esa-sceva/satcom-chunk-collection huggingface dataset:
# Blockwise Frequency Domain Active Noise Controller Over Distributed Networks
## 4 Experimental Results
However, when the nodes performs their local updating while waiting for the network information (_case 2_), the influence of the increased delay is lower than in case 1, obtaining an \(NR_{k}(t)\) in all cases only 5 dB lower than the case of an ideal network. Similar results are obtained for the node with the worst performance. Figure 9 shows the \(NR_{k}(t)\) curves of the worst node in the network with different values of \(p\), (**b**) for the case 1 and (**d**) for the case 2. Therefore, for networks with communication constraints, the behavior of the system can be improved if the nodes are allowed to update their filter coefficients while waiting for the network information. It is important to take into account that the final behavior of both cases depends on the degree of acoustic interaction between nodes, and, therefore, it should be studied in future works. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Operations** & **Generic** & \(\mathbf{N=1}\) & \(\mathbf{N=4}\) & \(\mathbf{N=8}\) \\ \hline \multirow{4}{*}{(1)} & MUX & 4 \(LN+4\)\(LN^{2}\) & 8 \(L\) & 80 \(L\) & 288 \(L\) \\  & ADD & \(LN+3\)\(LN^{2}\) & 4 \(L\) & 52 \(L\) & 200 \(L\) \\  & FFTs & 2 + 6 \(N\) & 8 & 26 & 50 \\ \hline \multirow{4}{*}{(2)} & MUX & 2 \(L+6\)\(LN\) & 8 \(L\) & 26 \(L\) & 50 \(L\) \\  & ADD & \(L+3\)\(LN\) & 4 \(L\) & 13 \(L\) & 25 \(L\) \\ \cline{1-1}  & FFTs & 4 + 4 \(N\) & 8 & 20 & 36 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Total number of multiplications (MUX), additions (ADD) and Fast Fourier Transforms (FFTs) per blockwise iteration of the FPBFxLMS algorithm in both: (1) centralized and (2) distributed ANC systems. \(L\): length of the adaptive filters; \(N\): number of nodes. Figure 9: _Cont._  
Finally, note that all the results accomplished in this work depend on particular settings, but their behavior can be easily extrapolated to other configurations.
## 2 Materials and Methods
\(\rm x_{mj,A}\) was calculated as the ratio of entering mixed traffic flow \(\rm q_{mj}\) in vehicles per hour and entry capacity \(\rm C_{mj}\) in vehicles per hour:  
\[\rm x_{mj,A}=\frac{\rm q_{mj}}{C_{mj}}, \tag{4}\]  
Figure 5: Base capacity at single-lane roundabouts as a function of outer radius. where \(\mathrm{x_{mj,A}}\) is the entry degree of saturation according to the analytical model, \(\mathrm{q_{mj}}\) is mixed traffic flow on legs' entry (veh/h), and \(\mathrm{C_{mj}}\) is entry capacity (veh/h). In the regression model, entry capacity \(\mathrm{C_{Ej}}\) in passenger car units per hour was defined as [1]  
\[\mathrm{C_{Ej}}=\frac{1}{\gamma}\ \bigg{[}1500-\frac{8}{9}\cdot\Big{(}\ \beta\cdot\mathrm{Q_{Cj}}+\alpha\cdot\mathrm{Q_{Sj}}\ \Big{)}\bigg{]}, \tag{5}\]  
where \(\mathrm{C_{Ej}}\) is entry capacity (pcu/h), \(\mathrm{Q_{Cj}}\) is circulating traffic flow in front of the leg being considered (pcu/h), \(\mathrm{Q_{Sj}}\) is exiting traffic flow on the same leg as the entry (pcu/h), \(\alpha\) is a factor reflecting the impact of exiting traffic on entry capacity by distance \(\mathrm{b_{j}}\), \(\beta\) is a factor for adjusting circulating flow depending on the number of circulatory lanes, and \(\gamma\) is a factor for adjusting entry capacity depending on the number of circulatory lanes. Conflict factor \(\alpha\) was determined from the chart in Figure 6 for measured distance \(\mathrm{b_{j}}\) and middle curve. The factors \(\beta\) and \(\gamma\) were set to 1.0, as single-lane circulatory roadways were investigated [1]. The degree of saturation of entry was defined as  
\[\mathrm{x_{mj,R}}=\frac{\gamma\cdot\mathrm{Q_{Ej}}}{\mathrm{C_{Ej}}}, \tag{6}\]  
where \(\mathrm{x_{mj,R}}\) is the entry degree of saturation according to the regression model, \(\gamma\) is a factor for adjusting entry capacity depending on the number of circulatory lanes (set to 1.0), \(\mathrm{Q_{Ej}}\) is entering traffic flow (pcu/h), and \(\mathrm{C_{Ej}}\) is entry capacity (pcu/h). To present the influence of \(\mathrm{R_{o}}\) and \(\delta\) on calculated \(\mathrm{x_{mj}}\), regression analysis was performed, and best-fit curves for \(\mathrm{x_{mj}}\) values were created. Second-degree polynomial curves with a coefficient of determination larger than 0.99 were used to visualize the trend. To further quantify the impact of the application of different models in the roundabout design process, the reversed calculation of traffic flow at each leg was performed according to the regression model methodology. The calculation was based on the condition that the intersection enables the same level of saturation as previously defined by the analytical model (i.e., for the previously determined values of \(\mathrm{x_{mj,A}}\)). With this reversed calculation, the potential traffic flow volume in veh/h was determined for each roundabout, summarized, and compared with the input total flow rate of 1800 veh/h. Figure 6: Conflict factor reflecting the impact of exiting traffic on entry capacity by the distance between exiting and entering traffic streams along the center of the circulatory lane.
# Sequential Polar Decoding with Cost Metric Threshold
## 5 Conclusions  
In conclusion, our research has yielded significant advancements in the realm of polar code decoding, culminating in the development of the improved SC-Creeper algorithm. Through extensive experimentation and rigorous analysis, we have demonstrated the efficacy of our approach in achieving notable performance improvements over conventional decoding techniques. The enhanced SC-Creeper decoder not only rivals but surpasses the capabilities of established methods such as CA-SCL-8 and traditional Fano decoding algorithms. For large code lengths, the improvement in performance is obvious for any length of the original message; the performance can not only overcome the value of SCL-8, but also approach SCL-16. Thus, with the help of additional control functions (threshold, cost), we can hypothetically increase the list of potential candidates for the correct codeword from 8 to 16.  
The new SC-Creeper uses a classic tree-moving scheme, as in the sequential Fano decoding strategy. However, this scheme has been improved with the ability to traverse only those nodes in the tree that lead to the most likely codeword. The cost function also allows us to ignore repeated passes of nodes, which was unacceptable in the original SC-Creeper.  
Our research is characterized by the application of innovative methods, including iterative refinement techniques and adaptive cost metric calculations, which contribute to the enhanced performance of the decoder. Through comprehensive experimental validation, we have meticulously assessed the decoder's effectiveness across a range of communication scenarios.  
Figure 7: Comparison of normalized complexity.  
It can also be noted that decoding based on the structure of the tree and its modifications is a promising direction nowadays [21; 22]. The development of more sophisticated decoding strategies, coupled with enhanced computational efficiency and scalability, will not only benefit high-throughput communication systems but also find application in a wide array of fields, ranging from wireless communication to data storage and beyond.
# Primary User Localization Algorithm Based on Compressive Sensing in Cognitive Radio Networks
## 1 Introduction
However, both merely concern the correlation between each beacon node and the goal node instead of the correlation between all the beacon nodes and the goal node integrally. Consequently, the obtained degree of correlation is not enough to accurately locate the position of goal nodes. In this paper, we proposed a new primary user localization algorithm based on compressive sensing in CRN. Initially, energy detection is adopted by secondary users for collecting the energy fingerprint of source signal, and then the correlation coefficients between source signal and SUs are constructed by compressive sensing [14] to determine weights of SUs. Finally, the weighted centroid algorithm is used to estimate source position and compare with the primary nodes position, which is known in CRN. This confirms whether PUEA exists. The rest of this paper is organized as follows. The system model is introduced in Section 2. Compressive sensing theory is briefly introduced in Section 3. Section 4 describes the proposed localization algorithm based CS. Section 5 demonstrates the simulation results, and conclusion is given in Section 6.
## 6 Technical Challenges in IoT Integration for Smart Buildings
### Obstacles to Connectivity  
Numerous places, especially in developing nations, have substantial connection obstacles owing to insufficient internet and telecommunications infrastructure. The absence of consistent connectivity hinders the formation of stable connections for IoT devices, hence restricting the efficacy and scope of IoT applications. Inadequate telecommunications networks may obstruct the implementation of IoT solutions, particularly in rural or underdeveloped regions, while elevated deployment costs for securing dependable connections may pose a significant barrier to entry for several projects. Moreover, environmental elements such as physical barriers or electromagnetic interference might impede connection, exacerbating the issue. Tackling these connection difficulties is crucial to guaranteeing that IoT solutions provide their intended advantages to consumers.
## 4 Results and Interpretations
### Facies Associations and Lobe Complexity
#### 4.3.1 Facies Association 1 (FA1): Lobe Axis  
Lobe axis facies association is characterized by massive sandstone units, generally having thicknesses of more than 100 cm. The thickness of an individual sand unit may go up to more than 800 cm. These units are often structureless as there is no grading and only a minor change in grain size within the sand beds. Multimeter massive sandstone with an amalgamation structure is the characteristic of this facies. S2 and S5 facies and occasionally S1 facies are included in this facies association. The association of this facies is interpreted as unconfined lobe settings with lobe axis and lobe off-axis alternate beds that are stacked together [92; 93], having amalgamated bodies (Figure 6) representing the proximal part of the lobe system. The facies is associated with high-density turbidity currents, where the huge amount of sand influx with rare or no argillaceous content is indicative of a lobe axis depositional environment.
## 5 Analysis Techniques for WebAssembly
### Detecting Vulnerabilities in WebAssembly Binaries
#### 5.2.4 Comparative Analysis  
This section presents the comparative analysis of the detection techniques outlined in the above sections. The results from the analysis are summarized in Table 4.  
**Runtime Compatibility**. The versatility of the proposed detection techniques is determined by their runtime compatibility, WASI support, and whether they require a high-level source code for their analysis. Some schemes, like TaintAssembly, are inherently tied to a specific runtime, which limits their usefulness. Other schemes, like Wasabi, are not tied to any specific runtime and can be applied more generally. Additionally, schemes that do not support WASI, like [PERSON] et al.'s method, are fundamentally limited since they cannot analyze most WebAssembly binaries used on servers or embedded devices. Finally, schemes that require high-level source code for analysis, like WASP\({}_{1}\), are limited to the analysis of open source projects.  
**Overhead**. The overhead for dynamic detection methods varies greatly. Wasabi and [PERSON] et al. have the highest overhead, reaching up to 163% and 100%, respectively. [PERSON] et al.'s method has a constant overhead, while [PERSON]'s overhead varies depending on the type and number of instructions being analyzed. This means that [PERSON]'s overhead can be as low as 2% in practice. In contrast, TaintAssembly and Fuzzm demonstrate much lower overheads, within the range of 5-12% and 5-6%, respectively. The lower overhead associated with TaintAssembly indicates that integrating taint-tracking into VMs can be a viable option for increased security with low-to-moderate overhead. However, this integration must carefully consider the balance between security improvements and potential performance trade-offs for each specific use case.
## 3 Numerical Results
### Prototype  
The method presented in the former section is applied to predict the dynamic response of the grooved cylinder shown in Figure 2. The cylinder is composed of 10 blocks. The chosen mesh is a result of a convergence study with respect to the quasi-static displacement and the contact forces. The mesh is composed of 35,640 nodes and 29,440 linear elements.  
The material domain is composed of the potential contact surface (in red) \(\Gamma_{c}\) and the rim zone \(\Gamma_{u}\) (in blue) where the following Dirichlet boundary condition is applied:  
\[\mathbf{u}(\mathbf{X},t)=\begin{bmatrix}Vt&0&-d\end{bmatrix}^{\intercal}+ \mathbf{R}(\omega t)\mathbf{X}-\mathbf{X}\quad\text{ in }\ \Gamma_{u} \tag{36}\]  
The structure is loaded kinematically by applying a vertical displacement \(d\) in the rim zone. The load could be thus calculated by summing the vertical reactions in the contact patch. \(V\) is the translation velocity, and \(\mathbf{R}\) is the rotation matrix associated with the angular velocity \(\omega\). The translation velocity depends on the angular velocity via the effective radius (also known as the rolling radius) \(r_{\omega}=V/\omega\). A first order approximation of \(r_{\omega}\) is given as a function of the geometrical radius \(R_{e}\) (see [23] for more details) as follows  
\[r_{\omega}\approx R_{e}-\frac{d}{3} \tag{37}\]  
The tire rubber is commonly modeled by using an hyperelastic material constitutive law. The simplest hyperelastic material model is the Saint Venant-Kirchhoff model, which is just an extension of the geometrically linear elastic material model to the geometrically nonlinear regime.  
\[\mathbf{S}=\lambda\text{tr}(\mathbf{E})\mathbf{I}+2\mu\mathbf{E} \tag{38}\]  
where \(\lambda\) and \(\mu\) are the Lame constants. The numerical results presented in the next section are obtained using the geometrical and the material constitutive law properties given in Table 1. The rolling conditions and the simulation numerical parameters are also given in Table 2. The chosen parameters are the result of a preliminary convergence study that is not presented. In fact, the resulting quasi-static displacement is practically invariant with respect to higher values of \(\varepsilon_{n}\) and lower values of \(\varepsilon_{r}\) using the chosen mesh and the mechanical properties given in Table 1.  
Figure 2: The prototype mesh.
# Load Transfer Efficiency Based on Structural Deflection Assessment of the Precast Floating Track
## 5 Results and Discussion
### Load Case II
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Load** **(kN)**} & \multicolumn{6}{c}{**Rail Displacement (mm)**} & \multicolumn{6}{c}{**FEA Result**} \\ \cline{2-11}  & **Loaded** & **Adjacent** & **Step** & **Incli-** & **Lle** **(\%)** & **Landed** & **Adjacent** & **Step** & **Incli-** & **Nation** & **LTE** **(\%)** & **Panel** & **Panel** & **(mm)** & **Nation** & **LTE** **(\%)** \\ \hline
150 & 2.24 & 2.21 & 0.03 & 0.40 & 99.33 & 2.40 & 2.39 & 0.01 & 0.13 & 99.79 \\
2  
As mention above, the purpose when applying the loads at Load case II is to verify the efficiency of the load transmitted between panels. From the data of the test and program, the LTE results from the assembly test were smaller than FEA. The evaluated LTE of rail at maximum load (440 kN) was 99.38%, and this value from FEA was 99.84% with a relative difference of 0.46%. Moreover, the error in the panel was 1.05% in the same condition. However, these results show that this type of track can transfer the load perfectly with various kinds of load (150-440 kN) with the LTE more than 99% for the rail and 97% for the panel. Table 8 presents comparisons of the average load transfer efficiency and numerical method (Midas civil program). The results show that the LTE from FEA was slightly larger and equal to 1.01 times compared with the experiment. In terms of structural safety and ride comfort, the step standard is presented in the design guidelines of the Korea Railroad Authority \"Honam High-speed Rail Design Guidelines (Civil Work)\" [25], and the design standards such as the Japanese railway structures Displacement Limitation [26], and the European standards. In this case, the Japanese standard was used for the concrete slab track. The average LTE of the rail was 99.24%, and the panel was 98.90%. The precast floating track does not have a load-carrying structure, such as a dowel, which connects the track slabs directly to each other. However, load transfer occurred through the rails (60 K rails), which were fastened at the top of the panel.
# Are Green Buildings an Indicator of Sustainable Development?
## 3 Results and Discussion
### GBRS and GDP  
The relationship between the amount of GBRS certifications per year (dependent variable) and the average GDP per capita in the EU (independent variable) is studied through simple linear regression with data taken from Eurostat Database and GBRS Public Directories.  
The ten points in Figure 10 (blue dots) represent the years between 2010 and 2019. The trendline is linear with an equation of y = 0.0016x + 24.213, a \(p\)-value = 0.0004 and an R\({}^{2}\) = 0.8059. However, if we do not consider 2014 (highlighted with a red triangle in Figure 11 and characterised by extreme climate conditions with significantly fewer heating degree days compared to other years), the chart assumes a more linear equation y = 0.0016x + 24.286 with more accurate \(p\)-value = 0.0004 and R\({}^{2}\) = 0.8475.  
Figure 8: Relationship between HDD and GHG emissions from buildings in the EU (2010–2019).  
Figure 9: Relationship between HDD and GHG emissions from buildings in the EU (2010–2013 and 2015–2019).  
According to the assumptions stated in the Methodology, \(p\)-value and \(\mathrm{R}^{2}\) are consistent, and the equation correlates the two variables in a very accurate way with a strong significance.  
The insights illustrate the economic implications that have not been considered in similar studies published in the literature [23; 24]. As forecasted by the EKC, in a developed area such as the EU, more GBRS certifications are related to a higher income per capita due to the extra cost needed to implement advanced construction features. This is in line with the spread of GBRS, that are mostly localised in the EU countries characterised by the highest GDP [17; 18; 19; 20].
# A UAV Coverage Path Planning Method Based on a Diameter-Height Model for Mountainous Terrain
## 3 UAV Coverage Path Planning Method Based on the DH Model
### Coverage Path Planning Method Based on the DH Model
#### 3.2.2 The Equal-Interval Circle CPP Method  
For the CPP problem on the flat sub-regions, the equal-interval circle CPP method can be performed. Intuitively, on the basis of the above region segmentation method on the flat region in the 3D map, a series of concentric circles can be easily obtained from the segmented sub-regions. Thus, the distance M to the projection circle of the DH model can be used to calculate the equal-interval circle path. Considering that the coverage path needs to move along the middle position of the trajectory width, the radius M of these equal-interval circles can be calculated according to (7). By using this equal-interval circle CPP method, the final generated equal-interval circle path for the flat region in the 3D map can be illustrated in Figure 6.  
\[\text{M}=\left(\text{k}-\dfrac{1}{2}\right)\text{L}\ \ \ \ (\text{k}=1,\ 2,\ \dots,\ \text{m}) \tag{7}\]  
Figure 5: Schematic diagram of equal-interval spiral ascent 3D path generated for side surfaces of the DH model.
## 2 Literature Review
### Customer Satisfaction  
Customer satisfaction is a pivotal metric that reflects the overall contentment experienced by customers throughout their engagement with a product, service, or business entity. At its core, customer satisfaction hinges on the cognitive assessment that customers make regarding whether their expectations have been met or exceeded. When customers discover that a product or service aligns seamlessly with their needs and desires, they feel a sense of contentment and fulfillment. Conversely, when a perceptible gap emerges between customer expectations and actual experiences, dissatisfaction sets in ([PERSON] et al., 2019). Customer satisfaction goes beyond merely meeting expectations; the ultimate goal is to consistently surpass them. This principle emphasizes that higher levels of satisfaction are attained when a product or service outperforms the initial anticipation, whereas lower satisfaction arises when performance falls short of expectations ([PERSON] et al., 2019).  
Initially, businesses were primarily focused on optimizing their production processes and efficient distribution of goods. However, as markets evolved to become more competitive and saturated, there was a noticeable shift in priorities toward understanding and effectively meeting the evolving needs of customers ([PERSON] et al., 2019). This transition undersored the pivotal role that customer satisfaction plays in determining business success ([PERSON] et al., 2019). Concurrently, advancements in technology, particularly the internet and social media, empowered customers by providing them unprecedented access to information and alternative choices. This newfound access heightened customer expectations, prompting businesses to prioritize responsiveness and transparency in addressing customer feedback ([PERSON] et al., 2019). Consequently, organizations have significantly ramped up their investments in CRM systems, real-time analytics, and personalized marketing strategies. These strategic initiatives are aimed at not only enhancing overall customer satisfaction but also at fostering long-term customer loyalty in today's fiercely competitive global marketplace ([PERSON] et al., 2019).  
Customer satisfaction substantially affects business success. Satisfied customers are more inclined to continue their associations with a company, and they evolve into passionate brand advocates who enthusiastically recommend the company to others. The recommendations of these customers contribute significantly to positive word-of-mouth marketing ([PERSON] et al., 2019). Therefore, businesses must prioritize and actively manage customer satisfaction as it not only leads to a positive brand image but also fosters customer retention, both of which are key factors in achieving long-term success in a competitive marketplace.