esa-sceva/satcom-chunk-collection huggingface dataset:
# Megalos: A Scalable Architecture for the Virtualization of Large Network Scenarios +
## 7 Evaluating the Scalability  
To assess the efficiency and effectiveness of Megalos we implemented the Architecture described in Section 4 (source code and testbed used in this paper are available at [53]).  
As we said in Section 4.3, any suitable language can be used to describe a network scenario that has to be realized with Megalos. In any case, in order to perform the experiments described in this section we used the same language of Kathara and the Megalos Controller is realized using a modified version of Kathara that uses Kubernetes APIs.  
We performed the following four experiments.  
Virtual LAN Scalability: We performed tests to check if Megalos can concurrently manage a large number of virtual LANs.  
Virtual Device Scalability: We designed Megalos in order to manage, even on cheap clusters, large network scenarios where each VD can be as complex as a network device. Hence, we verified that Megalos can emulate a large number of VDs each equipped with a fully fledged network protocol stack.  
Latency Scalability: A weak point of complex architectures (like Megalos) is that they might introduce unnecessary latency. Hence, we performed tests to measure the impact of Megalos on the latency of the virtual network.  
Startup Scalability: We measured the time required to startup a network scenario first by just using Kathara (single- and multi-thread) and then by using Megalos (single- and multi-worker).
# IoT-Based Implementation of Field Area Network Using Smart Grid Communication Infrastructure
## 3 Related Work  
### Web-Based Smart Energy System  
The developed prototype is intended for the remote wireless monitoring and control of a smart microgrid system situated in a field area network. The HTML webpage was designed for the monitoring and control of various energy sources. The prototype uses IEEE 802.11 and IEEE 802.3 standards for monitoring and control. An ethernet shield is used for communication between Arduino Uno and the user interface. A graphical user interface (GUI) is developed for the monitoring and control of the smart power system. The data is received at an interval of 2 s. The system works successfully in the range of around 50 m in the wireless local area network. The designed prototype was tested using all three energy sources. Sequential priorities were assigned to sources. Initially the system works on a grid. The load will then be shifted to solar and battery power based on the value of the threshold current. The prototype represents a direct current (DC) microgrid. It can operate in both grid-connected and island mode.  
The prototype was tested for a local area network using the WPA-PSK security mode. A maximum of 254 devices can be connected and regulated in the network. Other encryption options such as the wired equivalent protocol (WEP), the wireless fidelity protected access temporal key integrity protocol (WPA-TKIP), and WPA2 are also available. Further extension can be achieved by using different network devices such as switches and routers.  
A serial terminal program CoolTerm has been used to capture real-time data. Various farming machineries can be operated on any of the three energy sources based on their load serving capabilities. Figure 3 shows the design of the remote wireless monitoring and control of a smart power system. Figure 4 shows flow charts of the monitoring and control of the developed prototype. The user can monitor the data and control an entire system by entering the predefined commands on the local network webpage, as shown in Figure 5. Figure 6 shows the IoT-based monitoring and control of the developed prototype. The address of the website developed for the designed system is \"smartfield. dlinkddns.com\". When the prototype is functioning on the local network, the port can be forwarded for a WAN application. The designed prototype was tested on the developed website.  
Figure 3: Design of a smart power system.  
Figure 4: Flow charts for the (**a**) energy monitoring and (**b**) control of the prototype.  
Figure 5: Snapshot of remote wireless monitoring and control of a smart power system through an HTML webpage.  
Figure 6: Snapshot of the remote wireless monitoring and control of a smart power system on the website.
## 3 A Resilient Routing Protocol
### Routing Algorithm
#### 3.2.3 Implementation Considerations  
The practical implementation of the proposed routing protocol addresses critical challenges such as scalability, communication overhead, and energy efficiency.  
To maintain scalability, the protocol employs clustering to partition nodes into manageable groups. This reduces the complexity of routing decisions by limiting the decision-making scope to cluster representatives. The integration of deep neural networks in the DQN enables the protocol to generalize effectively across diverse network states, ensuring robust performance even in large-scale networks.  
To minimize communication overhead, the protocol uses event-driven updates. Nodes report significant changes in parameters, such as buffer usage rate or link quality, reducing redundant transmissions. Data aggregation techniques compress multiple updates into single messages, conserving bandwidth.  
Energy efficiency is achieved through intelligent routing strategies that prioritize nodes with higher residual energy and evenly distribute routing tasks. By preventing nodes with lower energy levels from serving as primary relays, the protocol extends the network's operational lifetime while maintaining high performance.
## 3 Probability of Chip Error in Coherent O-QPSK
### Validation of the Analytical Model through Simulations  
The validity of our analytical framework has been tested using Monte-Carlo simulations. The simulation tool has been implemented in MATLAB (The MathWorks Inc., Natick, MA, USA) using the complex envelopes of the signals. Asynchronous symbols are obtained by shifting the complex envelope in the time axis, while the random carrier phase is obtained through rotating the complex envelope on the complex plane. SIR values with a step of \(0.3\) dB from \(-10\) dB to \(5\) dB are simulated. At each specific SIR value, \(10,000\) random O-QPSK symbols are generated for both the interferer and useful transmitter. The complex baseband representation of the O-QPSK symbol is generated by using \(100\) points; therefore, the resolution of the time for the asynchronous O-QPSK symbols was \(10\) ns. On the other hand, the resolution for the carrier phase was \(2\pi/100\). Random asynchronous interfering symbols with a random carrier phase are generated with uniformly-distributed parameters. The excellent agreement between simulation points and analytical curves is shown in Figure 4. Since the analysis in Sections 3.1 and 3.2 is exact (no approximation is used), we expect a perfect overlapping between simulations and the analytical model. Asymptotically, there is a \(3\)-dB difference between the results of half-sine shaped and non-shaped symbols. In half-sine pulse shaping, \(P_{c}\) goes to zero at \(0\) dB, while the threshold is \(3\) dB in the absence of pulse shaping.
## 4 Antenna Array
### Normal Array
#### 4.2.2 Beamforming  
For this case, the same triangular amplitude tapering and phase values are used as in the previous configuration but considering the inversion phase feeding for the elements 2 and 4. The measured results and a comparison with the configuration of the normal array are shown in Figure 13.  
As the uniform case, the measurement of the co-polar patterns for both configurations and polarizations agree very well. The measured cross-polarization values is again comparable for both configurations with a slight deterioration when the elements are rotated 180\({}^{\circ}\)  
Figure 12: Comparison normal array and array with 180\({}^{\circ}\) rotation @ \(f_{0}\) = 1.325 GHz: normalized co-polar and cross-polar patterns (\(\varphi=~{}90^{\circ}\)). Uniform amplitude and phase distribution.  
providing an increase of the sidelobe level. The measured cross-polarization levels are higher than the simulated values. This difference is again more visible for the horizontal polarization. However, it can be seen that the overall measurements fit very well the simulated data.  
In the view of the measurements results, it can be stated that the 180\({}^{\circ}\) rotation of the antenna elements 2 and 4 do not lead to any improvement in the cross-polarization level in comparison with the configuration of the normal array, since it provides similar cross-polarization suppression values.
## 4 Results  
### Insights from Case Studies  
#### 4.1.1 Textile Industry  
Concerning the context of the textile industry, it can be perceived that a common point exists between the two companies analyzed: the need for measures to draw conclusions. The approach of using spreadsheets to collect data consumes many resources and does not allow real-time measurement (only possible weekly or monthly due to the excessive resource consumption). The adoption of systems to monitor the overall equipment effectiveness (OEE) indicator was a visible practice in the two textile companies studied (Company 1 and Company 2). Company 1 developed an app that allowed a broad range of resources, such as manufacturing order (MO) management, definition of procedures/parameters/components, and production path communication (it being possible to make annotations about MO tasks). The OEE calculation system is linked to the ERP, which makes the cost evaluation of MOs easier. Linked to this, this company also creates dashboards to analyze MO efficiency. Regarding Company 2, in addition to the OEE monitoring system mentioned, it adopted advanced planning and scheduling (APS) to evaluate production scenarios and a system to avoid paper documentation, showing dematerialization principles. Concerning the commercial part, the last company implemented a CRM system, whereby it was possible to understand prospection processes, define rules, and manage documents. The installation of a data network and the utilization of dashboards may facilitate the understanding of production status, especially of costs or efficiency, and improve the degree of accuracy concerning production dates. Regarding the best practices identified in these two case studies, Company 1 not only added technology by itself but formed teams to use the developed app and other systems and trained people to analyze data and make improvement decisions. Before starting the high-tech addition process, Company 2 analyzed its current state by means of maturity models. Still in the domain of the textile industry, it can be seen that the lean philosophy facilitates the management of DT.
# Formulating Cybersecurity Requirements for Autonomous Ships Using the SQUARE Methodology
###### Abstract  
Artificial intelligence (AI) technology is crucial for developing autonomous ships in the maritime industry. Autonomous ships, based on the collected information, recognize the environment without any human intervention and operate themselves using their own judgment. However, ship-to-land connectivity increased, owing to the real-time monitoring and remote control (for unexpected circumstances) from land; this poses a potential cyberthreat to various data collected inside and outside the ships and to the applied AI technology. For the safety of autonomous ships, cybersecurity around AI technology needs to be considered, in addition to the cybersecurity of the ship systems. By identifying various vulnerabilities and via research cases of the ship systems and AI technologies, this study presents possible cyberattack scenarios on the AI technologies applied to autonomous ships. Based on these attack scenarios, cyberthreats and cybersecurity requirements are formulated for autonomous ships by employing the security quality requirements engineering (SQUARE) methodology.  
maritime cybersecurity; autonomous ships; AI security; security requirements
## 3 Results and Discussion
### Interaction Energy  
The molecular dynamics simulation results showed that the interaction energy between water molecules and pipelines' surfaces were different (Figure 12). Interaction energy indicates the interaction role between different molecules and surfaces [45; 52; 53; 54]. The results showed that the interaction energy between water drops and pipelines were different, and the vibration decreased the interaction energy between water drops and pipelines (by almost 20%). For instance, the interaction energy between water drops and iron casting without vibration was \(-436.58\) kJ/mol, and the vibration caused the interaction energy to change by \(-358.73\) kJ/mol. The interaction energy between water drops and steel was \(-388.03\) kcal/mol, and the 300 Hz vibration caused the interaction energy to change by \(-307.24\) kcal/mol.
## 3 Research Results
### Questionnaire Survey Results
#### 3.2.2 Analysis of the Answer Data of the Questionnaire Survey  
The statistics of the collected Likert's five-scale data of the answers to the questions in the questionnaire survey are listed in Table 7, including the means and standard deviations of the data of each question, as well as other statistical numerals. It can be seen that the standard deviation values are between 0.62 and 0.86, and all the means are above 4.0 except two (namely, questions C1 and Y3), which manifest that the respondents' opinions are quite concentrated, showing small differences and conforming to normal distributions.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Data Category** & \multicolumn{4}{c}{**Statistics (Number/Percentage)**} \\ \hline \multirow{3}{*}{Gender} & Male & Female & \multirow{3}{*}{-} & \\ \cline{2-2} \cline{4-5}  & 30/42.9\% & 40/57.1\% & & - \\ \hline \multirow{2}{*}{Age} & Under 18 & 19–30 & 31–45 & over 45 \\ \cline{2-5}  & 3/4.3\% & 43/61.4\% & 8/11.4\% & 16/22.9\% \\ \hline \multirow{2}{*}{Education level} & High school & College & Graduate & \multirow{2}{*}{N/A} \\ \cline{2-2} \cline{4-5}  & 14/20\% & 46/65.7\% & 10/14.3\% & \\ \hline \multirow{3}{*}{Profession} & Civil & \multirow{3}{*}{Student} & \multirow{3}{*}{Others} & \\ \cline{2-2} \cline{4-5}  & servantOthers & & & \\ \cline{2-2} \cline{4-5}  & 3/4.3\% & 5/7.1\% & 43/61.4\% & 19/27.1\% \\ \hline \multirow{2}{*}{Media source} & Live shows & \multirow{2}{*}{Tv and movie} & Internet & Others \\ \cline{2-2} \cline{4-5}  & 33/47.1\% & 16/22.9\% & 15/21.4\% & 6/8.6\% \\ \hline \multirow{3}{*}{Watching puppetry} & In two weeks & \multirow{2}{*}{In two months} & \multirow{2}{*}{In one year} & More than \\ \cline{2-2} \cline{4-5}  & recently & & & \\ \cline{2-2} \cline{4-5}  & 28/40\% & 14/20\% & 14/20\% & 14/20\% \\ \hline \multirow{2}{*}{Experience of operating} & Yes & No & \multirow{2}{*}{-} & \\ \cline{2-2} \cline{4-5}  & similar devices & 25/35\% & 45/65\% & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Statistics of the basic data of the participants.  
The largest mean value of 4.66 comes from the answers to the question, \"C3: after using the system, I admire the puppeteer's manipulation skills\", meaning that after experiencing the role-play, the respondents agree that it is not easy to be a puppet performer, who must have multiple professional abilities to be competent. On the contrary, the lowest mean value of 3.63 comes from the answers to the question, \"Y3: after experiencing the system, I can write puppetry-show scripts and perform them by myself\", reflecting that even after experiencing the role-play process on the proposed system, the interviewees still have doubts about whether they can write and perform puppet shows by themselves, and the second lowest mean 3.77 comes from the first question, \"C1: I am very fond of watching the performances of traditional puppet shows\", which shows that the interviewees have doubts about the quite positive tone \"...very fond of watching...\" expressed in this question.
## 3 The Digital Identity Model  
A person's identity is typically certified by governments through official documents, such as birth certificates, driver's licenses, passports, and visas. Currently, a person's digital identity might be scattered on the Internet from reliable cloud services (offered by the government) and those created by self (for example, social networks, email, etc.). The latter might cause a lack of certainty about a person's identity, especially if a person could impersonate another.  
Unlike self-sovereign identity models, we are interested in trusted certifier identity systems within a blockchain ecosystem, and particularly, the government figure as a trusted entity. To do that, it is mandatory to establish a mechanism to create the first user, which we will call the government.  
Figure 1 illustrates our digital identity model in Business Process Model and Notation (BPMN). The figure includes three general roles: government, blockchain, and entities. First, the government is established, and then it has the ability to add entities and issue digital identity tokens upon request. These tokens are used to link other tokens that belong to each entity. All critical data and logic are stored through smart contracts in the blockchain that receive requests and are processed according to them. The rest of this section explains the processes of the government's creation and linking of tokenized objects in a high-level explanation. At any moment, you can relate each explanation with Figure 1 to follow the general flow.
## 3 Background and Related Works
### HIP DEX Distribution Scheme
#### 4.1.1 Initialization Phase  
Only the IoT HIP domain network is concerned with the steps of this phase. The outsider Internet hosts are not conscious of that. This phase initiates all the security parameters for all the communicating entities. In general, there are two methods to distribute the generated public key: manual and automated.  
* Manual method: This solution requires a distribution of the public key to the end devices by uploading it to their memory manually. So, there are no messages exchange to distribute the key. The pair-keys must be changed periodically and charged again to all end devices to resist key recovery. The manual distribution key is beneficial from a security point of view because attackers can not divine the public key. However, it is not practical for IoT networks qualified by their wide geographical areas;
* Automated method: Despite the energy efficiency of the manual key distribution method (omitting the key transmission), it is not practical for many IoT applications where the administrator must charge the key in devices memories at least once a month.  
We are adopting the automated method in our solution, which is more efficient than the manual method in the context of IoT and does not require any administrator intervention. This method considers the key to be exchanged in the HIP messages during initial communication. Alternatively, it is stored in the device memory and is valid even after the HIP association is terminated.
# Rolling Bearing Fault Diagnosis Based on Wavelet Packet Transform and Convolutional Neural Network
## 4 Experiment Studies  
In this section, a real-time bearing dataset from rolling bearing accelerated degradation tests is used to evaluate the effectiveness of the proposed method.
## 2 Materials and Methods
### MDDS Waveform Generator  
#### 2.3.1 Design of the MDDS Waveform Generator  
To generate the wideband waveform and satisfy the requirement, it was important to select the core component (e.g., FPGA or DAC). In this study, we selected the component considering the trade-off between the requirement and the development costs. In the proposed structure, the multiplexer (MUX) and DAC were selected based on the requirement to mix signals four-times faster. The hardware design, considering the proposed architecture, is depicted in Figure 5.  
We included a signal generation block, a clock generator, and a DAC control block in the FPGA. The signal generation block was designed for a four-times-faster signal. The FPGA outputs eight signals, which consist of cosine and sine, for two DACs. The output signals are input to each DAC and mixed to four-times-faster signals in the MUX. The clock generator creates an internal clock using an external clock for signal generation. The FPGA and DACs operate at 100 MHz and 1000 MHz of the external clock, respectively. First, the FPGA start DACs using then 100 MHz clock. Then, the DAC outputs the digital signal processing clock, which is divided by the 1000 MHz clock, to FPGA. We modified the external clock to generate the desired signal. The DAC control block controls two  
Figure 4: Pre-distortion process.  
Figure 3: Phase error compensation block (compensation phase error, CPE).  
DACs using several parameters. The parameters decide the phase shift, form of signal output, signal timing, and clock dividing value. The phase shift select (PSS) shifts a phase from 0 to 7 clocks. This can slightly adjust the phase so that the PSS is unsuitable for phase compensation. We propose a Simulink block structure for phase compensation because the phase error is larger than tens of clocks and randomly appears during RF modulation. The output clock division select (OCDS) controls the clock by dividing by 2, 4, or 8. We used the OCDS to produce a 125 MHz data clock from a 1000 MHz external clock. We used the OCDS for producing a 125 MHz data clock from a 1000 MHz external clock. Since the DAC is manufactured to use data input from a quarter of an internal clock in a 4:1 multiplex ratio, the data is read every two clock cycles. The MUX selects the multiplex rate. The MUX is set to four into one in accordance with the proposed structure. We programed the software porting between FPGA and DACs using very-high-speed-integrated-circuits hardware description language (VHDL). FPGA outputs (I of 96 pins and Q of 96 pins) are connected with DAC input pins. DAC function pins are also connected with the FPGA, so that we can control the DAC by modifying VHDL code.  
One advantage of the MDDS is that the waveform generator can output a wide bandwidth waveform using a relatively small clock at the FPGA. We used a 125 MHz clock to generate the waveform in the FPGA, although the final output has 500 MHz of bandwidth, which is a four-times-faster performance.
## 4 Performance Analysis of Multi-Constellation Kinematic PPP
### Results and Analysis  
#### 4.2.1 Availability of Multi-Constellation Kinematic PPP  
To investigate the benefits of multi-constellation PPP, the availability was analysed in terms of the numbers of visible satellites and the positional dilution of precision (PDOP) value, which is important for quantifying the GNSS positioning accuracy [25].  
Figure 2 shows the number of visible satellites and the PDOP values for each processing case. G represents GPS only, G + R represents the GPS/GLONASS combination, G + C represents the GPS/BDS combination, and G + R + C represents the GPS/GLONASS/BDS combination (as mentioned below). As shown in this figure, the GPS-only geometry was weaker than those of the three combined systems. The largest PDOP value of GPS was 20, whereas the PDOP value of the GPS/GLONASS/BDS  
Figure 1: The vehicle’s route.  
combination was always below 5. The numbers of satellites and the PDOP values of the four systems varied very stably in the first 0.4 h and from 1.1 to 1.5 h. In contrast, variation occurred very frequently during the rest of the experimental period. The reason for this result was that the vehicle stayed in static mode for the first 0.4 h and the 1.1-1.5 h. Figure 3 also explains this situation, as it shows the coordinate increments at the directions of north, east and up.
## 4 Optimization of Measurement Parameters  
It is necessary to optimize the test conditions, such as laser modulation frequency, laser modulation depth, phase angle, and demodulation method, so that the best measurement conditions for the three different gases can be met at the same time.