esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The Norm Systems  
### The Triangular Norms  
Triangular norms are used to construct operations on fuzzy sets and Yager [32] fuzzy sets.  
Definition 1: The triangular norm or the \(\boldsymbol{t}\)**-norm** in \([0,1]\) is the operation \(\bullet_{t}:[0,1]\times[0,1]\to[0,1]\), when for any numbers \(x,y,z\in[0,1]\) meets the following conditions:  
* \(0\bullet_{t}y=0,y\bullet_{t}1=y\)--boundary conditions,
* \(x\bullet_{t}y\leq z\bullet_{t}y\), when \(x\leq z\)--monotonicity,
* \(x\bullet_{t}y=y\bullet_{t}x\)--commutativity,
* \(x\bullet_{t}(y\bullet_{t}z)=(x\bullet_{t}y)\bullet_{t}z\)--associativity.  
The triangular \(t\)-conorm or the \(\boldsymbol{s}\)**-norm** in \([0,1]\) is the operation \(\bullet_{s}:[0,1]\times[0,1]\to[0,1]\), when for any numbers \(x,y,z\in[0,1]\) it meets the following conditions:  
* \(0\bullet_{s}y=y,y\bullet_{s}1=1\)--boundary conditions,
* \(x\bullet_{s}y\leq z\bullet_{s}y\), when \(x\leq z\)--monotonicity,
* \(x\bullet_{s}y=y\bullet_{s}x\)--commutativity,
* \(x\bullet_{s}(y\bullet_{s}z)=(x\bullet_{s}y)\bullet_{s}z\)--associativity.  
**Theorem 1**.: _Operation \(\bullet:[0,1]\times[0,1]\to[0,1]\) is the s-norm if it is defined by the formula \(x\bullet y=1-(1-x)\bullet_{t}(1-y)\), for any numbers \(x,y\in[0,1]\)._  
**Example 1**.: _The operation defined by the formula \(x\bullet_{t}y=\min\{x,y\}\) for any \(x,y\in[0,1]\) is a t-norm._  
_The operation defined by the formula \(x\bullet_{s}y=\max\{x,y\}\) for any \(x,y\in[0,1]\) is the s-norm._  
Further in this paper, we consider only the continuous t-norms and s-norms. The general construction of triangular norms and the functional equations [41] leads to the Theorem:  
**Theorem 2**.: _For each strictly decreasing continuous function \(f_{t}:[0,1]\to[0,+\infty)\) such that \(f_{t}(1)=0\) and for any \(x,y\in[0,1]\), the t-norm is the operation determined by the formula:_  
\[x\bullet_{t}y=\begin{cases}f_{t}^{-1}[f_{t}(x)+f_{t}(y)],\,\text{for}\,\,f_{t }(x)+f_{t}(y)\in[0,f_{t}(0)],\\ 0,\text{otherwise}.\end{cases} \tag{2}\]  
_For each strictly increasing continuous function \(f_{s}:[0,1]\to[0,+\infty)\) such that \(f_{s}(0)=0\) and for any \(x,y\in[0,1]\), the s-norm is the operation determined by the formula:_  
\[x\bullet_{s}y=\begin{cases}f_{s}^{-1}[f_{s}(x)+f_{s}(y)],\,\text{for}\,\,f_{s }(x)+f_{s}(y)\in[0,f_{s}(1)],\\ 1,\text{otherwise}.\end{cases} \tag{3}\]  
Then the \(f_{t},f_{s}\) functions are called t-norm and s-norm **generators**, respectively.  
When the functions \(f_{t},f_{s}\) satisfy the condition: \(f_{s}(x)=1-f_{t}(1-x)\) for every \(x\in[0,1]\), then they are called dual t-norm and s-norm generators.  
**Remark 1**.: _Only dual standard generators will be described hereinafter._  
**Example 2**.: _For any \(x,y\in[0,1]\), if the t-norm \(x\bullet_{t}y=1-\min\{1,((1-x)^{p}+(1-y)^{p})^{1/p},p\geq 1\) is considered, then the generator is \(f_{t}(x)=1-x^{p}\)._  
_For any \(x,y\in[0,1]\), if the s-norm \(x\bullet_{s}y=\min\{1,(x^{p}+y^{p})^{1/p}\},p\geq 1\) is considered, then the generator is \(f_{s}(x)=x^{p}\)._
## 3 MG-Based BTS Operation
### MG-Based BTS Measurements and Control Electronics
This configuration breaks ground loops (leading to less interference in data wires), isolates low power electronics from the higher power parts (cutting off unexpected overloads) and also isolates the SBC and its peripherals, which avoids problems related to different grounding configurations among devices. Regardless of the source, the power is always drawn from the BESS to avoid the eventual loss of power due to a grid failure. To this aim, three different low-cost DC/DC converters, with a rated current of 4 A that meets the current demanded by the SBC driver and the SBC, have been used. To keep the isolation among the aforementioned parts, drivers based on the FOD3182 optocoupler [45] and the digital isolator MAX14937 [46] for the transistors and I2C communications are included. The SBC controls the optocoupler drivers through two I2C expanders [47]. Finally, electromagnetic noise, due to abrupt changes in DC current flows, must be kept within certain limits. In the early stages of the MG-based BTS development, noise coupling was detected in measurements, generated by the DC currents of the BESS and the loads. Consequently, an analysis of this electromagnetic interference was performed, seeing that a 100-mV noise was coupled into the input signals of the ADC (leading up to a 5 A error in the measurements of DC currents through the loads) and into the BME 680 power supply (leading to a malfunctioning). In the final design of the SBC driver, the components were rearranged to minimize the coupling noise. Figure 6 depicts current measurements taken in the final set up of the SBC driver in the presence of electromagnetic interference. Figure 6 shows a sudden change in the currents through the non-critical loads (Figure 6a) and in the BESS (Figure 6c). Particularly important is the 40 A change in the current through the BESS, which induces electromagnetic interference in the input signal of the ADC, introducing a  
Figure 5: Conditioning circuits of the transistors and relays (SBC driver). 0.4 A measurement error in the critical load DC currents. This error is shown in Figure 6b in the shape of a noise peak. Hence, it is important to reduce the negative impact of the noise on the ADC input, achieved in the final design.
###### Abstract  
From the wide range of methods available to landslide researchers and practitioners for monitoring ground displacements, remote sensing techniques have increased in popularity. Radar interferometry methods with their ability to record movements in the order of millimeters have been more frequently applied in recent years. Multi-temporal interferometry can assist in monitoring landslides on the regional and slope scale and thereby assist in assessing related hazards and risks. Our study focuses on the Corvara landslides in the Italian Alps, a complex earthflow with spatially varying displacement patterns. We used radar imagery provided by the COSMO-SkyMed constellation and carried out a validation of the derived time-series data with differential GPS data. Movement rates were assessed using the Permanent Scatterers based Multi-Temporal Interferometry applied to 16 artificial Corner Reflectors installed on the source, track and accumulation zones of the landslide. The overall movement trends were well covered by Permanent Scatterers based Multi-Temporal Interferometry, however, fast acceleration phases and movements along the satellite track could not be assessed with adequate accuracy due to intrinsic limitations of the technique. Overall, despite the intrinsic limitations, Multi-Temporal Interferometry proved to be a promising method to monitor landslides characterized by a linear and relatively slow movement rates.  
Keywords: landslides; multi-temporal radar interferometry; X-band data; corner reflectors; validation; Dolomites +
Footnote †: journal: Remote Sensing, 2017
## 3 Cloud-Edge Collaborative Intelligent Security Encryption Strategy
### Edge Encryption Architecture for the IIoT  
The edge device layer mainly includes various sensors and IoT devices. Sensors are responsible for monitoring the environment or device status, collecting a large amount of raw data, such as temperature, humidity, images, sound, etc. These data are used as the basis for subsequent processing and analysis. IoT devices mainly include some robotic arms and assembly line devices, which play a role in receiving upper level commands and executing them.  
Edge Computing Layer [30]  
The edge computing layer comprises numerous edge processing nodes endowed with data processing and storage capabilities. These nodes process data from the industrial equipment layer to a certain extent. When the data volume is excessive or specific tasks surpass the capacity of edge nodes, tasks can be uploaded via the edge gateway for processing by the computational resources of larger cloud computing centers. Subsequently, the results are returned to the industrial equipment. More considerable computing resources within the cloud computing center handle the tasks, after which the computation results are returned to the industrial equipment.  
The enterprise node layer consists of hardware encryption devices, gateways, regulatory interfaces, and edge servers. Professional devices can perform encryption tasks to  
Figure 2: Industrial collaboration architecture diagram under IIoT.  
ensure the security and efficiency of these data. Supervision by third-party trusted institutions ensures the accuracy of data. The gateway is responsible for forwarding messages to ensure that data can accurately and accurately reach the destination. We will demonstrate the functionality of these components later.  
Cloud Computing Layer [31; 32]  
The cloud computing layer houses extensive computing and storage resources. Its primary function involves storing and processing large volumes of data with non-real-time requirements and extracting potential value from massive datasets. Furthermore, the cloud computing layer oversees the security supervision of the enterprise node layer, engaging in dynamic management to uphold system security and stability.  
In the industrial cloud, key technologies include but are not limited to the cloud computing platform, industrial Internet of Things (IIoT), big data analysis, artificial intelligence (AI), edge computing, and 5G communication. These technologies work together to support the following core capabilities: unified data management, service oriented and platformized, intelligent analysis and optimization, security and privacy protection, and flexible expansion and upgrading.
# Fewer Dimensions for Higher Thermal Performance: A Review on 2D Nanofluids
## 3 Application of 2D Nanofluids
### Heat Exchangers
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Reference** & **Authors/Year** & **Nanomaterial/Concentration** & **Base Fluid** & **Heat Exchange Type** & **Main Findings** & **Remarks** \\ \hline  & & & & & Increases of 8.7\% and & & \\
128 & Esfahani and Langmuir 2017 & GO at 0.01\% and 0.1\% wt. & Water & Shell and tube & 18.9\% in the TC at & 10\% in the energy loss and & 4.01 and 0.1 wt.\% \\  & & & & and at 25\% C and 0.4 \% C, & at 0.01 and 0.1 wt.\% \\  & & & & & respectively. & \\ \hline  & & & & Increase of & \\  & & & & & approximately 11\% in & \\  & & & & the HTC at 0.6\%, vol. and & & \\  & & & & at a mass flow rate of & & Increase of 1.56 times in \\  & & & & 0.04 kg/s & & the pressure drop at 0.6\% \\  & & 0.6\% vol. & & Increase of & & vol. and at mass flow \\  & & & & & approximately 3.0\% in the TC at 0.6\% vol. and & & rate of 0.08 kg/s. \\  & & & & temperature values & between 30 °C and & \\  & & & & & 50 °C. & \\ \hline
130 & Fares et al., 2020 & Gr at 0.2\% wt. & Water & Shell and tube & Increase in the HTC of & Increase in the thermal \\  & & & & 29\% at 0.2\% wt. & & \\ \hline
131 & Sen and Variyenli, 2021 & Gr-CuO at 0.5\% vol. & Water & Concentric tube & Increase of 9.6\% in the & Decrees of 5\% in the \\  & & & & the HTC. & total energy loss. & \\ \hline
132 & Abdalah et al., 2021 & Gr at 0.02\%, 0.055\%, and & & & & \\  & & 0.06\% wt. & Water & Double & & \\  & & & & and at 0.06\% wt. and & & higher at 0.06\% wt. than \\  & & & & & 0.055\% wt. & at the other \\  & & & & & concentrations. & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Recent experimental works on the use of 2D nanofluids in heat exchangers. In essence, additional studies should be conducted on the corrosive and erosive consequences and fouling formation associated with the flow of 2D nanofluids in the exchanger channels and surfaces. There is also a research gap concerning the high-temperature usage of two-dimensional nanofluids in different types of heat exchangers. These studies are pivotal, given that it has already been reported in the literature that the pressure drop in the piping and the initial pumping power are decreased at high fluid inlet temperature values. Efforts should be made to undertake in-depth studies concerning other thermophysical characteristics of 2D nanofluids flowing in heat exchangers aside from the usually scrutinized TC and viscosity, such as the specific heat capacity and latent heat capacity. Additionally, more experimental and numerical works on the applicability of 2D nanofluids are required, such as Gr family dispersions in the role of thermal fluids operating in heat exchangers and similar equipment, investment analysis, and potential heat transfer working gains. Finally, more studies on 2D nanofillers based on h-BN nanostructures to be applied in all types of heat exchangers are lacking in the literature.
# On Ad Hoc Communication in Industrial Environments
## 5 Examination of the Industrial Ad Hoc Channels
### Performed Tests  
In order to evaluate the channel characteristics of industrial ad hoc channels, tests in different environments and with different setups were conducted. The goal is to differentiate between the influence of environment and mobility on ad hoc communication and how to extract this information from the NEPs.  
A reference test was performed to check the general functionality of the protocol and to deliver a reference for the examined network characteristics. It was performed in an office environment with static nodes.  
A static industry test describes the measurement with nodes in an industrial environment. In this test all nodes collectively moved in an industrial environment; hence, they did not experience any relative movement and therefore moved as one group. The goal of this test is to characterize the effect of interference on the industry, while mitigating the effects of mobility and variable signal propagation. The absolute movement of the node group enabled the observation of the spatial variation in the interference.  
Lastly a mobile industry test was conducted by utilizing AGVs in an accessible production facility to implement mobility. The nodes were mounted on the AGVs in an unobstructed way. Therefore, two signal attenuation effects influenced the existence of encounters in the resulting NEP. Firstly, large scale fading causes path loss between transmitter and receiver due to the distance between them. Secondly, small-scale fading caused by reflection, refraction, and scattering can be caused by obstacles on the primary propagation path.  
The tests are characterized by a number of varying parameters. When comparing the presented results of the measurements, variations in these parameters have to be taken into account. Table 1 compiles and describes the different parameters and their values for the performed experiments.  
Some parameters are restricted by external requirements. The send period \(dt\) of the trace protocol, for example, had to be adjusted, as a minimal bandwidth impact of the measurement was required. Table 1 compares the measurement parameters of the three measurements.  
All tests were performed with IEEE802.11 b/g/n communication interfaces at 20 dbm send power. The protocol was implemented with the Click modular router [34] on a battery-powered single-board computer. The implementation and the resulting NEPs are published in [35].
## 3 System Design
### Fault Detection and Link Self-Healing
This, combined with the SRT layer's rapid caller-listener rehashshake process taking about 500 ms, ultimately allows the system to achieve link self-healing and resume playback within a 1 to 2 s window in most anomaly cases, which is significantly faster than traditional methods, which usually take minutes and require manual intervention. Through this design, the system accomplishes multiple fault tolerance objectives: rapid isolation of local faults, swift link break convergence, minimal reconstruction windows, and uninterrupted business playback switching. Even in extreme network conditions involving multi-hop consecutive failures, the system can maintain stable operation of remaining links by relying on real-time feedback, thereby significantly enhancing overall system availability and business continuity assurance.
# Optimization of Intelligent Maintenance System in Smart Factory Using State Space Search Algorithm
## 3 Results
### Data Collection  
In this research, we utilized data on six types of spare parts imported from the new IMS to obtain the values of interest for each month, as follows (Figures 17-20):  
From data of 3 months, the breakdown of the % of RM (Remaining Time percentage) for each item:  
Bearing: 4%, Belt: 28%, Heater: 52%, Break: 59%, Electric: 71%, Pneumatic: 76%  
The total of these percentages is 290%.  
From data of 6 months, the breakdown of the % of RM (Remaining Time percentage) for each item:  
Bearing: \(-92\%\), Belt: \(-44\%\), Heater: 4%, Break: 18%, Electric: 42%, Pneumatic: 52%  
The total of these percentages is \(-20\%\).  
Figure 17: Data from 3 month.  
Figure 18: Data from 6 month.  
From data of 9 months, the breakdown of the % of RM (Remaining Time percentage) for each item:  
Bearing: \(-188\%\), Belt: \(-116\%\), Heater: \(-44\%\), Break: \(-23\%\), Electric: \(14\%\), Pneumatic: \(28\%\)  
The total of these percentages is \(-329\%\).  
From data of 12 months, the breakdown of the % of RM (Remaining Time percentage) for each item:  
Bearing: \(-284\%\), Belt: \(-188\%\), Heater: \(-92\%\), Break: \(-65\%\), Electric: \(-15\%\), Pneumatic: \(4\%\)  
The total of these percentages is \(-640\%\).  
Data from 3, 6, 9, and 12 months indicated that in 3 months all items have positive remaining times, indicating they are within their expected lifetimes; in 6 months some items have exceeded their expected lifetimes, with Bearing and Belt needing immediate attention; in 9 months most items have significantly exceeded their expected lifetimes, requiring urgent replacements; and in 12 months all items except Pneumatic have exceeded their expected lifetimes, with Bearing and Belt being the most critical.
## 3 Automated Calibration of Chaboche Parameter
### Determination of Ratcheting Parameters Using Intelligent Optimization Methods
#### 3.4.1 Genetic Algorithm  
Genetic Algorithm is a versatile optimization method in which the best solution is found by assigning a big population of individuals to satisfy cost functions such as minimizing cost function or maximizing fitness function. Artificial GA mimics the evolution of living in nature encompassing selection, cross over, and mutation.  
The Genetic Algorithm is commonly adopted as a method to identify parameters of physical models to satisfy the cost function [25; 26; 41]. Herein, the cost function is the Chaboche stress \(\sigma_{NLK}\) which is the function of backstress mentioned in Section 3, and expressed as Equation (19):  
\[\sigma_{NLK}=\ f(\alpha_{NLK}), \tag{19}\]  
\[\text{where}\ \alpha_{NLK}=f\Big{(}C_{1},C_{2},C_{3},C_{4},\gamma_{1},\gamma_{2}, \gamma_{4},\ \sigma_{0}^{1}\Big{)}.\]Therefore \(\sigma_{NLK}\) is a dependant variable and \(x_{GA}=\{C_{1},C_{2},C_{3},C_{4},\gamma_{1},\gamma_{2},\gamma_{4}\}\) is an independent variable, known as chromosome. The parameter optimization and model can be evaluated by calculating the mean square error (MSE) as presented in Equation (20):  
\[MSE=\frac{1}{N}\sum_{i=1}^{N}{(\sigma^{1}-\sigma_{NLK})}^{2}, \tag{20}\]  
where, \(N\) is the number of proportional strain data points from the experiment. To perform the GA, the three main steps, namely, selection, crossover and mutation are to be implemented.  
Selection Activity  
Selection is the repetitive action of forming an initial population, which adapts into a new superior population. In this study the initial population is made randomly by choosing a real number. To proceed selecting a new population, the roulette wheel method is used to select chromosomes. Each chromosome possesses its own probability (\(P_{i}\)), defined as:  
\[P_{i}=\frac{\zeta_{max}-\zeta_{i}}{\sum_{j=1}^{npop}(\zeta_{max}-\zeta_{j})} \tag{21}\]  
where, \(npop\) is the number of chromosome in population, \(\zeta_{max}\) is maximum cost function, \(\zeta_{i}\) is current chromosome cost function and \(\zeta_{j}\) is cost function of remaining chromosomes. After characterizing the eligibility of each chromosome, the roulette wheel tries to select members according to the high probability criterion. The cumulative vector is the sum of probabilities:  
\[v=[p_{1}\,,p_{1+}\,p_{2}\,,p_{1+}\,p_{2+}p_{3}\,,\ldots\,p_{1+\ldots+}p_{n}] \tag{22}\]  
or in the new form:  
\[v(i)=\sum_{j=1}^{i}p_{j}\, \tag{23}\]  
\[\text{where}\ \ i=min\{j|r\leq v_{j}\}\ \ 0<r<1,\]  
where \(i\) is an index of iteration to promote chromosomes of old population to build the new eligible population. Selection is a fundamental task that should be done before and after crossover and mutation activities.
## 4 Results of the Experimental Studies  
The object of the simulation experiment was to check whether roundabout traffic reorganisation has an effect on the roundabout capacity. A study was performed to find out the impact of an increasing number of trucks on roundabout traffic in order to make a reliable choice of the best configuration of regulations. The study accounted for the sizes of such vehicles and their limited technical and physical capabilities, such as e.g., slow acceleration, or low manoeuvring speed.  
The experiments were conducted in a 2-lane roundabout with four feeder roads, for right-hand traffic. Each feeder road consists of the entrance road and the exit road, each with two lanes. The roundabout island diameter amounted to 56 m. The roundabout capacity was examined on the sample of 500 vehicles, by measuring the number of iterations needed for moving all the vehicles through the roundabout, and using the formula:  
\[b=\frac{n_{vehicles}}{n_{iterations}} \tag{8}\]  
where \(b\) is roundabout capacity, \(n_{vehicles}\) is the number of vehicles that have driven across the roundabout (500), and \(n_{iterations}\) is the number of CA iterations.  
The simulation was repeated 1000 times in order to obtain results that are not distorted by random events. The quantity of vehicles in the feeder roads was even. The entrance road for each vehicle was assigned at random with the same probability (25%). The exit road was assigned at random by the programme in the same manner. The entrance and exit roads had two lanes, so the individual lanes were assigned to the vehicles at random. The probability of assigning a given exit lane depended on the examined traffic rules and the roundabout lane on which the vehicle was travelling. In Scenario 1 the vehicle was able to take either of the two lanes in the exit road, if it was moving along the outer lane. In the case the probability of choosing either lane in the exit road was 0.5. If the vehicle was moving along the inner lane of the roundabout, it was able to take the left-hand lane only, and the probability of choosing the left-hand lane was 1. Selection of lanes in the roundabout was made on the same principles, if the principles made it possible to take any lane, the probability was \(\frac{1}{n_{roundabout,1 eno}}\), while for a 2-lane roundabout it was 0.5. In the case of random assigning of the entrance lane, the probability was always 0.5 in all the scenarios. The experiments were run assuming mixed traffic, with 90% of cars (including motorcycles), and 10% of trucks. An exception was the examination of the impact of the number of trucks on the roundabout capacity. Then the quantity of trucks varied.