Development and Performance Assessment of a Low-Cost UAV Laser Scanner System (LasUAV)

Programmable Integrated Photonics (PIP) is a new paradigm that aims at designing common integrated optical hardware configurations, which by suitable programming can implement a variety of functionalities that, in turn, can be exploited as basic operations in many application fields. Programmability enables by means of external control signals both chip reconfiguration for multifunction operation as well as chip stabilization against non-ideal operation due to fluctuations in environmental conditions and fabrication errors. Programming also allows activating parts of the chip, which are not essential for the implementation of a given functionality but can be of help in reducing noise levels through the diversion of undesired reflections. After some years where the Application Specific Photonic Integrated Circuit (ASPIC) paradigm has completely dominated the field of integrated optics, there is an increasing interest in PIP justified by the surge of a number of emerging applications that are and will be calling for true flexibility, reconfigurability as well as low-cost, compact and low-power consuming devices. This book aims to provide a comprehensive introduction to this emergent field covering aspects that range from the basic aspects of technologies and building photonic component blocks to the design alternatives and principles of complex programmable photonics circuits, their limiting factors, techniques for characterization and performance monitoring/control and their salient applications both in the classical as well as in the quantum information fields. The book concentrates and focuses mainly on the distinctive features of programmable photonics as compared to more traditional ASPIC approaches.

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Energy balance and performance assessment of PV systems installed at a positive-energy building (PEB) solar energy research centre

Solar Energy ◽

10.1016/j.solener.2020.10.080 ◽

2020 ◽

Vol 212 ◽

pp. 258-274

Author(s):

C. Zomer ◽

I. Custódio ◽

S. Goulart ◽

S. Mantelli ◽

G. Martins ◽

...

Keyword(s):

Energy Balance ◽

Solar Energy ◽

Performance Assessment ◽

Research Centre ◽

Positive Energy ◽

Energy Research ◽

Pv Systems ◽

And Performance

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The Use of Microcomputer Simulations in Undergraduate Neurophysiology Experiments

Alternatives to Laboratory Animals ◽

10.1177/026119298701400303 ◽

1987 ◽

Vol 14 (3) ◽

pp. 134-140 ◽

Cited By ~ 2

Author(s):

K.A. Clarke

Keyword(s):

Low Cost ◽

Animal Experiments ◽

Theoretical Background ◽

General Purpose ◽

Microcomputer System ◽

Laboratory Equipment ◽

Teaching Objectives ◽

Compound Action Potentials ◽

Experimental Management ◽

And Performance

Practical classes in neurophysiology reinforce and complement the theoretical background in a number of ways, including demonstration of concepts, practice in planning and performance of experiments, and the production and maintenance of viable neural preparations. The balance of teaching objectives will depend upon the particular group of students involved. A technique is described which allows the embedding of real compound action potentials from one of the most basic introductory neurophysiology experiments—frog sciatic nerve, into interactive programs for student use. These retain all the elements of the “real experiment” in terms of appearance, presentation, experimental management and measurement by the student. Laboratory reports by the students show that the experiments are carefully and enthusiastically performed and the material is well absorbed. Three groups of student derive most benefit from their use. First, students whose future careers will not involve animal experiments do not spend time developing dissecting skills they will not use, but more time fulfilling the other teaching objectives. Second, relatively inexperienced students, struggling to produce viable neural material and master complicated laboratory equipment, who are often left with little time or motivation to take accurate readings or ponder upon neurophysiological concepts. Third, students in institutions where neurophysiology is taught with difficulty because of the high cost of equipment and lack of specific expertise, may well have access to a low cost general purpose microcomputer system.

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Application of the endurance time methodology on seismic analysis and performance assessment of hydraulic arched tunnels

Tunnelling and Underground Space Technology ◽

10.1016/j.tust.2021.104022 ◽

2021 ◽

Vol 115 ◽

pp. 104022

Author(s):

Benbo Sun ◽

Mingjiang Deng ◽

Sherong Zhang ◽

Chao Wang ◽

Yang Li ◽

...

Keyword(s):

Performance Assessment ◽

Seismic Analysis ◽

Endurance Time ◽

And Performance

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Experiments with Neural Networks in the Identification and Control of a Magnetic Levitation System Using a Low-Cost Platform

Applied Sciences ◽

10.3390/app11062535 ◽

2021 ◽

Vol 11 (6) ◽

pp. 2535

Author(s):

Bruno E. Silva ◽

Ramiro S. Barbosa

Keyword(s):

Neural Networks ◽

Neural Control ◽

Magnetic Levitation ◽

Low Cost ◽

Training Data ◽

Neural Controllers ◽

Levitation System ◽

Internal Model Controller ◽

Magnetic Levitation System ◽

And Performance

In this article, we designed and implemented neural controllers to control a nonlinear and unstable magnetic levitation system composed of an electromagnet and a magnetic disk. The objective was to evaluate the implementation and performance of neural control algorithms in a low-cost hardware. In a first phase, we designed two classical controllers with the objective to provide the training data for the neural controllers. After, we identified several neural models of the levitation system using Nonlinear AutoRegressive eXogenous (NARX)-type neural networks that were used to emulate the forward dynamics of the system. Finally, we designed and implemented three neural control structures: the inverse controller, the internal model controller, and the model reference controller for the control of the levitation system. The neural controllers were tested on a low-cost Arduino control platform through MATLAB/Simulink. The experimental results proved the good performance of the neural controllers.

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