• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1263-1269
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• 2014

As rapid development of new hardware control interface technology, new concepts have been being proposed and emerged. In this paper, a new approach based on leap motion system is proposed. While we employ a position information from sensor, the hand gesture recognition is suggested with the pre-defined patterns. To do this, we design a recognition algorithm with hand gesture and finger patterns. We apply the proposed scheme to 3-dimensional avatar controling and editing software tool for making animation in the cyber space as a representative application. This proposed algorithm can be used to control computer systems in medical treatment, game, education and other various areas.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.566-568
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• 1998

In this paper, we suggest a optimal design method of Fuzzy-Neural Networks model for complex and nonlinear systems. FNNs have the stucture of fusion of both fuzzy inference with linguistic variables and Neural Networks. The network structure uses the simpified inference as fuzzy inference system and the BP algorithm as learning procedure. And we use a clustering algorithm to find initial parameters of membership function. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance index, we use the time series data for gas furnace and the sewage treatment process.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1634-1640
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• 2017

The study aims to distinguish hemiplegic gait and normal gait using simple wearable device and classification algorithm. Thus, we developed a wearable system equipped three axis accelerometer and three axis gyroscope. The developed wearable system was verified by clinical experiment. In experiment, twenty one normal subjects and twenty one patients undergoing stroke treatment were participated. Based on the measured inertial signal, a random forest algorithm was used to classify hemiplegic gait. Four-fold cross validation was applied to ensure the reliability of the results. To select optimal attributes, we applied the forward search algorithm with 10 times of repetition, then selected five most frequently attributes were chosen as a final attribute. The results of this study showed that 95.2% of accuracy in hemiplegic gait and normal gait classification and 77.4% of accuracy in hemiplegic-side and normal gait classification.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.293-299
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• 1996

The breakdown of machines lead to the lateness of parts and the change of schedules. Its treatment is very important problem in the shop floor control system. In this study, we present an algorithm minimize the lateness, earliness and change of schedule by controlling machining speed of available machines. Production time and production cost required to manufacture a piece of product are usually expressed as a unimodal convex fuction with respect to machining speed, and each has its minimal point at the minimum time speed or the minimum cost speed, and a speed range between these two speeds is called 'efficiency speed range'. Therefore, the algorithm determines the machining speed in the efficiency speed range. An example is demonstrated to explain the algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.108-116
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• 2009

In this paper, we develop an ELM(Extreme Learning Machine) based short-tenn water demand prediction algorithm which solves overfitting problem of MLP(Multi Layer Perceptron) and has quick training time. To show effectiveness of proposed method, we analyzed time series data collected in A water treatment plant at Chung-Nam province during $2007{\sim}2008$ years and used the selected data for the verification of developed algorithm. According to the experimental results, MLP model showed 5.82[%], but the proposed ELM based model showed 5.61[%] with respect to MAPE, respectively. Also, MLP model needed 7.57s training time, but ELM based model was 0.09s. Therefore, the proposed ELM based short-term water demand prediction model can be used to operate the water treatment plant effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.199-208
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• 2014

At present, the effect of oriental treatment system is proved in the west and using the data of tongue and pulse of body, the doctor can decide the patient's body state without Xray and CT data of large machines. In this paper, the patient's medical data is transmitted to the doctor and the real time decision algorithm is developed and so the doctor can decide the medical treatments. Using the mobile phone, the pulse data and bio data can be sent to the doctor and therefore the patients, who can't care in real time, can be treated in real time in the impossible medical treatment areas. Therefore in this paper, the oriental medical treatment system algorithm and artificial intelligence electrical needle simulation are processed for real time and checked and treated, so anyone can decide patient's state using mobile phone.

• Archives of Plastic Surgery
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• v.44 no.1
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• pp.59-64
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• 2017

Background Silicone implants are frequently used in augmentation rhinoplasty in Asians. A common complication of silicone augmentation rhinoplasty is capsular contracture. This is similar to the capsular contracture after augmentation mammoplasty, but a classification for secondary contracture after augmentation rhinoplasty with silicone implants has not yet been established, and treatment algorithms by grade or severity have yet to be developed. Methods Photographs of 695 patients who underwent augmentation rhinoplasty with a silicone implant from May 2001 to May 2015 were analyzed. The mean observation period was 11.4 months. Of the patients, 81 were male and 614 were female, with a mean age of 35.9 years. Grades were assigned according to postoperative appearance. Grade I was a natural appearance, as if an implant had not been inserted. Grade II was an unnatural lateral margin of the implant. Clearly identifiable implant deviation was classified as grade III, and short nose deformation was grade IV. Results Grade I outcomes were found in 498 patients (71.7%), grade II outcomes in 101 (14.5%), grade III outcomes in 75 (10.8%), and grade IV outcomes in 21 patients (3.0%). Revision surgery was indicated for the 13.8% of all patients who had grade III or IV outcomes. Conclusions It is important to clinically classify the deformations due to secondary contracture after surgery and to establish treatment algorithms to improve scientific communication among rhinoplasty surgeons. In this study, we suggest guidelines for the clinical classification of secondary capsular contracture after augmentation rhinoplasty, and also propose a treatment algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.62-68
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• 2022

Due to medical and economic development, various treatment methods are being studied to restore or maintain beautiful and healthy teeth. In particular, interest in aesthetic treatment procedures such as prosthetic treatment and whitening to restore tooth loss is increasing. One of the important things in the field of prosthetics and esthetic treatment is to determine the correct color of teeth because harmony with natural teeth is an important factor in determining the perfection of esthetic prostheses. This study is about the development of a colorimetry application for tooth colorimetry using a smartphone camera. The colorimetry application UI was designed, the colorimetry algorithm was derived and the application was implemented, and the validity of the application was verified through testing the implemented application.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1279-1288
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• 2021

Objective: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. Materials and Methods: This retrospective study included patients who underwent transarterial radioembolization for HCC followed by hepatic surgery between January 2011 and December 2019. The resected lesions were determined to have either complete (100%) or incomplete (< 100%) necrosis based on histopathology. Three radiologists independently reviewed the CT or MR images of pre- and post-treatment lesions and assigned categories based on the LI-RADS version 2018 and the TRA, respectively. Diagnostic performances of LI-RADS treatment response (LR-TR) viable and nonviable categories were assessed for each reader, using histopathology from hepatic surgeries as a reference standard. Inter-reader agreements were evaluated using Fleiss κ. Results: A total of 27 patients (mean age ± standard deviation, 55.9 ± 9.1 years; 24 male) with 34 lesions (15 with complete necrosis and 19 with incomplete necrosis on histopathology) were included. To predict complete necrosis, the LR-TR nonviable category had a sensitivity of 73.3-80.0% and a specificity of 78.9-89.5%. For predicting incomplete necrosis, the LR-TR viable category had a sensitivity of 73.7-79.0% and a specificity of 93.3-100%. Five (14.7%) of 34 treated lesions were categorized as LR-TR equivocal by consensus, with two of the five lesions demonstrating incomplete necrosis. Interreader agreement for the LR-TR category was 0.81 (95% confidence interval: 0.66-0.96). Conclusion: The LI-RADS version 2018 TRA can be used to predict the histopathologic viability of HCCs treated with transarterial radioembolization.

• Journal of Radiation Protection and Research
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• v.28 no.1
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• pp.59-63
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• 2003

Purpose : Measurement of transmission dose is useful for in vivo dosimetry of QA purpose. The objective of this study is to develope an algorithm for estimation of tumor dose using measured transmission dose for open radiation field. Materials and Methods : Transmission dose was measured with various field size (FS), phantom thickness (Tp), and phantom chamber distance (PCD) with a acrylic phantom for 6 MV and 10 MV X-ray Source to chamber distance (SCD) was set to 150 cm. Measurement was conducted with a 0.6 cc Farmer type ion chamber. Using measured data and regression analysis, an algorithm was developed for estimation of expected reading of transmission dose. Accuracy of the algorithm was tested with flat solid phantom with various settings. Results : The algorithm consisted of quadratic function of log(A/P) (where A/P is area-perimeter ratio) and tertiary function of PCD. The algorithm could estimate dose with very high accuracy for open square field, with errors within ${\pm}0.5%$. For elongated radiation field, the errors were limited to ${\pm}1.0%$. Conclusion : The developed algorithm can accurately estimate the transmission dose in open radiation fields with various treatment settings.