• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.1-8
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• 2004

According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.552-560
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• 2021

With the recent development of the art distribution system, interest in art investment is increasing rather than seeing art as an object of aesthetic utility. Unlike stocks and bonds, the price of artworks has a heterogeneous characteristic that is determined by reflecting both objective and subjective factors, so the uncertainty in price prediction is high. In this study, we used LSTM Recurrent Neural Network deep learning model to predict the auction winning price by inputting the artist, physical and sales charateristics of the Korean artist. According to the result, the RMSE value, which explains the difference between the predicted and actual price by model, was 0.064. Painter Lee Dae Won had the highest predictive power, and Lee Joong Seop had the lowest. The results suggest the art market becomes more active as investment goods and demand for auction winning price increases.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• Smart Media Journal
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• v.10 no.4
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• pp.45-54
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• 2021

The skin is the body's first line of defense against external infection. When a skin disease strikes, the skin's protective role is compromised, necessitating quick diagnosis and treatment. Recently, as artificial intelligence has advanced, research for technical applications has been done in a variety of sectors, including dermatology, to reduce the rate of misdiagnosis and obtain quick treatment using artificial intelligence. Although previous studies have diagnosed skin diseases with low incidence, this paper proposes a method to classify common illnesses such as warts and corns using a convolutional neural network. The data set used consists of 3 classes and 2,515 images, but there is a problem of lack of training data and class imbalance. We analyzed the performance using a deep metric loss function and a cross-entropy loss function to train the model. When comparing that in terms of accuracy, recall, F1 score, and accuracy, the former performed better.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1152-1157
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• 2023

Common carotid artery occlusion (CCAO) is a very rare disorder that has rarely been studied. CCAO causes several neurological symptoms but can sometimes be asymptomatic due to the development of various anastomoses. Herein, we report the case of a 70-year-old male patient diagnosed with asymptomatic CCAO due to anastomotic flow. The patient underwent transfemoral cerebral angiography (TFCA) and was found to have CCAO with two collateral pathways, including an occipital artery-vertebral artery anastomosis. We emphasize the importance of TFCA when CCAO is suspected and review the types and anastomotic pathways of CCAO.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.145-157
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• 2004

The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

• The Journal of Korean Academy of Sensory Integration
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• v.7 no.1
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• pp.27-36
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• 2009

Introduction : Occupational therapists commonly use clinical observation to assess neuromuscular function witch is a fundamental component of sensory integration function. Clinical Observation of Motor and Postural Skills (COMPS) is a standardized assessment with seven items and used to screen if a child's problem is due to neuromuscular and sensory integration system. However, developmental standard of the test need to be validated with Korean children. Objective : This study is purposed to propose developmental standard of the COMPS for Korean children. Method : Seven to nine years old students (76 male and 70 female) participated in this study. In order to find out any difference by gender and age, the data was analyzed using t-test and ANOVA. Results : There is no significant difference by gender for all other items except Prone Extension Position (PEP). There is significant difference between children who are 7 years old and those who are 9 years old for Slow Motion(SM), Finger-Nose Touching (FNT), Asymmetrical Tonic Neck Reflex (ATNR), Supine Flexion(SF). There is also significant difference between those who are 8 years old and 9 years old for SM, FNT, ATNR. However, there is no significant difference between those who are 7 years and 8 years old. Conclusions : This study examines any difference in neuromuscular characteristics by age among school-aged children, based on the COMPS. The result of this study will provide a good evidence to establish developmental standard of COMPS for Korean children. It issuggested to continue further standardization work of the COMPS in order to establish a developmental standard for Korean children.

• Korean Journal of Cognitive Science
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• v.26 no.1
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• pp.53-67
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• 2015

Metacognitive monitoring refers to high dimensional cognitive activities. Understanding one's own cognitive processes accurately can make effective controls for their performance. Brain area related with metacognition is PFC which is completed the order of late and it can be inferred that monitoring abilities is developing during late adolescent. In this study, we explored the developmental difference in monitoring accuracy between high school students and college students using by measuring JOL(Judgment of Learning). Participants was asked that they study Spanish-Korean word pairs and judge their future performance of memory. In the result, people in both groups thought that they could remember word pairs better than their actual performance. Absolute bias scores which mean the degree to predict their performance apart from true scores showed the interaction between subject groups and task difficulty. Specifically, people judged their learning state quite accurately in easy task condition. However, in difficult task condition, both groups showed inaccuracy for predicting their learning and the magnitude of the degree was bigger in the group of high school students.

• The Journal of Korean Orthopaedic Ultrasound Society
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• v.5 no.2
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• pp.61-65
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• 2012

Purpose: The aim of this study was to evaluate the effectiveness of ultrasound-guide steroid injection according to Morton's neuroma size. Materials and Methods: From October 2008 to September 2011, 17 patients (23 cases) diagnosed with Morton's neuroma were investigated. All cases were female and mean age was 52.6 years old. Neuroma were measured by the horizontal and longitudinal length of the mass and underwent ultrasound-guided steroid (5 mg dexamethasone) injection. The efficacy of the injection was determined by Visual Analogue Scale pain score and patient satisfaction(subdivided 4 group-much improved, improved, not improved, aggrevation) Results: 7 of 23(30.4%) cases showed much improved and improved satisfaction and mean longitudinal and horizontal length were $0.71{\pm}0.39cm$ and $0.47{\pm}0.24cm$, respectively. 16 of 23(69.6%) cases showed not improved and aggrevation satisfaction and mean longitudinal and horizontal length were $0.83{\pm}0.42cm$ and $0.54{\pm}0.14cm$, repectively. There was a significant difference in VAS and patient satisfaction in case longitudinal and horizontal length were smaller than 0.5 cm and 0.4 cm. (p<0.05) Conclusion: The ultrasonography is a important modality in diagnosis and treatment of morton's neuroma. Ultrasound-guide steroid injection is effective in case longitudinal and horizontal length were smaller than 0.5 cm and 0.4 cm, respectively.