esa-sceva/satcom-chunk-collection huggingface dataset:
# Short-Term and Long-Term Travel Time Prediction Using Transformer-Based Techniques
## 3 Proposed Methodology
### Overall Structure of the Proposed Framework  
Figure 1 presents the architecture of the proposed Short-Term and Long-Term Integrated Transformer (SLIT), which is composed of two main modules: the Enhanced Data Preprocessing (EDP) and the Short-Term and Long-Term Integrated Encoder-Decoder (SLIED). At the beginning, the EDP module refines input historical traffic data \(\mathbf{X}\) into attribute-encoded periodic segments \(\hat{S}\). These segments capture both short-term and long short-term patterns of historical traffic data. They incorporate periodic information, temporal attributes, and positional encodings to extract patterns over various time horizons, thereby enhancing the model's predictive capabilities for diverse time frames. Subsequently, SLIED, a Transformer-based encoder-decoder architecture, processes these enriched segments to generate multi-step travel time predictions \(\hat{Y}\).  
Figure 1: The architecture of the proposed framework.
## 1 Introduction
In this paper, we describe the use of the FEM-DBCI (Finite Element Method-Dirichlet Boundary Condition Iteration) [21; 22] numerical method to perform the computation of coupling factors at low frequency by showing how this method is well suited to this aim. The most attractive property of FEM-DBCI is the possibility of leaving the various coils outside the analysis domain to be meshed, which can then be minimized. Furthermore, the same mesh can be used for all the source coils considered. The well-known FEM-BEM (Boundary Element Method) also shares the properties of mesh minimization and invariance with respect to the change in external coils, but FEM-DBCI is simpler to implement and requires less computing time [23]. This paper is structured as follows. Section 2 briefly recalls the FEM-DBCI method. Section 3 describes how to use it for the calculation of coupling factors. Section 4 reports the results regarding some case study calculations. Finally, the authors' conclusions follow.
## 3 Use Case. CEDER-CIEMAT Microgrid
### Characterising the Efficiency of the Elements of the Microgrid
#### 3.3.4 LFP Batteries: Two Racks with 196 Cells of 3.2 V Each, with a Capacity of 50 Ah  
Repeating the same process for Lithium Ferro-Phosphate batteries produces the values shown in Table 6.  
The efficiency of these batteries varies between 58 and 62%, with a higher efficiency observed at higher discharge powers (limited to 20 by the inverter). An average efficiency of 60% is considered.  
Table 7 shows a summary of the average performance of each dispatchable generation source and storage system connected to the CEDER-CIEMAT microgrid.  
With these values and according to the methodology defined in this paper, priority will be given to the use of PEPA I lead-acid batteries, followed by PEPA II lead-acid batteries, then LFP batteries, and lastly, the turbine and hydraulic pumps, which, in addition to  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Discharging** & **Charging** & **Performance** \\ \hline
**Power (kW)** & **Energy (kWh)** & **Energy (kWh)** & **\%** \\ \hline
5 & 25 & 43 & 58 \\
10 & 24 & 40 & 60 \\
20 & 23 & 37 & 62 \\ \hline \hline \end{tabular}
\end{table}
Table 6: LFP battery discharging and charging at different powers.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Discharging** & **Charging** & **Performance** \\ \hline
**Power (kW)** & **Energy (kWh)** & **Energy (kWh)** & **\%** \\ \hline
10 & 152 & 183 & 83.1 \\
20 & 94 & 114 & 82.5 \\
30 & 83 & 100 & 83 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Lead-acid battery PEPA I discharging and charging at different powers.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Discharging** & **Charging** & **Performance** \\ \hline
**Power (kW)** & **Energy (kWh)** & **Energy (kWh)** & **\%** \\ \hline
4 & 102.5 & 124.6 & 82.2 \\
12 & 94.2 & 107 & 88.1 \\
16 & 53.1 & 72.7 & 73.1 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Lead-acid battery PEPA II discharging and charging at different powers.  
having the lowest performance, have much higher operating and maintenance costs than the other systems.  
Normally, LFP batteries would have higher charging efficiency than lead-acid batteries. However, in our case, the opposite happens. This is due to the fact that the PEPA II batteries are new, so it is normal that their performance is higher than the PEPA I batteries, which are about five years old, and the LFP batteries, which are more than 10 years old. It also makes sense that the performance of the hydraulic system is lower, since it is not designed to be optimised but rather depends on the orography of the terrain at CEDER and the available pumps. LFP batteries require less maintenance, are more modular, allow for a higher depth of discharge, and have lower self-discharge and faster charging than lead-acid batteries. In addition, LFP batteries do not emit gases during the charging and discharging process.
## 3 Problem Formulation  
The problem under consideration is to design a transmit waveform matrix \(\mathbf{S}\) so that the power radiation in the sidelobe region can be minimized. Moreover, there are two constraints. The first constraint is the waveform synthesis (WS) constraint, i.e., the transmit waveform matrix \(\mathbf{S}\) synthesizes the desired radar waveform \(\mathbf{x}_{R}\) and the desired communication waveform \(\mathbf{x}_{C}\) in the direction of the radar target and communication users, respectively, as given by Equation (5). The second constraint is the constant modulus constraint which prevents the nonlinear signal distortion in the amplifiers to increase the efficiency of the transmitter. The constant modulus constraint is expressed as  
\[|\mathbf{S}(m,n)|=1,0\leq m\leq M-1;0\leq n\leq N. \tag{6}\]  
The problem can be formulated as an optimization problem given by  
\[\begin{split}\underset{\mathbf{S}}{\text{minimize}}& \parallel\mathbf{A}^{H}\Big{(}\tilde{\Theta}\Big{)}\mathbf{S} \parallel_{F}^{2}\\ \text{subject to}&\mathbf{A}^{H}(\Theta)\mathbf{S} =\mathbf{X}\\ &|\mathbf{S}(m,n)|=1,0\leq m\leq M-1;0\leq n\leq N,\end{split} \tag{7}\]  
where \(\Theta=[\theta_{R},\theta_{C}]\) is the collection of radar and communication direction angles while \(\tilde{\Theta}=[\theta_{1},\theta_{2},\cdots,\theta_{K}]\) is the collection of angles of \(K\) sidelobes.  
The CM constraint Equation (6) renders the optimization problem (7) as non-convex. Being NP-hard, this problem is difficult to solve using any convex optimization methods. The problem (7) can be re-formulated for ease of analysis in two steps: the vectorization step and the realization step.  
Figure 1: System model.
# Performance Analysis of Physical Layer-Based Multiple-Input Multiple-Output on WiMAX (MIMO-WiMAX) +
###### Abstract  
High data transmission rates over wide regions and to clients in locations where broadband service is not accessible are provided by WiMAX, based on IEEE 802.16 standards for Broadband Wireless Access (BWA). The use of several antennas for sending and receiving data is a common feature of MIMO systems in wireless communications. WiMAX-MIMO devices are designed to improve WiMAX system performance. An analysis of MIMO-WiMAX systems using various modulations and coding rates in a Rayleigh fading channel is presented in this work. Matlab software version (R2018a) is used to examine the relationship between bit error rates and signal-to-noise ratios with various cyclic prefixes and single/multiple transceivers. The codes of Alamouti STBC are used to examine the BER performance of MIMO-WiMAX.  
MIMO; STBC; WiMAX +
Footnote †: journal: Engineering Proceedings
# An Application of the Associate Hopfield Network for Pattern Matching in Chart Analysis
## 3 Materials and Methods
### Pattern Representation
#### 3.1.1 Perceptually Important Point  
The well-known segmentation method PIP would be used in our matching approach. There are three variant ways to measure the distance between the adjacent points in PIP, which are the euclidean distance (PIP-ED), perpendicular distance (PIP-PD) and vertical distance (PIP-VD). The results of [PERSON] et al. [3] illustrate that the PIP-VD would be the best choice in terms of efficiency and effectiveness. The PIP-VD can be calculated as follows:  
\[VD(p_{3},p_{c})=|y_{c}-y_{3}|=\Big{|}(y_{1}+(y_{2}-y_{1})\frac{x_{c}-x_{1}}{x_ {2}-x_{1}})\Big{|} \tag{7}\]  
where \(p_{3}(x_{3},y_{3})\) denotes the next chosen PIP, \(p_{1}(x_{1},y_{1})\) and \(p_{2}(x_{2},y_{2})\) are the exiting PIPs and \(p_{c}(x_{c},y_{c})\) is the point in the line between \(p_{1}\) and \(p_{2}\). The schemematic diagram is illustrated in Figure 3:  
Algorithm 1 is the pseudocode for the selection procedure of the PIPs:  
Figure 3: The above subgraph is the demonstration of the PIP-VD measure. A 80 days’ normalized time series data (black line) is represented by 7 extracted PIPs (red points) using PIP-VD.  
```
0: sequence \(S(s_{1},\cdots,s_{m})\), predefined template \(P(p_{1},\cdots,p_{n})\);
0:\(SP\): PIPs with the length of n;
1: Set \(SP_{1}=s_{1}\), \(SP_{n}=s_{m}\);
2:repeat
3: Select point \(S_{j}\) with maximum VD distance to the adjacent points in \(SP\);
4: Add \(S_{j}\) to \(SP\);
5:until \(SP\) is filled.
6:return \(SP\);
```  
**Algorithm 1** Perceptually important point identification with VD measure.
# A New Approach to Estimating the Path Loss in Underground Wireless Sensor Networks
## 4 Results and Discussion
At this location, the CRIM-Fresnel model again provided the least accurate estimation of attenuation (RMSE = 11.58). Both the models based on the Modified-Friis approach were very similar in their estimations. However, similar to locations A and B, the Modified-Friis method with the permittivity estimated from TDR provided a better approximation (RMSE = 1.36) than the conventional Modified-Friis model (RMSE = 1.47), which uses the Peplinski mixing model to estimate permittivity. It should be noted that, although none of the models accurately predict all the measured attenuation values, the Modified-Friis method using permittivity values based on TDR measurements performed equally well, if not better, than the Modified-Friis method using the Peplinski approach to determine the permittivity values. This novel approach will make a significant impact on the community, as the soil does not have to be brought back to the laboratory for assessment, and field-based TDR measurements can be used.
## 5 The Routing Algorithm
### f-Value Update  
This first stage takes place each time a connection between the host and another node in the vehicular network has ended. Since some of the host's features may have changed (such as buffer occupancy, dropping rate, and others), its fitness value has to be recomputed as well. For this, the considered features \(x_{i}\) are obtained in the fitness center, and they are passed through a process of normalization to obtained normalized features \(x^{\prime}_{i}\), according to Equation (5), where \(x\) is a feature that is being transformed, and \(x_{m}\) and \(x_{M}\) are the minimum and maximum registered values of that feature.  
\[x^{\prime}=\frac{x-xm}{x_{M}-x_{m}} \tag{5}\]  
This will give final input values \(x^{\prime}_{i}\), with \(0\ \leq x^{\prime}_{i}\leq 1\), which in turn will make the prediction process more reliable. These normalized values are forward passed through the network, according to Equations (3) and (4) to get the final updated \(f\) value.  
A similar process is executed each time a message is received by the host. Whenever this happens, the \(f\) value of the incoming message is computed according to Equations (3) and (4) in its corresponding neural network. Finally, the message is put in the queue according to its fitness. This way, the message queue is always ready with the messages ordered by the fittest message first.
## 3 IberSpeech-RTVE 2018 Evaluation Tasks
### Multimodal Diarization Challenge  
#### 3.3.1 Challenge Description and Databases  
The multimodal diarization evaluation consisted of segmenting broadcast audiovisual documents according to a closed set of different speakers and faces and linking those segments that originated from the same speaker and face. For this evaluation, a list of characters to recognize was given. The rest of the characters on the audiovisual document were discarded for evaluation purposes. System outputs should give for each segment who was speaking and who was/were in the image from the list of characters. For each character, a set of face pictures and a short audiovisual document were given.  
The goal of this challenge was to start a new series of Albayzin evaluations based on multimodal information. In this edition, we focused on face and speaker diarization. We wanted to evaluate the use of audiovisual information for speaker and face diarization. We encouraged participants to use both speaker and face information jointly for diarization, although we accepted systems that used visual and audio information separately.  
Development and Evaluation Data
* For development, the dev2 partition contained a two-hour show \"La noche en 24H\" labeled with speaker and face timestamps. Enrollment files for the main characters were also provided. Enrollment files consisted of pictures and short videos with the character speaking. Additionally, the dev2 partition contained around 14 h of speaker diarization timestamps. No restrictions were placed on the use of any data outside the RTVE2018.
* For the evaluation, three television programs were distributed, one from \"La Manana\" and two from \"La Tarde en 24H Tertulia\", which totaled four hours. For enrollment, photos (10) and video (20 s) of the 39 characters to be labeled were provided.
# Design of the CIEMAT Corrosion Loop for Liquid Metal Experiments
## 3 CiCLo-C Loop: Requirements and Design
### Main Components and Functioning
The melting tank is located at the bottom of a _glove box_ (GB) [35] and connected to the main tank of the loop by a pipeline with a small inclination that compels gravity filling. The vacuum-stored ingots are introduced inside the GB and opened in Ar atmosphere to avoid oxidation. Located inside the main tank, surrounded by band-barrel heaters, ingots are melted at 350 \({}^{\circ}\)C (melting point: 235 \({}^{\circ}\)C). Once totally heated, the first important step is represented by the purification of the melted material: all the impurities eventually present begin to float on the surface of the molten tank [11; 35]. They are removed with extreme caution before starting the next phase: the filling of the loop draining tank. A ball valve at the bottom of the molten tank opens the PbLi pass to the connection with the draining tank of the loop. Conductive probes located at different heights measure the PbLi level inside it, informing when the tank is starting to fill, half-filled, and completely filled. Once filled, the connection with the GB is closed, the loop is inertly insulated from the rest of the installations, and the second phase, loop filling, can be started. The loop filling is performed with argon pressure; it is adjusted so that the liquid metal starts rising into the loop slowly. Three sensor levels inside the expansion tank are responsible for informing when the loop starts filling (the first one) and is completely filled (the second one). The third one is a safety sensor that has the important role of immediately draining the loop if it is activated by accidental overfilling. The PbLi circulates in a clockwise direction at the selected velocity thanks to the PMP located in one of the corners of the circuit. The _flow meter_ is installed just before the pump to allow the correct measurement of the flow before the liquid metal enters the PMP. Finally, the entire loop, except the test section, will be internally coated with tantalum. The treatment is a gas phase process that is able to coat even surfaces with more complex geometries (e.g., fittings, elbows, and pump channels). All dimensions of the components are suitable to be chemically coated with tantalum. As a result, the stainless-steel tubes gain superb corrosion resistance of tantalum while maintaining the mechanical properties of stainless steel and thus enlarging the durability of the loop itself. Samples of 316 stainless steel covered by tantalum have already been produced and analyzed after several heating cycles, showing no signs of defects or distortions (Figure 7). An SEM microscopy image shows good adhesion with the substrate and uniform thickness. The extremely rugged, uniform, and the inert surface will ensure that all the corrosion impurities are only derived from the degradation of the samples in the test section.
## 1 Introduction
Additionally, the percentage of acceleration allows for determining intensity thresholds specific to an individual player or playing position, avoiding generic values for all players [16, 35]. Similarly, the use of absolute thresholds for the speed profile could underestimate the intensity of actions for slower players and overestimate it for faster players during matches [13, 22, 36, 37]. In conclusion, employing an individualized threshold offers the opportunity to assess the specific demands of each player, reducing errors in quantifying physical performance at different intensities [5, 14]. When quantifying the external load from the acceleration profile, it should be considered that the ability to accelerate largely depends on the initial speed (V0) of the player, with a correlation coefficient of 0.98 between both variables [16]. Each player's maximum possible acceleration progressively decreases as the initial running speed increases [31, 38], and most efforts with high accelerations reach low or moderate maximum speeds [16]. A common mistake is to qualify an acceleration of low or high intensity by referring to an absolute numerical value, without considering the initial speed [31, 39]. Therefore, regardless of the chosen threshold, the intensity of accelerations should be classified based on the initial speed into three sections: walking (0-7 km/h), jogging (7.1-14.3 km/h), and running (>14.4 km/h) [16, 35, 31]. Considering the different tactical roles of different playing positions in soccer matches, recent studies confirm that total distance traveled, maximum speed, high-intensity distance, average speed, sprint distance, and the number of accelerations are related to the playing position [40, 41, 42, 43]. Therefore, just like the quantification method, the playing position might influence the external load of soccer players [38, 44]. This could explain the variability in the speed and acceleration profile based on playing position [45]. Therefore, the main goal of this study was to determine the relative profile based on speed and acceleration in semi-professional soccer players according to their playing position.
# Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs
## 3 Concept of Agriculture 4.0
### Virtualization of an Agro-Food Supply Chain
Agriculture 4.0 technologies refer to production systems that deploy robotics, sensors, and Big Data analytics allowing farmers to manage their farms at detailed spatial and temporal scales [26]. Though precision agricultural technologies have been in use for about a decade and normally take the form of yield monitors in cropping systems and robotic milking parlors for dairy, the step of innovation has picked up since the cost of sensors and robotics has fallen [67]. Nevertheless, the high mobility of production facilities makes planning and control more difficult since the surrounding conditions are not always clear, and communication is often inconsistent due to the low availability and bandwidth of wireless connections. The wireless technologies result to be the most convenient solution in terms of power consumption and communication range in agriculture [23; 26; 64; 76; 77]. Particularly, narrowband-IoT (NB-IoT) is a new IoT system constructed from existing Long-Term Evolution (LTE) functionalities [78]. The NB-IoT enables the interconnection and communication among ordinary objects through many applications in many domains, such as industry-focused applications (e.g., supply chain management, transportation, and logistics) and environment-focused applications, such as in agriculture activities [79]. The design goals of NB-IoT cover high coverage area, extended battery life (about 10 years), high network size (52,000 devices/channel/cell), and low-cost devices [80]. In the future, NB-IoT technologies will take place in agricultural applications due to low power consumption and will be used when the agricultural information is to be communicated over long distances [79]. Another key differentiator among agricultural and industrial supply chains is the amount of the division of work (rationalization effects in the industrial production vs. the small division of labor/workforce in a family environment in agriculture). Furthermore, employees in the industrial sector are highly specialized in their skill levels, while farmers carry out a great variety of responsibilities.
## 2 Proposed Antenna Design
### Evolution of C-Band Notch  
To enhance performance and mitigate interference in the designated UWB frequency range, a notch in the C-band is introduced. By etching a square-shaped CSRR onto the patch's feed line, the desired notching characteristic for the C-band is achieved. The CSRR length can be adjusted to fine-tune the notch. Equation (1) provides the relationship between length and frequency for the notching criterion. As the CSRR lengthens, the notch band moves down in frequency, while a shorter CSRR raises the frequency.  
\[S_{R}=2(a+b-c)=\frac{\lambda}{2}=\frac{c}{2f_{n}\sqrt{\varepsilon_{ref}}} \tag{1}\]This notching formula establishes the relationship between length and frequency for achieving the desired notch characteristics. The square-shaped Complementary Split-Ring Resonator (CSRR) on the patch feed line has a calculated wavelength of \(\lambda\) = 19.4 mm. By introducing this CSRR, the desired notching characteristic is achieved in the specific frequency band of 4.5 GHz as shown in Figure 2. The notching characteristics are helpful to enhance communication reliability and mitigate the interference between the UWB and narrow occupy band.