• CDE review
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• v.3 no.2
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• pp.1-4
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• 1997

본 기사에서는 CAD 모델을 공학적 해석이나 제조공정에 사용하는데 있어 문제가 되고 있는 솔리드 모델의 결함에 관한 문제를 다루고자 한다. International TechneGroup사(ITI) 등과 같은 몇몇 회사들은 솔리드 모델의 결함을 발견하는 소프트웨어를 개발하고 있으며, XOX('zocks'라고 발음함)사는 이런 결함을 자동적으로 수정하는 프로그램을 개발하고 있다.

• Laser Solutions
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• v.15 no.1
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• pp.6-9
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• 2012

In TFT-LCD manufacturing process, various defects are generated by manufacturing machine trouble or particle. These defects can be repaired through the TFT-Laser repair process that only can't be automated in TFT-LCD manufacturing Process. In this Paper, we propose auto defect algorithm for TFT-LCD laser repair machine using image processing algorithm in order to automate process. Proposed algorithm can detect very small defects (< 2um) in 98% success ratio, and generated laser repair path guarantee highly precise position accuracy. Through proposed system, much of the work still done the old-fashioned way, by hand, can be automated and manufacturing company can be strengthed the competitiveness of cost.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.398-405
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• 2014

Recently the embedded software has been widely applied to the safety-critical systems in aviation and defense industries, therefore, the higher level of reliability, availability and fault tolerance has become a key factor for its implementation into the systems. The integrity of the software can be verified using the static analysis tools. And recent developed static analysis tool can evaluate code integrity through the mathematical analysis method. In this paper we detect the autocode error and violation of coding rules using the formal verification tool, Polyspace(R). And the fundamental errors on the flight control law model have been detected and corrected using the formal verification results. As a result of verification process, FBW helicopter control law autocode can ensure code integrity.

• Journal of KIISE
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• v.44 no.8
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• pp.832-841
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• 2017

Bug reports are essential documents for developers to localize and fix bugs. These reports contain information regarding software bugs or failures that occur during software operation and maintenance phase. Information Retrieval-based Bug Localization (IR-BL) techniques have been proposed to reduce the time and cost it takes for developers to resolve bug reports. However, if a low-quality bug report is submitted, the performance of such techniques can be significantly degraded. To address this problem, we propose a quality prediction method that selects low-quality bug reports. This process; defines a Quality property of a Bug report as a Query (Q4BaQ) and predicts the quality of the bug reports using machine learning. We evaluated the proposed method with 3 open source projects. The results of the experiment show that the proposed method achieved an average F-measure of 87.31% and outperformed previous prediction techniques by up to 6.62% in the F-measure. Finally, a combination of the proposed method and traditional automatic query reformulation method improved the MRR and MAP by 0.9% and 1.3%, respectively.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.125-134
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• 2009

This paper proposes a change management system of sensor network applications based on version synchronization that supports to effectively manage defect correction of applications, change of functions for applications or improvement of applications without suspending the sensor network. The proposed change management system consists of the NADE which is an application development environment, the Node Management Server, and the Node Agent. NADE is an Eclipse-based development environment for developing applications which are installed into nodes. NADE is also connected with CVSNT which is a version management tool and performs application version management using the CVSNT. Node Management Server manages nodes to maintain latest versions of applications by synchronizing versions of applications which are performed on the nodes with the versions of applications which are developed in the NADE. Node Agent which is loaded into the node periodically sends the version information of the application to the server, and stores and updates the version information of the application. Through the proposed change management system, applications of nodes are automatically updated when versions of applications are changed by correcting defects, changing functions or improving applications. Therefore, the user can effectively manage the execution of sensor network system without suspending or delaying the sensor network. Also, visibility of change management for sensor network applications will be improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.2
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• pp.81-89
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• 2001

Space systems are operating in a changing and uncertain space environment and are desired to have autonomous capability for long periods of time without frequent telecommunications from the ground station At the same time. requirements for new set of projects/systems calling for ""autonomous"" operations for long unattended periods of time are emerging. Since, by the nature of space systems, it is desired that they perform their mission flawlessly and also it is of extreme importance to have fault-tolerant sensor/actuator sub-systems for the purpose of validating science measurement data for the mission success. Technology innovations attendant on autonomous data validation and health monitoring are articulated for a growing class of autonomous operations of space systems. The greatest need is on focus research effort to the development of a new class of fault-tolerant space systems such as attitude actuators and sensors as well as validation of measurement data from scientific instruments. The characterization for the next step in evolving the existing control processes to an autonomous posture is to embed intelligence into actively control. modify parameters and select sensor/actuator subsystems based on statistical parameters of the measurement errors in real-time. This research focuses on the identification/demonstration of critical technology innovations that will be applied to Autonomous Spacecraft Health Monitoring/Data Validation Control Systems (ASHMDVCS). Systems (ASHMDVCS).

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.