esa-sceva/satcom-chunk-collection huggingface dataset:
# An Evaluation Survey of Knowledge-Based Approaches in Telecommunication Applications
## 3 Evaluation of Different Knowledge-Based Approaches
### Assessment Results
#### 3.3.4 Graph-Based Formalisms  
Graph-based representations are adept at reflecting real-world entities and relationships precisely, maintaining accuracy by directly mirroring the connections and attributes present in the domain. They facilitate nuanced and detailed modeling of relationships, supporting precise descriptions within the domain by allowing for a granular depiction of associations and attributes. They effectively accommodate diverse information and multiple facets of a domain and provide a visually intuitive representation of the domain's generic relationships.  
However, the extent of their generalizability may differ depending on the domain, and in some cases, adaptations or extensions might be necessary for broader applicability.  
Despite their strengths, they are not directly suitable to explicitly capture uncertainty in reasoning within the graph structure. It necessitates additional mechanisms or annotations to express degrees of belief or uncertainty explicitly. Furthermore, while graph structures inherently ensure consistency by facilitating conflict detection and resolution, expressing absolute confidence levels can be challenging without specific scoring mechanisms. On the other hand, knowledge graphs are highly expandable. They allow for the incorporation of new nodes and edges, facilitating the integration of evolving domain knowledge and the derivation of novel insights. Additionally, they handle scalability efficiently, managing large volumes of data, complex relationships, and diverse domains effectively.  
In summary, graph-based representations, particularly knowledge graphs, excel in various aspects of knowledge representation, but might have certain limitations in expressing certainty, confidence, and generalizability across diverse domains.
# Analysis of the Effect of Capillary Water Absorption on the Resistivity of Cementitious Materials
## 3 Results and Discussion  
### Compressive Strength  
Figure 3 shows the compressive strength test results of cement mortar after 28 d curing. It can be seen from the figure that compared with the specimens of the JZ group, the 28 d compressive strength of the specimens increased to different degrees after adding different amounts of mineral admixtures. The compressive strength of the FA group increased by 2.6%, 4.1%, 7.02%, and 8.3%, respectively. The compressive strength of the SL group increased by 5.2%, 6.89%, 7.72%, and 9.4%, respectively. The compressive strength of the SF group increased by 16.68%, 30.85%, and 45.81%, respectively, and the growing range increased with the increase in the admixtures. This is because the admixtures can promote the secondary hydration reaction of the system and react with cement hydration products to generate more C-S-H gels. At the same time, the content of Ca(OH)\({}_{2}\) with low strength in the system is reduced, so the pore diameters of specimens in each group doped with admixtures are refined compared with those in the JZ group, and the structural system is more compact. This is evidenced in the Section 3.3 and 3.4 below. Among the three kinds of admixtures, SF has the best effect on enhancing strength, because SF has high chemical activity and can better promote the secondary hydration reaction of cement [30]. This led to a significant decrease in the porosity of the specimen along with the refinement of the pore size, resulting in a significant increase in strength. As shown in the Section 3.3, it can be seen that more gel pores and transition pores can lead to strength improvement in the case of similar porosity, and lower porosity has a significant effect on strength improvement at the point of large difference in porosity [31; 32; 33].  
Figure 3: 28 d compressive strength of cement mortar.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Time** & **60 s** & **5 min** & **10 min** & **20 min** & **30 min** & **60 min** & **Every Hour up to 6 h** & **12 h** & **24 h** & **Once a Day up to 36 Days** \\ \hline Tolerance & 2 s & 10 s & 2 min & 2 min & 2 min & 2 min & 5 min & 5 min & 1 h & 2 h \\ \hline \hline \end{tabular}
\end{table}
Table 3: Timing and tolerance of capillary water absorption quality tests.
## 4 Crowd Sourced Audio-Visual Evidence  
_Crowd sourced audio-visual evidence_ is a phenomenon where law enforcement agencies collect video, audio and photographic footage (collectively referred to herein as audio-visual) from the public to aid in the investigation of tempestuous events such as civil unrest and riots. Whilst the use of crowd sourced audio-visual evidence has not yet been expanded beyond this, it could also serve as a useful source of evidence in many other incidents wherein footage taken by the public on or around the time of an incident could prove useful in a subsequent investigation and can augment evidence already gathered through traditional systems such as CCTV.  
Crowd sourced audio-visual evidence has a value outside the domain of law enforcement, for instance, it is of great value to news agencies who have relied on crowd sourced audio-visual evidence for years. Such evidence was used during a number of recent international events such as the conflicts, civil disorders and uprisings in Egypt, Syria and Turkey. However, like the law enforcement agencies, the news agencies must validate and authenticate the submitted evidence and in the absence of such authentication, they present it with the disclaimer/caveat that the evidence is \"unverified footage\" or is based on \"unconfirmed reports\".  
This form of footage is invaluable to governments and responder agencies such as the United Nations who often gain insights into world events through such reporting. However, they are unable to react to serious incidents until such footage and particularly the incidents the footage purports to represent are confirmed and validated.  
There have been two prominent recent examples of the use of crowd sourced audio-visual evidence by law enforcement agencies: the Victoria Stanley Cup riots in Vancouver (2011) and the UK riots of the same year.
## 3 Results
### Winter Trial
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Statistics** & \begin{tabular}{c} **VARROMED** \\ **(ITALY\_FEM)** \\ \end{tabular} & \begin{tabular}{c} **VARROMED** \\ **(ITALY\_IZSUT)** \\ \end{tabular} & \begin{tabular}{c} **VARROMED** \\ **(ITALY\_IZSUT)** \\ \end{tabular} & \begin{tabular}{c} **VARROMED** \\ **(ITALY\_IZSVE)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(CROATIA)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(ITALY\_FEM)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(ITALY\_IZSUT)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(ITALY\_IZSVE)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(TRALY\_IZSVE)** \\ \end{tabular} & \begin{tabular}{c} **CONTROL** \\ **(TRALY\_IZSVE)** \\ \end{tabular} & \
\begin{tabular}{c} **CONTROL** \\ **(TRALY\_IZSVE)** \\ \end{tabular} &
\begin{tabular}{c} **CONTROL** \\ **(CROATIA)** \\ \end{tabular} \\ \hline Minimum & 73.1 & 87.8 & 64.8 & 42.9 & 1.1 & 0.6 & 1.7 & 0 \\ Maximum & 100 & 98.9 & 98.7 & 87.3 & 19.6 & 23.8 & 33.3 & 35.7 \\ Median & 94.6 & 97.0 & 93.7 & 74.1 & 6.6 & 6.5 & 14.4 & 16.0 \\
3 rd Quartile & 99.8 & 97.6 & 96.0 & 82.3 & 10.2 & 11.8 & 23.3 & 20.3 \\ Mean & 89.9 & 95.6 & 89.7 & 71.8 & 8.3 & 8.6 & 15.0 & 14.8 \\ Variance (n\({}^{-1}\)) & 1.2 & 0.1 & 1.1 & 1.9 & 0.3 & 0.5 & 1.6 & 1.5 \\ Standard & 11.1 & 3.5 & 10.5 & 13.7 & 5.3 & 7.3 & 12.7 & 12.0 \\ deviation (n\({}^{-1}\)) & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Acaricide efficacy recorded during the summer/autumn trial in the apiaries and relative mite fall during the same period in the control group (%). Figure 7: Box plot of acaricide efficacies recorded during the winter trial and relative mite fall during the same period in the control group (%). The horizontal line in boxes shows the median. The box shows the first and third quartile. Whiskers extend to 1.5 \(\times\) interquartile range (IQR). Additionally, the pluses show mean values. During the summer/autumn trials, the mean environmental temperatures recorded during VarroMed treatments were as follows: 30.2 \(\pm\) 2.5 \({}^{\circ}\)C in Croatia; 23.6 \(\pm\) 1.3 \({}^{\circ}\)C in Italy; 15.6 \(\pm\) 4.2 \({}^{\circ}\)C in Slovenia; 12.4 \(\pm\) 2.7 \({}^{\circ}\)C in Belgium. During the winter trials, we recorded the following mean environmental temperatures: 7.4 \(\pm\) 3.4 \({}^{\circ}\)C in Italy_IZSVE; 6.4 \(\pm\) 3.2 \({}^{\circ}\)C in Italy_IZSLT; 4.2 \(\pm\) 4.6 \({}^{\circ}\)C in Croatia and 3.3 \(\pm\) 2.6 \({}^{\circ}\)C in Italy_FEM.
# MTRSRP: Joint Design of Multi-Triangular Ring and Self-Routing Protocol for BLE Networks
## 5 Network Performance
### Network Performance of MTRSRP
Specifically, the average overhead for the three configurations of the multi-ring network was O(1.24N), which is higher than that of CORP (O(1.0N)) and BLEmesh (O(1.1N)), where N represents the total number of nodes. This indicates that compared to CORP, the MTRSRP network improves network connectivity and reliability by incurring additional communication link costs to form rings and dual bridge links between scatternets. In summary, the network topology plays a pivotal role in shaping routing efficiency, path optimality, and traffic distribution. The proposed MTRSRP leverages a hierarchical triangular ring structure that offers predictable, loop-free routing paths and evenly distributes load across bridge nodes. This regularized topology reduces average hop count (Figure 9), minimizes packet collisions, and improves packet delivery performance (Figure 7), particularly under high-traffic conditions. Compared to less structured approaches such as BLEmesh and CORP--where routing paths and node connectivity may be irregular--MTRSRP demonstrates more stable and scalable performance. Furthermore, the evaluation of Cases 1-3 reveals that bridge node configuration significantly impacts routing behavior. Higher bridge density leads to improved path redundancy and traffic balancing, which in turn reduces congestion, lowers latency, and enhances overall delivery success. These findings highlight the importance of topological design and bridge placement in optimizing network performance, reaffirming the advantages of the MTRSRP framework in structured BLE scatternets. Finally, Table 5 presents a comprehensive comparison of the proposed MTRSRP protocol with two representative BLE-based protocols: CORP [12] and BLEmesh [13]. The comparison covers key aspects such as topology structure, routing approach, stability, and scalability. It highlights how MTRSRP combines a regular multi-triangular ring formation  
Figure 10: The average number of topology construction overhead of MTRSRP, CORP, and BLEmesh. with self-routing based on binary labeling, offering higher throughput, lower packet loss, and better structural scalability under moderate to dense network deployments.
## 3 Simulation Results
### Annual PV Real Power Generation, Injection, and Curtailment  
To estimate the annual generation of power by the PV system for economic evaluation, the local hourly weather data collected by the Central Weather Bureau of Taiwan over a one-year period is used. By a statistic regression analysis, the maximal real power output \(P_{mpo}\) (W) of a 1-kWp PV module is formulated as follows [16]:  
\[P_{mpo}=-11.18+0.834G+0.734T-1.955\times 10^{-3}G\cdot T, \tag{5}\]  
\begin{table}
\begin{tabular}{c c} \hline
**Cost Parameters** & **Numerical Value** \\ \hline PV Installation Cost with normal inverter (NTS/kWp) & 51,850 \\ PV Installation Cost with smart inverter (NTS/kWp) & 56,350 \\ PV Performance De-rating Rate (\%/year) & 1.4 \\ O&M Cost (\%/year) & 0.5 \\ Economic Life (years) & 20 \\ PV Power Purchase Price or FIT rate (NT$/kWh) & 4.8845 \\ Discount Rate (\%/year) & 3 \\ \hline \end{tabular}
\end{table}
Table 1: Cost parameters used for economic evaluation; O&M: operating and maintenance; FIT: feed-in tariff.  
Figure 3: One-line diagram of an 11.4 kV distribution feeder in a Taipower system.  
where \(G\) and \(T\) are the solar irradiation in W/m\({}^{2}\) and the surface temperature of PV panels in \({}^{\circ}\)C, respectively. Accordingly, the annual PV real power generation for different PV capacities can be plotted in Figure 4.  
For the PV with fixed unity power factor (_pf_ = 1.0), the annual PV generation, injection, and curtailment for PV capacity ranging from 500 kWp to 5000 kWp are drawn in Figure 5. From Figure 5, it is shown that (1) the larger the PV capacity, the larger the annual power generation; (2) when the PV capacity exceeds 1500 kWp, the curtailment will rapidly increase and the actual power injection into the feeder will gradually increase and become flat.  
Figure 4: Annual PV real power generation (in kWh).  
Figure 5: Annual PV generation, injection, and curtailment for different capacities (_pf_ = 1.0).
## 2 Protocol  
As shown in Figure 1, this protocol can be divided into two parts: cryptographic key preparation and encrypted signal transmission over a public network; watermark-based identity authentication and cascade-ablation-based cryptographic key extraction.  
**Part I**: Cryptographic key preparation and encrypted signal transmission over a public network.  
**1. Sharing of initial keys.** The server generates \(N\) random binary patterns \(IK_{j}\) (\(j=1,2,3,\cdots,t+1\)) of the same pixel-size as the QR code image, and shares them to each legitimate user through an absolutely secure private medium (such as a non-reproducible flash disk or a U shield) in advance. Secure media such as USB flash drives or USB shields are easy to carry and suitable for storing large-scale initial keys. In view of this, the server can distribute such a non-reproducible medium to every legitimate user in advance to ensure absolute security.  
Figure 1: Schematic of a multi-party cryptographic key distribution (CKD) protocol over a public network based on a quick-response (QR) code. FPs: fragment patterns; FSP: fragment synthesis pattern.
# HCLE: Hybrid Clustering Approach for Extending WBAN Lifetime
## 3 Preliminaries
### Performance Metrics
#### 3.4.4 End-to-End Delay  
End-to-end delay (EED) is a metric that measures the time it takes for a packet to travel from a source (i.e., sensor node) to the destination node (i.e., sink). It is particularly important in WBANs to monitor physiological data, where timely information delivery is necessary for medical applications. EED metrics in WBANs ensure the timely delivery of critical data from sensor nodes to the sink node. The delay needs to be examined and controlled to ensure that the monitored data reach the sink in a timely manner. Delays in delivering data beyond acceptable thresholds may result in inaccurate or outdated information, which can be detrimental to medical diagnosis, treatment, or patient monitoring.  
To calculate EED, the time at which the sensor node transmits the first packet is noted, and the time at which that first data packet arrives at the sink is recorded. The difference between these two times provides EED for that specific packet [66]. This calculation is performed for multiple packets, and the overall average EED is determined. Mathematically, the overall average EED in a WBAN can be calculated by dividing the total time required to send all packets (\(T_{sp}\)) by the total number of packets received at the sink node (\(T_{rp}\)), as in Equation (5) [25; 67]. This calculation provides an average value that represents the average delay experienced by packets in reaching their destinations.  
\[EED=\frac{T_{sp}}{T_{rp}} \tag{5}\]
## 3 Results
### Vocabulary Mapping  
Furthermore, vocabulary concepts, assigned to relation types in the CDM, could be queried via the Concept_relationship table in the Standardized Vocabularies Domain. This linking of relationship types makes it possible to query additional information of a concept without this information being available in the source system. It was possible to implement 79 distinct relationships. The \"Maps to\" relation was the most frequently occurring relation (\(n\) = 463,880, 16.77%) (Table 2). The relation \"Has priority\", on the other hand, was the least represented, with five (0.0002%) events. In total, 2,765,952 oncological data-related elements could be mapped to the standard. It was possible to map 153,490 data entries to the standardized Cancer Modifier vocabulary. Among them, the concept of topography of the tumor (\(n\) = 53,744, 35.01%) could be mapped most frequently. The OncoRegimenFinder algorithm extracted 16,303 Treatment Regimens from the documented ATC data in the source system. There were 26,443 documented protocols, similar to Treatment Regimens of the Episode Domain, in the source system. Therefore, the algorithm extracted 38.35% fewer Treatment Regimens than were stored in the source system. A brief comparison of time intervals showed that only 42% of the detected Treatment Regimens had at least one correct start or end date, assuming that the documented protocols of the source system represented the actual values. From these Treatment Regimens, 60% (\(n\) = 9800) could be assigned to the regimen class Chemotherapy. The regimen class Immunosuppressive Therapy had the lowest number of events, with only 3% (\(n\) = 485). The achieved vocabulary mapping score between the CDM and source system depending on the Domain can be seen in Table 3. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Relationship\_ID** & \(n\) & **Percent (\(\approx\)\%)** \\ \hline Maps to & 463,880 & 17 \\ Mapped from & 422,273 & 15 \\ Is a & 214,233 & 8 \\ Variable to Schema & 212,210 & 8 \\ Has Answer & 160,424 & 6 \\ Has parent item & 134,531 & 5 \\ Has start date & 134,531 & 5 \\ Subsumes & 105,450 & 4 \\ Has method & 87,313 & 3 \\ Concept same\_as from & 58,737 & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Top 10 relations with number and percentage of connected concepts. Figure 3: (**a**) Sunburst plot of Disease Dynamic concepts. The segmented pie chart shows the first to fourth remission status of all patients in the Episode Domain. (**b**) Sunburst plot of Treatment concepts. The segmented pie chart shows first to fourth line therapies of all patients in the Episode Domain.
## 6 Simulation and Analysis
### Performance of the Proposed Transport Scheme
Because the RTS reduced the energy consumption by limiting the redundancy injected into the network and controlling unnecessary transmissions/replications, the average delay was slightly higher, but the effective communication duration was greatly increased compared to RTS-MV under the same energy constraints. In spite of this, with the proliferation of selfish nodes, the efficiency of the RTS-MV declined dramatically, while the RTS delivered files very steadily and outperformed the RTS-MV. In general, the RTS could use limited energy more efficiently, and was able to keep high efficiency for a longer time. In addition, the storage congestion caused by load increase also affected the transmission efficiency. In this work, we increased the file size, so that number of pieces \(K\) that the file is divided into also increased, given that the size individual packet was fixed, and \(p\) was set to 10%. Then the performances of both RTS and RTS-MV with the change of \(K\) were investigated. It can be seen from the Figures 15-17 that, with the increase of \(K\), the mean round-trip delay and energy consumption of both RTS and RTS-MV rose greatly, and the number of files successfully delivered of both RTS and RTS-MV declined significantly. This is because the large load as well as the use of redundancy-based methods (epidemic routing strategy and rateless coding) accelerated the exhaustion of cache, leading to storage congestion. Then the packet-forwarding efficiency was greatly affected. Compared with the RTS-MV, the mean round-trip delay of the RTS was higher, the mean energy consumption to deliver a file of the RTS was significantly lower, while the number of files successfully delivered in the simulation time was remarkably larger. For example, when \(K\) = 20, RTS had a 38% larger delay than that od RTS-MV, but had a 55% less energy consumption and 67% more delivered files than that of RTS-MV. This is mainly due to the appropriate control of redundancy in the proposed RTS, so as to reduce the consumption of storage and improve the efficiency of message forwarding. These results prove that the proposed transport scheme could somehow achieve congestion control in ONs. In fact, the proposed transport scheme could be combined with an appropriate cache management strategy to achieve more efficient congestion control and more reliable data transfer in human ONs. That will be investigated in our future work. In summary, the RTS could significantly reduce the energy consumption of file delivery by limiting the redundancy injected into the network and controlling unnecessary transmissions/replications. Although the delivery delay slightly increased, the occurrence of selfish behaviors among nodes could be alleviated, and the number of files successfully delivered could be improved notably. Therefore, the reliability and stability of the communication service in human ONs were enhanced. The RTS was very reliable and suitable for some scenarios where network resources, especially power, were very scarce and the number of messages to be sent was large.
# Michelson Interferometric Methods for Full Optical Complex Convolution
## 1 Introduction
We compare the RCCM with existing optical convolution methodologies to assess its performance and potential advantages. Our research investigates optical real-time dynamic data processing, focusing on its application in tensor algebra operations. These operations are computationally demanding in fields such as machine learning, cryptography, and digital holography [10; 11; 12; 13]. While electronic semiconductor hardware faces certain limitations in complex calculations [14], optical methods present alternative solutions. The optical Fourier transform and dot-product multiplication, performed passively by a single lens or metalens, potentially offer reduced computational complexity for specific applications. We acknowledge current limitations in optical computing systems, particularly the refresh rate constraints of SLMs. However, ongoing research in phase-changing materials and 2D materials indicates potential solutions to this challenge [15; 16; 17; 18; 19; 20]. This paper presents a comprehensive study of the RCCM for optical computing. Our research addresses current challenges in data processing and explores the potential of optical computing to overcome these limitations. The study examines the fundamental principles underlying the RCCM, including Fourier optics and the crucial role of spatial light modulators. We present experimental results demonstrating the capabilities of our convolution-based processor, which independently modulates both phase and amplitude across two million pixels. Throughout the paper, we discuss current technological limitations and potential future research directions. By examining both theoretical foundations and practical implementations of the RCCM, this work aims to contribute to the ongoing development of optical computing technologies and their potential integration into next-generation computing systems.