• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.42-48
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• 2015

Generally, the current commercial cloud system is hosted by the centralization large datacenter. However, the other clouding forms existed and one of them is the P2P cloud. The P2P Cloud is a distributed systems, is freedom to join and leave and is possible to provide the IaaS. Commonly, P2P Cloud System is based on Pure-P2P System. Since a number of connection paths exist, it has a high reliability and easily scalability of the network. However, there are disadvantages of the slow rate of route because of looking up the all peers in order to search for the peer. In this paper, it proposes the P2P cloud system based on super-peer P2P. Super-peer P2P system has fast routing time, because of searching for cluster unit and it also can has high reliability and high scalability. We designs the super Peer cloud service and proposes the system model and Resource Allocation Algorithm for IaaS in Super peer P2P environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.4
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• pp.310-317
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• 2013

In this paper an ESPRIT-based super-resolution time delay estimation algorithm is developed for real-time locating system (RTLS) and its performance is analyzed in various multipath environments. The performance of the existing correlation method for time delay estimation seriously degrades in multipath environments where the relative time delays of multipath signals are less than a PN chip. To solve the problem we shall develop a frequency domain super-resolution time delay estimation algorithm using the ESPRIT, the most representative super-resolution direction-of-arrival (DOA) estimation algorithm, and analyze its performance in various multipath environments.

• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.481-490
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• 2006

In a super-peer based P2P network, The network is clustered and each cluster is managed by a special peer, called a super-peer which has information of all peers in its cluster. This clustered P2P model is known to have efficient information search and less traffic load. In this paper, we first estimate the message traffic cost caused by peer's query, join and update actions within a cluster as well as between the clusters and with these values, we present the optimal number of super-peers that minimizes the traffic cost for the various size of super-peer based P2P networks.rks.

• Nuclear Engineering and Technology
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• v.42 no.1
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• pp.47-54
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• 2010

The SuperCritical Water-cooled Reactor (SCWR) pursues high power density to reduce its capital cost. The fast spectrum SCWR, called a super fast reactor, can be designed with a higher power density than thermal spectrum SCWR. The mechanism of increasing the average power density of the super fast reactor is studied theoretically and numerically. Some key parameters affecting the average power density, including fuel pin outer diameter, fuel pitch, power peaking factor, and the fraction of seed assemblies, are analyzed and optimized to achieve a more compact core. Based on those sensitivity analyses, a compact super fast reactor is successfully designed with an average power density of 294.8 W/$cm^3$. The core characteristics are analyzed by using three-dimensional neutronics/thermal-hydraulics coupling method. Numerical results show that all of the design criteria and goals are satisfied.

• Journal of IKEEE
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• v.23 no.3
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• pp.756-761
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• 2019

In this paper, we propose SC-SJ(Shielding Connected-Super Junction) UMOSFET structure in which p-pillars of conventional 4H-SiC Super Junction UMOSFET structures are placed under the shielding region of UMOSFET. In the case of the proposed SC-SJ UMOSFET, the p-pillar and the shielding region are coexisted so that no breakdown by the electric field occurs in the oxide film, which enables the doping concentration of the pillar to be increased. As a result, the on-resistance is lowered to improve the static characteristics of the device. Through the Sentaurus TCAD simulation, the static characteristics of proposed structure and conventional structure were compared and analyzed. The SC-SJ UMOSFET achieves a 50% reduction in on-resistance compared to the conventional structure without any change in the breakdown voltage.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.95-101
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• 2019

Recently, there have been many issues related to text recognition using Tesseract. One of these issues is that the text recognition accuracy is significantly lower for smaller fonts. Tesseract extracts text by creating an outline with direction in the image. By searching the Tesseract database, template matching with characters with similar feature points is used to select the character with the lowest error. Because of the poor text extraction, the recognition accuracy is lowerd. In this paper, we compared text recognition accuracy after applying various super-resolution methods to smaller text images and experimented with how the recognition accuracy varies for various image size. In order to recognize small Korean text images, we have used super-resolution algorithms based on deep learning models such as SRCNN, ESRCNN, DSRCNN, and DCSCN. The dataset for training and testing consisted of Korean-based scanned images. The images was resized from 0.5 times to 0.8 times with 12pt font size. The experiment was performed on x0.5 resized images, and the experimental result showed that DCSCN super-resolution is the most efficient method to reduce precision error rate by 7.8%, and reduce the recall error rate by 8.4%. The experimental results have demonstrated that the accuracy of text recognition for smaller Korean fonts can be improved by adding super-resolution methods to the OCR preprocessing module.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2204-2212
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• 2022

Recently, the demand for alpha imaging detectors for quantifying the distributions of alpha particles has increased in various fields. This study aims to reconstruct a high-resolution image from an alpha imaging detector by applying a super-spatial resolution method combined with the maximum-likelihood expectation maximization (MLEM) algorithm. To perform the super-spatial resolution method, several images are acquired while slightly moving the detector to predefined positions. Then, a forward model for imaging is established by the system matrix containing the mechanical shifts, subsampling, and measured point-spread function of the imaging system. Using the measured images and system matrix, the MLEM algorithm is implemented, which converges towards a high-resolution image. We evaluated the performance of the proposed method through the Monte Carlo simulations and phantom experiments. The results showed that the super-spatial resolution method was successfully applied to the alpha imaging detector. The spatial resolution of the resultant image was improved by approximately 12% using four images. Overall, the study's outcomes demonstrate the feasibility of the super-spatial resolution method for the alpha imaging detector. Possible applications of the proposed method include high-resolution imaging for alpha particles of in vitro sliced tissue and pre-clinical biologic assessments for targeted alpha therapy.

• 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.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.609-615
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• 2022

This study aims to investigate the relationship between quality of life, activities of daily living, and depression among Korean super-aged women. In this study, the 7th (2018) data of the Korean Longitudinal Study of Aging (KLoSA) were used. The participants in this study were 363 super-aged women. The mean age was 88.67 years old. Quality of life was significantly related with Activities of daily living (ADL) (r = .34, p < .001), and depression (r = -.47, p < .001). The analysis of the hypothesized model showed a good fit to the data except for the χ² value (χ² = 38.8, df = 11, p < .001, CFI = .98, TLI = .96, RMSEA = 0.08). The hypothesized model explained 34% of the variance in super-aged women. The activities of daily living of elderly women had an indirect effect on quality of life via depression. Very old women with a high level of ADL were more likely to be feeling less depression, and elderly people who had less depression were likely to have a better quality of life. The findings thus highlight prevailing depression and activities of daily living as critical foci for clinical management strategies in super-aged women.

• Journal of Distribution Science
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• v.13 no.2
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• pp.85-94
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• 2015

Purpose - This study attempts to examine the impacts of consumers' perceived service convenience of retailers on various service performance metrics such as service quality and customer satisfaction. It also tries to investigate differences in the importance of service convenience dimensions on service performance between a department store and a general super market. Research design, data, and methodology - The four hypotheses in this study were proposed and tested. Two hypotheses were on the causal relationships between service convenience dimensions and service performances (service quality and customer satisfaction). The other two hypotheses were on comparisons for the effects of convenience dimensions on service quality and customer satisfaction between department stores and general super markets. To test the hypotheses, three department store chains (Hyundai, Lotte, and Shinsegae department Store) and three general super markets (E-mart, Homeplus, and Lotte mart) were involved. Overall, 510 usable responses were used. The data were analyzed using regression analysis. Results - The results largely support the hypothesized relationships of the proposed model. The results show that access convenience, transaction convenience, benefit convenience, and post-benefit convenience have positive influences on service quality, whereas decision convenience, access convenience, transaction convenience, benefit convenience, and post-benefit convenience have positive effects on customer satisfaction. Furthermore, the results show that there are differences between department stores and general super markets in the effects of benefit convenience and post-benefit convenience on service quality as well as the effects of transaction convenience and post-benefit convenience on customer satisfaction. Conclusions - The concept of service convenience is important in retail environments but little is known about this topic in retail literature. Specially, while service convenience dimensions have different impacts on service performance in distinct retail environments, there has been little investigation or comparison between retail types as regards service convenience. This study is the first to test the differences between distinct retail types (department stores and general super markets) on the service convenience-service performance links. Managerially, the findings of this study suggest that the service convenience management of retailers is an important part of successful service performance management. Because it is most important that both department stores and general super markets enhance benefit convenience to improve service performance, managers of both store types need to invest their resources to reduce consumers' perceived time and effort expenditures to experience the retailer's core benefits. Therefore, the results of this study suggest that retail stores should spend human and financial resources to enhance customer perceptions of service convenience, while also considering what constitutes the service outcome in the consumer's mind. Furthermore, the findings suggest that managers need to use different service convenience management tactics in department stores and general super markets. Specifically, managers in general super markets should pay more attention to benefit convenience and transaction convenience to achieve better service performance whereas managers in department stores should concentrate on post-benefit convenience to create customers' positive evaluation.