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WoS SCOPUS Document Type Document Title Abstract Authors Affiliation ResearcherID (WoS) AuthorsID (SCOPUS) Author Email(s) Journal Name JCR Abbreviation ISSN eISSN Volume Issue WoS Edition WoS Category JCR Year IF JCR (%) FWCI FWCI Update Date WoS Citation SCOPUS Citation Keywords (WoS) KeywordsPlus (WoS) Keywords (SCOPUS) KeywordsPlus (SCOPUS) Language Publication Stage Publication Year Publication Date DOI JCR Link DOI Link WOS Link SCOPUS Link
Article Conformal and Ultra Shallow Junction Formation Achieved Using a Pulsed-Laser Annealing Process Integrated With a Modified Plasma Assisted Doping Method Recently, a shallow and conformal doping profile is required for promising 3D structured devices. In this study, we deposited the dopant phosphorus (P) using modified plasma assisted doping (PaD) followed by an annealing process to electrically activate the dopants. A rapid thermal annealing process (RTP) was the first approach tested for activation but it resulted in a deep junction ( > 35 nm). To reduce the junction depth, we tried the fiash lamp annealing process (FLP) to shorten the annealing time. We also predicted the annealing temperature by numerical thermal analysis, which reached 1,020 degrees C. However, the FLP resulted in a deep junction (similar to 30 nm), which was not shallow enough to suppress short channel effects. Since an even shorter annealing process was required to form a ultra-shallow junction, we tried the laser annealing process (LAP) as a promising alternative. The LAP, which had a power density of 0.3 J/cm(2), increased the surface temperature up to 1,100 degrees C with a shallow isothermal layer. Using the LAP, we achieved a USJ with an activated surface dopant concentration of 3.86 x 10(19) cm(-3) and a junction depth of 10 nm, which will allow further scaling-down of devices. Baik, Seunghun; Kwon, Dong-Jae; Kang, Hongki; Jang, Jae Eun; Jang, Jaewon; Kim, Y. S.; Kwon, Hyuk-Jun Gyeongbuk Inst Sci & Technol DGIST, Dept Informat & Commun Engn, Daegu 42988, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Lam Res Corp, Fremont, CA 94538 USA; SEMES, Hwaseong 18383, South Korea; Daegu Gyeongbuk Inst Sci & Technol DGIST, Convergence Res Adv Ctr Olfact, Daegu 42988, South Korea Kang, Hongki/AFM-2155-2022 57207761062; 57221814465; 36158223200; 15057779600; 57194107504; 57196173991; 57298892000 ys.kim@lamresearch.com;hj.kwon@dgist.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.66 2025-06-25 10 10 Annealing; Plasmas; Three-dimensional displays; Surface treatment; Silicon; Doping profiles; Ultra-shallow junction; phosphorus; plasma assisted doping; laser annealing process DOPANT DIFFUSION; SPREADING RESISTANCE; INDUCED DEFECTS; POINT-DEFECTS; SILICON; PHOSPHORUS; PROFILES; DAMAGE; FLASH Laser annealing process; Phosphorus; Plasma assisted doping; Ultra-shallow junction Pulsed lasers; Rapid thermal processing; Thermoanalysis; Annealing temperatures; Dopant concentrations; Flash lamp annealing; Laser annealing process; Pulsed laser annealing; Rapid thermal annealing process; Surface temperatures; Ultra shallow junction; Rapid thermal annealing English 2020 2020 10.1109/access.2020.3024636 바로가기 바로가기 바로가기 바로가기
Article Coupled Multipath BBR (C-MPBBR): A Efficient Congestion Control Algorithm for Multipath TCP Multipath transmission control protocol (MPTCP) is a promising transport layer protocol that enables a device to utilize multiple communication interfaces simultaneously, thereby achieving high throughput. A congestion control algorithm (CCA) employed in MPTCP constitutes a key part that controls the data flow through different subflows (SFs). There are two fundamental challenges associated with MPTCP CCAs. First, MPTCP flows should have an advantage over single-path flows; second, MPTCP flows should be fair, indicating that SFs sharing a common bottleneck should occupy a capacity fairly close to that occupied by a single-path flow. Several MPTCP CCAs have been developed; however, they have failed to satisfy these challenges in all scenarios. Recently, Google has introduced the bottleneck bandwidth and round-trip-time (BBR), a new CCA for single-path TCP, achieving high throughput with minimum delay by employing a network model. In the present paper, we propose a novel MPTCP CCA based on BBR named coupled multipath BBR (C-MPBBR) that satisfies the fundamental challenges by exploiting the concept of network modeling in BBR. C-MPBBR addresses the first challenge by closing the low-bandwidth SFs by tracking the delivery rate and bottleneck bandwidth (BtlBW). Then, it satisfies the second challenge through identifying those SFs that share a common bottleneck and dividing the BtlBW share corresponding to a SF among them. We implemented C-MPBBR in the Linux kernel, tested it on a wide range of scenarios by the Mininet emulation experiments, and the real-world Internet, and confirmed that the proposed C-MPBBR outperforms the existing MPTCP CCAs in terms of successfully satisfying the fundamental challenges by ensuring both throughput and fairness. Mahmud, Imtiaz; Lubna, Tabassum; Song, Yeong-Jun; Cho, You-Ze Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea Mahmud, Imtiaz/R-1089-2019 56203487900; 57205303733; 57210919165; 7404469829 yzcho@ee.knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.82 2025-06-25 12 18 Throughput; Bandwidth; Google; Delays; Packet loss; Protocols; Multipath TCP; multipath BBR; coupled multipath BBR; coupled congestion control FAIRNESS Coupled congestion control; Coupled multipath BBR; Multipath BBR; Multipath TCP Bandwidth; Computer operating systems; Transmission control protocol; Bottleneck bandwidth; Communication interface; High throughput; Low-bandwidth; Multi-path transmission control protocols; Network modeling; Round-trip time; Transport layer protocols; Traffic congestion English 2020 2020 10.1109/access.2020.3022720 바로가기 바로가기 바로가기 바로가기
Article CPU-Accelerator Co-Scheduling for CNN Acceleration at the Edge Convolutional neural networks (CNNs) are widely deployed for many artificial intelligence (AI) applications, such as object detection and image classification. Due to the burgeoning revolution in edge AI, CNN hardware accelerators are also being employed in resource-constrained edge devices for achieving better performance and energy efficiency at the edge. Although CNN accelerators enable fast and energy-efficient CNN inference at the edge, the remaining hardware resources on the edge devices except for the CNN accelerator remain idle, which could otherwise be utilized for attaining even better performance and energy efficiency for CNN inferences. In this paper, we propose a CPU-accelerator co-scheduling technique for convolution (CONV) layer operations ofCNNinferences in resource-constrained edge devices. Our proposed co-scheduling technique exploits an inherent parallelism in CNN output channels, that is, the operations for generating different output channels in a CONV layer can be executed in parallel. For load balancing between the CPU and the CNN accelerator, we also propose a simple, yet accurate latency model for CONV layer operations in the CPU and the accelerator. Based on the latency estimation of CONV layer operations provided by our proposed model, we distribute the tasks to the CPU and the CNN accelerator in a load-balance manner to minimize the idle period during the CONV layer operations in both the CPU and the CNN accelerator. We implement our proposed hardware/software (HW/SW) co-scheduling technique in various field-programmable gate array system-on-chip (FPGA-SoC) platforms as a proof-of-concept. Experimental results indicate that our proposed co-scheduling technique improves system performance by 1.18x- 2.00x with energy reduction of 14.9% - 49.7% as compared to the accelerator-only execution. Kim, Yeongmin; Kong, Joonho; Munir, Arslan Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Kansas State Univ, Dept Comp Sci, Manhattan, KS 66506 USA 57216737789; 25927220400; 24587067400 joonho.kong@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 1.07 2025-06-25 11 18 Convolutional neural networks; resource-constrained edge devices; co-scheduling; latency model; load balancing co-scheduling; Convolutional neural networks; latency model; load balancing; resource-constrained edge devices Acceleration; Convolution; Energy efficiency; Field programmable gate arrays (FPGA); Object detection; Programmable logic controllers; Scheduling; System-on-chip; Energy efficient; Energy reduction; Hardware accelerators; Hardware resources; Hardware/software; Inherent parallelism; Latency estimation; Proof of concept; Convolutional neural networks English 2020 2020 10.1109/access.2020.3039278 바로가기 바로가기 바로가기 바로가기
Article Cross Fusion-Based Low Dynamic and Saturated Image Enhancement for Infrared Search and Tracking Systems Unmanned aerial vehicles and battleships are equipped with the infrared search and tracking (IRST) systems for its mission to search and detect targets even in low visibility environments. However, infrared sensors are easily affected by diverse types of conditions, therefore most of IRST systems need to apply advanced contrast enhancement (CE) methods to cope with the low dynamic range of sensor output and image saturation. The general histogram equalization for infrared images has unwanted side effects such as low contrast expansion and saturation. Also, the local area processing for saturation reduction has been studied to solve the problems regarding the saturation and non-uniformity. We propose the cross fusion based adaptive contrast enhancement with three counter non-uniformity methods. We evaluate the proposed method and compare it with conventional CE methods using the discrete entropy, PSNR, SSIM, RMSE, and computation time indexes. We present the experimental results for images from various products using several datasets such as infrared, multi-spectral satellite, surveillance, general gray and color images, as well as video sequences. The results are compared using the integrated image quality measurement index and they show that the proposed method maintains its performance on various degraded datasets. Kim, Byeong Hak; Bohak, Ciril; Kwon, Ki Hoon; Kim, Min Young Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Univ Ljubljana, Fac Comp & Informat Sci, Ljubljana 1501, Slovenia; Hanwha Syst Co, Gumi 39376, South Korea; Kyungpook Natl Univ, Res Ctr Neurosurg Robot Syst, Daegu 41566, South Korea 56406686400; 55582372100; 57190749004; 56739349100 minykim@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.66 2025-06-25 7 9 Infrared images; IRST; image enhancement; low dynamic; fusion; target detection HISTOGRAM EQUALIZATION fusion; image enhancement; Infrared images; IRST; low dynamic; target detection Antennas; Fusion reactions; Image fusion; Infrared detectors; Infrared imaging; Object recognition; Search engines; Security systems; Target tracking; Tracking (position); Adaptive contrast enhancement; Contrast Enhancement; Discrete entropy; Histogram equalizations; Integrated images; IRST; Low dynamic range; Non-uniformities; Image enhancement English 2020 2020 10.1109/access.2020.2966794 바로가기 바로가기 바로가기 바로가기
Article DCBT-Net: Training Deep Convolutional Neural Networks With Extremely Noisy Labels Obtaining data with correct labels is crucial to attain the state-of-the-art performance of Convolutional Neural Network (CNN) models. However, labeling datasets is significantly time-consuming and expensive process because it requires expert knowledge in a particular domain. Therefore, real-life datasets often exhibit incorrect labels due to the involvement of nonexperts in the data-labeling process. Consequently, there are many cases of incorrectly labeled data in the wild. Although the issue of poorly labeled datasets has been studied, the existing methods are complex and difficult to reproduce. Thus, in this study, we proposed a simpler algorithm called "Deep Clean Before Training Net" (DCBT-Net) that is based on cleaning wrongly labeled data points using the information from eigenvalues of the Laplacian matrix obtained from similarities between the data samples. The cleaned data were trained using deep CNN (DCNN) to attain the state-of-the-art results. This system achieved better performance than the existing approaches. In conducted experiments, the performance of the DCBT-Net was tested on three commercially available datasets, namely, Modified National Institute of Standards and Technology (MNIST) database of handwritten digits, Canadian Institute for Advanced Research (CIFAR) and WebVision1000 datasets. The proposed method achieved better results when assessed using several evaluation metrics compared with the existing state-of-the-art methods. Specifically, the DCBT-Net attained an average 15%, 20%, and 3% increase in accuracy score using MNIST database, CIFAR-10 dataset, and WebVision dataset, respectively. Also, the proposed approach demonstrated better results in specificity, sensitivity, positive predictive value, and negative predictive value evaluation metrics. Olimov, Bekhzod; Kim, Jeonghong; Paul, Anand Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea Paul, Anand/V-6724-2017; Olimov, Bekhzod/AAA-9362-2021 57220579660; 55138548100; 56650522400 jhk@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.66 2025-06-25 12 12 Training; Noise measurement; Data models; Computational modeling; Labeling; Convolutional neural networks; Neural networks; Clustering; deep convolutional neural networks; eigenvalues and eigenvectors; image classification; noisy (corrupted) labels Clustering; deep convolutional neural networks; eigenvalues and eigenvectors; image classification; noisy (corrupted) labels Convolution; Deep neural networks; Eigenvalues and eigenfunctions; Labeled data; Matrix algebra; Advanced researches; Evaluation metrics; National Institute of Standards and Technology; Negative predictive value; Positive predictive values; SIMPLER algorithms; State-of-the-art methods; State-of-the-art performance; Convolutional neural networks English 2020 2020 10.1109/access.2020.3041873 바로가기 바로가기 바로가기 바로가기
Article Deep Learning Based Channel Estimation for MIMO Systems With Received SNR Feedback Channel estimation with received signal-to-noise ratio (SNR) feedback is promising and effective for practical wireless multiple-input multiple-output (MIMO) systems. In this paper, we investigate the channel estimation problem for the MIMO system with received SNR feedback, of which goal is to estimate the MIMO channel coefficients at a transmitter based on the received SNR feedback information from a receiver in the sense of minimizing the mean square error (MSE) of the channel estimation. For analysis, we consider two very common and widely adopted scenarios of fading: (i) quasi-static block fading and (ii) time-varying fading. In both fading scenarios, it is generally challenging to analytically tackle the channel estimation problem due to its nonlinearity and nonconvexity. To intelligently and effectively address this issue, deep learning is exploited in this paper. First, in the quasi-static block fading scenario, we propose a novel learning scheme for joint channel estimation and pilot signal design by constructing a deep autoencoder via a convolutional neural network (CNN). Also, in the time-varying fading scenario, a novel channel estimation scheme is developed by connecting a recurrent neural network (RNN) to a CNN. Moreover, in both fading scenarios, we present new and effective ways to train the proposed schemes using generative adversarial networks (GANs) to address the practical issue of a limited number of actual channel samples (i.e., real-world data) required for training. Through extensive numerical simulations, we demonstrate effectiveness and superior performance of the proposed schemes. Kang, Jae-Mo; Chun, Chang-Jae; Kim, Il-Min Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Korea Electrotechnol Res Inst, Ind Applicat Res Div, Chang Won 51543, South Korea; Queens Univ, Dept Elect & Comp Engn, Kingston, ON K7L 3N6, Canada Chun, Changjae/AAF-2393-2019 56024930400; 55694574800; 36040390300 ilmin.kim@queensu.ca; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 3.21 2025-06-25 42 58 Autoencoder; channel estimation; convolutional neural network (CNN); deep learning; generative adversarial network (GAN); recurrent neural network (RNN); received SNR feedback; pilot signal design MASSIVE MIMO; DESIGN; MODEL Autoencoder; channel estimation; convolutional neural network (CNN); deep learning; generative adversarial network (GAN); pilot signal design; received SNR feedback; recurrent neural network (RNN) Channel estimation; Convolutional neural networks; Learning systems; Mean square error; MIMO systems; Recurrent neural networks; Adversarial networks; Feed back information; Joint channel estimation; Learning schemes; Minimizing the mean square errors; Practical issues; Recurrent neural network (RNN); Time-varying fading; Signal to noise ratio English 2020 2020 10.1109/access.2020.3006518 바로가기 바로가기 바로가기 바로가기
Article Deep Learning-Based Computational Color Constancy With Convoluted Mixture of Deep Experts (CMoDE) Fusion Technique In the human and computer vision, color constancy is the ability to perceive the true color of objects in spite of changing illumination conditions. Color constancy is remarkably benefitting human and computer vision issues such as human tracking, object and human detection and scene understanding. Traditional color constancy approaches based on the gray world assumption fall short of performing a universal predictor, but recent color constancy methods have greatly progressed with the introduction of convolutional neural networks (CNNs). Yet, shallow CNN-based methods face learning capability limitations. Accordingly, this article proposes a novel color constancy method that uses a multi-stream deep neural network (MSDNN)-based convoluted mixture of deep experts (CMoDE) fusion technique in performing deep learning and estimating local illumination. In the proposed method, the CMoDE fusion technique is used to extract and learn spatial and spectral features in an image space. The proposed method distinctively piles up layers both in series and in parallel, selects and concatenates effective paths in the CMoDE-based DCNN, as opposed to previous works where residual networks stack multiple layers linearly and concatenate multiple paths. As a result, the proposed CMoDE-based DCNN brings significant progress towards efficiency of using computing resources, as well as accuracy of estimating illuminants. In the experiments, Shi's Reprocessed, gray-ball and NUS-8 Camera datasets are used to prove illumination and camera invariants. The experimental results establish that this new method surpasses its conventional counterparts. Choi, Ho-Hyoung; Yun, Byoung-Ju Kyungpook Natl Univ, Adv Dent Device Dev Inst, Sch Dent, Daegu 41940, South Korea; Kyungpook Natl Univ, IT Coll, Sch Elect Engn, Daegu 41566, South Korea 37048369000; 7006416932 bjisyun@ee.knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.82 2025-06-25 16 14 Color constancy; CMoDE fusion technique; multi-stream deep neural network (MSDNN); illumination estimation; residual networks ILLUMINANT ESTIMATION; TRANSFORMATIONS; CHROMATICITY; NETWORKS; MODEL CMoDE fusion technique; Color constancy; Illumination estimation; Multi-stream deep neural network (MSDNN); Residual networks Cameras; Color; Computer vision; Convolution; Convolutional neural networks; Deep neural networks; Learning systems; Mixtures; Network layers; Object detection; Object tracking; Computational color constancy; Computing resource; Convoluted mixtures; Fusion techniques; Gray world assumption; Illumination conditions; Local illumination; Scene understanding; Deep learning English 2020 2020 10.1109/access.2020.3030912 바로가기 바로가기 바로가기 바로가기
Article Delay-Aware BBR Congestion Control Algorithm for RTT Fairness Improvement In late 2016, Google proposed the Bottleneck Bandwidth and Round-trip propagation time (BBR) congestion control algorithm to achieve high bandwidth and low latency for Internet traffic. Unlike loss-based congestion control algorithms, BBR works without filling the bottleneck buffer. Consequently, BBR can reduce packet loss and minimize end-to-end packet delay, which has attracted the attention of many researchers in recent years. However, some studies have reported the creation of persistent queues that cause unintended problems, resulting in a serious fairness issue between TCP BBR flows with different round-trip times (RTTs). Although existing congestion control algorithms also exhibit fairness issue between different RTT flows, BBR has a more serious problem in that the imbalance is considerable even with small RTT difference between the two flows, and the long RTT flow uses most of the bandwidth. The preponderance of long RTT flows is a serious problem because a particular user may cause imbalance by maliciously increasing the delay. Therefore, we propose a Delay-Aware BBR (DA-BBR) congestion control algorithm to mitigate the RTT fairness issue between BBR flows. In a network emulation experiment using the Mininet, the DA-BBR increased the fairness index by 1.6 times that of the original BBR, and the retransmission was greatly reduced. DA-BBR flow with short RTT demonstrated fair throughput even in competition with DA-BBR flows where RTT is five times higher. Kim, Geon-Hwan; Cho, You-Ze Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea 57189040274; 7404469829 yzcho@ee.knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 1.81 2025-06-25 24 33 BBR; congestion control; fairness; round-trip time; TCP TCP BBR BBR; congestion control; fairness; round-trip time; TCP Bandwidth; Congestion control (communication); Packet networks; Transmission control protocol; Bottleneck bandwidth; Fairness; Fairness index; Internet traffic; Network emulation; Propagation time; Retransmissions; Round-trip time; Traffic congestion English 2020 2020 10.1109/access.2019.2962213 바로가기 바로가기 바로가기 바로가기
Article Design of Secure Authentication Protocol for Cloud-Assisted Telecare Medical Information System Using Blockchain Telecare medical information system (TMIS) implemented in wireless body area network (WBAN) is convenient and time-saving for patients and doctors. TMIS is realized using wearable devices worn by a patient, and wearable devices generate patient health data and transmit them to a server through a public channel. Unfortunately, a malicious attacker can attempt performing various attacks through such a channel. Therefore, establishing a secure authentication process between a patient and a server is essential. Moreover, wearable devices have limited storage power. Cloud computing can be considered to resolve this problem by providing a storage service in the TMIS environment. In this environment, access control of the patient health data is essential for the quality of healthcare. Furthermore, the database of the cloud server is a major target for an attacker. The attacker can try to modify, forge, or delete the stored data. To resolve these problems, we propose a secure authentication protocol for a cloud-assisted TMIS with access control using blockchain. We employ ciphertext-policy attribute-based encryption (CP-ABE) to establish access control for health data stored in the cloud server, and apply blockchain to guarantee data integrity. To prove robustness of the proposed protocol, we conduct informal analysis and Burrows-Adabi-Needham (BAN) logic analysis, and we formally validate the proposed protocol using automated validation of internet security protocols and applications (AVISPA). Consequently, we show that the proposed protocol provides more security and has better efficiency compared to related protocols. Therefore, the proposed protocol is proper for a practical TMIS environment. Son, Seunghwan; Lee, Joonyoung; Kim, Myeonghyun; Yu, Sungjin; Das, Ashok Kumar; Park, Youngho Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Int Inst Informat Technol Hyderabad, Ctr Secur Theory & Algorithm Res, Hyderabad 500032, India; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea Lee, JoonYoung/AAM-9838-2021; Das, Ashok Kumar/U-2790-2019 57221744477; 57203970123; 57210278739; 57203974524; 55450732800; 56962990300 parkyh@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 4.37 2025-06-25 69 97 Attribute-based encryption; bilinear pairing; blockchain; cloud computing; mutual authentication and key agreement; telecare medical information system KEY MANAGEMENT PROTOCOL; PRIVACY PRESERVATION; HEALTH-CARE; SCHEME; AGREEMENT; INTERNET Attribute-based encryption; Bilinear pairing; Blockchain; Cloud computing; Mutual authentication and key agreement; Telecare medical information system Authentication; Bioinformatics; Blockchain; Computation theory; Cryptography; Digital storage; Health; Information use; Network security; Quality control; Storage as a service (STaaS); Wearable technology; Wireless local area networks (WLAN); Ciphertext-policy attribute-based encryptions; Internet security; Quality of health care; Secure authentications; Storage services; Various attacks; Wearable devices; Wireless body area network; Medical information systems English 2020 2020 10.1109/access.2020.3032680 바로가기 바로가기 바로가기 바로가기
Article Dynamic Compensation of Path Length Difference in Optical Coherence Tomography by an Automatic Temperature Control System of Optical Fiber Optical fiber is widely used in optical coherence tomography (OCT) to propagate light precisely with low attenuation and low dispersion. However, the total optical path length within the optical fiber varies in accordance with changes of the temperature. This leads changes in the total optical travel path of the interfering signals and results in shifting of OCT image position to an unintended depth pixel value. In this paper, we presented the temperature-based automatic path length compensating method in OCT to limit the external temperature effect and control the image position in micro-scale without manual movement of optical components. By utilizing developed hardware and software of automatic temperature control system, the external temperature of optical fiber is precisely regulated that evokes thermal expansion and finally changes the physical length of fiber, which is main mechanism of temperature-based path length compensating method. The effectiveness of the presented method was verified by two-dimensional OCT images of mirror and in vivo retina. The obtained results confirmed the path length variance due to temperature change is computable and can be regulated in real-time for whole pixel range of OCT image. Therefore, the proposed temperature-based path length compensating method can be used as an alternative method to precisely control the position of OCT image, while eliminating the effect of external temperature and apply to effectively configuring compact optical systems. Seong, Daewoon; Han, Sangyeob; Jeon, Deokmin; Kim, Yoonseok; Wijesinghe, Ruchire Eranga; Ravichandran, Naresh Kumar; Lee, Jaeyul; Lee, Junsoo; Kim, Pilun; Lee, Dong-Eun; Jeon, Mansik; Kim, Jeehyun Kyungpook Natl Univ, Sch Elect Engn, Coll IT Engn, Daegu 41566, South Korea; Kyungil Univ, Dept Biomed Engn, Coll Engn, Gyongsan 38428, South Korea; Kyungil Univ, Dept Autonomous Robot Engn, Coll Smart Engn, Gyongsan 38428, South Korea; Kyungpook Natl Univ, Inst Biomed Engn, Sch Med, Daegu 41944, South Korea; Kyungpook Natl Univ, Sch Architecture & Civil Engn, Daegu 41566, South Korea; Korea Basic Sci Inst, Ctr Sci Instrumentat, Daejeon 34133, South Korea ; Lee, Junsoo/IUO-9627-2023; Lee, Jung Bok/HHZ-3200-2022; Wijesinghe, Ruchire/K-3797-2016; RAVICHANDRAN, NARESH KUMAR/D-2190-2017 57212512353; 57193695305; 57204570554; 57216828837; 56018152300; 57125825900; 57188689420; 57209986073; 56967482800; 56605563300; 24171094000; 7601373350 dolee@knu.ee.kr;msjeon@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.99 2025-06-25 18 19 Optical fiber; automatic temperature control system; thermal expansion; micro position control; optical coherence tomography IN-VIVO; PERFORMANCE automatic temperature control system; micro position control; optical coherence tomography; Optical fiber; thermal expansion Control systems; Optical fibers; Optical systems; Pixels; Position control; Temperature control; Thermal expansion; Tomography; Compensating method; Dynamic compensation; External temperature; Hardware and software; Interfering signals; Optical path lengths; Path length difference; Temperature changes; Optical tomography English 2020 2020 10.1109/access.2020.2990357 바로가기 바로가기 바로가기 바로가기
Article Efficient Visual Tracking With Stacked Channel-Spatial Attention Learning Template based learning, particularly Siamese networks, has recently become popular due to balancing accuracy and speed. However, preserving tracker robustness against challenging scenarios with real-time speed is a primary concern for visual object tracking. Siamese trackers confront difficulties handling target appearance changes continually due to less discrimination ability learning between target and background information. This paper presents stacked channel-spatial attention within Siamese networks to improve tracker robustness without sacrificing fast-tracking speed. The proposed channel attention strengthens target-specific channels increasing their weight while reducing the importance of irrelevant channels with lower weights. Spatial attention is focusing on the most informative region of the target feature map. We integrate the proposed channel and spatial attention modules to enhance tracking performance with end-to-end learning. The proposed tracking framework learns what and where to highlight important target information for efficient tracking. Experimental results on widely used OTB100, OTB50, VOT2016, VOT2017/18, TC-128, and UAV123 benchmarks verified the proposed tracker achieved outstanding performance compared with state-of-the-art trackers. Rahman, Md. Maklachur; Fiaz, Mustansar; Jung, Soon Ki Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea ; Jung, Soon Ki/P-7687-2018; Rahman, Md Maklachur/GRI-9663-2022 57216556379; 57208735843; 57226791905 skjung@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 1.53 2025-06-25 28 28 Target tracking; Computer architecture; Visualization; Feature extraction; Object tracking; Training; Deep learning; Siamese architecture; stacked channel-spatial attention; visual object tracking OBJECT TRACKING; INTEGRATION; FEATURES Deep learning; Siamese architecture; stacked channel-spatial attention; visual object tracking Benchmarking; Target tracking; Discrimination ability; Spatial attention; State of the art; Target and background; Target information; Tracking performance; Visual object tracking; Visual Tracking; Object tracking English 2020 2020 10.1109/access.2020.2997917 바로가기 바로가기 바로가기 바로가기
Article Enhancement Mode Flexible SnO2 Thin Film Transistors Via a UV/Ozone-Assisted Sol-Gel Approach The effect of ultraviolet/Ozone (UV/O-3)-assisted annealing process on the structural, chemical, and electrical properties of sol-gel-processed SnO2 films is investigated in this study. Via the UV/O-3-assisted annealing processes, mixed-phase SnO2 films composed of amorphous SnO2 and polycrystalline SnO were obtained. Furthermore, the XPS spectra indicate an increase in the SnO2/SnO ratio and a substantial decrease in the number of -OH groups (serving as trap sites). This results in an increase in the conductivity and field-effect mobility of the films. The field-effect mobility of the UV/Ozone-assisted 300 degrees C-annealed SnO2 thin film transistor (TFT) increases considerably (by similar to 500x), yielding a device with a field-effect mobility of 3.09 cm(2)/Vs. In addition, fiexible SnO2 TFTs with Al2O3 insulator and Au gate on Polyimide substrate fabricated via gate electrode engineering shows a decreased conduction bandgap offset, compared to the SnO2 TFTs on SiO2, and enhancement mode operation properties (normally off at zero gate voltage) with a field-effect mobility of 1.87 cm(2)/Vs. Jang, Bongho; Kang, Hongki; Lee, Won-Yong; Bae, Jin-Hyuk; Kang, In-Man; Kim, Kwangeun; Kwon, Hyuk-Jun; Jang, Jaewon DGIST, Dept Informat & Commun Engn, Daegu 42988, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Hongik Univ, Dept Elect & Elect Convergence Engn, Sejong 30016, South Korea Kang, Hongki/AFM-2155-2022 57194718232; 36158223200; 57209527128; 35326180700; 7203062678; 36004977500; 57298892000; 57194107504 hj.kwon@dgist.ac.kr;j1jang@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.66 2025-06-25 10 11 Sol-gel; SnO2; UV/Ozone; thin film transistors; enhancement mode OXIDE enhancement mode; SnO<sub>2</sub>; Sol-gel; thin film transistors; UV/Ozone Alumina; Aluminum oxide; Annealing; Electron mobility; Refractory metal compounds; Silica; Sol-gel process; Thin film transistors; Annealing process; Band-gap offsets; Enhancement modes; Field-effect mobilities; Gate electrodes; Polycrystalline; Polyimide substrate; Sol-gel approach; Thin films English 2020 2020 10.1109/access.2020.3007372 바로가기 바로가기 바로가기 바로가기
Article Extension of pQSAR: Ensemble Model Generated by Random Forest and Partial Least Squares Regressions Quantitative structure-activity relationship (QSAR) regression models are mathematical ones which relate the structural properties of chemicals to the potencies of the biological activities of the chemicals. In QSAR models, the physical and chemical information of the molecules is encoded into quantitative numbers called descriptors. Recently, experimental test results (profiles) have been used as descriptors of chemicals. Profile QSAR 2.0 (pQSAR) model suggested by Martin et al., is a multitask, two step machine learning prediction method with a combination of random forest regressions (RFRs) and partial least squares regression (PLSR). In pQSAR model, one fills the profile table's missing values with RFRs and then builds PLSR using the profile predictions. Note that in the second step of the pQSAR method, PLSR's predictor variables are profiles; so activity values, and the response variables are also activity values. Thus we can use the PLSRs to update the profile table and then repeat the second step. In this work, we propose an extended model of pQSAR generated by RFRs and PLSRs. Experiment of updating the given full initially predicted profile table by two kinds of prediction models, RFRs and PLSRs, has been conducted iteratively for the PKIS and ChEMBL data sets. Even though prediction performance of individual combination of RFRs and PLSRs varies, the average of the all possible predicted profile tables for given iteration shows better performance. This ensemble model has better prediction performance in sense of Pearson's R-2 compared to that of the pQSAR model. Kim, Byung Chun; Joe, Dosang; Woo, Youngho; Kim, Yongkuk; Yoon, Gangjoon Natl Inst Math Sci, Daejeon 34047, South Korea; Kyungpook Natl Univ, Daegu 41566, South Korea Yoon, Gangjoon/GZM-8532-2022 57204677482; 57219455400; 37125597900; 7410204041; 7103257925 yoon@nims.re.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.25 2025-06-25 2 5 Bio-activity prediction; drug discovery; fingerprint; optimization; QSAR; similar property principle PROFILE-QSAR; PREDICTION; ACCURACY; AFFINITY Bio-Activity prediction; drug discovery; fingerprint; optimization; QSAR; similar property principle Chemicals; Decision trees; Forecasting; Iterative methods; Least squares approximations; Molecular graphics; Predictive analytics; Random forests; Regression analysis; Structural properties; Chemical information; Partial least squares regression; Partial least squares regressions (PLSR); Prediction methods; Prediction performance; Predictor variables; Profile prediction; Quantitative structure-activity relationships; Computational chemistry English 2020 2020 10.1109/access.2020.3027828 바로가기 바로가기 바로가기 바로가기
Article Fabrication of AlGaN/GaN Fin-Type HEMT Using a Novel T-Gate Process for Improved Radio-Frequency Performance To increase the radio-frequency (RF) performance of AlGaN/GaN-based fin-type high electron mobility transistors (HEMTs), a novel T-gate process was developed and applied to fabricate a device with high RF performance. In a single lithography process, the applied T-gate process shows a technique for forming a T-gate using the reactivity difference of several photoresists. The fabricated device has a steep fin width (W-fin) of 130 nm, a fin height (H-fin) of 250 nm, and a gate length (L-G) of 190 nm. The device exhibits a low leakage current (I-off) of 6.6 x 10(-10) A/mm and a high I-on/I-off current ratio of 4.7 x 10(8). Moreover, the fabricated device achieved a high cut-off frequency (f(T)) of 9.7 GHz and a very high maximum oscillation frequency (f(max)) of 27.8 GHz. The f(max) value of the proposed device is 138% higher than that of GaN-based fin-type HEMTs without T-gate. Cho, Min Su; Seo, Jae Hwa; Lee, Sang Ho; Jang, Hwan Soo; Kang, In Man Kyungpook Natl Univ, Sch Elect Engn, Daegu 702201, South Korea; Samsung Elect Co Ltd, Semicond Res & Dev Ctr, Flash TD Team, Hwasung Si 445701, South Korea; Daegu Gyeongbuk Inst Sci & Technol, Ctr Core Res Facil, Daegu 711873, South Korea ; Lee, Sang Ho/MCX-8396-2025; Seo, Jae Hwa/KYP-7367-2024 57188742288; 55516610100; 57416738400; 35210247400; 7203062678 imkang@ee.knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.66 2025-06-25 16 17 FinFET; Gallium compounds; nanofabrication; nanolithography; high electron mobility transistor; T-gate; E-beam lithography; maximum oscillation frequency LINEARITY; IMPACT; F(T) E-beam lithography; FinFET; Gallium compounds; high electron mobility transistor; maximum oscillation frequency; nanofabrication; nanolithography; T-gate Aluminum gallium nitride; Fabrication; Fins (heat exchange); Gallium nitride; III-V semiconductors; Leakage currents; Photoresists; Radio waves; Cut-off frequency (fT); Fabricated device; High electron mobility transistor (HEMTs); Lithography process; Low-leakage current; Maximum oscillation frequency; Radio frequencies; Radio frequency performance; High electron mobility transistors English 2020 2020 10.1109/access.2020.3011103 바로가기 바로가기 바로가기 바로가기
Article Fabrication of Dental Crown by Optical Coherence Tomography: A Pilot Study Digital impressions have been studied for better gingival retraction in including the under subgingival finish line condition. Here, we employed swept-source optical coherence tomography (SS-OCT) of 1310 nm wavelength, which is capable of noninvasive, high-resolution, and high-speed, to discern the utilization-possibility for supporting the fabrication of the dental crown. A three-dimensional (3D) abutment was used at the 0.5 mm of the subgingival finish line below the level of the gingiva. The SS-OCT system scanned a field of view of 10 mm x 10 mm using the 3D working model by the depth-directional three focal points. The obtained 1500 images of OCT cross-sections, which are 1221 x 1220 pixels, were rendered to the 3D model for the effective design of a virtual crown. Then, the ceramic crown was fabricated through a milling machine with a computer-aided design and computer-aided manufacturing (CAD/CAM) software. The marginal fit of the crown was evaluated 219.1 +/- 48.9 mu m by a silicone replica technique. Although the marginal fit is not sufficient for the clinical allowable gap at one resin typodont, this study can be anticipated to encourage further researches for the enhanced fabrication of dental crown under subgingival finish line conditions. Lee, Sangbong; Son, Keunbada; Lee, Jaeyul; Jeon, Mansik; Lee, Kyu-Bok; Kim, Jeehyun Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Adv Dent Device Dev Inst, Daegu 41566, South Korea; Kyungpook Natl Univ, Grad Sch, Dept Dent Sci, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Dent, Dept Prosthodont, Daegu 41566, South Korea Lee, Junsoo/IUO-9627-2023; SON, Keunbada/AAG-8089-2019; Son, Keunbada/AAG-8089-2019 57205251578; 57202916520; 57188689420; 24171094000; 15925571200; 7601373350 msjeon@knu.ac.kr;kblee@knu.ac.kr; IEEE ACCESS IEEE ACCESS 2169-3536 8 SCIE COMPUTER SCIENCE, INFORMATION SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;TELECOMMUNICATIONS 2020 3.367 34.3 0.16 2025-06-25 3 4 Swept-source optical coherence tomography; virtual crown; subgingival scanning; two-dimensional image stack; three-dimensional modeling ZIRCONIA-BASED IMPLANT; HUMAN GINGIVAL SULCUS; INTRAORAL SCANNERS; ACCURACY; IMPRESSIONS; ULTRASOUND; PRECISION; OUTCOMES; MODEL; FIT subgingival scanning; Swept-source optical coherence tomography; three-dimensional modeling; two-dimensional image stack; virtual crown 3D modeling; Ceramic Prosthetics; Ceramics industry; Clinical research; Computer aided manufacturing; Fabrication; Optical tomography; Silicones; Tomography; Ceramic crowns; Field of views; High resolution; Pilot studies; Replica technique; Swept source optical coherence tomographies; Threedimensional (3-d); Working models; Computer aided design English 2020 2020 10.1109/access.2020.3014315 바로가기 바로가기 바로가기 바로가기
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Publication Year 논문이 출판된 연도입니다.
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