esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Problem Formulation
Due to its particular isolation, it is clear that it cannot be connected to Australia's primary power grid, making it an ideal candidate to study possible smart metering scenarios. A small central portion of the site has been taken due to a higher density of concentrated customers compared to other areas where there is not a sufficient number of users to perform the performance study, in addition to the fact that the portion of land chosen allows an adequate visualization for the analysis of the deployment of devices. Under the above, it has been decided to establish 156 consumption measurement points, 50 data concentrators, three base stations and two central offices, giving 211 nodes connected. Figure 2 shows the distribution of infrastructure elements for the proposed heterogeneous wireless network. A communication system solution for energy metering generates a set of nodes and links. Therefore, we consider a graph from which the sets of vertices and edges are established. Given this background, the model used in this study contemplates a Set Cover Problem (SCP), thus determining the application of an algorithm based on heuristics due to its efficiency and simplicity concerning computational time [26]. This problem has previously defined a topology created by the Prim [27] algorithm, which determines the minimum spanning tree considering a connection capacity constraint per node and a maximum range given in kilometers. Any positive integer can be included in the capacity variable, depending on the wireless technology, while the range is any number, element of positive rationals, and is also defined by the connection technology of the device. In addition, to determine the distances between nodes of the system, the Haversine formula generates the graph's edges, resulting in the conformation of the logical matrices necessary for the SCP, PRIM, and Dijkstra algorithms. In this work model, the Dijkstra algorithm is considered to determine the shortest route to perform the routing between devices. The computational cost described as an NP-Complete for MST problem warns as notation Big Oh--\(O(n\log n)\) and the set cover algorithm \(log_{2}(n)/2\). The names of each of the variables and parameters of the system and algorithms are established in Table 3. In addition, to test the model used, two stages are considered to establish a difference between a pre-established scenario and its optimal reconstruction. The first stage begins with a distance measurement through [PERSON]'s formula, taking into account that all devices must be adequately defined by their longitude and latitude, followed by the routing between all nodes through Dijkstra and calculating the total cost of the paths found. In this way, a tree or preliminary topology of the wireless network of the scenario can be obtained at the lowest cost, considering the shortest distance according to the pre-established range in meters for each node. This first stage works specifically as indicated by Algorithm 1, which is divided into three steps: the establishment of input data, the calculation of distances, and the determination of the minimum paths with their cost.
# Research on Location Selection Model of 5G Micro Base Station Based on Smart Street Lighting System
## 5 Simulation and Analysis
### Comparative Analysis
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multicolumn{3}{c}{**Coverage Requirement**} \\ \cline{2-4}  & \(\gamma\) = 90\% & \(\gamma\) = 95\% & \(\gamma\) = 99\% \\ \hline Combined ratio \(\alpha_{\text{h}}\) & 100\% & 100\% & 100\% \\ Coupling ratio \(\alpha_{m}\) & 100\% & 87.50\% & 81.82\% \\ Unity ratio \(\alpha_{t}\) & 70.34\% & 71.34\% & 74.27\% \\ System coordination \(F^{{}^{\prime}}\) & 97.51\% & 95.29\% & 89.54\% \\ Select number & 7 & 8 & 11 \\ Coverage rate & **94.88\%** & **95.68\%** & **99.47\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Location selection results of the residential area under different coverage constraints. independent pole, the demand for a 5G network of residential users achieves a high degree of system coordination (93.44%). The infrastructure construction of the industrial area is relatively backward. The area has a large area and few light poles, which makes location selection difficult. As the demand for network coverage increases, the number of single independent poles increases, and the coordination degree of carrying equipment is also reduced, which leads to an increase in base station construction cost and resource utilization cost. When the basic coverage requirement is 90%, the combined ratio is 100%, and the coupling ratio and subsystem coordination are the highest. Considering the construction cost of the industrial area and the base station coverage requirement comprehensively, the network coverage requirement of 90% is the optimal 5G micro-base station location selection scheme.
## 3 Using the Digital Platform--DNS/SWAT
### Sediment Yield--Land Phase Simulation  
Transport of sediment in the land phase of the basin in the SWAT module consists of simulating the mass of the sediment leaving individual area units (HRU) using the MUSLE (2) equation per time and per unit area, known as sediment yield (SYLD) [135]. HRUs allow the spatial heterogeneity of land use, soil, and slope to be taken into account, increasing the accuracy of SYLD forecasting, which is of particular importance in distinctly dual character basins such as the Raba. The basin area is often considered the most important explanatory factor for SYLD, due to the reduction in the rate of topsoil erosion on smaller slopes and the increased likelihood of sediment deposition as the basin area increases. In addition, especially in mountainous areas, SYLD is influenced by factors such as topography, land cover, reservoir effects, and climatic conditions. However, their relative importance in explaining the spatial variation of SYLD is still not fully understood, as it is specific to each basin area [136]. Analyses of regional SYLD patterns mainly concern larger river systems [137; 138], and this further limits information on smaller basins that are often more important for sediment transport. The Western Carpathians, including the Raba River basin, can be called \"hot spots\" where, as a result of erosion, the transport of significant amounts of SYLD is initiated. Nevertheless, sediment yield monitoring in this area is very limited and was carried out for a limited time, only for individual tributaries of the Dobczyce dam reservoir [139]. Only the use of mathematical models has significantly increased the knowledge of the transport of sediment particles in the land phase throughout the Carpathian region [56; 57; 58; 140; 141]. The digital platform--DNS/SWAT made it possible to estimate the aggregated values of SYLD, being a function of the runoff processes, for each of the 36 Raba sub-basins, taking into account their temporal variability. Thus, spring was identified as the period of maximum average sediment yield values reaching 0.92 t/ha and 0.57 t/ha, and winter with minimum values of 0.28 t/ha and 0.21 t/ha for the upper and lower parts of the basin, respectively [142; 138]. These studies can therefore both confirm the role of modeling as a reliable means of obtaining detailed information on the rate and amount of soil loss in areas such as the Carpathian region, and help understand the effect of basin factors such as slopes, land use, and soil type on the spatial variability of SYLD.
## 3 Effects of Power Lines on Aerial Manipulators
### Effects of the Magnetic Field  
Power line can be seen as a thin straight long conductor, which generates the magnetic field proportional to the current flowing through it:  
\[B=\frac{\mu_{0}I}{2\pi r} \tag{1}\]  
where \(I\) is the current flowing through the conductor, \(B\) is the magnetic field strength, \(r\) is the distance from the conductor and \(\mu_{0}\) is the permeability of vacuum.  
The magnetic field isomagnetic lines of a single conductor are circular (Figure 2), centered on the conductor, and their direction is determined by a right-hand rule. With two or more conductors, the magnetic field becomes more complex.  
The typical current flowing through the power line conductor is an alternating current with a frequency of 50 or 60 Hz and with the strength of several hundred amperes. It generates a strong alternating magnetic field with the same frequency as the current. In such a setup, at a distance of less than 1 m from the power line, the magnetic field strength is stronger than the earth's magnetic field, rendering the information from the drone's on-board compass useless.  
On the other hand, since the idea is to perform operations on the power line, the magnetic field generated by the current flowing through the conductors can be used for precise localization with respect to the power line. We explored this approach in [24], where the position of the drone with respect to the two-wire power line was calculated, using measurements from magnetometers mounted on the drone. Here, we present an analytical solution derived from the nonlinear magnetic field equations that promises low computational time. To determine the orientation of the drone with respect to the power lines, only three magnetometers are needed, and neither the current nor the magnetic field equations need to be known. It was shown that an analytical solution for calculating the drone position can be determined by combining the magnetic field equation with the magnetic energy equation.
## 2 System Model  
Consider transmission over an AWGN channel and ideal timing synchronisation at the receiver in sensor node. The CFO and carrier phase offset (CPO) are assumed to be unknown and random but constant with respect to a packet transmission [2]. Without loss of generality, we follow the discrete-time signal model in [2] but with some changes. In particular, the baseband equivalent chip sequence for the \(m\)th bit \(E[m]\) is  
\[r_{m,k}=s_{m,k}e^{j(2\pi k/T_{c}+\theta)}+\eta_{m,k},\quad 1\leq k\leq K. \tag{1}\]  
Here, \(s_{m,k}\) is the \(k\)th bipolar BPSK modulated chip, \(f\) is the CFO in Hz, and \(\theta\) is arbitrary modulo-\(2\pi\) reduced CPO in radians. \(T_{c}\) is the chip duration, \(\eta_{m,k}\) is a discrete-time, circularly symmetric, zero-mean complex AWGN with variance \(\sigma_{m,k^{\prime}}^{2}\), and \(K=15\) is the length of the pseudorandom number (PN) code [1]. We assume that \(f\) and \(\theta\) are statistically independent of each other, and of the AWGN \(\{\eta_{m,k}\}\).  
Notice that the channel is supposed to only introduce CPO, but otherwise is assumed to be perfectly equalized. That is to say, a phase noncoherent channel is considered. Signal distortion caused by multipath fading is not considered for simplicity in describing detection principle, i.e., the indoor short-range propagation model is used, where the complex channel gain equals to 1 [19]. The CFO is due to instabilities associated with the inexpensive carrier oscillators in transmitting node and receiving node. The bandwidth of the receiving filter \(B\) is wide enough for all of the signal energy spread by CPO and CFO to pass [20]. In this case, all of the modeling and analysis in this work can be performed using the discrete-time complex baseband model in [8].
## 3 Results and Discussion  
### Initial Parameters of Aquaculture Wastewater before Phytoremediation  
Based on the Environmental Quality (Sewage and Industrial Effluent) Regulations (2009), the initial physico-chemical parameters, including the temperature, pH, DO, TSS, and NH\({}_{3}\)-N, of the aquaculture complied with the required a and b standards. The same goes for the other parameters, including phosphate, turbidity, conductivity, total dissolved solids (TDS), and BOD\({}_{5}\), which were taken during water sampling, were all at permissible levels. Table 2 shows the initial reading of the aquaculture wastewater parameters prior to phytoremediation process.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Unit** & **Average Value** & **Class/Standard** \\ \hline Temperature & \({}^{\circ}\)C & 27.77 \(\pm\) 0.06 & Standard A \\ pH & - & 8.29 \(\pm\) 0.02 & Standard A \\ DO & mg/L & 4.63 \(\pm\) 0.04 & Standard A \\ Conductivity & \(\mu\)s/cm & 95.73 \(\pm\) 0.15 & - \\ Turbidity & NTU & 205.00 \(\pm\) 1.00 & - \\ TSS & mg/L & 45.67 \(\pm\) 0.60 & Standard A \\ TDS & mg/L & 59.49 \(\pm\) 0.45 & - \\ BOD\({}_{5}\) & mg/L & 10.66 \(\pm\) 0.03 & - \\ NH\({}_{3}\)-N & mg/L & 4.20 \(\pm\) 0.10 & Standard A \\ Phosphate & mg/L & 0.35 \(\pm\) 0.10 & - \\ Temperature & \({}^{\circ}\)C & 27.77 \(\pm\) 0.06 & Standard A \\ pH & - & 8.29 \(\pm\) 0.02 & Standard A \\ DO & mg/L & 4.63 \(\pm\) 0.04 & Standard A \\ \hline \hline \end{tabular}
\end{table}
Table 2: Initial reading of aquaculture wastewater parameters before phytoremediation.  
Figure 1: Schematic diagram of the phytoremediation treatment in the laboratory, which (**a**) _C. asiatica_; (**b**) _I. aquatic_; (**c**) _S. molesta;_ (**d**) _P. Stratiodes_; (**e**) _E. crassipes_; (**f**) Control.
## 5 Conclusions and Outlook  
In a recent project, the \(SE\) values of various conductive and magnetic textile fabrics, together with some 3D-printed materials, were investigated. The fabrics crocheted from highly conductive yarns showed only low EMI shielding properties due to their large pores.  
In contrast, the metalized fine woven fabrics revealed high shielding values around 80 dB, which is higher than most other textile materials with conductive coatings reported in the literature. Generally, this study shows the importance of combining small pore sizes with high conductivity, which is optimal for the metalized woven fabrics used here.  
It must be mentioned that these metalized fabrics are known to be damaged by washing and sweat since the metal coating will be oxidized or even abraded under harsh conditions. The next steps will thus aim at increasing the washability and sweat resistance of the described fabrics by using conductive and nonconductive coatings while maintaining their drapability and at testing fine-knit fabrics from conductive yarns, which typically have a higher drapability and elasticity than woven fabrics. Such fabrics would often be favorable, e.g., for garments for people working in EMI-prone areas or in several technical applications, such as covering bent parts of cars or planes or flexible EMI shielding covers for laboratory instruments and machine parts. Moreover, combining the relatively thick, three-dimensional structure of crocheted or knitted fabrics with thin woven fabrics with very small pores is another promising approach to preparing new textile structures for EMI shielding with flexible, drapable fabrics.  
Conceptualization, T.B. and A.E.; methodology, D.W., M.S., M.M. and A.E.; formal analysis, D.W., M.S., M.M. and A.E.; investigation, D.W., M.S., M.M., K.T., M.D., Y.T. and A.E., writing--original draft preparation, D.W., M.S., M.M., T.B. and A.E.; writing--review and editing, all authors; visualization, D.W., M.S., M.M. and A.E. All authors have read and agreed to the published version of the manuscript.  
This research was partly funded by the German Federal Ministry for Economic Affairs and Energy (grant no. KK5129710 KT1). T.B. acknowledges the partial support from the local SUT Grant 14/030/RGJ23/0221. M.M. acknowledges the partial support from the local SUT Grant 02/140/RGJ22/0017.  
Not applicable.  
Data Availability Statement: Data are available from the corresponding author on reasonable request.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 3 Results and Discussion
### Major Barriers and Policy Implications in India
#### 3.7.3 Infrastructural Barriers in India  
In India, there is the lack of infrastructural development; investors are therefore required to spend a lot of research and time to locate the potential sites for the construction of CSP plants [1]. Another challenge is that after identifying the potential sites, investors require approval from various authorities in order to develop CSP technologies [11; 13; 80; 86]. To address this matter, the government needs to support the entire project implementation, including the allocation of potential sites, funds, transportation facilities, water resources, and other development measures required for the infrastructure. This will be beneficial in the development of the economy and also the infrastructure of the state [87].
###### Abstract  
The fuel cell is an electrochemical energy converter that directly converts the chemical energy of the fuel into electrical current and heat. The fuel cell has been able to identify itself as a source of clean energy over the past few decades. In order to achieve the durability and stability of fuel cells, many parameters should be considered and evaluated Therefore, in this study, a single-channel high-temperature polymer exchange membrane fuel cell (HT-PEMFC) has been numerically simulated in three-dimensional, isothermal and single-phase approach. The distribution of the hydrogen and oxygen concentrations, as well as water in the anode and cathode, are shown; then the effect of different parameters of the operating pressure, the gas diffusion layer porosity, the electrical conductivity of the gas diffusion layer, the ionic conductivity of the membrane and the membrane thickness are investigated and evaluated on the fuel cell performance. The results showed that the pressure drop in the cathode channel was higher than the anode channel, so that the pressure drop in the cathode channel was higher than 9 bars but, in the anode channel was equal to 2 bars. By examining the species concentration, it was observed that their concentration at the entrance was higher and at the output was reduced due to participation in the reaction and consumption. Also, with increasing the operating pressure, the electrical conductivity of the gas diffusion layer and ionic conduction of the membrane, the performance of the fuel cell is improved.  
high-temperature PEM fuel cell; operating pressure; porosity coefficient; ionic conduction; electrical conductivity; fuel cell performance
## 1 Introduction
We also construct a lightweight Shared Convolutional Detection Head (SCDH) based on group-normalized shared-weight convolution, which significantly reduces the computational overhead while maintaining accuracy. Furthermore, replacing the SPPF module with a Spatial Pyramid Shared Conv (SPSC) module reduces long-range target feature loss and decreases model redundancy. * A UCMD coal mine underground miner localization image dataset is constructed by simulating various conditions in a fully mechanized mining face. Based on this dataset, the paper integrates MSS-YOLO with the SGBM binocular stereo vision matching algorithm to solve the 3D spatial positions of miners and verifies its performance in a simulated roadway. Experimental results show that MSS-YOLO detects miners in real time and with high accuracy under different dust concentrations and distances, while the binocular-based localization achieves excellent precision and stability. The rest of this paper is organized as follows. Section 2 introduces some related work within this topic, and Section 3 outlines the traditional YOLOv8 network. Building on this, the MSS-YOLO network proposed in this paper is described in detail, along with a miner localization method combining MSS-YOLO with SGBM binocular stereo vision matching technology. Additionally, the construction scheme of UCMD for the personnel dataset of the fully mechanized mining face is introduced. The construction of the related experimental platform as well as the experimental demonstration is given in Section 4, and Section 5 discusses and summarizes the research work in this paper. All source code and all data in this article are available upon request.
# Sillcom: A Communication-Efficient Privacy-Preserving Scheme for Indoor Localization
## 5 Sillcom\({}_{3R}\): Basic Design with Three Online Rounds
### Communication-Efficient Distance Computation via RSS \(\Pi_{SED}\)  
Since square root operations are costly in MPC, we adopt the squared Euclidean distance, which preserves relative ordering, as the distance metric for comparison.  
In distance computation, computing the dot product of inputs with dimension \(n\) requires \(n\) multiplications. Homomorphic multiplication incurs high computational costs, and designs based on secret sharing frameworks such as ABY [27] require certain communication overhead in both offline and online phases for each multiplication. In our three-party setting, the communication overhead of multiplication using RSS arises from share reconstruction after local computation. As a result, the \(n\) reconstruction steps in dot product computation can be compressed into only one single data transmission, making the communication cost of dot product computation independent of the dimension \(n\). Algorithm 1 provides details on the squared Euclidean distance computation.  
```
0: RSS shared fingerprints \(F_{i}\) of \(RP_{i}\) and \(F_{q}\) of client, \(i\in[m]\).
0: RSS shared square Euclidean distance between \(F_{i}\) and \(F_{q}\). Offline preprocessing:
1: DO RSS share fingerprints \(F_{i}\) to three computing servers \(P_{0}\), \(P_{1}\) and \(P_{2}\), \(i\in[m]\). Online computing:
2: Client RSS shares fingerprint \(F_{q}\) to \(P_{0}\), \(P_{1}\) and \(P_{2}\).
3:for\(i\gets 1\) to \(m\)do
4: Server \(P_{b}\) locally computes \([\![f_{q}]\!]_{b}-[\![f_{q}]\!]_{b}\), \(j\in[n]\), \(t\in[3]\),.
5:\(P_{b}\) gets 3P-ASS share of square Euclidean distance \(d_{iq}\) between \(F_{i}\) and \(F_{q}\) by locally computing \([d_{iq}]_{b}=\sum_{j=1}^{n}(([\![f_{q}]\!]_{b}-[\![f_{q}]\!]_{b})^{2}+2\cdot([ \![f_{q}]\!]_{b}-[\![f_{q}]\!]_{b})\cdot([\![f_{j}]\!]_{b+1}-[\![f_{q}]\!]_{b+ 1}))\).
6: Servers perform RSS construction with compressed communication in one round.
7:endfor
```  
**Algorithm 1** Secure square Euclidean distance computation via RSS \(\Pi_{SED}\)
## 2 Materials
### Data Set
#### 2.2.2 Water Level Records  
Continuous observation records of the water level in Dafeng Port, Lanshayang, Xiaoyangkou Port and Xinyang Port were collected, as well as the forecast water levels from the Jiangsu coastal tidal gauge stations (Sheyang river mouth tidal gauge station, Chenjiawu tidal gauge station, Jianggang tidal gauge station and Lvsi tidal gauge station), to validate the hydrodynamic model simulation results.