• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.465-473
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• 2019

This paper is meaningful as the first case where a 4 - sided hull-fixed phased array radar was installed on a mast separated from Korea and the alignment was verified. The mechanical alignment method was studied for accurately mounting two separate masts for naval ships and the 3D scanner for alignment. Hull-fixed phased array radar uses very high frequency, so the short wavelength can cause a phase difference of the device due to the small positional error. Since the array antenna is fixed with the hull, it has higher accuracy control than the rotary radar for 4 array surfaces. The study describes a method of checking the flatness of two radar masts manufactured at a factory, a method of aligning masts in a shipyard, and a method of aligning four array pad mounting surfaces. As a tool for this, a 3D laser scanner and a software-based method for comparing survey results with 3D CAD are used. This paper is meaningful as the first example of installing a four-sided hull-fixed phased array radar on a separate mast from a Korean naval ship and deriving a mechanical alignment method.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.2
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• pp.13-24
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• 2020

This study derives the characteristics of the private external space planning in multi-family housing through the analysis of the good case built after 2000 in Europe. First, the cases were categorized into block or block perimeter, linear and point type to examine the relationship between the type of building in urban context and the location of private external space. By block or block perimeter and linear type, private external spaces are planned in the inner courtyards or open space between buildings used as common space for residents, inducing communications between neighbors. And the direction of private external space depends on the arrangement of the building mass in urban context. In the classification as point type, there are many cases, where private external spaces are arranged in all directions, connected almost all interior spaces. Second, based on the above results, the planned characteristics of the private external space are derived by dividing it into three categories: intermediated space between inside and outside, intermediate space between private and public /individual and collective space and the identity of the intermediate space. (1) In most cases, direction, size of enclosed area and location of private extern space is designed to fit the surrounding context, so residents can perceive as much of the assets of the surrounding environment as possible, and it can be used as an extended area of living space. In another cases, it is divided into various sub-areas to experience the spatial transition from inside to outside or vice versa. 2) The private external space, which is placed in a courtyard or in a collective open space, is partially enclosed and blocked, allowing interaction with the neighbors without pressure. Along the street, they are designed to allow residents to experience the vitality of the city and to be formative element of the facade, which could confidently reveal the lifestyle and taste of residents. 3) By some of point types, which facade is three-demensional layer as a habitable external space, the private external space is very flexible for use. This intermediate space is composed of diverse spaces for various needs, or it has generous size with positional conditions connected with all interior spaces to be used multi-functional.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.60 no.8
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• pp.390-395
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• 2017

Background and Objectives With increasing frequency of car accidents, patients of dizziness caused by car accidents are also increasing. Various types of dizziness or vertigo can occur from car accidents depending on different injury mechanisms. Since accurate diagnosis is important for providing proper treatments, we evaluated clinical characteristics related to vestibular function of patients with dizziness caused car accidents. Subjects and Method In this retrospective case review study that runs from January 2011 to March 2013, a total of 82 patients with dizziness following car accident were enrolled consecutively. We analyzed the final diagnosis of dizziness according to different mechanisms of injury during car accident through clinical record review. Patients who developed dizziness within one month of car accident were included, excluding those who had temporal bone fracture and previous history of dizziness. Results Of the different types observed, 36.6% was head injury, 24.4% whiplash injury, 3.7% complex injury, 2.4% others and the rest was unknown. In the final diagnosis, the different types included 36.6% benign paroxysmal positional vertigo (BPPV), 23.2% unclassifiable dizziness, 18.3% cervical vertigo, 7.3% labyrinthine concussion, 3.7% BPPV with labyrinthine concussion and the rest was others. Of the different types of dizziness symptoms, 58.5% was headache, 45.1% was audiologic symptoms, and others included earfullness, tinnitus and hearing disturbance. Tinitogram and pure tone audiogram results show that 2.9% (27 people) of patients have tinnitus and 7.3% (6 people) have hearing disturbance. Conclusion An accurate diagnosis and timely management would be very important in forming a proper approach for post traumatic vertigo patients.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.127-133
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• 2021

A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.80-91
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• 2021

The purpose of this study is to present the applicability to the effective survey into the actual condition of lands such as analysis of occupied location of government owned lands based on orthoimages created from aerial photographs taken by UAV. The boundary point coordinates and areas of the parcels were observed respectively by VRS-GNSS surveying and orthoimages for each land use of two categories of land, i.e. building site and farmland. As a result of comparing boundary point coordinates and areas extracted from UAV orthoimages with VRS-GNSS surveying data which were used as reference data, the RMS error of the coordinates for the boundary points was ±0.074m for both X and Y in the building site, and ±0.150m and ±0.127m for the X and Y respectively in the farmland. The positional error of the boundary point was 1.7~ 2 times higher in the farmland than in the building site where the boundary points were relatively clear. The RMS error of ±8.964㎡ of areas in the farmland was 4.7 times higher than that of ±1.898㎡ of areas in the building site. The area errors of all 22 parcels measured from the orthoimage were found to be within the allowed error range, indicating that it is feasible to apply the orthoimage generated by UAV to survey of government owned lands in terms of accuracy.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.1-22
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• 2022

Lavie's perceptual load theory (Lavie, 1995) proposes that the influence of distractors would be blocked as the load gets higher. Studies of perceptual load have usually adopted the flanker task, developed by Eriksen and Eriksen (1974), which measures reaction time on the target flanked by distractors. In the post-cueing forced task, participants should report the identity of the target cued later, and negative repetition effect (NRE) has often been observed. NRE means the effect that the accuracy of identification is worse when the target is flanked by the same nontargets than when flanked by different nontargets. This study has tried to check whether perceptual load has an effect on identification rate and NRE. Experiment 1 manipulated the similarity between targets and a distractor, and observed a tendency of NRE, but not the effect of perceptual load. Experiment 2 used 4, 2 (in two kinds of diagonal arrangement), or none distractors of the same identity to burden more perceptual load. NRE was significant and perceptual load showed significance but not a linear trend. Experiment 3 checked again whether NRE would be varied according to two levels of perceptual load strengthened by positional variability of load stimuli, but did not find the effect of perceptual load. It is concluded that perceptual load might have a limited effect on the early stage of perceptual processing due to divided attentional processing of the targets briefly exposed. Implications of this study were discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.207-215
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• 2022

This research has been focused on accessing precision and accuracy of UAV (Unmanned Aerial Vehicle)-derived 3-D surveying coordinates. To this end, a highly precise and accurate testing control network had been established by GNSS (Global Navigation Satellite Systems) campaign and its network adjustment. The coordinates of the ground control points and the check points were estimated within 1cm accuracy for 95% of the confidence level. FC330 camera mounted on DJI Phantom 4 repeatedly took aerial photos of an experimental area seven times, and then processed them by two widely used software packages. To evaluate the precision and accuracy of the aerial surveys, 3-D coordinates of the ten check points which automatically extracted by software were compared with GNSS solutions. For the 95% confidence level, the standard deviation of two software's result is within 1cm, 2cm, and 4cm for the north-south, east-west, and height direction, and RMSE (Root Mean Square Error) is within 9cm and 8cm for the horizontal, vertical component, respectively. The interest is that the standard deviation is much smaller than RMSE. The F-ratio test was performed to confirm the statistical difference between the two software processing results. For the standard deviation and RMSE of most positional components, exception of RMSE of the height, the null hypothesis of the one-tailed tests was rejected. It indicates that the result of UAV photogrammetry can be different statistically based on the processing software.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.363-369
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• 2021

High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.