• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Steel and Composite Structures
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• v.50 no.3
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• pp.281-298
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• 2024

Stainless steel bolts (SSB) are increasingly utilized in bolted steel connections due to their good mechanical performance and excellent corrosion resistance. Fire accidents, which commonly occur in engineering scenarios, pose a significant threat to the safety of steel frames. The post-fire behavior of SSB has a significant influence on the structural integrity of steel frames, and neglecting the effect of temperature can lead to serious accidents in engineering. Therefore, it is important to evaluate the performance of SSB at elevated temperatures and their residual strength after a fire incident. To investigate the mechanical behavior of SSB after fire, 114 bolts with grades A4-70 and A4-80, manufactured from 316L austenitic stainless steel, were subjected to elevated temperatures ranging from 20℃ to 1200℃. Two different cooling methods commonly employed in engineering, namely cooling at ambient temperatures (air cooling) and cooling in water (water cooling), were used to cool the bolts. Tensile tests were performed to examine the influence of elevated temperatures and cooling methods on the mechanical behavior of SSB. The results indicate that the temperature does not significantly affect the Young's modulus and the ultimate strength of SSB. Up to 500℃, the yield strength increases with temperature, but this trend reverses when the temperature exceeds 500℃. In contrast, the ultimate strain shows the opposite trend. The strain hardening exponent is not significantly influenced by the temperature until it reaches 500℃. The cooling methods employed have an insignificant impact on the performance of SSB. When compared to high-strength bolts, 316L austenitic SSB demonstrate superior fire resistance. Design models for the post-fire mechanical behavior of 316L austenitic SSB, encompassing parameters such as the elasticity modulus, yield strength, ultimate strength, ultimate strain, and strain hardening exponent, are proposed, and a more precise stress-strain model is recommended to predict the mechanical behavior of 316L austenitic SSB after a fire incident.

• Journal of Service Research and Studies
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• v.9 no.2
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• pp.31-40
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• 2019

In this paper, we have studied the improvement of operational control for the enhancement of business continuity of information system becoming more important with the development of information technology such as big data, Iot, and artificial intelligence. The operational management and audit guidance of the current information system, which is coming in the fourth industrial age, where various services, data and industries are converged, is based on the existing general information system pattern and needs to be improved. The provision of services at fixed times is linked to the survival of enterprises and countries and serves as a key element. Therefore, it is necessary to study the application of optimized check items of the operation audits to minimize the service interruption damage of the information system and to provide the stable service in terms of business continuity management. To accomplish this, the check items presented in the operational control of the information system were derived by combining the PDCA step contents and 8 resource requirements provided in ISO 22301. From the point of view of increasing the business continuity according to the derivation criteria of the inspection items, the operational inspection check items were derived by exemplifying the improved check items and review items of the information system operation audit and the products to be checked during the operational audit. The check items were divided into management audit improvement check items for service continuity management, and operational audit improvement check items for performance and availability management. The average score of the IT professionals' survey on the suitability of the proposed checklist was 4.63, which was concluded to be appropriate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.568-578
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• 2021

Patents that are research results from industry-university cooperation (IUC) are a source of innovation, and play an important role in economic growth, such as technology transfer and commercialization. For this reason, there are many efforts to revitalize IUC, but in general, company patents are achievements that can be commercialized, rather than research achievements, so not all patents are used for business, even after their creation as the outcome of IUC. Therefore, this research supports the design of measures in which IUC can ultimately be linked to successful utilization of patents by identifying the purposes of IUC, even after it has been successfully promoted, and patents have been filed as a result. To this end, first, the patents registered for industry-academia cooperation in the United States are collected, and second, a predictive model is designed, with unexpired and expired patents predicted using machine learning techniques. The final identified patents are intended to derive available factors in terms of marketability and technicality. This study is expected to help predict the utilization of unexpired and expired patents, and is expected to contribute to setting goals for research results from technical cooperation between corporate and university officials planning early IUC.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.147-157
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• 2017

Recently, ICT Retail Convergence(IRC) has been rapidly increasing to improve consumer satisfaction and consumer experience. In this paper, we aim to diagnose IRC from consumers' point of view by reviewing the present status and value of IRC according to consumer purchase decision making process. Based on the previous studies in retail industry, we classified IRC into 4 types: Experience-specific tech(Virtual Reality and Augmented Reality); Information-specific tech(Artificial Intelligence and Big Data); Location-based tech(Radio Frequency Identification and Beacon); Payment-related tech(Fin-tech and Biometrics). Next, we found that there is a difference in value provided to consumers according to the type of technology, analysing the value by consumer purchase decision making process. This study can be useful to introduce IRC for improving consumer satisfaction as well as ICT and Retail. Also, it can be basic data for future technology studies with a consumer perspective.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.895-907
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• 2020

With the recent increasing influence of multimedia content other than the text-based content, services that help to process information in content brings us great convenience. These services' representative features are searching and masking the sensitive data. It is not difficult to find the solutions that provide searching and masking function for text information and image. However, even though we recognize the necessity of the technology for searching and masking a part of the audio data, it is not easy to find the solution because of the difficulty of the technology. In this study, we propose web application that provides searching and masking functions for audio data using audio partitioning method. While we are achieving the research goal, we evaluated several speech to text conversion APIs to choose a proper API for our purpose and developed regular expressions for searching sensitive information. Lastly we evaluated the accuracy of the developed searching and masking feature. The contribution of this work is in design and implementation of searching and masking a sensitive information from the audio data by the various functionality proving experiments.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.299-305
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• 2015

Modbus is a serial communications protocol, it has since become a practically standard communication protocol, and it is now a commonly available means of connecting industrial electronic devices. Therefore, it can be connected with all devices using Modbus protocol to the measurement and remote control on the ships, buildings, trains, airplanes and etc.. In this paper, we add the Modbus communication protocol to the existing lighting controller sensitivity to enable verification and remote control by external environmental factors, and also introduces a fuzzy inference system was configured by external environmental factors to control LED lighting. External environmental factors of temperature, humidity, illuminance value represented by the LED through a fuzzy control algorithm, the values accepted by the controller through the sensor. Modbus is using the RS485 Serial communication with other devices connected to the temperature, humidity, illumination and LED output status check is possible. In addition, the remote user is changed to enable it is possible to change the RGB values in the desired color change. Produced was confirmed that the LED controller output is based on the temperature, humidity and illumination.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.483-492
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• 2019

The culture and education are very active with the active policy and support to form the government's Maker Movement. The purpose of this study is to grasp the current status of the education sector of the domestic maker movement, which is increasing recently, and to propose a plan for activating maker education for the development of a positive direction. To this end, first, the current status and problems of domestic maker training are derived through in-depth interviews with existing maker training operators and participants. Second, based on the contents of the interview script, keyword analysis and its characteristics through the qualitative survey analysis program (NVIVO) are identified. Third, based on the analysis results, we propose a plan and development direction for domestic maker education. Based on the educators who performed maker training and the students involved, professional maker teachers were required for the professionalism of education, and the expansion of maker channels and professional networking of participating students was required. In addition, there was a need for specialized programs and appropriate policy support that reflected the characteristics of maker training. This study aims at contributing to the activation of maker education, which is a major field of maker movement, by helping to improve concrete support methods, training related educators, and educational environment for maker education.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.367-375
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• 2021

The quality of medical care can be defined as four types such as effectiveness, efficiency, adequacy, and scientific-technical quality. For the management of scientific-technical aspects, medical institutions annually disseminate the latest knowledge in the form of conservative education. However, there is an obvious limit to the fact that the latest knowledge is distributed quickly enough to the clinical site with only one-time conservative education. If intelligent information processing technologies such as big data and artificial intelligence are applied to the medical field, they can overcome the limitations of having to conduct research with only a small amount of information. In this paper, we construct databases on which the existing medicine prescription adaptations can be extended. To do this, we collect, store, manage, and analyze information related to oriental medicine at domestic and abroad Journals. We design a processing and analysis technique for oriental medicine evidence research data for the construction of a database of oriental medicine prescription extended adaption. Results can be used as a basic content of evidence-based medicine prescription information in the oriental medicine-related decision support services.