up to 92.37%, which is better than the previous approaches. To detect if a pot has infected leaves, the accuracy of StrawberryTalk can be up to 97.92% at the zoom factor 30X. In commercial operation, it is important to detect all infected strawberry pots. StrawberryTalk is able to detect all infected pots (i.e., recall is 100%) with a camera of zoom factor of 12X. The accuracy is 96.88%.

IoT-based Strawberry Disease Detection with Wall-mounted Monitoring Cameras

Web API Verifier for IoTtalk and Its Applications

Reconciling business analytics with graphically initialized subspace clustering for optimal nonlinear pricing

IoTtalk is a platform for IoT device interaction, which has been used to develop many IoT applications such as home automation. This paper uses Dandelion Mirror artwork as an example to show how interactive visual design can be conveniently implemented in IoTtalk. The Dandelion Mirror artwork conducts cyber physical interaction, which animates a dandelion in a mirror when a person smiles at that mirror. The dandelion grows larger as the person smiles bigger. The flower also vibrates following the heartbeat rate of the person. In our approach, the camera detecting the face expression and the heartbeat rate is considered as an input IoT device, and the mirror display for dandelion animation is considered as an output IoT device. In IoTtalk, the features of the dandelion animation are considered as the actuators that can be independently controlled. IoTtalk nicely connects these IoT devices, where various features can be created for interactive visual design with little or without any programming effort.

Yi-Bing Lin

Papers

Guest Editorial Cognitive Cyber-Physical Systems With AI Based Solutions in Medical Informatics

IoT-based Strawberry Disease Detection with Wall-mounted Monitoring Cameras

Web API Verifier for IoTtalk and Its Applications

Reconciling business analytics with graphically initialized subspace clustering for optimal nonlinear pricing

Dandelion mirror: An interactive visual design using IoTtalk