esa-sceva/satcom-chunk-collection huggingface dataset:
# Hidden Markov Model-Based Dynamic Hard Shoulders Running Strategy in Hybrid Network Environments
## 3 Dynamic Hard Shoulder Running Strategy Based on Hidden Markov Model
### Viterbi Algorithm Prediction  
The proposed freeway HSR strategy in mixed traffic flows with CAVs in this research was mainly based on the traffic breakdown prediction based on the hidden Markov model in Section 3.2. The road detector detects the traffic density \(K\) of a road segment as well as the corresponding CAV penetration rate \(\rho_{CAV}\) and the average vehicle speed \(V_{mean}\) per \(t_{c}\) minutes. Therefore, the breakdown state variables \(S(t)\), \(K(t)\), \(\rho_{CAV}(t)\) and \(V_{mean}(t)\) can be obtained at the current moment \(t\).  
In order to predict the road traffic state in the next \(t_{c}\) minutes, the display state sequence with a length of \(t_{c}\) is obtained by first estimating \(K(t+t_{c})\), \(\rho_{CAV}(t+t_{c})\) after \(t_{c}\) minutes based on the road segment density and CAV penetration rate transition matrix and the current traffic observations. Since the breakdown state of the past \(t_{c}\) minutes is known, the breakdown state before \(t_{c}\) minutes is defined as the initial value of the hidden state, which corresponds to the initial hidden state distribution vector \(\pi\). Then, the Viterbi algorithm is used to predict the traffic breakdown state after \(t_{c}\) minutes based on the display state sequence and the initial hidden state distribution vector \(\pi\) as well as the hidden state transition probability matrix \(A\) and the two-state corresponding probability matrix \(B\). The prediction process is as shown in Figure 4.  
Figure 4: Viterbi algorithm process.  
Since the final result of the Viterbi algorithm is the probability of an event occurring, in order to specify the traffic state and provide a basis for HSR, the maximum event probability obtained for each operation is defined as \(\delta(i,t)\), that is, the breakdown state of the road section at moment \(t\) is most likely to be \(i\).
# Enhancing Supercapacitor Simulation Accuracy Through a Novel Hybrid Modeling Approach
## 2 SC Modeling and Parameter Estimation Methods
### Supercapacitor Modeling Approaches
#### 2.1.1 Electrochemical Modeling  
The electrochemical modeling of supercapacitors presents the ability to accurately represent the reaction process occurring inside the SC without using coupled partial differential equations [21]. These models rely on electrochemical theory based on physical principles and require complex equations [37]. [PERSON] [38] recognized and described the phenomenon of the electric double layer using a model that assumed that all charges were adsorbed at the electrode surface. This design resembles a standard dielectric capacitor in terms of construction. In [39], [PERSON] refines the [PERSON] approach to consider the ion mobility inside the electrolyte solutions in the form of a function that includes diffusion and electrostatic forces. Analytically, the link between the local electric potential and the ion concentration in the diffuse layer was represented by the Boltzmann distribution equation. These models have the capability to encompass the effects of inter-particle pores and porous electrodes, which are directly relevant to the specific application of the supercapacitor model and the demand for such information in the context of supercapacitors.  
However, despite their relatively high accuracy, the electrochemical models suffer from high computational time and complex model calibration, which reduce their practical utilization in supercapacitor modeling [10; 40].
## 4 Analysis Example and Methods
### Results from the BHP Vibration Experiment
#### 5.3.2 Pulsation Absorption Experiment Results for the BHP with Different Lengths of Pipeline  
The flow pulsation curves for the different BHPs are shown in Figure 19. The amplitude of the flow pulsation at the outlet of both the double-layer BHP with RTV as the elastic layer and the three-layer BHP with RTV-SWCNTs composite materials as the elastic layer decreases with the increase in the length of the pipeline. In the limited length range of the experiment, the capacity of the BHP to absorb flow pulsation increases with the increase in its length.  
In reference to Section 5.3.1, the comparison curves for the flow pulsation at the outlet of the double-layer BHP with RTV or RTV-SWCNTs composite materials as the elastic layer under the same length of pipeline are shown in Figure A3 (Appendix C).  
It can be seen from Figure A3 that the amplitude of the flow pulsation in the three-layer BHP with RTV-SWCNTs composite materials as the elastic layer is significantly lower than that of the double-layer BHP with RTV as the elastic layer. The absorption effect of the flow pulsation in the BHPs with different lengths is shown in Table 9.  
The standard deviation for the flow pulsation in the three-layer BHP with SWCNTs added is significantly lower than that of the double-layer BHP with RTV as the elastic layer. With the increase in the length of the pipeline, the standard deviation for the flow pulsation at the outlet of the pipeline decreases, and the effect of the pulsation absorption increases. When the length of the pipeline is 230 mm, the percentage of pulsation reduction is the largest and the absorption effect of the flow pulsation is the best, which lays the experimental foundation for further optimization of BHPs.
# Diode Laser Welding/Brazing of Aluminum Alloy to Steel Using a Nickel Coating
## 5 Conclusions  
Laser welding/brazing of Al alloy to Ni-coated steel by characterization of a microstructure, hardness distribution, and joint fracture load was performed. The influence of Ni coating was clarified by comparing the Al/bare steel joints. The following conclusions were made:  
1. For the Al/Ni-coated steel joint, a nonhomogeneous reaction layer was observed at the interface: Ni\({}_{5}\)Zn\({}_{21}\) formed at the direct irradiation zone, while Al\({}_{3}\)Ni formed at the FZ root.
2. For the Al/bare steel joint, a homogeneous reaction layer consisting of Fe\({}_{2}\)Al\({}_{5}\) and FeZn\({}_{10}\) was formed at the interface.
3. The microhardness of the interfacial reaction layer in an Al/Ni-coated steel joint is 278-318 HV, which is much lower than that of the Al/bare steel joint (~512-526 HV).
4. The fracture load of the Al/bare steel joint was only 743 \(\pm\) 65 N, but it improved to 932 \(\pm\) 92 N by adding the Ni coating.
5. The Ni coating acted a physical barrier to avoid the direct mixing of elements Fe and Al, which inhibited the formation of brittle Fe\({}_{2}\)Al\({}_{5}\). Hence, it led to the improvement of joint strength.  
[PERSON] conceived and performed the experiments, analyzed the data, and wrote the paper. [PERSON], [PERSON] and [PERSON] provided the experimental materials and laboratory equipment, and directed the research. [PERSON], [PERSON], [PERSON] and [PERSON] contributed to the discussion and interpretation of the results.  
This work was supported by National Natural Science Foundation of China (grant Nos. 51665038, 51775091 and 51605276), Key Project of the Natural Science Foundation of Jiangxi Province (grant No. 20171 ACB21011) and the Science and Technology Planning Project of Sichuan Province (grant No. 2018 GZ0284).  
The authors declare no conflicts of interest.
## 6 Experiments and Results
### Standalone AtomGID Experiments
#### 6.1.1 Simulation with Eight Directions  
In addition to the naturalistic experiments that were conducted at our lab, a simulator was developed to validate the algorithm on a larger number of gestures. The simulator uses a uniform distribution to generate noise in the gestures. It is not copying the behavior of RSSI observed in a smart environment, which is quite challenging to approximate. In the smart home, the observed noise is not random, and therefore patterns can be distinguished depending on the zone of the localization. These patterns cannot be modelized since they depend on the exact configuration of the objects/persons in the smart environment. The results of any RFID simulation are always optimistic, but it gives a good overview of the potential application within realistic contexts.  
Several simulations were conducted to validate the algorithm. In this section, we present the most interesting using a continuous stream of eight randomly generated directions. The reader may first take a look at the confusion matrix of the overall simulations presented on Figure 9. Overall, 56,741 gestures were generated over approximately three days of computing. The overall accuracy averaged 93.23%. As the matrix shows, the only gesture affecting the accuracy is the idle gesture with an average of 63.73%. Without it, the performance climbed to 99.75%. These results suggest that the transition between different gestures is actually very well detected. Obviously, as shown by previous experiments in the smart home, the simulation is too optimistic compared to the real RFID localization but gives a good overview of the capacities of AtomGID.  
Figure 8: Example gestures used for the experiments. Eight are composed of two directions, four are composed of only one. The last on the picture is idle.  
One final experiment we performed with gesture recognition was to compare different correlation thresholds and different sizes for the idle gesture. With the simulator, the results were unambiguous. A lower correlation threshold drastically improves the recognition of the idle gesture. At 0.25, the accuracy is 96% (under that, it becomes lower). Then, it is, respectively, 88.4%, 75.34%, 64.6%, 52.38%, and 38.9% at 0.3, 0.35, 0.4, 0.45, and 0.5. The accuracy of the other gestures correlates inversely but is more stable, varying from 96.4% at 0.25 to 99.75% at 0.45. The thresholds do not behave in the same way in the smart home, where noise is much harder to distinguish from gestures. This shows that the thresholds are closely tied to how well an idle object can be distinguished, while at the same time, they do not much affect the overall recognition. Note that it is assumed that most objects are idle in the smart home and only one at a time can be active. Since an ad hoc algorithm performs this filtering, AtomGID is set to a higher threshold.
## 2 The State-of-the-Art
\begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Goal** & **Approach** & **Capability** & **Weakness** & **Algorithm** & **Authors** \\ \hline  & & & Adversarial example detection using latent neighborhood graph [24] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [24] \\ \hline  & & & Feature distance space analysis [25] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [25] \\ \hline Fault resilience & Redundancy and fault masking & Perturbation absorption & Computational intensive model synthesis and inference redundancy & Explicit redundancy [31] & [PERSON]; [PERSON]; [PERSON] [31] \\ \hline  & & & Weight representation with error-correcting codes [32] & [PERSON]; [PERSON] [32] \\ \hline  & & & Fault-tolerant training based on fault injection during training [33] & [PERSON]; [PERSON]; [PERSON] [33] \\ \hline  & & & Neural architecture search [34] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [34] \\ \hline  & Graceful degradation and recovery by downloading a clean copy of weights & The model does not improve itself and information from vulnerable weights is not spread among other neurons & Encoding the most vulnerable model weights using a low-collision hash-function [44] & [PERSON]; [PERSON] [44] \\ \hline  & & & Checksum-based algorithm that computes low-dimensional binary signature for each weight group [45] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [45] \\ \hline  & Active recovery & Performance recovery & Not reliable recovery & Contrastive fine-tuning on diagnostic sample [46] & [PERSON]; [PERSON]; [PERSON]; [PERSON] [46] \\ \hline  & & & Weight-shifting mechanism in self-organizing map [47] & [PERSON]; [PERSON] [47] \\ \hline  & & & Applicable only to counteract virtual concept drift and useless in case of real concept drift & Domain randomization [35] & [PERSON]; [PERSON] [35] \\ \hline  & & & Adversarial data augmentation [36] & [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [36] \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._The analysis of related works allows us to conclude that most studies focus on separate principles of resilience of data classification models, but there are virtually no works which consider their coterminous combination to provide a synergy effect. The analysis shows that the known approaches implementing particular resilience properties do not take into account the principles of affordable resilience [7], which is relevant in the context of limited resources. To summarize, there is a strong need to evolve a new algorithm to provide image classifier resilience to well-known perturbations considering the resource efficiency.
# Effects of Sidewall Brightness on LED Lighting Environment and Visual Performance in Road Tunnels
## 3 Tunnel Lighting Environment Parameters
### Spectral Distribution of LED Light Sources  
The spectral distribution of LED light sources with different color temperatures is shown in Figure 7. According to the spectral distribution in Figure 7, the spectral irradiance of the LED light sources increased with the increasing brightness in the tunnel. The spectral irradiance distribution reflects the radiation energy of light at different wavelengths. When the electric power of LED lamps was the same, the spectral irradiance of the LED light sources in the tunnel decorated with energy-storage and luminescent coating was greater than that decorated with gray cloth. For the LED light sources, the spectrum presented the bimodal distribution characteristics, and there were obvious differences in the bimodal distribution characteristics of LED light sources with different color temperatures. The spectrum with relatively high peak on the left (about 450 nm, see Figure 7c-e) corresponded to high color temperature, and that on the right (between 540 nm and 590 nm, see Figure 7a,b) corresponded to low color temperature. For the LED light sources with low color temperatures of 2500 K and 3500 K, the blue light component with the wavelength of 430-480 nm was less, while the red and yellow light component with the wavelength of 580-780 nm was more. As the color temperature increased to more than 4500 K, the blue light in the range of 430-480 nm gradually increased and the red and yellow light in the range of 580-780 nm gradually decreased.
# An Evaluation Framework and Algorithms for Train Rescheduling
## 7 Description of the Experiment
### Freight Train Performance  
According to the average values of the metrics used for freight train performance (Table 18), the rescheduling strategy used by ALG1 is problematic from a freight train perspective. Note that none of the algorithms explicitly optimize any metric related to freight trains. In addition, note that, in this experiment, there is no additional time associated with enforcing an unplanned train stop, unlike in, e.g., the model adopted in [19]. Hence, no correlation between the increase of unplanned stops and travel times is expected.  
The solutions obtained by the algorithms for scenario 7 are interesting; the freight trains have eight unplanned stops (see Figure 3). For this scenario, ALG1 obtained a solution (i) with larger deviation in freight train departure times (\(d=16\) min) compared to ALG2 (\(d=8\) min), (ii) with minimal increase in travel times (\(i=2\) min) compared to ALG2 (\(i>10\) min). Hence, with respect to freight train travel times, the solution of ALG1 may be seen as a good alternative to ALG2's solution.  
Disturbance scenarios 11-20 are those where a passenger train runs slower throughout its route. For a majority of these scenarios, ALG2 obtains solutions in which the values of \(d\), \(i\), and \(u\) are negligible (see Figure 3). ALG2 shows a similar performance for disturbance scenarios 21-30, wherein it obtains solutions with small values of the considered metrics. In the solutions obtained by ALG1 for the last ten scenarios, the freight trains incur comparatively (i) large departure deviations, (ii) larger number of unplanned stops, and (iii) higher increase in travel times (see Figure 3). The rescheduling performed by ALG1 often caused many freight trains to arrive early (see Figure 4), even when the train initially affected by the disturbance is a passenger train.
## 4 Results
### Experimental Results of Method 2  
In experiment 2, we obtained the image shown in Figure 7a through camera 2 and built an image deviation detection platform with the help of the Labview platform to achieve a fast belt deviation detection.  
Figure 5: Image processing results using Method 1: (**a**) original image, (**b**) region of interest, (**c**) binary image, (**d**) result of Canny algorithm, (**e**) line in the parameter space, (**f**) result of Hough transform.  
Figure 6: Image processing results using Method 1: (**a**) \(d_{x}\), the x-coordinate where the line intersects the X-axis, (**b**) \(\theta\), the angle between the line and the Y-axis.  
Figure 7a is the raw data image obtained by camera 2. There are two mutually perpendicular laser lines on the conveyor belt surface. Among them, the laser along the bandwidth is used to detect the cross-sectional area of the material. The laser line is used as the measurement reference line for deviation. Figure 7b is the HSV image obtained by converting the RGB image, Figure 7c is the binary image after threshold segmentation, and Figure 7d is the distance information obtained by caliper processing, and its unit is a pixel. All the measurement data during the entire experiment were output to Figure 8.  
The two curves in Figure 8a respectively represent the distance between the left and right edges of the conveyor belt and the laser reference line, and Figure 8b shows the difference between the two distances. When we set a threshold T in Figure 8b, when the difference between the two distances exceeds this threshold \(T\), the system will issue an alarm and make the deviation device act and adjust the deviation in time to avoid failure. This method also accurately reproduces the process of simulating the deviation of the conveyor belt.
## 4 Discussion
### Literature Analysis
#### 4.2.1 Description of Techniques for Image Acquisition  
Within the WBCT workflow, techniques for image acquisition are used to dynamically position the patient under physiological load during acquisition to improve detection of designated pathologies. The most investigated one, syndesmotic instability [17,79,80], has cadaveric and clinical studies showing that, due to the configuration of the distaltibiofibular joint and the injury mechanism, external torque potentializes the diagnostic capabilities of WBCT. Without this stress test and if no post-processing is applied, WBCT does not appear to be superior to MDCT in diagnostic terms, although it already is in terms of radiation and time spent in the workflow. This occurs only if manual, one-dimensional measurements are taken. However, post-processing techniques such as distance mapping of the syndesmosis and surface or volumetric measurements described below have re-established this superiority.  
The Coleman block test Is reported In a level IV study Investigating hindfoot alignment in cavovarus feet using clinical examination, radiographic views assessing the hindfoot angle and WBCT assessment of the foot-ankle offset [19], showing correlation between the 3 modalities.  
In another level V report [43], the use of shed auto-varus is reported in the diagnosis of lateral ankle instability and suggests the use of standardized jigs to induce a normalized amount of varus or valgus depending on the target diagnosis (Figure 5).  
Techniques for image acquisition also included static methods for acquiring more data. In a level III study, [PERSON] et al. used a built-in pedagraphy sensor [44] to assess the position of the center of pressure and compared it to the result of the foot-ankle offset (as anatomical foot center) in 90 patients (180 feet). They found an average distance between the two centers at 28.7 mm, being the anatomical foot center distal to the center of pressure in 175 feet and lateral to it in 112 feet. No significant medio-lateral differences were found. It could be anticipated that more sensors investigating weight or bone density could be used in the future to increase semetiology during WBCT acquisition. This could be useful in assessing bone health or pressure points in diabetic patients, for example, or more simply to standardize positioning of patients within the WBCT machine during acquisition. This issue has been taken into account by the industry, using specific gentry to standardize positioning, especially in the knee, but the reproducibility seems to remain questionable, as has been reported recently by a group of radiology researchers [15].  
Figure 5: Example of a coronal plane MPR (multiplanar reconstruction) view following shed auto-varus in a case of lateral ankle instability with laxity.
## 1 Introduction
Although the GO materials show great adsorption abilities, insufficient research focus on the adsorption of these chemical agents. In part, most studies applied the GO materials to the hydrolysis products or the simulant to study the adsorption due to the difficulty of acquiring these chemical agents. However, it is still particularly important to investigate the adsorption of actual and representative chemical agents. Furthermore, in consideration of the highly toxic and lethal properties, the major point for the adsorbing material should be the adsorption rate. In this study, Magnetic Graphene Oxide Nanoplatelet Composites (MGNCs) were synthesized by physically blending GO and Fe\({}_{3}\)O\({}_{4}\) and were successfully employed as adsorbents for L, VX, GB, and GD. The adsorption rate was optimized by ad  
Figure 1: Structural formula of several typical chemical agents: (**a**) L; (**b**) VX; (**c**) GB; (**d**) GD. justing contact time, temperature, and adsorbent dosage. Notably, the results demonstrated that chemical agents could be effectively adsorbed within 20 min. Furthermore, the adsorption kinetics and mechanisms were investigated in detail. The results indicated that the materials prepared in the research obtained good adsorption properties and showed great potential for the removal of chemical agents. The excellent adsorption properties provided the potential to apply the materials in special aqueous purification devices for adsorbing chemical agents. Moreover, we also provide recommendations on the application prospects in the field of protection suits or gas masks. In addition, due to the magnetic characteristics, the adsorbed material could be easily separated compared to other adsorption materials, which offers the potential for absorbing chemical agents in exposed environments.
# A Reliable Scheme for Synchronizing Multimedia Data Streams under Multicasting Environment
## 4 Proposed Solution
### Proposed Design Requirements
#### 4.2.5 The Calculation of Playout Time at Sender Includes Two Parameters  
* System Time (Send time of SR packet)--(\(t_{sr}\)).
* Playout-delay offset (\(d_{\mathit{off}}\)).