연구성과로 돌아가기

2023 연구성과 (154 / 285)

※ 컨트롤 + 클릭으로 열별 다중 정렬 가능합니다.
Excel 다운로드
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 Induction Motor Fault Diagnosis Using Support Vector Machine, Neural Networks, and Boosting Methods Induction motors are robust and cost effective; thus, they are commonly used as power sources in various industrial applications. However, due to the characteristics of induction motors, industrial processes can stop when motor failures occur. Thus, research is required to realize the quick and accurate diagnosis of faults in induction motors. In this study, we constructed an induction motor simulator with normal, rotor failure, and bearing failure states. Using this simulator, 1240 vibration datasets comprising 1024 data samples were obtained for each state. Then, failure diagnosis was performed on the acquired data using support vector machine, multilayer neural network, convolutional neural network, gradient boosting machine, and XGBoost machine learning models. The diagnostic accuracies and calculation speeds of these models were verified via stratified K-fold cross validation. In addition, a graphical user interface was designed and implemented for the proposed fault diagnosis technique. The experimental results demonstrate that the proposed fault diagnosis technique is suitable for diagnosing faults in induction motors. Kim, Min-Chan; Lee, Jong-Hyun; Wang, Dong-Hun; Lee, In-Soo Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea ; Kim, Sang/J-5399-2012 58061974000; 57201265019; 57336497500; 54979862300 insoolee@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 5 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 5.62 2025-06-25 35 45 induction motor; fault diagnosis; support vector machine; multilayer neural network fault diagnosis; induction motor; multilayer neural network; support vector machine Cost effectiveness; Failure (mechanical); Failure analysis; Fault detection; Graphical user interfaces; Induction motors; Multilayer neural networks; Multilayers; Boosting method; Cost effective; Fault diagnosis technique; Faults diagnosis; Inductions motors; Industrial processs; Motor fault; Neural network method; Power sources; Support vectors machine; Support vector machines English 2023 2023-03 10.3390/s23052585 바로가기 바로가기 바로가기 바로가기
Article NetAP-ML: Machine Learning-Assisted Adaptive Polling Technique for Virtualized IoT Devices To maximize the performance of IoT devices in edge computing, an adaptive polling technique that efficiently and accurately searches for the workload-optimized polling interval is required. In this paper, we propose NetAP-ML, which utilizes a machine learning technique to shrink the search space for finding an optimal polling interval. NetAP-ML is able to minimize the performance degradation in the search process and find a more accurate polling interval with the random forest regression algorithm. We implement and evaluate NetAP-ML in a Linux system. Our experimental setup consists of a various number of virtual machines (2-4) and threads (1-5). We demonstrate that NetAP-ML provides up to 23% higher bandwidth than the state-of-the-art technique. Park, Hyunchan; Go, Younghun; Lee, Kyungwoon; Hong, Cheol-Ho Jeonbuk Natl Univ, Div Comp Sci & Engn, Jeonju 54896, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daugu 41566, South Korea; Chung Ang Univ, Sch Elect & Elect Engn, Seoul 06974, South Korea Lee, Kyungwoon/AGE-8826-2022 23478123400; 58100150000; 57190025432; 35179802400 kwlee87@knu.ac.kr;cheolhohong@cau.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 3 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0 2025-06-25 0 0 edge computing; I; O virtualization; adaptive polling; machine learning PERFORMANCE; IMPLEMENTATION; LATENCY adaptive polling; edge computing; I/O virtualization; machine learning Computer operating systems; E-learning; Internet of things; Machine learning; Virtual reality; Virtualization; Adaptive polling; Edge computing; I/O virtualization; Machine learning techniques; Machine-learning; Performance; Performance degradation; Polling interval; Search spaces; Virtualizations; article; bandwidth; machine learning; random forest; Edge computing English 2023 2023-02 10.3390/s23031484 바로가기 바로가기 바로가기 바로가기
Article Non-Orthogonal Multiple Access with One-Bit Analog-to-Digital Converters Using Threshold Adaptation In digital communication systems featuring high-resolution analog-to-digital converters (ADCs), the utilization of successive interference cancellation and detection can enhance the capacity of a Gaussian multiple access channel (MAC) by combining signals from multiple transmitters in a non-orthogonal manner. Conversely, in systems employing one-bit ADCs, it is exceedingly difficult to eliminate non-orthogonal interference using digital signal processing due to the considerable distortion present in the received signal when employing such ADCs. As a result, the Gaussian MAC does not yield significant capacity gains in such cases. To address this issue, we demonstrate that, under a given deterministic interference, the capacity of a one-bit-quantized channel becomes equivalent to the capacity without interference when an appropriate threshold value is chosen. This finding suggests the potential for indirect interference cancellation in the analog domain, facilitating the proposition of an efficient successive interference cancellation and detection scheme. We analyze the achievable rate of the proposed scheme by deriving the mutual information between the transmitted and received signals at each detection stage. The obtained results indicate that the sum rate of the proposed scheme generally outperforms conventional methods, with the achievable upper bound being twice as high as that of the conventional methods. Additionally, we have developed an optimal transmit power allocation algorithm to maximize the sum rate in fading channels. Min, Moonsik; Kong, Jae-Ik; Kim, Tae-Kyoung Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Gachon Univ, Dept Elect Engn, Seongnam 13120, South Korea 55386299100; 58487885900; 57216708769 msmin@knu.ac.kr;te04034@knu.ac.kr;tk415kim@gmail.com; SENSORS SENSORS-BASEL 1424-8220 23 13 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0 2025-06-25 0 0 one-bit analog-to-digital converter; interference cancellation; multiple access channel; successive detection; power allocation WAVE MASSIVE MIMO; SYSTEMS; CAPACITY; CHANNEL; COMMUNICATION; UPLINK; ADCS interference cancellation; multiple access channel; one-bit analog-to-digital converter; power allocation; successive detection Acclimatization; Algorithms; Normal Distribution; Signal Processing, Computer-Assisted; Analog to digital conversion; Digital communication systems; Digital signal processing; Multiple access interference; Analog to digital converters; Gaussian multiple-access channels; Interference cancellation; Interference detection; Multiple access channels; Non-orthogonal; One-bit analog-to-digital converter; Power allocations; Successive detections; Successive interference cancellations; acclimatization; algorithm; normal distribution; signal processing; Fading channels English 2023 2023-07 10.3390/s23136004 바로가기 바로가기 바로가기 바로가기
Article Novel ANOVA-Statistic-Reduced Deep Fully Connected Neural Network for the Damage Grade Prediction of Post-Earthquake Buildings Earthquakes are cataclysmic events that can harm structures and human existence. The estimation of seismic damage to buildings remains a challenging task due to several environmental uncertainties. The damage grade categorization of a building takes a significant amount of time and work. The early analysis of the damage rate of concrete building structures is essential for addressing the need to repair and avoid accidents. With this motivation, an ANOVA-Statistic-Reduced Deep Fully Connected Neural Network (ASR-DFCNN) model is proposed that can grade damages accurately by considering significant damage features. A dataset containing 26 attributes from 762,106 damaged buildings was used for the model building. This work focused on analyzing the importance of feature selection and enhancing the accuracy of damage grade categorization. Initially, a dataset without primary feature selection was utilized for damage grade categorization using various machine learning (ML) classifiers, and the performance was recorded. Secondly, ANOVA was applied to the original dataset to eliminate the insignificant attributes for determining the damage grade. The selected features were subjected to 10-component principal component analysis (PCA) to scrutinize the top-ten-ranked significant features that contributed to grading the building damage. The 10-component ANOVA PCA-reduced (ASR) dataset was applied to the classifiers for damage grade prediction. The results showed that the Bagging classifier with the reduced dataset produced the greatest accuracy of 83% among all the classifiers considering an 80:20 ratio of data for the training and testing phases. To enhance the performance of prediction, a deep fully connected convolutional neural network (DFCNN) was implemented with a reduced dataset (ASR). The proposed ASR-DFCNN model was designed with the sequential keras model with four dense layers, with the first three dense layers fitted with the ReLU activation function and the final dense layer fitted with a tanh activation function with a dropout of 0.2. The ASR-DFCNN model was compiled with a NADAM optimizer with the weight decay of L2 regularization. The damage grade categorization performance of the ASR-DFCNN model was compared with that of other ML classifiers using precision, recall, F-Scores, and accuracy values. From the results, it is evident that the ASR-DFCNN model performance was better, with 98% accuracy. Preethaa, K. R. Sri; Munisamy, Shyamala Devi; Rajendran, Aruna; Muthuramalingam, Akila; Natarajan, Yuvaraj; Ali, Ahmed Abdi Yusuf Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, 80 Daehak Ro, Daegu 41566, South Korea; KPR Inst Engn & Technol, Dept Comp Sci & Engn, Coimbatore 641407, India; Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & T, Chennai 600062, India; Univ Johannesburg, Dept Elect Engn, ZA-2006 Johannesburg, South Africa ; raj, yuva/GWV-2080-2022; Natarajan, Yuvaraj/GWV-2080-2022; Devi, Shyamala/AAS-7396-2021; Nandhini, Aruna/JFS-2170-2023; R, Aruna/JFS-2170-2023 57214320928; 36688404200; 58509317500; 35118760000; 57204528689; 58968921000 k.r.sripreethaa@kpriet.ac.in;shyamaladevim@veltech.edu.in;drraruna@veltech.edu.in;yuvaraj.n@kpriet.ac.in;aali@uj.ac.za; SENSORS SENSORS-BASEL 1424-8220 23 14 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 1.83 2025-06-25 7 14 ANOVA; activation; classifier; PCA; gradient descent; regularization; DFCNN activation; ANOVA; classifier; DFCNN; gradient descent; PCA; regularization Buildings; Chemical activation; Classification (of information); Convolutional neural networks; Deep neural networks; Earthquakes; Feature extraction; Forecasting; Gradient methods; Grading; Neural network models; Principal component analysis; Statistical tests; Convolutional neural network; Deep fully connected convolutional neural network; Dense layer; Fully connected neural network; Grade predictions; Gradient-descent; Neural network model; Performance; Principal-component analysis; Regularisation; Analysis of variance (ANOVA) English 2023 2023-07 10.3390/s23146439 바로가기 바로가기 바로가기 바로가기
Article Optimized Replication of ADC-Based Particle Counting Algorithm with Reconfigurable Multi-Variables in Pseudo-Supervised Digital Twining of Reference Dust Sensor Systems As the application fields for digital twins have expanded, various studies have been conducted with the objective of optimizing the costs. Among these studies, research on low-power and low-performance embedded devices has been implemented at a low cost by replicating the performance of existing devices. In this study, we attempt to obtain similar particle count results in a single-sensing device replicated from the particle count results in a multi-sensing device without knowledge of the particle count acquisition algorithm of the multi-sensing device. Through filtering, we suppressed the noise and baseline movements of the raw data of the device. In addition, in the process of determining the multi-threshold for obtaining the particle counts, the existing complex particle count determination algorithm was simplified to make it possible to utilize the look-up table. The proposed simplified particle count calculation algorithm reduced the optimal multi-threshold search time by 87% on average and the root mean square error by 58.5% compared to existing method. In addition, it was confirmed that the distribution of particle count from optimal multi-thresholds has a similar shape to that from multi-sensing devices. Lee, Seungmin; Kwon, Jisu; Park, Daejin Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 57200005388; 57215531728; 55463943600 lsm1106@knu.ac.kr;kjisu96@knu.ac.kr;boltanut@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 12 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.39 2025-06-25 2 3 digital twin; dust sensing; particle count; ADC filter; embedded device TEMPLATE; PM2.5 ADC filter; digital twin; dust sensing; embedded device; particle count Algorithms; Dust; Analog to digital conversion; Embedded systems; Field programmable gate arrays (FPGA); Mean square error; Table lookup; ADC filter; Dust sensing; Embedded device; Multi variables; Multithreshold; Particle counting; Particle-counts; Performance; Reconfigurable; Sensing devices; algorithm; dust; Dust English 2023 2023-06 10.3390/s23125557 바로가기 바로가기 바로가기 바로가기
Article Parameter Optimization of Coupled 1D-2D Hydrodynamic Model for Urban Flood Inundation In this study, the sensitivity of the parameters was analyzed using PEST (Parameter ESTimation) to improve the accuracy of the runoff and flooding analysis in urban areas. Using four parameters (watershed width, roughness coefficient of impervious and pervious areas, and Manning's roughness coefficient for conduits) with high sensitivity, six scenarios were created according to the number of parameters considered, and a PEST-SWMM (Storm Water Management Model) combined simulation was performed. The scenarios were applied to the Seocho 3, 4, 5, Yeoksam, and Nonhyun drainage basins in which inundation damage occurred due to the heavy rain on 21 July 2013. The sensitivity of the four parameters was in the order of Manning's roughness coefficient for conduits, the roughness coefficient of the impervious area, the watershed width, and the roughness coefficient of the pervious area. When the PEST-SWMM coupled analysis for each scenario was performed using the analyzed sensitivity results, the RMSE (Root Mean Square Error) decreased by up to 2.37 cm and the RPE (Relative Peak Error) decreased by 22.04% compared to the SWMM alone. When the accuracy of each scenario was analyzed, similar or better accuracy was obtained as far as the parameters were considered. However, the further consideration of less sensitive parameters tends to reduce the accuracy. In this study, it was found that a more efficient simulation in terms of accuracy and calculation time could be obtained when constructing scenarios by considering only highly sensitive parameters. Additionally, when combining two-dimensional (2D) flood analysis with other rainfall events, it can help study real-time flood forecasting in urban areas. Ha, Chang-Young; Kim, Beom-Jin; Lee, Jae-Nam; Kim, Byung-Hyun Korea Rural Community Corp, Gyeonggi Reg Headquarters, Daegu 41463, South Korea; Korea Atom Energy Res Inst, Adv Struct & Seism Safety Res Div, Daejeon 34057, South Korea; Korea Rural Community Corp, Rural Res Inst, Ansansi 15634, South Korea; Kyungpook Natl Univ, Dept Civil Engn, Daegu 41566, South Korea ; Kim, Byung-Hyun/HGB-5885-2022 58550173600; 57222745004; 57226716531; 56097886500 cyha@ekr.or.kr;beomjin88@kaeri.re.kr;jnlee@ekr.or.kr;bhkimc@knu.ac.kr; WATER WATER-SUI 2073-4441 15 16 SCIE ENVIRONMENTAL SCIENCES;WATER RESOURCES 2023 3 30.9 0.5 2025-06-25 3 3 urban runoff; PEST; sensitivity analysis; optimization; flood inundation CALIBRATION flood inundation; optimization; PEST; sensitivity analysis; urban runoff Catchments; Flood control; Mean square error; Rain; Runoff; Sensitivity analysis; Sewage; Water management; Watersheds; 2D hydrodynamic models; Flood inundation; Optimisations; Parameter optimization; Parameters estimation; Roughness coefficient; Sensitive parameter; Urban areas; Urban floods; Urban runoff; flood forecasting; flooding; hydrodynamics; optimization; parameter estimation; roughness; runoff; sensitivity analysis; two-dimensional modeling; watershed; Floods English 2023 2023-08 10.3390/w15162946 바로가기 바로가기 바로가기 바로가기
Article Physicochemical characteristics of an alcohol hangover relief drink containing persimmon vinegar The development of alcohol hangover relief drinks by adding persimmon vinegar was investigated in this study. This study aimed to develop and investigate the physicochemical characteristics of a hangover relief drink, derived from persimmon vinegar, that may have health benefits. Persimmon vinegar was added at concentrations of 0, 2.5, 5, 7.5, 10 and 12.5%. The higher the concentration of persimmon vinegar, the lower the pH, degrees Brix and reducing sugar content of the product. In contrast, higher titratable acidity, turbidity and tannin values were obtained with increasing concentrations of persimmon vinegar. The addition of 12.5% persimmon vinegar induced the highest alcohol dehydrogenase and acetaldehyde dehydrogenase activities at 160.91 and 117.14%, respectively. The L value also decreased as persimmon vinegar concentration increased. The addition of persimmon vinegar at high concentrations decreased fructose, glucose and maltose content but increased the sucrose content of the drink. Ca, K and Na were the most abundant minerals in the drink. Some organic acids, such as oxalic, malic, lactic, acetic, citric and succinic acids, were also detected in the developed alcohol hangover relief drink. This study suggests that adding 7.5% of persimmon vinegar improves the physicochemical characteristics, especially the Alcohol dehydrogenase and aldehyde dehydrogenase activities. This finding indicates that this formulated drink with 75% persimmon vinegar may be beneficial against oxidative stress. Lee, Soo Won; Moon, Hey Kyung; Lee, Seul; Yun, Yong Deuk; Kim, Jong Kuk Kyungpook Natl Univ, Dept Food & Food Serv Ind, 2559 Gyeongsang Daero, Sangju City 37224, Gyeongsangbug D, South Korea Kuk, Kim/ABH-5221-2020 58172210800; 57196465303; 57194116993; 58175591300; 57203324852 kjk@knu.ac.kr; AIMS AGRICULTURE AND FOOD AIMS AGRIC FOOD 2471-2086 8 2 ESCI AGRICULTURE, MULTIDISCIPLINARY;AGRONOMY;FOOD SCIENCE & TECHNOLOGY 2023 1.9 30.9 0.22 2025-06-25 1 1 beverage; extraction; persimmon; vinegar; alcohol hangover relief drink ANTIOXIDANT CAPACITY; SENSORY CHARACTERISTICS; ACID; JUICES; LIVER alcohol hangover relief drink; beverage; extraction; persimmon; vinegar English 2023 2023 10.3934/agrfood.2023016 바로가기 바로가기 바로가기 바로가기
Article Provably Secure Mutual Authentication and Key Agreement Scheme Using PUF in Internet of Drones Deployments Internet of Drones (IoD), designed to coordinate the access of unmanned aerial vehicles (UAVs), is a specific application of the Internet of Things (IoT). Drones are used to control airspace and offer services such as rescue, traffic surveillance, environmental monitoring, delivery and so on. However, IoD continues to suffer from privacy and security issues. Firstly, messages are transmitted over public channels in IoD environments, which compromises data security. Further, sensitive data can also be extracted from stolen mobile devices of remote users. Moreover, drones are susceptible to physical capture and manipulation by adversaries, which are called drone capture attacks. Thus, the development of a secure and lightweight authentication scheme is essential to overcoming these security vulnerabilities, even on resource-constrained drones. In 2021, Akram et al. proposed a secure and lightweight user-drone authentication scheme for drone networks. However, we discovered that Akram et al.'s scheme is susceptible to user and drone impersonation, verification table leakage, and denial of service (DoS) attacks. Furthermore, their scheme cannot provide perfect forward secrecy. To overcome the aforementioned security vulnerabilities, we propose a secure mutual authentication and key agreement scheme between user and drone pairs. The proposed scheme utilizes physical unclonable function (PUF) to give drones uniqueness and resistance against drone stolen attacks. Moreover, the proposed scheme uses a fuzzy extractor to utilize the biometrics of users as secret parameters. We analyze the security of the proposed scheme using informal security analysis, Burrows-Abadi-Needham (BAN) logic, a Real-or-Random (RoR) model, and Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation. We also compared the security features and performance of the proposed scheme and the existing related schemes. Therefore, we demonstrate that the proposed scheme is suitable for IoD environments that can provide users with secure and convenient wireless communications. Park, Yohan; Ryu, Daeun; Kwon, Deokkyu; Park, Youngho Keimyung Univ, Sch Comp Engn, Daegu 42601, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea 55660095600; 58116873200; 57221739597; 56962990300 kdk145@knu.ac.kr;parkyh@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 4 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 2.87 2025-06-25 21 23 AVISPA; BAN logic; Internet of Drones; mutual authentication; PUF LIGHTWEIGHT; DESIGN; PROTOCOL; SURVEILLANCE; EXCHANGE; PRIVACY; SYSTEM AVISPA; BAN logic; Internet of Drones; mutual authentication; PUF Antennas; Authentication; Computer circuits; Cryptography; Denial-of-service attack; Internet of things; Mobile security; Network security; Security systems; Sensitive data; Authentication and key agreements; Automated verification; Automated verification of internet security protocol and application; Burrow–abadi–needham logic; Internet of drone; Internet security; Key agreement scheme; Mutual authentication; Security application; Security protocols; article; biometry; denial of service attack; environmental monitoring; internet of things; internet security; logic; privacy; simulation; unmanned aerial vehicle; vulnerability; wireless communication; Drones English 2023 2023-02 10.3390/s23042034 바로가기 바로가기 바로가기 바로가기
Article Reinforcement Learning-Aided Channel Estimator in Time-Varying MIMO Systems This paper proposes a reinforcement learning-aided channel estimator for time-varying multi-input multi-output systems. The basic concept of the proposed channel estimator is the selection of the detected data symbol in the data-aided channel estimation. To achieve the selection successfully, we first formulate an optimization problem to minimize the data-aided channel estimation error. However, in time-varying channels, the optimal solution is difficult to derive because of its computational complexity and the time-varying nature of the channel. To address these difficulties, we consider a sequential selection for the detected symbols and a refinement for the selected symbols. A Markov decision process is formulated for sequential selection, and a reinforcement learning algorithm that efficiently computes the optimal policy is proposed with state element refinement. Simulation results demonstrate that the proposed channel estimator outperforms conventional channel estimators by efficiently capturing the variation of the channels. Kim, Tae-Kyoung; Min, Moonsik Gachon Univ, Dept Elect Engn, Seongnam 13120, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 57216708769; 55386299100 tk415kim@gmail.com;msmin@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 12 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.26 2025-06-25 1 2 data-aided channel estimation; non-iterative approach; first-order Gaussian-Markov channel model; reinforcement learning MASSIVE MIMO; PILOT data-aided channel estimation; first-order Gaussian—Markov channel model; non-iterative approach; reinforcement learning Algorithms; Computer Simulation; Markov Chains; Policy; Channel estimation; Iterative methods; Learning algorithms; Learning systems; Markov processes; MIMO systems; Multiplexing equipment; Time varying networks; Data-aided; Data-aided channel estimation; First order; First-order gaussian—markov channel model; Gaussians; Iterative approach; Markov channel model; Non-iterative; Non-iterative approach; Reinforcement learnings; algorithm; computer simulation; Markov chain; policy; Reinforcement learning English 2023 2023-06 10.3390/s23125689 바로가기 바로가기 바로가기 바로가기
Article Reliability Assessment of a Vision-Based Dynamic Displacement Measurement System Using an Unmanned Aerial Vehicle In recent years, many studies have been conducted on the vision-based displacement measurement system using an unmanned aerial vehicle, which has been used in actual structure measurements. In this study, the dynamic measurement reliability of a vision-based displacement measurement system using an unmanned aerial vehicle was examined by measuring various vibrations with a frequency of 0 to 3 Hz and a displacement of 0 to 100 mm. Furthermore, free vibration was applied to model structures with one and two stories, and the response was measured to examine the accuracy of identifying structural dynamic characteristics. The vibration measurement results demonstrated that the vision-based displacement measurement system using an unmanned aerial vehicle has an average root mean square percentage error of 0.662% compared with the laser distance sensor in all experiments. However, the errors were relatively large in the displacement measurement of 10 mm or less regardless of the frequency. In the structure measurements, all sensors demonstrated the same mode frequency based on the accelerometer, and the damping ratios were extremely similar, except for the laser distance sensor measurement value of the two-story structure. Mode shape estimation was obtained and compared using the modal assurance criterion value compared with the accelerometer, and the values for the vision-based displacement measurement system using an unmanned aerial vehicle were close to 1. According to these results, the vision-based displacement measurement system using an unmanned aerial vehicle demonstrated results similar to those of conventional displacement sensors and can thus replace conventional displacement sensors. Kim, Hongjin; Kim, Guyeon Kyungpook Natl Univ, Dept Architectural Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Architectural Civil Environm & Energy Engn, Daegu 41566, South Korea 56278546400; 58429828600 kky9967@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 6 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.78 2025-06-25 6 6 VDMS using UAV; shaking table test; system identification; reliability assessment COMPUTER VISION; INSPECTION; SENSORS; PROOF; UAV reliability assessment; shaking table test; system identification; VDMS using UAV Accelerometers; Antennas; Displacement measurement; Parameter estimation; Reliability analysis; Structural dynamics; Structural health monitoring; Vibrations (mechanical); Aerial vehicle; Displacements measurements; Laser distance sensors; Measurement system; Reliability assessments; Shaking table tests; Structure measurement; System-identification; VDMS using UAV; Vision based; Unmanned aerial vehicles (UAV) English 2023 2023-03 10.3390/s23063232 바로가기 바로가기 바로가기 바로가기
Article RIS-Assisted Hybrid Beamforming and Connected User Vehicle Localization for Millimeter Wave MIMO Systems A reconfigurable intelligent surface (RIS) is a type of metasurface that can dynamically control the reflection and transmission of electromagnetic waves, such as radio waves, by changing its physical properties. Recently, RISs have played an important role in intelligently reshaping wireless propagation environments to improve the received signal gain as well as spectral efficiency performance. In this paper, we consider a millimeter wave (mmWave) vehicle-to-vehicle (V2V) multiple-input multiple-output (MIMO) system in which, an RIS is deployed to aid downlink V2V data transmission. In particular, the line-of-sight path of the mmWave system is affected by blockages, resulting in higher signaling overhead. Thus, the system performance may suffer due to interruptions caused by static or mobile blockers, such as buildings, trees, vehicles, and pedestrians. In this paper, we propose an RIS-assisted hybrid beamforming scheme for blockage-aware mmWave V2V MIMO systems to increase communication service coverage. First, we propose a conjugate gradient and location-based hybrid beamforming (CG-LHB) algorithm to solve the user sub-rate maximization problem. We then propose a double-step iterative algorithm that utilizes an error covariance matrix splitting method to minimize the effect of location error on the passive beamforming. The proposed algorithms perform quite well when the channel uncertainty is smaller than 10%. Finally, the simulation results validate the proposed CG-LHB algorithm in terms of the RIS-assisted equivalent channel for mmWave V2V MIMO communications. Sarker, Md. Abdul Latif; Son, Woosung; Han, Dong Seog Kyungpook Natl Univ, Ctr ICT & Automot Convergence, Daegu 41566, South Korea; Kyungpook Natl Univ, Grad Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea ; Han, Dong Seog/N-8949-2018 42262729500; 57223306362; 7403219442 dshan@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 7 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.26 2025-06-25 2 2 millimeter-wave MIMO; RIS; vehicle-to-vehicle communications; connected autonomous vehicle; spectral efficiency; location error RECONFIGURABLE INTELLIGENT SURFACES; REFLECTING SURFACES; CHANNEL ESTIMATION; POWER ALLOCATION; NETWORKS; DESIGN; ARCHITECTURES; ANALOG connected autonomous vehicle; location error; millimeter-wave MIMO; RIS; spectral efficiency; vehicle-to-vehicle communications Beamforming; Covariance matrix; Errors; Iterative methods; Location; Millimeter waves; MIMO systems; Vehicle to vehicle communications; Vehicle transmissions; Autonomous Vehicles; Connected autonomous vehicle; Location errors; Millimeter-wave multiple-input multiple-output; Multiple inputs; Multiple outputs; Reconfigurable; Reconfigurable intelligent surface; Spectral efficiencies; Vehicle-to-vehicle communication; algorithm; article; autonomous vehicle; conjugate; covariance; human; pedestrian; signal transduction; simulation; uncertainty; Spectrum efficiency English 2023 2023-04 10.3390/s23073713 바로가기 바로가기 바로가기 바로가기
Article Robust Adaptive Control Strategy for a Bidirectional DC-DC Converter Based on Extremum Seeking and Sliding Mode Control This paper presents a new control strategy that combines classical control and an optimization scheme to regulate the output voltage of the bidirectional converter under the presence of matched and mismatched disturbances. In detail, a control-oriented modeling method is presented first to capture the system dynamics in a common canonical form, allowing different disturbances to be considered. To estimate and compensate for unknown disturbances, an extended state observer (ESO)-based continuous sliding mode control is then proposed, which can guarantee high tracking precision, fast disturbance rejection, and chattering reduction. Next, an extremum seeking (ES)-based adaptive scheme is introduced to ensure system robustness as well as optimal control effort under different working scenarios. Finally, comparative simulations with classical proportional-integral-derivative (PID) control and constant switching gains are conducted to verify the effectiveness of the proposed adaptive control methodology through three case studies of load resistance variations, buck/boost mode switching, and input voltage variation. Trinh, Hoai-An; Nguyen, Duc Giap; Phan, Van-Du; Duong, Tan-Quoc; Truong, Hoai-Vu-Anh; Choi, Sung-Jin; Ahn, Kyoung Kwan Univ Ulsan, Dept Mech Engn, Ulsan 44610, South Korea; Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea; Univ Ulsan, Dept Elect Elect & Comp Engn, Ulsan 44610, South Korea; Pohang Univ Sci & Technol POSTECH, Dept Mech Engn, Gyeongbuk 37673, South Korea Truong, Anh/AHC-8849-2022; Phan, Du/ITU-6736-2023; Duong, Tan-Quoc/GVS-5682-2022 57219930708; 57221496576; 59949524500; 57279619600; 57193444182; 7408120164; 14017829800 kkahn@ulsan.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 1 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 2.61 2025-06-25 12 21 bidirectional DC-DC converter; voltage regulation; continuous sliding mode control; extended state observer; extremum seeking STORAGE; DESIGN; STATE bidirectional DC-DC converter; continuous sliding mode control; extended state observer; extremum seeking; voltage regulation Adaptive control systems; Boost converter; Disturbance rejection; Power quality; Proportional control systems; State estimation; Two term control systems; Voltage regulators; Adaptive control strategy; Bidirectional DC/DC converters; Classical control; Continuous sliding mode control; Continuous sliding modes; Control strategies; Extended state observer; Extremum seeking; Robust-adaptive control; Sliding-mode control; article; buck (mammal); control strategy; controlled study; human; male; simulation; Sliding mode control English 2023 2023-01 10.3390/s23010457 바로가기 바로가기 바로가기 바로가기
Article Robust and Efficient Authentication and Group-Proof Scheme Using Physical Unclonable Functions for Wearable Computing Wearable computing has garnered a lot of attention due to its various advantages, including automatic recognition and categorization of human actions from sensor data. However, wearable computing environments can be fragile to cyber security attacks since adversaries attempt to block, delete, or intercept the exchanged information via insecure communication channels. In addition to cyber security attacks, wearable sensor devices cannot resist physical threats since they are batched in unattended circumstances. Furthermore, existing schemes are not suited for resource-constrained wearable sensor devices with regard to communication and computational costs and are inefficient regarding the verification of multiple sensor devices simultaneously. Thus, we designed an efficient and robust authentication and group-proof scheme using physical unclonable functions (PUFs) for wearable computing, denoted as AGPS-PUFs, to provide high-security and cost-effective efficiency compared to the previous schemes. We evaluated the security of the AGPS-PUF using a formal security analysis, including the ROR Oracle model and AVISPA. We carried out the testbed experiments using MIRACL on Raspberry PI4 and then presented a comparative analysis of the performance between the AGPS-PUF scheme and the previous schemes. Consequently, the AGPS-PUF offers superior security and efficiency than existing schemes and can be applied to practical wearable computing environments. Yu, Sungjin; Park, Youngho Elect & Telecommun Res Inst, Daejeon 34129, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea 57203974524; 56962990300 sj.yu@etri.re.kr;parkyh@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 12 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.65 2025-06-25 5 5 physical unclonable function (PUF); privacy-preserving; authentication; group proof; wearable computing PROVABLY SECURE; PROTOCOL; INTERNET; DEVICES authentication; group proof; physical unclonable function (PUF); privacy-preserving; wearable computing Communication; Computer Security; Costs and Cost Analysis; Humans; Telemedicine; Wearable Electronic Devices; Computer crime; Cost effectiveness; Crime; Cryptography; Cybersecurity; Efficiency; Hardware security; Network security; Wearable sensors; Computing environments; Cyber security; Efficient authentication; Group proof; Physical unclonable function; Privacy preserving; Proof schemes; Security attacks; Sensor device; Wearable computing; computer security; cost; human; interpersonal communication; telemedicine; Authentication English 2023 2023-06 10.3390/s23125747 바로가기 바로가기 바로가기 바로가기
Article Robust H-K Curvature Map Matching for Patient-to-CT Registration in Neurosurgical Navigation Systems Image-to-patient registration is a coordinate system matching process between real patients and medical images to actively utilize medical images such as computed tomography (CT) during surgery. This paper mainly deals with a markerless method utilizing scan data of patients and 3D data from CT images. The 3D surface data of the patient are registered to CT data using computer-based optimization methods such as iterative closest point (ICP) algorithms. However, if a proper initial location is not set up, the conventional ICP algorithm has the disadvantages that it takes a long converging time and also suffers from the local minimum problem during the process. We propose an automatic and robust 3D data registration method that can accurately find a proper initial location for the ICP algorithm using curvature matching. The proposed method finds and extracts the matching area for 3D registration by converting 3D CT data and 3D scan data to 2D curvature images and by performing curvature matching between them. Curvature features have characteristics that are robust to translation, rotation, and even some deformation. The proposed image-to-patient registration is implemented with the precise 3D registration of the extracted partial 3D CT data and the patient's scan data using the ICP algorithm. Kwon, Ki Hoon; Kim, Min Young Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Res Ctr Neurosurg Robot Syst, Daegu 41566, South Korea 57190749004; 56739349100 minykim@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 10 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.13 2025-06-25 1 1 H-K curvature; image-to-patient registration; spherical unwrapping; iterative closest point (ICP); template matching ROTATION; MODEL; SCALE H-K curvature; image-to-patient registration; iterative closest point (ICP); spherical unwrapping; template matching Algorithms; Humans; Rotation; Tomography, X-Ray Computed; Computerized tomography; Data mining; Iterative methods; Medical computing; Medical imaging; Template matching; Computed tomography data; H-K curvature; Image-to-patient registration; Iterative close point; Iterative Closest Points; Iterative closest points algorithms; K-curvature; Matchings; Patient registration; Spherical unwrapping; algorithm; human; rotation; x-ray computed tomography; Navigation systems English 2023 2023-05-19 10.3390/s23104903 바로가기 바로가기 바로가기 바로가기
Article Table-Balancing Cooperative Robot Based on Deep Reinforcement Learning Reinforcement learning is one of the artificial intelligence methods that enable robots to judge and operate situations on their own by learning to perform tasks. Previous reinforcement learning research has mainly focused on tasks performed by individual robots; however, everyday tasks, such as balancing tables, often require cooperation between two individuals to avoid injury when moving. In this research, we propose a deep reinforcement learning-based technique for robots to perform a table-balancing task in cooperation with a human. The cooperative robot proposed in this paper recognizes human behavior to balance the table. This recognition is achieved by utilizing the robot's camera to take an image of the state of the table, then the table-balance action is performed afterward. Deep Q-network (DQN) is a deep reinforcement learning technology applied to cooperative robots. As a result of learning table balancing, on average, the cooperative robot showed a 90% optimal policy convergence rate in 20 runs of training with optimal hyperparameters applied to DQN-based techniques. In the H/W experiment, the trained DQN-based robot achieved an operation precision of 90%, thus verifying its excellent performance. Kim, Yewon; Kim, Dae-Won; Kang, Bo-Yeong Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Chung Ang Univ, Sch Comp Sci & Engn, 84 Heukseok Ro, Seoul 06974, South Korea; Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, Daegu 41566, South Korea ; Kang, Bo-Yeong/IXW-6764-2023 58309651100; 57205734453; 26643468300 yewonkim.knu@gmail.com;dwkim@cau.ac.kr;kby09@knu.ac.kr; SENSORS SENSORS-BASEL 1424-8220 23 11 SCIE CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION 2023 3.4 30.9 0.39 2025-06-25 2 3 reinforcement learning; deep Q-network; cooperative robot; human-robot interaction FRAMEWORK cooperative robot; deep Q-network; human–robot interaction; reinforcement learning Artificial Intelligence; Humans; Robotics; Behavioral research; Deep learning; Human robot interaction; Intelligent robots; Learning systems; Artificial intelligence methods; Convergence rates; Cooperative robots; Deep Q-network; Human behaviors; Humans-robot interactions; Learning technology; Network-based; Optimal policies; Reinforcement learnings; artificial intelligence; human; procedures; robotics; Reinforcement learning English 2023 2023-05-31 10.3390/s23115235 바로가기 바로가기 바로가기 바로가기
페이지 이동:

논문 데이터 용어 설명

용어 설명
WoS Web of Science. Clarivate Analytics에서 제공하는 학술 데이터베이스입니다. 해당 논문이 WoS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
SCOPUS Elsevier에서 제공하는 세계 최대 규모의 초록 및 인용 데이터베이스입니다. 해당 논문이 SCOPUS에 수록되어 있는지 여부를 표시합니다 (○: 수록됨).
Document Type 문헌의 유형을 나타냅니다. Article(원저), Review(리뷰), Proceeding Paper(학회논문), Editorial Material(편집자료), Letter(레터) 등으로 분류됩니다.
Title 논문의 제목입니다.
Abstract 논문의 초록(요약)입니다. 연구의 목적, 방법, 결과, 결론을 간략히 요약한 내용입니다.
Authors 논문의 저자 목록입니다. 공동 저자가 여러 명인 경우 세미콜론(;)으로 구분됩니다.
Affiliation 저자들의 소속 기관 정보입니다. 대학, 연구소, 기업 등 저자가 소속된 기관명이 표시됩니다.
ResearcherID (WoS) Web of Science의 고유 연구자 식별번호입니다. 동명이인을 구분하고 연구자의 업적을 정확하게 추적할 수 있습니다.
AuthorsID (SCOPUS) SCOPUS의 고유 저자 식별번호입니다. 연구자의 모든 출판물을 추적하고 관리하는 데 사용됩니다.
Journal 논문이 게재된 학술지의 정식 명칭입니다.
JCR Abbreviation Journal Citation Reports에서 사용하는 저널의 공식 약어입니다. 저널을 간략하게 표기할 때 사용됩니다.
ISSN International Standard Serial Number. 국제표준연속간행물번호로, 인쇄본 저널에 부여되는 고유 식별번호입니다.
eISSN Electronic ISSN. 전자 버전 저널에 부여되는 고유 식별번호입니다.
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.
SCOPUS Citation SCOPUS에서 집계된 해당 논문의 총 인용 횟수입니다.
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.