esa-sceva/satcom-chunk-collection huggingface dataset:
# FPSO Hull Structures with Sandwich Plate System in Cargo Tanks
## 6 Ultimate Strength Analysis
### Finite Element Model  
The FPI rules [18] have some requirements for the finite element model that must be followed. First, the strength analysis follows a \"net\" ship approach. Therefore, the nominal design corrosion margin must be deducted from the scantling for the FEA. Second, the analysis must be a three-dimensional global model of three cargo tanks located at amidships with two frames of the end bulkheads (see Figure 7). Thus, the primary load-carrying members will be modeled as shown in Figure 7, which includes: transverse web frames, longitudinal and horizontal girders, centerline ring frames, side stringers, etc. This is due to the fact that the 3D finite element analysis (FEA) is used to determine the primary and secondary bending of the hull girder, as well as appropriate boundary conditions for the use in the fine-mesh FEA of local structures. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Structure** & **Steel Arrangement [ton]** & **SPS Arrangement [ton]** & **Difference** \\ \hline Bottom & 6950 & 5709 & \(-\)18\% \\ Side & 8920 & 8920 & - \\ Deck & 6251 & 6251 & - \\ Long BKD & 2541 & 2530 & \(-\)0.4\% \\ Side BKD & 4748 & 4748 & - \\ Trans BKD & 3062 & 3062 & - \\ Web Frame & 8487 & 8487 & - \\ Aft & 4096 & 4096 & - \\ Total Hull & 45,055 & 43,804 & \(-\)2.8\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Calculations of the weight for each part of the structure for both arrangements. Figure 7: FEM extension considered in the study. Moreover, the consistent modeling throughout the three cargo tanks is preferred. The desired mesh is considered in the middle tank, aiming at more accurate results in the strength assessment. According to [18; 19], the equivalent thickness model is an accurate model for the assessment of the ultimate strength and the distribution of the stresses. This model consists of using thicker plates that have inertia equal to a plate with longitudinal stiffeners. There are two benefits to it. The first one is the simplification of complex geometry. The second is that with fewer nodes and elements, less computational power is needed, and it is easier to achieve a converged solution. Therefore, the steel plates used both in the traditional and with the SPS plates structures are shown in Table 7.  
In the context of FEA of steel sandwich plates, there are several references on how to model it, such as [16]. Generally, one of the combinations below is required:  
* A single layer of layered shell elements, to be used through the thickness of the entire sandwich plates. * Shell elements for the faces, solid elements for the core, with the isotropic material properties for both. * Solid elements for both the face and the core with isotropic properties. The difference between them is related to the size of the model applied. According to the experience of SPS Technology and the DNV-CG-0154 [16], for more complex models, an
# Predicting the Risk of Chronic Kidney Disease (CKD) Using Machine Learning Algorithm
## 2 Materials and Methods  
### Dataset  
In this work, we used the open source data provided by National Health Insurance Sharing Service (NHISS), available from the site: [[https://nhiss.nhis.or.kr/](https://nhiss.nhis.or.kr/)]([https://nhiss.nhis.or.kr/](https://nhiss.nhis.or.kr/)). The dataset contains the regular heath check information for 1 million subjects between 25 and 90 years of age, data collected in 2017. There are 24 collected attributes; we added another three attributes, namely, GFR, Stage, and CKD, and their description is listed in Table 1.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ser** & **Variable** & **Type** & **Class** & **Description** \\ \hline
1 & Sex & Categorical & Predictor \\ \hline
2 & Age & Numerical & Predictor \\ \hline
3 & Waist & Numerical & Predictor \\ \hline
4 & Listen\_left & Categorical & Predictor & hearing impairment or not \\ \hline
5 & Listen\_right & Categorical & Predictor & hearing impairment or not \\ \hline
6 & Vision\_left & Numerical & Predictor \\ \hline
7 & Vision\_right & Numerical & Predictor \\ \hline
8 & BP\_HIGH & Numerical & Predictor & systolic pressure \\ \hline
9 & BP\_LWST & Numerical & Predictor & diastolic pressure \\ \hline
10 & BLDS & Numerical & Predictor & fasting blood sugar \\ \hline
11 & TOT\_CHOLE & Numerical & Predictor & total cholesterol \\ \hline
12 & TRIGLYCERIDE & Numerical & Predictor & triglycerides \\ \hline
13 & HDL\_CHOLE & Numerical & Predictor & high-density lipoprotein \\ \hline
14 & LDL\_CHOLE & Numerical & Predictor & cholesterol \\ \hline
15 & HMG & Numerical & Predictor & hemoglobin \\ \hline
16 & OLIG\_PROTE\_CD & Categorical & Predictor & the level of urine protein \\ \hline
17 & SGOT\_AST & Numerical & Predictor & aspartate amino-transferase \\ \hline
18 & SGPT\_ALT & Numerical & Predictor & alanine amino-transferase \\ \hline
19 & GAMMA\_GTP & Numerical & Predictor & gamma glutamyl transpeptiddas \\ \hline
20 & SMK\_STATE & Categorical & Predictor & smoking status \\ \hline
21 & DRINK\_OR\_NOT & Categorical & Predictor & drink habit \\ \hline
22 & MOUTH\_CHECK & Categorical & Predictor & decayed teeth or not \\ \hline \hline \end{tabular}
\end{table}
Table 1: Description of variables used in the analysis.  
In the first stage of the experiment, the 24 th entry in Table 1 is the target variable, where 1 to 23 are input variables to the regression model. The attributes 25-27 are not contained in the original collected data. Those added attributes are derived as follows. The 25 th attribute of glomerular filtration rate (GFR) is calculated using the formula shown below.  
\[GFR=186\times[Creatinine]^{-1.154}\times[Age]^{-0.203}\times[1.212\quad if\_ Black]\times[0.742\quad if\_Female] \tag{1}\]  
GFR is divided into 6 stages from normal level to renal failure, according to flow rate shown in Table 2. This is the 26 th attribute in Table 1. Stages 1 and 2 are regarded as normal non-CKD (class 0), and below that flow rate is regarded as CKD (class 1). This is the 27 th entry in Table 1 and is our final classification target (Target_2).
## 3 Current Signal Processing and Feature Extraction
### Characteristic Processing of High-Frequency Current Signal
#### 3.1.3 Pulse Indicators  
The pulse index \(I_{f}\) is defined as the ratio of signal peak to absolute mean, and the calculation formula is:  
\[I_{f}=\frac{x_{\max}}{|\overline{x}|}=\frac{\max[x_{\tau}(\tau)]}{\frac{1}{N} \sqrt{\sum\limits_{i=1}^{N}|x_{i}|}} \tag{3}\]  
In the formula, \(|\overline{x}|\) is the signal absolute mean.
# Delay-Sensitive Service Provisioning in Software-Defined Low-Earth-Orbit Satellite Networks
###### Abstract  
With the advancement of space technology and satellite communications, low-Earth-orbit (LEO) satellite networks have experienced rapid development in the past decade. In the vision of 6G, LEO satellite networks play an important role in future 6G networks. On the other hand, a variety of applications, including many delay-sensitive applications, are continuously emerging. Due to the highly dynamic nature of LEO satellite networks, supporting time-deterministic services in such networks is challenging. However, we can provide latency guarantees for most delay-sensitive applications through data plane traffic shaping and control plane routing optimization. This paper addresses the routing optimization problem for time-sensitive (TS) flows in software-defined low-Earth-orbit (LEO) satellite networks. We model the problem as an integer linear programming (ILP) model aiming to minimize path handovers and maximum link utilization while meeting TS flow latency constraints. Since this problem is NP-hard, we design an efficient longest continuous path (LCP) approximation algorithm. LCP selects the longest valid path in each topology snapshot that satisfies delay constraints. An auxiliary graph then determines the routing sequence with minimized handovers. We implement an LEO satellite network testbed with Open vSwitch (OVS) and an open-network operating system (ONOS) controller to evaluate LCP. The results show that LCP reduces the number of path handovers by up to 31.7% and keeps the maximum link utilization lowest for more than 75% of the time compared to benchmark algorithms. In summary, LCP achieves excellent path handover optimization and load balancing performance under TS flow latency constraints.  
low earth orbit; satellite network; time-sensitive; traffic shaping; routing optimization Article  
Delay-Sensitive Service Provisioning in Software-Defined Low-Earth-Orbit Satellite Networks  
123474[[https://doi.org/10.3390/electronics12163474](https://doi.org/10.3390/electronics12163474)]([https://doi.org/10.3390/electronics12163474](https://doi.org/10.3390/electronics12163474))
# _electronics_
## 3 Coded Packages Naming Lookup and Cache Placement  
### Naming and Finding Coded Packages  
In traditional NDN, each data block has its unique corresponding content name. After network coding is adopted, due to the different naming granularity of interest packages [23], an interest name no longer corresponds to a single data package [24], but to multiple coded packages. The user requests content from the access satellite by sending interest packages. The request arrives at the satellite networks and is forwarded to the cluster head node. The cluster head node checks its cache table. The cache table adopts a secondary directory, as shown in Figure 2. To reduce the number of first-level directory entries in the cache table,the granularity of the recorded content name is the file level. If the cluster head node finds the corresponding content, it will look for the secondary directory of the cache table. The secondary directory of the cache table is arranged in descending order, according to the number of file-coded blocks, and it also records the Node ID where the coded block is located. The cluster head forwards the request to the corresponding satellite node, and the node retrieves its own content storage (CS) table to find the stored coded package and deliver it.  
To reduce the large amount of stored entry data in the satellite node's CS table, this paper uses the naming dictionary tree to store it. Assuming that the content requested by the interest package is /par.com/video, the node will search for the prefix of the local cache entry using the dictionary tree. This search aims to find a matching complete string, extending from the root node of the dictionary tree to any leaf node that aligns with the content concatenation to constitute a content name; at the same time, the child nodes of any node on the concatenation path share the same naming prefix. As shown in Figure 3, when the satellite node retrieves node 4 and completes the matching, the content of the leaf node of node 4 /par.com/video/chunk1 and /par.com/video/chunk2 are the required coded packages.  
Figure 3: The structure of the naming dictionary tree.  
Figure 2: The structure of the cluster head node’s cache table.
# Experimental Study on the Surface Properties of Nanoalumina-Filled Epoxy Resin Nanocomposites
## 4 Conclusions  
This work studied the surface properties (namely the wettability and roughness) of EPNCs manufactured with different curing agents (DDM and DDSA+MNA) and reinforced with alumina NPs. The weight fractions of alumina NPs were 1, 3, and 5 wt. (%).  
From the obtained results, it was concluded that the CA decreases as the weight fraction of alumina NPs increases in the case of EPNCs with DDM as the curing agent, presenting hydrophobic behavior (\(90^{\circ}<9^{\circ}<120^{\circ}\)) until 3 wt. (%) and hydrophilic behavior (\(9^{\circ}<90^{\circ}\)) for the 5 wt. (%) sample. For EPNCs with DDSA+MNA as the hardener, complex behavior is achieved and the addition of alumina NPs promotes a decrease in CA in the CS until 1 wt. (%), with both being hydrophilic, followed by an increase of CA for 3 wt. (%) NPs and a small decrease for 5 wt. (%) NPs. For the two last NP loadings, the EPNCs were shown to be hydrophobic. The higher loading of alumina NPs (5 wt. (%)) were shown to have a negative effect on the hydrophobicity for EPNCs with DDM as the hardener, which became hydrophilic.  
Figure 7: Roughness versus contact angle.  
A decrease in the roughness for EPNCs with both hardeners was achieved from CS until 3 wt. (%), followed by an increase for 5 wt. (%). In the case of EPNCs with DDM, the higher roughness was observed for 5 wt. (%), while for EPNCs with DDSA+MNA, the higher roughness was observed for CS. The results for the average measured roughness did not show the same tendency as for the contact angle, as was expected. It may be necessary to ensure the homogeneity of the sample surfaces of EPNCs before testing, for instance by selecting the right polishing technique.  
[PERSON] designed and conducted experiments (contact angles, AFM images, and data processing), and contributed to the discussion of results. [PERSON] analyzed and interpreted results and wrote the manuscript. [PERSON] interpreted the results and wrote the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors acknowledge the Programa de Cooperacion Territorial INTERREG V-A MAC 2014-2020 and Proyecto Ecofibras (MAC/4.6d/040); the partial support of Fundacao para a Ciencia e a Tecnologia (FCT) (Project PEst-OE/QUUI/U10674/2019, CQM, Portuguese government funds) and Agencia Regional para o Desenvolvimento da Investigacao Tecnologia e Inovacao (ARDITI) through the project M1420-01-0145-FEDER-000005-CQM + (Madeira 14-20 Program); and to the project UID/EMS/00285/2019.This research is sponsored by the project UID/EMS/00285/2019. The authors also greatly appreciate [PERSON]'s help and support in the AFM analysis.  
The authors declare no conflict of interest.
# The Development of the Pipe Jacking Guidance Technology
## 9 Conclusions  
1. With the development of pipe jacking construction, pipe jacking construction develops in the direction of small-diameter and long-distance curved pipe jacking construction, which puts forward higher requirements for pipe jacking guiding technology.
2. Current guiding methods can be divided into four categories, namely, the manual visual inspection method, the laser target method, the prism method, the inertial guidance method and the hybrid method. The manual visual inspection method has a high degree of dependence on the technical level of technical personnel, but it is one of the important guiding means in the field of short, straight-line construction of pipe jacking. The laser target method is an upgrade from the manual visual method. This method is widely used in short, straight-line construction. However, since the laser can only propagate along a straight line and the laser spot dispersion increases with distance, it affects the guidance accuracy. Therefore, it cannot be applied in long-distance, curved construction, and it is necessary to add laser equipment for laser relay, which has a high cost and low reliability. The prism method is suitable for large-diameter pipe jacking construction, which can be applied to long-distance and curved projects by increasing the number of prisms and erecting new total stations, but the accuracy is limited by space and visibility conditions. The inertial guidance method can achieve independent guidance without the help of other equipment and has been widely studied in the application of long-distance and curved pipe jacking. However, due to the problem of error divergence accumulated over time, multiple sensors are often used to fuse data to improve accuracy. The hybrid method is based on the combined application of the above methods.
3. As can be seen from the classification of pipe-jacking guidance technologies, each method has its own problems. Multi-source data fusion can use multiple sensors to collect the same or complementary types of data, build data fusion models and improve guidance accuracy.  
Conceptualization, D.Q. and L.W.; methodology, D.Q. and Y.Z.; software, D.Q.; validation, D.Q., Y.Z. and Y.Q.; formal analysis, D.Q.; investigation, D.Q.; resources, D.Q.; data curation, D.Q.; writing--original draft preparation, D.Q.; writing--review and editing, D.Q., L.W., Y.Z. and Y.Q.; visualization, D.Q.; supervision, L.W.; project administration, L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
## 3 Results  
A chi-square test of independence was conducted to examine the relationship between scoring the first goal and the final match outcome. The results indicated a significant association between these variables: \(\chi^{2}(2,\) N = 36) = 8.167, \(p\) = 0.017. The observed frequencies were as follows: teams that scored the first goal lost 4 matches, drew 15, and won 17 games. The expected frequencies were 12 for each outcome, indicating that teams that scored the first goal were less likely to lose and more likely to draw or win compared to what would be expected by chance. The significant chi-square test result suggests that scoring the first goal is associated with the final match outcome, as teams scoring the first goal tend to avoid losses and are more likely to achieve draws or wins (Table 1). In order to examine the relationship between goals scored in the first half and the second half, a chi-square test of independence was also conducted (Table 1), which indicated no significant association between the goals scored in the first half and the second half, \(\chi^{2}(12,\) N = 36) = 10.869, \(p\) = 0.540. Additionally, a chi-square test for goodness of fit was conducted to examine whether the distribution of goals scored in six 15 min intervals of soccer matches differed significantly. Although the final interval (75-90 min) had the highest number of goals, no significant differences were noted regarding the goals scored across the six 15 min intervals, \(\chi^{2}(5,\) N = 82) = 4.049, \(p\) = 0.542, \(p\) > 0.05. The Kruskal-Wallis tests revealed significant differences among winning, drawing, and losing teams concerning several key attacking metrics (Table 2). Winning teams demonstrated superior performance in \"Goals Scored\", \"Total Attempts\", \"Attempts on Target\", \"Assists\", and \"Runs into the Penalty Area\", indicating their offensive efficiency. Additionally, metrics like \"Dribbles\" and \"Runs into Attacking Third\" also significantly favored winning teams. Interestingly, while winning teams tended to cover more distance on average, this difference was not statistically significant. This could suggest that while higher distance coverage may be a characteristic of winning teams, total distance covered was not a decisive factor in determining match outcome. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Goals Scored** & **M \(\pm\) SD** & **Min** & **Max** & **Sum** \\ \hline
1 st half goals & 1.08 \(\pm\) 0.93 & 0 & 3 & 39 \\
2 nd half goals & 1.19 \(\pm\) 1.16 & 0 & 4 & 43 \\
0–15 min & 0.36 \(\pm\) 0.54 & 0 & 2 & 13 \\
15–30 min & 0.44 \(\pm\) 0.60 & 0 & 2 & 16 \\
30–45 min & 0.28 \(\pm\) 0.51 & 0 & 2 & 10 \\
45–60 min & 0.36 \(\pm\) 0.63 & 0 & 2 & 13 \\
60–75 min & 0.31 \(\pm\) 0.52 & 0 & 2 & 11 \\
75–90 min & 0.53 \(\pm\) 0.60 & 0 & 2 & 19 \\ \hline \hline \end{tabular} Note: M \(\pm\) SD—mean \(\pm\) standard deviation, Min—minimum, Max—maximum, Sum—summation.  
\end{table} 
Table 1: Goals scored by match time intervals.
# Tulip-Shaped Pattern Imprinting for Omni-Phobic Surfaces Using Partially Cured Photopolymer
## 1 Introduction  
Functional films that realize characteristics appearing in nano- and micro-scale patterns have been fabricated biomimetically [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12]. Two representative processes for fine patterning are photolithography and soft lithography. Although photolithography allows excellent dimensional accuracy, it is limited in the size and surface curvature of the structure that can be manufactured and the process is expensive. On the other hand, soft lithography has the advantage of being able to nano-scale a structure, a simple process with a low process cost. In this paper, micro-sized structures were patterned on a substrate using ultraviolet (UV) nano-imprint lithography among soft lithography. Among the materials used in the UV nano-imprint lithography process, polyurethane acrylate (PUA) resins include radical polymerization resins containing acrylate as the main component and cation polymerization resins containing epoxy as the main component. Radical polymerization resins have a property of inhibiting UV curing by generating an inert material (I-R-O-O) when reacting with oxygen. This characteristic deteriorates the mechanical properties of fine structures manufactured with the correct dimensions. Therefore, studies have investigated optical curing mechanisms that either block oxygen or are not affected by oxygen [13; 14; 15].  
However, a recent study reported the use of curing inhibition characteristics to transform micro-scale line patterns. When PUA was imprinted using a porous polydimethylsiloxane (PDMS) mold, oxygen inherent in the mold cavity or penetrating the mold diffused into the resin, thus inhibiting ultraviolet (UV) curing. This produced partially cured structures with Bingham plastic behaviors; the partially cured structures deformed under the application of pressure exceeding the yield stress [16].  
In this paper, a tulip-shaped pattern imprinting process was designed to fabricate an omni-phobic surface with hydrophobicity and oleophobicity by referring to the ideas of the preceding study, and hydrophobicity and oleophobicity were confirmed through static contact angle measurement [17; 18]. Previously, chemical surface treatment processes such as etching [19; 20; 21; 22; 23; 24; 25] and deposition/coating [26; 27; 28; 29; 30; 31; 32; 33; 34] were used as a process to fabricate hydrophobic/oleophobic surfaces, but chemicals that are not good for the human body or the environment, such as fluorine, were used. In contrast, the tulip-shaped pattern imprinting process proposed in this paper has the advantages of not using chemicals harmful to humans and the environment and being able to perform the process in minutes by inducing micro-pattern deformations based on UV nano-imprint lithography. Furthermore, when applying the Roll-to-Roll process, it is possible to fabricate a large-area omni-phobic surface.
# An Affinity Propagation-Based Self-Adaptive Clustering Method for Wireless Sensor Networks
## 5 Performance Evaluation
### Study of Affinity Propagation (AP) Preference  
The parameter \(p\) has a great impact on the performance of APSA in terms of convergence time and number of clusters. Different values of \(p\) are tested under the same network model (100 sensors) and the simulation result is shown as Table 3. As shown in Table 3, when \(p\) is set as -6000, the algorithm convergences faster and achieves a more reasonable number of clusters.