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This study endeavored to enhance the efficiency and utility of microcomputer meters. In the past, their role was predominantly confined to remote meter reading, entailing high construction and communication transmission costs, coupled with subsequent maintenance and operational expenditures. These factors collectively impacted the enthusiasm of various stakeholders to invest in this realm. Hence, in alignment with the smart city development initiative, the natural gas industry has pioneered the establishment of an advanced metering infrastructure with heterogeneous wireless sensor networks (HWSNs) at its core. This visionary leap incorporates global machine-to-machine connectivity (G-M2MC) technology, interconnecting all facets of its operations, thereby positioning itself as a trailblazer within the industry. While advancing this endeavor, the project's scheduling aligns with the enterprise's sustainability goals in the early stages of digital transformation. This strategic allocation of resources is responsive to government policies and aspires to cultivate a digitally connected smart green energy hub, thereby expediting the transformation of the living environment. The objective is to provide a stable, secure, cost-effective, and reliable system that can be shared among peers. Furthermore, this study delved into the analysis of congestion avoidance in intelligent Zigbee satellite transport networks based on the HWSNs-GM2MC of non-synchronous satellite orbit system (NGSO) pivotal technologies, utilizing them to integrate the smart LNGas management system (SGMS). Concurrently, it developed application services through the smart meter application interface (SMAPI), distinct from conventional microcomputer meters. However, it is imperative to acknowledge that cloud computing, while processing sensitive data, grapples with issues of latency, privacy, efficiency, power consumption, and zero-trust security risk information management and ethical authority management capabilities in the defense of disaster relief responses. [ABSTRACT FROM AUTHOR]

This paper explores applications of the coordinated multi-point (CoMP) architecture operation of enhanced node B (eNB) in wireless communication networks featuring device-to-device (D2D) signaling. This is applied to cellular phone coverage for rapid mass transit systems, such as the Taiwan high speed rail transport system, and indoor public environments. The paper is based on formulas pertaining to the link between budget design and guidelines, as well as principles and theories of engineering practice, allowing designers to analyze and fully control the uplink and downlink signals and output power of fiber repeaters linking cellular phones to base stations. Finally, we employ easily installed cellular-over-fiber optic solutions for a small cell enhancement (SCE) system with novel architecture based on a leakage coaxial cable system using LTE-A technology. As a result, we successfully applied enhanced coverage designs for distributed antenna systems. These can be used to create self-organizing networks (SoN) for an Internet of Things. [ABSTRACT FROM AUTHOR]

In this paper, the robust In this paper, the robust H∞ control problem of output dynamic observer-based control for a class of uncertain neutral systems with discrete and distributed time delays is considered. Linear matrix inequality (LMI) optimization approach is used to design the new H∞ output dynamic controls. The minimal H∞-norm bound and the maximal perturbed bound are given. Based on the result of this paper, the constraint of matrix equality is not necessary for designing the H∞ observer-based controls. Finally, a numerical example is given to illustrate the efficiency of the proposed approach.

Traditional PID controllers are widely used in industrial applications due to their simple computational architecture. However, the gain parameters of this simple computing architecture are fixed, and in response to environmental changes, the PID parameters must be continuously adjusted until the system is optimized. This research proposes to use the most important deep reinforcement learning (DRL) algorithm in deep learning as the basis and to modulate the gain parameters of the PID controller with fuzzy control. The research has the ability and advantages of reinforcement learning and fuzzy control and constructs a tracking unmanned wheel system. The mobile robotic platform uses a normalization system during computation to reduce the effects of reading errors caused by the wheeled mobile robot (WMR) of environment and sensor processes. The DRL-Fuzzy-PID controller architecture proposed in this paper utilizes degree operation to avoid the data error of negative input in the absolute value judgment, thereby reducing the amount of calculation. In addition to improving the accuracy of fuzzy control, it also uses reinforcement learning to quickly respond and minimize steady-state error to achieve accurate calculation performance. The experimental results of this study show that in complex trajectory sites, the tracking stability of the system using DRL-fuzzy PID is improved by 15.2% compared with conventional PID control, the maximum overshoot is reduced by 35.6%, and the tracking time ratio is shortened by 6.78%. If reinforcement learning is added, the convergence time of the WMR system will be about 0.5 s, and the accuracy rate will reach 95%. This study combines the computation of deep reinforcement learning to enhance the experimentally superior performance of the WMR system. In the future, intelligent unmanned vehicles with automatic tracking functions can be developed, and the combination of IoT and cloud computing can enhance the innovation of this research. [ABSTRACT FROM AUTHOR]

The optimization of several practical large-scale engineering systems is computationally expensive. The computationally expensive simulation optimization problems (CESOP) are concerned about the limited budget being effectively allocated to meet a stochastic objective function which required running computationally expensive simulation. Although computing devices continue to increase in power, the complexity of evaluating a solution continues to keep pace. Ordinal optimization (OO) is developed as an efficient framework for solving CESOP. In this work, a heuristic algorithm integrating ordinal optimization with ant lion optimization (OALO) is proposed to solve the CESOP within a short period of time. The OALO algorithm comprises three parts: approximation model, global exploration, and local exploitation. Firstly, the multivariate adaptive regression splines (MARS) is adopted as a fitness estimation of a design. Next, a reformed ant lion optimization (RALO) is proposed to find N exceptional designs from the solution space. Finally, a ranking and selection procedure is used to decide a quasi-optimal design from the N exceptional designs. The OALO algorithm is applied to optimal queuing design in a communication system, which is formulated as a CESOP. The OALO algorithm is compared with three competing approaches. Test results reveal that the OALO algorithm identifies solutions with better solution quality and better computing efficiency than three competing algorithms. [ABSTRACT FROM AUTHOR]

Electrical resistivity tomography (ERT) is one of the most widely used geophysical methods in geological, hydrogeological, and geo-environmental investigations. Although 3D ERT is now available, 2D ERT remains state-of-the-practice due to its simplicity in fieldwork and lower space requirements. 2D ERT assumes that the ground condition is perpendicular to the survey line and outside the survey line is homogeneous. This assumption can often be violated in conditions such as geologic strikes not perpendicular to the survey line and topographic changes or buried objects near the survey line. Possible errors or artifacts in the 2D resistivity tomogram arising from violating the 2D assumption are often overlooked. This study aimed to numerically investigate the boundary effects on 2D ERT under various simplified conditions. Potential factors including resistivity contrast, depth and size of buried objects, and electrode spacing were considered for the parametric studies. The results revealed that offline geologic features may project onto the 2D tomogram to some extent, depending on the aforementioned factors. The mechanism and implications of boundary effects can be drawn from these parametric studies. [ABSTRACT FROM AUTHOR]

Abstract Molybdenum oxide (MoO x) thin films were prepared by pulse DC sputtering using a molybdenum target and their optical and electrochromic properties were investigated. These MoO x thin films were reactively sputter-deposited at various oxygen flow rates. The effects of the oxygen flow rate on the growth and microstructure of the molybdenum oxide films were examined using X-ray diffractometry (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The optical density and modulation of the MoO x films were analyzed using a UV/VIS spectrophotometer (UV–visible). Electrochromic tests were conducted using an electrochemical analyzer. Experimental results reveal that the electrochromic properties depended strongly on the crystalline phase, thickness, chemical composition and microstructure, which were controlled by varying the oxygen flow rate. Highlights • MoOx thin films were deposited by bipolar pulsed magnetron sputtering of pure Mo targets. • Increasing oxygen flow rate resulted in the crystal structure of MoO 3 which favors the electrochromic properties. • The maximum optical modulation for 25-sccm oxygen partial pressure coating are 19.2% at 400 nm, 36.2% at 550 nm, and 41.7% at 800 nm, respectively. [ABSTRACT FROM AUTHOR]

A high sensory robot system conveniently controls the mobile robot action through the Natural human-machine interaction. Therefore, different hand motions are realized to approximate the required service tasks. Magnetic sensors are located at the defined path to guide the robot platform. Three ultrasonic sensors settle at the outside of mobile robot platform to detect possible blocks in an unknown environment. The RFID reader is proposed to understand the real position of mobile robot in the dynamic space. In data fusion machine, some matched position signals are selected into database for extracting the possible tracks in advance. Therefore, the appropriate path is remembered and will be reloaded again to guide the mobile robot into the desired target at the patrol mode. In practical experiments, people communicate with robot through the hand recognitions of Kinect sensor. Sensor information is suitable to handle various service tasks, i.e. pull the pallet in or extend it out, by the human-like movement. A fuzzy system with suitable rules is utilized to drive the server motor for achieving the great performance. The robot system is not only controlled by an interactive interface but also reached an autonomous navigation by extracting the appropriate mapping information. The high sensory robot system obtains interactive actions with the combinations of image recognitions, suitable path planning and obstacle detecting technologies to approach the guiding goal. In the implementation of hardware, the architectures of mobile robot and motor drivers are completely assembled to support the home tasks. The soft fuzzy system generates the robust robot regulation to automatically achieve the perfect feasibility of fetch-and-give tasks. [ABSTRACT FROM AUTHOR]

This paper develops a Monte Carlo Simulation (MCS) approach to estimate the performance of a multistate manufacturing network (MMN) with joint buffers. In the MMN, products are allowed to be produced by two production lines with the same function to satisfy demand. A performance index, system reliability, is applied to estimate the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The joint buffers with finite storage are considered in the MMN. That is, extra work-in-process output from different production lines can be stored in the same buffer. An MCS algorithm is proposed to generate the capacity state and to check the storage usage of buffers to evaluate whether the demand can be satisfied or not. System reliability of the MMN is estimated through this MCS algorithm. Besides, performability for demand pairs assigned to production lines can be obtained. A practical example of touch panel manufacturing system is used to demonstrate the applicability of the MCS approach. Experimental result shows that system reliability is overestimated when buffer storage is assumed to be infinite. Moreover, joint buffer for an MMN is more reliable than buffers are installed separately in different production lines. [ABSTRACT FROM AUTHOR]

Failures of cast-resin transformers not only reduce the reliability of power systems, but also have great effects on power quality. Partial discharges (PD) occurring in epoxy resin insulators of high-voltage electrical equipment will result in harmful effects on insulation and can cause power system blackouts. Pattern recognition of PD is a useful tool for improving the reliability of high-voltage electrical equipment. In this work, a fuzzy logic clustering decision tree (FLCDT) is proposed to diagnose the PD concerning the abnormal defects of cast-resin transformers. The FLCDT integrates a hierarchical clustering scheme with the decision tree. The hierarchical clustering scheme uses splitting attributes to divide the data set into suspended clusters according to separation matrices. The hierarchical clustering scheme is regarded as a preprocessing stage for classification using a decision tree. The whole data set is divided by the hierarchical clustering scheme into some suspended clusters, and the patterns in each suspended cluster are classified by the decision tree. The FLCDT was successfully adopted to classify the aberrant PD of cast-resin transformers. Classification results of FLCDT were compared with two software packages, See5 and CART. The FLCDT performed much better than the CART and See5 in terms of classification precisions. [ABSTRACT FROM AUTHOR]

File pollution is a recent security threat to peer-to-peer (P2P) file sharing systems. By disseminating numerous polluted files with mismatched or partially tampered contents in the P2P system, the attacker causes users to download unexpected files. This attack is aimed at frustrating users and making them abandon the system. Present researches on combating file pollution have mostly focused on pollution modeling or evaluating the extent of pollution. Only a few researches have proposed effective methods to eliminate pollution attacks, and they are primarily based on reputation systems and blacklisting mechanisms. However, these methods require exchange of significant feedback among the peers in order to identify the malicious peers or polluted files in the system. In this paper, we describe the application of fault-tolerant mechanism used in the redundant arrays of independent disks system to suppress file pollution attacks based on the concept that P2P file sharing systems currently have global file storage systems. We have extended the previously developed Fluid Model to analyze and evaluate the proposed antipollution mechanism. The model accuracy has been demonstrated by performing several simulation experiments; the proposed mechanism could effectively suppress the pollution and successfully decrease the polluted-time exposure of a P2P file sharing system by approximately 40∼60%. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the robust H ∞ filter scheme for the discrete-time switched systems with interval time-varying delay and linear fractional perturbations is proposed. A convex optimization problem with some LMI constraints is formulated to design the stable switched filter which minimizes the H ∞ norm bound for filtering error system. Some nonnegative inequalities and the free weighting matrix technique are used to provide the additional degree of freedom which improves the conservativeness of the proposed results. Finally, a numerical example is illustrated to show the use of the main results. [Copyright &y& Elsevier]