As wireless communication continues to develop in limited frequency resource environments, it is becoming important to identify the state of spectrum utilization and predict the amount needed in future. It is essential to collect reliable information for data analysis. This paper introduces a platform that enables the gathering of the scheduling information of a long‐term evolution (LTE) cellular system

Abstractive text summarization is a process of making a summary of a given text by paraphrasing the facts of the text while keeping the meaning intact. The manmade summary generation process is laborious and time‐consuming. We present here a summary generation model that is based on multilayered attentional peephole convolutional long short‐term memory (MAPCoL; LSTM) in order to extract abstractive

In this paper, we propose one‐bit feedback‐based distributed beamforming (DBF) techniques for simultaneous wireless information and power transfer in interference channels where the information transfer and power transfer networks coexist in the same frequency spectrum band. In a power transfer network, multiple distributed energy transmission nodes transmit their energy signals to a single energy

With cyberattack techniques on the rise, there have been increasing developments in the detection techniques that defend against such attacks. However, cyber attackers are now developing fileless malware to bypass existing detection techniques. To combat this trend, security vendors are publishing analysis reports to help manage and better understand fileless malware. However, only fragmentary analysis

The objective of this study was to implement an in vitro exposure system for 28 GHz to investigate the biological effects of fifth‐generation (5G) communication. A signal source of 28 GHz for 5G millimeter‐wave (MMW) deployment was developed, followed by a variable attenuator for antenna input power control. A power amplifier was also customized to ensure a maximum output power of 10 W for high‐power

Distributed consensus requires the consent of more than half of the congress to produce irreversible results, and the performance of the consensus algorithm deteriorates with the increase in the number of nodes. This problem can be addressed by delegating the agreement to a few selected nodes. Since the selected nodes must comply with the Byzantine node ratio criteria required by the algorithm, the

We propose 8.2‐GHz band radar RFICs for an 8 × 8 phased‐array frequency‐modulated continuous‐wave receiver developed using 65‐nm CMOS technology. This receiver panel is constructed using a multichip solution comprising fabricated 2 × 2 low‐noise amplifier phase‐shifter (LNA‐PS) chips and a 4ch RX front‐end chip. The LNA‐PS chip has a novel phase‐shifter circuit for low‐voltage operation, novel active

This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to

Traditional wisdom on how late industrialized countries follow the technology trajectories of preceding economies is in need of reformation as these countries have attained industrial leadership in a growing number of fields. However, current understandings about these countries' development of their emerging technologies have yet to investigate the divergence of idiosyncratic technology trajectories

Several methods exist for detecting hacking programs operating within online games. However, a significant amount of computational power is required to detect the illegal access of a hacking program in game clients. In this study, we propose a novel detection method that analyzes the protected memory area and the hacking program's process in real time. Our proposed method is composed of a three‐step

The World Health Organization provides guidelines for managing the particulate matter (PM) level because a higher PM level represents a threat to human health. To manage the PM level, a procedure for measuring the PM value is first needed. We use a PM sensor that collects the PM level by laser‐based light scattering (LLS) method because it is more cost effective than a beta attenuation monitor‐based

The Joint Video Exploration Team (JVET) has studied future video coding (FVC) technologies with a potential compression capacity that significantly exceeds that of the high‐efficiency video coding (HEVC) standard. The joint exploration test model (JEM), a common platform for the exploration of FVC technologies in the JVET, employs quadtree plus binary tree block partitioning, which enhances the flexibility

The research domain of underwater communication has garnered much interest among researchers exploring underwater activities. The underwater environment differs from the terrestrial setting. Some of the main challenges in underwater communication are limited bandwidth, low data rate, propagation delay, and high bit error rate (BER). As such, this study assessed the underwater acoustic (UWA) aspect

The evolution of blockchain‐based systems has enabled researchers to develop next‐generation e‐voting systems. However, the classical consensus method of blockchain, that is, Proof‐of‐Work, as implemented in Bitcoin, has a significant impact on energy consumption and compromises the scalability, efficiency, and latency of the system. In this paper, we propose a hybrid consensus model (PSC‐Bchain) composed

Several code‐division multiple access (CDMA)‐based interconnect schemes have been recently proposed as alternatives to the conventional time‐division multiplexing bus in multicore systems‐on‐chip. CDMA systems with a dynamic assignment of spreading codewords are particularly attractive because of their potential for higher bandwidth efficiency compared with the systems in which the codewords are statically

This article presents a multi‐dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made

Fifth generation (5G) mobile systems are designed to support voice, data, video, games, smart grids, smart factories, intelligent building systems (IBS), Internet of Things (IoT), cyber physical systems (CPSs), autonomous vehicles, connected vehicles, intelligent transportation systems (ITS), and much more. In addition, various novel designs for Beyond 5G (B5G) technologies are now being proposed.

Sixth generation will exploit satellite, aerial, and terrestrial platforms jointly to improve radio access capability and unlock the support of on‐demand edge cloud services in three‐dimensional (3D) space, by incorporating mobile edge computing (MEC) functionalities on aerial platforms and low‐orbit satellites. This will extend the MEC support to devices and network elements in the sky and forge a

In edge computing, most procedures, including data collection, data processing, and service provision, are handled at edge nodes and not in the central cloud. This decreases the processing burden on the central cloud, enabling fast responses to end‐device service requests in addition to reducing bandwidth consumption. However, edge nodes have restricted computing, storage, and energy resources to support

5G AgiLe and fLexible integration of SaTellite And cellulaR (5G‐ALLSTAR) is a Korea‐Europe (KR‐EU) collaborative project for developing multi‐connectivity (MC) technologies that integrate cellular and satellite networks to provide seamless, reliable, and ubiquitous broadband communication services and improve service continuity for 5G and beyond. The main scope of this project entails the prototype

In this paper, we propose a supervised‐learning‐based spatial performance prediction (SLPP) framework for next‐generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data

Because of the rapid increase of mobile traffic, flexible broadband supportive unmanned aerial vehicle (UAV)‐based 6G mobile networks using free space optical (FSO) links have been recently proposed. Considering the advancements made in UAVs, big data processing, and artificial intelligence precision control technologies, the formation of an additional wireless network based on UAV aerial platforms

Recently, to make the best use of limited and precious spectrum resources, spectrum sharing between satellite and cellular networks has received much interest. In this study, we mathematically analyze the success probability of a fixed (satellite) earth station (FES) based on a stochastic geometry framework. Both the FES and base stations (BSs) are assumed to be equipped with a directional antenna

Recently, there is an increasing demand for ultra‐low‐latency (ULL) services such as factory automation, autonomous driving, and telesurgery that must meet an end‐to‐end latency of less than 10 ms. Fifth‐generation (5G) New Radio guarantees 0.5 ms one‐way latency, so the feasibility of ULL services is higher than in previous mobile communications. However, this feasibility ensures performance at the

A 40 nm complementary metal oxide semiconductor carrier‐aggregated drive amplifier with high linearity is presented for sub‐GHz Internet of Things applications. The proposed drive amplifier consists of two high linear amplifiers, which are composed of five differential cascode cells. Carrier aggregation can be achieved by switching on both the driver amplifiers simultaneously and combining the two

In this study, an E‐band low‐noise amplifier (LNA) monolithic microwave integrated circuit (MMIC) has been designed using silicon‐germanium 130‐nm bipolar complementary metal‐oxide‐semiconductor technology to suppress unwanted signal gain outside operating frequencies and improve the signal gain and noise figures at operating frequencies. The proposed impedance‐controllable filter has series (Rs) and

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation

It is necessary to achieve high performance in the task of zero anaphora resolution (ZAR) for completely understanding the texts in Korean, Japanese, Chinese, and various other languages. Deep‐learning‐based models are being employed for building ZAR systems, owing to the success of deep learning in the recent years. However, the objective of building a high‐quality ZAR system is far from being achieved

As low‐power wide‐area network (LPWAN) end devices (EDs) are deployed in massive scale, their economic and environmental costs of operation are becoming too significant to ignore and too difficult to estimate. While LPWAN architectures and protocols are designed to primarily save energy, this study shows that energy saving does not necessarily lead to lower cost or environmental footprint of the network

The filtered orthogonal frequency division multiplexing (F‐OFDM) system has been recommended as a waveform candidate for fifth‐generation (5G) communications. The suppression of out‐of‐band emission (OOBE) and asynchronous transmission are the distinctive features of the filtering‐based waveform frameworks. Meanwhile, the high peak‐to‐average power ratio (PAPR) is still a challenge for the new waveform

In the last few years, detection has become a powerful methodology for network protection and security. This paper presents a new detection scheme for data recorded over a computer network. This approach is applicable to the broad scientific field of information security, including intrusion detection and prevention. The proposed method employs bidimensional (time‐frequency) data representations of

Space‐based automatic dependent surveillance‐broadcast (ADS‐B) is an important emerging augmentation of existing ground‐based ADS‐B systems. In this paper, the problem of space‐based ultra‐long‐range reception processing of ADS‐B signals is described. We first introduce a header detection method for accurately determining the pulse position of a weak ADS‐B signal. We designed a signal encoding method

Self‐recovery is a tamper‐detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region‐based scalable self‐recovery (RSS) method is proposed for salient‐object images. As the images consist of two main regions, the region of interest

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

MapReduce is a framework that can process huge datasets in parallel and distributed computing environments. However, a single machine failure during the runtime of MapReduce tasks can increase completion time by 50%. MapReduce handles task failures by restarting the failed task and re‐computing all input data from scratch, regardless of how much data had already been processed. To solve this issue

We developed a 0.1‐μm metamorphic high electron mobility transistor and fabricated a W‐band monolithic microwave integrated circuit chipset with our in‐house technology to verify the performance and usability of the developed technology. The DC characteristics were a drain current density of 747 mA/mm and a maximum transconductance of 1.354 S/mm; the RF characteristics were a cutoff frequency of 210 GHz

We present AB9, a neural processor for inference acceleration. AB9 consists of a systolic tensor core (STC) neural network accelerator designed to accelerate artificial intelligence applications by exploiting the data reuse and parallelism characteristics inherent in neural networks while providing fast access to large on‐chip memory. Complementing the hardware is an intuitive and user‐friendly development

This study presents a new architecture for a field programmable analog array (FPAA) for use in low‐frequency applications, and a generalized circuit realization method for the implementation of nth‐order elliptic filters. The proposed designs of both the FPAA and elliptic filters are based on the operational transconductance amplifier (OTA) used in implementing OTA‐C filters for biopotential signal

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

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

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

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