esa-sceva/satcom-chunk-collection huggingface dataset:
# Dynamic Load Test and Contact Force Analysis of the AERORail Structure
## 3 AERORail Dynamic Load Test and Analysis
### Dynamic Load Identification
#### 3.2.1 5 m Span Dynamic Load Identification
Among them, the existence of two contact force peaks may be caused by the fact that this identification method is equivalent to the equivalent treatment of the actual vehicle moving load; the contact force fluctuation is caused by the coupled vibration of the vehicle-rail, the stability of the algorithm and the fluctuation of the signal itself. The data fluctuation at the head and tail of the curve is caused by the sensitivity of the algorithm to the initial value condition. From the contact force identification results in Figure 13, as the speed increases, the obvious point of the contact force usually appears in the second wave, and positive and negative changes appear, indicating that the relationship between the contact force and the vehicle speed in this span is affected by the passing time of the vehicle. To further analyze the results of the 5 m span to draw more instructive general conclusions, the mean and maximum values of the above results are calculated, and the results are shown in Table 4:  
Except for the abnormal data of 10 km/h, the data at other speeds have a statistical law that decreases with increasing vehicle speed on average. Specifically, it has the following three characteristics: the mean contact force decreases with increasing velocity in an \begin{table}
\begin{tabular}{c c c c c c c} \hline  & **5 km/h** & **10 km/h** & **15 km/h** & **20 km/h** & **25 km/h** & **Mean** & **Maximum Value** \\ \hline mean force (N) & 4137.1 & 706.0 & 3470.1 & 2838.8 & 2241.0 & 2678.6 & 4137.1 \\ max force (N) & 8816.7 & 1610.5 & 7077.2 & 5876.3 & 7736.4 & 6223.4 & 8816.7 \\ \hline \end{tabular} Note: data take absolute value, the same below.  
\end{table} 
Table 4: Statistical characteristics of the 5 m span contact force curve. Figure 13: The contact force identification result of the 5 m span. (**a**) 5 km/h, (**b**) 10 km/h, (**c**) 15 km/h, (**d**) 20 km/h. approximately linear trend; the maximum contact force fluctuates to a certain extent with the change in vehicle speed; there is a weak correlation between the statistical properties of the contact force curve and the vehicle speed.
## 3 Problem Formulation
### System Model  
Consider a set of \(N_{U}\) UAVs, denoted by \(\mathcal{U}=\{U_{1},U_{2},\ldots,U_{N_{U}}\}\), operating in a two-dimensional Euclidean space. These UAVs are deployed to service a dynamically evolving set of tasks over a planning horizon divided into \(H\) discrete stages, indexed by \(h\in\{1,2,\ldots,H\}\). At each stage \(h\), the set of tasks is represented by \(\mathcal{D}_{h}=\{D_{1},D_{2},\ldots,D_{N_{D_{h}}}\}\), where \(N_{D_{h}}\) denotes the number of tasks available at stage \(h\). Each task \(D_{j}\in\mathcal{D}_{h}\) is located at coordinates \((x_{j},y_{j})\) and has an associated workload \(L_{j}^{h}\), which quantifies the amount of service required.  
Additionally, there are \(N_{S}\) stationary charging stations, denoted by \(\mathcal{S}=\{S_{1},S_{2},\ldots,S_{N_{S}}\}\), located at fixed positions \((x_{S_{U}},y_{S_{L}})\) for \(k=1,2,\ldots,N_{S}\). Each charging station has a charging rate \(r_{\text{charge}}\) and a capacity limit \(C_{\text{max}}\), which restricts the number of UAVs that can charge simultaneously. UAVs are initially stationed at designated charging stations and must return to a station for recharging when their energy levels are insufficient to continue their tasks.  
The distance between any two points \(p_{m}=(x_{m},y_{m})\) and \(p_{n}=(x_{n},y_{n})\) (where \(p_{m},p_{n}\) may represent tasks or stations) is given by the Euclidean distance:  
\[d_{m,n}=\sqrt{(x_{m}-x_{n})^{2}+(y_{m}-y_{n})^{2}}. \tag{1}\]
# A Two-Stage Automatic Container Code Recognition Method Considering Environmental Interference
## 3 Methodology
### Step 2: The Framework of CCR: C-DeepLabv3  
#### 3.3.2 Improved ASPP  
The ASPP module is composed of multiple atrous convolutions with different dilation rates and Spatial Pyramid Pooling (SPP). The atrous convolution is used to extract multi-scale features from the feature map output by the backbone network, and the features are fused and processed through the SPP module to obtain richer contextual semantic information.  
Compared with standard convolution, atrous convolution has an additional hyperparameter called dilation rate, which can adjust the receptive field of the atrous convolution, so that the receptive field of the atrous convolution is increased and more details are retained without increasing the computational burden. The atrous combination rate of DeepLabv3+ is (6, 12, 18), which can perform fine segmentation of large-scale targets. However, the single container number character belongs to a small target, so the original DeepLabv3+ has an incomplete effect in the CCR task.  
Therefore, the algorithm introduces a new atrous convolutional branch. Moreover, the atrous combination rate is adjusted to (3, 6, 9, 12), so that the network can alleviate the problem of information loss and rough detection of category boundary and can recognize and retain more details of the container number character. Figure 4 shows the comparison of the ASPP module before and after modification.  
Figure 4: Comparison of ASPP (the ASPP before modification is displayed on the left, and the ASPP after modification is displayed on the right).  
Figure 3: The overall structure of improved C-DeepLabv3.
## 2 Materials and Methods
### Hardware  
#### 2.1.1 3D Printing  
3D printing [20], also known as Additive Manufacturing (AM), is already being adopted for rapid prototyping and manufacturing. Recently, cheaper and faster AM techniques have been developed for high-quality printing. There are several types of 3D printing [21], such as fused deposition modeling (FDM), stereolithography (SLA), digital light processing (DLP), selective laser sintering (SLS), direct metal laser sintering (DMLS), electron beam melting (EBM) and laminated object manufacturing (LOM). Among these, FDM [19] is one of the most widely used additive manufacturing processes to manufacture prototypes and functional parts in common engineering plastics. This process is based on the extrusion of thermoplastic filaments, which are heated through an extruder and a nozzle, deposited in layers on a platform to build parts, layer by layer, from a digital model of the part. The simplicity, reliability, and affordability of the FDM process have made additive manufacturing technology widely recognized and adopted by industry, academia, and consumers.  
Thermoplastic filament is the material used for extrusion in the fused deposition modeling process. Through the FDM process, both are melted and then extruded through a nozzle to form the layers that create the final part [22; 23; 24; 25; 26]. There are several types of filaments, and the most commonly used filaments in 3D printing [27] are: polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) and polyethylene terephthalate glycol (PETG). PLA [27; 28] has the highest surface hardness, is the most difficult to finish if needed, produces the best results with proper cooling, has a low thermal shrinkage, and produces no odor during printing. This is ideal for 3D printing where aesthetics are important. Due to its lower print temperature, it is easier to print with, and thus more suitable for parts with fine details, producing the best results with proper cooling. The printing of the proposed robotic arm structure was performed with a PLA filament due to its characteristics, properties and good results achieved by others in the literature when developing robotic arm structures with a PLA filament.  
Applications of 3D printing apply to several areas: healthcare [29], food processing [30], electrochemical energy [31], musical instruments [32], robotic grippers [33], automotive applications [34], microwave applications [35], pharmaceutical applications [36], environmental applications [37] and microsatellite creation [38].
# Evaluation of IEEE802.15.4g for Environmental Observations
## 4 Analysis
### Advanced Metering Infrastructure Scenario
#### 4.4.2 RX at 400 m  
Figure 14a depicts the PDR values for short packets. 2 FSK-FEC-50 and O-QPSK PHYs present PDR values above 75%. The rest of the PHYs do not have any reliability, PDR values are zero. OQPSK-12.5, OQPSK-25 and OQPSK-50 have 98% PDR. In Figure 14b is shown the PDR for 2047 B packets. The PDR of 2 FSK-FEC-50 decays below 20% while the PDR of OQPSK-50 is still high, at 78%. Therefore, the radio setting with the highest reliability for short and long packets is OQPSK-50 and we highlight it.  
Figure 14: AMI, 400 m. It is normal to have several buildings and any other kind of obstacles between nodes. Having these conditions, the most useful radio setting is OQPSK-50. (**a**) PDR values with packets of 127 B. OQPSK-12.5, OQPSK-25 and OQPSK-50 have 98% PDR. We see that the most advantageous of that group is OQPSK-50, offering same reliability with higher data rate; (**b**) PDR values with packets of 2047 B. OQPSK-50 offers the highest reliability, 78%, between the 5 radio settings with non-zero PDR; (**c**) Maximum amount of TX short packets under 0.1% duty cycle regulation. O-QPSK-50 can send up to 90 short packets, more than any other radio setting; (**d**) Maximum amount of TX long packets under 0.1% duty cycle regulation. OQPSK-50 is able to send up to 8 long packets within one hour; (**e**) Average electric charge consumed per packet of 127 B transmitted. OQPSK-50 consumes on average, 3.4 mC per packet transmitted; (**f**) Average electric charge consumed per packet of 2047 B transmitted. OQPSK-50 is the less electric charge-hungry radio setting, consuming 37 mC per packet transmitted.  
Figure 14c shows the maximum number of short packets that can be transmitted. The radio setting that can transmit more packet within one hour is OQPSK-50 with roughly 90 packets. Now considering long packets, see Figure 14d, OQPSK-50 is still the PHY with a maximum of 8 possible packets per hour. Ergo, in order to maximize the throughput of the nodes and being compliant with the duty cycle regulation, OQPSK-50 is the most convenient.  
It is depicted in Figure 14e the average electric charge consumed per short packet transmitted. The less power-hungry is the OQPSK-50 PHY, with 3.4 mC. Similarly, Figure 14f shows the electric charge consumption for long packets. The tendency is maintained, OQPSK-50 consumes the less amount of electric charge per 2047 B packet, with 37 mC. Thus, OQPSK-50 is the more electric charge-efficient PHY for this scenario, despite of the length of the packet.
# Energy Efficient Dynamic Symmetric Key Based Protocol for Secure Traffic Exchanges in Smart Homes
###### Abstract  
Highly sensitive information about people's social life and daily activities flows in smart home networks. As such, if attackers can manage to capture or even eavesdrop on this information, the privacy of the users can be compromised. The consequences can be far-reaching, such as knowing the status of home occupancy that can then facilitate burglary. To address these challenges, approaches such as data aggregation and signcryption have been utilized. Elliptic curve cryptography, bilinear pairing, asymmetric key cryptosystem, blockchain, and exponential operations are among the most popular techniques deployed to design these security solutions. However, the computational, storage and communication complexities exhibited by the majority of these techniques are too high. This renders these techniques unsuitable for smart home components such as smart switches and sensors. Some of these schemes have centralized architectures, which present some single points of failure. In this paper, symmetric key authentication procedures are presented for smart home networks. The proposed protocol leverages on cryptographic primitives such as one-way hashing and bitwise exclusive-Or operations. The results indicate that this scheme incurs the lowest communication, storage, and computation costs compared to other related state-of-the-art techniques. Empirically, our protocol reduces the communication and computation complexities by 16.7% and 57.7%, respectively. In addition, it provides backward key secrecy, robust mutual authentication, anonymity, forward key secrecy, and unlinkability. Moreover, it can effectively prevent attacks such as impersonation, session hijacking, denial of service, packet replays, man-in-the-middle, and message eavesdropping.  
Keywords:anonymous; authentication; attacks; IoT; privacy; security; smart homes; symmetric key +
Footnote †: journal: _Applied_
## 7 A Compact Sequentially Rotated Circularly Polarized Dielectric Resonator Antenna Array  
In this paper [6], the authors propose a compact 2 \(\times\) 2 dielectric resonator antenna (DRA) array having sequentially rotated (SR) circularly polarized (CP) characteristics. To obtain the CP radiation, a rectangular dielectric resonator (RDR) is coupled with an elliptical slot (ES). In addition, The SR feeder can maximize the transferred power to each element using four quarter-wavelength microstrip transformers. To validate the proposed antenna, the authors compared the measured results with the simulated results. The results demonstrate that the proposed antenna achieved the axial ratio bandwidth of 0.95 GHz and matching bandwidth of 1 GHz.  
Polarization and Incidence Angle Independent Low-Profile Wideband Metamaterial Electromagnetic Absorber Using Indium Tin Oxide (ITO) Film  
[PERSON] et al. [7] proposed a metamaterial electromagnetic (EM) absorber with a high absorbance in a wide frequency range using indium tin oxide (ITO) which is one of the representative resistive materials. The proposed absorber has insensitive characteristics for polarization and incidence angles due to symmetrical split ring resonators made of ITO film. The proposed absorber with a size of only 0.171 \(\lambda\) shows a wideband absorbance from 7.2 GHz to 27 GHz, with a 90% absorption criterion.  
A Cross-Correlation-Based Approach to Pattern Distortion and Mutual Coupling for Shared-Aperture Antennas  
In this paper [8], a pattern distortion coefficient is proposed as a new figure of merit to quantitatively estimate both mutual coupling and pattern distortions for multi-antennasystems. The proposed coefficient is expressed by a cross correlation between unaffected and affected far-field patterns of antennas under test, and the input pattern of a weighted Gaussian function is used to consider the target operation angle. To validate the feasibility of the proposed antenna, a two antennas system which is composed of an inverted-F antenna and a microstrip patch antenna is utilized. Through the results, the authors demonstrate that the proposed figure of merit well describes the amplitude and phase distortions caused by mutual coupling and platform effects.  
Design of a Printed 5G Monopole Antenna on Vehicle Window Glass Using Parasitic Elements and a Lattice-Structure Reflector for Gain Enhancement  
[PERSON] et al. [9] proposed a novel design of a printed 5G monopole antenna on a vehicle window glass. The proposed antenna is composed of a coplanar waveguide (CPW), a monopole radiator, parasitic elements, and a lattice-structure reflector. To improve the bore-sight gain, the parasitic elements are located at either side of the monopole radiator. The lattice-structure reflector can solve the pattern distortion problem caused by the thick vehicle window glass. The authors measured and fabricated the proposed antenna, and the results confirm that the enhancement of the bore-sight gain and the minimization of the pattern distortion.
## 4 Results
### Principal Component Analysis (PCA)  
For a total of six datasets, PCA is applied on the four convolutional-related features to retain only the principal components of the extensive number of features. To decide on the ideal number of components, a scree graph is used. It is a line graph between variance and number of components. By observing the scree graph, the elbow value corresponding to the X-axis beyond which there is negligible decrease in variance is chosen as the ideal value. Figure 9, for instance, shows the scree graph for the ASL alphabet on convolutional features.  
In Figure 9, the X-axis indicates the number of PCA components, whereas the Y-axis indicates the decrease in variance for that specific count of PCA components. It is evident from Figure 9 that 10 is the ideal number of PCA components since beyond this value there is negligible decrease in variance. In the presence of multiple elbows, however, an approximate value is taken as the ideal count. Table 9 outlines the ideal number of components for all the datasets.  
Figure 8: CNN architecture—NUS II dataset.  
Figure 7: CNN architecture—NUS I dataset.  
Figure 9: Scree graph on convolutional features-ASL alphabet.
## 2 IM/DD Fast-OFDM-CDMA System Architecture  
Figure 1 depicts the architecture of the proposed Fast-OFDM-CDMA system based on a cost-effective IM/DD technique for an amplifier-free upstream PON configuration. The system architecture includes an optical line terminal (OLT), the SSMF channel, a coupler, and the optical network unit (ONU).  
The data sent by the user to the ONU side is mapped to a symbol according to the selected constellation mapping schema (i.e., 16 QAM), then transferred to the Fast-OFDM subcarrier block for subcarrier selection. The total number of subcarriers selected for the system is equal to 64 subcarriers, but to meet the Fast-OFDM requirement only half of the frequency spacing among subcarriers is considered. Then, the mapped user signal from the Fast-OFDM subcarrier block is multiplied by the OCDMA signature generated by the OCDMA encoder, and sent to the optical modulator to convert the electrical signal to the optical one.  
On the OLT block, the received signal is converted from optical to electrical thanks to the optical demodulator. Then, the generated signal is multiplied by the desired signature provided by the OCDMA decoder, and the Fast-OCDMA subcarrier decoder is applied to restore the symbol. Finally, the symbol is de-mapped to restore the emitted user data.
# Experimental Evaluation of Display Field Communication Based on Machine Learning and Modern Design
## 5 Experimental Evaluation  
The experiments were performed in an indoor lab environment. The experimental devices and default parameters are mentioned in Table 1. In addition, as shown in Table 3, the original input image size is \(256\times 256\) pixels. The data are embedded in the image using addition and power allocation. For the power allocation, note that the value of \(\alpha\) is chosen to be a variable in the range \(0<\alpha<1\) based on the PSNR. By adjusting the value of \(\alpha\), we can get reliable performance with respect to PSNR. After data embedding, the image is displayed on an electronic display of resolution \(1920\times 1080\) pixels. Then, the image was captured using the iPhone XS Max with a 12 MP rear camera. As the captured image has background clutters, the display area was extracted from the captured image using the techniques mentioned in the previous sections. The extracted image is then resized to its original size and the data are decoded.  
In the case of conventional DFC [10], we have considered the Gaussian noise channel. However, in the real practical experiment, note that the noise may not be exactly Gaussian. Moreover, there is a lot of corruption from the real optical wireless channel. Hence, in the following sections, we first analyze the behavior of real practical noise observed in an actual wireless D2C link, and then evaluate the performance of our proposed scheme based on various system design parameters including the transmit image size, distance between display and camera, camera angle, and image rotation. Furthermore, apart from the Lena image, we will also use other standard images and check the performance of our scheme.
## 4 Case Study
### Results and Analysis
#### 4.2.2 Sensitivity Analysis  
In order to test the sensitivity of the improved universal gravitation algorithm to the parameters of the model, the recovery rate and recovery price were taken as the analysis quantities. For the recovery rate, four cases of 10% reduction, 5% reduction, 5% increase and 10% increase were simulated on the basis of the original setting, which were compared with the original results, as shown in Table 15.  
The results show that when the recovery rate decreases, the site selection of recycling facilities basically remains unchanged. When the recovery rate of each recovery station increases by 5% and 10%, the possibility of alternative city 6 as the facility site is greatly increased. Through comparison, it can be seen that once the recovery rate changes, the site selection of recycling facilities will also change accordingly. However, the existing  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**The Ordinal Number of the Pareto Solution** & **Recovery of Benefits (Yuan)** & **Carbon Emission (kg)** \\ \hline \(1\) & 205,302,443 & 4,020,005,113 \\ \(2\) & 205,312,161.2 & 3,991,128,213 \\ \(3\) & 205,243,776 & 4,194,329,  
cities that have established logistics facilities have little change, and the main change is the construction of logistics facilities in remote areas.  
To test the sensitivity of the improved gravitation algorithm to the parameters of the model, the facility capacity was taken as the analysis quantity. According to the facility capacity, four scenarios of 20% reduction, 40% reduction, 20% increase and 40% increase were simulated on the basis of the original setting, which were compared with the original results, as shown in Table 16.  
The results show that when the capacity of recycling facilities is reduced, the number of cities with recycling facilities will increase significantly, which brings about the change of transportation routes. When the capacity of each recycling facility increases by 20% and 40%, the number of recycling facilities will be reduced and fixed gradually, and transportation carbon emissions and transportation costs will also have corresponding changes. In conclusion, although the change of the capacity of recycling facilities will also have an impact on the site selection of recycling facilities, the recycling benefits will not have a large fluctuation.
# A Flower-Shaped Miniaturized UWB-MIMO Antenna with High Isolation
## 2 The Proposed Antenna System  
### Antenna Geometry  
Figure 1 depicts the topology of the proposed dual-port, flower-shaped UWB-MIMO antenna system, and Figure 2 shows the fabricated prototype. Compared with the antennas reported in [3; 6; 8; 9; 11; 12; 14], the MIMO antenna system proposed in this study has a smaller size of 30 \(\times\) 18 mm\({}^{2}\) (0.84\(\lambda\)\(\times\) 0.50\(\lambda\)), and was designed on an FR4 substrate with 1.6 mm thickness (tan\(\delta\) = 0.02 and \(\varepsilon\)\(\tau\) = 4.4). Two similar flower-shaped radiating elements and a metal ground make up the overall antenna model. Each flower-shaped radiating element directly supplied by a microstrip line is made up of three elliptically shaped patches set above the substrate, each at an angle of 60 degrees from the others. Next, improved and inverted L-shaped branches with mirror symmetry and an I-shaped stub above L-shaped branches are added to create a T-like branch at the bottom of the substrate and above the rectangular floor, thereby establishing the proposed ground structure with a rectangular floor. The role of the T-like branching in this design is comparable to that of the ladder resonator proposed in [16], which will effectively block or absorb the surface current between the patch antenna elements at the operating frequency, thereby reducing the mutual influence. The specific design process and principle are described below. The parameters of the proposed dual-port UWB-MIMO antenna are listed in Table 1.  
Figure 1: The proposed dual-port, flower-shaped UWB-MIMO antenna system structure.  
Figure 2: Fabricated prototype of the proposed dual-port, flower-shaped UWB-MIMO antenna: (**a**) front view, (**b**) back view.