esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
To conclude, it can be said that the presented EHS can harvest electrical energy from the exhaust gas of a heating system and thus it delivers a contribution for a more efficient usage of the inserted primary energy carrier. The efficiency of the entire system is currently not very high; however, since the waste heat is normally unused, such systems can be worthwhile. The energy amount is high enough to supply small DC applications, e.g., to charge a mobile phone. Also, it is possible to supply the heating and their components during a short blackout, but for this purpose, an accumulator is needed to store the electrical energy over the year--which, it has to be admitted, could also be loaded by the electrical grid. To improve the EHS and to increase the efficiency of the heating, the water to be heated could be used as a cooling medium and thus, the water will be preheated (less energy input of the heating is necessary) and the thermoelectric devices will produce more electrical power. It can be summarized that especially if there is a need for a robust, maintenance free and reliable power supply and the investment costs do not matter, thermoelectric EHS are highly recommended, e.g., for usage in space applications. To increase the energy yield, the number of TEGs or the temperature difference applied over the thermoelectric devices has to be enhanced. [PERSON] conceived, designed and performed the experiments, analyzed the data and wrote the paper. [PERSON] supported the work through its expertise, knowledge, feedback and input. The authors declare no conflict of interest.
## 3 Mathematical Modelling, Theoretical Aspects
### General Aspects  
A major issue in the design of beam-type elements with significant axial loads is to improve the stability of the element and avoid their failure through buckling, which phenomenon threatens the structural integrity of the whole structural assembly. The phenomenon is more relevant in the case of statically determined structural assemblies.  
The first step in the modelling of beam-type elements to improve their stability is to analyze [PERSON]'s critical load derived in 1757, which is presented in Expression (1) [6].  
\[F_{cr,E}=\frac{\pi^{2}\cdot E\cdot I_{min}}{L_{f}^{2}} \tag{1}\]  
In Expression (1) \(E\) represents [PERSON]'s modulus, \(I_{min}\) denotes the minimum value of the moment of inertia of the cross-section, \(L_{f}\) and represents the buckling length of the beam-type element subjected to compression forces, with respect to the imposed kinematic constraints to the joints.  
[PERSON]'s formula highlights two important aspects unaware of the kinematic restrains of the joints, the length of the element and the moment of inertia of the cross-section. The factor of direct proportionality with the critical load is the moment of inertia. This design parameter gain importance when the buckling modes are studied. The deflection shape associated with the primary buckling mode emphasizes potential critical areas of the element, which by similarity, can be scribed as potential areas of appearance of plastic hinges. In this manner it is required to amplify the value of the moment of inertia, therefore a variable cross-section beam-type element is obtained. In order to avoid sudden changes of the elements cross-section, which can be identified as stress concentration points, it is proposed the modelling of the cross-section of the element through a continuous function.  
Modelling the cross-section of the element is performed with respect to [PERSON]'s principle. According to [PERSON]'s principle, the cross-section area of every section will remain unchanged during the modelling process, but the moment of inertia will change in accordance with the primary buckling mode. As a consequence of the mentioned principle, the elastic resistance of every cross-section is identical. Modelling a beam-type element with a variable cross-section follows the increase of the critical elastic buckling load, in an ideal case exceeding the elastic resistance of the cross-section, thus the buckling phenomenon can be avoided.
###### Abstract  
This study investigated the performance of a combined vertical-horizontal flow biochar filter (VFF-HFF) system in terms of organic matter, total nitrogen (Tot-N), _Escherichia coli_ and _Salmonella_ removal and explored the effects of hydraulic loading rate (HLR) on pollutant removal. The combined VFF-HFF system used biochar as the filter medium and comprised two stacked sections: (i) an aerobic vertical flow filter (VFF) in which the wastewater percolated through the biochar medium in unsaturated mode and (ii) a horizontal flow filter (HFF), in which the biochar was saturated with water and had limited access to air, to enable anaerobic conditions and enhance the denitrification process. The system was tested over 126 weeks using real wastewater applied at different HLR (23, 31, 39 L m\({}^{-2}\) day\({}^{-1}\)). The results showed that long-term removal of organic matter in the entire system was 93 \(\pm\) 3%, with most (87 \(\pm\) 5%) occurring in the VFF. For Tot-N, the long-term removal was 71 \(\pm\) 12%, with increasing trends for nitrification in the VFF and denitrification in the HFF. Mean long-term nitrification efficiency in the VFF was 65 \(\pm\) 15% and mean long-term denitrification efficiency in the HFF 49 \(\pm\) 14%. Increasing HLR from 23 to 31 L m\({}^{-2}\) day\({}^{-1}\) increased the nitrification efficiency from 42 to 61%. Increasing the HLR further to 39 L m\({}^{-2}\) day\({}^{-1}\) decreased the denitrification efficiency from 45 to 25%. HLR had no significant effects on VFF and HFF performance in terms of _E. coli_ and _Salmonella_ removal, although the VFF achieved a 1.09-2.1 log\({}_{10}\) unit reduction and the HFF achieved a 2.48-3.39 log\({}_{10}\) unit reduction. Thus, long-term performance, i.e., removal of pollutants measured during the last 52 weeks of the experiment, was satisfactory in terms of organic matter and nitrogen removal, with no signs of clogging, indicating good robustness of the combined VFF-HFF biochar filter system.  
biochar filters; denitrification; _Escherichia coli_; hydraulic loading rate; long-term removal; nitrification; onsite systems; _Salmonella_ spp.; wastewater treatment
## 5 Experimental Results
Sequentially, another digital meter, also called Fluke 8050A, is used to measure the input voltage. Accordingly, the input power can be worked out. As for the output power, six LED strings with the same number of LEDs, manufactured by Everlight Lighting Co., are used as the load of this LED driver. At the same time, the voltages across these six LED strings are measured by the other digital meter, also called Fluke 8050A. After this, the currents in these six LED strings are measured by a current probe, named TCPA 300, manufactured by Tektronix Co. Accordingly, the output power can be worked out. Finally, the corresponding efficiency can be figured out based on the calculated input and output powers. Figure 18 shows the curve of efficiency versus load current percentage. From this figure, it can be seen that the efficiency is above 90% all over the load range and can be up to 97.6%.
# A Variable Neighbourhood Search-Based Algorithm for the Transit Route Network Design Problem
## 2 Materials and Methods
### The TRNDP Problem
Let: \(ATT_{RS}\): Average Travel Time for route set \(RS\)  
**C**: the vector of path costs on the transit network  
\(d_{0 RS}\): Percentage of passenger demand satisfied without transfers for route set \(RS\)  
\(d_{1 RS}\): Percentage of passenger demand satisfied with one transfer for route set \(RS\)  
\(d_{2 RS}\): Percentage of passenger demand satisfied with two transfers for route set \(RS\)  
\(d_{unRS}\): Percentage of unsatisfied demand for route set \(RS\)  
\(R\): Route \(\in RS\)  
**RS**: Vector of optimal routes  
\(RM\): Maximum number of routes \(R\) in \(RS\)  
\(RS\): Set of routes _{R_}  
**Q**: the vector of segment flows on the transit network  
\(s_{R}\): Number of stops per route \(R\)  
\(s_{min}\): Minimum number of stops  
\(s_{max}\): Maximum number of stops  
\(U\): the user route choice model function  
The problem's objective may be formulated as follows:  
\[(\hat{\textbf{R}}\textbf{S})=\text{argmin}Z\;(\textbf{RS},\textbf{Q}) \tag{4}\]  
\[Z=ATT_{RS} \tag{5}\]  
The problem seeks to determine the route set that minimises the objective function (Equation (4)). The latter represents the user cost associated with the route set, as previously explained (Equation (5)). The problem is subject to the following constraints:  
\[(\textbf{Q},ATT_{RS},d_{0 RS},d_{1 RS},d_{2 RS},d_{unRS})=U(\textbf{C}(\textbf{RS })) \tag{6}\]  
The value of \(ATT\), along with other route evaluation criteria, is derived from the transit assignment process, which is represented by Equation (6) [34] and is addressed in Section 3. \[s_{\min}\leq s_{R}\leq s_{\max},\;\forall R\in RS \tag{7}\]  
Equation (7) specifies the minimum and maximum number of stops per route. \[R\
eq K\;\forall R,K\in RS \tag{8}\]  
Equation (8) states that two individual routes cannot coincide. \[|RS|\leq RM \tag{9}\]  
Equation (9) specifies the maximum number of lines. \[d_{unRS}=0 \tag{10}\]  
Last, Equation (10) states that the percentage of unsatisfied passengers must be zero.
## 2 Methodology of Time-Frequency Separation Neural Network
### Enhanced Defect Detection with a Time-Frequency Separation Neural Network  
As shown in Figure 2, a time-frequency separation neural network (TFSNN) was proposed on the basis of an instantaneous mixing scenario in order to separate the independent acoustic source and identify the AE defect signal. The topological structure of TFSNN mainly includes two parts, a TF feature extractor and a separation weight estimator. Notably, estimating the separation sources or weights is the ultimate aim in such a self-organizing structure. The training process of this network is also the estimating process of the final separation weights. In this sense, the output of this network is specified for a certain mixing system or weights, and the network should be retrained if the mixing system changes. In addition, the whole-length mixture observations are the only data provided to the network, which can be regarded as both training and testing datasets. Given a set of mixture observations, \(\mathbf{x}(t)=[\mathbf{x}_{1}(t),\cdots,\mathbf{x}_{m}(t)]\), the signals should first be centralized (subtracting their mean) and pre-whitened to guarantee the uncorrelated hypothesis just as the conventional ICA theorem requires. According to authors' previous work, the pre-whitening process could be easily achieved through singular value decomposition (SVD) or Schmidt orthogonalization of the observations' autocorrelation matrix [11]. Then, the pre-whitened signals are transformed into spatial time-frequency distributions (STFDs), using SPWVD to obtain a high-resolution representation in both the time and frequency domains. Subsequently, following the temporal order, the frequency spectrum in the STFDs is successively fed into the feature extractor of the network in a frame-by-frame manner.
# A Lyapunov-Optimized Dynamic Task Offloading Strategy for Satellite Edge Computing
###### Abstract  
Satellite edge computing (SEC) has garnered significant attention for its potential to deliver services directly to users. However, the uneven distribution of receiving tasks among satellites in the constellation can lead to uneven utilization of computing resources. This paper proposes a task offloading strategy for SEC that aims to minimize the average delay and energy consumption of tasks by assigning them to appropriate satellite nodes. The approach uses Lyapunov optimization to convert the long-term optimization problem with task queue length constraints into an assignment problem within a single time slot and solve it based on the Hungarian algorithm. Experimental simulations have shown that the proposed algorithm performs better than other baseline algorithms.  
satellite edge computing; task offloading; Lyapunov optimization; Hungarian algorithm +
Footnote †: journal: Applied sciences
# Nozzle with a Feedback Channel for Agricultural Drones
## 1 Introduction
However, these studies have been limited to evaluating the nozzle performance, and research on the spray system is insufficient. Therefore, further research into spraying systems for agricultural drones is needed [20; 21]. The spraying performance of agricultural drones can be evaluated through various factors, such as the effective spray width, spray uniformity, droplet size, spray droplet adhesion rate, and scattering characteristics. However, research on existing agricultural drones focuses mainly on improving the effective spray width. In addition to the spaying width, the important issue in agricultural spraying is to maintain an even liquid distribution and to avoid the drift of the droplets. Especially, drifting is an important and costly problem because it requires additional air flows in some applications. It is well-known that this drift problem depends on the droplet size. The droplet size also affects the penetration performance of the spray into the crops. Therefore, in this study, we developed a nozzle with a feedback channel for the spraying system of agricultural drones that can improve the effective spray width, droplet size, and spray uniformity.
## 4 Results  
### Usage of Service Facilities and Visitor Age Recognition Results  
Figure 5 illustrates the usage of service facilities in the rest areas near Ginkgo Avenue, FangQiao, and LingQiao, along with the age identification results of the visitors.  
Figure 5: Service facility usage and visitor age recognition results.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Evaluation Standard** & **Aging-Friendly Adequacy Rate** \\ \hline F \(<\) 30\% & High \\
30\% \(\leq\) F \(\leq\) 70\%, Y \(\leq\) 90\% & Relatively high \\
30\% \(\leq\) F \(\leq\) 70\%, Y \(>\) 90\% & Relatively low \\ F \(>\) 70\% & Low \\ \hline \hline \end{tabular}
\end{table}
Table 3: Evaluation standards for the aging-friendly adequacy rate of rest area facilities in scenic areas.  
The age recognition accuracy test was conducted using a video captured on a different day, taken from Position 2 on a weekend afternoon. The video had a duration of one hour, with one photo taken every minute. The test results indicate that the recognition accuracy for service facility usage was 88.3% while the accuracy of age range identification was 89.2%, demonstrating a high level of precision.  
The reasons for incorrect judgments of service facility usage include passersby obstructing individuals using the facilities; children, due to their short stature and body frame with a height-to-width ratio of less than 2.5, being mistakenly counted as occupying seats when passing by; individuals sitting in wheelchairs directly in front of the facilities being incorrectly identified as occupying seats; and mutual occlusion between individuals sitting on the chairs. The reasons for incorrect age recognition include visitors sitting with their backs or sides to the camera, resulting in incomplete facial information; faces being obscured by hats, clothing, etc.; and varying lighting conditions affecting age recognition. The error recognition situation is shown in Figure 6.
## 5 Evacuation Modeling Packages
### Microscale
#### 5.3.3 Microscale Models  
Quadstone Paramics and EXODUS are powerful tools for analyzing detailed traffic behavior at the individual vehicle or pedestrian level. These microscale models can be used to validate predetermined transportation evacuation plans and procedures and assess the effectiveness of novel emergency evacuation management methods, such as contraflow. By simulating traffic interactions and movements at a micro level, these models can identify bottlenecks and evaluate the effects of individual vehicle movements on overall traffic during evacuations. EXODUS, in particular, is designed to simulate large-scale evacuations with hundreds of thousands of people in extensive environments, making it a valuable tool for modeling evacuation scenarios in densely populated urban areas.  
By leveraging the capabilities of these simulation packages, emergency management authorities, urban planners, and researchers can gain valuable insights into the evacuation process under wildfire threats. The use of macroscale, mesoscale, and microscale models allows for a comprehensive understanding of evacuee behavior, traffic dynamics, and the interplay between wildfire behavior and evacuation decisions. This holistic approach can significantly enhance the development of evacuation strategies and ultimately contribute to saving lives and protecting communities in wildfire-prone regions.  
The following Table 1 provides a comprehensive overview of various evacuation software across different scales, ranging from macro to meso to micro. The table highlights the main features and their potential usability in such scenarios.
## 4 The Prediction Model When Signal Approaches the Ground Station (Section B)
### Measuring Building Shadowing Loss  
Building shadowing loss relates to the transmission loss through a building, as illustrated in Figure 7. Measurements were formulated to calculate values of building shadowing loss to be used in planning frequency sharing between the satellite and ground station. For example, the average loss through a concrete/brick building for a frequency of 11 GHz with vertical and horizontal polarization is 30.1 dB (standard deviation 5.0) for V-Pol and 28.6 dB (standard deviation 5.5) for H-Pol.
# Radiation Hardened Read-Stability and Speed Enhanced SRAM for Space Applications
## 2 Proposed RHRSE-20T SRAM
### Double Node Upset Recovery Analysis
#### 2.6.2 Single Event Transient Occurs Simultaneously at Nodes Q and S0
Through this process, all nodes are restored to their original states. 2.7. Multiple Node Upset Recovery Analysis  
Single Event Transient Occurs Simultaneously at Nodes Q, QB, S0, and S3  
The recovery process for all potential cases of MNU is presented in Figure 6. Due to the layout technique that isolates node S1 from the other nodes, MNU only considers scenarios where Q, QB, S0, and S3 are simultaneously affected by radiation. When SETs occur simultaneously at nodes Q, QB, S0, and S3, Q changes from '1' to '0', QB from '0' to '1', S0 from '0' to '1', and S3 from '1' to '0'. This situation activates transistors P3, P1, and N5. However, these changes do not affect the values stored in S1 and S2. Because node S1 firmly maintains its '1' state and activates transistor N1, even if P1 is temporarily activated by radiation, S0 is restored to '0'. The recovered S0 then activates transistor P6, restoring S3 to '1'. The restored S3 subsequently activates transistor N4. Since N4 has a wider channel width than P3, even with P3 being activated, QB is restored to '0'. Consequently, QB activates transistor P4, and Q is also restored to '1', ensuring that all nodes recover to their original states.
# A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem
## 4 5-Approximation Algorithm for \(P\big{|}s_{j},p-batch,K_{i}\big{|}C_{\max}\)
By Lemma 1, for \(i=i_{\max}+1,i_{\max}+2,\ldots,m\), we have  
\[\sum\limits_{g=1}^{h_{i}-1}p_{s}(B_{i,g})\geq\sum\limits_{g=1}^{h_{i}}p(B_{i, g})-p(B_{i,1})>T. \tag{8}\]  
It follows that  
\[\sum\limits_{j\in\bigcup\limits_{i=\max}^{m}\bigcup\limits_{l_{i}}\bigcup \limits_{l_{i}}B_{i,g}}p_{j}\cdot s_{j}>\sum\limits_{i=i_{\max}+1}^{m}K_{i} \cdot T. \tag{9}\]  
In \(\Sigma\), all the short jobs in \(\bigcup\limits_{i=i_{\max}+1}^{m}\bigcup\limits_{g=1}^{h_{i}}B_{i,g}\) have to be processed on machines \(M_{i_{\max}+1},M_{i_{\max}+2},\ldots,M_{m}\). In addition, we have also proved that the overall processing time \(\sum\limits_{j\in H\cap\bigcup\limits_{i=i_{\max}+1}^{m}\mathcal{B}_{i}}p_{j}\) of the planned long and median jobs on machines \(M_{i_{\max}+1},M_{i_{\max}+2},\ldots,M_{m}\) in \(\Sigma\) as a lower bound. Therefore, the above inequality shows that \(\Sigma\) cannot make all of the jobs done in the \(T\geq OPT\) time, which is a contradiction. The algorithm performs a binary search within the range \([LB,UB]\). Finally, we will get a schedule with one-job-overfull batches (Figure 1a) whose makespan is at most \(9 OPT/4\). We can turn it into a viable scheduling solution (Figure 1b), where the maximum completion time is \(9 OPT/2\), as follows: for each one-job-overfull batch, move the last packed job into a new batch and calculate the new batch on the same machine. Since the iterative number could be \(O(\log(\sum_{j=1}^{n}p_{j}))\), then the following theorems are obtained. Figure 1: Illustration of the 4.5-approximation algorithm. (**a**) The 4.5-approximation algorithm with one-job-overfull batches. (**b**) The 4.5-approximation algorithm with a feasible schedule. **Theorem 1**. : _There is a 4.5-approximation algorithm for \(P\big{|}s_{j},p-batch,K_{i}\big{|}C_{\max}\) that runs in \(O(n^{2}+mn\log p_{sum})\) time, where \(p_{sum}=\sum_{j=1}^{n}p_{j}\)._  
In order to achieve a strongly polynomial time algorithm, we use a technique described to modify the above algorithm slightly. Therefore, the following theorems are obtained. **Theorem 2**. : _There is a \((4.5+\varepsilon)\)-approximation algorithm for \(P\big{|}s_{j},p-batch,K_{i}\big{|}C_{\max}\) that runs in \(O(n^{2}+mn\log(1/\varepsilon))\) time, where \(\varepsilon>0\) can be made arbitrarily small._
# Assessment of Active Wheelset Steering System Using Computer Simulations and Roller Rig Tests
## 3 Computer Simulations  
The idea of actively controlled wheelsets steering is not entirely new. Various wheelset steering algorithms have been already proposed and tested by computer simulations [17]. Feed forward approach will be applied in this study. This method is based on the control of the yaw angle of both wheelsets with respect to the bogie frame. This is achieved by controlling the position of actuators that acting in the longitudinal direction between the bogie frame and axle-boxes. The required actuator position, determining yaw angle of wheelset, is a function of the track curvature. The advantage of this method is a relative simplicity, as the control algorithm does not require knowledge of time variable and difficult-to-measure inputs such as actual wheel profile or creep coefficients. For the practical implementation the two fundamental tasks have to be solved:  
* detection of the actual track radius;
* control algorithm of wheelset steering.  
Computer simulations are planned in several steps. In the initial phase a simplified vehicle model was used, and a large number of simulations was performed in order to compare various approaches of detecting the track curvature and the algorithms for controlling wheelset steering. The performance of selected solution will be consequently assessed by detailed simulation model of an electric locomotive. The simulations focused on the detection of the track radius using simplified vehicle model are described in this study, the simulations focused on the comparison of control algorithms, as well as simulations with detailed vehicle model, will be published in subsequent papers.