• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.277-282
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• 2012

In this paper, we present a real-time eye contact system for realistic telepresence using a Kinect depth camera. In order to generate the eye contact image, we capture a pair of color and depth video. Then, the foreground single user is separated from the background. Since the raw depth data includes several types of noises, we perform a joint bilateral filtering method. We apply the discontinuity-adaptive depth filter to the filtered depth map to reduce the disocclusion area. From the color image and the preprocessed depth map, we construct a user mesh model at the virtual viewpoint. The entire system is implemented through GPU-based parallel programming for real-time processing. Experimental results have shown that the proposed eye contact system is efficient in realizing eye contact, providing the realistic telepresence.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.713-720
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• 2018

The Signal Intelligence (SIGINT) system based on Angle-of-Arrival(AOA) estimation, interference suppression, and transmission beamforming techniques is a cutting edge technology for efficiently collecting various signal information. In this paper, we present the efficient structure of a satellite system consisted of an AOA estimator, an adaptive beamformer, a signal processing and D/B unit, and a transmission beamformer, for collecting signal information. For accurately estimating AOAs of various signals, efficiently suppressing interference or jamming signals, and efficiently transmitting the collected information or data, we employ Multiple Signal Classification (MUSIC), Minimum Variance Distortionless Response (MVDR), and Minimum Mean Square Error (MMSE) algorithms, respectively. Also, we evaluate and analysis the performance of the presented satellite system through the computer simulation.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.489-496
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• 2016

Thousands of pathological images are produced daily per hospital and they are stored and managed by a pathology information system (PIS). Since image edge detection is one of fundamental analysis tools for pathological images, many researches are targeted to improve accuracy and performance of image edge detection algorithm of HIS. In this paper, we propose a novel image edge detection method. It is based on Canny algorithm with adaptive threshold configuration. It also uses a dividing ruler to configure the two threshold instead of whole image to improve the detection ratio of ruler itself. To verify the effectiveness of our proposed method, we conducted empirical experiments with real pathological images(randomly selected image group, image group that was unable to detect by conventional methods, and added noise image group). The results shows that our proposed method outperforms and better detects compare to the conventional method.

• The KIPS Transactions:PartC
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• v.12C no.3 s.99
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• pp.395-400
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• 2005

The IEEE 802.11b WLAN supports multiple transmission rates and the rate is chosen in an adaptive manner by an auto rate control algorithm. This auto rate control algorithm deeply affects the total system performance of the IEEE 802.11b WLAN. In this paper, we examine the WLAN performance with regard to the auto rate control algorithm especially the ARF scheme. The experimental results indicate that the ARF scheme works well in the face of signal noise due to node location. However, the ARF scheme severely degrades system performance when multiple nodes contend to obtain the wireless channel and the packet is lost due to signal collision. In addition, TCP prevent the performance degradation due to ARF scheme by retaining number of active nodes. However, some applications, such as transporting multimedia data, adopt the UDP. Therefore, the TCP cannot be an optimal solution for all WLAN applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.99-103
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• 2006

In this paper, we focus on the problem of designing an energy efficient MAC protocol for wireless sensor networks and analyze S(Sensor)-MAC and T(Time-out)-MAC. S-MAC is based on the concept of the 'listen/sleep mode cycle'. This applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data moves through the network. However unlike the S-MAC, where the duration of the cycle is fixed, T-MAC introduces an adaptive duty cycle in a novel way: by dynamical ending the active part of it. This reduces the amount of energy wasted on idle listening, in which nodes wait for potentially incoming messages while still maintaining a reasonable throughput. In this paper we discuss the design of these two Protocols. We analyze them from the aspect of latency, throughput, and power savings when using the OMNeT++ simulator in various environments.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.303-310
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• 2008

To increase the lifetime of ad-hoc networks, a ratio of energy consumption for each node should be kept constant by equally distributing network traffic loads into all of the nodes. In this paper, we propose a modified AODV routing protocol to determine a possible route by considering a remaining battery capacity of a node and the degree of its usage. In addition, to reduce the amount of energy consumption during the path rediscovery process due to the huge amount of the AODV control messages the limited number of possible routes are stored into a routing table of a source node. When some links of a route fail, another possible path can be looked up in the table before the route discovery process should be initiated. We have tested our proposed method with a conventional AODV and a MMBCR method which is one of the power-efficient energy routing protocols based on the three performance metrics, i.e., the total remaining battery capacity, network lifetime and the ratio of data packets received by the destination node to compare their performance.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.297-306
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• 2002

Continuous multimedia applications require a guaranteed retricval and transfer rate of streaming data, which conventional file server mechanism generally does not provide. In this paper we describe a dynamic negotiated admission control and dick bandwidth scheduling framework for Continuous Media (CM : e.g., video) servers. The framework consists of two parts. One is a reserve-based admission control mechanism and the other part is a scheduler for continuous media streams with dynamic resource allocation to achieve higher utilization than non-dynamic scheduler by effectively sharing available resources among contending streams to improve overall QoS. Using our policy, we could increase the number of simultaneously running: clients that coo]d be supported and cot]d ensure a good response ratio and better resource utilization under heavy traffic requirements.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.129-136
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• 2010

With mobile computing, wireless sensor network and sensor technologies, ubiquitous computing services are being realized and could satisfy the feasibility of ubiquitous healthcare to everyone. This u-Healthcare service can improve life quality of human since medical service can be provided to anyone, anytime, and anywhere. To confirm the vision of u-Healthcare service, we've implemented a healthcare system for heart disease patient which is composed of two components. Front-end collects various signals such as temperature, blood pressure, SpO2, and electrocardiogram, etc. As a backend, medical information server accumulates sensing data and performs back-end processing. To simply transfer these sensing values to a medical team may be too trivial. So, we've designed a model based on context awareness for more improved medical service which is based on artificial neural network. Through rigid experiments, we could confirm that the proposed system can provide improved medical service.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.501-512
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• 2021

Recently, a breakthrough has been made in the NLP area by Transformer techniques based on encoder-decoder. However, this only can be used in mainstream languages where millions of dataset are well-equipped, such as English and Chinese, and there is a limitation that it cannot be used in non-mainstream languages where dataset are not established. In addition, there is a deflection problem that focuses on the beginning of the document in mechanical summarization. Therefore, these methods are not suitable for documents with flows such as fairy tales and novels. In this paper, we propose a hybrid summarization method that does not require a dataset and improves the deflection problem using GAN with two adaptive discriminators. We evaluate our model on the CNN/Daily Mail dataset to verify an objective validity. Also, we proved that the model has valid performance in Korean, one of the non-mainstream languages.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.155-164
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• 2015

This paper describes a design and implementation of CABAC decoder, which would handle HEVC syntax elements in adaptively pipelined-parallel computation manner. Even though CABAC offers the high compression rate, it is limited in decoding performance due to context-based sequential computation, and strong data dependency between context models, as well as decoding procedure bin by bin. In order to enhance the decoding computation of HEVC CABAC, the flag-type syntax elements are adaptively pipelined by precomputing consecutive flag-type ones; and multi-bin syntax elements are decoded by processing bins in parallel up to three. Further, in order to accelerate Binary Arithmetic Decoder by reducing the critical path delay, the update and renormalization of context modeling are precomputed parallel for the cases of LPS as well as MPS, and then the context modeling renewal is selected by the precedent decoding result. It is simulated that the new HEVC CABAC architecture could achieve the max. performance of 1.01 bins/cycle, which is two times faster with respect to the conventional approach. In ASIC design with 65nm library, the CABAC architecture would handle 224 Mbins/sec, which could decode QFHD HEVC video data in real time.