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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 |
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| ○ | ○ | Article | Integrated, Automated, Fast PCR System for Point-Of-Care Molecular Diagnosis of Bacterial Infection | We developed an integrated PCR system that performs automated sample preparation and fast polymerase chain reaction (PCR) for application in point-of care (POC) testing. This system is assembled from inexpensive 3D-printing parts, off-the-shelf electronics and motors. Molecular detection requires a series of procedures including sample preparation, amplification, and fluorescence intensity analysis. The system can perform automated DNA sample preparation (extraction, separation and purification) in <= 5 min. The variance of the automated sample preparation was clearly lower than that achieved using manual DNA extraction. Fast thermal ramp cycles were generated by a customized thermocycler designed to automatically transport samples between heating and cooling blocks. Despite the large sample volume (50 mu L), rapid two-step PCR amplification completed 40 cycles in <= 13.8 min. Variations in fluorescence intensity were measured by analyzing fluorescence images. As proof of concept of this system, we demonstrated the rapid DNA detection of pathogenic bacteria. We also compared the sensitivity of this system with that of a commercial device during the automated extraction and fast PCR of Salmonella bacteria. | Lee, Dongkyu; Kim, Deawook; Han, Jounghyuk; Yun, Jongsu; Lee, Kang-Ho; Kim, Gyu Man; Kwon, Ohwon; Lee, Jaejong | Korea Inst Machinery & Mat, Daegu Res Ctr Med Devices, Daegu 42994, South Korea; Kyungpook Natl Univ, Dept Mech Engn, Daegu 41566, South Korea; Korea Inst Machinery & Mat KIMM, Nanomech Syst, Daejeon 34103, South Korea | Lee, Jaejong/AAC-5426-2021 | 8673376500; 57221396601; 57221397434; 57189457042; 56697620500; 55664733000; 57026875700; 56193091300 | dongkyu@kimm.re.kr;wooki@kimm.re.kr;hyek9210@kimm.re.kr;jsyoon@kimm.re.kr;kangholee6@kimm.re.kr;gyuman.kim@knu.ac.kr;owkwon@kimm.re.kr;jjlee@kimm.re.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 2 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 1.25 | 2025-07-30 | 14 | 10 | fast PCR; automated system; molecular diagnostics; sample preparation; rapid thermocycle | NUCLEIC-ACID EXTRACTION; ULTRAFAST | Automated system; Fast PCR; Molecular diagnostics; Rapid thermocycle; Sample preparation | Bacteria; Bacterial Infections; DNA; Humans; Point-of-Care Systems; Polymerase Chain Reaction; 3D printers; Automation; Bacteria; Diagnosis; DNA; Extraction; Fluorescence; Molecular biology; Purification; DNA; Automated extraction; Bacterial infections; DNA sample preparation; Fluorescence intensities; Heating and cooling; Molecular diagnosis; Pathogenic bacterium; Separation and purification; bacterial infection; bacterium; genetics; human; point of care system; polymerase chain reaction; Polymerase chain reaction | English | 2021 | 2021-01 | 10.3390/s21020377 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Learning Explainable Time-Morphology Patterns for Automatic Arrhythmia Classification from Short Single-Lead ECGs | Automatic detection of abnormal heart rhythms, including atrial fibrillation (AF), using signals obtained from a single-lead wearable electrocardiogram (ECG) device, is useful for daily cardiac health monitoring. In this study, we propose a novel image-based deep learning framework to classify single-lead ECG recordings of short variable length into several different rhythms associated with arrhythmias. By transforming variable-length 1D ECG signals into fixed-size 2D time-morphology representations and feeding them to the beat-interval-texture convolutional neural network (BIT-CNN) model, we aimed to learn the comprehensible characteristics of beat shape and inter-beat patterns over time for arrhythmia classification. The proposed approach allows feature embedding vectors to provide interpretable time-morphology patterns focused at each step of the learning process. In addition, this method reduces the number of model parameters needed to be trained and aids visual interpretation, while maintaining similar performance to other CNN-based approaches to arrhythmia classification. For experiments, we used the PhysioNet/CinC Challenge 2017 dataset and achieved an overall F-1NAO of 81.75% and F-1NAOP of 76.87%, which are comparable to those of the state-of-the-art methods for variable-length ECGs. | Lee, Hyeonjeong; Shin, Miyoung | Kyungpook Natl Univ, Sch Elect & Elect Engn, Biointelligence & Data Min Lab, Daegu 41566, South Korea | 57207747683; 7401536642 | leehj1224k@gmail.com;shinmy@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 13 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 1.69 | 2025-07-30 | 25 | 29 | arrhythmia classification; atrial fibrillation (AF); electrocardiogram (ECG); convolutional neural network (CNN); deep learning | P-WAVE MORPHOLOGY; ATRIAL-FIBRILLATION | Arrhythmia classification; Atrial fibrillation (AF); Convolutional neural network (CNN); Deep learning; Electrocardiogram (ECG) | Algorithms; Atrial Fibrillation; Electrocardiography; Humans; Neural Networks, Computer; Chemical detection; Convolutional neural networks; Deep learning; Diseases; Electrocardiography; Morphology; Textures; Arrhythmia classification; Atrial fibrillation; Automatic Detection; Feature embedding; Learning frameworks; Learning process; State-of-the-art methods; Visual interpretation; algorithm; atrial fibrillation; electrocardiography; human; Biomedical signal processing | English | 2021 | 2021-07 | 10.3390/s21134331 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | LECAR: Location Estimation-Based Congestion-Aware Routing Protocol for Sparsely Deployed Energy-Efficient UAVs | Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time. | Mahmud, Imtiaz; Cho, You-Ze | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | Mahmud, Imtiaz/R-1089-2019 | 56203487900; 7404469829 | imtiaz@knu.ac.kr;yzcho@ee.knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 21 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.22 | 2025-07-30 | 2 | 4 | DTN; DTN-based routing protocol; energy-efficient routing protocol; energy-efficient UAV; FANET; location estimation-based routing protocol; LECAR | AD-HOC NETWORKS | DTN; DTN-based routing protocol; Energy-efficient routing protocol; Energy-efficient UAV; FANET; LECAR; Location estimation-based routing protocol | Ad hoc networks; Antennas; Delay tolerant networks; Energy utilization; Location; Power management (telecommunication); Routing protocols; Unmanned aerial vehicles (UAV); Congestion-aware routing; Delay-Tolerant Network; Delay-tolerant network-based routing protocol; Energy efficient; Energy efficient routing protocol; Energy-efficient unmanned aerial vehicle; FANET; Location estimation; Location estimation-based congestion-aware routing protocol; Location estimation-based routing protocol; Network-based; Routing-protocol; Energy efficiency | English | 2021 | 2021-11 | 10.3390/s21217192 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Lightweight Microcontroller with Parallelized ECC-Based Code Memory Protection Unit for Robust Instruction Execution in Smart Sensors | Embedded systems typically operate in harsh environments, such as where there is external shock, insufficient power, or an obsolete sensor after the replacement cycle. Despite these harsh environments, embedded systems require data integrity for accurate operation. Unintended data changes can cause a serious error in reduced instruction set computer (RISC)-based small embedded systems. For instance, if communication is performed on an edge, where there is insufficient power supply, the peak threshold is not reached, resulting in data transmission failure or incorrect data transmission. To ensure data integrity, we use an error-correcting code (ECC), which can detect and correct errors. The ECC parity bit and data are stored together using additional ECC memory, and the original data are extracted through the ECC decoding process. The process of extracting the original data is executed in the instruction fetch stage, where a bottleneck appears in the RISC-based structure. When the ECC decoding process is executed in the bottleneck, the instruction fetch stage increases the instruction fetch time and significantly reduces the overall performance. In this study, we attempt to minimize the effect of ECC on the transmission speed by executing the ECC decoding process in parallel to improve speed by degrading the bottleneck. To evaluate the performance of a parallelized ECC decoding block, we applied the proposed method to the tiny processing unit (TPU) with a RISC-based von Neumann structure and compared memory usage, speed, and reliability according to different transmission success rates in each model. The experiment was conducted using a benchmark that repeatedly executed several 3*3 matrix calculations, and reliability improvement was compared by corrupting the stored random date to confirm the reliability of the transmission success rate. As a result, in the proposed model, using the additional parity bits for parallel processing, memory usage increased by 10 bits per instruction, reducing the data rate from 80 to 61%. However, it showed an improvement in overall reliability and a 7% increase in speed. | Kang, Myeongjin; Park, Daejin | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea | 57216440453; 55463943600 | audwls3158@knu.ac.kr;boltanut@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 16 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.15 | 2025-07-30 | 1 | 2 | embedded system; parallelized execution; ECC; performance improvement | ECC; Embedded system; Parallelized execution; Performance improvement | Data mining; Data transfer; Decoding; Embedded systems; Errors; Microcontrollers; Reliability; Error correcting code; Matrix calculations; Parallel processing; Reduced instruction set computers; Reliability improvement; Replacement cycles; Transmission speed; Transmission success rate; Data reduction | English | 2021 | 2021-08 | 10.3390/s21165508 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Marker-Based Method for Recognition of Camera Position for Mobile Robots | Position recognition is one of the core technologies for driving a robot because of differences in environment and rapidly changing situations. This study proposes a strategy for estimating the position of a camera mounted on a mobile robot. The proposed strategy comprises three methods. The first is to directly acquire information (e.g., identification (ID), marker size and marker type) to recognize the position of the camera relative to the marker. The advantage of this marker system is that a combination of markers of different sizes or having different information may be used without having to update the internal parameters of the robot system even if the user frequently changes or adds to the marker's identification information. In the second, two novel markers are proposed to consider the real environment in which real robots are applied: a nested marker and a hierarchical marker. These markers are proposed to improve the ability of the camera to recognize markers while the camera is moving on the mobile robot. The nested marker is effective for robots like drones, which land and take off vertically with respect to the ground. The hierarchical marker is suitable for robots that move horizontally with respect to the ground such as wheeled mobile robots. The third method is the calculation of the position of an added or moved marker based on a reference marker. This method automatically updates the positions of markers after considering the change in the driving area of the mobile robot. Finally, the proposed methods were validated through experiments. | Gwak, Dong-Gi; Yang, Kyon-Mo; Park, Min-Ro; Hahm, Jehun; Koo, Jaewan; Lee, Joonwoo; Seo, Kap-Ho | Korea Inst Robot & Technol Convergence, HRI Res Ctr, Pohang 37553, South Korea; Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Pohang Univ Sci & Technol, Dept Mech Engn, Pohang 37673, South Korea | 57191957109; 55698480000; 57188662021; 57201356120; 57217782518; 57209469100; 7201838999 | dg.gwak@kiro.re.kr;kmyang@kiro.re.kr;minro@kiro.re.kr;jhham@kiro.re.kr;jwkoo3236@kiro.re.kr;jwl@knu.ac.kr;neoworld@kiro.re.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 4 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.22 | 2025-07-30 | 3 | 4 | artificial marker; indoor localization; mobile robot; position recognition | TRACKING | Artificial marker; Indoor localization; Mobile robot; Position recognition | Cameras; Camera positions; Core technology; Different sizes; Internal parameters; Position recognition; Real environments; Robot system; Wheeled mobile robot; Mobile robots | English | 2021 | 2021-02 | 10.3390/s21041077 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Multivariate Analysis of Concrete Image Using Thermography and Edge Detection | With the growing demand for structural health monitoring system applications, data imaging is an ideal method for performing regular routine maintenance inspections. Image analysis can provide invaluable information about the health conditions of a structure's existing infrastructure by recording and analyzing exterior damages. Therefore, it is desirable to have an automated approach that reports defects on images reliably and robustly. This paper presents a multivariate analysis approach for images, specifically for assessing substantial damage (such as cracks). The image analysis provides graph representations that are related to the image, such as the histogram. In addition, image-processing techniques such as grayscale are also implemented, which enhance the object's information present in the image. In addition, this study uses image segmentation and a neural network, for transforming an image to analyze it more easily and as a classifier, respectively. Initially, each concrete structure image is preprocessed to highlight the crack. A neural network is used to calculate and categorize the visual characteristics of each region, and it shows an accuracy for classification of 98%. Experimental results show that thermal image extraction yields better histogram and cumulative distribution function features. The system can promote the development of various thermal image applications, such as nonphysical visual recognition and fault detection analysis. | Kim, Bubryur; Choi, Se-Woon; Hu, Gang; Lee, Dong-Eun; Serfa Juan, Ronnie O. | Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, 80 Daehak Ro, Daegu 41566, South Korea; Daegu Catholic Univ, Dept Architectural Engn, Hayang Ro 13-13, Gyeongasan Si 38430, South Korea; Harbin Inst Technol, Sch Civil & Environm Engn, Shenzhen 518055, Peoples R China; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80 Daehak Ro, Daegu 41566, South Korea | ; Serfa Juan, Ronnie/I-1924-2018; HU, Gang/P-8189-2018 | 57198355299; 39360956300; 56735061500; 56605563300; 57189444986 | brkim@knu.ac.kr;watercloud@cu.ac.kr;hugang@hit.edu.cn;dolee@knu.ac.kr;ronnie71@naver.com; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 21 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.59 | 2025-07-30 | 9 | 9 | crack analysis; concrete; cumulative distribution function; edge detection; Sobel edge detection | COMPRESSIVE STRENGTH; CRACK; ENHANCEMENT; RESOLUTION; ALGORITHM | Concrete; Crack analysis; Cumulative distribution function; Edge detection; Sobel edge detection | Image Processing, Computer-Assisted; Multivariate Analysis; Neural Networks, Computer; Thermography; Crack detection; Distribution functions; Edge detection; Fault detection; Graphic methods; Image analysis; Image enhancement; Image segmentation; Multivariant analysis; Structural health monitoring; Concrete images; Crack analysis; Cumulative distribution function; Growing demand; Image-analysis; Multi variate analysis; Neural-networks; Sobel edge detection; Structural health monitoring systems; Thermal images; image processing; multivariate analysis; thermography; Concretes | English | 2021 | 2021-11 | 10.3390/s21217396 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Non-Invasive Optical Coherence Tomography Data-Based Quantitative Algorithm for the Assessment of Residual Adhesive on Bracket-Removed Dental Surface | The aim of this study was to quantitatively assess the residual adhesive on orthodontic ceramic bracket-removed dental surface. In orthodontic process, ceramic bracket was repeated debonding physically, then the adhesive remained on the dental surface. The residual adhesive caused a lack of adhesive strength between dental and ceramic bracket. Since commonly used adhesive in orthodontics is translucent, residual adhesive is hard to be detected with conventional microscopes. Therefore, 1310 nm center wavelength swept-source OCT system based on laboratory customized image processing algorithm was used for the precise detection of residual adhesive on tooth surface. The algorithm separates residual adhesive from dental surface by comparing the height of adjacent B-scan images, while providing color-scaled images emphasizing the thickness information of residual adhesive. Finally, the acquired results were compared with microscopic and adhesive remnant index scoring gold standards, while the comparison confirmed the potential merits and the improvements of the proposed method over gold standards. | Kim, Yoonseok; Jung, Gu-In; Jeon, Deokmin; Wijesinghe, Ruchire Eranga; Seong, Daewoon; Lee, Jaeyul; Do, Woo Jong; Kwon, Sung-Min; Lee, Jong Hoon; Hwang, Jun Ho; Kim, Hyun Deok; Lee, Kyu-Bok; Jeon, Mansik; Kim, Jeehyun | Kyungpook Natl Univ, Coll IT Engn, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Inst Adv Convergence Technol, Daegu 41061, South Korea; Univ Sri Jayewardenepura, Fac Technol, Dept Mat & Mech Technol, Pitipana, Homagama, Sri Lanka; Kyungpook Natl Univ, Adv Dent Device Dev Inst, Daegu 41940, South Korea; Kyungpook Natl Univ, Sch Dent, Dept Prosthodont, Daegu 41940, South Korea | ; Wijesinghe, Ruchire/K-3797-2016; Kim, Yong Joon/IQS-7291-2023; Lee, Junsoo/IUO-9627-2023 | 57216828837; 59269989600; 57204570554; 56018152300; 57212512353; 57188689420; 57211515942; 56949626400; 57204786073; 57204783286; 55663858300; 15925571200; 24171094000; 7601373350 | otter0618@knu.ac.kr;guin83@knu.ac.kr;deokmin.jeon@gmail.com;erangawijesinghe@sjp.ac.lk;smc7095@knu.ac.kr;jaeyul@knu.ac.kr;loseo@knu.ac.kr;sungmin@iact.or.kr;laser@iact.or.kr;hjh@iact.or.kr;hdkim@knu.ac.kr;kblee@knu.ac.kr;msjeon@knu.ac.kr;jeehk@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 14 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 1.33 | 2025-07-30 | 18 | 20 | dental optical coherence tomography; orthodontic imaging; dental adhesive; residual adhesive; bracket removal inspection | SHEAR BOND STRENGTH; ENAMEL; LASER; OCT; TECHNOLOGY; REMNANT; SYSTEM | Bracket removal inspection; Dental adhesive; Dental optical coherence tomography; Orthodontic imaging; Residual adhesive | Adhesives; Algorithms; Ceramics; Materials Testing; Orthodontic Brackets; Surface Properties; Tomography, Optical Coherence; Gold metallography; Image processing; Optical data processing; Optical tomography; adhesive agent; Adhesive remnant index; Adhesive strength; Center wavelength; Dental surfaces; Gold standards; Image processing algorithm; Swept source OCT; Tooth surface; algorithm; ceramics; materials testing; optical coherence tomography; orthodontic bracket; surface property; Adhesives | English | 2021 | 2021-07 | 10.3390/s21144670 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Piezoelectric Ring Bender for Characterization of Shear Waves in Compacted Sandy Soils | Shear wave velocity and small-strain shear modulus are widely used as the mechanical properties of soil. The objective of this study is to develop a new shear wave monitoring system using a pair of piezoelectric ring benders (RBs) and to evaluate the suitability of RB in compacted soils compared with the bender element and ultrasonic transducer. The RB is a multilayered piezoelectric actuator, which can generate shear waves without disturbing soils. For five compacted soil specimens, the shear waves are monitored by using three different piezoelectric transducers. Results of time-domain response show that the output signals measured from the RB vary according to the water content of the specimen and the frequency of the input signal. Except at the water content of 9.3%, the difference in the resonant frequencies between the three transducers is not significant. The shear wave velocities for the RB are slightly greater than those for the other transducers. For the RB, the exponential relationship between the shear wave velocity and dry unit weight is better established compared with that of the other transducers. The newly proposed piezoelectric transducer RB may be useful for the evaluation of the shear wave velocity and small-strain shear modulus of compacted soils. | Kim, Dong-Ju; Yu, Jung-Doung; Byun, Yong-Hoon | Kyungpook Natl Univ, Sch Agr Civil & Bioind Engn, Daegu 41566, South Korea; Korea Univ, Sch Civil Environm & Architectural Engn, Seoul 02841, South Korea | Byun, Yong-Hoon/JKI-8441-2023; Yu, Jungdoung/GRR-3547-2022 | 7409760881; 55261077800; 42761048000 | kyrix1028@knu.ac.kr;noorung2@korea.ac.kr;yhbyun@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 4 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.52 | 2025-07-30 | 8 | 8 | compacted soil; piezoelectric transducers; shear modulus; shear wave velocity | Compacted soil; Piezoelectric transducers; Shear modulus; Shear wave velocity | Acoustic wave velocity; Elastic moduli; Natural frequencies; Piezoelectric actuators; Piezoelectric transducers; Piezoelectricity; Shear strain; Shear waves; Soils; Ultrasonic transducers; Wave propagation; Bender elements; Compacted soil; Dry unit weight; Piezoelectric rings; Shear wave velocity; Small-strain shear modulus; Time domain response; Wave monitoring systems; Shear flow | English | 2021 | 2021-02 | 10.3390/s21041226 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Provably Secure Three-Factor-Based Mutual Authentication Scheme with PUF for Wireless Medical Sensor Networks | Wireless medical sensor networks (WMSNs) are used in remote medical service environments to provide patients with convenient healthcare services. In a WMSN environment, patients wear a device that collects their health information and transmits the information via a gateway. Then, doctors make a diagnosis regarding the patient, utilizing the health information. However, this information can be vulnerable to various security attacks because the information is exchanged via an insecure channel. Therefore, a secure authentication scheme is necessary for WMSNs. In 2021, Masud et al. proposed a lightweight and anonymity-preserving user authentication scheme for healthcare environments. We discover that Masud et al.'s scheme is insecure against offline password guessing, user impersonation, and privileged insider attacks. Furthermore, we find that Masud et al.'s scheme cannot ensure user anonymity. To address the security vulnerabilities of Masud et al.'s scheme, we propose a three-factor-based mutual authentication scheme with a physical unclonable function (PUF). The proposed scheme is secure against various security attacks and provides anonymity, perfect forward secrecy, and mutual authentication utilizing biometrics and PUF. To prove the security features of our scheme, we analyze the scheme using informal analysis, Burrows-Abadi-Needham (BAN) logic, the Real-or-Random (RoR) model, and Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation. Furthermore, we estimate our scheme's security features, computation costs, communication costs, and energy consumption compared with the other related schemes. Consequently, we demonstrate that our scheme is suitable for WMSNs. | Kwon, DeokKyu; Park, YoHan; Park, YoungHo | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Keimyung Univ, Sch Comp Engn, Daegu 42601, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea | 57221739597; 55660095600; 56962990300 | kdk145@knu.ac.kr;yhpark@kmu.ac.kr;parkyh@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 18 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 2.21 | 2025-07-30 | 20 | 31 | wireless medical sensor networks; PUF; biometrics; BAN logic; RoR model; AVISPA | KEY AGREEMENT SCHEME; USER AUTHENTICATION; PROTOCOL; LIGHTWEIGHT; INTERNET; EXCHANGE; DESIGN; SYSTEM | AVISPA; BAN logic; Biometrics; PUF; RoR model; Wireless medical sensor networks | Biometry; Computer Security; Computer Simulation; Confidentiality; Humans; Telemedicine; Authentication; Computation theory; Cost benefit analysis; Cryptography; Diagnosis; Energy utilization; Gateways (computer networks); Health care; Security systems; Wireless sensor networks; Automated verification; Healthcare environments; Medical sensor networks; Offline password guessing; Perfect forward secrecy; Physical unclonable functions (PUF); Security vulnerabilities; User authentication scheme; biometry; computer security; computer simulation; confidentiality; human; telemedicine; Network security | English | 2021 | 2021-09 | 10.3390/s21186039 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging | The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed. | Kwak, Dong-Hoon; Son, Guk-Jin; Park, Mi-Kyung; Kim, Young-Duk | DGIST, ICT Res Inst, Daegu 42988, South Korea; Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea | ; Park, Mi-Kyung/J-9643-2017 | 57222297059; 57191336333; 7404491155; 55955831300 | gns9452@dgist.ac.kr;sudopop@dgist.ac.kr;parkmik@knu.ac.kr;ydkim@dgist.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 16 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 1.25 | 2025-07-30 | 16 | 22 | foreign object detection; hyperspectral imaging; visible and near-infrared; spectroscopy; signal processing; seaweed | FOOD QUALITY | Foreign object detection; Hyperspectral imaging; Seaweed; Signal processing; Spectroscopy; Visible and near‐infrared | Algorithms; Foreign Bodies; Hyperspectral Imaging; Seaweed; Vegetables; Belt conveyors; Dimensionality reduction; Hyperspectral imaging; Inspection; Object recognition; Seaweed; Spectroscopy; Accuracy Improvement; Conveyor belts; Diffuse reflection; Foreign object; Manufacturing sites; Mass production; Sargassum fusiforme; Subtraction method; algorithm; foreign body; seaweed; vegetable; Object detection | English | 2021 | 2021-08 | 10.3390/s21165279 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Reflected Wave Reduction Based on Time-Delay Separation for the Plane Array of Multilayer Acoustic Absorbers | This paper presents a control technique for reducing the reflection of acoustic signals for the plane array of multilayer acoustic absorbers underwater. In order to achieve this, a plane array of multilayer acoustic absorbers is proposed to attenuate low-frequency noise, with each unit consisting of a piezoelectric transducer, two layers of polyvinylidene fluorides and three layers of the acoustic window. Time-delay separation is used to find the incident and reflected acoustic signals to achieve reflected sound reduction. Experimental comparison of the attenuation rate of the reflected acoustic signal when performing passive and active controls is considered to verify the effectiveness of the time-delay separation technique applied plane array absorbers. Experiments on the plane array of smart skin absorbers confirmed that the reduction of reflected acoustic signals makes it suitable for a wide range of underwater applications. | Park, Hwijin; Won, Yeong Bae; Jeong, Sehyeong; Pyun, Joo Young; Park, Kwan Kyu; Lee, Jeong-Min; Seo, Hee-Seon; Yi, Hak | Kyungpook Natl Univ, Dept Mech Engn, Daegu 41566, South Korea; Hanyang Univ, Dept Convergence Mech Engn, Seoul 04763, South Korea; Agcy Def Dev, Maritime Technol Res Inst, Chang Won 51682, South Korea | ; Park, Kwan/AAC-1269-2021; Park, Kwan Kyu/L-1074-2016 | 57212660551; 57221051724; 57374839400; 57207316774; 55827729700; 57196138392; 24765212200; 56567311000 | phj0917@knu.ac.kr;wyp1028s@knu.ac.kr;jsh9634@knu.ac.kr;jooyoungpyun@hanyang.ac.kr;kwankyu@hanyang.ac.kr;leemin@add.re.kr;hsseo@add.re.kr;yihak@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 24 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0 | 2025-07-30 | 0 | 0 | smart skin; acoustic absorber; active noise control; piezoelectric material | Acoustic absorber; Active noise control; Piezoelectric material; Smart skin | Acoustic noise; Delay control systems; Fluorine compounds; Multilayers; Piezoelectricity; Separation; Time delay; % reductions; A-plane; Acoustic absorbers; Acoustic signals; Control techniques; Low-Frequency Noise; Polyvinylidene fluorides; Reflected waves; Smart skin; Two-layer; Timing circuits | English | 2021 | 2021-12 | 10.3390/s21248432 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | SalfMix: A Novel Single Image-Based Data Augmentation Technique Using a Saliency Map | Modern data augmentation strategies such as Cutout, Mixup, and CutMix, have achieved good performance in image recognition tasks. Particularly, the data augmentation approaches, such as Mixup and CutMix, that mix two images to generate a mixed training image, could generalize convolutional neural networks better than single image-based data augmentation approaches such as Cutout. We focus on the fact that the mixed image can improve generalization ability, and we wondered if it would be effective to apply it to a single image. Consequently, we propose a new data augmentation method to produce a self-mixed image based on a saliency map, called SalfMix. Furthermore, we combined SalfMix with state-of-the-art two images-based approaches, such as Mixup, SaliencyMix, and CutMix, to increase the performance, called HybridMix. The proposed SalfMix achieved better accuracies than Cutout, and HybridMix achieved state-of-the-art performance on three classification datasets: CIFAR-10, CIFAR-100, and TinyImageNet-200. Furthermore, HybridMix achieved the best accuracy in object detection tasks on the VOC dataset, in terms of mean average precision. | Choi, Jaehyeop; Lee, Chaehyeon; Lee, Donggyu; Jung, Heechul | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea | ; Lee, Chae Yeon/HHS-3863-2022; Jung, Heechul/HTL-7199-2023 | 57375161300; 57222731243; 57169003900; 55652175200 | jaebb95@knu.ac.kr;123456ccdd@knu.ac.kr;dglee@knu.ac.kr;heechul@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 24 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.81 | 2025-07-30 | 16 | 16 | deep learning; data augmentation; convolutional neural network (CNN); image classification | NETWORKS | Convolutional neural network (CNN); Data augmentation; Deep learning; Image classification | Neural Networks, Computer; Classification (of information); Convolution; Convolutional neural networks; Deep learning; Image enhancement; Image recognition; Image segmentation; Object detection; Augmentation techniques; Convolutional neural network; Data augmentation; Deep learning; Image-based; Images classification; Performance; Saliency map; Single images; article; convolutional neural network; deep learning; Image classification | English | 2021 | 2021-12 | 10.3390/s21248444 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Self-Organizing IoT Device-Based Smart Diagnosing Assistance System for Activities of Daily Living | Activity of daily living (ADL) is a criterion for evaluating the performance ability of daily life by recognizing various activity events occurring in real life. However, most of the data necessary for ADL evaluation are collected only through observation and questionnaire by the patient or the patient's caregiver. Recently, Internet of Things (IoT) device studies using various environmental sensors are being used for ADL collection and analysis. In this paper, we propose an IoT Device Platform for ADL capability measurement. Wearable devices and stationary devices recognize activity events in real environments and perform user identification through various sensors. The user's ADL data are sent to the network hub for analysis. The proposed IoT platform devices support many sensor devices such as acceleration, flame, temperature, and humidity in order to recognize various activities in real life. In addition, in this paper, using the implemented platform, ADL measurement test was performed on hospital patients. Through this test, the accuracy and reliability of the platform are analyzed. | Park, Yu Jin; Jung, Seol Young; Son, Tae Yong; Kang, Soon Ju | Kyungpook Natl Univ, Ctr Self Organizing Software, 80 Daehakro, Daegu 41566, South Korea; Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, 80 Daehakro, Daegu 41566, South Korea | 55494454700; 44061313100; 57192990931; 55666313900 | ilbsyjp@gmail.com;snowflower@ee.knu.ac.kr;pipikako@gmail.com;sjkang@ee.knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 3 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 0.29 | 2025-07-30 | 3 | 6 | activity of daily living; IoT device; home healthcare | MILD COGNITIVE IMPAIRMENT; CARE; HOME; DISABILITY; IMPACT | Activity of daily living; Home healthcare; IoT device | Acceleration; Activities of Daily Living; Caregivers; Humans; Reproducibility of Results; Wearable Electronic Devices; Diagnosis; Wearable sensors; Activities of Daily Living; Activity of daily livings; Assistance system; Environmental sensor; Internet of Things (IOT); Real environments; Stationary devices; User identification; acceleration; caregiver; daily life activity; electronic device; human; reproducibility; Internet of things | English | 2021 | 2021-02 | 10.3390/s21030785 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | The Extensive Usage of the Facial Image Threshing Machine for Facial Emotion Recognition Performance | Facial emotion recognition (FER) systems play a significant role in identifying driver emotions. Accurate facial emotion recognition of drivers in autonomous vehicles reduces road rage. However, training even the advanced FER model without proper datasets causes poor performance in real-time testing. FER system performance is heavily affected by the quality of datasets than the quality of the algorithms. To improve FER system performance for autonomous vehicles, we propose a facial image threshing (FIT) machine that uses advanced features of pre-trained facial recognition and training from the Xception algorithm. The FIT machine involved removing irrelevant facial images, collecting facial images, correcting misplacing face data, and merging original datasets on a massive scale, in addition to the data-augmentation technique. The final FER results of the proposed method improved the validation accuracy by 16.95% over the conventional approach with the FER 2013 dataset. The confusion matrix evaluation based on the unseen private dataset shows a 5% improvement over the original approach with the FER 2013 dataset to confirm the real-time testing. | Kim, Jung Hwan; Poulose, Alwin; Han, Dong Seog | Kyungpook Natl Univ, Sch Elect & Elect Engn, 80 Daehak Ro, Daegu 41566, South Korea | POULOSE, ALWIN/S-4914-2018; , ALWIN POULOSE/S-4914-2018; Han, Dong Seog/N-8949-2018 | 57222321332; 57205504085; 7403219442 | jkim267@knu.ac.kr;alwinpoulosepalatty@knu.ac.kr;dshan@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 6 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 3.98 | 2025-07-30 | 51 | 62 | facial emotion recognition (FER); autonomous driving; convolution neural network (CNN); Xception; ResNet; MTCNN; FER 2013 Dataset; CK plus Dataset | Autonomous driving; CK+ Dataset; Convolution neural network (CNN); Facial emotion recognition (FER); FER 2013 Dataset; MTCNN; ResNet; Xception | Algorithms; Emotions; Face; Facial Expression; Facial Recognition; Agriculture; Autonomous vehicles; Image enhancement; Speech recognition; Statistical tests; Confusion matrices; Conventional approach; Data augmentation; Facial emotions; Facial recognition; Poor performance; Real-time testing; Threshing machines; algorithm; diagnostic imaging; emotion; face; facial expression; facial recognition; Face recognition | English | 2021 | 2021-03 | 10.3390/s21062026 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Wind-Induced Pressure Prediction on Tall Buildings Using Generative Adversarial Imputation Network | Wind tunnel testing techniques are the main research tools for evaluating the wind loadings of buildings. They are significant in designing structurally safe and comfortable buildings. The wind tunnel pressure measurement technique using pressure sensors is significant for assessing the cladding pressures of buildings. However, some pressure sensors usually fail and cause loss of data, which are difficult to restore. In the literature, numerous techniques are implemented for imputing the single instance data values and data imputation for multiple instantaneous time intervals with accurate predictions needs to be addressed. Thus, the data imputation capacity of machine learning models is used to predict the missing wind pressure data for tall buildings in this study. A generative adversarial imputation network (GAIN) is proposed to predict the pressure coefficients at various instantaneous time intervals on tall buildings. The proposed model is validated by comparing the performance of GAIN with that of the K-nearest neighbor and multiple imputations by chained equation models. The experimental results show that the GAIN model provides the best fit, achieving more accurate predictions with the minimum average variance and minimum average standard deviation. The average mean-squared error for all four sides of the building was the minimum (0.016), and the average R-squared error was the maximum (0.961). The proposed model can ensure the health and prolonged existence of a structure based on wind environment. | Kim, Bubryur; Yuvaraj, N.; Sri Preethaa, K. R.; Hu, Gang; Lee, Dong-Eun | Dong A Univ, Dept Architectural Engn, Busan 49315, South Korea; Dong A Univ, Dept ICT Integrated Ocean Smart Cities Engn, Busan 49315, South Korea; KPR Inst Engn & Technol, Dept Artificial Intelligence & Data Sci, Coimbatore 641407, Tamil Nadu, India; Harbin Inst Technol, Sch Civil & Environm Engn, Shenzhen 518055, Peoples R China; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80 Daehak Ro, Daegu 41566, South Korea | HU, Gang/P-8189-2018; raj, yuva/GWV-2080-2022; Hu, Gang/P-8189-2018; Natarajan, Yuvaraj/GWV-2080-2022 | 57198355299; 57204528689; 57214320928; 56735061500; 56605563300 | rlaqjqfuf@dau.ac.kr;yuvaraj.n@kpriet.ac.in;k.r.sripreethaa@kpriet.ac.in;hugang@hit.edu.cn;dolee@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 21 | 7 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2021 | 3.847 | 28.9 | 1.4 | 2025-07-30 | 19 | 21 | wind-pressure coefficients; wind load; machine learning; data imputation; generative adversarial imputation network; tall building | Data imputation; Generative adversarial imputation network; Machine learning; Tall building; Wind load; Wind-pressure coefficients | Mean square error; Nearest neighbor search; Pressure measurement; Pressure sensors; Structural dynamics; Tall buildings; Testing; Wind stress; Wind tunnels; Accurate prediction; K-nearest neighbors; Machine learning models; Measurement techniques; Multiple imputation; Pressure coefficients; Pressure predictions; Wind-tunnel testing; Forecasting | English | 2021 | 2021-04 | 10.3390/s21072515 | 바로가기 | 바로가기 | 바로가기 | 바로가기 |
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