• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.1987-1996
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• 2009

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

• Clinical and Experimental Reproductive Medicine
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• v.24 no.2
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• pp.273-277
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• 1997

This case report describes the pregnancy following the transfer of cryopreserved embryos generated from intracytoplasmic sperm injection (ICSI) using frozen-thawed sperm obtained by microepididymal sperm aspiration (MESA) in patient with congenital absence of the vas deferens (CAVD).

• Smart Media Journal
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• v.8 no.1
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• pp.27-34
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• 2019

Ransomware is a malicious program code evolved into various forms of attack. Unlike traditional Ransomware that is being spread out using email attachments or infected websites, a new type of Ransomware, such as WannaCryptor, may corrupt files just for being connected to the Internet. Due to global Ransomware damage, there are many studies conducted to detect and defense Ransomware. However, existing research on Ransomware detection only uses Ransomware signature database or monitors specific behavior of process. Additionally, existing Ransomware detection methods hardly detect and defense a new Ransomware that behaves differently from the traditional ones. In this paper, we propose a method to detect Ransomware by arranging decoy files and analyzing the method how Ransomware accesses and operates files in the file system. Also, we conduct experiments using proposed method and provide the results of detection and defense of Ransomware in this paper.

• Korean Journal of Materials Research
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• v.31 no.1
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• pp.16-22
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• 2021

In this study, quantum dot-sensitized solar cells (QDSSC) using CdSe/ZnS quantum dots (QD) of various sizes with green, yellow, and red colors are developed. Quantum dots, depending their different sizes, have advantages of absorbing light of various wavelengths. This absorption of light of various wavelengths increases the photocurrent production of solar cells. The absorption and emission peaks and excellent photochemical properties of the synthesized quantum dots are confirmed through UV-visible and photoluminescence (PL) analysis. In TEM analysis, the average sizes of individual green, yellow, and red quantum dots are shown to be 5 nm, 6 nm, and 8 nm. The J-V curves of QDSSC for one type of QD show a current density of 1.7 mA/㎠ and an open-circuit voltage of 0.49 V, while QDSSC using three type of QDs shows improved electrical characteristics of 5.52 mA/㎠ and 0.52 V. As a result, the photoelectric conversion efficiency of QDSSC using one type of QD is as low as 0.53 %, but QDSSC using three type of QDs has a measured efficiency of 1.4 %.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.93-104
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• 2011

A conditional access system is an essential element in IPTV services enabling service providers to allow authorized access to their services only to paid subscribers. Currently, there are two types of IPTV service models, namely PPC (pay-per-channel) and PPV (pay-per-view). However, a more desirable model would be the flexible PPC model, in which subscribers are free to choose any combination of preferred channels and add/remove channels independently. In this paper, we first point out that a previously proposed key management scheme for F-PPC is not secure. We then propose a new conditional access system using 4-level key hierarchy to realize secure F-PPC services. Compared to existing schemes, the proposed system is very efficient, just requiring O(1) communication for key update.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.47-55
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• 2019

As the damage caused by GPS jamming has been increased, researches for detecting and preventing GPS jamming is being actively studied. This paper deals with a GPS jamming detection method using multiple GPS receiving channels and three-types machine learning techniques. Proposed multiple GPS channels consist of commercial GPS receiver with no anti-jamming function, receiver with just anti-noise jamming function and receiver with anti-noise and anti-spoofing jamming function. This system enables user to identify the characteristics of the jamming signals by comparing the coordinates received at each receiver. In this paper, The five types of jamming signals with different signal characteristics were entered to the system and three kinds of machine learning methods(AB: Adaptive Boosting, SVM: Support Vector Machine, DT: Decision Tree) were applied to perform jamming detection test. The results showed that the DT technique has the best performance with a detection rate of 96.9% when the single machine learning technique was applied. And it is confirmed that DT technique is more effective for GPS jamming detection than the binary classifier techniques because it has low ambiguity and simple hardware. It was also confirmed that SVM could be used only if additional solutions to ambiguity problem are applied.

• Journal of Drive and Control
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• v.18 no.4
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• pp.1-8
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• 2021

An electro proportional pressure control valve is mainly used to control the clutch of an agricultural tractor's automatic transmission. During transmission, the operating, hydraulic oil is mix with many kinds of contaminants. The contaminants can be trapped between the valve body and spool of the proportional pressure control valve leading to abnormal operating conditions and finally critical damage to the transmission hydraulic system. The present study aimed to verify the valve control algorithm as a basic study of developing control logic that removes contaminants between the spool and the body of the proportional pressure control valve. To develop the algorithm, MATLAB/SIMULINK was used. PWM method was used to control the applied solenoid coil current. The effectiveness of the algorithm was verified by comparing the actual pressure of the normal valve with the actual pressure of the abnormal valve. Based on the present study findings, when the algorithm was applied, the response of the valve pressure according to the current became stable and oil contaminated particles were removed. In the future study, the control algorithm will be optimized for the stability of the proportional pressure reducing valve, and it will be verified in consideration with the driving of the clutch.

• Journal of Powder Materials
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• v.30 no.1
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• pp.53-64
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• 2023

Atomic layer etching (ALE) is a promising technique with atomic-level thickness controllability and high selectivity based on self-limiting surface reactions. ALE is performed by sequential exposure of the film surface to reactants, which results in surface modification and release of volatile species. Among the various ALE methods, thermal ALE involves a thermally activated reaction by employing gas species to release the modified surface without using energetic species, such as accelerated ions and neutral beams. In this study, the basic principle and surface reaction mechanisms of thermal ALE?processes, including "fluorination-ligand exchange reaction", "conversion-etch reaction", "conversion-fluorination reaction", "oxidation-fluorination reaction", "oxidation-ligand exchange reaction", and "oxidation-conversion-fluorination reaction" are described. In addition, the reported thermal ALE processes for the removal of various oxides, metals, and nitrides are presented.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.105-118
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• 2023

In this study, we predicted the presence of fog with a one-hour delay using the XGBoost DART machine learning algorithm for Andong, which had the highest occurrence of fog among inland stations from 2016 to 2020. We used six datasets: meteorological data, agricultural observation data, additional derived data, and their expanded data. The weather phenomenon numbers obtained through naked-eye observations and the visibility distances measured by visibility meters were classified as fog [1] or no-fog [0]. We set up twelve machine learning modeling experiments and used data from 2021 for model validation. We mainly evaluated model performance using recall and AUC-ROC, considering the harmful effects of fog on society and local communities. The combination of oversampled meteorological data features and the target induced by weather phenomenon numbers showed the best performance. This result highlights the importance of naked-eye observations in predicting fog using machine learning algorithms.