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Yen H. Vo,Thanh V. Le,Hieu D. Nguyen,Tuong A. To,Hiep Q. Ha,Anh T. Nguyen,Anh N.Q. Phan,Nam T.S. Phan 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.64 No.-
Zirconium-based metal-organic framework MOF-808 was synthesized, and sulfated with aqueous sulfuric acid. Sulfated MOF-808 was utilized as a recyclable heterogeneous catalyst for the synthesis of quinazolinones from β-ketoesters and benzamides, and for the synthesis of benzimidazoles from β-ketoesters and o-phenylenediamines in glycerol as a green solvent. The sulfated MOF-808 catalyst was more active than many heterogeneous and homogeneous catalysts. The combination of the sulfated MOF-808 and glycerol was also effective for the reaction of o-aminothiophenols with β-diketones or cyclic β-diketones to produce benzothiazoles. To our best knowledge, MOF-based catalysts were not previously utilized as heterogeneous catalyst in glycerol as green solvent.
Design of a High Accuracy 3-Axis Coordinate Measuring Machine Working on the Shop Floor
Vo, Tran Anh,Dung, T.H.,Kim, Hyun Chul Trans Tech Publications, Ltd. 2015 Advanced materials research Vol.1125 No.-
<P>One of the key features of advanced manufacturing technologies is the metrology of geometric quantities. Coordinate measuring machines (CMMs) now are widely used to perform relevant measurements. Normally, the use of CMMs in traditional quality control rooms, isolated from the production floor, often proves unsuitable for effective and timely feedback on the manufacturing process. However, CMMs are sensitive to environmental factors such as humidity, suspended dust and oil, vibrations, and especially temperature. For this reason, measuring machines must to be designed with features that make them more resistant to the environmental influences on shop floor operations. The main goal of this work is to enhance accuracy of a CMM working on the shop floor conditions by design improvements and error compensation. A 3-axis CMM will be built with some improved designed features and a software compensation technique will be applied to enhance the machine accuracy.</P>
김태석 ( Tae-seok Kim ),( Anh H. Vo ),( Marvin John Ignacio ),( Khuong G. T. Diep ),김용국 ( Yong-guk Kim ) 한국정보처리학회 2023 한국정보처리학회 학술대회논문집 Vol.30 No.2
본 논문은 다양한 종류의 생성형 AI 용도의 UI/UX 중 텍스트 기반 UI/UX, 이미지 기반 UI/UX, 오디오 기반 UI/UX, 그리고 Multi-modal 을 기반으로 둔 UI/UX 와 같은 다양한 유형의 UI/UX 를 살펴보고 최신 기술을 활용한 미래전망에 대해 알아 보도록 한다. 현재 생성 모델은 다양한 산업분야에서 광범위하고 다양한 응용 프로그램으로 사용되고 있으며, 최근 연구자와 실무자들로부터 상당한 관심을 받고 있다. 생성형 AI 용도의 UI/UX 를 사용하면 생활에 편리해지며 시간과 돈이 매우 절약이 된다. 특히 사용자들이 편안하게 사용할 수 있는 생성형 AI 의 UI/UX 대한 연구방향에 대해 알아 보도록 한다.
Hung-Cuong Trinh,Van-Huy Pham,Anh H. Vo 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.12
Ensuring reliability of a machinery system involve the prediction of remaining useful life (RUL). In most RUL prediction approaches, noise is always considered for removal. Nevertheless, noise could be properly utilized to enhance the prediction capabilities. In this paper, we proposed a novel RUL prediction approach based on noise injection and a Kalman filter ensemble of modified bagging predictors. Firstly, we proposed a new method to insert Gaussian noises into both observation and feature spaces of an original training dataset, named GN-DAFC. Secondly, we developed a modified bagging method based on Kalman filter averaging, named KBAG. Then, we developed a new ensemble method which is a Kalman filter ensemble of KBAGs, named DKBAG. Finally, we proposed a novel RUL prediction approach GN-DAFC-DKBAG in which the optimal noise-injected training dataset was determined by a GN-DAFC-based searching strategy and then inputted to a DKBAG model. Our approach is validated on the NASA C-MAPSS dataset of aero-engines. Experimental results show that our approach achieves significantly better performance than a traditional Kalman filter ensemble of single learning models (KESLM) and the original DKBAG approaches. We also found that the optimal noise-injected data could improve the prediction performance of both KESLM and DKBAG. We further compare our approach with two advanced ensemble approaches, and the results indicate that the former also has better performance than the latters. Thus, our approach of combining optimal noise injection and DKBAG provides an effective solution for RUL estimation of machinery systems.
Novel Reward Function for Autonomous Drone Navigating in Indoor Environment
( Khuong G. T. Diep ),( Viet-tuan Le ),( Tae-seok Kim ),( Anh H. Vo ),( Yong-guk Kim ) 한국정보처리학회 2023 한국정보처리학회 학술대회논문집 Vol.30 No.2
Unmanned aerial vehicles are gaining in popularity with the development of science and technology, and are being used for a wide range of purposes, including surveillance, rescue, delivery of goods, and data collection. In particular, the ability to avoid obstacles during navigation without human oversight is one of the essential capabilities that a drone must possess. Many works currently have solved this problem by implementing deep reinforcement learning (DRL) model. The essential core of a DRL model is reward function. Therefore, this paper proposes a new reward function with appropriate action space and employs dueling double deep Q-Networks to train a drone to navigate in indoor environment without collision.