esa-sceva/satcom-chunk-collection huggingface dataset:
# Improving Healthcare Facilities in Remote Areas Using Cutting-Edge Technologies
## 5 Discussion
### Constraint and Limitation  
The study proposed the use of cutting-edge technologies to provide remote access to healthcare facilities. However, a few implementation details mentioned in the proposed methodology are generic to make it more flexible. Further, 5G is provided as a means of communication between various healthcare entities, while 5G is not implemented completely yet, especially in remote areas. How the organization will use cloud computing facilities and in which capacity, what ML algorithms and techniques will be used for prediction and detection of vitals is also mentioned generically so that healthcare organizations may tailor it according to their needs.
## 1 Introduction
For example, in a hospital environment, where many WBASNs are used for medical purposes, nearby WBASNs or other equipment operating at the same frequency band cause interference, and the lost signals may lead to a dangerous situation in the medical systems. Hence, it is considerably necessary to consider interference mitigation in the design. WBASN interference can be categorized into three types: (1) Intra-WBASN interference occurs among sensor nodes within the same WBASN; (2) inter-WBASN interference occurs among WBASNs working at the same frequency band; and (3) inter-domain interference or cross-interferenceoccurs between a WBASN and other wireless networks (e.g., Bluetooth, Zigbee, or WiFi) [7]. These forms of interference should be avoided or mitigated to ensure signal quality in WBASNs. In this paper, existing interference mitigation schemes for WBASNs are extensively surveyed and discussed. The interference mitigation schemes are categorized into power control approach, MAC approach, cognitive radio approach, ultra wideband (UWB) approach, and signal processing approach. The important aspects of coexistence and interference in WBASNs are investigated first. Various interference mitigation schemes are then reviewed and compared. Some open issues and challenges are also discussed. This paper is organized as follows: In the following section, the key points on coexistence and interference in WBASNs are introduced. The interference mitigation schemes are reviewed in detail in Section 3, and they are qualitatively compared and discussed in Section 4. In Section 5, open issues and challenges are discussed. Finally, the paper is concluded in Section 6.
# Bridging the Gap: A Survey and Classification of Research-Informed Ethical Hacking Tools
## 6 Evaluation
### Tool Development and Maintenance  
We examined the GitHub repositories of the 59 publicly available tools to understand specific features related to tool development and maintenance. Specifically, we collected data on the number of _commits_ and the dates of the first and the last _commits_. We believe analysing _commit_ activity in GitHub repositories provides insights into the development intensity and duration. However, we must consider that projects can move from one repository to another and that a private repository is used alongside a private one, and the public one is used only for dissemination purposes. Therefore, we can only attempt to capture some trends with this analysis, but we must be cautious about making statements regarding specific projects.  
Table 5 (a) provides an overview of the distribution of project activity periods. We measured the difference in months between the first and last _commit_ for the considered projects. The data shows that approximately one-third of the projects have a relatively short activity span of less than 3 months. This may indicate that the publication of the source code has likely been instrumental to the publication of the paper.  
Comparing the year of publication of the paper and the date of the first _commit_, we can see that around 90% of the projects have been active sometime in the year before or after the publication. This is not surprising. However, fewer than 10% of the projects have been active 2 or more years before the publication, according to publicly available data.  
Another parameter we considered is the number of _commits_ (Table 5 (b)). The data highlights the diversity in project engagement and development intensity within the examined dataset. Around 30% of the projects have just up to 10 _commits_. As the _commit_ ranges increase, the percentage of projects gradually decreases. Projects with a higher number of _commits_ (500+) account for 13.33% of the total, indicating a smaller but notable proportion of projects with an extensive development history.  
Table 6 represents the activity level as a percentage of the time between a project's release and the present. Additionally, _100-100_ indicates continuous activity throughout the period, while _0-0_ signifies no activity at all. For example, _26-50_ means that the project was active for at least 26% and up to 50% of the considered time interval (9-18 months).  
Figure 7: Distribution of tools by license type.  
The data shows that one-third of the projects remained active within three years after their release. However, over half of these projects ceased activity after just 1.5 years. This trend sheds light on the development lifecycle of these projects, indicating a high initial engagement that tends to taper off relatively quickly for a significant number of projects.
# Future Scenarios for Software-Defined Metro and Access Networks and Software-Defined Photonics
## 3 Solutions for Software Defined Metro and Access Networks
### Physical Layer Re-Configurability
#### 3.2.4 Optical Switching at the Physical Layer
The offset time between BHP and BDP allows the router to be buffer-less, avoiding optical memories, such as fiber delay lines, contrarily required by OPS [52]. Moreover, while OPS requires fast switching speed (approximately in nanoseconds), OBS can be realized even with simple nodes with millisecond to microsecond switching speeds. Optical flow switching (OFS) can be considered a subcategory of OBS, where end-to-end flows are established and bursts are longer by at least hundreds of milliseconds. All these techniques will allow to process packets, bursts, or flows on-the-fly in the framework of future photonic routers or nodes, even in the access and metro networks.
## 3 Results and Discussion
### Experimental Results  
The experimental studies for the Vo-CAP process were carried out on the manufactured die in accordance with the optimized process parameters. During the process, the workpiece emerges from the channel marked with red dashed lines as shown in Figure 16a. The die's conical design allows for easy assembly and disassembly without using tradi  
Figure 14: Pareto-optimal solutions generated by NSGA-II (optimum point \(\overline{\epsilon}\) = 16.49, ML = 15.69, and CV\(\varphi\) = 0.375).  
Figure 15: Optimum design variables of Vo-CAP. (**a**) Geometrical details. (**b**) Manufactured Vo-CAP die.  
tional fasteners like bolts or nuts. The resistor rods and thermocouples integrated into the die holder kept the processing temperature constant at 210 \({}^{\circ}\)C throughout the experiments.  
The processed AA6082 workpieces, as shown in Figure 16b, demonstrate the successful implementation of the Vo-CAP process. The workpiece show uniform deformation along its length, with no visible surface defects or irregularities, indicating stable material flow during processing. The dimensional consistency of the processed workpiece confirms the precision of the manufacturing process and the effectiveness of the die design.  
The unprocessed workpiece shown in Figure 17 clearly demonstrates the effectiveness of the Vo-CAP process. The workpiece has taken the precise shape of the die channel geometry, showing both the VE and ECAP channel. This processed part demonstrates that the workpiece successfully flowed through all stages of the die, maintaining the designed forming patterns. The shape particularly highlights the combined effect of both the vortex and ECAP deformation mechanisms.  
Figure 16: (**a**) View of the workpiece (red dashed line) emerging through the exit channel during the Vo-CAP process. (**b**) Vo-CAP-processed AA6082.  
Figure 17: Deformation path geometry in Vo-CAP die.
# Potential of a SAR Small-Satellite Constellation for Rapid Monitoring of Flood Extent
## 2 Methods
### Assessment of Revisit Rates and Revisit Time  
As a preliminary step for the subsequent virtual experiment in flood monitoring using the designed SAR small-satellite constellation, we sought the appropriate \(T/P/F\) parameter settings in the WC method. Although the potential combinations of these parameters are finite (assuming that \(F\) is an integer number), predetermination of the parameter setting that is likely to perform well for each \(T\) is advisable to ensure effective analysis. Thus, revisit rates and revisit time were assessed for all combinations of \(T/P/F\) for each \(T\). Here, we provisionally tried to determine the settings of \(T\) that were likely to accomplish the revisit time in the order of one to several hours. To investigate the area to be observed by each SAR small-satellite constellation, the mapping of observable range \(L\) along the satellites' passes was simulated for the period of the recurrent days--18 days in this case--as listed in Table 1. Then, several representative points were prepared to check the observation timings. We named these points ground check points (GCPs) and set GCPs at five locations in Japan: Sapporo, Sendai, Tokyo, Osaka, and Fukuoka, whose locations are depicted in Figure 2 (left). Figure 2 (right) presents an example of the ground tracks of satellites (purple line), observable range \(L\) (yellow belt zone), and swath width (orange belt zone) both in an ascending pass and a descending pass. The revisit rates and revisit time can be calculated by extracting the date and time when the observable zone catches the GCPs. Because the calculation period was set at 18 days, the daily revisit rates at each GCP was calculated by dividing the total number of observations for that point by 18. For the revisit time, the mean revisit time was calculated by averaging the time interval between observations for all GCPs and the maximum revisit time was calculated by extracting the largest time interval between observations for all GCPs.
# Fault ride-Through Control Strategy for Variable Speed Pumped Storage Unit with Full-Size Converter
## 3 Analysis of Fault Ride-Through Characteristics
### LVRT Characteristics
Under the pumping conditions, the rotor speed of the motor satisfies Equation (9). \[J_{T}\omega_{g}\frac{d\omega_{g}}{dt}=-P_{m}+P_{s} \tag{9}\]  
During the low-voltage period, the converter is unable to smoothly transmit power from the grid to the motor in a short period, and the electromagnetic power \(P_{S}\) on the machine side will be significantly reduced. The mechanical power \(P_{m}\) remains basically unchanged, which will lead to a spontaneous decrease in frequency or speed of the unit. According to Equation (2), it is known that a significant decrease in unit frequency or speed will significantly decrease the flow rate and water head. If the frequency or speed is too low, the unit will seriously deviate from the optimal pumping point, and its operation efficiency will be reduced. Additionally, if the water flow surges in the diversion pipeline for a long time, it will pose a safety risk on the pipeline or even force the unit to shut down.
## 4 Conclusions  
The present study describes the first synthesis and characterization of the [Cu(L)(NO\({}_{3}\))(H\({}_{2}\)O)\({}_{2}\)]\(\bullet\)H\({}_{2}\)O complex. The AMT ligand is a bidentate N,O donor, which coordinates with Cu\({}^{2+}\) in 1:1 ratio. Full characterization of the [Cu(L)(NO\({}_{3}\))(H\({}_{2}\)O)\({}_{2}\)]\(\bullet\)H\({}_{2}\)O complex suggests the octahedral structure shown in Figure 8. The reaction between AMT and copper(II) was used to develop an effective spectrophotometric procedure for the determination of copper in water samples. The developed method is simple, low cost, and sensitive with LOD of 11.00 ppb. The proposed chromogenic reagent operates at a wide range of concentrations and pH values. On the other hand, the developed method can work as a sensitive chemo sensor for copper monitoring in water samples since color change due to reaction of AMT with Cu(II) appears rapidly within less than 10 s and remains stable for up to 2 h.  
**Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2076-3417/10/11/3895/s1](http://www.mdpi.com/2076-3417/10/11/3895/s1)]([http://www.mdpi.com/2076-3417/10/11/3895/s1](http://www.mdpi.com/2076-3417/10/11/3895/s1)), Figure S1: 1\(\mathrm{H}\) NMR spectrum of AMT ligand, Figure S2: 13C NMR spectrum of AMT ligand, Figure S3: The electronic spectrum of [Cu(L)(NO\({}_{3}\))(H\({}_{2}\)O)\({}_{2}\)]\(\bullet\)H\({}_{2}\)O.  
**Author Contributions:** Investigation, methodology, validation and writing: S.S.A. and H.M.A.-S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multicolumn{3}{c}{**Spectrophotometric Method**} & \multicolumn{3}{c}{**ICP-OES**} \\ \cline{2-7}  & \begin{tabular}{c} **Amount of Added** \\ **Cu(II)** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} **Found** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} **Recovery \%** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} **Amount of Added** \\ **Cu(II)** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Found** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} &
\begin{tabular}{c} **Recovery \%** \\ **(ug mL\({}^{-1}\))** \\ \end{tabular} \\ \hline Red Sea water & — & ND & — & — & ND & — \\ Red Sea water & 4 & \(3.79\pm 0.31\) & 95.0 & 4 & \(3.62\pm 0.22\) & 90.5 \\ Tap water & — & ND & — & — & ND & — \\ Tap water & 4 & \(3.95\pm 0.23\) & 98.7 & 4 & \(3.78\pm 0.15\) & 95.0 \\ \hline \hline \end{tabular}  
* ND: not detected.  
\end{table}
Table 7: Evaluation of proposed spectrophotometric method by determining copper in water samples *.
# 25 Years of Bluetooth Technology
## 6 Recent Research Results on Bluetooth
### Health  
Many research works have focused on demonstrating the use of Bluetooth Low Energy (BLE) for developing wearable IoT sensor networks for health applications [44; 45; 46; 47; 48]. These BLE health sensor networks implement different types of monitoring including temperature, humidity, and carbon dioxide for environmental observations or body temperature and heart rate for physiological conditions [44; 46]. A BLE sensor network consisting of emotion sensors has been demonstrated to help observe a body's emotion regulation process. These can serve as wearable biofeedback devices and are useful in clinical and psychological research [45].  
Remote health monitoring using wearable sensors for continuous examination of blood pressure, heart rate, and body temperature is also becoming a popular Bluetooth use-case [46]. The vital data can be communicated from sensors via Bluetooth to nearby \"gateway\" devices such as Android smart phones, and so on. It has been demonstrated that Bluetooth provides better transmission rate than Zigbee and better cost-efficiency than the Global System for Mobile Communication (GSM) [46].  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Attacks Prior to Pairing** & **Attacks after Pairing** \\ \hline BlueJacking & Backdoor \\ BlueSmarfing & Denial of Service (DoS) \\ BlueBugging & Worm \\ MAC spoofing & Bluesemack \\ Helemoto & MultiBlue \\ BluePrinting & Offline PIN recovery \\ Fuzzing & BD\_ADDR \\ BlueBorne & Reflection/Relay \\ \hline \hline \end{tabular}
\end{table}
Table 3: List of Bluetooth attacks.  
Recently, researchers have also investigated Bluetooth for developing pervasive healthcare solutions for mental health [47]. By utilizing a Bluetooth-based wireless monitoring system, researchers have shown the possibility of monitoring mental health in individuals by collecting and analyzing physiological signals such as short-term Heart Rate Variability (HRV) from a wristband worn during natural daily activities. Remote management of patients for chronic diseases in general has also been the focus of research lately. The remote monitoring kits include wireless sensors with Bluetooth Low Energy connectivity to a local gateway (tablet/smartphone with specialized software) and a network connection to a centralized cloud-oriented application for data processing and storage [48].
## 3 The Extraction of Offset, Gain, Time Skew, and Bandwidth Mismatch
### The Extraction of the Offset and Gain  
The offset can be extracted from the following formula:  
\[\widetilde{o}_{i}=\frac{\sum\limits_{n=1}^{L_{\text{o}}}y_{i}[n]}{L_{\text{o}}}, \tag{10}\]  
where the offset \(\widetilde{o}_{i}\) is approximated by the \(L_{\text{o}}\) samples of the \(i\)-th sub-ADC. Similarly, the gain can be extracted from the following formula [28]:  
\[\widetilde{g_{i}}=\frac{\sqrt{\sum\limits_{n=1}^{L_{\text{g}}}y_{i}^{2}[n]}}{ L_{\text{g}}}, \tag{11}\]  
here the gain \(\widetilde{g}_{i}\) is approximated by the \(L_{\text{g}}\) samples of the \(i\)-th sub-ADC.  
Based on Equations (10) and (11), the offset and gain can be estimated. However, the process of estimating the gain in Equation (11) involves many multiplications. When the offset has been calibrated, Equation (5) can be rewritten as follows:  
\[Y_{\text{ical o}}(j\omega)=\Delta g_{i}e^{-j\omega\Delta\tau_{i}}H_{\Delta \omega_{ij}}(j\omega)X_{i}(j\omega). \tag{12}\]  
Based on the Equations (8) and (12), the correction of the gain, time skew, and bandwidth mismatch can be represented as follows:  
\[y_{\text{ical o, g, \tau, \omega}}[n]=y_{\text{ical o}}[n]*h_{\Delta g_{i} \Delta\tau_{i}\Delta\omega_{i}}[k], \tag{13}\]  
where \(h_{\Delta g_{i}\Delta\tau_{i}\Delta\omega_{i}}[k]\) can be obtained with the following:  
\[h_{\Delta g_{i}\Delta\tau_{i}\Delta\omega_{i}}[n]=\frac{h_{\Delta\tau_{i} \Delta\omega_{i}}[n]}{\Delta g_{i}}. \tag{14}\]  
Figure 3: Proposed structure of correction time skew and bandwidth mismatch.
# Efficient Collaborative Edge Computing for Vehicular Network Using Clustering Service
## 2 Background  
### Edge Computing  
In contrast to cloud computing, edge computing performs computing at the edge of the network to provide all kinds of computing closer to the source of the data [2,14]. Edge computing has been introduced and defined by different scientific people from different perspectives. For example, Professor [PERSON] at Carnegie Mellon University defined edge computing as follows: \"Edge computing is a new computing model that deploys computing and storage resources (such as cloudlets, micro data centers, or fog nodes,etc.) at the edge of the network closer to mobile devices or sensors\" [14]. [PERSON] et al. defined the concept of edge computing as follows: \"Edge computing is a new computing mode of network edge execution. The downlink data of edge computing represents cloud service, the uplink data represents the Internet of Everything, and the edge of edge computing refers to the arbitrary computing and network resources between the data source and the path of cloud computing center.\" [15,16].  
China's edge computing industry describes edge computing as follows: \"Near the edge of the network or the source of the data, an open platform that integrates core capabilities such as networking, computing, storage, applications, and provides edge intelligent services nearby to meet the industry agility key requirements in connection, real-time business, data optimization, application intelligence, security, and privacy\" [17]. In other words, edge computing is the process of migrating the cloud network's partial capabilities to the edge of the network, near the IoT source. On the other hand, the IoT source devices migrate their heavy processes, fast decision making, and power to the same corresponding edge computing network. Figure 1 compares the network load between the IoT using the cloud and the IoT using the edge server.  
Edge computing is utilized to enhance vehicular services by distributing computation tasks among edge servers and vehicular end devices. In this case, the application/services will be closer to the vehicular end-device users or even perform computing directly in the vehicles. There are many advantages in the field, such as higher efficiency, lower latency, and proximity services. Several approaches push cloud computing capabilities to the network edge, including fog computing, MEC, and cloudlets. Although all solutions in edge computing have the same intention and motivation, various paradigms also have their particular features. The concepts are partially overlapping but complementary as well. Table 1 illustrates a comparison between three edge computing paradigms.
# IAACaaS: IoT Application-Scoped Access Control as a Service +
###### Abstract  
access control is a key element when guaranteeing the security of online services. However, devices that make the Internet of Things have some special requirements that foster new approaches to access control mechanisms. Their low computing capabilities impose limitations that make traditional paradigms not directly applicable to sensors and actuators. In this paper, we propose a dynamic, scalable, IoT-ready model that is based on the OAuth 2.0 protocol and that allows the complete delegation of authorization, so that an as a service access control mechanism is provided. Multiple tenants are also supported by means of application-scoped authorization policies, whose roles and permissions are fine-grained enough to provide the desired flexibility of configuration. Besides, OAuth 2.0 ensures interoperability with the rest of the Internet, yet preserving the computing constraints of IoT devices, because its tokens provide all the necessary information to perform authorization. The proposed model has been fully implemented in an open-source solution and also deeply validated in the scope of FIWARE, a European project with thousands of users, the goal of which is to provide a framework for developing smart applications and services for the future Internet. We provide the details of the deployed infrastructure and offer the analysis of a sample smart city setup that takes advantage of the model. We conclude that the proposed solution enables a new access control as a service paradigm that satisfies the special requirements of IoT devices in terms of performance, scalability and interoperability.  
IoT; security; access control; identity management; OAuth 2.0; IAACaaS Article
## 6 Conclusions  
The results of our systematic, comparative study clearly suggest that at this stage of technology, capacitive sensing with electronic detection (CE) of vapour traces of explosives in the atmosphere is far superior to the existing solutions based on chemo-mechanical (CMO) sensing using MEMS with an optical detection. The advantage of CE is not only in nearly two-orders of magnitude higher sensitivity to vapours, but also in a much better temperature stability of sensors and detection equipment, robustness to mechanical (acoustic) noise from the environment, and much smaller volume and power consumption. Moreover, we expect that by further integration of comb sensors and by decreasing the spacing between the electrodes of comb sensors, the sensitivity of the CE method could be increased by an additional two orders of magnitude. This means that detection of 1 molecule of TNT in 10\({}^{+14}\) molecules of a carrier N\({}_{2}\) could be achieved in the near future.