esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Evaluation
### Experimental Result
#### 5.2.1 Memory-Updated Information of Unit Test  
The experiment performs according to the process of illustrated in Figure 3. First, a unit test is performed to check whether a function is normally operated. The unit test sets inputs for initial state setting and functional testing and confirms that the function normally operates. The updated information is analyzed by the collected memory data of unit test. At the same time, the test specifications are analyzed in the test script and include the test conditions, expected values and time intervals between inputs. IDUR is identified using memory-updated information and test specifications. Refer to Figure 10a. \"Left-turn Signal\" initializes as 0 at 200 ms and inputs to a test condition value (input value) of 32 at 700 ms. If the left signal lamp changes from 0 to 1 (the expected value), it is determined to be normal. In (b) left, mCanLampModeSet is initialized as 0 from frame number #27, then the values of the other symbols are updated in order. The statusLLeftSignalLamp is initialized as 0 from frame number #31. In (b) right, mCanLampModeSet is updated from #77 as 32 to the test condition value and is sequentially updated until #81 and the statusLeftSignalLamp is output as 1, which is the same as the expected value. Because the SUT and the simulator are not synchronized, the timestamp of the test specification and the updated frame number of the MUI may be different. However, the input time difference between the test specification (500 ms) and the MUI (50 frames) is the same (one frame is 10 ms).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Operator** & **Mutation** \\ \hline \multirow{2}{*}{Statement} & SSDL & Statement Deletion \\  & STRI & Trap on if Condition \\ \hline \multirow{2}{*}{Operator} & OEAA & Operator Replacement (Plain assignment to Plain assignment) \\  & OEBA & Operator Replacement (Plain assignment to Bitwise assignment) \\  & OCNG & Logical context negation \\ \hline \multirow{2}{*}{Constant} & CCSR & Constant for Scalar Replacement \\  & CCGR & Constant for Constant Replacement \\ \hline \hline \end{tabular}
\end{table}
Table 4: List of mutation operators.  
Figure 10: Unit Test of “Left Turn Signal”: (a) “Left Turn Signal” Unit Test Specification; (b) Initialize and Test input (\(\text{MUI}_{\text{IDUA,IDUR}}\)).
# Derivation and Validation of Bandgap Equation Using Serepentine Resonator
## 4 Experimental Validation  
### Fabrication  
The unit structure is designed as a serpentine resonator to experimentally verify the bandgap generated from the numerical results as shown in Figure 8. The serpentine resonator is made of acrylic material with elastic modulus \(E\) = 3.2 GPa, mass density \(\rho\) = 1165 kg/m\({}^{3}\), and Poisson's ratio \(\
u\) = 0.4. The tip mass of the serpentine resonator is made of a nut & bolt pair, which weights 5.9 g, and it is assumed to be rigid in the desired frequency range. Table 3 shows the dimensions of the serpentine resonator used to generate the bandgap from 201-290 Hz within a cuttable width of 8 mm acrylic. Fabricated sample was manufactured by laser cutting and dimensions were changed due to manufacturing conditions. Dimensions were taken within the same design zone in Figure 5.  
Figure 9a shows the dispersion curve of the fabricated sample and unit structure analyzed by a three-dimensional (3D) FE simulation using COMSOL Multiphysics. The shaded part highlighted in black is the bandgap generated based on FEM (COMSOL Multiphysics) and the section enclosed in the box in red is the bandgap generated based on the theoretical implementation. The bandgap generated through the FEM simulation ranges from 201 to 290 Hz and that generated by the theoretical implementation is in the range of 204-294 Hz. Figure 9b shows the mode shapes of the serpentine resonator unit structure. A and B are the Bloch mode shapes at the lower and upper bounds of the bandgap, respectively; A is in-phase mode, and B is out-of-phase mode. C is the bending mode in x-axis and D is the bending mode in y-axis.  
Figure 7: (**a**) Relative error of resonance frequency and bandgap when \(N\) = 2, \(l_{p}\) = 1, (**b**) \(l_{p}\) = 1.5, (**c**) \(l_{p}\) = 2, according to the change in \(l_{o}\)/\(b\), and (**d**) unit structure.  
Figure 8: Fabricated serpentine resonator.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**1\({}_{o}\)** & **\(I_{p}\)** & **\(b\)** & **\(t\)** & **\(L_{xm}\)** & **\(L_{ym}\)** & **\(L_{xh}\)** & **\(L_{yh}\)** & **\(T\)** \\ \hline
15 mm & 3 mm & 2 mm & 8 mm & 12 mm & 12 mm & 25 mm & 25 mm & 1 mm \\ \hline \hline \end{tabular}
\end{table}
Table 3: Dimensions of the fabricated serpentine resonator.  
Figure 9: (**a**) Dispersion curve and (**b**) mode shapes of the fabricated sample.  
The serpentine resonators are all cut with the same machine and acrylic plate to reduce process errors between samples. To evaluate the deviation between the FE model and fabricated samples, the resonance frequencies of five samples were measured. The fabricated samples were vertically attached with a silicon glue on the shaker to realize the fixed boundary condition, and the resonance frequencies were measured using laser scanning vibrometer (LSV) and compared with the FE model. Table 4 shows the resonance frequencies of the five samples. As shown in the table, the average frequency of the measurement results is 189 Hz, and the average is 190 Hz with the 3D FE simulation.
## 5 Discussion
### Application of Prediction Model  
The scope of the test used in this paper covers a variety of typical working conditions of on-orbit maintenance of the Chinese space station. When predicting the vibration exposure of the PPT tool, the vibration exposure is obtained by inputting the length of the operating rod and the number of the non-detaching fastening device. When astronauts use PPT tools to carry out a specific on-orbit maintenance mission, the astronauts will select the appropriate category from the serialized operating rods and operate a certain number of non-detaching fastening devices according to the requirements of the maintenance mission. Therefore, the length of the operating rod and the number of the non-detaching fastening device can be taken as the input of the model, and the second-order polynomial model or the quadratic cumulative nonlinear model can be selected according to the above operating conditions. the possible vibration exposure of the astronaut's hand is calculated by the prediction model. According to the predicted vibration exposure, guide the maintenance mission procedures, work rhythm control, and work sequence planning of the astronauts.  
The prediction model can also quickly predict the hand-transmitted vibration exposure produced by the PPT tool when the operating rod of other length specifications is equipped. Moreover, the theoretical model prediction is used to replace the complex ground simulation test to provide a more accurate vibration exposure prediction for the application of the new operating rod.  
For the scheme iteration and optimal design of the new generation of handheld EVA power tools, the prediction model can provide a set of rapid prediction methods of hand-transmitted vibration exposure based on the comparison of existing test data. Moreover, it could provide some technical references for developing and using new tools.
# Strain Rate Effect on Artificially Cemented Clay with Fully Developed and Developing Structure
## 5 Conclusions  
This paper focused on the mechanism of rate effect on clayey soil with different structural states. Specifically, the artificially cemented kaolin with different curing times and confining stresses was tested at a constant strain rate at the pre-peak stage and a stepwise changed strain rate at the post-peak stage using a triaxial shear apparatus.  
1. The fully developed ACK exhibited a shearing behaviour primarily governed by the proportion of intact bonds under low confining stresses, making it insensitive to strain rate. In contrast, under a large confining stress, the cementing bonds are significantly destroyed during isotropic compression, and a negative rate effect is observed due to local drainage at a slow rate of shearing. During the post-peak stage, the shear behaviour of the fully developed ACK switched to a pure isotach with a well-formed shear plane owing to its inherent viscosity.
2. The ACK with a developing structure shows a slight negative effect during the pre-peak stage under both low and high confining stresses, resulting from the combined effect of curing time and local drainage. In the post-peak stage, the presence of an intense stick-slip shear pattern and increased bond breakage at a well-formed shear plane results in an increase in shear resistance, i.e., a negative rate effect.
3. Two types of stick-slip shear patterns were observed during the undrained shearing of ACK with a developing structure. Both types of stick-slip only occurred with a critical threshold strain rate associated with the confining stress. The stick-slip effect at the post-peak stage could be manifested by the normal force on the sliding shear plane, and a linear relationship was found  
Conceptualisation, Q.L. and B.A.B.; methodology, Q.L. and B.A.B.; formal analysis, Q.L., X.Z. and B.A.B.; writing--original draft preparation, Q.L., X.Z. and B.A.B.; writing--review and editing, Q.L., X.Z. and B.A.B.; supervision, B.A.B.; funding acquisition, Q.L. and X.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China (grant no.: 2023 YFC3009300), Stable Support Plan for Colleges and Universities of Shenzhen (grant no.: 20220810151354002), and National Natural Science Foundation of China (grant no.: 52211530088, 52178375).  
Not applicable.  
Figure 9: Stick-slip shear pattern observed in the post-peak shearing stage of YACK: (**a**) under different confining stresses (50, 100, 300, and 600 kPa) and (**b**) Quantified stick-slip effect.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
**Conflicts of Interest:** No potential conflicts of interest were reported by the authors.
# Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships
## 2 Artificial Potential Field
### Modified Artificial Potential Field (APF)
For an emergency action, \(F_{re1}\) and \(F_{re3}\) are the repulsive force from the obstacles and the attractive force from the goal, respectively. \(F_{re2}\) makes the OS avoid collisions from the right or the left side of \(p_{ot}\) according to which side of the \(p_{ot}\) line the vector \(v_{to}\) is on. This modified APF calculates the steering angle (\(\
abla\psi_{os}\)), desired heading (\(\psi_{os}\)), and dynamic position (\(p_{os}\)) by inputting \(p_{ts}\), \(p_{os}\), \(p_{gs}\), \(v_{os}\), \(v_{ts}\), \(R_{os}\), \(R_{ts}\), \(d_{safe}\), \(\rho_{0}\), \(\eta_{d}\), \(\eta_{s}\), and \(\eta_{e}\).
# Automatic Assembly Technology of Dense Small Screws for Flat Panel Parts
## 1 Introduction
By calculating the physical distance, it guides the manipulator to move the camera over the threaded hole to be installed, where further precise positioning is carried out through the industrial camera. 3. A screw assembly quality assessment system was developed. Experiments show that the angle-torque curves of the same type of assembly errors exhibit similar trends. Therefore, the corresponding template curve was fitted using a polynomial, and the screw assembly quality was determined by comparing the screw tightening curve with various assembly template curves based on the Frechet distance. In the scheme presented in this paper, existing issues can be specifically addressed. Firstly, the visual servo method can resolve the problem of poor absolute positioning accuracy of the manipulator. Traditional methods require the target threaded hole to be in the center of the camera's field of view after the manipulator's long-distance movement, a requirement hard to achieve due to the manipulator's absolute positioning accuracy. However, servo-positioning only needs to ensure that the camera's field of view covers the workpiece area. Then, through multiple short-distance movements, the target threaded hole can be approached gradually, allowing the manipulator to complete the task with ease. Secondly, taking advantage of the similarity in the shape of the angle-torque curves of the same type, we designed an assembly quality assessment method based on the Frechet distance. This approach no longer depends on manually setting thresholds or training with  
Figure 1: Missing installation of threaded holes due to motion error of manipulator. large amounts of experimental data. Its principle is easy to understand, making it more suitable for widespread adoption in factories. The structure of this paper is as follows. The introduction describes the research background, current situation, and purpose. Section 2 introduces the automatic screw assembly method in detail, including the main process, definition of the key coordinate system, the servo-positioning strategy, and the screw assembly quality assessment method. Section 3 discusses the prototype experiments and presents the analysis of experimental results to verify the validity of the method. Finally, Section 4 summarizes the conclusions. It also reviews the research content and findings as well as proposes future research directions.
# Enhancement of Low-Light Images Using Illumination Estimate and Local Steering Kernel
## 2 Related Research
### Low-Light Image Enhancement Based on RetinexNet  
RetinexNet was proposed based on the Retinex theory to perform image enhancement by decomposing low-light images into reflection and illumination components. RetinexNet uses Decom-Net to decompose the input image into reflectance and illumination components in the decomposition stage, and trains by using pairs of low-light and normal images in the training stage. However, while RetinexNet's results significantly enhance image brightness, they may introduce color distortion, and issues such as blurriness or noise amplification occur during the process of decomposing and combining images [20]. The improved network model proposed by [PERSON] et al. [21] uses the HSV color space model to address the color distortion and noise problems in RetinexNet. Advanced RetinexNet [22] uses two subnets, DecomNet and EnhanceNet, to appropriately enhance the contrast and suppress noise in the resulting image.  
However, existing low-light image enhancement methods can result in insufficient illumination improvement or color imbalance, and the process of amplifying low-light areas can also amplify noise components. Due to these issues, enhanced images may exhibit distortion and blurriness.
# Blockchain and Cloud to Overcome the Problems of Buyer and Seller Watermarking Protocols
## 5 Security Analysis  
The conducted analysis is based on the following ideal behaviour of the proposed watermarking protocol: \(\mathcal{CP}\) sells \(X\) to \(\mathcal{B}\); \(\mathcal{B}\) gets the protected content \(\bar{X}\) from \(\mathcal{CP}\); \(\mathcal{CL}\) embeds watermarks into the contents sold or published by \(\mathcal{CP}\); \(\mathcal{BC}\) is a ledger that registers the purchase transactions of digital contents sold or published by \(\mathcal{CP}\); \(\mathcal{RA}\) generates data needed to protect \(X\); \(\mathcal{J}\) decides whether \(\mathcal{B}\) is guilty of releasing pirated copies.  
The analysis assumes that:  
* \(\mathcal{J}\) and \(\mathcal{RA}\) cannot be corrupted since they are TTPs.
* \(\mathcal{CP}\) and \(\mathcal{B}\) can be corrupted only \"statically\", i.e., the corrupt entities are decided before the execution of the protocol and cannot be modified throughout the execution [42].
* \(\mathcal{BC}\) and \(\mathcal{CL}\) are characterized by an \"honest-but-curious\" behaviour [42]. They have to follow the rules of the protocol, even though they can try their best to get information from the executed actions. As a consequence, \(\mathcal{BC}\) has to correctly manage the blockchain, whereas \(\mathcal{CL}\) has to correctly apply the received watermarks. In fact, these assumptions are reasonable, since \(\mathcal{BC}\) has only to run smart contracts whose code is accepted in advance and cannot be modified during the life of the blockchain [19]. Similarly, \(\mathcal{CL}\) acts like a delegate that supplies security web services on behalf of \(\mathcal{CP}\). Therefore, if \(\mathcal{CL}\) cannot ensure high security standards, its reputation can be compromised as well as its business possibilities, which ultimately depend on the capability to actually protect the contents distributed by \(\mathcal{CP}\).
* Uncorrupt buyers and content providers do not release pirated copies. With these assumptions, the protocol ensures that:
* If \(\mathcal{CP}\) and \(\mathcal{B}\) are uncorrupt, \(\mathcal{B}\) receives a unique and personalised protected content \(\bar{X}\). Furthermore, pirated copies of \(\bar{X}\) found on the web can be traced back to the original buyer and purchase transaction.
* If \(\mathcal{CP}\) is corrupt, \(\mathcal{B}\) receives a content \(\bar{X}\) that prevents the identification of traitors. In fact, such a corruption is useless and deleterious just for \(\mathcal{CP}\).
* If \(\mathcal{B}\) is corrupt, \(\mathcal{CP}\) aborts the purchase transaction and does not release any content.
## 1 Introduction
In this section, we review some fundamental results of q-calculus theory that were utilized in the design of our q-version of parallel numerical schemes for locating all distinct roots of the nonlinear equation  
\[f(x)=0. \tag{1}\]  
Given \(q\in(0,1)\), the q-integer is defined as  
\[[m;q]=1+q+q^{2}+q^{m}+\ldots+q^{m-1}=\frac{1-q^{m}}{1-q};for\;m=1,2,3,\ldots. \tag{2}\]  
whereas  
\[[m;q]=m;\;\text{for}\;q=1. \tag{3}\]  
The \(q\)-binomial is defined for \(0<j<m\), as  
\[\left[ \begin{array}{cc}m&;q\\ j&;q\end{array} \right]=\frac{[m;q]!}{[j;q]![m-j;q]!}. \tag{4}\]  
Finally, the \(q\)-factorial \([m;q]\) is defined as  
\[[m;q]!=[m;q][m-1;q]\ldots[3;q][2;q][1;q] \tag{5}\]  
and \([0;q]=1\). **Definition 1** ([30; 31]). : _The q-derivative of \(f(x)\) is defined as_  
\[\partial_{q}(x)=\partial_{q}^{[1]}(x)=\big{(}\partial_{q}f\big{)}(x)=\left[ \frac{d}{dx}\right]_{q}f(x)=\frac{f(qx)-f(x)}{qx-x},q\
eq 1. \tag{6}\]  
_For q\(\to 1\), we have_  
\[\partial(x)=f^{\prime}(x)=\left[\frac{d}{dx}\right]f(x), \tag{7}\]_which is the classical derivative. The \(q\)-derivative \(\Big{(}\widehat{\cup}_{q}^{[1]}f\Big{)}(x)\) is known as Jakson derivative [32]. We define higher \(q\)-derivatives as_  
\[\widehat{\cup}_{q}^{0}f=f,\widehat{\cup}_{q}^{n}f=\widehat{\cup}_{q}\Big{(} \widehat{\cup}_{q}^{n-1}\Big{)}\ \ \text{for}\ \ n=1,2,3,\ldots \tag{8}\]  
**Definition 2**. : _Product and quotient of functions \(f(x)\) and \(g(x)\) are defined, respectively, as [33]_  
\[\widehat{\cup}_{q}^{[1]}(f(x)*g(x)) = g(x)\widehat{\cup}_{q}^{[1]}f(x)+f(qx)\widehat{\cup}_{q}^{[1]}g( x), \tag{9}\] \[= g(qx)\widehat{\cup}_{q}^{[1]}f(x)+f(x)\widehat{\cup}_{q}^{[1]}g( x),\]  
_and_  
\[\widehat{\cup}_{q}^{[1]}\Big{(}\frac{f(x)}{g(x)}\Big{)}=\frac{g(x)\widehat{ \cup}_{q}^{[1]}f(x)-f(x)\widehat{\cup}_{q}^{[1]}g(x)}{g(qx)g(x)},g(qx)g(x)\
eq 0. \tag{10}\]  
**Definition 3**. : \(q\)_-[PERSON]'s formula [34] for \(f(x)\) is given as_  
\[f(x) = f(C)+\frac{(x-C)^{[1]}}{[1:q]}\Big{(}\widehat{\cup}_{q}^{[1]}f \Big{)}(x)+\frac{(x-C)^{[2]}}{[2:q]!}\Big{(}\widehat{\cup}_{q}^{[2]}f\Big{)}(x) \tag{11}\] \[+\ldots+\frac{(x-C)^{[n]}}{[n:q]!}\Big{(}\widehat{\cup}_{q}^{[n]} f\Big{)}(x)+R_{n},\] \[f(x) = \sum_{j=1}^{\infty}\frac{\widehat{\cup}_{q}^{[1]}(x-C)^{[j]}}{j!} +R_{n};(\forall x\in(a,b)), \tag{12}\]  
_where \((x-C)^{0}=1,(x-C)^{i}=\overset{n-1}{\Pi}(x-Cq)^{i},i\in N.0<q<1\), \(R_{n}=\frac{(x-C)^{[n+1]}}{[n+1:q]! }\Big{(}\widehat{\cup}_{q}^{[n+1]}f\Big{)}(\xi)\) and \(\widehat{\cup}_{q}^{[1]},\widehat{\cup}_{q}^{[2]},\ldots\) are all \(q\)-derivatives._  
The remainder of the article is structured as follows. In Section 2, we present and analyze a parallel numerical scheme for solving (1) formulated in the framework of quantum calculus. Section 3 discusses the neural network implementation of the proposed q-version of the parallel solver. We address the numerical solution of two nonlinear engineering problems in Section 4. Finally, the paper concludes in Section 5 with some remarks arising from this study.
## 3 Results and Discussion
### Investigations on the Effect of Ultrasound on the Structure of an Olive Leaf  
#### 3.2.1 Examination of Leaf Surface  
Leaf surfaces were examined using ESEM, which does not require any preparation, so a whole leaf could be observed as is. In order to evaluate the impact of ultrasound on leaves, we compared an untreated leaf, a control leaf (after 60 min of stirring), and leaves treated by ultrasound for 5 min, 15 min, and 60 min (Figure 2). Leaves were observed on both surfaces: adaxial (upper surface) and abaxial (lower surface). Observations were conducted on the center of the leaf, corresponding to the exposed area to the ultrasonic field.  
On the control leaf, it was noted the presence of umbrella-like structures, referred to in the literature as non-glandular multicellular hairs [32]. On the abaxial surface, such structures overlapped and recovered the surface of the leaf (Figure 2B), which was not the case on the adaxial surface where hairs were less numerous and more spaced (Figure 2A). Olive leaf hairs are reported to be protective against UV, water loss, and probably insect and pathogen attacks [33]. Furthermore, white particles could be noted on both surfaces of the leaf, which could be dust particles (Figure 2A,B). After 60 min of stirring, it was noted the removal of a few hairs on both surfaces of the leaves (Figure 2C,D), implying that the sole action of solvent stirring led to a partial removal of some hairs. As for the control leaf, dust-like particles were still present on both surfaces of the leaf (Figure 2C,D).  
For leaves submitted to ultrasound, a gradual effect was noticed (Figure 2E-J). Increasing sonication duration from 5 min to 60 min led to sharp modifications of the leaf surface in terms of hair coverage and structure. On the adaxial surface, it appeared that increasing sonication duration resulted in increasing hair removal: after 5 min of sonication, the majority of hairs were still present on the leaf surface (Figure 2E), while after 15 min and 60 min of sonication, the surface was cleared of hairs (Figure 2G,I). A different trend was noticed on the abaxial surface. If after 5 min of sonication, no modification of hair coverage was noticed (Figure 2F), 15 min of sonication led to a complete removal of all hairs (Figure 2H), whereas it was not the case for 60 min of sonication. In the latter case, a partial removal of hairs was noted (Figure 2J). For all ultrasound-treated leaves, dust-like particles were less numerous, suggesting that ultrasound induced local erosion. It is well-known that ultrasound can be used to mechanically remove small particles [34], which also seems to have been the case in our experiments. Overall, we could not notice impacts on the cuticle due to the implosion of cavitation bubbles, and unlike other studies, it could not be concluded that cavitation leads to cell breakage [35]. In our experimental conditions, it appeared that the predominant effect of ultrasound was the removal of plant structures occurring on the surface of the leaves, which is in accordance with the findings of [PERSON] et al. [15].