• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.988-995
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• 2020

Air gun shock systems are commonly used as alternative explosion energy sources for underwater explosion (UNDEX) shock tests owing to their low cost and environmental impact. The airbag inflator of automotive airbag systems is also very useful to generate extremely rapid underwater gas release in labscale tests. To overcome the restrictions on the very small computational time step owing to the very fine fluid mesh around the nozzle hole in the explicit integration algorithm, and also the absence of a commercial solver and software for gas UNDEX of airbag inflator, an idealized airbag inflator and fluid mesh modeling technique was developed using nozzle holes of relatively large size and several small TNT charges instead of gas inside the airbag inflator. The objective of this study is to validate the results of an UNDEX response analysis of one and two idealized airbag inflators by comparison with the results of shock tests in a small water tank. This comparison was performed using the multi-material Arbitrary Lagrangian-Eulerian formulation and fluid-structure interaction algorithm. The number, size, vertical distance from the nozzle outlet, detonation velocity, and lighting times of small TNT charges were determined. Through mesh size convergence tests, the UNDEX response analysis and idealized airbag inflator modeling were validated.

• Journal of Integrative Natural Science
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• v.13 no.4
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• pp.132-140
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• 2020

With the recent introduction of artificial intelligence (AI) technology, the use of data is rapidly increasing, and newly generated data is also rapidly increasing. In order to obtain the results to be analyzed based on these data, the first thing to do is to classify the data well. However, when classifying data, if only one classification technique belonging to the machine learning technique is applied to classify and analyze it, an error of overfitting can be accompanied. In order to reduce or minimize the problems caused by misclassification of the classification system such as overfitting, it is necessary to derive an optimal classification by comparing the results of each classification by applying several classification techniques. If you try to interpret the data with only one classification technique, you will have poor reasoning and poor predictions of results. This study seeks to find a method for optimally classifying data by looking at data from various perspectives and applying various classification techniques such as LDA and QDA, such as linear or nonlinear classification, as a process before data analysis in data analysis. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable and the correlation between the variables. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified to suit the purpose of analysis. This is a process that must be performed before reaching the result by analyzing the data, and it may be a method of optimal data classification.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.321-326
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• 2021

Blockchain is increasing in value as a platform for safe transmission of capital transactions or secure data. In addition, blockchain has the potential as a new platform that can safely store large amounts of data such as videos, music, and photos, and safely manage transaction details and service usage specifications. Since it is not possible to store large-capacity media data in a block, research on the performance of storing sound source information in a block and retrieving the stored sound source data by using the distributed storage system (IPFS) and the hash information of the sound source signature data was conducted. In this paper, we propose a sound source signature indexing method using a bloom filter that can improve the search speed suggested by previous studies. As a result of the experiment, it was confirmed that improved search performance (O(1)) than the existing search performance (O(n)) can be achieved.

• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1377-1384
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• 2018

Accurate measurement of the absorbed dose and the effective dose is required in dental panoramic radiography involving relatively low energy with a rotational X-ray tube system using long exposures. To determine the effectiveness of measuring the irradiation by using passive dosimetry, we compared the entrance skin doses by using a radiophotoluminescent glass dosimeter (RPL) and an optically stimulated luminescence detector (OSL) in a phantom model consisting of nine and 31 transverse sections. The parameters of the panoramic device were set to 80 kV, 4 mA, and 12 s in the standard program mode. The X-ray spectrum was applied in the same manner as the panoramic dose by using the SpekCalc Software. The results indicated a mass attenuation coefficient of $0.008226cm^2/g$, and an effective energy of 34 keV. The equivalent dose between the RPL and the OSL was calculated based on a product of the absorbed doses. The density of the aluminum attenuators was $2.699g/cm^3$. During the panoramic examination, tissue absorption doses with regard to the RPL were a surface dose of $75.33{\mu}Gy$ and a depth dose of $71.77{\mu}Gy$, those with regard to the OSL were surface dose of $9.2{\mu}Gy$ a depth dose of $70.39{\mu}Gy$ and a mean dose of $74.79{\mu}Gy$. The effective dose based on the International Commission on Radiological Protection Publication 103 tissue weighting factor for the RPL were $0.742{\mu}Sv$, $8.9{\mu}Sv$, $2.96{\mu}Sv$ and those for the OSL were $0.754{\mu}Sv$, $9.05{\mu}Sv$, and $3.018{\mu}Sv$ in the parotid and sublingual glands, orbit, and thyroid gland, respectively. The RPL was more effective than the OSL for measuring the absorbed radiation dose in low-energy systems with a rotational X-ray tube.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.495-504
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• 2012

This paper presents various speed optimization techniques for software implementation of the HIGHT block cipher on CPUs and GPUs. We considered 32-bit and 64-bit operating systems for CPU implementations. After we applied the bit-slicing and byte-slicing techniques to HIGHT, the encryption speed recorded 1.48Gbps over the intel core i7 920 CPU with a 64-bit operating system, which is up to 2.4 times faster than the previous implementation. We also implemented HIGHT on an NVIDIA GPU equipped with CUDA, and applied various optimization techniques, such as storing most frequently used data like subkeys and the F lookup table in the shared memory; and using coalesced access when reading data from the global memory. To our knowledge, this is the first result that implements and optimizes HIGHT on a GPU. We verified that the byte-slicing technique guarantees a speed-up of more than 20%, resulting a speed which is 31 times faster than that on a CPU.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1133-1143
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• 2012

Currently, Many Cyber Security Centers(CSC) are established and being operated in our country. But, in the absence of indicators to evaluate activities of the Managed Security Service(MSS), We can't identify the CSC's level of overall job performance. Therefore, we can't derive strengths and weaknesses from the CSC. From these reasons, The purpose of this research is to develop an objective indicator to evaluate activities of the MSS. I studied both international and domestic Information Security Management System(ISMS) as related standards(ISO/IEC 27001, G-ISMS). Moreover, I analysed the NIST Computer Security Incident Handing Guide and the Incident Management Capability Metrics(IMCM) of Carnegie Mellon Software Engineering Institute(SEI). The implications for this analysis and domestic hands-on experience are reflected in the research. So I developed 10 evaluation domains and 62 detail evaluation items. This research will contribute to our understanding the level of the CSC's job performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.49-61
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• 2009

Recently, a great attention has been paid to a vehicle black box device in the auto markets since it provides an accident re-construction based on the data which contains audio, video, and some meaningful driving informations. It is expected that the device will get to promote around commercial vehicles and the market will greatly grow within a few years. Drivers who equips the device in their car believes that it can find the origin of an accident and help an objective judge. Unfortunately, the current one does not provide the integrity of the data stored in the device. That is the data can be forged or modified by outsider or insider adversary because it is just designed to keep the latest data produced by itself. This fact cause a great concern in car insurance and law enforcement, since the unprotected data cannot be trusted. To resolve the problem, in this paper, we propose a novel real-time integrity protection scheme for vehicle black box device. We also present the evaluation results by simulation using our software implementation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.113-120
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• 2010

Content security and privacy protection are important issues in emerging network-based video surveillance applications. Especially, satisfying both real-time constraint and energy efficiency with embedded system-based video sensors is challenging since the battery-operated sensors need to compress and protect video content in real-time. In this paper, we propose a multicore-based solution to compress and protect video surveillance data, and evaluate the effectiveness of the solution in terms of both real-time constraint and energy efficiency. Based on the experimental results with MPEG2/AES software, we confirm that the multicore-based solution can improve the energy efficiency of a singlecore-based solution by a factor of 30 under the real-time constraint.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.585-597
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• 2021

This paper presents a comparative study of analytical method, finite element method (FEM) and Multilayer Perceptron (MLP) for analysis of a contact problem. The problem consists of a functionally graded (FG) layer resting on a half plane and pressed with distributed load from the top. Firstly, analytical solution of the problem is obtained by using theory of elasticity and integral transform techniques. The problem is reduced a system of integral equation in which the contact pressure are unknown functions. The numerical solution of the integral equation was carried out with Gauss-Jacobi integration formulation. Secondly, finite element model of the problem is constituted using ANSYS software and the two-dimensional analysis of the problem is carried out. The results show that contact areas and the contact stresses obtained from FEM provide boundary conditions of the problem as well as analytical results. Thirdly, the contact problem has been extended based on the MLP. The MLP with three-layer was used to calculate the contact distances. Material properties and loading states were created by giving examples of different values were used at the training and test stages of MLP. Program code was rewritten in C++. As a result, average deviation values such as 0.375 and 1.465 was obtained for FEM and MLP respectively. The contact areas and contact stresses obtained from FEM and MLP are very close to results obtained from analytical method. Finally, this study provides evidence that there is a good agreement between three methods and the stiffness parameters has an important effect on the contact stresses and contact areas.