esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Harmonic Suppression Method
### The Traditional Harmonic Suppression Method
According to Figure 9, the open-loop transfer function of the inner current loop with the QPR is  
\[H_{\text{QPR}}(s)=\frac{k_{\text{pQPR}}s^{2}+2(k_{\text{pQPR}}+k_{\text{rQPR}}) \omega_{\text{c}}s+k_{\text{pQPR}}\omega_{n}^{2}}{(s^{2}+2\omega_{\text{c}}s+ \omega_{n}^{2})(sL+r)} \tag{16}\]  
The performance of the resonant elements controller is affected by \(k_{\text{pQPR}}\) and \(k_{\text{rQPR}}\). Taking the \(k_{\text{pQPR}}\) and \(k_{\text{rQPR}}\) in three different scenarios allows for the analysis of the QPR controller's characteristics. The first value is set as \(k_{\text{pQPR}}\) = 1, \(k_{\text{rQPR}}\) = 100, the second value is set as \(k_{\text{pQPR}}\) = 100, \(k_{\text{rQPR}}\) = 1, and the third value is set as \(k_{\text{pQPR}}\) = 100, \(k_{\text{rQPR}}\) = 100. The bode diagram is described in \[G_{\text{RE}}(s)=k_{\text{pRE}}+\sum\limits_{i=2}^{l}\frac{k_{\text{rRE}i} \omega_{i}^{2}}{s^{2}+\omega_{i}^{2}} \tag{13}\]0  
In Figure 11, \(\omega_{\text{c1}}\)\(\omega_{\text{c2}}\) and \(\omega_{\text{c3}}\) are the cut-off frequencies of the \(H_{\text{QPR}}\)(s) under the three different values. A conclusion can be drawn by \(\omega_{\text{c1}}>\omega_{\text{c3}}\) that reducing \(k_{\text{pQPR}}\) will increase the system's bandwidth and response speed, but it will also decrease the phase margin, increasing the probability of system instability. It can be obtained through \(\omega_{\text{c2}}<\omega_{\text{c3}}\) that diminishing \(k_{\text{rQPR}}\) will enhance the system's phase margin, but it will cut down the system's bandwidth, resulting in slower system response. The fundamental gain and phase margin do not differ significantly under the three scenarios, therefore, employing a QPR controller will enhance the system's stability. However, the QPR controller only has a suppressive effect on high-frequency harmonics and cannot eliminate the impact of low-frequency harmonics.
# Brake Light Detection Algorithm for Predictive Braking
## 3 Methods
### Experiments  
All the camera feed was captured using Spinnaker Python API. The captured raw video format had to be converted into AVI for an OpenCV suitable format. The collected image data was acquired by extracting the bounding boxes placed by YOLOv3. As the bounding box sizes varied, the vehicle rear image sizes also varied. This image data of vehicle rears was used to quantify the classification accuracy of the proposed brake light detection algorithm.  
In order to locate the feasible operation range of the algorithm, a test setup was created with two vehicles. The test setup consists of traffic cones placed on the side of a road. The cones were placed with 25 m spacing from 0 to 150 m, resulting in 6 different measurement points. All the cones were placed using a laser distance measurement to achieve accurate distances. Two vehicles were utilized for the experiments. The vehicle with brake light detection was in a standstill at 0 m and the vehicle to be detected was placed with 25 m increments all the way up to 150 m. A video of each position was captured, ensuring that each increment includes a video with brake lights on and off.
## 6 Conclusions  
The space industry has shown an increasing interest in implementing AI in SatCom systems, which presents itself as a promising alternative to time-consuming and highly complex optimization techniques encountered in radio resource management.  
In this sense, this paper evaluates and discusses two ML technologies for radio resource management in multibeam satellites. The study mainly focused on RL and SL-based analysis, especially regarding the intrinsic features of the models used, the performance and the added delay due to whether training is online or offline. In addition, two different architectures are discussed to implement the AI Chipset on the ground or onboard the satellite. This is defined based on whether training is conducted online or offline.  
According to the results presented in this paper, RL-based algorithms can perform better than those using SL techniques. However, this superiority comes at the cost of increased training time, which, in the case of RL, is divided into exploration and exploitation time. An additional relevance of RL-based techniques is that the training is online, i.e., the RL model will be updated every time the traffic demand in the service area is modified, thus generating an added delay to the resource update response. This represents a trade-off between the performance obtained and the efficiency of the implementation.  
On the other hand, SL-based algorithms are usually trained offline. Hence, SL-based algorithms are presented as an exciting alternative for implementing onboard satellite AI Chipset.  
In addition, we have identified different AI accelerators currently available in the market that may be candidates for future implementation projects, establishing which are the main features to be considered for their selection. The discussion presented in this paper is expected to serve as a milestone for upcoming projects in which the feasibility of AI Chipset implementation in future SatCom systems, such as the SPAICE project [35] and TechEdSat-13 [36], will be tested.  
Conceptualization, F.G.O.-G. and L.L.; methodology, F.G.O.-G. and L.L.; validation, E.L., R.M., D.T. and M.A.S.-N.; formal analysis, E.L., R.M. and D.T.; investigation, F.G.O.-G., L.L. and E.L.; data curation, F.G.O.-G. and L.L.; writing--original draft preparation, F.G.O.-G.; writing--review and editing, J.Q., L.L. and E.L.; supervision, E.L. and S.C.; project administration, R.M., E.L. and S.C.; funding acquisition, R.M., E.L. and S.C. All authors have read and agreed to the published version of the manuscript.  
This work has been supported by the Luxembourg National Research Fund (FNR) under project SmartSpace (C21/IS/16193290), project FlexSAT (C19/IS/13696663), project ROSETTA (C17/IS/11632107) and project MegaLEO (C20/IS/14767486) and by the Spanish Government, Ministerio de Economia, Industria y Competitividad through the National Program of Research, Development and Innovation within project FUTURE-RADIO (TEC2017-85529-C3-1-R).  
Not applicable.  
The data that support the findings of this study are available from the corresponding author upon reasonable request.
# Implementation Aspects in Simulation Extrapolation-Based Stocking-Lord Linking
## 5 Discussion
Results showed that the repeated iterative estimation in the SL linking method was unnecessary, as the precision of the linking parameter estimation remained essentially unaffected. Consequently, the one-step update of SL linking based on a Taylor approximation proved useful for practical implementation. Furthermore, the one-step update could also be applied to the replication-based approach, which demonstrated superior performance compared to the simulation-based SIMEX SL linking approach when dealing with a small set of ten items. These findings suggest that practitioners can use SIMEX-based SL linking without resorting to computationally intensive routines. As in any simulation study, our simulation study had several limitations. First, we only handled uniform DIF effects. Although nonuniform DIF effects (i.e., DIF in item discriminations) seem to appear in practical applications less frequently [35], an extension of the proposed SIMEX-based SL linking methods to nonuniform DIF effects might be an interesting topic for future research. Second, SIMEX-based SL linking [36; 37] could also be explored for polytomous item responses in the generalized partial credit model [38]. Third, alternative IRT models might be studied in SIMEX-based SL linking, such as the Rasch model or the three- or four-parameter logistic IRT models. Moreover, SIMEX-based SL linking can be investigated in longitudinal linking studies [39]. In addition, the proposed shortcut based on Taylor approximation in the SIMEX method could also be applied in fixed item parameter calibration in future research [40]. The following supporting information can be downloaded at: [[https://osf.io/b4](https://osf.io/b4) rdh]([https://osf.io/b4](https://osf.io/b4) rdh) (accessed on 3 October 2024). Conceptualization, A.R. ; methodology, A.R. ; software, A.R. ; validation, A.R. ; formal analysis, A.R. ; investigation, A.R. ; resources, A.R. ; data curation, A.R. ; writing--original draft preparation, A.R. ; writing--review and editing, A.R. ; visualization, A.R. ; supervision, A.R. ; project administration, A.R. ; funding acquisition, A.R. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. This article only uses simulated datasets. Replication material for creating the simulated datasets in Section 3 can be found at [[https://osf.io/b4](https://osf.io/b4) rdh]([https://osf.io/b4](https://osf.io/b4) rdh) (accessed on 3 October 2024) (Supplementary Materials). The author declares no conflict of interest.
# Evaluation of VoIP QoS Performance in Wireless Mesh Networks
## 2 VoIP Application and Scenarios
### Urban and Rural Deployment  
There have been successful municipal Wi-Fi installations for public services like in Tallinn, Mountain View, and Kuala Lumpur [48], which are examples of urban deployments. Many other countries have also started to provide similar services for the public in many cities. Municipal Wi-Fi installations can be supported by a WMN backbone. These installations are cost effective and highly available for many services including VolP services [49]. While using mesh technologies for providing backhauling to the mesh clients is very effective and improves the network's availability factor, the same solution could be used among the mesh clients to improve the network's coverage and connection areas where backbone WMN equipment cannot provide adequate coverage or where the installation of backbone equipment is not cost-effective. An example of an urban mesh network is shown in Figure 3a (adapted from [50]).  
Usually, rural areas do not benefit from the many services that modern communication technology can offer. This is the case in many undeveloped and developing countries [51]. Wi-Fi mesh can solve this problem to an extent by enabling people in rural areas to communicate among themselves, call  
Figure 2: Flooded village [38] scenario where the fixed communication infrastructure is affected and WMNs could be used to establish connectivity among affected people and first responders.  
local offices like the police station, firefighting teams, hospitals, etc., even if they are not connected to the Internet or to call gateways to make long-distance calls, as shown in Figure 3b.
# Design and Testing of Two Haptic Devices Based on Reconfigurable 2R Joints
## 6 Discussion on Haptic Device Test Results
### Joint Designs Assessment  
According to the results of the statistical analysis, presented in Table 3, there is a significant difference in sample means in tasks 3 and 4 in the position control mode. The absence of differences in the results of these tasks in the velocity control mode indicates that the velocity control mode provided similar performance in both haptic devices.  
Analyzing the means of the samples in tasks 3 and 4 (see Tables A1 and A2 of Appendix A) it can be seen that the differential gear-based design joint provided smaller mean values in both tasks, which corresponds to better performance.  
The worse performance of the active 2R spherical mechanism-based joint can be explained by its more complex kinematics. This joint has singular positions, one for each of the blue actuators (4 in Figure 1a). This takes place when the red actuator (3 in Figure 1a) is inclined \(\pm\)25\({}^{\circ}\) from the vertical position. In order to keep the joint in fcontrol, it is necessary to switch between the encoders that are connected to the blue shafts and between the two actuators of the force feedback system. However, due to the clearances in the joint, there is a difference in these two encoder readings. That difference causes a variation in the calculated angle that defines the horizontal displacement of the end-effector. The value of this angle can change in range of 3\({}^{\circ}\)-5\({}^{\circ}\), which results in a big leap of the end-effector in the moment of switching between the encoders. As tasks 3 and 4 were focused on precision, this feature affected the device's performance significantly.  
The second reason is the high friction forces in certain positions of the blue actuators, which lead to jamming of the joint. This take place near the workspace border, when the force feedback generates a resisting force. In these cases, the additional force of the feedback increases friction and it becomes very hard for the operator to change the position of the handle. In the velocity control mode, these extreme positions in the active 2R spherical mechanism-based joint can be avoided by lowering the speed, but in the position control mode it is impossible. This disadvantage affected the execution of task 4, as it required precise and fast reactions from the operator.  
The problem of clearances in the joint can be solved by using more precise manufacturing methods; however, the second problem is conditioned directly by the joint kinematics and cannot be solved easily.  
In addition to the statistical analysis, the survey of the testers showed that 100% of the operators who participated in both haptic device tests chose the differential gear-based joint design as the best one.  
It can be concluded that due to its simpler kinematics, the differential gear-based joint design demonstrated better performance than the active 2R spherical mechanism-based joint in a haptic device application.
## 6 Performance Evaluation
### Simulation Environment  
In the simulations, CIDF-WSN consider several heterogeneous wireless sensor nodes deployed in the monitoring area of 100 m \(\times\) 100 m with a total number of 100 nodes which are organized into five layers with an equal number of nodes. These nodes are static, and each node is equipped with a GPS module to acquire its physical location. The transmission range of nodes is restricted to one hop (i.e., towards the upstream node in the upper-layer or downstream node in the lower layer). The simulations are conducted in ndnSim [17] (an NS-3 extension developed for simulating NDN-enabled networks) on a desktop computer with a Core i5 CPU (2.90 GHZ), 8 GB of RAM, and a Linux Ubuntu operating system (i.e., 20.04).  
The complete simulation parameters are summarized in Table 2.
# Key Management Scheme Based on Route Planning of Mobile Sink in Wireless Sensor Networks
## 4 Simulation and Evaluation
### Energy Consumption  
In the proposed scheme, the MS moving model is abstracted to a TSPN model, and that is to say data collection can be undertaken as long as the MS is within the the communication range of the sensor nodes. Compared to the TSP model, this model can reduce the movement distance of the MS and the energy consumption for transmitting data of the cluster heads. Now we let the MS collect data docking at the distance of 1-30 m to cluster heads, and the initial energy is 0.1 J. By computing the energy consumption when the cluster head transmits 4000 bits of data to the MS and a base station, respectively, we can analyze the comparison results and prove that it can effectively save the energy consumption of data transmission when we introduce a MS node. The simulation result is shown as Figure 8. We also give the relationship between the movement distance and the stop sites of the MS, shown in Figure 9.  
In a wireless sensor network, if we do not adopt the MS movement model, the fused information of the cluster head has to be transmitted to thr base station in single hop or multiple hop mode. Data transmission over long distances not only will easily interfere to the data transmission links, but also increase the energy consumption of the nodes. However, the energy consumption of transmission could be obviously reduced after introducing the MS node.  
Figure 8: The contrast of energy consumption for transmitting data to the base station and the MS.  
Figure 7: The comparison of node’s storage overhead among E-G, AP, and the proposed scheme after the session key establishment.  
In this scheme, the proposed dynamic clustering method makes the network topology change at any time, so the optimal MS route will change relatively. From the point of view of energy analysis, the proposed scheme saves energy consumption. Therefore, it prolongs the survival time of the network. The selection of stop sites of the MS will influence the survival time of the network, and this relationship is shown in Figure 10.  
If we define the death time of the first node as the survival time of the network, and the initial energy is 0.1 J, the first node will die in the 222 nd, 217 th, and 211 th round when the MS stops at the distance of 5 m, 10 m and 15 m from the cluster head, respectively, and the first dead node dies in the 191 th round when sending the collected data to the base station. As shown in Figure 9, the farther the distance from the stop site to cluster head is, the shorter the movement distance of the MS will be, and if the stop site is far from the cluster head, the round of the first node death will appear ahead of time, and the survival time of the network is shorter. For a MS, the energy of the node is relatively abundant, but from the perspective of security, a node's premature death will easily make the network unstable, and even lead to cracking. Therefore, it is worth extending the survival time of the network at the cost of sacrificing the movement distance of the MS.
# Performance of the Dual-Chamber Fungal Fuel Cell in Treating Tannery Wastewater
Energy occurs in many types resulting from either biogas production, biohydrogen, or voltage output [20; 21]. All energy outputs come from the degradation of organic constituents present in the wastewater. Training studies should be performed for the available adaptation of fungi strains to reduce the toxicity levels of metals. This training study addresses the possible adaptation of fungi strains to metal stress conditions [27]. Microbial fuel cells (MFCs) are a technology that is able to decrease organic compounds present in wastewater using microbial activity and convert the chemical energy into electrical energy via spontaneous oxidation-reduction mechanisms [26]. MFCs can be considered as a method needed for both energy recovery and pollutant removal in tanny wastewater [28]. MFC technology has been used to treat domestic wastewater, swine wastewater, and wastewater from paper recycling [29; 30]. Organically loaded compounds in the paper industry were used as a source of energy using microorganisms in a dual-chamber mi crobial fuel cell (MFC) [31]. Studies have shown that the increase in the wastewater ionic conductivity increases the MFC power output. Electrolytic matrices as a common additive to stabilize pH [32; 33], boost anodic cell conductivity [34; 35], and speed up proton transfer mechanisms [36] were necessary for optimal MFC performance. [PERSON] et al. [37] showed that the addition of 50 mM of phosphate buffer solution (PBS) increased the power output by 136% to 438 mW/m\({}^{2}\), and 200 mM of PBS increased the power output by 158% to 528 mW/m\({}^{2}\), when treating beer brewery wastewater. [PERSON] and [PERSON] [38] observed that the maximum power densities increased from 144 mW \(\times\) m\({}^{-2}\) to 501 mW \(\times\) m\({}^{-2}\) with 50 mM PBS, and 672 mW \(\times\) m\({}^{-2}\) with 200 mM PBS, when treating paper recycling wastewater. Therefore, it is important to assess the effect of adding electrolytes on energy output. The novelty of this study was to assess the feasibility of treatment of tannery wastewater using a dual-chamber FFC and observe how to improve the operation via the selection of fungal strain, training of fungal strain, and the effect of electrolytic matrices (PBS and BBS) on FFC performance. The performance is determined via assessing the variations in organic degradation represented in COD, TN elimination, and total chromium removal along with the determination of variation in energy output represented in cell voltage output (V), power density (PD), and current density (CD).
# Reversing File Access Control Using Disk Forensics on Low-Level Flash Memory
## 2 General Background
### Flash Memory  
NAND flash has been used broadly as the external storage in both standard computers and mobile devices today [16], as it consumes much less power and is capable of much faster read/write speeds. Flash memory is typically organized into blocks, each of which consists of pages which contain a certain number of bytes of data. Each page contains a small out-of-bounds (OOB) area [6]. This OOB area is a small number of bytes (16 in our test drive) which is used to store extra data, such as error correcting codes. However, this OOB space is not typically fully used, and as such can be taken advantage of. Flash memory also has several unique hardware characteristics including erase-before-write, suffering from wear, etc. These unique features distinguish flash memory from traditional mechanical drives.  
**Erase-before-write**. The way in which NAND flash performs writes is unique. Each page has a default state which is entirely made up of '1's. When a write is performed and a buffer is provided, the drive simply sets any '1's to '0's where the buffer directs, leaving other bits alone. As one would expect, a write operation run on the disk is performed at the smallest size the drive can handle, one page. However, because of this unique system, an erase operation is performed on the scale of an entire block of (usually 64) pages. As a result, an entire block must be erased before a page can be overwritten and erasures are treated as a very expensive operation [17].
# Elicitation of the Allelopathic Potential of Rice by Methyl Salicylate Treatment
###### Abstract  
Weed infestation is one of the most severe problems affecting rice production worldwide. Current weed control practices are either costly or pose a threat to the environment. The use of competitive rice genotypes seems to be a promising strategy. The aim of our study was to improve the allelopathic potential of three selected rice genotypes by foliar application of methyl salicate (MeSA), a signaling molecule eliciting the plant defense response. Aqueous extracts of the shoots and roots of two competitive (UPR 2962-6-2-1 and Govind) and one non-competitive (UPR 2992-17-3-1) rice genotypes treated with MeSA solution at different concentrations (1 mM, 2 mM, and 3 mM) showed phytotoxic effects on the growth of the weed _Echinochla colona_. Specifically, shoot and root extracts obtained from the competitive rice genotypes similarly decreased both the _E. colona_ germination rate (9% to 44.5%) and the length of its roots and shoots (11% to 48%). Extracts of the non-competitive rice genotype showed a similar trend but lower effects, inhibiting the _E. colona_ germination up to 32% and reducing the growth of the weed roots and shoots by 6-23.5% and 7-28%, respectively, according to the increasing MeSA concentrations. High-performance liquid chromatography (HPLC) analysis demonstrated an increase in different allelopathic phenolic acids in the three rice genotypes in response to MeSA treatments. Among the detected compounds, vanillic and protocatechuric acids showed the greatest differences compared to controls with values up to 2.1-fold higher in shoots of the two competitive UPR-2962-6-2-1 and Govind rice genotypes, while their roots were characterized by the greatest increases of 8-hydroxyquinoline (8.2-fold) and protocatechuric acid (1.7-fold). Differently, non-competitive genotype UPR 2992-17-3-1 showed the highest increase for gallic acid (2.2-fold) in shoots and for p-hydroxybenzoic acid (2.4-fold) in roots. Lastly, MeSA was found to improve the competitiveness of rice genotypes without any detrimental effect on the host plant.  
allelochemicals; elicitors; _Oryza sativa_; paddy; phenolics; phytotoxicity