• 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.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.35-59
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• 2018

Professor Bin Cheng said that outer space was res extra commercium, while the moon and the other celestial bodies were res nullius before the 1967 Outer Space Treaty(OST). However, Article 2 of the OST made the moon and other celestial bodies have the legal status as res extra commmercium, not appropriated by any country or private enterprises or individual person, but the resources there can be freely available, as those on the high seas. The non-appropriation principle was introduced to corpus juris spatialis internationalis. Whether or not the non-appropriation principle is binding for the non-parties of the OST, many scholars see this principle as an international customary law, even developing into jus cogens. Article 11(2) of the Moon Agreement(MA) reconfirms the nonappropriation principle of Article 2 of the OST, but it has much less effect than the OST because the MA binds only the 18 parties involved. The MA applies only to the moon and celestial bodies other than the Earth in the Solar System, the OST's application scope extends to the Galaxy because the OST has no such substantive enactment. As referred to in the 2015 CSLCA of USA or Luxembourg's Law of Space Resources, allowing individuals and enterprises run by other countries to commercially explore and utilize the space resources, the question may arise whether this violates the non-appropriation principle under Article 2 of the OST and Article 11 of the MA. In the case of the CSLCA, the law explicitly specifies that sovereignty, possessory rights, and judiciary rights to a specific celestial body cannot be claimed, let alone ownership. This author believes that this law respects the legal status of outer space and the celestial bodies as res extra commmercium. As long as any countries or private enterprises or individuals respect the non-appropriation principle of outer space and the celestial bodies, they could use, exploit it. Another question might be raised in the difference between res extra commercium on the high seas and res extra commercium in outer space and the celestial bodies. Collecting resources on the high seas and exploiting space resources should be interpreted differently. On the high seas, resources can be collected without any obstacles like fishing, whereas, in the case of the deep sea-bed area, the Common Heritage of Mankind principles under the UNCLOS should be operated by the International Seabed Authority as an international regime. The nature or form of the sea resources found on the high seas are thus different from that of space resources, which are fixed on the moon and the celestial bodies without water. Thus, if individuals or private enterprises collect these resources from outer space and the celestial bodies, they might secure a certain section and continue collecting or mining works without any limitation. If an American enterprise receives an approval from the U.S. government, secures the best location and collects resources on the moon, can other countries' enterprises access to this area? How large the exploiting place can be allotted on the moon? How long should such a exploiting activity be lasted? Under the current international space law, these matters might be handled according to the principle of "first come, first served." As a consequence, the international community should provide a guideline or a proposal for the settlement of any foreseeable disputes during the space activity to solve plausible space legal questions in the near future.