• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.89-96
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• 2004

Abstraction is an important concept applied widely to variables, functions, complex data, abstract data types, classes and polymorphism in programming languages. However, the concept of abstraction has been considered as ambiguous and explained differently because it is not defined clearly and uniformly. In this paper, we analyse many aspects of abstraction in programming languages, and propose the taxonomy of abstraction. We classify abstraction according to the mechanism of formation into 4 categories such as napping abstraction, bundling abstraction. integrating abstraction and extending abstraction. We also consider many concepts related closely to abstraction such as functions, abstract data types, objects, encapsulation and classes in the view of abstraction. These analysis and consideration will make it possible to explain uniformly various aspects of abstraction which have been treated individually and differently, and to understand the meanings, necessity and importance of abstraction more intensively.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.23-32
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• 2003

Since the data is collected from disparate sources in many actual data mining environments, it is common to have data values in different abstraction levels. This paper shows that such multiple abstraction levels of data can cause undesirable effects in decision tree classification. After explaining that equalizing abstraction levels by force cannot provide satisfactory solutions of this problem, it presents a method to utilize the data as it is. The proposed method accommodates the generalization/specialization relationship between data values in both of the construction and the class assignment phase of decision tree classification. The experimental results show that the proposed method reduces classification error rates significantly when multiple abstraction levels of data are involved.

• Research in Mathematical Education
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• v.13 no.3
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• pp.197-216
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• 2009

The purpose of this study was to investigate middle and high school mathematics teachers' levels and multiple approaches in United States practicing their abstraction levels and, different strategies and method of solutions towards given number theory problems. The mathematics teachers taking part in this study are consisted of 25 members of online graduate and undergraduate course (MAE 5641 and MAE 4813) delivered through Online Learning System called as the Blackboard (http://www.blackboard.com). Data collection methods include journal entries, written solutions to problems, the teachers' reflections on said problems, and post interviews. Data analysis was done based on [Hazzan, O. & Zazkis, R. (2005). Reducing abstraction: The case of school mathematics. Educ. Stud. Math. 58(1), 101-119]. Analysis of students' written solutions revealed that transitions among the solution methods have major effect on abstraction levels. Elevation and reducing abstraction is a dynamic process.

• Journal of The Korean Association of Information Education
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• v.22 no.3
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• pp.375-383
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• 2018

Wing, J. M. emphasized the importance of computational thinking competency to live in the 21st century. In this study, the abstraction of computational thinking is classified into object abstraction, data abstraction, and procedural abstraction through related studies. In addition, abstraction achievement and assessment standards were developed for the abstractable competency assessment. As a result of applying to the school site, the students showed that the object abstraction and the data abstraction competency which are expressed in writing and drawing, they are excellent in solving the problem. However, students hard to write a computer program. The abstractable competency assessment developed in this study will help teach students to teach software education.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.103-116
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• 2003

States explosion due to composition of spaces of data, temporal, and locational values is one of the well-known critical problems which cause difficulty in understanding and analysing real-time systems specified with state-based formal methods. In order to overcome this problem, this paper presents an abstraction method for state minimization based on an abstraction in system specification and an abstraction in system execution. The first is named the syntactic in system specification and an abstraction in system execution. The first is named the syntactic abstraction, through which the patterns of the unconditionally internalized computation and the repetition and selection structures are abstracted. The latter is named the semantic abstraction, through which the patterns of the execution space represented with data. Through the abstractions, the components of a system in specification and execution model is hierarchically organized. The system can be analyzed briefly in the upper level in an skeleton manner with low complexity. The system, however, can be abstraction method for the state minimization and the decrease in analysis complexity through the abstraction with examples.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.125-136
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• 2007

The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.99-117
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• 1999

Since query language is used as a handy tool to obtain information from a database, a more intelligent query answering system is needed to provide user-friendly and fault-tolerant human-machine Interface. Frequently, database users prefer less rigid querying structure, one which allows for vagueness in composing queries, and want the system to understand the intent behind a query. When there is no matching data available, users would rather receive approximate answers than a null information response. This paper presents a knowledge abstraction database that facilitates the development of such a fault-tolerant and intelligent database system. The proposed knowledge abstraction database adepts a multilevel knowledge representation scheme called the knowledge abstraction hierarchy(KAH), extracts semantic data relationships from the underlying database, and provides query transformation mechanisms using query generalization and specialization steps. In cooperation with the underlying database, the knowledge abstraction database accepts vague queries and allows users to pose approximate queries as well as conceptually abstract queries. Specifically. four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual Join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.87-96
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• 2006

Most conventional database systems support specific queries that are concerned only with data that match a query qualification precisely. A cooperative query answering supports query analysis, query relaxation and provides approximate answers as well as exact answers. The key problem in the cooperative answering is how to provide an approximate functionality for alphanumeric as well as categorical queries. In this paper, we propose a metricized knowledge abstraction hierarchy that supports multi-level data abstraction hierarchy and distance metric among data values. In order to facilitate the query relaxation, a knowledge representation framework has been adopted, which accommodates semantic relationships or distance metrics to represent similarities among data values. The numeric domains also compatibly incorporated in the knowledge abstraction hierarchy by calculating the distance between target record and neighbor records.

• ETRI Journal
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• v.46 no.3
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• pp.501-512
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• 2024

With an explosive increase of data produced annually, researchers have been attempting to develop solutions for systems that can effectively handle large amounts of data. Single-operating-system (OS) non-uniform memory access (NUMA) abstraction technology is an important technology that ensures the compatibility of single-node programming interfaces across multiple nodes owing to its higher cost efficiency compared with scale-up systems. However, existing technologies have not been successful in optimizing user performance. In this paper, we introduce a single-OS NUMA abstraction technology that ensures full compatibility with the existing OS while improving the performance at both hypervisor and guest levels. Benchmark results show that the proposed technique can improve performance by up to 4.74× on average in terms of execution time compared with the existing state-of-the-art opensource technology.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.177-184
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• 2009

Environmental monitoring systems are widely developed for analyzing environment and understanding an ecosystem according to the advance of wireless communication and various sensing techniques. To extract useful information, it requires high cost for processing a query, because these systems have to handle huge volume of raw sensor data which is transmitted from a wide area in environmental monitoring applications. Besides, it is also hard to answer an user defined query which requests to check current and near future condition. In this paper, we propose the monitoring system structure for processing a user defined query for environmental monitoring. It also describes the utilization of sensor data filtering and abstraction model. The designed abstraction model which is based on the slope grid in GIS supports fast data access and update. To analyze condition, the extracted data from abstraction model of each sensor type is combined in a query processor. It is useful to provide meaningful information to users.