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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 Development and Validation of a Multimodal-Based Prognosis and Intervention Prediction Model for COVID-19 Patients in a Multicenter Cohort The ability to accurately predict the prognosis and intervention requirements for treating highly infectious diseases, such as COVID-19, can greatly support the effective management of patients, especially in resource-limited settings. The aim of the study is to develop and validate a multimodal artificial intelligence (AI) system using clinical findings, laboratory data and AI-interpreted features of chest X-rays (CXRs), and to predict the prognosis and the required interventions for patients diagnosed with COVID-19, using multi-center data. In total, 2282 real-time reverse transcriptase polymerase chain reaction-confirmed COVID-19 patients' initial clinical findings, laboratory data and CXRs were retrospectively collected from 13 medical centers in South Korea, between January 2020 and June 2021. The prognostic outcomes collected included intensive care unit (ICU) admission and in-hospital mortality. Intervention outcomes included the use of oxygen (O-2) supplementation, mechanical ventilation and extracorporeal membrane oxygenation (ECMO). A deep learning algorithm detecting 10 common CXR abnormalities (DLAD-10) was used to infer the initial CXR taken. A random forest model with a quantile classifier was used to predict the prognostic and intervention outcomes, using multimodal data. The area under the receiver operating curve (AUROC) values for the single-modal model, using clinical findings, laboratory data and the outputs from DLAD-10, were 0.742 (95% confidence interval [CI], 0.696-0.788), 0.794 (0.745-0.843) and 0.770 (0.724-0.815), respectively. The AUROC of the combined model, using clinical findings, laboratory data and DLAD-10 outputs, was significantly higher at 0.854 (0.820-0.889) than that of all other models (p < 0.001, using DeLong's test). In the order of importance, age, dyspnea, consolidation and fever were significant clinical variables for prediction. The most predictive DLAD-10 output was consolidation. We have shown that a multimodal AI model can improve the performance of predicting both the prognosis and intervention in COVID-19 patients, and this could assist in effective treatment and subsequent resource management. Further, image feature extraction using an established AI engine with well-defined clinical outputs, and combining them with different modes of clinical data, could be a useful way of creating an understandable multimodal prediction model. Lee, Jeong Hoon; Ahn, Jong Seok; Chung, Myung Jin; Jeong, Yeon Joo; Kim, Jin Hwan; Lim, Jae Kwang; Kim, Jin Young; Kim, Young Jae; Lee, Jong Eun; Kim, Eun Young Lunit Inc, 27 Teheran Ro 2 Gil, Seoul 06241, South Korea; Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Dept Radiol, Seoul 06351, South Korea; Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Med AI Res Ctr, Seoul 06351, South Korea; Pusan Natl Univ, Sch Med, Pusan Natl Univ Hosp, Dept Radiol, Busan 49241, South Korea; Biomed Res Inst, Busan 49241, South Korea; Chungnam Natl Univ, Coll Med, Chungnam Natl Univ Hosp, Dept Radiol, Daejeon 35015, South Korea; Kyungpook Natl Univ, Kyungpook Natl Univ Hosp, Sch Med, Dept Radiol, Daegu 41944, South Korea; Keimyung Univ, Sch Med, Dongsan Hosp, Dept Radiol, Daegu 42601, South Korea; Gachon Univ, Coll Med, Dept Biomed Engn, Incheon 21565, South Korea; Chonnam Natl Univ Hosp, Dept Radiol, 42 Jebong Ro, Gwangju 61469, South Korea; Gachon Univ, Coll Med, Gil Med Ctr, Dept Radiol, Namdong Daero 774 Beon Gil, Incheon 21565, South Korea Chung, Myung/C-1876-2011; Kim, Juhee/KFS-3069-2024; Lee, Jeong Hoon/AAF-2400-2020; Kim, Jinsoo/G-6348-2012 57281283900; 57712046900; 55728272500; 57706214000; 55910532600; 55515341400; 55862597800; 57211074065; 57196009389; 55577620300 sosal@snu.ac.kr;johnahn92@lunit.io;mj1.chung@samsung.com;jeongyj@pusan.ac.kr;michelan@cnu.ac.kr;limjaekwang@gmail.com;jinkim0411@naver.com;youngjae@gachon.ac.kr;rollycandy2@naver.com;oneshot0229@gmail.com; SENSORS SENSORS-BASEL 1424-8220 22 13 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.34 2025-06-25 4 4 COVID-19; artificial intelligence; prognosis; chest radiograph CHEST RADIOGRAPHS; SYSTEM artificial intelligence; chest radiograph; COVID-19; prognosis Artificial Intelligence; COVID-19; Humans; Intensive Care Units; Prognosis; Retrospective Studies; Decision trees; Deep learning; Diagnosis; Forecasting; Intensive care units; Patient monitoring; Polymerase chain reaction; Respiratory therapy; Ventilation; Artificial intelligence systems; Chest radiographs; Effective management; Infectious disease; Laboratory datum; Medical center; Multi-modal; Prediction modelling; Prognose; Real- time; artificial intelligence; clinical trial; diagnosis; human; intensive care unit; multicenter study; prognosis; retrospective study; therapy; COVID-19 English 2022 2022-07 10.3390/s22135007 바로가기 바로가기 바로가기 바로가기
Article Development of a Dual-Layer Structure for Cymbal Transducer Arrays to Achieve a Wider Bandwidth Cymbal transducers are typically grouped and arranged in planar arrays. For projector arrays, a wide bandwidth on the transmitting voltage response (TVR) spectrum is required for better underwater communication and data transmission within a short time. The purpose of this study is to develop a wideband cymbal array by controlling the center-to-center (CTC) spacing between the cymbal transducers in the array. In the practical design of the array, due to the arrangement of elements in one layer, the minimum CTC spacing between the cymbals is constrained to the diameter of the cymbals in use. To overcome this limitation, we propose a new dual-layer array structure. Finite element analysis of the cymbal array showed that the bandwidth was generally inversely proportional to the CTC spacing. We explained the mechanism of this relationship using a theoretical analysis of the mutual radiation impedance between the cymbals in the array. Subsequently, we identified the optimum CTC spacing to achieve the widest possible bandwidth for the cymbal array. The validity of the wideband array design was verified through the fabrication and characterization of prototype arrays. We confirmed that the two-layered arrangement could significantly widen the bandwidth of the cymbal array while maintaining the TVR above a specified level. Mudiyala, Jahnavi; Shim, Hayeong; Kim, Donghyun; Roh, Yongrae Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea 57880158400; 57202806954; 58950709000; 7102361870 yryong@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 17 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.85 2025-06-25 9 10 cymbal transducer; arrays; wideband; dual-layer structure; mutual radiation impedance DESIGN; PROJECTOR; PATTERN arrays; cymbal transducer; dual-layer structure; mutual radiation impedance; wideband Transducers; Array; Cymbal transducer; Dual layer structure; Mutual radiation impedance; Planar arrays; Radiation impedance; Transducer array; Transmitting voltage response; Wide bandwidth; Wide-band; Bandwidth English 2022 2022-09 10.3390/s22176614 바로가기 바로가기 바로가기 바로가기
Article Efficient Object Detection Based on Masking Semantic Segmentation Region for Lightweight Embedded Processors Because of the development of image processing using cameras and the subsequent development of artificial intelligence technology, various fields have begun to develop. However, it is difficult to implement an image processing algorithm that requires a lot of calculations on a light board. This paper proposes a method using real-time deep learning object recognition algorithms in lightweight embedded boards. We have developed an algorithm suitable for lightweight embedded boards by appropriately using two deep neural network architectures. The first architecture requires small computational volumes, although it provides low accuracy. The second architecture uses large computational volumes and provides high accuracy. The area is determined using the first architecture, which processes semantic segmentation with relatively little computation. After masking the area using the more accurate deep learning architecture, object detection is implemented with improved accuracy, as the image is filtered by segmentation and the cases that have not been recognized by various variables, such as differentiation from the background, are excluded. OpenCV (Open source Computer Vision) is used to process input images in Python, and images are processed using an efficient neural network (ENet) and You Only Look Once (YOLO). By running this algorithm, the average error can be reduced by approximately 2.4 times, allowing for more accurate object detection. In addition, object recognition can be performed in real time for lightweight embedded boards, as a rate of about 4 FPS (frames per second) is achieved. Yun, Heuijee; Park, Daejin Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea Yun, Heuijee (Heejee)/GOJ-9000-2022 57222516795; 55463943600 boltanut@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 22 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.6 2025-06-25 5 7 autonomous driving; object detection; OpenCV; ENet; YOLO; deep learning autonomous driving; deep learning; ENet; object detection; OpenCV; YOLO Algorithms; Artificial Intelligence; Image Processing, Computer-Assisted; Neural Networks, Computer; Semantics; Autonomous vehicles; Deep neural networks; Image enhancement; Network architecture; Object recognition; Semantic Segmentation; Semantics; Autonomous driving; Deep learning; Efficient neural network; Embedded boards; Neural-networks; Objects detection; Open source computer vision; Open-source; Semantic segmentation; You only look once; algorithm; artificial intelligence; image processing; procedures; semantics; Object detection English 2022 2022-11 10.3390/s22228890 바로가기 바로가기 바로가기 바로가기
Article Equivalent Circuit to Analyze the Transmitting Characteristics of a Cymbal Array A cymbal transducer has a simple structure consisting of a piezoceramic disk and metallic caps and has broadband characteristics when built as an array. The finite element method (FEM) is generally used to analyze the characteristics of acoustic transducers. However, the FEM requires a longer analysis time as the model becomes larger, which makes it limited and less efficient for analyzing the cymbal array. In this study, a new equivalent circuit with higher efficiency and accuracy, comparable to that of the FEM, was proposed to analyze the performance of cymbal arrays. The equivalent circuit for the array was constructed by connecting the equivalent circuits of individual cymbal transducers in parallel with a radiation impedance matrix that included both the self- and mutual radiation characteristics of the array. The validity of the new equivalent circuit was verified by measuring the transmitting voltage response of a cymbal array specimen and comparing it with that calculated using the circuit. The comparison confirmed the efficiency of the equivalent circuit in analyzing the characteristics of the cymbal array. The proposed equivalent circuit can facilitate the design of a large array of cymbal transducers. Shim, Hayeong; Kim, Kyungseop; Seo, Heeseon; Roh, Yongrae Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea; Agcy Def Dev, Chang Won 51678, South Korea 57202806954; 9634041100; 24765212200; 7102361870 yryong@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 22 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.43 2025-06-25 4 5 cymbal transducer; equivalent circuit; broadband transducer; cymbal array TRANSDUCER; MODELS; CELL broadband transducer; cymbal array; cymbal transducer; equivalent circuit Acoustics; Equipment Design; Transducers; Acoustic impedance; Efficiency; Electric network analysis; Piezoelectric ceramics; Timing circuits; Analysis time; Broadband characteristics; Broadband transducers; Cymbal array; Cymbal transducer; High-accuracy; Metallics; Piezoceramic disks; Simple structures; Transmitting characteristics; acoustics; equipment design; transducer; Equivalent circuits English 2022 2022-11 10.3390/s22228743 바로가기 바로가기 바로가기 바로가기
Article Estimation of Online State of Charge and State of Health Based on Neural Network Model Banks Using Lithium Batteries Lithium batteries are secondary batteries used as power sources in various applications, such as electric vehicles, portable devices, and energy storage devices. However, because explosions frequently occur during their operation, improving battery safety by developing battery management systems with excellent reliability and efficiency has become a recent research focus. The performance of the battery management system varies depending on the estimated accuracy of the state of charge (SOC) and state of health (SOH). Therefore, we propose a SOH and SOC estimation method for lithium-ion batteries in this study. The proposed method includes four neural network models-one is used to estimate the SOH, and the other three are configured as normal, caution, and fault neural network model banks for estimating the SOC. The experimental results demonstrate that the proposed method using the long short-term memory model outperforms its counterparts. Lee, Jong-Hyun; Lee, In-Soo Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 57201265019; 54979862300 whdugs8428@knu.ac.kr;insoolee@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 15 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 1.54 2025-06-25 13 19 lithium batteries; state of charge; state of health; multilayer neural networks; long short-term memory; estimation ION BATTERY; MANAGEMENT-SYSTEM; CIRCUIT; DIAGNOSIS; FAULT estimation; lithium batteries; long short-term memory; multilayer neural networks; state of charge; state of health Electric Power Supplies; Electricity; Lithium; Neural Networks, Computer; Reproducibility of Results; Battery management systems; Brain; Charging (batteries); Health; Lithium batteries; Long short-term memory; lithium; Battery safety; Model banks; Neural network model; On-line state; Portable device; Portable energy; Power sources; Recent researches; State of health; States of charges; electricity; power supply; reproducibility; Multilayer neural networks English 2022 2022-08 10.3390/s22155536 바로가기 바로가기 바로가기 바로가기
Article Fabrication and Underwater Testing of a Vector Hydrophone Comprising a Triaxial Piezoelectric Accelerometer and Spherical Hydrophone A vector hydrophone is an underwater acoustic sensor that can detect the direction of a sound source. Wide-band characteristics and high sensitivity enhance the performance of underwater surveillance systems in complex environments. A vector hydrophone comprising a triaxial piezoelectric accelerometer and spherical hydrophone was fabricated and tested in the air and underwater. The vector hydrophone was designed to exceed the quantitative figures of merit (i.e., receiving voltage sensitivity and bandwidth) of commercially available hydrophones. Accelerometer performance was enhanced by placing a pair of piezoelectric single crystals on each axis and modifying the seismic mass material. The receiving voltage sensitivity of the omnidirectional hydrophone was approximately -160 dB relative to 1 V/mu Pa with the amplifier in water; the sensitivity of the accelerometer exceeded 300 mV/g in air and -215 dB relative to 1 V/Pa underwater over the frequency range of interest. The receiving directivity of the vector hydrophone was validated underwater, which confirmed that it could detect the direction of a sound source. Roh, Taehoun; Yeo, Hong Goo; Joh, Cheeyoung; Roh, Yongrae; Kim, Kyungseop; Seo, Hee-seon; Choi, Hongsoo DGIST, Dept Robot Engn, Daegu 42988, South Korea; Sun Moon Univ Asan, Dept Adv Mat Engn, Asan 31460, South Korea; Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea; Agcy Def Dev, Chang Won 51678, South Korea 58025279100; 7005735800; 7004543755; 7102361870; 9634041100; 24765212200; 57762223900 mems@dgist.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 24 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 1.02 2025-06-25 12 13 piezoelectric accelerometer; PMN-PT piezoelectric single crystal; vector hydrophone SENSOR piezoelectric accelerometer; PMN-PT piezoelectric single crystal; vector hydrophone Accelerometry; Acoustics; Equipment Design; Sound; Water; Acoustic generators; Fabrication; Hydrophones; Piezoelectric devices; Piezoelectricity; Single crystals; Underwater acoustics; Vectors; water; Band characteristics; Performance; Piezo-electric accelerometers; Piezoelectric single crystals; PMN-PT piezoelectric single crystal; Sound source; Underwater acoustic sensors; Vector hydrophones; Voltage sensitivity; Wide-band; accelerometry; acoustics; equipment design; sound; Accelerometers English 2022 2022-12 10.3390/s22249796 바로가기 바로가기 바로가기 바로가기
Article Ghostformer: A GhostNet-Based Two-Stage Transformer for Small Object Detection In this paper, we propose a novel two-stage transformer with GhostNet, which improves the performance of the small object detection task. Specifically, based on the original Deformable Transformers for End-to-End Object Detection (deformable DETR), we chose GhostNet as the backbone to extract features, since it is better suited for an efficient feature extraction. Furthermore, at the target detection stage, we selected the 300 best bounding box results as regional proposals, which were subsequently set as primary object queries of the decoder layer. Finally, in the decoder layer, we optimized and modified the queries to increase the target accuracy. In order to validate the performance of the proposed model, we adopted a widely used COCO 2017 dataset. Extensive experiments demonstrated that the proposed scheme yielded a higher average precision (AP) score in detecting small objects than the existing deformable DETR model. Li, Sijia; Sultonov, Furkat; Tursunboev, Jamshid; Park, Jun-Hyun; Yun, Sangseok; Kang, Jae-Mo Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Pukyong Natl Univ, Dept Informat & Commun Engn, Busan 48513, South Korea Park, Jun-Hyun/CAG-5910-2022; SULTONOV, FURKAT/NFS-3340-2025 57836380100; 57455045300; 57410135900; 57455816200; 56115729600; 56024930400 jmkang@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 18 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 1.37 2025-06-25 13 17 small object detection; GhostNet; regional proposals; two-stage transformer GhostNet; regional proposals; small object detection; two-stage transformer Decoding; Deformation; Feature extraction; Object recognition; Detection tasks; End to end; Features extraction; Ghostnet; Objects detection; Performance; Regional proposal; Small object detection; Targets detection; Two-stage transformer; article; feature extraction; Object detection English 2022 2022-09 10.3390/s22186939 바로가기 바로가기 바로가기 바로가기
Article iAKA-CIoT: An Improved Authentication and Key Agreement Scheme for Cloud Enabled Internet of Things Using Physical Unclonable Function The Internet of Things (IoT) with cloud services are important functionalities in the latest IoT systems for providing various convenient services. These cloud-enabled IoT environments collect, analyze, and monitor surrounding data, resulting in the most effective handling of large amounts of heterogeneous data. In these environments, secure authentication with a key agreement mechanism is essential to ensure user and data privacy when transmitting data between the cloud server and IoT nodes. In this study, we prove that the previous scheme contains various security threats, and hence cannot guarantee essential security requirements. To overcome these security threats, we propose an improved authentication and key agreement scheme for cloud-enabled IoT using PUF. Furthermore, we evaluate its security by performing informal, formal (mathematical), and simulation analyses using the AVISPA tool and ROR model. The performance and security properties of our scheme are subsequently compared with those of other related schemes. The comparison confirms that our scheme is suitable for a practical cloud-enabled IoT environment because it provides a superior security level and is more efficient than contemporary schemes. Park, Kisung; Park, Youngho Elect & Telecommun Res Inst, Blockchain & Big Data Res Dept, Daejeon 34129, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea Park, Kisung/KIG-3849-2024 57194833768; 56962990300 parkyh@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 16 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.43 2025-06-25 3 5 key establishment; Internet of Things (IoT); physical unclonable function; authentication PROVABLY SECURE; POWER ANALYSIS; PROTOCOL authentication; Internet of Things (IoT); key establishment; physical unclonable function Authentication; Cloud computing; Cryptography; Data privacy; Hardware security; Monitoring; Security systems; Authentication and key agreements; Cloud services; Heterogeneous data; Internet of thing; Key agreement; Key agreement scheme; Key establishments; Large amounts; Secure authentications; Security threats; article; internet of things; security; simulation; Internet of things English 2022 2022-08 10.3390/s22166264 바로가기 바로가기 바로가기 바로가기
Article Improved Spoken Language Representation for Intent Understanding in a Task-Oriented Dialogue System Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users' articulation styles and background noises cause automatic speech recognition (ASR) errors, and these may lead language models to misclassify users' intents. To overcome the limited performance of the intent classification task in the spoken dialogue system, we propose a novel approach that jointly uses both recognized text obtained by the ASR model and a given labeled text. In the evaluation phase, only the fine-tuned recognized language model (RLM) is used. The experimental results show that the proposed scheme is effective at classifying intents in the spoken dialogue system containing ASR errors. Kim, June-Woo; Yoon, Hyekyung; Jung, Ho-Young Kyungpook Natl Univ, Grad Sch, Dept Artificial Intelligence, Daegu 41566, South Korea 57219550643; 57273359500; 57198760619 kaen2891@knu.ac.kr;yhk04150@knu.ac.kr;hoyjung@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 4 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.43 2025-06-25 2 5 intent understanding; task-oriented dialogue system; spoken dialogue system; speech recognition; spoken language modeling Intent understanding; Speech recognition; Spoken dialogue system; Spoken language modeling; Task-oriented dialogue system Intention; Language; Natural Language Processing; Character recognition; Computational linguistics; Deep learning; Modeling languages; Natural language processing systems; Speech processing; Text processing; User profile; Automatic speech recognition; Dialogue systems; Intent understanding; Language model; Recognition error; Spoken dialogue system; Spoken language modeling; Spoken languages; Task-oriented; Task-oriented dialog system; behavior; language; natural language processing; Speech recognition English 2022 2022-02 10.3390/s22041509 바로가기 바로가기 바로가기 바로가기
Article Knowledge-Based Remote E-Coaching Framework Using IoT Devices for In-Home ADL Rehabilitation Treatment of Degenerative Brain Disease Patients The activities of daily living (ADL) ability level of an elderly patient is an important indicator in determining the patient's degree of degenerative brain disease and is mainly evaluated through face-to-face interviews with doctors and patients in hospitals. It is impossible to determine the exact ADL ability of a patient through such a temporary interview, and the pursuit of accurate ADL ability evaluation technology is a very important research task worldwide. In this paper, in order to overcome the limitations of the existing ADL evaluation method mentioned above, first of all, a self-organized IoT architecture in which IoT devices autonomously and non-invasively measure a patient's ADL ability within the context of the patient's daily living place was designed and implemented. Second, a remote rehabilitation treatment concept for enhancing the patient's ADL ability we call an "e-coaching framework", in which a doctor remotely gives an instruction in a specific ADL scenario, and the patient's ability to understand and perform the instruction can be measured on-line and in real time, was additionally developed on top of the self-organized IoT architecture. In order to verify the possibility of remote rehabilitation treatment through the proposed architecture, various remotely directed ADL scenarios were performed and the accuracy of the measurements was verified. Kim, Hyo-Jung; Jeong, Seol-Young; Kang, Soon-Ju Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Software Educ Inst, Daegu 41566, South Korea 57948145600; 44061313100; 55666313900 sjkang@ee.knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 20 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0 2025-06-25 0 0 knowledge-based system; activities of daily living (ADL); e-coaching framework; user behavior recognition; IoT devices SMART HOME; ASSISTANT; SENSOR; SYSTEM activities of daily living (ADL); e-coaching framework; IoT devices; knowledge-based system; user behavior recognition Activities of Daily Living; Aged; Brain Diseases; Humans; Mentoring; Technology; Wireless Technology; aged; brain disease; daily life activity; human; mentoring; technology; wireless communication English 2022 2022-10 10.3390/s22207957 바로가기 바로가기 바로가기 바로가기
Article Localization of Cracks in Concrete Structures Using an Unmanned Aerial Vehicle Active research on crack detection technology for structures based on unmanned aerial vehicles (UAVs) has attracted considerable attention. Most of the existing research on localization of cracks using UAVs mounted the Global Positioning System (GPS)/Inertial Measurement Unit (IMU) on the UAVs to obtain location information. When such absolute position information is used, several studies confirmed that positioning errors of the UAVs were reflected and were in the order of a few meters. To address these limitations, in this study, without using the absolute position information, localization of cracks was defined using relative position between objects in UAV-captured images to significantly reduce the error level. Through aerial photography, a total of 97 images were acquired. Using the point cloud technique, image stitching, and homography matrix algorithm, 5 cracks and 3 reference objects were defined. Importantly, the comparative analysis of estimated relative position values and ground truth values through field measurement revealed that errors in the range 24-84 mm and 8-48 mm were obtained on the x- and y-directions, respectively. Also, RMSE errors of 37.95-91.24 mm were confirmed. In the future, the proposed methodology can be utilized for supplementing and improving the conventional methods for visual inspection of infrastructures and facilities. Woo, Hyun-Jung; Seo, Dong-Min; Kim, Min-Seok; Park, Min-San; Hong, Won-Hwa; Baek, Seung-Chan Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, Daegu 41566, South Korea; Kyungil Univ, Dept Architecture, Gyongsan 38428, South Korea 57219244497; 57222555933; 59073001500; 57880756600; 7401527968; 56909374400 baeksc@kiu.kr; SENSORS SENSORS-BASEL 1424-8220 22 17 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 1.54 2025-06-25 14 18 unmanned aerial vehicles; crack; localization; concrete structure POINT CLOUD; UAV; RECONSTRUCTION; OVERLAP concrete structure; crack; localization; unmanned aerial vehicles Aerial photography; Aircraft detection; Antennas; Concrete buildings; Concretes; Crack detection; Errors; Global positioning system; Unmanned aerial vehicles (UAV); Absolute position; Aerial vehicle; Detection technology; Inertial measurements units; Localisation; Location information; Position information; Relative positions; Structure-based; Unmanned aerial vehicle; algorithm; article; photography; unmanned aerial vehicle; Concrete construction English 2022 2022-09 10.3390/s22176711 바로가기 바로가기 바로가기 바로가기
Article Low Latency and High Data Rate (LLHD) Scheduler: A Multipath TCP Scheduler for Dynamic and Heterogeneous Networks The scheduler is a crucial component of the multipath transmission control protocol (MPTCP) that dictates the path that a data packet takes. Schedulers are in charge of delivering data packets in the right order to prevent delays caused by head-of-line blocking. The modern Internet is a complicated network whose characteristics change in real-time. MPTCP schedulers are supposed to understand the real-time properties of the underlying network, such as latency, path loss, and capacity, in order to make appropriate scheduling decisions. However, the present scheduler does not take into account all of these characteristics together, resulting in lower performance. We present the low latency and high data rate (LLHD) scheduler, which successfully makes scheduling decisions based on real-time information on latency, path loss, and capacity, and achieves around 25% higher throughput and 45% lower data transmission delay than Linux's default MPTCP scheduler. Lubna, Tabassum; Mahmud, Imtiaz; Cho, You-Ze Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA Mahmud, Imtiaz/R-1089-2019 57205303733; 56203487900; 7404469829 yzcho@ee.knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 24 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.26 2025-06-25 2 3 data rate; delay; MPTCP; schedulers MPTCP data rate; delay; MPTCP; schedulers Computer operating systems; Transmission control protocol; Data packet; Data-rate; Delay; High data rate; High data-rates; Low latency; Low-high; Multi-path transmission control protocols; Path loss; Scheduler; article; Internet; Heterogeneous networks English 2022 2022-12 10.3390/s22249869 바로가기 바로가기 바로가기 바로가기
Article mmS-TCP: Scalable TCP for Improving Throughput and Fairness in 5G mmWave Networks The millimeter-wave (mmWave) band, which can provide data rates of multi-gigabits per second, could play a major role in achieving the throughput goals of 5G networks. However, the high-bandwidth mmWave signal is susceptible to blockage by various obstacles, which results in very large and frequent degradation in the quality of the received signals. TCP, the most representative transport layer protocol, suffers from significant performance degradation due to the very dynamic channel conditions of the mmWave signal. Therefore, in this paper, we propose a congestion control algorithm that guarantees sufficient throughput in 5G mmWave networks and that does not significantly worsen TCP fairness. The proposed algorithm, which is a modification of Scalable TCP (S-TCP) that is designed for high-speed networks, provides a more stable performance than the existing TCP congestion control algorithm in mmWave networks through simple modifications. In various simulation experiments that considered the actual mobile user environment, the proposed mmWave Scalable TCP (mmS-TCP) algorithm demonstrated throughput up to 2.4 times higher than CUBIC TCP in single flow evaluation, and the inter-protocol fairness index when competing with CUBIC flow significantly improved from 0.819 of S-TCP to 0.9733. Moreover, the mmS-TCP algorithm reduced the number of duplicated ACKs by 1/4 compared with S-TCP, and it improved the average total throughput and intra-protocol fairness simultaneously. Kim, Geon-Hwan; Cho, You-Ze Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 57189040274; 7404469829 kgh76@ee.knu.ac.kr;yzcho@ee.knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 10 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.34 2025-06-25 3 4 active queue management; congestion control algorithm; TCP; 5G mmWave 5G mmWave; active queue management; congestion control algorithm; TCP Algorithms; Computer Simulation; 5G mobile communication systems; HIgh speed networks; Millimeter waves; Queueing networks; Traffic congestion; 5g millimeter-wave; Active Queue Management; Congestion control algorithm; Data-rate; Millimeter wave signals; Millimeter-wave band; Mm waves; Multi-gigabits; Protocol fairness; Scalable TCP; algorithm; computer simulation; Transmission control protocol English 2022 2022-05 10.3390/s22103609 바로가기 바로가기 바로가기 바로가기
Article Multiple Sensor Fault Detection Using Index-Based Method The research on sensor fault detection has drawn much interest in recent years. Abrupt, incipient, and intermittent sensor faults can cause the complete blackout of the system if left undetected. In this research, we examined the observer-based residual analysis via index-based approaches for fault detection of multiple sensors in a healthy drive. Seven main indices including the moving mean, average, root mean square, energy, variance, first-order derivative, second-order derivative, and auto-correlation-based index were employed and analyzed for sensor fault diagnosis. In addition, an auxiliary index was computed to differentiate a faulty sensor from a non-faulty one. These index-based methods were utilized for further analysis of sensor fault detection operating under a range of various loads, varying speeds, and fault severity levels. The simulation results on a permanent magnet synchronous motor (PMSM) are provided to demonstrate the pros and cons of various index-based methods for various fault detection scenarios. Narzary, Daijiry; Veluvolu, Kalyana Chakravarthy Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea Veluvolu, Kalyana/C-6366-2011; NARZARY, DAIJIRY/AIE-7187-2022; Veluvolu, Kalyana Chakravarthy/C-6366-2011 57201854373; 8703318200 veluvolu@ee.knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 20 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.43 2025-06-25 4 5 fault detection; fault detection index; residuals analysis; permanent magnet synchronous motor; multi-sensor faults TOLERANT CONTROL; SHORT-CIRCUIT; DIAGNOSIS; MODEL; SYSTEMS; PMSM fault detection; fault detection index; multi-sensor faults; permanent magnet synchronous motor; residuals analysis Algorithms; Computer Simulation; algorithm; computer simulation English 2022 2022-10 10.3390/s22207988 바로가기 바로가기 바로가기 바로가기
Article N-Step Pre-Training and Decalcomanie Data Augmentation for Micro-Expression Recognition Facial expressions are divided into micro- and macro-expressions. Micro-expressions are low-intensity emotions presented for a short moment of about 0.25 s, whereas macro-expressions last up to 4 s. To derive micro-expressions, participants are asked to suppress their emotions as much as possible while watching emotion-inducing videos. However, it is a challenging process, and the number of samples collected tends to be less than those of macro-expressions. Because training models with insufficient data may lead to decreased performance, this study proposes two ways to solve the problem of insufficient data for micro-expression training. The first method involves N-step pre-training, which performs multiple transfer learning from action recognition datasets to those in the facial domain. Second, we propose Decalcomanie data augmentation, which is based on facial symmetry, to create a composite image by cutting and pasting both faces around their center lines. The results show that the proposed methods can successfully overcome the data shortage problem and achieve high performance. Lee, Chaehyeon; Hong, Jiuk; Jung, Heechul Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea ; Jung, Heechul/HTL-7199-2023; Lee, Chae Yeon/HHS-3863-2022 57222731243; 57353688600; 55652175200 heechul@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 22 17 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2022 3.9 29.4 0.43 2025-06-25 5 5 deep learning; image processing; facial micro-expression; emotion recognition; convolutional neural network (CNN) convolutional neural network (CNN); deep learning; emotion recognition; facial micro-expression; image processing Convolutional neural networks; Deep learning; Face recognition; Transfer learning; Convolutional neural network; Data augmentation; Deep learning; Emotion recognition; Facial micro-expression; Images processing; Micro-expressions; Performance; Pre-training; article; convolutional neural network; deep learning; emotion; face; human; human experiment; image processing; protein expression; transfer of learning; Emotion Recognition English 2022 2022-09 10.3390/s22176671 바로가기 바로가기 바로가기 바로가기
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Title 논문의 제목입니다.
Abstract 논문의 초록(요약)입니다. 연구의 목적, 방법, 결과, 결론을 간략히 요약한 내용입니다.
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Journal 논문이 게재된 학술지의 정식 명칭입니다.
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ISSN International Standard Serial Number. 국제표준연속간행물번호로, 인쇄본 저널에 부여되는 고유 식별번호입니다.
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Volume 저널의 권(Volume) 번호입니다. 보통 연도별로 하나의 권이 부여됩니다.
Issue 저널의 호(Issue) 번호입니다. 한 권 내에서 여러 호로 나누어 출판되는 경우가 많습니다.
WoS Edition Web of Science의 에디션입니다. SCIE(Science Citation Index Expanded), SSCI(Social Sciences Citation Index), AHCI(Arts & Humanities Citation Index) 등으로 구분됩니다.
WoS Category Web of Science의 주제 분류 카테고리입니다. 저널과 논문이 속한 학문 분야를 나타냅니다.
JCR Year 해당 저널의 JCR(Journal Citation Reports) 지표가 산출된 연도입니다.
IF (Impact Factor) 저널 영향력 지수. 최근 2년간 발표된 논문이 해당 연도에 평균적으로 인용된 횟수를 나타냅니다. 저널의 학술적 영향력을 나타내는 대표적인 지표입니다.
JCR (%) 해당 카테고리에서 저널이 위치하는 상위 백분율입니다. 값이 낮을수록 우수한 저널임을 의미합니다 (예: 5%는 상위 5%를 의미).
FWCI Field-Weighted Citation Impact. 분야별 가중 인용 영향력 지수입니다. 논문이 받은 인용을 동일 분야, 동일 연도, 동일 문헌 유형의 평균과 비교한 값입니다. 1.0이 평균이며, 1.0보다 높으면 평균 이상의 인용을 받았음을 의미합니다.
FWCI UpdateDate FWCI 값이 마지막으로 업데이트된 날짜입니다. FWCI는 인용이 누적됨에 따라 주기적으로 업데이트됩니다.
WOS Citation Web of Science에서 집계된 해당 논문의 총 인용 횟수입니다.
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Keywords (WoS) 저자가 논문에서 직접 지정한 키워드입니다. Web of Science에 등록된 저자 키워드 목록입니다.
KeywordsPlus (WoS) Web of Science에서 자동으로 추출한 추가 키워드입니다. 논문의 참고문헌 제목에서 자주 등장하는 단어들로 생성됩니다.
Keywords (SCOPUS) 저자가 논문에서 직접 지정한 키워드입니다. SCOPUS에 등록된 저자 키워드 목록입니다.
KeywordsPlus (SCOPUS) SCOPUS에서 자동으로 추출하거나 추가한 색인 키워드입니다.
Language 논문이 작성된 언어입니다. 대부분 English이며, 그 외 다양한 언어로 작성된 논문이 포함될 수 있습니다.
Publication Year 논문이 출판된 연도입니다.
Publication Date 논문의 정확한 출판 날짜입니다 (년-월-일 형식).
DOI Digital Object Identifier. 디지털 객체 식별자로, 논문을 고유하게 식별하는 영구적인 식별번호입니다. 이를 통해 논문의 온라인 위치를 찾을 수 있습니다.