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Cuong Dinh Tran,Tam Thanh Dao,Ve Song Vo,Thang Trung Nguyen 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1
Cuckoo Search Algorithm (CSA), a new meta-heuristic algorithm based on natural phenomenon of Cuckoo species and Lévy flights random walk has been widely and successfully applied to several optimization problems so far. In the paper two modified versions of CSA, where new solutions are generated using two distributions including Gaussian and Cauchy distributions in addition to imposing bound by best solutions mechanism are proposed for solving economic load dispatch (ELD) problem with multiple fuel options. The advantages of CSA with Gaussian distribution (CSA-Gauss) and CSA with Cauchy distribution (CSA-Cauchy) over CSA with Lévy distribution and other meta-heuristic are fewer parameters. The proposed CSA methods are tested on two systems with several load cases and obtained results are compared to other methods. The result comparisons have shown that the proposed methods are highly effective for solving ELD problem with multiple fuel options and/nor valve point effect.
One Rank Cuckoo Search Algorithm for Bi-Objective Load Dispatch Problem
Cuong Dinh Tran,Thang Trung Nguyen,Hanh Minh Hoang,Bao Quoc Nguyen 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.4
This paper presents the application of a One Rank Cuckoo Search Algorithm (ORCSA) to bi-objective load dispatch (BOLD) problem where two objectives including fuel and emission are taken into consideration. ORCSA is an improvement of basic Cuckoo search algorithm (BCSA) where several modifications are carried out so as to improve the performance of the BCSA. The performance of the proposed ORCSA is validated by using two systems including a three-unit system with one load case and a six-unit system with three load cases and comparing the obtained results with other methods available in the article. The analysis on the result comparison indicates that the ORCSA is very efficient for the problem.
Tran, Van Cuong,Nguyen, Ngoc Thanh,Fujita, Hamido,Hoang, Dinh Tuyen,Hwang, Dosam Elsevier 2017 Knowledge-based systems Vol.132 No.-
<P><B>Abstract</B></P> <P>In recent years, many applications in natural language processing (NLP) have been developed using the machine learning approach. Annotating data is an important task in applying machine learning to NLP applications. A common approach to improve the system performance is to train on a large and high-quality set of training data that is annotated by experts. Besides, active learning (AL) and self-learning can be utilized to reduce the annotation costs. The self-learning method discovers highly reliable instances based on a trained classifier, while AL queries the most informative instances based on active query algorithms. This paper proposes a method that combines AL and self-learning to reduce the labeling effort for the named entity recognition task from tweet streams by using both machine-labeled and manually-labeled data. We employ AL queries based on the diversity of the context and content of instances to select the most informative instances. The conditional random fields are also chosen as an underlying model to train a classifier for selecting highly reliable instances. The experiments using Twitter data show that the proposed method achieves good results in reducing the human labeling effort, and it can significantly improve the performance of the systems.</P>
Optimization of Spin-Valve Structure NiFe/Cu/NiFe/IrMn for Planar Hall Effect Based Biochips
Bui Dinh Tu,Le Viet Cuong,Tran Quang Hung,Do Thi Huong Giang,Tran Mau Danh,Nguyen Huu Duc,CheolGi Kim IEEE 2009 IEEE transactions on magnetics Vol.45 No.6
<P>This paper deals with the planar Hall effect (PHE) of Ta(5)/NiFe(t<SUB>F</SUB>)/Cu(1.2)/NiFe(t<SUB>P</SUB>)/IrMn(15)/Ta(5) (nm) spin-valve structures. Experimental investigations are performed for 50 mumtimes50 mum junctions with various thicknesses of free layer (t<SUB>F</SUB> = 4, 8, 10, 12, 16, 26 nm) and pinned layer (t<SUB>P</SUB> = 1, 2, 6, 8, 9, 12 nm). The results show that the thicker free layers, the higher PHE signal is observed. In addition, the thicker pinned layers lower PHE signal. The highest PHE sensitivity S of 196 muV/(kA/m) is obtained in the spin-valve configuration with t<SUB>F</SUB> = 26 nm and t<SUB>P</SUB> = 1 nm. The results are discussed in terms of the spin twist as well as to the coherent rotation of the magnetization in the individual ferromagnetic layers. This optimization is rather promising for the spintronic biochip developments.</P>
Nguyen Duc Cuong,Tran Thai Hoa,Dinh Quang Khieu,Nguyen Duc Hoa,Nguyen Van Hieu 한국물리학회 2012 Current Applied Physics Vol.12 No.5
The development of a low cost and scalable gas sensor for the detection of toxic and flammable gases with fast response and high sensitivity is extremely important for monitoring environmental pollution. In this work, we introduce two different synthesis pathways for the preparation of scalable Fe2O3nanoparticles for gas sensor applications. One is co-precipitation and the other is hydrothermal method. The gas sensing properties of the a-Fe2O3 nanoparticles (NPs) fabricated by different synthesis pathways were studied and compared. The performance of the NPs in the detection of toxic and flammable gases such as carbon dioxide, ammonia, liquefied petroleum gas, ethanol, and hydrogen was evaluated. The Fe2O3 NP-based gas sensors exhibited high sensitivity and a response time of less than a minute to analytic gases. However, the NPs fabricated by the one-step direct method exhibited higher sensitivities than those generated by the a-Fe2O3 NPs obtained by co-precipitation synthesis possibly because of their nanoporous structure. This performance is attributed to the large specific surface area of the NPs, which results in higher sensitivity. The development of a low cost and scalable gas sensor for the detection of toxic and flammable gases with fast response and high sensitivity is extremely important for monitoring environmental pollution. In this work, we introduce two different synthesis pathways for the preparation of scalable Fe2O3nanoparticles for gas sensor applications. One is co-precipitation and the other is hydrothermal method. The gas sensing properties of the a-Fe2O3 nanoparticles (NPs) fabricated by different synthesis pathways were studied and compared. The performance of the NPs in the detection of toxic and flammable gases such as carbon dioxide, ammonia, liquefied petroleum gas, ethanol, and hydrogen was evaluated. The Fe2O3 NP-based gas sensors exhibited high sensitivity and a response time of less than a minute to analytic gases. However, the NPs fabricated by the one-step direct method exhibited higher sensitivities than those generated by the a-Fe2O3 NPs obtained by co-precipitation synthesis possibly because of their nanoporous structure. This performance is attributed to the large specific surface area of the NPs, which results in higher sensitivity.
An adaptive approach for the chloride diffusivity of cement-based materials
Bao-Viet Tran,Duc-Chinh Pham,Mai-Dinh Loc,Minh-Cuong Le 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.23 No.2
Adaptive schemes are constructed in this paper for modeling the effective chloride diffusion coefficient of cementbased materials (paste and concrete). Based on the polarization approximations for the effective conductivity of isotropic multicomponent materials, we develop some fitting procedures to include more information about the materials, to improve the accuracy of the scheme. The variable reference parameter of the approximation involves a few free scalars, which are determined through the available numerical or experimental values of the macroscopic chloride diffusion coefficient of cement paste or concrete at some volume proportions of the component materials. The various factors that affect the chloride diffusivity of cement-based material (porous material structure, uncertainty of value of the chloride diffusion coefficient in water-saturated pore spaces, etc.) may be accounted to make the predictions more accurate. Illustrations of applications are provided in a number of examples to show the usefulness of the approach.
Study on the Melting of the Defective Interstitial Alloys TaSi and WSi with BCC Structure
Nguyen Quang Hoc,Tran Dinh Cuong,Bui Duc Tinh,Le Hong Viet 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.74 No.8
The statistical moment method is used to study the melting of defective interstitial AB alloys, where A is the main element and B is an interstitial atom, with a body-centered-cubic (BCC) structure. The melting temperature of the AB alloy with defects is obtained from the temperature of absolute stability for the crystalline state and the equilibrium vacancy concentration. Numerical calculations are performed for the interstitial alloys TaSi and WSi. Our calculated results are in good agreement with other calculations.