For a graph search algorithm, the end vertex problem is concerned with which vertices of a graph can be the last visited by this algorithm. We show that for both lexicographic depth-first search and maximum cardinality search, the end vertex problem is NP-complete on bipartite graphs, even if the maximum degree of the graph is bounded.

Today, advances in 3D modeling make it possible to identically reproduce objects, animals, humans and even entire scenes. The broad applications concern video games, virtual reality or augmented reality and cinema, for example. In this article, we propose a new method to build a 3D scene directly from several complementary photographs. The positions of the objects for which we already have a 3D model

To solve the problem of low accuracy of traditional travel route recommendation algorithm, a travel route recommendation algorithm based on interest theme and distance matching is proposed in this paper. Firstly, the real historical travel footprints of users are obtained through analysis. Then, the user’s preferences of interest theme and distance matching are proposed based on the user’s stay in

Linear canonical transform as a general integration transform has been considered into Wigner-Ville distribution (WVD) to show more powerful ability for non-stationary signal processing. In this paper, a new WVD associated with linear canonical transform (WVDL) and integration form of WVDL (IWVDL) are presented. First, the definition of WVDL is derived based on new autocorrelation function and some

In this article, a dual-layered ultra-wideband hexagonal-shaped patch antenna with an EBG structure is presented for IEEE C, X, Ku and K band applications. Parametric analysis of slots, notches, substrate height, substrate stacking, and EBG structures demonstrates the intermediate and finally optimized results. The proposed antenna (A9) is considered for desired specifications after a systematic investigation

In adaptive filters, variable step-size-based algorithms have demonstrated better performance than conventional least mean square (LMS) and normalized LMS (NLMS) algorithms in terms of convergence speed, mean square error (MSE), and signal-to-noise ratio (SNR) improvement. Recently, adaptive filters have been recommended to be implemented on field programmable gate array (FPGA) devices due to their

Generally, deep networks learn to recognize a category of objects by training on a large number of annotated images accurately. However, a meta-learning problem known as a low-shot image recognition task occurs when a few images with annotations are available for learning a recognition model for a single category. Consequently, the objects in testing/query and training/support image datasets are likely

This work proposes a new adaptive robust output feedback control method for attitude reference tracking of a quadrotor unmanned aerial vehicle without using the angular velocity measurements. By using the K-filters well known in the adaptive control community, the necessity of velocity measurements or estimating is avoided. The attitude system model is transformed into a second-order model where the

Classroom teaching quality evaluation system can enable the school’s functional departments to accurately assess the performance of the teaching staff and current teaching operations. As per the requirements for cultivating high-quality talents, planned teaching staff construction and teaching reforms need to be carried out to promote teachers’ appointments. Improving the system makes the appointment

Studying the movement characteristics of the coalmine emulsion pump valve is of great significance for optimizing the dynamic response characteristics of the pump valve, reducing the hysteresis effect, and improving the volumetric efficiency. This article combines the Internet of Things (IoT) and cellular automata techniques to investigate the movement characteristics of the valve of the emulsion pump

In the Connected Dominating Set (CDS) problem we are given a graph G and seek a min-size dominating set S such that the subgraph G[S] of G induced by S is connected. In the 2-Edge-Connected Dominating Set problem G[S] should be 2-edge-connected. We give the first non-trivial approximation algorithm for this problem, with expected approximation ratio O(log2⁡n⋅log⁡log⁡n⋅(log⁡log⁡log⁡n)3). We also show

In the digital era, innovations in business intelligence are critical to staying competitive and popular across the growing business trends. Businesses have begun to investigate the next stage of data analytics and business intelligence solutions. On the other hand, Customer Churn Prediction (CCP) is a crucial process in business decision making, which properly identifies the churn users and takes

Wireless sensor networks applications have been used in many areas that are difficult to access by humans. However, Routing remains the key challenges in sensor networks as it is important for the timely delivery of sensed datato the base station. In recent years, Multipath Routing has been used to ensure reliable and scalable data transmission in WSN. Although many multipath routing algorithms have

Intelligent reflecting surfaces (IRS)-assisted wireless transmission has recently emerged as a potential candidate to enable a smart and reconfigurable radio environment for future wireless communication systems. This paper investigates the performance of an IRS-assisted wireless communication system, where an IRS deployed on top of the source (S) acts as an intelligent access point that can adjust

MANET—Mobile Ad Hoc Network is the connection of several remote mobile nodes. These networks are dynamic and independent to move anywhere. It does not contain any central controller, and hence it is stated as a structure-less network. MANET is one of the most emerging technologies getting popular in recent days. The significant features, and real-time issues grab the research community's attention

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Printed electronics (PE) is an emerging technology that provides attractive and complementary features compared to traditional wafer-scale silicon fabrication, such as flexible substrate and point-of-use ultralow-cost manufacturing. The low-cost manufacturing and larger feature sizes mandate reduced complexity in circuit size and also limited and transparent printing layers. This enables optical inspection

Emerging nonvolatile memories (NVMs), such as resistive RAM (RRAM) and spin-transfer-torque RAM (STTRAM), present exciting opportunities for data storage applications and offer improved access speeds, retention times, power consumption, and scalability. However, these technologies leak the Hamming weight of data through power side-channel during read and write operations. We propose a technique leveraging

Hardware intellectual property (IP) piracy and misuse have introduced new challenges in the semiconductor industry as untrusted parties in the IP’s life cycle may clone, reverse-engineer, or extract important design secrets from an IP. A promising solution to protect a hardware IP against such attacks is to perform logic locking, where additional logic controlled by a secret key is inserted in strategic

This article presents multiwire phase encoding (MWPE), a transition signaling technique aimed at chip-to-chip communication on silicon interposer technology, where multiple, relatively low-bandwidth transmission lines can be easily routed between high-performance dies. The encoding exploits timing correlation between transitions on multiple band-limited wires to achieve high ensemble bandwidth, potentially

Hybrid test schemes comprising on-chip test compression and logic built-in self-test are expected to play a pivotal role in the design of new integrated circuits and delivering high quality tests. As architectural differences between these two paradigms are gradually blurring, and both schemes efficiently share test logic, they become more vulnerable to unknown (X) states whose sources vary from uninitialized

This article presents an receiver (RX) only equalization (ROE) technique that eliminates feed-forward equalization (FFE) in transmitter (TX) and bandwidth improved output driver without increment of power consumption. With a help of the proposed design technique, the power consumption, circuit complexity, and design cost are improved. The proposed RX with one-tap finite-impulse response (FIR) and second-tap

To minimize the area of analog-to-digital converters (ADCs) for multichannel applications and break the SNDR limitation caused by DAC-induced nonlinearity, a more area-efficient mismatch error shaping (MES) scheme is proposed in noise shaping (NS) successive-approximation (SAR) ADC. By employing a switched-capacitor (SC) voltage divider, the proposed method makes the flash ADC and data weighted averaging

Write assists (WAs), such as negative bitline and collapse supply voltage (VDD), can effectively improve the write $V_{\text {min}}$ of static random access memory (SRAM) cells. The energy overhead associated with such assists is considerable due to the switching activities on high capacitive nodes for every write operation. In this brief, a conditional biasing WA with built-in time-based write-margin-tracking

This brief presents a novel timing mismatch background calibration algorithm for time-interleaved (TI) analog-to-digital converters (ADCs). It can calibrate an arbitrary number of channels with an arbitrary input frequency. It also increases the calibration accuracy by applying the autocorrelation functions with an expanded interval. Besides, the proposed algorithm effectively prevents the small derivative

Single event transients (SETs) have become increasingly problematic for modern CMOS circuits due to the continuous scaling of feature sizes and higher operating frequencies. Especially when involving safety-critical or radiation-exposed applications, the circuits must be designed using hardening techniques. In this brief, we present a new radiation-hardened-by-design full-adder cell on 45-nm technology

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The papers in this special section explores the state-of-the-art advances in adopting blockchain technologies for the Industrial Internet of Things (IIoT). There is a growing trend of adopting blockchain technologies to the IIoT due to the traceability, nonrepudiation, and immutability of blockchain systems. The proliferation of IIoT to industrial systems is fostering the fourth industrial revolution

When IoT meets Industry 4.0, we talk about Industrial Internet of Things (IIoT) or the use of typical Internet of Things (IoT) solutions in the industrial sector, integrating different technologies such as machine learning, big data and analytics, sensor data, Machine to Machine communication (M2M) and automation. Its application within the fourth industrial revolution has initiated a profound change

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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One of the leading speech enhancement technologies is the deep neural network-based approach, which dominates the recent development in single-channel speech enhancement. In this paper, we propose a convolutional network with multi-scale and attention mechanisms for end-to-end single-channel speech enhancement (MASENet). More specifically, the MASENet network consists of five modules, namely multi-scale

An online censoring (OC) based weighted-frequency Fourier linear combiner (OC-WFLC) adaptive filtering structure is proposed to reduce data processing costs in the estimation of pathological hand tremor (PHT) measurements. The proposed OC-WFLC is combined with the Fourier linear combiner (FLC) to effectively separate the PHT and voluntary movement from the hand tremor signal. The OC-WFLC is shown to

Signal modeling is an important technique in many engineering applications. This paper is concerned about signal modeling problem for the sine multi-frequency signals or periodic signals. In terms of different characteristics between the signal output and the signal parameters, a separable modeling scheme is presented for estimating the signal parameters. In order to seize the real-time information

The practical visual data do not necessarily lie in linear subspaces, so deep convolutional subspace clustering network is proposed to segment the practical visual data into multiple categories accurately. The original convolutional subspace clustering network contains the stacked convolutional encoder module, the stacked convolutional decoder module and the self-expression module. We firstly alter

With the proliferation of remote sensing images, how to segment buildings more accurately in remote sensing images is a critical challenge. First, most networks have poor recognition ability on high resolution images, resulting in blurred boundaries in the segmented building maps. Second, the similarity between buildings and background results in intra-class inconsistency. To address these two problems

Positive and Unlabeled learning (PU learning) has drawn plenty of attention among researchers over the last few years, where only labeled positive examples and unlabeled examples are available for training a classifier. Many classic techniques for solving PU learning problems belong to the category of “two-step strategy”. However, quite a number of them cannot extract reliable negative examples accurately

Channel estimation is the key technology to ensure reliable transmission in orthogonal frequency division multiplexing (OFDM) system. In order to improve the accuracy of the channel estimation algorithm in a low signal-to-noise ratio (SNR) channel environment, in this paper, we proposed an improved channel estimation algorithm based on the transform domain. The improved algorithm with wavelet denoising

Power quality disturbance (PQD) is essential for devices consuming electricity and meeting today’s energy trends. This study contains an effective artificial intelligence (AI) framework for analyzing single or composite defects in power quality. A convolutional neural network (CNN) architecture, which has an output powered by a gated recurrent unit (GRU), is designed for this purpose. The proposed

The evolution of cellular technology development has led to explosive growth in cellular network traffic. Accurate time-series models to predict cellular mobile traffic have become very important for increasing the quality of service (QoS) with a network. The modelling and forecasting of cellular network loading play an important role in achieving the greatest favourable resource allocation by convenient

With the development of the Internet of Things, the requirement of a wide range of human-centered services may now make use of as many computing resources for media technologies and holographic images. The IoT system can monitor the status of equipment in real-time with a robust infrared image recognition algorithm. However, few researchers discuss data mining on images with valuable information. In

In order to improve the effect of college English classroom teaching, this paper combines optical recognition to improve machine vision algorithms and uses computer optical vision technology to process teaching images. The system designed in this paper can be applied to philosophical teaching in college English classrooms. Moreover, the system can optimize teaching resources, manage teaching classrooms

In recent years, badminton has become more and more popular in national fitness programs. Amateur badminton clubs have been established all over the country, and amateur badminton events at all levels have increased significantly. Due to the lack of correct medical supervision and health guidance, many people have varying degrees of injury during sports. Therefore, it is very important to study the

In this paper a dual E–shaped patch (ESP) antenna is proposed to enhance the wider impedance bandwidth to be use for wireless communications in 5G applications. The proposed dual ESP antenna performance analysis is carried out with stub in this work. The proposed ESP antenna with stub achieving reflection coefficient below -10 dB for obtained multiple resonant bands. The dual ESP antenna operates at

This paper presents a fast configurable automatic gain control (AGC) with strong focus on fast acting control and low power consumption. This AGC includes two paths, main amplification path and gain adjusting path. Using the gain adjusting path through an extra amplifier provides a way for tracking and comparing the input signal with four adjusted thresholds to be judged for selecting the appropriate

We find the asymptotic spectral distribution of random Kummer matrix. Then we formulate and prove a free analogue of HV independence property, which is known for classical Kummer and Gamma random variables and for Kummer and Wishart matrices. We also prove a related characterization of free-Kummer and free-Poisson (Marchenko–Pastur) non-commutative random variables.

This paper considers an online two-agent scheduling problem. All jobs belong to two agents A and B, and each job is arriving over time, which means that no information of the job is known in advance before its arrival. The objective is to schedule all jobs on a single machine such that the linear combination of the makespans of the two agents, i.e. CmaxA+θCmaxB(θ≥1), is minimized. For the problem,

In recent years, in Space-Ground-Sea Wireless Networks, the rapid development of image recognition also promotes the development of images fusion. For example, the content of a single-mode medical image is very single, and the fused image contains more image information, which provides a more reliable basis for diagnosis. However, in wireless communication and medical image processing, the image fusion

Toward making the conventional carrier sense multiple access (CSMA) protocol transmit and control mobile ad hoc network systems, as well as reducing energy consumption, an adaptive multichannel multipriority two-dimensional probability detection and 1-stick joint control strategy carrier sense multiple access with variable collision duration and three-way handshake mechanisms (iCSMA for short) is proposed

By accelerating the aforementioned industrialisation and urbanisation, people’s way of life has undergone enormous changes. The incidence of overweight and obesity increases rapidly. This research first broke through the impact of basketball on improving physical health and then designed experiments separately. The experiment is divided into two experimental groups and a replacement group, with 150

Entailment is undecidable in general for Separation (SL) Logic formulæ with inductive definitions, but it has been shown to be decidable [1] if the inductive rules satisfy three conditions, namely progress, connectivity and establishment. We show that entailment is undecidable if the latter condition is dropped, thus drawing a much clearer frontier for (un)decidability.

Recently, various Cross-Domain Collaborative Filtering (CDCF) algorithms are presented to address the sparsity problem, leveraging ratings of auxiliary domains to improve target domain’s recommendation performance. Therein, two-sided CDCF algorithms have shown better performance, given the fact that they can extract both user and item information. However, as the auxiliary domains are not all related

Text understanding from natural scene images has progressively gained much interest in computer vision due to the frequent emergence of handheld or wearable devices. Sometimes, these devices capture low-quality images. As a result, the image can be disrupted with unpredictable blur caused by text movement and camera shake. Further, the problem is integrated with edge intelligence, an emerging paradigm

Today with the rapid development of the information age, the exchange of science and technology has brought closer the closeness of countries, and our country has also begun to conduct in-depth research on WSN. This research mainly discusses the computer simulation algorithm of gymnastics formation change path based on wireless sensor. In this research, an improved Leader-Follower method is designed

In this paper, we present a low complexity sparse beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA). In the proposed method, we firstly use the beamspace transformation (BT) to transform the signal model of UCA in element-space domain to that of virtual uniform linear array (ULA) in beamspace domain. Subsequently, by applying the vectoring operator on the virtual

Neither a monocular RGB camera nor a small-size microphone array is capable of accurate three-dimensional (3D) speaker localization. By taking advantage of accurate visual object detection, and audio-visual complementary sensor fusion, we formulate the three-dimensional (3D) speaker localization problem as a visual scaling factor estimation problem. As a result, we effectively reduce the traditional