robustness

摘要： Any failure or disruption in traffic flow can propagate through the road network. However, the server of such disruption and its consequences depends on the robustness and resiliency of transportation systems. In this context, traffic management (TM) measures will help the traffic stream to prevent the occurrence of such conditions or recover faster after experiencing the disruption. The main objective of this paper was to elaborate the contribution of TM measures to the resiliency of transportation systems, as well as, their vulnerability against external threats. Furthermore, a concept design for variable message signs (VMS) is developed and evaluated in terms of contribution to the resiliency of road networks. As well, new vulnerabilities associated with the implementation of VMS are investigated. The result of this study pointed out that ramp-metering, variable message signs, variable speed limits, and autonomous vehicles are valuable tools to mitigate the severity of traffic disruptions. VMS is one of the most effective approaches that enhance traffic resiliency by reducing traffic inflow to congested areas. However, these measures have opened new vulnerabilities to threats, especially cyber-attacks. Several cases of VMS hacks have occurred in the world and provided false messages to road users. It gets even worse with using an integrated wireless communication interface. Therefore, it is necessary to consider the security of such systems in advance, before practical application.

摘要： Aim: In prone breast treatments, a carbon fiber support device resides under the contralateral breast. Tangent beams are designed to encompass the treated breast and these often pass through the board at a shallow angle, resulting in significant attenuation. Our planners account for this attenuation by adding field-in-field dose to the deep part of the breast, through the board. Concern was raised about how accurate the treatment delivery is when the inherent uncertainties of patients’ positions are accounted for. Furthermore, transmission measurements are usually carried out perpendicular to the board, a non-clinical situation. The goal of this study is to evaluate the dosimetric effect of the board and the robustness of the plan to positional uncertainty. Materials and Methods: Twenty-two breast patients treated on a commercial prone breast board between 2017 and 2020 were selected for this retrospective study. To evaluate the board’s attenuation, we compared the plans with the board removed from the dose calculation. To quantify the robustness of this technique, we moved the beam isocenter with respect to the patient and board. Results: Our results showed that when the breast board is removed from a plan which was designed to account for the board attenuation, the average point dose increases by 7.48%, with a maximum of 22%. Comparing results with a mixed Analysis of Variance (ANOVA) and a least-square means analysis, our robustness evaluation indicates that anterior shifts at every magnitude (1 mm through 5 mm) make a significant difference in all dose statistics (D95, max, 95% prescription coverage and homogeneity index) investigated. In/out and right/left shifts resulted in an insignificant change in dose statistics. Conclusion: Prone breast boards can add significant dosimetric uncertainty into the treatment delivery process. Accounting for plan robustness in the design of the plan is highly recommended. A prone breast board design with support moved away from the beam path is warranted.

摘要： In this paper,the Kalman filter(KF)and the unbiased finite impulse response(UFIR)filter are fused in the discrete-time state-space to improve robustness against uncertainties.To avoid the problem where fusion filters may give up some advantages of UFIR filters by fusing based on noise statistics,we attempt to find a way to fuse without using noise statistics.The fusion filtering algorithm is derived using the influence function that provides a quantified measure for disturbances on the resulting filtering outputs and is termed as an influence finite impulse response(IFIR)filter.The main advantage of the proposed method is that the noise statistics of process noise and measurement noise are no longer required in the fusion process,showing that a critical feature of the UFIR filter is inherited.One numerical example and a practice-oriented case are given to illustrate the effectiveness of the proposed method.It is shown that the IFIR filter has adaptive performance and can automatically switch from the Kalman estimate to the UFIR estimates according to operating conditions.Moreover,the proposed method can reduce the effects of optimal horizon length on the UFIR estimate and can give the state estimates of best accuracy among all the compared methods.

摘要： The performance and accuracy of computer vision systems are affected by noise in different forms.Although numerous solutions and algorithms have been presented for dealing with every type of noise,a comprehensive technique that can cover all the diverse noises and mitigate their damaging effects on the performance and precision of various systems is still missing.In this paper,we have focused on the stability and robustness of one computer vision branch(i.e.,visual object tracking).We have demonstrated that,without imposing a heavy computational load on a model or changing its algorithms,the drop in the performance and accuracy of a system when it is exposed to an unseen noise-laden test dataset can be prevented by simply applying the style transfer technique on the train dataset and training the model with a combination of these and the original untrained data.To verify our proposed approach,it is applied on a generic object tracker by using regression networks.This method’s validity is confirmed by testing it on an exclusive benchmark comprising 50 image sequences,with each sequence containing 15 types of noise at five different intensity levels.The OPE curves obtained show a 40%increase in the robustness of the proposed object tracker against noise,compared to the other trackers considered.

摘要： This paper presents the design of a robust control system for a high-purity distillation column. It is concerned with the design of a two degree-of-freedom (2DOF) product-composition controller for a high-purity distillation column. The H∞ optimization problem is set up to ensure a guaranteed level of robust stability, robust disturbance attenuation and robust reference tracking performance.

摘要： High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global navigation satellite system(SINS/GNSS)integrated navigation system,and its estimation plays an important role in the performance evaluation of the navigation system.Traditional filter estimation methods usually assume that the measurement noise conforms to the Gaussian distribution,without considering the influence of the pollution introduced by the GNSS signal,which is susceptible to external interference.To address this problem,a high-precision filter estimation method using Gaussian process regression(GPR)is proposed to enhance the prediction and estimation capability of the unscented quaternion estimator(USQUE)to improve the navigation accuracy.Based on the advantage of the GPR machine learning function,the estimation performance of the sliding window for model training is measured.This method estimates the output of the observation information source through the measurement window and realizes the robust measurement update of the filter.The combination of GPR and the USQUE algorithm establishes a robust mechanism framework,which enhances the robustness and stability of traditional methods.The results of the trajectory simulation experiment and SINS/GNSS car-mounted tests indicate that the strategy has strong robustness and high estimation accuracy,which demonstrates the effectiveness of the proposed method.

摘要： Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.

摘要： BACKGROUND Endoscopy artifacts are widespread in real capsule endoscopy(CE)images but not in high-quality standard datasets.AIM To improve the segmentation performance of polyps from CE images with artifacts based on ensemble learning.METHODS We collected 277 polyp images with CE artifacts from 5760 h of videos from 480 patients at Guangzhou First People’s Hospital from January 2016 to December 2019.Two public high-quality standard external datasets were retrieved and used for the comparison experiments.For each dataset,we randomly segmented the data into training,validation,and testing sets for model training,selection,and testing.We compared the performance of the base models and the ensemble model in segmenting polyps from images with artifacts.RESULTS The performance of the semantic segmentation model was affected by artifacts in the sample images,which also affected the results of polyp detection by CE using a single model.The evaluation based on real datasets with artifacts and standard datasets showed that the ensemble model of all state-of-the-art models performed better than the best corresponding base learner on the real dataset with artifacts.Compared with the corresponding optimal base learners,the intersection over union(IoU)and dice of the ensemble learning model increased to different degrees,ranging from 0.08%to 7.01%and 0.61%to 4.93%,respectively.Moreover,in the standard datasets without artifacts,most of the ensemble models were slightly better than the base learner,as demonstrated by the IoU and dice increases ranging from-0.28%to 1.20%and-0.61%to 0.76%,respectively.CONCLUSION Ensemble learning can improve the segmentation accuracy of polyps from CE images with artifacts.Our results demonstrated an improvement in the detection rate of polyps with interference from artifacts.

摘要： Switched systems, i.e., systems changing the parameter values(even structural forms) abruptly and randomly at arbitrary instants, have been extensively utilized in many fields of modern industries. Rapid identification of switched systems, i.e.,capturing all the changing instants and reconstructing the mathematical models rapidly, is of great significance for behavior prediction, performance evaluation and possible control, but is restricted by small data amount available. Here, the rapid identification problem is successfully solved by a data-driven method in variational framework. The data-driven method only requires a small amount of data due to the compact form of the variational description, and is robust to data noise due to the holistic viewpoint. Two numerical examples, i.e., Duffing oscillator and van der Pol system(as two representative systems in nonlinear dynamics), are adopted to illustrate its application, efficiency and robustness to noise.

摘要： The original preset schedule of space telescopes can be disrupted when they receive ultra-high-priority unpredictable tasks.The main objective of this study is to observe such unpredictable tasks,the instability of which leads to failures in delivering the promises made.This paper proposes a method for retaining the robustness of the original plan.We use space-based multi-band variable objects monitor(SVOM)mission as an example to introduce the proposed method.First,the reasons for instability are discussed in detail.Two proactive strategies are proposed to promote the robustness of the schedule.The proactive strategies use the available windows of a given list of jobs.However,the realistic problem of SVOM is analysed using a rescheduling algorithm based on NSGA-II experiments with SVOM scenarios showing that the two proposed strategies are effective in reducing the instability caused by unpredictable interruption.

摘要： The problem of stability on repetitive control system rnwith multi-channel periodic input signal was rnanalyzed. R introduced rnfilter into multi-channel repetitive controller rn(MCRC) and built a multi-channel filter repetitive rncontroller (MCFRC) to increase rnstableness and robustness of system. Compared with rnoriginal method, this method has excellent control rneffect and improves the rnprecision and robustness of tracking system by rncalculation and simulation.

摘要： It makes the representation and recognition of watermarking information much visual and easy to embed a digital image into numeric relational data as digital watermarks. In this paper, a new numeric relational data watermarking algorithm is presented based on Arnold transform. In the algorithm, by the use of visual features of human being and image scrambling technology which could confuse the well-regulated watermarking information and diffuse errors, the identification of watermark would not be obviously affected while some continuous pixels could not be correctly detected. Our proposed algorithm could detect the watermark without original data, and has high security. The experiment results prove that the algorithm is very robust.

摘要： It makes the representation and recognition of watermarking information much visual and easy to embed a digital image into numeric relational data as digital watermarks. In this paper, a new numeric relational data watermarking algorithm is presented based on Arnold transform. In the algorithm, by the use of visual features of human being and image scrambling technology which could confuse the well-regulated watermarking information and diffuse errors, the identification of watermark would not be obviously affected while some continuous pixels could not be correctly detected. Our proposed algorithm could detect the watermark without original data, and has high security. The experiment results prove that the algorithm is very robust.

摘要： It makes the representation and recognition of watermarking information much visual and easy to embed a digital image into numeric relational data as digital watermarks. In this paper, a new numeric relational data watermarking algorithm is presented based on Arnold transform. In the algorithm, by the use of visual features of human being and image scrambling technology which could confuse the well-regulated watermarking information and diffuse errors, the identification of watermark would not be obviously affected while some continuous pixels could not be correctly detected. Our proposed algorithm could detect the watermark without original data, and has high security. The experiment results prove that the algorithm is very robust.

摘要： It makes the representation and recognition of watermarking information much visual and easy to embed a digital image into numeric relational data as digital watermarks. In this paper, a new numeric relational data watermarking algorithm is presented based on Arnold transform. In the algorithm, by the use of visual features of human being and image scrambling technology which could confuse the well-regulated watermarking information and diffuse errors, the identification of watermark would not be obviously affected while some continuous pixels could not be correctly detected. Our proposed algorithm could detect the watermark without original data, and has high security. The experiment results prove that the algorithm is very robust.

摘要： It makes the representation and recognition of watermarking information much visual and easy to embed a digital image into numeric relational data as digital watermarks. In this paper, a new numeric relational data watermarking algorithm is presented based on Arnold transform. In the algorithm, by the use of visual features of human being and image scrambling technology which could confuse the well-regulated watermarking information and diffuse errors, the identification of watermark would not be obviously affected while some continuous pixels could not be correctly detected. Our proposed algorithm could detect the watermark without original data, and has high security. The experiment results prove that the algorithm is very robust.