esa-sceva/satcom-chunk-collection huggingface dataset:
# A Two-Grid Interline Dynamic Voltage Restorer Based on Two Three-Phase Input Matrix Converters
## 6 TI-IDVR Control Algorithm  
The control objectives of this algorithm are the following:  
* The TI-IDVR must keep the load voltages stable at their nominal values despite the different types of disturbances (balanced and unbalanced sags and swells, voltage distortion and voltage interruption) that arise in the feeders.
* Have a good targeting of the input currents to the TI-IDVR.
* Hold the voltage waveforms of the feeders and the loads as close as possible to the sinewave.
* Maintain a power factor as close as possible to the unit in the feeders.  
The control algorithm presented meets the control objective of producing currents and voltages as close as possible to the sinewave at the input terminals of the TI-IDVR and performs a satisfactory compensation of the load voltages. By implementing this control algorithm, the TI-IDVR compensates for the disturbance present in the load with a good dynamic response. It should be mentioned that the topology of the TTI-MC and its control algorithm implemented in this work allow for a unit power factor at the terminals of the two feeders.  
Consider the following scenario for a practical application. Assume a multi-feeder system or a CPP with two feeders where each of the feeders has its own sensitive load. The TI-IDVR is connected to the two feeders so that one of the inputs of the TI-IDVR is connected to feeder 1 and the other is connected to feeder 2. In this way, the TI-IDVR can integrate the power of the two feeders to maintain the voltage of the loads at their nominal value. When there is a voltage sag in feeder 1, it is reflected in the load voltage 1. Then, the TI-IDVR takes power from both feeders to hold load voltage 1 at its nominal value.  
On the other hand, if a severe event manifests as a voltage interruption in any of the feeders, then the TI-IDVR behaves as a reconfiguration device and takes power from the healthy feeder to maintain the nominal values of the load voltage for the duration of the event. When there is no short-term disturbance in the feeders, but there is a voltage distortion or imbalance, the TI-IDVR can cope with these events and in this way, and the operating time of the TI-DVR is optimized.  
The topology of the TI-IDVR is constituted of a TTI-MC and two CSIs. In this way, the control algorithm can be divided into two parts that are synchronized with each other: (a) the control of the CSIs, and (b) the control of the TTI-MC.  
Figure 5: Carrier-based pulse width modulation (MCB-PWM) with double reference scheme for one branch of the TTI-MC. Where, \(T_{s}\) is the period of the triangular carrier signal and \(d_{3}\) and \(d_{1}\) are the duty cycles of switches S3 and S1, respectively.
## 1 Introduction
### Cyber-Physical Systems  
The combination of physical and virtual spaces is referred to as _cyber-physical systems_ (CPSs), and it aims to create a communicative interface between the digital and physical worlds by integrating computation, networking, and physical assets [5]. While the definition of CPS may vary based on perspectives and backgrounds, it is well-understood that the interconnection between the physical world is represented by hardware (e.g., sensors, actuators, robots) and cyber software (communication, networking and internet). CPS is at the core of Industry 4.0, and its success depends on the smart management of interconnected systems between its physical components and computational capabilities, utilizing state-of-the-art technology in both worlds [6].  
CPSs have been an important topic in both research and the implementation of industrial technology ever since they were first introduced. The term Cyber-Physical Production System (CPPS) is used in the manufacturing industry to refer to the most recent advancements in computer science, information and communication technologies on the one hand, and manufacturing science and technology on the other [7]. CPPSs have been used in various industries in automotive, healthcare, and energy [8; 9; 10; 11]. Further research on the sustainability of CPPS towards smart manufacturing, achieving a full life-cycle, and improving logistics, design, performance, and maintenance has been thoroughly discussed in [12] the references therein.
## 3 Applications
### Isothermal Mineral Reactions and Grain Growth
Figure 14: The evolution of the mineral fractions as a function of time during isothermal sintering of a quartz-calcite (mass ratio 1:1) green body at 848 \({}^{\circ}\)C obtained by the binary images of the single phases. The colored lines represent a linear fit to the data over the whole time interval. This example demonstrates that the growth of distinct grains can be investigated over time without the need to use a new sample for each time step, which is a major advantage over conventional quench experiments. This enables studying the mechanism(s) of nucleation and growth, the quantification of grain growth rates, the identification of rate-limiting reaction steps, and potentially the determination of activation energies from isochronal heating experiments.
## 2 Materials  
### Study Area and Reference Data  
In this research, the urban area of the city of Zagreb (Figure 1) was used for the accurate detection of individual allergenic tree species, with a focus on protected green areas, such as Botanical Garden, park Zrinjevac (Figure 1--Example subset 1), [PERSON]'s green \"horseshoe\", and parks with developed and cultivated green infrastructures, e.g., Newlyweds Park (Figure 1--Example subset 2). According to the last population census from 2021, the city of Zagreb has 769,944 inhabitants, with a positive yearly increase in the number of inhabitants. Therefore, an extent of 27.84 square km (5.80 \(\times\) 4.80 km) was used in this research, mostly focusing on the central urban part of the city of Zagreb. Zagreb'sclimate is classified as an oceanic climate (Cfb) [33] with warm summers and an average annual precipitation and temperature of 840 mm and 11.6 \({}^{\circ}\)C, respectively.  
The forest vegetation in the Zagreb county is characterized primarily by forests of pedunculate oak, narrow-leashed ash, black alder, willows, and poplars [34]. In the urban area of the city of Zagreb, birch, sycamore, plane tree, and pine are the most dominant species. According to [PERSON] et al. [2], the most allergenic plant groups are: alder, hazel, yew/cypress, birch, ash, hornbeam, grasses, elder, nettles, sweet chestnut, artemisinin, and ambrosia.  
For this research, the Web Map Service (WMS) of the Green Cadastre application was used as the reference dataset, which includes data on public green areas, playgrounds, and park equipment. The original dataset consists of 61,564 sample points, and after data filtering (e.g., trunk thickness higher than 10 cm, tree height higher than 5 m, etc.), 11,430 sample points were included as reference point data in a final model. According to [PERSON] et al. [2], three major allergenic tree species were chosen in this research, whilst the remaining tree species were categorized as other (Table 1).
# Gaining Insights into Conceptual Models: A Graph-Theoretic Querying Approach
## 6 OPM Query Implementation
### Centrality Queries
#### 6.3.1 Centrality UI Implementation  
Upon entering the \"Centrality Queries\" section in the \"OPM Insights\" feature of OPCloud, a dialog window shown in Figure 21 opens. The \"Flat Model Visibility\" property in this view has the optional values \"Hide\", which will present only the OPM things that have the highest rank, and \"Show\", which will show the flat model all grayed out, except for the highest ranking OPM things, which are colored. The \"Link Type\" property determines whether to calculate the node rank based on procedural links only, fundamental links only, or any type of link. The \"Number of Items\" property limits the list of ranked nodes in descending order based on the rank level. The \"Thing Type\" property determines whether to filter out all but processes, all but object and states or no filter at all for the rank consideration.  
Figure 21: _PageRank_ query dialog window.  
Figure 22 is an OPM model in which a **Coffee Making** process, handled by the agent **Barista**, results in the object **Coffee**. **Coffee** is consumed either by **Coffee Taking Away** or by **Coffee Serving**, handled by the agent **Waiter**. Both processes affect the object **Customer**.  
Figure 22: _Coffee Making_ OPM model.  
Figure 23a is a graph representation of the OPM model in Figure 22. Each of the highlighted graph nodes, **Coffee Serving** and **Customer**, have the maximum number of incoming links, which is 2. As _PageRank_ measures node influence, the number of links is not the only factor in the calculation.  
The influence rank of the source nodes contributes to the influence rank of the target nodes. Figure 23b is the _PageRank_ query result showing that the most influential OPM thing in this system is the object **Customer.**
## 4 Experimental Results
### Network Lifetime  
A system's life cycle is how long it can operate and fulfil a specific mission. Figure 7 compares the performance of the newly discovered approaches to the current technologies throughout a network's life cycle. The graph below shows that the suggested technique resulted in a system lifespan of 3300 rounds, significantly longer than the previous methods. As the number of nodes in a network grew, the network's lifetime decreased. The lifespan of the system using the current approach, LEACH, EECRP, FEEC-IIR, and CL-IoT, was 1500, 2800, 2500, and 3000 cycles, respectively, as mentioned in Table 5.
# Electromagnetic Field Variation of ELF Near-Region Excited by HED in a Homogeneous Half-Space Model
## 2 Propagation Model of ELF Near-Field Region Excited by HED  
The EM field model in the near-field region of ELF excited by an HED in an unbounded, homogeneous half-space medium is shown in Figure 2. The homogeneous half-space medium model can be an air-seawater or air-lithosphere model. This paper focuses on the air-seawater medium. The sea surface was taken as the \(z=0\) plane; the sea region and air region were marked as regions 1 and 2, respectively.  
Assuming that the HED antenna is located in the positive direction of the \(z\)-axis, parallel to the \(x\)-axis direction, the distance from the \(xoy\) plane, i.e., the sea level, is set as \(d\) meters; the electric moment is \(ldl\); and the distance from the observation point \(P\) to the sea level is \(z\) meters. In a cylindrical coordinate system, the coordinates of the observation point \(P\) can be expressed as \(P(\rho,\,\varphi,\,z)\). The components of each electromagnetic field at point \(P\) are shown in Figure 2. Region 1 (\(z\geq 0\)) was filled with seawater. \(\mu_{0}\), \(\sigma_{1}\), and \(\epsilon_{r1}\) are the permeability, conductivity, and relative dielectric constant, respectively, and the wave number can be expressed as \(k_{1}=\sqrt{\epsilon_{r1}}\omega/c\), where \(\omega\) is the angular frequency and  
Figure 2: Model diagram of the ELF near-field region excited by HED.  
is the speed of light. Region 2 (\(z\leq 0\)) is an air medium with a permeability, conductivity, relative permittivity, and wave number of \(\mu_{0}\), \(\sigma_{2}\), \(\varepsilon_{r2}=1\), and \(k_{2}=k_{0}=\omega/c\), respectively. \(\rho\) is the propagation distance between the projection point of the electric dipole source and the observation point \(P\), and \(r_{1}\) is the geometric distance between the electric dipole source point and the observation point \(P\) in seawater. For low-frequency electric dipole excitation, which varies with the time harmonic factor \(e^{-j\omega t}\), the integral expression of the EM field generated in region 1 (\(z\geq 0\)) is given in [PERSON]'s work [13] and will not be repeated here. The approximate analytical method is used to simplify the Sommerfeld integral of the ELF near-field region EM fields in homogeneous half-space seawater and derive its approximate analytical expression for the EM fields.
# A Survey on MLLMs in Education: Application and Future Directions
## 3 Applications of MLLMs in Education
### Grading and Assessment Tools
#### 3.6.3 Examples of Applications  
Several applications and systems illustrate the use of MLLMs in grading and assessment. Automated essay scoring (AES) systems, such as E-Rater by ETS, employ NLP techniques to assess essays in standardized tests, evaluating features such as grammar, usage, mechanics, style, and development. Short-answer scoring (SAS) systems assess brief responses to questions, requiring models to understand and evaluate the correctness and relevance of concise student inputs [97]. Code assessment platforms, including systems like MOSS (Measure of Software Similarity) [101] and CodeRunner, utilize AI to evaluate programming assignments, checking for correctness, efficiency, and plagiarism [102]. Handwritten response grading involves AI models processing scanned images of handwritten math or short-answer responses, interpreting handwriting and assessing correctness. Oral language proficiency testing is seen in applications like Duolingo English Test, which use speech recognition and MLLMs to evaluate language proficiency through spoken responses [43]. Multimodal assignment evaluation includes tools that assess student presentations or projects combining text, visuals, and audio, using MLLMs to analyze each component and the overall coherence.
# IAQ Prediction in Apartments Using Machine Learning Techniques and Sensor Data
## 3 Methods
### Prediction Model Validation  
A rigid and comprehensive cross-validation procedure was applied to achieve an exhaustive performance evaluation of all MLTs included in our analysis. The schema explaining this procedure is shown in Figure 3.  
The cross-validation procedure consisted of five folds. In a single fold, the data from four apartments were used for model training, and the data from one remaining apartment were applied for model testing. In each fold, the data used for testing were associated with a different apartment.  
By applying the presented cross-validation approach, we asked about the common character of the relationship between the IAQ in the kitchen and in the living room in various apartments. If confirmed, the MLT models could be claimed as having high generalization potential and being applicable in different apartments than those providing data for model training.
###### Abstract  
We propose a new method of fabricating metal-polymer composite targets for sputtering, which makes it easier to control the composition and enables the homogeneous and reproducible fabrication of metal-polymer nanocomposites over large areas. Using Cu/polytetrafluoroethylene composite targets containing 20, 50, and 80 wt.% Cu, Cu/plasma polymer fluorocarbon (PPFC) nanocomposite thin films were prepared by radio-frequency (RF) sputtering. Targets with 80 wt.% Cu were conductive; moreover, sputtering was possible not only with RF but also with mid-range frequency (MF) and direct current (DC) power sources. The nanocomposite thin film deposited by MF and DC power using an 80 wt.% Cu target showed near-metallic characteristics, exhibited absorption peaks at 618 and 678 nm, and had a surface resistance of 2 \(\times\) 10\({}^{4}\) and 34.55 \(\Omega\)/sq, respectively. We also analyzed the structure and composition of the Cu/PPFC nanocomposite films by X-ray diffraction and X-ray photoelectron spectroscopy. The described metal-polymer targets can advance the applications and commercialization of nanocomposite thin films.  
Cu/polytetrafluoroethylene composite target; plasma polymer fluorocarbon; nanocomposite thin film; sputtering power source; surface plasmon resonance +
Footnote †: journal: Applied Physics Letters
## 6 Conclusions  
This paper investigates the stability of VSC-HVDC operation in a bidirectional power flow mode. DC cable length affects the reverse power transmission power of the system. An improved virtual impedance control strategy is presented to increase the reverse power transmission power of the system. A system stability analysis based on the impedance model is applied to the proposed control strategy. System stability is affected by the power flow, controller parameters, DC cable length, and DC side capacity.  
1. DC-side oscillation occurs when the transmission power of the system is large. The maximum transmission power of a DC voltage-controlled converter to a power-controlled converter is less than that in the opposite transmission direction.
2. The shorter the DC cable is, the more easily the oscillation of DC voltage will occur.
3. The smaller the DC side capacity is, the more easily the oscillation of DC voltage will occur.
4. The weaker the AC grid strength is, the more easily the DC side oscillation will occur.
5. Appropriate virtual impedance parameters can improve system stability. The phase margin of the system is insufficient to suppress DC-side oscillation when the virtual impedance parameter is small. If the virtual impedance parameters, \(R_{eq}\) or \(L_{eq}\), are too large, then the system will enter a new unstable state.  
The simulation results show that the proposed improved control strategy can eliminate the steady-state error of DC voltage caused by virtual impedance and maintain the advantage of a virtual impedance strategy to improve system stability. The proposed control method has better dynamic performance compared to the traditional control method.  
All the authors have contributed to this paper in different aspects. [PERSON] proposed the original concept and wrote the original draft. [PERSON] acted as supervisor and gave suggestions on paper improvement. [PERSON], [PERSON], and [PERSON] helped with software simulation and methodology improvement.  
This research was funded by [Nation Key Research and Development Program of China] grant number [2017 YFB0903700] And The APC was funded by [2017 YFB0903700].  
The authors declare no conflict of interest.
## 4 Delay Compensation Controller Based on Model Prediction
### Simulation Test of Delay Compensation Controller under Sinusoidal Motion Condition  
During the simulation test, the acceleration of the vehicle followed a sinusoidal function with an amplitude of \(1.5\) m/s\({}^{2}\) in real time. Figure 8 shows the acceleration simulation under different delays. Initially, the vehicle travelled at a constant speed of \(10\) m/s before transitioning to sinusoidal acceleration after \(3\) s. The performance of the delay compensation controller was then tested under three different conditions: no delay, a delay of \(0.7\) s and a delay of \(1.4\) s.  
Figure 8: Acceleration simulation under different delays.  
Figure 7: Delay compensation for twin test vehicle.  
Under a delay of 0.7 s, the acceleration curve lags without delay but still maintains a sinusoidal function form. The result meets the requirements of the twin test vehicle. Under a delay of 1.4 s, the acceleration curve significantly lags without delay. Furthermore, there is significant distortion when reaching the first wave peak and trough. In order to evaluate the performance of the delay compensation controller, the goodness-of-fit (R\({}^{2}\)) needs to be calculated. Under a delay of 0.7 s, R\({}^{2}\) is 0.826, which is a significant improvement compared to an R\({}^{2}\) of 0.636 under a 1.4 s delay. The result shows that the compensation effect is better under a 0.7 s delay.
## 3 The Procedure of TC Center Estimation
### Stage 2: Precise Estimation  
1. Determining SSWD points and candidate points: Centered on the coarsely estimated TC center position, a sub-SAR image with a coverage of \(L_{1}\)\({}^{\circ}\)\(\times\)\(L_{1}\)\({}^{\circ}\) is extracted from the original SAR image. At this stage, the coverage of the candidate area is also \(L_{1}\)\({}^{\circ}\)\(\times\)\(L_{1}\)\({}^{\circ}\). Subsequently, employing intervals of \(m_{2}\) and \(M_{2}\), grids for SSWD points and candidate points are created, resulting in grid sizes of \(\frac{L_{1}}{m_{2}}\)\(\times\)\(\frac{L_{1}}{m_{2}}\) and \(\frac{L_{1}}{M_{2}}\)\(\times\)\(\frac{L_{1}}{M_{2}}\), respectively. In this stage, \(L_{1}\) is set to \(1.2\)\({}^{\circ}\), \(m_{2}\) to \(0.01\)\({}^{\circ}\), and \(M_{2}\) to \(0.005\)\({}^{\circ}\);
2. SSWD retrieval and quality control: Centered on these points, image slices with dimensions of 1000 \(\times\) 1000 pixels are extracted from the sub-SAR image. The SSWDs are then retrieved from these image slices by the ILG method. Subsequently, Equation (1) was used to remove outliers of retrieved SSWDs. In this stage, \(A\) is set to 5, and the SSWD is removed if \(S>0.5\) or \(S<0.001\);
3. Estimating the TC center position: A total of 121 compensation angles within [\(-50\)\({}^{\circ}\), \(10\)\({}^{\circ}\)] were set at an interval of \(0.5\)\({}^{\circ}\). For each compensation angle, the retrieved SSWD is adjusted by adding the compensation angle. Subsequently, the perpendicular lines of these compensated SSWDs are obtained, and the number of these perpendicular lines passing through each candidate point is counted.  
Figure 3: Variation in maximum values in heatmaps by compensation angles. The vertical blue and orange lines represent the compensation angle corresponding to the peak values of the curves. (**a**) TC Noru; (**b**) TC Doksuri; (**c**) TC Koinu. The global maximum values of the first stage (Stage 1) occurred at \(0.5\)\({}^{\circ}\), \(-16.5\)\({}^{\circ}\), and \(-17.5\)\({}^{\circ}\), respectively, and the corresponding heat maps are shown in Figure 4; the global maximum values of the second stage (Stage 2) occurred at \(-0.5\)\({}^{\circ}\), \(-27.5\)\({}^{\circ}\), and \(-23.0\)\({}^{\circ}\), respectively, and the corresponding heat maps are shown in Figure 5.
## 3 Performance Evaluations  
In this section, we evaluate the performance of the proposed communication and sensing system using a PN code that can be generated, as described in Section 2.2. First, the performance of the proposed ISAC system is investigated in an additive white Gaussian noise (AWGN) channel (no fiber). Then, the ISAC system performance is evaluated with a fiber channel. For that purpose, the system model is implemented using photonics technology, and the evaluation is conducted using VPIphotonics 11.4 software and lab experiments.
## 3 Results and Discussions
### Supervised Classification
This is evident in the change in the annual maximum temperature averages and precipitation, Figure 7, which shows the annual maximum temperature average in the period of 1981-2016, for some cities in the area of the marshes in southern Iraq (Chibayish, Shatra, Amara, Souq al Shoyokh, Maimona, Nasseriya, Qurna and Qalat Saleh). Figure 8 illustrates the annual precipitation average for the same time period and sites. The above two figures show that there has been a clear change in the maximum temperature that has risen in all sites, indicating that the marshes are affected by climate change. The trend line in marshes for the last 40 years shows a weak decrease in precipitation only in 2 cases of 8 stations; but in all cases, recent years were very dry, which has had a significant impact on Iraq's available water imports and reduced water supply to the marshes. Figure 5: _Cont._  
Figure 5: Supervised classification for Iraqi southern marshes: (**A**) Landsat 2 in 1977, (**B**) Landsat 8 in 2017 and (**C**) Sentinel 2 2017. Figure 6: Comparison between areas of land covers classes in Iraqi southern marshes for three satellite images in 1977 and 2017. Figure 7: Changes of the Annual maximum temperature average in period of 1981–2016. Figure 8: Changes of the Annual precipitation average in period of 1981–2016.