esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theoretical Framework
### Self-Determination Theory (SDT)
#### 2.2.3. Competence  
This need refers to effective behavior, the expansion of personal capabilities, and the desire to be enough [48]. In this context, SDT indicates that competence allows individuals to master tasks or achieve aims with ease [55]. When this basic need is satisfied, individuals begin to acquire the feeling of being effective in developing tasks [54].  
According to [49], in the field of ICT, the need for competence is associated with factors such as (1) job satisfaction; (2) levels of job burnout; (3) experience in using technology; (4) expectations of the outcomes of using computers; (5) emotional reactions to computers; and (6) actual computer use, among others. Consequently, it is possible to define a relationship between competence and the degree to which people benefit from the use of ICT [86].  
In addition, previous studies carried out in the educational context have shown that there is a relationship between competence and the constructs PU and PEU [87]. In our case, students' competence corresponds to the need to become more effective in the use of OSS in order to achieve high academic levels [88]. This is because competence is expected to make students more effective in their OSS use. This anticipation would increase the PU and PEU of OSS. The following hypotheses have been defined (Figure 2):  
**Hypothesis 8 (H8).**_Competence (COMP) has a positive effect on the perceived usefulness (PU) of OSS._  
**Hypothesis 9 (H9).**_Competence (COMP) has a positive effect on the perceived ease of use (PEU) of OSS._
## 3 Proposed Method
### Cross-Attention Fusion Module (CAFM)
**Channel Attention Fusion (CAF):** After XAF, in order to fuse global information in the channel dimension, we use the proposed channel attention mechanism to integrate the channel information. First, the two cross-attention fusion (XAF) dual-branch information \(I^{U}\) and \(I^{D}\) are merged to obtain \(Q_{S}\), and the channel information \(Q_{S}\) is extracted using the global average pooling GAP. Next, the fully connected layer activates \(Q_{S}\) to generate adaptive selection weights such as \((X_{A},X_{B})=fc(Q_{s})\). The Softmax function converts the adaptive selection weights into attention weights \((X_{a},X_{b})\) as follows:  
\[X_{a}=\frac{e^{X_{A}}}{e^{X_{A}}+e^{X_{B}}},X_{b}=\frac{e^{X_{B}}}{e^{X_{A}}+e ^{X_{B}}} \tag{10}\]  
Here, \((X_{A},X_{B})=fc(Q_{s})\) denotes the adaptive selection weights, and \((X_{a},X_{b})\) denotes the attention weights of \(I^{U}\) and \(I^{D}\), respectively. Applying the attention weights \((X_{a},X_{b})\) to \(I^{U}\) and \(I^{D}\) yields the final feature map \(E\). \[E=I^{U}X_{a}+I^{D}X_{b} \tag{11}\]  
Here, \([X_{a}+X_{b}]=[1,1...1]\in R^{c}\), \(E=[E_{1},E_{2},\ldots,E_{C}]\). The figure shows the architecture of channel fusion attention.
## 2 Materials and Methods
### Data Analysis
#### 2.5.3 Comparative Analysis of On-Screen Affordance Transmission and Model Evaluation  
The goal is to detect which affordances are easier or more challenging to convey from on-screen evaluation. Mean values for each question were calculated for DoIA% and used as dependent variables in Kruskal-Wallis tests (applied due to violations of variance homogeneity) with Bonferroni correction to check for significant differences (\(p<0.05\)  
\begin{table}
\begin{tabular}{l l c c} \hline \hline \multicolumn{1}{c}{**Metric**} & \multicolumn{1}{c}{**Definition**} & \multicolumn{1}{c}{**Reference Value for**} & \multicolumn{1}{c}{**Scaled Metric**} \\  & & **Scaling Metrics Into \%** & & \\ \hline DoI & Duration of interval (seconds): & - & - \\  & the total time spent observing the stimulus. & & \\  & Total duration of fixations in AoI (seconds): & & \\ TDoF & a fixation is an eye movement with a velocity of & DoI & TDoF\% \\  & less than 30\({}^{\circ}\)/s. & NoF in AoI Stimulus & NoF\% \\ NoF & Number of fixations in AoI. & DoI & TtfF\% \\ TtFF & Time to first fixation in AoI (seconds). & DoI & DoFF\% \\ DoFF & Duration of first fixation in AoI (seconds). & & \\  & Total duration of visits in AoI (seconds): & & \\  & a visit corresponds to all data (including saccadic & & \\ TDoV & movements, blinks, or invalid gaze data) from & DoI & TDoV\% \\  & the start of the first fixation inside an AoI to the & & \\  & end of the last fixation in the same AoI. & & \\ NoV & Number of visits in AoI. & - & - \\ \hline \hline \end{tabular}
\end{table}
Table 5: Metrics calculated for each stimulus and participant, along with the reference values used for scaling.  
between affordances. DoIA%, where lower values reflect easier transmission, serves as a clear indicator of affordance transmission.  
For on-screen evaluation of models, ratings were assigned to ranks in UA1 as follows: +2 for the best, +1 for the second best, \(-2\) for the worst, \(-1\) for the second worst, and \(0\) for non-selected models. For each affordance, a non-parametric Scheirer-Ray-Hare test was conducted using ratings as the dependent variable and model, version (with or without rubber), and their interaction as factors (with \(p=0.05\)). Additionally, a non-parametric Kruskal-Wallis test was performed as a post hoc analysis to compare significant differences between versions (with and without rubber) for each model and affordance, using rubber as a factor and ratings as the dependent variable. A separate Kruskal-Wallis test was also applied across models, regardless of the version, to examine significant differences in ratings based on model as the factor.
Sensors_**2013**, _13_, 10087-10122; doi:10.3390/s130810087  
Sensors  
ISSN 1424-8220  
www.mdpi.com/journal/sensors  
Advancements of Data Anomaly Detection Research in  
Wireless Sensor Networks: A Survey and Open Issues  
[PERSON] 1,2,*, [PERSON] 1,* and [PERSON] 1  
Faculty of Computing, Universiti Teknologi Malaysia, Johor 81310, Malaysia;  
E-Mail: [EMAIL_ADDRESS]  
Faculty of Engineering and Information Technology, Taiz University, Taiz 6803, Yemen  
Authors to whom correspondence should be addressed; E-Mails: [EMAIL_ADDRESS] (M.A.R.); [PERSON]ADDRESS] (A.Z.); Tel.: +60-17-3681303 (M.A.R.); Fax: +60-07-556-5044 (A.Z.).  
Received: 23 April 2013; in revised form: 4 July 2013 / Accepted: 25 July 2013 /  
Published: 7 August 2013  
Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept \"_Internet of Things_\" has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed.  
wireless sensor networks (WSNs); data anomaly detection; detection effectiveness; detection efficiency; energy consumption
## 2 Structure and Research Methods
The variation in conductivity of VO\({}_{2}\) films in the THz frequency range may also be related to surface plasmon resonance. When the THz wavelength matches the surface plasmon resonance frequency of the film, it can induce oscillation of surface charges and thereby affect the film's conductivity. The changes in conductivity can also impact the absorption capability of VO\({}_{2}\) films towards THz radiation, resulting in variations in absorption bandwidth. The absorbers designed were simulated using CST Microwave Studio simulation software (2022), following an analysis of the optical properties, a study was conducted on a dynamically adaptable absorber using terahertz metamaterials. During the simulation process, the frequency domain finite element method (FEM) was used, a frequency-domain solver with tetrahedral meshing was used in simulation and the cells per max model box edge were set to 10. The distance between the port and the material surface was set to greater than 1/4 of the center wavelength, the incident terahertz waves approached the absorber from the direction opposite to the surface along the -\(z\)-axis, and the incident wave had its electric field aligned with the \(x\)-axis and the magnetic field aligned with the \(y\)-axis. The boundaries were defined by the unit cells in the \(x\)-axis and \(y\)-axis directions, and open boundary conditions were defined in the \(z\)-axis direction. The representation of the THz absorber's absorptance is as follows:  
\[A(\omega)=1-\mathbb{R}(\omega)-\mathbb{T}(\omega) \tag{2}\]  
where R(\(\omega\)) and T(\(\omega\)) represent the reflectance and transmittance, respectively, and R(\(\omega\)) = \(\left|S_{11}\right|^{2}\), T(\(\omega\)) = \(\left|S_{21}\right|^{2}\), \(\left|S_{11}\right|\), \(\left|S_{21}\right|\) represent the reflection coefficient and transmission coefficient in the S-parameters. Since the thickness of the continuous metal film in the bottom layer of the structure is much greater than the skin depth of the THz wave inside it, the incident THz wave is completely reflected. Thus, T(\(\omega\)) is always 0 and Equation (2) can be directly simplified into \(A(\omega)=1-\text{R}(\omega)\).
# Chaotic Synchronizing Systems with Zero Time Delay and Free Couple via Iterative Learning Control
###### Abstract  
This study aims to orchestrate a less restrictive learning controller by using the iteration-varying function, the so-called iterative learning controller (ILC), to synchronize two nonlinear systems with free time delay and couple free. The mathematical theories are proven rigorously and controllers are developed for system synchronization, and then an example is forged to demonstrate the effectiveness of synchronization by the designed ILC. The ILC is designed with a feed-forward based by the error dynamics between the two considered nonlinear drive and response systems. The stability of the synchronization facilitated by the designed ILC is ensured by rendering the convergence of an error dynamics that satisfied the Lyapunov function. The Lorenz system within a drive-response system is considered as one system that drives another for the demonstration of the effectiveness of the designed ILC to achieve synchronization and verified initial conditions. Simulations are conducted for the controlled Lorenz system, and the results validated well the expected capability of the designed ILC for synchronization and matched the proposed mathematical theory.  
synchronization; chaos; Lorenz system; Iterative Learning Control (ILC); Lyapunov function; error convergent +
Footnote †: journal: Applied Sciences
# Pipe Routing with Topology Control for Decentralized and Autonomous UAV Networks +
## 3 Overview of Pheromone-Based UAV Mobility Model
The ConCov model uses artificial potential fields, along with one-hop neighbor locations and their routing information, to minimize overlap in the area sensed by neighboring UAVs, but maintain BS connectivity. The heading of a UAV is the weighted sum of repelling forces from neighboring UAVs and an attractive force to a neighboring UAV with a route to the BS. The coverage and connectivity trade-off can be tuned by adjusting the relative weight of these two forces.
# Optimization Design of the Spaceborne Connecting Structure for a Lightweight Space Camera
## 2 Connecting Structure Design Principle  
### Decomposition of Camera LOS Drift  
For an imaging system, under the influence of the external environment, the optical elements will move slightly, which makes the image of a static object move in the image plane. This phenomenon is called camera LOS drift, as shown in Figure 1. Due to the camera LOS drift, the image on the detector of the camera is not in the ideal position, and it may even move out of the image plane, which seriously affects the image quality. A typical design objective of an imaging system is to limit the drift within a small part of a pixel [12]. LOS drift can be obtained by using the ray tracing method; however, it takes much time and cannot be used in mechanical analysis. In mechanical analysis, the displacement of mirror finite element nodes can be analyzed by the finite element method. By processing the displacement data, the rigid body motions of mirrors were obtained, which reflects the amount of the camera LOS drift.  
A few remarks were made in the following regarding the relative displacements between mirrors. When the secondary mirror and primary mirror move in the same direction, it has a compensation effect on the LOS drift. On the contrary, when the displacement in the same direction is opposite, the LOS drift will increase. In addition, in the process of camera alignment, the primary mirror is generally used as the benchmark to install and adjust the secondary mirror. Therefore, by constraining the relative displacements between mirrors, the LOS drift can be suppressed.  
In this study, the aperture of the camera is 0.26 m, and the distance between the primary mirror and the second mirror is 0.40 m. Due to the influence of the external environment and thermal control accuracy of the space camera, the actual working temperature may have a maximum temperature difference of 4 \({}^{\circ}\)C (actually less than 4 \({}^{\circ}\)C). Under the influence of the temperature difference, the connecting structure deforms elastically, and the deformation between components will degrade the camera performance. In addition, the camera is also affected by 1 g gravity in the state of adjustment. After comprehensive consideration, the structure design requirements are that the relative linear displacements between the mirrors of the space camera should be no more than 10 \(\upmu\)m, and the relative angular displacements should be no more than 10\({}^{\prime\prime}\) under external loads. Considering the dynamic performance, the first natural frequency of the optomechanical structure is required to be no less than 100 Hz [13]. The relationship between the spaceborne connecting structure and camera is shown in Figure 2.  
Figure 1: Movement of an image on an image plane. (**a**) Movement in the direction perpendicular to the optical axis. (**b**) Movement in the direction parallel to the optical axis.
# TCNformer Model for Photovoltaic Power Prediction
## 2 Preliminary  
### Time Series Features of Photovoltaic Power Data  
According to the literature [29; 30], the current photovoltaic power prediction problem is usually defined as a time series data prediction problem. However, as the time granularity increases, the degree of the photovoltaic power data affected by external factors increases, and the self-similarity decreases. The basic photovoltaic power data studied in this paper are collected at a 15-min granularity, and they are greatly affected by external factors that have a certain regularity and contingency, so the statistical features of photovoltaic power data show certain periodicity, abruptness, and contingency.  
As shown in Figure 1, the 4-day power history data of a photovoltaic station were randomly selected, showing obvious periodicity and volatility.  
As shown in Figure 2, in order to explore the long-term time series features of photovoltaic power data, this study employed the classic skills of a seasonal prediction model to select the historical data of a photovoltaic power station at 8:30 for 4 consecutive years. Although they show greater volatility, a certain periodicity can still be seen.
## 5 Conclusions  
Based on the obtained research results and their analysis, the following conclusions were formulated:  
1. The results of the research have shown that vacuum impregnation under a pressure of 5 kPa significantly influences the final grain moisture. In the tested temperature range of 12-18 \({}^{\circ}\)C, during 36 h of moistening, the grain soaked and malted under atmospheric pressure reached the final moisture level of 42%. The vacuum-impregnated Kangoo grain required 6 h less soaking time. This confirms the observation of many researchers, that vacuum impregnation accelerates the mass transfer in the solid-liquid system, despite the low susceptibility of the cereal grains to grain vacuum impregnation, in relation to, for example, fruit tissues.
2. The pH value in the obtained congress wort changed, depending on all of the tested factors (pressure, temperature and malting time), during the production of malt. The wort obtained from the malt subjected to vacuum impregnation showed a greater decrease in the pH value in the range of temperature changes of 12-18 \({}^{\circ}\)C. A detailed analysis of the pH changes shows that the eight-day malting caused an excessive decrease in the pH of the wort. The analysis of the pH changes also shows that the vacuum-impregnated grain should be malted for five days.
3. It was observed that, in the wort composed of non-vacuum-impregnated malt, the value of the extract content increased twofold. Such an increase was observed at temperatures of 14-18 \({}^{\circ}\)C.
4. The vacuum impregnation of barley grain under various conditions allows us to shorten the amount of time for moistening this grain to 42% moisture content by approximately 6 h. This is the greatest advantage of using vacuum impregnation in the malting process of grain. It allows for a significant shortening of the malt production cycle, in which soaking the grain before malting is a time-consuming process.  
Conceptualization, L.R.; methodology, L.R.; software, T.G.; validation, L.R. and R.R.; formal analysis, L.R. and R.R.; investigation, M.N. and T.G.; resources, K.V.; data curation, M.N.; writing--original draft preparation, L.R. and M.N.; writing--review and editing, L.R. and R.R.; visualization, M.N.; supervision, L.R.; project administration, L.R.; funding acquisition, L.R. and M.N. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.
## 2 Related Works  
### Quantum Key Agreement: Historical Evolution and Technological Progression  
The field of QKA has undergone significant evolution since its inception, representing a paradigm shift from traditional centralized key distribution approaches toward collaborative quantum cryptographic protocols. The foundational work by [PERSON] et al. in 2004 [PERSON] et al. (2004) marked a pivotal moment in quantum cryptography by introducing the first QKA protocol utilizing Einstein-Podolsky-Rosen (EPR) pairs, establishing the theoretical framework for collaborative key generation without relying on trusted third parties.  
Following this groundbreaking contribution, the QKA landscape has diversified considerably through various technological approaches and cryptographic methodologies. [PERSON] and [PERSON] advanced the field by developing BB84-based QKA schemes [PERSON] and [PERSON] (2015), which leveraged the well-established BB84 protocol [PERSON] and [PERSON] (2015) principles while adapting them s. These protocols demonstrated how classical-quantum key distribution foundations could be extended to achieve collaborative key agreement, maintaining the security guarantees of single-party systems while enabling distributed participation.  
The progression continued with the development of Bell state-based protocols, which exploited the unique properties of maximally entangled two-qubit states to facilitate secure key generation. These approaches offered enhanced security features through the intrinsic correlations of Bell states [PERSON] et al. (2006), providing robust protection against both external eavesdropping and internal manipulation attempts. Simultaneously, researchers explored entanglement-based protocols [PERSON] et al. (2006) that utilized more complex quantum correlations, enabling sophisticated key agreement mechanisms capable of supporting larger participant groups while maintaining quantum security advantages. [PERSON] et al. (2016) propose a measurement-device-independent three-party QKA protocol using GHZ states that requires only Bell state and single-particle measurements, ensuring security and fairness while remaining experimentally feasible.  
Complementing these entanglement-centric approaches, single-particle system protocols [PERSON] et al. (2012); [PERSON] et al. (2013); [PERSON] et al. (2013) emerged as practical alternatives that avoided the technical complexities associated with entanglement generation and maintenance. These protocols demonstrated that effective QKA could be achieved using simpler quantum resources, making the technology more accessible for real-world implementations where entanglement infrastructure might be challenging to establish or maintain.
## 4 Results and Discussion
### I-V Characteristic and Static Resistance Analysis
#### 4.1.2 Static Resistance  
The static resistance of the proposed MSM diode was analyzed with varied V\({}_{\text{MSM}}\), shown in Figure 5. A nearly zero static resistance, found in the forward-biased region at greater than 2 V\({}_{\text{MSM}}\), means that it is exhibited to be a good conductor. When decreasing V\({}_{\text{MSM}}\) below the knee voltage, the highest static resistance of 97 k\(\Omega\) and 107 k\(\Omega\) at the first and second MSM diodes are found at \(-1\) V\({}_{\text{MSM}}\). However, if V\({}_{\text{MSM}}\) was further reduced, the static resistance become unstable due to its burnt indigo layers.
# A Survey of Precision Formation Relative State Measurement Technology for Distributed Spacecraft
## 2 Research Status of the Precision Formation of Distributed Spacecraft Project
### Cannyal-X  
CANYVAL-X [21] is a cooperation project between Yonsei University, the Korean Institute of Aeronautics and Astronautics, and NASA and was launched in December 2018. It consists of two cube satellites, named Tom and Jerry. One of the two satellites is used as the lens system, and the other is used as the detector system, forming a virtual telescope system, as shown in Figure 8. The mission is to verify the inertial alignment system of the target (the sun). The project utilizes a tandem telescope during the flight and observes celestial objects near the bright radiation source by blocking the radiation of the target celestial object in the line-of-sight direction of the other satellite. The relative-state measurement method of the program is based on vision measurement technology using visible light. The main satellite is fitted with a visual camera, while the slave satellite is equipped with a laser diode. The measurement of the relative state between the satellites is completed using image projection. The altitude measurement control accuracy is 1\({}^{\circ}\), the position measurement accuracy is at an approximately dm level, and the control accuracy is at approximately m level. The relative measurement accuracy is shown in the figure.