• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1152-1154
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• 2003

The needs of 3-D data have been increasing for various applications like visualization, 3-D modeling, planning and management as well as entertainment. Mobile mapping has become a quick and practical means for acquiring necessary 3-D data for above-mentioned applications. A mobile mapping system mainly consists of two main components, viz. data acquisition devices and positioning devices. The data acquisition devices consist of CCD cameras or/and laser scanners. The positioning devices consist of GPS, INS, Odometer (shaft encoder) and some other referencing devices. The overall accuracy of mobile mapping system depends on the accuracy of positioning devices and their integrated output. Though, GPS is the main input device for the position information, the signal is not available for the computation of position all the times in urban area. The GPS satellites are normally obstructed by high-rise buildings. Thus it is very important to understand the accuracy of such a system in different environments and means to solve such problems. We have developed a mobile mapping system called VLMS (Vehicle-borne Laser Mapping System), which consists of CCD Cameras, Laser scanners, GPS, INS and Odometer. In this paper, we will present and discuss the accuracy of this system with data acquired in different environments (open area, urban area, tunnel, express way etc) by analyzing the data with respect to other existing digital data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.185-194
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• 2010

In recommender systems which are used widely at e-commerce, collaborative filtering needs the information of user-ratings and neighbor user-ratings. These are an important value for recommendation in recommender systems. We investigate the in-formation of rating in NBCFA (neighbor Based Collaborative Filtering Algorithm), we suggest new algorithm that improve prediction accuracy of recommender system. After we analyze relations between two variable and Error Value (EV), we suggest new algorithm and apply it to fitted line. This fitted line uses Least Squares Method (LSM) in Exploratory Data Analysis (EDA). To compute the prediction value of new algorithm, the fitted line is applied to experimental data with fitted function. In order to confirm prediction accuracy of new algorithm, we applied new algorithm to increased sparsity data and total data. As a result of study, the prediction accuracy of recommender system in the new algorithm was more improved than current algorithm.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.7-15
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• 2007

The accuracy of a Video Image Detector (VID) is gradually reduced due to various environmental and mechanical factors. However, there has been no systematic research about the decrease of VID accuracy. To maintain a proper level of VID accuracy for advanced traffic management, a regular VID calibration process needs to be introduced. However, the calibration cannot be performed frequently because of the cost. In this study, the researchers collected field data for accuracy estimation and inferred an accuracy decreasing function by using regression and considering the heteroscedasticity problem. Using the invented data collection equipment which was used for checking adaptability, some data in the field were collected and analyzed. Although the data were limited, the results are promising. More data need to be investigated in the future and this study will help to maintain the data quality for broad utilization of the data in ITS centers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.187-194
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• 1998

In this study, effective multispectral Landsat TM band combinations for a merging with the high resolution IRS-1C PAN data using the IHS method to improve landuse accuracy is discussed. From the pre-classified image using the merged images with TM all six band images(with the exception of band 6 image) and PAN image, a sample data which has ten classes was generated. An evaluation of the overall classification accuracy for the representative seven merged images which were merged using each TM three-band images and IRS-1C PAN image by IHS method for the sample area. The increase in classification accuracy is most significant with the inclusion of two of TM4, TM5 and TM7 infrared band images. Especially, the largest increase(11.8 percent) in landuse classification accuracy were investigated when Landsat TM247 bands were merged with IRS-1C PAN data. The classification accuracy when TM three band image and PAN image were used without merging is higher than result of the case of using the merged images.

• The Journal of Advanced Prosthodontics
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• v.15 no.3
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• pp.145-154
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• 2023

PURPOSE. The objective of this study was to investigate how internal structures influence the overall and marginal accuracy of full arch preparations fabricated through additive manufacturing in different printing systems. MATERIALS AND METHODS. A full-arch preparation digital model was set up with three internal designs, including solid, hollow, and grid. These were printed using three different resin printers with nine models in each group. After scanning, each data was imported into the 3D data processing software together with the master cast, aligned and trimmed, and then put into the 3D data analysis software again to compare the overall and marginal deviation whose results are expressed using root mean square values and color maps. To evaluate the trueness of the resin model, the test data and reference data were compared, and the precision was evaluated by comparing the test data sets. Color maps were observed for qualitative analysis. Data were statistically analyzed by one-way analysis of variance and Bonferroni method was used for post hoc comparison (α = .05). RESULTS. The influence of different internal structures on the accuracy of 3D printed resin models varied significantly (P < .05). Solid and grid models showed better accuracy, while the hollow model exhibited poor accuracy. The color maps show that the resin models have a tendency to shrink inwards. CONCLUSION. The internal structure design influences the accuracy of the 3D printing model, and the effect varies in different printing systems. Irrespective of the kind of printing system, the printing accuracy of hollow model was observed to be worse than those of solid and grid models.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.4
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• pp.204-211
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• 2004

Autonomous profiling CTD floats are a useful tool for observing the oceans. We, however, cannot perform post-deployment calibration of the CTD's attached to the floats, and the assessment of the accuracy and stability of the profile data from the floats is one of the important issues in the delayed mode quality control of the profiles. Variations in salinity in the intermediate level of East Sea is comparable to the accuracy of salinity data required by the international Argo Program, which is 0.01. Therefore, we can assess the credibility of salinity data from the floats deployed in the East Sea using three independent methods while considering the East Sea as a salinity calibration bath. The methods utilized here are 1) comparison of high quality CTD data and float data obtained at similar locations at similar time, 2) comparison of float data obtained at similar locations at similar time, and 3) investigation of long term stability and accuracy of salinity data from parking depths. All three methods show that without any calibration, the salinity data satisfy the accuracy criterion by the Argo Program. While assuming that the intermediate level temperature in the East Sea is as homogeneous as the salinity, we have applied the three methods to temperature data. We found that the accuracy of temperature reading is 0.01$^{\circ}C$, which is about twice larger than the requirement by the Argo Program, 0.005$^{\circ}C$. This does not mean that the temperature readings are inaccurate, because the intermediate level temperature does vary spacially and temporally more than the accuracy interval required by the Argo Program. If we take into account the variation in the intermediate level temperature, the accuracy of temperature data from the floats is not significantly different from that proposed by the Argo Program. Therefore, one could use both temperature and salinity profiles from the floats assessed in this study without calibration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.257-263
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• 2011

There are many previous researches such as verification of accuracy, application, and change detection of discrete return LiDAR data, but no researches for full waveform LiDAR data. In this study, we selected the forest area and urban area as case study areas and compared the height accuracy of full waveform LiDAR data with field surveying data. As a result, we got an RMSE of 3.lcm in urban area, 4.7cm in forest area, and it is verified that height accuracy of full waveform LiDAR is high. We think that it is very usefull in aerial photogrammetry.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.167-174
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• 2023

This paper attempted to improve the accuracy of the colorectal cancer diagnosis model using image data augmentation in convolutional neural network. Image data augmentation was performed by flipping, rotation, translation, shearing and zooming with basic image manipulation method. This study split 4000 training data and 1000 test data for 5000 image data held, the model is learned by adding 4000 and 8000 images by image data augmentation technique to 4000 training data. The evaluation results showed that the clasification accuracy for 4000, 8000, and 12,000 training data were 85.1%, 87.0%, and 90.2%, respectively, and the improvement effect depending on the increase of image data was confirmed.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.177-183
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• 2024

The study investigates the impact of data quality on the performance of artificial intelligence (AI). To this end, the impact of labeling error levels on the performance of artificial intelligence was compared and analyzed through simulation, taking into account the similarity of data features and the imbalance of class composition. As a result, data with high similarity between characteristic variables were found to be more sensitive to labeling accuracy than data with low similarity between characteristic variables. It was observed that artificial intelligence accuracy tended to decrease rapidly as class imbalance increased. This will serve as the fundamental data for evaluating the quality criteria and conducting related research on artificial intelligence learning data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.549-554
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• 2021

Precise 3D road geospatial information is the basic infrastructure for autonomous driving and is essential data for safe autonomous driving. MMS (Mobile Mapping System) is being used as equipment for road spatial information construction, and related research is being conducted. However, there are insufficient studies to analyze the effect of the baseline reference point distance, which is an important factor in the accuracy of the MMS outcome, on the accuracy of the outcome. Therefore, in this study, the accuracy of the data acquired using MMS by reference point distance was analyzed. Point cloud data was constructed using MMS for the road in the study site. For data processing, 4 data were constructed considering the distance from the reference point for MMS data, and the accuracy was analyzed by comparing the results of 12 checkpoints for accuracy evaluation. The accuracy of the MMS data showed a difference of -0.09 m to 0.11 m in the horizontal direction and 0.04 m to 0.19 m in the height direction. The error in the vertical direction was larger than that in the horizontal direction, and it was found that the accuracy decreased as the distance from the reference point increased. In addition, as the length of the road increases, the distance from the reference point may vary, so additional research is needed. If the accuracy evaluation of the method using multiple reference points is made in the future, it will be possible to present an effective method of using reference points for the construction of precise road spatial information.