• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.91-103
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• 2009

A cryptographic module (CM) is an implementation of various cryptographic algorithms and functions by means of hardware or software, When a CM is validated or certified under the CM validation program(CMVP), a finite state model(FSM) of the CM should be developed and provided, However, guides or methods of modeling and analysis of a FSM is not well-known, because the guide is occasionally regarded as a proprietary know-how by developers as well as verifiers of the CM. In this paper, we propose a set of guides on modeling and analysis of a FSM, which is needed for validation of a CM under CMVP, and a transition test path generation algorithm, as well as implement a simple modeling tool (CM-Statecharter). A FSM of a CM is modeled by using the Statechart of UML 2.0, Statechart, overcoming weakness of a FSM, is a formal and easy specification model for finite state modeling of a CM.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.21 no.4
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• pp.15-26
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• 2019

In recent years, researchers are increasingly trying to use BIM-based 3D models for BIM nD design such as 4D (3D + Time) and 5D (4D + Cost). However, there are still many problems in efficiently using process management based on the BIM information created at each design stage. Therefore, this study proposes a method to automate 4D and 5D design support in each design stage by using BIM-based Dynamo algorithm. To do this, I implemented an algorithm that can automatically input the process information needed for 4D and 5D by using Revit's Add-in program, Dynamo. In order to support the 4D design, the algorithm was created to enable automatic process simulation by synchronizing process simulation information (Excel file) through the Navisworks program, BIM software. The algorithm was created to automatically enable process simulation. And to support the 5D design, the algorithm was developed to enable automatic extraction of the information needed for mass production from the BIM model by utilizing the dynamo algorithm. Therefore, in order to verify the 4D and 5D design support algorithms, we verified the applicability through consultation with related workers and experts. As a result, it has been demonstrated that it is possible to manage information about process information and to quickly extract information from design and design changes. In addition, BIM data can be used to manage and input the necessary process information in 4D and 5D, which is advantageous for shortening construction time and cost. This study will make it easy to improve design quality and manage design information, and will be the foundation for future building automation research.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.117-124
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• 2021

Among growth disorders, 'Short Stature' can be improved through rapid diagnosis and treatment, and for that, it is important to detect early'Short Stature'. It is recommended to measure the height steadily for early detection of 'Short Stature' and checking the kid's growth process, but existing height measurement methods have problems such as time and space limitations, cost occurrence, and difficulty in keeping records. So in this paper, we proposed an 'Development of Kid Height Measurement Application based on Image using computer vision' method using smart phones, a medium that is highly accessible to people. In images taken through a smartphone camera, the kid's height is measured using algorithms from OpenCV, a computer vision library, and the measured heights were printed on the screen through 'a comparison graph with the standard height by gender and age' and 'list by date', made possible to check the kid's growth process. It is expected to measure height anytime, anywhere without time and space limitations and costs through this proposed method, and it is expected to help early detection of 'Short Stature' and other disorder through steady height measurement and confirmation of growth process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.672-678
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• 2020

Ultra-high-speed images that accurately depict the minute movements of objects have become common as low-cost and high-performance cameras that can film at high speeds have emerged. In this paper, the proposed method removes unexpected noise contained in images after input at high speed, and then extracts an area of interest that can represent personal information, such as skin areas, from the image in which noise has been removed. In this paper, noise generated by abnormal electrical signals is removed by applying bilateral filters. A color model created through pre-learning is then used to extract the area of interest that represents the personal information contained within the image. Experimental results show that the introduced algorithms remove noise from high-speed images and then extract the area of interest robustly. The approach presented in this paper is expected to be useful in various applications related to computer vision, such as image preprocessing, noise elimination, tracking and monitoring of target areas, etc.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• Imaging Science in Dentistry
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• v.51 no.1
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• pp.1-7
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• 2021

Purpose: The aim of this study was to assess artifacts generated in cone-beam computed tomography (CBCT) of 3 types of dental implants using 3 metal artifact reduction (MAR) algorithm conditions (pre-acquisition MAR, post-acquisition MAR, and no MAR), and 2 peak kilovoltage (kVp) settings. Materials and Methods: Titanium-zirconium, titanium, and zirconium alloy implants were placed in a dry mandible. CBCT images were acquired using 84 and 90 kVp and at normal resolution for all 3 MAR conditions. The images were analyzed using ImageJ software (National Institutes of Health, Bethesda, MD) to calculate the intensity of artifacts for each combination of material and settings. A 3-factor analysis of variance model with up to 3-way interactions was used to determine whether there was a statistically significant difference in the mean intensity of artifacts associated with each factor. Results: The analysis of all 3 MAR conditions showed that using no MAR resulted in substantially more severe artifacts than either of the 2 MAR algorithms for the 3 implant materials; however, there were no significant differences between pre- and post-acquisition MAR. The 90 kVp setting generated less intense artifacts on average than the 84 kVp setting. The titanium-zirconium alloy generated significantly less intense artifacts than zirconium. Titanium generated artifacts at an intermediate level relative to the other 2 implant materials, but was not statistically significantly different from either. Conclusion: This in vitro study suggests that artifacts can be minimized by using a titanium-zirconium alloy at the 90 kVp setting, with either MAR setting.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1329-1338
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• 2021

There are rarely effective methods to help visually impaired people when they want to know the expiration date of products excepted to only Braille. In this study, we developed an expiration date notification system based on YOLO and OCR for visually impaired people. The handicapped people can automatically know the expiration date of a specific product by using our system without the help of a caregiver, fast and accurately. The proposed system is worked by four different steps: (1) identification of a target product by scanning its barcode; (2) segmentation of an image area with the expiration date using YOLO; (3) classification of the expiration date by OCR: (4) notification of the expiration date by TTS. Our system showed an average classification accuracy of about 86.00% when blindfolded subjects used the proposed system in real-time. This result validates that the proposed system can be potentially used for visually impaired people.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1231-1238
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• 2021

Recently, large online shopping malls are providing image search services as well as text or category searches. However, in the case of an image search service, there is a problem in that the search service cannot be used in the absence of an image. This paper describes the development of a system that allows users to find the clothes they want through hand-drawn images of the style of clothes when they search for clothes in an online clothing shopping mall. The hand-drawing data drawn by the user increases the accuracy of matching through neural network learning, and enables matching of clothes using various object detection algorithms. This is expected to increase customer satisfaction with online shopping by allowing users to quickly search for clothing they are looking for.

• Plant Journal
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• v.17 no.4
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• pp.53-60
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• 2021

The purpose of this study was to develop a portable vibration analyzer that is effective for acquiring and analyzing vibration data of rotating equipment of a power plant and a domestic vibration monitoring system manufacturer Nada Co., Ltd. The hardware of the developed portable vibration analyzer minimizes measurement errors by calibrating the measured values obtained through measurement uncertainty for calibration of the measuring devices in the system, and is composed of a signal processing device with high resolution through high speed data processing. The software structure implements a variety of vibration plots to execute a detailed analysis program, and applies algorithms to measure and remove noise caused by disturbances while operating a rotating machine. The developed product contributed greatly to increase the user's mobility and performance, as well as to reduce the purchase cost due to localization.