• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.651-656
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• 1997

Fission product release (FPR) assessment for End Fitting Failure (EFF) in CANDU reactor loaded with CANFLEX-natural uranium (NU) fuel bundles has been peformed. The predicted results are compared with those for the reactor loaded with standard 37-element bundles. The total channel I-131 release at the end of transient for EFF accident is calculated to be 380.8 TBq and 602.9 TBq for the CANFLEX bundle and standard bundle channel cases, respectively. They are 4.9% and 7.9% of the total inventory, respectively. The lower total releases of the CANFLEX bundle O6 channel are attributed to the lower initial fuel temperatures caused by the lower linear element power of the CANFLEX bundle compared with the standard bundle.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.469-475
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• 2010

This paper presents a method of classifying discolored defects of metal pads using geometric texture for AFVI (Automated Final Vision Inspection) systems. In PCB manufacturing process, the metal pads on PCB can be oxidized and discolored partly due to various environmental factors. Nowadays the discolored defects are manually detected and rejected from the process. This paper proposes an efficient geometric texture feature, SUTF (Symmetry and Uniformity Texture Feature) based on the symmetric and uniform textural characteristics of the surface of circular metal pads for automating AFVI systems. In practical experiments with real samples acquired from a production line, 30 discolored images and 1232 roughness images are tested. The experimental results demonstrate that the proposed method using SUTFs provides better performance compared to Gabor feature with 0% FNR (False Negative Rate) and 1.46% FPR (False Positive Rate). The performance of the proposed method shows its applicability in the real manufacturing systems.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.57-61
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• 2015

The level of change in distant PTC, near PTC, distant NTC, and near NTC was measured divided by before and after viewing 3D images. The 50 examinees were categorized into Low/ Middle/ High groups according to the level of change by test subject. Among all the entries, the exophoria group showed the highest change distribution, and in the distant and near NTC entries showed statistically significant differences in variation.

• Journal of the Korean Society of Combustion
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• v.9 no.3
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• pp.1-9
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• 2004

This study is aimed to characterize the combustion behavior of solid fuel in the various types of the combustors: stoker, rotary kiln and fluidized bed type combustors. Three different types of reduced-scale combustors are introduced, and temperatures and flue gas compositions are measured for various fuel sizes, water contents, initial temperature, and air flow rates. In case of the rotary kiln combustor, effects of rotating speed of the combustor are also investigated. Mean carbon conversion time (MCCT) and flame propagation rate (FPR) are used for the quantitative analysis. It is revealed that the reaction rates of the fuel are significantly influenced by the fuel characteristics, type of the combustors and air flow rate. Major design parameters for each type of the combustors are summarized through the reduced-scaled model analysis.

• Journal of the Korean Geophysical Society
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• v.5 no.1
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• pp.51-62
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• 2002

Investigation of underwater sedimentary layers has been carried out with GPR(Ground Penetration Radar) survey. FPR survey has been proved to be very satisfactory since the target area has shallow water depth of about 2.5 m, is a lake with no water flow, and the thickness of mud layer, which is a main survey target, is relatively thin. The results clearly showed the underwater sedimentary layers, which includes mud, sand, gravel and basement layer. Specially, the distribution and total amount of mud layers from the survey results can be used as a basic data for the dredging of mud layer in the area.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.107-118
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• 2024

With the seamless growth of the technology, network usage requirements are expanding day by day. The majority of electronic devices are capable of communication, which strongly requires a secure and reliable network. Network-based intrusion detection systems (NIDS) is a new method for preventing and alerting computers and networks from attacks. Machine Learning is an emerging field that provides a variety of ways to implement effective network intrusion detection systems (NIDS). Bagging and Boosting are two ensemble ML techniques, renowned for better performance in the learning and classification process. In this paper, the study provides a detailed literature review of the past work done and proposed a novel ensemble approach to develop a NIDS system based on the voting method using bagging and boosting ensemble techniques. The test results demonstrate that the ensemble of bagging and boosting through voting exhibits the highest classification accuracy of 99.98% and a minimum false positive rate (FPR) on both datasets. Although the model building time is average which can be a tradeoff by processor speed.

• Smart Media Journal
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• v.13 no.2
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• pp.85-94
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• 2024

Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

• Communications of Mathematical Education
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• v.33 no.4
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• pp.425-444
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• 2019

Comparing to the U.S. mathematics textbooks, this study examines the opportunity to learn statistical processes represented in mathematics textbooks reflecting 2015 revised curriculum. Analyzing four different kinds of Korean middle school mathematics textbooks and two kinds of corresponding U.S. textbooks for seventh graders, we found that the tasks dealing with all the phases of statistical processes were found only in the U.S. textbooks while not even one task in such a case was not observed in the Korean textbooks. To make matters worse, the proportion of the tasks dealing with only one phase of statistical processes was 93.3% of all the tasks in Korean textbooks. In terms of types of tasks, the types of tasks were very homogeneous in Korean textbooks, usually Types FPR or PR while more various types of tasks were found in the U.S. textbooks such as Types FRI, PRI, FR, or RI. In views of features of each phase in statistical processes, Korean textbooks heavily focused only on some particular statistical behaviors such as 'formulating a problem', 'collecting data', 'transforming data', and 'analyzing a part of data.' The findings of this study provide meaningful implications for improving statistics education and developing mathematics textbooks to enhance students' statistical thinking and problem-solving ability.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2307-2310
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• 2013

Curcumin previously was proven to inhibit angiogenesis and display potent antitumor activity in vivo and in vitro. In the present study, we investigated whether a combination curcumin with hyperthermia would have a synergistic antitumor effect in the LL/2 model. The results indicated that combination therapy significantly inhibited cell proliferation of MS-1 and LL/2 in vitro. LL/2 experiment model also demonstrated that the combination therapy inhibited tumor growth and prolonged the life span in vivo. Furthermore, combination therapy reduced angiogenesis and increased tumor apoptosis. Our findings suggest that the combination therapy exerted synergistic antitumor effects, providing a new perspective fpr clinical tumor therapy.