• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.251-258
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• 2014

This paper proposes an efficient token flow design methodology for a decoder in the MPEG Reconfigurable Media Coding (RMC) framework. The MPEG RMC framework facilitates a decoder to be configured with a set of modules called functional units (FUs) that are connected by tokens. Such a modular design philosophy of the MPEG RMC framework enables the reusability and reconfigurability of FUs. One drawback of the MPEG RMC framework is that the decoder performance can be affected by increasing the token transmissions between FUs. The proposed method improves the design of the FU network in the RMC framework toward real-time decoder implementation. In the proposed method, the merging of FU, the separation of token flow, and the merging of token transactions are applied to minimize the token traffic between FUs. The experimental results of the MPEG-4 SP decoder show that the proposed method reduces the total decoding time by up to 77 percent compared to the design of the RMC simulation model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.220-223
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• 2016

Explosive growth of smartphone-based mobile nodes has increased exponentially the mobile data traffic on the Internet. To reduce the traffic load on the network and to support the seamless mobility of the mobile nodes, the IETF and 3GPP have standardized a number of mobility management mechanisms. More recently, they are making an effort to find some schemes to distribute the networking systems that involve in the mobility management in order to assure the scalability and the reliability of the network. In IETF, DMM concept for the distributed mobility management on the Internet is being discussed. Specifically, the DMM can be classified into the partially distributed management and fully distributed management. In this paper, we propose a fully distributed mobility management scheme (FuDMM) on PMIPv6-based network by applying the extended NDP. We also present the performance of FuDMM using the comparative analysis with the existing ones.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.773-783
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• 2016

Both coordinated multi-point transmission and frequency reuse are effective approaches to mitigate inter-cell interference and improve network coverage. The motivation of this work is to explore the manner to effectively utilize the spectrum resource by reasonably combining cooperation and frequency reuse. The $Mat{\acute{e}}rn$ cluster process, which is appropriate to model networks with hot spots, is used to model the spatial distribution of base stations. Two cooperative mechanisms, coherent and non-coherent joint transmission (JT), are analyzed and compared. We also evaluate the effect of multiple antennas and imperfect channel state information. The simulation reveals that the proposed approach to combine cooperation and frequency reuse is effective to improve the network coverage for users located at both the center and the boundary of the cooperative region.

• Structural Engineering and Mechanics
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• v.16 no.6
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• pp.643-654
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• 2003

Two real-time modeling prediction (RMP) schemes are presented in this paper for analyzing the behavior of deep excavations during construction. The first RMP scheme is developed from the traditional AR(p) model. The second is based on the simplified Elman-style recurrent neural networks. An on-line learning algorithm is introduced to describe the dynamic behavior of deep excavations. As a case study, in-situ measurements of an excavation were recorded and the measured data were used to verify the reliability of the two schemes. They proved to be both effective and convenient for predicting the behavior of deep excavations during construction. It is shown through the case study that the RMP scheme based on the neural network is more accurate than that based on the traditional AR(p) model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.51-57
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• 2022

The problem of optimal stochastic GA control of the system with uncertain parameters and unsure noise covariates is studied. First, without knowing the explicit form of the dynamic system, the open-loop determinism problem with path optimization is solved. Next, Gaussian linear quadratic controllers (LQG) are designed for linear systems that depend on the nominal path. A robust genetic neural network (NN) fuzzy controller is synthesized, which consists of a Kalman filter and an optimal controller to assure the asymptotic stability of the discrete control system. A simulation is performed to prove the suitability and performance of the recommended algorithm. The results indicated that the recommended method is a feasible method to improve the performance of active tuned mass damper (ATMD) shear buildings under random earthquake disturbances.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1463-1478
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• 2012

Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The $(R/S)^d$ algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2180-2200
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• 2015

This paper considers mobility control to improve packet delivery in delay-tolerant networks (DTNs) under group mobility. Based on the group structure in group mobility, we propose two mobility control techniques; group formation enforcement and group purposeful movement. Both techniques can be used to increase the contact opportunities between groups by extending the group's reachability. In addition, they can be easily integrated into some existing DTN routing schemes under group mobility to effectively expedite the packet delivery. This paper is divided into 2 parts. First, we study how our proposed mobility control schemes reduce the packet delivery delay in DTNs by integrating them into one simple routing scheme called group-epidemic routing (G-ER). For each scheme, we analytically derive the cumulative density function of the packet delivery delay to show how it can effectively reduce the packet delivery delay. Then, based on our second proposed technique, the group purposeful movement, we design a new DTN routing scheme, called purposeful movement assisted routing (PMAR), to further reduce the packet delay. Extensive simulations in NS2 have been conducted to show the significant improvement of PMAR over G-ER under different practical network conditions.

• Parasites, Hosts and Diseases
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• v.57 no.4
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• pp.445-450
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• 2019

Human infections due to the monkey malaria parasite Plasmodium knowlesi is increasingly being reported from most Southeast Asian countries specifically Malaysia. The parasite causes severe and fatal malaria thus there is a need for urgent measures for its control. In this study, the level of polymorphisms, haplotypes and natural selection of full-length pkmsp8 in 37 clinical samples from Malaysian Borneo along with 6 lab-adapted strains were investigated. Low levels of polymorphism were observed across the full-length gene, the double epidermal growth factor (EGF) domains were mostly conserved, and non-synonymous substitutions were absent. Evidence of strong negative selection pressure in the non-EGF regions were found indicating functional constrains acting at different domains. Phylogenetic haplotype network analysis identified shared haplotypes and indicated geographical clustering of samples originating from Peninsular Malaysia and Malaysian Borneo. This is the first study to genetically characterize the full-length msp8 gene from clinical isolates of P. knowlesi from Malaysia; however, further functional characterization would be useful for future rational vaccine design.