esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Development of the Designed Optical Module  
To validate the operating principle of the optical module designed in this study, a 3-axis machine tooling equipment, VM 6500 (DN solutions, Changwon-si, Republic of Korea), was used to manufacture the CFL array plate and lightguide plate. However, when designing the CFL array plate, although the ideal shape of a cylindrical Fresnel lens was considered, the machining freedom of the device was not high enough to properly implement the vertical walls of each zone of the Fresnel lens. Therefore, as shown in Figure 8a, the draft angle of each zone was changed to \(20^{\circ}\) for manufacturing. Figure 8b illustrates the shape of the CFL array plate and the modified design shape together. As shown in Figure 8b, while the pitch of the manufactured CFL array, the radius to each zone, and the wall angle of each zone were generally well implemented, fillet curvature occurred at the corners of each zone.  
A photograph of the assembled optical module prototype, consisting of the machined CFL array plate and the lightguide plate integrated with the CCPC, is presented in Figure 9. As \(\Delta S\) was set to 1.3 mm in the designed optical module shown in Figure 4, the total thickness of the module is 15.3 mm, while the thickness of the manufactured optical module ranged from approximately 15.25 to 15.27 mm. Taking the fabrication errors of the CFL shape and the thickness deviation of the optical module into account, the key parameters were recalculated according to the variations in \(\alpha\) and \(\beta\). In this analysis, for the shape of CFL, draft angles and edge fillet radii were set to \(20^{\circ}\) and 0.1 mm, respectively. Figure 10 illustrates the transmittance through the module and light concentration efficiency  
Figure 8: Modified design of CFL (**a**) and its fabrication result with the designed profile (**b**).  
Figure 7: Transmitted power through the module and the concentrated power on the CCPC end along with \(\alpha\) and \(\beta\): (**a**) result of variation in \(\alpha\) and (**b**) result of variation in \(\beta\).  
as a percentage of the incident optical power of 5 W, compared to the characteristics of an ideal optical module.  
Comparing to the results of the ideal module, the optical module considering fabrication deviations reveals that there is approximately a 5% decrease in the concentrated optical efficiency at the CCPC end surface for \(\alpha\) and \(\beta\) variations in the maximum efficiency range, \(\mid\alpha\mid\) \(<\) 15\({}^{\circ}\) and \(\mid\beta\mid\) \(<\) 1.5\({}^{\circ}\). Furthermore, compared to the results for the ideal module, the transmittance through the module shows a similar level of transmittance for \(\alpha\) variations within the range of \(\mid\alpha\mid\) \(<\) 40\({}^{\circ}\), while for \(\beta\) variations, it exhibits approximately a 5% higher transmittance in the minimum transmittance range of \(\mid\beta\mid\) \(<\) 1.5\({}^{\circ}\).
## 4 Financial and Environmental Analysis  
### Financial Feasibility  
To assess the financial viability of incorporating the PCM in the studied building model described so far, we first need to determine the initial cost of incorporating these materials including the installation cost in the external walls. Afterwards, we need to subtract it from the cost of incorporating the conventional insulation material in the baseline building model, which is a 2.5 cm panel of XPS extruded polystyrene. The annual energy cost saving is then calculated by multiplying the yearly energy savings by the electricity tariff in Jordan. Finally, the expenses and the energy cost savings are utilized to estimate the payback period, to determine whether the application of PCMs in buildings is financially viable.  
Accordingly, the price of a 3.7 cm panel thickness of BioPCM\({}^{\circledgtr}\) M91/Q23 including the installation cost in the external walls of the building is 36.65 \(\upmu\)m\({}^{2}\). The total gross area of the external walls is 179.60 m\({}^{2}\). Therefore, the total cost of incorporating the external walls of the building with BioPCM\({}^{\circledgtr}\) M91/Q23 is USD 6582.54. Additionally, the cost of installing a 2.5 cm panel of extruded polystyrene in the external walls of the building is 11.28 USD/m\({}^{2}\). Therefore, the total cost of incorporating the extruded polystyrene insulation in the external walls of the building is USD 2025.40. Subtracting USD 6582.54 from USD 2025.40 will result in USD 4557.15 as a net expense.  
The energy use intensity difference per total floor area for Amman city, as illustrated in Table 7, is 26.6 kWh/m\({}^{2}\)/year. Therefore, the annual energy savings for the PCM-incorporated building after multiplying 26.6 kWh/m\({}^{2}\)/year by the total floor area of the building will result in 5476.14 kwh energy saved per year. This is translated to approximately USD 1150 saved annually at an electricity tariff of 0.21 USD/kWh [57]. The payback period is then estimated by dividing the initial cost of incorporating BioPCM\({}^{\circledgtr}\) M91/Q23 in the external walls of the building by the annual energy-saving amount, resulting in a payback period of 4 years, affirming the financial feasibility of PCM application and its economic benefits.  
In Oracle, the price of electrical energy is approximately USD 0.3 per kWh. For heating, the city utilizes a district heating system that supplies thermal energy at USD 86 per Gcal (equivalent to USD 0.074 per kWh) [58], posing a question about the cost-effectiveness of PCM use considering the 5.64% energy savings observed in simulations. Notably, the heating energy price is subsidized by the City Council of Oracle, which influences the economic feasibility of PCM integration.
## 2 Architectural Framework of IBSN and Its Components
### Communication Strategies
#### 2.5.4 Routing  
Routing within IBSN is plain since the number of nodes in the network is less and topology is simpler than conventional WSN. However, the physical channel is highly dynamic due to human behavior and rapid changing environment. A good routing mechanism must be able to handle the dynamic changes of the link quality between the nodes in compliance with the IEEE 802.15.6 standard of a physical layer.
## 5 Experiment Results and Analysis
### Quantitative Results
However, when our method was implemented in an outdoor environment, it sometimes faced difficulties in detecting and removing shadowed regions. For this reason, original object shapes might be distorted, or foreground regions might be removed as shadow pixels, as demonstrated in Figure 8b. In contrast, if the moving object and background surface have pixel intensities with large differences, the suggested method could remove shadow pixels without distortion, as demonstrated in Figure 8a. In our future research, we are going to address that problem by applying neural network and deep learning approaches. Clearly, the proposed method still works successfully when tracking moving objects in all types of indoor environments (e.g., conference halls, offices, or indoor sports game locations).
## 5 Classification of EV Charging Infrastructures
### Hybrid-Microgrid-Based EV Charging Infrastructure  
The hybrid-microgrid-based EV charging infrastructure incorporates both DC and AC fast-charging techniques. Moreover, the infrastructure includes charging systems that are available to the general public, as well as those specifically designated for personal use. Public charging stations are frequently powered by solar or wind energy and strategically positioned in communal areas, such as parking lots, streets, and other publicly accessible spaces. Private charging systems are typically powered by grid electricity or a hybrid combination of grid and renewable energy sources. These systems are commonly installed in residential dwellings, commercial buildings, and other private settings. The hybrid charging infrastructure for EVs may include rapid charging systems that offer a greater power output in comparison to traditional charging systems. Rapid charging systems, which are commonly found at public charging stations, possess the ability to fully charge an EV within minutes, as opposed to the significantly longer timeframe of several hours [86]. Figure 22 depicts a standard hybrid microgrid configuration, showcasing both grid-connected and non-grid-connected structures. This setup utilizes various energy sources, such as solar power, wind power, diesel generators, and fuel cells, along with energy storage devices, to establish an effective charging infrastructure.
## 4 Simulation Results
### Discussion of Results  
Some observation based on the simulation results can be made.  
1. It turned out that for the control algorithm in the QV version, the same set of gains allows the tracking task to be carried out for both two different trajectories and two vehicles with significantly different dynamics. Such information proves a certain universality of a correctly selected set of controller gains.
2. The coefficients that give satisfactory performance using the QV algorithms can be used to select the gains of a classic controller. For example the obtained gains set using QV \(k_{v_{x}}=k_{v_{y}}=4\), \(k_{p_{x}}=k_{p_{y}}=1\), \(k_{l_{x}}=k_{l_{y}}=0.25\), suggests that for ROPOS the gains for the CL algorithm may be chosen as follows: \(k_{v_{x}}=k_{v_{y}}=20\div 30\), \(k_{p_{x}}=k_{p_{y}}=5\div 10\), \(k_{l_{x}}=k_{l_{y}}=1\div 2\). For example the obtained gains set using QV \(k_{v_{x}}=k_{v_{y}}=4\), \(k_{p_{x}}=k_{p_{y}}=1\), \(k_{l_{x}}=k_{l_{y}}=0.25\) for XX AUV model, suggests that the gains for the CL algorithm may be chosen as follows: \(k_{v_{x}}=10\div 20\), \(k_{v_{y}}=5\div 10\), \(k_{p_{x}}=3\div 8\), \(k_{p_{y}}=1\div 5\), \(k_{l_{x}}=1.0\div 1.5\), \(k_{l_{y}}=0.2\div 0.5\).
3. Both algorithms (QV and CL) make it possible to track a desired trajectory with the use of small values of applied forces and torques, which is also consistent with the results shown in [56].
4. It was found that significant changes in the vehicle dynamic parameters do not cause a significant deformation of the lateral velocity (the remaining quasi-speeds are equal to the velocities in the respective directions of movement).
# A Review of Low-Frequency Active Vibration Control of Seat Suspension Systems
## 2 Seating Systems with Active Suspension
### Experiments with Prototypes
#### 2.1.1 Pneumatic Actuator
(2014) [54] proposed an adaptive controller for an active seat suspension (Figure 7). This is a multicontroller approach to control the entire system, where the primary controller is used to calculate the force required to reduce the vibration. The inverse model is used to calculate the effective area of the proportional control valve. The application of the inverse model in the controller can directly derive the input signal according to the required force. The Proportional-Derivative (PD) predictor is used to generate the corresponding control signal to speed up the controller. Finally, the adaptive mechanism is able to estimate the load mass based on the inflation and deflation of the pneumatic spring. This active seat suspension is able to achieve good vibration control performance compared with a passive system, having a load range from 50 to 150 kg at a resonant frequency of 1.3 Hz. The advantage of this controller is that the adaptive control itself makes the system quickly return to stability by estimating the initial suspended load. The shortcoming of the controller is that the complexity of the multicontroller may delay signals, and in the case of high road roughness, the vibration control performance of the seating system is degraded. Figure 5: A seating system with an active pneumatic spring suspension [52]. Figure 6: Schematic of the triple feedback loop controller [52]. [PERSON] et al. (2018) [55] developed a horizontal active seat suspension using pneumatic muscles (Figure 8) for horizontal vibration control. This original control system (Figure 9) combined a primary controller and an inverse model module to provide a control signal to the pneumatic muscles, and a PD control module was used to speed up the signal. According to the final results, the proposed active seat suspension performed better than a passive seat suspension for vibration attenuation in the 1-10 Hz frequency range. Figure 8: (**a**) The pneumatic muscle at the nominal length and (**b**) After contraction [55]. Figure 7: Schematic of the multicontroller [54]. Figure 9: Block diagram of the control structure of the vibration control system [55]. The utilization of pneumatic springs as actuators has some advantages, such as being simple, reliable, and compact. At the same time, their low response speed, poor control precision, and dependence on a compressor pipeline hinder their actual use.
# Applications of Satellite Radar Imagery for Hazard Monitoring: Insights from Australia
## 3 Hydrological Hazards  
### Flooding  
Severe flooding is common in Australia: tropical cyclones impact parts of the country (generally north of \(-25^{\circ}\) S), and the flat topography, particularly along the coasts, results in regular inundation (e.g., [21]). Optical sensors such as MODIS (MODerate Resolution Imaging Spectrometer) provide imagery for flood mapping at 250-1000 m spatial resolution twice daily and have been implemented for operational flood monitoring in Australia (e.g., via the 'FloodMap' platform: [22]). However, floods are inherently associated with precipitation and cloud cover that impacts the imaging capability of optical sensors. Therefore, the all-weather, all-time-of-day imaging capability of SAR is advantageous in these conditions, offering observations at significantly higher spatial resolutions (few ms-tens m: Table S2). Open water strongly scatters the SAR wave energy, which usually leads to a contrasty differentiation between water and all other land cover types in SAR images. In addition, long-wavelength SAR (e.g., L-band: \(\sim\)23 cm: see examples in Table S2) is also able to partially \"see\" through vegetation, identifying inundation beneath canopy-cover (e.g., [23]) and benefiting hydrodynamic models of flooding in mangroves, wetlands, and other sensitive ecosystems (e.g., [24]).  
Despite these advantages, the use of SAR for this purpose in Australia includes only ad hoc validation case studies [22] and international response to large-scale flooding events. The International Charter Space and Major Disasters has been activated by Geoscience Australia in response to tropical cyclones (Queensland: January 2011, February 2015, March 2017) and flash flooding (Lachlan River, New South Wales: 2016). At these times, the Copernicus Emergency Management Service (EMS) and other value-adding agencies have provided additional SAR acquisitions and flood-map products (e.g., the German Aerospace Center automated flood mapping: [25]). Geoscience Australia has also carried out data analysis on request and produced flood maps using simple thresholding of intensity data in single SAR images [26], with operational workflows utilising Sentinel-1 currently under development as part of DEA.
## 3 Pattern Selection with SymCHM
### SymCHMMerge: Improved Pattern Selection
#### 3.2.1 Merging Redundant Patterns  
Since parts in our model are learned in an unsupervised manner, several parts may represent similar and overlapping patterns (e.g., patterns shifted by a few notes). Inhibition reduces redundant activations of such parts, however it is usually not enforced strongly, as it could overly reduce the number of activations and found patterns. To reduce the number of such overlapping patterns, we merge them into single, longer patterns.  
Let \(\pi(A(P_{i}^{n}))\) represent a pattern occurrence defined by the projection \(\pi\) of the activation \(A\) of the part \(P_{i}^{m}\) onto the layer \(\mathcal{L}_{0}\). \(\Psi_{i}^{n}\) represents the set of all such pattern occurrences discovered by activations of the part:  
\[\Psi_{i}^{n}=\bigcup_{k}\{\pi(A_{k}(P_{i}^{n}))\}. \tag{11}\]  
Two pattern occurrences \(a_{i}\) and \(a_{j}\), produced by the parts \(P_{i}^{n}\) and \(P_{j}^{m}\), are taken to be redundant, if they overlap significantly. We express this by calculating the Jaccard similarity coefficient and compare it to a threshold \(\tau_{R}\):  
\[\begin{split} a_{i}=\pi(A(P_{i}^{n})),a_{j}=\pi(A(P_{j}^{m}))\\ J(a_{i},a_{j})=\frac{|a_{i}\cap a_{j}|}{|a_{i}\cup a_{j}|}>\tau_ {R}.\end{split} \tag{12}\]  
We aim to merge redundant pattern occurrences of two parts if they frequently produce overlapping patterns. Therefore, we calculate the proportion of such patterns produced by the two parts as:  
\[\frac{1}{|\Psi_{i}^{n}|+|\Psi_{j}^{m}|}\sum_{a_{i}\in\Psi_{i}^{n}}\sum_{a_{j} \in\Psi_{j}^{m}}|J(a_{i},a_{j})>\tau_{R}|. \tag{13}\]  
If the proportion exceeds a threshold \(\tau_{M}\), all redundant pattern occurrences of the two parts are merged.  
For evaluation, the thresholds \(\tau_{R}\) and \(\tau_{M}\) were both set to 0.5, meaning that pattern occurrences produced by two parts had to share at least 50% of events in the input layer and appear together in at least 50% of cases, to be merged.
## 7 Discussion  
This paper presents the results of a geological survey conducted on the southern slope of the open-pit slope of the Yinshan Mine, utilizing UAV mapping technology and the digital structural surface recognition method. Additionally, a production blasting vibration test was performed to analyze the influence of blasting vibration on the rock mass of the slope. Using FLAC3D software, the impact of the underground goaf on the stability of the slope was analyzed, and the limit balance analysis method was applied to evaluate the status quo of the open-pit slope and the stability of the design excavation slope. The following results were obtained:  
1. The southern slope of the mining area primarily exhibits a medium-large inclination angle structural surface. The development of thousands of rock fragments in each area was traced from the statistical results of joint fractures in the entire measurement site, where the average joint spacing was found to be 5-30 m, and the average joint density was 0.033-0.2/m.
2. A total of three blasting vibration tests were conducted using the blasting vibration monitoring system, in accordance with the specification. Based on the monitoring results, the maximum one-stage charge of the three blasts was 410 kg, and the measured value did not exceed 24 cm/s. The analysis of the measured data allowed for the blasting vibration attenuation law for the Yinshan Mine to be obtained, and the vibration velocity attenuation law formula was fitted.
3. According to the three-dimensional finite element analysis, the entire slope exhibits no large range of plastic zone damage, with only a small range of plastic zone generated on the step slope above the location of the empty area, which is mainly shear failure.
4. A typical section was selected to carry out the limit equilibrium analysis. Load combination I (considering only the self-weight stress) and load combination II (which includes the blasting vibration force) of the current slope meet the safety factor of 1.20, and the overall slope is stable. However, the designed excavation slope is near the  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Present Safety Slope**} & \multicolumn{3}{c}{**Planned Excavation Slope**} \\ \multicolumn{2}{c}{**Coefficient**} & \multicolumn{3}{c}{**Planned Excavation Slope**} \\ \multicolumn{2}{c}{**Parameters**} \\ \hline
**Load** & **Load** & **Load** & **Load** & **Final Slope** & **Maximum Height** \\
**Combination I** & **Combination II** & **Combination I** & **Combination II** & **Angle (\({}^{\circ}\))** & **(m)** \\ \hline
1.473 & 1.409 & 1.130 & 1.081 & 44.8 & 540 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Planned excavation slope safety factor.  
Figure 17: Planned excavation slope safety factor. (**a**) Load combination I. (**b**) Load combination II.  
critical value of the safety factor specified in the code under the conditions of load combination I and load combination II, and, thus, poses a certain risk of instability.
# Vehicular Visible Light Communication for Intersection Management +
## 2 Related Works
To determine the delay, the number of vehicles queuing in each cell at the beginning and end of the green time is determined by VLC (V2V2I) observation. A standard four-legged intersection is compared with the split intersection and a dynamic phasing diagram flow is presented based on a matrix of states. The durations of movable states can be entered for any state at a dynamic time. It is possible for the IM to execute the following actions based on the request information: modify the durations of the cycle; enter the fixed times; change the durations of states with the transportable from any state at a dynamic time, and modify the intersection coordination offset, depending on the request information. The results indicate that the cooperative and dynamic V-VLC system increases safety by directly monitoring critical points such as queue formation and dissipation, relative speed thresholds, as well as inter-vehicle spacing. This paper focuses on the concept rather than on the practical implementations. Implementing the system in a real environment requires considering several constraints, including the dimensions, orientation, and motion of the target vehicles; the precise motion and position of the vehicle; the strategic locations of landmarks; and the unambiguously covered distances and speeds, as well as the field of view. The practical implementation of many tasks such as steering/velocity control, perception of the environment, and performance under all conditions of the roadway and environment will be challenging.