• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.103-109
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• 2005

At the adjacent sea area of Busan Central Wharf, a variety of vessels, such as middle-large passenger ships, small fast sailing ships, container ships, cargo ships and working ships as well as small miscellaneous vessels are freely sailing comparatively without special steering and sailing Rules and marine traffic control because exclusive wharfs in accord with their purpose and use have been arranged in each wharf. In this research, we analyzed traffic stream and navigational characteristics of main traffic route based on statistics and distribution of tracks by ship's type and tonnage of the passing vessels after conducting marine traffic survey twice using exclusive software by targeting the sea area during the period of time. We examined the traffic safety of the passing vessels by classifying the sea area by each function based on the analysis about this traffic situation, and analyzing the effect by designating 'Buknea passage'. We also studied the plan for the effective rearrangement of Central Wharf considering basically the traffic safety oif arrival and departure in a point if view of navigators.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2B
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• pp.1-10
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• 2005

TCP/IP protocols have been implemented in software program running on CPU in end systems. As the increased demand of fast protocol processing, it is required to implement the protocols in hardware, and Host Interface is responsible for communication between external CPU and the hardware blocks of TCP/IP implementation. The Host Interface follows AMBA AHB specification for the communication with external world. For control flow, the Host Interface behaves as a slave of AMBA AHB. Using internal Command/status Registers, the Host Interface receives commands from CPU and transfers hardware status and header information to CPU. On the other hand, the Host Interface behaves as a master for data flow. Data flow has two directions, Receive Flow and Transmit Flow. In Receive Flow, using internal RxFIFO, the Host Interface reads data from UDP FIFO or TCP buffer and transfers data to external RAM for CPU to read. For Transmit Flow, the Host Interface reads data from external RAM and transfers data to UDP buffer or TCP buffer through internal TxFIFO. TCP/IP hardware blocks generate packets using the data and transmit. Buffer Descriptor is one of the Command/Status Registers, and the information stored in Buffer Descriptor is used for external RAM access. Several testcases are designed to verify TCP/IP functions. The Host Interface is synthesized using the 0.18 micron technology, and it results in 173 K gates including the Command/status Registers and internal FIFOs.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.98-113
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• 2002

In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.

• Korean Journal of Applied Biomechanics
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• v.26 no.4
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• pp.343-351
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• 2016

Objective: The purpose of this study was to help improve game performance and provide preliminary data to enhance the efficiency of the kick and stability of the support foot by comparing the kinematic characteristics of the repeated side kick (geodeupyeopchagi) in poomsaeKoryo between expert and non-expert groups. Method: The subjects were divided into 2 groups according to proficiency in Taekwondo, an expert group and a non-expert group (n = 7 in each group), to observe the repeated side-kick technique. Four video cameras were set at a speed of 60 frames/sec and exposure time of 1/500 sec to measure the kinematic factors of the 2 groups. The Kwon3D XPprogramas used to collect and analyze three-dimensional spatial coordinates. Ground reaction force data were obtained through a force plate with a 1.200-Hz frequency. An independent samplesttest was performed, and statistical significance was defined as .05. The SPSS 18.0 software was used to calculate the mean and standard deviation of the kinematic factors and to identify the difference between the experts and non-experts. Results: The angular displacement of the hip joint in both the expert and non-expert groups showed statistical significance on E1 and E4 of the left support foot and E5 of the right foot (p<.05). The angle displacement of the knee joint in both groups showed statistical significance on E4 of the left support foot, and E1 and E2 of the right foot (p<.05). The angular velocity of the lower leg in both groups showed no statistical significance on the left support foot but showed statistical significance on E2 and E6 of the right foot (p<.05). The angular velocity of the foot in both groups showed no statistical significance on the left support foot but showed statistical significance on E2 of the right foot (p<.05). The vertical ground reaction force in both groups showed statistical significance on E2 (p<.05). The center of pressure in all directions in both groups showed statistical significance (p<.5). Conclusion: While performing the repeated side kick (geodeupyeopchagi), the experts maintainedconsistency and stability of the angle of the support leg while the kick foot moved high and fast. On the other hand, the angle of the support foot of non-experts appeared inconsistent, and the kick foot was raised, relying on the support leg, resulting in unstable and inaccurate movement.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.100-107
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• 2013

As the eBook market grows fast recently, various eBook viewer solutions such as hardware viewers and software readers came out to the market. We can, however, hardly find mobile eBook interfaces for the reading disabled people who have difficulties in reading for their visual impairment or learning disabilities, or dyslexia. An eBook viewer interfaces for the reading disabled people should be carefully and distinctively designed because the reading disabled people cannot use normal versions of eBook viewer. In this paper, we suggest a eBook viewer interface model to make the reading disabled people read eBooks easily. Depending on the type of the reading disabled people: the full blind, the almost blind, the just learning disabled, our model provides an adaptive interface to make them read eBooks effectively. In addition, unlike the existing simple audio books, we also support annotation systems to make the reading disabled people interact with eBook viewer. To show the effectiveness of our model, we implemented an eBook viewer prototype on an android-based mobile device. We are sure that our model and implementation can make the reading disabled people, who is 10% of all the domestic people, read eBooks effectively.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.337-350
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• 2014

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and are actuated. IoT applications provide smart services to users by interacting with multiple devices connected to the network. IoT devices provide the simple set of the information and also offer smart services by collaborating with other devices. That is, IoT applications always interact with IoT devices which are becoming very popular at a fast pace. However, due to this fact, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. Moreover, since IoT computing has its own characteristics which are distinguished from other former paradigms such as embedded computing and mobile computing, IoT applications also reveal their own technical challenges. Therefore, we analyze technical challenges occurring in developing IoT applications and present effective solutions to overcome the challenges. To verify identified issues and presented solutions, we present the result of performing a case study of developing an IoT application. Through the case study, we verify how the unconventional technical issues are raised in a real domain and analyze effectiveness of applying the solutions to the application.

• Korean Journal of Optics and Photonics
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• v.29 no.1
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• pp.19-27
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• 2018

A change in object distance would generally change the magnification of an optical system. In this paper, we have proposed and designed a double-Gauss optical system with a fixed magnification and image surface regardless of any change in object distance, according to moving the lens groups a little bit to the front and rear of the stop, independently parallel to the direction of the optical axis. By maintaining a constant size of image formation in spite of various object-distance changes in a projection system such as a head-up display (HUD) or head-mounted display (HMD), we can prevent the field of view from changing while focusing in an HUD or HMD. Also, to check precisely the state of the wiring that connects semiconductor chips and IC circuit boards, we can keep the magnification of the optical system constant, even when the object distance changes due to vertical movement along the optical axis of a testing device. Additionally, if we use this double-Gauss optical system as a vision system in the testing process of lots of electronic boards in a manufacturing system, since we can systematically eliminate additional image processing for visual enhancement of image quality, we can dramatically reduce the testing time for a fast test process. Also, the Gaussian bracket method was used to find the moving distance of each group, to achieve the desired specifications and fix magnification and image surface simultaneously. After the initial design, the optimization of the optical system was performed using the Synopsys optical design software.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.