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Simple Synthesis of Multi-Halogen Pyrazino[1,2-a]indole-1,8(2H,5aH)-diones
Rui-Xia Yang,Yu-Cheng Zhao,Ling-Bin Kong,Sheng-jiao Yan,Jun Lin 대한화학회 2016 Bulletin of the Korean Chemical Society Vol.37 No.10
A concise and efficient one-pot synthesis of multi-halogen pyrazino[1,2-a]indole-1,8(2H,5aH)-dione (MHPID) derivatives by the reaction of an enamino ester with multi-halogen benzoquinone derivatives is described. MHPIDs 3a–3d were obtained with good yields (78–83%) by refluxing enamino esters 1a and 1b and tetrahalogen-1,4-benzoquinones 2a and 2b for 24 h without the use of catalysts. Compounds 3e–3p were also obtained with excellent yields (69–92%) via the reaction of the phenyl-substituted enamino esters 1c–1h with tetrahalogen-1,4-benzoquinones 2a and 2b in CH3CN catalyzed by Cs2CO3. These two protocols are efficient and effective for the synthesis of MHPIDs.
A New Hybrid Algorithm for Invariance and Improved Classification Performance in Image Recognition
Rui-Xia Shi,정동규 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.3
It is important to extract salient object image and to solve the invariance problem for image recognition. In this paper we propose a new hybrid algorithm for invariance and improved classification performance in image recognition, whose algorithm is combined by FT(Frequency-tuned Salient Region Detection) algorithm, Guided filter, Zernike moments, and a simple artificial neural network (Multi-layer Perceptron). The conventional FT algorithm is used to extract initial salient object image, the guided filtering to preserve edge details, Zernike moments to solve invariance problem, and a classification to recognize the extracted image. For guided filtering, guided filter is used, and Multi-layer Perceptron which is a simple artificial neural networks is introduced for classification. Experimental results show that this algorithm can achieve a superior performance in the process of extracting salient object image and invariant moment feature. And the results show that the algorithm can also classifies the extracted object image with improved recognition rate.
A New Bank-card Number Identification Algorithm Based on Convolutional Deep Learning Neural Network
Rui-Xia Shi,정동규 한국인터넷방송통신학회 2022 International journal of advanced smart convergenc Vol.11 No.4
Recently bank card number recognition plays an important role in improving payment efficiency. In this paper we propose a new bank-card number identification algorithm. The proposed algorithm consists of three modules which include edge detection, candidate region generation, and recognition. The module of ‘edge detection’ is used to obtain the possible digital region. The module of ‘candidate region generation’ has the role to expand the length of the digital region to obtain the candidate card number regions, i.e. to obtain the final bank card number location. And the module of ‘recognition’ has Convolutional deep learning Neural Network (CNN) to identify the final bank card numbers. Experimental results show that the identification rate of the proposed algorithm is 95% for the card numbers, which shows 20% better than that of conventional algorithm or method.
Cheng Xia,Rui-Tang Guo,Zhen-rui Zhang,Chen-yuan Fan,Yu-zhe Liu,Yu-cheng Lin,Chu-fan Li,Wei-Guo Pan 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.128 No.-
Recently, the photocatalytic CO2 reduction technology is an effective solution to remit the energy crisis. Inorder to improve the photocatalytic performance, Z-scheme W18O49/NiAl-LDH composite catalysts wereprepared by hydrothermal method. Fortunately, the prepared catalysts revealed excellent photocatalyticperformance under the simulated sunlight, and CO and CH4 could be detected in the reduction products. WO/LDH-0.5 catalyst possessed the optimal activity, with CO and CH4 yield of 37.09 and 8.01 lmol g-1h1separately, which were 7.9 and 3.6 times that of NiAl-LDH monomer. In addition, W18O49 endowedW18O49/NiAl-LDH catalysts with photothermal effect, which raised the surface temperature andfacilitated the catalytic reaction. Meanwhile, the Z-scheme heterojunction composed of flower-likeNiAl-LDH and urchin-like W18O49 accelerated the separation of photoexcited carriers and enhanced theredox ability. Through a series of characterizations and investigations, this work is promising to breaknew ground for the design of photocatalysts with photothermal effect.
A New Hybrid Algorithm for Invariance and Improved Classification Performance in Image Recognition
Shi, Rui-Xia,Jeong, Dong-Gyu The Institute of Internet 2020 International journal of advanced smart convergenc Vol.9 No.3
It is important to extract salient object image and to solve the invariance problem for image recognition. In this paper we propose a new hybrid algorithm for invariance and improved classification performance in image recognition, whose algorithm is combined by FT(Frequency-tuned Salient Region Detection) algorithm, Guided filter, Zernike moments, and a simple artificial neural network (Multi-layer Perceptron). The conventional FT algorithm is used to extract initial salient object image, the guided filtering to preserve edge details, Zernike moments to solve invariance problem, and a classification to recognize the extracted image. For guided filtering, guided filter is used, and Multi-layer Perceptron which is a simple artificial neural networks is introduced for classification. Experimental results show that this algorithm can achieve a superior performance in the process of extracting salient object image and invariant moment feature. And the results show that the algorithm can also classifies the extracted object image with improved recognition rate.
OPTIMAL IMPULSE AND REGULAR CONTROL STRATEGIES FOR PROPORTIONAL REINSURANCE PROBLEM
RUI-CHENG, YANG,KUN-HUI, LIU,BING, XIA 한국전산응용수학회 2005 Journal of applied mathematics & informatics Vol.18 No.1
We formulate a stochastic control problem on proportional reinsurance that includes impulse and regular control strategies. For the first time we combine impulse control with regular control, and derive the expected total discount pay-out (return function) from present to bankruptcy. By relying on both stochastic calculus and the classical theory of impulse and regular controls, we state a set of sufficient conditions for its solution in terms of optimal return function. Moreover, we also derive its explicit form and corresponding impulse and regular control strategies.
Two Indolocarbazole Alkaloids with Apoptosis Activity from a Marine-derived Actinomycete Z2039-2
Rui Liu,Tianjiao Zhu,Dehai Li,Jingyan Gu,Wei Xia,Yuchun Fang,HongbingLiu,Weiming Zhu,Qianqun Gu 대한약학회 2007 Archives of Pharmacal Research Vol.30 No.3
Bioassay-guided fractionation of the EtOAc extract from the fermentation broth of a marinederived actinomycete Z2039-2 led to the isolation of two known indolocarbazole alkaloids, K252c (1) and arcyriaflavin A (2). 1 and 2 exhibited moderate cytotoxic activities against the K562 cell line, and induced apoptotic activities at 10 and 100 µM, respectively. This is the first report on the significant apoptosis inducing effect of indolocarbazole alkaloids against K562 cancer cells.
Rui-fang Liu,Xin Ma,Jun-ci Cao,Shuang-xia Niu,Zhi-gang Wu 한국자기학회 2019 Journal of Magnetics Vol.24 No.2
Amorphous materials have the advantages of high permeability and low core losses. Their application in the motor can reduce the energy consumption and improve the efficiency. To investigate the advantage of amorphous materials on the performance of permanent magnet synchronous motors (PMSMs) at lower speed situation, three 1.5 kW motors used in steering pumps of electric vehicles are analyzed and compared. Two prototypes and the experimental platform are built. The experimental results indicate that the efficiency of the PMSM motor with amorphous materials increases by 1.4 % at 1200 rpm, which shows that amorphous materials can also improve the motor performance at lower speed. To further take advantage of amorphous materials, the particle swarm optimization algorithm is used to optimize the dimensions of amorphous motor and the efficiency is increased by 0.54 %.