esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background
### Potential Threats  
Whilst users are browsing the web, there are a number of security issues they may potentially be subjected to. In addition to breaking the law, should users download illegal files such as pirated movies or software, they are also engaging in risky security behaviour, placing their system at risk. The files downloaded may contain viruses or malware [8].  
Interaction with websites featuring coding vulnerabilities is also risky and users are generally unaware of such flaws [14]. If an application is poorly constructed, users may expose themselves to an attack by simply visiting a site, e.g., vulnerability to XSS attacks or session hijacking. Cross-site scripting (XSS) attacks are common on the web and may occur where users have to insert data into a website, e.g., a contact form. Attacks related to social engineering are also linked to technology flaws. Often,users divulge too much information about themselves on social networking sites [1], e.g., it is possible to extract geolocation data from a specific Twitter account to establish the movements of a user. Such patterns have the potential to highlight the workplace or home of a user. An attacker could target a user, gathering the information shared to produce a directed attack against the victim e.g., sending the victim an email containing a malicious link about a subject they are interested in [9]. Sending a user an email of this type is known as a phishing attack (a spear phishing attack when it is targeted towards specific users). The malicious link contained within the email may link to a site asking users to enter information such as bank account details. As such, many average users would fail to identify a phishing email, potentially revealing private information [15, 16]. The rise in spear phishing attacks has led the FBI to warn the public regarding this issue [17].  
Perhaps one of the most common risky security behaviours involves the misuse of passwords for online accounts which link to personal information. There can be a trade off between the level of security of a password provides and its usability [7]. Passwords, which are shorter, are less secure however, they are easier for users to remember and are therefore usable. Users may also engage in the practice of sharing passwords. When [PERSON] _et al._[6] interviewed 1167 end-users in devising a taxonomy of risky behaviours, it was found that 23% of those interviewed shared their passwords with colleagues. 27.9% of participants wrote their passwords down.  
These are just a sample of the attacks users may be subjected to whilst browsing the web on a daily basis. Security tools such as virus scanners and anti-malware software can aid users if their machines have been infected with malicious software. If users are educated regarding risky security behaviour, this may prevent their machines from becoming infected in the first instance. A considerable amount of research has been conducted into educating and helping users understand risky security behaviour online, and Section 3 discusses varying approaches.
## 3 Research Questions and Communication Efficient Methods
### RQ2-How Can Communication Be More Efficient in an FL Environment?
#### 3.2.2 Client Selection
The results that the authors achieve are computed relatively faster and provide a higher accuracy of results than the baseline random selection methods [70]. Uplink and downlink communication with participating clients in a federated network is necessary. Having to communicate with clients that have a dependable network bandwidth and energy sources could aid in achieving a well-trained global model moreefficiently. Implemented client selection techniques can aid in reducing the cost of the overall communication that is needed to achieve a dependable global model. Considering mobility participants in FL, load-balancing is a key point when managing available resources and minimizing the training and communication delay. Authors in [71] proposed a load balancing and computation offloading technique for mobile-edge computing systems that can also be implemented in the FL environment.
# 3 GPP 5G V2X Error Correction Coding for Various Propagation Environments: A QoS Approach
## 5 Simulation Results
### Impact of Channel State on V2X System Model  
Figure 2(b) illustrates the increase in FER when the channel state changes from LOS to NLOSv for the SOVA algorithm. This measurement has been calculated both when the channel state change occurs in urban environments, i.e., scenarios S3 and S5, and in highway traffic environments, i.e., scenarios S1 and S2. In urban environments, FER becomes worse by 355.5%, and in highway environments, by 53.7%, resulting in an overall average FER increase of 204.6%, as shown in Figure 2(b). As a result, we can deduce that  
the LOS channel state is much more efficient than NLOSv, especially in the highway traffic model, where the presence of scatterers affects the reliability of the channel less. In Figure 3c, we also present the behavior of the FER when there is a channel change from LOS to NLOS, where this change concerns only an urban environment, i.e., scenarios S3 and S4. We can observe that the absence of a line-of-sight signal deteriorates the performance of the communication system by 66.6%, which is greater than the LOS-to-NLOSv change in an urban environment.
# What is 5G? Emerging 5G Mobile Services and Network Requirements
## 4 5G Mobile Services
### Omnipresent 5G Services  
#### 4.3.1 Internet of Things  
5G introduces many heterogeneous devices with different characteristics as compared to 4G. The introduction of wearable devices and network-connected home devices that often communicate with each other generates much exchange of information. These information exchanges generate huge volume of information in various dimensions that are saved in storage devices and are later processed using big data technologies. As shown in Figure 8, IoT can be categorized into smart personal networks, smart buildings and smart cities, depending on its application and network size. Smart personal networks contain smart watches, smart glasses, various healthcare devices and motion detection devices. A feature of smart personal network services is monitoring personal health conditions and suggesting exercises or medicine. The market volume of these devices is expected to increase to 162.9 million units in 2020 [21]. Smart buildings contain various sensors, light and temperature controllers, efficient energy controllers and crime prevention systems. In smart cities, efficient traffic light control systems can be deployed using various types of traffic sensors. This will eventually help to control traffic smartly while communicating with vehicles and road side units (RSUs). IoT is helpful in establishing efficient city infrastructure by using big data technologies to process information about traffic flow. Then, it is possible to inform users of the recommended transportation and the estimated arrival time according to traffic conditions. However, a network with low latency is a prerequisite or an otherwise serious problems in traffic safety might take place. The massive increase in network connected devices will soon exhaust the International Mobile Subscriber Identity (IMSI) and IPv4. In future IoT scenarios, a tremendous amount of connected devices will be present compared to current 4G network scenarios. Therefore, 5G technologies for transmission and networks have to be able to maintain multiple network connections with many devices using limited resources. Currently, the pricing policy of mobile services is applied per terminal or connection. The number of terminals is expected to increase exponentially; therefore, a new criteria of billing is required.  
Figure 7: Crowded area services.
## 3 Results
### Morning and Afternoon Transitions of the Urban Boundary Layer
#### 3.3.1 Durations
The delay in our case was likely caused by a combination of multiple factors. The AT started at around 11:00-14:00 CST and mostly ended about 1 h before sunset (16:50 CST, monthly averaged), meaning it could last 3-6 h. Interestingly, the AT duration (D\({}_{\rm AT}\)) showed no obvious correlation with WS (\(r<-0.1\)), while the ratio of \(H\) decay (\(r_{\Delta H}\)) during D\({}_{\rm AT}\) showed a strong positive correlation with the WS averaged during D\({}_{\rm AT}\) (\(r=0.5\) for the 8-m level and \(r=0.6\) for the 47-m level). In addition, \(r_{\Delta H}\) had a negative correlation (\(r=-0.4\)) with the PM\({}_{2.5}\) concentration averaged during D\({}_{\rm AT}\), due to the aerosol cooing effect. In contrast, as compared with a new stable boundary-layer development near the ground in the morning, the boundary layer in the evening was already developed after a growth in the afternoon [66]. This difference will also modulate the magnitude of duration, due to different thermal-dynamical and aerosol context between morning and evening. Notably, it has been proven that there are interactions between the urban boundary layer and aerosol pollutants [31; 67], from which it can be concluded that the long D\({}_{\rm MT}\) and rapid \(r_{\Delta H}\) both support a suitable condition for the accumulation of aerosol pollutants, and in turn, the high concentrations of aerosol pollutants, with their radiation effects, can prolong the D\({}_{\rm MT}\) and accelerate the \(r_{\Delta H}\). Therefore, the transition process is very complex [50], and aerosol pollutants add another level of complexity. Based on the above findings, a schematic illustration of the diurnal cycle of the ABL on a polluted weak and windy day (taking 19 December as an example) is shown in Figure 8. The RL height (250 m) was taken from [31]. As can be seen, the CBL onset is at 11:00 CST, with a 4-h D\({}_{\rm MT}\), which is larger than the mean value (2.4 h). This delayed development is caused by the weak wind (0.7 m s\({}^{-1}\) at the 8-m level, averaged during D\({}_{\rm MT}\)) and cooling effect of aerosols (PM\({}_{2.5}\) concentration = 267 ug m\({}^{-3}\), averaged during D\({}_{\rm MT}\)). Note that the CBL height tends to decrease obviously from about 4 h after the peak time of \(H\), which implies that the response of the urban BLH variations lag behind the thermal forcing. This result is consistent with previous results derived from observational measurements [8] and a large-eddy model [50]. Moreover, the crossover of \(H\) is at 18:00 CST, 1 h after sunset, which can be explained by the weak wind and the high thermal conductivity of the concrete in built-up areas (large heat storage of the urban canopy). The existence of pollutants in the RL, formed on the previous polluted day, plays an important role in the changes of pollutants at the surface in the morning, which can reach the ground the following morning through convection [29; 68]. This mechanism of pollutant vertical mixing is very complex, and can be further investigated via model simulations.
## 3 Method and Case Study  
In this research, we propose the application of a combined method to evaluate accessibility in serious games, considering the Web Content Accessibility Guidelines (WCAG) 2.1. As a case study, we evaluated the accessibility in 82 serious games developed by the PhET project [12]. The evaluation started on 19 January 2020 and ended on 20 June 2020. The study involved two expert evaluators in accessibility, who had experienced since 2015 and have contributed several articles in the area when there were discrepancies in the evaluation of the collaboration of a third expert was requested. In this study, the combined method includes the application of two automatic tools and manual evaluation. The evaluation method is summarized in the eight steps shown in Figure 1.  
Phase 1: Select the serious games. In this phase, we selected the serious games of the PhET project. To select the sample size, we apply equation (1). \[n=\frac{NZ^{2}PQ}{(N-1)E^{2}+Z^{2}PQ} \tag{1}\]  
where \(n\) is the sample size to be calculated, \(N\) is the size of the universe, in this case, 87 serious games, with a confidence level of 97%, where \(Z\) corresponds to 2.17, with an error margin \(E=0.03\). Applying the formula, we obtained the value of 82, which is the number of serious games, selected sequentially, and evaluated in this research by the two accessibility experts. Table 1 contains the evaluated serious games, including the identification of each game and the name of the serious games within each URL (The complete URL is constructed by adding to the beginning of each address [[https://phet.colorado.edu/sims/html/](https://phet.colorado.edu/sims/html/)]([https://phet.colorado.edu/sims/html/](https://phet.colorado.edu/sims/html/)). For example, the complete address for the first serious game is [[https://phet.colorado.edu/sims/html/acid-base-solutions/latest/acid-base-solutions_es.html](https://phet.colorado.edu/sims/html/acid-base-solutions/latest/acid-base-solutions_es.html)]([https://phet.colorado.edu/sims/html/acid-base-solutions/latest/acid-base-solutions_es.html](https://phet.colorado.edu/sims/html/acid-base-solutions/latest/acid-base-solutions_es.html))). \begin{table}
\begin{tabular}{c l c} \hline \hline
**ID** & **URL** & **Subject** \\ \hline
1 aci & acid-base-solutions/1.2.24/acid-base-solutions\_es.html & Chemistry \\
2 are & area-builder/1.12.0/area-builder\_es.html & Math \\
3 are & area-model-algebra/1.2.1/area-model-algebra\_es.html & Math \\
4 are & area-model-decimals/1.2.1/area-model-decimals\_es.html & Math \\
5 are & area-model-introduction/1.2.1/area-model-introduction\_es.html & Math \\
6 ari & area-model-multiplication/1.2.1/area-model-multiplication\_es.html & Math \\
7 ato & arithmetic/1.0.2/arithmetic\_es.html & Math \\
8 bal & atomic-interactions/1.1/atom-icinteractions\_es.html & Chemistry \\
9 bal & balancing-act/1.1.2/balancing-act\_es.html & Math \\
10 bal & balancing-chemical-equations/1.210/balancing-chemical-equations\_es.html & Chemistry \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Serious games were selected for evaluation. Figure 1: Diagram of accessibility evaluation of serious games.
## 3 The Proposed HCDBAVNS Algorithm
### Definition of Parameters and Operations
#### 3.1.4 Update Operations of the Bat Loudness and Pulse Emission Rate  
Supposing \(R_{i}^{0}\in[0,1]\) and \(A_{i}^{t}\in[0,1]\) are the initial pulse emission rate and loudness of bat \(i\) at iteration \(t\). Then, at iteration \(t+1\), its loudness \(A_{i}^{t+1}=\alpha A_{i}^{t}\), and pulse emission rate \(R_{i}^{t+1}=R_{i}^{0}\times[1-\exp(-\gamma t)]\), where the loudness factor \(0<\alpha<1\) and pulse emission rate factor \(\gamma>0\).
# Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation
## 2 CO2 Observation, Datasets, Global Related Research
### Satellite Remote Sensing Observations
#### 2.2.2 Development of Short-Wave Infrared Hyperspectral Sensors  
The use of SWIR techniques to analyze atmospheric CO\({}_{2}\) has become a new approach with the continuous advancement of methods and means of space-based remote sensing observations. The reflection spectrum detected in the sensors carries information about the whole atmosphere and contains CO\({}_{2}\) information in the near-surface layer, Short-wave infrared sensors are mainly sensitive to the CO\({}_{2}\) concentration near the surface and are often used to invert the column concentration of atmospheric CO\({}_{2}\). Sensors that utilize the short-wave infrared band (1.6 um) for the inversion of CO\({}_{2}\) mainly include SCIAMACHY, GOSAT, OCO-2, and TanSat.  
European Satellites  
The European polar-orbiting Earth observation satellite Envisat-1, launched on 1 March 2002, carried the Scanning Imaging Absorption Spectrometer for Atmospheric Charting (SCIAMACHY), the world's first satellite sensor capable of measuring carbon dioxide and methane concentrations. SCIAMACHY has three modes of observation: limb, nadir, and occultation, with a spatial resolution of 30 km \(\times\) 60 km.  
Japanese Satellites  
The GOSAT satellite, launched by Japan in 2009, was a pioneering mission for greenhouse gas monitoring, utilizing the Thermal and Near Infrared Sensor for carbon Observation Fourier-Transform Spectrometer(TANSO-FTS) and the Cloud and Aerosol Imager  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Sensor** & **Mounting Platform** & **Launching Time** & **Spectral Type** & **Spectral Range** & **Spectral Resolution/cm\({}^{-1}\)** & **Spatial Resolution/km** & **Width/km** \\ \hline IMG & ADEOS & 1996 & Intervene & 600\(\sim\)3030 cm\({}^{-1}\) & 0.15\(\sim\)0.25 & 22 & - \\  & & & & 8.80\(\sim\)15.4 μm & 0.55 & & \\ AIRS & EOS-Aqua & 2002 & Encoder & 6.20\(\sim\)8.22 μm & 1.2 & 13.5 & 1650 \\  & & & 3.74\(\sim\)4.61 μm & 2.0 & & \\ TES & EOS-Aura & 2004 & Intervene & 3.2\(\sim\)15.4 μm & 0.06 & 5 & 182 \\ IASI & METOP & 2006 & Intervene & 3.4\(\sim\)15.5 μm & 0.35\(\sim\)0.55 & 12 & 2200 \\ HIRAS & FY-3D & 2017 & Intervene & 8.8\(\sim\)15.38 μm & 0.625 & & \\  & & & 5.71\(\sim\)8.26 μm & 1.25 & 16 & 2250 \\  & & & 3.92\(\sim\)4.64 μm & 2.5 & & \\ AIUS & GF-5 & 2018 & Intervene & 750\(\sim\)4100 cm\({}^{-1}\) & 0.02 & - & 1850 \\ IRS & MTG & 2022 & Intervene & 8.26\(\sim\)14.28 μm & 0.625 & 4 & - \\  & & & 4.60\(\sim\)6.25 μm & 10 & - \\ \hline \hline \end{tabular}
\end{table}
Table 1: Thermal infrared sensors for CO\({}_{2}\) detection.  
(CAI) instruments to measure global CO\({}_{2}\) and CH\({}_{4}\) concentrations. Its data products are categorized into four levels, from raw spectral data (Level 1) to global CO\({}_{2}\) fluxes (Level 4). GOSAT's spatial resolution is 10 km \(\times\) 10 km with a re-observation period of 3 days. The GOSAT-2, launched in 2018, improves upon this with enhanced TANSO-FTS-2 and CAI-2 instruments for more precise measurements.
## 3 Preliminaries
### IEEE Std 1855-2016 and Fuzzy Markup Language  
The IEEE std 1855-2016 defines a common framework for the development and deployment of fuzzy systems [21]. It was introduced to provide interoperability, scalability, and standardization in fuzzy logic applications across different domains, ensuring consistency in their implementation. The core element of this standard is the FML, an XML-based representation designed to describe FISs independently of the underlying hardware or software.  
FML enables the structured definition of fuzzy logic components, including the following:  
* **Linguistic variables and terms**: Representations of imprecise concepts such as \"low temperature\" or \"high humidity\".
* **Fuzzy rules**: Causal relations between linguistic variables and terms inspired by human reasoning.
* **Inference mechanisms**: Methods for aggregating fuzzy rules to derive conclusions.
* **Defuzzification methods**: Techniques to transform fuzzy outputs into crisp values for real-world applications.  
This standard provides a structured methodology to ensure interoperability across different fuzzy logic implementations. However, it does not define specific software implementations, leading to the development of libraries such as JFML to support its adoption.
# Influence of Preconditioning and Tunnel Support on Strain Burst Potential
## 1 Introduction
While work has been done to assess the rockburst hazard better [3; 18; 32], and improve the rock support system and preconditioning measures currently implemented [7; 25; 28; 33; 34], the effect of mitigation measures on strain burst hazard potential is unclear. This paper studies the influence of the implementation of shotcrete and rockbolts support and destress blasting in tunnels on strain burst potential. More specifically, two-dimensional numerical models of circular tunnels are realized considering the DISL approach to represent brittle spalling behavior. These models are compared to the well-known depth of failure charts. Strain burst hazard levels are defined and compared in four cases: (1) no mitigation measures are considered, (2) shotcrete and rockbolts are applied around the tunnel, (3) destressing blasting is used to manage the strain burst, and (4) both shotcrete and rockbolts, as well as destressing, are considered. This works focuses on the strain burst hazard assessment and is looking to compare hazard levels with or without any mitigation measures, which is an aspect unknown to date.
## 2 Derivation of Boundary Conditions of 4D C/C Composite
### The Temperature and Heat Flux of Unit Cells Formed by 180\({}^{\circ}\) Rotational Symmetry  
\(M\) is an arbitrary node in the cube in Figure 4. The \(z\)-axis is defined as the axis of rotation. The left half of the cube would completely coincide with the right half if it rotates 180\({}^{\circ}\) around the \(z\)-axis, and \(M=(x_{1},y_{1},z_{1})\) can be converted to the node \(M^{\prime}=(-x_{1},-y_{1},z_{1})\). As shown in Figure 4, a smaller-size unit cell is constructed using a 180\({}^{\circ}\) rotational transformation, by the domain \(0\leq x\leq l/2\), \(0\leq y\leq w\), \(0\leq z\leq h\). Considering the relationship between the direction of heat flux and the rotation axis (\(z\)-axis), it can be divided into two categories: (1) antisymmetric thermal stimulus, which means that the heat flux is perpendicular to the axis of rotation in Figure 4, (2) symmetric thermal stimulus, which means the heat flux is parallel to the axis of rotation in Figure 5.  
Based on the discussion above, the heat flux distributions and temperature relations of antisymmetric thermal stimulus and symmetric thermal stimulus can be depicted by Equations (1) and (2), respectively.  
\[T_{M}-T_{O}=T_{O}-T_{M^{\prime}}\mu_{x|M}=q_{x|M^{\prime}}, \tag{1}\]  
\[T_{M}-T_{O}=T_{M^{\prime}}-T_{O}\mu_{x|M}=q_{x|M^{\prime}}, \tag{2}\]  
Figure 4: The relations of the antisymmetric thermal stimulus from rotational transformation.  
Figure 5: The relations of the symmetric thermal stimulus from rotational transformation.  
Figure 3: Topological relationship of the main yarns in UC1.  
where, \(T_{M}\), etc., is the temperature of the nodes in the cube, \(q_{x|M}\), etc., is the heat flux of the nodes in x direction. It should be mentioned that the temperature of the node will be represented by the subscript of its coordinates in the following discussion. When describing the heat flux of the node, the left side of the subscript represents the direction of heat flow, and the right side represents the position of the node.
# Resilient Consensus Control for Multi-Agent Systems: A Comparative Survey
## 2 Preliminaries and Consensus Problem for MASs
### Preliminaries about Graph Theory  
The information connection among agents can be modeled by a graph \(\mathcal{G}(\mathcal{V},\ \mathcal{E})\), where \(\mathcal{V}\) denotes the set of vertices \(\{v_{1},\ v_{2},\ \dots,\ v_{N}\}\) which represents the set of agents in the system, and \(\mathcal{E}\subseteq\mathcal{V}\times\mathcal{V}\) gives the set of links which mimics the connection among agents. Given nodes \(i\) and \(j\in\mathcal{V}\), \(i\) can send information to \(j\) if there exists a directed edge from \(i\) to \(j\), which is in the form of \((j\gets i)\). The adjacency matrix associated with graph \(\mathcal{G}\) is denoted by \(\mathcal{A}=[a_{ij}]\), where \(a_{ij}=1\) if \((j,i)\in\mathcal{E};0\), otherwise. \(\mathcal{G}(\mathcal{V},\ \mathcal{E})\) is called an undirected graph if \(\mathcal{A}\) is symmetric. The Laplacian matrix of \(\mathcal{G}\) is defined by \(\mathcal{L}=[l_{ij}]\), where \(l_{ij}=-a_{ij}\) if \(j\
eq i\); \(l_{ii}=\sum_{j=1}^{N}a_{ij}\) otherwise.  
At time \(t\), denote by \(\mathcal{G}(t)\) the pair \((\mathcal{V},\ \mathcal{E}(t))\), where the edge set \(\mathcal{E}(t)\) varies with time. If there is a random process governing the change of \(\mathcal{G}(t)\), one calls the communication graphs to be randomly switching.