esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Satellite Image Preprocessing
#### 2.3.3 Polarization Decomposition Method  
The polarization decomposition method, which is considered an effective technique for obtaining polarization and physical features from SAR observations [44], was applied to fully polarimetric SAR data. In this study, two polarization decomposition methods were used to obtain the decomposition parameters: the Freeman-Durden [45] and eigenvalue decomposition methods [46]. The Freeman-Durden method is a decomposition algorithm based on the physical scattering mechanism model. This method divides pixels into three scattering categories: volume scattering (Vol), double-bounce scattering (Dbl), and surface or single-bounce scattering (Odd) according to the dominance of the backscatter power [45]. The total of these parameters (Span) represents the sum of Vol, Dbl, and Odd scattering power. Compared with the Freeman-Durden method, the eigenvalue decomposition method distinguishes the main scattering type and its correlation [46], rather than distributing the energy into three categories. It decomposes the coherency matrix into different eigenvector and eigenvalue set parameters, which are used to describe the scattering mechanisms. The decomposition parameters include three variables: entropy, alpha, and anisotropy. In addition, several eigenvalue set parameters (single-bounce eigenvalue relative difference (SERD) and double-bounce eigenvalue relative difference (DERD)) [47] were selected to analyze the relationships between the decomposition parameters and the LAI and biomass. The eigenvalue decomposition method was applied using PolSARPro version 5.0.
## 5 Conclusions  
In this paper, a clustering algorithm based on an improved ant colony optimization algorithm is proposed, which can meet the communication requirements of next-generation urban rail transit systems with low delay and high reliability. The proposed algorithm includes the cluster-head election algorithm CHCF, low-delay queuing algorithm LDQSP, and a routing method based on improved ACO. CHCF selects cluster heads according to node cost. LDQSP enables cluster heads to implement different queuing strategies according to service priorities to ensure the end-to-end delay requirements of higher-priority services are met. Then, the improved ACO algorithm is used to find the best route under conditions of different train locations and wireless channel quality. Finally,  
Figure 7: Throughput at different positions.  
the proposed algorithm was compared with the LEACH and AODV algorithms through simulation. The simulation results indicate that compared with the typical ad hoc network routing algorithms, the proposed algorithm in this paper can guarantee the different services' requirements, reduce the packet loss rate and end-to-end delay about by 60% and 50%, respectively, and improve the network throughput by about 40% in an urban rail transit scenario.  
Conceptualization, Z.S.; Methodology, Z.S.; Software, Z.S.; Validation, Z.H.; Resources, Z.H.; Writing--original draft, Z.S.; Writing--review & editing, L.L.; Supervision, L.L.; Project administration, L.L.; Funding acquisition, X.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Beijing Natural Science Foundation under the grant [L211002].  
Not applicable.  
Because the data in this paper will continue to be used in the future, participants of this study do not allow the data to be publicly shared.  
Author [PERSON] was employed by the company Traffic Control Technology Co., Ltd. Beijing. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 5 Evaluation
### Comparison Schemes  
The simulations employed the MHT method mentioned in Section 3 as the attack model. Three pseudonym-changing schemes were implemented to compare the performance of the proposed CPCROK scheme, as described below:  
* The plain mix-zone (MZ) scheme proposed in [30] changes the pseudonym of the vehicle when it enters the mix zone, but without any additional protection.
* The fake beacon (FB) scheme proposed in [24] generates a fake trajectory that directs the vehicle towards an alternative exit point within the mix zone, bewildering potential adversaries. This fake trajectory is carefully crafted based on the vehicle's pre-entry state and the distance between the entrance and the selected exit.
* The advanced fake beacon (AFB) scheme [24] utilizes an approach similar to the FB scheme but enhances privacy protection by generating two distinct fake trajectories with different estimated states.  
Figure 5: Five commonly encountered junction shapes utilized in the simulation. (**a**) T-junction 1, (**b**) T-junction 2, (**c**) crossroad 1, (**d**) crossroad 2, (**e**) multi-way. The red circular areas indicate the mix-zone ranges, and the green areas represent non-road regions.  
Since the traditional Kalman filter cannot provide turning information, it is unable to offer possibilities other than going straight when generating fake trajectories; therefore, there is no need for comparative analysis against the traditional Kalman filter.
## 4 Control Mechanism Transformation in New Heterogeneous Traffic Flow Environments on Urban Roads
### Critical Challenges in Heterogeneous Traffic Control  
The transformation toward intelligent connected traffic control faces several fundamental challenges that limit practical deployment. Scalability limitations emerge when extending single-intersection successes to network-level implementations, as coordination complexity grows exponentially with system size. Robustness concerns arise from the brittle nature of many AI-based control algorithms, which may fail catastrophically under edge cases or adversarial conditions not present in training data. Standardization gaps hinder interoperability between different manufacturers' systems, creating vendor lock-in situations and limiting system flexibility. Cybersecurity vulnerabilities in connected systems introduce new attack vectors that traditional traffic control systems never faced, requiring entirely new security frameworks. Equity implications of optimization algorithms may inadvertently favor certain traffic flows or user groups, potentially exacerbating transportation disadvantages for vulnerable populations.  
5 New Heterogeneous Traffic Control Mechanisms for Urban Roads in Intelligent Connected Environments  
The rapid development of intelligent connected technologies is leading major transformations in the traffic control field. Compared to traditional traffic control, intelligent connected environments enable real-time information interaction capabilities between controllers and controlled entities, making refined, proactive, and collaborative traffic control possible. This section systematically organizes and deeply analyzes new heterogeneous traffic control mechanisms in intelligent connected environments from three different levels--isolated intersections, arterials, and networks--revealing their core technical characteristics and development trends.
## 2 Methods
### Background Pollutant Concentrations  
The background pollutant concentrations used in this work were the ambient monitoring data from nearby U.S. EPA air monitoring sites. The data were obtained from the EPA Air Quality System (AQS). NOx and CO background concentrations came from monitoring data at the Carnegie Science Center site (40.4456\({}^{\circ}\) latitude, \(-\)80.0162\({}^{\circ}\) longitude), which is \(\sim\)900 m away from the Fort Pitt Tunnel. For the particle-phase OC and EC concentrations, we used the ambient monitoring data from the Lawrenceville site (40.4654\({}^{\circ}\) latitude, \(-\)79.9608\({}^{\circ}\) longitude). This site is \(\sim\)5 km away from the tunnel and is representative of urban background concentrations in Pittsburgh.  
Background CO\({}_{2}\) concentrations were measured on the campus of Carnegie Mellon University with a Li-Cor LI-820 CO\({}_{2}\) monitor at 1 Hz from 29 April to 17 May, 2014. Diurnal patterns of weekday and weekend CO\({}_{2}\) ambient concentrations were used to background correct the CO\({}_{2}\) concentrations measured in the tunnel. We assumed that these data were relevant for background correction of both spring and winter measurements.  
The pollutant concentrations measured in the tunnel were in general much larger than the ambient background concentrations. In Figure 1, we present the diurnal average fraction of background air contribution to each of the measured pollutants. The NOx background concentrations were less than 3% of the tunnel measurement, and the EC background concentrations were around 10%. CO had a higher background contribution, around 20% during the day and 30% in the early morning hours (02:00-04:00). OC and CO\({}_{2}\) had the highest contributions from the background. The OC background ratios were 40-60%.  
Figure 1: Background fraction of pollutants measured in the tunnel in the spring campaign. OC: organic carbon, EC: elemental carbon.
## 2 Materials and Methods
### Hysteresis Models
#### 2.2.2 J-A Model  
The scalar J-A model [7] is one of the most famous _physics-based_ hysteresis models that takes domain wall motion into account. The two modes of domain wall transitions (both its bending and translational motions) result in a reversible and an irreversible component of magnetization, respectively. The mutual coupling of the domains, i.e., the pinning of domain walls at impurity sites during the motion and flexibility of the domain walls, is also taken into account. The energy dissipated in overcoming these pinning sites contributes to hysteresis loss. The total magnetization inside a material is computed using an ordinary differential equation (ODE) and is given by [34]:  
\[\frac{dM(t)}{dH}=\frac{c_{J}}{1+c_{J}}\frac{dM_{an}\left(M_{s},a_{J}\right)}{ dH}+\frac{1}{1+c_{J}}\frac{M_{an}\left(M_{s},a_{J}\right)-M(t)}{\mathrm{sign} \left(\frac{dH}{dt}\right)k-\alpha_{J}\left(M_{an}\left(M_{s},a_{J}\right)-M (t)\right)} \tag{5}\]  
where \(M_{an}\) is the anhysteretic magnetization that is computed using [PERSON]'s polynomial [7], while \(M_{s},\alpha_{J},a_{J},k\) and \(c_{J}\) are the five J-A model parameters, which represent the saturation magnetization, the inter-domain coupling coefficient, the effective domain density, the energy-dissipative features in the microstructure and the reversibility coefficient, respectively [35].  
The MATLAB code of the J-A model is provided by [PERSON] in [29], where the _ode23_ function was used to solve (5) and an NLS method based on the Nelder and Mead Simplex algorithm was employed to identify the five parameters.
# Creating Welsh Language Word Embeddings
## 3 Methods
### Pre-Processing  
Given a text corpus represented as a sequence of characters, tokenisation is the task of segmenting this sequence into tokens, which roughly correspond to words. Brute-force tokenisation, which removes punctuation and then identifies tokens as continuous character sequences between white spaces, oversimplifies the task and consequently achieves subpar results [32]. For example, consider the following sentence: \"Mae'r haul yn taro'r paneli'n gyson a'n systemau'n rhedeg ar drydan wedi'i gynhyrchu y m s d'wetha' \" (Engl. \"The sun hits the panels consistently and our systems run on electricity produced in the last month\"). The use of apostrophes in this example represents three different processes. For example, 'r is a form of the definite article which must follow a vowel (e.g., mae'r and taro'r). Similarly, 'n is either a function word yn reduced following a vowel (e.g., paneli'n and systemau'n) or a possessive pronominal, in this case ein (e.g., a n systemau). Furthermore, 'i in wedi'i is another function word ei, an agreement prolific following wedi. So far, these examples represent words or grammatical items separated from other words using an apostrophe. However, the last word d'wetha' represents a different use of apostrophe, which represents a less conservative written variety of standard Welsh by omitting the sounds of the full word diwethaf and shortening it to d'wetha' as is most commonly heard in standard speech. Clearly, one cannot assume that the apostrophe represents a word boundary.  
We considered three tokenisation methods for the Welsh language. The first tokenisation method, used as a baseline, is a brute-force method consisting of the following steps. First, all characters are converted to lowercase. Next, all punctuation characters are removed. Finally, tokens are identified using white spaces. The second tokenisation method considered was the one from the Gensim library. This tokeniser returns tokens corresponding to maximal contiguous sequences of alphabetic characters. We chose not to remove accentuation from the lowercased text. The final tokeniser we considered was the one from the WNLT, which has been developed specifically for Welsh.  
Following tokenisation, we removed rarely occurring tokens using by setting a threshold at 5 occurrences. This step helps to remove misspelled words from the corpus. No stemming or lemmatisation were performed because previous studies have found that these actions remove information that can be used by machine learning to create language models [33].
# A Method for 5G-ICN Seamless Mobility Support Based on Router Buffered Data
## 2 Related Work
### Seamless Mobility Support in ICN
PMLS is used to repair old links so that connectivity to the pNAR can be maintained, and this forces the previous router to buffer interests arriving during the move, forwarding them to the producer after the handover. However, these methods currently only focus on using the buffer resources on the access device to reduce packet loss during the handover, and lack specific design solutions for buffer resource allocation.
# Eight Element Wideband Antenna with Improved Isolation for 5G Mid Band Applications
## 5 Results and Discussion
### S-Parameters  
The Anritsu S820E two-port VNA with a frequency range from I MHz to 40 GHz was used to validate the proposed antenna's scattering properties as shown in Figure 20. Figure 21 shows the simulated and measured reflection coefficients and port isolation of the proposed antenna. The antenna covers the n79 band, as can be seen from the figure, with a measured \(-10\) dB impedance bandwidth of 4.5-5.5 GHz. The port isolation of the antenna has a notable value of 24 dB throughout the operating bandwidth. The findings of the simulation and measurement agree with a small variation related to cable losses and fabrication tolerances.
# Instability and Drift Phenomena in Switching RF-MEMS Microsystems
## 6 Conclusions  
RF-MEMS switches are devices with suspended beams, intrinsically designed to be unstable. Instead of being a drawback, mechanical instability is exploited and controlled in order to switch between two electrical states that act differently on the signal line. However, in spite of the simplicity of this approach and the advantages in terms of performance, several unwanted conditions can lead to additional sources of drift and unstable behavior in these devices. The progress of research in the last decade has been very successful in preventing or minimizing these unwanted effects, especially with respect to the minimization and control of dielectric charging, but also in exploiting design solutions to increase the temperature stability and the long-term contact reliability. However, some concerns still prevent the complete elimination of reliability issues and, consequently, the full exploitation of these devices in commercial applications. Among them, some noteworthy concerns are the difficulties of an MEMS-compatible, hermetic, low-cost, wafer-level packaging, essential to avoid failure due to humidity or chemical contamination, and the scarcity of MEMS-specific methods for accelerated reliability testing. Nevertheless, some commercial RF-MEMS switches have appeared on the market and are gaining success for specific applications and uses, giving hope for the future.  
This research received no external funding.  
The author declares no conflict of interest.
## 3 Method and Materials
### Asphalt Mixture Monitoring System  
The asphalt mixture mixing monitoring system includes a data acquisition system, 5G network transmission system, and a data processing system. The mixing station data acquisition system is constructed by installing SBW series temperature transmitters next to the discharge bin and installing METTLER-TOLEDOIND series load cells and other sensing devices in the reduction bin screening system. The system automatically monitors the quality, weight, and discharge temperature of the silo aggregates in real time, and collects key data such as on sieve holes and mixture weight. The collected data are processed into an internal transmission format, and a data processing system is compiled through software engineering. The network system is constructed based on the 5G communication technology and transmitted to the data processing system through the 5G network. The data processing system analyzes the collected data. If a certain index reaches the specified threshold, the system automatically gives a warning and notifies the staff to rectify the problem through SMS or email and calculates the asphalt aggregate ratio and gradation. The system also transfers the data to a remote central server (as shown in Figure 5).
# Toward Secure Smart Grid Systems: Risks, Threats, Challenges, and Future Directions
## 8 Proposed Framework: Multi-Layer Threat-Defense Alignment Framework
### Applications of MLTDAF in Counter-Terrorism
#### 8.4.2 Enhancing Threat Detection and Early Warning  
One of the key aspects of counter-terrorism is the timely identification of threats. MLTDAF integrates advanced detection mechanisms, including machine-learning-based anomaly detection and SDN-supported traffic monitoring, which are vital in detecting covert or Advanced Persistent Threats (APTs). For example, coordinated zero-day attacks or GPS spoofing attempts can be rapidly identified by mapping irregularities to the Control Layer, enabling swift mitigation.
# Experimental Study on Slender CFRP-Confined Circular RC Columns under Axial Compression
## 7 Conclusions  
The following conclusions are obtained based on the results and comparisons of this study.  
1. The ultimate axial load of CFRP wrapped columns moderately decreases as slenderness increases. For the circular RC columns with a slenderness ratio less than 60, CFRP hoop wraps can still effectively improve the axial load-carrying capacity.
2. The ultimate axial load of CFRP-wrapped specimens and unwrapped specimens decreases by approximately 27% and 19% when the slenderness ratio increases from 12 to 56, respectively.
3. On the basis of the present study, the limit value of slenderness ratio of 26.5 is proposed for CFRP-confined circular RC columns. Slenderness effects can be neglected if the slenderness ratio of the columns is below this limit.
4. According to the equations of GB 50367, CSA S806, ACI 440, and CNR DT200, the axial load predictions of specimens are compared with test results. In the range of the slenderness ratio of the present study, ACI 440 can provide conservative predictions for the ultimate axial load of the test columns.
5. A modified equation is proposed to estimate the ultimate load-carrying capacity of CFRP-confined circular RC columns. The calculated values of ultimate load capacity agree with the experimental results by introducing the stability coefficient into the equation. The applicability of the above formula needs to be confirmed further by more research due to the limited experimental data.  
Figure 10: Prediction versus test ultimate load capacity.  
**Author Contributions:** Conceptualization, investigation, H.Y.; writing--original draft preparation, data curation, Q.L.; supervision and review, Z.H.; formal analysis, software, Y.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data used to support the findings of this study are available from the first author or the corresponding author upon request.  
**Conflicts of Interest:** The authors declare no conflict of interest regarding the publication of this paper.
## 3 Results
### Ground Vibration Test  
In the dynamic frame-by-frame imaging process, the certain error of velocity, caused by random vibration, has occurred in the mechanical structure. The error of velocity leads to the imaging shift on the camera focal plane within the exposure time, which directly causes the image blur. Therefore, it is necessary to analyze the influence of the error of velocity caused by satellite vibration on dynamic imaging.  
In the ground test platform, the multi-cycle tracking velocity is obtained, as shown in Figure 5a, where the blue curve is the actual tracking velocity, and the red curve is the ideal tracking velocity. It can be seen that there is a certain error between the actual velocity and the ideal velocity from Figure 5a. Based on the error analysis of the ground tracking velocity, the curve of the error of velocity is obtained, as shown in Figure 5b, where the error of velocity peaks at different frequencies have been marked.  
Five pieces of data are extracted in the actual error of the velocity range (0.0007577\({}^{\circ}\)/s, 0.001146\({}^{\circ}\)/s); meanwhile, the influences of different error velocities and attitude angles on the MTF of the system are analyzed in the following part.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Serial Number** & **Simulation Parameters** & **Value** \\ \hline
1 & height of the track & 500 km \\
2 & camera focal length & 0.5 m \\
3 & earth radius & 6400 km \\
4 & dynamic scan velocity & 10\({}^{\circ}\)/s \\
5 & pixel size of camera focal plane & 3.5 \(\mu\)m \\
6 & attitude angle & -50\({}^{\circ}\leq\theta\leq 50^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.