• Journal of KIISE
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• v.43 no.3
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• pp.370-379
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• 2016

Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.

• Geophysics and Geophysical Exploration
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• v.17 no.3
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• pp.129-136
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• 2014

Electromagnetic (EM) methods are generally divided into frequency-domain EM (FDEM) and time-domain EM (TDEM) methods, depending on the source waveform. The FDEM and TDEM fields are mathematically related by the Fourier transformation, and the TDEM field can thus be obtained as the Fourier transformation of FDEM data. For modeling in time-domain, we can use fast frequency-domain modeling codes and then convert the results to the time domain with a suitable numerical method. Thus, frequency-to-time transformations are of interest to EM methods, which is generally attained through fast Fourier transform. However, faster frequency-to-time transformation is required for the 3D inversion of TDEM data or for the processing of vast air-borne TDEM data. The diffusion expansion method (DEM) is one of smart frequency-to-time transformation methods. In DEM, the EM field is expanded into a sequence of diffusion functions with a known frequency dependence, but with unknown diffusion-times that must be chosen based on the data to be transformed. Especially, accuracy of DEM is sensitive to the diffusion-time. In this study, we developed a method to determine the optimum range of diffusion-time values, minimizing the RMS error of the frequency-domain data approximated by the diffusion expansion. We confirmed that this method produces accurate results over a wider time range for a homogeneous half-space and two-layered model.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.49-56
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• 1999

In many continuous speech recognition systems based on HMMs, decision tree-based state tying has been used for not only improving the robustness and accuracy of context dependent acoustic modeling but also synthesizing unseen models. To construct the phonetic decision tree, standard method performs one-level pruning using just single Gaussian triphone models. In this paper, two novel approaches, two-level decision tree and multi-mixture decision tree, are proposed to get better performance through more accurate acoustic modeling. Two-level decision tree performs two level pruning for the state tying and the mixture weight tying. Using the second level, the tied states can have different mixture weights based on the similarities in their phonetic contexts. In the second approach, phonetic decision tree continues to be updated with training sequence, mixture splitting and re-estimation. Multi-mixture Gaussian as well as single Gaussian models are used to construct the multi-mixture decision tree. Continuous speech recognition experiment using these approaches on BN-96 and WSJ5k data showed a reduction in word error rate comparing to the standard decision tree based system given similar number of tied states.

• Land and Housing Review
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• v.15 no.2
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• pp.125-137
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• 2024

A conventional Design for Safety (DfS), introduced to eliminate potential hazards in the design phase proactively, has encountered persistent challenges, such as perfunctory risk assessments and hazard identifications based on 2D drawings and inefficient workflow processes. This study proposes a BIM-based approach to Design for Safety (DfS) to address the limitations of conventional methods, aiming to enhance efficiency and achieve practical safety management benefits. The proposed workflow process for BIM-based DfS has been refined and validated for on-site applicability through various case studies, including risk assessments during the design phase and field applications for safety management activities during the construction phase. Specifically, the critical process of risk assessment within the DfS methodology has also been transitioned to a BIM-based approach. This BIM-based risk assessment process has been evaluated through case studies, encompassing safety reviews for structural design, construction equipment operation, and construction methodology with sequence in design projects. Additionally, the proposed BIM-based DfS has demonstrated exceptional on-site applicability and efficiency, as validated by the application of a BIM deliverable embedded in DfS information for CDE-based daily activity briefing, VR-based safety training, AR-based mitigation measures inspections, and other safety management activities in the construction phase.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.4
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• pp.159-168
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• 2005

This study carries out a finite difference nonlinear analysis of anisotropic advanced composite plate structures with various layer sequences. In the numerical analysis of various mechanical problems involving complex partial differential equations, the finite difference method (FDM) developed in this study has an advantage over the finite element method in its ability to avoid mesh generation and numerical integration. Many studies in FDM have been made on clamped or simple boundary conditions using merely an energy approach. These approaches cannot be satisfied, however, with pivotal points along the free boundary. Therefore, this study addresses the nonlinear problem of anisotropic plates by adopting a finite difference modeling elimination of pivotal difference points in the case of a free boundary condition. Complex nonlinear behaviors of composite plate structures for various parameters, especially for layer sequences, are analyzed using the proposed approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.5
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• pp.502-515
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• 2020

To identify the dynamic characteristics of the Auto-leveling system applied to the Tractor-Trailer type Transporter for mounting a large scale precision equipment, Dynamics Modeling & Simulation were performed using general Dynamics Analysis Program - RecurDyn(V9R2). The axial load data, transverse load data and pad trace data of leveling actuators were obtained from M&S. And they were analyzed and compared with each other by parameters, i.e. friction coefficients on the ground, landing ram speed of actuators, and direction & quantity of ground slope. It was observed that ground contact friction coefficients affected to transverse load and pad trace; the landing ram speed of actuators to both amplitude of axial & transverse load, and this phenomena was able to explain from the frequency analysis of the axial load data; the direction of ground slope to driving sequence of landing ram of actuators. But the dynamic behaviors on the two-directional slope were very different from them on the one-directional slope and more complex.

• Wind and Structures
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• v.26 no.3
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• pp.147-161
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• 2018

For wind engineering applications downbursts are, presently, almost exclusively modeled, both experimentally and numerically, as transient impinging momentum jets (IJ), even though that model contains none of the physics of real events. As a result, there is no connection between the IJ-simulated downburst wind fields and the conditions of formation of the event. The cooling source (CS) model offers a significant improvement since it incorporates the negative buoyancy forcing and baroclinic vorticity generation that occurs in nature. The present work aims at using large-scale numerical simulation of downburst-producing thunderstorms to develop a simpler model that replicates some of the key physics whilst maintaining the relative simplicity of the IJ model. Using an example of such a simulated event it is found that the non-linear scaling of the velocity field, based on the peak potential temperature (and, hence, density) perturbation forcing immediately beneath the storm cloud, produces results for the radial location of the peak radial outflow wind speeds near the ground, the magnitude of that peak and the time at which the peak occurs that match well (typically within 5%) of those produced from a simple axi-symmetric constant-density dense source simulation. The evolution of the downdraft column within the simulated thunderstorm is significantly more complex than in any axi-symmetric model, with a sequence of downdraft winds that strengthen then weaken within a much longer period (>17 minutes) of consistently downwards winds over almost all heights up to at least 2,500 m.

• Structural Engineering and Mechanics
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• v.55 no.3
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• pp.555-581
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• 2015

Triangular pyramid and Quadrangular pyramid elements for partial double-layer spherical reticulated shells of pyramidal system are investigated in the present study. Macro programs for six typical partial double-layer spherical reticulated shells of pyramidal system are compiled by using the ANSYS Parametric Design Language (APDL). Internal force analysis of six spherical reticulated shells is carried out. Distribution regularity of the stress and displacement are studied. A shape optimization program is proposed by adopting the sequence two-stage algorithm (RDQA) in FORTRAN environment based on the characteristics of partial double-layer spherical reticulated shells of pyramidal system and the ideas of discrete variable optimization design. Shape optimization is achieved by considering the objective function of the minimum total steel consumption, global and locality constraints. The shape optimization of six spherical reticulated shells is calculated with the span of 30m~120m and rise to span ratio of 1/7~1/3. The variations of the total steel consumption along with the span and rise to span ratio are discussed with contrast to the results of shape optimization. The optimal combination of main design parameters for six spherical reticulated shells is investigated, i.e., the number of the optimal grids. The results show that: (1) The Kiewitt and Geodesic partial double-layer spherical reticulated shells of triangular pyramidal system should be preferentially adopted in large and medium-span structures. The range of rise to span ratio is from 1/6 to 1/5. (2) The Ribbed and Schwedler partial double-layer spherical reticulated shells of quadrangular pyramidal system should be preferentially adopted in small-span structures. The rise to span ratio should be 1/4. (3) Grids of the six spherical reticulated shells can be optimized after shape optimization and the total steel consumption is optimized to be the least.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.427-445
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• 2016

Star sensors are the attitude estimation sensors of the satellite orbiting in its path. It gives information to the control station on the earth about where the satellite is heading towards. It captures the images of a predetermined reference star. By comparing this image with that of the one captured from the earth, exact position of the satellite is determined. In the process of imaging, stray lights are eliminated from reaching the optic lens by the mechanical enclosures of the star sensors called Baffles. Research in space domain in the last few years is mainly focused on increased payload capacity and reduction in launch cost. In this paper, a star sensor baffle made of Aluminium is considered for the study. In order to minimize the component weight, material wastage and to improve the structural performance, an alternate material to Aluminium is investigated. Carbon Fiber Reinforced Polymer is found to be a better substitute in this regard. Design optimisation studies are carried out by adopting suitable design modifications like implementing an additional L-shaped flange, Upward flange projections, downward flange projections etc. A better configuration of the baffle, satisfying the design requirements and achieving manufacturing feasibility is attained. Geometrical modeling of the baffle is done by using UNIGRAPHICS-Nx7.5(R). Structural behavior of the baffle is analysed by FE analysis such as normal mode analysis, linear static analysis, and linear buckling analysis using MSC/PATRAN(R), MSC-NASTRAN(R) as the solver to validate the stiffness, strength and stability requirements respectively. Effect of the layup sequence and the fiber orientation angle of the composite layup on the stiffness are also studied.