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The fading is leading to the delay spread of the transmitted data and causing to the inter-symbol interference (ISI) at the receiver.
(a) (b) Figure. 2 (a) Experimental setup of channel measurement and (b) Flow chart of data processing.
Furthermore, we can describe a flow chart of the data processing as illustrated in Fig. 2 (b).
Firstly, the simulation data is generated by using computer simulation as well as the computational measured channel data.
Sharma, Diversity: A fading reduction technique, International Journal of Advanced Research in Computer Science and Software Engineering, 2 (2012), 58-61

The purpose of the present study is to investigate the effect of blockage at the leading edge of cavity by using PIV which is to collect the u and v velocity profile data for each blockage in the cavity.
In Fig. 1, one example of image was included and also the validation data with previous researcher with the same experiment environment without any blockage to prove the experiment result [6].
(a) (b) Fig. 2 (a) Example of cavity image with blockage and (b) Validation data compared with S.M.
At leading edge, there are no clear different data to compare in the cavity but at the above, the vortex seems to be high for any kind of blockages.
Mean velocity profile data have been gathered throughout the cavity within four sections.

The experimental setup allows for precise control of drying parameters, facilitating accurate data collection.
The study on drying kinetics pointed out that the Weibull model best fitted to drying kinetics data.
Data Measurement The performance of the dryer must be assessed using the following crucial metrics: Ambient temperature Ta: The average temperature will be measured with a Dallas temperature sensor to determine the overall temperature increase during the drying process.
Teklehaymanot, “Data on drying kinetics, moisture sorption isotherm, composition study of Ethiopian oyster mushroom (Pleurotus ostreatus mushroom) drying in tray dryer,” Data Br., p. 110861, 2024, doi: 10.1016/j.dib.2024.110861
Mei, “Rolling-horizon dispatch of advanced adiabatic compressed air energy storage based energy hub via data-driven stochastic dynamic programming,” Energy Convers.

Data analysis showed that there was a converse “U” type relationship between industrial water demand and industrial value added.
Data sources and select sample data Industrial value added data was from the "China Statistical Yearbook".
Industrial water demand data was from the Ministry of Water Resources, "Water Resources Bulletin".
We applied historical data from 2001 to 2013 to model industrial water recycling rate.
The industrial structure and policy factor was not included as variables in the model due to limitations of data.

The new method is applied on thermal error modeling for a CNC turning center and two groups of new measured data are used for model validation.
The PLSNN has good fitting capability for the modeling data.
For this reason, another two groups of new data were also measured in this experiment for the model validation.
For testing data 1, the maximal prediction residual is 4.17 μm, and the average of residuals in absolute value is 1.96 μm; for testing data 2, the maximal prediction residual is 4.09 μm, and the average of residuals in absolute value is 1.90 μm.
Model performance of PLSR, D-MRA, V-MRA, D-NN, V-NN and PLSNN is compared based on the modeling and testing data.

IoT systems empower the comprehensive collection of data pertaining to various aspects of road infrastructure.
This invaluable data serves as the foundation for the development of innovative strategies aimed at curbing urban pollution [15].
Alternatively, employing cameras with integrated embedded PCs, such as the LTM sensor, enables on-site data processing.
These systems offer real-time data, forecasting capabilities, and the identification of vehicles parked in unauthorized zones.
Such data informs city planning and infrastructure development, leading to more efficient urban designs and transportation systems.

Introduction The rise of Additive Manufacturing (AM) offers new opportunities such as cost reductions and freedom of manufacturing, depending on the type of the component.
Secondly, the size of the cavity was limited because of the torch accessibility, giving a limited mass reduction (34%) compared to design expectations (around 50%).
By using the manufacturing with 8 dof robotic cell, the closing of the cavity has been improved and the design expectation was met by significant 49% reduction of mass compared to a full blade.
The application of this methodology helped to realize the hollow propeller blade in one set-up and an expected mass reduction, which would have been impossible without multi-axial toolpath.
References [1] ISO/ASTM 52900, « ISO/ASTM 52900:2015 », ISO. https://www.iso.org/cms/render/live/fr/sites/isoorg/contents/data/standard/06/96/69669.html

Neutralization of Ion Beams for Reduction of Charging Damage in Plasma Etching A.
The available data for the spread of parameters were chosen in the worst-case scenario.
Finally, we combined surface and gas phase neutralization and compared the results to the experimental data from [8].

Computational experience on randomly generated data sets and an industrial case shows that improved genetic algorithm gives superior results than the genetic algorithm without improving for storage location assignment with ordering restriction.
The problem can be defined as: given P cargos, their average demand and planned inventory levels for T periods and the layout of the storage area divided into lattice of storage locations, the problem is to establish classes of products and allocate them to storage locations so that the total cost of order picking and storage space is minimized in a single command warehouse exploiting the reduction in area because of clubbing the parts into classes.
Computational experience on randomly generated data sets shows that superior crossover and mutation operators play a very important role in the performance of the GA.

Biosorption equilibrium data were best described by Langmuir isotherm model.
Conventional methods for removing metals from aqueous solutions include chemical precipitation, chemical oxidation or reduction, ion exchange, electrochemical treatment, reverse osmosis, membrane technologies and evaporation recovery.
Based on the correlation coefficient R2, it is clear that both the Langmuir(Fig 4) and Freundlich(Fig 5) isotherm models fitted with the experimental data well, and the former model was a better fit than the latter.