esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Theory of Filtering over Vertical Horizontal (HOVE) Angular Grid
#### 2.3.2 Determination of the Point Density  
The output data form a homogenously distributed grid. Due to the repeated filtering, larger holes are normally occurring in some areas and the initial structure is retained in other areas. Where, after repeated filtering, the initial structure is retained, this indicates a continuous terrain surface without much vegetation. These points should be maintained in the further filtering process. Areas which have large gaps in the grid after some filter repeats, however, indicate that the area is generally flatter and has vegetation. A precise distinction between ground and non-ground point is virtually impossible without precise knowledge of the terrain. An automated algorithm can only calculate with probabilities. The probability of a ground point in areas with low grid point density after few iterative filtering is significantly lower than in areas were high grid point density retained. It therefore makes sense to gradually reduce the threshold value of the Wedge Filtering in these areas depending on the grid point density. A HOVE raster is ideal for determining the point density.  
Particularly important is this additional information for small objects, such as hills or edges protruding from the surrounding surface. Such terrain elements are a problem with all filter methods. A remaining high point density after iterative filtering within a certain angular segment and therefore many similar neighbouring points indicates a natural surface even with sharp edges.  
[PERSON] et al. (2016) propose a method to filter terrestrial laser scanner point clouds using morphological filters and spectral information to conserve surface micro-topography.
## 3 Results and Discussion
### Effect of Thermal Modification and Wax Impresation on Water Adsorption and Water Absorption of Wood  
The _EMC_, which indicates the capacity for water adsorption, and the \(W\) which demonstrates the capacity for water absorption, are shown in Figure 1a,b, respectively. In contrast to the control group, the _EMC_ decreased obviously after TM and TM + WI, and the _EMC_ of the TM + WI groups presented the lowest values. In contrast to the control group, the _EMC_ of the 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h TM specimens decreased by 10.87% and 16.94%, respectively, while the 200 \({}^{\circ}\)C/2 h and 200 \({}^{\circ}\)C/6 h TM specimens decreased by 28.32% and 36.16%. These results show that TM decreased the _EMC_ of the wood, and the reduction became greater due to more severe TM, which is in agreement with a previous study [33]. However, after WI the _EMC_ decreased by 69.40% and 73.58% for the 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h TM specimens, presenting the lowest values in the study. Compared with the _EMC_ of the 200 \({}^{\circ}\)C/6 h TM specimens, the _EMC_ decreased by almost half after WI. These results suggest that WI further decreased the capacity of the wood water adsorption. Compared with the control group, the _EMC_ of the 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h TM specimens decreased by 10.87% and 16.94%, respectively, while the 150 \({}^{\circ}\)C/2 h and 6 h TM specimens after WI decreased by 69.40% and 73.58%, thus, the contribution of WI to the reduction of _EMC_ was 58.53% and 56.64%, respectively. The contribution of WI to the reduction of the _EMC_ of the wood was 5.38 times and 3.34 times compared to TM, at 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h. The results suggest that wax impregnation played a dominant role in reducing wood water adsorption capacity, due to a large volume of wax being impregnated into the wood.  
The \(W\), water absorption ratio, was much greater than that of the _EMC_ for all groups, indicating that more water was absorbed into the wood. No significant differences were found in \(W\) between the control group and the groups after 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h TM. Compared with the control group, the \(W\) of the specimens after 200 \({}^{\circ}\)C/2 h and 200 \({}^{\circ}\)C/6 h TM, and the specimens of 150 \({}^{\circ}\)C/2 h and 150 \({}^{\circ}\)C/6 h TM + WI, presented significant differences. In contrast to the control group, the \(W\) of specimens decreased by 13.45% after 200 \({}^{\circ}\)C/6 h TM, and 29.94% after 150 \({}^{\circ}\)C/6 h TM + WI, while the \(W\) of the specimen after 150 \({}^{\circ}\)C/6 h TM barely changed. These results indicate that the WI could reduce the capacity of wood water absorption to a greater extent. The reduced \(W\) may have been caused by the wax, which impregnates fully or partly into cell lumens, occupying some space, and also forms wax films attached to wood cell walls. Consequently, the spaces of the cell lumens for water absorption were reduced, and the free water migration path was blocked due to the hydrophobic property of wax films [29].
The results demonstrated that they performed efficiently without requiring adjustments for angular dependence [28]. A clinical application for the single edgeless diodes in a study of dose escalation for patient-specific QA of functional brain diseases treated by CyberKnife [17] confirmed that the edgeless diodes performed well in verifying the dose specifically tailored for each patient on a set of 10 patients, especially in cases where very high doses are administered, but also highlighted the limitation of having single dose point measurements in assessing the quality of a treatment delivery. This study aimed to assess the feasibility of using single edgeless diodes assembled in a 2D array using an advanced tissue-equivalent bonding technique and verifying that such an array of silicon diodes can perform 2D small-field dosimetry with acceptable accuracy on a plane without the need for correction factors.
# Creation, Analysis and Evaluation of AnnoMI, a Dataset of Expert-Annotated Counselling Dialogues +
## 5 Inter-Annotator Agreement (IAA)  
### Default Measure: Fleiss' Kappa at Utterance Level  
We use Fleiss' kappa [32] as the default measure for calculating utterance-level inter-annotator agreement (IAA) over the annotations on the 7 transcripts. We consider 3 methods of calculation: All, All(Strict), and Binary. All applies to all the utterance attributes, while the other two modes apply to Input, Reflection, and Question only.  
Specifically, since these three attributes have a default \"absence\" option (i.e., no input, no reflection, and no question, as shown in Table 4), we compute a two-class presence-vs.-absence (i.e., Binary) IAA for them, in addition to the fine-grained all-class IAA (i.e., All). When computing All-IAA for Question, for example, we consider the original label space: {Open question (+), Closed question (+), No question (-)}, where (+) means that there is a question in the utterance and (-) means that there is not. Conversely, we only consider the presence-vs.-absence [(+), (-)] space when calculating Binary-IAA.  
We also calculate All(Strict)-IAA, which computes IAA within the original label space but on a more challenging subset of utterances, motivated by the observation that it is substantially more difficult to distinguish between the presence (+) labels than between presence (+) and absence (-). For example, differentiating between \"Simple reflection (+)\" and \"Complex reflection (+)\" is more difficult than between Reflection and non-Reflection. Therefore, we compute All(Strict) on the utterances where at least one annotator chose a presence (+) option. For Reflection, for example, we calculate All(Strict)-IAA on the utterances where at least one annotator selected \"Simple reflection (+)\" or \"Complex reflection (+)\".
## 4 Discussion
### Limitations and Strengths  
The most important limitation of this study is that this study did not analyse all matches from the group stage of the UCL. Specifically, only 20 randomly selected matches were observed. In addition, the study did not include the influence of specific factors that can affect the RPs in the AP and DP of the game, such as the team quality, tactical formation, quality of the opponent and information about sector of the playing field where the running actions were developed.  
This was the first study to assess the RP separately in the AP and DP of the game in different teams in relation to their achievement in the UCL. Moreover, our study was the first to utilize five different speed categories and playing positions with respect to the RP.  
Specifically, previous studies have mostly included the total distance covered and one to two speed categories. In contrast, this study included the total distance covered, as well as the walking, jogging, running, high-speed running, and sprinting distances covered in the AP and DP of the game. In addition, previous studies have mostly included the team's RP to analyse these issues, while this study included the RP of the players in different playing positions. This approach enabled a more detailed analysis of the RP and information about the individual contributions of the players.
## 4 Experiment and Result Analysis
### Experimental Environment and Parameter Settings
#### 4.1.1 Baseline  
In order to compare the performance differences between different detection methods, the OD-LSF method is compared with the following four methods: (1) Reference [19]: It is a new method, recently proposed, which can calculate the probability that a superpixel point cloud belongs to an obstacle according to its height from the road surface, and complete the obstacle detection in traffic scenes; (2) Reference [10]: It is a classic obstacle detection method based on stereo vision that can describe the traffic scenes using a multi-layer stixel; (3) The OD-PNV method proposed in this paper; (4) The OD-SPH method proposed in this paper. For the convenience of comparison, the outputs of reference [19], the OD-PNV method and the OD-SPH method are represented in the form of a stixel using the SGA-SO proposed in this paper. The detection performance of the methods based on the obstacle height can be evaluated by comparing reference [19] with the OD-SPH method, and the detection performance of the fusion methods can be evaluated by comparing OD-LSF with OD-PNV and OD-SPH.
## 2 Broadband System
### Wireless Broadband System
#### 2.2.3 Local Multipoint Distribution Service  
The LMDS wireless access technology concept is very similar to that of MMDS. It is a terrestrial PtMP radio service that offers wireless broadband access to the subscribers' fixed networks located throughout the target service area [16; 113; 153]. It offers an ideal solution for offering high-bandwidth services to subscribers, especially over an area where the wired network might be uneconomical or inconvenient. As illustrated in Figure 5, a sector antenna is employed at the BS for signal transmission in a PtMP manner over a planned coverage area. Therefore, the BSs are generally configured as a sectorized site to ensure frequency reuse while multiple users can be assigned to any of the sectors. Usually, the number of channels as well as the general frequency plan is determined by the available spectrum in a specified market and the aggregate capacity demanded in a particular geographic zone. However, LMDS typically operates in the higher radio frequencies between 27.5 GHz and 31 GHz [16; 113; 151; 154]. As a result of this, it gives considerably better bandwidth compared with MMDS. In addition, LMDS can give two-way broadband services such as multimedia data, voice, internet, and video [16; 155]. For effective transmission, LoS is required between the BS and customer transceiver (TRx) with typical downstream (DS) rates between 45 to 155 Mbps. Moreover, for wide-area coverage, LMDS presents a more cost-effective solution compared with PtP microwave links. Nevertheless, owing to challenging issues such as multipath fading, shadowing, rainfall, and free-space attenuation effects at the frequency of operation, its range capability is limited [16; 113; 156; 157; 158]. Similarly, the available radio spectrum limits the achievable capacity and individual peak data rate for the subscriber [16]. Besides, another related problem is a way of gaining access to the rooftops for antenna installation [159].  
Figure 5: A typical LMDS architecture.
## 4 Evaluation of Prototypes with Edge Damping
### Mechanical Vibration Measurement  
All laser measurements were performed at the Technical University of Dresden with the Keyence HK-052 triangulation laser head and the Klippel KA3 measurement system, as shown in Figure 13. The triangulation laser is optimized for displacement measurements, and the displacement decreases by approximately 12 dB per octave above the fundamental resonance frequency, which reduces the signal-to-noise ratio (SNR). A sufficient SNR of the measured signal to 10 kHz with a 10 dB overhead can be reached by averaging the signal 256 times and shaping the stimulus to increase the displacement at higher frequencies. Due to the short time signal at higher frequencies, the signal voltage can be increased to 8 Vrms in the frequency range from 5 kHz to 10 kHz. Furthermore, the following data are displayed instead of displacement in acceleration to guarantee a more straightforward evaluation. The decay of 12 dB per octave of the displacement response is removed in the acceleration domain. The acceleration is the second derivative in the frequency domain calculated from the displacement signal multiplied by minus omega squared.
# An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers
## 2 The Resource Scheduling Model in Containerized Microservice
### Critical Factors in Resource Scheduling
#### 2.3.2 Resource Utilization  
Because the computing resources in the edge cloud are relatively small compared to traditional data centers, the energy consumption of the physical host when it is not loaded accounts for around 70% of the energy consumption when it is fully charged. Therefore, it is of considerable significance to the edge cloud data center to effectively use the computing resources and reduce the energy consumption in the data center. When resource scheduling is performed, one of the optimization goals is to occupy the lowest number of physical hosts under the premise of meeting their needs, so that the resources of the physical hosts are effectively used.  
We define the parameter Z to represent the total number of physical hosts occupied by deploying containers with microservices, as shown in Equation (8). In the entire edge cloud, the overall resource utilization rate of the physical host group activated for the deployment of microservices is represented by the parameter U, as shown in Equation (9).  
\[Z=\sum\limits_{i=1}^{n}{{P_{i}}} \tag{8}\]  
\[U=\left({\frac{{\sum\limits_{i=1}^{n}{{\sum\limits_{j}^{m}{{\sum\limits_{j}^{s }{{p_{i}}\times{k_{ij}}\times{r_{jl}}}}\over{{\sum\limits_{i}^{n}{{\sum\limits_{j}^{s }{{p_{i}}\times{c_{il}}}}}}}}}}}}}}}\right) \tag{9}\]  
In the edge cloud computing center, microservices have different requirements for different types of resources, so it is easy to cause a load of various types of resources in the physical host to be unbalanced, thereby causing a waste of server resources. To effectively use various resources, an optimization goal is to make the physical server achieve a better resource balance as much as possible. This study defines the quantitative calculation method of resource utilization, as shown in Equation (10), where \(u_{il}\) represents the utilization of type \(l\) resources on host \(i\). The parameter \(u_{i}\) represents the average utilization rate of all resources on the physical host \(i\).  
\[\left\{{\begin{array}{*{20}{c}}{{u_{il}}}=\frac{{{\sum\limits_{i=1}^{m}{{k_{ ij}}\times{r_{jl}}}}}}{{{c_{il}}}}\\ {{u_{i}}}=\frac{{1}}{{s}}\sum\limits_{l=1}^{s}{{u_{il}}}}\\ \end{array}}\right. \tag{10}\]
# Autonomous Navigation Based on the Earth-Shadow Observation near the Sun-Earth L2 Point
###### Abstract
Moreover, while the relative navigation between the objective spacecraft and the observation spacecraft can be achieved by the other measurement information, the absolute navigation is hard to achieve [22; 23; 24]. [PERSON] et al. [25] proposed an autonomous navigation method for spacecraft based on intersatellite ranging and orbit orientation parameter constraints. This method assumes that the coordinates connected to the Earth and the absolute orientation of the constellation in inertial space cannot be established solely through inter-satellite ranging. Thus, its orbit must be determined by combining dynamic equations and prediction information [26; 27; 28]. [PERSON] [29] studied the inter-satellite distance measurement technology in the static and dynamic environment, discussed the autonomous navigation technology based on the intersatellite distance measurement, and proposed a ranging technology that can gradually improve the precision in a static environment. The study also proved that the high-precision distance between spacecraft could not be obtained only through inter-satellite distance measurement [30; 31; 32]. Based on the related Earth-shadow researches [33; 34], we focus on the autonomous navigation at the Sun-Earth L2 point. The difficulty of navigation around the Sun-Earth L2 point is that there are few observations available for navigation [35; 36; 37]. This paper studies the autonomous navigation method based on the Earth-shadow observation near the Sun-Earth L2 point. This method determines the position and velocity of the spacecraftby measuring the proportion that the Sun is blocked by the Earth. In Section 2, we build the dynamic model and establish the measurement model of the Earth-shadow. Then, we derive the expression of the measurement function from three different observation scenarios. In Section 3, we apply the fifth-degree cubature Kalman filter algorithm to simulate the different models with an amplitude of 5000 km along the X direction. In Section 4, we obtain the simulation results of navigation and provide the analysis of the simulation results. Finally, the conclusions are given in Section 5.
## 2 Statistical Models
### Natural Language Preprocessing  
A document may be considered a sequence of characters not separated by punctuation marks or spaces, which is an obstacle to the further processing of the document. For this purpose, text segmentation methods are used, which involve partition of the text into words and punctuation marks or dividing documents into utterances. In general, for languages with specified utterance boundaries, segmentation can be performed by splitting texts by punctuation marks or apostrophes, but there are cases where this simple rule does not work, for example, with abbreviations or possesses. This process is essential for most text representation algorithms that operate on single words or tokens.  
The noise can be reduced by limiting the size of the dictionary. This can be achieved by different methods (described further), but during preprocessing it can be done by simplifying different inflexion forms of the same word. Three methods are used for this purpose: morphological analysis, lemmatisation and stemming. Morphological analysis is a method of natural language analysis, which provides information on grammatical properties and brings words into basic forms. The second method is based on simplifying words by reducing their inflected forms, for instance, \"better\" \(\rightarrow\) \"good\". This method is usually used when processing languages with rich flexion, for example, Polish. The last method of reducing vocabulary size is stemming, which brings words into their basic form, for example, \"running\", \"runs\", \"ran\" \(\rightarrow\) \"run\".  
Documents are usually gathered from different sources and in different data formats, such as XML and HTML. Thus, during processing, the format of texts should be unified. Usually, they contain special characters, for example, text decorations used on Internet forums or e-mail addresses, which should be removed to reduce the bias of machine learning models.  
In natural language, some words are required by language syntax but they do not carry much information. They are often the most frequent words in a given language and are often removed from texts to reduce vocabulary size, accelerate computations and reduce bias. Examples of stop words in English are: \"the\", \"a\", \"an\". The drawback of this step is spoiling the syntax properties of text.
### Conception  
The main objective is making it possible to show data path applications on FPGA, which handles the acceleration tasks and passes packets to the NICs effectively, utilizing the least amount of FPGA hardware resources possible, as shown in Figure 1.  
As it allows for additional consolidation by fitting many application accelerators on the same FPGA, minimal utilization of the FPGA resources is particularly significant [15].  
Instead, the decision to adopt XDP is driven by two advantages that the technology offers [16]. Because it offers an on-NIC optimization method that is widely known to a sizable community for Unix coders, programmers are spared from having to learn novel development tools like those offered by P4 or Flow Blaze It also makes NIC offloading for XDP programmes that have previously been deployed simple [17; 18].  
Requirements: From the discussion above, we list three high-level requirements for hXdp:  
1. It must run compiled XDP programmes without modification and, therefore, must support the provided coverage foundations' tool chain, providing immense contribution to reloading and user-mode access to maps.
2. Performance for processing packets ought to be at least on par with top-tier processing packets.
3. It can be utilized only for the small portion of the hardware in the FPGA.  
Figure 1: Specific accelerators of FPGA NIC resources and hXdp network accelerator.  
We will now provide a quick history of XDP before providing a more thorough explanation of the hXDP idea.
## 3 A Routing Protocol Based on Energy and Link Quality (REL)
### Link Quality Estimation
Most of applications require high Packet Delivery Ratio (PDR), _i.e._, higher than 80%, to ensure reliable data delivery/QoS support between nodes, as expected for many WSNs/IoT applications, e.g., healthcare or intrusion detection. Thus, in this work we conduct experiments to find the optimal \(LQI_{th}\) that can provide a PDR higher than 80% (see Section 4.1). Additionally, REL has an opportunistic behavior, since it uses all the received packets to continuously analyze the LQI value. As result, this solution provides a more accurate measurer means of frequent updates of the link quality for a given route. In contrast with other schemes, our proposal evaluates routes by using the average of the LQI value of a given destination. REL stores \(n\) values of LQI for each destination, computes the average rather than individual ones. Using the average values of LQI, it is possible to reduce the risk of constant switching between available routes, causing additional delay, and overhead. Thus, when _WeakLinks_ is used, REL is less susceptible to extensive link quality variation.