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- 저자 : Cuong Vo Le (검색결과 5 건)
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Evaluation of Recurrent Neural Network Variants for Person Re-identification
Cuong Vo Le,Nghia Nguyen Tuan,Quan Nguyen Hong,Hyuk-Jae Lee 대한전자공학회 2017 IEIE Transactions on Smart Processing & Computing Vol.6 No.3
Instead of using only spatial features from a single frame for person re-identification, a combination of spatial and temporal factors boosts the performance of the system. A recurrent neural network (RNN) shows its effectiveness in generating highly discriminative sequence-level human representations. In this work, we implement RNN, three Long Short Term Memory (LSTM) network variants, and Gated Recurrent Unit (GRU) on Caffe deep learning framework, and we then conduct experiments to compare performance in terms of size and accuracy for person reidentification. We propose using GRU for the optimized choice as the experimental results show that the GRU achieves the highest accuracy despite having fewer parameters than the others.
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Critical Factors of Subcontractor Evaluation and Selection: A Case Study in Vietnam
VO, Khoa Dang,PHAM, Cuong Phu,PHAN, Phuong Thanh,VU, Ngoc Bich,DUONG, My Tien Ha,LE, Loan Phuc,NGUYEN, Quyen Le Hoang Thuy To Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.3
A contractor or a main contractor is a company with full capacity to construct all project's works for the owner. A subcontractor is an organization that works with the main contractor to execute and complete work packages for the project. Selecting an effective subcontractor will help the efficiency and success of any projects in the construction industry. Therefore, this study identified subcontractor evaluation factors in Vietnam by collecting questionnaire survey data from engineers and staffs in the construction industry project environment. An exploratory factor analysis (EFA) was then performed to identify the critical factors when evaluating and selecting the subcontractor in construction projects. Moreover, when considering the impact level in terms of the average value, the research results showed that the most critical concern was the subcontractor's reputation. Furthermore, the top five factors affecting the sub-contractor evaluation and selection are (i) reputation, (ii) price, (iii) construction techniques, (iv) ability to implement projects according to commitments, and (v) subcontractor competence (the team of workers, technician staff, engineers with full capacity according to regulations). These research results provide an overall perspective that will help main contractors develop suitable subcontractors' evaluation and selection factors in their projects in the construction industry.
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The Ky Vo,Van Nhieu Le,Van Cuong Nguyen,Mugeun Song,Daekeun Kim,Kye Sang Yoo,Bum Jun Park,Jinsoo Kim 한국공업화학회 2020 Journal of Industrial and Engineering Chemistry Vol.86 No.-
Mixed-ligand metal–organic frameworks (MIXMOFs) containing two or more organic linkers that exhibitfunctionalities can show improved selective gas adsorption and separation properties with respect tothose of the conventional MOFs. In this study, the mixed-ligand UiO–66(Zr) framework was rapidlyprepared by employing a microwave-assisted continuous-flow method, which can be easily scaled up forefficient mass production. A microfluidic syringe pump system was used to introduce the precursorsolutions of zirconium metal salt and ligand mixture (terephthalic acid and 2-amino terephthalic acid)into a polytetrafluoroethylene tubular reactor kept under microwave irradiation. MIXMOFs wereobtained within 10 min, a much shorter time than the reaction time required by the conventional heatingmethod. The prepared samples were characterized by N2 porosimetry,field-emission scanning electronmicroscopy, Fourier transform infrared spectrometry, thermogravimetric, and powder X-ray diffractionanalyses to elucidate the effects of the ligand ratios. Furthermore, the toluene adsorption–desorptiontests were conducted using the synthesized mixed-ligand UiO–66(Zr) adsorbents at differenttemperatures.
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Anomalous Trajectory Detection in Surveillance Systems Using Pedestrian and Surrounding Information
Doan Trung Nghia,Sunwoong Kim,Vo Le Cuong,Hyuk-Jae Lee 대한전자공학회 2016 IEIE Transactions on Smart Processing & Computing Vol.5 No.4
Concurrently detected and annotated abnormal events can have a significant impact on surveillance systems. By considering the specific domain of pedestrian trajectories, this paper presents two main contributions. First, as introduced in much of the work on trajectory-based anomaly detection in the literature, only information about pedestrian paths, such as direction and speed, is considered. Differing from previous work, this paper proposes a framework that deals with additional types of trajectory-based anomalies. These abnormal events take places when a person enters prohibited areas. Those restricted regions are constructed by an online learning algorithm that uses surrounding information, including detected pedestrians and background scenes. Second, a simple data-boosting technique is introduced to overcome a lack of training data; such a problem particularly challenges all previous work, owing to the significantly low frequency of abnormal events. This technique only requires normal trajectories and fundamental information about scenes to increase the amount of training data for both normal and abnormal trajectories. With the increased amount of training data, the conventional abnormal trajectory classifier is able to achieve better prediction accuracy without falling into the over-fitting problem caused by complex learning models. Finally, the proposed framework (which annotates tracks that enter prohibited areas) and a conventional abnormal trajectory detector (using the data-boosting technique) are integrated to form a united detector. Such a detector deals with different types of anomalous trajectories in a hierarchical order. The experimental results show that all proposed detectors can effectively detect anomalous trajectories in the test phase.
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Van-Truc Nguyen,Thanh-Binh Nguyen,Thi-Dieu-Hien Vo,Nguyen Duy Dat,Thi-Kim Quyen Vo,Xuan Cuong Nguyen,Viet-Cuong Dinh,Thi-Ngoc-Chau Le,Thi-Giang-Huong Duong,Manh-Ha Bui,Xuan-Thanh Bui 대한환경공학회 2023 Environmental Engineering Research Vol.29 No.3
This study explores the adsorption of doxycycline (DOX) from aqueous solutions onto biochar derived from banana peel, which was prepared using a potassium hydroxide activation method (KOH-BPB). The biochar properties were characterized based on morphology, surface area (SBET of 710.241 ㎡ g<SUP>−1</SUP>), functional groups, and surface charge (pHPZC = 7.7). Parameters, including initial pH, DOX concentration, and ionic strength, that influenced the DOX adsorption capacity of KOH-BPB were examined. Adsorption equilibrium of DOX on KOH-BPB was assessed through four isothermal models: the Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich models. The obtained data were most compatible with the Langmuir model (R² = 0.9879). KOH-BPB has a maximum DOX absorption capacity of 121.95 mg g<SUP>-1</SUP> which exceeds that of many comparable absorbents. The maximum DOX removal was 96.7% at pH 6, a DOX concentration of 20 mg L<SUP>-1</SUP>, and a KOH-BPB dose of 1.0g L<SUP>-1</SUP>. These findings reveal that biochar from banana peel effectively removes antibiotic residues from water. This study provides a potential, low-cost, and environmentally friendly adsorbent.
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