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Implementation of platform for long‐term evolution cell perspective resource utilization analysis ETRI J. (IF 1.094) Pub Date : 2020-12-22 Jungsun Um; Igor Kim; Seungkeun Park
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
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Multi‐layered attentional peephole convolutional LSTM for abstractive text summarization ETRI J. (IF 1.094) Pub Date : 2020-12-18 Md. Motiur Rahman; Fazlul Hasan Siddiqui
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
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Real‐time implementation of distributed beamforming for simultaneous wireless information and power transfer in interference channels ETRI J. (IF 1.094) Pub Date : 2020-12-18 Yong‐Gi Hong; SeongJun Hwang; Jiho Seo; Jonghyeok Lee; Jaehyun Park
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
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Fileless cyberattacks: Analysis and classification ETRI J. (IF 1.094) Pub Date : 2020-12-17 GyungMin Lee; ShinWoo Shim; ByoungMo Cho; TaeKyu Kim; Kyounggon Kim
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
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Implementation of an in vitro exposure system for 28 GHz ETRI J. (IF 1.094) Pub Date : 2020-12-08 Young Seung Lee; Philip Ayiku Dzagbletey; Jae‐Young Chung; Sang Bong Jeon; Ae‐Kyoung Lee; Nam Kim; Seong Jong Song; Hyung‐Do Choi
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
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Algorithm based on Byzantine agreement among decentralized agents (BADA) ETRI J. (IF 1.094) Pub Date : 2020-10-20 Jintae Oh; Joonyoung Park; Youngchang Kim; Kiyoung Kim
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
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8.2‐GHz band radar RFICs for an 8 × 8 phased‐array FMCW receiver developed with 65‐nm CMOS technology ETRI J. (IF 1.094) Pub Date : 2020-10-14 Seon‐Ho Han; Bon‐Tae Koo
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
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A lightweight true random number generator using beta radiation for IoT applications ETRI J. (IF 1.094) Pub Date : 2020-11-12 Kyunghwan Park; Seongmo Park; Byoung Gun Choi; Taewook Kang; Jongbum Kim; Young‐Hee Kim; Hong‐Zhou Jin
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
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Divergence of knowledge production strategies for emerging technologies between late industrialized countries: Focusing on quantum technology ETRI J. (IF 1.094) Pub Date : 2020-12-10 Inje Kang; Jae‐Yong Choung; Dong‐in Kang; Inyong Park
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
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A method for preventing online games hacking using memory monitoring ETRI J. (IF 1.094) Pub Date : 2020-12-08 Chang Seon Lee; Huy Kang Kim; Hey Rin Won; Kyounggon Kim
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
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Anomaly detection in particulate matter sensor using hypothesis pruning generative adversarial network ETRI J. (IF 1.094) Pub Date : 2020-12-08 YeongHyeon Park; Won Seok Park; Yeong Beom Kim
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
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Adaptive block tree structure for video coding ETRI J. (IF 1.094) Pub Date : 2020-12-06 Aram Baek; Daehyeok Gwon; Sohee Son; Jinho Lee; Jung‐Won Kang; Hui Yong Kim; Haechul Choi
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
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Filter orthogonal frequency‐division multiplexing scheme based on polar code in underwater acoustic communication with non‐Gaussian distribution noise ETRI J. (IF 1.094) Pub Date : 2020-12-06 Mustafa Sami Ahmed; Nor Shahida Mohd Shah; Yasin Yousif Al‐Aboosi; Mohammed S. M. Gismalla; Mohammad F. L. Abdullah; Yasir Amer Jawhar; Mohammed Balfaqih
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
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Secure large‐scale E‐voting system based on blockchain contract using a hybrid consensus model combined with sharding ETRI J. (IF 1.094) Pub Date : 2020-11-30 Yousif Abuidris; Rajesh Kumar; Ting Yang; Joseph Onginjo
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
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Distributed arbitration scheme for on‐chip CDMA bus with dynamic codeword assignment ETRI J. (IF 1.094) Pub Date : 2020-11-26 Tatjana R. Nikolic; Goran S. Nikolic; Goran Lj. Djordjevic
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
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A multi‐dimensional crime spatial pattern analysis and prediction model based on classification ETRI J. (IF 1.094) Pub Date : 2020-11-26 Gaurav Hajela; Meenu Chawla; Akhtar Rasool
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
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Special issue on 5G & B5G enabling edge computing, big data and deep learning technologies ETRI J. (IF 1.094) Pub Date : 2020-11-16 Sang‐Chul Kim; Taesang Choi; Sejun Song; Emilio Calvanese Strinati; Jong‐Moon Chung
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.
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6G in the sky: On‐demand intelligence at the edge of 3D networks (Invited paper) ETRI J. (IF 1.094) Pub Date : 2020-10-20 Emilio Calvanese Strinati; Sergio Barbarossa; Taesang Choi; Antonio Pietrabissa; Alessandro Giuseppi; Emanuele De Santis; Josep Vidal; Zdenek Becvar; Thomas Haustein; Nicolas Cassiau; Francesca Costanzo; Junhyeong Kim; Ilgyu Kim
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
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Performance analysis of local exit for distributed deep neural networks over cloud and edge computing ETRI J. (IF 1.094) Pub Date : 2020-10-18 Changsik Lee; Seungwoo Hong; Sungback Hong; Taeyeon Kim
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
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Design of cellular, satellite, and integrated systems for 5G and beyond ETRI J. (IF 1.094) Pub Date : 2020-11-16 Junhyeong Kim; Guido Casati; Nicolas Cassiau; Antonio Pietrabissa; Alessandro Giuseppi; Dong Yan; Emilio Calvanese Strinati; Marjorie Thary; Danping He; Ke Guan; Heesang Chung; Ilgyu Kim
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
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A supervised‐learning‐based spatial performance prediction framework for heterogeneous communication networks ETRI J. (IF 1.094) Pub Date : 2020-11-16 Shubhabrata Mukherjee; Taesang Choi; Md Tajul Islam; Baek‐Young Choi; Cory Beard; Seuck Ho Won; Sejun Song
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
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Combined time bound optimization of control, communication, and data processing for FSO‐based 6G UAV aerial networks ETRI J. (IF 1.094) Pub Date : 2020-11-16 Seungwoo Seo; Da‐Eun Ko; Jong‐Moon Chung
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
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Performance analysis of satellite and terrestrial spectrum‐shared networks with directional antenna ETRI J. (IF 1.094) Pub Date : 2020-11-16 Jeong Seon Yeom; Gosan Noh; Heesang Chung; Ilgyu Kim; Bang Chul Jung
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
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Ultra‐low‐latency services in 5G systems: A perspective from 3GPP standards ETRI J. (IF 1.094) Pub Date : 2020-11-16 Sunmi Jun; Yoohwa Kang; Jaeho Kim; Changki Kim
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
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A dual‐path high linear amplifier for carrier aggregation ETRI J. (IF 1.094) Pub Date : 2020-10-07 Dong‐Woo Kang; Jang‐Hong Choi
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
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E‐band low‐noise amplifier MMIC with impedance‐controllable filter using SiGe 130‐nm BiCMOS technology ETRI J. (IF 1.094) Pub Date : 2020-10-12 Woojin Chang; Jong‐Min Lee; Seong‐Il Kim; Sang‐Heung Lee; Dong Min Kang
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
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A precise sensor fault detection technique using statistical techniques for wireless body area networks ETRI J. (IF 1.094) Pub Date : 2020-11-11 Smrithy Girijakumari Sreekantan Nair; Ramadoss Balakrishnan
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
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Zero‐anaphora resolution in Korean based on deep language representation model: BERT ETRI J. (IF 1.094) Pub Date : 2020-10-25 Youngtae Kim; Dongyul Ra; Soojong Lim
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
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Can energy optimization lead to economic and environmental waste in LPWAN architectures? ETRI J. (IF 1.094) Pub Date : 2020-10-25 Mina Rady; Jean‐Philippe Georges; Francis Lepage
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
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Improving PAPR performance of filtered OFDM for 5G communications using PTS ETRI J. (IF 1.094) Pub Date : 2020-10-18 Yasir Amer Al‐Jawhar; Khairun N. Ramli; Montadar Abas Taher; Nor Shahida M. Shah; Salama A. Mostafa; Bashar Ahmed Khalaf
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
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Network intrusion detection method based on matrix factorization of their time and frequency representations ETRI J. (IF 1.094) Pub Date : 2020-10-12 Spiros Chountasis; Dimitrios Pappas; Dimitris Sklavounos
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
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Parameter estimation of weak space‐based ADS‐B signals using genetic algorithm ETRI J. (IF 1.094) Pub Date : 2020-10-11 Feng Tao; Liang Jun
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
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Region‐based scalable self‐recovery for salient‐object images ETRI J. (IF 1.094) Pub Date : 2020-09-07 Navid Daneshmandpour; Habibollah Danyali; Mohammad Sadegh Helfroush
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
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Special issue on SoC and AI processors ETRI J. (IF 1.094) Pub Date : 2020-08-10 Ji‐Hoon Kim; Minjae Lee; Jongsun Park; Ho‐Young Cha
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
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Task failure resilience technique for improving the performance of MapReduce in Hadoop ETRI J. (IF 1.094) Pub Date : 2020-08-18 Kavitha C; Anita X
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
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W‐Band MMIC chipset in 0.1‐μm mHEMT technology ETRI J. (IF 1.094) Pub Date : 2020-08-14 Jong‐Min Lee, Woo‐Jin Chang, Dong Min Kang, Byoung‐Gue Min, Hyung Sup Yoon, Sung‐Jae Chang, Hyun‐Wook Jung, Wansik Kim, Jooyong Jung, Jongpil Kim, Mihui Seo, Sosu Kim
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
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AB9: A neural processor for inference acceleration ETRI J. (IF 1.094) Pub Date : 2020-08-12 Yong Cheol Peter Cho, Jaehoon Chung, Jeongmin Yang, Chun‐Gi Lyuh, HyunMi Kim, Chan Kim, Je‐seok Ham, Minseok Choi, Kyoungseon Shin, Jinho Han, Youngsu Kwon
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
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Field programmable analog arrays for implementation of generalized nth‐order operational transconductance amplifier‐C elliptic filters ETRI J. (IF 1.094) Pub Date : 2020-08-12 Maha S. Diab, Soliman A. Mahmoud
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
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An impulse radio (IR) radar SoC for through‐the‐wall human‐detection applications ETRI J. (IF 1.094) Pub Date : 2020-08-08 Piljae Park, Sungdo Kim, Bontae Koo
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
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Function‐level module sharing techniques in high‐level synthesis ETRI J. (IF 1.094) Pub Date : 2020-08-07 Hiroki Nishikawa, Kenta Shirane, Ryohei Nozaki, Ittetsu Taniguchi, Hiroyuki Tomiyama
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
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PSO‐optimized Pareto and Nash equilibrium gaming‐based power allocation technique for multistatic radar network ETRI J. (IF 1.094) Pub Date : 2020-08-05 Thoka Harikala; Ravinutala Satya Narayana
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
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Efficient hardware implementation and analysis of true random‐number generator based on beta source ETRI J. (IF 1.094) Pub Date : 2020-08-04 Seongmo Park, Byoung Gun Choi, Taewook Kang, Kyunghwan Park, Youngsu Kwon, Jongbum Kim
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
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40‐TFLOPS artificial intelligence processor with function‐safe programmable many‐cores for ISO26262 ASIL‐D ETRI J. (IF 1.094) Pub Date : 2020-08-02 Jinho Han, Minseok Choi, Youngsu Kwon
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
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Automated optimization for memory‐efficient high‐performance deep neural network accelerators ETRI J. (IF 1.094) Pub Date : 2020-07-29 HyunMi Kim, Chun‐Gi Lyuh, Youngsu Kwon
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
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Korean TableQA: Structured data question answering based on span prediction style with S3‐NET ETRI J. (IF 1.094) Pub Date : 2020-07-26 Cheoneum Park; Myungji Kim; Soyoon Park; Seungyoung Lim; Jooyoul Lee; Changki Lee
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
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Real‐time implementation and performance evaluation of speech classifiers in speech analysis‐synthesis ETRI J. (IF 1.094) Pub Date : 2020-07-12 Sandeep Kumar
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
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Hybrid genetic‐paired‐permutation algorithm for improved VLSI placement ETRI J. (IF 1.094) Pub Date : 2020-07-08 Vladimir V. Ignatyev; Andrey V. Kovalev; Oleg B. Spiridonov; Viktor M. Kureychik; Alexandra S. Ignatyeva; Irina B. Safronenkova
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
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Predicting numeric ratings for Google apps using text features and ensemble learning ETRI J. (IF 1.094) Pub Date : 2020-07-06 Muhammad Umer; Imran Ashraf; Arif Mehmood; Saleem Ullah; Gyu Sang Choi
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
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New framework for adaptive and agile honeypots ETRI J. (IF 1.094) Pub Date : 2020-07-06 Seamus Dowling; Michael Schukat; Enda Barrett
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
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Transversal wideband bandpass filter with a wide stopband and multiple transmission zeros ETRI J. (IF 1.094) Pub Date : 2020-06-29 Li‐Tian Wang; Yang Xiong; Zhi‐Peng Wang; Zhao Li; Xia‐Qing Li; Zhe‐Long Liang; Li Gong; Ming He
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
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Online nonparametric Bayesian analysis of parsimonious Gaussian mixture models and scenes clustering ETRI J. (IF 1.094) Pub Date : 2020-06-28 Ri‐Gui Zhou; Wei Wang
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
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Millimeter‐wave diffraction‐loss model based on over‐rooftop propagation measurements ETRI J. (IF 1.094) Pub Date : 2020-06-21 Kyung‐Won Kim; Myung‐Don Kim; Juyul Lee; Jae‐Joon Park; Young Keun Yoon; Young Jun Chong
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
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Ultradense 2‐to‐4 decoder in quantum‐dot cellular automata technology based on MV32 gate ETRI J. (IF 1.094) Pub Date : 2020-06-21 Akram Abbasizadeh; Mohammad Mosleh
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
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An optimization technique for simultaneous reduction of PAPR and out‐of‐band power in NC‐OFDM‐based cognitive radio systems ETRI J. (IF 1.094) Pub Date : 2020-06-10 Sravan Kumar Kaliki; Shiva Prasad Golla; Rama Naidu Kurukundu
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
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Adaptive algorithm for optimal real‐time pricing in cognitive radio enabled smart grid network ETRI J. (IF 1.094) Pub Date : 2020-06-04 Deepa Das, Deepak Kumar Rout
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
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Fast‐convergence trilinear decomposition algorithm for angle and range estimation in FDA‐MIMO radar ETRI J. (IF 1.094) Pub Date : 2020-06-02 Cheng Wang; Wang Zheng; Jianfeng Li; Pan Gong; Zheng Li
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
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Efficient programmable power‐of‐two scaler for the three‐moduli set {2n+p, 2n − 1, 2n+1 − 1} ETRI J. (IF 1.094) Pub Date : 2020-05-27 MohammadReza Taheri, Keivan Navi, Amir Sabbagh Molahosseini
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
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Compressive sensing‐based two‐dimensional scattering‐center extraction for incomplete RCS data ETRI J. (IF 1.094) Pub Date : 2020-05-18 Ji‐Hoon Bae; Kyung‐Tae Kim
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
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Refined identification of hybrid traffic in DNS tunnels based on regression analysis ETRI J. (IF 1.094) Pub Date : 2020-05-10 Huiwen Bai; Guangjie Liu; Jiangtao Zhai; Weiwei Liu; Xiaopeng Ji; Luhui Yang; Yuewei Dai
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
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On the performance of improved quadrature spatial modulation ETRI J. (IF 1.094) Pub Date : 2020-05-03 Tasnim Holoubi, Sheriff Murtala, Nishal Muchena, Manar Mohaisen
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
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