• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.377-399
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• 2015

Objective: The aim of this study is to understand and identify the critical issues in vision research area using content analysis and network analysis. Background: Vision, the most influential factor in information processing, has been studied in a wide range of area. As studies on vision are dispersed across a broad area of research and the number of published researches is ever increasing, a bibliometric analysis towards literature would assist researchers in understanding and identifying critical issues in their research. Method: In this study, content and network analysis were applied on the meta-data of literatures collected using three search keywords: 'visual search', 'eye movement', and 'eye tracking'. Results: Content analysis focuses on extracting meaningful information from the text, deducting seven categories of research area; 'stimuli and task', 'condition', 'measures', 'participants', 'eye movement behavior', 'biological system', and 'cognitive process'. Network analysis extracts relational aspect of research areas, presenting characteristics of sub-groups identified by community detection algorithm. Conclusion: Using these methods, studies on vision were quantitatively analyzed and the results helped understand the overall relation between concepts and keywords. Application: The results of this study suggests that the use of content and network analysis helps identifying not only trends of specific research areas but also the relational aspects of each research issue while minimizing researchers' bias. Moreover, the investigated structural relationship would help identify the interrelated subjects from a macroscopic view.

• Clinical Endoscopy
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• v.57 no.3
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• pp.317-328
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• 2024

Background/Aims: In this meta-analysis, we studied the safety and efficacy of endoscopic submucosal dissection (ESD) for colorectal dysplasia in patients with inflammatory bowel disease (IBD). Methods: Multiple databases were searched, and studies were retrieved based on pre-specified criteria until October 2022. The outcomes assessed were resection rates, procedural complications, local recurrence, metachronous tumors, and the need for surgery after ESD in IBD. Standard meta-analysis methods were followed using the random-effects model, and I²% was used to assess heterogeneity. Results: Twelve studies comprising 291 dysplastic lesions in 274 patients were included with a median follow-up of 25 months. The pooled en-bloc resection, R0 resection, and curative resection rates were 92.5% (95% confidence interval [CI], 87.9%-95.4%; I²=0%), 81.5% (95% CI, 72.5%-88%; I²=43%), and 48.9% (95% CI, 32.1%-65.9%; I²=87%), respectively. The local recurrence rate was 3.9% (95% CI, 2%-7.5%; I²=0%). The pooled rates of bleeding and perforation were 7.7% (95% CI, 4.5%-13%; I²=10%) and 5.3% (95% CI, 3.1%-8.9%; I²=0%), respectively. The rates of metachronous recurrence and additional surgery following ESD were 10% (95% CI, 5.2%-18.2%; I²=55%) and 13% (95% CI, 8.5%-19.3%; I²=54%), respectively. Conclusions: ESD is safe and effective for the resection of dysplastic lesions in IBD with an excellent pooled rate of en-bloc and R0 resection.

• The korean journal of orthodontics
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• v.52 no.5
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• pp.313-323
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• 2022

Objective: This study aimed to estimate the clinical effects of different types of bone-anchored maxillary protraction devices by using a network meta-analysis. Methods: We searched seven databases for randomized and controlled clinical trials that compared bone-anchored maxillary protraction with tooth-anchored maxillary protraction interventions or untreated groups up to May 2021. After literature selection, data extraction, and quality assessment, we calculated the mean differences, 95% confidence intervals, and surface under the cumulative ranking scores of eleven indicators. Statistical analysis was performed using R statistical software with the GeMTC package based on the Bayesian framework. Results: Six interventions and 667 patients were involved in 18 studies. In comparison with the tooth-anchored groups, the bone-anchored groups showed significantly more increases in Sella-Nasion-Subspinale (°), Subspinale-Nasion-Supramentale(°) and significantly fewer increases in mandibular plane angle and the labial proclination angle of upper incisors. In comparison with the control group, Sella-Nasion-Supramentale(°) decreased without any statistical significance in all treated groups. IMPA (angle of lower incisors and mandibular plane) decreased in groups with facemasks and increased in other groups. Conclusions: Bone-anchored maxillary protraction can promote greater maxillary forward movement and correct the Class III intermaxillary relationship better, in addition to showing less clockwise rotation of mandible and labial proclination of upper incisors. However, strengthening anchorage could not inhibit mandibular growth better and the lingual inclination of lower incisors caused by the treatment is related to the use of a facemask.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.121-128
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• 2019

An Internet of Things(IoT) technology which provides intelligent services by combining context-awareness based intelligences, inter-communication is made of between things and things or between things and person through the network connected with intelligent things is spreading rapidly. Especially as this technology is converged into smart device, mobile, cloud, big data technologies, it is applied into various domains. Therefore, this is different from existing Web or Mobile Application. New types of IoT applications are emerging by adapting IoT into Web or mobile. Because IoT application is not only focused on software but also considering hardware or things aspect, there are limitations existing development process. Existing development processes don't consider analysis and design techniques considering both hardware and things. We propose not only a meta-model for development process which can support IoT application's development but also meta-models for main activities in this paper. Especially we define modeling elements by using UML's extension mechanisms, provide development process, and suggest design techniques how to apply those elements into IoT application's modeling phase. Because there are many types of IoT application's type, we propose an Android and Arduino-based on IoT application as a case study. We expect that proposed technique can be applied into many of various IoT application development and design with a form of flexible and extensible as well as main functionalities or elements are more concretely described. As a result, it brings IoT application's flexibility and the effect of quality improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• STI Policy Review
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• v.6 no.1
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• pp.24-35
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• 2015

This research constructs a data set regarding competition policy through a comprehensive review of previous studies, and performs a meta-analysis to quantitatively assess the price effects of deregulation. A structural econometric model is used to eliminate possible biases from heterogeneity of the studies,such as in publication types and measurement methods. Four types of regulations that deter competition are characterized and three groups of industries are made for drawing practical implications. We fnd that deregulation to promote competition reduces prices by 0.23% and that these estimated price effects are more stable when we control for the publication types and measurement ways. Easing regulations that restrict consumers' choice is shown to be most effcient in promoting competition, lowering prices by 0.7%. This is followed by eliminating the limitation in the number of frms in the industry, with 0.2% price reduction. Overall, the network and service industries are shown to be more responsive to deregulation than the R&D industry. These results could shed light on policy implementation when a pro-competition policy is called for due to restrictive regulations in the corresponding industries.

• Structural Engineering and Mechanics
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• v.44 no.3
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• pp.379-403
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• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• Korean Journal of Clinical Pharmacy
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• v.30 no.1
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• pp.1-10
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• 2020

Objective: The aim of the study was to perform a meta-analysis of randomized clinical trials to compare the clinical efficacy and safety between combination of cyclin-dependent kinase (CDK) 4/6 inhibitors with aromatase inhibitors (AIs) and AIs alone in patients with hormone receptor+/human epidermal growth factor receptor type2-(HR+/HER2-) advanced breast cancer. Methods: Published clinical studies were identified through electronic database searches until February 2019. Literature qualities were assessed by the Scottish Intercollegiate Guidelines Network Checklist. Key endpoints of efficacy were progression-free survival (PFS), objective response rate (ORR), and clinical benefit (CB). Endpoints of safety were adverse events (AEs) (neutropenia, leukopenia, any grade 3/4 AEs, and serious AEs) and on-treatment death. Meta-analysis was performed using the RevMan 5.3 software. Results: The selected five studies were evaluated as "good" in quality assessment. Compared to AIs alone, the combination therapy significantly improved PFS (pooled hazard ratio=0.55; 95% confidence interval (CI) 0.49-0.62), ORR (odds ratio=1.78; 95% CI=1.49-2.13), and CB (odds ratio=1.86; 95% CI=1.51-2.28). The prevalence of AEs was significantly higher in the combination group than in the AIs alone group. On-treatment death was greater in the combination group than in the AIs alone group, although insignificant. Conclusion: The combination therapy of CDK4/6 inhibitors with AIs was more effective for the treatment of HR+/HER2- advanced breast cancer, but less safe than AIs alone. The combination therapy should be effectively managed through patient monitoring, and further studies are needed to reduce AEs in the combination therapy of CDK4/6 inhibitors with AIs.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.520-530
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• 2021

This study conducted a meta-analysis on the variables related with case management performance in Korea. In order to do a meta-analysis, a total of 27 journals, theses and dissertations published between 1998 and 2020 were reviewed systematically. Through this process, this study calculated average effect size of each variable and explored moderator variables. This study results were as follows. First, this study identified a total of 14 individual, enviroment of institution, population variables related with case management performance. Second, the results indicated that case management performance variables which showed large effect sizes included professional capability, supervision, network, case management significance recognition, manual, agency support. Third, variables with medium effect sizes included self-efficacy, case management education, autonomy, motivation, number of conference and variables with small effect sizes included work experience, academic ability, age. Fourth, Moderator effects were identified in the field, target, publication of case management. Finally, the implications of the study findings were discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.767-772
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• 2018

Recently, some meta-heuristic algorithms, such as GA(Genetic Algorithm) and GP(Genetic Programming), have been used to optimize CNN(Convolutional Neural Network). The CNN, which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, the recent attempts to automatically construct CNN architectures are investigated and analyzed. First, two GA based methods are summarized. One is the optimization of CNN structures with the number and size of filters, connection between consecutive layers, and activation functions of each layer. The other is an new encoding method to represent complex convolutional layers in a fixed-length binary string, Second, CGP(Cartesian Genetic Programming) based method is surveyed for CNN structure optimization with highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The comparison for three approaches is analysed and the outlook for the potential next steps is suggested.