• Proceedings of the Korean Vacuum Society Conference
• /
• 2013.02a
• /
• pp.176-177
• /
• 2013

Surface plasmon polaritons (SPPs) have attracted the attention of scientists and engineers involved in a wide area of research, microscopy, diagnostics and sensing. SPPs are waves that propagate along the surface of a conductor, usually metals. These are essentially light waves that are trapped on the surface because of their interaction with the free electrons of conductor. In this interaction, the free electrons respond collectively by oscillating in resonance with the light wave. The resonant interaction between the surface charge oscillation and the electromagnetic field of the light constitutes the SPPs and gives rise to its unique properties. In this papers, we studied theoretical and experimental extraordinary transmittance (T) and reflectance (R) of 2 dimensional metal hole array (2D-MHA) on GaAs in consideration of the diffraction orders. The 2d-MHAs was fabricated using ultra-violet photolithography, electron-beam evaporation and standard lift-off process with pitches ranging from 1.8 to $3.2{\mu}m$ and diameter of half of pitch, and was deposited 5-nm thick layer of titanium (Ti) as an adhesion layer and 50-nm thick layer of gold (Au) on the semiinsulating GaAs substrate. We employed both the commercial software (CST Microwave Studio: Computer Simulation Technology GmbH, Darmstadt, Germany) based on a finite integration technique (FIT) and a rigorous coupled wave analysis (RCWA) to calculate transmittance and reflectance. The transmittance was measured at a normal incident, and the reflectance was measured at variable incident angle of range between $30^{\circ}{\sim}80^{\circ}$ with a Nicolet Fourier transmission infrared (FTIR) spectrometer with a KBr beam splitter and a MCT detector. For MHAs of pitch (P), the peaks ${\lambda}$ max in the normal incidence transmittance spectra can be indentified approximately from SP dispersion relation, that is frequency-dependent SP wave vector (ksp). Shown in Fig. 1 is the transmission of P=2.2 um sample at normal incidence. We attribute the observation to be a result of FTIR system may be able to collect the transmitted light with higher diffraction order than 0th order. This is confirmed by calculations: for the MHAs, diffraction efficiency in (0, 0) diffracted orders is lower than in the (${\pm}x$, ${\pm}y$) diffracted orders. To further investigate the result, we calculated the angular dependent transmission of P=2.2 um sample (Fig. 2). The incident angle varies from 30o to 70o with a 10o increment. We also found the splitting character on reflectance measurement. The splitting effect is considered a results of SPPs assisted diffraction process by oblique incidence.

• Journal of the Korean GEO-environmental Society
• /
• v.15 no.3
• /
• pp.65-74
• /
• 2014

Borehole investigation which is mainly used to figure out geotechnical characterizations at construction work has the benefit that it provides a clear and convincing geotechnical information. But it has limitations to get the overall information of the construction site because it is performed at point location. In contrast, geophysical measurements like seismic survey has the advantage that the geological stratum information of a large area can be characterized in a continuous cross-section but the result from geophysics survey has wide range of values and is not suitable to determine the geotechnical design values directly. Therefore it is essential to combine borehole data and geophysics data complementally. Accordingly, in this study, a three-dimensional spatial interpolation of the cross-sectional distribution of seismic refraction was performed using digitizing and geostatistical method (krigring). In the process, digital map were used to increase the trustworthiness of method. Using this map, errors of ground height which are broken out in measurement from boring investigation and geophysical measurements can be revised. After that, average seismic velocity are derived by comparing borehole data with geophysical speed distribution data of each soil layer. During this process, outlier analysis is adapted. On the basis of the average seismic velocity, integrated analysis techniques to determine the three-dimensional geological stratum information is established. Finally, this analysis system is applied to dam construction field.

• The Journal of Engineering Geology
• /
• v.34 no.1
• /
• pp.39-49
• /
• 2024

The construction of underground infrastructure is garnering growing increasing research attention owing to population concentration and infrastructure overcrowding in urban areas. An important associated task is establishing a monitoring system to evaluate stability during infrastructure construction and operation, which relies on developing techniques for ground investigation that can evaluate ground stability, verify design validity, predict risk, facilitate safe operation management, and reduce construction costs. The method proposed here uses satellite imaging in a cost-effective and accurate ground investigation technique that can be applied over a wide area during the construction and operation of infrastructure. In this study, analysis was performed using Synthetic Aperture Radar (SAR) data with the time-series radar interferometric technique to observe surface displacement during the construction of urban underground roads. As a result, it was confirmed that continuous surface displacement was occurring at some locations. In the future, comparing and analyzing on-site measurement data with the points of interest would aid in confirming whether displacement occurs due to tunnel excavation and assist in estimating the extent of excavation impact zones.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Food Hygiene and Safety
• /
• v.25 no.4
• /
• pp.388-394
• /
• 2010

Metabolomics aims at the comprehensive, qualitative and quantitative analysis of wide arrays of endogenous metabolites in biological samples. It has shown particular promise in the area of toxicology and drug development, functional genomics, system biology and clinical diagnosis. In this study, analytical technique of MS instrument with high resolution mass measurement, such as time-of-flight (TOF) was validated for the purpose of investigation of amino acids, sugars and fatty acids. Rat urine and serum samples were extracted by selected each solvent (50% acetonitrile, 100% acetonitrile, acetone, methanol, water, ether) extraction method. We determined the optimized liquid chromatography/time-of-flight mass spectrometry (LC/TOFMS) system and selected appropriated columns, mobile phases, fragment energy and collision energy, which could search 17 metabolites. The spectral data collected from LC/TOFMS were tested by ANOVA. Obtained with the use of LC/TOFMS technique, our results indicated that (1) MS and MS/MS parameters were optimized and most abundant product ion of each metabolite were selected to be monitorized; (2) with design of experiment analysis, methanol yielded the optimal extraction efficiency. Therefore, the results of this study are expected to be useful in the endogenous metabolite fields according to validated SOP for endogenous amino acids, sugars and fatty acids.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.41 no.1
• /
• pp.21-33
• /
• 2013

The purpose of this study is to find applicabilities of human bioclimatic maps, using human thermal sensation(comfort) in summer, with microclimatic in situ data and computer simulation results at the study site of downtown Daegu. This includes the central business district(CBD) area and two urban parks, the Debt Redemption Movement Memorial Park and the 2.28 Park, for urban and landscape planning and design. Climatic data and urban setting information for the analysis of human thermal sensation were obtained from in situ measurement and the geographic information system data. As a result, the CBD had higher air temperature than the parks when the wind speed was low. Relative humidities were opposite to the air temperature. Especially, same directional streets with local wind direction had lower air temperature than streets perpendicular to the wind direction. The most important climatic variable of human thermal sensation in summer was direct beam solar radiation. Also, creating shadow areas would be the most relevant method for modifying hot thermal environments in urban areas. The most effective method of creating shadow patterns was making a tree shadow over a pergola, and the second best one was making a tree shadow on the front of north directional building walls. Moreover, how to plant trees for creating shadow patterns was important as well as what kind of trees should be planted. The results of human thermal sensation were warm to very hot at sunny areas and neutral to warm at shaded ones. At the sunny areas, wide, squared shape areas had a little bit higher thermal sensation than those of narrow streets. The albedo change of building walls 0.15 and ground surface 0.1 could change 1/6 of a sensation level at the shaded areas and 1/3 at the sunny ones. These microclimatic approaches will be useful to find appropriate methods for modifying thermal environments in urban areas.