• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.709-719
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• 2023

In general, most of the electrical equipment responsible for control within power plants is housed in self-standing cabinets. These cabinets are typically fixed to a slab using post-installed anchors. Although the fixation method of using post-installed anchors provides stability, there is a risk of conductor failure due to external forces, including moments. However, the performance assessment of current anchors is only evaluated through uniaxial material tests. Therefore, the primary purpose of this study is to compare the static performance of post-installed anchors, considering on-site installation conditions, with their performance in material tests and to analyze the behavioral characteristics of the anchors. While conducting experiments using actual cabinets would be ideal, practical and spatial constraints make this approach difficult. As an alternative, experiments were conducted using a test specimen consisting of a steel column and a support. As a result, the pull-out performance of anchors reflecting on-site installation conditions was measured to be about 10% higher than that observed in material tests. The trends in load reduction and the point of maximum performance for the anchors also differed. To verify the reliability of the experimental study, a 3D FEM analysis was performed, which will provide predictive information on the loads transferred to the post-installed anchors for structural performance evaluations of electrical cabinets using shaking table test in the future.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.255-266
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• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.31-38
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• 2023

In this study, runoff characteristics analysis was conducted as a basic research to establish a forecasting and warning system for flood risk areas in small mountainous basins in South Korea. The Danyang 1 Bridge basin located in Danyang-gun, Chungcheongbuk-do was selected as the study basin, and the watershed characteristic factors were calculated using Q-GIS based on the digital elevation model (DEM) of the basin. In addition, nine heavy rainfall events were selected from 2020 to 2023 using hydrometeorological data provided by the National Water Resources Management Comprehensive Information System. HEC-HMS rainfall-runoff model was used to analyze the runoff characteristics of small mountainous basins, and rainfall-runoff model simulation was performed by reflecting 9 heavy rainfall events and calculated basin characteristic factors. Based on the rainfall-runoff model, parameter optimization was performed for six heavy rain events with large error rates among the simulated events, and the appropriate parameter range for the Danyang 1 Bridge basin, a small mountainous basin, was calculated to be 0.8 to 3.4. The results of this study will be utilized as foundational data for establishing flood forecasting and warning systems in small mountainous basin, and further research will be conducted to derive the range of parameters according to basin characteristics.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.35-55
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• 2003

The purpose of this study is to review the previous studies on the safety problems in Korea and to propose a psychological total safety system model. The model consisted of four agents; the government as the safety management agent, the suppliers of safety goods and services, consumer of safety goods and services, and civil movement institutions for safety. It was emphasized that the culture specific social representations of safety and accident have emerged in the course of rapid industrialization process in Korea during last 30 years. We delineated the social representations of the Korean people on safety and accident according to the model. A psychological analysis of drinking and driving behavior was performed as an application of the model. It was emphasized that safety psychologists have to develope and to apply the knowledge and the information from human engineering psychology and applied social psychology on safety and accidents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.183-189
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• 2023

This paper proposes a new JPEG format, All-in-JPEG, which can include not only multiple photos but also various media such as audio and text by extending the JPEG format. All-in-JPEG add images, audio, and text at the existing JPEG file, and stores meta information by utilizing the APP3 segment of JPEG. With All-in-JPEG, smartphone users can save many pictures taken in burst shots in one file, and it is also very convenient to share them with others. In addition, you can create a live photo, such as saving a short audio at the time of taking a photo or moving a part of the photo. In addition, it can be used for various applications such as a photo diary app that stores images, voices, and diary text in a single All-in-JPEG file. In this paper, we developed an app that creates and edits All-in-JPEG, a photo diary app, and a magic photo function, and verified feasibility of the All-in-JPEG through them.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.483-494
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• 2023

Measurement of the physical properties of rocks or minerals is an important factor in determining the distribution of the underground medium as well as mineral resource investigations. Resistivity and induced polarization, which are widely used in Korea, are methods for measuring electrical properties, which are representative properties of obtaining subsurface information. In order to precisely analyze the exploration data obtained from various sites, it is important to accurately measure the material properties. Electrical properties of rock is measured using two-electrode or four-electrode method. Compared to the four-electrode method, the two-electrode method is generally used because it is very easy to contact the sample and the electrode, but there is a problem in that the impedance of the electrode and the sample is measured together. In this study, the time-domain the induced polarization effects were measured using the 2-electrode method and the 4-electrode method for artificial samples mixed with graphite and cement having induced polarization characteristics, and the results were compared. Although the 4-electrode method has difficulties in installing potential electrodes, it was confirmed that it is effective in measuring electrical properties because it can reduce the problem caused by the impedance of potential electrodes compared to the 2-electrode method.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.867-874
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• 2023

Recently, many problems are occurring in the bee ecosystem due to rapid climate change. The decline in the bee population and changes in the flowering period are having a huge impact on the harvest of bee-keepers. Since it is impossible to continuously observe the beehives in the hive with the naked eye, most people rely on knowledge based on experience about the state of the hive.Therefore, interest is focused on smart beekeeping incorporating IoT technology. In particular, with regard to swarming, which is one of the most important parts of beekeeping, we know empirically that the swarming time can be determined by the sound of the queen bee, but there is no way to systematically analyze this with data.You may think that it can be done by simply recording the sound of the queen bee and analyzing it, but it does not solve various problems such as various noise issues around the hive and the inability to continuously record.In this study, we developed a system that records queen bee sounds in a real-time cloud system and analyzes sound patterns.After receiving real-time analog sound from the hive through multiple channels and converting it to digital, a sound pattern that was continuously output in the queen bee sound frequency band was discovered. By accessing the cloud system, you can monitor sounds around the hive, temperature/humidity inside the hive, weight, and internal movement data.The system developed in this study made it possible to analyze the sound patterns of the queen bee and learn about the situation inside the hive. Through this, it will be possible to predict the swarming period of bees or provide information to control the swarming period.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.