• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.31-38
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• 2016

In this paper, we propose multi-scale infrared target detection algorithm with varied filter size using integral image. Filter based target detection is widely used for small target detection, but it doesn't suit for large target detection depending on the filter size. When there are multi-scale targets on the sky background, detection filter with small filter size can not detect the whole shape of the large targe. In contrast, detection filter with large filter size doesn't suit for small target detection, but also it requires a large amount of processing time. The proposed algorithm integrates the filtering results of varied filter size for the detection of small and large targets. The proposed algorithm has good performance for both small and large target detection. Furthermore, the proposed algorithm requires a less processing time, since it use the integral image to make the mean images with different filter sizes for subtraction between the original image and the respective mean image. In addition, we propose the implementation of real-time embedded system using FPGA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.39-48
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• 2005

This paper proposes novel texture segmentation method using Bayesian estimation method and neural networks. We use multi-scale wavelet coefficients and the context information of neighboring wavelets coefficients as the input of networks. The output of neural networks is modeled as a posterior probability. The context information is obtained by HMT(Hidden Markov Tree) model. This proposed segmentation method shows better performance than ML(Maximum Likelihood) segmentation using HMT model. And post-processed texture segmentation results as using multi-scale Bayesian image segmentation technique called HMTseg in each segmentation by HMT and the proposed method also show that the proposed method is superior to the method using HMT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.347-370
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• 2019

In the computer-aided detection (CAD) system of pulmonary nodules, a high false positive rate is common because the density and the computed tomography (CT) values of the vessel and the nodule in the CT images are similar, which affects the detection accuracy of pulmonary nodules. In this paper, a method of automatic detection of pulmonary nodules based on multi-scale enhancement filters and 3D shape features is proposed. The method uses an iterative threshold and a region growing algorithm to segment lung parenchyma. Two types of multi-scale enhancement filters are constructed to enhance the images of nodules and blood vessels in 3D lung images, and most of the blood vessel images in the nodular images are removed to obtain a suspected nodule image. An 18 neighborhood region growing algorithm is then used to extract the lung nodules. A new pulmonary nodules feature descriptor is proposed, and the features of the suspected nodules are extracted. A support vector machine (SVM) classifier is used to classify the pulmonary nodules. The experimental results show that our method can effectively detect pulmonary nodules and reduce false positive rates, and the feature descriptor proposed in this paper is valid which can be used to distinguish between nodules and blood vessels.

• Steel and Composite Structures
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• v.31 no.5
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• pp.517-527
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• 2019

To move forward in large steps rather than in small increments, the community would benefit from a systematic and comprehensive database of multi-scale composites and measured properties, driven by comprehensive studies with a full range of types of fiber-reinforced polymers. The multi-scale hierarchy is a promising chemical approach that provides superior performance in synergistically integrated microstructured fibers and nanostructured materials in composite applications. Achieving high-efficiency thermal conductivity and mechanical properties with a simple surface treatment on single-walled carbon nanotubes (SWCNTs) is important for multi-scale composites. The main purpose of the project is to introduce ozone-treated SWCNTs between an epoxy matrix and basalt fibers to improve mechanical properties and thermal conductivity by enhancing dispersion and interfacial adhesion. The obvious advantage of this approach is that it is much more effective than the conventional approach at improving the thermal conductivity and mechanical properties of materials under an equivalent load, and shows particularly significant improvement for high loads. Such an effort could accelerate the conversion of multi-scale composites into high performance materials and provide more rational guidance and fundamental understanding towards realizing the theoretical limits of thermal and mechanical properties.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.903-911
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• 2019

The multi-utility tunnel is one of the essential social infrastructures, but it is difficult to establish the multi-utility tunnel due to the scale of the National Land Planning and Utilization Act (2 million square meters). In this paper, we analyze the feasibility of establishing the multi-utility tunnel in the existing city in order to activate the multi-utility tunnel installation. For the feasibility analysis, the scale was classified into four categories based on related laws, and related indicators were selected and evaluated using feasibility and economic analysis. Three kinds/four kinds of suitable multi-utility tunnel for the scale of the existing city were shown, and five kinds of multi-utility tunnel were considered suitable for the new city over 2 million square meters. The results of the overall score evaluation of the tunnel type of the existing city and the open type of the new city of 2 million square meters or more, which is the obligation to install the multi-utility tunnel, do not show much difference and suggest the validity of the installation of the multi-utility tunnel in various scale of the existing city.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1164-1171
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• 2004

A new multi-scale simulation model is proposed to analyze heart mechanics. Electrophysiology of a cardiac cell is numerically approximated using the previous model of human ventricular myocyte. The ion transports across cell membrane initiated by action potential induce an excitation-contraction mechanism in the cell via cross bridge dynamics. Negroni and Lascano model (NL model) is employed to calculate the tension of cross bridge which is closely related to the ion dynamics in cytoplasm. To convert the tension on cell level into contraction force of cardiac muscle, we introduce a simple geometric model of ventricle with a thin-walled hemispheric shape. It is assumed that cardiac tissue is composed of a set of cardiac myocytes and its orientation on the hemispheric surface of ventricle remains constant everywhere in the domain. Application of Laplace law to the ventricle model enables us to determine the ventricular pressure that induces blood circulation in a body. A lumped parameter model with 7 compartments is utilized to describe the systemic circulation interacting with the cardiac cell mechanism via NL model and Laplace law. Numerical simulation shows that the ion transports in cell level eventually generate blood hemodynamics on system level via cross bridge dynamics and Laplace law. Computational results using the present multi-scale model are well compared with the existing ones. Especially it is shown that the typical characteristics of heart mechanics, such as pressure volume relation, stroke volume and ejection fraction, can be generated by the present multi-scale cardiovascular model, covering from cardiac cells to circulation system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.115-123
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• 2015

The incremental learning method performs well in face face tracking. However, it has a drawback in that it is sensitive to the tracking error in the previous frame due to the environmental changes. In this paper, we propose a selective incremental learning method to track a face more reliably under various conditions. The proposed method is robust to illumination variation by using the LBP(Local Binary Pattern) features for each individual frame. We select patches to be used in incremental learning by using Staggered Multi-Scale LBP, which prevents the propagation of tracking errors occurred in the previous frame. The experimental results show that the proposed method improves the face tracking performance on the videos with environmental changes such as illumination variation.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.27-40
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• 2004

When we derive multi-scale databases from a source spatial database, thegeometries and topological relations in the source database are transformed according to a predefined set of constraints. This means that the derived databases should be checked to see if the constraints are respected during the construction or updates of databases and to maintain the consistency of multi-scale databases. In this paper, we focus on the topological consistency between the source and derived databases, which is one of the important constraints to respect. In particular, we deal with the method of assessment of topological consistency, when 2-dimensional objects are collapsed to 1-dimensional ones. We introduce eight types of topological relations between 2-dimensional objects and 19 topological ones between 1-dimensional objects and propose four different strategies to convert 2-dimensional topological relations in the source database to 1-dimensional ones objects in the target database. With these strategies, we guarantee the topological consistency between multi-scale databases.

• Smart Structures and Systems
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• v.16 no.1
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• pp.223-242
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• 2015

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

• Journal of Families and Better Life
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• v.16 no.4
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• pp.155-166
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• 1998

The purpose of this study was to develop ' the Behavior Problem Scale for Children and Adolescence' The 518 subjects were selected from 5th and 6th grades of elementary schools and first and second grades of middle schools in Pusan. Statistics used for data analysis were χ2 cramer's V, factor analysis multi-regression Pearson's r, Cronbach's a. The major finding of this study were as follows 1) 80 items of the 159 item scale were acceptable through item discriminant method The discriminant coefficients of the items(Cramer's V) ranged from .48 to .81. 2) 6 factors(shyness aggression hyperactivity withdrawal anxious immature) extracted from factor analysis,. Multi-regression analysis conducted to reduce the length of scale have drawn 42 items for 'the Behavior Problem Scale Children and Adolescence' 3) Reliability coefficients(Cronbach's a) of this scale was 94.