esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Computational Study  
### Test Facility  
A prototype DCS employing a wireless network was constructed to test the principles discussed in previous Sections. In the test bed, the overall structure of which is as shown in Figure 4, a real-time Hardware-In-The-Loop (HIL) approach was used in order to be able to evaluate control performance and CPU overheads for the method applied to a typical process plant. The Simulink(r) Real-Time Windows Target (RTWT) environment was employed to run a real-time simulation of a process model on the HIL simulation PC. Given the simplicity of the implementation details of the sensor and actuator nodes, their operations were integrated into the simulation model employed by the HIL simulation PC. The real-time controller node consists of an embedded processor employed to implement the functionality of the central control node. The main processing element in the node hardware platform is  
Figure 3: End-to-end elements of the proposed compensation technique (top: sensor node, middle: controller node, bottom: actuator node).  
a 32-bit LPC2387 microcontroller with ARM7 TDMI-S core from NXP semiconductors, mounted on a development board manufactured by Olimex\({}^{\copyright}\). The device was operated with a CPU clock speed of 72 MHz, and it features 512 Kb of on-chip flash, 98 Kb of on-chip RAM plus a rich set of I/O peripherals including multiple UARTs. In order to implement the wireless communication link, a set of simple RF serial communication transceivers from USBscope\({}^{\copyright}\) were employed. These devices work at 433 MHz, have a range of approximately 400 m and implement half-duplex RS-232/485-like links at each end, operating at 57,600 bps. A transceiver was interfaced directly to an on-chip UART of the LPC2378 to implement RF communications with a similar transceiver interfaced to the simulation PC via USB.  
In this study, 24-byte packets were used: two bytes for addressing, a 20 byte payload, plus a two byte checksum. This allows for up to 10 control signals of resolution 16-bits each to be transmitted per packet. Serial port emulation was employed on the HIL simulation PC, to enable data to be exchanged with RTWT via packet input/output blocks. Packet I/O is well supported in the RTWT environment, with \"error\" and \"data ready\" signals being available in order to control the buffering scheme in the simulated actuator node and controller nodes. This setup had the added advantage that sensor and/or controller packet losses may also be enforced using fault injection within the Simulink model, which can be driven by representative stochastic models (e.g., [13]). The techniques proposed in the previous Sections were coded into a small embedded \"C\" library for test purposes, and the routines were embedded onto the controller node and linked into RTWT function blocks as appropriate.
# Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery
## 2 Study Site and Data Acquisition  
A 40-km stretch of sandy coast in the South West of France was selected as the study site for the present work (Figure 1). This section of the Aquitanian coast presents a relatively low shoreface bordered by aeolian dunes with an average crest elevation of about 15 m [19; 20; 21]. The sediment consists of fine to medium quartz, with mean grain sizes ranging from 200 to 400 \(\upmu\)m [21]. This section of the coast is characterized by a macro-tidal regime, with an average tidal range of 3.2 m that can reach 5 m during spring tides [22]. The coast is exposed to high energy North Atlantic swells travelling mainly from the W-NW sector [23].  
The Pleiades-HR 1A (hereinafter referred to as PL1A) stereo-pair was acquired on 14 November 2017 over a predefined area (orange box in Figure 1). The optical stereo-pair was obtained between 11:15 a.m. and 11:16 a.m. with a 40-s time-lag. The satellite orbits at 694 km altitude (base to height ratio of 0.36) and follows a descending orbit trajectory (North-South) in WGS84 decimal coordinates. A topographic DEM and ortho-image, covering the entire area of interest, was subsequently produced using NASA's AMES Stereo Pipeline [24].  
In-situ RTK-GPS beach topographic measurements were used as ground-truth for inter-comparison with the Pleiades and LiDAR DEMs. The RTK-GPS survey was performed in the central section of the area of interest (coastal region of Capbreton) between the 7\({}^{\text{th}}\) and 9\({}^{\text{th}}\) of November 2017 (Figure 1). The average tidal range during the beach surveys was 3.4 m with a moderate wave climate (wave height under 3 m). Beach profiles were surveyed in continuous mode (waypoint every 1 second using a  
Figure 1: Satellite image of the West of France (source: Google Earth Pro 2018) showing the location where Pleiades stereo-pair was obtained (orange rectangle located in the Southwest of France) on the 14\({}^{\text{th}}\) of November 2017 (**A**). Zoom in of the Pleiades mosaic showing the area where the airborne-LIDAR topographic survey was performed (polygon with dashed green outline) and the region where RTK-GPS topographic measurements were undertaken (**B**). Panel (**C**) shows the RTK-GPS survey lines (red) and photograph of the surveyor with the GPS rover unit.  
position dilution of precision--PDOD--mask of 3) from the waterline to the back of the frontal dune ridge along discrete cross-shore profiles spaced by approximately 250 m (Figure 1). Note that due to radio transmission shadowing (resulting in no real time correction) or ground obstacles (e.g., fences, walls, etc.), the survey coverage presents some spatial irregularities (Figure 1). In addition to the RTK-GPS dataset, a high resolution airborne-LiDAR topographic survey and orthophoto map (aerial imagery was orthorectified with the LiDAR observations) of the entire SW coast of France (performed by the Institut National de L'Information Geographic et Forestiere--IGN; in cooperation with the Bureau de Recherches Geologiques et Minieres--BRGM) were acquired in October 2017.
# Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar
## 3 Results
### Simulation of Forest Succession  
The life history of the simulated forests follows an ordinary successional pathway (Figure 3a). Initially, the plot is colonized by small (PFT 10) and medium (PFT 7) shade intolerant trees, and small (PFT 9 and PFT 12) and large (PFT 2) intermediate tolerance trees, as well as an in-seeding of large shade tolerant trees. After the initial exponential increase in biomass, crowding leads to thinning and by year 50, shade intolerant PFTs 7 and 10, and intermediate PFT 9, are out-competed by larger intermediate and shade tolerant trees (PFTs 1 to 6). PFTs 3-6 have initial biomass peaks that thin by year 100. PFT 2 establishes as the dominant plant functional type, but peaks around year 100 when shade tolerant trees are thriving in closed canopy shadier conditions.  
In year 200, canopy emergent and canopy shade tolerant classes (PFTs 1 and 3) dominate the overall biomass, while PFT2 and PFT4 are on the decline toward a more stable equilibrium. But in year 400, the forest reaches a climax state, dominated by large shade tolerant followed by intermediate tolerance tree species. From this stable equilibrium, small fluctuations of biomass occur following the deaths of large trees, and shade intolerant species colonize the gaps formed by treefalls (as seen by short peaks in biomass of PFTs 7 and 10) and are eventually out-competed or out-lived by intermediate or shade tolerant trees that colonize in the shady sub-canopy conditions.  
The model accurately reproduces aboveground biomass (t/ha; \(r^{2}\) = 0.976), stem numbers (\(r^{2}\) = 0.895), and basal area (m\({}^{2}\)/ha; \(r^{2}\) = 0.995) for the BTP study site (Figure 3a-e). The \(>\)10 cm simulated trees match well for the smalleratured plant functional types (PFT5-PFT12). Aboveground biomass in the simulation was slightly overestimated for the main canopy and emergent intermediate trees, and slightly underestimated for the main canopy and emergent shade tolerant trees.  
As shown in Figure 3b, the model slightly overestimates the number of trees 0.2 m-DBH and less, but underestimates the number of trees between 0.25 m and 0.5 m-DBH. This is further explained in Figure 3d, which shows stem number as overestimated in the simulation for PFT 1, and underestimated for PFTs 4, 5, 6, 8, and 9. Basal area was slightly underestimated in the simulation for PFTs 2 and 4. The slightly low aboveground biomass and basal area but inflated simulated stem numbers for PFT 1 suggest that the model grows a larger number of comparatively smaller shade tolerant canopy emergent trees (in terms of maximum size) than was measured in BTP. Overall, however, the results show that the model reproduces the main forest structural patterns observed in the BTP plots with respect to aboveground biomass, stem numbers, and basal area (Figure 3c-e).
# Durability of Mortars with Partial Cement Replacement by Recycled Brick Powder
## 3 Results
### Carbonation Resistance  
Figure 8 shows images of various test specimens following a phenolphthalein staining of each analysed mixture. Figure 9 presents data on the carbonation depth in each mortar  
Figure 7: Porosity accessible to water.  
at 7 and 28 days. The reported values represent the arithmetic mean of the measurements taken on each face.  
As observed, the carbonation in the analysed samples exhibits highly variable results. Up to a substitution level of 35%, the carbonation depth remains practically similar across all samples compared to C00 at both 7 and 28 days (with variations of less than \(\pm\)9%). However, samples C40 and C45 demonstrated lower resistance to carbonation, with penetration rates between 30% and 60% faster, reaching carbonation rates exceeding 40 mm/year\({}^{1}\)/\({}^{2}\). Very few authors have investigated the carbonation resistance of mortars in which OPC is partially replaced by RBP. Researchers who have conducted similar experimental plans have reported findings consistent with those observed in this study. Both [PERSON] et al. and [PERSON] et al. recorded comparable carbonation front penetration in reference samples and in mixes with up to 25% OPC replacements by RBP. However, at higher substitution levels (between 40% and 60%), they observed an increased carbonation rate [63; 89].  
As described in Section 3.2, increasing the proportion of RBP in the mixture leads to a reduction in the material's pore network (noticeable when analysing porosity results or chloride diffusion data), thereby improving its resistance to carbonation. This reduction in porosity limits the ingress of carbon dioxide (CO\({}_{2}\)), which is a key factor in the carbonation  
Figure 8: Carbonation depth analysis (7 days).  
Figure 9: Carbonation depth results.  
process. However, at higher levels of substitution--specifically above 35%, as observed in this study--there is a pronounced tendency for the formation of a substantial amount of calcium silicate hydrate (C-S-H) gel because of the pozzolanic reaction. Additionally, a proportion of unreacted calcium silicates remains within the matrix, as discussed in Section 3.1 and corroborated by other studies [90]. In such cases, the increased presence of these reactive phases enhances their interaction with carbonic acid (H\({}_{2}\)CO\({}_{3}\)), which is generated when CO\({}_{2}\) penetrates the material and reacts with pore water (H\({}_{2}\)O). This chemical environment consequently promotes a more rapid progression of carbonation, as supported by findings in the existing literature [91].
# Multi-Module Combination for Underwater Image Enhancement
## 4 Experiment
### Summary  
Through the above experiments, we found that UMMC achieved good results overall in the six experimental tests. For underwater image enhancement, we successfully eliminated color bias while largely preserving image quality. At the same time, we also found that it is easy to overcompensate when the degree of color bias is small, and for foggy images, it does not work as well as it should, and the processing effect is poor. The modeling algorithm needs to be adjusted in the future. UMMC runs faster while ensuring quality. The significance of each component of UMMC and its overall performance is further illustrated through the ablation experiment. However, the feature point matching test did not achieve the desired results; the model needs to be further adjusted for analysis.
# Feasibility of a Quasi-Static Approach in Assessing Side-Wind Hazards for Running Vehicles
## 3 Feasibility of the Quasi-Static Approach Under a Uniform Wind  
The feasibility of the quasi-static approach in estimating reasonable tire forces was examined under uniform wind conditions with an incident angle of 90 degrees to the vehicle--i.e., perpendicular to one side of the vehicle. The quasi-static approach was validated using the commercial software TruckSim (v2017.1), which was developed by Mechanical Simulation Corporation (2017) to provide various vehicle types, such as vans, busses, and trucks, with a sophisticated modeling capacity for optional suspension types, steering conditions, powertrain modeling, brake systems, and interaction mechanisms with a driver. The benchmarking responses for validation were the tire forces of two vehicle types--vans (vehicle with two axles) and trailers (vehicle with one axle and one hitch point)--under various wind speeds. As a numerical integration method, the Adams-Moulton second order method was adopted. This is an implicit linear multistep method that involves a prediction procedure at each half step. A time step of 0.001 s was selected, which was confirmed as a sufficiently small value via convergence testing.
# A Multi-Objective Path-Planning Approach for Multi-Scenario Urban Mobility Needs
## 2 Preliminaries
### Dynamic Weight-Adjustment Mechanism
#### 2.3.4 Nighttime Travel  
Safety and traffic efficiency are critical considerations for nighttime travel, particularly for rideshare drivers and emergency responders. The dynamic weight-adjustment mechanism increases the weights for safety and time, ensuring safe and efficient travel in high-risk environments.
## 5 Testing and Experimental Configuration
### Communication between Nodes and Station  
The end nodes were located in the agricultural fields of the Chirinche Bajo community, while the gateway was located in an inhabitant's house from where it was linked to the Internet through a wireless Wi-Fi connection.  
Three autonomous networked end nodes were considered for the experimental test. Nodes 1 and 2, working at a frequency of 915 MHz for uplinks, while node 3 at 904 MHz for downlinks, were placed on poles 1 m above the ground, as illustrated in Figure 9a. Eight different locations were chosen based on the spatial distribution in agricultural fields and topography, in order to cover all possibilities and different types of environments, short and long distance, Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS), the latter being affected by obstructions resulting from houses, trees, crops and slopes, as can be seen in Figure 8.  
Figure 9: _Cont_.  
The LoRa gateway has 2 channels at frequencies of 915 MHz and 904 MHz for uplink and downlink by full-duplex communication. The gateway was placed on the roof of a house (1\({}^{\circ}\)04\({}^{\prime}\)58.8\({}^{\prime\prime}\) S 78\({}^{\circ}\)38\({}^{\prime}\)54.4\({}^{\prime\prime}\) W) at 4 m from the ground with the antennas placed vertically (normally a base station of this type is placed higher to achieve better coverage). In addition, the choice of the gateway location is based on two reasons. First, electrical power. As the gateway communicates with both the end nodes and the Internet, the power consumption is higher. Thus, a direct connection to the power outlet would avoid supply problems. Second, the connection to the Internet [42]. The gateway can be connected via Wi-Fi directly to the switch located in the house. Thus, communication with the IoT platform Thinger.io is ensured.  
Figure 9: (**a**) Flowchart of the optimized gateway algorithm and (**b**) Flowchart of the optimized end-node algorithm.
## 2 On-Site Measurements
### Measurements
#### 2.2.2 Track Geometry  
In the high-speed railway under commercial operation, the track geometry is periodically checked (e.g., once per month) by a track inspection car. However, the car measures track irregularity using a chord versus method that measures the maximum deviation on a 10 to 30-m straight line, it is impossible to directly measure the absolute extent of long-wavelength track irregularity. Therefore, the change of the track geometry caused by a vertical deformation of the main arch element of the bridge during the winter and summer seasons was measured, in the present study, by applying a 3D precision survey technique. The absolute positions of the top of the rail were measured, as a baseline, against fixed points on the bridge using the GRP system FX [21]. The survey was conducted for a total length of 360 m, and measurements were taken at one point for every three sleepers (approximately 1.8 to 2 m). The number of measuring points was minimized, considering that the measurements had to be done within the night repair time (about 3 h and 30 min). Table 1 shows the ambient and arch-member temperatures at the track-geometrical measurement points.  
Figure 2: Locations of temperature sensors installed on test bridge.
## 3 LR-Aided MIMO Detector Design
### Performance Analysis
Figure 2: BER performance of various LR-aided detectors over 200 \(\times\) 200 MIMO system and using 64-QAM as a modulation scheme. the ELR-aided detector requires lower SNR to attain any BER compared to the LLL-aided detector, which means that it requires lower transmit power. After we have established that the ELR-aided detectors are capable of attaining an improved performance compared to their LLL-aided detectors, in the following we analyse the complexity difference between these detectors. We consider the complexity in terms of the number of arithmetic operations including real additions and real multiplications. Given that the detection techniques are the same in the ELR and LLL-aided detectors, we compare the complexity of the LLL and the ELR algorithms for performing the LR. Figure 3 shows the average number of arithmetic operations for the basis update in the LLL and ELR algorithms versus the number of MIMO transmit and receive antennas, where the plot assumes the same number of transmit and receive antennas. As shown in Figure 3, the ELR has a significantly lower number of arithmetic operations than the LLL algorithm, which is consistent for all number of antennas. The ELR requires nearly an order of magnitude less arithmetic operations that the LLL algorithm, as shown in Figure 3. Therefore, we can conclude that our proposed ELR-aided detectors will require significantly lower complexity than their LLL-aided counterparts, while at the same time achieving better performance. Therefore, in our hardware implementation of the LR-aided K-Best detector we aim to utilise the ELR algorithm, which is capable of attaining a better performance and has a lower complexity. In Figure 4 we show the performance of the ML, K-Best and ELR K-Best detectors when applied to MIMO system employing four transmit and receive antennas. As shown in the Figure, the ELR-aided K-Best detector is capable of outperforming the K-Best detector and attains a closer-to-ML performance. Furthermore, in Figure 5 we show the SNR performance gap from the ML detector for the K-Best and ELR-aided K-Best detectors to attain a BER of \(10^{-5}\). The performance gap is evaluated as the difference in the SNR required to attain a BER of \(10^{-5}\) between the two detectors and the ML detector for a variable number of transmit and receive antennas. As shown in Figure 5 the performance gap from ML of the ELR-aided K-Best detector is always smaller than that for the K-Best detector. In the  
Figure 3: Average number of arithmetic operations for basis updates of LLL and ELR algorithms versus the number of MIMO transmit and receive antennas [13]. following section we describe the hardware implementation of the ELR-aided K-Best detector when applied to a MIMO system utilising four transmit and four receive antennas.
# Communication Network Standards for Smart Grid Infrastructures
## 2 Network Standards That Support Communication in Smart Grid Infrastructures
### Smart Home and Building Automation  
According to ISO 16484-2 and ISO 16484-3, HBES/BACS refers to the equipment required for automatic control, monitoring, manual intervention, and management of optimization services, including outdoor installations and other equipment [10; 63]. The main benefit from the development of smart grids exclusively concerns the distribution and the forecasting of energy loads. A main objective of HBES/BACS technologies is the reduction of the consumed energy through the use of energy optimization functions as well as the cost reduction that can be achieved by appropriate load distribution based on graduated pricing (cost reduction per kWh) and, of course, the conventional power limitations on a case-by-case basis [64; 65; 61].  
In addition, in the context of smart grids and the development of smarter billing methods, the ability to handle additional billing information is a prerequisite. Finally, HBES/BACS systems can handle or integrate in their operation, alternative sources (for instance wind turbines), as well as energy storage systems (for instance electric cars). This leads to a semantic and syntactic compatibility requirement between HBES/BACS systems and AMI technology [10, 64].  
The operation of HBES/BACS integrates all TCP/IP-based wired and wireless communication technologies through the establishment of the following standards: ISO 16484 series, ISO/IEC 14543-3, EN 13321 series, EN 13757 series, EN 50090 series, EN 50428, IEEE P1701 to IEEE P1705, EN 50491 series, ISO/IEC 15045, ISO/IEC 15067-3, ISO/IEC 18012, China: GB/Z 20965, USA: ANSI/ASHRAE 135 together with other protocols such as OpenHAN, HomePlug AV & C&C, Z-wave, ITU G.9960, etc. [7]. It should be noted that the standardization of common semantics, data models, and cooperation methods between AMI and HBES/BACS is pending.