esa-sceva/satcom-chunk-collection huggingface dataset:
# Substitution of Pork Fat with Beeswax-Structured Oleogels in Semi-Smoked Sausages
## 3 Results and Discussion
### Sensory Characteristics of Semi-Smoked Sausages  
The results of the sensory evaluation showed that the experimental samples OG7 and OG10 had an attractive appearance when sliced, with a homogeneous texture and a red-pink color without any gray spots, which was uniform throughout the volume of the sausages. The aroma was pleasant and characteristic of semi-smoked sausages, and the taste was also typical of semi-smoked sausages. The sensory analysis of the produced sausages showed that the addition of oleogel in the amount of 7% does not deteriorate the organoleptic properties. However, increasing the oleogel to 10% leads to a deterioration in texture and juiciness (\(p<0.05\)). The evaluation of the tasters of the overall appearance of the sausage and its cross-section showed the lowest scores for the sample with 10% oleogel. (Table 5).  
The changes in consistency and texture may be due to the interaction between the oleogel and the meat proteins, which can result in the formation of a more rigid protein matrix in the final product [65].  
According to the results of a sensory evaluation, the use of soybean oil deogels to replace pork fat in cured frankfurters did not have an effect on the aroma [56]. [PERSON] et al. (2016) found that replacing up to 20% of animal fat with phytosterol oleogels did not result in any differences in the acceptability of aroma or taste [57]. One potential interaction is the formation of an oil-protein complex, which can impact the gelation and emulsification properties of the meat batter. The formation of this complex can also affect the water-holding capacity of the meat, which may lead to changes in texture, juiciness, and tenderness [66; 67].  
The lower scores given by tasters for the overall appearance and cross-section of the sausage with 10% oleogel further support the idea that higher concentrations of oleogel can negatively affect the sensory properties of the sausage. This can be explained by the fact that the beeswax component of oleogel is a hydrophobic material that can reduce water-binding capacity, leading to a decrease in juiciness [68]. Monoglyceride is an emulsifier that can affect the fat distribution and homogeneity of the sausage matrix, potentially leading to a less desirable texture. Sunflower oil, on the other hand, is a liquid fat that may not be able to contribute to the formation of a stable matrix, especially at high concentrations [69]. Therefore, it is recommended to use oleogel in moderate amounts (up to 7%) to achieve the desired improvements in texture without compromising the overall quality of the sausage product.
# A Pilot-Based Integration Method of Ranging and LS Channel Estimation for OFDM Systems
## 1 Introduction
At present, using a single pseudorandom code for ranging is the most common method. The maximum fuzz-free distance measured by this method is proportional to the period of the pseudorandom code. Therefore, the period of the pseudorandom code will be relatively large when measuring distant targets, which means that it is impossible to quickly acquire and track the pseudorandom code [34]. In this paper, different short-period pseudorandom codes are utilized as pilots, and each pseudorandom code is combined into a composite code by using the characteristics of parallel data transmission in the OFDM system. The composite code has a longer period, which can measure a longer fuzz-free distance. Due to each pilot utilizing short-period pseudorandom code, the acquisition and tracking process will cost less time than traditional pseudorandom code. Moreover, the receiver can acquire and track each pilot when using these pilots to estimate the channel. According to the acquisition and tracking results of each pilot, the measured distance of the corresponding composite code can be ranged through the Chinese remainder theorem. In this way, the integration of ranging and communication can be realized under the original OFDM system framework. In this paper, the communication system paired with this pilot is designed. The paper verifies the feasibility of this design scheme through a simulation and analyzes the channel estimation and ranging performance when using the new pilot. The results show that the OFDM system combined with the ranging code maintains the original good communication performance and achieves the ranging. The rest of this paper is organized as follows. The system model will be described in Section 2. Section 3 describes the distance solving principles and methods. Section 4 gives the simulation result plots for model verification analysis. Finally, Section 5 concludes the paper.
# Surface Subsidence Monitoring in Kunming City with Time-Series InSAR and GNSS
## 3 Dataset and Processing
### SBAS-InSAR Data Processing  
Using ISCE + StaMPS software, SBAS-InSAR is used to process time series data. Firstly, in order to suppress spatio-temporal de-correlation images, the time baseline threshold is set as 150 d, and the spatial baseline threshold is set as 180 m. Based on the spatio-temporal baseline distance, images with the date 2 June 2018 is selected as the main image, and the remaining images are registered with the main image respectively as the slave image, to generate 92 pairs of differential interferometry pairs. Figure 3 shows the combination of the selected differential interferometry pairs. DEM is then used to remove terrain phase.  
In order to improve the monitoring accuracy of SBAS-InSAR technology, the error term of Equation (2) should be effectively estimated and removed. On this basis, the  
Figure 3: Time-position of Sentinel-1A image interferometric pairs. Blue line represents the interferometric pairs. The red points are the master and slave Synthetic Aperture Radar (SAR) images.  
Figure 2: SAR data coverage of the study area.  
linear relationship between the elevation error and the baseline is analyzed. On this basis, the linear relationship between the elevation error and the baseline was analyzed. 981,456 candidate points are obtained by setting the amplitude deviation index of the registered image. Combined with the noise characteristics of pixels, 205,336 PS points are finally selected and extracted. The distance and azimuth multivisual ratio is 4:1. The filtering method is Goldstein, and the unwrapping method is the Minimum Cost Flow based on Delaunay triangulation network. During this process, 82 interference pairs are retained for SBAS data after the interferogram with large unwrapping errors and orbit errors in the initial differential interference pair is removed. In the conventional InSAR analysis methods for temporal sequences, time high-pass filtering and space low-pass filtering are usually used to separate the atmospheric phase, but some scholars find that this spatio-temporal filtering method is carried out on the assumption that the atmospheric delay is not time dependent. Therefore, this paper proposes to use GACOS model to correct the atmosphere.  
The atmospheric correction delay is corrected using StaMPS SBAS from GACOS, which is based on the high resolution European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric numerical product of 0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\) grid [36]. In this paper, GACOS data corresponding to SAR images involved in unwrapping are obtained. The GACOS data corresponding to the main image is shown in Figure 4a. The atmospheric delay phase standard deviation STD is used as the atmospheric evaluation index. As shown in Figure 4b, it can be seen that the STD change rate after correction is significantly reduced by 76.8%, which indicates that GACOS has a certain effect on the correction of atmospheric delay.
## 1 Introduction  
Recently, smart cities have gained significant traction as urban areas embrace advanced technologies to improve efficiency, sustainability, and quality of life [1; 2]. To integrate diverse urban systems and improve the quality of services provided to residents, smart cities incorporate cutting-edge technologies such as the Internet of Things (IoT), big data analytics, and artificial intelligence [3; 4; 5; 6].  
UAVs offer unique advantages in smart-city environments, making them essential for a wide variety of programs. These flights offer actual-time surveillance and monitoring capabilities, permitting authorities to accumulate essential statistics from quite a few resources and locations wherein UAVs have verified benefits in range of scenarios from site visitor tracking to environmental evaluation and disaster response for public protection [7; 8]. The ability to navigate challenging terrain and far off areas with ease makes them priceless assets for growing situational focus and a rapid response time [9; 10; 11].
# Nearest Neighbours Graph Variational AutoEncoder
## 3 Results
### Ablation Study on Pooling  
We performed an ablation study to asses the impact of the pooling technique on the model's performance. The model was evaluated on the Water + Slab dataset using the reconstruction metrics discussed in Section 3.1. Five pooling techniques were considered:  
* ReNN-Pool: the one proposed in this work with only the simple node masking;
* ReNN Mean Pool: mean pooling on clusters defined by the masking operation of ReNN-Pool;
* ReNN Max Pool: max pooling on clusters defined by the masking operation of ReNN-Pool;
* Random Pool: dropping random nodes in the graph;
* Top-k Pool: defined in [22], dropping nodes on the base of features' alignment with a learnable vector.  
For the Random Pool and Top-k Pool, we fixed the ratios of the pooled nodes to be the same as the one of the ReNN-Pool. Such ratios are sequentially: 50%, 87% and 84%. After the node dropping, the adjacency matrix is updated from \(A\) to \(A^{2}\), connecting second order neighbours, as conducted in this work and recommended in [22], where the Top-k pooling was introduced. The un-pooling operations employ the same node masks and adjacency matrices of the pooling operations; thus, they are always symmetrical to them. The results of the ablation study are presented in Table 2, where it is demonstrated how the  
Figure 7: **Results on sprite dataset. (a) Comparison between input sprite images (first row) and reconstructed ones (second row). (b) Images generated fixing all the latent variables’ dimensions but one, which is varied. Generated sprites have fixed attributes but a continuously varying hair style.**architectures with the ReNN-Pool and Un-Pool operations outperform the other models. The results relative to the addition of mean and max operations are very likely related to the kind of data processed, which are smooth energy distributions in a cylinder. With such data, it is reasonable that the ReNN Mean Pool performs similarly to the simple ReNN-Pool and that adding the max operation leads to worse results.  
A plausible explanation of the better performances of ReNN-Pool-based techniques with respect to the Random and Top-k Pool relates to the connectivity of the graphs. ReNN-Pool is specifically designed for data to always be represented by a single connected graph. Indeed, after each pooling operation, the receptive field of the remaining nodes is enlarged but there is no loss of information due to the disconnected clusters of nodes. Conversely, with random pooling or Top-k pooling there is no guarantee that this will happen. Actually, in most cases, after such pooling operations, the graph structure breaks up in different unconnected clusters. That is particularly true when the graph exhibits only local connectivity.
# A Framework for Attribute-Based Access Control in Processing Big Data with Multiple Sensitivities
## 3 Results
### Analysis and Observations
#### 3.4.3 Verification of Security Software  
Software that provides security functionality should be subject to rigorous and independent evaluation. An example of this is the Common Criteria Evaluated Assurance Levels and Target Profiles of Protection, applied to operating systems to test their security services. Governments and businesses prefer the Red Hat version of Linux because of its independent certification ([[https://www.redhat.com/en/about/press-releases/red-hat-adds-common-criteria-certification-red-hat-enterprise-linux-8](https://www.redhat.com/en/about/press-releases/red-hat-adds-common-criteria-certification-red-hat-enterprise-linux-8)]([https://www.redhat.com/en/about/press-releases/red-hat-adds-common-criteria-certification-red-hat-enterprise-linux-8](https://www.redhat.com/en/about/press-releases/red-hat-adds-common-criteria-certification-red-hat-enterprise-linux-8)) accessed 14 January 2023).  
Independently writing security software and hooks to interface with critical security services, such as the Kerberos Key Distribution Center (KDC), can help circumvent this type of rigorous testing. Exposure to flawed error handling, buffer overflows, brute force attacks and poor audit logging are all areas that require independent verification [56].  
Veracode's State of Software Security Report found that more than three-quarters (75.2%) of applications have security flaws [57]. It is a large software manufacturer that did not include small glue code rapidly developed under business pressures to obtain investment in BDP.  
In the analysis, we noted several security issues in the software components. Many of the configuration files contained administrator passwords in clear text. Log files, which can contain sensitive information such as Kerberos service tickets, were stored in multiple potentially unprotected locations. 3 DES and R4 are the data encryption algorithms used in Apache Hadoop and are relatively weak [58]. Additional configuration is required to incorporate the AES. Rigorous security testing can help identify design flaws that can then be remedied.
# Silica Mesoporous Structures: Effective Nanocarriers in Drug Delivery and Nanocatalysts
## 5 Application of Silica Mesopores in Drug Delivery
### Ultrasound-Responsive Drug Delivery  
Ultrasound-responsive drug delivery belongs to the non-invasive stimulus category. Some studies have shown that ultrasound can induce chemical reactions, even to the point of being able to cleave some chemical bonds. [PERSON] et al., prepared an ultrasound-responsive system on a MSN surface that acted as a pore gatekeeper [215]. In this system, nanoparticles can be loaded with the drug at low temperatures. Their study showed that MSN could be released by remote stimuli, which is essential in drug delivery and cancer therapy.
## 3 Optimal Service Provisioning Framework
### Customized Mist-Edge-Cloud Framework
#### 3.1.2. Mist Layer  
Mist nodes operate at the edge of perception, adding lightweight analytics and decision-making capabilities to reduce data load and minimize latency. For example, if a patient's heart rate exceeds critical thresholds, the mist node can instantly trigger alerts to nearby healthcare staff without waiting for cloud-level processing. The mist layer is also mobility-aware and maintains continuous service flow even when patient devices move across network zones.
# Integrated GNSS/IMU-Gyrocompass with Rotating IMU. Development and Test Results
## 5 Results
### Results with Complete GNSS Signal Outage  
It would be also interesting to estimate how accurately the prototype GNSS/IMU gyrocompass after complete loss of satellite signals.  
There were no complete satellite signal outages during the car test, so it was decided to use data obtained at the previous point with forced removal of all satellite signals from processing starting from 2001 s. The following operation mode was used. GNSS/IMU gyrocompass was started using phase measurements (12) of a single effective GLONASS satellite and measurements (10), (11) of the whole observable satellite constellation. The whole state vector (8) including FOG biases and rhumb drifts was estimated for 2000 s. Further all satellite signals were forcedly removed from processing, and INS was corrected by additional external linear velocity measurements. The altitude during the motion was considered identically zero, which is acceptable for automobile conditions. In this case the state vector (19) was estimated by measurements (20). But the accuracy of estimating FOG bias and rhumb drift in this case is much lower than when using measurements (10), (11).  
Figure 16 presents heading, roll and pitch errors. The experimental results demonstrate that with no satellite signals the maximum heading error does not exceed 3\({}^{\circ}\) for 1.5 h after signal outage. Maximum roll and pitch errors did not exceed 0.2\({}^{\circ}\), which is typical for all conditions of car test. These errors are given without account for synchronization errors between GNSS/IMU gyrocompass prototype and reference INS, which critically degrade the attitude error during the maneuvers (shown by ovals in Figure 16b). Figure 16c present the heading error after signal outage between two vehicle manoeuvres.  
Figure 16: Attitude error of GNSS/IMU gyrocompass with satellite signals completely removed from processing starting from 2000 s: (**a**) Heading error; (**b**) Roll and pitch errors; (**c**) The heading error histogram.
## 1 Introduction
### Notational Conventions  
The entries of a matrix \(\mathbf{X}\) and a (column) vector \(\mathbf{x}\) are denoted by \(X_{ij}\) and \(x_{i}\), respectively. Sets are represented by calligraphic capital letters and \(\mathbb{R}_{+}\) denotes the non-negative real numbers. The notation \(T\) stands for matrix or vector transposition; \(\mathbf{0}\) and \(\mathbf{1}\) refer to the all-zero and all-one vectors; while \(\mathbf{I}_{N}\) denotes the \(N\times N\) identity matrix. For a vector \(\mathbf{x}\), \(\operatorname{diag}(\mathbf{x})\) is a diagonal matrix whose \(i\)th diagonal entry is \(x_{i}\). The operators \(\otimes,\,\odot,\,\circ\), and \(\operatorname{vec}(\cdot)\) stand for Kronecker product, Khatri-Rao (columnwise Kronecker) product, Hadamard (entrywise) product and matrix vectorization, respectively. The spectral radius of matrix \(\mathbf{X}\) is denoted by \(\lambda_{\max}(\mathbf{X})\) and \(\|\mathbf{X}\|_{p}\) stands for the \(\ell_{p}\) norm of \(\operatorname{vec}(\mathbf{X})\). Lastly, for a function \(f\), denote \(\|f\|_{\infty}=\sup_{\mathbf{X}}|f(\mathbf{X})|\).
# Policy-Based Composition and Embedding of Extended Virtual Networks and SFCs for IIoT
## 4 Methodology
### Transformations
#### 4.1.5 Bandwidth  
Adding VNos, VLis, and VNFs to the EVN requires the adaptation of the resource requirements. For example, adding a VNo that represents a certain device requires adapting the bandwidth demand of the new and original VLis based on the parameters of the data resource of the device. Subsequently, all of the next VLis shall be updated, including these inside the FG. This approach can be applied to feed-forward VNs, which we use in defining our exemplary ARs.  
We consider two types of VNos, VNos that have no incoming edges and intermediate VNos that have incoming edges. For each VNo that has no incoming edges, its produced load per interval, if exists, is used in order to calculate the required bandwidth that is assigned to all of its outgoing edges.  
\[\begin{split} P:\{e^{ij}_{AR}|e^{ij}_{AR}.bandwidthDemand=0 \wedge n^{i}_{AR}.inEdges=0\}\\ T(SN,AR):\{e^{ij}_{AR}.bandwidthDemand=n^{i}_{AR}.dataDemand.size /n^{i}_{AR}.dataDemand.cycle\}\end{split} \tag{7}\]  
For intermediate VNos that have incoming edges, we sum the required bandwidth of all incoming edges and set it as demanded bandwidth for all outgoing edges. If the VNo has the property of multiplier, then it is considered during the calculation for the outgoing bandwidth demand. In our work we define a specific bandwidth multiplier for each specific VNF type as a property. The default value is 1.  
\[\begin{split} P:\{e^{ij}_{AR}|e^{ij}_{AR}.bandwidthDemand=0 \wedge\exists e\in n^{i}_{AR}.inEdges:e.bandwidthDemand\
eq 0\}\\ T(SN,AR):\{e^{ij}_{AR}.bandwidthDemand=\\ \sum_{k=0}^{n^{i}_{AR}.inEdges}(e^{ki}_{AR}.bandwidthDemand\times n ^{i}_{AR}.bandwidthMultiplier)\}\end{split} \tag{8}\]
# Fault-Tolerant Tripod Gait Planning and Verification of a Hexopod Robot
## 3 Planning Method of F-TT Gait  
### Analysis of Support Polygon  
In the practical application of a hexapod robot, leg failure could be caused by the failure of a driving device or power transmission equipment, or by impact. The relationship between the relative position of the fault leg and the fault tolerance of the hexapod robot is analyzed using the support triangle in the tripod gait, which is the design principle to determine the relative position of the support leg in the fault tolerance walking process of the hexapod robot. Figure 3 shows all six possible support triangles for a hexapod robot.  
In the case of Figure 3a,b, the COG is outside the support triangle, the stability margin value is negative, and the hexapod cannot maintain stability; in Figure 3c, the support triangle is composed of three legs separated one by one, and the COG is at the center of the triangle with the best stability, which is expected for support as much as possible. In Figure 3d-f, the support triangles pass through the COG, which is a critical state. However, the stability margin can be increased by stability improvement measures, so these support triangles are reasonable.
###### Abstract  
The treatment of sulfate-bearing soil with calcium-based stabilizers such as cement or lime often results in ettringite formation, consequently leading to swelling and strength deterioration. Ettringite formation has negative environmental and economic effects on various civil engineering structures. This study was conducted to investigate the use of different materials (nano-magnesium oxide (M), ground granulated blast-furnace slag (GGBS), and rice husk ash (RHA)) for gypyeous soil stabilization to prevent ettringite formation. Various tests were performed, including flexural strength, unconfined compression strength, linear expansion, and microstructure analysis (SEM/EDX), on lime (L)-, (M)-, (M-RHA), (M-GGBS)-, and (M-GGBS-RHA)-stabilized gypyeous soil samples to determine their properties. The results indicated that the swelling rates of the soil samples mixed with 20% M-RHA, M-GGBS, and M-GGBS-RHA binders were much lower (less than 0.01% of volume change) than those of the soil samples mixed with 10% and 20% lime-stabilized binders after a curing period of 90 days. Meanwhile, the strengths of the soil samples mixed with 20% of M-RHA, M-GGBS, and M-GGBS-RHA soil specimens after soaking of 90 days were obviously higher (with a range from 2.7-12.8 MPa) than those of the soil samples mixed with 20% of lime-stabilized binder. The SEM and EDX results showed no ettringite formation in the M-RHA-, M-GGBS-, and M-GGBS-RHA-stabilized soils. Overall, the test results proved the potential of M-RHA, M-GGBS, and M-GGBS-RHA as effective soil stabilizers.  
s +
Footnote †: journal: Applied Sciences