• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.29-41
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• 2010

Due to the recent technological advance, new types of AS/RS which can handle containers are being developed, and it is expected that they will be applied to related industries before long. Some companies and institutes in our country have constructed pilot systems for high-density-high-stacking systems and tested them to develop AS/RS-typed warehouses for containers. Along with this kind of construction efforts, development of rules to operate such systems efficiently and safely is also important. When outward-bound shipment is scheduled in container port, re-marshalling which rearranges containers in the yard to make shipment easy is conducted. In this paper, operating rules for the re-marshalling as well as simulation experiments to evaluate the performance of the rules are presented. We suggested two kinds of alternative sets of operating rules for re-marshalling and described the relevant logics corresponding to all possible cases for each alternative of operating rules. Through various simulation experiments, we found that each alternative has the merits and demerits at the same time and we could not say the one is always superior to the other. As a useful strategy, changing the applying operating rule is recommended from moment to moment depending on the expected number of operations at the landside input/output position.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.291-299
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• 2010

As recent advances in science, technology and performance requirements of the weapons system are getting highly diversified and complex, the performance requirements also get stringent and strict. Moreover, the weapons system should be intimately connected with other systems such as watchdog system, command and control system, C4I system, etc. However, a tremendous amount of time, cost and risk being spent to acquire new weapons system, and not being diminished compared to the rapid pace of its development speed. Defense Modeling and Simulation(M&S) comes into the spotlight as an alternative to overcoming these difficulties as well as constraints. In this paper, we propose the development process of virtual test framework based on the synthetic environment as a tool to analyze the effectiveness of the weapons system of underwater engagement model. To prove the proposed concept, we develop the test-bed of virtual test using Delta3D simulation engine, which is open source S/W. We also design the High Level Architecture and Real-time Infrastructure(HLA/RTI) based Federation for the interoperation with heterogeneous simulators. The significance of the study entails (1)the rapid and easy development of simulation tools that are customized for the Korean Theater of War; (2)the federation of environmental entities and the moving equations of the combat entities to manifest a realistic simulation.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.32-38
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• 2023

In this study, the electrochemical properties of dopamine coated silicon/silicon carbide/carbon(Si/SiC/C) composite materials were investigated to improve cycle stability and rate performance of silicon-based anode active material for lithium-ion batteries. After synthesizing CTAB/SiO₂ using the Stöber method, the Si/SiC composites were prepared through the magnesium thermal reduction method with NaCl as heat absorbent. Then, carbon coated Si/SiC anode materials were synthesized through polymerization of dopamine. The physical properties of the prepared Si/SiC/C anode materials were analyzed by SEM, TEM, XRD and BET. Also the electrochemical performance were investigated by cycle stability, rate performance, cyclic voltammetry and EIS test of lithium-ion batteries in 1 M LiPF₆ (EC: DEC = 1:1 vol%) electrolyte. The prepared 1-Si/SiC showed a discharge capacity of 633 mAh/g and 1-Si/SiC/C had a discharge capacity of 877 mAh/g at 0.1 C after 100 cycles. Therefore, it was confirmed that cycle stability was improved through dopamine coating. In addition, the anode materials were obtain a high capacity of 576 mAh/g at 5 C and a capacity recovery of 99.9% at 0.1 C/0.1 C.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.305-312
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• 2023

Purpose: Although the damage caused by abnormal temperatures is extensive, blow-up or black ice is typical in concrete structures. In this study, PCM with high phase change energy was mixed with concrete to reduce temperature damage to concrete pavement. Method: In order to reduce temperature damage to low temperatures and high temperatures, capsule-type PCM with phase change temperatures of 4.5℃ and 44℃ was replaced by 10%, 30%, and 50%, and thermal performance experiments and compressive strength experiments were conducted using thermocouples and variable chambers. Result: As a result of the thermal performance experiment, it was found that the incorporation of PCM improves temperature resistance by up to 25% or more, and increases thermal resistance at all temperatures with high specific heat when substituted in large amounts. As a result of the compression strength experiment, a substitution of 30% or more resulted in a decrease in the compression strength, and a large strength difference was shown based on the phase change temperature of the PCM. Conclusion: The incorporation of PCMs has been shown to increase the thermal performance of concrete, with the greatest increase in thermal performance near the phase change temperature of PCM. In addition, a small strength reduction of 10% to 20% occurs at the highest substitution rate of 50% substitution, so there is no significant problem with usability, and additional PCM substitution is expected to improve thermal performance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.160-167
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• 2023

An INS is a composite navigation system providing "added value" so defined if work stations provide Multi-Function Displays(MFDs) integrating information and functions for navigational tasks. Even though the minimum requirements for an INS are defined by IMO performance standards, a generic list of the devices and functions that constitute an INS does not exist, so the configuration of the INS is different for each manufacturer, and guidelines based on users' perspectives are also insufficient. This study was conducted to enhance the usability of the INS by analyzing the information required by users according to the ship's operating status and tasks and effectively structuring it in the MFD of the INS. By analyzing INS-related international standards and manufacturers' component equipment lists, mandatory navigation information was selected and card sorting tests were conducted on ship operators with experience in using MFDs to group the information required for each INS task. The results of the study can serve as a basic guideline for manufacturers to structure information based on users' experience when designing products.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.