esa-sceva/satcom-chunk-collection huggingface dataset:
# Wheat Yield Estimation Study Using Hyperspectral Vegetation Indices
## 3 Results
### Multiple Methods to Build Models Based on Vegetation Index
#### 3.3.6 Computational Complexity and Noise Robustness of the Model  
When constructing the production estimate model, the multiple stepwise regression method has high computational complexity, needs to evaluate multiple variable combinations, and is relatively sensitive to noise in the data. The multiple linear regression method has low computational complexity, can directly fit the linear relationship, and has good robustness to slight noise. Principal component analysis reduces the dimensionality of high dimensional data with a low computational complexity and has a certain noise robustness. Although neural networks have a high computational complexity, their nonlinear fitting ability and flexibility of parameter adjustment give them a certain degree of noise robustness. Random forest has low computational complexity due to the integration of multiple decision trees, and has strong robustness to light noise. Computational complexity and noise robustness of different methods are summarized in Table 5.
## 1 Introduction
In order to solve it, the authors of [25] proposed a new SMO control strategy to reduce the estimated speed chattering of the motor, in which the switching function is replaced by a sigmoid function. The sigmoid function has also been used in SMO for UAV in [26]; however, it is conducted without experiment. The main contributions of this study are given as follows. 1. In order to alleviate the estimation chattering problem of traditional SMESO, a new observer named fuzzy adaptive saturation super-twisting extended state observer (FASTESO) is proposed, in which a saturation function is invited to replace the discontinued sign function, meanwhile a super-twisting algorithm is introduced to prevent excessively high observer gain and TD [19] and is incorporated for avoiding directly using acceleration information, which is full of noise. 2. To stay robustness under disturbances with unknown bounds, fuzzy logic rules are introduced as an adaptive algorithm to adaptively adjust the observer switching gains. Furthermore, it also contributes to the chattering attenuation under high switching gain with low estimation value and observer performance improvement under low switching gain with high estimation value. 3. The proposed method is verified with effectiveness on a quadrotor UAV manipulator prototype in several simulations and experiments. The rest of this article is organized as follows. Section 2 introduces some preliminaries of this work. Section 3 describes the kinematic and dynamic models of the quadrotor UAV manipulator. The construction of proposed FASTESO and attitude controller are given in Section 4. Additionally, several simulations are conducted in Section 5. Moreover, Section 6 shows the experiment. Finally, Section 7 presents the conclusion.
## 3 System Design
### Path State-Aware Multicast Tree Node Selection Mechanism
Step 2: Replies to the edge router with a detection response message, which includes the Max Load field and Average Load field, as shown in Figure 3b. The value of the Max Load field in the detection response message is \(max(L_{max},~{}R)\), and the value of the Average Load field in the path detection message is \((L_{sum}+R)/(C+1)\). Edge routers need to interact with NRS frequently to obtain the MTNs and need to frequently detect the path state of each MTNs. To reduce the pressure on the edge router, the edge router can cache the MTNs and the path state information of them locally for a while. Different from other multicast methods that use the shortest path between the source or core and each receiver to construct the multicast tree, we selected the MTN with the best path state for each receiver to join. In this way, we could make full use of low-load links and effectively avoid traffic aggregation. As shown in Figure 4, H1 joined the multicast service identified by MSEID1, and NRS maintained the mapping between MSEID1 and (NA1, NA2). When H2 wants to join the multicast service, H2 just sends a join message (arrow 1). After receiving the join message, the edge router R5 queries the NRS to obtain the MTNs' NAs (NA1, NA2) (arrows 2, 3). RS sends a path state detection message to NA1 and NA2, respectively (arrows 4-7), and the routers that the message passes through record their interface rates in the message. After receiving the path state detection message, the routers located in NA1 and NA2 return the path state information to R5 (arrows 8-11). RS selects the NA2 with the best path state to join (arrows 13, 15). The routers R5 and R3, which the join message passes through, register the mapping between MSEID1 and their NAs with the NRS (arrows 12, 14). Then the multicast flow is forwarded to H2 along the path R1 \(\rightarrow\) R2 \(\rightarrow\) R3 \(\rightarrow\) R5 \(\rightarrow\) H2 (arrows 16 \(-\) 18), rather than along the shortest path R1 \(\rightarrow\) R4 \(\rightarrow\) R5 \(\rightarrow\) H2. Figure 3: The format of messages. (**a**) The format of the path state detection message; (**b**) the format of the detection response message.
# Quantum Key Distribution Networks: Challenges and Future Research Issues in Security
## 2 Background to Quantum Key Distribution (QKD) Networks
### QKD Network Type
#### 2.3.2 Trusted Node Network  
In contrast to the active optical switch network, any quantum node only establishes a quantum channel with its neighboring nodes (shown in Figure 3b), and thus, it can only generate security materials with its neighbors. Thus, the two remote nodes cannot distribute the security key using the QKD protocol directly. Therefore, if the two remote nodes want to distribute security keys, they need help from other nodes using a hop-by-hop communication strategy. For example, in Figure 3b, when node A wants to distribute the session keys with node F, it needs the help of nodes B and C. However, any node on the routing path can know the session key that the source node wants to distribute to the destination node because of the hop-by-hop communication strategy; thus, the quantum node must be assumed to be trusted (i.e., they must protect the session keys without leaking any information to attackers). Although the assumption of a quantum node is not realistic in real Internet environments, a trusted node network is still the mainstream framework in existing practical field experiments because it is not limited by communication distance  
Figure 3: Active optical switch network and trusted node network, in which (**a**) presents the schematic diagram of active optical switch based QKD network and (**b**) presents the schematic diagram of a trusted QKD network.  
or node numbers and can be made up of different QKD devices implementing different QKD technologies.
# Precipitable Water Vapor Retrieval Based on DPC Onboard GaoFen-5 (02) Satellite
## 2 Materials and Methods
### Dataset
#### 2.1.2 MODIS PWV  
The MODIS sensors on board the Terra and Aqua satellites have five near-infrared bands that can be used for water vapor retrieval: Band 2 (865 nm), Band 5 (1240 nm), Band 17 (905 nm), Band 18 (936 nm), and Band 19 (940 nm). Band 2 and Band 5 are located in the atmospheric window region and are not affected by the absorption of atmospheric gases, while Bands 17-19 are located in the spectral region of strong water vapor absorption, and the absorption effect of gases other than water vapor on these three bands is negligible. National Aeronautics and Space Administration (NASA) released official MODIS PWV data based on the above five bands. The basic principle of the official MODIS PWV retrieval algorithm is as follows: firstly, the TOA reflectance in Bands 17-19 without considering water vapor absorption is calculated using the TOA reflectance in MODIS Band 2 and Band 5 by means of linear interpolation; then, the water vapor absorption transmittance in these three water vapor absorption bands is calculated according to the TOA reflectance in Bands 17-19 and the actual TOA reflectance in Bands 17-19 when water vapor absorption is not considered. Finally, water vapor retrieval can be realized according to the obtained water vapor absorption transmittance [13]. Since we used the same PWV retrieval strategy using near-infrared channels as MODIS, and the MODIS PWV data have been extensively validated with high accuracy [23; 24; 25; 26; 27], we performed an intercomparison between DPC-derived PWV and MODIS official PWV data (MYD05) to comprehensively evaluate the accuracy of our developed algorithm in this research. Due to the large number of MODIS PWV data and due to the accuracies of MOD05 data developed based on Terra/MODIS data and MYD05 data developed based on Aqua/MODIS data being close [28], MYD05 data were randomly selected as the representatives of MODIS PWV data to participate in the intercomparison. The MODIS official water vapor product (MOD05/MYD05) mentioned above can be accessed at the NASA data website ([[https://ladsweb.modaps.eosdis.nasa.gov](https://ladsweb.modaps.eosdis.nasa.gov)]([https://ladsweb.modaps.eosdis.nasa.gov](https://ladsweb.modaps.eosdis.nasa.gov)), accessed on 25 February 2022).
# A Systematic Review of Radio Frequency Threats in IoMT
## 3 Results and Discussion
### Cybersecurity Experimentation with AI-Enabled CS  
The paper [42] explores artificial intelligence (AI) cybersecurity systems. A platform is needed to test big data and fog computing, cyber situational awareness, innovative simulations, and cyber decision support systems (CDSS). For example, safety-critical systems include production and industrial control systems (ICS), and mission-critical includes communication, access management, interfaces, and business system (HRM, financial, procurement, product, innovation, sales, marketing, etc.). The corporate system cannot depend only on the external penetration testing strategies but develop an internal red team--to attack the system--and a blue team--to defend the system--providing a competitive advantage in attaining cyber maturity. To achieve and reduce the dependability on external penetration tester, the low-cost testbed can be performed to improve the effectiveness and usability of continuous security monitoring (CSM), facilitate attack and defense awareness among employees, and thus reduce KT cost between IT and operational departments. The testbed can also be scaled to accommodate upcoming threats from similar market segments and innovate new strategies--deception against advanced persistent threats (APTs).  
Researchers state that the inability to experiment with cybersecurity threats on the low-cost testbed is an excellent threat to the ICS. The research claims that open-source hardware and software can develop a testbed within 500 euros for ethical industrial control system hacking, education, competency development, and research. However, it lacks rationality in the choice of hardware and software concerning functional and non-functional attributes such as performance, security, scalability, maintainability, interoperability, usability, and availability. Additionally, this approach will improve the real-world simulation of attack and defense strategies discussed in the previous paper. This approach motivates us to identify a cost-effective way to conduct field experiments as we implement our framework. Using interoperable data-driven systems, the research examines the industry 4.0 problem.  
Additionally, they investigated the four levels of cybersecurity in ICS and how intruder threats, including insider threats, can experiment against them. Based on the analysis, insider threats and associated tools impact 0 and 1 compared to a remote intruder. The author demonstrated that a low-cost testbed could address the growing demand for attack vectors and surfaces in the corporate ecosystem. Expert assessments and other studies are recommended for fog computing and AI-enabled systems [43].  
Using low-cost SDR hardware and universal radio hacker (URH), we have developed a framework and validated attack and defense scenarios in the hospital ecosystem [42].
To the best of our knowledge, there has been very limited research in Europe to examine the concentrations and sources of PAHs and trace metals in indoor dust [18; 19; 20] and even scarce focusing on residences with infants and young children [7]. Additionally, the present work is the first of its kind to be conducted in Greece. The objectives of this study were: (a) to identify the concentrations and profiles of PAHs and trace metals in indoor dust collected from Greek households, (b) to examine the relationship between the household characteristics and occupant's activities with PAH and trace metals concentrations in indoor dust, (c) to determine the sources of PAHs and trace metals in indoor dust of Greece, (d) to conduct a health risk assessment and to evaluate the cancer risks of exposure to PAHs and metals in residential environments.
## 3 Formulation of Optimization Problem
### Optimization Procedure  
In this sub-section, the procedure of the proposed optimization method to determine the optimal schedule of controllable loads, is explained. In this paper, it is assumed that power consumption except for controllable loads and heat load which the residential people use can be forecasted. Thus, the variable number to be solved, are charge/discharge power of the fixed battery, charge/discharge of EV and operation starting time of the HP. The optimization step with using TS is as follows.  
1. The initial values for charge/discharge power of the battery and EV are set in addition to the operation starting time of the HP.
2. The neighborhood solutions which is slightly moved from initial solution or the chosen solution in a previous iteration, are produced and evaluated.
3. The neighborhood solutions are evaluated in the Equation (4), the best neighborhood solution which is not recorded is chosen and recorded in the tabu list. If the best solution already lies in the tabu list, the next best solution in the neighborhood ones is selected. Even if the selected solution is worse than a solution selected in the previous iteration, its registration to the tabu list is executed. Old recorded solutions are overwritten with the new chosen one in turns and new solutions are recorded.
4. If the chosen solution is better than the solution which is previously reserved as the optimal solution, the chosen solution is reserved as the optimal one.
5. If number of the global iteration achieves criteria one which was set in advance, the search process is finished. Otherwise, the algorithm proceeds to Step 6.
6. For the best solution obtained in Step 3, the process goes to Step 2 where the neighborhood solutions are derived from the best one again.  
where, the pseudo-code of the optimization algorithm using TS is as follows Algorithm 1[22].  
```
\(x=x_{0}\); % Set of initial solution for\(j=1\) to \(N_{S}\)do  Generate a set \(A\) which is a neighborhood solutions from \(x\) or previous one \(x_{nei_{y}}\);  Find best neighborhood solution \(x\) of \(A\); % check of constraints conditions, the solutions is not recorded in the tabu list; \(x=x^{\prime}\);  Update tabu list; if\(f(x)<f(x_{BST})\)then \(x_{BEST}=x\) \(x_{nei_{y+1}}=x\) endif endfor \(x_{BEST}\) is the best-found solution.
```  
**Algorithm 1** Optimization algorithm using TS
# Review on Corrosion Inhibitors for Oil and Gas Corrosion Issues
## 2 Corrosion
### Sources of Corrosion
It should be considered that the rusting rates in pits can be a few times larger and that the carbon dioxide rusting rate is inconsistent at low temperatures. Mixtures of oxygen with carbon dioxide or hydrogen sulfide prompt immediate-corrosion environments with smaller oxygen concentrations such as 0.1 ppm [33]. Bacteria  
Microorganism activity is the root of bacterial corrosion, which can be damaging, especially in enhanced recovery processes. Sulphate-reducing and iron bacteria are known to be the most common bacteria that promote corrosion. Microbiologically-influenced corrosion (MIC) was thoroughly examined from the industrial practice perspective, in order to attain profitable solutions in observing large water injection systems [34]. Water Cut  
The presence of oil is considered advantageous as it employs a kind of inhibition effect by forming a film on a steel surface to prevent water wetting. On the other hand, gas and condensates do not employ any useful effect due to its non-inhibition characteristic. As for the vertical tubing, an oil film produced on the surface of the steel is steady up to about 20%-40% water cuts. Using the [PERSON] Waard and Milliams method, the corrosion rate for higher water quantities can be predicted, as the steel can be considered water-wet. Besides, the volume of water is not a significant factor for the horizontal pipes. Figure 2: Comparison of rusting rates of three gases [27]. Commonly, water is heavier compared to oil, gas and condensed products, thus it may segregate on the lowest surfaces at the 6 o'clock position for stratified flow. As for this case, the corrosion is anticipated to occur only on the water-wet surfaces. For the stratified flow, corrosion is probable to happen in the highest point of the line because of the condensation of water droplets from the wet gas. In this case, the inhibition effect is said to be poor and the corrosion rate in the highest point of the line can be expected to be 10% of the projected rate in a completely immersed condition, regardless of the carbon dioxide content. Strong Acids  
In the oil and gas industries, the acid stimulation method is widely applied to enhance production by improving the formation permeability. The commonly used fluids for this method are hydrofluoric acid and hydrochloric or acetic acids for sandstone and carbonates, respectively, which can cause corrosion of production tubing, downhole tools and casing in the absence of corrosion inhibitors [27]. Brines  
Usually, brines are utilized during the completion stage of oil and gas wells to aid the final operations before the fluid production begins. This is because brines consist of zinc chlorides or calcium bromides and have the capability to regulate the well without damaging the formation. However, they can be harmful to the downhole equipment of the well, since there is the presence of dissolved oxygen.
# Cooperative Content Caching Framework Using Cuckoo Search Optimization in Vehicular Edge Networks
## 6 Cooperative Content Caching Framework
### Caching Techniques  
We propose cooperative content caching (COOP) with K-means clustering to cache data using the cuckoo search algorithm in VENs to determine the optimal path for content delivery. We devised a caching approach that takes user preferences into account. User opinion is reflected in content ratings. The top suggested movies are cached at RSUs and MBS using COOP. When a user requests a video, the server checks its cache and delivers it if it is there. This is a cache hit; the server boosts its popularity after delivering the content. If the requested content isn't in the cache, this is a cache miss. The total number of files in RSU is calculated using Equation (7).  
\[F_{R}=M+\sum\
olimits_{R=1}^{n}\ N_{R} \tag{7}\]  
Caching capacities of MBS, RSU, and vehicles are S\({}_{MBS}\), S\({}_{RSU}\), and S\({}_{V}\) in GBs. Caching constraints are explained below whose purpose is to cache the files less than the total caching capacity, i.e., S\({}_{V}<\) S\({}_{RSU}<\) S\({}_{MBS}\).  
Total number of files cached by RSU is \(\sum_{f=1}^{F}s_{R}{}^{F}\leq\) S\({}_{RSU}\)  
Total number of files cached by MBS is \(\sum_{f=1}^{F}s_{B}{}^{F}\leq\) S\({}_{MBS}\)  
Total number of files cached by vehicle is \(\sum_{f=1}^{F}s_{V}{}^{F}\leq\) S\({}_{V}\)  
Content delivery follows caching. Find the ideal path to deliver content to a node. The existing approach employs ACO, explained later.
# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 4 Challenges
### Over-the-Air (OTA) Updates
However, little or minimal attention has been given to the aspect of reducing the time of the OTA software updates.
## 5 Experimental Investigations
### Transverse Load-Bearing Behavior of Cross-Beams for Construction State  
In order to verify the operation principle of the introduced reinforcement layout of the cross-beams from the precast deck slab elements in the construction phase, experimental investigations were conducted. A total of four tests were performed on cantilevers. The parameters investigated were (a) the spacing \(s\) of the additional loops, which project from the upper surface of the cross-beam, and (b) their anchorage length \(l_{\mathrm{b}}\). The additional loops form a substitution for the concrete cover, which is, among other things, responsible for the transfer of bond stresses.  
The effects of reduced or no concrete cover on the bond strength have already been investigated in a number of pull-out and bending tests with and without a confining reinforcement [24; 25]. Due to the reduction in the concrete cover, the longitudinal reinforcement can no longer be brought to a state of yielding, as premature splitting failure occurs before. Pull-out tests on eccentric half-joint cantilever specimens were conducted by [PERSON] and [PERSON] [26] to investigate how bond conditions are affected by reductions in concrete cover. Several tests have been carried out in which the concrete cover was gradually reduced until the rebar was only half-embedded in the concrete. Transverse reinforcement in the form of links was present in all specimens. All tests with half-embedded rebars resulted in a low pull-out resistance compared to the tests with appropriate concrete cover. No additional loops above the protruding reinforcement were provided.
# Effect of Admixtures on Selected Properties of Fly Ash-Based Geopolymer Composites
## 4 Results and Discussion
### Water Absorption  
Average water absorption results for all the series are shown in Figure 5. The best results were obtained in the series with a liquifying admixture based on stabilized polycarboxylates and an activator to fly ash ratio of 0.5. In comparison with control samples with the same activator to fly ash ratio, an approximate 25% improvement in properties was observed when an admixture based on stabilized polycarboxylates was used.  
Regardless of the activator content, the lowest water absorptions were obtained in mortars with the admixture based on stabilized polycarboxylates (Figure 6). The increase in activator content caused an increase in the absorption of water, regardless of the type of admixture used.  
Figure 5: Water absorption results for all the series.  
Figure 6: Water absorption results depending on the activator to fly ash ratio (ANOVA certainty in whiskers).  
In mortars with the admixture based on stabilized polycarboxylates, a total increase of 40% was observed. In samples with a plasticizing admixture and an admixture based on modified polynaphthalenes, the increases were 21% and 37%, respectively.