• Title/Summary/Keyword: Improvement Approaches

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Approximate Approaches in Chinese and Chosun Mathematics (중국 및 조선 수학에서의 근사적 접근)

  • Chang, Hye-Won
    • Journal for History of Mathematics
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    • v.24 no.2
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    • pp.1-15
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    • 2011
  • Approximation is a very useful approach in mathematics research. It was the same in traditional Chinese and Chosun mathematics. This study derived five characteristics from approximation approaches which were found in Chinese and Chosun mathematical books: improvement of approximate values, common and inevitable use of approximate values, recognition of approximate values and their reasons, comparison of their exactness, application of approximate principles. Through these characteristics, we can infer what Chinese and Chosun mathematicians recognized approximate values and how they manipulated them. They took approximate approaches by necessity or for the sake of convenience in mathematical study and its applications. Also, they tried to improve the degree of exactness of approximate values and use the inverse calculations to check them.

Character Segmentation using Side Profile Pattern (측면윤곽 패턴을 이용한 접합 문자 분할 연구)

  • Jung Minchul
    • Journal of Intelligence and Information Systems
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    • v.10 no.3
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    • pp.1-10
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    • 2004
  • In this paper, a new character segmentation algorithm of machine printed character recognition is proposed. The new approach of the proposed character segmentation algorithm overcomes the weak points of both feature-based approaches and recognition-based approaches in character segmentation. This paper defines side profiles of touching characters. The character segmentation algorithm gives a candidate single character in touching characters by side profiles, without any help of character recognizer. It segments touching characters and decides the candidate single character by side profiles. This paper also defines cutting cost, which makes the proposed character segmentation find an optimal segmenting path. The performance of the proposed character segmentation algorithm in this paper has been obtained using a real envelope reader system, which can recognize addresses in U.S. mail pieces and sort the mail pieces. 3359 mail pieces were tested. The improvement was from $68.92\%\;to\;80.08\%$ by the proposed character segmentation.

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LDCSIR: Lightweight Deep CNN-based Approach for Single Image Super-Resolution

  • Muhammad, Wazir;Shaikh, Murtaza Hussain;Shah, Jalal;Shah, Syed Ali Raza;Bhutto, Zuhaibuddin;Lehri, Liaquat Ali;Hussain, Ayaz;Masrour, Salman;Ali, Shamshad;Thaheem, Imdadullah
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.463-468
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    • 2021
  • Single image super-resolution (SISR) is an image processing technique, and its main target is to reconstruct the high-quality or high-resolution (HR) image from the low-quality or low-resolution (LR) image. Currently, deep learning-based convolutional neural network (CNN) image super-resolution approaches achieved remarkable improvement over the previous approaches. Furthermore, earlier approaches used hand designed filter to upscale the LR image into HR image. The design architecture of such approaches is easy, but it introduces the extra unwanted pixels in the reconstructed image. To resolve these issues, we propose novel deep learning-based approach known as Lightweight deep CNN-based approach for Single Image Super-Resolution (LDCSIR). In this paper, we propose a new architecture which is inspired by ResNet with Inception blocks, which significantly drop the computational cost of the model and increase the processing time for reconstructing the HR image. Compared with the other state of the art methods, LDCSIR achieves better performance in terms of quantitively (PSNR/SSIM) and qualitatively.

Improvement of hole transport from p-Si with interfacial layers for silicon solar cells

  • Oh, Gyujin;Kim, Eun Kyu
    • Proceedings of the Korean Vacuum Society Conference
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    • 2016.02a
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    • pp.239.2-239.2
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    • 2016
  • Numerous studies and approaches have been performed for solar cells to improve their photoelectric conversion efficiencies. Among them, the study for electrode containing transparent conducting oxide (TCO) layers is one of issues as well as for the cell structure based on band theory. In this study, we focused on an interfacial layer between p-type silicon and indium tin oxide (ITO) well-known as TCO materials. According to current-voltage characteristics for the sample with the interfacial layers, the improvement of band alignment between p-type silicon and ITO was observed, and their ohmic properties were enhanced in the proper condition of deposition. To investigate cause of this improvement, spectroscopic ellipsometry and ultraviolet photoelectron spectroscopy were utilized. Using these techniques, band alignment and defect in the band gap were examined. The major materials of the interfacial layer are vanadium oxide and tungsten oxide, which are notable as a hole transfer layer in the organic solar cells. Finally, the interfacial layer was applied to silicon solar cells to see the actual behavior of carriers in the solar cells. In the case of vanadium oxide, we found 10% of improvement of photoelectric conversion efficiencies, compared to solar cells without interfacial layers.

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A Study on Policy and System Improvement Plan of Geo-Spatial Big Data Services in Korea

  • Park, Joon Min;Yu, Seon Cheol;Ahn, Jong Wook;Shin, Dong Bin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.6
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    • pp.579-589
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    • 2016
  • This research focuses on accomplishing analysis problems and issues by examining the policies and systems related to geo-spatial big data which have recently arisen, and suggests political and systemic improvement plan for service activation. To do this, problems and probable issues concerning geo-spatial big data service activation should be analyzed through the examination of precedent studies, policies and planning, pilot projects, the current legislative situation regarding geo-spatial big data, both domestic and abroad. Therefore, eight political and systematical improvement plan proposals are suggested for geo-spatial big data service activation: legislative-related issues regarding geo-spatial big data, establishing an exclusive organization in charge of geospatial big data, setting up systems for cooperative governance, establishing subsequent systems, preparing non-identifying standards for personal information, providing measures for activating civil information, data standardization on geo-spatial big data analysis, developing analysis techniques for geo-spatial big data, etc. Consistent governmental problem-solving approaches should be required to make these suggestions effectively proceed.

STATUS AND SCOPE OF SMALL RUMINANTS PRODUCTION IN DRY AREAS OF PAKISTAN - REVIEW -

  • Rafiq, M.
    • Asian-Australasian Journal of Animal Sciences
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    • v.8 no.3
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    • pp.205-212
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    • 1995
  • This paper describes small ruminant production systems in dry areas of Pakistan. Formal and informal surveys had identified that poor feed resources, as a result of harsh climatic conditions, is a major factor responsible for low sheep and goats production. In view of their recommendations, use of approaches like supplemental feeding and pasture production through an introduction of improved forage species in the country, are reviewed. The improvement in sheep production and associated socioeconomic benefits, are discussed.

Applying Workflow Management System to CPC (CPC에서의 Workflow 응용)

  • 전희철
    • CDE review
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    • v.8 no.1
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    • pp.58-65
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    • 2002
  • Collaborative product commerce(CPC) involves many people working together with heterogeneous and distributed software applications. For such an environment, Workflow Management System(WFMS) can be useful for coordination of people, software agents and processes. It provides diverse services including automatic work muting, project management continuous process improvement and application integration. However, there are some limitations to apply WFMS to CPC environment due to inflexibility and lack of design support facilities. This paper identifies the problems and addresses possible approaches to overcome the difficulties.

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Multiresponse Optimization in the Presence of the Goal Regions for the Respective Responses: A Method by Minimization of the Sum of Squares of Relative Changes (각 반응의 목표 영역 존재시의 다반응 최적화: 상대변화 제곱합의 최소화에 의한 방법)

  • 홍승만;임성수;이민우
    • Journal of Applied Reliability
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    • v.1 no.2
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    • pp.165-173
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    • 2001
  • The desirability function approach by Derringer and Suich (1980) and the generalized distance approach by Khuri and Conlon (1981) are two major approaches to multiresponse optimization for improvement of quality of a product or process. So far, the desirability function method has been the only tool for multiresponse optimization in the situations where there are the goal regions for the respective responses. For such situations, we propose a multiresponse optimization method based on the generalized distance approach.

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Reconceptualizing Home Economics by Focusing the Concept of 'Family life welfare' (가정복지' 개념을 중심으로 한 가정학의 재개념화)

  • 허정원
    • Journal of Families and Better Life
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    • v.17 no.2
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    • pp.173-184
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    • 1999
  • The purposed of this study was to reconceptualize home economics by focusing the concept of 'Family life welfare' which pursue the improvement of family life through making the home resourceful and developing the community. The reconceptualization of home economics as family life welfare could solve the problem identification and professionalization which home economics lack of. It also would contribute to the extension of an arena and activation of the Discussion no the family life by criticizing several approaches based on functionalism Finally the utilization of home economics major in public affair means the advancement of women's social participation.

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Dense Neural Network Graph-based Point Cloud classification (밀집한 신경망 그래프 기반점운의 분류)

  • El Khazari, Ahmed;lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.498-500
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    • 2019
  • Point cloud is a flexible set of points that can provide a scalable geometric representation which can be applied in different computer graphic task. We propose a method based on EdgeConv and densely connected layers to aggregate the features for better classification. Our proposed approach shows significant performance improvement compared to the state-of-the-art deep neural network-based approaches.