• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.61-70
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• 2014

A randomized block design is a method to apply a treatment into the experimental unit of each block after dividing into several blocks with a binded homogeneous experimental unit. Jonckheere (1964) and Terpstra (1952), Page (1963), Hollander (1967) proposed various methods of ordered alternative in randomized block design. Especially, Page (1963) test is a weighted combination of within block rank sums for ordered alternatives. In this paper, we suggest a new nonparametric method expanding the Page test for an ordered alternative. A Monte Carlo simulation study is also adapted to compare the power of the proposed methods with previous methods.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.813-821
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• 2012

Environmental and public health concern for the emission of air pollutants from burn-up process in waste incineration plants located in the vicinity of living environment was increased during the past decade. The purpose of this study was to suggest of the simple and rapid method of priority setting model for the decision of full-scale public health assessment. This method was consists of total 5-step. Step 1 was "secure the satellite map" and we can use the satellite map which serves from the website such as NAVER Co. Step 2 was "drawing mesh on the map" for catch the point of occupation of environmental sensitivity facilities, and step 3 was "identification and sorting of the facilities", Step 4 was "setting of weight" using the "weighted linear combination (WLC) method". Finally, all facility was sorted by score. As a result, we can set a priority of 145 facilities based on 177 facilities which managed in local government. Facilities in Seoul metropolitan area was high rank in priority list. On the other side, Facilities located at the country or rural area was low rank because of low occupation of the house and the environmental sensitivity facilities such as kindergarten, elementary school, and hospital. In this study, we suggested simple and rapid method that using for screening procedure of public health assessment.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.117-123
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• 2017

The personalized search algorithm is a search system that analyzes the user's IP, cookies, log data, and search history to recommend the desired information. As a result, users are isolated in the information frame recommended by the algorithm. This is called 'Filter bubble' phenomenon. Most of the personalized data can be deleted or changed by the user, but data stored in the service provider's server is difficult to access. This study suggests a way to neutralize personalization by keeping on sending random query words. This is to confuse the data accumulated in the server while performing search activities with words that are not related to the user. We have analyzed the rank change of the URL while conducting the search activity with 500 random query words once using the personalized account as the experimental group. To prove the effect, we set up a new account and set it as a control. We then searched the same set of queries with these two accounts, stored the URL data, and scored the rank variation. The URLs ranked on the upper page are weighted more than the lower-ranked URLs. At the beginning of the experiment, the difference between the scores of the two accounts was insignificant. As experiments continue, the number of random query words accumulated in the server increases and results show meaningful difference.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.421-433
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• 2015

Recently, there have been fast-growing social network services based on the Internet environment and web technology development, the prevalence of smartphones, etc. Social networks also allow the users to convey the information and news so that they have a great influence on the public opinion formed by social interaction among users as well as the spread of information. On the other hand, these social networks also serve as perfect environments for rampant malware. Malware is rapidly being spread because relationships are formed on trust among the users. In this paper, an effective patch strategy is proposed to deal with malicious worms based on social networks. A graph is formed to analyze the structure of a social network, and subgroups are formed in the graph for the distributed patch strategy. The weighted directions and activities between the nodes are taken into account to select reliable key nodes from the generated subgroups, and the Incremental PageRanking algorithm reflecting dynamic social network features (addition/deletion of users and links) is used for deriving the high influential key nodes. With the patch based on the derived key nodes, the proposed method can prevent worms from spreading over social networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.639-644
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• 2002

Nonlinear filters which are utilized rank-order information and temporal-order information, have many proposed, in order to restore nonstationary signals which are corrupted by additive noise. In this paper, we propose a data-dependent LWOS filter whose coefficients change based on local statistics. LWOS(Linear Combination of Weighted Order Statistics) filters［1］which also utilized two informations, and have properties of efficient impulsive and nonimpulsive noise attenuation and sufficiently details and edges preservation. DD-LWOS filters can remove non-impulsive oises while preserving signal details. DD-LWOS2 filter gets more better performance than DD-LWOS filter when input image corrupted by additive noise which includes Impulsive noise components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3873-3887
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• 2018

In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1059-1068
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• 2022

Recently, research using image-based deep learning is being conducted to determine similar fonts or recommend fonts. In order to increase the accuracy in judging the similarity of Hangul fonts, a previous study was conducted to calculate the similarity according to the combination of stroke elements. In this study, we tried to solve this problem by designing an integrated model that reflects the weights for each stroke element. By comparing the results of the user's font similarity calculation conducted in the previous study and the weighted model, it was confirmed that there was no difference in the ranking of the influence of the stroke elements. However, as a result of comparison by letter sizes, it was confirmed that there was a difference in the ranking of the influence of stroke elements. Accordingly, we proposed a weighted model set separately for each font size.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.53-62
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• 1994

Complex decision-making problems are often characterized by multicriteria phenomena and fuzziness inherent in the structure of information and therefore suitable scientific solution methods. Especially, when similar dependent criteria are introduced, the problems become more complex. This paper presents a fuzzy intersectional dependence relation model for this kind of multicriteria decision-making problems. The model we propose is based on the fuzzy relation from fuzzy systems theory. In ths case of introducing similar dependent criteria, the rank reversal by distortion of weights is hard to occur by our proposed method. A numerical example is presented to illustrate the use of the model.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.169-178
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• 1994

Nonparametric tests for comparing two treatments when data are subject to unequal patterns of censorship are discussed. Best precedence test proposed by Slud can be viewed as a nice alternative test comparing with weighted log-rank tests, not to mention the advantage of short experimental period. This research revises some missing parts of Slud's test and examines the asymptotic power of it under the nonproportional hazard alternatives through the simulation. The simulation studies show best precedence test has reasonable power in the sense of robustness under nonproportional hazard alternatives and could be recommended at such situation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.338-341
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• 2005

In this paper, we present analytic forms of the ordered weighted averaging (OWA) operator weighting functions, each of which has properties of rank-based weights and a constant level of orness, irrespective of the number of objectives considered. These analytic forms provide significant advantages for generating OWA weights over previously reported methods. First, OWA weights can be efficiently generated by use of proposed weighting functions without solving a complicated mathematical program. Moreover, convex combinations of these specific OWA operators can be used to generate OWA operators with any predefined values of orness once specific values of orness are α priori stated by decision maker. Those weights have a property of constant level of orness as well. Finally, OWA weights generated at a predefined value of orness make almost no numerical difference with maximum entropy OWA weights in terms of dispersion.