esa-sceva/satcom-chunk-collection huggingface dataset:
# Distributed Software Build Assurance for Software Supply Chain Integrity
## 2 Software Supply Chain Background  
**Generic Software Supply Chain Paths:** The software supply chain starts with the developer who stores and shares the source code (s) in a repository. The source code, along with the dependencies, will then be used in the build process involving compiling the source code into machine-readable code. The build/compilation process outputs the software build (\(b\)) and the documentation (\(d\)).  
There are two popular paths to download and build software. First, the user can download the source code and the dependencies from the source code repository and the dependencies repositories, respectively, and then build/compile the software themself. Second, a distribution platform can facilitate the download by providing the pre-build packages to the user. The user then compiles and builds the software from those packages.  
Our work focuses on these two paths as they are the most typical paths for software download/build.  
**SBOM and Reproducible Build:** More recent software download and build processes involve reproducible build for \(b\) and the software bill of materials (SBOM) for \(d\). SBOM is mandated for the software for commerce and generates a record and documentation of the software supply chain components to enable transparency, accountability, and tracking of the software development process. Reproducible build, also known as deterministic verifiable build, provides an identical build output given the source code and the build condition to detect a compromise in the compiler or in the build condition. Major open-source software projects, such as Debian for Linux distribution, Tor for anonymous routing, and cryptocurrency blockchain (including Bitcoin Core and Ethereum), support reproducible build; we discuss the relevant recent research in Section 7.2. We also describe the concrete implementation of SBOM using Syft and reproducible build for Ethereum Archanes in greater detail in Section 5.
###### Abstract  
This study aimed to improve the hydrophobicity of cellulose nanofibril (CNF) films using a natural wax coating. For this purpose, firstly, the selection, extraction and characterization of a natural wax and fatty acids were carried out. These compounds were extracted from the aerial part of the _Halimium viscosum_ plant. The chromatogram resulting from the chemical analysis of the extract revealed the presence of 15 compounds, with nonacosane being the major compound present. For film production, two different chemical pulps gels (sulfite and sulfate) were first characterized in terms of solids content, rheology and Fourier transform infrared spectroscopy (FTIR). The CNF films were produced by the solvent casting method, coated on one side with the extracted wax and subsequently characterized by wettability, surface energy, differential scanning calorimetry (DSC), FTIR, structural properties and water vapor permeability. The results showed that the wax-coated films exhibited a significant increase in water resistance, with a water contact angle exceeding 100\({}^{\circ}\), demonstrating improved hydrophobicity. Also, the water vapor transmission rate (WVTR) of the films was drastically reduced after wax coating. Furthermore, the coated films maintained good transparency, making them a viable alternative to synthetic plastic. This study highlights the potential of natural wax coatings to improve the moisture barrier properties of biodegradable CNF films, promoting their application in sustainable packaging solutions.  
cellulose nanofibrils; natural wax; hydrophobicity; biodegradable films; coating +
Footnote †: journal: Applied sciences  
0000-0001-5000-5000][PERSON]
# Distributed MIMO Measurements for Integrated Communication and Sensing in an Industrial Environment
## 6 Analysis and Discussion
### Local Scattering Function
Considering the maximum speed of the mobile robot \(v=1\,\mathrm{m}/\mathrm{s}\), the stationarity region becomes approximately \(4.5\) wavelengths. As mentioned above, we choose \(N=N_{\text{f}}\), assuming that the stationarity bandwidth is \(35\,\mathrm{MHz}\) since the relative bandwidth is less than \(1\%\). Figure 9: Using MRT, we clearly see a channel hardening effect where the deep fading dips are canceled. Here, all links are depicted using the average power of all subcarriers.
## 2 Electrical Resistivity/Impedance Measurement: Is It Really that Simple?
### Stress and Strain
[215] designed a self-sensing pavement (embedded with smart cement-based sensors, realized with the addition of nickel powders enhancing self-sensing capability--[216]) for traffic detection and monitoring. They proposed an FCR equal to approximately 18% with a compressive strength of 0.5 MPa (caused by a small vehicle of approximately 1000 kg on an area of the four tires of approximately 20000 mm\({}^{2}\)), thus obtaining a reversible and sensitive response in terms of electrical resistivity. [PERSON] and [PERSON] [52] studied contact electrical resistance under dynamic loading in two overlapped mortar strips; they observed an irreversible increase in electrical resistivity at a stress amplitude of 15 MPa, probably because of the production of severe debris. The inclusion of steel fibers decreases the noise present in FCR data [122]. Contrarily, [PERSON] et al. [122] noticed that FCR cannot predict the compressive behavior of ultra-high-performance concretes containing CNTs, probably because the external load changes the conductive paths only slightly, due to their dense microstructure, whereas it can simulate quite well the tensile behavior (in terms of stress-strain and stress-crack opening displacement). A non-linear relationship between stress and FCR and a linear relationship between strain and FCR (R\({}^{2}\) > 0.9) were found.
# Semantic-Enhanced Foundation Model for Coastal Land Use Recognition from Optical Satellite Images
## 5 Experiment  
### Study Area and Implementations  
#### 5.1.1 Study Area  
Coastal land use forms can represent the conditions of eco-social developments, biodiversity, and the ecosystem [33; 34]. Thus, we selected the coastline in California as the study area. The population growth in California curved the coastline's natural land use, while artificial constructions distributed along the coastline significantly made a human-induced print on the coastal environment. Moreover, the activities of artificial constructions such as commercial manufacturing, transportation systems, and industries have caused a loss of vegetable coverage.  
The red polyline in Figure 5A denotes the location of coastal areas in California--the study area used for evaluating the proposed methodology--which ranges from the US-Mexico border to the California-Oregon border. The coastal land cover forms in the study area included a variety of urban, rural, and natural land cover classes, such as downtown, sand, shore, pier, road, and so on. Figure 5B illustrates the selected image samples from the 1000 high-resolution images we collected from Google Earth Pro. Although all collected images contain coastlines, their content comprises different coastal land cover classes, meaning the land use forms represented by each image might vary accordingly.
# Popularity-Aware Closeness Based Caching in NDN Edge Networks
## 5 Conclusions  
In this work we have proposed a novel caching strategy for edge domains, called PaCC, which accounts for content popularity and proximity to the consumers. Achieved results, collected under a variety of settings, confirm that the devised solution allows more judicious content caching decisions that are particularly crucial when the storage capabilities of the edge domain are small. As a consequence, the content retrieval delay experienced by PaCC is reduced compared to the considered benchmark schemes.  
As a further benefit, the proximity of contents to consumers achieved by PaCC allows for reduction in the overall amount of exchanged data traffic at the expense of a negligible additional overhead per NDN packet. Such a finding is relevant because future networks will be overwhelmed by a myriad of (huge) contents exchanged by massively deployed devices and requested by increasingly demanding users.  
The performance of the conceived solution can be further improved by addressing the following aspects: (i) optimizing the method for tracking the content popularity, (ii) optimizing the computation of the popularity-aware closeness metric. In PaCC, a threshold-based mechanism is implemented to track the popularity of contents based on the number of received content requests. However, more accurate mechanisms could be introduced in our design, for instance based on artificial intelligence (AI) content popularity prediction algorithms [20]. In parallel, more accurate metrics could be considered to estimate the proximity of the caches to the consumers. In our design, we leverage the hop count metric, which, however, cannot reflect the presence of congested links or congested nodes. The proximity information could be improved by taking into account other additional metrics like the round-trip-time over the network links and/or the load on the nodes.  
Conceptualization, M.A., C.C., and G.R.; methodology, M.A. and C.C.; software, M.A.; validation, M.A.; investigation, M.A., C.C., and G.R.; writing--original draft preparation, M.A. and C.C.; writing--review and editing, M.A. and C.C.; supervision, A.M. and G.R. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. Not applicable. Not applicable. Not applicable. Not applicable. Not applicable. The authors declare no conflict of interest.
# Measurements of Operating Parameters of a Metal Hydride Compressor with a Heat Pump
## 1 Introduction
The advantages of this technology include simple production, absence of moving parts, safety and reliability, and a possibility to use the waste industrial heat and/or excess renewable energy. The analysis provided by this study clearly shows that a hydrogen compressor containing metal hydride has a good potential to be commercialised, provided that certain measures are implemented with the aim of shifting the power engineering industry away from using fossil fuels and increasing the proportion of renewable sources on the market. Designs of metal hydride compressors often depend on analytical and numerical calculations, and with a sufficient database of experimental data from real-life applications it is possible to create models for predicting the operating parameters of single- and multi-stage MHCs. Such a model was created by the team led by Mr. [PERSON]. The model facilitates predicting the cycle productivities of the MH materials in compressors, throughput productivity of the hydrogen compressor, H\({}_{2}\) pressures in between the stages for multi-stage layouts, and specific heat consumption for the H\({}_{2}\) compression. Authors of the model reported a satisfactory concordance between the predicted results and the real values obtained by experiments, with a deviation of less than 18%. The developed model was proposed as a useful tool in the development of a metal hydride hydrogen compressor via optimising the properties of the metal hydride materials for hydrogen compression and their relative amounts at each particular stage [23; 24]. The key challenge in designing metal hydride compressors is the reduction of energy demand of hydrogen compression by discovering a cheap source of cold and heat. One of the promising visions is the use of highly efficient thermodynamic cycles of heat pumps,which significantly save the consumed energy when compared to the conventional sources. It is therefore necessary to use a heat pump with a high COP (Coefficient of Performance) when defining the range of operating temperatures of the used MH materials. In the present article, the prototype design is presented for a tandem hydrogen compressor with a metal hydride alloy and a heat pump, which is intended for the compression of hydrogen of higher purities, produced primarily in electrolysers. The use of the heat pump increases the efficiency of heat transport between the tanks that are arranged in series. Moreover, the use of a thermal cycle in which the hydrogen is not in contact with the movable parts of the compressor results in a high safety standard [25].
# Reservoir Performance Prediction in Steam Huff and Puff Injection Using Proxy Modelling
## 3 Results and Discussion
### Proxy Models for Predicting Reservoir Conditions after an Injection Cycle
The neural network model of \(sw_{end}\) has an architecture of three hidden layers with a 4-4-2 neuron configuration. For training data, the R-square values for the polynomial regression model and the neural network model are 0.939 and 0.982, while the R-square values for the testing data are 0.935 and 0.980. The MAE of the training and testing data for the polynomial regression model is 0.0259 and 0.0264 and, for the neural network model, is 0.0152 and 0.0156. The RMSE of the training and testing data for the polynomial regression model is 0.0331 and 0.0338 and,  
Figure 16: Predicted and simulated plot of (**a**) training data and (**b**) testing data for reservoir water saturation at the end of the cycle—neural network model. for the neural network model, is 0.0208 and 0.0218. Similar to the reservoir temperature model, polynomial regression and the neural network model are observed fit well. For the polynomial model, a slight distortion is detected above the 0.6 water saturation value. After conducting Sobol analysis for these models, it is observed that the parameter that dominates the contribution to each output model is the initial value of the parameters themselves, before implementing the steam huff and puff injection cycle. Table 3 shows the top five highest contributing parameters, as the other parameters contribute significantly less than the first five parameters. The most important parameter for the reservoir pressure model at the end of the cycle is the initial pressure with 32.7%. For the reservoir temperature, the most important parameter is the initial temperature with 50.9% significance and for reservoir water saturation is the initial water saturation with 78.5% significance. This explains the high fitting value of both the polynomial regression model and the neural network model, where the model is highly linear due to the dominance of one input parameter. This proposes the idea that at the end of the cycle, the traces and effects of steam injection have diminished, leaving the reservoir condition to be nearly similar to the initial condition of the reservoir that demanded the steam injection treatment. However, for the reservoir pressure model, water saturation and viscosity are other parameters that provide a significant contribution. This result can be justified considering that reservoir pressure changes as the volume of the fluid filling the pore spaces changes. Production activity, which displaces the fluid out from the reservoir, depletes the reservoir pressure. This process is the underlying mechanism that determines the reservoir production performance. Hence, the two most important parameters from the developed production predictive models above--water saturation and oil viscosity--may possibly take part in impacting the reservoir pressure model.
# Kleene Algebra to Compute Invariant Sets of Dynamical Systems
## 3 Kleene Algebra
### Definition  
A Kleene algebra \((\mathcal{K},+,\cdot,\ast)\) is a set \(\mathcal{K}\) together with two binary operations \(+:\mathcal{K}\times\mathcal{K}\rightarrow\mathcal{K}\) and \(\cdot:\mathcal{K}\times\mathcal{K}\rightarrow\mathcal{K}\) and one function \(\ast:\mathcal{K}\rightarrow\mathcal{K}\), so that the axioms listed in the Table 1 are satisfied.  
The literature contains several inequivalent definitions of Kleene algebras and related algebraic structures (41). Our definition differs when we introduce the Kleene operator: we assume _star-continuity_, which is needed as soon as infinite cardinal sets are considered.  
Probably the mainstream definition is that of Kozen in (42), where the Kleene operator is defined formally by the following properties  
\[\begin{array}{c}1+aa^{\ast}\leq a^{\ast}\\ 1+a^{\ast}a\leq a^{\ast}\\ ax\leq x\Rightarrow a^{\ast}x\leq x\\ aa\leq x\Rightarrow xa^{\ast}\leq x\end{array}\]  
and the star-continuity is defined by  
\[xa^{\ast}y=\sum_{i\geq 0}xa^{i}y.\]  
Now, if we take \(x=y=1\), we get  
\[a^{\ast}=1\cdot a^{\ast}\cdot 1=\sum_{i\geq 0}1\cdot a^{i}\cdot 1=\sum_{i\geq 0 }a^{i}.\]  
which corresponds to our definition.  
The following proposition illustrates the fact that applying a Kleene star operator to \(a\) amounts to computing a fixed point. This will be used later in the algorithms.  
**Proposition 1**.: _Given a star continuous Kleene algebra \((\mathcal{K},+,\cdot,\ast)\), we have_  
\[(1+a)^{\infty}=\lim_{i\rightarrow\infty}(1+a)^{i}=a^{\ast} \tag{4}\]  
_where_  
\[\begin{array}{ccc}a^{0}&=&1\\ a^{i+1}&=&a\cdot a^{i}\\ a^{\infty}&=&\lim_{i\rightarrow\infty}a^{i}\quad\text{(if it exists)}\end{array}\]  
Proof.: We first show by induction that  
\[(1+a)^{n}=\sum_{i\in\{0,n\}}a^{i}. \tag{5}\]  
Assume that the proposition is true for \(n\). We have\[(1+a)^{n+1} = (1+a)(1+a)^{n}\] \[\stackrel{{(5)}}{{=}} (1+a)\cdot\sum_{i\in\{0,n\}}a^{i}\] \[= \left(\sum_{i\in\{0,n\}}a^{i}+a\cdot\sum_{i\in\{0,n\}}a^{i}\right)\] \[= \left(\sum_{i\in\{0,n\}}a^{i}+\sum_{i\in\{0,n\}}a^{i+1}\right)\] \[= \left(\sum_{i\in\{0,n\}}a^{i}+\sum_{i\in\{1,n+1\}}a^{i}\right)\] \[= \sum_{i\in\{0,n+1\}}a^{i}.\]  
Since the two sequences involved in (5) are equal, they have the same limit. Therefore,  
\[\lim_{n\to\infty}(1+a)^{n}=\lim_{n\to\infty}\left(\sum_{i\in\{0,n\}}a^{i} \right)=\sum_{i\in\{0,\ldots,\infty\}}a^{i}=a^{*}.\]
## 6 Conclusions  
This study, using a five-story building as an example, investigated evacuation strategies for differently-abled people in multi-story buildings under various assistance ratios. The research identified two types of evacuation strategies for differently-abled people: elevator-determined evacuation and stair-determined evacuation. Based on these, a comprehensive evacuation efficiency analysis model, specifically for multi-story buildings where with differently-abled reside, was proposed, leading to the following conclusions:  
For stair-determined evacuation, when the assistance ratio is below 70%, improvement in evacuation efficiency is minimal, allowing differently-abled people to utilize their own evacuation abilities; however, if differently-abled people are unable to evacuate independently and assistance is needed to enhance overall evacuation efficiency, the assistance ratio should be greater than 70%.  
For elevator-determined evacuation, adopting unrestricted evacuation on middle floors can enhance evacuation efficiency.  
The multi-story building evacuation efficiency analysis model proposed in this paper can clearly determine the optimal evacuation method for each floor. This research can provide insights for the development of emergency evacuation plans for places where differently-abled people reside.  
In the design of evacuation plans for five-story buildings, when the assistance ratio is below 40%, it is recommended to use high-level stairwells, mid-high-level elevators, middle-level unrestricted evacuation, and ground-level stairwells for evacuation. When the assistance ratio exceeds 40%, it is recommended to use high-level stairwells, mid-high-level unrestricted evacuation, and middle-level and ground-level stairwells for evacuation.  
Figure 12: Analysis model of optimal evacuation efficiency for each floor in stairwell-based evacuation.  
**Author Contributions:** Conceptualization, K.L. and W.F.; methodology, K.L. and W.F.; validation, K.L., W.F., and J.C.; formal analysis, K.L., W.F., L.Q. and J.C.; investigation, L.Q. and J.C.; data curation, T.Y. and X.L.; writing--original draft preparation, W.F.; writing--review and editing, all authors; project administration, K.L. and W.F.; funding acquisition, K.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** All date used during the study appear in submitted article.  
**Conflicts of Interest:** Author [PERSON] was employed by the Chongqing Changan Automobile Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 4 Experimental Evaluation
### Validation on Other Dataset  
In order to fully verify the generalization and robustness of the proposed method, 1000 complex background gesture images were selected for manual annotation in the public dataset TinyHGR and used as experimental data. The proposed method was compared with the original YOLOv5l algorithm, the YOLOv7 algorithm, and the YOLOv3-tiny-T algorithm for experimental experiments, and the results are shown in Tables 3 and 4.  
Table 3 shows a comparison of the recognition accuracies of the compared methods. It can be seen that all of the methods achieved good results on this dataset, which is due to the relatively low difficulty of recognition in this dataset, which included dark backgrounds, motion blur, and incomplete gestures. However, the proposed method still achieved the best results for each metric, which is good evidence that the proposed method has better recognition performance and robustness for all types of complex backgrounds.  
Table 4 shows a comparison of the proposed method's gesture recognition results. It can be seen that the proposed method showed good recognition accuracy for all types of gestures, with only OK and 1 gestures having a full rate of less than 99%, although they reached 95.2%. For all gestures, an accuracy rate of more than 96.5% was reached. In these two gesture categories, despite their reduced AP values, 58.3% and 56.2% were reached, respectively.
# Precision Agriculture: A Remote Sensing Monitoring System Architecture +
## 4 The Network Layer
### The Encapsulation Layer
* The IPv6 over 802.11 ah [10] or Wi-Fi-ah (HaLow) is a low-power/low-rate protocol able to support numerous sensor node devices on a single base station. This technology can be used for precision agriculture by enabling wireless base stations in the field to transmit data while also being energy conservative. Wi-Fi-ah (HaLow) uses special characteristics of the 6 LoWPAN technology for effective transmission of IPv6 protocol packets over IEEE 802.11 ah wireless networks. * RPL (IPv6 Routing over Low Power and Lossy Networks) [26] is the most popular IoT routing protocol based on the distance vector routing technique. It is a proactive protocol that constructs a specific graph able to direct all traffic towards the sink node. RPL is the ideal routing protocol for agricultural LLNs, since it can quickly create network routes between sensor nodes in the field, share routing knowledge and adapt the topology in an efficient way. It is also efficient for multi-hop, many-to-one and one-to-one communication. * LOADng-IoT is another IoT routing protocol, proposed in [28] as an enhancement for reactive protocol LOADng, which is considered to be the best current solution for LLNs. LOADng-IoT is able to boost the process of route discovery, reduce the overhead of control messages, and improve the network's quality-of-service(QoS). In a smart farm monitoring system, this protocol will allow sensor nodes without an Internet connection to forward their data packets to external Internet services with much greater reliability and lower latency.