esa-sceva/satcom-chunk-collection huggingface dataset:
# Load Prediction Control Study of a Pitch Control System for Large Offshore Wind Turbines
[PERSON], designed a two-level control architecture for multi-rotor turbines with the following characteristics: (1) A decentralized primary control system using oversized generators replaces conventional pitch control for power limitation; (2) A higher-level controller coordinates auxiliary turbine thrust through torque adjustments to alleviate main tower mechanical loads [22]. [PERSON], [PERSON], proposed a variable pitch control strategy incorporating active blade damping, demonstrating improved power output stability, enhanced generator speed control precision, and reduced blade root loads [23]. [PERSON], [PERSON], implemented a robust perturbation regulation controller through independent pitch control, achieving fatigue load reduction on blades and towers while maintaining generator speed performance [24]. [PERSON], [PERSON], conducted Aerodyn simulations of the National Renewable Energy Laboratory (NREL) 5-MW turbine, analyzing cyclic pitch modulation effects. The results confirmed significant load fluctuation reduction at specific pitch amplitudes and phases [25]. [PERSON], [PERSON], investigated active yaw control, revealing a greater than 90% blade load reduction and decreased tip vibration through optimized yaw angle adjustments compared to the results for non-yawing turbines [26]. [PERSON], developed an adaptive fault-tolerant pitch tracking controller, addressing aerodynamic uncertainties, actuator failures, and time-varying parameters, achieving effective dynamic compensation and precise pitch angle control [27]. [PERSON], introduced an L1 neural network adaptive control strategy to handle non-affine nonlinear characteristics in high-wind-speed turbine operations [28]. [PERSON], designed a hybrid pitch control strategy integrating state feedback with disturbance accommodating control (DAC), successfully mitigating wind disturbance impacts while improving power stability and reducing structural loads [29]. While the aforementioned scholars have investigated load force prediction and pitch control strategies for wind turbines, the load perturbation phenomenon during the pitch process remains underexplored. Specifically, the impact of load perturbations on pitch accuracy has not been systematically analyzed. Furthermore, research on the high-performance control of electro-hydraulic servo-pump-controlled pitch systems remains limited, particularly regarding their application to wind turbines operating in complex environments. This paper presents an electro-hydraulic servo pump-controlled independent pitch hydraulic system and analyzes the geometrical relationship of the pitch mechanism. A mathematical model is established to characterize the relationship between hydraulic cylinder displacement, external load force, and servomotor rotational speed. To address the impact of load disturbances on pitch accuracy, a load disturbance observation method is adopted. Furthermore, a load disturbance-compensated position control strategy is proposed, and its effectiveness is validated through simulation and experimental analysis.
## 2 Literature Review
### A Review of Factors Influencing BEVUX  
Existing academic research primarily focuses on the technical feasibility of BEVs and initial user responses, typically emphasizing individual vehicle characteristics. For instance, [PERSON] et al. explored the critical role of UX in evaluating BEVs, highlighting advantages in areas such as low noise, driving pleasure, performance, and environmental friendliness [13; 14; 15; 16]. Additionally, [PERSON] et al. investigated the implications of BEV quietness on driving safety, finding that experienced drivers tended to react more quickly in critical situations [17]. [PERSON] et al. introduced the concept of a \"range comfort zone\" to evaluate the impact of driving experience on range anxiety, suggesting that driving expertise significantly contributes to user satisfaction [18].  
Advancing research has increasingly recognized the multifaceted nature of UX. [PERSON] et al. performed an exhaustive synthesis of the literature to pinpoint determinants of electric vehicle adoption, encompassing technological characteristics, usage context, cost considerations, and personal and social factors [19]. [PERSON] and [PERSON] revealed the substantial impact of social norms and perceived behavioral control on the adoption of electric vehicles [20]. [PERSON] et al. determined the salient factors that undergird user satisfaction with BEVs, including vehicle performance, charging infrastructure availability, and supportive government policies [21].  
Recent studies highlighted how various driving conditions impact BEV user experience. For instance, [PERSON] et al. found the BEV range reduced to 64% in winter conditions due to cold temperatures [22]. Similarly, [PERSON] et al. observed that battery efficiency dropped significantly in colder climates, leading to decreased range [23]. Urban versus rural environments also create distinct experiences. [PERSON] et al. reported higher energy consumption in urban traffic, while rural users can optimize range by adjusting travel times [24].  
Furthermore, [PERSON] et al. scrutinized how the intricacies of BEV driving experience bolster user confidence and adoption intentions [25]. In particular, [PERSON] and [PERSON] showed that BEVs perform more efficiently in urban driving but lose range at highway speeds [26]. In mountainous areas, frequent braking and acceleration elevate energy consumption and reduce range satisfaction. [PERSON] and [PERSON] highlighted that driving behaviors, such as acceleration and braking style, can extend the range and improve the UX when managed effectively [27].  
This body of research highlights the critical need for a comprehensive, multidimensional approach that integrates a range of factors--including driving environment, seasonal climate variations, and user behaviors--into the evaluation of BEV user experience. Nevertheless, current studies predominantly emphasize singular factors, lacking a holistic framework that systematically considers these interconnected influences.
# Retrieval and Comparison of Multi-Satellite Polar Ozone Data from the EMI Series Instruments
## 2 Data  
The second-generation EMI series are Chinese imaging spectrometers on board the GaoFen-5 (GF-5) and DaQi-1 (DQ-1) satellites that are used to monitor atmospheric constituents such as O\({}_{3}\) and NO\({}_{2}\) and the properties of various other trace gases [35; 36; 37]. At present, a multi-satellite observation network of three satellites hosts the EMI series instruments: the Environmental Trace Gas Monitor EMI-GF5 (02) (launched in 2021), the Hyperspectral Integrated Observation Satellite Atmospheric Trace Gas Differential Absorption Spectrometer EMI-DQ01 (launched in 2022), and the Atmospheric Environment Satellite Ultraviolet Hyperspectral Atmospheric Composition Detector EMI-GF5 (01A) (launched in 2022).  
The EMI series instruments orbit the earth 14-15 times per day, have a spatial resolution of currently 13 \(\times\) 24 km\({}^{2}\) at nadir, and have a large swath of 2600 km [35; 36; 37; 38]. The technical specifications for the spectral resolution, spectral range, overpass time, and other indicators of the three EMI instruments are listed in Table 1.  
TROPOMI is onboard the S5 Psatellite, with an overpass time of 13:30 LST. TROPOMI TOC products have been extensively verified by satellite data and ground observation data, and the mean deviation and mean standard deviation between TROPOMI and ground TOC are within 2% and 5% [34]. The TROPOMI dataset, including the daily mean VCD product (source: [https://s5 phub.copernicus.eu/dhus/#/home](https://s5 phub.copernicus.eu/dhus/#/home); last accessed 10 May 2024), were compared to the EMI series retrieval results.  
In addition, the WOULC dataset (source: [[https://woudc.org](https://woudc.org)]([https://woudc.org](https://woudc.org)); last accessed 10 May 2024) and the Reliable System data from the Systeme d'Analyse par Observations Zenithale (SAOZ) (source: [[http://saoz.obs.uvsq.fr/SAOZ-RT_2023.html](http://saoz.obs.uvsq.fr/SAOZ-RT_2023.html)]([http://saoz.obs.uvsq.fr/SAOZ-RT_2023.html](http://saoz.obs.uvsq.fr/SAOZ-RT_2023.html)); last accessed 12 June 2024) dataset were used to evaluate the performance of the EMI series TOCs.
# Benefits and Lessons Learned from the Sentinel-3 Tandem Phase
## 3 The Sentinel-3 Tandem for Climate Study
### Main Results  
Table 1 below provides an overview of the main analyses performed on Sentinel-3 tandem data and the outcomes and lessons learned. These points are further described in the rest of the paper.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sensor** & **Products** & **Analyses** & \begin{tabular}{c} **Outcome and** \\ **Lessons Learned** \\ \end{tabular} & \begin{tabular}{c} **References (Paper** \\ **or Subsection)** \\ \end{tabular} \\ \hline SRAL & SSH & \begin{tabular}{c} Signal correlation under \\ different swell conditions \\ \end{tabular} & \begin{tabular}{c} Quantified impact of swell on \\ SAR acquisitions \\ \end{tabular} & [16] \\ \hline SRAL & Ice surface height & \begin{tabular}{c} Comparisons at different sites \\ Triple co-location with \\ IceBridge measurements \\ \end{tabular} & \
\begin{tabular}{c} Sentinel-3A and B are \\ statistically indistinguishable \\ on land ice. \\ Accuracy ranges from the \\ order of -0.1 m (inland \\ regions) to -1 m \\ (coastal regions). \\ \end{tabular} &
\begin{tabular}{c} [17] and Section 9.2 \\ regions) to -1 m \\ (coastal regions). \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 1: Overview of the Sentinel-3 tandem for climate analyses.
# A Review of Seatbelt Technologies and Their Role in Vehicle Safety
## 3 Results
### The Retractor  
Over the years, innovations in retractor mechanisms have significantly uplifted occupant protection, integrating advanced technologies such as acceleration sensors and energy absorption systems. Various patents have been filed, proposing novel improvements to seatbelt retractors; some have been developed into practical applications, while others present ideas that warrant further exploration and refinement. For instance, in [13], a vehicle acceleration sensor for seatbelt retractors was introduced, aimed at improving the responsiveness of the retraction mechanism during sudden deceleration. Similarly, [PERSON]. [14] proposed a seatbelt retractor with an energy absorption mechanism, designed to regulate the force exerted on the occupant in the event of a crash. Another noteworthy innovation by [15] focuses on an improved seatbelt retractor and seatbelt device, potentially enhancing the overall efficiency of the restraint system.  
While these patents highlight significant advancements in seatbelt retractor technology, further research and development are necessary to optimize their real-world implementation. Further on, we will explore the current state of the art, analyzing key contributions from studies that have shaped modern seatbelt retractor systems. The role of the retractor is to store the seatbelt webbing and to lock it in case of an impact through two distinct mechanisms. According to ECE-R16 [12], for locking retractors, the seatbelt webbing must not move more than 25 mm between two successive locking positions. In variants where  
Figure 7: Seatbelt label.  
operation is powered by an external energy source, the retractor must immediately lock in the event of a power interruption.  
The retractor contains two locking mechanisms that stop the spool's movement when the vehicle is involved in a collision. The two types of locking mechanisms used are presented in Table 2.  
In Figure 8, the ball-in-cup inertial locking mechanism, a vehicle-sensitive component integrated within a seatbelt extractor to enhance occupant safety during sudden deceleration, is presented. Under normal driving conditions, a steel ball rests securely within a shallow cup, allowing the retractor to freely extend and retract the seatbelt. In the event of rapid deceleration or impact, the vehicle's inertia causes the ball to dislodge from the cup due to the change in momentum. As it shifts, the ball contacts a lever or pawl, which in turn engages a ratchet gear attached to the spool, immediately locking the belt in place. This mechanical response prevents further belt extension, restraining the occupant and minimizing forward motion during a collision.
## 1 Introduction
However, studies pertinent to the protection of key targets from damages caused by projectile ricocheting have received less attention. Setting up a bulletproof board wall with uniform strength around the target is a conventional protective method, while this aimless prevention measure neither eliminates the threat of secondary damage from a ricochet projectile completely nor benefits from achieving an economical defence. Accordingly, it is significant to develop an effective way to predict the ricochet range of a projectile obliquely penetrating the target by utilizing ballistic prediction technology so as to identify the most critical area for battlefield protection and build a well-focused and flexible defence against ricochet projectiles. In this study, the ricochet range of a projectile obliquely penetrating a thick steel target is purposefully investigated. Firstly, the moment of momentum (MM) equation of a ricochet projectile based on theoretical mechanics is utilized to analytically calculate its trajectory, where a mathematical model of two-stage ricochet impacting is established through geometrical analysis of the ricochet process for determining the ricochet range of the projectile and the size of the bulletproof structure. Then, impacting experiments of projectile obliquely penetrating thick steel targets at different striking velocities and inclination angles are carried out, and the influences of the striking velocity and angle of attack on the damage pattern, area and penetration depth are discussed to identify the ricochet phenomenon. Moreover, the deflection angle of the ricochet projectile is computed and compared with the experimental measurements in order to validate the accuracy of this proposed model. This proposed research may promote security protection in live-firing training and provide a theoretical foundation for the optimization of purposeful protection.
# A Programmable SRv6 Processor for SFC
## 3 Protocol-Independent Pipeline Design
### Programmable SR Forwarding for Network Slice
#### 3.4.2 Multiple Semantics and Function for SID  
The programmable capability of SRv6 comes from the following three parts: (1) multiple segments can be combined to form SRv6 paths, that is, paths can be edited. (2) the SRv6 segment defines network instructions in the SRv6 network programming, indicating where to go and how to get there. The ID that identifies an SRv6 segment is called an SRv6 SID. An SRv6 SID is a 128 bit value in the form of an IPv6 address, and it consists of three parts, namely the locator, function, and arguments. Each segment of SRv6 is 128 bit, which can be flexibly divided into multiple segments. The function and length of each segment can be customized, so they have flexible programming capability, that is, they are service editable. (3) When packets are transmitted on the network, irregular information needs to be encapsulated on the forwarding plane. This can be accomplished by using the flexible combination of optional type-length-value (TLV) in SRH, that is, the application editable.  
In programmable SRv6 processor, you can complete the complex processing of packets by adding SID entries to the actions table of the deparser plus and using the SID's function field to look for instructions that need to be executed. After instructions are passed to the PDT module, the PDT controls the action module to execute the instructions represented by the function field.
# Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series
## 3 Data and Methods
### Reference Datasets
The splits were performed on the polygon level to minimize the effects of spatial correlation. We randomly split the _rice_ polygons into 50% used for training of the model, 25% used for model selection and 25% for accuracy assessment. No data for training the model were necessary from the _no_rice_ class, so we split it into 50% used for model selection and 50% for accuracy assessment. For the training, selection and validation of our model, we used all MODIS pixels where the centroid was located inside one of the polygons, resulting in a total of 27,384 useable pixels for the _rice_ and 26,936 for the _no_rice_ class. Figure 2: Distribution of reference data in mainland China’s major rice growing regions. Additionally we acquired agricultural census data at the province level from China's Statistical Yearbooks [2, 50, 51, 52]. The basis for this data is the censuses at the county and township level, which are collected by Statistical Bureaus at the province level, as well as reports by state-owned farms collected by the Bureau of Reclamation. These data are compiled into Statistical Yearbooks by the National Bureau of Statistics of China [2]. The data we used were _Output of Rice_, _Total Sown Area of Rice_ for the years 2014, 2010, 2005 and 2002, as well as _Sown Area of Early Rice_, _Sown Area of Middle-season Rice and Single-Cropping Late Rice_ and _Sown Area of Double-Cropping Late Rice_ for the years 2010, 2005 and 2002. The province names used throughout this paper have been taken from China's Statistical Yearbooks, and the province boundaries have been extracted from the Global Administrative Areas dataset [65].
# A 11 mW 2.4 GHz 0.18 \(\upmu\)m CMOS Transceivers for Wireless Sensor Networks
## 5 Conclusions  
This paper presents a low-cost 2.4 GHz CMOS transceiver. An input-output matching network is shared by the LNA and PA to save silicon and simplify the topology. Power consumption optimization is carried out in the phase-locked loop to maintain a good balance among phase noise and working range. Implemented in standard 0.18 \(\upmu\)m CMOS technology, the proposed work is able to work 2.4 GHz with 500 K bps transferring rate, while consumption is 11 mW from a 1.8 V supply voltage.
###### Abstract  
The aim of this research work is to investigate the innovative concept of magnetohydrodynamic (MHD) three-dimensional rotational flow of nanoparticles (single-walled carbon nanotubes and multi-walled carbon nanotubes). This flow occurs in the presence of non-linear thermal radiation along with heat generation or absorption based on the Casson fluid model over a stretching sheet. Three common types of liquids (water, engine oil, and kerosene oil) are proposed as a base liquid for these carbon nanotubes (CNTs). The formulation of the problem is based upon the basic equation of the Casson fluid model to describe the non-Newtonian behavior. By implementing the suitable non-dimensional conditions, the model system of equations is altered to provide an appropriate non-dimensional nature. The extremely productive Homotopy Asymptotic Method (HAM) is developed to solve the model equations for velocity and temperature distributions, and a graphical presentation is provided. The influences of conspicuous physical variables on the velocity and temperature distributions are described and discussed using graphs. Moreover, skin fraction coefficient and heat transfer rate (Nusselt number) are tabulated for several values of relevant variables. For ease of comprehension, physical representations of embedded parameters such as radiation parameter \((Rd)\), magnetic parameter \((M)\), rotation parameter \((K)\), Prandtl number \((Pr)\), Biot number \((\lambda)\), and heat generation or absorption parameter \((Q_{h})\) are plotted and deliberated graphically.  
Single-Walled Carbon Nanotube (SWCNT); Multi-Walled Carbon Nanotube (MWCNT); MHD; Casson model; stretching sheet; non-linear thermal radiation; HAM
# Laser Technology in Photonic Applications for Space
## 2 Laser Devices
### Semiconductor Lasers
#### 2.1.1 Edge-Emitting Laser (EEL)  
EELs are the most common semiconductor laser devices. Thanks to their diode junction structure, these devices can transform electrical energy into light. Apart from SSL pumping, they are mostly suited to applications, such as information relay (inter and intra satellite), matter light interaction (spectroscopy and pyrotechnics), planetary exploration and monitoring, metrology, and sensors [11]. Some direct applications for which they are being used include, for instance, the autofocus system of the ChemCam laser [12] or the rendezvous sensor for the docking of the European Automatic Transfer Vehicle to the International Space Station (ISS) [13]. EEL have already been deployed in satellites, in deep space, and also on the Martian surface.
## 2 Model Experiments  
### Design of Experiment Parameters  
Based on the law of similitude, this paper establishes the similitude relation between indoor model experiments and the field prototype test. A total of 15 physical quantities were considered in this experiment, which are: tamping energy (\(E\)), mass of tamper (\(W\)), tamper's bottom area (\(A\)), drop height (\(H\)), compactness (\(K\)), embedded depth of reinforced geogrid (\(S_{rf}\)), interval of reinforced layers (\(S_{c}\)), number of reinforced layers (\(N_{c}\)), deflection of first reinforced layer (\(S_{g}\)), elastic modulus of reinforced geogrid (\(E_{g}\)), number of tamper passes (\(N_{h}\)), crater depth on unreinforced condition (\(H_{uf}\)), crater depth on reinforced condition (\(H_{rf}\)), effective reinforced depth (\(D_{e}\)), and earth pressure (\(P\)). The physical equation is shown as follows.  
\[f\Big{(}E,W,K,N_{c},N_{h},E_{g},P,H,H_{uf},H_{rf},S_{rf},S_{c},S_{g},D_{e},A \Big{)}=0, \tag{1}\]  
By selecting \(W\) and \(H\) as the basic quantities, the other 13 quantities can be expressed as dimensionless variables \(\pi_{i}=(i=1,2,\cdots,13)\), the physical equation is \(f(\pi_{1},\pi_{2},\pi_{3},\cdots,\pi_{13})=0\). The physical equation can be further expressed as follows.  
\[f\Bigg{(}\frac{E}{WH},K,N_{c},N_{h},\frac{E_{g}H^{2}}{W},\frac{PH^{2}}{W},\frac {H_{uf}}{H},\frac{H_{rf}}{H},\frac{S_{rf}}{H},\frac{S_{c}}{H},\frac{S_{g}}{H}, \frac{D_{e}}{H},\frac{A}{H^{2}}\Bigg{)}=0, \tag{2}\]  
If the similarity constant of the tamper weight and the drop height is determined, the similarity constant of other related physical quantities can be calculated. In field engineering, tamper weight is 200 kN, drop height is 10 m, and tamping energy is 20,000 kN\(\cdot\)m. In a model experiment, tamper weight is 25 N, drop height is 1.0 m, and tamping energy is 25 N\(\cdot\)m. The ratio of earth pressure and displacement between the model and prototype is 1:80 and 1:10, respectively. In this paper, each layer was initially filled to a thickness of 10 cm and then hammered down to a thickness of 5 cm. After testing, the dry density of the soil sample is 1.63 and the experiment is executed under strict control of an initial compactness of 0.93.
# An AUV-Aided Cross-Layer Mobile Data Gathering Protocol for Underwater Sensor Networks +
## 3 System Model
### Network Architecture  
A homogeneous network of sensors is assumed in terms of transmission range and power. Sensors are anchored to the subsea-floor to be fixed within the network topology [21; 23]. To measure the pairwise distances, the Received Signal Strength Indicator (RSSI) is used by sensors. No localization to obtain the exact geographical coordinates is required in our proposed model.  
An AUV can operate at a fixed depth above the acoustic sensors while it can move freely in all directions. The full geographical coordinates of each node can be obtained by the AUV when it approaches the sensors within the field. AUV can mark the locations where it receives data from [24]. All collected data by AUV will be delivered to a static sink on the water surface. These assumptions have been widely used in the literature [21; 23; 24].