• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.6
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• pp.84-96
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• 2008

This research investigated the landscape characteristics of the skyline and the cognitive characteristics of Mt. Mudeung (1,186m) from various viewpoints. Mt. Mudeung, the representative landscape of Gwangju City, has been recognized as a natural landmark and theme of paintings. By analyzing the perspective from 32 points with a digital terrain model, some landscape indices of the skyline were derived and the relationships are discussed. Assessment of the semantic differential scale with 21 adjective variables and representativeness to 15 landscape photographs of the mountain were accomplished. 1. Through regression analysis of the skyline indices, significant relationships were found between them the angle from the visual axis and number of skyline jumps, the vertical angle fluctuation and number of jumps per degree, the visual depth fluctuation and vertical angle fluctuation of skyline, and between the vertical angle mean and number of jumps per degree. Meaningful relations were found between the number of jumps of skyline to number of jumps per degree and the angle from visual axis to visual distance. However, in the representative assessment no difference was found on the angle from visual axis of viewpoints. On the other hand, it seemed to relate representativeness with visual clarity based on visual distance. 2. We found 4 factors "familiarity", "fluctuation of skylines", "openness", and "feeling of texture" in the results of factor analysis of semantic differential assessment. When considering the results of assessment for representativeness, adjective words for familiarity and openness seemed to have a close assessment. Specifically, the research showed that the landscape representation was highly assessed in a view which could be seen from the higher parts to the lower part of hills. This result indicates that the management of viewpoints which could get a scene from intermediate to distant, and locating a high elevation is important. 3. In the picturesque expression of Mt. Mudeung, various impressions from the different points, a skyline based on the top of Mt. Mudeung and a mono structure by overlapping hills were common characteristics. These common characteristics were also partially found through the analysis of topographical landscape indices and landscape images. Therefore, the viewpoints for the representative landscape management should be selected in natural or open spaces.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.79-92
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• 2023

With a growing interest in the Han River Skyline, which greatly influences Seoul's image, careful consideration of the skyline form has become crucial in the redevelopment plans for apartment complexes along the Han River. The Seoul Metropolitan City government has lifted the height limitations for apartments along the Hang River to cultivate a vibrant skyline. However, traditional skyline analysis often overlooks specific attributes, limiting the provision of precise guidelines for Seoul's unique skyline plans. Despite advancements in Digital Twin technology, only some tools effectively manage urban skylines with preferred shapes. Hence, this study aims to make a substantial contribution to the advancement of a Digital Twin 3D modeling program capable of effectively managing urban skylines. This is achieved through the utilisation of Conjoint Analysis, which assesses the importance of each attribute in determining the preferred skyline shape. Focusing on Apgujeong apartment complexes along the Han River currently undergoing redevelopment or planned for redevelopment, the study analyses the preferred skyline shape to propose standards for the Digital Twin 3D modeling program development. It also suggests that Conjoint Analysis can be beneficial in this process.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1277-1298
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• 2017

Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.259-260
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• 2014

본 논문은 편의점, 까페 등의 창업시 많은 후보군들 사이에서 적절한 위치를 추천하는 서비스를 만들어보고자 수행되었다. 본 연구는 Skyline Query를 이용하여 사용자가 설정한 지점으로부터의 거리에 따른 예상이익을 도출해내고, MapReduce를 사용하여 많은 후보군들을 대상으로 이를 효율적으로 처리하도록 구현하였다. 본 연구의 방법을 사용하여 창업자가 설정한 한정적 자원 및 거리 제한 조건 안에서 최적의 위치를 손쉽게 추천해줄 수 있을 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.474-477
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• 2011

본 논문은 평면상에 주어진 자료점의 집합 P로부터 질의 집합 Q에 대해 skyline을 성질을 만족하는 P의 부분집합을 찾는 알고리즘을 제시한다. 이 때 P의 점들 간의 우위는 Q의 점에서의 거리를 이용하여 판단하는데 이 논문에서는 두 점간의 거리를 $L_1$거리로 정의한다. 이와 같은 환경 하에서 |P|$\geq$|Q|라고 가정할 때 우리는 O(|P|log|P|) 시간에 모든 skyline을 찾는 알고리즘을 제시하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.370-381
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• 2012

Multi-criteria result extraction is crucial in many scientific applications that support real-time stream processing, such as habitat research and disaster monitoring. Skyline evaluation is computational intensive especially over continuous time-interval data streams where each object has its own customized expiration time. In this work, we propose TI-Sky - a continuous skyline evaluation framework. To ensure correctness, the result space needs to be continuously maintained as new objects arrive and older objects expire. TI-Sky strikes a perfect balance between the costs of continuously maintaining the result space and the costs of computing the final skyline result from this space whenever a pull-based user query is received. Our key principle is to incrementally maintain a partially precomputed skyline result space - however doing so efficiently by working at a higher level of abstraction. TI-Sky's algorithms for insertion, deletion, purging and result retrieval exploit both layers of granularity. Our experimental study demonstrates the superiority of TI-Sky over existing techniques to handle a wide variety of data sets.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.289-293
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• 2009

In sensor networks, many methods have been proposed to process in-network aggregation effectively. Contrary to normal aggregation queries, skyline query processing that compare multi-dimension data for producing result is very hard. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approach like MFTAC restricts unnecessary data transitions by deploying filters to whole sensors. However, network lifetime is reduced by energy consumption for filters transmission. In this paper, we propose a lazy filtering-based skyline query processing algorithm of in-network for reducing energy consumption by filters transmission. The proposed algorithm creates the skyline filter table (SFT) in the data gathering process which sends from sensor nodes to the base station and filters out unnecessary transmissions using it. The experimental results show that the proposed algorithm reduces false positive by 53% and improves network lifetime by 44% on average over MFTAC.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.280-291
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• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.7-18
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• 2012

It has been studied to support data having multiple properties, called Skyline Query. The skyline query is not exploring data having all properties but only meaningful data, when we retrieve informations in large data base. The skyline query can be used to provide some information about various environments and situations in sensor network. However, the legacy skyline query has a problem that increases the number of comparisons as the number of sensors are increasing in multi-dimensional data. Also important values are often omitted. Therefore, we propose a new method to reduce the complexity of comparison where the large number of sensors are placed. To reduce the complexity, we transfer a CMF(Category Based Member Function) which can identify preference of specific data when interest query from sync-node is transferred to sub-node. To show the validity of our method, we analyzed the performance by simulations. As a result, it showed that the time complexity was reduced when we retrieved information in multiple sensing data and omitted values are detected by great dominance Skyline.