esa-sceva/satcom-chunk-collection huggingface dataset:
# Robotic Cell Layout Optimization Using a Genetic Algorithm
## 3 Results
### Assembly Cell--Case Study 3  
The assembly of the parts is carried out in the third cell, where the material stations are distributed in such a way that a 6-axis robot (RV-7 FRD, Mitsubishi Electric, Tokyo, Japan) takes the material from each station, places the parts in the assembly station, and removes the finished product. Figure 10 shows the actual layout of the assembly cell, a circular cell where the stations with the individual components are arranged around the base of the robot. Table 6 provides the dimensions of each workstation.  
In Figure 11, the proposed solution by the algorithm is shown. In Figure 11, the proposed solution by the algorithm is shown. Table 7 presents the current travel times performed by the robot and  
A reduction of 0.98 s in transfer time was achieved, representing a 9.15% decrease compared to the currently operating robotic cell. This improvement was made possible through the optimization performed by the algorithm, which adjusted the station layout and the robot's movement paths within the cell. Table 8 summarizes the results obtained for each of the robotic cells evaluated, highlighting the superiority of the proposed method with a 3.44 s improvement in production time.  
The results demonstrate a significant improvement in the operational efficiency of the robotic cell due to the optimization of the workstation layout using a genetic algorithm. The new arrangement allowed for a notable reduction in transfer times, achieving a decrease in operational cycles by 9.06%. This optimization not only speeds up the production process but also maximizes the utilization of available resources, resulting in increased productivity and greater competitiveness on the production line. The use of the genetic algorithm has been key to exploring multiple possible configurations and finding the optimal solution that would otherwise be difficult to identify manually.
# Extracting Crop Spatial Distribution from Gaofen 2 Imagery Using a Convolutional Neural Network
## 5 Discussion  
### Tuning of the Parameter Settings of the Proposed CEM  
When constructing the structure of the CEM model, we borrowed from the classical RefineNet model and the structure of the VGG model. The multipath structure of the RefineNet model can effectively integrate high-and low-level features and improve the feature extraction ability of the model. We implemented the multipath structure as the basic structure of the CEM model. Considering the characteristics of GF-2 remote sensing images, we set up a feature extraction unit using three downscaling and two feature extraction units that do not change scale. This design could ensure that the CEM model extracts enough features.  
When designing the structure of the feature extraction unit, we borrowed the structure of the VGG model and adopted three convolution layer superposition strategies. The advantage of this design is it makes it possible to ensure that feature extraction has sufficient receptive domains and can reduce parameters.  
Considering that there are a large number of mixed pixels in the GF-2 images, the use of spectral features is beneficial to improve classification accuracy. Two convolution kernels were set for each class to extract spectral features, and a total of 16 convolution kernels were set. Among them, considering that the infrared band in the GF-2 image is sensitive to vegetation, a fixed convolution kernel was set to map the infrared band's ability to respond to vegetation.  
The above strategy effectively improved the generalization ability of the model.
###### Abstract  
The identification of sensing group targets and extended targets is of paramount importance in the context of vehicle tracking and early warning detection. As the scope of target monitoring and tracking extends, conventional single-sensor-based tracking techniques are proving to be inadequate in meeting the practical demands of the field. Consequently, multi-sensor fusion tracking technology has emerged as a viable alternative. However, the use of multiple sensors is constrained by their limited fields of view (FOVs), which leads to issues such as the loss of target detection and the introduction of false targets after fusion. Hence, this study proposes a combination of weighted geometric averaging (WGA) and weighted arithmetic averaging (WAA) methods to solve distributed multi-group/extended target tracking with different fields of view. Specifically, a local Poisson multi-Bernoulli mixture (PMBM) filter was first used on individual sensors. Subsequently, we combined a sequential fusion technique and the proposed fusion approach to fuse the PMBM filter densities. The efficacy and superiority of this approach were demonstrated through simulations.  
group/extended target; limited FOV; distributed fusion; WGA; WAA; PMBM +
Footnote †: journal: Applied  
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# Real-Time Lightweight Morphological Detection for Chinese Mitten Crab Origin Tracing
## 3 Experimental Results and Analysis
### Crab Classification
#### 3.3.3 Comparison with Traditional Methods  
To highlight the advantages of the proposed method, we conducted a comparison with two representative traditional traceability approaches: morphological identification and biochemical analysis.  
Morphological methods rely heavily on expert judgment. The classification process typically takes several minutes per sample and is prone to subjectivity, leading to inconsistent results when used by non-experts. This approach is not scalable for real-time or large-scale applications.  
Biochemical techniques such as Sr isotope fingerprinting offer high precision [4], but the analysis requires high-end instruments (e.g., MC-ICP-MS), complex sample digestion and purification steps, and typically 2-3 working days to complete one batch. The per-sample testing cost is also relatively high (200-500 RMB depending on protocol and lab). Furthermore, they are unsuitable for rapid or automated field deployment.  
In contrast, the proposed two-stage deep learning framework achieves a classification accuracy of 99.5% and an inference speed of 309 FPS without relying on extensive manual labor or chemical analysis. It offers a low-cost, real-time, and efficient solution suitable for large-scale aquatic product origin traceability.
# An Improved Grey Wolf Optimizer Based on Differential Evolution and OTSU Algorithm
###### Abstract  
Aimed at solving the problems of poor stability and easily falling into the local optimal solution in the grey wolf optimizer (GWO) algorithm, an improved GWO algorithm based on the differential evolution (DE) algorithm and the OTSU algorithm is proposed (DE-OTSU-GWO). The multithreshold OTSU, Tsallis entropy, and DE algorithm are combined with the GWO algorithm. The multithreshold OTSU algorithm is used to calculate the fitness of the initial population. The population is updated using the GWO algorithm and the DE algorithm through the Tsallis entropy algorithm for crossover steps. Multithreshold OTSU calculates the fitness in the initial population and makes the initial stage basically stable. Tsallis entropy calculates the fitness quickly. The DE algorithm can solve the local optimal solution of GWO. The performance of the DE-OTSU-GWO algorithm was tested using a CEC2005 benchmark function (23 test functions). Compared with existing particle swarm optimizer (PSO) and GWO algorithms, the experimental results showed that the DE-OTSU-GWO algorithm is more stable and accurate in solving functions. In addition, compared with other algorithms, a convergence behavior analysis proved the high quality of the DE-OTSU-GWO algorithm. In the results of classical agricultural image recognition problems, compared with GWO, PSO, DE-GWO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm had accuracy in straw image recognition and is applicable to practical problems. The OTSU algorithm improves the accuracy of the overall algorithm while increasing the running time. After adding the DE algorithm, the time complexity will increase, but the solution time can be shortened. Compared with GWO, DE-GWO, PSO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm has better results in segmentation assessment.  
grey wolf optimizer; differential evolution; multithreshold OTSU; tsallis entropy; image segmentation; straw coverage detection 2020
# ESCAPE: Evacuation Strategy through Clustering and Autonomous Operation in Public Safety Systems
## 6 Numerical Results  
In this section, we present indicative numerical results that illustrate and explain the operation, features, and benefits of the proposed ESCAPE service. Initially, in Section 6.1, we focused on the evaluation of the operational characteristics of our proposed pure framework. Furthermore,in Section 6.2 we provided scalability and complexity analysis of the proposed framework, while in Section 6.3 we performed a comparative study of our proposed approach against alternative strategies in order to better reveal its benefits.  
In our study, unless otherwise explicitly stated, we consider a set of 301 evacuees, i.e., \(|M|=301\), and four possible evacuation routes, i.e., \(|E|=4\), with randomly assigned respective capacities \(C_{e}\in[9,15],C_{e}\in\mathbb{N},\forall e\in E\). Moreover, the number of evacuees who were already in a certain evacuation route \(e\) was initialized to \(|M|_{e}=0,\forall e\in E\) and evacuation rates were randomly initialized to \(\lambda_{e}\in[0.2,0.9],\forall e\in E\). The distance of each evacuee \(m\) from each evacuation route \(e\) was normalized within the range of \((0.0,1.0]\), and randomly assigned as \(d_{m,e}\in(0.0,1.0]\).
# A Miniaturized RHCP Slot Antenna for Wideband Applications Including Sub-6 GHz 5G
## 2 Antenna Structure  
The geometry of the proposed wide-slot antenna is exhibited in Figure 1. The antenna is etched on an FR4 substrate with a dielectric constant of \(\varepsilon_{r}\) = 4.3, height of h = 1.6 mm, and loss tangent of tan\(\delta\) = 0.025. The overall dimensions of this antenna are 54 \(\times\) 50 \(\times\) 1.6 mm\({}^{3}\), which is equivalent to 0.39\(\lambda\)\(\times\) 0.36\(\lambda\)\(\times\) 0.0117\(\lambda\), where \(\lambda\) is the free-space wavelength corresponding to the lowest resonant frequency. The tuning stub of the antenna is fed by using a 50 \(\Omega\) microstrip feedline, while the ground plane is engraved as a square slot on the bottom surface of the dielectric substrate. To obtain good coupling and achieve wideband CP, modified strips and stubs are added to the tuning stub and the wide slot. All the key parameters that improve the CP performance are studied in Section 5. Simulated results of the proposed antenna are acquired by using the CST Microwave Studio Suite.  
The proposed wide-slot antenna is based on a modified feeding mechanism and an optimized slot geometry. Starting from the conventional rectangular slot antenna, this design improves the impedance matching and the ARBW by leveraging the parasitic and strip elements of the design. Therefore, these strategies contribute to achieving wideband CP while maintaining a compact size to make it useful in many wireless communications applications, such as ISM bands (2.4-2.5 GHz), WiMAX (2.3-3.8 GHz), and C-band (3.3-4.2 GHz).
# Influence of Pile Foundation Stiffness on Column Design in One-Story Reinforced Concrete Frames
## 1 Introduction  
The absence of slenderness restrictions in Eurocode 2 [1] and the use of increasingly better materials make it possible to design slimmer columns than in the past, but this involves more careful analyses and, according to Section 5.8.7 of Eurocode 2 [1], \"where relevant, soil-structure interaction should be taken into account\". The importance of the interaction between the soil and the structural system of various structures has been demonstrated in many works, for example, in [2; 3]. The influence of slenderness in the calculation of reinforced concrete columns is the subject of many scientific publications [4; 5; 6; 7]. The paper from [8] analyzed the safety level of the calculation, and [9; 10] dealt with the determination of the lower limit above which the influence of slenderness is significant.  
Column deflections due to first- and second-order effects cause increments in the eccentricities of longitudinal forces and, thus, increments in the bending moments in the columns. Foundation rotations result in additional increments of the moments, which can be significant in some structures. The stiffness of pile foundations is known to increase with rotation. Therefore, the authors of this paper decided to analyze the effect of pile foundation stiffness on the increment of moments in columns of reinforced concrete single-story frames.  
The increments of moments associated with second-order effects can be calculated through the use of the simplified method or the general method. The simplified method is based on the concept of isolated elements, in which the reinforced concrete columns of single-story halls are calculated according to the current valid provisions of Eurocode 2 [1]. The design length \(l_{0}\) should be taken as for cantilevers (i.e., \(l_{0}=2l_{col}\)) because there are no provisions in [1] that allow for a different length to be taken. On the other hand, based on the presented analyses, among others, in [11], in a single-story hall building with columns restrained in the footings and pinned to the roof structure, the buckling length factor for each column is 2.0 only if the stiffness ratios of the columns \(EI\) to the longitudinal forces\(N_{Ed}\) occurring in them are the same. This condition cannot always be met in the design, so taking \(\mu=2.0\) for each column will not always be correct. The problem of calculating design lengths is primarily concerned with the simplified method. Formulas to determine the effective lengths of separated columns have been developed in papers [12; 13].  
In principle, the application of the general method does not require the design lengths to be determined, as the shape of the deformed elements and the associated increase in the moments are determined directly in the calculations. For this reason, it is recommended to use the strict method for designs, which consists of a second-order analysis that takes into account the nominal stiffnesses (the calculation methods are described in papers [11; 14; 15]).
## 3 Linear and Nonlinear Characterizations
### Linear Characterizations
Here, we reasonably assume \(\alpha_{1}\) to be 1.7 dB/cm considering it is the minimal propagation loss value we have extracted for the waveguides with different dimensions and from the ridge waveguide with a very shallow etch, i.e., \(h=230\) nm and \(w=840\) nm. Thus, with Equation (2), we can use the measured propagation losses of the SRN ridge waveguides with different dimensions to fit \(L_{c}\) and \(\sigma^{2}\). The fitted values of (5, 11.3) nm for (\(\sigma\), \(L_{c}\)) were found to be able to provide nice fittings of the calculated losses using Equation (2) to the measured propagation losses, as shown in Figure 3, and meanwhile consistent with the values (\(\sigma=5\) nm, \(L_{c}=45\) nm) reported in other literature where the sidewall roughness of a fabricated SRN waveguide was characterized [30]. Thus, it is reasonable to use Equation (2) to predict propagation losses of the SRN ridge waveguide with any \(w\) and \(h\). Figure 3: The measured and calculated propagation losses of the fabricated silicon-rich nitride ridge waveguides with different dimensions.
###### Abstract  
Solar-induced chlorophyll fluorescence (SIF) observations from space have shown close relationships with terrestrial photosynthesis rates. SIF originates from the light reactions of photosynthesis, whereas carbon fixation takes place during the dark reactions of photosynthesis. Questions remain regarding whether SIF is able to track changes in the efficiency of the dark reactions in photosynthesis. Using concurrent measurements of leaf-scale gas exchange, pulse amplitude-modulated (PAM) fluorescence, and fluorescence spectral radiances, we found that both far-red fluorescence radiances and PAM fluorescence yields responded rapidly to changes in photosynthetic carbon assimilation due to changes in environmental factors or induced stomatal closure under constant light conditions. Uncertainties in outgoing and incoming irradiance mismatch for SIF measurements may very likely obscure the contributions of the dark reactions, thereby causing the inconsistent findings previously reported, which were no change in far-red SIF and PAM fluorescence yields after clear reductions in the photosynthetic carbon assimilation efficiency of dark reactions. Our results confirm that high-quality SIF measurements have the potential to provide insights into the dark reactions of photosynthesis. This study is particularly relevant for better interpreting satellite SIF observations that are obtained under roughly constant overpass times and relatively stable light intensities.  
solar-induced chlorophyll fluorescence; gross primary productivity; far-red chlorophyll fluorescence; dark reactions; CO\({}_{2}\) concentration; air temperature; stomatal closure +
Footnote †: journal: Applied Sciences
# A Review of Methods and Applications for a Heart Rate Variability Analysis
## 5 Dimensionality Reduction Techniques
### Independent Component Analysis (ICA)  
An Independent Component Analysis (ICA) is an analysis system used in ML to separate independent sources from the input mixed signal, which is also known as blind source separation (BSS) or the blind signal parting problem [74; 75]. The test signal is transformed linearly into components that are independent of each other. In ICA, the hidden factors are analyzed, viz., sets of random variables. ICA is more similar to PCA. ICA is proficient in discovering the causal influences or foundations. Before the implementation of the ICA technique on the data, a few preprocessing steps, like whitening, centering, and filtering, are usually performed on the data to improve the value of the signal and eliminate the noise.
# Development of Track Support Stiffness Measurement and Evaluation System for Slab Tracks
## 4 Conclusions  
In this study, we developed a track support stiffness measurement system and software that can control the test equipment and save, analyze, and evaluate the measurement results. We also evaluated the performance of the developed system and adequacy in terms of field applicability. The results are as follows.  
1. The field test results proved the adequacy of static and dynamic spring stiffness evaluation results, and the adequacy of the test equipment (load control capacity, dynamic vibration capacity, and loading rate), which are the performance requirements of the development system, and are also related to the relevant test standards and evaluation method. Among the main performance requirements set in this study, the adequacy of the TSS tester (load control capability, dynamic vibration capability, and loading rate) is the realization of the excitation frequency of the static and dynamic excitation loads with the control accuracy of the static and dynamic test loads.
2. The evaluation system in this study reflects the field conditions and can be directly tested on operational tracks to analyze and compare the results at various test points. In addition, the error range of the field test results was analyzed to be less than 3% in both the static and dynamic test results, indicating a reliable level in terms of measurement accuracy. Furthermore, the error of the dynamic test result of the track support stiffness measured by the design standard value and test equipment was less than 5%. Therefore, it was concluded that the track support stiffness measurement system and its evaluation program of this study can be used to predict the spring stiffness of resilience pad in the real field and should be of practical use in track maintenance.
3. In continuation of this research, the authors intend to perform further experiments under different field conditions.  
Conceptualization, J.-Y.C. and J.-S.C.; investigation, J.-Y.C.; data curation, J.-S.C. and J.-Y.C.; resources, M.-H.K.; writing--original draft preparation, J.-Y.C. and S.-H.K.; writing--review and editing, S.-H.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
This Work was supported by the Technology Development Program (S2463949) funded by the Ministry of SMEs and Startups (MSS, Korea).  
The authors declare no conflict of interest.
# Analysis of _In Vivo_ Plant Volatiles Using Active Sampling and TD-GC\(\times\)GC-TOFMS
###### Abstract  
Plants constantly produce primary and secondary metabolites, and a significant fraction of these are volatile organic compounds (VOCs). Factors including the life stage of the plant, temperature, environment, and stress influence the abundance and types of VOCs emitted. The analysis of VOCs released by plants during different stages or with different conditions provides insight into plant metabolism and stress responses. Collecting the VOC profiles of plants _in vivo_ makes it possible to obtain a representative sample of the entire plant volatilome under controlled conditions with minimal invasiveness. In addition, _in vivo_ sampling can also be used to compare the impacts of different environmental conditions or stressors on plants, i.e., the presence/absence of a pest or amount of nitrogen in soil. **Methods:** In this study, an _in vivo_ plant sampling technique is introduced and validated using active sampling and thermal desorption (TD) tubes with comprehensive two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer (TD-GC\(\times\)GC-TOFMS). The purpose of this work is to highlight a novel technique to analyze headspace secondary plant metabolites with a minimal invasiveness. **Results:** It was concluded that _in vivo_ active sampling onto TD tubes provides a wider global coverage of compounds and larger peak areas when compared to extraction by solid-phase microextraction (SPME). Additionally, the Horwitz ratio of active sampling onto TD tubes was 0.893, demonstrating this technique to be a reliable and reproducible method. Lastly, a variety of plants were sampled to assess the versatility of this technique across various plant species with different sizes and volatile profiles. Hundreds of compounds were measured with this analysis, including terpen, aldehydes, ketones, terpenoids, and alcohols. **Conclusions:** This novel _in vivo_ active sampling method provides an additional technique for extracting and analyzing volatile secondary plant metabolites.  
_in vivo_ active sampling; comprehensive two-dimensional gas chromatography; plant volatiles; thermal desorption (TD); volatile organic compounds (VOCs)
# Ex-Situ Evaluation of Commercial Polymer Membranes for Vanadium Redox Flow Batteries (VRFBs)
## 2 Materials and Methods  
### Materials  
Eight (8) of the current state-of-the-art commercially available polymer membranes for VRFB application were selected for ex-situ evaluation, including three (3) PFSA dense membranes, one (1) reinforced PFSA membrane and four (4) hydrocarbon membranes. All the membranes were used directly without further treatment. The investigated membranes, including their trade name, manufacture (supplier), types, thickness and IEC, are listed in Table 1. More detailed information is provided in Table S1. The benchmark PFSA membrane, Nafion 212, is used as a baseline in this report.