esa-sceva/satcom-chunk-collection huggingface dataset:
# Knowledge Tracing Model and Student Profile Based on Clustering-Neural-Network
## 2 Frame of C-B-KT
### Data Encoding And Data Clustering  
Question encoding is used for question vectorization to facilitate clustering. One-hot coding has been widely used in KT research [17]. In one-hot coding, each question is usually represented as a manually marked knowledge concept, but the rich information contained in the question text has not been fully mined. In order to mine text information, this paper uses the [PERSON] model for coding. [PERSON] uses Transformer, which is more efficient than Recurrent Neural Networks (RNNs) and can capture longer-distance dependencies [18]. The question vector after Bert encoding contains more hidden information.  
Student encoding is used for student vectorization to facilitate clustering. This paper assumes that a student's ability does not change in a short period of time. The student vector is obtained by observing the student's response to all questions. Suppose the response sequence \(s_{i}=(e_{i_{1}},r_{i_{1}}),(e_{i_{2}},r_{i_{2}}),\ldots,(e_{i_{r}},r_{i_{l}})\). Here, \((e_{i_{l}},r_{i_{l}})\) means that if student i answers the question \(e_{i_{l}}\) correctly, then \(r_{i_{l}}=1\); for a wrong answer, \(r_{i_{l}}=1\); for no answer, \(r_{i_{l}}=2\). According to the student answer sequence, the student vector \(q_{i}=(r_{i_{1}},r_{i_{2}},\ldots,r_{i_{l}})\), \(q_{i}\) represents the vector of student i.  
Data clustering. In this paper, the K-means clustering algorithm is used to cluster the data. The algorithm has the following features: (1) the unsupervised clustering algorithm can automatically cluster data features; (2) clustering is controllable, and the number of clusters can be controlled by the K-value; (3) it benefits from high performance, meaning that it is less time consuming than hierarchical clustering algorithms; (4) and the clustering effect is the best possible. This paper studies various clustering algorithms based on experimental data (see Table A1).The clustering results are shown in Figure 2.  
Figure 1: The KT framework based on the clustering neural network mainly consists of three parts: data encoding and data clustering (S200, S300), model training (S400), and building student portraits (S500).
## 4 Feasibility Test of the API Protocol via Simulations
### Feasibility Test of Partial Initialization
#### 4.1.2 Results
Figure 5: Similarities according to the number of transmissions for different data type, initialization rate, and the BER when the STD of the generated data with normal distribution and that with uniform distribution are respectively 10 and 11.54, and the number of slave nodes is 30. (**a**) BER = \(5\times 10^{-3}\), (**b**) BER = \(10^{-3}\), and (**c**) BER = \(10^{-2}\). Second, the similarity results are analyzed in the aspect of the BER as follows:  
* It can be intuitively predicted that the higher similarity is guaranteed as the BER is lower. This prediction is checked by varying the BER and the initialization rate, as illustrated in Figure 5a-c.
* As the BER decreases, the similarity becomes higher and more fluctuated according to the number of transmissions. * The similarity of the generated data with normal distribution is lower than that with uniform distribution as the BER increases. * However, the similarity is over 90% after a certain number of transmissions even when the BER is \(10^{-2}\). * As a result, even if a transmission failure occurs due to a slightly poor channel condition, it can be seen that the data statistics of the API and the FI have similarity. Third, the similarity results are investigated in the view of the number of slave nodes as follows:
* As the number of slave nodes increases, the amount of data to be applied to the data statistics also increases. It is shown that the increase of the number of slave nodes affects the similarity differently according to the type of data. Figure 6: Similarities according to the number of transmissions for different data types, initialization rates, and amounts of slave nodes when the STD of the generated data with normal distribution and that with uniform distribution are, respectively, 10 and 11.54, and the BER is \(10^{-3}\). (**a**) The number of slave nodes = 10. (**b**) The number of slave nodes = 30. (**c**) The number of slave nodes = 50. * In the generated data with normal distribution, the higher the number of slave nodes, the faster the similarity reaches 90%. In addition, as the number of slave nodes increases, the similarity also increases, as shown in Figure 6a-c.
* On the contrary, in the generated data with uniform distribution, the similarity variation with respect to the number of slave nodes is unremarkable. * As a result, the number of slave nodes can affect the similarity differently depending on the type of data distribution. In addition, if the number of slave nodes has influence on the similarity, the similarity increases as its value increases.
# Effective Blind Frequency Offset Estimation Scheme for BST-OFDM Based HDTV Broadcast Systems
## 5 Simulation Results and Discussion
Regarding the number of flops when \(N_{a}=1\), the proposed estimation scheme needs \(15N_{p}-7\) real flops, whereas the conventional estimation scheme requires \(13N_{f}\). Considering that \(N_{p}=N_{f}\), the complexity of the proposed scheme is  
Figure 2: MSE of the proposed LS estimator versus \(N_{a}\) in the ISDB-T 2k mode: (1) \(\Delta_{c}=0.01\) and \(\Delta_{s}=10\) ppm (2) \(\Delta_{c}=0.02\) and \(\Delta_{s}=20\) ppm. slightly increased by 11% and 13% in comparison with that of the conventional scheme considering 2k and 4k modes, respectively. In summary, we confirm that the information-carrying TMCC signal can be efficiently used for reliable joint LS estimation of CFO and SFO, achieving a satisfactory performance with moderate computational burden. The impact of the parameter \(N_{a}\) on the performance of the proposed joint LS estimation scheme is further investigated in Figure 6. The performance of the SFO estimator is not affected by the increase of SFO values, whereas the increased SFO leads to a severe error floor in the CFO estimation at high SNR. The reason for that primarily stems from the fact that the impact of \(I(\Delta_{s})\) becomes more dominant compared to that of SFO-induced ICI at high SNR. In order to obtain the same MSE of the CFO regardless of SNR, approximately four times as many \(N_{a}\) are needed in the 2k mode, compared to 8k mode. As expected, the effect of averaging over \(N_{a}\) is pronounced for \(N_{a}<10\), whereas the attainable performance gain becomes marginal when \(N_{a}>10\) and the price to be paid for using the averaging strategy is an increased processing delay. To account for this problem, the use of TMCC in combination with AC1, which is also present in an equal number irrespective of a segment type, can enhance the estimation accuracy because the receiver knows the locations of TMCC and AC1 subcarriers. Figure 4: MSE of the proposed LS estimator versus \(N_{a}\) in the ISDB-T 8k mode: (1) \(\Delta_{c}=0.01\) and \(\Delta_{s}=10\) ppm (2) \(\Delta_{c}=0.02\) and \(\Delta_{s}=20\) ppm. Figure 3: MSE of the proposed LS estimator versus \(N_{a}\) in the ISDB-T 4k mode: (1) \(\Delta_{c}=0.01\) and \(\Delta_{s}=10\) ppm (2) \(\Delta_{c}=0.02\) and \(\Delta_{s}=20\) ppm.
## 6 Discussion
### Governance
#### 6.3.5 Maritime Single Window  
The Maritime Single Window (MSW) is an IMO initiative to streamline ship documentation processes when coming into port, whereby all documentation will be submitted online through a single portal. Whereas safety certificates are among the bundle of documents required--including passenger lists, a pre-arrival security form listing previous ports of call, and others--there is no current requirement for a specific cybersecurity, or cyber qualification certificate as part of that bundle. As one interviewee noted, \"there is no specific form to say that the ship is cyber secure. That's not one of the existing file forms. And as mentioned, there's no plan in the short term at least to introduce such a form. But what we do have is the MSC resolution\" [73]. As noted above, if the ship does not have a valid ship safety assessment and plan, issued by their class society, which should incorporate cybersecurity, this would be grounds for detention. At the time of writing, there is an initiative to require \"systematic and mandatory attention for cybersecurity\" as part of the implementation of the MSW [78]. This could be achieved through the regular amendments to FAL (the Annex to the Convention on Facilitation of International Maritime Traffic, 1965 (FAL Convention)) by inserting into Section 1 C., Systems for the electronic exchange of information, a new paragraph, as follows:  
1.4 Cybersecurity--Contracting Governments shall safeguard the cybersecurity of entities operating and being connected to the system for the electronic exchange of Information by creating a mandatory framework. [78]  
As the MSW will require centralisation and digitalisation of documentation for ships entering and departing international ports, it would seem a pertinent requirement for national governments of port operators to incorporate cybersecurity into the designs, frameworks, portals, and online infrastructure of such processes, in much the same way as the IACS UR E26 and 27 do for shipboard devices and systems.
# PVPBC: Privacy and Verifiability Preserving E-Voting Based on Permissioned Blockchain
## 1 Introduction  
Many conventional offline services, such as voting, mail, and payments, are migrating online due to the rapid development of the Internet and information technologies [1]. E-voting is an area of research which is attracting significant attention. The uptake of e-voting has gradually spread throughout European countries -and to non-European countries- with successful outcomes. However, e-voting comes with its own security challenges which need to be overcome to safeguard the pillars of free-and-fair election processes. These challenges include ensuring: (1) strong voter authentication; (2) voter privacy; (3) end-to-end (E2E) verifiability; and, finally, (4) election transparency and integrity [2].  
To design and implement a successful e-voting system, several requirements must be met. These requirements are named and described as follows:  
1. **Eligibility:** each voter should only be allowed to vote once. Only eligible voters are allowed to vote;
2. **Fairness:** no early results can be declared during the election period which would influence others who have not voted yet;3. **Individual verifiability:** the ability to check that the vote was correctly counted should be available to individual voters;
4. **Universal verifiability:** every independent person should be able to verify the operations performed at every stage of the election as well as to check that the published results actually sum to the total number of cast votes;
5. **Vote privacy:** how a voter voted should not be disclosed to anyone;
6. **Receipt freeness:** the system should not offer any information which voters can use to prove how they voted. This information is typically expressed in the form of a receipt;
7. **Coercion resistance:** the system should not allow the voter to present evidence to a coercer of how they voted. We address the following problem. How can blockchain be used in an e-voting framework in a way in which voter usability is preserved, privacy is enforced, and, finally, verifiability is ensured? We hypothesize that a solution addressing this problem statement should consist of (1) a conceptual framework which is based on blockchain; (2) the use of novel cryptographic primitives and mechanisms as part of this framework to enable checks of individual and universal verifiability. Consequently, voters must be able to verify the availability and accuracy of their votes in the final tally and that the published results are correct (sum of all votes); and, finally, (3) safeguarding the voter's privacy during the authentication phase and post-election phase, as well as ballot privacy during the election phase. In our previous work, we put forth the VMV (Verify-My-Vote) voting system [3], which uses the Selene voting scheme as the underlying voting system to preserve verifiability. In this paper, we extend VMV by incorporating privacy and verifiability functionalities into existing e-voting platforms without affecting the voter's usability.
## 3 Results and Discussion
### Shear Strength and Fracture Morphology after Aging Process  
Figure 7a provides the corresponding illustration of shearing process and Figure 7b is the detailed plot between shear strength and aging time. Clearly, it can be observed that the shear strength of SAC0307-0.05 Pr/Cu decreases with aging time at a certain rate, while the shear strength of SAC0307/Cu decreases also with a certain rate first but at a rapid decrease with aging time. After 840 h aging, the shear strengths of SAC0307/Cu and SAC0307-0.05 Pr/Cu were declined to 9.5 MPa and 7.5 MPa, respectively. In addition, the shear strength of SAC0307-0.05 Pr/Cu solder joint was larger than that of SAC0307/Cu solder joint after each aging process. This was mainly associated with their interfacial IMC layer' growth, as explained above.  
Figure 7: (**a**) Illustration of shearing process; (**b**) Changes in shear strength at Sn-0.3 Ag-0.7 Cu solder/Cu and Sn-0.3 Ag-0.7 Cu-0.05 Pr/Cu solder aged for different hrs.  
Figure 8 provides SEM images of corresponding fracture morphology at SAC0307/Cu, SAC0307-0.05 Pr/Cu interfaces and the aged samples. Clearly, elongated dimples parallel to shear direction can be observed on the surface of fractured SAC0307/Cu shear joint, indicative of a distinct ductile fracture. For a fractograph of SAC0307-0.05 Pr/Cu shear joint, dimples with smaller size emerge, indicating better ductility. After 840 h aging treatment, the dimples of these two types of joints became larger and more superficial, indicating the decrease in ductility with aging treatment. However, the average size of dimples on surface of fractured SAC0307-0.05 Pr/Cu shear joint was still a bit larger than those on the fracture surface of SAC0307/Cu shear joint. It means the ductility of SAC0307-0.05 Pr was still better than SAC0307/Cu solder even with 840 h aging. However, it should be noted that Pr oxides emerges on the fracture surface of SAC0307-0.05 Pr/Cu shear joint after 840 h aging, possibly due to the appearance of PrSn\({}_{3}\) in the aged SAC0307-0.05 Pr solder microstructure (Figure 1d).
# TMD Damping for Structures with Uncertain Modal Parameters
## 2 Modelling
### Modal Parameter Uncertainties  
According to [21], the uncertainty range of the actual eigenfrequency of lightweight structures can be up to \(\pm 9\%\). According to [27], the difference between the actual modal mass, which is obtained from mode shape measurements with numerous accelerometers to ensure the high spatial resolution of the mode shape, and the nominal modal mass, which results from the assumption of pure harmonic mode shape, can be up to \(\pm 12\%\). To cover these uncertainty ranges, with some reserve (reserve approx. 100%), the transfer function (5) is computed for the following ranges of the actual eigenfrequency \(f_{1}\) and actual modal mass \(m_{1}\) relative to their nominal values \(f_{1,nom}\) and \(m_{1,nom}\) that are used for TMD design:  
\[\left[min(f_{1})=0.8\;f_{1,nom},max(f_{1})=\frac{1}{0.8}f_{1,nom}\right] \tag{12}\]  
\[\left[min(m_{1})=0.8\;m_{1,nom},max(m_{1})=\frac{1}{0.8}m_{1,nom}\right] \tag{13}\]  
Uncertainties in the actual inherent damping ratio \(\zeta_{1}\) of the primary structure are not considered because the transfer function (5) does not depend on \(\zeta_{1}\), as [PERSON] considered \(\zeta_{1}=0\) for low damped structures (4).
## 4 Experiments and Discussions
Figure 7: _Cont._  
Figure 8a,b show the time profiles of the input currents applied to the left and right solenoids of the segmented robot for the linear and right-turning motions, respectively. To generate the linear motion, the current signals of \(\pm 0.6\) A are applied to a pair of solenoid actuators, and then these signals actuate the pair of PM plungers at the same time. For the turning motion, reverse input signals are applied to the pair of solenoids, indicating the solid and dashed lines of the graph. Figure 8c shows the photos of the experimental results when the solenoid pair is actuated for the linear and right/left-turning motions over 0.2 s. We measure the displacement of the front segment moving on the surface with kinetic frictional coefficient \(\mu_{k}=0.2\) using an infrared sensor (2Y0A02, Sharp Corporation, Osaka, Japan). The captured images over a cycle are shown in Figure 8c. It takes 0.1 s to move one segment and 0.2 s for two segments to complete the linear motion over one cycle. For the rectilinear motion, both plungers of the solenoid pair drive the first segment in the same direction. However, unwanted backward or slip motion occurs between two segments. It is because the back segment is not weighty enough to keep stationary during expansion (\(0<t<0.1\) s) and the front segment has a backward motion during contraction (\(0.1<t<0.2\) s). We measure the linear displacement over 10 cycles and the averaged displacement becomes 4.9 mm. The experimental displacement over the cycle is smaller than the theoretical one which is the plunger stroke of 15 mm. For the turning motion, the solenoid pair moves in the opposite direction from each other to generate an asymmetrical force. The experimental angular displacement (1.84 degrees) is lower than the theoretical one of \(\theta_{M}=8.82\) degree from Equation (8) due to the backward or slip motion between the two segments. To evaluate the effect of friction between the surface and the segmented robot, we implement experiments for the four cases of \(\mu_{k}=0.2\), 0.35, 0.5, and a fixed condition holding the back segment stationary. We measure the linear and turning motions over 10 cycles for the four cases and the results are summarized in Table 2. The discrepancy between the theory and experiments decreases with the increasing friction coefficient. The preliminary experiments using two segments can be extended to multi-segmented robots by attaching additional segments with a pair of solenoids. Figure 7: The resultant magnetic forces as a function of the plunger position z\({}_{p}\) from the solenoid center for various coil turns: **(a)** 1100 turns; **(b)** 1200 turns; **(c)** 1300 turns; **(d)** 1400 turns; **(e)** 1500 turns; **(f)** 1600 turns.
## 2 Materials and Methods
* Antegional notch depth from the perpendicular line from the deepest point of the mandibular inferior border notch concavity to the mandibular plane. * Third molar width from the mesial aspect to distal aspect of third molar. The 4 angular measurements are represented in Figure 2 and listed in Table 1 with their corresponding numbers:  
1. Angle condyle--coronoid process: the intersection between the highest point of the mandibular condyle's head to the highest point of the mandibular coronoid process. 2. Gonial angle: the intersection between the line that connects the point where the external contour of the cranial base intersects with the dorsal contour of the condylar head to the point of maximal convexity on the posterior border of the angular process of the mandible and the mandibular plane. 3. Inclination of lower posterior teeth: the intersection between the mandibular plane and the long axis of the first molar. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multicolumn{2}{c}{**Control Group (A)**} & \multicolumn{2}{c}{**Experimental**} & \multirow{2}{*}{_p Value_*} \\ \cline{2-2} \cline{4-6}  & **Mean** & **SD** & **Mean** & **SD** & \\ \hline
1. Condyle length (cm) & 1.77 & 0.41 & 1.84 & 0.45 & 0.463 \\ \hline
2. Coronoid length (cm) & 1.37 & 0.46 & 1.53 & 0.36 & 0.080 \\ \hline
3. Ramus height (cm) & 6.37 & 0.57 & 6.18 & 0.68 & 0.199 \\ \hline
4. Total ramus height (cm) & 7.40 & 0.73 & 7.30 & 0.80 & 0.540 \\ \hline
5. Ramal width (cm) & 3.62 & 0.52 & 3.66 & 0.39 & 0.676 \\ \hline
6. Mandibular body length (cm) & 10.97 & 1.24 & 10.90 & 1.11 & 0.787 \\ \hline
7. Sigmoid notch depth (cm) & 1.43 & 0.33 & 1.59 & 0.31 & **0.030** \\ \hline
8. Posterior ramus notch depth (cm) & 0.25 & 0.14 & 0.30 & 0.14 & 0.088 \\ \hline
9. Anterior ramus notch depth (cm) & 0.27 & 0.22 & 0.24 & 0.19 & 0.490 \\ \hline
10. Antegional notch depth (cm) & 0.23 & 0.24 & 0.20 & 0.15 & 0.515 \\ \hline
11. Third molar width (cm) & 1.38 & 0.27 & 1.41 & 0.14 & 0.424 \\ \hline Retromolar space (cm) & 1.52 & 0.63 & 1.14 & 0.60 & **0.007** \\ \hline
1. Angle condyle—coronoid process (deg) & 30.13 & 5.35 & 29.53 & 4.81 & 0.599 \\ \hline
2. Gonial angle (deg) & 124.84 & 6.78 & 122.63 & 68.33 & 0.195 \\ \hline
3.Inclination of lower posterior teeth (deg) & 95.53 & 5.93 & 92.65 & 6.23 & 0.521 \\ \hline
4. Angle of impaction (deg) & 88.61 & 16.72 & 68.53 & 34.06 & **0.002** \\ \hline Retromolar space/3M width (ratio) & 1.09 & 0.40 & 0.81 & 0.44 & **0.004** \\ \hline \hline \end{tabular}  
* using Student’s \(t\)-test.  
\end{table} 
Table 1: Reference points: 13 variables (8 linear, 4 angular and 1 ratio) determined and measured. 4 Angle of impaction: the intersection between the mandibular plane and the long axis of the third molar.
# Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data
## 1 Introduction
### Factors That Raise Marine Traffic Engineering Awareness  
The current work focuses on Aegean, an archipelago of the Mediterranean Sea which connects three continents, such as Europe, Asia and Africa. Aegean Sea is an area in which shipping traffic has increased dramatically. This increasingly heavy traffic brings a great risk of maritime disaster, which could have long lasting environmental and socio-economic impact. The Aegean archipelago has the highest accident rate in the Mediterranean.  
The development of shipping, the international trade and tourism relations but most importantly the geographical location of the Aegean contributes to increased shipping traffic in the area. Every day, hundreds of ships are cruising the waters of the Aegean to transport people, goods, materials and fuel to and from various regions of Greece, Cyprus, Egypt, Turkey and the Middle East. The following factors need to be identified to provide a qualitative insight on marine engineering awareness.