• 대한수학회지
• /
• 제35권3호
• /
• pp.765-782
• /
• 1998

The purpose of this paper is to give convergence theorems both for closed convex set valued and relative fuzzy valued martingales, and sub- and super- martingales. These kinds of martingales, sub- and super-martingales are the extension of classical real valued martingales, sub- and super-martingales. Here we compare two kinds of convergences, in the Hausdorff metric and in the Kuratowski-Mosco sense. We also introduce a new convergence for the fuzzy valued case in the graph sense and obtain convergence theorems.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2023년도 춘계학술발표대회
• /
• pp.513-514
• /
• 2023

초해상은 저해상도의 영상을 고해상도 영상으로 합성하는 기술이다. 이 기술에 딥러닝이 적용되어, 2014년에는 SRCNN(Super Resolution Convolutional Neural Network) 모델이 발표됐다. 이후에는 SRCAE(Super Resolution Convolutional Autoencoders)와 GAN(Generative Adversarial Networks)을 기반으로 한 SRGAN(Super Resolution Generative Adversarial Networks) 등, SRCNN의 성능을 능가하는 모델들이 발표됐다. ESRGAN(Enhanced Super Resolution Generative Adversarial Networks)은 SRGAN 모델의 성능을 개선했지만, 완벽한 성능을 내지 못하는 문제점이 있다. 이에 본 논문에서는 판별자(Discriminator) 구조를 변경하여 ESRGAN의 성능을 개선한다. 실험 결과, 제안하는 모델이 ESRGAN보다 더 높은 성능을 보일 것으로 기대된다.

• 한국산업융합학회 논문집
• /
• 제27권4_2호
• /
• pp.909-923
• /
• 2024

This study aims to classify the types of financial super apps and analyzes their evolution and growth paths by type. Super apps, which provide various services on a single platform, are gaining attention as a key strategy for digital transformation in the financial sector. By adopting the grounded theory methodology, this research has categorized financial super apps into three types: "lifestyle financial super app", "integrated financial super app", and "universal financial super app". Ansoff Matrix was used as a theoretical framework to understand how each type of super app grew and evolved through various strategies. Our analysis revealed that super apps of each type grew using a different mix of 'market penetration', 'product development', 'mark et development', and 'diversification' strategies, with each mix showcasing a distinct evolutionary path. The findings of this study are expected to enhance understanding of financial super app typology and evolutionary trajectories, contributing to the development of practical strategies, such as channel optimization for financial super apps in the future.

• Journal of applied mathematics & informatics
• /
• 제5권2호
• /
• pp.507-516
• /
• 1998

In this study we are concerned with the problem of ap-proximating a locally unique solution of an equation on a Banach space. A semilocal convergence theorem is given for the Super-Halley method in Banach spaces. Earlier results have shown that the order of convergence is four for a certain class of operators [4] [5] [8] These results were not given in affine invariant form and made use of a real quadratic majorizing polynomial. Here we provide our re-sults in affine invariant form showing that the order of convergence is at least four. In cases that it is exactly four the rate of convergence is improved. We achieve these results by using a cubic majorizing polynomial. Some numerical examples are given to show that our error bounds are better than earlier ones.

• Journal of applied mathematics & informatics
• /
• 제24권1_2호
• /
• pp.367-376
• /
• 2007

In this paper we consider the global convergence of a new super memory gradient method for unconstrained optimization problems. New trust region radius is proposed to make the new method converge stably and averagely, and it will be suitable to solve large scale minimization problems. Some global convergence results are obtained under some mild conditions. Numerical results show that this new method is effective and stable in practical computation.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2022년도 추계학술발표대회
• /
• pp.501-503
• /
• 2022

초해상이란 해상도가 낮은 영상을 해상도가 높은 영상으로 합성하는 기술이다. 딥러닝은 영상의 해상도를 높이는 초해상 기술에도 응용되며 실현은 2아4년에 발표된 SRCNN(Super Resolution Convolutional Neural Network) 모델로부터 시작됐다. 이후 오토인코더 (Autoencoders) 구조로는 SRCAE(Super Resolution Convolutional Autoencoders), 합성된 영상을 실제 영상과 통계적으로 구분되지 않도록 강제하는 GAN (Generative Adversarial Networks) 구조로는 SRGAN(Super Resolution Generative Adversarial Networks) 모델이 발표됐다. 모두 SRCNN의 성능을 웃도는 모델들이나 그중 가장 높은 성능을 끌어내는 SRGAN 조차 아직 완벽한 성능을 내진 못한다. 본 논문에서는 SRGAN의 성능을 개선하기 위해 사전 훈련된 특징 추출기(Pre-trained Feature Extractor) VGG(Visual Geometry Group)-19 모델을 변경하고, 기존 모델과 성능을 비교한다. 실험 결과, VGG-19 모델보다 윤곽이 뚜렷하고, 실제 영상과 더 가까운 영상을 합성할 수 있는 모델을 발견할 수 있을 것으로 기대된다.

• 한국산업융합학회 논문집
• /
• 제27권2_2호
• /
• pp.343-356
• /
• 2024

Super app is an application that provides a variety of services in a unified interface within a single platform. With the acceleration of digital transformation, super apps are becoming more prevalent. This study aims to suggest service enhancement measures by analyzing the user review data before and after the transition to a super app. To this end, user review data from a payment-based super app(Shinhan Play) were collected and studied via topic modeling. Moreover, a matrix for assessing the importance and usefulness of topics is introduced, which relies on the eigenvector centrality of the inter-topic network obtained through topic modeling and the number of review recommendations. This allowed us to identify and categorize topics with high utility and impact. Prior to the transition, the factors contributing to user satisfaction included 'payment service,' 'additional service,' and 'improvement.' Following the transition, user satisfaction was associated with 'payment service' and 'integrated UX.' Conversely, dissatisfaction factors before the transition encompassed issues related to 'signup/installation,' 'payment error/response,' 'security authentication,' and 'security error.' Following the transition, user dissatisfaction arose from concerns regarding 'update/error response' and 'UX/UI.' The research results are expected to be used as a basis for establishing strategies to strengthen service competitiveness by making super app services more user-oriented.

• Kyungpook Mathematical Journal
• /
• 제59권3호
• /
• pp.403-414
• /
• 2019

Theta functions are the sections of line bundles on a complex torus. Noncommutative versions of theta functions have appeared as theta vectors and quantum theta operators. In this paper we describe a super version of theta vectors and quantum theta operators. This is the natural unification of Manin's result on bosonic operators, and the author's previous result on fermionic operators.

• 한국융합학회논문지
• /
• 제11권8호
• /
• pp.7-13
• /
• 2020

기상과 기후는 인간의 생활과 밀접하게 연관되어 있다. 특히 고해상도 기상 데이터를 활용하여 정밀한 연구나 실생활에 유용한 서비스가 가능하므로, 고해상도 기상·기후 데이터를 생산해야할 필요성이 증가하고 있다. 기존의 고해상도 기상 데이터는 적절한 보간법에 따라 데이터를 생산하지만, 본 논문에서는 SRCNN을 이용하여 기온 데이터를 초해상화 하는 방안을 제안한다. 기온 데이터 초해상화에 가장 적절한 SRCNN 모델을 구축하고, 기온 데이터를 초해상화 한다. 결과 데이터를 평가하기 위해 역거리 가중법을 이용하여 비 관측 지점에 대한 기온을 구하고, 제안한 방법을 적용한 기온 데이터와 보간법을 이용한 기온 데이터를 비교한다. 비교 결과, 기온 데이터를 초해상화하기 위한 적절한 SRCNN 모델을 구축하였고, 제안한 방법이 보간법을 이용한 방법보다 약 10.8% 더 높은 예측 성능을 보였다.

• International journal of advanced smart convergence
• /
• 제8권3호
• /
• pp.95-101
• /
• 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.