• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.12
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• pp.3892-3898
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• 1996

In this study, the prediction of the fatigue life as well as the extimation of the characteristics of fatigue cumulative damage on GFRP under random loading were performed. The constant amplitude tests and the ramdom loading test were carried on notched GFRP specimens with a circular hole. Random waves were generated with a micro-computer and had wide band spectra. Since it is useful that the prediction of fatigue life ot the given load sequences is based on S-N curves under constant amplitude loading, the estimation of equivalent stress is done on every random waves. The equivalent stress wasat first estimated by Miner's rule and then by the proposed model which was based on Hashin-Rotem's comulative damage theory regarding nonlinear fatigue cumulative damage behavior. The fatigue lives were predicted from each equivalent stress evaluated. And each predicted fatigue llife was compared with experimental results. The number of cycles of random loads were counted by mean-cross counting method. The reuslts showed that the fatigue life predicted by proposed model was correlated well with the experimental results in comparison with Miner's model.

• Journal of Information Science Theory and Practice
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• v.3 no.1
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• pp.66-76
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• 2015

This research uses a new approach to analyze the extent of influence journal papers have on the progress of varied research fields by estimation of subject-based influence on research other than impact factor that relies on citation index. It is initiated with the hypothesis that earlier established citation relations between journal and citing paper, which reveals the research field that contains the highest citation index and hence has received the greatest contribution from a particular journal, would have inconsistent contribution to the research field over the year of journal publication. The target research is primarily 128 journal papers and 4,123 citing papers from Information Systems Research published in the years 2001, 2004, 2007, and 2010. The characteristics of citation history and hallmarks of research field of citing papers were studied and analysis on significant distinction between citing fields based on the year of publication was performed. The analysis results show the order of citation rate to be highest from Computer Science (2,221 cases), Business & Economics (2,191 cases), and Information Science & Library Science (1,901 cases). The citation history of the journal, nonetheless, indicates increase in citation during 2-3 years after the earliest publication till it achieves constant citation. The statistical analysis shows significant variation in citing fields in accordance with the publication year; especially in 2010, journal contribution has increased in the fields of Business & Economics, Operations Research & Management Science, and Health Care Sciences & Services but, however, is reduced in Education & Educational Research and Social Sciences - Other Topics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2275-2280
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• 2009

u-Healthcare service is one of attractive applications in ubiquitous environment. In this paper, we propose a method to recognize exercises using a new accelerometer based body-attached platform for supporting u-Healthcare service. The platform consists of a device for measuring accelerometer data and a device for receiving the data. The former measures a user's motion data using a 3-axis accelerometer. The latter transmits the accelerometer data to a computer for recognizing the user's exercise. The algorithm for exercise recognition classifies the type of exercise using principle components analysis(PCA) from the accelerometer data transformed by discrete fourier transform(DFT), and estimates the repetition count of the recognized exercise using a peak detection algorithm. We evaluate the performance of the algorithm from the accuracy of the recognition of exercise type and the error rate of the estimation of repetition count. In our experimental result, the algorithm shows the accuracy about 98%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.584-591
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• 2007

The recognition of human gestures in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle filter and apply the MAILAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.

• Current Optics and Photonics
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• v.3 no.3
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• pp.210-214
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• 2019

The allowable path-deviation time of aircraft in a free-space optical communication system has been estimated from various trajectories, using different values of aircraft speeds and turn rates. We assumed the existence of a link between the aircraft and a ground base station. First, the transmitter beam's divergence angle was calculated through two different approaches, one based on a simple optical-link equation, and the other based on an attenuation coefficient. From the calculations, the discrepancy between the two approaches was negligible when the link distance was approximately 110 km, and was under 5% when the link distance ranged from 80 to 140 km. Subsequently, the allowable path-deviation time of the aircraft within the tracking-error tolerance of the system was estimated, using different aircraft speeds, turn rates, and link distances. The results indicated that the allowable path-deviation time was primarily determined by the aircraft's speed and turn rate. For example, the allowable path-deviation time was estimated to be ~3.5 s for an aircraft speed of 166.68 km/h, a turn rate of $90^{\circ}/min$, and a link distance of 100 km. Furthermore, for a constant aircraft speed and turn rate, the path-deviation time was observed to be almost unchanged when the link distance ranged from 80 to 140 km.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1193-1215
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• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.27-41
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• 2024

Accurately estimating the performance of tunnel boring machines (TBMs) is crucial for mitigating the substantial financial risks and complexities associated with tunnel construction. Machine learning (ML) techniques have emerged as powerful tools for predicting non-linear time series data. In this research, six advanced meta-heuristic optimization algorithms based on long short-term memory (LSTM) networks were developed to predict TBM penetration rate (TBM-PR). The study utilized 1125 datasets, partitioned into 20% for testing, 70% for training, and 10% for validation, incorporating six key input parameters influencing TBM-PR. The performances of these LSTM-based models were rigorously compared using a suite of statistical evaluation metrics. The results underscored the profound impact of optimization algorithms on prediction accuracy. Among the models tested, the LSTM optimized by the particle swarm optimization (PSO) algorithm emerged as the most robust predictor of TBM-PR. Sensitivity analysis further revealed that the orientation of discontinuities, specifically the alpha angle (α), exerted the greatest influence on the model's predictions. This research is significant in that it addresses critical concerns of TBM manufacturers and operators, offering a reliable predictive tool adaptable to varying geological conditions.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.76-84
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• 2013

In the passive emitter localization using instantaneous TDOA (time difference of arrival) and FDOA (frequency difference of arrival) measurements, the estimation accuracy can be improved by collecting additional measurements. To achieve this goal, it is required to increase the number of the sensors. However, in electronic warfare environment, a large number of sensors cause the loss of military strength due to high probability of intercept. Also, the additional processes should be considered such as the data link and the clock synchronization between the sensors. Hence, in this paper, the passive localization of a stationary emitter is presented by using the successive TDOA and FDOA measurements from two moving sensors. In this case, since an independent pair of sensors is added in the data set at every instant of measurement, each pair of sensors does not share the common reference sensor. Therefore, the QCLS (quadratic correction least squares) methods cannot be applied, in which all pairs of sensor should include the common reference sensor. For this reason, a Gauss-Newton algorithm is adopted to solve the non-linear least square problem. In addition, to show the performance of the proposed method, we compare the RMSE (root mean square error) of the estimates with CRLB (Cramer-Rao lower bound) and derived the CEP (circular error probable) planes to analyze the expected estimation performance on the 2-dimensional space.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.131-136
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• 2003

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.