• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.33-39
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• 2020

Developers spend considerable time manually repairing code that was not built during project construction. If the build fails, it is necessary to understand the failed execution, identify the cause of the failure, and then implement the solution. Build tools such as Gradle have been developed to reduce this effort and automate project construction. However, build tools still do not solve many errors, requiring developers to try to solve build errors. In this study, we propose a solution recommendation method to increase the success rate of Gradle build and reduce the effort required to resolve errors. We provide a way to collect build errors and a way to transition from build error messages to successful builds. In particular, 296 build error messages collected from Github's Java project are classified as solutions, and 89% show that the solution can be applied.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Proceedings of the ESK Conference
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• 1998.04a
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• pp.167-172
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• 1998

Methods of evaluating the physiological activity of the living body are EEG, EOG, Heart rate, and Rectal temperature, etc. In the study of Hagiwara and Araki(1993), they found positive correlations among performance test, physiological measurement, and subjective feeling measurement. Human alertness of pilot directly influences on the flight performance that accomplishes a lot of vigilance task and procedure execution in flight. Accordingly, this paper deals with the quantitative and objective performance test based on tracking error and reaction time by means of the new computer test program into which the perception-motion system of human beings is applies. Throughout this experiment using performance thst, the results suggest that performance capability in state of sleep deprivation 2 hours and alcoholic 0.05 .apaprox. 0.06% in blood were more impaired than one in a normal state, and they further showed statistically significant differences between them, which were influenced by impairment factors of body regulation and pilot's grade. We also obtained the prediction value and the 95% confidence interval of tracking error and reaction time at the normal state for the purpose of distinguishing performance capability between the normal state and the abnormal state. And it is ecpected that the evaluation of human alertness using performance test will be applied to the quantitative assessment of an each pilot's realistic consciousness/attention, and will lead a flight commander to the accurate decision of mission approval prior to a flight.

• Journal of the Ergonomics Society of Korea
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• v.21 no.3
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• pp.13-24
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• 2002

Reduction and prevention of human error is one of the major interests for the enhancement of system safety and availability in Nuclear Power Plants (NPPs). As human beings have become the weak point in the system safety, a systematic evaluation on human performance during emergency situation should be performed in advance to identify the potential vulnerability of human tasks. Though the data gathering and analysis from real field is an important precondition, there were no available data in nuclear field of korea. This paper presents the result of human performance analysis on emergency tasks in NNPs. Firstly, a task analysis was performed to identify the characteristics of operator tasks during emergency condition and to classify them into a set of generic emergency tasks. Secondly, simulation data were collected and analyzed for the emergency tasks using the full scope simulator of Younggwang NPPs. The analyzed human performance information cover the event diagnosis time, the execution time of each procedural step, observation parameters, typer of irrelevant response, pattern of communication among staffs, and so on. These performance data would be used for human reliability analysis and the research of human error as technical bases.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.815-823
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• 2009

Most of existing watermarking schemes insert and extract a watermark, focusing on the visual conservation of an original image. However, existing watermarking schemes could be difficult for a watermark detection in case of various distortion caused by display-capture devices. Therefore, we propose a new display-capture based mobile watermarking scheme. The proposed watermarking scheme is a new concept for embedding a watermark, which uses the generated image instead of a given original image. For effective watermark decoding, we also present a method for detecting the background image whose error bit can not be corrected because of various heavy distortion and for avoiding it from the decoding process. For this scheme, we adopt distortion coefficients of camera calibration when we separate a background image from a captured image. For finding available correction bits of ECC through the decoding process, we capture 30,000 images and then calculate the separation ratio of a background image and the average error bits per an image. As experimental result, the separation ratio of a background image is about 96.5% in 30,000 captured image. And the false alarm ratio shows about $5.18{\times}10^{-4}$ in the separated background image. And also we can confirm the availability of real-time processing because the mean execution time is about 82ms per an image for capturing and decoding.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4618-4625
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• 2011

This paper suggests a specific model that could efficiently improve the interaction and the interface between MES(Manufacturing Execution System) server and POP(Point Of Production) Terminal through RFID(Radio Frequency Identification) system in Automative Module Assembly Line. The proposed model shows that the new method by RFID can more efficiently perform to receive work order informations and transmit work performances, compared with the current approach by proximity sensor. As a result of the certain test among the MES server, RFID system, PLC(Programmable Logic controller) and POP terminal, it is noted in case of the automatic control by RFID that the effects of proposed model are as follows; (a) While the processing time per truck for carrying by the current method was 10 minutes, the processing time by the new method was 1 minutes. (b) While the error rate by the current method was 20 %, the error rate by the new method was 1 %.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.421-428
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• 2006

This paper proposes an integrated recovery approach applying retry and rollback techniques to recover the TMR failure. Combining the time redundancy techniques with W system is apparently effective to recover the TMR failure(or masked error) primarily caused by transient faults. These policies need fewer reconfigurations at the cost of extra time required for the time redundant schemes. The optimal numbers of retry and rollback to minimize the mean execution time of tasks are derived for the proposed method through computing the likelihoods of all possible states of the failed system. The effectiveness of the proposed method is validated through examining certain numerical examples and simulations conducted with a variety of parameters governing environmental characteristics.

• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.223-228
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• 2008

In order to acquire the images requested by users, it is very important to calculate mission schedule parameters such as imaging execution time and attitude tilt angle accurately. These parameters are based on orbit prediction. This paper describes the accuracy of orbit propagation for image planning. The orbit prediction data from PSS and MAPS has a certain discrepancy due to different orbit propagator. It is necessary for mission planner to confirm this value during mission planning phase. The pointing error which means the difference between target center and real image received is calculated and analyzed using KOMPSAT-2 image data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1359-1371
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• 2020

In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.