esa-sceva/satcom-chunk-collection huggingface dataset:
# Efficient Multi-Identity Full Homomorphic Encryption Scheme on Lattice
## 5 Multi-Identity Based Full Homomorphic Encryption Scheme
### Efficiency Analysis of MIBFHE Scheme  
The mIBFHE scheme proposed in this paper is compared with the CM15 scheme proposed by [PERSON] et al. [12]. The comparison results are shown in Table 2.  
From the analysis in Table 2, it can be seen that compared with the CM15 scheme based on the trapdoor generation algorithm in [21], the mIBFHE scheme in this paper used the MP12 trapdoor generation algorithm and the preimage matrix for encryption. The scheme is more concise and the encryption algorithm is simpler. Therefore, the main efficiency parameters of the mIBFHE scheme in this paper are significantly optimized. The lattice security dimension \(m\) is reduced from \(6n\log q\) to \(2n\log q\), the size of the joint secret key \(\hat{\mathfrak{s}}\) is reduced from \(ND\) to \(m^{\prime}D\), and the size of extended ciphertext is reduced from \(DN\times DN\) to \(m^{\prime}D\times DN\).
###### Abstract  
Background: Anterior cruciate ligament (ACL) injuries have been studied using a variety of methods and tools. However, each is hindered by specific limitations with respect to its application. Aim: To assess the combined effects of external moments and muscle activations on ACL loading using serial, forward dynamics (FD) simulations of single leg, hyperextension landings in OpenSim. Methods: The FD tool of OpenSim was iteratively run using different combinations of knee-spanning muscle activation levels, internal rotation and valgus knee moment magnitudes. A regression was conducted on the data in order to predict ACL loading under different conditions. Results: A purely abduction moment leads to greater mean ACL loading than a purely internal rotation moment or any combination of the two. Additionally, the generalized boosted regression model using both external moments and certain knee muscles identified the internal rotation moment as the most important variable in predicting the ACL load (R\({}^{2}\) = 0.9; \(p<0.0001\)). Conclusion: This study demonstrated a novel and practical application of an OpenSim musculoskeletal model that supports the ACL injury mechanism of landing with low knee flexion angles, high muscle forces of the Quadriceps muscles and an external knee valgus moment, though further investigation is needed.  
knee joint; biomechanics; motion analysis; computer simulations; in silico; injury mechanism
# Research on the Coverage of Ultraviolet Communication Network in the Arbitrary Polygon Area
## 3 k-Connectivity
### Transceiver Elevation Angles and Node Coverage Range  
Figure 6 shows how the node coverage range changes with the transmitting elevation angle (\(\theta_{1}\)) under different receiving elevation angles (\(\theta_{2}\)). We observe that as \(\theta_{1}\) increases, the range gradually decreases. By contrast, we note that when \(\theta_{1}\) is 50\({}^{\circ}\), the coverage range is greater than that when \(\theta_{1}\) is 40\({}^{\circ}\). Since the volume of the effective scatterer (\(V\)) becomes larger as \(\theta_{1}\) increases from 40\({}^{\circ}\) to 50\({}^{\circ}\).
## 3 Research Questions and Communication Efficient Methods  
Communication between the participating devices and the central server is essential for an FL environment. The model is communicated over rounds of communication that download, upload, and train the ML model. However, as mentioned, this comes with its challenges. To gain more insight into the challenges present in an FL environment regarding communication, two research questions are proposed. The first **RQ1** aims to provide a brief analysis of _What are some of the challenges that are presented in FL with regard to communication?_ The second **RQ2** provides an in-depth analysis of various methods and approaches that can be implemented to answer _How can communication be more efficient in an FL environment?_  
To thoroughly conduct our survey based on the defined research questions, we explored various libraries, including Google Scholar, Springer Link, Science Direct, ACM Digital Library, IEEE Xplore, and ArXiv, using specific keywords such as federated learning, communication, etc. Consequently, this paper presents a comprehensive survey of the current challenges and its applicable solutions within FL environments.
# Analyzing Zone-Based Registration Using a Three Zone System: A Semi-Markov Process Approach
## 3 New Mathematical Model
### Semi-Markov Process Model for 3Z
#### 3.2.3 Paging Procedure  
In this study, it is assumed that sequential paging to the three zones was performed. When an incoming call occurred, the paging procedure was completed if there was a response from the paged zone. If there was no response, paging was performed again for the remaining zones.  
The paging order should be determined to minimize paging costs. In this study, the most recently registered zone is paged first. If there is no response, the center zone is paged next. If there is no response again, the remaining edge zone is paged. Note that if the UE is in state I\({}_{ij}\), the first paging attempt always succeeds.  
Figure 6: A call occurs in a 3Z system.
# Biosynthesis of Edible Terpenoids: Hosts and Applications
## 3 Application of Terpenoid Microbial Cell Factories in the Food Industry
### Acting as Biopreservatives
#### 3.2.2 Pinene  
Pinene is a monoterenoid derived from plants, and it is widely used as flavors, fragrances, and pharmaceuticals. Its dimerized form can serve as a high-density renewable fuel for aircraft [39]. Moreover, pinene can also be used as a raw material for the synthesis of fragrances such as terpineol and linalool.  
In the monoterpene cell factories, only one heterologous monoterpene synthase is usually needed for the production of monoterpenes. In _E. coli_, [PERSON] et al. identified an effective pinene synthase \(PtPS1^{Q45/L}\) and improved its hydrophilicity and solubility by N-terminal truncation, facilitating folding and preventing degradation. Next, they introduced a GPPS mutant \(A_{\beta}GPPS^{D90G/L175P}\) to enhance the supply of precursor GPP and optimize fermentation conditions. Ultimately, in the optimal host DH10B, a titer of 1035 mg/L pinene was produced in 1.3 L fed-batch fermentation [93]. In order to break through the limitations of mass transfer and reduce the impact of pinene on cell viability, [PERSON] et al. achieved gram-scale production of pinene using a cell-free system. They constructed a module co-catalysis cell-free system containing an MEV upstream module and a pinene downstream module and optimized the physicochemical parameters using Plackett-Burman experimental design and the steepest ascent strategy. The final pinene titer was 1256 mg/L [94]. To some extent, cell-free systems are an effective alternative to whole-cell catalysis for synthesizing terpenoids with toxicity.
## 4 Theoretical Works
\begin{array}{c}e_{\omega}^{p}\text{ \emph{\tiny$\
u$}}\text{if }(\overline{s_{2}}\
eq 0 \wedge|e_{\omega}|>\varepsilon)\text{ \emph{\tiny$\
u$}}\text{ \emph{\tiny$\sqrt{s_{2}}=0$}}\\ l_{1}e_{\omega}+l_{2}\text{sign}(e_{\omega})e_{\omega}{}^{2},\text{ if }\overline{s_{2}}\
eq 0\wedge\text{ e}_{\omega}<\varepsilon\end{array} \right. \tag{42}\]  
\[\overline{s}_{2}=\dot{e}_{\omega}+k_{1}e_{\omega}+k_{2}e_{\omega}{}^{p} \tag{43}\]  
Following, we consider the below subsystem with coordinate mapping. \[m\dot{s}_{2}=f_{2}+u_{2} \tag{44}\]  
\[f_{2}=-m\dot{v}_{r}+d_{2}(t)-\omega_{r}{}^{2}x_{e}+m\big{(}|\dot{\omega}_{r} \big{|}x_{e}+\dot{\omega}_{r}y_{e}+\big{|}\omega_{r}\big{|}(v-v_{r}+\omega_{r}y _{e})\big{)} \tag{45}\]  
\[+mk_{1}\dot{e}_{\omega}+mk_{2}\dot{e}_{\omega}\Psi_{e_{\omega}}\]  
with  
\[\Psi_{e_{\omega}}=\left\{ \begin{array}{c}pe_{\omega}^{p}\text{, \emph{\tiny$\
u$}}\text{ if }( \overline{s}_{2}\
eq 0\wedge|e_{\omega}|>\varepsilon)\text{ \emph{\tiny$\
u$}}\text{ \emph{\tiny$\sqrt{s_{2}}=0$}}\\ l_{1}+2l_{2}\text{sign}(e_{\omega})e_{\omega}\text{, \emph{\tiny$\
u$}}\text{ if } \overline{s}_{1}\
eq 0\wedge|e_{\omega}|<\varepsilon\end{array} \right. \tag{46}\]  
With the above assumptions, the nonlinear factor \(f_{2}\) in system (44) can be bounded by  
\[\big{|}f_{2}\big{|}\leq m\big{|}\dot{v}_{r}\big{|}+\big{|}d_{2}(t)\big{|}+m \big{|}\omega_{r}\big{|}\big{|}\dot{\omega}_{e}\big{|}+m\big{|}\dot{\omega}_{ r}\big{|}\big{|}\omega_{e}\big{|}+m\big{|}k_{1}+k_{2}H_{\omega_{e}}\big{|}\dot{ \omega}_{e}\big{|}\leq a_{2}+b_{2}|z_{2}| \tag{47}\]  
where \(a_{2}\) and \(b_{2}\) are positive values, \(\Big{|}z_{2}\Big{|}=\sqrt{\dot{e}_{\omega}^{2}+\dot{e}_{\omega}^{2}}\)  
Lastly, a sliding mode control law is suggested as  
\[u_{2}=-(\beta_{2}+\hat{k}_{2})s_{2} \tag{48}\]  
where \(a_{2},b_{2}\) are positively tuning gains. Consider that \(a_{2}^{2}=\phi_{2}\), \(b_{2}^{2}=\chi_{2}\). \(\overline{\phi},\widetilde{\chi}\) are the estimators of \(\phi,\chi\), respectively, thus the relationship among estimators is  
\[\hat{k}_{2}=\frac{1}{2\dot{e}_{3}^{2}}\hat{\phi}_{2}+\frac{1}{2\dot{e}_{4}^{2}} \hat{k}2z_{2}{}^{2} \tag{49}\]  
The adaptive laws are designed as follows. \[\widetilde{\dot{\phi}}_{2}=-\varepsilon_{3}\widetilde{\dot{\phi}}_{2}+\frac{1 }{2\dot{e}_{3}^{2}}s_{2}^{2} \tag{50}\]  
\[\widetilde{\dot{x}}_{2}=-\varepsilon_{4}\widetilde{\dot{x}}_{2}+\frac{z_{2}^{2} }{2\dot{e}_{4}^{2}}s_{2}^{2} \tag{51}\]\(\varepsilon_{3}\), \(\varepsilon_{4}\) are positive gains. Substituting the sliding mode control law (48) into system (44) yields  
\[\dot{m\dot{s}_{2}}=-\beta_{2}s_{2}+\widetilde{Y}_{2} \tag{52}\]  
where  
\[\widetilde{Y}_{2}=f_{2}-\hat{\kappa}_{2}s_{2}.\]  
**Theorem 2**. : _Considering the system in (57), \(s_{2}\), \(\hat{\phi}_{2}\), \(\hat{\chi}_{2}\) are uniformly and ultimately bounded with the adaptive control law (50,51,51)._  
**Proof:** Select the Lyapunov function as  
\[V_{2}=\frac{1}{2}({m{s_{2}}^{2}}+\widetilde{\phi}_{2}^{2}+\widetilde{\chi}_{2 }^{2}) \tag{53}\]  
where \(\widetilde{\phi}_{2}=\phi_{2}-\hat{\phi}_{2}\) and \(\widetilde{\chi}_{2}=\chi_{2}-\hat{\chi}_{2}\).
## 3 Methodology
### Design of the Proposed Magic System
#### 3.2.5 Main Technology for FUI Implementation  
Range Finding by Laser Scanning  
The primary technology employed in the magic show system \"FUI Magic\" to implement the FUI function is \"laser scanning for touch sensing by range finding\". Specifically,  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Software Package** & **Hardware Equipment** \\ \hline Resolume Arena _(ver 7.18.1)_ & Computer \\ \hline TouchDesigner _(ver. 2023.11510)_ & Display screen with projection film \\ \hline loopMIDI (ver. 1.0.16.27) & Hokuyo UST-10 LX rangefinder \\ \hline Adobe Illustrator (ver. Adobe 2018) & Projector \\ \hline Adobe After Effects (ver. Adobe 2018) & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Hardware and software used in the proposed magic show system for magic presentations.  
Figure 5: The architecture of the proposed magic show system “FUI Magic”.  
the touch sensing determines the magician's touch position on the display panel using the range-finding technique: if the touch point falls within the sensing area provided by the laser scanning range, it triggers the desired FUI process for the magic presentation designed in this study.  
As previously explained, the range-finding function is realized in this study using the Hokuyo UST-10 LX device (from Hokuyo Company, Japan). The device conducts horizontal laser scanning to create a fan-shaped area. Since the device is mounted on the display panel to \"face\" downward, the horizontal fan shape becomes vertical and roughly parallel to the panel surface.  
A touch from an object (such as the magician's hand or fingers in the magic performances of this study) within the fan area can be precisely located according to the range-finding principle by measuring the flight time of the laser beam between the touch point and the range finder. The Hokuyo laser scanner not only captures the detected object's position but also measures its size and movement direction, displaying the scanned image of the object on a screen. The laser scanner has a maximum detection distance of 10 m, a scanning angle of 270 degrees, and a scanning time of 25 ms. The detection function remains effective regardless of strong ambient light and can operate in low-light conditions.
# Each-Phase Metering with Gas-Liquid Stratified Flow Based on the Multi-Frequency Coriolis Principle
## 2 Theoretical Background
### Error Sources of Measuring Gas-Containing Fluid by Single-Frequency Coriolis Flowmeters  
For gas-containing fluids, the bubble effect and resonance effect are considered to be main factors for measurement errors of Coriolis flowmeters [19]. The bubble effect is due to the relative motion between the gas and liquid phase, which leads to the secondary flow around the bubbles, resulting in underestimation of the actual density and mass flow [20]. Under the action of free bubble, theoretical deviations of density and mass flow is shown in Equation (5). The bubble effect has the same negative deviations on density and mass flow measurement.  
\[E_{b}=\frac{-2\alpha}{1-\alpha} \tag{5}\]  
where \(\alpha\) is the gas volume fraction.  
The reason for the resonance effect is that the existence of a small amount of gas in the liquid leads to a sharp decrease in sound velocity, increases compressibility of two-phase fluid, reduces the resonance frequency of the mixture in the tube, and leads to overestimations of density and mass flow [3]. The acoustic resonance frequency in measuring tube can be calculated from the lowest resonance mode of tube, as follows:  
\[f_{0}=c.\frac{\lambda_{1}}{2\pi R} \tag{6}\]  
where \(\lambda_{1}\) is a constant equal to 1.842; \(R\) is the radius of the measuring tube; \(f_{0}\) is the lowest acoustic resonance frequency of fluid.  
Different from the bubble effect, the mass flow deviation caused by the resonance effect is twice the density [13]:  
\[E_{\rho}=\left(r_{0}+r_{1}.\frac{1}{1-\frac{f^{2}}{f_{0}^{2}}}\right)-1 \tag{7}\]  
where the values of \(r_{0}\) and \(r_{1}\) are constant and equal to 0.16 and 0.84, respectively, which describe the active and inactive portion of the fluid mass in the measuring tube for the resonance effect. \(f_{0}\) is the natural frequency of the first modes of measuring tube free vibration [14].  
\[E_{\dot{m}}=2\cdot\mathrm{E}_{\rho} \tag{8}\]The existence of gas leads to bubble effect and resonance effect (an increase in fluid compressibility), which increases the total errors of Coriolis flowmeters. The expression of total instrument error is shown in Equation (9).  
\[E_{c}=\varepsilon+\text{E}_{d} \tag{9}\]  
where \(\varepsilon\) is the basic error of the meter; \(E_{d}\) is the measurement deviation caused by the presence of gas in fluid, and therefore the purpose of this study is to reduce \(E_{d}\) by establishing a correction model suitable for stratified flow.
# Measurement and Modeling of 3D Solar Irradiance for Vehicle-Integrated Photovoltaic
## 4 Discussion
### Feasibility of the VIPV Based on Our Measurement and Modeling  
Compared with the past reports by Toyota Motors [2] and New Energy and Industrial Technology Development Organization (NEDO) [3] which did not consider the shading effect by surrounding objects and loss by the curved surface, our research gives a more realistic solar resource on the car roof and car side. These two reports gave an overestimation of the energy yield expectation. The rough number suggested by this research is around 3/4 using highly curved PV modules on the car roof and shading effects (taken by the capital of the local government in Japan).  
As it is measured and modeled in this study, the energy yield of VIPV is undoubtedly less than that of the PV power plant that is constructed maximizing the energy yield by a given amount of the solar panels. However, considering that the related soft-cost and other balance of system costs (construction, structure, connecting to the grid, distribution, and the cost of the constructing and operation of the EV charging station) that are to be eventually shared by car owners or car manufacturers, VIPV will be attractive option both in cost and user-friendliness.
## 3 Numerical Simulation
### Computation Domain and Boundaries  
#### 3.2.1 Geometries  
So far, dynamic and sliding mesh [30] methods are the two most frequently used techniques in tunnel aerodynamic effect related research where the relative motion between HST and internal tunnel space is solved. The present investigation was conducted relying on the sliding mesh due to its accurate resolution and relatively low cost in the computation resource compared to the dynamic mesh. The overall computation domain is divided into two individual parts, namely the static zone and moving region as shown in Figure 4.  
The static zone is 1628 m in length, 100 m wide and 50 m tall, containing both the external flow field and internal test tunnel area. As shown in Figure 4a, the static zone denotes the computation domain within and outside the tunnel except the region within the yellow dotted lines. For any situation, HST starts running through the tunnel entrance portal is named as Train A while the other one corresponds to Train B. Without doubt, the body of Train A and B, as well as their surrounding area are classified into the moving regions as exhibited in Figure 4b. The 800 m long extra moving region, is constructed outside the external flow field to ensure the moving region being located within the static zones in the whole simulation period [31]. In addition, interface is applied to achieve the exchange of solution data from static and moving zones. An overview of the computation domain constructed in simulation can be found in Figure 4c.  
The test tunnel and HSTs built-up in the computation domain is the 1:1 reproduction of those applied in the field tests. Simplification is considered to the physical model  
Figure 4: Diagram of computation domain in simulation: (**a**) Top view; (**b**) Cross-section view; (**c**) 3D view.  
construction of HST to avoid unnecessary time cost as the research interest of this paper is tunnel aerodynamic effect instead of the pressure loads at vehicle components. Thus, lightings, handles, and bogies are ignored, and carriages are merged.
## 3 Results
### Morphology and Structure of CNSs
The specific surface area and pore volume were determined using the Brunauer-Emmett-Teller (BET) method, while the pore width was obtained from Barrett, Joyner, and Halenda (BJH) calculations (Figure 3). As the carbonization temperature was increased from 500 to 1000 \({}^{\circ}\)C, the BET SSA was increased from \(\sim\)6.2 to \(\sim\)2960 m\({}^{2}\)/g (Figure 3A). This could be attributed to the formation of porous structures and a reduction in the size of the particles with the increase in temperature, which provides an enhanced surface area [40]. As discussed earlier, a hierarchical porous structure within the carbon matrix is formed due to self-activation, facilitated by the presence of alkali metals that play a primary role in obtaining carbon residues with a large surface area [39]. Similarly, the pore volume was also increased from 0.009 cm\({}^{3}\) to 2.1 cm\({}^{3}\)/g (Figure 3B). However, the pore width did not exhibit any specific order (Figure 3B). All the CNSs were found to be mesoporous (pore diameter = 2 to 50 nm). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**CNSs**} & **Carbon (C)** & **Oxygen (O)** & **Sodium (Na)** & **Magnesium (Mg)** & **Sulfur (S)** & **Potassium (K)** & **Calcium (Ca)** \\ \cline{2-7}  & & & & **Atomic Percentage (\%)** & & \\ \hline CNS500 & 74.2 & 19.4 & 0.5 & 0.8 & 0.2 & 0.9 & 4.0 \\ CNS600 & 78.9 & 17.6 & 0.7 & 0.5 & - & 0.5 & 1.8 \\ CNS700 & 87.2 & 10.9 & - & 0.2 & - & 1.0 & 0.7 \\ CNS800 & 84.6 & 8.8 & - & 0.4 & - & 2.0 & 4.2 \\ CNS900 & 89.5 & 9.9 & - & - & - & 0.6 & - \\ CNS1000 & 90.7 & 8.6 & - & - & - & 0.7 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Elemental composition (Atomic %) of ON CNSs.
## 3 Simulated Results and Discussions
### Parametric Analysis  
The performance of the FSS shield is analyzed by tuning and optimizing various geometric parameters. Figure 6a shows the impact of varying the length of the U-shaped stubs. Increasing the length shifts the resonance frequency downwards, helping to achieve a miniaturized unit cell, also resulting in a reduction in operational bandwidth. Figure 6b illustrates that fine-tuning the radius \(r_{3}\) helps to accomplish the desired FSS performance. Moreover, inter-element spacing also has a profound effect on the FSS's response. Smaller inter-element spacing results in wider bandwidth and higher angular stability, and avoids the early onset of grating lobs, depending on the physical geometry of the FSS. Figure 6c specifies that an increase in inter-element spacing reduces the SE and rejection bandwidth while shifting the resonant frequency towards higher frequencies.  
Figure 5: (**a**) SE of the FSS element rotated at \(45^{\circ}\) for TE and TM modes at \(\theta=0^{\circ}\); (**b**) SE of the FSS for TE mode, verifying its angular stability up to \(60^{\circ}\); (**c**) SE of FSS at various oblique angles for TM mode.  
Figure 6: (**a**) SE of the FSS by optimizing U-stubs length. (**b**) Impact of radius \(r_{3}\) on the SE. (**c**) SE of FSS as a function of inter-element spacing. (**d**) Permittivity effect on FSS performance. (**e**) SE analysis as a function of loss tangent. (**f**) Thickness effect on SE behavior of the FSS.  
In addition, the SE behavior of the FSS was also investigated by varying characteristics of the employed dielectric material. It can be seen in Figure 6d that the SE curves shift to higher frequencies with a decrease in permittivity of the dielectric. The results in Figure 6e reveal that the FSS achieves SE of more than 45 dB when the loss tangent of the substrate has a minimum value. The SE decreases as the loss tangent increases. Furthermore, increasing the thickness of the dielectric does not impact the SE of the FSS, but it shifts the resonant frequency to lower frequencies, as shown in Figure 6f.
## 2 Related Theory
### Traditional Tolerance Analysis  
A dimensional chain is a representation of how a functional requirement \(x\) depends on a known set of functional dimensions \(d_{i}\)[39], Letting \(x=f(d_{1},d_{2}\cdots d_{n})\) be a dimensional chain. Each functional dimension has a deviation from its nominal value: \(\Delta d_{i}=d_{i}-\bar{d}_{i}\), and a deviation will occur on the functional requirement: \(\Delta x=x-\bar{x}\). The equation can be linearized by a first-order Taylor approximation(as the deviations on the dimensions are small compared to nominal values, higher-order terms of a Taylor series can be omitted).  
\[x+\Delta x=f(d_{1},d_{2}\cdots d_{n})+\frac{\partial f}{\partial d_{1}}\Delta d _{1}+\frac{\partial f}{\partial d_{2}}\Delta d_{2}+\cdots+\frac{\partial f}{ \partial d_{n}}\Delta d_{n}. \tag{1}\]  
Then,  
\[\Delta x=\sum\limits_{i=1}^{n}\frac{\partial f}{\partial d_{i}}\Delta d_{i}. \tag{2}\]  
If \(\partial f/\partial d_{i}\) can be calculated, then \(\Delta x=\sum\limits_{i=1}^{n}\frac{\partial f}{\partial d_{i}}\Delta d_{i}\) is linear and \(s_{i}\) is referred to as sensitivity for dimension \(d_{i}\), In most cases, \(x=f(d_{1},d_{2}\cdots d_{n})\) is nonlinear and \(s_{i}\) cannot be calculated directly, even though there exists an explicit functional equation. Such is the case with tolerance analysis considering clearances in joints.