• Journal of IKEEE
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• v.13 no.2
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• pp.232-240
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• 2009

This paper presents a robust vehicle detection and tracking algorithm for supervision of illegal parking. The proposed algorithm is composed of four parts. First, a vehicle detection algorithm is proposed using the improved codebook object detection algorithm to segment moving vehicles from the input sequence. Second, a preprocessing technique using the geometric characteristics of vehicles is employed to exclude non-vehicle objects. Then, the detected vehicles are tracked by an object tracker which incorporates histogram tracking method with Kalman filter. To make the tracking results more accurate, histogram tracking results are used as measurement data for Kalman filter. Finally, Real Stop Counter (RSC) is introduced for trustworthy and accurate performance of the stopped vehicle detection. Experimental results show that the proposed algorithm can track multiple vehicles simultaneously and detect stopped vehicles successfully in the complicated street environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.221-232
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• 2012

The double-density discrete wavelet transform(DWT) is an improvement upon the critically sampled DWT with important additional properties. It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is overcomplete by a factor of two. Also, this transformation is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. Proposed method is a DWT that combines the double-density DWT and quincunx sampling, each of which has its own characteristics and advantages. Especially, the quincunx sampling treats the different directions more homogeneously. As a result, since proposed method can generate sub-images of multiple degrees rotated versions, this method provides an improved performance in image processing fields.

• Journal of dental hygiene science
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• v.19 no.4
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• pp.220-227
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• 2019

Background: This descriptive study aimed to examine the relationship between the 4C core competencies and work ability among dental hygienists. Methods: From November 2018 to January 2019, data were collected-from 190 dental hygienists workong in dental clinics in Busan, Ulsan, and Gyeongsangnam province using structured questionnaires. For the general characteristics of the dental hygienists, frequency and percentage were calculated, and the level of the 4C core competencies and work ability of dental hygienists was calculated using means and standard deviations. A multiple regression analysis was conducted to analyze the effects of the 4C core competencies on work ability. Results: The mean scores for the 4C core competency levels of the dental hygienists were as follows: communication ability 3.34, critical thinking ability 3.41, creative problem-solving 3.40, and collaborative self-efficacy 3.27. Meanwhile the mean score for work ability level was 3.65. The predictive factors influencing work ability were communication ability and cooperative self-efficacy (p<0.001), and the sub-factors of critical thinking ability that affect work ability were sound conferences (p<0.01), intellectual fairness (p<0.05), intellectual enthusiasm (p<0.05), and self-confidence (p<0.001). Finally, the sub-factors of creative problem-solving ability that affect work ability were planning and execution (p<0.01) and performance evaluation (p<0.05). Conclusion: The current study showed that education programs covering the core competencies of dental hygienists, rather than the existing theoretical education program, should be developed and implemented to enhance 4C core competencies that affect work ability.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.3
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• pp.54-62
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• 2016

Micro plasma thruster (${\mu}PT$) was studied experimentally with a dual-stage micro-hollow cathode discharge (MHCD) plasma. Electrostatic-like acceleration exhibiting more directional and elongated exhaust plume was achieved by a dual layer MHCD at the total input power less than 10 W with argon flow rate of 40 sccm. V-I characteristic indicated that there was an optimal regime for dual-stage operation where the acceleration voltage across the second stage remained constant. Estimated exhaust plume length showed a similar trend to the analytic estimate of exhaust velocity which scales with an acceleration voltage. ${\mu}PT$ with multiple holes exhibited similar performance with single-hole thruster indicating that higher power loading is possible owing to decreased power through each hole. Boltzmann plot of atomic argon spectral lines showed average electron excitation temperature of about 2.6 eV (~30,170 K) in the exhaust plume.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.209-218
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• 2005

In this paper, we present an Active Optical Network(AON) . The AON uses the Dense Wavelength Division Multiplexing(DWDM) from optical communication access network of ring type, and will be able to provide the smoothly service in the Bandwidth on Demand by using DWDM. It supports the connection of the multiple wavelength and the Sub-Carrier from the optical gigabit ethernet switch. The Wavelength Add Drop Multiplexer(WADM) extracts a specific wavelength, and composes a node of the ring network. The specific wavelength becomes demultiplexing in the Sub-Carrier and it is distributed in the user The active connection of optical gigabit ethernet switch where the distribution of access network is started and access terminal connection equipment is possible. By the BoD from the AON it compares the buffer size which changes, and it analyzes. Also the Time delay of bit compares with the throughput of server The limit of amount of time is decided. Consequently it will be able to realize the dynamic use protocol and an efficient algorithm of the network.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.11
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• pp.1127-1133
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• 2012

A finned-tube-type evaporator module has been proposed for a 2 t/h-class water-tube-type industrial boiler with multiple burners. The geometry of the fins was changed at each module to equalize the evaporation. The modules were designed by considering the energy balance at each row rather than by following a conventional bulk design procedure. The designed module was built into a 2 t/h-class water-tube-type boiler, and its performance was tested. A numerical simulation was also conducted to evaluate the two- or three-dimensional effects of factors such as the inlet conditions. The numerical simulation also included the conjugate heat transfer problem to predict the fin tip temperature. The heat transfer coefficient with fins is lower than that obtained from the empirical correlation of a bare tube. The fin tip temperature from CFD is higher than that from the analytical solution.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.7
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• pp.627-633
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• 2009

Composite has become one of the most frequently used material for a tube of satellite camera due to its attractive characteristics. However, laminated composites can be weakened by delamination which comes from interlaminar stress. Such failure mode cause structural instability of the camera as well as degradation of optical quality. Therefore composite tube should be robust in delamination. Also, composite tube should have high stiffness, sufficient high natural frequency and small coefficient of thermal expansion. The design procedures presented in this paper are based on design of experiments. The experiments for mechanical analysis are designed by the tables of orthogonal arrays. In order to manipulate the various mechanical properties systematically, multiple-attribute decision making(MADM) is employed. Through analysis of variance and F-test, the critical design variables which have dominant influences on mechanical performance are determined. Finally improved ply angles for composite tube are determined.

• Knowledge Management Research
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• v.21 no.1
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• pp.175-195
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• 2020

The development of platform service based on the information and communication technology has revolutionized patterns of commercial transactions, driving the growth of global economy. Furthermore, the radical advancement of artificial intelligence(AI) presents the huge potential to innovate almost all the industrial and economic activities. Given these technological developments, the goal of this paper is to investigate AI's impact on the platform service innovation as well as its influence on the business performance. For the goal, this paper presents the review of the types of service innovation, the nature of platform services, and technological characteristics of leading AI technologies, such as chatbot and recommendation system. As an empirical study, this paper performs a multiple case study of Kakao Group which is the leading mobile platform service with the most advanced AI in Korea. To understand the role and effect of AI on Kakao platform service, this study investigated three cases, including chatbot agent of Kakao Bank, Smart Call service of Kakao Taxi, and music recommendation system of Kakao Mellon. The analysis results of the case study show that AI initiated innovations in platform service concepts, service delivery, and customer interface, all of which lead to a significant decrease in the transaction costs and the personalization of services. Finally, for the successful development of AI, this research emphasizes the significance of the accumulation of customer and operational data, the AI human capital, and the design of R&D organization.