• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2413-2419
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• 2013

Background: Use of epidermal growth factor receptor inhibitors (EGFR-TKIs ) is now standard for non-small-cell lung cancer (NSCLC). However, the effects of EGFR-TKIs in maintenance therapy for advanced NSCLC patients are still unclear. The preent meta-analysis was performed to examine pooled data of randomized control trials (RCT) where EGFR-TKIs were compared against placebo in maintenance regimens for patients with advanced NCSLC to quantify potential benefits and determine safety. Methods: Several data bases were searched, including PubMed, EMBASE and CENTRAL, and we performed an internet search of conference literature. The endpoints were objective response rates (ORR), progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of the published data, using Comprehensive Meta Analysis software (Version 2.0). with a fixed effects model and an additional random effects model, when applicable. The results of the meta-analysis are expressed as hazard ratios (HRs) or risk ratios (RRs), with their corresponding 95% confidence intervals (95%CIs). Results: The final analysis included six trials, covering 3,758 patients. Compared with placebo, EGFR-TKIs maintenance therapy improved ORR and PFS for patients with advanced NSCLC, the difference being statistically significant (P<0.05), but proved unable to prolong patients' OS. The main adverse reactions were diarrhea and rashes. Conclusion: EGFR-TKIs demonstrated encouraging efficacy, safety and survival when delivered as maintenance therapy for patients with advanced NSCLC after first-line chemotherapy, especially for the patients who had adenocarcinomas, were female, non-smokers and patients with EGFR gene mutations.

• Journal of Korean Neurosurgical Society
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• v.63 no.4
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• pp.455-462
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• 2020

Objective : Recent studies have reported that arachnoid plasty (ARP) using gelatin sponges with fibrin glue reduced the occurrence of chronic subdural hematoma (CSDH) following clipping surgery for unruptured intracranial aneurysm (UIA). This meta-analysis was conducted to collate further evidence for the efficacy of ARP in preventing postoperative CSDH. Methods : Data of patients who underwent clipping surgery were extracted from PubMed, EMBASE, and Cochrane Central Register of Controlled Trials by two independent reviewers. A random effects model was used to investigate the efficacy of ARP by using odd ratios (ORs) and 95% confidence intervals (CIs). A meta-regression analysis for male sex was additionally preformed. Results : Data from six studies with 1715 patients were consecutively included. Meta-analysis revealed that ARP was significantly associated with lower rates of CSDH development after surgical clipping for UIA (ARP group vs. control group : 3.2% vs. 7.2%; OR, 0.40; 95% CI, 0.18-0.93; I²=44.3%; p=0.110). Meta-regression analysis did not highlight any modifying effect of the male sex on postoperative CSDH development (p=0.951). Conclusion : This meta-analysis indicated that ARP reduced the incidence rates of CSDH following clipping surgery for UIA. If feasible, ARP would be implemented as an additional surgical technique to prevent postoperative CSDH development during surgical clipping of UIA.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.533-540
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• 2006

This paper describes the design and implementation of a grid system META (Metacomputing Environment using Test-run of Application) which facilitates the execution of a CFD (Computational Fluid Dynamics) analysis program on distributed environment. The grid system META allows the CFD program developers can access the computing resources distributed over the network just like one computer system. The research issues involved in the grid computing include fault-tolerance, computing resource selection, and user-interface design. In this paper, we exploits an automatic resource selection scheme for executing the parallel SPMD (Single Program Multiple Data) application written in MPI (Message Passing Interface). The proposed resource selection scheme is informed from the network latency time and the elapsed time of the kernel loop attained from test-run. The network latency time highly influences the executional performance when a parallel program is distributed and executed over several systems. The elapsed time of the kernel loop can be used as an estimator of the whole execution time of the CFD Program due to a common characteristic of CFD programs. The kernel loop consumes over 90% of the whole execution time of a CFD program.

• Journal of the Korean Society for information Management
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• v.26 no.1
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• pp.185-214
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• 2009

The purpose of this study is aimed to clarify the usefulness of meta search system using Open API of library online catalog by constructing OPAC-based search system using Open API of library online catalog and meta search system using Open API of library online catalog, and comparing the usability of the two experimental search systems. As for usability, on the whole, it was higher in meta search system using Open API of library online catalog than OPAC-based search system using Open API of library online catalog, and there was statistically significant difference. Therefore, if libraries share and use enriched content which is provided through Open API for book search, which is opened by Internet bookstores, search engines and Web portals, it is expected that it will be helpful in enhancing bibliographic data, expanding subject access point, empowering subject search ability, extending meta search service, improving book availability, and reducing catalog cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.196-203
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• 2022

Purpose: This study aimed to evaluate the accuracy and clinical usability of an identification model using deep learning for 79 dental implant types. Materials and Methods: A total of 45396 implant fixture images were collected through panoramic radiographs of patients who received implant treatment from 2001 to 2020 at 30 dental clinics. The collected implant images were 79 types from 18 manufacturers. EfficientNet and Meta Pseudo Labels algorithms were used. For EfficientNet, EfficientNet-B0 and EfficientNet-B4 were used as submodels. For Meta Pseudo Labels, two models were applied according to the widen factor. Top 1 accuracy was measured for EfficientNet and top 1 and top 5 accuracy for Meta Pseudo Labels were measured. Results: EfficientNet-B0 and EfficientNet-B4 showed top 1 accuracy of 89.4. Meta Pseudo Labels 1 showed top 1 accuracy of 87.96, and Meta pseudo labels 2 with increased widen factor showed 88.35. In Top5 Accuracy, the score of Meta Pseudo Labels 1 was 97.90, which was 0.11% higher than 97.79 of Meta Pseudo Labels 2. Conclusion: All four deep learning algorithms used for implant identification in this study showed close to 90% accuracy. In order to increase the clinical applicability of deep learning for implant identification, it will be necessary to collect a wider amount of data and develop a fine-tuned algorithm for implant identification.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.533-540
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• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.436-450
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• 2005

In this paper we propose an integrated media format for a photo album including media resources and corresponding meta-data The main purpose of the integrated media is to be more reusable meta-data and to facilitate constructing a photo album from a large number of photo images as well. The proposed media format is based on MAF(multimedia Application Format) which is recently going on progress in MPEG standards. In this paper, we propose the integrated media consisting of JPEG data and content-based meta-data based on MPEG-7 MDS. We verified the usefulness of the proposed media through experiments with implementation of encoder and photo MAF player for the MAF-based media format.

• Journal of Digital Convergence
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• v.6 no.2
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• pp.55-64
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• 2008

The Internet possesses not only features of mass media but also features of word of mouth communication. Communication channel is considered as one of most important variables in diffusion process. In this paper, we examined functionality of technology diffusion on the Internet through the use of meta tags. We have measured the coefficients of the Bass diffusion model which has been well-established in new product diffusion. This research shows that the Bass model is appropriate for describing technology diffusion on the Internet. The external influence as represented by the coefficient of innovation was found to be much smaller while the internal influence dominates in all meta tag diffusion. In meta tag diffusion, the internal influence as represented by the coefficient of imitation was increased at least twice bigger than that of consumer durables and information technology. Collecting necessary data in social sciences research can be a burden. This research shows that it can be alleviated through the use of software agents over the Internet. The research made use of software agents for collecting longitudinal data from publicly accessible archive such as Archive.org.

• Journal of Korean Library and Information Science Society
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• v.33 no.2
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• pp.109-137
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• 2002

A literature analysis for the planning and realization of meta database system was carried out to establish the ocean electronic resources, the first in Korea. The study targeted from web resources and to oceanographic survey data. The focus of the analysis lies in the providing practical information retrieval service for ocean electronic resources based on the framework of effective Dublin Core metadata with network resources description. The analyses included ocean electronic resources, metadata descriptive elements, metadata classification, system organization and retrieval for planning and implementation of meta database system.