esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### DUS-Guided Procedural Optimization  
In the present study, the intraoperative DUS assessment guided further treatment such as post-dilatation or stenting that eventually produced an integrated technical success rate of 95%. Of note, following our purposed optimization algorithm, the final stent rate increased significantly from 8% (5/62) to 23% (14/62) since in nine cases, balloon post-dilatation only failed to fix residual stenosis or seal flow-limiting dissections properly. In fact, in our study, the reported stent rate (23%) was higher than those reported in the LONG SFA study (10.5%) or in the reports of the ILLUMINATE Global Study (17.3%) [15,16]. In this regard, it is important to underline that despite the bail-out stenting of the superficial femoral artery being generally accepted, it might also result in restenosis due to neointimal hyperplasia secondary to the mechanical damage of the arterial wall produced by the stent itself. However, the stenting of heavily calcified lesions, such those in our studypopulation, often results in persistent residual stenosis and should therefore be avoided unless anticipating adequate lesion preparation using calcite plaque modification devices (CMPDs). Indeed, devices like intravascular lithotripsy (IVL) or debulking systems like atheectomy were shown to be safe and effective for the treatment of heavy calcite plaque at different vascular districts, including lower limb arteries [17; 18; 19]. In our study, CPMDs had never been employed, but in consideration of the fact that the proportion of moderate to severely calcified lesions was very high (56%), it would have been possible to lower the stent rate if a proper lesion preparation by CPMD had been performed systematically in cases of persistent residual stenosis despite many conventional balloon dilatations.  
Compared to other more expensive intravascular imaging modalities, such as IVUS or OCT, intraoperative DUS has the advantage to minimize the impact on procedural costs, and it is also available in most Cath-labs where peripheral interventions are performed. Furthermore, in patients with severe chronic kidney disease (CKD), intraoperative DUS may reduce the total procedural load of contrast if used instead of angiography to assess the results after lesion pre-dilatation, after DEB angioplasty, post-dilatation, or after stenting. This strategy might represent a valid and cheaper alternative to CO2 angiography to reduce the incidence of contrast-induced nephropathy among patients with CKD undergoing peripheral angioplasty.
## 3 Our Implementation
### Termination Criteria  
The proposed NBV exploration process ceases when specific criteria are met, indicating either completion or the inability to make further progress. Primarily, termination occurs when the algorithm fails to determine a valid next best view. This situation arises if there are no more suitable candidates generated, all candidates are discarded in the filtering  
Figure 3: Illustration of the information gain calculation.  
stage or all filtered candidates subsequently fail necessary validation steps, such as inverse kinematics solvability or collision-free path planning, preventing the robot from reaching any potential view.  
Additionally, the exploration can be configured to terminate when the ratio of the explored volume to the total target workspace volume exceeds a predefined threshold (e.g., 95%), signifying sufficient coverage has been achieved, even if some unexplored frontiers might remain. This ensures the process concludes either upon comprehensive mapping according to the planner's logic or when a user-defined coverage goal is met.
# Detecting and Mitigating Attacks on GPS Devices
## 4 Factors Contributing to GPS-Denied or GPS-Disrupted Environments  
Several factors can contribute to GPS degradation or disruption, either intentionally through malicious attacks or unintentionally from unintended interference or propagation-related degradation. These factors include multipath fading, signal shadowing, unintentional interference, jamming, and spoofing. These various degradation factors have different degrees of implementation difficulty, require different levels of hardware and software complexity, and require varying levels of technical expertise to implement, making different attack scenarios more likely. Additionally, these various degradation factors have key differences in terms of potential effect, scope of the potential effect, and different potential ramifications. The various types of GPS degradation factors and their key characteristics are summarized in Table 4.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
\begin{tabular}{c} GPS-based navigation \\ is not possible or \\ is not possible or \\ causes crashes or \\ impacts due to \\ position error \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of GPS degradation factors.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Authors** & **Reference** & **Type of Results** & \begin{tabular}{c} **Scenario/Conditions** \\ **Considered** \\ \end{tabular} & **Factors Considered** & \begin{tabular}{c} **General Conclusions of** \\ **Accuracy** \\ \end{tabular} \\ \hline [PERSON] et al. & [38] & \begin{tabular}{c} Theoretical, \\ experimental \\ \end{tabular} & Various & \begin{tabular}{c} Geometry, number of \\ satellites, ranging errors, \\ types of receiver signal \\ processing and hardware \\ \end{tabular} & Position accuracy: 0.01–30 m \\ \hline [PERSON] & [39] & Theoretical & Various & \begin{tabular}{c} Location on Earth, various \\ error sources \\ \end{tabular} & \begin{tabular}{c} Variable: centimeters to \\ 10’s of meters \\ \end{tabular} \\ \hline [PERSON]. & [40] & Theoretical & Various & Various & Position accuracy: \textless{}10 m \\ \hline [PERSON] and & [41] & Theoretical & Open & \begin{tabular}{c} Single vs. multi-frequency \\ receivers \\ \end{tabular} & \begin{tabular}{c} Ranging accuracy: \\ 10–100 m \\ \end{tabular} \\ \hline [PERSON] and & [42] & Experimental & Urban stationery & Multipath propagation & Position accuracy: 7–13 m \\ \hline [PERSON] et al. & [43] & \begin{tabular}{c} Theoretical, \\ Experimental \\ \end{tabular} & \begin{tabular}{c} Urban stationary, \\ urban mobile \\ \end{tabular} & Multipath propagation & \begin{tabular}{c} Position accuracy: \\ \textless{}5 m \\ \end{tabular} \\ \hline [PERSON]. [PERSON] et al. & [28] & Theoretical & \
\begin{tabular}{c} Urban stationary, \\ urban mobile \\ \end{tabular} & Multipath propagation &
\begin{tabular}{c} N/A—Focus on \\ detection and acquisition \\ of GPS signals \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 3: _Cont._
# Recognition and Location Algorithm for Pallets in Warehouses Using RGB-D Sensor
## 2 Methods
### Grid Compressing Template and Category Matrix  
Because the size of the template and category matrix has a great impact on the speed of the algorithm, we propose a grid compression algorithm to speed up the algorithm by compressing the template and category matrix with less information loss. Because the size of the template and category matrix has a great impact on the speed of the algorithm, we propose a grid compression algorithm that compresses the template and category matrix to speed up the algorithm [47]. Meanwhile, the grid compression algorithm improves the robustness of the algorithm and reduces the impact of misclassification of pixels (shown in Figure 4) on the matching process. Because there are only four categories and most of the regions in them represent the same category, the template and category matrices contain a lot of redundant information, so the matrix size can be reduced, and most of the information can be preserved by grid compression.  
The grid compression operation is shown in Figures 4 and 5. The template and category matrix are compressed in the same proportion based on the grid. The size of each compression unit is \(s_{u}\times s_{u}\). \(s_{u}\) is calculated based on the size of the pallet in the template. The calculation principle is that the compressed grid of the template has the same category, and it retains the pallet structure information in the template. After compression, the template and category matrix are \(s_{u}\) times smaller. Finally, the information on the proportional number of categories in the compressed grid unit is retained by means of the homogenization vector. The grid units of the template and category matrices are represented by \(T_{ij}\) and \(M_{ij}\), respectively, as in Equations (9) and (10).  
\[T_{ij}=[\frac{c_{1}}{\sum_{t=1}^{A}c_{n}}\quad\frac{c_{2}}{\sum_{t=1}^{A}c_{ n}}\quad\frac{c_{3}}{\sum_{t=1}^{A}c_{n}}\quad\frac{c_{4}}{\sum_{t=1}^{A}c_{n}}] \tag{9}\]  
Figure 6: Diagram of the spatial relationship between the sensor and the pallet.  
\[M_{ij}=\begin{bmatrix}\frac{c_{1}}{\sum_{n=1}^{C}c_{n}}c_{n}\\ \frac{\sum_{n=1}^{C}c_{n}}{\sum_{n=1}^{C}c_{n}}\\ \frac{\sum_{n=1}^{C}c_{n}}{\sum_{n=1}^{C}c_{n}}\\ \end{bmatrix} \tag{10}\]  
where \(c_{n}\) represents the number of pixels of category n in the \(T_{ij}\), \(M_{ij}\) grid unit.
## 4 System Model and Description of the Proposed Protocols
### Transmission and Receiving Energy Calculations in BF-SPR-Three
#### 4.2.3 Layers Division in BF-SPR-Three  
In BF-SPR-Three network is distributed into sublayers for reliable data delivery. As the noise rate increases while moving from higher depth area towards the lower depth area. Therefore, in this protocol, the UWSN is distributed into unequal layers. These layers become closer near the sea surface and far in the sea depth. The reason for being closer is the high noise ratio at sea surface. This happens to reduce high noise ratio at the sea surface. The basic purpose of this approach is reliable data delivery and minimum packet drop ratio. Therefore, the ratio for the unequal layers distribution is computed by Equation (14).  
\[C(i,j)=\frac{k_{1}i_{2}+k_{2}i_{1}}{k_{1}+k_{2}},\frac{k_{1}j_{2}+k_{2}j_{1}}{ k_{1}+k_{2}}. \tag{14}\]  
Here, the endpoint coordinates are denoted by \(i_{1},j_{1},i_{2}\) and \(j_{2}\), whereas \(C(i,j)\) is the division point (see Figure 12). Whereas, the point \(C\) divides the line in \(k_{1}:k_{2}\) depending upon the strength of noise (using Equation (8)).
## 4 Experiment
### Performance Evaluation
#### 4.2.1 Taillight Detection  
For evaluating the performance of the proposed taillight detection method, 511 images were randomly selected from the raw dataset to create the test set. Each sample in this test set comprises two images that are the detection result and the corresponding ground truth, as illustrated in Figure 25.  
The number of correctly detected taillights is indicated by _Correct Detection_, the number of falsely detected taillights is indicated by _False Detection_, and that of the missed taillights is indicated by _Missed Detection_. They respectively play a role of _True Positive_, _False Positive_, and _False Negative_ in Equations (35) and (36). We evaluate the performance of the proposed taillight detection method in Table 4.  
Figure 25: Some test samples for taillight detection: (**a**) detection result; (**b**) ground truth image.  
The obtained results indicate that the recall rate is high as the proposed method can detect the candidate taillight region well. However, it comes along with a high value of _False Detection_, which makes the precision rate relatively poor. Although many false detections may be removed in the taillight pairing stage, the taillight detection needs to be improved in future work to make it more efficient for the real-time application.
# Sentinel: Automated Detection of Android Vishing Apps Using Optical Character Recognition
## 3 Background
### Malicious Behavior in Vishing Apps
#### 3.1.3 Duplicated Contacts  
Android provides APIs that allow developers to retrieve, and modify contacts stored on a device. Vishing applications exploit these APIs to exfiltrate or modify contacts on a victim's device for malicious purposes. Additionally, we introduce a malicious behavior called _Duplicated Contacts_. Duplicated Contacts involves adding the attacker's number to the victim's contact list under an existing contact name or editing it as a secondary contact. According to a FINLEY, [PERSON], et al. [25], many smartphone users store contacts on their devices rather than memorizing phone numbers, making Duplicated Contacts effective in tricking victims into thinking they are receiving a call from someone they know. Android users overlook the actual number displayed beneath the contact name, and iOS users do not see the number at all, allowing attackers to exploit this limitation.
## 2 Related Work
The basic idea for use of simulators is justified by the fact that deployment of real networks and gathering performance metrics is cumbersome, time consuming and economically not feasible for most of cases. Thus, the use of simulators provides ease of setting up and modifying network scenarios easily, and monitoring becomes more manageable. Furthermore, [18] have revealed the inherent limitations the simulation tools have in modeling the Media Access Control (MAC) and physical layer aspects of the network. It signifies that the results from a simulation tool are only good for approximation of the performance parameters. In this study, the use of multiple paths is also suggested as one of the possible ways to counter a security threat. In addition, there is a lack of consistency between the results of the same protocol being run on different simulation tools. In addition to the brief overview of different approaches presented above, a variety of other approaches have been proposed by researchers based on promiscuous monitoring of packets, trust based proposal, by introducing new control packets, and data structures, _etc_. On the basis of the reviewed schemes above, it was observed that additional overhead is being incurred by the approaches like prior knowledge of certificates, extra processing by intermediate nodes, use of additional control packets to nail down bad nodes, or dependence on the CAs. Trust among the entities plays a vital role. Thus, in the case of MANETs transmission through trusted parts can also save a lot of resources and provide a secure transmission, but trust alone is not sufficient to ensure the integrity and authenticity of the transmission. Thus, a new security framework is being proposed which does not depend upon any CA, saves resources of the participating peer nodes and does not require any knowledge about the network topology and density. It uses a combination of trust and cryptographic approach is used to safeguard of the data packets. As the cryptographic based computations are being done at the communication end, only so no additional load is incurred on the intermediate nodes, details are provided in Section 4.
# Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm
## 4 Experimental Setup
### Evaluation Metrics  
For evaluating the ATS process, the following four metrics are used: ROUGE, precision, recall, and F-measure.  
Recall-Oriented Understudy for Gisting Evaluation (ROUGE) compares machine-generated summary (or system summary) with respect to human-generated summary (or reference summary). _ROUGE-N_ measures n-gram recall or co-occurrences of n-grams which is calculated as is given in Equation (17).  
\[ROUGE-N=\frac{\sum_{R_{S}\in(reference\ summaries)}\frac{\sum_{gram_{R_{S}}\in R _{S}}Count_{match}(gram_{R})}{\sum_{R_{S}\in(reference\ summaries)}\sum_{gram_{R}\in R _{S}}Count(gram_{R})} \tag{17}\]  
where  
\(R_{S}\): reference sentence;  
\(N_{S}\): length of n-gram;  
\(Count(gram_{R})\): total number of n-grams in reference sentence;  
\(Countmatch(gram_{R})\): possible number of n-grams shared between system and reference sentence.  
The precision metric is also called a positive predictive value, defined as a fraction of the relevant instances retrieved over the total of the retrieved instances. In other words, the precision metric in the context of ROUGE determines how much of the system summary is, in fact, relevant, as is given in Equation (18).  
\[Precision=\frac{\textit{system\ summary}\cap reference\ summary}{\textit{ system\ summary}} \tag{18}\]  
Recall metric is also called sensitivity which is defined as a fraction of the relevant instances retrieved over the total of the relevant instances. In other words, recall metric in the context of ROUGE determines how much of the reference summary is the system summary recovering as is given in Equation (19).  
\[Recall=\frac{\textit{system\ summary}\cap reference\ summary}{\textit{ reference\ summary}} \tag{19}\]  
As stated in Equations (18) and (19), system summary \(\cap\) reference summary stands for the number of overlapping words between the system summary and reference summary [71]. An F-measure metric is also called an F-score which is defined in ROUGE as the harmonic mean of the precision and recall as is given in Equation (20).  
\[F=\frac{2*Precision*Recall}{Precision+Recall} \tag{20}\]In this research, ROUGE-N (N = 1, 2), i.e., ROUGE-1 and ROUGE-2 metrics are taken into consideration. ROUGE-1 determines an overlap of unigrams between system and reference summaries. ROUGE-2 determines an overlap of bigrams between system and reference summaries.
## 1 Introduction
### Novelties of This Article  
* The techno-economic reliability of providing energy to five off-grid communities in the Rayagada region of Odisha state in India was studied, leveraging existing renewable energy sources in the area, such as solar and biomass. Furthermore, a novel method of combining these two energy sources was proposed to create a reliable energy system that optimizes cost-effectiveness and maximizes sustainability. This new approach could be applied to other off-grid communities to provide secure and affordable energy access;
* Six specific configurations are modeled by the available RE sources and suggested batteries \"PV/BMG/LA@70% DOD, PV/BMG/LA@80% DOD, PV/BMG/Li-Ion@50% DOD, PV/BMG/Li-Ion@70% DOD, PV/BMG/Li-Ion@80% DOD, and PV/BMG/Ni-Fe@80% DOD\" with their varying depths of discharge to figure out which configuration will provide the most reliable power supply;
* To identify the most reliable power supply, six specific configurations of renewable energy sources and suggested batteries have been modeled, with varying depths of discharge. The configurations are PV/BMG/LA@70% DOD, PV/BMG/LA@80% DOD, PV/BMG/Li-Ion@50% DOD, PV/BMG/Li-Ion@70% DOD, PV/BMG/Li-Ion@80% DOD; and PV/BMG/Ni-Fe@80% DOD;
* This research has presented a unique solution for solving optimization problems--the salp swarm algorithm. This algorithm is a novel metaheuristic algorithmic approach that does not rely on predetermined parameters. Furthermore, the results obtained from testing this algorithm demonstrate superior performance to existing optimization algorithms across various metrics. This algorithm shows a high degree of robustness and convergence efficiency compared to eight other algorithms, including the particle swarm optimization (PSO) [21], differential evolutionary algorithm (DE) [22], genetic algorithm (GA) [23], ant lion optimization (ALO) [24], grasshopper optimization algorithms (GOA) [25], grey wolf optimization (GWO) [26], moth flame optimization (MFO) [27], and dragonfly algorithm (DA) [28]. It is clear that the salp swarm algorithm is a reliable and effective algorithm for solving optimization problems and can be used to significantly improve the performance of optimization solutions;
* This research not only explored various demand-side management techniques but also implemented energy-conservation-based demand-side management for the current study area. The results were impressive, as it effectively reduced peak-load demands and improved customer satisfaction while providing a reliable and cost-effective power system. Furthermore, with these successes in mind, this strategy can be applied to other areas in need of a demand-side management technique, allowing for a larger-scale approach to energy conservation and security. As such, this method proves to be an innovative, effective, and much-needed solution for meeting the growing energy requirements.
# Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review
## 6 Taxonomy
### Bias/Fairness Through Time
#### 6.13.3 Multidimensional Class Evaluation  
As shown in Table 30, this small class comprises two papers equally focused on general concept drift and data drift, explicitly addressing drift in fairness and bias metrics. This explicit focus underscores the growing recognition that fairness and ethical compliance require continuous monitoring over time, similar to traditional performance metrics. The singular application context identified is financial services, highlighting the critical nature of fairness tracking in high-stakes decision-making environments where model biases can have significant ethical and legal implications. Explanations are evenly balanced between local and global scopes, emphasizing the necessity of both detailed instance-level bias tracking and broader systemic assessments to ensure comprehensive fairness. The audience includes both data scientists and end-users, demonstrating a deliberate aim to transparently communicate fairness implications directly to stakeholders who may be affected by biased decisions. No explicit interpretability-related metrics are mentioned, suggesting that interpretability primarily arises directly from the fairness metrics themselves, such as SHAP-based bias scores, rather than from additional standardized measures. Hybrid learning modes dominate this group, highlighting the combination of immediate online monitoring for rapid bias detection with periodic offline analyses, effectively balancing responsiveness and thoroughness in bias mitigation.