esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Side-Channel Timing Attack on Streaming Applications over NDN
### Content Retrieval Time (CRT)  
In this paper, content retrieval time (CRT) is presented to specify the RTT only for content retrieval. The CRT definition was used for cached and uncached contents between the edge router and the consumer (adversary included).  
CRT calculation was adapted from the TCP/IP RTT estimation [34]. Figure 7 illustrates the CRT calculation from the edge router to the adversary node. In this example, the adversary sends \"_Interest 1_\" and retrieves \"_Data 1_\", and then repeats again the same \"_Interest 1_\". Then, the adversary analyzes the obtained \(CRT_{1}\) and \(CRT_{2}\) values to conclude whether \"_Data 1_\" was cached or uncached from the edge router. The targeted \"_Data 1_\" is considered cached by the NDN edge router, if the adversary obtains \(CRT_{1}=CRT_{2}\), within a very small error tolerance (note that, it is possible to have this for uncached contents from the producer with short sequential requests).  
When an interest packet is forwarded to the upstream node, the NDN router is starting a timer, which will be used to measure the CRT. When the data packet corresponding to the \(n\) interest arrives at the router, this calculates the new CRT by the equation:  
\[<CRT>_{n}=\gamma*<CRT>_{n-1}+(1-\gamma)*CRT_{n} \tag{1}\]  
where \(n\) is the number of received content/data packets and \(0<\gamma<1\). When \(\gamma\) is equal to \(1-\frac{1}{n}\), then the real CRT is achieved. When the \(\gamma\) is close to 1, then the weighted average CRT becomes not sensible to delay changes for a short time interval. When \(\gamma\) is close to 0, then the weighted average CRT is very sensitive to new delay changes. These CRT calculations are presented for the same interest name sequence for the adversaries [35; 36].  
Figure 7: CRT measurements using one repetition of the same packet (Adapted from [35]).
# Optimization of Intelligent-Reflecting-Surface-Enabled Covert Communication in Multi-Sensor Systems
## 3 System Model
### Transmission Scheme  
By employing random coding generation of the 2-BPSK codebook, [PERSON] encodes a message \(W\) into a codeword \(\mathbf{c}_{1}^{n}=\left[c_{1,1},\dots,c_{1,n}\right]\in\mathbb{C}^{n}\) or \(\mathbf{c}_{2}^{n}=\left[c_{2,1},\dots,c_{2,n}\right]\in\mathbb{C}^{n}\), where \(c_{1,i}\in\{(-\beta,\tilde{\theta}_{1}),(\beta,\tilde{\theta}_{1})\}\) and \(c_{2,i}\in\{(-\beta,\tilde{\theta}_{2}),(\beta,\tilde{\theta}_{2})\}\) with \(i\in[1,n]\). For the \(i\)-th symbol, its amplitude is independently selected from \(\pm\beta\) and its phase angle is independently selected from \(\{\tilde{\theta}_{1},\tilde{\theta}_{2}\}\) equiprobably [8; 42]. The codeword \(\mathbf{c}^{n}\) is generated independently and identically distributed according to the following probability distribution:  
\[\mathbf{P}(\mathbf{c}^{n})=\frac{1}{2}\prod_{i=1}^{n}P_{\mathbf{c}_{1}}(c_{1,i} )+\frac{1}{2}\prod_{i=1}^{n}P_{\mathbf{c}_{2}}(c_{2,i}). \tag{7}\]Then, the mutual information can be expressed as  
\[\mathbb{I}(\mathbf{Y}_{b}^{n};\mathbf{\varsigma}^{n})=\mathbb{I}(Y_{b,1},\ldots,Y_{b, n};c_{1},\ldots,c_{n}). \tag{8}\]  
where \(\mathbf{\varsigma}^{n}\) denotes the discrete input and \(\mathbf{Y}_{b}^{n}\) denotes the channel output. Combined with the construction o the 2-BPSK codebook, the mutual information in (8) can be expressed as  
\[\mathbb{I}(\mathbf{Y}_{b}^{n};\mathbf{\varsigma}^{n})=\frac{1}{2}\mathbb{I}(Y_{b, 1,1},\ldots,Y_{b,1,n};c_{1,1},\ldots,c_{1,n})+\frac{1}{2}\mathbb{I}(Y_{b,2,1}, \ldots,Y_{b,2,n};c_{2,1},\ldots,c_{2n}). \tag{9}\]
## 2 Related Works
They also provide initial observations regarding drops in link quality and network performance due to rain events and the external environment. The direct sunlight received at WSN nodes is highly variable and dependent on natural obstacles [4] in addition to weather conditions (_i.e._, cloudiness) and seasons (_i.e._, total available sunshine hours). For the ASWP testbed, there are limited available sunshine hours (45% [21,22]), which are further obstructed by natural obstacles (_i.e._, tree canopy) from reaching the WSN nodes (e.g., see Figure 1). [PERSON] _et al._[17] deployed 33 WSN motes to monitor a redwood tree during 44 days. The deployment used battery-powered Mica2 Dot motes and the analysis shows a 49% data yield, considering that some  
Figure 1: Examples of two WSN node configurations deployed at the ASWP testbed. Both examples show how natural obstacles obstruct the direct sunlight received at the wireless sensor network (WSN) nodes. motes start dying after 10 days of operation. In [19], authors present a four-month habitat monitoring deployment consisting of 150 battery-powered motes. Motes were divided into a single-hop network and a multi-hop network, where motes in the multi-hop network achieved average lifetimes of 29 or 60 days, depending on their configuration. These works provide initial observations of the challenges faced by WSNs in outdoor deployments; however, they are based on particular experiments carried during field trips or expeditions, and therefore, they do not consider the challenges of continuous WSN operations and maintenance costs incurred during long-term outdoor WSN deployments. Not all outdoor WSN testbeds undergo the same kind of environmental conditions as those found in heavy forested areas. GreenOrbs [6] is one of the few battery-powered deployments that present similar environmental conditions to the ASWP testbed. In their work, 330 TelosB motes were deployed in a forest for collecting sensor data (_i.e._, temperature, humidity, illumination, and carbon dioxide). However, their reported deployment analysis time period is still quite short (_i.e._, from a duration in an order of days). Similarly, WSN deployments have been reported for demonstration and validation purposes, also limiting their deployment durations [23; 24; 25; 26; 27]. Single-hop WSN deployments have been reported, such as Life Under Your Feet (LUYF) [28], CrossVit [29] and others [30; 31]; however, they do not have any routing considerations in their analysis.
# Smart Inverters for Microgrid Applications: A Review
## 2 Smart Inverters
### Autonomy
#### 2.4.2 Mode Flexibility  
Another autonomous feature for an inverter is its ability to change its operational mode without external intervention in a smooth and seamless way. Depending on the control structure, an inverter can operate as grid forming, grid feeding and grid supporting [10]. In grid-connected mode, since the parameters are set by the grid the inverters perform as either grid feeding or grid supporting. By contrast, in islanded mode, there must be at least one grid forming inverter setting the voltage and frequency references of the grid. Figure 6 is a representation of these different configurations. As it can be observed in Figure 6a, the grid forming inverter functions as an ideal voltage source with fixed voltage and frequency. The additional loop (in green) is a descriptive illustration of voltage base grid supporting inverter or VSI. The control structure of these inverters is designed to work out the active and reactive power flow of each inverter and by using different control schemes provide voltage and frequency references. Figure 6b presents the same concept for grid feeding inverters and CSIs, which inject fixed or variable active and reactive power according to their inner loops and MPPT algorithms if they are of renewable energy nature [100].  
The concern here is the transition state when inverters roles are switched between these different modes. This switching is required due to the transition of the state of the microgrid from grid connected to islanded or the other way around. One side effect of this phenomenon is frequency unbalances and voltage and current disturbances so the inverters are required to be equipped with suitable control schemes the be able to compensate for these transient effects and provide a smooth transient state [94; 101; 102; 103; 104].  
In [103] a method has been proposed consisting of a phase-locked-loop (PLL) in order to retrieve the inverters output voltage angle and use it as a reference for droop control. In addition, a virtual inductor is used to limit the current inrush. Therefore, a smooth transition mode can be achieved. There are other approaches using a similar idea, based on PLL controllers. For instance, in [105] a method with the capability of ensuring a smooth transition in booth direction, grid connected to islanded and islanded to grid connected, has been proposed. Another method gathers voltage samples from grid and point of common coupling (PCC) at islanded mode, the values can be fed to a synchronization controller and after that been introduced to the droop control scheme, as reference values, which is regulating voltage and frequency at islanded mode. In this manner, a seamless mode transition is achieved after synchronization [106].  
Figure 6: Representation of different modes of inverters in microgrids. (**a**), grid forming/grid supporting VSI, (**b**), grid feeding/grid supporting CSI.
## 4 Results and Discussion
### Rail Uplift Force and Rail Stress  
When designing a precast slab track, the performance of components such as fasteners, slabs, and elastic devices can be secured by applying each performance standard or structural design standard. However, even though each component requires performance,  
Figure 8: Wheel load variation results: (**a**) Precast Floating Slab Track (Type I), (**b**) Precast-Fast Improvement slab Track (Type II).  
if they behave systematically in a combined state, the performance of the system's usability should be confirmed considering long-term maintenance [26]. In the track system, if the rail stresses and rail uplift forces are huge, the life of the rail and fastener become shortened and the maintenance cost will increase by changing the rail pad. Therefore, it is important to evaluate these problems.  
Figure 9 shows the results of rail uplift force when the train runs on the middle panel of both types of track. The rail uplift force must not be greater than the initial clamping force of the rail fastener so that the rail pad cannot move or twist. In these types of precast slab tracks, the Vossloh System 300-1 type of fastener was used to connect rails with the concrete panel. The initial clamping force of this device is 16.9 kN and the allowable force is 70% of this value, equal to 11.83 kN [26]. As can be seen in Figure 9, the rail uplift force of both types of precast slab track met the requirement. The maximum uplift force of Type I was 1.09 kN, while the force of Type II was slightly larger (1.28 kN).  
In this paper, the KR-60 rail was mounted on both types of precast slab tracks. The allowable stress of the KR-60 rail is normally 130 MPa [5]. The reference value to analyze the rail stresses is 70% [27] of 130 MPa and equal to 90 MPa. Figure 10 describes the rail bottom stress of precast slab track systems when operating the train.  
Figure 10: Rail bottom results: (**a**) Type I, (**b**) Type II.  
Figure 9: Rail Uplift Force results: (**a**) Type I, (**b**) Type II.  
As can be seen in Figure 10, the rail bottom stress in the precast slab track systems section was larger than ballasted section. The maximum rail bottom stresses occurred at the transition point between ballasted section and precast slab track section. This happened due to the change of supported stiffness when the train runs from the ballast track to the concrete track. The precast slab track Type II has a distance of the elastic devices closer and stiffer than Type I, so the maximum of rail bottom stress of Type II was smaller than Type I.
## 3 The Virtual-Force-Based Guidance Law
### Virtual Centripetal Force for Curve Following  
For curve following, the reference point is not in an equilibrium state. The virtual spring force and the virtual drag force are insufficient to guide a UAV to accurately track a curve. Then, a virtual centripetal force (\(F_{vc}\)) is designed to enable a UAV to track the maneuver of the reference point. \(F_{vc}\) points to the center (\(O\)) of the curvature circle at the reference point as shown in Figure 3.  
The magnitude of the force \(F_{vc}\) is  
\[F_{vc}=\frac{v_{T}^{2}}{l} \tag{11}\]  
where \(l\) is the distance from the UAV to the center \(O\); and \(v_{T}\) is the velocity component of the UAV along the tangent direction at the point V.  
The virtual centripetal force pulls the UAV to circle the point \(O\) at a radius of the current distance \(l\). It counteracts the influence of \(P_{r}\)'s maneuver on \(d\), so that the virtual spring force and the virtual drag force guide the UAV to track a curve like a straight-line. Then, the dynamics of \(d\) are same as those of the straight-line case. After the UAV converges to the reference curve, \(l=r\), the virtual centripetal force keeps the UAV moving along the reference curve.
# Tomato Maturity Estimation Using Deep Neural Network
## 4 Results and Discussion
### Evaluation of the Estimation Speed  
The DNN model was constructed using shallow CNN layers; as such, this architecture has advantages in terms of real-time processing, allowing for its practical use in the target system. The method was tested with a high-end GPU-based hardware configuration, as well as in a low-cost Jetson board (Xavier NX; NVIDIA, Santa Clara, CA, USA). The test was conducted by inputting the consecutive frames, and multiple tomatoes in each frame were evaluated for their maturity, where the locations of the tomatoes were pre-determined for every frame. Figure 8 depicts the inference time measured by the software timer by frame and Table 3 shows the processing speed comparison by the GPU. For the Volta GPU in the Xavier NX, the number of CUDA cores is more than 10 times smaller than that in the Titan-V; however, the Jetson board showed only an approximately 3-4 times longer processing time. The processing time for the Xavier NX was approximately 0.02 s, which is equivalent to 50 fps, meaning that it can operate well enough to be used in a robotic system without a significant increase in the processing time. This result indicates the practicality of our method, considering a shallow DNN architecture (although pre- or post-processing algorithms were not considered).
# Advantages of Corrosion-Resistant Overlay Welding on Steel S355J2N
## 2 Materials and Methods
### Welding Process  
The welding base system (at the Department of Materials Science and Technology, SZE, Gyor, Hungary) consists of an IGM KUKA RTE-4 robotic arm, which features 6 + 2 rotational axes and a TPS 4000 power source (IGM Robot Systems Ltd., Gyor, Hungary) (Figure 1).  
Welding by the robot was performed using flux-cored wire, which is considered a modern filler material. Compared to solid wire, it offers several advantages, such as high productivity, applicability to a wide range of chemical compositions, lower sensitivity to edge misalignment, a lower average temperature of the weld pool, reduced spattering, and stable arc behaviour; it also keeps the contaminant levels low. Its disadvantages include higher procurement costs and the need for skilled personnel.  
There are specific rules for the use of flux-cored wires, which must be followed during application, as the ferrite number is significantly reduced if carbon and nitrogen from the environment enter the weld (such as from the workpiece surface, the shielding gas, the welder's gloves, etc.). Variations of flux-cored arc welding with shielding gas are well suited for overlay welding purposes, as they can be applied within a wide current range. During the experiments, the chosen welding materials were always used with consideration of a recommended shielding gas for the wire, and these parameters are included in the welding procedure specification. The key parameters of the welding procedure specification relevant to our experiment are included in Figure 2.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Tubular Cored Electrode** & **C** & **Si** & **Mn** & **P** & **S** & **Cr** & **Mo** & **Ni** & **Cu** \\  & **\%** & **\%** & **\%** & **\%** & **\%** & **\%** & **\%** & **\%** & **\%** \\ \hline
**FOXcore 309 LMo-T0** & 0.02 & 0.70 & 1.30 & 0.024 & 0.005 & 22.00 & 2.60 & 13.30 & 0.10 \\
**FOXcore 316L-T0** & 0.02 & 0.62 & 1.48 & 0.025 & 0.010 & 18.96 & 2.82 & 12.28 & 0.11 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Chemical composition of the electrodes.  
Figure 1: IGM KUKA RTE-4 welding machine during working.
# Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks
## 5 Challenges and Future Research Directions
### Distributed Learning Information  
Distributed AI can control the future D2D generations. The mutual information between ML and communications communities are essential and strongly required for promising unique solutions. The D2D community designers should provide ML designers with sufficient information about the devices/locations/speeds/environments so as to invent suitable algorithms that succeed to perform distributive learning.
###### Abstract  
The treatment of landfill leachate, due to its great polluting load, is a very difficult task. In particular, the abatement of high ammonium concentrations represents one of the main issues. Among the available techniques, struvite precipitation is an effective method for the removal and recovery of NH\({}_{4}\)\({}^{+}\) load. However, due to the lack of phosphorus and magnesium amounts, the struvite formation results in an expensive process in the leachate treatment. To overcome this issue, in the present work, we developed a simple and suitable method for ammonium removal by the multiple recycling of struvite decomposition residues. In this regard, a procedure for acid dissolution of struvite, produced by using industrial grade reagents, was initially defined. The effect of pH, temperature, and acid type was investigated. The experimental results proved the effectiveness of both hydrochloric and acetic acid, which allow a high and selective release of ammonium at T = 50 \({}^{\circ}\)C and pH = 5.5. The multiple reuse of decomposition products, combined with the supplementation of a small quantity of phosphorus and magnesium at molar ratios of \(n\)(N):\(n\)(Mg):\(n\)(P) = 1:0.05:0.05, guarantees stable NH\({}_{4}\)\({}^{+}\) abatement of about 82%. The proposed process allows a cost saving of around to 74% and can be easily applied in industrial treatment plants.  
ammonium removal; landfill leachate; struvite; wastewater treatment Article
# Single-Lens Imaging Spectral Restoration Method Based on Gradient Prior Information Optimization
## 2 System Model  
The single-lens imaging system in this study utilizes the axial chromatic dispersion of a single lens, and a spectral imaging model is established on the basis of this characteristic, as shown in Figure 1. A coordinate system (_xy_) is established at the lens position, and another coordinate system (_x_y_y_) is established at the imaging position, with the opticalaxis along the _z_-axis.  
Moving the detector along the optical axis, data are collected at specific positions, and include image information from different wavelengths, known as a mixed spectrum. Assuming that data are collected at the focal position corresponding to wavelength \(\lambda_{1}\), the collected mixed spectrum can be represented as follows:  
\[\begin{split} g_{1}(x,y)&=h_{1}(x,y,z_{1})*f(x,y, \lambda_{1})+h_{2}(x,y,z_{1})*f(x,y,\lambda_{2})\\ &\qquad\qquad+\cdots h_{i}(x,y,z_{1})*f\big{(}x,y,\lambda_{j}) \end{split} \tag{1}\]  
where \(g_{1}\)(_x_y_) represents collected mixed spectrum information, \(h_{i}\)(_x_y_,\(z\)1) represents the point spread function (PSF) corresponding to different wavelengths at the collection position,_f_(_x_y_,_l_) represents the original image at different wavelengths, and \"\(*\)\" denotes the convolution operation.
# Performance of Narrow Band Wide Area Networks with Gateway Diversity
## 1 Introduction
Unlike existing literature which mainly analyses the UL performance [6], this paper presents not only the UL performance, but also the DL performance which is an essential part of the network. In UL, multiple GWs can listen to the packets from the ENs, hence providing spatial diversity. In DL, only one of the GWs responds to an EN. This paper presents the performance evaluation to determine the number of GWs to achieve a certain PSR target in a given coverage area. This paper also evaluates the coverage area that can be achieved under interference from multiple end-nodes and multiple GWs while considering packet collisions. The paper is organized as follows. In Section 2, the principles of the LoRa modulation are introduced, followed by the illustration of the benefits of IQ inversion for the LoRa modulation. The system model for channel access, interference, and path loss can be found in Section 3. Finally, the numerical results and conclusions of this work are presented in Sections 4 and 5, respectively. Figure 1: LPWAN with GW diversity.
# Transaction Mechanism Based on Two-Dimensional Energy and Reliability Pricing for Energy Prosumers
## 4 Case Study
### Performance Evaluation
#### 4.2.2 Grid Reliability  
For utility, grid reliability can be defined as such factors as voltage stability and frequency regulation state maintenance [29]. It is required for better situational awareness and operator assistance to improve grid reliability [5]. The predictability is an important term that affects reliability. In this work, the mean absolute error (MAE) between the actual generation and its forecasting is used as a performance metric to measure predictability. In Figure 8, the MAE improves with increasing EES capacity. It is said that grid reliability improves with increasing EES capacity. Additionally, the MAE under the proposed ERT has a lower value than that under the conventional pricing mechanism. This means that the implementation of the proposed ERT effectively improves grid reliability versus the conventional pricing case. However, the MAE is not monotonically improved, as shown by the proposed ERT case with 15% EES capacity of installed generation (the point in the dashed circle in Figure 9). This is because the performance of MAE not only relates to the price but also the generation characteristics.  
Figure 8: Comparison of user revenue enhancement under the conventional pricing mechanism and the proposed ERT.
# Performance Analysis of Physical Layer-Based Multiple-Input Multiple-Output on WiMAX (MIMO-WiMAX) +
## 3 MIMO-WMAX System  
In order to provide customers with high-speed broadband internet access, WiMAX-MIMO systems were developed. These systems incorporate the benefits that are associated with WiMAX technology and MIMO systems [13]. The goal of this research is to obtain diversity gain by combining WiMAX technology with the spatial diversity approach used in MIMO systems. In order to evaluate how well MIMO-WMAX is functioning, Alamouti Space Time Block Codes are included [14]. The schematic of blocks is shown in Figure 5.  
The high data rate transmission that arises from the combination of WiMAX with MIMO technology is one of the ways the performance of WiMAX-MIMO systems may be improved over that of normal WiMAX systems. The performance of this technology is superior to that of standard WiMAX, which does not make use of MIMO systems for both BER and SNR. Alamouti systems are implemented using two transmit antennas and nr reception antennas, and are capable of having a maximum diversity order of 2 Nr. Maximum Likelihood Decoding is used at receivers for Alamouti code encoding.