esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experimental Setup and Measurements
### Normal Angle of Incidence  
The EM performance of the FSS panel is measured using the above-mentioned setup for different polarizations and incident angles. Figure 9a shows the measured SE of the FSS for TE and TM polarizations at normal incidence. Since the design is four-fold symmetric, it therefore exhibits an identical spectral response for both the vertical and horizontal waves. The results reveal that the FSS achieves SE of more than 35 dB and 40 dB at both operating frequencies. It is observed that the FSS shield exhibits rejection bandwidths of more than 2.10 GHz and 2.40 GHz for the transverse electric, whereas 2.20 GHz and 2.60 GHz for the transverse magnetic modes of operation at the X- and Ku-bands, respectively.
## 1 Introduction
This study introduces a workflow for detecting the displacements of paving blocks adjacent to deep excavation sites. This workflow mainly relies on close-range terrestrial photogrammetry and structure-from-motion (SfM) photogrammetric techniques. The requirements for establishing reliable point cloud data (PCD) for paving blocks including ground sampling distance, image network geometry, and parameters of the camera mounted on an unmanned ground vehicle (UGV) are presented. The applicability of the cloud-to-cloud (C2C) distance computation algorithm is discussed to trace temporal changes in the uplift, settlement, and horizontal movement of paving blocks.
## 5 Discussion
### Technological Complexities and Data Preprocessing  
The integration of data from Sentinel, Landsat, and UAVs for shoreline monitoring presents a host of challenges that surpass resolution and revisit times.  
For example, there is heterogeneity in the data: Landsat provides multispectral imagery, while UAVs deliver high-resolution orthophotos; these need complex preprocessing to harmonize inputs [54; 57]. The complexity further adds to misalignments due to differences in the angles of satellites and flight paths of UAVs, which require advanced techniques of rectification and accurate georeferencing with the help of ground control points [55; 65]. Tidal fluctuations complicate shoreline data even more, making accurate tidal models essential for consistent analysis [37; 56]. Integrating UAV imagery with long-term Landsat archives generates large datasets, creating significant computational demands [53; 66]. Algorithms such as J-Net Dynamic, used for subpixel shoreline detection, introduce additional layers of complexity [54]. Environmental factors, like cloud cover, often impede optical satellite imagery. UAVs, while less reliant on good weather, require manual launching and supervision. Human activities, particularly those involving coastal engineering, result in rapid changes along the shoreline and further complicate monitoring [57; 65]. With its essential contribution, validation using GNSS remains resource-intensive and time-consuming [37; 55]. Addressing these challenges requires automated data processing pipelines and standardized methods to ensure consistency and reliability in shoreline monitoring [56].
# Image Quality Assessment of Augmented Reality Glasses as Medical Display Devices (HoloLens 2)
## 3 Results
### Evaluation of Minimal and Maximal Luminance  
The luminance of HoloLens 2 ranges from a minimum of 1.6 cd/m\({}^{2}\) to a maximum of 2366 cd/m\({}^{2}\), resulting in a luminance ratio (\(L_{max}/L_{min}\)) of 1478.75. Consequently, HoloLens 2 meets the requirements for both primary and secondary display devices.
# A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks
## 4 Performance Evaluation  
In this section, we evaluate the performance of the ICV-MIMO scheme via simulations. We also compare it with the CMIMO, which resembles the ICV-MIMO scheme in the inter-cluster communication modes.
# Continuous-Wave THz Imaging for Biomedical Samples
## 5 The Application of CW Imaging with Biological Tissues
### Tumour Tissues
#### 5.1.4 Human Colon Tissues  
Colon cancer, with the highest incidence in the 40-50 years old age group, is a common malignant tumor of the digestive tract in the colon and often occurs at the junction of the rectum and the sigmoid colon. It is asymptomatic in the early stage, but abdominal distension and indigestion can occur in the middle and late stages [89]. In 2016, [PERSON] et al. imaged human dehydrated colon tissue resections embedded in paraffin of 2 mm thickness and 0.5 mm spatial resolution, using high-resolution transmissive and reflective imaging technologies at 590 GHz [90]. The contrast of THz wave absorption between the tumour and normal tissues reached 23%, and the colon cancer tissues had higher absorption and reflectivity, which distinguished cancer tissues from normal tissues. They also used the same system to image fresh samples and reached the same delimitation conclusion, which meant that the high water content in THz images could distinguish cancer and normal tissues in both fresh and dry samples. The imaging system could also distinguish the tumour stages, such as pT3 type (underdeveloped) and pT4 type (slightly developed). Due to the thickness and unevenness of samples, extracting accurate parameters (such as absorption) from the THz images is challenging. In recent years, some optimised CW imaging systems were developed to improve the imaging accuracy, such as THz polarisation imaging technology. In 2013, [PERSON] et al. used an optically pumped far-infrared molecular gas laser to produce the frequency of 584 GHz, the reflective polarisation THz imaging system as shown in Figure 3, and they imaged fresh human colon sections with 4-6 mm thickness by reflective polarisation THz imaging with a 0.6 mm spatial resolution [41]. The normal and cancerous tissues have a sharp contrast in their absorption of THz waves, so the boundary of the colon tumours can be clearly identified in Figure 14. For the minimally invasive diagnosis of malignant tumor, CW imaging technology can be applied to the diagnosis and treatment methods, such as endoscopic and laparoscopic surgery. In 2016, the same group demonstrated a THz endoscopic system at 584 GHz to visualise human colon cancer tissues using the THz transmissive and reflective co- and cross-polarised imaging methods [91]. The boundary of the cancer tissues could be clearly observed from the cross-polarised THz images, paving the way for THz endoscopic system clinical applications in colon cancer detection.
###### Abstract  
Background: Many studies examine young adolescents' motivation for physical activity (PA), but few explore the problem in depth, considering the self-assessment of sport skills or the impact of additional PA. Insufficient PA among adolescents is a significant global issue. This study aimed to analyze the differences in types of motivation, the self-assessment of sports skills, and overall fitness among young adolescents with regard to additional PA. Material and Methods: A sample of high school students (\(n=355\)) was assessed using an MPAM-R questionnaire, a self-developed sport skills competency test, and an IFIS questionnaire. Results: There are significant differences in types of motivation between genders: girls achieved higher results in terms of appearance, whereas boys were mostly focused on enjoyment and competence. Additionally, participants who reported engaging in additional PA, regardless of gender, achieved higher results in nearly all types of motivation, except for social. The findings consistently highlight a strong emphasis on appearance among young adolescents. The self-assessments of sports skills and overall fitness were also higher in the group of participants with additional PA. The study revealed further differences between boys and girls in the assessment of tactical and technical skills. Boys rated themselves higher in team sports, whereas girls in individual activities such as gymnastics. Conclusions: These results provide new insights into teenagers' motivations and self assessment of sport skills and can serve as a solid foundation for further research for developing activities aimed at increasing leisure-time PA among youth.  
motivation; youth; after school physical activity; gender 2025157043
# The Enhanced Adaptive Grasping of a Soft Robotic Gripper Using Rigid Supports
## 3 Design and Grasping Principles of the Proposed Gripper
### Lifting Force Measurement  
The experimental setup is depicted in Figure 6a. The soft robotic gripper grasps a lightweight spherical object (55 g; 75 mm in diameter) to which a thin rope is tied. The force transducer is moved downward manually at a slow speed until the gripper fails to grasp the object. The maximum lifting force under a certain pressure is the maximum force measured by the force transducer plus the weight of the spherical object.  
Grippers with different distributions of silicones and with or without the rigid supports are all tested in this experiment (Figure 6).  
Comparing groups 3 and 4, the rigid supports increase the lifting force of the original soft gripper without the rigid supports by 152.4% in the same incremental pressure (26.4 kPa), and the level of performance improvement will be higher when the incremental pressure is higher. In general, the lifting force is reinforced by 150 \(\pm\) 20% in about 26.5 kPa. As depicted in Figure 6, the maximum lifting force of the soft grippers with the designed rigid supports (groups 1 and 3) is larger than the soft grippers without the designed rigid supports (groups 2 and 4), which indicates that the designed rigid supports can improve the grasping performance in the same incremental pressure to a greater extent.  
Comparing groups 1 and 3 at low incremental pressure (below 27 kPa), the pure silicone gripper (group 1) exhibits better gripping ability. When the grippers grip light objects (below 3 kg) at low incremental pressure, objects are lifted mainly by friction. The chambers near the center of the pure silicone gripper expand more than that of the hybrid silicone gripper (group 3), resulting in better gripping ability under the constraint of rigid supports. At high incremental pressure (over 27 kPa), the hybrid silicone gripper (group 3) exhibits better gripping ability. When the grippers grip heavy objects (over 4 kg) at  
Figure 6: The experimental setup and maximum lifting force in different pressures. (**a**): The experimental setup; (**b**): maximum lifting force in different pressure (Line 1: 0050:0030 = 0:1, with rigid supports; Line 3: 0050:0030 = 1:1, with rigid supports; Line 4: 0050:0030 = 1:1, without rigid supports).  
high incremental pressure, the objects are lifted mainly by the support force. And the deformation at the end of the hybrid silicone gripper (group 3) is greater, providing greater support, thus demonstrating better grasping ability.  
With the help of the rigid supports, soft grippers (groups 1 and 3) all show excellent heavy items grasping ability. The soft robotic gripper coupling with rigid supports can grasp items with large weights requiring low incremental pressure (object: about 75 mm in diameter, below 5 kg: pressure requirement: below 30 kPa).
## 5 Results and Discussions
### Space-Based Tracking Scenario  
To estimate the target position using the algorithm defined in Section 2.2, we define the satellite orbital elements in the ECI frame and the Cartesian frame (Table 4). The values of the corresponding error coefficients must be computed to calculate the errors in target position estimates. The error coefficients are sums of partial derivatives that are mentioned in [48]. The sigmas for each \(\mathrm{x_{t}}\), \(\mathrm{y_{t}}\), \(\mathrm{z_{t}}\) are calculated using Equations (5)-(8) with the corresponding azimuth angles \(\mathrm{\theta_{1}}\) = 27 deg and \(\mathrm{\theta_{2}}\) = 315 deg, and elevation angles \(\mathrm{\phi_{1}}\)=58 deg and \(\mathrm{\phi_{2}}\) = 62 deg. Assuming that the state-of-the-art star trackers can provide the RSO sigma position \(\mathrm{\sigma_{p}}\)= 0.5 m and sensor angular error \(\mathrm{\sigma_{\theta}}\) = 0.0022 degrees, running the algorithm allows us to obtain the sigmas listed in Table 5.  
Using the mathematical framework presented in Sections 2.2 and 2.3, the covariance matrix corresponding to the navigation errors, tracking errors, and total error can be presented in the form of an uncertainty ellipsoid, illustrated in Figure 11.  
Figure 10: AN system architecture for ground-based tracking scenario.
## 3 Review of Methods
### Long Short-Term Memory (LSTM)
By employing _Stacked LSTMs_ (_SLSTMs_) embedded between two fully connected networks (_FCNs_) and using randomly cropped training data within the _Backpropagation Through Random Time_ (BPTRT) method for the training process, an average accuracy of 97.6% was achieved for the recognition of four different coarse-grained activities (punching three times, squatting and picking up an object, stepping in place, and raising hands into a horizontal position). In [59], an SFCW radar system was employed to produce spectrograms for multiple frequencies in the collection of data from 11 subjects who performed six different activities with transitions. By comparing the single-frequency LSTM and Bi-LSTM with their multi-frequency counterparts, it was shown that the classification performance was significantly higher, resulting in accuracies of 85.41% and 96.15%. Due to their ability to memorize even longer temporal sequences, which applies to a wide range of human activities, LSTM networks are, in general, suitable for radar-based HAR, as long as the limitations are considered. RNNs also have limitations, i.e., numerical problems with the determination of gradients and setup constraints due to the sample lengths of input data [46]. Moreover, in comparison with other techniques, LSTM networksrequire a high memory bandwidth, which can be a major drawback in online applications if hardware with limited resources is used [82].
# Design of a Hand-Launched Solar-Powered Unmanned Aerial Vehicle (UAV) System for Plateau
## 4 UAV Flight Control
### Successive Loop Closure Flight Control
#### 4.4.2 Lateral-Directional Control Law  
The lateral-directional control law is still based on the successive closed-loop theory [20]. For the UAV with aileron-free design, the rudder was the only input for lateral-directional control. That is, the rudder can simultaneously control the two channels of roll and sideslip: Channel 1, the rudder was treated as a pseudo-aileron, controlling the roll channel. Formula (26) is the control law when the rudder is used as a pseudo-aileron. Channel 2, the rudder was used to control the sideslip of the UAV, and Formula (27) is the output of rudder command during coordinated turn.  
\[\begin{split} p_{c}&=(k_{p_{\phi}}+k_{d_{\phi}}\cdot s )(\phi_{c}-\phi)\\ \delta_{a}&=(k_{p}+k_{p_{d}}\cdot s)(p_{c}-p)\\ & r_{c}=\frac{g}{V_{0}}\tan\phi_{c}\\ \delta_{r}&=k_{r}(r_{c}-r)\\ \end{split} \tag{26}\]  
The outer loop was a straight-line trajectory tracking by the \(L_{1}\) method [21], Figure 14 shows the path diagram of UAV and linear target. In the figure, \(d\) is track error, \(L_{1}\) is the distance between conference point and UAV, \(V\) is velocity component of the horizontal plane, \(\chi\) is the flight path angle, as is expected lateral acceleration, and \(\psi_{t}\) is the azimuth angle of target trajectory. The control instruction of horizontal trajectory tracking based on \(L_{1}\) method is shown in Formula (28).  
\[\begin{split} a_{s}&=2\frac{V^{2}}{L_{1}}\sin\eta \approx 2\frac{V}{L_{1}}\bigg{(}\dot{d}+\frac{V}{L_{1}}d\bigg{)}\\ \phi_{cmd}&=\arctan\bigg{(}2\frac{V}{L_{1}g} \bigg{(}\dot{d}+\frac{V}{L_{1}}d\bigg{)}\bigg{)}\\ \psi_{cmd}&=\psi_{t}+\eta_{1}\\ \end{split} \tag{28}\]  
The simulation results of UAV straight-line trajectory tracking are shown in the Figure 15. Figure 15a shows that the response time of the roll angle command was about 1.4s and there was no static error or overshoot. Figure 15b shows that the response time of lateral distance command (50 m) was about 10.39 s with 2.12 m overshoot. The simulation results show that the trajectory tracking control based on \(L_{1}\) method is feasible for the UAV flight at 4500-m altitude with aileron-free configuration.  
Figure 13: Simulation of pitch angle and altitude command tracking: (**a**) Pitch angle tracking. (**b**) Altitude tracking.
# Cross-Platform Gait Analysis and Fall Detection Wearable Device
## 6 Conclusions  
Due to the progress in medical technology and the advent of an aging society, the rehabilitation treatment gets attention gradually. The rehabilitation methods are different according to different parts of the body and symptoms.  
In this paper, it focused on gait analysis, such as step count, step length, and angle of knee joint measurements, since the gait analysis was often needed for elderly. In addition to gait analysis, fall accident was also often occurred for elderly.  
In the above mention, it showed the importance for gait analysis and fall detection in modern rehabilitation medicine. However, the existed gait analysis in hospital was still executed by specific medical instruments. In this way, the time and money for patients must increase. The feasibility of gait analysis thus decreased, since the gait analysis could not be executed in any place and any time. For medical institutions, the manpower also increased.  
Hence, how to ensure that gait analysis could be executed in any place and any time becomes an important issue. However, how to ensure that the gait analysis was correct at home becomes another important issue, since the incorrect gait analysis may lead to incorrect rehabilitation. The rehabilitation treatments may be discounted.  
Therefore, a cross-platform gait analysis and fall detection wearable device, CPGAFDWD, was proposed to address the above issues in this paper. In CPGAFDWD, it aimed to ensure that the gait analysis could be correct without limiting to any time and place for patients. The experimental results also showed that the correct rate of gait analysis was over 90% and the correct rate of fall detection was close to 100%. It proved that CPGAFDWD we proposed could be applied for gait analysis and fall detection in any time and place. The time, money, and manpower thus could be reduced for patients and medical institutions. In the future, we will apply IRB for CPGAFDWD used in clinical medicine.  
**Author Contributions:** [PERSON] was responsible for Supervision and Project Administration. [PERSON] was responsible for Conceptualization, Methodology, Investigation, Writing--Original Draft, and Writing--Review & Editing. [PERSON] was responsible for Resources and Software. [PERSON] was responsible for Validation and Formal analysis. [PERSON] was responsible for Data Curation and Visualization. All authors have read and agreed to the published version of the manuscript.  
**Funding:** APC was funded by National Science and Technology Council (NSTC) of Taiwan to National Yunlin University of Science and Technology under 111-2221-E-143-002.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** This paper was supported by the National Science and Technology Council (NSTC) of Taiwan to National Yunlin University of Science and Technology under 111-2221-E-143-002.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Results and Discussion  
### Horizontal Line  
In previous LCLD studies, to minimize direct ablation of deposited copper particles by laser, most of them used low laser power of 0.1-3 W. Accordingly, the feed rate of the laser beam was very low of 0.0025 to 0.015 mm/s to activate the chemical reaction by applying sufficient thermal energy to the reaction area even with low laser power [13; 16; 18; 23]. On the other hand, in this study, to overcome such low productivity, experiments were conducted by increasing the laser power and feed rate more than 10 times. Therefore, the average power was fixed at 20 W, the maximum power generated by the used equipment. The laser scan speed was fixed at 1 mm/s, which is the minimum feed speed of the galvanometer scanner. To maximize the thermal effect, the laser mode was set to continuous wave (CW) mode. In the case of patterning the lines repeatedly, the line interval, which is the center-to-center interval, was fixed at 20 \(\upmu\)m so that the overlapping ratio between lines was 50% or more for dense deposition.  
Compared with previous studies, the thermal energy for the reduction reaction was relatively insufficient on a single line basis, so only a small amount of copper ions were reduced and deposited, as shown in Figure 3b. Accordingly, the number of lines was increased to 3 and 5 for obtaining a dense and complete conductive line. Through this, the laser energy was repeatedly irradiated to the local area to increase the thermal energy effect, thereby obtaining a more improved deposition result, as shown in Figure 3c,d. However, it could be seen that the deposition was mainly performed on one edge of a laser-irradiated horizontal line. This was due to the following reasons. First, in this experiment, unlike existing LCLD studies, because a high-power laser was irradiated to the deposition solution, bubbles were generated, and these bubbles expanded/exploded and pushed the reduced copper atoms to the edge region. This phenomenon is also commonly observed in the LIBWE process similar to LCLD [12; 24; 25]. In addition, since high laser power was used in this experiment, the deposited thin copper layer during the first scan was partially ablated at the overlapping area when the next laser scan was irradiated. Thus, in this experiment, when the scan paths of the horizontal line descend in order from top to bottom, the copper was deposited on the edge of the line, but the copper formed on the lower edge of the line was ablated during the next laser scan. As can be seen from the results, the deposition area was mainly observed only at one edge of the line.