• International Commerce and Information Review
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• v.10 no.1
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• pp.279-293
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• 2008

The number of participants in an online dispute resolution(ODR) system is crucial to its survival. Securing participation is nonetheless difficult. Clearly, it is important to offer a system that is fair, transparent and offers an efficient service at low cost. These factors are fundamental to ensure trust and to build a returning customer base to the system, but are not what attracts a party to submit a dispute for settlement. This paper describes and discusses four main categories of legal measures found in the online dispute resolution services offered by SquareTrade and WIPO. In spite of shortcomings in the offered, the legal measures have contributed to attract large numbers of participants. Large participation secures the long-term economic viability of an online dispute resolution system. The four categories of legal measures described and discussed in this paper need to be part of the specifications and the design and development of future ODR system.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.14-16
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• 2004

Although there have been wide range of studies to characterize forest stands based upon spectral information of satellite image, it was not fully understood the texture information of forest stand using high resolution data. The objective of this study is to evaluate several texture measures for characterizing forest stand structure, such as species composition, diameter at breast height(DBH), stand density, and age. High resolution IKONOS satellite imagery data were acquired in August 200 lover the forested area near Ulsan, Korea. Primary forest types were plantation pine, mixed forest, and natural deciduous forest of stand age ranging from 10 to 50 years old. Several GLCM-based texture measures were compared with forest stand characteristics. In overall, a texture measure (contrast) calculated using red band were better to differentiate species and age group than other texture measures and near infrared bands.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.294-302
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• 2008

In this paper, we present a new image up-sampling method which registers low resolution images to the high resolution grid when Bayesian super-resolution image processing is performed. The proposed up-sampling method interpolates high-resolution pixels using high-frequency data lying in all the low resolution images, instead of up-sampling each low resolution image separately. The interpolation is based on B-spline non-uniform re-sampling, adjusted for the super-resolution image processing. The experimental results demonstrate the effects when different up-sampling methods generally used such as zero-padding or bilinear interpolation are applied to the super-resolution image reconstruction. Then, we show that the proposed hybird up-sampling method generates high-resolution images more accurately than conventional methods with quantitative and qualitative assess measures.

• Earthquakes and Structures
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• v.7 no.5
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• pp.609-626
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• 2014

The capabilities of a high-resolution Digital Image Correlation (DIC) system are presented within the context of deformation measurements of full-scale concrete columns tested under reversed cyclic loading. The system was developed to have very high-resolution such that material strains on the order of the cracking stain of concrete could be measured on the surface of full-scale structural members. The high-resolution DIC system allows the measurement of a wide range of deformations and strains that could only be inferred or assumed previously. The DIC system is able to resolve the full profiles of member curvatures, rotations, plasticity spread, shear deformations, and bar-slip induced rotations. The system allows for automatic and objective measurement of crack widths and other damage indices that are indicative of cumulated damage and required repair time and cost. DIC damage measures contrast prevailing proxy damage indices based on member force-deformation data and subjective damage measures obtained using visual inspection. Data derived from high-resolution DIC systems is shown to be of great use in advancing the state of behavioral knowledge, calibrating behavioral and analytical models, and improving simulation accuracy.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1467-1472
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• 2018

For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high- and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.52.1-52.1
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• 2019

The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

• Journal of Arbitration Studies
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• v.30 no.3
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• pp.95-113
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• 2020

The worldwide diffusion of COVID-19 contributes to electronic commerce all over the world. The proliferation of high volume and small value electronic commerce naturally has combined artificial intelligence with online dispute resolution (ODR). This paper investigates the age effect on Artificial Intelligence acceptability in online dispute resolution and its empirical findings are as follows. First, seven measures out of the nine employed in this case study shows a coherent dynamic pattern over the age spectrum. In other words, the total samples are a heterogenous group rather than a homogeneous one. Second, medium answer occupies a non-negligible portion across answers from nine research questions. It seems to indicate that a considerable portion of Korean respondents are hesitant to make a choice on artificial intelligence at this juncture. Third, all of the respondents agree that the introduction of AI to the dispute resolution could contribute to the hastening of the dispute resolution process. Fourth, most of the respondents agree that artificial intelligence might have the cognitive ability but not the sympathetic or affective ability to handle the electronic commerce disputes.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.18-21
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• 2008

Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.402.1-402.1
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• 2014

Photonic force microscopy (PFM) is an optical tweezers-based scanning probe microscopy, which measures the forces in the range of fN to pN. The low stiffness leads proper to measure single molecular interaction. We introduce a novel photonic force microscopy to stably map various chemical properties as well as topographic information, utilizing weak molecular bond between probe and object's surface. First, we installed stable optical tweezers instrument, where an IR laser with 1064 nm wavelength was used as trapping source to reduce damage to biological sample. To manipulate trapped material, electric driven two-axis mirrors were used for x, y directional probe scanning and a piezo stage for z directional probe scanning. For resolution test, probe scans with vertical direction repeatedly at the same lateral position, where the vertical resolution is ~25 nm. To obtain the topography of surface which is etched glass, trapped bead scans 3-dimensionally and measures the contact position in each cycle. To acquire the chemical mapping, we design the DNA oligonucleotide pairs combining as a zipping structure, where one is attached at the surface of bead and other is arranged on surface. We measured the rupture force of molecular bonding to investigate chemical properties on the surface with various loading rate. We expect this system can realize a high-resolution multi-functional imaging technique able to acquire topographic map of objects and to distinguish difference of chemical properties between these objects simultaneously.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.