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5 results for “Channel design”
UNSUPERVISED MACHINE LEARNING AND VECTOR MODELS IN DESIGNING AND OPTIMIZATION OF TELECOM RETAIL CHANNELS
<p>This paper examines the use of unsupervised machine learning and vector models in the design and optimization of retail channels for telecommunications services. Unsupervised machine learning allows you to analyze and identify hidden patterns in large volumes of untagged data, which is especially important in a dynamically changing consumer market. Vector models, in turn, provide high accuracy of demand forecasting and inventory management, contributing to an increase in the efficiency of trading channels. The synergy of these technologies allows companies to improve customer experience, optimize operational processes and increase competitiveness in the market. The main focus of the work is on data processing methods, including correlation analysis, the use of the support vector machine (SVM) method and its adaptation to solve problems related to predicting customer behavior and optimizing logistics processes.</p>
Node-Pore Coded Coincidence Correcting Microfluidic Channel Framework: Code Design and Sparse Deconvolution
<p>This is the dataset for the work titled and authored by:</p> <p><strong>Node-Pore Coded Coincidence Correcting Microfluidic Channel Framework: Code Design and Sparse Deconvolution</strong></p> <p>Michael Kellman, Francois Rivest, Alina Pechacek, Lydia Sohn, Michael Lustig</p> <p>We present a novel method to perform individual particle (e.g. cells or viruses) coincidence correction through joint channel design and algorithmic methods. Inspired by multiple-user communication theory, we modulate the channel response, with Node-Pore Sensing, to give each particle a binary Barker code signature. When processed with our modified successive interference cancellation method, this signature enables both the separation of coincidence particles and a high sensitivity to small particles. We identify several sources of modeling error and mitigate most effects using a data-driven self-calibration step and robust regression. Additionally, we provide simulation analysis to highlight our robustness, as well as our limitations, to these sources of stochastic system model error. Finally, we conduct experimental validation of our techniques using several encoded devices to screen a heterogeneous sample of several size particles.</p> <p>Software can be found under this DOI:</p> <p>10.5281/zenodo.846448</p>
Phonon calculations for "Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics"
<p>These are the phonon calculations for</p> <p>R. Hanus, <strong>J. George</strong>, M. Wood, <strong>A. Bonkowski</strong>, Y. Cheng, D. L. Abernathy, M. E. Manley, G. Hautier, G. J. Snyder, R. P. Hermann, “Uncovering design principles for amorphous-like heat conduction using two-channel lattice dynamics”, <em>Materials Today Physics</em>, <strong>2021</strong>, In Press, <a href="https://doi.org/10.1016/j.mtphys.2021.100344">https://doi.org/10.1016/j.mtphys.2021.100344</a></p>
The influence of flow electrode channel design on flow capacitive deionization performance: Experimental and CFD modelling insights
<p>Flow capacitive deionization (FCDI) is an emerging desalination technology at which flow electrodes (shearthinning<br>flowable carbon slurries) are used to remove ions from saline water. The geometry of flow electrode<br>channels, which provide the path and ensure the distribution and mixing of the flow electrodes, is one of the most<br>important aspects to be optimized. This work presents experimental and computational fluid dynamics (CFD)<br>modelling analysis of the influence of the geometry of flow electrode channels on FCDI performance. Flow<br>electrode gaskets (with open, serpentine (short) horizontal and serpentine (long) vertical channels) were 3D<br>printed using a polyethylene terephthalate glycol (PET-G) filament. The FCDI cell with a vertical serpentine flow<br>electrode channel exhibited the poorest performance due to channel blockage by carbon particles, while the best<br>results were achieved with a horizontal serpentine flow electrode channel. CFD simulations aided in understanding<br>this behaviour by showing that the channel geometry strongly affects the local shear rate, and thus the<br>local viscosity of flow electrodes. Thus, it is recommended to design channels that induce flow disturbance<br>aiming for increasing the shear rate and hence reducing flow electrode viscosity, therefore promoting their<br>flowability and reducing clogging chances.</p>
A designer peptide against the EAG2-Kvβ2 potassium channel targets the interaction of cancer cells and neurons to treat glioblastoma
GEO Series GSE231577. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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