연구성과로 돌아가기
2024 연구성과 (185 / 286)
※ 컨트롤 + 클릭으로 열별 다중 정렬 가능합니다.
Excel 다운로드
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ○ | ○ | Article | Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration | The discomfort caused by whole-body vibration (WBV) has long been assessed using subjective surveys or objective measurements of body acceleration. However, surveys have the disadvantage that some of participants often express their feelings in a capricious manner, and acceleration data cannot take into account individual preferences and experiences of their emotions. In this study, we investigated vibration-induced mental stress using the electroencephalogram (EEG) of 22 seated occupants excited by random vibrations. Between the acceleration and the EEG signal, which contains electrical noise due to the head shaking caused by random vibrations, we found that there was a strong correlation, which acts as an artifact in the EEG, and therefore we removed it using an adaptive filter. After removing the artifact, we analyzed the characteristics of the brainwaves using topographic maps and observed that the activities detected in the frontal electrodes showed significant differences between the static and vibration conditions. Further, frontal alpha asymmetry (FAA) and relative band power indices in the frontal electrodes were analyzed statistically to assess mental stress under WBV. As the vibration level increased, EEG analysis in the frontal electrodes showed a decrease in FAA and alpha power but an increase in gamma power. These results are in good agreement with the literature in the sense that FAA and alpha band power decreases with increasing stress, thus demonstrating that WBV causes mental stress and that the stress increases with the vibration level. EEG assessment of stress during WBV is expected to be used in the evaluation of ride comfort alongside existing self-report and acceleration methods. | Song, Byoung-Gyu; Kang, Namcheol | Kyungpook Natl Univ, Dept Mech Engn, Daegu, South Korea; Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea | 57211027939; 24830970900 | nckang@knu.ac.kr; | FRONTIERS IN NEUROSCIENCE | FRONT NEUROSCI-SWITZ | 1662-453X | 18 | SCIE | NEUROSCIENCES | 2024 | 3.2 | 41.2 | 0 | 2025-04-16 | 1 | 1 | adaptive filter; electroencephalogram; mental stress; movement artifact; whole-body vibration | SEATED HUMAN-BODY; VERTICAL VIBRATION; FREQUENCY; FRAMEWORK; EMG | adaptive filter; electroencephalogram; mental stress; movement artifact; whole-body vibration | acceleration; adult; alpha power; Article; artifact; assessment of humans; audiometry; controlled study; electrical noise; electroencephalogram; electroencephalography; electromyography; emotion; eye movement; female; frontal lobe; gamma power; head movement; human; human experiment; male; mathematical analysis; mental stress; muscle contraction; neurophysiological monitoring; normal human; physiological stress; power spectrum; random excitation; signal noise ratio; signal processing; skin conductance; spectral density; topography; vibration; whole body vibration; young adult | English | 2024 | 2024-04-25 | 10.3389/fnins.2024.1328704 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | Meeting Abstract | The population structure of Bursaphelenchus xylophilus and insect-associated nematodes occurring in natural pinewood nematode-infested dead pine tree stands in island areas | Okki, Mwamula Abraham; Lee, S. M.; Jung, Y. H.; Kim, Y. S.; Lee, D. W. | Kyungpook Natl Univ, Res Inst Invertebrate Vector, Sangju 37224, South Korea; SM Biovis Co, Jinju 52849, South Korea; Kyungpook Natl Univ, Dept Entomol, Sangju 37224, South Korea | JOURNAL OF NEMATOLOGY | J NEMATOL | 0022-300X | 2640-396X | 56 | 1 | SCIE | ZOOLOGY | 2024 | 1.3 | 41.2 | 0 | English | 2024 | 2024-03-01 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | ○ | Article | Application of Deep Neural Networks for the Parameter Identifications of Lumped and Distributed Parameter Models Under Severe Noises and Various Initial Values | PurposeIdentifying unknown parameters has long been significant in the field of engineering, as they can be used for fault diagnosis and the development of numerical models. This study aims to determine the unknown parameters of mechanical models by applying deep neural networks (DNNs) using frequency-response functions (FRFs).MethodsThe proposed network consists of several DNNs that estimate unknown parameters. The inputs of the DNNs requires the initial values of the unknowns. The estimated parameters by the DNNs were used to calculate the outputs. The magnitude and phase of the FRF obtained from an experiment were used as target data. To optimize the performance of the DNNs, Bayesian optimization is employed to search for appropriate weight factors in the loss function and hyperparameters in the DNNs. Additionally, the estimated parameters were adopted as the optimal parameters after the difference between the output and target data satisfied the stopping criterion.ResultsThe performance of the DNN-based method was confirmed for lumped and distributed parameter models with noise, which could significantly challenge the parameter identification. The proposed method showed high accuracy within 5% for both models and was validated in terms of convergence by simulations and experiments. Furthermore, we compared the proposed method with the conventional optimization methods across various noise levels and initial values.ConclusionThe proposed method successfully estimated unknown parameters under severe noise and initial conditions compared with the other methods. | Song, Byoung-Gyu; Kang, Namcheol | Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea | 57211027939; 24830970900 | nckang@knu.ac.kr; | JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES | J VIB ENG TECHNOL | 2523-3920 | 2523-3939 | 12 | 3 | SCIE | ENGINEERING, MECHANICAL;MECHANICS | 2024 | 2.4 | 41.5 | 0 | 2025-05-07 | 1 | 1 | Parameter identification; Deep neural network (DNN); Frequency response function (FRF); Lumped and distributed parameter model; Impact hammer test | FAULT-DIAGNOSIS; VECTOR MACHINE; WIND TURBINES; DECOMPOSITION; BEARINGS; SUPPORT; MAINTENANCE | Deep neural network (DNN); Frequency response function (FRF); Impact hammer test; Lumped and distributed parameter model; Parameter identification | English | 2024 | 2024-03 | 10.1007/s42417-023-01074-5 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Advancing Ancient Artifact Character Image Augmentation through Styleformer-ART for Sustainable Knowledge Preservation | The accurate detection of ancient artifacts is very crucial in recognizing and tracking the origin of these relics. The methodologies used in engraving characters onto these objects are different from the ones used in the modern era, prompting the need to develop tools that are accurately tailored to detect these characters. The challenge encountered in developing an object character recognition model for this purpose is the lack of sufficient data needed to train these models. In this work, we propose Styleformer-ART to augment the ancient artifact character images. To show the performance of Styleformer-ART, we compared Styleformer-ART with different state-of-the-art data augmentation techniques. To make a conclusion on the best augmentation method for this special dataset, we evaluated all the augmentation methods employed in this work using the Fr & eacute;tchet inception distance (FID) score between the reference images and the generated images. The methods were also evaluated on the recognition accuracy of a CNN model. The Styleformer-ART model achieved the best FID score of 210.72, and Styleformer-ART-generated images achieved a recognition accuracy with the CNN model of 84%, which is better than all the other reviewed image-generation models. | Suleiman, Jamiu T.; Jung, Im Y. | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | 58571666300; 18037522200 | jamiu.suleiman111@gmail.com;iyjung@ee.knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 15 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.41 | 2025-05-07 | 1 | 1 | imprinted ship characters; automatic recognition; recognition accuracy; dataset augmentation; machine learning classifiers | automatic recognition; dataset augmentation; imprinted ship characters; machine learning classifiers; recognition accuracy | accuracy assessment; artifact; instrumentation; machine learning; tracking | English | 2024 | 2024-08 | 10.3390/su16156455 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | An Intelligent Hybrid Machine Learning Model for Sustainable Forecasting of Home Energy Demand and Electricity Price | Home energy systems (HESs) face challenges, including high energy costs, peak load impact, and reliability issues associated with grid connections. To address these challenges, homeowners can implement solutions such as energy management, renewable resources, and energy storage technologies. Understanding consumption patterns and optimizing HES operations are crucial for effective energy management. As a primary step, addressing these concerns requires an efficient forecasting tool to predict home energy demand and electricity prices. Due to the complexity of big data, and uncertainties involved in forecasting, machine learning (ML) methods are necessary. In this study, we develop a hybrid machine learning approach, utilizing one year of data on home energy demand and prices to address the challenge of forecasting home energy consumption. A comprehensive comparison of different deep and non-deep ML models highlights the superiority of the proposed hybrid approach. The performance of these models, measured using metrics such as RMSE, MAE, R2, and RT (running time), are compared. Finally, an optimized hybrid XGBoost (XGB) ML model that combines price and energy demand forecasting is introduced. The proposed ML method's parameters are optimally determined using Particle Swarm Optimization. The hybrid ML model's performance is evaluated in predicting both energy demand and consumption prices using historical data from diverse households with various features and consumption patterns. The results indicate that the hybrid ML model achieves accurate predictions for energy consumption and prices, with improvements in RMSE (up to 36.6%), MAE (up to 36.8%), and R2 (up to 3.9), as compared to conventional ML methods. This research contributes to sustainable energy practices by providing an effective tool for forecasting energy consumption and associated costs in the dynamic landscape of home energy systems. | Parizad, Banafshe; Ranjbarzadeh, Hassan; Jamali, Ali; Khayyam, Hamid | RMIT Univ, Sch Engn, Melbourne 3000, Australia; Deakin Univ, Sch Engn, Geelong 3217, Australia; Kyungpook Natl Univ, Sch Elect Engn, Dept Artificial Intelligence, Daegu 37224, South Korea | ; Jamali, Ali/AAX-5841-2020 | 58962438600; 54409212100; 13805822900; 26422988300 | s4023374@student.rmit.edu.au;hranjbar@deakin.edu.au;alijamali@knu.ac.kr;hamid.khayyam@rmit.edu.au; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 6 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.81 | 2025-05-07 | 4 | 5 | hybrid machine learning; intelligent optimization; XGBoost; energy demand forecast; renewable energy; home energy demand | SHORT-TERM LOAD; NEURAL-NETWORK; CONSUMPTION; ALGORITHM; PREDICTION | energy demand forecast; home energy demand; hybrid machine learning; intelligent optimization; renewable energy; XGBoost | alternative energy; complexity; demand analysis; electricity generation; energy management; energy market; forecasting method; machine learning; optimization; sustainability | English | 2024 | 2024-03 | 10.3390/su16062328 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Are South Korea's Environmental Policies Rational? An Analysis Focusing on Fine Dust Programs in the Seoul Metropolitan Area | Since 2018, the government of South Korea has strengthened its environmental policies to solve the problem of fine particulate matter in the air. Because of these strict regulations, diesel cars have been replaced with cleaner vehicles, and coal power plants have been shut down. Despite these government efforts, some researchers assert that fine dust programs have failed in Seoul, the capital of Korea. In other words, they conclude that the central and local governments designed and implemented the policies unreasonably. Despite these critics, this study attempts to prove that the government has thoroughly and meticulously prepared its policies on fine particles. Also, it tries to demonstrate that the policy scheme has been properly established. To attain these research goals, the theory of procedural rationality is adopted and utilized. As a result of the analysis, six steps of procedural rationality were identified in the Korean policy on fine dust: problem identification, goal setting, searching for alternatives, consequence prediction, comparison of alternatives, and policy decision. In conclusion, this study provides suggestions for environmental policies in other metropolitan cities, especially in developing countries that suffer from severe air pollution. | Jin, Sang-hyeon | Kyungpook Natl Univ, Res Inst Publ Affairs, Sch Publ Adm, Daegu 41566, South Korea | Jin, Sang-Hyeon/AFU-7621-2022 | 55587091300 | upperhm@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 15 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.41 | 2025-05-07 | 1 | 1 | procedural rationality; environmental Kuznets curve; path dependency; air pollution; fine dust | ECONOMIC-GROWTH; KUZNETS CURVE; STREAMS; MODEL | air pollution; environmental Kuznets curve; fine dust; path dependency; procedural rationality | Seoul [South Korea]; South Korea; atmospheric pollution; dust; environmental policy; local government; metropolitan area; particulate matter; policy implementation | English | 2024 | 2024-08 | 10.3390/su16156293 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Biosorption of Cd(II), Co(II), and Cu(II) onto Microalgae under Acidic and Neutral Conditions | The biosorption of Cd, Co, and Cu onto three microalgae species (Chlorella vulgaris, Scenedesmus sp., and Spirulina platensis) was compared to determine the microalgae's capability for heavy metal adsorption in acidic and neutral environments. The Langmuir, Freundlich, and Dubinin-Radushkevich isotherm models were used to characterize the adsorption of the heavy metals onto microalgae. The maximum adsorption capacity (q(max)) determined using the Langmuir and D-R model showed results in the order of Cu > Co > Cd in both acidic and neutral conditions. A shift from acidic to neutral conditions increased the microalgae's adsorption affinity for heavy metals, as determined using the Freundlich parameter (K-F). The adsorption affinity of the biomass for Cd and Co was in the order S. platensis > C. vulgaris > Scenedesmus sp. while that of Cu was in the order C. vulgaris > Scenedesmus sp. > S. platensis. In addition, it was found that the adsorption of Cd and Co enhanced the production of Dissolved Organic Content (DOC) as a byproduct of biosorption, whereas the adsorption of Cu appeared to suppress the generation of DOC. The mean adsorption energy (E) values computed by the D-R model were less than 8 (kJ/mol), indicating that physisorption was the primary force of sorption in both acidic and neutral settings. The findings of this study suggest that microalgae may be used as a low-cost adsorbent for metal removal from industrial effluent. | Phiri, Jesse T.; Oh, Sanghwa | Kyungpook Natl Univ, Sch Architectural Civil Environm & Energy Engn, Daegu 41566, South Korea | 57236845700; 26665620700 | jesset.phiri@knu.ac.kr;shoh@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 15 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.81 | 2025-05-07 | 3 | 2 | biosorption; heavy metals; microalgae; adsorption models; acidic environment; neutral environment | AQUEOUS-SOLUTION; WATER-QUALITY; METAL-IONS; REMOVAL; ADSORBENT; CADMIUM; CONTAMINATION; EQUILIBRIUM; ADSORPTION; SORPTION | acidic environment; adsorption models; biosorption; heavy metals; microalgae; neutral environment | acid neutralization; adsorption; byproduct; dissolved organic matter; heavy metal; isotherm; microalga | English | 2024 | 2024-08 | 10.3390/su16156342 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Changes in Wuhan's Carbon Stocks and Their Spatial Distributions in 2050 under Multiple Projection Scenarios | Urbanization in the 21st century has reshaped carbon stock distributions through the expansion of cities. By using the PLUS and InVEST models, this study predicts land use and carbon stocks in Wuhan in 2050 using three future scenarios. Employing local Moran's I, we analyze carbon stock clustering under these scenarios, and the Getis-Ord Gi* statistic identifies regions with significantly higher and lower carbon-stock changes between 2020 and 2050. The results reveal a 2.5 Tg decline in Wuhan's carbon stock from 2000 to 2020, concentrated from the central to the outer city areas along the Yangtze River. By 2050, the ecological conservation scenario produced the highest carbon stock prediction, 77.48 Tg, while the economic development scenario produced the lowest, 76.4 Tg. High-carbon stock-change areas cluster in the north and south, contrasting with low-change area concentrations in the center. This research provides practical insights that support Wuhan's sustainable development and carbon neutrality goals. | Zhang, Yujie; Wang, Xiaoyu; Zhang, Lei; Xu, Hongbin; Jung, Taeyeol; Xiao, Lei | Kyungpook Natl Univ, Dept Landscape Architecture, Daegu 41566, South Korea; South China Univ Technol, Sch Architecture, Dept Landscape Architecture, Guangzhou 510641, Peoples R China; Inner Mongolia Acad Forestry, Hohhot 010010, Peoples R China; State Key Lab Subtrop Bldg & Urban Sci, Guangzhou 510641, Peoples R China; Guangzhou Key Lab Landscape Architecture, Guangzhou 510641, Peoples R China | 57932075700; 59252544000; 59251902700; 59510478000; 55490551100; 55834314300 | jungty@knu.ac.kr;xiaolei@scut.edu.cn; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 15 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0 | 2025-05-07 | 1 | 1 | carbon storage; Wuhan; scenario simulation; local spatial autocorrelation; land use; PLUS-InVEST model | LAND-USE CHANGE; CHINA; URBANIZATION; EVOLUTION; STORAGE; CITY; EXPANSION; GUANGDONG; POLICIES; IMPACT | carbon storage; land use; local spatial autocorrelation; PLUS-InVEST model; scenario simulation; Wuhan | China; Hubei; Wuhan; autocorrelation; carbon storage; ecological economics; economic development; land use change; spatial distribution; sustainable development | English | 2024 | 2024-08 | 10.3390/su16156684 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Chlorine Gas Removal by H2 Treated Red Mud for the Potential Application in Waste Plastic Pyrolysis Process | In the process of pyrolyzing waste plastics, the generation of Cl-2 gas can pose a problem. During the pyrolysis processing, incomplete combustion of organic compounds containing chlorine can lead to the formation of toxic chemicals, which can cause issues in subsequent processing stages. Therefore, an adsorbent plays an important role in removing Cl-2 in the dechlorination process, and alkaline adsorbents and metal oxides are generally used. Waste red mud is composed of Fe metal oxide and alkaline components, so it is intended to be used as a Cl-2 adsorbent. The Cl-2 removal ability of red mud with different redox status of iron oxides was assessed. Hydrogen treatment was performed at various temperatures to control the reduction potential of the Fe in the metal oxides, and phase changes in the Fe oxide component of red mud were confirmed. In the case of red mud hydrogenated at 700 degrees C, most of the Fe2O3 structure could be converted to the Fe3O4 structure, and the Fe3O4 structure showed superior results in Cl-2 adsorption compared to the Fe2O3 structure. As a result, red mud at an H-2 treatment temperature of 700 degrees C showed about three times higher Cl-2 adsorption compared to red mud without H-2 treatment. | Kim, Tae-Young; Hong, Seo-Hye; Kim, Jae-Chang; Jang, Hye-Won; Lee, Yeji; Kim, Hyun-Ji; Lee, Soo-Chool; Kang, Suk-Hwan | Kyungpook Natl Univ, Res Inst Adv Energy Technol, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Chem Engn, Daegu 41566, South Korea; Inst Adv Engn, Yongin 41718, South Korea | ; Kim, Yu/L-8480-2017 | 57208461628; 58879701600; 55382762400; 58879542500; 57224079250; 57396524500; 8524020100; 8549491400 | tyoung0218@knu.ac.kr;tjgp0403@knu.ac.kr;kjchang@knu.ac.kr;heoni331@naver.com;yejeelee@knu.ac.kr;hj.kim@iae.re.kr;soochool@knu.ac.kr;shkang@iae.re.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 3 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0 | 2025-05-07 | 0 | 0 | red mud; H-2-treatment; dechlorination; waste plastic; pyrolysis | POLY(VINYL CHLORIDE); REDUCTION BEHAVIOR; DEGRADATION; POLYETHYLENE; RECOVERY; HYDROGEN; FUEL | dechlorination; H<sub>2</sub>-treatment; pyrolysis; red mud; waste plastic | adsorption; chlorine; combustion; dechlorination; hydrogen; iron oxide; mud; plastic waste; pollutant removal; pyrolysis; toxic substance | English | 2024 | 2024-02 | 10.3390/su16031137 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Comprehensive Analysis of Land Use Change and Carbon Sequestration in Nepal from 2000 to 2050 Using Markov Chain and InVEST Models | The escalating pace of migration and urbanization in Nepal has triggered profound alterations in land use practices. This event has resulted in a considerable diminution of ecological diversity and a substantial decline in the potential for carbon sequestration and other ecosystem services, thereby impeding climate change mitigation efforts. To address this, a comprehensive assessment of land use change and carbon storage was conducted from 2000 to 2019 and forecasted to 2050 in Nepal. Employing the Markov chain and InVEST models, this study evaluated the loss and gain of carbon, elucidating its economic value and spatial distribution. The findings revealed that carbon storage in 2000 and 2019 were 1.237 and 1.271 billion tons, respectively, with a projected increase to 1.347 million tons by 2050. Carbon sequestration between 2000 and 2019 amounted to 34.141 million tons, which is anticipated to surge to 76.07 million tons from 2019 to 2050, translating to economic valuations of 110.909 and 378.645 million USD, respectively. Forests emerged as pivotal in carbon storage, exhibiting higher carbon pooling than other land use types, expanding from 37% to 42% of the total land area from 2000 to the predicted year 2050. Notably, carbon distribution was concentrated in parts of the terai and mountain regions, alongside significant portions of the hilly terrain. The findings from this study offer valuable insights for governing Nepal and REDD+ in developing and implementing forest management policies. The results emphasize the importance of providing incentives to local communities judiciously to promote effective conservation measures. | Chaulagain, Deepak; Ray, Ram Lakhan; Yakub, Abdulfatai Olatunji; Same, Noel Ngando; Park, Jaebum; Suh, Dongjun; Lim, Jeong-Ok; Huh, Jeung-Soo | Kyungpook Natl Univ, Dept Convergence & Fus Syst Engn, Sangju 37224, South Korea; Kyungpook Natl Univ, Inst Global Climate Change & Energy, Daegu 41566, South Korea; Prairie View A&M Univ, Cooperat Agr Res Ctr, Coll Agr Food & Nat Resources, Prairie View, TX 77446 USA | Ray, Ram L/L-1286-2015; Ray, Ram/L-1286-2015 | 57208742538; 22433611700; 57894905100; 57895613600; 57237034300; 36613529600; 7403454245; 7102258915 | chaulagaindeepu11@gmail.com;raray@pvamu.edu;yakubabdulfatai1@gmail.com;samenoel1@gmail.com;woqja133@naver.com;dongjunsuh@knu.ac.kr;jolim@knu.ac.kr;jshuh@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 17 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.41 | 2025-05-07 | 2 | 2 | carbon distribution; ecological diversity; ecosystem services; forest; local communities; mitigation | MIDDLE HILLS; IMPACT; MANAGEMENT; DYNAMICS; STORAGE; REGION; FOREST; BASIN; STOCK | carbon distribution; ecological diversity; ecosystem services; forest; local communities; mitigation | Nepal; biodiversity; carbon sequestration; carbon storage; climate change; economic conditions; ecosystem service; forest management; land use change; migration; spatial distribution; urbanization | English | 2024 | 2024-09 | 10.3390/su16177377 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Consumer Usability Test of Mobile Food Safety Inquiry Platform Based on Image Recognition | Recently, as the types of imported food and the design of their packaging become more complex and diverse, digital recognition technologies such as barcodes, QR (quick response) codes, and OCR (optical character recognition) are attracting attention in order to quickly and easily check safety information (e.g., food ingredient information and recalls). However, consumers are still exposed to inaccurate and inconvenient situations because legacy technologies require dedicated terminals or include information other than safety information. In this paper, we propose a deep learning-based packaging recognition system which can easily and accurately determine food safety information with a single image captured through a smartphone camera. The detection algorithm learned a total of 100 kinds of product images and optimized YOLOv7 to secure an accuracy of over 95%. In addition, a new SUS (system usability scale)-based questionnaire was designed and conducted on 71 consumers to evaluate the usability of the system from the individual consumer's perspective. The questionnaire consisted of three categories, namely convenience, accuracy, and usefulness, and each received a score of at least 77, which confirms that the proposed system has excellent overall usability. Moreover, in terms of task completion rate and task completion time, the proposed system is superior when it compared to existing QR code- or Internet-based recognition systems. These results demonstrate that the proposed system provides consumers with more convenient and accurate information while also confirming the sustainability of smart food consumption. | Park, Jun-Woo; Cho, Young-Hee; Park, Mi-Kyung; Kim, Young-Duk | Daegu Gyeongbuk Inst Sci & Technol DGIST, Div Automot Res, Daegu 42988, South Korea; Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea | Park, Mi-Kyung/J-9643-2017 | 59403062500; 59402406400; 7404491155; 55955831300 | qkrwnsdn233@dgist.ac.kr;aprilyhee@naver.com;parkmik@knu.ac.kr;ydkim@dgist.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 21 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0 | 2025-05-07 | 0 | 0 | food safety; image recognition; artificial intelligence; usability test | artificial intelligence; food safety; image recognition; usability test | algorithm; artificial intelligence; food consumption; food safety; image processing; sustainability | English | 2024 | 2024-11 | 10.3390/su16219538 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Deactivation Patterns of Potassium-Based γ-Alumina Dry Sorbents for CO2 Capture | Gamma-alumina (gamma-Al2O3) is an essential support material in dry sorbents used to capture CO2 from flue gas. This study explores the deactivation of potassium-based gamma-Al2O3 sorbents due to by-products such as KAl(CO3)(OH)(2) during CO2 capture. We synthesized sorbents with K2CO3 loadings of 5, 10, 20, and 30 wt% and subjected them to repeated capture and regeneration cycles. The results show significant variations in the deactivation degree: the sorbent with 5 wt% K2CO3 exhibited a 100% deactivation rate, while the 30 wt% variant showed a markedly reduced rate of 44.6%. These findings highlight the impact of the formation of KAl(CO3)(OH)(2) at the interface between K2CO3 and gamma-Al2O3 on sorbent deactivation. An equation that can be used to predict the final CO2 capture capacity based on the ratio of active material to support was proposed using these results. | In, Soo Yeong; Min, Ji Hwan; Kim, Jae Chang; Lee, Soo Chool | Kyungpook Natl Univ, Dept Chem Engn, 80 Daehakro, Daegu 41566, South Korea; Kyungpook Natl Univ, Res Inst Adv Energy Technol, 80 Daehakro, Daegu 41566, South Korea | 57408939900; 59197630900; 55382762400; 8524020100 | soo0@knu.ac.kr;dc07006@naver.com;kjchang@knu.ac.kr;soochool@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 12 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0 | 2025-05-07 | 0 | 0 | CO2 capture; sorbent; potassium carbonate; gamma-Al2O3; KAl(CO3)(OH)(2); CCS | CARBON-DIOXIDE CAPTURE; FIXED-BED OPERATIONS; FIRED POWER-PLANT; REGENERATION PROPERTIES; SOLID SORBENTS; RECOVERY; GAS | CCS; CO<sub>2</sub> capture; KAl(CO<sub>3</sub>)(OH)<sub>2</sub>; potassium carbonate; sorbent; γ-Al<sub>2</sub>O<sub>3</sub> | byproduct; carbon sequestration; equation; potassium; regeneration | English | 2024 | 2024-06 | 10.3390/su16125117 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Deciphering Whether Illite, a Natural Clay Mineral, Alleviates Cadmium Stress in Glycine max Plants via Modulation of Phytohormones and Endogenous Antioxidant Defense System | Globally, cadmium (Cd) stress dramatically reduces agricultural yield. Illite, a natural clay mineral, is a low-cost, environmentally acceptable, new promising method of reducing the heavy metal (HM) stress of cereal crops. In research statistics, there is little research on stress tolerance behavior of Illite (IL) on an experimental soybean plant. In the present study, we took IL and examined it for tolerance to Cd, as well as for other plant-growth-promoting (PGP) characteristics in Glycine max (soybean). The results showed that applying clay minerals in different concentrations enhanced the level of SA (defense hormone) and reduced the level of ABA (stress hormone). Cd 1 mM significantly reduces plant growth by altering their morphological characteristics. However, the application of IL significantly enhanced the seedling characteristics, such as root length (RL), 29.6%, shoot length (SL), 14.5%, shoot fresh biomass (SFW), 10.8%, and root fresh biomass (RFB), 6.4%, in comparison with the negative control group. Interestingly, IL 1% also enhanced the chlorophyll content (C.C), 15.5%, and relative water content (RWC), 12.5%, in all treated plants. Moreover, it resulted in an increase in the amount of superoxide dismutase (SOD), phenolics, and flavonoids in soybean plants, while lowering the levels of peroxidase (POD) and H2O2. Furthermore, compared to control plants, soybean plants treated with the Illite exhibited increased Si absorption and lower Cd levels, according to inductively coupled plasma mass spectrometry (ICP-MS). Thus, the IL can operate as an environmentally beneficial biofertilizer and sustainable approach under Cd stress by promoting plant development by activating signaling events. | Kang, Sang-Mo; Shaffique, Shifa; Injamum-Ul-Hoque, Md.; Gam, Ho-Jun; Woo, Ji-In; Jeon, Jin Ryeol; Lee, Da-Sol; Lee, In-Jung; Mun, Bong-Gyu | Kyungpook Natl Univ, Coll Agr & Life Sci, Dept Appl Biosci, Daegu 41566, South Korea; Kyungpook Natl Univ, Inst Agr Sci & Technol, Daegu 41566, South Korea; Chungbuk Natl Univ, Dept Environm & Biol Chem, Cheongju 28644, South Korea | shaffique, shifa/KUC-7102-2024; Lee, In-Jung/GLS-0432-2022; Mun, BongGyu/GYD-6010-2022; Kang, Sang-Mo/MBG-7823-2025; Gam, Hojun/MXJ-6421-2025; Injamum-Ul-Hoque/ADJ-9141-2022 | 56189696900; 57203898867; 58663974700; 57450591400; 58295960600; 58781998600; 57222624235; 16425830900; 57147241300 | kmoya@hanmail.net;shifa.2021@knu.ac.kr;munbg@cbnu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 22 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0 | 2025-05-07 | 0 | 0 | plant hormones; metal stress; illite; ROS; defense mechanism | RESPONSES; ACID | defense mechanism; illite; metal stress; plant hormones; ROS | antioxidant; biofertilizer; chlorophyll; clay mineral; defense mechanism; heavy metal; illite; phytohormone; reactive oxygen species; soybean; water content | English | 2024 | 2024-11 | 10.3390/su162210039 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Enhancing Building Energy Efficiency with IoT-Driven Hybrid Deep Learning Models for Accurate Energy Consumption Prediction | Buildings remain pivotal in global energy consumption, necessitating a focused approach toward enhancing their energy efficiency to alleviate environmental impacts. Precise energy prediction stands as a linchpin in optimizing efficiency, offering indispensable foresight into future energy demands critical for sustainable environments. However, accurately forecasting energy consumption for individual households and commercial buildings presents multifaceted challenges due to their diverse consumption patterns. Leveraging the emerging landscape of the Internet of Things (IoT) in smart homes, coupled with AI-driven energy solutions, presents promising avenues for overcoming these challenges. This study introduces a pioneering approach that harnesses a hybrid deep learning model for energy consumption prediction, strategically amalgamating convolutional neural networks' features with long short-term memory (LSTM) units. The model harnesses the granularity of IoT-enabled smart meter data, enabling precise energy consumption forecasts in both residential and commercial spaces. In a comparative analysis against established deep learning models, the proposed hybrid model consistently demonstrates superior performance, notably exceling in accurately predicting weekly average energy usage. The study's innovation lies in its novel model architecture, showcasing an unprecedented capability to forecast energy consumption patterns. This capability holds significant promise in guiding tailored energy management strategies, thereby fostering optimized energy consumption practices in buildings. The demonstrated superiority of the hybrid model underscores its potential to serve as a cornerstone in driving sustainable energy utilization, offering invaluable guidance for a more energy-efficient future. | Natarajan, Yuvaraj; Preethaa, K. R. Sri; Wadhwa, Gitanjali; Choi, Young; Chen, Zengshun; Lee, Dong-Eun; Mi, Yirong | Kyungpook Natl Univ, Dept Robot & Smart Syst Engn, 80,Daehak Ro, Daegu 41566, South Korea; KPR Inst Engn & Technol, Ctr Res & Dev, Coimbatore 641407, India; ZIH Tech Univ Dresden TUD, Ctr Scalable Data Analyt & Artificial Intelligence, Budapester Str 34b, D-01062 Dresden, Germany; Earth Turbine, 36,Dongdeok Ro 40 Gil, Daegu 41905, South Korea; Chongqing Univ, Sch Civil Engn, Chongqing 400045, Peoples R China; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80,Daehak Ro, Daegu 41566, South Korea | Natarajan, Yuvaraj/GWV-2080-2022; raj, yuva/GWV-2080-2022 | 57204528689; 57390422000; 57219654131; 58937691800; 55866149500; 56605563300; 57225181327 | yuvaraj.n@kpriet.ac.in;k.r.sripreethaa@kpriet.ac.in;gitanjali.wadhwa@tu-dresden.de;youngch5@naver.com;zengshunchen@cqu.edu.cn;dolee@knu.ac.kr;2021320938@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 5 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 4.05 | 2025-05-07 | 10 | 14 | AI-driven energy solutions; building energy efficiency; deep learning techniques; energy forecasting; energy prediction model; hybrid deep learning model | DEMAND | AI-driven energy solutions; building energy efficiency; deep learning techniques; energy forecasting; energy prediction model; hybrid deep learning model | energy efficiency; energy management; energy use; innovation; machine learning; numerical model; prediction | English | 2024 | 2024-03 | 10.3390/su16051925 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Review | From Potential to Power: Advancing Nigeria's Energy Sector through Renewable Integration and Policy Reform | Nigeria is a nation endowed with both abundant renewable and non-renewable energy resources. Despite its vast potential, Nigeria struggles with a consistent power supply due to various systemic issues, such as inadequate funding, infrastructural decay, corruption, technical skill shortages, and macroeconomic instability. These challenges hinder the effective harnessing and distribution of energy resources, particularly renewable ones like wind, solar, biomass, and hydropower. This study assesses the existing energy policies and their efficacy in promoting sustainable energy development towards achieving universal electricity access by 2030. It highlights the necessity for a just energy transition that integrates a substantial proportion of renewable energy into the national grid, aiming to meet up to 60% of the country's energy demands with clean sources by 2050. This transition is critical not only for energy security and reducing the environmental impact but also for fostering socioeconomic equity. Recommendations include overhauling the legal and regulatory frameworks to support renewable energy growth, particularly in off-grid areas, to ensure clean, affordable, and secure energy access. Strategic investments, enhanced infrastructure, and robust public-private partnerships are essential to overcome the current barriers and realize Nigeria's energy potential. This paper calls for a comprehensive approach that addresses both the technical and socioeconomic dimensions of the energy crisis, laying the groundwork for a sustainable and prosperous energy future for Nigeria. | Adeshina, Mohammad Awwal; Ogunleye, Abdulazeez M.; Suleiman, Habeeb Olaitan; Yakub, Abdulfatai Olatunji; Same, Noel Ngando; Suleiman, Zainab Adedamola; Huh, Jeung-Soo | Daegu Gyeongbuk Inst Sci & Technol DGIST, Div Biotechnol, Daegu 42988, South Korea; Arizona State Univ, W P Carey Sch Business, Tempe, AZ 85287 USA; Kyungpook Natl Univ, Coll IT Engn, Sch Elect & Elect Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Convergence & Fus Syst Engn, Sangju 37224, South Korea; Kyungpook Natl Univ, Inst Global Climate Change & Energy, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Environm Engn, Daegu 41566, South Korea; Kyungpook Natl Univ, Dept Energy Convergence & Climate Change, Daegu 41566, South Korea | 57216582237; 57933554600; 57764914500; 57894905100; 57895613600; 59384688500; 7102258915 | mohammadadeshina1@gmail.com;azeezsucczeez@gmail.com;suleiman.habeeb16@knu.ac.kr;zasuleiman5@gmail.com;jshuh@knu.ac.kr; | SUSTAINABILITY | SUSTAINABILITY-BASEL | 2071-1050 | 16 | 20 | SCIE;SSCI | ENVIRONMENTAL SCIENCES;ENVIRONMENTAL STUDIES;GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | 2024 | 3.3 | 41.6 | 0.37 | 2025-05-07 | 1 | 3 | renewable energy transition; sustainable development; energy policy; socioeconomic equity | HIGH-ALTITUDE LOCATIONS; WIND ENERGY; ELECTRICITY-GENERATION; CONVERSION SYSTEMS; OYO STATE; COST; HYDROPOWER; VIABILITY; TURBINES | energy policy; renewable energy transition; socioeconomic equity; sustainable development | Nigeria; alternative energy; energy policy; energy resource; environmental impact; equity; regulatory framework; smart grid; socioeconomic status; sustainable development | English | 2024 | 2024-10 | 10.3390/su16208803 | 바로가기 | 바로가기 | 바로가기 | 바로가기 |
페이지 이동: