• Journal of Engineering Education Research
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• v.19 no.3
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• pp.23-34
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• 2016

Teaching orientations represent teachers' general way of conceptualizing their teaching. The orientations are regarded as a very important factor in developing teachers' pedagogical content knowledge because they often guide their instructional decisions such as the selection of contents and teaching strategies, the use of curricula materials, and the evaluation of learning. Thus, understanding teachers' orientations can provide meaningful suggestions to understand their instructional approaches and furthermore to enhance the quality of engineering education in college. The research question for this present study was what kinds of teaching orientations engineering professors possessed in teaching engineering courses and how the orientations were represented in their teaching. Six engineering professors, particularly interested in instructional approaches, participated in the research. The data sources included in-depth interviews with individual professors, classroom observations with field notes, and related documents. In results, four teaching orientations toward engineering courses were identified: 1) expert knowledge in engineering, 2) engineering practice, 3) social practice, and 4) interdisciplinary design. Individual professors had between one to three different teaching orientations. Even though the professors had similar orientations but their instructional strategies somewhat varied based on the disciplines.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.1
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• pp.44-49
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• 2004

The aim of this study is to compare the methods in analyzing bio-signals representing measure driver's psychophysiological staus. This study has considered three approaches: first, the deterministic approach calculating the mean and standard deviation of bio-signal, second, probabilistic approach converting driver's bio-signal values to probability density function and identifying individual state relative to overall distribution, and third, diagnostic approach identifying the pattern change of signal over certain period of time. For evaluation of analysis methods, driver's bio-signal was collected under various road conditions, and three analysis approaches were applied respectively. In result, the deterministic approach was found to be simple to use, but generated a large variability of bio-signal. The probabilistic approach provide a relative status of individual driver among overall population, but too much affected by temporal variability of individual driver. The diagnostic approach seemed to reasonably find driver's psychophysiological change over certain period of time, but still needs to develop quantification method of the bio-signal.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Advances in Energy Research
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• v.6 no.2
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• pp.91-101
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• 2019

This paper proposes an efficient data-driven approach to build models for predicting energy consumption in buildings. Data used in this research is collected by installing humidity and temperature sensors at different locations in a building. In addition to this, weather data from nearby weather station is also included in the dataset to study the impact of weather conditions on energy consumption. One of the main emphasize of this research is to make feature selection independent of domain knowledge. Therefore, to extract useful features from data, two different approaches are tested: one is feature selection through principal component analysis and second is relative importance-based feature selection in original domain. The regression model used in this research is gradient boosting regression and its optimal parameters are chosen through a two staged coarse-fine search approach. In order to evaluate the performance of model, different performance evaluation metrics like r2-score and root mean squared error are used. Results have shown that best performance is achieved, when relative importance-based feature selection is used with gradient boosting regressor. Results of proposed technique has also outperformed the results of support vector machines and neural network-based approaches tested on the same dataset.

• Archives of Pharmacal Research
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• v.25 no.2
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• pp.111-136
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• 2002

The prodrug and antedrug concepts, which were developed to overcome the physical and pharmacological shortcomings of various therapeutic classes of agents, employ diametrically different metabolic transformations. The prodrug undergoes a predictable metabolic activation prior to exhibiting its pharmacological effects in a target tissue while the antedrug undergoes metabolic deactivation in the systemic circulation upon leaving a target tissue. An increased therapeutic index is the aspiration for both approaches in designing as well as evaluation criteria. The recent research endeavors of prodrugs include the gene-directed and antibody-directed enzymatic activation of a molecule in a targeted tissue, organ specific delivery, improved bioavailabilities and cellular penetration of nucleotides. As for antedrugs, emphasis in research has been based upon the design and synthesis of systemically inactive molecule by incorporating a metabolically labile functional group into an active molecule.

• Nuclear Engineering and Technology
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• v.35 no.2
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• pp.154-164
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• 2003

The explicit consideration of different pressurization rates in estimating the probabilities of containment failure modes has a profound effect on the confidence of containment performance evaluation that is so critical for risk assessment of nuclear power plants. Except for the sophisticated NUREG-1150 study, many of the recent containment performance analyses (through Level 2 PSAs or IPE back-end analyses) did not take into account an explicit distinction between slow and fast pressurization in their analyses. A careful investigation of both approaches shows that many of the approaches adopted in the recent containment performance analyses exactly correspond to the NUREG-1150 approach for the prediction of containment failure mode probabilities in the presence of fast pressurization. As a result, it was expected that the existing containment performance analysis results would be subjected to greater or less conservatism in light of the ultimate failure mode of the containment. The main purpose of this paper is to assess potential conservatism of a plant-specific containment performance analysis result in light of containment failure mode probabilities.

• Journal of Soil and Groundwater Environment
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• v.17 no.1
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• pp.22-32
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• 2012

This study suggests a method to grade groundwater quality quantitatively using statistical approaches for evaluating the quality of groundwater in wells included in the Groundwater Quality Monitoring Network (GQMN). The proposed analysis method is applied to GQMN data from 2001 to 2008 for nitrate nitrogen, chloride, trichloroethylene, potential of hydrogen (pH), and electrical conductivity. The analysis results are obtained as groundwater quality grades of the groundwater representing each of the monitoring stations. The degree of groundwater contamination is analysed for water quality parameters, district, and usage. The results show that the degree of groundwater contamination is relatively high by nitrate nitrogen, bacteria and electrical conductivity and at Seoul, Incheon, Gwangju, Gyeonggido and Jeollado. The degree of contamination by nitrate nitrogen and trichloroethylene is especially high when the groundwater is used for agricultural and industrial water, respectively. It is evaluated that potable groudnwater in GQMN is significantly vulnerable to nitrate nitrogen and bacteria contamination.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.1-12
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• 2018

Mixed-criticality systems consist of components with different criticality. Recently, components are categorized depending on criticality by ISO 26262 standard and DO-178B standard in automotive and avionic domain. Existing mixed-criticality system research achieved efficient and safe scheduling through system-level criticality mode. The drawback of these approaches is performance degradation of low-criticality tasks on high-criticality mode. Task-level criticality mode is one method to address the problem and improve the performance of low-critical tasks. In this paper, we propose probabilistic performance metric for the approach. In simulation results with probabilistic performance metric, we showed that our approach has better performance than the existing approaches.

• Genomics & Informatics
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• v.17 no.2
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• pp.17.1-17.3
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• 2019

Text mining has become an important research method in biology, with its original purpose to extract biological entities, such as genes, proteins and phenotypic traits, to extend knowledge from scientific papers. However, few thorough studies on text mining and application development, for plant molecular biology data, have been performed, especially for rice, resulting in a lack of datasets available to solve named-entity recognition tasks for this species. Since there are rare benchmarks available for rice, we faced various difficulties in exploiting advanced machine learning methods for accurate analysis of the rice literature. To evaluate several approaches to automatically extract information from gene/protein entities, we built a new dataset for rice as a benchmark. This dataset is composed of a set of titles and abstracts, extracted from scientific papers focusing on the rice species, and is downloaded from PubMed. During the 5th Biomedical Linked Annotation Hackathon, a portion of the dataset was uploaded to PubAnnotation for sharing. Our ultimate goal is to offer a shared task of rice gene/protein name recognition through the BioNLP Open Shared Tasks framework using the dataset, to facilitate an open comparison and evaluation of different approaches to the task.

• Ocean and Polar Research
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• v.41 no.3
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• pp.193-202
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• 2019

There have been various approaches for efficiency improvement of a Darrieus tidal stream turbine after it was introduced as an alternative of horizontal axis turbines. Among the approaches, the researches on the interaction effect of dual configuration were conducted. In this study, a dual Darrieus turbine with a coupling mechanism was proposed for investigating the interaction effect. Also, the effect of bi-directional tidal stream was analyzed with prototype fabrication, apparatus set-up and experiment conduction in indoor and offshore facilities. As the results of the experiments, the dual turbine in case of counter-rotation and inflow between the turbines improved efficiencies by 9.5% and 11.31%, respectively, as compared to the single turbine. Also, the dual turbine in case of the inflow improved efficiencies by 9.4% and 16.62%, respectively, as compared to that in case of outflow between the turbines which represented the case of 180 degrees change of flow direction after slack water. Therefore, the proposed dual turbine showed the advantage in terms of the efficiency as compared to the single turbine and the effect level of the slack water on the performance of the dual turbine was investigated.