esa-sceva/satcom-chunk-collection huggingface dataset:
# A Survey of Internet of Things (IoT) Authentication Schemes +
## 5 Analysis of IoT Authentication Schemes
### Mobile Network and Applications  
To allow remote users to access Internet services any time, anywhere, the authors of [128] proposed a new scheme to provide a secure roaming for anonymous users benefiting from the group signature technique. They call it Conditional privacy-preserving authentication with access linkability (CPAL). In [129], the authors proposed two authentication schemes, the first one is based on pseudo-random authentication and the second is based on zero-knowledge authentication for providing authentication and location privacy-preserving scheme for LTE-A. The schemes enable all the entities in LTE-A networks to mutually authenticate each other and update their location without involving the subscriber server. The authors of [130] provided also a group-based authentication scheme for LTE networks by developing a group temporary key. It is based on both Elliptic Curve Diffie-Hellman (ECDH) that provides forward and backward secrecy, while using asymmetric key protocol to provide user's privacy. The authors of [131] proposed SEGR for the authentication of a group of devices using both 3 GPP or WIMAX systems. It is based on certificate-less aggregate signature which was proposed to remove the complication of certificate management in public key cryptography.  
Due to challenging issues in developing a user-friendly authentication scheme for smart phone environment where touch screen is the most user-friendly input peripherals, the authors of [132] provided an authentication process for Android smartphone devices using dual-factor authentication called (Duth). The protocol is made up of a registration step in which the place and time of user entering patterns to the touch screen are stored and then the stored data are used as dual factors for authentication. This approach can improve security without adding any extra hardware.  
The authors of [133] proposed a new authentication scheme for mobile phone users based on behavioural pattern. They started by collecting the behavior of mobile phone user regarding the applications used in a specific time and the duration of usage, and then they change these data to a unique pattern to be used as an authentication between the user and the mobile phone.The proposed scheme will be used as complementary to the existing authentication schemes provided by mobile phones (pin code, fingerprint, gestures, etc.).
## 3 Results and Discussion  
### Results of the Test under S1 and S2 Conditions  
#### 3.1.1 Tests on Formation of the Initial Seepage Field in the Dam Slopes of S1 and S2  
Firstly, the dam slopes of S1 and S2 were subjected to the seepage tests under the constant total head of 0.48 m. Both dam slopes had the same infiltration position. Five pressure measuring pipes were arranged in the dam body (as shown in Figures 3 and 4), and two settlement observation positions were set at the top and the middle of the dam-slope surface. In the seepage tests, the water level of the pressure measuring pipe would change with time. When the water level was stable in the pipes, it showed that the stable seepage fields were formed in the dams, and then the seepage tests were over.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **Condition’s** \\ **Name** \\ \end{tabular} } & \begin{tabular}{c} **Outer Slope** \\ **Ratio of the Dam** \\ **Slope** \\ \end{tabular} & \begin{tabular}{c} **Total Height** \\ **of Dam Slope** \\ **(cm)** \\ \end{tabular} & \begin{tabular}{c} **Initial Dam** \\ **Height** \\ **(cm)** \\ \end{tabular} & \
\begin{tabular}{c} **Rainfall** \\ **Intensity** \\ **(mm-h-1)** \\ \end{tabular} &
\begin{tabular}{c} **Length of the** \\ **Dry Beach** \\ **(cm)** \\ \end{tabular} & \multirow{2}{*}{**Test Conditions**} \\ \hline S1 & 1:2 & 50 & 10 & 17 & 60 & First, a stable seepage field was formed in the fly-ash dam, and then rainfall began. \\ S2 & 1:3 & 50 & 10 & 17 & 10 & First, a stable seepage field was formed in the fly-ash dam, and then rainfall began. \\ S3 & 1:2 & 50 & 10 & 17 & / & Dry-stack, direct rainfall. \\ S4 & 1:3 & 50 & 10 & 17 & / & Dry-stack, direct rainfall. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Test conditions.  
Figure 4: Measuring points of saturation line and settlement in the dam; (**a**) slope ratio 1:2, 1–5 were the pressure measuring pipes, D1-1 and D1-2 were the settlement observation positions; (**b**) slope ratio 1:3, 1–5 were the pressure measuring pipes, D2-1 and D2-2 were the settlement observation positions.  
The measurement results of the saturation lines during the tests are shown in Figure 5. As seen in Figure 5, the saturation lines in the dams were basically stable after 11 h, and the distribution of the final saturation lines in the two dams were basically the same.  
The settlement measurement results at the top and middle of the dam-slope surface during the seepage of the dams are shown in Figure 6. From Figure 6, the dam-slope surface had a certain settlement during the seepage process. Comparing the dam slopes with the slope ratio of 1:2 and 1:3, the vertical settlement of the latter was larger. According  
Figure 5: Time-dependent relationship of saturation lines in the dams; (**a**) slope ratio 1:2; (**b**) slope ratio 1:3.  
to the test results, the final average slope ratio of the dam slope, with the initial slope ratio of 1:2 and 1:3, turned to 1:2.1 and 1:3.2, respectively, after seepage tests.
# Intelligent Transmission Control Scheme for 5G mmWave Networks Employing Hybrid Beamforming
## 5 Experimental Results
### Research Summary  
Initially, we constructed the 5G network with a hundred user nodes, four base stations, and one server. Then, we implemented a multimedia messaging service (MMS) using mmS-TCP. Next, we estimated the channel using the RCTS-AMP. Next, we implemented digital beamforming using the \"multi-user scenario-based MATD3 (Mu-MATD3)\" method to improve communication performance. Next, we trained the beam using the DAH-BT-LSTM network. Next, we optimized the bottleneck-aware congestion mitigation using LLCCS. Finally, we plotted performance for the following metrics: number of users vs. throughput (MBPS), number of users vs. round-trip time (ms), number of users vs. end-to-delay (ms), number of users vs. packet loss (%), number of users vs. SNR (dB), and number of users vs. beamforming accuracy (%); these are illustrated in Figures 3-8 and Tables 5-11.
# Handover Management for Drones in Future Mobile Networks--A Survey
## 3 Connectivity Requirements for Drones  
Drone implementation confronts a number of challenges; one of the most significant is the connectivity. Drones' connectivity is more complicated than that of terrestrial UEsbecause of their characteristics. Drones, for example, have a higher mobility than UEs, resulting in a huge variance in the Reference Signal Received Power (RSRP). Connected drones may continue switching the connection link from one cell to another. As a result, connection between drones and the serving network may be quickly lost. To address this issue, several studies have been conducted throughout the literature, in which several key requirements for drones' communication have been discussed. Thus, in this paper, the key requirements for drones' communication, and its capabilities and 6G expectations, are discussed in the following.
## 3 Comprehensive Evaluation of Configuration
### Analysis of Performance Indicators  
The analytic hierarchy process (AHP) [30] is employed during the definition of indicator weights to assess the correlations between configuration performance indicators. Let \(a_{ij}\) denote the relative importance of indicator \(i\) over indicator \(j\) and \(a_{ji}\) represent the relative importance of indicator \(j\) over indicator \(i\). If indicators \(i\) and \(j\) are equally important, both \(a_{ij}\) and \(a_{ji}\) are assigned a value of 1. If indicator \(i\) is slightly more important than indicator \(j\), the relative importance \(a_{ij}\) is 3, while \(a_{ji}\) is 1/3. If indicator \(i\) is significantly more important than indicator \(j\), \(a_{ij}\) is 5, and \(a_{ji}\) is 1/5. If indicator \(i\) is strongly more important than indicator \(j\), \(a_{ji}\) is 7, and \(a_{ji}\) is 1/7. The resulting table of relative importance is shown in  
Figure 8: Membership of each indicator of multi-winged deployment mechanism configurations.  
Then, the judgment matrix A is as follows:  
\[A=\begin{bmatrix}1&1/3&1/3&1/3&1/3\\ 3&1/3&1/3&1/3&1/3\\ 3&3&1&1/3&1/3\\ 3&3&3&1&1/3\\ 3&3&3&3&1\end{bmatrix}\]  
Due to the inherent subjectivity of the judgment matrix, the root method is employed to determine the eigenvector of the matrix.  
The initial weighting coefficients are calculated according to Equation (13).  
\[W_{i}^{\prime}=\sqrt[n]{a_{1i}a_{2}\cdots a_{im}} \tag{13}\]  
where \(i\) is the no. i indicator; \(m\) is the total number of indicators; and \(a\) is the value of the indicator correlation.  
The normalized weighting coefficients \(W_{i}\) are calculated as indicated in Equation (14).  
\[W_{i}=W_{i}^{\prime}/\sum_{i=1}^{m}W_{i}^{\prime} \tag{14}\]  
The weights of each indicator are calculated utilizing Equations (13) and (14), as illustrated in Figure 9.
## 1 Introduction
No matter in wireless sensor networks (WSNs) or WRSNs, multi-hop transmission is employed to forward data back to the sink node and the appearance of the energy hole will interrupt the communications. Figure 1 shows the concept of the multi-hop transmission and demonstrates how the sensor nodes in the hot zone take the responsibility of forwarding the data to the sink node. Wireless charger deployment problems have attracted substantial attention in recent years. We review a number of the relevant previous studies. [PERSON] et al. [10] focused on the omnidirectional wireless charger deployment problem and deployed charging devices in the sensing area of interest to provide enough charging power to maintain the operation of the network, but they explored the space with a more traditional triangle solution. [PERSON] et al. [11] divided the sensing areas into grids  
Figure 1: The power unbalanced phenomenon of wireless sensor networks (WSNs). and placed omnidirectional wireless chargers on various grid points. Their deployment also took into consideration the moving paths of mobile sensors. In a study by [PERSON] [12], the coverage area of the chargers was conical, and the sleep schedule of the chargers was considered in order to reduce the power consumption. Compared with the aforementioned studies of omnidirectional wireless chargers, studies by [PERSON] and [PERSON] [13; 14] considered the deployment of the directional chargers and defined the charging area of a directional charger as a sector with a given angle. In the [PERSON] and [PERSON] study [13], triangles were used to represent the charging area of directional chargers, so an integer linear programming solution was proposed in which each grid point represents a possible location of the deployment. The [PERSON] et al. study [14], meanwhile, minimized the number of deployed chargers while also considering the connections among chargers. The reviewed literature is organized in Table 1 below. Interestingly, these studies did not consider the unbalanced power consumption effect caused by forwarding data to the sink node. Such unbalanced power consumption can make the sensor nodes near the sink rapidly lose power.
# Automated Docking System for LNG Loading Arm Based on Machine Vision and Multi-Sensor Fusion
## 2 Design of Docking Logic and Kinematic Analysis for LNG Loading Arm
### Decomposition of LNG Loading-Arm Docking Tasks
#### 2.1.1 Characteristics and Control Strategy of the Automatic Docking System  
The automatic docking system for LNG loading arms is designed to meet the following requirements, ensuring reliable operation in complex marine environments:  
* Docking accuracy: The system must achieve high precision in aligning the loading arm with the target flange, even under environmental disturbances such as wind and waves. The docking accuracy must meet engineering standards, typically within a millimeter-level error range, to ensure safe and reliable operations;
* Docking speed: The system must achieve high precision in aligning the loading arm with the target flange, even under environmental disturbances such as wind and waves. The docking accuracy must meet engineering standards, typically within a millimeter-level error range, to ensure safe and reliable operations.  
To fulfill these requirements, the docking process is divided into two phases: coarse docking and fine docking. Each phase has tailored control strategies to balance speed and accuracy, ensuring effective and efficient docking under various operational conditions.
## 2 Background
### An Overview of Internet of Vehicles
#### 2.1.1 Benefits of Internet of Vehicles  
IoV has the potential to transform the transportation industry's landscape, making travel safer, more efficient, and friendlier to the environment. The IoV provides several opportunities for improvement and numerous benefits, including the following [3]:  
* Lower costs: Improved traffic control results in lower costs, including insurance premiums and operational costs.
* Time efficiency: Traffic is meticulously monitored, examining the time people spend on the road.
* Reduced risk of fatalities: Examining the transportation environment can reduce accidents, such as by helping drivers navigate traffic [8].
* Smart cities development: Smart cities are more organized due to the services they provide, including enhanced navigation and real-time traffic.
* Greenhouse effect reduction: This limits harm to the world.
* Emergency response: IoV can autonomously notify emergency services in the case of an accident, potentially diminishing reaction times and saving human lives.
* Autonomous driving: IoV is an essential part of the development of autonomous and semi-autonomous vehicles, both of which can lower the number of accidents resulting from human mistakes and enhance general road safety.
* Traffic documentation: Filming traffic accidents using services such as pics-on-wheels allows any vehicle on the road to act as a witness to any accident. Among other outcomes, this encourages people to maintain decorum on the road.  
In general, IoV offers the potential for safer, more intelligent, and more efficient mobility for individuals and society as a whole.
# Degradation Assessment of In-Service Transformer Oil Based on Electrical and Chemical Properties
## 4 Discussion
### Assessment of the DGA Results
#### 4.2.1 CO2/CO Ratio  
The presence of carbon monoxide, carbon dioxide, methane, and moisture content across all transformers signifies cellulose insulation degradation. It was observed that the degradation rate was most pronounced in T1 and T2, as shown by consistently elevated carbon monoxide and moisture levels with each service year, in contrast to the T3 profile, where carbon monoxide levels decreased while moisture content continued to rise. According to the IEC 60599 standard, a carbon dioxide to carbon monoxide ratio of less than 3 is associated with cellulose insulation due to electric faults [14,28]. The ratio was evaluated for each transformer for every service year (Table 5) and was found to be well below 3, hence, representing the degradation of cellulose insulation.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Fault Gas**} & \multicolumn{8}{c}{**Indication**} \\ \cline{2-10}  & **Cellulose** & **Mineral Oil** & **Leaks in Oil** & **Thermal** & **Thermal** & **Thermal** & **Thermal** & & \\  & **Aging** & **Decomposition** & **Expansion** & **Fault–** & **Fault–** Oil** & **Fault–** Oil** & **Fault–** Oil** & **Fault–** Oil** \textgreater{} & **Fault–** Oil** & **Fault– Oil** \textgreater{} & **P0 \textasci{} 1** & **Arcing** \\  & & & **Systems** & **Cellulose** & **(150-300 \textasci{}C)** & **(300-700 \textasci{}C)** & **700 \textasci{}C** & **700 \textasci{}C** & & \\ \hline CO & Y 2 & — & — & — & Y & — & — & — & — & — \\ CO2 & Y & — & Y & Y & — & — & — & — & — \\ CH4 & — & Y & — & Y & Y & Y & Y & Y & Y \\ C2H3 & — & Y & — & — & — & T3 & Y & T & Y \\ C2H4 & — & Y & — & — & — & T & Y & — & Y \\ C2H6 & — & Y & — & — & Y & Y & — & — & — \\ O
## 3 Results and Discussion
The presented data can be interpreted as a reduction of structure's size in the direction perpendicular to the field direction, and thus loss of scattering at lower \(Q\). In Figure 5, the formation of a local maximum at \(Q\approx 10^{-4}\) A\({}^{-1}\) corresponding to the typical size of about 6 \(\upmu\)m is observed, which is close to the mean particle diameter. This would suggest the formation of elongated aggregates of aligned individual particles. However, such explanation does not work well for Figures 2 and 3 where a tendency to formation of a local maximum corresponding to the typical size of roughly 20 \(\upmu\)m or larger can be assumed after what was said above. Also for these samples, loss of scattering for lower \(Q\) is observed. The typical size of 20 \(\upmu\)m would be larger than the distance between uniformly distributed spherical particles with the mean diameter as used in our samples, corresponding to several particle diameters. Clearly, the particle concentration in Figures 2  
Figure 5: USANS curves of the MAE sample with 80 mass% of Fe and a soft matrix for different magnetic fields. and 3 is much smaller than in Figure 5. It is unlikely that large particle aggregates formed in these samples in the non-magnetized state. The origin of the observed effects may be in the resulting anisotropy of neutron scattering due to magnetically induced anisotropy of particle distribution. Such an effect has been observed in [31] where it has been found that the maximum amplitude of scattering is in the direction parallel to the field direction. The hysteresis of Figure 5 becomes more clearly visible in Figure 6 where we plotted the area under the interpolated scattering curve in dependence on the magnetic flux density. The points in Figure 6 have been obtained in the following way. Each curve in Figure 6 was linearly interpolated between the measurement points and then integrated, the result of integration was divided by the length of the \(Q\) range and normalized by the maximum of the available results. The hysteresis in Figure 6 is attributed to the magnetic-field-induced restructuring of filler particles, which is also the origin of magnetic hysteresis in such a material. It is known that the CIP particles are soft magnetic and possess a negligible magnetic hysteresis loop at room temperature [36]. In soft MAEs, the magnetic hysteresis appears in a particular form of a \"pinched\" hysteresis loop and it completely disappears at low temperatures when the matrix becomes stiff [37]. The relation of hysteresis of magnetic properties to the hysteresis of the consolidation of filler particles into elongated aggregates was explained by [PERSON] et al. [30].
# A Review of Practice and Implementation of the Internet of Things (IoT) for Smallholder Agriculture
## 3 Results and Discussion
### Discussion of Challenges and Recommendations
#### 3.3.1 Measurement Device Challenges  
Access to components: Off-the-shelf IoT products are often not available, suitable, or affordable for commercial technologies in developing countries. Therefore, custom made solutions are designed in-house or by local IoT companies. During our site visit in Kenya, a number of IoT implementation teams that we spoke to indicated that procuring electronic and hardware components during the product development phase often delayed the project and increased costs.  
_Technologists_: A good starting point for prototype circuit components is the local electronics and scrap market (e.g., CBD in Nairobi, Kisenyi in Kampala, Suame Magazine in Kumasi). These markets usually stock basic circuit and prototyping components that can be used as a \"good enough\" solution to reach a proof-of-concept prototype.  
Device design: Smallholder farms are often in rugged and remote locations and require special consideration when designing a connected, electronic device for long-term monitoring.  
_Technologists_: As soon as possible in the design process, test your device at a pilot site that is representative of the actual implementation site.  
_Project managers_: Involve the farmers, agriculture extension agents, and farmer co-operatives in the product design phase to help your team identify non-obvious challenges and improve the likelihood that farmers will accept the idea.  
Sensor calibration: Correlating the raw sensor measurements to actual physical values requires performing controlled calibration tests that can be expensive and time consuming.  
_Technologists_: Aim to eventually provide calibration documentation for your product so that it can be benchmarked against other products and measurement methods. Perform some simple tests to check factory-calibrated sensors in conditions as close to the implementation conditions as possible in case there is a need to apply a correction factor.  
Access to expertise: Many teams we visited mentioned a lack of access to expertise and resources for technical and business challenges. For example, several engineers reported spending significant amounts of time combing through websites to find technical solutions during their product development.  
_Technologists_: Participate in online communities focused on IoT for agriculture hardware, especially for idea exchange, technical support, and recruiting. For example, we found the Gathering of Open Ag Tech to be a good example of such a resource in the agriculture sector (forum.goatech.org).
# Magnetic Field Penetration Depth in Various Materials and Applications
## 4 Discussion
The application of the magnetic field penetration depth could revolutionize areas such as the detection of metals and other materials under complex media, including water, rock, sand, clay, wet soil, biological tissues (such as animal skin), wood, and concrete. This approach could significantly improve scanning and diagnostic capabilities in hard-to-reach environments. The design of new materials capable of blocking magnetic fields without interfering with data transmission represents a promising challenge. Such shielding could be key to ensuring signal integrity in advanced communication systems, particularly in environments with high electromagnetic interference. The exploration of the magnetic field as a means to transport wireless energy and information could transform telecommunications technology and remote power systems, offering more efficient and sustainable solutions. The interaction of the magnetic field with biological tissues opens up new possibilities in regenerative medicine, such as the controlled stimulation of skin, soft tissue, and bone regeneration. This could be an effective alternative in the treatment of chronic diseases and traumatic injuries. Magnetic field-based technology could be used to detect cracks and structural defects in buildings in a non-invasive way. This would provide a valuable tool for the assessment and maintenance of critical infrastructure. The use of the magnetic field in modulating biological behavior could help control insect populations harmful to human health. In addition, selective exposure to magnetic fields could be investigated as a method to deactivate or destroy viruses and other pathogens in the environment. Figure 11: Symbolic schematic of magnetic field penetration (adapted from [89]). These ideas, presented through experience, mathematical models, and scientific readings, advance the possibility of futuristic scenarios combining applied physics, advanced engineering, and biotechnology, opening new frontiers for science and technology.