esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Simulation Results
### Packet Delay Assessment  
The metric of packet delay is assessed for the proposed scheme and DFSA protocol in a heavy traffic load, and the results are shown in Figure 8. For the proposed scheme, we evaluate the performance of packet delay via both simulation (solid lines) and analytical method (dash lines),  
Figure 7: Trade-off between average long-term data delivery probability and network normalized throughput under different EH rates \(\tilde{\beta}\in\{1,2,3\}\), \(e_{max}=10\). For access schemes, number of time slots in each frame \(N=200\) (only for time division multiple access (TDMA) and the proposed scheme, since the frame length of dynamic frame slotted Aloha (DFSA) is dynamic), QPSK modulation, \(E_{s}/N_{0}=10\) dB.  
and they are well matched under different energy harvesting rates. Moreover, as the energy harvesting rate increases, the performance of packet delay becomes better. For instance, the probabilities of a packet being received successfully within 2 frames are about 0.48, 0.8, and 0.85 under the EH rates \(\tilde{\beta}=1,2\), and 3 respectively. This is because the (re)transmission probability is not only constrained by the current energy level, but also the \(PLR\) threshold, regardless of the packet being transmitted for the first time or being retransmitted. Therefore, with the constraint of \(PLR\) threshold, almost all the packets can be correctly received as long as they are transmitted, and retransmissions will not block the channel. According to the analysis in Section 5.2, for the lower EH rates (e.g., \(\tilde{\beta}=1\) and \(\tilde{\beta}=2\)), the EH rate dominates the delivery probability, while for the higher EH rate, \(\eta_{PLR_{\text{th}}}\) determines the delivery probability. Thus, the packet delay when \(\tilde{\beta}=3\) performs slightly better than when \(\tilde{\beta}=2\).  
Since TDMA is a collision-free protocol, no retransmissions occur in this system. Therefore, we only adopt DFSA to compare with the proposed scheme in terms of packet delay. For DFSA, packets are transmitted as long as EH-STs have energy, and no replicas are used, which will consume less energy. For different EH rates \(\tilde{\beta}\in\{1,2,3\}\), almost every EH-ST has energy to transmit its packet; thus, their performances of packet delay are nearly the same. Since each packet is only transmitted once in a frame, EH-STs applying DFSA have more energy and chances to retransmit their data when the EH rate is low (\(\tilde{\beta}=1\)) compared with those applying the proposed scheme. Therefore, the packet delay performance of DFSA is better than that of the proposed scheme when \(\tilde{\beta}=1\). However, without a packet collision resolution mechanism, EH-STs applying DFSA have to retransmit their data more times. Therefore, when the EH rate becomes higher, EH-STs applying the proposed scheme have more opportunities to transmit their data, and the packet delay performance of the proposed scheme is superior to that of DFSA.
# Real-Time Conveyor Belt Deviation Detection Algorithm Based on Multi-Scale Feature Fusion Network
## 2 Materials and Methods
### Weighted Loss Function  
In the conveyor image, the number of edge and non-edge pixels are seriously unbalanced and about 90% are non-edge pixels. However, the traditional loss function does not balance the edge pixels and non-edge pixels reasonably. To solve this problem, this paper improves the traditional cross-entropy loss function and uses weighted cross-entropy loss to increase the weight of the edge pixels. The weighted cross-entropy loss can be expressed as:  
\[loss=-w\times g\times log(\sigma(y))-(1-g)\times log(1-\sigma(y)). \tag{1}\]  
In Equation (1), \(w\) represents the weight coefficient of the edge pixels in the image and \(g\) presents the label for the category of the pixels (edge pixels or non-edge pixels). \(y\) is the prediction result and \(\sigma\) denotes the _sigmoid_ function. By increasing the weight of the edge pixels, the network needs to pay  
Figure 4: Specific structure and parameters of our multi-scale feature fusion network. Its convolution layers are divided into five stages, in which a maxpooling layer is connected after each stage. Feature maps of each stage are connected to a conv layer with kernel size \(1\times 1\) and channel depth 2 and then upsampled to original image. Finally, a weighted cross-entropy loss/softmax layer is followed to get the output.  
more attention to the edge part in order to achieve more accurate edge detection results. In this paper, the different \(w\) are used to conduct experiments and the results are in Section 4.
## 2 Removal of Optical Thick Clouds
### Substitution Techniques  
Substitution is a very simple way of cloud cover removal. In general a pixel identified as cloudy is simply replaced by the digital numbers (DN) of a pixel at the same location of another image of the same sensor [8]. Because of significant differences between the DN of a pixel between two image acquisitions, some calibrations and corrections are mandatory for cloud substitution. These differences originate from factors like atmospheric conditions, sun-target-sensor geometry, sensor calibration, soil moisture or vegetation phenology [4]. The signal attenuation due to atmospheric distortions has to be corrected image-wise to consider the specific conditions during image acquisition [9,10]. In order to account for the sun-target-sensor geometry, topographic normalization can be applied to reduce spectral reflectance differences that occur due to the influence of terrain slope and aspect [11]. Although the reflectances of the images contributing to the cloud-free mosaic were corrected in two ways, the occurrence of different reflectances is still possible. Therefore the differences in the mean reflectance level between the cloudy image and the cloud-free fill image have to be reduced [12]. The advantage of substitution techniques is the simplicity of the used algorithms, since a pixel value is replaced by the corresponding DN of another image from the same sensor. Hence, complex interpolation techniques are not necessary here and issuesdue to the usage of different sensors can be neglected. A drawback of these techniques is the number of potential error sources in the preprocessing chain due to the high number of the aforementioned steps. The most significant shortcoming, however, is that temporal differences, for example land cover change, between the images are often completely neglected (e.g., [13]).
# Remote Monitoring of the Impact of Oil Spills on Vegetation in the Niger Delta, Nigeria
## 3 Results and Discussion
### Time Series Analysis of \(\Delta\)NDVI for SS and CS
For sparse vegetation (Figure 15b), degradation during the time period overall appears to become less severe with an increase in spill volume of up to approximately 500 bbl before then increasing in severity again at higher spill volumes. Overall, some degradation of mangrove vegetation (Figure 15c) persists throughout the time period, although it is greatest at spill volumes of 1554 and 2500 bbl when 100% of \(\Delta\)NDVIs are less than zero. Overall, vegetation degradation is not directly proportional to the oil spill volume. Possible reasons could be that some oil spills were remediated quicker than others or due to differences in the toxicity of the oil at some locations. Nevertheless, regardless of the vegetation type, the negative impact on the health was most prominent for oil spill volume above 1500 bbl. Another factor that could impact the impact of the oil spill in the Niger Delta is the topography and the relief of the spill site. High topography can influence the migration of large oil spills from the source [30]. Therefore, each spill site must be treated on an individual basis. Figure 15: _Cont._
## 2 Materials and Methods
### DeepLab v3+ Training and Evaluation  
The DeepLab v3+ network [31], which employs atrous convolution and pyramid pooling to capture features at multiple scales, was trained separately for each of the five folds. Training involved three epochs, a batch size of 64, and an initial learning rate that was reduced by a factor of 0.3 after each epoch. Although the number of epochs was small, data augmentation mitigated underfitting risks. Each model's performance was then tested on the data held out for that particular fold. Segmentation accuracy was evaluated using the Dice Similarity Coefficient (DSC) and Intersection over Union (IoU). Given a predicted set of pixels \(S\) and a ground-truth set \(G\), these metrics were computed as  
\[DSC=\frac{2|S\cap G|}{|S|+|G|},\ IoU=\frac{|S\cap G|}{|S\cup G|}\]  
Both DSC and IoU measure how closely the segmentation output aligns with the manually annotated ground truth. For each test slice, the metrics were calculated on a pixel-by-pixel basis, and mean values were reported. In addition, the inference speed, defined as the number of images processed per second (fps), was recorded to assess potential clinical utility. No further postprocessing was applied, allowing the results to reflect the raw predictive ability of the network.
# Traffic Sign Detection Based on the Improved YOLOv5
## 4 Conclusions  
Aiming at the problem that current traffic sign recognition technology cannot meet the real-time and accuracy standards required by intelligent assisted driving systems, an improved YOLOv5 algorithm is proposed. Training and testing are performed on the TT100K and GSTDB datasets. The experimental results on the TT100K dataset show that the loss function value of the YOLOv5 algorithm after the improvement is significantly reduced compared to before. The convolutional block attention model and the CSP1_3 model are fused together to create a novel CSP1_3 CBAM model. ACONC is selected as the activation function of YOLOv5. Thus, the feature extraction ability of the model for useful information is improved, the recall rate, accuracy rate, detection accuracy rate, and detection speed are improved, and false detections and missing detections during real-time detection are significantly reduced. At the same time, the resulting mAP after training on the GSTDB dataset is 91.5%, indicating that the model has good generalization ability. The light weight of the model will be studied in the future for easy deployment to mobile devices.  
Methodology, R.Z.; software, K.Z.; validation, K.Z., R.Z. and P.S.; investigation, Y.M.; resources, R.Z.; writing--original draft preparation, R.Z.; writing--review and editing, K.Z.; visualization, R.Z.; supervision, H.L.; project administration, T.Q. All authors have read and agreed to the published version of the manuscript.  
This research was funded by The National Natural Science Foundation of China, Nos. 51605003 and 51575001, the Natural Science Research Project of Anhui Province, China, No. KJ2020A0358, and the young and middle-aged Top Talent Training Program of Anhui Polytechnic University.  
No new data were created in this study. Data sharing is not applicable to this article.  
The authors declare no conflict of interest.  
Figure 8: Improved YOLOv5 algorithm comparison detection graph: (**a**) multiple traffic signs and small targets on a highway; (**b**) single traffic sign on a street; (**c**) single traffic sign on a campus; and (**d**) small and middle targets.
# Shock-Absorber Rotary Generator for Automotive Vibration Energy Harvesting
## 7 Conclusions  
This paper proposed the applicability and development direction of suspension with energy harvesting by installing blades on suspension. Blades were installed instead of the orifice, and a shock absorber was modeled including a rotor and piston, snap ring, and bearing. The vehicle's driving conditions were set using the CarSim-Simulink. The vibration characteristics were analyzed. The suspension speed was calculated, and the curve was derived using ANSYS Fluent. For maximum power generation, w was selected, and the selected w was interpreted as the input of the designed rotary generator. As a result, a value of 48.5452 W could be confirmed.  
To increase the power generation significantly, the generator was optimized using an orthogonal array provided by PIAnO. As a result, 59.4562 W was generated, which is an increase of 122.47% compared to the initial model.  
1. In this study, the blade was installed in place of the orifice of the existing suspension. Therefore, it necessary to check whether the installed blade generates as much damping force as the existing orifice.
2. The optimal design of the blades is needed to achieve the maximum power generation under limited conditions.
3. The addition of the rotors increased the load significantly, but further analysis and verification related are required.
4. The amount of power generation needs to be verified by inputting the velocity that changes over time instead of the average value of the inlet velocity of the fluid.
5. For simplified analysis, the fluid is marked at ambient temperature. Therefore, it will be necessary to calculate the energy equation by entering a change in the fluid temperature.
6. In the future, an analysis will be performed by changing the rotational speed of the generator, and the operation point will be identified by generating the generator \(T\)-\(\omega\) curve.  
In this study, many simplifications were made. Hence, the design will need to be optimized by reducing the simplifications in later studies.  
Conceptualization, J.H.K. and T.D.K.; software, T.D.K.; writing--original draft preparation, T.D.K.; writing--review and editing, J.H.K.; and T.D.K.; supervision, J.H.K.; funding acquisition, J.H.K. All authors have read and agreed to the published version of the manuscript.  
Figure 19: Optimal design results: (**a**) current of optimal model; (**b**) voltage of optimal model; (**c**) magnetic flux line; (**d**) magnetic flux density; (**e**) power.  
**Funding:** This research was funding by Yeungnam University Research Grant in 2020.  
**Acknowledgments:** This research was supported by Yeungnam University Research Grant in 2020.  
**Conflicts of Interest:** The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 4 Experiments and Results  
The proposed multiple watermarking algorithm was implemented to validate its performance, utilizing ShapeFile format data for the experiments. Specifically, an in-depth analysis was conducted to assess the robustness of the algorithm against random noise attacks and its capacity to handle multiple watermarks.
## 3 Push-Off Tests on Joints between Segments
### Grouped Grounded Joint
#### 3.2.2 Influence of Investigated Parameters on Joint Capacity  
In the diagram in Figure 14c, the maximum shear stress \(\tau_{max}\) achieved in the experiments is plotted against the nominal prestressing stress \(\sigma=P/A\), allowing a comparison of the resistance of the different joint types. All test results from this series are listed in Table 7.  
It became apparent that the relationship between the prestressing level and the maximum load \(F\) could be described by a linear function in the investigated range. Therefore, only high and low prestress forces were investigated in the grout 1 series.  
The positive effect of joint grouting on the shear resistance can be seen when the results of specimens with plain joints are compared to the results with dry joints (light grey line in Figure 14c). The plain grout 1 specimens showed an average increase of 53 kN, while the increase with grout 2 specimen was about 40 kN.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Name**} & \multirow{2}{*}{**Grout**} & \multirow{2}{*}{**Type**} & \(F_{max}\)1 [kN] & \(\tau_{max}\)2 [FOOTNOTE:1]Footnote 1: \(F_{0.2}\) at shear deformation of \(s=0.2\) mm is chosen for \(F_{max}\). 1 experimental data of column \(F_{max}\) also in [21]. 2 \(\tau_{max}=F_{max}/A\) with \  
The comparison of grooved joints with plain joints shows that grooved joints have a higher shear capacity, presumably because of their higher roughness. Nevertheless, the increase is more pronounced with the grout 2 specimens, seeing an average increase of 36 kN. By contrast, only a small increase of about 8 kN could be observed in the Grout 1 specimens. It is assumed that the different ratio between the compressive and tensile strength of the mortars leads to this difference.  
The keyed joint showed almost the same load capacity as the grooved joint (see Table 7). However, as discussed above, the load deflection curve is different.
# Evaluating the Effectiveness of Large Language Models in Converting Clinical Data to FHIR Format
## 5 Methodology
### Hypotheses
#### 5.1.2 Impact of Few-Shot vs. Zero-Shot Prompting  
Providing examples in the prompt (few-shot prompting) can guide the model by showing it the expected format and content. This guidance can help the model to identify relevant information and generate more complete FHIR bundles. However, overreliance on examples may lead to the reproduction of irrelevant or incorrect information.  
**H2.1**: _Few-shot prompting will result in more complete and accurate FHIR bundles compared to zero-shot prompting._  
**H2.2**: _Few-shot prompting may introduce biases or irrelevant information._
## 1 Introduction
(5) Filter orthogonal frequency division multiplexing (F-OFDM) [15] filters the entire subband. (6) Orthogonal time frequency space (OTFS) [16; 17; 18; 19] is a waveform based on a specific two-dimensional Fourier transform, i.e., a symplectic Fourier transform, which loads the modulated symbols into the delay-Doppler domain. These waveforms encounter various problems when supporting the communication in large bandwidths of the THz communication band. Recently, we proposed a new waveform called generalized filter bank orthogonal frequency division multiplexing (GFB-OFDM) in [20; 21; 22] for THz communication. The waveform utilizes the two-level IFFTs and the polyphase filters to jointly process of the multiple subbands. In [21], it shows that the out-of-band leakage of GFB-OFDM is lower than that of CP-OFDM without error performance loss. In [22], more comparisons were provided in different subcarrier spacings. However, there is still a lack of solid proof regarding an equivalence between the GFB-OFDM transmitter and the CP-OFDM transmitter. Moreover, the complexity analysis and a more detailed evaluation are required to validate its advantages. In this paper, we present the complexity analysis, solid proof of the equivalence between the two transmitters, and a comprehensive performance evaluation of the coded GFB-OFDM. By decomposing the large size of an IFFT into two levels of IFFTs in smaller sizes, the GFB-OFDM facilitates efficient handling of the large IFFT size and the subband filtering, which reduces the computational complexity and enables the ultra-wideband communication. The GFB-OFDM allows for a flexible configuration of the system parameters,including the number of subbands, the number of subcarriers in each subband, the subcarrier spacing, and the filter parameters, etc. This capability can improve the transmission stability in high-mobility scenarios by suppressing the effects of Doppler spread and satisfy various application requirements in 6G communication, especially in terms of the high bandwidth and different services. Furthermore, the GFB-OFDM can be also configured to reduce power consumption regarding the energy efficiency of 6G networks. Overall, the GFB-OFDM provides a versatile and efficient solution for the complex demands of 6G communication, particularly in supporting ultra-wideband THz communication, improving spectral efficiency, and offering adaptable configurations for diverse applications and services.
# UV Light Application as a Mean for Disinfection Applied in the Dairy Industry
## 8 Conclusions  
The application of UV technology can have many advantages in the dairy industry, including increased shelf life and microbial protection of dairy products, as well as energy savings due to the non-thermal technology. Nowadays, consumers look for goods that are manufactured in an environmentally friendly manner, so sustainability and environmental issues are becoming highly relevant. Ultraviolet processing can provide more desirable food items with fresh-like qualities. Many microorganisms are killed by short-wave UV-C radiation, which can be used to make food items safe. Despite the fact that UV light radiation can inactivate a broad variety of microorganisms, some elements of its usage in food should be examined. Currently, this technology is not commonly used in the dairy industry, although it may be in the future and, in order to maximize its impact on foodborne pathogens and spoilage microflora, the appropriate form of the lamp should be considered in each method. It would be of great importance to investigate the impact of this treatment on foods in terms of nutritive value as well bioavailability of nutrients.  
The research showed that the MPM UV lamp is an economical and practical alternative especially for those companies that want to increase the quality of the final product. Some of the technologies are already well-established across the globe like disinfection of drinking water with UV light which is used for brewing and drug treatment. The studies in this review demonstrated the advantages of ultraviolet light, but there are some drawbacks to use it in dairy products, such as limited penetration potential, and contamination. To overcome contamination, UV Light Emitting Diodes could be of great potential instead of mercury or amalgam lamps, as these are more food plant-friendly.  
Moreover, the application of UV technology in combination with other techniques, such as pasteurization, ultra-high pressure homogenization (UHPH) was reported. However, there is a need for further research in this area, in order to determine the optimal conditions for manufacturing safe products at a minimal shift in sensory and nutritive properties.  
Conceptualization, A.C.; resources, A.C., A.L., J.T. and J.Z.; writing--original draft preparation, A.C.; writing--review and editing, A.L. and J.Z.; visualization, A.C. and J.T.; supervision, A.L. and J.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 5 Mechanisms Used by Industrial Technologies to Improve Performance Metrics  
This section discusses the mechanisms used by industrial technologies for addressing the requirements of industrial automation wireless networks in terms of real-time capability and reliability. The mechanisms include Media Access Control (MAC) layer contention techniques, priority management schemes, channel hopping, and multipath routing.