esa-sceva/satcom-chunk-collection huggingface dataset:
# Automated Pixel-Level Deep Crack Segmentation on Historical Surfaces Using U-Net Models
## 4 Experimental Results  
In this study, simulation experiments were performed on a Kaggle kernel with an NVIDIA TESLA P100 GPU and 16 GB memory. The proposed approach was designed with Tensorflow and Pytorch using a Python environment on the Linux platform. To evaluate the proposed models, five performance metrics, namely accuracy, precision, recall, Dice coincidence index (Sorensen similarity coefficient), Jaccard coefficient, and IoU, were calculated according to Equations (11) to (16), respectively [30].  
\[Accuracy=\frac{TP+TN}{TP+FN+TN+FP} \tag{11}\]  
\[recall=\frac{TP}{TP+FN} \tag{12}\]  
\[precision=\frac{TP}{TP+FP} \tag{13}\]  
\[Dice_{index}=\frac{2\cdot Precision\cdot Recall}{Precision+Recall} \tag{14}\]  
\[IoU=\frac{GroundTruth\cap Prediction}{GroundTruth\cup Prediction} \tag{15}\]  
\[Jaccard=\frac{TP}{TP+FP+FN} \tag{16}\]  
The _TP_, _FP_, _TN_, and _FN_ terms are defined as follows:  
* _True Positive (TP)_: the pixel is a crack and is classified as a crack;
* _False Positive (FP)_: the pixel is intact and is classified as a crack;
* _True Negative (TN)_: the pixel is intact and is classified as intact;
* _False Negative (FN)_: the pixel is a crack and is classified as intact.
## 3 Forensic Human Identification through the Analysis of Biomedical Images
### AI-Based Approaches for Comparative Radiography
#### 3.3.2 3D-2D Approaches for Comparative Radiography
Once AM (X-Ray) and PM (CT) data are segmented (either automatically or manually), both are superimposed using an evolutionary image registration algorithm. Three main interconnected blocks are represented: (i) The transformation to obtain a projection of the 3D model; in this example, the geometric transformation includes translation (tx, ty, and tz), rotation (rx, ry, and rz), and source to image distance (SID). (ii) The similarity metric that compares the PM projection and the AM segmentation considering an occlusion region (i.e., where the frontal sinuses are occluded or not clearly defined). (iii) The optimization process to estimate the nine parameters of the transformation that are only limited by the context and expert knowledge from the X-ray acquisition protocol. Figure 6: Diagram showing the approximation followed in [147]. A deep ConvNet is trained to segment frontal sinuses in skull radiographs. A real outcome of the network is displayed on the right, where the frontal sinus, the occlusion region, and the segmentation error are displayed in blue, green and red, respectively. The frontal sinus is an anatomical region of extremely diffuse boundaries and complex morphology. In fact, its lower limit overlaps other anatomical structures, hardening the segmentation process.
## 3 Proposed Real-Time Shipping Container Accident Inference Edge System
### Transmission Message and Dashboard in Operation and Management  
This subchapter defines the method and message structure for transmitting the results of container accident risk classification. The communication between the edge server, which is an AI-based safety evaluation system, and the operation and management server and DB server uses the HTTP protocol based on TCP/IP communication. In addition, the edge server transmits the inference results in the message, and the communication method is set to send the message after establishing a connection with the server. Figure 8 shows the basic message structure. The message consists of a message-length field that allows us to input the length information of the message content field and a message content field that allows us to input the risk assessment results and images used in the assessment. In addition, as shown in Figure 8, the risk assessment result generated by the AI-based inference model is sent by inputting the binary information and the length value of the JSON file into the text area field as well as the length information of the image area field and the image value to be stored in the image area field into the image area field.  
Figure 9 shows the dashboard in the operation and management server of the RSCAIES. The operation and management server displays dangerous areas and safe areas based on the risk assessment results and location information inferred and transmitted by the edge server at the location of the containers in the port, and it utilizes the results to prevent container accidents.
## 3 WSAN System Models
### Modified AODV over IEEE 802.15.4 for Building Temperature Control
#### 4.2.1 Design Concepts  
As we know from the simulation results described in the previous subsection, the original AODV routing protocol makes the decision to change a route too late. It tries to select the lower path although it experiences the unsuccessful transmission of packets, which results in an uncontrollable system and high power consumption. In addition, the previous results also give the information that route changes can improve both the control output and the energy consumption. The path without the high traffic interruption is the better choice for data transmission. According to this knowledge, a design concept  
Figure 8: _Cont._of how the routing algorithm can automatically avoid selecting a path with the high traffic interruption is presented. In this work, a delay-time for the RREQ message transmission between any pair of connected nodes is an indicator used for detecting any congested connection [28]. On the congested link, incoming RREQ messages in buffers will wait for a longer time before they are sent in comparison with the case of no congestion. For this reason, we propose that the considered link is assumed to be congested if the delay-time for the RREQ message transmission is higher than a predefined threshold, and the receiving node in that link will not process the RREQ message further. By this technique, the congested paths will not be selected for data transmission. How the routing algorithm is performed according to the design concept is described below.
# A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models
## 5 Fair Editions of Ensemble Models  
This section provides a succinct overview of ensemble-based algorithmic variants introduced in the literature. Table 4 highlights the core characteristics and comparative features of each method.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Key Idea** & **Fairness Metric(s)** & **Datasets** & **Remarks** \\ \hline AdaFair [23; 24] & \begin{tabular}{c} AdaBoost extension \\ reweighting instances for fairness and accuracy; \\ dynamically optimizes \\ weak learners \\ \end{tabular} & \begin{tabular}{c} Equalized Odds, \\ Statistical Parity, \\ Equal Opportunity \\ \end{tabular} & \begin{tabular}{c} Adult, Bank, \\ COMPAS, \\ KDD Census \\ \end{tabular} & \begin{tabular}{c} AdaFair integrates fairness \\ into the boosting loop \\ \end{tabular} \\ \hline FAIRGBM [25] & \begin{tabular}{c} Adds convex fairness \\ constraints into GBDT via \\ Lagrangian optimization \\ \end{tabular} & \begin{tabular}{c} Equal Opportunity, \\ Equalized Odds \\ \end{tabular} & \begin{tabular}{c} ACS Income, Adult, \\ Account \\ Opening Fraud \\ \end{tabular} & \begin{tabular}{c} FairGBM outperforms \\ similar by achieving high \\ fairness without significant \\ performance loss \\ \end{tabular} \\ \hline Fair XGBoost [26] & \begin{tabular}{c} XGBoost with fairness \\ regularizer controlled by \\ hyperparameter \(\mu\) to reduce \\ correlation with \\ sensitive attributes \\ \end{tabular} & Disparate Impact & \
\begin{tabular}{c} Adult, COMPAS, \\ Default, Bank \\ \end{tabular} &
\begin{tabular}{c} Each dataset responds \\ differently to \(\mu\) tuning \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of fairness-aware ensemble methods.
## 3 Results and Discussion
### Design Review with Back-Analysis
#### 3.3.1 The Hoek-Brown Constitution Model  
The MC constitutive model assumes a linear elastic-perfectly plastic stress-strain relationship exists, but this assumption does not fully account for the wide range of stress levels in exposed rock masses. The Mohr-Coulomb (MC) strength criteria have been widely utilized in many classical analytical expressions and numerical modeling studies [36] because they can be physically computed simply and easily comprehended, although they are not appropriate for defining the failure envelope of rock masses. The analysis of rock slopes is complicated by the existence of heterogeneous and discontinuous rock masses with bedding planes, joints, faults, and fractures [37].  
The HB constitutive model, on the other hand, provides a superior non-linear stress-strain relationship for rock masses [38]. Therefore, the new design was developed using the HB constitutive model. The HB constitutive model requires six key parameters to define the stress-strain relationship of the rock. These parameters are the elasticity modulus of the rock mass (E), the uniaxial compressive strength of the intact rock (\(\sigma_{\text{cl}}\)), Poisson's ratio (\(v\)), the disturbance factor (D), the geological strength index (GSI), and the empirical model parameter of the intact rock (m\({}_{\text{i}}\)).  
The Hoek-Brown failure criterion is expressed in Equation (9) as the non-linear relationship between large principal stress and small principal stress values. (Tensile stresses are positive values, and compressive stresses are negative values.)  
\[\Delta\mu\epsilon=\text{B}_{\text{f}}-\text{B}_{\text{i}}*\text{C}_{\text{f}}* \text{G}_{\text{f}} \tag{10}\]  
The value of m\({}_{\text{b}}\) is defined as the rock coefficient (Equation (11)) depending on the rock discontinuity content.  
\[\text{m}_{\text{b}}=\text{m}_{\text{i}}\text{e}^{\frac{\text{GSI}-100}{28-1 \text{D}}} \tag{11}\]  
Auxiliary parameters with s and a values are defined in Equations (12) and (13).  
\[\text{s}=\text{e}^{\frac{\text{GSI}-100}{9-3\text{D}}} \tag{12}\]  
\[\text{a}=\frac{1}{2}+\frac{1}{6}\Big{[}\text{e}^{\frac{-\text{GSI}}{23}}- \text{e}^{\frac{-20}{3}}\Big{]} \tag{13}\]Parameters s and a are used to define a material's behavior. The inclusion of these factors provides a more realistic representation of rock mass behavior than the MC model.
# Simulation Study on Ground Vibration Reduction Measures of the Elevated Subway Line
## 4 Conclusions  
This paper establishes the train-track-viaduct rigid-flexible coupling dynamics model as the vibration source model and the pier-soil-building finite element model as the transmission path model, carries out a simulation study on the ground vibration caused by the metro vehicle running on the viaduct line in a nearby building, and analyzes the vibration reduction effect of the different vibration reduction schemes. The effects of train  
Figure 17: Ground vibration results before and after the installation of continuous support: (**a**) time domain results; (**b**) frequency domain results.  
Figure 18: Ground vibration acceleration results before and after installation of continuous support: (**a**) time domain results; (**b**) frequency domain results.  
running speed, fastener stiffness, track vibration damping pads, and track continuous support on ground vibration were analyzed, and the following conclusions were made.  
1. Because the building is close to the line, the ground vibration requirements near the building are high, and the existing line vibration reduction design cannot meet the environmental requirements.
2. When the train running speed is reduced to 30 km/h, the ground vibration can meet the environmental limit value requirements, but the actual operating speed of the train has a greater impact. When applying vibration-damping fasteners alone, the system has the best vibration-reducing performance when the vertical stiffness of fasteners is 10 kN/mm, but it still cannot meet the requirements of ground environmental limits.
3. A simulation study on the vibration reduction effect of track vibration reduction pads and a continuous support vibration reduction structure was carried out. The results show that when the vehicle running speed is 65 km/h, the vibration reduction effect of the track vibration reduction pad is outstanding, and the margin to meet the vibration limit value is larger; the vibration reduction effect of the continuous support vibration reduction structure is obvious, and the vibration reduction effect of the joint application of the fasteners and the continuous support vibration reduction structure can satisfy the vibration limit value requirement and have a reasonable margin.  
Conceptualization, H.W. and Z.T.; methodology, H.W.; software, L.L.; formal analysis, H.W.; investigation, X.H. and H.L.; data curation, Z.T.; writing--original draft preparation, H.W. and L.S; writing--review and editing, H.W.; visualization, H.W.; supervision, L.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article, and further inquiries can be directed to the corresponding author.  
Author [PERSON] and [PERSON] were employed by China Harbour Engineering Company Limited. The remaining authors declare that the re-search was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# A Hybrid Encryption Scheme for Quantum Secure Video Conferencing Combined with Blockchain
## 4 Our Construction
### QKD Real-Time Monitoring  
The QKME sets \(T_{start}\) as the start time of heartbeat monitoring, \(T_{current}\) as the current system time, \(T_{cread}\) as the current system time of reading the file size, and \(T_{csend}\) as the current system time of sending the heartbeat command. At regular intervals, the QKME sends \(T_{Hearbeat}\) to the user, and the user sets the longest waiting time of heartbeat \(T\). If \(T\geq T_{Hearbeat}\), the QKD network runs normally; otherwise, the video conference system displays the QKD network abnormality in the main interface. See Algorithm 3 for the specific flow of the real-time monitoring algorithm.
## 4 Design Architecture
### Distance Comparison Unit
#### 4.1.3 Threshold Checker  
Since in practical applications only results with a low Hamming distance (highly similar signatures) are of interest, the threshold checker is used to filter the results by comparing them with a threshold value, which can be set at runtime. The advantage is that very long distances, which are not of interest, are omitted, saving memory and time when the results are read. The threshold can be set dynamically at runtime, which offers the possibility to read all results, e.g., for testing purposes.
# Demand Flexibility: A Review of Quantification Methods, Models, and Required Data
## 4 Discussion
### Applications of Flexibility Quantification
#### 4.1.4 Policy Development  
Finally, flexibility quantification can be used for policy development [8; 10; 22; 38; 39; 68]. By informing policymakers of the opportunities available through demand-side flexibility and benefits gained by the grid, more effective policies can be proposed to support or require the integration of flexibility into all demand sectors. Similar to the development of building performance standards (BPSs) and other decarbonization initiatives, scientific research can be used to inform the development of policies that can require and incentivize certain actions by building owners and operators [68]. Flexibility provides alternative pathways to DSM than efficiency measures that may not be suitable for all applications. Similar to informing statutory decisions, stakeholders such as grid operators could implement flexibility quantification techniques to inform the integration of flexibility into energy markets [10; 22; 23; 25; 37; 49; 50; 58]. By illustrating the value of this resource and understanding its availability, system operators can work with policymakers to develop technical and policy practices to support this integration. However, this requires a deep understanding of the spatiotemporal variability and availability of the resource. If developed properly, demand flexibility can be a major component for day-ahead and balancing markets as well as ancillary service markets where various services such as frequency regulation, load following, and voltage control are offered. Policy and system support for this resource can help ensure ease of implementation at all levels, from individual building operations to the entire energy market.
## 4 Algorithms for TSOAP
### Breaking Symmetry
Such a reduced task set would then have a _reduced hyperperiod_\(h_{r}\) defined as follows:  
\[h_{r}=lcm(h_{1},\ldots,h_{n}) \tag{19}\]  
Equation (18) defines a hyperperiod that contains no symmetries; since \(h_{r}\leq h\) (and in most cases \(h_{r}<<h\)) an alternative formulation to decide TSAFP would be to perform hyperperiod simulation using \(\tau\)'. To show that such an algorithm is proper, from (12) and (13) it would need to be shown that \(\tau\)' contains all (and only) those task congruences that are present in \(\tau\). **Theorem 5**: \(\tau\)' contains all (and only) those task congruences that are present in \(\tau\). **Proof**: By showing that \(gcd(p_{1},p_{2})=gcd(h_{1},h_{2})\). Let \(x=gcd(p_{1},p_{2})\) and \(y=gcd(h_{1},h_{2})\). From (18) and by the definition of \(lcm\), we have \(h_{1}=ax\) and \(h_{2}=bx\), where \(a\) and \(b\) are some positive (non-zero) co-prime integers. Then we have \(y=gcd(ax,\,bx)\); since \(a\) and \(b\) are co-prime, by definition \(gcd(ax,\,bx)=x\). Since we have that in fact \(y=x\), the Theorem is proved. This shows that all task congruences are preserved by using such a method, and no further congruences are introduced. It can be noted that this also gives a fast and effective way to detect instances which can be decided rapidly using traditional means, for example equivalent synchronous systems; _i.e._, those in which all periods are co-prime, or task sets with high degrees of harmonic coupling. The LCS algorithm can be modified to detect such instances as follows: if \(nh\)' \(<<2^{n}\) then hyperperiod simulation is used; else the procedure defined in Section 3 is used. However, early experience with LCS indicates that in the average case, a more suitable test can be \(nh\)' \(<np_{Max}\), where \(p_{Max}\) is the largest of the task periods.
# Compact Beam-Scanning Reflectarray Antenna with SLL Reduction Using In-Plane Panel Translations
## 4 Experimental Validation
This contrasts with more complex mechanical implementations, such as systems employing multiple moving components like [22] or feed translations like [23]. These more complex systems benefit from a more flexible antenna geometry that enhances their scanning performance at the expense of added complexity. Some of the listed designs like [17; 19] overcome their mechanical complexity by targeting fixed multi-beam configurations using multiple coexisting feeds, as opposed to having a single feed capable of facilitating the smooth, continuous steering of the beam. Compared to the entries listed, the presented design achieves the highest gain (31.6 dBi) while maintaining the smallest focal ratio (\(F/D=0.47\)) and very low scanning losses. A particularly relevant entry is [27], which uses a similar scanning mechanism using a rollable panel instead of a moving one. Compared to [27], our design achieves a significantly higher maximum gain (exceeding it by more than 6 dB), a lower scan loss over the same scanning range, and improved aperture efficiency, all while using a more compact and structurally efficient configuration. However, because of this compact structure, side lobes are increased even after the SLL mitigation stage used during the design process. Figure 8: Measured in-band scanning performance. Figure 9: Broadband demonstrator performance in terms of the maximum and minimum beam levels within the optimized panel translation range.
## 3 Underwater Acoustics Channel Statistics
### Temporal Coherence Coefficient  
The time variation of the channel is defined in terms of the temporal coherence, which describes the coherence degree of the channel within a certain time. The temporal coherence is defined as [23]:  
\[\rho(n,\Delta n)=\Bigg{\langle}\frac{\sum\limits_{m=1}^{M}h^{*}(n,m)h(n+\Delta n,m)}{\sqrt{\sum\limits_{m=1}^{M}\left|h(n,m)\right|^{2}\sum\limits_{m=1}^{M} \left|h(n+\Delta n,m)\right|^{2}}}\Bigg{\rangle}, \tag{7}\]  
where \(\langle\cdot\rangle\) denotes the ensemble average over time sampling index \(n\). \(h(n,m)\) and \(h(n+\Delta n,m)\) denote the CIRs measured at time sampling index \(n\) and \(n+\Delta n\), respectively. \(M\) denotes the number of taps used in the calculation and \(*\) denotes the conjugation operation.
###### Abstract  
This paper aims to improve the source tracking efficiency of distributed vibration signals generated by phase-sensitive optical time-domain reflectometry (\(\Phi\)-OTDR). Considering the two dimensions (time and length) of \(\Phi\)-OTDR signals, the authors saved and processed these signals as images after particle filtering. The filtering method could save 0.1% of hard drive space without sacrificing the original features of the signals. Then, an integrated feature extraction method was proposed to further process the generated image. The method combines three individual extraction methods, namely, texture feature extraction, shape feature extraction and intrinsic feature extraction. Subsequently, the signal of each frame image was recognized to track the vibration source. To verify the effect of the proposed method, several experiments were carried out to compare it with popular and traditional approaches. The results show that: Hard drive space is greatly conserved by saving the distributed vibration signals as images; the proposed particle filter is a desirable way to screen the vibration signals for monitoring; the integrated feature extraction outperforms the individual extraction methods for texture features, shape features and intrinsic features; the proposed method has a better effect than other popular integrated feature extraction methods; and, the signal source tracking method has little impact on the positioning accuracy of the vibration source. The research findings provide important insights into the source tracking of \(\Phi\)-OTDR signals.  
Keywords:phase-sensitive optical time-domain reflectometry (\(\Phi\)-OTDR); image-based signal storage; integrated feature extraction; vibration source tracking +
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