• Journal of Korean Library and Information Science Society
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• v.46 no.2
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• pp.257-287
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• 2015

This study proposes a methodology for using facet analysis in ontology modeling and investigates how facet analysis could be utilized in ontology design processes. We applied facet analysis methods developed by Ranganathan and CRG (Classification Research Group) to modeling Smartphone ontology. Utilizing the guiding principles of Ranganathan and CRG, main facets, such as Type, Spec, Function, Operation, Product, Person, Agent, Space and Time, are derived for Smartphone ontology. It is hoped that the methods and procedures employed in identifying and categorizing facets and ontology in this study will provide insights into designing future ontologies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.703-714
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• 2010

This paper proposes an approach for staged finite element modeling with coupled seepage and stress analysis. The stage modeling is based on the predefined inter-relationship between the base model and the unit stage models. A unit stage constitutes a complete finite element model, of which the geometries and attributes are subject to changes from stage to stage. The seepage analysis precedes the mechanical stress analysis at every stage. Division of the wet and dry zone and the pore pressures are evaluated from the seepage analysis and used in determining input data for the stress analysis. The results of the stress analysis may also be associated with the pore water pressures. For consolidation analysis, the pore pressure and the displacement variables are mixed in a coupled matrix equation. The time marching solution produces the dissipation of excess pore pressure and variation of stresses with passage of time. For undrained analysis, the excess pore pressures are computed from the stress increment due to loading applied in the unit stage and are used in revising the hydraulic head. The solution results of a unit stage are inherited and accumulated to the subsequent stages through the relationship of the base model and the individual unit stages. Implementation of the proposed approach is outlined on the basis of the core procedures, and numerical examples are presented for demonstration of its application.

• Clinical and Experimental Pediatrics
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• v.65 no.5
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.257-266
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• 2002

In the recent years flow around bridges are investigated using computer modeling. Selvam (1998), Selvam and Bosch (1999), Frandsen and McRobie (1999) used finite element procedures. Larsen and Walther (1997) used discrete vorticity procedure. The aeroelastic instability is a major criterion to be checked for long span bridges. If the wind speed experienced by a bridge is greater than the critical wind speed for flutter, then the bridge fails due to aeroelastic instability. Larsen and Walther (1997) computed the critical velocity for flutter using discrete vortex method similar to wind tunnel procedures. In this work, the critical velocity for flutter will be calculated directly (free oscillation procedure) similar to the approaches reported by Selvam et al. (1998). It is expected that the computational time required to compute the critical velocity using this approach may be much shorter than the traditional approach. The computed critical flutter velocity of 69 m/s is in reasonable comparison with wind tunnel measurement. The no flutter and flutter conditions are illustrated using the bridge response in time.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.703-705
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• 1999

In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1751-1768
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• 2011

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.

• Computers and Concrete
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• v.1 no.1
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• pp.1-14
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• 2004

Computer-based analysis tools for forensic assessment of reinforced concrete structures are presented. The analysis tools, mostly in the form of nonlinear finite element procedures, are based on the concepts and formulations of the Modified Compression Field Theory. Relevant details regarding their formulation are provided. Development of realistic constitutive models and corroboration of the analysis procedures, through comprehensive experimental programs, are discussed. Also presented are graphics-based pre- and post-processors, which are of significant aid in structural modeling, input of data, and interpretation of analysis results. The details and results of a case study, illustrating the application and value of such analytical tools, are also discussed.

• Journal of the Korean Society of Safety
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• v.11 no.3
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• pp.143-153
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• 1996

Shutdown of boiler plants is a dynamic, complicated, and hazardous operation. Operational error is a major contributor to danserous situations during boiler plant shutdowns. It is important to develop an automatic system which synthesizes operating procedures to safely go from normal operation to complete shutdown. Knowledge representation for automatic shutdown of boiler plants makes use of the hierarchical, rule-based framework for heuristic knowledge, the semantic network, frame for process topology, and AI techniques such as rule matching, forward chaining, backward chaining, and searching. This knowledge representation and modeling account for the operational states, primitive operation devices, effects of their application, and planning methodology. Also, this is designed to automatically formulate subgoals, search for positive operation devices, formulate constraints, and synthesize shutdown procedures in boiler plants.

• Archives of design research
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• v.12 no.2
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• pp.89-95
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• 1999

Carlo H. Sequin, a computer scientist, became to know a sculpture of subtle space construction which was created by Brent Collins, a sculptor, and introduced it as 'Visual Mathematics' in a journal. Sequin who was able to deduce a basic logic of the construction, has developed a software which can be used for virtual modeling merely by substituting simple numerical values using a computer and supplied it to Collins. The present author who was exposed to their collaboration works through series of their papers published in the journal, Leonardo, introduces the Collins' sculptures and the author's modeling procedures of animation works both of which show many common things in visual characteristics and modeling expansion method. The author investigates the mathematical characteristics which is used as a basic motive of modeling and then supplied as a principal visual characteristics of a material. 'Modeling Development by Principle Expansion,' in which the expansion is developed on the base of space twist as for Collins whereas the space section as for the present author, is introduced in this study. With the same stream of the mutual reaction in 'arts, sciences and technology' which has been stressed with the development of sciences and technology, this modeling technology is suggested as a research theme which has a possiblity of various applications.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.36-44
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• 1993

In the development of a high speed and light weight manipulator, it is necessary to consider the flexibility of a robotic arm. The infinite dynamics must be analyzed to obtain the finite mode modeling to achieve the feasible controller design of the robotic arm. The modeling procedures of the flexible robot arm, and natural frequencies and mode shapes by the constrained and unconstrained mode method are illustrated. The transfer function of the robot arm with a payload is also shown. The controller is designed by the pole assignment and optimal control theory to compensate for the unmodelled dynamic effects to the low order system. Also, the pole assignment method involving the harmonic vibration mode is presented through computer simulation.