• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.192-197
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• 2020

Recently, the technologies related to autonomous drive has studying the goal for safe operation and prevent accidents of vehicles. There is radar and camera technologies has used to detect obstacles in these autonomous vehicle research. Now a day, the method for using LiDAR sensor has considering to detect nearby objects and accurately measure the separation distance in the autonomous navigation. It is calculates the distance by recognizing the time differences between the reflected beams and it allows precise distance measurements. But it also has the disadvantage that the recognition rate of object in the atmospheric environment can be reduced. In this paper, point cloud data by triangular functions and Line Regression model are used to implement measurement algorithm, that has improved detecting objects in real time and reduce the error of measuring separation distances based on improved reliability of raw data from LiDAR sensor. It has verified that the range of object detection errors can be improved by using the Python imaging library.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.68-78
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• 2000

This paper suggests a new map-matching algorithm for matching traveling trace of vehicle, which is measured by GPS receiver, to the road of a digital map This eventually brings the Improvement of positioning accuracy of the vehicle with GPS receiver After representing the travelling vehicle's motion by state equations using Singer's model, the proposed map-matching algorithm places the position of a vehicle right on the road and also improves the positioning accuracy of the vehicle using a Kalman filter In the crossroad, since it is difficult to determine precisely a current travelling road, we take linear regression to the estimated values from Kalman filtering This gives the direction angle of turning vehicle, then we can determine the correct route direction after comparing with each route-direction angle at the intersection.

• Journal of Korean Society of Steel Construction
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• v.26 no.3
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• pp.191-204
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• 2014

In this paper a systematic numerical analysis is performed to obtain the bending moment resisting capacity of a top and seat angle connection, which is a type of partially restrained connection, for a CFT composite frame subjected to cyclic loading. This partially restrained composite CFT connections are fabricated using high strength steel connection bar. The three-dimensional nonlinear finite element models are constructed to investigate the rotational stiffness, bending moment capacity, and failure modes. A wide scope of additional structural behaviors explain the different influences of the top and seat angle connection's parameters, such as the different thickness of connection angles and the gage distances of the high strength steel bar. The moment-rotation angle relationships obtained from the finite element analysis are compared with those from Richard's theoretical equation.

• Journal of the Korea Institute of Building Construction
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• v.11 no.4
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• pp.371-378
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• 2011

Concrete is affected by various deterioration factors, such as $CO_2$ and chloride ions from the sea, which cause carbonation and salt attack on concrete. These deterioration phenomena cause steel corrosion in RC structures. Although a great deal of research has been carried out in this area thus far, it is difficult to know the point at which corrosion will occur to a reinforced bar. As the diffusion of deterioration factors depends on the water content in concrete, it is imperative to assess the condition of absorbed water content. A mass measuring method was applied to calculate the absorbed water diffusion coefficient, as well as non-linear finite element method(FEM) analysis. As a result, it was found that W/C and unit water content in concrete mixture affect the diffusion coefficient decision.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.125-132
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• 2000

pH, EC and TDS are basic components in the investigation of groundwater quality, and are very important to the preliminary assessment of groundwater quality. These three chemical components investigated at the Youngsan and Sumjin river basins in 1998 suggest that the groundwater quality is generally good in these basins. Linear regression analysis shows that TDS versus EC has an linear correlation, but EC versus pH, and TDS versus pH have nearly no correlation. The relation of TDS and EC is 1.0 mg/1=1.52 $mu\textrm{S}$/cm, and it is the quality of natural water. In geostatistical analysis. three kinds of data are stationary random functions and they have exponential variograms. According to the isopleth maps of the groundwater quality, the groundwater quality of the Youngsan river basin is more contaminated than that of the Sumjin river basin. The isopleth maps of TDS and EC show very similar patterns because of the strong correlation between TDS and EC. The minimum and maximum values of the groundwater quality data are not reflected on the isopleth maps because kriging produces smooth distributions with minimum estimation variances.

• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.165-172
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• 2021

Breaking wave is one of the important design factors in the design of coastal and port structures as they are directly related to various physical phenomena occurring on the coast, such as onshore currents, sediment transport, shock wave pressure, and energy dissipation. Due to the inherent complexity of the breaking wave, many empirical formulas have been proposed to predict breaker indices such as wave breaking height and breaking depth using hydraulic models. However, the existing empirical equations for breaker indices mainly were proposed via statistical analysis of experimental data under the assumption of a specific equation. In this study, a new Munk-type empirical equation was proposed to predict the height of breaking waves based on a representative linear supervised machine learning technique with high predictive performance in various research fields related to regression or classification challenges. Although the newly proposed breaker height formula was a simple polynomial equation, its predictive performance was comparable to that of the currently available empirical formula.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.183-190
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• 2018

Predicting accurate electricity prices is an important task in the electricity trading market. To address the electricity price forecasting problem, various approaches have been proposed so far and it is known that linear regression-based approaches are the best. However, the use of such linear regression-based methods is limited due to low accuracy and performance. In traditional linear regression methods, it is not practical to find a nonlinear regression model that explains the training data well. If the training data is complex (i.e., small-sized individual data and large-sized features), it is difficult to find the polynomial function with n terms as the model that fits to the training data. On the other hand, as a linear regression model approximating a nonlinear regression model is used, the accuracy of the model drops considerably because it does not accurately reflect the characteristics of the training data. To cope with this problem, we propose a new electricity price forecasting method that divides the entire dataset to multiple split datasets and find the best linear regression models, each of which is the optimal model in each dataset. Meanwhile, to improve the performance of the proposed method, we modify the proposed localized linear regression method in the map and reduce way that is a framework for parallel processing data stored in a Hadoop distributed file system. Our experimental results show that the proposed model outperforms the existing linear regression model. Specifically, the accuracy of the proposed method is improved by 45% and the performance is faster 5 times than the existing linear regression-based model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.46-57
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• 2019

Generally speeding appeared to be the most contributing factor of fatalities occurred in work zones, and highway agencies in South Korea have concerned of the safety of workers and drivers in the poor circumstances. In this study, a portable variable message signs (PVMS) system as an alternative of control speeding in work zones was implemented. This study evaluated the safety effectiveness of the PVMS based on speeds and the compliance with the speed limit. Linear regression and logistic regression models were adopted to quantify the safety effect of the PVMS between the 'before' and 'after'. The results showed that most of points had statistically significant speeds reduction experience after PVMS installation. Also, the percentage of vehicle exceeding the speed limit by 10 km/h or more was decreased significantly between 50 and 80% in the 'after' periods compared to the 'before' periods. Therefore, the PVMS would be contributed to benefit safety in work zones which there is a difference in design speed of the adjacent normal section.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.185-194
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• 2014

One in every 10 persons suffer from chronic gastritis in Korea. Endoscopy is most commonly used to diagnose the chronic gastritis. Endoscopic diagnosis is precise but it is accompanied with pain and high cost. According to pulse diagnosis in Traditional East Asian Medicine, health problems in stomach can be diagnosed with radial pulse signals in 'Guan' location in the right wrist, which are non-invasive and cost-effective. In this study, we developed a classification model of chronic gastritis using pulse signals in right 'Guan' location. We used both linear discrimination method and logistic regression model with respect to pulse features obtained with a peak-valley detection algorithm and a Gaussian model. As a result, we obtained sensitivity ranged between 77%~89% and specificity ranged between 72%~83% depending on classification models and feature extraction methods, and the average classification rates were approximately 80%, irrespective of the models. Specifically, the Gaussian model were featured by superior sensitivities (89.1% and 87.5%) while the peak-valley detection method showed superior specificities (82.8% and 81.3%), and the average classification rate (sensitivity + specificity) of the Gaussian model was 80.9% which was 1.2% ahead of the peak-valley method. In conclusion, we obtained a reliable classification model for the chronic gastritis based on the radial pulse feature extraction algorithms, where the Gaussian model was featured by outperformed sensitivity and the peak-valley method was featured by outperformed specificity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.223-235
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• 2020

In this study, we propose an approach for calibrating the elevation of a DEM (Digital Elevation Model), one of the key data in realizing unmanned aerial vehicle image-based precision agriculture. First of all, radiometric correction is performed on the orthophoto, and then ExG (Excess Green) is generated. The non-vegetation area is extracted based on the threshold value estimated by applying the Otsu method to ExG. Subsequently, the elevation of the DEM corresponding to the location of the non-vegetation area is extracted as EIFs (Elevation Invariant Features), which is data for elevation correction. The normalized Z-score is estimated based on the difference between the extracted EIFs to eliminate the outliers. Then, by constructing a linear regression model and correcting the elevation of the DEM, high-quality DEM is produced without GCPs (Ground Control Points). To verify the proposed method using a total of 10 DEMs, the maximum/minimum value, average/standard deviation before and after elevation correction were compared and analyzed. In addition, as a result of estimating the RMSE (Root Mean Square Error) by selecting the checkpoints, an average RMSE was derivsed as 0.35m. Comprehensively, it was confirmed that a high-quality DEM could be produced without GCPs.