• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10B
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• pp.619-629
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• 2005

In this paper, we propose energy-aware routing schemes which are simple enough to be applicable to the wireless sensor networks. The one hop upstream no de in direction of the base-station is determined in four different ways based on the energy information of neighboring nodes, which are obtainable via the process of self-organization of the network. The fair distribution of the energy consumption over all the possible routes to the base-station is one of the design objectives. Also, an alternate route search mechanism is proposed to cope with the situation in which no routing information is available due to lack of remaining energy of the neighboring nodes. The mechanism turns out to be a supplementary scheme to improve the energy efficiency. Lots of simulations are performed to examine the performance metrics such as the energy efficiency, throughput, network lifetime, and the transmission latency of the proposed schemes. Simulation results show the feasibility of the simple routing schemes for the sensor networks.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.126-132
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• 2023

Object recognition is a technology that detects and identifies various objects in images and videos. LBP is a descriptor that operates robustly to illumination variations and is actively used in object recognition. LBP considers the range of neighboring pixels, the order of combining the neighbors after the comparison operation, and the starting position of combining. In particular, the starting position of the LBP becomes the "most significant bit"; it dramatically affects the performance of object recognition. In this paper, based on the N starting positions, the data most similar to the input data are searched in each of the N feature spaces. Object recognition is performed by the confidence measure that can compare different results of each feature space under the same criterion and select the most reliable result. In the experimental results, it was confirmed that there is a difference in performance depending on the starting position of LBP. The proposed method showed a high performance of up to 12.66% compared to the recognition performance of the existing LBP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.751-764
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• 2013

In cognitive radio ad-hoc networks, common control channel overload and packet collisions are occured due to indiscriminate broadcasting of control packets. So that the path reliability is reduced and control channel is easily saturated. In this paper, we propose a new routing algorithm considering the probability of appearance of primary user and channel status of neighbor nodes. When the source node needs to transmit a data packet to the destination, it performs route discovery process by exchanging control messages using a control channel in ADOV CR Ad-hoc networks. If any intermediate node doesn't have common data channel with previous node to transmit data, it doesn't rebroadcast control packet. And if it has common data channels with previous node, each node determines channel contribution factor with the number of common channels. Based on the channel contribution factor, each node performs different back-off broadcasting. In addition, each node controls control packet flooding by applying to proposed advanced mode using such as number of available channels and channel stability. With the proposed method, the number of control packets to find the data transmission path and the probability of collision among control packets can be decreased. While the path reliability can be increased. Through simulation, we show that our proposed algorithm reduces packet collisions in comparison with the traditional algorithm.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.219-234
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• 2018

In this study, we explored the possibility of automating the process of analyzing elements of scientific argument in the context of a Korean classroom. To gather training data, we collected 990 sentences from science education journals that illustrate the results of coding elements of argumentation according to Toulmin's argumentation structure framework. We extracted 483 sentences as a test data set from the transcription of students' discourse in scientific argumentation activities. The words and morphemes of each argument were analyzed using the Python 'KoNLPy' package and the 'Kkma' module for Korean Natural Language Processing. After constructing the 'argument-morpheme:class' matrix for 1,473 sentences, five machine learning techniques were applied to generate predictive models relating each sentences to the element of argument with which it corresponded. The accuracy of the predictive models was investigated by comparing them with the results of pre-coding by researchers and confirming the degree of agreement. The predictive model generated by the k-nearest neighbor algorithm (KNN) demonstrated the highest degree of agreement [54.04% (${\kappa}=0.22$)] when machine learning was performed with the consideration of morpheme of each sentence. The predictive model generated by the KNN exhibited higher agreement [55.07% (${\kappa}=0.24$)] when the coding results of the previous sentence were added to the prediction process. In addition, the results indicated importance of considering context of discourse by reflecting the codes of previous sentences to the analysis. The results have significance in that, it showed the possibility of automating the analysis of students' argumentation activities in Korean language by applying machine learning.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.63-70
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• 2018

Biomedical signal measurement technology using images has been developed, and researches on respiration signal measurement technology for maintaining life have been continuously carried out. The existing technology measured respiratory signals through a thermal imaging camera that measures heat emitted from a person's body. In addition, research was conducted to measure respiration rate by analyzing human chest movement in real time. However, the image processing using the infrared thermal image may be difficult to detect the respiratory organ due to the external environmental factors (temperature change, noise, etc.), and thus the accuracy of the measurement of the respiration rate is low.In this study, the images were acquired using visible light and infrared thermal camera to enhance the area of the respiratory tract. Then, based on the two images, features of the respiratory tract region are extracted through processes such as face recognition and image matching. The pattern of the respiratory signal is classified through the k-nearest neighbor classifier, which is one of the statistical classification methods. The respiration rate was calculated according to the characteristics of the classified patterns and the possibility of breathing rate measurement was verified by analyzing the measured respiration rate with the actual respiration rate.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.247-259
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• 2000

This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.11
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• pp.730-742
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• 2014

In the case of On-demand routing protocol in cognitive radio ad-hoc networks, broadcasting of control packets may occur common control channel overload and packet collisions during the routing procedure. This situation is to increase the overhead of path finding and also limited to find the accurate and reliable path. Since reliable channel and path finding is restricted, path life time is shorten and path reliability is reduced. In this paper, we propose a new routing algorithm that reduces control channel overhead and increases path life time by considering the probability of appearance of primary user and channel status of neighbor nodes. Each node performs periodic local sensing to detect primary user signal and to derive primary user activity patterns. The probability of primary appearance on the current channel and the channel status can be obtained based on the periodic sensing. In addition, each node identifies the quality of the channel by message exchange through a common channel with neighbor nodes, then determines Link_Levels with neighbor nodes. In the proposed method, the Link Level condition reduces the number of control messages that are generated during the route discovery process. The proposed method can improve path life time by choosing a path through Path_Reliability in which stability and quality are weighted depending on the location. Through simulation, we show that our proposed algorithm reduces packet collisions and increases path life time in comparison with the traditional algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1521-1531
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• 2015

According to the service attributes, D2D communications establish 1-1, or 1-n channels and require the differentiated device discovery technology. This paper proposes a sector-based device discovery mechanism for 1-n D2D communication scenario in LTE-Advanced networks that a disaster happened. Our proposal is a mechanism that can extend the coverage in a disaster situation which a number of devices(survivors) need to be discovered in a short time. In the single cell environment, a larger discovery coverage can be obtained, and in the multi-cell, it is possible to mitigate the interference with adjacent links due to sector-based coverage control. Through a set of simulations, we have confirmed that our proposal has better performance in the number of devices discovered and the interference than the legacy broadcast device discover mechanism.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.72-79
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• 2006

Recently, a MMORPG(Massively Multi-play Online Role Playing Game) has built distribute server by Seamless world. This paper proposes an efficient collision detection method. DLS is used to dynamically adjust spatial subdivisions in each the boundary regions of distribute server We use an index table to effectively utilize the relationships between in the nodes and can perform the collision detection efficiently by reconstructing nodes of the tree. Also, we maintain the information for the boundary region to efficiently detect the collections and adjust the boundary regions between distributed servers by using DLS. As the DLS uses pointers, the information for each server is not needed and the boundary regions between the distributed servers are efficiently searched. Using node index points, the construction table can be made to find between ray and neighborhood node, In addition, processes for Network traffic reduce because a copy of the boundary regions is not needed when a object moves with realtime.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.429-436
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• 2005

A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.