• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2646-2651
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• 2021

A rectangular-shaped PET system with an adjustable gantry (AGPET) has been developed for imaging small animals. The AGPET system employs a new depth of interaction (DOI) method using a depth dependent reflector patterns and a new digital time pickoff method based on the pulse reconstruction method. To evaluate the performance of the AGPET, timing resolution, intrinsic spatial resolution and point source images were acquired. The timing resolution and intrinsic spatial resolution were measured using two detector modules and Na-22 gamma source. The PET images were acquired in two field of view (FOV) sizes, 30 mm and 90 mm, to demonstrate the characteristic of the AGPET. As a result of in the experiment results, the timing resolution was 0.9 ns using the pulse reconstruction method based on the bi-exponential model. The intrinsic spatial resolution was an average of 1.7 mm and the spatial resolution of PET images after DOI correction was 2.08 mm and 2.25 mm at the centers of 30 mm and 90 mm FOV, respectively. The results show that the proposed AGPET system provided higher sensitivity and resolution for small animal imaging.

• Journal of Arbitration Studies
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• v.22 no.2
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• pp.31-52
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• 2012

Although political uncertainty exists between China and Taiwan, the two countries have been expanding their economic exchange since the 1980s. That economic exchange is not limited to trade, and its investment segment is constantly expanding. The investment was one-sided by Taiwan in the past, but since a change in policy by the Taiwan government in 2009, Chinese capital is able to flow into Taiwan for direct investment. These kinds of policy changes related to investment between the two countries require follow-up actions such as profit protection for investors, elimination of investment limitations, simplification of investment procedures, and establishment of an investment dispute resolution system. The main topic of this study is the resolution mechanism for investment disputes between China and Taiwan. At present, an individual investment dispute between two countries is settled according to each country's own regulations for dispute resolution. However, these two countries have not prepared dispute resolution regulations related to cases of investment disputes between Chinese or Taiwanese investors and the Chinese or Taiwanese government, or between the Chinese government and the Taiwanese government. Moreover, they do not have any agreements related to investment disputes. Therefore, in this paper, I enumerate the regulations related to investment dispute resolution between China and Taiwan, and then I point out the problems and suggest solutions for improvement. Also, through this study, I would like to contribute to establishing and implementing an investment dispute resolution mechanism between South Korea and North Korea.

• Journal of Arbitration Studies
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• v.19 no.2
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• pp.73-94
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• 2009

There are significant differences between disputes among enterprises and disputes between consumers and an enterprise. A majority of consumers may suffer from the same damages at the same time with small amount concerned and sometimes low chances for find the real cause. Among these distinctive features, the most significant characteristic in consumer-business disputes can be found in that consumers are in a disadvantageous position compared to businesses. When it comes to consumer policy, the biggest aim lies with turning back the damage a consumer is suffering into normalcy. In this regard, the Consumer Dispute Resolution System is the most essential among consumer policies. In Korea, the Collective Alternative Dispute Resolution (ADR) System was introduced to the Consumer Dispute Resolution System in 2007 in line with revision on the Consumer Basic Law. However, smooth damage redress for consumers is still not taking place. Against this backdrop, this report suggests that 'consumer arbitration' program should be introduced to the Consumer Dispute Resolution System as part of making good and smooth progress for consumer damage redress.

• Journal of Arbitration Studies
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• v.25 no.3
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• pp.155-184
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• 2015

This paper addresses the question of what kinds of dispute resolution choices can effectively handle complex intellectual property disputes, given the rising importance of IP, the increasing frequency and complexity of IP disputes, and the lack of research on dispute resolution strategies. For this analysis, the study adopted the analytic hierarchy process approach, which covers complex, multi-criteria decision problems, to quantify the expert's judgments on IP dispute resolution choice. Its results show that the effectiveness of resolution methods differs, depending on the type of IP dispute classified into seven issues, which are (i) requirement for validity of IP right, (ii) range and duration of IP right, (iii) transfer of IP right, (iv) licensing, (v) use of IP right, (vi) declaration of IP infringement, and (vii) estimation of damage. The disputes over IPR ownership and IP infringement remain challenging issues in due to strong requirement of the cross-border enforcement. Alternative dispute resolution (ADR), especially arbitration, is determined to be a more effective method to deal with international IP disputes, but various advanced types of ADR techniques should be further developed to deal with the increasing complexity of IP disputes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1141-1162
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• 2024

Humidity is an important parameter in meteorology and is closely related to weather, human health, and the environment. Due to the limitations of the number of observation stations and other factors, humidity data are often not as good as expected, so high-resolution humidity fields are of great interest and have been the object of desire in the research field and industry. This study presents a novel super-resolution algorithm for humidity fields based on the Wasserstein generative adversarial network(WGAN) framework, with the objective of enhancing the resolution of low-resolution humidity field information. WGAN is a more stable generative adversarial networks(GANs) with Wasserstein metric, and to make the training more stable and simple, the gradient cropping is replaced with gradient penalty, and the network feature representation is improved by sub-pixel convolution, residual block combined with convolutional block attention module(CBAM) and other techniques. We evaluate the proposed algorithm using ERA5 relative humidity data with an hourly resolution of 0.25°×0.25°. Experimental results demonstrate that our approach outperforms not only conventional interpolation techniques, but also the super-resolution generative adversarial network(SRGAN) algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2730-2747
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• 2016

Due to the limitation of the bandwidth resource and capture resolution of depth cameras, low resolution depth maps should be up-sampled to high resolution so that they can correspond to their texture images. In this paper, a novel depth map up-sampling algorithm is proposed by exploiting the fractal internal self-referential feature. Fractal parameters which are extracted from a depth map, describe the internal self-referential feature of the depth map, do not introduce inherent scale and just retain the relational information of the depth map, i.e., fractal transforms provide a resolution-independent description for depth maps and could up-sample depth maps to an arbitrary high resolution. Then, an enhancement method is also proposed to further improve the performance of the up-sampled depth map. The experimental results demonstrate that better quality of synthesized views is achieved both on objective and subjective performance. Most important of all, arbitrary resolution depth maps can be obtained with the aid of the proposed scheme.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.463-466
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• 2009

The numerical simulation optimized by Four Dimensional Data Assimilation (FDDA) with Quick Scatterometer (QuikSCAT) data is carried out to evaluate wind resource characteristics at various heights in the southeastern area of the Korean Peninsula, where wind farms are planned to be built on on- and off-shore as well as comparable diurnal wind variations are characterized at the surface. The temporal and spatial distributions of modeled wind speeds showed good agreement with the observations based on the temporal variation analysis. Model results indicate that the higher model is performed in resolution, the more precise results is at turbine hub height. Occasionally, wind speed variations for each numerical resolution has a different regional and seasonal variations. In the coast area, hub height wind speed of 9km-resolution is simillar to that of 3km-resolution. On the other hand, hub height wind speed of 3km-resolution is simillar to that of 1km-resolution in the Jiri mountainous area.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.23-29
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• 2014

The emergence of high resolution satellite images and the evolution of spatial resolution facilitate various studies using high resolution satellite images. Above all, target detection algorithms are effective for monitoring of traffic flow and military surveillance and reconnaissance because vehicles, airplanes, and ships on broad area could be detected easily using high resolution satellite images. Recently, many satellites are launched from global countries and the diversity of satellite images are also increased. On the contrary, studies on comparison about the spatial resolution or target detection, especially, are insufficient in domestic and foreign countries. Therefore, in this study, effects of spatial resolution on target detection are analyzed using the PSO target detection algorithm. The resampling techniques such as nearest neighbor, bilinear, and cubic convolution are adopted to resize the original image into 0.5m, 1m, 2m, 4m spatial resolutions. Then, accuracy of target detection is assessed according to not only spatial resolution but also resampling method. As a result of the study, the resolution of 0.5m and nearest neighbor among the resampling methods have the best accuracy. Additionally, it is necessary to satisfy the criteria of 2m and 4m resolution for the detection of airplane and ship, respectively. The detection of airplane need more high spatial resolution than ship because of their complexity of shape. This research suggests the appropriate spatial resolution for the plane and ship target detection and contributes to the criteria of satellite sensor design.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.395-407
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• 2023

Super-resolution (SR) has great significance in image processing because it enables downstream vision tasks with high spatial resolution. Recently, SR studies have adopted deep learning networks and achieved remarkable SR performance compared to conventional example-based methods. Deep-learning-based SR models generally require low-resolution (LR) images and the corresponding high-resolution (HR) images as training dataset. Due to the difficulties in obtaining real-world LR-HR datasets, most SR models have used only HR images and generated LR images with predefined degradation such as bicubic downsampling. However, SR models trained on simple image degradation do not reflect the properties of the images and often result in deteriorated SR qualities when applied to real-world images. In this study, we propose an image degradation model for HR satellite images based on the modulation transfer function (MTF) of an imaging sensor. Because the proposed method determines the image degradation based on the sensor properties, it is more suitable for training SR models on remote sensing images. Experimental results on HR satellite image datasets demonstrated the effectiveness of applying MTF-based filters to construct a more realistic LR-HR training dataset.