esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
The authors found that heat transfer was reduced due to the addition of nanoparticles. Furthermore, the Brownian motion significantly affects the heat transfer rate according to the Rayleigh number, Hartmann number, and nanoparticle volume fraction. [PERSON] et al. [38] experimented with different types of nanofluids with various shapes of nanoparticles and analyzed the oriented magnetic field effect on natural convection in an inclined square enclosure. They established that an increase in Rayleigh number and the nanoparticles' volume fraction enhance the heat transfer, whereas the increase in Hartmann number reduced by the same. [PERSON] et al. [39] carried out numerical investigation of flow of Cu-water nanofluid flow inside an isosceles triangular cavity under uniform magnetic field and illustrated that the flow strength enhanced as Rayleigh number increases and deteriorated as the Hartman number increases. Using the lattice Boltzmann method, [PERSON] et al. [40] considered the nanofluid (water-Al2O3) flow in an incinerator-shaped enclosure with a heated source situated at the bottom. They found that the Rayleigh number, the nanoparticles volume fraction and the heat source height enhanced the heat transfer and influenced the flow and thermal structures. [PERSON] and [PERSON] [41] studied the effect of magnetic field on natural convection in micropolar nanofluid inside an inclined rectangular cavity and remarked that the thermal properties of the base fluid are altered by the presence of nanoparticles. It is worth mentioning that very few papers have investigated the magnetic field effect on double diffusive convection in nanofluid. [PERSON] et al. [42] used Buongiorno mode and examined the effect of magnetic field on nanofluid double-diffusive natural convection on a linearly stretching sheet, and they identified that buoyancy ratio and magnetic field enhance the skin friction but decrease the heat and mass transfer rates. On the basis of the aforementioned literature review, the authors' understand that the three-dimensional double-diffusive natural convection in micropolar nanofluid filled cavity under the influence of uniform magnetic field has not been explored so far and hence is the topic of research of this article. The influences of relevant parameters such as Rayleigh number, Hartmann number,buoyancy ratio, nanoparticles' volume fraction, and vortex viscosity parameter on flow structure and heat are elaborately analyzed.
## 2 Materials and Methods
The hybrid technological basis between adjusted proprietary (Esri) and open source (PostgreSQL) software has been found to be most effective [35] and has made it possible to create different applications around it for data collection, processing, and validation, and for their integration into the data systems of State agencies. The developed applications for the FFP approach in Colombia are visually oriented. The applications show maps of the parcel boundaries and include the names and pictures of the neighbouring settle farms, pictures that were taken in the field and a satellite image that shows the natural elements that can be recognized by the Indigenous peoples, such as rivers and vegetational corridors. This makes it easier to communicate field results with the Indigenous peoples. Using these innovative technologies and adjusting the mobile application to this purpose has led to several advantages, which can be summarized as follows: (i) it makes it possible to capture physical and legal administrative data in an integrated way; (ii) it is user-friendly; (iii) it is robust enough to guarantee the capture of the spatial, semantic, and topological relationships of the data without the need for direct intervention of the data collector; (iv) it can work in a disconnected way in areas without internet; (v) it makes it possible to centralize information from a database in the cloud, without intermediate files; and (vi) the collected data comply with the profile of the Land Administration Domain Model (LADM) standards for Colombia. The used GNSS antenna, Trimble R2, is equipped with a FieldPoint real-time extended (RXT) correction service. It communicates with an operations centre through a satellite link or through the internet and provides the antenna the real-time position with a submeter accuracy [35]. The accuracy of the vertices that are measured in the field meet the official standards in Colombia, which have been adjusted recently to comply with the realities in the field. No geodetic network needs to be established before starting the field measurement, which facilitates the work in remote, Colombian rural areas. Moreover, the fact that the antenna is easily operable by land users themselves enhances the participative process. This increases trust of the community in the collected field data. After data collection, the results of the field surveys per community are shown and publicly discussed in a so-called public inspection: all land users can judge the results concerning their own parcels and other parcels. Conflicts or disputes can be settled during the public inspection, where Colombian cadastral authorities are also present. The status of the moment is captured, both agreements and disagreements. This information is then handed over to the local Colombian land institutions, who are responsible for resolving the land conflicts.
# Impact of Partial Replacement of Cement with a Blend of Marble and Granite Waste Powder on Mortar
## 2 Materials and Methods
### Mortar Mix Preparation  
The initial phase of this study focuses on assessing the strength properties of mortar specimens by varying the replacement percentages of OPC with MGWP. These replacement percentages were 5%, 10%, 15%, 20%, 25%, and 30%, with ratios of marble and granite waste powder varying at 1:1, 1:2, and 2:1. Furthermore, a control mix was prepared, consisting only of OPC, with a consistent water-to-cement ratio of 0.51. The compressive strength test results indicated that the mortar specimens containing a 1:1 ratio of MWP and GWP exhibited the highest strength across all the replacement percentages considered. Consequently, mortar mixes utilizing a 1:1 MWP to GWP ratio were selected for further investigation. In Table 3, the codes assigned to each mixture of the finally considered mortar mixes are displayed. It also includes the corresponding proportions of OPC, MWP, and GWP used in each mixture.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No** & **Test** & **Standard** & **Result** & **Unit** \\ \hline
1 & Fineness modulus & ASTM C33/C33M [22] & 3.1 & [–] \\
2 & Specific gravity & ASTM C128 [23] & 2.74 & [–] \\
3 & Water absorption & ASTM C128 [23] & 3.09 & [\%] \\
4 & Free moisture content & ASTM C566 [24] & 2.1 & [\%] \\
5 & Loose bulk density & ASTM C29/C29M [25] & 1686.33 & [kg/m\({}^{3}\)] \\
6 & Compacted bulk density & ASTM C29/C29M [25] & 1870.5 & [kg/m\({}^{3}\)] \\
7 & Voids & ASTM C29/C29M [25] & 2 & [\%] \\
8 & Silt content & ASTM C136 [21] & 1.67 & [\%] \\ \hline \hline \end{tabular}
\end{table}
Table 2: The test results of the physical properties of the fine aggregate.  
Figure 2: Gradation curve of the fine aggregate.
###### Abstract  
A numerical study was conducted on the influence of turbulence intensity and Reynolds number on the mean topology and transition characteristics of flow separation to provide better understanding of the unsteady jet flow of turboelectric distributed propulsion (TeDP) aircraft. By solving unsteady Reynolds averaged Navier-Stokes (URANS) equation based on C-type structural mesh and \(\gamma-\widetilde{\text{Re}}_{\theta t}\), transition model, the aerodynamic characteristics of the NACA0012 airfoil at different turbulence intensities was calculated and compared with the experimental results, which verifies the reliability of the numerical method. Then, the effects of varied low Reynolds numbers and turbulence intensities on the aerodynamic performance of NACA0012 and SD7037 were investigated. The results show that higher turbulence intensity or Reynolds number leads to more stable airfoil aerodynamic performance, larger stalling angle, and earlier transition with a different mechanism. The generation and evolution of the laminar separation bubble (LSB) are closely related to Reynolds number, and it would change the effective shape of the airfoil, having a big influence on the airfoil's aerodynamic characteristics. Compared with the symmetrical airfoil, the low-Reynolds-number airfoil can delay the occurrence of flow separation and produce more lift in the same conditions, which provides guidance for further airfoil design under TeDP jet flow.  
**Keywords:** turboelectric distributed propulsion; low Reynolds number; turbulence intensity; laminar separation bubble; stall +
Footnote †: journal: Applied Physics Letters
## 5 Results and Discussion
### Current Density Distribution Analysis
#### 5.5.2 Normalized Current Density Line Charts  
Figure 10a-c present the normalized current density profiles for the 2D models. The normalized current density (\(J/J_{\rm DC}\)) is calculated as the ratio of the local current density (\(J\)) to the uniform current density under DC conditions (\(J_{\rm DC}\)). Here, \(J_{\rm DC}\) represents the current density when the current is evenly distributed across the conductor's cross-sectional area, as is typical in direct current scenarios. These profiles illustrate how the current density varies across the conductor's radius under alternating current conditions. As the number of segments increases, the current distribution becomes more uniform across the conductor's cross-section. The single-segment model shows a pronounced peak in current density near the conductor's surface, reflecting the strong influence of the skin effect. In the three-segment model, the current distribution is more balanced, with a noticeable reduction in peak concentrations. The five-segment model, while exhibiting improved uniformity, displays a slight increase in peak current density at the segment edges, likely due to geometric factors such as sharp edges that alter the local field distribution.  
Figure 10: Normalized current density vs. distance from center at 50 Hz (2D models) of 1-segment (**a**), 3-segment (**b**) and 5-segment (**c**).
# An Image-Based Fall Detection System for the Elderly
## 6 Conclusions  
In this paper, we presented the IFADS method to detect falls in the elderly using videos from surveillance systems or webcams. Given a video, IFADS can track a person, position the person based on the relationship between the person and the chair, recognize the person's posture by the change in the person's state and his/her position, and finally determine whether the person falls. We used 99 videos to test IFADS, and its accuracy was 95.96%. IFADS can be easily integrated into existing surveillance systems or webcams to help caregivers and security staff quickly detect falls. As a result, IFADS can be used by nursing homes to improve the quality of residential care facilities. In the future, we plan to extend IFADS to other scenarios, such as falling while picking something up from the ground and falling while getting out of bed.  
[PERSON] contributed to the system's design and implementation, the experimental work, and the manuscript's drafting. [PERSON] contributed to the system's design, the experiment's design, and the revision of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model Name** & **Time** & **Success Cases** & **Fall Cases** & **Accuracy** \\ \hline IFADS & 0.13 s & 62 & 62 & 100\% \\ YOLO & 0.12 s & 37 & 62 & 59.7\% \\ ssd\_mobilenet\_v1\_coco & 6.22 s & 25 & 62 & 40.3\% \\ faster\_RCNN\_inception\_v2\_coco & 10.03 s & 44 & 62 & 71.0\% \\ RFCN\_resnet101\_coco & 18.73 s & 50 & 62 & 80.6\% \\ faster\_RCNN\_NAS & 26.01 s & 47 & 62 & 75.8\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: The results of a falling person detected by the machine learning methods.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Actual: Fall** & **Actual: Non-Fall** & \\ \hline Predicted: Fall & 62 (TP) & 4 (FP) & Precision = 62/66 = 93.94\% \\ \hline Predicted: Non-fall & 0 (FN) & 33 (TN) & - \\ \hline Recall = 62/62 = 100\% & - & Accuracy = 95/99 = 95.96\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: Experimental results.  
Figure 20: (**a**) The person is unable to be detected; (**b**) The person is detected as another object.  
**Funding:** This work was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 107-2628-E-224-001-MY3.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry
## 2 Materials and Methods
### Modelling \(dh\) Uncertainty
#### 2.3.1 Theoretical Uncertainty of \(\omega\)  
\(\omega\) uncertainty (\(\sigma_{\omega}\)) depends on the parameters involved in its computation. Again, the variance propagation law can be used to obtain the estimate of the theoretical value of \(\sigma_{\omega}\) (Equation (6)):  
\[\sigma_{\omega}=\sqrt{\left(\frac{\partial\omega}{\partial B}\right)^{2}\cdot \sigma_{B}^{2}+\left(\frac{\partial\omega}{\partial R}\right)^{2}\cdot\sigma_{ R}^{2}+\left(\frac{\partial\omega}{\partial\theta}\right)^{2}\cdot\sigma_{B}^{2}+ \left(\frac{\partial\omega}{\partial R}\frac{\partial\omega}{\partial\theta} \right)\rho_{(R,\theta)}\sigma_{R}\sigma_{\theta}} \tag{6}\]  
where \(R\) is the slant range (here computed as \(R=\frac{H}{\cos\theta}\)); \(\sigma_{B}\) is the baseline uncertainty; \(\sigma_{R}\) and \(\sigma_{\theta}\) are the slant and look angle uncertainty, respectively; \(\rho_{(R,\theta)}\). is the Pearson's correlation coefficient between \(R\) and \(\theta\). These are known to be geometrically related (thus correlated), and consequently \(\rho_{(R,\theta)}\) must be set to +1.  
Concerning \(\sigma_{B}\), the S1-declared positional accuracy of the ESA provided precise orbit state vectors (Precise Orbit Determination--POD) is 5 cm [35,36]. This determines a \(\sigma_{B}\) value of 12 cm. \(\sigma_{\theta}\) was assumed equal to 0.01\({}^{\circ}\), and that is the nominal antenna attitude accuracy. \(\sigma_{R}\) can be estimated by Equation (7), assuming factors contribution as additive:  
\[\sigma_{R}=\sqrt{\sigma_{tropo}{}^{2}+\sigma_{iomo}{}^{2}+\sigma_{proc}{}^{2}+ \sigma_{TOF}{}^{2}} \tag{7}\]  
where \(\sigma_{tropo}\) and \(\sigma_{iomo}\) are the uncertainty of atmospheric delay induced by troposphere and ionosphere; \(\sigma_{proc}\) is the estimated contribution of SAR data processing effects in the S1 IW products; \(\sigma_{TOF}\) is the uncertainty of slant range signal time, i.e., the minimum detectable slant range distance between two scatterers.  
In order to evaluate the relative contribution of factors to the final estimate of \(\sigma_{\omega}\), \"weights\" of Table 2 (\(w_{i}\)) were computed with reference to \(\sigma_{\omega}^{2}\) according to Equation (6).
## 5 Conclusions  
This study developed a fuzzy set theory-based navigational obstacle risk assessment system that considers both collision and pollution risks, aiming to facilitate the rapid removal of navigational obstacles. The system was designed as a tool to infer the comprehensive risk by integrating the collision and pollution risk assessment models. Through both micro- and macro-level case studies, it was confirmed that the system provides reliable risk assessments, responds sensitively to changes in risk, and effectively reflects realistic site conditions.  
Therefore, this system has been shown to overcome the limitations of previous research and serve as a valuable decision-making tool for the rapid removal of navigational obstacles. Furthermore, the system demonstrates the potential for integration with maritime monitoring and response systems to provide real-time risk assessments and generate actionable recommendations for obstacle removal. However, certain limitations should be acknowledged. For example, reliance on static data sources, such as AIS data, may reduce applicability in dynamic or data-sparse environments. Additionally, challenges in implementing the system across different regions with varying maritime conditions and data availability could affect its overall effectiveness.  
This study represents an initial step toward the efficient removal of navigational obstacles. Future research will focus on addressing these limitations while leveraging this system to develop specific strategies for determining the timing and methods of obstacle removal.  
Conceptualization, D.L. and H.N.; methodology, D.L. and H.N.; software, D.L.; validation, D.L. and H.N.; formal analysis, D.L.; investigation, D.L.; resources, H.N.; data curation, S.-L.Y.; writing--original draft preparation, D.L.; writing--review and editing, H.N.; visualization, S.-L.Y.; supervision, H.N. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Research Foundation of Korea (NRF), funded by the Ministry of Education (MOE) through the \"Regional Innovation Strategy (RIS)\" (Grant No. 2023 RIS-009).  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors would like to extend their deep gratitude to [PERSON] of Mokpo National Maritime University for his invaluable assistance throughout the progress of this research.  
Author [PERSON] was employed by Future Ocean Information Technology, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AIS & Automatic Identification System \\ ALARP & As Low as Reasonably Possible \\ COG & Course Over Ground \\ DEEPP & Development of European Guidelines for Potentially Polluting \\ FIPA & Fisheries Infrastructure Public Agency \\ IMO & International Maritime Organization \\ \end{tabular}
# Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach
## 5 Problem Formulation and Algorithm  
### Optimization Problem  
In the energy market of the CEI, prosumers, utility grid and CHP operator compete with each other to maximize its own interests for their selfishness. To guarantee both efficiency and fairness, social welfare maximization is introduced and widely used. Social welfare maximization ensures the overall interests and maximizes each individual interest simultaneously. Here, we add up all the profits or utilities of the participants as the social welfare:  
\[\begin{array}{l}W(t)=P_{G}(t)+P_{P}(t)+P_{CHP}^{H}(t)\\ \quad\quad=\sum\limits_{i\in V_{G}}\left[p_{e}(t)P_{i}(t)-C_{i}(t)\right]\\ \quad\quad+\sum\limits_{i\in V_{P}}\left[p_{e}(t)(PV_{i}(t)-P_{i}(t)-P_{i}^{hp }(t))+p_{h}(t)(P_{i}^{hp}(t)COP-H_{i}(t))-I_{i}(t)\right]\\ \quad\quad+\sum\limits_{i\in V_{CHP}}\left[p_{e}(t)P_{i}(t)+p_{h}(t)H_{i}(t)-F_ {i}(H_{i}(t))\right]\end{array} \tag{16}\]  
At any time, the electric power and thermal power should be balanced in practical operation.  
\[\sum\limits_{i\in V_{G}}P_{i}(t)+\sum\limits_{i\in V_{CHP}}P_{i}(t)=\sum \limits_{i\in V_{P}}\left(P_{i}(t)+P_{i}^{hp}(t)-PV_{i}(t)\right) \tag{17}\]  
\[\sum\limits_{i\in V_{CHP}}H_{i}(t)=\sum\limits_{i\in V_{P}}\left(H_{i}(t)-P_{ i}^{hp}(t)COP\right) \tag{18}\]  
Now, we can rewrite Equation (16) by using Equations (17) and (18):  
\[max\quad\sum\limits_{i\in V_{G}}-C_{i}(t)+\sum\limits_{i\in V_{P}}-I_{i}(t)+ \sum\limits_{i\in V_{CHP}}-F_{i}(H_{i}(t)) \tag{19}\]  
Based on the previous description, energy management of the CEI can be formulated as a convex optimization problem:\[\begin{array}{ll}\min&\sum\limits_{i\in V_{G}}C_{i}(t)+\sum\limits_{i\in V_{P}}I_ {i}(t)+\sum\limits_{i\in V_{CHP}}F_{i}(H_{i}(t))\\ s.t.&\sum\limits_{i\in V_{G}}P_{i}(t)+\sum\limits_{i\in V_{CHP}}P_{i}(t)=\sum \limits_{i\in V_{P}}(P_{i}(t)+P_{i}^{hp}(t)-PV_{i}(t))\\ &\sum\limits_{i\in V_{CHP}}H_{i}(t)=\sum\limits_{i\in V_{P}}(H_{i}(t)-P_{i}^{ hp}(t)COP)\\ &P_{i}^{min}\leq P_{i}^{hp}(t)\leq P_{i}^{max},\;i\in V_{P}\\ &P_{i}^{min}\leq P_{i}(t)\leq P_{i}^{max},\;i\in V_{P}\\ &H_{i}^{min}\leq H_{i}(t)\leq H_{i}^{max},\;i\in V_{P}\\ &P_{i}^{min}\leq P_{i}(t)\leq P_{i}^{max},\;i\in V_{G}\\ &P_{i}^{min}\leq P_{i}(t)\leq P_{i}^{max},\;i\in V_{CHP}\\ &H_{i}^{min}\leq H_{i}(t)\leq H_{i}^{max},\;i\in V_{CHP}\end{array}\]  
where the equality constraints are global power constraints which describes the electric power balance and thermal power balance, the inequality constraints are local power constraints for all the participants, \(P_{i}^{min}\) and \(P_{i}^{max}\) are the lower and upper limit of electric power, \(H_{i}^{min}\) and \(H_{i}^{max}\) are the lower and upper limit of thermal power, respectively.
# A Study on the Effect of Drift Factor on Feature Optimization in Electronic Nose Detection
## 1 Introduction
[15] proposed a method for transferring the collar reconstruction limit learning machine, which reduces the difference in the distribution between the source domain and the target domain through the reconstruction and thus improves the robustness of the electronic nose. [PERSON] [16] used a nonlinear feature extraction method to tackle the drift problem of an electronic nose and improve contaminated gas detection. Although the influence of drift on the performance of electronic noses has been extensively explored and proven, we believe that the potential impact of drift on the feature optimization process has received insufficient attention. In light of this, the purpose of this study is to investigate the effect of the drift factor on the feature optimization module, as well as some methods for reducing its effect on this module, to improve the e-nose's drift-resistant performance. The following are the specific steps in our study:  
1. Processing of dataset and exploration of the effect of drift factor on feature optimization: First, we processed the data to visualize the drift effect and optimized the sensor features for different test environments. In this way, we obtained the scores of the sensors under different conditions, confirmed the influence of the drift factor on the feature optimization by comparison, and explored its regularity. 2. Processing of secondary feature optimization and sensor score concentration evaluation criteria: We present a method for performing this feature optimization before and after compensation in order to limit the impact of drift on feature optimization. Furthermore, we suggest and demonstrate the hypothesis that sensor concentration is positively connected with the proper categorization rate of the electronic nose. Exploring the optimal compensation processing method: We compare various combinations of feature optimization and compensation to determine the optimal processing group for the unweighted quadratic feature optimization group, which significantly improves the electronic nose's anti-drift performance.