• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.311-322
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• 2014

IoT(Internet of Things) is a concept of connected internet pursuing direct access to devices or sensors in fused environment of personal, industrial and public area. In IoT environment, it is possible to access realtime data, and the data format and topology of devices are diverse. Also, there are bidirectional communications between users and devices to control actuators in IoT. In this point, IoT is different from the conventional internet in which data are produced by human desktops and gathered in server systems by way of one-sided simple internet communications. For the cloud or portal service of IoT, there should be a file management framework supporting systematic naming service and unified data access interface encompassing the variety of IoT things. This paper implements a DB-based virtual file system maintaining attributes of IoT things in a UNIX-styled file system view. Users who logged in the virtual shell are able to explore IoT things by navigating the virtual file system, and able to access IoT things directly via UNIX-styled file I O APIs. The implemented virtual file system is lightweight and flexible because it maintains only directory structure and descriptors for the distributed IoT things. The result of a test for the virtual shell primitives such as mkdir() or chdir() shows the smooth functionality of the virtual file system, Also, the exploring performance of the file system is better than that of Window file system in case of adopting a simple directory cache mechanism.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.469-480
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• 2019

One of the goals of the new 2015 revised curriculum is to cultivate the creativity of students who will live in the era of the Fourth Industrial Revolution to create new things through diverse ideas and challenges based on basic learning skills. Accordingly, in order to solve the given problems rationally, the convergence problem solving ability that can process and utilize various areas of knowledge and information is becoming important. Therefore, in this study, we designed the integrative education using a 3D printer based on Tinkercad modeling and applied it to the class to investigate the effect on the improvement of computing thinking ability of elementary school students. To verify the contents of the study, two classes of 25 sixth-grade elementary school students were divided into an experimental group and a controlled group. For the experimental group, 12 classes of convergence education programs using a 3D printer were applied for about three months, and the same amount of general curriculum was conducted for the control group. After that, the t-tests were carried out using the pre-post test to measure the effectiveness of the computational thinking ability. After the application of the program, the experimental group showed statistically significant improvement in computational thinking ability, but the controlled group showed no statistically significant difference. The results show that convergence education using the Tinkercad modeling-based 3D printer has a positive effect on the improvement of computing thinking ability of elementary school students.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.321-326
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• 2019

Image denoising methods based on block matching are founded on the experimental observations that neighboring patches or blocks in images retain similar features with each other, and have been proved to show superior performance in denoising different kinds of noise. The methods, however, take into account only neighboring blocks in searching for similar blocks, and ignore the characteristic features of the reference block itself. Consequently, denoising performance is negatively affected when outliers of the Gaussian distribution are included in the reference block which is to be denoised. In this paper, we propose an expanded block matching method in which noisy images are first decomposed into a number of bit-planes, then the range of true signals are estimated based on the distribution of pixels on the bit-planes, and finally outliers are replaced by the neighboring pixels belonging to the estimated range. In this way, the advantages of the conventional Gaussian filter can be added to the blocking matching method. We tested the proposed method through extensive experiments with well known test-bed images, and observed that performance gain can be achieved by the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.863-871
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• 2018

Existing vulnerability analysis tools are prone to missed detections, incorrect detections, and over-detection, which reduces accuracy. In this paper, cross-checking based on a vulnerability detection method using static and dynamic analysis is proposed, which develops and manages safe applications and can resolve and analyze these problems. Risks due to vulnerabilities are computed, and an intelligent vulnerability detection technique is used to improve accuracy and evaluate risks under the final version of the application. This helps the development and execution of safe applications. Through incorporation of tools that use static analysis and dynamic analysis techniques, our proposed technique overcomes weak points at each stage, and improves the accuracy of vulnerability detection. Existing vulnerability risk-evaluation systems only evaluate self-risks, whereas our proposed vulnerability risk-evaluation system reflects the vulnerability of self-risk and the detection accuracy in a complex fashion to evaluate relative. Our proposed technique compares and analyzes existing analysis tools, such as lists for detections and detection accuracy based on the top 10 items of SANS at CWE. Quantitative evaluation systems for existing vulnerability risks and the proposed application's vulnerability risks are compared and analyzed. We developed a prototype analysis tool using our technique to test the application's vulnerability detection ability, and to show that our proposed technique is superior to existing ones.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.119-126
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• 2023

Sarcopenia is not well known enough to be classified as a disease in 2021 in Korea, but it is recognized as a social problem in developed countries that have entered an aging society. The diagnosis of sarcopenia follows the international standard guidelines presented by the European Working Group for Sarcopenia in Older People (EWGSOP) and the d Asian Working Group for Sarcopenia (AWGS). Recently, it is recommended to evaluate muscle function by using physical performance evaluation, walking speed measurement, and standing test in addition to absolute muscle mass as a diagnostic method. As a representative method for measuring muscle mass, the body composition analysis method using DEXA has been formally implemented in clinical practice. In addition, various studies for measuring muscle mass using abdominal images of MRI or CT are being actively conducted. In this paper, we develop an AI image segmentation model based on abdominal images of CT with a relatively short imaging time for the diagnosis of sarcopenia and describe the multicenter validation. We developed an artificial intelligence model using U-Net that can automatically segment muscle, subcutaneous fat, and visceral fat by selecting the L3 region from the CT image. Also, to evaluate the performance of the model, internal verification was performed by calculating the intersection over union (IOU) of the partitioned area, and the results of external verification using data from other hospitals are shown. Based on the verification results, we tried to review and supplement the problems and solutions.

• Korea Science and Art Forum
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• v.35
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• pp.145-155
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• 2018

The goal of the study is to provide a new type of audio-visualization method through case analysis and work production based on Polysomnography(PSG) data that is difficult to interpret or not familiar to the public. Most art works are produced with conscious actions during waking hours. On the other hand, during sleep, we get into the world of unconsciousness. Therefore, through the experiment, want to discover if could get something new when we were in the subconscious state, and if so, wondered what kind of art could be made through it. The study method is to consider definition of sleep and sleep data first. The sleep data were classified into normal group and Narcolepsy, Insomnia, and sleep apnea by focusing on sleep disorder graphs that is measured by sleep polygraph. After that, I refined and converted the acquired biometric data into a text-based script. The degree of sleep in the text form of the script was rendered as a 3D animated image using Maya. In addition, the heart rate data script was transformed into a midi format, and the audition was implemented in the garage band. After Effects combines the image and sound to create four single channel images of 3 minutes and 20 seconds each. As a result of the research, I made an opportunity for anyone easy to understand the results, having difference with the normal data, through art instead of using difficult medical term. It also showed the possibility of artistic expression even when conscious actions did not occur. Through the results of this research, I expect the expansion and diversity of artistic audiovisual expression of biometric data.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.123-134
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• 2008

Since the end treatments of guardrails installed on domestic roads have the shapes which can easily penetrate and turnover a vehicle, the occupant can be subjected to severe injury when a vehicle impacts the end treatments. In this study, the criteria of performance evaluation for end treatments are suggested which are suitable to domestic road circumstances. Based on the investigation for the installation and studies instances of end treatments, the mechanism of end treatments is examined and the new end treatment suitable to domestic road circumstances is suggested. The suggested end treatment was verified by computer simulation using d LS-DYNA programs and satisfied the suggested performance evaluation criteria for end treatments. And the developed end treatment was verified by full-scale vehicle crash test and satisfied the following three primary appraisal factors of the suggested performance evaluation criteria for end treatments; occupant risk criteria, structural adequacy, and after-collision vehicle trajectory. This study is the first to develop end treatments considering the occupant safety in Korea. Therefore, If the developed end treatments is installed on roads and highways, it can be expected that it will reduce the grave situation of end treatment accidents and increase the safety of roads.

• Horticultural Science & Technology
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• v.28 no.6
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• pp.1066-1071
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• 2010

To evaluate the effect of horticultural therapy (HT) on the emotional improvement of depressed patients, computer-based heart rate variability (HRV) was compared with self-report scale (SRS) known as existing subjective evaluation method. SRS included four test areas: mental stress scale (MSS), physical stress scale (PSS), Beck anxiety inventory (BAI), and Beck depression inventory (BDI). HRV was itemized into four parameters: standard deviation of the N-N intervals (SDNN), square root of mean squared difference of successive N-N intervals (RMSSD), total power (TP), and low-frequency/high-frequency ratio (LF/HF ratio). Thirty patients with depression at the same mental hospital participated in this study. 15 patients of the treatment group received HT once a week for three months, but the control group did not during the same period. As a result, the emotional improvement in treatment group was clearly identified through HRV as well as SRS. The significant difference was shown at three test areas (MSS, BAI, and BDI, $p$ < 0.001) in SRS and at one parameter (total power, $p$ < 0.05) in HRV. There was noticeable increase in SDNN, RMSSD, and LF/HF ratio in treatment group after HT activity, but no significant difference. Although all parameters of HRV did not show significance, the possibility of HRV as an objective evaluation method to HT was recognized in this study. These results also implied that HT was efficient in the mental and physical regeneration of the depressed patients in both subjective and objective evaluation methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.12
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• pp.1039-1047
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• 2017

This paper presents a test development of a Fly-By-Wireless flight control system for a fixed-wing unmanned aerial vehicle (UAV). Fly-By-Wireless system (FBWLS) refers to a system that uses a wireless network instead of a wired network to connect sensors and actuators with a flight control computer (FCC), reducing considerable amount of wires. FBWLS enables to design a much lighter aircraft along with decreased maintenance time and cost. In this research we developed a Zigbee-based FWBLS UAV in which sensors (GPS and AHRS) are wirelessly connected via a FCC to aileron and elevator servo motors. In order to see the effect of time delay due to wireless signal on the flight stability of the UAV, several flight tests were conducted. From the tests, it was confirmed that the effect is minor by comparing the flight response of the FBWLS with the corresponding Fly-By-Wire system.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.