esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Compact Modelling
### UTC Photodiode Compact Modeling  
The compact model for the UTC-PDs reported in [13] is a Verilog-A model for describing the semiconductor physics governing the junction currents and the optical response of the photodiode. The model is further enhanced by incorporating improved descriptions of the dark and photocurrents. The schematic (Figure 3) shows the equivalent circuit of the UTC-PD, including extrinsic pads and coplanar waveguide (CPW) parasitic elements. The intrinsic part is represented by the diode dark current source, \(I_{dark}\), the junction capacitance, \(C_{j}\), the shunt resistance, \(R_{sh}\), the series resistances, \(R_{s}\), and the photocurrent, \(I_{ph}(w)\). In order to facilitate model scaling, the diode currents and the junction capacitances are normalized by the device active area, \(S\), of UTC-PDs.
# Prediction of the Moisture Content in Corn Straw Compost Based on Their Dielectric Properties
## 3 Results
### Bulk Density Dependence of the Dielectric Properties of Samples  
To investigate how the bulk density affects the dielectric properties of the samples, the dielectric constant \(\epsilon^{\prime}\) and the loss factor \(\epsilon^{\prime\prime}\) of the samples with various bulk densities at different moisture contents (5-35%) were examined at a room temperature of 22.3 \({}^{\circ}\)C and at the chosen measurement frequency (10 kHz). The results are displayed in Figure 7. The bulk densities of the samples with various moisture contents are presented in Table 1.  
Figure 7: Bulk density dependence of dielectric properties at various moisture contents: (**a**) dielectric constant, (**b**) loss factor.  
Figure 7 reveals that when the moisture content of the samples was less than 25%, the relationship between \(\varepsilon^{\prime}\) and \(\varepsilon^{\prime\prime}\) of samples and the bulk density was not apparent. However, when the moisture content of samples was greater than 25%, the \(\varepsilon^{\prime}\) and \(\varepsilon^{\prime\prime}\) of samples exhibited an obvious increasing trend with the increase in the bulk density.
# Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System
###### Abstract  
Mobile cranes are essential for transporting heavy materials at construction sites, but their operation carries significant safety risks, particularly due to the potential for overturning accidents. These accidents can be classified into two main categories: mechanical accidents, which are caused by factors such as outrigger failure, excessive load weight, and operator skill, and environmental accidents, which arise from ground subsidence due to groundwater and sinkholes. While numerous studies have addressed the causes and prevention of mechanical accidents, there has been a lack of research focusing on the prevention of environmental accidents. This study presents the development of an Electrical Resistivity Measurement System (ERMS) designed to prevent overturning accidents caused by ground subsidence at mobile crane work sites. The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. Unlike typical buried electrode methods, the proposed system features a foldable electrode mechanism and a water supply device, thereby making installation and removal more efficient. Furthermore, it uses a ground stability determination algorithm that qualitatively assesses soft ground conditions, which are the primary cause of ground subsidence. The performance of the ERMS was validated through comparisons with commercial equipment, and its applicability was further confirmed through field tests conducted at mobile crane installations. The ERMS is expected to significantly reduce the risk of accidents caused by ground subsidence during mobile crane operations and to contribute to enhancing overall safety in construction environments.  
electrical resistivity tomography; ground subsidence; mobile crane +
Footnote †: journal: Applied sciences
## 3 Results and Discussion
### Temperature Influences on Aerobic Metabolisms of PAOs in Conjunction with Cu(II) Presence  
#### 3.3.1 Aerobic Phosphate Uptake  
Figure 3a shows the impacts of Cu(II) concentration on aerobic SPUR of PAOs at different temperatures. Unlike anaerobic phosphate release, the biochemical reaction of PAOs aerobically taking up phosphate with the addition of Cu(II) was remarkably inhibited. The temperature effect on such inhibition in conjunction with Cu(II) presence was apparent. The order of inhibition extent was 10 \({}^{\circ}\)C \(>\) 20 \({}^{\circ}\)C \(>\) 30 \({}^{\circ}\)C, as shown in Figure 3b. PAOs completely ceased phosphate uptake at 10 \({}^{\circ}\)C when 0.5 mgL\({}^{-1}\) of Cu(II) was present, whereas phosphate uptake ceased at 1.0 and 2.0 mgL\({}^{-1}\) at 20 and 30 \({}^{\circ}\)C, respectively.  
Figure 3: Copper toxic effects on aerobic specific phosphorus uptake rate (SPUR), PHAs degradation, and glycogen synthesis under different temperature conditions. (**a**) SPUR; (**b**) SPUR inhibition; (**c**) PHA degradation rate; (**d**) PHA degradation inhibition; (**e**) Glycogen synthesis rate; (**f**) Glycogen synthesis inhibition.
## 4 Results
### In Situ Electrical Conductivity of the Saturated Soil Paste Extract Estimation  
The laboratory results of the ECe from 30 plots are reported in Table 5. The average ECe values from two soil depth levels (0-25 and 25-50 cm) using Equation (1) vary from 15.84 mS/m at Sai O sub-district to 4359.5 mS/m at Kampang sub-district. The average ECe value of 30 plots is 1095.12 mS/m, and the standard deviation is 1291.09 mS/m. A large standard deviation value suggests that the measured values are scattered widely about the mean [60]. The average value of ECe by sub-district indicates strongly saline (800-1600 mS/m) and very strongly saline (>1600 mS/m) soil in six sub-districts, namely, Non Thai, Dan Chak, Samrong, Kampang, Khang Phlu, and Ban Wang. This finding is reconfirmed by the spatial patterns of average ECe, which were interpolated based on average ECe data from 30 plots using the IDW method, as shown in Figure 7.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Land** & **Field** & **Measuring** & \multicolumn{3}{c}{**ECa Statistic Data (mS/m)**} & \multicolumn{3}{c}{**FAO Standard**} \\
**Cover** & **Photograph** & **Mode** & **Minimum** & **Maximum** & **Mean** & **SD** & **ECe Value** (mS/m)** & **Severity Class** \\ \hline Salt patch & & HH & 1541.01 & 1604.00 & 1566.86 & 10.81 & & 800–1600 & Strongly saline \\  & & VV & 1182.02 & 1411.95 & 1325.96 & 42.06 & & \\ \hline Bare land & & HH & 140.16 & 407.99 & 227.99 & 46.02 & & 200–400 & Slightly saline \\  & & VV & 171.08 & 479 & 264.34 & 57.65 & & \\ \hline Cassava & & HH & 13 & 45 & 26.93 & 6.58 & & \\  & & VV & 26 & 79 & 50.49 & 10.89 & & \\ \hline Paddy field & & HH & 109 & 292 & 177.36 & 27.16 & & 200–400 & Slightly saline \\  & & VV & 224.01 & 524.99 & 278.97 & 47.05 & & \\ \hline Corn field & & HH & 94.01 & 130 & 113.71 & 6.32 & & \\  & & VV & 113.02 & 150 & 138.56 & 6.53 & & \\ \hline \end{tabular}
\end{table}
Table 4: Statistical data of the measured ECa values of HH and VV modes in five land use types.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & & & & & \multicolumn{2}{c}{**ECe in mS/m**} & \multicolumn{2}{c}{**Average ECe in mS/m**} \\ \cline{5-8}
**No.** & **Sub-District** & **Code** & **Longitude** & **Latitude** & **At Depth** & **At Depth** & **By** & **By** \\  & & & & **(X)** & **(Y)** & **0-25 cm** & **25-50 cm** & **Depth** & **Sub-District** \\ \hline  
\\ \hline  & & & & & & & & 1095.12 & \\ \hline  & & & & & & & & & \\ \multicolumn{5}{c}{Standard deviation} & & & & & & & \\ \end{tabular}
\end{table}
Table 5: The saturated soil paste extraction (ECe) at the exact soil sample collection location.  
Figure 7: Spatial distribution of average ECe using the IDW method.
# Sparse Multiuser Receiver Design in Large Scale Array System
## 2 System Model  
Assuming that a massive BS is equipped with \(M\) antennas and \(N\) RF chains (\(N<M\)), which are expected to simultaneously service \(K\) single-antenna users [2; 13] as shown in Figure 1, the signal received by the BS is the sum of signals transmitted by several users, and it can be given by [14]  
\[y=G_{A}{\sum_{k}}h(\theta_{k})x_{k}+G_{A}w=G_{A}Hx+G_{A}w, \tag{1}\]  
where \(y\) is the \(N\times 1\)-dimensional received signal, \(G_{A}\) is the adopted analog matrix, \(w\) is the noise, \(H=[h(\theta_{0}),h(\theta_{1}),\cdots,h(\theta_{K-1})]\) is the channel matrix, and \(x=[x_{0},x_{1},\cdots,x_{K-1}]^{T}\) is the signal vector sent by \(K\) users. Given the incident angle of user \(k\), namely \(\theta_{k}\), the \(N\times 1\) channel vector \(h(\theta_{k})\) between user \(k\) and the BS is expressed as  
\[h(\theta_{k})=\Big{[}e^{j2\pi f(0)\frac{d}{\pi}\sin\theta_{k}}\cdots e^{j2\pi f (m)\frac{d}{\pi}\sin\theta_{k}},\cdots,e^{j2\pi f(M-1)\frac{d}{\pi}\sin \theta_{k}}\Big{]}^{T}. \tag{2}\]Generally, for the BS, \(N>K\) is the precondition to ensure that each user is assigned an independent RF chain. Conversely, in some exceptional cases where \(N<K\), it is impossible to realize 'one user, one chain'.  
Further, since the matrix \(G_{A}H\in C^{N\times K}\) is not of total rank, the minimum mean square error (MMSE) estimation of \(x\) is not available by using the least square (LS) method according to the traditional view. Nevertheless, \(x\) is usually generated by simple modulation such as BPSK, there is still room for improvement in the estimator, which is supposed to follow a Gaussian distribution.  
Therefore, we first propose an analog matrix designing scheme that is effective in scenarios where \(K>N\). That means the loss of some users' signals can be avoided despite the absence of one-to-one correspondence between users and RF chains. Subsequently, a method based on the GAMP algorithm is developed, which can still achieve accurate reception of BPSK signals when \(K>N\).
## 5 Conclusions  
The variable spray system based on PWM-PID control can achieve rapid and accurate change of flow according to prescription information, effectively reducing herbicide use and enhance chemical effect.  
1. Using serial communication technology to receive the prescription value information after the prescription translation, the PWM technology was used to adjust the rotation speed of the micro-diaphrag pump to realize the variable spray, and the spray effect of the spray system was tested. The results show that the variable spray system designed by the research group ensures that the atomization effect is stable under the duty cycle of different PWM square wave signals,  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Unit** & **Prescription Value (L-hm\({}^{-2}\))** & **Sampling Band** & **Deposition (ug-cm\({}^{-2}\))** \\ \hline Boundary & & S16 & 23.07 \\ \hline  & & S17 & 69.76 \\ \cline{2-4}
4 & 37.5 & S18 & 129.87 \\ \cline{2-4}  & & S19 & 134.26 \\ \hline \hline \end{tabular}
\end{table}
Table 5: _Cont._  
Figure 22: Droplet depositions in operation units.  
and the coefficient of variation of the system flow rate with the duty cycle of the PWM square wave signal is 39.21%, which can satisfy various kinds of different spray requirements;
2. The PID algorithm was used to control the flow adjustment process to reduce the steady-state time of the system, so that the deviation between the actual flow and the target flow is stable at 2.16%, indicating that the system can adjust the flow well;
3. The outdoor sedimentation test shows that the variable spray system can quickly change the spray flow according to the prescription value of the working plot. Variable pulse spraying can be realized by PWM technology.
4. Based on the data of experimental deposition and deposition density, the variable spray system can be stabilized within 0.4 s from receiving the prescription value to adjusting the flow rate to a predetermined value, and the effective injection rate of actual operation is about 5 m.  
Conceptualization, S.W., Q.Z., J.D. and Y.L.; methodology, W.S., Q.Z. and J.S.; software, S.W., Q.Y., and J.S.; validation, Q.Z., X.Y. and J.S.; formal analysis, S.W. and Y.L.; investigation, W.S.; resources, J.Z. and Y.L.; data curation, Q.Z. and J.S.; writing of the original draft preparation, Q.Y.; writing of review and editing, S.W.; visualization, S.W. and J.Z.; supervision, S.W.; project administration, S.W.; funding acquisition, S.W. and J.Z.  
This research was funded by the Science and Technology Program of Guangzhou, China (Grant No. 201707010047), Science and Technology Program of Guangdong, China (Grant No.: 2016A020210100, and 2017A020208046), National Key Technologies Research and Development Program (Grant No.: 2016 YFD0200700), and National Natural Science Foundation of Guangdong, China (Grant No.: 2017A030310383).  
Thanks to [PERSON], et al. from the National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology for helping the authors to complete the outdoor experiment.  
The authors declare no conflicts of interest.
## 4 WT/PV ES Optimization Decision
### Stage 1: WT/PV Siting and Sizing
#### 4.2.2 Constraint Condition  
1. Power-flow constraint of distribution network  
When the distribution network operates stably, its voltage and power must satisfy the power-flow equations:  
\[\left\{\begin{array}{l}P_{Li}=U_{i}\sum\limits_{j=1}^{n}U_{j}(G_{ij}\cos \theta_{ij}+B_{ij}\sin\theta_{ij})\\ Q_{Li}=U_{i}\sum\limits_{j=1}^{n}U_{j}(G_{ij}\sin\theta_{ij}-B_{ij}\cos \theta_{ij})\end{array}\right., \tag{29}\]  
where \(G_{ij}\) and \(B_{ij}\) are the conductance and susceptance, respectively, between nodes \(i\) and \(j\) and \(\theta_{ij}\) is the phase-angle difference between nodes \(i\) and \(j\).  
2. Node voltage constraint  
To ensure the power quality of the distribution network, according to the relevant regulations, the node voltage of the power-grid system should be within a reasonable range during operation:  
\[U_{i,\min}\leq U_{i}\leq U_{i,\max}, \tag{30}\]  
where \(U_{i,\min}\) and \(U_{i,\max}\) are the minimum and maximum allowable values of node voltage deviation, respectively.  
3. Total capacity constraint of WT/PV access  
After the WT/PV unit is connected, to avoid curtailment of wind and solar power, the total capacity minus the total load capacity should not exceed the maximum power that the transformer of the upper power grid can bear:  
\[P_{DG}\leq P_{DG,\max}, \tag{31}\]  
where \(P_{DG}\) is the actual capacity of WT/PV connected to the distribution network and \(P_{DG,\max}\) is the maximal permitted connected capacity of renewable energy.
# Cybersecurity and Medical Imaging: A Simulation-Based Approach to DICOM Communication
## 3 Methodology
### Encryption  
The DICOM simulator provides an option to add a TLS layer for encryption, which is supported by Orthanc as well. Enabling TLS support in the DICOM simulator ensures that the transmission of DICOM data between the simulator and PACS server is encrypted, thereby enhancing data security. To enable TLS support in ORTHANC, the following steps should be completed:  
* **Building a TLS Context.** A TLS context needs to be created within ORTHANC. The TLS context defines the configuration and settings for the TLS encryption.
* **Loading the Necessary Certificate and Private Key.** To establish secure communication, a valid TLS certificate, and its corresponding private key need to be provided. The TLS certificate is obtained from a trusted Certificate Authority (CA) and serves as proof of identity for the server.
* **Adding the Supported Context with the TLS Context to the AE.** In Orthanc, an AE represents a network entity that can communicate using the DICOM protocol. The TLS context is then added to the AE configuration in order to associate the TLS encryption capabilities with the AE.  
By completing these steps and configuring the TLS settings correctly, the DICOM simulator with TLS support ensures that DICOM data transmitted between the simulator and the PACS server is encrypted. This encryption helps to protect the confidentiality and integrity of the data during transmission, mitigating the risk of unauthorized access or tampering.  
Figure 2: Establishment of the association between the AE and the PACS server.
## 3 The Proposed Coverage Flight Path Planning Algorithm
### Path Searching on the Waypoints Graph  
After constructing the WG, the path searching is carried out to find the complete coverage path from the pre-determined location of the UAV. The source point \(p\) represents the point from where the UAV starts the mission and point \(q\) represents the endpoint of the mission. Once the complete graph is constructed, the pathfinding process starts from the point \(p\) and continues until the complete coverage is achieved. We used the ACO algorithm generated order for the collision-free pathfinding over WG with minimum overlapping and informed search. The proposed algorithm keeps track of the locations to be visited along the path by using the order generated for footprints' sweeps visits and their connections. We assume that UAV is able to take turns with sufficient accuracy while switching from one sweep to another during the mission. The proposed approach is able to find the minimum length path with less path overlapping, less number of turns, and reduced computation time compared to the existing methods in most scenarios.
# Damage Identification in Warren Truss Bridges by Two Different Time-Frequency Algorithms
## 3 Numerical Algorithms for Signal Processing
### Huang Hilbert Transform (HHT)  
The second approach proposed in the paper uses the Huang-Hilbert Transform, which is generally adopted for the time-frequency analysis of non-stationary, nonlinear real time signals. It provides time-frequency information from the processed signal, through two steps:  
* In the first step the empirical mode decomposition is applied, dividing the signal into different intrinsic mode functions (IMFs).  
Figure 5: Scheme illustrating the way in which the CWT was used in the present work.  
In the second step the Hilbert transform is applied, from which the instantaneous frequency and the energy of the signal are obtained [39].  
The plot of the Hilbert spectrum provides the time-frequency information about the processed signal. This procedure has been exploited in the diagnostics of railway infrastructure [40], while herein it is applied to drive-by methods for the condition monitoring of railway bridges.  
As shown in the flow chart of Figure 6, in this work the HHT is directly applied to the difference of the acceleration signals in the time domain: this is necessary to perform the IMF. A peak in terms of instantaneous energy, always associated to a specific frequency, allows detection of the presence of the damage and estimation of its position along the bridge.
# Mail Inspection Based on Terahertz Time-Domain Spectroscopy
## 4 Conclusions  
Terahertz time-domain spectroscopy provides unique possibilities to nondestructively inspect mail with the aim of identification of drugs and explosives. As typical enclosures used for mail are of dielectric nature and therefore more or less transparent for terahertz waves, this application fits well to this part of the electromagnetic spectrum. Further, relevant drugs and explosives show specific absorption features, which allow the identification by using terahertz spectroscopy. Nevertheless, the transition from lab demonstration requires advances in applicability and usability.  
We have successfully shown that our developed mail scanning system based on terahertz time-domain spectroscopy is able to reliably identify suspicious substances hidden in mail. With the help of some engineering refinements as the side swap mechanism, the system completely fulfills the demands to be used in small offices as for example in correctional facilities. Especially the artificial absorption bands induced by multiple reflections from the mail paper sheets could be strongly suppressed, which results in a dramatic drop in the false positive rate of our evaluation algorithm. Additionally, the dry air purging of already 90% of the terahertz beam path leads to a remarkable improvement of the overall system performance. The presented different sample scan strategies as well as the various visualization options are helpful features to make the invisible visible. Last but not least, the intuitive graphical user interface helps operators who do not have a technical background to easily use the system to reliably check the daily mail.  
Conceptualization, D.M., D.H., T.S., K.N., F.P., R.B., J.J., and F.E.; Data curation, D.M., D.H., G.T., and F.E.; Formal analysis, D.M., K.N., F.P., and F.E.; Funding acquisition, D.M., T.S., R.B., J.J., G.v.F., and F.E.; Investigation, D.M., D.H., T.S., K.H., and F.E.; Methodology, D.M., D.H., T.S., K.N., F.P., G.T., R.B., J.J., and F.E.; Project administration, T.S., R.B., J.J., G.v.F., and F.E.; Software, D.M., K.N., and F.P.; Validation, D.M., D.H., K.N., F.P., G.T., and F.E.; Visualization, D.M., D.H., T.S., R.B., and F.E.; Writing--original draft, D.M. and F.E.; Writing--review and editing, T.S., K.H., K.N., F.P., G.T., R.B., and G.v.F. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on reasonable request from the corresponding authors.  
We thank [PERSON], [PERSON] and their colleagues from the correctional facility in Wurzburg, Germany for their support and valuable feedback.  
The authors declare no conflict of interest.
# Around View Monitoring-Based Vacant Parking Space Detection and Analysis
## 4 Experimental Results
### Analysis of Detection Failures  
#### 4.5.1 Parking Space Detection Failures  
Although the proposed algorithm performed favorably in both indoor and outdoor settings, relying solely on image-based information was inadequate in certain situations. Some examples of failures and the reasons for the failures are discussed below. Figure 26 shows examples of parking space detection failures. Figure 26a shows an example where dark shadows were caused by the lighting. Because the shadows covered the parking space markings, the corner detector was not able to successfully extract features. Figure 26b shows an example where the parking space markings are severely damaged. Because the paint at the line junctions was faded, the system was unable to detect corners. Figure 26c shows an example involving standing water. The divider lines were not detected because of reflections in the water.