esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 NFP-Based Hybrid Placement Strategy  
### No-Fit Polygon  
This study adopted the method of constructing a no-fit polygon (NFP) to satisfy the constraint that the workpieces to be arranged do not overlap. Moreover, the inner polygon is introduced to determine whether all the workpieces to be arranged are completely contained within the boundary of the raw material sheet.  
There are three main construction methods for the no-fit polygon: (1) the Minkowski sum [18; 19; 20; 21], (2) the decomposition algorithm [22], and (3) the orbital sliding algorithm [23; 24; 25]. The Minkowski sum method has a high computational complexity and requires a large amount of computational resources. The execution time of the algorithm significantly increases as the polygon's number of vertices increases. The decomposition algorithm may be ineffective and unable to manage polygons with concave or convex structures due to the decomposition algorithm's potential to produce a large number of vertices and tangents.  
In comparison, the track sliding algorithm can accommodate a variety of irregular shapes and is relatively simple to implement. In addition, it has good applicability and versatility. Furthermore, by altering the parameters, this method can increase the accuracy by reducing the distance between the created NFP and actual components. The track sliding approach has a low computing complexity when compared to other methods, which allows for the quick completion of a significant amount of calculation work. Additionally, the independent calculation steps of this method make it simple to parallelize and boost the computational efficiency. The calculation of the NFP in this study utilizes the orbital sliding algorithm. The operational procedure is outlined as follows:  
Given two polygons \(\Omega_{i}\) and \(\Omega_{j}\), polygon \(\Omega_{i}\) remains fixed while a reference point (e.g., the top-right corner) is selected on polygon \(\Omega_{j}\). Polygon \(\Omega_{j}\) is then slid along the edges of polygon \(\Omega_{i}\) for one full rotation, keeping the edges of both polygons in contact and non-overlapping. Neither of the polygons undergo rotation throughout the entire movement. The trajectory of the reference point forms a new polygon, called \(NFP_{ij}\), as shown in Figure 2.  
If the reference point is inside \(NFP_{ij}\), the two polygons will overlap, denoted as \(\Omega_{i}\cap\Omega_{j}\
eq\varnothing\), which means that the packing solution is not feasible, as shown in Figure 3a. If the reference point is on the edge of \(NFP_{ij}\), the two polygons will touch only at the edges, and if the reference point is outside of \(NFP_{ij}\), the two polygons will not overlap, denoted as \(\Omega_{i}\cap\Omega_{j}=\varnothing\). Both cases satisfy the condition and the packing solution is feasible, as shown in Figure 3b,c.  
Figure 2: NFP generation process.
# Resilience Evaluation of Multi-Path Routing against Network Attacks and Failures
## 1 Introduction  
### Motivations  
The Internet was not designed to maintain high availability in the face of malicious activities. Recent patches to improve Internet security and availability have been constrained by the current Internet architecture design. As network-based attacks on availability continue to increase each year [1], an improvised Internet architecture should offer availability and security based on its design, provide incentives for deployment, and consider economic, political, and legal issues at the design stage [2].  
Currently, the Internet provides single path (SP) routing, which lacks a rapid mitigation mechanism to counter Internet hazards, such as network congestion, link failures, or DDoS attacks. Under network congestion or DDoS attacks, the performance of the Internet, such as latency or loss rate, is highly affected, and, in the case of a link failure, it can take several minutes until failover [3]. Fault recovery of the border gateway protocol (BGP) at times takes several minutes before the routes converge to a consistent form [4]. Path outages even lead to significant disruptions in communication, which may last tens of minutes or longer [5; 6; 7]. However, if such a network congestion or network failure occursfrom a link that an autonomous system (AS) cannot handle, sophisticated operations or cooperation among AS administrators will be required. Detailed routing information is maintained only within a single AS. The information shared with other providers and ASes is heavily filtered and summarized using BGP running at the border routers between ASes [8].
## 3 Test Results and Analysis
### Effect of Biopolymer on Compressive Strength
#### 3.1.4 Failure Behavior  
The failure modes of GRS treated with different biopolymers in unconfined compressive tests are presented in Figures 11-13. From the Figures, it is evident that as the biopolymer content increases, the samples exhibit more cracks. Furthermore, as the content continues to rise, distinct shear bands become visible in the samples. This suggests that biopolymer content plays a significant role in influencing the compressive behavior of GRS. This failure characteristic is closely linked to the action mechanism of biopolymers in GRS. The addition of biopolymers alters the bonding mechanisms and stress distribution between soil particles. At low concentrations, more cracks are observed within the soil, indicating that the structural failure is more dispersed. This may be due to biopolymers acting as binders or fillers, which changes how soil particles are interconnected. As the biopolymer content increases, the bonding strength between soil particles gradually improves. However, this enhanced bonding can also lead to uneven stress distribution within the soil. As the biopolymer content rises further, distinct shear bands form in the sample under higher stress. The appearance of shear bands signifies that internal stress within the soil becomes concentrated, leading to preferential failure along the shear band areas. Under different curing times, the failure modes of the samples show no significant differences. This suggests that curing time has a minimal effect on the failure modes observed in the unconfined compressive tests.  
Figure 11: Failure behavior of XG-treated GRS in UCS test at different curing times: (**a**) 0; (**b**) 3; (**c**) 7; and (**d**) 14 days.
# Vibration Responses of a Coaxial Dual-Rotor System with Supporting Misalignment
## 3 Simulation and Discussions
### Effects of the Coefficient of the Harmonic Component  
The bearing load is a static force to the non-rotating observer. However, it acts as a periodic load on the rotating rotor. According to the Fourier analysis, any periodic function or periodic signal can be decomposed into the sum of a (possibly infinite) set of simple oscillating functions, namely sines and cosines. [PERSON] [37], [PERSON] [38], and [PERSON] [39] et al. decomposed the periodic misalignment force into the sum of harmonic components \(1\times\), \(2\times\), \(3\times\), and \(4\times\). The four harmonic components have equal weight coefficients. In Section 2.2, the weight coefficients of these four harmonic frequencies are set to 1, 1/4, 1/9, and 1/16, respectively, because the latter is in line with the actual situation of a dual-rotor system. The weight coefficients of the four harmonic components are set to be the same in order to compare the difference between the two cases. The dynamic bearing load caused by misalignment can be expressed as follows:  
\[\mathbf{F}_{b}^{j}=\left[\begin{array}{l}0\\ Y_{i}(\cos(\Omega_{1}t)+\cos(2\Omega_{1}t)+\cos(3\Omega_{1}t)+\cos(4\Omega_{1 }t))\\ 0\\ 0\end{array}\right]^{T} \tag{10}\]  
The orbit and frequency spectrum of each bearing are shown in Figures 15 and 16 when the weight coefficients of the four harmonic components are equal. Comparing the two figures with Figures 7-9, it is shown that the amplitudes of \(2\times\), \(3\times\), and \(4\times\) at the three bearings have all increased significantly. The maximum vibration frequencies of  
Figure 14: The spectrum of Bearing 3 and Bearing 4 (without bearing damping).  
Figure 13: The spectrum and the orbit of Bearing 1 (without bearing damping).  
Bearing 1 and Bearing 3 of the inner rotor change from 1\(\times\), 1.6\(\times\), and 2\(\times\) to 2\(\times\), 3\(\times\), and 4\(\times\). The shape of the orbit also becomes more complicated due to the large change in the vibration frequency component. The experimental results in Section 4 indicate that the non-uniform weight coefficient model (Equation (9)) is more reasonable than the equal weight coefficients model (Equation (10)).
# Influence of Oak Chips and Oak Barrel Ageing on Volatile Profile in Chardonnay Wine of Romania
## 3 Results
### Volatile Profile of White Wines Aged with Non-Toasted and Light-Toasted Oak Chips
#### 3.2.5 Volatile Phenols  
The total content of phenolic volatiles in Chardonnay wines, calculated by adding up the individual concentration of each compound, ranged from 365 to 463 ug/L for N1M-N3M wines, from 393 to 505 ug/L for L1M-L3M wines and from 350 to 468 ug/L for BAR1M-BAR3M. Among methods of ageing, light toasting led to the highest values, and non-toasted to the lowest ones. Volatile phenols that resulted from wood to toasting, have significantly higher values in the wines of L1M-L3M variants (_p_-vinyl guaiacol--58-65 ug/L, acetovanillone--143-171 ug/L and vanilla 133-139 ug/L), compared to the variants from non-toasted wood.
# Mixed Reality Enhanced User Interactive Path Planning for Omnidirectional Mobile Robot
## 5 The Description of VFH* Algorithm
### Modification of VFH* Algorithm  
#### 5.2.1 The Threshold Setting  
After generating the polar histogram, the selection of threshold values is very important to determine the direction. If the threshold is too high, the mobile robot will neglect some obstacles on the map, leading to collisions. At the same time, a high threshold will produce more candidate directions and increase the calculation load. If the threshold is too low, the choice of candidate direction will be reduced. When a narrow, passable road section is encountered, the passable direction is neglected by a low threshold, precluding smooth movement. Besides, when virtual obstacles are added into the map, the range of polarity will also increase. Therefore, the threshold of dynamic change shown in the Figure 4 is adopted in this paper. When the mean value of polar coordinates in the polar histogram is less than or equal to the specified value, the small threshold value is selected. When it is greater than the specified value, the large threshold is selected. The change of threshold is related to the mean value of polar coordinates, as shown below:  
\[T_{1}=\left\{\begin{aligned} & t_{low}\quad(\sum_{n}p_{n}\leq \delta_{p})\\ & t_{high}\quad(\sum_{n}p_{n}>\delta_{p})\end{aligned}\right. \tag{13}\]  
where \(p_{n}\) is the polar histogram of each sector and \(\delta_{p}\) is a parameter that distinguishes the size of the density. In the experiment, we used \(\delta_{p}=1.6\), \(t_{low}=1.2\) and \(t_{high}=2\).  
There is another special case to consider when selecting a threshold. When the target point is located between the obstacle and the current position of the robot, and the obstacle is within the detectable range. In this case, the direction to the target point is detected as impassable, so the robot cannot reach the target point eventually. To avoid the result, we need to set a special and large threshold for this case to make the direction of the target point passable. Combined with the previous optimization process, the selection of the threshold is as follows:  
\[T_{2}=max(T_{1},\frac{\gamma}{d_{rt}^{2}}) \tag{14}\]  
where \(d_{rt}\) is the distance from the mobile robot to the target point, and \(\gamma\) is a custom parameter that determines the threshold change condition, in this experiment, \(\gamma=0.5\).
# Load-Carrying Capacity of Bailey Bridge in Civil Applications
## 5 Results and Discussion
### Main Girders
This example confirms that in the case of shorter spans of the three-girder alternatives of the Bailey bridge, the two inner main girders (i.e., the inner and the middle ones) are much more loaded than the outer one. The analysis revealed an additional requirement to increase the buckling resistance of first two compressed diagonals of the inner girder. As the load-carrying capacity based on resistance of the cross-section was sufficient enough, a \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Exclusive** & **Configuration** & **TS-12** & **TS-18** & **TS-21** & **DD-24** & **DD-27** & **TD-33** & **TD-36** \\ \cline{2-9}
**Coapacity** & **Span Length [m]** & **12.192** & **18.288** & **21.336** & **24.384** & **27.432** & **33.528** & **36.576** \\ \cline{2-9}
**[tons]** & **Predominant Stress** & \(V_{e}\) & \(V_{e}\) & \(V_{e}\) & \(V_{e}\) & \(V_{e}\) & \(V_{e}\) & \(V_{e}\) \\ \hline \multirow{3}{*}{Chords} & T + B (bottom) & 53.1 & 47.7 & 37.0 & 45.7 & 40.0 & 46.9 & 40.0 \\  & C (top) & 76.2 & 50.6 & 42.0 & 59.8 & 51.4 & 55.2 & 47.8 \\ \cline{2-9}  & C & 33.2 & 34.1 & 33.4 & 46.5 & 45.9 & 47.4 & 47.0 \\ \cline{2-9}  & T & 56.9 & 64.0 & 60.8 & 78.5 & 78.2 & 81.2 & 80.9 \\ \cline{2-9}  & C & 28.9 & 29.9 & 29.3 & 40.5 & 39.8 & 41.1 & 40.6 \\ \cline{2-9}  & T & 64.6 & 66.7 & 65.3 & 82.4 & 82.2 & 85.2 & 85.0 \\ \cline{2-9}  & C & 46.2 & 44.7 & 45.1 & 49.2 & 48.8 & 51.8 & 52.1 \\ \cline{2-9}  & T & 62.5 & 64.2 & 61.0 & 91.0 & 92.0 & 93.2 & 93.8 \\ \cline{2-9}  & C & 40.6 & 39.0 & 38.9 & 41.9 & 41.5 & 45.2 & 44.6 \\ \cline{2-9}  & T & 73.2 & 75.3 & 71.3 & 98.1 & 99.1 & 100.4 & 101.1 \\ \cline{2-9}  & C & 42.1 & 30.7 & 30.7 & 51.2 & 51.3 & 51.8 & 56.2 \\ \cline{2-9}  & T & 106.2 & 99.0 & 87.7 & 129.5 & 125.6 & 152.8 & 148.0 \\ \cline{2-9}  & C & 75.8 & 76.3 & 74.6 & 68.9 & 70.1 & 77.0 & 76.5 \\ \cline{2-9}  & T & 80.3 & 71.2 & 67.2 & 87.6 & 80.9 & 79.6 & 76.7 \\ \cline{2-9}  & Pii joint & S + B & 68.8 & 72.3 & 73.4 & 74.4 & 75.1 & 76.2 & 76.7 \\ \cline{2-9}  & Chord bolts & S + T & & & & 113.2 & 109.8 & 115.4 & 114.1 \\ \hline \hline \end{tabular} Nomenclature for as yet undefined predominant stress: T—tension; C—compression; B—bending; S—shear.  
\end{table} 
Table 4: Exclusive load-carrying capacities of main girders parts. Figure 16: Example of enhancement of load-carrying capacity by arrangement of panels. simple enhancement of stiffness of these diagonals for in-plane buckling could be suggested, as shown in Figure 16.
## 2 Materials and Methods
### Machine Learning Algorithms and Susceptibility Modeling
#### 2.6.1 Random Forest (RF)  
RF is an ensemble learning method that works on the principle of generating a large number of random trees to minimize the risk of overfitting [56]. RF does not require rescaling and resampling the data, as this model can handle the missing values very easily by building a DT. A DT, being a binary model, is constructed by dividing input data into an increasing number of homogenous nodes. The number of trees (_ntree_) and number of variables used to split each node (_mtry_) are the two main parameters used to tune and train the RF models. Considering the size and type of the sample data, the optimal values of these parameters can be found with the help of different methods [57] to achieve higher performance in modeling. In this study, a grid-based search method [58], a widely accepted approach for parametrization, was utilized for tuning the models. The modeling was performed through the 'caret' and 'randomForest' packages in R.
# Merging Ontologies and Data from Electronic Health Records
## 4 Description of Our Approach
### Data Acquisition
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* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] Using Knowledge Graph Structures for Semantic Interoperability in Electronic Health Records Data Exchanges. _Information_**2022**, _13_, 52. [CrossRef]
* [PERSON] et al. (2005) [PERSON]; [PERSON]; [PERSON] The openEHR foundation. _Stud. Health Technol. Inform._**2005**, _115_, 153-173. [PubMed]
* [PERSON] et al. (2011) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] The ISO/EN 13606 standard for the interoperable exchange of electronic health records. _J. Health. Eng._**2011**, \(2\), 1-24. [CrossRef]
* [PERSON] (2007) [PERSON] An overview of interoperability standards for electronic health records. In Proceedings of the Integrated Design and Process Technology, Antalya, Turkey, 3-8 June 2007. * [PERSON] and [PERSON] (2013) [PERSON]; [PERSON] [PERSON] HL7 FHIR: An Agile and RESTful approach to healthcare information exchange. In Proceedings of the Symposium on Computer-Based Medical Systems, Porto, Portugal, 20-22 June 2013; pp. 326-331. * [PERSON] (2008) [PERSON] HL7-Based Data Exchange in EHR Systems. In Proceedings of the Ph.D. Conference, Jizerka, Czechia, 29 September-1 October 2008. * [PERSON] et al. (2001) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] The HL7 clinical document architecture. _J. Am. Med. Inform. Assoc._**2001**, \(8\), 552-569. [CrossRef]

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# DCO-MAC: A Hybrid MAC Protocol for Data Collection in Underwater Acoustic Sensor Networks
## 5 Approximate Performance Analysis  
According to the renewal theory [22], the average channel utilization can be given as the ratio of the average data transmission time and total transmission time. That is, as follows:  
\[S=\frac{\overline{U}}{\overline{B}+\overline{I}} \tag{9}\]  
where \(\overline{B}\) is the expected time duration of a busy period when the channel is being utilized. \(\overline{I}\), the expected time duration of an idle period, denotes the time interval between two consecutive busy periods. \(\overline{U}\) denotes the expected time duration when the channel is used to transmit the data packets.
## 6 Conclusions  
With the rapid growth in number of vehicles and the complexity of the town's roads, previous studies have proposed many routing protocols that are used in VANETs, such as the LAR protocol. However, applying the conventional LAR protocol directly in VANET ignores two essential aspects, i.e., (1) the LAR does not exploit the fact that nodes in VANET do not have pure random movement, (2) the nodes in conventional LAR protocol use the location information of the destination node before selecting the route location, which is most likely to be expired because of the fast movement of the nodes in the VANET environment. Therefore, this paper developed an estimation based on a heuristic RALAR approach. The idea is to reject the bad GPS location data and accept good ones based on a moving rectangular zone according to the node's mobility model. The proposed RALAR protocol was optimized using an efficient GA optimization technique to select the most suitable timeout variable. The proposed RALAR protocol was compared with the conventional KALAR and LAR protocol in terms of performance metrics such as PDR, average E2E delay, routing overhead, and average energy consumption. The results proved that the performance of the proposed heuristic RALAR protocol outperformed the KALAR and LAR protocol in terms of regular network performance measures in the VANET environment. The proposed RALAR protocol also provides a position estimation subsystem that can be used with any other location-based routing protocol or even location-based service (LBS) for the vehicle in the VANET environment.
## 3 Finite Element Model and Experiment
### Finite Element Model  
ABAQUS/standard was used to establish the finite element models of bolted joints. The simulation conditions (e.g., material parameters, sizes, boundaries, loads, and excitations) were set to be the same as the experimental conditions.  
Each model consisted of two beams connected by an M6 bolt and two washers (Figure 2a). The interactions between the beam-beam pairs and washer-beam pairs were defined as normal hard contact with penalty friction for contact, and the bolt-washer pairs were tied. Aluminum and composite beams were investigated in this work, whose connect modes are denoted as Al-Al and C-C. The geometric and material parameters are shown in Table 1 and Figure 2b.  
The simulation process consisted of two steps, viz., the bolt preload application and VAM propagation (Figure 2c). One end of the beam was clamped to make the whole structure a cantilever. The bolt preload was set as the axial compressive stress applied to the center of its cross-section, whose amount was equivalent to the applied torque in the experiment (calculated by Equation (1)). After the preloading of the bolt, continuous LF and HF sine waves were simultaneously excited at the free beam, and the transmitted waves were detected by an output node at the clamped beam. The excitations were selected by the modal tests to ensure the measurable out-of-plane displacement of the joints. For the Al-Al joints, LF = 0.99 kHz and HF = 14.24 kHz. For the C-C joints, LF = 0.76 kHz and HF = 14.99 kHz. The minimum time step interval was 5 us, and the sampling frequency was 200 kHz. In order to precisely capture the waveform, the grids were meshed to satisfy the minimum requirements, i.e., eight nodes per shortest wavelength [30].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Material Type** & **Elasticity Modulus \(E\) (GPa)** & **Poisson’s Ratio \(\
u\)** & **Density (kg/m3) \(\rho\)** & **Friction Coefficient \(\tau\)** \\ \hline Aluminum & 75.6 & 0.33 & 2700 & 0.1 \\ \hline \multirow{3}{*}{Composites} & \(E_{1}/E_{2}/E_{3}\) & \(\
u_{11}/\
u_{13}/\
u_{23}\) & & \\ \cline{2-5}  & 130/7/7 & 0.32/0.32/0.45 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Material parameters of the bolted joints.