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SSRN 2024年

作者： Jin, Juyoung Bang, Hyojin Kim, Seungyeon Yang, Hee Yun Bae, Sukang Yu, Seung Min Kim, Yonghun Kwon, Jung-Dae Kim, Hong Seung Kim, Tae-Wook Yoon, Jongwon Department of Flexible and Printable Electronics LANL-JBNU Engineering Institute-Korea Jeonbuk National University Jeollabuk-do Jeonju54896 Korea Republic of Energy & Environments Materials Research Division Korea Institute of Materials Science Gyeongsangnam-do Changwon-si51508 Korea Republic of College of Engineering Major of Nano-Semiconductor Engineering Korea Maritime & Ocean University Busan49112 Korea Republic of Functional Composite Materials Research Center Institute of Advanced Composite Materials Korea Institute of Science and Technology Jellabuk-do 55324 Korea Republic of Department of JBNU-KIST Industry-Academia Convergence Research Jeonbuk National University Jeollabuk-do Jeonju54896 Korea Republic of Jeonju Center Korea Basic Science Institute Jeollabuk-do Jeonju54907 Korea Republic of

The sensitive and selective detection of ammonia (NH3) gas at sub-ppm level and room temperature has attracted significant attention due to its promising applications in environment monitoring and medical diagnosis. Furthermore, these applications require flexible and wearable functionalities for both potential and practical use. Here, we report an NH3 gas sensor based on a porous copper bromide (CuBr) film, converted from the two-dimensional (2D) copper nanosheets (Cu NSs). The porous CuBr film as a sensing material is prepared by an all-solution and vacuum-free process at low temperature, enabling device fabrication on a plastic substrate. The optimized gas sensor, achieved by controlling the morphology and surface coverage of the porous CuBr film, exhibits a sensitive and selective NH3 gas response at sub-ppm levels and room temperature. The mechanical bending test over 1000 bending cycles at a bending radius (r) of 2 mm reveals the feasibility of flexible and wearable applications. © 2024, The Authors. All rights reserved.

关键词： Gas detectors

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Enhanced climate variability during the last millennium recorded in alkenone sea surface temperatures of the northwest Pacific margin

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Global and Planetary Change 2021年 204卷

作者： Lee, Kyung Eun Park, Wonsun Yeh, Sang-Wook Bae, Si Woong Ko, Tae Wook Lohmann, Gerrit Nam, Seung-Il Department of Ocean Science Korea Maritime and Ocean University Busan Korea Republic of Ocean Science and Technology School Korea Maritime and Ocean University Busan Korea Republic of GEOMAR Helmholtz Centre for Ocean Research Kiel Kiel24105 Germany Department of Marine Science and Convergence Engineering Hanyang University ERICA Seoul15588 Korea Republic of Alfred-Wegener-Institute Bremerhaven27570 Germany Arctic Research Center Korea Polar Research Institute Incheon Korea Republic of

Previous studies on surface temperature reconstructions for the last 2000 years (2 k) revealed a long-term cooling trend for the last millennium in comparison to the previous millennium. However, knowledge on the decadal- to centennial-scale variability in sea surface temperature and the underlying governing mechanisms throughout the period is limited. We reconstructed high-resolution continuous sea surface temperature changes over the last 2 k in the northwest Pacific margin based on the alkenone unsaturation index. Our alkenone temperature record revealed enhanced and more rapidly changing climate variability during the last millennium (approximately 1200–1850 Common Era) than during the previous millennium. Cold and hot extremes also occurred more frequently during the last millennium. The enhanced and rapidly changing climate variability appears to be associated with frequent volcanic eruptions and grand solar minima. The reconstructed surface temperature variability tends to be associated with variations in the East Asia summer monsoon and the Pacific Decadal Oscillation, implying that these variations are also enhanced in the last millennium than in the previous millennium. © 2021 Elsevier B.V.

关键词： Surface temperature

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Highly Linear Relationship Between Nanocomposite Film Thickness and Sensitivity in Mercury Ion Plastic Optical Fiber Sensor

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Tsai, Yao-Tung Lee, Yong Wook Chiang, Chia-Chin Hsu, Yi-Ting Tsai, Liren Wen, Hsin-Yi National Kaohsiung University of Science and Technology Department of Mechanical Engineering Kaohsiung80778 Taiwan Pukyong National University School of Electrical Engineering 45 Yongso-ro nam-gu Busan48513 Korea Republic of Pukyong National University Industry4.0 Convergence Bionics Engineering 45 Yongso-ro Nam-gu Busan48513 Korea Republic of National Kaohsiung University of Science and Technology Department of Chemical and Materials Engineering Kaohsiung80778 Taiwan

This study introduces a novel plastic optical fiber probe for detecting mercury ions in solution. The sensor is designed to be cost-effective and enhance sensing capabilities by applying a layer of nanocomposite film to the end face of the plastic optical fiber. This film is composed of silver nanoparticles (AgNPs) molecularly imprinted with sodium alginate (SA) and embedded in polyvinyl alcohol (PVA). The research reveals a strong correlation between the thickness of the coated film and the sensor's sensitivity. The results demonstrate that with a film thickness of 5.2 μm, the probe exhibits a wavelength sensitivity of 303.825 a.u./ppm and a high linearity of 0.955 within the mercury ion concentration range of 0.01 ppm to 10 ppm. Furthermore, the study discovers a highly linear relationship between film thickness and sensitivity, reaching a value of 0.975. This research is consistent with development of Nations Sustainable Development Goal SDG 3. © 1963-2012 IEEE.

关键词： Green development

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Li Reaction Pathways in Ge and High-Performance Ge Nanocomposite Anodes for Li-Ion Batteries

SSRN

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SSRN 2022年

作者： Lee, Dong-Hun Kim, Do-Hyeon Jung, Heechul Park, Cheol-Min School of Materials Science and Engineering Kumoh National Institute of Technology 61 Daehak-ro Gumi Gyeongbuk 39177 Korea Republic of Electrode Group 1 Samsung SDI 130 Samsung-ro Gyeoggi-do Suwon-si16678 Korea Republic of Department of Energy Engineering Convergence Kumoh National Institute of Technology 61 Daehak-ro Gumi Gyeongbuk 39177 Korea Republic of Department of Energy and Mineral Resources Engineering Dong-A University Saha-gu Busan49315 Korea Republic of

Ge is a highly researched anode material for Li-ion batteries (LIBs) owing to its high theoretical Li storage capacity and higher electrical conductivity compared to that of Si. However, Li reaction pathways in Ge have not been definitively established due to the formation of various and complicated Li-Ge alloy phases during lithiation/delithiation. Evaluation of the Li storage characteristics of bulk and nanocrystalline Ge demonstrated that nanocrystalline Ge showed higher Li reversibility than bulk Ge. Various cutting-edge ex situ techniques were used to analyze nanocrystalline Ge, and the Li reaction pathways in Ge were thoroughly demonstrated. To enhance the electrochemical Li storage characteristics of Ge, a Ge-based nanocomposite, Ge/Al 2 O 3 /C, was synthesized via simple one-pot mechanical solid-state reduction using GeO 2 , Al, and C. Ge/Al 2 O 3 /C exhibited very stable cyclic behavior at a current density of 100 mA g −1 over 300 cycles (capacity retention after 300 cycles: ~95%). Moreover, Ge/Al 2 O 3 /C exhibited excellent rate capability with high reversible capacity and stable cyclic behavior at a high 1C-rate. The superior electrochemical performance of Ge/Al 2 O 3 /C was attributed to the nanoscale dimensions of Li-active nanocrystalline Ge (~10 nm) and Li-inactive Al 2 O 3 (~12 nm) embedded uniformly in the amorphous carbon matrices. The size of nanocrystalline Ge in nanocomposite was consistently maintained during repeated cycles owing to the anti-agglomeration effect of the uniformly distributed Li-inactive Al 2 O 3 and amorphous carbon matrices. We anticipate that the electrochemical Li reaction pathways in Ge and the resulting high-performance nanocomposite anodes will be highly useful in investigating high-performance Ge-based anodes for LIBs. © 2022, The Authors. All rights reserved.

关键词： Nanocomposites

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Sum-rate maximization for UAV-assisted visible light communications using NOMA: Swarm intelligence meets machine learning

arXiv

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arXiv 2021年

作者： Pham, Quoc-Viet Huynh-The, Thien Alazab, Mamoun Zhao, Jun Hwang, Won-Joo Research Institute of Computer Information and Communication Pusan National University Busan46241 Korea Republic of ICT Convergence Research Center Kumoh National Institute of Technology Gyeongsangbuk-do39177 Korea Republic of College of Engineering IT and Environment Charles Darwin University CasuarinaNT0810 Australia School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Department of Biomedical Convergence Engineering Pusan National University Busan46241 Korea Republic of

As the integration of unmanned aerial vehicles (UAVs) into visible light communications (VLC) can offer many benefits for massive-connectivity applications and services in 5G and beyond, this work considers a UAV-assisted VLC using non-orthogonal multiple-access. More specifically, we formulate a joint problem of power allocation and UAV’s placement to maximize the sum rate of all users, subject to constraints on power allocation, quality of service of users, and UAV’s position. Since the problem is non-convex and NP-hard in general, it is difficult to be solved optimally. Moreover, the problem is not easy to be solved by conventional approaches, e.g., coordinate descent algorithms, due to channel modeling in VLC. Therefore, we propose using harris hawks optimization (HHO) algorithm to solve the formulated problem and obtain an efficient solution. We then use the HHO algorithm together with artificial neural networks to propose a design which can be used in real-time applications and avoid falling into the "local minima" trap in conventional trainers. Numerical results are provided to verify the effectiveness of the proposed algorithm and further demonstrate that the proposed algorithm/HHO trainer is superior to several alternative schemes and existing metaheuristic algorithms. © 2021, CC BY.

关键词： Neural networks

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Carbon burial in sediments below seaweed farms matches that of Blue Carbon habitats (vol 15, pg 180, 2025)

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NATURE CLIMATE CHANGE 2025年第4期15卷 458-458页

作者： Duarte, Carlos M. Delgado-Huertas, Antonio Marti, Elisa Gasser, Beat Martin, Isidro San Cousteau, Alexandra Neumeyer, Fritz Reilly-Cayten, Megan Boyce, Joshua Kuwae, Tomohiro Hori, Masakazu Miyajima, Toshihiro Price, Nichole N. Arnold, Suzanne Ricart, Aurora M. Davis, Simon Surugau, Noumie Abdul, Al-Jeria Wu, Jiaping Xiao, Xi Chung, Ik Kyo Choi, Chang Geun Sondak, Calvyn F. A. Albasri, Hatim Krause-Jensen, Dorte Bruhn, Annette Boderskov, Teis Hancke, Kasper Funderud, Jon Borrero-Santiago, Ana R. Pascal, Fred Joanne, Paul Ranivoarivelo, Lanto Collins, William T. Clark, Jennifer Gutierrez, Juan Fermin Riquelme, Ricardo Avila, Marcela Macreadie, Peter I. Masque, Pere Marine Science Program Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia Andalusian Earth Sciences Institute CSIC and Universidad de Granada Armilla Spain Departamento de Biología Recursos Naturales y Medio Ambiente Instituto Universitario de Investigación Marina (INMAR) University of Cadiz Puerto Real Spain Radioecology Laboratory International Atomic Energy Agency—Marine Environment Laboratories (IAEA-MEL) Principality of Monaco Monaco School of Science and Centre for Marine Ecosystems Research Edith Cowan University Joondalup Western Australia Australia Oceans 2050 Foundation Berlin Germany Coastal and Estuarine Environment Research Group Port and Airport Research Institute Yokosuka Japan Coastal Fisheries and Ecosystems Group Japan Fisheries Research and Education Agency Yokohama Japan Atmosphere and Ocean Research institute University of Tokyo Kashiwa Japan Environmental Sciences Colby College Waterville MA USA Bigelow Laboratory for Ocean Sciences East Boothbay MA USA Island Institute Rockland MA USA Seaweed Research Unit Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Seadling Kota Kinabalu Sabah Malaysia Ocean College Zhejiang University Zhoushan China Department of Oceanography Pusan National University Busan Korea Department of Ecological Engineering Pukyong National University Busan Korea Faculty of Fisheries and Marine Science Sam Ratulangi University Manado Indonesia Research Center for Fisheries National Research and Innovation Agency Jakarta Indonesia Department of Ecoscience Aarhus University Aarhus Denmark Centre for Circular Bioeconomy Aarhus University Aarhus Denmark Norwegian Institute for Water Research Oslo Norway Seaweed Solutions AS Trondheim Norway Ocean Farmers Toliara Madagascar Institute of Fisheries and Marine Science University of Toliara Toliara Madagascar Cascadia Seaweed Sydney British Columbia

Seaweed farming has emerged as a potential Blue Carbon strategy, yet empirical estimates of carbon burial from such farms remain lacking in the literature. Here, we quantify carbon burial in 20 seaweed farms distributed globally, ranging from 2 to 300 years in operation and from 1 to 15,000 ha in size. The thickness of sediment layers and stocks of organic carbon accumulated below the farms increased with farm age, reaching 140 tC ha−1for the oldest farm. Organic carbon burial rates averaged 1.87 ± 0.73 tCO2e ha−1yr−1in farm sediments, twice that in reference sediments. The excess CO2e burial attributable to the seaweed farms averaged 1.06 ± 0.74 CO2e ha−1yr−1, confirming that seaweed farming in depositional environments buries carbon in the underlying sediments at rates towards the low range of that of Blue Carbon habitats, but increasing with farm age.

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Artificial intelligence based real-time microcirculation analysis system for laparoscopic colorectal surgery

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World Journal of Gastroenterology 2020年第44期26卷 6945-6962页

作者： Sang-Ho Park Hee-Min Park Kwang-Ryul Baek Hong-Min Ahn In Young Lee Gyung Mo Son Department of Electronic Engineering Pusan National UniversityBusan 46241South Korea Department of Surgery Pusan National University Yangsan HospitalGyeongsangnam-do 50612South Korea Department of Medicine Pusan National UniversityGyeongsangnam-do 50612South Korea Department of Surgery Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and TechnologyPusan National University Yangsan HospitalYangsan-si 50612South Korea

BACKGROUND Colonic perfusion status can be assessed easily by indocyanine green(ICG)angiography to predict ischemia related anastomotic complications during laparoscopic colorectal ***,various parameter-based perfusion analysis have been studied for quantitative evaluation,but the analysis results differ depending on the use of quantitative parameters due to differences in vascular anatomical ***,it can help improve the accuracy and consistency by artificial intelligence(AI)based real-time analysis microperfusion(AIRAM).AIM To evaluate the feasibility of AIRAM to predict the risk of anastomotic complication in the patient with laparoscopic colorectal cancer *** The ICG curve was extracted from the region of interest(ROI)set in the ICG fluorescence video of the laparoscopic colorectal ***-processing was performed to reduce AI performance degradation caused by external environment such as background,light source reflection,and camera shaking using MATLAB 2019 on an I7-8700k Intel central processing unit(CPU)*** learning and evaluation were performed by dividing into a training patient group(n=50)and a test patient group(n=15).Training ICG curve data sets were classified and machine learned into 25 ICG curve patterns using a self-organizing map(SOM)*** predictive reliability of anastomotic complications in a trained SOM network is verified using test *** AI-based risk and the conventional quantitative parameters including T1/2max,time ratio(TR),and rising slope(RS)were consistent when colonic perfusion was favorable as steep increasing ICG curve *** the ICG graph pattern showed stepped rise,the accuracy of conventional quantitative parameters decreased,but the AI-based classification maintained accuracy *** receiver operating characteristic curves for conventional parameters and AI-based classification were comparable for predicting the anastomotic complication *** pe

关键词： Indocyanine green Laparoscopic Artificial intelligent Anastomotic complications Colorectal surgery Microcirculation analysis

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Generation and propagation of 21-day bottom pressure variability driven by wind stress curl in the East China Sea

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Acta Oceanologica Sinica 2020年第7期39卷 91-106页

作者： Hua Zheng Xiao-Hua Zhu Hirohiko Nakamura Jae-Hun Park Chanhyung Jeon Ruixiang Zhao Ayako Nishina Chuanzheng Zhang Hanna Na Ze-Nan Zhu Hong-Sik Min State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China School of Oceanography Shanghai Jiao Tong UniversityShanghai 200030China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Faculty of Fisheries Kagoshima UniversityKagoshima 8900056Japan Department of Ocean Sciences Inha UniversityIncheon 22212Korea Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridge 02139USA School of Earth and Environmental Sciences Seoul National UniversitySeoul 08826Korea Ocean Circulation and Climate Research Center Korea Institute of Ocean Science and TechnologyBusan 49111Korea

Between June 2015 and June 2017,two pressure-recording inverted echo sounders(PIESs)and five current and pressure-recording inverted echo sounders(CPIESs)deployed along a section across the Kerama Gap acquired a dataset of ocean bottom pressure records in which there was significant 21-day variability(Pbot21).The Pbot21,which was particularly strong from July-December 2016,was coherent with wind stress curl(WSC)on the continental shelf of the East China Sea(ECS)with a squared coherence of 0.65 for a 3-day time lag.A barotropic ocean model demonstrated the generation,propagation,and dissipation of *** modeled results show that the Pbot21 driven by coastal ocean WSC in the ECS propagated toward the Ryukyu Island Chain(RIC),while deep ocean WSC could not induce such *** the continental shelf,the Pbot21 was generated nearly synchronously with the WSC from the coastline to the southeast but dissipated within a few days due to the effect of bottom *** detection of Pbot21 by the moored array was dependent on the 21-day WSC patterns on the continental *** Pbot21 driven southeast of the Changjiang Estuary by the WSC was detected while the Pbot21generated northeast of the Changjiang Estuary was not.

关键词： pressure-recording inverted echo sounder East China Sea bottom pressure wind stress curl

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Deep learning for intelligent demand response and smart grids: A comprehensive survey

arXiv

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arXiv 2021年

作者： Prabadevi, B. Pham, Quoc-Viet Liyanage, Madhusanka Deepa, N. Mounik, V.V.S.S. Reddy, Shivani Reddy Maddikunta, Praveen Kumar Khare, Neelu Reddy Gadekallu, Thippa Hwang, Won-Joo The School of Information Technology Vellore Institute of Technology Tamil Nadu632014 India The Research Institute of Computer Information and Communication Pusan National University Busan46241 Korea Republic of The School of Computer Science University Collage Dublin Ireland and Centre for Wireless Communications University of Oulu Finland The Computer Science and Engineering Indian Institute of Technology Madras India The School of Electronics and Communication Engineering Vellore Institute of Technology Tamil Nadu632014 India The Department of Biomedical Convergence Engineering Pusan National University Yangsan50612 Korea Republic of

Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such as power generation (e.g., wind turbines), transmission and distribution (microgrids and fault detectors), load management (smart meters and smart electric appliances). Thanks to recent advancements in big data and computing technologies, Deep Learning (DL) can be leveraged to learn the patterns from the generated data and predict the demand for electricity and peak hours. Motivated by the advantages of deep learning in smart grids, this paper sets to provide a comprehensive survey on the application of DL for intelligent smart grids and demand response. Firstly, we present the fundamental of DL, smart grids, demand response, and the motivation behind the use of DL. Secondly, we review the state-of-the-art applications of DL in smart grids and demand response, including electric load forecasting, state estimation, energy theft detection, energy sharing and trading. Furthermore, we illustrate the practicality of DL via various use cases and projects. Finally, we highlight the challenges presented in existing research works and highlight important issues and potential directions in the use of DL for smart grids and demand response. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

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Virtuous utilization of carbon dioxide in pyrolysis of polylactic acid

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Chemical engineering Journal 2023年第1期466卷

作者： Cho, Seong-Heon Kim, Youkwan Lee, Sangyoon Andrew Lin, Kun-Yi Chen, Wei-Hsin Jung, Sungyup Lee, Doyeon Hyun Moon, Deok Jeon, Young Jae Kwon, Eilhann E. Department of Earth Resources and Environmental Engineering Hanyang University Seoul04763 Korea Republic of Department of Environmental Engineering & Innovation and Development Center of Sustainable Agriculture National Chung Hsing University 250 Kuo-Kuang Road Taichung Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Department of Environmental Engineering Kyungpook National University Daegu41566 Korea Republic of Department of Civil and Environmental Engineering Hanbat National University Daejeon34158 Korea Republic of Department of Environmental Engineering Chosun University Gwangju61452 Korea Republic of Department of Microbiology Pukyong National University Busan48513 Korea Republic of School of Marine and Fisheries Life Science Pukyong National University Busan48513 Korea Republic of

Polylactic acid has been adopted as a strategic alternative to petroplastics because of its biodegradability. The waste generation rate could be proportional to its use, considering the short lifespan of polylactic acid. However, a practical disposal or recycling protocol for polylactic acid waste has not yet been developed. Thus, this study suggests a promising thermochemical platform for valorizing polylactic acid waste into energy resources (syngas). Specifically, carbon dioxide-assisted pyrolysis has been suggested to impart environmental features to polylactic acid disposal. Before the pyrolysis tests, the polylactic acid waste sample was characterized by Fourier transform-infrared spectrometer and thermogravimetric analyses, which showed that polylactic acid contained a substantial amount of additives and impurities (∼13 wt%). The impurity containing polylactic acid was converted into pyrogenic gases and biocrudes through pyrolysis process. The pyrolysis was performed under carbon dioxide condition and led to enhanced carbon monoxide formation from simultaneous homogeneous reactions between CO2 and volatile organic compounds evolved from thermal degradation of polylactic acid. CO2 was reduced and the volatile compounds were oxidized. The evolution of carbon monoxide from pyrolysis under carbon dioxide condition was 2 times higher than that from nitrogen condition. The concentration of carbon monoxide from the pyrolysis of polylactic acid waste with respect to plastics and biomass was considerably higher. This observation indicates that the susceptibility of carbon dioxide to the homogeneous reaction is highly sensitive. To seek a way to hasten the homogeneous reaction, silica supported nickel catalysts were applied. The evolution of carbon monoxide from catalytic pyrolysis under carbon dioxide condition was 4.5 times higher than inert atmosphere. © 2023 Elsevier B.V.

关键词： Carbon dioxide

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