esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Classification Based on Taxonomy and Design Drivers  
### Range Query  
In [13, 19, 22, 30, 35, 36], the range query mechanism is implemented in different format. [PERSON] _et al._[22] propose an efficient technique, illustrated in Section 3.3, for a DCS similarity search that includes both a point and range query. A range query is divided into sub-queries and then the sub-queries are forwarded to their corresponding indexing node. For example, the level of carbon monoxide found in the air in a forest may be represented by levels that range from 50 L/mol to 150 L/mol. This range is split equally into four (_4\({}^{\prime}\)=4_, four index node referred as _I0, I1, I2, I3_) sub-ranges [50, 75], [75, 100], [100, 125], [125, 150]. Hence, if a range query is to find data within [60, 80], then the sub-ranges of _I0_ and _I1_ are located as they cover the given query.  
[PERSON], _et al._[13], proposed a method called DIM, which includes both a point and a range query in a multidimensional DCS model. In DIM, each sensor is linked as a node in a tree structure where each node represents a range of values. A root node represents the entire range of values and splits into two equal parts for left and right child nodes. This process continues for each non-leaf node until leaf nodes are reached.  
Figure 5: Multidimensional Range Query Mechanism (MDAs) [35].  
DIFS [30], referring to Section 3.10, performs a data fusion based on data conveyance through the network. The routing is designed on top of a quad tree in a manner that balances the communication load across the index, and the range is maintained along the sensor node hierarchy.  
In MDA [35], described in Section 3.13, a range query is split into a \(k\)-dimension range of multiple sub-queries. After splitting, each attribute sub-query is assigned with a bit code and tuples of \(k\)-bit codes, referred to as code \(B\), are produced. The code \(B\) are then mapped to range space \(R\) and data is stored in nodes located in the mapped \(R\). The state-of-the-art approaches in the field of range query DCS are summarized in Table 1.
## 3 Eigenvalue Fusion and other Fusion Methods for Detecting General Wideband Signals  
The eigenvalue-based detection for narrowband signals can be used to detect wideband signals as well. To this end, the model considered in the previous section has to be adapted to a situation in which received samples are represented in the frequency domain. Therefore, before going into the specifics of the proposed eigenvalue fusion scheme, we first address the channel and signal models in the frequency domain. Then we discuss how the sample fusion process works when samples are in the frequency domain. The proposed eigenvalue fusion is presented in the sequel. For the sake of completeness, the section ends with the description of the decision fusion process in the context of general wideband signals.
# An Overview of Shared Mobility Operational Models in Europe
## 4 Bikesharing
### Operational Challenges of Bikesharing in Europe  
Bike-share systems can decrease dependence on cars, reduce emissions, and even boost users' levels of physical activity by enabling more journeys by bicycle. For instance, the city of Paris claimed that its public bike rental program reduced CO2 emissions by almost 18,000 tons annually, highlighting the possible environmental benefits of widespread bikesharing [65]. Moreover, bikesharing often serves as a first-mile/last-mile solution; when seamlessly integrated with public transportation, it encourages multimodal travel and makes it easier for commuters to switch from trains or buses to bicycles for short trips. According to [66], co-locating bike stations close to transit hubs and using unified payment methods or applications can greatly increase the use of bike shares as an alternative to public transportation. Overall, in dense urban areas, bikesharing is seen as a key element of sustainable mobility strategies, helping to alleviate congestion and reduce pollution while offering affordable travel options.  
It is important to recognize that bikesharing systems in Europe provide measurable socioeconomic implications and operational issues that go beyond modal classification and operational typologies. When combining the direct investment impact with the health advantages of increased physical activity, a research of 13 European cities revealed that every euro invested in public bikesharing systems produced an estimated economic return of \(\mathfrak{C}\)1.37 to \(\mathfrak{C}\)1.72. The WHO's HEAT approach for valuing averted premature deaths and the [PERSON] input-output model for economic spillover effects were used to calculate these benefits [67].  
However, operational challenges still exist. Despite their flexibility, dockless systems have created congestion and saturation in public areas, which has created tension between users, local governments, and citizens. Concerns regarding future integration with current public transportation networks and urban mobility initiatives have also been raised due to poorly managed services. Furthermore, the analysis draws attention to the differences between institutional and non-institutional systems: commercial dockless services frequently prioritize market share over accessibility, safety, and sustainability, whereas public models typically provide regulated, equitable access. These results highlight the importance of city-operator coordination, laws and regulations, and sustainability criteria that extend beyond the original implementation or user counts [67].
# Development of Post Processing for Wave Propagation Problem: Response Filtering Method
###### Abstract  
This study develops a new response filtering approach for recovering dynamic mechanical stresses under impact loading. For structural safety, it is important to consider the propagation of transient mechanical stresses inside structures under impact loads. Commonly, mechanical stress waves can be obtained by solving [PERSON]'s second law using explicit or implicit finite element procedures. Regardless of the numerical approach, large discrepancies called the Gibb's phenomenon are observed between the numerical solution and the analytical solution. To reduce these discrepancies and enhance the accuracy of the numerical solution, this study develops a response filtering method (RFM). The RFM averages the transient responses within split time domains. By solving several benchmark problems and analyzing the stresses in the frequency domain, it was possible to verify that the RFM can provide an improved solution that converges toward the analytical solution. A mathematical theory is also presented to correlate the relationship between the filtering length and the frequency components of the filtered stress values.  
stress wave propagation; finite element; numerical dispersion; Gibbs phenomenon; response filtering method; post-processing +
Footnote †: journal: Applied Sciences
## 2 Structure and Operation Principle of the Proposed Converter
### Operation of the Proposed Converter in CCM  
When the load current increases, the converter operates in CCM as depicted in Figure 3b. In CCM, both the input current and the current through all inductors are operating in CCM. Moreover, the voltage transfer ratio of the converter significantly increases in this mode. Figure 3b illustrates the two operation modes for this situation and shows the corresponding current waveforms of the proposed converter operating in CCM.  
Mode 1: [0 to t0]: The MOSFETs Sw1 and Sw2 are both turned on simultaneously, resulting in the diodes D1, D2, D5, and D6 being switched on. Meanwhile, D3, D4, and D7 are in the off state. L1 starts linearly charging energy from the input source, and L2 begins to charge energy from the input source through D1. C1 starts discharging energy through D2 through Sw1. During this mode, capacitors C2 and C3 act as a dual source, storing a significant amount of power that is used to charge L3 through Sw2, while L4 starts charging from C2 and C3 through D5. C4 starts discharging energy through D6. C5 provides energy to the load. The proposed converter for this mode is illustrated in Figure 2b.  
Mode 2: [t0-t1]: Both MOSFETs are turned off, while diodes D1, D2, D5, and D6 are in the off state. The inductor L1 discharges its energy to capacitor C1 through L2. In this mode, L1 and L2 are connected in series. Meanwhile, L1 and L2 begin discharging their energy to charge capacitors C2 and C3 through D3 and D4. C4 starts accumulating energy from L3. In this mode, both L3 and L4 are in series. Capacic C5 accumulates a significant amount of energy from L3 and L4 during the discharging period and supplies high power to the load through D7. The proposed converter for this mode is illustrated in Figure 2c. Figure 3b shows that all inductor currents are in CCM when the proposed converter operates in CCM mode, and the load current increases above 60% duty ratio, as shown in Figure 4a,b.  
Figure 4a,b show the dynamic performance of the proposed converter in DCM and CCM. It can be seen that from the condition in Equation (25), the proposed converter can operate in DCM when the duty ratio is below 0.6 in CCM, the load current increases at the duty ratio above 60%, and the proposed converter supply is around 2 KW.  
Figure 4: The proposed converter dynamic performance: (a) K (Kcrit) vs. K load factor (b); Kcrit and K vs. duty cycle.
# Additive Manufacturing of Bone Scaffolds Using PolyJet and Stereolithography Techniques
## 2 Materials and Methods
### Mechanical Testing of Standard Blocks and 3D-Printed Scaffold Structures  
Compression testing was performed following the ASTM D-695 (ISO 604) standard [44]. This is the standard test method used for compressive properties of rigid plastics. A Zwick/Roel Z50 universal testing machine integrated with the Zwick TestXpert simulation software was used to determine the compressive performance of the samples, with a maximum loading capacity of 50 kN.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test Fluid** & **Tap Water** & **15\% Glycerol–Water** & **20\% Glycerol–Water** \\ \hline Density (kg/m\({}^{3}\)) & 998 & 1045 & 1060 \\ Pressure (Pa) & 7833 & 8192 & 8318 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Density and pressure values for the test fluids used in the permeability measurements.  
Figure 3: Standard samples with cylindrical and rectangular cross-sections.  
Startrite-20 RWF was used to cut the circular packing around the 3D-printed scaffold structures and a grinder was used to remove extra material to obtain the final samples for the compression test. After cutting and grinding the scaffold structures, the samples were subjected to a compression testing machine to determine the compressive strength, elastic moduli, and yield strength.  
Force was applied with a compression speed of 2 mm/min and deformation in the samples was measured in the vertical direction. All specimens were compressed until failure. A standard force (N) versus displacement (mm) curve was plotted in the Zwick TestXpert simulation software. The force versus displacement curve data were extracted from the TestXpert software and later used in the formulae \(\sigma=\frac{\text{F}}{\text{A}}\) (\(\sigma=\text{stress}\), F = force, A = area) and \(e=\frac{\text{F}}{\text{A}}\) ( \(e=\text{strain}\), \(\delta=\text{length reduction}\), L = original length) to plot the stress-strain diagram for the scaffold structures. The stress strain diagram was used to determine the compressive properties of the scaffold structures.  
The surface finish is of critical importance in bioimplant applications. The biocompatibility of the scaffolds and the long-term wear resistance and fatigue performance are crucial in such applications; however, since the current study was focused on the porosity and compression, the scaffolds were used directly after removing the support structure (as-built).
# Performance Analysis of a Novel TCP Protocol Algorithm Adapted to Wireless Networks
## 2 Materials and Methods
### TCP Sockets
#### 2.3.4 Sending NACK Notifications  
We created and implemented the NACK sending function based on the tcp_send_ack function, located inside the /net/ipv4/tcp_output.c file, due to the similarity between NACK and ACK approach.  
* New tcp_send_nack function: This function, declared inside the /include/net/tcp.h file, sends NACK_notifica- tions by four steps. First, it checks if the connection was restarted, if this is true, then the NACK notification is annulled. After that, it calls theskb_reserve function, that creates a socket buffer with a memory space of the maximum TCP header size. Then, the tcp_init_nondata_skb function sends the posi- tive NACK flag state and the sequence number to be retransmitted to the control buffer. Finally, the packet is transmitted to the network layer by the tcp_transmit_skb function. Algorithm 2 shows the description of the NACK sending function.  
```
if TCP state == close then return endif skb_reserve(maximum TCP header size) tcp_init_nondata_skb(NACK flag state, sequence number) tcp_transmit_skb0
```  
**Algorithm 2** tcp_send_nack function algorithm  
Figure 3: TCP-NACK header.  
* _tcp_transmit_skb_ modification: If the packet to be transmitted has raised the TCP_FLAG_NACK flag, the TCP confirmation number field must contain the sequence number of the corrupted packet. Algorithm 3 shows this modification.  
```
ifNACK flag == 1 then  TCP header <- sequence number of the corrupted packet else  TCP header <- sequence number of the next expected packet endif
```  
**Algorithm 3**_tcp_transmit_skb_ function modification  
The negative confirmations must be triggered by reception of the corrupted TCP packets, thus _tcp_send_nack_ function is then called inside _tcp_rcv_established_ function for detecting an error.
## 7 Conclusions and Future Works  
In this paper, we have followed an efficient approach for linear system identification problems, which basically involves three key items, i.e., (i) the nearest Kronecker product decomposition of the impulse responses, (ii) low-rank approximations, and (iii) a particular symmetric filter. Such an approach fits very well for the identification of long-length impulse responses, which raise significant challenges in many real-world system identification problems.  
In this framework, we have developed an iterative Wiener filter, which is able to outperform the conventional Wiener filter (in terms of the accuracy of its solution), especially when only a small amount of data is available to estimate the required statistics and/or in noisy conditions (e.g., low SNRs). For example, when \(N=2L\) data samples are available and \(\text{SNR}=10\) dB, the conventional Wiener filter fails to provide an accurate solution (i.e., its normalized misalignment is close to \(0\) dB), while the proposed iterative version provides a reasonable attenuation of the misalignment (around \(-10\) dB).  
In addition, an adaptive solution has also been proposed, which results in an RLS algorithm with symmetric filter, namely the RLS-SF. This new adaptive filter provides improved performance features as compared to the conventional RLS benchmark, such as an improved tracking capability and a lower computational complexity. Moreover, the RLS-SF leads to more accurate solutions as compared to the conventional RLS filter, which reflect into lower misalignment levels (e.g., up to \(5\)-\(10\) dB improvement, depending on the SNR).  
The proposed algorithms have been tested in the framework of network and acoustic echo cancellation, which represent very challenging system identification problems. Simulation results have indicated the good performance of the iterative Wiener filter and the RLS-SF algorithm, also supporting the theoretical findings behind their development.  
In future works, we aim to improve the current solutions based on a different selection of the permutation matrix, which would further allow to better exploit the low-rank features of the systems to be identified. In addition, the development of a Kalman filter based on this approach will also be considered, which could open the path toward other potential applications, e.g., see [44, 45], and the references therein.  
Conceptualization, I.-D.F.; methodology, J.B.; validation, L.-M.D.; investigation, C.P.; formal analysis, S.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a grant of the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number: PN-III-P1-1.1-PD-2019-0340.  
Not applicable  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 1 Introduction
\begin{array}{ll}\left(\mathbf{S}_{1}\right)&y\left(v\right)>0,\ y^{\prime} \left(v\right)>0,y^{\prime\prime}\left(v\right)>0,\ \ y^{\left(\kappa-1\right)}\left(v\right)>0,\ \ y^{\left(\kappa\right)}\left(v\right)<0,\\ \left(\mathbf{S}_{2}\right)&y\left(v\right)>0,y^{\left(\kappa\right)}\left(v \right)>0,y^{\left(\kappa+1\right)}\left(v\right)<0\text{ for all odd integer}\\ &r\in\left\{1,3,...,\kappa-3\right\},y^{\left(\kappa-1\right)}\left(v\right)>0,y^{\left(\kappa\right)}\left(v\right)<0,\\ \left(\mathbf{S}_{3}\right)&y\left(v\right)>0,\ y^{\left(\kappa-2\right)} \left(v\right)>0,\ \ y^{\left(\kappa-1\right)}\left(v\right)<0,\ \ L_{y}\leq 0,\end{array} \]  
_for \(v\geq v_{1}\), where \(v_{1}\geq v_{0}\) is sufficiently large._  
**2. Oscillation Criteria**  
**Theorem 1**. : _Assume that (2) holds. If the differential equations_  
\[\left(\frac{\left(\kappa-2\right)!a^{\frac{1}{\beta}}\left(v\right)}{\left( \theta v^{\kappa-2}\right)^{\beta}}\left(y^{\prime}\left(v\right)\right)^{ \beta}\right)^{\prime}+kq\left(v\right)y^{\beta}\left(v\right)=0,\quad\forall \theta\in\left(0,1\right), \tag{9}\]  
\[y^{\prime\prime}\left(v\right)+y\left(v\right)\frac{1}{\left(\kappa-4\right)! }\int_{v}^{\infty}\left(\xi-v\right)^{\kappa-4}\left(\frac{1}{a\left(\xi \right)}\int_{\xi}^{\infty}q\left(s\right)\mathrm{d}s\right)^{1/\beta}\mathrm{ d}\xi=0, \tag{10}\]  
_and_  
\[\left(a\left(v\right)\left(y^{\prime}\left(v\right)\right)^{\beta}\right)^{ \prime}+y^{\beta}\left(v\right)kq\left(v\right)\left(\frac{\zeta\left(\eta \left(v\right)\right)}{\zeta\left(v\right)}\right)^{\beta}\left(\frac{\theta_ {1}}{\left(\kappa-2\right)!}\eta^{\kappa-2}\left(v\right)\right)^{\beta}=0, \quad\theta_{1}\in\left(0,1\right) \tag{11}\]  
_are oscillatory for every constant \(\theta,\theta_{1}\in\left(0,1\right)\), then every solution of (1) is either oscillatory or satisfies \(\lim\limits_{v\rightarrow\infty}y\left(v\right)=0\)._  
Proof. : Assume to the contrary that \(y\) is a positive solution of (1). Then, we can suppose that \(y\left(v\right)\)and \(y\left(\eta\left(v\right)\right)\) are positive for all \(v\geq v_{1}\) sufficiently large. From Lemma 4, we have three possible cases \(\left(\mathbf{S}_{1}\right)\), \(\left(\mathbf{S}_{2}\right)\) and \(\left(\mathbf{S}_{3}\right)\). Let case \(\left(\mathbf{S}_{1}\right)\) hold. Using Lemma 2, we find  
\[y^{\prime}\left(v\right)\geq\frac{\theta}{\left(\kappa-2\right)!}v^{\kappa-2}y ^{\left(\kappa-1\right)}\left(v\right), \tag{12}\]for every \(\theta\in\left(0,1\right)\) and for all large \(v\).
# Experimental Validation and Evaluation of a Coupled Twist-Camber Morphing Wing Concept
## 2 Morphing Wing Concept
### Internal and External Components  
As an open shell structure, the wing skin had very limited load-bearing capability since the load was likely to be carried only by the lower skin in a normal upward load case situation, also due to low buckling loads of the skin alone. The design concept relied on the restriction of the relative upper and lower skin TEs displacements in the chordwise direction to force the upper and lower skins to carry the bending loads simultaneously. This restriction was enforced by the addition of sliding \"comb-like\" parts that were bonded near and along the TEs of the upper and lower skins and are depicted in Figure 5.  
As for torsional stiffness and controlled twist and camber deformation, the concept relied on the actuation system capability to carry the load and deform the wing sections using a mix of linear and rotational servos distributed along the wingspan.  
A total of six rotational servos and two linear servos were used. In order to increase the actuation speed while maneuvering, the rotational servos were used everywhere other than at the root. The implications of this choice were a constant power consumption required to maintain a prescribed configuration during flight that increases for configurations with increased camber. It is still to be investigated if linear actuators can satisfactorily fit and actuate the wing fast enough to allow acceptable roll rates and load alleviation strategies.  
The linear servos were used at the root. They did not contribute to the roll maneuverability and serve as actuation for configuration setting only, which was deemed to change shape somewhat slower without jeopardizing the configuration adaptation to different flight segments. This choice allowed higher actuation loads in the wing region where they were required to maintain the desired shape, without energy expenditure while the configuration was maintained. It is still to be investigated if the lower actuation speed is compatible with a load alleviation strategy that increases camber at the root while decreasing camber and twist towards the tip of the wing.  
Structural members as stiffeners could also be valid options in the design since they act primarily in bending without a significant increase in actuation forces, but the current concept was intended to explore load alleviation capabilities as means to maintain the wing structure as mass competitive as possible, by limiting the root bending moment (RBM) during maneuvering or gust loads.