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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 | Hybrid-driven-based resilient control for networked T-S fuzzy systems with time-delay and cyber-attacks | This work investigates design problem of the hybrid-triggered-based resilient controller for a class of Takagi-Sugeno (T-S) fuzzy systems subject to nondeterministic cyber-attacks, probabilistic time-delay, controller gain variations and actuator failures in which nondeterministic cyber-attacks and hybrid-triggered mechanism are implemented by probabilistic variables gratifying the Bernoulli distributions. To save the network resources, a new kind of hybrid-triggered-based resilient controller design is introduced. By employing Lyapunov technique together with improved Wirtinger's integral inequalities and event-generator function, new delay-dependent sufficient conditions are constructed which assures that the resulting closed-loop system is mean square asymptotically stable and satisfies a prescribed performance. At last, two numerical examples are provided to display the effectiveness and advantage of the constructed method. | Saravanakumar, T.; Lee, Tae H. | Jeonbuk Natl Univ, Div Elect Engn, Jeonju, South Korea; Kyungpook Natl Univ, Dept Elect Engn, Daegu, South Korea; Jeonbuk Natl Univ, Div Elect Engn, 567 Baekje Daero, Jeonju 54896, South Korea | Thangavel, Saravanakumar/JXN-6649-2024; Lee, TaeHee/I-3043-2019 | 56716219500; 56678696600 | fesuselee@gmail.com; | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | INT J ROBUST NONLIN | 1049-8923 | 1099-1239 | 33 | 13 | SCIE | AUTOMATION & CONTROL SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;MATHEMATICS, APPLIED | 2023 | 3.2 | 4.1 | 1.9 | 2025-06-25 | 16 | 15 | hybrid-triggered scheme; networked control systems; nondeterministic cyber-attacks; resilient control design; T-S fuzzy systems | INFINITY FILTER DESIGN; FAULT-TOLERANT CONTROL; STABILITY CONDITIONS; TRIGGERED CONTROL; SUBJECT | hybrid-triggered scheme; networked control systems; nondeterministic cyber-attacks; resilient control design; T-S fuzzy systems | Closed loop systems; Computer crime; Controllers; Crime; Cyber attacks; Delay control systems; Fuzzy systems; Network security; Numerical methods; Probability distributions; Time delay; Control design; Cyber-attacks; Hybrid-driven; Hybrid-triggered scheme; Nondeterministic cybe-attack; Probabilistics; Resilient control; Resilient control design; Resilient controller; Takagi Sugeno fuzzy systems; Networked control systems | English | 2023 | 2023-09-10 | 10.1002/rnc.6801 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |
| ○ | ○ | Article | Laser-Responsive Shape Memory Device to Program the Stepwise Control of Intraocular Pressure in Glaucoma | There is an unmet need in the glaucoma clinic to control changes in the intraocular pressure (IOP), i.e., patient-specific hypotony and tissue fibrosis-mediated ocular hypertension, owing to the fixed tube diameter of the glaucoma drainage device. As a potential solution, the tube diameter can be adjusted, depending on the IOP, by shape memory polymer (SMP) and clinical laser systems, which can control the energy level, focus, and frequency by minimizing untargeted influences. To develop a translatable device, a laser-responsive SMP with two additional elements: i) a tube with an intimal gel coating to release 5-fluorouracil as an anti-fibrotic drug and ii) a safety lock ring to block late hypotony in special cases is employed. When the SMP tube is inserted into a silicone tube and wrapped externally by the ring, intimal gel degradation and argon laser-triggered diameter increase enable a three-step IOP control. Sustained drug release of the intimal gel suppresses tissue fibrosis, and the ring prevents late hypotony by externally squeezing the silicone tube. The advanced design and functions are validated using computational in vitro and rabbit glaucoma models by determining clinic-friendly argon laser parameters. | Lee, Kyubae; Choi, Wungrak; Kim, Si Yeong; Lee, Eon-Bee; Oh, Won Take; Park, Jeongeun; Lee, Chan Hee; Lee, Jihei Sara; Bae, Hyoung Won; Jang, Dong-Su; Lee, Kang Suk; Yi, Se Won; Kang, Mi-Lan; Kim, Chan Yun; Sung, Hak-Joon | Yonsei Univ, Dept Med Engn, Coll Med, 50-1 Yonsei Ro, Seoul 03722, South Korea; Yonsei Univ, Inst Vis Res, Dept Ophthalmol, Coll Med, 50-1 Yonsei Ro, Seoul 03722, South Korea; Kyungpook Natl Univ, Coll Vet Med, Lab Vet Pharmacokinet & Pharmacodynam, Daegu 41566, South Korea; Yonsei Univ, Off Res Affairs, Coll Med, 50-1 Yonsei Ro, Seoul 03722, South Korea; TMD LAB Co Ltd, 6th Floor,31 Gwangnaru Ro 8 Gil, Seoul 04799, South Korea | Lee, Jung Bok/HHZ-3200-2022; Kim, Jin-Soo/AAF-3359-2019; Park, Jeongeun/KDN-4631-2024; Lee, Kyubae/IXN-5539-2023; Lee, Jeong-Hoon/Q-1055-2018 | 57211256250; 56523796300; 57226930200; 57216526135; 57931489200; 57227115100; 57409275700; 57196009488; 57284234000; 57203079162; 58085739100; 57211926086; 57199380136; 23481971700; 7201871300 | kcyeye@yuhs.ac;hj72sung@yuhs.ac; | ADVANCED FUNCTIONAL MATERIALS | ADV FUNCT MATER | 1616-301X | 1616-3028 | 33 | 35 | SCIE | CHEMISTRY, MULTIDISCIPLINARY;CHEMISTRY, PHYSICAL;MATERIALS SCIENCE, MULTIDISCIPLINARY;NANOSCIENCE & NANOTECHNOLOGY;PHYSICS, APPLIED;PHYSICS, CONDENSED MATTER | 2023 | 18.5 | 4.1 | 0.64 | 2025-06-25 | 5 | 6 | anti-fibrotic drug release; clinician-specified control of intraocular pressure; computational fluid dynamics modeling; glaucoma; laser-responsive shape memory polymers | DRUG-DELIVERY; NANOPARTICLES; POLYMER; FORMULATION; CARRIERS; HYPOTONY; RELEASE | anti-fibrotic drug release; clinician-specified control of intraocular pressure; computational fluid dynamics modeling; glaucoma; laser-responsive shape memory polymers | Drug products; Laser safety; Ophthalmology; Polyols; Silicones; Targeted drug delivery; Tissue; Tubes (components); Anti-fibrotic drug release; Clinician-specified control of intraocular pressure; Computational fluid dynamics modeling; Drug release; Glaucoma; Intraocular pressure; Laser-responsive shape memory polymer; Shape memory polymers; Shape-memory; Tube diameters; Controlled drug delivery | English | 2023 | 2023-08 | 10.1002/adfm.202300264 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |
| ○ | ○ | Article | Stability analysis and fault detection filter design for discrete-time switched systems with all modes unstable | In this article, we investigate the stabilization and fault detection problem for discrete-time switched systems with all modes unstable. A set of mode-dependent fault detection filters are designed with respect to each subsystem and combined with the switched system into an augmented switched system. Sufficient conditions for both guaranteeing globally uniformly asymptotically stable (GUAS) and H-/H infinity$$ {H}-/{H}\ᵢₙfₜy $$ performance of the augmented switched system are derived by utilizing the discretized Lyapunov function technique and dwell time (DT) switching strategy. A novel pair of the residual evaluation function and threshold function are also provided for improving the sensitivity and practicability of fault detection logic. Numerical experiments demonstrate the effectiveness of the proposedmethod. | Huang, Jinjie; Hao, Xianzhi; Yang, Jung-Min | Harbin Univ Sci & Technol, Sch Comp Sci & Technol, Harbin, Peoples R China; Heilongjiang Prov Key Lab Complex Intelligent Syst, Harbin, Peoples R China; Harbin Univ Sci & Technol, Sch Automat, Harbin, Peoples R China; Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea; Kyungpook Natl Univ, Sch Elect Engn, 80 Daehakro, Daegu 41566, South Korea | 15069583900; 57209826326; 57208450551 | jmyang@knu.ac.kr; | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | INT J ROBUST NONLIN | 1049-8923 | 1099-1239 | 33 | 12 | SCIE | AUTOMATION & CONTROL SYSTEMS;ENGINEERING, ELECTRICAL & ELECTRONIC;MATHEMATICS, APPLIED | 2023 | 3.2 | 4.1 | 0.63 | 2025-06-25 | 4 | 5 | fault detection; residual evaluation function; switched systems; threshold function; unstable modes | STABILIZATION | fault detection; residual evaluation function; switched systems; threshold function; unstable modes | Fault detection; Function evaluation; Numerical methods; Analysis detection; Discrete-time switched system; Evaluation function; Fault detection filters; Faults detection; Residual evaluation function; Stability analyze; Switched system; Threshold functions; Unstable modes; Lyapunov functions | English | 2023 | 2023-08 | 10.1002/rnc.6726 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | The animal protein hydrolysate attenuates sarcopenia via the muscle-gut axis in aged mice | Age-related muscle loss and dysfunction, sarcopenia, is a common condition that results in poor quality of life in the elderly. Protein supplementation is a potential strategy for preventing sarcopenia and increasing muscle synthesis, but the effectiveness of protein type and level in improving sarcopenia is not well understood. In this study, we compared animal protein hydrolysate (APH), which has a high protein digestibility-corrected amino acid score (PDCAAS) and low molecular weight, with casein as a control group to investigate the effects and mechanisms of sarcopenia improvement, with a particular focus on the gut-muscle axis. APH supplementation improved age-related declines in muscle mass, grip strength, hind leg thickness, muscle protein level, muscle fiber size, and myokine levels, compared to the control group. In particular, levels of plasma cortisol, muscle lipids, and muscle collagen were markedly reduced by APH supplements in the aged mice. Furthermore, APH efficiently recovered the concentration of total SCFAs including acetic, propionic, and isovaleric acids decreased in aged mice. Finally, APH induced changes in gut microbiota and increased production of SCFAs, which were positively correlated with muscle protein level and negatively correlated with pro-inflammatory cytokines. In conclusion, APH can help to inhibit age-related sarcopenia by increasing muscle synthesis, inhibiting muscle breakdown, and potentially modulating the gut-muscle axis. | Lee, Ji-Yoon; Shin, Su-Kyung; Bae, Heekyong R.; Ji, Yosep; Park, Hae-Jin; Kwon, Eun-Young | Kyungpook Natl Univ, Dept Food Sci & Nutr, 80 Daehak ro, Daegu 41566, South Korea; Kyungpook Natl Univ, Ctr Food & Nutr Genom Res, 80 Daehak ro, Daegu 41566, South Korea; HEM Pharm, Changnyong daero, Suwon 16229, Gyeonggi Do, South Korea; Daegu Haany Univ, Bio Convergence Testing Ctr, 1 Haanydaero, Gyongsan 38610, Gyeongsangbug D, South Korea; Kyungpook Natl Univ, Ctr Beautiful Aging, 1370 San Kyuk, Daegu 41566, South Korea | Lee, Ji-Yoon/HLP-4514-2023 | 58631087000; 23988149900; 57191253762; 37761601000; 7601569369; 15765422500 | hjpark@dhu.ac.kr;eykwon@knu.ac.kr; | BIOMEDICINE & PHARMACOTHERAPY | BIOMED PHARMACOTHER | 0753-3322 | 1950-6007 | 167 | SCIE | MEDICINE, RESEARCH & EXPERIMENTAL;PHARMACOLOGY & PHARMACY | 2023 | 6.9 | 4.1 | 1.22 | 2025-06-25 | 7 | 7 | Animal protein hydrolysate (APH); Sarcopenia; Gut microbiota; Short -chain fatty acids; Muscle -gut axis; Aging | DIETARY-PROTEIN; UREA CYCLE; AMMONIA METABOLISM; OLDER PERSONS; INFLAMMATION; MASS; BIOSYNTHESIS; STRENGTH; QUALITY | Aging; Animal protein hydrolysate (APH); Gut microbiota; Muscle-gut axis; Sarcopenia; Short-chain fatty acids | Aged; Animals; Humans; Mice; Muscle Proteins; Muscle, Skeletal; Protein Hydrolysates; Quality of Life; Sarcopenia; acetic acid; amino acid; animal protein; casein; collagen; cytokine; isovaleric acid; lipid; propionic acid; short chain fatty acid; muscle protein; protein hydrolysate; age; aged; animal experiment; animal model; animal tissue; Article; controlled study; digestion; grip strength; hydrocortisone blood level; hydrolysis; intestine flora; male; molecular weight; mouse; muscle level; muscle mass; nonhuman; protein synthesis; sarcopenia; skeletal muscle cell; animal; human; metabolism; quality of life; sarcopenia; skeletal muscle | English | 2023 | 2023-11 | 10.1016/j.biopha.2023.115604 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Ultra-Fast Photonic Digital Polymerase Chain Reaction based on N-Heterocyclic Carbene Self-Assembled Monolayer | A molecular diagnosis of the respiratory syncytial virus (RSV) without bulky and expensive instrumentation is of great importance for the early detection and prevention in a fast-spreading pandemic. However, the current representative diagnostic methods have the limitation of being time-consuming, cost, the processing time for polymerase chain reaction (PCR), and inaccurate for lateral flow assay (LFA), representatively. Herein, an integrated photonic digital PCR (dPCR) is developed with high-velocity photonic scanner for in situ fluorescence detection by introducing the N-heterocyclic carbene self-assembled monolayer-based Au film to prevent the quenching effect. The on-site rapid molecular diagnostic platform shows the driving of 40 cycles in under 8 min and fluorescence scanning in under 7 min, resulting in a total analysis time within 15 min. In particular, the technology clearly demonstrates the classification of SARS-CoV-2 patients and healthy controls (99% in sensitivity, 98.6% in specificity, and 96.4% in accuracy with RdRp gene), comparing with standard RT-qPCR. This platform can be utilized for prompt point-of-care molecular diagnostics in early diagnosis and large-scale prevention of next pandemic spreading for upcoming infectious diseases and for the distinction diagnosis with other RSV. | Kim, Kyung Ho; Seo, Sung Eun; Kim, Jinyeong; Park, Seon Joo; An, Jai Eun; Shin, Chan Jae; Ryu, Choong-Min; Lee, Sung Woon; Nam, Ho Chul; Yoon, Tae Ho; Shin, Jong Cheol; Kim, Yu Kyung; Oh, Hanseul; Hong, Jung Joo; Kim, Brian N.; Lee, Kyoung G.; Song, Hyun Seok; Lee, Sang Hun; Kwon, Oh Seok | Korea Res Inst Biosci & Biotechnol KRIBB, Infect Dis Res Ctr, Daejeon 34141, South Korea; Korea Res Inst Biosci & Biotechnol KRIBB, Immunotherapy Res Ctr, Daejeon 34141, South Korea; Sungkyunkwan Univ SKKU, SKKU Adv Inst Nanotechnol SAINT, Dept Nano Engn, Suwon 16419, South Korea; Korea Univ Sci & Technol UST, Sch Biosci, Korea Res Inst Biosci & Biotechnol KRIBB, Daejeon 34113, South Korea; RevoSketch Inc, 506 1662 YuSeong daero, Daejeon 34054, South Korea; Kyungpook Natl Univ, Sch Med, Dept Clin Pathol, Daegu 41944, South Korea; Chungbuk Natl Univ, Coll Vet Med, Cheongju 28644, Chungcheongbuk, South Korea; Korea Res Inst Biosci & Biotechnol KRIBB, Natl Primate Res Ctr, Cheongju 28116, Chungcheongbuk, South Korea; Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL USA; Ctr Nano Bio Dev Natl NanoFab Ctr, 291 Daehak ro, Daejeon 34141, South Korea; Korea Inst Sci & Technol, Sensor Syst Res Ctr, Seoul 02792, South Korea; Hanbat Natl Univ, Dept Chemcial & Biol Engn, Daejeon 34158, South Korea | ; Kim, Kyung Ho/GPK-5175-2022; Shin, Chan Jae/MCX-9369-2025 | 57226848520; 57208651527; 57207438329; 36165743800; 57235640400; 58087021500; 7101906863; 58284390000; 57201664580; 58283589000; 58283910700; 59679525600; 56683810800; 36808240600; 53881377000; 57208732163; 58168289300; 58884841400; 7402195808 | doublekh0119@kribb.re.kr;sanghunlee@hanbat.ac.kr;oskwon79@skku.edu; | ADVANCED FUNCTIONAL MATERIALS | ADV FUNCT MATER | 1616-301X | 1616-3028 | 33 | 37 | SCIE | CHEMISTRY, MULTIDISCIPLINARY;CHEMISTRY, PHYSICAL;MATERIALS SCIENCE, MULTIDISCIPLINARY;NANOSCIENCE & NANOTECHNOLOGY;PHYSICS, APPLIED;PHYSICS, CONDENSED MATTER | 2023 | 18.5 | 4.1 | 0.96 | 2025-06-25 | 3 | 9 | carbene chemistry; dPCR; PoCT; portable devices; respiratory syncytial virus | GOLD; FUNCTIONALIZATION | carbene chemistry; dPCR; PoCT; portable devices; respiratory syncytial virus | Diagnosis; Diseases; Fluorescence; Molecular biology; Self assembled monolayers; Viruses; 'current; Carbene chemistry; Digital PCR; Molecular diagnosis; Molecular diagnostics; N-heterocyclic carbenes; PoCT; Portable device; Respiratory syncytial virus; Ultra-fast photonics; Polymerase chain reaction | English | 2023 | 2023-09-12 | 10.1002/adfm.202303728 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |
| ○ | Article | Unpredictably Disordered Distribution of Hetero-Blended Graphene Oxide Flakes with Non-Identical Resistance in Physical Unclonable Functions | In this study, a new concept of physical unclonable functions (PUFs) is introduced comprising reduced graphene oxide (GO) materials. To create a disordered conductivity distribution, two types of GO are used: HGO, are produced by the conventional Hummers’ method, and PGO, produced by Brodie's method with an additional unique purification procedure. It is found that PGO becomes graphene-like after room-temperature chemical reduction. These two reduced GOs have a distinct conductivity difference of up to 104 times. By blending these two materials, a random mixture is created that can generate a highly unpredictable electrical signal, serving as an ideal security key with strong randomness and uniqueness. The optimized PUF device, based on this approach, demonstrates excellent performance in generating secure keys. © 2023 Wiley-VCH GmbH. | Lee, Subin; Choi, Seon Yeon; Jang, Byung Chul; Lee, Dong Hyun; Cho, Joon Young; Han, Joong Tark; Yoo, Hocheon; Kim, Hyun Ho | Department of Electronic Engineering Gachon University, 1342 Seongnam-daero, Seongnam, 13120, South Korea; Department of Energy Engineering Convergence & School of Materials Science and Engineering, Kumoh National Institute of Technology, 61 Daehakro, Gumi, 39177, South Korea; School of Electronics Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu, 41566, South Korea, School of Electronics and Electrical Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu, 41566, South Korea; Department of Electronic Engineering Gachon University, 1342 Seongnam-daero, Seongnam, 13120, South Korea; Nano Hybrid Technology Research Center, Korea Electrotechnology Research Institute (KERI), 12, Jeongiui-gil, Seongsan-gu, Changwon, 51543, South Korea; Nano Hybrid Technology Research Center, Korea Electrotechnology Research Institute (KERI), 12, Jeongiui-gil, Seongsan-gu, Changwon, 51543, South Korea; Department of Electronic Engineering Gachon University, 1342 Seongnam-daero, Seongnam, 13120, South Korea; Department of Energy Engineering Convergence & School of Materials Science and Engineering, Kumoh National Institute of Technology, 61 Daehakro, Gumi, 39177, South Korea | 57252680900; 58515326700; 9238827900; 57347247700; 57193489420; 8600333500; 56637576900; 55808014500 | hyoo@gachon.ac.kr;kimhh@kumoh.ac.kr; | Advanced Functional Materials | ADV FUNCT MATER | 1616-301X | 1616-3028 | 33 | 48 | SCIE | CHEMISTRY, MULTIDISCIPLINARY;CHEMISTRY, PHYSICAL;MATERIALS SCIENCE, MULTIDISCIPLINARY;NANOSCIENCE & NANOTECHNOLOGY;PHYSICS, APPLIED;PHYSICS, CONDENSED MATTER | 2023 | 18.5 | 4.1 | 0.64 | 2025-06-25 | 6 | digital fingerprints; hardware-based security; inter-hamming distance; physical unclonable function; reduced graphene oxide | Blending; Cryptography; Graphene; Hardware security; Conductivity distributions; Digital fingerprint; Disordered distribution; Graphene oxides; Hummers method; Inter-hamming distance; Non-identical; Oxide materials; Purification procedures; Reduced graphene oxides; Hamming distance | English | Final | 2023 | 10.1002/adfm.202304432 | 바로가기 | 바로가기 | 바로가기 | |||||||
| ○ | ○ | Article | A Privacy-Preserving Authentication Scheme for a Blockchain-Based Energy Trading System | The adoption of renewable energies such as solar power, heat pumps, and wind power is on the rise, and individuals have started generating energy using their own solar panels. In recent years, many blockchain-based energy trading schemes have been proposed. However, existing schemes cannot fully address privacy issues and dependency on energy brokers during energy trading. In this paper, we propose a privacy-preserving authentication scheme for blockchain-based energy traders. An energy user encrypts a request message through lightweight attribute-based encryption, and only energy sellers who have proper attribute keys can decrypt and conduct further processes with the energy user. We analyze the proposed scheme using both informal and formal methods, such as the BAN logic, AVISPA simulation tool, and RoR model. Furthermore, we compare the computational and communication costs of our scheme with related schemes and show that the proposed scheme has competitive performance. | Son, Seunghwan; Oh, Jihyeon; Kwon, Deokkyu; Kim, Myeonghyun; Park, Kisung; Park, Youngho; Lansky, Jan | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea; Elect & Telecommun Res Inst, Daejeon 34129, South Korea | Lansky, Jan/A-3602-2008; Park, Kisung/KIG-3849-2024 | 57221744477; 57222066296; 57221739597; 57210278739; 57194833768; 56962990300 | parkyh@knu.ac.kr; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 22 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 0.49 | 2025-06-25 | 2 | 2 | access control; lightweight attribute-based encryption (ABE); consortium blockchain; energy trading; mutual authentication | LIGHTWEIGHT AUTHENTICATION; KEY-EXCHANGE; SMART; SECURITY; PROTOCOL; VEHICLES; INTERNET; DESIGN | access control; consortium blockchain; energy trading; lightweight attribute-based encryption (ABE); mutual authentication | English | 2023 | 2023-11 | 10.3390/math11224653 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Algorithms for coupled Burgers' equations by sharing characteristic curves within BSLM | This paper introduces a new perspective of the traditional view on the velocity of each physical particle in the coupled Burgers' equation in the backward semi-Lagrangian method (BSLM). The proposed methods reduce the number of Cauchy problems to be solved by observing a single virtual characteristic curve with a velocity. This can drastically reduce the computational cost of determining the departure point. Then, we solve the derived system reflected by the single virtual characteristic curve. Moreover, an efficient strategy for the derived linear system of equations is provided. Four examples are tested to demonstrate the adaptability and efficiency of the proposed method. The test results show that the proposed method has third- and fourth-order accuracy in time and space, respectively. In addition, compared with the existing method of solving the problem along two particles with different velocities, we confirm that the proposed method significantly reduces computational cost while maintaining accuracy well. | Bak, Soyoon; Jeon, Yonghyeon | Kyungpook Natl Univ, Dept Math, Daegu 41566, South Korea; Hongik Univ, Mechatron Res Ctr, Sejong 30016, South Korea | Bak, Soyoon/HSE-8486-2023 | 56450371300; 57197815771 | yhjeon@hongik.ac.kr; | ADVANCES IN CONTINUOUS AND DISCRETE MODELS | ADV CONTIN DISCRET M | 2731-4235 | 2023 | 1 | SCIE | MATHEMATICS, APPLIED;MATHEMATICS | 2023 | 2.3 | 4.2 | 0 | 2025-06-25 | 0 | 0 | Backward semi-Lagrangian method; Characteristic curve; Coupled Burgers' equations; Nonlinear Cauchy problem | LATTICE BOLTZMANN MODEL; NUMERICAL-SIMULATION | Backward semi-Lagrangian method; Characteristic curve; Coupled Burgers’ equations; Nonlinear Cauchy problem | English | 2023 | 2023-10-09 | 10.1186/s13662-023-03785-1 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Causality-Driven Efficient Feature Selection for Deep-Learning-Based Surface Roughness Prediction in Milling Machines | This paper studies the application of artificial intelligence to milling machines, focusing specifically on identifying the inputs (features) required for predicting surface roughness. Previous studies have extensively reviewed and presented useful features for surface roughness prediction. However, applying research findings to actual operational factories can be challenging due to the additional costs of sensor installations and the diverse environments present in each factory setting. To address these issues, in this paper, we introduced effective features for predicting surface roughness in situations where additional sensors are not installed in the existing environment. These features include feed per tooth, Fz; material removal rate, Q; and the load information. These features are suitable for use in highly constrained environments where separate sensor installation is not required, making it possible to apply the research findings in various factory environments. Additionally, to efficiently select the optimal subset for surface roughness prediction among subsets formed by available features, we apply causality to the feature selection method, proposing an approach called causality-driven efficient feature selection. The experimental results demonstrate that the features introduced in this paper are quite suitable for predicting surface roughness and that the proposed feature selection approach is more effective and efficient compared to existing selection methods. | Lee, Hyeon-Uk; Chun, Chang-Jae; Kang, Jae-Mo | Korea Electrotechnol Res Inst KERI, Artificial Intelligence Res Ctr, Changwon Si 51543, Gyeongsangnam D, South Korea; Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Sejong Univ, Dept Artificial Intelligence, Seoul 05006, South Korea | ; Chun, Changjae/AAF-2393-2019 | 57271194000; 55694574800; 56024930400 | chopa7@keri.re.kr;cjchun84@gmail.com;jmkang@knu.ac.kr; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 22 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 0.98 | 2025-06-25 | 4 | 4 | surface roughness; feature selection; deep learning; computer numerical control; milling machine | computer numerical control; deep learning; feature selection; milling machine; surface roughness | English | 2023 | 2023-11 | 10.3390/math11224682 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Enhanced Night-to-Day Image Conversion Using CycleGAN-Based Base-Detail Paired Training | Numerous studies are underway to enhance the identification of surroundings in nighttime environments. These studies explore methods such as utilizing infrared images to improve night image visibility or converting night images into day-like representations for enhanced visibility. This research presents a technique focused on converting the road conditions depicted in night images to resemble daytime scenes. To facilitate this, a paired dataset is created by augmenting limited day and night image data using CycleGAN. The model is trained using both original night images and single-scale luminance transform (SLAT) day images to enhance the level of detail in the converted daytime images. However, the generated daytime images may exhibit sharpness and noise issues. To address these concerns, an image processing approach, inspired by the Stevens effect and local blurring, which align with visual characteristics, is employed to reduce noise and enhance image details. Consequently, this study contributes to improving the visibility of night images by means of day image conversion and subsequent image processing. The proposed night-to-day image translation in this study has a processing time of 0.81 s, including image processing, which is less than one second. Therefore, it is considered valuable as a module for daytime image translation. Additionally, the image quality assessment metric, BRISQUE, yielded a score of 19.8, indicating better performance compared to conventional methods. The outcomes of this research hold potential applications in fields such as CCTV surveillance systems and self-driving cars. | Son, Dong-Min; Kwon, Hyuk-Ju; Lee, Sung-Hak | Kyungpook Natl Univ, Sch Elect & Elect Engn, 80 Daehak Ro, Daegu 41566, South Korea | ; Son, Dong-Min/LZH-4025-2025 | 57216612214; 55169908300; 7601395661 | forhollow@knu.ac.kr;olin1223@knu.ac.kr;shak2@ee.knu.ac.kr; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 14 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 3.68 | 2025-06-25 | 9 | 15 | image-to-image translation; CycleGAN; Pix2Pix; luminance adaptation transform; image processing; Stevens effect | CycleGAN; image processing; image-to-image translation; luminance adaptation transform; Pix2Pix; Stevens effect | English | 2023 | 2023-07 | 10.3390/math11143102 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Enhanced Non-Maximum Suppression for the Detection of Steel Surface Defects | Quality control in manufacturing equipment relies heavily on the detection of steel surface defects. Recently, there have been an increasing number of efforts in which object detection techniques have been utilized to achieve promising results in the detection of steel surface defects since the defect patterns can be considered objects. To enhance the detection performance in the object detection problem, the non-maximum suppression (NMS) step, which eliminates redundant boxes overlapped with a box having the greatest detection score, is essential. In this work, we propose a novel NMS to improve the detection method of steel surface defects. The proposed NMS approach is composed of three novel techniques: IoU regularization, threshold adjustment, and comparison rule modification to enhance the detection performance. To evaluate the performance of the proposed NMS, we carry out extensive numerical experiments using the YOLOv7 and EfficientDet models on the steel surface defect datasets, NEU-DET and GC10-DET. The experimental results demonstrate that the proposed NMS outperforms the conventional NMS methods in both quantitative and qualitative manners. | Kang, Seong-Hwan; Palakonda, Vikas; Kim, Il-Min; Kang, Jae-Mo; Yun, Sangseok | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Queens Univ, Dept Elect & Comp Engn, Kingston, ON K7L 3N6, Canada; Pukyong Natl Univ, Dept Informat & Commun Engn, Busan 48513, South Korea | 58690142500; 57193028485; 36040390300; 56024930400; 56115729600 | k3s6h5@knu.ac.kr;vikas475@knu.ac.kr;ilmin.kim@queensu.ca;jmkang@knu.ac.kr;ssyun@pknu.ac.kr; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 18 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 1.47 | 2025-06-25 | 6 | 7 | computer vision; deep learning; non-maximum suppression; object detection; steel surface defect | NETWORK; SCALE | computer vision; deep learning; non-maximum suppression; object detection; steel surface defect | English | 2023 | 2023-09 | 10.3390/math11183898 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Evaluating Domain Randomization in Deep Reinforcement Learning Locomotion Tasks | Domain randomization in the context of Reinforcement learning (RL) involves training RL agents with randomized environmental properties or parameters to improve the generalization capabilities of the resulting agents. Although domain randomization has been favorably studied in the literature, it has been studied in terms of varying the operational characters of the associated systems or physical dynamics rather than their environmental characteristics. This is counter-intuitive as it is unrealistic to alter the mechanical dynamics of a system in operation. Furthermore, most works were based on cherry-picked environments within different classes of RL tasks. Therefore, in this work, we investigated domain randomization by varying only the properties or parameters of the environment rather than varying the mechanical dynamics of the featured systems. Furthermore, the analysis conducted was based on all six RL locomotion tasks. In terms of training the RL agents, we employed two proven RL algorithms (SAC and TD3) and evaluated the generalization capabilities of the resulting agents on several train-test scenarios that involve both in-distribution and out-distribution evaluations as well as scenarios applicable in the real world. The results demonstrate that, although domain randomization favors generalization, some tasks only require randomization from low-dimensional distributions while others require randomization from high-dimensional randomization. Hence the question of what level of randomization is optimal for any given task becomes very important. | Ajani, Oladayo S.; Hur, Sung-ho; Mallipeddi, Rammohan | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 37224, South Korea | Mallipeddi, Rammohan/AAL-5306-2020; AJANI, Oladayo/HIR-9607-2022 | 57465126000; 36455858700; 25639919900 | oladayosolomon@gmail.com;shur@knu.ac.kr;mallipeddi.ram@gmail.com; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 23 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 0.74 | 2025-06-25 | 3 | 4 | generalization; deep reinforcement learning; dynamic environments; locomotion; domain randomization | deep reinforcement learning; domain randomization; dynamic environments; generalization; locomotion | English | 2023 | 2023-12 | 10.3390/math11234744 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | EvolveNet: Evolving Networks by Learning Scale of Depth and Width | Convolutional neural networks (CNNs) have shown decent performance in a variety of computer vision tasks. However, these network configurations are largely hand-crafted, which leads to inefficiency in the constructed network. Various other algorithms have been proposed to address this issue, but the inefficiencies resulting from human intervention have not been addressed. Our proposed EvolveNet algorithm is a task-agnostic evolutionary search algorithm that can find optimal depth and width scales automatically in an efficient way. The optimal configurations are not found using grid search, and are instead evolved from an existing network. This eliminates inefficiencies that emanate from hand-crafting, thus reducing the drop in accuracy. The proposed algorithm is a framework to search through a large search space of subnetworks until a suitable configuration is found. Extensive experiments on the ImageNet dataset demonstrate the superiority of the proposed method by outperforming the state-of-the-art methods. | Shibu, Athul; Lee, Dong-Gyu | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea | 58090284100; 57169003900 | athulshibu@knu.ac.kr;dglee@knu.ac.kr; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 16 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 0.25 | 2025-06-25 | 1 | 1 | convolutional neural network; network scaling; evolutionary computation | convolutional neural network; evolutionary computation; network scaling | English | 2023 | 2023-08 | 10.3390/math11163611 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||||
| ○ | ○ | Article | Filamentary structures as the origin of blazar jet radio variability | Supermassive black holes at the centre of active galactic nuclei power some of the most luminous objects in the Universe. Typically, very-long-baseline interferometric observations of blazars have revealed only funnel-like morphologies with little information on the internal structure of the ejected plasma or have lacked the dynamic range to reconstruct the extended jet emission. Here we present microarcsecond-scale angular resolution images of the blazar 3C 279 obtained at 22 GHz with the space very-long-baseline interferometry mission RadioAstron, which allowed us to resolve the jet transversely and reveal several filaments produced by plasma instabilities in a kinetically dominated flow. The polarimetric properties derived from our high-angular-resolution and broad-dynamic-range images are consistent with the presence of a helical magnetic field threaded to the jet. We infer a clockwise rotation as seen in the direction of flow motion with an intrinsic helix pitch angle of similar to 45 degrees and a Lorentz factor of similar to 13 at the time of observation. We also propose a model to explain blazar jet radio variability in which emission features travelling down the jet may manifest as a result of differential Doppler boosting within the filaments, as opposed to the standard shock-in-jet model. Characterizing such variability is particularly important given the relevance of blazar physics from cosmic particle acceleration to standard candles in cosmology. | Fuentes, Antonio; Gomez, Jose L.; Marti, Jose M.; Perucho, Manel; Zhao, Guang-Yao; Lico, Rocco; Lobanov, Andrei P.; Bruni, Gabriele; Kovalev, Yuri Y.; Chael, Andrew; Akiyama, Kazunori; Bouman, Katherine L.; Sun, He; Cho, Ilje; Traianou, Efthalia; Toscano, Teresa; Dahale, Rohan; Foschi, Marianna; Gurvits, Leonid I.; Jorstad, Svetlana; Kim, Jae-Young; Marscher, Alan P.; Mizuno, Yosuke; Ros, Eduardo; Savolainen, Tuomas | Inst Astrofis Andalucia CSIC, Granada, Spain; Univ Valencia, Dept Astron & Astrofis, Burjassot, Spain; Univ Valencia, Observ Astron, Paterna, Spain; Ist Radioastron INAF, Bologna, Italy; Max Planck Inst Radioastron, Bonn, Germany; INAF, Ist Astrofis & Planetol Spaziali, Rome, Italy; Russian Acad Sci, Lebedev Phys Inst, Moscow, Russia; Princeton Univ, Princeton Grav Initiat, Princeton, NJ USA; MIT, Haystack Observ, Westford, MA USA; Natl Astron Observ Japan, Mitaka, Japan; Harvard Univ, Black Hole Initiat, Cambridge, MA USA; CALTECH, Pasadena, CA USA; Indian Inst Sci Educ & Res Kolkata, Mohanpur, India; Joint Inst VLBI ERIC JIVE, Dwingeloo, Netherlands; Delft Univ Technol, Aerosp Fac, Delft, Netherlands; Boston Univ, Inst Astrophys Res, Boston, MA USA; St Petersburg State Univ, Astron Inst, St Petersburg, Russia; Kyungpook Natl Univ, Dept Astron & Atmospher Sci, Daegu, South Korea; Korea Astron & Space Sci Inst, Daejeon, South Korea; Shanghai Jiao Tong Univ, Tsung Dao Lee Inst, Shanghai, Peoples R China; Shanghai Jiao Tong Univ, Sch Phys & Astron, Shanghai, Peoples R China; Goethe Univ Frankfurt, Inst Theoret Phys, Frankfurt, Germany; Aalto Univ, Dept Elect & Nanoengn, Aalto, Finland; Aalto Univ, Metsahovi Radio Observ, Kylmala, Finland | Gómez, José/C-4195-2008; Bruni, Gabriele/ABB-2523-2021; Perucho, Manel/A-9528-2017; Jorstad, Svetlana/AAM-3279-2021; Martí, José/AAA-4239-2019; Lobanov, Andrei/G-5891-2014; 韓之強, Chih/AAZ-8498-2020; Lico, Rocco/L-8308-2019; Toscano Domingo, Teresa/ITV-2430-2023; Gomez, Jose L./C-4195-2008; Kovalev, Yuri/J-5671-2013; Kim, Jae-Young/IUO-6466-2023; Fuentes, Antonio/R-3900-2019; Ros, Eduardo/B-1014-2015 | 56699569900; 7402094981; 56232990800; 9537076500; 55478882500; 55363924100; 7101957568; 56950092500; 7004589011; 55324722200; 55669706400; 36627851000; 57192429990; 57203071154; 57204824800; 57702184700; 57274820700; 58079527600; 7006254892; 59785012300; 57211836467; 7004154914; 15070911300; 7102531000; 7003371610 | afuentes@iaa.es;jlgomez@iaa.es; | NATURE ASTRONOMY | NAT ASTRON | 2397-3366 | 7 | 11 | SCIE | ASTRONOMY & ASTROPHYSICS | 2023 | 13.3 | 4.2 | 2.72 | 2025-06-25 | 20 | 25 | ACTIVE GALACTIC NUCLEI; MAGNETIC-FIELDS; SIZE | English | 2023 | 2023-11 | 10.1038/s41550-023-02105-7 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||||
| ○ | ○ | Article | Greenhouse Micro-Climate Prediction Based on Fixed Sensor Placements: A Machine Learning Approach | Accurate measurement of micro-climates that include temperature and relative humidity is the bedrock of the control and management of plant life in protected cultivation systems. Hence, the use of a large number of sensors distributed within the greenhouse or mobile sensors that can be moved from one location to another has been proposed, which are both capital and labor-intensive. On the contrary, accurate measurement of micro-climates can be achieved through the identification of the optimal number of sensors and their optimal locations, whose measurements are representative of the micro-climate in the entire greenhouse. However, given the number of sensors, their optimal locations are proven to vary from time to time as the outdoor weather conditions change. Therefore, regularly shifting the sensors to their optimal locations with the change in outdoor conditions is cost-intensive and may not be appropriate. In this paper, a framework based on the dense neural network (DNN) is proposed to predict the measurements (temperature and humidity) corresponding to the optimal sensor locations, which vary relative to the outdoor weather, using the measurements from sensors whose locations are fixed. The employed framework demonstrates a very high correlation between the true and predicted values with an average coefficient value of 0.91 and 0.85 for both temperature and humidity, respectively. In other words, through a combination of the optimal number of fixed sensors and DNN architecture that performs multi-channel regression, we estimate the micro-climate of the greenhouse. | Ajani, Oladayo S.; Usigbe, Member Joy; Aboyeji, Esther; Uyeh, Daniel Dooyum; Ha, Yushin; Park, Tusan; Mallipeddi, Rammohan | Kyungpook Natl Univ, Dept Artificial Intelligence, Daegu 41566, South Korea; Michigan State Univ, Dept Biosyst & Agr Engn, E Lansing, MI 48824 USA; Kyungpook Natl Univ, Upland Field Machinery Res Ctr, Daegu 41566, South Korea; Kyungpook Natl Univ, Smart Agr Innovat Ctr, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Bioind Machinery Engn, Daegu 41566, South Korea | AJANI, Oladayo/HIR-9607-2022; Park, Tusan/C-2057-2012; Aboyeji, Esther/IZP-8228-2023; Mallipeddi, Rammohan/AAL-5306-2020 | 57465126000; 58512627500; 58406711200; 57194449611; 57192072314; 57202780408; 25639919900 | oladayosolomon@gmail.com;usigbemember@gmail.com;aboyejitolulopeesther@gmail.com;uyehdooyum@gmail.com;yushin72@knu.ac.kr;tusan.park@knu.ac.kr;mallipeddi.ram@gmail.com; | MATHEMATICS | MATHEMATICS-BASEL | 2227-7390 | 11 | 14 | SCIE | MATHEMATICS | 2023 | 2.3 | 4.2 | 2.95 | 2025-06-25 | 13 | 12 | greenhouse; temperature; relative humidity; optimal sensor locations; multi-channel regression; dense neural network | TECHNOLOGIES; LOCATION; SYSTEMS | dense neural network; greenhouse; multi-channel regression; optimal sensor locations; relative humidity; temperature | English | 2023 | 2023-07 | 10.3390/math11143052 | 바로가기 | 바로가기 | 바로가기 | 바로가기 |
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