• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.154-162
• /
• 2022

Purpose: The government intends to come up with measures to revitalize safety management at construction sites to shift safety management at construction sites from human capabilities to system-oriented management systems using advanced technologies AIoT and Mobile technologies. Method: The construction site safety management monitoring system using AIoT and Mobile technology conducted an experiment on the effectiveness of the construction site by applying three algorithms: virtual fence, fire monitoring, and recognition of not wearing a safety helmet. Result: The number of workers in the experiment was 215 and 7.61 virtual fence intrusion was 3.5% compared to the number of subjects and 0.16 fire detection were 0.07% compared to the subjects, and the average monthly rate of not wearing a safety helmet was 8.79, 4.05% compared to the subjects. Conclusion: It was found that the construction site safety management monitoring system using AIoT and Mobile technology has a valid effect on the construction site.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.4
• /
• pp.410-418
• /
• 2022

Channel reliability estimation for iterative codes such as turbo codes is very important factor in time varying underwater acoustic channel, an incorrect estimation of channel reliability induced performance degradation. Therefore, this paper presents an optimal channel reliability estimation method for turbo coded FSK signal with rate of 1/3. The estimated BER algorithm is a method that can estimate the reliability of received data by comparing received data and decoded data, and we determine optimal channel reliability by using the method. In order to analyze the performance, the experiment was conducted on a lake in Munkyeong city by moving in the range of 300 m to 500 m. At the result of applying presented method to failed decoding packets, we confirm all packets are decoded successfully.

• Journal of People, Plants, and Environment
• /
• v.24 no.4
• /
• pp.441-450
• /
• 2021

Background and objective: The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods: After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results: Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m² and 14,897 m³, respectively, and the green coverage and volume measured through the field survey were 6,339 m² and 17,167 m³. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion: The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

• Journal of Fashion Business
• /
• v.26 no.1
• /
• pp.1-15
• /
• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.2
• /
• pp.210-217
• /
• 2022

Passive source depth estimation has been studied for decades since the source depth can be used for target classification, target tracking, etc. The purpose of this paper is to solve the problem of ambiguity in the previous paper [S.-il. Cho et al. (in Korean), J. Acoust. Soc. Kr. 38, 120-127 (2019)] that source depth is estimated in two points. The patterns of phase shift of Channel Impulse Response(CIR) reflected in ocean surface and bottom is used for removing ambiguity of the source depth estimation, and after removing ambiguity, source depth is estimated at one point through the intersection of CIR. In order to extract CIR in case of unknown source signal and continuous signal or noise, Ray-based blind deconvolution is used. The proposed algorithm is demonstrated through numerical simulation in ocean waveguide.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.2
• /
• pp.176-182
• /
• 2023

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.551-561
• /
• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.2 no.4
• /
• pp.545-551
• /
• 1998

The Radio communication by existing SSB, VHF, etc. in a coast station and a base station for military affairs is still used to a very important the device of information delivery or transmitting and receiving by the remote controller to using to the exclusive cable for a equipment established at a long distance. When a number of consumer to connected and operated by a number of transceiver is essential for a circuit controller of ICS, in KOREA, is devoted by import to considerable quantity because of to be delayed development of this field. This Paper has been realized to optimal algorithm and designing of a circuit connection controller by multi-processor to pre-stage for the development of ICS. The H/W is composed able to remote control to circuit connector with the several slave processor and a processor for master, and this has taken possible through without any obstacle to communication circuits of a control signal by FSK system. The S/W make possible monitoring for communication condition of other circuits by means of a serial communication system by the multi-processing. This paper has been studied for connecting to a circuits wished to rapidly and precisely by the full application to a interrupt technique. A technique to control by remote to a number of transceiver is a way increasing to application for a frequency resource of the limited MF/SF, VHF and the existing radio communication technique. According to, this paper will achieve to be the reduction of energy & equipment and multiplicity of information delivery in the general communication and disposal to rapid and exact for the important communication as distress, urgency and safety on the sea.

• Journal of Korea Multimedia Society
• /
• v.7 no.11
• /
• pp.1597-1609
• /
• 2004

A lot of lipreading system has been proposed to compensate the rate of speech recognition dropped in a noisy environment. Previous lipreading systems work on some specific conditions such as artificial lighting and predefined background color. In this paper, we propose a real-time lipreading system which allows the motion of a speaker and relaxes the restriction on the condition for color and lighting. The proposed system extracts face and lip region from input video sequence captured with a common PC camera and essential visual information in real-time. It recognizes utterance words by using the visual information in real-time. It uses the hue histogram model to extract face and lip region. It uses mean shift algorithm to track the face of a moving speaker. It uses PCA(Principal Component Analysis) to extract the visual information for learning and testing. Also, it uses HMM(Hidden Markov Model) as a recognition algorithm. The experimental results show that our system could get the recognition rate of 90% in case of speaker dependent lipreading and increase the rate of speech recognition up to 40～85% according to the noise level when it is combined with audio speech recognition.

• Journal of KIISE:Software and Applications
• /
• v.31 no.4
• /
• pp.411-419
• /
• 2004

When the imaging object rotates in image plane during MRI scan, its rotation causes phase error and non-uniform sampling to MRI signal. The model of the problem including phase error non-uniform sampling of MRI signal showed that the MRI signals corrupted by rotations about an arbitrary center and the origin in image plane are different in their phases. Therefore the following methods are presented to improve the quality of the MR image which includes the artifact. The first, assuming that the angle of 2-D rotational motion is already known and the position of 2-D rotational center is unknown, an algorithm to correct the artifact which is based on the phase correction is presented. The second, in case of 2-D rotational motion with unknown rotational center and unknown rotational angle, an algorithm is presented to correct the MRI artifact. At this case, the energy of an ideal MR image is minimum outside the boundary of the imaging object to estimate unknown motion parameters and the measured energy increases when the imaging object has an rotation. By using this property, an evaluation function is defined to estimate unknown values of rotational angle at each phase encoding step. Finally, the effectiveness of this presented techniques is shown by using a phantom image with simulated motion and a real image with 2-D translational shift and rotation.