• Geomechanics and Engineering
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• v.30 no.2
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• pp.139-151
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• 2022

The mechanical properties of expansive soil are very unstable, highly sensitive to water, and thus easy to cause major engineering accidents. In this paper, the expansive soil foundation pit project of the East Huada Square in the eastern suburb of Chengdu was studied, the moisture content of the expansive soil was considered as an important factor that affecting the mechanics properties of expansive soil and the stability of the non-equal-length double-row piles in the foundation pit support. Three groups of direct shear tests were carried out and the quantitative relationships between the moisture content and shear strength τ, cohesion c, internal friction angle φ were obtained. The effect of cohesion and internal friction angle on the maximum displacement and the maximum bending moment of piles were analyzed by the finite element software MIDAS/GTS (Geotechnical and Tunnel Analysis System). Results show that the higher the moisture content, the smaller the matrix suction, and the smaller the shear strength; the cohesion and the internal friction angle are exponentially related to the moisture content, and both are negatively correlated. The maximum displacement and the maximum bending moment of the non-equal length double-row piles decrease with the increase of the cohesion and the internal friction angle. When the cohesion is greater than 33 kPa or the internal friction angle is greater than 25.5°, the maximum displacement and maximum bending moment of the piles are relatively small, however, once crossing the points (the corresponding moisture content value is 24.4%), the maximum displacement and the maximum bending moment will increase significantly. Therefore, in order to ensure the stability and safety of the foundation pit support structure of the East Huada Square, the moisture content of the expansive soil should not exceed 24.4%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.203-207
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• 2023

Recently, real-time streaming services are gaining popularity among the MZ generation and the market size is continuously growing. Pre-recorded and edited videos only show one-way communication, but real-time streaming services have the advantage of responding immediately to questions and requests from users, as they enable two-way communication. With the transition from face-to-face culture to non-face-to-face culture due to the COVID-19 pandemic, the number of users communicating in real-time video for activities such as classes, meetings, and leisure has dramatically increased. However, as real-time streaming services become more active and diverse generations participate, there is a problem of conflicts arising from language differences, including the use of neologisms. To address this issue, this paper proposes a method of collecting the meaning of neologisms through the Wikipedia API and presenting them to each other, so that they can understand each other's intentions.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.598-610
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• 2022

Avoiding a fault zone would be a best practice for safety in underground construction, which is only sometimes possible because of many restrictions and other field conditions. For instance, there is an ongoing conception of Korea-Japan subsea tunnels that inevitably cross a massive fault system in the Korea Strait. Therefore it was deemed necessary to find an efficient way of predicting the likely behaviour of underground structures under fault slip. This paper presents the findings from simple numerical analysis for investigating the stress induced at a normal fault with a dip of 45 degrees. We used a boundary element software that assumed constant displacement discontinuity, which allowed the displacement to be estimated separately at both the fault's hangingwall and footwall sides. The results suggested that a principal stress rotation of 45 degrees occurred at the edges of the fault during the slip, which was in agreement with the phenomenon for fault plane suggested in the body of literature. A simple numerical procedure presented in this paper could be adopted to investigate other fault-related issues associated with underground structure construction.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.141-148
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• 2023

The algebraic reconstruction technique is one of the reconstruction methods in CT and shows good image quality against noise-dominant conditions. The number of iteration is one of the key factors determining the execution time for the algebraic reconstruction technique. However, there are some rules for determining the number of iterations that result in more than a few hundred iterations. Thus, the rules are difficult to apply in practice. In this study, we proposed a method to determine the number of iterations for practical applications. The reconstructed image quality shows slow convergence as the number of iterations increases. Image quality 𝜖 < 0.001 was used to determine the optimal number of iteration. The Shepp-Logan head phantom was used to obtain noise-free projection and projections with noise for 360, 720, and 1440 views were obtained using Geant4 Monte Carlo simulation that has the same geometry dimension as a clinic CT system. Images reconstructed by around 10 iterations within the stop condition showed good quality. The method for determining the iteration number is an efficient way of replacing the best image-quality-based method, which brings over a few hundred iterations.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.637-647
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• 2022

Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1039-1046
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• 2022

After the COVID-19 pandemic, the spread of the untact culture and the Fourth Industrial Revolution, which generates various types of data, generated so much data that it was not compared to before. This led to higher data throughput, revealing little by little the limitations of the existing network system centered on vendors and hardware. Recently, SDN technology centered on users and software that can overcome these limitations is attracting attention. In addition, SDN-based load balancing techniques are expected to increase efficiency in the load balancing area of the server cluster in the data center, which generates and processes vast and diverse data. Unlike existing SDN load distribution studies, this paper proposes a load distribution technique in which a controller checks the state of a server according to the occurrence of an event rather than periodic confirmation through a monitoring technique and allocates a user's request by weighting it according to a load ratio. As a result of the desired experiment, the proposed technique showed a better equal load balancing effect than the comparison technique, so it is expected to be more effective in a server cluster in a large and packet-flowing data center.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1121-1128
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• 2022

Information about the present invention is made available for business use. You are helping to use the LCD, you can't use the LCD screen. During software configuration, Raspbian was used to provide the system environment. We made our way through the menu and made our financial through play. It provides various information such as weather, weather, apps, streamer music, and web browser search function, and it can be charged. Currently, the 'Google Assistant' will be provided through the GUI within a predetermined time.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.41-50
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• 2023

Recently, as the Coronavirus disease 2019 (COVID-19) prolongs along with the development of artificial intelligence technology, a non-contact society has become commonplace. Many companies are promoting digital transformation and the activation of artificial intelligence introduction to respond to this which leads to dramatic increase of demand for Chatbot. In addition, a Chatbot has reached the point of processing business transactions from responding simple inquiries. However, it is necessary to develop an API to interface with the legacy system and there are many difficulties in connecting. To solve this, it is becoming important to establish a hybrid Chatbot environment through RPA interface. Recently, the combination of RPA and Chatbot is considered an effective tool for handling many business processes. But, there are many difficulties due to the lack of interface cases and the difficulty in finding a method to development them. This study suggests a method for building a hybrid Chatbot which is an interface Chatbot(Conversational UX) and RPA(Task Automation) from the perspective of hyper-automation based on actual development cases and review of literature review is presented, so that the interface method can be understood and develop more easily. Therefore, there are implications for actively using AI Chatbot for digital transformation.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.