esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
### Design Requirements  
This paper randomly selected 132 people who had the intention to buy interior decoration items and conducted a questionnaire survey on them. An amount of 132 questionnaires were issued, and 126 were returned and valid. The questionnaires were analyzed in the following words. The research question is the demand analysis of the respondents on the VR technology interior decoration interaction design system.  
Figure 4 shows the relevant data of the respondents' understanding of AI and VR technology and their expectation of their application in the interactive design of interior decoration.  
According to Figure 4a, 19 respondents were very familiar with AI and VR technologies, accounting for 15.08%; 38 respondents quite understood them, accounting for 30.16%; 52 respondents understood them, accounting for 41.27%; 13 respondents did not know much about them, accounting for 10.32%; four respondents had never heard of AI and VR technology, accounting for 3.17%. In view of the fact that a small number of respondents did not know these technologies very well, this paper carried out corresponding science popularization for the respondents in this part, and then we conducted further investigation.  
According to Figure 4b, 43 respondents very much expected AI and VR technologies to be applied in the interactive design of interior decoration, accounting for 34.13%; 47 respondents relatively expected the technologies, accounting for 37.30%; 32 respondents  
Figure 4: Understanding and expectation. (**a**)—Degree of understanding; (**b**)—Degree of expectation.  
generally expected the technologies, accounting for 25.40%; four respondents did not very much expect this, accounting for 3.17%; none of the respondents did not totally expect this. It can be seen that the combination of AI and VR technologies with the interactive design of interior decoration had met the expectations of most people.  
Table 1 shows the specific types of data related to respondents' desire for AI and VR technologies to be used in interior decoration.  
It can be seen from Table 1 that 35 respondents hoped that AI and VR technologies could be applied to furniture for interior decoration, accounting for 27.78%; 33 respondents wanted to apply them to wallpaper, accounting for 26.19%; there were 28 respondents who wanted to apply them to the floor, accounting for 22.22%; there were 12 respondents who wanted to apply them to the ceiling, accounting for 9.52%; 10 respondents hoped to apply them to decorative paintings, accounting for 7.94%; eight respondents also hoped to apply them to other items, accounting for 6.35%.
# 5G New Radio Open Radio Access Network Implementation in Brazil: Review and Cost Assessment
## 2 Background
### Open RAN Architecture
#### 2.2.5 Resource Utilization  
Another key consideration is the effective utilization of network resources, such as spectrum and computing power.  
The centralized management and coordination in c-RAN and v-RAN can enable a more efficient use of resources through joint optimization and dynamic allocation.  
Open RAN, with its distributed architecture and potential for a more diverse ecosystem, may introduce challenges in coordinating resource utilization across the different components, potentially leading to suboptimal performance.  
In contrast, localized decision making in the d-RAN architecture can limit overall optimization of resource utilization across the network.
## 3 Results and Discussion
The contact results revealed the frictional stress (0.251 MPa at the D3 tune) and contact pressure (1.208 MPa at the D3 tune) between the bridge and soundboard and the outputs related to contact results were seen to increase from the B2 (Si) tune to the D3 (Re) tune. Lateral sliding (in the Z direction) of the bridge on the soundboard was also observed (0.022 mm at the D3 tune). It was interpreted that the contact results did not disturb the sound occurrence. Numerical data supported the graphical expressions of the simulation outputs, and soundboard deformation by settled tunes and contact results between the bridge and soundboard are given in Figures 6 and 7, respectively. Figure 5: Simulation visual outputs of the deformation and stress distribution. Figure 6: Simulation numerical outputs of the maximum deformation and stress values. Figure 7: Simulation numerical outputs of the contact results between bridge and soundboard. In a stress analysis, calculating the factor of safety (FoS) is crucial for ensuring the structural integrity and safety of a component or structure under expected loading conditions. In this regard, the FoS of the components and the strings were calculated. The results indicated that there was no evidence of failure on the components and the strings in consideration of the failure threshold of the related materials. A minimum FoS of 2.95 and 1.34 for the bridge (at the D3 tune) and lower string group (at the D3 tune) were calculated, respectively. Additionally, reaction forces acting on the components where string tension has a major effect were extracted from the simulation results. FoS calculations and reaction forces of the components are given in Tables 4 and 5, respectively. Another concern is the choice of material for the instrument. Past experiences have shown that the texture of the wood used in constructing string instruments plays an important role in determining the sound quality, in addition to the instrument's shape. The study discussed in this paper assumes a linear material model in the simulation, and therefore does not take into account how changes in the acoustic features are affected by the texture of the material. However, this aspect could be explored in future studies. Using FEA is a valuable way to understand how materials behave in structural analyses. However, it is important to note that simulations based on numerical methods only offer an approximate representation of real-world phenomena. As such, it is crucial to carefully assess how well the results of simulation studies reflect actual physical conditions. The most reliable way to validate these simulation results is to correlate them via experimental testing. Regarding the final evaluation of outputs obtained from the simulation study, several factors were taken into account. These included unexpected and unpredictable dynamic
## 3 Results  
### Speaker Test  
Figure 6 shows the estimated azimuth (left) and elevation (right) of the replayed vocalizations in Experiment 1 (top) and 2 (bottom). A red line represents the expected value. Each box plot represents the distribution of localized values when the microphone array was placed \(x\) m from the loudspeaker. In Experiment 1, the expected azimuth and elevation angles were 0 degrees. The errors of observed azimuth were equal to or less than 5 degrees when the distance was equal to or less than 50 m. The errors of observed elevation were equal to or less than 10 degrees except in the case of 15 m distance. The slightly larger error when the distance = 15 m was expected to be due to the vocalization of another species (Brown-eared Bulbul (_Hypspietes amaurotis_)). The large error when the distance = 0 m is expected to be due to that the DOA substantially became different among localized sounds because they can change drastically even with small noise if the microphone is right under the loudspeaker. Thus, both the elevation and azimuth angles of replayed vocalizations were successfully estimated in this experiment.  
In Experiment 2, the expected azimuth was 0 degrees, while the expected elevation decreased inversely proportional to the distance of 90 degrees, as shown in Figure 6 (bottom right). The errors of the observed azimuth were equal to or less than 5 degrees until the horizontal distance was equal to or less than 35 m, while it became larger than Experiment 1. This result was expected because the net distance between the microphone and the loudspeaker was larger. This was also expected because other species were vocalizing in the same direction as the speaker, causing the localization of replayed sounds to deviate from the expected value, which was sometimes observed in Experiment 2.  
The observed elevation also reflected well the expected value; it decreased inversely proportional to the distance and errors were less than 15 degrees, except in some cases (e.g., 15 or 40 m away). We expect that the errors can be reduced if we adopt a transfer function with a higher resolution of elevation angles.  
Overall, we were able to correctly estimate both the elevation and azimuth of bird vocalizations even when the songs were far away from the microphone array, if there were no other vocalizations or sounds in the similar direction as the target sounds.
# Electrochemical Ion Pumping Device for Blue Energy Recovery: Mixing Entropy Battery
## 5 Intercalation Materials as Cathode Electrode in MEB  
The behavior of a battery is based on the redox reactions which take place on the surface of the electrodes. The equilibrium potential of these reactions depends on the concentration of the electroactive components in the electrolyte solution, which ideally follows a Nernstian response, so that the change of the solution leads to the voltage rise that can be exploited for the energy extraction [1].  
Valid candidates to replace the \"sodium-capturing electrode\" have been found in the PBA family. These materials have an open crystal structure composed of a face-centered cubic setting of transition metal cations octahedrally coordinated to hexacyanometallate groups. Large interstitial \"A sites\" within the structure can accommodate zeolitic water or alkali insertion ions. This results in a general chemical formula of \(\mathrm{A_{x}P[R(CN)_{6}]_{1-y}\cdot nH_{2}O}\), where A is an alkali cation, P is the N-coordinated transition metal cation, \(\mathrm{R(CN)}_{6}\) is the hexacyanometallate anion and represents a hexacyanometallate vacancy. Both the N-coordinated and C-coordinated transition metals can be electrochemically active in this structure. The PBA framework structure has wide channels between the A sites, allowing for the rapid insertion and removal of monovalent and multivalent cations. Some researches verify intercalation of \(Na^{+}\), \(Li^{+}\), \(Mg^{2+}\), \(Cu^{2+}\), \(Al^{3+}\) and \(NH_{4}{}^{+}\) in PBA [7; 8; 36; 37; 8].  
The principal cathode materials, based on PBAs tested in the MEB, are Cobalt Hexacyanoferrate (CoHCF) [23], Nickel Hexacyanoferrate (NiHCF) [27; 39] and Copper Hexacyanoferrate (CuHCF) [7; 8; 11; 13; 18] to capture \(Na^{+}\) ions from seawater. The use of materials in the PBA family in MEBs is an advantage, because most are low-cost cathode materials [40].
# Effect of Heat Treatment on Some Titanium Alloys Used as Biomaterials
## 2 Materials and Methods
### Heat Treatment  
Some characteristics can be achieved with the help of thermal treatments known under the generic name of annealing. They are applied to semi-finished products obtained by casting, hot or cold plastic deformation (free forging or in a mold, lamination, extruding, drawing), or welded (metal constructions, machine parts, complex tools). The heat treatment for the Ti-Mo-Zr-Ta alloys has been realized using the IU 72/1F 2 RV 60 \(\times\) 60 \(\times\) 40 10 bar CP type I vacuum furnace (IVA Schmetz GmbH, Menden, Germany) [23]. The hot zone, heat exchanger, high-capacity radial fan with an electric motor, and gas conduits are all included within the casing. The furnace's loading and unloading are done from the front using a rail-guided loading car to precisely place the cargo into the hot zone, as presented in Figure 1.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multicolumn{1}{c}{\multirow{2}{*}{**Alloy**}} & \multicolumn{4}{c}{**Average Chemical Composition (wt.\%)**} \\  & **Ti** & **Mo** & **Zr** & **Ta** & **Si** \\ \hline Ti15 Mo7 Zr15 Ta & 73.85 \(\pm\) 0.3 & 9.00 \(\pm\) 0.1 & 7.15 \(\pm\) 0.2 & 10.00 \(\pm\) 0.2 & - \\ Ti15 Mo7 Zr15 Ta0.5 Si & 66.50 \(\pm\) 0.1 & 11.00 \(\pm\) 0.2 & 7.00 \(\pm\) 0.3 & 15.00 \(\pm\) 0.1 & 0.50 \(\pm\) 0.3 \\ Ti15 Mo7 Zr15 Ta0.75 Si & 66.20 \(\pm\) 0.1 & 9.00 \(\pm\) 0.3 & 7.00 \(\pm\) 0.1 & 17.00 \(\pm\) 0.3 & 0.80 \(\pm\) 0.3 \\ Ti15 Mo7 Zr15 Ta1 Si & 73.00 \(\pm\) 0.1 & 10.00 \(\pm\) 0.2 & 8.00 \(\pm\) 0.1 & 8.00 \(\pm\) 0.2 & 1.00 \(\pm\) 0.3 \\ Ti20 Mo7 Zr15 Ta & 58.35 \(\pm\) 0.1 & 19.00 \(\pm\) 0.2 & 8.15 \(\pm\) 0.1 & 14.50 \(\pm\) 0.3 & - \\ Ti20 Mo7 Zr15 Ta0.5 Si & 59.25 \(\pm\) 0.2 & 18.50 \(\pm\) 0.3 & 7.00 \(\pm\) 0.1 & 14.80 \(\pm\) 0.1 & 0.45 \(\pm\) 0.1 \\ Ti20 Mo7 Zr15 Ta0.75 Si & 57.86 \(\pm\) 0.1 & 19.50 \(\pm\) 0.1 & 6.85 \(\pm\) 0.1 & 15.04 \(\pm\) 0.3 & 0.75 \(\pm\) 0.1 \\ Ti20 Mo7 Zr15 Ta1 Si & 57.23 \(\pm\) 0.1 & 19.83 \(\pm\) 0.3 & 6.93 \(\pm\) 0.1 & 14.98 \(\pm\) 0.2 & 1.03 \(\pm\) 0.1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Chemical composition for Ti-Mo-Zr-Ta alloys obtained.  
Figure 1: Horizontal high-temperature vacuum chamber furnace: (**a**) furnace front-view, (**b**) furnace set-up, (**c**) furnace chamber and sample holder.  
After loading, the swiveling furnace door will be hydraulically fastened to the furnace casing to prevent overpressure. After that, the treatment cycle runs completely on its own [14]. The furnace has an operating system that allows the user to program each treatment step, considering factors such as temperature, cooling rate, gas pressure, ventilation etc.
# Low-Cost Digitalization Solution through Scalable IIoT Prototypes
## 2 State of the Art
On the other end of the spectrum, many more works have explored small microcontroller-based boards as a means for digitizing machines with IoT. In contrast with the solutions provided by the leading automation companies, these boards provide a low-cost way to digitize, although they sacrifice many features that mature solutions deliver. However, they are very interesting from the point of view of this research, as they mitigate one of the biggest obstacles and fears the decision makers have when facing Industry 4.0 adoption. Various works use Arduino boards, and the applications are covering diverse topics and areas. This type of approach is researched at length for home automation, such as [42; 43; 44; 45]. There are also several works coping with the use of Arduino in an industrial setting. The applications are numerous, monitoring the humidity and the temperature in industrial storage rooms [46], a remote bio-gas monitoring system [47], a monitoring system for renewable energy generation facilities [48], and real-time monitoring of photovoltaic systems [49]. All these works have been proposing the utilization of Arduino boards as a low-cost solution for sensor control in data gathering. In the work of [PERSON] et al. [50], three different retrofitting applications have been presented in the manufacturing sector. Two of the machines were retrofitted with Arduino boards while in the third one, a Raspberry Pi was used. Additionally, pairing Arduino as a data-gathering system with Raspberry Pi was considered by several authors. Their presented architectures use the Raspberry Pi as a communication link and the data transmission hub [51; 52; 53; 54]. The reason behind the inclusion of the Raspberry Pi board is that the microcontrollers often lack the power necessary for applications that require higher processing power.
# Inverse Multiscale Discrete Radon Transform by Filtered Backprojection
## 2 Proposed Method
### Characterization of the Impulse Responses  
The next step before inverting the direct Radon transform is to completely characterize the impulse response of the operator conformed by the direct transform together with the just defined extended backprojection.  
The most favorable case would be that, regardless of the location of these impulses, the response would be the same, only shifted. In that case it would be a time-invariant system that if it were in addition lineal--which it is in our case--it would allow to be quickly deconvolved dividing by the Fourier transform of the impulse response.  
Unfortunately, the impulse responses change with the position in our case. The different responses are produced by how the different discrete lines travel the initial impulse depending on its position, because these same lines will be the ones that the backprojection transform returns. A single point--the isolated impulse to characterize--on the original image will be projected to exactly one displacement per angle, and will give rise to a line in the backprojection algorithm. All those lines (\(4\cdot N\), one per angle) will be backprojected and will intersect at the original point location. This accumulation of lines around the impulse will not be homogeneous nor the same in all positions of the input image because the definition of the lines yield non-straight lines.  
Figure 3: Depiction of how initial DRT values map to a 4 times bigger DRT. A few dashed lines on the left are represented on Radon slope-displacement space on the right. On green, initially contiguous values in slope with incrementally decreasing displacement, map to slopes at distance four and with double displacement increments, on a 4 times bigger DRT, on blue. Moreover, the blue originally odd slopes get an additional increase of 3 in slope, and 2 in displacement that will be discussed later.  
The digital lines of the DRT are 'broken' lines (concatenation of line segments that approximate the line of desired slope) that avoid interpolation and that internally are the key to accelerate the algorithm since their recursive formula is fundamental to the divide-and-conquer approach. Therefore, it cannot be discussed if the non-uniformity of this lines can be relaxed, smoothed, as this is the heart of the method. The work that has to be done is to study how variable are these discrete impulse responses that the 'broken' lines give place to, and, in spite of this heterogeneity, how much the deconvolution can be accelerated even though the system is not properly LTI. That study is carried out in the next section.
## 3 Results and Discussion
### Fatty Acid Composition  
In the studied hams, a low content of polyunsaturated fatty acids (PUFA) was characterized from 5.40% to 9.55% after production (Table 3). The highest PUFA content was in the control hams. After 8 months of storage, the sum of PUFA decreased in the control hams, while it did not change in the hams with apple vinegar, and it increased in the hams with acid whey. PUFAs are particularly susceptible to oxidation [80; 81]. This can be related to the results of TBARS (Table 1). The difference can be explained by the additional antioxidative compounds delivered with acid whey and apple vinegar. Cysteine is the abundant amino acid of acid whey characterized by antioxidant properties that would have inhibited PUFA oxidation [82]. In vinegar, the antioxidant activity is related to the phenolic content. The acidic environment stabilizes vinegar polyphenols, increasing their antioxidant activity [15]. This is concordant with the results of [PERSON]'s salted beef fermented sausages with or without the addition of acid whey. The content of PUFA in beef sausages with acid whey after 21 days of ripening was higher in comparison with salted samples. The antioxidative effect was enhanced by the acid whey protection of haem iron loss during meat ripening [15]. The n6/n3 ratio in the studied beef hams ranged from 1.84 (A variant after production) to 3.00 (AW variant after 8 months storage). The n-3 and n-6 fatty acids are crucial fatty acids for the human diet. Many studies have shown that the consumption of food containing n-3 and n-6 fatty acids is associated with a decreased risk of cardiovascular disease, insulin resistance, lipid profile, and obesity [83]. Research indicates that the balance between n-6 to n-3 polyunsaturated fatty acids (PUFA) in the diet is crucial in preventing atherosclerosis and metabolic disorders [84]. The optimal ratio in the human diet of n-6/n-3 PUFA is considered to be 5:1 [85]. The A ham variants, after 8 months of storage, had a ratio of 4.56, which was higher than C and AW treatments.
# Energy Consumption Model for Sensor Nodes Based on LoRa and LoRaWAN
## 5 LoRa and LoRaWAN Technologies
### LoRa Modulation Technique  
#### 5.2.1 LoRa basics  
The LoRa radio has different configuration parameters: the carrier frequency, the spreading factor, the bandwidth and the coding rate [9; 10]. The combination of these parameters provides different energy values and transmission ranges:  
* Carrier Frequency (_CF_): The CF is the center frequency used for the transmission band. For the _SX1272_ transceiver, _CF_ is in the range of 863 MHz to 870 MHz in Europe.
* Spreading Factor (_SF_): The _SF_ is the number of chips per symbol. Its value is an integer number between 6 and 12. The greater value of _SF_, the more capability the receiver has to move away the noise from the signal. Thus, the greater value is taken, the more time is taken to send a packet.
* Bandwidth (_BW_): The _BW_ represents the range of frequencies in the transmission band [16]. It can only be chosen among three options: 125 kHz, 250 kHz or 500 kHz. If a fast transmission is required, a 500 kHz value is better. However, if a long range is needed, a 125 kHz value must be configured.
* Coding Rate (_CR_): The coding rate expression is \(CR=\dfrac{4}{4+n}\), \(n\) is from 1 to 4. It denotes that every four useful bits are encoded by 5, 6, 7 or 8 transmission bits. The smaller the coding rate is, the higher the time on air is to transmit data.  
The nominal bit-rate (in bits per second), is obtained taking into account these parameters. The expression of the bit-rate is given in Equation (13):  
\[R_{bit}=SF\cdot\dfrac{BW}{2^{SF}}\cdot CR \tag{13}\]  
Table 2 presents the chirp packet length based on the _SF_ parameter. Modifying this parameter provides a trade-off between increasing the communication distance and decreasing the data transfer rate. Each symbol is spread through a chirp code whose length is \(2^{SF}\). The receiver divides the received code into \(\frac{2^{SF}}{SF}\) length blocks which can be then decoded.
# An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks
## 4 Data Link Layer Design  
The link layer architecture proposed in this paper comprises multiple interrelated components: network topology, ASFS algorithm, LoRa parameters calculator, MAC protocol, and the adaptive data link (ADL) mechanism. These components are described with more detail in the respective subsections. Figure 1 shows where the components that are executed inside the end nodes and/or the packet forwarders are located.
# CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications
## 3 The RPL and Problem Description
### Route Repair  
To assure the reliability of routing protocol, RPL supports two repair mechanisms, namely local repair and global repair. Local repair is to solve the issue locally instead of repairing the whole network. On the other hand, global repair can only be originated by the root node and fundamentally rebuilds the network topology by increasing the DODAG version number. When a node detects a network inconsistency such as a link/node failure or a local loop in a route, the node triggers the local repair. As a solution, it tries to find out the alternate path through the same ranked nodes although the recovery path may not be the optimal one.