• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.879-888
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• 2004

Ad Node transmits packets to a destination node using routing function of intermediate nodes on the path in Ad Hoc networks. When the link to a next hop node in a path is broken due to the next hop node's mobility, a new route search process is required for continuing packets transmission. The node which recognizes link fault starts a local route recovery or the source node starts a new route search in the on demand routing protocol AODV. In this case, the new route search or the local route search brings packet delays and bad QoSs by packet delay. We propose RPAODV that the node predicts a link fault selects a possible node in neighbor nodes as a new next hop node for the path. The proposed protocol can avoid path faults and improve QoS.

• Journal of KIISE
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• v.42 no.11
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• pp.1339-1348
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• 2015

In a distributed system environment based on a service-oriented architecture, separate systems collaborate to achieve the goals of the entire system by using services provided other systems. A service quality violation from using one service can cause runtime system failure in the environment. The existing self-adaptation methods follow fault tolerance mechanism that responds to a failure after a service quality violation. In other words, these methods are limited to responsive action. Therefore, a service-dependability-case based self-adaptation mechanism is necessary to preserve the dependability of the self-adaptive system. This paper demonstrates that the service-dependability-case based self-adaptation mechanism is better than QoS(quality of service)-based self-adaptation with fault tolerance to preserve the dependability of the self-adaptive system. Additionally, this paper suggests a method to present and analyze service dependability by using GSN(Goal Structuring Notation) which is the existing modeling method for the presentation of assurance cases, an action mechanism adapted using an analysis result of service-dependability-cases, a methods of leveraging the service-dependability-case based self-adaptation mechanism by following the service's life cycle, and the framework architecture including the major components and the interactions between the components in the control loop of the self-adaptation process.

• The KIPS Transactions:PartA
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• v.10A no.3
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• pp.215-224
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• 2003

Since there are various networks and heterogeneity of nodes in Internet, the existing load-sharing algorithms are hardly adapted for use in Internet-based clustering systems. Therefore, in Internet-based clustering systems, a load-sharing algorithm must consider various conditions such as heterogeneity of nodes, characteristics of a network and imbalance of load, and so on. This paper has proposed an expanded-WF algorithm which is based on a WF (Weighted Factoring) algorithm for load-sharing in Internet-based clustering systems. The proposed algorithm uses an adaptive granularity strategy for load-sharing and duplicate execution of partial job for fault-tolerance. For the simulation, the to matrix multiplication using PVM is performed on the heterogeneous clustering environment which consists of two different networks. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 55%, 63% and 20%, respectively. Also, this paper shows that It can process the fault-tolerance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

• Journal of the Semiconductor & Display Technology
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• v.23 no.3
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• pp.127-134
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• 2024

Products were typically produced using specialized equipment such as CNC machines, milling machines, and lathes in traditional manufacturing. However, modern manufacturing is increasingly attempting with technological advancements to leverage large industrial robots for machining, offering greater flexibility, efficiency, and a high degree of freedom throughout the entire production process. Additionally, the demand for industrial robots continues to rise as industries adopt smart factories. These robots are becoming larger, more precise, and faster, as they take over tasks previously requiring specialized equipment or skilled human operators. Where numerous robots are in operation in factories, ensuring a stable supply chain and maintaining operational uptime is crucial. Therefore, preparing for potential mechanical failures in each robot is necessary, and there is a growing need for technologies that enable real-time fault diagnosis and predictive maintenance. A large industrial robot used for machining was employed as a testbed for fault diagnosis in this study. The Vibration data was collected from various robot axes under both normal operating conditions and abnormal conditions, such as end-effector overloads and drive malfunctions. The collected vibration data was then preprocessed, and key features were analyzed and extracted. The extracted features were used to build a learning model, and in this study, the CNN (Convolutional Neural Network) algorithm was applied instead of k-NN (k-Nearest Neighbors) to diagnose defects occurring in the discontinuous movements of the robot, thereby improving accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1348-1351
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• 1997

The federated Kaman filter(FKF) is being widely used in many multisensor navigatiion systems. It is know that the FKF has advantages of simplicity and fault-tolerance over other decentralized filter techniques. In this paper, optimal and suboptimal FKF configuratiions are mentioned and a covariance analysis technique for the suboptimal FKF is newly presented. The suboptimal FKF configuration, known as No-reset(NR) mode, has better fault tolerance capability than the optimal FKF coniguratioin. In the suggested technique, a suboptimal fusion process of FKF is considered a swell as suboptimal gains of local filters. An upper boun of error covariance for suboptimal FKF is derived. Also, it is mathematically shown that this bound is smaller thanexisting bound in the literatrue. A vehicle-navigaion system is designed using the FKF. In thissystem, a map constraing equation is introduced and used as a measurement equatioin of Kalman filter. Performance analysis is done by the suggested covariance analysis techniques.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.57-64
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• 2000

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model, Numerical examples are provided for illustrative purposes.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.115-131
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• 2004

As dual port memories are being frequently used, test and diagnosis for dual port memories becomes more important. In this paper, anew diagnosis algerian which can classify faults in detail when the fault is detected during test process is developed. The new algerian increases its efficiency by using the information that can be obtained by test results as well as results using additional diagnostic pattern set. In addition the algorithm can diagnose various fault models for dual port memories.

• Journal of Powder Materials
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• v.10 no.5
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• pp.318-324
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• 2003

The nano-scale crystallite sizes of uranium oxide powders in simulated spent fuel were measured by the neutron diffraction line broadening method in order to analyze the sintering behavior of the dry process fuel. The mixed $UO_2$ and fission product powders were dry-milled in an attritor for 30, 60, and 120 min. The diffraction patterns of the powders were obtained by using the high resolution powder diffractometer in the HANARO research reactor. Diffraction line broadening due to crystallite size was measured using various techniques such as the Stokes' deconvolution, profile fitting methods using Cauchy function, Gaussian function, and Voigt function, and the Warren-Averbach method. The non-uniform strain, stacking fault and twin probability were measured using the information from the diffraction pattern. The realistic crystallite size could be obtained after separation of the contribution from the non-uniform strain, stacking fault and twin.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.194-196
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• 2005

The command processor in satellite handles the capability of the process of command transmitted from ground station and deliver the processed data to on board computer in satellite. The command processor is consisted of redundant box to increase the reliability and availability of the capability. At each command processor, the processing time of each command processor is different, so the mismatch of processing time makes it difficult to timely synchronize the reception to on board computer and even will be became worse under the command processor's fault. To minimize the tine loss induced by the command processor's fault on board computer must analyze the time distribution of command propagation. This paper presents the logic of minimizing the delay error of command propagation the logic of analyzing the output of command processor.