• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.31-40
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• 2005

Main airports in the Intra-Asian market have faced competition not only to attract China-bound transshipment cargoes but also to be hub airport in same region. In spite of such a importance, the previous research has been short of evaluation of airport competitiveness. Implication of the previous research has mainly been focused on evaluation of airport critical factor service qualify and efficiency. The aim of this paper is to present critical points that affect airport competitiveness using an algorithm based on reversed fuzzy evaluation and senario method. The results of senario analysis and reversed fuzzy evaluation shows that Incheon international airport needs to enhance service level of 7% as a result of senario analysis and service level of 5% and brand equity level of 10% at the same time as a result of reversed fuzzy evaluation analysis, to ensure competitiveness in same region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3315-3337
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• 2012

Crowded scenes analysis is a challenging topic in computer vision field. How to detect diverse motion patterns in crowded scenarios from videos is the critical yet hard part of this problem. In this paper, we propose a novel approach to mining motion patterns by utilizing motion information during both long-term period and short interval simultaneously. To capture long-term motions effectively, we introduce Motion History Image (MHI) representation to access to the global perspective about the crowd motion. The combination of MHI and optical flow, which is used to get instant motion information, gives rise to discriminative spatial-temporal motion features. Benefitting from the robustness and efficiency of the novel motion representation, the following motion pattern mining is implemented in a completely unsupervised way. The motion vectors are clustered hierarchically through automatic hierarchical clustering algorithm building on the basis of graphic model. This method overcomes the instability of optical flow in dealing with time continuity in crowded scenes. The results of clustering reveal the situations of motion pattern distribution in current crowded videos. To validate the performance of the proposed approach, we conduct experimental evaluations on some challenging videos including vehicles and pedestrians. The reliable detection results demonstrate the effectiveness of our approach.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.1-8
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• 2023

An Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication system has drawn wide attention for its high transmission rate and high spectrum efficiency in not only radio but also Underwater Acoustic (UWA) applications. Because of the narrow sub-carrier spacing of OFDM, orthogonality between sub-carriers is easily affected by Doppler effect caused by the movement of transmitter or receiver. Previously, Doppler compensation signal processing algorithm for Desired propagation path was proposed. However, other Doppler shifts caused by delayed Undesired signal arriving from different directions cannot be perfectly compensated. Then Receiver Bit Error Rate (BER) is degraded by Inter-Carrier-Interference (ICI) caused in the case of Multi-path Doppler channel. To mitigate the ICI effect, a modified Delay and Doppler Profiler (mDDP), which estimates not only attenuation, relative delay and Doppler shift but also sampling clock shift of each multi-path component, is proposed. Based on the outputs of mDDP, an ICI canceling multi-tap equalizer is also proposed. Computer simulated performances of one-tap equalizer with the conventional Time domain linear interpolated Channel Transfer Function (CTF) estimator, multi-tap equalizer based on mDDP are compared. According to the simulation results, BER improvement has been observed. Especially, in the condition of 16QAM modulation, transmitting vessel speed of 6m/s, two-path multipath channel with direct path and ocean surface reflection path; more than one order of magnitude BER reduction has been observed at CNR=30dB.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.303-309
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• 2018

Computer vision technology is a component inspection to obtain a video image from the camera to the machine to perform the capabilities of the human eye with a field of artificial intelligence, and then analyzed by the algorithm to determine to determine the good and bad of production parts It is widely applied. Shape inspection method was used as how to identify the location of the start point and the end point of the search range, measure the height to the line scan method, in such a manner as to determine the presence or absence of the bolt tabs average brightness of the inspection area in a circular scan type value And the degree of similarity was calculated. The total time it takes to test in the test performance tests of two types of bolts tab enables test 300 min, and demonstrated the accuracy and efficiency of the inspection on the production line represented a complete inspection accuracy.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.43.1-43.1
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• 2018

Star formation in galaxies predominantly takes place in giant molecular clouds (GMCs). While it is widely believed that UV radiation feedback from young massive stars can destroy natal GMCs by exciting HII regions and driving their expansion, our understanding on how this actually occurs remains incomplete. To quantitatively assess the effect of UV radiation feedback on cloud disruption, we conduct a series of theoretical studies on the dynamics of HII regions and its role in controlling the star formation efficiency (SFE) and lifetime of GMCs in a wide range of star-forming environments. We first develop a semi-analytic model for the expansion of spherical dusty HII regions driven by the combination of gas and radiation pressures, finding that GMCs in normal disk galaxies are destroyed by gas-pressure driven expansion with SFE < 10%, while more dense and massive clouds with higher SFE are disrupted primarily by radiation pressure. Next, we turn to radiation hydrodynamic simulations of GMC dispersal to allow for self-consistent star formation as well as inhomogeneous density and velocity structures arising from supersonic turbulence. For this, we develop an efficient parallel algorithm for ray tracing method, which enables us to probe a range of cloud masses and sizes. Our parameter study shows that the net SFE, lifetime (measured in units of free-fall time), and the importance of radiation pressure (relative to photoionization) increase primarily with the initial surface density of the cloud. Unlike in the idealized spherical model, we find that the dominant mass loss mechanism is photoevaporation rather than dynamical ejection and that a significant fraction of radiation escapes through low optical-depth channels. We will discuss the astronomical.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.232-239
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• 2016

Recently, in order to increase the efficiency and mission success rate of UAVs (Unmanned Aerial Vehicles), the necessity for formation flights is increased. In general, GPS (Global Positioning System) is used to obtain the relative position of leader with respect to follower in formation flight. However, it can't be utilized in environment where GPS jamming may occur or communication is impossible. Therefore, in this study, monocular vision is used for measuring relative position. General PC-based vision processing systems has larger size than embedded systems and is hard to install on small vehicles. Thus FPGA-based processing board is used to make our system small and compact. The processing system is divided into two blocks, PL(Programmable Logic) and PS(Processing system). PL is consisted of many parallel logic arrays and it can handle large amount of data fast, and it is designed in hardware-wise. PS is consisted of conventional processing unit like ARM processor in hardware-wise and sequential processing algorithm is installed on it. Consequentially HW/SW co-designed FPGA system is used for processing input images and measuring a relative 3D position of the leader, and this system showed RMSE accuracy of 0.42 cm ~ 0.51 cm.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.41-47
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• 2010

It is very important to prolong the lifetime of wireless sensor networks by using their limited energy efficiently, since it is not possible to change or recharge the battery of sensor nodes after deployment. LEACH protocol is a typical routing protocol based on the clustering scheme for the efficient use of limited energy. It is composed of a few clusters, which consist of head nodes and member nodes. Though LEACH starts from the supposition that all nodes have data transferred to a head, there must be some nodes having useless data in actual state. In this paper we propose a power saving scheme by making a member node dormant if previous sensed data and current data is same. We evaluate the performance of the proposed scheme in comparison with original clustering algorithms. Simulation results validate our scheme has better performance in terms of the number of alive nodes as time evolves.

• Journal of IKEEE
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• v.14 no.4
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• pp.317-323
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• 2010

The video surveillance system is adopted in many places due to its efficiency and constancy in monitoring a specific area over a long period of time. However, many surveillance systems composed of a single static camera often produce unsatisfactory results due to their lack of field of view. In this paper, we present a video surveillance system based on wide baseline stereo cameras to overcome the limitation. We adopt the codebook algorithm and mathematical morphology to robustly model the foreground pixels of the moving object in the scene and calculate the trajectory of the moving object via 3D reconstruction. The experimental results show that the proposed system detects a moving object and generates a top view trajectory successfully to track the location of the object in the world coordinates.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.461-467
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• 2019

As the convergence solutions become more common, the use of Arduino and Raspberry Pi boards has been increasing. These control boards has to be executed under power blackout. In this environment, we take advantage of solar power system to overcome the power out. In this paper, we poposed a effficient power control strategy. Our experimental device is a DSLR shooting device executed based a predesigned interval time. The control module of our experimental device is the compound system of Raspberry Pi and Arduino boards. Arduino board send the force signals to wake up Raspberry Pi. We developed a new control strategy algorithm for the efficient use of solar power energy. In this paper, we mesured the efficiency of solar enery consuming of our system. We programmed a control system to send DSLR shooting signals. In experimentals, we ensured a stable consuming of electricity during 10 days. In the end, it was found that the consumption power of the Raspberry was reduced by about 81% when the Aduino was combined to save power.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.90-94
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• 2024

Diagnosing wounds presents a significant challenge in clinical settings due to its complexity and the subjective assessments by clinicians. Wound deep learning algorithms quantitatively assess wounds, overcoming these challenges. However, a limitation in existing research is reliance on specific datasets. To address this limitation, we created a comprehensive dataset by combining open dataset with self-produced dataset to enhance clinical applicability. In the annotation process, machine learning based on Gradient Vector Flow (GVF) was utilized to improve objectivity and efficiency over time. Furthermore, the deep learning model was equipped U-net with residual blocks. Significant improvements were observed using the input dataset with images cropped to contain only the wound region of interest (ROI), as opposed to original sized dataset. As a result, the Dice score remarkably increased from 0.80 using the original dataset to 0.89 using the wound ROI crop dataset. This study highlights the need for diverse research using comprehensive datasets. In future study, we aim to further enhance and diversify our dataset to encompass different environments and ethnicities.