esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Field Experiments  
This section describes two experimental testbeds, one for testing UPD localization techniques and the other for testing the RTK positioning system used on the autonomous tractor. Field tests for both the GNSS and RSSI UPD localization techniques were performed during autumn of 2013 at the FTW field experiment site in the Danube Park (latitude: 48 deg14'16.0\" N, longitude: 16 deg44'29.6\" E). RTK field tests were performed over a one-week period during the winter of 2013 at the Center for Automation and Robotics field experiment site at the Spanish National Research Council (CISC) in Madrid (latitude: 40 deg18'48.9\" N, longitude: 03 deg28'54.8\" W).
# Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review
## 5 Inversion Analysis of Characteristic Parameter
### Traditional Inversion Analysis Method  
The inversion analysis of material characteristic parameters is ultimately attributed to solving the function problem or the minimum residual problem of the sum of squares of minimum values [69]. The traditional inversion analysis method for determining the characteristic parameters of formation materials is mainly based on solving the minimum problem defined by the objective function.  
In 1983, one of the main early researchers of the displacement inversion analysis method, [PERSON], a Japanese scholar, established the inverse analysis method of tunnel displacement based on gradient search method and proposed the nonlinear programming theory of the linkage constraints between the identified parameters and the observed data [10], which can be expressed as Equation (4).  
\[\min\{J(m,d_{m})\},m\in R^{P},d_{m}\in R^{M} \tag{4}\]  
where \(R^{P}\) is the space of acceptable parameters, m represents the parameter vector to be identified, belonging to space \(R^{P}\) and dm is the observed data vector, belonging to space \(R^{M}\).  
The work of [PERSON] et al. [70] optimizes the relationship, uses the norm metric to obtain the objective function of the least square problem for parameter identification, such as the following formula, and compares different kinds of parameter inversion methods.  
\[J(p)=\left(d_{m}-d_{c}(m)\right)^{T}\omega(d_{m}-d_{c}(m)) \tag{5}\]  
where \(\omega\) is the weight matrix, considering the influence of the observation data of different observation points on the parameter identification results; \(d_{c}(m)\) is the data vector calculated by the model, which can be regarded as a function of the dependent variable m.  
If the computational model of parameter inversion is viewed as an optimization model, the computational process will transform into the problem of solving the optimal solution of the original model. At that time, Levenberg-Marquardt algorithm was proved to be one of the most effective methods to solve unconstrained optimization problems [71], so the least square parameter back analysis method based on this algorithm came into being. [PERSON] et al. [72] studied the Bayesian method for the inversion of an elastic-plastic parameters of rock mass. [PERSON] and [PERSON] [73] used the dual boundary control method (see Figure 10) to study the inversion of elastic parameters. [PERSON] et al. [74] carried out the elastic-plastic inversion analysis of rock mass parameters. This kind of inversion analysis is regarded as an alternative calculation problem of the nonlinear least square method, for which a unique solution of the parameters is found after global optimization design.  
However, due to the uncertainty of observation information, the traditional parameter inversion analysis method cannot obtain practical parameter identification results in the early research stage, and the mathematical formula is cumbersome, which is difficult to apply to practice.
# Data Anonymization for Hiding Personal Tendency in Set-Valued Database Publication
## 4 Proposed Method
### Item Selection for Partial Swapping  
The concept of swapping in this proposal is different from the existing swapping techniques. At first, we count the frequency of items in each \(t_{k}\in\mathcal{D}\) based on its category. Thus, we can understand the magnitude of an individual tendency from his/her record.  
It is undoubtedly true that randomly swapping items from a record to another record can successfully hide personal tendency. However, such an operation may reduce usefulness of the modified database. To avoid such a negative effect, we introduce our heuristic solution called mean tendency value (\(MTV\)) which acts as a threshold. The \(MTV_{t_{k}}\) is determined for each \(t_{k}\) by dividing the record's length \(|t_{k}|\) over the number of categories \(g_{j}\) whose items appear in the \(t_{k}\), as shown in Equation (5). For each \(g_{j}\) which has weight higher than \(MTV_{t_{k}}\), add all the \(g_{j}\) into a bucket \(Cg\). After that, we select the \(g_{j}\) with the highest weight out of \(Cg\) as \(g_{j}^{\prime}\) and obtain all the items of the selected \(g_{j}^{\prime}\in t_{k}\) as the items for swapping. Such procedures of item selection is shown in Algorithm 1 which outputs a set of \(I_{swap}=\{I_{k}|t_{k}\in\mathcal{D}\}\) where \(I_{t_{k}}=\{i|i\in t_{k}\wedge i\in g_{j}^{\prime}\}\).  
However, if all the \(WR_{t_{k},gj}\) in \(t_{k}\) have equal value with \(MTV_{t_{k}}\), we do not swap any of its items to the other records since there is no significant information to learn about the individual that has an equal tendency to all \(g_{j}\).  
\[MTV_{t_{k}}=\frac{|t_{k}|}{|\{g_{j}\in C|i\in t_{k}\wedge i\in g_{j}\}|}, \tag{5}\]  
where \(G\) is a set of all categories of the database as explained in Section 3.  
```
INPUT : \(\mathcal{D}\); OUTPUT : \(I_{swap}\) ; // \(I_{swap}\) is a set of items from selected \(g_{j}^{\prime}\) Read \(\mathcal{D}\);  Set \(C_{g}\) as an empty set; foreach\(t_{k}\in\mathcal{D}\)do  compute the \(|t_{k}|\);  compute the \(MTV_{t_{k}}\); foreach\(g_{j}\in t_{k}\)do if\(WR_{t_{k},g_{j}}>MTV_{t_{k}}\)then  append \(g_{j}\) to \(Cg\);  end if  end foreach\(g_{j}^{\prime}\gets g_{j}\) having the maximum weight out of \(C_{g}\);  select \(i\in g_{j}^{\prime}\) as items for swapping;  clear the \(C_{g}\);  end fore
```  
**Algorithm 1**Procedure of item selection.
## 4 Discussion
### Limitations  
Considering the scope and depth of this review, there are several limitations that may affect the completeness and applicability of the results. Limitations in the literature reviews can arise in the pre-selection of papers due to restrictions in the search string. Web of Science is one of the most widely used principle search systems [242], and makes the literature searches reproducible and, if the complexity remains at a reasonable level, transparent [243].  
However, Boolean expressions like \"AND\" make the search very sensitive [244] and depend on clear formulation by authors. At the same time, Boolean strategies allow for clear delineations [243; 244].  
For example, the timeframe from January 2014 to January 2024 excludes studies published before and after this date. However, as remote sensing is developing rapidly [55; 89; 90], especially in forestry applications [58], and this review is intended to represent the current state of research rather than historical development, our timeframe was considered to be appropriate, especially since important milestones in remote sensing took place after or around the beginning of the timeframe, such as the launch of the Copernicus program [91], the commissioning of Landsat 8 [93], or the launch of commercial high-resolution satellite fleets such as Planet [235].  
The non-use of the term \"disturbance\" in the search string and the exclusion of terms such as \"beetle\" or \"inscets\", which describe biotic disturbances, had a major influence on the selection of studies examined. Avoiding the term \"disturbance\" was intended to circumvent a one-sided focus on disturbances in the forest and not necessarily on forest responses to changing climate conditions or EWEs. Examples of this would be the changes in phenology or the effects on productivity as described in the results. Consequences, such as bark beetle infestations or forest fires, are closely related to weather extremes in the forest, especially drought. Excluding \"fire\", \"beetle\", and \"insect\" resulted in a reduction in over 70 papers that were selected as relevant before the manual filter.  
However, by excluding these terms from the TI and AK, it was ensured that papers in which the bark beetle occurs were not generally excluded, but that papers dealing centrally with this biotic disturbance were excluded. Again, this restriction was important in order to be able to make statements about the influence of extreme events that are as independent as possible.  
The final evaluation of the individual papers is influenced by the categorization of the contents, which can lead to a loss of information. In order to provide an overall picture of the current state of science, these supplements are important. They enable a straightforward comparison of the databases, methods, and results of different studies.
# Beyond Static Estimates: Dynamic Simulation of Fire-Evacuation Interaction in Historical Districts
## 2 Methods
### Indicators in Analysis
#### 2.6.1. Built Environmental Indicators  
Fire propagation patterns and intensity are assessed through quantification of burned and actively burning structural areas, expressed as percentages of the total study area. Additionally, the impacts of structural and environmental modifications resulting from fire events are measured through detailed spatial analyses of high-temperature zones. Key indicators include the proportional area covered by high-temperature zones, perimeter measurements, and centroid distances relative to ignition points, given their significant influence on evacuation route viability. Further evaluations consider road network conditions, specifically measuring the proportion of impassable segments within the overall network, blockage rates on principal evacuation routes, and the generation of dead-end streets.
## 4 Use Case in the Energy Wholesale Market  
### Integrating Forecasting Error into Energy Procurement Strategy  
In this use case, the challenge of mitigating risks associated with the mean absolute percentage error (MAPE) in electrical load forecasting was addressed by incorporating MAPE into our energy procurement strategy. Specifically, the MAPE have to be taken into consideration to evaluate potential forecast inaccuracies and adjust the energy procurement accordingly. This conservative strategy involves purchasing additional energy beyond the forecasted load as a countermeasure for potential shortfall deviations.  
Moreover, two different scenarios will be assessed to compare [40] their outcomes with the standard contract in the Greek energy market. The first scenario will explore an isolated Spot Market aggregation of the portfolio, while the second will take a more feasible approach to account for forecast uncertainty including the Futures Market. Both scenarios will be evaluated against a typical contract framework in the Greek market, factoring in the costs and risks associated with Real-Time Market fluctuations. The primary objective remains to minimize the likelihood of incurring penalties or purchasing missing energy quantities at higher prices in the Real-Time Market, which is generally far more expensive than the Day-Ahead Market (DAM), as well as that the portfolio is always balanced against energy shortfalls. This dual-scenario analysis will offer a comprehensive comparison to ensure a robust and cost-effective strategy in conjunction with the added or lost value in comparison with the selected contract in Greece.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Framework** & **Model Category** & **MAPE (\%)** & **Time (s)** \\ \hline AutoTS & Model Averaging & 14.01 & 14.4 \\ FlaML & Hyperparameter Optimization & 13.95 & 13.3 \\ AutoML by H2O & Bagging, Boosting, Stacking, Hyperparameter Optimization & 12.89 & 16.8 \\ \hline \end{tabular}
\end{table}
Table 1: Results of different AutoML frameworks.  
Figure 3: Actual and predicted values.
## 4 Materials and Experimental Results
### Ablation Experiments
The unspecifically labelled LSTM model takes the output of the last time step as the input to softmax. For the binary classification task, the combined CNN and LSTM model achieves an average accuracy of 84.45%, indicating that the combined model can integrate the temporal-frequency-spatial information of the multidimensional features well and produce good results. Bi-LSTM overcomes the limitation of LSTM in learning sequences only sequentially by learning sequences in both directions and combining the hidden layer states to determine the output results, which improves accuracy by approximately 4% compared to the CNN-LSTM model. SENet can focus on important channels in the feature matrix and improve model accuracy by assigning different weights. FeaNet uses two-dimensional discrete cosine variations to compress the feature map, avoiding the loss of frequency components caused by SENet and improving accuracy by 2% at a subtle computational cost. Additionally, to highlight the importance of different frame moments in the sample, the weighted sum of all time step hidden layer states is chosen as the output, achieving the best accuracy of 94.58%. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & \multirow{2}{*}{**Metrics**} & **Accuracy (\%)** & **Training** & **Testing** \\  & & **(avg)** & **Time (s)** & **Time (s)** \\ \hline \multirow{4}{*}{CNN-LSTM} & Valence & & & \\  & Arousal & & & \\  & Dominance & & & \\  & Liking & & & \\ \hline \multirow{4}{*}{CNN-BiLSTM} & Valence & & & \\  & Arousal & & & \\  & Dominance & & & \\  & Liking & & & \\ \hline \multirow{4}{*}{CNN-SENet-BiLSTM} & Valence & & & \\  & Arousal & & & \\  & Dominance & & & \\  & Liking & & & \\ \hline \multirow{4}{*}{CNN-FcaNet-BiLSTM} & Valence & & & \\  & Arousal & & & \\  & Dominance & & & \\  & Liking & & & \\ \hline \multirow{4}{*}{Ours} & Valence & & & \\  & Arousal & & & \\  & Dominance & & & \\  & Liking & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Ablation experiments for different structural models.
# Analysis of Shielding Effectiveness of a Cavity with Internal Dielectric Plate and Apertures
## 4 Conclusions  
This study focuses on the characteristics of single-layer shielded cavities, combining transmission line theory, the Robinson algorithm, and electromagnetic topology theory, and derives the BLT equation to calculate the shielding effectiveness of single-layer cavities under plane-wave irradiation, with verification through HFSS simulation. This study considers the effects of hole size, shape, quantity, dielectric plate thickness, and position on shielding effectiveness. The results indicate that reducing the size of a single hole and increasing the number of hole arrays can significantly improve the shielding effectiveness when the aperture area is fixed. The presence of a dielectric plate effectively suppresses the resonance of the cavity, significantly improving the shielding efficiency near some resonance frequency points, which significantly improves the shielding efficiency. In addition, the influences of different thicknesses and positions of the dielectric plates on the shielding effectiveness were explored. The simulation results showed that as the thickness of the dielectric plate was increased, the resonant frequency of the cavity gradually decreased, which improved the shielding efficiency near the resonant frequency point of the cavity. Adjusting the position of the dielectric plate had a significant impact on the suppression effect of the resonance point. The shielding efficiency of the cavity can be effectively improved by adjusting the position of the dielectric plate.  
This study provides theoretical guidance and technical support for safe coal mine production in an electromagnetic interference environment and has reference value for electromagnetic compatibility design in other fields. Through in-depth analysis of the shielding effectiveness of perforated cavities, a scientific basis for electromagnetic compatibility design is provided to more effectively protect electronic devices from electromagnetic interference, ensuring the stable operation of equipment and personnel safety.  
Conceptualization, X.S.; Methodology, L.G.; Software, X.L.; Validation, C.G.; Resources, L.M.; Writing--original draft, X.S.; Writing--review & editing, X.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the 14 th Five Year National Key R&D Program Project (Project Number: 2023 YFB3211001).  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflict of interest.
# An Efficient RRT Algorithm for Motion Planning of Live-Line Maintenance Robots
## 5 Simulation and Experiment
### Field Test  
Two field operations were carried out in August 2021, including a drainage operation in Figure 24 and a broken drainage operation in Figure 25. The two field tests were mainly to verify whether path planning can improve work efficiency. We compared the efficiency of manual operations, teleoperation operations, and path planning.  
The time for the system to complete three drainage is 40 min, and the manual operation time for the same task is about 30 min (including wearing protective equipment). In order to ensure the safety of operation, each trajectory of the robot is executed only after the safety is confirmed manually, which takes a lot of time (25-30 min according to the video recording).  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Wire Stripping**} & \multicolumn{3}{c}{**Clamp Installation**} \\ \hline \multirow{2}{*}{**Planning Algorithm**} & **RRT* -Offline** & **RRT** -Connect** & **RRT* -Offline** & **RRT** -Connect** & **RRT* -Connect** & **RRT* \\ \hline Number of collisions & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline Potentially dangerous path & 0 & 3 & 4 & 4 & 7 & 5 \\ \hline success of first planning & 15 & 16 & 15 & 14 & 10 & 7 \\ \hline Result optimality & 1.52 & 7.61 & 2.44 & 1.71 & 5.23 & 3.20 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation results at the test site.  
In addition, we compared the time-consuming of manual operation and automatic operation in the process of fire removal. In manual operation, the operator needs to remotely control the manipulator to move the tool to the target position, and a single operation takes about 3-7 min. The automatic operation takes less than 1 min (including cable positioning process).  
Figure 23: The impact of planning algorithms on the task process. (**a–c**) During the stripping operation, the non-fixed parts should be kept open during the tool removal operation. (**d–f**) During the movement of the long tool, each joint of the robot is in a proper state of force and the load capacity is improved. (**g–i**) During the installation of the cable, the robot body maintains the principle cable to prevent entanglement.)  
Figure 24: Field work: drainage operation on overhead lines. ((**a**) wire stripping, (**b**) inspect stripping quality, (**c**) install the clamp, and (**d**) single-phase drainage operation is complete).
# Performance Analysis of RIS-Assisted SatComs Based on a ZFBF and Co-Phasing Scheme
## 5 Conclusions  
In this paper, we conducted an asymptotic analysis of a ZFBF combined with the co-phasing technique for mitigating IBI and IRI in RIS-assisted SatCom systems. In particular, we analyzed the performance of the ZFBF combined with co-phasing technique based on full CSI and demonstrated that IBI and IRI are asymptotically eliminated as the number of RIS elements increases to infinity. To make the analysis more practical, we proposed a novel deterministic ZFBF and co-phasing technique that only requires partial CSI, while still achieving asymptotic elimination of IBI and IRI. Furthermore, we derived a closed-form expression for the asymptotic ergodic capacity of the proposed scheme, allowing us to accurately determine the system's performance without extensive simulations. Additionally, we proved that the outage probability decreases as \(N\) increases, confirming the RIS's ability to provide reliable SatCom services in a large \(N\) regime. The simulation results validated the accuracy of our asymptotic analyses, and we observed consistent results between the approximated ergodic capacity and actual simulation results. Moreover, the proposed scheme demonstrated asymptotic optimality as it closely achieved the ideal performance, and this verifies the effectiveness of the proposed scheme in achieving optimal performance. Additionally, the outage probability demonstrated a potential convergence to zero as the number of RIS elements increases to infinity, further supporting the reliability and efficiency of the proposed scheme.  
Figure 3: Performance comparison of the outage probabilities for \(N\).  
**Author Contributions:** Conceptualization, M.J.; methodology, T.K. and H.S.; software, M.J.; validation, M.J., T.K. and H.S.; formal analysis, M.J.; investigation, M.J.; resources, M.J.; data curation, M.J.; writing--original draft preparation, M.J.; writing--review and editing, T.K. and H.S.; visualization, M.J.; supervision, T.K. and H.S.; project administration, M.J., T.K. and H.S.; funding acquisition, M.J., T.K. and H.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) under the metaverse support program to nurture the best talents (IITP-2023-RS-2023-00254529) grant funded by the Korean government (MSIT) and by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (No. 2022R1F1A1064106, No. 2021R1C1C1012950, and No. 2021R1F1A1051075).  
**Data Availability Statement:** Data are contained within the article.  
**Conflicts of Interest:** The authors declare no conflicts of interest.