esa-sceva/satcom-chunk-collection huggingface dataset:
# A Data Secured Communication System Design Procedure with a Chaotic Carrier and Synergetic Observer
## 3 Methodology and the System Design Procedure
### Security Analysis of Chaotic Carrier Data Transmission System with Parameters Nonlinear Modulation  
In the previous sections, we described different schemes for mixing a useful signal with a chaotic one. In particular, the works of [PERSON] [22] indicated in Section 2 show the vulnerability of systems with additive parametric modulation. In his works, it was shown that it is possible to create a filter that selects a useful (i.e., deterministic) signal from a chaotic carrier. In this regard, the security analysis of systems in Section 3.2 with multiplicative parametric modulation is valid. It is obvious that nonlinear mixing and the system (1) global reconstruction into Equations (3) and (4) will provide a more complex waveform for \(Z(t)\), but it is necessary to prove this mathematically. For this purpose, we applied the signal \(Z(t)\) to the communication channel with a multiplicatively mixed some useful periodic signal (hereinafter, a useful signal transmission) and without a mixed useful signal (hereinafter, an idle transmission). To analyze these transmissions, we used the standard signal processing functions from the MATLAB: autocorrelation and Fourier transform.
## 2 Unsaturated Subgrade Filler Triaxial Testing System
### Photogrammetry System and Camera Calibration  
A digital image correlation (DIC) system was employed in this study, as shown in Figure 6. Equipped with two 35 mm fixed-focus lenses (Canon EF 35 mm f/2 IS USM), the system features lenses with a large aperture and short focal length, making them particularly suitable for observing small deformations in confined spaces, especially in experiments requiring a larger field of view. The camera's image sensor has a resolution of 12.3 megapixels (4000 \(\times\) 3000 pixels), providing sufficient detail to ensure high precision during 3D reconstruction. Although camera lenses may exhibit barrel or pincushion distortion, photogrammetry assumes the camera lens to be an ideal pinhole lens, necessitating distortion correction. To achieve this, the digital image correlation system employed multi-lens calibration technology, capturing 15 images of a standard calibration board to obtain accurate internal and external camera parameters. The internal parameters include focal length, principal point location, and distortion parameters, while the external parameters include the camera's translation vector and rotation matrix. These parameters were calculated accurately using the Levenberg-Marquardt optimization algorithm, ensuring high accuracy and reliability of the measurement data. The camera's calibration results are listed in Table 3.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multirow{2}{*}{**Serial Number**} & \multicolumn{3}{c}{**Preliminary Condition**} \\ \cline{3-5}  & & \(w\) (\%) & \(e\) & \(s\) (kPa) \\ \hline \multirow{4}{*}{Set 1} & 1 & 15.89 & 0.655 & 28.0 \\  & 2 & 14.56 & 0.655 & 57.2 \\  & 3 & 13.48 & 0.652 & 170.0 \\  & 4 & 13.05 & 0.654 & 241.4 \\  & 5 & 12.16 & 0.652 & 387.3 \\  & 6 & 11.76 & 0.647 & 501.7 \\ \hline \multirow{4}{*}{Set 2} & 1 & 15.90 & 0.656 & 73.1 \\  & 2 & 13.41 & 0.654 & 145.6 \\  & 3 & 12.92 & 0.652 & 253 \\  & 4 & 11.98 & 0.650 & 364.8 \\  & 5 & 11.84 & 0.647 & 417.2 \\ \hline \multirow{4}{*}{Set 3} & 1 & 15.56 & 0.658 & 34.0 \\  & 2 & 14.22 & 0.655 & 76.7 \\ \cline{1-1}  & 13.61 & 0.653 & 130.3 \\ \cline{1-1}  & 4 & 12.57 & 0.650 & 265.8 \\ \cline{1-1}  & 5 & 12.04 & 0.649 & 364.6 \\ \cline{1-1}  & 6 & 11.83 & 0.648 & 430.3 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Soil samples’ initial coefficients in the testing procedure.  
Figure 6: Schematic of the digital image correlation (DIC) system.
## 1 Introduction
It has been proven in [27] that low-frequency oscillations can be suppressed by the PCC-PT control technique, which uses the peak capacitor current as feedback. Moreover, the PCC-PT controlled buck converter features a simple design, fast transient response, small output voltage ripple, and a wide load range. Different from single stage DC/DC converters, when the traditional PT control method is introduced into the two-stage WPT system, the low-frequency oscillations at the output voltage can be further amplified due to the asynchronization of oscillations between the input voltage and the output voltage, leading to an unstable output voltage. In this paper, a double-side feedback control strategy for regulating the output voltage of two-stage WPT systems based on capacitor current and output voltage feedback is proposed. Compared to the conventional PT control strategy, the two feedback state variables in the proposed method are sampled from the output sides of the front-stage power converter and back-stage WPT. Hence, different from all reported PT control strategies, the proposed CC&OV-PT control strategy can compensate for the phase difference between control and response and eliminate most low-frequency oscillations by combining the filter capacitor current of the front-stage buck converter together with the output voltage of the WPT system as feedback variables for regulating the output voltage. This control strategy is then tested, which displays higher robustness and faster response compared with existing methods; this can provide a new reference for designing voltage regulators for WPT systems. It is also more suitable for some scenarios requiring high stability and response speed, such as the wireless charging of implanted medical devices, underwater and mining wireless power supply. The rest of the paper proceeds as follows. The structure diagram of the two-stage WPT system and the analysis of low-frequency oscillations are presented in Section 2. Section 3 illustrates the control principle of the proposed double-side CC&OV-PT control. The dynamic model of the two-stage WPT system is established in Section 4. Section 5 simulates the PWM control, the traditional PT control and the proposed CC&OV-PT control methods, respectively. The output load variation and input voltage variation are studied, and the circuit parameter design is presented. In Section 6, experimental results are presented to verify that the proposed double-side CC&OV-PT method has the best control performance.
## 3 Methodology
### Spatio-Temporal Visual Similarity Modelling  
In contrast to other approaches that use clustering for boundary detection, we construct a similarity matrix that jointly describes spatial similarity and temporal proximity. The generic element \(S_{ij}\) defines the similarity between frames \(i\) and \(j\), as shown in Equation (1).  
\[S_{ij}=exp\left(-\frac{d_{1}^{2}(\psi(x_{i}),\psi(x_{j}))+\alpha\cdot d_{2}^{2 }(x_{i},x_{j})}{2\sigma^{2}}\right) \tag{1}\]  
where, \(\psi(x_{i})\) and \(\psi(x_{j})\) are the list of visual tags for the \(i\)th and \(j\)th frame, respectively. \(d_{1}^{2}\) is the cosine distance between frame \(x_{i}\) and \(x_{j}\), while \(d_{2}^{2}\) is the normalised temporal distance between frame \(x_{i}\) and frame \(x_{j}\). The parameter \(\alpha\) tunes the relative importance of semantic  
Figure 3: Overview of the framework for Shot Detection. Shot is defined as a group of continuous frames without a cut. To predict shot boundaries, the framework utilises only frame-level visual features from the given input video.  
Figure 2: Overview of the proposed pipeline. Given the input video, the framework extracts visual features to obtain frame-level semantics. The enriched semantic information can then be used for search and retrieval of video segments, predict shot and scene boundaries, and also to create object timelines.  
similarity and temporal distance. The effect of alpha on the similarity matrix is shown in Figure 4.  
As shown in Figure 4, the effect of applying increasing values of \(\alpha\) to the similarity matrix is to raise the similarities of adjacent frames, thereby boosting the temporal correlations of frames in the neighbourhood. At the same time, too high values of \(\alpha\) would lead to the boosting of the temporal correlation of very close neighbouring frames, thereby failing to capture gradual shot changes. The final boundaries are created between frames that do not belong to the same cluster. An experiment was conducted with the videos of the RAI dataset, where values from 1 to 10 were provided for \(\alpha\), and its effect was studied. We found that an \(\alpha\) value of 5 performed well on average, for both gradual and sharp shot changes. Therefore, we use an \(\alpha\) value of 5 for our shot boundary detection experiments, since it provides the right amount of local temporal similarity for the prediction of boundaries.  
As seen in Equation (1), semantic composition-based frame-similarity estimation is composed of the following two sub parts:  
* Semantic similarity scoring scheme
* Temporal model analysis
###### Abstract  
The logical separation of the data plane and the control plane of the network device conceptually defined by software-defined networking (SDN) creates many opportunities to create smart networking with better efficiency for network management and operation. SDN implementation over telecommunications (Telcos) and Internet service provider (ISP) networks is a challenging issue due to the lack of a high maturity level of SDN-based standards and several other critical factors that are considered during the real-time migration of existing legacy IPv4 networks. Different migration approaches have been studied; however, none of them seem to be close to realizing implementation. This paper implements the SDN-IP and Open Network Operating System (ONOS) SDN controller to migrate legacy IPv4 networks to multi-domain software-defined IPv6 (SoDIP6) networks and experimentally evaluate the viability of joint network migration in the ISP networks. We present results using extensive simulations for the suitable placement of the master ONOS controller during network migration by considering minimum control path latency using optimal path routing and the breadth first router replacement (BFR) technique. Our empirical analysis and evaluations show that the identification of the median router to attach the master controller and router migration planning using BFR give better results for carrier-grade legacy networks' migration to SoDIP6 networks.  
SDN; SoDIP6; network router; network migration; ONOS; SDN-IP Article
# Training-Free Acoustic-Based Hand Gesture Tracking on Smart Speakers
## 5 Related Work  
### Gesture Recognition Based on Wireless Signal  
Wireless sensing technologies have been widely employed for gesture recognition, including Wi-Fi, radar, UWB, visible light, LoRa, and RFID. Wireless sensing relies on analyzing the wireless signals reflected from the target to obtain gesture information. DPSense [15] leverages the proposed EDP metric to effectively classify signals into segments according to their sensing qualities and process them differently. This system enhances the sensing quality and avoids distortion from low-quality signals to assure the robustness of gesture recognition. [PERSON] et al. [9] presented a multistream convolutional neural network (MS-CNN)-based in-air digits recognition method using a frequency-modulated continuous-wave (FMCW) radar. With one FMCW radar comprising two receiving channels, a novel three-stream CNN network with range-time, Doppler-time, and angle-time spectrograms as inputs was constructed, and the features were fused together in the later stage before making a final recognition. [PERSON] et al. [16] proposed a sign language (SL)/hand gesture recognition method based on a novel discriminative feature, built a measurement system of hand movements using an UWB radar, measured 10-type, 15-type SL actions, and 10-type hand gesture actions, and completed the tasks of 10-type SL/hand gesture recognition based on the extracted new features. [PERSON] et al. [17] presented a method for recognizing gestures via the analysis of interrupted light patterns using visible light. MineSOS [18] is a distress gesture sensing system utilizing LoRa technology, in response to rescues in long-distance coal mine tunnels full of dust and dangerous gases. [PERSON] et al. [19] proposed a device-free gesture identification system that recognizes different hand movements by processing through Edge Machine Learning (EML) algorithms, received signal strength indication (RSSI) and phase values from backscattered signals of a collection of RFID tags mounted on a plastic plate. Among these device-based systems, Wi-Fi-based systems have low sensing precision because of environmental interferences, and systems based on other signals usually require expensive dedicated devices.
# Monitoring of Possible Activities of Yangsan Fault Zone Using GNSS
## 4 Results--Discussion  
### Time Series  
#### 4.1.1 Daily Solution  
From 17 July 2018, to 31 December 2021, the daily solution was estimated through high-precision baseline analysis using the IGS stations, resulting in the three-dimensional time series coordinates of each corresponding station. Appendix A, Appendix B, Appendix C, and Appendix D are time series representations of the coordinates for each observing station, which shows that the movement in the southeast direction is dominant in that area. This is consistent with the fact that the crust of the Korean Peninsula is known to move in the southeast direction at a rate of about three centimeters every year.  
In the case of the vertical (up) component, there was no tendency in the movement of the station, and this is because the magnitude of vertical change is smaller than the accuracy of GNSS positioning. Due to the geometric limitations of satellites, it is known that the accuracy in the vertical component is always 2-3 times worse than that in the horizontal (north, east) direction.
# The Challenges and Compatibility of Mobility Management Solutions for Future Networks
## 4 Suitability of Legacy Techniques and Standards for 5G and Upcoming Networks
### Multipath TCP (MPTCP) and Stream Control Transmission Protocol (SCTP)  
MPTCP is a continuing struggle of the Internet Engineering Task Force's (IETF) working group, whose objective is to permit a TCP connection to utilize multiple paths in order to capitalize on resource usage and raise redundancy [36; 37; 38]. SCTP provides multipath congestion awareness and redundancy, like in MPTCP [39]. Furthermore, SCTP is also a prospective enabler for the latest MM mechanisms [40]. In order to judge the compatibility of MPTCP and SCTP for 5G and future networks, we list their advantages and drawbacks in the following section [41].  
**Advantages** (MPTCP)  
- Multiple sub-flows can be handled independently [35; 42]  
- We have a specific congestion control mechanism for each flo  
- There is flexibility against connection failure due to the division of flows [23; 42]  
**Drawbacks** (MPTCP)  
- Lack of optimized middleboxes for supporting the MPTCP [23]  
- Proxies are needed to take full advantage of MPTCP architecture [43; 44].  
**Advantages** (SCTP)  
- With the support of a multi-homing feature, the network-level fault tolerance can be achieved [24].  
- The congestion awareness is embedded to avoid the SCTP suite's congestion [24].  
- This approach (SCTP) permits the execution of multiple connections at the transport layer [24]. Hence, connection failures can be tackled by shifting the control to other available flows.  
**Drawbacks** (SCTP)  
- We need to update the existing protocols of all SCTP-enabled communicating devices with the SCTP protocol [24].  
As a result, from the above findings on MPTCP and SCTP, it is revealed that IETF MPTCP-SCTP fulfills parameter AL5 (Table 2) by offering the service granularity per flow, per service, and per user. Similarly, MPTCP-SCTP approaches meet the criteria DL5 of Table 2 (allowing the single user several flows over the network) and DL1 of Table 2 (consideration of congestion provisioning awareness as part of MM characteristics) for the dependability criterion.
# Energy Consumption and Financial Development in NAFTA Countries, 1971-2015
## 1 Introduction
Urbanization can affect economic growth, energy consumption, and CO\({}_{2}\) emissions. Specifically, when urbanization affects (positive or negative) emissions significantly, it will affect sustainable development and climate change policies [11], mainly due to the fact that activities in urban areas were responsible for 67% of energy consumption and 70% of greenhouse gases around the globe [12]. When the impact is positive, it can affect the forecasts of the models and the climate change policy because CO\({}_{2}\) emissions will be underestimated if the impact of urbanization on environmental degradation is not taken into account. If the impact of urbanization on CO\({}_{2}\) emissions is negative, then the objectives of sustainable development might be easier to achieve when urbanization reduces polluting emissions [11]. It is difficult to determine the impact of urbanization on the environment, as it can be positive or negative according to the theories of ecological modernization and the urban environment transition [11]. For the case of the countries that make up the NAFTA, given their strong integration due to trade and investments, it would be interesting to know the main determinants of energy consumption in the region, to contribute in the design of policies that allow one to take advantage of the benefits of trade without affecting the environment. The question conducting this research is as follows: what is the relationship between energy consumption, financial development, prices, GDP, urbanization, and trade openness in the country-members of the NAFTA during the period of 1971-2015? In this sense, the objective of this paper is thus to analyze the relationship between energy consumption, financial development, prices, GDP, urbanization, and trade openness for NAFTA countries from 1971 to 2015. The central contribution of this research is to examine the main variables (e.g., economic growth, trade, urbanization, financial development and prices) that determine the behavior of energy consumption in the three countries of the North America region (Figure 1). The article is structured as follows: after the introduction, the Section 2 briefly describes the literature on the subject; then, the econometric modelsare presented; in the Section 4, the results are presented and analyzed; and finally, a conclusion section ends the research.
## 2 Materials and Methods
### Applications of the Automated SHS Quantification Algorithm
#### 2.4.3 Pre-Ablation Subsquamous SHS Characteristics and RFA Treatment Response  
The objective of this study was to investigate the association between pre-ablation squamous SHS and treatment response. Similar to the previous study, we included the same cohort of patients (n = 21). However, SHS quantification was performed within the 2 cm segment proximal to M (denoted by ROI\({}_{\text{SE}}\), Figure 3C). The SHS characteristics were correlated to the reduction of maximum BE length (change of M in EGD) after RFA treatment. To account for the differences in baseline BE lengths between different patients, we normalized the change of BE length by the initial BE length at the first study visit. To understand the effect of age on the treatment response, we divided the patients into \(\leq\)70 (n = 10) and \(>\)70 years old (n = 11) and analyzed the correlations separately.
## 5 Numerical Evaluation Results
### Separated Peak Demands
#### 5.2.2 Impact of Flexibility Parameter \(V\)  
The mean-plus drift parameter \(V\) in the optimization framework, see Equation (7), relates to the degree of flexibility with which the operators can share the total aggregate backhaul capacity \(Z\) beyond their own backhaul capacity \(Z_{o}\). Figure 4 shows the performance of the resource allocation algorithm for increasing values of the flexibility parameter \(V\), namely for \(V=1\), 10, and 100, while for \(V=1000\) we refer to Figure 3c,d. Moreover, Figure 4g,h shows the optimization performance without the economic constraint (6). We observe from Figure 4a,c that for small \(V\) values, e.g., \(V=1\) and 10, the rate allocation with SDN optimization is nearly equivalent to the no-SDN benchmark. The small differences between the allocations with the SDN optimization and the no-SDN benchmark are mainly some low-amplitude oscillations in the SDN allocations. The allocation oscillations result from the optimization framework striving to adapt to slight random variations in the traffic generation processes. Accordingly, both the SDN optimization and the no-SDN benchmark give essentially the same eNB queue lengths as observed from Figure 4b,d. Intuitively, small \(V\) values restrict the drift from the mean in the optimization framework, which inherently corresponds to a low degree of flexibility when operators want to share each other's resources.  
Figure 4: Upstream backhaul bitrate allocations and eNB queue lengths when demand peaks for operators 1 and 2 are spaced apart: Increasing the “flexibility parameter” \(V\), see Equation (7), increases the sharing of backhaul capacity among the two operators and decreases the queue lengths compared to the benchmark without SDN orchestrated backhaul resource sharing; for \(V=1000\), please refer to Figure 3c,d. The QMW case corresponds to the SDN-based optimization without a long-term constraint.  
In contrast, we observe for the higher \(V=100\) and \(1000\) values in Figure 4f and Figure 3d that SDN optimization with flexible backhaul resource sharing among operators achieves smaller eNB queue lengths than the no-SDN benchmark. We observe that the queue lengths for \(V=1000\) in Figure 3d are nearly as small as the queue lengths in Figure 4h for optimization without the long-run rate allocation constraint. Indeed, the rate allocation without the rate allocation constraint in Figure 4g is being approximated by the SDN rate allocation in Figure 3c. The rate allocation constraint safeguards against persistent unfair backhaul capacity usage by a given operator and is therefore generally recommended for operational networks.  
Overall, we observe from Figures 3 and 4 that the SDN-based optimization of backhaul resource sharing can significantly lower the eNB queue lengths. These lowered eNB queue lengths translate into significantly reduced latencies for the end-user upstream traffic.