esa-sceva/satcom-chunk-collection huggingface dataset:
# Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem
## 4 Security Model
### Leakage Functions  
Since perfect privacy is impossible in practical settings (e.g., some access pattern or control-flow information may leak), we define leakage profiles for each party:  
* Client: Receives only the final output \((\{\mu_{j}\},\mathcal{C})\).
* Cloud Server (CS):
* Number of input records \(N\) and dimension \(d\).
* Number of clusters \(K\) and number of iterations \(T\).
* Encrypted dataset \(\{E(x_{i})\}\) and all ciphertexts exchanged during computation (e.g., encrypted distances, encrypted cluster centers, encrypted assignments).
* Protocol structure (e.g., number and types of homomorphic operations).
* Computation Service Provider (CSP):
* Number of clusters \(K\), dimension \(d\), and iteration count \(T\).
* Ciphertexts for comparisons (e.g., distance minimum selection) and ciphertexts related to assignment operations.
* Receives only encrypted or masked intermediate results, not raw values or secret key material.  
We denote the leakage to CS as \(\mathsf{L}_{\text{CS}}\) and to CSP as \(\mathsf{L}_{\text{CSP}}\).
## 3 Construction of OD Passenger Flow Prediction Deep Learning Model
### Attention Mechanism  
This study draws on the principle of attention mechanisms in the existing literature, and through the innovative adjustment of the overall architecture, the mechanism can be specialized for OD (starting and ending points) passenger flow prediction tasks. By assigning different weights to each influencing factor, we effectively improved the accuracy of the interval flow prediction, thus enhancing the accuracy and robustness of the prediction model. The specific form is shown in Figure 8. Assuming that the constituent elements in a data source (source) is composed of a series of \(<\)key, value\(>\) data pairs, given the query of a certain element in the target, the similarity or correlation between the query and each key is calculated to obtain the weight coefficient of the value corresponding to each key. Then, the value is weighted and summed to obtain the final attention value. Essentially, the attention mechanism is to weighted sum the values of elements in the data source (source), and query and key are used to calculate the weight coefficients of the corresponding values. By utilizing attention mechanisms, the model can better focus on the information of customer traffic and assign sufficient weight to key information. The passenger flow during peak hours is processed through the attention mechanism, and the processing process is as follows:  
\[Attention\ (Query,Source)=\sum_{i=1}^{L_{x}}Similarity(Query,Key_{i})*Value_{i} \tag{11}\]  
where \(L_{x}\) is the length of the data series.  
The calculation process of the attention mechanism can be roughly divided into three stages, as shown in Figure 9.  
Step 1: According to the similarity or correlation between query and key calculations, the method used is a vector dot product calculation:  
\[Similarity\ (Query,Key_{i})=Query\cdot Key_{i} \tag{12}\]  
Step 2: The original score of the first stage is normalized. The original calculation branch is sorted into a probability distribution with the sum of all element weights of 1, and the weight of important elements is highlighted more through the internal mechanism of Softmax. It is calculated as follows:  
\[a_{i}=Soft\max(Sim_{i})=\frac{e^{Sim_{i}}}{\sum_{j=1}^{L_{x}}e^{Sim_{i}}} \tag{13}\]  
Figure 8: The essence of the attention mechanism.  
Step 3: The weighted sum of the value term with the absolute weight coefficient is calculated as follows:  
\[\textit{Attention}\left(\textit{Query},\textit{S}\textit{oure}\right)=\sum _{i=1}^{L_{x}}a_{i}\textit{:Value}_{i} \tag{14}\]
# Investigation of High-Q Lithium Niobate-Based Double Ring Resonator Used in RF Signal Modulation
## 4 Conclusions  
In summary, through the comparison and analysis of the double ring resonator and the single ring resonator, we demonstrate that the Q-factor of the double ring resonator under modulated 35 GHz RF signals is 7.05 \(\times\) 10\({}^{8}\) in an ideal situation. It is improved by two orders of magnitude and can effectively improve the modulation performance of the conventional single ring resonator. In the future, the processing of the chip will be completed based on the parametric analysis of the microring structure presented in this paper in order to verify the performance of the double ring structure under 35 GHz modulation. Meanwhile, the proposed double ring resonator has certain scalability and its potential applications in microwave photonics, biosensing, and communication fields.  
[PERSON], [PERSON] and [PERSON] proposed the conceptualization and methodology; [PERSON] analyzed the data, reviewed and modified the manuscript; [PERSON] and [PERSON] carried out the simulations, and wrote the original draft preparation; [PERSON], [PERSON], [PERSON] and [PERSON] edited and revised the article; [PERSON], [PERSON] and [PERSON] contributed investigation; [PERSON] and [PERSON] contributed data analysis and modification of the paper. All authors have read and agreed to the published version of the manuscript.  
This work was supported by \"Dalian Life and Health Planning Project\"(2022 ZXYG22) and \"Fundamental Research Funds for the Central Universities\"(2022 ZXYG22).  
The study was not applicable involving humans or animals.  
Data Availability StatementData available in a publicly accessible repository.  
Figure 12: (**a**) The transmission characteristic curves of the double ring resonator at different wavelengths and applied RF signals and (**b**) the wavelength drift at different applied RF signals.  
**Acknowledgments:** [PERSON], [PERSON] and [PERSON] would like to acknowledge the financial support from Dalian Life and Health Planning Project and Fundamental Research Funds for the Central Universities.
## 3 System Model and Problem Statement
### Energy Consumption Model  
Due to the fact that communication energy consumption is very small compared to the total energy consumption of UAVs, we only consider the flight energy consumption of UAVs. The battery energy \(E\) of the UAV is used for flight (flying to the next coordinate in the 3D Cartesian coordinate system) or hovering (maintaining a certain coordinate in the air without movement). The flight power of the UAV during time slot \(t\) is modeled as follows [31]:  
\[P_{f}^{t}=\frac{P_{0}v_{0}}{v_{v}[t]+P_{b}}+\varepsilon_{v}(v_{v}[t]+P_{b})+ \varepsilon_{h}v_{h}[t] \tag{4}\]  
where \(P_{0}\) represents the induction power of the UAV in hover state, \(v_{0}\) represents the average speed of the UAV rotor, and  
We ignore the impact of clouds on solar energy collection and model the power of a UAV collecting solar energy at height \(z[t]\) during time slot \(t\) as [10]:  
\[P_{solar}(z[t])=\eta_{s}SG_{s}\left(\alpha_{s}-\beta_{s}e^{-\frac{z[t]}{2s}}\right) \tag{7}\]  
where \(\eta_{s}\) is the energy conversion efficiency, \(S\) is the area of the solar panel, \(G_{s}\) is the average solar radiation, \(\alpha_{s}\) is the maximum atmospheric transmittance, \(\beta_{s}\) is the atmospheric extinction coefficient, and \(\delta_{s}\) is the average atmospheric height. As can be seen from the above equation, UAVs can collect more solar energy at a higher altitude within a time slot unit. Therefore, the solar energy collected in time slot \(t\) can be expressed as:  
\[E_{solar}^{t}=P_{solar}(z[t])\Delta\tau \tag{8}\]  
From this, it can be concluded that the solar energy collected by the UAV during the entire flight cycle is:  
\[E_{solar}^{D}=\sum_{t=1}^{M}E_{solar}^{t} \tag{9}\]
# Dimensional Stability of SBR-Modified Cementitious Mixtures for Use in 3D Additive Construction
## 2 Research Objectives  
Dimensional stability is defined as \"the degree to which a material maintains its original dimensions when subjected to changes in temperature and internal relative humidity\" [12]. When freshly hardened concrete is exposed to ambient temperature and humidity, it generally undergoes thermal and drying shrinkage. The stresses produced by such changes in environmental factors can be determined when the modulus of elasticity, relaxation characteristics, and degree of restraint of the material is known. The occurrence of cracks can be determined when the magnitude of this stress is understood. Theoretically, cracks occur when the stress due to temperature changes (\(\sigma_{t}=E\times\alpha\times\Delta T\), where \(\sigma_{t}\): tensile stress, \(\alpha\): the coefficient of thermal expansion, \(E\): elastic modulus, and \(\Delta T\): temperature change) or relative humidity changes (\(\sigma_{t}=E\times\varepsilon\), where \(\varepsilon\): drying shrinkage strain and \(E\): elastic modulus) exceed the tensile strength of the cementitious mixture, assuming that the material is completely elastic. Factors important when analyzing deformation characteristics include the elastic modulus and drying and thermal shrinkage.  
Since 3 DAC is a stacking or layering construction method that differs from the more historically common formwork-based construction process, specific material properties are required to be employed in 3 DAC. In particular, the properties of fresh printing materials are completely different; they can only be utilized for 3 DAC when the four conditions of flowability, extrudability, buildability, and open time are met. Thus, the optimal flow of SBR-modified cementitious mixtures (\(70\%\pm 1\%\)) to apply 3 DAC was determined by [PERSON] et. al. [13]. However, we still do not know yet whether the mixtures that can be utilized for 3 DAC are stable enough to maintain their original dimensions after the mixtures have been printed (i.e., it is exposed to ambient temperature and humidity). Hence, the novelty of this research is to determine whether the original dimensions of the SBR-modified cementitious mixtures printed through the 3 DAC process are maintained when the temperature and humidity are changed. Therefore, the objective of this study was to experimentally investigate the elastic modulus, drying shrinkage strain, and coefficient of thermal expansion. These are important factors in determining the dimensional stability of SBR-modified cementitious mixtures, a component produced by applying the mixing ratio identified after consideration of the above four requirements.
## 4 Performance Evaluation  
### Flight Test Preparation  
TRN simulation is a good method to verify that the proposed formula actually calculates the position of the closest point accurately. However, the proposed formula is effective in dynamic environments with wind influences. Therefore, we carried out an actual flight test to obtain the real data needed for TRN simulation.  
The configuration for the flight test was as follows. The IRA used for the flight test was developed by the Agency for Defense Development and Hanwha Systems as described in Section 1 and Reference [13]. The aircraft used in the test was a King Air 60 model, on which the test fixture was mounted. A total of three IRA antennas were installed at the bottom of the mounting plate. The Inertial Navigation System (INS) was installed on the opposite side of the mounting plate where the IRA antenna is installed (Figure 13a). Since the machining error of the test fixture is negligibly small, it was assumed that the INS and IRA antennas were aligned without mounting error. The navigation system consists of a navigation grade INS and Global Positioning System (GPS). INS was designed to compensate for position, velocity, and attitude errors by using GPS to perform \"In Flight Alignment (IFA)\" during navigation. The altitude of the INS was corrected based on the GPS altitude (Mean Sea Level). When performing a real TRN, the altitude of the INS was corrected based on the barometric altimeter. The altitude error of barometric altimeter varies depending on the altitude or temperature of flight area, and is generally larger than the altitude error of GPS. Therefore, GPS correction was applied instead of the barometric altimeter. The Carrier Differential Global Positioning System (CDGPS) solution was used to more accurately correct the position error of the aircraft after the flight test. GPS signals were distributed from GPS antennas originally mounted on the aircraft. The GPS antenna was installed 2 m above the IRA antenna at the top of the aircraft, which was compensated for in the performance evaluation. The flight trajectory was selected for mountainous areas (Figure 13b) Table 1 shows the information on the flight test trajectory.  
In conclusion, for accurate performance evaluation, errors other than IRA were rejected as much as possible.
# Influence of Crack Geometry on Dynamic Damage of Cracked Rock: Crack Number and Filling Material
## 2 SHPB Test  
### Experimental Setup  
An SHPB system was adopted to systematically investigate the dynamic behavior of cracked rock. The configuration of this apparatus is schematically shown in Figure 1. The dynamic loading system, containing a high-pressure gas source, a gas gun, a striker, an incident bar and a transmitted bar, could dynamically load the specimen. All bars were made of a superior alloy steel material with a Young's modulus of 206 GPa and a longitudinal wave velocity of 5122.698 m/s. The striker bar had a length and diameter of 600 mm and 100 mm, respectively, while the length and diameter of the incident bar were 5000 mm and 100 mm, respectively.  
During the tests, the strain pulse signal was captured using a Wheatstone bridge and a pair of strain gauges (Type: BE120-5 AA, Resistance: 120.4 \(\pm\) 0.1, Gage factor: 2.20 \(\pm\) 1%) symmetrically mounted on the incident and transmitted bar surfaces across the bar diameter. The schematic showing the position of the strain gauges is given in Figure 2. It indicates that the distance between the strain gauge and the specimen on the incident bar was equal to that on the transmitted bar, i.e., 2500 mm. Thereafter, the signal was amplified and then recorded by an amplifier and an oscilloscope. In this study, an eight-channel digital oscilloscope was applied, and the sampling rate was set at 130 kHz.  
Figure 1: Schematics of a split Hopkinson pressure bar (SHPB) apparatus.  
Generally, careful pulse shaping is crucial to dynamic tests conducted on the SHPB system for brittle materials. Applying this technique to the SHPB system can generate a ramp incident pulse rather than a trapezoidal one, facilitating the force equilibrium in a dynamic test [35; 36]. Among all the methods, the pulse shaper is a relatively simple one for pulse shaping. A pulse shaper made of AC1100 copper and 50 mm in diameter and 1.0 mm in thickness was thus employed in this study. Before a single test, a shaper was centrally attached to the impact end of the incident bar.  
For a single dynamic test, specimens were assembled between the incident bar and the transmitted bar. To minimize the interfacial friction on both ends of the specimen, Vaseline was used as a lubricant. Before the specimen was sandwiched between the incident and transmitted bar, Vaseline was applied on both ends of the specimen. When the specimens were assembled, the striker was launched by the sudden release of high-pressure gas. After the striker impacted the incident bar, an incident pulse was generated and propagated through the bar. Owing to the mismatch of wave impedance between the bar and the specimen, part of the incident pulse was reflected at the rock-steel interface. At the same time, the rest of the incident pulse was transmitted into the specimen and the transmitted bar [37]. The specimen was thus dynamically loaded.
## 4 Analysis and Results
### Discussion  
From the ICAFE case study, HMP-Coffee estimated that, between 2006 and 2019, 89.21%, 7.3%, and 3.5% of small-coffee productions in Costa Rica obtained Favorable. Average, and Unfavorable levels of profitability, respectively. This estimation matches with the information provided by the ICO that, according to the report of Profitability of coffee production in Latin American countries in 2019 [46]. It is noticeable that Costa Rica promotes economically sustainable coffee production by supporting producers, in reducing costs and increasing yields, to guarantee their level of competitiveness, particularly in low carbon markets.  
Overall, HMP-Coffee can estimate the profitability level of small coffee productions with a precision of about 82%. It is noteworthy that, unlike the related work (Section 2.2), our approach offers the following characteristics jointly: it is non-data driven, easy to interpret, and considers the three coffee's profitability factors. As opposed to HMP-Coffee, [PERSON] et al. [14] estimated the profitability with a data-driven approach; such an approach is hard to adopt in developing countries where there is low adoption of modern information management tools in small coffee farms [16]. Unlike [PERSON] et al. [11] and [PERSON] et al. [13], that estimate profitability based on climatic variables in diverse types of crops, HMP-Coffee performs estimations considering the particularities of coffee crop profit defined by ICO. [PERSON] et al. [12] implemented the artificial intelligence approaches applying the K-Nearest Neighbors algorithms for six crops Aus rice, Aman rice, Boro rice, Potato, Jute, and wheat; however, the output models are black box. In contrast, HMP-Coffee  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Class** & **1: Favorable** & **2: Average** & **3: Unfavorable** & **Overall** \\ \hline
**Precision** & 0.990 & 0.460 & 0.990 & 0.813 \\
**Recall** & 0.914 & 0.989 & 0.866 & 0.923 \\
**F1-score** & 0.955 & 0.621 & 0.928 & 0.834 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Results of statistical criteria (precision, recall, F1-score) to evaluate the HMP-Coffee proposed to estimate three profitability levels/classes: Favorable, Average and Low. The Overall contains the average by statistical criteria.  
maintains its hierarchical nature to ensure interpretability. The interpretability is pivotal to support decision-making in developing countries, where around 70% farmers have a low educational level [47].  
As we conceived HMP-Coffee with the classical set theory [48], where there are no intermediate situations (an element belongs or does not belong to a set), its main shortcoming is to handle values close to levels' limits. Indeed, [PERSON] et al. [49] state that the overall precision in set, theory-based models, such as HMP-Coffee, can be affected when there are many border values. According to [PERSON] et al. [50], techniques such as Fuzzy theory that can operate with intermediate values are proper to overcome this shortcoming, seeking to achieve a more flexible and precise model.
# Joint Task Offloading and Power Allocation for Satellite Edge Computing Networks
## 3 System Model and Problem Formulation  
### System Model  
The LEO satellite edge computing system is shown in Figure 1. We denote the satellite set as \(\mathcal{M}=\{0,1,2,\ldots,M\}\), which contains \(M+1\) LEO satellites equipped with MEC servers. In this scenario, there is one master satellite (MS) that generates the computation task, and the remaining LEO satellites in the communication range are slave satellites (SSs), which receive and assist in processing the computation task data. When the MS generates a time-sensitive task and there are not enough computing resources in the MS, part of the data generated by the task can be offloaded to the SSs in a cooperative approach. We assume that the time period \(T\) is divided into \(N\) slots, which are denoted by \(i\in\mathcal{T}=\{1,2,\ldots,N\}\). In this time slot, \(i\), the physical network topology of the satellite system is assumed to be fixed and the set of SSs is represented by \(k\in\mathcal{K}=\{1,2,\ldots,M\}\). All parameters used in this study are summarized and shown in Table 1.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Abbreviations** & **Description** \\ \hline N & Number of slots \\ M & Number of slave satellites \\ \(\mathcal{E}_{1}\) & Energy upper limit to execute the whole task \\ \(\mathcal{E}_{2}\) & Energy upper limit of a satellite \\ D & Data needs to be processed \\ \(C_{0}\) & The main frequency of the CPU \\ \(R_{k,i}\) & The normalized transmission data rate \\ \(\sigma^{2}\) & The receiver noise power \\ B & Communication bandwidth \\ \hline \hline \end{tabular}
\end{table}
Table 1: Abbreviations.
## 3 Results and Discussion  
### I-Corps Program  
Upper limb prosthesis are classified as follows: passive hook, passive hand, body-powered hook, body-powered hand, electric hook, electric gripper, and electric hand, among others [1]. In order to design the appropriate prosthesis for the majority of users, this work began by selecting the type of prosthesis through the I-Corps program. This program consisted of open interviews in person and by telephone with 106 people from Mexico, Colombia, and Guatem. Ten medical facilities were visited in the cities of Morelia, Monterrey, Guadalajara, Mexico City, and Puebla. In addition, three volunteers with direct experience concerning the challenges facing users on a day-to-day basis participated in the study and provided useful information. Some of the most significant comments from the interviews are presented in Table 1.  
The results showed that, in Mexico, the use of electric prostheses is almost non-existent due to certain factors, such as the weather. The high temperatures and high humidity levels caused by the country's geographic location make it difficult for the user to wear a closed silicone socket. Furthermore, the connection between the socket and the myoelectric sensors is inadequate due to sweating. In Mexico, there is also no standardization of medical services. Most of the country has neither specialists nor the sufficient infrastructure necessary to place and maintain an electrical prosthesis. Moreover, the public health system in Mexico cannot afford this type of prosthesis. Thus, electric prostheses do not comply with any of the \"A's\" (availability, accessibility, appropriateness, and affordability) in Mexico. Similarly, passive prostheses were not a good alternative either because the largest group of amputees in Mexico are male workers who require a highly functional prosthesis.  
Regarding body-powered hand prostheses, the glove must be frequently replaced, and they have a limited functionality, even though they have a hand-shaped design. In contrast, body-powered hook prostheses are lighter, more functional, more robust, and more comfortable. Several users commented that they prefer body-powered hooks over body-powered hands. In addition, the National Rehabilitation Institute (INR, for its acronym in Spanish), which is the largest and most important rehabilitation center in Mexico, provides mainly body-powered hook prostheses.  
As a result of the I-Corps program, a body-powered hook was selected as the appropriate prosthesis. Some of its advantages are as follows: lower weight, higher functionality, lower cost, low maintenance, and user feedback, Moreover, a body-powered hook does not require highly equipped prosthetics workshops, nor does it require highly qualified personnel for its installation. Finally, the skin inside the stump socket can be covered with cotton, allowing perspiration. Furthermore, commercial prostheses of this type in Mexico comply with the \"4 A's\".