• Tunnel and Underground Space
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• v.22 no.6
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• pp.412-428
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• 2012

To achieve mine development, a large amount of data concerned with the geological structure and the ore body had to be investigated and collected through geological survey, drilling and geophysical explorations. In most previous cases, however, the data were usually analyzed two dimensionally and those results showed some limits because of their 2D presentation. Those 2D maps such as geological plane sections or longitudinal sections cause lots of difficulties in understanding the complex geological structure or the feature of ore body in a spatial way. In this study, research area was set on the abandoned Yangyang iron mine in Korea and the Sugaeng ore body within the mine was selected as the research target to design a mine haulage system for reopening. A 3D mine model of this area was tried to be constructed using a 3D modelling software, GEMS. An accurate 3D model including the ore body, the geological structure, the old underground mine drifts and the new mine drifts was constructed under the purpose of reopening of the abandoned iron mine. Especially, mine design for trackless haulage system was conducted. New inclines and drifts were planned and modelled 3 dimensionally considering the utilization of old drifts and shaft. In addition to the 3D modelling, geostatistical technique was adopted to generate a spatial distribution of the ore grade and the rock physical properties. 3D model would be able to contribute in solving problems such as evaluating ore reserves, planning the mine development and additional explorations and changing the development plans, etc.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.03a
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• pp.79-88
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• 2008

Since the hydraulic fracturing field testing method was introduced first to Korean geotechnical engineers in 1994, there have been lots of progresses in a hardware system as well as an interpretation tool. The hydrofracturing system of first generation was the pipe-line type, so it was not easy to handle. It had been modified to a wire-line system at their second generation. It was more compact one but it also needed an additional air-compressor. Our current system is much more compact and operated by all-in-one system, so it doesn't need an additional air-compressor. With a progress in a hardware system, the software for analyzing the in-situ stress regime has also been progressed. For example, the shut-in pressure, which is the most ambiguous parameter to be obtained from hydrofracturing pressure curves, can now be acquired automatically from the various methods. While the hardware and software for hydrofracturing tests are being developed during the last decade, the author could accumulate the field test results which can cover the almost whole area of South Korea. Currently these field data are used widely in a feasibility study or a preliminary design step for tunnel construction in Korea. Regarding the difficulties in a site selection and a test performance for the in-situ stress measurement at an off-shore area, the in-situ stress regime obtained from the field experiences in the land area can be used indirectly for the design of a sub-sea tunnel. From the hydrofracturing stress measurements, the trend of magnitude and direction of in-situ stress field was shown identically with the geological information in Korea.

• Journal of radiological science and technology
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• v.40 no.1
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• pp.19-25
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• 2017

The aim of this study was to evaluate Magnetic Resonance Imaging safety by measuring the translational attraction, torque and susceptibility artifact for Bone-Anchored Hearing Aid (BAHA) implant at 1.5 T and 3.0 T MRI by standard criteria. In vitro assessment tools were made of acrylic-resin by American Society for Testing and Materials (ASTM) F2052-06 and F2119-07 standard. Translational attraction of BAHA implant was measured by the maximum deflection angle at 96 cm position, where the magnetically induced deflection was the greatest. The torque was assessed by the qualitative criteria of evaluating the alignment and rotation pattern, when the BAHA implant was positioned on a line with $45^{\circ}$ intervals inside the circular container in the center of the bore. The susceptibility artifact images were obtained using the hanged test tool, which was filled with $CuSO_4$ solution. And then the artifact size was measured using Susceptibility A rtifact Measurement (SA M) software. In results, the translational attraction was 0 mm at both 1.5 T and 3.0 T and the torque was 0(no torque) at 1.5 T, and +1(mild torque) at 3.0 T. The size of susceptibility artifacts was between 13.20 mm and 38.91 mm. Therefore, The BAHA implant was safe for the patient in clinical MR environment.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.211-224
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• 2002

As system become larger and more complex, it is important to correctly analyze and specify user's requirements. Use case modeling is widely used in Object-Oriented Analysis and Design(OOAD) and Component-Based Development(CBD). It is useful to mitigate the complexity of the requirements analysis. However, use cases are difficult to be structured, to explicitly represent non-functional requirements, and to analyze what is affected by changes of use cases. To alleviate these problems, we propose scenario-based goal-oriented approach for use case modeling. The approach is to apply goal-oriented analysis method to use case model. Since goal-oriented analysis method is not systematic and heuristics is considerably involved, we adopted scenarios as the basis for the goal extraction. The proposed method is applied to City Bus Information Subsystem(CBIS) in Intelligent Transport Systems(ITS) domain. The proposed approach helps software engineer to analyze what is affected by use case's changes and represent non-functional requirements.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.177-182
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• 2010

The flow of a universal system-level design methodology consists of system specification, system-level hardware/software partitioning, co-design, co-verification using virtual or physical prototype, and system integration. In the developing process of a hardware component in system, the design phase has been regarded as a phase consuming lots of time and cost. However, the verification phase in which functionality of the designed component is verified has recently been considered as a much important phase. In this paper, the implementation of a verification environment which is based on SystemC infrastructure and verifies the functionality of a hardware component is described. The proposed verification system uses SystemC user-defined channel as communication interface between variables of SystemC module and registers of Verilog module. The functional verification of an UART is performed on the proposed verification system. SystemC provides class library for hardware modeling and has an advantage of being able to design a system consisting hardware and software in higher abstraction level than register transfer level. Source codes of SystemC modules are reusable with a minor adaptation on verifying functionality of another hardware component.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.1 s.9
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• pp.147-157
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• 1997

A national program for GIS Training had been established by a feasibility study which was performed during the period of from July, 1995 through April, 1996 initiated by Ministry of Science and Technology (MOST). Systems Engineering Research Institute (SERI), one of government-supported institutes in the fields of software development, have taken in charge of Korean GIS training program with emphases on short courses since July, 1996. To distinguish these national programs from those of major commercial GIS software vendor, GIS training programs by executing staffs within SERE have been established with the basis of its own educational paradigm; therefore, they was composed of several specific training curricular developed by executing staffs. In this paper, the practical aspects during execution and progress of these programs are described, and all courses named after decision maker course, GIS manager course, and user course in the first year of GIS training program are evaluated with questionnaire result riven to the trainees. As results, the satisfaction-rate after the decision maker, the GIS manager, and the user course is 84.8%, 81.2%, and 66.7% respectively These whole results are shown as more affirmative ones than expected, and each result, as a kind of feedback of this executing program, plays an important role to flourish Korean GIS training project in future.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.841-856
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• 2008

The priority of requirement is important because the priority is a critical activity of release plan especially in software development which has an open market customer. Also, it is important for stakeholders to select a method and aspects to prioritize requirements. The selection is based on the organizational experience of a priority process, the process model of the product, goals and a type of products, and dependencies between requirements. But, the current researches considered only static dependency between requirements and did not suggest a systematic priority process. In addition, the current researches only suggest limited aspects to prioritize requirements, such as cost and value. Therefore, this paper proposes an adjustable priority process based on a priority model to select a method and aspects for the suitable priority for product and organization. Especially, this paper enhances the completeness of a release plan by a definition of static and dynamic dependency types between requirements. This paper suggests a priority model, which considers the dependencies between requirement and various viewpoint of software development. Based on the priority model, the paper suggests a systematic priority process to promote reasonable decisions to the priority and release plan of requirement.

• Journal of Broadcast Engineering
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• v.6 no.3
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• pp.246-259
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• 2001

Due to recent rapid deployment of Internet streaming service and digital broadcasting service, the issue of how to efficiently support streaming workload in so called "Internet Home Appliance" receives prime interests from industry as well as academia. The underlying dilemma is that it may not be feasible to put cutting edge CPU, boards, disks and other peripherals into that type of device. The primary reason is its cost. Usually, Internet Home Appliances has its dedicated usage, e.g. Internet Radio, and thus it does not require high-end CPU nor high-end Va subsystem. The same reasoning applies to I/O subsystem. In Internet Home Appliances dedicated to handle compressed moving picture, it is not equipped with high end SCSI disk with fast rotational speed. Thus, it is mandatory to devise elaborate software algorithm to exploit the available hardware resources and maximize the efficiency of the system. This paper presents our experiences in the design and implementation of a new multimedia file system which can efficiently deliver the required disk bandwidth for a periodic I/O workload. We have implemented the file system on the Linux operating system, and examined itsperformance under streaming I/O workload. The results of the study show that the proposed file system exhibits superior performance than the Linux Ext2 file system under streaming I/O workload. The result of this work not only contribute to advance the state f art file system technology for multimedia streaming but also put forth the software which is readily available and can be deployed. deployed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.521-530
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• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.25-32
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• 2020

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.