• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.619-624
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• 2016

Social-aware video displays not only the relationships between characters but also diverse information on topics such as economics, politics and culture as a story unfolds. Particularly, the speaking habits and behavioral patterns of people in different situations are very important for the analysis of social relationships. However, when dealing with this dynamic multi-modal data, it is difficult for a computer to analyze the drama data effectively. To solve this problem, previous studies employed the deep concept hierarchy (DCH) model to automatically construct and analyze social networks in a TV drama. Nevertheless, since location knowledge was not included, they can only analyze the social network as a whole in stories. In this research, we include location knowledge and analyze the social relations in different locations. We adopt data from approximately 4400 minutes of a TV drama Friends as our dataset. We process face recognition on the characters by using a convolutional- recursive neural networks model and utilize a bag of features model to classify scenes. Then, in different scenes, we establish the social network between the characters by using a deep concept hierarchy model and analyze the change in the social network while the stories unfold.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.194-202
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• 2018

This study was designed to analyze the impact of Christian counseling for the common faith and religious wellbeing within the Korean Luther Church, and to provide church growth factors based on the results. The study target was based on the survey results of a total of 83 members who were attending layman in the ${\bigcirc}{\bigcirc}{\bigcirc}$ church, which is affiliated with the Korean Lutheran Church. The research tool used NCD questionnaire for church health diagnosis by the Korea Church Growth Institute for the church growth model and the reliability of Cronbach's ${\alpha}$ in this study was 0.91. The collected questionnaire was tested for correlation to verify the relationship between church development and growth, and for multiple recursive analysis to confirm factors affecting church development and growth. The results showed that church's services, programs, and atmosphere were highly correlated with development of church, including counseling. The research showed that the relationship between church services, programs, and friends, including counseling, was highly correlated with spiritual growth and self-growth, while community activities and mutual communication were low. Therefore, for continuous church growth, the importance of community programs in the church is considered necessary.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of Korean Neurosurgical Society
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• v.50 no.4
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• pp.299-303
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• 2011

Objective : Brainstem metastases are rarely operable and generally unresponsive to conventional radiation therapy or chemotherapy. Recently, Gamma Knife Radiosurgery (GKRS) was used as feasible treatment option for brainstem metastasis. The present study evaluated our experience of brainstem metastasis which was treated with GKRS. Methods : Between November 1992 and June 2010, 32 patients (23 men and 9 women, mean age 56.1 years, range 39-73) were treated with GKRS for brainstem metastases. There were metastatic lesions in pons in 23, the midbrain in 6, and the medulla oblongata in 3 patients, respectively. The primary tumor site was lung in 21, breast in 3, kidney in 2 and other locations in 6 patients. The mean tumor volume was $1,517mm^3$ (range, 9-6,000), and the mean marginal dose was 15.9 Gy (range, 6-23). Magnetic Resonance Imaging (MRI) was obtained every 2-3 months following GKRS. Follow-up MRI was possible in 24 patients at a mean follow-up duration of 12.0 months (range, 1-45). Kaplan-Meier survival analysis was used to evaluate the prognostic factors. Results : Follow-up MRI showed tumor disappearance in 6, tumor shrinkage in 14, no change in tumor size in 1, and tumor growth in 3 patients, which translated into a local tumor control rate of 87.5% (21 of 24 tumors). The mean progression free survival was 12.2 months (range, 2-45) after GKRS. Nine patients were alive at the completion of the study, and the overall mean survival time after GKRS was 7.7 months (range, 1-22). One patient with metastatic melanoma experienced intratumoral hemorrhage during the follow-up period. Survival was found to be associated with score of more than 70 on Karnofsky performance status and low recursive partitioning analysis class (class 1 or 2), in terms of favorable prognostic factors. Conclusion : GKRS was found to be safe and effective for management of brainstem metastasis. The integral clinical status of patient seems to be important in determining the overall survival time.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.209-218
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• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.53-66
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• 2006

This paper proposes the combined image retrieval system that gives the same relevance as exhaustive search method while its performance can be considerably improved. This system is combined with two different retrieval methods and each gives the same results that full exhaustive search method does. Both of them are two-stage method. One uses condensation of feature vectors, and the other uses binary-tree clustering. These two methods extract the candidate images that always include correct answers at the first stage, and then filter out the incorrect images at the second stage. Inasmuch as these methods use equal algorithm, they can get the same result as full exhaustive search. The first method condenses the dimension of feature vectors, and it uses these condensed feature vectors to compute similarity of query and images in database. It can be found that there is an optimal condensation ratio which minimizes the overall retrieval time. The optimal ratio is applied to first stage of this method. Binary-tree clustering method, searching with recursive 2-means clustering, classifies each cluster dynamically with the same radius. For preserving relevance, its range of query has to be compensated at first stage. After candidate clusters were selected, final results are retrieved by computing similarities again at second stage. The proposed method is combined with above two methods. Because they are not dependent on each other, combined retrieval system can make a remarkable progress in performance.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.2
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• pp.110-116
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• 2005

It is very important to reduce the computational processing time for the application of the vision system in real time such as inspection, the determination of object's dimension and welding etc, because the vision system model involves a lot of measurement data acquired by CCD camera. Also, a lot of computation time is required in estimating the parameters in the vision system model if the iterative batch estimation method such as Newton Raphson is used. Thus, the effective computation method such as the Extended Kalman Filtering(EKF) is required to solve the above problems. The EKF has much advantages in that it takes explicitly into account the measurement uncertainties, and is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm to compute the parameters in the vision system model in real time. This vision system model involves the six parameters to account for the cameras inner and outer parameters. Also the EKF is applied to estimate the object's dimension. Finally, practicality of the estimation scheme of the vision system based on the EKF is verified experimently by performing the estimation of object's dimension.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.21-29
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• 2003

It is very important to reduce the computational time in estimating the parameters of vision control algorithm for robot's position control in real time. Unfortunately, the batch estimation commonly used requires too murk computational time because it is iteration method. So, the batch estimation has difficulty for robot's position control in real time. On the other hand, the Extended Kalman Filtering(EKF) has many advantages to calculate the parameters of vision system in that it is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm for the robot's vision control in real time. The vision system model used in this study involves six parameters to account for the inner(orientation, focal length etc) and outer (the relative location between robot and camera) parameters of camera. Then, EKF has been first applied to estimate these parameters, and then with these estimated parameters, also to estimate the robot's joint angles used for robot's operation. finally, the practicality of vision control scheme based on the EKF has been experimentally verified by performing the robot's position control.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.3
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• pp.187-187
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• 2004

In this paper, we present an efficient architecture of a versatile Reed-Solomon (RS) decoder which can be programmed to decode RS codes continuously with my message length k as well as any block length n. This unique feature eliminates the need of inserting zeros for decoding shortened RS codes. Also, the values of the parameters n and k, hence the error-correcting capability t can be altered at every codeword block. The decoder permits 3-step pipelined processing based on the modified Euclid's algorithm (MEA). Since each step can be driven by a separate clock, the decoder can operate just as 2-step pipeline processing by employing the faster clock in step 2 and/or step 3. Also, the decoder can be used even in the case that the input clock is different from the output clock. Each step is designed to have a structure suitable for decoding RS codes with varying block length. A new architecture for the MEA is designed for variable values of the t. The operating length of the shift registers in the MEA block is shortened by one, and it can be varied according to the different values of the t. To maintain the throughput rate with less circuitry, the MEA block uses both the recursive technique and the over-clocking technique. The decoder can decodes codeword received not only in a burst mode, but also in a continuous mode. It can be used in a wide range of applications because of its versatility. The adaptive RS decoder over GF($2^8$) having the error-correcting capability of upto 10 has been designed in VHDL, and successfully synthesized in an FPGA chip.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.3
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• pp.29-38
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• 2004

In this paper, we present an efficient architecture of a versatile Reed-Solomon (RS) decoder which can be programmed to decode RS codes continuously with my message length k as well as any block length n. This unique feature eliminates the need of inserting zeros for decoding shortened RS codes. Also, the values of the parameters n and k, hence the error-correcting capability t can be altered at every codeword block. The decoder permits 3-step pipelined processing based on the modified Euclid's algorithm (MEA). Since each step can be driven by a separate clock, the decoder can operate just as 2-step pipeline processing by employing the faster clock in step 2 and/or step 3. Also, the decoder can be used even in the case that the input clock is different from the output clock. Each step is designed to have a structure suitable for decoding RS codes with varying block length. A new architecture for the MEA is designed for variable values of the t. The operating length of the shift registers in the MEA block is shortened by one, and it can be varied according to the different values of the t. To maintain the throughput rate with less circuitry, the MEA block uses both the recursive technique and the over-clocking technique. The decoder can decodes codeword received not only in a burst mode, but also in a continuous mode. It can be used in a wide range of applications because of its versatility. The adaptive RS decoder over GF(2$^{8}$ ) having the error-correcting capability of upto 10 has been designed in VHDL, and successfully synthesized in an FPGA chip.