Bui Thu Lam, Le Quy Don Technical University
Deputy Editor-In-Chief
Tran Xuan Nam, Le Quy Don Technical University
Advisory Member
Pham The Long, Le Quy Don Technical University
Nguyen Binh, Posts and Telecommunications Institute of Technology
Dinh The Cuong, Directorate of Information Technology
Luong Chi Mai, Vietnam Academy of Science and Technology
Huynh Quyet Thang, Hanoi University of Science and Technology
Nguyen Huu Thanh, Hanoi University of Science and Technology
Vu Duc Thi, Vietnam National University, Hanoi
Nguyen Thanh Thuy, Vietnam National University, Hanoi
Dao Thanh Tinh, Le Quy Don Technical University
Scientific Secretary
Nguyen Van Giang, Le Quy Don Technical University
Table: Current Issue
ID Paper
[Pdf link]
rules for Fuzzy object functional dependencies in
Fuzzy object-oriented dataBase
Vu Duc Quang, Doan Van Ban, Ho Cam Ha 5-22
In this article, we focus on reseaching, extending the inference rules for fuzzy object functional dependency (FOFD) in fuzzy object-oriented database (FOODB). Based on these rules, some potential FOFDs can be detected. FOFDs are considered as one of the tools to identify fuzzy objects in FOODB and well supports for designing application databases.
concatenated LDPC- V-BLAST system 
L. V. Cao, T. D. Nguyen, V. H. Nguyen 23-31
In this paper we propose a concatenated LDPC – VBLAST system for improving the performance of the MIMO system. In the proposed schenario we implement the set partitioning QPSK modulation and the iterative decoding process between the LDPC decoder and the demodulator. The complexity of this proposed schenario is similar to other regular concatenated channel code systems such as: the concatenated recursive convolution (RSC), unity rate code (URC) and VBLAST schenario, while the performance of our proposed schenario is much more oustanding.
 Towards a Theoretic Model for Parallelization of Cooperative Co-Evolutionary Algorithms
Cuong C. Vu, Lam T. Bui, and Hung H. Nguyen 32-48
Evolutionary algorithms (EAs) have been popularly studied in Artificial Intelligence. A special paradigm of EAs has been promoted allowing several populations to co-evolve together. During the evolutionary process, these populations can be either cooperative or competitive. The cooperative co-evolutionary algorithms (CCEAs) has shown a great deal in solving large and complex problems. However, there are limited studies on parallelizing cooperative co-evolutionary algorithms. In this paper, we developed an approach for combining CCEAs with a synchronous parallel model with a theoretic model of speedup ratio. The design especially facilitates solving large scale problems. We conducted a preliminary investigation with several experiments on benchmark large scale problems. The experimental results indicated a promising performance of the proposed algorithm on the selected problems.
algorithm to recalculate the headgun position based on
Do Nang Toan, Pham Ba May, Cao Huu Tinh 49-59
In the shooting training systems by simulation technology, determining the point of aim has always been a practical problem posed. In this paper we refer to the exact coordinates of the starting point of the trajectory based on camera. By this, the accuracy of hitting point can be improved. Installation techniques have been tested for infantry shooter training system within the framework of the cooperation to keep the Vietnamese Academy of Science and Technology and the Military Technical Academy.
 A Proposal Mathematical Model of Generalized Pareto Distribution for IP Packet Delay
Dao Ngoc Lam, Le Huu Lap, Le Nhat Thang 60-70
Broadband multi-service traffic is transported over Internet Protocol (IP) networks, which are composed of different network nodes, physical links or sections. In practice cases, delay distribution of IP packet in each network component can be determined and expressed in a well-known mathematical function. It is proved in the paper that delay distribution of IP packet transported over the whole networks can be composed from delay components of generalized Pareto distribution and degenerate distribution by explicit mathematical model with certain hypotheses. The proposed model plays an important role in analyzing and evaluating performance, network planning or designing and traffic engineering for improving IP network performance.
 A Model of Fired-Color for Visual Fire Detection.
Ha Dai Duong, Dao Thanh Tinh 71-81
Color is an important feature used in most studies of visual fire detection. Color model is commonly used in the first step of the process and is crucial to the final result. However, to date, most proposals proved to be effective in some certain conditions. This study proposes a color model of pixel in fire blob based on Bayesian classification in the RGB color space. Experimental results show that the proposed model gives good results on the test data set. This paper focuses on a yellow-red flame, however this approach can also be used for other color image segmentation problem.
 GPU-Accelerated Radar Screen Simulation
Nguyen Trung Kien 82-95
In reality, simulation application usually does a huge computation but is required to run in interactive time. This paper introduces an approach and proposes an algorithm for radar screen simulation using GPU. Almost mathematic computations are processed in GPU instead of CPU as normal. GPU processes more efficently to accelarate the simulation running in realtime
Handwritten characters segmentation using structure of
Anh D Phan, Tao Q Ngo, Hung V Pham 96-103
Segmentation of handwritten text into characters has always been an important step in handwritten text recognition process. In this paper, they propose a thinning-based segmentation method using broken line instead of straight vertical line for unconstrained Vietnamese text. Most thinning-base method cannot be applied on Vietnamese text because other than just touching characters, there are cases when the accents touch characters and cannot be separated with just vertical cuts. The experimental results show a reliable performance of the proposed method for segmentation of Vietnamese handwritten characters.
 Inference Technique for Grid General Type-2 Fuzzy Sets based on GPU Computing Platform
Ngo Thanh Long 104-116
This paper deals with an efficient inference technique of grid type-2 fuzzy sets based on the representation by dividing domain into grid. This inference process is to speed-up on computation of type-2 fuzzy sets by taking advantage on grid matrices. Experiments are implemented in various resolution of grid that are summarised on runtime and accuracy in comparison with CPU computation to show efficiency of the approach.
 DDos detection
using neural network
Nguyen Viet Hung, Tran Nguyen Ngoc 117-124
Distributed Denial of Service (DDoS) attacks falls in the category of critical attacks that compromises the availability of the network resources and detection of these attacks is also a challenging task. The objective of this paper is to develop a Network-based Intrusion Detection System using Machine Learning Algorithms Artificial Neural Networks .
 Reseach and development of RSA digital signature algoritthm
Luu Hong Dung 125-133
This paper proposed a digital signature algorithm is developed from the RSA algorithm. Proposed a new algorithm that allows multiple people using the same modulo n, that is just a couple of parameters (p, q) for all end users, thus solving the problem modulo of sharedRSA algorithm. At the same time, this paper also analyzes the safety of the new algorithm, suggesting the possibility of its application in practice.
 A joint optimal precoding and equalization design for ISI MIMO channels
Tạ Chi Hieu, Truong Anh Dung, Le Anh Phong 134-146
Joint optimal precoding and equalization schemes allow for utilizing the multi-input multi-output channels to improve the transmission efficiency. In this paper, a design for joint optimal precoding and equalization for ISI MIMO channels based on GMD algorithm is presented. The proposed scheme can utilize the channel better than the conventional ones in the literature and therefore can achieve a lower bit error rate and higher mutual information.
 Extract MFCC, F0 to HMM-based statistical speech synthesis  for Vietnamese language
Phan Thanh Son, Vu Tat Thang 147-155
HMM-based statistical speech synthesis method is not requiring a very large speech corpus for training the system. In this system, statistical modeling is applied to learn distributions of context-dependent acoustic vectors extracted from speech signals, each vector containing a suitable parametric representation of one speech frame and Vietnamese phonetic rules to synthesize speech. The method presented in this paper allows accurate MFCC, F0 and tone extraction and high-quality reconstruction of speech signals. Its suitability for high-quality HMM-based speech synthesis is shown through evaluations subjectively