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Heat Transfer between Casting and Die during High Pressure Die Casting Process of AM50 Alloy-Modeling and Experimental Results

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Journal of Materials Science & Technology 2008年第1期24卷 131-135页

作者： Zhipeng GUO Shoumei XIONG sang-hyun cho Jeong-Kil choi Key Laboratory for Advanced Manufacturing by Materials Processing Technology Department of Mechanical Engineering Tsinghua University Beijing 100084 China Advanced Material R＆D Center Korean Institute of Industrial Technology 994-32 Dongchun-Dong Yonsu-Ku Inchon Korea

A method based on die casting experiments and mathematic modeling is presented for the determination of the heat flow density （HFD） and interfacial heat transfer coefficient （IHTC） during the high pressure die casting （HPDC） *** were carried out using step shape casting and a commercial magnesium alloy,*** profiles were measured and recorded using thermocouples embedded inside the die. Based on these temperature readings,the HFD and IHTC were successfully determined and the calculation results show that the HFD and IHTC at the metal-die interface increases sharply right after the fast phase injection process until approaching their maximum values,after which their values decrease to a much lower level until the dies are *** patterns of heat transfer behavior were found between the die and the casting at different *** thinner the casting was,the more quickly the HFD and IHTC reached their steady ***,the values for both the HFD and IHTC values were different between die and casting at different thicknesses.

关键词： : Interfacial heat transfer coefficient High pressure die casting process AM50 Magnesium alloy

Development of high performance casting analysis software by coupled parallel computation

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China Foundry 2007年第3期4卷 215-219页

作者： sang hyun cho Jeong Kil choI Center For e-Design Korea Institute of Industrial Technology994-32Dongchun-DongYeonsu-GuIncheon406-800Korea

Up to now,so much casting analysis software has been continuing to develop the new access way to real casting processes. Those include the melt flow analysis,heat transfer analysis for solidification calculation,mechanical property predictions and microstructure predictions. These trials were successful to obtain the ideal results comparing with real situations,so that CAE technologies became inevitable to design or develop new casting processes. But for manufacturing fields,CAE technologies are not so frequently being used because of their difficulties in using the software or insufficient computing performances. To introduce CAE technologies to manufacturing field,the high performance analysis is essential to shorten the gap between product designing time and prototyping time. The software code optimization can be helpful,but it is not enough,because the codes developed by software experts are already optimized enough. As an alternative proposal for high performance computations,the parallel computation technologies are eagerly being applied to CAE technologies to make the analysis time shorter. In this research,SMP (Shared Memory Processing) and MPI (Message Passing Interface) (1) methods for parallelization were applied to commercial software "Z-Cast" to calculate the casting processes. In the code parallelizing processes,the network stabilization,core optimization were also carried out under Microsoft Windows platform and their performances and results were compared with those of normal linear analysis codes.

关键词： parallel computation message passing interface casting analysis SMP performance improvement

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Neural Regeneration Research 2011年第4期6卷 283-287页

作者： Sung Ho Jang sang-hyun cho Mi Young Lee Yong hyun Kwon Min Cheul Chang Department of Physical Medicine and Rehabilitation College of MedicineYeungnam UniversityDaegu 705-717Republic of Korea Department of Physical Therapy Institute of Health ScienceYonsei University College of Health ScienceWounju-siGangwon-do 220-710Republic of Korea Department of Physical Therapy College of Health and TherapyDaegu Haany UniversitySuseongkuDaegu 706-060Republic of Korea Department of Physical Therapy Yeungnam College of Science and TechnologyNamkuDaegu 705-703Republic of Korea

The corticospinal tract （CST） is one of the most important neural tracts for motor function in the human brain. Little is known about age-related changes of the CST. tn this study, we tried to evaluate age-related changes of the CST using diffusion tensor imaging in 60 healthy subjects. The diffusion tensor imaging result revealed that the tract number and fractional anisotropy value were decreased, and the apparent diffusion coefficient （ADC） value was increased with aging. The distribution showed a semilog pattern for tract number, fractional anisotropy and ADC of the CST, and the pattern of each graph was near-linear. When compared with the diffusion tensor imaging parameters of subjects in the 20 s age group, tract number and fractional anisotropy values were significantly decreased in the 50 s-70 s age groups. Likewise, the ADC value was significantly higher in the 50 s-70 s age groups. The CST in the brain of normal subjects degenerated continuously from the 20 s to the 70 s, with a near-linear pattern, and degeneration of the CST began to manifest significantly in the subjects in their 50 s, compared with the subjects in their 20 s.

关键词： corticospinal tract motor function aging diffusion tensor imaging

Red ginseng for atopic dermatitis

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World Journal of Dermatology 2014年第3期3卷 58-63页

作者： sang hyun cho Department of Dermatology Incheon St.Mary’s Hospital College of Medicine The Catholic Universityof Korea Seoul 403-720 South Korea

Red ginseng is known for its significant biological activities which include anti-inflammation. Red ginseng may be used for the management and prevention of atopic dermatitis based on its effect on an atopic dermatiti... 详细信息

关键词： Red ginseng Atopic dermatitis Allergy Dermatitis Inflammation

Lichen Planus Pigmentosus Inversus:Two Case Reports

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International Journal of Dermatology and Venereology 2022年第2期5卷 116-118页

作者： Se Hoon Lee Minah cho Yu Jin Han Yu Ri Woo sang hyun cho Jeong Deuk Lee Hei Sung Kim Department of Dermatology Incheon St.Mary’s HospitalThe Catholic University of KoreaSeoulSouth Korea Department of Biomedicine&Health Sciences The Catholic University of KoreaSeoulSouth Korea.

Introduction:Lichen planus pigmentosus inversus(LPPI)is a rare a rare variant of lichen planus characterized by hyperpigmented patches with predominating localization in intertriginous *** to its rarity,only a few LPPI cases are *** herein describe two rare cases of *** presentation:The two patients were all with a brownish macular lesion on the intertriginous area.A diagnosis of LPPI was made based on their clinical manifestations,dermoscopic features,and histopathologic features,which revealed an interface change,lichenoid infiltration,and pigmentary ***:LPPI is pruritic or asymptomatic,hyperpigmented macules and patches on the flexural *** axillae and flanks were the most commonly affected areas,followed by the groin and *** half of the female patients had inframammary fold *** shows higher female predominance than Lichen planus *** were fewer cases that lasted more than 3 years compared to ***:LPPI is a rare variant of lichen planus,with a locational characteristic and female ***,in the case of a pigmented disease occurring in the flexural folds,it should be placed in the differential diagnosis.

关键词： lichen planus pigmentosus lichen planus pigmentosus inversus

A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 813-834页

作者： Chanhyeong cho Byeori Kim Haehyun cho Taek-Young Youn Department of Cyber Security Dankook UniversityYongin16890Republic of Korea Department of Software Soongsil UniversitySeoul07027Republic of Korea

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly ***,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient *** paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative *** bundle includes updated information,allowing only the updated portions to be reencrypted when changes *** encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates *** proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext *** utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those *** approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data *** validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size *** show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size ***,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

关键词： Cloud collaboration mode of operation data update efficiency

薄板坯连铸连轧钛铌微合金HSLA和UHSS钢的研发

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薄板坯连铸连轧钛铌微合金HSLA和UHSS钢的研发

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

2019全国高效连铸应用技术及铸坯质量控制研讨会

作者： Peng Zhang Xiaoping Ma sang-hyun cho Shuhe Yang Jay Patel Erminio Cerilli Joseph Miskiw Kate Kuuskman 唐杰民 research and product development Algoma Steel Inc. steelmaking and caster Algoma Steel Inc. DSPC and cold mill Algoma Steel Inc.

为满足80级高强度低合金钢、90级超高强度钢的要求,使用薄板坯连铸连轧生产热轧卷材,研究化学成分和热轧工艺参数对机械性能的影响。通过添加钛(Ti)和铌(Nb)微合金元素,采用细晶粒强化、沉淀强化、优化工艺参数手段,获得了较高的强度。...

为满足80级高强度低合金钢、90级超高强度钢的要求,使用薄板坯连铸连轧生产热轧卷材,研究化学成分和热轧工艺参数对机械性能的影响。通过添加钛(Ti)和铌(Nb)微合金元素,采用细晶粒强化、沉淀强化、优化工艺参数手段,获得了较高的强度。冶炼和连铸工艺是控制钢的内外在质量的关键,对此进行了阐述。高强度低合金钢在汽车、能源、农业、建筑等行业有着广泛的应用,这类钢通常是低碳

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Fruit Ripeness Prediction Based on DNN Feature Induction from Sparse Dataset

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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