• Journal of Korean Tunnelling and Underground Space Association
• /
• v.15 no.5
• /
• pp.505-522
• /
• 2013

Previously, a new concept of indexing methodology has been proposed for quantitative assessment of tunnel collapse hazard level at each tunnel face with respect to the given geological data, design condition and the corresponding construction activity (Shin et al, 2009a). In this paper, 'linear' model, in which weights of influence factors are invariable, and 'non-linear' model, in which weights of influence factors are variable, are taken into account with some examples. Then, the 'non-linear' model is validated by using 100 tunnel collapse cases. It appears that 'non-linear' model allows us to have adapted weight values of influence factors to characteristics of given tunnel site. In order to make a better understanding and help for an effective use of the system, a series of operating processes of the system are built up. Then, by following the processes, the system is applied to a real-life tunnel project in very weak and varying ground conditions. Through this approach, it would be quite apparent that the tunnel collapse hazard indices are determined by well interlinked consideration of face mapping data as well as design/construction data. The calculated indices seem to be in good agreement with available electric resistivity distribution and design/construction status. In addition, This approach could enhance effective usage of face mapping data and lead timely and well corresponding field reactions to situation of weak tunnel faces.

• The KIPS Transactions:PartD
• /
• v.17D no.4
• /
• pp.259-270
• /
• 2010

Information systems nowadays are heterogeneous and distributed which integrate the enterprise information by processes. They are also very complex, because they are linked together by processes. It aims to integrate the systems so that these systems work as one system. A process is a framework which contains all of the business activities in an enterprise, and has a lot of information which is needed for measuring performance. A process consists of activities, and an activity contains events which can be considered information sources. In most cases, it is very valuable to determine if a process is meaningful, but it is difficult because of the complexity in measuring performance, and also because finding relationships between business factors and events is not a simple problem. So it would reduce operation cost and allow efficient process execution if I could evaluate the process before it ends. In this paper we propose an event based process measurement model. First, we propose the concept of process performance measurement, and a model for selecting process and activity indexes from the events which are collected from information systems. Second, we propose at methodologies and data schema that can store and manage the selected process indexes, the mapping methods between indexes and events. Finally, we propose a process Performance measurement model using the collected events which gives users a valuable managerial information.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.10 no.1
• /
• pp.1-8
• /
• 2008

The concept of growing degree-days (GDD) is widely accepted as a tool to relate plant growth, development, and maturity to temperature. Information on GDD can be used to predict the yield and quality of several crops, flowering date of fruit trees, and insect activity related to agriculture and forestry. When GDD is expressed on a spatial basis, it helps identify the limits of geographical areas suitable for production of various crops and to evaluate areas agriculturally suitable for new or nonnative plants. The national digital climate maps (NDCM, the fine resolution, gridded climate data for climatological normal years) are not provided on a daily basis but on a monthly basis, prohibiting GDD calculation. We applied a widely used GDD estimation method based on monthly data to a part of the NDCM (for Hapcheon County) to produce the spatial GDD data for each month with three different base temperatures (0, 5, and $10^{\circ}C$). Synthetically generated daily temperatures from the NCDM were used to calculate GDD over the same area and the deviations were calculated for each month. The monthly-data based GDD was close to the reference GDD using daily data only for the case of base temperature $0^{\circ}C$. There was a consistent overestimation in GDD with other base temperatures. Hence, we estimated spatial GDD with base temperature $0^{\circ}C$ over the entire nation for the current (1971-2000, observed) and three future (2011-2040, 2041-2070, and 2071-2100, predicted) climatological normal years. Our estimation indicates that the annual GDD in Korea may increase by 38% in 2071-2100 compared with that in 1971-2000.

• Journal of the Society of Disaster Information
• /
• v.17 no.1
• /
• pp.176-183
• /
• 2021

Purpose: The introduction of smart factories that reflect the 4th industrial revolution technologies such as AI, IoT, and VR, has been actively promoted in Korea. However, in order to solve various problems arising from existing file-based operating systems, this research will focus on identifying and verifying non-file system-based data protection technology. Method: The research will measure security storage that cannot be identified or controlled by the operating system. How to activate secure storage based on the input of digital key values. Establish a control unit that provides input and output information based on BIOS activation. Observe non-file-type structure so that mapping behavior using second meta-data can be performed according to the activation of the secure storage. Result: First, the creation of non-file system-based secure storage's data input/output were found to match the hash function value of the sample data with the hash function value of the normal storage and data. Second, the data protection performance experiments in secure storage were compared to the hash function value of the original file with the hash function value of the secure storage after ransomware activity to verify data protection performance against malicious ransomware. Conclusion: Smart factory technology is a nationally promoted technology that is being introduced to the public and this research implemented and experimented on a new concept of data protection technology to protect crucial data within the information system. In order to protect sensitive data, implementation of non-file-type secure storage technology that is non-dependent on file system is highly recommended. This research has proven the security and safety of such technology and verified its purpose.