• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.89-94
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• 2019

This study will examine the awareness of students in radiology who have applied the reorganization of the safety management system of frequent visitors according to the amendment of the Nuclear Safety Act. A survey was conducted on 175 students from the Department of Radiology at K University. 98.1% of the students in the second grade, 90.3% in the third grade, and 97.7% in the fourth grade were recognized as need to be classified as person with frequent access by the Nuclear Safety Act. Limiting the operation of radiation equipment in radiography practice is a regulation that violates students' right to learn, and it is necessary to enact an exception rule for learning so that the right to study is not violated.

• ETRI Journal
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• v.30 no.3
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• pp.421-431
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• 2008

In this paper, we offer a new technique to discover frequent spatiotemporal patterns from a moving object database. Though the search space for spatiotemporal knowledge is extremely challenging, imposing spatial and timing constraints on moving sequences makes the computation feasible. The proposed technique includes two algorithms, AllMOP and MaxMOP, to find all frequent patterns and maximal patterns, respectively. In addition, to support the service provider in sending information to a user in a push-driven manner, we propose a rule-based location prediction technique to predict the future location of the user. The idea is to employ the algorithm AllMOP to discover the frequent movement patterns in the user's historical movements, from which frequent movement rules are generated. These rules are then used to estimate the future location of the user. The performance is assessed with respect to precision and recall. The proposed techniques could be quite efficiently applied in a location-based service (LBS) system in which diverse types of data are integrated to support a variety of LBSs.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.229-236
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• 2017

An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.23-30
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• 2015

As BigData is issued, many applications that operate based on the results of data analysis have been developed, typically applications are products recommend service of e-commerce application service system, search service on the search engine service and friend list recommend system of social network service. In this paper, we suggests a decision frequent pattern tree that is combined the origin frequent pattern tree that is mining similar pattern to appear in the data set of the existing data mining techniques and decision tree based on the theory of computer science. The decision frequent pattern tree algorithm improves about problem of frequent pattern tree that have to make some a lot's pattern so it is to hard to analyze about data. We also proposes to model for a Mapredue framework that is a programming model to help to operate in distributed environment.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.117-129
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• 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average- and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed- and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.2
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• pp.173-181
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• 2014

In this paper, using the definition and properties of frequency measurement, we describe the properties of solutions of a difference equation as the initial value belongs to different intervals of the whole domain. We get the main result that if the initial value belongs to [-1, 1] which is different from $\frac{-1{\pm}\sqrt{5}}{2}$, then the solution defined by initial value have two frequent limits 0 and 1 of the same degree 0.5.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.647-653
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• 2022

Data mining is a technique that explores knowledge such as relationships and patterns between data by exploring and analyzing data. Data that occurs in the real world includes a temporal attribute. Temporal data mining research to find useful knowledge from data with temporal properties can be effectively utilized for predictive judgment that can predict the future. In this paper, we propose an algorithm using time-unit grouping to classify the database into regular time period units and discover frequent pattern itemsets in time units. The proposed algorithm organizes the transaction and items included in the time unit into a matrix, and discovers frequent items in the time unit through grouping. In the experimental results for the performance evaluation, it was found that the execution time was 1.2 times that of the existing algorithm, but more than twice the frequent pattern itemsets were discovered.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.22-32
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• 2018

In VANET, frequent movement of nodes causes dynamic changes of the network topology. Therefore the routing protocol, which is stable to effectively respond the changes of the network topology, is required. Moreover, the existing cluster-based routing protocol, that is the hybrid approach, has routing delay due to the frequent re-electing of the cluster header. In addition, the routing table of CBRP has only one hop distant neighbor nodes. PCBRP (Paired CBRP), proposed in this paper, ties two clusters in one pair of clusters to make longer radius. Then the pair of the cluster headers manages and operates corresponding member nodes. In the current CBRP, when the cluster header leaves the cluster the delay, due to the re-electing a header, should be occurred. However, in PCBRP, another cluster header of the paired cluster takes the role instead of the left cluster header. This means that this method reduces the routing delay. Concurrently, PCBRP reduces the delay when routing nodes in the paired cluster internally. Therefore PCBRP shows improved total delay of the network and improved performance due to the reduced routing overhead.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.209-215
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• 2004

Together with the requirements of tunnels, its construction methods and technologies have been pretty much developed, but frequent accidents happened under the constructions are just one of important problems which should be improved. To detect the potential hazardous factors in or ahead of time, speedy and accurate observation are absolutely required, but currently surveying method using tapes, level and total station, has been generally taken in measuring of tunnel convergence and crown. The purpose of this study is, as using of industrial photogrammetry system which is supplying more accuracy and speedy in the measure of tunnel convergence and crown. From the result of this study, we have got up to 1/20,000 accuracy and totally 6 minutes, from picturing 5 sections by one person to data edition, has been taken except setting targets.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.57-65
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• 2021

This paper explains a DMFC-Lithium Battery hybrid system applied to a forklift. A conventional Lead Acid battery forklift has several problems: long charging times, short operation times, and frequent battery replacements. As a result, hydrogen-powered forklifts are replacing Lead acid battery-powered forklifts due to their shorter refueling time and longer operation times. However, in doing so, we are confronted with the problem of a high hydrogen refueling infrastructure. A Direct Methanol Fuel Cell (DMFC), on the other hand, is an eco-friendly generator that directly converts the chemical energy of methanol into electricity. In general, DMFC is regarded as a small power generator under kW power. In this paper, a DMFC-Battery hybrid system is applied to a 1.5 ton forklift by increasing the power output of the DMFC stack and utilizing the high charge-discharge characteristics of a lithium battery.