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Energy & Environmental Materials 2024年第1期7卷 81-86页

作者： seoungwoo byun Zhu Liu Dong Ok Shin Kyuman Kim Jaecheol Choi Youngjoon Roh Dahee Jin Seungwon Jung Kyung-Geun Kim Young-Gi Lee Stefan Ringe Yong Min Lee Department of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Intelligent Sensors Research Section Electronics and Telecommunications Research Institute (ETRI) Department of Advanced Device Technology University of Science and Technology (UST) Intelligent Polymer Research Institute and ARC Centre of Excellence for Electromaterials Science University of Wollongong Energy Science and Engineering Research Center Daegu Gyeongbuk Institute of Science and Technology (DGIST) Department of Chemistry Korea University

The increasing demand for short charging time on electric vehicles has motivated realization of fast chargeable lithium-ion batteries（LIBs）.However,shortening the charging time of LIBs is limited by Li+intercalation... 详细信息

关键词： de-solvation digital twins fast charging graphite anodes polymeric binders

Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation

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Journal of Magnesium and Alloys 2024年第1期12卷 186-196页

作者： Sujeong byun Jinyeong Yu Seho Cheon Seong Ho Lee Sung Hyuk Park Taekyung Lee School of Mechanical Engineering Pusan National UniversityBusan 46241South Korea School of Materials Science and Engineering Kyungpook National UniversityDaegu 41566South Korea

Mg alloys possess an inherent plastic anisotropy owing to the selective activation of deformation mechanisms depending on the loading *** characteristic results in a diverse range of flow curves that vary with a deformation *** study proposes a novel approach for accurately predicting an anisotropic deformation behavior of wrought Mg alloys using machine learning(ML)with data *** developed model combines four key strategies from data science:learning the entire flow curves,generative adversarial networks(GAN),algorithm-driven hyperparameter tuning,and gated recurrent unit(GRU)*** proposed model,namely GAN-aided GRU,was extensively evaluated for various predictive scenarios,such as interpolation,extrapolation,and a limited dataset *** model exhibited significant predictability and improved generalizability for estimating the anisotropic compressive behavior of ZK60 Mg alloys under 11 annealing conditions and for three loading *** GAN-aided GRU results were superior to those of previous ML models and constitutive *** superior performance was attributed to hyperparameter optimization,GAN-based data augmentation,and the inherent predictivity of the GRU for *** a first attempt to employ ML techniques other than artificial neural networks,this study proposes a novel perspective on predicting the anisotropic deformation behaviors of wrought Mg alloys.

关键词： Plastic anisotropy Compression Annealing Machine learning Data augmentation

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Recent advances in 3D printed electrode materials for electrochemical energy storage devices

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Journal of Energy Chemistry 2023年第6期81卷 272-312,I0008页

作者： Suhail Mubarak Duraisami Dhamodharan Hun-Soo byun Department of Chemical and Biomolecular Engineering Chonnam National UniversityYeosuJeonnam 59626Republic of Korea Greenlab Department of prosthodonticsSaveetha Dental College and HospitalsSaveetha Institute of Medical and Technical SciencesChennaiTamil Nadu 600077India

Electrochemical energy storage(EES)systems like batteries and supercapacitors are becoming the key power sources for attempts to change the energy dependency from inadequate fossil fuels to sustainable and renewable *** energy storage devices(EESDs)operate efficiently as a result of the construction and assemblage of electrodes and electrolytes with appropriate structures and effective *** manufacturing procedures have restrictions on regulating the morphology and architecture of the electrodes,which would influence the performance of the devices.3D printing(3DP)is an advanced manufacturing technology combining computer-aided design and has been recognised as an artistic method of fabricating different fragments of energy storage devices with its ability to precisely control the geometry,porosity,and morphology with improved specific energy and power *** capacity to create mathematically challenging shape or configuration designs and high-aspect-ratio 3D architectures makes 3D printing technology unique in its ***,the control settings,interactive manufacturing processes,and protracted post-treatments will affect the reproducibility of the printed *** intelligent software,sophisticated control systems,high-grade industrial equipment,and post-treatment-free methods are necessary to develop.3D printed(3DPd)EESDs necessitate dynamic printable materials and composites that are influenced by performance criteria and fundamental ***,we review the recent advances in 3DPd electrodes for EES *** emphasis is on printable material synthesis,3DP techniques,and the electrochemical performance of printed *** the fabrication of electrodes,we concentrate on major 3DP technologies such as direct ink writing(DIW),inkjet printing(IJP),fused deposition modelling(FDM),and stereolithography3DP(SLA).The benefits and drawbacks of each 3DP technology are extensively di

关键词： 3D printing 3D printed electrodes Electrochemical energy storage Lithium-ion battery Zinc-ion battery Supercapacitor

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Blockchain and Machine Learning for Intelligent Multiple Factor-Based Ride-Hailing Services

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Computers, Materials & Continua 2022年第3期70卷 4429-4446页

作者： Zeinab Shahbazi Yung-Cheol byun IIST Department of Computer EngineeringJeju National UniversityJeju-siJeju Special Self-Governing Province63243Kore

One of the common transportation systems in Korea is calling taxis through online applications,which is more convenient for passengers and drivers in the modern ***,the driver’s passenger taxi request can be rejected based on the driver’s location and ***,there is a need to specify driver’s acceptance and rejection of the received *** security of this systemis anothermain core to save the transaction information and safety of passengers and *** this study,the origin and destination of the Jeju island SouthKorea were captured from T-map and processed based on machine learning decision tree and XGBoost *** blockchain framework is implemented in the Hyperledger Fabric *** experimental results represent the features of *** cross-validation was *** is another factor for the taxi trip,which in total trip in midnight is quite *** process presents the successful matching of ride-hailing taxi services with the specialty of distance,the trip request,and safety based on the total city measurement.

关键词： Taxi trip blockchain machine learning ride-hailing prediction trip distance

Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction

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Computers, Materials & Continua 2023年第3期74卷 5507-5525页

作者： Subhajit Chatterjee Yung-Cheol byun Department of Computer Engineering Jeju National UniversityJeju-si63243Korea Department of Computer Engineering Major of Electronic EngineeringJeju National UniversityInstitute of Information Science&TechnologyJeju63243Korea

The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient *** kickboards are gradually growing in popularity in tourist and education-centric *** the upcoming arrival of electric kickboard vehicles,deploying a customer rental service is *** to its freefloating nature,the shared electric kickboard is a common and practical means of *** plans for shared electric kickboards are required to increase the quality of service,and forecasting demand for their use in a specific region is *** demand accurately with small data is *** data is necessary for training machine learning algorithms for effective *** generation is a method for expanding the amount of data that will be further accessible for *** this work,we proposed a model that takes time-series customers’electric kickboard demand data as input,pre-processes it,and generates synthetic data according to the original data distribution using generative adversarial networks(GAN).The electric kickboard mobility demand prediction error was reduced when we combined synthetic data with the original *** proposed Tabular-GAN-Modified-WGAN-GP for generating synthetic data for better prediction *** modified The Wasserstein GAN-gradient penalty(GP)with the RMSprop optimizer and then employed Spectral Normalization(SN)to improve training stability and faster ***,we applied a regression-based blending ensemble technique that can help us to improve performance of demand *** used various evaluation criteria and visual representations to compare our proposed model’s *** data generated by our suggested GAN model is also *** TGAN-Modified-WGAN-GP model mitigates the overfitting and mode collapse problem,and it also converges faster than previous GAN models for synthetic data creation.

关键词： Machine learning generative adversarial networks electric vehicle time-series TGAN WGAN-GP blend model demand prediction regression

Generating Synthetic Data to Reduce Prediction Error of Energy Consumption

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Computers, Materials & Continua 2022年第2期70卷 3151-3167页

作者： Debapriya Hazra Wafa Shafqat Yung-Cheol byun Department of Computer Engineering Jeju National UniversityJeju-siKorea

Renewable and nonrenewable energy sources are widely incorporated for solar and wind energy that produces electricity without increasing carbon dioxide *** industries worldwide are trying hard to predict future energy consumption that could eliminate over or under contracting energy resources and unnecessary *** learning techniques for predicting energy are the trending solution to overcome the challenges faced by energy *** basic need for machine learning algorithms to be trained for accurate prediction requires a considerable amount of *** critical factor is balancing the data for enhanced *** Augmentation is a technique used for increasing the data available for *** data are the generation of new data which can be trained to improve the accuracy of prediction *** this paper,we propose a model that takes time series energy consumption data as input,pre-processes the data,and then uses multiple augmentation techniques and generative adversarial networks to generate synthetic data which when combined with the original data,reduces energy consumption prediction *** propose TGAN-skip-Improved-WGAN-GP to generate synthetic energy consumption time series tabular *** modify TGANwith skip connections,then improveWGANGPby defining a consistency term,and finally use the architecture of improved WGAN-GP for training *** used various evaluation metrics and visual representation to compare the performance of our proposed *** also measured prediction accuracy along with mean and maximum error generated while predicting with different variations of augmented and synthetic data with original *** mode collapse problemcould be handled by TGAN-skip-Improved-WGAN-GP model and it also converged faster than existing GAN models for synthetic data *** experiment result shows that our proposed technique of combining synthetic data with original data could significantly red

关键词： Energy consumption generative adversarial networks synthetic data time series data TGAN WGAN-GP TGAN-skip prediction error augmentation

Pleckstrin Homology-Like Domain, Family A, Member 1 (PHLDA1): A Multifaceted Cell Survival Factor that Drives Metabolic Disease

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Engineering 2023年第1期20卷 9-18页

作者： Tamana Yousof Jae Hyun byun Jack Chen Richard C.Austin Department of Medicine Division of NephrologyMcMaster UniversityThe Research Institute of St.Joe’s Hamilton and the Hamilton Centre for Kidney ResearchHamiltonOntarioL8N 4A6Canada

Pleckstrin homology-like domain, family A, member 1 (PHLDA1) is a multifaceted intracellular protein belonging to the evolutionarily conserved pleckstrin homology-related domain family. Its murine homologue, T-cell death-associated 51 (TDAG51) gene, was initially discovered for its role in activation-induced apoptosis in T-cell hybridomas. In recent years, PHLDA1 has received increased attention due to its association with obesity, fatty liver disease, diabetes, atherosclerosis, and cancer. Accumulating evidence also supports its role in endoplasmic reticulum stress signaling pathways as a crucial mediator of apoptosis, autophagy, and cell proliferation. In this review, the current knowledge of PHLDA1 gene and protein regulation, localization, and function is summarized. This review highlights the pro- and anti-apoptotic roles of PHLDA1 that contribute to vast array of metabolic diseases.

关键词： ER-stress Metabolism Apoptosis Cell survival PHLDA1

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Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

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Computers, Materials & Continua 2023年第4期75卷 1447-1465页

作者： Debnath Bhattacharyya EaliStephen Neal Joshua N.Thirupathi Rao Yung-cheol byun Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGuntur522302Andhra PradeshIndia Department of Computer Science&Engineering Vignan’s Institute of Information Technology(A)Visakhapatnam530049Andhra PradeshIndia Department of Computer Engineering Jeju National University102 Jejudaehak-roJeju-siJeju-do690-756Korea

Lung cancer is the leading cause of mortality in the world affectingboth men and women *** a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are *** of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one *** the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most *** employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.

关键词： Magnetic resonance imaging(MRI) lung cancer Luna-16 logistic distribution segmentation deep learning juxta plural pulmonary nodules

High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble

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Computers, Materials & Continua 2022年第12期73卷 4743-4762页

作者： Yong-Woon Kim Yung-Cheol byun Dong Seog Han Dalia Dominic Sibu Cyriac Centre for Digital Innovation CHRIST(Deemed to be University)Bangalore560029India Department of Computer Engineering Jeju National UniversityJeju63243Korea School of Electronics Engineering Kyungpook National UniversityDaegu41566Korea

Awide range of camera apps and online video conferencing services support the feature of changing the background in real-time for aesthetic,privacy,and security *** studies show that theDeep-Learning(DL)is a suitable option for human segmentation,and the ensemble of multiple DL-based segmentation models can improve the segmentation ***,these approaches are not as effective when directly applied to the image segmentation in a *** paper proposes an Adaptive N-Frames Ensemble(AFE)approach for high-movement human segmentation in a video using an ensemble of multiple DL *** contrast to an ensemble,which executes multiple DL models simultaneously for every single video frame,the proposed AFE approach executes only a single DL model upon a current video *** combines the segmentation outputs of previous frames for the final segmentation output when the frame difference is less than a particular *** method employs the idea of the N-Frames Ensemble(NFE)method,which uses the ensemble of the image segmentation of a current video frame and previous video ***,NFE is not suitable for the segmentation of fast-moving objects in a video nor a video with low frame *** proposed AFE approach addresses the limitations of the NFE *** experiment uses three human segmentation models,namely Fully Convolutional Network(FCN),DeepLabv3,and *** evaluated our approach using 1711 videos of the TikTok50f dataset with a single-person *** TikTok50f dataset is a reconstructed version of the publicly available TikTok dataset by cropping,resizing and dividing it into videos having 50 frames *** paper compares the proposed AFE with single models and the Two-Models Ensemble,as well as the NFE *** experiment results show that the proposed AFE is suitable for low-movement as well as high-movement human segmentation in a video.

关键词： High movement human segmentation artificial intelligence deep learning ensemble video instance segmentation

Pressure changes in tapered and cylindrical shaped cuff after extension of head and neck:A randomized controlled trial

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World Journal of Clinical Cases 2022年第31期10卷 11419-11426页

作者： Gukjin Seol Juhwa Jin Jinyoung Oh Sung-Hye byun Younghoon Jeon Department of Oral and Maxillofacial Surgery School of DentistryKyungpook National UniversityDaegu 41944South Korea Department of Anesthesiology and Pain Medicine Kyungpook National University HospitalDaegu 41944South Korea Department of Anesthesiology and Pain Medicine School of MedicineKyungpook National UniversityDaegu 41944South Korea Department of Anesthesiology and Pain Medicine School of DentistryKyungpook National UniversityDaegu 41944South Korea

BACKGROUND The proper cuff pressure of endotracheal tube(ET)plays an important role in sealing the airway and preventing airway complications during mechanical *** ET cuff shape affects the cuff pressure after positional *** To investigate cuff pressure between tapered and cylindrical cuff after extension of head and neck during nasal endotracheal *** In a randomized clinical trial,52 patients were randomized to one of two groups:cylindrical cuff or Tapered *** pressure with 22 cmH_(2)O was applied to patients in the neutral *** extension of head and neck,the cuff pressure was evaluated again and readjusted to 22 cmH_(2)*** addition,the extent of cephalad migration of ET tip was assessed and postoperative airway complications such as sore throat,and hoarseness were *** The cuff pressure was higher in the tapered cuff(28.7±1.0 cmH_(2)O)than in the cylindrical cuff(25.5±0.8 cmH_(2)O)after head and neck extension(P<0.001).The extent of cephalad migration of tube tip was greater in TaperGuard ET(18.4±2.2 mm)than in conventional ET(15.1±1.2 mm)(P<0.001).The incidence of postoperative airway complications was comparable between two *** After head and neck extension,the cuff pressure and the extent of cephalad migration of ET was greater in tapered cuff than in cylindrical cuff during nasal intubation,respectively.

关键词： Cuff pressure Cylindrical cuff Endotracheal tube Nasal intubation Tapered cuff