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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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| ○ | ○ | Proceedings Paper | Multi-objective Evolutionary Algorithm based on Ensemble of Initializations for Overlapping Community Detection | Recently, developing efficient multi-objective evolutionary algorithms (MOEAs) for detect communities in complex networks has received immense recognition. Employing MOEAs for community detection provide a set of Pareto-optimal solutions (PS) where each solution in PS represent different network partition. In literature, majority of existing approaches proposed for detecting community structures focus on obtaining disjoint communities (each node belongs to a unique community). However, communities in real-world networks often overlap with each other and thus it is essential to develop algorithms for overlapping community detection. Hence, in this paper, we propose a MOEA based on ensemble of initializations for overlapping community detection (OCD-enMOEA). In OCD-enMOEA, we employ an ensemble of initialization procedure, where the individuals are encoded by an indirect representation based on permutation. Then, a decoding procedure based on community fitness is employed to transform the individuals into communities. The community fitness metrics adopted for decoding is associated with a resolution parameter alpha, which allows exploration of community structures at different levels of granularity. However, the community fitness metric is very sensitive to the parameter alpha and adapting the parameter to achieve better performance is very difficult. Hence, in this paper, we employ a set of values for the parameter alpha as an ensemble and transform the individuals into communities. To validate the performance of proposed OCD-enMOEA, we have employed five real-world networks and compared with six baseline algorithms to detect overlapping communities. The experimental results demonstrate that the proposed method exhibit better performance in comparison with the baseline algorithms. | Yusupov, Jamshid; Palakonda, Vikas; Mallipeddi, Rammohan; Veluvolu, Kalyana Chakravarthy | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 702701, South Korea; Kyungpook Natl Univ, Sch Elect Engn, Dept Artificial Intelligence, Daegu, South Korea | Veluvolu, Kalyana/C-6366-2011; Mallipeddi, Rammohan/AAL-5306-2020 | 57222517053; 57193028485; 25639919900; 8703318200 | jamshid96se@gmail.com;vikas.11475@gmail.com;mallipeddi.ram@gmail.com;veluvolu@ee.knu.ac.kr; | 2021 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 0 | 2025-07-30 | 0 | 0 | Complex network; overlapping community detection; ensemble initialization; multiobjective evolutionary algorithm (MOEA) | COMPLEX NETWORKS; MODULARITY | Complex network; Ensemble initialization; Multiobjective evolutionary algorithm (MOEA); Overlapping community detection | Complex networks; Decoding; Health; Pareto principle; Population dynamics; Community detection; Community structures; Initialization procedures; Multi objective evolutionary algorithms; Overlapping communities; Overlapping community detections; Pareto optimal solutions; Resolution parameters; Evolutionary algorithms | English | 2021 | 2021 | 10.1109/iceic51217.2021.9369811 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | ○ | Proceedings Paper | Multicast Beamforming Planning Based on Massive MIMO Antenna Array | Massive MIMO and beamforming are primary technologies in 5G and beyond (B5G). The line-of-sight (LOS) beamforming technology form a beam path for a specific user to significantly compensates for the high attenuation of millimeter-wave (mmWave). This paper considers serving multicast users using beamforming based on the massive MIMO antenna array, aiming to optimize the beam utilization and maximize the successfully served users. In particular, we divide the massive MIMO antenna array into multiple smaller sub-arrays with different scales to form flexible beams with various beam widths and transmission coverage to serve unicast or multicast users based on needs. Regarding this, we propose an Integer Linear Programming (ILP) optimization model to minimize the power consumption of the entire antenna array while maximizing the number of successfully served users using beamforming multicast and/or unicast, subject to the constraints of power consumption and signal-to-interference-noise ratio (SINR). The proposed optimization model is numerically evaluated, and results show that significant power can be saved using multicast beamforming technology. | Liu, Xiaoxiao; Mei, Haoran; Peng, Limei | Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea | Liu, Xiaoxiao/HNI-6180-2023 | 57222269504; 57208655106; 7201574271 | liuxiaoxiao@knu.ac.kr;meihaoran@knu.ac.kr;auroraplm@knu.ac.kr; | INTERNATIONAL SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND ROBOTICS 2021 | 0277-786X | 1996-756X | 11884 | 0 | 2025-07-30 | 0 | 0 | Beamforming; Multicasting; SINR | Beamforming; Multicasting; SINR | 5G mobile communication systems; Beam forming networks; Electric power utilization; Flexible structures; Integer programming; Millimeter waves; Multicasting; Signal interference; Signal to noise ratio; Beam path; Flexible beam; Line of Sight; Lines-of-sight; MIMO-antennas; Optimization models; Primary technologies; Signalto-interference noise ratios (SINR); Subarray; Unicast; Beamforming | English | 2021 | 2021 | 10.1117/12.2607219 | 바로가기 | 바로가기 | 바로가기 | ||||||||||
| ○ | ○ | Proceedings Paper | Multimodal Preclinical Imaging System Using Transparent Ultrasonic Transducer | We present a multimodal imaging system that seamlessly integrates ultrasound imaging, photoacoustic imaging, and optical coherence tomography using a transparent ultrasonic transducer. We demonstrate the system's use in imaging responses to mouse body in vivo. | Park, Jeongwoo; Park, Byullee; Kim, Tae Yeong; Jung, Sungjin; Choi, Woo June; Ahn, Joongho; Yong, Uijung; Jang, Jinah; Kim, Won Jong; Kim, Hong Kyun; Jeong, Unyong; Kim, Hyung Ham; Kim, Chulhong | Pohang Univ Sci & Technol, Dept Elect Engn, Creat IT Engn Mat Sci & Engn, Chem,MechEngn,Sch Interdisciplinary Biosci & Bio, 77 Cheongam Ro, Pohang 37673, South Korea; Pohang Univ Sci & Technol, Med Device Innovat Ctr, 77 Cheongam Ro, Pohang 37673, South Korea; Chung Ang Univ, Sch Elect & Elect Engn, 84 Heukseok Ro, Seoul 06974, South Korea; Kyungpook Natl Univ, Dept Ophthalmol, Sch Med, 680 Gukchaebosang Ro, Daegu 41944, South Korea | Jang, Jinah/AGE-7920-2022; Park, Byullee/ITU-4262-2023; Park, Jeongwoo/LIC-1971-2024; Kim, Chang-Hoon/D-7205-2016; Yong, Uijung/NPJ-0657-2025 | 57205588351; 57200376082; 57204738205; 57211573322; 24070138500; 57194204029; 57216159817; 55212064400; 7405810991; 57218260940; 57415301200; 14829036600; 57202234822 | chulhong@postech.edu; | OPTO-ACOUSTIC METHODS AND APPLICATIONS IN BIOPHOTONICS V | 0277-786X | 1996-756X | 11923 | 0 | 2025-07-30 | 0 | 0 | Imaging systems; Medical imaging; Optical tomography; Photons; Ultrasonic imaging; In-vivo; Multi-modal; Multimodal imaging systems; Photo-acoustic imaging; Preclinical imaging; System use; Ultrasound imaging; Ultrasonic transducers | English | 2021 | 2021 | 10.1117/12.2615887 | 바로가기 | 바로가기 | 바로가기 | ||||||||||||
| ○ | Conference paper | Multimodal preclinical imaging system using transparent ultrasonic transducer | We present a multimodal imaging system that seamlessly integrates ultrasound imaging, photoacoustic imaging, and optical coherence tomography using a transparent ultrasonic transducer. We demonstrate the system’s use in imaging responses to mouse body in vivo. © 2021 The Author(s) | Park, Jeongwoo; Park, Byullee; Kim, Tae Yeong; Jung, Sungjin; Choi, Woo June; Ahn, Joongho; Yong, Uijung; Jang, Jinah; Kim, Won Jong; Kim, Hong Kyun; Jeong, Unyong; Kim, Hyung Ham; Kim, Chulhong | Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-Ro, Dongjak-Gu, Seoul, 06974, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Ophthalmology, School of Medicine, Kyungpook National University, 680 Gukchaebosang-Ro, Jung-Gu, Daegu, 41944, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea; Department of Electrical Engineering, Creative IT Engineering, Materials Science and Engineering, Chemistry, Mechanical Engineering, School of Interdisciplinary Bioscience and Bioengineering, Medical Device Innovation Center, Pohang University of Science and Technology, 77, Cheongam-Ro, Nam-Gu, Pohang, 37673, South Korea | 57205588351; 57200376082; 57204738205; 57211573322; 24070138500; 57194204029; 57216159817; 55212064400; 57226897746; 57218260940; 6603678987; 14829036600; 57202234822 | Optics InfoBase Conference Papers | 2162-2701 | 0 | 2025-07-30 | 0 | Imaging systems; Optical tomography; Ultrasonic imaging; In-vivo; Multi-modal; Multimodal imaging systems; Photo-acoustic imaging; Preclinical imaging; Ultrasound imaging; Ultrasonic transducers | English | Final | 2021 | 바로가기 | |||||||||||||||||||||
| ○ | Book chapter | Nanostructured Heterojunction (1D-0D and 2D-0D) Photocatalysts for Environmental Remediation | Global warming and environmental pollution are the most important problems or challenges present in the scientific community. To successfully tackle the environmental problems, the novel nanotechnologies that work with efficient nanomaterials are the only way. Therefore, the development of nanomaterials and their composites with heterojunctions has made great demand in view of the environmental remediation. Hence in this book chapter we have focused on the development of various heterojunction nanomaterials including 1D-0D and 2D-0D heterojunction photocatalysts comprising of various metal oxides and metals for environmental remediation, organic dye degradation, wastewater treatment, air purification, and antibacterial treatments. The 1D-0D heterojunctions consisting of 1D nanostructures like TiO2 nanotubes, nanobelts, ZnO nanorods, metal oxide nanowires with 0D metals, and metal oxides of Cu, CuxO, MnO2, Ag, Ag2O, Au, Pt, etc. were reported emphasizing the special properties associated with the nanostructures like high surface area, abundant active sites, and efficient charge transfer across the interface of the heterojunction. Followed by 2D-0D heterojunctions associated with g-C3N4, rGO and GO nanosheets coupled with metal oxides of Ag2O, Cu2O, ZnO, In2O3, MoO3, V2O5, and TiO2 and various transition and noble metals of Cu, Ag, Au, Pt, Pd, etc. were also reported. The important properties associated with the 2D nanosheets like high surface area and higher electron transport properties and special properties of nanometals like SPR effect and a greater number of active sites on the surface of the nanometal particles were highlighted. Various characterization techniques to investigate the physicochemical properties of those nanomaterials were reported. For example, HR-TEM, XRD, DRS UV-Vis, PL spectra, time-resolved PL spectra, transient photocurrent densities, XPS, etc. are studied which were helpful to investigate the higher photocatalytic efficiencies. Finally, the summary and future prospects of these heterojunction photocatalysts and further improvements are summarized. Therefore, this book chapter will give an overview of different types of heterojunction photocatalysts and their properties associated with improving the catalytic properties for a wide range of readers. © Springer Nature Switzerland AG 2021. All rights are reserved. | Nagappagari, Lakshmana Reddy; Lee, Kiyoung; Rakesh, Ajay; Balakumar, Subramanian; Shankar, M.V. | Department of Energy Chemical Engineering, School of Nano & Materials Science and Engineering, Kyungpook National University, Sangju, South Korea; Department of Energy Chemical Engineering, School of Nano & Materials Science and Engineering, Kyungpook National University, Sangju, South Korea; National Centre for Nanoscience and Nanotechnology (NCNN), University of Madras, Tamil Nadu, Chennai, India; National Centre for Nanoscience and Nanotechnology (NCNN), University of Madras, Tamil Nadu, Chennai, India; Nanocatalysis and Solar Fuels Research Laboratory, Department of Materials Science & Nanotechnology, Yogi Vemana University, Andhra Pradesh, Kadapa, India | 56499352000; 57219211501; 57557377900; 57200977501; 7005167181 | shankar@yogivemanauniversity.ac.in; | Nanostructured Materials for Environmental Applications | 0.37 | 2025-07-30 | 1 | 1D-0D heterojunction; 2D-0D heterojunction; Air purification; Direct oxidation; Dye degradation; Environmental remediation; Graphitic carbon nitride; Heterojunctions; Metal oxides; Metals; Nanosheets; Nanotubes; Photocatalysts; Surface-interface properties; TiO2 nanostructures; Wastewater treatment; ZnO nanostructures | English | Final | 2021 | 10.1007/978-3-030-72076-6_2 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Book chapter | Nanotoxicology-toxicology of nanomaterials and incidental nanomaterials | According to the International Organization for Standardization (ISO), nanomaterials exist in more than one dimension, and their size ranges between 1 and 100 nm. From fertilizers to pesticides, food preservation, packing materials, water purification, and much more, nanomaterials have become the driving force behind increasing the production of food in the agriculture sector. Despite numerous benefits, exploration into the risks of nanotoxicity due to incorporation of NPs into food has become imperative as engineered and incidental nanomaterials can cause health problems upon entering the human body. We focus on how these nanoparticles (NPs) impact living systems, especially the end users-humans. The properties of these materials and their interaction with environment will also be discussed. An explanation of the chemical and physical parameters that lead to nanomaterial toxicity will also be included, and how they ultimately become exposed to living beings and an overview about future prospects will be outlined. © 2021 Elsevier Inc. All rights reserved. | Waris, Aisha A.; Athar, Tabinda; Fatima, Hina; Nisar, Madiha | Institute of Soil and Environmental Sciences, Faculty of Agriculture, University of Agriculture Faisalabad, Faisalabad, Pakistan; Institute of Soil and Environmental Sciences, Faculty of Agriculture, University of Agriculture Faisalabad, Faisalabad, Pakistan; School of Applied Biosciences, Kyungpook National University, Daegu, South Korea; Institute of Soil and Environmental Sciences, Faculty of Agriculture, University of Agriculture Faisalabad, Faisalabad, Pakistan | 57204141168; 57215817227; 59800323300; 58243906400 | Nanomaterials: Synthesis, Characterization, Hazards and Safety | 1.53 | 2025-07-30 | 5 | Incidental nanoparticles; Nanoparticles; Nanotoxicology; Toxicity | English | Final | 2021 | 10.1016/b978-0-12-823823-3.00003-3 | 바로가기 | 바로가기 | ||||||||||||||||||||
| ○ | Proceedings Paper | Natural Speed Planning and Control of the Autonomous Vehicle within Social Norm | The tradeoff between strict regulation of autonomous vehicle-driving rules and natural behavior is sufficient to realize autonomous driving technology. However, most autonomous vehicles' control logic is designed to strictly satisfy the driving rules that can sometimes cause car accidents and unnatural behavior. In this study, by relaxing the constraints in the optimization problem, we propose the controller, which makes the autonomous vehicle natural behavior, even though it slightly violates the social norm. The autonomous vehicle sometimes exceeds the road speed limit to pass the traffic light by adding the slack variables to the state and control constraints in the optimization problem, which is similar to the human driver's behavior in front of the traffic light. Our approach shows that autonomous vehicle behaves more natural than conventional techniques. In addition, the overall trip time is decreased, thus minimizing fuel consumption. | Kwon, Solyeon; Han, Kyoungseok | Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea | solyeonkwon@knu.ac.kr;kyoungsh@knu.ac.kr; | 2021 21ST INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2021) | 2093-7121 | 0 | Autonomous Vehicle; Signal Phase and Timing; Optimization Problem; Slack Variable; Social Norm | English | 2021 | 2021 | 바로가기 | |||||||||||||||||||||||
| ○ | Conference paper | Natural Speed Planning and Control of the Autonomous Vehicle within Social Norm | The tradeoff between strict regulation of autonomous vehicle-driving rules and natural behavior is sufficient to realize autonomous driving technology. However, most autonomous vehicles' control logic is designed to strictly satisfy the driving rules that can sometimes cause car accidents and unnatural behavior. In this study, by relaxing the constraints in the optimization problem, we propose the controller, which makes the autonomous vehicle natural behavior, even though it slightly violates the social norm. The autonomous vehicle sometimes exceeds the road speed limit to pass the traffic light by adding the slack variables to the state and control constraints in the optimization problem, which is similar to the human driver's behavior in front of the traffic light. Our approach shows that autonomous vehicle behaves more natural than conventional techniques. In addition, the overall trip time is decreased, thus minimizing fuel consumption. © 2021 ICROS. | Kwon, Solyeon; Han, Kyoungseok | School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, South Korea; School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, South Korea | 57444079500; 56465294700 | kyoungsh@knu.ac.kr; | International Conference on Control, Automation and Systems | 1598-7833 | 2021-October | 0 | 2025-07-30 | 0 | Autonomous Vehicle; Optimization Problem; Signal Phase and Timing; Slack Variable; Social Norm | Accidents; Autonomous vehicles; Behavioral research; Timing circuits; Autonomous driving; Autonomous Vehicles; Optimization problems; Planning and control; Signal phase; Signal timing; Slack variables; Social norm; Speed planning; Traffic light; Optimization | English | Final | 2021 | 10.23919/iccas52745.2021.9649919 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Proceedings Paper | Network Traffic Classification Using Ensemble Learning in Software-Defined Networks | Accurate network traffic classification is essential for network management. However, existing network traffic classification methods cannot meet the demand of real networks in terms of classification performance, user privacy, latency, and control overhead. Thus, a machine learning-based approach has been used for network traffic classification. In this paper, we propose a network traffic classification framework using software-defined network (SDN) architecture. The proposed framework is entirely located in the network controller; thus, we can leverage the superior computational capacity, global visibility, and programmability of the SDN controller to realize real-time, adaptive, and accurate traffic classification. We also apply four ensemble algorithms and analyze their classification performance in terms of accuracy, precision, recall, F1-score, training time, and classification time. The experimental results reveal that ensemble model-based network traffic classifiers outperform other classifiers based on the proposed framework and the real-world network traffic dataset. Notably, the LightGBM model achieves the best classification performance. | Eom, Won-Ju; Song, Yeong-Jun; Park, Chang-Hoon; Kim, Jeong-Keun; Kim, Geon-Hwan; Cho, You-Ze | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu, South Korea | dnjswn9612@knu.ac.kr;syj5385@knu.ac.kr;pch4495@knu.ac.kr;kjg818@knu.ac.kr;kgh76@ee.knu.ac.kr;yzcho@ee.knu.ac.kr; | 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (IEEE ICAIIC 2021) | 11 | Software-defined network (SDN); traffic classification; ensemble learning | ISSUES | English | 2021 | 2021 | 10.1109/icaiic51459.2021.9415187 | 바로가기 | 바로가기 | |||||||||||||||||||||
| ○ | Article | Neuromyelitis Optica Spectrum Disorders Mimicking Multiple Brain Tumors | We report a rare case of neuromyelitis optica spectrum disorders (NMOSD), mimicking multiple brain tumors. A 53-year-old woman presented with weakness and paresthesia in her right arm and leg. Upon admission, brain MRI showed about 10 multiple brain tumors, which had to be differentiated from multiple brain metastases, lymphoma, and high-grade glioma in both hemispheres. No primary cancer was found in the chest-abdomen-pelvis CT. Subsequent spine MRI revealed multifocal cord signal change involving C2-T7, suggesting myelitis. A decrease in visual acuity was noted when taking a medical history, and optic neuritis was diagnosed upon ophthalmologic examination. With clinical and radiological appearances, multiple brain and spinal cord lesions have been diagnosed as NMOSD. Steroid and immunosuppressive drugs were administered. We should consider the possibility of an autoimmune disease, such as NMOSD, involving the optic nerve, spinal cord, and central nervous system when multiple hemispheric tumefactive lesions are observed. © 2021 The Korean Brain Tumor Society, The Korean Society for NeuroOncology, and The Korean Society for Pediatric Neuro-Oncology. | Park, Seong-Hyun; Hwang, Jeong-Hyun | Department of Neurosurgery, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, South Korea; Department of Neurosurgery, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, South Korea | 21734563200; 7403896906 | nsdoctor@naver.com; | Brain Tumor Research and Treatment | 2288-2405 | 9 | 1 | 0 | 2025-07-30 | 0 | Neuromyelitis optica spectrum disorders; Optic neuritis; Spinal cord; Tumor | English | Final | 2021 | 10.14791/btrt.2021.9.e1 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | New approaches for renewable energy management in autonomous marine vehicles | The current powering limitations of the autonomous underwater vehicles make necessary the design of energy packs that can offer prolonged energy during operation. This paper presents an analysis of the operational values of the energy pack considered in autonomous underwater vehicles with extended endurance capability. The hardware, software and external conditions that contribute to the power consumption are considered under a range of different operational scenarios. The power consumption of the hardware used in different missions due to, for example, sensors, propulsion unit, etc., together with the energy pack characteristics definition are considered. The approach leads the development of condition-based maintenance management strategies for underwater operations together with the optimization of the battery life-cycle as a function of charge/discharge uses. A real case-study is presented based on the ENDURUNS European project, where a fuel cell is used as a primary power source, being responsible for re-charging the Li-ion battery stack onboard when required. © 2020 Taylor & Francis Group, London. | Bernalte, P.J.; Márquez, F.P.G.; Marini, S.; Bonofoglio, F.; Barbieri, L.; Gjeci, Nikolla; Ottaviani, E.; Govindaraj, S.; Coene, S.; But, A.; Pedersen, J.; Vetke, C.; Madricardo, F.; Foglini, F.; Antonini, M.; Montenegro, S.; Weiss, P.; Nowak, K.; Peer, M.; Gobert, T.; Turetta, A.; Chatzidouros, E.; Lee, D.; Yamas, T.; Papaelias, M. | School of Industrial Engineering, University of Castilla La Mancha, Ciudad Real, Spain; School of Industrial Engineering, University of Castilla La Mancha, Ciudad Real, Spain; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Onairweb; Onairweb; Space Applications Services NV/SA, Sint-Stevens-Woluwe, Brussels Area, Belgium; Space Applications Services NV/SA, Sint-Stevens-Woluwe, Brussels Area, Belgium; Space Applications Services NV/SA, Sint-Stevens-Woluwe, Brussels Area, Belgium; Tuco Group ApS, Krogsbjergvej, Faabor, Denmark; Tuco Group ApS, Krogsbjergvej, Faabor, Denmark; Institute of Marine Sciences, National Research Council of Italy (CNR), Bologna, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), Bologna, Italy; HysyTech s.r.l., Torino, Italy; HysyTech s.r.l., Torino, Italy; COMEX, Marseille, France; COMEX, Marseille, France; COMEX, Marseille, France; COMEX, Marseille, France; Graal Tech S.r.l., Genova, Italy; Engitec Systems International Ltd, Novate Milanese, Milan, Italy; School of Electronics Engineering, Kyungpook National University, Daehakro. Bukgu, Daegu, South Korea; ALTUS-LSA, Chania, Greece; School of Metallurgy and Materials, The University of Birmingham, Edgbaston, Birmingham, United Kingdom | 57216411206; 57200782595; 8729024700; 57300809000; 57203759560; 57193198789; 7102082014; 56040282500; 57203390957; 57214791245; 57218837054; 57300514300; 8401894000; 23027607700; 57193339166; 57300514400; 57197445260; 57218837256; 57203390599; 56323321000; 9240224000; 43960934200; 55698910600; 57218834643; 6505791928 | Developments in Renewable Energies Offshore - Proceedings the 4th International Conference on Renewable Energies Offshore, RENEW 2020 | 1.05 | 2025-07-30 | 3 | Autonomous underwater vehicles; Autonomous vehicles; Battery Pack; Electric power utilization; Fuel cells; Life cycle; Lithium-ion batteries; 'current; Autonomous marine vehicles; Autonomous underwater vehicles]; Condition based maintenance; Energy; External conditions; Hardware/software; New approaches; Operational scenario; Renewable energies | English | Final | 2021 | 바로가기 | ||||||||||||||||||||||
| ○ | Book chapter | New approaches for renewable energy management in autonomous marine vehicles | The current powering limitations of the autonomous underwater vehicles make necessary the design of energy packs that can offer prolonged energy during operation. This paper presents an analysis of the operational values of the energy pack considered in autonomous underwater vehicles with extended endurance capability. The hardware, software and external conditions that contribute to the power consumption are considered under a range of different operational scenarios. The power consumption of the hardware used in different missions due to, for example, sensors, propulsion unit, etc., together with the energy pack characteristics definition are considered. The approach leads the development of condition-based maintenance management strategies for underwater operations together with the optimization of the battery life-cycle as a function of charge/discharge uses. A real case-study is presented based on the ENDURUNS European project, where a fuel cell is used as a primary power source, being responsible for re-charging the Li-ion battery stack onboard when required. © 2020 Taylor & Francis Group, London. | Bernalte, P.J.; Márquez, F.P.G.; Marini, S.; Bonofoglio, F.; Barbieri, L.; Gjeci, Nikolla; Ottaviani, E.; Govindaraj, S.; Coene, S.; But, A.; Pedersen, J.; Vetke, C.; Madricardo, F.; Foglini, F.; Antonini, M.; Montenegro, S.; Weiss, P.; Nowak, K.; Peer, M.; Gobert, T.; Turetta, A.; Chatzidouros, E.; Lee, D.; Yamas, T.; Papaelias, M. | School of Industrial Engineering, University of Castilla La Mancha, Ciudad Real, Spain; School of Industrial Engineering, University of Castilla La Mancha, Ciudad Real, Spain; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), La Spezia, Italy; Onairweb, Italy; Onairweb, Italy; Space Applications Services NV/SA, Brussels Area, Sint-Stevens-Woluwe, Belgium; Space Applications Services NV/SA, Brussels Area, Sint-Stevens-Woluwe, Belgium; Space Applications Services NV/SA, Brussels Area, Sint-Stevens-Woluwe, Belgium; Tuco Group ApS, Krogsbjergvej, Faabor, Denmark; Tuco Group ApS, Krogsbjergvej, Faabor, Denmark; Institute of Marine Sciences, National Research Council of Italy (CNR), Bologna, Italy; Institute of Marine Sciences, National Research Council of Italy (CNR), Bologna, Italy; HysyTech s.r.l, Torino, Italy; HysyTech s.r.l, Torino, Italy; COMEX, Marseille, France; COMEX, Marseille, France; COMEX, Marseille, France; COMEX, Marseille, France; Graal Tech S.r.l, Genova, Italy; Engitec Systems International Ltd, Milan, Novate Milanese, Italy; School of Electronics Engineering, Kyungpook National University, Daehakro. Bukgu, Daegu, South Korea; ALTUS-LSA, Chania, Greece; School of Metallurgy and Materials, The University of Birmingham, Edgbaston, Birmingham, United Kingdom | 59532165700; 57200782595; 8729024700; 57300809000; 57203759560; 57193198789; 7102082014; 56040282500; 57203390957; 57214791245; 57218837054; 57300514300; 8401894000; 23027607700; 57193339166; 57300514400; 57197445260; 57218837256; 57203390599; 56323321000; 9240224000; 43960934200; 59818026400; 57218834643; 6505791928 | Proceedings in Marine Technology and Ocean Engineering | 2638-647X | 2021 | 0 | 2025-07-30 | 1 | English | Final | 2021 | 10.1201/9781003134572-84 | 바로가기 | 바로가기 | |||||||||||||||||||
| ○ | Article | New Measures of Herding Behavior and Cross-sectional Time Dispersion (CSTD) by IPO Firms in Chinese IPO Markets | In this paper, we develop a new way of measuring the herding behavior of market participants and test herding behavior among investors in Chinese IPO firms, compared with prior methods of herding measure developed by Christie and Huang (1995), Chang, Chen, and Khorana (2000), and Hwang and Salmon (2009). Our proposed new non-parametric herding measure, cross sectional time dispersion (CSTD), is defined differently as dispersion in IPO issuance timing, compared with traditional definitions of herding as dispersion in IPO returns or risk measure. Traditional CSSD, CSAD and beta herding measures do not provide statistically significant or consistent relationship between the herding measures and the IPO firms’ initial or long-term returns. In contrast, the new measure of time herding, CSTD clearly and consistently indicates that investors are affected more by the herding behaviors of IPO firms than by those of investors in the IPO markets in China. © 2021, Korean Finance Association. All rights reserved. | Kim, Sunghwan; Lim, Dongmin; Kim, Jihyun | Kyungpook National University, South Korea; Gyeongsang National University, South Korea; University of Missouri-Columbia, United States | 57218341982; 58669550000; 58669680700 | indianak@knu.ac.kr; | Asian Review of Financial Research | 1229-0351 | 34 | 2 | 0 | 2025-07-30 | 0 | China; Cross-sectional Time Dispersion; CSTD; Herding; IPO; Market performance | English | Final | 2021 | 10.37197/arfr.2021.34.2.1 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | New Results from the Silicon Vertex Detector of the Belle II Experiment | The Silicon Vertex Detector (SVD) consists of four layers of double-sided silicon strip sensors. The SVD is one of the two vertex subdetectors within Belle II. Since the start of data taking in 2019 at the Super-KEKB collider (KEK, Japan), which has the highest peak-luminosity ever recorded, the SVD is operated reliably and with high efficiency, despite exposure to harsh beam background. Measurements using data show that the SVD has both high signal-to-noise ratio and hit efficiency, as well precise spatial resolution. Further these properties are stable over time. Recently the simulation has been tuned, using data, to improve the agrement between data and MC for cluster properties. The good hit-time resolution can be exploited to further improve the robustness against the higher levels of background expected as the instantaneous luminosity increases in the next years of running. First effects of radiation damage on strip noise, sensor currents and depletion voltage have been measured, although they do not have any detrimental effect on the performance of the detector. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0) | Corona, L.; Adamczyk, K.; Aggarwal, L.; Aihara, H.; Aziz, T.; Bacher, S.; Bahinipati, S.; Batignani, G.; Baudot, J.; Behera, P.K.; Bettarini, S.; Bilka, T.; Bozek, A.; Buchsteiner, F.; Casarosa, G.; Czank, T.; Das, S.B.; Dujany, G.; Forti, F.; Friedl, M.; Gabrielli, A.; Ganiev, E.; Gobbo, B.; Halder, S.; Hara, K.; Hazra, S.; Higuchi, T.; Irmler, C.; Ishikawa, A.; Jeon, H.B.; Jin, Y.; Joo, C.; Kaleta, M.; Kaliyar, A.B.; Kandra, J.; Kang, K.H.; Kapusta, P.; Kodyš, P.; Kohriki, T.; Kumar, M.; Kumar, R.; La Licata, C.; Lalwani, K.; Lee, S.C.; Libby, J.; Massaccesi, L.; Mayekar, S.N.; Mohanty, G.B.; Morii, T.; Nakamura, K.R.; Natkaniec, Z.; Onuki, Y.; Ostrowicz, W.; Paladino, A.; Paoloni, E.; Park, H.; Polat, G.; Rao, K.K.; Ripp-Baudot, I.; Rizzo, G.; Sahoo, D.; Schwanda, C.; Serrano, J.; Suzuki, J.; Tanaka, S.; Tanigawa, H.; Thalmeier, R.; Tiwari, R.; Tsuboyama, T.; Uematsu, Y.; Verbycka, O.; Vitale, L.; Wan, K.; Wang, Z.; Webb, J.; Wiechczynski, J.; Yin, H.; Zani, L. | Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Punjab Agricultural University, Ludhiana, 141004, India; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; Tata Institute of Fundamental Research, Mumbai, 400005, India; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Indian Institute of Technology, Satya Nagar, Bhubaneswar, India; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; IPHC, UMR 7178, Université de Strasbourg, CNRS, Strasbourg, 67037, France; Indian Institute of Technology Madras, Chennai, 600036, India; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Faculty of Mathematics and Physics, Charles University, Prague, 121 16, Czech Republic; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan; Malaviya National Institute of Technology, Jaipur, 302017, India; IPHC, UMR 7178, Université de Strasbourg, CNRS, Strasbourg, 67037, France; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; Dipartimento di Fisica, Università di Trieste, Trieste, I-34127, Italy, INFN Sezione di Trieste, Trieste, I-34127, Italy; Dipartimento di Fisica, Università di Trieste, Trieste, I-34127, Italy, INFN Sezione di Trieste, Trieste, I-34127, Italy; INFN Sezione di Trieste, Trieste, I-34127, Italy; Tata Institute of Fundamental Research, Mumbai, 400005, India; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan; Tata Institute of Fundamental Research, Mumbai, 400005, India; Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; INFN Sezione di Trieste, Trieste, I-34127, Italy; Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Tata Institute of Fundamental Research, Mumbai, 400005, India; Faculty of Mathematics and Physics, Charles University, Prague, 121 16, Czech Republic; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Faculty of Mathematics and Physics, Charles University, Prague, 121 16, Czech Republic; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan; Malaviya National Institute of Technology, Jaipur, 302017, India; Punjab Agricultural University, Ludhiana, 141004, India; Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan; Malaviya National Institute of Technology, Jaipur, 302017, India; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; Indian Institute of Technology Madras, Chennai, 600036, India; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Tata Institute of Fundamental Research, Mumbai, 400005, India; Tata Institute of Fundamental Research, Mumbai, 400005, India; Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa, 277-8583, Japan; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Department of Physics, Kyungpook National University, Daegu, 41566, South Korea; Aix Marseille Université, CNRS, IN2P3, CPPM, Marseille, 13288, France; Tata Institute of Fundamental Research, Mumbai, 400005, India; IPHC, UMR 7178, Université de Strasbourg, CNRS, Strasbourg, 67037, France; Dipartimento di Fisica, Università di Pisa, Pisa, I-56127, Italy, INFN Sezione di Pisa, Pisa, I-56127, Italy; Tata Institute of Fundamental Research, Mumbai, 400005, India; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; Aix Marseille Université, CNRS, IN2P3, CPPM, Marseille, 13288, France; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; Tata Institute of Fundamental Research, Mumbai, 400005, India; High Energy Accelerator Research Organization (KEK), Tsukuba, 305-0801, Japan, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; H. Niewodniczanski Institute of Nuclear Physics, Krakow, 31-342, Poland; Dipartimento di Fisica, Università di Trieste, Trieste, I-34127, Italy, INFN Sezione di Trieste, Trieste, I-34127, Italy; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; Department of Physics, University of Tokyo, Tokyo, 113-0033, Japan; School of Physics, University of Melbourne, Melbourne, 3010, VIC, Australia; INFN Sezione di Pisa, Pisa, I-56127, Italy; Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, 1050, Austria; Aix Marseille Université, CNRS, IN2P3, CPPM, Marseille, 13288, France | 57209105515; 56448523500; 57232053300; 26431253400; 57198200847; 57014918700; 35226929900; 35226921900; 7003306478; 57943353600; 55116333600; 56624583600; 57225386308; 56446995000; 36169158700; 57028463700; 57202083225; 56200044200; 35227146800; 10044712100; 57943838100; 57215857442; 35227306900; 57209094410; 57205557485; 57222816542; 57224139534; 15069585600; 35227389900; 57014196800; 59299091500; 54398896700; 57203805096; 57193274163; 57015230400; 57224903543; 24329126300; 14826956800; 35227561100; 58018872200; 55553737220; 57218128893; 46661127500; 57257924100; 55820982400; 57355100000; 55949914700; 35227732200; 57014635700; 56394864900; 35227761700; 35227766800; 35227773600; 56572518100; 35227715200; 58642658300; 57219720176; 59633046200; 35227855600; 35227845800; 57215857178; 35228014600; 35230925400; 57222040123; 57232742000; 57203804357; 56447101400; 58299015900; 16020533400; 57216843679; 57216841841; 57198320699; 57195153044; 59649324200; 57014140800; 15835927600; 57013958200; 57195150092 | luigi.corona@pi.infn.it; | Proceedings of Science | 1824-8039 | 398 | 0 | 2025-07-30 | 0 | Efficiency; Radiation damage; Signal to noise ratio; Silicon; Silicon detectors; Double sided; High signal-to-noise ratio; Higher efficiency; Hit efficiencies; KEKB collider; New results; Silicon strip sensor; Silicon Vertex Detectors; Spatial resolution; Subdetectors; Luminance | English | Final | 2021 | 바로가기 | |||||||||||||||||||
| ○ | Book chapter | Nitric oxide synthase in the plant kingdom | After the discovery of nitric oxide (NO) as an important signaling molecule in plants, its involvement has been reported in several key physiological processes. At the cellular level, slight alterations in the quantity of NO or its various adducts, also known as reactive nitrogen intermediates (RNIs), have phenomenal implications. In plants this highly reactive, diatomic gaseous molecule regulates a plethora of physiological processes ranging from development, to reproduction, and defense against biotic and abiotic stresses. In animals, NO is produced enzymatically via the nitric oxide synthase (NOS) enzyme. However, after decades of research, it is now clear that in plants there is not one but several routes for NO production. Interestingly the discovery of a NOS enzyme in plants has remained an attractive topic of research for plant scientists over the years; the enzyme still remains elusive. In this chapter we briefly discuss the different pathways responsible for NO production in plants with special emphasis on the enzymatic production. We also discuss the NOS enzyme and its presence in lower and higher plants. © 2022 Elsevier Inc. | Hussain, Adil; Imran, Qari Muhammad; Shahid, Muhammad; Yun, Byung-Wook | Department of Agriculture, Abdul Wali Khan University, Khyber Pakhtunkhwa, Mardan, Pakistan; Department of Medical Biochemistry and Biophysics, Umea University, Umea, Sweden, School of Applied Biosciences, Kyungpook National University, Daegu, South Korea; School of Applied Biosciences, Kyungpook National University, Daegu, South Korea, Agriculture Research Institute, Khyber Pakhtunkhwa, Mingora, Pakistan; School of Applied Biosciences, Kyungpook National University, Daegu, South Korea | 41961162600; 55849263700; 59577718600; 8245123600 | Nitric Oxide in Plant Biology: An Ancient Molecule with Emerging Roles | 1.97 | 2025-07-30 | 5 | Nitric oxide (NO); NO production in plants; NO synthase (NOS); Reactive nitrogen intermediates (RNIs) | English | Final | 2021 | 10.1016/b978-0-12-818797-5.00016-9 | 바로가기 | 바로가기 |
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