esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussions
### Life Cycle Cost of Intelligent Scheme at Road Side  
Based on the deployment scheme for intelligent infrastructure of different road types, combined with the cost and energy consumption data of intelligent equipment, the lifecycle cost of deploying intelligent infrastructure of different levels on different road types can be obtained. Combined with the service life of the roadside intelligent configuration, the corresponding annual cost can be derived, as shown in Figure 13. The annual costs for primary, intermediate, and advanced intelligent upgrades of urban expressway, class-1 highway, class-2 highway, and motorway are \(\mathbb{V}87\),\(370\), \(\mathbb{V}92\),\(580\), and \(\mathbb{V}107\),\(240\), respectively. Urban main road and urban secondary road, as open roads with complex traffic scenarios, require denser perception equipment and greater computing power to address occlusion blind spots. The annual costs for primary, intermediate, and advanced intelligent upgrades are \(\mathbb{V}174\),\(740\), \(\mathbb{V}185\),\(058\), and \(\mathbb{V}214\),\(379\) respectively. Since the roadside intelligent infrastructure needs to operate normally around the clock to support the functional realization of passing vehicles, its utilization rate and working time are much higher than the vehicle-side intelligent device, and it can be seen that the power consumption cost accounts for a larger proportion in the total cost.  
Combining the usage intensity characteristics of different road types in Beijing and the costs related to intelligence, as well as the forecast data for the future ownership of intelligent vehicles in Beijing (2018), the per-vehicle per-kilometer allocation cost for deploying intelligent infrastructure of different levels on highways and urban roads in different years can be obtained, as shown in Figure 14. Due to the higher usage intensity of urban roads, the allocation cost of roadside intelligent infrastructure is significantly lower than that of highways of all levels through cost-sharing due to the larger traffic flow. Especially for urban expressways, even if advanced intelligent infrastructures are deployed now, the allocation cost is only \(\mathbb{V}0.0134\)/veh/km. In contrast, for class-3 highway, due to its lower usage intensity, even if the penetration rate of intelligent vehicles basically reaches \(100\%\) by \(2050\), the allocation cost for deploying primary intelligent infrastructures is still \(\mathbb{V}0.2493\)/veh/km.  
Figure 12: Life cycle cost of intelligent scheme at vehicle side.
## 3 Results and Discussion
### Coefficient of Friction  
Abrasive wear is one of the dominant wear mechanisms in machining nickel-based alloys [41]. Therefore, the coefficient of friction of the cutting tool plays a significant role in the cutting process.  
In study [42], the friction coefficient was determined for an AlTiN coating applied to a carbide cutting tool. Researchers found that the coefficient is variable over time and depends on the wear level of the cutting tool, with a maximum value of 0.85. The measured friction coefficient for the S205 insert is shown in Figure 15. It is important to note that the measurement was conducted over 80 min, whereas the tool life of inserts used for machining nickel alloys typically does not exceed 20 min. The obtained friction coefficient for the S205 insert with a TiCN/Al2O3/TiN coating applied via CVD method fluctuates around 0.7, which is approximately 20% lower than the AlTiN-coated insert. Efforts to reduce friction and thus extend tool life are focused on replacing conventional cooling/Iubrication methods. One such approach was proposed by [PERSON] et al. [43], who used an atomized spray cutting fluid (ASCF), achieving an almost 40% increase in tool life.  
Figure 15: Coefficient of friction plot vs. time.
## 4 Navigation Signal Processing  
This section proposes the navigation receiver architecture for DDBDM, which primarily consists of acquisition and tracking modules. The architecture enables continuous and accurate measurement of delay and Doppler frequency for navigation. Additionally, its design, similar to that of traditional navigation receivers, helps to reduce the development cost and facilitate upgrades of UE.
## 3 Study Area and Data Used
In comparison, the proportion of highly permeable sections in the basins belonging to the central part of the Taiwan mountain area is slightly lower than that in the basins of the southern part of the Taiwan mountain area. According to the objectives of this study, the field data of the \"Groundwater Resources Investigation in Mountain Areas\" project initiated by the Central Geological Survey of Taiwan were collected from 104 drilling boreholes and seven types of hydrogeological tests after drilling. The data related to this study include drill core photos, core logging, borehole images, and double-packer hydraulic tests. The first three data types for each borehole were mainly utilized as necessary information to calculate the three hydrogeological indices (including RQD, FA, and FD). The raw data of double-packer hydraulic tests were used as the essential information for interpreting the hydrogeological index of hydraulic conductivity and as input data for studies of groundwater flow dimension \(n\) and fracture/matrix permeability ratio (\(\text{K}_{\text{f}}/\text{K}_{\text{m}}\)). Figure 2 shows the water injection process of a constant-head double-packer hydraulic test, where the black line represents the change of rock mass inflow with time, and the other lines stand for the changes of different water pressure gauges with time (P\({}_{\text{g}}\), pressure on the ground; P\({}_{\text{u}}\), pressure over the upper packer; P\({}_{\text{c}}\), pressure between two packers; and P\({}_{\text{d}}\), pressure below the lower packer). Because the water injection process lasted for at least two hours until achieving a stable injection rate, hydraulic responses with time due to fracture geometries were collected. Such collected data were supposed to reveal a fracture network density pattern around a double-packer test section. The result of this analysis can then be integrated with the data of hydrological and geological parameters of the test section for correlation analysis.
# Formation Control Algorithm of Multi-UAV-Based Network Infrastructure
## 5 System Evaluation
### Network and Transport Protocol  
There are \(|D|+1\) subnetworks, one for ad hoc and \(|D|\) for APs. Internet Protocol (IP) addresses for the UAVs and the GCS is pre-assigned at the simulation environment install step. For the terrestrial nodes, IP addresses could be changed dynamically, no IP address is assigned in advance. However, it should be noted that ns-3 does not support automated Wi-Fi selection scheme internally. Mobile nodes cannot change the IP address dynamically by scanning the around APs and change the connection. To resolve the phenomenon, we explicitly probed the APs nearby each mobile node and reassigned the IP address in a certain period. In our implementation, the AP scan occurs per 3 s. Also, we employed Ad hoc On-demand Distance Vector (AODV) routing protocol [38] for the ad hoc network. In our previous work, we found that AODV outputs the best performance of the ns-3 supporting routing protocols for the ad hoc networking in terms of the connectivity and the data rate. Finally, to focus on the PHY to the Network layer performance, we employed User Datagram Protocol (UDP) protocol to reduce the transport layer overhead of the simulation.
## 5 Experiments and Results
### Comparing Results with Existing Research  
Table 6 shows the comparison of our results with those reported in previous research. Study 2 [41], leveraging a large corpus of 64k, achieved 90.52% accuracy with DarijaBERT. Despite using a smaller corpus of 10,200 sentences, our DarijaBERT implementation yielded a satisfactory accuracy of 86%. The results reported in study 3 [47] achieved 87% accuracy.  
Figure 21: Comparison of algorithms accuracy.  
Figure 22: Best model performances in terms of precision, recall, and F1-measure (F1) per class.  
This slight improvement is likely attributed to their comments containing more words per sentence, potentially providing richer contextual information for the model. The difference in performance between our work and study 3 is, therefore, minimal.  
Study 1 [48] also demonstrated the detrimental effect of limited corpus size on the performance of NV and SVM algorithms, reporting accuracies of no more than 71.03% and 75.04%, respectively. In contrast, our use of a larger dataset resulted in significantly higher accuracies for these algorithms, ranging from 91% to 93%. This underscores the importance of adequate data training to achieve robust performance with these models.
###### Abstract  
Mangrove ecosystems can be both significant sources and sinks of greenhouse gases. The restoration of mangrove forests is increasingly used as a natural climate solution tool to mitigate climate change. However, the estimates of carbon exchanges remain unclear, especially from restored mangroves. In this study, we observed the temporal variations in carbon dioxide (CO2) and methane (CH4) fluxes and their biophysical controls for 4 years, based on a closed-path eddy covariance (EC) system. The measurements were conducted in a mangrove wetland park with 14-year-old restored mangroves surrounded by open waters in Guangdong Province, China. The EC measurements showed that the mangrove ecosystem acted as a CO2 source with a net CO2 ecosystem exchange (NEE) of 305 g C m\({}^{-2}\) from January 2019 to May 2020 by the 5-m tower measurement. After the tower was adjusted to 10 m, the mangrove showed a CO2 sink with an NEE of \(-345\) g C m\({}^{-2}\) from June 2020 to December 2022. The change in tower height influenced the interpretation of interannual trends on NEE. There were no significant interannual trends in the gross primary productivity (GPP) and the ecosystem respiration (Re) values. The change from CO2 source to sink may be attributed to the decrease in land surface proportion by the tower replacement, which reduces the proportion of the mangrove canopy respiration and, therefore, captures lower CO2 fluxes from open waters. The restored mangroves indicated strong CH4 sources of 23.2-26.3 g C m\({}^{-2}\) a\({}^{-1}\). According to the random forest analysis, the land surface proportion, radiation, and relative humidity were the three most important predictors of NEE, while the CH4 flux was most sensitive to air temperature. Compared to the natural and long-term restored mangroves, this 14-year-old restored mangrove had not yet achieved a maximum carbon sequestration capability. Our study highlights the need for the careful design of long-term observations from restored mangroves and proposes future needs in the context of carbon neutrality.  
carbon dioxide; methane; mangrove restoration; Southeast China; eddy covariance 2023
# A Complete Key Management Scheme for LoRaWAN v1.1 +
## 5 Centralized Key Management Scheme for LoRaWAN
### Key Back-Up/ Recovery/ Revocation Scheme (KBURRS)  
To make the LoRaWAN system running more smoothly to prevent the case of servers' failure. A backup and recovery scheme are discussed in the section. Although in the design that the CKMS is one single entity dealing with the key management lifecycle. However, CKMS is the key management server that can be as many as it is required by the network. It only appears as one single entity from the application user's point of view. Each CKMS is designed to cover a certain population (end devices) of the area. Hence, it depends on the recourses of CKMS party; it might require at least two CKMSs for one area that has a high density of usage (one server is for daily use, another is for backup). It also can use a shared-CKMS scheme that two close-related CKMSs can use as part of their storages to backup other's keys. The KBURS would trigger the backup-server (another CKMS nearby) when an unwanted situation happened. Hence, all the old keys would be recovered, and all the participant parties in the network would roll back to the previous state when the unwanted situations occurred. Furthermore, when the old keys are no longer in use, it will be removed from the CKMS.
## 3 Experimental Results and Analysis  
### Indoor CBR  
The relationship between \(T\), \(\omega\), degree of \(K\), and indoor CBR is illustrated in Figure 2. It is evident that at a constant temperature and moisture content, the CBR value increases with an increase in the degree of \(K\), although the rate of increase in CBR values slows as the degree of compaction rises.  
From Figure 2a, it is observed that at room temperature, soil samples with a 20% moisture content exhibit lower CBR values. This is because a 20% moisture content is close to the liquid limit of the test soil sample, where the presence of water increases the distance between soil particles, enhancing the compressibility of the soil and thus reducing its bearing capacity. When the degree of \(K\) is constant, the CBR value increases as the \(T\) decreases. Above \(-3.1\)\({}^{\circ}\)C, for every \(1\)\({}^{\circ}\)C decrease in temperature, the CBR value increases by approximately 50%. Below \(-3\)\({}^{\circ}\)C, the CBR value tends to stabilize with changes in \(T\). This stabilization occurs because as the temperature decreases, the content of unfrozen water in the soil sample decreases, and the ice content increases. Consequently, the binding interaction between ice and soil particles strengthens, and the strength of the ice also increases. However, as the temperature continues to drop, the ice content and strength tend to stabilize, thus initially enhancing and subsequently stabilizing the soil sample's bearing capacity.  
Figure 2b shows that under sub-zero conditions, with a constant degree of \(K\), the CBR value increases with an increase in \(\omega\). When the moisture content is less than 40%, for  
Figure 2: Variation in soil sample CBR values with temperature and moisture content. (**a**) variation in CBR values with temperature for a sample with 40% moisture content; (**b**) variation in CBR values with moisture content for a sample at \(-2.1\)\({}^{\circ}\)C.  
every 10% increase in moisture content, the CBR value increases by about 40%. When the moisture content exceeds 40%, the CBR value tends to stabilize. This is due to the fact that as the \(\omega\) increases, the ice content also increases, enhancing the adhesive bonding between soil particles and ice crystals. When the pores are completely filled with ice crystals, the bonding between soil particles and ice crystals reaches an optimal state. In this study, high-moisture-content soil samples were formed using premade ice sand, which does not cause volumetric expansion and thus prevents damage to the soil skeleton and avoids strength degradation due to cracking. Therefore, the bearing capacity of the soil sample first increases and then stabilizes as the \(\omega\) increases.
## 1 Introduction
Additional research has also focused on specific simulation techniques to model these interference scenarios [6; 12] and examined relevant regulatory power limits applicable to MVDS operations to protect satellite services [13]. The collective body of work underscores the need for careful system design and coordination, which this paper aims to contribute to by analyzing the specific Lebanese MVDS case. While existing research often addresses multipoint video distribution systems (MVDS) and their potential interference with satellite services in a general manner or within different geographical and systemic contexts, a specific gap persists in the literature. There is currently a lack of a comprehensive analysis specifically tailored to the unique operational parameters and deployment characteristics of MVDS systems as they are utilized in Lebanon. Furthermore, dedicated studies focusing on the potential impact of these Lebanese MVDS operations on geostationary orbit (GEO) satellite receivers are notably absent. This study, therefore, aims to fill this critical void by providing an in-depth investigation focused on the distinct Lebanese MVDS environment and its specific implications for GEO satellite services. This paper is structured to provide a comprehensive analysis of the interference between MVDS systems and GEO satellites. Following this introduction, Section 2 will detail the system model, outlining the scenario under investigation and the operational parameters of both MVDS and GEO satellite systems. Section 3 will provide a detailed description of the systems involved, including the technical specifications of MVDS and GEO satellite technologies, as well as the various interference mechanisms considered. Section 4 will focus on the mathematical models used to quantify the different types of interference, including link budget calculations and specific formulations for adjacent satellite interference and MVDS side lobe interference. Section 5 will present and analyze the results obtained from these calculations, comparing ideal scenarios with those incorporating different interference sources. Section 6 will then present a comparative analysis of the interference levels under varying MVDS power and bandwidth conditions. Subsequently, Section 7 will propose and evaluate a potential mitigation strategy to reduce the identified interference. Finally, the paper will conclude with a summary of the key findings and suggestions for future research directions.
## 2 Experimental Setup  
### CEA Pipe Whip Tests  
This research deals with the validation of the simulated numerical models of the 1D/3D coupled system with the previously conducted French Commissariat a l'Energie Atomique (CEA) tests. Several CEA tests were conducted in the Cadarache Laboratory in France using the Aquitaine II steam facility to analyze the pipe whipping phenomenon. A total of 16 tests were performed under PWR conditions on the Schedule 80, 3-inch pipe, and they validated the pipe response with their numerical codes. These bulk tests were classified into two types based on the object of impact. The impact tests on stiff structural members and concrete slab were the two major considerations, with deviations in their gap dimensions [2; 4; 5].  
Test 5 from the CEA experiments is compared with the numerical results of the presented modeling approach. The experimental results of test 5 are often considered a benchmark for validation of numerical models with its \"pipe-on-wall-impact\" scenario [2; 4]. Test 5 includes a long pipe with an elbow made of French steel which has mechanical properties equivalent to that of A106 grade B steel. The experiment is carried out under controlled PWR conditions with the use of an explosive cord to initiate the instantaneous high-pressure flow or line break. The pipe is maintained at a temperature of about 300\({}^{\circ}\) Celsius and a pressure of around 16.6 MPa is maintained inside the pipe [2]. With such high operating pressures, the estimated duration of the tests was kept at 20 to 30 milliseconds (ms).  
A typical experimental setup of the pipe is shown in Figure 1, where one end of the straight horizontal section of the pipe is attached to a water filled tank kept at operating pressure while the other end containing the elbow is kept unrestrained. A slab of concrete is kept fixed right below the elbow with a fixed gap where the pipe is expected to impact after a sudden high-pressure flow is initiated. The original experiments involved two major studies which included the mechanical response of the impacted slab during the pipe whipping effect and the measurement of the impact force on the slab. The large displacements of the whipping pipe are measured with a high-speed 5000 fps camera along with strain gauges kept on the rebars of the concrete slab to measure the impact parameters.  
The deformation of the pipes in every experimental test depends on the geometry of the pipe, where the strain rate plays a vital role in the mechanical response of the pipe to the fluid transient. It is observed that the plastic strain is distributed uniformly along the length of the pipe for longer dimensions while localized plastic strain is present for shorter dimensions. Hence, the strain rate influence on the material behavior for the pipe whipping scenario can be neglected with reasonable justifications. The maximum impact force was observed in test 5 with a value of 385 kN and with a time to impact of 13.2 ms, as well as a localized crushing stiffness at the impact zone [4].
## 4 Geometry and Meshes
### Meshes  
We performed simulations considering more than 8 levels of mesh refinement. After some numerical experiments, the following meshes were considered:  
* \(M_{1}\)--uniform mesh with 160 \(\times\) 16 computational cells and a minimum \(\Delta x/H\) and \(\Delta y/H\) mesh spacing of 0.0625;
* \(M_{2}\)--uniform mesh with 320 \(\times\) 32 computational cells and a minimum \(\Delta x/H\) and \(\Delta y/H\) mesh spacing of 0.03125;
* \(M_{3}\)--uniform mesh with 640 \(\times\) 64 computational cells and a minimum \(\Delta x/H\) and \(\Delta y/H\) mesh spacing of 0.015625.  
The tree meshes are shown in Figure 4.  
Numerical simulations were also performed considering a mesh with additional refinement in the centerline of the channel, as shown in Figure 5. A total number of 16,000 cells was used.  
Figure 4: Three consequently refined uniform meshes used in this work.