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A novel electrospinning method for self-assembled tree-like fibrous scaffolds:Microenvironment-associated regulation of MSC behavior and bone regeneration

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Journal of Materials Science & Technology 2022年第20期115卷 52-70页

作者： Jeong In kim Ju yeon kim Sung-Ho Kook Jeong-Chae Lee Cluster for Craniofacial Development and Regeneration Research Institute of Oral Biosciences and School of DentistryJeonbuk National UniversityJeonju 54896Republic of Korea Department of Bionanosystem Engineering Jeonbuk National UniversityJeonju 54896Republic of Korea Department of Bioactive Material Sciences Research Center of Bioactive MaterialsJeonbuk National UniversityJeonju 54896Republic of Korea

Numerous studies highlight advantages of electrospun scaffolds in bone tissue engineering,in which cellular behavior is tightly affected by fiber topographical cues of ***,the classic electrospinning setup limits a desired presentation of biomimetic fibrous microenvironments that sense mechanosignaling and regulate stem cell *** aims of this study were to fabricate advanced asspun scaffolds presenting tree-like microfiber/nanonet networks and to evaluate their regulatory potentials on behavior of human mesenchymal stem cells(h MSCs)and bone *** we developed a novel electrospinning setup that allowed the presentation of patterned Trunk microfibers(TMF)and/or branched nanonet fibers(BNn Fs)in biomimetic fibrous *** the cellular mechanisms,anisotropichierarchical topography of TMF controlled behavior of h MSCs through focal adhesion formation and Yesassociated protein(YAP)induction,whereas BNn F disturbed such mechanosensing responses in the *** fiber microenvironment-related expression and nuclear localization of YAP *** correlated with the potentials of as-spun scaffolds to enhance osteogenic differentiation of the h MSCs and alveolar bone defect healing in an animal ***,this study provides an advanced approach of the modified electrospinning setup for presentation of biomimetic fibrillar microenvironments in as-spun scaffolds along with their application in stem cell behavior regulation and regenerative tissue engineering.

关键词： Electrospinning Advanced biomimetic scaffolds Stem cell behavior Mechanosensing Bone tissue engineering

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A Deep Learning Hierarchical Ensemble for Remote Sensing Image Classification

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Computers, Materials & Continua 2022年第8期72卷 2649-2663页

作者： Seung-yeon Hwang Jeong-Joon kim Department of Computer Engineering Anyang UniversityAnyang-si14028Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14028Korea

Artificial intelligence,which has recently emerged with the rapid development of information technology,is drawing attention as a tool for solving various problems demanded by society and *** particular,convolutional neural networks(CNNs),a type of deep learning technology,are highlighted in computer vision fields,such as image classification and recognition and object *** these CNN models requires a large amount of data,and a lack of data can lead to performance degradation problems due to *** CNN architecture development and optimization studies become active,ensemble techniques have emerged to perform image classification by combining features extracted from multiple CNN *** this study,data augmentation and contour image extraction were performed to overcome the data shortage *** addition,we propose a hierarchical ensemble technique to achieve high image classification accuracy,even if trained from a small amount of ***,we trained the UCMerced land use dataset and the contour images for each image on pretrained VGGNet,GoogLeNet,ResNet,DenseNet,and *** then apply a hierarchical ensemble technique to the number of cases in which each model can be *** experiments were performed in cases where the proportion of training datasets was 30%,50%,and 70%,resulting in a performance improvement of up to 4.68%compared to the average accuracy of the entire model.

关键词： Image classification deep learning CNNs hierarchical ensemble UC-Merced land use dataset contour image

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A Universal Activation Function for Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3553-3569页

作者： Seung-yeon Hwang Jeong-Joon kim Department of Computer Engineering Anyang UniversityAnyang-si14028Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14028Korea

Recently,deep learning has achieved remarkable results in fields that require human cognitive ability,learning ability,and reasoning *** functions are very important because they provide the ability of artificial neural networks to learn complex patterns through *** activation functions are being studied to solve problems such as vanishing gradients and dying nodes that may occur in the deep learning ***,it takes a lot of time and effort for researchers to use the existing activation function in their ***,in this paper,we propose a universal activation function(UA)so that researchers can easily create and apply various activation functions and improve the performance of neural *** can generate new types of activation functions as well as functions like traditional activation functions by properly adjusting three *** famous Convolutional Neural Network(CNN)and benchmark datasetwere used to evaluate the experimental performance of the UA proposed in this *** compared the performance of the artificial neural network to which the traditional activation function is applied and the artificial neural network to which theUA is *** addition,we evaluated the performance of the new activation function generated by adjusting the hyperparameters of *** experimental performance evaluation results showed that the classification performance of CNNs improved by up to 5%through the UA,although most of them showed similar performance to the traditional activation function.

关键词： Deep learning activation function convolutional neural network benchmark datasets universal activation function

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Data Augmentation Using Contour Image for Convolutional Neural Network

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Computers, Materials & Continua 2023年第6期75卷 4669-4680页

作者： Seung-yeon Hwang Jeong-Joon kim Department of Computer Engineering Anyang UniversityAnyang-si14058Korea Department of ICT Convergence Engineering Anyang UniversityAnyang-si14058Korea

With the development of artificial intelligence-related technologies such as deep learning,various organizations,including the government,are making various efforts to generate and manage big data for use in artificial ***,it is difficult to acquire big data due to various social problems and restrictions such as personal information *** are many problems in introducing technology in fields that do not have enough training data necessary to apply deep learning ***,this study proposes a mixed contour data augmentation technique,which is a data augmentation technique using contour images,to solve a problem caused by a lack of ***,a famous convolutional neural network(CNN)architecture,and CIFAR-10,a benchmark data set,are used for experimental performance evaluation to prove the superiority of the proposed *** to prove that high performance improvement can be achieved even with a small training dataset,the ratio of the training dataset was divided into 70%,50%,and 30%for comparative *** a result of applying the mixed contour data augmentation technique,it was possible to achieve a classification accuracy improvement of up to 4.64%and high accuracy even with a small amount of data *** addition,it is expected that the mixed contour data augmentation technique can be applied in various fields by proving the excellence of the proposed data augmentation technique using benchmark datasets.

关键词： Data augmentation image classification deep learning convolutional neural network mixed contour image benchmark dataset

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Clinical efficacy of 0.05%cyclosporine nano-emulsion in the treatment of dry eye syndrome associated with meibomian gland dysfunction

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International Journal of Ophthalmology(English edition) 2022年第12期15卷 1924-1931页

作者： yeon Ji Jo Ji Eun Lee Jong soo Lee Efficacy of nano-cyclosporine to DES with MGD 1 Department of Ophthalmology Pusan National University School of Medicine&Medical Research InstitutePusan National University HospitalPusan 49241Republic of Korea Department of Ophthalmology Pusan National University School of Medicine&Medical Research CenterYangsan Pusan National University HospitalYangsan 626-770Republic of Korea

AIM:To evaluate the clinical efficacy of topical 0.05%cyclosporine nano-emulsion in the treatment of dry eye syndrome(DES)with meibomian gland dysfunction(MGD).METHODS:This prospective study included 64 patients with DES and MGD who were randomly assigned to three groups:Group 1(n=24,conventional cyclosporine),Group 2(n=21,nano-emulsion cyclosporine),and Group 3(n=19,control).Lid margin telangiectasia(LMT),meibomian gland secretion(MGS),conjunctival injection(CI),corneal staining(CS),tear break-up time(TBUT),Schirmer test I(STI),Ocular Surface Disease Index(OSDI),and lipid layer thickness(LLT)was evaluated at 4,8,and 12wk of ***:In Group 3(control),LMT,CS,and CI improved after 8wk,MGS,TBUT after 12wk of *** Group 1(conventional cyclosporine),LMT,MGS,and TBUT improved significantly after 4wk,whereas CS,CI,STI,and LLT improved significantly after 8wk,and OSDI at *** Group 2(nano-cyclosporine),LMT,MGS,CS,CI,TBUT,and OSDI significantly improved after 4wk,and STI after ***,LLT was significantly higher than other groups after ***:Cyclosporine and nano-cyclosporine shows significant improvement in DES with MGD than the control *** contrast,the nano-cyclosporine group shows more statistically improved CI and CS at 4wk,especially LLT at 4,8,and 12wk compared to the conventional cyclosporine group.

关键词： anti-inflammatory treatment cyclosporine dry eye disease meibomian gland dysfunction

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Accurate Multi-Site Daily-Ahead Multi-Step PM_(2.5)Concentrations Forecasting Using Space-Shared CNN-LSTM

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Computers, Materials & Continua 2022年第3期70卷 5143-5160页

作者： Xiaorui Shao Chang soo kim Department of Information Systems Pukyong National UniversityBusan608737Korea

Accurate multi-step PM_(2.5)(particulate matter with diameters≤2.5 um)concentration prediction is critical for humankinds’health and air populationmanagement because it could provide strong evidence for ***,it is very challenging due to its randomness and *** paper proposed a novel method based on convolutional neural network(CNN)and long-short-term memory(LSTM)with a space-shared mechanism,named space-shared CNN-LSTM(SCNN-LSTM)for multi-site dailyahead multi-step PM_(2.5)forecasting with self-historical *** proposed SCNN-LSTM contains multi-channel inputs,each channel corresponding to one-site historical PM_(2.5)concentration *** which,CNN and LSTM are used to extract each site’s rich hidden feature representations in a stack ***,CNN is to extract the hidden short-time gap PM_(2.5)concentration patterns;LSTM is to mine the hidden features with long-time *** channel extracted features aremerged as the comprehensive features for future multi-step PM_(2.5)concentration ***,the space-shared mechanism is implemented by multi-loss functions to achieve space information ***,the final features are the fusion of short-time gap,long-time dependency,and space information,which enables forecasting more *** validate the proposed method’s effectiveness,the authors designed,trained,and compared it with various leading methods in terms of RMSE,MAE,MAPE,and R^(2)on four real-word PM_(2.5)data sets in Seoul,South *** massive experiments proved that the proposed method could accurately forecast multi-site multi-step PM_(2.5)concentration only using self-historical PM_(2.5)concentration time series and running ***,the proposed method obtained averaged RMSE of 8.05,MAE of 5.04,MAPE of 23.96%,and R^(2)of 0.7 for four-site daily ahead 10-hourPM_(2.5)concentration forecasting.

关键词： PM_(2.5)forecasting CNN-LSTM air quality management multi-site multi-step forecasting

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Game Outlier Behavior Detection System Based on Dynamic Time Warp Algorithm

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Computer Modeling in Engineering & Sciences 2022年第4期131卷 219-237页

作者： Shinjin Kang soo Kyun kim School of Games Hongik UniversitySejong30016Korea Department of Computer Engineering Jeju National UniversityJeju63243Korea

This paper proposes a methodology for using multi-modal data in gameplay to detect outlier *** proposedmethodology collects,synchronizes,and quantifies time-series data fromwebcams,mouses,and *** expressions are varied on a one-dimensional pleasure axis,and changes in expression in the mouth and eye areas are detected ***,the keyboard and mouse input frequencies are tracked to determine the interaction intensity of ***,we apply a dynamic time warp algorithm to detect outlier *** detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that differed greatly from those of other *** outlier patterns can provide game designers with feedback on the actual play experiences of users of the *** results can be applied to the game industry as game user experience analysis,enabling a quantitative evaluation of the excitement of a game.

关键词： Facial expression recognition webcam behavior analysis affective computing

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Remarkably slow corrosion rate of high-purity Mg microalloyed with 0.05wt% Sc

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Journal of Magnesium and Alloys 2023年第3期11卷 991-997页

作者： soo-Min Baek Jeong-Ki kim Du-Won Min Sung soo Park Department of Materials Science and Engineering Ulsan National Institute of Science and TechnologyUlsan 44919Republic of Korea

We report that the corrosion resistance of Mg is significantly improved by adding 0.05wt%*** rates evaluated from weight loss values after room-temperature immersion in 0.6 M NaCl solution for two weeks were 0.27 and 4.0 mm y^(-1)for the high-purity Mg samples with and without microalloyed 0.05wt%Sc,*** beneficial effect of Sc microalloying on the corrosion resistance of Mg is discussed in connection with Sc-induced microstructural modifications.

关键词： Magnesium Microalloying Intermetallic phase Microgalvanic corrosion

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Context Awareness by Noise-Pattern Analysis of a Smart Factory

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Computers, Materials & Continua 2023年第8期76卷 1497-1514页

作者： So-yeon Lee Jihoon Park Dae-Young kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Recently,to build a smart factory,research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology,a field of artificial *** of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training ***,compared to numerical raw data,learning based on image data has the disadvantage that creating a training dataset is very ***,we devised a two-step data preprocessing method that efficiently detects machine anomalies in numerical raw *** the first preprocessing process,sound signal information is analyzed to extract features,and in the second preprocessing process,data filtering is performed by applying the proposed *** efficient dataset was built formodel learning through a total of two steps of data *** addition,both showed excellent performance in the training accuracy of the model that entered each dataset,but it can be seen that the time required to build the dataset was 203 s compared to 39 s,which is about 5.2 times than when building the image dataset.

关键词： Noise-pattern recognition context awareness deep learning fault detection smart factory

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Analytical evaluation and experimental validation on dynamic rocking behavior for shallow foundation considering structural response

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Earthquake Engineering and Engineering Vibration 2022年第1期21卷 37-51页

作者： Kil-Wan Ko Jeong-Gon Ha Dong-soo kim Department of Civil and Environmental Engineering UC BerkeleyCalifornia 94720USA Advanced Structures and Seismic Safety Research Division Daejeon 34057Korea Department of Civil and Environmental Engineering KAISTDaejeon 34141Korea

The challenge in the practical application of rocking foundations is the estimation of its performance,particularly the rotation angle,during a strong *** this study,the dynamic rocking behavior for a shallow foundation considering structural response was evaluated through two analytical approaches:the conventional soil-foundation-structure interaction(SFSI)governing equation of a single-degree-of-freedom(SDOF)structure on a rocking shallow foundation,and the Housner rocking model(i.e.,a rocking rigid block on a rigid base).Both approaches were validated with dynamic centrifuge *** test models consisted of a soft soil deposit,a shallow rectangular foundation,and an SDOF structure dominated by a bending behavior.A total of 11 foundation-structure systems and six seismic waves,including recorded earthquake signals and sinusoidal waves,were *** results showed that the conventional SFSI equation well predicted the maximum rotation during strong ***,this method was less accurate regarding the rotational phase information and maximum rotation of the foundation during weak *** the other hand,although the modified Housner′s rocking model required five parameters relevant to a soil-foundation-structure system,it overestimated the maximum rotation of the foundation when compared with the results from dynamic centrifuge tests.

关键词： soil-foundation-structure interaction maximum rotation angle rocking foundation Housner rocking model dynamic centrifuge test

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