• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.247-250
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• 2003

Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2482-2488
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• 2014

This paper proposes that a user account of the MS-SQL is checked whether expirated or not in C++ program environment. Vulnerability checking module decides security weakness for password change time or user configuration time. The proposed module prevents and protects a user account from a malicious user account. Recently, Information Assets becomes more important. If the loss of database information it would make large damage in our life. This paper develops user account checking module, which checks whether user password have not been changed for a long time or whether the user account expirated in the MS-SQL Database. By checking security vulnerability using this feature, a malicious user cannot access the Database.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3456-3468
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• 1999

Most of previous parallel join algorithms assume a database partition system(DPS), where each database partition is owned by a single processing node. While the DPS is novel in the sense that it can interconnect a large number of nodes and support a geographically distributed environment, it may suffer from poor facility for load balancing and system availability compared to the database sharing system(DSS). In this paper, we propose a dynamic load balancing strategy by exploiting the characteristics of the DSS, and then extend the conventional hash join algorithms to the DSS by using the dynamic load balancing strategy. With simulation studies under a wide variety of system configurations and database workloads, we analyze the effects of the dynamic load balancing strategy and differences in the performances of hash join algorithms in the DSS.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.62-65
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• 2010

Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.1999-2004
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• 2008

While a lot of comparisons of DBMS performance for processing large scale database are given as results of bench-mark tests, there are few comparisons of DBMS performance for processing small scale database. Therefore, in this study, we compared and analyzed on the performance of commercial DBMS and public DBMS for small scale database. Analysis results show that while Oracle has low performance on the operations of update and insert due to the overhead of rollback for data safely, MySQL and MS-SOL have good performance without additional overhead.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.317-327
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• 2024

Along with the rapid development of the database technology, as well as the widespread application of the database management systems are more and more large. Now the data mining technology has already been applied in scientific research, financial investment, market marketing, insurance and medical health and so on, and obtains widespread application. We discuss data mining technology and analyze the questions of it. Therefore, the research in a new data mining method has important significance. Some literatures did not consider the differences between attributes, leading to redundancy when constructing concept lattices. The paper proposes a new method of uncertain data mining based on the concept lattice of connotation difference degree (c_diff). The method defines the two rules. The construction of a concept lattice can be accelerated by excluding attributes with poor discriminative power from the process. There is also a new technique of calculating c_diff, which does not scan the full database on each layer, therefore reducing the number of database scans. The experimental outcomes present that the proposed method can save considerable time and improve the accuracy of the data mining compared with U-Apriori algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4835-4855
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• 2015

TV white space (TVWS) is showing promise to become the first widespread practical application of cognitive technology. In fact, regulators worldwide are beginning to allow access to the TV band for secondary users, on the provision that they access the geolocation database. Device-to-device (D2D) can improve the spectrum efficiency, but large-scale D2D communications that underlie TVWS may generate undesirable interference to TV receivers and cause severe mutual interference. In this paper, we use an established geolocation database to investigate the power allocation problem, in order to maximize the total sum throughput of D2D links in TVWS while guaranteeing the quality-of-service (QoS) requirement for both D2D links and TV receivers. Firstly, we formulate an optimization problem based on the system model, which is nonconvex and intractable. Secondly, we use an effective approach to convert the original problem into a series of convex problems and we solve these problems using interior point methods that have polynomial computational complexity. Additionally, we propose an iterative algorithm based on the barrier method to locate the optimal solution. Simulation results show that the proposed algorithm has strong performance with high approximation accuracy for both small and large dimensional problems, and it is superior to both the active set algorithm and genetic algorithm.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.673-673
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• 2015

Earthwork is an operation that provides space for structures, and it takes up a large portion of the construction costs in a construction project. In large-scale earthwork, numerous types of construction equipment are used in the operation. The types of equipment should be selected based on the field conditions and the construction methods. These construction vehicles are constantly changing positions during the earthwork operation. Therefore, the equipment operators require effective communication to ensure the efficiency of the earthwork operation. All equipment operators should exchange information with the other equipment operators. Information should be exchanged continuously to support decision making and increase productivity during the earthwork operation at the construction site. This paper investigates the attributes required for an information interface between construction vehicles during an earthwork operation. This paper 1) discusses the importance of an information interface for construction vehicles in order to increase productivity during an earthwork operation, 2) analyses the types of attributes that need to be communicated between construction vehicles, and 3) provides a database that has been built for attribute control. The database built for the information interface between construction vehicles will enhance communication between vehicle operators. Table I shows the typical attributes that should be shared between the excavator operator and the dump truck operator. This information needs to be shared among the operators, as it helps them to plan the earthwork operation in a more efficient manner. A database has been developed to store this information in an entity relation diagram. A user-interface display environment is also developed to provide this information to the operators in the construction vehicles. The proposed interface can help exchange information effectively and facilitate a common understanding during the earthwork operation. For example, the vehicle operators will be aware of the planned volume, excavated volume, transportation time, and transportation numbers. As a part of this study, mobile devices, such as mobile phones and google glasses, will be used as hands-on communication tools.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.16-16
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• 2018

Flora investigations have been conducted by many researchers for a long time in Korea. Even though large amount of investigation data has been accumulated, there is no accurate statistics or database because most of data were published in a printed form. We developed a web-based database of flora investigation, named as the Integrated Korean Flora Database (http://www.floradb.net/) to understand distribution patterns and habitats of plants in Korea. Till now, 480 published paper, 356 thesis, 76 reports and books, and 8 unpublished papers written in between 1962 and 2017 were collected and their species lists from 280 papers were parsed into the database. From 124,105 records, 3,100 species belonging to 206 families and 965 genera were identified via comparing with two major Korean plant species lists. 55 endangered species, 159 endemic species, and 367 rare species were identified. The most frequently surveyed species were Commelina communis in herbaceous and Rosa multiflora in woody plants. Microclimate data provided by Korea Meteorological Administration were also integrated and analyzed to assign cold hardness zones for each species. By comparing minimum temperature (<2%) acquired from automated weather stations (AWS) near by plant species, 6a to 10b zones (7b is the most frequent zone) were identified. Integrated Korean Flora Database will be a fundamental platform of korea flora investigation as well as a new standard for classifying distribution of plants based on accurate microclimate data. Moreover, it can also provide evidences of investigated plant species, such as specimen and/or pictures with connecting to the InfoBoss Cyber Herbarium (http://herbarium.infoboss. co.kr/) and Biodiversity Observation Datbase (BODB; http://www.biodiversitydb.org/).

• Animal cells and systems
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• v.16 no.1
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• pp.11-19
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• 2012

A major concern regarding the collection and storage of biodiversity information is the inefficiency of conventional taxonomic approaches in dealing with a large number of species. This inefficiency has increased the demand for automated, rapid, and reliable molecular identification systems and large-scale biological databases. DNA-based taxonomic approaches are now arguably a necessity in biodiversity studies. In particular, DNA barcoding using short DNA sequences provides an effective molecular tool for species identification. We constructed a large-scale database system that holds a collection of 5531 barcode sequences from 2429 Korean species. The Korea Barcode of Life database (KBOL, http://koreabarcode.org) is a web-based database system that is used for compiling a high volume of DNA barcode data and identifying unknown biological specimens. With the KBOL system, users can not only link DNA barcodes and biological information but can also undertake conservation activities, including environmental management, monitoring, and detecting significant organisms.