• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1677-1688
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• 2020

In the sodium-cooled fast reactor, the steam generator is a heat exchange device between sodium and water, which may cause leakage, resulting in a sodium-water reaction accident, which in turn affects the safe operation of the entire nuclear reactor. To this end, the electromagnetic vortex flowmeter is used to detect leakage of the steam generator and its signal processing method is studied in this paper. The hydraulic experiment was carried out by using water instead of liquid sodium, and the sensor output signal of the electromagnetic vortex flowmeter under different gas injection volumes was collected. The bubble noise signal is reflected by the base line of the sensor output signal. According to the relationship between the proportion of the bubble noise signal in the sensor output signal and the gas injection volume, a signal processing method based on the energy ratio calculation is proposed to detect whether the water contains bubbles. The gas injection experiment of liquid sodium was conducted to verify the effectiveness of the signal processing method in the detection of bubbles in sodium, and the minimum detectable leak rate of water in the steam generator was detected to be 0.2 g/s.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.451-456
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• Journal of Korean Academy of Nursing
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• v.20 no.3
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• pp.300-306
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• 1990

Colorectal cancer is second only to lung cancer as a cause of death due to cancer in the united States. Studies have shown that fecal occult blood(FOB) tests are effective in detecting colorectal cancer in its early stages. To motivate worksite FOB testing, a randomized controlled trial was conducted. Employees 40 years or older from three federal agencies in Washington State were randomized to a control group(n＝139) which received a letter stating the availability of the FOB test at the worksite clinic or to an intervention group(n＝139) which received the letter about facts on colorectal cancer and a Colorectal Cancer Risk Appraisal. The Colorectal Cancer Risk Appraisal included a feedback on an individual's risk of developing colorectal cancer compared to his / her peers in terms of ‘normal’, ‘moderate’, or ‘high’ risk status. After 3 months, a follow-up questionnaire was sent to all participants to measure the effectiveness of the intervention. In the analysis of the three major outcomes, two possible confounding factors(dietary fat and family history of colorectal cancer) were controlled by logistic regression. Based on a review of the worksite clinic records, the Intervention group had 4.3% higher compliance rate with the FOB test during the follow-up period compared to the control group(p＝.10). The largest effect of the intervention was on the employees' intention to get a FOB test within the next year(62.6% in the intervention group vs. 36.2% in the control group, OR＝3.18, p＜.001). In the final Multivariate logistic model, the employees who were more likely to intend to get a FOB test within the next year were in the intervention group ; were at ‘moderate’ or ‘high’ risk of colorectal cancer ; knew more about the availability of the FOB test at the worksite clinic ; and had a FOB test during the last three years.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.561-564
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• 2004

Crack sealing automation machines' have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). It is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose a crack network mapping and modeling algorithm using neural network for improving the accuracy of the algorithm used in the APCS. It is anticipated that the effective use of the proposed algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2C
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• pp.37-47
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• 2012

In this study, three centrifuge tests were performed to evaluate the feasibility of three physical quantities for detecting internal defect of earth core fill dam: pore water pressure, temperature, and electrical resistance. For this purpose, the measurement system for pore water pressure, temperature and electrical resistance on centrifuge model dams was established. Three centrifuge tests included a fill dam without internal defect and two other dams with artificial internal defect in the core. The effectiveness of seepage monitoring was examined during the centrifuge test. Test results showed the applicability of monitoring techniques to detect internal defect by monitoring pore water pressure, temperature, and electrical resistance.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.53-60
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• 2011

This paper proposes fusion methods of license plate detection and super-resolution for improving license plate recognition in low-resolution images. In the proposed method, we apply the license plate detection based on local structure pattern feature and the sequential super-resolution based on Kalman filter. The proposed fusion methods are divided into two according to whether the license plate is detected or not in the input image : (i) performing license plate detection after restoring whole image through super resolution, and (ii) restoring only the detected region through super-resolution after detecting the license plate. We demonstrated effectiveness of the proposed methods in various environments.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.81-87
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• 2015

In order for a Power Assisted Wheelchair (PAW) to maintain a straight driving direction, the same force must be delivered to both wheels. However, a human has different strength between the right and left arms, and cannot control the force uniformly at all times. Therefore, appropriate assist torque shall be generated from unbalanced human torque inputs by detecting the user intention, in order to maintain direction uniformly in straight sections or change direction quickly in curved sections. In this study, a special function is proposed to detect the intention of drivers on the basis of temporal similarity between the input torque signals, and a torque balancing technique based on this function is proposed. In the experiments, the effectiveness of the proposed torque balancing method are verified.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.5
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• pp.429-436
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• 2010

Recently, (terahertz ray) applications have emerged as one of the most promising new powerful nondestructive evaluation (NDE) techniques. In this study, a new T-ray time-domain spectroscopy system was utilized for detecting and evaluating layup effect and flaw in FRP composite laminates. Extensive experimental measurements in reflection and thru-transmission modes were made to map out the T-ray images. Especially this was demonstrated in thick GFRP laminates containing double saw slots. In carbon composites the penetration of terahertz waves is limited to some degree and the detection of flaws is strongly affected by the angle between the electric field(E-field) vector of the terahertz waves and the intervening fiber directions. The artificial defects investigated by terahertz waves were bonded foreign material, simulated disbond and delamination and mechanical impact damage. The effectiveness and limitations of terahertz radiation for the NDE of composites are discussed.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.37-47
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• 2013

Recently, lots of research results on program comparison have been reported since the code theft become frequent as the increase of code mobility. This paper proposes a plagiarism detection method using class structures. The proposed method constructs a graph representing the referential relationship between the member variables and the methods. This relationship is shown as a bipartite graph and the test for graph isomorphism is applied on the set of graphs to measure the similarity of the programs. In order to measure the effectiveness of this method, an experiment was conducted on the test set, the set of Java source codes submitted as solutions for the programming assignments in Object-Oriented Programming course of Pusan National University in 2012. In order to evaluate the accuracy of the proposed method, the F-measure is compared to those of JPlag and Stigmata. According to the experimental result, the F-measure of the proposed method is higher than those of JPlag and Stigmata by 0.17 and 0.34, respectively.