• Journal of the Korean Geotechnical Society
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• v.39 no.9
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• pp.13-24
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• 2023

To investigate the stability of temporary retaining walls during excavation, it is essential to develop reverse analysis technologies capable of precisely evaluating the properties of the ground and a learning model that can assess stability by analyzing real-time data. In this study, we targeted excavation sites where the C.I.P method was applied. We developed a Deep Neural Network (DNN) model capable of evaluating the stability of the retaining wall, and estimated the physical properties of the ground being excavated using a Differential Evolution Algorithm. We performed reverse analysis on a model composed of a two-layer ground for the applicability analysis of the Differential Evolution Algorithm. The results from this analysis allowed us to predict the properties of the ground, such as the elastic modulus, cohesion, and internal friction angle, with an accuracy of 97%. We analyzed 30,000 cases to construct the training data for the DNN model. We proposed stability evaluation grades for each assessment factor, including anchor axial force, uneven subsidence, wall displacement, and structural stability of the wall, and trained the data based on these factors. The application analysis of the trained DNN model showed that the model could predict the stability of the retaining wall with an average accuracy of over 94%, considering factors such as the axial force of the anchor, uneven subsidence, displacement of the wall, and structural stability of the wall.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.173-184
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• 2019

The data processing of this study is based on the word data search in social media through textom and the big data analysis is carried out and three areas (2019 Gwangju World Swimming Championships, 2019 Gwangju World Swimming Masters Competition, 2019 World Swimming Championships Problem) was consistently handled through data collection and refinement in the web environment. We applied the collected words to the program of Ucinet6, visualized them, and conducted a CONCOR analysis to grasp the similar relationship of words and to identify the cluster of common factors. As a result of the analysis, the clusters related to the 2019 Gwangju World Swimming Championships mainly consisted of four major areas of recognition and perception, mainly searching for operational aspects related to the swimming championship, and the community related to the 2019 Gwangju World Swimming Masters Competition Is mainly searched for the promotion of the Masters Competition and the aspect of the competition divided into two areas of major recognition and peripheral recognition. The cluster related to the problems of the 2019 Gwangju World Swimming Championships is divided into five areas, And they are mainly searching for the place, operation, institution, event, etc. of the problem of the swimming championship.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.9-18
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• 2023

Predicting the compressive strength of high-performance concrete (HPC) is challenging because of the use of additional cementitious materials; thus, the development of improved predictive models is essential. The purpose of this study was to develop an HPC compressive-strength prediction model using an ensemble machine-learning method of combined bagging and stacking techniques. The result is a new ensemble technique that integrates the existing ensemble methods of bagging and stacking to solve the problems of a single machine-learning model and improve the prediction performance of the model. The nonlinear regression, support vector machine, artificial neural network, and Gaussian process regression approaches were used as single machine-learning methods and bagging and stacking techniques as ensemble machine-learning methods. As a result, the model of the proposed method showed improved accuracy results compared with single machine-learning models, an individual bagging technique model, and a stacking technique model. This was confirmed through a comparison of four representative performance indicators, verifying the effectiveness of the method.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• Composites Research
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• v.19 no.5
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• pp.28-33
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• 2006

In this paper, we have studied the complex permittivities and their influence on the design of microwave absorbers of E-glass fabric/epoxy composite laminates containing three different types of carbon-based nano conductive fillers such as carbon black (CB), carbon nano fiber (CNF) and multi-wall nano tube (MWNT). The measurements were performed fur permittivities at the frequency band of 0.5 GHz$\sim$18.0 GHz using a vector network analyzer with a 7 mm coaxial air line. The experimental results show that the complex permittivities of the composites depend strongly on the natures and concentrations of the conductive fillers. The real and imaginary parts of the complex permittivities of the composites were proportional to the filler concentrations. But, depending on the types of fillers and frequency band, the increasing rates of the real and imaginary parts with respect to the filler concentrations were all different. These different rates can have an effect on the thickness in designing the single layer microwave absorbers. The effect of the different rates at 10 GHz was examined by using Cole-Cole plot; the plot is composed of a single layer absorber solution line and measured permittivities from these three types of composites. Single layer absorbers of 3 different thicknesses using carbon nano materials were fabricated and the -10 dB band of absorbing performances were all about 3 GHz.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.9-16
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• 2009

While the broadband network and multimedia technology are being developed, the commercial market of digital contents as well as using IPTV has been widely spreading. In this background, Time-Shift system is developed for requirement of multimedia. This system is independent of Time but is not independent of Place and Occasion. For solving these problems, in this paper, we propose the TPO(Time, Place, Occasion)-Shift system for mobile multimedia devices. The profile that can be applied to the mobile multimedia devices is much different from that of the setter-box. And general mobile multimedia devices could not have such large memories that is for multimedia data. So it is important to continuously store and manage those multimedia data in limited capacity with mobile device's profile. Therefore we compose the basket in a way using defined time unit and manage these baskets for effective buffer management. In addition. since the file name of basket is made up to include a basket's time information, we can make use of this time information as DTS(Decoding Time Stamp). When some multimedia content is converted to be available for portable multimedia devices, we are able to compose new formatted contents using such DTS information. Using basket based buffer systems, we can compose the contents by real time in mobile multimedia devices and save some memory. In order to see the system's real-time operation and performance, we implemented the proposed TPO-Shift system on the basis of mobile device, MS340. And setter-box are desisted by using directshow player under Windows Vista environment. As a result, we can find the usefulness and real-time operation of the proposed systems.

• Land and Housing Review
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• v.14 no.2
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• pp.51-71
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• 2023

Based on the challenges encountered in the urban regeneration projects (general neighborhood-type) of Anjung District and Sinjang District in Pyeongtaek City, this study aims to explore the key factors of improvement measures for urban regeneration projects. Using the first survey conducted among shopping mall owners, employees, and residents, this study finds a significant level of awareness and very strong needs for urban regeneration projects. On the other hand, the overall satisfaction levels are observed to be low across the three factors: social, economic, and cultural. The second expert survey and the subsequent Analytic Hierarchy Process (AHP) analysis conducted for improvement measures reveal notable discrepancies in the prioritization of factors between administrative experts and practical experts. For the importance of administrative experts, the establishment of network-type regional governance was ranked first for the importance, followed by hosting events related to the U.S. military and long-term pre-market operations, and expanding exchange and cooperation between the U.S. Forces Korea and the community. For the importance of working-level experts, hosting U.S. military-related events and long-term pre-market operations was ranked first, while supporting U.S. military-related festivals and developing local natural landscape resources was ranked second. Our findings suggest the need for proactive measures such as attracting commercial facilities to stimulate demand from both the U.S. military and local residents, thereby revitalizing general neighborhood-type urban regeneration projects, developing programs for local tourism, and operating pre-market operations in the long run. Therefore, this study highlights the importance of regional government cooperation for urban regeneration projects.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.86-96
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• 2022

The development trend of jet fighter's avionics system architecture is the digitization of subsystem component functions, increased RF sensor sharing, fiber optic channel networks, and modularized integrated structures. The avionics system architecture of the fifth generation jet fighters (F-22, F-35) has evolved into an integrated modular avionics system based on computing function integration and RF integrated sensor systems. The integrated modular avionics system of jet fighters should provide improved combat power, fault tolerance, and ease of jet fighter control. To this aim, this paper presents the direction and requirements of the next-generation jet fighter's avionics system architecture through analysis of the fifth generation jet fighter's avionics system architecture. The core challenge of the integrated modularized avionic system architecture requirements for next-generation fighters is to build a platform that integrates major components and sensors into aircraft. In other words, the architecture of the next-generation fighters is standardization of systems, sensor integration of each subsystem through open interfaces, integration of functional elements, network integration, and integration of pilots and fighters to improve their ability to respond and control.