• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.148-155
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• 2005

An accurate prediction of blooming date is crucial for many authorities to schedule and organize successful spring flower festivals in Korea. The Korea Meteorological Administration (KMA) has been using regression models combined with a subjective correction by forecasters to issue blooming date forecasts for major cities. Using mean monthly temperature data for February (observed) and March (predicted), they issue blooming date forecasts in late February to early March each year. The method has been proved accurate enough for the purpose of scheduling spring festivals in the relevant cities, but cannot be used in areas where no official climate and phenology data are available. We suggest a thermal time-based two-step phenological model for predicting the blooming dates of spring flowers, which can be applied to any geographic location regardless of data availability. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units until a pre-determined chilling requirement for rest release. After the projected rest release date, it accumulates daily heat units (growing degree days) until a pre- determined heating requirement for flowering. Model parameters were derived from the observed bud-burst and flowering dates of cherry tree (Prunus serrulata var. spontanea) at KMA Seoul station along with daily temperature data for 1923-1950. The model was applied to the 1955-2004 daily temperature data to estimate the cherry blooming dates and the deviations from the observed dates were compared with those predicted by the KMA method. Our model performed better than the KMA method in predicting the cherry blooming dates during the last 50 years (MAE = 2.31 vs. 1.58, RMSE = 2.96 vs. 2.09), showing a strong feasibility of operational application.

• Hwankyungkyoyuk
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• v.12 no.1
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• pp.205-224
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• 1999

This is a study of strengthening the practice of environmental education in the primary and secondary school music program. Since the world war II, the environmental situation has been getting worse and worse. So it is now a global issue to conserve energy and solving the ecological problems we are confronting. Solving the environmental problem is not just a scientist's task nor a specific school education subject's either, but a responsibility of all human beings. In this sense, it is necessary for every school subject, including music, should include elements of environmental education in its education contents. in this paper the researcher has tried to point out some reasonable aspects of environmental education guidelines which would be pursued through school music programs. In the music subject the following eight environmental education strategies could be suggested: 1. An affective aspect of music should be used in educating students to aware of the importance of environmental problems. 2. The effectiveness of employing music for various educational purposes should be implemented to make students environmentally enlightened individual. 3. The main issue of environmental problem must be used in various musical activities such as singing, implementing, composing and appreciating music. 4. By employing an alternative materials for making musical instruments, students and musicians can participate in environmental education program actively. 5. Music is analogues to life and nature. Thus it is highly suggested for teachers to teach students music more sincerely In a way of studying music more seriously, students could achieve environmental education goals by discovering the similarities of the nature of the environment and music as a human environment. 6. By appreciating many musical works of dealing with environmental problems and ecological problems, one could achieve the necessary goals of environmental education. 7. By enlarging the boundary of music including the sounds of nature such as birds' singing, sounds of winds and various streams and tree's trembling, music could achieve the major goals of environmental education. 8. By recognizing sounds as an important human environment, school music program could attain the goals of environmental education. The researcher also has mentioned about the characteristics of music as a schooling subject. and has provided with some detailed curriculum guidelines for strengthening environmental education programs in music classes. Some model lesson plans implementing the environmental education for elementary, junior high school and 10th grade music classes are also suggested followed by six specific teaching ＆ learning methods for environmental education.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.4
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• pp.45-56
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• 2016

In this study, an analysis has been conducted on the evaluation criteria of current G-SEED(Green Standard for Energy and Environmental Design) and on the 78 buildings, certified by G-SEED, for 3 years from November, 2012 to November, 2015. Based on the results of this analysis, four issues are driven and proposed hereinafter. Issue 1 : Nowadays, the psychological proportion of landscape architecture in building is getting greater than ever so that it shows reliable reduction of carbon dioxide. Therefore, so far as the eight kinds of buildings are concerned, the evaluation items of G-SEED must include those of landscape architecture mandatorily through its enlargement. Issue 2 : It is undesirable factor that inhibits precise evaluation on landscaping area to let other areas appraise landscape architecture because it requires outstanding professionalism. So, G-SEED should not only ensure landscaping professionalism for the correct evaluation but also let landscape area participate in assessing other areas. Issue 3 : Many previous researches turned out that landscape planting technique has excellent effect on saving energy and reducing temperature of buildings. Thus, landscape planting technique of landscape area is required to be one of the evaluation items of energy sector. Issue 4 : Tree management also has to be newly included as one of the evaluation factor for the maintenance relating to the landscape architecture. G-SEED, enacted and enforced by the Green Building Creation Support Act in 2013, surely is effective system to reduce carbon dioxide in buildings. This is a special Act in its nature that is superior to Construction Law and must be observed by all means to construct buildings. Under the umbrella of this legal system, various of researches and products are contributing to creating new jobs in construction area. However, it is a well-known fact that landscape architecture area has shown less interest on this Act than that of construction area. In conclusion, it is necessary that landscape industry should conduct continuous researches on G-SEED and pay more attention to the Act enough to harvest related products and enlarge its work area.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.253-258
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• 2010

Traditional frequent pattern mining considers equal profit/weight value of every item. Weighted Frequent Pattern (WFP) mining becomes an important research issue in data mining and knowledge discovery by considering different weights for different items. Existing algorithms in this area are based on fixed weight. But in our real world scenarios the price/weight/importance of a pattern may vary frequently due to some unavoidable situations. Tracking these dynamic changes is very necessary in different application area such as retail market basket data analysis and web click stream management. In this paper, we propose a novel concept of dynamic weight and an algorithm DWFPM (dynamic weighted frequent pattern mining). Our algorithm can handle the situation where price/weight of a pattern may vary dynamically. It scans the database exactly once and also eligible for real time data processing. To our knowledge, this is the first research work to mine weighted frequent patterns using dynamic weights. Extensive performance analyses show that our algorithm is very efficient and scalable for WFP mining using dynamic weights.

• Information Systems Review
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• v.7 no.2
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• pp.23-40
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• 2005

Discovering customers' behavioral patterns from large data set and providing them with corresponding services or products are critical components in managing a current business. However, the diversity of customer needs coupled with the limited resources suggests that companies should make more efforts on understanding and managing specific groups of customers, not the whole customers. The key issue of this paper is based on the fact that the behavioral patterns extracted from the specific groups of customers shall be different from those from the whole customers. This paper proposes the idea of pre-segmentation before developing customer classification models. We collected three customers' demographic and transactional data sets from a credit card, a tele-communication, and an insurance company in Korea, and then segmented customers by major variables. Different churn prediction models were developed from each segments and the whole data set, respectively, using the decision tree induction approach, and compared in terms of the hit ratio and the simplicity of generated rules.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.55-62
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• 2011

Amidst the raising of climate change in relation to the earth's environment as an international issue, there is a growing interest in forest resources. In particular, Korea faces a period in which we need to control carbon release pursuant to the Convention on Climate Change and the enforcement of the Kyoto Protocol; therefore, the importance of forests is becoming greater. Recently, there has been a focus on light detection and ranging (Lidar) which is a means of acquiring in a short time various necessary pieces of information for forest management as three dimensional geospatial information. In this study, the carbon absorption of a forest was measured by using the Lidar data obtained from the Lidar. Carbon absorption release was calculated on the basis of three criteria involving the minimum height of a tree, the density of the forest, and the minimum area of the forest, which are items proposed by the Forest resources surveyor. Through this study, a method of extracting the carbon absorption of a forest area using the Lidar data quantitatively was confirmed.

• Journal of KIISE
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• v.44 no.10
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• pp.1071-1080
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• 2017

With today's complex networks, asset identification of network devices is becoming an important issue in management and security. Because these assets are connected to the network, it is also important to identify the network structure and to verify the location and connection status of each asset. This can be used to identify vulnerabilities in the network architecture and find solutions to minimize these vulnerabilities. However, in an IoT(Internet of Things) network with a small amount of resources, the Traceroute packets sent by the monitors may overload the IoT devices to determine the network structure. In this paper, we describe how we improved the existing the well-known double-tree algorithm to effectively reduce the load on the network of IoT devices. To balance the load, this paper proposes a new destination-matching algorithm and attempts to search for the path that does not overlap the current search path statistically. This balances the load on the network and additionally balances the monitor's resource usage.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.518-527
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• 2007

It is an important issue to find out the difference between RDF documents, because RDF documents are changed frequently. When RDF documents contain blank nodes, we need a matching technique for blank nodes in the change detection. Blank nodes have a nested form and they are used in most RDF documents. A RDF document can be modeled as a graph and it will contain many subtrees. We can consider a change detection problem as a minimum cost tree matching problem. In this paper, we propose a change detection technique for RDF documents using the labeling scheme for blank nodes. We also propose a method for improving the efficiency of general triple matching, which used predicate grouping and partitioning. In experiments, we showed that our approach was more accurate and faster than the previous approaches.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.117-121
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• 2008

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Therefore, the energy consumption is important in the routing design, otherwise cluster schemes are efficient in energy conserving. For the above reasons, an Energy conserving Context aware Clustering algorithm (ECC) is proposed to establish the network clustering structure, and a routing algorithm is introduced to choose the Optimal Energy Routing Protocol (OERP) path in this paper. Because in ad hoc network, the topology, nodes residual energy and energy consuming rate are dynamic changing. The network system should react continuously and rapidly to the changing conditions, and make corresponding action according different conditions. So we use the context aware computing to actualize the cluster head node, the routing path choosing. In this paper, we consider a novel routing protocol using the cluster schemes to find the optimal energy routing path based on a special topology structure of Resilient Ontology Multicasting Routing Protocol (RODMRP). The RODMRP is one of the hierarchical ad hoc network structure which combines the advantage of the tree based and the mesh based network. This scheme divides the nodes in different level found on the node energy condition, and the clustering is established based on the levels. This protocol considered the residual energy of the nodes and the total consuming energy ratio on the routing path to get the energy efficiently routing. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.