esa-sceva/satcom-chunk-collection huggingface dataset:
# MAC Layer Protocols for Internet of Things: A Survey
## 3 Long Range MAC Layer Protocols
### SigFox
The uplink modulation is D-BPSK, the bit rate can be 100 bps or 600 bps according to the regional rules and the transmission power can go up to 22 dBm EIRP at radio configuration zone number two (RCZ2). The topology followed by Sigfox is simple. It follows a star topology approach around the world. Objects transmit their messages to a SigFox base station. Point to point links connect a Sigfox base station to its Internet database and so, after receiving and decoding the message, data are sent to its internet database. Finally, SigFox cloud backend pushes the messages to the customer servers and IT platforms through APIs (Application Programming Interface). Downlink communication procedure is triggered by the network node and therefore cannot be transmitted to the device at any time. Devices open their reception widow after a transmission, in order to receive the downlink packets. When the device needs to receive a downlink message, a flag is set in the uplink message requesting the sending of a downlink message. Only after this flag is sent will the device be ready to receive its downlink message during the interval of a time window that is set for receiving downlink messages. This procedure characterizes the sending of a downlink message to a specific device. To receive the broadcast messages, the nodes have a default time window for waiting to receive broadcast messages. This receiving window opens after the transmission of every uplink message. This procedure reduces the power consumption without communication requests, which exempts the use of network communication control. This makes the protocol simpler and allows greater network capacity. Without the need for traffic signaling and control in the MAC layer, the nodes are free to transmit at any time by simply going out of the sleep mode, transmitting and returning to the sleep mode. The transmission is then repeated two more consecutive times in random carriers in order to avoid collisions increasing capacity and scalability. Other aspects that contribute to the low power consumption are the fact that the message payload has only 12 bytes prolonging the life of the batteries of the element, reducing the cost of the nodes, and the low number of transmission per day. The modulation technique combined with a few hundred Hertz occupying its operational frequency band leads to high spectral efficiency. The small bandwidth used in the frequency spectrum available also contributes to the high capacity of the system. Due to its high reception sensitivity at the gateway and ability to transmit with a considerable level of power, Sigfox technology reaches a high link-budget. It is also possible to improve its performance adjusting its irradiating system [83; 116].
## 7 Cluster Analysis
### ICT and Internet Use  
For the cluster analysis of the use group of variables, cluster 1 stands out, with Beijing and Shanghai (shown in red in Figure 4) showing the highest ICT use in terms of mobile phone subscribers and phone penetration rate, as evident from the cluster center values in Table 9. This is expected given their status as the technological centers of the country. Following these two megacities, in cluster 2 (in yellow) are eastern coastal provinces and the central provinces of Chongqing and Ningxia. This cluster is characterized by the highest ranking of all broadband subscribers to the internet, but it is lower in mobile internet flow and phone penetration compared to the first cluster. The inclusion of Ningxia in this cluster is unexpected given its relatively low levels of urbanization and economic development.  
Figure 4: Clusters of ICT and internet use, China, 2020.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Cluster Number**} \\ \cline{2-6}  & **1** & **2** & **3** & **4** & **5** \\ \hline Number of domain names per capita & 0.17 & 0.06 & 0.02 & 0.03 & 0.004 \\ Mobile phone base stations (100,000) per capita & 0.11 & 0.07 & 0.08 & 0.06 & 0.15 \\ Capacity of mobile phone exchange per capita & 4.27 & 2.60 & 2.06 & 1.85 & 7.73 \\ Optical cable lines (km) per area (km\({}^{2}\)) & 28.83 & 113.42 & 12.43 & 11.16 & 0.21 \\ Number of provinces & 1 & 1 & 16 & 12 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 8: K-means clusters of digital infrastructure, China 2020.  
Clusters 3 and 4 (in blue and purple, respectively, in Figure 4), located in the nation's center and north and comprising two-thirds of the provinces, have relatively moderate-low ICT use compared to the first two clusters, reinforced by the middling cluster center values shown in Table 9. Cluster 5 (in green), consisting of Tibet, Qinghai, Yunnan, and Guangxi, has levels of mobile factors similar to clusters 3 and 4, which is not surprising given its average ICT infrastructure, shown in Figure 3. But, the lower adoption of broadband internet indicates that individuals in these regions may rely more on their own mobile data plan to access the internet while on the go, as there is a shortage of urban infrastructure and opportunities like restaurants and shops that provide free Wi-Fi hotspots.
# On the Use of Focused Incident Near-Field Beams in Microwave Imaging
###### Abstract  
We consider the use of focused incident near-field (NF) beams to interrogate the object of interest (OI) in NF microwave imaging (MWI). To this end, we first discuss how focused NF beams can be advantageously utilized to suppress scattering effects from the neighbouring objects whose unknown dielectric properties are not of interest (i.e., undesired scatterers). We then discuss how this approach can also be helpful in reducing the required measured data points to perform imaging. Driven by the relation between the electromagnetic inverse source and inverse scattering problems, our approach emphasizes the importance of tailoring the induced contrast sources in the imaging domain through the utilized incident NF beams. To demonstrate this idea, we consider two recently-proposed NF beams, and simulate them for imaging applications. The first one is a subwavelength focused NF beam generated by a passive NF plate, and the other is a Bessel beam generated by a leaky radial waveguide. Simple imaging examples are considered to explore the potential advantages of this approach, in particular, toward mainly _seeing_ the object of interest, and not the unknown undesired scatterers. The scope of this paper is limited to homogeneous dielectric objects for which the induced total field distributions in the interrogated objects are similar to the incident field distributions (e.g., those that satisfy the Born approximation). Simple inversion results for focused and non-focused beams are presented accompanied by discussions comparing the achieved reconstructed values.  
microwave imaging (MWI); near-field (NF) zone; sub-wavelength focusing; near-field plates; Bessel beams; inverse scattering; inverse source problems +
Footnote †: journal: Sensors
## 2 Speckle Noise Model  
The continuous interactions of the signals with the target surface initiate the inconsistent constructive and distorted noisiness that leads to a granular pattern, known as speckle-noise, obtained in SAR images, which is multiplicative in nature. The speckle noise is relatively affected, like a salt-and-paper noise. Speckle is an assorted exercise but not a noise [38]. The continuous contact of the high-frequency RADAR signals critical pattern of the diffusers usually limits the perspectives of the SAR processing model development and applications. Also, it affects the SAR images.  
The multiplicative nature of the granular form in SAR images can be expressed mathematically as follows [6; 38]:  
\[\mathrm{I}=\mathrm{D}[\mathrm{i}]\mathrm{M}[\mathrm{n}] \tag{1}\]  
where \(\mathrm{D}[\mathrm{i}]\) denotes the desired image and \(\mathrm{M}[\mathrm{n}]\) refers multiplicative noise.
## 5 Results and Discussion
### 100 kHz Windowed Cross-Correlation Analysis  
Example waveforms of the out-of-plane component from the corresponding measurement points in the area of investigation are plotted in Figure 5 for the healthy and disbonded panel respectively. The measurements presented were at the left hand boundary on the centreline denoted by point A in Figure 2. This measurement point lay equidistant between the excitation site and the stiffener.  
From visual comparison, it is evident that there is a significant difference between the two waveforms. The signal measured from the disbonded panel had a higher level of noise than the signal measured from the healthy panel. This is mostly likely due to a difference in the level of backscattered light received. Even by simple visual comparison, the incoming wave is similar. However, by 0.45 ms there is a significant change in the waveforms. The healthy panel shows the reflected wave-packet from the stiffener whereas this is not present in the waveform from the disbonded panel as the wave is transmitted through the disbond.  
To quantify this difference in the measured waves, a windowed cross-correlation analysis was conducted. Starting at 0.21 ms, both waveforms were windowed into respective 100 \(\upmu\)s time windows and the cross-correlation coefficient was calculated. The windows were transposed by 20 \(\upmu\)s forward and the cross-correlation coefficient was once again calculated. The cross-correlation coefficients from this analysis are plotted in Figure 6.  
Figure 5: Waveforms from the left hand boundary of the area of investigation in-line with the disbonded region for each panel—(**a**) Healthy (**b**) Disbonded. The dashed lines denote the section of waveforms that was used for time windowing.  
Figure 6: Moving window cross-correlation coefficient plot.  
The first two time windows show a low value for the cross-correlation coefficient. This is due to random noise mostly being present in these windows. As the wave arrives in the 0.25-0.35 ms time window, the value of the cross-correlation coefficient significantly increases to 0.93 and continues to increase until it peaks in the 0.31-0.41 ms time window at 0.97. It is worth noting that in an installed acousto-ultrasonic system, the cross-correlation coefficient may be higher than this. However, due to two similar panels being used in this experiment and small differences in experimental setup this indicates a good correlation of the two wave forms.  
As the waveforms start to differ due to the reflections, the cross-correlation coefficient starts to reduce significantly. In the 0.47-0.57 ms time window the cross-correlation coefficient was found to be 0.38 indicating a large difference in the waveforms and hence, the presence of the disbonded region.  
This analysis demonstrates that wave transmitted from the excitation site was comparable on both panels during this experiment. For an installed SHM system this technique demonstrates that reflected waves from the stiffener can be used to identify the presence of disbonds.
# Multipoint Thermal Sensing System for Power Semiconductor Devices Utilizing Fiber Bragg Gratings
## 2 FBG Temperature Sensing Principle
### Heat Transfer Model  
In [2], it is assumed that the mechanical stress remains constant throughout the distributed sensitive portion of the FBG sensors. Similarly, this work will adhere to that assumption, ensuring that the reflected wavelength depends solely on the thermal variations along the length of the sensor head. In this research, we employed a three-phase inverter (from SEMIKRON corporation), a renowned manufacturer of power semiconductor devices, including IGBTs, to investigate multipoint temperature sensing for IGBTs in the inverter. The inverter is a multifunctional three-phase inverter with a six-diode packed rectifier and IGBT modules, suitable for different converter configurations, as detailed in Figure 1.  
The heat transfer through the IGBT layers to the sensor interface was modeled to evaluate the thermal behavior of the PSDs arranged on the heatsink. Here, the heat transfer equation for an IGBT module is derived for the direct on-chip sensor placement, the outer casing, and the heatsink. Subsequently, the model is extended to include multiple semiconductor devices, including two IGBTs, and a rectifier module to achieve multipoint temperature measurement.
## 4 Results and Discussion
### Initial Evaluation of ANN Models  
Multiple, multi-layer perceptron, sequential ANN models, with different architectures (varying number of hidden layers and number of neurons in hidden layers) and hyperparameters, are developed and evaluated. The same training dataset and testing dataset are also used for the initial evaluation of ANN models, and the MAPE values of ANN models are calculated using the same procedure (same as described in Section 4.1). In addition to the testing error, the ANN models are also tested with the training data after the models are trained to compute the training error. The purpose of this exercise is to quantify how well the ANN models learn from the training data and their ability to generalize the patterns present in training data. The variation of predicted AAR with experimental results for AAR are presented in Figure 11a,b for the training phase and testing phase, respectively, for one particular ANN model.  
The architecture of this particular ANN model consists of four hidden layers (L = 4) with forty neurons (N = 40) in each hidden layer. This is in addition to five neurons in the input layer (one for each input feature) and one neuron in the output layer (for output parameter, AAR). This particular set of hyperparameters turns out to be the optimum for the ANN model architecture for the problem considered (described in Section 4.6). Based on the comparison of predicted versus experimental AAR, with a MAPE of 0.08 and MAE of 0.053 during the training phase (Figure 11a), it is fair to say the ANN model extracts adequate information from data to build a reasonably good neural network structure during the training phase. The ANN model predictions during the initial testing phase are shown in Figure 11b and the resulting MAPE and MAE on test data are 0.127 and 0.082, respectively. This prediction accuracy places the ANN model superior to all other ML models developed in this study during the initial evaluation and testing phase.
# Parallel Computation for Inversion Algorithm of 2D ZTEM
## 2 2D ZTEM Forward Modeling and Inversion  
### ZTEM Forward Modeling  
According to the convention of the 2D ZTEM problem, the earth is regarded as a Half space conductor (\(z\geq 0\)) and the insulated air layer is above the earth. The electromagnetic field source is above the ground (\(z=-j\)). The ZTEM vertical field is collected in different positions using the MT method, and the horizontal field is the same as in the MT method.  
1. [label=(0)]
2. Math-physical model The Maxwell equation differential form is expressed as: \[\
abla\times E=\mathrm{i}\omega\mu_{0}H\] (1) \[\
abla\times H=\sigma E\] (2)  
Usually, a Descartes rectangular coordinate system is used. The origin of the coordinate is on the ground, the z-axis is straight down, and the y-axis is horizontal. \(E\) is the electric field, \(H\) is the magnetic field, \(\mu_{0}\) is the magnetic conductivity, \(\sigma\) is the conductivity, and \(\omega\) is the angular frequency. There are two polarization models in Maxwell equations.  
We set the height of the helicopter as \(h\), and the positive z-axis is down to the earth in the coordinate system. The tipper \(T\) is as follows:  
\[H_{z}=T_{zx}H_{x}+T_{zy}H_{y} \tag{3}\]  
Because the \(H_{z}\) is only in the TE mode, Equation (3) is simplified as:  
\[H_{x}=T_{xy}H_{y} \tag{4}\]
2. The finite differential method is used to solve the 2D ZTEM forward model problem We use the finite differential method to determine the 2D ZTEM forward modeling problem. The main work of the forward problem is to solve the partial differential equation. We set the boundary condition of the equation, and we can obtain the result of the problem.  
\[Kv=s \tag{5}\]  
\(K\) is the coefficient matrix. \(v\) is the magnetic field. \(s\) is the right vector of the equation. We solve the equation and obtain the magnetic field. Finally, we can obtain the tipper.
# Context-Based Energy Disaggregation in Smart Homes
## 3 Related Work
### Features
#### 3.1.1 Low Sampling Rate  
The choice to work with low sampling rates allows for analyzing steady-state features and provides several advantages from the economic point of view; the hardware required to collect these features has, in fact, a relatively low cost. One of the most investigated feature is the Real Power, which has been defined in the previous section. Several works [14; 15; 16; 17] have tried to use this unique feature to perform disaggregation, especially regarding high-power consuming appliances with distinctive power draw characteristics for which satisfactory accuracy results have been reached. However, in order to distinguish devices with similar consumption traces and handle possible simultaneous state changes, other features should be taken into account [7] too, such as Reactive Power [6; 18].  
Other research works have investigated if further information could allow NILM systems to reach better accuracy results [6; 13; 19; 20]. Such information can be directly measured (_i.e._, Voltage, Current) or derived (_i.e._, power peaks, Power Factor, Root Mean Squared voltage and current,phase differences, _etc._) [7]. Furthermore, in several works [21; 22; 23], a Fourier series analysis has been performed to determine current harmonics, although the low sampling constraint allows for extracting only the lowest ones. These additional features have helped to identify non-linear loads with a non-sinusoidal current trace and to discriminate between loads with constant power and constant impedance [7].  
In most works, data were sampled up to 1 kHz [6; 19], while in [13] and [24], the proposed appliance classification approaches were using samples gathered every 1 and 2 min, respectively.
_Article_  
**Sublethal Injury Caused to _Listeria monocytogenes_ by Natural Plant Extracts: Case Study on Grape Seed Extract and Garlic Extract**  
**[PERSON] 1,2,3, [PERSON] 1,2,3 and [PERSON] 1,2,3,* 2**  
Received: 6 June 2019; Accepted: 1 July 2019; Published: 5 July 2019  
**Featurered Application: Studies focusing on the development of novel (antibacterial) food preservation technologies involving natural plant extracts rarely take into account the sublethal injury induced to bacterial cells. In the current study, sublethal injury caused by two such natural plant extracts (i.e., grape seed and garlic extract) was quantified, disclosing the possible overestimation of the antibacterial effect of some of these novel food preservation technologies. Consequently, the use of those extracts without taking into account the extent of sublethal injury could result in serious food safety issues.**  
**Abstract:** Natural antimicrobials, such as grape seed extract (GSE) and garlic extract (GE), are often used as (a part of) novel food preservation technologies, especially due to their antilisterial effect. However, little is known on the extent of sublethal injury (SI) these extracts cause to _Listeria monocytogenes_, possibly leading to overestimated efficacies for such novel technologies. The influence of both extracts on the sublethal injury of _L. monocytogenes_ strain LMG23775 was investigated, also using propidium iodide staining to investigate the nature of the injury. Minimum inhibitory concentrations were 500 mg gallic acid equivalents (GAE)/L and 7.5 ug alcicin/mL for GSE and GE, respectively. These concentrations slowed down the growth of _L. monocytogenes_, while only causing a significant amount of SI for GSE. Pure extracts caused inactivation of the cells, with GSE being the most effective. Sublethal injury from pure GSE was mainly caused by membrane damage. In pure GE, a significant amount of SI, not caused by membrane damage, was also present, albeit less pronounced than in pure GSE. In conclusion, both extracts cause a significant amount of sublethal injury to _L. monocytogenes_, which is not taken into account in relevant studies investigating novel food preservation applications involving natural plant extracts.  
**Keywords:**_Listeria monocytogenes_; natural plant extracts; grape seed extract; garlic extract; sublethal injury; membrane damage
# A Security and Privacy Scoring System for Contact Tracing Apps
## 1 Introduction
### Digital Contact Tracing Methods
#### 1.2.2 GPS-Based Contact Tracing Methods  
In the GPS approach, the app logs the GPS location data of the phone. The data are either streamed to a server (referred to in this paper as _GPS streaming_) or stored locally (referred to in this paper as _GPS logging_). When someone tests positive, places they had been during the infectious period are identified. Then, in the GPS streaming system, other people that were there at the same time are found, using the location data on the server. In the GPS logging system, notification methods include the following: updating a publicly available map, which people can compare to their movements to see if they were in an at-risk location; a broadcast notification, using a national alert system; or other en masse communication methods [4].
## 1 Introduction
In a word, MAX/TC has complexity in threshold setting and high acquisition false alarm probability in weak signal scenarios. Recently, the double-dwell/maximum (DD/MAX) acquisition method has been proposed to solve the above problem. The double-dwell scheme uses no threshold in detecting weak GPS signals, and achieves improved performance in terms of detection probability and false alarm probability compared with the conventional MAX/TC criteria. Nevertheless, its low detection probability in weak signal environment leads to a rapid increase of acquisition energy cost [17]. For energy-constrained applications, energy will be an important issue. A novel acquisition method is proposed to reduce energy consumption for IoT applications. The main contributions are listed as follows. 1. An acquisition energy metric is proposed first to characterize the measure _acquisition mean computation overhead_ (AMCO). Previous research focuses on the acquisition performance, not the energy consumption. 2. A novel multi-peak double-dwell (MP/DD) acquisition method for GPS weak signals. Previous searching strategies (e.g., MAX/TC and DD/MAX) regard the correlation peak as the estimated signal, which is valid for strong signals. However, they ignore the fact that there is a high possibility of the signal appearing in the sub-peaks for weak signals. The MP/DD method not only detects the peak, but also some sub-peaks. 3. A hybrid very-large-scale integration (VLSI) architecture is proposed, including coarse-grained acquisition in the first dwell and fine-grained acquisition in the second dwell. A test chip with MP/DD method is fabricated in 40 nm CMOS technology. The rest of this paper is organized as follows. Section 2 introduces related GPS acquisition works. Section 3 introduces the proposed MP/DD GPS weak signal acquisition method. Section 4 discusses the simulation results and measurement results, and Section 5 concludes this paper.
## 3 Results and Discussion
### DVC Analysis
#### 3.2.4 Localization Factor
The value of \(L_{f}\) dropped to 0.77 when the stress reached the maximum value, indicating that significant damage occurred, and this failure process is consistent with the results of Figure 17. The value of \(L_{f}\) did not approach 0 when the stress reached 50 MPa because the specimen had not completely failed at this time and still had a bearing capacity (Figure 2). The result of \(L_{f}\) is in agreement with the experimental phenomenon.