• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.97-103
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• 2016

This paper deals with the cycle time minimization problem that determines the productivity in printed circuit board (PCB) with n components using the m placement machines. This is known as production cycle time determination problem (PCTDP). The polynomial time algorithm to be obtain the optimal solution has been unknown yet, therefore this hard problem classified by NP-complete. This paper gets the initial assignment result with the machine has minimum unit placement time per each component firstly. Then, the balancing process with reallocation from overhead machine to underhead machine. Finally, we perform the swap optimization and get the optimal solution of cycle time $T^*$ within O(mn) computational complexity. For experimental data, the proposed algorithm can be obtain the same result as integer programming+branch-and-bound (IP+B&B) and B&B.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.80-85
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• 2001

In Part 2, dynamic cutting force model, thermal behavior model, and feed drive model are presented for development of a virtual machine tool. Some relevant results with brief descriptions for each model are presented to verify the proposed models. Experimental results for each model agreed well with the estimated ones. The developed models in this two-part paper are partially integrated as a comprehensive software environment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.83-88
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• 2003

In this study, experiments were conducted with an ultra-precision machine, developed In domestic, to find the characteristics and the most suitable cutting conditions of ultra-precision machining. To maximize the performance of the machine, the machine was installed in a room that is protected from vibration and is maintained constant temperature and constant humidity. Selected work pieces are an aluminum-alloyed material, which has excellent corrosion resistance and has low deformation. The used tool is synthetic poly crystal diamond which has excellent abrasion resistance and has low affinity. Four types of tool nose radius were used such as 0, 0.1, 0.2 and 0.4mm. Machining is performed with cutting speed of 500, 800 and 1000m/min., feed rate of 0.005, 0.008, 0.010mm/rev. and cutting depth of 0.0005, 0.0025 and 0.005mm respectively which can generally be used in the field as a cutting condition. As a method of evaluation surface roughness was measured for each cutting condition and reciprocal characteristics are computed for each tool nose radius, cutting speed, feed rate and cutting depth. As a result the most suitable cutting condition and characteristics of ultra-precision machining were identified which can usefully be applied in the industrial field.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.9-15
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• 2004

In this study, experiments were conducted with an ultra-precision machine, developed in domestic, to find the characteristics and the most suitable cutting conditions of ultra-precision machining. To maximize the performance of the machine, the machine was installed in a room that is protected from vibration and is maintained constant temperature and constant humidity. Selected work pieces are an aluminum-alloyed material, which has excellent corrosion resistance and has low deformation. The used tool is synthetic poly crystal diamond, which has excellent abrasion resistance and has low affinity. Four types of tool nose radius were used such as 0, 0.1, 0.2 and 0.4mm. Machining is performed with cutting speed of 500, 800 and 1000m/min., feed rate of 0.005, 0.008, 0.010mm/rev. and cutting depth of 0.0005, 0.0025 and 0.005mm respectively which can generally be used in the field as a cutting condition. As a method of evaluation, surface roughness was measured for each cutting condition, and reciprocal characteristics are computed for each tool nose radius, cutting speed, feed rate and cutting depth. As a result, the most suitable cutting condition and characteristics of ultra-precision machining were identified which can usefully be applied in the industrial field.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.1012-1016
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• 1998

According to the adoption of inverter circuit topology for welding machine area, the improvement of welding performance can be achieved. However conventional CO2 inverter arc welding machine uses the constant voltage characteristics. So the metal transfer is performed under unoptimum condition in the sence of spatter generation. In this paper the new control algorithm is proposed for welding machine, which is the instantaneous output current control method using single chip microprocessor. But the optimum waveform of welding current is still uncertain, as a first step for figuring out the optimized waveforms, this study was performed. And as a result of performance test of the proposed system, it was demonstrated that all of the waveform variation parameter could be set individually and the generated spatter is reduced compared to conventional inverter arc welding machine.

• Korean Journal of Food Science and Technology
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• v.46 no.6
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• pp.723-728
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• 2014

The physicochemical characteristics of coffees extracted using 7 different extraction methods were investigated. The pH values of coffees extracted via different extraction methods ranged from 5.26 to 5.54, and coffee extracted by Ibrik had the highest pH among all samples. The soluble solid content and titratable acidity of coffee extracted using an Espresso machine were significantly higher than those obtained using other extraction methods. Furthermore, the total phenol and caffeine contents of coffee extracted using an Espresso machine were 6.46 and 2.65 mg/mL, respectively. In regard to color, the $L^*$, $a^*$ and $b^*$ values of coffee extracted via different extraction methods were in the ranges of 0.81-38.94, 4.49-37.75, and 0.71-66.42, respectively. In regard to the phenolic compounds, the chlorogenic acid, caffeic acid and ferulic acid contents of coffee extracted using an Espresso machine were higher than those obtained by other extraction methods at 0.15 mg/mL, $0.075{\mu}g/{\mu}L$, and $0.019{\mu}g/{\mu}L$, respectively.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.771-783
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• 2023

This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.195-202
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• 2023

In this study, we sought to compare and evaluate the accuracy and predictive performance of machine learning algorithms for estimating the growth of individual Larix kaempferi trees in Gangwon Province, Korea. We employed linear regression, random forest, XGBoost, and LightGBM algorithms to predict tree growth using monitoring data organized based on different thinning intensities. Furthermore, we compared and evaluated the goodness-of-fit of these models using metrics such as the coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE). The results revealed that XGBoost provided the highest goodness-of-fit, with an R² value of 0.62 across all thinning intensities, while also yielding the lowest values for MAE and RMSE, thereby indicating the best model fit. When predicting the growth volume of individual trees after 3 years using the XGBoost model, the agreement was exceptionally high, reaching approximately 97% for all stand sites in accordance with the different thinning intensities. Notably, in non-thinned plots, the predicted volumes were approximately 2.1 m³ lower than the actual volumes; however, the agreement remained highly accurate at approximately 99.5%. These findings will contribute to the development of growth prediction models for individual trees using machine learning algorithms.

• Fire Science and Engineering
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• v.26 no.3
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• pp.60-66
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• 2012

In this study, it was evaluated the fire risk during welding cutting tasks. Welding-cutting machines are representatively used at construction sites. Inverter AC/DC TIG welding macnine and inverter air plasma cutting machine were used in experiments. Temperature of spreaded cinders was measured using a thermal camera. Cinder sizes and spread range were measured according to the height and input current. It was also evaluated the fire risk during welding-cutting process, when flammable materials were located around the working area. There were used hay, dust fence, urethane foam, vinyl, paper and oil as flammable materials. Temperature of spreaded cinders was reached at about $450^{\circ}C$. Cinders were spread approximately 4.7 m, when a worker carried out cutting process at 2.5 m height. The possibility of a fire is very high, when flammable materials were located around the working area.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.964-968
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• 2007

The measurement of floor impact sound have been standardized in KS 2810-1 and 2. The height of receiving microphones position is specified in the standard as 1.2m which is almost half height of apartment rooms as a listening position. In this study, receiving positions are investigated by measuring the distribution of sound pressure levels at 792 receiving microphone positions in the standard testing building. Standard impact sources, tapping machine and impact ball, are driven on the center position in the source room where is located at the above floor. It was found that the distribution of sound pressure levels in the receiving room indicates significant deviation at different frequencies there is more than 5dB drop at 63Hz but 2dB rise at 125Hz at a height of 1.2m when the impact ball is driven, in the other case of a generating tapping machine there is more than 2dB rise at 125Hz at a height of 1.2m due to room modes.