esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methodology  
### Overall Methodology and Pre-Processing  
LiDAR data and landslide inventories were first pre-processed to eliminate noise and outliers. A high-resolution digital elevation model (DEM) at 0.5 m was then derived from LiDAR point clouds to generate other LiDAR-derived products (i.e., slope, aspect, height or (normalized digital surface model (nDSM)), and intensity. LiDAR-derived products and orthophotos were then composited by rectifying their geometric distortions to generate one coordinate system and were finally prepared in geographic information system (GIS) for feature extraction. Suitable parameters (scale, shape, and compactness) at various levels of segmentation were obtained via a supervised approach, i.e., a fuzzy-based segmentation parameter optimizer (FbSP optimizer) [13]. The stratified random method was used to evaluate the training dataset in accordance with the procedure in [35]. The correlation-based selection algorithm (CFS) [36] was used to rank features from the most to least important. RNN and MLR-NN models were applied to detect landslide locations. The results of the models were validated using a 10-fold cross validation method. In addition, the models were evaluated in another part of the study area (i.e., the test site). Slope and aspect layers were overlaid with the results to identify other landslide characteristics (i.e., direction and run off). The study flow is illustrated in Figure 2.  
Figure 1: Location of the study area. The red boundary represents the analysis area and the yellow boundary represents the test area.
## 1 Introduction
In [23], an overcurrent protection scheme based on harmonic voltage injection is proposed, and fault detection and isolation are achieved by integrating the amplitude and phase of harmonic currents. The methods proposed in [22; 23] mainly apply to microgrids under islanding operation mode. However, they provide a new idea for studying control-protection synergy in active distribution networks: active injection detection type protection. Considering that the system power supply will generate harmonics during faults in the distribution network and the distribution network has strict requirements for harmonic injection, whether the injection protection method can be applied to the distribution network needs further study. This paper revisits the feasibility of active injection detection protection in distribution networks with IBDGs and proposes an injection harmonic current differential protection (IHCDP) scheme based on control-protection synergy. The remainder of this paper is organized as follows. Section 2 deeply studies the equivalent model of IBDG, including its circuit structure, control strategy, and LVRT characteristics. Section 3 analyzes the change of short-circuit currents provided by IBDG before and after injecting characteristic harmonic signals. Section 4 describes the principle of IHCDP. On this basis, the implementation scheme of IHCDP is presented in Section 5. The feasibility of the proposed protection scheme is verified by PSCAD/EMTDC in Section 6. Section 7 summarizes the results and the contributions of this paper.
# Angle-Based Parametrization with Evolutionary Optimization for OESCL-Band Y-Junction Splitters
## 4 Results
### Convergence Rate  
Figure 3 depicts the FOM trend for each optimization run over the SCL (top) and OESCL (bottom) bands. From Figure 3 (top), we make two key observations regarding the Geomean. First, Geomean\({}_{CMA-ES}\) shows that CMA-ES is the fastest algorithm, converging at the 40 th generation. Notice that PSO has a high initial growth rate; however, the \(<\)2% criteria is only met in the 71 st iteration. Second, GA exhibits the slowest convergence rate; it converges at the \(\sim\)90 th iteration, obtaining the lowest FOM.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Value** & **Description** \\ \hline n & 40 & population size \\ k & 100 & number of iterations \\ p & 11 & number of characteristics \\ q & 10 & number of selected parents \\ r & 3 & range of random change in parameters \\ \(\omega\) & 1 & inertia weight \\ \(c_{i}\) & 1 & relative attraction coefficients \\ \hline \hline \end{tabular}
\end{table}
Table 2: Algorithm’s parameters.  
From Figure 3 (bottom), we make three observations. First, in the OESCL band, the fastest method, regardless of its maximum FOM (25.6), is the GA, which converges at the 20 th generation. However, as seen here and in the SCL analysis, the FOM values constantly get stuck. This is a drawback for the GA, even after 100 generations. Second, \(\text{Geomean}_{CMA-ES}\) achieves a maximum FOM at the 42 nd generation; however, its maximum is just behind that of \(\text{Geomean}_{PSO}\). Lastly, the PSO algorithm achieved a maximum FOM over 26, which is greater than \(\text{FOM}_{\text{GA}}\) at the \(\sim\)50 th generation.  
We conclude that the CMA-ES algorithm is the fastest and has a similar FOM to PSO in the SCL-band analysis. In the OESCL-band, its maximum FOM decays \(\sim\)2% in relative amplitude, and its convergence rate stays almost the same at the \(\sim\)40 th generation. This consistency is a desirable feature for a global optimization algorithm.
## 3 The Proposed Model  
In this paper, we develop a new BSHS-EODL method for secured medical image transmission and analysis in the IoMT environment. The presented BSHS-EODL technique enables BC assisted secured image communication and detection models for the IoMTenvironment. The proposed method includes data classification, data collection, and image encryption. At the initial stage, the IoMT devices enable data collection processes, and the gathered images are stored in BC for security. Once the images are gathered, they are encrypted using effective image encryption technique with a DOA based key generation process. Next, the encrypted image was securely transferred using BC technology. At the receiver end, the image decryption was implemented, and the disease diagnosis process was later. Figure 1 demonstrates the working process of the BSHS-EODL method.  
Figure 1: Working process of BSHS-EODL approach.
## 1 Introduction  
Articular cartilage permits frictionless joint motion [1]. This tissue has a maximum thickness of 4 mm [2] and its functional units are chondrocytes, which comprise approximately 2% of the total tissue. They are composed of 75-80% water, 15% collagen fibers, and 9-10% proteoglycans, which maintains the integrity of the articular cartilage matrix [3, 4].  
When the articular cartilage is damaged, a complex condition is generated and the whole joint is affected. The activation of matrix proteases plays a pivotal role in this process, leading to the development of osteoarthritis (OA) [5]. Osteoarthritis is the most common joint disease worldwide [5], affecting an estimated 9.6% of men and 18% of women over 60 years old [6].  
Currently, there are no pharmacological treatments that can modify the course of OA; it can only be managed by reducing inflammation and pain, surgically correcting deviations from the mechanical axis and/or joint instability, filling in cartilaginous defects, or, in more severe cases, performing a prosthetic joint replacement [7; 8]. At the present time, some authors have proposed the use of cadaveric cartilage from young donors as a source of cells for the repair of joint surface lesions [9; 10; 11]; other cellular sources that have been proposed involve the use of the synovial membrane [12] and Hoffa-fat-derived mesenchymal stem cells with a macroporous scaffold and biological macromolecules for the repair of meniscus cartilage [13], including for subchondral bone regeneration. The osteogenic potential of monosodium urate crystals on mesenchymal stem cells isolated from the synovium is being explored [14]. Undoubtedly, all these lines of research are promising and are still under development, however, until now, there has been no definitive solution to counteract the progression of OA.  
Three-dimensional (3D) treatment techniques used for the development of new therapeutic strategies for repairing articular cartilage lesions [15] are currently very diverse, such as the use of bioink-based hydrogel [16], 3D-printed fish gelatin scaffolds [17], [PERSON]'s jelly bioinks [18], and scaffolds based on Functionalized Poly(glycerol sebacate) [19], among others, with very varied results. On the other hand, we support the use of biocompatible materials such as PLA [20; 21] together with MSCs for the generation of cartilage and bone tissue, as they have been proven to be easy to implement and offer reliable results [22; 23].  
In this way, our multidisciplinary group seeks to obtain new therapeutic strategies for the repair of focal lesions of the joint cartilage using an accessible practical method that is low cost in comparison to the current investigations in development. Therefore, in this study, we aimed to use a sheep model to create an articular hybrid implant from autologous mesenchymal stem cells differentiated towards cartilage, bone, and bioabsorbable polymers using three-dimensional printing technology, in order to determine whether the hybrid implant was capable of maintaining the cell phenotype of cartilage/bone for up to 6 months after being implanted in different conditions in the sheep model.
## 4 Resource Management in Heterogeneous Network (RM HetNet)
### Spectrum Allocation (SA)
#### 4.4.3. Tera Hertz (THz)
Furthermore, they evaluated the influence of sub-band assignment on multi-connectivity-enabled THz communication systems, which allow users to associate and interact with several access points concurrently. To determine sub-band bandwidth, sub-band assignment, and optimum transmit power, they formulated resource allocation problems with a major emphasis on spectrum allocation. Moreover, they provided appropriate approximations and transformations for solving the stated issues analytically and developed iterative algorithms using the successive convex approximation approach. The results of simulations demonstrated that a large increase in throughput could be obtained by enabling and optimizing adaptive sub-band bandwidth compared to adopting equal sub-band bandwidth, with the throughput increase being most noticeable when the power budget restriction is more severe. They further demonstrated that the proposed approach outperforms the traditional sub-band assignment strategies, with the greatest performance improvement seen when allocating spectrum based on the average molecular absorption coefficient. However, the use of adaptive sub-band bandwidth is limited to situations in which the sub-bands have a relatively narrow bandwidth. They investigated the problem of resource allocation in THz downlink networks to optimize the system's spectral efficiency while simultaneously fulfilling users' data rate needs. Based on the indoor Terahertz channel model, an optimization issue to maximize SE is proposed in [142]. In order to tackle the optimization problem, it is first divided into two sub-problems, PA and sub-band allocation. First, hub-bands are distributed using the long user central window principle and the bipartite graph matching approach. Second, using an iterative procedure, the power is optimized via the sequential quadratic programming (SQP) approach. When compared to other conventional schemes, simulation results illustrated that the proposed algorithm achieved greater system spectrum efficiency. Nevertheless, the proposed THz system is limited to a small number of users.
# Collaborative Use of a Shared System Interface:
## 4 Methodology  
To validate our proposed GC index and investigate its hypothesized associations, we conducted two consecutive experimental studies, which were approved by the ethical committee of our institution, the Comite d'Etique de la Recherche (ethical approval code: 2020-3645). The two studies involved synchronous dual eye-tracking recording. In other words, eye movements of user dyads were recorded with real-time synchronization of clocks on two gaze data recording computers. Informed consent was obtained from all dyad members prior to participation.  
The first study assessed the content validity of the proposed GC index. Content validity refers to the degree to which a construct operationalization is representative of the content domain (i.e., the substance, the matter, or the topic) of the construct [37; 38; 39; 40]. 37-40 Simply put, we ascertained to what extent our GC operationalization reflected the GC of user dyads. To that end, GC was experimentally manipulated by having user dyads perform a task in two conditions: gaze convergence (referred to as the convergence condition) and gaze divergence (referred to as the divergence condition). Hence, the purpose of this study was to assess the extent to which our dyad GC index is able to distinguish between convergent and divergent dyad gaze behaviors.  
The second study explored the predictive validity of the proposed GC index, that is, the extent to which the operationalization of the construct was able to correlate with or predict endogenous constructs it is theoretically expected to correlate with or predict [40]. Specifically, this study tested whether dyad GC would predict the hypothesized dependent variables, namely, dyad cognitive load and dyad task performance. User dyads engaged in collaborative tasks using the same interface on different computer monitors, with only one of the two users controlling input devices (see Figure 3).  
This setup reflects a specific real-world setting in which users work together on the same task, on a shared system interface, to jointly perform a task. Examples include the following: two workers sharing their screen (e.g., using a screen sharing software) to work together from same or separate  
Figure 3: Eye-tracking experimental setup.  
offices or rooms but communicating directly of through the phone; or two IT network professionals jointly working on a shared interface with separate computer monitors in a technical equipment room, as each worker needs to stay at different locations to monitor different equipments. This setup is also common among couples who shop online together remotely, as revealed by a forthcoming paper about the state of the art on multiuser human-computer interactioin settings, providing preliminary evidence specific to settings in which couples shop online together [41]. In that survey study, more than 70% of couples shopping online together using separate screens reported sharing the same software window during the activity.
## 5 Conclusions and Recommendations
### Conclusions  
Based on the analysis of the flight test data, we concluded that the UTM application functioned well in monitoring the UAV's flight and provided sufficient warning levels to the UAV pilot when a conflict was detected. Since the conflict detection algorithm employed was based on a distance measurement, the warning level of conflict detection was opposite to the relative distance and height between UAVs. This result was confirmed by the result from the machine learning analysis that placed the relative distance and the relative height as the second and fourth most important parameters for warning detection. In addition, the machine learning technique results show that the most significant parameter of the warning level was the processing time.  
Moreover, due to the differences in livelihood level of the flight locations, the data latency increased with the distance from urban areas. Furthermore, the latency time was higher for the data transmitted from the Remote ID module in the flying condition than the ground condition. This result relates to the characteristic of the current 4G communication that focuses on urban locations and ground users. Interestingly, the machine learning analysis results indicate that the latency time was affected mostly by the query time.
## 3 Analysis of Torque Performance
### Analysis of MRF Flow
Assuming that the volume flow rate per unit width is \(Q\), the volume flow rate along the cross-sectional area integrated by Equation (5) can be obtained as  
\[Q=\int_{0}^{h}\omega(z)\mathrm{d}z=(\omega_{1}+\omega_{2})\frac{h}{2}-\frac{ h^{3}}{12\eta}\frac{\mathrm{d}p}{\mathrm{d}\theta} \tag{7}\]  
Suppose the thickness of MRF at \(p=p_{\mathrm{max}}\) is \(h_{0}\), and \(\mathrm{d}p/\mathrm{d}\theta=0\) at \(h=h_{0}\). The flow rate at this cross section can be expressed as  
\[Q_{0}=\frac{h_{0}}{2}(\omega_{1}+\omega_{2}) \tag{8}\]  
When the MRF flows continuously, the flow rate of each section is equal, and the gradient of pressure along the rotation direction is thus  
\[\frac{\mathrm{d}p}{\mathrm{d}\theta}=\frac{6\eta(\omega_{1}+\omega_{2})}{h^{3 }}(h-h_{0}) \tag{9}\]  
Since the two flat plates are parallel, \(h=h_{0}\), and neither viscosity \(\eta\) nor \((\omega_{1}+\omega_{2})\) is equal to zero, it can only be the case that \(\mathrm{d}p/\mathrm{d}\theta=0\). When the magnetic field strength \(H\) varies, the magnetic shear yield stress of the MRF is \(\tau_{y}(H)\). The interface of \(\sigma_{z\theta}=\tau_{y}(H)\) is defined as the decomposition surface of the yielded and unyielded regions. Assuming that \(z_{y}\) is the dimension at the decomposition plane between the yielded and unyielded regions, the Navier-Stokes Momentum Equations for the MRF flowing between the two slit flat plates as circumferential shear are [17] (pp. 115-118). \[\frac{\partial\tau_{r\theta}}{\partial r}+\frac{1}{r}\frac{\partial\sigma_{ \theta\theta}}{\partial\theta}+\frac{\partial\tau_{z\theta}}{\partial z}+ \frac{2}{r}\tau_{r\theta}=0 \tag{10}\]  
where \(\sigma_{\theta\theta}\) is the tangential pressure along the \(\theta\) direction and \(\tau_{r\theta}\) and \(\tau_{z\theta}\) are the shear stresses of the MRF. Since the angular velocity is constant along the flow direction, \(\tau_{r\theta}=0\). Since the two flat plates are parallel to each other, the pressure \(\sigma_{\theta\theta}\) is constant, and the above equation can be simplified as  
\[\frac{\mathrm{d}\tau_{z\theta}}{\mathrm{d}z}=0 \tag{11}\]  
From Equation (11), it can be determined that \(\tau_{z\theta}\) is a constant, independent of \(z\). Suppose the load torque on the driven shaft is \(T_{L}\), and the shear stress of the MRF required to make the output disk rotate is \(\tau_{L}\), then  
\[T_{L}=2\pi\int_{r_{3}}^{r_{2}}\tau_{L}r^{2}dr \tag{12}\]  
By the Integral Median Theorem, the integration of Equation (12) is  
\[T_{L}=\frac{2}{3}\pi\tau^{*}\Big{(}r_{2}^{3}-r_{3}^{3}\Big{)} \tag{13}\]  
where \(\tau^{*}\) is the value of the shear stress at point \(r_{0}\) in the interval (\(r_{3}\), \(r_{2}\)), and when (\(r_{2}-r_{3}\))/\(r_{3}<<1\), \(\tau^{*}\) is approximately equal to the value at \(r_{0}=(r_{2}+r_{3})/2\).
## 3 Results and Discussion
### Physical Characterization
#### 3.2.3 Density and Moisture Content Results  
The density values averaged 130 kg/m\({}^{3}\), with the lowest measurements of 121 kg/m\({}^{3}\) corresponding to sample 1, with 121 kg/m\({}^{3}\) shown in Figure 9. The moisture content of rice husk was found to have an average of 10.23 \(\pm\) 0.1%, which is consistent with the behavior observed in other natural fiber materials. This moisture level is considered desirable, as it supports the preservation of the thermal properties of insulation materials. Excessive moisture can negatively impact thermal conductivity, increase condensation, and reduce biological resistance. Conversely, maintaining low-to-moderate moisture levels enhances the material's biological resistance, making it well suited for use in building applications.  
Materials with open porosity, such as rice husk, facilitate moisture movement driven by vapor pressure gradients, gravity, and capillary action. However, in well-designed systems, vapor diffusion is the dominant mechanism, preventing excessive moisture levels and contributing to the material's effectiveness as a thermal insulator in energy-efficient buildings [52].  
Furthermore, the results suggest that rice husk insulation would not promote the proliferation of pathogens if installed in homes in regions such as Chile. Previous studies, such as those conducted by [PERSON] et al. (2023), have shown that similar natural fibers, like cellulose combined with wheat straw, do not support fungal growth or region-specific pathogens within comparable moisture ranges [28].  
Figure 9 presents the measurement results, showing that the samples exhibit a thermal conductivity below 0.041, demonstrating their potential as a thermal insulation material. This value is comparable to conventional insulating materials, reinforcing their suitability for energy-efficient construction applications [53]. Unlike traditional insulation materials, where a higher density reduces thermal conductivity, lignocellulosic fibers show the oppo  
Figure 8: Measurement of thermal conductivity.  
Figure 9: Relationship between thermal conductivity and density of samples.  
site trend, with conductivity increasing as density rises [28]. This highlights the importance of optimizing density to maintain insulation efficiency properties.
# Activation Process of ONU in EPON/GPON/XG-PON/NG-PON2 Networks
## 5 Simulation Results
### Simulations for ITU Standards
#### 5.1.1 Gpon  
The simulation was based primarily on the description of the ONU activation process described in Section 4.1. The Activation passed through four different states until it reached the fifth state in which it was finally possible to transfer the data. The time flow and the transmitted messages are shown in Figure 4. As shown, all downstream PLOAM messages were sent three times. State O1 and State O2, described previously, were unified for each ONU. After creating a quiet window, the ONUs sent messages with their serial numbers. The unit whose message was received by the OLT first was activated, and the other units were forced to wait. Activation took place until all units were finally connected. In the O4 state, the equalization delay was measured and subsequently transmitted by the Ranging Time message. The ONU must use this delay in its message transfer. Because the GPON standard measures this delay, the computation performed during the simulation presented in this work must be considered as exploratory in nature. The computation was based on information proposed in [26].  
\[EqD_{i}=T_{epd}-RTD_{i}, \tag{2}\]  
where \(T_{epd}\) is the so-called zero-distance \(EqD\) (offset between the downstream frame and the obtained frame that was requested). It can be computed as follows [26]:  
\[T_{epd}=2T_{pd}+RspTime+Prd+USframe, \tag{3}\]  
where \(RspTime\) is the response time of the ONU with its value set to \(35\,\upmu\)s, \(Prd\) is the pre-assigned delay set to \(202\,\upmu\)s and \(USframe\) is the upstream frame duration.  
\(RTD\) is the usual delay expressed as [26]:  
\[RTD_{i}=2T_{pd}+RspTime. \tag{4}\]  
During the simulation, the program lists the current status, the transmitted messages and the total time of activation of the given ONU in milliseconds.  
Figure 4: Visualization of the GPON activation.
# Mobile Robot Path Planning Algorithm Based on NSGA-II
## 4 Experimental Simulation and Analysis
### Path Smoothing Experiments and Analysis  
The simulation experiment results for path smoothing on maps of two different complexities are depicted in Figure 10. The smoothed paths conform to the principles of mobile robot motion, devoid of abrupt corners. The paths exhibit smooth curves overall, enabling the mobile robot to travel smoothly without the need to stop, turn, and restart at corner points. This is crucial for reducing wear and tear on the robot due to turning, thus extending its lifespan.
## 3 System Performance Analysis  
The probability density function (PDF) and cumulative distribution function (CDF) of Rayleigh distribution are given by \(f_{\left|h\right|^{2}}(x)=\frac{1}{\sigma}\text{exp}\left(-\frac{x}{\sigma}\right)\) and \(F_{\left|h\right|^{2}}(x)=1-\text{exp}\left(-\frac{x}{\sigma}\right)\), respectively, where \(\left|h\right|^{2}\) are random independent variables namely \(x\) in PDF and CDF and \(\sigma\) is expected channel gain with \(\sigma=E\Big{\{}\left|h\right|^{2}\Big{\}}\).