• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.372-381
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• 2019

This study was conducted to find proof for the hypothesis that the God tree of Chosun has been misrepresented in Chosun-Gersu-Nosu-Myungmokji (CGNM). The following results were obtained. First, it was established that 64 species and 3170 trees were recorded in CGNM. An old, big tree is classified as a God tree if linked to it there are testimonies and legends about divine elements, and it is classified as a Noble tree if linked to it there are testimonies and legends of historical elements. In total, 2632 trees of eight species were analyzed, from the Zelkova serrata, which has the greatest number of trees, to the eighth most frequent, Abies holophylla. The means of diameter at breast height (DBH), height, and age of the God and the Noble trees were calculated for each of the eight species. In seven out of eight species, the DBH and age of the Noble tree were more than those of the God tree. In addition, the height of the Noble tree was more than that of the God tree in six out of eight species. The fact that the God tree is smaller than the Noble tree, contrary to the common expectation that the Noble tree is a small size tree, was confirmed. This hypothesis was proved by the data gathered. Second, the Japanese Government-General of Korea has pursued a policy to defeat the village ritual based on the God tree being linked with superstition. For such a policy, the God tree should be small and unattractive, and it would have been good for the tree to be superstitious. The CGNM was created as explanatory material or evidence for distorting the sacredness of the God tree of Chosun. Third, CGNM compiled a chronological order of DBH data to make it easy to explain the fabricated facts that the God tree of Chosun is smaller and dwarfed compared to the Noble tree.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.23-30
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• 2015

As BigData is issued, many applications that operate based on the results of data analysis have been developed, typically applications are products recommend service of e-commerce application service system, search service on the search engine service and friend list recommend system of social network service. In this paper, we suggests a decision frequent pattern tree that is combined the origin frequent pattern tree that is mining similar pattern to appear in the data set of the existing data mining techniques and decision tree based on the theory of computer science. The decision frequent pattern tree algorithm improves about problem of frequent pattern tree that have to make some a lot's pattern so it is to hard to analyze about data. We also proposes to model for a Mapredue framework that is a programming model to help to operate in distributed environment.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.184-191
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• 2020

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.

• Journal of Forest and Environmental Science
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• v.11 no.1
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• pp.22-39
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• 1995

Following "Studies on Characteristics of Pin us densiflora Forest in Kangwon Province (III)- Studies on the Tree-Root Form and Distribution on the Campus Forest, Kangwon Nat'l Univ.-", the form and distribution of root system was investigated for 5 trees in Songhyun-Ri, Wangsan-Myon, Myengju-Gun, Kangwon Province. Vertical tap roots and flat roots were established very well. In root distribution, fine roots were sparsly distributed (+), although 7 smaller quadrats($10{\times}10cm$) were found with the value of 1(+~20%) index of fine root; big roots 0.2cm thick in diameter were most common. More than 50% of fine roots and big roots were found around the depth of 10~30cm in soil.

• Convergence Security Journal
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• v.21 no.1
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• pp.93-100
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• 2021

Damage caused by intelligent cyber attacks not only disrupts system operations and leaks information, but also entails massive economic damage. Recently, cyber attacks have a distinct goal and use advanced attack tools and techniques to accurately infiltrate the target. In order to minimize the damage caused by such an intelligent cyber attack, it is necessary to block the cyber attack at the beginning or during the attack to prevent it from invading the target's core system. Recently, technologies for predicting cyber attack paths and analyzing risk level of cyber attack using big data or artificial intelligence technologies are being studied. In this paper, a cyber attack path analysis method using attack tree and RFI is proposed as a basic algorithm for the development of an automated cyber attack path prediction system. The attack path is visualized using the attack tree, and the priority of the path that can move to the next step is determined using the RFI technique in each attack step. Based on the proposed mechanism, it can contribute to the development of an automated cyber attack path prediction system using big data and deep learning technology.

• Smart Media Journal
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• v.11 no.4
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• pp.9-18
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• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.2
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• pp.73-83
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• 2014

This study was conducted to evaluate defects in Zelkova serrata trees using an ultrasonic tomograph (PICUS) and suggest a management plan to maintain it as a natural and cultural resource. In previous study, health information of 16 protected trees were obtained by surveying the following categories; tree appearance, crown, bark, root exposure, water and nutrition, deterioration, pest, vitality, ground status, and pollutant. The average score of health was 16.5 in 16 trees, which means that general monitor is needed for management. In this study, the evaluation result of tree's inside defects using an ultrasonic tomograph showed that 43.8% of decay rate has been found in 16 trees. In fact, some trees look to be good even though they actually have a defects causing broken by natural disaster such as strong wind. Therefore, it is urgent to put some support to the trees and come up with a protective plan. The results of this study would be useful as basic data in developing a guideline for the efficient conservation and management of big and old trees.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.75-80
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• 2008

This paper proposes a method to detect scene change using global decision tree that extract boundary cut that have width of big change that happen by camera brake from difference value of frames. First, calculate frame difference value through regional X2-histogram and normalization, next, calculate distance between difference value using normalization. Shot boundary detection is performed by compare global threshold distance with distance value for two adjacent frames that calculating global threshold distance based on distance between calculated difference value. Global decision tree proposed this paper can detect easily sudden scene change such as motion from object or camera and flashlight.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.270-280
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• 2017

Selection of superior phenotypes of fruit trees and products based on established criteria by local people is a prerequisite for future species domestication and conservation. Thus the study objective was to identify the local people's perceptions and preferences on baobab trees and products. A sample of 142 respondents was randomly selected using structured interviews in Blue Nile and North Kordofan, Sudan in 2013. Descriptive analysis was employed using SPSS and Excel programs. The study results indicated that local people use the morphological characteristics of the tree (leaves, fruits, seeds, kernels and bark) to differentiate individual trees. Based on the perceptions, local people recorded trees with delicious leaves, white pulp color, big fruit size and mature capsule size, and high pulp yield as criteria for differentiating between baobab trees in the study areas. In contrast, the undesirable traits were connected to trees with acidic pulp, slimy pulp, bitter leaves, and low pulp yield. The study concluded that the ethnobotanical knowledge of the baobab tree and its products may play an important role in tree domestication and improvement in Sudan. However, further research on tree genetics is needed to complement the ethnobotanical knowledge for baobab resources domestication and conservation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.217-220
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• 2005

Internal cities such as gray level been enclosed to building forest are paying a lot of efforts and expenses to change to green city toot park and street tree get put together. By the example, 'GREEN CITY of PUSAN 21' progress to decorate army facilities like the park, and to plant street trees in several places of city plan in Pusan. And urban environment that big citys of advanced nation are agreeable is making in the large park and road street trees at several places in downtown. Because price of tree for the park is very expensive, tree management system was all-important. In this paper, Motes deliver the sensor information in each tree through radio sensor network by server side. This information can use in state grasping of tree, harmful insects courtesy call etc and this system design was suggested to inform to mode of life administration scholars.