esa-sceva/satcom-chunk-collection huggingface dataset:
# Multi-Layer Problems and Solutions in VANETs: A Review
## 2 Multi-Layer Challenges in VANETs
### Multi-Layer Challenges
#### 2.1.2 MAC Layer
The control channel is responsible for the safety messages, whereas the service channel is for the non-safety applications. A synchronization interval (Sync Interval) includes one service and one control channel. The channels shift in operation to providecontinuous and alternating access. It is important here that the channels are utilized in the most efficient way in order to support the urgent safety messages. [PERSON], et al. [PERSON] et al. (2019) proposed a scheme to efficiently utilize the SCH which enables the service providers to be able to broadcast their services to as many vehicles as possible. The work also highlights the hidden terminal problem that can occur in a broadcast transmission in multi-channel environment. * Contention versus Scheduling: Using Time Division Multiple Access instead of CSMA has shown performance improvement in several studies mentioned in the next section. * Hidden and Exposed Terminal Problems: The Hidden and Exposed Node problem is perhaps one of the most challenging issues related to the VANETs due to the broadcast nature of the IEEE 802.11p Control Channel (CCH). The Hidden and Exposed Node Problem is shown in the Figure 2.  
As shown in the Figure 2a, the hidden terminal problem occurs when node B is in the range of both nodes A and C but node A and C are not in the range of each other, so both can send data to node B and the collision is unavoidable as both cannot hear transmission of each other. In exposed terminal problem, shown in Figure 2b, B sends data to A, C can hear the transmission from B and prevents its transmission to D, even if it can send the data to D without any problem. C is therefore the exposed node [PERSON] et al. (2019). The MAC protocol should be designed in order to avoid this problem as it can affect the performance of the network and thus limits the scalability. * Distributed versus Centralized Approach: Since the VANETs are decentralized in nature, the MAC Protocol should provide good channel access, however the concepts of a centralized network can be applied to VANETs such as Clustering. Clustering based MAC protocols can be used in this regard. A few cluster based VANETs have been proposed with a cluster head (CH) acting as a centralized node [PERSON] et al. (2016); [PERSON] et al. (2016); [PERSON] et al. (2016). The cluster head is responsible for synchronization between the nodes. For a large scale network, several cluster heads exist and a rapidly varying nature of the network can put a limitation on this.
## 8 Security and Privacy Risk Assessment
### Security and Privacy Risk Assessment at the System Architecture Phase  
To conduct security and privacy risk assessment at the system architecture phase, the updated product requirements and system architecture will be taken as an input to this phase. Figure 9 illustrates the steps to conduct a risk assessment at the system architecture phase.  
Figure 9: Security and privacy risk assessment steps in the system architecture phase.  
Below is the list of key tasks that will be conducted during the security and privacy risk assessment at the system architecture phase:  
* Review system architecture according to security and privacy principles and requirements identified in Section 8.3.2.6.
* Apply risk analysis to identify the security and privacy risks.
* Identify acceptable and unacceptable risks.
* Identify the list of unacceptable risks which will require controls to mitigate.
* Update security and privacy requirements and product requirements with unacceptable risks.
* Check whether any update to the current system architecture is required due to newly identified security and privacy requirements. If yes, then make necessary changes to the system architecture and conduct risk analysis followed by risk evaluation and treatment.
# An In-Vehicle Smartphone RTK/DR Positioning Method Combined with OSM Road Network
## 3 Results  
### Experimental Program  
The experimental site is the campus of Southeast University in Nanjing, China, where the vehicle is driven along the route shown in Figure 5. The road is a single two-way lane with a total length of approximately 7200 m. The white circle is the starting point, and the white square is the ending point. The orange lines represent the open road section, while red one represents the complex road section. In order to obtain the reference trajectory of the smartphone, a geodesic GNSS receiver with a positioning accuracy of 3 to 5 cm is fixed on the hood of the car. Moreover, the horizontal distance between the smartphone and the geodetic GNSS receiver is measured, which is used to calculate the precise coordinates of  
Figure 4: Comparison of horizontal errors. (**a**) Smartphone Huawei P30; (**b**) Smartphone Huawei P40.  
the smartphone. The equipment installation is shown in Figure 6. Geodesic GNSS receivers are in the red square. Inside the car, two smartphones are affixed by brackets: Huawei P40 on the left and Huawei P30 on the right.  
During the test, the smartphone integrates the acquisition module of satellite observation data and inertial navigation data, receives the observation data from the reference station in real time through the network, and performs RTK positioning. At the same time, smartphones internally store acceleration, angular velocity, magnetic field strength, gravitational acceleration, and GNSS observation information. RTK positioning frequency is 1 Hz, and the inertial sensor data sampling frequency is 100 Hz. The test was repeated four  
Figure 5: Vehicle driving route.  
Figure 6: Equipment placement.  
times, and the results of each test were completely independent. After the test, RTK/DR positioning solution was performed.  
The antenna phase center of a smartphone is generally above the midpoint of the top. During dynamic positioning, since the smartphone's pitch angle and roll angle are continually changing, the position of the antenna phase center is also continually changing. Since the actual pitch and roll angles cannot be obtained, it is almost impossible to measure the smartphone's antenna phase center accurately. The smartphone is placed close to vertically, as shown in Figure 6, so this work ignores the influence of the antenna phase center on the horizontal positioning accuracy.
# Deep Learning-Based Flap Detection System Using Thermographic Images in Plastic Surgery
## 3 Results  
### Dataset  
For the development and training of the proposed neural network, data were collected from 40 patients who required surgical intervention to cover a tissular or cutaneous defect using flaps (in 2023). Of these, 16 were local advancement, rotation, transposition, or interposition flaps; 7 were axial pattern flaps; 11 were pedicled flaps; and 6 were free flaps. To increase the quality and heterogeneity of the training data, each selected case represented a particular, different case, as no two flaps were the same in the database. A total of 285 images were acquired from all patients, with the original size of the images being 320 \(\times\) 240. However, for each case, two images were chosen as the most accurate and illustrative representations of the flaps. In this way, 80 images, 2 from each patient, were used as training data and processed according to the previously mentioned protocol. From the initial dataset of 80 images, 60 were used for training, 5 for validation, and 15 for testing. In addition, the dataset used for training was augmented by applying various transformations such as rotation, flipping, cropping, padding, and elastic transformations. Following the augmentation process, from the original 60 images, a total of 480 images were obtained and used as training data for the DL algorithm.  
The size of this uniquely generated dataset of thermographic images of flaps is relatively small compared to other open source datasets [38; 39; 40] used for training and testing image segmentation algorithms for medical applications. This is primarily due to the smaller number of patients who have undergone surgical intervention to cover a tissular or cutaneous defect using flaps, as well as the arduous process required to generate the high-quality thermographic images of the flaps and the corresponding human-annotated binary images used as masks. More advanced methods could be used to augment the dataset, such as generating synthetic data using generative adversarial networks (GANs) or few-shot learning, which will be explored in future work. For this study, however, only the aforementioned training and testing data were used.
# Mobile Network Performance and Technical Feasibility of LTE-Powered Unmanned Aerial Vehicle
## 4 Results
### Drone Performance Evaluation  
Figure 21 shows the results of the data rate as well as latency for packet transmission from the drone to the ground station and vice versa. The average packet data transmitted from the drone to the ground station was 1303 kbps, and the average data received was 20 kbps with a delay of 94 ms for both uplink and downlink. However, according to the 3 GPP release-15 standard [19], the data rate requirement for CC and payload communications in uplink is 100 kbps and 4 Mbps with a latency of less than 50 ms. Therefore, the performance of the current LTE network needs to be improved for providing connectivity for BVLoS drone use cases that require real-time control and high-quality image or video transmission.
# Research on the Influence of Anxiety Psychology on Unsafe Behavior Among Construction Workers
## 4 Model Validation and Result Analysis
### Questionnaire Reliability and Validity Testing
#### 4.1.2 Confirmatory Factor Analysis (CFA)  
This study conducted confirmatory factor analysis (CFA) on the formal survey data using AMOS 24.0 software, with the results summarized in Table 3. The evaluation criteria included standardized factor loadings, composite reliability (CR), reliability coefficients, measurement errors, and average variance extracted (AVE). A measurement scale was deemed to exhibit satisfactory convergent validity only if the following thresholds were simultaneously met: standardized factor loadings > 0.5, CR > 0.6, and AVE > 0.5. As shown in Table 4, the standardized factor loadings for construction workers' anxiety psychology and its dimensions (organizational climate, job satisfaction, safety competency) as well as unsafe behaviors all exceeded 0.5, with reliability coefficients > 0.5, CR values > 0.6, and AVE values > 0.5. These results confirm that the survey data for anxiety psychology, organizational climate, job satisfaction, safety competency, and unsafe behaviors demonstrate robust convergent validity and model fit, with all indices meeting the established criteria.
# Scaling of FAPAR from the Field to the Satellite
## 2 Study Area and Data  
### Study Area  
The study area is located in Wuxing Village, Zhangye City, China, which is at the midstream of the Heihe River Basin (Figure 1). The Heihe River is the second longest inland river going through distinct landscapes from mountain cryosphere at the upper stream, the artificial oasis at the midstream and the natural oasis at the downstream. The study area is one focus experimental area (FEA) at the midstream that belongs to one key experimental area (KEAs) for intensive and long-term observationsin HiWATER [32]. The study area features a compound of croplands (72%), residential land (24%) and woodland (4%). Major crops are maize and small patches of orchards and vegetables.
# A Structure for Accurately Determining the Mass and Center of Gravity of Rigid Bodies
## 5 Physical Experiments  
Mass and CG of a sample were measured 20 times with the traditional structure and the improved one respectively, as shown in Figure 13, and the standard deviations of the data are listed in Table 1, which means that the new structure has higher repeatability. The accuracy of the load cell is 0.02%, and the range of the load cell is (0-220) kg.  
Figure 11: The simulation results of the side forces.  
Figure 12: The simulation result of offsets between the loading axes and the designed axes.  
Figure 13: Experiment platform for measuring mass and CG.  
According to the results of the mass measurement, the standard deviation of mass is 0.05 kg, and the maximum error is \(-0.07\) kg. Meanwhile, the standard deviation of the CG along X axis is 0.04 mm, and the standard deviation of the CG along Y axis is 0.05 mm, which means that the improved structure can be used to measure the mass and CG with high accuracy.
# All About Audio Equalization: Solutions and Frontiers
## 3 Parametric Equalizers
### FIR Shelving Filter Designs  
All types of equalizers discussed herein were originally designed as analog filters, and their digital implementation as IIR filters follows the analog designs as closely as possible. However, FIR (Finite Impulse Response) shelving filters have also been proposed. [PERSON] and [PERSON] [43,44] and [PERSON] [45] applied clever methods to design linear phase FIR shelving filters using long delay lines and a few mathematical operations per output sample. [PERSON] and [PERSON] used a multirate approach to implement the bass shelving filter at one fifth of the audio sample rate while the treble shelving filter was running at the full rate in a linear phase tone control system [46].  
Nevertheless, the FIR shelving filter designs have not become popular. One reason is that processing delay is a concern whenever any equalizer is used in live performance. While the maximum allowable total delay in an audio system may be a matter of discussion, it is safe to require each individual device to have the lowest possible processing delay, so as to allow cascading of several devices. This suggests using minimum phase IIR filters instead of linear phase FIR filters, since FIR filters typically exhibit higher latency for the same performance. Another motivation to use minimum phase equalizers is that they emulate more closely the behavior of analog filters.
## 3 Results and Discussion
### Flour Quality Parameters
The lowest (N\({}_{1}\)) wet gluten content among all cultivars was found in the flour of Hyking and Hybery hybrid cultivars. A similar trend was observed for the differences between the tested cultivars fertilised with N\({}_{1}\) and N\({}_{2}\) doses in terms of dry gluten, which ranged from 7.9 to 11.0 [40]. The range of wet and dry gluten content in the flour of the studied hybrid wheat cultivars was similar to the values of these parameters reported by [PERSON] et al. [41] and [PERSON] et al. [8]. However, higher contents of wet gluten in the range from 28.3 to 37.0% were found by [PERSON] et al. [42]. The gluten index is the parameter used to determine the quality of washed gluten. According to [PERSON] et al. [26], the cultivar genotype is the main factor for the statistically significant variability of this parameter. In the conducted study, no significant influence of cultivar (with the exception for Hybery and Hyventohybrid cultivars) and N fertilisation (with the exception for the Hyvento hybrid cultivar and the Hondiappopulation cultivar) on the values of this parameter could be determined. According to [PERSON] et al. [5] GI values between 75 and 90 ensure the optimum bread baking quality. The GI value in the flour of the majority of hybrid cultivars ranged from 94 to 99, indicating too strong flour to be applicable for baking. The flour of the Hyvento hybrid cultivar was assessed markedly more favourably, as its GI remained in the optimum range from 83 (N\({}_{1}\)) to 92 (N\({}_{2}\)). The study results show a negative linear correlation between GI and bread specific volume (r = -0.64, \(p\) < 0.05), agreeing with the results obtained by [PERSON] et al. [26]. Compared to the population cultivars, the Hyfi hybrid cultivar (N\({}_{1}\), N\({}_{2}\)) was characterized by a higher total ash content. The Hyfi and Hyvento hybrid cultivars (N\({}_{1}\), N\({}_{2}\)) compared to the population cultivars were characterised by a significantly higher value of wet gluten content. The flour of the Hyvento hybrid cultivar was definitely more advantageous as compared to the population cultivars as the GI was in the optimal range from 83 (N\({}_{1}\)) to 92 (N\({}_{2}\)). The values of the coefficient of variation (CV) for the N\({}_{1}\) and N\({}_{2}\) doses were similar for the wet gluten as well as the dry gluten and falling number. The use of a higher dose of N\({}_{2}\) increased the stability of the gluten index whereas the ash content was characterised by higher variability.
# Cooperative Content Caching Framework Using Cuckoo Search Optimization in Vehicular Edge Networks
## 5 System Model
### Content Caching  
Data are cached on MBS, RSUs, and vehicles, as caching capacity of the vehicle is limited, and most recently fetched data are cached in it. While RSU and MBS servers have more caching and computation capability, both can serve a number of users at a time. These vehicular edge computing servers (MBS, RSU) download all the data from the cloud server and database back-haul link. Popular data are cached in BS, while location-based data are cached in RSU, and vehicle caches recently used data. After predicting, popularity data are downloaded one time on BS and all RSUs cooperatively receive copies of downloaded content from BS. There is no need to download the content again by all RSUs; end-users/vehicles will fetch that content from their controlling server. All the vehicles within 100 m are controlled by a single RSU; however, 1 MBS can serve a number of RSUs at a time server.
# Analysis of 5G and LTE Signals for Opportunistic Navigation and Time Holdover
## 3 Results  
### Site Survey  
The first step of the data collection process was a survey of the available cellular base stations visible from the chosen antenna location, the results of which are placed in Table 2, where the ID of each visible cell is presented along with the associated downlink carrier frequency and operator information.
## 3 Results and Discussion
### Results of Determination of Total Phenols, Proanthocyanidins and Antioxidant Activity  
The concentrations required for 50% inhibition efficiency are shown in Figure 1c. All the extracts achieved high values of inhibitory effectiveness. The visible difference, however, is the amount of extract concentration required to achieve 50% inhibitory potency. For example, curcumin has high percentages of antioxidant activity and low concentration (EC\({}_{50}\) = 0.708 mg/mL) is required to achieve 50% inhibitory potency. The figures are similar for grapes (EC\({}_{50}\) = 0.681 mg/mL). According to the literature, to obtain 50% antioxidant activity of curcumin extract, prepared by continuous magnetic stirring in methanol at 25 \({}^{\circ}\)C from different types and varieties of turmeric, the required concentrations of extract were measured from 0.03 to 0.23 mg/mL, which comes close to the results of this study [96]. However, rosmary (EC\({}_{50}\) = 2.199 mg/mL), horsetail (EC\({}_{50}\) = 3.384 mg/mL), and goji berries (EC\({}_{50}\) = 3.604 mg/mL) require a slightly higher concentration. The contents of the proanthocyanidins in mg per gram of material selected (mPAC/g material) are shown in Figure 1b, and the total phenol content in mg per gram of the selected material (mg GA/g material) is shown in Figure 1a. The values of proanthocyanidins and total phenols (mg/g material) are higher in cases of higher levels of antioxidant activity. With aqueous extracts of turmeric, methanolic extracts are also approximated in the measurements of total phenols: Methanolic extracts have reached a total phenol content of 43 to 158 mg GA/g extract [96]. Also, a study with ethanol extract confirmed our results on high levels of proanthocyanidins, a type of flavonoid known for its high antioxidant properties. They measured about 1.38 g/L [97].
# First Evidences of Ionospheric Plasma Depletions Observations Using GNSS-R Data from CYGNSS
## 3 Results
### Bubbles and Depletions
Another day of interesting results, this case in the Indian Ocean during 20 May 2019, is shown in Figure 6:1 As seen in the plot, the Indian Ocean was calm during that day in regions from the Equator  
Figure 6:2 Peak in \(S_{4}\) value in eastern part of northern Atlantic on 24 August 2017.  
to the North. The plot only shows the \(S_{4}\) values greater than 0.05, and they are distributed in regions relatively delimited between the Equator and latitude 15\({}^{\circ}\)N.  
Table 3 shows \(S_{4}\) peaks above 0.2 lasting for at least 5 s during that day, indicating its properties. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Date (dd-mm-yy)** & **LT** & **Sat** & **Ch** & **Lat (o)** & **Lon (o)** & **Duration (s)** & **Length (km)** & **Inclination (o)** & **Max \(S_{4}\)** \\ \hline
24-08-2017 & 4:34 & 1 & 1 & 36.53 & \(-\)60.96 & 9 & 67.3 & 29.2 & 0.31 \\  
Better statistics can be extracted by obtaining these tables for a large number of days. In the following lines, the study of 25 days equally distributed every 15 days from March 2017 to March 2018 is presented. The methodology used is to parse the whole day in all the oceanic regions from 40\({}^{\circ}\)N to 40\({}^{\circ}\)S recording the events with \(S_{4}\) above 0.2 lasting more than 5 s. The number of peaks recorded per day in the year is shown in Figure 6:3  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline
**Date (dd-mm-yy)** & **LT** & **Sat** & **Ch** & **Lat (\({}^{\circ}\))** & **Lon (\({}^{\circ}\))** & **Duration (s)** & **Length (km)** & **Inclination (\({}^{\circ}\))** & **Max S4** \\ \hline
20-05-2019 & 19:05 & 1 & 3 & \(-\  
Figure 16 shows the histogram of those peaks in terms of the LT in which they were recorded, according to the timezone. It shows a peak around 6 h in the morning, which matches to the mean sunrise time. Figure 17 shows the same data regarding the maximum \(S_{4}\) value reached during the peak.