• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.119-128
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• 1993

Effective machine capacity is affected by the physical and geometrical conditions of the fields. In the small and scattered farmland structure field efficiency is greatly influenced by plot geometry. In this paper, a method for estimating field efficiency and effective machine capacity was developed . The developed method was applied to Korean paddy cultivation. Various time elements related to farm operations for small and scattered plots are discussed in this paper . Available working time is divided into two parts, viz. the preparation time for machine operation and actual working time. Two kinds of machine efficiencies, namely , Machine Efficiency 1, applicable on a single large plot or set of well consolidated plots ; and Machine Efficiency 2, applicable on small and scattered multiple plots, are considered. Based assumptions made and steps followed to construct the model are discussed. Effective capacity of each machine based on different plot geometries are calculated y the model. Machine efficiency on a single plot increases with increase in the dimension of longer side of the plot . Low speed, low theoretical capacity machines have higher machine efficiency which is only slightly influenced by plot geometry. As plot geometry is improved , the machine efficiency of high speed, high capacity machines increases rapidly. The effects of short side length and plot size on machine efficiency on a single plot depend on the type of farm operation. For a particular plot shape, as plot size increases, machine efficiency on multiple plots increases rapidly. The effects of consolidation on machine efficiency is highly significant if the plot size is small and/or machine size is large.

• Proceedings of the Korean Society of Sericultural Science Conference
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• 1997.06a
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• pp.103-117
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• 1997

Decrease in the cocoon production of Japan is drastic because of low price of cocoon, scarcity of successors and so on. To tide over the difficulty, the automation system in the sericulture was discussed and some trials have been conducted by the Ministry of Agriculture, Forestry and Fisheries of Japan. The attempts are based on a low cost artificial diet which does not rely on mulberry leaves. Automatic machines developed until now are a rearing machine constituted with repeated belt conveyor, an reformation type of former rearing machine "Bombyx" and a mounting machine. Running parallel with them, utilization of 20-hydroxyecdysone extracted from a plant to the mounting was also studied to use their machines efficiently in the fields. In conclusion, 10 tons of law cocoon will come to be produced by two persons labor. At present, an automatic rearing system on low cost artificial diet has been developing for the future sericulture.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.47-50
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• 2016

Big Data is coming rapidly in recent times and keep the vast amount of data was utilized them. These data are utilized in many fields in particular, based on the patient data in the medical field to increase the therapeutic effect, as well as re-incidence to better treatment, lowering the readmission rates increased the quality of life. In this paper it is practiced to report basis of the analysis and verification of data using python. And it can be analyzed the data through a simple formula, from Select reason of Python to how it used; by Press analysis of Agriculture, Forestry and Fisheries research. In this process, a simple formula can be used that expression for analyzing the actual data so it taking advantage of the use of functions in real life.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.159-168
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• 2019

Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE $L{\ast}a{\ast}b{\ast}$ color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.

• Journal of Forest and Environmental Science
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• v.9 no.1
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• pp.1-9
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• 1993

In the fall of 1992, growth characteristics and cone-bearing behaviour of crown top shoots were investigated on Pin us koraiensis trees, belonging to age class VII and IV, in the School Forests, College of Forestry, Kangwon National University to obtain basic information for the design of Korean pine cone harvesting machine. The results were summarized as follows. 1. The length of terminal main shoots and lateral shoots of the trees in age class IV was 27~56cm and 18~47cm, respectively, both of which were significantly higher than those of the trees in age class VII. 2. There was no significant difference between two age classes in the branching angle ($24{\sim}89^{\circ}$) of lateral shoots and in the diameter (10~30mm) of two-year-old main shoots. However, one-year-old terminal main shoots of age class IV showed the higher diameter (9~18mm) than those of age class VII. 3. Mean cone number per tree was 5, and mean fresh weight of cone was 272g. No significant difference was found in these traits between both age classes. 4. Cones, on an average, hung on the two-year-old main shoots 15cm above the basal ends in age class VII and 33cm above in age class IV. Both lengths are equivalent to one half and four fifths of the shoots, respectively. 5. The fresh weight range of crown-top shoots containing cones was 1.0~7.4kg.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.299-310
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• 1994

This study was carried out to examine the optimal road spacing and road density to minimize the total harvesting cost(road construction cost plus yarding cost) for mechanized yarding system to roadside by one - and two-stage two-way in Forestry build-up region. Chunchon-kun, Kangwon-do. The estimated road construction costs were ranged from ten million won to sixty million won per km. The results have indicated that cable crane was appropriate for yarding machine by one-stage, two-way, and estimated optimal road spacing was 1,698m~4,192m, averaged 3,087m, and road density was 3.44m/ha~8.44m/ha, and averaged 5. 12m/ha. In hilly terrain, combination of medium yarder and Logging bogie was suited to yarding machine by two-stage, two-way, and calculated optimal road spacing was 1,483m~3,481m, averaged 2,589m, and road density was 4.05m/ha~9.46m/ha, averaged 5.90m/ha. In steep terrain, combination of medium yarder and jinsung winch was suited, and estimated optimal road spacing was 1,693m~3,982m, averaged 2,960m, and road density was 3.68m/ha~8.64m/ha, averaged 5.38m/ha.

• Journal of the Korean Wood Science and Technology
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• v.25 no.4
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• pp.17-21
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• 1997

This study was carried out to develop the manufacturing technique of Korean paper(Hanji) and find out new uses of machine-made Hanji produced on a a large scale by paper machine. Six kinds of Hanji were made and laminated with backpaper by acryl-based or vinyl acetate ethylene-based adhesive. Six kinds of wallpapers were made such as WH 1, WH 2-1, WH 2-2, WH 3-1, WH 3-2 and WH 4. Physical properties and quality test on the wallpapers were examined. Physical strength of the wallpapers was better than each strength of the Hanji and backpaper. It might be a roll of adhesive. And so, Production cost of the Hanji could be brought down if the Hanji was made thin to get strength not enough to cut during lamination of two papers(Hanji and backpaper). Hanji wallpapers of WH 3-1 and WH 4 are lower than a standard in sunlight resistance and WH 1 is in properties of opacity. WH 2-1, WH 2-2 and WH 3-2 were better than Korean standard in some quality tests. WH 2-2 and WH 3-2 were superior to other wallpapers as a whole. About, twenty kinds of wallpapers with surface treatment, are now being produced on the basis of these two types of wallpapers.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Journal of the Korean Wood Science and Technology
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• v.48 no.4
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• pp.458-471
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• 2020

Effect of pre-treatment and compression ratio on specific gravity (SG) and dimensional stability improvement of three lesser-used wood species from natural forest area of North Kalimantan Province, Indonesia had been investigated. Hot soaking at 80℃ for 3 hours within 2 and 5% of boron solution was applied as pre-treatment, while compression ratio applied was 20 and 40% from the initial thickness. Densification was conducted using hot pressing machine at 30 kg/㎠ of pressure and 160℃ of temperature for 15 minutes. Specific gravity was measured gravimetrically, while dimensional stability was evaluated through thickness swelling and water absorption as the indicator. Results show that SG of densified wood was influenced by wood species and compression ratio, but not by pre-treatment applied; while dimensional stability was influenced by wood species, compression ratio, and pre-treatment. Specific gravity and water absorption of densified wood was improved significantly. Specific gravity increased 28.86-63.03%, while water absorption decreased 12.80-15.89%. Thickness swelling of 20% densified wood was lower than that of 40% densified wood.