Accurate spatial information on forest roads is important for forest management and harvest operations. This study evaluated the positional accuracy, shape similarity, and cost of three mapping techniques: GNSS (Global Navigation Satellite System) mapping, CAD file conversion (as-built drawing), and image warping. We chose five road routes within the national forest road system in the Republic of Korea and made digital road maps using each technique. We then compared map accuracy to reference maps made from field surveys. The mapping and field-survey results were compared using point-correspondence, buffering analysis, shape index, and turning function methods. The comparisons indicate that GNSS mapping is the best technique because it generated the highest accuracy (Root Mean Square Error: GNSS mapping 1.28, image warping 7.13, CAD file conversion 13.35), the narrowest buffering width for 95% of the routes overlapped (buffering width: GNSS mapping 1.5 m, image warping 18 m, CAD file conversion 24 m), highest shape similarity (shape index: GNSS mapping 19.6–28.9, image warping 7.2–10.8, CAD file conversion 6.5–7.4), and smallest area size difference in turning function analysis (GNSS mapping 2814–4949, image warping 7972–26,256, CAD file conversion 8661–27,845). However, GNSS requires more time (236 min/km) and costs more ($139.64/km) to produce a digital road map as compared to CAD file conversion (99 min/km and $40.90/km) and image warping (180 min/km and $81.84/km). Managers must decide on the trade-off between accuracy and cost while considering the demand and purpose of maps. GNSS mapping can be used for small-scale mapping or short-haul routes that require a small error range. Image warping was the lowest cost and produced low-accuracy maps, but may be suitable for large-scale mapping at the regional or national level. CAD file conversion was expected to be the most accurate method, because it converted as-built drawings to a map. However, we found that it was the least accurate method, indicating low accuracy of the as-built drawings. Efforts should be made to improve the accuracy of the as-built drawings in Korea.

In this study, an active steering bogie with a redesigned primary axial rubber spring for urban trains was developed. The applied axial rubber spring had a reasonable stiffness that can be achieved in the X, Y and Z directions. Therefore, the steering performance of the bogie can improve because of the lower longitudinal stiffness. The running performance of an active steering vehicle on a curved track was simulated by means of a co-simulation with VI-Rail and MATLAB/ Simulink. Further, a control algorithm was developed and applied to an actual active steering bogie. The radius of curvature acquired from the actual active steering bogie by the control algorithm was in reasonable agreement with that acquired from a track inspection vehicle. The numerical analysis revealed a significant improvement in the vehicle safety and ride quality and a reduction in the wheel-rail wear and noise. As a result, the validities of the developed primary suspension and control algorithm of the active steering bogie were confirmed. Further, this study may enable railway vehicles to run more stably and faster on sharp curves.

In high-aspect ratio laser drilling, many laser and optical parameters can be controlled, including the high-laser beam fluence and number of drilling process cycles. Measurement of the drilled hole depth is occasionally difficult or time consuming, especially during machining processes. This study aimed to estimate the drilled hole depth in high-aspect ratio laser drilling by using captured two-dimensional (2D) hole images. The measuring conditions included light brightness, light exposure time, and gamma value. In this study, a method for predicting the depth of a machined hole by using a deep learning methodology was devised. Adjusting the laser power and the number of processing cycles for blind hole generation and image analysis yielded optimal conditions. Furthermore, to forecast the form of the machined hole, we identified the best circumstances based on changes in the exposure duration and gamma value of the microscope, which is a 2D image measurement instrument. After extracting the data frame by detecting the contrast data of the hole by using an interferometer, the hole depth was predicted using a deep neural network with a precision of within 5 μm for a hole within 100 μm.

This study was conducted to optimize the blending ratio of kimchi seasoning through the perception of consumers of commercial kimchi, and to develop the best kimchi sauce. Surveys on 189 women were conducted and the optimum kimchi recipe was selected using the response optimization tool for the proportion of fermented anchovy sauce, saltedfermented shrimp, and water in the ingredients of kimchi. 41.3% of the respondents were under 30 years of age, and most of the respondents were housewives and students. The reason for purchasing kimchi products is because it has become troublesome and economically burdensome to make it at home, and the younger generation of Koreans does not know how to make it. Also, the smaller the number of family members is, the higher the tendency to buy commercial kimchi becomes because the members eat less kimchi. The reason one does not want to purchase commercial kimchi is lack of trust in the ingredients, and high price. The rank of kimchi based on taste appears in the order of savory taste, pungent taste, salted seafood taste, salty taste, and sweet taste. The optimal ratio of myeolchi aekjeot (fermented anchovy sauce), water, and saeujeot (salted-fermented shrimp) was 27.12: 62.88: 10.00 (w/w).

The primary suspension system of a railway vehicle restrains the wheelset and the bogie, which greatly affects the dynamic characteristics of the vehicle depending on the stiffness in each direction. In order to improve the dynamic characteristics, different stiffness in each direction is required. However, designing different stiffness in each direction is difficult in the case of a general suspension device. To address this, in this paper, an optimization technique is applied to design different stiffness in each direction by using a conical rubber spring. The optimization is performed by using target and analysis RMS values. Lastly, the final model is proposed by complementing the shape of the weak part of the model. An actual model is developed and the reliability of the optimization model is proved on the basis of a deviation average of about 7.7% compared to the target stiffness through a static load test. In addition, the stiffness value is applied to a multibody dynamics model to analyze the stability and curve performance. The critical speed of the improved model was 190km/h, which was faster than the maximum speed of 110km/h. In addition, the steering performance is improved by 34% compared with the conventional model.