esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Performance Metrics
### Performance Metrics for Non\(-\)Emergency Packets  
When an incoming non\(-\)emergency packet voluntarily leaves the system with probability \((1-f)\) or requests access with probability \(f\) while the system has no vacancies, this incoming non\(-\)emergency packet will be blocked. Non\(-\)emergency packets' blocking rate \(\beta_{2}\) is expressed as following two situations.  
\begin{table}
\begin{tabular}{c c} \hline \hline Step 1 & Create unit matrix \(\mathbf{Q}=\left(\begin{array}{cc}1&\\ &\ddots&\\ &&1\end{array}\right)_{(2K+H+3)\times(2K+H+3)}\) \\ \hline Step 2 & Create column vector \(\mathbf{e}=\left(\begin{array}{c}1\\ \vdots\\ 1\end{array}\right)_{(2K+H+3)\times 1}\) \\ \hline Step 3 & Create matrix \(\mathbf{Q}^{\prime}=(\mathbf{W}-\mathbf{Q},\mathbf{e})\). \\ \hline Step 4 & Create row vector \(\mathbf{e}^{\prime}=(0,\cdots,0,1)_{1\times(2K+H+4)}\), which contains \((2K+H+3)\) zeros. \\ \hline Step 5 & Resolve \(\mathbf{\Pi}=\mathbf{e}^{\prime}/\mathbf{Q}^{\prime}\). \\ \hline \hline \end{tabular}
\end{table}
Table 2: The procedures for solving \(\pi_{x,g,z}\).  
1. If \(H=K\), \(\beta_{2}\) is expressed as follows. \[\begin{split}\beta_{2}&=\sum\limits_{x=0}^{H}\pi_{x,0,0 }p_{2}\frac{x}{\alpha}+\sum\limits_{x=1}^{K+1}\left(\pi_{x,0,1}+\pi_{x,1,1} \right)p_{2}\frac{x}{\alpha}\\ &+(\pi_{K,0,0}+\pi_{K,0,1}\bar{s}_{2}+\pi_{K,1,0}\bar{s}_{1})(1- \frac{K}{\alpha})p_{1}p_{2}\\ &+\big{(}\pi_{K+1,0,1}(\bar{s}_{2}+s_{2}p_{1})+\pi_{K+1,1,1}( \bar{s}_{1}+s_{1}p_{1})\big{)}(1-\frac{K+1}{\alpha})p_{2}\end{split}\] (21)
2. If \(0\leq H\leq K-1\), \(\beta_{2}\) is expressed as follows. \[\begin{split}\beta_{2}&=\sum\limits_{x=0}^{H}\pi_{x,0,0}p_{2}\frac{x}{\alpha}+\sum\limits_{x=1}^{K+1}\left(\pi_{x,0,1}+\pi_{x,1,1} \right)p_{2}\frac{x}{\alpha}\\ &+(\pi_{K,0,1}\bar{s}_{2}+\pi_{K,1,0}\bar{s}_{1})(1-\frac{K}{ \alpha})p_{1}p_{2}\\ &+\big{(}\pi_{K+1,0,1}(\bar{s}_{2}+s_{2}p_{1})+\pi_{K+1,1,1}(\bar {s}_{1}+s_{1}p_{1})\big{)}(1-\frac{K+1}{\alpha})p_{2}\end{split}\] (22)  
When a non\(-\)emergency packet is interrupted, the interrupted packet will be discarded if there are no available spaces in the cache. Non\(-\)emergency packets' outage and loss rate \(\phi_{2}\) is expressed as follows.  
\[\phi_{2}=\pi_{K+1,0,1}\bar{s}_{2}p_{1} \tag{23}\]  
Non\(-\)emergency packets' throughput \(\theta_{2}\) is the amount of emergency packets forwarded completely in a unit time slot, expressed as follows.  
\[\theta_{2}=p_{2}-\beta_{2}-\phi_{2} \tag{24}\]  
Non\(-\)emergency packets' average latency \(\eta_{2}\) refers to the time interval between non\(-\)emergency packets entering and leaving the system. According to [PERSON]'s formula [28], \(\eta_{2}\) is expressed as following two situations.  
1. If \(H=0\), \(\eta_{2}\) is expressed as follows. \[\eta_{2}=\frac{\sum\limits_{x=1}^{K+1}\left(\pi_{x,0,1}x+\pi_{x,1,1}(x-1) \right)}{p_{2}-\beta_{2}}\] (25)
2. If \(1\leq H\leq K\), \(\eta_{2}\) is expressed as follows. \[\eta_{2}=\frac{\sum\limits_{x=1}^{H}\pi_{x,0,0}x+\sum\limits_{x=1}^{K+1}\left( \pi_{x,0,1}x+\pi_{x,1,1}(x-1)\right)}{p_{2}-\beta_{2}}\] (26)
# GSFedSec: Group Signature-Based Secure Aggregation for Privacy Preservation in Federated Learning
## 4 Security Analysis of the Proposed Algorithm  
No networking algorithm can be implemented in a network if it is not safe to use. The proposed technique can overcome noteworthy attacks. The protocol has been tested on privacy and authentication related security criteria. We provide mathematical analysis and simulation results for our algorithm. We also present a few popular attacks and discuss how our protocol overcomes them. The major security attacks to evaluate the security of the proposed algorithm include the below:  
1. Privacy attack on the identity of the user
2. Inference attack on the data received in various iterations.  
3. _Impersonation attack by an unauthenticated intruder_
4. _Sybil Attack or fake identities attack_
5. _Honest-but-curious attack by the server_
6. _Collusion attack by clients on a targeted client_
# Research on Path Planning Multiple Mobile Robots Based on the LAPGWO Algorithm
## 3 Methodology  
In this section, the path planning method for multiple mobile robots based on the LAPGWO algorithm proposed in this paper is elaborated in detail. This method solves multi-mobile robot path planning problems, such as long global path search time, low efficiency, and the proneness of collisions between robots. Especially in environments with numerous obstacles, it is difficult for robots to quickly and effectively find the optimal path from the starting point to the target point, which minimizes the total cost of all robots completing tasks.
# Area-Efficient Early-Termination Technique for Belief-Propagation Polar Decoders
## 5 Conclusions  
We developed a novel early-termination method for BP polar decoders to reduce hardware complexity without deteriorating the decoding throughput. Previous early-termination techniques have several disadvantages. The threshold-based [15] technique demands high hardware complexity, and information-BER-based [16] and frozen-BER-based [17] methods incur in performance degradation in terms of system throughput. Experimental results show that the proposed method maintained the smallest value of average decoding iterations demanding a small additional hardware circuitry compared with the previous early-termination method for BP polar decoders [15; 16; 17]. The proposed method for (1024, 512) polar codes can reduce hardware complexity up to 72.7% compared with the previous early termination without any frame-error-rate performance degradation. Thus, the proposed method can provide an area-efficient solution to adopt an early-termination scheme in BP polar decoders.  
Conceptualization, H.Y.; Data curation, S.C.; Formal analysis, S.C.; Funding acquisition, H.Y.; Investigation, S.C.; Methodology, S.C.; Project administration, H.Y.; Resources, S.C.; Software, S.C.; Supervision, H.Y.; Validation, S.C.; Visualization, S.C.; Writing--original draft, S.C.; Writing--review & editing, H.Y.  
This research received no external funding.  
This work was supported by the National Security Research Institute grant funded by the Korea government (MSIP) (2019-0424-01), and EDA tools were supported by IDEC, Korea.  
The authors declare no conflict of interest.
# Sustainability-Based Analysis of Conventional to High-Speed Machining of Al 6061-T6 Alloy
## 4 Analysis of Experimental Data: Transitional Speed Machining (TSM)
### Confirmatory Experiments  
Confirmatory experiments were performed based on the findings of main effect plots (Figures 6 and 7), and the results are presented in Table 11. As with the case of conventional speed machining, the setting of the machining parameters required to obtain optimal values of SCE and Ra were observed to be entirely different, further strengthening the requirement of a multi-objective model for cutting parameters.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variable** & **DOF** & **Seq. SS** & **Adj. MS** & **F-Value** & \(p\)**-Value** & **CR (\%)** \\ \hline \(v\) (m/min) & 3 & 16.774 & 5.59133333 & 30.65 & 0.000 & 16.90\% \\ \(f\) (mm/rev) & 3 & 56.344 & 18.7813333 & 102.97 & 0.000 & 58.10\% \\ \(d\) (mm) & 3 & 15.981 & 5.327 & 29.21 & 0.000 & 16.07\% \\ Error & 38 & 6.931 & 0.182394737 & & & 8.93\% \\ Total & 47 & 96.03 & & & & 100.00\% \\ \hline \hline \end{tabular}  
* Std. dev = 0.427076; R\({}^{2}\) = 92.78%; R\({}^{2}\) predicted = 88.48%.  
\end{table}
Table 10: Analysis of variance and percentage contribution results for Ra.  
Figure 6: Main effect plots showing the influence of cutting parameters on SCE in TSM.
# Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment
## 1 Introduction
Additionally, methods using DOP coefficients or DOP mapping approaches have the following shortcomings for UAV integrity monitoring or path planning applications in urban areas:  
* In low-cost receivers, DOP coefficients are calculated by applying a matrix inversion to each quad (four-combination) of the visible satellites (although there are some alternative methods) for selecting subsets of satellites with optimal positioning performance [22]. The DOP update and continuous mapping during the flight in this way are computationally very expensive and not feasible for smaller UAVs. Instead, elevations and number of visible satellites can be extracted from navigation message without any calculation for quick updates. * DOP maps, even in a static environment, are time-varying because of the movement of satellites, so their validity can change during the flight and integrity risks may increase. Due to their time-varying nature, DOP maps are not well suited for the provision of integrity limitations. With using time-independent environmental variables, such as cut-off elevation, integrity risks can be analyzed more accurately before and during the flight. The use of DOP coefficients for accuracy or availability characterization was thoroughly studied by many authors. Nevertheless, application of DOP maps is mostly limited to availability analysis and does not include integrity requirements. One of the most recent examples of DOP maps generation and application can be seen in [23], where authors use scanned environment profiles for visibility analysis and DOP prediction for an availability analysis. We use a different approach that can be beneficial when no scanned information was available. Moreover, we focus on integrity analysis, which was not covered previously using either DOP coefficients or elevation and visibility criteria. Considering the previous works and mentioned challenges, this paper concerns integrity monitoring of the GPS-based UAV positioning in urban environments. We focus on the analysis of environmental parameters to derive limiting values suitable for integrity characterization within an urban air mobility concept. For this purpose, we consider the influence of cut-off elevation and satellite visibility on the behavior of DOP coefficients and, therefore, the integrity of the positioning for UAVs. One of the key novelties of our integrity monitoring approach is in the proposition and use of DOP-based indirect protection levels as the replacement of the standard position error-based protection levels, as DOP coefficients can be extracted from receiver outputs during flight, unlike unobservable position errors. Another novel proposition is to supplement DOP-based integrity measures with parameters specific to the immediate environment that allow for estimating integrity in a particular environment and can be used to decide on mitigation measures in cases of observed integrity failures.
# Detecting Anatomical Leg Length Discrepancy Using the Plug-in-Gait Model
## 2 Methods
### Motion Capture  
Anthropometrical measurements performed included--inter anterior superior iliac spine (ASIS) distance, distance of the right and left ASIS to the respective medial malleolus (MM) (clinical leg length), right and left knee, ankle width and tibial torsion measured by an intermalleolar angle in prone position. Subsequently, 13 reflective passive skin markers were placed on the pelvis and lower limbs, adhering to the PGM protocol [15]. Thigh and shank wand markers were aligned using the mirror method [19]. The thigh wand was aligned co-linearly with the HJC (greater trochanter) and the knee and shank marker were attached co-linearly with the knee and ankle markers [19].  
Three-dimensional motion analysis was obtained by 8 MX3 cameras (Vicon Motion Systems(r), Oxford, UK) and the Nexus(r) software (Version 1.8, Vicon Motion Systems(r), UK, 2013). Following a standard protocol, a static calibration trial was performed for each subject while standing. All subjects' measurements, marker placement and alignment were performed by the primary experienced investigator in gait analysis. Calculated subject measurements were extracted from the static measurements file.
## 3 Proposed Methodology
### Federated Classification Method with ResVGG-SwinNet
#### 3.7.1 Model Architecture  
The ResVGG-SwinNet architecture includes ResNet, VGGNet, and Swin-Transformer. A layered model for deep-feature extraction, efficient learning, and long-term contextual comprehension uses these components in order. The ResNet Block is the primary feature-extraction layer that captures low-level features and deep representations. ResNet uses residual connections to reduce the vanishing gradient issue. This shows ResNet Block feature extraction:  
\[\mathcal{F}_{\text{R}}(z)=\mathcal{H}(z)+z \tag{17}\]  
We use \(z\) as the input feature map and \(\mathcal{H}(z)\) as the output after applying convolutional layers and residual connections. \(z\) refers to the input feature map sent through the network, whereas \(\mathcal{F}_{\text{R}}(z)\) holds the extracted features.  
VGGNet Block (Feature Optimisation Layer): After ResNet extracts features, VGGNet optimises them. VGGNet, a deep convolutional network, employs modest (3 \(\times\) 3) convolution filters and a basic design. After ResNet, VGGNet optimises the features:  
\[\mathcal{F}_{\text{V}}(z)=\phi(W\cdot\mathcal{F}_{\text{R}}(z)+b) \tag{18}\]  
\(\mathcal{F}_{\text{R}}(z)\) is the ResNet Block input, \(W\) is the weight matrix, \(b\) is the bias term, and \(\phi\) is the activation function. Using computational efficiency, VGGNet optimises feature depth and performance.  
Contextual Dependency Layer Swin-Transformer Block: The Swin-Transformer block captures long-range dependencies and contextual information for interpreting complicated data interactions. It uses window-based self-attention to learn global and local dependencies:  
\[\mathcal{F}_{\text{S}}(z)=\text{Swin-Transformer}(\mathcal{F}_{\text{V}}(z)) \tag{19}\]  
Self-attention inside non-overlapping windows and window shifts capture local and global relationships, helping the model grasp complex data patterns.
## 2 Materials and Methods
### Single-Image-Based Pin-Array Impression Reconstruction Method (SIBPAIR)  
The three-dimensional (3D) morphology of the sole of the tested foot was measured using a novel method called Single-Image-Based Pin-Array Impression Reconstruction Method (SIBPAIR) implemented on a commercial foot assessment system (FAST, Enford International Co., Taiwan, Figure 1) [39]. The machine is 55.2 cm \(\times\) 30.1 cm \(\times\) 30.1 cm in length, width, and height, respectively, and has 2129 color-coded (green, red and white) pins (diameter: 3 mm) allocated in a measurement area (30 cm \(\times\) 12 cm) with a maximum measurement depth of 35 mm. According to the manufacturer, the machine has a high 3D surface reconstruction accuracy with a bias of 0.06 mm and a precision of 0.35 mm, as well as a high surface reconstruction reliability (ICC \(>\) 0.98). Each subject stood on the machine with the tested foot placed on the measurement area, with the longitudinal axis of the foot connecting the tip of the second metatarsal head and the heel tip parallel to the measurement area, pressing the probe pins downwards to form a 3D impression of the foot. The position of the pins could be locked and maintained firmly by a uni-axis fast locking mechanism. A single image (2048 \(\times\) 1536 pixels) of the impression was then taken using a tablet (Zenpad 8.0, ASUS, Taiwan; OS: Android 7.0), which was supported by a 37 cm movable tablet-supporting arm affixed to the machine, and oriented at an angle of about 20 degrees relative to the horizontal. These spatial parameters were chosen to optimize the accuracy of the 3D measurements, according to the manufacturer. A calibration image without a foot impression is also needed for the subsequent image analyses and 3D reconstruction. The SIBPAIR Method identifies the color-coded pins that are at known positions on the calibration image to define the local coordinate system of the measurement area of the FAST machine, along with the intrinsic and extrinsic parameters of the camera of the tablet, using [PERSON]'s method [40]. With the parameters of the camera, the SIBPAIR method reconstructs the 3D surface of the foot impression by the following steps: (1) identifies the 2D coordinates of the color-coded pins on the image of the impression; (2) reconstructs the 3D coordinates of the pins using the camera parameters, 2D positions of the pins, as well as the known physical distribution of the pins in the measurement area; (3) calculates the morphological parameters of the sole from the reconstructed 3D surface.
## 1 Introduction
Finally, an integrated system was used to confirm the accuracy of the repeated stimulus by measuring electromyography (EMG) signals from electrodes that were attached to the patients' arm and detecting the motor-evoked potential (MEP) to confirm that the same cortical stimulation could be repeated. The rest of this paper is structured as follows. Section 2 introduces the entire system integrating the positioning robot and navigation system. The kinematic analysis of the robot, finite-element method (FEM) and modal analysis, and control method of the robot are described in Section 3. The functions used in the developed navigation program and the coordinate system used in the whole system are explained in detail in Section 4. The evaluation of the robot's repeatability [16; 17], accuracy, and repeated stimulation experiments is analyzed in Section 5. Finally, Section 6 concludes with a planned experiment and an overview of the research using the developed integrated system.
## 6 Performance Evaluation
### Comparative Analysis
#### 6.3.2 Makespan  
A comparison of makespan, which is the total time taken to execute a set of tasks, is also performed. The simulation result indicates that our proposed work has a shorter makespan time than that of TTSA.  
The comparison of makespan between the proposed and existing methods is presented in Figure 6, in which the finishing time of the final task does not contain any overhead in our proposed work. VMs are provided with a light load and high computing power for executing several tasks in different sizes via the load balancing algorithm of WLC, which balances load on the basis of the weight assigned to each VM. The highest priority task is allocated first to the highest weight VM. This method increases the efficiency of the VM in executing various tasks, and thus, decreases the makespan time of our proposed work compared with that of TTSA.
# Approximate Networking for Universal Internet Access
## 1 Introduction
### Contributions of This Paper  
The main contribution of this paper is to investigate the extension of the concept of approximate computing to the field of networking. We propose approximate networking as an overarching, cross-layered framework that encompasses classical approximation techniques, as well as recently-developed techniques in the field of approximate computing, to implement context-appropriate networking trade-offs that are necessary for the aims of _\"Global Access to the Internet for All\"_ (GAIA). In order to facilitate these trade-offs, apart from the classical approximation techniques adopted in networking (in the areas of software/hardware, algorithms, protocols, and architecture), approximate networking will also leverage the advances in the fast-emerging field of approximate computing as an extra degree-of-freedom for finer-grained tradeoff optimization. We also propose approximate networking as an overarching framework for systematically thinking about networking trade-offs that must be adopted for ensuring GAIA. Furthermore, we also present an application of approximate networking in 5G with a case for low income and rural regions.  
This paper is organized as follows. Section 2 describes approximate networking technologies. In Section 3, we present context-appropriate approximate trade-offs for networking. We describe a case study for approximate 5G networks in rural and low income areas in Section 4. We present discussion issues for approximate networking in Section 5 and conclude in Section 6.
# Multiblock Analysis Applied to TD-NMR of Butters and Related Products
## 4 Discussion  
The traditional method of measuring fat in food products is the Soxhlet method, which is time consuming, destructive and uses polluting solvents. TD-NMR has been used to solve these problems. International standards have even been established (AOCS Cd 16b-93, AOCS Cd 16-81, ISO 8292, IUPAC 2.150). However, these NMR standard methods are often non-applicable to non-anhydroous products 1. This paper shows that the use of multi-block methods combining solid and liquid phase TD-NMR signals makes it possible to measure the fat content of fatty products containing water.  
TD-NMR signals are produced after one or several radiofrequency pulses, followed by relaxation phenomena that result in the exponential decay of the signals with time constants characteristic of the molecule mobility in the material being analyzed. Consequently, the classical signal processing in TD-NMR data consists of least squares fitting procedures [30] or uses a numerical inversion of the Laplace transform [31]. Such a signal processing task can be rather fastidious and is known to be an ill-conditioned and ill-posed problem, resulting in a large number of solutions that small noise in the data can easily affect. Chemometric methods have been developed to process ill-conditioned data in a stable and robust manner. Their application to process TD-NMR raw data is presently demonstrated as a good solution to overcome the above methodological limitations.  
The results provided by CovSel, with mono-block or multi-block data, show that it is possible to considerably simplify and improve the standards measurement protocols, avoiding the destruction of the sample and the use of pollutant solvents in comparison to standard Soxhlet methods and using the TD-NMR raw data directly without further fastidious preprocessing methods. For both temperatures, T\({}_{\rm 1L}\) measurements can be performed based on eight or even less sequences, which is an excellent timesaver. With eight measurements and a recycle time of 5000 ms, the experiment should last only 40 s, which is three to four times less than what is needed for T\({}_{2}\) relaxation time measurements with 16 scans and an echo time of 0.1 ms.  
The results reported in this article are as good as or better than those obtained by existing methods. In particular, the repeatability error is excellent, which shows the stability and robustness of the chemometric methods used. The results are good for both measurement temperatures. This suggests that it would be possible to build models independent of temperature, which would greatly shorten and simplify the measurement protocol, making it even more suitable for online use. Chemometrics offers a lot of methods for building such robust models.
## 6 Experiments and Results
### Sensitivity Analysis of Population Size  
Our DMOGWO algorithm has one key parameter, namely the population size \(N\). To investigate the impact of different \(N\) values on the algorithm's performance, nine levels of \(N\) are selected from the range [50,800], and the MK08 instance is tested. Each level independently runs 10 times, and the average HV and IGD values are computed. The influence of the key parameter \(N\) on the algorithm's performance is illustrated in Figure 8. It can be observed that DMOGWO is not very sensitive to the setting of \(N\) under the ranges considered, which effectively shows the algorithm's stability and robustness. Considering the balance between the number of evenly distributed solutions and the computational cost, the population size \(N\) is ultimately set to 200 in this study.