This study analyzes the problem of robust stability of fractional-order delay systems of neutral type under actuator saturation. A Lyapunov-Krasovskii (LK) function is constructed and conditions of the asymptotic robust stability of such systems are given, which are formulated by linear matrix inequalities (LMIs), using the Lyapunov direct method. An algorithm is introduced to compute the gain of the

We propose a joint feature and metric learning deep neural network architecture, called the associative affinity network (AAN), as an affinity model for multi-object tracking (MOT) in videos. The AAN learns the associative affinity between tracks and detections across frames in an end-to-end manner. Considering flawed detections, the AAN jointly learns bounding box regression, classification, and affinity

A tunable stepped-impedance resonator using liquid crystal is demonstrated. Two resonant frequencies at 3.367 and 7.198 GHz are realized and can be continuously tuned by external applied voltages. Continuous tunable ranges of 52 and 210 MHz have been achieved at a particularly low driving voltage of 14 V, which shows good agreement with the simulation results. The voltage-induced hysteresis phenomenon

Soft sensors are widely used to predict quality variables which are usually hard to measure. It is necessary to construct an adaptive model to cope with process non-stationaries. In this study, a novel quality-related locally weighted soft sensing method is designed for non-stationary processes based on a Bayesian network with latent variables. Specifically, a supervised Bayesian network is proposed

This paper studies the transfer path planning problem for safe transfer of an aircraft on the aircraft carrier flight deck under a poor visibility condition or at night. First, we analyze the transfer path planning problem for carrier-based aircraft on the flight deck, and define the objective to be optimized and the constraints to be met. Second, to solve this problem, the mathematical support models

With the rapid development of Internet technology and the advent of the era of big data, more and more cyber security texts are provided on the Internet. These texts include not only security concepts, incidents, tools, guidelines, and policies, but also risk management approaches, best practices, assurances, technologies, and more. Through the integration of large-scale, heterogeneous, unstructured

This paper presents a methodology of designing an amplifier integrated with a microstrip filter using an active coupling matrix. The microstrip filter is directly coupled to the active device, and the integrated filter amplifier can achieve filtering as well as matching functionalities, simultaneously, eliminating the need for separate matching networks. The filter amplifier is represented by an active

Quality control is of vital importance in compressing three-dimensional (3D) medical imaging data. Optimal compression parameters need to be determined based on the specific quality requirement. In high efficiency video coding (HEVC), regarded as the state-of-the-art compression tool, the quantization parameter (QP) plays a dominant role in controlling quality. The direct application of a video-based

Optimal transportation plays a fundamental role in many fields in engineering and medicine, including surface parameterization in graphics, registration in computer vision, and generative models in deep learning. For quadratic distance cost, optimal transportation map is the gradient of the Brenier potential, which can be obtained by solving the Monge-Ampère equation. Furthermore, it is induced to

Heterogeneous vehicular clustering integrates multiple types of communication networks to work efficiently for various vehicular applications. One popular form of heterogeneous network is the integration of long-term evolution (LTE) and dedicated short-range communication. The heterogeneity of such a network infrastructure and the non-cooperation involved in sharing cost/data are potential problems

Physiological signal based biometric analysis has recently attracted attention as a means of meeting increasing privacy and security requirements. The real-time nature of an electrocardiogram (ECG) and the hidden nature of the information make it highly resistant to attacks. This paper focuses on three major bottlenecks of existing deep learning driven approaches: the lengthy time requirements for

This paper presents a mechanical reliability study of 3-dB waveguide hybrid couplers in submillimeter and terahertz bands. To show the necessity of improving the mechanical properties of the coupler’s branch in submillimeter and terahertz bands, a comprehensive study regarding the displacement of hybrid branch variation with varying width-length ratio and height-length ratio has been completed. In

The artificial bee colony (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’ food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is required to apply it to binary optimization problems. In this study, we modify the ABC algorithm to solve

Volume rendering plays a significant role in medical imaging and engineering applications. To obtain an improved three-dimensional shape perception of volumetric datasets, realistic volume illumination has been considerably studied in recent years. However, the calculation overhead associated with interactive volume rendering is unusually high, and the solvability of the problem is adversely affected

This study investigates the consensus problem of a nonlinear discrete-time multi-agent system (MAS) under bounded additive disturbances. We propose a self-triggered robust distributed model predictive control consensus algorithm. A new cost function is constructed and MAS is coupled through this function. Based on the proposed cost function, a self-triggered mechanism is adopted to reduce the communication

Recently, cloud computing has become a vital part that supports people’s normal lives and production. However, accompanied by the increasing complexity of the cloud network, failures constantly keep coming up and cause huge economic losses. Thus, to guarantee the cloud network performance and prevent execrable effects caused by failures, cloud network diagnostics has become of great interest for cloud

Over-the-air (OTA) testing is an industry standard practice for evaluating transceiver performance in wireless devices. For the fifth generation (5G) and beyond wireless systems with high integration, OTA testing is probably the only reliable method to accurately measure the transceiver performance, suitable for certification as well as for providing feedback for design verification and optimization

We demonstrate a heuristic approach for optimizing the posterior density of the data association tracking algorithm via the random finite set (RFS) theory. Specifically, we propose an adjusted version of the joint probabilistic data association (JPDA) filter, known as the nearest-neighbor set JPDA (NNSJPDA). The target labels in all possible data association events are switched using a novel nearest-neighbor

Given the potential for bit flipping of data on a memory medium, a high-speed parallel Bose-Chaudhuri-Hocquenghem (BCH) error correction scheme with modular characteristics, combining logic implementation and a look-up table, is proposed. It is suitable for data error correction on a modern field programmable gate array full with on-chip embedded memories. We elaborate on the optimization method for

This study focuses on the multiphase flow properties of crowd motions. Stability is a crucial forewarning factor for the crowd. To evaluate the behaviors of newly arriving pedestrians and the stability of a crowd, a novel motion structure analysis model is established based on purposiveness, and is used to describe the continuity of pedestrians’ pursuing their own goals. We represent the crowd with

This paper studies the sampled data based containment control problem of second-order multi-agent systems with intermittent communications, where velocity measurements for each agent are unavailable. A novel controller for second-order containment is put forward via intermittent sampled position data measurement. Several necessary and sufficient conditions are derived to achieve intermittent sampled

In the semiconductor manufacturing industry, the dynamic model of a controlled object is usually obtained from a frequency sweeping method before motion control. However, the existing isolators cannot properly isolate the disturbance of the inertial force on the platform base during frequency sweeping (the frequency is between 0 Hz and the natural frequency). In this paper, an adjustable anti-resonance

The prediction of regional traffic flows is important for traffic control and management in an intelligent traffic system. With the help of deep neural networks, the convolutional neural network or residual neural network, which can be applied only to regular grids, is adopted to capture the spatial dependence for flow prediction. However, the obtained regions are always irregular considering the road

In this study, we provide a detailed analysis of the frequency division duplex long term evolution downlink (FDD LTE DL) signal for passive bistatic radars that use the signal as an illuminator of opportunity. In particular, we analyze the cross-ambiguity function and illustrate its undesired deterministic peaks in the Doppler dimension due to the specific structure of the FDD LTE DL signal. A new

Sepsis treatment is a highly challenging effort to reduce mortality in hospital intensive care units since the treatment response may vary for each patient. Tailored treatment recommendations are desired to assist doctors in making decisions efficiently and accurately. In this work, we apply a self-supervised method based on reinforcement learning (RL) for treatment recommendation on individuals. An

In this paper, an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation. A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external disturbances. To guarantee the prescribed performance, an error transformation

Recently, bionic signals have been used to achieve covert underwater acoustic communication (UWAC) with high signal-to-noise ratios (SNRs) over transmission systems. A high SNR allows the attackers to proceed with their mischievous goals and makes transmission systems vulnerable against malicious attacks. In this paper we propose an improved Merkle hash tree based secure scheme that can resist current

A sheer number of techniques and web resources are available for software engineering practice and this number continues to grow. Discovering semantically similar or related technical terms and web resources offers the opportunity to design appealing services to facilitate information retrieval and information discovery. In this study, we extract technical terms and web resources from a community of

This work presents the application of the technique named signal analysis based on chaos using density of maxima to analyze brushless direct current motors. It uses a correlation coefficient estimated from the density of maxima of the current signal. This study demonstrates in experiments the speed estimation of a brushless motor on a testbench and failure detection in a small flying drone. The experimental

Requirement traceability is an important and costly task that creates trace links from requirements to different software artifacts. These trace links can help engineers reduce the time and complexity of software maintenance. The information retrieval (IR) technique has been widely used in requirement traceability. It uses the textual similarity between software artifacts to create links. However,

Healthcare and telemedicine industries are relying on technology that is connected to the Internet. Digital health data are more prone to cyber attacks because of the treasure trove of personal data they possess. This necessitates protection of digital medical images and their secure transmission. In this paper, an encryption technique based on DNA mutated with Lorenz and Lü chaotic attractors is employed

Distributed optimization has been well developed in recent years due to its wide applications in machine learning and signal processing. In this paper, we focus on investigating distributed optimization to minimize a global objective. The objective is a sum of smooth and strongly convex local cost functions which are distributed over an undirected network of n nodes. In contrast to existing works,

High-throughput satellites (HTSs) play an important role in future millimeter-wave (mmWave) aeronautical communication to meet high speed and broad bandwidth requirements. This paper investigates the outage performance of an aeronautical broadband satellite communication system’s forward link, where the feeder link from the gateway to the HTS uses free-space optical (FSO) transmission and the user

With the fast development of consumer-level RGB-D cameras, real-world indoor three-dimensional (3D) scene modeling and robotic applications are gaining more attention. However, indoor 3D scene modeling is still challenging because the structure of interior objects may be complex and the RGB-D data acquired by consumer-level sensors may have poor quality. There is a lot of research in this area. In

Blind signcryption (BSC) can guarantee the blindness and untrackability of signcrypted messages, and moreover, it provides simultaneous unforgeability and confidentiality. Most traditional BSC schemes are based on the number theory. However, with the rapid development of quantum computing, traditional BSC systems are faced with severe security threats. As promising candidate cryptosystems with the

Multi-agent reinforcement learning (MARL) has long been a significant research topic in both machine learning and control systems. Recent development of (single-agent) deep reinforcement learning has created a resurgence of interest in developing new MARL algorithms, especially those founded on theoretical analysis. In this paper, we review recent advances on a sub-area of this topic: decentralized

Millimeter wave (mmWave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5G and beyond. To realize applications in future vehicular communications, it is important to take a robust mmWave vehicular network into consideration. However, one challenge in such a network is that mmWave should provide an ultra-fast and high-rate data exchange among vehicles or vehi

This paper addresses the problem of joint tracking and classification (JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model (RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the

A general empirical path loss (PL) model for air-to-ground (A2G) millimeter-wave (mmWave) channels is proposed in this paper. Different from existing PL models, the new model takes the height factor of unmanned aerial vehicles (UAVs) into account, and divides the propagation conditions into three cases (i.e., line-of-sight, reflection, and diffraction). A map-based deterministic PL prediction algorithm

Video summarization has established itself as a fundamental technique for generating compact and concise video, which alleviates managing and browsing large-scale video data. Existing methods fail to fully consider the local and global relations among frames of video, leading to a deteriorated summarization performance. To address the above problem, we propose a graph convolutional attention network

In the standard grey wolf optimizer (GWO), the search wolf must wait to update its current position until the comparison between the other search wolves and the three leader wolves is completed. During this waiting period, the standard GWO is seen as the static GWO. To get rid of this waiting period, two dynamic GWO algorithms are proposed: the first dynamic grey wolf optimizer (DGWO1) and the second

We propose a novel circuit for the fractional-order memristive neural synaptic weighting (FMNSW). The introduced circuit is different from the majority of the previous integer-order approaches and offers important advantages. Since the concept of memristor has been generalized from the classic integer-order memristor to the fractional-order memristor (fracmemristor), a challenging theoretical problem

Rule-based autonomous driving systems may suffer from increased complexity with large-scale intercoupled rules, so many researchers are exploring learning-based approaches. Reinforcement learning (RL) has been applied in designing autonomous driving systems because of its outstanding performance on a wide variety of sequential control problems. However, poor initial performance is a major challenge

Object detection is one of the hottest research directions in computer vision, has already made impressive progress in academia, and has many valuable applications in the industry. However, the mainstream detection methods still have two shortcomings: (1) even a model that is well trained using large amounts of data still cannot generally be used across different kinds of scenes; (2) once a model is

Three-dimensional (3D) reconstruction of shapes is an important research topic in the fields of computer vision, computer graphics, pattern recognition, and virtual reality. Existing 3D reconstruction methods usually suffer from two bottlenecks: (1) they involve multiple manually designed states which can lead to cumulative errors, but can hardly learn semantic features of 3D shapes automatically;

长期以来困扰人工智能领域的一个问题是: 人工智能是否具有创造力, 或者说, 算法的推理过程是否可以具有创造性. 本文从思维科学的角度探讨人工智能创造力的问题. 首先, 列举形象思维推理的相关研究; 然后, 重点介绍一种特殊的视觉知识表示形式, 即视觉场景图; 最后, 详细介绍视觉场景图构造问题与潜在应用. 所有证据表明, 视觉知识和视觉思维不仅可以改善当前人工智能任务的性能, 而且可以用于机器创造力的实践.

Network on chip (NoC) is an infrastructure providing a communication platform to multiprocessor chips. Furthermore, the wormhole-switching method, which shares resources, was used to increase its efficiency; however, this can lead to congestion. Moreover, dealing with this congestion consumes more energy and correspondingly leads to increase in power consumption. Furthermore, consuming more power results

To boost research into cognition-level visual understanding, i.e., making an accurate inference based on a thorough understanding of visual details, visual commonsense reasoning (VCR) has been proposed. Compared with traditional visual question answering which requires models to select correct answers, VCR requires models to select not only the correct answers, but also the correct rationales. Recent

As one of the early COVID-19 epidemic outbreak areas, China attracted the global news media’s attention at the beginning of 2020. During the epidemic period, Chinese people united and actively fought against the epidemic. However, in the eyes of the international public, the situation reported about China is not optimistic. To better understand how the international public portrays China, especially

Unfortunately the fifth author’s name was misspelt. It should be Sidheswar ROUTRAY.

Urban modeling facilitates the generation of virtual environments for various scenarios about cities. It requires expertise and consideration, and therefore consumes massive time and computation resources. Nevertheless, related tasks sometimes result in dissatisfaction or even failure. These challenges have received significant attention from researchers in the area of computer graphics. Meanwhile

Millimeter-wave (mmWave) communication is regarded as the key enabling component for fifth-generation (5G) cellular systems due to the large available spectrum bandwidth. To make mmWave new radio (NR) a reality, tremendous efforts have been exerted from the industry and academia. Performance evaluation of mmWave NR is a mandatory step and the key to ensuring the success of mmWave 5G deployment. Over-the-air

An ultra-massive phased array can be deployed in high-throughput millimeter-wave (mmWave) communication systems to increase the transmission distance. However, when the signal bandwidth is large, the antenna array response changes with the frequency, causing beam squint. In this paper, we investigate the beam squint effect on a high-throughput mmWave communication system with the single-carrier frequency-domain

毫米波天线设计面临高增益、宽带、低成本等诸多挑战,在该频段基片集成波导(Substrate Integrated Waveguide,SIW)由于其辐射损耗低和易集成的优势而被广泛应用。然而在毫米波频段SIW的介质损耗直接降低了天线辐射效率,若采用低损耗介质材料会导致较高的制造成本。基片集成空腔波导(Empty Substrate Integrated Waveguide,ESIW)结构通过去除SIW中介质,可实现电磁波低损耗传输,在毫米波频段具有广阔应用前景。本文面向5G n260频段应用,提出一款采用低成本FR-4 PCB板材设计的缝隙天线阵。天线采用基片集成空腔波导结构设计,消除了介质损耗,并引入高次模腔体结构,减小馈电网络复杂度,在保证天线性能前提下,实现了毫米波天线低成本制造,为低成本毫米波天线设计提供了技术参考。 天线由5层FR-4 PCB板组成,从顶层往下依次为缝隙辐射层、高

As the fifth-generation (5G) mobile communication system is being commercialized, extensive studies on the evolution of 5G and sixth-generation (6G) mobile communication systems have been conducted. Future mobile communication systems are evidently evolving toward a more intelligent and software-reconfigurable functionality paradigm that can provide ubiquitous communication, as well as sense, control

Millimeter-wave (mmWave) technology has been well studied for both outdoor long-distance transmission and indoor short-range communication. In the recently emerging fiber-to-the-room (FTTR) architecture in the home network of the fifth generation fixed networks (F5G), mmWave technology can be cascaded well to a new optical network terminal in the room to enable extremely high data rate communication

In this study, we consider a multi-cell millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) system with a mixed analog-to-digital converter (mixed-ADC) and hybrid beamforming architecture, in which antenna selection is applied to achieve intelligent assignment of high- and low-resolution ADCs. Both exact and approximate closed-form expressions for the uplink achievable rate are derived

In recent years, the conventional degrees of freedom in frequency and time have been fully used. It is difficult to further improve the performance of communication systems with such degrees of freedom. Orbital angular momentum (OAM), which provides a new degree of freedom for millimeter-wave (mmWave) wireless communication systems, has been recognized as a key enabling technique for future mobile

The deployment of millimeter-wave (mmWave) cellular systems in dense urban environments with an acceptable coverage and cost-efficient transmission scheme is essential for the rollout of fifth-generation and beyond technology. In this paper, cluster-based analysis of mmWave channel characteristics in two typical dense urban environments is performed. First, radio propagation measurement campaigns are

With the increased demand for unmanned driving technology and big-data transmission between vehicles, millimeter-wave (mmWave) technology, due to its characteristics of large bandwidth and low latency, is considered to be the key technology in future vehicular communication systems. Different from traditional cellular communication, the vehicular communication environment has the characteristics of