esa-sceva/satcom-chunk-collection huggingface dataset:
# Efficient SMC Protocol Based on Multi-Bit Fully Homomorphic Encryption
## 6 Conclusions  
Based on the efficient FHE scheme, a leveled, multi-bit, multi-key, secure multi-party computation protocol under the CRS model is constructed in this paper. This protocol has a total of three rounds of communication, which is proven to be safe in a semi-honest and semi-malicious environment, and the security is based on DLWE and the some-are-errorless LWE. Moreover, compared with the existing protocol, the ciphertext expansion rate of this protocol is small, and the multi-bit encryption greatly reduces the number of homomorphic calculations. Meanwhile, the complexity of the NAND gate is low, and the ciphertext size is small. The overall performance is optimal among the existing FHE-based secure multi-party computation protocols. Therefore, for the next study steps, attention will be paid to how to conduct the appropriate methods to ensure the safe transmission of data and meet the coordination requirements of the session when implementing the protocol. Meanwhile, the protocol will be further improved to achieve practical standards.  
Both authors took part in the discussion of the work described in this paper. [PERSON] wrote the paper; [PERSON] revised and finalized the paper. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation Project under Grant No. 62062009 and the Guangxi Innovation-Driven Development Project under Grant Nos. AA17204058-17 and AA18118047-7.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Protocol** & **Basic** & **Rd** & **CTE Ratio** & **Depth** & **Ciphertext Size** \\ \hline [PERSON] et al. [11] & GSW13 & 2 & \(O(1)\) & \(\widetilde{O}(BN(nd)^{\omega})\) & \((n+1)^{2}\lceil\log q\rceil^{2}\) \\ \hline [PERSON] et al. [12] & GSW13 & 3 & \(O(1)\) & \(\widetilde{O}(B(nd)^{\omega})\) & \((n+1)^{2}\lceil\log q\rceil^{2}\) \\ \hline [PERSON] et al. [16] & GSW13 & 3 & \(O(1)\) & \(\widetilde{O}((nd)^{\omega})\) & \((n+B)^{2}\lceil\log q\rceil^{2}\) \\ \hline [PERSON] & GSW13 & 3 & \(O(1)\) & \(\widetilde{O}((nd)^{\omega})\) & \(\frac{(n+B)^{2}\lceil\log q\rceil^{2}}{\lceil\log p\rceil}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Performance comparison of SMC protocol based on FHE.  
**Data Availability Statement**: No data were used to support this study.  
The authors would also like to thank the anonymous referees for their constructive comments and suggestions.  
The authors declare no conflict of interest.
## 3 Results
### Eye Movement  
Table 3 presents the ANOVA results for fixation rate. No interaction effect (\(p>0.05\)) between air route alternation and display design was found in terms of AoI 1 (Overall), AoI 2 (Speed) and AoI 3 (Altitude). For the fixation rate in AoI 1, 2 and 3, the main effect of air route was significant (AoI 1 (Overall): F (1, 13) = 108.727, \(p<0.001\); AoI 2 (Speed): F (1,13) = 97.807, \(p<0.001\); AoI 3 (Altitude): F (1, 13) = 122.709, \(p<0.001\)), and the fixation rate of the three AoIs in the air-route-altered condition was 83.33%, 85.63% and 82.74% higher than those in air-route-as-planned condition, respectively. Furthermore, the main effect of display design on fixation rate in AoI 3 (Altitude) was also significant (F (2, 26) = 5.036, \(p=0.014\)), showing that the fixation rate for altitude area in Interface 2 is clearly decreased compared to Interface 3 (\(p=0.009\)).  
For the fixation rate in AoI 4 (Course), a significant interaction effect between air route and display design was observed (F (2, 22) = 4.324, \(p=0.026\)). In Interface 1, 2 and 3, fixation rate in the air-route-altered condition, respectively, increased by 50.34% (F (1, 14) = 8.424, \(p=0.012\)), 100.78% (F (1, 16) = 74.807, \(p<0.001\)) and 48.41% (F (1, 17) = 14.646, \(p=0.001\)), compared with those in the air-route-as-planned condition. Meanwhile, a significant difference in display design was found in the air-route-altered condition, showing that the fixation rate in Interface 2 is increased compared to Interface 1 (\(p=0.029\)).  
There were significant main effects of air route alternation (F (1, 19) = 27.661, \(p<0.001\)) and display design (F (2, 38) = 14.005, \(p<0.001\)) on the average pupil diameter (Table 3). Specifically, we found that the participants' average pupil diameter dilated in the air-route-altered condition compared to that in the air-route-as-planned condition. The average pupil diameters in Interface 2 (\(p=0.001\)) and Interface 1 (\(p=0.003\)) were also dilated compared to Interface 3.
# Stabilization Methodology in Foundation Soils by ERT-3D Application in Estepona, South Spain
## 3 Case Study  
This research shows the results of applying the proposed methodology to a specific case of differential settlements in a building in anat-risk area after soil removal [5]--see Figure 1. The land movements occurred after heavy rains [64] in the 2009-2010 hydrological years, but measurements presented in this paper were taken in 2012.  
The applied methodology is based on ERT-3D and consists of placing electrodes along profiles separated from each other according to the resolution, depth, and objectives to be covered. The lower the separation, the greater the resolution; the greater the separation, the greater the depth. An optimal distance of 0.80 m. has been determined in our methodology between electrodes to obtain a balance between resolution tomographic profiles and depth in accordance with the problem in question.  
Prior to performing the tomographic profiles, it is recommended that preliminary geological research be carried out in the area where the buildings are located [64]. In this case, the affected buildings were located at Paraje del Arroyo, La Cala, Estepona, Malaga (Spain), which is in the south of the Baetic Mountain Range (South Iberian Peninsula). The damage occurred at coordinates 36.461094, \(-5.160498\) (Figure 1). In the first phase, it is proposed that a granulometric analysis and a Standard Penetration Test (SPT) be executed in the geotechnical surveys. In the present case, soil consistency increased with depth (Table 1). Change in the geotechnical response of the soil occurred at an approximate depth between one and four meters, according to the SPT hits along the analyzed sample (Table 1).  
Note that the numbers in bold correspond to values that are too low. The grey background switching to white marks a discontinuity and an important change of capacity and bearing resistance in the subsoil, coincident with level I of Table 2.  
Based on geological and geotechnical studies, the materials extracted in the area depict the lithological levels listed in Table 2. The analyzed soils were mainly rocky and clayey, of varying thickness, which could be verified in field work and through laboratory geotechnical tests.
# A Short Review of Through-Silicon via (TSV) Interconnects: Metrology and Analysis
## 5 Conclusions  
3D integration with through-silicon vias (TSVs) is a promising candidate to perform system-level integration with smaller package size, higher interconnection density, and better performance. TSV fabrication is the key technology to permit communications between various strata of the 3D integration system. This review delves into the various methods employed for measuring the geometry and electrical properties of TSVs, as well as the potential reliability issues associated with TSVs in 3D integrated circuits. Currently, measurements of TSVs primarily focus on the geometry of the TSV, including any filling defects and the integrity of the insulating dielectric liner. However, the risks associated with TSV reliability in service are primarily due to copper contamination, thermal fields, stress fields, and noise coupling between TSVs. In particular, the coupling between several physical fields poses a significant challenge to the design of 3D-ICs with TSVs. As a result, there is a pressing need for comprehensive design tools and methods in this area. To address these issues, numerical simulations based on finite element methods, as well as artificial intelligence and machine learning, have been applied to this field. However, there is still much work to accomplish to fully understand the potential risks of TSVs in 3D integrated circuits and to optimize their performance. Furthermore, the increased integration of 3D-ICs also presents a significant challenge to the manufacturing process of TSVs.  
Conceptualization, J.W.; investigation, F.D. and Z.L.; data curation, S.C.; writing--original draft preparation, J.W.; writing--review and editing, F.D. and H.C.; visualization, J.W.; supervision, J.L.; project administration, H.C. and X.Y. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the Key-Area Research and Development Program of Guangdong Province under Grant 2022B0701180002 and supported by supported by the CEPREI Innovation and Development Fund No. 22Z04.  
We confirm that the manuscript has been read and approved by all named authors.  
The authors agree to publication in The International Journal of Advanced Manufacturing Technology.  
The data sets supporting the results of this article are included within the article and its additional files.  
The authors declare that they have no conflict of interest.
## 1 Introduction
### Background
The agency fosters research in space science, communications, navigation and space physics, and it advances scientific, engineering and technological competencies and capabilities through human capital development, outreach activities and infrastructure development, and fosters international co-operation (including with other African organizations) in space-related activities. The Earth Observation Program of SANSA aims to coordinate South Africa's Earth observation activities. The main objectives are to collect, archive, assimilate and disseminate earth observation data over the Southern African region to support policy, decision-making and sustainable economic growth in the country and the region. Its impact is in providing, among other things, essential EO data and services, including value-added products and services to state-owned departments, the private sector and other Small and Medium Enterprises (SME), and supporting EO research and application development, as well as human capital development and outreach activities. Thus, through the provision of EO data, products and services, SANSA is supporting several legislative acts and regulations, e.g., the Conservation of Agricultural Resources Act No. 43 of 1983, Water Services Act No. 108 of 1997, National Water Act No. 36 of 1998, National Environmental Management (NEM): Biodiversity Act No. 10 of 2004, NEM: Protected Areas Act No. 57 of 2003, Spatial Planning and Land Use Management Act No.16 of 2013, Disaster Management Act No. 57 of 2002, and South Africa's Vision 2030 (also known as the National Development Plan 2030), among others. Among SANSA's five strategic goals, human capital development has been highlighted as cross-cutting and integral to the success of the South African Space Program. To achieve this objective, SANSA uses several collaborative capacity building approaches to advance skills development on the African continent. Its multi-pronged approach includes funding of post-graduate students, short training courses, supervision of postgraduate students, guest lecturing at universities, internships and studentship programs.
## 3 Benchmark Problems
### Water Tank Control Problem  
The first benchmark control problem is the water level control in a tank [39; 40] and is illustrated in Figure 2.  
The mathematical model of this controller is expressed in Equation (3):  
\[h(t)=h\;(0)+\;\int_{0}^{t}\frac{1}{A}\big{(}q_{in}\big{(}t^{\prime}\big{)}-\;q _{out}\big{(}t^{\prime}\big{)}\big{)}\;dt^{\prime}=\;\int_{0}^{t}\frac{1}{A} \bigg{(}q_{in}\big{(}t^{\prime}\big{)}-\;a\sqrt{2 gh\;(t^{\prime})}\bigg{)}dt^{\prime} \tag{3}\]  
The fuzzy system for this problem is of Mamdani type, used the max aggregation and the centroid defuzzification, which is composed of two inputs which have three triangular membership functions and a one output which has five triangular membership functions, as represented in Figure 3, the fuzzy rules that are used are shown in Figure 4.  
Figure 3: Water tank system.  
Figure 2: Water tank system.  
The fuzzy rules that are outlined in Figure 4 were obtained based on analyzing the filling of a water tank [5]. Basically the knowledge needed to control the valve in filling the tank is used for designing the rules.
# An Improved Single-Epoch Attitude Determination Method for Low-Cost Single-Frequency GNSS Receivers
## 4 Experiments and Results
### Static Experiment
In fact, for all the unfixed epochs of the MCLAMBDA method, it ends up with 200,000 times searching for ambiguities, the total time of this method is very long. For the CLAMBDA-search method, the searching time of \(\eta=5^{\circ}\) is about one-half of \(\eta=2.5^{\circ}\). With the ascending baseline length, the searching time also increases. In fact, the actual data are often disturbed by the changing multipath as the baseline length increases. Thus, the success rates may decrease [33]. Another possible reason is that the increasing baseline length enlarges the ambiguity candidate regions, which makes the searching more time consuming. As the step size decreases, the Euler angle success rate continues to increase, as shown in Table 7. Equation (25) shows that the correct attitude angle will bring a more accurate ambiguity model, which is consistent with the experimental results. However, because the direct method is used for the attitude calculation, various step sizes do not affect the error characteristics. This can be attributed to the fact that the method performance is related to the baseline length. The average computing time is just 330 ms when \(\eta=1.25^{\circ}\), the same order of magnitude as the MCLAMBDA method, with better results at the same time. That means our method takes moderate computing burden and yields high efficiency. Meanwhile, we can customize the step \(\eta\) to meet the need of the specific environment.
## 2 Narrow Tearing Modes
### Island Width Estimate  
Local measurements using the DBS diagnostic allowed for the tearing mode localization to be estimated. For this purpose, ray tracing was performed using a 3D ray tracing code written in the Wentzel-Kramers-Brillouin (WKB) approximation and for the Globus-M2 geometry [23]. The microwave beam trajectory was calculated and positions of the cut-offs were obtained. The results of calculations for discharge #40420 are presented in Figure 4. It depicts the poloidal cross-section of the Globus-M2 tokamak with DBS antennas (brown triangles) and magnetic probe (blue circle) schematically shown. The series of lines in Figure 4 indicate the trajectories of the probing beams which correspond to the available 20, 29, 39, 48, 60 GHz probing frequencies. The magnetic field configuration was calculated using EFIT data [24] and a series of flux surfaces were also introduced to the figure.  
The TM was observed on only the 48 GHz channel among the available 20, 29, 39, 48, 60 GHz channels. The trajectory of the probing beam with the 48 GHz frequency is shown in blue in Figure 4. The cut-off position for the 48 GHz channel corresponds to the magnetic surface with \(q=2\) which was calculated by EFIT and is introduced to Figure 4 in bright red. The toroidal number of the mode \(n=1\) was established by means of a toroidal array of magnetic probes. This leads us to the conclusion that the TM seems to have a mode structure of \(m/n=2/1\).  
Figure 3: Spectrograms of the DBS phase derivative for discharge #40420.  
Using DBS data, we may also estimate the island width for the #40420 discharge. The TM was detected on one channel, so it was dubbed the narrow tearing mode. As the TM was not found on the 39 or 60 GHz channels, the island width is limited by their cut-off positions. This is why in Figure 4 the areas in yellow indicate the area where the TM could potentially have developed, however there was no DBS data available to confirm this. Using the radii values of the cut-offs we can estimate the island width to be less than 3 cm.
## 3 Field Data Acquisition and Processing  
### Site Description and Blasting Practice  
The research work reported in this paper employed a dataset comprising 231 blastholes that generated flyrock during 79 full-scale blasts (with a total of 4110 blastholes) conducted at five distinct surface mines in India, each identified by a unique code name for the purpose of this study: Mine A, Mine B, Mine C, Mine D, and Mine E. Of these, mines A and B were situated in the Jharia Coalfields region and consist of a Barakar formation overburden rock. Mine C was located in Singrauli coalfields and encompasses a Lower Gondwana Barakar formation overburden rock. Mine D was an iron ore mine from the Chlipi formation belonging to the iron ore series of the Dharvarian system of the Pre-Cambrian or Archean age. Lastly, Mine E comprised the flaggy limestone of the Rapirup group. For examining the physicomechanical characteristics of the predominant rock formations at the selected sites, a variety of rock specimens were collected and prepared for laboratory testing. The prepared rock samples were subjected to a series of laboratory tests following the recommended methods [92] by the International Society for Rock Mechanics (ISRM). Each test involved a minimum of ten samples, and the resulting data were utilized to determine the average values. The findings of these tests are summarized in Table 2.  
In each blast conducted, blastholes were drilled following a staggered pattern and loaded with fully coupled column charges of bulk site mixed emulsion (SME) explosives. The final cup density (\(\rho_{c}\)) of the explosives ranged from 1.03 g/cm\({}^{3}\) to 1.28 g/cm\({}^{3}\), while the confined in-hole velocity of detonation (\(c_{dc}\)) ranged from 4328 m/s to 4899 m/s. For mitigating the scattering effect on nominal delay intervals, electronic initiation with digital detonators was employed in all the blasts. Comprehensive data were collected, including information on parameters such as \(B\), \(S\), \(q\), \(l_{s}\), \(d\), \(\rho_{c}\), \(\rho_{r}\), \(c_{dc}\), linear charge concentration (\(q_{lc}\)), explosive energy content (\(We\)), linear energy concentration (\(W_{lc}\)), bench height (\(H_{b}\)), flyrock launch velocity (\(\gamma\)), flyrock range (\(R_{max}\)), and \(\theta\). It is worth noting that the variables summarized herein are specifically those utilized for predictive modeling and analysis. Notably, \(q\) has commonly been employed by many researchers for predicting flyrock. However, considering the potential variations in energy content due to differences in density and manufacturing among suppliers, the energy factor (\(W\)) was utilized as a predictor variable instead of the traditional powder factor. The value for \(W\) was calculated
## 3 Results and Discussion
### Imaging Potassium Concentrations  
The good correlation between the color of the sensor film and the concentration of K\({}^{+}\) prompted us to study whether such films may be read out (\"imaged\") using a digital camera mounted on a microscope. This method has been proven to be a viable, rapid and convenient approach to quantify the changes in color or fluorescence as they occur in sensor films designed to detect and image, for example, salinity [26], oxygen and pH values _in vivo_[32] or air pressure and temperature [33]. Others have used smart phones that can serve the same purpose ([34] and the references cited therein). The pictures of our new sensor films exposed to various concentration of K\({}^{+}\) were acquired with a digital camera and a microscope and are shown in Figure 4.  
The RGB data sets of the digital pictures were then separated into the three-color channels (red, green and blue; RGB) of which any digital picture is composed. Subsequent mathematical processing allows analytical evaluation of the potassium ion content of aqueous solutions (Figure 5). The normalized values were obtained from the absolute individual RGB intensity by division through the maximum value of the average intensity of the respective channel (I\({}_{\mathrm{rel}}\) = I/I\({}_{\mathrm{max(av)}}\)). The standard deviations of the blue and the green channel obviously are too high to allow for a precise calculation of [K\({}^{+}\)], but an evaluation of the red channel reveals an almost linear decrease (by 80%) in intensity on going from 10 uM to 10 mM potassium concentrations. Although the errors seem very high in general, these standard deviations symbolize the batch variation from sensor to sensor, with these resulting from measurements with five different films prepared by the same protocol. The errors obtained from a single film used for consecutive measurements are negligibly small. Then, the blue channel can also be used for content analysis, as its intensity rises 62% when the concentration of potassium ions increases from 1 to 10 uM.  
Figure 4: Microscope images (50-fold enlargement) of the photonic crystal film immersed into water solutions of KCl in varying concentrations.
## 3 Peak-Shaving Costs and Economic Dispatch Model
### Prioritized Dispatch Model of Integrated Wind Power  
Considering the peak-shaving costs function above, the economic dispatch model with consideration of wind power integration is established to minimize the summation of the peak-shaving costs, the start/stop cost, and the penalty of curtailed wind power generation as Equation (15).  
\[\min\sum\limits_{t=1}^{T}U_{it}\sum\limits_{i=1}^{N}\left[F_{i}(P_{i,t})+U_{i,t }(1-U_{i,t-1})S_{iup}+U_{i,t-1}(1-U_{i,t})S_{idown}\right]+\theta\sum\limits_ {t=1}^{T}\left(P_{w,t}^{pr}-P_{w,t}\right) \tag{15}\]  
The full set of constraints includes the power balance constraint, the unit power constraint, minimum ON-OFF time constraint, wind power output limits, and spinning reserve requirements, detailed as follows.  
\[s.t.\left(\begin{array}{c}\sum\limits_{i=1}^{N}U_{i,t}P_{i,t}+P_{w,t}=P_{i,t }\\ P_{imin}\ \leq P_{i,t}\leq P_{\max}\\ \sum\limits_{k=\Omega_{j}}P_{k,j}\leq P_{\max,j}\\ (U_{i,t-1}-U_{i,t})\Big{(}T_{i,t-1}^{on}-T_{ion}\ \Big{)}\geq 0\\ (U_{i,t}-U_{i,t-1})\Big{(}T_{i,t-1}^{off}-T_{ioff}\Big{)}\geq 0\\ P_{i,t}-P_{i,t-1}\leq U_{i,t-1}\alpha_{iup}\ +(U_{i,t}-U_{i,t-1})\alpha_{istart}\\ P_{i,t-1}-P_{i,t}\leq U_{i,t}\alpha_{idown}\ +(U_{i,t-1}-U_{i,t})\alpha_{istart}\\ 0\leq P_{w,t}\ \leq P_{w,t}^{pr}\\ \sum\limits_{t=1}^{N}U_{i,t}\Big{(}P_{i,t}^{U}-P_{i,t}\Big{)}\geq R_{uw,t}\\ \sum\limits_{i=1}^{N}U_{i,t}\Big{(}P_{i,t}-P_{i,t}^{D}\Big{)}\geq R_{dw,t}\\ \end{array}\right. \tag{16}\]  
As the presented economic dispatch is a mixed-integer non-linear programming problem, it is solved by the self-modified branch-and-bound algorithm embedded with DICOPT solver of GAMS software [30].