esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Descriptions of the Ferrous Objects  
The winch (Figure 1a and Supplementary Material Figure S1a) is a mechanical winding device that allows adjusting the tension of, or extending or retracting, a rope, wire, or cable [5; 6]. The total weight of this winch was 11.5 kg. Its drum was 149 mm long, with a maximum diameter of 146 mm and an average diameter of 112 mm. The shaft was 296 mm long and 20 to 24 mm thick.  
Heart-shaped shackle (Figure 1b and Supplementary Material Figure S2a) is a primary connecting link in the rigging system, with a bolt and pin made of iron, allowing fast connection and disconnection of rigging elements, such as chain cables [7; 8]. The heart shape of the shackle enables the connection of lines, chains, or ropes at different angles. This shackle weighed 3.2 kg. Its link was 281 mm long, with an average thickness of 18 mm. It was 153 mm long by 55-63 mm wide and had an average thickness of 19 mm. The bolt diameter was 27.5 mm.  
Deadeye strap with futtock plate (Figure 1c and Supplementary Material Figure S2b). Deadeyes were part of the standing rigging system of a sailing ship. A typical deadeye was made of a circular hardwood block with groves for ropes. They were used in pairs to set the tension of stays (ropes, wires, or shafts located on the bow and stern of the vessel) and shrouds (sets of ropes providing lateral support to the ship's masts). They secured the lower end of the shroud to a metal chain plate fastened to the ship's hull. The main metal parts of such deadeyes included a strap wrapped around the wooden block, a loop forge-welded around a bolt, a securing element below the loop, a futtock plate, and a shackle that connected the futtock plate to an iron chain with a bolt [8; 9; 10; 11]. The strap weighed 1.7 kg. Its internal diameter was 139 mm and its external diameter was 164 mm. The strap itself was 51 mm wide and 12 mm thick. The futtock plate was 381 mm long, 65 mm wide, and 9.5 mm thick. The bolt diameter was 29 mm.  
Stud-link chain controller (Figure 1d and Supplementary Material Figure S1b) was possibly used to support the anchor stud-link chain [12]. This item weighed 12 kg and was 405 mm long, 81 mm wide, and 135 mm high; the arc thickness varied between 40 and 70 mm. The circular hole, which was apparently for the handle (e.g., [13]) had an in  
Figure 1: Iron objects retrieved from the Akko Tower shipwck: (**a**) winch drum with a shaft; (**b**) heart-shaped shackle; (**c**) deadeye strap with a futtock plate; and (**d,e**) stud-link chain controller ([PERSON] and [PERSON]).  
ternal diameter of 42 mm and an external diameter of 33 mm. The chain passageway was 35 mm wide.
# Systematic Analysis of the Hydrogen Value Chain from Production to Utilization
## 2 Hydrogen Production Technologies
### Thermochemical Processes
#### 2.1.2 Partial Oxidation  
Partial oxidation is a thermochemical process, similar to SRM. The main difference between the two processes lies in the way the syngas is produced. In partial oxidation, the natural gas reacts with limited amounts of oxygen, typically from air, in a high-pressure refractory-lined reactor, producing the desired syngas [31]. After the production of the syngas, the process follows the same steps as described for SRM, as represented in Figure 4.  
Unlike SMR, partial oxidation is an exothermic process. It is faster than SMR, requires a smaller reactor vessel, and could use feedstock different from natural gas, such as heavy fuel oil [31]. However, this process produces less hydrogen per unit of input fuel than SMR and has a higher hydrogen production cost.
## 2 Results and Discussion
### Effect of Acid Concentration on Enzyme Activity  
As demonstrated for Novozym 435, it is possible to use a higher acid concentration under ultrasonic energy when compared to mechanical stirring [19]. This fact might be explained by the better mixing of the acetic acid in the organic solvent caused by ultrasounds, which prevents the acid from becoming accumulated in the microenvironment of the enzyme, perhaps also avoiding the formation of a water phase in this microenvironment that could inactivate the enzyme [8].  
The time course of ultrasound-assisted esterifications with 0.3 M and 2.0 M acid concentrations are presented in Figure 4. Using 0.3 M, conversion reached to 97% after 1.5 h, whereas the conversion was 90% after 2.5 h when 2.0 M acetic acid was used. In terms of productivity, the ultrasound-assisted butyl acetate synthesis catalyzed by MCI-CALB using 2.0 M of acetic acid represents approximately 840 mmol\(\cdot\)L\({}^{-1}\)h\({}^{-1}\), which is six times higher than the productivity in the same reaction, but with mechanical stirring, (140 mmol\(\cdot\)L\({}^{-1}\)h\({}^{-1}\)) [20]. Additionally considering the 1.5-fold enhancement in the operational stability caused by the ultrasound technology, the final improvement in the overall process productivity is almost 10 times higher.  
Figure 3: Operational stability of CALB during repeated batches on butyl acetate synthesis. (\(\blacksquare\)) MCI-CALB under optimal condition I; (\(\Circinus\))MCI-CALB under optimal Condition II; (\(\Diamond\)) MCI-CALB under mechanical stirring conditions; (\(\blacktriangle\)) Novozym 435 under ultrasound conditions; (\(\times\)) Novozym 435 under mechanical stirring conditions.
## 3 Networks and Protocols of Communication
### Cellular Technologies  
#### 3.2.1 Long Term Evolution  
Long Term Evolution (LTE) is a mobile communication architecture that has previously been designed for wireless device communication and operation on licensed bands. It has high spectral proficiency, excellent data rates, low latency in the exchange of messages, and flexibility in the use of the frequency band. It is a pattern that has been designed by the 3 rd Generation Partnership Project (3 Gpp). The physical layer of an LTE system has downlink and uplink capabilities and requires high peak transmission rates. The access method that LTE uses is based on Orthogonal Frequency Division Multiple Access (OFDMA) with a mixture of higher bandwidth modulation [30]. Due to its wide coverage, application support, and quality assurance of Service (Quality of Services--QoS), LTE networks are considered a choice suitable for M2M applications that use wireless communication. LTE networks are the most suitable cellular network that can be used for wireless applications due to longevity, low latency and spectral efficiency [31].  
The LTE system is based on multi-carrier modulations--FDMA single carrier for uplink and OFDMA for downlink--which provides robustness, flexibility, and adaptability management of radio resources. For this reason, it is more suitable to withstand high data rates than conventional single-carrier solutions or CDMA solutions. In addition, multiple access management is more efficient than IEEE 802.11a CSMA/CA and b, and allows us to easily differentiate the quality of radio service into various terminals for data exchange [32].
# Versatile High-Throughput Platform for Focused Ultrasound In Vitro Application
## 3 Results
### Influence of the Well Plate  
A significant issue that was investigated in this study was the impact of the well plate on the sound pressure. In our experiments, a standard well plate with a membrane bottom of a minimal thickness (190 \(\upmu\)m) was used (Greiner Bio-One, Kremsmunster, Austria, type \(\upmu\)Clear(r), item no. 65090).  
Sound pressure measurements were conducted with the hydrophone in 32 wells and compared with the free-field measurements at precisely the same locations. The investigations were conducted with the high-intensity focused ultrasound (HIFU) platform, operating at a center frequency of 1 MHz, due to its minimal dependence on filling volume resulting from its pronounced focusing at approximately 2 mm (for further details see Section 3.3.2).  
In the free-field measurements carried out without the presence of a well plate, the maximum sound pressure was observed to be 255 kPa on average when driven with a voltage of V\({}_{\text{peak}}\) = 20 V. At the same excitation voltage, a sound pressure of approximately 200-240 kPa (standard deviation of 40-54 kPa) was measured in the wells (dependent on  
Figure 11: Single element output in terms of maximum pressure and I\({}_{\text{SPPA}}\) as a function of the driving voltage (mean and standard deviation values for the 8 elements in row 8) in the HIFU platform. Volume in well 250 \(\upmu\)L.  
Figure 10: (a) dB scaled pressure distribution measured by a 2D scan of a calibrated hydrophone; The cross signs in the figure show the position of the individual wells. (b) Corresponding statistical analysis of applicator homogeneity.  
the filling volume, between 200 \(\upmu\)L and 350 \(\upmu\)L). The results indicated that the impact of the well plate, contingent upon the filling volume, ranged between \(-\)2.2 and \(-\)0.6 dB of attenuation, representing a minimal influence.
## 5 Relations between Impact Resistance and Tensile Properties
### Relation between Blow Number \(N_{\rm c}\) and Stress \(\sigma_{\rm c}\)  
Table 7 lists the major test results of the tensile properties and impact resistance. The tensile properties, \(\sigma_{\rm c}\) and \(\varepsilon_{\rm f}\), and the impact resistance, blow numbers and crater diameter, are tabulated. At the first crack moment, \(\sigma_{\rm c}\) of the slab specimen increased from 1.78 MPa to 2.64 MPa, 3.04 MPa and 3.67 MPa when more PVA fibers were added. Meanwhile, the blow number \(\rm N_{\rm c}\) of the disc specimen increased from 11 to 88, 805, and up to 1662. The relation between \(\rm N_{\rm c}\) of the disc specimen and \(\sigma_{\rm c}\) of the slab specimen is shown in Figure 13. Although the dataset is relatively small, the general change trend can be observed that the \(\rm N_{\rm c}\) increased obviously with an increase of \(\sigma_{\rm c}\). The \(\rm N_{\rm c}\) of disc specimen depends largely on the \(\sigma_{\rm c}\) of slab specimen. This phenomenon indicates that much more blows are needed to cause the appearing of first visible crack when the \(\sigma_{\rm c}\) of PVA-FRCM is larger.
## 2 Problem Formulation  
In wireless communication systems, the efficient transmission of high-quality images is one of the key applications. By utilizing subcarriers, OFDM is adopted to optimize the bandwidth and increase the data transmission rates. However, as the modulation order increases, it becomes more susceptible to inter-symbol interference and channel distortion, which can result in high error rates under challenging channel conditions. The proposed CDM is applied to reduce the error rate at high modulation orders, and its block diagram for OFDM-based image reconstruction is presented in Figure 1. Through the application of the proposed CDM, the distortion in the received image can be mitigated, producing high-quality image samples. This section provides an overview of the OFDM system and discusses the diffusion model.  
Figure 1: Scheme for OFDM-based image reconstruction in wireless communication utilizing the CDM.
# Integrating Environmental Data for Mental Health Monitoring: A Data-Driven IoT-Based Approach
## 5 Discussion
### Impact of Environmental Factors  
The analysis revealed a strong correlation between environmental factors--temperature, humidity--and stress levels. These findings align with existing research, confirming that elevated temperatures and humidity levels are associated with higher stress. The thresholds identified for temperature and humidity provide actionable insights for designing interventions, particularly in enclosed environments such as offices and homes. These results underscore the importance of addressing environmental conditions as a critical factor in emotional well-being.
# High-Precision Ranging Method of 5G NR Co-Band PRS in Industrial Internet Scenarios
## 2 System Model
### 5G NR Co-Band PRS Signal Model  
According to 3 GPP TS 38.211 V17.0.0, the reference signal sequence \(r(m)\) is defined by  
\[r(m)=\frac{1}{\sqrt{2}}(1-2c(2m))+j\frac{1}{\sqrt{2}}(1-2c(2m+1)) \tag{1}\]  
The PRS initialization sequence is defined as  
\[c_{init}=\left(2^{22}\left[\frac{n_{ID,seq}^{PRS}}{1024}\right]+2^{10}\left(N_ {symb}^{slot}n_{s,f}^{u}+l+1\right)\cdot\left(2\left(n_{ID,seq}^{PRS}\bmod 1024 \right)+1\right)+\left(n_{ID,seq}^{PRS}\bmod 1024\right)\right)\bmod 2^{31} \tag{2}\]  
where \(n_{s,f}^{u}\) is the slot time, determined by the higher-layer parameter DL-PRS-Subcarrier. The downlink PRS sequence ID \(n_{ID,seq}^{PRS}\in\{0,1,\ldots,4095\}\) is given by the higher-layer parameter dl-PRS-SequenceID and \(l\) is the OFDM symbol within the slot to which the sequence is mapped. For each downlink PRS resource configured, the UE shall assume the  
Figure 1: 5G NR Co-Band communication and positioning fusion system.  
sequence \(r(m)\) is scaled with a factor \(\beta_{PRS}\) and mapped to resource elements \((k,l)_{p,\mu}\). We define the mapping function as MAP\(\{.\}\), and then we obtain  
\[\begin{split} p_{k,l}^{(p,\mu)}&=\text{MAP}\{\beta_{ PRS}r(m)\}\\ m&=0,1,\ldots\\ k&=mK_{comb}^{PRS}+\left(\left(k_{offset}^{PRS}+k^{ \prime}\right)\text{ mod }K_{comb}^{PRS}\right)\\ l&=l_{start}^{PRS},l_{start}^{PRS}+1,\ldots,l_{start}^{ PRS}+L_{PRS}-1\end{split} \tag{3}\]  
where \(k\) denotes the frequency domain mapping number of the resource grid and \(l\) denotes the time domain mapping number of the resource grid. In order to prevent interference of the positioning signal to the communication signal, \(\beta_{PRS}\) should be significantly less than 1.  
The communication data are spread over the whole \((k,l)_{p,\mu}\) resource block, which is configured according to the UE's needs and can be expressed as  
\[d_{k,l}^{(p,\mu)}=data(m). \tag{4}\]  
The PRS sequence \(r(m)\) and the communication data sequence \(data(m)\) are mapped and superimposed to generate \(\{X_{i,n}|n=0,...,N-1\}\), where \(N\) represents the number of fast Fourier transform points and \(i\) represents the number of OFDM symbols in the time domain. It should be noted that the number of subcarriers used is \(N_{\text{SC}}<N\), and \(N\) is a power of 2. The superimposed signal can be expressed as  
\[X_{i,n}=p_{k,l}^{(p,\mu)}+d_{k,l}^{(p,\mu)}. \tag{5}\]  
At the transmitter side, an N-point IFFT is constructed by adding zeros after the \(N_{\text{SC}}\) useful data. Addditionally, a cyclic prefix of length \(T_{gi}\) needs to be added before the OFDM symbols to prevent intersymbol interference (ISI). To ensure the orthogonality between subcarriers, the length of \(T_{gi}\) needs to be greater than or equal to the maximum delay of the multipath channel. At this point, the transmitted baseband signal in the time domain can be expressed as  
\[f(t)=\frac{1}{N}\sum_{i=0}^{\infty}\sum_{n=0}^{N-1}X_{i,n}e^{j2\pi\frac{n\left( t-T_{gi}-iT\right)}{T_{sub}}} \tag{6}\]  
where \(iT<t<(i+1)T\), \(T_{sub}\) denotes the useful symbol interval.
# Gaze Tracking Using an Unmodified Web Camera and Convolutional Neural Network
## 3 Materials and Methods
### Network Architecture of the Tested Models
#### 3.4.3 Both Eye Images as a Neural Network Input  
For this experiment, a network architecture was prepared to accept left and right eye images as its input parameters. The schema is shown in Figure 7. The neural network consists of three convolutional layers, one subsampling layer 2 \(\times\) 2, one concatenation layer, and three fully connected layers. The fully connected layers consist of a layer for each input image, i.e., FC-LE1 and FC-RE1 with 1024 neurons, the concatenate layer, and two layers: FC1 with 2048 neurons and FC2 with 1024 neurons. The details of the convolutional layers of the neural network are presented in Table 2. The output of the developed neural network architecture is a set of twenty points representing the position of the area on which the subject focuses his/her gaze. This solution will be referred to as ARCH-LRE.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Layer** & **Number of Filters** & **Filter Size** & **Step** \\ \hline LF1 & 96 & \(11\times 11\) & 4 \\ LF3 & 256 & \(5\times 5\) & 1 \\ LF5, LF6 & 384 & \(3\times 3\) & 1 \\ LF7 & 256 & \(3\times 3\) & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristics of convolutional layers for an experiment using face image as neural network inputs.  
Figure 7: Network architecture for the network using both eyes images.  
All three presented network architectures are a little bit different in terms of topology. For instance, one eye image architecture contains only three convolutional layers, one subsampling layer, and one fully connected layer (Figure 5). Face image architecture is more complicated and contains two sets of alternate convolutions and subsampling layers and then again three convolutional layers, one subsampling layer, and finally two fully connected layers (Figure 6). For both eyes architecture (Figure 7), the network has a similar architecture as one eye network, but the outputs from the left eye and right eye stacks are concatenated at the end and sent to two fully connected layers. All three architectures have a different number of parameters because they all have a different numbers of layers. The proposed architectures were chosen from a set of several possibilities that were initially studied. These networks are not generic, and the search for possible better architectures requires further studies.
# Improvement of Boeing Bump Method Considering Aircraft Vibration Superposition Effect
## 5 Results and Discussion
### Modification of Boeing Bump Index  
The Boeing Company mainly utilizes only the B727 as the test aircraft for investigating Boeing Bump criteria. Although the results show a reliable relationship with the dynamic responses of the B727, their extension for application to other aircraft types may be poor. This paper analyzes the peak value of the CGA for five aircraft at the most unfavorable speed under different wavelength bumps (Figure 10). The CGA of the B737 is the largest within the 15 m wavelength whereas the CGA of the B747 is the largest at more than 50 m wavelength. In general, when the bump wavelength is near the sensitive wavelength of a certain aircraft model, the dynamic response is the greatest because the excitation frequency is close to the natural frequency of that aircraft.  
To ensure that a runway's roughness can meet the requirements for all types of aircraft, the aircraft with the greatest dynamic response should be selected as the simulation aircraft for the corresponding wavelength range. Table 9 shows the selection of the simulation aircraft models based on different wavelengths. Based on the criteria for the MGDLC, NGDLC, PSA, and CGA, we modified the bump height as the upper limit in the acceptable zone and unacceptable zone, as shown in Table 10.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Wavelength (m)** & **0-15** & **15-25** & **25-40** & **40–50** & **50-120** \\ \hline Aircraft type & B737-800 & B757-200 & B787-8 & B777-300 ER & B747-400 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Selection of simulation aircraft under different wavelength bumps.  
Figure 10: Maximum value of CGA versus different wavelength bumps for five aircraft model types.  
Figure 11 shows the fitting curves of the upper limits of the modified Boeing Bump height in the acceptable zone and unacceptable zone. The bump height increases as the bump length increases. Figure 12 presents a comparison between the modified and original Boeing Bump evaluation criteria. The upper limits of the acceptable and unacceptable zones in the modified criteria are both below the original standard line, especially under the middle and long waves. Thus, the revised evaluation criteria are more conservative and have a wider application range than the original Boeing Bump criteria, especially in terms of the middle and long waves on a runway.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{3}{*}{**Wavelength (m)**} & \multirow{3}{*}{**Aircraft Type**} & \multirow{3}{*}{
\begin{tabular}{c} **Bump Height** \\ \(L=\lambda/2\)**(m)** \\ \end{tabular} } & \multicolumn{2}{c}{**Upper Limit of**} & \multicolumn{1}{c}{**Upper Limit of**} \\  & & **Bump Height** & **Bump Height in** & **Bump Height in** \\  & & \(L=\lambda/2\)**(m)** & **Acceptable Zone** & **Unacceptable** \\  & & & **(mm)** & **Zone (mm)** \\ \hline  
\hline \hline \end{tabular}
\end{table}
Table 10: Limits of Boeing Bump height in acceptable zone and unacceptable zone.  
Figure 11: Modification of Boeing Bump.
# A Novel Anomaly Behavior Detection Scheme for Mobile Ad Hoc Networks
###### Abstract  
To sustain the security services in a Mobile Ad Hoc Networks (MANET), applications in terms of confidentially, authentication, integrity, authorization, key management, and abnormal behavior detection/anomaly detection are significant. The implementation of a sophisticated security mechanism requires a large number of network resources that degrade network performance. In addition, routing protocols designed for MANETs should be energy efficient in order to maximize network performance. In line with this view, this work proposes a new hybrid method called the data-driven zone-based routing protocol (DD-ZRP) for resource-constrained MANETs that incorporate anomaly detection schemes for security and energy awareness using Network Simulator 3. Most of the existing schemes use constant threshold values, which leads to false positive issues in the network. DD-ZRP uses a dynamic threshold to detect anomalies in MANETs. The simulation results show an improved detection ratio and performance for DD-ZRP over existing schemes; the method is substantially better than the prevailing protocols with respect to anomaly detection for security enhancement, energy efficiency, and optimization of available resources.  
Mobile Ad Hoc Networks (MANETs); anomaly detection; anomaly behavior detection; security; energy preservation
# Superpixel Segmentation Using Weighted Coplanar Feature Clustering on RGBD Images
###### Abstract
* Due to the artifacts in raw depth maps, there are some areas without depth data, so superpixels cannot cover these regions. Worse still, errors may influence the robustness of the superpixel methods. * Although some superpixel methods, especially RGBD images, can run on point clouds and produce supervoxels, the neighborhood data of each point is insufficient. This makes the methods inefficient. In this paper, we propose a novel superpixel method, named weighted coplanar feature clustering (WCFC), which processes single-frame RGBD images. Weighted coplanar feature clustering makes a trade-off between the color and depth information by a content-adaptive weight and allows superpixels to completely cover the entire image by using the raw RGBD image. Moreover, based on the effective use of point cloud spatial information, WCFC projects the point cloud back onto the image plane, which enables the pixel to regain adequate neighborhood information. Additionally, WCFC runs quickly, meets real-time needs and outperforms state-of-the-art superpixel methods in terms of quality. Examples of superpixels produced by WCFC are shown in Figure 1, where the average superpixel size is approximately 500 pixels in the upper left of each image and approximately 300 in the lower right. The organization of the paper is as follows: first, in Section 2, we provide an overview of existing methods, including both traditional superpixel segmentation methods and RGBD methods. In Section 3, the WCFC framework is introduced, especially the concept of distance measure in the framework; the preprocessing is also discussed in detail. After introducing the distance measure in the algorithm framework, Section 4 focuses on the computation of the geometric part of the distance measure, and the concept of plane projection length (PPL) is presented. In Section 5, several experiments and evaluations are presented. Finally, the conclusions are given in Section 6.