• Journal of the Korea Society of Computer and Information
• /
• v.16 no.11
• /
• pp.45-56
• /
• 2011

WBAN is short range wireless communication technology which is consists of several small devices close to, attached to or implanted into the human body. WBAN is classified into between medical and non-medical by applications based on technology and medical data with periodic characteristics is used the GTS method for transmitting data to guarantee the QoS. In this paper we proposed algorithm that resolve lack of GTSs while data transmit GTS method in superframe structure of WBAN. Coordinator dynamically allocates GTSs according to the data rate of devices and make devices share GTSs when lack of GTSs. We compared delay bounds, throughput for performance evaluation of the proposed algorithm. In other words, we proposed algorithm adaptive WFQ scheduling that GTS allocation support differential data rate in environments of WBAN. The experiment results show the throughput increased and the maximum delay decreased compared with Round Robin scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.1845-1865
• /
• 2019

Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention. In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithm based on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.21 no.6
• /
• pp.94-104
• /
• 1984

Based on a new concept of connection index of a weighted graph, a new efficient houris tic algorithm of 0(v.e) for network partitioning is presented, where v and e are the number of nodes and edges, respectively. Experimental results show that our algorithm is very efficient and yields an optimal or near optimal solution for a number of partitioning problems tested. Some applications of the proposed algorithm are suggested and its computer implementation is described in detail.

• Journal of the Optical Society of Korea
• /
• v.20 no.1
• /
• pp.204-211
• /
• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2414-2433
• /
• 2019

The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.

• Journal of Korea Multimedia Society
• /
• v.20 no.8
• /
• pp.1175-1186
• /
• 2017

Human emotion recognition is one of the promising applications in the era of artificial super intelligence. Thus far, facial expression traits are considered to be the most widely used information cues for realizing automated emotion recognition. This paper proposes a novel facial expression recognition (FER) method that works well for recognizing emotion from image sequences. To this end, we develop the so-called weighted soft voting classification (WSVC) algorithm. In the proposed WSVC, a number of classifiers are first constructed using different and multiple feature representations. In next, multiple classifiers are used for generating the recognition result (namely, soft voting) of each face image within a face sequence, yielding multiple soft voting outputs. Finally, these soft voting outputs are combined through using a weighted combination to decide the emotion class (e.g., anger) of a given face sequence. The weights for combination are effectively determined by measuring the quality of each face image, namely "peak expression intensity" and "frontal-pose degree". To test the proposed WSVC, CK+ FER database was used to perform extensive and comparative experimentations. The feasibility of our WSVC algorithm has been successfully demonstrated by comparing recently developed FER algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.3C
• /
• pp.241-248
• /
• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.807-810
• /
• 2013

In this paper, a new technique for image enhancement using weighted cross-shaped median filter with edge-detection algorithm is proposed. It consists of simple hypothesis test for edge-detection, and makes use of the cross-shaped moving window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of weighted cross-shaped median filter is superior to other median filters.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.1
• /
• pp.193-214
• /
• 2017

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

• Journal of Communications and Networks
• /
• v.12 no.5
• /
• pp.449-458
• /
• 2010

In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.