esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Monitoring Methods
### Sub-Pixel Algorithm for Calculating Coordinates of Center of Ring Mark
#### 3.2.2 Sub-Pixel Corner Detection
Because the stability of the Harris corner detection algorithm is related to \(k\), and \(k\) is an empirical value, it is difficult to set the optimal value. The Shi-Tomasi method is based on the Harris algorithm. The stability of the corner is actually related to the smaller eigenvalue of the matrix \(M\), and the smaller eigenvalue is used as the corner response function \(R\)[24]. The form of the corner response function \(R\) of the Shi-Tomasi method is given as follows:  
\[R=\text{min}(\lambda_{1},\lambda_{2}) \tag{9}\]If \(R\) is larger than the set threshold, the corner point is detected. The corner points extracted by the above method can only reach the pixel level, and the corner coordinates are integers. To obtain more accurate corner position coordinates, the relevant algorithm can be used to make the corner coordinates reach the sub-pixel level. In the corner detection algorithm with sub-pixel accuracy, the vector from the sub-pixel corner point to the surrounding pixel point must be perpendicular to the gray gradient of the image, and the coordinate value of the sub-pixel accuracy is obtained by the iterative method of minimizing the error function. Therefore, the cornerSubPix() function is used in OpenCV to obtain sub-pixel corner values. OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning library ([[https://opencv.org](https://opencv.org)]([https://opencv.org](https://opencv.org))). Figure 5 shows the detection results of the sub-pixel method for ring marks. The red dots in the figure represent the detected subpixel corners.
## 2 Experiment I: Directivity-Controlled Auditory Distance in Auralized Rooms
### Influence of the Signal  
The influence of the signal \(S_{1\ldots 3}\) on the auditory distance of the design \(A\) in \(R_{1}\) is evaluated by supplementing responses of set 13 with re-mapped responses of set 1 to 3 using Equation (2).  
Figure 6 shows the median values and corresponding 95% confidence intervals of the auditory distance for the room \(R_{1}\) and beampattern design \(A\). Along the indices, the distance impression exhibits a monotonic increase for all signals until \(A_{5}\). The ANOVA of neighboring values reveals beampatterns \(A_{2\ldots 5}\) as a significant factor (\(p<0.03\)). By contrast, beampatterns \(A_{5\ldots 7}\) do not yield a significant change (\(p\geq 0.45\)), despite continuously reducing the D/R ratio. This seems to comply with a general tendency to auditorily underestimate the physical distance [2].  
A signal-wise comparison of the obtained data reveals the significantly smaller auditory distance for \(S_{2}\) than for \(S_{1}\) or \(S_{3}\) (\(p_{5_{2}/S_{1}}\ll 0.01\), \(p_{5_{2}/S_{3}}=0.02\)). This seems to comply with the finding in [20; 21] that the auditory distance of broadband signals decreases with the relative amount of high-frequency energy.
# Smart Embedded System for Skin Cancer Classification
## 5 Conclusions and Future Work  
This paper describes the design of a low-cost system for skin cancer classification implemented in an FPGA. The deep learning model considers two models with different accuracies and complexities. The more accurate model only runs in the case of a low confident classification of the less complex model.  
The models were quantized and mapped to the FPGA using a Vitis-AI design flow. The system achieves 13.5 FPS with an accuracy of 87% with minimal resources, and 6.2 FPS with an accuracy of 88%. The proposed solution is accurate and can run in low-density devices with an acceptable throughput. It helps in achieving solutions with the same accuracy as highly accurate models with a higher throughput or a smaller device.  
Only networks within the ResNet family were considered in this work. However, other models, like MobileNet, can be considered. The dual-model technique is now being applied to an object detection problem.  
Conceptualization, P.F.D. and M.P.V.; methodology, P.F.D. and M.P.V.; software, P.F.D.; validation, P.F.D. and M.P.V.; formal analysis, P.F.D.; investigation, P.F.D. and M.P.V.; resources, P.F.D. and M.P.V.; data curation, P.F.D.; writing--original draft preparation, P.F.D.; writing--review and editing, M.P.V.; visualization, P.F.D. and M.P.V.; supervision, M.P.V.; project administration, M.P.V.; funding acquisition, M.P.V. All authors have read and agreed to the published version of the manuscript.  
This work was supported by national funds through Fundacao para a Ciencia e a Tecnologia (FCT) with reference UIDB/50021/2020 and IPL/2022/e52 ST_ISEL through Instituto Politecnico de Lisboa.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Param (\(\times 10^{6}\))** & **Performance (FPS)** & **Energy/Frame (j)** \\ \hline
**Model** & & **Acc = 88\%** & **Acc = 87\%** & **Acc = 87\%** \\ \hline ResNet50 & 23.5 & — & 3.1 & 1.61 \\ ResNet18-F-F-F & 34.7 & 4.6 & 5.0 & 1.00 \\ ResNet18-F-F-S & 34.7 & — & 10.8 & 0.46 \\ ResNet18-F-F-VS & 34.7 & — & 8.8 & 0.57 \\ ResNet18-F-S-F & 26.3 & — & 7.6 & 0.66 \\ ResNet18-F-S-S & 26.3 & — & 9.8 & 0.51 \\ ResNet18-F-S-VS & 26.3 & — & 9.4 & 0.53 \\ ResNet18-F-VS-F & 24.2 & — & 10.3 & 0.49 \\ ResNet18-F-VS-S & 24.2 & — & 10.1 & 0.50 \\ ResNet18-F-VS-VS & 24.2 & — & 6.8 & 0.74 \\ ResNet18-S-F-F & 28.4 & 6.2 & 8.1 & 0.62 \\ ResNet18-S-F-S & 28.4 & — & 12.7 & 0.39 \\ ResNet18-S-F-VS & 28.4 & — & 13.5 & 0.37 \\ ResNet18-S-S-F & 24.8 & — & 10.2 & 0.49 \\ ResNet18-S-S-S & 24.8 & — & 10.3 & 0.49 \\ ResNet18-S-S-VS & 24.8 & — & 7.9 & 0.63 \\ ResNet18-S-VS-F & 23.8 & — & 10.8 & 0.46 \\ ResNet18-S-VS-S & 23.8 & — & 13.1 & 0.38 \\ ResNet18-S-VS-VS & 23.8 & — & 8.2 & 0.61 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Accuracy and performance of dual models running in the FPGA.
## 3 VRDeepSafety Simulation Environment
### V2X Communication Integration
#### 3.7.2 Protocol Specification  
To understand V2X communication, it is essential to explore the two key protocols used. IEEE 802.11p, also known as Wireless Access in Vehicular Environments (WAVE), operates in the 5.9 GHz band and is designed for low-latency, short-range (up to 1000 m) data exchange. It is ideal for urgent alerts. IEEE 802.11p can work independently of network infrastructure but degrades in crowded environments due to interference. In contrast, C-V2X, developed by the 3 rd Generation Partnership Project (3 GPP), uses 4G LTE and 5G to support both short- and long-range communication. C-V2X operates in direct communication (PC5) for V2V and V2I without relying on cellular towers and network-assisted communication (Uu) using cellular infrastructure. While C-V2X is more reliable with extended coverage, it has higher latency, particularly during network congestion.
# Towards Automatic License Plate Recognition in Challenging Conditions
## 5 Conclusions  
Accurate detection and recognition of vehicle license plates in natural scene images is an important task to be performed by machine learning algorithms. Nowadays, it is an integral part of modern intelligent traffic control systems. However, this task is quite challenging due to various factors, for instance, the non-uniform patterns of the plates, variations in view angles, such as blurriness, and the occlusions. With such factors, it is always difficult for a single algorithm to handle the aforedescribed issues. This paper discussed methods to detect and identify license plates that appear in an image. The proposed method is composed of three distinct but interconnected steps: (i) vehicle detection, (ii) license plate detection, and (iii) license plate recognition. To locate the vehicles, a fine-tuned version of the Faster RCNN was used, while the license plate area was located through our own developed plate localization module. Finally, the recognition task is achieved using the deep learning network. Simulations were performed on three databases, which are the PKU, the AOLP, and the CCPD license plate dataset. Our proposed method achieves competitive performance and yields 99%, 96.0231%, and 98.7000% recognition rates on the aforesaid datasets. We are optimistic that our findings are promising and will be applicable to a variety of real-world applications, including surveillance and the monitoring of suspicious vehicles.  
In the future, the proposed method could be modified to handle extreme blurriness. Similarly, the proposed method could also be improved to handle occlusion. Moreover, the developed algorithm could also be made intelligent by being trained in parallel over various time intervals.  
Conceptualization, F.S. and Z.M.; methodology, F.S.; software, F.S., Y.A.S., K.K., M.S., U.K. and Z.M.; validation, F.S.; formal analysis, F.S., Y.A.S., K.K., M.S., U.K. and Z.M.; investigation, F.S. and Z.M.; resources, F.S., Y.A.S., K.K., M.S., U.K. and Z.M.; data curation, F.S.; writing--original draft preparation, F.S., Y.A.S., K.K., M.S., U.K. and Z.M.; writing--review and editing, F.S., Y.A.S., K.K., M.S., U.K. and Z.M.; visualization, F.S. and Z.M.; supervision, Z.M.; project administration, Z.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.
## 2 Materials and Methods
### Measurements  
During familiarization, LOP was measured and confirmed with a Doppler probe in supine position. For all experimental sessions, occlusion pressures were set at 0%, 40%, or 80% of each LOP of participants. The IMTP was performed with participants gripping a wire-linked bar at mid-thigh height (Figure 2), with cable length individually adjusted to ensure proper body alignment and eliminate vertical displacement during testing.  
Figure 1: Session protocol scheme.  
Figure 2: Wire-linked bar positioned to mid-thigh height.  
The FEMD recorded force and displacement data using a 12-bit load cell and a 2500 ppr encoder powered by a 2000 W motor. Data were sampled at 1000 Hz. The built-in MyoQuality(r) software (version 2.6.2) applied a uniform internal filtering algorithm before data export. Output was provided in both kilograms and Newtons, though all calculations were performed using SI units (N, N-s, N/s). Kilogram values were retained only for interpretability.  
Before each maximal IMTP, participants performed two submaximal familiarization trials (50% and 75% effort). Force data were exported in 10 ms intervals. Peak force (PF) and impulse (IP) were extracted as the maximum instantaneous and cumulative force, respectively. RFD was calculated across three intervals: 0-50 ms, 51-150 ms, and 151-250 ms. Force onset was defined as the first non-zero data point in the filtered force-time signal.
## Abstract  
Scleractinian corals predominantly reproduce by means of fragmentation; thus, experimental infliction of tissue lesions is the primary approach to investigate coral growth. However, most of the early investigations were performed from the field, sometimes in difficult conditions and inaccessible areas. In this study, clones of _P. damicornis_ produced by inducing tissue regeneration through a simple in vitro system were used to examine the effect of various monochromatic lights on the growth of its tissues and density of in situ symbiotic zooxanthellae using light microscopy. To induce coral regeneration, small apical colony fragments (c.a. = 8-10 cm) were excised, then fixed separately on a cover slip with a drop of silica gel inside a glass dish containing raw seawater. After 1-2 weeks, new tissue layers tended to extend towards the glass surfaces. Healthy clones were exposed independently to intermittent light treatment (14 h light: 10 h dark) every 48 h for 10 days at irradiance levels of 1.0, 1.5 and 2.0 W/m\({}^{2}\), respectively. The length of tissue extension and density of in situ zooxanthellae cells from light-treated and control samples were calculated by examining serial micrographs. Coral tissue growth and populations of zooxanthellae cells changed significantly depending on the coral light and intensity. Among monochromatic lights, blue rays (470 nm) further enhanced tissue regeneration by up to 159.7 \(\upmu\)m/day, for a 5.34% growth rate, and increased zooxanthellae density to 35.8 cell/\(\upmu\)m\({}^{2}\)/day or by 4.42%. In contrast, red 62 (620 nm), far red (737 nm) and UV-A (375 nm) radiation inhibited the proliferation rates of both host and symbiont cells. This study contributes knowledge to further understand coral reproducibility and its viability for clone production that could be utilized as a feasible source of explants for various coral examinations, transplantation, husbandry, biotechnology and microscale analyses.  
keywords: _Pocillopora damicornis_; in vitro regeneration; monochromatic lights; tissue extension; zooxanthellae density
## 3 Results and Discussion
### Adsorption Isotherm  
Figure 3a shows the Pb(II) adsorption isotherm at 25 \({}^{\circ}\)C. The adsorbing capacity was continually enhanced with increasing initial Pb(II) concentration over the studied range. In this study, [PERSON] and Freundlich isothermal models were applied to simulate the adsorbing isotherms; theoretically, the former is used to describe a monolayer adsorption process, whereas the latter is applied to depict a multilayer adsorption process [5]. The [PERSON] and Freundlich models are given in Equations (3) and (4), respectively.  
\[\frac{C_{e}}{q_{e}}=\frac{C_{e}}{q_{m}}+\frac{1}{bq_{m}} \tag{3}\]  
\[\text{lg}q_{e}=\text{lg}k+\frac{1}{n}\text{lg}e_{e} \tag{4}\]  
Herein, \(q_{m}\) (mg/g) represents the maximum adsorbing amount and \(b\) (L/mg) refers to the Langmuir isotherm constant, whereas \(k\) and \(n\) refer to the Freundlich isotherm constants. The simulated curves and parameters are presented in Figure 3b,c and Table 2. The correlation coefficient fitted by Langmuir model is more close to 1.0, indicating that Langmuir model is more suitable for describing its adsorbing equilibriums. In other words, the Pb(II) was adsorbed onto PEI-functionalized MNPs in the form of uniform monolayer. Besides, the maximum adsorbing capacity for PEI-functionalized Fe\({}_{3}\)O\({}_{4}\) MNPs at 25 \({}^{\circ}\)C was calculated to be 60.98 mg\(\cdot\)g\({}^{-1}\), higher than that of majority of Fe\({}_{3}\)O\({}_{4}\) MNPs synthesized by one-step approach [29]. Although frequently reported magnetic adsorbents, such as magnetic biochar [2,3], magnetic grapheme [23], and magnetic chitosan and alginate beads [1,26], exhibited much higher adsorption capacity, their extensive applications were restricted to some degree because  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**q\({}_{e,exp}\) (mg/g)**} & \multicolumn{3}{c}{**Pseudo First-Order Equation**} & \multicolumn{3}{c}{**Pseudo Second-Order Equation**} \\ \cline{2-7}  & **k\({}_{1}\) (l/min)** & **q\({}_{e}\) (mg/g)** & **R\({}^{2}\)** & **k\({}_{2}\) (g/(mg-min))** & **q\({}_{e}\) (mg/g)** & **R\({}^{2}\)** \\ \hline
**33.651** & 0.033 & 10.199 & 0.702 & 0.023 & 34.014 & 0.999 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Kinetic parameters of Pb(II) adsorption at 25 \({}^{\circ}\)C.  
Figure 2: Effect of solvothermal reaction time on the adsorbing capacity **(a)**, effect of adsorption time on adsorbing capacity **(b)**, and fitting of Pb(II) adsorption kinetics using pseudo first-order model **(c)** and pseudo second-order model **(d)**.  
of the relatively complicated synthetic procedures. As a result, the PEI-functionalized Fe\({}_{3}\)O\({}_{4}\) MNPs remained a class of prospective nanomaterials for Pb(II) sorption from water environment.
# Experimental Study on the Damage of Optical Materials by out of Band Composite Laser
## 1 Introduction
The damage effect of composite lasers is related to the overlap of pulse time domains, and the damaging effect of composite lasers is better than that of long-pulse lasers. [PERSON] [12], using 1053 nm pulsed and 1064 nm multiple compound lasers to study the irradiation effect of steel found that the surface reflection of steel decreased with the increase of pulsed laser frequency. The pre-irradiation of steel plates with a long pulse laser can increase its absorption rate for subsequent lasering. [PERSON] [13; 14] simulated the thermodynamic characteristics of the continuous-pulse composite laser irradiation of aluminum alloys. Through simulation, it was found that the composite laser could significantly increase the size of the molten pool and increase the center temperature of the irradiation spot. The longer the \"preheating\" time, the shorter the yield time of the material, the larger the plastic deformation, and the larger the yield range. According to the analysis of the above literature, it is known that the research on the laser irradiation effects of composite lasers is still in its infancy. Almost all reported studies have used low-energy in-band laser sources. The research targets have mostly been photoelectric sensors and metal structural parts. Composite laser damage studies on optical components have not been reported. For this paper, high-power laser damage experiments were performed on a common Ge-based and Si-based flat window to provide technical support for the design of high-power laser emission systems.
## 3 Results and Discussion
### Results of the Measurement of Brake Discs' Temperature during Repeated Braking 15 Times in a Row  
The impact of repeated braking on brake discs' temperature is shown in Figure 8. Black colour displays the value measured with low-priced brake discs, green colour represents the mid-priced brake discs and red colour corresponds to the high-priced ones. The solid line depicts the course of the values measured with brake discs with maximum thickness, and the broken line depicts the minimum thickness of brake discs.  
The brake discs' temperature during repeated braking 15 times in a row increased significantly depending on the brake discs. The differences were higher than 80 \({}^{\circ}\)C, which is higher than 65% in some measurements (Figure 8). Both the price and the characteristics of a brake disc have affected the temperature more than its thickness.  
The highest temperature was seen in the low-priced brake discs with a minimum thickness. The lowest temperature during repeated braking was seen in solid mid-priced brake discs, not high-priced ones with holes. The solid brake discs had lower temperatures during repeated braking than brake discs with holes, which was also the case during the measurements mentioned in the publications [100; 101; 102; 103]. The authors in publication [103] explained a higher temperature of the brake discs with holes by a smaller friction surface reduced by the area of holes. Thus, the holes in brake discs or their higher price do not guarantee a lower temperature. However, the temperature of high-priced brake discs was lower than the temperature of low-priced brake discs. Such a difference might have been caused by using different materials of brake discs and brake pads [104; 105].  
The thickness affected the temperature of high-priced brake discs less sharply than their price. The biggest differences were measured with mid-priced brake discs due to different thicknesses. The highest difference measured was 20 \({}^{\circ}\)C, which is an increase in temperature by 20% as a result of the reduced brake disc's thickness (Figure 8).  
Figure 8: Brake discs’ temperature during repeated braking 15 times in a row.  
The temperature of brake discs spread further to other vehicle parts, as is also evident from Figure 9.
# Diagnosing Phosphorus Limitation in Subtropical Forests in China under Climate Warming
## 3 Results
### Spatial Pattern of Additional Accumulated Phosphorus Demand  
The spatial distribution of AAPD for the period of 1951-2010 for S\({}_{1}\) is similar as that for S\({}_{2}\), but differs from S\({}_{2}\) in values. The AAPD are between 0.064-0.3 gC\(\cdot\)m\({}^{-2}\) for S\({}_{1}\) and between 0.005-0.064 gC\(\cdot\)m\({}^{-2}\) for S\({}_{2}\) (Figure 4). The higher values mainly distributed in central subtropical China, including northeastern and southwestern Sichuan, and northwestern Yunnan, with values between 0.25 and 0.30 gC\(\cdot\)m\({}^{-2}\) for S\({}_{1}\) and 0.016 and 0.064 gC\(\cdot\)m\({}^{-2}\) for S\({}_{2}\).  
Figure 3: Forest NPP changes during 1950–2010, averaged over: (**a**) evergreen broad-leaved forest (EBF), (**b**) evergreen needle-leaved forest (ENF) and (**c**) deciduous broad-leaved forest (DBF).  
Figure 5 compares the AAPD for the first (1951-1980) and the latter (1981-2010) 30 years for S\({}_{1}\) and S\({}_{2}\). For both S\({}_{1}\) and S\({}_{2}\), the AAPD in the latter 30 years was mostly higher than that in the first 30 years and the higher AAPD values (greater than 0.128 gC\(\cdot\)m\({}^{-2}\) for S\({}_{1}\) and greater than 0.016 gC\(\cdot\)m\({}^{-2}\) for S\({}_{2}\)) sporadically distributed in the western subtropical China in the first 30 years, but occupied large central and eastern subtropical regions in the latter 30 years.  
Figure 4: Spatial distribution of additional accumulated phosphorus demand (AAPD) for the period of 1951–2010 for: (**a**) S\({}_{1}\) and (**b**) S\({}_{2}\). S\({}_{1}\) and S\({}_{2}\) are the scenarios for the low and high mineralization rates, respectively.  
Figure 5: Additional accumulated phosphorus demand (AAPD) in the period of: (**a**) 1951–1980 for S\({}_{1}\); (**b**) 1981–2010 for S\({}_{1}\); (**c**) 1951–1980 for S\({}_{2}\); and (**d**) 1981–2010 for S\({}_{2}\). S\({}_{1}\) and S\({}_{2}\) are the scenarios for the low and high mineralization rates, respectively.  
We take S1 as an example to illustrate the changes of the spatial pattern of AAPD. For the first 30 years, the AAPD was below 0.032 gC\(\cdot\)m\({}^{-2}\) in 16% of the total forest area, and was in the range of 0.032-0.064 gC\(\cdot\)m\({}^{-2}\) and 0.064-0.256 gC\(\cdot\)m\({}^{-2}\) in 47% and 37% of the total forest area, respectively. However, for the latter 30 years, only 1% of the total forest area was covered by AAPD below 0.032 gC\(\cdot\)m\({}^{-2}\), while 18% and 80% of the total forest areas were covered by AAPD in the range of 0.032-0.064 gC\(\cdot\)m\({}^{-2}\) and 0.064-0.256 gC\(\cdot\)m\({}^{-2}\), respectively.