esa-sceva/satcom-chunk-collection huggingface dataset:
# Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting +
## 4 Experimental Results
### Hyperparameter Tuning and Forecasting Accuracy  
Empirical testing of the research models requires the selection of the performance metric and tuning of the hyperparameters. In this study, we focused on forecasting accuracy as the primary model performance characteristic. The forecasting accuracy is measured using two widely used metrics, mean absolute error (MAE) and root-mean-squared error (RMSE):  
Figure 4: Spatial graph settings: (**a**) graph for the 10-min neighborhood; (**b**) percentage of achievable nodes within specified travel time (min); and (**c**) spatial graph Laplacian’s heat map, ordered by geographical coordinates.  
\[MAE_{t}=\frac{1}{k}\sum_{i=1}^{k}\abs{y_{i,t}-\hat{y}_{i,t}}, \tag{15}\] \[RMSE_{t}=\sqrt{\frac{1}{k}\sum_{i=1}^{k}(y_{i,t}-\hat{y}_{i,t})^{2}}, \tag{16}\]  
where \(\hat{y}_{i,t}\) is a predicted value for a spatial location \(i\) and time point \(t\). The obtained MAE and RMSE values were aggregated by spatial and temporal dimensions, and their mean values used for model comparisons.  
The models' hyperparameters were tuned for one-step-ahead forecasting accuracy, while the model performance was compared for longer forecasting horizons as well. We utilized the rolling window cross-validation technique [55] for the estimation of out-of-sample MAE and RMSE values. The list of tuned hyperparameters includes:  
* Radii of spatial neighborhoods \(r_{1}\), \(r_{2}\), and the spatial inflation _step_ for SpX-lm, SpX-SVR, and SpX-ARIMAX models;
* Spatial weights' definition and distance decay parameter \(\sigma^{2}\) for SpX and GCNN models;
* ARIMA orders for conventional ARIMA and SpX-ARIMAX models, tuned by [PERSON]'s algorithm [56];
* Cross-correlation threshold \(\theta\) for SpVAR-cc model;
* Order \(p\) for VAR, SpVAR-tt, and SpVAR-cc models;
* Size of the rolling window (the look-back interval) \(L\) for all models (gradually increased until the models' forecasting performance metrics are stabilized).  
The hyperparameters and their tested sets are summarized in Table 2.  
The GCNN model was trained for 100 epochs and \(3\times 3\) windows for spatial and temporal convolutions. In addition, we tested the performance of the GCNN model for detrended and original time series and came to the preference of detrended data, which were also used in all other model specifications.
# Estimating the Optimal Overall Slope Angle of Open-Pit Mines with Probabilistic Analysis
## 3 Results
### Deterministic vs. Probabilistic Analysis
#### 3.1.2 Maximum Shear Strain  
Figure 6 depicts the maximum shear strain at different slope angles. It can be seen that the shear strain increases as the slope angle increases. Also, the probabilistic analysis gives higher values of shear strain compared to deterministic analysis. Figure 7 presents the probability density function (PDF) curves for the obtained shear strain at various overall slope angles.  
Figure 6: Maximum shear strain at different overall slope angles (deterministic vs. probabilistic analysis).
# Black Loaded Columns--State of the Art Review
## 1 Introduction  
In the last five decades, terrorist attacks have become more frequent. There are different types of terrorist attacks, but according to data provided by the National Consortium for the Study of Terrorism and Response to Terrorism [1], in the last two decades, explosive attacks exceed 50% of the total number of incidents, shown in Figure 1. The attacks on The Twin Towers of the World Trade Center on 11 September 2001 and bridges in California and New York have an impact on the design of structures in the United States and also in the rest of the world [2]. In every country, the transportation system is essential for performing everyday activities, so the Blue Ribbon Panel (BRP) indicates the transportation system as one of the viable targets for a bombing attack. Due to a large number of bridges worldwide, lots of potential casualties, high repair costs, and importance in everyday life, the bridges are increasingly in the focus of terrorist attacks. This is confirmed by the fact that in the last few attacks in Nigeria in 2020, seven bridges were destroyed. It is important to identify which bridges are vulnerable due to their easy accessibility to protect against attacks. Moreover, BRP states that the columns are one of the most critical components on all types of bridges [3]. As there are many types of bridges and many ways to attack the bridge, it is difficult to predict the construction's response to the blast loadings [4]. When detonation of an explosion is under the bridge, then columns are exposed to large lateral forces, depending on standoff distance, which can result in large deformations leading to flexural or shear failures. The contact explosion can breach the column to render it incapable of supporting the dead loads. For small standoff distance, blast waves can cause a serious reduction in a concrete cross-section in terms of spalling and cratering. Since the column failure depends on the position and amount of explosives, all examined attack scenarios were observed.  
The main objective of this review article is an extensive literature overview of experimental and numerical research conducted on blast-loaded columns. Both building and bridge columns are considered due to differences in their static and blast behavior. A systematic summary is given of column behavior, possible damage and failure modes, and a review of software used for blast load simulation and analysis.
Consequently, regulatory decision-making in environmental monitoring campaigns will improve dramatically due to the 95% probability of the expected concentration levels [22; 23]. Furthermore, the integration of solid-phase extraction (SPE) with high-resolution technologies, such as UHPLC-Orbitrap HRMS, offers several advantages for the detection of low concentrations of pesticides in environmental water samples [25; 26; 27; 28]. SPE can achieve high preconcentration factors and sample purification, thereby enhancing the sensitivity of the method for detecting such compounds [25; 28]. This capability is particularly important for the analysis of complex environmental matrices, such as aquaculture water, where the presence of co-eluted compounds can affect the chromatographic profile of the analytes [25; 26; 29]. Simultaneously, UHPLC-Orbitrap HRMS provides unparalleled resolution and precision, enabling rapid and consistent sample analysis [6; 30]. Consequently, the combination of these technologies ensures exceptional method detection and quantification levels, rendering this approach ideal for monitoring environmental contaminants in sensitive ecosystems. The overall goal of the present study was to validate a simple, efficient SPE-LC-HRMS-based protocol for the successful and accurate determination of contemporary pesticides in freshwater and seawater and to address the measurement uncertainty. To this end, the specific objectives of the study were as follows: (a) to optimize critical factors involved in sample preparation, including extraction cartridges, elution solvents, and sample pH,to enhance recovery and reduce interference, (b) to establish a robust HRMS method for the accurate quantification of targeted pesticides in water samples, (c) to perform a comprehensive validation according to regulatory guidelines considering a range of pesticide concentrations relevant to environmental monitoring, (d) to quantify measurement uncertainty including all contributing factors, and (e) to ensure the applicability of the method by analyzing a diverse set of water samples and assessing at the same time the prevalence and concentrations of the selected pesticides in the sampling area for the first time.
## 1 Introduction
The strength of the Magefreehome algorithm lies in its selective use of pixel values filtered by the threshold rather than processing all pixels in the image. This selective approach significantly enhances image processing efficiency. However, despite its high segmentation efficiency, the Magefreehome algorithm has three primary drawbacks:1. Ineffective segmentation of the foreground across diverse image backgrounds. 2. Suboptimal performance when the image center point lies outside the target area. 3. High sensitivity to noise and reduced robustness in determining the start and end points of the segmentation area. To address these issues, this study proposes the following solutions:
1. Dynamic Thresholding for Background Adaptation  
The fixed threshold in the Magefreehome algorithm is replaced with a dynamic threshold to improve foreground segmentation across varying image backgrounds. The optimal dynamic threshold is first determined using the OTSU algorithm, which is then applied to binarize the image, allowing for adaptation to different backgrounds and reducing their influence. Additionally, a shadow detection mechanism is introduced to identify shadows; if shadows are detected, the start and end points of the segmentation foreground are reset. This refinement improves precision and recall by 8.00% and 8.42%, respectively, without affecting processing speed. 2. Improved Image Center Point Selection  
To resolve the issue of suboptimal segmentation performance when the image center falls outside the target area, an improved method for selecting the image center point is proposed. This method calculates multiple reference center points to determine the optimal center point of the image. This enhancement improves precision and recall by 5.17% and 1.18%, respectively, while maintaining the same processing speed. 3. Noise-Resilient Start/End Point Determination  
To mitigate the sensitivity to noise when determining the start and end points of the segmentation foreground, a method based on continuity detection is proposed. This method leverages the characteristic that pixels within the segmented region generally have similar grayscale values while the region's boundaries exhibit grayscale discontinuity. It detects the continuity of coordinates with a grayscale value of 255 in rows and columns to identify the presence of noise. If noise is detected, the segment with the highest number of continuous coordinates is selected as the target region, and its endpoints are set as the start and end points of the segmentation foreground. This approach enhances precision and recall by 6.61% and 5.71%, respectively, without impacting processing speed. The remaining components of the paper are structured as follows: Section 2 discusses related work, Section 3 details the proposed method, Section 4 presents the experimental results, analysis, and significance, and Section 5 concludes the paper.
# Fast Reconfigurable SOA-Based Wavelength Conversion of Advanced Modulation Format Data +
## 2 Theory  
### Phase Noise and FWM  
Consider two pumps with electric field intensities given by \(\overset{\rightarrow}{E}_{p2}\) and \(\overset{\rightarrow}{E}_{p1}\) mixing with a signal having an electrical field intensity of \(\overset{\rightarrow}{E}_{s}\), generating an idler through FWM with a field intensity of \(E_{i}\). Let the frequencies of the mixing pumps and the signal be represented as \(\omega_{p1}\), \(\omega_{p2}\), and \(\omega_{s}\), respectively. Let the phase of the mixing pumps and the signal be represented as \(\phi_{p1}\), \(\phi_{p2}\), and \(\phi_{s}\) respectively. The frequency and the phase of the idler are related to the mixing frequencies by,  
\[\omega_{i}=\ \omega_{p2}-\ \omega_{p1}+\ \omega_{s} \tag{1}\]  
\[\phi_{i}=\ \phi_{p2}-\ \phi_{p1}+\ \phi_{s} \tag{2}\]  
Figure 1: (**a**) A single pump semiconductor optical amplifier (SOA)-based wavelength converter employing one fast tunable pump laser. (**b**) A dual-pump SOA-based wavelength converter employing fast tunable pump lasers where the output wavelengths can be chosen by appropriately selecting the wavelength of the tunable lasers. The wavelengths of the tunable lasers are adjusted by the control signals to the SG-DBR devices. (**c**) Schematic of an all-optical packet-switched network.  
Unless both pumps have correlated phase noise, the phase noise of the idler is related to the phase noise of the mixing frequencies by the following relationship when the phase noise of the mixing frequencies is uncorrelated [16; 30],  
\[\Delta\sigma_{i}^{2}=\Delta\sigma_{p1}^{2}+\Delta\sigma_{p2}^{2}+\Delta\sigma_{s }^{2} \tag{3}\]  
where \(\Delta\sigma^{2}\) represents the variance of the phase noise. For white frequency phase noise, the linewidth (represented by \(\Delta\omega\)) and the phase error variance are linearly related [37]. Therefore, the linewidth of the idler due to white phase noise is related to the linewidth of the mixing pumps and the signal by,  
\[\Delta\omega_{i}=\Delta\omega_{p1}+\ \Delta\omega_{p2}+\ \Delta\omega_{s} \tag{4}\]  
Thus it can be observed from Equation (4) that the phase noise of the idler will be the sum of the phase noise of the mixing frequencies.
## 1 Introduction  
Composite materials are widely used in several engineering applications, including biomedical [1], aerospace [2], and specific electromagnetic [3; 4]. For the researchers composites are especially interesting because their features drastically depend on the preparation technique and the initial compounds' properties [5; 6; 7]. Another appealing aspect is the theoretical and numerical modelling of composites as ordered, for instance layered [8; 9], corrugated [10], or disordered [11; 12] media.  
Composites filled with more than one type of inclusions, or hybrid composites, have received a good deal of attention in recent decades [13; 14; 15]. This is because, on the one hand, the combination of fillers provides the multifunctional materials with advanced properties in comparison with one-type filled conterpartners [16; 17]. On the other hand, the interaction between fillers may determine the synergetic effects [18; 19]. In the case of multi-walled carbon nanotubes (MWCNT), the frequent choice of the second filler is graphene nanoplatelets or graphene oxide [20; 21; 22; 23], which allows the combination of different shielding properties [24]. At the same time, composites filled with a combination of carbonaceous and inorganic inclusions have been given less recognition [25; 26].  
In the meantime, for practical applications, the high hardness, good wear and corrosion resistance of ceramics matrices are important (for example alumina, Al\({}_{2}\)O\({}_{3}\)), which makes them attractive for further investigations. In particular, it has been demonstrated that MWCNT/alumina phosphate composites show advanced thermal, mechanical, and electrical properties in comparison with polymer-based composites [27; 28].  
The addition of SiC nanoparticles results in substantially improved mechanical properties of ceramics [29]. Ceramics with SiC also exhibit good microwave shielding properties [30].  
However, the investigations of the electromagnetic properties of hybrid ceramics with carbon and SiC nanoinclusions are rather rare [31]. The aim of this paper is to investigate the electromagnetic properties of aluminium phosphate-based ceramics with carbon nanotubes (CNT) and SiC nanoinclusions and to find the synergy effect, if any.  
The paper is organised in the following way: firstly we discuss in detail the sample preparation procedure; next the dielectric permittivity of the hybrid and one-component samples in wide frequency range is presented with the focus on the comparison at low frequencies. Finally, we present the numerical approach for the shielding properties calculation for the free-standing film in the GHz range and compare the results with experimentally measured data. The impact of SiC loading is discussed both for the low frequency and GHz ranges.
# Projection-Based Augmented Reality Assistance for Manual Electronic Component Assembly Processes
## 3 Proposed Method
### Setup  
The proposed system consists of four different parts: an illumination system, a 2D high-resolution image acquisition setup, a screen and a projector (see Figure 2). The illumination system, the camera and the projector must be located at sufficient height in order to not disturb the operator during manual operation. Given user experiences and comments, the minimum ergonomic height settled on was 600 mm. A 12 mega-pixel camera is at the center of the illumination system, at a height of 700 mm. This positioning, combined with the optical lens, offers a field of view of 500 \(\times\) 420 mm. A PCB's maximum size was established to 320 \(\times\) 400 mm, which is covered by the proposed setup.  
The projector model used is conventional, more specifically, an Optoma ML750e, which uses LED technology and has a light output of 700 lumens. It is not a very powerful projector, but it has proven to be sufficient (Section 3.6.2), and, in return, thanks to its small dimensions, it has allowed us to achieve a fairly compact setup. It is positioned next to the camera, covering all the field of view of the camera.  
Figure 1: Pipeline of the system.  
The screen is in front of the operator, hopefully at the most ergonomic position. The screen shows the outputs and feedback of the proposed system. It is a complementary visualization, since this output is also shown directly on the board using the projector.
# Real-Time, Content-Based Communication Load Reduction in the Internet of Multimedia Things
## 4 Results
### Evaluation Parameters
#### 4.2.1 Data Sent
The amount of data is very low on average, no doubt because of the limited size of the ROM. For this video, another pattern is noticeable, one different from that of Figure 7a. For a few consecutive frames, values of data transmitted remain almost the same but change shortly afterwards, depending upon how much change is detected. Here, the proposed method has its minimum value approximately at \(\approx\)0.003 kB whereas, for the complete frames method, minimum data value is \(\approx\)21.28 kB. Clearly, for this type of video with relatively small ROMs in each frame, the proposed method can consistently reduce the amount of data transmitted. On the contrary, if Figure 7d is considered, markers for both methods are plotted near to one another. Data are reduced to some extent but not by a large margin. The reason here is the presence of more motion in the video sequence, as compared to the three previous videos. Similarly, in Figure 7e, the video sequence, Football, has again more motion. Although data values for the proposed method are lower than the All Frames method, due to smaller differences between frames, the line plots can barely be distinguished. Figure 7d,e show the results for videos with large motions and, thus, the identified ROMs are large in extent. As a result of more motion, the proposed method shows data values slightly lower or equal to the All Frames method. Comparisons in Figure 7, show that the proposed method results in lower amounts of data sent for most frames, even though the difference in quantity is small for those video sequences in which there is motion across a significant extent of each frame. The reader can judge whether their application will benefit from the proposed method. As many applications in the broad category of surveillance or monitoring by an IoMT do not have large areas of motion occurring for a long time, one can argue that the proposed method has considerable value, though relaying a sports' event may not be one of those applications.
## 4 Results and Discussion
### Overall Weights  
As shown in Figure 8, in the total weight analysis, Property Protection (C24, 0.1894) is considered the most important factor, indicating that ensuring the security of users' financial assets is the most significant factor for medical websites. This is followed by Credibility (C21, 0.1852), which emphasizes the critical importance of establishing and maintaining users' trust in medical websites. Privacy Protection (C22, 0.1194), ranking third, highlights the importance of safeguarding users' personal data, a key component that cannot be overlooked for medical websites. Effectiveness (C1, 0.0932) and Findability (C16, 0.0579), ranking fourth and fifth, respectively, stress the importance of the efficient delivery of medical information and services and their accessibility to users. Effectiveness focuses on whether services meet the actual needs of users, while Findability concerns whether users can easily locate the information and features they need. Lower-ranking indicators, such as Screen Design and Layout (C10, 0.0018), Consistency (C11, 0.0032), and  
Figure 6: B3 level weights.  
Figure 7: B4 level weights.  
Interactivity (C13, 0.0039), performed poorly. The low importance of these indicators might suggest that, although they have some impact on the overall user experience, they are not the primary factors considered by users when assessing the usability of medical websites.  
These findings provide valuable insights for the future design and improvement of online medical platforms. To enhance user satisfaction and overall website usability, developers and designers should focus on these high-weight indicators. Balancing and optimizing these factors will help create safer, more trustworthy, and user-friendly medical websites.
# Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey
## 3 Network Structure  
Protocols belonging to the network structure scheme are classified in two subcategories according to whether the nodes are treated as equals or whether they are members of a hierarchy. These subcategories are: Flat and Hierarchical protocols as described below.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Protocol** & **Advantages** & **Disadvantages** & **Scalability** & **Mobility** & **Routing** & **Robustness** \\ \hline SPIN [35] & It is energy efficient and reduces redundant data. & It is not suitable for constant data delivery applications. & Good & Supported & Single hop routing used. & Good \\ SPIN-PP [36] & It is simple, avoids implosion and has small set-up cost. & The data delivery is not guaranteed. & Good & Supported & Single hop routing used. & Good \\ SPIN-EC [36] & It considers energy constrains and adapts its operation. & The nodes below the energy threshold can receive ADV or REQ messages thus & Good & Supported & Single hop routing used. & Good \\ SPIN-BC & It utilizes cheap one to many communications. & It is a waiting time before sending the REQ messages. & Good & Supported & Single hop routing used. & Good \\ SPIN-RL [36] & It has path loss tolerance. & It is time consuming. & Good & Supported & Single hop routing used. & Good \\ \hline \hline \end{tabular}
\end{table}
Table 3: Synopsis of Communication Model protocols of the Negotiation based subcategory.