esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Proposed Method
### Reference Image Generator  
The Reference Image Generator generates a reference image using multiple images received from a camera. A reference image is a kind of background image, which is constructed through observing colors that show little change over a long period of time. This reference image is used to detect areas where changes have occurred by comparing it with camera images captured in real time. In the real environment, it is not easy to obtain a background image that removes all objects that are likely to change in the future. In our research, to get a more accurate reference image, we adopt a stochastic method that selects color values appearing frequently in the background. Algorithm 1 illustrates the procedure for generating the reference image using Gaussian Mixture modeling.  
Figure 2: Overview of proposed method.  
```
Input: video--input video sequence Parameters: width--width of video frame height--height of video frame channels--number of color channels in video frame numClusters--number of Gaussian clusters (default: 2) Output: backgroundImage--static background reference image
``` procedureExtractBackground(video) stackedFramesframes \(\leftarrow\) Stack(ExtractFramesFromVideo(video)) backgroundImage \(\leftarrow\)InitializedImage(width, height, channels) forx = 0 to width-1 do fory = 0 to height-1 do forc = 0 to channels-1 do  pixelIntensities[] \(\leftarrow\) extract intensities(stackedFrames, x, y, c)  clusters[] \(\leftarrow\) fit GaussianMixtureModel(pixelIntensities, numClusters = 2)  dominantCluster \(\leftarrow\) get most weighted cluster(clusters) backgroundImage[x, y, c] \(\leftarrow\) dominantCluster.mean returnbackgroundImage ```  
**Algorithm 1**Background Extraction using Gaussian Mixture Modeling
## 2 Related Work
Therefore, it does include a packet retransmission strategy and a discovery service. One common characteristic found in AODV, DSR, GPSR, GyTAR, TO-GO, CGMR, LORA-CBF, CAR, GPRS-L and DDOR is that most of them where designed without considering a specific channel model. In fact, most of them have been evaluated by considering an ideal path loss model or channel models that were not specifically developed for V2V communications. Although this assumption is a good starting point for the design and evaluation of a routing strategy, recent works have shown that the path loss model has a significant impact in the routing algorithm performance [55]. Furthermore, the authors in [37] showed that the relative direction of vehicles seriously affects the link path loss in highway scenarios. Therefore, it is really important to consider the path loss model when designing new routing mechanisms for highway scenarios. Based on the previous discussion, it can be stated that two significant issues that must be addressed when designing new routing protocols for highway VANETs are: the selection of an adequate V2V wireless propagation channel model [37], and the design of a reliable destination discovery service. As explained in Section 3, the FPBR protocol introduced in this paper considers these design constraints.
# Hybrid Data Hiding Based on AMBTC Using Enhanced Hamming Code
## 4 Experimental Results
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multicolumn{2}{c}{**[PERSON] and [PERSON] [29]**} & \multicolumn{2}{c}{**[PERSON] and [PERSON] [30]**} & \multicolumn{2}{c}{**[PERSON] [33]**} & \multicolumn{2}{c}{**The Proposed**} \\ \cline{2-9}  & **PSNR** & **SSIM** & **PSNR** & **SSIM** & **PSNR** & **SSIM** & **PSNR** & **SSIM** \\ \hline Boats & 31.3506 & 0.6433 & 30.3823 & 0.6675 & 31.3846 & 0.6828 & 31.4158 & 0.7298 \\ Goldhill & 31.7499 & 0.6942 & 31.1779 & 0.7345 & 32.2203 & 0.7279 & 31.4158 & 0.7642 \\ Airplane & 31.7282 & 0.6614 & 31.1754 & 0.6526 & 31.9034 & 0.7042 & 31.3737 & 0.7305 \\ Lena & 33.2362 & 0.6614 & 32.4231 & 0.6870 & 33.3540 & 0.7094 & 33.4090 & 0.7566 \\ Peppers & 33.3636 & 0.6556 & 32.7389 & 0.6966 & 33.3905 & 0.7081 & 33.5822 & 0.7316 \\ Zelda & 35.4041 & 0.6936 & 34.5442 & 0.7177 & 35.7839 & 0.7335 & 35.9442 & 0.7778 \\ Average & 32.8054 & 0.6683 & 32.0736 & 0.6943 & 33.0061 & 0.7110 & 32.8568 & 0.7484 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Performance comparison of the PSNR and SSIM among the proposed and previous schemes (using 120,000 bits). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multicolumn{2}{c}{**[PERSON] and [PERSON] [29]**} & \multicolumn{2}{c}{**[PERSON] and [PERSON] [30]**} & \multicolumn{2}{c}{**[PERSON] [33]**} & \multicolumn{2}{c}{**The Proposed**} \\ \cline{2-9}  & **MSE** & **NC** & **MSE** & **NC** & **MSE** & **NC** & **MSE** & **NC** \\ \hline Boats & 49.9795 & 0.9946 & 97.2898 & 0.9932 & 51.0112 & 0.9945 & 47.6810 & 0.9950 \\ Goldhill & 50.2434 & 0.9939 & 70.2292 & 0.9934 & 53.1714 & 0.9938 & 52.0115 & 0.9940 \\ Airplane & 43.4923 & 0.9960 & 88.157 & 0.9952 & 44.2237 & 0.9960 & 48.1400 & 0.9961 \\ Lena & 32.3098 & 0.9954 & 57.5453 & 0.9948 & 33.3644 & 0.9953 & 31.3258 & 0.9957 \\ Peppers & 32.3199 & 0.9955 & 55.0679 & 0.9948 & 34.0308 & 0.9943 & 30.4184 & 0.9958 \\ Zelda & 21.1771 & 0.9943 & 32.3215 & 0.9938 & 21.4966 & 0.9943 & 18.0991 & 0.9948 \\ Average & 38.2537 & 0.9943 & 66.7685 & 0.9942 & 39.5497 & 0.9949 & 37.9460 & 0.9952 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance comparison of the MSE and Normalized Cross-Correlation (NCC) between the proposed and previous schemes (using 150,000 bits).
## 3 Construction and Assembly  
The fabrication comprised several phases from the manufacturing of the optical elements to the fabrication of the structure, the mechanical components and the tracking electronic control. In the following subsections, details are given.
# Research on the Impact of BDS-2/3 Receiver ISB on LEO Satellite POD
## 3 POD Strategy
### Experiment Design  
To study the POD potential of the onboard BDS measurements for the LEO satellite, we first solved the LEO satellite high-precision orbit based on the onboard GPS dual-frequency code and phase measurements. Taking the GPS-based POD results as the reference orbit, we evaluated the BDS-based POD results. The BDS-based POD experiments were divided into four parts. The first part was BDS-2-based POD, the second part was BDS-3 POD and the third part was denoted as BDS-2/3 POD, which treated BDS-2 and BDS-3 as one navigation system to solve the LEO satellite orbit. The final part denoted as BDS-2/3-B treated the BDS-2 and BDS-3 signals with different hardware delay biases in the onboard receivers, and BDS-2 and BDS-3 were treated as two navigation systems.  
In addition, in order to analyze the performance of multi-GNSS-based POD, this paper preliminarily tried to obtain the orbit solutions of the different combined strategies from GPS, BDS-2 and BDS-3. GPS, BDS-2 and BDS-3 could be viewed as three separate systems for the onboard GNSS receiver. There are three combined POD solutions, the GPS+BDS-2-based POD solution, the GPS+BDS-3-based POD solution and the GPS+BDS-based POD solution. GPS and BDS-2 are treated as two system to solve the receiver ISB in the GPS+BDS-2-based POD solution, and the same thing was used with the GPS+BDS-3-based POD solution. In the GPS+BDS-based POD solution, GPS, BDS-2 and BDS-3 are treated as three systems to solve two ISBs.
## Appendix A
\begin{array}{l}{4N+1\leq k\leq(10N-9)/2}\\ {w_{k}=\frac{1}{2880}k^{9}+(-\frac{1}{72}N+\frac{1}{80})k^{8}+(\frac{35}{144}N^{2 }-\frac{4}{9}N+\frac{91}{480})k^{7}+(-\frac{1058}{432}N^{3}+\frac{245}{36}N^{2} -\frac{637}{108}N+\frac{63}{40})k^{6}}\\ {+\frac{(4475)}{288}N^{4}-\frac{1055}{18}N^{3}+\frac{22295}{28}N^{2}-42N+\frac{ 7483}{40})k^{5}}\\ {+(-\frac{185731}{288}N^{9}+\frac{22375}{28}N^{4}-\frac{480052}{84}N^{3}+\frac{ 367}{80}N^{2}-\frac{27415}{126}N+\frac{1860}{80})k^{4}}\\ {+(\frac{75555}{432}N^{6}-\frac{18731}{18}N^{5}+\frac{201625}{864}N^{4}-\frac{ 5275}{28}N^{3}+\frac{1309252}{103}N^{2}-\frac{1246}{3}N+\frac{20531}{728})k^{3} }\\ {+(-\frac{5458}{144}N^{7}+\frac{75755}{36}N^{6}-\frac{1704521}{286}N^{5}+\frac{ 67125}{86}N^{4}-\frac{5438925}{864}N^{3}+\frac{318052}{8}N^{2}-\frac{29531}{54 }N+\frac{761}{20})k^{2}}\\ {+(\frac{185525}{576}N^{8}-\frac{458458}{18}N^{7}+\frac{2057505}{864}N^{6}- \frac{56193}{4}N^{5}+\frac{2398875}{1728}N^{4}-\frac{938985}{122}N^{3}+\frac{ 1033585}{42}N^{2}-\frac{3044}{99}N+14)k}\\ {+(-\frac{5271131}{36288}N^{9}+\frac{185525}{144}N^{8}-\frac{4319018}{864}N^{7} +\frac{27755087}{8}N^{6}-\frac{2023493}{1728}N^{5}+\frac{398275}{48}N^{4}-\frac {31155205}{9072}N^{3}+\frac{26635}{36}N^{2}-\frac{560}{9}N)}\end{array}  \tag{10}\]  
The polynomial window function is symmetric for \(k=(10N-9)/2\).
# Study on the Machinability of Ni-Based Superalloy by
## 4 Conclusions  
An experimental study on the milling of GH4169 Ni-based superalloy was carried out in this paper. The effects of the cutting speed, feed per tooth, and radial cutting depth on the workpiece surface roughness and milling force were analyzed. On this basis, the milling machinability of GH4169 under dry cutting, air cooling, MQL, and nanofluid MQL conditions was investigated, and the following conclusions were drawn:  
1. With the increase in the feed per tooth and radial cutting depth, the surface roughness of GH4169 Ni-based superalloy increases, while the cutting speed shows an opposite trend. The milling force decreases first and then increases with the increasing cutting speed. The influence tendency of the feed per tooth and radial cutting depth on the milling force is consistent with that of the surface roughness;
2. The cutting parameters have a nonsignificant effect on the depth of the work hardening layer of GH4169 Ni-based superalloy. With the increasing cutting speed, feed per tooth, and radial cutting depth, the hardness of the machined surface increases compared with the substrate, and the work hardening rate also increases to a certain extent;
3. MQL and nanofluid MQL can greatly reduce the surface roughness of the workpiece and the milling force. The order of the workpiece surface roughness and milling force under different cooling modes is as follows: dry cutting > air cooling > MQL > nanofluid MQL.  
Investigation, Y.J. and G.D.; methodology, H.Y. and G.D.; writing--original draft, Y.J.; supervision, H.Y., X.W. and Q.L.; writing--review & editing, Y.J.; validation, H.Y. and Q.L.; data curation, H.Y. All authors have read and agreed to the published version of the manuscript.  
This research is supported by the National Natural Science Foundation of China (Grant Nos. 52104087 and 52174116).  
Not applicable.  
Data Availability Statement: Data sharing is not applicable to this manuscript.  
The authors declare no conflict of interest.
## 4 Discussion
### Limitations and Future Research  
There are some limitations in our study. First, the results were obtained specifically based on the C-band PQ10W RADARSAT-2 dataset over an agricultural area in Southwestern Ontario, Canada. Although radar signals are affected by both the sensor configurations (radar frequency, incidence angle, look direction) and the targets (crop mixture in different ecoregions), the information used for separating the targets stays the same. As long as there are structural differences and varying growth patterns among different crop types, the multitemporal SAR-based methodology presented in this study can be applied to crop classifications under different climate scenarios, and the classification accuracy will fluctuate depending on the complexity of the crop mix. Second, it is known that applying masks of noncropland land cover types could be helpful in reducing commission errors in the resulting crop classification map. However, a current and accurate cropland mask does not always exist and, therefore, we carried out the land cover classification in an agricultural site without that mask.  
Future work will focus on crop growth monitoring and crop classification with PolSAR data at other radar frequencies (such as TerraSAR-X at X band, ALOS-2 at L band) and over different agricultural sites. Moreover, the forward selection procedure is helpful for investigating which type of features (time or polarimetric information) can contribute more to land-cover classification. For instance, the well-used and freely accessible Sentinel-1 data can only provide a dual-pol mode but with high temporal resolution (only six days for the two-satellite constellation). In addition, temporal variation of interferometric coherence has shown great potential in monitoring dynamics of the surface properties [60; 61; 62], which needs further investigation for crop monitoring and classification.
# Hierarchical Federated Learning-Based Intrusion Detection for In-Vehicle Networks
## 3 Materials and Methods
### Model Initialization and Pre-Training  
The model is initialized on the server side, followed by distributing a copy to each participating client. In this paper, we use a pre-trained model, as [PERSON] et al. [36] demonstrates that pre-training models on a central server before distribution to edge devices enhance task accuracy, especially with non-IID client data. Additionally, many advantages arise from pre-training a model on a centralized dataset for FL. Firstly, it enhances generalization by enabling the model to capture general features and patterns, ensuring better adaptability to the diverse data distributions across devices. Furthermore, initializing a pre-trained model on a powerful centralized server can significantly reduce the time required to fine-tune the model for specific devices [37]. To pre-train the models, we extract a small data sample representing each class, amounting to 0.8% (less than 1%) of the entire original dataset, for use in pre-training. The remaining data are then partitioned across clients. Our approach builds on the methodology outlined in [31], employing K-Means clustering to capture underlying patterns and the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. The sampling process starts by grouping the data into clusters using K-Means. To ensure a representative subset, we apply a group-based sampling strategy, selecting 0.8% of data points from each cluster. This approach retains diversity in the sampled dataset while significantly reducing its size. The selected samples are subsequently excluded from the full dataset before partitioning the data among clients. As the sampled data often display label imbalance, SMOTE is applied to effectively balance the classes.
# Landscape Ecology Analysis of Traditional Villages: A Case Study of Ganjiang River Basin
## 4 Discussion
### Uncertainty and Limitations  
This paper has achieved some research results in the study of the driving forces behind the continuation of traditional villages, the classification of traditional village landscape types, and their distribution characteristics. However, there are still many uncertainties in the research process and results.  
Firstly, in the study of driving forces using the geographical detector, the experiment chose the kernel density value of traditional villages as the Y value. This led to two experimental phenomena: one is that traditional villages in the central Jitai Basin area of the basin are densely distributed around Ji'an City, resulting in some areas with dense construction land and almost no traditional villages having higher than expected kernel density values; the second is that some traditional villages scattered along rivers have too low a kernel density value, failing to adequately reflect the importance of this river distance element for the continuation of these villages. These phenomena are due to the limitations of the experimental model and the scale effect of the research. Fortunately, in the interaction detection, these environmental elements obtained higher Q values, with results aligning with our expectations. This research suggests that interaction detection is more suitable for studying the driving forces of traditional villages. In future research, it is hoped that more research models will be compared and used to summarize more appropriate methods and approaches for the study of traditional villages.  
Secondly, in the process of classifying traditional village landscapes, the environmental elements used and the data thresholds for classification types are also content worthy of further study. Among the elements, the area of cultivated land and forest land are important bases for the classification of landscape types in this study. However, judging solely from land use types ignores the complexity of vegetation-covered land. Including the NDVI index in the study or incorporating elements such as canopy density, forest types, and types of crops in cultivated land can make our classification more detailed and accurate. At the same time, traditional villages from different cultural backgrounds often have significant differences in village site selection and production and living styles. This paper's research is based on geographical features and does not consider the cultural factors of traditional villages. The Ganjiang River Basin has a rich variety of traditional village cultures, with the most representative being the Lu-ling culture in the central part and the Hakka culture in the south. Future research will start from the perspective of landscape genes, classifying traditional villages by cultural characteristics and analyzing traditional village architectural styles and internal spatial patterns at a microscopic level to promote the inheritance and protection of culture.
###### Abstract  
Diabetes Mellitus (DM) is identified as an important condition that leads to implant complications, and the apico-coronal position and the prosthetic abutment seem to interfere with peri-implant tissue behavior This study aimed at assessing the effect on peri-implant parameters after implant loading of two different methodologies in type two diabetics patients (T2 DM) who received implant muco-retained overdentures. Twenty-two mandibular edentulous T2 DM received two implants: Test group: prosthetic abutment of a diameter smaller than the platform of the implant and a morse taper subcrestal implant level; Control group: prosthetic abutment of diameter identical to the platform and hexagonal external implant placed at crestal bone level. Clinical, inflammatory, and tomographic evaluations were performed at baseline (after prosthesis installation), and twelve and twenty-four months after implant loading. Test implants presented inferior probing depth and clinical attachment level compared to control at baseline and 12 months (\(p<0.05\)). Test implants presented reduced levels of pro-inflammatory cytokines at 24 months compared to the control implants (\(p<0.05\)). The control group had more changes in bone parameters from baseline to the first and second years (\(p<0.05\)). The test group resulted in reduced bone remodeling and better clinical conditions and positively modulated peri-implant immunohistochemistry molecules. Trial identification UTN code: U1111-1239-3638.  
diabetes mellitus; dental implants; biological markers; dental prosthesis; prosthesis; implants +
Footnote †: journal: Medical  
augmented bone loss around implants has been related to external hexagonal connections. On the other hand, the morse taper connection promotes a lower concentration and better distribution of stresses/strains in bone tissue around implants when compared with external hexagonal connections [12; 13; 14; 15]. Additional theories have been suggested to elucidate the higher peri-implant bone remodeling in external hexagonal dental implants, including the potential role of the micro gap in the implant-abutment interface regarding bacterial contamination of the connection's internal portion, resulting in the establishment of peri-implant biological width and, consequently, in bone resorption [15; 16; 17].  
Thus, considering the beneficial aspects of the morse taper implant combined with the platform-switching concept [9], it would be useful to determine whether this therapeutic approach could be considered a better alternative than the hexagonal external implant with the prosthetic component of a diameter equal to the platform in the rehabilitation of T2 DM patients with dental implants, since they may be more susceptible than non-diabetic patients to peri-implant changes regarding marginal bone remodeling and local changes in host immune mediators response [18].  
Therefore, this study aims at evaluating the effect of two different approaches in diabetic patients on clinical and tomographic parameters and to analyze their effects on peri-implant local biomarkers during rehabilitation using mandibular overdentures.
# An Approach for Deployment of Service-Oriented Simulation Run-Time Resources
## 5 Simulation Run-Time Resources Deployment Algorithm
### Mutation Operators
Subsequently, it can be determined which BS currently deploying servers is the farthest from these users, and then a closer, idle BS will be selected to replace it. Additionally, with resource availability, the middleware and as many constructive members as possible will be deployed on the BS with the smallest weighted distance. Evidently, this heuristic operator primarily aims to reduce communication time caused by user interactions. We have also devised operations for other objectives, including service queuing time, service communication time, and resource occupancy rate, which are similar to the current operator and hence will not be elaborated on further. These operators can make use of some heuristic information to enable our algorithm to quickly find some not-bad solutions. In other words, while guaranteeing the lower bound of the obtained solution, they greatly speed up the convergence rate of LGASRD. The third approach utilizes the information of EP, allowing the current variant individual to either become more similar to or less similar to one elitist. If the current individual's crowding distance is not equal to 0, it learns from the elitist and becomes more similar to it. For example, if the elitist deploys the middleware on server A, the variant individual will deploy it on B, which is the closest server to A among all servers. If the current individual's crowding distance is equal to 0, we want it to be unique. In other words, we will let it be different from other individuals in the current population. From an algorithmic perspective, the entire population tends towards EP, so we can make the current variant individual distant from them by reducing its similarity to the imitated elitist. If the variant individual overlaps with its adjacent individuals (solutions), this mutation operator increases the diversity of the population. Otherwise, when the current individual is approaching the imitated elitist, it may obtain better objective function values.