• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.503-516
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• 2021

Autonomous fire detection and suppression system requires advanced technology for complex detection technology and injection/control technology for accurate hitting by fire location. Also, foam spraying should be included to respond to oil fires. However, when a single spray monitor is used in common, water and foam spray properties appear different, so for accurate fire suppression, research on the spray trajectory and distance will be required. In this study, experimental studies and numerical analysis studies were combined to analyze the foam spray characteristics through the spray monitor developed for the establishment of an autonomous fire extinguishing system. For flow analysis of foam injection, modeling was performed using OpenFOAM analysis software, and the commonly used foaming agent (Aqueous Film-Forming Foam) was applied for foam properties. The injection distance analysis was performed according to the injection pressure and the injection angle according to the form of the foam, and at the same time, the results were verified and presented through the injection experiment.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.351-357
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• 2021

IoT devices, which are used in various ways in distributed environments, are becoming more important in data transmitted and received from IoT devices as fields of use such as medical, environment, transportation, bio, and public places are diversified. In this paper, as a method to ensure the reliability of IoT data, an autoencoder-based IoT-linked processing technique is proposed to classify and process numerous data by various important attributes. The proposed technique uses correlation indices for each IoT data so that IoT data is grouped and processed by blockchain by characteristics for IoT linkage processing based on autoencoder. The proposed technique expands and operates into a blockchain-based n-layer structure applied to the correlation index to ensure the reliability of IoT data. In addition, the proposed technique can not only select IoT data by applying weights to IoT collection data according to the correlation index of IoT data, but also reduce the cost of verifying the integrity of IoT data in real time. The proposed technique maintains the processing cost of IoT data so that IoT data can be expanded to an n-layer structure.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.47-55
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• 2021

Firstly, our Technical and Vocational Education and Training(TVET) ODA currently uses 70% of its budget on short-term assistance project works without much consideration for continuity from one project to another. Secondly, TVET ODA budget is much too concentrated on hardware support, lowering impact compared to the amount invested. Lastly, there is a lack of research on the needs of recipient nation which leads to lowering effectiveness of TVET ODA. This Study analyzed the characteristics of Korea's TVET ODA through the statistical data analysis of ODA. This study's main focus is to recommend methods for Korean colleges to overcome tendencies and limitations of TVET within Korea's ODA. Colleges have advantages in training students to fit needs of the market and companies based on decades of experience colleges have on academic-industrial collaboration. Colleges can also transfer qualification verification systems to fit the recipient country and dispatch TVET related personnel to strengthen software support. Additionally, the post project evaluation and post job placement management capabilities of colleges can be actively used for post management of TVET projects. I hope that through this study, ways to increase participation of colleges in TVET ODA can be discussed in more variety.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.817-839
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• 2021

To manage software safely, the military acquires and manages products in accordance with the RMF A&A. RMF A&A is standard for acquiring IT products used in the military. And it covers the requirements, acquisition through evaluation and maintenance of products. According to the RMF A&A, product development activities should reflect the risks of the military. In other words, developers have mitigated the risks through security by design and supply chain security. And they submit evidence proving that they have properly comply with RMF A&A's security requirements, and the military will evaluate the evidence to determine whether to acquire IT product. Previously, case study of RMF A&A have been already conducted. But it is difficult to apply in real-world, because it only address part of RMF A&A and detailed information is confidential. In this paper, we propose the evidence fulfilling method that can satisfy the requirements of the RMF A&A. Furthermore, we apply the proposed method to real-world drone system for verifying our method meets the RMF A&A.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.135-144
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• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.4
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• pp.457-467
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• 2022

Electron bombardment to silicate glass during electron probe microanalysis (EPMA) causes outward migration of Na from the excitation volume and subsequent decrease in the measured X-ray count rates of Na. To acquire precise Na₂O content of silicate glass, one should use proper analytical technique to avoid or minimize Na migration effect or should correct for decreases in the measured Na X-ray counts. In this study, we analyzed 8 silicate glass standard samples using automated Time Dependent Intensity (TDI) correction method of Probe for EPMA software that can calculate zero-time intercept by extrapolating X-ray count changes over analysis time. We evaluated an accuracy of TDI correction for Na measurements of silicate glasses with EPMA at 15 kV acceleration voltage and 20 nA probe current electron beam, which is commonly utilized analytical condition for geological samples. Results show that Na loss can be avoided with 20 ㎛-sized large beam (<0.1 nA/㎛²), thus silicate glasses can be analyzed without TDI correction. When the beam size is smaller than 10 ㎛, Na loss results in large relative errors up to -55% of Na₂O values without correction. By applying TDI corrections, we can acquire Na₂O values close to the reference values with relative errors of ~ ±10%. Use of weighted linear-fit can reduce relative errors down to ±6%. Thus, quantitative analysis of silicate glasses with EPMA is required for TDI correction for alkali elements such as Na and K.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.95-108
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• 2022

Airworthiness certification is critical, in ensuring the flight safety of military aircraft for development tests and production operations. The MIL-HDBK-516C, latest airworthiness certification document, handles the field of flying qualities in Chapter 6 (flight technology), and refers to specific chapters of MIL-STD-1797B, which is the specification document for developing military aircraft. Since the MIL-STD-1797B released in 2006 by the U.S. Department of Defense is not disclosed to other countries, the Chapter 6 (flight technology) of MIL-HDBK-516B Expanded, the former certification standards pursuant to flying qualities, has to be applied to military aircraft being developed in the Republic of Korea. However the requirements of Chapter 6 of MIL-HDBK-516B Expanded comprise unclear sentences, because of contents from various development specifications. Also, clarification is needed in that the same requirements have to be verified in different criteria. In this paper, the results of this study present an effective verification method, for acquiring the airworthiness certification in field of flying qualities based on MIL-HDBK-516B Expanded.

• Journal of Aerospace System Engineering
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• v.16 no.2
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• pp.63-72
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• 2022

As interest in microsatellites increases, research has been actively conducted recently on the performance and use, as well as the orbital design and deployment techniques, for the microsatellite constellations. The purpose of this study was to investigate orbital deployment techniques using thrust and differential atmospheric drag control (DADC) for the Walker-delta constellation. When using thrust, the time and thrust required for orbital deployment vary, depending on the separation speed and direction of the satellite with respect to the launch vehicle. A control strategy to complete the orbital deployment with limited performance of the propulsion system is suggested and it was analyzed. As a result, the relationship between the deployment period and the total thrust consumption was derived. It takes a relatively longer deployment time using differential air drag rather than consuming thrusts. It was verified that the satellites can be deployed only with differential air drag at a general orbit of a microsatellite constellation. The conclusion of this study suggests that the deployment strategy in this paper can be used for the microsatellite constellation.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.87-97
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• 2022

Although the use of BIM in architectural projects has increased, repetitive modeling tasks and frequent design errors remain as obstacles to the practical application of BIM. In particular, interior finishing elements include the most varied and detailed requirements, and thus requires improving its modelling efficiency and resolving potential design errors. Recently, visual programming-based modules has gained traction as a way to automate a series of repetitive modeling tasks. However, existing approaches do not adequately reflect the practical modeling needs and focus only on replacing siimple, repetitive tasks. This study developed and evaluated the performance of three modules for automatic detailing of walls, floors and ceilings. The three elements were selected by analyzing the man-hours and the number of errors that typically occur when detailing BIM models. The modules were then applied to automatically detail a sample commercial facility BIM model. Results showed that the implementations met the practical modeling requirements identified by actual modelers of an construction management firm.