• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1087-1094
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• 2004

Normally, formalization and standardization are followed while doing any system analysis and design. But, in actual system development, products can't be written using the automated tool for all products due to their own characteristics. That results the inconsistency among development products and various kinds of problem can occur in the products. In this paper, we present a technique that supports consistency among products of analysis and design phase developed according to object oriented method. And, this paper also presents the implementation tool.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1171-1179
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• 2014

ISO(Independent System Operator) or TSO(Transmission System Operator) use power system analysis program to simulate contingency analysis and remedial actions to operate power system stably. Generally, power system analysis program provides automated analysis functions(or modules) to deal with wide area power system. However, because of missed contingency cases, automated contingency analysis has no practical use or has limitation. And in case of remedial action, it doesn't support automated function or takes a lot of times to study, because of simulation in manual for each cases. This paper suggests that new relation with buses and transmission line properties of power system DB used for power system analysis program to simulate automated contingency including all contingency cases needed in the field without missed cases. And it proposes automated remedial action scheme based on practical approach analysis to alleviate overloading or voltage problems. Finally it deals with automated contingency/remedial action analysis(automated scheduled outage) program which is developed by KEPCO and its performance and proposed schemes are proven by case study for real Korean power system data.

• Journal of Digital Contents Society
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• v.16 no.6
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• pp.893-900
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• 2015

IMO has been proceeding in the maritime SQA for software quality is considered to be essential for the development of the introduction of the e-Navigation In order to ensure software quality, follow the prescribed procedures throughout the software development project and create the output as a result of executing the respective steps. This paper is introduced a case for applying to maritime software development using the tool that is capable of real-time monitoring and automated documentation. Also, It is discussed the improvement of procedures for applying the expected effects and maritime SQA for the tool utilization. The Development of customized tools for maritime SQA that is reflected an improved procedure for tool is the future goals.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1377-1383
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• 2015

As the cloud services users' increase, there are important files created by individual in cloud storage. Thus, investigation of cloud artifact should be conducted. There are two methods of analyzing cloud service, one is that investigates cloud server provider (CSP), and another is that investigates client. In this paper, we presents an automated framework to detect the altered artifact and developes a tool that detects the cloud artifact. We also developed Cloud Artifact Tool that can investigate client computer. Cloud Artifact Tool provides feature of collection and analysis for the services such as Google Drive, Dropbox, Evernote, NDrive, DaumCloud, Ucloud, LG Cloud, T Cloud and iCloud.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.4
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• pp.498-506
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• 1999

본 논문에서는 ATM 통신프로토콜을 위한 자동시험시스템인 ACTS(ATM Conformance Test System)의 개발과 적용을 소개한다. ACTS는 ITU-T 또는 ATM Forum의 ATM 사용자-망 접속표준을 준용하는 ATM 단말과 망장비의 프로토콜적합성을 확인하는데 사용된다. 본 논문에서는 ACTS 개발에 사용된 방법을 소개한 뒤, ACTS를 실제 ATM 단말과 장비에 적용한 사례들을 소개한다. ACTS의 적용을 통하여 시험대상 장비들이 지닌 프로토콜구현상의 문제점을 파악하였고, 문제에 대한 원인분석을 수행하였다. 또한 이러한 문제점들이 상호운용에 미치는 장애를 예측함으로써, ACTS를 상호운용하는 ATM 장비를 확보하기 위한 유용한 도구로 사용할 수 있음을 보인다.Abstract This paper presents development and application of ACTS(ATM Conformance Test System), an automated test system for ATM protocols. ACTS is a test system that checks conformance of ATM terminal and network equipment implementing either ITU-T or ATM Forum user-network interface. This paper, after presenting the methodology and process used for developing ACTS, conducts case studies of its applications to real ATM equipment. By applying ACTS, we were able to detect numerous problems in protocol implementations of ATM equipment and analyse causes of the problems, thereby demonstrating the efficacy of ACTS as an efficient automated testing tool. Furthermore, by predicting the potential effects of the problems on interoperability, we show how ACTS can be used as a useful tool for ensuring interoperable ATM equipment.

• The korean journal of orthodontics
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• v.52 no.1
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• pp.3-19
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• 2022

Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.

• Archives of Plastic Surgery
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• v.51 no.1
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• pp.30-35
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• 2024

Background Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices. Methods S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split. The software requires the distances of sternal notch to nipple or nipple-to-nipple as input and performs image preprocessing steps, including ratio correction and 8-bit normalization. Breast asymmetry indices and centimeter-based measurements are provided as the output. The accuracy of S-BEST was validated using a paired t-test and Bland-Altman plots, comparing its measurements to those obtained from physical examinations of 100 females diagnosed with breast cancer. Results S-BEST demonstrated high accuracy in automatic landmark localization, with most distances showing no statistically significant difference compared with physical measurements. However, the nipple to inframammary fold distance showed a significant bias, with a coefficient of determination ranging from 0.3787 to 0.4234 for the left and right sides, respectively. Conclusion S-BEST provides a fast, reliable, and automated approach for breast aesthetic evaluation based on 2D frontal photographs. While limited by its inability to capture volumetric attributes or multiple viewpoints, it serves as an accessible tool for both clinical and research applications.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.146-156
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• 2024

Objective: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. Materials and Methods: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. Results: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883). Conclusion: Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.