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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

Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting

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Computers, Materials & Continua 2021年第11期69卷 1893-1913页

作者： Prince Waqas Khan yung-cheol byun Department of Computer Engineering Jeju National UniversityJeju-siKorea

Despite the advancement within the last decades in the field of smart grids,energy consumption forecasting utilizing the metrological features is still *** paper proposes a genetic algorithm-based adaptive error curve learning ensemble(GA-ECLE)*** proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach.A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast *** approach combines three models,namely CatBoost(CB),Gradient Boost(GB),and Multilayer Perceptron(MLP).The ensembled CB-GB-MLP model’s inner mechanism consists of generating a meta-data from Gradient Boosting and CatBoost models to compute the final predictions using the Multilayer Perceptron network.A genetic algorithm is used to obtain the optimal features to be used for the *** prove the proposed model’s effectiveness,we have used a four-phase technique using Jeju island’s real energy consumption *** the first phase,we have obtained the results by applying the CB-GB-MLP *** the second phase,we have utilized a GA-ensembled model with optimal *** third phase is for the comparison of the energy forecasting result with the proposed ECL-based *** fourth stage is the final stage,where we have applied the GA-ECLE *** obtained a mean absolute error of 3.05,and a root mean square error of *** experimental results are provided,demonstrating the superiority of the proposed GA-ECLE model over traditional ensemble models.

关键词： Energy consumption meteorological features error curve learning ensemble model energy forecasting gradient boost catboost multilayer perceptron genetic algorithm

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

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

Thrust Analysis of a Fish Robot Actuated by Piezoceramic Composite Actuators

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Journal of Bionic Engineering 2011年第2期8卷 158-164页

作者： Quang Sang Nguyen Hoon cheol Park Doyoung byun Biomimetics and bltelligent Microsystems Laboratory Department of Advanced Technology Fusion Konkuk University Seoul 143-701 South Korea Department of Advanced Technology Fusion Konkuk University Seoul 143-701 South Korea Department of Aerospace Engineering Konkuk University Seoul 143-701 South Korea

In this work, a three-dimensional （3D） Computational Fluid Dynamics （CFD） model was built to simulate the tail fin motion of a fish robot actuated by a piezoceramic composite actuator, and to determine the maximum thrust tail-beat frequency. A simulation of the tail fin at a tail-beat frequency was performed to confirm measured thrust data from a previous study. The computed and measured thrusts were in good agreement. A series of thrust simulations were conducted for various tail-beat frequencies to confirm the maximum thrust frequency that was obtained from thrust measurements in the previous study. The largest thrust was calculated at a tail-beat frequency of 3.7 Hz and vortices around the tail were fully separated. The calculated maximum thrust tail-beat frequency was in good agreement with the measured frequency. Flow characteristics during tail fin motion were examined to explain why the largest thrust occurred at this particular tail-beat frequency.

关键词： fish robot CFD LIPCA thrust measurement thrust analysis composite actuator vortex shedding

The Role of Elytra in Beetle Flight: Ⅰ.Generation of Quasi-Static Aerodynamic Forces

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Journal of Bionic Engineering 2010年第4期7卷 354-363页

作者： Patar Ebenezer Sitorus Hoon cheol Park Doyoung byun Nam Seo Goo cheol Heui Han National Research Laboratory for Biomimetics and Intelligent Microsystems Konkuk University Department of Advanced Technology Fusion Konkuk University Department of Aerospace Information System Engineering Konkuk University Department of Aeronautical and Mechanical Design Chungju National University

We conducted a comprehensive study to investigate the aerodynamic characteristics and force generation of the elytra of abeetle,Allomyrina *** analysis included wind tunnel experiments and three-dimensional computational fluiddynamics simulations using ANSYS-CFX *** first approach was a quasi-static study that considered the effect ofinduced flapping flow due to the flapping motion of the fore-wings (elytra) at a frequency of around 30 Hz to 40 *** dihedralangle was varied to represent flapping motion during the upstroke and *** found that an elytron producespositive lift at 0° geometric angle of attack,negative lift during the upstroke,and always produces drag during both the upstrokeand *** also found that the lift coefficient of an elytron does not drop even at a very high geometric angle of *** a beetle with a body weight of 5 g,based on the quasi-static method,the fore-wings (elytra) can produce lift of less than 1%of its body weight.

关键词： elytra angle of attack dihedral angle CFD wind tunnel test

Wetting Characteristics of Insect Wing Surfaces

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Journal of Bionic Engineering 2009年第1期6卷 63-70页

作者： Doyoung byun Jongin Hong Saputra Jin Hwan Ko Young Jong Lee Hoon cheol Park Bong-Kyu byun Jennifer R.Lukes Department of Aerospace Information Engineering Artificial Muscle Research CenterKonkuk UniversitySeoul 143-701Republic of Korea Department of Mechanical Engineering and Applied Mechanics University of PennsylvaniaPA 19104USA Department of Advanced Technology Fusion Artificial Muscle Research CenterKonkuk UniversitySeoul 143-701Republic of Korea Korea National Arboretum PocheonKyoungki 487-821Republic of Korea

Biological tiny structures have been observed on many kinds of surfaces such as lotus leaves,which have an effect on the coloration of Morpho butterflies and enhance the hydrophobicity of natural *** investigated the micro-scale and nano-scale structures on the wing surfaces of insects and found that the hierarchical multiple roughness structures help in enhancing the *** examining 10 orders and 24 species of flying Pterygotan insects,we found that micro-scale and nano-scale structures typically exist on both the upper and lower wing surfaces of flying *** tiny structures such as denticle or setae on the insect wings enhance the hydrophobicity,thereby enabling the wings to be cleaned more *** the hydrophobic insect wings undergo a transition from Cassie to Wenzel states at pitch/size ratio of about *** order to examine the wetting characteristics on a rough surface,a biomimetic surface with micro-scale pillars is fabricated on a silicon wafer, which exhibits the same behavior as the insect wing,with the Cassie-Wenzel transition occurring consistently around a pitch/width value of 20.

关键词： insect wing superhydrophobicity mimicry hierarchical structure micro- and nano-scale structures Cassie-Wenzel transition

Curcumin attenuates the release of pro-inflammatory cytokines in lipopolysaccharide-stimulated BV2 microglia

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Acta Pharmacologica Sinica 2007年第10期28卷 1645-1651页

作者： Jae-dong LEE cheol PARK yung hyun CHOI Gi-young KIM Department of Microbiology College of Natural Sciences Pusan National UniversityBusan 609-735 Department of Biochemistry Dongeui University College of Oriental MedicineBusan 614-054Korea Faculty of Applied Marine Science Cheju National UniversityJeju-siJeju Special Self-Governing Province 690-756Korea

Aim:Pro-inflammatory mediators,such as prostaglandin E2（PGE2） and nitric oxide（NO）,and pro-inflammatory cytokines such as interleukin （IL）-1β,IL-6,and TNF-α,play pivotal roles in brain *** anti-inflammatory properties are knownto be associated with significant reductions in pro-inflammatory mediators in *** the present study we investigate whether the effects of curcumin onthe production of pro-inflammatory mediators in lipopolysaccharide （LPS）-stimu-lated BV2 ***:Curcumin were administered and their effects onLPS-induced pro-inflammatory mediators were monitored by Western blottingand ***:Curcumin significantly inhibited the release of NO,PGE2,and pro-inflammatory cytokines in a dose-dependent *** alsoattenuated the expressions of inducible NO synthase and cyclooxygenase-2 mRNAand protein ***,curcumin suppressed NF-kB activation via thetranslocation of p65 into the *** data also indicate that curcumin exertsanti-inflammatory properties by suppressing the transcription of proinflammatorycytokine genes through the NF-kB signaling ***:Anti-inflam-matory properties of curcumin may be useful for treating the inflammatory anddeleterious effects of microglial activation in response to LPS stimulation.

关键词： curcumin inducible nitric oxide synthase cyclooxygenase-2 pro-inflammatory cytokines NF-kB