esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments and Results
### Experimental Setup
#### 4.1.3 Episode Definition  
In the experiments, three speakers stood casually in the room and had a conversation. For each episode, one of the speakers uttering the keywords was treated as the target speaker. The other two speakers were presented as interfering sound sources. The sound of a television program was considered as the background noise and its level was about 55 dB measured 1.5 m away from the television. All the sound sources mentioned above can be considered as far-field signals introduced in [40]. The starting position of the robot  
Figure 4: (**a**) The experimental platform. (**b**) The sensor configuration. The RGB-D camera is mounted on the head of the robot which is 1 m above the ground. The omnidirectional microphone is placed on top of the camera and the 4-channel microphone array is installed 0.1 m above the camera.  
Figure 3: Room impulse response measurement. A 4-channel microphone array, indicated by the red rectangle, was positioned in the center of the room. A loudspeaker marked by the blue rectangle was placed at positions indicated by the yellow circle with a 1 m radius around the microphone array. The initial position of the loudspeaker was marked as 0\({}^{\circ}\) and measurements were taken in a counter-clockwise direction, at 10\({}^{\circ}\) intervals, from the positions marked by the green points.  
was a random position in the room and the starting orientation of the robot was a random direction with the target speaker out of the FOV of the camera. An episode was considered successful if the robot was able to stop within 1.5 m of the speaker who spoke the keywords and keep the camera facing this speaker. As an example, a specific configuration of an episode in the experiments is presented in Figure 5.
# A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor
## 2 Determination of the Optimal Scaling Factor Values
### Optimal Scaling Factor for Different Irradiance Levels  
In this study, the optimal scaling factors for different irradiance levels are obtained via intensive simulations. To fairly evaluate and compare the acquired results of different scaling factor values, tracking energy loss (E\({}_{\text{loss}}\)) is utilized as a performance index in this study. Tracking energy loss is adopted because it can simultaneously take the tracking time and steady-state tracking accuracy into account. Figure 2 shows a typical tracking response of one MPP tracking curve under certain irradiance level and panel temperature. The tracking energy  
irradiance level changes, two additional perturbation steps will be performed and the state estimation will be used again to estimate the new irradiance level and calculate the new optimal scaling factor accordingly. The proposed method has advantages such as simple operation, fast tracking, and zero steady-state oscillation under any circumstances.
# Research on Permanent Magnet Synchronous Motor Control System Based on Adaptive Kalman Filter
## 3 Simulation Results and Discussions
### Experiment of PMSM Control System Based on PAEKF  
This section gives the experimental results of the PMSM control system based on PAEKF. As shown in Figure 8, the experiment uses STM32F446 chip and DRV8301 three-phase gate driver as the core hardware platform to drive the 57 BL55806 series motor. The parameters of the motor are as shown in Table 3. The motor in Figure 8a is in a state of stopping, and the motor in Figure 8b is rotating. In Figure 9, Curves A and B represent the experimental results of the PMSM control system based on EKF and PAEKF when Q = diag(0.1,0.1,50,0.1), respectively. It can be seen from Figure 9 that when the accurate process noise covariance Q cannot be obtained, the PMSM control system based on PAEKF and EKF can achieve the convergence of estimation speed, but the convergence time of EKF algorithm is slower than that of PAEKF algorithm. In addition, the estimation speed of EKF algorithm fluctuates greatly when it converges, which is inferior to PAEKF algorithm in stability and accuracy.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Values** \\ \hline Voltage \(V_{dc}\) (V) & 24 \\ Rated speed (r/min) & 3000 \\ Inductance L (mH) & 1.4 \\ Resistance R (\(\Omega\)) & 0.59 \\ viscous damping F (N\(\cdot\)m\(\cdot\)s) & 6.12 \(\times\) 10\({}^{-6}\) \\ Pole pairs p & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The 57 BL5506 series PMSM parameters.  
Figure 7: (a) Speed estimation based on the method in [22]. (b) The difference between the actual speed and the speed estimated is based on the method in [22].  
As shown in Figure 10, curves A and B are experimental results and simulation results, respectively. Curve C is the set speed reference value. The experimental results show that the PMSM control system based on PAEKF can well estimate the real-time speed of the motor, effectively reduce the steady-state jitter, and improve the filtering adaptability and calculation accuracy. Moreover, it can be proved that the theoretical derivation of PMSM vector control based on PAEKF is efficient.  
Figure 8: PMSM experiment platform. (**a**) the motor is in a state of stop. (**b**) the motor is in a state of rotation.  
Figure 10: (**a**) Experimental results of PMSM control system based on PAEKF; (**b**) experimental results of PMSM control system based on EKF.  
Figure 9: Experimental results of PMSM control system based on EKF and PAEKF.
fabricated 3D-graphene aerogels--mesoporous silica materials--that exhibited a high absorption capacity for phenols because of their high surface area (1000.80 m\({}^{2}\) g\({}^{-1}\)), narrow mesopore size distribution (1.87 nm), and porous structures [27]. [PERSON] et al. prepared sandwich-like multilayer silica-Fe\({}_{3}\)O\({}_{4}\)-GO composites with mesopores and a large surface area for the removal of methylene blue from water [28]. [PERSON] et al. synthesized Si/rGO nanosheet composites with a large surface area by a sol-gel process for the high-efficiency removal of methylene blue and thionine from water [29]. Thus, it was found that a high surface area, narrow mesopore distribution, and multilayer structure could improve the removal efficiency of contaminants in water. However, materials such as the silicon source tetraethyl orthosilicate (TEOS) greatly increase the cost of industrial applications. Therefore, finding a low-cost preparation method is a key issue for industrial production. To find rGO/SiO\({}_{2}\) composites that were low cost, could be prepared in large quantities, and had high adsorption capacity for removing water pollutants, we designed the following experiments. Herein, cationic neutral red (NR) dye (pH = 5) was selected as the model compound in order to evaluate the adsorption ability of rGO/SiO\({}_{2}\) nanocomposites from an aqueous solution. The composites were synthesized by the post synthesis treatment illustrated in Scheme 1. By controlling the ratio of rGO and SiO\({}_{2}\), the surface properties could be adjusted to improve the adsorption quantity of NR. The parameters were evaluated for NR removal, with a focus on the ratio of GO and SiO\({}_{2}\), concentration of NR, adsorption quantity, equilibrium times, pseudo-first-order kinetic parameters, and pseudo-second-order kinetic parameters. **Scheme 1. ** Illustration showing the formation process of the rGO/SiO\({}_{2}\) composites as a functional adsorbent for the removal of neutral red (NR).
# Traits and Transports: The Effects of Personality on the Choice of Urban Transport Modes
## 3 Previous Research  
### Personality and Choice of Modes of Transport  
Regarding the Environmental personality, previous research has found that a high degree of Environmental personality increases the likelihood of choosing an environmentally friendly mode, for instance bicycling instead of public transport and public transport instead of car [22].  
Previous research regarding the Big Five personality traits and choice of mode of transport is very limited. To the best of our knowledge there are only two studies that investigate the Big Five personality traits in relation to car driving and use of public transportation. The present study seems to be the first study to report results from the Big Five personality traits in relation to bicycling.  
A nationally representative study of the Swedish population reports that car driving is influenced by a low degree of Openness, a high degree of Extraversion and a low degree of Neuroticism [23]. The same study reported that use of public transportation is influenced by a high degree of Openness and Agreeableness, and a low degree of Conscientiousness and Extraversion [23]. In contrast, a study on the Big Five personality traits and use of public transportation in Tehran (Iran) reports that use of public transportation is positively related to Extraversion and negatively related to Neuroticism [1]. The different results can be explained by different samples. The first study represents the Swedish population based on choice of modes of transport in everyday life [23]. The respondents in the second study are departure passengers waiting at the check-in lounge, Imam Khomeini International Airport in Tehran, Iran. The second study focuses on public transportation to the airport [1].  
The different results can also be explained by cultural differences. Different societies have carried out different investments regarding modes of transport and transport options also reflect the society's culture, economy, politics, technology, etc. [24; 25].
## 1 Introduction
### Motivation and Contributions  
Image captioning is essential, and many reasons motivate researchers to delve into this field, such as wanting to help visually impaired individuals by creating a product that helps people with visual impairments move around the world by converting the scene in front of them into descriptive text and then converting this text into an audible sound. It can be used in closed-circuit television cameras (CCTV cameras) so that relative descriptions are provided along with viewing the scene so an alert can be raised if there is malicious activity. Also, it can be used in self-driving cars by providing linguistic explanations of the scene around the car to reduce the psychological strain on passengers and avoid accidents. Many surveys focus on collecting, presenting, and analyzing different methodologies for image captioning. Similarly, we discuss how to generate a human-like description of an image to provide the interested reader with the latest developments in image captioning. Due to the development we have seen in performance using the encoder-decoder architecture, we  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Ref.** & **Year** & **Visual Model** & **Language Model** & **Loss** & **Dataset** & **Metrics** & **Languages Coverd** & **Conventional/Systematic** \\ \hline
[27] & 2019 & ✓ & ✓ & ✓ & ✓ & One & Conventional \\
[22] & 2019 & ✓ & ✓ & ✓ & ✓ & One & Systematic \\
[32] & 2019 & ✓ & ✓ & ✓ & ✓ & One & Conventional \\
[23] & 2020 & ✓ & ✓ & ✓ & ✓ & One & Systematic \\
[34] & 2020 & ✓ & ✓ & ✓ & ✓ & One & Conventional \\  
have limited our focus to the encoder-decoder architecture of English image captioning and how to use these techniques in Arabic image captioning. This survey follows a systematic search procedure to gather methods based on the encoder-decoder architecture and other relevant information. Our contributions are  
1. A systematic literature review is performed on encoder-decoder-based image captioning models from 2015 until 2023.
2. We also include Arabic image captioning research in the systematic procedure.
3. We discuss how the English captioning models can be adapted for image captioning to support the Arabic language.
## 6 Conclusions  
In this paper, a new smart outage management system denoted by \(SOMS_{DGs}^{EDRPs}\) is provided. The EDRPs and the DGs are considered in the proposed framework to optimize the operation of the outage management system. In the first stage of the proposed framework, the clustering method is used to cluster the outages. In the second stage, the multi-objective function is provided to optimize the RRC time, the outage cost and the EDRP cost. Two case studies were used to show the efficiency of the proposed framework: the IEEE 34 bus test system and an actual Iranian 66 bus power distribution feeder. The results show that the outage clustering method is an effective solution for clustering the outage into each depot. Furthermore, the processing time is a very important parameter in a crisis time, and also, the outage clustering in the first stage causes a decrease in the optimization time. Additionally, the results show that the optimal operation of the crews (the output of the model) decreases the outage cost and increases the served load in each time interval. Furthermore, it can be concluded that the EDRP is a very effective program for decreasing the outage cost of the distribution system. Additionally, the EDRP is a useful problem for increasing the served load, and consequently, social welfare is increased. One of the important outputs of the proposed framework is the priority list of the outages for repair by crews. The priority of the outages is dependent on various factors such as the distance, needed resources and public hazard. Furthermore, the results show that the location of the outage is a very important feature for prioritization by the proposed framework to clear. In this regard, the importance of the outage location, which causes the highest impact on customers, is more than that of others. Additionally, the results show that the location of the load point demand response contracts plays an important role in the proposed outage management system. Therefore, EDRP contract allocation based on the probability of a crisis occurring in a location is an interesting topic for future research in the smart outage management system research field.  
Conceptualization, S.D., R.D. and H.R.S.; Methodology, S.D.; Supervision, R.D. and H.R.S.; Validation, R.D.; Visualization, S.D.; Writing--original draft, S.D.; Writing--review & editing, R.D. and H.R.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 14: The effect of the EDRP on the served load in the 66 bus case.
## 3 Verification of Structural Safety of Non-Circular Gears
### Analysis Results  
The angular velocity ratio during one revolution of the driving gear was extracted through 'DAFUL' analysis, based on the time points when the velocity was sufficiently developed.  
The results are shown in Figure 17, and it can be seen that analysis results of angular velocity ratio are identical to the graph of angular velocity ratio obtained by theoretical calculations.  
Figure 16: Contact condition setting for non-circular gears.  
Figure 14: Boundary condition setting for dynamic analysis.  
Figure 15: Setting the rotational velocity of the driving gear and the rotational load of the driven gear.  
In order to verify the structural safety, Von-Mises stresses of driving and driven gears were extracted. Figure 18 show the stress distribution of each section during one revolution of the driving gear and driven gear, respectively. In the sections of corresponding to circular motion with a constant speed, Von-Mises stress is relatively constant, but in the sections where the angular velocity of the driven gear increases or decreases, stress is higher than in the constant velocity section.  
Figure 17: The angular velocity result through dynamic analysis.  
Figure 18: Stress distributions during one revolution of the driving and driven gears. (**a**) Driving gear and (**b**) Driven gear.  
Table 4 showed the maximum equivalent stress at each section of the driving and driven gears considering safety factor 1.2, and the maximum stress in Section (8) was 411.45 MPa, which was lower than the yield strength (SUS440C) as shown in Figure 19, i.e., 445 MPa so that structural evaluation of non-circular gear was considered to be safe.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Range (\({}^{\circ}\))** & \multicolumn{2}{c}{**Max. Stress (MPa)**} \\ \cline{3-4}  & & **Driving Gear** & **Driven Gear** \\ \hline Section 1 & 0–67.5 & 375.36 & 201.99 \\ Section 2 & 67.5–90 & 372.70 & 309.43 \\ Section 3 & 90–112.5 & 256.76 & 284.77 \\ Section 4 & 112.5–141 & 218.25 & 271.27 \\ Section 5 & 141–173.5 & 399.89 & 360.14 \\ Section 6 & 173.5–202.5 & 193.58 & 238.99 \\ Section 7 & 202.5–337.5 & 399.22 & 285.49 \\ Section 8 & 337.5–360 & 387.65 & 411.45 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Max. equivalent stress result for each section.  
Figure 19: The simulation results of structural evaluation of non-circular gears. (**a**) The maximum Von-Mises stress in each section. (**b**) The maximum Von-Mises stress at the Section (8).
## 5 Conclusions  
The present work deals with the wave dispersion in longitudinally FG CNTs-reinforced composite beams lying on an elastic medium, modeled as a Winkler-Pasternak foundation. The graduation of CNT fibers is here modeled by means of a power-law function, defining a variation from linear to parabolic distributions. The equations of motion of the composite beams rely on a classic Euler-Bernoulli beam theory and Hamiltonian principle, whose theoretical results can be summarized as follows:  
* The phase velocity and wave frequency of the composite beam can be improved by increasing the volume fraction of CNT fibers and the power term \(k\).
* The Winkler-Pasternak foundation affects significantly the wave propagation response of composite beam structures. The enhancement of Winkler and Pasternak coefficients has a beneficial effect on the phase velocity and wave frequency, whose increased values can be related to an improved overall stiffness of the structure. The wave frequency and phase velocity reduce significantly by selecting higher values of coefficient \(\alpha\) within the power law distribution function.
* The CNTs volume fraction at both sides of the beam, has a meaningful influence on the wave propagation. The volume fraction at the left side of the beam (\(V_{\rm CNT-L}\)) and the \(V_{\rm CNT-R}/V_{\rm CNT-L}\) ratio has a hardening effect on the structure, with an improved response in terms of wave frequency and phase velocity.  
Conceptualization, R.D. and F.T.; Data curation, R.D. and F.T.; Formal analysis, A.S., A.T., R.D. and F.T.; Investigation, A.S., A.T., R.D. and F.T.; Methodology, R.D. and F.T.; Software, F.T.; Supervision, R.D. and F.T.; Validation, R.D. and F.T.; Writing--Original draft, A.S. and A.T.; Writing--Review & editing, R.D. and F.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
Figure 12: Phase velocity vs. \(V_{\rm CNT-L}\) for different \(k\).
## 2 Materials and Methods
### Life Cycle Impacts Assessment  
The methodology used for the evaluation of environmental impacts was ReCiPe 1.07. Six midpoint indicators were chosen as characterization factors, aiming to provide more accurate results. These factors were the following: climate change (CC), fossil depletion (FD), human toxicity (HT), ozone depletion (OD), particulate matter formation (PMF), and terrestrial acidification (TA).
# Malicious URL Detection Model Based on Bidirectional Gated Recurrent Unit and Attention Mechanism
## 4 Experimental Results and Analysis
### Experimental Comparison
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Loss** & **Accuracy** & **F1\_Score** & **Precision** & **Recall** \\ \hline MLP & 0.1041 & 0.9711 & 0.9616 & 0.9778 & 0.9458 \\ Att-BiLSTM & 0.0922 & 0.9733 & 0.9643 & 0.9809 & 0.9482 \\ Att-BiGRU & 0.0859 & 0.9776 & 0.9687 & 0.9833 & 0.9544 \\ DA-BiLSTM & 0.094 & 0.9740 & 0.9618 & 0.9790 & 0.9453 \\
**DA-BiGRU** & **0.0814** & **0.9792** & **0.9691** & **0.9834** & **0.9553** \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of results of different models on test sets. model is lower than other models in all parameters. This may be related to the MLP model itself, without taking into account the sequence of URLs and some deeper key information, so the classification effect is not good. By longitudinal comparison of the Att-BiLSTM, Att-BiGRU, DA-BiLSTM, and DA-BiGRU models, the model based on BiGRU is better than that based on BiLSTM, which shows that GRU is more suitable for URLs with strong sequences. Through the comparison between Att-BiGRU and DA-BiGRU, it is found that Att-BiGRU with dropout mechanism improves the fitting ability of the model, extracts useful features more accurately, and obtains the sequence information of the whole URLs, thereby improving the classification accuracy.
# Rapid Estimation of Moisture Content in Unpeeled Potato Tubers Using Hyperspectral Imaging
## 2 Materials and Methods
### Partial Least Squares Regression  
Partial least squares regression (PLSR) was selected as a regression technique because of its high performance and the fact that it has been widely used for the analysis of HSI data from numerous crops [42; 43; 44; 45; 46; 47; 48]. PLSR enables us to investigate the relationship between multiple dependent and independent variables. In spectral data analysis, it has proven to be a dependable, resilient, and accurate method [47; 48; 49].  
Based on the proposed PLSR model, the moisture content of the unpeeled potatoes was predicted from the respective HSI spectra (204 wavelengths). Prior to model creation, the dataset was randomly partitioned into training (80%) and test (20%) sets. The 'train test split' function from the sklearn.model selection python package was used to split the data into training and testing sets, with a value of 20 for the 'random state' parameter in the train test split function. To gain the optimum performance and avoid overfitting, the full cross-validation (leave-one-out) method was employed to calculate the number of latent variables (LVs) [50; 51; 52]. For determining the optimum number of LVs, initially, the root mean square error (RMSE) was calculated from the cross-validation set, and then the optimal number was selected from the minimum RMSE.