• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1708-1717
• /
• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• Journal of the Korean Wood Science and Technology
• /
• v.26 no.2
• /
• pp.16-23
• /
• 1998

This paper examines the effects of specimen length and grade on the strength and stiffness properties of structural timber of radiata pine. The tensile strength and modulus of elasticity of 1,902 machine-graded boards with 3.15- and 1.62-m clear span lengths, were determined using a horizontal tension test machine. The mean failure and characteristic stress values for tensile strength show an extremely high dependency on test specimen length. The mean and characteristic values of both modulus of elasticity and tensile strength show significant dependency on machine stress grades.

• Journal of Korean Elementary Science Education
• /
• v.40 no.1
• /
• pp.66-80
• /
• 2021

This study is a case study that applies plant classification learning using machine learning to fourth graders in elementary school in online learning situations. In this study, a plant classification learning education program associated with 2015 revision science curriculum was developed by applying the Artificial Intelligence biological classification teaching Learning model. The study participants were 31 fourth graders who agreed to participate voluntarily. Plant classification learning using machine learning was applied six hours for three weeks. The results of this study are as follows. First, as a result of image analysis on artificial intelligence, participants were mainly aware of artificial intelligence as mechanical (27%), human (23%) and household goods (23%). Second, an artificial intelligence recognition survey by semantic discrimination found that artificial intelligence was recognized as smart, good, accurate, new, interesting, necessary, and diverse. Third, there was a difference between men and women in perception and emotion of artificial intelligence, and there was no difference in perception of the ability of artificial intelligence. Fourth, plant classification learning using machine learning in this study influenced changes in artificial intelligence perception. Fifth, plant classification learning using machine learning in this study had a positive effect on reasoning ability.

• Journal of the Korean Home Economics Association
• /
• v.11 no.4
• /
• pp.363-373
• /
• 1973

The Sewability was tested with the seam strength and Puckering Grade by a general sewing machine according to some properties of simulated Leather, yarn tensile strength needle and stitches. The main results tested are as follows ; 1. The thick and uncomfortable leather is unable to be sewed by a general sewing machine, but the thin and soft one is able to. 2. The interval between stitches depends on type of leather used, and the variance in accordance with type of leather varies much more in the case of narrower interval. 3. When the sewability of leather-surface is not so good, is desirable to pour oil on the surface for the purpose of better efficiency. 4. The seam strength is directly proportional to interval of stitch and tensile strength of yarn and leather used, and needle No. 14 is more effective than No.1l. 5. The more the soft and thin leather is, the lower the Puckering Grade becomes. Type of yarn and interval of stitches do not seem to effect the Puckering Grade.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.513-516
• /
• 2013

Earthmoving equipment's haul-route has a great influence on the productivity of the earth work operation. Haul-route grade is a critical factor in selecting the haul-route. The route that has low grade resistance contributes to increase machine travel speed and production. This study presents a mathematical model called "Hauling-Unit Optimal Routes Selecting system" (HUORS). The system identifies optimal path that maximize the earth-work productivity. It consists of 3 modules, i.e., (1) Module 1 which inputs site characteristic data and computes site location and elevation using GIS(Geographical Information System); (2) Module 2 which calculates haul time; (3) Module 3 which displays an optimum haul-route by considering the haul-route's gradient resistances (i.e., from the departure to the destination) and hauling time. This paper presents the system prototype in detail. A case study is presented to demonstrate the system and verifies the validity of the model.

• ETRI Journal
• /
• v.43 no.4
• /
• pp.694-701
• /
• 2021

Catastrophic events cause casualties, damage property, and lead to huge social impacts. To build common standards and facilitate international communications regarding disasters, the relevant authorities in social management rank them in subjectively imposed terms such as direct economic losses and loss of life. Terrorist attacks involving uncertain human factors, which are roughly graded based on the rule of property damage, are even more difficult to interpret and assess. In this paper, we collected 114 183 open-source records of terrorist attacks and used a machine learning method to grade them synthetically in an automatic and objective way. No subjective claims or personal preferences were involved in the grading, and each derived common factor contains the comprehensive and rich information of many variables. Our work presents a new automatic ranking approach and is suitable for a broad range of gradation problems. Furthermore, we can use this model to grade all such attacks globally and visualize them to provide new insights.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1995.03a
• /
• pp.174-180
• /
• 1995

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.7
• /
• pp.327-332
• /
• 2016

This study is a leading research project to develop an automatic grade decision making algorithm of a 6-years-old fresh ginseng. For this work, we developed a Ginseng image acquiring instrument which can take 4-direction's images of a Ginseng at the same time and obtained 245 jingen images using the instrument. The 12 parameters were extracted for each image by a manual way. Lastly, 4 parameters were selected depending on a Ginseng grade classification criteria of KGC Ginseng research institute and a survey result which a distribution of averaging 12 parameters. A pattern recognition classifier was used as a support vector machine, designed to "k-class classifier" using the OpenCV library which is a open-source platform. We had been surveyed the algorithm performance(Correct Matching Ratio, False Acceptance Ratio, False Reject Ratio) when the training data number was controlled 10 to 20. The result of the correct matching ratio is 94% of the $1^{st}$ ginseng grade, 98% of the $2^{nd}$ ginseng grade, 90% of the $3^{rd}$ ginseng grade, overall, showed high recognition performance with all grades when the number of training data are 10.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.85-86
• /
• 2008

• Journal of Korea Technical Association of The Pulp and Paper Industry
• /
• v.35 no.5
• /
• pp.46-52
• /
• 2003

In this work we developed the closed-loop model of a paper machine during grade change with the intention to provide a reliable dynamic model to be used in the model-based grade change control scheme. During the grade change, chemical and physical characteristics of paper process change with time. It is very difficult to represent these characteristics on-line by using physical process models. In this work, the wet circulation part and the drying section were considered as a single process and closed-loop identification technique was used to develop the grade change model. Comparison of the results of numerical simulations with mill operation data demonstrates the effectiveness of the model identified.