• Journal of Ship and Ocean Technology
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• v.1 no.1
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• pp.35-47
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• 1997

The consequences associated with ships running aground depend very much on the soil characteristics of the sea bed and the geometrical shape of the ship bow. The penetration into the sea bed depends on these factors and the penetration is an important factor for the ship motion because it influences the ship heave and pitch motions as well as the friction between the ship and the soil. In this paper a rational calculation model is presented for the sea bed soil reaction forces on the ship bottom. The model is based on the assumption that the penetration of the ship bow generates a flow of pore water through the grain skeleton of the soil. The flow is governed by Darcy\`s law and it is driven by the pressure of the pore water at the bow. In addition to this pore water pressure, the bow is subjected to the effective stresses in the grain skeleton at the bow surface. These stresses are determined by the theory of frictional soils in rupture. Frictional stresses on the bow surface are assumed to be related to the normal pressure by a simple Coulomb relation. The total soil reaction as a function of velocity and penetration is found by integration of normal pressure and frictional stresses over the surface of the bow. The analysis procedure is implemented in a computer program for time domain rigid body analysis of ships running aground and it is verified in the paper through a comparison of calculated stopping lengths, effective coefficients of friction, and sea bed penetrations with corresponding experimental results obtained by model tests as well as large, scale tests.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.211-217
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• 2011

Recent IT (information technology) environmental changes, such as emerging social network services or increasing user participation in multimedia environment, have made it necessary for e-learning systems to undergo changes in various ways. Metadata is an agreement for interoperability between different systems. The standardization of metadata for e-learning system has been driven by some domestic and international organizations, but applying diverse environmental changes into the design of e-learning metadata is in dire need. In this paper, we present a methodology for the analysis and design of modeling e-learning metadata and elicit the design requirements, on the basis of the metadata standard KEM 3.0, about the elements that are expected to be needed in future e-learning systems. Based on the requirements from the analysis, we present the three-layer model for classifying the requirements by the importance of metadata elements per Kana Model. An intelligent e-learning system is to be developed based on the proposed modeling design, which we hope to influence the development of an international standard in the future.

• Journal of Hydrogen and New Energy
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• v.24 no.4
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• pp.295-301
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• 2013

Long-term global energy-demand growth is expected to increase driven by strong energy-demand growth from developing countries. Fusion power offers the prospect of an almost inexhaustible source of energy for future generations, even though it also presents so far insurmountable scientific and engineering challenges. One of the challenges is safe handling of hydrogen isotopes. Metal hydrides such as depleted uranium hydride or ZrCo hydride are used as a storage medium for hydrogen isotopes reversibly. The metal hydrides bind with hydrogen very strongly. In this paper, we carried out a modeling and simulation work for absorption/desorption of hydrogen by ZrCo in a horizontal annulus cylinder bed. A comprehensive mathematical description of a metal hydride hydrogen storage vessel was developed. This model was calibrated against experimental data obtained from our experimental system containing ZrCo metal hydride. The model was capable of predicting the performance of the bed for not only both the storage and delivery processes but also heat transfer operations. This model should thus be very useful for the design and development of the next generation of metal hydride hydrogen isotope storage systems.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.578-586
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• 2005

Air mattress is now used widely to prevent the pressure ulcer by reducing the localized pressure peaks. The pressure control method based on the anthrophometric model of an air-cell mattress developed in this study is presented. The air-cell mattress has 18 cylindrical air cells made of porous material allowing air leakage. Even though the air leakage can contribute to reducing the development of pressure ulcer by lowering the pressure peak, temperature and humidity, the air pressure changes with time and the desired air-cell pressure has to be determined as an optimal value for each user. To select the desired air-cell pressure, we first divide the parts of the body into four sections such as head, trunk, hip, and leg. Then, the pressure of each section grouped with air-cells is calculated from the weight of each part estimated from the individual height and body weight. Air supply system for the air-cell mattress is implemented by using four electronic solenoid valves and an air compressor, and it is driven by a real-time microcontroller. We experimented with five subjects of the contact pressure on skin. The experimental results show that the proposed air-cell mattress is effective for the prevention of the pressure ulcer.

• Atmosphere
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• v.22 no.2
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.12
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• pp.1980-1991
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• 2010

This study proposes the O P E N Triad framework as a future set of tools and perspectives for individual members and institutes to further their professional and academic potential as well as prospect and vitalize the future of the Korean Clothing and Textiles discipline through a global perspective. The millennial generation desires On-demand, Personal, Engaging, and Networked (O P E N) experiences effecting cultural change for creative and influential interaction in transactions, communication, and education. O P E N Individuals offers a WebSphere model as a holistic learning system that has a synergizing value of education across academic courses, industries, and cultures. Through a digitalized and virtualized class, it complements relevant technologies already familiar to the student population. By employing environmental scanning approaches, the most influential and viable future global issues related to the clothing and textiles discipline are identified and dialogued within O P E N Institutes. For future clothing and textiles institutes, this scanning allows them to be open to new ideas, to focus on inter-engagements, to collaborate among individuals, to associate as a part of web of people, organizations, and ideas, to personalize an institutes curricula, and to dialogue generative knowledge. O P E N Industries reveals three dominant future issues that cross academia and industry, sustainability, supply chain management, and social networking. In-depth interviews with U.S. industry experts identified interdependent gaps in global consumer experience practices and suggested the following gaps as future research areas: a standardized business model to the entrepreneurial model, strategic management to a sustainable competitive advantage, standardized to differentiated products, services and operations, market segmentation to global consumer clusters, business-driven marketplaces to consumer-engaged marketspaces, and excellent services to optimal experience. This O P E N Triad framework empowers millennial students, universities, and industries to anticipate and prepare for a radically changing world.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5377-5383
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• 2015

Background: Participation is one of the major factors affecting the long-term success of population-based prostate cancer screening programs. The aim of this study was to explore strong factors linked to participation in prostate cancer screening among older Jordanian adults using the Health Belief Model (HBM). Materials and Methods: Data were obtained from Jordanian older adults, aged 40 years and over, who visited a comprehensive health care center within the Ministry of Health. A pilot test was conducted to investigate the internal consistency of the the Champion Health Belief Model Scale for prostate cancer screening and the clarity of survey questions. Sample characteristics and rates of participation in prostate cancer screening were examined using means and frequencies. Important factors associated with participation in prostate cancer screening were examined using bivariate correlation and multivariate logistic regression analysis. Results: About 13% of the respondents had adhered to prostate cancer screening guidelines over the previous decade. Four out of the seven HBM-driven factors (perceived susceptibility, benefits and barriers to PSA test, and health motivation) were statistically significant. Those with greater levels of susceptibility, benefits of PSA test and health motivation and lower levels of barriers to PSA testing were more likely to participate in prostate cancer screening. Family history, presence of urinary symptoms, age, and knowledge about prostate cancer significantly predicted the participation in prostate cancer screening. Conclusions: Health professionals should focus more on the four modifiable HBMrelated factors to encourage older adults to participate in prostate cancer screening. Intervention programs, which lower perceived barriers to PSA testing and increase susceptibility, benefits of PSA testing and health motivation, should be developed and implemented.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.115-120
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• 2015

The Testing Frontier Capability Assessment Model (TCAM) is based on ISO/IEC 9126, TMMi and TPI. Since ISO/IEC 9126, TMMi and TPI were made over 10 years ago, TCAM faces the problem that it can not assess and analyze the capability of small businesses that employ new software development methods or processes, for example Agile, TDD(Test Driven Development), App software, and Web Software. In this paper, a method to improve the problem is proposed. The paper is composed of the following sections: 1) ISO/IEC 9126, ISO/IEC 25010 and ISO/IEC/IEEE 29119 part 2 review 2) TCAM review 3) software product quality perspective comparison, and analysis between ISO/IEC 9126, ISO/IEC 25010 and TCAM 4) comparison, and analysis between ISO/IEC/IEEE 29119 part2 and TCAM and 5) proposal for the improvement of TCAM.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• The Plant Pathology Journal
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• v.36 no.1
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• pp.54-66
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• 2020

This study was conducted to evaluate usefulness of numerical weather prediction data generated by the Unified Model (UM) for plant disease forecast. Using the UM06- and UM18-predicted weather data, which were released at 0600 and 1800 Universal Time Coordinated (UTC), respectively, by the Korea Meteorological Administration (KMA), disease forecast on bacterial grain rot (BGR) of rice was examined as compared with the model output based on the automated weather stations (AWS)-observed weather data. We analyzed performance of BGRcast based on the UM-predicted and the AWS-observed daily minimum temperature and average relative humidity in 2014 and 2015 from 29 locations representing major rice growing areas in Korea using regression analysis and two-way contingency table analysis. Temporal changes in weather conduciveness at two locations in 2014 were also analyzed with regard to daily weather conduciveness (C_i) and the 20-day and 7-day moving averages of C_i for the inoculum build-up phase (C_inc) prior to the panicle emergence of rice plants and the infection phase (C_inf) during the heading stage of rice plants, respectively. Based on C_inc and C_inf, we were able to obtain the same disease warnings at all locations regardless of the sources of weather data. In conclusion, the numerical weather prediction data from KMA could be reliable to apply as input data for plant disease forecast models. Weather prediction data would facilitate applications of weather-driven disease models for better disease management. Crop growers would have better options for disease control including both protective and curative measures when weather prediction data are used for disease warning.