esa-sceva/satcom-chunk-collection huggingface dataset:
# Lossless and High-Throughput Congestion Control in Satellite-Based Cloud Platforms +
## 6 Conclusions  
This paper proposes the CCLF method as a solution for congestion control challenges in satellite-based cloud platforms. By optimizing the storage and forwarding mechanisms of NDN, including output queue monitoring and prioritized packet scheduling, the CCLF method achieves zero packet loss and meets QoS requirements. It dynamically adjusts the forwarding rates of data flows in response to the time-varying conditions of satellite networks, enabling full bandwidth utilization. This approach addresses the conventional throughput limitations imposed by bottleneck bandwidth, enhancing network throughput. The simulation results indicate that the CCLF method achieves zero packet loss, reduces the flow completion time, improves network throughput, and provides QoS guarantees. In summary, the CCLF method addresses critical issues such as packet loss, retransmission timeouts, and significant transmission delay variations. Its features of lossless transmission, high throughput, and low delays make it highly suitable for the development of satellite-based cloud platforms. In future work, we will quantify variations in transmission delays  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Performance** & **PCON** & **CCLF** \\ \hline Packet loss & Occurrence & Non-occurrence \\ Control master & Consumers and routers & Routers \\ Control mode & Adjust sending rate of Interests & Data scheduling and forwarding \\ Throughput & Floating & Stable \\ Bandwidth usage & Underutilized bandwidth & Full bandwidth utilization \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of congestion control schemes.  
across different priority levels, providing predictable delays for data flows supporting various applications.  
Conceptualization, W.D. and T.L.; methodology, W.D.; validation, J.A. and Y.Z.; formal analysis, Z.L.; writing--original draft preparation, W.D.; writing--review and editing, T.L.; visualization, Z.L.; supervision, Y.Z.; project administration, J.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The data presented in this study are private, from the School of Information and Electronics, Beijing Institute of Technology.  
The authors declare no conflicts of interest.
# Experimental Study on Dynamic Response Characteristics of RPC and RC Micro Piles in SAJBs
## 3 Experimental Results
### Bending Moment of Piles
#### 3.3.2 The Influence of Seismic Waves  
The bending moments of RPC and RC piles under different seismic loads in cases 6, 7, and 8 (EI-Centro wave, Kobe wave, and artificial wave) were also output and plotted in Figure 9a,b, respectively. The bending moment distribution laws under different seismic wave loads are also basically consistent for each pile. It can be seen that the bending moments of piles above the soil surface decrease linearly from the soil surface to the top of the piles, and the bending moments of RPC and RC piles increase rapidly with the increase of buried depth and reach the maximum positive value at the buried depths of 0.637 m (6.4D) and 0.425 m (4.3D), respectively. Furthermore, the bending moments of piles gradually diminish to 0 kN\(\cdot\)m as the buried depth increases. The reason for the different buried depths at the corresponding peak bending moment of piles also resemble what was mentioned previously. It can be seen that the elastic modulus and flexural rigidity of the RPC pile are larger than that of the RC pile, and that the peak bending moments and corresponding buried depths are larger than that of the RC pile.  
As seen in Figure 9, it was also found that the peak bending moments of RPC and RC micro piles under different seismic loads in cases 6, 7, and 8 are 1.01 kN\(\cdot\)m and 0.73 kN\(\cdot\)m, 0.49 kN\(\cdot\)m, and 0.40 kN\(\cdot\)m, 1.57 kN\(\cdot\)m, and 1.11 kN\(\cdot\)m respectively. Therefore, it concluded that the bending moment of micro piles under an artificial wave load is significantly greater than that of the other two seismic loads. The bending moment of the pile under the Kobe wave load is smallest, and that of EI-Centro follows. Accordingly, the influence of different seismic wave loads on the bending moment of piles is remarkable, and the effect of artificial wave load is significant. Besides, the bending moment of the RC pile is smaller than that of the RPC pile, which is decreased by 40%. It was because the flexural rigidity of the RPC micro pile is larger than that of the RC pile, and the bending moment of piles increases significantly with the increase of flexural rigidity under seismic wave loads.
## 3 Proposed Method
### Clustering and Labeling  
In the training phase, a large number of moving objects \(\mathbf{O}\) are extracted by the background-subtraction method. According to prior knowledge, these objects have two characteristics: (1) numerous objects; (2) fewer categories.  
Several parts of the pumping unit are detected as foreground targets, which are classified into the same category. The moving objects that need to be recognized in the pumping-unit monitoring site are divided into three categories: pumping unit, vehicle, and pedestrian. There are many kinds of clustering algorithms that are used to deal with data-structure partition [22; 23; 24]. In this paper, foreground objects are subdivided into several subcategories by a hierarchical clustering algorithm, and then these subcategories are divided into pumping unit, vehicle, and pedestrian through human intervention, which are used as the training data of GoogLeNet.  
Strategies for hierarchical clustering generally fall into two types, agglomerative and divisive [25]. This clustering method uses data linkage criteria to repeatedly merge or split the data to build a hierarchy of clusters through a hierarchical architecture. The clustering process is as follows:  
(1) Assuming that foreground moving object \(\mathbf{O}=\{o_{1},o_{2},\cdots o_{k}\}\) has \(k\) samples, the resolution of foreground moving object \(\mathbf{O}\) is resized to \(224\times 224\).  
(2) Samples are aggregated by a bottom-up approach, and Euclidean distance is chosen as the similarity measurement between categories:  
\[d(o_{i},o_{j})=\big{\|}o_{i}-o_{j}\big{\|}_{2} \tag{3}\]  
where \(i,j=1,2\cdots k\). Linkage criteria use the average distance between all pairs of objects in any two clusters:  
\[D(r,s)=\frac{1}{n_{r}n_{s}}\sum_{i=1}^{n_{r}}\sum_{j=1}^{n_{s}}d\big{(}o_{ri},o_{sj}\big{)}, \tag{4}\]  
where \(r\) and \(s\) are clusters and \(n_{r}\) and \(n_{s}\) are the number of objects in cluster \(r\) and \(s\), respectively. Similarly, \(o_{ri}\) and \(o_{sj}\) are the \(i\)th and \(j\)th object in cluster \(r\) and \(s\), respectively.  
(3) The pedestrian and vehicle categories in hierarchical clustering are selected separately, and the other categories are classified as part of the pumping-unit category.  
Figure 4 shows the clustering process of foreground objects.
# The Application of Nano Titanium Dioxide for Hydrogen Production and Storage Enhancement
###### Abstract  
The utilization of hydrogen (H\({}_{2}\)) as a renewable and clean energy carrier, free from the reliance on fossil fuels, represents a significant technological challenge. The use of renewable energy sources for hydrogen production, such as photocatalytic hydrogen generation from water under solar radiation, has garnered significant interest. Indeed, the storage of hydrogen presents another hurdle to the ongoing advancement of hydrogen energy. Concerning solid-state hydrogen storage, magnesium hydride (MgH\({}_{2}\)) has emerged as a promising option due to its high capacity, excellent reversibility, and cost-effectiveness. Nevertheless, its storage performance needs improvement to make it suitable for practical applications. Titanium dioxide (TiO\({}_{2}\)) has distinguished itself as the most extensively researched photocatalyst owing to its high photo-activity, good chemical and thermal stability, low toxicity, and affordability. This review highlights the application of TiO\({}_{2}\) for hydrogen production under visible and solar light, with a particular focus both on its modification without the use of noble metals and its utilization as a catalyst to enhance the hydrogen storage performance of MgH\({}_{2}\).  
titanium dioxide; hydrogen production; hydrogen storage +
Footnote †: journal:  
_Applied_  
_sciences_
## 4 Discussion  
### The Identification of a Set of Significant Causes That Lead to Accidents on Building Scaffoldings  
On the basis of the obtained results, it can be concluded that in the analyzed case, the Pareto principle that 20% of the identified causes occur in 80% of accidents involving scaffolding was not 100% fulfilled. In the analyzed cases, the following proportions of the causes with regard to their effects occurred:  
* Very significant technical causes were: \(t_{1}\)--lack of or inadequate protective devices; \(t_{2}\)--lack of or inadequate measures of collective protection; \(t_{3}\)--improper spatial structure of scaffoldings; \(t_{4}\)--improper stability of scaffoldings. These causes constituted 28.6% of all the identified technical causes and occurred in 83% of all the accidents.
* Very significant organizational causes were: \(o_{1}\)--a lack of supervision; \(o_{2}\)--admission of scaffoldings to operation without the required inspection and supervision; \(o_{3}\)--lack of or inadequate training in the area of occupational health and safety; \(o_{4}\)--acceptance of deviations from the rules and regulations of occupational health and safety; \(o_{5}\)-- inadequate professional training of an employee; \(o_{6}\)--lack of instructions on how to use scaffoldings safely; \(o_{7}\)--admission of an employee to work without medical examination or with medical contraindications; \(o_{8}\)--inadequate passages and access points. These causes constituted 40% of all the organizational causes and occurred in 84% all the accidents.
* Very significant human causes were: \(l_{1}\)--failure to use personal protective equipment by an employee; \(l_{2}\)--disregarding danger; \(l_{3}\)--being surprised by an unexpected event; \(l_{4}\)--consumption of alcohol, drugs or psychotropic substances; \(l_{5}\)--insufficient concentration; \(l_{6}\)--going to, driving through or staying in places that are forbidden; \(l_{7}\)--performing work that is not included in the scope of an employee's duties; \(l_{8}\)--ignorance of hazards. These causes accounted for 30.76% of all the identified human causes and occurred in 80% of all the accidents.  
Figure 6: Share of technical, organizational and human causes in the subsets of accident events \(Ak\) (\(k=1,2,3\)).  
There is a very high probability that with an increase in the number of accidents involving scaffolding, the obtained proportions will be closer to the theoretical proportion of the Pareto principle, i.e., 20%/80%.
## 4 Technical Implementation
This involves two main steps: first, a linear buckling analysis (LBA) is conducted to determine the critical buckling load factor and extract buckling modes, which are then used to introduce initial geometric imperfections into the model based on selected mode shapes. Second, a material and geometrical nonlinear analysis is performed on the geometrically imperfect model to evaluate the maximum equivalent plastic strain and joint rotation under a predefined load level. Once these parameters are assessed, the corresponding penalty functions are calculated and combined with the volume function to establish the final fitness value for each individual, as presented in Algorithm 1. Finally, the genetic operators described earlier are applied to generate the offspring population. During this phase, the chromosomes are modified, resulting in new design configurations along with their corresponding physical representations and automatically generated FE models. This iterative process is repeated until the specified number of generations is reached. Furthermore, it is worth highlighting that the proposed framework, along with its technical implementation, is adaptable to a broad range of structural problems analyzed \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Maximum number of generations & 10 \\ Population size & 20 \\ Crossover probability & 0.7 \\ Mutation probability & 0.1–0.9 \\ Tournament size & 2 \\ Elitism size & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The initial parameters of the genetic algorithm. Figure 3: The workflow of the developed framework. using FEM. Specifically, the ABAQUS software environment supports extensive model development through PYTHON scripting, enabling seamless integration with GA-based optimization routines. Within this framework, the objective function, penalty terms, and constraints can be readily modified or replaced with alternative mathematical formulations tailored to guide the optimization process toward the most suitable solution for the problem under investigation. Potential future applications include the holistic optimization of entire structural frames, encompassing both connection detailing and cross-sectional design under various load combinations. Moreover, the methodology could be extended to the design of steel plate shear walls with rigid connections, such as those investigated by [PERSON] et al. [23, 24], with the goal of determining optimal infill web-strip configurations that minimize plastic deformations under dynamic loading conditions.
# Dynamic Repositioning of Aerial Base Stations for Enhanced User Experience in 5G and Beyond
## 3 System Model
### Aerial Base Stations  
The small cells are mounted on UAVs called ABSs, and their deployment locations can be changed in response to user changes in density and mobility. We assume that the ABSs can autonomously move to the candidate location, perch, and connect to the power source there. Exactly how these tasks will be accomplished is outside the scope of this work, but given the rapid advancements in the autonomous flight of UAVs and localization, these assumptions are realistic.
# Modeling Shadow with Voxel-Based Trees for Sentinel-2 Reflectance Simulation in Tropical Rainforest
## 4 Discussion  
### The Effect of Canopy Shape on Reflectance Simulation  
Considering the potential role of canopy shape in estimating reflectance and shadow fraction, it is crucial to quantify its effects, and therefore improve the simulation. The optimal canopy shape was determined by comparing the simulated reflectance with satellite-based reflectance, which enabled estimating the canopy shape without field measurements. This was the first study to conduct an analysis of canopy shape in a reflectance simulation. Based on the results of the analysis, we could choose the SZA when the canopy shape had the most significant effect on the reflectance simulation, namely, the SZA of 40\({}^{\circ}\). At 40\({}^{\circ}\) SZA, the reflectance simulation varied distinctly with different canopy shapes and could therefore be used to determine the optimal combination. In addition, this method is flexible and can be applied to various forests by adjusting the parameters. The slope is also in the parameters, so forests in mountainous areas can also be represented.  
The results in Table 6 showed that the optimal canopy shape that had the least RMSE (0.385) in the reflectance simulation also had the lowest RMSE (0.032) in the shadow fraction estimation. Additionally, canopy shapes with larger RMSE in the reflectance simulation had larger RMSE in the shadow simulation. These findings emphasize that the results of reflectance simulations using CSRS are effective for estimating the shadow fraction. Therefore, it is possible to determine the optimal canopy shape by simulating the reflectance using a virtual forest, and then applying it in estimating the shadow fraction.  
Furthermore, relative reflectance calculated based on the images from two seasons was adopted instead of using absolute reflectance. In absolute reflectance, if the spectral reflectance of each overstory or understory given to the CSRS differs from the actual one, the error becomes larger. With relative reflectance, on the other hand, the effects of canopy shape and SZA are larger than those effects; this helped us with obtaining optimal canopy shape. Although the UAV-SfM results were used to determine parameters other than canopy shape in this study, satellite-based forest structure products or allometric equations for representative tree species contribute to not using field measurements. To extend the method greatly, it will be necessary to simulate various forest structures and create look-up tables for Sentinel-2 reflectance and canopy shape. This will enable estimation of shadow fraction at arbitrary locations, which is expected to further improve the accuracy of GPP estimation in the future. In addition, a trait-based approach using remote sensing data has recently been developed [32]. This approach is limited in coverage because the forest structure is obtained by the Airborne Laser Scanner, but it is expected that the method could be extended to a wider area by combining it with CSRS.
## 3 Comparison Traditional Access Control vs. Security Access Control Based on Three Layers
### Traditional Security-Based Fundamental Access Control Policy Approaches
#### 3.1.1 Network Access Control Policy (NAC)  
This technique focuses on the management and control of access to enterprise networks. NAC controls the devices that access the corporate network and provides secure and regulated network access to various devices from various locations. In addition, NAC can implement authentication and encryption security controls and integrate MDM tools into the network infrastructure to manage network services and resources and monitor the entire network. This strategy uses virtual local area network (LANs)to reduce network traffic by classifying users according to access control policies or functions [13]. Some network BYOD solutions, such as those developed by Cisco and Meru Networks, recommend BYOD management through network methods [13]. However, NAC is subject to the following limitations:  
* Managing and accessing rich media material can contribute to network congestion.
* Malicious devices linked to the network can contaminate it.
* Malicious or infected devices can infect others on the same virtual local area network (VLAN).
## Materials and Methods
### Characterization  
The crystalline structure and phases of the samples were performed by X-ray diffraction (XRD, Rigaku Denki Co. Ltd., Tokyo, Japan) using a Cu K\(\alpha\) radiation (\(\lambda\) = 0.15418 nm) in a scattering range (20) of 10-80\({}^{\circ}\) at an accelerating voltage of 40 kV. X-ray photoelectron spectroscopy (XPS) studies were performed using the ESCALAB 250 Xi (Thermo Fisher Scientific, Waltham, MA, USA). The morphologies of the as-synthesized samples were characterized by scanning electron microscopy (SEM, JSM-7500F, JEOL, Beijing, China) and transmission electron microscopy (TEM, JEM-2100 microscope with an accelerating voltage of 200 kV, JEOL, Beijing, China). The EM parameters of complex relative permeability (\(\mu_{\mathrm{r}}\) = \(\mu^{\prime}-j\mu^{\prime\prime}\)) and permittivity (\(\epsilon_{\mathrm{r}}\) = \(\varepsilon^{\prime}-j\varepsilon^{\prime\prime}\)) in the frequency range of 2-18 GHz were performed by vector network analyzer, Agilent, N5230A (Agilent Technologies Inc., Santa Clara, CA, USA, as shown in Figure 1a). The as-prepared samples were mixed with paraffin (different mass percentages) and pressed into toroidal-shaped samples (inner diameter \(\phi_{\mathrm{in}}\) = 3.04 mm, outer diameter \(\phi_{\mathrm{out}}\) = 7.00 mm, as shown in Figure 1b).
# Demand Forecasting in Supply Chain Using Uni-Regression Deep Approximate Forecasting Model
## 5 Results and Discussions
### Comparative Methods
#### 5.3.2 Comparative Analysis of Demand Forecasting Dataset Based on K-Fold  
The evaluation's Figure 5a demonstrates the UDAF model's exceptional performance in demand forecasting, outperforming NARX with the lowest error of 1.67 and an MAE of 1.22.  
Figure 5b further showcases the UDAF model's effectiveness in demand forecasting, surpassing NARX by 22.49% with an MSE of 1.16 for a K-fold 10.  
When it comes to demand forecasting, the UDAF model, as seen in Figure 5c, excels in comparison to NARX. It achieves an improvement of 81.02 and has an RMSE of 1.08 for a K-fold 10, surpassing previous techniques.  
Furthermore, Figure 5d demonstrates the UDAF model's proficiency in demand forecasting through RMSSE, outperforming NARX by 47.36% with a 0.019 RMSSE for a K-fold 10.  
Figure 4: Comparative analysis based of demand forecasting dataset based on delay: (**a**) MAE, (**b**) MSE, (**c**) RMSE, (**d**) RMSSE, and (**e**) R-squared.  
Regarding demand forecasting, Figure 5e showcases the superior performance of the UDAF model compared to NARX with an R-squared of 0.96 for a K-fold 10, which is 1.04% improved over NARX.
## 4 Conclusions  
Nowadays, satellite precipitation products (SPPs) are widely applied in meteorology, hydrology, and ecology research fields. In this study of six major precipitation products, namely 3B42 RT, 3B42V7, GPCP-1 DD, PERSIANN-CDR, CMORPH, and APHRODITE, our objective was to evaluate their ability to accurately assess the daily, monthly, seasonal, and annual rainfalls over Malaysia. The main conclusions obtained by using 342 rain gauges surveyed during 2003-2007 are as follows:  
1. There was a tendency for 3B42V7 and APHRODITE to yield accurate and unbiased estimations and for GPCP-1D to perform the worst. In addition, while APHRODITE and CMORPH dramatically underestimated precipitation, GPCP-1 DD exhibited slight underestimations and 3B42 RT, 3B42V7, and PERSIANN-CDR showed slight overestimations. TRMM products (3B42 RT and 3B42V7) showed better estimation of seasonal precipitation. The SPPs performed better in the northeast monsoon than in the southwest monsoon.
2. The SPPs' performance was the best in the regions receiving higher annual precipitation, such as eastern and southern Peninsular Malaysia and northern East Malaysia. By contrast, poor SPP performance occurred over western Peninsular Malaysia, which is characterized by low rainfall amounts since it is sheltered from the monsoons by the Titiwangsa Range and Sumatra.
3. In terms of rain-detection ability, the precipitation products had a high accuracy (ACC) and probability of detection (POD) performance and moderate false alarm ratio (FAR), critical success index (CSI), and Heidke skill score (HSS) performance. PERSIANN-CDR received the highest POD value, but its HSS value was also the lowest in all six products. Overall, 3B42 RT and 3B42V7 performed better in rain-detection ability as they had better ACC, CSI, FAR, and HSS values.
4. Most of the SPPs showed best performance during flood events, but had the tendency to underestimate the tiny to heavy rain amount (rain \(<\) 1 mm/day; rain \(\geq\) 20 mm/day) and to overestimate the moderate ones (1 \(\leq\) rain \(<\) 20 mm/day). This was with the exception of 3B42 RT and 3B42V7, which were accurate across the whole range of event sizes.  
These results demonstrate the large discrepancies in the quality of available precipitation products for daily to monthly time scales. The spatial-temporal assessment of the products performed in the present study allowed us to identify some of the sources of errors such as the effect of various sensors, topography, and the retrieval algorithm [66, 67]. Future studies should evaluate whether SPPs could provide reliable enough input information to hydrological models for simulating water movements and floods in river basins over Malaysia. Besides that, the TRMM products could be used through hydrological modeling [68] to analyze the causes of the flood events that hit Malaysia recently (December 2006 to January 2007; December 2014 to January 2015), the latter of which has affected more than 230,000 people, killing 23 and costing $560 million.