• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.21-30
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• 2014

Ordinary survival analysis cannot be applied when a significant fraction of patients may be cured. A cure rate model is the combination of cure fraction and survival model and can be applied to several types of cancer. In this article, the cure rate model is considered in the interval censored data with a cluster effect. A shared frailty model is introduced to characterize the cluster effect and an EM algorithm is used to estimate parameters. A simulation study is done to evaluate the performance of estimates. The proposed approach is applied to the smoking cessation study in which the event of interest is a smoking relapse. Several covariates (including intensive care) are evaluated to be effective for both the occurrence of relapse and the smoke quitting duration.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.583-591
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• 2020

Employability has recently become the first target of the national higher education. Its model has been updated to catch the new trend of Industry 4.0. This paper aims at analyzing and ranking the determinants of undergraduate employability, focusing on business and economics majors in Ho Chi Minh City, Vietnam. In-depth interviews with content analysis have been primarily conducted to reach an agreement on a key group of factors: human capital, social capital, and identity. The Stochastic Fractal Search Algorithm (SFSA) is then applied to rank the sub-factors. Human capital is composed of three major elements: attitude, skill, and knowledge. Social capital is approached at both structural and cognitive aspects with three typical types: bonding, bridging, and linking. The analysis has confirmed the change of priority in employability determinants. Human capital is still a driver but the priority of attitude has been confirmed in the contemporary context. Then, social capital with the important order of linking, bridging, and bonding is emphasized. Skill, knowledge, and identity share the least weight in the model. It is noted that identity is newly proposed in the model but a certain role has been found. The findings are crucial for education strategies to enhance university graduate employability.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.487-492
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• 2008

Most Web search engines use ranking methods that take both the relevancy and the importance of documents into consideration. The importance of a document denotes the degree of usefulness of the document to general users. One of the most successful methods for estimating the importance of a document has been Page-Rank algorithm which uses the hyperlink structure of the Web for the estimation. In this paper, we propose a new importance estimation algorithm for the blog environment. The proposed method, first, calculates the importance of each document using user's bookmark and click count. Then, the Guru point of a blogger is computed as the sum of all importance points of documents which he/she wrote. Finally, the guru points are reflected in document ranking again. Our experiments show that the proposed method has higher correlation coefficient than the traditional methods with respect to correct answers.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.659-668
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• 2010

Collaborative filtering systems grasp behaviors for a new user and need new information for the user in order to recommend interesting items to the user. For the purpose of acquiring the information the collaborative filtering systems learn behaviors for users based on the previous data and can obtain new information from the results. In this paper, we propose an inductive inference method to obtain new information for users and rank items by using the new information in the proposed method. The proposed method clusters users into groups by learning users through NMF among inductive machine learning methods and selects the group features from the groups by using chi-square. Then, the method classifies a new user into a group by using the bayesian probability model as one of inductive inference methods based on the rating values for the new user and the features of groups. Finally, the method decides the ranks of items by applying the Rocchio algorithm to items with the missing values.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.147-152
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• 2020

The baseball elimination problem(BEP) is eliminates teams that finishes the season in the early stage without play the remaining games because of the team never most wins even though all wins of remaining games. This problem solved by max-flow/min-cut theorem. But the max-flow/min-cut method has a shortcoming of iterative constructs the network for all of team and decides the min-cut for each network. This paper suggests ascending sort in wins game plus remaining games for each team, then the candidate eliminating team set K with lower 1/2 rank and most easy, simple, and fast computes the existence or not of subset R that a team elimination decision. As a result of various experimental data, this algorithm can be find all of elimination teams for whole data with fast and correct.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.129-136
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• 2006

Information Retrieval System aims towards providing fast and accurate information to users. However, current search systems are based on plain svntactic analysis which makes it difficult for the user to find the exact required information. This paper proposes the SW-IRS (Semantic Web-based Information Retrieval System) using an Ontology Server. The proposed system is purposed to maximize efficiency and accuracy of information retrieval of unstructured and semi-structured documents by using an agent-based automatic classification technology and semantic web based information retrieval methods. For interoperability and easy integration, RDF based repository system is supported, and the newly developed ranking algorithm was applied to rank search results and provide more accurate and reliable information. Finally, a new ranking algorithm is suggested to be used to evaluate performance and verify the efficiency and accuracy of the proposed retrieval system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.2 s.54
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• pp.129-136
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• 2009

The paper presents an algorithm of selecting optimal locations for measuring displacements(OLD) to adjust cable tension forces during the construction of cable-stayed bridges. The rank for optimal locations can be determined from the effective independence distribution vectors(EIDV) that are computed from the Fisher Information Matrices(FIM) formulated with the displacement sensitivities. To examine the efficiency and reliability of the proposed algorithm for determining OLD, a simulation study on a cable-stayed bridge has been carried out. The results using FIM formulated with displacements are compared with those using FIM with displacement sensitivities through the simulation study. The effects of measurement noise and error in cable length on the adjustment of cable tension forces are evaluated statistically by applying the Monte Carlo scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.520-525
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• 1997

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.23-33
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• 2008

In this paper, we propose a image retrieval algorithm using spatial information and color changing ratio. The proposed method extracts color regions from images by threshold $\tau$ to extract spatial information. During this process, we count extracted color regions and color changing, and these values are used to obtain color changing ratio. Image similarity between images is measured by extracted spatial information. Additively, color changing ratio makes images that has similar color changing ratio to be more higher retrieval rank. In our experiment using various natural images, we demonstrate a proposed method shows better performance than other common retrieval methods using color informations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5563-5582
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• 2016

Parametric min-cuts is an object proposal algorithm, which can be used for accurate image segmentation. In parametric min-cuts, foreground seeds generation plays an important role since the number and quality of foreground seeds have great effect on its efficiency and accuracy. To improve the performance of parametric min-cuts, this paper proposes a new framework for foreground seeds generation. First, to increase the odds of finding objects, saliency detection at multiple scales is used to generate a large set of diverse candidate seeds. Second, to further select good-quality seeds, a two-stage cascaded ranking classifier is used to filter and rank the candidates based on their appearance features. Experimental results show that parametric min-cuts using our seeding strategy can obtain a relative small pool of proposals with high accuracy.