esa-sceva/satcom-chunk-collection huggingface dataset:
# Applications of the Open-Source Hardware Arduino Platform in the Mining Industry: A Review
## 4 Arduino in Autonomous Mine Systems
[PERSON] and [PERSON] [77] used an Arduino UNO board to develop a CMS based on UAVs. The system was designed as an autorotating surveying system using a single-point LiDAR sensor. A rotating falling body could gather 3D survey data in underground cavities, as shown in Figure 12. To develop the CMS, the Arduino UNO board was integrated with a horizontal facing LiDAR sensor (LiDAR-Lite V2) for surveying the cavity walls during descent and a vertical facing LiDAR sensor (SF30/B) for monitoring the vertical position. In addition, a gyroscope (ADXRS649) and an accelerometer (ADXL345) were used to monitor the angular velocity and acceleration, respectively, along the vertical axis during the flight of the UAV. Figure 13 shows the electronics used for developing the initial prototype autorotating cavity surveyor in Mitchell and Marshall [77]. The system was tested in the laboratory; however, more complicated conditions in a real underground cavity were not considered, such as air currents from ventilation, and harsh humidity and temperature conditions. Figure 12: Operational phases including setup, launch, scanning, and data recovery for a potentially disposable auto-rotating cavity surveying device [77]. (License Number 4851090213631). The deterioration of mineral grades is an important issue to be overcome in the mining industry, as the development of mines has continued over time. To solve this problem, techniques for improving recovery efficiency have been studied. Arduinos are being used in part as an auxiliary role to help with these studies. [PERSON] et al. [78] conducted a study to improve the flotation of copper sulfides inside tailings using ultrasounds. Ultrasound can improve the overall recovery by removing the oxidized layer from the particle surface and aiding in desliming. The 'Denver' flotation cell was modified to control the ultrasound in the flotation test. A calibrated probe designed to measure cavitating acoustic fields converted external mechanical disturbances into electrical signals. These signals were processed through the code input to the Arduino board. As a result, the distribution of the absolute critical pressure inside the Denver flotation cell could be analyzed. Zn and Cu are often mineralized together and both the Cu extraction from CuFeS\({}_{2}\) and the electrodeposition of Zn are highly energy-intensive processes. To increase economic efficiency, [PERSON] and [PERSON] [79] integrated the two energy-intensive metallurgical processes into a battery-like device called a trifunctional battery (TFB), which is capable of extracting Cu as well as storing energy. To demonstrate the practical use of the TFB, the cell was charged and connected to an LED mounted on the Arduino board. The Arduino measures the voltage of the cell, and the LED blinks when the voltage falls below a threshold value.
## 3 EM Techniques for CH Diagnosis
### Infrared Spectroscopy (IRS) and Raman Spectroscopy in CH Applications
#### 3.7.1 Practical Application of IRS and Raman Spectroscopy to CH  
According to [PERSON]'s opinion mentioned in the previous subsection, in [134] (p. 7), it is stated: \"FTRI spectroscopy analysis was carried out mainly to obtain information about the organic components\". This quote is taken from the work of [PERSON]. [PERSON] et al. on [PERSON]'s _Pink Water Llies_, and the FTRI analysis mentioned has been used to obtain information about the organic components in three different layers of the painting: the ground layer, the binder of the color layer, and the varnish. The IR spectrum highlights the presence of proteins in the ground layer, probably attributable to the presence of collagen (a main component of animal glue). This provides insights into [PERSON]'s technique: the glue might have been used for a pre-priming layer of the canvas. FTRI spectroscopy has been applied for similar purposes also on a [PERSON] instrument; in particular, reflection FTRI has been used for the characterization of several organic substances historically used in making musical instruments [66] (abstract).  
Applications of Raman spectroscopy for CH analysis have gained prominence over the last two decades, covering a wide range of artifacts--from paper [135] to ceramics [136; 137], glass [138; 139], parchment, and wool [140]. It is often employed to examine pigments and binding media in paintings. Raman spectroscopy is specially chosen for pigment analysis because of its non-destructive nature and its ability to analyze particles down to 1 \(\upmu\)m [141]. In the case of Raman microscopy (a combination of Raman spectroscopy with traditional light microscopy), the data obtained are immune to interference from adjacent pigments because the spatial resolution is less than 1 \(\upmu\)m [142].  
In [143], in situ analysis conducted through portable Raman spectroscopy allowed the determination of the palette and pigment mixture used by [PERSON] and the identification of at least two different blues. The painting is on paper.  
In Figure 13, the Raman spectrum of [PERSON]'s yellow dress shows the predominant presence of antimonate and calcium carbonate.  
Figure 13: _[PERSON] meeting his new brake-to-be [PERSON]_, Fresco by [PERSON], known as [PERSON], 1519 Villa Farnesina, Rome. Raman spectrum of [PERSON]’s yellow dress. Credit [PERSON] et al. [28]. Distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license: [[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)) (accessed on 20 November 2024). No changes were made to the figure but to capture.
## 2 Multi-Energy System Structure  
MES includes electrical loads, thermal loads, controllable EVs, CHPs, energy storage devices, distributed renewable energy, and the associated electricity, heating and information transmission networks. A typical MES structure is shown in Figure 1. The MES can operate in islanded mode or grid-connected mode by connecting with the external main grid.  
The increasing inclusion of plug-in EV has the potential of not only bringing benefits by reducing the on-peak demand, but also improving the economic efficiency. Consequently, in the MES, the scheduling of aggregated EVs is being promoted by persuading the EV owners to participate in the scheduling program. On one hand, the aggregated EVs can be considered as a battery energy storage device in MES when an electricity power imbalance arises or when the buying electricity price from main grid is relatively higher; on the other hand, the aggregated EVs can be regarded as a bulk electricity demand to be charged when the electricity price is cheaper or the load is lower. Consequently, the coordination between EVs and other energy generators in MES has been receiving increasing attention from the researchers. However, there exists an intractable challenge, i.e., the flexibility of available EV charging or discharging electric power and capacity is uncertain and depends on the peoples' daily commuting behaviors, for example when to arrive in the office and when to go home.  
As an important energy coupling component, CHP units can supply both electrical and thermal power and can impose significant impacts on the operation of MES. The gas turbine CHP consists mainly of an air compressor, a gas combustion chamber, a turbine, a control system and related auxiliary equipment. The CHP units are classified as backpressure and extraction-condensing units. As shown in Figure 2, the produced thermal power of the back-pressure units depends linearly on the output of the electricity power, thus leading to a limited operation flexibility. For the extraction-condensing units, the operation region in Figure 3 is described as an irregular quadrilateral [23]. Obviously, the feasible operation region (FOR) of the extraction-condensing units is much bigger than that of the backpressure units [24]. The effective coordination between these two types of complementary CHPs makes it possible to simultaneously satisfy electricity and heat demands. In addition, electric heater and heat storage are also installed in MES, in order to offer more flexibility.  
Figure 1: System architecture of a typical multi-energy system (MES). EVs: electric vehicles; CHP: combined heat and power.  
Figure 2: Relationship between thermal and electricity power generation of combined heat and power (CHP) units with fixed heat-to-electricity ratio.  
The electricity utility company makes a direction guide for charging time of EVs owners by setting peak and valley electricity price for 24 h in a day. The price of natural gas is usually fixed during the period of a day.
## 3 Proposed Protocol Design Scheme
### Energy Consumption and Network Model
\[f=\frac{Residual\ Energy}{Distance\times BER} \tag{10}\]  
The node with the highest residual energy and the lowest BER is designated as the first destination, according to Equation (10). The best relay node is selected if the BER falls below a certain threshold. The source directs the data packet to its final destination once the destination has been chosen.
# Poly(lactic acid)-Based Electrospun Fibrous Structures for Biomedical Applications
## 8 Biomedical Applications of PLA-Based Nanofibrous Structures
### Tissue Engineering
#### 8.3.2 PLA Scaffolds for Neural Tissue Engineering  
Nerve tissue repair and regeneration strategies have become crucial challenges, because they directly affect the patient's quality of life. Recent advances in nerve regeneration have included the use of tissue engineering principles, and this has opened up a new perspective on neurotherapy [152]. Synthetic scaffolds for nerve tissue engineering are usually either hollow or filled tubes developed to be biocompatible, immunologically inert, biodegradable, infection-resistant biomaterial, and mechanically matched to nerves to support neurite outgrowth [153]. Due to such design criteria, PLA and its composites have been used for the development of biodegradable nerve scaffolds. In recent years, a lot of research has been focused on changes in the topography, alignment, and mechanical properties of PLA fibrous scaffolds to aid in neural regeneration [72]. Table 3 shows different studies in which electrospun PLA fibers have been used for nerve tissue engineering. A bio-coaxial electrospinning technique has been used by [PERSON] et al. [144] for the development of oriented tubular PLA scaffold containing PC-12 cells to be used as a nerve guide conduit (NGC). Randomly oriented and aligned hollow fibers have been developed with diameters in tens of micrometers and wall thicknesses of around a few micrometers. PC12 cells were successfully located inside the hollow fibers, and after the addition of the nerve growth factor, have been differentiated with neurite extended along the hollow fibers in the desired direction. Co-electrospinning was used also by [PERSON] et al. [145] to develop PLA/Silk Fibroin/Nerve Growth Factor (called PS/N) through encapsulating nerve growth factor (NGF) along with silk fibroin (SF) as the core. The effect of air plasma treatment of PS/N scaffold on cell behavior was investigated and the results showed that plasma-treated PS/N scaffolds supported the attachment and differentiation of PC12 cells, and have a great potential to be used in nerve tissue engineering.
## 5 Illustrative Example
### Results
#### 5.3.2 Oil Tanker  
In ice regime 1, the oil tanker received a modified RIO of 15 ('normal operations'). In the more severe ice conditions of ice regime 2, the modified RIO was reduced to \(-5\) ('elevated operational risk'). In both regions of heightened environmental sensitivity, the high spill consequence value of the oil tanker resulted in a modified RIO of \(-15\) ('operation subject to special consideration').  
The oil tanker should avoid Route A since operating in either of the environmentally sensitive regions imposes the strictest operational criteria. Navigation of the oil tanker along Route B would require reduced speeds, additional watch keeping, or icebreaker escort. Along Route C it could maintain 'normal operation' as this route had the lowest operational exposure.  
Note that in the socio-economic protection status region, the moderate spill consequence category of the bulk carrier resulted in less restrictive operational criteria than the oil tanker (high spill consequence). This exemplified the impact of differences in spill consequence category on operating criteria.
# Intelligent Reception of Frequency Hopping Signals Based on CVDP
###### Abstract  
The frequency hopping communication systems have been widely used in anti-jamming communication due to their anti-interception and anti-interference capabilities. With the increasingly complex electromagnetic environment, the transmitter of the frequency hopping communication system adopts more flexible frequency hopping patterns to cope with interference. Therefore, to address the problem of traditional frequency hopping receiver systems being unable to receive properly due to intelligent frequency hopping sequence decisions made at the transmitter, we design a CVDP (CNN_VIT_Dual Multi-head _Prob sparse_ Self-attention) network based on a convolutional neural network (CNN) module and Transformer Encoder module to realize the intelligent reception of frequency hopping signals. The designed CNN module extracts the global features and spatial information of the time-frequency spectrograms and serves as the input of the VIT (Vision Transformer) network, which not only solves the problem that the VIT network is difficult to converge on small data sets but also improves the stability and robustness of the VIT network. In the Transformer Encoder module of the VIT network, a dual multi-head self-attention mechanism is used to extract critical time-frequency features and a _Prob sparse_ self-attention idea is introduced to reduce the computational complexity. Simulation results on hopping frequency estimation and received BER(Bit Error Rate) of CVDP networks in different interference and channel environments show that when a hopping sequence is unknown, CVDP-based intelligent hopping receiver systems can achieve nearly the same receiver performance as conventional reception systems in which a hopping sequence is known.  
Keywords:complex electromagnetic environment; frequency hopping system; neural network; intelligent reception; vision transformer +
Footnote †: journal:
## 3 Optimization Configuration Method of ESS
### ESS Planning Formulation  
In the optimization configuration model, the objective function proposed includes the operating cost of generators, the construction cost of ESSs, and the penalty cost of RESs. The specific expression is shown in Equations (17) and (18).  
\[C_{\mathrm{con}}^{\mathrm{total}}=C_{\mathrm{SG}}^{t}+C_{\mathrm{res}}^{t}+C_{ \mathrm{ess}}^{t} \tag{17}\]\[\left\{\begin{array}{l}C_{\text{SG}}^{t}=\sum\limits_{i=1}^{N_{\text{SG}}}a_{m} \left(P_{\text{SG},t}^{i}\right)^{2}+b_{m}P_{\text{SG},t}^{i}+c_{m}\right)\\ C_{\text{res}}^{t}=\sum\limits_{i=1}^{N_{\text{res}}}c_{i,\text{res}}^{\text{ re}}(P_{i,\text{res}}^{\text{f}}-P_{i,\text{res}}^{\text{r}})\\ C_{\text{ess}}^{t}=(\sum\limits_{i=1}^{N_{\text{GFL}}^{\text{GFL}}}k_{\text{GFL} }^{\text{p}}*P_{\text{GFL}}^{\text{e}}+\sum\limits_{i=1}^{N_{\text{GFL}}^{ \text{GFM}}}k_{\text{GFM}}^{\text{p}}*P_{\text{GFM}}^{\text{e}})*\frac{r(1+r)^{n }}{\left(1+r\right)^{n}-1}\end{array}\right. \tag{18}\]  
In the power system, \(C_{\text{SG}}^{t}\) represents the operational expenditure of conventional SGs; \(C_{\text{res}}^{t}\) is the penalty charges of RESs, which is designed to maximize the utilization efficiency of renewable energy; \(C_{i,\text{res}}^{\text{re}}\) is the penalty coefficient of RESs; \(N_{\text{SG}}\) is the quantity of conventional SGs; \(N_{\text{res}}\) is the quantity of RESs; \(a_{m}\), \(b_{m}\), \(c_{m}\) is the power generation cost coefficient of conventional SGs; \(P_{i,\text{res}}^{i}\) is the active power output of conventional SGs; \(P_{i,\text{res}}^{\text{f}}\) and \(P_{i,\text{res}}^{\text{r}}\) are the predicted output and actual output of RESs; \(P_{\text{GFL}}^{\text{e}}\) and \(P_{\text{GFM}}^{\text{e}}\), respectively, represent the power capacity of GFL-ESSs and GFM-ESSs; \(k_{\text{GFL}}^{\text{p}}\) represents the cost coefficient of GFL-ESSs; \(k_{\text{GFM}}^{\text{p}}\) represents the cost coefficient of GFM-ESSs; \(r\) is the benchmark discount rate; and \(n\) is the operational life of ESS.
## 5 Proposed Scheme
### User Registration Phase  
During the registration, the user transmits a real identity to the \(CS\). Figure 4 represents the user registration phase of the scheme.  
**Step 1:**: \(U_{r_{i}}\) chooses identity \(ID_{i}\) and password \(PW_{i}\) and generates random number \(r_{i}\). The user transmits its identity \(ID_{i}\) to the \(CS\) for registration.
**Step 2:**: The \(CS\) generates random number \(k_{i}\) and calculates the user's temporary identity \(UID_{i}=h(ID_{i}||k_{i})\) and shared secret value \(UI_{i}=h(ID_{i}||k_{i})\). The \(CS\) also computes \(UA_{i}=k_{i}\oplus h(S_{k}||UID_{i})\) to hide \(UI_{i}\). Then, the \(CS\) transmits \(UID_{i}\) and \(UI_{i}\) to \(U_{r_{i}}\) securely and stores \(UA_{i}\) with \(UID_{i}\).
**Step 3:**: After receiving that, \(U_{r_{i}}\) computes a value for hiding random number \(R_{0}=r_{i}\oplus h(ID_{i}||PW_{i})\), a value for login \(R_{1}=h(ID_{i}||PW_{i}||r_{i})\), and \(R_{2}=UI_{i}\oplus h(PW_{i}||r_{i})\).  
Figure 4: User registration phase of the proposed scheme.  
Figure 3: Flowchart of the proposed scheme.
## 5 Experimental Verification  
In this section, experimental tests were carried out to validate the previous analytical results. The experimental setup included two 5 kW Danfoss VSCs operating back-to-back, LCL filters, a grid simulator (Chroma 61845), and a DS1007 dSPACE control system. The first VSC acted as a constant power source, emulating a primary source such as PV or a wind turbine, and supplied the second three-phase grid-connected VSC. The second VSC was connected to a grid simulator through an LCL filter and transfered the received power to the power grid. It contained CC, HPF, PLL, AVC, and DVC. To emulate weak grid conditions and reduce the required inductors in practice, some of the power system and control parameters were changed, and a down-scaled power system was designed. Table 6 shows the parameters that differed from the main circuit parameters.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Power System Parameters** & **Control Parameters** \\ \hline Nominal power (\(P_{n}\)) & 5 [kW] & Conventional control method \\ Nominal line voltage (\(v_{g}\)) & 172 [V] & \(k_{pc},k_{c}\) & 7.068, 3.3 \(\times\) 10\({}^{3}\) \\ Filter capacitor (\(C_{f}\)) & 30 [\(\mu\)F] & \(k_{pp},k_{ip}\) & 0.41, 14.7 \\ Inverter-side inductor (\(L_{f}\)) & 1.5 [mH] & \(k_{pa},k_{ia}\) & 0, 9.23 \\ Grid-side inductor (\(L_{g}\)) & 1.9–19 [mH] & Proposed control method \\ DC-link voltage (\(v_{dc}\)) & 600 [V] & \(k_{pp},k_{ip}\) & 0.41, 14.7 \\ \hline \hline \end{tabular}
\end{table}
Table 6: System and control parameters of down-scaled power system.  
Figure 11: Time-domain simulations showing the system response for 20-degree phase jumps at grid voltage under different PLL bandwidths (\(P=P_{n}\), SCR = 2).  
Figure 12: Time-domain simulations showing the system response for 10% voltage sag at grid under grid inductance uncertainties (\(P=P_{n}\)), (**a**) \(f_{PLL}=1\) Hz; (**b**) \(f_{PLL}=\)12 Hz.  
Figures 13 and 14 show the system response under different power levels and PLL bandwidths under weak and strong grid conditions (SCR = 1.63 and 5.3), respectively. Even though a perfect match between the analytical and experiments was not presented due to laboratory implementation limitations, the results demonstrated the same trend.  
As shown, the system response under weak grids was sensitive to inverter power level, and a low grid SCR limited the application of a high-bandwidth PLL. While under a strong grid, this phenomenon could not be seen. The following section summarizes the presented discussions and results in the previous sections.
# Telehealth Secure Solution to Provide Childhood Obesity Monitoring
###### Abstract  
Childhood obesity causes not only medical and psychosocial problems, it also reduces the life expectancy of the adults that they will become. On a large scale, obese adults adversely affect labor markets and the gross domestic product of countries. Monitoring the growth charts of children helps to maintain their body weight within healthy parameters according to the World Health Organization. Modern technologies allow the use of telehealth to carry out weight control programs and monitoring to verify children's compliance with the daily recommendations for risk factors that can be promoters of obesity, such as insufficient physical activity and insufficient sleep hours. In this work, we propose a secure remote monitoring and supervision scheme of physical activity and sleep hours for the children based on telehealth, multi-user networks, chaotic encryption, and spread spectrum, which, to our knowledge, is the first attempt to consider this service for safe pediatric telemedicine. In experimental results, we adapted a recent encryption algorithm in the literature for the proposed monitoring scheme using the assessment of childhood obesity as an application case in a multi-user network to securely send and receive fictitious parameters on childhood obesity of five users through the Internet by using just one communication channel. The results show that all the monitored parameters can be transmitted securely, achieving high sensitivity against secret key, enough secret key space, high resistance against noise interference, and 4.99 Mb/sec in computational simulations. The proposed scheme can be used to monitor childhood obesity in secure telehealth application.  
obesity; telehealth; multiuser network; spread spectrum; chaos Article