• Title/Summary/Keyword: Generate Data

Search Result 3,066, Processing Time 0.031 seconds

Analysis of Defective Causes in Real Time and Prediction of Facility Replacement Cycle based on Big Data (빅데이터 기반 실시간 불량품 발생 원인 분석 및 설비 교체주기 예측)

  • Hwang, Seung-Yeon;Kwak, Kyung-Min;Shin, Dong-Jin;Kwak, Kwang-Jin;Rho, Young-J;Park, Kyung-won;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.19 no.6
    • /
    • pp.203-212
    • /
    • 2019
  • Along with the recent fourth industrial revolution, the world's manufacturing powerhouses are pushing for national strategies to revive the sluggish manufacturing industry. Moon Jae-in, the government is in accordance with the trend, called 'advancement of science and technology is leading the fourth round of the Industrial Revolution' strategy. Intelligent information technology such as IoT, Cloud, Big Data, Mobile, and AI, which are key technologies that lead the fourth industrial revolution, is promoting the emergence of new industries such as robots and 3D printing and the smarting of existing major manufacturing industries. Advances in technologies such as smart factories have enabled IoT-based sensing technology to measure various data that could not be collected before, and data generated by each process has also exploded. Thus, this paper uses data generators to generate virtual data that can occur in smart factories, and uses them to analyze the cause of the defect in real time and to predict the replacement cycle of the facility.

A Study on the Integration of Airborne LiDAR and UAV Data for High-resolution Topographic Information Construction of Tidal Flat (갯벌지역 고해상도 지형정보 구축을 위한 항공 라이다와 UAV 데이터 통합 활용에 관한 연구)

  • Kim, Hye Jin;Lee, Jae Bin;Kim, Yong Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.38 no.4
    • /
    • pp.345-352
    • /
    • 2020
  • To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

Host Interface Design for TCP/IP Hardware Accelerator (TCP/IP Hardware Accelerator를 위한 Host Interface의 설계)

  • Jung, Yeo-Jin;Lim, Hye-Sook
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.30 no.2B
    • /
    • pp.1-10
    • /
    • 2005
  • TCP/IP protocols have been implemented in software program running on CPU in end systems. As the increased demand of fast protocol processing, it is required to implement the protocols in hardware, and Host Interface is responsible for communication between external CPU and the hardware blocks of TCP/IP implementation. The Host Interface follows AMBA AHB specification for the communication with external world. For control flow, the Host Interface behaves as a slave of AMBA AHB. Using internal Command/status Registers, the Host Interface receives commands from CPU and transfers hardware status and header information to CPU. On the other hand, the Host Interface behaves as a master for data flow. Data flow has two directions, Receive Flow and Transmit Flow. In Receive Flow, using internal RxFIFO, the Host Interface reads data from UDP FIFO or TCP buffer and transfers data to external RAM for CPU to read. For Transmit Flow, the Host Interface reads data from external RAM and transfers data to UDP buffer or TCP buffer through internal TxFIFO. TCP/IP hardware blocks generate packets using the data and transmit. Buffer Descriptor is one of the Command/Status Registers, and the information stored in Buffer Descriptor is used for external RAM access. Several testcases are designed to verify TCP/IP functions. The Host Interface is synthesized using the 0.18 micron technology, and it results in 173 K gates including the Command/status Registers and internal FIFOs.

Data Mining Algorithm Based on Fuzzy Decision Tree for Pattern Classification (퍼지 결정트리를 이용한 패턴분류를 위한 데이터 마이닝 알고리즘)

  • Lee, Jung-Geun;Kim, Myeong-Won
    • Journal of KIISE:Software and Applications
    • /
    • v.26 no.11
    • /
    • pp.1314-1323
    • /
    • 1999
  • 컴퓨터의 사용이 일반화됨에 따라 데이타를 생성하고 수집하는 것이 용이해졌다. 이에 따라 데이타로부터 자동적으로 유용한 지식을 얻는 기술이 필요하게 되었다. 데이타 마이닝에서 얻어진 지식은 정확성과 이해성을 충족해야 한다. 본 논문에서는 데이타 마이닝을 위하여 퍼지 결정트리에 기반한 효율적인 퍼지 규칙을 생성하는 알고리즘을 제안한다. 퍼지 결정트리는 ID3와 C4.5의 이해성과 퍼지이론의 추론과 표현력을 결합한 방법이다. 특히, 퍼지 규칙은 속성 축에 평행하게 판단 경계선을 결정하는 방법으로는 어려운 속성 축에 평행하지 않는 경계선을 갖는 패턴을 효율적으로 분류한다. 제안된 알고리즘은 첫째, 각 속성 데이타의 히스토그램 분석을 통해 적절한 소속함수를 생성한다. 둘째, 주어진 소속함수를 바탕으로 ID3와 C4.5와 유사한 방법으로 퍼지 결정트리를 생성한다. 또한, 유전자 알고리즘을 이용하여 소속함수를 조율한다. IRIS 데이타, Wisconsin breast cancer 데이타, credit screening 데이타 등 벤치마크 데이타들에 대한 실험 결과 제안된 방법이 C4.5 방법을 포함한 다른 방법보다 성능과 규칙의 이해성에서 보다 효율적임을 보인다.Abstract With an extended use of computers, we can easily generate and collect data. There is a need to acquire useful knowledge from data automatically. In data mining the acquired knowledge needs to be both accurate and comprehensible. In this paper, we propose an efficient fuzzy rule generation algorithm based on fuzzy decision tree for data mining. We combine the comprehensibility of rules generated based on decision tree such as ID3 and C4.5 and the expressive power of fuzzy sets. Particularly, fuzzy rules allow us to effectively classify patterns of non-axis-parallel decision boundaries, which are difficult to do using attribute-based classification methods.In our algorithm we first determine an appropriate set of membership functions for each attribute of data using histogram analysis. Given a set of membership functions then we construct a fuzzy decision tree in a similar way to that of ID3 and C4.5. We also apply genetic algorithm to tune the initial set of membership functions. We have experimented our algorithm with several benchmark data sets including the IRIS data, the Wisconsin breast cancer data, and the credit screening data. The experiment results show that our method is more efficient in performance and comprehensibility of rules compared with other methods including C4.5.

Characteristic and Accuracy Analysis of Digital Elevation Data for 3D Spatial Modeling (3차원 공간 모델링을 위한 수치고도자료의 특징 및 정확도 분석)

  • Lee, Keun-Wang;Park, Joon-Kyu
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.19 no.11
    • /
    • pp.744-749
    • /
    • 2018
  • Informatization and visualization technology for real space is a key technology for construction of geospatial information. Three-dimensional (3D) modeling is a method of constructing geospatial information from data measured by various methods. The 3D laser scanner has been mainly used as a method for acquiring digital elevation data. On the other hand, the unmanned aerial vehicle (UAV), which has been attracting attention as a promising technology of the fourth industrial revolution, has been evaluated as a technology for obtaining fast geospatial information, and various studies are being carried out. However, there is a lack of evaluation on the quantitative work efficiency and data accuracy of the data construction technology for 3D geospatial modeling. In this study, various analyses were carried out on the characteristics, work processes, and accuracy of point cloud data acquired by a 3D laser scanner and an unmanned aerial vehicle. The 3D laser scanner and UAV were used to generate digital elevation data of the study area, and the characteristics were analyzed. Through evaluation of the accuracy, it was confirmed that digital elevation data from a 3D laser scanner and UAV show accuracy within a 10 cm maximum, and it is suggested that it can be used for spatial information construction. In the future, collecting 3D elevation data from a 3D laser scanner and UAV is expected to be utilized as an efficient geospatial information-construction method.

Vector-Based Data Augmentation and Network Learning for Efficient Crack Data Collection (효율적인 균열 데이터 수집을 위한 벡터 기반 데이터 증강과 네트워크 학습)

  • Kim, Jong-Hyun
    • Journal of the Korea Computer Graphics Society
    • /
    • v.28 no.2
    • /
    • pp.1-9
    • /
    • 2022
  • In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.

Generative Adversarial Network Model for Generating Yard Stowage Situation in Container Terminal (컨테이너 터미널의 야드 장치 상태 생성을 위한 생성적 적대 신경망 모형)

  • Jae-Young Shin;Yeong-Il Kim;Hyun-Jun Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
    • /
    • 2022.06a
    • /
    • pp.383-384
    • /
    • 2022
  • Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

  • PDF

An Evaluation of Building Effect in 2-Dimensional Inundation Analysis Using GIS (GIS를 활용한 2차원 침수해석에서의 건물영향 분석)

  • Cho, Wan-Hee;Han, Kun-Yeun;Kim, Young-Joo
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.13 no.2
    • /
    • pp.119-132
    • /
    • 2010
  • In this study, 2-dimensional inundation analysis for Taehwa watershed in Ulsan metropolitan city was conducted to analyze flow behaviors, inundation depth and inundation stage, considering the building effect. Lidar having the interval of 1 m was employed to generate topographic data with 10m interval, and building data extracted from digital map was combined with the constructed topographic data for 2-dimensional inundation analysis. A few scenarios were constructed for the analysis to provide an effective and accurate inundation analysis method through analyzing the results. The disagreement based on the areas of inundation showed over 10% between the cases with and without consideration of building effect. The maximum inundation depth without considering the effects of buildings was 0.29m higher than that with considering the building effects. On the contrary, the maximum inundation stage with consideration of building effects was 0.49m higher than that without consideration of building effects.

Simulation Study of Altitude and Angle Estimation with an InSAR Altimeter (InSAR 고도계의 높이 및 각도 추정에 대한 모의실험)

  • Paek, Inchan;Lee, Sangil;Chun, Joohwan;Lee, Hyukjung;Jang, Jong Hun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.25 no.8
    • /
    • pp.838-848
    • /
    • 2014
  • We present a simulation study of an algorithm for the range and angle of arrival(AOA) estimation with an interferometric synthetic aperture radar(InSAR) altimeter using a real digital elevation model(DEM). We also illustrate a step-by-step procedure of generating raw InSAR data, as well as their range and azimuth compressed data, which is to be used for the subsequent altitude and angle estimation. The AOA is estimated using a deterministic maximum likelihood estimator(DMLE) applied to the first arrived point for each pulse in the compressed data obtained with three antennas. The range bin size and the pulse repetition interval(PRI) are much smaller than the cell size of the DEM used in this study. To make the DEM compatible to the radar parameters, we first generate a higher resolution DEM by linearly interpolating the given DEM. After a brief description of the principle of the InSAR altimeter, the algorithms for altitude and angle estimation are presented, and their performance is assessed through simulation.

Incidence and Trends of Malignant and Benign Pancreatic Lesions in Yazd, Iran between 2001 and 2011

  • Zahir, Shokouh Taghipour;Arjmand, Azita;Kargar, Saeed;Neishaboury, Mohamadreza
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.14 no.4
    • /
    • pp.2631-2635
    • /
    • 2013
  • Background: Despite recent valuable steps in initiating a cancer registry in Iran, data depicting prevalence, incidence, and clinical picture of pancreatic tumors in the country are exceedinglyly sparse. With the aim of filling this knowledge gap, we reviewed cases in the pathology archive of Shahid Sadoughi hospital (Yazd, Iran), between 2001 and 2011. Materials and Methods: Medical records of 177 patients are reported in the present study. In cases for which paraffin-embedded blocks were available, the specimens were evaluated by two independent pathologists blinded to the primary diagnosis. We extrapolated the frequency of malignant lesions in our study to the population of Yazd province, derived from national census data, to generate cancer incidence rates. Results: Final diagnosis of malignancy was made in 117 cases (66.1%), and the remainder (60 lesions, 33.9%) were classified as benign. Adenecarcinoma and neuroendocrine tumors were the two most common histological types of malignancy identified in 88 (75.2%) and 11 (9.4%) specimens, respectively. Crude annual incidence of pancreatic cancer was 0.55 per 100,000 person in 2001 and increased to 1.68 in 2011. Age standardized incidence rates in 2001 and 2011 were 0.75 and 2.68, respectively. A significant increasing trend in cancer incidence was observed during the 11 years of the study period (r=+0.856, p=0.009). Sex-stratified analysis, confirmed the observed trend in men (r=+0.728, p=0.034), but not women (r=+0.635, p=0.083). Conclusions: Over the past decade, incidence of pancreas malignancies has risen steadily in Yazd, Iran. Nevertheless, these figures are still substantially lower than those prevalent in developed nations.