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RISS 인기검색어
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- 저자 : Ngo Xuan Bach (검색결과 3 건)
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Bach, Quang-Vu,Le, Van Tam,Yoon, Yong Soo,Bui, Xuan Thanh,Chung, Woojin,Chang, Soon Woong,Ngo, Huu Hao,Guo, Wenshan,Nguyen, Dinh Duc Elsevier 2018 Journal of Cleaner Production Vol.178 No.-
<P><B>Abstract</B></P> <P>A new hybrid pilot plant configuration based on a modularized rolled pipe system (RPS) combined with a submerged flat sheet membrane bioreactor (MBR) was investigated to enhance the sewage treatment and membrane performance. The system was operated under actual conditions for more than four months, that is, at a constant flow rate of 30 m³/d and with two internal recycling ratios. The results indicate that the hybrid system produces an excellent effluent quality and considerably mitigated membrane fouling. The average concentrations of SS, COD, TN, NH<SUB>4</SUB> <SUP>+</SUP>-N, NO<SUB>3</SUB> <SUP>−</SUP>-N, and PO<SUB>4</SUB> <SUP>3-</SUP>-P remained below 2.81, 8.29, 8.77, 0.15, 8.17, and 1.49 mg/L, respectively. It was estimated that the periodic chemical cleaning of the membrane could be extended to approximately six months. The MBR and RPS can virtually complete nitrification and denitrification, respectively. The highest average denitrification rate of the RPS is 116.95 mg NO<SUB>3</SUB>-N/(g MLVSS d), with a hydraulic retention time of 1.05 h. Therefore, the RPS–MBR hybrid system has potential to improve the sewage treatability. The emerging RPS technique can obtain high rates of denitrification coupled with a compact design, ease of installation, and small footprint.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A new hybrid sewage treatment system was explored. </LI> <LI> Excellent denitrification is achieved with the novel rolled pipe system. </LI> <LI> High rates of simultaneous nitrification and denitrification are obtained. </LI> <LI> The hybrid system performs well in removing organic and nitrogen compounds. </LI> <LI> The membrane fouling rate of the hybrid system is significantly low. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
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Melvyn WB Zhang,Bach Xuan Tran,Huong Lan Thi Nguyen,Huong Thi Le,Nguyen Hoang Long,Huong Thi Le,Nguyen Duc Hinh,Tran Dinh Tho,Bao Nguyen Le,Vu Thi Minh Thuc,Chau Ngo,Nguyen Huu Tu,Carl A. Latkin,Roger 대한의료정보학회 2017 Healthcare Informatics Research Vol.23 No.2
Objectives: The average alcohol consumption per capita among Vietnamese adults has consistently increased. Although alcoholrelated disorders have been extensively studied, there is a paucity of research shedding light on this issue among Internet users. The study aimed to examine the severity of alcohol-related disorders and other associated factors that might predispose individuals towards alcohol usage in a sample of youths recruited online. Methods: An online cross-sectional study was conducted with 1,080 Vietnamese youths. A standardized questionnaire was used. Respondent-driven sampling was applied to recruit participants. Multivariate logistic and Tobit regressions were utilized to identify the associated factors. Results: About 59.5% of the males and 12.7% of the total youths declared that they were actively using alcohol. From the total sample, a cumulative total of 32.3% of the participants were drinking alcohol, with 21.8% and 25.0% of the participants being classified as drinking hazardously and binge drinkers, respectively. The majority of the participants (60.7%) were in the pre-contemplative stage. Conclusions: A high prevalence of hazardous drinking was recognized among online Vietnamese youths. In addition, we found relationships between alcohol use disorder and other addictive disorders, such as tobacco smoking and water-pipe usage. Our results highlighted that the majority of the individuals are not receptive to the idea of changing their alcohol habits, and this would imply that there ought to be more government effort towards the implementation of effective alcohol control policies.
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FGW-FER: Lightweight Facial Expression Recognition with Attention
Huy-Hoang Dinh,Hong-Quan Do,Trung-Tung Doan,Cuong Le,Ngo Xuan Bach,Tu Minh Phuong,Viet-Vu Vu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9
The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.
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