esa-sceva/satcom-chunk-collection huggingface dataset:
# A Model-Assisted Combined Machine Learning Method for Ionospheric TEC Prediction
###### Abstract
The genetic algorithm (GA) can optimize the neural network to establish a short- or long-term prediction model of ionospheric parameters in a single station or a certain region and can get good results [23; 24; 25]. There are also some innovative optimization algorithms used to improve neural networks. For example, the artificial neural network (ANN) based on multi-source data and optimized by the genetic algorithm can be used to build a global ionospheric model for predicting various ionospheric parameters such as foF2 and hmF2 [26]. The radial basis function (RBF) neural network classification algorithm based on partial least squares (PLS) and GA (PLS-GA-RBF) is proposed to solve some recognition problems caused by small samples. The results indicate a good picture of the PLS-GA-RBF algorithm; the operating efficiency and recognition accuracy improved substantially [27]. The prediction accuracy of ionospheric parameters based on the backpropagation neural network (BP-NN) can be improved by using an improved particle swarm optimization algorithm [28]. In order to improve the long-term prediction accuracy of TEC, a new combined intelligent prediction algorithm was proposed by combining the IRI model, TEC statistical learning model, artificial neural network, and genetic algorithm. Furthermore, to improve the prediction accuracy, the weight and threshold of BP-NN are optimized by an adaptive genetic algorithm with a multi-mutation and multi-cross location. The detailed arrangement of this paper is as follows: Section 2 is the modeling data and processing process; Section 3 proposes the model principle and modeling process; in Section 4, the predicted results are compared with the measured data and the predicted data of other models to verify the practicability of the method.
## 3 Results  
### Elastase and Collagen Inhibitory Activity  
Skin aging is caused by the alteration of the dermal connective tissue and is due to intrinsic and extrinsic factors. Aging is an intrinsic factor, while chronic sun exposure is an example of an extrinsic factor. When skin ages, the amount of elastin and collagen decreases, resulting in the loss of strength and flexibility in the skin. Elastase and collagenase are responsible for the breakdown of elastin and collagen in the extra-cellular matrix, respectively. We assessed the anti-aging properties of the extracts by measuring their ability to inhibit elastase and collagenase activity. The results are shown in Figure 2. The elastase inhibitory activity was greater in the flesh of fruit (13-29%) than in the peels (1-10%) at all fruit-maturity stages (Figure 2A). Considering only the flesh of the fruit, the immature green stages (EJF and MSF) had more activity than the color-turning stages (EOF and MOF) and mature stages (LNF). The leaf and flower extracts had very little elastase inhibitory activity (0.6-4%). In the collagenase inhibition assay, the inhibitory activity was higher in the flesh (9.7-106.6%) than the peel (0-8.9%) at all fruit-maturity stages (Figure 2B). The most collagenase inhibition showed in the EJF stage (85%). The EJF extract was examined in more detail by a dilution concentration of the extract (Figure S2). The anti-collagenase activity was highly dependent on the concentration of the extract. Although the inhibitory activity of elastase and collagenase was somewhat different, the EJF stage had the greatest inhibitory activity in both enzyme assays.
# Building Geometry Simplification for Improving Mesh Quality of Numerical Analysis Model
## 5 Evaluation of Simplification Effect
### Geometrical Properties
#### 5.1.2 Meshing Complexity  
The meshing complexity and mesh quality of the numerical analysis model increase with the complexity of the target geometry. [PERSON] et al. [34] proposed the ITC as an index for evaluating the hexahedral meshing complexity, and the calculation formula is as follows:  
\[\text{C}_{\text{ITC}}=\text{min}\bigg{(}\frac{1}{2}\bigg{(}\frac{6}{|F|}+ \frac{12}{|E|}\bigg{)},\;1\bigg{)} \tag{9}\]  
where \(\text{C}_{\text{ITC}}\) is the ITC, \(F\) is a set of faces, and \(E\) is a set of edges in the target model.  
The ITC is an index for evaluating the complexity of a geometry and the ease of hexahedral meshing based on the basic geometric information, i.e., the number of faces and edges. It has a range of \(0<\text{C}_{\text{ITC}}\leq 1\), and a lower value is calculated for a model with more complex surfaces, which comprises multiple faces and edges. The ITC of the cube (\(|F|=6\), \(|E|=12\)), which is ideal for the hexahedron mesh design, is equal to the maximum value, 1.
## 1 Introduction
However, it was assumed that the drone has only one parcel to deliver and collect/forward data along the way to certain destinations as an added value service. In addition, it was assumed that the drone remains connected to the source and destination throughout the data delivery process, which is hard to maintain in isolated remote areas. In this work, we consider the use of UAVs jointly for providing DTN connectivity and goods delivery to remote rural areas. In the case of remote delivery, there is a need to track each item carried and/or delivered and to log the time and location of delivery. In addition, suitable measures need to be taken to secure the carried data (for confidentiality and privacy purposes), the carried goods (protection from loss or theft), and the UAV itself (protection from attack, damage, or theft). Therefore, the main novelty of this paper is related to proposing techniques for recording and storing the transaction information securely in the absence of internet connectivity. Thus, the UAV is assumed to deliver goods, e.g., medicine, humanitarian support, etc., to remote areas, while carrying data in a DTN fashion. We propose efficient techniques for encrypting the transaction logs. After the UAV's return, this encrypted information can be recovered and processed at the Control Center. The novel contributions of this paper can be summarized as follows:  
* Proposing a novel framework for encrypting the transaction logs when using UAVs for autonomous delivery with multiple stops at various destinations;
* Describing how cipher block chaining, physical layer security, and symmetric and asymmetric encryption techniques work in tandem with the proposed approach to track goods delivery and secure the transaction logs;
* Showing that the proposed framework is feasible and securely encrypts the data in the absence of connectivity until the drone returns safely to base;
* Analyzing the proposed approach and showing its robustness to attacks;
* Discussing the suitability of the proposed approach in the face of malicious attempts to tamper with the UAV or its payload; and
* Demonstrating that the proposed approach can work with existing encryption techniques to achieve the desired objectives. The rest of this paper is organized as follows. Section 2 presents the system model considered in this paper. The proposed approach is presented in Section 3. The resultsrelated to the probability of detecting the encryption keys are presented in Section 4, and the security features are analyzed and discussed in Section 5. Finally, Section 6 concludes the paper.
# Remote Sensing Scene Classification and Explanation Using RSSCNet and LIME
## 5 Conclusions  
As a result of continued advances in technology, better-quality and higher-resolution data can be obtained, leading to improvements in remote sensing image classification and in predictions based on it. It takes a lot of time to train and adjust the classification. In order to reduce the time required for the training of the model and to explore how quickly the model can converge with high-generation capability, we recommend the RSSCNet model integrated with the simultaneous use of a two-stage cyclical learning-rate training policy and the no-freezing transfer learning technology that requires only a small number of iterations. In this way, an excellent level of accuracy can be obtained. Data augmentation technology, regularization, and early stopping strategy can then be used to also deal with the problem of limited generalization encountered in the rapid training of deep neural  
Figure 24: Test accuracy of with and without two-stage cyclical learning-rate method.  
networks. The experimental results that were obtained also confirm that the use of the model and training strategies proposed in this paper can outperform current models in terms of accuracy.  
In this study, by using the LIME super-pixel explanation, the root causes of model classification errors were made clearer and a better understanding was obtained. This made it easier to carry out subsequent processing and adjustment of the data or models. After the image correction preprocessing on the four misclassified images using the RSSCNet model in the WHU-RS19 dataset, this image correction procedure was found to improve the overall classification accuracy. This investigation is only a preliminary study.  
In future research, we will try to establish universal image correction preprocessing for the case of suspected outliers and merge different XAI (explainable artificial intelligence) analysis technologies to improve interpretation capabilities so that they can be applied to a more diverse range of imagery with different classification issues.  
[PERSON] and [PERSON] conceptualized and designed the whole framework and the experiments, as well as wrote the manuscript. [PERSON] performed the experimental analysis. [PERSON] contributed to the discussion of the experimental results. [PERSON] helped to organized and revise the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Science and Technology, Taiwan, grant numbers MOST 108-2621-M-040-002 and MOST 109-2121-M-040-001. The support is greatly appreciated.  
The authors declare no conflict of interest.
## 4 Conclusions, Limitations and Future Research
### Future Research Directions  
To enhance the understanding of flood risks in the Vistula Lagoon and develop more effective adaptation strategies, future research should address the following areas:  
* _Integration of dynamic climate projections._ The latest IPCC-based climate models to refine predictions of wind intensification and sea level rise effects should be incorporated.
* _Coupling wind surge and precipitation-driven flooding._ Compound flooding scenarios in the city of Elblag that combine storm surges, extreme rainfall, and riverine floods should be investigated.
* _Adaptation and mitigation strategies._ The effectiveness of potential flood protection measures, such as storm barriers, retention restoration, and improved drainage infrastructure should be assessed.  
In conclusion, while this study provides a valuable preliminary assessment of storm surge-induced flood risks in the Elblag region, further interdisciplinary research is necessary to refine hazard and risk predictions and develop robust flood management policies in the face of climate change.  
**Author Contributions:** Conceptualization, M.S.; methodology, M.S.; validation, M.S; formal analysis, M.S. and K.G.; investigation, M.S., K.G. and A.W.G.; resources, M.S. and K.G.; data curation, K.G. and A.W.G.; writing--original draft preparation, M.S., K.G. and A.W.G.; writing--review and editing, M.S., K.G. and A.W.G.; visualization, M.S., K.G. and A.W.G. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# The Effect of Railway Projects Increasing Safety on the Frequency of Occurrences
## 1 Introduction
Last but not least, in the case of the modernization of the Sopron-Szombathely-Szentgotthard line, the economic impact of traffic restrictions during construction is declared, as well as the benefit in the form of higher reliability of rail traffic after the completion of the line modernization. The results show that the increased reliability of rail transport (lower number of train delays) has a non-negligible economic benefit, here specifically EUR 30.9 million, which in the case of this construction is about 15% of the investment costs. It should be considered here that these are non-discounted values and therefore that the overall impact on economic efficiency will not be so significant. At the same time, the results of this research are burdened with a certain amount of uncertainty, because they do not have a sufficient volume of data available, e.g., the data on the average delay of trains after the construction is completed are drawn from only one year, namely, 2011. [PERSON] et al. investigate, in [28], the relationship between rail traffic safety and rail network performance in the context of the UK rail network, using statistical data from 17 transport companies from 2006 to 2016. [PERSON] et al., in the study [29], investigate the effects of increased reliability on the results of economic efficiency of railway constructions, while examining these effects on the example of an intercity direct rail connection. According to the conclusions of this study, the increased reliability of rail transport can be a relatively significant benefit of the economic CBA, while it should be emphasized that this is a simplified model of a direct (without transfer) intercity connection. The background [30] also deals with general contexts associated with the economic analysis of railway projects using the CBA method. In their treatise, [PERSON] and [PERSON] [31] subsequently declare the necessity of a comprehensive approach including the technical, social, and safety dimensions of modeling the impacts of extraordinary events on a railway transport route. As part of the research work on the project \"Evaluation of increased safety and reliability of the railway infrastructure after its modernization or reconstruction\", the influence of the implementation of specific buildings on the severity and number of occurrences of extraordinary events on the railway transport route is investigated. The objective of this contribution is to determine the real benefit of the implementation of railway projects involving investments in increasing the safety and reliability of the railway transport route to reduce the occurrence of extraordinary events on the railway transport route and their socio-economic impacts. Within the presented part of the research, the following research question was formulated: RQ1: To what extent can the frequency and impact of extraordinary events be reduced through the modernization of the railway infrastructure?
## 3 Indoor Positioning Systems
### Systems Based on Light
#### 3.4.1 Visible Light  
The transmission of data by visible light uses any type of lamp for this purpose; however, LED lights are the most suitable [5]. Visible light communication (VLC) uses the ability to turn the light source on and off at noticeably short intervals [100]. This on/off operation can occur so quickly that it is invisible to the human eye. The VLC for IPS has been tested in some indoor location studies, as described by [PERSON] and a group of collaborators, who reused the artificial light infrastructure available in the environment to insert encodings [101]. This approach allowed the authors to reduce the cost of implementing their indoor positioning system significantly.  
The principle of VLC is that each fixed lamp has different scintillation coding so that the sensor receives the light and compares the modulation with known coding schemes and associates it with the location close to the corresponding lamp [102]. An advantage of this arrangement is that it is non-invasive because human users see only ordinary lamps fixed in standard locations such as the ceiling. The receiver can be a photodiode or an optoelectronic device capable of capturing light intensity (for example, a photocell) or an image sensor (for example, a camera) to register the transmitter's light pulses. The advantage of an image sensor is that it can record several lamps with their positions simultaneously, thus achieving more accurate location estimates.  
All VLC-type projects are of the passive type, as the central element for the emission of information is the lamps, which are often heavy and need a connection to the power grid. Still, authors such as [PERSON] and [PERSON] report accuracy levels below 0.20 m [5,99].  
Some authors have experimented with the use of VLC in the Li-Fi mode [103]. The Li-Fi and LIDAR (Light Detection and Ranging) technologies, in addition to allowing the operation of guiding people in indoor environments, also reduce energy consumption, since transmission occurs only when users are detected in the environments. Another interesting feature of Li-Fi is its speed, which is much higher than that available in Wi-Fi technologies.  
Most VLC systems locate the target based on information acquired from various luminaires (usually three or more), requiring a unique identifier, and the combined signal received from all visible luminaires needs to be separated [104]. The consequence of using several VLC devices is the need to apply multiplexing/de-multiplexing schemes.
# Transformer-Based Distillation Hash Learning for Image Retrieval
## 4 Experiment and Analysis
### Comparison to the State of the Art
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Methods** & \multicolumn{3}{c}{**MIR Flickr-25K**} & \multicolumn{3}{c}{**NUS-WIDE**} \\ \hline PCAH [43] & 0.6444 & 0.6321 & 0.6377 & 0.6534 & 0.5775 & 0.5052 & 0.4921 & 0.4924 \\ \hline DSH [47] & 0.6962 & 0.7076 & 0.6851 & 0.6612 & 0.5944 & 0.5987 & 0.5725 & 0.5795 \\ \hline DH [45] & 0.6021 & 0.6176 & 0.6144 & 0.6174 & 0.4745 & 0.4631 & 0.4625 & 0.4755 \\ \hline DeepBit [46] & 0.5887 & 0.6033 & 0.6092 & 0.6091 & 0.5465 & 0.5551 & 0.5626 & 0.5612 \\ \hline BDNN [48] & 0.6654 & 0.6692 & 0.6678 & 0.6695 & 0.5932 & 0.5922 & 0.5912 & 0.6098 \\ \hline DVB [49] & - & - & - & - & - & - & 0.562 & - \\ \hline DOH [50] & - & - & 0.6728 & 0.6712 & - & - & 0.6145 & 0.6251 \\ \hline Ours—student & 0.7046 & 0.7112 & 0.7092 & 0.7088 & 0.6361 & 0.6473 & 0.6526 & 0.6482 \\ \hline Ours—teacher & 0.7471 & 0.7582 & 0.7485 & 0.7435 & 0.6818 & 0.6932 & 0.6925 & 0.6882 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._  
Figure 3: Performance curves of retrieval results on the MIRFlickr-25K dataset. (**a**) Precision using hash lookup within the Hamming radius 2; (**b**) Precision–recall curve for 48 bits; (**c**) Precision curve for 48 bits; (**d**) Precision–recall curve for 24 bits; and (**e**) Precision curve for 24 bits.
# The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios
## 1 Introduction
* For the store-carry-forward mechanism, specific vehicles were selected to be data-ferries so as to exchange information between different disconnected networks. Moreover, the redundant transmissions of this process were _further_ suppressed. * A channel congestion control was designed according to the status of local network traffic. * A comprehensive performance evaluation was performed by means of realistic simulations. Three classical data dissemination protocols were compared with TrAD in both urban and highway scenarios. Furthermore, the impact of GPS drift on the data dissemination speed was also investigated. The remainder of this paper is organized as follows. In Section 2, the state-of-the-art in data dissemination protocols are summarized and the issues in need of solutions are highlighted. Section 3 presents the TrAD protocol motivated by these challenges, and where every detailed technique or mechanism is elaborated. In Section 4, the performance of the TrAD protocol is evaluated by considering realistic scenarios. In the last section, we establish an assessment of the TrAD protocol and present the future work.
# Analyzing and Controlling Inter-Head Diversity in Multi-Head Attention
## 3 Similarity Measures for Multi-Head Attention  
### Multi-Head Attention  
Multi-head attention is first suggested by [PERSON] et al. [1] as a strategy that diversifies representation subspaces in order to fully utilize a model's capability. We briefly review how single-head and multi-head attention operates.  
For single-head attention, an output matrix \(X^{\prime}\in\mathbb{R}^{L\times d}\) with its inputs (a query vector \(q^{\prime}\in\mathbb{R}^{d}\), a key matrix \(K^{\prime}\in\mathbb{R}^{L\times d}\), and a value matrix \(V^{\prime}\in\mathbb{R}^{L\times d}\)) is computed as follows;  
\[X^{\prime}=\text{softmax}(\frac{q^{\prime}K^{\prime 7}}{\sqrt{d}})V^{ \prime}, \tag{1}\]  
where \(L\) is a length of key and value matrix and \(d\) is a hidden dimension size. The single-head attention first computes attention weights by taking softmax function onto similarity scores between a query vector and key matrix, then finally operates multiplication with value matrix which can be considered as a pooling operation from a value matrix with the attention weights.  
On the other hand, multi-head attention operates \(H\)-many single-head attentions in parallel with \(q_{i}\in\mathbb{R}^{d_{h}}\), \(K_{i}\in\mathbb{R}^{L\times d_{h}}\), \(V_{i}\in\mathbb{R}^{L\times d_{h}}\), where \(q_{i}\), \(K_{i}\), \(V_{i}\) are projections of \(q\), \(K\), \(V\) onto smaller dimension \(d_{h}\) with weight matrices \(W_{i}^{q}\), \(W_{i}^{K}\), \(W_{i}^{V}\in\mathbb{R}^{d\times d_{h}}\) respectively for each \(i\)-th head. The output of multi-head attention is calculated by concatenating all outputs of \(H\)-many heads followed by final linear projection;  
\[X=[X_{1},...,X_{H}]W^{O}, \tag{2}\]  
where \(X_{i}\) indicates an output of the \(i\)-th head and \(W^{O}\in\mathbb{R}^{d\times d}\) is a weight matrix.  
Figure 1 shows examples of self-attention weights in Transformer model. Given the query word \"_representation_\", the single-head attention module outputs attention weights for other words (a). On the other hand, each head in multi-head attention assigns different weights for other words as each head has its own weight matrix (b).  
Although it has been believed that multi-head attention diversifies representation subspaces, measuring the similarity among deep representations of each head has been rarely studied. Measuring the inter-head similarity requires taking account of heads' response over the entire dataset. To do so, we adopt the following advanced tools for measuring similarity of representations in neural networks.