• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Clean Technology
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• v.16 no.3
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• pp.213-219
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• 2010

Vortex tube is the device that can separate small particles from the compressed gas, as well as compressed gas into hot and cold gas. Due to energy and particle separation ability, a vortex tube can be used as the main component of the $CO_2$ absorption device. In this study, experimental approach has been performed to analyze the energy separation characteristics of the vortex tube. To obtain the preliminary design data, energy separation characteristics of the vortex tube has been tested for orifice diameter, nozzle area ratio, and tube length. As a result, the orifice diameter is the major factor of the vortex tube design. The nozzle area ratio and tube length have a minor effect on the energy separation performance. For Dc=0.6D, AR=0.14~0.16, and L=16D, maximum energy separation has been occurred. The result from this study can be used as the basic design data of the $100Nm^3$/hr class vortex tube applied to the $CO_2$ absorption device. Compared with the $CO_2$ absorption process containing an absorption tower, the process with a vortex tube is expected to have a huge advantage of saving the installation space and the operating cost.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.250-261
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• 2023

In this study, the noise contributions by the duct, stator and rotor, which are the propulsor components, are evaluated to identify the flow noise source in cavitation and non-cavitation conditions on pumpjet propulsion and the noise levels in both conditions are compared. The unsteady incompressible Reynolds averaged Navier-Stokes (RANS) equation based on the homogeneous mixture assumption is applied on the suboff submarine hull and pumpjet propeller in the cavitation tunnel, and the Volume of Fluid (VOF) method and Schnerr-Sauer cavitation model are used to describe the two-phase flow. Based on the flow simulation results, the acoustic analogy formulated by Ffowcs Williams and Hawkings (FW-H) equation is applied to predict the underwater radiated noise. The noise contributions are evaluated by using the three types of impermeable integral surface on the duct, stator and rotor, and the two types of permeable integral surface surrounding the propulsor. As a result of noise prediction, the contribution by the stator is insignificant, but it affects the generation of flow noise source due to flow separation in the duct and rotor, and the noise is predominantly radiated into the upward and right where the flow separations are. Also, the noise is radiated into the thrust direction due to pressure fluctuation between suction and pressure sides on the rotor blades, and the it can be seen that the cavitation effect into the noise can be considered through the permeable integral surface.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.17-27
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• 2022

A certain level of stability margin airworthiness criteria should be met to secure robustness against uncertainties between the real plant and the model in a flight control system design. The U.S. Department of Defense (DoD) specification of MIL-F-9490D and airworthiness certification standard of MIL-HDBK-516B uses gain and phase margin criteria of flight control system. However, the same stability margin criteria is applied at all development phases without considering the design maturity of each development phase of the aircraft. Ultimately, a problem arises when the aircraft operation envelope is excessively restricted. This paper proposes the relation of handling qualities and stability margin, and presents re-established stability margin criteria as a development phases and verification methods. The results of the research study are considered to contribute to the verification of the stability margin criteria more flexibly and effectively by applying the method to not only the currently manned developing aircrafts but also the unmanned vehicle to be developed in the future.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.447-455
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• 2017

At the modern industry, the composite material has been widely used. Particularly, the material of carbon fiber reinforced plastic hardened with resin on the basis of fiber is excellent. As the specific strength and rigidity are also superior, it receives attention as the light material. Among these materials, the carbon fiber reinforced plastic using carbon fiber has the superior mechanical property different from another fiber. So, it is utilized in vehicle and airplane at which high strength and light weight are needed at the same time. In this paper, the tensile property due to the fiber design is investigated through the analysis study with CT specimen composed of carbon plastic reinforced plastic. At the stress analysis of CFRP composite material with hole, the fracture trend at the tensile environment is examined. Also, it is shown that the lowest stress value happens and the deformation energy of the pre-crack becomes lowest at the analysis model composed of the stacking angle of 60° through the result due to the stacking angle. On the basis of this study result, it is thought to apply the foundation data to anticipate the fracture configuration at the structure applied with the practical experiment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.737-743
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• 2009

Shield TBM, since it was employed for Suyoungman Bay riverbed tunnel of Busan Subway in 2000,has been increasingly adopted in Korea, and in line with growing popularity, the study on Shield TBM has been expanded. However the studies mostly focus on ground condition in a bid to estimate the advancement rate and develop the model for calculating the excavation efficiency, whereas the efforts to analyze the cause of delay and to develop the improvement measures have been neglected. Thus the studies were mostly intended to analyze the schedule slippage focusing on ground conditions, while the study on schedule behind due to equipment itself and related facilities have yet to be attempted in earnest. This study hence was aimed at evaluating the troubles and schedule slippage caused by mechanical elements such as shield TBM equipment and tools and ground conditions, making use of FMEA approach so as to analyze the risk of schedule delay by such elements, thereby proposing the preventive measures to deal with high-risk factors. So, this study suggest the solution to highly ranked trouble factor for the purpose of enhance the efficiency on Shield TBM.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.