esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Applications and Simulations
### Data Storage and Retrieval
#### 6.2.4 Performance  
We have carried out simulations to insert \(10,000\) data generated by a set of randomly chosen nodes for Model 1. Each datum has a value ranging from zero to 100. Figure 12 shows the distribution of the loading factor, _i.e._, the ratio of the actual load to the ideal load, where the ideal load is achieved when the data are evenly distributed over all nodes in the network. As can be seen, the loading factor is nicely distributed, where more than 40% of nodes enjoy a perfect loading factor of one, signifying well-balanced traffic among sensor nodes.
# Solving the Container Relocation Problem by Using a Metaheuristic Genetic Algorithm
## 4 A New Method for CRP Resolving Based on Genetic Algorithm  
### Genetic Algorithm  
As mentioned earlier, the genetic algorithm is a nature-inspired metaheuristic algorithm based on a process of natural selection. Nature-inspired metaheuristic algorithms generally find a solution to a given problem that is close to the optimum in a short time, thus speeding up the process of finding a good enough solution. It cannot be said with certainty that the solution is the best, since these algorithms have not searched the entire solution space given the speed at which a solution is found. However, the relationship between the speed at which a solution is found and the goodness of the solution found argues for the use of these algorithms in solving NP-hard problems such as the CRP. As stated before, the genetic algorithm finds a solution to a given problem by imitating the process of natural selection. At the beginning of the solution finding process, a sample set of potential solutions (chromosomes) is randomly generated. This set is called the initial population. Each solution in the population is called a chromosome. A chromosome consists of a set of genes. A gene is part of an overall solution that represents the chromosome. To evaluate how well each chromosome (i.e., its genes) represents the solution to the optimization problem, a fitness function must be defined to determine the goodness of each chromosome (solution). To have the process of natural selection work, each chromosome contains the same genes and the same number of genes [10]. In order to obtain better solutions in the next population of chromosomes, the basic operators of the genetic algorithm must be applied to the chromosomes of the previous generation. Selection, crossover and mutation are the basic operators of genetic algorithm. Selection selects better chromosomes from the previous population that will be part of the next generation. The operator crossover crosses two chromosomes from the previous population to create a better chromosome (solution) for the next generation. Crossing of two good chromosomes promotes the creation of child chromosomes that are better than their parent chromosomes. Mutation involves changing one or more genes within a chromosome to eventually find a better chromosome. The pseudo code of the genetic algorithm is shown in Algorithm 1.
# Multi-User Detection Based on Improved Cheetah Optimization Algorithm
## 3 Results and Discussion  
### Initialization Parameter Test of the Algorithm  
The experiments are based on the improved HCO algorithm for multi-user detection, using direct expansion system communication signals. The signal-to-noise ratio is set to 5 dB, and the stable distribution model is employed to model the complex impact noise. By determining the model parameters and superimposing the signals, signal data containing noise are generated. According to Equation (3) and the noise requirements of this paper, the specific model parameters are set as follows: set \(\alpha\) to 1.6. \(\beta\) uses the default value of 0. \(\gamma\)is obtained by calculating the variance of the noise signal and the standard deviation of the signal, and the center of the distribution can be dynamically adjusted to adapt to different situations. \(\mu\) uses the default value of 0. The experimental verification is carried out in the case of 10 users, with each user having the same signal power. The data signal has a length of 10,000 bits, and the loop iterates eight times. The relationship between the change in the initialization parameter and the BER is shown in Figure 4.  
The simulation experiment results demonstrate that the optimal values of T1 and mod in the initialization parameter T = ceil(dim/10) \(\times\) T1 of the algorithm are 0.52 and 0.34, which have the least effect on the BER. The simulation plot of the maximum and minimum values of the scaling factor (beta) of the hybrid algorithm indicates that the effect of the randomly generated scaling factor is optimal when the upper limit is in the vicinity of 0.3 and the lower limit is in the vicinity of 0.1, which has the least impact on the detection BER. Several parameters involved in this algorithm also have a very small impact on the BER, fluctuating within 0.01%, and demonstrate adaptive adjustment capability.
## 6 Conclusions  
This work is motivated by the newly emerging multicarrier satellite communication services at the VHF band that require linear and power-efficient PAs in their transmitters. Therefore, a solution to reduce envelope distortion in high efficiency and wide fractional bandwidth polar-mode PAs was described and tested to meet the demands of the satellite transmitters used in this application. Additionally, a hybrid EA (linear and switchmode power stages combination) that was also based on GaN HEMT technology was developed to verify the functionality of the system.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Channel** & \multicolumn{2}{c}{**EVM**} & \multicolumn{2}{c}{**ACPR**} & \multicolumn{2}{c}{**Channel \(P_{\text{OUT}}\)**} & \multicolumn{2}{c}{**Combined \(P_{\text{OUT}}\)**} & \multicolumn{2}{c}{**Power**} & \multirow{2}{*}{**PAE** *} \\
**Frequency** & **RMS** & **Peak** & **Lower** & **Upper** & **Mean** & **Peak** & **Mean** & **Peak** & **Efficiency*** \\ \hline
120 MHz & 0.57\% & 1.22\% & \(-51.2\) dBc & \(-47.4\) dBc & 35.8 dBm & 38.4 dBm & & & \\
123 MHz & 0.76\% & 1.59\% & \(-50.3\) dBc & \(-48.5\) dBc & 35.6 dBm & 38.8 dBm & 41.6 & 49.8 & 42\% & 40\% \\
128 MHz & 0.67\% & 1.40\% & \(-50.4\) dBc & \(-48.6\) dBc & 35.7 dBm & 38.2 dBm & dBm dBm & dBm & & \\
130 MHz & 0.48\% & 0.86\% & \(-50.6\) dBc & \(-50.2\) dBc & 35.5 dBm & 38.7 dBm & & & \\ \hline \hline \end{tabular}  
* Power efficiency and PAE figures for combined overall performance of EA and RF PA.  
\end{table}
Table 1: Summary of P-RFPA linearity and power performance for a 4C-CH VDL-T signal.  
The demonstrator for the VHF HCVS class-D PA operating in polar mode in combination with the proposed EA was tested for wide fractional bandwidth multicarrier analog and digitally modulated signals, yielding good linearity and power efficiency figures. This shows that the proposed idea of using a GaN-based HCVS class-D topology for RF PA design is a feasible way to mitigate the nonlinearity issues concerning these polar-mode PA architectures when high-performance EAs (also built with GaN devices) are used for modulating its power supply port. Furthermore, these results show that the proposed system did not require the use of DPD techniques, as other PA architectures (e.g., Doherty PAs) usually do, considering the overall power efficiency and the demanding linearity nature of the modulated multicarrier signal envelope.  
Conceptualization, M.P.-G. and F.-J.O.-G.; methodology, M.P.-G.; software, M.P.-G.; validation, M.P.-G. and F.-J.O.-G.; formal analysis, M.P.-G. and F.-J.O.-G.; resources, F.-J.O.-G.; writing--original draft preparation, M.P.-G.; writing--review and editing, M.P.-G. and F.-J.O.-G.; supervision, F.-J.O.-G.; project administration, F.-J.O.-G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
## 4 Discussion
### Comparisons with Previous Work  
As a review of previous TSASs successfully implemented in aviation, there are several types of vibrotactile displays to cue situation information for pilots [3; 18; 39]. The comparison between their and our work on actor cued is illustrated in Table 6.  
The TSAS developed by the US Navy consists of 40 tactors, and was successfully implemented to cue flight attitude with a resolution of five degrees [3]. In this TSAS, different attitude angle ranges were cued by different actors, and fine angle intervals in each range were indicated by corresponding intensity levels (i.e., LI coding method). The belt-type TSAS consisted of eight tactors, designed by [PERSON] et al. and can only be used to indicate the four basic flight states as shown in Figure 3b. In this TSAS, different flight states were indicated by different vibration locations [18]. As similar with the belt-type TSAS, the TSAS in literature [39] utilized the 60 torso tactors, with each ring mapped to at  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**TSASs** & **Tactor Arrangement** & **Number of Used Tactors** & **Coding Methods** & **Resolution /Degree** \\ \hline This work & 4 \(\times\) 5 matrix vest & 20 & Coding with LRM & 5 \\
[3] & 8 \(\times\) 5 matrix vest & 40 & Coding with LI & 5 \\
[18] & 8-tactor belt & 8 & Coding with L & Simple information \\
[39] & 60-tactor jacket & 60 & Coding with L & 30 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Performance comparison between our work and previous TSASs.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Source** & **Quadratic Sum** & **Dof** & **Mean Square** & \(F\) & **Sig** \\ \hline States & 0.019 & 3 & 0.006 & 0.197 & 0.898 \\ Locations & 0.281 & 3 & 0.094 & 2.970 & 0.032 \\ Rhythms & 0.109 & 2 & 0.054 & 1.721 & 0.181 \\ States \(\times\) Locations & 0.323 & 9 & 0.036 & 1.136 & 0.337 \\ States \(\times\) Rhythms & 0.121 & 6 & 0.020 & 0.638 & 0.700 \\ Locations \(\times\) Rhythms & 0.049 & 4 & 0.012 & 0.385 & 0.819 \\ States \(\times\) Locations \(\times\) Rhythms & 0.292 & 12 & 0.024 & 0.770 & 0.681 \\ \hline \hline \end{tabular}
\end{table}
Table 5: MANOVA in the preferred coding method.  
least 30 degree of the vertical dimension and each column mapped to 30 degree of the horizontal dimension. The TSAS in current work present attitude information of a similar resolution with the TSAS in literature [3] but using less tactors. Although some TSASs in reported work were also used to cue other situational information such as flight height and drifting direction, which we did not include in the current work, this information can be presented by improving the coding strategies in our current vibrotactile design. It will be discussed in following section.
# Sum Rate Optimization Scheme of UAV-Assisted NOMA under Hardware Impairments
## 1 Introduction
### Contributions and Organization  
Motivated by previous work, the UAV's deployment location and resource allocation were considered in a NOMA communication network with imperfect hardware conditions. Particularly, we focused on a system's sum rate optimization problem subject to multiple ground users' minimum rate threshold and power constraints. Furthermore, UAVs can present flexible deployment and the SIC decoding order changes with the position of the drone. A binary decoding decision variable, which represents channel coefficient relationships between the UAV and ground multi-users, was introduced to this problem. On the other hand, the proposed optimization problem was a mixed integer programming problem that was hard to handle directly. Therefore, we proposed an effective iterative algorithm based on variable substitution, successive convex approximation (SCA) method, and quadratic transform algorithm to handle this problem. Numbers of the simulation results show that the proposed scheme can always achieve the optimal system's sum rate performance in the presence of hardware impairments when compared with other comparison schemes. Finally, the feasibility and effectiveness of the proposed algorithm were proved.
# Targeted Molecular Imaging of Pancreatic Cancer with a Miniature Endoscope
## 2 Materials and Methods
### Miniaturized Endoscopic Imaging System and Scanning Mechanism  
The multimodal endoscopic probe with a size of 1 mm in diameter described in detail before [35] was used to directly reach the surface of the pancreas through a hole in the abdomen of mouse. Here, photoacoustic imaging was performed first, followed by fluorescence imaging. In brief, a double-clad fiber was integrated into the probe to deliver a light beam, which was then focused by a gradient-index (GRIN) lens with a diameter of 0.25 mm and a working distance of 5 mm. A custom-made unfocused ultrasound transducer with a center frequency of 40 MHz and dimensions of 0.6 mm \(\times\) 0.5 mm \(\times\) 0.2 mm was used to detect the photoacoustic signals. The imaging system is schematically shown in Figure 1. The probe was mounted to the stage consisting of a one-dimensional (1D) linear stage and a rotator. A nanosecond-pulsed Nd:YAG pumped Optical Parametric Oscillator (OPO) laser with a repetition frequency of 20 Hz was used as the light source. The light beam, attenuated by a neutral density (ND) filter, was then split into two parts. One part reached the photodiode (PD) module to monitor light intensity in real time for calibration. The other part, shaped by a small iris, was focused by a convex lens (L1); then, the light beam passed through a 100-\(\upmu\)m pinhole for spatial filtering and was coupled into the double-clad fiber in the multimodal endoscopic probe. A data acquisition (DAQ) card (PCI-5124, National Instrument, Austin, TX, USA) embedded in a computer (PC) with 12-bit resolution and a sampling rate of 200 MS/s was utilized as the data acquisition system. Also, an ultrasound receiver (5073 PR, Olympus, Waltham, MA, USA) with an integrated amplifier and a bandwidth of 75 MHz was utilized to receive the photoacoustic signal. The laser exposure was about 8 mJ/cm\({}^{2}\) at the surface of the tissue, which is lower than the American National Standards Institute (ANSI) laser safety limit (20 mJ/cm\({}^{2}\)).  
To minimize the invasiveness associated with the procedure of plugging the endoscopic probe into the abdomen of a mouse, a novel fan-shaped scanning method was developed. As shown in Figure 2, a hole with a size slightly larger than 1 mm in diameter was drilled through the abdomen of the mouse. A volumetric image of the tissue was obtained by scanning the probe through the tissue in a two-dimensional (2D) fan-shaped plane with the hole location as the center. The 2D fan-shaped scanning (20 mm (radius) \(\times\) 60 degrees) was realized through the combination of a linear translation along radial direction (a step size of 30 \(\upmu\)m) and a circular rotation (a step size of 0.3 degree).  
Figure 1: Endoscopic imaging system. ND, neutral density filter; L1, L2, L3, lenses; PH, pinhole; BP, beam splitter; PD, photodiode; DAQ, data acquisition; US, ultrasound.
# An Overview of Material Extrusion Troubleshooting
## 3 Troubleshooting of ME Parts
### Print Quality Problems
#### 3.3.16 Warping  
The corner of the printed object is lifted from the build platform. Warping is often experienced when printing ABS, high-performance polymers (PEEK, and PSU) and semi crystalline polymers (PP and PA), due to an immediate change between the extrusion and the ambient temperature, causing an uneven plastic shrinkage and bend, greasy build surface, and/or infills and walls set too high. Solutions include the following:  
Figure 13: Blobs and zits marks on outer shell surface of the part.  
1. Keep a consistent ambient temperature. An open window or a cold environment will increase the chance of warping. Printing in an enclosed room can reduce the risk of warping. Alternatively, build an insulating chamber around your printer.
2. Keep the build surface grease-free. Cleaning the surface with 90% IPA solution, acetone or a glass cleaner (e.g., Windex).
3. Use a different build surface to increase surface adhesion such as blue tape (refer to 3.1.2: (6) Poor build platform adhesion).
4. Reduce the infill percentage to less than 20%. A high infill percentage increase the stress on the model causing them to warp. Avoid using more than two to three walls in the model or use a brim.
# Deep Learning-Based Secure MIMO Communications with Imperfect CSI for Heterogeneous Networks
## 6 Conclusions  
In this paper, we investigate two types of deep learning-based secure MIMO detectors for heterogeneous networks. In the considered system, the equivalent channel fading matrix of the femto BS is zero-forced through null-space eigenvectors. The BER of the associated user is adopted as the metric to evaluate the system performance. with the help of deep convolutional neural networks, the macro BS produces more accurate CSI. The impacts of system parameters, such as the correlation factor of imperfect CSI, the normalized doppler frequency, the number of antennas are investigated in different setup scenarios. Considerable performance gains can be obtained from the deep learning-based detectors compared with the classical maximum likelihood algorithm.  
The contributions of the authors are listed as follows: model, investigation and writing, D.D. and M.Z.; supervision, X.L., K.M.R. and R.K. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Natural Science Foundation of Guangdong Province (grant number 2018A030313736), Scientific Research Project of Education Department of Guangdong, China (grant number 2017 GKTSCX045) Science and Technology Program of Guangzhou, China (grant number 201707010389), Application Technology Collaborative Innovation Center of GZPYP (grant number 2020 KY01), Project of Technology Development Foundation of Guangdong(grant number 706049150203), the Henan Scientific and Technological Research Project (grant number 182102210307), National Natural Science Foundation of China(grant number 61801165).  
The authors declare no conflict of interest.
# Beam Grouping Based RS Resource Reuse and De-Contamination in Large Scale MIMO Systems
## 2 System Model
### LS-MIMO Model  
When a downlink LS-MIMO system with \(N_{t}\) TX antennas, and \(K\) single antenna receivers (RXs) is considered, the received signal vector at RXs can be represented as follows:  
\[\mathbf{y} = \sqrt{\rho_{t}}\mathbf{Hs}+\mathbf{z}, \tag{1}\]  
where \(\mathbf{y}\) is the \(K\times 1\) received vector for \(K\) UEs, \(\rho_{t}\) is the total TX power for forward link, \(\mathbf{H}\) is the \(K\times N_{t}\) channel matrix between the transmitter with \(N_{t}\) TX antennas and \(K\) RX terminals, \(\mathbf{s}\) is the \(N_{t}\times 1\) TX signal vector, and \(\mathbf{z}\) is the \(K\times 1\) noise (AWGN) vector at the UEs. We only consider the narrowband signal since orthogonal frequency division multiplexing (OFDM) can successfully change  
Figure 1: The high level concept of beam grouping resource reuse (BGRR).  
the wideband signal to the narrowband signal. We assume the transmitter has perfect channel state information (CSI). Note that usually the LS-MIMO system satisfies the condition of \(N_{t}>10K\).
# Low-Cost Digitalization Solution through Scalable IIoT Prototypes
## 3 Materials and Methods
### Hardware  
Numerous solutions can fulfill the requirements and provide a means of performing the machine digitization. The solutions vary in their complexity, scale, robustness, and readiness for implementation in the industrial setting etc. The chosen hardware must enable speeding up the measurement phase of the development. The requirements these solutions must fulfill are given in Section 1:  
* Cost effectiveness--Depending on an application, some solutions do not provide enough benefits to convince decision-makers of their usefulness.
* Implementation simplicity--The solutions should aim to provide quick results because long development and complex implementation demand a level of expertise not present in the SMEs.
* Unobtrusiveness--The normal operation of the factory must not be negatively affected by the solution, so a wireless connection and an installation that does not require extensive changes to the machine are necessary.  
Scalability--The goal of the solution is to provide the digitalization of the entire factory process; therefore, the solution must provide easy vertical and horizontal scalability.
* Security--The security of data is always very important, especially in an industrial context. This requirement is not as important in the prototyping phase of the development, but is paramount in the final version of the solution.
## 3 Experimental Design
### Optical Interference  
For determining the optical interference of close emitters within an OCC system an experiment was developed. The angles \(\beta\) and \(\gamma\) were set to 90\({}^{\circ}\), while the distance \(D\) (between the LED board and the camera) varied. Adjusting the distance \(D\) the test could have three scenarios: a perfect spatial separation between the LEDs among the pictures (pixel distance greater than 10); a limited spatial separation (pixel distance between 6 and 9); and a critical spatial separation (pixel distance less than 5). These link ranges were deduced using Equations (1) and (2), previously validated, with the particular parameters of this experiment, as shown in Figure 6.  
* Distance for perfect spatial separation: 100 cm.
* Distance for limited spatial separation: 140 cm.
* Distance for critical spatial separation: 200 cm.  
Figure 5: Designed LED’s Board with the distances between its elements.  
As shown in Figure 7, the experiment had four phases: Image Acquisition; Image's Region of Interest (ROI) extraction; Image's ROI Masking; and NPSIR Analysis. For this purpose, the board was programmed to turn on the LEDs for each color: blue, green, red and white (the three orthogonal colors at the same time) following the sequence:  
* Only one LED at the time (four combinations).
* Two horizontal LEDs at the time (two combinations).
* Two vertical LEDs at the time (two combinations).
* Two diagonal LEDs at the time (two combinations).
* Four LEDs at the time (one combination).