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检索条件"任意字段=25th International Conference on Methods and Models in Automation and Robotics"

共 1217 条记录，以下是191-200 订阅

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Integrated Maintenance Decision Making Platform for Gantry Cranes in Container Terminal 24

Integrated Maintenance Decision Making Platform for Gantry C...

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24th international conference on methods and models in automation and robotics (MMAR)

作者： Szpytko, Janusz Salgado Duarte, Yorlandys AGH Univ Sci & Technol Ave A Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9781728109336

the paper presents a risk-based model to coordinate the preventive-predictive maintenance process of gantry cranes in a container terminal with vessels high demand. the model coordinates the preventive-predictive maintenance process minimizing the risk of Gantry Cranes Inefficiency (GCI). the risk is estimated with a sequential Markov Chain Monte Carlo (MCMC) simulation model. In this paper, the Preventive-Predictive Maintenance Scheduling (PPMS) process of gantry cranes is non-linear stochastic optimization problem and it is efficiently solved with the algorithms Particle Swarm Optimization (PSO). the model allows the terminal container operators to obtain a maintenance schedule that minimizes the risk of GCI, as much as possible in a container terminal;as well as establishing the desired level of risk the paper demonstrates the proposed model effectiveness with data of a real container terminal.

关键词： Containers Cranes Mathematical model Maintenance engineering Reliability Stochastic processes Predictive models

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AR Time-Series Identification using Quantized Observations 19

AR Time-Series Identification using Quantized Observations

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19th international conference on methods and models in automation and robotics (MMAR)

作者： Figwer, Jaroslaw Silesian Tech Univ Inst Automat Control PL-44100 Gliwice Poland

ISBN: (纸本)9781479950812

In the paper an approach to AR time-series identification based on observations obtained using data acquisition system equipped with a quantizer having saturation is presented. In the presented approach AR time-series model identification is replaced by an ARMA time-series model identification that returns parameters of AR time-series. A focus on model identification for ultra low-and ultra high-power AR time-series is given. the presented discussion is illustrated by a simulation case study showing properties of the presented approach.

关键词： autoregressive moving average processes quantisation (signal) signal detection time series AR time-series identification ARMA time-series model identification data acquisition system quantized observation ultra high-power AR time-series ultra low-power AR time-series Data acquisition Data models Estimation Quantization (signal) Random processes Standards White noise

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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models 27

Interpretable deep learning approach for classification of b...

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27th international conference on methods and models in automation and robotics (MMAR)

作者： Buler, Jakub Buler, Rafal Bobowicz, Maciej Ferlin, Maria Rygusik, Marlena Kwasigroch, Arkadiusz Grochowski, Michal Gdansk Univ Technol Dept Intelligent Control Syst & Decis Support Gdansk Poland Med Univ Gdansk Dept Radiol 2 Gdansk Poland

ISBN: (纸本)9798350311075

Breast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer. the design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially at pixel level, the large size of the images with relatively small cancer lesion sizes and class imbalance, a wide diversity of cancerous lesions, a variety of breasts, both in size and density, make the training of the neural models challenging. Moreover, clinicians are often concerned about using these black-box models because of the lack of transparency in their inference. To address these issues, we propose an approach taking advantage of Multiple Instance Learning (MIL), supported by attention mechanisms. We researched Attention-based MIL (AMIL), Gated AMIL (GAMIL), Dual Stream MIL (DSMIL) and CLustering-constrained AMIL (CLAM) models trained in a weakly-supervised manner and compared them with a common model in image classification tasks, ResNet18. the approach described in this paper is multimodal and combines two mammographic projections (CC and MLO) in the training process. the developed neural system achieved high classification efficiency. Furthermore, exploiting the generated attentional maps allowed the localisation of cancerous lesions, thus increasing the interpretability of the algorithm. thanks to this mechanism, we were also able to detect artifacts in the analyzed database, difficult to spot but drastically skewing the algorithm's performance.

关键词： breast lesion classification weakly-supervised learning decision support diagnosis multimodal learning attention maps dataset biases trustworthy AI

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Applying Training Hidden Features to Joint Curve Evolution for Brain MRI Segmentation

Applying Training Hidden Features to Joint Curve Evolution f...

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11th international conference on Control, automation, robotics and Vision (ICARCV 2010)

作者： Farzinfar, Mahshid Teoh, Eam Khwang Xue, Zhong Nanyang Technol Univ Sch Elect Elect Engn Singapore 639798 Singapore Cornell Univ Methodist Hosp Res Inst Weill Med Coll Houston TX USA

ISBN: (纸本)9781424478132

According to the level of information provided in images, segmentation techniques can be categorized into two groups. One is region-labeling, which obeys the intensity-based classification methods. Although modeling the tissue intensity is straightforward by applying local statistical methods and spatial dependencies, the results might suffer from noise and incomplete data. the second group of techniques applies active contour models, in which the objective is to find the optimal partition of the image domain using a closed or open curve by using prior constraints on the shape variation. However, estimating optimal curve is intractable due to the incomplete observation data. this paper extends a previously reported joint active contour model for medical image segmentation in a new Expectation-Maximization (EM) framework, wherein the evolution curve is constrained not only by a shape-based statistical model but also by applying a hidden variable model from the image observation. In this approach, the hidden variable model is defined by the local voxel labeling computed from its likelihood function, depended on the image functions and the prior anatomical knowledge. Comparative results on segmenting putamen and caudate shapes in MR brain images confirmed both robustness and accuracy of the proposed curve evolution algorithm.

关键词： Statistical shape model active contours level set methods Expectation-Maximization algorithm

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Continuous-Time Input-Output Linear Dynamic System Identification using Sampled Data 20

Continuous-Time Input-Output Linear Dynamic System Identific...

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20th international conference on methods and models in automation and robotics (MMAR)

作者： Figwer, Jaroslaw Silesian Tech Univ Inst Automat Control Akad 16 PL-44100 Gliwice Poland

ISBN: (纸本)9781479987016

In the paper an approach to parametric continuous-time input-output linear dynamic system identification based on a randomized search method is presented. During identification experiment the excitation signal is generated directly from D/A converter that is equipped only with zero-order or first-order hold filter - the corresponding low-pass analogue reconstruction filter is not used. In this experiment only samples of the system output signal are gathered. In the corresponding data acquisition system there is no analogue antialiasing filter. Samples of the system output signal are acquired with a deterministic constant or random sampling interval. Properties of the presented approach are illustrated by simulation experiments.

关键词： Data sampling Dynamic systems System identification INPUT-OUTPUT excitation signal output(systems) DATA ACQUISITION SYSTEMS Search methods antialiasing filter reconstruction filter DOE DESIGN AGENCY designer's alterations DA

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Application of Computer Aided Tools and methods for Unmanned Cargo Aircraft Design 20

Application of Computer Aided Tools and Methods for Unmanned...

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20th international conference on methods and models in automation and robotics (MMAR)

作者： Czyba, Roman Hecel, Micha Jablonski, Karol Lemanowicz, Marcin Platek, Krzysztof Silesian Tech Univ Dept Automat Control Fac Automat Control Elect & Comp Sci 16 Akad St PL-44100 Gliwice Poland Silesian Tech Univ Fac Chem Dept Chem Engn & Proc Design PL-44100 Gliwice Poland Silesian Tech Univ Fac Mech Engn PL-44100 Gliwice Poland

ISBN: (纸本)9781479987016

Nowadays, novel construction materials, more efficient power supplies and advanced artificial intelligence algorithms allow one to use unmanned aerial vehicles (UAV) in various fields of life. One of the biggest events promoting this idea is the Air Cargo Challenge (ACC) competition. In this paper the motivation for ACC participation and the overall procedure of CAD aided UAV design are presented. the nonlinear aircraft model as well as Computational Fluid Dynamic simulations are discussed. Finally, some details concerning designed UAV prototype are revealed.

关键词： UAV CAD CFD Rapid Prototyping

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Night vision applicability in anti-sway vision-based solutions 20

Night vision applicability in anti-sway vision-based solutio...

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20th international conference on methods and models in automation and robotics (MMAR)

作者： Hyla, Pawel AGH Univ Sci & Technol Fac Mech Engn & Robot PL-30059 Krakow Poland

ISBN: (纸本)9781479987016

this paper describes a common issues in architecture of the variety kind of vision-based sway sensors dedicated for the anti-sway solution as a feedback in close-loop systems. However, in the statement the author's attention was focused on the issue related with vision sensor architecture insensitiveness on actual exposure light conditions. the night vision functionality was obtained through use infrared radiation. Author main attention was focused on possibility of use IR as a solution for insufficient light condition and their usefulness in different non-contact vision-based sensor architecture. All obtained results and considerations were conducted on the base vision sway sensor integrated with infrared illuminator assembled on the physical scaled model of the overhead travelling crane with hosting capability of 150 kg.

关键词： night vision infrared radiation swinging sensor overhead travelling crane vision methods smart camera

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A flowshop scheduling problem with machine deterioration and maintenance activities

A flowshop scheduling problem with machine deterioration and...

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17th international conference on methods and models in automation and robotics (MMAR)

作者： Rudek, Agnieszka Rudek, Radoslaw Wroclaw Univ Technol Dept Syst & Comp Networks PL-50370 Wroclaw Poland Wroclaw Univ Econom Inst Business Informat Wroclaw Poland

ISBN: (纸本)9781467321242

In this paper, we analyse the makespan minimization flowshop scheduling problem, where the processing times of jobs depend on the number of performed jobs and maintenance activities. Since the considered problem with two machines seems to be NP-hard, thus, we propose a branch and bound method and some heuristic and metaheuristic algorithms to solve it.

关键词： maintenance activities processing time Branch and bound methods jobs machine Nondeterministic polynomial-time hard Heuristics

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Continuation method approach to trajectory planning in robotic systems

Continuation method approach to trajectory planning in robot...

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16th international conference on methods and models in automation and robotics (MMAR)

作者： Karpinska, Joanna Tchon, Krzysztof Wroclaw Univ Technol Inst Comp Engn Control & Robot PL-50372 Wroclaw Poland

ISBN: (纸本)9781457709142

this paper uses the continuation method as a guideline to address the trajectory planning problem in robotic systems. It is assumed that the robotic system can be represented by a control affine system with output. From the homotopy map a partial differential equation is derived involving the control system and its variational system, whose solution yields a 1 parameter family of control functions. this family contains a solution to the trajectory planning problem, corresponding to the parameter growing up to infinity. the approach developed in the paper is illustrated with a trajectory planning problem for the kinematics of the rolling ball.

关键词： trajectory planning rolling ball control systems Continuation methods Homotopy Differential equations kinematics

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Iterative Learning Control of Polyhydroxybutyrate Production in a Sequencing Batch Reactor 20

Iterative Learning Control of Polyhydroxybutyrate Production...

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20th international conference on methods and models in automation and robotics (MMAR)

作者： Jung, Seyong Zhang, Jie Oliveira, Rui Newcastle Univ Sch Chem Engn & Adv Mat Newcastle Upon Tyne NE1 7RU Tyne & Wear England Univ Nova Lisboa FCT Dept Chem P-2829516 Caparica Portugal

ISBN: (纸本)9781479987016

this study investigates the iterative learning control of a sequencing batch reactor for the production of polyhydroxybutyrate (PHB). In order to overcome the effect of model plant mismatches and unknown disturbances, a batch to batch iterative learning control strategy with incrementally updated models is developed. the reference batch is taken as the immediate previous batch in order to cope with nonlinearities and process variations. After each batch, the newly obtained process operation data is added to the historical process data base and an updated linearised model is re-identified. To cope with colinearity in the modeling data, principal component regression and partial least squares regression are used in identifying batch-wise linearised models. the proposed technique has been successfully applied to a sequencing batch reactor for the production of PHB.

关键词： iterative learning control PHB batch processes sequencing batch reactor linearised models

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