esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Basic Watermarking Procedure  
The basic watermarking procedure and fundamental knowledge are presented here. A classical watermarking procedure is shown in Figure 2.  
Figure 1: Research diagram to show the robustness computation model.  
Figure 2: Watermarking procedure.  
In the watermarking procedure, the original watermark information is converted into binary watermark sequence, then embedded into the watermark domain, which is transformed or generated from the host data. After watermarked data has been delivered or distributed, the copyright information is extracted by the inverse method and compared to the original one. Thus, the copyright can be identified clearly as long as the watermarking algorithm is sufficiently robust.  
It has to be pointed that the copyright information includes text, voice, image and so on, and it is converted into binary sequence before the process of embedding. In addition, the comparison of copyright information is equal to the comparison of binary sequence as long as the conversion is reversible. Thus binary watermark sequence is regarded as the form of what watermarking algorithm embed and extracted in this paper. Watermark synchronization and robustness evaluation index, which are closely related to the issue of robustness computation for image cropping attacks, are discussed as follows.
# An Active Path-Associated Cache Scheme for Mobile Scenes
## 5 Simulation Results and Analysis
### Link Load  
Debt balance is a key problem in computer network research. It can be seen that researchers attach great importance to link load. In this paper, we use the average link load to calculate the time consumption of these caching strategies.  
As shown in Figure (d)d-f, with the increase in Alpha, the average link load also begins to decrease. We mentioned in the previous analysis that with the increase in Alpha, popular content is more likely to be cached and requested, which will reduce the delay exponentially. All the caching schemes have achieved a faster load drop speed. Our solution still achieved the best load performance.  
In the experiment of increasing the cache space, both LCE and CL4M showed that as the space increased, the average network load did not decrease. This shows that the two strategies have more cache redundancy. The best-performing LCD and our strategy have seen a significant load reduction as the space increases, which shows that the idea of pulling content to the edge and making full use of other nodes in the cache link is very effective. In addition, it is worth mentioning that the cache efficiency of MINE is significantly higher  
Figure 9: Performance of Link Load.  
than that of LCD. It can be seen from Figure 9a-c that our strategy saves 60% of the space compared to LCD when obtaining the same performance as LCD, which is a very amazing optimization effect.
## 2 Existing Work  
PMIPv6, the localized network-based mobility management standard introduced by the IETF, does not include mobile nodes such as vehicles in mobility-related signals. Instead, the network entity assigns the vehicle a special home network prefix (HNP) when it enters the PMIPv6 mobility domain. This prefix will be used to identify the vehicle consistently inside a mobility domain. As a result, the vehicle considers the PMIPv6 domain to be its principal network. The two functional parts of the underlying PMIPv6 architecture are the mobile access gateway (MAG) and a local mobility anchor (LMA). The MAG or access router (AR) is concerned with monitoring the vehicle's movement, whereas the LMA is the anchor point of the PMIPv6 domain. As soon as the MAG notices the movement of the vehicle, it starts the procedures needed for handover with the LMA. It accomplishes this by sending a proxy binding update (PBU) message to the LMA. Additionally, a tunnel connects the LMA and MAG so that they may use the vehicle's HNP address [12; 13]. All vehicular traffic passes via the LMA, which serves as a topological anchor point and is responsible for preserving the PMIPv6 domain's routing and vehicle accessibility. Through binding cache entry (BCE) [13; 14], the LMA also keeps track of each registered vehicle's binding status. The established interface identification of the tunnel, the vehicle's HNP, a proxy registration flag, and other details are all contained in the BCE. When a vehicle's point of attachment changes, Layer 2 handovers, intra-domain handovers, and inter-domain handovers are all possible. When a vehicle switches access points while still in the same MAG, a Layer 2 handover takes place. This modification does not affect the LMA, since the MAG only affects the binding of the vehicle locally. An inter-domain handover takes place when a vehicle transitions between two MAGs connected to the same LMA. The MAGs maintain the vehicle attached to the LMA by switching PMIPv6's handoff signals. On the other hand, the vehicle's attachment points alternate between two MAGs connected to different LMAs during the inter-domain handover. Originally, the PMIPv6 protocol was only responsible for managing intra-domain mobility roaming. While assessing the total packet delivery cost for VANET in PMIPv6, none of the existing solutions consider authentication during handoff; however, we have considered the authentication cost during handover, along with the IP multicasting that enables the inter-domain handover for VANET in PMIPv6. Thus, neglecting this situation invariably results in a handover that is not secure and is inefficient. To solve these issues, we suggest a method that takes the authentication costs into account while evaluating the overall cost of packet delivery in PMIPv6 for a vehicular network, along with IP multicasting, which allows inter-domain handover for VANET in PMIPv6.
# Practical Grammar Compression Based on Maximal Repeats +
## Appendix A  
Figures 11-11 are provided to help in understanding the proof of Theorem 4.  
Let \(G_{rp}\), \(G_{nmr}\), and \(G_{mr}\) be the grammars generated by RePair, Naive-MR-RePair, and MR-RePair, respectively. For a given text \(T=a_{1}\cdots a_{n}\) (\(a_{i}\in\Sigma,\ 1\leq i\leq n\)) of length \(|T|=n\), let \(g_{rp}\), \(g_{nmr}\), and \(g_{mr}\) be the sizes of \(G_{rp}\), \(G_{mmr}\), and \(G_{mr}\), respectively. Let us assume that \(T=(aw)^{2(2^{m}-1)+1}a\), where \(w\in\Sigma^{+}\) such that \(awa\) is the most frequent maximal repeat of \(T\) and \(m\in\mathbb{N}^{+}\). Then, according to the proof of Theorem 4, \(g_{mmr}>g_{rp}\) holds for some \(m\) and \(w\) such that \((m-1)(|w|-1)>1\).  
Figure 11 illustrates a specific example of the grammar generation process of RePair and \(G_{rp}\) for \(T=(\mathtt{abcd})^{7}\mathtt{a}\) with \(m=2\) and \(|w|=3\). The size \(g_{rp}\) is 18 in this example. Figure 12 illustrates an example of the process of Naive-MR-RePair and \(G_{nmr}\) for the same \(T\). It can be noticed from the figures that the size \(g_{nmr}\) is 19, and thus \(g_{mmr}>g_{rp}\) holds. As shown in Figure 12, Naive-MR-RePair may fail to extract repetitive patterns in particular cases (such as \(\mathtt{abcd}\) of \((\mathtt{abcd})^{7}\mathtt{a}\) in the running example). However, this problem can be solved using MR-RePair. Figure 13 illustrates an example of the process of MR-RePair and \(G_{mr}\) for the same \(T=(\mathtt{abcd})^{7}\mathtt{a}\). The size \(g_{mr}\) is 16, which is smaller than \(g_{rp}=18\). Although the most frequent maximal repeat at the second replacement step is \(v_{\mathtt{a}}v_{\mathtt{b}}v_{\mathtt{c}}v_{\mathtt{d}}v_{\mathtt{a}}\), MR-RePair replaces \(v_{\mathtt{a}}v_{\mathtt{b}}v_{\mathtt{c}}v_{\mathtt{d}}v_{\mathtt{a}}\) with a new variable \(v_{\mathtt{I}}\), providing the additional **Step 3** in Definition 3.  
Figure 11: Grammar generation process of RePair and its generated grammar for the text (abcd)\({}^{7}\)a. The grammar size is 18.  
Figure 12: Grammar generation process of Naïve-MR-RePair and its generated grammar for the text (abcd)\({}^{7}\)a. The grammar size is 19.
# CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC
## 4 Proposed Scheme
Finally, the RAR message transmission phase is a process for allocating uplink resources to devices that have successfully transmitted the preamble codeword. In legacy RA, low PUSCH utilization decreases the RA success rate as the number of PUSCH non-allocable devices increases. In order to improve the PUSCH resource utilization, we propose an improved PUSCH allocation procedure based on the PUSCH waiting message. The PUSCH waiting message is transmitted to devices that have not been allocated PUSCH resources when the allocable PUSCH resource is less than the number of received preamble codewords. Since the proposed PUSCH allocation method does not require significant changes in the RAR transmission process, we can follow the legacy random access procedure with small modifications. Among the four phases of the proposed CeRA-eSP scheme mentioned above, phases 1 and 3 are the same as in the procedure of the legacy CeRA. As the main difference from the legacy CeRA, first, we propose the preamble codeword set selection algorithm to improve the RA success rate in phase 2 of the CeRA-eSP. Second, we propose an improved PUSCH allocation scheme based on a novel PUSCH waiting message to improve PUSCH utilization. In the following subsections, we describe the two proposed schemes in phases 2 and 4. Figure 4: Overall procedures of the proposed CeRA-eSP scheme.
# Application of Fiber Bragg Grating Sensing Technology for Bol Force Status Monitoring in Roadways
## 5 Conclusions  
An FBG bolt force sensor was designed, and its measuring principle and structure are introduced here. This sensor provides the online monitoring and direct reading functions. It uses a cantilever and a circular diaphragm as elastic elements--two FBGs as sensing elements. The center wavelength difference between the two FBGs is utilized as a measuring signal, thus improving measuring precision. The experimental results show that this sensor has good linearity with a sensitivity of 38.79 pm/kN and a correlation coefficient of 99.98% in the measuring range.  
The presented FBG bolt force sensor has been utilized to monitor roadway bolt force in the Shaqu coal mine in Shanxi, China. The engineering applications indicate that the change law of the bolt force and the affected mining range monitored by the FBG sensor provides continuity and timeliness, and the monitoring results are of great significance in the parameter design of bolt support in roadways. Above all, such a sensor is also widely used in quasi-distributed measurement and the long-term online monitoring of bolt force in such fields as geotechnical engineering, tunnel engineering, and slope engineering.  
This study was financially supported by the Fundamental Research Funds for the Central Universities (No. 2014 ZDPY22).  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments and analyzed the data; [PERSON] and [PERSON] wrote the paper.  
The authors declare no conflict of interest.
## Appendix A. Pyminisat Module Implementation  
The various model elements discussed in Sections 2 and 3 were implemented as part of the Pyminisat Python module [28], which is publicly available under an open-source license. In its implementation, we exclusively used standard Python libraries, such as numpy, scipy for numerical manipulations, and matplotlib for result visualization. The Pyminisat module implements the satsim class, which contains all essential attributes of the satellite network pertaining to the constellation and transceiver systems. The satsim class invokes two sub-modules, namely the linkmodel class, which can be used to study an end-to-end OIL, and the constellation class, which incorporates the constellation dynamics and determines the optimal \(F\) value and the minimum distances that need to be covered in order to ensure network connectivity.  
To study a given constellation, e.g., the one described in Table 1, the satsim class carries out the simulation in the following steps: first use the constellation class to estimate the best value for \(F\) and, therefore, determine the initial satellite position in the constellation. Then, initialize the constellation with the optimal value of \(F\) and calculate the minimum link distances required to provide connectivity to the nearby neighboring satellites (see Figure 4) over one orbital period. Given the parameters of the receiver and the data rate, use the linkmodel class to calculate the receiver sensitivity. Based on this value, calculate the required transmitter power for each instance of the orbital period using the link budget in (11). The Github repository of the model [28] further describes how the initialization parameters of the satsim class can be changed to fit various network scenarios.  
To the extent possible, we optimized the code in order to take advantage of the large speed-ups involved when numpy vectorization is used instead of for loops. By far the most computationally challenging task is to optimize the constellation in terms of the \(F\) parameter. We can take advantage of the fact that the estimation of the distances in (9) is an embarrassingly parallel problem for the different time instances \(t=t_{l}\) assumed. We can, therefore, use Python's multiprocessing module to distribute the load to the available central processing unit (CPU) cores. On a standard 6-core, AMD Ryzen 5 7530U CPU (with 2 threads per core), the time required to optimize the constellation in Table 1 and estimate the power requirements is \(\approx\)14.3 s. For completeness, we tested a scenario with a constellation even denser than Scenario C, tripling both the number of satellites per orbit and the total number of orbits compared to Scenario A, yielding a total of 14,256 satellites. The computation time required in the same platform was now 165.7 s.
## 3 Results and Discussion
### Measurement Results
#### 3.2.3 Radiation Patterns Measurement  
As illustrated in Figure 23, the far fields were tested inside the anechoic chamber. The BSA was mounted on a body phantom that served as a receiving device, while the horn-shaped antenna served as a transmitting antenna, moving in the azimuth and elevation planes. Keysight vector network analyzer model PNA-X N5242A was used to measure S\({}_{21}\)  
Figure 22: Set-up for the path loss. A: WiFi router, B: BSA, C: spectrum analyzer, BPF: band pass filter, LNA: low noise amplifier.  
and the radiation patterns. The dielectric properties of the phantom are similar to human muscle tissue, with a relative permittivity (\(\varepsilon_{\text{r}}\)) of 52.7 and 48.2, and a conductivity of 1.95 and 6 S/m, at the lower and higher bands, respectively [66]. Figure 24 shows the predicted measured radiation patterns for different cases and frequencies. The arm is usually a good place for mounting wearable antennas because the radiation in horizontal positions from the arm is less influenced than the radiation from the antennas placed on the chest. The first location is less surrounded by the tissues than the second. At the lower band, it can be seen that the BSA has an omnidirectional radiation pattern, which can be employed for on-body communication. At the upper band, omnidirectional radiation was also achieved, which could be useful for off-body communication. Fabrication tolerances and imperfections of the materials might impair the performance of textile antennas in real-world circumstances. As can be seen, the BSA maintained a good radiation pattern stability under different conditions at different frequency bands.  
Figure 23: (**a**) Setup for far-field measurement, (**b**) phantom for the chest position, and (**c**) phantom for the arm position.
## 3 Experimental Results
### MLP Architecture Selection
This test is used to determine the most appropriate MLP configuration for coronary arteries detection in X-ray angiograms by pairwise comparison of all candidate architectures using the testing set of images. The hypothesis test determines whether the detection performance between two configurations are similarly distributed, by using a significance level of 5%. On the other hand, when the hypothesis of similarly distributed detection performance is rejected, the sum of ranks is employed to determine whether the left or right hand configuration is stochastically dominant. For the best 10 MLP configurations, Table 2 illustrates the hypothesis testing process by reporting the \(p\)-value and the corresponding left and right hand sum of ranks, denoted respectively by \(-\) and \(+\). The stochastic dominance comparison is summarized in Figure 6, where a high detection performance can be observed for configurations with more than 4 neurons in each hidden layer. In this figure, the configuration [9; 9] is highlighted with a dotted line, corresponding to the architecture that stochastically dominates most of the other configurations of the comparative analysis. The stochastic dominance comparison results are ranked according to the number of other architectures stochastically dominated, in order to determine the most appropriate configuration to be used in the proposed method. Table 3 shows the comparative results of the top 10 architectures from the 100 comparative architectures tested. According to comparative analysis, the configuration that stochastically dominates the most of other architectures is the [9; 9] architecture, being superior to other 90 configurations. In addition, the [9; 9] architecture obtains a detection performance stochastically similar to only other 9 configurations, and it is not stochastically dominated by any other configuration. Because the MLP [9; 9] configuration presents the highest stochastic dominance results, it was selected as the most appropriate architecture to provide the final detection response of the proposed method. Figure 6: Distribution of the number of architectures dominated by each configuration according to the ranking procedure using the testing set of images. The configuration [9; 9] that dominates most of the other architectures is highlighted with a dotted line.
## 3 Environment Characterization
### Urban Environment  
The urban environment refers to an area characterized by a high-density population, a diversity of used devices, and a concentration of human-built infrastructure and services such as transportation systems, housing, commercial buildings, and cultural institutions. It is often characterized by a high concentration of wired and wireless communication infrastructure, providing residents with a wide range of communication options.  
First, in an urban environment, by using the existing power grid, PLC is used to provide high-speed connectivity without the need for additional infrastructure or cables and is also used to support specific communication services, such as home automation, smart grid applications, and remote monitoring. However, PLC has some drawbacks compared to other communication technologies. In fact, the quality and reliability of a PLC signal is affected by noise, electrical interference on the power grid, and other factors such as distance, interference from other electrical devices, and the quality of the power grid infrastructure. In addition, PLC is subject to regulatory and safety requirements related to power grid operations [47].  
Second, RF communication plays a crucial role in enabling smart grid applications in urban environments. In fact, RF technology enables communication between different components of the grid, such as meters, sensors, and control systems. Therefore, they provide a range of services, such as remote meter reading, demand responses, and real-time monitoring and control of the grid. For example, AMI uses RF communication to enable two-way communication between smart meters and utility companies, allowing real-time monitoring of electricity usage, besides the remote disconnection and reconnection of service. However, it has several limitations that affect its reliability and performance in terms of the SNR and communication range. Some of the key limitations include the interference with other wireless devices, buildings, and other physical obstacles, as well as signal attenuation due to trees and other objects leading to reduced signal power and range.  
Therefore, both RF communication and PLC provide redundant or complementary communication services and multiple communication paths for smart meter data, ensuring reliable and secure communication even in the presence of interferences or other disruptions. In urban environments, smart meters and data concentrators are designed to work within a range of a few hundred meters. This range is usually sufficient for most urban environments, where buildings, other structures, and electric network topology can often obstruct the transmission of wireless and wired signals.
# Quality Assessment of Dual-Parallel Edge Deblocking Filter Architecture for HEVC/H.265
###### Abstract  
Preserving the visual quality is a major constraint for any algorithm in image and video processing applications. AVC and HEVC are the extensively used video coding standards for various video processing applications in recent days. These coding standards use filters to preserve the visual quality of the processed video. To retain the quality of the reconstructed video, AVC uses an in-loop filter, called the deblocking filter, while HEVC uses two in-loop filters, the sampling adaptive offset filter and the deblocking filter. These filters are implemented in hardware by adopting various optimization techniques such as reduction of power utilization, reduction of algorithm complexity, and consuming lesser area. The quality of the reconstructed video should not be impacted by these optimization measures. For the HEVC/H.265 coding standard, a parallel edge deblocking filter architecture is designed, and the effectiveness of the parallel edge filter architecture is evaluated using various quantization values for various resolutions. The quality of the parallel edge filter architecture is on par with the HEVC reference model.  
deblocking filter; quality assessment; parallel edge filter; HEVC/H.265; sample  
The discontinuities are perceivable for the human visual system (HVS) as blocking effects in the region with lower activity in the video frame [6]. Preserving the same visual quality as the original visual scene is a significant challenge. The AVC and HEVC coding standards utilize lossy compression algorithms such as DCT/DWT, and, hence, the originality of the pixel intensities are lost when the video data are reconstructed. However, measures are taken to upgrade the quality of the reconstructed video in the codec. AVC has an in-loop filter called the deblocking filter (DBF) to reduce visible discontinuities. HEVC standard reduces this visible discontinuity in the main profile by the use of two in-loop filters applied to the reconstructed video in succession. These two in-loop filters are the DBF and the sample adaptive offset (SAO) filter. Although these filters are employed to improve the reconstructed video's quality, these enhancement methods do not produce a perfect replica of the original image.  
The DBF and SAO filters used in HEVC are optimized by modifying the filtering algorithms or by implementing the algorithms efficiently in hardware concerning cost and energy saving. Even though these optimization techniques enhance the quality of the video, we need to measure the quality to compare with different optimization techniques.