• Journal of The Korean Digital Architecture Interior Association
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• v.2 no.1
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• pp.9-15
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• 2002

As architectural forms tend to be large-scaled, high-storied and complicated, use of computer for processing design information has been generalized. However, CAD use in the process of developing architectural design has been neglected greatly in the educational field of architectural field due to the surging of recognition that it may limit the essential property of architectural design. It may be resulted from the limitation of CAD system, that is, it is because of tardy speed of application development for the related areas with the lack of simplicity and clarity of flexibility to be secured on the drawing and user interface. Recent CAD systems, however, overcome such a limitation, convert into object-based design from entity-based drawing, drafting and modeling for implementing design concept of architects and it connects with internet linked to superspeed information communication network and changes process and stream of architectural design. Therefore, this study deals with utility of object based CAD system with products of Autodesk Co. and consequently obtain the following conclusions. First, it expands architect's design areas by supporting cooperative design system based on model-based architectural design and internet. Second, it reduces consumption of personal and material resources and time in the process of drawing production for improving architectural design works. Third, it can reduce the frequent design changes by improving understanding of architectural space with visualization of immediate 3D information, escaping from traditional methods to deliver design information to building owner through 2D drawing or model and perspective drawing requiring much cost and time. Fourth, it keeps exactness without omission or duplication of design information and generate and renew information of all related drawings on a drawing. Fifth, it is possible to change difficult and boring architectural design work into a pleasure owing to immediate modeling and drawing of design idea. In addition, digital drawing generated by using object-based CAD system can playa role of establishing Urban Information System to be used for protecting from building in disaster and urban disasters in connection with GIS numerical map and be used for reference of all kinds of information required fro post-management of buildings. However, what is more important is that surplus time from introduction of object-based CAD system should be used for consideration to be recognized as a good space and building built as a product of this project for comfort to urban people.

• Journal of the Korean Geographical Society
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• v.47 no.3
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• pp.426-439
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• 2012

The goal of this study is to propose a new method to capture the qualitative person spatial behavior. Beyond tracking or indexing the change of the location of a person, the changes in the relationships between a person and its environment are considered as the main source for the formal model of this study. Specifically, this paper focuses on the movement behavior of a person near the boundary of a region. To capture the behavior of person near the boundary of regions, a new formal approach for integrating an object's scope of influence is described. Such an object, a spatio-temporally extended point (STEP), is considered here by addressing its scope of influence as potential events or interactions area in conjunction with its location. The formalism presented is based on a topological data model and introduces a 12-intersection model to represent the topological relations between a region and the STEP in 2-dimensional space. From the perspective of STEP concept, a prototype analysis results are provided by using GPS tracking data in real world.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.23-35
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• 2012

This paper presents a 3-D pose (position and orientation) estimation method for an elliptic object in 3-D space. It is difficult to resolve the problem of determining 3-D pose parameters with respect to an elliptic feature in 3-D space by interpretation of its projected feature onto an image plane. As an alternative, we propose a two points-based pose estimation algorithm to seek the 3-D information of an elliptic feature. The proposed algorithm determines a homogeneous transformation uniquely for a given correspondence set of an ellipse and two coplanar points that are defined on model and image plane, respectively. For each plane, two triangular features are extracted from an ellipse and two points based on the polarity in 2-D projection space. A planar homography is first estimated by the triangular feature correspondences, then decomposed into 3-D pose parameters. The proposed method is evaluated through a series of experiments for analyzing the errors of 3-D pose estimation and the sensitivity with respect to point locations.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.229-234
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• 2017

Because of the invisible nature of software and the bad coding habits (bad smell) of the existing developers, there are many redundant codes and unnecessary codes, which increases the complexity and makes it difficult to upgrade software. Therefore, it is required a code visualization so that developers can easily and automatically identify the complexity of the source code. To do this, it is necessary to construct SW visualization tool based on open source software and redefine the coupling and cohesion according to the object oriented viewpoint. Specially to identify a bad smell code pattern, we suggest how to plug-in diverse parsers within our tool. In this paper, through redefining coupling and cohesion from an object oriented perspective, we will extract bad smell code patterns within source code from inputting any pattern into the tool.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.223-233
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• 2008

In the mid 90's, the U.S. government released images acquired by the first generation of photo reconnaissance satellite missions between 1960 and 1972. The Declassified Intelligent Satellite Photographs (DISP) from the Corona mission are of high quality with an astounding ground resolution of about 2 m. The KH-4A panoramic camera system employed a scan angle of $70^{\circ}$ that produces film strips with a dimension of $55\;mm\;{\times}\;757\;mm$. Since GPS/INS did not exist at the time of data acquisition, the exterior orientation must be established in the traditional way by using control information and the interior orientation of the camera. Detailed information about the camera is not available, however. For reconstructing points in object space from DISP imagery to an accuracy that is comparable to high resolution (a few meters), a precise camera model is essential. This paper is concerned with the derivation of a rigorous mathematical model for the KH-4A/B panoramic camera. The proposed model is compared with generic sensor models, such as affine transformation and rational functions. The paper concludes with experimental results concerning the precision of reconstructed points in object space. The rigorous mathematical panoramic camera model for the KH-4A camera system is based on extended collinearity equations assuming that the satellite trajectory during one scan is smooth and the attitude remains unchanged. As a result, the collinearity equations express the perspective center as a function of the scan time. With the known satellite velocity this will translate into a shift along-track. Therefore, the exterior orientation contains seven parameters to be estimated. The reconstruction of object points can now be performed with the exterior orientation parameters, either by intersecting bundle rays with a known surface or by using the stereoscopic KH-4A arrangement with fore and aft cameras mounted an angle of $30^{\circ}$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.168-176
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• 2015

Trends of integrating products and services lead to the emergence of Product-Service System (PSS). To implement and embody a PSS solution in new product development, a comprehensive design framework is allowed designers to facilitate the design factors of the PSS in complex business environments. A physical product, containing functionalities for services, is the role of medium between customers and a manufactures. Customers can access those metaphysical interfaces to utilize the product fully or expand its performances. The PSS is aiming to prolong its lifecycle while maintaining its expected quality. Since the quality can be represented as a measure which belongs to user's perspective, guaranteeing certain level of quality can be interpreted to sustaining customer satisfaction. The objective of this paper is to propose a PSS design framework to identify design factors for developing products and services by integrating object-oriented concepts and blueprinting in context of a business ecosystem. The proposed model is developed based on relationship products and services matching with their design factors. The products and the services are then brought together to form a PSS. Functions and processes can be categorized to identify the design factors in different levels using the object-oriented concepts. Objected-oriented concepts provide PSS analysis tools for describing a business process or a workflow process in the PSS. The blueprint is used to identify the relationships between the products functions and the service processes that are offered as part of a job. To demonstrate of the effectiveness of the proposed model, we use a case study involving a smart phone.

• Journal of Aerospace System Engineering
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• v.16 no.2
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• pp.13-24
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• 2022

As the scale of airborne system software increases, the use of OOT (Object-Oriented Technology) is increasing for functional expansion, efficient development, and code reuse, but the verification method for airborne object-oriented software is conducted from the perspective of the existing procedure-oriented program. The purpose of this paper was to analyze the characteristics of OOT and the vulnerabilities derived from the functional characteristics of OOT, and present a verification method applicable to each software development process (Design, Coding and Testing) to ensure the functional safety integrity of aviation software to which OOT is applied. Additionally, we analyzed the meaning of the static analysis results among the step-by-step verification measures proposed by applying LDRA, a static analysis automation tool, to PX4, an open source used to implement flight control software.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.126-139
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• 2023

At present, naked-eye 3D appears more and more commonly on the facades of urban buildings. It brings an incredible visual experience to the audience by simulating the natural 3D 3D space effect. At the same time, it also creates enormous commercial value for city publicity and commercial advertisements. There is much research on naked-eye 3D visual effects, but for right-angle LED screens. Right-angle LED screen's brand-new expression method that has only become popular in recent years, how to convey a realistic naked-eye 3D effect through two LED screens combined at right angles has become a problem worth exploring. To explore the whole design ideas and production process of the naked-eye 3D impact of the right-angle LED screen, this paper is a preliminary study aimed at understanding the performance principle and expression features. Before the case analysis, first, understand the standard virtual 3D space construction techniques. Combining it with the optical illusion phenomenon, according to the expression principle of the naked-eye 3D effect of the right-angle LED screen, it can be summarized into seven expressions: Shadow, Color contrast, Background structure line, Magnify object, Object out of bounds, Object floating, Fusion of picture and background. By analyzing the optical illusion phenomenon used in the case, we summarized the main performance characteristics of the naked eye 3D effect. The emergence of right-angle LED screens breaks the limitation of a single plane of optical illusion art, perfectly combines building facades with naked-eye 3D visual effects, and provides designers with a brand-new creative platform. Understanding its production principles and main expressive features can help designers enter this innovative platform better.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.