• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.11
• /
• pp.2553-2562
• /
• 2013

It is difficult for TCP congestion control algorithm to ensure the bandwidth and delay bound required for media streaming services in broadband wireless network environments. In this paper, we propose the COIN TCP (COncave INcrease TCP) scheme for providing a high-quality media streaming services. The COIN TCP concavely increases the congestion window size by adjusting the increment rate of congestion window, that is inversely proportional to the amount of data accumulated in the router queue. As a result, our scheme can quickly occupy the available bandwidth and prevent the heavy congestion. It also improves the link utilization by adjusting the decrement rate of congestion window according to the packet loss rate with the random loss. Through the simulation results, we prove that our scheme improves the total throughput in broadband wireless network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.123-125
• /
• 2015

Wireless ad hoc network which is comprised of wireless nodes that have the limited communication range is utilized to monitoring disaster area, tracing object, and tactical system. But in the case of wireless node on the ground, a network performance decrease because wireless channel is affected from obstacle or the node deployment is restricted. In this paper, we consider wireless network based on UAV(Unmanned Aerial Vehicle) which has little spatial constraint and quickly deploy a position. We implement test-bed included ground nodes and UAV, and measure throughput and PDR(Packet Delivery Ratio) according to the usage of UAV. We show that network performance is improved by relaying data on UAV.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.38 no.3
• /
• pp.61-67
• /
• 2001

In this paper, a method that apply LP algorithm to image for speech recognition is suggested, using both speech and image information for recogniton of korean numeral speech. The input speech signal is pre-emphasized with parameter value 0.95, analyzed for B th LP coefficients using Hamming window, autocorrelation and Levinson-Durbin algorithm. Also, a gray image signal is analyzed for 2-dimensional LP coefficients using autocorrelation and Levinson-Durbin algorithm like speech. These parameters are used for input parameters of neural network using back-propagation algorithm. The recognition experiment was carried out at each noise level, three numeral speechs, '3','5', and '9' were enhanced. Thus, in case of recognizing speech with 2-dimensional LP parameters, it results in a high recognition rate, a low parameter size, and a simple algorithm with no additional feature extraction algorithm.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.3
• /
• pp.70-77
• /
• 2017

Recently, Internet of Things (IoT) and deep learning techniques have affected video surveillance systems in various ways. The surveillance features that perform detection, tracking, and classification of specific objects in Closed Circuit Television (CCTV) video are becoming more intelligent. This paper presents real-time algorithm that can run in a PC environment using only a low power CPU. Traditional tracking algorithms combine background modeling using the Gaussian Mixture Model (GMM), Hungarian algorithm, and a Kalman filter; they have relatively low complexity but high detection errors. To supplement this, deep learning technology was used, which can be trained from a large amounts of data. In particular, an SRGB(Sequential RGB)-3 Layer CNN was used on tracked objects to emphasize the features of moving people. Performance evaluation comparing the proposed algorithm with existing ones using HOG and SVM showed move-in and move-out error rate reductions by 7.6 % and 9.0 %, respectively.

• Journal of Broadcast Engineering
• /
• v.18 no.2
• /
• pp.149-158
• /
• 2013

In this paper, we propose a new system which can generate digital holograms for natural color scene. The system consists of both a camera system for capturing images and softwares(SWs) for various image processings. The camera system uses a vertical rig with a depth and a RGB camera and a cold mirror which has the different transmittance according to wavelength for obtaining images with the same view point. The S/W is composed by the engines for processing and servicing the captured images and computer-generated hologram (CGH) for generating digital holograms using general-purpose computing on graphics processing unit (GPGPU). Each algorithm was implemented using C/C++ and CUDA languages, and all engines were integrated in LabView environment. The proposed system can generate 10 digital holographic frames per second using about 6K light sources.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.7
• /
• pp.1618-1626
• /
• 2013

Virtualization service processes all operation including the data creation, storing, and disposal in a server and transmits processed data as the streaming media form. Therefore, client can use the same environment as the traditional desktop environment without considering the type of device. Virtualization service should consider not only the video quality but also the delay bounds and continuity of video playback for improving the user perceived Quality of Service(QoS) of streaming service. In this paper, we propose a network-adaptive transmission architecture that focuses on guaranteeing QoS requirements for virtualization service. In order to provide those, the proposed architecture have the transmission rate adaptation function based on available bandwidth and the content bit-rate control function based on sender buffer state. Through each function, proposed architecture guarantee the delay bounds and continuity of virtualization contents playback. The simulation results show that proposed network-adaptive transmission architecture provides a improve performance of throughput and transmission delay.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.13 no.5
• /
• pp.390-399
• /
• 1988

A conventional BTC has the merit of real time processing and simple computation, but has the problem that its compression rate is low. In this paper, a modified BTC using the Quad Tree which is frequently used in binary image is proposed. The method results in the low compression rate by decreasing the total number of subblocks by mean of making the size of a subblock large in the small variation area of graty level and the size af a subblock small in the large variation area of gary level. For the effective transmission of bit plane, the Huffman run-lengh code for the large size of a subblock and the lookup table for tha small size of a subblock are used. The proposed BTC method show the result of coding 256 level image at the average data rate of about 0.8 bit/pixel.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.8
• /
• pp.680-687
• /
• 2013

We investigate a generalized combined power and rate adaptation scheme in direct-sequence (DS) code-division multiple-access (CDMA) communications over Nakagami fading channels. The transmission power allocated to user i is proportional to $G^p_i$, where $G_i$ is the channel gain of user i and p is a real number, and the data rate (i.e., spreading gain) is jointly adapted so that a desired QoS is maintained. We analyze the average data rate of the proposed adaptation scheme subject to fixed average and peak transmission power constraints. Our results show that the proposed joint adaptation scheme provides a significant performance improvement over power-only and rate-only adaptation.

• Journal of Korean Society of Transportation
• /
• v.21 no.2
• /
• pp.63-70
• /
• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• Journal of Radiation Protection and Research
• /
• v.22 no.4
• /
• pp.263-272
• /
• 1997

A Radiation Alarm Monitor has been developed and manufactured in order to protect radiation workers from over-exposure. A visual and audible alarm system has been attached to initiate evacuation when accident occurs such as an unexpected change of radiation level or an over-exposure. The Radiation Alarm Monitor installed with microprocessor can record the information of radiation field change between 90 min. before the alarm and 30 min. after the alarm and also provide the data to an IBM compatible computer to analyze the accidents and to set a counterplan. It features a wide detection range of radiation field(10 mR/h-100 R/h), radiation field data storage, portability, high precision (${\pm}5%$) due to self-calibration function, and adaption of a powerful alarm system. According to ANSI N42.17A, the most stringent test standards, performance tests were carried out under various conditions of temperature, humidity, vibration, and electromagnetic wave hindrance at Korea Research Institute of Standards & Science (KRISS). As a result, the Radiation Alarm Monitor passed all tests.