esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Setup
### Identification of Breakaway Transients  
The force control was implemented for the identification of the breakaway force as a function of the ultrasonic amplitude and the sealing ring material. With the linearly increasing target force being applied to the sealing ring (see Figure 6b), the displacement signal was used to detect the breakaway force. Instead of the traversing velocity, the slope of the force ramp and the US amplitude were varied. \(F_{n}\) and \(t_{1}\) signify the longitudinally applied force and the time since standstill when the breakaway point was reached. This was the moment when the transition from sticking or pre-sliding to sliding in the metal-elastomer contact took place. Additionally, the impacts of adhesive forces on the breakaway dynamics were taken into account by a variation series of the dwell time before a force was applied in the longitudinal direction.  
Figure 6: The velocity profile for the investigation of sliding friction force (**a**) and the force profile for the identification of breakaway force (**b**).  
ultrasonic excitation. Due to the significant reduction in the frictional force that only started at 16 \(\upmu\)m, the vibration amplitude increased to 32 \(\upmu\)m. This caused a further reduction of up to 81%. In terms of stable thermal and kinetic operation conditions, a maximal amplitude of 16 \(\upmu\)m was chosen for further experiments. With the investigation of the two materials, PTFE and NBR70, at a speed of 50 mm/s, the positive effects in terms of friction reduction at different ultrasonic amplitudes were clearly demonstrated. For a better understanding of the conditions within the breakaway area, the breakaway forces were measured with the use of force control.
# Improving Throughput of Mobile Sensors via Certificateless Signature Supporting Batch Verification
## 3 A Certificateless Signature Scheme Supporting Batch Verification  
### Zero-Knowledge Proof with Pairing  
In the above scheme, we need to provide a NIZKP of \(y\) in the user public key to avoid adversaries bypassing \([x]P\) by setting \([y]P\). However, zero-knowledge proof requires additional overhead and increases the length of the user public key. We provide an extension scheme that uses bilinear pairing tools to verify the binding relationship between \([x]P\) and \([y]P\). A user who verifies the signature can ensure that the signer knows the y corresponding to Y by calculating \(e([x]P,[y]P)=e([xy]P,P)\). The extension scheme is depicted in the following.
## 2 Literature Review
### Dual-Channel Supply Chain  
A dual-channel supply chain can be defined as a supply chain that exists concurrently with both a producer's direct sales channel and a traditional retailer's distribution channel. The advent of the Internet has precipitated a shift in consumer purchasing patterns, with an increasing number of consumers opting to purchase products directly from producers via e-commerce platforms. This has led to the emergence of a hybrid model, characterised by the coexistence of online direct sales channels and offline distribution channels. The majority of research conducted on dual-channel supply chains focuses on three key areas: pricing strategy, channel selection, and channel coordination.  
[PERSON] [12] conducted an early study on dual-channel supply chains, established a mathematical model for analysing the Nash equilibrium under pricing decisions, and highlighted that the addition of direct sellers will have an impact on existing retailers. [PERSON] et al. [13] conducted a study on green supply chains with reverse logistics, calculating the pricing decisions and green strategies of different subjects as core enterprises. Their findings revealed the existence of a market share threshold, determining whether a producer enterprise would choose to open a direct sales channel. [PERSON] et al. [14]considered a scenario where a supplier provides both organic and conventional agricultural products and analysed the optimal pricing decisions and consumer demand for a dual-channel supply chain in such circumstances. In their study on the pricing decision problem in a dual-channel supply chain, [PERSON] et al. (2015) considered the retailer's tendency towards fairness in a closed-loop dual-channel supply chain. They concluded that while the retailer's risk aversion may increase the manufacturer's profit, the manufacturer's profit may also be decreased by the retailer's fairness concerns.  
Although the development of e-commerce has brought about a boom in online shopping, it is not clear whether the addition of new online channels is profitable for each subject in the supply chain. [PERSON] et al. (2016) studied the channel choice problem for producers in the supply chain and found that producers can choose an online dual-channel sales strategy when the consumers in the new channel are price-insensitive. [PERSON] et al. (2017) analysed the pricing and channel choice problems when producers sell green products to environmentally conscious consumers. They conducted an analysis of the pricing and channel selection problems when producers sell green products to environmentally conscious consumers. They proposed that consumers' green awareness affects the channel selection behaviour of supply chain members. [PERSON] et al. (2018) proposes a dual-channel, multi-product, multi-period, multi-echelon closed-loop supply chain under uncertainty for the tyre industry. They find that setting the appropriate prices in different channels for the available tyre types is critical for sustainable tyre supply chain management.
## 5 Results and Discussion
### Sensitivity Analysis
Figure 14 provides contours of the velocity and temperature fields for different equivalence ratios at fixed \(Re=1200\) and \(H/d=\)2.0. As \(\phi\) increases from 0.9 to 1.2, the height of the premixed cone first decreases and then increases, which is inversely proportional to the laminar flame speed of the premixed methane flame [59]. It can also be found that the velocity behind the reaction region is directly proportional to the laminar flame speed. When the equivalence ratio gradually increases, its velocity increases and then decreases. The flame temperature of \(\phi=0.9\) is lower than the other three due to less fuel participating in the reaction. Figure 15 shows the radial \(Nu\) distribution of different equivalence ratios. The results show that for fixed \(H/d\), when the premixed cone does not touch the impingement plate, the closer the flame tip is to the plate, \(Nu_{0}\) is higher, which is consistent with the results observed by [PERSON] and [PERSON] [19]. In the wall jet region, the radial \(Nu\) distribution rises with increasing \(\phi\) since more fuel is burned (releasing more heat), which is the major exothermic reaction from the oxidation of CO to CO\({}_{2}\) in the post-flame region of the premixed cone [4]; that is, OH + CO \(\rightarrow\) CO\({}_{2}\) + H. The distribution of OH changes more widely with \(\phi=0.9\) increases to 1.2, as shown in Figure 16. In addition, it is also observed that the OH concentration in the reaction zone is related to the \(Nu\) value in the  
Figure 12: The contours of 2D velocity (**left**) and temperature (**right**) fields of the PMIFJ at \(\phi=1.2\) and \(H/d=1.5\) against different \(Re=\) (**a**) 600, (**b**) 800, (**c**) 1000, and (**d**) 1200. Figure 13: Radial Nusselt number (\(Nu\)) on impingement plate at \(\phi=1.2\) and \(H/d=1.5\) against different \(Re\). stagnation zone. PMIFJs with \(\phi=0.9\) and \(1.2\) have similar premixing cone heights, and the radial \(Nu\) distribution also has the same trend. However, the OH concentration of \(\phi=0.9\) is higher than that of \(\phi=1.2\), causing the \(Nu\) value of \(\phi=0.9\) in the stagnation region to be greater than \(\phi=1.2\). The \(Nu\) distribution at \(\phi=0.9\) in the wall jet region is significantly decayed, attributed to excess air in the unburned mixture and less heat released by the flame [25; 59]. Figure 14: The contours of 2D velocity (**left**) and temperature (**right**) fields of the PMIF at \(Re=\)1200 and \(H/d=2.0\) against different \(\phi=\) (**a**) 0.9, (**b**) 1.0, (**c**) 1.1, and (**d**) 1.2. Figure 15: Radial Nusselt number (\(Nu\)) on impingement plate at \(Re=1200\) and \(H/d=2.0\) against different \(\phi\).
# Usability Testing of Mobile Applications:
## 4 Methodological Framework for Mobile Usability Testing
### Research Settings for Usability Testing of Mobile Applications
#### 4.1.2 Field Studies  
By definition, a field study is understood as an investigation that is conducted in an environment that is not under the total control of the researcher [68]. Such a testing strategy assumes that the tasks are performed directly by the users in the field, in the workplace, or in any other non-laboratory location. Although there are no formal standards, it is widely accepted practice that users are not under any control. However, they are generally instructed as to the objectives of the study and the predefined tasks. One could also think of controlled laboratory research [69], that is, research that is carried out in an environment that is specifically designed for research [70].  
The main advantage of field study is its generalizability to real-life contexts as it represents a greater variety of situations and environments that users experience in their natural environment. It is a powerful method for understanding the role of context in shaping user experience by providing a better understanding of subjective attitudes. A unique strength lies in its ability to reveal elements of users' experiences that we were previously unaware of [71].  
On the other hand, embedded context includes possible factors that may affect the user while performing a task. These can be external, environmental, and personal influences. Let us consider three examples. In the case of external factors, a user is exposed to factorsbeyond his or her control, such as blinding sunlight, deafening noise, heavy rain or snow, or strong wind. Environmental factors involve interaction with the environment. For example, a user standing on a bus, holding on to the handrail with one hand, and using a smartphone with the other hand, has limited capacity. Personal factors are related to motivation, pressure, and stress [72], which can have different causes and sources, related to both personal life and professional work.  
From a practical point of view, field-based testing is carried out by means of a mobile device and a wireless camera, both attached to a portable stand, or by means of a screen recorder installed on a mobile device [73]. In addition, it is claimed that the process per se is time-consuming and complicates data collection [74].
# Influence of Thin Fluorine Resin Film on DUV LED Packaging Devices
## 3 Results and Discussion
The light output power remained over 100% for all devices, better than the at least 10% decay in previous studies [15,16], indicating that fluorine resin has no influence on the lifetime characteristic under this level of light output power. In order to verify whether the thin fluorine resin film can also be beneficial in the higher light output power of DUV LED packaging devices, Chip B and Chip C were used in the samples by dripping fluorine resin two times and the curing time was 24 h. The test current was 100 mA for Chip B and 350 mA for Chip C, respectively. The photoelectric and reliability characteristics are shown in Figure 6. As can be seen in Figure 6a, the light output power improved from 12.78 mW to 13.96 mW at 100 mA with a rise of 9.23% for Chip B, and the light output power improved from 49.82 mW to 55.01 mW at 350 mA with a rise of 10.41% for Chip C. The results prove that a \(\sim\)10% enhancement of light output power can be achieved when fluorine resin is used for packaging. However, as the preliminary reliability test result shows in Figure 6b, after aging for 1000 h, the relative output power of the fluorine-resin-packaged device with Chip B decayed by 11.26% at 100 mA, while no decay was observed in the devices without fluorine resin at the same current. At the same time, the reduction was 16.99% for Chip C with fluorine resin compared with bare Chip C at 350 mA. This result may have been caused by DUV-induced photolysis related to the two oxygen atoms in the five-membered ring [14].When the light output power is 12 mW or larger, obvious decay is observed, the fluorine resin material is still unstable for high-power DUV applications.
# An Evaluation Framework and Algorithms for Train Rescheduling
## 7 Description of the Experiment
### Statistical Analysis  
Given the results obtained for the input problem dataset, for a performance indicator, we want to confirm or reject statistically that there is a significant difference in the performance of the algorithms. To this end, the results of the experiment are analyzed using a statistical test. A general assumption of many statistical tests, called parametric tests, is that the data are normally distributed [38]. Non-parametric statistical tests, unlike their parametric counterparts, make no assumption about the data distribution. Hence, we use a non-parametric test called Wilcoxon signed-rank to test our hypotheses.  
Using the Wilcoxon signed-rank test, we test if there is a difference between the performance of the two algorithms. The null hypothesis is that the median of the differences between pairs of observations is zero [39]. The \(p\)-value is interpreted as the probability that the difference in the medians of the observations (corresponding to the two algorithms) can be attributed to chance alone [40]. We apply the two-tailed Wilcoxon signed-rank test with a significance level \(\alpha=0.05\). We reject the null hypothesis if the obtained \(p\)-value is less than 0.05. Rejecting the null hypothesis shows that the difference between the performance of the two algorithms was unlikely to occur by chance. We use the scipy.stats.wilcoxon() function from the open-source software SciPy to perform the Wilcoxon signed-rank test. In the next section, wherever relevant, we mention the \(p\)-value obtained from the aforementioned test.
# Building Penetration Losses at 3.5 GHz: Dependence on Polarization and Incidence Angle
###### Abstract  
We measured and analyzed the building penetration losses for four different kinds of facades as a function of the incidence angle and polarization at 3.5 GHz, which is a frequency of interest for fifth generation (5G) communication systems. Results show that the attenuation may vary up to 8 dB with the incidence angle, which justifies the need for an angular characterization of the penetration losses, going beyond the simpler characterization used for normal incidence. We also found that there is a relevant polarization dependence of this attenuation, as electromagnetic theory predicts for wave transmission across flat discontinuities and even across flat dielectric slabs. Results would be of interest for the network design of future 5G base stations using orthogonal polarizations.  
Keywords:5G; incidence angle; penetration losses; polarization Article Building Penetration Losses at 3.5 GHz: Polarization and Incidence Angle
# MPC for Optimized Energy Exchange between Two Renewable-Energy Prosumers
## 2 Problem Formulation
### State-Space Formulation  
To develop a state-space representation of the system, it is first necessary to define an objective function and system outputs. Table 1 organizes the definitions of objective function terms and corresponding outputs. Each term represents a system energy component that can be penalized by selection of corresponding weighting terms, \(C_{1}\) to \(C_{5}\). Note that renewable energy that is consumed directly by the loads is not penalized, whereas there are objective terms for externally supplied power  
Figure 2: Coupled microgrid block diagram with two prosumers.  
\((J_{1R},J_{1C})\), energy into and out of the batteries \((J_{2R},J_{2C})\), energy flows to other network prosumers \((J_{3R},J_{3C})\), RER flows between the coupled prosumers \((J_{4R},J_{4C})\), and battery flows between the coupled prosumers \((J_{5R},J_{5C})\). Constants \(C_{1}\) to \(C_{5}\) serve as weighting parameters that can modify the relative significance of each objective term. The definition of the terms \((J_{1R})\) relies on the constraint that the load must be completely satisfied at each time step \((P_{1R}=P_{LR}-P_{2R}-P_{4R}-P_{CR}-P_{BCR})\). The same constraint holds for the commercial prosumer.  
To formulate the state-space model, we define the ten system outputs listed in Table 1 which are combined as a single output vector \(y(k)\). The system input \(x(k)\) is constructed from \(x_{m}(k)\) and \(y(k)\). The following expressions summarize these relationships.  
\[y(k+1)=[y_{mR}(k),\ y_{mC}(k),\ y_{aR}(k),\ y_{aC}(k),\ y_{bR}(k),...\]  
\[y_{bC}(k),\ y_{dR}(k),\ y_{dC}(k),\ y_{eR}(k),\ y_{eC}(k)]^{\top},\]  
\[x(k)=\left[\begin{array}{c}x_{m}(k)\\ y(k)\end{array}\right].\]  
\[x(k+1)=Ax(k)+Bu(k), \tag{2}\]  
\[y(k)=Cx(k),\]  
where  
\[A=\left[\begin{array}{cccccccc}I_{2\times 2}&0_{2\times 10}\\ 0_{10\times 2}&0_{10\times 10}\end{array}\right],\]  
\[B=\left[\begin{array}{ccccccccc}0&0&\eta_{c}&0&-\eta_{D}&0&0&0&0\\ 0&0&0&\eta_{C}&0&-\eta_{D}&0&0&0&0\\ C_{1}&0&0&0&C_{1}&0&0&C_{1}&0&0\\ 0&C_{1}&0&0&0&C_{1}&C_{1}&0&0&0\\ C_{3}&0&C_{3}&0&0&0&C_{3}&0&0&0\\ 0&C_{3}&0&C_{3}&0&0&0&C_{3}&0&0\\ 0&0&C_{2}&0&C_{2}&0&0&0&0&0\\ 0&0&0&C_{2}&0&C_{2}&0&0&0&0\\ 0&0&0&0&0&0&C_{4}&0&0&0\\ 0&0&0&0&0&0&0&C_{4}&0&0\\ 0&0&0&0&0&0&0&C_{5}&0\\ 0&0&0&0&0&0&0&0&C_{5}\end{array}\right],\]  
and  
\[C=\left[\begin{array}{cc}0_{10\times 2}&I_{10\times 10}\end{array}\right].\]
## Further Security and Privacy Insights
### Enhanced Privacy through PETs  
Our suggested framework allows data processing while maintaining privacy through the use of PETs. PETs enable computations to be carried out on encrypted data, producing an encrypted output that, upon decryption, corresponds to the results of operations conducted on the original plaintext. For example, threshold homomorphic encryption guarantees that only authorized entities can decrypt the ciphertexts, preventing unauthorized access and data breaches.  
Implementing and integrating advanced cryptographic techniques like zero-knowledge proofs and secure multiparty computing improves the privacy and security of VANETs by allowing verification of data integrity and authenticity without disclosing the actual data. This is crucial in situations where disclosing sensitive data (such as location or driver behavior trends) could put user privacy or security at risk. The cryptographic primitives in our suggested framework meet current security needs and are designed to handle future threats and problems in the evolving field of vehicular communications. Our framework establishes a new benchmark for privacy and security in VANETs by implementing advanced security techniques to secure sensitive data from complex cyber threats.
## 3 Experimental Techniques to Check a Possible Degradation of PCM
### X-ray Powder Diffraction (\"XRD\")  
X-ray powder diffraction (XRD) is mainly employed for the phase identification of a crystalline material, which can be used to perform compound identification. Therefore, the material is finely ground, homogenized, and the average bulk composition is determined. Based on these features, XRD can be easily applied to determine changes in the crystalline structure or the formation of new materials of a solid PCM due to a degradation process.  
XRD measurements are presented as a diffractogram, where the X-ray intensity is plotted as a function of the scanning angle. The typical aspect of a diffractogram consists of a horizontal baseline alternated with sharp peaks denoted as diffractions. These diffractions are used to identify the compounds present in the sample. If, e.g., due to a degradation on thermal cycling, new solid compounds appear in the solid PCM, they can be identified when comparing the diffractogram of the original sample with that of the degraded sample. Mass concentrations as low as 2% with respect to the sample mass can be detected.  
A potential phase separation can also be investigated by extracting aliquots from different locations of the PCM sample submitted to thermal cycling and comparing their phase/compound compositions by XRD. Some XRD devices can perform measurements under different temperatures, giving the possibility to study the variations of the structure of the solid PCM upon heating or cooling.
### The Analysis of the Impact of Mining Size on Fault Activation
#### 2.4.1 Analysis of Barrier Effect of Mining Size on Rock Mass Movement  
As the depth and mining size becomes greater, the barrier degree of the fault plane is enhanced, and the maximum displacement value of the surrounding rock on the hanging wall near the fault plane increases dramatically. When the mining size increases along the vertical direction, the displacement difference between the rock masses on both sides of the fault plane will also have a positive correlation change, and the stress value and the maximum principal stress concentration will also increase. When the vertical direction of mining size changes to 50 m \(\times\) 100 m, 50 m \(\times\) 200 m, 50 m \(\times\) 300 m, the corresponding displacement difference changes are 0.06 cm, 0.35 cm, and 2.52 m. When the mining size changes along the horizontal direction, it also presents the same change law as the vertical direction. When the mining size changes along the horizontal direction are 100 m \(\times\) 50 m, 200 m \(\times\) 50 m, 300 m \(\times\) 50 m, the corresponding displacement difference changes are 0.15 m, 0.8 m, and 1.0 m. Figure 20 illustrates the displacement field distribution of the surrounding rock under different mining sizes. Compared with the aforementioned initial excavation size, the increase in the excavation size resulted in a large discontinuous change in the displacement distribution and maximum principal compressive stress of the rock mass on both sides of the fault plane. Especially after doubling the mining depth, the displacement and the maximum principal compressive stress values of the surrounding rock in the excavation area close to the fault plane increase more year-on-year, which also indicates that the barrier effect of the fault plane has been greatly strengthened. Through comparison, it can be found that the influence of the mining area change in vertical depth direction on the barrier degree is more sensitive than the change in horizontal length direction under the condition that the mining area and fault are separated by the same distance. The influence area of rock mass movement and deformation increases with the depth of the excavation area. The more potential energy consumed by the plastic deformation of the fault plane and the friction of the structural plane, the more significant the difference in deformation of rock movement between the two sides of the fault plane.  
Figure 19: The stress field distribution in the surrounding rock at the excavation size of 200 m \(\times\) 50 m, they should be listed as: (**a**) Maximum principal stress distribution; (**b**) Minimum principal stress distribution.  
Figure 20: _Cont._