esa-sceva/satcom-chunk-collection huggingface dataset:
# Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks
## 3 Azimuth Bias
### Optical Encoder
 \tag{24}\]  
and solving the triangle for \(\theta\):  
\[\theta=atan\left(\frac{x}{y}\right)=atan\left(\frac{\tan(\theta_{m})}{\cos(s_ {enc})}\right) \tag{25}\]  
and then \(\theta_{m}\) can be calculated as:  
\[\theta_{m}=atan(\cos(s_{enc})\tan(\theta))=atan\left(\cos(s_{enc})\frac{x}{y}\right) \tag{26}\]  
A Taylor series of order 2 on the bias variable \(s_{enc}\) is made to get an approximation of the measure:  
\[\theta_{m}\approx\theta-\frac{1}{2}\cos(\theta)\sin(\theta)s_{enc}^{2}=\theta -\frac{s_{enc}^{2}}{4}\sin(2\theta) \tag{27}\]  
In this Taylor series, the first order term is zero and the second order term is considered. As this term is raised to second power, with small values of \(s_{enc}\) the value of the bias will be negligible. In both terms related with the encoder the error has been calculated supposing that the difference of the centers and the swash are in the azimuth \(\theta=0\). Supposing that in reality the azimuth of the difference of centers is \(\alpha_{ecc}\) and the azimuth of the swash is \(\alpha_{enc}\) the resultant encoder bias, comprising both the effects described in (23) and (27), is:  
\[\Delta\theta_{enc}=-\frac{s_{enc}^{2}}{4}\sin(2\theta-2\alpha_{enc})-\frac{ \Delta R}{R}\sin(\theta-\alpha_{ecc}) \tag{28}\]  
Figure 6: Swash of the optical encoder. (**a**) Schematic model of the optical encoder; (**b**) Mechanical encoder circumference and its projection on the horizontal plane. An equivalent model can be derived by using trigonometric relations, in order to express all the biases with a linear structure similar to the one in Equation (16):  
\[\Delta\theta_{enc}=s_{enc,s}\sin(2\theta)+s_{enc,c}\cos(2\theta)+\Delta R_{y}\sin (\theta)-\Delta R_{x}\cos(\theta) \tag{29}\]  
where:  
\[ \begin{array}{c}s_{enc,s}=\frac{s_{enc}^{2}\sin^{2}(\alpha_{enc})-s_{enc}^{2} \cos^{2}(\alpha_{enc})}{4}\\ s_{enc,c}=s_{enc}^{2}\cos(\alpha_{enc})\sin(\alpha_{enc})\end{array}  \tag{30}\]  
and \(\Delta R_{y}\) and \(\Delta R_{x}\) are the terms of the center deviation in the \(y\)-axis and in the \(x\)-axis.
# A Trusted Multi-Cloud Brokerage System for Validating Cloud Services Using Ranking Heuristics
###### Abstract  
Cloud computing offers a broad spectrum of services to users, particularly in multi-cloud environments where service-centric features are introduced to support users from multiple endpoints. To improve service availability and optimize the utilization of required services, cloud brokerage has been integrated into multi-cloud systems. The primary objective of a cloud broker is to ensure the quality and outcomes of services offered to customers. However, traditional cloud brokers face limitations in measuring service trust, ensuring validity, and anticipating future enhancements of services across different cloud platforms. To address these challenges, the proposed intelligent cloud broker integrates an intelligence mechanism that enhances decision-making within a multi-cloud environment. This broker performs a comprehensive validation and verification of service trustworthiness by analyzing various trust factors, including service response time, sustainability, suitability, accuracy, transparency, interoperability, availability, reliability, stability, cost, throughput, efficiency, and scalability. Customer feedback is also incorporated to assess these trust factors prior to service recommendation. The proposed model calculates service ranking (SR) values for available cloud services and dynamically includes newly introduced services during the validation process by mapping them with existing entries in the Service Collection Repository (SCR). Performance evaluation using the Google cluster-usage traces dataset demonstrates that the ICB outperforms existing approaches such as the Clustering-Based Trust Degree Computation (CBTDC) algorithm and the Service Context-Aware QoS Prediction and Recommendation (SCAQPR) model. Results confirm that the ICB significantly enhances the effectiveness and reliability of cloud service recommendations for users.  
cloud broker; cloud service; service registry; service ranking; service recommendation Article
# Tightly-Coupled GNSS/Vision Using a Sky-Pointing Camera for Vehicle Navigation in Urban Areas
## 6 Experiment and Results
### Hardware  
The experimental system consisted of a camera synchronized with a u-blox 6T GPS receiver rigidly mounted on the top of the car and driven around downtown Calgary (Alberta, Canada). The camera  
Figure 12: The consumer-grade GNSS receiver used.  
has a field of view of \(90^{\circ}\), and images with a resolution of \(1288\times 728\) were taken at a frequency of 10 frames per second. A NovAtel SPAN(r) * LCISystem that includes a GNSS receiver and an LCI inertial navigation system was used as the reference system. The reference solution is generated post-mission, and its accuracy is at the decimetre-level or better [14]. Figure 13 shows the test vehicle, as well as a zoomed-in view of the equipment mounted on the roof of the vehicle.  
The NovAtel GNSS module, as well as the consumer-grade GNSS receiver and the computers that record the images and GNSS data are inside the vehicle and not shown.  
The vehicle was driven around areas with tall buildings as well as areas with short buildings (and with buildings on one side of the road). The travelled path and the buildings' height in downtown Calgary are shown in Figure 14. The buildings' height is obtained from the commercially available 3D building model presented in [17; 22; 64]. Since the camera is pointed upwards, both the NLOS mitigation algorithm and the visual odometry are influenced by the building height. Tall buildings captured by the camera mean that the path between the satellites and the GNSS antenna is highly obstructed. This suggests that the GNSS may perform poorly. Inversely, high buildings in an image provide more feature points to be detected in successive images and, thus, leads to more accurate visual odometry.  
The hardware specifications of the equipment used in this paper are provided in Table 1.  
Figure 14: Data collection path travelled. The vehicle starts at the bottom black box (with purple edges), travels following the path indicated with the arrows and stops at the top box (with green edges).  
Figure 13: Experiment setup. Left: the used vehicle with the mounted equipment; Right: top view of the vehicle.  
where:  
VFOV stands for Vertical Field of View;  
\(r_{i\ (i=1,2,3)}\) and \(t_{j\ (j=1,2)}\) are the radial lens and the tangential distortions obtained from the calibration matrix as defined in Section 3.1.
# Virtual Sensing Directional Hub MAC (VSDH-MAC) Protocol with Power Control
## 1 Introduction
The hub node is equipped with multiple directional antennas, and the channel is efficiently utilized through the benefits of spatial reuse. A dynamic transmit power control algorithm is employed at the wireless sensor nodes to improve node energy efficiency. A uniform signal-to-interference-plus-noise ratio (SINR) is achieved for packets from all sensor nodes in the network. As shown through simulations, the proposed protocol leads to improvements in network throughput, energy consumption, and fairness performance. The effects of antenna pattern overlap are also significantly reduced by the proposed protocol. The rest of the paper is organized as follows: In Section 2, we describe the network topology and proposed MAC protocol in detail. In Section 3, we describe the simulation methodology and in Section 4, we present results that show the improved throughput and performance that can be achieved, along with the effect of the antenna gain, power control algorithm, and antenna pattern.
## 4 Results and Discussion
### Simulation Scenario and Parameters
As mentioned, most of these hyper-parameters were tuned to increase the performance of the respective models. The tuning of the hyper-parameters was done via extensive computer simulations. The training of the model, as well as the performance comparison of the evaluated metrics are presented below.
## 5 Conclusions  
The primary objective of this study was to gain deeper insights into the chemical reactions induced by the combined effect of chloride and sulfate ions on low-carbon cementitious materials. To that end, this study assesses the effectiveness of SCM blends by utilizing pure Portland cement, and binary, ternary, and quaternary pastes. Powders extracted from the pastes at an early age were exposed to various environmental conditions and compared. Based on the findings obtained during this investigation, the following conclusions can be drawn:  
* In the sole presence of sulfate, a substantial reduction in portlandite and AFm content was observed, accompanied by a notable formation of ettringite. Furthermore, a marked increase in porosity was observed, and the complete depletion of sulfate ions from the solution was detected (Mix1) by Raman spectroscopy.
* The simultaneous presence of chloride and sulfate ions had a mitigating effect on the sulfate attack on the cementitious materials.
* The FTIR analysis method detected the formation of Friedel's salt and the consumption of portlandite in the presence of chloride ions alone. However, this phenomenon was not observed when sulfate and chloride ions were coupled.
* The presence of sulfate ions accelerates the attack of chloride ions by inhibiting the binding of free chloride ions.  
Figure 10: Schematic illustration of the chemical changes that occurred in Mix1 on both day 1 and day 25 in the four different environments.  
* The incorporation of multiple SCM resulted in a lesser pH increase, a delay in ettrinigite formation, and a reduction in crack generation. This led to an enhancement of the materials' resistance to attacks. Future research should include a full study on the combined effects of sulfate and chloride on low-carbon cementitious materials, addressing both chemical reactions and physical processes (physico-chemical properties). It is imperative that not only the chemical interactions are considered, but also the physical aspects, such as the penetration rates of chloride and sulfate ions into the cementitious matrix, because this phenomenon highly impacts the effects of the coupling of sulfate and chloride on cementitious materials. A comprehensive approach will provide a more complete understanding of the complex interplay between these ions and their influence on the properties and durability of concrete.  
**Author Contributions:** Validation, conceptualization, methodology, writing--review and editing, O.O.M., M.M. and M.Q.; writing--original draft preparation, investigation, and formal analysis, F.E.I; supervision, O.O.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Benefit Components
### Social Benefit Indicators  
The social benefits brought by the maintenance plan mainly consider the extension of road surface service life and savings in user costs after the implementation of maintenance measures.  
1 Extension of road service life  
Figure 1: Illustration of the do-nothing and benefit areas [35].  
The pavement's life without preventive maintenance is \(\rm T_{n}\). The service life of the road surface after implementing some preventive maintenance when the road age is j is \(\rm T_{a}^{j}\), then the calculation of the extension of pavement service life \(\rm\Delta T^{j}\) is as follows [8]:  
\[\rm\Delta T^{j}=\rm T_{a}^{j}-T_{n} \tag{27}\]  
2 Road user cost savings  
The cost savings in fuel consumption after pavement maintenance can be expressed as [22]  
\[\rm\Delta FCC=Q\cdot(FC_{0}-FC_{1})/100\cdot P_{F}\cdot I \tag{28}\]  
where  
\(FC_{0}\)--the fuel consumption of a single vehicle before maintenance.  
\(FC_{1}\)--the fuel consumption of a single vehicle after maintenance.  
The cost savings in tire wear after pavement maintenance can be calculated using the following formula [22].  
\[\rm\Delta WC=Q\cdot(W_{0}-W_{1})/1000\cdot P_{T}\cdot I \tag{29}\]  
where  
\(W_{0}\)--the tire wear of a single vehicle before maintenance.  
\(W_{1}\)--the tire wear of a single vehicle after maintenance.  
The cost savings in repair materials after pavement maintenance can be calculated using the following formula [22].  
\[\rm\Delta RC=Q\cdot(R_{0}-R_{1})/1000\cdot P_{R}\cdot I \tag{30}\]  
where  
\(R_{0}\)--The ratio of maintenance cost per kilometer for 1000 vehicles before maintenance to the price of a new car  
\(R_{1}\)--The ratio of maintenance cost per kilometer for 1000 vehicles after maintenance to the price of a new car  
The savings in user travel time cost after implementing pavement maintenance \(\rm\Delta T\) can be expressed by the following equation [22]:  
\[\rm\Delta TTC=Q\cdot(T_{0}-T_{1})\cdot\theta \tag{31}\]  
where  
\(T0\)--the travel time of a single vehicle before maintenance.  
\(T1\)--the travel time of a single vehicle after maintenance.  
The savings in accident cost after implementing pavement maintenance \(\rm\Delta AC\) can be expressed by the following Equation (32) [22]:  
\[\rm\Delta AC=(AT_{0}-AT_{1})\cdot P_{A} \tag{32}\]  
where  
\(AT_{0}\)--The number of accidents before maintenance.  
\(AT_{1}\)--The number of accidents after maintenance.
## 3 Results and Discussion
### Optical Properties
#### 3.5.2 Photoluminescence and CIE Diagram  
The emission spectra in the visible field were recorded using excitation wavelengths of 450 and 550 nm. The transition states and their spectra are depicted in Figure 9. Similar transitions can be detected in emission spectra with an excitation wavelength of 450 nm, whereas spectra with an excitation wavelength of 550 nm show a significant peak around 600 nm. Because of the spectral overlap in the host, 0.3 mol% in B0H indicates a higher intensity of the \({}^{5}\)F\({}_{5}\)-\({}^{5}\)I\({}_{8}\) transition [29; 30; 31].  
To validate the emission color acquired for the B0H collection, the CIE (Commission International de l'Eclairage) coordinates diagram was plotted (Figure 10) using the emission data supplied. Table 3 illustrates the findings of applying the CIE 1931 chromaticity diagram [40] and the McCamy analytical formula for CCT (correlated color temperature) [41] under 450 and 550 nm excitation, which are corroborated by (x, y) co-ordinate values. Based on the applications [42], we will customize the host to have a desired emission color. The results show that, when the prepared B0H set of glasses was excited at 550 nm, it emitted  
Figure 8: Indirect band gap (**left**) and Urbach energy (**right**) plots.
## 7 Current Challenges and Future Research Directions
### Real Evaluation Instead of Simulation  
In the previous analysis of methods to defend against LDDoS attacks in SDN, most methods were implemented in a simulation environment. There is a need to implement and test these methods in a realistic SDN architecture to more accurately evaluate performance and adjust network traffic depending on the topology and size of the network. Although the results obtained in simulation are acceptable for research. In certain cases, researchers use a simplified simulated SDN environment with a single controller and two hosts with limited resources. Therefore, a great effort is needed to design up-to-date and large-scale test rules that enable SDN to validate and minimize LDDoS detection in real network hardware environment as available in traditional IP networks.
## 5 Discussion
The proposed method effectively reduces estimation errors in predicting link delays under high contention scenarios by switching to the highest stable least distance mode. As routing is the basis for information dissemination in vehicular networks, the proposed routing method is capable of routing packets without violating latency constraints while at the same time achieving reliability benchmarks in vehicular communication. However, in order to achieve such superior performance over other existing routing approaches, an optimum value for the link lifetime threshold (200 ms) was required to be determined.
## Case Study  
### Hotel Characteristics and Needs  
The building chosen for the experiment is a hotel in Villahermosa, Tabasco, Mexico. It has a rectangular shape and 154 double rooms (308 guests maximum). Its main needs, related to the current research, are represented by drinking water, domestic water heating and air cooling, as indicated below.  
1. Drinking water, daily required by the hotel, can be divided into two categories: * Water offered to guests: Two \(\times\) 0.5 dm\({}^{3}\) for each guest (maximum 308 guests, corresponding to a maximum of 308 dm\({}^{3}\)/day), provided in bottles and representing a cost to hotel management of 7 pesos/dm\({}^{3}\). * Water for kitchen uses and ice making. For kitchen uses, at least 1000 dm\({}^{3}\)/day of water is required, but 1600-1800 dm\({}^{3}\)/day was considered desirable. If bought in tanks, the water costs 1.4 pesos/dm\({}^{3}\).
2. Domestic hot water (DHW): Based on hotel records, it was calculated that about 140 dm\({}^{3}\)/day per guest at an average temperature of 40 \({}^{\circ}\)C (corresponding to 280 dm\({}^{3}\)/room) was required. The existing plant meeting these requirements has the following elements: * one heat generator, which burns LPG fuel, characterized by thermal power of 820 kW; * domestic water thermal storage with a capacity of 12,000 dm\({}^{3}\); * one recirculating pump between the boiler (heat generator) and the thermal storage unit.  
The existing equipment heats domestic water, up to 55 \({}^{\circ}\)C, by means of direct heating inside the heat generator. The heated water is collected in the storage tank. There are no auxiliary heat exchangers between the heat generator and the storage tank, and no electric heating coils are used as back up. The heating efficiency of the existing boiler was estimated to be about 70%. The boiler is also employed to produce high temperature steam.
3. Cool air--The hotel currently employs a traditional air conditioning system, which serves guest rooms and common rooms. The system does not reach the laundry room, which has a surface area of about 150 m\({}^{2}\) and a height of 3 m. The laundry currently employs only an extractor fan, and its internal environment is not comfortable, sharing the hot and humid characteristics of the external environment and exacerbated by steam used for cleaning operations. It was decided, in compliance with hotel owner requirements, to deliver a portion of the fresh and dry airflow from the integrated system to the laundry in order to increase indoor comfort. A ratio of 13 air changes per h--that is, 5850 m\({}^{3}\)/h of fresh air--was taken into account [10].
# Spatiotemporal Variation of Land Surface Temperature Retrieved from FY-3D MERSI-II Data in Pakistan
## 2 The Study Region and the Data
### The MODIS Data  
Terra and Aqua are the sensors of the MODIS satellite, which collects data at a high frequency of two observations per day, accessed from portal ([[https://lpdaac.usgs.gov/products/mod11](https://lpdaac.usgs.gov/products/mod11) alv061/]([https://lpdaac.usgs.gov/products/mod11](https://lpdaac.usgs.gov/products/mod11) alv061/)) (accessed on 6 May 2022). Its LST products are among the most mature methods, and have been evaluated in numerous previous studies [26; 27; 28; 29; 30]. As we know, the MERSI-II was launched in recent years, and it provide data from 2018, which is not enough to understand the spatiotemporal variations of LST in a broader way at historical scales. Therefore, the MODIS 1 km LST products (MYD11A1 and MYD21A1) were used in this study for two purposes, the first being to cross-validate the LST retrieved from MERSI-II, and second, to evaluate the long-term LST trend for the period between 2005 and 2018. We chose observations from the Terra satellite that provide an estimate of the daily maximum and minimum temperatures. The LST observations were monitored carefully for visual interpretation to ensure that the average LST pixels were within the acceptable quality range for accurate analysis.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Instrument** & **Country** & \begin{tabular}{c} **Launch** \\ **Time** \\ \end{tabular} & **Sensor** & **Channel** & \begin{tabular}{c} **Wavelength** \\ **(\(\mu\)m)** \\ \end{tabular} & **Resolution** \\ \hline FY-3D & China & 2017 & MERSI-II & \begin{tabular}{c} B24 \\ B25 \\ \end{tabular} & \begin{tabular}{c} 10.30–11.30 \\ 11.50–12.50 \\ \end{tabular} & 1000 m \\ \hline MODIS & USA & 1999 & Aqua & \
\begin{tabular}{c} B31 \\ B32 \\ \end{tabular} &
\begin{tabular}{c} 10.78–11.28 \\ 11.77–12.27 \\ \end{tabular} & 1000 m \\ \hline \hline \end{tabular}
\end{table}
Table 1: FY-3D sensor characteristics that correspond to the MODIS TIR Bands are commonly used for retrieving land surface temperature.  
Figure 2: Spectral response functions of the MERSI-II and MODIS TIR channels.
## 2 Introduction
[20] analyzed the dynamic response of a long tunnel and tunnel shaft during an earthquake using a multi-scale method. However, these studies did not consider liquefaction or liquefiable soil characteristics. Liquefaction usually occurs in loose sandy soils that tunnel shafts often pass through, and it can induce a remarkable amount of kinematic force on the shaft body depending on the ground and input earthquake conditions. Therefore, an appropriate investigation of the seismic performance of a tunnel shaft under liquefiable soil conditions is needed to obtain a safe and sustainable seismic design of the entire tunnel system. In this study, three-dimensional numerical modeling was performed to predict the dynamic behavior of a vertical tunnel shaft that passes through a liquefiable loose sand layer. Important parameters such as the thickness of the liquefiable sand layer and input earthquake magnitude were varied and used for the analysis of 12 different cases. The seismicity levels of artificially described earthquake records were defined to reflect the revised Korean seismic design criteria [21]. Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) was used as the simulation tool, and detailed dynamic soil properties and shaft properties were determined based on preliminary analyses and typical conditions. The input earthquake motions were input at the base of the model and artificially defined based on Pohang earthquake records. The upper sand layer was completely saturated and sufficiently loose to liquefy under the applied earthquake levels. This study highlights the key aspects of the seismic behavior of a tunnel shaft under liquefaction, such as excess pore pressure generation and the seismic bending moment, and displacement of the shaft, and provides a meaningful discussion regarding earthquake risk assessment with damage indices based on the analysis results.