• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.55-68
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• 2007

DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods. In this paper, we proposed a DNA sequence alignment algorithm utilizing quality information and a fuzzy inference method utilizing characteristics of DNA sequence fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods using DNA sequence quality information. In conventional algorithms, DNA sequence alignment scores were calculated by the global sequence alignment algorithm proposed by Needleman-Wunsch applying quality information of each DNA fragment. However, there may be errors in the process for calculating DNA sequence alignment scores in case of low quality of DNA fragment tips, because overall DNA sequence quality information are used. In the proposed method, exact DNA sequence alignment can be achieved in spite of low quality of DNA fragment tips by improvement of conventional algorithms using quality information. And also, mapping score parameters used to calculate DNA sequence alignment scores, are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments. From the experiments by applying real genome data of NCBI (National Center for Biotechnology Information), we could see that the proposed method was more efficient than conventional algorithms using quality information in DNA sequence alignment.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.244-254
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• 2009

This paper describes a remote system to monitor the circadian behavioral patterns of elders who live alone. The proposed system was designed and implemented to provide more conveniently and reliably the required functionalities of a remote monitoring system for elders based on the development of first phase prototype[2]. The developed system is composed of an in-house sensing system and a server system. The in-house sensing system is a set of wireless sensor nodes which have pyroelectric infrared (PIR) sensor to detect a motion of elder. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to caregivers (friends, family and social workers) for more cost effective intelligent care service. The improved second phase system can provide 'automatic diagnosis', 'going out detection', and enhanced user interface functionalities. We have evaluated the first and second phase monitoring systems from real field experiments of 3/4 months continuous operation with installation of 9/15 elders' houses, respectively. The experimental results show the promising possibilities to estimate the behavioral patterns and the current status of elder even though the simplicity of sensing capability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1380-1386
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• 2007

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

• Journal of agriculture & life science
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• v.46 no.3
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• pp.11-17
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• 2012

This study was conducted to clarify the effect of horticultural therapy on activities of daily living and interpersonal relation of institutionalized intellectual disabilities. The experiment was performed with 8 controls and 8 experiments of J institution in Yongdam, Jeju. Horticultural therapy program was performed once a week for 2 hours total 20 times from Mar. 2009 through mid July 2009. Evaluation in activities of daily living indicated that all functions except eating showed no change or worsened in controls, however, all functions except moving were improved in experimental subjects. Interpersonal relation evaluation showed no difference from 42.25 to 42.25 in control, but increased 8.62 points from 41.75 to 50.37 showing very significant change at the level of 99% in experimental subjects. Group activity evaluation increased very significantly at the level of 99% in physical/perceptual abilities, social interaction, cognitive ability, emotion status, and vocational interests. From the above results, horticultural therapy proved effectively in activities of daily living and interpersonal relation of institutionalized intellectual disabilities.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.303-316
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• 2005

Strong radar returns were observed in oyster sea farms, and coherent interferometric pairs were successfully constructed. Tide height in coastal area is possible to be measured by using interferometric phase and intensity of SAR data. This SAR application technique for measuring the tide height in the near coastal zone can be further improved when applied to double bounce dominant areas. In this paper, we investigate the characteristics of polarimetric signature in the oyster farm structures. Laboratory experiments were carried out using Ku-band according to the target scale. Radar returns from vertical poles are stronger than those from horizontal Pole by 10.5 dB. Single bounce components were as strong as double bounce components and more sensitive to antenna look direction. Double bounce components show quasi-linear relation with the height of vertical poles, which implies double bounce is more useful to determine water level than total power. A L-band NASA/IPL airborne SAR (AIRSAR) image was classified into single-, double-bounce, and volume scattering components. It is observed that oyster farms are not always characterized by double bounced scattering. Double bounce is a main scattering mechanism in oyster farms standing above seawater, while single bounce is stronger than double bounce when bottom tidal flats are exposed to air. Ratios of the normalized single to double bounce components in the former and latter cases were 0.46 and 5.62, respectively. It is necessary to use double bounce dominant sea farms for tide height measurement by DInSAR technique.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1039-1048
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• 2019

Symbolic execution, an automatic search method for vulnerability verification, has been technically improved over the last few years. However, it is still not practical to analyze the program using only the symbolic execution itself. One of the biggest reasons is that because of the path explosion problem that occurs during program analysis, there is not enough memory, and you can not find the solution of all paths in the program using symbolic execution. Thus, it is practical for the analyst to construct a path for symbolic execution to a target with vulnerability rather than solving all paths. In this paper, we propose a static analysis - based backward CFG(Control Flow Graph) generation technique that can be used in symbolic execution for program analysis. With the creation of a backward CFG, an analyst can select potential vulnerable points, and the backward path generated from that point can be used for future symbolic execution. We conducted experiments with Linux binaries(x86), and indeed showed that potential vulnerability selection and backward CFG path generation were possible in a variety of binary situations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3367-3378
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• 2021

The design phase and safety assessment of Generation IV liquid metal-cooled fast reactors calls for the improvement of fuel pin performance codes, in particular the enhancement of their predictive capabilities towards uranium-plutonium mixed oxide fuels and stainless-steel cladding under irradiation in fast reactor environments. To this end, the current capabilities of fuel performance codes must be critically assessed against experimental data from available irradiation experiments. This work is devoted to the assessment of three European fuel performance codes, namely GERMINAL, MACROS and TRANSURANUS, against the irradiation of two fuel pins selected from the SUPERFACT-1 experimental campaign. The pins are characterized by a low enrichment (~ 2 wt.%) of minor actinides (neptunium and americium) in the fuel, and by plutonium content and cladding material in line with design choices envisaged for liquid metal-cooled Generation IV reactor fuels. The predictions of the codes are compared to several experimental measurements, allowing the identification of the current code capabilities in predicting fuel restructuring, cladding deformation, redistribution of actinides and volatile fission products. The integral assessment against experimental data is complemented by a code-to-code benchmark focused on the evolution of quantities of engineering interest over time. The benchmark analysis points out the differences in the code predictions of fuel central temperature, fuel-cladding gap width, cladding outer radius, pin internal pressure and fission gas release and suggests potential modelling development paths towards an improved description of the fuel pin behaviour in fast reactor irradiation conditions.

• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.664-670
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• 2021

Stainless steel was applied as bipolar plate (BP) of polymer electrolyte membrane fuel cell (PEMFC) due to high mechanical strength, electrical conductivity, and good machinability. However, stainless steel was corroded and increased contact resistance resulting PEMFC performance decrease. Although the corrosion resistance could be improved by surface treatment such as noble metal coating, there is a disadvantage of cost increase. The stainless steel corrosion behavior and passive layer influence on PEMFC performance should be studied to improve durability and economics of metal bipolar plate. In this study, SUS316L bipolar plate of 25 cm² active area was manufactured, and experiments were conducted for corrosion behavior at an anode and cathode. The influence of SUS316L BP corrosion on fuel cell performance was measured using the polarization curve, impedance, and contact resistance. The metal ion concentration in drained water was analyzed during fuel cell operation with SUS316L BP. It was confirmed that the corrosion occurs more severely at the anode than at the cathode for SUS316L BP. The contact resistance was increased due to the passivation of SUS316L during fuel cell operation, and metal ions continuously dissolved even after the passive layer formation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.473-482
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• 2021

The introduction of automated flight systems has greatly improved aviation safety, but aircraft pilots continue to face new challenges. The pilot's stress from an aeronautical perspective can be distinguished by the 'Startle and Surprise' responses. 'Startle' is a short, strong physiological response to sudden or threatening stimuli such as unexpected gunfire. 'Surprise' is a cognitive-emotional response to an event that goes beyond one's expectations. In Martin et al.'s (2012) Startle Effect Experiment, the pilot identified physiological responses in the 'Startle' state, including delayed response and increased heart rate. In the Rahim (2020) Startle/Surprise experiment, the pilot's breathing rate and pulse rate did not change due to pre-planned emergency training. On the other hand, it was confirmed that the pilot's respiratory and heart rate were greatly increased due to the complicated aircraft and unplanned emergencies. Based on the results of these experiments, domestic pilots need to be trained to handle non-technical and various unexpected emergencies that could arise in an aircraft, rather than be just put through courses for enhancing technical capabilities or simple repetitive training as required by aviation law.