• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1697-1703
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• 2020

Sensor nodes that directly collect data from the surrounding environment have many constraints, such as power supply and memory size, thus efficient use of resources is required. In this paper, in a sensor node that receives location data of a vehicle on a lane, the data reception period is changed by the target's speed estimated by the Kalman filter and distance weight. For a slower speed of the vehicle, the longer data reception interval of the sensor node can reduce the processing time performed in the entire sensor network. The proposed method was verified through a traffic simulator implemented as MATLAB, and the results achieved that the processing time was reduced in the entire sensor network using the proposed method compared to the baseline method that receives all data from the vehicle.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.63-69
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• 2022

In this paper, we propose a new GPU-based framework for quickly calculating adaptive and continuous SDF(Signed distance fields), and examine cases related to rendering/collision processing using them. The quadtree constructed from the triangle mesh is transferred to the GPU memory, and the Euclidean distance to the triangle is processed in parallel for each thread by using it to find the shortest continuous distance without discontinuity in the adaptive grid space. In this process, it is shown through experiments that the cut-off view of the adaptive distance field, the distance value inquiry at a specific location, real-time raytracing, and collision handling can be performed quickly and efficiently. Using the proposed method, the adaptive sign distance field can be calculated quickly in about 1 second even on a high polygon mesh, so it is a method that can be fully utilized not only for rigid bodies but also for deformable bodies. It shows the stability of the algorithm through various experimental results whether it can accurately sample and represent distance values in various models.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.67-81
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• 2005

Recently, the interest and research on the development of new application services such as the Location Based Service and Telemetics providing the emergency service, neighbor information search, and route search according to the development of the Geographic Information System have been increasing. User's search in the spatio-temporal database which is used in the field of Location Based Service or Telemetics usually fixes the current time on the time axis and queries the spatial and aspatial attributes. Thus, if the range of query on the time axis is extensive, it is difficult to efficiently deal with the search operation. For solving this problem, the snapshot, a method to summarize the location data of moving objects, was introduced. However, if the range to store data is wide, more space for storing data is required. And, the snapshot is created even for unnecessary space that is not frequently used for search. Thus, non storage space and memory are generally used in the snapshot method. Therefore, in this paper, we suggests the Hash-based Spatio-Temporal Clustering Algorithm(H-STCA) that extends the two-dimensional spatial hash algorithm used for the spatial clustering in the past to the three-dimensional spatial hash algorithm for overcoming the disadvantages of the snapshot method. And, this paper also suggests the knowledge extraction algorithm to extract the knowledge for the path search of moving objects from the past location data based on the suggested H-STCA algorithm. Moreover, as the results of the performance evaluation, the snapshot clustering method using H-STCA, in the search time, storage structure construction time, optimal path search time, related to the huge amount of moving object data demonstrated the higher performance than the spatio-temporal index methods and the original snapshot method. Especially, for the snapshot clustering method using H-STCA, the more the number of moving objects was increased, the more the performance was improved, as compared to the existing spatio-temporal index methods and the original snapshot method.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Culinary science and hospitality research
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• v.17 no.3
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• pp.20-32
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• 2011

The purpose of this study is to analyze customers' behavior in using word-of-mouth(WOM) information about Korean local food restaurants. The questionnaire developed for this study was distributed to 500 customers living in Jeonbuk area and a total of 455 copies (91.0%) were used for analysis. The statistical analysis was conducted using SPSS Win(12.0). The results were summarized as follows. The recommendation of people experienced'($M=3.57{\pm}1.24$) and 'word-of-mouth through people around'($M=3.52{\pm}1.20$) were major word-of-mouth information sources of Korean local foods; 'taste of food'($M=4.16{\pm}1.15$) and 'service quality'($M=3.79{\pm}1.11$) were important attributes in word-of-mouth information. In addition, to the question about the reasons for recommending the restaurant to the people around, the most people replied that 'flavor, nutrition and quality of local foods can be kept only in the specific location' ($3.53{\pm}1.08$), followed by 'to keep the memory of the visit to the areas in mind through local foods'($3.51{\pm}1.03$). These results showed that people usually recommend a restaurant based on the quality of the food itself or local characteristics. As a result, it is deemed that word-of-mouth effect is an important factor for the spread of Korean local foods.

• Smart Structures and Systems
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• v.4 no.2
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• pp.221-232
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• 2008

This paper represents the final results of a research program sponsored by the European Commission through project WIND-CHIME ($\underline{W}$ide Range Non-$\underline{IN}$trusive $\underline{D}$evices toward $\underline{C}$onservation of $\underline{HI}$storical Monuments in the $\underline{ME}$diterranean Area), in which the possibility of using advanced seismic protection technologies to preserve historical monuments in the Mediterranean area is investigated. In the current research, the dynamic characteristics of two outstanding Mamluk-Style minarets, which similar minarets were reported to experience extensive damage during Dahshur 1992 earthquake, are investigated. The first minaret is the Qusun minaret (1337 A.D, 736 Hijri Date (H.D)) located in El-Suyuti cemetery on the southern side of the Salah El-Din citadel. The minaret is currently separated from the surrounding building and is directly resting on the ground (no vaults underneath). The total height of the minaret is 40.28 meters with a base rectangular shaft of about 5.42 ${\times}$ 5.20 m. The second minaret is the southern minaret of Al-Sultaniya (1340 A.D, 739 H.D). It is located about 30.0 meters from Qusun minaret, and it is now standing alone but it seems that it used to be attached to a huge unidentified structure. The style of the minaret and its size attribute it to the first half of the fourteenth century. The minaret total height is 36.69 meters and has a 4.48 ${\times}$ 4.48 m rectangular base. Field investigations were conducted to obtain: (a) geometrical description of the minarets, (b) material properties of the minarets' stones, and (c) soil conditions at the minarets' location. Ambient vibration tests were performed to determine the modal parameters of the minarets such as natural frequencies and mode shapes. A $1/16^{th}$ scale model of Qusun minaret was constructed at Cairo University Concrete Research Laboratory and tested under free vibration with and without SMA wire dampers. The contribution of SMA wire dampers to the structural damping coefficient was evaluated under different vertical loads and vibration amplitudes. Experimental results were used along with the field investigation data to develop a realistic 3-D finite element model that can be used for seismic risk evaluation of the minarets. Examining the updated finite element models under different seismic excitations indicated the vulnerability of such structures to earthquakes with medium to high a/v ratio. The use of SMA wire dampers was found feasible for reducing the seismic risk for this type of structures.

• Women's Health Nursing
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• v.5 no.1
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• pp.146-165
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• 1999

The purpose of this paper was to identify the performance of health promoting lifestyles and health perception over 18 years old women living Wonju city so that the results will be based for setting up women's health nursing center. The subjects were 1080 women selected by stratified and purposive sampling. The data were collected by self reporting questionnaire and interview from May to June, 1998. Data were analyzed by SPSS win program. The results were as follows : 1. The range of age was 18-84 years, The proportion according to women's lifecycle was premarital group 20.0%, delivery and rearing group 49.9%, over middle aged-elderly group 29.8%. 2. The mean menarchial age was 15.2 and menopausal age was 48. Mean frequenices of pregnancy is 2.4 and artificical abortion rate is 36.4%. Primary cause of abortion was unwanted babies 42.8%. The practice rate of family planning was 79.4% and permanent sterilization rate was 37.6%. 3. Fatigue was predominated problem in target population. Depression and headache was predominated in premarital group, headache and nervous felling in delivery and rearing group, arthritis and loss of memory in over middle aged-elderly group. 4. Only 13.7% of the target population make some efforts for their health in compare to 85.9% have attention for their health. Perception of unhealthy rate was 9.1% in premarital group, 24.8% in delivery and rearing group, 30.1% in middle aged-elderly group. 5. The average score of the HPLP(Health Promoting Lifestyle Profile) was 2.41. The variable with the highest degree of performance was interpersonal relationship, whereas the one with the lowest degree was the professional health maintenance. The significant difference was found in HPLP according to age, residential area, marital status, educational level, income level. 6. Majority(95.1%) of the target population agreed on necessity for women's health nursing center. Proper location area was presented to women's center and public health center. The priority for health education program was proper diet, family health, stress management, and exercise. In conclusion, we should prepare the education program for women's health according to women's lifecycle, because health perception, HPLP, and education program needed was differentiated in women's lifecycle. Also we suggest that women's health nursing center based community was needed for proper management of women's health.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.129-136
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• 2017

Geographic Information System The geographic information system (GIS) has been limited to the government and some public sectors. Recently, the market has been diversified by combining with other areas such as mobile and CRM (Customer Relationship Management). The development direction of GIS technology in the 21st century is Web GIS, 3D GIS, mobile GIS, LBS, etc. as general technology for GIS application system development and spatial information service. In this study, we developed a new concept marking nail (a marking nail with built - in intelligent storage memory device) from the function of simple positioning of a marking nail related to a previously used underground item,, Burial depth, pipe thickness, piping material, management agency, contractor, contact, etc.) and store it in DB server, if necessary.Make it available in the right place. Through this research, it is possible to prevent and minimize various accidents caused by irregular excavation works, etc., and to provide information for establishing countermeasures related to sink holes. In order to provide systematic and reliable information on underground burial management, it was proposed to input information conveniently in the field, and the purpose was to reduce the incidence of buried underground pipes absolutely.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.286-297
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• 2018

In the present study, wave measurements at KOGA-W01 were analyzed and then the numerical wind waves simulations have been conducted to investigate the characteristics of wind waves in the Yellow sea. According to the present analysis, even though the location of the wave stations are close to the coastal region, the deep water waves are prevailed due to the short fetch length. Chun and Ahn's (2017a, b) numerical model has been extended to the Yellow Sea in this study. The effects of tide and tidal currents should be included in the model to accommodate the distinctive effect of large tidal range and tidal current in the Yellow Sea. The wave hindcasting results were compared with the wave measurements collected KOGA-W01 and Kyeockpo. The comparison shows the reasonable agreements between wave hindcastings and measured data, however the model significantly underestimate the wave period of swell waves from the south due to the narrow computational domain. Despite the poorly prediction in the significant wave period of swell waves which usually have small wave heights, the estimation of the extreme wave height and corresponding wave period shows good agreement with the measurement data.