Artificial Intelligence (AI) has evolved into a general technology for a wide range of purposes and has been applied in all aspects of economy and society. It has already been extensively used in various fields, including medical services, finance, security, education, transportation, and logistics, and had led to the emergence of new commercial activities, business models, and game‐changing product

More than 42 000 fires occur nationwide and cause over 2500 casualties every year. There is a lack of specialized equipment, and rescue operations are conducted with a minimal number of apparatuses. Through‐the‐wall radars (TTWRs) can improve the rescue efficiency, particularly under limited visibility due to smoke, walls, and collapsed debris. To overcome detection challenges and maintain a small‐form

High‐level synthesis (HLS), which automatically synthesizes a register‐transfer level (RTL) circuit from a behavioral description written in a high‐level programming language such as C/C++, is becoming a more popular technique for improving design productivity. In general, HLS tools often generate a circuit with a larger area than those of hand‐designed ones. One reason for this issue is that HLS tools

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high‐speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C‐means

This paper presents an efficient hardware random‐number generator based on a beta source. The proposed generator counts the values of “0” and “1” and provides a method to distinguish between pseudo‐random and true random numbers by comparing them using simple cumulative operations. The random‐number generator produces labeled data indicating whether the count value is a pseudo‐ or true random number

The proposed AI processor architecture has high throughput for accelerating the neural network and reduces the external memory bandwidth required for processing the neural network. For achieving high throughput, the proposed super thread core (STC) includes 128 × 128 nano cores operating at the clock frequency of 1.2 GHz. The function‐safe architecture is proposed for a fault‐tolerance system such

The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high‐performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high‐performance accelerators along with dataflow control. Furthermore, the processing of various neural networks (NNs) requires a flexible memory architecture, programmable control

The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR‐E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linea

This paper addresses Very large‐scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such

This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers

Herein, we present a compact transversal bandpass filter (BPF) with an extremely wide upper stopband and multiple transmission zeros (TZ). Three signal transmission paths with shorted stubs and open‐coupled lines allow signal transmission from input port to output port. Two resonant modes can be excited simultaneously and managed easily for bandpass response. Eleven TZs are achieved via transmission

The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile, the inference of the model depends on the efficient online variational Bayesian approach, which enhances the information exchange between the whole

Measuring the diffraction loss for high frequencies, long distances, and large diffraction angles is difficult because of the high path loss. Securing a well‐controlled environment to avoid reflected waves also makes long‐range diffraction measurements challenging. Thus, the prediction of diffraction loss at millimeter‐wave frequency bands relies on theoretical models, such as the knife‐edge diffraction

Quantum‐dot cellular automata (QCA) is an alternative complementary metal‐oxide‐semiconductor (CMOS) technology that is used to implement high‐speed logical circuits at the atomic or molecular scale. In this study, an optimal 2‐to‐4 decoder in QCA is presented. The proposed QCA decoder is designed using a new formulation based on the MV32 gate. Notably, the MV32 gate has three inputs and two outputs

Noncontiguous orthogonal frequency division multiplexing (NC‐OFDM)‐based cognitive radio (CR) systems achieve highly efficient spectrum utilization by transmitting unlicensed users' data on subcarriers of licensed users’ data when they are free. However, there are two disadvantages to the NC‐OFDM system: out‐of‐band power (OBP) and a high peak‐to‐average power ratio (PAPR). OBP arises due to side lobes

Integration of multiple communication technologies in a smart grid (SG) enables employing cognitive radio (CR) technology for improving reliability and security with low latency by adaptively and effectively allocating spectral resources. The versatile features of the CR enable the smart meter to select either the unlicensed or the licensed band for transmitting data to the utility company, thus reducing

A frequency diverse array (FDA) multiple‐input multiple‐output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle‐range‐dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive

Scaling is an important operation because of the iterative nature of arithmetic processes in digital signal processors (DSPs). In residue number system (RNS)–based DSPs, scaling represents a performance bottleneck based on the complexity of inter‐modulo operations. To design an efficient RNS scaler for special moduli sets, a body of literature has been dedicated to the study of the well‐known moduli

We propose a two‐dimensional (2D) scattering‐center‐extraction (SCE) method using sparse recovery based on the compressive‐sensing theory, even with data missing from the received radar cross‐section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal‐spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single

Quadrature spatial modulation (QSM) utilizes the in‐phase and quadrature spatial dimensions to transmit the real and imaginary parts of a single signal symbol, respectively. The improved QSM (IQSM) transmits two signal symbols per channel use through a combination of two antennas for each of the real and imaginary parts. The main contributions of this study can be summarized as follows. First, we derive

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers

Using 23 867 standard essential patents claimed for three different wireless telecommunication standards (GSM, WCDMA, and LTE), this research examined the difference in technological importance and breadth of patents between practicing and non‐practicing entities. We discovered that compared to manufacturers and service providers, organizations who do not appropriate innovation‐derived profits directly

Electromagnetic (EM) waves used to send signals under seawater are normally restricted to low frequencies () because of sudden exponential increases of attenuation () at higher . The mathematics of EM wave propagation in seawater demonstrate dependence on relative permeability (), relative permittivity (), conductivity (), and of transmission. Estimation of and based on the W. Ellison interpolation

Two‐dimensional torus network nodes are typically interconnected using XY routing algorithm for transmitting a packet from a source node to a destination node. In XY routing, if all the paths are used efficiently, the throughput and latency can be improved. In this paper, to utilize all the paths efficiently, we propose a novel binary optical routing algorithm (BORA) to improve the throughput and latency

This paper presents an automatic proficiency assessment method for a non‐native Korean read utterance using bidirectional long short–term memory (BLSTM)–based acoustic models (AMs) and speech data augmentation techniques. Specifically, the proposed method considers two scenarios, with and without prompted text. The proposed method with the prompted text performs (a) a speech feature extraction step

We herein propose a heuristic redundancy selection algorithm that combines resubmission, replication, and checkpointing redundancies to reduce the resiliency overhead in fault‐tolerant workflow scheduling. The appropriate combination of these redundancies for workflow tasks is obtained in two consecutive phases. First, to compute the replication vector (number of task replicas), we apportion the set

The reconstruction of archaeological fragments in 3D geometry is an important problem in pattern recognition and computer vision. Therefore, we implement an algorithm with the help of a 3D model to perform reconstruction from the real datasets using the slope features. This approach avoids the problem of gaps created through the loss of parts of the artifacts. Therefore, the aim of this study is to

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple‐input multiple‐output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space‐time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency

Unusual data patterns or outliers can be generated because of human errors, incorrect measurements, or malicious activities. Detecting outliers is a difficult task that requires complex ensembles. An ideal outlier detection ensemble should consider the strengths of individual base detectors while carefully combining their outputs to create a strong overall ensemble and achieve unbiased accuracy with

A spectrally encapsulated (SE) orthogonal frequency‐division multiplexing (OFDM) precoding scheme for wireless short packet transmission, which can suppress the out‐of‐band emission (OoBE) while maintaining the advantage of the cyclic prefix (CP)‐OFDM, is proposed. The SE‐OFDM symbol consists of a prefix, an inverse fast Fourier transform (IFFT) symbol, and a suffix generated by the head, center, and

Network security situation prediction is difficult due to its strong uncertainty, but DS evidence theory performs well in solving the problem of uncertainty. Based on DS evidence theory, this study analyzed the prediction of the network security situation, designed a prediction model based on the improved DS evidence theory, and carried out a simulation experiment. The experimental results showed that

In this study, an efficient scheme for hiding data directly in partially encrypted versions of high efficiency video coding (HEVC) videos is proposed. The content owner uses stream cipher to selectively encrypt some HEVC‐CABAC bin strings in a format‐compliant manner. Then, the data hider embeds the secret message into the encrypted HEVC videos using the specific coefficient modification technique

Highly dispersive S‐boxes are desirable in cryptosystems as nonlinear confusion sub‐layers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information

We present a novel GPU‐based ray‐casting algorithm for volume rendering of unstructured grid data. Our volume rendering system uses a ray‐casting method that guarantees accurate rendering results. We also employ the per‐pixel intersection list concept in the Bunyk algorithm to guarantee an accurate result for non‐convex meshes. For efficient memory access for the lists on the GPU, we represent the

To recover the neural activity from Magnetoencephalography (MEG) and Electroencephalography (EEG) measurements, we need to solve the inverse problem by utilizing the relation between dipole sources and the data generated by dipolar sources. In this study, we propose a new approach based on the implementation of a particle filter (PF) that uses minimum sampling variance resampling methodology to track

Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users

The non‐orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi‐carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource

Human–object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters

A hierarchical iterative algorithm for the canonical polyadic decomposition (CPD) of tensors is proposed by improving the traditional conjugate gradient least squares (CGLS) method. Methods based on algebraic operations are investigated with the objective of estimating the direction of arrival (DoA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector‐sensors

The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish

Herein, a low‐ripple coarse‐fine digital low‐dropout regulator (D‐LDO) without ringing in the transient state is proposed. Conventional D‐LDO suffers from a ringing problem when settling the output voltage at a large load transition, which increases the settling time. The proposed D‐LDO removes the ringing and reduces the settling time using an auxiliary power stage which adjusts its output current

As side‐channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side‐channel analysis. However, a drawback of machine learning algorithms is that their performance depends on human engineering. Therefore, recent studies in the field focus on exploiting deep learning algorithms, which can extract

In real‐world intelligent transportation systems, accuracy in vehicle license plate detection and recognition is considered quite critical. Many algorithms have been proposed for still images, but their accuracy on actual videos is not satisfactory. This stems from several problematic conditions in videos, such as vehicle motion blur, variety in viewpoints, outliers, and the lack of publicly available

Three‐dimensional (3D) selfie services, one of the major 3D printing services, print 3D models of an individual's face via scanning. However, most of these services require expensive full‐color supporting 3D printers. The high cost of such printers poses a challenge in launching a variety of 3D printing application services. This paper presents a stencil‐based 3D facial relief creation method employing

We consider a hybrid combiner design for downlink massive multiple‐input multiple‐output systems when there is residual inter‐user interference and each user is equipped with a limited number of radio frequency (RF) chains (less than the number of receive antennas). We propose a hybrid combiner that minimizes the mean‐squared error (MSE) between the information symbols and the ones estimated with a

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps

The study reports on the design and performance of two air‐filled and two partial ethanol‐filled photonic crystal fiber (PCF) structures with a tetra core for supercontinuum generation. The PCFs are nonlinear with ultra‐flattened zero dispersion. Holes with smaller areas are used to create a tetra‐core PCF structure. Ethanol is filled in the holes of smaller area while the larger holes of cladding

Directional sensor networks (DSNs) can significantly improve the performance of a network by employing energy efficient communication protocols. Neighbor discovery is a vital part of medium access control (MAC) and routing protocol, which influences the establishment of communication between neighboring nodes. Neighbor discovery is a challenging task in DSNs due to the limited coverage provided by

Detecting visual relationships in an image is important in an image understanding task. It enables higher image understanding tasks, that is, predicting the next scene and understanding what occurs in an image. A visual relationship comprises of a subject, a predicate, and an object, and is related to visual, language, and spatial cues. The predicate explains the relationship between the subject and

Massive computation of the reconstruction algorithm for compressive sensing (CS) has been a major concern for its real‐time application. In this paper, we propose a novel high‐speed architecture for the orthogonal matching pursuit (OMP) algorithm, which is the most frequently used to reconstruct compressively sensed signals. The proposed design offers a very high throughput and includes an innovative

Open‐source software development projects are well suited for exploring new ideas and acquiring knowledge from developers outside of the project. In this paper, we examine the impact of external developers on innovation in open‐source software development from the perspective of organizational learning theory. We examine the roles of external and internal developers, who “explore” and “exploit,” respectively

An arbiter physical unclonable function (APUF) has exponential challenge‐response pairs and is easy to implement on field‐programmable gate arrays (FPGAs). However, modeling attacks based on machine learning have become a serious threat to APUFs. Although the modeling‐attack resistance of an MA‐APUF has been improved considerably by architecture modifications, the response generation method of an MA‐APUF

A denial‐of‐service (DoS) attack is a serious attack that targets web applications. According to Imperva, DoS attacks in the application layer comprise 60% of all the DoS attacks. Nowadays, attacks have grown into application‐ and business‐layer attacks, and vulnerability‐analysis tools are unable to detect business‐layer vulnerabilities (logic‐related vulnerabilities). This paper presents the business‐layer

In this paper, a blind symbol timing offset (STO) estimation method is proposed for offset quadrature phase‐shift keying (OQPSK) modulated signals, which also works for other linearly modulated signals (LMS) such as binary‐PSK, QPSK, π /4‐QPSK, and minimum‐shift keying. There are various methods available for blind STO estimation of LMS; however, none work in the case of OQPSK modulated signals. The

A correlation exists between luminance samples and chrominance samples of a color image. It is beneficial to exploit such interchannel redundancy for color image compression. We propose an algorithm that predicts chrominance components Cb and Cr from the luminance component Y. The prediction model is trained by supervised learning with Laplacian‐regularized least squares to minimize the total prediction