esa-sceva/satcom-chunk-collection huggingface dataset:
# Effects of Grout Compactness on the Tensile Behavior of Ground Splice Sleeve Connectors
## 2 Tensile Tests on GSS Connectors with Different Compactness  
In the experiments, four types of GSS with 100%, 90%, 70%, and 50% grout compactness, were subjected to monotonic tensile loads to study their failure modes, tensile capacity, stress, and strain distribution along the rebar and the sleeve. It is recognized that with the material and grout quality guaranteed, the angle between the two opposite reinforcement ribs and their misalignment are the reasons for sleeve connection failure. As for the sleeve studied in this paper, one end is equipped with ribs in the inner wall to hook the reinforcement, and the other end with an annular rubber plug to fix another reinforcement for positioning and alignment.
## 2 Experimental Section  
### 3D Photogrammetry  
The 3D model of the apsidal conch of St. Panfilo church was obtained by applying a photogrammetric approach that required the preliminary acquisition of the necessary frames, totaling 156. To do this, a Nikon D5300 digital SLR camera (Tokyo, Japan), equipped with a 17/35 mm multifocal lens, was used. To obtain the photos, the camera was mounted on a tripod and the exposure parameters were set from time to time to ensure the correct exposure with every shot. For each frame acquisition, two white LED lamps (E27 85W CFL bulb lamps, 5500 K daylight colour) were positioned on both sides of the camera, at about 45\({}^{\circ}\) to the subject.  
After the acquisition phase, performed on-site in the church, the 156 photographs were processed by the software Agisoft Metashape(r) (Saint Petersburg, Russia) that can photogrammetrically process digital images, aerial and close-range photographs to obtain 3D models with the advantage of generating photorealistic surfaces.  
The used software is based on the Structure from Motion (SfM) approach that, thanks to the high degree of overlapping of the acquired photos, can cover the complete geometry of the object to be rendered. This characteristic of the approach gives it the name SfM, i.e., \"structure derived from a motion sensor\" [27].  
The working flow, widely explained elsewhere [28], enables generation of a dense points cloud that is used to generate a polygonal model (mesh), which can be texturized to return a photorealistic 3D digital model.  
For the 3D model sizing of the presbytery of San Panfilo church, 10 targets were positioned on the walls, whose coordinates (x, y, z; relative to a local geographical reference system) were measured with a Total Station model Topcon GPT 7005 with angular accuracy 5\". This system guarantees a sizing of the model achieving sub-centimeter precision. The captured frames were saved in.jpg format with 24 MP resolution, 24-bit sRGB depth; each frame size was about 6 MB. The images were processed on a workstation with the following specifications: Intel(R) Core processor (TM) i7-4770 CPU @ 3.40 GHz; Ram 32 GB; 64-bit system, Windows 10(r); GeForce GTX 970 4 Gb video card.2.2., equipped with constructing bits RGB.
## 5 Discussion
### Study Limitations  
Practical difficulties linked to online-based experiments may reduce the significance of the observed effects and limit their comparison with similar lab-based studies. The inherent lack of control on the participants' experimental conditions, such as the use of diverse headphones models and different environmental noise levels, may have increased the variability of the reported distances.  
In this study, the influence of divergent environmental characteristics on auditory distance perception was examined. Participants were asked to assess the perceived distance of auditory stimuli, but no reporting about externalization was proposed. Externalization and auditory distance perception are two related concepts; however, they primarily depend on distinct cues [18]. The presence of binaural cues in the sound signal is mandatory for externalization, which can be considered a prerequisite for an accurate distance perception for some listeners [10]. In this respect, the perception of externalization is regarded as dichotomous, whereas distance perception is continuous and mainly driven by monaural cues [3,18]. Therefore, precautions were taken to favor the externalization, such as preserving binaural cues in the auditory stimuli. Generic HRTFs were applied to generate the binaural stimuli, which is known to increase the risk of in-head localization, especially for frontal sources [42]. However, aside from practical constraints linked to the online-based experiment, this decision was motivated by previous findings showing that nonindividual HRTFs had no impact on the auditory distance perception of frontal sound sources [36].
## 1 Introduction
Additionally, products such as the \"Hydro Estimator\" (HE; [17]) or the \"Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Network\" (PERSIANN; [18]), which are IR sensor-based products, can be associated with PMW/AMW sensor-based retrievals [1], such as the \"Climate Prediction Center MORPHing\" technique (CMORPH; [19]), the \"Global Satellite Mapping of Precipitation\" (GSMaP; [20]), or products provided by NASA under the Global Precipitation Measurement (GPM) programme, such as the \"Integrated Multi-SatellitE Retrievals for GPM\" (IMERG; [21]). More recently, an innovative technique has been developed to estimate precipitation using the quality and attenuation of signals' broadband communication satellites [22; 23]. According to the satellites, and the sensors and assumptions used to develop the different rain products, performances in the precipitation estimates at global and/or at finer scales can be impacted. The objective of this study is to evaluate the rain estimations of nine satellite products during two rainy events, with contrasted intensities, which occurred over France in 2022. For both cases, a comparative approach with rain gauges and ground-based radar measurements for cumulative rain amounts was used to evaluate each satellite product. This paper is organised as follows: after a description of the data, the methodology as well as the case studies are described in Sections 2 and 3 presents the results of the comparative analyses for rain amounts. Section 4 provides a discussion of the strengths and weakness of the products evaluated in this study, while Section 5 concludes and gives some perspectives.
## 3 Optimization and Performance Evaluation
In other words, the computation volume of the optimized method is only about twice that of the conventional method, and the computing time is still at the same order of magnitude. By increasing a small number of calculations, the optimization gains a reliable communication ability under the condition of high moving speed and acceleration.
## 3 Results
### Identification of Key Aromatic Compounds in the Pulps of Five Mango Cultivars
There were 19 kinds of aromatic components in QM, and the substances with an aromatic intensity greater than 2 were 1-hexanol (2.12), methyl-3-methylcyclohex-3-en-1-one (2.67), \(\beta\)-phellandrene (2.1), and decanal (3) showing an overall aromatic profile of lemon, sweet, and green grass. Seventeen aromatic components were identified in GF, and the substances with aroma intensities greater than 2 were 1-hexanol (2.13), phellandrene (2.5), terpionlene (2.33), and p-menthol (2.25) showing an overall aroma profile of citrus and lemon, fresh green leaves, and green grass. There were 22 aromatic components in HY, and the substances with aromatic intensity greater than 2 were phellandrene (3), colimene (2.5), \(\alpha\)-pinene (2.2), \(\gamma\)-terpinene (2.5), terpionlene (2.2), and 1,3,8-\(p\)-menthatriene (2.2) showing an overall aroma profile of flower, citrus, green grass, and pine wood. TN had 22 aromatic components, including hexanal (2.2), 2-carene (2.2), phellandrene (3.53), \(p\)-cymene (8.7), \(\gamma\)-terpinene (2.5), terpionlene (2.8),and decanal (3) with aromatic intensity values greater than 2. This has an overall aroma profile of sweet, fruit, green grass, and pine wood. There were no significant differences in the numbers of overall aromatic substances identified using the two methods (FD and OSME). The number of substances with an FD \(\geq\)6 identified in TN by the FD method was the highest, followed by QM, JM, HY, and GF. The highest number of aromatic components with intensity values \(>\)2 was also found in TN, followed by HY and JM. QM and GF had the same number of aromatic substances. Therefore, the identification results obtained using FD and OSME were similar. These were highly consistent in identifying key aromatic substances. 2-Cyclohepten-1-one, ethyl cyclopropanecarboxylate, 1,3,8-\(p\)-menthatriene, and citral were identified for the first time and regarded as a characteristic aroma substance in mangoes, regardless of analytical method used (FD or OSME), although 1,3,8-\(p\)-menthatriene and citral were previously detected in lychee fruits [16]. In contrast to previous findings of aromatic substances in mangoes, some potent odorants, such as linalool and isoamyl acetate, were not detected, which might be due to differences in varieties, storage conditions, and extraction techniques. According to sensory analysis, the main aromatic profiles (fruit, sweet, flower, and rosin aromas) of pulp from the five mango cultivars were similar to those identified using the FD and intensity methods, indicating that the intensity method combined with the FD method can accurately illustrate the characteristic aromatic components with high or low intensity.
# A Flexible FPGA-Based Channel Emulator for Non-Stationary MIMO Fading Channels
## 4 Resource Consumption and Measurements
### Measured Results and Analysis
Figure 10b gives the measured PDFs at three different time instants \(t=0\) s, \(4\) s, and \(8\) s. For comparison purpose, the corresponding theoretical results are also extracted from Figure 10a and showed in Figure 10b, which also fit well with the measured ones. In addition, we configure the channel parameters by referring to [31] as follow. The height of BS is 30 m, and the initial distance between the MS and BS is 90 m. The MS is moving towards the BS at a speed of 10 m per second. By using the similar method as above, we can obtain the measured PDF as shown in Figure 10c. It is shown that the measured PDF of proposed channel emulator is close to the result of field test in [31]. Based on the theoretical expressions of (28)-(30) in [32] and (9)-(10) in [33], the absolute values of time-variant CCF of firt two paths are calculated and given in Figure 11. In the figure, we assume that the antenna spaces of the BS and MS are the same, and equal to twice the wavelength of carrier. Then, the measured CCF of proposed emulator can be obtained in a similar way as mentioned above and given in Figure 11 for comparison purpose. As can be seen from the figure, the CCF changes over time due to the movement of the MS. Again, the measured CCF aligns well with the theoretical one, proving the correctness of output correlation properties. Figure 10: (**a**) The theoretical results of time-variant PDFs, (**b**) the measured time-variant PDFs of proposed emulator at different time instants, and (**c**) the measured PDF of proposed emulator and the PDF of field test.
# Iterative QR-Based SFSIC Detection and Decoder Algorithm for a Reed-Muller Space-Time Turbo System
## 3 The Novel Iterative QR-Based SFSIC Detection and Decoder Algorithm  
The proposed scheme, named the iterative QR-based soft feedback segment interference cancellation detection and decoder algorithm, is depicted on the right-hand side of the Figure 1. It is composed of an iterative QRSFSIC detector (inner decoder) and an iterative trellis-based MAP RM turbo decoder (outer decoder), which mitigates the multi-stream interference with inner iterations executed by the inner decoder and fulfills error correcting through outer iterations by the outer decoder to obtain the desired information bit by exchanging information between inner and outer decoders. The operation of iterative detection and the decoder algorithm is to maximize a posterior LLR, which is made up of a priori or old information and new information, or more technically, extrinsic information, acquired during this iterative detection and decoding procedure, the latter of which is only information exchanged in processing cycles.
## 4 Case Study and Proof of Concept  
Two distribution test systems are considered for the evaluation of ECD, EMD, and ECED with and without incorporating DSM strategy. Fossil-fuel generators consider the valve point loading effect, resulting in cost and emission fitness functions that are both nonconvex and nonlinear. The whole of the work conducted in this study is divided into three distinct parts. The first step involves incorporating demand side management (DSM) into the projected load demand model, taking into account the willingness of 40% of consumers to engage in the DSM approach. ECD and EMD are evaluated in the second stage regarding both load demand models, both with and without the DSM strategy being implemented. ECED is evaluated in the third stage to obtain a balanced trade-off result among minimum generation cost and pollutants emitted. An algorithm that was developed recently (AOA) and its variations serve as the optimization tool for this research. The following section provides a detailed discussion of the findings achieved, which are directly related to the issues outlined in Section 2.
# On the Spectral Efficiency for Distributed Massive MIMO Systems
## 3 Power Unbalance on Sub-6 Ghz D-MIMO Systems  
This section presents the effect of the power unbalance for a D-MIMO system composed by multiple MIMO subsystems acquired in a reverberation chamber. The first part of the section briefly describes the acquisition process of the propagation channels. The second part shows and details the results of this power unbalance. From an analytical perspective, the relevance of this section lies in understanding how the spectral efficiency can be maximized while the power allocation is minimized at the same time.
# MANET Routing Protocols' Performance Assessment Under Dynamic Network Conditions
## 5 Results and Comparative Analysis
### Scenarios with Homogeneous Nodes
#### 5.1.5 Energy Consumption
\begin{table}
\begin{tabular}{c c c c} \hline
**Network Size** & **Proactive Protocols (OLSR,** & **Reactive Protocols (ADDV,** & **Hybrid Protocols (ZRP, GRP)** \\
**(Nodes)** & **DSDV)** & **DSR, AOMDV, TORA)** & **Hybrid Protocols (ZRP, GRP)** \\ \hline
20 Nodes & Moderate energy consumption, efficient for smaller networks & Varying energy consumption, generally higher than proactive protocols & Moderate energy consumption, balanced performance Balanced increase, effective management of increased energy consumption \\
80 Nodes & Noticeable increase, consistent performance & Significant increase due to route discovery overhead & Balanced increase, effective management of increased energy consumption \\
200 Nodes & Sharp rise, high energy consumption & Peak energy consumption, highlighting scalability challenges & Peak energy consumption, balanced performance, effective integration of strategies \\
500 Nodes & Decrease or stabilizes, less optimal due to maintenance overhead & Stabilizes, indicating return to efficiency & Stabilizes, maintains efficient performance, most suitable for high-density networks \\ \hline \end{tabular}
\end{table} 
Table 9: Protocol Suitability for Different Scenarios Considering Energy Consumption. less appropriate for situations with limited energy resources because, although they offer low-latency routing under stable circumstances, their operational requirements might result in quick energy loss.
## 6 Experimental Results
### Crowdsourcing the FLP in Video Game Plays
The interaction between humans and computers in carrying out crowdsourcing activities can complement the Pareto search space, as the solutions obtained by the crowdsourcing approach can be superior to those generated by genetic algorithms in many cases, as shown in Figure 7. To further enhance the quality of solutions, a hybrid combination of crowdsourcing and genetic algorithms could be explored, leveraging the strengths of both approaches. Our empirical study indicates that crowdsourcing can offer a sufficient number of solutions to fill the gaps presented by genetic algorithms. Additionally, the use of machine learning techniques could provide insights into the heuristics employed by users to solve computationally challenging problems. As a proposed future direction, we suggest that combining the best solutions from crowdsourcing with those generated by genetic algorithms could reduce the convergence time or improve the quality of the solutions. However, we must acknowledge that reducing the convergence time of genetic algorithms lies beyond the scope of this work. The crowdsourcing-based approach has a drawback in that not all user responses carry significant value. Moreover, some players may not comprehend the video game instantly, especially those without engineering or mathematical backgrounds, resulting in suboptimal solutions for multi-objective optimization problems (MOPs). The research was conducted in a university setting with a diverse audience, thereby leading to a lack of expertise in MOPs. However, despite these limitations, we observed a statistically significant enhancement in the solutions, even though not all players contributed with high-quality answers.
## 3 Materials and Methods
### Segmentation Approach
#### 3.2.3 Assessment Metric  
The metrics used to access the performance of the segmentation models are: global accuracy, mean accuracy, mean IoU, weighted IoU, and mean BF score.  
* **Global accuracy** is a more general metric that gives insight into the percentage of correctly classified pixels without considering the classes. This metric is completely misleading in the case of highly unbalanced datasets.
* **Mean accuracy** gives an idea about the portion of correctly classified pixels considering all the classes. Mathematically defined as: \[Accuracy=\frac{\mathit{TPs}}{\mathit{TPs}+\mathit{FNs}}\] (5) where \(\mathit{TPs}\) is the number of true positives, the number of positive pixels correctly classified.
* **Mean IoU** or Jaccard similarity measure, computed as the average _IoU_ measure of all data classes calculated for all the images and averaged. In other words, it is a statistical measure of precision that penalizes _FPs. IoU_ (or Jaccard) metric is mathematically defined as:\[IoU=\frac{TPs}{TPs+FPs+FNs} \tag{6}\]
* **Weighted IoU** is a measure that considers the minority classes in unbalanced datasets. Hence, the overall score is more realistic. This metric is defined as the mean _IoU_ of each class in the data, weighted by the number of pixels in that class.
* **Mean BF Score**, the boundary F1 contour matching score, mathematically defined by the following formula: \[BF=\frac{TPs}{TPs+0.5*(FPs+FNs)}\] (7)  
The mean \(BF\) score is pointed as the mean value of the \(BF\) score calculated overall images for a corresponding class. This metric measures the degree of matching of the object contours (prediction) and the given ground truth.
# A Wideband Eight-Port MIMO Antenna with Reduced Mutual Coupling for Future 5G mm-Wave Applications
## 2 Antenna Design
### Single-Port Rectangular-Shaped MIMO Antenna  
Equation (1) is used to achieve the required geometry parameters of a rectangular-shaped antenna [38].  
\[W=\frac{c}{2f\sqrt{\frac{(\varepsilon_{r}+1)}{2}}} \tag{1}\]  
Here, \(\varepsilon_{r}\) is the dielectric constant, c is the speed of light and \(f\) is the resonant frequency. The design development of the antenna is given in Figure 1. The size of the single-port antenna is 17.5 \(\times\) 22 \(\times\) 0.8 mm\({}^{3}\).  
Figure 1: Design development of the single-port antenna. (**a**) Rectangular antenna, (**b**) rectangular slot antenna, (**c**) rectangular chamfered edge antenna, and (**d**) proposed single-port antenna.  
In the first step, a simple rectangular antenna of size 17.5 \(\times\) 22 \(\times\) 0.8 mm\({}^{3}\) is simulated, and the results are given in Figure 2. To achieve the desired S-parameter, a square-shaped slot with size S1 = 9 mm and S2 = 12 mm was etched in the radiator to enhance the bandwidth. The lower edges (C1 and C2) of the radiator were chamfered by 4.5 mm, and a rectangular-shaped stub of size S = 7 mm and T = 6 mm was added to secure a 28-46 GHz bandwidth. The \(\mid\)S\({}_{11}\)\(\mid\) results for the design development stages are presented in Figure 2, and it is clear that the antenna used in step (d) achieves a vast bandwidth of 18 GHz, varying from 28 to 46 GHz for the proposed single-element design.
## 10 Emerging Topics and New Trends
### Personal Sound Zones  
In the last years, there is an increasing interest in the possibility of reproducing different content in adjacent spatially restricted zones for multiple listeners by reducing the interference between the zones. These approaches are known as personal sound zones [245], multi-zone synthesis, or multi-zone sound control. A recent review on this topic can be found in [246], and more details in the numerous published papers on the subject [247; 248; 249]. At the current state, the achievable suppression between the zones is limited by various acoustical and practical restrictions, resulting in a limited applicability to real-world scenarios. In [262], an overview is presented on the major challenges that have to be dealt with for multi-zone sound control in a reverberant environment. Interference mitigation and room compensation robust to changes and uncertainties in the acoustic environment remain as challenging problems. An approach to room equalization for sound pressure control over a region of space combined with a wave domain sound field representation is presented in [262]. The approach is reported to be robust at low frequencies, but ineffective at high frequencies where the reverberant sound field is diffuse, calling for a very high number of loudspeakers.
# ECG Arrhythmia Classification using High Order Spectrum and 2D Graph Fourier Transform
## 2 Methods
### Pre-processing  
The first step of our algorithm consisted of data pre-processing.  
ECG signal can be contaminated by several artifacts, such as baseline wander, electromyographic artifacts and power frequency interferences [27; 28]. These noises will affect the detection of real components and the classification of signal features. It is essential to figure out the suitable method for preprocessing while retaining the remarkable characteristics.  
In the preprocessing stage, we used four steps to reduce noise. First, the DC component is eliminated by subtracting the average value. Then, the baseline drift is reduced with a median filter. The low-pass filter is used to remove power frequency interference and electromyogram (EMG) noise. Finally, the high-pass filter can eliminate some other low-frequency noise. After denoising, the R peak points are subsequently detected. The single heartbeat data are configured by segmenting the signal to be centered on the R peak point.