esa-sceva/satcom-chunk-collection huggingface dataset:
# Computational Load Analysis of a Galileo OSNMA-Read Receiver for ARM-Based Embedded Platforms +
## 6 Conclusions  
This paper presents the software profiling analysis of the OSNMA functions implemented in a real-time GNSS software receiver targeted for ARM-based embedded platforms. This analysis has been performed for three different embedded platforms, and a standard PC has been used as a reference.  
The first step of the analysis is about the computational burden of the basic OSNMA functionalities (TESLA key verification, MAC verification, MACSEQ verification, digital signature verification, public key verification). The execution times measured for the embedded platforms show a performance degradation that ranges from 4 to 21 with respect to the execution time recorded on the PC. The functionality that exhibits the worst degradation is the digital signature verification, whose complexity increases with the EC order, except for the P256 curve, which shows the best performance, likely due to a low-level implementation optimization of the used cryptographic library function.  
The second step of the analysis is the assessment of the compatibility of the Galileo OSNMA implementation on ARM-embedded boards with the real time elaboration of the GNSS signal: a complete profiling has been executed, including all the steps of the GNSS signal elaboration (e.g., acquisition, tracking, PVT computation).  
All the reported results demonstrate that the OSNMA support does not impair the real-time capability of the ARM-based implementation, especially when the most recent platforms are considered. At the same time, the need for an optimized scheduling of the multi-thread architecture of the receiver has been demonstrated by the real-time tests, which have been strongly affected by the different operating systems of the considered platforms.  
[PERSON] is the principal developer of the ARM-based software application, and performed the porting from the PC to the embedded platforms and the testing phase; [PERSON] is the principal developer of the PC-based software application and supervised the porting and testing phases; [PERSON] guided and coordinated the entirety of the team's work. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available in this published article.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 10: Time evolution of the CPU usage on the four platforms (**a**) and real-time capability of eNGene receiver on the three embedded platforms (**b**) for 16 satellites, i.e., 6 GPS and 6 Galileo, simultaneously tracked.
## 4 LEO Satellite Mega-Constellation Network Caching Policy
### Caching Policy Based on RF
: _The cache viscosity is given by:_  
\[CV=RP\times\log\frac{\mathbb{N}}{\mathbb{M}}, \tag{14}\]  
_where \(\overline{\mathbb{M}}\) represents how many satellite nodes cache content \(c\), \(RP=CT/\sum_{c=1}^{L}CN_{c}\) is the caching response rate, \(CT\) represents response time to cached content \(c\) in the current satellite node \(i\) within unit time according to the CS table, and \(\sum_{c=1}^{L}CN_{c}\) counts the total number of requests to all cached contents in the satellite node \(i\)._  
Using the cache viscosity, the cache matching rule is given by:  
Matching rule: The matching relationship between cached content and satellite nodes is given by calculating the cache viscosity. The higher the viscosity value of the cache, the greater the matching relationship between the satellite nodes and the content, and the satellite nodes are more suited to the content. The threshold value of a matching relationship is given by \(\varepsilon\); if the cache viscosity \(CV\geq\varepsilon\), this means there is a good match with the content \(c\) on the satellite node \(i\), and content \(c\) is suited to be cached in the satellite node \(i\), then \(s(i,t)=1\); otherwise, \(s(i,t)=0\). The matching rule guides the deployment of caches. Especially, the content is cached in advance at the future satellite to maintain communication with the current ground segment at the time of satellite switchover. The caching Algorithm 1 flow diagram is shown in Figure 10.  
The cache policy CARF overall process is as follows. Figure 10: Caching algorithm flow diagram.
# AAGA: A Priori Adaptive Splitting Algorithm for the Split Delivery Vehicle Routing Problem
## 2 Problem Definition and the Proposed Solution
### A Priori Adaptive Splitting Algorithm (AASA)
#### 2.3.2 AASA Algorithm
```
0:\(G=(V,E),Q,\vec{dist},\vec{D},p\)
0:\(G^{\prime}=(V^{\prime},E^{\prime})\)
1: Initialize \(L,d\gets gcd(Q,\vec{D})\), \(\mu\gets avg(\vec{D}/d),s_{max}\leftarrow[log_{p}^{\mu}]\)
2:for\(i:1..L\)
3:\(\vec{s}_{i}\leftarrow d*(exp_{p}\{0..s_{max}-i+1\})\)
4:endfor
5:\(l\vec{abel}=clustering(V)\)\(\triangleright\)\(l\vec{abel}(v)\in\{1,...,L\}\)
6:repeat
7:\(V=V\setminus\{v\}\)
8:\(i\gets l\vec{abel}(v)\)
9:\(V^{\prime}=V^{\prime}\cup split(v,\vec{s_{i}})\)
10:until\(V=\emptyset\)
11:return\(G^{\prime}=(V^{\prime},E^{\prime})\)
```  
**Algorithm 1** A priori Adaptive Splitting Algorithm (\(AASA\))  
The algorithm takes into account \(L\) different levels for the distance-based clustering as provided in (5). Then, for each level \(i\), the splitting rule \(\vec{s}_{i}\) is determined using the value \(s_{max}\). Next, the clustering of the customers is made according to Equation (5). The _split_ function substitutes each node (customer) of the graph \(G\) with new customers according to the rule \(\vec{s}_{i}\) to gradually form the graph \(G^{\prime}\). Note that the splitting rule ensures that the demands further away from the depot are split with coarser rules. Once the graph \(G^{\prime}\) is completed, the CVRP solver will solve the generated new problem. We experimented with different values of the prime number \(p\) and observed that \(p=2\) has the best performance overall in the current version of AASA. For example, consider the instance \(SD6\) from SET-1 as shown in Figure 2. We will have \(d=gcd(\vec{D},Q)\), i.e., \(d=gcd(60,90,10)=10\). The simple distance-based clustering in Equation (5) with \(L=2\) results in two levels, where \(l=1\) covers the customers that are furthest from the depot and \(l=2\) covers the customers that are closest to the depot. We  
Figure 3: AASA framework. will have \(\mu=7.5\) and \(s_{max}=3\). Therefore, for the first level, we have \(\vec{s_{1}}=\{10,20,40,80\}\) and for \(\vec{s_{2}}=\{10,20,40\}\). VRPH solver: Once the a priori splitting rule is applied to an SDVRP problem, any commercial solver can be used to solve the resulting CVRP instance. In this paper, we use the VRPH solver to solve CVRP instances. VRPH is a publicly available solver with a provable record of generating high-quality solutions. It takes as input a CVRP instance written to a file with a format similar to that of the Traveling Salesman Problem Library (TSPLIB) files and prints the solution to an output file. VRPH implements an open-source library of several local search heuristics for generating and improving feasible solutions to the CVRP instances. We refer the reader to [35] for a detailed description of the heuristics and the modular structure of the VRPH software. In this paper, we use VRPH as a standalone solver with the parameters set at their default values.
# An Efficient Approach for LBS Privacy Preservation in Mobile Social Networks
## 3 Preliminaries
### The Relationship of \(k\) and \(l\)  
As we all know, k-anonymity and l-diversity are classical techniques used to protect privacy in LBS. Many studies and privacy approaches were proposed based on k-anonymity and l-diversity in sporadic privacy protection. The combination of k-anonymity and l-diversity is to ensure that \(k\) users request at least \(l\) services in a clustering process of LBS query, which is shown as Figure 5. But the relationships between \(k\) and \(l\) are needed to be rigorously explored.  
**Theorem 1**.: _In a clustering process, the number of diversity is not more than the number of anonymity: \(l\leq k\)._  
Proof of Theorem 1.: In sporadic privacy protection, with the premise that one user sends one kind of service category in a clustering process. As shown in Figure 5. One user corresponds to one kind of service category, and some users may have the same kind of service category. Therefore, the number of diversity is not more than the number of anonymity (i.e., the number of users) in a clustering group.  
**Theorem 2**.: _In a clustering process, k-anonymity is easier to be satisfied than l-diversity._  
Proof of Theorem 2.: In sporadic privacy protection, with the premise that one user sends one kind of service category in a clustering process. Under the system architecture of TTP-free, assume that there already has a clustering group which does not yet achieve the conditions of clustering success (i.e., \(k<th_{k}\) and \(l<th_{l}\)). The condition \(th_{k}\) is easier to be satisfied than the condition \(th_{l}\), the reason is that finding a new user is easier than finding a new user who must be with a different kind of service category (i.e., different \(l\)) from that clustering group.  
**Theorem 3**.: _Under the same condition \(th_{k}\), bigger \(th_{l}\) can provide better protection in LBS query._  
Proof of Theorem 3.: By comparing Figures 5 and 6, we can see that the condition \(th_{k}\) is both 5, the condition \(th_{l}\) of Figure 5 is 3, and the condition \(th_{l}\) of Figure 6 is 4. Assume that the kinds of service category \(l_{a},l_{b},l_{c}\) are the same in Figures 5 and 6, if an attacker owns some background knowledge, and he can ensure [PERSON] absolutely not request \(l_{a}\) and \(l_{b}\). Then the attacker may deduce which is [PERSON] from Figure 5 by using his background knowledge. But under the same setting, he cannot ensure which is [PERSON] from Figure 6.  
Figure 4: A random sum of \(L_{i}\) when \(L=7\).
## 4 Analysis
### Security Analysis
#### 4.1.2 Sybil Attack  
In a Sybil attack, a single node presents multiple identities to other nodes in the network. It is only reasonable to expect a node to accept but a single set of coordinates from each of its neighbors, but by using the Sybil attack an adversary can be in more than one place at once.  
The prerequisite for a node to pass authentication is to own a legitimate location-based private key. Location-based key management for mobile networks is implemented to mitigate a Sybil attack. With our scheme in place, when a malicious node intends to impersonate a legitimate node, it does not have the authentic LBK and, thus, cannot successfully finish mutual authentication with other legitimate nodes. For the same reason, a malicious node cannot claim forged IDs and/or locations without being detected. Therefore, the Sybil attack is effectively defeated.
## 3 A Prototype System for Pedestrian Positioning
### Electronic Module  
The built electronic module, see Figure 2, is a dedicated PCB with a microcontroller, 6 DOF sensor and GPS receiver. The microcontroller reads out data from the 6 DOF sensor, ADIS16355 at a rate of 820 Hz. Downsampling is carried out to limit data stream to the PC. An 8 th order, lowpass Chebyshev filter is used to avoid aliasing. Samples are sent to the computer at a rate of 205 Hz. The module sends data through the USB interface.
## 7 Conclusions  
In an urban environment, the distribution density and position of complex scatterers at different heights are different. This causes differences in channel characteristics. In the face of the complex and changeable channel characteristics of the urban environment, the errors caused by using a single channel have brought huge challenges to the reliability of data transmission. In the urban emergency management, in order to reduce the attenuation, interference, loss, distortion and packet loss of data during the transmission process, a more accurate adaptive SUUL-SULA channel model is established in this paper. The channel is divided into two parts according to height: ultra-low altitude (0\(\sim\)100 m) and low altitude (100\(\sim\)1000 m). First of all, in the ultra-low altitude, the distribution density of obstructions such as buildings and trees is relatively high. Due to the influence of these complex scatterers, large-scale fading and small-scale fading make the signal experience a lot of loss and attenuation on different transmission paths. Therefore, based on the LOO model, the SUUL model proposed in this paper assumes that the LOS component obeys the lognormal distribution, and the multipath component obeys the Rayleigh distribution. Under this condition, the probability density function and bit error rate of the received signal are derived. Secondly, in the low-altitude environment, as the UAV's flight altitude increases, the influence of shadow fading on the channel gradually weakens. At this time, the Doppler frequency shift caused by the flying speed of the UAV has a major impact on the signal attenuation. A SULA channel model is proposed based on the Jakes' model. The uniform circular array beamforming technology is adopted to design the Doppler frequency shift compensation algorithm. Finally, the experimental results show that the  
Figure 11: Relationship between BER and normalized Doppler frequency.  
SUUL-SULA channel has a good improvement in BER performance and system stability, which improves the reliability of the UAV communication.  
Methodology, software and writing--original draft preparation, [PERSON]; formal analysis, [PERSON] and [PERSON]; writing--review and editing, [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON]; resources and project administration, [PERSON]; supervision, [PERSON], [PERSON], [PERSON] and [PERSON] All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (61771186), Outstanding Youth Project of Provincial Natural Science Foundation of China in 2020 (YQ2020F012) and Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province (UNPYST-2017125).  
The authors declare no conflict of interest.
## 2 Materials and Methods  
### Measurement Setups  
The measurements were performed using steady-state and lifetime fluorimeters:  
(a) Fluorimeter FS 900 (Edinburgh Instr., Livingston, Scotland) allowing the measurement of excitation-emission matrices (EX-EMs);  
(b) EasyLife System (Photon Technology International, Birmingham, NJ, USA) with LED excitation of 280, 340, and 460 nm for fluorescence measurements of suspensions and solid particles (Figure 1). Fluorescence excitation was performed using nanosecond pulse LEDs.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Compound** & **EX [nm]** & **Em [nm]** & **Lifetime [ns]** & **Reference** \\ \hline Phe & 257–260 & 282 & 6.4\(-\)6.8 & [33; 34] \\ \hline Tyr & 274\(-\)275 & 303\(-\)304 & 3.6 & [33; 34] \\ \hline Trp & 280\(-\)295 & 348\(-\)353 & 3.1 & [33; 34] \\ \hline NADH & 346 & 457 & 0.48 & [33; 37; 38; 39; 40] \\ \hline FAD & 450 & 520 & 2.3\(-\)2.9 & [40] \\ \hline Riboflavin & 370, 450 & 518 & 5.06 & [20; 41; 47] \\ \hline \multirow{2}{*}{Folic acid} & \multirow{2}{*}{361} & \multirow{2}{*}{442} & \(\begin{array}{c}\text{t}_{1}=1.6\ (12\%)\\ \text{t}_{2}=4.78\ (88\%)\end{array}\) & [42] \\ \hline FMN & 451 & 520 & 4.66 & [40; 43] \\ \hline \multirow{2}{*}{B-Carotene} & \multirow{2}{*}{471, 498} & \multirow{2}{*}{568} & \(\begin{array}{c}\text{t}_{1}=0.16\ (75\%)\\ \text{t}_{2}=1.07\ (25\%)\end{array}\) & [44; 46] \\ \hline \hline Pterine & 353 & 440\(-\)450 & 5.0\(-\)7.6 & [45] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Lifetimes of biological fluorophores [33; 34; 37; 38; 37; 39; 47].
# New Insights into the Neuromyogenic Spectrum of a Gain of Function Mutation in SPTLC1
## 3 Results
### Transcript Findings in Quadriceps Muscle Derived from the p.(A205)-Sptlcc1-Patient  
To follow up on inflammatory processes in muscle suggested by our immunohistochemistry findings, we next investigated expression of transcripts that encode for markers expressed by antigen presenting cells, or markers known to either activate macrophages or be expressed by these cells. We identified increased expression of MRC1, TGFB, STAT1, STAT2, and IL1B in the patient muscle compared to NDCs by 3 to 29-fold (Table 2). A considerable increase of HLA-DRA (254-fold) and HLA-DPB (183-fold) was detected, while expression of HLA-DOB or HLA-DRB could not be detected (n.d.) at all (Table 2).  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**HLA-DRA** & **HLA-DPB1** & **HLA-DOB** & **HLA-DRB** & **TGFB** & **STAT1** & **STAT2** & **IL1B** & **MRC1 (CD206)** \\ \hline
254\(\times\) & 183\(\times\) & n.d. & n.d. & 28\(\times\) & 7\(\times\) & 29\(\times\) & 27\(\times\) & 3\(\times\) \\ \hline \end{tabular}
\end{table}
Table 2: Transcript expression in the p.(A205)-SPTLC1-patient derived quadriceps muscle.  
Figure 5: Immunofluorescence studies focusing on phosphor-FAK1 (pFAK) in quadriceps muscle biopsies derived from the p.(A205)-SPTLC1-patient and a control: phospho-FAK1 is expressed in the sub-sarcolemmal region of muscle fibers derived from the healthy control, whereas in the biopsy derived from the patient, phospho-FAK1 is upregulated in perimysial areas and in immune cells.  
To further study SPTLC1 expression, RNA extracted from immortalized lymphocytes, derived from the patient and healthy controls, was analyzed. Our studies revealed similar expression of SPTLC1 transcripts in the patient compared to controls (Figure 6A) but decreased level of expression of the wildtype transcript containing exon 2 (Figure 6B). In line with this, nanopore sequencing of the SPTLC1 cDNA demonstrated a reduced coverage for the whole exon 2 (Figure 6C) and an additional drop in coverage for the first 28 bases of exon 2 (Figure 6D), indicating the expression of three distinct transcripts in the patient cells (Figure 6E).
## 2 Materials and Methods  
### Fengyun-4 Meteorological Satellite and Its CLM Products  
Fengyun-4A (FY-4A for short) is the latest generation of GEO meteorological satellite in China. It was successfully launched from Xichang Satellite Launch Center on 11 December 2016. FY-4A realizes the combination of GEO observation and infrared hyperspectral atmospheric vertical detection. It takes only 1 min to perform special area scanning, which greatly improves the temporal as well as spatial resolution of earth observation. The sensors loaded on FY-4A satellite mainly include Advanced Geosynchronous Radiation Imager (AGRI), Geosynchronous Interferometric Infrared Sounder (GIIRS), Lightning Mapping Imager (LMI), etc. [28]. With high temporal and spectral resolution, FY-4A satellite can realize all day long multi-dimensional remote sensing monitoring [29]. FY-4A satellite provides a large amount of level 2 product data, mainly including atmospheric vertical detection, real-time cloud detection, cloud types, and other various types of product, which can provide fast and effective data support for agriculture, forestry, industry, transportation, and other fields [30].  
The FY-4A satellite ARGI has a wide range of meteorological products, and CLM products are one of the important products. The FY-4A CLM are produced mainly using 6 spectral bands of the ARGI, including 0.65 \(\upmu\)m, 3.75 \(\upmu\)m, 7.1 \(\upmu\)m, 10.8 \(\upmu\)m, and 12.0 \(\upmu\)m bands. At the same time, a variety of supplementary data sources are combined to distinguish between clouds and clear sky by using the different features exhibited in each spectral bands [28; 31]. The CLM product, with a 4 km spatial resolution, contains the value of the full-disk with a grid size of 2748 \(\times\) 2748 pixels, and the digital number '0' for cloud, '1' for possible cloud, '2' for possible clear sky, '3'for clear sky, '126' for blank, and '127' for invalid fill. A binary image of CLM is shown as Figure 1.  
The satellite data used in this study are obtained from the official data website of the National Meteorological Satellite Center. The selected data used is the L2 CLM product data from the FY-4A with 4 km resolution. The time range is from '00:00:00 1 March 2021' to '00:00:00 2 March 2021'. It is worth noting that we assume that cloud detection is done onboard with mature machine learning based algorithms and special processing chips.  
Figure 1: A binary image of FY-4A CLM.
# Deep Learning for Neuromuscular Control of Vocal Source for Voice Production
## 2 Materials and Methods
### LeTalker
#### 2.2.2 Subglottal and Supraglottal Airway  
The airway was modeled as a series of cylindrical sections. As the focus of the current study was on the neuromuscular control of the vocal source, the airway was kept constant without any articulation. The subglottal airway was modeled after MRI measurements [32] and consisted of 32 cylindrical sections. An /o/ vowel shape with 44 cylindrical sections was used for the supraglottal airway [33]. Each subglottal and supraglottal section was 0.3968 cm long [34], half the distance the sound travels in 1/44,100 s. The area function values for both subglottal and supraglottal airways were given in [35]. Attenuation factors were used to model the airway losses [29]. The choice of the section length allowed the computation of forward and backward traveling waves at section boundaries [34]. Radiation impedance was modeled by an inertance (L) and resistance (R) in parallel as in [36].
# Graph-Based Modeling in Shop Scheduling Problems: Review and Extensions
###### Abstract  
Graphs are powerful tools to model manufacturing systems and scheduling problems. The complexity of these systems and their scheduling problems has been substantially increased by the ongoing technological development. Thus, it is essential to generate sustainable graph-based modeling approaches to deal with these excessive complexities. Graphs employ nodes and edges to represent the relationships between jobs, machines, operations, etc. Despite the significant volume of publications applying graphs to shop scheduling problems, the literature lacks a comprehensive survey study. We proposed the first comprehensive review paper which (1) systematically studies the overview and the perspective of this field, (2) highlights the gaps and potential hotspots of the literature, and (3) suggests future research directions towards sustainable graphs modeling the new intelligent/complex systems. We carefully examined 143 peer-reviewed journal papers published from 2015 to 2020. About 70% of our dataset were published in top-ranked journals which confirms the validity of our data and can imply the importance of this field. After discussing our generic data collection methodology, we proposed categorizations over the properties of the scheduling problems and their solutions. Then, we discussed our novel categorization over the variety of graphs modeling scheduling problems. Finally, as the most important contribution, we generated a creative graph-based model from scratch to represent the gaps and hotspots of the literature accompanied with statistical analysis on our dataset. Our analysis showed a significant attention towards job shop systems (56%) and Un/Directed Graphs (52%) where edges can be either directed, or undirected, or both, Whereas 14% of our dataset applied only Undirected Graphs and 11% targeted hybrid systems, e.g., mixed shop, flexible, and cellular manufacturing systems, which shows potential future research directions.  
graph theory; shop scheduling problem; modeling; manufacturing systems; a systematic review and categorization methodology +
Footnote †: journal: Applied Sciences