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This dataset comprises Internet core network data inferred using the methodology detailed in the article titled 'Exploring Internet Evolution Through Analysis of its Core Network'.
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122 Views
Dynamic models are indispensable for the optimization, prediction and control of thermal comfort in buildings.A new method is proposed for modeling the nonlinear dynamics of radiator-heated buildings and measuring modeluncertainties. The model uncertainty range obtained by the method can describe the uncertainties in the presence of model structure deviations and unknown noise distributions, without making restrictive assumptions that the noise follows a Gaussian distribution as in existing methods.
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250 Views
When it comes to full-service home renovations and new construction, Vancouver residents know and trust Vibe Design Build. We are experts in making homes look and feel better, and we provide a wide variety of services to improve the aesthetics, practicality, and resale value of your home.
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21 Views
The dataset includes the Stanford Bunny, Elephant, and Pony models, which have been processed with added noise to adapt to the proposed algorithm. Additionally, the data encompasses point clouds of residential areas obtained by LIDAR, also subjected to noise addition. This comprehensive dataset, with its various models and point clouds, serves to thoroughly test and validate the robustness and effectiveness of the proposed algorithm in handling noisy data from different sources.
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258 Views
This is a data set about a practical explicit-time controller designing for a MIMO robotic system with proportional feedback. The robotic parameters are as follows: the weight is 35 KG; the arm span is 646 mm; the sample time is 0.0005s; the motor speed is 3000 RPM; the current signal amplification ratio is 1000; the motor maximum torque is [1.27, 1.27, 0.64, 0.318, 0.318, 0.159]^T (N \cdot m); the transmission ratio is [81.7853, 101.0453, 101.1892, 81.6735, 80.9486, 51.0270]^T.
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44 Views
The noisy nanopore channel is introduced as a model of the nanopore sequencer in DNA storage that includes inter-symbol interference, sample duplications, and measurement noise. Information rates of the noisy nanopore channel with Markov sources are computed numerically based on a Monte Carlo technique that builds upon existing techniques for finite-state channels. However, the analogous technique for channels with duplications poses a challenging problem from an algorithmic perspective.
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48 Views
We report on the fabrication and micro-transfer printing of InGaAs/InP avalanche photodiodes onto silicon substrates. A process flow was developed to suspend the devices using semiconductor tethers. The devices were characterised in linear mode operation both before suspension and after printing. Despite the additional fabrication steps required and the physical nature of the micro-transfer printing process, the electrical characteristics of the devices were preserved and no degradation in the devices’ optical performance was measured.
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80 Views
This is a accompanied supplement to the study. First, a short presentation is given from a study on fracture diagnosis using electrical logging. In this study, substandard fracture fillers had a negative impact on the signal results. It was one of the motivations for this study. Second, we give the detailed form of the formula for the electrical properties of the mixture and a link to the literature. Third, we give a simulation test using coal coke fracture fillers, which mainly considers the mechanical properties of coal coke.
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114 Views
A series of experiments including torque output tests, transparency tests, cardiopulmonary exercise tests and surface electromyography tests with five healthy subjects (height, 1.76 ± 0.05 m; weight, 72.5 ± 7.26 kg; age, 27.2 ± 2.86 years; all male) to validate the effectiveness of the SPURS. All participants provided written informed consent to participate in the study.
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53 Views
Dynamic nonlinear equations (DNEs) are essential for modeling complex systems in various fields due to their ability to capture real-world phenomena. However, the solution of DNEs presents significant challenges, especially in industrial settings where periodic noise often compromises solution fidelity. To tackle this challenge, we propose a novel approach called Periodic Noise Suppression Neural Dynamic (PNSND), which leverages the gradient descent approach and incorporates velocity compensation to overcome the limitations of the traditional Gradient Neural Dynamic (GND) model.
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222 Views