• Title/Summary/Keyword: Model efficiency

Search Result 9,250, Processing Time 0.045 seconds

Development of Deep Learning Structure for Defective Pixel Detection of Next-Generation Smart LED Display Board using Imaging Device (영상장치를 이용한 차세대 스마트 LED 전광판의 불량픽셀 검출을 위한 딥러닝 구조 개발)

  • Sun-Gu Lee;Tae-Yoon Lee;Seung-Ho Lee
    • Journal of IKEEE
    • /
    • v.27 no.3
    • /
    • pp.345-349
    • /
    • 2023
  • In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

High-resolution Urban Flood Modeling using Cellular Automata-based WCA2D in the Oncheon-cheon Catchment in Busan, South Korea (셀룰러 오토마타 기반 WCA2D 모형을 이용한 부산 온천천 유역 고해상도 도시 침수 해석)

  • Choi, Hyeonjin;Lee, Songhee;Woo, Hyuna;Noh, Seong Jin
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.43 no.5
    • /
    • pp.587-599
    • /
    • 2023
  • As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.

Comparison of CNN and GAN-based Deep Learning Models for Ground Roll Suppression (그라운드-롤 제거를 위한 CNN과 GAN 기반 딥러닝 모델 비교 분석)

  • Sangin Cho;Sukjoon Pyun
    • Geophysics and Geophysical Exploration
    • /
    • v.26 no.2
    • /
    • pp.37-51
    • /
    • 2023
  • The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

The Effects of Coupled Open Innovation of Small- and Medium-sized Enterprises on Firm Performance: Focusing on R&D and Non-R&D Innovation Cooperation Activities (중소기업의 결합형 개방형 혁신이 기업성과에 미치는 효과: R&D 및 R&D 이외의 혁신협력활동을 중심으로)

  • Ji-Hoon Park;Jungwoo Lee
    • Knowledge Management Research
    • /
    • v.23 no.4
    • /
    • pp.177-205
    • /
    • 2022
  • Small- and medium-sized enterprises (SMEs) have strong incentives to engage in open innovation to enhance innovation efficiency and effectiveness due to their 'liability of smallness.' Previous research examined the performance effects of various open innovation practices, but whether coupled open innovation practices positively affect SMEs' firm performance is somewhat controversial. To resolve the issue, this study examined the effects of coupled open innovation activities on SMEs' firm performance using Heckman's two stage model to control endogeneity of the firms' self-selection bias in open innovation engagement. This study used the Korean Innovation Survey (KIS) 2020 collected by the Science and Technology Policy Institute (STEPI), and tested the effects of SMEs' coupled open innovation activities, R&D and non-R&D cooperation, on their innovative and financial performance indicators. The results showed that SMEs' R&D cooperation positively affects the new-to-market (NTM) product innovation only. Moreover, SMEs' non-R&D cooperation has positive effects on the product innovation, business process innovation, new-to-the-market product innovation, and new-to-firm (NTF) product innovation. However, the results showed that both R&D and non-R&D innovation cooperation activities have no significant effects on SMEs' financial performance indicators. This study contributes to research on SMEs' open innovation and provides insights for SMEs' managers and policymakers.

The Design and implementation of parallel processing system using the $Nios^{(R)}$ II embedded processor ($Nios^{(R)}$ II 임베디드 프로세서를 사용한 병렬처리 시스템의 설계 및 구현)

  • Lee, Si-Hyun
    • Journal of the Korea Society of Computer and Information
    • /
    • v.14 no.11
    • /
    • pp.97-103
    • /
    • 2009
  • In this thesis, we discuss the implementation of parallel processing system which is able to get a high degree of efficiency(size, cost, performance and flexibility) by using $Nios^{(R)}$ II(32bit RISC(Reduced Instruction Set Computer) processor) embedded processor in DE2-$70^{(R)}$ reference board. The designed Parallel processing system is master-slave, shared memory and MIMD(Mu1tiple Instruction-Multiple Data stream) architecture with 4-processor. For performance test of system, N-point FFT is used. The result is represented speed-up as follow; in the case of using 2-processor(core), speed-up is shown as average 1.8 times as 1-processor's. When 4-processor, the speed-up is shown as average 2.4 times as it's.

A Study on the Peer Review Activity of Domestic Researchers in International Journals: Focused on Publons (국내 연구자의 국제 학술지 동료 심사 활동에 관한 연구 - Publons를 중심으로 -)

  • Cho, Jane
    • Journal of the Korean BIBLIA Society for library and Information Science
    • /
    • v.33 no.1
    • /
    • pp.5-24
    • /
    • 2022
  • As a new academic publication model is attempted to improve the transparency, efficiency, and speed of scientific knowledge production and distribution, the open peer review platform for verification and openness of peer review history is also activated. Publons is a global platform for tracking, validating, disclosing, and recognizing the peer-reviewed histories of more than 3 million researchers worldwide. This study analyzed the review activities of 579 researchers from domestic universities who are actively reviewing international journals through Publons. As a result of the analysis, first, researchers from domestic universities who actively review international academic journals were found to be in the fields of medicine and electrical and electronics, and in most fields, assistant professors or higher with high WOS indexed research papers are participating. Second, there was a long-tail phenomenon in which a small number of reviewers with extremely high number of review papers existed in all academic fields, and there was no significant difference in the number of review papers and review report length depending on the nationality, academic status, and age of the reviewers. Lastly, although there was a weak correlation between the amount of papers reviewed by reviewers and the number of published papers, it was found that researchers with an extremely large number of reviews do not necessarily produce as many research papers.

Fabrication of complete denture using digital technology in patient with mandibular deviation: a case report (하악 편위 환자에서 디지털 방식을 이용한 총의치 제작 증례)

  • Lee, Eunsu;Park, Juyoung;Park, Chan;Yun, Kwi-Dug;Lim, Hyun-Pil;Park, Sangwon
    • Journal of Dental Rehabilitation and Applied Science
    • /
    • v.38 no.1
    • /
    • pp.34-41
    • /
    • 2022
  • Recently, digital technology and computer-aided design/computer-aided manufacturing (CAD/CAM) environment have changed the clinician treatment method in the fabrication of dentures. The denture manufacturing method with CAD/CAM technology simplifies the treatment and laboratory process to reduce the occurrence of errors and provides clinical efficiency and convenience. In this case, complete dentures were fabricated using stereolithography (SLA)-based 3D printing in patient with mandibular deviation. Recording base were produced in a digital model obtained with an intraoral scanner, and after recording a jaw relation in the occlusal rim, a definitive impression was obtained with polyvinyl siloxane impression material. In addition, facial scan data with occlusal rim was obtained so that it can be used as a reference in determination of the occlusal plane and in arrangement of artificial teeth during laboratory work. Artificial teeth were arranged through a CAD program, and a gingival festooning was performed. The definitive dentures were printed by SLA-based 3D printer using a Food and Drug Administration (FDA)-approved liquid photocurable resin. The denture showed adequate retention, support and stability, and results were satisfied functionally and aesthetically.

An Importance-Performance Analysis of Location Selection Factors for International Distribution Center in Port Hinterland (IPA기법을 통한 항만배후단지 내 국제물류센터 입주결정요인 분석)

  • Kim, Si-Hyun
    • Korea Trade Review
    • /
    • v.42 no.1
    • /
    • pp.283-301
    • /
    • 2017
  • As a consequence of the changed role and functions in port operations, the role of port hinterland has transformed to multi-functional logistic centre linking more efficiently elements of the supply chain. This paper analysed distribution centre selection factors in Busan new port hinterland, aiming to diagnose and evaluate the operational situations of port hinterland as multi-functional logistics centre. Based on a data collected from all 122 samples located in Busan new port hinterland, determinants for location competitiveness identified were: political support, market potentiality, infrastructure utilization, market niche, and connectivity. Comparing the difference between an importance and performance, it is revealed that the target port hinterland requires urgent improvement in political supports such as incentive programmes offered by host country, free trade system and related law, financial assistance in constructing distribution centers, and simplicity, ease and efficiency of administrative procedures. The results provide useful insights for establishing future improvement strategies and a strategic agenda to successfully respond to the demands of the companies located in port hinterlands and/or new customers those who want to move in.

  • PDF

A Study of Activation Approaches by the on the Analysis Problems and Success Cases of Traditional Markets (재래시장의 문제점과 사례 분석을 통한 활성화 방안)

  • Lee, Jae-Han;Kim, Kyu-Won;Yu, Jong-Pil
    • The Korean Journal of Franchise Management
    • /
    • v.1 no.1
    • /
    • pp.19-42
    • /
    • 2010
  • Since circulation market whole surface opening, traditional market is real condition that is looked away more gradually to consumer as reasons of international retail firms and domestic enterprise firms to enter distribution industry, internet mail order rapid increase by information-oriented society, the pursuit of upgradation and normalization by elevation of income level and consumption pattern change that consideration convenience with young consumers as the central figure. Therefore, the purpose of this study is to analyze stagnation cause of traditional market and problem within a change of new distribution environment, and to develop new approaches for dealing with domestic traditional market relationship prompting competition through activation example analysis of foreign traditional market and domestic traditional market. The result of the study indicated that there are a lot of cases that are begun by a few's merchant with leadership that has been will which is strong in activation in beginning in market's occasion that succeed in activation. In particular, software side such as operational efficiency or marketing expertise strengthening of management is that effect is high relatively than hardware side market activation. Also essential to the settlement of credit transactions using credit cards is important for expanding the effort, for the expansion of credit card merchant credit card advantage and raise awareness among traders about the expected effects is needed. Though these study finding submits plan that create market ecosystem so that many consumers may become place that could visit naturally and create pleasure and convenience, and time, monetary, psychological value of shopping to traditional market, there is sense.

Data-Driven Technology Portfolio Analysis for Commercialization of Public R&D Outcomes: Case Study of Big Data and Artificial Intelligence Fields (공공연구성과 실용화를 위한 데이터 기반의 기술 포트폴리오 분석: 빅데이터 및 인공지능 분야를 중심으로)

  • Eunji Jeon;Chae Won Lee;Jea-Tek Ryu
    • The Journal of Bigdata
    • /
    • v.6 no.2
    • /
    • pp.71-84
    • /
    • 2021
  • Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.