• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.629-638
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• 2023

This study introduces an innovative approach to monitor the whereabouts of workers within indoor construction settings. While traditional modalities such as GPS and NTRIP have demonstrated efficacy for outdoor localizations, their precision dwindles in indoor environments. In response, this research advocates for the adoption of Aruco markers. Leveraging computer vision technology, these markers facilitate the quantification of the distance between a worker and the marker, subsequently pinpointing the worker's instantaneous location with heightened accuracy. The methodology's efficacy was rigorously evaluated in a real-world construction scenario. Parameters including system stability, the influence of lighting conditions, the extremity of measurable distances, and the breadth of recognition angles were methodically appraised. System stability was ascertained by maneuvering the camera at a uniform velocity, gauging its marker recognition prowess. The impact of varying luminosity on marker discernibility was scrutinized by modulating the ambient lighting. Furthermore, the camera's spatial movement ascertained both the upper threshold of distance until marker recognition waned and the maximal angle at which markers remained discernible.

• KIEAE Journal
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• v.15 no.2
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• pp.117-122
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• 2015

Purpose: Generally, 30% of the total energy consumption in office building is used for artificial indoor lightings, and almost 75-85% of electric power in fluorescent and Light-Emitting Diode (LED) lightings can be dissipated as a form of heat into indoor environment. The heat generated by indoor lightings can cause the increase of cooling load in office buildings. Thus, it its important to consider indoor lightings as a heat and light source, simultaneously. Method: In this study, we installed two kinds of indoor lightings including fluorescent and LED lightings and measured surface temperature of both indoor lightings. In addition, we obtained ambient temperature of indoor space and finally calculated total heat dissipated from plenum area and surface of lightings. Result: Total indoor heat gain was 87.17Wh and 201.36Wh in cases of six 40W-LED lightings and 64W-fluorescent lightings, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.339-345
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• 2002

Extracting of car licens plate os important for identifying the car. Since there are some problems such as poor ambient lighting problem, bad weather problem and so on, the car images are distorted and the car license plate is difficult to be extracted. This paper proposes a method of extracting car license plate using motor vehicle regulation. In this method, some features of car license plate according to motor vehicle regulation such as color information, shape are applied to determine the candidate of car license plates. For the result of recognition by neural network, the candidate which has characters and numbers patterns according to motor vehicle regulation is certified as license-plate region. The results of the experiments with 70 samples of real car images shoe the performance of car license-plate extraction by 84.29%, and the recognition rate is 80.81%.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.142-143
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• 2008

In the present work, high-speed video images of the ground take-off flight of a live butterfly were captured and their dynamic motions during the first full-stroke were analyzed. To capture the dynamic images of the take-off motion, the experimental setup consisted of a high-speed camera, a Xenon lamp as a light source and a transparent chamber of $15^W{\times}15^L{\times}17^H$ $cm^3$ in physical size. The ambient temperature and supplementary lighting devices were precisely controlled. The weight and wing span of the butterfly tested in this study was 104 mg and 63.14 mm, respectively. The ground take-off images were captured with 4000 fps with a spatial resolution of (1024${\times}$512) pixels. The period of the first full-stroke was 80.5ms and the flapping speed of downstroke was 2 times faster than that of upstroke. As a result, butterflies used the fling and near-clap motion to generate lifting force and an interesting take-off behavior of early pronation and downstroke was observed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.596-599
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• 2001

Extracting of car licens plate is important for identifying the car. Since there are some problems such as poor ambient lighting problem, bad weather problem and so on, the car images we distorted and the tar license plate is difficult to be extracted. This paper proposes a method of extracting car license plate using motor vehicle regulation. In this method, some features of car license plate according to motor vehicle regulation such as color information, shape are applied to determine the candidate of car license plates. For the result of recognition by neural network, the candidate which has characters and numbers patterns according to motor vehicle regulation is certified as license-plate region. The results of the experiments with 70 samples of real car images shoe the performance of car license-plate extraction by 84.29%, and the recognition rate is 80.81%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.608-614
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• 2018

In addition to the diffusion of ICT technology, various protocols of short range wireless communication technology are being applied for efficient information operation. However, due to limitations of short-range wireless communication, communication is not smooth in places where frequency environment is poor, such as frequency confusion and warehouse type factory. When an alternative is needed. The development of LED technology and expansion of infrastructure through LED based visible light communication is attracting attention as an alternative and spreading the usage in wide range now a days. In addition, the infrastructure has been expanded with solar panels in response to the development of smarthome built-in with renewable energy. In this situation, visible light communication using PD has been limitedly applied in a near environment where the receiving angle of the PD and the ambient light ensure the LoS and the influence of the ambient light is small. In order to solve this problem, we have implemented visible light communication using LED lighting with large current infrastructure and solar panel with large receiving area, and proposed a circuit for restoring accurate data even in ambient light. Through this study results, it is expected that visible light communication can be more widely used and this result used as the base data for visible light communication research using the solar panel as the receiver.

• Journal of Energy Engineering
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• v.26 no.2
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• pp.64-72
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• 2017

The performance analysis of the 70 W class LED lighting system suitable for the Middle East environment was performed using the lumped parameter model. The LED light is composed of a heating substrate, a heat pipe, and a heat sink. We divided the LED lights into four objects and applied energy equilibrium to each of them to establish four lumped nonlinear differential equations. The solution of the simultaneous equations was obtained by the Runge-Kutta method. Convective heat transfer coefficients of the lumped model were obtained by multidimensional CFD analysis. As a result of comparison with experiment, it was found that the heating substrate had an error of $1.5^{\circ}C$ and the upper heat sink had an error of $1.8^{\circ}C$ and the relative error was about 0.6 %. Using this model, temperature distribution analysis was performed for normal operating conditions with an ambient temperature of $55^{\circ}C$, with sunlight only, with abnormal operating conditions with sunlight, and without an upper heat sink.

• KIEAE Journal
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• v.13 no.5
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• pp.43-50
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• 2013

Recent researches on plant factory system deal with the convergence of lighting technology, agricultural technology inclusive to the high-tech industries worldwide in order to respond to the decreasing crop harvest due to global warming and abnormal weather phenomena. However, the fundamental performance standard is not currently being introduced in the case of plants factory and its commercialization is not activated because of high initial investment and operating cost. Large portion of the initial investment and operating cost of a plant factory is ascribed to artificial light sources and thermal control facilities, therefore, innovation should be provided in order to improve the economics of the plant factory. As an alternative, new plant factory could harness solar thermal and geothermal systems for heating, cooling and ventilation. In this study, a natural light dependent multi-layer plant factory's thermal environment was analyzed with two-dimensional numerical methods to elicit efficient operation conditions for optimized internal physical environment. Depending on the supply air temperature and airflow rate introduced in the facility, the temperature changes around the crops was interpreted. Since the air supplied into the plant factory does not stay long enough, the ambient temperature predicted around the plating trays was not significantly different from that of the supplied air. However, the changes of airflow rate and air flow pattern could cause difference to the temperature around the planting trays. Increasing the amount of time of air staying around the planting trays could improve energy performance in case the thermal environment of a natural light based multi-layer plant factory is considered.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1853-1858
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• 2021

O-rings fill the gaps between mechanical parts. Until now, the sorting of defective products has been performed visually and manually, so classification errors often occur. Therefore, a camera-based defect classification system without human intervention is required. However, a binarization process is required to separate the required region from the background in the camera input image. In this paper, an adaptive binarization technique that considers the surrounding pixel values is applied to solve the problem that single-threshold binarization is difficult to apply due to factors such as changes in ambient lighting or reflections. In addition, the convex hull technique is also applied to compensate for the missing pixel part. And the learning model to be applied to the separated region applies the residual error-based deep learning neural network model, which is advantageous when the defective characteristic is non-linear. It is suggested that the proposed system through experiments can be applied to the automation of O-ring defect detection.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.14-23
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• 2017

In high-density high-rise cities such as Hong Kong, buildings account for nearly 90% of energy consumption and 61% of carbon emissions. Therefore, it is important to study the design of buildings, especially high-rise buildings, to achieve lower carbon emissions in the city. The carbon emissions of a building consist of embodied carbon from the production of construction materials and operational carbon from energy consumption during daily operation (e.g., air-conditioning and lighting). An integrated analysis of both types of carbon emissions can strengthen the design of low carbon buildings, but most of the previous studies concentrated mainly on either embodied or operational carbon. Therefore, the primary objective of this study is to develop a holistic methodology framework considering both embodied and operational carbon, in order to enhance the sustainable design of low carbon high-rise buildings. The framework will be based on the building information modeling (BIM) technology because BIM can be integrated with simulation systems and digital models of different disciplines, thereby enabling a holistic design and assessment of low carbon buildings. Structural analysis program is first coupled with BIM to validate the structural performance of a building design. The amounts of construction materials and embodied carbon are then quantified by a BIM-based program using the Dynamo programming interface. Operational carbon is quantified by energy simulation software based on the green building extensible Markup Language (gbXML) file from BIM. Computational fluid dynamics (CFD) will be applied to analyze the ambient wind effect on indoor temperature and operational carbon. The BIM-based framework serves as a decision support tool to compare and explore more environmentally-sustainable design options to help reduce the carbon emissions in buildings.