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Few-Shot Graph Classification with Structural-Enhanced Contrastive Learning for Graph Data Copyright Protection

Tsinghua Science and Technology 2024年第2期29卷 605-616页

作者： Kainan Zhang DongMyung Shin daehee Seo Zhipeng Cai Department of Computer Science Georgia State UniversityAtlantaGA 30303USA LSWare Inc. Seoul 08504Republic of Korea College of Intelligence Information Engineering Sangmyung UniversitySeoul 03016Republic of Korea

Open-source licenses can promote the development of machine learning by allowing others to access,modify,and redistribute the training ***,not all open-source licenses may be appropriate for data sharing,as some may not provide adequate protections for sensitive or personal information such as social network ***,some data may be subject to legal or regulatory restrictions that limit its sharing,regardless of the licensing model ***,obtaining large amounts of labeled data can be difficult,time-consuming,or expensive in many real-world ***-shot graph classification,as one application of meta-learning in supervised graph learning,aims to classify unseen graph types by only using a small amount of labeled ***,the current graph neural network methods lack full usage of graph structures on molecular graphs and social network *** structural features are known to correlate with molecular properties in chemistry,structure information tends to be ignored with sufficient property information ***,the common binary classification task of chemical compounds is unsuitable in the few-shot setting requiring novel ***,this paper focuses on the graph classification tasks of a social network,whose complex topology has an uncertain relationship with its nodes'*** two multi-class graph datasets with large node-attribute dimensions constructed to facilitate the research,we propose a novel learning framework that integrates both meta-learning and contrastive learning to enhance the utilization of graph topological *** experiments demonstrate the competitive performance of our framework respective to other state-of-the-art methods.

关键词： few-shot learning contrastive learning data copyright protection

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Lightweight Super-Resolution Model for Complete Model Copyright Protection

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Tsinghua Science and Technology 2024年第4期29卷 1194-1205页

作者： Bingyi Xie Honghui Xu YongJoon Joe daehee Seo Zhipeng Cai Department of Computer Science Georgia State UniversityAtlantaGA 30303USA LSWare Inc. Seoul 08504Republic of Korea College of Intelligence Information Engineering Sangmyung UniversityRepublic of KoreaSeoul 03016

Deep learning based techniques are broadly used in various applications, which exhibit superior performance compared to traditional methods. One of the mainstream topics in computer vision is the image super-resolution task. In recent deep learning neural networks, the number of parameters in each convolution layer has increased along with more layers and feature maps, resulting in better image super-resolution performance. In today’s era, numerous service providers offer super-resolution services to users, providing them with remarkable convenience. However, the availability of open-source super-resolution services exposes service providers to the risk of copyright infringement, as the complete model could be vulnerable to leakage. Therefore, safeguarding the copyright of the complete model is a non-trivial concern. To tackle this issue, this paper presents a lightweight model as a substitute for the original complete model in image super-resolution. This research has identified smaller networks that can deliver impressive performance, while protecting the original model’s copyright. Finally, comprehensive experiments are conducted on multiple datasets to demonstrate the superiority of the proposed approach in generating super-resolution images even using lightweight neural networks.

关键词： lightweight adversarial learning image super-resolution copyright protection

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Weight gain after 35 years of age is associated with increased breast cancer risk: findings from a large prospective cohort study

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Cancer Biology & Medicine 2024年第8期21卷 651-655页

作者： Katherine De la Torre Woo-Kyoung Shin Hwi-Won lee Dan Huang Sukhong Min Aesun Shin Wonshik Han daehee Kang Department of Preventive Medicine Seoul National University College of Medicine Department of Biomedical Sciences Seoul National University Graduate School Division of Food and Pharmaceutical Technology Mokwon University Integrated Major in Innovative Medical Science Seoul National University Graduate School Cancer Research Institute Seoul National University Department of Surgery Seoul National University College of Medicine Biomedical Research Institute Seoul National University Hospital

Adiposity affects lifetime estrogen exposure, which is a key factor in breast carcinogenesis. However, adiposity effects,often assessed as the body mass index （BMI）, on pre-and post-menopausal breast cancer risk are paradoxical. Body weight gain may reflect body fat mass accumulation during adulthood better than the BMI, potentially representing age-related metabolic changes1.

关键词： ADULTHOOD

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Neuroprotective Effects of the Biologically Active Components From Traditional Korean Medicine on the Brain Ischemia in Rats

Neuroprotective Effects of the Biologically Active Component...

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第十五届国际药理学大会

作者： daehee lee Miyeon Kim Jinhee Jung Seongmi Choi Hocheol Kim Dep.of Herbal Pharmacology College of Oriental MedicineKyung Hee Univ.SeoulKorea. Korea Institute of Science and Technology for Eastern Medicien （KISTEM） NeuMed Co. Korea Institute of Science and Technology for Eastern Medicien （KISTEM） NeuMed Co. Korea Institute of Science and Technology for Eastern Medicien （KISTEM） NeuMed Co. Dep.of Herbal Pharmacology College of Oriental MedicineKyung Hee Univ.SeoulKorea.

＜正＞ The purpose of the study is to observe the neuroprotective components of herbs which have been used to treat stroke in traditional Korean medicine. For global cerebral ischemia,male wister rats weighing 180 ± 10 g were used and common carotid arteries and vertebral arteries were occluded for 10 min. For focal cerebral ischemia,male SD rats weighing 300 ± 10 g were used and the right middle cerebral artery were occluded for 2 hrs. As the results,decursin （10 mg/kg） showed 36.46% , gomisin A. （30 mg/kg） showed 41.18% of neurorprotection in global cerebral ischemia. Nodakenin （30 mg/kg）. wogonin （30 mg/kg） showed 61. 33% and 42.67% of neuroprotection effect compared with control,respectively. Gomisin A showed the highest effect as 64.67 % of neuroprotection in focal cerebral ischemia. In conclusion,it could be suggested that gomisin A in Schizandra chinensis. decursin and nodakenin in Angelica gigas. wogonin and baicalein in Scutellaria baicalensis are effective components for the treatment of stroke.

关键词： Scutellaria Schizandra Angelica brain ischemia stroke

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An unsupervised anomaly detection framework for detecting anomalies in real time through network system’s log files analysis

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High-Confidence Computing 2021年第2期1卷 1-6页

作者： Vannel Zeufack Donghyun Kim daehee Seo Ahyoung lee Department of Computer Science Kennesaw State UniversityMariettaGA 30060USA Department of Computer Science Georgia State UniversityAtlantaGA 30303USA Faculty of Artificial Intelligence and Data Engineering Sangmyung UniversitySeoul 03016South Korea

Nowadays,in almost every computer system,log files are used to keep records of occurring *** log files are then used for analyzing and debugging system *** to this important utility,researchers have worked on finding fast and efficient ways to detect anomalies in a computer system by analyzing its log *** in log-based anomaly detection can be divided into two main categories:batch log-based anomaly detection and streaming log-based anomaly *** log-based anomaly detection is computationally heavy and does not allow us to instantaneously detect *** the other hand,streaming anomaly detection allows for immediate ***,current streaming approaches are mainly *** this work,we propose a fully unsupervised framework which can detect anomalies in real *** test our framework on hdfs log files and successfully detect anomalies with an F-1 score of 83%.

关键词： Anomaly detection Unsupervised machine learning Clustering OPTICS Log analysis

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Frequent low dose alcohol intake increases gastric cancer risk: the Health Examinees-Gem (HEXA-G) study

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Cancer Biology & Medicine 2022年第8期19卷 1224-1234页

作者： Hwi-Won lee Dan Huang Woo-Kyoung Shin Katherine de la Torre Minkyo Song Aesun Shin Jong-Koo lee daehee Kang Department of Biomedical Sciences Seoul National University Graduate SchoolSeoul 03080Korea Department of Preventive Medicine Seoul National University College of MedicineSeoul 03080Korea Integrated Major in Innovative Medical Science Seoul National University Graduate SchoolSeoul 03080Korea Department of Family Medicine Seoul National University HospitalSeoul 03080Korea

Objective:Epidemiological studies indicate that alcohol increases gastric cancer(GC)risk,yet most studies have focused on heavy alcohol intake,leaving other factors understudied.A comprehensive investigation of the effects of the frequency and amount of alcohol intake may help elucidate the GC risk associated with drinking ***:The Health Examinees-Gem(HEXA-G)study,a community-based large-scale prospective cohort study,enrolled Korean adults 40–69 years of age between the years 2004 and *** GC cases were identified through linkage to Korea Central Cancer Registry data until December 31,***-reported questionnaires were used to survey alcohol consumption-related factors(duration,frequency,amount,and type of alcoholic beverages).The frequency and amount of alcohol consumption were combined to explore GC risk according to 4 drinking patterns:“infrequent-light”,“frequent-light”,“infrequent-heavy”,and“frequent-heavy”.We used Cox proportional hazard models to estimate the adjusted hazard ratios(HRs)and 95%confidence intervals(CIs),and investigate the relationship between alcohol intake and GC ***:A total of 128,218 participants were included in the *** an average follow-up period of 8.6 years,462 men and 385 women were diagnosed with *** men,current drinkers showed a 31%greater risk of GC than non-drinkers(HR 1.31,95%CI 1.03–1.66),whereas no significant association was observed in *** men,GC risk was associated with a higher frequency(P trend 0.02)and dose of ethanol intake in grams(P trend 0.03).In men,the“frequent-light”(≥5 times/week and<40 g ethanol/day)drinking pattern was associated with a 46%greater risk of GC(HR 1.46,95%CI 1.02–2.07)than the“infrequent-light”pattern(<5 times/week and<40 g ethanol/day).Conclusions:This study suggests that frequent intake of alcohol,even in low quantities per session,increases GC *** research is warranted to evaluate the relationship between alcohol and GC in detai

关键词： Gastric cancer alcohol consumption drinking behavior prospective cohort Health Examinees-Gem(HEXA-G)study

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Link-Privacy Preserving Graph Embedding Data Publication with Adversarial Learning

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Tsinghua Science and Technology 2022年第2期27卷 244-256页

作者： Kainan Zhang Zhi Tian Zhipeng Cai daehee Seo the Department of Computer Science Georgia State UniversityAtlantaGA 30303USA the Department of Electrical and Computer Engineering George Mason UniversityFairfaxVA 22030USA the National Center of Excellence in Software Sangmyung UniversitySeoul 03016Republic of Korea

The inefficient utilization of ubiquitous graph data with combinatorial structures necessitates graph embedding methods,aiming at learning a continuous vector space for the graph,which is amenable to be adopted in traditional machine learning algorithms in favor of vector *** embedding methods build an important bridge between social network analysis and data analytics,as social networks naturally generate an unprecedented volume of graph data *** social network data not only brings benefit for public health,disaster response,commercial promotion,and many other applications,but also gives birth to threats that jeopardize each individual’s privacy and ***,most existing works in publishing social graph embedding data only focus on preserving social graph structure with less attention paid to the privacy issues inherited from social *** be specific,attackers can infer the presence of a sensitive relationship between two individuals by training a predictive model with the exposed social network *** this paper,we propose a novel link-privacy preserved graph embedding framework using adversarial learning,which can reduce adversary’s prediction accuracy on sensitive links,while persevering sufficient non-sensitive information,such as graph topology and node attributes in graph *** experiments are conducted to evaluate the proposed framework using ground truth social network datasets.

关键词： graph embedding privacy preservation adversarial learning

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iNID： An Analytical Framework for Identifying Network Models for Interplays among Developmental Signaling in Arabidopsis

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Molecular Plant 2014年第5期7卷 792-813页

作者： Daeseok Choi Jaemyung Choi Byeongsoo Kang Seungchul lee Young-hyun Cho Ildoo Hwang daehee Hwang School of Interdisciplinary Bioscience and Bioengineering POSTECH 790-784 Pohang Republic of Korea Department of Life Sciences POSTECH 790-784 Pohang Republic of Korea Department of New Biology DGIST Daegu 711-873 Republic of Korea Division of Integrative Biosciences and Biotechnologies POSTECH 790-784 Pohang Republic of Korea Center for Systems Biology of Plant Senescence and-Life History Institute for BasicScience DGIST Daegu 711-873 Republic of Korea

Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors （IEFs）. However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling （iNID） in Arabidopsis. iNID provides a comprehensive resource of （1） transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and （2） protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of （1） phytohormones and light and （2） phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid （BR）-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.

关键词： transcriptome analysis network analysis signal interplays development Arabidopsis.

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Facile synthesis of fully ordered L10-FePt nanoparticles with controlled Pt-shell thicknesses for electrocatalysis

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Nano Research 2017年第8期10卷 2866-2880页

作者： Yonghoon Hong Hee Jin Kim daehee Yang Gaehang lee Ki Min Nam Myung-Hwa Jung Young-Min Kim Sang-II Choi Won Seok Seo Department of Chemistry Sogang University Seou104107 Republic of Korea Department of Chemistry and Green-Nano Materials Research Center Kyungpook National University Daegu 41566 Repubfic of Korea Korea Basic Science Institute and University of Science and Technology Daejeon 34133 Republic of Korea Department of Chemistry Mokpo National University Jeonnam 58554 Republic of Korea Department of Physics Sogang University Seoul 04107 Republic of Korea Center for Integrated Nanostructure Physics Institute for Basic Science (IBS) Suwon 16419 Repubfic of Korea Department of Energy Science Sungkyunkwan University (SKKU) Suwon 16419 Republic of Korea

We report a simple one-step approach for the synthesis of -4 nm uniform and fully L10-ordered face-centered tetragonal （fct） FePt nanoparticles （NPs） embedded in -60 nm MCM-41 （fct-FePt NPs@MCM-41）. We controlled the Pt-shell thickness of the fct-FePt NPs by treating the fct-FePt NPs@MCM-41 with acetic acid （HOAc） or hydrochloric acid （HC1） under sonicafion, thereby etching the surface Fe atoms of the NPs. The fct-FePt NPs deposited onto the carbon support （fct-FePt NP/C） were prepared by mixing the fct-FePt NPs@MCM-41 with carbon and subsequently removing the MCM-41 using NaOH. We also developed a facile method to synthesize acid-treated fct-FePt NP/C by using a HF solution for simultaneous surface-Fe etching and MCM-41 removal. We studied the effects of both surface-Fe etching and Pt-shell thickness on the electrocatalytic properties of fct-FePt NPs for the methanol oxidation reaction （MOR）. Compared with the non-treated fct-FePt NP/C catalyst, the HOAc-treated and HCl-treated catalysts exhibit up to 34% larger electrochemically active surface areas （ECASAs）; in addition, the HCl-treated fct-FePt NP （with -1.0 nm Pt shell）/C catalyst exhibits the highest specific activity. The HF-treated fct-FePt NP/C exhibits an ECASA almost 2 times larger than those of the other acid-treated fct-FePt NP/C catalysts and shows the highest mass activity （1,435 mA·mgPt^-1, 2.3 times higher than that of the commercial Pt/C catalyst） and stability among the catalysts tested. Our findings demonstrate that the surface-Fe etching for the generation of the Pt shell on fct-FePt NPs and the Pt-shell thickness can be factors for optimizing the electrocatalysis of the MOR.

关键词： FePt face centered tetragonal bimetallic methanol oxidation reaction electrocatalysts

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A Novel Transparent and Auditable Fog-Assisted Cloud Storage with Compensation Mechanism

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Tsinghua Science and Technology 2020年第1期25卷 28-43页

作者： Donghyun Kim Junggab Son daehee Seo Yeojin Kim Hyobin Kim Jung Taek Seo Department of Computer Science Kennesaw State UniversityMariettaGA 30060USA Department of Information Security Engineering Soonchunhyang UniversityAsan 31538South Korea

This paper introduces a new fog-assisted cloud storage which can achieve much higher throughput compared to the traditional cloud-only storage architecture by reducing the traffics toward the cloud storage. The fog-storage service providers are transparency to end-users and therefore, no modification on the end-user devices is necessary. This new system is featured with(1) a stronger audit scheme which is naturally coupled with the proposed architecture and does not suffer from the replay attack and(2) a transparent and efficient compensation mechanism for the fog-storage service providers. We provide rigorous theoretical analysis on the correctness and soundness of the proposed system. To the best of our knowledge, this is the first paper to discuss about a storage data audit scheme for fog-assisted cloud storage as well as the compensation mechanism for the service providers of the fog-storage service providers.

关键词： fog computing cloud computing network storage data audit merkle hash tree integer factorization payment transparency

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