esa-sceva/satcom-chunk-collection huggingface dataset:
# A Polarization-Dependent Frequency-Selective Metamaterial Absorber with Multiple Absorption Peaks
###### Abstract  
A polarization-dependent, frequency-selective metamaterial (MM) absorber based on a single-layer patterned resonant structure intended for F frequency band is proposed. The design, fabrication, and measurement for the proposed absorber are presented. The absorber's absorption properties at resonant frequencies have unique characteristics of a single-band, dual-band, or triple-band absorption for different polarization of the incident wave. The calculated surface current distributions and power loss distribution provide further understanding of physical mechanism of resonance absorption. Moreover, a high absorption for a wide range of TE-polarized oblique incidence was achieved. Hence, the MM structure realized on a highly flexible polyimide film, making the absorber suitable for conformal geometry applications. The proposed absorber has great potential in the development of polarization detectors and polarizers.  
absorber; metamaterial; multi-band absorption; polarization-dependent Article
## 2 Antenna Design and Analysis
### MIMO Configuration  
MIMO technology has the capacity to improve communication systems by enhancing link quality, minimizing the impacts of multipath fading, and increasing spectral efficiency [19]. In this section, we extend the 2 \(\times\) 1 antenna array to a two-port MIMO antenna with a size of 126 \(\times\) 63 mm\({}^{2}\). Initially, the two antennas were designed in series with a common partial ground plane (109 \(\times\) 27 mm\({}^{2}\)), as illustrated in Figure 8a. As depicted in Figure 9, the isolation between ports reached 7 dB within the desired bands, which falls far below the acceptable value of 15 dB required for optimal MIMO antenna performance. To enhance the isolation, a rectangular slot was introduced in the middle part of the ground plane, as shown in Figure 8b. By adding this slot, the isolation improved significantly from 7 dB to 20 dB, as demonstrated in Figure 9. The presence of the slot changed the distribution of the electromagnetic fields and disrupted the electromagnetic coupling between antenna elements by modifying the current paths on the ground plane [20]. This modification led to reduced mutual coupling and interference, thus enhancing isolation. For additional insight, a completely separated ground plane structure was employed to examine its impact on isolation, as depicted in Figure 8c. In Figure 9, it is evident that the separated ground planes resulted in decreased isolation in both the lower and upper frequency bands compared to the partial slotted common ground plane. Thus, for better isolation a 16.5 \(\times\) 21.3 mm\({}^{2}\) rectangular slot was etched on the ground plane. The width and length of this rectangular slot were carefully optimized to enhance isolation while maintaining dual-band behavior. Since there should be a ground plane under the 75 ohm transmission lines feeding the antennas, the width of the ground plane was ensured to be twice the width of these lines on the sides, and the remaining parts in between were emptied. As the common ground plane contributed to lowering the isolation compared to the separated one, the depth of the slot (21.3 mm) was made as deep as possible without compromising the electrical common ground plane.  
Figure 8: Two-element MIMO antenna design: (**a**) partial common ground plane; (**b**) partial slotted common ground plane (proposed); (**c**) partial separated ground plane.
## 5 IPv6 in Networking  
IPv6 plays a crucial role in enhancing load-sharing and link-failure systems by providing advanced capabilities that improve network resilience and efficiency. The expanded address space of IPv6 allows for a more extensive allocation of IP addresses, facilitating the distribution of network traffic across multiple servers or routes. This scalability ensures balanced resource utilization, reduces congestion, and enhances overall network performance.  
IPv6 also includes features like Stateless Address Auto Configuration (SLAAC) and Duplicate Address Detection (DAD), which are essential for link-failover systems. These features enable devices to automatically configure their IPv6 addresses and detect address conflicts, ensuring smooth transitions between alternative paths during link failures. The flexibility and adaptability of IPv6 contribute to continuous connectivity and efficient resource usage in dynamic network environments.
## 3 Results  
A mannequin phantom was used to evaluate the accuracy of the developed method for recording and reproducing the NHP. The phantom CT data were obtained at an arbitrary position in the CT coordinate system. The calibration plate and the phantom were optically scanned sequentially using a 3D scanner. At that time, the phantom was set to be parallel to the global horizon, and this posture was defined as the NHP of the phantom. The coordinate system of the 3D scanned model was oriented to the global coordinate system immediately by applying the orientation information from the calibration plate. As a result, the scanned phantom model was also aligned with the global horizon by applying the same orientation as in the calibration (Figure 3c,d). Then, we automatically determined the transformation of the phantom CT model into the scanned NHP model by registration between the CT model and the NHP model using the modified CPD method (Figure 4). The deviation errors associated with the registration were expressed as color mapping (Figure 5). The mean deviation error was 0.26 \(\pm\) 0.25 mm, and the positive and negative definite deviations were lower than one millimeter for most of the patients (Figure 5). We reproduced the phantom CT model in the NHP by applying the rotation from the registration to the CT model (Figure 6). For five patients with severe and mild facial asymmetries, we recorded the NHP of each patient once, and reproduced the patients' CT head model in the NHP using the same method (Figures 5 and 7).  
Figure 4: The phantom shown before rotation of the 3D CT model (in yellow) into the 3D calibrated scanned model (in red) (**a**), after rotation by coarse registration between the two models using a principal component analysis (PCA) (**b**), and after rotation by fine registration using CPD (**c**).  
Figure 5: Three-dimensional registration error based on the modified CPD in the mannequin phantom (**a**) and in the patient (**b**).  
Figure 6: The phantom CT model shown before (**a**,**c**) and after (**b**,**d**) NHP rotation.  
Figure 7: Patient CT head models shown before NHP reproduction (**a**) and after NHP reproduction (**b**) for patients with severe and mild facial asymmetries.  
We evaluated the differences between true and calculated orientations in the roll, pitch, and yaw directions (Table 1). The mean angle differences were \(-0.05\pm 0.13^{\circ}\), \(0.08\pm 0.22^{\circ}\), and \(-0.05\pm 0.18^{\circ}\) in the roll, pitch and yaw directions, respectively, and the those of the worst case were \(-0.23^{\circ}\), \(0.40^{\circ}\), and \(-0.32^{\circ}\). The measured roll, pitch, and yaw directions were not significantly different from the true directions assessed by one-sample \(t\)-tests (\(p>0.05\)).
# A Quantum-Resistant FHE Framework for Privacy-Preserving Image Processing in the Cloud
###### Abstract  
The advent of quantum computing poses an existential threat to the security of cloud services that handle sensitive visual data. Simultaneously, the need for computational privacy requires the ability to process data without exposing it to the cloud provider. This paper introduces and evaluates a hybrid quantum-resistant framework that addresses both challenges by integrating NIST-standardized post-quantum cryptography with optimized fully homomorphic encryption (FHE). Our solution uses CRYSTALS-Kyber for secure channel establishment and the CKKS FHE scheme with SIMD batching to perform image processing tasks on a cloud server without ever decrypting the image. This work provides a comprehensive performance analysis of the complete, end-to-end system. Our empirical evaluation demonstrates the framework's practicality, detailing the sub-millisecond PQC setup costs and the amortized transfer of 33.83 MB of public FHE materials. The operational performance shows remarkable scalability, with server-side computations and client-side decryption completing within low single-digit milliseconds. By providing a detailed analysis of a viable and efficient architecture, this framework establishes a practical foundation for the next generation of privacy-preserving cloud applications.  
fullly homomorphic encryption; post-quantum cryptography; image processing; cloud security; privacy-preserving computation; CRYSTALS-Kyber; CKKS
# Land Suitability Mapping Using Geochemical and Spatial Analysis Methods
## 4 Results and Discussion
### Element Content in the Soil of Study Area and Source Apportionment  
#### 4.2.1 Cadmium  
All soil samples in the Ioannina plain contained Cd content well above European topsoil's median value [58] (Table 1). The geochemical spatial distribution map of Cd included in the Geochemical Atlas of Europe [58] indicated Cd content in the soil of the study area varying between 0.37 and 0.83 mg kg\({}^{-1}\), while this study revealed that Cd range for soil is 0.3-5.1 mg kg\({}^{-1}\) (Table 1). Cadmium content in soil ranging from 2.5 to 5.1 mg kg\({}^{-1}\) is observed at sampling sites located parallel to the Ioannina plain's north-eastern edge, especially in the proximity of the airport of Ioannina city (Figure 5A,B). According to [PERSON] [55], the phosphoric rocks can be considered as a lithological source of Cd in the soil of the Ioannina basin. The spatial distribution of Cd concentration in soil at the Ioannina basin does not demonstrate a significant association of Cd contents with a geological formation outcropping in the area studied (Figure 5B).  
Many researchers [31; 63] have studied Cd contents in the vicinity of roadways and reported a direct link between Cd and traffic emissions, supporting the suggestion that vehicles are an additional Cd contamination source for topsoil of the study area. Moreover, Cd is mainly found in automobile paints and is employed extensively in automobile radiator fine stock and batteries [64], suggesting that vehicle crushing and dismantling activities occurring at the eastern part of the study area promotes the emission of Cd. Furthermore, [PERSON] et al. [64] recorded significant differences between Cd content in plants collected inside (0.612 mg kg\({}^{-1}\)) and outside (0.484 mg kg\({}^{-1}\)) a scrapyard of discarded vehicles at Zaraq city (Jordan). The primary anthropogenic sources of Cd in sampling locations parallel to the north-eastern edge of the Ioannina plain (Figure 5A,B) can be attributed to (a) automobile emissions; (b) airborne contamination related to airport activities; and (c) emissions from vehicle crushing and dismantling industry (e.g., shredder residues particles, batteries).  
According to [PERSON] et al. [65], the Cd emissions related to aircraft engines' function is up to 0,0146 mg Cd per 1 kg of combusted fuel. Atmospheric deposition of Cd in the soil in many airports as an environmental impact related to air-traffic activities is also reported by [PERSON] et al. [66]. In the western edge of the Ioannina basin, Cd concentration in soil ranges from 1.1 to 5.1 mg kg\({}^{-1}\) (Figure 5A,B), which is mainly attributed to (a) vehicle emissions and (b) emissions related to airport traffic.
## 3 Experiment  
### Datasets and Experimental Setups  
The experiments in this study were conducted on a system equipped with an Intel(R) Core(TM) i7-9750H CPU @ 2.60 GHz (Intel, Santa Clara, CA, USA) and a single NVIDIA GeForce GTX 1660 Ti GPU (NVIDIA, Santa Clara, CA, USA). Filtering operations on digital images were performed using the PyTorch v1.13.1 deep learning framework. The joint estimation of the PRNU fingerprint and camera source identification was carried out in the Matlab2022a software package. The performance evaluation of the proposed algorithm for PRNU fingerprint extraction was conducted on two publicly available datasets. A comparative analysis with several similar algorithms was performed using ROC curves and Kappa values as evaluation metrics. The DAXING [19] and DRESDEN [20] datasets fully encompass real-world scene images of different lighting conditions, degrees of blurriness, and image textures.
# One-Class LSTM Network for Anomalous Network Traffic Detection
## 4 Experimental Setup
### Compared Methods
#### 4.1.3 One-Class LSTM (OC-LSTM)  
Unlike one-class deep SVDD and other deep baseline models, OC-LSTM is an end-to-end training network and does not rely on a pretrained model. The original data were fed as input to a feed-forward neural network consisting of a single LSTM layer, along with linear activation functions, as recommended in [20] for producing the best results. The number of hidden units within each LSTM cell of the model \(h\in\{32,\,64,\,128,\,256\}\) was tuned via a grid search. Note that the main reason for using an LSTM layer instead of other types of layers is that the experiment in [21] proved that LSTM is a better feature extractor for structured data. The extracted features were then fed into a classification network that was characterized by a fully connected neural network. The fully connected layer (followed by a softmax regression layer) assigned a confidence score to each feature representation and the output of the classification network was the confidence score. The learning and drop-out rates were sampled from a uniform distribution in the range [0.01, 0.001] in order to obtain the best performance. The optimal value of the parameter \(v\in[0,\,1)\) was set according to the respective outlier proportions. The Adam optimizer was used to minimize the squared error loss, and the other parameters were set to their default values. The entire network was trained end-to-end using the loss function as described in Equation (6).
## 7 Practical Applications of NCS
### Manufacturing Systems  
With the growth in economic processes that specialize in high price with low volume, the producing system design is growing from ancient centralized model to the distributed model and then proceeds to the modern networked system/model. In present situations, the producing systems are designed as in a networked model framework with the help of networking communication systems which consist of the diverse collections of manufacturing devices. Such a type of modern networked producing system monitors and controls by provision of maximizing the standard of service provided by the prevailing manufacturing resources [83].  
A typical Industrial Manufacturing Control System is shown in Figure 18 [161]. It consists of large number of control loops, Human-Machine Interface (HMIs), remote diagnostics section, sensors, and actuators, built on layered network architectures, with the help of networked layer. A control loop consists of sensors, actuators, and controllers to deploy certain controlled processes. A sensor is a device that produces a measurement of some physical property and then sends this information as controlled variables to the controller. The controller interprets the signals and generates corresponding manipulated variables, based on a control algorithm and target set points, which it transmits to the actuators. Actuators are used to deploy the controlled processes based on the commands being received through the controller.  
Although Radio-Frequency Identification (RFID) is widely used for the application of asset tracking, it requires a power supply for the operation. But, for some cases, where is no power supply available, such as monitoring the activities of the aircraft cabin's maintenance workers, wireless sensor networks (WSN) is the best choice for workers as it requires no power supply [83].
# Learning-Based Branching Acceleration for Unit Commitment with Few Training Samples
## 4 Branching Acceleration for Unit Commitment
### The Branching Acceleration for UC Framework
#### 4.3.3 Testing Phase  
In the testing phase, branching acceleration for UC is used to efficiently solve UC problems (testing samples). The method employs the enhanced pruning policy to make additional pruning decisions for each node that the original pruning policy has not pruned. The testing process is presented in detail in Algorithm 3.  
For the B&B search tree, an overly conservative pruning policy may preserve too many nodes, leading to increased computational costs, while an overly aggressive pruning policy risks failing to yield a feasible solution. Therefore, this paper aims to dynamically control the search space during the testing phase to strike the optimal balance between performance and computational cost.  
Fortunately, neural network classifiers can achieve this ideal process by setting a threshold \(\wedge\). The output \(e\) is a two-dimensional vector, where the values represent the probabilities of preserving and pruning the current node, respectively. These probability values are compared against the threshold to determine the policy action (preserve or prune). For instance, if \(e_{2}\geq\wedge\), the node is pruned; otherwise, it is preserved. A pruning policy with higher thresholds tends to preserve more nodes, achieving better performance but expanding the search space. If the testing phase fails to produce feasible solutions, iteratively increasing the threshold has proven highly effective in numerical studies.  
```
1. problem list \(\Psi=\{\ \}\), node number \(n=0\), testing iteration \(h=0\), upper bound \(UB=c^{*}=+\infty\), initial threshold \(\wedge\);
2. \(N_{1}{\rightarrow}W_{1}{\rightarrow}\Psi\), \(\Psi=\{W_{1}\}\);
3. **while**\(c^{*}=+\infty\)do
4. \(h=h+1\);
5. if\(h\
eq 1\)then
6. \(n=0\), increasing the \(\wedge\);
7. end if
8. while\(\Psi\
eq\mathcal{O}\)do
9. \(n=n+1\);
10. Pop the node relaxed problem \(W_{n}\) from \(\Psi\) and solve it \(\to x_{n}^{*}\), \(v_{n}^{*}\), \(s_{n}\);
11. if\(x_{n}^{*}[a],\forall a\), is an integer then
12. \(UB=c^{*}=\min(UB,\ v_{n}^{*})\);
13. else
14. if\(v_{n}^{*}<UB\)then
15. \(\kappa(s_{n}){\rightarrow}e\);
16. if\(e_{2}\geq\wedge\)then
17. \(r_{n}=1\);
18. else
19. \(r_{n}=0\), two children nodes of \(N_{n}{\rightarrow}\big{(}N_{n}^{1},\ N_{n}^{2}\big{)}{\rightarrow}\big{(}W_{n }^{1},\ W_{n}^{2}\big{)}{\rightarrow}\Psi\);
20. end if
21. end if
22. end while
24. end while
```  
**Algorithm 3** The testing process of branching acceleration for UC
# Integration Between Serious Games and EEG Signals:
## 6 Challenges and Future Research Directions  
The field of integrating serious games with EEG signals presents many technical, methodological, and usability challenges. One of the main challenges is related to the accuracy and reliability of real-time EEG systems. The individual variability of brain signals makes it difficult to obtain consistent and highly accurate results, especially in applications requiring complex control, such as interactive games. In addition, adapting EEG signal processing algorithms that can be generalized to different users, rather than requiring extensive customization, is an important area for improving the accessibility and functionality of these applications.  
From a methodological point of view, another obstacle is the lack of standardization in the design of experiments and data collection. Many ongoing studies use different approaches and parameters, limiting the comparability and reproducibility of results. The establishment of common experimental protocols and standards would facilitate the integration of results and collaboration between research groups, contributing to more consistent progress in this area.  
On the other hand, designing an optimized interface and user experience remains a challenge. Despite advances in EEG technology, the interface must be intuitive and attractive to users, ensuring that the learning process is effective without distractions and interaction difficulties. A promising direction in this area is to combine EEG with emerging technologies such as virtual reality or augmented reality, which can improve immersive experiences and potentially learning outcomes.  
Regarding future research directions, the need to study physiological and psychological aspects of users is emphasized in order to better understand how interaction with serious EEG-based games can affect learning and cognitive development. This would include measuring aspects such as cognitive load and attention levels, which could be correlated with game performance and learning outcomes. Finally, the creation of interfaces compatible with cloud computing will increase the flexibility and scalability of EEG systems, facilitating the analysis of large amounts of data and improving the availability of these technologies in educational and therapeutic contexts.
# Sliding Mode Control of Servo Feed System Based on Fuzzy Reaching Law
## 1 Introduction
To solve the jitter problem, domestic and foreign scholars have tried to reduce jitter by reconstructing sliding modes, constructing state observers and adjusting sliding mode parameters [18; 19; 20]. The main methods are the dynamic sliding mode method [21], the improved convergence law parameter method [22], the quasi-sliding mode boundary layer thickness adjustment method [23], the signal filtering method [24], and the applied interference observer method [25]. They all weaken the jitter phenomenon to some extent. Among them, the design of convergence law can not only improve the motion quality when the sliding mode function converges to the sliding mode surface, but also can effectively reduce the jitter. In the literature [26], an improved fast approximation law is proposed to shorten the time to reach the slip surface and speed up the convergence of the system. In the literature [6], a new segmentation function is applied to the power convergence law to replace the symbolic function in the traditional sliding mode control, which improves the speed of system convergence to the sliding mode surface and effectively reduces the high frequency chattering of the system. An adaptive timing fault-tolerant control scheme is proposed in the literature [27]. Using inverse trigonometric functions, a new double power convergence law is constructed to reduce the chattering phenomenon while accelerating the state stability. In the literature [28; 29], an improved power exponential convergence law sliding mode velocity controller was designed to adjust the convergence law parameters of the sliding mode control using the integral term and fuzzy control, which not only improved the convergence velocity but also weakened the chattering to some extent. In the above-mentioned literature, some scholars have not conducted experimental studies on the adopted convergence law method, and the convergence law is less applied in the sliding mode control of servo-feed systems. In this paper, we address the problem of fixed convergence parameters in the traditional exponential convergence law, which leads to large sliding mode jitter and tracking errors, and use fuzzy algorithm to soften the sliding mode control signal from the perspective of combining sliding mode variable structure control with intelligent algorithm. An adaptive fuzzy sliding mode controller (FSMC) is designed for the position tracking control of a servo-feed drive system. Experiments are conducted to verify the effectiveness of the designed control strategy compared to PID controllers and sliding mode controllers.