esa-sceva/satcom-chunk-collection huggingface dataset:
# The Implementation of Precise Point Positioning (PPP): A Comprehensive Review
## 3 PPP Models
### Ambiguity-Fixed PPP
At the user's end, after applying the received correction \(\Delta b^{s}_{A_{MW}}\), \(N_{WL}\) is fixed by smoothing the \(\Delta A_{MW}\) observation to get rid of the noise term \(\Delta e_{A_{MW}}\). Subsequently, \(N_{WL}\) is substituted in (50) to resolve the \(N_{1}\) ambiguity. Although \(N_{1}\) is the L1 phase ambiguity, it is usually referred to as the NL ambiguity. The phase biases are called the NL FCBs, because \(N_{1}\) is multiplied by \(17\lambda_{IF}\), equaling \(\lambda_{NL}\). The NL biases tend to vary more rapidly than their WL counterparts and, therefore, can be modeled as piecewise constants [68]. Even with corrections provided directly by the network, a substantial initialization period is still required to smooth the measurements and allow changes in satellite geometry for resolving the IAs [82]. Fixing the IA can be accomplished by simple rounding, bootstrapping, or more advanced integer least-squares techniques like the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) method [83; 84].
# Routing Protocols for Delay Tolerant Networks:
## 2 Reference Architecture
### Implementation Aspects of DTN Routing Protocols
BubbleRap combines the knowledge on the community structure and the centrality of the nodes to decide whether to forward. Each message has two types of ranking, global and local (related to its community). Forwarding is done using the global ranking, until the message reaches a node that is in the same community of the destination node. Then, local ranking is used until the destination is reached or the message expires. Each node forwarding a message does not delete its copy unless the message is delivered to the community of its destination. In this case, forwarding is social based, and replication is unlimited. In SimBet, similarity and betweenness utility functions are combined to select the message to be forwarded, and there is only a single copy of the message in the network (_i.e.,_ no replication). \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Direct**} & \multicolumn{3}{c}{**First**} & \multicolumn{3}{c}{**Spray-and**} & \multicolumn{3}{c}{**Fuzzy**} & \multicolumn{3}{c}{**ScAR**} & \multicolumn{3}{c}{**FAD**} & \multicolumn{3}{c}{**MaxProp**} & \multicolumn{3}{c}{**RAPID**} & \multicolumn{3}{c}{**Cluster**} & \multicolumn{3}{c}{**Work**} & \multicolumn{3}{c}{**HiBOp**} & \multicolumn{3}{c}{**SimDet**} & \multicolumn{3}{c}{**BubbleExp**} \\  & & **Contact** & **Contact** & **E** & **PRoPRET** & \multicolumn{3}{c}{**Swap-and**} & \multicolumn{3}{c}{**Fuzzy**} & \multicolumn{3}{c}{**SCAR**} & \multicolumn{3}{c}{**FAD**} & \multicolumn{3}{c}{**MaxProp**} & \multicolumn{3}{c}{**RAPID**} & \multicolumn{3}{c}{**Cluster**} & \multicolumn{3}{c}{**NFTCAR**} & \multicolumn{3}{c}{**ORWAR**} & \multicolumn{3}{c}{**HiBOp**} & \multicolumn{3}{c}{**SimDet**} & \multicolumn{3}{c}{**BubbleExp**} \\ \hline \multirow{5}{*}{FW} & Direct Del. & \(\surd\) & - & - & - & \(\surd\) & - & - & - & - & - & - & - & - & - & - & - & - & - & - \\  & Always & - & \(\surd\) & \(\surd\) & - & \(\surd\) & \(\surd\) & - & - & - & - & - & - & - & - & - & - & - & - \\  & Context & - & - & - & - & - & - & \(\surd\) & - & - & - & - & - & - & - & - & - & - \\  & History & - & - & - & \(\surd\) & - & - & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & - & \(\surd\) & - & - & - \\  & Social & - & - & - & - & - & - & - & \(\surd\) & - & - & - & - & - & - & - & \(\surd\) & - \\ \hline \multirow{5}{*}{R} & Single & \(\surd\) & \(\surd\) & - & - & - & - & - & - & - & - & - & - & - & - & - & - & - \\  & Limited & - & - & - & - & \(\surd\) & - & \(\surd\) & - & - & - & - & - & - & - & - & - \\  & Controlled & - & - & - & \(\surd\) & - & \(\surd\) &
## 1 Introduction
Furthermore, this work includes a case study to illustrate the practical applicability of the model. Using real-world Arabic text, we show how the model effectively handles compound and nested entities with high confidence, demonstrating its capability to address real-world linguistic complexities. The case study not only underscores the model's effectiveness but also provides a tangible example of its use in practical applications, such as digital content analysis or information extraction from Arabic texts. The contributions of this work are threefold. First, we propose novel architectural enhancements, including the Hybrid Feature Fusion Layer, Compound Span Representation Layer, and Enhanced Multi-Label Classification Layer, which collectively address critical challenges in Arabic NER [1]. Second, we conduct a comprehensive evaluation using diverse datasets and scenarios, providing a robust benchmark for future research. Third,we present practical insights through a detailed case study, bridging the gap between research and real-world applications. This paper addresses the significant challenges of Arabic NER through a carefully designed framework that leverages advanced techniques to enhance lexical integration, span representation, and multi-label classification. By bridging the gap between general-purpose architectures and the specific needs of Arabic NER, this work contributes to the growing body of research aimed at advancing NLP for the Arabic language. The remainder of this paper is structured as follows: Section 2 discusses related work, highlighting recent advancements and gaps in Arabic NER research. Section 3 presents the methodology, detailing the architectural components of the proposed model. Section 4 provides an in-depth experimental analysis and results, including dataset descriptions, ablation studies, and visualizations. Section 5 concludes with a summary of the findings, limitations, and directions for future research.
## 3 DCS Scheme Families
### Distributed Erasure Coding in DCS  
In contrast to pure replication, [PERSON] _et al_ propose an alternate approach by incorporating erasure coding in DCS. In [29], the authors use the Redundant Residue Number System (RRNS) to encode data into a set of fragments based on _n out of m_ code that guarantees the survival of the data in the event of the loss of a limited number of fragments (up to _m-n_). The _put(d:k)_ primitive function first selects a set of sensors \(N_{k}\) to store the data based on the number of fragments to be computed, then it multicasts a storage request of _d:k_ to the sensors in \(N_{k}\). Prior to sending the storage request, each sensor \(p\) (\(p\) belongs to \(N_{k}\)) is assigned with a module denoted by _m(p)_, which is used to compute the fragments. The assigned module is randomly chosen from a library of \(m=n+r\) pairwise prime moduli \(m_{1},....,m_{n+r}\). Once a sensor \(p\) is assigned with a module _m(p)_ for storing the pair _d:k_, it stores _x:k_ in its memory where \(x\) is the fragment given by the residue of \(d\) module _m(p)_. Upon receiving a request from a query node for data _d:k_ stored by sensors in \(N_{k}\), the reconstruction might happen using one of two strategies. In the first strategy, each sensor in \(N_{k}\) retrieves the fragment _x:k_ that corresponds to _d:k_ and sends it to the query node. In the second strategy, one sensor in \(N_{k}\) reconstructs _d:k_ after collecting all of the fragments _x:k_ from \(N_{k}\) and sends this reconstructed data to the query node. The first method ensures reliable data reconstruction at the cost of high energy consumption, on the other hand, the second method trades off energy consumption with reliability requiring only local communication in reconstructing the data, and only one final packet is sent to the sink.
# Acceptance Model for Mobile Building Information Modeling (BIM)
## 3 Exploring the Key Factors for Mobile BIM Acceptance
### Exploratory Factor Analysis of the Key Factors  
The survey conducted as part of this study collected 111 sets of responses from stakeholders in the construction industry (i.e., designers, contractors, CMs, engineers, and BIM contractors). A factor analysis was performed to remove external variables that did not significantly affect the acceptance of mobile BIM and its separate assessment items that had a significant impact on similar factors. First, a PCA was performed for factor extraction, and the varimax method with Kaiser normalization was performed as a factor rotation method. As a result, 10 items were eliminated from the 39 items that impeded the validity of the analysis. These excluded items are related to screening composition of system quality, items related to cost, and items related to the education of internal support systems. Second, the remaining 29 items were analyzed using factor analysis (see Table 3).  
First, the KMO measure provides the statistical figure to which relationship between variables is well explained by the other variables, and it indicates the fitness of the variables selected by the factor analysis. In general, a KMO measure of 0.90 or higher is considered highly appropriate, and a KMO measure of less than 0.50 is considered unacceptable. The KMO measure of this study was 0.870. This implies that the 29 selected variables were appropriately selected. Next, [PERSON]'s test of sphericity checks whether a factor analysis model is appropriate by determining the model's goodness of fit with the \(p\)-value. [PERSON]'s test of sphericity showed a \(p\)-value less than 0.05; thus, the factor analysis model was assumed to be appropriate for the study. Meanwhile, the cumulative dispersion value of the data was 77.746%, and the results of factor analysis had a high description.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  
The first factor included 10 items, the second factor included 8 items, the third factor included 5 items, and the fourth and fifth factors included 3 items each. The first factor was named technology quality, the second was named behavior control, the third was named personal efficacy, the fourth was named organization innovativeness, and the fifth was named collective efficacy. These factors were used as the external variables in the TAM model. The details of each factor are described in Section 4.2: Research Hypotheses.
## 2 Analysis
### Analytical Model
#### 2.2.1 Network Spectral Efficiency
 \tag{8}\]  
The probability density functions of the UE distances from serving tier \(i\) and from candidate-serving tier \(j\) are as follows:  
\[f_{\mathcal{R}_{i}}(r_{i})=2.5\cdot\pi\cdot\lambda_{i}\cdot r_{i}\cdot e^{-1. 25\cdot\pi\cdot\lambda_{i}\cdot r_{i}^{2}} \tag{9}\]  
\[f_{\mathcal{R}_{j}}(r_{j})=2\cdot\pi\cdot\lambda_{j}\cdot r_{j}\cdot e^{-\pi \cdot\lambda_{j}r_{j}^{2}} \tag{10}\]  
respectively. Developing (9) and (10) converges to the following relations, which comprehend spectral efficiencies of the macro and pico tier, respectively, as:  
\[SE_{i}=\frac{\lambda_{i}}{\ln 2}\int\limits_{0}^{\infty}\int\limits_{\tau \cdot r_{i}}^{\infty}\frac{f_{\mathcal{R}_{i}}(r_{i})\cdot f_{\mathcal{R}_{j} }(r_{j})\cdot\mathcal{P}_{i}}{1+\gamma}d\gamma dr_{i}dr_{j} \tag{11}\]  
\[SE_{j}=\frac{\lambda_{j}}{\ln 2}\int\limits_{0}^{\infty}\int\limits_{\frac{r_{ j}}{\tau}}^{\infty}\frac{f_{\mathcal{R}_{i}}\left(r_{j}\right)\cdot f_{ \mathcal{R}_{j}}(r_{i})\cdot\mathcal{P}_{j}}{1+\gamma}d\gamma dr_{j}dr_{i} \tag{12}\]  
The overall HetNet spectral efficiency is:  
\[SE_{\mathrm{TOT}}=SE_{i}+SE_{j} \tag{13}\]
## 4 Simulations Results and Discussion with Performance Evaluation
### Simulation Results
#### 4.3.4 Prt  
The PRR of the existing protocols is high than the proposed protocols as shown in Figure 12. In FLMPC-One and FLMPC-Two protocols, PRR is higher because of the formation of binary trees from cross nodes towards the destined sink. In proposed protocols, the possibility of void nodes is eliminated. The PRR of SPF-Three and BFS-SPF-Three is lower than existing protocols because it selects a single shortest path from the source towards the destination. Opportunistic routing causes a collision in several data packets because of same shortest path selection. This selection results in several packets drop. However, BFS-SPF-Three show high performance as compared to the SPF-Three.
# Interactive Parametric Design and Robotic Fabrication within Mixed Reality Environment
###### Abstract  
In this study, a method, in which parametric design and robotic fabrication are combined into one unified framework, and integrated within a mixed reality environment, where designers can interact with design and fabrication alternatives, and manage this process in collaboration with other designers, is proposed. To achieve this goal, the digital twin of both design and robotic fabrication steps was created within a mixed-reality environment. The proposed method was tested on a design product, which was defined with the shape-grammar method using parametric-modeling tools. In this framework, designers can interact with both design and robotic-fabrication parameters, and subsequent steps are generated instantly. Robotic fabrication can continue uninterrupted with human-robot collaboration. This study contributes to improving design and fabrication possibilities such as mass-customization, and shortens the process from design to production. The user experience and augmented spatial feedback provided by mixed reality are richer than the interaction with the computer screen. Since the whole process from parametric design to robotic fabrication can be controlled by parameters with hand gestures, the perception of reality is richer. The digital twin of parametric design and robotic fabrication is superimposed as holographic content by adding it on top of real-world images. Designers can interact with both design and fabrication processes both physically and virtually and can collaborate with other designers.  
parametric design; robotic fabrication; digital fabrication; mixed reality; augmented reality; digital twin; interactive design; shape grammar; design-to-production; human-robot collaboration +
Footnote †: journal: _Sci_  
In this paper, we propose an interactive, parametric design and robotic fabrication method that allows users to dynamically explore design and fabrication alternatives within a mixed-reality environment throughout the whole design and fabrication process. With the proposed method, both parametric modeling and robotic fabrication steps can be created within the mixed-reality environment and controlled by parameters. In order to test the proposed method, a natural stone robotic fabrication environment is created. The proposed method was tested on a design product, which was defined by the shape-grammar method using parametric-modeling tools. Natural stone material was chosen to test the proposed method in robotic fabrication. The results of the proposed method and the existing methods are compared and discussed based on the observations obtained from the test results in terms of mass-customization, design-to-production process, scalability, machine time, process, and material efficiency, and human-robot collaboration. In addition to the production possibilities, design possibilities such as production-immanent modeling, interactive design, emergent design, parametric design, and generative design are offered to the user within the mixed-reality environment.
## 2 A Voltage Ride-Through (VRT) Control Model for Energy Storage Systems
### Hybrid Optimization Algorithm Design  
#### 3.3.1 Establish the Objective Function  
The control parameters listed in Table 1 are defined as the primary identification target.  
The sensitivity analysis of these six features is performed using the Sobol index method to select control parameters that have a significant impact during energy storage voltage faults. Based on the actual hardware limitations of the controller, a parameter search space is established. The optimized objective function is then formulated as follows:  
\[J(\theta)=\sum_{i=1}^{5}\alpha_{i}\cdot\left(f_{i}^{\text{sim}}-f_{i}^{meas} \right)^{2}+\alpha_{P,Q}\text{MSE}_{P,Q}+\beta\text{THD} \tag{19}\]  
where \(\alpha\) represents the importance of each indicator in the optimization objective, with higher \(\alpha\) values indicating greater importance. \(f_{i}^{sim}\) denotes the value of each feature obtained from simulation data, while \(f_{i}^{meas}\) represents the value derived from measured data. \(\beta\) is the weighting factor for the THD term.
# Should the Application of Diode Laser Completely Replace Conventional Pulpotomy of Primary Tenth?
###### Abstract
Although there are many lasers available on the market, the Er: YAG laser is mainly used in pulpotomy procedures. This way, the placement of chemicals in the pulp chamber is avoided. Pulpotomy is performed by placing a laser on the coronal part of the tooth, with or without water. The laser beam penetrates through the pulp chamber for 15 s until adequate hemostasis is achieved, after which zinc oxide eugenol is placed [19]. The laser beam is only slightly absorbed by the dentin, which is of particular importance when sterilizing the root canal since the goal is to achieve deep penetration of the laser into the intertubular tissue, and thus a bactericidal effect in the deeper layers. This is why diode lasers as well as Nd: YAG lasers are particularly suitable for endodontic purposes. Most of the Gram-negative and some Gram-positive bacteria (e.g., _E. faecalis_) are very sensitive to their use which is supported by the success rate of 99.91% in reducing _E. faecalis_ bacteria with a diode laser [6]. It is considered that the diode laser has a better antimicrobial effect than the classic methods of pulpotomy [5]. Other advantages of laser pulpotomy are improved patient cooperation, simplicity of the method, and reduced pain [20]. Nevertheless, classic materials for covering the pulp remain the basis of therapy [21]. Conversely, the use of lasers in exposed pulps to stimulate healing has proven to be superior compared to manual or rotary techniques [22]. By using the Er,Cr:YSGG laser, the duration of the procedure for cleaning and widening the root canals of primary teeth was reduced while maintaining the same quality of the preparation [23; 24]. This research aims to compare the effectiveness of two different pulotomy methods for primary teeth in the follow-up period of 6, 12, and 24 months. Given that the majority of studies in the available literature [18; 25; 26; 27; 28; 29] conducted the follow-up of teeth treated with pulpotomy for up to one year, the question arises as to what the fate of these teeth is after more than a year from the end of the treatment. Therefore, the null hypothesis of this study is: \"The type of pulpotomy (diode laser vs. conventional) and the material of the final restoration (composite and glass ionomer cement) have no influence on the clinical and radiological success of the treated deciduous teeth.\"
## 2 Data and Methods
### Data  
Landsat 5 Thematic Mapper (TM) data was collected for three footprints that covered nine of eleven administrative districts, either wholly or in large part. The footprints were located at nominal scene centers of Path: 172, Row: 071; Path: 172, Row: 072; and Path: 173, Row: 071. Given the breadth of study area and characteristic smallholder farming, the Landsat 5 TM instrument offered the optimal pixel resolution of 30 m [55]. Two images were selected for each satellite footprint with acquisition dates corresponding to the pre-season of 2008 and the harvest season of 2009 (Table A1). The choice of 2008/2009 imagery coincided with survey data collected during 2007-2008. Optimally, scenes from the growing season would also be utilized but persistent heavy cloud cover combined with the 16-day reacquisition interval did not yield an image of sufficient quality. Quantized calibrated pixel values were converted to at-sensor radiance based on the minimum and maximum spectral radiance for each band [56]. Radiance values were subsequently converted to surface reflectance using an image-based procedure of dark-object subtraction [57,58]. Fmask software ([[https://code.google.com/p/fmask/](https://code.google.com/p/fmask/)]([https://code.google.com/p/fmask/](https://code.google.com/p/fmask/))) was utilized to identify cloud/heavy haze and cloud shadow in each TM scene. Cloud masks were combined into a cumulative mask and applied to both images. Multi-temporal composites were then generated for each footprint by stacking the six multi-spectral bands (TM 1-5, and 7) of the seasonal image pairs to generate a 12-layer image.
# A Phase Bias Compensation Method for Anti-Interference Antenna Arrays in RTK Positioning
## 3 Results  
### The Phase Bias Simulation  
Assume the incident signal from \((30^{\circ},\ 60^{\circ})\). The RF is 1268.52 MHz, intermediate frequency (IF) is 46.52 MHz, and sampling frequency is 62 MHz. A broadband interference signal is taken from the nearby angular domain \(\theta\ =\ 10^{\circ}\), \(20^{\circ}\), \(30^{\circ}\), \(40^{\circ}\), \(50^{\circ}\), \(\varphi\ =\ 40^{\circ}\), \(50^{\circ}\), \(60^{\circ}\), \(70^{\circ}\), \(80^{\circ}\). The phase biases that \(\mathbf{w}^{H}\mathbf{a}\) has introduced by the SAP PI algorithm, STAP PI algorithm, and SAP MVDR algorithm are as follows.  
In the SAP PI algorithm, the phase biases of three-dimension distribution and two-dimension distribution are shown in Figure 7a,b. The phase bias ranges from \(-10^{\circ}\) to \(7^{\circ}\). When the direction of the interference signal is the same as the satellite signal, the phase bias is \(-16^{\circ}\).  
Figure 6: The structure of phase bias compensation algorithm based on antenna array output signal.  
In the STAP PI algorithm, the phase biases of three-dimension distribution and two-dimension distribution are shown in Figure 8a,b. The phase bias ranges from \(70^{\circ}\) to \(110^{\circ}\). When the direction of the interference signal is the same as the satellite signal, the phase bias is \(-39^{\circ}\).  
In the STAP MVDR algorithm, the phase biases of three-dimension distribution and two-dimension distribution are shown in Figure 9a,b. Based on the analysis of Section 2.5.1, the MVDR criterion will not introduce phase bias. Therefore, the phase bias in Figure 9 is \(0^{\circ}\).