• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.101-109
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• 2018

Recently, the improvement of virtual reality and augmented reality technologies leverages many new technologies like the virtual study room, virtual architecture room. Such virtual worlds require free handed drawing technology such as writing descriptions of formula or drawing blue print of buildings. In nature, lots of view point modifications occur when we walk around inside the virtual world. Especially, we often look some objects from near to far distance in the virtual world. Traditional drawing methods like using fixed size image for drawing unit is not produce acceptable result because they generate blurred and jaggy result as view distance varying. We propose a novel method which robust to the environment that produce lots of magnifications and minimizations like the virtual reality world. We implemented our algorithm both two dimensional and three dimensional devices. Our algorithm does not produce any artifacts, jaggy or blurred result regardless of scaling factor.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.85-94
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• 2012

Lane marking detection is essential to both ITS and DAS systems. The objective of this paper is to provide more robust technique for lane marking detection than traditional techniques by using scale-space technique. Variable thresholding that is based on the local statistics may be very effective for detecting such objects as lane markings that have prominent intensities. However, such techniques that only rely on local statistics have limitations containing irrelevant areas as well. We reduce the candidate areas by combining the variable thresholding result with cost-efficient horizontal 1D LoG filtered scale space. Through experiments using practical images, we could achieve significant improvement over the techniques based not only on the variable thresholding but also on the Hough transform that is another very popular technique for this purpose.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.8
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• pp.543-548
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• 2003

In this paper, we have proposed and fabricated a two-axis rotational micro-mirror with large tilt angle. Such a micro-mirror is a key element for N$\times$N high capacity optical cross-connect switches. The micro-mirror is required to have large tilt angle to increase the capacity of the cross-connect switches. For larger micro-mirror tilt angle between the grounded mirror plate and the bottom electrode is to be large enough to provide space for the tilting of the mirror. For our proposed structure, the gap was produced in such a way that the grounded mirror plate and the bottom electrode were made separately in different substrates by using the bulk micromachining technology, and combined later by employing self-align technique. As a result, a large tilt angle has been achieved without using additional actuators. The measured tilt angles were as large as $\pm$5.5$^{\circ}$ and $\pm$8.4$^{\circ}$ in the x and y direction respectively, and the pull-in voltages for the two directions were 380 V and 275 V respectively. Finally the fabricated mirror was successfully utilized to steer the optical beam. To our knowledge, our micro-mirror has the best performance among the micro-mirrors reported internationally so far.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.447-455
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• 2019

Since the forest type map in Korea has been mostly constructed every five years, the forest information from the map lacks up-to-date information. Forest research has been carried out by aerial photogrammetry and field surveys, and hence it took a lot of times and money. The vertical structure of forests is an important factor in evaluating forest diversity and environment. The vertical structure is essential information, but the observation of the vertical structure is not easy because the vertical structure indicates the internal structure of forests. In this study, the index map and texture map produced from KOMPSAT-3/3A/5 satellite images and the canopy information generated by the difference between DSM (Digital Surface Model) and DTM (Digital Terrain Model) were classified using the artificial neural network. The vertical structure of forests of single and multi-layer forests was classified to identify 81.59% of the final classification result.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.91-97
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• 2022

Recently, as per a representative education method to develop core capabilities (such as critical thinking, communication, collaboration, and creativity) problem based learning (PBL) has been widely adopted in universities. Two important features of PBL are 'collaboration between team members' and 'participation based self-directed learning'. These two features should be satisfied in online education, although it is difficult due to the limitation on space and time in the COVID-19 pandemic. This paper presents a new design of PBL class in Metaverse, based on improving the online PBL class operated in the previous semesters in the H university. In the proposed PBL class, students are able to display materials (e.g., image, pdf, video files) in 3D virtual space, that are related to problem solving. The 3D virtual space is called gallery in this paper. The concept of gallery allows for active participation of students. In addition, the gallery can be used as a tool for collaborative meeting or for final presentation. If possible, the new design of PBL class will be applied and its effectiveness will be analyzed.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.7
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• pp.429-434
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• 2016

Among various De-NOx technologies, Urea-based Selective Catalytic Reduction (SCR) systems are known to be the most effective in marine diesel applications. The spraying and mixing behavior of the urea-water solution has a decisive effect on the system's net efficiency. Therefore, in this study, the spray behavior and ammonia uniformity with and without a static mixer were analyzed by CFD in order to optimize the SCR system. The results showed that the static mixer significantly affected the uniformity of velocity and ammonia concentration. Static mixers may be especially suited for marine SCR systems with space constraints.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.3-20
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• 2022

Recently, prior to the commercialization of urban air mobility (UAM), the importance of R&D for air transportation-related industries in urban areas has significantly increased. To create a UAM environment, research is being conducted on personal air vehicles (PAVs). They are key means of air transportation, but research on the physical factors influencing their passengers is relatively insufficient. In particular, because the PAV is expected to be used as a living space for the passengers, research on the effects of the physical elements generated in the PAV on the human body is essential to design an interior space that supports the in-vehicle activities of the passengers. Therefore, the purpose of this study is to derive the constraint factors that affect the human body due to the air navigation characteristics of the PAV and to understand the impact of these constraint factors on the bodies of the passengers performing in-vehicle activities. The results of this study indicate that when the PAV was operated at less than 4,000 ft, which is the operating standard, the constraint factors were noise, vibration, and motion sickness caused by low-frequency motion. These constraint factors affect in-vehicle activity; thus, the in-vehicle activities that can be performed in a PAV were derived using autonomous cars, airplanes, and PAV concept cases. Furthermore, considering the impact of the constraint factors and their levels on the human body, recommended constraint factor criteria to support in-vehicle activities were established. To reduce the level of impact of the constraint factors on the human body and to support in-vehicle activity, the seat's shape and built-in functions of the seat (vibration reduction function, temperature control, LED lighting, etc.) and external noise reduction using a directional speaker for each individual seat were recommended. Moreover, it was suggested that interior materials for noise and vibration reduction should be used in the design of the interior space. The contributions of this study are the determination of the constraint factors affecting the in-vehicle PAV activity and the confirmation of the level of impact of the factors on the human body; in the future, these findings can be used as basic data for suitable PAV interior design.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.225-233
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• 2008

Rapid advancement information and communication technologies has introduced various dimension of e-Learning environment such as u-learning(ubiquitous learning), m-learning(mobile learning) and t-learning(television learning). These technologies enabled learners to access learning contents through variety of devices with more flexibility and consistency. In order to implement learning through these multiple environments, basically it is necessary to acquire and process the platform information that contains properties and status of the web-accessing devices. In this study, we introduce the design and implementation of a Platform Analyzer Model which is essential for learning systems that support multi-platform environment. We also present a Interactive DTV-Centered multi-platform learning environment framework using PC, PDA or Mobile phone. Finally, we will discuss the possibility of the multi-platform learning environment with sample scenario and contents.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.