Aviation safety can be secured through regulations and policies of various areas and thorough execution of them on the field. Recently, for aviation safety management Korea is making efforts to prevent aviation accidents by taking various measures: such as selecting and promoting major strategic goals for each sector; establishing National Aviation Safety Program, including the Second Basic Plan for Aviation Policy; and improving aviation related legislations. Obstacle limitation surface is to be established and publicly notified to ensure safe take-off and landing as well as aviation safety during the circling of aircraft around airports. This study intends to review current aviation obstacle management system which was designed to make sure that buildings and structures do not exceed the height of obstacle limitation surface and identify its operating problems based on my field experience. Also, in this study, I would like to propose ways to improve the system in legal and regulatory aspects. Nowadays, due to the request of residents in the vicinity of airports, discussions and studies on aviational review are being actively carried out. Also, related ordinance and specific procedures will be established soon. However, in addition to this, I would like to propose the ways to improve shortcomings of current system caused by the lack of regulations and legislations for obstacle management. In order to execute obstacle limitation surface regulation, there has to be limits on constructing new buildings, causing real restriction for the residents living in the vicinity of airports on exercising their property rights. In this sense, it is regarded as a sensitive issue since a number of related civil complaints are filed and swift but accurate decision making is required. According to Aviation Act, currently airport operators are handling this task under the cooperation with local governments. Thus, administrative activities of local governments that have the authority to give permits for installation of buildings and structures are critically important. The law requires to carry out precise surveying of vast area and to report the outcome to the government every five years. However, there can be many problems, such as changes in the number of obstacles due to the error in the survey, or failure to apply for consultation with local governments on the exercise of construction permission. However, there is neither standards for allowable errors, preventive measures, nor penalty for the violation of appropriate procedures. As such, only follow-up measures can be taken. Nevertheless, once construction of a building is completed violating the obstacle limitation surface, practically it is difficult to take any measures, including the elimination of the building, because the owner of the building would have been following legal process for the construction by getting permit from the government. In order to address this problem, I believe penalty provision for the violation of Aviation Act needs to be added. Also, it is required to apply the same standards of allowable error stipulated in Building Act to precise surveying in the aviation field. Hence, I would like to propose the ways to improve current system in an effective manner.
1. Results in Nursery This experiment was carried out on the effect of the seed treament, soil preparations, kinds of covering soil and inside covering methods in two rice varieties, 'Tongil' and 'Akibare' to find out the most reasonable model of the flat nursery bed, with which lower cost is required comparing with the tunnel nursery. The results obtained are as follows: (1) The seedling of all plots of the ordinary seed were very poor compared to the plots of sprouted seed. (2) In case that the variety 'Tongil' was cultivated on the dry nursery bed, the good seedling percentage and the plant height rat io were significantly increased but the other characteristics of the seedling were not noticeable. (3) The kinds of the covering soil had not an effect on the seedling growth significantly. (4) Inside straw mulching was seemed effective for the protection in the case of the extreme high temperature and heavy rain fall, even though there was not significant differences between inside straw mulching and no treatments at the flat type nursery. (5) Difference of seedling growth between the flat type nursery and the tunnel type nursery was not significant. And it's reason was thought that the covering period of polyethylene film was short in semi hot nursery for the common early transplanting cultivation of rice. (6) The percentage of good seedling was higher at 'Akibare' than 'Tongil', variety but the number of seedling leaf and the seedling growth ratio in height were significantly increased in the variety 'Tongil'. The other seedling characters between there two varieties were not significantly different. 2. Results after transplanting This experiment was conducted to study on the ripening percentage, rice yield and disease, appearance of the seedling from sprouted seed plots including common irrigated nursery as check plot after transplantnig. The results obtained are summarized as follows: (1) The rice yield, the yield components and the appearance of leaf discoloration of both varieties, 'Tongil' and 'Akibare' were slightly betterat the plot of the standard tunnel nursery than that of the flat nursery with inside mulching or the among these three plots. (2) For 'Tongil' variety, the ripening percentage and the rice yield were significantly decreased at the common irrigated nursery compared with semi hot nursery. (3) The ripening percentage and the rice yield of 'Akibare' contrasted with 'Tongil' were significantly decreased at thesemi 'hot-nursery compared with common irrigated nursery. The main reason was thought to be the injury of the rice stripe disease (Rice stripe disease virus). Considering above mentioned experimental result, the seedling of 'Tongil' must be cultivated on the semi bot nursery for better ripening percentage as well as rice yield and for prevention of red discoloration. And as a model of semi hot nursery, the polyethylene covering nursery of standard tunnel type is most desirable but that of flat type with inside straw mulching is thought to be desirable too.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used