• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

• Computers and Concrete
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• v.24 no.6
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• pp.561-570
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• 2019

Understanding the realistic behavior of concrete up to failure under different loading conditions within the framework of damage mechanics and plasticity would lead to an enhanced design of concrete structures. In the present investigation, QR (Quick Response) code based random speckle pattern is used as a non-contact sensor, which is an innovative approach in the field of digital image correlation (DIC). A four-point bending test was performed on RC beams of size 1800 mm × 150 mm × 200 mm. Image processing was done using an open source Ncorr algorithm for the results obtained using random speckle pattern and QR code based random speckle pattern. Load-deflection curves of RC beams were plotted for the results obtained using both contact and non-contact (DIC) sensors, and further, Moment (M)-Curvature (κ) relationship of RC beams was developed. The loading curves obtained were used as input data for material model parameters in finite element analysis. In finite element method (FEM) based software, concrete damage plasticity (CDP) constitutive model is used to predict the realistic nonlinear quasi-static flexural behavior of RC beams for monotonic loading condition. The results obtained using QR code based DIC are observed to be on par with conventional results and FEM results.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.561-566
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• 2015

Hadoop is becoming widely adopted in scientific and commercial areas as an open-source distributed data processing framework. Recently, for real-time processing and analysis of data, an attempt to apply high-performance computing technologies to Hadoop is being made. In this paper, we have expanded the Hadoop Filesystem library to support Lustre, which is a popular high-performance parallel distributed filesystem, and implemented the Hadoop MapReduce execution environment over the Lustre filesystem. We analysed Hadoop MapReduce over Lustre by using Hadoop standard benchmark tools. We found that Hadoop MapReduce over Lustre execution has a performance 2-13 times better than a typical Hadoop MapReduce execution.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.859-870
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• 2021

KARI (Korea Aerospace Research Institute) is developing a design framework for the concept and preliminary design of eVTOL aircrafts. A low fidelity mission analysis tool was developed for the eVTOL aircrafts of Lift-Tilt Concept, which have tilt propellers and lift propellers, using open source SUAVE package. For its development, a review for the propeller performance analysis functionality was made. To find the trim solution at each mission segment automatically, an algorithm is implemented, using a global optimization technique through parallel processings and DOE(design of experiment). Using the tool, the one seated eVTOL OPPAV(optionally piloted personal air vehicle) was modeled and evaluated, which results were compared with the preliminary design data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.292-293
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• 2018

최근 증강현실 산업 분야가 많은 각광을 받고, 시장이 성장함에 따라 보다 쉽게 증강현실을 구현 할 수 있도록 많은 SDK(Software Development Kit)들이 발표되었다. 기존에 발표 된 SDK들이 대부분 강체 추적만을 제공한다. 이는 현재 추적 알고리즘의 기반이 되는 이론이 강체에 한정되어 있기 때문이다. 그러나 제안하는 프레임워크는 강체 추적뿐만 아니라 비강체 추적 또한 가능하다. 이를 위하여, 제안하는 프레임워크는 증강현실의 핵심 기술인 추적 엔진과 보다 넓은 확장성을 가지도록 추적하고자 하는 물체를 사전에 분석하고 실시간으로 모델 변형 정보를 추정하는 시뮬레이션 엔진으로 구성된다. 추적 엔진은 기본적으로 물체의 표면에 존재하는 특징점 정보를 이용하여 추적을 진행 하되, 비강체 추적을 위하여 시뮬레이션 엔진의 도움을 받는 형태로 구성된다. 시뮬레이션 엔진에서는 물체의 역학 파라미터를 추정하여 이를 추적을 진행 할 때, 추적 엔진의 물체 표면 특징점 정보를 이용하여 물체의 변형 정보를 추정한다. 또한 제안하는 프레임워크는 성능 상의 장점 외에도 오픈소스로 공개되기에 국내 증강현실 시장 성장에 발판이 될 것으로 기대된다.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.49-55
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• 2019

Organizations design and operate business process models to achieve their goals efficiently and systematically. With the advancement of IT technology, the number of items that computer systems can participate in and the process becomes huge and complicated. This phenomenon created a more complex and subdivide flow of business process.The process instances that contain workcase and events are larger and have more data. This is an essential resource for process mining and is used directly in model discovery, analysis, and improvement of processes. This event log is getting bigger and broader, which leads to problems such as capacity management and I / O load in management of existing row level program or management through a relational database. In this paper, as the event log becomes big data, we have found the problem of management limit based on the existing original file or relational database. Design and apply schemes to archive and analyze large event logs through Hadoop, an open source distributed file system, and HBase, a NoSQL database system.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.63-70
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• 2019

These days, as Interest in Image recognition with deep learning is increasing, there has been a lot of research in image recognition using deep learning. In this study, we propose a system for classifying rocks through rock images of 18 types of rock(6 types of igneous, 6 types of metamorphic, 6 types of sedimentary rock) which are addressed in the high school curriculum, using CNN model based on Tensorflow, deep learning open source framework. As a result, we developed a classifier to distinguish rocks by learning the images of rocks and confirmed the classification performance of rock classifier. Finally, through the mobile application implemented, students can use the application as a learning tool in classroom or on-site experience.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.75-87
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• 2023

This paper presents a revised version of the vocabulary analyzer for self-reflection (VACSR), called VACSR v.2.0. The initial version of the VACSR automatically analyzes the occurrences and the level of vocabulary items in the transcribed texts, indicating the frequency, the unused vocabulary items, and those not belonging to either scale. However, it overlooked words with multiple parts of speech due to their identical headword representations. It also needed to provide more explanatory result tables from different corpora. VACSR v.2.0 overcomes the limitations of its predecessor. First, unlike VACSR v.1, VACSR v.2.0 distinguishes words that are different parts of speech by syntactic parsing using Stanza, an open-source Python library. It enables the categorization of the same lexical items with multiple parts of speech. Second, VACSR v.2.0 overcomes the limited clarity of VACSR v.1 by providing precise result output tables. The updated software compares the occurrence of vocabulary items included in classroom corpora for each level of the Common European Framework of Reference-Japan (CEFR-J) wordlist. A pilot study utilizing VACSR v.2.0 showed that, after converting two English classes taught by a preservice English teacher into corpora, the headwords used mostly corresponded to CEFR-J level A1. In practice, VACSR v.2.0 will promote users' reflection on their vocabulary usage and can be applied to teacher training.

• Information Systems Review
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• v.21 no.4
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• pp.99-123
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• 2019

The software industry is a high value-added industry in the knowledge information age, and its importance is growing as it not only plays a key role in knowledge creation and utilization, but also secures global competitiveness. Among various SW available in today's business environment, Open Source Software(OSS) is rapidly expanding its activity area by not only leading software development, but also integrating with new information technology. Therefore, the purpose of this research is to empirically examine and analyze the effect of factors on the switching behavior to OSS. To accomplish the study's purpose, we suggest the research model based on "Push-Pull-Mooring" framework. This study empirically examines the two categories of antecedents for switching behavior toward OSS. The survey was conducted to employees at various firms that already switched OSS. A total of 268 responses were collected and analyzed by using the structural equational modeling. The results of this study are as follows; first, continuous maintenance cost, vender dependency, functional indifference, and SW resource inefficiency are significantly related to switch to OSS. Second, network-oriented support, testability and strategic flexibility are significantly related to switch to OSS. Finally, the results show that willingness to secures SW competitiveness has a moderating effect on the relationships between push factors and pull factor with exception of improved knowledge, and switch to OSS. The results of this study will contribute to fields related to OSS both theoretically and practically.

• Journal of the Korean GEO-environmental Society
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• v.9 no.5
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• pp.45-52
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• 2008

The present study has extended OpenSees, which is an open-source software framework DOS program for developing applications to idealize geotechnical and structural problems, for the static analysis of axial load capacity and settlement of single piles in MS Windows environment. The Windows version of OpenSees as improved by this study has enhanced the DOS version from a general purpose software program to a special purpose program for driven and bored pile analysis with additional features of pre-processing and post-processing and a user friendly graphical interface. The method used in the load capacity analysis is the numerical methods based on load transfer functions combined with finite elements. The use of empirical nonlinear T-z and Q-z load transfer curves to model soil-pile interaction in skin friction and end bearing, respectively, has been shown to capture the nonlinear soil-pile response under settlement due to load. Validation studies have shown the static load capacity and settlement predictions implemented in this study are in fair agreement with reference data from the static loading tests.