Unmanned aerial vehicles can improve shortterm weather forecasting by acquiring information from weather sensors and other sensors. Withthis information, there is the possibility of making relevant maps like solar ra...
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ISBN:
(纸本)9798350364309;9798350364293
Unmanned aerial vehicles can improve shortterm weather forecasting by acquiring information from weather sensors and other sensors. Withthis information, there is the possibility of making relevant maps like solar radiation, pollen, emissions, particles, and others. Another advantage of this acquisition system is the high rate of flights, compared to the classic measurements made withthe weather balloon, which is launched twice a day. In addition to the advantages listed above, we discuss the multiplication factor of the acquired data, these systems being able to operate in various geographical locations.
this paper presents the performance analysis and the most significant design decisions taken to improve the runtime performance of a quality-diversity volume rendering framework, focusing on using parallel and distrib...
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ISBN:
(纸本)9798350364309;9798350364293
this paper presents the performance analysis and the most significant design decisions taken to improve the runtime performance of a quality-diversity volume rendering framework, focusing on using parallel and distributed computing to optimize specific stages within the framework pipeline. After considering the benefits and trade-offs of several aspects like minimization of execution time, portability and hardware independence, we developed a hybrid CPU-GPU parallel computing model that increased the overall efficiency. Using this model, we achieved significant improvement in runtime speed for critical components of the framework compared to the sequential implementation. Additionally, this model can be applied in a wide range of scenarios, where the performance improvements provided by GPU processing can be complemented by CPU parallelization, with better runtime results.
the Artificial Pancreas Problem (APP) offers a potential framework for control Engineering studies, specifically in the field of continuous monitoring and actuation to control glucose levels. the models that give a sa...
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ISBN:
(纸本)9798350364309;9798350364293
the Artificial Pancreas Problem (APP) offers a potential framework for control Engineering studies, specifically in the field of continuous monitoring and actuation to control glucose levels. the models that give a satisfactory level of accuracy are nonlinear by nature however, the standard approach in linear control is to find a linear representation of the model. the current paper proposes a comparison between standard linearization and linearization via the Koopman Operator for an input-affine nonlinear model from insulin intake to glucose level. Each model also has an additive disturbance component. To account for it, the current paper proposes a method of modeling the disturbance based on Gauss Processes. For a meaningful comparison between the considered linear matrix inequality-based controllers (LMI) and linear-quadratic regulators (LQR), the paper introduces the term Glucose Absolute Error (GAE) as an error index adapted for the Insulin-Glucose system.
Many people around the world enjoy traveling as a popular leisure activity. the process of trip planning can be time-consuming, requiring travelers to choose between various options and make decisions based on their p...
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ISBN:
(纸本)9798350364309;9798350364293
Many people around the world enjoy traveling as a popular leisure activity. the process of trip planning can be time-consuming, requiring travelers to choose between various options and make decisions based on their preferences and interests. this paper addresses the tourist trip design problem by proposing a Travel Planning Optimization system (TPOS), which includes an architecture that employs genetic algorithms to streamline travel planning. the paper's novelty lies in considering numerous travel factors, such as duration of visits, travel time, preferred types of locations, operating hours, destination popularity and the scheduling of places to eat in the daily program, into a single metric. this approach holds great promise in transforming travel planning by providing customized experiences that closely match the unique preferences and interests of each traveler, while using real location-related information in determining an efficient multiple-day itinerary.
Model predictive control has emerged as a prominent technique in control engineering due to its ability to handle constraints on bothcontrol signals and system states. this capability makes model predictive control a...
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ISBN:
(纸本)9798350364309;9798350364293
Model predictive control has emerged as a prominent technique in control engineering due to its ability to handle constraints on bothcontrol signals and system states. this capability makes model predictive control a powerful tool, particularly for complex systems with operational limitations. However, a major challenge associated with model predictive control is the "curse of dimensionality" arising from the constrained optimization problem solved at each time step. this problem becomes computationally expensive as the system dimension increases. this study proposes an accelerated model predictive control algorithm that addresses the curse of dimensionality. We achieve this by solving an equivalent suboptimal model predictive control problem within a reduceddimensional subspace. the subspace is efficiently calculated using singular value decomposition of the Hessian matrix associated withthe quadratic cost function. An adaptation law dynamically determines the subspace size, balancing accuracy and computational efficiency of the model predictive controlcontroller.
this paper presents a controller based on input-output linearisation (IOL) for a vapor compression cycle leveraging a moving-boundary model of the evaporator. After a presentation of the test rig and adaptations of a ...
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ISBN:
(纸本)9798350364309;9798350364293
this paper presents a controller based on input-output linearisation (IOL) for a vapor compression cycle leveraging a moving-boundary model of the evaporator. After a presentation of the test rig and adaptations of a previously published highorder simulation model, the control-oriented moving-boundary model is derived. Special emphasis is laid on steady-state solutions of the governing partial differential equations. the corresponding ansatz functions enable a high model accuracy while keeping the model order low. the IOL based on the moving-boundary model is compared by simulations with a previously published IOL based on a lumped-parameter approach. Here, the IOL based on the moving-boundary model shows a high performance in a much larger operation range. these results can be confirmed through the comparative evaluation with experimental data. Finally, we show the general applicability of the controller with an implementation on a dedicated test rig at the Chair of Mechatronics, University of Rostock.
Cloud computing can be an useful tool when dealing with spatially distributed resources, which need to be simultaneously managed. In this work, a simulation environment is developed using OpenStack to apply a Distribu...
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ISBN:
(纸本)9798350364309;9798350364293
Cloud computing can be an useful tool when dealing with spatially distributed resources, which need to be simultaneously managed. In this work, a simulation environment is developed using OpenStack to apply a Distributed Model Predictive control strategy for a platooning application consisting of multiple autonomous mobile robots. the idea is to develop the entire algorithm by taking advantage of the possibility of creating virtual machines. thus, each autonomous mobile robot is treated as an individual agent and is modeled and controlled on a virtual machine, whereas the communication between the agents is performed in the cloud, using the TCP/IP protocol standard. the simulation results illustrate that the platooning application deployed in OpenStack outperforms the simulation performed on a single computer.
this paper presents an algorithmic approach for segmenting news broadcasts produced by television stations. the proposed approach uses advanced signal processing techniques to extract and classify audio segments from ...
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ISBN:
(纸本)9798350364309;9798350364293
this paper presents an algorithmic approach for segmenting news broadcasts produced by television stations. the proposed approach uses advanced signal processing techniques to extract and classify audio segments from Romanian TV news broadcasts. By using derivative of 1-dimensional Gaussian filter and binary classification models, this paper aims to automatically identify and classify news segments into categories such as studio news, field news, commercials and music breaks. the primary objective of this paper is to develop a segmentation methodology optimized for reduced computational memory and quick processing. By leveraging efficient computational techniques, the news segmentation can be performed in a timely manner without compromising accuracy. this optimization is crucial for real-time or near-real-time applications within TV networks, facilitating tasks such as content monitoring and analysis.
Accurate plant detection is an important task in modern precision agriculture, enabling growers to quantify their plant numbers and estimate crop yields accurately. this paper looks at an example tobacco crop with a s...
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ISBN:
(纸本)9798350364309;9798350364293
Accurate plant detection is an important task in modern precision agriculture, enabling growers to quantify their plant numbers and estimate crop yields accurately. this paper looks at an example tobacco crop with a small dataset and aims to augment it to produce reliable object detection and counting. To obtain a trainable dataset, the source masks are separated into base classes, noise is removed from the masks, and images are augmented. the newly obtained clean dataset is then split into patches and used to obtain a JSON file describing all the labels present in the image. the model used for this job is YOLOv8 and it is trained on a COCO-formatted augmented dataset. Choosing the proper set of weights is done by evaluating and studying the performance metrics over the whole training phase, picking the one that offers the greatest balance between performance, training duration, and risk of induced overfitting due to over-learning.
the paper develops a comprehensive framework for analyzing the invariance of polyhedral sets with respect to the trajectories of nonlinear continuous-time dynamic systems. the fundamental contribution consists in stat...
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ISBN:
(纸本)9798350364309;9798350364293
the paper develops a comprehensive framework for analyzing the invariance of polyhedral sets with respect to the trajectories of nonlinear continuous-time dynamic systems. the fundamental contribution consists in stating and proving a general theorem, which takes into account nonlinear time-varying systems and, respectively, polyhedral sets with arbitrary time-dependence. To the intrinsic mathematical value of this result, the work adds the significance of some problems with specific contexts, which can be derived as particular cases of our general setting. At the same time, it is shown that some of these particular cases are correlated with specific invariance properties, which were studied individually, through separate researches. the specificity of the properties refers both to characteristics of dynamics and to subclasses of polyhedral sets.
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