• Title/Summary/Keyword: Database Application System

Search Result 1,087, Processing Time 0.029 seconds

The effect of motor learning in children with cerebral palsy: A systemic review (뇌성마비 아동의 운동학습 효과 체계적 고찰)

  • Kim, Jung-Hyun
    • Journal of Korean Physical Therapy Science
    • /
    • v.28 no.1
    • /
    • pp.33-45
    • /
    • 2021
  • Background: Children with cerebral palsy have difficulty acquiring motor skills through motor learning due to lack of motor planning of the central nervous system and musculoskeletal dysfunction. Motor learning is the acquisition or modification of movements with the aim of developing skilled movements and behaviors. Cerebral palsy improve motor function through motor learning, and effective motor learning mainly depends on practice parameters such as learning feedback. Therefore, we investigate the effect of motor learning in children with cerebral palsy and try to present the possibility of clinical application. Design: A systemic review. Methods: Research papers were published from Jan, 2010 to Dec, 2020 and were searched using PubMed and Medline. The search terms are 'task specific training' OR 'motor learning' OR 'feedback(Mesh term)' OR 'goal activity' AND 'cerebral palsy(Mesh term)'. A total of eight papers were analyzed in this study. The paper presented the quality level based on the research evidence, and also presented PEDro (Physiotherapy Evidence Database) scores to evaluate the quality of design studies in randomized clinical trials. Results: The results showed that motor learning coaching in children with cerebral palsy improved motor function in post and follow up tests. Also, self-control feedback of motor learning is more effective than external control feedback. 100% external control feedback of motor learning is effective in the acquisition phase and 50% external feedback of motor learning is effective in the retain phase. Conclusion: These results suggest that it will be an important data for establishing evidence on the effect of motor learning arbitration methods in children with cerebral palsy to develop clinical applicability and protocols.

Channel Attention Module in Convolutional Neural Network and Its Application to SAR Target Recognition Under Limited Angular Diversity Condition (합성곱 신경망의 Channel Attention 모듈 및 제한적인 각도 다양성 조건에서의 SAR 표적영상 식별로의 적용)

  • Park, Ji-Hoon;Seo, Seung-Mo;Yoo, Ji Hee
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.24 no.2
    • /
    • pp.175-186
    • /
    • 2021
  • In the field of automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, it is usually impractical to obtain SAR target images covering a full range of aspect views. When the database consists of SAR target images with limited angular diversity, it can lead to performance degradation of the SAR-ATR system. To address this problem, this paper proposes a deep learning-based method where channel attention modules(CAMs) are inserted to a convolutional neural network(CNN). Motivated by the idea of the squeeze-and-excitation(SE) network, the CAM is considered to help improve recognition performance by selectively emphasizing discriminative features and suppressing ones with less information. After testing various CAM types included in the ResNet18-type base network, the SE CAM and its modified forms are applied to SAR target recognition using MSTAR dataset with different reduction ratios in order to validate recognition performance improvement under the limited angular diversity condition.

Derivation of Surface Temperature from KOMPSAT-3A Mid-wave Infrared Data Using a Radiative Transfer Model

  • Kim, Yongseung
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.4
    • /
    • pp.343-353
    • /
    • 2022
  • An attempt to derive the surface temperature from the Korea Multi-purpose Satellite (KOMPSAT)-3A mid-wave infrared (MWIR) data acquired over the southern California on Nov. 14, 2015 has been made using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. Since after the successful launch on March 25, 2015, the KOMPSAT-3A spacecraft and its two payload instruments - the high-resolution multispectral optical sensor and the scanner infrared imaging system (SIIS) - continue to operate properly. SIIS uses the MWIR spectral band of 3.3-5.2 ㎛ for data acquisition. As input data for the realistic simulation of the KOMPSAT-3A SIIS imaging conditions in the MODTRAN model, we used the National Centers for Environmental Prediction (NCEP) atmospheric profiles, the KOMPSAT-3Asensor response function, the solar and line-of-sight geometry, and the University of Wisconsin emissivity database. The land cover type of the study area includes water,sand, and agricultural (vegetated) land located in the southern California. Results of surface temperature showed the reasonable geographical pattern over water, sand, and agricultural land. It is however worthwhile to note that the surface temperature pattern does not resemble the top-of-atmosphere (TOA) radiance counterpart. This is because MWIR TOA radiances consist of both shortwave (0.2-5 ㎛) and longwave (5-50 ㎛) components and the surface temperature depends solely upon the surface emitted radiance of longwave components. We found in our case that the shortwave surface reflection primarily causes the difference of geographical pattern between surface temperature and TOA radiance. Validation of the surface temperature for this study is practically difficult to perform due to the lack of ground truth data. We therefore made simple comparisons with two datasets over Salton Sea: National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) field data and Salton Sea data. The current estimate differs with these datasets by 2.2 K and 1.4 K, respectively, though it seems not possible to quantify factors causing such differences.

Contact Tracking Development Trend Using Bibliometric Analysis

  • Li, Chaoqun;Chen, Zhigang;Yu, Tongrui;Song, Xinxia
    • Journal of Information Processing Systems
    • /
    • v.18 no.3
    • /
    • pp.359-373
    • /
    • 2022
  • The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

Automation Review of Road Design Standard using Visual Programming (비주얼 프로그래밍 기법을 활용한 도로설계기준 자동검토 방안)

  • Hyoun-seok Moon;Hyeoun-seung Kim
    • Journal of the Society of Disaster Information
    • /
    • v.18 no.4
    • /
    • pp.891-898
    • /
    • 2022
  • Purpose: There is not much time left for mandatory BIM implementation for all sectors and stages of the construction industry. Therefore, it is necessary to find a way to secure technology to substantially improve the productivity of BIM work. In the research, we proposed a method to automatically verify related construction standards for major objects produced by BIM modeling procedures so that engineers can verify construction standards in the BIM-based design process. Method: We defined a modeling work procedure for BIM-based road design work and prepared a method for constructing related design standards in a database. In addition, a process map for developing a BIM-based design basis review automation system was also presented. Result: A BIM-based design standard review automation module was developed using Civil3D and Dynamo. And it was confirmed by the test application that it is possible to quickly judge whether the BIM object manufactured in the design process conforms to the construction design standard. Conclusion: BIM-based design standard review automation technology can improve the productivity of BIM model production work and secure the quality of the BIM model.

Using machine learning to forecast and assess the uncertainty in the response of a typical PWR undergoing a steam generator tube rupture accident

  • Tran Canh Hai Nguyen ;Aya Diab
    • Nuclear Engineering and Technology
    • /
    • v.55 no.9
    • /
    • pp.3423-3440
    • /
    • 2023
  • In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

Design of Food Waste Trading E-Commerce Service with IoT-based Capacity Information Collection (사물인터넷 기반의 용량 정보 수집을 통한 음식물 쓰레기 전자상거래 서비스의 설계)

  • Wahyutama, Aria Bisma;Hwang, Mintae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.05a
    • /
    • pp.112-114
    • /
    • 2022
  • This paper proposes an E-Commerce service that supports large quantities of food waste sales generated by collective residences, including apartments, to consumers in urban areas, such as livestock farmers, through online transactions. Unlike general E-Commerce, the proposed service uses a smart food waste bin equipped with an IoT-based sensor and communication module to automatically collect the location information of each apartment and the amount of food waste to be displayed in a specialized E-Commerce platform. The key of this system is to provide information and sell it to consumers. The smart food waste bin periodically delivers its current capacity and location using a weight sensor, GPS sensor and LoRa communication module to a cloud-based database to be used in web or mobile applications. The proposed E-Commerce service is expected to help resolve the food waste disposal problem and revitalize the local economy by linking with a service that delivers food waste from each apartment to a nearby location where the buyer is located.

  • PDF

An Introduction of Korean Soil Information System (한국 토양정보시스템 소개)

  • Hong, S. Young;Zhang, Yong-Seon;Hyun, Byung-Keun;Sonn, Yeon-Kyu;Kim, Yi-Hyun;Jung, Sug-Jae;Park, Chan-Won;Song, Kwan-Cheol;Jang, Byoung-Choon;Choe, Eun-Young;Lee, Ye-Jin;Ha, Sang-Keun;Kim, Myung-Suk;Lee, Jong-Sik;Jung, Goo-Bok;Ko, Byong-Gu;Kim, Gun-Yeob
    • Korean Journal of Soil Science and Fertilizer
    • /
    • v.42 no.1
    • /
    • pp.21-28
    • /
    • 2009
  • Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.

Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant (원자력발전소 PSI/ISI 데이터 관리를 위한 지능형 데이터 베이스 프로그램 개발)

  • Park, Un-Su;Park, Ik-Keun;Um, Byong-Guk;Park, Yun-Won;Kang, Suk-Chul
    • Journal of the Korean Society for Nondestructive Testing
    • /
    • v.18 no.5
    • /
    • pp.389-397
    • /
    • 1998
  • For an effective and efficient management of large amounts of preservice/inservice inspection(PSI/ISI) data in nuclear power plants, an intellegent Windows 95-based data management program was developed. This program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. The program extracts, and the associated remedies. Furthermore, additional inspection data and comments can be easily added or deleted for subsequent PSI/ISI operation. Although the initial version of the program was applied to Kori nuclear power plant, this program can be equally applied to other nuclear power plant. And also this program can be used to offer the fundamental data for application of evaluation data related to fracture mechanics analysis(FMA), probabilistic reliability assessment(PRA) of PSI/ISI results, performance demonstration initiative(PDI) and risk-informed ISI based on probability of detection(POD) information of ultrasonic examination. Besides, the program can be further developed as a unique PSI/ISI data management expert system that can be apart of PSI/ISI data management expert system that can be a part of PSI/ISI Total Support System(TSS) for Korean nuclear power plants.

  • PDF

Design of EPG Information Player System using DCT based Blind Watermark (DCT기반의 블라인드 워터마크를 이용한 EPG 정보 재생기 설계)

  • Kim, Dae-Jin;Choi, Hong-Sub
    • The Journal of the Korea Contents Association
    • /
    • v.11 no.4
    • /
    • pp.1-10
    • /
    • 2011
  • While the broadband network and multimedia technologies have been developing, the commercial market of digital contents has also been widely spreading with recently starting IPTV. Generally, PC player can display digital contents obtained through middleware like a settop box and can only bring the informations about contents like CODEC, bitrate etc. useful for only experts. But general users want to know more optional informations like content's subject, description etc. So unlike previous PC player, we proposed a player system that can get inserted informations, namely EPG(Electronic Program Guide), without database after bringing contents to PC through settop box. In addition, we also proposed DCT(Discrete Cosine Transform) based blind watermark generating method to insert EPG informations. We can extract watermark without original image and insert robust watermark in proportion to coefficients in frequency domain. And we analyzed and parsed PSI data from MPEG-TS. So we could insert wanted information using watermark from EPG. And we composed UI by extracting EPG information from watermark interted contents. Finally we modularized whole system into the watermark insert/extract application and directshow filter based player. So we tried to design this system so that the general developer can do in a way that is easier and faster.