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Relationship between the zonal displacement of the western Pacific subtropical high and the dominant modes of low-tropospheric circulation in summer

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Progress in Natural Science:Materials International 2008年第2期18卷 161-165页

作者： Chan-Su ryu Center for Asian Monsoon and Climate Environment Research Chosun University Gwangju Republic of Korea

The zonal displacement of the western Pacific subtropical high remarkably influences the climate anomalies in China. In this paper,a new zonal index of the subtropical high is defined by modifying previous indices,and is used to investigate the relationship between the zonal displacement of the subtropical high and the dominant modes of 850-hPa circulations. It is found that the zonal displacement of the subtropical high is significantly correlated with the first two leading modes of circulations. In particular,the correlation coefficient between the index and the time series associated with the second mode is as high as 0.78 in 1958-2003 (46 years). Since the second mode is not associated with significant anomalies of sea surface temperatures,the above results imply the diffculty in seasonal forecasting of the zonal displacement of the subtropical high. In addition,the interannual variability in the zonal displacement of the subtropical high has been considerably enhanced since 1978,due to the effects of both dominant modes,especially the second mode. This is likely to account for the frequent occurrence of anomalous climate in China during the recent two decades.

关键词： Western Pacific subtropical high General circulation Dominant mode Interannual variability Interdecadal variation

Ubiquitin homeostasis: from neural stem cell differentiation to neuronal development

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Neural Regeneration Research 2015年第8期10卷 1209-1210页

作者： Han-Wook ryu Kwon-Yul ryu Department of Life Science University of Seoul

Ubiquitin（Ub）is a well-known eukaryotic protein that exerts diverse signaling functions inside the cells,including targeting its substrates for proteasomal degradation（Hershko and Ciechanover,1998）.

关键词： Ubiquitin neuronal homeostasis eukaryotic sequential targeting diverse suppression maintain impaired

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Applying machine learning techniques to predict detonation initiation fromhot spots

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Energy and AI 2022年第3期9卷 121-127页

作者： Je Ir ryu Department of Mechanical Engineering University of California-BerkeleyBerkeleyCA 94720USA

As hot spots can be a source of detonation initiation by autoignition in a reactive mixture, understanding hotspot initiated detonation is significantly important for energy-related applications of detonation. Although theZel’dovich reactivity gradient theory is extremely useful to predict reaction propagation modes from hot spots,the prediction is limited due to the changes in the unburnt mixture during the induction time. In the currentstudy, machine learning based estimation methods by training the numerical simulation result data set aresuggested to avoid the extensive and empirical effort to find initial conditions of hot spot initiated detonationin inhomogeneous mixtures. The data set was obtained from the detailed numerical simulations with variousconditions of hot spots and divided into training and test data sets. Some variables were normalized withothers to avoid multicollinearity. Three different machine learning techniques, logistic regression, classificationand regression trees, and artificial neural network, were utilized to develop prediction models. Using thedeveloped models by machine learning approaches, the modes of hot spot initiated reaction front propagationcan be predicted without computationally expensive numerical simulations. The accuracies of the machinelearning based prediction models were significantly improved compared to the baseline model simply usingthe Zel’dovich reactivity gradient theory. These models can be utilized as preliminary prediction methods ofhot spot induced detonation initiation conditions for further detailed numerical simulations and dominantinput variables.

关键词： Detonation Deflagration Hydrogen Syngas Logistic regression CART Artificial neural network

Organic solar cells for indoor power generation

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Science China Chemistry 2020年第1期63卷 1-2页

作者： Hwa Sook ryu Han Young Woo Department of Chemistry College of Science Korea University

During last decades,organic solar cells(OSCs)have achieved remarkable advancements via extensive studies on the optimization of photovoltaic donor/acceptor(D/A)materials,device fabrication,and the D/A bulk heterojunction *** conversion efficiencies(PCEs)up to〜16%for single junction cells and over 17%PCEs were successfully demonstrated for tandem OSC devices[1,2].OSCs may find real industrial applications soon,including building integrated photovoltaics,portable power sources and indoor power generation for low power consumption electronic devices(i.e.,internet of things(IOT)sensors).Among them,indoor applications have great potentials because OSCs can convert indoor lights into electricity more efficiently compared to inorganic counterparts[3].

关键词： D/A power portable

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A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect Prediction

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Journal of Computer Science & Technology 2015年第5期30卷 969-980页

作者： Duksan ryu Jong-In Jang Jongmoon Baik School of Computinq Korea Advanced Institute of Science and Technology Yuseong-gu Daejeon 305-701 Korea

Software defect prediction （SDP） is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires sufficient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction （CPDP） using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor （HISNN） method that performs a hybrid classification selectively learning local knowledge （via k-nearest neighbor） and global knowledge （via na/ve Bayes）. Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD （probability of detection） or high PF （probability of false alarm） which is impractical to overall performance as well as high PD and low PF. use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.

关键词： software defect analysis instance-based learning nearest-neighbor algorithm data cleaning

Comparison of different nutritional assessments in detecting malnutrition among gastric cancer patients

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World Journal of Gastroenterology 2010年第26期16卷 3310-3317页

作者： Seung Wan ryu In Ho Kim Department of Surgery and Division of Gastrointestinal Surgery The Keimyung University School of Medicine Daegu 700-712 South Korea

AIM: To evaluate the prevalence of preoperative and postoperative malnutrition and the relationships between objective and subjective nutritional assessment of gastric cancer patients. METHODS: From October 2005 to July 2006, we studied 80 patients with no evidence of recurrent disease and no loss to follow-up after curative surgery for gastric cancer. In this group, 9 patients underwent total gastrectomy and 71 patients subtotal gastrectomy. At admission, 6 and 12 mo after surgery, the patients were assessed on the subjective global assessment (SGA), nutritional risk screening (NRS-2002), nutritional risk index (NRI) and by anthropometric measurements and laboratory data. Differences between the independent groups were assessed with the Student's t test and oneway analysis of variance. Spearman's rank correlation coefficients were calculated to evaluate the association between the scores and variables. RESULTS: The prevalence of malnutrition at admissionwas 31% by SGA and 43% by NRS-2002. At admission, the anthropometric data were lower in the malnourished groups defined by the SGA and NRS-2002 assessments, but did not differ between the groups using the NRI assessment. Body weight (BW), body mass index (BMI), triceps skin fold and midarm circumference were significantly reduced, but the total lymphocyte count, albumin, protein, cholesterol and serum iron levels did not decrease during the postoperative period. Six months after surgery, there was a good correlation between the nutritional assessment tools (SGA and NRS-2002) and the other nutritional measurement tools (BW, BMI, and anthropometric measurements). However, 12 mo after surgery, most patients who were assessed as malnourished by SGA and NRS-2002 had returned to their preoperative status, although their BW, BMI, and anthropometric measurements still indicated a malnourished status. CONCLUSION: A combination of objective and subjective assessments is needed for the early detection of the nutritional status

关键词： Gastrectomy Malnutrition Nutritional assessment Nutritional risk screening Postoperative follow up Subjective global assessment

A Reprocessing Model for Complete Execution of RFID Access Operations on Tag Memory

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Journal of Computer Science & Technology 2012年第1期27卷 213-224页

作者： Wooseok ryu Bonghee Hong Joonho Kwon Ge Yu Department of Computer Engineering Pusan National UniversityBusan 609-735Korea Institute of Logistics Information Technology Pusan National UniversityBusan 609-735Korea School of Information Science and Engineering Northeastern UniversityShenyang 110004China

This paper investigates the problem of inconsistent states of radio frequency identification （RFID） tag data caused by incomplete execution of read/write operations during access to RFID tag memory. Passive RFID tags require RF communication to access memory data. This study is motivated by the volatility of RF communication, where instability is caused by intermittent connections and uncertain communication. If a given tag disappears from the communication area of the reader during the reading or writing of tag data, the operation is incomplete, resulting in an inconsistent state of tag data. To avoid this inconsistency, it is necessary to ensure that any operations on tag memory are completed. In this paper, we propose an asynchronous reprocessing model for finalizing any incomplete execution of read/write operations to remove inconsistent states. The basic idea is to resume incomplete operations autonomously by detecting a tag＇s re-observation from any reader. To achieve this, we present a concurrency control mechanism based on continuous query processing that enables the suspended tag operations to be re-executed. The performance study shows that our model improves the number of successful operations considerably in addition to suppressing inconsistent data access completely.

关键词： asynchronous reprocessing concurrency control continuous query RFID tag access operation

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Connolly Surface on an Atomic Structure via Voronoi Diagram of Atoms

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Journal of Computer Science & Technology 2006年第2期21卷 255-260页

作者： Joonghyun ryu Rhohun Park Deok-Soo Kim Voronoi Diagram Research Center Hanyang University Seoul Korea Department of Industrial Engineering Hanyang University Seoul Korea

One of the most important geometric structures of a protein is the Connolly surface of protein since a Connolly surface plays an important role in protein folding, docking, interactions between proteins, amongst other things. This paper presents an algorithm for precisely and efficiently computing the Connolly surface of a protein using a proposed geometric construct called β-shape based on the Voronoi diagram of atoms in the protein. Given the Voronoi diagram of atoms based on the Euclidean distance from the atom surfaces, the proposed algorithm first computes a β-shape with an appropriate probe. Then, the Connolly surface is computed by employing the blending operation on the atomic complex of the protein by the given probe.

关键词： protein Connolly/molecular surface β-shape Voronoi diagram of atoms blending surface

Effects of dispersoid preforming via multistep sintering of oxide dispersion-strengthened CoCrFeMnNi high-entropy alloy

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Journal of Materials Science & Technology 2023年第9期140卷 187-200页

作者： SeungHyeok Chung Ji Ho Shin Ho Jin ryu Department of Nuclear and Quantum Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea Central Research Institute Korea Hydro and Nuclear Power Co.Ltd.(KHNP)Daejeon 34101Republic of Korea

Dispersoid formation and microstructural evolution in an oxide dispersion-strengthened CoCrFeMnNi high-entropy alloy(HEA)using a newly designed multistep sintering process are *** proposed multistep sintering consists of a dispersoid preforming heat treatment of as-milled 0.1 wt%Y_(2)O_(3)-CoCrFeMnNi high-entropy alloy powders at 800℃,followed by sintering at 800–1000℃ under uniaxial *** the conventional single-step sintered bulk,the coarsened BCC Y_(2)O_(3)dispersoids mainly form with an incoherent interface with the HEA *** contrast,finer FCC Y_(2)O_(3)dispersoids,an atypical form of Y_(2)O_(3),are formed in the matrix region after multistep *** of FCC Y_(2)O_(3)disper-soids is initiated on the favorable facet,the{111}plane of the austenitic matrix,with the formation of a semi-coherent interface with the matrix during the dispersoid preforming heat treatment and it maintains its refined size even after *** is found that dispersoid preforming prior to sintering appears promising to control the finer dispersoid formation and refined grain structure.

关键词： Oxide dispersion strengthening High-Entropy alloy Multistep sintering Dispersoid preforming Microstructure evolution Interfacial structure