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Fruit Ripeness Prediction Based on DNN Feature Induction from Sparse Dataset

Computers, Materials & Continua 2021年第12期69卷 4003-4024页

作者： wan hyun cho Sang Kyoon Kim Myung Hwan Na In Seop Na Department of Statistics Chonnam National UniversityGwangju61186Korea Department of Electronics Eng. Mokpo National UniversityMuan58557Korea National Program of Excellence in Software Centre Chosun UniversityGwangju61452Korea

Fruit processing devices,that automatically detect the freshness and ripening stages of fruits are very important in precision ***,based on deep learning,many attempts have been made in computer image processing,to monitor the ripening stage of ***,it is timeconsuming to acquire images of the various ripening stages to be used for training,and it is difficult to measure the ripening stages of fruits accurately with a small number of *** this paper,we propose a prediction system that can automatically determine the ripening stage of fruit by a combination of deep neural networks(DNNs)and machine learning(ML)that focus on optimizing them in combination on several image ***,we used eight DNN algorithms to extract the color feature vectors most suitable for classifying them from the observed images representing each ripening ***,we applied seven ML methods to determine the ripening stage of fruits based on the extracted color ***,we propose an automatic prediction system that can accurately determine the ripeness in images of various fruits such as strawberries and tomatoes by a combination of the DNN and ML ***,we used the transfer learning method to train the proposed system on few image datasets to increase the training ***,we experimented to find out which of the various combinations of DNN and ML methods demonstrated excellent classification *** the experimental results,a combination of DNNs and multilayer perceptron,or a combination of DNNs and support vector machine or kernel support vector machine generally exhibited excellent classification ***,the combination of various DNNs and statistical classification models shows that the overall classification rate is ***,in the case of using tomato images,it was found that the classification rate for the combination of various DNNs and ML methods was generally similar to the results obtained

关键词： Ripening stage prediction deep neural network machine learning tomato strawberry small dataset

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Ungraded Matrix Factorizations as Mirrors of Non-orientable Lagrangians

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Acta Mathematica Sinica,English Series 2024年第1期40卷 26-42页

作者： Lino AMORIM Cheol-hyun cho Department of Mathematics Kansas State University138 Cardwell Hall1228 N.17th StreetManhattanKS 66506USA Department of Mathematical Sciences Research Institute of MathematicsSeoul National UniversitySan 56-1ShinrimdongGwanakguSeoul 47907South Korea

We introduce the notion of ungraded matrix factorization as a mirror of non-orientable Lagrangian *** ungraded matrix factorization of a polynomial W,with coefficients in a field of characteristic 2,is a square matrix Q of polynomial entries satisfying Q^(2)=W·*** then show that non-orientable Lagrangians correspond to ungraded matrix factorizations under the localized mirror functor and illustrate this construction in a few *** main example is the Lagrangian submanifold RP^(2)⊂CP^(2)and its mirror ungraded matrix factorization,which we construct and *** particular,we prove a version of Homological Mirror Symmetry in this setting.

关键词： Mirror symmetry non-orientable Lagrangian submanifold matrix factorization

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Automatic Classification for Various Images Collections Using Two Stages Clustering Method

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Open Journal of Applied Sciences 2013年第1期3卷 47-52页

作者： wan hyun cho In Seop Na Jun Yong choi Tae Hoon Lee Department of Statistics Chonnam National University Gwagnju Korea School of School of Electronic & Computer Engineering Chonnam National University Gwangju Korea

In this paper, we propose an automatic classification for various images collections using two stage clustering method. Here, we have used global and local image features. First, we review about various types of feature vector that is suita-ble to represent local and global properties of images, and similarity measures that can be represented an affinity be-tween these images. Second, we consider a clustering method for image collection. Here, we first build a coarser clus-tering by partitioning various images into several clusters using the flexible Mean shift algorithm and K-mean cluster-ing algorithm. Second, we construct dense clustering of images collection by optimizing a Gaussian Dirichlet process mixture model taking initial clusters as given coarser clustering. Finally, we have conducted the comparative experi-ments between our method and existing methods on various images datasets. Our approach has significant advantage over existing techniques. Besides integrating temporal and image content information, our approach can cluster auto-matically photographs without some assumption about number of clusters or requiring a priori information about initial clusters and it can also generalize better to different image collections.

关键词： Automatic Classification Images Collections Clustering Mean Shift Gaussian Dirichlet Processing Mixture Model

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Defect Detection Model Using Time Series Data Augmentation and Transformation

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Computers, Materials & Continua 2024年第2期78卷 1713-1730页

作者： Gyu-Il Kim hyun Yoo Han-Jin cho Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon-si16227Korea Contents Convergence Software Research Institue Kyonggi UniversitySuwon-si16227Korea Department of Energy IT Engineering Far East UniversityEumsung-gun27601Korea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon-si16227Korea

Time-series data provide important information in many fields,and their processing and analysis have been the focus of much ***,detecting anomalies is very difficult due to data imbalance,temporal dependence,and ***,methodologies for data augmentation and conversion of time series data into images for analysis have been *** paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to *** method of data augmentation is set as the addition of *** involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the *** addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into *** enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the *** anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat *** allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies *** performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to ***,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training *** proposed method can provide an important springboard for research in the field of anomaly detection using time series ***,it helps solve problems such as analyzing complex patterns in data lightweight.

关键词： Defect detection time series deep learning data augmentation data transformation

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Depolarization mitigated in ferroelectric Hf_(0.5)Zr_(0.5)O_(2)ultrathin films(<5 nm)on Si substrate by interface engineering

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Journal of Advanced Ceramics 2024年第3期13卷 282-292页

作者： Se hyun Kim Younghwan Lee Dong hyun Lee Geun Hyeong Park hyun Woo Jeong Kun Yang Yong Hyeon cho Young Yong Kim Min Hyuk Park Department of Materials Science and Engineering College of EngineeringSeoul National UniversitySeoul 08826Republic of Korea Research Institute of Advanced Materials College of EngineeringSeoul National UniversitySeoul 08826Republic of Korea Inter-university Semiconductor Research Center College of EngineeringSeoul National UniversitySeoul 08826Republic of Korea Pohang Accelerator Laboratory Pohang University of Science&TechnologyPohang 790784Republic of Korea

(Hf,Zr)O_(2)offers considerable potential for next-generation semiconductor devices owing to its nonvolatile spontaneous polarization at the ***,scaling this material to sub-5 nm thickness poses several challenges,including the formation of an interfacial layer and high trap *** particular,a low-k SiO_(2)interfacial layer is naturally formed when(Hf,Zr)O_(2)films are directly grown on a Si substrate,leading to high depolarization fields and rapid reduction of the remanent *** address these issues,we conducted a study to significantly improve ferroelectricity and switching endurance of(Hf,Zr)O_(2)films with sub-5 nm thicknesses by inserting a TiO_(2)interfacial *** deposition of a Ti film prior to Hf_(0.5)Zr_(0.5)O_(2)film deposition resulted in a high-k TiO_(2)interfacial layer and prevented the direct contact of Hf_(0.5)Zr_(0.5)O_(2)with *** findings show that the high-k TiO_(2)interfacial layer can reduce the SiO_(2)/Si interface trap density and the depolarization field,resulting in a switchable polarization of 60.2μC/cm^(2)for a 5 nm thick Hf_(0.5)Zr_(0.5)O_(2)***,we propose that inserting a high-k TiO_(2)interfacial layer between the Hf_(0.5)Zr_(0.5)O_(2)film and the Si substrate may offer a promising solution to enhancing the ferroelectricity and reliability of(Hf,Zr)O_(2)grown on the Si substrate and can pave the way for next-generation semiconductor devices with improved performance.

关键词： ferroelectric charge trapping hafnia depolarization

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Bone-targeted lipoplex-loaded three-dimensional bioprinting bilayer scaffold enhanced bone regeneration

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Regenerative Biomaterials 2024年第4期3卷 138-148页

作者： Woo-Jin Kim Jeong-hyun Ryu Ji Won Kim Ki-Tae Kim Hye-Rim Shin Heein Yoon hyun-Mo Ryoo Young-Dan cho Department of Molecular Genetics School of Dentistry and Dental Research InstituteSeoul National UniversitySeoul03080Republic of Korea Department of Periodontology School of Dentistry and Dental Research InstituteSeoul National University and Seoul National University Dental HospitalSeoul03080Republic of Korea

Clinical bone-morphogenetic protein 2(BMP2)treatment for bone regeneration,often resulting in complications like soft tissue inflammation and ectopic ossification due to high dosages and non-specific delivery systems,necessitates research into improved biomaterials for better BMP2 stability and *** tackle this challenge,we introduced a groundbreaking bone-targeted,lipoplex-loaded,three-dimensional bioprinted bilayer scaffold,termed the polycaprolactone-bioink-nanoparticle(PBN)scaffold,aimed at boosting bone *** encapsulated BMP2 within the fibroin nanoparticle based lipoplex(Fibroplex)and functionalized it with DSS6 for bone tissue-specific targeting.3D printing technology enables customized,porous PCL scaffolds for bone healing and soft tissue growth,with a two-step bioprinting process creating a cellular lattice structure and a bioink grid using gelatin-alginate hydrogel and DSS6-Fibroplex,shown to support effective nutrient exchange and cell growth at specific pore *** PBN scaffold is predicted through in silico analysis to exhibit biased BMP2 release between bone and soft tissue,a finding validated by in vitro osteogenic differentiation *** PBN scaffold was evaluated for critical calvarial defects,focusing on sustained BMP2 delivery,prevention of soft tissue cell infiltration and controlled fiber membrane pore size in *** PBN scaffold demonstrated a more than eight times longer BMP2 release time than that of the collagen sponge,promoting osteogenic differentiation and bone regeneration in a calvarial defect *** findings suggest that the PBN scaffold enhanced the local concentration of BMP2 in bone defects through sustained release and improved the spatial arrangement of bone formation,thereby reducing the risk of heterotopic ossification.

关键词： 3D bioprinting bone-targeting lipoplex BMP2 bone regeneration

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Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

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Journal of Meteorological Research 2024年第2期38卷 262-284页

作者： Yunjae cho hyun Mee KIM Eun-Gyeong YANG Yonghee LEE Jae-Bum LEE Soyoung HA Department of Atmospheric Sciences Yonsei UniversitySeoul 03722Republic of Korea Air Quality Forecasting Center National Institute of Environmental ResearchIncheon 22689Republic of Korea National Center for Atmospheric Research BoulderCO 80305USA University of Maryland Baltimore County BaltimoreMD 21250USA Global Modeling and Assimilation Office NASA Goddard Space Flight CenterGreenbeltMD 20771USA

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality *** data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the *** this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean *** nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological *** the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner *** indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological *** to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with *** effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the ***,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

关键词： meteorological data assimilation regional air quality forecast particulate matter concentration optimal model domain forecast error WRF-Chem

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Endoscopic ultrasound-guided tissue sampling induced pancreatic duct leak resolved by the placement of a pancreatic stent:A case report

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World Journal of Clinical Cases 2024年第9期12卷 1677-1684页

作者： Ki-hyun Kim Chang Hwan Park Eunae cho Yohan Lee Department of Internal Medicine Chonnam National University HospitalGwangju 61469South Korea Department of Gastroenterology Chonnam National University HospitalGwangju 61469South Korea

BACKGROUND Pancreatic ductal leaks complicated by endoscopic ultrasonography-guided tissue sampling(EUS-TS)can manifest as acute *** SUMMARY A 63-year-old man presented with persistent abdominal pain and weight ***:Laboratory findings revealed elevated carbohydrate antigen 19-9(5920 U/mL)and carcinoembryonic antigen(23.7 ng/mL)*** resonance imaging of the pancreas revealed an approximately 3 cm ill-defined space-occupying lesion in the inferior aspect of the head,with severe encasement of the superior mesenteric *** ductal adenocarcinoma was confirmed after pathological examination of specimens obtained by EUS-TS using the fanning *** and outcomes:The following day,the patient experienced severe abdominal pain with high amylase(265 U/L)and lipase(1173 U/L)*** tomography of the abdomen revealed edematous wall thickening of the second portion of the duodenum with adjacent fluid collections and a suspicious leak from either the distal common bile duct or the main pancreatic duct in the *** retrograde cholangiopancreatography revealed dye leakage in the head of the main pancreatic ***,a 5F 7 cm linear plastic stent was deployed into the pancreatic duct to divert the pancreatic *** patient’s abdominal pain improved immediately after pancreatic stent insertion,and amylase and lipase levels normalized within a *** chemotherapy was then *** Using the fanning method in EUS-TS can inadvertently cause damage to the pancreatic duct and may lead to clinically significant *** a pancreatic stent may immediately resolve acute pancreatitis and shorten the waiting time for curative *** using the fanning method during EUSTS,ductal structures should be excluded to prevent pancreatic ductal leakage.

关键词： Endoscopic ultrasound-guided tissue sampling Pancreatitis Pancreatic duct leak Pancreatic stent Case report

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Porously Reduced 2-Dimensional Bi_(2)O_(2)CO_(3) Petals for Strain-Mediated Electrochemical CO_(2) Reduction to HCOOH

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Energy & Environmental Materials 2024年第1期7卷 215-221页

作者： Won Seok cho Dae Myung Hong wan Jae Dong Tae hyung Lee Chul Jong Yoo Donghwa Lee Ho Won Jang Jong-Lam Lee Department of Materials Science and Engineering Pohang University of Science and Technology(POSTECH)Pohang Gyungbuk 37673Korea Department of Materials Science and Engineering Research Institute of Advanced Materials Seoul National UniversitySeoul 08826Korea

Here we introduce bismuth-based catalysts for the efficient electrochemical reduction of CO_(2)to formic acid(HCOOH),which are composed of petal-shaped Bi_(2)O_(2)CO_(3)(BOC)that spontaneously formed from Bi thin film in aqueous carbonate solution at room *** the electrochemical reduction process,the BOC petals transform to reduced BOC(R-BOC)consisting of individual BOC and Bi *** mismatch between both domains induces biaxial strain at the *** functional theory calculations suggest that the tensile strain on the Bi domain stabilizes the*Ocho intermediate,reducing the thermodynamic barrier toward CO_(2)conversion to *** with the thermodynamic benefit and the unique nanoporous petal-shaped morphology,R-BOC petals have a superior Faradaic efficiency of 95.9%at-0.8 V_(RHE)for the electrochemical conversion of CO_(2)to *** work demonstrates that the spontaneously formed binary phases with desirable lattice strain can increase the activity of bismuth catalysts to the CO_(2)reduction reaction;such a strategy can be applicable in design of various electrocatalysts.

关键词： bismuth carbon dioxide reduction formic acid heterointerfaces strain

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Gastric Cancer Disparities in the United States: Overcoming the Barriers

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International Journal of Clinical Medicine 2024年第1期15卷 19-30页

作者： Chul hyun Dohyun cho Englewood Hospital Medical Center Englewood NJ USA The Stomach Cancer Task Force Englewood Cliffs NJ USA

In this narrative review, we highlight the disparities in the incidence and mortality of gastric cancer across various racial and ethnic populations in the United States (US). Despite the low and decreasing trend in the incidence of gastric cancer in the US, the incidence remains significantly high among Asian and Hispanic Americans, showing a striking racial and ethnic disparity. The low survival rate of gastric cancer further accentuates the magnitude of this disparity. In addition, there is a marked funding disparity among different cancers in the US, reflecting the significantly lower level of support for cancers, such as gastric cancer, which are more prevalent in minority populations, compared to the cancers more prevalent among non-Hispanic Whites (NHW). Moreover, the economic burden from health disparities remains high. Although studies from the US and Asia suggest that screening for stomach cancer may be cost-effective, there is no currently available guideline for scree-ning high-risk populations in the US. A multidimensional framework involving the community, physicians, and policymakers is proposed to tackle these gastric cancer disparities and to develop population-based screening and surveillance programs to reduce the burden of gastric cancer.

关键词： Gastric (Stomach) Cancer Epidemiology Prevention Health Disparity Immigrants Minority Health Endoscopic Screening

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