• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.72-77
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• 2017

This paper focuses on the development of a supporting S/W tool for the automated design of an automotive press trim die. To define the die design process based on automation, we analyze the press die design process of the current industry and group repetitive works in the 3D modeling process. The proposed system consists of two modules, namely the template models of the trim steel parts and UI function for their auto-positioning. Four kinds of template models are developed to adapt to various situations and the rules of the interaction formula which are used for checking and correcting the directions of the datum point, datum curve, datum plane are implemented to eliminate errors. The system was developed using CATIA Knowledgeware, CAA(CATIA SDK) and Visual C++, in order for it to function as a plug-in module of CATIA V5, which is one of the major 3D CAD systems in the manufacturing industry. The developed system was tested by applying it to various panels of current automobiles and the results showed that it reduces the time-cost by 74% compared to the traditional method.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.5-12
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• 2007

This paper gives a novel approach that can be represented an image efficiently with its region and shape information together. To do this, we introduced a region-centralized shape descriptor(RCSD) that the size of region only exists at a center point. RCSD consists of circles with three parameters, the distance and the angle between the tenter points, and the diameter, respectively We verified the RCSD parameters to have an information of shape. We can be proved this by reconstructing the shape from the given parameters and evaluated the difference between the its image and the original one. To get this image, we find the estimated points on the contour from the parameters, and connect them by using an interpolation. According to the evaluation, we obtained 88% performance for real images, and showed that it can be used efficiently for representing the binary images. Also we cu make RCSD parameters to be the normalized patterns to have an invariant of its scale or position, and expand them to improve the quality of the performance.

• Journal of Veterinary Clinics
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• v.31 no.4
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• pp.298-302
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• 2014

An 8-year-old castrated male domestic shorthair cat (Case 1) and 3-year-old castrated male Siamese cat (Case 2) was presented with acute paresis of the hindlimbs, constant open-mouth breathing, and hemoptysis. Heart murmur (Case 1) and gallop sound (Case 2) was ausculated on the left heart base. Radiographs revealed alveolar infiltration of the caudodorsal lung lobes with aerophagea in Case 1 and prominent cardiomegaly in Case 2. Marked concentric hypertrophy of the ventricular septum and free wall, and left atrial enlargement was detected through echocardiography in both cats. Based on the examinations including echocardiography, those cats were diagnosed as hypertropic cardiomyopathy. Abdominal ultrasound revealed echogenic material in the aortic trifurcation region, aortic thromboembolism (ATE). Although prognosis of those animals was guarded, interventional therapeutic approach through direct endovascular thrombolytic therapy was attempted. ATE was visualized through angiography; however dissolving the embolus using interventional thrombolytic approach was not successful due to the extensive thrombus.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.27-35
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• 2017

Human activity such as agriculture, industrial development and urban sprawl has been the major threat to wetlands ecosystem, which have caused the greatest losses of coastal wetlands. The Garorim bay provides one of the most important wetland habitate and Ministry of Oceans and Fisheries designated Garorim bay to marine ecosystem protected area in July 2016. The purpose of this research is to analysis the spatial pattern of Garorim bay using Landsat 5 (TM), Landsat 7 (ETM+), Landsat 8 (OLI & TIRS). The surface temperature and NDVI of Garorim bay were processed with spatial analysis method and time series analysis were applied to 25 years Landsat satellite 19 images. The results of time series distribution map compared with the several wetland habitate on remotely sensed images. Landsat images showed the change area of wetland vegetation distribution from 1988 to 2014. The southern part habitate of Garorim bay have been changed with vegetation patterns on coastal wetland which were covered with tidal flat.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.105-112
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• 2010

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.291-296
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• 2014

Inserting a $SiO_2$ layer underneath the p-pad electrode as the current blocking layer (CBL) structure and extending p-metal finger patterns, the GaN LEDs using an indium-tin-oxide (ITO) layer show the improved light output intensity, resulting from better current spreading and reduced light loss on the surface of p-pad metal. The LEDs with an oxide layer of $100{\mu}m$-pad-width and $6{\mu}m$-finger-width have better light output intensities than those with an oxide layer of $105{\mu}m$-pad-width and $12{\mu}m$-finger-width. Using the ATLAS device simulator from Silvaco Corporation, the current density distributions on the active layer in CBL LEDs have been investigated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.1-10
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• 2010

Mapping virtual process topology to physical processor topology is one of the most important design issues in parallel programming. However, the mapping problem is complicated due to the topology irregularity and routing complexity. This paper proposes a new process mapping scheme called adjacency-based mapping (AM) for irregular cluster systems assuming that the two-dimensional mesh process topology is specified as an interprocess communication pattern. The cluster systems have been studied and developed for many years since they provide high interconnection flexibility, scalability, and expandability which are not attainable in traditional regular networks. The proposed AM tries to map neighboring processes in virtual process topology to adjacent processors in physical processor topology. Simulation study shows that the proposed AM results in better mapping quality and shorter interprocess latency compared to the conventional approaches.

• Journal of the Korean Geographical Society
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• v.32 no.2
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• pp.197-215
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• 1997

The purpose of this study is to show practices of teaching method based on the type of knowledge in geography education. The results of examining the type of knowledge according to the five themes in guidelines for geographic education in america are as follows: the empirical-analytic knowledge-centered contents are suited for designing concepts inquiry-centered teaching. The historical-hermeneutic knowledge-centered contents are suited for designing problem solving-centered teaching. The critical knowledge-centered contents are suited for designing decision-making-centered teaching. In this shsdy, 1 emphasized teaching method based on the type of knowledge in Ceographv Education according to the responses of students and academic achievement. However, in practice l propose that teachers construct their lesson plans according to their various spheres of interest.

• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.72-86
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• 2013

Industrial agglomeration is an old theme in economic geography and many studies have been devoted to this topic. But only few have empirically looked at the time trend of industrial agglomeration. This study measured agglomeration of U.S. industries over last 29 years and measurement results indicated that industrial clustering has occurred during the study period in all study industries without a common time trend shared amongst the study industries. The agglomeration levels then were plugged in to investigate causalities, i.e. causal relations, around industrial agglomeration. Three variables were selected to see causal relations with agglomeration levels based on literatures, and our focus was given to the causality between transport network and agglomeration. Causal relation from transport to agglomeration was found in various industries and this supports the argument that the development of transportation influences industrial agglomeration. At the same time inverse and bi-directional causalities were also revealed implying more complex relationship between these two.