esa-sceva/satcom-chunk-collection huggingface dataset:
# Transport-Layer Limitations for NFV Orchestration in Resource-Constrained Aerial Networks
## 2 Background and Related Work
In [18], the authors explore the use of SUAVs as network nodes, with the capacity to extend the programmable infrastructure of the 5G network; these SUAVs are able to onboard all the required computing, storage and network resources to provide a fully working NFVI platform where VNFs can be deployed, configured and run, saving on infrastructure deployment and maintenance costs in comparison with traditional NFVIs. This concept is further developed in [5; 19], where the authors introduce a new NFV system design able to support the agile configuration and deployment of moderately complex NSes over a cloud platform composed of SUAVs with constrained equipment and resources. On the other hand, The NFV-SUAV combination has delivered of its benefits can be seen in [20], where authors propose a full video-surveillance system for big poorly internet-covered areas using UAVs, whose mobility can be used to distribute the aircraft along an specific geographical region to obtain video footage, using NFV as the platform to transmit the video signal through a network of several VNFs running inside the aircraft. This behavior can be considered rather complex to perform through pure virtualization, due to the execution times needed for performing all aircraft actions, which might not be fast enough to provide the service, especially since the amount of resources that can be onboarded are constrained by their space and weight to allow the aircraft to stay in the air as much as possible. Instead, authors propose using paravirtualization, where Virtual Machines (VMs) share the hardware directly with their host, allowing its Operative System (OS) to be a platform for directly (and exclusively) operating with the VNFM, saving valuable execution time and allowing a better management of the resources on the aircraft. Other outstanding work line in this area is related with the migration of VNFs between the NFV units of a network composed of several SUAVs in order to perform a seamless transition of VNFs between UAVs to minimize service cuts and/or reduce the amount of time a service remains offline. This behavior can only be performed if all the associated network services, routing and operational control migrate quickly. An example of this can be seen in [21], where authors propose an NFV-based solution that takes into account the high-mobility requirements of these networks. The work in [22] presents an architecture of function softwarization in an irrigation system based on a network of sensors and UAVs.
## 3 Application Areas of IoT and UAV in Smart Farming
### Planting Seeds and Seedlings  
Undoubtedly plantation of seeds and seedlings can be made more efficient using UAVs. For instance, authors in [50] shows an effective use of UAVs on a large area of uneven rice paddies. They used a UAV based system for effective and timely distribution of seeds, fertilizers and plant nutrients. Plantation of seed and seedlings using UAVs is still in development stage, the researchers are developing UAVs equipped with image recognition technology and an optimized planting technique [6].
# Exploiting Data Similarity to Improve SSD Read Performance
## 5 Experiment
### Results and Analysis
#### 5.2.1 Read and Write Latency Comparison  
To evaluate the performance, we employ different page allocation schemes on eight real trace files under the same SSD environment configuration. The corresponding average read and write latency results are normalized and presented in Figure 10.  
Figure 10a illustrates the write latency under different allocation schemes. In comparison to the two static allocation schemes, DS-FTL exhibits a significant improvement by reducing the average write latency by up to 54.0% and an average reduction of 24.7%. When compared to dynamic allocation, DS-FTL achieves a 36.7% decrease in average write latency, with the largest improvement observed for the webusers trace. In addition, we compare DS-FTL with the HIPA [21], DS-FTL demonstrates a more substantial reduction in write latency of 30.3% for write-intensive workloads (e.g., home3 and webusers), with an overall average write latency reduction of 19.0%.  
Figure 10b illustrates the read latency under different allocation schemes. Compared to the two static allocation schemes, DS-FTL can reduce the average read latency time by up to 56.3% and 35.3% on average. Compared with dynamic allocation, the average read latency is reduced by 34.2%. HIPA exhibits better performance in reducing read latency, and DS-FTL shows a similar performance with HIPA. HIPA is even better on online workloads with more read requests, but overall, DS-FTL reduces the read latency by up to 23.0% and 9.8% on average compared to HIPA.
# Classification of Hyperspectral Images Based on Supervised Sparse Embedded Preserving Projection
## 4 Experimental Results and Analysis
### Zhangjiangkou Mangrove Nature Reserve HJIA-HSI Dataset
Both Figure 3 and Table 4 show that the SSEPP algorithm greatly reduced the misidentification phenomenon of mangroves, that is, the fewest red noise points were observed, and its classification result image was closest to the Zhangjiang estuary mangroves HJ1A-HSI ground truth image. Table 5 shows that the proposed SSEPP method yielded the best overall accuracy and kappa coefficient, followed by the SDE algorithm. Relative to the traditional sparse preserving projection algorithm, SSEPP classification accuracy and the kappa coefficient were increased by 3% and 0.04, respectively, which means that the sample label information was introduced and the spacing of same class samples considered could both result in better classification. Compared with the SDE and PCA algorithms, the proposed algorithm improved by 2% and 3%, respectively, and the Kappa coefficient was increased by 0.02 and 0.03, respectively.
## 5 Maintenance Decision
### Predictive Maintenance  
#### 5.3.1 CBM  
CBM takes advantage of modern condition perception methods to track MSAE health state in real-time, realize fault diagnosis and failure prognostics according to DIaK, and make maintenance decisions in combination with the health state, diagnosis, and prognostics results. It is an important maintenance strategy under PHM. According to this strategy, the maintenance work will be completed when the MSAE is needed. Figure 14 compares the health stages in which different maintenance methods are performed. The goal of CBM is to reduce the cost of spare parts, system downtime, and maintenance time, which requires engineers to complete the work at the right time. Many researchers have shown that the CBM strategy is more effective than the PM strategy. It is reported in the literature that the use of CBM may extend maintenance overhaul cycles by up to 50% and save between 25% and 45% of maintenance costs [212].  
Figure 14: Health stage of different maintenance options.  
Although CBM can significantly save maintenance costs and reduce failure risk, the current survey shows that only 10% of the marine industry uses CBM as the preferred maintenance strategy [302]. One of the main reasons limiting the application of CBM onboard ships is that the ship is a complex system composed of systems, subsystems, equipment, and components, whether it is the physical process and function description of the system, the analysis of DIaK, and even the formulation of maintenance decision-making need to be completed by professionals with high technical levels.
# Cyberattack on Flight Safety: Detection and Mitigation Using LoRa
## 3 Flight Safety Framework
### Wireless Sensor Network Protocol  
The wireless sensor network protocol between a node and a GS was as follows. Each node could send and receive messages using its integrated radio transceiver from or to any other node that exists in the network with its unique ID. Furthermore, each node contained  
Figure 4: The node containing a microprocessor, a LoRa 2.4 GHz transceiver, and an optional GPS.  
a routing table of its neighboring nodes. Occasionally, a node would perform a health check with its neighbors and update its routing table. A message could be transmitted to a node directly if the receiver node was a neighbor of the origin node or through other nodes, which would act as relays and retransmit the message to their neighbors while ensuring that it was not sent back to the origin node (Figure 5). Each node contained a distance table in addition to the routing table. The distance table was constructed using the ranging feature of the radio device. Occasionally, a node would send a message to its neighbors to perform a ranging request. The distance table was published via a message to its neighbors to construct an entire network distance table. Using the distance table of its neighbors, a node could calculate its relative position using the following algorithm: If a node knew its distance from another node, then its position was known within a sphere. If there were two nodes to provide the distance, then the position was known within a ring of the two spheres. Together with a third node's distance, its position was known on the three-sphere intersection. This intersection provided two possible points, but only one was on the Earth. Further, using a sensor to measure the altitude of the node, the position could be calculated precisely. Some nodes had their global position received by an integrated GPS sensor. Those nodes broadcast their GPS position as part of their beacon. Other nodes that did not have the integrated GPS sensor calculated their exact location using their distance table and their neighbors' GPS location.
# Dynamical Manipulation of Surface Plasmon Polaritons
## 5 Nondiffracting SPP Beams
The phase difference of SPP generated by the upper and lower slits is \(\Delta\varphi_{sp}=2\alpha_{\pm}\alpha_{-kp}\lambda_{sp}/4\). With the incident of LCP light, the SPP generated by the upper and lower slits are in phase (\(\Delta\varphi_{sp}=0\)) and interfere constructively along the \(x\)-axis. For RCP incident light, the SPP generated by the upper and lower slits are out of phase (\(\Delta\varphi_{sp}=\pi\)) and interfere destructively. Therefore, SPP beams with profiles of the zeroth-order Bessel function and the first-order Bessel function can be observed for LCP and RCP light, respectively. Figure 6: **(a)** Dynamic modulation of the trajectory of SPP Airy beam with SLM [42]; **(b)** Controlling the position of the SPP Airy beam by varying the incident polarization [74]; **(c)** Dynamic SPP Bessel beam through phase control [41]; **(d)** Polarization-based manipulation of SPP Bessel beams [75]. Reproduced with permissions from: [42], OSA, 2011, [74], OSA, 2017, [41], OSA, 2014, [75], OSA, 2018.
###### Abstract  
In this work, homogeneous, thin-film proton exchange membranes (PEMs) with superior proton conductivities and high methanol rejection were fabricated via a facile synthesis procedure. Sulfonated polyether ether ketone (sPEEK) was crosslinked via a Friedel-Crafts reaction by \(\alpha\),\(\alpha^{\prime}\)-dichloro-p-xylene, a non-hazardous and hydrophobic compound. PEMs with varying crosslinking and sulfonation degrees were fabricated to overcome the traditional trade-off between methanol rejection and proton conductivity. The sulfonation of PEEK at 60 \({}^{\circ}\)C for 24 h resulted in a sulfonation degree of 56%. Those highly sulfonated backbones, in combination with a low membrane thickness (ca. 20 \(\mu\)m), resulted in proton conductivities superior to Nafion 117. Furthermore, X-ray photoelectron spectroscopy proved it was possible to control the crosslinking degree via the crosslinking time and temperature. The PEMs with the highest crosslinking degree showed better methanol rejection compared to the commercial benchmark. The introduction of the crosslinker created hydrophobic membrane sections, which reduced the water and methanol uptake. Subsequently, the membrane became denser due to the crosslinking, hindering the solute permeation. Those two effects led to lower methanol crossovers. This study proved the successful fabrication of PEMs overcoming the trade-off between proton conductivity and methanol rejection, following a facile procedure using low-cost and non-hazardous materials.  
electrochemistry; membrane synthesis; cation exchange membrane; proton conductivity; polyether ether ketone; methanol retention Article
## 2 Background
### Attack Types  
Spyware is utilized to sabotage ICSs by infiltrating them, manipulating transactions, or accessing sensitive data. Stuxnet is a famous example of spyware designed against Iran's nuclear facilities in 2010, which disrupted the facility's operation by changing the speed of centrifuges. In addition, Night Dragon (2010) attackers utilized sophisticated malware to target global energy, oil, and petrochemical companies. In the Duqu/Flame/Gauss (2011) incident, highly developed and sophisticated malware was utilized to target particular organizations, such as ICS producers. In the Shamoon (2012) incident, the malware was utilized to target large energy companies in the Middle East, including RasGas and Saudi Aramco. Havex (2013) is an example of an ICS-focused malware campaign [11].  
A distributed denial of service (DDoS) attack represents a malicious attempt to sabotage a network due to overwhelming its capability to process legitimate requests and traffic. Consecutively, the activity mentioned above denies the victim of service, which leads to expensive setbacks and downtime. A DDoS attack represents a network-based attack, which utilizes network-based internet services, e.g., domain name service (DNS), routers, and network time protocol (NTP). It aims to disrupt network devices connecting the organization to the internet. Load balancers, routers (traditional WAN and ISP edge routers), and firewalls can be listed among these devices.  
A significant number of security vulnerabilities in ICSs are caused by human errors such as misconfigurations, outdated software, and user errors. Moreover, malicious insiders can also damage ICSs.  
Social engineering attacks target human vulnerabilities, defrauding users and causing information leaks. Such attacks are realized especially with phishing and spear phishing attacks via e-mail.  
A zero-day attack represents a software vulnerability that attackers use before the vendor realizes it. In this case, there is no patch; therefore, attackers can use the vulnerability easily since they know that defense is absent, which transforms zero-day vulnerabilities into a significant security threat. Such attacks can be used to damage ICSs.  
Advanced persistent threats (APTs), which are long-term, targeted, and sophisticated attacks, aim to infiltrate ICSs, gather intelligence from inside systems, and manipulate the infrastructure. MITM attacks are performed to modify, hack, or spoof data in communication channels. These attacks can be utilized to manipulate command and control messages to ICSs.
## 4 Results
### Comparison with Other Algorithms under the Same Agent Number  
Figure 9 presents the comparison of the efficiency of four types of algorithms for human-robot function allocation as the number of agents varies. When comparing the iteration number between HRL and the alternative algorithms for different numbers of agents, we consistently find that the iteration number for HRL is always significantly less than the others. Furthermore, the iteration number of HRL is able to remain relatively stable to a higher degree as the number of agents increases, compared to alternative algorithms.  
When the number of agents of each type is 3, 4, 5, 6, and 7, the number of iterations of HRL is 930, 1040, 1250, 1650, and 1960. Meanwhile, the number of iterations for RL is 6000, 10, 16, 22, and 31, respectively. The number of iterations for DRL is 12,000, 20,000, 28, 38, and 52,000, respectively. The number of iterations for HDRL is 5000, 9000, 12, 16, and 25, respectively.  
Figure 8: The result of the human–robot function allocation based on the HDRL algorithm.  
Figure 9: Comparison of the allocation efficiency of each algorithm for different numbers of agents.  
The proposed HRL is at least 90.49% more computationally efficient than regular RL for different numbers of agents by at least 94.89%, compared to DRL; this is at least 88.26% better than the HDRL algorithm. It can be shown that the proposed approach is in general highly robust compared to other traditional algorithms.  
In summary, a series of simulation experiments and calculations have been performed in randomly varying and complex environments with agents planning while marching, and with varying numbers of agents to verify that the proposed method is effective and robust. Combining the results of experiments 1 and 2, it appears that the proposed method not only efficiently increases the computational efficiency compared to regular RL, DRL and HDRL algorithms, but also remains primarily highly robust while the number of agents changes.
###### Abstract  
At present, the problem of rail routes reconstruction in a global reference system is increasingly important. This issue is called Absolute Track Geometry, and its essence is the determination of the axis of railway tracks in the form of Cartesian coordinates of a global or local coordinate system. To obtain such a representation of the track centerline, the measurement methods are developed in many countries mostly by the using global navigation satellite system (GNSS) techniques. The accuracy of this type of measurement in favorable conditions reaches one centimeter. However, some specific conditions cause the additional supporting measurements with a use of such instruments as tachymetry, odometers, or accelerometers to be needed. One of the common issues of track axis reconstruction is transforming the measured GNSS antenna coordinates to the target position, i.e., to the place between rails on the level of rail heads. The authors in their previous works described the developed methodology, while this article presents a method of determining the correction of horizontal coordinates for measurements in arc sections of the railway track. The presence of a cant causes the antenna's center to move away from the track axis, and for this reason, the results must be corrected. This article presents a method of calculation of mentioned corrections for positions obtained from mobile satellite surveying with additional inertial measurement. The algorithm presented in the article and its implementation have been illustrated on an example of a complex geometric layout, where cant transitions exist without transition curves in horizontal plane. Such a layout is not preferable due to the additional accelerations and their changes. However, it allows the verification of the presented methods.  
Keywords:railway track; track geometric layout; track centerline; railway track inventory; GNSS surveying; inertial measurement; cant measurement; Inertial Measurement Unit (IMU) +
Footnote †: journal: Accepted: 12 October 2019; Published: 15 October 2019
# Comparison of Methods for Reconstructing MODIS Land Surface Temperature under Cloudy Conditions
## 1 Introduction
The linear equation can be used to fill in the missing value based on the temporal distance between the period in question and the LST of the most recent period with data. Based on this idea, a more sophisticated temporal approach (Harmonic Analysis of Time Series) was used. [PERSON] et al. [21] and [PERSON] et al. [22] used the Savitzky-Golay (S-G) method and the Harmonic Analysis of Time Series (HANTS) to interpolate daily invalid data, respectively. Among the spatiotemporal methods, [PERSON] et al., 2014 [10] proposed a novel interpolation approach. An adaptive window is established with invalid pixels as the center to search for effective and similar pixels geographically. At the same time, combined with the effective images on adjacent days, the search process of effective pixels is completed together. If the maximum window is reached without a pixel threshold being met, the search process continues using the image of another clear-sky day until the threshold is met. As a result, the missing surface temperature value can be reconstructed using data from another period, and a linear connection established from similar pixels. This method has been widely applied in MODIS LST research in different geographical regions [23; 24; 25]. [PERSON] et al., 2014 [26] associated LST with normalized difference vegetation index (NDVI). The second-order polynomial regression relationship was fitted between LST and NDVI to reconstruct the invalid values of LST. Currently, there is no unified and fixed method for the reconstruction of MODIS LST, and it is still necessary to compare the advantages and disadvantages of other methods. The purpose of this study is to propose a novel reconstruction method for MODIS LST by contrasting the commonly used methods (linear interpolation, smoothing filter, fitting,and fusion) and making full use of the spatiotemporal advantage. The Heihe River Basin (HRB), located in the northwestern arid and semi-arid regions of China, was selected as the study area. We reconstructed the MODIS LST products from 2016 to 2019 and validated the reconstructed results using in situ observations from an automatic weather station (AWS) [27; 28]. Section 2 introduces the research area, remote sensing data, and station measurements. Then, the performances of LST reconstruction using the temporal, spatial, and spatiotemporal methods are compared and analyzed. Finally, a new method based on classification and an adaptive window is proposed. In Section 3, the performance of different reconstruction methods is systematically evaluated using daily LST measurements from the AWS station. Then, the variation law of soil moisture with LST on different underlying surfaces is analyzed. Section 4 discusses the advantages and limitations of different methods. In Section 5, we provide a conclusion and analyze the performance of each method in MODIS LST reconstruction in the Heihe River Basin.