• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.67-74
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• 2016

Distributed agile software development faces difficulties for instance lack of visibility across development and delivery processes, complex and disjointed development processes, inability to capitalize on business opportunities, lack of communication agility between disconnected owners, development teams, and users or clients. However these difficulties are solved with the help of cloud computing services. This study proposes a framework to provide a skeletal or structural environment for distributed agile software development in cloud computing environment. The framework guide towards the best tooling to deliver a consistent, automated, governed, and unified agile software development process with reduced technical debt, and minimized project backlog. In addition to this, the study highlights the benefits of cloud computing in agile software development.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.95-100
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• 2009

Recent advances in computer technology have brought more dependence on software to railway systems. Hence, the safety assurance of the vital software running on the railway system is very critical task and yet, not many works have been done. While much efforts have been reported to improve electronic hardware's safety, not so much systematic approaches to evaluate software's safety. In this paper, we suggested an automated analysis tool for S/W change impact in railway system, and presented its result of implementation. The analysis items in the implemented tool had referred to the international standards in relation to the software for railway system, such as IEC 61508 and IEC 62279. In these international standards, 'change impact analysis' for railway system S/W has to be required mandatorily. The proposed tool can be utilized at the assessment stage and also the software development stage.

• Imaging Science in Dentistry
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• v.32 no.4
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• pp.187-194
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• 2002

Purpose: To evaluate the performance of the LOGICON Caries Detector using RVG-4 and RVG-ui sensors, by comparing results of each detector to the results of clinical and histological examinations. Materials and Methods : Pairs of extracted teeth were radiographed, and a total of 57 proximal surfaces, which included both carious and non-carious situations, were analyzed. The RVG-4 produced 8-bit images, while the RVG-ui unit produced 12-bit images, which were taken in the high sensitivity mode. The images produced by the LOGICON were evaluated by a trained observer using both automated and manual caries detection software modes. Ground sections of the teeth established the actual absence or existence of caries. Results: LOGIC ON-aided caries detection and depth discrimination of the RVG-4 and RVG-ui sensors were equally inconsistent irrespective of whether the LOGIC ON software was set to the automated or manual mode. Sensitivity ranged from 50% to 57% for caries penetration of the enamel-dentin junction. Conclusion: Care needs to be taken when using LOGIC ON in conjunction with RVG images as an adjunct for treatment planning dental caries. Even when applied by a trained observer, substantial discrepancies exist between the results of the LOGIC ON software-guided evalutations using RVG images and histologic examination.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.164-171
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• 2021

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.83-92
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• 2013

IFC based open BIM has internationally developed as a solution for interoperability problem among different software applications. Despite much interest and effort, the open BIM technologies are rarely introduced to the construction industry and need more technical development for a practical application as well. This research aims to develop automated code checking modules for quality assurance process of BIM data. The research have analyzed domestic regulations focusing on super-tall buildings and developed open BIM-based code checking modules for the evacuation regulations. The modules are able to validate evacuation regulations such as installation of emergency elevator and fire safety zone. The authors expect to improve the process of BIM quality assurance and enhance the quality of BIM data by this research on automated checking system.

• Journal of information and communication convergence engineering
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• v.15 no.4
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• pp.250-255
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• 2017

In this paper, we propose a method of detecting the region for measuring intima-media thickness (IMT). The existing methods for IMT measurement are automatic, but the region used for measuring IMT is not detected automatically but often set by the user. Therefore, research on detecting the intima-media region is needed for fully automated IMT measurement. The proposed method uses a morphological feature of the carotid artery visible as two long high-brightness horizontal lines at the upper and lower parts. It uses Gaussian blurring, ends-in search stretching, color quantization using a color-importance-based self-organizing map, and morphological operations to emphasize and to detect the morphological feature. The experimental results for evaluating the performance of the proposed method showed a 97.25% (106/109) success rate. Therefore, the proposed method can be used to develop a fully automated IMT measurement system.

• ETRI Journal
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• v.33 no.2
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• pp.259-266
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• 2011

We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

• Steel and Composite Structures
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• v.13 no.6
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• pp.561-570
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• 2012

Seismic collapse analysis requires efficient and automated method to perform thousands of time history analyses. The paper introduced the advantages of speed and convergence property of explicit method, provided a few techniques to accelerate speed of calculation and developed an automated procedure for collapse assessment, which combines the strong capacity of commercial explicit finite element software and the flexible, intelligent specialties of control program written in FORTRAN language aiming at collapse analysis, so that tedious and heavy work of collapse analysis based on FEMAP695 can be easily implemented and resource of calculation can be made the best use of. All the key commands of control program are provided to help analyzers and engineers to cope with collapse assessment conveniently.

• ETRI Journal
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• v.42 no.6
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• pp.965-975
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• 2020

This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the existing taxonomies governing the development and deployment of honeypots are inadequate for evolving malicious programs and their variants. Malware-propagation and compromise methods are highly automated and repetitious. These automated and repetitive characteristics can be exploited by using embedded reinforcement learning within a honeypot. A honeypot for automated and repetitive malware (HARM) can be adaptive so that the best responses may be learnt during its interaction with attack sequences. HARM deployments can be agile through periodic policy evaluation to optimize redeployment. The necessary enhancements for adaptive, agile honeypots require a new development and deployment framework.

• Korean Journal of Construction Engineering and Management
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• v.9 no.2
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• pp.67-80
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• 2008

Recently, automated construction machines have been developed for technically solving construction industry problems such as labor, productivity, qualify and the profit decrease. In spite of the importance of performance analysis in order to commercialize the automated construction machines, previous studies are mainly forced on developing hardware and software of automated construction machines. The primary objective of this research is to propose the performance analysis model of automated construction machines, which can measure productivity, quality and safety improvement rate based on the research and development phases, and to develop a performance analysis system, which enables performance evaluator to easily analyze the performance of the automated construction machines. Finally, it is anticipated that the effective use of the performance analysis model and computerized system would be able to develop the automated construction machines having high performance, and to establish the marketing strategy effectively in order to increase the possibility of commercialization of the developed construction machines.