esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Performance of NS RA-Modified Asphalt
### Brookfield Rotary Viscosity Test  
The viscosity can reflect the actual usage of pavement structure asphalt at high temperatures. Under loading, the shear deformation of the high-viscosity asphalt is small; its elastic recovery ability is strong, and its permanent plastic deformation becomes small. Therefore, its anti-rutting capability becomes strong. The Brookfield rotary viscosity tests of NS RA-modified asphalts for Esso AH-70 base asphalt were conducted according to American Association of State Highway and Transportation Officials T316 by using a Digital Viscometer BROOKFIELD DV-II (Brookfield Company, Middleboro, MA, USA). According to the Superpave specifications, the viscosity of the original asphalt is required to be a maximum of 3 Pa s at 60 \({}^{\circ}\)C. The results are shown in Figure 3.  
Figure 3 shows that comparing the base asphalt and the NS RA-modified asphalt at the same temperature, the viscosity value of the modified asphalt was significantly increased with an increase in NS RA content. At 135 \({}^{\circ}\)C, the viscosity value of modified asphalt with 8% NS RA content was 1.56 Pa\(\cdot\)s, and it was approximately three times larger than the viscosity value of the base asphalt, indicating that under loading, the shear deformation of the NS RA-modified asphalt was smaller than that of the base asphalt, and that its ability for elastic recovery was stronger. Therefore, its permanent plastic deformation became smaller, and its anti-rutting ability was enhanced. At the same time, the viscosity values of the modified asphalts with NS RA ranged from 2% to 8% less than 3 Pa\(\cdot\)s at 135 \({}^{\circ}\)C, which could meet the Superpave specifications for an asphalt binder.  
Figure 3: Viscosity of the NS RA-modified asphalt.
# Improved Control Strategy of MMC-HVDC to Improve Frequency Support of AC System
###### Abstract  
With the continuous development of power electronics technology, variable-speed offshore wind turbines that penetrated the grid system caused the problem of inertia reduction. This study investigates the frequency stability of synchronous, offshore wind-farm integration through a modular-multilevel-converter high-voltage direct-current (MMC-HVDC) transmission system. When full-scale converter wind turbines (type 4) penetrate the AC grid, the AC system debilitates, and it becomes difficult to maintain the AC system frequency stability. In this paper, we present an improved inertial-response-control method to solve this problem. The mathematical model of the synchronous generator is based on the swing equation and is theoretically derived by establishing a MMC-HVDC. Based on the above model, the inertia constant is analyzed using a model that integrates the MMC-HVDC and offshore synchronous generator. With the new improved control method, a more sensitive and accurate inertia index can be obtained using the formula related to the effective short-circuit ratio of the AC system. Moreover, it is advantageous to provide a more accurate inertial control evaluation for AC systems under various conditions. Furthermore, the impact of the MMC-HVDC on system safety is assessed based on the capacitor time constant. This simulation was implemented using the PSCAD/EMTDC platform.  
modular multilevel-converter high-voltage direct-current (MMC-HVDC) transmission system; full-scale converter wind turbines (type 4), improved inertia-response control; effective short circuit ratio (ESCR) +
Footnote †: journal: Applied Sciences
# Synthesize and Segment: Towards Improved Catheter Segmentation via Adversarial Augmentation
## 4 Experiments
### Experimental Setup  
For training and testing CycleGAN, we selected X-ray images with no true catheter, including images with little to no visibly of artifacts i.e., \(1000\) training and \(500\) validation, respectively. During training, for any given image; randomly selected catheter masks (obtained offline) were augmented by random flips for composite creation. Adam [46] solver with a batch size of \(8\) was used with \(\lambda=10\) in the loss objective. The proposed method was trained with a learning rate of \(2e-4\) for \(300\) epochs. The generators and discriminators were trained alternately, with the discriminator later discarded during inference. The trained generator was later applied to synthesize images of size \(256\times 256\) following training on the composite dataset. The evaluation of generative models is often challenging, especially when ground-truth labels are absent. Instead, we qualitatively analyzed the generated images based on visual judgments and domain knowledge.  
Furthermore, we present the quantitative results of the segmentation models trained in a supervised setting with synthetically generated images when the catheter mask is present, to confirm that applicability of synthetically generated data for catheter segmentation in real X-ray angiograms. The segmentation models were trained for \(250\) epochs with an initial learning rate was set to \(1e-3\) for \(100\) epochs and gradually reduced to \(1e-5\) for the remainder. The mini-batch size was set as \(128\) with Adam optimizer [46] used to minimize  
Figure 4: (**a**) Cattheter in natural image (**b**) X-ray image without catheter (**c**) camera catheter mask generated using [45] given (**a**) as input (**d**) composited X-ray with camera catheter mask (**e**) generated X-ray image using camera catheter.  
Figure 3: (**a**) X-ray image without catheter (**b**) random groundtruth (**c**) composited X-ray with groundtruth (**d**) generated X-ray image with catheter.  
the Dice loss. The proposed synthesis and segmentation framework was implemented using Keras with a Tensorflow backend on a workstation with NVIDIA Titan XP GPU. The dice metric was used to evaluate segmentation performance; it measures the number of similar pixels divided by the total number of pixels present in both the target and predicted masks. Formally:  
\[Dice=\frac{2\times(A\cap B)}{A+B}, \tag{7}\]  
where \(A\) is the ground truth and \(B\) is the predicated mask. The dice coefficient ranges from 0 to 1, where 1 means complete overlap.
# Performance Analysis of Two-Hop mmWave Relay Nodes over the 5G NR Uplink Signal
## 3 Link-Level Co-Operative Simulator
In Figure 7, the relay node shows two blocks, respectively, inside the digital/IF/RF unit and baseband unit, which describe the receiver and transmitter stages in the relaying protocol. For the first stage of the NR-relay node, an mmWave receiver chain has been designed and implemented by means of Simulink(tm). Now, the functionality of the baseband unit of the relay node depends on the used relaying protocol, as well as was described in Section 2. In this context, the baseband unit in the A&F relay node amplifies the received signal and is transmitted to the gNodeB through the digital/IF/RF unit transmitter which is emulated as an NI-USRP 2944R. However, when the D&F relay node with or without the knowledge channel is considered, the receiver signal processing and transmitter signal processing stages are performed, respectively--demodulation-decoding and encoding-modulation algorithms. After that, the modulated signal is transmitted by means of the NI-USRP 2944R transmitter RF stage to destination (gNodeB). The last node in our link-level co-operative simulator is the gNodeB, which is achieved through an RF stage in Simulink(tm) (simulated with the same characteristics of a NI-USRP 2944R) and a baseband unit developed by Matlab(tm) tool, where the received signal decoding has been performed. Additionally, as can be seen in Figure 7, the transmitted symbols by the NR-UE node is determined and compared with the detected symbols in baseband units in the gNodeB. In this sense, the Key Performance Indicators (KPIs) of the bit error rate (BER) and throughput of the uplink mmWave MIMO NR relay node co-operative system have been measured.
## 2 Supervisory Control and Data Acquisition Systems
### Emerging Trends in SCADA Systems  
Recent advancements in technology have paved the way for the next generation of SCADA systems, characterized by the integration of advanced visualization, artificial intelligence (AI), and cyber-physical systems (CPS) [7]. Key trends include the following:  
* Virtual Reality (VR) and Augmented Reality (AR): VR and AR technologies are being explored to create immersive interfaces for SCADA systems, enabling operators to interact with virtual representations of physical infrastructure [15].
* Digital Twins: The concept of digital twins, which involves creating a virtual replica of a physical system, is gaining traction in SCADA applications. Digital twins enable real-time monitoring, predictive maintenance, and scenario analysis [18].
* Edge Computing: The use of edge computing capabilities in SCADA systems allows for localized data processing, reducing latency and improving response times [8].
* Cybersecurity Enhancements: As SCADA systems become more interconnected, ensuring robust cybersecurity measures is critical to protect against cyber threats [19].
## 1 Introduction
### Review of Related Works
#### 1.1.3 Design Considerations
In [95; 96], Markov-based techniques for the estimation of packet loss rate characteristics for dynamically varying line-of-sight (LoS) channel between the subscribers and the base stations (BSs) for high-frequency band broadband FWA (BFWA) were presented. Additionally, in [97], a broadband system was designed and evaluated for an FWA network with channel measurements to establish the appropriate temporal, spatial, and frequency characteristics. Furthermore, it was demonstrated that self-interference due to channel estimation errors is the main constraint on the system performance. Furthermore, in [98], a BFWA link fading channel was demonstrated based on an analytical model that correlates the Rician K-factor with the rain fading effects to realize a prediction model for the Rician K-factor cumulative distribution. Similarly, the Ricean fading channel model was employed in [99] for the characterization of LoS multiple-input, multiple-output (MIMO) schemes channel for the fixed wireless systems. A physical model was offered in [100] regarding the BFWA QoS statistics to study the effect of climatic conditions on the BFWA channel QoS. The BFWA channels interfered by the adjacent terrestrial links that operate at the same high-frequency band were considered to investigate the spectral and spatial coexistence of point-to-point (PtP) links and BFWA networks. In the paper, it was established that, as a result of rain spatial inhomogeneity, the resulting attenuation is the main fading mechanism that severely worsens the interference level. Similarly, in [101], interference levels in the BFWA were quantified in view of realistic rainfall variations over the propagation paths. It was inferred that, for an FWA system that operates at mm-wave frequencies, there is a need to consider rain-induced interference. Apart from the fact that this will help in effective radio communication planning, it will also facilitate an adequate design and implementation of mitigation techniques. Furthermore, to demonstrate the 5G FWA technical viability, there is a need for system-level simulations for performance analysis for different use cases. Regarding this, 5G radio deployment scenarios for FWA were defined using radio simulations in [5; 8; 11; 27]. In addition, based on empirical data measurements, the uplink (UL) traffic behavior in a BFWA network was studied in [102]. Besides, support for non-real-time and real-time BFWA network communication services was discussed in [103]. The proposed media access control (MAC) protocol in the work was based on the probing process in which information coordination and exchange between the BSs is not necessary for data packet transmission improvement.
# Optical and Thermal Remote Sensing for Monitoring Agricultural Drought
## 3 Thermal Remote Sensing
### Temperature-Based Drought Indices
When evaluated over the Australian wheatbelt using the Multifunction Transport Satellite-2 (MTSAT-2) data, the TRI showed a strong correlation with precipitation and soil moisture anomalies, and its correlations with wheat yields peaked higher and earlier by almost one month in comparison to other indices [191], implying the great potential of geostationary satellite observations for agricultural drought monitoring. Table 3 gives an overview of the indices mentioned in this section.
# Dynamic Load Modelling within Combined Transport Trains during Transportation on a Railway Ferry
## 2 Improvement of the Load-Bearing Structure of the Flat Wagon  
The purpose of this section is to highlight the features of improving the supporting structure of a flat wagon for the safe transportation of containers on a rail ferry by sea. Research conducted by the authors of the article has established that the typical scheme of interaction between the wagon and the container does not ensure the stability of the container during sea transportation [8]. In this regard, it is advisable to use wagons of model 13-9744 (TU 3182-002-47766175-2004) with special superstructures for transporting containers as part of combined trains.  
It is also possible to install such removable superstructures on the supporting structures of other models of wagons that are used for railway and ferry transport. Since the fleet of universal flat wagons has a larger number of units than a specialized one, such a solution will allow for the adaptation of universal flat wagons for the carriage of containers by sea on railway ferries. As part of this study, the model 13-401 wagon was selected as a prototype. This model of a flat wagon was chosen as a prototype because there is a project of its modernization for container transportation, developed by the Research and Development Centre \"Wagons\" (Russia). This modernization consists of placing fitting stops on the supporting structure for fastening and transporting containers. However, the authors of the article propose further improvement of this wagon for the possibility of safe transportation of containers by sea. The load-bearing structure of the wagons, in view of the installation of removable superstructures, is shown in Figure 2.  
For fastening containers on the main longitudinal beams of the frame, hinged fitting stops are installed, which makes it possible to transport containers of different standard sizes. The superstructures interact with the supporting structure by welding. The load-bearing elements of the superstructures are made of the same profiles as on the 13-9744 flat wagon. The installing of a material with viscous properties on the internal surfaces of superstructures has been proposed to reduce the dynamic load of containers. Elastomer is one option. When the supporting structure of the container interacts with such material, partial damping of natural vibrations occurs, which takes place during the roll of the ship. It is possible to use other materials with similar energy-absorbing properties.
# Deep Learning in Financial Modeling: Predicting European Put Option Prices with Neural Networks
## 3 Materials and Methods
### Analytical Solution  
The closed-form solution for a European put option is  
\[P_{\circ}=Ke^{-rT}\times N(-d2)-S_{\circ}N(-d1) \tag{2}\]  
where  
\[d1=\frac{\ln(\frac{S_{\circ}}{K})+(r+\frac{\sigma^{2}}{2})T}{\sigma\sqrt{T}} \quad\text{and}\ d2=d1-\boldsymbol{\sigma}\sqrt{T} \tag{3}\]  
Here, N (\(\cdot\)) is the cumulative distribution function of the standard normal distribution.  
These formulas are widely used in financial practice but rely on idealized assumptions, such as constant volatility, which limit their real-world applicability.  
The 3D graph in Figure 1 shows the price of a European put option as a function of the spot price (S) and time to maturity (T), based on the Black-Scholes model:  
1. **Spot Price (S):** The put option value decreases as the spot price increases, reflecting its nature to gain value when S is below the strike price (K). For S \(\gg\) K, the option price approaches zero.
2. **Time to maturity (T):** As T decreases, the option price declines, especially for S \(\geq\) K, due to the reduced probability of favorable price movements as expiration approaches.
3. **Key Behavior:** The option retains value near S \(\ll\) K due to its intrinsic value, while at S \(\approx\) K, the price is most sensitive to changes in S or T.  
This graph confirms how Black-Scholes prices options by combining intrinsic and time values, while also showing its limitations, such as assuming constant volatility.
## 3 Results and Discussion
### Effects of RPIDLs on Vehicle Speeds at Entrance of Long Downhill Tunnel
#### 3.1.2 Effect on Average Vehicle Speed  
The average speed and standard deviation of vehicles in the whole experimental section controlled by RPIDLs with different group lengths are shown in Figure 12. Compared with the average speed without RPIDLs, those with the 30 m, 60 m, and 120 m RPIDLs decreased by around 1.8%, 7.0%, and 3.5%, respectively, indicating that RPIDLs with all three group lengths decrease the average speed near the tunnel entrance. Also, the standard deviation of the vehicle speeds with the 60 m RPIDLs is the lowest, being 11.1% lower than that of the vehicle speeds without RPIDLs. Therefore, the 60 m RPIDLs decrease both the vehicle speeds and their dispersion near the tunnel entrance.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**RPIDL Length** & **No RPIDLs** & **30 m** & **60 m** & **120 m** \\ \hline Speed difference & 66.0 km/h & 59.2 km/h & 45.8 km/h & 79.1 km/h \\ \hline \hline \end{tabular}
\end{table}
Table 1: Difference between maximum and minimum vehicle speeds with and without RPIDLs.  
Figure 11: Average speeds of vehicle controlled by RPIDLs with different group lengths: (**a**) no RPIDLs; (**b**) 30 m; (**c**) 60 m; (**d**) 120 m.
# Blind Compensation of \(I/q\) Impairments in Wireless Transceivers
## 1 Introduction
However, both of these techniques, similar to [4], are data-aided techniques that, as previously mentioned, reduce the throughput of the system. Blind compensation methods for both the transmitter and the receiver \(I/Q\) imbalance compensation have been proposed in [15; 16]. The former relies upon carrier frequency offset to decouple these imbalances followed by Cholesky decomposition for the estimation procedure. While the later proposes a two-step blind compensation technique using marginalized particle filter, which suffers from high computational complexity. In addition, none of these techniques provides an experimental validation of the proposed methodologies and their resulting impairments in realistic scenarios using measurement set-ups. This paper proposes a novel post-compensation methodology for the transceiver (Tx-Rx) impairments that has the advantage of joint blind compensation for both the modulator and demodulator \(I/Q\) imbalances at the receiver, based on the statistics of the received signal. In addition, the proposed technique also eliminates the need for decoupling these imbalances. Statistics-based methods have been shown to perform reasonably well in the case of other front-end impairments such as power amplifier nonlinearity [17; 18]. The proposed methodology requires only prior knowledge of the standard deviation of the actual \(I\) and \(Q\) signals and does not require pilots or training sequences. Another important feature of the proposed methodology is that it does not need a feedback path at the transmitter, resulting in a much simpler architecture. The restrictions for low cost and implementation size of the uplink scenario (mobile to base station communication) demand effective post-compensation schemes due to the difficulty in implementing complex compensation schemes in the mobile set, while maintaining computational and cost efficiency. Post compensation allows the base station receiver to apply the mitigation algorithm, as it has more computational resources and hardware flexibility than that of the mobile receiver system. The implementation of these methods helps avoid the feedback path at the transmitter saving valuable hardware resources such as demodulators, filters, and analog-to-digital converters (ADCs) and the resulting impairments. The rest of the paper is organized as follows: Section 2 starts with a detailed model description and mathematical formulation, followed by the proposed mitigation strategy. Section 3 describes the performance evaluation of the proposed methodology using computer simulations. Section 4 provides a discussion regarding the proposed work. Section 5 presents the measurement setup and results obtained using the proposed methodology. Conclusions are summarized in Section 6.
# Software Defined Networking for Improved Wireless Sensor Network Management: A Survey
## 4 WSN Applications and the Need for SDN-Based Management
### Wireless Home Networks  
WSNs for home use have seen increasing demands with arising smart homes and buildings in general. Homes are now composed of a network of light, motion and temperature sensor nodes that can be integrated in appliances to introduce smart capabilities in a home. This network can also be linked to the Internet to allow users to remotely control these home appliances. However, in addition to a network of smart devices is a network of other communication technologies such as WiFi, ethanet, cellular and power-line communications. The challenge with such a heterogeneous network is the lack of an automated system to enable network optimization by selecting the best communication technology to use, this decision is usually made by the user manually. [PERSON] et al. [71] have proposed an SDN-based management technique to improve management of such heterogeneous home networks by using OpenFlow-enabled link switches. SDN techniques have also been proposed to enhance the development and management of smart homes [72]. Smart device use is increasing in homes and this creates difficulty in management especially with the advent of video streaming services such as Youtube and Netflix. User demand and control becomes an important management factor leading to the need for smart home network management based on SDN. In addition, these user applications such as voice, video, gaming and others have to compete for bandwidth resulting in poor quality of service. [PERSON] et al. [73] have proposed and experimented on an SDN-based solution that allows users some control over the service quality for their devices enabled by ISPs. Other bandwidth allocation techniques for managing home applications like video and voice have been proposed based on SDN to improve quality of service including home slice [74], Network Assisted Video Streaming (NAVS) [75] and SDN@home [76].