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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 | Orographic-Induced Strong Wind Associated With a Low-Pressure System Under Clear-Air Condition During ICE-POP 2018 | A strong wind event under clear-air conditions during the 2018 Winter Olympic and Paralympic games in Pyeongchang, Korea, was examined using various datasets. High spatiotemporal resolution wind information was obtained by Doppler lidars, automatic weather stations, wind profiler, sounding observations, reanalysis datasets under the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). This study aimed to understand the possible mechanisms of localized strong winds across a high mountainous area and on the leeside associated with the underlying large-scale pattern of a low-pressure system (LPS). The evolution of surface winds shows quite different patterns, exhibiting intensification of strong winds in the leeside and periodically persistent strong winds in upstream mountainous areas with the approaching LPS. The surface wind speed was intensified from similar to 3 to similar to 12 m s(-1) (gusts were stronger than 20 m s(-1) above the ground) at a surface station in the leeside. A budget analysis of the horizontal momentum equation suggested that the pressure gradient force (PGF) contributed from adiabatic warming and the passage of LPS was the main factor in the acceleration of the surface wind in the leeward side of the mountains. The detailed 3D winds revealed that the PGF also modulated the background winds at the mountainous station, which caused persistent strong and periodic winds (range of similar to 7 to similar to 12 m s(-1)) related to the channeling effect. The evidence showed that under the same synoptic condition of a LPS, different mechanisms are important for strong winds in determining the strength and persistence of orographic-induced strong winds under clear-air conditions. | Tsai, Chia-Lun; Kim, Kwonil; Liou, Yu-Chieng; Kim, Jung-Hoon; Lee, YongHee; Lee, GyuWon | Kyungpook Natl Univ, Dept Astron & Atmospher Sci, Ctr Atmospher REmote Sensing CARE, Daegu, South Korea; Natl Cent Univ, Dept Atmospher Sci, Jhongli, Taiwan; Seoul Natl Univ, Sch Earth & Environm Sci, Seoul, South Korea; Korea Meteorol Adm, Numer Modeling Ctr NMC, Seoul, South Korea | ; Kim, Jung-Hoon/M-9163-2017; Liou, Yu-Chieng/H-5178-2012; Tsai, Chia-Lun/AHI-4361-2022; Kim, Kwonil/HTN-0103-2023; Kim, Jung-Hoon/AEK-6080-2022 | 55474132500; 57191964318; 7102949463; 56813053700; 47962282400; 7404852271 | gyuwon@knu.ac.kr; | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES | J GEOPHYS RES-ATMOS | 2169-897X | 2169-8996 | 127 | 13 | SCIE | METEOROLOGY & ATMOSPHERIC SCIENCES | 2022 | 4.4 | 29.3 | 0.62 | 2025-06-25 | 7 | 6 | strong wind; clear-air; Doppler lidar; WISSDOM; pressure gradient force; channel effect | DOPPLER LIDAR OBSERVATIONS; DOWNSLOPE WINDSTORM; COMPLEX TERRAIN; SENSITIVITY EXPERIMENT; NUMERICAL SIMULATIONS; WEATHER RADAR; GAP FLOW; TURBULENCE; MODEL; TOPOGRAPHY | channel effect; clear-air; Doppler lidar; pressure gradient force; strong wind; WISSDOM | Air; Kangwon; Korea; Niger [West Africa]; Pyeongchang; South Korea; acceleration; Doppler lidar; equation; low pressure system; momentum; orography; pressure gradient; spatial resolution; surface wind | English | 2022 | 2022-07-16 | 10.1029/2021jd036418 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |
| ○ | Article | Penetrated surface characteristics of cement - mixed sand in powder bed 3D printing | Powder bed 3D printing is an additive manufacturing process that combines powder particles by selectively depositing a liquid activator on a powder bed. Sand molds for high-resolution casting can be realized as a high-quality green body via powder bed 3D printing. In this study, we investigated the effect of vertical penetration of aqueous droplets on the quality of the green body formed from a cement-mixed sand powder. The cement was hydrated by aqueous droplets and acted as a binder between the sand particles. The penetration ratio of the prepared powders was calculated from the penetration depth and spread diameter. Evidently, the penetration ratio and penetration resolution determined the strength and surface resolution of the green body. The results showed that an increase in the silica sand grain size led to a desirable penetration resolution with a relatively high green body strength at the same cement content. Additionally, the green body made from the sand with a particle size of 70 μm showed a relatively high green body strength and an excellent green body surface resolution even at 5% cement content, and it was determined that the green body strength and resolution depend on the penetration pattern. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of The Korean Ceramic Society and The Ceramic Society of Japan. | Chun, S.-Y.; Kim, T.; Ye, B.; Lee, M.-J.; Lee, G.; Jeong, B.; Lee, H.; Kim, H.-D. | Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea, Department of Energy Chemical Engineering, Kyungpook National University (KNU), Sangju, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea; Department of Material Science and Engineering, Pusan National University, Busan, South Korea; Industrial Environment Green Deal Agency, Korea Institute of Industrial Technology, Ulsan, South Korea | 57215651466; 57212837670; 57188965283; 57207730158; 57223329686; 56912891300; 55706794700; 35205685400 | hdkim@kitech.re.kr; | Journal of Asian Ceramic Societies | J ASIAN CERAM SOC | 2187-0764 | 2187-0764 | 10 | 2 | SCIE | MATERIALS SCIENCE, CERAMICS | 2022 | 2.3 | 29.3 | 0.34 | 2025-06-25 | 5 | calcium aluminate cement; green body; Powder bed 3D printing; vertical penetration | 3D printers; Calcium compounds; Cements; Drops; Particle size; Silica; Sodium Aluminate; 3-D printing; 3D-printing; Aqueous droplets; Body strength; Calcium-aluminate cement; Cement-mixed sands; Green body; Powder bed; Powder bed 3d printing; Vertical penetration; Silica sand | English | Final | 2022 | 10.1080/21870764.2021.2024734 | 바로가기 | 바로가기 | 바로가기 | |||||||
| ○ | ○ | Article | A Case Study of Quantizing Convolutional Neural Networks for Fast Disease Diagnosis on Portable Medical Devices | Recently, the amount of attention paid towards convolutional neural networks (CNN) in medical image analysis has rapidly increased since they can analyze and classify images faster and more accurately than human abilities. As a result, CNNs are becoming more popular and play a role as a supplementary assistant for healthcare professionals. Using the CNN on portable medical devices can enable a handy and accurate disease diagnosis. Unfortunately, however, the CNNs require high-performance computing resources as they involve a significant amount of computation to process big data. Thus, they are limited to being used on portable medical devices with limited computing resources. This paper discusses the network quantization techniques that reduce the size of CNN models and enable fast CNN inference with an energy-efficient CNN accelerator integrated into recent mobile processors. With extensive experiments, we show that the quantization technique reduces inference time by 97% on the mobile system integrating a CNN acceleration engine. | Garifulla, Mukhammed; Shin, Juncheol; Kim, Chanho; Kim, Won Hwa; Kim, Hye Jung; Kim, Jaeil; Hong, Seokin | Kyungpook Natl Univ, Sch Comp Sci Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Chilgok Hosp, Dept Radiol, Daegu 41404, South Korea; Sungkyunkwan Univ, Dept Semicond Syst Engn, Suwon 16419, South Korea | 57386911200; 58593023900; 57216946967; 36081886500; 57203506201; 57211615348; 55597086808 | seokin@skku.edu; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 1 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 1.71 | 2025-06-25 | 15 | 20 | deep neural network; quantization; point-of-care; neural processing unit | Deep neural network; Neural processing unit; Point-of-care; Quantization | Humans; Neural Networks, Computer; Convolution; Convolutional neural networks; Diagnosis; Energy efficiency; Medical imaging; Case-studies; Convolutional neural network; Disease diagnosis; Medical image analysis; Neural processing unit; Neural-processing; Point of care; Portable medical device; Processing units; Quantisation; human; Deep neural networks | English | 2022 | 2022-01 | 10.3390/s22010219 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | A Low-Complexity Algorithm for a Reinforcement Learning-Based Channel Estimator for MIMO Systems | This paper proposes a low-complexity algorithm for a reinforcement learning-based channel estimator for multiple-input multiple-output systems. The proposed channel estimator utilizes detected symbols to reduce the channel estimation error. However, the detected data symbols may include errors at the receiver owing to the characteristics of the wireless channels. Thus, the detected data symbols are selectively used as additional pilot symbols. To this end, a Markov decision process (MDP) problem is defined to optimize the selection of the detected data symbols. Subsequently, a reinforcement learning algorithm is developed to solve the MDP problem with computational efficiency. The developed algorithm derives the optimal policy in a closed form by introducing backup samples and data subblocks, to reduce latency and complexity. Simulations are conducted, and the results show that the proposed channel estimator significantly reduces the minimum-mean square error of the channel estimates, thus improving the block error rate compared to the conventional channel estimation. | Kim, Tae-Kyoung; Min, Moonsik | Gachon Univ, Dept Elect Engn, Seongnam 13120, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, 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 | 22 | 12 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.34 | 2025-06-25 | 3 | 4 | multiple-input multiple-output; channel estimation; Markov decision process; reinforcement learning | MASSIVE MIMO; TRACKING | channel estimation; Markov decision process; multiple-input multiple-output; reinforcement learning | Algorithms; Channel estimation; Computational complexity; Computational efficiency; Errors; Learning algorithms; Markov processes; Mean square error; MIMO systems; Reinforcement learning; Telecommunication repeaters; Channel estimator; Data symbols; Estimation errors; Low complexity algorithm; Markov Decision Processes; Multiple-Input Multiple- Output systems; Pilot symbols; Reinforcement learning algorithms; Reinforcement learnings; Wireless channel; algorithm; Feedback control | English | 2022 | 2022-06 | 10.3390/s22124379 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Review | A Review on the Trends in Event Detection by Analyzing Social Media Platforms' Data | Social media platforms have many users who share their thoughts and use these platforms to organize various events collectively. However, different upsetting incidents have occurred in recent years by taking advantage of social media, raising significant concerns. Therefore, considerable research has been carried out to detect any disturbing event and take appropriate measures. This review paper presents a thorough survey to acquire in-depth knowledge about the current research in this field and provide a guideline for future research. We systematically review 67 articles on event detection by sensing social media data from the last decade. We summarize their event detection techniques, tools, technologies, datasets, performance metrics, etc. The reviewed papers mainly address the detection of events, such as natural disasters, traffic, sports, real-time events, and some others. As these detected events can quickly provide an overview of the overall condition of the society, they can significantly help in scrutinizing events disrupting social security. We found that compatibility with different languages, spelling, and dialects is one of the vital challenges the event detection algorithms face. On the other hand, the event detection algorithms need to be robust to process different media, such as texts, images, videos, and locations. We outline that the event detection techniques compatible with heterogeneous data, language, and the platform are still missing. Moreover, the event and its location with a 24 x 7 real-time detection system will bolster the overall event detection performance. | Mredula, Motahara Sabah; Dey, Noyon; Rahman, Md. Sazzadur; Mahmud, Imtiaz; Cho, You-Ze | Jahangirnagar Univ, Inst Informat Technol, Savar 1342, Bangladesh; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | Mahmud, Imtiaz/R-1089-2019 | 57274281100; 57221113060; 59860333500; 56203487900; 7404469829 | mmredula12@gmail.com;noyondey8@gmail.com;sazzad@juniv.edu;imtiaz@knu.ac.kr;yzcho@ee.knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 12 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.58 | 2025-06-25 | 10 | 17 | deep machine learning; event detection; review; social sensing; shallow machine learning; social media | PARTICLE FILTERS; HEARTBEAT GRAPH; TWITTER; REPRESENTATION; NETWORK | deep machine learning; event detection; review; shallow machine learning; social media; social sensing | Algorithms; Humans; Natural Disasters; Social Media; Deep learning; Signal detection; Social networking (online); Deep machine learning; Event detection algorithm; Events detection; Machine-learning; Review papers; Shallow machine learning; Social media; Social media platforms; Social sensing; algorithm; human; natural disaster; social media; Disasters | English | 2022 | 2022-06 | 10.3390/s22124531 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | A Stacked Generalization Model to Enhance Prediction of Earthquake-Induced Soil Liquefaction | Earthquakes cause liquefaction, which disturbs the design phase during the building construction process. The potential of earthquake-induced liquefaction was estimated initially based on analytical and numerical methods. The conventional methods face problems in providing empirical formulations in the presence of uncertainties. Accordingly, machine learning (ML) algorithms were implemented to predict the liquefaction potential. Although the ML models perform well with the specific liquefaction dataset, they fail to produce accurate results when used on other datasets. This study proposes a stacked generalization model (SGM), constructed by aggregating algorithms with the best performances, such as the multilayer perceptron regressor (MLPR), support vector regression (SVR), and linear regressor, to build an efficient prediction model to estimate the potential of earthquake-induced liquefaction on settlements. The dataset from the Korean Geotechnical Information database system and the standard penetration test conducted on the 2016 Pohang earthquake in South Korea were used. The model performance was evaluated by using the R-2 score, mean-square error (MSE), standard deviation, covariance, and root-MSE. Model validation was performed to compare the performance of the proposed SGM with SVR and MLPR models. The proposed SGM yielded the best performance compared with those of the other base models. | Preethaa, Sri; Natarajan, Yuvaraj; Rathinakumar, Arun Pandian; Lee, Dong-Eun; Choi, Young; Park, Young-Jun; Yi, Chang-Yong | KPR Inst Engn & Technol, Dept Artificial Intelligence & Data Sci, Coimbatore 641665, Tamil Nadu, India; Kyungpook Natl Univ, Intelligent Construct Automat Ctr, 80 Daehak Ro, Daegu 41566, South Korea; QpiCloud Technol, Bangalore 560045, Karnataka, India; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80 Daehak Ro, Daegu 41566, South Korea; Earth Turbine, 36,Dongdeok Ro 40 Gil, Daegu 41905, South Korea | ; Natarajan, Yuvaraj/GWV-2080-2022; raj, yuva/GWV-2080-2022 | 57214320928; 57204528689; 57416033800; 56605563300; 58937691800; 57191258386; 36614886300 | py0307@knu.ac.kr;cyyi@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 19 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.43 | 2025-06-25 | 6 | 5 | liquefaction; prediction; machine learning; ensemble models; settlement; data augmentation | CPT | data augmentation; ensemble models; liquefaction; machine learning; prediction; settlement | Algorithms; Earthquakes; Machine Learning; Neural Networks, Computer; Soil; Earthquakes; Learning algorithms; Machine learning; Mean square error; Numerical methods; Soil liquefaction; Statistical tests; Building construction; Data augmentation; Design phase; Ensemble models; Machine-learning; Multilayers perceptrons; Performance; Settlement; Stacked generalization; Support vector regressions; article; covariance; earthquake; liquefaction; machine learning; multilayer perceptron; prediction; root mean squared error; soil; South Korea; support vector machine; Forecasting | English | 2022 | 2022-10 | 10.3390/s22197292 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Accurate Ship Detection Using Electro-Optical Image-Based Satellite on Enhanced Feature and Land Awareness | This paper proposes an algorithm that improves ship detection accuracy using preprocessing and post-processing. To achieve this, high-resolution electro-optical satellite images with a wide range of shape and texture information were considered. The developed algorithms display the problem of unreliable detection of ships owing to clouds, large waves, weather influences, and shadows from large terrains. False detections in land areas with image information similar to that of ships are observed frequently. Therefore, this study involves three algorithms: global feature enhancement pre-processing (GFEP), multiclass ship detector (MSD), and false detected ship exclusion by sea land segmentation image (FDSESI). First, GFEP enhances the image contrast of high-resolution electro-optical satellite images. Second, the MSD extracts many primary ship candidates. Third, falsely detected ships in the land region are excluded using the mask image that divides the sea and land. A series of experiments was performed using the proposed method on a database of 1984 images. The database includes five ship classes. Therefore, a method focused on improving the accuracy of various ships is proposed. The results show a mean average precision (mAP) improvement from 50.55% to 63.39% compared with other deep learning-based detection algorithms. | Lee, Sang-Heon; Park, Hae-Gwang; Kwon, Ki-Hoon; Kim, Byeong-Hak; Kim, Min Young; Jeong, Seung-Hyun | Kyungpook Natl Univ, Sch Elect Engn, Daegu 41566, South Korea; Korea Inst Ind Technol, Cheonan 31056, South Korea; Oceanlightai Co Ltd, Daegu 41260, South Korea; Res Ctr Neurosurg Robot Syst, Daegu 41566, South Korea; Korea Univ Technol & Educ, Sch Mechatron, Cheonan 31253, South Korea | 58001917000; 57226778835; 57190749004; 56406686400; 56739349100; 57219224526 | minykim@knu.ac.kr;sh.jeong@koreatech.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 23 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.68 | 2025-06-25 | 6 | 8 | convolution neural network; image enhancement; satellite photography; ship detection | SHAPE | convolution neural network; image enhancement; satellite photography; ship detection | Algorithms; Databases, Factual; Weather; Deep learning; Feature extraction; Geometrical optics; Image segmentation; Satellites; Ships; Textures; Convolution neural network; Electro-optical images; Electro-optical satellites; Feature enhancement; Global feature; High resolution; Optical satellite images; Pre-processing; Satellite photography; Ship detection; algorithm; factual database; weather; Image enhancement | English | 2022 | 2022-12 | 10.3390/s22239491 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | An Automated Image-Based Multivariant Concrete Defect Recognition Using a Convolutional Neural Network with an Integrated Pooling Module | Buildings and infrastructure in congested metropolitan areas are continuously deteriorating. Various structural flaws such as surface cracks, spalling, delamination, and other defects are found, and keep on progressing. Traditionally, the assessment and inspection is conducted by humans; however, due to human physiology, the assessment limits the accuracy of image evaluation, making it more subjective rather than objective. Thus, in this study, a multivariant defect recognition technique was developed to efficiently assess the various structural health issues of concrete. The image dataset used was comprised of 3650 different types of concrete defects, including surface cracks, delamination, spalling, and non-crack concretes. The proposed scheme of this paper is the development of an automated image-based concrete condition recognition technique to categorize, not only non-defective concrete into defective concrete, but also multivariant defects such as surface cracks, delamination, and spalling. The developed convolution-based model multivariant defect recognition neural network can recognize different types of defects on concretes. The trained model observed a 98.8% defect detection accuracy. In addition, the proposed system can promote the development of various defect detection and recognition methods, which can accelerate the evaluation of the conditions of existing structures. | Kim, Bubryur; Choi, Se-Woon; Hu, Gang; Lee, Dong-Eun; Juan, Ronnie O. Serfa | 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 | ; Hu, Gang/P-8189-2018; HU, Gang/P-8189-2018; Serfa Juan, Ronnie/I-1924-2018 | 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 | 22 | 9 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 1.11 | 2025-06-25 | 11 | 13 | concrete cracks; convolutional neural network; delamination; multivariant defects; spalling; surface crack | DATA AUGMENTATION; DAMAGE DETECTION; CRACK; RECONSTRUCTION | concrete cracks; convolutional neural network; delamination; multivariant defects; spalling; surface crack | Humans; Neural Networks, Computer; Recognition, Psychology; Concretes; Convolution; Crack detection; Physiology; Surface defects; Concrete cracks; Concrete defects; Convolutional neural network; Defect recognition; Human physiology; Image-based; Metropolitan area; Multivariant defect; Structural flaws; Surface cracks; human; Spalling | English | 2022 | 2022-05 | 10.3390/s22093118 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Analysis of LoRaWAN 1.0 and 1.1 Protocols Security Mechanisms | LoRaWAN is a low power wide area network (LPWAN) technology protocol introduced by the LoRa Alliance in 2015. It was designed for its namesake features: long range, low power, low data rate, and wide area networks. Over the years, several proposals on protocol specifications have addressed various challenges in LoRaWAN, focusing on its architecture and security issues. All of these specifications must coexist, giving rise to the compatibility issues impacting the sustainability of this technology. This paper studies the compatibility issues in LoRaWAN protocols. First, we detail the different protocol specifications already disclosed by the LoRa Alliance in two major versions, v1.0 and v1.1. This is done through presenting two scenarios where we discuss the communication and security mechanisms. In the first scenario, we describe how an end node (ED) and network server (NS) implementing LoRaWAN v1.0 generate session security keys and exchange messages for v1.0. In the second scenario, we describe how an ED v1.1 and an NS v1.1 communicate after generating security session keys. Next, we highlight the compatibility issues between the components implementing the two different LoRaWAN Specifications (mainly v1.0 and v1.1). Next, we present two new scenarios (scenarios 3 and 4) interchanging the ED and NS versions. In scenario three, we detail how an ED implementing LoRaWAN v1.1 communicates with an NS v1.0. Conversely, in scenario four, we explain how an ED v1.0 and an NS v1.1 communicate. In all these four scenarios, we highlight the concerns with security mechanism: show security session keys are generated and how integrity and confidentiality are guaranteed in LoRaWAN. At the end, we present a comparative table of these four compatibility scenarios. | Loukil, Slim; Fourati, Lamia Chaari; Nayyar, Anand; Chee, K. -W. -A. | Univ Sfax, Higher Inst Business Adm, Sfax 3018, Tunisia; ISIMS & SM RTS CRNS Lab Signals Syst ARtificial I, Sfax 3018, Tunisia; Duy Tan Univ, Grad Sch, Fac Informat Technol, Da Nang 550000, Vietnam; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Coll IT Engn, Daegu 41566, South Korea | loukil, slim/HPI-1405-2023; Nayyar, Anand/F-3732-2015; FOURATI, Lamia/AAQ-9134-2020 | 58743994800; 55819752700; 55201442200; 57524559900 | slimloukil@yahoo.fr;lamiachaari1@gmail.com;anandnayyar@duytan.edu.vn;aghjuee@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 10 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 1.11 | 2025-06-25 | 9 | 13 | Internet of Things; LoRaWAN; secure communication protocols; compatibility scenarios | INTERNET; PRIVACY; FUTURE | compatibility scenarios; Internet of Things; LoRaWAN; secure communication protocols | Computer Security; Confidentiality; Data Collection; Internet of things; Internet protocols; Low power electronics; Network architecture; Network security; Specifications; Compatibility scenario; LoRaWAN; Low Power; Network server; Protocol security; Protocol specifications; Secure communication protocols; Security mechanism; Session key; Wide-area networks; computer security; confidentiality; information processing; Wide area networks | English | 2022 | 2022-05 | 10.3390/s22103717 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Analysis of the Effect of Tillage Depth on the Working Performance of Tractor-Moldboard Plow System under Various Field Environments | The purpose of this study was to analyze the tillage depth effect on the tractor-moldboard plow systems in various soil environments and tillage depths using a field load measurement system. A field load measurement system can measure the engine load, draft force, travel speed, wheel axle load, and tillage depth in real-time. In addition, measurement tests of soil properties in the soil layer were preceded to analyze the effect of field environments. The presented results show that moldboard plow at the same tillage depth had a wide range of influences on the tractor's working load and performance under various environments. As the draft force due to soil-tool interaction occurred in the range of 5.6-17.7 kN depending on the field environment, the overall mean engine torque and rear axle torque were up to 2.14 times and 1.67 times higher in hard and clayey soil, respectively, than in soft soil environments. In addition, the results showed tractive efficiency of 0.56-0.73 and were analyzed to have a lugging ability of 67.8% with a 44% maximum torque rise. The engine power requirement in hardpan was similar within 3.6-9.6%, but the power demand of the rear axle differed by up to 18.4%. | Kim, Yeon-Soo; Lee, Sang-Dae; Baek, Seung-Min; Baek, Seung-Yun; Jeon, Hyeon-Ho; Lee, Jun-Ho; Kim, Wan-Soo; Shim, Jong-Yeal; Kim, Yong-Joo | Korea Inst Ind Technol KITECH, Smart Agr R&D Grp, Gimje 54325, South Korea; Chungnam Natl Univ, Dept Smart Agr Syst, Daejeon 34134, South Korea; Kyungpook Natl Univ, Dept Bioind Machinery Engn, Daegu 41566, South Korea; Fdn Agr Technol Commercializat & Transfer FACT, Agr Machinery Certificat Team, Iksan 54667, South Korea; Chungnam Natl Univ, Dept Biosyst Machinery Engn, Daejeon 34134, South Korea | ; Lee, JunHo/KII-0245-2024; Lee, Sang-Woong/ABF-6191-2020; Kim, Yong-Joo/AAK-1840-2021 | 57192923355; 59845799100; 57204040500; 57216612175; 57204036949; 57557580300; 57192918810; 57558878300; 57204759454 | kimtech612@kitech.re.kr;sdlee96@kitech.re.kr;bsm1104@naver.com;kelpie0037@gmail.com;jhh5888@naver.com;dlwnsgh211@naver.com;wansoo.kim@knu.ac.kr;tison21c@efact.or.kr;babina@cnu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 7 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 1.2 | 2025-06-25 | 13 | 15 | tillage depth; soil properties; moldboard plow; field load measurement system; agricultural tractor | DRAFT FORCE; AGRICULTURAL TRACTOR; GEAR SELECTION; WATER-CONTENT; WHEEL SLIP; PTO LOAD; SOIL; TRANSMISSION; MODEL; REQUIREMENTS | agricultural tractor; field load measurement system; moldboard plow; soil properties; tillage depth | Agriculture; Soil; Agriculture; Engines; Loads (forces); Soil testing; Soils; Tractors (truck); Depth effects; Draft force; Field load measurement system; Loads measurements; Measurement system; Moldboard plows; Soil environment; Soil property; Tillage depth; Working performance; agriculture; procedures; soil; Tractors (agricultural) | English | 2022 | 2022-04 | 10.3390/s22072750 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Analysis of the Response Characteristics of Toluene Gas Sensors with a ZnO Nanorod Structure by a Heat Treatment Process | The sensing characteristics of toluene gas are monitored by fabricating ZnO nanorod structures. ZnO nanostructured sensor materials are produced on a Zn film via an ultrasonic process in a 0.01 M aqueous solution of C6H12N4 and Zn(NO3)(2)center dot 6H(2)O. The response of the sensors subjected to heat treatment in oxygen and nitrogen atmospheres is improved by 20% and 10%, respectively. The improvement is considered to be correlated with the increase in grain size. The relationship between the heat treatment and sensing characteristics is evaluated. | Kwon, Dae-Hwan; Jin, Eui-Hyun; Yoo, Dae-Hwang; Roh, Jong-Wook; Suh, Dongjun; Commerell, Walter; Huh, Jeung-Soo | Korea Gas Safety Corp, Eumseong Gun 27738, Chungcheongbuk, South Korea; Kyungpook Natl Univ, Sch Convergence & Fus Syst Engn, 2559 Gyeongsang Daero, Sangju Si 37224, Gyeongsangbuk D, South Korea; Kyungpook Natl Univ, Inst Global Climate Change & Energy, Daegu 41566, South Korea; Kyungpook Natl Univ, Sch Nano & Mat Sci & Engn, 2559 Gyeongsang Daero, Sangju Si 37224, Gyeongsangbuk D, South Korea; TH Ulm, Eberhard Finckh Str 11, D-89075 Ulm, Germany | 57192931424; 57712918700; 7103242532; 25638796100; 36613529600; 56431049800; 7102258915 | chocopy@kgs.or.kr;eddiejins@naver.com;dhyoo@knu.ac.kr;jw.roh@knu.ac.kr;dongjunsuh@knu.ac.kr;walter.commerell@thu.de;jshuh@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 11 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.34 | 2025-06-25 | 5 | 4 | heat treatment; ZnO nanorod; metal oxide semiconductor gas sensor; toluene gas | MECHANISM; VOCS | heat treatment; metal oxide semiconductor gas sensor; toluene gas; ZnO nanorod | Hot Temperature; Nanostructures; Nanotubes; Toluene; Zinc Oxide; Chemical sensors; Gas detectors; Gases; Heat treatment; II-VI semiconductors; Magnetic semiconductors; Metals; MOS devices; Nanorods; Oxide semiconductors; Semiconducting zinc compounds; Wide band gap semiconductors; Zinc oxide; nanomaterial; nanotube; toluene; zinc oxide; Gas-sensors; Heat-treatment process; Metal oxide semiconductor gas sensors; Nanostructured sensors; Response characteristic; Sensing characteristics; Sensor materials; Toluene gas; Ultrasonic process; ZnO nanorod; chemistry; heat; Toluene | English | 2022 | 2022-06 | 10.3390/s22114125 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Automatic Recognition of Road Damage Based on Lightweight Attentional Convolutional Neural Network | An efficient road damage detection system can reduce the risk of road defects to motorists and road maintenance costs to traffic management authorities, for which a lightweight end-to-end road damage detection network is proposed in this paper, aiming at fast and automatic accurate identification and classification of multiple types of road damage. The proposed technique consists of a backbone network based on a combination of lightweight feature detection modules constituted with a multi-scale feature fusion network, which is more beneficial for target identification and classification at different distances and angles than other studies. An embedded lightweight attention module was also developed that can enhance feature information by assigning weights to multi-scale convolutional kernels to improve detection accuracy with fewer parameters. The proposed model generally has higher performance and fewer parameters than other representative models. According to our practice tests, it can identify many types of road damage based on the images captured by vehicle cameras and meet the real-time detection required when piggybacking on mobile systems. | Liang, Han; Lee, Seong-Cheol; Seo, Suyoung | Kyungpook Natl Univ, Dept Civil Engn, Daegu 37224, South Korea | Liang, Han/HPC-7877-2023; Seo, Suyoung/AAB-8465-2020 | 57222620902; 35784449900; 35198914000 | seonglee@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 24 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 1.11 | 2025-06-25 | 9 | 15 | object detection; lightweight network; attention mechanism; road damage; computer vision | POTHOLES | attention mechanism; computer vision; lightweight network; object detection; road damage | Algorithms; Neural Networks, Computer; Recognition, Psychology; Spine; Automobile drivers; Computer vision; Convolution; Damage detection; Feature extraction; Highway administration; Real time systems; Roads and streets; Attention mechanisms; Automatic recognition; Convolutional neural network; Damage detection systems; Lightweight network; Maintenance cost; Objects detection; Road damage; Road maintenance; Traffic management; algorithm; spine; Object detection | English | 2022 | 2022-12 | 10.3390/s22249599 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Characterization of English Braille Patterns Using Automated Tools and RICA Based Feature Extraction Methods | Braille is used as a mode of communication all over the world. Technological advancements are transforming the way Braille is read and written. This study developed an English Braille pattern identification system using robust machine learning techniques using the English Braille Grade-1 dataset. English Braille Grade-1 dataset was collected using a touchscreen device from visually impaired students of the National Special Education School Muzaffarabad. For better visualization, the dataset was divided into two classes as class 1 (1-13) (a-m) and class 2 (14-26) (n-z) using 26 Braille English characters. A position-free braille text entry method was used to generate synthetic data. N = 2512 cases were included in the final dataset. Support Vector Machine (SVM), Decision Trees (DT) and K-Nearest Neighbor (KNN) with Reconstruction Independent Component Analysis (RICA) and PCA-based feature extraction methods were used for Braille to English character recognition. Compared to PCA, Random Forest (RF) algorithm and Sequential methods, better results were achieved using the RICA-based feature extraction method. The evaluation metrics used were the True Positive Rate (TPR), True Negative Rate (TNR), Positive Predictive Value (PPV), Negative Predictive Value (NPV), False Positive Rate (FPR), Total Accuracy, Area Under the Receiver Operating Curve (AUC) and F1-Score. A statistical test was also performed to justify the significance of the results. | Shokat, Sana; Riaz, Rabia; Rizvi, Sanam Shahla; Khan, Inayat; Paul, Anand | Univ Azad Jammu & Kashmir, Dept Comp Sci & IT, Muzaffarabad 13100, Pakistan; Raptor Interact Pty Ltd, Eco Blvd,Witch Hazel Ave, ZA-0157 Centurion, South Africa; Univ Buner, Dept Comp Sci, Buner 19290, Pakistan; Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea | Khan, Inayat/AAZ-2156-2020; Riaz, Rabia/HJI-6429-2023; Rizvi, Sanam Shahla/GQQ-8390-2022; shokat, sana/AAV-4754-2020; Paul, Anand/V-6724-2017 | 57188872438; 24475180100; 25927493500; 57189853778; 56650522400 | snagul@yahoo.com;rabiaiqbal18@gmail.com;sanam_shahla@hotmail.com;inayat_khan@uop.edu.pk;paul.editor@gmail.com; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 5 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.6 | 2025-06-25 | 6 | 7 | machine learning; RICA features; PCA features; Braille patterns; visually impaired; SVM; KNN; Decision Tree; text conversion | TEXT ENTRY METHOD; TRANSLATION; MACHINE | Braille patterns; Decision Tree; KNN; Machine learning; PCA features; RICA features; SVM; Text conversion; Visually impaired | Algorithms; Humans; Machine Learning; Predictive Value of Tests; Reading; Support Vector Machine; Character recognition; Extraction; Feature extraction; Independent component analysis; Principal component analysis; Support vector machines; Braille pattern; Feature extraction methods; Independent components analysis; K‐ near neighbor; Nearest-neighbour; PCA feature; Reconstruction independent component analyse feature; Support vectors machine; Text conversion; Visually impaired; algorithm; human; machine learning; predictive value; reading; support vector machine; Decision trees | English | 2022 | 2022-03 | 10.3390/s22051836 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Compact Dual Circularly-Polarized Quad-Element MIMO/Diversity Antenna for Sub-6 GHz Communication Systems | In this paper, a compact dual circularly-polarized (CP) planar multiple-input-multiple-output (MIMO) antenna is presented for a sub-6 GHz frequency band. The antenna consists of four identical resonating elements, which are placed in a mirrored-image pattern to obtain polarization diversity. Element 2 is a mirror image of element 1, and elements 3 and 4 are mirror images of elements 1 and 2. Each antenna element comprises an elliptical resonator, a 50-ohm microstrip feed line, and a rectangular stub integrated with the feed to increase the surface current path of the antenna, shifting the resonating frequency to the lower side. Additionally, the rectangular stub is lengthened towards the right side (along the +x-axis direction in the antenna element 1), which balances the magnitude and 90 degrees phase variance among the horizontal (E-x) and vertical (E-y) fields. The proposed MIMO antenna supports both types of circular polarization, where radiators 1 and 3 radiate right-hand CP (RHCP) rays and radiators 2 and 4 radiate left-hand CP (LHCP) rays. Developing a compact-size MIMO antenna is a challenging task, especially when the antenna elements share the same ground plane and are placed less than half a wavelength apart. The mutual coupling in the proposed antenna is reduced by increasing the spacing between the elements without the use of any extra decoupling structure. Optimal spacing is maintained to achieve compact geometry with less inter-element correlation. The radiators are closely placed with an edge-to-edge spacing of 0.08 lambda(0), where lambda(0) is the free space wavelength at 3.6 GHz. A peak gain of 5 dBi, efficiency of 90%, an envelope correlation coefficient (ECC) of less than 0.1, and isolation of more than 18 dB are obtained between different ports of the prototype antenna. The overall size of the antenna element is 17 mm x 17 mm x 1.6 mm, and the MIMO antenna is 40 mm x 40 mm x 1.6 mm. | Kumar, Sachin; Palaniswamy, Sandeep Kumar; Choi, Hyun Chul; Kim, Kang Wook | SRM Inst Sci & Technol, Dept Elect & Commun Engn, Kattankulathur 603203, India; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | PALANISWAMY, SANDEEP KUMAR/AAF-2240-2021; Kumar, Sachin/W-2211-2019 | 56907994000; 56158830800; 57193342681; 57204432422 | kang_kim@ee.knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 22 | 24 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.85 | 2025-06-25 | 7 | 11 | 5G; circularly-polarized; compact; diversity; isolation; MIMO; sub-6 GHz band | MIMO ANTENNA; PERFORMANCE; DIVERSITY; INPUT | 5G; circularly-polarized; compact; diversity; isolation; MIMO; sub-6 GHz band | 5G mobile communication systems; Antenna feeders; Antenna grounds; Circular polarization; Microwave antennas; MIMO systems; Radiators; Slot antennas; Structural optimization; 5g; Circularly-polarized; Compact; Diversity; GHz band; Isolation; Multiple inputs; Multiple outputs; Multiple-input-multiple-output; Sub-6 GHz band; Mirrors | English | 2022 | 2022-12 | 10.3390/s22249827 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | Article | Comparison of Characteristics of a ZnO Gas Sensor Using a Low-Dimensional Carbon Allotrope | Owing to the increasing construction of new buildings, the increase in the emission of formaldehyde and volatile organic compounds, which are emitted as indoor air pollutants, is causing adverse effects on the human body, including life-threatening diseases such as cancer. A gas sensor was fabricated and used to measure and monitor this phenomenon. An alumina substrate with Au, Pt, and Zn layers formed on the electrode was used for the gas sensor fabrication, which was then classified into two types, A and B, representing the graphene spin coating before and after the heat treatment, respectively. Ultrasonication was performed in a 0.01 M aqueous solution, and the variation in the sensing accuracy of the target gas with the operating temperature and conditions was investigated. As a result, compared to the ZnO sensor showing excellent sensing characteristics at 350 °C, it exhibited excellent sensing characteristics even at a low temperature of 150 °C, 200 °C, and 250 °C. | Lee, Jihoon; Park, Jaebum; Huh, Jeung-Soo | Department of Convergence and Fusion System Engineering, Institute of Global Climate Change and Energy, Kyungpook National University, 41566, Daegu, South Korea; Department of Convergence and Fusion System Engineering, Institute of Global Climate Change and Energy, Kyungpook National University, 41566, Daegu, South Korea; Department of Energy Convergence and Climate Change, Kyungpook National University, 41566, Daegu, South Korea | 59832369300; 57237034300; 7102258915 | Sensors (Basel, Switzerland) | SENSORS-BASEL | N/A | 1424-8220 | 23 | 1 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2022 | 3.9 | 29.4 | 0.09 | 2025-06-25 | 1 | carbonnanotube; formaldehyde; gas sensor; graphene; ZnO | Air Pollutants; Aluminum Oxide; Carbon; Graphite; Humans; Zinc Oxide; aluminum oxide; carbon; graphite; zinc oxide; air pollutant; human | English | Final | 2022 | 10.3390/s23010052 | 바로가기 | 바로가기 | 바로가기 |
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