• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.232-239
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• 2012

The purpose of this study was to investigate the relationship among functional evaluation systems, the Selective Motor Control Scale (SMC scale), the Gross Motor Function Classification System (GMFCS), the Gross Motor Function Measure (GMFM) and Activities of daily living in children with spastic cerebral palsy and to provide the foundation data about SMC scle for evaluation system of abilities of selective motor control in children with spastic cerebral palsy. For this, sixty eight children with spastic cerebral palsy were participated in this study. The children were evaluated by using the SMC scale for their selective motor control ability and by using the GMFCS and GMFM for their gross motor function. The activities of daily living were assessed by using the Functional Independence Measure of Children (WeeFIM). There were a significant correlation between the SMC scale and the GMFCS (r = -.485, p < .05). The good correlation between the SMC scale and GMFM was found (r = .482, p < .05). The activities of daily living were not a significant correlation with SMC scale (r = .019, p > .05). The SMC scale in practice will provide usefulness for assessment of abilities of selective motor control in children with spastic cerebral palsy.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.17-26
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• 2017

Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

• Journal of The Korean Astronomical Society
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• v.45 no.2
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• pp.31-38
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• 2012

In this study we apply Support Vector Machine (SVM) to the prediction of geo-effective halo coronal mass ejections (CMEs). The SVM, which is one of machine learning algorithms, is used for the purpose of classification and regression analysis. We use halo and partial halo CMEs from January 1996 to April 2010 in the SOHO/LASCO CME Catalog for training and prediction. And we also use their associated X-ray flare classes to identify front-side halo CMEs (stronger than B1 class), and the Dst index to determine geo-effective halo CMEs (stronger than -50 nT). The combinations of the speed and the angular width of CMEs, and their associated X-ray classes are used for input features of the SVM. We make an attempt to find the best model by using cross-validation which is processed by changing kernel functions of the SVM and their parameters. As a result we obtain statistical parameters for the best model by using the speed of CME and its associated X-ray flare class as input features of the SVM: Accuracy=0.66, PODy=0.76, PODn=0.49, FAR=0.72, Bias=1.06, CSI=0.59, TSS=0.25. The performance of the statistical parameters by applying the SVM is much better than those from the simple classifications based on constant classifiers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1219-1226
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• 2010

It is necessary to implementation of system contain intelligent decision making algorithm because discriminant and prediction system for Red Tide is insufficient development and the study of red tide are focused for the investigation of chemical and biological causing. In this paper, we designed inference system using case based reasoning method and implemented knowledge base that case for Red Tide. We used K-Nearest Neighbor algorithm for recommend best similar case and input 375 EA by case for Red Tide case base. As a result, conducted 10-fold cross verification for minimal impact from learning data and acquired confidence, we obtained about 84.2% average accuracy for Red Tide case and the best performance results in case by number of similarity classification k is 5. And, we implemented Red Tide monitoring system using inference result.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.155-162
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• 2008

The quality of the fruits is measured by a lot of parameters. The grader of the fruits to measure the size of them is using the rotation drum method. Therefore when we classify the size of the fruits, they will be damaged. Also the optical grader used for estimating the degree of the saccharinity will incur high cost for it. In the proposed system, to select the characteristics of the fruits, three cameras are used. Because the information such as the volume and the degree of the maturity is used to classify the fruits, the degree of the saccharinity can't be estimated itself, but the information such as the color and the damage of the fruits can be estimated. Therefore, because we don't need the digital image with high resolution, we can develop the grader system of the fruit with low cost. To evaluate the performance of the proposed system, we compared it with the sight estimation and then we classified the sample. The result shows the accuracy of 96.7%.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.11-18
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• 2008

Document clustering is an important method for document analysis and is used in many different information retrieval applications. This paper proposes a new document clustering model using the re-weighted term based NMF(non-negative matrix factorization) to cluster documents relevant to a user's requirement. The proposed model uses the re-weighted term by using user feedback to reduce the gap between the user's requirement for document classification and the document clusters by means of machine. The Proposed method can improve the quality of document clustering because the re-weighted terms. the semantic feature matrix and the semantic variable matrix, which is used in document clustering, can represent an inherent structure of document set more well. The experimental results demonstrate appling the proposed method to document clustering methods achieves better performance than documents clustering methods.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.143-151
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• 2006

This paper deals with the simulation model for design and operations of A-Mart logistic center for low temperature products. In developed simulation model, receiving docks, digital classification system (DCS), shipping docks, material handling devices and manual sorting stations are considered. Five types of cargo such as fruits, palletized fruits, delicatessen and fisheries, vegetables and refrigerated cargoes are considered. The simulation model and process animation are developed using the simulation package ARENA. Among various design and operation alternatives consisting of the number of workers of receiving dock, allocation of receiving docks by cargo types, DCS capacity, the number of folk-lift, the number of manual sorting operators and overall layout, the best alternatives of each subsystem are selected by simulation analysis. The major performance measures such as DCS throughput, utilization of operators at each station, receiving docks utilization and folk-lift utilization are considered for the alternative evaluation.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.209-217
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• 2016

Recently, the outdoor activities were increased in accordance with economic growth and improved quality of life. In addition, weather and outdoor activities are closely related. Currently, Outdoor Activities decisions are determined by the Korea Meteorological Administrator's forecasts and subjective experience. Therefore, we need the analysis method that can provide a basis for the decision on outdoor activities based on meteorological information. In this paper, we propose an algorithm that can analyze meteorological information to support decision-making outdoor activities. And the algorithm is based on the data mining. In addition, we have constructed a baseball game schedule with automatic weather system's observation data in the training data. We verified the improved performance of the proposed algorithm.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.157-166
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• 2013

This paper proposes a non-intrusive speech quality estimation method considering the effects of packet loss to perceptual quality. Packet loss is a major reason of quality degradation in a packet based speech communications network, whose effects are different according to the input speech characteristics or the performance of the embedded packet loss concealment (PLC) algorithm. For the quality estimation system that involves packet loss effects, we first observe the packet loss of G.729 codec which is one of narrowband codec in VoIP system. In order to quantify the lost packet affects, we design a classification algorithm only using speech parameters of G.729 decoder. Then, the degradation values of each class are iteratively selected that maximizes the correlation with the degradation PESQ-LQ scores, and total quality degradation is modeled by the weighted sum. From analyzing the correlation measures, we obtained correlation values of 0.8950 for the intrusive model and 0.8911 for the non-intrusive method.

• Journal of Korean Neurosurgical Society
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• v.46 no.3
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• pp.245-251
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• 2009

Objective : The authors analyzed the effectiveness and therapeutic response of Novalis shaped beam radiosurgery for metastatic brain tumors, and the prognostic factors which influenced the outcome. Methods : We performed a retrospective analysis of 106 patients who underwent 159 treatments for 640 metastatic brain lesions between January 2000 and April 2008. The pathologies of the primary tumor were mainly lung (45.3%), breast (18.2%) and GI tract (13.2%). We classified the patients using Radiation Therapy Oncology Group Recursive Partitioning Analysis (RPA) and then analyzed the survival and prognostic factors according to the Kaplan Meier method and univariate analysis. Results : The overall median actuarial survival rate was 7.3 months from the time of first radiosurgery treatment while 1 and 2 year actuarial survival estimates were 31% and 14.4%, respectively. Median actuarial survival rates for RPA classes I, II, and III were 31.3 months, 7.5 months and 1.7 months, respectively. Patients' life spans, higher Karnofsky performance scores and age correlated closely with RPA classes. However, sex and the number of lesions were not found to be significantly associated with length of survival. Conclusion : This result suggests that Novalis radiosurgery can be a good treatment option for treatment of the patients with brain metastases.