esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Simulation  
In this section we discuss the simulations and their results. Table 1 explains simulation setup and the environment that we utilized to conduct the simulations.  
In hotline-assisted simulation scenarios the nodes are deployed in clusters as explained in Section 4.1. The cluster head act as a gateway and all the communication to and from the cluster takes place through the gateway. All the gateways are connected via Ethernet cable. Multiple sources send data to a sink to emulate bursty traffic. The protocols we have compared are AODV and AOMDV which do not handle hotline based routing natively. The factors that are used to measure the reliability of a WSN are: (1) Packet Success Ratio and (2) end-to-end Delay.  
Figure 9: Overall procedure for intermediate node to receive data packet.  
If the packets are being dropped frequently, that network will be considered unreliable. In some mission critical applications like military and healthcare immediate communication is required, therefore end-to-end Delay is also considered to be one of the important criterions for measuring the reliability [26]. We have divided the simulation discussion into three parts. Part A discusses the effect on reliability with respect to increasing number of connections from source to the sink, Part B talks about the effect on reliability with respect to increasing packet generation rate and in Part C we have compared the effect on reliability with respect to increasing node density.
# Bacterial Flagellar Filament: A Supramolecular Multifunctional Nanostructure
## 6 Filament-Host Interaction
### Additional Applications of Flagellin  
Considering the great variability in the outer domains of flagellin in a single strain alone, as well as the propensity of flagellin for polymerization, it is possible to design filaments that could exhibit a variety of functions. From the late 1980s, numerous studies have confirmed that _Salmonella_ and _E. coli_ filaments could be used as platforms for peptide display [231]. Moreover, the variable D3 domain in _Salmonella_ FliC was successfully replaced by various small proteins such as thioredoxin [232], xylanase A [233], and GFP [234] without affecting its ability to polymerize in vitro or losing the activity of the inserted protein domains. Flagellin monomers and flagellin-protein fusions readily adsorb to hydrophobic surfaces with their D3 domains oriented towards the liquid phase [235], a feature that can be utilized in different ways. For example, [PERSON] et al. [236] designed a biosensor by immobilizing a flagellin fusion in which D3 was replaced by the nickel-binding domain of the transcription factor NikR, and successfully used it in binding kinetics studies. Different variants of flagellin can be used to create surface coatings that have either anti-adhesive (in case of the wild type flagellin) or highly adhesive (D3 replaced with a RGD motif) properties [237]. Flagellar filaments can also be used as biotemplates for synthesizing nanomaterials. Such structures can be produced by adding a 12-cysteine tag on the flagellin D3 [238; 239], replacing D3 by iron-binding motifs [240], or introducing loops rich with charged residues into the flagellin-thioredoxin fusions [241]. It has been demonstrated that polycations induced assembly of flagellin monomers into nanofilaments, forming thick and smooth composite films through a novel polyelectrolyte multilayer buildup mechanism [242]. These films could find diverse applications in nanotechnology and in biomedical sciences considering the recent discovery of naturally occurring enzymatically active D3 domains of flagellin subunits exposed to the surface of filaments [243].
## 5 Applications of Integrating Federated Learning and Blockchain in Vehicular Networks  
While transmitting data, valuable information can be disclosed through the model parameters by reverse engineering [128]. The disclosure of valuable data motivated researchers and developers to adopt known security and privacy defense methods, e.g., functional encryption and differential privacy, to FL [129].  
The following are some of the advantages of FL and BC in the VANET environment:  
* In the modern VANET environment, advanced vehicles have larger battery capacity and are more resourceful than traditional end devices. Using FL and BC as a basic storage and computing unit will improve the competence of VANET.
* Compared to traditional vehicular networks, for high data transmission, FVN uses heterogeneous communication systems, and for efficient data exchange and update, FVC is introduced.
* The integration of FL and BC to VANET infrastructure provides the continuous interaction with end devices, but this will also incentivize several entities, such as vehicles, clients, and venues in the FVN participation.
* As compared to fog- and edge-based networks, FVN is more reliable and secured due to trained data/model offloading to vehicles. The sensitive information is stored in the vehicle's OBUs in FVN. The training phase is complete without the involvement of third parties.
* Compared to the traditional fog learning model, FVN provides a well-organized and secure framework from a communication point of view [130].
* The incorporation of BC into VANET systems will enable data transactions and mitigate malicious activities between several end devices.  
Table 2 presents the evaluation of available FL paradigms in the VANET environment.
# Exploiting Blockchain Technology for Enhancing Digital Twins' Security and Transparency
## 4 Experimental Results
### Stub Testing
The provided tests were essential to assess the security requirements for the components of the system mostly subjected to possible attacks and provided an opportunity to closely examine the actual functionality of the final system in different scenarios. Moreover, it is possible to further analyze the recorded results with respect to the CIA triad model to better highlight the design choices from a security strategy point of view. The aforementioned model comprised three essential aspects:  
* Confidentiality ensures that only authorized users have access to information;
* Integrity ensures information non-repudiation and authenticity;
* Availability ensures reliable access to information. In this regard, the choice of the blockchain as the underlying distributed ledger for secure information exchange aimed to follow the model prescriptions. In fact, the massive use of encryption, both for saving data and service access, naturally enforces confidentiality and integrity. In addition, by its distributed architecture, the decentralized nature of blockchain ensures a high degree of availability. For what concerns the systems components, considering the analysis summarized in Table 1, it is clear that the proposed approach guarantees confidentiality, allowing only authorized transactions to be propagated and hence recorded on the blockchain as a hash value (thus enforcing integrity). The availability of the system is strongly connected to the availability of the blockchain, because the smart contracts are also stored on the blockchain and hence their availability is also guaranteed.
## 2 Materials and Methods
### Measurement of Ammonia and Hydrogen Sulfate Concentrations  
NH\({}_{3}\) and H\({}_{2}\)S concentrations were measured with a real-time analyzer (OMS-300, Smart Control & Sensing, Daejeon, Korea) calibrated with high precision standard gases (5-point dilution, R\({}^{2}\) = 0.99). The analyzer was equipped with NH\({}_{3}\)/CR-200 and H\({}_{2}\)S/C-50 electrochemical gas sensors (Membrapor, Wallisellen, Switzerland), NH3/CR-200 (0 to 100 ppm) and H\({}_{2}\)S/C-50 (0 to 50 ppm), respectively. OMS-300 collects the sample (2 L-min\({}^{-1}\)) required for an electrochemical sensor via an internal pump, then shows the voltage output from the sensor via a Raspberry Pi (Raspberry Pi Foundation, Caldecote, UK).
# Survey on Q-Learning-Based Position-Aware Routing Protocols in Flying Ad Hoc Networks
## 4 Q-Learning-Based Position-Aware Routing Protocols in FANETs
### Simulated Annealing Inspired Q-Learning (SAIQL)  
[PERSON] et al. [56] proposed simulated annealing-inspired Q-learning (SAIQL) for FANETs that utilizes an adaptive learning rate operated through heuristic simulated annealing optimization (SAO), where the temperature parameter (\(T\)) captures the influence of the UAV's mobility to update the Q-value. SAIQL considers a piecewise linear mobility model, where UAVs maintain piecewise linear motion over a time slot whose duration is exponentially distributed. In each time slot, the UAVs maintain constant velocity and direction, which may vary in the next time slot. The learning rate is obtained using \(T\) of the SAO, which promptly adapts to the UAV's average velocities during each time slot. SAIQL reduces the energy consumption of UAVs and increases the PDR of FANETs.  
_Advantages_: SAO at high temperatures has more aggressive exploration rates, and the algorithm learns gradually toward the optimal decisions over time by cooling the temperature that minimizes the end-to-end transmission energy of UAVs. SAIQL avoids routing loops as intermediate UAVs cannot be included in the end-to-end routing path more than once, and each UAV maintains an updated Q-table with information regarding the visited UAV nodes.  
_Limitations_: During exploration, a new action is selected randomly, which may produce unnecessary detours and delay the convergence of the algorithm. A specific guide is necessary to select a new action during exploration, such as a set of UAV nodes with sufficient residual energy, which indicates the distance progress toward the destination and satisfies the PTT to deliver the data successfully within the deadline.
## 4 Discussion and Conclusions
In addition, higher fluctuations can be expected in following situations under high-density conditions [36]. The study has some limitations, which need to be taken into consideration. Firstly, this study used a limited sample, and the data was collected in a controlled experiment only for a single-file movement. Therefore, the findings may not be applicable to more complex scenarios involving different cycling formations, e.g., several lines of cyclists on one-way paths, two-way paths, or wider paths. Additionally, the study did not take into account the potential impact of demographic characteristics on cyclists' behaviors. Further research is needed to understand how demographic factors, e.g., gender and age of the riders, influence the reactions and behaviors of the cyclists. Moreover, future studies could also consider other factors such as wider paths, grades (upward/downward paths), bicycle size, road conditions, weather, time of the day, etc. Future studies could incorporate these factors as well as reaction times into simulation models to improve their accuracy and reliability. Conceptualization, C.D. and Q.H. ; methodology, C.D. and M.A. ; software, C.D. and M.A. ; validation, C.D., M.A. and A.M.S. ; formal analysis, C.D., M.A., Q.H. and A.M.S. ; investigation, C.D., M.A. and H.N. ; data curation, C.D. and Q.H. ; writing--original draft preparation, C.D., M.A. and A.M.S. ; writing--review and editing, Q.H. and H.N. ; visualization, C.D. and M.A. All authors have read and agreed to the published version of the manuscript. This research was supported by Qatar University under the Student Grant scheme (Grant no: QUST-1-CENG-2023-779). Not applicable. The data used in this study are available at DOI: [[https://doi.org/10.34735/ped.2012.1](https://doi.org/10.34735/ped.2012.1)]([https://doi.org/10.34735/ped.2012.1](https://doi.org/10.34735/ped.2012.1)). This research was supported by Qatar University under the Student Grant scheme (Grant no: QUST-1-CENG-2023-779). The findings achieved herein are solely the responsibility of the authors. The authors declare no conflict of interest.
## 2 Research Method and Data  
### Research Method  
In this study, 324,495 data points composed of spatial and attribute information, and 2293 data points containing damage history were collected for heat transport pipelines buried for district heating in urban areas of South Korea. The attribute information includes various data, such as information on the operator, pipe function (supply and return pipes),pipe diameter, completion year, sensor wire condition, pressure, and auxiliary facilities. Most of the data, however, include large amounts of missing or unreliable data. Therefore, the operator, pipe function, pipe diameter, completion year, and sensor wire condition were selected as variables that can be utilized. For the collected pipeline data, data were not constructed with certain standards. Therefore, a method to calculate basic units with certain standards was presented, and the data were divided based on the basic units. The heat transport pipeline damage tendency, according to the attribute information, was examined by analyzing damage probability for each factor using the attribute information of heat transport pipelines, with damage history classified into basic units. In addition, correlation analysis was conducted to select factors that have a statistical impact on damage to heat transport pipelines. A dataset for AI model development was constructed by selecting the influence factors identified through this analysis as input data and heat transport pipelines with damage history as output data. The output data, i.e., pipelines with damage history, represent a very small proportion (approximately 0.75%) of the entire dataset. Thus, the dataset was reinforced by adding pipelines that were used for over 20, 25, and 30 years, which had high damage risks, to the output data.  
To develop a model for predicting heat transport pipeline damage probability, the entire dataset was divided into training, validation, and test data at a ratio of 64:16:20. Models were developed by training ML algorithms using 80% of the training data, and the generalization performance of the models was verified using the validation data. The performance of the models was verified using the test data that did not participate in learning. The constructed training dataset was used for the training of RF, XGB, and LGBM, which are ML algorithms. A model with the optimal performance was then selected by tuning hyperparameters. Accuracy and F2-score were selected as indicators for evaluating the performance of the model. In addition, overfitting of the model was assessed using the AUC curves of the training and test data. Finally, the importance of the variables used during heat transport pipeline damage classification was derived through the developed model, and decision-making measures for efficient maintenance were presented by visualizing the heat transport pipelines in some of the target areas using the damage probability predicted by the model.
## 4 Results and Discussion
### Structural Optimisation  
The structural optimisation work focused on a 2D model of the primary load-bearing truss structure, designed to manage the principal loads and bending moments within the overall structural system. This model was mainly tailored to address the operational demands during the concrete casting phase. With the Karamba3D plug-in in Grasshopper, experimental mechanical properties were assigned to each structural element, and maximum displacements were calculated by strategically applying loads to specific nodes and members. This method assesses the deformation behaviour of the entire structure under specific load conditions and introduces a \"scoring\" system to quantify and evaluate the mechanical performance of various structural geometries. Although this scoring system is not typically used in conventional design, it serves as a valuable benchmark for optimisation, guiding adjustments in the structural design.  
The primary goal of this optimisation is to identify a configuration with minimal displacement by adjusting the heights of the primary and secondary arches, thereby enhancing the stability of the load-bearing structure. Employing the Galapagos component--a genetic algorithm solver in Grasshopper--the project sought the optimal height configuration for the specific loading scenario, achieving a 25.3% reduction in displacement score compared to the initial design. Further validation in Strand 7 with the same model configuration and mechanical settings showed a 16.6% reduction in maximum displacement, confirming a significant improvement in controlling overall structural deformation. This optimisation approach allows for rapid adjustments to structural geometric parameters early in the design phase. Designers can explore the mechanical performance of different configurations and swiftly pinpoint a more suitable structural geometry, suggesting substantial potential for enhancing working efficiency through the parametric design workflow. However, the current optimisation methods face certain limitations. Since the optimisation is based solely on a 2D model, the results may not fully capture the complex 3D mechanical behaviour of the OMSS. The capability of this method in a 3D structural model needs further verification. Additionally, the optimisation results heavily depend on the quality of the parametric model. The programming process can be time-consuming and may lack efficiency, particularly when simulating the structure's fundamental forces and deformation characteristics across various operational stages and analysing stress distribution and buckling effects.
## 10 Conclusions  
Frequency stability is an important issue for islands or micro-grid power systems. In this work, different frequency support methods have been utilized, including GR, the use of BESS, DLC and EDRP. These methods provide the system operators various options for preventive control. To compare the different frequency support methods, the costs for each method are calculated. Finally, this work develops a software platform that integrates the frequency support capability and cost analysis for the preventive methods in an actual power plant, while demonstrating the effectiveness of the proposed methods. The contributions in this work are summarized as follows.  
The complete preventive control strategy that ensures sufficient system frequency stability and minimal operating costs has been proposed and the strategies include GR, BESS, DLC and EDRP methods.  
The frequency support capability from BESS, DLC and EDRP are proposed and the formulation relationship between frequency nadir and the required amount of BESS, DLC or EDRP is achieved.  
The costs for each frequency support method are calculated with appropriate assumptions, providing a clear way to analyze and compare these methods.  
Figure 16: Probability distribution of the required DLC load shedding.  
Figure 17: Probability distribution of the required EDRP load reduction.  
**Author Contributions:** Conceptualization, Y.-K.W. and K.-T.T.; methodology, Y.-K.W. and K.-T.T.; software, K.-T.T.; validation, Y.-K.W., K.-T.T. and W.-S.T.; formal analysis, Y.-K.W. and K.-T.T.; investigation, Y.-K.W. and K.-T.T.; resources, Y.-K.W. and K.-T.T.; data curation, Y.-K.W. and K.-T.T.; writing--original draft preparation, Y.-K.W., K.-T.T. and Z.K.L.; writing--review and editing, Y.-K.W., K.-T.T. and W.-S.T.; supervision, Y.-K.W.; project administration, Y.-K.W.; funding acquisition, Y.-K.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work is financially supported by \"This research was funded by the Ministry of Science and Technology (MOST) of Taiwan, grant number 108-3116-F-194 -001- and The APC was funded by the Ministry of Science and Technology (MOST) of Taiwan.  
**Conflicts of Interest:** The authors declare no conflict of interest.
###### Abstract  
Today, with the increasing transition to electric vehicles (EVs), the design of highly energy-efficient vehicle architectures has taken precedence for many car manufacturers. To this end, the energy consumption and recovery rates of different powertrain vehicle architectures need to be investigated comprehensively. In this study, six different powertrain architectures--four independent in-wheel motors with regenerative electronic stability control (RESC) and without an RESC, one-stage gear (1G) transmission, two-stage gear (2G) transmission, continuously variable transmission (CVT) and downsized electric motor with CVT--were mathematically modeled and analyzed under real road conditions using nonlinear models of an autonomous hydrogen fuel-cell electric vehicle (HFCEV). The aims of this paper were twofold: first, to compare the energy consumption performance of powertrain architectures by analyzing the effects of the regenerative electronic stability control (RESC) system, and secondly, to investigate the usability of a downsized electrical motor for an HFCEV. For this purpose, all the numerical simulations were conducted for the well-known FTP75 and NEDC urban drive cycles. The obtained results demonstrate that the minimum energy consumption can be achieved by a 2G-based powertrain using the same motor; however, when an RESC system is used, the energy recovery/consumption rate can be increased. Moreover, the results of the article show that it is possible to use a downsized electric motor due to the CVT, and this powertrain significantly reduces the energy consumption of the HFCEV as compared to all the other systems. The results of this paper present highly significant implications for automotive manufacturers for designing and developing a cleaner electrical vehicle energy consumption and recovery system.  
energy consumption and recovery; transmission layouts; fuel-cell electric vehicles +
Footnote †: journal: Applied Sciences
# Covert Channel Communication as an Emerging Security Threat in 2.5D/3D Integrated Systems
## 5 Covert Channel Attacks in 2.5D/3D ICs
### Existing Works
#### 5.2.1 Power Covert Channels in 2.5D FPGAs  
FPGAs are an example application domain of 2.5D integration technology, with commercial FPGAs consisting of multiple dies on the same package [89; 90]. [PERSON] et al. demonstrated that sensing the changes in supply voltage between separated dies within an FPGA chip was possible [91]. The same receiving and transmitting RO setup was used as [38]. However, the attack took place within the same FPGA. Similarly, this attack was also fully remote, because attackers did not have physical access to cloud FPGAs. The authors demonstrated that, as transmitter size (amount of ROs) increased from 100 to 500, the BER decreased from 25% to 0.1% [91]. Since this covert channel took place on-chip, a much higher bandwidth of 4.6 Mbps was achieved with Manchester encoding at a BER of 2.4% [91]. However, the overhead to reach this BER and bandwidth was relatively high. Specifically, there were 12 transmitters, each consisting of 2000 ROs [91]. The overhead for sensing the supply voltages on the receiver side was much lower. Specifically, there were 5 receivers, each consisting of 5 ROs [91]. Unfortunately, the area and LUT usage was not quantified, but the sheer amount of ROs required to make this attack successful could make this attack more detectable.
# Enhancing Data Security Through VLSM Subnetting and TCP/IP Model in an ENT
## 2 Literature Review
### Routing Protocols
#### 2.3.3 Open Shortest Path First (OSPF)  
The configuration of OSPF leads to collect all neighbours' and available paths for the generated topology [13]. Better load balancing and routing authentication relating to password authentication are present in OSPF. Load balancing and performance with both EIGRP and OSPF may be an interesting area to explore. Judging from the analysis in [10], where EIGRP outperforms OSPF in terms of throughput, it may be worth considering EIGRP for parts of the network with only Cisco devices, OSPF in other parts with mixed vendor devices, and BGP at the borders between these network parts. While RIPv2 does have limitations of hop counts and sluggish convergence visible in large networks, OSPF presents no restrictions of a hop count. Deep reinforcement learning-based routing on software-defined networks for a single-path routing of OSPF can be applicable to multi-path routing [11].