• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.489-496
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• 2016

Thousands of pathological images are produced daily per hospital and they are stored and managed by a pathology information system (PIS). Since image edge detection is one of fundamental analysis tools for pathological images, many researches are targeted to improve accuracy and performance of image edge detection algorithm of HIS. In this paper, we propose a novel image edge detection method. It is based on Canny algorithm with adaptive threshold configuration. It also uses a dividing ruler to configure the two threshold instead of whole image to improve the detection ratio of ruler itself. To verify the effectiveness of our proposed method, we conducted empirical experiments with real pathological images(randomly selected image group, image group that was unable to detect by conventional methods, and added noise image group). The results shows that our proposed method outperforms and better detects compare to the conventional method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.4
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• pp.267-271
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• 2018

A high directivity TIR (total internal reflection) lens in the UV-A region was designed using a silicone resin, and a UV light source module with a maximum irradiation density of $150mW/cm^2$ was fabricated. The beam angle of the TIR lens was designed to be $8.04^{\circ}$ and the maximum diameter of the TIR lens was Ø13.5. A silicone resin having a UV transmittance of 93% and a refractive index of 1.4 at a wavelength of 365 nm was used, and the lens was manufactured using an aluminum mold, from which silicone could be easily released. The module was fabricated in a metal printed circuit board of COB (chip on board) type using a $0.75{\times}0.75mm^2$ UV chip. A jig was used to adjust the focal length between lens and chip and to fix the position of the lens. The optical characteristics such as illumination distributions of the lens and module were designed using 'LightTools' optical simulation software. The heat dissipation system was designed to use a forced-air cooling method using a heat-sink and fan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.324-327
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• 2006

The person who gets a ALS(Amyotrophic Lateral Sclerosis) has language disability and physical disability together. A common first symptom is a painless weakness in a hand, foot, arm or leg, which occurs in more than half of all cases. Other early symptoms include muscle weakness of speech. In the early stage of this disease they can communicate with other persons, but it will become increasingly difficult. In our research we have designed and implemented communication tools for them. We have implemented Chunjiin(the Korean computer keyboard) at PDA(personal digital assistant). And we have also implemented software which is consisted of frequently used words.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1568-1574
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• 2009

One of the most difficult problems in user requirement engineering is the communication gap that exists between different end-users, stakeholders, and software engineers. Since scenarios allow different stakeholders to describe and review the problem in their own language instead of some abstract model, they are also a solution to the problem. We propose a progressive, iterative and interleaved process of using scenario at different requirement engineering stages including elicitation, analysis and validation. This process model has been applied to our TRES System. In our proposed system, we combine prototype, scenarios and use cases in a single and comprehensive framework to avoid most of the shortcomings in other tools. Our system is an XML-based system for scenario-driven requirement engineering. Within the TRES system, scenarios are stories capture information about users and their tasks, including the context of use. In our TRES system, scenarios are stored in XML-based database and described using XML notation.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.459-466
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• 2002

Modern embedded system employs a hybrid architecture which contains a general micro processor and reconfigurable devices such as FPGAS to retain flexibility and to meet timing constraints. It is a hard and important problem for embedded system designers to explore and find a right system configuration, which is known as design space exploration (DSE). With DES, it is possible to predict a final system configuration during the design phase before physical implementation. In this paper, we implement a timing analysis simulator for a DSE on a hybrid embedded system. The simulator, integrating exiting timing analysis tools for hardware and software, is designed by extending Y-chart approach, which allows quantitative performance analysis by varying design parameters. This timing analysis simulator is expected to reduce design time and costs and be used as a core module of a DSE for a hybrid embedded system.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.587-595
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• 2015

Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of central processing unit (CPU) cores. In order to support such large-scale scientific workflows, large-capacity cluster systems such as supercomputers are widely used. However, as users require a diversity of software packages and configurations, a system administrator has some trouble in making a service environment in real time. In this paper, we present a container-based cluster management platform and introduce an implementation case to minimize performance reduction and dynamically provide a distributed computing environment desired by users. This paper offers the following contributions. First, a container-based virtualization technology is assimilated with a resource and job management system to expand applicability to support large-scale scientific workflows. Second, an implementation case in which docker and HTCondor are interlocked is introduced. Lastly, docker and native performance comparison results using two widely known benchmark tools and Monte-Carlo simulation implemented using various programming languages are presented.

• Journal of Korean Neurosurgical Society
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• v.41 no.6
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• pp.371-376
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• 2007

Objective : The aim of this study was to investigate the usefulness of diffusion-weighted imaging [DWI] and apparent diffusion coefficiency [ADC] in distinguishing brain abscesses from cystic or necrotic brain tumors, which are difficult to be differentiated by conventional magnetic resonance imaging techniques. Methods : Seven patients with brain abscesses and ten patients with cystic brain tumors were studied from September 2003 to October 2005. Abscess, subdural empyema and ventriculitis were categorized to the abscess group and cystic or necrotic brain gliomas or metastatic brain tumors into the tumor group. Preoperative magnetic resonance images were performed in all patients and diffusion-weighted images and apparent diffusion coefficiency values of lesions were calculated directly from software of 1.5 tesla MRI [General Electrics, USA]. The ratio of the ADC of the lesion to contralateral regional ADC was also measured [relative ADC, rADC]. Results : The average ADC value of pyogenic abscesses group was $0.82+/-0.14{\times}10^{-3}\;[mean+/-S.D.]\;mm^2/s$ and mean rADC was 0.75. Cystic or necrotic areas had high ADC values [$2.49+/-0.79{\times}10^{-3}\;mm^2/s$, mean rADC=2.14]. ADC and rADC values of abscesses group showed about three times lower values than those of cystic or necrotic tumor group. Conclusion : This study results based on numerical comparison of signal intensities and quantitative analysis to distinguish between brain abscess and cystic or necrotic tumor, DWI and ADC mapping are thought to be very useful diagnostic tools.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.479-486
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• 2017

Recently, GPGPU has been able to increase the degradation of computer performance, and it is now possible to run physically based real-time simulations on PCs that require high computational complexity. Physical calculations applied in physics simulation can be performed by parallel processing, and can be efficiently performed using parallel computation using Compute shader recently supported by OpenGL 4.3 and Unity 4.0. In this paper, we measure and compare the number of performance in real - time physics simulation in OpenGL running on various platforms and Unity, a content creation tool supporting various platforms. Particle simulation experiments show that particle simulation using Unity performs faster than 136.04%. It is expected that it will be able to select better development tools for future multi - platform support.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.232-249
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• 1998

The first Korean remote sensing satellite, Korea Multi-Purpose Satellite (KOMPSAT-1), is going to be launched in 1999. This will carry a 7m resolution Electro-Optical Camera (EOC) for earth observation. The primary mission of the KOMPSAT-1 is to acquire stereo imagery over the Korean peninsular for the generation of 1:25,000 scale cartographic maps. For this mission, research is being carried out to assess the possibilities of automated or semi-automated mapping of EOC data and to develop, if necessary, such enabling tools. This paper discusses the issue of automated digital elevation model (DEM) generation from EOC data and identifies some important aspects in developing a DEM generation system from EOC data. This paper also presents the current status of the development work for such a system. The development work will be described in three pares of sensor modelling, stereo matching and DEM interpolation. The performance of the system is shown with a SPOT stereo pair. A DEM generated from commercial software is also presented for comparison. The proposed system seems to generate promising results.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.117-124
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• 2021

In this paper, we propose CANVAS (Creative ANalytics enVironment And System), an analytics system of the National Research Data Platform (DataON). CANVAS is a personalized analytics cloud service for researchers who need computing resources and tools for research data analysis. CANVAS is designed in consideration of scalability based on micro-services architecture and was built on top of open-source software such as eGovernment Standard framework (Spring framework), Kubernetes, and JupyterLab. The built system provides personalized analytics environments to multiple users, enabling high-speed and large-capacity analysis by utilizing high-performance cloud infrastructure (CPU/GPU). More specifically, modeling and processing data is possible in JupyterLab or GUI workflow environment. Since CANVAS shares data with DataON, the research data registered by users or downloaded data can be directly processed in the CANVAS. As a result, CANVAS enhances the convenience of data analysis for users in DataON and contributes to the sharing and utilization of research data.