esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Implementation Details
### Hardware  
A test system is developed to validate the idea principle and take measurements to evaluate possible performance and limitations.  
The amplifier board, shown in Figure 5, is designed with a high-impedance operational amplifier set to offset the signal and provide gain, allowing both sides of the oscillation to be viewed within the 0 V to 3.3 V range, making it compatible with a microcontroller ADC. The gain can be fine-tuned using an on-board electronic potentiometer, allowing for sensitivity control during operation. This sensor board measures 3 cm by 3 cm.  
The breakout board, shown in Figure 6, is used solely for testing purposes. It facilitates the connections necessary to sample the data during the experiments. This board measures 5 cm by 4 cm.  
The emitters, depicted in Figure 7, are based on an STM Nucleo-32 board and generate pulses to drive the ultrasound emitter. An ultrasound driver is implemented using an H-bridge configuration, which allows for efficient switching of the voltage polarity to the ultrasound transducer, thereby maximizing the output power. The width and number of pulses can be adjusted via software. The boards are connected using flat cables to form the emitter network. The emitter device measures 10 cm long by 7 cm tall by 6 cm wide.  
Figure 5: Amplifier board from the top and bottom sides, respectively.  
Figure 6: Breakout board used for sampling data during testing.  
The hardware was developed with the purpose of demonstrating the viability and capability of capturing precise time differences in ultrasound signal arrivals with a very low-cost approach. It is important to note that these dimensions represent the current development and testing hardware. In a final implementation, the hardware would be significantly miniaturized. The current larger sizes are due to the use of development boards, connectors, and other components that facilitate testing and modification. A production version would be optimized for size and efficiency, resulting in much more compact hardware suitable for integration into various robotic platforms.
# Compressive Sensing-Based IoT Applications: A Review
## 3 Compressive Sensing Overview
### Reconstruction Algorithms
#### 3.3.2 Greedy Algorithms  
Greedy algorithms have been widely exploited in CS applications due to their relatively simple framework which provides a fast reconstruction with a low implementation cost. These methods enhance iteratively the approximation for the signal by making locally optimal choices. Greedy algorithms consist of two main steps, element(s) selection and coefficients update. These methods are usually initialized with a residual \(\mathbf{r}^{[0]}=\mathbf{y}\), signal estimate \(\hat{\mathbf{x}}^{[0]}=0\) and empty support set \(\text{T}=\emptyset\). At each iteration \(j\), single or multiple elements from the sensing matrix are added to the support set, the signal estimate is calculated using a least square approach \(\mathbf{x}^{[j]}=\mathbf{\Phi}_{T}^{\dagger}\mathbf{y}\). Additionally, the residual is minimized \(\mathbf{r}^{[j]}=\mathbf{y}-\mathbf{\Phi}_{T}\mathbf{x}^{[j]}\). The algorithms halt when the residual norm is smaller than a predefined threshold.  
Currently, the well established greedy algorithms include gradient pursuit [43], matching pursuit (MP) [44; 45] and orthogonal matching pursuits (OMP) [46]. OMP offers a fast recovery compared to convex optimization approaches, yet it suffers from bad recovery quality for signals with a low degree of sparsity. Thus, several improved versions of OMP have been proposed, such as compressive sampling matching pursuit (CoSaMP) [47], subspace pursuit (SP) [48], Regularized OMP [49], Stagewise OMP [50] and orthogonal multiple matching pursuit [51].  
The performance of these recovery algorithms depends on the targeted application and no unique recovery metric is established to determine the best recovery technique for all scenarios. Thus, both theoretical and experimental performance comparison between the different classes of CS recovery algorithms can be found in [52; 53; 54; 55]. Table 2 lists the details regarding the complexity and the minimum number of measurements required for each algorithm to achieve its optimal recovery bound.
###### Abstract
The aim of this work is to improve the performance of the IPMSM including the power and torque density and reduce the torque ripple and noise based on an original \"V-type\" IPMSM. Therefore, an optimized structure is proposed from the aspects of the stator winding and rotor pole topology to satisfy those requirements. This paper compares the optimized structure with the original structure by means of the finite element method (FEM). According to the simulation results, the analysis of the no-load magnetic density distribution, electromagnetic force (EMF), cogging torques, high-speed stress, temperature rise, torque ripples and efficiency performance proves the feasibility of the optimized structure. In addition, the experimental test is carried out, and the results coincide exactly with the simulation analysis. This article is organized as follows. Section 2 presents the original machine details of the IPMSM and the structure optimization of the fractional-slot single-and-double-layer hybrid winding and \"\(\
abla\)-type\" rotor magnetic-pole topology. In Section 3, the performance comparison of the original and optimized structures is studied by the simulation. And then, the steady-state performance of a prototype IPMSM analyzed in the experimental test is shown in Section 4, which can verify the validity of proposed structure, and the conclusions are drawn in Section 5 finally.
## 4 Discussion
### Application Value  
The rapid economic and social development from 2000 to 2020 has led to the expansion of construction land, such as urban and rural settlements, to the periphery of the B-T-H urban agglomerations. Simultaneously, the proportion of living space has increased from 8.3% to 13%, and the production space has decreased from 50.8% to 46.1%, but the proportion of ecological space has not changed much (Figure 6). Ecological space is an important carbon sink and climate reservoir. Because the \"Ecological space\" is dominated by land types such as grassland and woodland, its carbon sink capacity usually becomes stronger over time [52; 53]. From a practical point of view, strengthening the protection and management of ecological space and improving the structure of existing vegetation and the quality of tree stands further improve carbon sequestration [54]. Subsequently, the \"Three Zone Space\" should be rationally laid out in a mutually beneficial symbiotic relationship to promote the enhancement of carbon sinks.  
For future applications, on the one hand, the establishment of an ecosystem-based carbon cycling model is necessary to improve the prediction of the stability of ecological spatial carbon sinks [55]. We suggest that it is necessary to conduct intensive and long-term ecosystem carbon monitoring on a wide geographical scale [56], incorporating meteorological indicators such as wind speed, evaporation, sunshine hours, and ground temperature, in addition to basic precipitation and temperature, to improve the spatial carbon sink simulation model across ecological spaces [57]. With this, we can accurately assess the ecosystem carbon sink capacity and their dynamics under various climate and policy scenarios and regulate climate policies more accurately using simulation results [58]. On the other hand, although climate factors are hard to control, we cannot just sit back and wait for the significant climate impacts; more importantly, we need to find targeted adaptation strategies, such as adjusting the spatial zoning and optimizing land use layout based on the spatial autocorrelation of carbon sinks [59] For example, the design of urban breezeway is based on the direct and indirect effects of wind speed [60], especially for the Beijing-Tianjin Heat Island Cluster; the impact of sunshine hours is used to improve the plant community and the reasonable layout of green belts [61]. In this paper, the spatially accurate estimation of carbon sinks across ecological spaces under various climate factors can help the government to quickly and accurately adjust the climate policy and realize the visualization of carbon sinks under different scenarios, which is of great significance for China to effectively and timely achieve the double carbon goal.
## 3 The CLICP Construction Scheme
### CLICP Function Design  
As shown in Figure 5, the CLICP functions include both core business functions and extended service functions. This section focuses on the design and analysis of extended service functions. The basic functions of CLICP are not analyzed in detail, as they are similar to those of most current transportation platforms. Instead, we examine the research and design of custom value-added functions. Real-time bidding function, freight information push function and carrier one-stop service management are as follows. The essential difference between these three functions is the different usage scenarios of the service objects. The real-time bidding function can improve the efficiency of matching vehicles and goods. Freight information push function can expand the scope of information sharing and improve the transparency of work. Carrier one-stop service management can reduce additional work costs of the carrier and can improve convenience on the way.
# Experimental Study on Milling CFRP with Staggered PCD Cutter
## 3 Results and Discussion  
### Tool Wear  
Figure 2 shows the tool wear topography of milling 84-meter CFRP with a staggered PCD cutter. It can be seen from Figure 2 that the wear of the staggered PCD cutter was mainly concentrated on the cutting edge, its main form was blunt wear, and rake and flank wear were not obvious. Nonetheless, the cutting-edge wear of the staggered PCD cutter was obviously uneven in an approximately circular arc. That is, it was relatively small in the contact zone with the upper and lower surfaces of the workpiece, while it was larger in the contact area with the middle of the workpiece. For an accurate measurement of the worn cutting-edge radius, the extended depth of field microscope was used to obtain the cross-section contour of the cutting edge, which is shown in Figure 3. In order to study the variation law of the cutting-edge wear due to various milling lengths, the maximum cutting-edge radius \(R_{\text{max}}\) was introduced to characterize the edge wear.  
Figure 1: Test system: (**a**) test layout; (**b**) cutting tool and workpiece.  
Figure 2: Flank wear topography of staggered PCD cutter after milling 84 m.  
Figure 4 shows the variation law of the maximum cutting-edge radius \(R_{\max}\) due to variations in milling length \(L\), in which the initial cutting-edge radius was 20 \(\upmu\)m. The tool wore rapidly with an increase of milling length; the cutting-edge material was removed and the sharp cutting edge became obtuse-circular, which resulted in the increase in the cutting-edge radius. The \(R_{\max}\) reached 57 \(\upmu\)m when the milling length was 21m. Afterwards, the tool wear began to slow down, thus the \(R_{\max}\) fell into 57-70 \(\upmu\)m, and its increase was not clear. However, when the milling length was more than 72 m, the \(R_{\max}\) increased more, reaching 76 \(\upmu\)m when the milling length was 81 m. Nonetheless, the cutting-edge topography was still good, and defects such as obvious tipping and grooves did not occur. Through further EDS analysis of the wear area, obvious signs of adhesive, oxidation or diffusion wear were not found. It was concluded from the wear zone topography and wear curve characteristics that the main wear mechanism of the staggered PCD cutter is abrasive wear.
## 3 Results and Discussion
### Quantitation of Odor-Active Compounds and OVA Calculation
2-methylbutanoate (32.96 \(\pm\) 22.46 \(\upmu\)g/kg), (Z)-geraniol (31.80 \(\pm\) 13.19 \(\upmu\)g/kg), \(L\)-borneol (27.69 \(\pm\) 26.93 \(\upmu\)g/kg), (E)-2-deconal (25.56 \(\pm\) 52.14 \(\upmu\)g/kg), geranic acid (25.13 \(\pm\) 38.39 \(\upmu\)kg), dihydro-\(\beta\)-ionone (24.86 \(\pm\) 7.32 \(\upmu\)g/kg), and 1-octen-3-ol (23.52 \(\pm\) 49.27 \(\upmu\)g/kg) in SBT samples were relatively low. These odor-active compounds were the first quantified in SBT. The contributions of odor-active compounds to the aroma profile of SBT not only depend on its content but also depends on its odor threshold value. Odor-active compounds with OAVs greater than or equal to one were usually considered to play a major role in the aroma profile of the samples ([PERSON], 2018). To further deeply elucidate the contribution of the odor-active compounds in SBT, their OAVs were calculated using the quantitative results and reported thresholds, and the calculation results are shown in Tables 2 and S3. The OAVs of (_E_)-\(\beta\)-damascenone (OAV: 61538.79), \(\beta\)-ionone (OAV: 41851.78), dihydro-\(\beta\)-ionone (OAV: 24856.37), linaloalo (OAV: 354.13), \(\alpha\)-ionone (OAV: 168.68), geraniol (OAV: 163.53), phenylethyl alcohol (OAV: 74.02), (E)-2-decenal (OAV: 63.89), methyl salicylate (OAV: 49.16), benzeneacetaldehyde (OAV: 41.19), (E)-nerolidol (OAV: 20.74), linaloalo oxide II (OAV: 18.56), 1-octen-3-ol (OAV: 15.68), 1-methyl-naphthalene (OAV: 11.60), \(\beta\)-cyclocitral (OAV: 11.58), hexanal (OAV: 7.71), 2-pentyl-furan (OAV: 7.07), linaloalo oxide I (OAV: 5.09), \(D\)-limonene (OAV: 3.46), \(\alpha\)-terpineol (OAV: 2.52), and geranyl acetone (OAV: 1.79) were  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**No.
## 5 Design, Manufacturing and O&M Integration Key Technology of Complex Product Based on Digital Twin
### Data Intelligent Perceptive Technology  
The data intelligent perceptive technology, the premise of achieving the design, manufacturing and O&M integration of a complex product, can collect the physical entity data of a product's life cycle in real-time and provide a data foundation for constructing the data twin body and virtuality and reality interaction. The data sensing network of design, manufacturing and O&M integration can comprehensively utilize a complex product's life-cycle data. As shown in Figure 6, the intelligent perception system construction of design, manufacturing and O&M integration mainly comprises: (1) Uniform data access interface and protocol at each stage. (2) Construction of the product's whole life cycle perception network through the arrangement of the wired or wireless sensor. (3) Construction of comprehensive perception indicators, general technology and standard system for multisensor. (4) Multisource heterogeneous data fusion.  
The intelligent perceptive technology of the whole life cycle arranges sensors in the equipment, personnel and materials of actual production and O&M to collect real-time data. Different types and structures of sensors are used because these data have distinct transmission interfaces and protocols. Therefore, arranging a specific data access model for uniform access to data with different resources is necessary. Additionally, the data shall be extracted, cleaned, transformed and uploaded to achieve data integration due to the diversified structure. The collaboration network is established to achieve the  
Figure 6: Design, Manufacture, and O&M-integrated intelligent sensing system.  
objective at each stage of design, manufacturing and O&M. With the perception, calculation and interaction ability, the collaboration network could achieve the all-round and full-coverage data perception of a complex product, and fully obtain the product data in design, manufacturing and O&M process to construct an intact digital twin body.
# The Potential of Blockchain Technology and Smart Contracts in the Energy Sector: A Review
## 2 Background Information
### A Use Case of Smart Contract for Energy Trade  
A sample smart contract is described below (i.e., Figure 2) to highlight the energy sector use case. The detailed steps of the smart contract are as follows:  
1. The contract is named \"Energy Trade\".
2. The smart contract begins by reading essential parameters, such as the Owner Address (OA), Energy Balance of Owner (EBoO), Requested Value per Unit (RVpU), and SmartMeterReadings. SmartMeterReadings are included for dynamic energy balancing.
3. A check is introduced to evaluate if the SmartMeterReadings fall below a defined Minimum Threshold. If the energy production is below this threshold, the contract cannot be fulfilled, preventing transactions during periods of insufficient energy generation.
4. The contract proceeds to evaluate whether the Quantity of Energy Requested (QoER) is less than or equal to the Energy Balance of the Owner (EBoO). This condition ensures that the owner has sufficient energy to fulfill the requested amount.
5. A credit-based transaction condition checks if the Requested Value (RV) is within the Total Funds Available (TFA) and if the Buyer's Credit Score meets the Minimum Credit Score requirement.
6. If all conditions are met, the Build_Contract is set to \"True\", indicating that the contract can be executed. The necessary adjustments are made to the energy balances of both the owner and the buyer. SmartMeterReadings are updated to reflect dynamic energy balancing.
7. If any of the conditions fail, the Build_Contract is set to \"False\", and a corresponding error message (Msg) is generated. Failure conditions include insufficient funds, low credit scores, or inadequate energy from the owner.  
Figure 2: The pseudocode of a sample smart contract.
## 3 Access Class Barring Configuration (ACBC) Scheme
### Simple Low-Pass FIR Filter  
Besides investigating the benefits of our ACBC scheme with the two previously described adaptive filter algorithms, we also consider the inclusion of a simple FIR filter with fixed weights \(w_{m}\). We refer to this as the low-pass filtering (LPF) method.  
The filter weights must be chosen to ensure the following two conditions are met.  
\[\sum_{m=0}^{M-1}w_{m}=1 \tag{17a}\] \[w_{m}>0,\qquad\text{for all }m\in\{0,1,\dots,M-1\}. \tag{17b}\]  
For this, let \(\rho\) be the degree of the decreasing polynomial function that determines the fixed weights of the filter. Naturally, the rapidness of the response of the fixed filter to sudden changes in the input \(u(j)\) increases with \(\rho\), but so does its sensitivity. In other words, the selection of \(\rho\) creates a trade-off between the responsiveness and the stability of the filter output.  
In particular, we choose the filter weights as  
\[w_{m}=(M-m)^{\rho}\left(\sum_{m=0}^{M-1}{(M-m)^{\rho}}\right)^{-1}=(M-m)^{\rho} \left(\sum_{\ell=1}^{M}{\ell^{\rho}}\right)^{-1}; \tag{18}\]  
where \(\sum_{\ell=1}^{M}{\ell^{\rho}}\) is the normalization factor.
## 2 Materials and Methods
### EEG Data Pre-Processing  
Generally, acquiring EEG signals is a challenging task due to their weak nature and susceptibility to contamination from environmental noise or distortion caused by physiological artifacts such as ocular and muscle artifacts. Consequently, noise removal plays a crucial role in the processing of EEG signals. Furthermore, proper data cleaning may improve the signal-to-noise ratio and allow for discriminating the most meaningful features from the EEG signals.  
Figure 1: The figure shows 10/20 International Standard for EEG electrodes positioning.  
In clinical practice, trained neurologists visually detect artefacts by discarding contaminated EEG epochs. Although the pre-processing phase is operator-dependent, monotonous and time-consuming, in clinical practice, no automatic tools are applied in clinical context to detect and eliminate artefacts without eliminating useful signal parts.  
In this study, a qualified neurologist examined each EEG recording to identify and annotate epochs corrupted by noise and artifacts (refer to Figure 2). Afterwards, all EEG data were pre-processed using an automatic routine that individuates the EEG portions where the amplifier is in a saturation stage (i.e., electrode malpositioning). The procedure scans all recordings and eliminates the portions of the EEG data (for all channels) where the amplifier is in saturation mode or all EEG recordings, if corrupted for the entire duration. Then, digital filtering techniques were applied. To mitigate high-frequency artifacts and power-line interference, we specifically applied a Butterworth band-pass filter with a frequency range of 0.1 to 70 Hz. Additionally, a notch filter with a cut-off frequency of 50 Hz was utilized. These filtering techniques were employed to minimize the impact of such disturbances during signal processing, as depicted in Figure 3.  
Figure 3: The plots show filtered EEG signals acquired from electrodes positioned on the frontal and central lobes.  
Figure 2: The plots show EEG signals acquired from electrodes positioned on the frontal and central lobes.  
After noise removal, EEG signals were segmented in EEG epochs of 10 s to apply the following feature extraction methods on each epoch. Considering the average duration of each recording, an average number of 111 epochs was obtained for each channel for each subject. Segmenting the EEG signal into epochs is beneficial as it enables a more precise analysis of local variations within the signal. This segmentation approach facilitates a detailed examination of the EEG signal's fluctuations on a localized level, and also extends the dataset without using artificial methods, enhancing the accuracy of the analysis.
# An Overview of Cooperative Driving in the European Union: Policies and Practices
## 4 Current State of the Art of C-ITS Systems
### C-Roads Pilot Sites
#### 4.1.13 Slovenia  
C-Roads Slovenia pilot sites have been developed in two phases. The first, in which both ITS-G5 and cellular networks are tested, is planned along 100 km of the TEN-T core network. In the second phase, planned to start in 2020, roadside C-ITS-G5 infrastructure will be extended to the pilot length of 300 km, including critical points connected with the Central C-ITS-G5 Server real-time platform located at the Dragomelj Traffic Management Centre. The implementing bodies are the Ministry of Infrastructure and the Motorway Company of the Republic of Slovenia (DARS). The tested services are all Day-1 type, namely SSV, TJM, RWW, WTC, VSGN, VSPD, and GLOSA applications.
## 3 Results
### Pore Types and Pore Throat Characteristics  
Casting thin sections and SEM observations revealed the presence of two main types of pores in the He8 Section of the study area, including micron-scale intergranular pores and dissolved pores. Meanwhile, pore throat is dominated by micron-sized clay minerals, including intercrystalline pores, intergranular pores of overgrowth quartz, and microfractures. As nano-scale intergranular pores and dissolved pores mainly constitute tight sandstone reservoir spaces, their pore size, distribution, and quantity influences the entire tight sandstone reservoir capacity, and as micron-scale intercrystalline pores and intergranular pores of overgrowth quartz grains, their distribution, number, and shape affect the permeability of tight sandstone.  
For micron-sized pores, the pore distribution, average pore throat coordination number, and average pore size of the tight sandstones were quantitatively analyzed using Matlab and casting thin sections. For nano-scale pore throats, each type of pore was quantitatively analyzed by Matlab and SEM images. However, the whole pore throat physical property of the sample cannot be gained by thin sections. For a better understanding of the whole sample, and also to comprehensively quantify the effect of different pore and throat types on tight sandstones, high-pressure mercury intrusion curves were combined with the analysis results of Matlab. Since micron-scale pores and nano-sized pores have different size grades, the pore space, structure, and size that are exhibited are also quite different. The pore characterizations at two different scales are discussed below.