esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Turbulence Model
#### 3.3.2 Results of Spalart-Allmaras  
Figure 31 depicts the distributions of P/P\({}_{\text{t}}\) and T/T\({}_{\text{t}}\), and Table 22 contains the mean error ratios. We then determine the total mean error ratios under different configurations and the optimal results are highlighted in red in Figure 32. As to the far-field distance, the following 2.83%, 2.05%, and 2.98% are the three preferred results. As for the NACA0012 model, the best performances are 3.29%, 2.83%, 2.98%, 2.05%, 4.51%, and 3.48% in order. As for the flux type, ROE has the optimal value of 2.05%, and that of AUSM is 3.28%. Therefore, the ideal configuration is 16 m + 200 points combined with ROE. The optimal result is 2.05%, and the related accuracy growths are 40.51%, 37.82%, 44.69%, 27.65%, 46.10%, 42.59%, 67.92%, 57.41%, 31.21%, 28.59%, 39.37%, 54.63%, 62.07%, 55.99%, 64  
Figure 32: Comparison of the simulation performances of SA turbulence model under different sim-ulation configurations.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Simulation** \\ **Configurations** \\ \end{tabular} } & \multicolumn{4}{c}{**Mean Error Ratios under Different Configurations**} \\ \cline{2-7}  & **P/Pt** & **T/T\({}_{\text{t}}\)** & **U/U\({}_{\text{t}}\)** & **P/Pt** & **T/T\({}_{\text{t}}\)** & **U/U\({}_{\text{t}}\)** \\ \hline  
\hline \end{tabular}
\end{table}
Table 22: The mean error ratios of P/P\({}_{\text{t}}\), T/T\({}_{\text{t}}\), and U/U\({}_{\text{t}}\) of SA turbulence model.
# Road Scanner: A Road State Scanning Approach Based on Machine Learning Techniques
## 5 Experiments
### Classification Models
#### 5.2.2 Support Vector Machines  
The SVM (Support Vector Machine) [26] is a supervised ML technique that is largely employed for classification. This approach is founded on two fundamental ideas. The first premise is the maximization of the hyperplane's margin. The objective is to identify the best hyperplane that divides classes by the largest margin. In the case where data are separable in a linear manner, this is a typical quadratic-type optimization issue. Nonetheless, data are frequently linearly inseparable. The kernel function that represents the second essential concept provides the answer by translating the original data space into a higher-dimensional space, where it is probable to obtain a linear separator. The SVM concept handles nonlinear classification problems effectively in this manner [27; 28]. An illustration of the SVM Algorithm is shown in Figure 8.
## 4 Result and Discussion
### Finite Element Analysis  
The finite element analysis was conducted in order to examine the deformations of pavements during the accelerated simulation and to measure rut depth. Figure 6 indicates the cross-sectional vertical deformations of each testing pavement at 50 loading cycles. As shown in Figure 5(a), the rut depth at the initial stage of the simulation was calculated to 1.16 mm. This was the largest rut depth compared to the other pavements. In the rest of pavements, the rutting calculations were 0.63, 0.82 and 0.34 mm for concrete block and bound stone pavement A and B, respectively. Comparing two types of stone pavements, the rut depth of bound stone pavement B was calculated relatively lower. The difference in this comparison was mainly caused by the different type of base courses. The asphalt base course was considered as a flexible construction.  
Figure 5: Skid resistance measurement and falling weight deflectometer test result.  
Figure 6: _Cont._Figure 7 indicates rut depth calculation data according to the cumulative number of loading cycles. As shown in Figure 7a, the trend lines of vertical deflection were gradually increased in all the testing pavements except concrete block pavement. For the concrete block pavement, there was a rapid drop from 0 to 5000 loading cycles, and it was made by the compaction of laying sand. The terminal deformations of the pavements were determined as 17.7, 6.1, 6.3 and 3.6 mm for asphalt, concrete block and bound stone A and B pavement, respectively. The greater value was calculated in the bound stone pavement A compared to stone pavement B. Additionally, a slope of the trend line in the bound stone pavement A increased after one million loading cycles. These circumstances were caused by different material types of base courses which were asphalt and concrete.  
Figure 6: FEM analysis results (deformation).  
Figure 7: Vertical deflection (FEM analysis).  
Figure 8 is a plotted data of rut depth measurements obtained from the APT in the first part of the current study. The final rut depth of the APT was recorded as 16.0, 4.5, 3.0 and 1.5 mm for asphalt, concrete pavement and bound stone pavement A and B, respectively. Approximately, the trend lines in Figures 7 and 8 show great agreements over both accelerated and computational simulation periods in asphalt and concrete block pavements. On the other hand, comparing rut depth outcomes at the end of both test and simulation, there were 52.4% and 58.3% of increases in FEM analysis of the bound stone pavement A and B, respectively. For the improved analysis of bound stone pavements, it would be necessary to consider the enhanced modelling of bedding course such as the influence of joint mortar loss.  
**Funding:** This study was supported by the Research Scholarship of the Chungnam National University in 2019. The authors gratefully acknowledge this support.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Detecting Axial Ratio of Microwave Field with High Resolution Using NV Centers in Diamond
## 3 Experiments and Results
### MW Magnetic Field Detection Using a Single NV Center in Diamond
As \(B_{MW}\propto\sqrt{P}\), \(\omega_{MW}=\gamma_{e}B_{MW}\), the Rabi frequency increased linearly with the square root of the resonant MW field power. The linear dependence was verified by detecting Rabi oscillation signals with different MW field powers applied. Figure 4 shows the linear dependence of Rabi frequency on microwave magnetic field strength. This is consistent with the measurement principle. Turning over the permanent magnet to apply a bias magnetic field in the reverse direction, the \(\sigma^{+}\) component of the MW magnetic field perpendicular to the NV axis can be detected similarly. Therefore, the axial ratio of the MW magnetic field at the NV point perpendicular to the NV axis can be derived.
## 3 Obstacle Avoidance Motion Planning Framework
### Violation Cost Potential Field
#### 4.3.3 Violation Penalty  
The severity of a violation is closely related to the type of violation, and an intuitive indicator is the penalty that corresponds to the type of violation. To incorporate the violation penalty into autonomous driving motion planning, the basic violation propositions are validated in the first place. Then, the violation objects are identified to determine the specific violations. The consequences of different violations are specified according to the relevant penalty regulations.  
This study consults the penalties for violations specified in the relevant Chinese laws, the _Measures for the Administration of Points Assigned for Road Traffic Violations_[38] and the _Road Traffic Safety Violations, Codes, and Penalty Scoring Standards_[39]. The penalties for violations are cumulative. Certain violations do not result in the assignment of demerit points, instead resulting in warnings and monetary penalties. This study solely focuses on the deduction of driving license points. Specific violations and their penalties are listed in Table 4.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Violation Type** & **Degree Calculation** \\ \hline Speeding & \\ Failure to stop & \(\left\{\begin{array}{c}\frac{s(ego)+\frac{1}{2}l(ego)-s(s(tgt_{r})-l(tgt_{r})} \\ \frac{s(ego)+\frac{1}{2}l(ego)-s(tgt_{r})-l(tgt_{r})}{d_{ego}}\\ \frac{s(ego)+\frac{1}{2}l(ego)-s(s(stopline)}{l(ego)}\end{array}\right.\) & \text{stopline} \\ \text{Failure to yield}&\frac{s(ego)+\frac{1}{2}l(ego)-s(tgt_{r})}{l(ego)} & \\ Marked lane violation & \(\left\{\begin{array}{c}\frac{d(ego)+\frac{1}{2}w(ego)-d(lanemline_{r})}{w(ego) }\\ \frac{d(lanemline_{r})-l(ego)+\frac{1}{2}w(ego)}{w(ego)}\end{array}\right.\) & left \\ Improper turn & \(\left\{\begin{array}{c}\frac{d(ego)+\frac{1}{2}w(ego)-d(lanemline_{r})}{w(ego) }\\ \frac{d(lanemline_{r})-l(ego)+\frac{1}{2}w(ego)}{w(ego)}\end{array}\right.\) & left \\ Illegal reversing & \(\frac{s(ego)+\frac{1}{2}l(ego)-s(lanemline_{r})+\frac{1}{2}l( navigling)}{l(ego)}\) \\ Illegal stopping & \(\frac{s(ego)+\frac{1}{2}l(ego)-s(lanemline_{r})+\frac{1}{2}l(ego)}{l(ego)}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Measurement methods of violation degree.  
Collision risk, violation degree, and violation penalty are extracted to constitute the PVCI, based on the principle of obstacle avoidance in unanticipated obstacle scenarios. The PVCI is defined as:  
\[\text{PVCI}=f(R,D,P)=k_{R}R+k_{D}D+k_{P}P \tag{34}\]  
where \(k_{R}\), \(k_{D}\), and \(k_{P}\) are the weights of PVCI related to predicted collision risk \(R\), violation degree \(D\), and violation penalty \(P\), respectively.
# Interference Challenges and Management in B5G Network Design: A Comprehensive Review
## 7 Conclusions  
A wide range of devices and applications will be supported by the next generation, which will raise demand for massive data rates with almost zero latency. The system should maintain the spectrum frequency and QoS for each user. Unfortunately, severe interference in wireless networks causes the wireless links to degrade and reduces the system performance, which leads to preventing its commercial deployment. In the B5G networks, the interference issues are expected to be more critical since there is continuously growing traffic, density, and size. The developments of interference management techniques result in increasing the knowledge and ability to understand and enhance the performance of the networks. This paper presents a comprehensive review of the interference management issues in B5G wireless networks and highlights the importance of interference issues in HetNets, D2D, UDNs and UAVs by focusing on the methodologies, strengths, limitations, and the upcoming challenges of the latest related works. Recent interference management issues in HetNets were reviewed by considering co-tier interference, cross-tier interference, and hybrid interference. Similarly, the paper addresses the issues of interference in D2D with a focus on power allocation, spectrum allocation, and hybrid strategies. Additionally, in UDNs, different approaches such as time domain, frequency domain, power domain and spatial domain were extensively discussed. Moreover, extensive discussion on the interference management in UAVs was provided by focusing on several interference schemes including drone interference, inter-cell interference, co-channel interference and mutual interference. Overall, several state-of-the-art studies along with open issues and prospective research directions related to the interference management issues in B5G were presented and discussed in this comprehensive review. This article is anticipated to serve as an effective and practical evolutionary guide for the design of next-generation wireless networks.  
Conceptualization: K.D. and K.A.N.; Methodology: O.T.H.A. and M.N.H.; Visualization: K.D. and R.H., Writing--original draft preparation: O.T.H.A. and M.N.H., Writing--review and editing: F.Q., A.N.A.W. and K.D.; Funding acquisition: F.Q. and A.N.A.W. All authors have read and agreed to the published version of the manuscript.  
This paper is supported by the Universiti Kebangsaan Malaysia Research Grant, GGPM-2019-065. This research is also supported by the Fundamental Research Grant Scheme (FRGS) from the Ministry of Higher Education, Grant no: FRGS/1/2018/TK04/UM/02/1 (FP091-2018A).  
Not applicable.  
The authors would also like to thank the respected Editor and Reviewer for their support.  
The authors declare no conflict of interest.
# Analysis of Grating Lobe Effects on GEO DSC Distributed Antennas
## 3 Analysis of Grating Lobes in DSC Distributed Antennas
### Grating Lobe Suppression
#### 3.3.2 Signal Domain Grating Lobe Suppression  
Considering the signal entering the grating lobe as interference, methods from the radar signal processing field can be applied to suppress the grating lobe in the signal domain. For instance, techniques such as deconvolution [21], cascaded Doppler filtering for beamforming [22], and frequency orthogonal signal deblurring can be employed to eliminate the interference caused by the grating lobe signal. Further analysis and research are required to examine the impact of these methods on communication signals. It is important to note that these methods come at the expense of increased signal processing requirements.
# D-Limonene: Promising and Sustainable Natural Bioactive Compound
## 6 Pharmacological Activity of D-Limonene: A Potential Natural Medicine
### Anti-Inflammatory Activity  
A number of studies have reported that D-limonene exerts anti-inflammatory and analgesic effects [160, 161] because it blocks the release of inflammatory mediators, inhibits vascular permeability, and reduces neutrophil migration [20]. [PERSON] et al. [162] found that D-limonene significantly inhibited formalin-injection-induced paw swelling and oxidative-stress-induced pain in mice and it inhibited RAW265.7 cell migration, suggesting that D-limonene has potential anti-inflammatory activity. In animal trials, D-limonene was shown to exert anti-inflammatory effects by reducing the production of pro-inflammatory cytokines, such as tumor necrosis factor-\(\alpha\) (TNF-\(\alpha\)), interleukin-6 (IL-6), and myeloperoxidase-dase, thereby increasing the concentration of antioxidant substances, such as glutathione peroxidase and superoxide dismutase, and maintaining the integrity of the inflammation site [17, 163]. In addition, D-limonene can inhibit inflammation induced by exogenous substances [158], such as inhibition of the increased activity of inflammatory markers triggered by carbon tetrachloride, including high-sensitivity corticotropin-releasing factor, IL-6, and TNF-\(\alpha\)[159].  
Moreover, D-limonene is cardioprotective and gastoprotective [20, 164], in addition to inhibiting the activity of cardiotoxicity biomarkers, such as alanine aminotransferase, lactate dehydrogenase, creatine kinase, creatine kinase MB, and the MAPK/NF-\(\kappa\)B pathway; to reduce the damage of myocardial infarction, it also prevents cardiac histopathological changes [159, 165]. Furthermore, oral D-limonene can increase local gastric mucosal defense mechanisms, such as mucus secretion, regulation of oxidative stress and inflammatory responses, and inhibition of the NF-\(\kappa\)B pathway, to exert gastoprotective effects [17]. Aside from inhibiting oxazolone-induced colitis and histopathological changes, it also reduces pain caused by oxidative stress and prevents gastric ulcers caused by ethanol [166].  
It has been demonstrated that D-limonene plays an active role in inhibiting the spread of cancer cells, acting on molecules such as Bcl-2, Bax, and caspases involved in various pathways, such as apoptosis pathways, PI3K/Akt signaling, autophagy, and vascular endothelial growth factor activity against cancer [167]. In addition, D-limonene has the ability to inhibit cancer cell growth; its combination with docetaxel induced more ROS production, thereby significantly enhancing the ability of docetaxel to induce apoptosis in cancer cells [168]; and D-limonene can induce apoptosis in cancer cells by inducing the mitochondrial death pathway and by inhibiting the PI3K/Akt pathway [169]. Other researchers have experimentally demonstrated that D-limonene has antifibrosis activity [170],prevents ischemia-induced brain injury, and alleviates acute kidney injury owing to its antioxidant and anti-inflammatory activities [171; 172].
## 6 Verification of the Proposed Methodology  
By applying the methodology, real data are obtained from industrial enterprises and outputs are compared with the assumptions we made during our design of the methodology. To ensure the correctness of the conclusions from the case studies, the industrial enterprises had to be a representative selection. Internal logistics was an extensive area in these companies, so a team solution (several logistics workers) was used in a structured interview for data collection. The main thing was that the evaluation was objective and in a large industrial company the team evaluation proved to be successful, which unifies both the knowledge and differences in the opinions of the experts. Consultations took place with experts in warehouse management, but also with the department for packaging processes. The head of the logistics department or their deputy was always a part of it.  
To maintain the representativeness of the verification of a smaller study, the methodology was applied to a total of 29 different industrial enterprises in the Czech Republic. The evaluated companies are either Czech or international companies that have several branches here. The verification deals with data analysis from the applied methodology  
Figure 2: Question for I10: Degree of automation.  
(especially values of the overall readiness, values of dimensions, sub-dimensions and their indicators), which it compares with general characteristics of the company. The characteristics that created the diversity of the evaluated companies include:  
* Automotive (13 companies), engineering (11 companies), electrical engineering (5 companies).
* Company size and number of employees
* Small and medium-sized enterprises, large enterprises.
* Type of production according to repeatability degree
* Piece/small series (8 companies), serial (14 companies), large series (7 companies).
* Manufacturing programme  
The sample analysed and evaluated includes large and medium-sized enterprises, but also several small enterprises with a small number of employees. The automotive sector is represented as a core industry. Engineering companies are also represented. For efficient production, for example, CNC machines can cooperate with industrial robots in the field of manipulation.
# Mechanical Properties of Disconnectable Coupling Joints for Steel Bracing under Eccentric Load
## 2 Numerical Model and Verification  
### Finite Element Model  
In the literature [22], the mechanical properties of DC joint specimens under axial load were studied experimentally, and the load-displacement curve and ultimate failure mode of the specimens--welded with Q235 steel [33]--were obtained [22]. The experimental results showed that the weld was not cracked. Therefore, the welds are set as a rigid connection in the numerical models. The geometric dimension of the numerical models is consistent with that of the specimens, as displayed in Figure 3.  
Figure 3: Dimensions of joint specimens.  
The yield strength, ultimate strength, Young's modulus and true stress-strain relationship of Q235 steel were obtained through experiments by the literature [34; 35]. The physical and mechanical parameters of materials are shown in Tables 1 and 2. A numerical model of DC joints was constructed in the FEM software package ABAQUS 2016/Standard. The numerical model was meshed with the C3D8I element. C3D8I is an improved version of the C3D8 element, and is an incompatible mode 8-node brick element. In the bending problem, the result equivalent to the quadratic element can be obtained with fewer elements in the thickness direction, which greatly reduces the calculation cost. A total of 22,508 meshes were obtained. The finite element model is listed in Figure 4a. The boundary condition of the model is only to restrict the movement of the flange plate completely. The rotation of the flange is free, as shown in Figure 4b. The numerical model adopts the contact form of surface to surface. The normal contact method adopts hard contact. Tangential contact is applied in a penalty calculation, and the friction coefficient is 0.2 [34]. To accurately simulate the interaction between the loading plate and end plate, the reference point RP-1 is established, and the outer surface of the end plate is connected to the center of RP-1 through kinematic coupling. A concentrated force is applied at RP-1, as shown in Figure 4c. Two steps are set, gravity is applied at the first step, and the concentrated force is applied at the second step. The concentration force increases from 0 to 6200 kN, and its increment is 1%.
# Risk-Based Access Control Model: A Systematic Literature Review
## 2 An Overview of Access Control
### Traditional Access Control Models  
Traditional access control (also called classical or static) approaches utilize rigid and predetermined policies to determine the access decision. These static and rigid policies provide the same decision in different circumstances. Although traditional access control approaches were successfully applied in different environments to solve various problems, these approaches are designed to provide a relationship between information associated with an access control rule logic and a resource for which access is requested. The implementation of an access control approach is subject to manipulation, which can range from an unexpected situation, including poorly written access policies to several malicious entities acquiring access to a set of existing accounts. Therefore, traditional access control approaches provide a set of advantages, but they also have drawbacks. One of these drawbacks is that it cannot handle unpredicted situations as they are based on static and predefined policies [10]. This inflexible approach cannot provide a robust security method for various dynamic and distributed systems such as IoT and Cloud Computing, which need more flexibility in accessing system resources. Instead, this static approach can be the best solution in situations where there is no way to collect a contextual feature/attribute while making the access request, for example the operating system.  
There are various traditional access control approaches including Access Control List (ACL), Discretionary Access Control (DAC), Mandatory Access Control (MAC), and Role-Based Access Control (RBAC). ACL is a list of specific objects that involve lawful users together with their access permissions. ACLs are utilized in various systems, for example, UNIX systems. Although ACL is an efficient and effective model, it is not scalable, in which it cannot cope with a huge list of objects and subjects. For DAC, it is mainly built for multi-user databases and systems with few previously known users. Granting access in DAC is mainly based on the subject identity and authorization that are determined using open policies. This enables the object's owner to allow access to this object to any subject. For MAC, the level of sensitivity of objects is used to categorize objects into several sensitivity levels--for example, sensitive, not sensitive, confidential, etc. Each object has a label that specifies the sensitivity level of that object. In addition, each subject has a label that specifies the object the subject can access [11; 12]. For RBAC, it involves three main components: users or subjects, roles (collections of permissions), and actions (activities performed on target resources) [13]. The basis of RBAC depends on roles, in which each role is accompanied by a set of access permissions. Each organization has several roles--for example, client, employee, manager, administrator, etc. A user can be a member of one or more roles, and a role can involve one or more users [14].