esa-sceva/satcom-chunk-collection huggingface dataset:
# A Vision-Based Method for Simultaneous Instance Segmentation and Localization of Indoor Objects
## 4 Experiments Results and Discussion
### Location Results and Analysis
#### 4.4.2 Test of Dynamic Positioning Accuracy  
The tester traverses a rectangular area within the camera's field of view, and the blue dot represents their movement trajectory as depicted in Figure 10.  
The positioning error calculation method is the same as that described in the previous section. The Cumulative Distribution graph of dynamic positioning error is presented in Figure 11, revealing that 65% of the positioning results exhibit an error below 0.2 m, while 85% demonstrate an error less than 0.3 m. Furthermore, the maximum positioning error is below 0.8 m.  
Figure 11: Cumulative distribution graph of the dynamic positioning error.  
Figure 9: Cumulative distribution graph of the static positioning error.  
The primary causes for the high positioning error are attributed to both instance segmentation and feature matching inaccuracies. Based on our experimental findings, the maximum error observed is less than 0.8 m. This discrepancy can be primarily attributed to challenges in accurately segmenting specific targets due to their similarity with the background, as well as discrepancies between calculated individual features and the actual target location.
# Intelligent Detection of Rebar Size and Position Using Improved DeeplabV3+
## 2 Methodology
### Improved DeeplabV3+  
Based on rebar feature information and segmentation detail information, DeeplabV3+ was improved, as shown in Figure 2.  
1. The detection of rebars was the target of present study. To reduce the complexity of original DeeplabV3+ model, ResNet50 was selected as the backbone extraction network;
2. According to the feature information and distribution pattern of the rebar dataset, an efficient attention module was added to the backbone network to optimize the feature extraction pattern of the network, as well as to deepen the sensitivity of the network to identify rebar. Thus, the redundant operations of the network to extract non-object features could be avoided;
3. To solve the problem of incomplete edge information and loss of detailed information in the segmentation effect of the original DeeplabV3+ model, the convolutional dilation rate and convolutional density of the cavity convolution in the ASPP module were changed from 6, 12, and 18 to 3, 6, and 9, so there was no cavity loss when performing scale fusion.  
Figure 2: Structure of improved DeeplabV3+.
## 3 Results and Discussion
### Thermal Transmittance of the Test FaCdes
#### A comparison of the two methods  
Comparing the thermal transmittance of the two facades before and after renovation, there is a clear difference in both cases (see Figure 14). Looking at the calculated U-values based on material properties, there is a reduction of 43%. The U-values based on energy use data were lower in both cases than the calculated U-values. The reduction in U-values between facades A and B based on energy use data was 33% (see Table 5).  
The U-values based on actual energy use data during the heating period were lower than what was expected from their material properties.  
This was a result from the first heating season (the first winter). There was still some excess moisture in the walls from the building process. The second heating season might have given a better thermal performance for both facades as they were allowed to dry further during the summer, most likely leading to better insulating properties.
# Research on Ecological Lawn Regulation and Storage System in Flight Area Based on Sponge Airport
## 4 Simulation Analysis of Design Results
### Simulation Analysis of Runoff Control  
The simulation shows that under the precipitation scenarios with return periods of 5a, 10a, 20a, 30a, 50a and 100a, the runoff flow of the traditional airport flight area lawn is significantly greater than that of the ecological lawn regulation and storage system with different return periods, and the rainwater control rate ranges from 19.06% to 30.39%. With the addition of the ecological lawn regulation and storage system, the highest rainwater control rate is seen with the 5-year return period, reaching 79.79%. Although the rainwater control rate decreases with an increase in the return period, it still reaches 67.25% with the 100-year return period (Figure 5). The ecological lawn regulation and storage system has a significant and stable effect on runoff control in the airport flight area with different return periods.
# Dynamic Performance of a New-Type PSC I-girder for Railway Bridge Application
## 2 Dynamic Performance Evaluation of New Type of PSC I-girder Bridge
### Dynamic Performance Evaluation of New PSC I-girder Bridge
#### 2.3.2 Dynamic Stability Check  
This section analyzes the vertical acceleration (Figures 10a, 11a, 12a, 13a), vertical deflection (Figures 10b, 11b, 12b, 13b) and twist (Figures 10c, 11c, 12c, 13c) responses of the bridge deck obtained by moving load analysis. As a matter of fact, the largest vertical acceleration and deflection responses occur at mid-span. Besides, the maximum twist occurs at the position of the rails at spacing of 3 m in the longitudinal direction when the rails are distant by 1.5 m as suggested by the Railway Design Code. The governing response related to the vertical acceleration is seen to happen nearby the critical speed or the sub-critical speed corresponding to the first flexural mode. On the other hand, the maximum vertical acceleration in the 35 m-bridge under HEMU is observed at 390.0 km/h between the speed of 374.27 km/h corresponding to the first flexural mode and the speed of 409.16 km/h corresponding to the first torsional mode. This result seems to indicate superposition of the response due to the proximity of the flexural and torsional modes. Nevertheless, the vertical acceleration response in the analyzed bridges according to the speed of the considered trains satisfied the design limits. The vertical displacement response appears to be mostly governed by the freight train regardless of the span length of the bridge. Moreover, the response with respect to the speed per type of train is observed to be the largest at the critical speed or the sub-critical speed corresponding to the first flexural mode. Here also, the vertical displacement response in the analyzed bridges according to the speed of the considered trains satisfied the design limits. Furthermore, the twist response seems also to be mostly governed by the freight train regardless of the span length of the bridge and satisfied the design limits.  
Figure 8: Vibration modes for span length of 30 m: (**a**) first mode (torsion); (**b**) second mode (flexure).  
Figure 9: Vibration modes for span length of 35 m: (**a**) first mode (flexure); (**b**) second mode (torsion).  
Figure 11: Moving load analysis results for span length of 35 m: (**a**) vertical acceleration response; (**b**) vertical displacement response; and (**c**) twist response.  
Figure 12: Moving load analysis results for span length of 40 m: (**a**) vertical acceleration response; (**b**) vertical displacement response; and (**c**) twist response.  
Figure 10: Moving load analysis results for span length of 30 m: (**a**) vertical acceleration response; (**b**) vertical displacement response; and (**c**) twist response.
## 3 Types of Supplementary Dampers and Their Characteristics
### Viscous Dampers
#### 3.1.4 Types of Viscous Dampers  
Viscous dampers can be categorized into several types, each with unique characteristics:  
1. Linear viscous dampers: These dampers exhibit a linear force-velocity relationship, making them predictable and easy to model. They are suitable for a wide range of applications due to their consistent behavior across different loading conditions. A prominent example of this type of damper is evident in the cable-stayed Rion-Antirion bridge in Greece (Figure 4), which is situated in a region with significant seismic activity [53].
2. Nonlinear viscous dampers (Figure 5): These dampers exhibit a nonlinear force-velocity relationship, usually with an exponent \(\alpha\) < 1. This nonlinearity allows them to provide higher damping forces at low velocities while limiting forces at high velocities, making them particularly effective in scenarios with varying load intensities [54].
3. Bidirectional viscous dampers (Figure 6): These specialized dampers are capable of dissipating energy in two orthogonal directions. They are particularly useful in structures with complex motion patterns, where vibrations may occur in multiple planes simultaneously [55].  
Figure 4: Example of linear viscous damper [53].  
Figure 5: Example of nonlinear viscous damper [54].  
Figure 6: Example of bidirectional viscous damper [55].
## 3 Results and Discussion
### Effects of Injection Pressure  
#### 3.1.1 Combustion Characteristics  
Figure 2 reflects the performance of cylinder pressure (CP) and heat release rate (HRR) for different fuels at incremental injection pressures. The peaks of CP and HRR and their corresponding crank angles are summarized in Table 5. It can be observed for all fuels that the larger injection pressure increased the cylinder pressure peak. Compared with the injection pressure under 300 bar, the peak pressure of D100 increased by 5%, 8.5%, and 13.5% at 350, 400, and 450 bar, respectively, while that of P50D50 increased by 3.7%, 9.1%, and 12.6%. The trend of HRR was similar to that of CP, which HRRmax increased with the injection pressure. From the data in Figure 2 and Table 5, it can be seen that before reaching the peak, the injection pressure positively affected the rise rate of HRR, advanced the heat release of the fuel, and shortened the period required to reach the maximum value of HRR. This may be attributed to the fact that the fuel in the injector achieved higher kinetic energy under high pressure, thereby forming droplets with smaller diameters, which improved the fuel distribution in the cylinder [22]. A better atomization of the fuel is conducive to better mixing of the mixed gas in the pre-mixing stage and to a more adequate and earlier release of the heat contained, which is reflected in the higher CP and HRR [23; 24]. For different fuels, it can be found that the CPmax of D100 was always greater than that of P50D50. In addition to poor spray atomization due to the larger viscosity and density of P50D50, the large heating value of D100 was the key to a larger CP. In a word, the peak values of CP and HRR increased due to a higher premixed combustion phase resulting from a better atomization of the fuel at higher injection pressure.  
Ignition delay (ID) is mostly defined as the crank angle corresponding to the start of fuel injection to 10% of the combustion mass, which varies with injection pressure and fuel properties. As shown in Figure 3, a high injection pressure significantly shortened the ID. When the injection pressure varied from 300 bar to 400 bar, the ID was greatly shortened. When the injection pressure reached 450 bar, the ID was the shortest, especially for P50D50, whose ID was shortened by 33%. A high injection pressure often leads to spray droplet diameter, shorter split length, and wider dispersion, which minimizes local fuel accumulation [25]. Good atomization makes a mixture more uniform, thus reducing the ID [26]. A shorter ID means that the heat release starts earlier, which is consistent with the previous statement that the heat release of fuel advances with the increase in injection pressure. The ID of P50D50 was longer than that of D100 under the same conditions, which may be attributed to the fact that crude palm oil reduced the cetane number of the blend. A high injection pressure is conducive to a shorter ID.
## 5 Conclusions and Future Work  
This study presents QAAPA, a novel methodology facilitating real-time transmission of ship data via the Beidou Navigation System. The approach involves the real-time compression of sequential ship status data, achieving precision while adhering to predefined data ranges. QAAPA integrates quantization, attention-averaging-based predictive coding, and arithmetic coding algorithms to compress the data stream effectively. Experimental evaluation using real ship monitoring data showcases the efficacy of QAAPA. The results demonstrate its proximity to the theoretical minimum estimated through commercial compression algorithms, surpassing traditional approaches in similar contexts.  
Future research avenues include expanding the method's utility in analogous scenarios, such as dynamically adjusting coding accuracy to limit message lengths and integrating incremental learning to eliminate the need for pre-training. Additionally, optimizing the structure of the predictive coding predictor stands as a promising area for enhanced efficiency and effectiveness of the QAAPA approach.  
Conceptualization, C.Z.; methodology, C.Z.; validation, J.Z.; formal analysis, J.Z.; investigation, J.Z.; resources, C.Z. and J.Z.; data curation, C.Z.; writing--original draft preparation, C.Z. and J.Z.; writing--review and editing, J.Z.; visualization, J.Z.; supervision, C.Z.; project administration, C.Z.; and funding acquisition, C.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Key R&D Program of China (2022 YFB4301403).  
Not applicable.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multicolumn{6}{c}{**Statistics in Bits**} \\ \cline{2-7}  & **Mean** & **Std** & **Min** & **25\%** & **50\%** & **75\%** & **Max** \\ \hline train (70\%) & 109.96 & 18 & 68 & 96 & 108 & 120 & 360 \\ valid (20\%) & 108.38 & 18 & 68 & 96 & 104 & 120 & 360 \\ test (10\%) & 104.10 & 20 & 68 & 88 & 100 & 112 & 348 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Average coding length of our QAAPA method.  
Figure 8: The generated code length versus time.  
Data Availability Statement: Data available on request due to restrictions: The data presented in this study are available on request from the corresponding author.  
The authors declare no conflicts of interest.  
Notes
# Cell Disruption and Hydrolysis of _Microchloropysis salina_ Biomass as a Feedback for Fermentation
## 3 Results and Discussion
### Composition of the Microalgal Biomass Hydrolysate
According to the total sugars measured in the hydrolysate (8.08 g L\({}^{-1}\)) and the carbon content of the dry microalgae biomass, a saccharification efficiency of 21% and a carbon solubilization efficiency of 31% were achieved on a 200 L scale in this study. Since microorganisms can utilize both sugars and peptides as carbon sources, total carbon solubilization is more important for the use of biomass hydrolysate as a feedstock for fermentation and should be considered as a more practical measure of hydrolysis efficiency in this case.
# Performance Comparisons of Broadband Power Line Communication Technologies
## 2 Structures of PLC
### IoT PLC
#### 2.1.3 Diversity Mapper  
The diversity mapper copies the input bits by a specified number of times. The number of copies is specified by parameter \(DV_{n}\). Users can set the values of \(DV_{n}\) from 1 to 15. OFDM is used in the transmission technique. The copied bits are placed at different frequencies and times of OFDM symbols. This gives the input bit frequency and time diversity, providing robustness against frequency-selective and time-varying distortions in the PLC channel.  
An OFDM symbol has a number of usable subcarriers, or tones, denoted as \(N_{tone}\). Each tone can transmit \(N_{bpt}\) bits, depending on the modulation scheme used. When quadrature phase shift keying (QPSK) is used for modulation, \(N_{bpt}=2\). The number of diversity mapper input bits is \(4N\) and the number of copies is \(DV_{n}\). Then, the number of bits to be transmitted is \(4N\times DV_{n}\) bits and an OFDM symbol can carry up to \(N_{tone}\times N_{bpt}\) bits. Note that \(4N\times DV_{n}\) is not always an integer multiples of \(N_{tone}\times N_{bpt}\). The number of tones in use is denoted as \(N^{\prime}_{tone}\), and extra padding bits are introduced. The padding bits are added at the end of the diversity mapper input bits and copied together. The padding bits are filled with the preceding bits of the diversity mapper inputs. The number of padding bits is denoted as \(N_{pad}\), and the number of required OFDM symbols is denoted as \(N_{sym}\). Then, the following equation should hold for all integer-valued variables.  
\[(4N+N_{pad})\times DV_{n}=(N^{\prime}_{tone}\times N_{bpt})\times N_{sym}. \tag{1}\]  
A method is described to find \(N^{\prime}_{tone}\), \(N_{pad}\), and \(N_{sym}\) when integer values are given for \(N,DV_{n},N_{tone}\), and \(N_{bpt}\)[9]. Figure 5a shows \(N_{pad}\) and \(N^{\prime}_{tone}\) according to \(DV_{n}\) when \(N=1440\), \(N_{tone}=800\), and \(N_{bpt}=2\). It is observed that \(N_{pad}\) varies from 0 to 640 depending on \(DV_{n}\). However, the variation of \(N^{\prime}_{tone}\) is very small.  
Next, it is necessary to place the copied bits far apart in the frequency bands of OFDM symbols to fully exploit frequency diversity. The detailed frequency mapping algorithm is described in [9]. Figure 5b shows the frequency allocation result for the copied bits when \(DV_{n}=15\) as an example. When \(DV_{n}=15\), \(N^{\prime}_{tone}=795\), \(N_{bpt}=2\), and \(N=1440\), 55 OFDM symbols are required for the entire data transmission. The horizontal axis represents time, more specifically, the OFDM symbol sequence number. The vertical axis represents frequency, i.e., the subcarrier number of the OFDM symbol. It is noted that 15 copies of a bit are located at different frequencies and times with a considerable distance, providing robustness against distortions in both the frequency and time domain.  
Figure 4: Channel interleaver: (**a**) test input; and (**b**) output.
# Condition Monitoring of Wind Turbine Blades Using Active and Passive Thermography
## 1 Introduction
Several image processing techniques were applied to the raw thermal images to increase the contrast associated with internal defects. Once the most appropriate technique was determined, a passive thermography experiment was designed and the image processing technique was applied to the thermograms and the maps of surface temperature, to improve their quality. Passive thermography was also performed at different times of the day to assess the most favorable times for the best results. This paper is arranged as follows: Section 1 reviews the literature regarding NDT techniques and thermal imaging methods. The experimental procedures and materials are outlined in Section 2. Section 3 provides the theory of quantitative evaluation. Section 4 contains the results and discussion regarding experimental thermography for the inspection of subsurface defects. Finally, Section 5 provides a summary and conclusion.
# Carbon Nanoparticles and Their Biomedical Applications
## 5 X-ray Protection  
Radiology and nuclear medicine (as well as patients with cancer who undergo radiotherapy) can expose patients to radiation that can endanger their health. It is necessary to protect them adequately and effectively. Studies suggest that CNP-based materials could help to achieve this goal. [PERSON] et al. tested a material (polyaniline) decorated with GO as an X-ray radiation shielding. These shields have shown superior performance in blocking X-ray beams compared to non-GO shields [49]. [PERSON] et al. also confirmed that poly(vinylidene) fluoride homopolymer (PVDF)/barium sulfate attenuated 9.14% of a 20 kV X-ray beam while the addition of 4.0 wt% of a GO nanosheet increased the attenuation efficiency to 24.65% [50]. [PERSON] et al. described that carbon nanotubes (CNTs) are more effective at attenuating X-rays than pyrolytic graphite and fullerenes. The coating of textiles with a thickness of 25 mm, with CNTs, enhanced X-ray attenuation by 70% [51]. [PERSON] et al. compared the X-ray shielding effect among GO, pyrolytic graphite, MWCNTs, and amorphous carbon loaded on PVDF. They found that GO film with a thickness of 0.1 mm attenuated 82.9 and 48.5% of X-ray beams with energies of 6.9 and 8.1 keV [52]. [PERSON] et al. fabricated an X-ray radiation shield that combined polyaniline and hybrid GO nanoflakes with tungsten-bismuth-tin. They confirmed the effectiveness of this shield and suggested that this material could be used to make radiation-protective clothing, such as aprons, gonadal, and thyroid shields to protect against X-rays. Standard protective equipment and clothing are made of lead-based material, which is relatively heavy and difficult to handle [53]. [PERSON] et al. also attempted to replace conventional lead-based material with more lightweight and flexible material. They used a commonly available fabric, combined it with GO, and produced a shielding material that is wearable in clinical practice; it is effective, lightweight, flexible, and permeable to water and air [54].  
Study results suggest that CNPs are ideal candidates for X-ray protection.
# Effects of Wave-Induced Processes in a Coupled Wave-Ocean Model on Particle Transport Simulations
## 2 Methods
### Models and Set-Up
#### 2.1.3 Wave-Induced Processes  
Ocean waves influence the circulation through a number of processes: turbulence due to breaking and non-breaking waves, momentum transfer from breaking waves to currents in deep and shallow water, wave interaction with planetary and local vorticity, Langmuir turbulence. The NEMO ocean model has been modified to take into account the following wave effects [11; 18]: (1) the Stokes-Coriolis forcing; (2) sea-state dependent momentum flux, set as a scalar dependence of the flux from the atmosphere to waves and ocean or as a vector; and (3) a sea-state dependent energy flux. A description of the wave-induced forcing and the processes of wave interaction with the ocean circulation is given in Appendix A.1.
# Automatic Methodology for Forest Fire Mapping with SuperDove Imagery
## 3 Results  
The comprehensive analytical approach to testing the behavior of data provided by the SuperDove sensor, applied to the four fire zones, led to the following results, structured in three key components. Each of them contributes to establishing a reference framework for the use of these data in determining the burned area and the severity of forest fires, particularly small fires.
# Reduced-Complexity Tracking Algorithms on Chip for Real-Time Location Estimation
## The Implementation of Chip Results and Measurement
### Measurement of Chip  
The system architecture of FPGA evaluation board DE2-115. The red frame in the Figure 15b is the system peripheral functions which will be used during chip measurement. As shown in Figure 16, the architecture of the measurement environment after the chip comes back. First, connect each pad of the chip to the corresponding GPIO pin on FPGA, as shown in Table 9. The memory controller circuit programmed by Quartus to read the SRAM control signal, is transmitted to the chip for processing. The output signal of the chip processed by the SRAM, then passed into the seven-segment display to verify whether the position of the final outputs match. The signal is also pulled to the digital logic analyzer for analysis and viewed of the wave. If the function verification is correct, forward to CIC and use the V93000, measuring machine, to measure the chip operating frequency and voltage. The chip's pads are connected with jumper wire to the load-board of V93000. Then, set the definition of each digital pin, and connect the chip's pads to tester channel of V93000. Set timing file and vector file for pattern. Finally, the wave is shown in Figure 17a,b.  
Figure 16: Architecture of measurement environment on FPGA.  
Figure 17: (**a**) Actual wave of V93000 measuring machine. (**b**) Ideal wave of V93000 measuring machine.