• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.866-870
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• 1989

Direct application of adaptive algorithm to the actual I/O is not a good strategy. The importance of using a kind of filter for estimation or control is strongly recommended. Simple pre-filtering method and pseudo-plant method is introduced. And, the properties of each methods are compared by analysis and/or simulations. A guideline for the choice of filters are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.81-86
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• 1991

The iterative learning operation has been utilized in the temperature Control of a batch reactor. A generic form of feedback-assisted first-order learning control scheme was constructed and then various design and operation modes were derived through convergence and robustness analysis in the frequency domain. The proposed learning control scheme was then implemented on a bench scale batch reactor with the heat of reaction simulated by an electric heater. The results show a great improvement in the performance of control as the number of batch operations progressed.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.207-210
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• 2003

In this paper, the combinations of speech enhancement techniques are experimented. Specifically, the spectral subtraction, KLT based comb-filtering, and their combinations are applied to the Aurora2 database. The results show that recognition accuracy is improved when KLT based comb-filtering is applied after spectral subtraction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.47-50
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• 2022

In this paper, we proposed a method for Video-based point cloud compression reference software TMC2 encoder with an option for empty partitions in point cloud encoding. This encoder option allows tile initialization and process for an empty partition. The proposed method provides the TMC2 encoder the robustness to process dynamic point clouds.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.25-36
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• 2023

Today, as AI (Artificial Intelligence) technology is introduced in various fields, including security, the development of technology is accelerating. However, with the development of AI technology, attack techniques that cleverly bypass malicious behavior detection are also developing. In the classification process of AI models, an Adversarial attack has emerged that induces misclassification and a decrease in reliability through fine adjustment of input values. The attacks that will appear in the future are not new attacks created by an attacker but rather a method of avoiding the detection system by slightly modifying existing attacks, such as Adversarial attacks. Developing a robust model that can respond to these malware variants is necessary. In this paper, we propose two methods of generating Adversarial attacks as efficient Adversarial attack generation techniques for improving Robustness in AI models. The proposed technique is the XAI-based attack technique using the XAI technique and the Reference based attack through the model's decision boundary search. After that, a classification model was constructed through a malicious code dataset to compare performance with the PGD attack, one of the existing Adversarial attacks. In terms of generation speed, XAI-based attack, and reference-based attack take 0.35 seconds and 0.47 seconds, respectively, compared to the existing PGD attack, which takes 20 minutes, showing a very high speed, especially in the case of reference-based attack, 97.7%, which is higher than the existing PGD attack's generation rate of 75.5%. Therefore, the proposed technique enables more efficient Adversarial attacks and is expected to contribute to research to build a robust AI model in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.431-441
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• 2020

In this paper, we propose a new method using a feedforward disturbance observer that guarantees stability and robustness about the effects of external disturbance and model uncertainty. The method is consist of a disturbance observer, a feedforward controller, and an overshoot detecting logic. It has an advantage of reducing the excessive overshoot by external disturbance and model uncertainty. Also, it is easy to adjust the control gain due to a simple structure. In order to verify the effectiveness of a new method, simulation results are given for longitudinal model of F-16 aircraft. By reflecting a various of model uncertainties, the stability and the robustness are guaranteed. Finally, the stability and the robustness of the proposed method are verified using root locus plot and bode plot.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.541-550
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• 2010

The $L_1$-regression estimator is susceptible to the leverage points, even though it is highly robust to the vertical outliers. This article is concerned with the improvement of robustness of the $L_1$-estimator. To improve its robustness, in terms of the breakdown point, we attempt to dampen the influence of the leverage points by means of reducing the weights corresponding to the leverage points. In addition the algorithm employs the linear scaling transformation technique, for higher computational efficiency with the large data sets, to solve the linear programming problem of $L_1$-estimation. Monte Carlo simulation results indicate that the proposed algorithm yields $L_1$-estimates which are robust to the leverage points as well as the vertical outliers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1931-1942
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• 2002

In this paper a formulation of robust optimization is presented and illustrated by a design example of vibratory micro gyroscopes in order to reduce the effect of variations due to uncertainties in MEMS fabrication processes. For the vibratory micro gyroscope considered it is important to match the resonance frequencies of the vertical (sensing) and lateral (driving) modes as close as possible to attain a high sensing sensitivity. A deterministic optimization in which the difference of both the sensing and driving natural frequencies is minimized as an objective function results in highly enhanced performance but apt to be very sensitive to fabrication errors. The formulation proposed is to attain robustness of the performance by including the sensitivity of the response with respect to uncertain variables as a term of objective function to be minimized. This formulation is simple and practically applicable since no detail statistical information on fabrication errors is required. The geometric variables, beam width, length and thickness of vibratory micro gyroscopes are adopted as design variables and at the same time considered as uncertain variables because here occur the fabrication errors. A robustness test in terms of a percentage yield by using the Monte Carlo simulation has shown that the robust optimum produces twice more acceptable designs than the deterministic optimum. Improvement of robustness becomes bigger as the amount of fabrication errors is assumed larger. Considering that the magnitude of fabrication errors and uncertainties in a MEMS structure are comparatively large, the present method is illustrated to be a viable approach for a robust MEMS design.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.159-163
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• 2004

Data pertaining to first lactation records of 316 Murrah buffaloes, progeny of 47 sires, maintained at NDRI Farm for a period of 18 years were analysed to construct selection indices and to examine their robustness by changing the relative economic values of different economic traits. A total of 120 selection indices were constructed for three sets of relative economic values ( 40 for each set) considering different combinations of seven first lactation traits viz. age at first calving (AFC), first lactation 305 day or less milk yield (FLMY), first lactation length (FLL), first calving interval (FCI), milk yield per day of first lactation length (MY/FLL), milk yield per day of first calving interval (MY/FCI) and milk yield per day age at second calving (MY/ASC). The three sets of relative economic values were based on economic values of different traits, 1% standard deviation of different traits and regression of different traits on FLMY. The 'optimum' indices for the first two sets had five traits each namely AFC, FLMY, FLL, FCI and MY/ASC giving improvement in aggregate genotype of Rupees 269.11 and Rs. 174.88, respectively. The accuracy of selection from both indices was 70.79 and 69.39%, respectively. The 'best' selection index from the third set of data again had five traits (AFC, FLMY, FLL, FCI and MY/FLL) giving genetic gain of Rs. 124.16 and accuracy of selection of 71.81%. The critcal levels or break-even points for FLMY for varying levels of AFC and FCI estimated from the "optimum index" suggested the need of enhancement of present production level of the herd or reduction of AFC or FCI. It was concluded that economic values of various first lactation traits were the most appropriate to construct selection indices as compared to other criteria of assigning relative economic weights in Murrah buffaloes.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.64-73
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• 2012

In this paper, we propose a method to search for identical videos. The proposed method is spatio-temporal group feature fingerprinting. Frame of video is extracted from fixed rate method and is partitioned into vertical group and horizontal group. Descriptor is made of each group feature that is extracted from binary fingerprinting. Next, use descriptor of original video to build a two type of fingerprinting database and matching with query video. To efficient and effective video copy detection, method have high robustness, independence, matching speed. In proposed method, group feature have high robustness and independence in variable modification of video. Building a original fingerprinting database is able to fast matching with query video. The proposed method shows performance improvement in variable modifications in comparison to the existing methods. Especially, very singular performance in speed improvement is great advantage of this paper.