• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.83-92
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• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• Journal of Korean Society of Forest Science
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• v.9 no.1
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• pp.1-44
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• 1969

The important results which have been obtained in the investigation can be recapitulated as follows. 1. As demostrated by the experimental results and analyses concerning their effects in the on-ground type mushroom house, the constructions in relation to the side wall and ceiling of the experimental houses showed a sufficient heat insulation on effect to protect insides of the houses from outside climatic conditions. 2. As the effect on the solar type experimental mushroom house which was constructed in a half basement has been shown by the experimental results and analyses, it has been proved to be effective for making use of solar heat. However there were found two problems to be improved for putting solar houses to practical use in the farm mushroom growing: (1) the construction of the roof and ceiling should be the same as for the on-ground type house, and (2) the solar heat generating system should be reconstructed properly. A trial solar heat generating system is shown in Fig. 40. 3. Among several ventilation systems which have been studied in the experiments, the underground earthen pipe and ceiling ventilation, and vertical side wall and ceiling ventilation systems have been proved to be most effective for natural ventilation. 4. The experimental results have shown that ventilation systems such as the vertical side wall and underground ventilation systems are suitable to put to practical use as natural ventilation systems for farm mushroom houses. These ventilation systems can remarkably improve the temperature of fresh air which is introduced into the house by heat transfers within the ventilation passages, so as to approach to the desired temperature of the house without any cooling or heating operation. For example, if it is assuming that x is the outside temperature and y is the amount of temperature adjustment made by the influence of the ventilation system, the relationships that exist between x and y can be expressed by the following regression lines. Underground iron pipe ventilation system ${\cdots}{\cdots}$ y=0.9x-12.8 Underground earthen pipe ventilation system ${\cdots}{\cdots}$y=0.96x-15.11 Vertical side wall ventilation system${\cdots}{\cdots}$ y=0.94x-17.57 5. The experimental results have shown that the relationships existing between the admitted and expelled air and the $Co_2$ concentration can be described with experimental regression lines or an exponent equation as follows: 1) If it is assumed that x is an air speed cm/sec. and y is an expelled air speed in cm/sec. in a natural ventilation system, since the y is a function of the x, the relationships that exist between x and y can be expressed by the regression lines shown below: 2) If it is assumed that x is an admitted volume of air in $m^3/hr$ and y is an expelled volume of air in $m^3/hr$ in a natural ventilation system, since the y is a function of the x, the relationships that exist between x and y can be expressed by the regression lines shown below. 3) If it is assumed that the expelled air speed in cm/sec and replacement air speed in cm/sec. at the bed surface in a natural ventilation system are shown as x and y, respectively, since the y is a function of the x, the relationships that exist between x and y can be expressed by the following regression line: G.E. (100%)- C.V. (50%) ventilation system${\cdots}$ y=0.54X+0.84 4) If it is assumed that the replacement air speed in cm/sec. at the bed surface is shown as x, and $CO_2$ concentration which is expressed by multiplying 1000 times the actual value of $CO_2$ % is shown as y, in a natural ventilation system, since the y is a function of the x the relationships that exist between x and y can be expressed by the following regression line: G.E. (100%)- C.V. (50%) ventilation system${\cdots}{\cdots}$ y=114.53-6.42x 5) If it is assumed that the expelled volume of air is shown as x and the $CO_2$ concentration which is expressed by multiplying 1000 times the actual of $CO_2$ % is shown as y in a natural ventilation system, since the y is a function of of the x, the relationships that exist between x and y can be expressed by the following exponent equation: G.E. (100%)-C.V. (50%) ventilation system${\cdots}{\cdots}$ $$y=127.18{\times}1.0093^{-X}$$ 6. The experimental results have shown that the ratios of the crass sectional area of the G.E. and C.V. vent to the total cubic capacity of the house, required for providing an adequate amount of air in a natural ventilation system, can be estimated as follows: G.E. (admitting vent of the underground ventilation)${\cdots}{\cdots}$ 0.30-0.5% (controllable) C.V. (expelling vent of the ceiling ventilation)${\cdots}{\cdots}$ 0.8-1.0% (controllable) 7. Among several heating devices which were studied in the experiments, the hot-water boilor which was modified to be fitted both as hot-water toiler and as a pressureless steam-water was found most suitable for farm mushroom growing.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Applied Biological Chemistry
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• v.29 no.1
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• pp.62-72
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• 1986

At present, the definition and chemical analysis method of available soil phosphorus for plants have not been standardized because of the complexity of crop and soil characteristics in Korea and many analysis methods have been suggested with different extraction conditions. Suitable analytical method of available soil P should be established by the trial of various methods based on crop nutrition and soil conditions. To establish the most suitable analysis method of available soiIP, a pot experiment with young maize was conducted over 44 different upland soils collected over the land of Korea. The amount of uptaken P by the plant was determined by ten different chemical methods for the available soil P. The results obtained were as follows: 1. Total phosphorus content in the sample soils ranged ranged $533{\sim}4917\;ppm$, and showed significant positive correlation with the content of organic matter. 2. The P content was relatively low in the acid sulfate soil and very high in the volcanic ash soil although both types of soil contained high level of orgic matter. 3. The amount of extractable P determined by ten different methods were varied more or less, and the ratios of the extractable P to the total soil P were in the range of $1{\sim}48%$. 4. The relative values to the amount of extractable soil P by different methods were in the order of $H_2O(5\;min.)\;1.0\;<\;H_2O(60min.)\;2.27\;<\;NH_4HCO_3\;5.57\;<\;NaHCO_3\;7.42\;<\;Double\;lactate\;9.71\;<\;Bray\;No.1\;12.53\;<\;Lancaster\;17.63\;<\;Nelson\;25.96\;<\;AcOH\;27.6\;<\;CAL-method\;50.27$ 5. The amount of extractable P determined by all of applied methods was very low in acid sulfate soil, volcanic ash soil and coarse textured soil. 6. Soil pH and total soil P generally showed significant positive correlation with the chemically extracted P, and soil organic matter was negatively correlated with the determined by Nelson-and CAL-method. Olsen method which showed significant correlation with exchangeable calcium seemed to be recommendable for calcareous soils. 7. Total amount of uptaken P by Young maize through continuos twice cropping was 4.05% of total soil P in average, and the uptake in the second cropping was twice as much as that of the first cropping. 8. Three determination methods, i.e. Soltanpour-, Double lactate and Bray No. 1-method seemed to be more suitable than Lancaster method which is widely practiced at present in Korea. However, further study should be carried out with other crops and soils to most adequate chemical method for determination of available soil P.

• Korean Journal of Soil Science and Fertilizer
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• v.12 no.4
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• pp.189-213
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• 1980

1. Aiming at supply of basic informations on tree species siting and forest fertilization by understanding of soil properties that are demanded by each tree species through studies of forest soil's morphological, physical and chemical properties in relation to tree growth in our country, the necessary data have been collected in the last 10 years, are quantified according to quantification theory and are analyzed in accordance with multi-variate analysis. 2. Test species, larch and the Korean white pine, are plantable in extensive areas from mid to north in the temperate zone and are the two most recommended reforestation tree species in Korea. However, their respective site demands are not known and they have been in confusion or considered demanding the same site during reforestation. When the Korean white pine is planted in larch sites, it has shown relatively good growth. But, when larch is planted in the Korean white pine site it can be hardly said that the larch growth is good. To understand on such a difference soil factors have been studied so as to see how the soil's morphological, physical and chemical factors affect tree growth helped with the electronic computer. 3. All the stands examined are man-made mature forests. From 294 larch plots and 259 white pine plots dominant trees are cut as samples and through stem analysis site index is determined. For each site index soil profiles are made in the related forest-land for analysis. Soil samples are taken from each profile horizon and forest-land productivity classification tables are worked out through physical and chemical analysis of the soil samples for each tree species for the study of relationships between physical, chemical and the combined physical/chemical properties of soil and tree growth. 4. In the study of relationships between physical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of deposit form, soil depth, soil moisture, altitude, relief, soil type, depth of A-horizon, soil consistency content of organic matter soil texture bed rock gravel content aspect and slope. For the Korean white pine the influencing factors' order is soil type, soil consistency bed rock aspect depth of A-horizon soil moisture altitude relief deposit form soil depth soil texture gravel content and slope. 5. In the study of relationships between chemical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of base saturation organic matter CaO C/N ratio, effective $P_2O_5$ PH.exchangeable $K_2O$ T-N MgO C E C Total Base and Na. For the Korean white pine the influencing factors' order is effective $P_2O_5$ Total Base T-N Na C/N ratio PH CaO base saturation organic matter exchangeable $K_2O$ C E C and MgO. 6. In the study of relationships between the combined physical and chemical properties of soil and tree growth it is found out that larch growth is influenced by the following factors in the order of soil depth deposit form soil moisture PH relief soil type altitude T-N soil consistency effective $P_2O_5$ soil texture depth of A-horizon Total Base exchangeable $K_2O$ and base saturation. For the Korean white pine the influencing factors' order is soil type soil consistency aspect effective $P_2O_5$ depth of A-horizon exchangeable $K_2O$ soil moisture Total Base altitude soil depth base saturation relief T-N C/N ratio and deposit from. 7. In the multiple regression of forest soil's physical properties larch's correlation coefficient is 0.9272 and for the Korean white pine it is 0.8996. With chemical properties larch has 0.7474 and the Korean white pine has 0.7365. So, the soil's physical properties are found out more closely related with tree growth than chemical properties. However, this seems due to inadequate expression of soil's chemical factors and it is proved that the chemical properties are not less important than the physical properties. In the multiple regression of the combined physical and chemical properties consisting of important morphological and physical factors as well as chemical factors of forest soils larch's multiple correlation coefficient is found out to be 0.9434 and for the Korean white pine it is 0.9103 leading to the highest correlation. 8. As shown in the partial correlation coefficients larch needs deeper soil depth than the Korean white pine and in the deposit form colluvial and creeping soils are demanded by the larch. Adequately moist to too moist should be soil moisture and PH should be from 5.5 to 6.1 for the larch. Demands of T-N soil texture and soil nutrients are higher for the larch than the Korean white pine. Thus, soil depth, deposit form, relief soil moisture PH N altitude and soil texture are good indicators for species sitings with larch and the Korean white pine while soil type and soil consistency are indicative only limitedly of species sitings due to their wide variation as plantation environments. For larch siting soil depth deposit form relief soil moisture PH soil type N and soil texture are indicators of good growth and for Korean white pine they are soil type soil consistency effective $P_2O_5$ and exchangeable $K_2O$, which is demanded more by the Korean white pine than larch generally. 9. Physical properties of soil has been known as affecting tree growth to greatest extent so far. However, as a result of this study it is proved through computer analysis that chemical properties of soil are not less important factors for tree growth than chemical properties and site demands for larch and the Korean white pine that have been uncertain So far could be clarified.