• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.633-640
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• 2005

Most existing methods for the footing settlement estimation are for either isolated or strip footings. No sufficient details are available for settlement calculation of footings with different shapes and multiple footing conditions, which are commonly adopted in actual construction projects. In this paper, estimation of footing settlements for various footing conditions of different shapes and multiple conditions is investigated based on Schmertmann's method with focus on values of the strain influence factor $I_z$. In order to examine the effect of multiple footing conditions, field plate load tests are performed in sands using single and double plates. 3D non-linear finite element analyses are also performed for various footing conditions with different footing shape and distance ratios. Results obtained in this study indicate that there are two significant components in the strain influence diagram that need to be taken into account for settlement estimation of rectangular and multiple footings: depth of $I_{zp}$ and depth of strain influence zone. Based on results from experimental and 3D non-linear finite element analyses, improved strain influence diagrams available for various footing conditions are proposed.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• Transactions of Materials Processing
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• v.9 no.4
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• pp.379-388
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• 2000

This study aims to examine the influence of experimental and numerical factors on the results of the test and finite element simulation to evaluate the formability of sheet metals. The stretch-forming test with a hemispherical punch is carried out to obtain the limiting dome height (LDH) and forming limit diagram (FLD) for several kinds of aluminium and steel sheet. The results of the LDH and FLD tests are analysed to find any correlation with the uniaxial tensile properties. It proves that the size of the prescribed grid has great influence on the measured value of strain. The finite element analysis of the punch stretching process is also carried out and the result is compared with the experimental data. The influence of the numerical parameters such as friction coefficient, element size and anisotropy model on the simulation results tms out to be very considerable.

• Resources Recycling
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• v.21 no.6
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• pp.74-81
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• 2012

The Influence of temperature on the recovery reaction of silver in aqueous solution was investigated based on Pourbaix diagram constructed by thermodynamic calculation at different temperatures. It was observed that the stability of water is more strongly affected by pH variation and the stable region of ${Ag^+}_{(aq)}$ is diminished at higher temperature. It was shown that the recovery of $Ag_{(aq)}$ in the forms of $Ag_{(s)}$ and $Ag_2O_{3(s)}$ is more advantageous thermodynamically at lower temperature, however, the recovery of $Ag_{(aq)}$ in the forms of $Ag_2O_{(s)}$ 및 $Ag_2O_{2(s)}$ is more advantageous as temperature increases. The rise of temperature is considered to demote the recovery of silver thermodynamically in strong acidic condition ($pH{\leq}2$), but more silver is regarded to be recovered with temperature above pH 2. Finally, The recovery of silver in the elemental state is shown to be more sensitively influenced by temperature variation compared with the recovery of silver in its oxide form.

• Journal of Korean Medical classics
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• v.36 no.1
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• pp.17-32
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• 2023

Objectives : This paper investigates the background, meaning and origin of the descriptions of the Heart such as 'seven orifices', 'sanmao', 'saw-toothed four layered lines' that are unique to the diagram in the Donguibogam. Methods : First the Heart diagram of the Donguibogam was compared with other Zhangfu diagrams of the past. Materials related to unique features in the descriptions of the Heart in the Donguibogam were collected, against which descriptive features were analyzed. Results : Of the many unique features, the descriptive basis of the 'seven orifices' could be found in the Qixingban[七星板] as a physical entity reflecting basic anatomical knowledge. The 'sanmao', which is compared to the Santaixing[三台星], could be understood as a non-physical entity whose descriptive basis could be found in the Xinxuetu of the Xinching. It could be assumed that the 'saw-toothed four layered lines' are likened to the multi-layered petals or calyx of a lotus flower bud to describe the Pericardium, or to the multiple walls of a mountain fortress surrounding a palace to describe the Danzhong, which is the chest cavity. These features could be understood as results of spiritualism influence. Conclusions : It could be concluded that Heo Jun, in his attempt to describe the Heart in more detail than previous diagrams of the Zangfu, referenced popular texts and images based on anatomical knowledge of previous texts, added varied descriptions resulting in a new diagram with a completely different origin.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.3124-3134
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• 1993

Diagnosis is composed of two different but interrelated steps ; retrieving the sensory responses f the system and reasoning the state of the system through the given sensor data. This paper explains the probabilistic nature of reasoning involved in the diagnosis when the uncertainties are inevitably included in experts' diagnostic decision making. Uncertainties in decision making are experts' personal experiences, preferences, and system's coherent characteristics. In order to ensure a consistent decision based on the same responses from the system, expert system technology is adopted with the Bayesian reasoning scheme.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.55
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• pp.85-96
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• 2000

This paper describes IDMS, a graph-based modeling system that supports problem structuring. We employs influence diagram as a problem representation tool, that is, a modeling tool. In particular, IDMS is designed as domain-independent shell. Therefore, a modeler can change the contents of the knowledge base to suit his/her own interested domain. Since the knowledge base of IDMS contains both modeling knowledge and domain knowledge, IDMS provides not only the syntactic support for modeling tool, but also the semantic support for problem domain. To apply the method in the real world context, we tested IDMS on the process selection problem in business reengineering, which is typical semi-structured problem.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.1-5
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• 2007

We construct the procedure to predict safety accidents following Bayesian approach. We make a model that can utilize the data to predict other levels of accidents. An event tree model which is a frequently used graphical tool in describing accident initiation and escalation to more severe accident is transformed into an influence diagram model. Prior distributions for accident occurrence rate and probabilities to escalating to more severe accidents are assumed and likelihood of number of accidents in a given period of time is assessed. And then posterior distributions are obtained based on observed data. We also points out the advantages of the bayesian approach that estimates the whole distribution of accident rate over the classical point estimation.