• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.157-163
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• 2017

The object segmentation approach has the merit of reducing the processing cost required to detect moths of interest, because it applies a moth detection algorithm to the segmented objects after segmenting the objects individually in the moth image. In this paper, an object segmentation method for moth detection in pheromone trap images is proposed. Our method consists of preprocessing, thresholding, morphological filtering, and object labeling processes. Thresholding in the process is a critical step significantly influencing the performance of object segmentation. The proposed method can threshold very elaborately by reflecting the local properties of the moth images. We performed thresholding using global and local versions of Ostu's method and, used the proposed method for the moth images of Carposina sasakii acquired on a pheromone trap placed in an orchard. It was demonstrated that the proposed method could reflect the properties of light and background on the moth images. Also, we performed object segmentation and moth classification for Carposina sasakii images, where the latter process used an SVM classifier with training and classification steps. In the experiments, the proposed method performed the detection of Carposina sasakii for 10 moth images and achieved an average detection rate of 95% of them. Therefore, it was shown that the proposed technique is an effective monitoring method of Carposina sasakii in an orchard.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.35-46
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• 2017

Recently, attackers using malicious code in cyber security have been increased by attaching malicious code to a mail and inducing the user to execute it. Especially, it is dangerous because it is easy to execute by attaching a document type file. The author analysis is a research area that is being studied in NLP (Neutral Language Process) and text mining, and it studies methods of analyzing authors by analyzing text sentences, texts, and documents in a specific language. In case of attack mail, it is created by the attacker. Therefore, by analyzing the contents of the mail and the attached document file and identifying the corresponding author, it is possible to discover more distinctive features from the normal mail and improve the detection accuracy. In this pager, we proposed IADA2(Intelligent Attack mail Detection based on Authorship Analysis) model for attack mail detection. The feature vector that can classify and detect attack mail from the features used in the existing machine learning based spam detection model and the features used in the author analysis of the document and the IADA2 detection model. We have improved the detection models of attack mails by simply detecting term features and extracted features that reflect the sequence characteristics of words by applying n-grams. Result of experiment show that the proposed method improves performance according to feature combinations, feature selection techniques, and appropriate models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.185-191
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• 2015

This paper suggest the safety class communication board in order to design the safety network of the nuclear safety class controller. The reactor protection system use the digitized networks because from analog system to digital system. The communication board shall be provided to pass the required performance and test of the safety class in the digital network used in the nuclear safety class. Communication protocol is composed of physical layer(PHY), data link layer(MAC: Medium Access Control), the application layer in the OSI 7 layer only. The data link layer data package for the cyber security has changed. CRC32 were used for data quality and the using one way communication, not requests and not responses for receiving data, does not affect the nuclear safety system. It has been designed in accordance with requirements, design, verification and procedure for the approving the nuclear safety class. For hardware verification such as electromagnetic test, aging test, inspection, burn-in test, seismic test and environmental test in was performed. FPGA firmware to verify compliance with the life-cycle of IEEE 1074 was performed by the component testing and integration testing.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.183-191
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• 2020

In this study, in order to obtain basic data on the development of a new hanbok skirt pattern for developing a customizing system, a new hanbok brand skirt pattern was compared and analyzed. After analyzing the patterns of six new hanbok brands, virtual simulation was performed to evaluate the appearance, clothing pressure, and airgap. As a result of analyzing the waist skirt patterns of commercial new hanbok brands A, B, C, D, E, and F, it was found that they were produced in different dimensions despite the free size skirt of the same design. The pattern of new hanbok waist skirt was composed of a flat pattern like the traditional hanbok. As a result of appearance evaluation, it was evaluated that there were significant differences between the patterns of the six brands in all the evaluation items on the front, side, and back. In the appearance evaluation, it was evaluated that the waist skirt of the B brand was excellent. As a result of examining the color distribution and airgap, it was evaluated that the airgap was large in most parts due to the characteristics of the waist skirt worn around the waist, and the garment pressure was low. In this paper, we propose a basic data for standardizing dimensions and patterns according to activation New Hanbok. It is thought that a unified pattern development based on the B brand pattern should be made.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• 한국사회정책
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• v.23 no.1
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• pp.95-123
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• 2016

As Korean society grows rapidly older, a systematic analysis of the determinants of labor supply behavior among the elderly becomes a prerequisite for designing more effective senior employment policies and income security regime for the elderly. Literatures review shows that a majority of previous researches have been ignoring the problem of "endogenous predictor" especially when it comes to the estimation of the effects of the two key variables, education and non-labor income, on labor supply decisions among older people. They have failed to take into consideration the unobserved heterogeneities which might affect both labor supply decisions of the elderly and their levels of education and non-labor income, which means, according to some econometric literatures, that the estimated coefficients of the two predictors can be inconsistent. The paper tries to redress the endogeneity problem by employing a panel logit model with data from the 1st. to 4th. wave of the KLoSA(Korean Longitudinal Survey of Ageing) to estimate the effects of key predictors on the probability of getting jobs among older people(ages of 60 or older). Both a random effects and a fixed effects model reaffirms that non-labor income has a negative effect on the chances of being employed. And a random effects model shows that the effect of education is also negative, as has frequently been reported by previous studies. That means the effects of education and non-labor income on elderly employment remain negative after the effect of unobserved heterogeneities is controled for and the problem of endogenous predictors is redressed through an appropriate panel data analysis. These findings mean, in turn, that when Korean baby-boomers, who had acquired an unprecedentedly higher level of education and were expected to enjoy ever-larger amount of non-labor income than their preceding generations, retires in near future, their incentives to work will become much weaker and the lack of labor-force and the burden of financing increased public pension expenditure will become more troublesome. The paper concludes with recommending some policy initiatives helpful to solve these expected problems.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.35-44
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• 2022

In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.303-312
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• 2022

Bridges across waterways act as interference factors, that reduce the navigable water area from the perspective of navigation safety. To analyze the safety navigational width of ships navigating bridges across waterways, the optimal traffic distribution based on AIS data was investigated, and ships were classified according to size through k-means clustering. As a result of the goodness-of-fit analysis of the clustered data, the lognormal distribution was found to be close to the optimal distribution for Incheon Bridge and Busan Harbor Bridge. Also, the normal distributions for Mokpo Bridge and Machang Bridge were analyzed. Based on the lognormal and normal distribution, the analysis results assumed that the safe passage range of the vessel was 95% of the confidence interval, As a result, regarding the Incheon Bridge, the difference between the normal distribution and the lognormal distribution was the largest, at 64m to 98m. The minimum difference was 10m, which was revealed for Machang Bridge. Accordingly, regarding Incheon Bridge, it was analyzed that it is more appropriate to present a safety width of traffic by assuming a lognormal distribution, rather than suggesting a safety navigation width by assuming a normal distribution. Regarding other bridges, it was analyzed that similar results could be obtained using any of the two distributions, because of the similarity in width between the normal and lognormal distributions. Based on the above results, it is judged that if a safe navigational range is presented, it will contribute to the safe operation of ships as well as the prevention of accidents.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.65-79
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• 2020

As Programmable Logic Controllers (PLCs), popular components in industrial control systems (ICS), are incorporated with the technologies such as micro-controllers, real-time operating systems, and communication capabilities. As the latest PLCs have been connected to the Internet, they are becoming a main target of cyber threats. This paper proposes two sanitizers that improve the security of uC/OS-II based firmware for a PLC. That is, we devise BU sanitizer for detecting out-of-bounds accesses to buffers and UaF sanitizer for fixing use-after-free bugs in the firmware. They can sanitize the binary firmware image generated in a desktop PC before downloading it to the PLC. The BU sanitizer can also detect the violation of control flow integrity using both call graph and symbols of functions in the firmware image. We have implemented the proposed two sanitizers as a prototype system on a PLC running uC/OS-II and demonstrated the effectiveness of them by performing experiments as well as comparing them with the existing sanitizers. These findings can be used to detect and mitigate unintended vulnerabilities during the firmware development phase.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.23-29
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• 2022

To detect harmful chemical substances in seawater, we fabricated a prototype sensor and evaluated its performance. The prototype sensor consisted of a detector, housing, and driving circuit. We built the detector by printing an Indium-Tin-Oxide (ITO) nanoparticle film on a flexible substrate, and it had two detection parts for simultaneous detection of temperature and HNS concentration. The housing connected the detector and the driving circuit and was made of Teflon material to prevent chemical reactions that may affect sensor performance. The driving circuit supplied electric power, and display measured data using a bridge circuit and an Arduino board. We evaluated the sensor performances such as response (ΔR), the limit of detection (LOD), response time, and errors to confirm the specification.