esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Applications of the Measuring Techniques in the Clinical Field  
This systematic review also aims to provide clinicians with a better understanding of how to execute the residual limb volume measurement and, at the same time, how to apply it to clinical fields. Some measurement techniques have the potential to be used for this purpose. Since some measuring techniques have been improved in their ways to perform the tests, measuring techniques seem to have become easier to learn and handle, and some techniques are user-friendly, with some portable devices used for measuring. The improvement of the measuring techniques potentially allows for clinicians to monitor their patients' residual limb volume in the clinical field as this is important for preparing them for prosthetic fitting or monitoring the residual limb volume in cases when a prosthetic socket change is needed.  
Currently, in most clinics, the way of recording the residual limb volume is by measuring the residual limb circumference at a certain point. This technique of recording is not a proper way of recording since the residual limb volume does not correlate well with circumference [33]. The laser scanning technique is one of the best techniques that can potentially be used to record the residual limb volume in the clinical field since this technique is user-friendly, easy for a clinician to learn, and has a short scanning time, and all the data can be saved digitally. These are unlike other techniques such as the bioimpedance technique, which is not so suitable to use for clinical applications since it can only record the amount of change in the residual limb volume. In addition, the techniques such as water displacement, contact probe, optical scanning, and bioimpedance have difficult setups for measuring the residual limb volume, while other techniques such as SXCT, MRI, and ultrasound are costly.
# Framework for Fast Experimental Testing of Autonomous Navigation Algorithms
## 5 New Localization Module: GNSS/SLAM Fusion
### Integrity Monitoring  
The entire information flow between the localization subsystems and the Kalman filter passes through an integrity monitoring module to avoid possible undesired behaviors. Each time an observation is generated from any high-level subsystem, we compute the Mahalanobis distance between the prediction and the observation to reject outliers. The rejected observations are excluded from the Kalman filter correction step.  
The integrity monitoring module also permits to correct the AMCL subsystem using the Kalman filter output, as we can see in Figure 7. This recovery procedure is especially useful to leave and return from/to the mapped area. The monitoring module will allow this correction step in cases where the AMCL variances exceed a certain threshold. To ensure the localization stability, this correction is applied only to the state vector of the AMCL, leaving the covariances as they are. This procedure helps to the convergence of the system when re-entering to a previously mapped area.
# Location-Based Deferred Broadcast for Ad-Hoc Named Data Networking
## 1 Introduction
The scheme takes advantage of location information to set up timers when rebroadcasting an interest. New algorithms are introduced in calculating the values for the timers to deal with the collision problem and set the forwarding priority for different potential forwarders. Our work, different from the early work, gives priorities to nodes that are closer to the straight lines between the previous forwarders and the data producer. By taking advantage of the location information, the nodes that are between data consumer and data producer will have higher priority to forward the interest packet. As such, the interest packets are accurately forwarded to the data producer with less overhead and shorter delay. The impact of the collision-avoidance timer on interest broadcast in ad-hoc NDN is separately evaluated in the wireless testbed ORBIT. The proposed protocol LBDB is evaluated using an NDN simulator (i.e., ndnSIM) with wireless additions. We have fully implemented LBDB and integrated it with the default NDN forwarding mechanism in ndnSIM. The performance of LBDB is compared with several existing protocols. The simulation results show that LBDB generates the least transmission overhead, shortest path, and shorter delivery delay than other broadcast schemes while maintaining a relatively high satisfaction ratio. This improvement is particularly important for CAVs because timely data acquisitions lead to quick responses in emergent live-death situations [PERSON] et al. (2016); [PERSON] et al. (2016). The rest of the paper is organized as follows: In Section 2, we analyze the differences and similarities of broadcast in traditional MANET and ad-hoc NDN; we then give a brief survey on different approaches in addressing the broadcast storm issue in ad-hoc NDN; Section 3 introduces our proposed Location-Based Deferred Broadcast scheme in detail and the ad-hoc NDN architecture with the LBDB scheme; Sections 4 and 5 evaluate the performance of LBDB and the trade-off in timer settings; and Section 6 concludes the paper.
## 3 Challenges in FSO Communication
### Atmospheric Channel Effects Phenomena
#### 3.1.3 Alignment and Pointing Accuracy  
In FSO communication, maintaining accurate alignment and pointing between the Tx and Rx is crucial. Misalignments, which can occur along both vertical and horizontal axes, are often modeled using Hoyt and Rayleigh distributions [8]. Such misalignments can cause PE that diminish the performance of the FSO system. These errors are quantified as the Euclidean distance between the centers of the photodetector and the beam footprint at the Rx. In addition to causing signal degradation, PE can lead to intermittent or complete signal loss. These errors may arise from various factors, including the movement of mobile stations, platform vibrations, building sway, transceiver sway, seismic activity, inaccuracies in the tracking system, or stress in the system's mechanical or electronic components. An alternative form of PE, known as beam wandering, is due to AT, where large-scale atmospheric eddies cause the transmitted beam to deviate from its intended trajectory [2; 7].  
Dynamic environments pose considerable challenges for the propagation and stability of optical signals. These environments are marked by ongoing changes in position, orientation, or atmospheric conditions, which can affect the alignment, signal integrity, and overall performance of FSO systems. Therefore, in mobile applications, continuous realignment is essential to sustain a stable connection, necessitating advanced tracking and control systems. A thorough review of pointing, acquisition, and tracking (PAT) mechanisms employed in FSO communication systems is provided in [7].
## 2 Materials and Methods
### Cell Viability Assessment with MTT Assay  
Following incubation of the breast cancer cells in presence of NPs, PRKCA siRNA+NPs, PTEN+NPs and PRKCA siRNA+PTEN+NPs for 48 h, 50 \(\mu\)L of MTT solution (5 mg/mL in PBS) was added to each well and the cells were incubated for 4 h at 37 \({}^{\circ}\)C. The medium was removed and 300 \(\mu\)L of DMSO was added to each well to dissolve the purple formazan crystals and absorbance was measured in a micro plate reader at 595 nm with a reference wavelength of 630 nm. Cell viabilities were normalized to the absorbance of untreated cells (control). Each treatment experiment was performed in triplicate and cell viability was expressed as mean \(\pm\) SD.  
The cell viability in the treated wells was expressed as a percentage and was calculated using the absorbance values obtained from MTT assay. The following formulae were used to calculate the cell viability data:  
\[\text{Cell viability}\left(\%\right)=\frac{\text{Abs}(\text{sample})-\text{Abs }\left(\text{negative control}\right)}{\text{Abs}\left(\text{positive control}\right)-\text{Abs}\left(\text{negative control}\right)}\times 100\]
## 3 Infrared Image Segmentation
### Copper Rod Segmentation Based on the Region Growing Algorithm  
The global threshold method has certain limitations because of the gray properties of some areas, such as copper rods, pipes, and electrolytes, in grayscale images. The gray properties in each copper rod area are similar. We can use the local region growing algorithm to segment each of the copper rods in grayscale images.
# Practical Performance Analysis of Interference in DSS System
## 5 Field Test and Performance Analysis
### Neighbor Cell Interference Test
#### 5.2.1 NR Downlink Interference from LTE of Neighbor Cells to DSS Test Cells  
The test results are shown in Figure 14.  
As can be seen in Figure 14, the downlink throughput decreases with increasing distance. When the neighbor cell is changed from NR Only to LTE Only, the downlink throughput is greatly reduced, and the throughput dropped by 57% at point 6 with the strongest interference. In the case of no-load, compared with NR, the LTE of neighbor cells will reduce the NR downlink performance of the DSS test cell by about 34% on average. With 50% load, LTE degrades the NR downlink performance of the DSS test cell by about 15%. It can be seen that the interference brought by LTE has a great influence and cannot be ignored.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Test Point** & **1** & **2** & **3** & **4** & **5** & **6** \\ \hline Distance (m) & 51 & 90 & 142 & 200 & 248 & 288 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Distance of The Six Test Points From The Test Cell.  
Figure 14: LTE to NR downlink interference test results.
## 4 Case Study
### Bridge Models  
The bridges are two ordinary standard bridges (OSBs) representing California highway bridges, and designed according to the Caltrans Seismic Design Criteria [42], Figure 3a. The two benchmark bridges differ because of their longitudinal connections between the deck and the abutments, which are realized with different bearing pads in symmetrical positions, according to the plan locations (Figure 3b).  
**Bridge 1 (B1):** The connections are realized with sliding isolators implemented with a simplified two-spring model, defined by the initial bending stiffness k1/2, yield strength Fy0, and post-yield stiffness k20 (28,500 kN/m, 287 kN, and 166.67 kN/m, respectively). More details may be found in [41; 43; 44].  
**Bridge 2 (B2):** This scheme may move longitudinally because the connections between the deck and the abutments are achieved with soft damping rubber bearings. Such devices are modeled with two longitudinal elastic springs (730 kN/m) for each pad (modulus of elasticity G = 0.4 MPa and equivalent viscous damping n = 10%) [41].  
In both bridges, the vertical and transversal directions of the abutments are restrained, and fixed connections are considered at the top of the column by restraining the translations and the rotations of the deck in all directions. The presence of the isolation allowed us to assume that the deck was capacity-designed; thus it was modeled with linear elastic beam-column elements (length: 90.00 m; width: 11.90 m; depth: 1.83 m; cross area: 5.72 m\({}^{2}\), transversal inertia: 2.81 m\({}^{4}\) and vertical inertia: 53.9 m\({}^{4}\), weight per unit length: 130.3 kN/m, as shown in Table 2). The 6.71 m RC column was represented with nonlinear fiber beam-column elements (see [45]) fixed at the base. Soil-structure interaction was also neglected, in correspondence with the connection between the soil and the approach ramps, which simulate the typical OSB concrete abutments (height: 6.71 m and length: 25 m) by assuming masses proportional to deck dead loads (to include the contribution of structural weight). The transversal direction of the bridge was constrained with rigid elements with a sufficiently high stiffness to be considered infinite, but allowing us to reproduce the rotation of the deck about the vertical axis [41].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Scenario** & \(\mathbf{r_{1}}\) & \(\mathbf{r_{2}}\) \\ \hline n.1 & 0 & 1.0 \\ n.2 & 0 & 0.5 \\ n.3 & 0.5 & 0.5 \\ n.4 & 0.5 & 0.75 \\ n.5 & 0.5 & 1.0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Various scenarios.
# Re-Keying Scheme Revisited: Security Model and Instantiations
## 5 New Concrete Re-Keying Schemes
### Building Blocks  
[PERSON] et al. [8] introduced the concept of the tweakable block cipher and gave several schemes. One of the schemes, known as LRW1, calls the block cipher with a secret key \(k\) twice as inner components where the input of one block cipher is the XOR of the tweak and the output of the other block cipher. Its latency is about twice as one of the block cipher's. [PERSON] et al. proved that LRW1 is a pseudo-random permutation.  
The other scheme, LRW2, described in Figure 8, reduces the number of the block cipher operations by one. It, however, requires additional operation of a keyed hash function. The output of the hash function is XORed with both the input and output of the block cipher. If an encryption device computes the keyed hash function in advance and stores the output, its latency is half of LRW1's. [PERSON] et al. proved that LRW2 is a strong pseudo-random permutation, if \(h_{l}\) is chosen from the \(\delta_{h}\)-\(\mathsf{AXU}_{2}\) hash function family \(h_{L}\). Here, \(h_{L}\) is the \(\delta_{h}\)-\(\mathsf{AXU}_{2}\) (\(\delta_{h}\)-almost two-\(\mathsf{XOR}\)-universal [8]) hash function family if \(\Pr_{l}[h_{l}(x)\oplus h_{l}(y)=z]\leq\delta_{h}\) holds for all \(x,y\), and \(z\) such that \(x\
eq y\).  
Figure 7: Experiments for the re-keying scheme.  
[PERSON] et al. [6] followed the concept of \"separation of duties\" to propose two other re-keying schemes. Their first scheme is identical to [PERSON] et al.'s scheme, but the requirement of \(F\) is different. They added the one-wayness property (precisely, [PERSON] et al. divided \(F\) into two parts: the first and second parts are assumed to have SCA resistance and one-wayness, respectively) to \(F\) and proved its security in the ideal cipher model. Note that their first scheme avoids the attack to recover \(mk\) from \(tk\); however, it is possible to search for the session key \(tk\) by the birthday attack.  
Their second scheme, depicted in Figure 9, replaces BC with a tweakable block cipher to achieve the beyond birthday security. The birthday attack above succeeds because the re-keying function and the block cipher work independently, and adversaries are able to collect the input-output pairs of the block cipher and the re-keying scheme, step by step. Their second scheme, however, binds the re-keying function with the (tweakable) block cipher by inputting the randomness into the tweakable block cipher as a tweak. It makes it difficult for adversaries to collect the input-output pairs independently.
# Three-Dimensional Formation Control for Robot Swarms
## 4 Formation Controls
### Distributed Generating of a Spanning Tree  
Before tacking the above problem, we address how to form a spanning tree in a distributed fashion. We form a spanning tree \(T\) rooted at an AR \(u\) by applying a distributed breadth first search (BFS) algorithm in [32]. Ref. [32] presented a distributed algorithm, so that a node in the network can guide a moving object across the network to a designated  
Figure 1: The AR \(u_{i}\) maneuvers toward a frontierPt \(f(u_{i})\). and the path of \(u_{i}\) is plotted as yellow lines. Large dots on the path of \(u_{i}\) plot the ARs, which are positioned along the path of \(u_{i}\). On the senseSphere of \(u_{i}\), frontierPts are plotted with dots.  
goal. Algorithm 2 in [32] can be applied to make a spanning tree \(T\) rooted at \(u\). The spanning tree \(T\) is rooted at \(u\), and \(T\) has an unique path from an AR to any other AR.  
The goal sensor in Algorithm 2 of [32] represents the root, say \(u_{r}\), in this article. Each AR \(u\) stores and updates \(hops_{g}(u)\) (the hop distance to the root \(u_{r}\)). The root \(u_{r}\) initializes \(hops_{g}(u_{r})=0\). Every other AR initializes \(hops_{g}(u)=\infty\) where \(u\
eq u_{r}\).  
Initially, \(u_{r}\) broadcasts \(hops_{g}(u_{r})\) to all its neighbors. Suppose an AR \(u\) receives a hop distance message from its neighbor, say \(n\). In this case, \(u\) updates its hop distance information as  
\[hops_{g}(u)=min(hops_{g}(u),hops_{g}(n)+1). \tag{6}\]  
Under (6), \(hops_{g}(u)\) can be updated to \(hops_{g}(n)+1\). In this case, the parent of \(u\) is updated to \(n\). Thereafter, \(u\) broadcasts \(hops_{g}(u)\) to its neighbors. Refs. [32; 33] proved that the number of message broadcasts of each AR is 1 in this algorithm. This implies that the distributed BFS has the computational complexity \(O(1)\).
## 6 Implementation of Structural Reliability Assessment on the OWT Support Structure
### Constraints and Design Criteria
#### 6.1.5 Vibration Constraint  
One of the critical concerns for OWTs on jacket support structures is the resonance phenomenon. In order to guard against such a phenomenon, the first eigen-frequency \(f_{1 st}\) of the OWT support structure must be separated sufficiently from rotor induced frequencies \(f_{1P}\) and blade-passing frequency \(f_{3P}\)A soft-stiff structural design, whereby the modal frequency lies between the rotor upper bound \(f_{1P}\) (\(f_{1 PH}\)) and lower bound \(f_{3P}\) (\(f_{3 PL}\)) frequencies, is presently the most usual and cost-effective design for a jacket. Therefore, the resonance constraint should be expressed as follows [5; 24; 89]:  
\[f_{1 PH}\leq f_{1 st}\leq f_{3 PL}, \tag{33}\]  
\[0.133\leq f_{1 st}\leq 0.233. \tag{34}\]  
The limit state function for the resonance criterion at the rotor upper bound can, thus, be expressed as  
\[g_{r}(x)=f_{1 st}-f_{1 PH}. \tag{35}\]  
On the other hand, it is expressed at the rotor upper bound as follows:  
\[g_{r}(x)=f_{3 PL}-f_{1 st}. \tag{36}\]  
The lower \(g\)-function value is chosen to be applied in the reliability assessment.
# Laser Technology in Photonic Applications for Space
## 2 Laser Devices
### Fiber Lasers  
The development of fiber optics technology for telecommunications have resulted in new devices, including novel optical sources, which have also been beneficial for space applications. Some of the most interesting aspects for space applications include standard benefits, such as high power, cost, beam quality, and efficiency, but also more space-relevant improvements, such as unattended operation, compactness, low susceptibility to optical misalignment and contamination, thanks to their monolithic structure, low sensitivity to environment changes, and high reliability. Space-qualified pump and seed laser sources are also available for this technology. NASA has already demonstrated  
Figure 1: ExoMars DPPSS green laser designed for the European Space Agency (ESA)/Roscosmos Mars mission 2020.  
its relevance for remote sensing and laser altimeters, but other applications include LIDAR, metrology, telecommunications, and automated planetary rovers [20].  
In 2009, the first fiber laser was launched into space within the Fiber Sensor Demonstrator for ESA's Proba-2 satellite. One of the aims of this mission was to demonstrate the reliability of a full fiber-optic sensor network in space The device included a fiber laser that could sweep the wavelength range from 1520 to 1560 nm. The systematic monitoring of the demonstrator showed that seven years after the launch, the system was still working as expected [21].
# Research on Improved Bridge Surface Disease Detection Algorithm Based on YOLOv7-Tiny-DBB
## 4 Experimental Analysis and Validation
### Experimental Results and Analysis
#### 4.3.3 Visualization Effects of Bridge Diseases Detection Before and After  
Algorithm Improvement  
The detection of bridge defects is conducted by randomly selecting three images, with the results illustrated in Figure 13.  
As illustrated in Figure 13, the detection performance of the YOLOv7-Tiny-DBB algorithm (upper) and the YOLOv7-Tiny algorithm (lower) for bridge exposure diseases, ordinary crack damage, and minor crack damage is presented.  
Through comparison, it can be observed that the YOLOv7-Tiny algorithm exhibits omission phenomena in the detection of the exposed reinforcement and the fine crack diseases, as illustrated in Figure 13a,c, resulting in suboptimal detection performance. In contrast, the improved algorithm demonstrates a more accurate identification of various types of bridge diseases. Additionally, this enhanced algorithm feature reduces complexity  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Methodology**} & **DBB Module** & \multirow{2}{*}{**MPDIoU**} & **Parameter Quantity/M** & **GFLOPs** & **mAP (\%)** & **Time per Picture (ms)** & **FPS** \\ \hline
1 & \(\times\) & \(\times\) & 6.23 & 13.9 & 73.3 & 21.7 & 46.1 \\
2 & \(\surd\) & \(\times\) & 6.01 & 13.0 & 79.4 & 17.0 & 58.8 \\
3 & \(\surd\) & \(\surd\) & 6.01 & 13.0 & 80.6 & 16.9 & 59.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of the ablation experiment results.  
Figure 12: Comparison of the classification loss function curves between YOLOv7-Tiny and YOLOv7-Tiny-DBB algorithms.  
and strengthens regression prediction capabilities. Consequently, it has shown commendable detection performance on test samples, effectively identifying a greater number of subtle bridge ailments while minimizing instances of missed detections. Therefore, the improved algorithm proves to be an effective tool for detecting surface diseases in bridges.
# Anomaly Detection of CAN Bus Messages Using a Deep Neural Network for Autonomous Vehicles
## 3 Proposed Method
### The Triplet Loss Network
In our experiment, we sampled the training data so that in each mini-batch, about 45 CAN bus sequences are selected for each identity. In addition, randomly sampled negative data sequences are added to each mini-batch. Figure 4: Learning machine of triplet loss network. The triplet loss minimizes the distance between an anchor and a positive, both of which have a normal data sequence, and maximizes the distance between the anchor and a negative of an abnormal data sequence. Where \(f\left(x_{i}^{a}\right),f\left(x_{i}^{p}\right),f\left(x_{i}^{n}\right)\) are anchor data, positive data and negative data, respectively.
## 4 Results
### X-ray Powder Diffraction  
The XRD patterns of PP/PE, PP/PE/SCB, and PP/PE/SW blend composites are displayed in Figure 3, and Table 3 summarizes the crystallinity index and size. The PP/PE blend patterns consist of crystalline peaks at 14.38\({}^{\circ}\) (110), 17.29\({}^{\circ}\) (040), 18.96\({}^{\circ}\) (130), and 22.24\({}^{\circ}\) (041), which are typical crystal lattices of \(\alpha\) PP [29]. Furthermore, there are also peaks at 21.6 (110) and 23.4 (200), which correspond to orthorhombic PE lattices, and halo bump peaks at 26.01\({}^{\circ}\) and 29.09\({}^{\circ}\)[8; 22]. The introduction of both untreated fibers and cellulose generally reduced the intensities of crystalline peaks, except for PP/PE/SCB with 5% cellulose. This is normally attributed to swelling of the amorphous domain due to the defects created by the fiber [16; 17]. It is also evident that the introduction of cellulose fiber did not change the crystalline structure of the PP/PE blend. However, in the case of PP/PE/SCB cellulose 5%, it seems that whatever cellulose derivative formed has favored more of the crystal lattices of PP. These observations are verified by the crystalline sizes, which were shown to increase with disruption of crystalline lattices (Table 3). Moreover, the PP/PE/SW cellulose 5% and PP/PE/SCB cellulose 5% displayed the highest crystallite size and lowest crystallinity compared to their fiber counterparts. The reason might be due to an increase in PP/PE crystalline interplanar distance because of strong cellulose interaction, caused by a decrease in intermolecular hydrogen bonding, as discussed in the FTIR results.  
Figure 2: FTIR spectra of PP/PE, PP/PE/SCB, and PP/PE/SW blend composites.