esa-sceva/satcom-chunk-collection huggingface dataset:
# Recycling Waste Paver Blocks in the Manufacture of New Concrete Paver Blocks and Building Bricks
## 3 Results
### Water Absorption  
Water absorption is considered an indirect indicator of the durability of concrete mixtures as it measures the volume of permeable pores [24]. The water absorption of concrete mixtures containing RB, RC, and RG increased with an increasing replacement ratio. It seems obvious that the water absorption of mixtures is influenced by that of recycled materials (Figure 8). The water absorption of NS used in this study was 1.48%, and the water absorption of the reference mixture made with NS was 5.02%. The mixture using RB with a water absorption of 7.70% had the highest absorption in the range of 6.97-7.65%, followed by the RC-based samples (water absorption of 5.64%) at 6.03-7.35%. For the RG series, even though the material had the lowest absorption of 0.56%, the absorption of the mixture containing RG was 5.73-6.31%, which was higher than that of the reference mixture. This increase in absorption can be explained by the material geometry and particle size. Compared to NS, GP has rougher and more angular geometry, and more than 90% of its particle size is less than 75 \(\upmu\)m. The increased specific surface area of RG increases the water demand due to increasing water absorption [1; 25].  
The water absorption test results for all concrete mixtures meet the standards for different applications. For concrete paving blocks and structural and exterior building bricks, the water absorption should be less than 7%. The non-load-bearing internal building bricks allow up to 13% water absorption. According to the standard, all concrete mixtures except RB-20, RB-30, and RC-30 can be used as paving blocks and building bricks for load-bearing structures. RB-20, RB-30, and RC-30 are not acceptable as paving blocks but are suitable internal building bricks with non-load-bearing structures.
## 3 Methods and Materials
### CNN Models with SVM
#### 3.3.2 SVM Algorithm  
SVM is an algorithm for solving regression and classification tasks. SVM aims to find a line or hyperplane in N dimensions to classify the features of WSIs clearly [37]. The best option for the algorithm to choose a hyperplane is the maximum margin between classes; in other words, the best hyperplane that has the maximum distance from it to the data points close to the classes, which is called the hard margin or maximum hyperplane margin [38]. SVM has the advantage of ignoring outliers (outliers) by finding the best hyperplane that increases the margin. So SVM finds the maximum margin between classes and handles any type of feature; this margin is called soft margin. But if the data are not linearly separable, the algorithm creates a new variable by the kernel with the creation of a new variable function of distance to the original. The nonlinear function is known as the kernel [39]. The kernel is a function that converts low-dimensional spaces into high-dimensionality, transforming nonlinear separable data into separable data [40]. Figure 3 illustrates the framework of the hybrid technique for diagnosing WSIs of abnormal cell types for the cervical cancer data set. Note that the VGG-16 and GoogLeNet models receive optimized WSIs - and extract high-dimensional feature maps. The PCA method [41] was used to reduce high-dimensional features and store them in feature vectors, to classify feature vectors by feeding them to the SVM classifier.  
Figure 3: Framework of hybrid technique for diagnosing abnormal cell images for the cervical cancer data set.
# Retractable Wireless Charging Windings for Inspection Robots
## 3 Design and Simulation of Retractable Wireless Power Transfer Coils
### Impact of Structural Materials  
In practical implementation, the presence of metallic structural components near the WPT coils such as elements of the retractable scissor-linkage frame or the robot chassis can significantly affect the electromagnetic performance of the system. These nearby conductive materials may induce eddy currents when exposed to alternating magnetic fields, leading to additional energy losses, the distortion of magnetic field distribution, and undesirable thermal effects. While the current study primarily focuses on validating the mechanical feasibility and electromagnetic performance in ideal conditions, the integration of metal structures warrants further investigation.  
Figure 7: (**a**) Lateral misalignment along the x–axis between Tx and Rx coils. (**b**) Angular misalignment around the z–axis (Rx coils are rotated around the z–axis).  
In a recent study [34], a comprehensive analysis of thermal risks in wireless EV charging systems under spatial misalignment was conducted, illustrating how metallic components can exacerbate local heating and reduce system efficiency. Although the study targets higher power EV applications, the modeling approach and analysis of dynamic spatial variation are directly applicable to WPT systems in mobile robots. Future development of the retractable WPT system will consider such effects through electromagnetic and thermal simulation, with the aim of introducing material shielding strategies or structural redesigns to mitigate performance degradation caused by metallic proximity.  
Figure 8: Lateral misalignment vs. \(k\) along the linear translation of the following: (**a**) x–axis. (**b**) y–axis. (**c**) z–axis. Angular misalignment vs. \(k\) rotation about the following: (**d**) x–axis. (**e**) y–axis. (**f**) z–axis. (Each coil iteration represented by the number of edges).
## 1 Introduction
Recent studies have confirmed that GY plays a key role in enhancing the strength of cement-stabilized clays through the formation of pore-filling ettrinigite, which contributes to a denser and more homogeneous soil matrix [20]. Additionally, its application in geotechnical engineering has proven beneficial not only for mechanical improvement but also for reducing environmental impact, despite its low global recycling rate [21]. However, its performance under environmental stressors such as freeze-thaw and wet-dry cycles is highly dependent on the presence of cement, as GY alone does not provide sufficient durability in aggressive conditions [22]. Among bio-based stabilizers, Xanthan gum (XG) has attracted considerable interest due to its biodegradable nature, energy efficiency, and low carbon footprint. This extracellular biopolymer, secreted by Xanthomonas camepstris, improves soil cohesion by forming viscous bonds between particles, generating dense and resistant matrices [23; 24]. It has been demonstrated that even at low concentrations (0.25% to 1.5%), XG significantly improves UCS, stiffness (UPV), and tensile strength, especially under longer curing times. SEM analyses have confirmed increased matrix densification, and the porosity/binder ratio (\(\eta/B_{iv}\)) has been shown to be an effective indicator of mechanical behavior, with a reported characteristic x value of 0.04 for XG-treated soils [25, 26]. According to [PERSON] et al. [25], the combination of XG with polypropylene fibers (XG-PPFs) represents a synergistic solution for soil improvement. While XG acts as a cohesive agent filling voids, the fibers provide mechanical reinforcement, distributing randomly and preventing weak planes. Recent studies show that the combined use of 1-5% XG with 0.5% PPF increases strength by more than 50% and improves stiffness by up to 63%, depending on compaction level and curing time. These improvements have been verified through UCS, UPV, and microstructural analyses [25]. The present study aims to compare the mechanical properties of strength and stiffness of clayey soil from Cartagena de Indias (Colombia), stabilized using two different approaches: (i) the incorporation of construction waste materials--crushed limestone waste (CLW), ground glass powder (GG), and recycled gypsum (GY)--combined with Portland cement (PC), and (ii) the application of xanthan gum (XG), both individually and in combination with polypropylene fibers (XG-PPFs). Geotechnical and physicochemical characterization tests were performed on the materials, and cylindrical specimens were prepared using different mixtures. These specimens were cured for 28 days under controlled laboratory conditions and subsequently subjected to unconfined compressive strength (UCS) and ultrasonic pulse velocity (UPV) tests to evaluate their mechanical performance. Additionally, the porosity/binder index (\(\eta/B_{iv}\)) was calibrated for each mixture, with the aim of developing a comparative and predictive tool for assessing the geotechnical behavior of soils treated with different stabilizing agents.
# IDSMatch: A Novel Deployment Method for IDS Chains in SDNs +
###### Abstract  
With the surge in cyber attacks, there is a pressing need for more robust network intrusion detection systems (IDSs). These IDSs perform at their best when they can monitor all the traffic coursing through the network, especially within a software-defined network (SDN). In an SDN configuration, the control plane and data plane operate independently, facilitating dynamic control over network flows. Typically, an IDS application resides in the control plane, or a centrally located network IDS transmits security reports to the controller. However, the controller, equipped with various control applications, may encounter challenges when analyzing substantial data, especially in the face of high traffic volumes. To enhance the processing power, detection rates, and alleviate the controller's burden, deploying multiple instances of IDS across the data plane is recommended. While deploying IDS on individual switches within the data plane undoubtedly enhances detection rates, the associated costs of installing one at each switch raise concerns. To address this challenge, this paper proposes the deployment of IDS chains across the data plane to boost detection rates while preventing controller overload. The controller directs incoming traffic through alternative paths, incorporating IDS chains; however, potential delays from retransmitting traffic through an IDS chain could extend the journey to the destination. To address these delays and optimize flow distribution, our study proposes a method to balance flow assignments to specific IDS chains with minimal delay. Our approach is validated through comprehensive testing and evaluation using a test bed and trace-based simulation, demonstrating its effectiveness in reducing delays and hop counts across various traffic scenarios.  
attack; forwarding traffic; intrusion detection; load balancing; SDN; matching problem Article
# Leveraging IPv6 and ICMPv6 for Delay-Tolerant Networking in Deep Space
## 3 Architecture Proposal
### Custom ICMPv6 Messages  
As previously identified, the status report messages defined in RFC9171 [10] for BPv7 lack an IP equivalent. Our proposal is to leverage the ICMPv6 functionalities outlined in RFC4443 [20] to signal DTN-specific information using a mechanism similar to status report. This effectively allows the upper layer to implement retransmission-based end-to-end reliability using the reported information. Next, we present the type and codes of the proposed ICMPv6 messages; its payload; a routing, processing, and security concerns discussion; and a control flow example.
## 5 Approaches of Optimal State Estimation Utilizing Filtering
### Kalman Filter (KF)  
Kalman Filter (KF) is additionally known as linear quadratic estimation (LQE), which is named after [PERSON] in the first development of state estimation in the 1960s. It is an algorithm that uses a series of measurements that may be observed over time [30,107,108].  
Kalman Filtering Algorithm  
The Kalman filter (KF) uses feedback control to estimate the state of a target. It estimates the process state at a given time and then receives feedback in the form of measurement noise. As a result, the Kalman filter equations are divided into two categories: (i) time update equations (_Prediction_), and (ii) measurement update equations (_Correction_). (i) _Prediction_ : The time update equations are in charge of projecting the current state and error covariance estimates forward at a time in order to obtain a priori estimates for the next time stage. (ii) _Correction_ : The feedback--that is, integrating a new measurement into the a priori estimate to produce an improved a posteriori estimate--is handled by the measurement update equations. Time update equations are also known as predictor equations, while measurement update equations are known as corrector equations. Indeed,  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Approach** & **Advantages** & **Drawbacks** \\ \hline \multirow{3}{*}{Taylor Series} & Easy to find the spread of the solution; and easy & Complex mathematically, compared to simple plotting of lines of position (LOP) [101,102]. \\  & detect-converge failure [101,102]. & Lines effect in-sample error and the maximum likelihood \\  & estimator can develop by a & \\  & considerable variety of estimation & \\  & situations [77,103]. & \\  & It may use instead of MLE in many non-linear statistical & Need synchronization between all sensors, affected by NLOS errors, and more than two sensors are needed [76,85]. \\  & software packages [76,85]. & Difficult to achieve the exact \\  & & weights, only estimated weights \\  & & compared to the LS estimator [87]. & are taken into account and \\  & & affected by NLOS errors [87]. \\  & & Any unsuitable choice will make \\  & & it difficult for the genetic \\  & & algorithm to converge, or it may \\  & & \\  & & generate meaningless \\  & results [105]. \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison between several approaches of optimizing geolocation and target tracking.  
as shown in Figure 19, the final estimation algorithm resembles a predictor-corrector algorithm for solving numerical problems [107].
# Interaural Coherence Estimation for Speech Processing in Reverberant Environment
## 3 Numerical Experiment and Results
### IC Estimation Performance Comparison with Conventional Method
In most of the diffuse speech bins, the conventional method estimated the IC accurately. As a result, the proposed method accurately estimated the IC of the direct speech bins including the boundaries, but the conventional method accurately estimated the diffuse speech bins. Figure 5: Averaged MACtotal using STFT with a 64-ms Hamming window, 16-ms hop length, and 1024-point FFT for 1680 speech samples of conventional and proposed methods in (a) 0.37 s, (b) 0.69 s, and (c) 0.79 s of RT60. Figure 6: The spectrogram of (**a**) clean speech and (**b**) reverberant speech with 0.79 s of RT60, calculated by STFT with a 25-ms Hamming window, 10-ms hop length, and 512-point FFT. From the clean speech, (**c**) the binary mask of direct speech was determined. The interaural coherence (IC) of time–frequency bins was estimated by (**d**) the proposed method and (**e**) the conventional method with optimal parameters. (**f**) The difference in coherence accuracy between each method.
# Research on Networking Protocols for Large-Scale Mobile Ultraviolet Communication Networks
## 3 Network Performance Analysis
### Network Performance
#### 3.2.2 Inter-Path Interference  
During the data transmission process, different transmission paths avoid mutual interference through the \"isolation zone\" formed by the silent nodes. However, due to the random movement of nodes, when the work nodes originating from different transmission paths become adjacent again, mutual interference is bound to occur, resulting in the failure of data transmission.  
In each transmission path, the total number of nodes in the work state is \(m+1\). Consequently, the total number of nodes in the work state across \(M\) transmission paths is \(M(m+1)\).  
Interference only occurs between pairs of nodes in the work state from different paths. The total number of node pairs can be determined by Equation (4):  
\[C(S,2)=\frac{S(S-1)}{2}\approx\frac{S^{2}}{2}. \tag{4}\]  
Since the two nodes in the node pair belong to different transmission paths, with \(d_{0}>A\). With the movement of the nodes, interference occurs when \(d_{0}-r\leq A\).  
\[P_{\text{interfere,pair}}(d_{0})=\int_{d_{0}}^{\infty}f(r)dr=\exp(-\frac{(d-A) ^{2}}{4v^{2}t^{2}})\approx\frac{A}{2 vt},\;\;vt\ll A. \tag{5}\]  
By means of the approximation of the small probability event, the probability of no interference can be obtained.  
\[P_{\text{no\_interfere}}=(1-P_{\text{interfere,pair}})^{C(S,2)}\approx 1-\frac{n^{2 }A}{4 vt}. \tag{6}\]
## 3 Results
### Practical Demonstration  
To ensure practical relevance, the project includes practical cases at ten factories. The factories are part of the HORSE Project consortium, as discussed in Section 2.2. In the HORSE Project, these factories provide first-hand experience of the transition to smart manufacturing. The project extensively utilises the factories to identify scenarios as the representatives of manufacturing practice. Detailed process models were developed by the researchers and accepted by the appropriate factory managers to be used for demonstrations of the HORSE System. The authors documented the evolution from initial observations to executable manufacturing process models in [76]. Table 3 provides a summary of the ten practical cases, with a short problem description and an explanation of the benefit of BPM in each case. Only the TRI case is discussed in detail in this article, but ample information on the other nine cases is given on the project website. The case study performed at Thomas Regout International (TRI) is the most substantial and significant of the practical evaluations. Located in Maastricht, The Netherlands, TRI is a global leader in the design and production of highly customisable, industrial-grade telescopic slides. Telescope slides are the components that allow drawers and cabinets to protrude and contract. A typical slide consists out of three metal profiles and two ball-bearing cages. Although a slide only consists of five parts, all those parts can be extensively customised. As a result, TRI can produce approximately 900 variances in the telescopic slides.
## 4 Results and Discussion
(**a**) Measurement of the execution time of [PERSON]’s algorithm, (**b**) Measurement of the execution time of [PERSON]’s method. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**System Configuration**} & **[PERSON]** & **[PERSON]** \\ \cline{2-3}  & **Time (μs)** & **Time (μs)** \\ \hline A & 186.1 & 169.8 \\ B & 668.1 & 389.3 \\ C & 1400 & 699.2 \\ D & 1100 & 607.3 \\ E & 15,900 & 4500 \\ F & 110,600 & 18,300 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Microcontroller unit (MCU) implementations results. the RS(255,223) configuration, the time needed to get a valid result with [PERSON]'s method is three times lower than that required with [PERSON]'s algorithm. To better appreciate these results, the execution times are also compared in Figure 13.  
Considering the overall results, it appears that the conclusions drawn by [PERSON] et al. in the paper introducing their method are fully valid only in the case of MCU implementation. In case of FPGA (or in general parallel architectures), the choice between [PERSON] and [PERSON]'s algorithms depends on what optimization strategy has to be followed. If the output delay is a strong constraint, [PERSON]'s method should be preferred, owing to the minor delay required. However, if a circuit with less occupied area is needed, [PERSON]'s method is the better choice.
## 5 Conclusions  
In this paper, the laser processing of groove structures on silicon carbide surfaces was studied, blowing-assisted laser processing was proposed to improve processing quality of microstructures, and comparative experiments between conventional and blowing-assisted laser processing of groove structures was carried out. The specific conclusions are summarized as follows:  
1. In conventional laser processing of silicon carbide material, white silicon dioxide products form and accumulate around the processing area with the increase of processing times, which can hinder further material removal and affect the processing quality of groove structures.
2. Blowing assistance can remove the oxidation products from the processing area to avoid accumulation and improve the laser processing capability of microstructures. Compared with conventional laser processing, blowing-assisted laser processing can machine deeper and narrower groove structures with higher quality.
3. Array structures of 1 mm \(\times\) 1 mm \(\times\) 0.658 mm can be processed on silicon carbide surfaces by a nanosecond laser assisted by blowing.  
Figure 12: Surface and cross-section of array grooves of 1 mm \(\times\) 1 mm processed with different times by blowing-assisted laser processing. (**a**) 100 times, (**b**) 150 times, (**c**) 200 times.  
The influence of blowing on the thermodynamic equilibrium of ablation reactions of silicon carbide requires further analysis in the future.  
Conceptualization, S.Z., B.H.; Investigation, J.L., J.Y.; Writing--original draft preparation, J.L., B.H.; Supervision, G.C.; Project administration, G.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study, and written informed consent has been obtained from the patients to publish this paper.  
The authors declare no conflict of interest.
# The Holistic Perspective of the INCISIVE Project--Artificial Intelligence in Screening Mammography
## 3 Data Preparation and Integration
### Annotation and De-Identification Tools  
#### 3.2.1 Annotation  
INCISIVE creates a data repository that consists of four different types of cancer (lung, colorectal, breast, and prostate) and six imaging modalities (MRI, PETCT, CT, MG, US, histopathological image, and X-ray), so further actions are required to ensure high quality in the annotation procedure amongst different data providers. The segmentation of organs and tumors, understood as the delineation of these structures, can be divided into three types, mainly depending on the degree of automation of the process and intervention of the clinical user: manual, semi-automatic, and automatic. Three types of annotations were initially planned:  
* classification where the whole image is assigned a corresponding label;
* bounding box where a rectangular region of interest is assigned a corresponding label;
* segmentation where each pixel is assigned a corresponding label.  
Figure 1: The data collection schema.  
Figure 2: Data preparation workflow.  
A set of labels was decided cooperatively with all the data providers for each combination of imaging modality and disease type used in INCISIVE.  
The tool adopted for the segmentation process was ITK-Snap. The results of the annotation process were exported as a NIFTI file and named using the following information:  
* SiteID is completed from each data provider (e.g., 001 for CERTH, 002 for ICCS, etc.).
* PatientID is created by the de-identification procedure, which took place before annotation (e.g., 000001, 000002).
* Modality is completed from each data provider (e.g., MRI, PETCT, CT, MMG, US, HP).
* Timepoint (BL, TP1, TP2, TP3).  
The medical expert annotators were instructed to keep their annotation environment as uniform as possible within their organization and within the INCISIVE consortium. This was quite important for the uniformity of the annotation of the data (and therefore their quality) since the INCISIVE project consists of a large number of data providers. Continuous technical support was provided, and guidelines were constructed for the medical expert annotators, especially during the first few months of the project, to ease the process of installation and usage of the annotation tool (ITK-Snap version 3.8.0) [28].