esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experimentation
### Results and Discussions
#### 5.2.1 Dynamic Response under Different Conditions
According to the aforementioned results, the dynamic response time of the normal mode and the boost mode with proposed methods are shown in Table 3. During the start-up and abrupt load torque change procedures, the response time of the boost modes are both shortened by about 1 s,  
Figure 12: Speed tracking curve. Figure 13: Part of the phase-current waveforms during abrupt load torque change from 1 to 3 N.m. (a) Normal state; (b) adjustment state (\(K_{2}=1\)). which is almost 30% of the response time under normal conditions. The response time of the speed adjustment process is shortened by 2 s, which is due to the data transmission delay by the series communication interface. Compared with the conventional full bridge inverter, the proposed topology is able to improve the dynamic response characteristics significantly. Meanwhile, excessive elements and a complicated control strategy are avoided to achieve a wide range of speed control performances in comparison with BL-Zeta or BDC combinations. However, only certain voltage output levels of the converter should be allowed to avoid frequent switching operations.
# Predicting Electromagnetic Performance Under Wrinkling in Thin-Film Phased Arrays
###### Abstract  
Deployable thin-film antennas deliver large aperture gains and high stowage efficiency for spaceborne phased arrays but suffer wrinkling-induced planarity loss and radiation distortion. To bridge the lack of electromechanical coupling models for tensioned thin-film patch antennas, we present a unified framework combining structural deformation and electromagnetic simulation. We derive a coupling model capturing the increased bending stiffness of stepped-thickness membranes, formulate a wrinkling analysis algorithm to compute tension-induced displacements, and fit representative unit-cell deformations to a dual-domain displacement model. Parametric studies across stiffness ratios confirm the framework's ability to predict shifts in pattern, gain, and impedance due to wrinkling. This tool supports the optimized design of wrinkle-resistant thin-film phased arrays for reliable, high-performance space communications.  
step-stiffness structure; membrane antenna; thin-film; electromagnetic performance; wrinkling analysis Article
## 3 Results and Discussion
### Parametric Study: Influence of the Refrigerant in the System  
In the continental climate system, a parametric study of the influence of the refrigerant impact was carried out. The Ecoinvent database [31] only includes the refrigerant R134a, but the HYBUILD continental demo makes use of the refrigerant R32, which has a global warming potential (GWP) half of that of R134a (675 kg CO\({}_{2}\) eq. vs. 1430). Therefore, different refrigerants that could be used in the innovative system without major changes to the equipment were selected (Table 11). As can be seen in Table 11, these refrigerants have a GWP similar to that of R134a (or slightly higher) or lower, going to as low as 3 kg CO\({}_{2}\) eq. Therefore, the impact of the refrigerant in the overall LCA of the system was calculated, changing the refrigerant impact from 150% to 0%, with 100% being the impact of R134a.  
Figure 6 shows that the contribution of the compression DC-driven chiller is between 5% and 6% in all cases studied, showing that the GWP of the refrigerant does not have any influence in the overall LCA analysis.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Refrigerants** & **GWP 100a** & **Reference** \\ \hline Reference (R134a) & 1430 & [32] \\ R32 & 675 & [33] \\ R407c & 1520 & [33] \\ R410a & 1725 & [33] \\ R600a (butane) & 3 & [32] \\ \hline R290 (propane) & 3 & [34] \\ R152a & 137 & [34] \\ R1234 ze (E) & 6 & [35] \\ R1234 yf & 4 & [32] \\ \hline \hline \end{tabular}
\end{table}
Table 11: GWP 100a of the selected refrigerant for the parametric study.  
Figure 6: Contribution of the refrigerant to the overall system change in the refrigerant impact: (**a**) R134a (100%); (**b**) 150%; (**c**) 50%; (**d**) 0%.  
Given these results, a new parametric study was conducted varying the replacement rate of the refrigerant. In the initial LCA, a life cycle of the refrigerant of 15 years was considered. Figure 7 shows that to see a change on the contribution of the compression DC-driven chiller in the overall LCA, the refrigerant life cycle needs to be considered as lower than 5 years, which is very unrealistic [36].
# Key Issues on the Design of an Offshore Wind Farm Layout and Its Equivalent Model
## 10 Aggregation of Equivalent Parameters of a Wind Farm  
A large wind farm typically comprises wind turbines of a single type. If a wind farm has one or a few wind turbines, then some of the parameters of the power system must be adjusted to specify the equivalent network environment, thus that the simulation closely reflects actual operating conditions. Equivalent parameters include wind speeds, wind power generators, power transformers, and power transmission lines. For example, the equivalent parameters of wind generators include the capacity of a wind turbine, rated power, stator reactance, magnetizing reactance, and resistance at the stator and rotor sides. Furthermore, a large offshore wind farm has the capacitance effect in the sea cables. The equivalent impedance of a sea cable is calculated using the constant voltage loss principle: The first step of the calculation is to determine the voltage difference between the high-voltage side and the low-voltage side of the transformer. Then, the average voltage difference through a wind turbine in the group of wind turbines is obtained.
## 2 Experimental Equipment and Signal Processing
### Acquisition Signal Processing
#### 2.4.2 Signal Processing Result  
The data obtained after noise reduction processing are presented in the form of cloud images. Before noise reduction processing, the images scanned by the press rigging with defects contain many unevenly distributed yellow-green patches, which are caused by oil or surface wear on the surface of the wire rope (belonging to interference signals), which seriously affect the quality of the images. It increases the difficulty of subsequent image labeling and defect recognition. The distribution of red area boundaries is scattered, which will interfere with the marking and recognition of the following pictures. After noise reduction, it can be observed that the yellow-green patches are significantly reduced, and the boundary of the red bars is obvious. Often, handheld devices may generate additional noise due to slight jitter or angle deviation, which is greatly reduced after noise reduction processing, further improving the accuracy and reliability of the data. The final cloud image not only has higher clarity and accuracy but also provides a more accurate basis for the defect detection and condition monitoring of the pressed rigging, as shown in Figure 4.  
Figure 3: Flow chart of Kalman filter.
# Implementing and Testing a U-Space System: Lessons Learnt
## 1 Introduction
### The Scope of Labyrinth
However, it was enough for the exercises to be executed, which were performed in empty environments without people at risk, very low possibility of collision with buildings or infrastructure and a maximum of three drones flying at the same time in the area. We cannot claim that we were implementing a complete Strategic Conflict Resolution or a Tactical Conflict Resolution service since we were lacking many of the inputs required to achieve, for example, the coordination with manned air traffic control. Instead, the main interest behind the experiments described here was addressed to verify how well the process of design and request for approval of the flight plans could satisfy the needs of the final users and detect any need that could not  
Figure 1: Web app UTM interface. Blue squares frame the areas of work of the path planner. be identified just running simulations without humans-in-the-loop. The flights supported the activities of final users willing to integrate drones into their tasks to increase efficiency. The use cases included: bird shepherding, runway inspection in airports, sanitary supplies delivery, evaluation of an emergency area, support for the evacuation of a mass of people, monitoring of loading activities and surveillance in maritime ports, infraction detection of car drivers and speed measurement of ground traffic. But another interesting source of feedback came from the work of the operators to integrate their platforms. They had to modify their ground control stations (GCSs) to log in the system, receive and load in the drone the flight plan approved, report the position during the flight and receive instructions and information. This illustrated their limitations, needs and preferences, and these should be considered if we want to facilitate the access of the operators to U-space. DLR was responsible for implementing the services, connecting with UC3M's path planning sub-service. The Spanish partners Arquimea and the National Institute of Aerospace Technology (INTA) would be in charge of testing the system by adapting their platforms and executing real flights that reflected the needs of different final users involved in the project. Note that, as a project addressed to implement U-space, there was no creativity regarding the architecture of the system or the expected functionality of its services, and the guidelines of the third edition of the ConOps were followed as close as possible. Therefore, the purpose of the work described here was not to suggest any divergence from the U-space ConOps, and any of the contributions are believed to fall within the implementation freedom allowed by the high-level specifications of the U-space concept.
# Electromagnetic Field Variation of ELF Near-Region Excited by HED in a Homogeneous Half-Space Model
## 3 Analytical Approximate Expression of the Field Component
### Quasistatic Approximate Propagation Conditions
#### 3.1.1 Approximation of the Propagation Parameter \(\gamma_{2}\)  
Air and seawater have different electric parameters in the \"air-seawater\" homogeneous half-space model; therefore, the ELF near-field EM fields of the HED near the interface of the two media conforms to the quasistatic assumption: \(\omega\to 0\), \(k_{2}\rho<<1\), \(k_{2}<<k_{1}\). Based on this assumption, the simplified root function can be approximated as follows:  
\[\gamma_{2}=\sqrt{k_{2}^{2}-\lambda^{2}}=\lim_{\omega\to 0}\sqrt{\left(\frac{ \varepsilon_{r2}^{1/2}}{c}\omega\right)^{2}-\lambda^{2}}\approx j\lambda \tag{2}\]  
where \(\omega\) is the angular frequency, \(\lambda\) is the wavelength, and \(j\) is an imaginary unit.
# A Trust-Based Predictive Model for Mobile Ad Hoc Network in Internet of Things +
## 3 Proposed Protocol  
A prediction-based trust management framework has been made to enable nodes to establish a trustworthy route and reliable data delivery in IoT-MANET. We have adopted the clustering framework as described in [26] for clustering and Clustrehead (CH) election. In order to collect network parameters for trust calculation, node \(A\) monitors traffic of each neighbor of node \(B\) and calculates the direct trust evidence (\(\zeta_{t}^{AB}\)) in a time period \(\tau_{Trust}\). Nodes are categorized from their Good and \(B\)ad behaviors. To ensure reliable data delivery, the following network parameters have been considered;  
1. number of packets properly forwarded (Good)
2. number of packets dropped (\(B\)ad)
3. number of packets falsely injected (\(B\)ad)  
Trust calculations have been performed periodically, and after the expiration of each time period of \(\tau_{Trust}\), the trust parameters are collected and direct observation \(\zeta_{dir}\) is calculated by node \(A\) using a \(\beta\) distribution.
# Application of Iron-Modified Activated Carbon for Phosphate Removal in Aqueous Systems
## 1 Introduction
Preceding research includes controlling various hydrophobic organic compound (HOC) substances contained in lakes and marine sediments [23] as well as controlling polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) in marine sediments [24]. Furthermore, activated carbon treatment has been reported to be environmentally safe [25]. Meanwhile, activated carbon has been shown to exhibit particularly strong adsorption capabilities for organic compounds compared to metals or inorganic substances [26]. To leverage the advantages of activated carbon effectively, methods such as surface modification using acids, alkalis, microwaves, etc. are employed [9]. Among these, surface-modified activated carbon using cationic metals has demonstrated enhanced adsorption capabilities for inorganic substances [27]. For example, nitrate and fluoride showing improved performance due to electrostatic interactions between positive charge of metal sites, and negative charged pollutants [28; 29; 30]. In the case of phosphate, several studies have reported that activated carbons impregnated with metals such as lanthanum, zirconium and iron exhibit high sorption efficiency through mechanisms including electrostatic attraction and surface complexation [31; 32; 33]. In this study, we conducted a case study with surface-modified activated carbon to prevent phosphorus release from river sediments. The study evaluated the adsorption capacity of surface-modified activated carbon for phosphate, and examined the differences in adsorption capacity according to the modification conditions. To assess the field applicability to Daecheong Lake soil, the study investigated the release of phosphate under hydraulic stress conditions simulated by a stirred batch simulators. Additionally, the study determined the impact of modified activated carbon on phosphate removal from the soil, leading to a possibility for river bed remediation.
# Virtual Reality-Based Interface for Advanced Assisted Mobile Robot Teleoperation
## 2 Proposed Application
### Virtual Environment
2D map: robot (blue circumference in (**a**)); reference (green circumference in (**a**)); detected objects (yellow points in (**a,b**)). 3D environment: reference (blue circle in (**a**)); system information (i.e., robot velocity and distance to the target) in (**b**); teleporting (blue arrowed circle in (**c**)); detected objects (brown walls in all figures); mobile robot boundary as a circle (2D) or cylinder (3D) (red–yellow elements in (**e,f**)). Moreover, the user is allowed to move through the VE in two ways:  
* _Physically:_ the VR headset position and orientation is tracked at any moment and, hence, the user is able to move through the environment as if they were in the real workspace (In general, this movement is limited by a security region free of obstacles established a priori. To avoid this problem, one possibility could be the use of VR omnidirectional treadmills [58]). * _Teleporting:_ the user can \"jump\" from their current position to another position in the environment using the gamepad. Figure 2c shows the designed teleporting element, which consists of an animated blue arrowed circle. This element is designed according to the standard representation of teleporting in most current VR applications. Note that, when the teleporting option is activated, the user cannot simultaneously move the reference position of the robot for security reasons. Finally, two types of sounds are developed to increase the feeling of reality in the VE:
* The movement of the robot produces a characteristic sound due to the robot servos, whose treble variation depends on the speed of the robot. To give it more realism, this sound is recorded directly from the actual sound of the robot moving at low speeds. The treble change of this base sound is carried out proportionally to the speed of the wheels, producing a real sensation of movement of the robot in the VE. This sound effect cannot be disabled by the user. In addition, this is a 3D sound that changes depending on the distance from the user to the robot position, providing the user with a more realistic level of immersion in the task. * An alarm sound is also included to warn the user of collisions between the robot boundary and the obstacles in its environment. As in the previous case, this is also a 3D sound. However, contrary to the later, the user is allowed to deactivate this warning sound, since the nature of the proposed assisted teleoperation approach can lead to situations where the user, for instance, takes the robot to areas where collisions occur, or takes the robot to very tight zones where collisions cannot be avoided. In either case, the user's attention would be on the robot, so the visual effect of the boundary alone would suffice. Note also that this warning sound for long periods could become annoying.
## 2 Related Work
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset** & **IoT Network** & **Anomaly** & **ML Validation** \\ \hline N-BaIoT [9] & IP cameras, PCs, and IoT devices & Mirai botnet and BASHLITE malware & Deep autoencoders [9]. Encoders [10]. LR and ANN [11]. RCNN, XCNN [12]. \\ \hline CCD-INID-V1 [12] & Smart sensors in an IoT network & ARP poisoning, ARP DoS, UDP Flood, Hydra Bruteforce with Asterisk protocol, SlowLoris & RCNN, XCNN, KNN, NB, LR, SVM [12]. \\ \hline [PERSON] et al. [14] & Smartphones and laptops & DDoS, Mirai & KNN, LVSM, DT, RF, NN [14] \\ \hline All eyes on you [15] & Smart home and user smartphones & Anomalous timestamps, DoS & grid-based, k-mean [15]. LR, SVM, DT, RF, ANN [16] \\ \hline Anthi [17] & Smart home & DoS & NB, Bayesian Network, J48, Zero R, OneR, Simple Logistic, SVM, MLP, RF [17]. \\ \hline SCADA IIoT [18] & Modbus traffic packet captures & Metasploit, fingerprinting, unauthorised packets & SVM, RF, KNN, k-means [19]. \\ \hline IIoT MODBUS [20], & Small automation testbed using MODBUS/TCP & Ping flooding, TCP SYN flooding, and MODBUS Query flooding. & KNN, SVM, DT, RF [20]. Autoencoder [28] \\ \hline UNSW [21] & Smart home & DoS, reflective TCP/UDP/ICMP flooding, and ARP spoofing & Boundary detection and Markov Chain [21]. \\ \hline BoT-IoT [22] & Smart Home (MQTT) & DoS, DDoS, data exfiltration, keylogging & SVM, RNN and LSTM-RNN [22]. \\ \hline IoT-NID [25] & Smart home, laptops, and smartphones & Mirai, MITM, DoS, scanning, etc & Autoencoder [28] \\ \hline IoT-23 [26] & Smart home (real IoT devices) & Mirai, Torii, and Gafgyt & RF, NB, SVM, DT [27], autoencoder [28] \\ \hline ToN-IoT [30] & Weather and industrial control sensors (MQTT) & Several normal and cyber attack events from IoT networks & DFF, CNN, RNN, DT, LR, NB [30]. Autoencoder [31] \\ \hline MedBIoT [32] & IoT network (i.e., fans, locks, light bulbs and switches). & Mirai, BashLite, Torii & KNN, SVM, DT, RF [32]. \\ \hline DAD [33] & Temperature IoT sensors (MQTT) & Duplication, interception, and modification of packets. & LR, RF, NB, AdaBoost, SVM [33]. \\ \hline MQTTset [35] & Temperature, humidity, motion sensors (MQTT) & Flooding DoS, MQTT Publish flood, SlowTfe, malformed data, and brute force authentication & DT, RF, MLP, NN, and Gaussian NB [35]. \\ \hline IoT-RPL dataset [36] & Simulated nodes & Hello food, blackhole, decreased rank, and version number & SVM, DT, RF, KNN, and MLP [36] \\ \hline IoT-Flock [37] & Smart home (MQTT/CoAP) & MQTT Packet Crafting Attack, MQTT Publish Flood, CoAP Memory Leak and Attack CoAP Segmentation Fault Attack & NB, RF, and KNN [37] \\ \hline SDN-IoT framework [38] & Simulated network nodes & DDoS & Still not implemented \\ \hline IoTID20 [39] & smart home & Flood Syn, HTTP and UDP, ARP Spoofing, brute force & SVM, Gaussian NB, LDA, LR, DT, RF, and ensemble clasifiers \\ \hline \hline \end{tabular}
\end{table} 
Table 1: IoT dataset review summary considering applications in ML-IDS.
# Patch-Font: Enhancing Few-Shot Font Generation with Patch-Based Attention and Multitask Encoding
## 5 Experimental Results  
### Experimental Setup  
#### 5.1.1 Dataset  
Our research primarily focused on the generation of Korean characters, encompassing both printed and handwritten styles. Additionally, we extended our investigation to printed Chinese fonts to assess our methodology's adaptability. In the case of Korean characters, our dataset included 90 printed and 88 handwritten fonts, all of which were publicly accessible. From these collections, 15 fonts from each category were allocated for the evaluation phase of our model. For the Chinese fonts, we compiled a dataset of 150 printed fonts, reserving 20 for a subsequent evaluation. The unseen fonts for evaluation were randomly selected from the corpus, ensuring a broad variety (e.g., thick, thin, italic, cursive).  
To train the model on Korean characters, we used 2350 commonly used Korean characters. These were split into two categories:'seen' and 'unseen' characters. The seen category comprised 2000 characters, while the unseen included the remaining 350 characters. The evaluation of the model was conducted using both these character sets. Specifically, when validation fonts were assessed against the seen characters, this scenario was designated as seen characters (SCs). Conversely, when the validation involved the unseen 350 characters, this scenario was referred to as unseen characters (UCs).  
For the Chinese fonts, we employed a similar training and validation approach. The total character set comprised 3500 characters, with the model being trained on 3000 characters. The evaluation phase then focused on the remaining 500 characters. This structured approach facilitated a comprehensive assessment of our method's effectiveness across different languages and character sets, providing insights into its generalization capabilities on unseen characters.
## 4 Experimental Results and Analysis
### One-Factor Experimental Analysis
The set surge height was 1.2 cm, and the distance between the experimental position and the wavemaker was 3.7 m. The infrared camera did not pick up a temperature anomaly in the nearby water column when the submersible was lowered to a depth of 30 cm. Through the aforementioned experimental results, it can be seen that, in the same dive depth when the height of the surge was increased, the seawater free surface layer in the wake area and the wake around the water's temperature difference were both significantly reduced. The different heights of the underwater surge had a significant impact on the temperature change in the free surface layer. The water temperature management in the tank was, however, suboptimal due to the closeness of the experimental time period and some experimental errors occurred. The wake was more strongly mixed with the surrounding water during the process of floating and spreading due to the effect of underwater surges, forming a fluid water mass mixed with hot and cold; so, the temperature fluctuations around the temperature measurement point were more violent, the temperature difference between the wake and the water surface was smaller, and the depth of the vehicle that created the wake was greater than in experiments on the infrared properties of the wake at calm water. The directional emissivity changed in response to transient changes in wake geometry at the water column's surface, resulting in shadow obscuration and multiple reflections in the direction of the detector's detection. This reduced the brightness of the thermal wake infrared radiation the detector could detect, making detection more challenging. The heat transfer between the wake and its surroundings as it rose to the surface may also have been accelerated by waves, another indirect contributor to the wake's heat exchange at the sea-air interface. This suggests that one of the variables influencing the wake's diffusion process was the surge.