esa-sceva/satcom-chunk-collection huggingface dataset:
# Validating and Testing an Agent-Based Model for the Spread of COVID-19 in Ireland
## 2 Materials and Methods
### Model Description
#### 2.1.2 Environment Component  
The model environment is made up of grid cells or patches in NetLogo. Thirty-one patches in the model are designated as counties (e.g., Leitrim County, and Cork County) or city/county areas (e.g., Dublin City, Cork City, Waterford City and County). These county and city labels are defined by the CSO and are referred to as county patches going forward. The number of primary and secondary schools in each actual county in Ireland can be found from the data from the Irish Department of Education. However, because we are scaling the model for 1 agent to represent 100 people, we reduce the number of schools in the counties. We do this by dividing the number of schools in the county by 50 (half the scale for agents to people) and rounding up. This gives us at least one primary and one secondary school in each county and also approximately reproduces the class and school network sizes that are found in the 1 to 1 scaling in the county model.  
Agents will only occupy the county patches in the model and can move between them. Although all agents on a county patch will physically be coded in the same location, the agents keep track of their location within the county and will be at either home, work, school, or in the community. Agents will only come into contact with other agents in the same location as them in the same county. For example, an agent in the community will not be in contact with an agent at home. Additionally, all agents in the community on the same patch will not be in contact with every other agent in the community. Instead, a set of parameters derived using the POLYMOD contact matrix data [27] is used to determine the number of community contacts that an agent will have. Agents can move between county patches. Agent movement is discussed in more detail in Section 2.1.4. While on a patch, we can access certain information about the patch, including the number of agents on the patch and the physical distance to the other patches.
## 4 Conclusions  
In this paper, we used a feed array antenna to achieve uniform electric field distribution in the near-field region for feeding a large-aperture antenna. Each element of the  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline \(d\) & 85.4 mm \\ \(h\) & 30.2 mm \\ \(\phi_{\text{\emph{age}}}\) & 24.3\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of proposed feed array antenna.  
Figure 10: Electric field distribution of the proposed feed array. (**a**) Measurement. (**b**) Simulation.  
array consisted of a Vivaldi radiator and parasitic rings, and it was possible to vary the near-field pattern of the parasitic rings by adjusting their radii. Thus, the required near-field distribution on a virtual target surface can be achieved by optimizing the radii of the parasitic rings. The reflection coefficient of a single element had a matching bandwidth of 1.78 GHz with a fractional bandwidth of 59%, and the average reflection coefficient in the operating frequency was \(-\)18 dB. The uniformity of the electric field distribution in the near-field was evaluated by the cost, and this cost was determined by considering both the average and the deviation of the near-electric field distribution. The average and deviation of the proposed feed array were 1.7 dB and 6.8 dB (cost = 3.2), respectively. The result demonstrated that the feed array with the optimum array configuration and parasitic rings can obtain uniform near-field distribution on the virtual surface placed within half a wavelength from the antenna aperture. The proposed antenna can be employed to operate various electrical large-aperture antennas, such as dielectric lens antennas, frequency selective surfaces, and metasurface transmissive arrays. Therefore, we expect that the proposed feed array will be useful in practical applications such as radars, satellite communications, and medical systems [26; 27]. On the other hand, the proposed antenna requires further studies to evaluate the antenna's durability.  
Conceptualization, M.H., D.J. and H.C.; methodology, M.H. and D.J.; software, M.H. and D.J.; validation, M.H., D.J. and H.C.; formal analysis, M.H. and D.J.; investigation, M.H. and D.J.; writing--original draft preparation, M.H.; writing--review and editing, M.H., D.J. and H.C.; visualization, M.H.; supervision, H.C.; project administration, H.C.; funding acquisition, H.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Research Institute for defense Technology planning and advancement (KRTT) grant funded by the Korea government (DAPA (Defense Acquisition Program Administration)) (No. KRTT-CT-22-021, Space Signal Intelligence Research Laboratory, 2022).  
Not applicable.  
Data are contained within the article.  
Author [PERSON] was employed by the company Hanwha Systems Company Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 5 Performance Evaluation
### Performance Evaluation for the Hop Count per Packet  
We recorded the number of hops or UAVs that a packet travels from the sender to the destination. The average result is presented in Figure 12. A lower hop count is better because it requires fewer transmissions per packet. The GPSR has the lowest hop count indicating that it fails to route the packets successfully and only delivers when the destination is a one-hop neighbor. This finding explains the most deficient performance in terms of packet delivery ratio. The GPSR-Q also has similar results. The packets could travel at most three hops, which also explains the poor packet delivery ratio. In addition, LER performs better, and LECAR takes a few more hops than LER. The LECAR protocol takes extra hops to avoid congestion, thus avoiding packet loss. The result is a better packet delivery ratio than LER. LAROD-LoDiS and Spray and Wait take many more hops because they cannot take advantage of the path-planning mechanism and adequately direct the packets to the destination. Instead, they follow a broadcasting approach that leads the packets through a greater number of hops.
# Current Biomedical Applications of 3D Printing and Additive Manufacturing
## 5 Open-Source Tools for 3D Bioprinting  
As 3D printing developed into a platform for hobbyists to design and produce parts, there was a rapid increase in the availability of open source software and 3D designs for printing. Many of these freely available tools are translatable alongside new ones that are directly applicable to the biomedical field. A few examples are detailed here.  
* **RepRep**--an online resource for all things 3D printing, including how to build custom 3D printers [161]. As many bioprinters have unique applications and require specific functions, many groups have modified low-cost FDM printers for affordable bioprinting set-ups [162; 163].
* **[PERSON] et al.**--this group recently released a complete set of instructions along with.stl files to print a \"large volume syringe pump extruder for desktop 3D printers\" [164]. This enables the user to convert a low-cost FDM filament printer into a bioprinter for the extrusion of gel or paste-like bioinks.
* 3D CAD models
* **NIH 3D Print Exchange**--an online free database of scientifically accurate and medically applicable models. Ranging from prosthetics to protein structures, the database has almost 7000 3D models that are free to download.
* **Thingiverse (MakerBot)**--a large online database of general 3D models. It includes a selection of anatomical models and models for a range of medical tools and devices uploaded by the printing community.
* Slicing software
* **Slic3r, Cura (Ultimaker), Repetier-Host, etc.**--there are many different open-source slicing packages available that all have similar functions and can be adapted for use with most 3D printers.
* **PetriPrinter**--a G-code generator developed with bioprinting for cell culture in mind, this software enables the user to design printing set-ups for multiple culture plates or petri dishes [165].  
* **Bioverse (Cellink)**--an online community of researchers involved in bioprinting where CAD models, protocols and other resources are shared for free.
* **Embodi3D**--an online biomedical 3D-printing community providing printable anatomic body parts (.stl files) and tools for converting medical dicom image stacks into printable files as a freeware service.
# Fault Detection of Resilient Navigation System Based on GNSS Pseudo-Range Measurement
## 3 Results
### Simulation Results
#### 3.1.1 No. 1 Simulation Results  
Figures 5-7 and Table 4 compare the performance of the Chi-square and the proposed method in the No. 1 scenario. In Figure 5, the diagram of the test statistic caused by a step fault in SV-1 shows that both methods can successfully detect the step fault in a single-satellite pseudo-range measurement. In Figure 6, the Chi-square method can generally detect satellite faults between 200-250 s. After isolating the position factor, position and speed will diverge without correction. The proposed method can isolate the fault pseudo-range measurements. Furthermore, the normal satellite data can correct the inertial navigation data as usual. Table 4 proves the proposed method has better accuracy with the RMS results by simulation under the step fault. The box diagram of position and velocity errors also shows the superiority of the proposed method in Figure 7. Positioning accuracy can be improved by more than 70%.
## 5 Experimental Study
### Analysis of Efficiency of Image Encryption
The histogram acquired over the original _airplane_ image, over the image acquired through encrypting the image, and over the image acquired from hiding a given sequence of secret data is shown in Figure 7. As encrypted image pixel intensities are uniformly distributed, the histogram of the encrypted image looks flat in Figure 7. Furthermore, the marked image histogram is the same as the encrypted image histogram, implying that the image encryption efficiency is favored through the proposed data-hiding process of the \(MPSA\) scheme. Figure 7: _Cont_.
## 2 Mechanism behind Thermal-Induced Measurement Errors
### Development and Verification of the Image Error Model for a Specific Camera System
As shown in Figure 8a, the camera system and a planar test pattern of a checkerboard were fixed tightly on the optical platform, and the surrounding temperature of the camera was kept constant during the experiment. Once the camera was switched on, the image of the checkerboard was captured with a frame rate of 1/60 frames per second (fps). Then, the coordinates of the corners in these images were obtained using the Harris algorithm, which can be used to calculate the pixel drift of subsequent images relative to the first captured image as well as further image distortion and translation errors. Using the specific thermal-induced image error models, the theoretical results for the thermal-induced pixel drift, image distortion error, and image translation error were calculated. The results of the experiment are presented in Figure 8b. These results indicate that the image error models established in this study can effectively describe the thermal-induced pixel drift, image distortion error, and image translation error. For the investigated camera system, we performed a series of experiments to investigate the responses of the thermal behaviours of the camera system to temperature and further obtained specific image error models, which were experimentally verified. In the following subsection, the relationship between the image error and measurement error in photo mechanics measurements is discussed in detail in order to establish the relationship between the temperature and measurement error. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \(R_{1}\) & \(R_{2}\) & \(R_{3}\) & \(R_{4}\) & \(R_{5}\) & \(R_{6}\) & \(K_{1}\) & \(K_{2}\) & \(K_{3}\) & \(K_{4}\) \\ \hline
0.100 & 0.055 & 0.176 & 0.052 & 0.034 & 0.049 & 0.955 & 0.061 & 0.
# Post-Quantum Migration of the Tor Application
### Purpose  
On the 13 th of August 2024, NIST [7] released three long-awaited PQC standards, including the CRYSTALS-Kyber KEM and CRYSTALS-Dilithium signature schemes ( renamed \"ML-KEM\" and \"ML-DSA\"), both based on lattice problems. Another lattice-based standard publication, with FALCON to follow. On the other hand, NIST more recently announced a new timeline, banning RSA and ECDSA starting in 2035 [8]. Amid the wave of new publications in the field, the following question persists:  
How can one evaluate its relay performance now as a reference point for later?  
The four core aims of this paper can be summarised in the following points to assist in answering the latter research question.  
* First, based on the literature analysis, this paper intends to identify a set of appropriate schemes for Tor post-quantum cryptography migration.
* To set up a functioning Tor network comprising multiple physical nodes in order to measure it and evaluate its performance at scale.
* Thirdly, identifying and measuring the cryptographic processes within Tor software.
* Finally, the scope of this research is to estimate a theoretical overhead value by incorporating the results of the previously defined objectives with post-quantum benchmark performances made on the devices used.
# Performance Optimization of Object Tracking Algorithms in OpenCV on GPUs
## 4 Performance Optimization of the OpenCV Object Tracking Algorithm
### Minimizing Kernel Call Overhead  
An OpenCL program consists of host and kernel programs. A host program performs many preprocessing operations such as selecting computing devices, reserving a memory space, transferring data, and queuing kernels to execute. In addition, a host program must handle the output data after kernels finish their operations.  
Computer vision algorithms generally process input images to produce output images, and such operations may consist of multiple consecutive operations. Subsequently, a series of computing operations is performed, and in this case, the output of a previous operation becomes the input of the next operation. When each operation is implemented as an individual kernel in the OpenCL framework, a host program needs to relay the output of a previous kernel to the input of the next one. This computing structure is natural and intuitive to a developer of a computer vision algorithm. Frequent kernel invocation, however, incurs high overheads, which are associated with OpenCL API calls, buffer allocation/management, and unnecessary data movement between kernels. As described in Section 3.2, the Farneback optical flow algorithm is such a case, launching many kernels.  
Kernel merging is an effective method to alleviate such overheads. If adjacent kernels share data and have no data dependency between work-items, they can be unified into one kernel. Consequently, the overheads associated with kernel invocation, such as buffer allocation and data transfer, can be eliminated. Figure 9 shows the flowchart of our kernel merging algorithm. This algorithm merges kernels if consecutive kernels have data dependency with each other and identical global/local work sizes.  
Table 5 shows the kernels in the main loop of the Farneback algorithm shown in Figure 5. The table includes the kernel names and their global and local work sizes. In the table, four kernels are candidates of kernel merging: updateFlow, updateMatrices, resizeLN, and KF. These kernels are executed in a row, have identical global and local work sizes, and transfer data from a previous kernel to the next. Therefore, we modified the resizeLN and KF kernels so that the resizeLN kernel executes the operation of the KF kernel. Please note that the two pairs of the two kernels process two different (consecutive) frames. Hence, merging the two kernels does not affect the result of the algorithm. Furthermore, we introduced a new updateFM by merging the two kernels, updateFlow and updateMatrices. The kernel after the kernel merging is shown in the table as well.
## 3 System Modeling and Problem Formulation  
The schematic of the studied FIBC is illustrated in Figure 1. \(S_{k}(k=1,2)\) are the power switches, \(D_{k}\) are the diodes, \(L_{k}\) are the inductors, \(C_{k}\) are the capacitors, and \(R\) is the load resistor. For the sake of simplicity, it is assumed that the circuit parameters, i.e., inductance and capacitance, on the two branches of the FIBC are completely identical. Based on this assumption, we have  
\[\begin{split} L_{1}&=L_{2}=L\\ C_{1}&=C_{2}=C\end{split} \tag{30}\]  
According to the [PERSON]'s current and voltage laws, the average model of the FIBC in the continuous mode is given by  
\[\begin{split}&\frac{d}{dt}v_{C_{k}}=\frac{1}{C}\big{(}(1-u_{k})i_ {L_{k}}-i_{o}\big{)}\\ &\frac{d}{dt}i_{L_{k}}=\frac{1}{L}\big{(}v_{in}-(1-u_{k})v_{C_{k} }\big{)}\end{split} \tag{31}\]where \(v_{in}\) is the input voltage, \(v_{c_{k}}(k=1,2)\) are the capacitor voltages, \(i_{L_{k}}\) represents the currents through the inductors, \(i_{o}=v_{o}/R\) denotes the load current of the FIBC with \(v_{o}\) as the output voltage, and \(u_{k}\) reflex the duty cycles of the PWM signals applied to the power switches.  
The output voltage of the FIBC is determined as  
\[v_{o}=\sum_{k=1}^{2}v_{c_{k}}-v_{in} \tag{32}\]  
Hence, the voltage gain in continuous conduction mode \((di_{L_{k}}/dt=0)\) is computed through the following equation  
\[G(D)=\frac{1+D}{1-D} \tag{33}\]  
where \(D\) is the equivalent duty ratio of the PWM pulse applied to the power switches.  
**Remark 1**.: _According to the voltage amplification coefficient Equation (33), it can be seen that the voltage gain of the FIBC is significantly higher than that of the conventional DC-DC boost converter. It indicates that the FIBC is one of the most appropriate solutions for fuel cell applications such as electric vehicles or DC microgrid applications, which require a stable few hundred volts of the DC bus while the input voltage is generally low._  
The main control objective is to stabilize the output voltage of the FIBC at the desired level under the input variation and load change, which naturally exists in real-life fuel cell applications such as electric vehicles and DC microgrids. To continuously monitor the current through inductors and the output voltage of the FIBC, two current sensors and a voltage sensor are adopted, respectively. In the system dynamics (31), the input voltage and load change are considered the external disturbances, which degrade the system performance of the FIBC.
## 5 Simulation Setup and Experiments  
For experimental purposes, we formed three clusters featuring (a) congested traffic, (b) sparse traffic, and (c) intermediate traffic, as shown in Figure 3. Each cluster band has two lanes, and each lane has at least one or more vehicles obeying the instructions of the CH vehicle, which is a unique vehicle in a cluster. We developed restful APIs in PHP to implement our proposed protocol. We employed the most recent PHP (PHP 8) version and MySQL to maintain CA, vehicle communication, and monitoring registers. We send five different HTTP requests using the HTTP GET method. We used the Postman tool for API performance evaluation and noted the results obtained in all scenarios.  
Moreover, we worked on the resource allocation of V2V and V2I communication by proposing two algorithms and their implementation in MATLAB. To measure the security and message delivery, we compared our implementation results with the research work of [PERSON] et al. [58], which simulated their proposed protocol using an open-source Network Simulator Version 2, NS2. This tool is frequently used by researchers in computer communications and networking-related research, especially wireless networks. In this paper, we compared their research work with ours. First, we compared our protocol's resultant authentication delay, detection accuracy, keying overhead, and packet delivery ratio with the authors' results [58]. Later, we compared the transmission range in the context of packet delivery, authentication delay, keying overhead, and detection accuracy. The details of the results obtained from our experiments are described in the following sub-sections.
# Fuzzy-Based Control System for Solar-Powered Bulk Service Queueing Model with Vacation
## 6 Methodological and Technical Details
### Simulation and \(\alpha\)-Cut Integration in Results  
Each \(\alpha\)-cut level corresponds to a confidence band for the system's response under uncertain conditions. The numerical results in the tables show how the performance metrics evolve across \(\alpha\)-cuts, reflecting how the system behaves from worst-case to best-case scenarios under the fuzzy decision rules. For example, as \(\alpha\) increases, the uncertainty narrows, and performance indicators (e.g., service time, energy usage, and cost) converge, indicating increased confidence in system output.  
This structured approach ensures that every number in the results section is traceable to a methodological step--from fuzzification through rule application to P-NLP-based \(\alpha\)-cut extraction and simulation analysis. The revised results section now includes cross-references to equations, figures, and rule logic to make this linkage explicit and transparent.  
The results reveal clear performance advantages of the fuzzy-controlled system, particularly in terms of reduced delay and cost. However, trade-offs exist in terms of initial setup complexity and computational overhead. The \(\alpha\)-cut sensitivity shows how decision aggressiveness scales with certainty, which is crucial for tuning system responsiveness in real-time environments.
## 8 Practical Significance of Results  
The data presented in this study suggest that forecasting the plugging of pipe piles based solely on pile dimensions and the geotechnical profile is difficult. This is not surprising considering that plugging is influenced by a myriad of installation effects that are not captured by many of the design methods in common use. Nevertheless, forecasting the plugging before driving is necessary not only to correctly compute the capacity, but also to ensure drivability to the desired depth, especially for cases of non-uniform pile wall thickness.  
The presented results have two implications. The first is that large diameter piles, piles with diameters larger than \(\sim\)0.9 m (36 inches), are highly likely to be unplugged. The second is that piles smaller than 0.5 m (20 inches) are likely to be plugged. The design engineer has two options. The first is to assume that all piles are unplugged. This approach is in our opinion best when estimation of the correct ultimate capacity is desirable. Our opinion is based on the mean normalized capacity being closest to 1 for the unplugged assumption when considering the 74 cases examined in Figure 2 using the 4 design methods. This opinion is also supported by examining the capacities computed in Appendix D using the CPT design methods. Alternatively, the proposed diameter criterion can be used to forecast the onset of plugging when determination of plugging is paramount, for example to size the driving equipment. Utilization of the proposed diameter criterion should however be limited to piles in the same size ranges considered here in (L > 9 m (30 ft), D = 0.25-2.5 m (10-100 inches), and L/D = 6-150).