Nguyen-Le H.,Danang University of Technology |
Le-Ngoc T.,McGill University |
Tran N.H.,University of Akron
IEEE Transactions on Vehicular Technology | Year: 2011
This paper is concerned with the problem of turbo (iterative) processing for joint channel and carrier frequency offset (CFO) estimation and soft decoding in coded multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexing (OFDM) systems over time- and frequency-selective (doubly selective) channels. In doubly selective channel modeling, a basis expansion model (BEM) is deployed as a fitting parametric model to reduce the number of channel parameters to be estimated. Under pilot-aided Bayesian estimation, CFO and BEM coefficients are treated as random variables to be estimated by the maximum a posteriori technique. To attain better estimation performance without sacrificing spectral efficiency, soft bit information from a soft-input-soft-output (SISO) decoder is exploited in computing soft estimates of data symbols to function as pilots. These additional pilot signals, together with the original signals, can help to enhance the accuracy of channel and CFO estimates for the next iteration of SISO decoding. The resulting turbo estimation and decoding performance is enhanced in a progressive manner by benefiting from the iterative extrinsic information exchange in the receiver. Both extrinsic information transfer chart analysis and numerical results show that the iterative receiver performance is able to converge fast and close to the ideal performance using perfect CFO and channel estimates. © 2011 IEEE.
Nguyen A.-T.,University of Liège |
Tran Q.-B.,National University of Civil Engineering |
Tran D.-Q.,Danang University of Technology |
Reiter S.,University of Liège
Building and Environment | Year: 2011
Energy conservation issues and environmental problems in recent years have increased interest in traditional architecture which is well known for its energy saving designs. This paper thoroughly investigates vernacular housing designs and evaluates on the aspect of building physics. A new research methodology which is adapted to the natural and social context of Vietnam was proposed and applied. The process was carried out step by step, including: climate zoning, systematic analysis, in-situ survey and building simulations. The results of this study indicate that vernacular housing in Vietnam is creatively adapted to the local natural conditions and uses various climate responsive strategies. Through this study, the most frequently used strategies and their effectiveness were derived. The authors also found that under extreme weather conditions, traditional designs might not be sufficient to maintain indoor thermal comfort. © 2011 Elsevier Ltd.
Nguyen A.-T.,University of Liège |
Nguyen A.-T.,Danang University of Technology |
Reiter S.,University of Liège |
Rigo P.,University of Liège
Applied Energy | Year: 2014
Recent progress in computer science and stringent requirements of the design of "greener" buildings put forwards the research and applications of simulation-based optimization methods in the building sector. This paper provides an overview on this subject, aiming at clarifying recent advances and outlining potential challenges and obstacles in building design optimization. Key discussions are focused on handling discontinuous multi-modal building optimization problems, the performance and selection of optimization algorithms, multi-objective optimization, the application of surrogate models, optimization under uncertainty and the propagation of optimization techniques into real-world design challenges. This paper also gives bibliographic information on the issues of simulation programs, optimization tools, efficiency of optimization methods, and trends in optimization studies. The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods (surrogate models) for large-scale building optimization problems; and reducing time and effort for such activities. Further effort is also required to quantify the robustness in optimal solutions so as to improve building performance stability. © 2013 Elsevier Ltd.
Nam C.T.,National Kaohsiung University of Applied Sciences |
Yang W.-D.,National Kaohsiung University of Applied Sciences |
Duc L.M.,Danang University of Technology
Bulletin of Materials Science | Year: 2013
TiO2 nanotubes were synthesized by the solvothermal process at low temperature in a highly alkaline water-methanol mixed solution. Their characteristics were identified by powder X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area (BET), Fourier transform infrared spectroscopy (FTIR) and UV-Vis absorption spectroscopy. The as-prepared samples were tested by the photodegradation reaction of methylene blue (MB) dye under visible-light irradiation. The ratios of methanol and water, as well as calcination temperature, affected the morphology, nanostructure and photocatalytic performance. The methanol solvent plays an important role in improving crystallization of the anatase phase, which affects the photocatalytic reaction. Titanate nanotubes were synthesized in methanol-water volume ratios of 10:90, 20:80 and 30:70 which still had high absorbability. Titania nanotubes formed at a calcination temperature of 300 °C using methanol-water volume ratio of 30:70 showed highest photocatalytic performance, much higher than that using water solvent and TiO2-P25 powder. © Indian Academy of Sciences.
Doan T.-T.-L.,Leibniz Institute of Polymer Research |
Doan T.-T.-L.,Danang University of Technology |
Brodowsky H.,Leibniz Institute of Polymer Research |
Mader E.,Leibniz Institute of Polymer Research
Composites Science and Technology | Year: 2012
Jute fibres were surface treated in order to enhance the interfacial interaction between jute natural fibres and an epoxy matrix. The fibres are exposed to alkali treatment in combination with organosilane coupling agents and aqueous epoxy dispersions. The surface topography and surface energy influenced by the treatments were characterized. Single fibre pull-out tests combined with SEM and AFM characterization of the fracture surfaces were used to identify the interfacial strengths and to reveal the mechanisms of failure. © 2012 Elsevier Ltd.
Duong Q.-B.,Grenoble Institute of Technology |
Zamai E.,Grenoble Institute of Technology |
Tran-Dinh K.-Q.,Danang University of Technology
Engineering Applications of Artificial Intelligence | Year: 2013
This paper proposes an estimation method for the confidence level of feedback information (CLFI), namely the confidence level of reported information in computer integrated manufacturing (CIM) architecture for logic diagnosis. This confidence estimation provides a diagnosis module with precise reported information to quickly identify the origin of equipment failure. We studied the factors affecting CLFI, such as measurement system reliability, production context, position of sensors in the acquisition chains, type of products, reference metrology, preventive maintenance and corrective maintenance based on historical data and feedback information generated by production equipments. We introduced the new 'CLFI' concept based on the Dynamic Bayesian Network approach and Tree Augmented Naïve Bayes model. Our contribution includes an on-line confidence computation module for production equipment data, and an algorithm to compute CLFI. We suggest it to be applied to the semiconductor manufacturing industry. © 2012 Elsevier Ltd. All rights reserved.
Tra K.,Danang University of Technology |
Pham T.V.,Danang University of Technology
International Conference on Advanced Technologies for Communications | Year: 2013
Nowadays, there are many fall detection systems based on intelligent video analysis. However, these systems are still facing many challenges such as lighting changes, long-term scene changes or added static background objects in new scene, etc. In this paper, adaptive background Gaussian mixture model (GMM) has been applied for moving object segmentation. An ellipse shape has been built from the segmented object for body modeling. Five features are extracted from this ellipse model and fed into two Hidden Markov Models (HMM) to classify fall and normal activities. We apply our proposed approach to challenging data sets recorded in different conditions. The qualitative results demonstrate that the combination of the adaptive GMM-based object segmentation and HMM certainly improves recognition accuracy under different scenarios. © 2013 IEEE.
Nguyen D.S.,Danang University of Technology
IEEE International Conference on Industrial Engineering and Engineering Management | Year: 2016
Nowadays, requirements of clients and customers for the quality of product are more and more tightened and complicated. The quality assurance of manufactured product is a key to success in the context of global and competitive economy. Many different parts of final product are made from raw material by multistage manufacturing processes in different places. The risk is that the final manufactured product does not fully meet the requirements. Thus, the paper proposes a method based on Bayesian networks that allows to model impact factors in a multistage machining process on product quality. The root cause analysis can be implemented by using the Bayesian network model. As a result, product quality predicted earlier at design stage can help product designer adjust the product designed and manufacturing processes in order to obtain a robust design with promised quality. © 2015 IEEE.
Hanh L.T.M.,Danang University of Technology |
Binh N.T.,Danang University of Technology
Proceedings - 4th International Conference on Knowledge and Systems Engineering, KSE 2012 | Year: 2012
Mutation testing is a fault-based technique widely used for testing software. Particularly, it allows the effectiveness of a set of test data to be evaluated in terms of the ability to reveal faults. Nowadays, many industrial complex systems are more and more developed. Such systems require more testing activities to ensure a good quality. Simulink is one of the most popular tools to develop this kind of systems. In this paper, we focus on studying the application of mutation testing technique to Simulink models. We propose a set of mutation operators by basing on investigating common faults in Simulink models. A process of mutation testing for Simulink models is also presented. Some first experimentations show the promising outcomes. © 2012 IEEE.
Bui H.B.,Danang University of Technology
International Journal of Recycling of Organic Waste in Agriculture | Year: 2014
Background: Microorganisms have been used to decompose cellulolytic waste in agriculture for the past many years. However, much of the cellulosic waste including coffee exocarps which are wastes from raw coffee process in Vietnam is often disposed of by biomass burning and discharged into the environment in developing countries, thus causing considerable environmental pollution. Besides, these organic wastes decompose slowly when they are used to produce compost in ordinary conditions. Therefore, using microorganisms to manufacture natural compost from coffee exocarps is considered a useful and environmentally sound alternative. Results: In the course of screening for cellulose-degrading bacteria and actinomycetes, 38 bacterial strains and 18 actinomycetes strains were isolated from 15 coffee exocarp samples in coffee-producing areas in Vietnam. The isolates grew with cellulose as the sole sources of carbon and energy. The results of cellulolytic activity determinations were that 13 bacteria (>34 %) and 10 actinomycetes (>56 %) showed enzymatic degradation of cellulose. The isolated strains were identified as belonging to members of the Genus Streptomyces, Actinomycetes, Clostridium and Bacillus. Cellulose-degrading ability of the isolated microorganism strains was mostly 96 % with filter paper; however, for coffee exocarps, it was considerably lower, only about 37 % of the cellulose was digested after 30 days of incubation to coffee exocarps. A medium containing rice husk powder and lactose with pH 7.0 positively affected the cellulolytic activity of A1 and A9 strains. Cellulolytic activity of B4 and B7 strains was also most appropriate when the medium contained peptone, CMC, and with a pH 7.0. Optimal temperature for actinomycetes and bacteria isolate strains was at 25–35 °C. Conclusion: We concluded that the cellulolytic bacteria and actinomycete could be isolated from coffee exocarps which are normally discharged into the environment in coffee-producing areas. These microorganisms could be used to decompose cellulosic wastes, making compost from coffee exocarps, which could be applied in agriculture in Vietnam and other developing countries. © 2014, The Author(s).