esa-sceva/satcom-chunk-collection huggingface dataset:
# A Connected and Autonomous Vehicle Reference Architecture for Attack Surface Analysis
## 6 Discussion
### Prioritising Attack Surface Analysis  
Given the limited resources, defenders need to prioritise specific attack surfaces to protect, starting with threats that pose a high risk (high likelihood and high impact). Therefore, defenders need to perform a risk assessment which takes into account threat agents' capabilities and motivations as well as the available controls in the system. However, performing a risk assessment is complicated, takes time as it involves a large number of threats and may contain uncertainties in the calculated risk. Moreover, CAV risks are not static due to its dynamic operating environments. Consequently, the risk assessment will need to be repeated frequently to adapt to such changes. Therefore, to make the analysis more effective, it is important to shape the focus by prioritising the security resources for several core parts.  
We argue that the core parts that should be prioritised are critical functional components exploited frequently by threat agents. When proper controls are applied the corresponding attack surfaces will be reduced, which creates further challenges for attackers. For CAVs these components are: (i) Communication, (ii) Sensors and (iii) Data Analysis. Wireless or physical communication is the vector through which many cyber-attacks will be perpetrated, as it acts as a gateway between external agents and the internal components. Sensors are important because they provide information about CAV's surrounding environments. If sensor information is unavailable or modified maliciously, CAV may be manipulated to make harmful decisions. Finally, the Data Analysis is important, as it influences CAVs' autonomous functions.
## 1 Introduction
However, these models may not provide adequate validation to align the REGCs. This violates the design and operational requirements of WPPs mentioned in [22; 23; 24]. An interconnected system was developed by integrating a LSWPP with the IEEE 9 Bus Power System in [25]. The study mainly focused on developing the point of common coupling (PCC) protection system that adapts to the conditions of the interconnected system and responds to the faulty conditions for both normal and increased loading conditions. The work published in references [1; 3; 4; 14; 26] emphasized the significance of REGCs for LSWPPs in the grid-connected mode of operation. The significant gap in all the studies reviewed above is that none have studied the LSWPP alone to ensure its operation meets the REGC specifications before integrating it into the considered power grid. This work stands out in the field due to its unique approach of combining REGC discussions with case studies. This approach provides a better understanding of the implications of integrating large-scale WPPs into the power grid. The significance of this work lies in its focus on the REGCs requirements, a crucial yet underexplored subject in the realm of renewable energy. Our revisit to these requirements, with the evaluation performed using a case study, promises to shed new light on their role in integrating LSWPPs, underscoring their importance in the field. Following the introduction of this article, Section 2 revisits REGCs with an emphasis on WPPs. The overview of the proposed test system is in Section 3. This includes the modeling and simulation consisting of a few case studies of the power grid into which the LSWPP is integrated and the LSWPP itself. In contrast, the integration of the LSWPP into the power grid is dealt with in Section 4. Section 5 is dedicated to the crucial evaluation of the operation of the interconnected system, which also formulates an essential aspect of our research. Section 6 discusses the results. Finally, conclusions and future work are drawn and stated in Section 7.
# Analysis of Multi-Antenna GNSS Receiver Performance under Jamming Attacks
## 2 Methodology
### Multi-Antenna Signal Simulations and Processing
#### 2.2.1 Power Minimization (PM)  
The PM approach was implemented in the pre-correlation stage with the receiver architecture shown in Figure 2. The covariance matrix of the received signal can be obtained as  
\[\mathbf{R}_{\mathbf{xx}}=\frac{1}{T}\sum_{1}^{T}\mathbf{xx}^{H} \tag{13}\]  
where \(T\) is the number of temporal Intermediate Frequency (IF) samples and \(\mathbf{R}_{\mathbf{xx}}\) is of dimension \(M\!N\times M\!N\).  
The optimum weight vector is given by [27]  
\[\mathbf{w}_{\text{PM}}=\frac{\mathbf{R}_{\text{xx}}^{-1}\mathbf{q}}{\mathbf{q}^{H }\mathbf{R}_{\text{xx}}^{-1}\mathbf{q}} \tag{14}\]  
where \(\mathbf{q}\) is the constraint vector with dimension \(M\!N\times 1\) and given by  
\[\mathbf{q}=[1,\ 0,\ 0,\ \ldots,\ 0]^{T} \tag{15}\]
# Performance Validation of Control Algorithm Considering Independent Generator Torque Control in PCS
## 3 Simulation Validation
Furthermore, it was determined that the variability in the generator torque command resulting from the PCS torque control system, as opposed to a constant value in the reference power control, contributes to oscillations in the generator power, indicating a limitation of the PCS torque control system. In addition, to verify the performance of the power control with the applied control switching logic, the simulation results under the conditions of average wind speeds of 10 m/s and 12 m/s, and turbulence intensity according to the normal turbulence model Class C, were compared. Figure 8 shows the simulation results of the power control considering the PCS independent generator torque control designed in this study, with mode switch and SPS applied to each algorithm, illustrating the rotor speed, pitch angle, generator torque, generator power, and the fore-aft bending moment at the tower bottom. Figure 8a presents the simulation results under the condition of an average wind speed of 10 m/s, while Figure 8b shows the results under an average wind speed of 12 m/s. Although the time-series data suggest similar performance, it can be observed that the peak values of the rotor speed are reduced due to the operation of the pitch actuator. This can be quantitatively confirmed through the comparison of the Design Equivalent Load (DEL) acting on the fore-aft bending moment at the tower bottom, and Table 5 presents the DEL values of the fore-aft bending moment at the tower bottom based on the simulation results. \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Condition**} & \multicolumn{4}{c}{**Electrical Power (kW, \%)**} \\ \cline{2-5}  & **Mean** & **Relative Diff.** & **Std.** & **Relative Diff.** \\ \hline Ref. with Mode SW (10 m/s) & 80.25 & - & \(18.16\) & - \\ PCS with Mode SW (10 m/s) & 80.35 & 0.12 & 17.35 & \(-4.46\) \\ Ref. with Mode SW (12 m/s) & 97.00 & - & 7.22 & - \\ PCS with Mode SW (12 m/s) & 96.55 & \(-0.46\) & 6.21 & \(-13.99\) \\ \hline \end{tabular}
\end{table} 
Table 4: Comparison of the generator power based on the simulation results.
# Future of IoT Networks: A Survey
## 1 Introduction  
The age of the Internet of Things (IoT) is forthcoming [1]. It will give objects and even generated contents to the ability to communicate with other mediums. With the generated data from every object, the data will not remain raw as they are today but will be customized to the users based on their needs and even converge with other data. The concept of IoT is simple, although its capability is unlimited and its usage can change the entire paradigm of legacy technology. It is based on embedding a network interface into objects, enabling communications among them to provide various services for users. Consequently, each object will have its own identifier, such as an Internet Protocol address (IP address) in the current Internet that can connect and communicate with other objects through the IoT networking environment. Unlike the era before IoT, when the users could obtain data only from the service provider, the users can directly access the sensors and give commands to the actuators. With this capability, data from IoT applications will be utilized to provide a novel service to industry, academia, and even personal use.  
To successfully manage IoT services, the IoT infrastructure must be well-designed. However, there are some limitations in the current research and development plan to create a complete IoT environment. First, the applications and services for IoT are sporadically developed from numerous vendors without the usage of the standard technology [2]. Second, there is no standard networking protocol for IoT applications. Even today, there are diverse networking protocols such as Wi-Fi, Bluetooth, ZigBee, Z-wave, and Long Term Evolution (LTE). Nonetheless, there is no device that can communicate with all existing networking protocols. To overcome this issue, the gateway, or the IoT device that can support heterogeneous networks, is crucial to create one complete IoT network. Additionally, the increasing number of IoT devices and the necessity of Big Data processing will expand the number of packets, where this issue can be a critical problem to the legacy network architecture.  
In this paper, we focus on the network layer of the IoT. Although many studies have already conducted surveys on IoT, some survey papers primarily focused on the service aspect of IoT. Moreover, surveys in [3; 4; 5; 6; 7] present results on each focused subject. Nevertheless, many papers consider tomaintain the legacy network infrastructure, since the modification of existing network infrastructure costs highly. Obviously, the concept of future network for IoT should be researched in a national scale, and this consideration is an essential prerequisite to realize IoT environment. Therefore, we will discuss the reason why the current network is insufficient as an IoT network. Furthermore, we will describe the needs for modification and argue in favor of creating a novel network infrastructure to support the IoT environment.
## 1 Introduction
Although the OSM project shows a high membership number and contributors are active, it needs to be noted that most of the VGI projects, and thus also OSM, rely on volunteers that do not necessarily have professional qualifications and background in geodata collection or surveying [6]. Furthermore, contributing to the project depends largely on technical aspects such as specific equipment, e.g., a PC/laptop, an internet connection, or potentially also a GPS receiver or Smartphone. The population density of the specific areas naturally plays a role too. Thus, the probability that more densely populated areas are mapped or more complete than sparsely populated areas is beyond question. However, the local knowledge of most participants should in fact make them local experts [27]. This raises numerous questions: How does the data perform in comparison (relative completeness and attribute accuracy) with other proprietary geodata providers? Can a difference be detected between urban and rural areas? How has the OSM project data developed in recent years? Can a projection be made for the data's future development? The remainder of the paper is structured as follows: The following section gives an overview of prior OSM quality research conducted in recent years. Also, the study area and data preparation steps applied during our research are being discussed. The next section provides the results conducted during our research with regards to the OSM street network evolution for the years 2007 to 2011. This is followed by a discussion of the results and aspects of future work.
## 6 Conclusions and Future Direction
### Future Direction
#### 6.2.2 Architectural Improvement for Intelligent Communication Systems
For example, in tele-medicine applications, the communication system might prioritize the accurate transmission of fine details in medical images that are critical for diagnosis, while, in video conferencing, the system might focus on maintaining smooth motion and natural facial expressions. From an implementation perspective, future design should consider adaptability through modular architectures where different perceptual quality modules can be activated based on the application requirements. These modules could employ specialized generative models trained on task-specific data to optimize the perceptual quality for particular use cases.
# Matching-Based Resource Allocation for Satellite-Ground Network
###### Abstract
We conduct a large number of simulation experiments, and compared with the greedy method, the random allocation method, and the two-sided matching method, and verify that the proposed algorithm is effective in delay, satellite revenue, etc. The rest of this article is organized as follows. Section 2 introduces the related work in recent years. Then, the model of the satellite-ground network resource allocation system is expounded, and in Section 4, maximizing satellite revenue is taken as an optimization problem. In Section 5, a three-sided cyclic matching algorithm is proposed to deal with the optimization problem. Then, in Section 6, the simulation results and corresponding analysis are given. Finally, conclusions are drawn in Section 7.
This study investigated the spatial distribution of the spawning period of the Pacific herring in Jinhae Bay using a ship-based echosounder and identified the exact period during which the adult and immature Pacific herring migrated, by installing a moored echosounder in the nearby waters of Jam Island in the bay and operating it for about 70 days during the fish spawning period from winter to spring. The purpose of the surveys was to compare the acoustic results with environmental data to determine the exact timing of the spread after spawning and determine the exact prohibition period to protect Pacific herring resources.
## 4 Discussion
As shown in Figure 6d, when the thickness of SiO\({}_{2}\) increases, the absorption peak gradually shifts to low frequencies. At the same time, the number of absorption peaks increases and the bandwidth narrows. When the thickness of SiO\({}_{2}\) decreases, the absorption peak gradually shifts to high frequency, and the bandwidth becomes larger. However, the number of absorption peaks and the absorptance decrease. The position of the resonance peak is affected by the thickness of the medium. The position of the resonance peak and the absorptance of the entire absorber are affected by the SiO\({}_{2}\) and VO\({}_{2}\). VO\({}_{2}\) and SiO\({}_{2}\) determine the impedance of the proposed system and have a significant influence on the absorptance and bandwidth. The results further confirmed the important role of geometrical structure parameters in absorber performance. After optimizing the structural parameters, a high-performance tunable dual broadband terahertz absorber is obtained. Figure 5: The electric field distribution in the top view at 2.3 THz (**a**), 3.6 THz (**b**), 8.8 THz (**c**) and 10.4 THz (**d**).
# Cooperative Multi-Objective Optimization of DC Multi-Microgrid Systems in Distribution Networks
## 4 Cooperative Multi-Objective Optimization Model
### Outer-Loop Optimization  
The outer-loop optimization model takes the network loss as the optimization goal. By optimizing the reactive power output of the DC/AC converters \(Q_{m,t}^{G}\), the daily network loss of the distribution network is minimized, thereby reducing network loss cost and carbon emissions of MMGS and the distribution network [30]. This paper assumes that the \(m\)-th MG is connected to node \(i\) of the distribution network.  
\[f_{2}=\min W_{S}^{G} \tag{32}\]  
\[W_{S}^{G}=\sum_{t=1}^{T}\sum_{i,j=1}^{N_{\text{tr}}}k_{i}R_{ij}\frac{P_{ij,t}^ {2}+Q_{ij,t}^{2}}{V_{ij,t}^{2}} \tag{33}\]\[W_{S}^{I} =W_{S}^{G}-W_{S}^{B} \tag{34}\] \[P_{ij,t} =P_{ij,t}^{0}+P_{m,t}^{G}\] (35) \[Q_{ij,t} =Q_{ij,t}^{0}+Q_{m,t}^{G}\] (36) \[W_{S}^{I} =f_{2}-W_{S}^{B}\] (37) \[C_{il}+C_{co} =W_{S}^{I}\bullet\Delta t\bullet k_{il}+W_{S}^{I}\bullet\Delta t \bullet e_{c}\bullet k_{c} \tag{38}\]  
\(W_{S}^{I}\) is the daily operating increased network loss of the distribution network. \(N_{lr}\) is the number of branches. \(i,j\) are the nodes, \(k_{i}\) is the state variable of the \(i\)-th branch switch, 1 means closed, 0 means open; \(R_{ij}\) is the resistance of branch \(ij\), \(P_{ij,t}\), \(Q_{ij,t}\) are the active and reactive power of branch \(ij\) in the \(t\)-th hour, \(V_{ij,t}\) is the voltage, \(P_{ij,t}^{0}\), \(Q_{ij,t}^{0}\) are initially active, reactive power when connected without MMGS. \(P_{m,t}^{G}\), \(Q_{m,t}^{G}\) are the active and reactive power through the DC/AC converters injected into node \(i\) by the \(m\)-th MG connected to node \(i\). To facilitate the calculation of network loss, a day is divided into 12 small periods, with a time interval of 2 h.
## 4 Simulation and Experimental Results
### Network Instability Period  
For a closer inspection, Figure 4 shows in which round has died the first sensor node. Additionally, the round in which the half of the nodes have died, and the death of all nodes is also reported in this figure. According to the obtained results, it is observed that the proposed protocol achieves the highest values. In our method, the first dead node occurs after 230 rounds, the 50% of the nodes died after 340 rounds, and the 100% of the sensor nodes died almost in 450 rounds. The protocols in comparison show inferior indices regarding the first, half, and last dead in the network.  
Figure 3: Clustering evolution of the network: (**a**) network configuration in round 5, (**b**) in round 100, (**c**) in round 270, and (**d**) in round 400.
# Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region
## 4 Results and Discussion
### Winter Wheat Mapping
#### 4.2.2 Optical Image Classification and Accuracy Assessment  
In order to evaluate the effect of the combination of SAR and optical images on the classification accuracy, the optical images were classified by RF and SVM. The accuracy of winter wheat classification is shown in Figure 6. For RF and SVM classifiers, the classification accuracy was the highest at the end of March 2016 (with the overall accuracy and kappa coefficient equal to more than 95% and 0.9500, respectively). Compared with the highest accuracy at the end of March, the classification accuracy at the end of April was obviously reduced. This might be due to the separability of the two crops, which was high at the end of March, in which rapeseed had begun to flower, while the winter wheat was in the jointing stage. However, the separability was reduced after the florescence of rapeseed at the end of April. At the end of February 2016 (early winter wheat growth), winter wheat had the lowest  
Figure 5: Comparison of processing time of different combinations classification by RF and SVM algorithms.  
classification accuracy, the reason being that the wheat had a much lower height and coverage at an early stage [20].
# Review on Free-Space Optical Communications for Delay and Disruption Tolerant Networks
## 2 Free-Space Optical Communications
### High Throughput Adiveements  
An overview of recent FSO systems that can offer high throughput for satellite-to-ground links is presented in Reference [15]. The world record on transmission speed was set by DLR by reaching a data-rate of 13.16 Tbps over 10.45 km for an FSO link in 2017 [16]. It is also demonstrated that optical technologies are suitable even under challenging conditions. In the recent systems developed, adaptive optics are used to stabilize the uplink channel with pre-distortion techniques, to compensate the effects that the atmosphere has on the link.  
GEO satellite relays for optical communications were shown to provide a big return-channel data throughput, with rates in the Gbps range [17]. Implementation ideas for these systems were also presented, namely for the necessary ground infrastructure. The results were exemplified in a case study on the applicability of FSO satellite communications to the radio astronomy community.
# Research on Path Planning for Robots with Improved A* Algorithm under Bidirectional JPS Strategy
## 3 Improved A* Algorithm
### Path Smoothing
#### 3.3.2 Quadratic Smoothing  
Although the path after primary smoothing reduces the number of redundant nodes and inflection points, it still exhibits problems such as unsmooth turning angles, which do not satisfy the motion characteristics of the robot. Therefore, to enhance the smoothness of the path, this paper adopts the dynamic circular cutting method for secondary smoothing. The schematic diagram of the dynamic circular cut method is shown in Figure 12.  
For the turning corner shown in Figure 12 \(\angle\)ABC, the steps of the dynamic circular cut method are as follows:  
Compare the lengths of the sides of \(\angle\)ABC. Choose the endpoint \(A\) of the shorter side \(AB\) as the tangent point and draw a perpendicular line through \(A\) to intersect the angle bisector BO\({}_{0}\) of \(\angle\)ABC at point O\({}_{1}\). Then proceed to step 2;  
Make a circle with O\({}_{1}\) as the center and AO\({}_{1}\) as the radius. Judge whether the arc \(AQ\) crosses obstacles or not. If it does, perform step 3; otherwise, use the arc \(AQ\) instead of the straight lines \(AB\) and \(BQ\);  
Figure 11: Schematic diagram for removing redundant nodes: (**a**) original path; (**b**) removing collinear nodes; (**c**) removing redundant turning nodes.  
The tangent point \(A\) is moved upward along \(AB\) by a length \(\lambda\) (the value of \(\lambda\) is chosen according to the actual situation), denoted as \(A_{1}\). Use \(A_{1}\) as the tangent point to perform step 1;  
* Determine whether all the turning corners have been smoothed. If yes, the secondary smoothing is completed; otherwise, continue with step 1.
## 2 Challenging Open Issues
### Other Open Issues
#### 2.2.4 Path Loss  
In WBSNs, sensor nodes might be placed on the body, e.g., chest, back, wrist or inside the body, e.g., pacemaker for regulating heart beating. The wireless transmission between these nodes must propagate through the human body, and compared to free space medium, which has a path loss exponent of two, the human body is an extremely lossy environment. The path loss exponent in the human body ranges from four to seven [16], a value relatively much higher than the condition in free space. The signal power will be severely degraded; thus, this factor must also be considered in designing a routing protocol for WBSNs.