esa-sceva/satcom-chunk-collection huggingface dataset:
# SDN Architecture for 6 LoWPAN Wireless Sensor Networks
## 3 SD6 WSN Architecture
This kind of change should be carefully evaluated because it is common for transient changes in the quality of the transmission medium in wireless networks. Therefore, the ETX metric is calculated by an exponential moving average. In all three cases, the relevance of the change is defined by percentage thresholds that are configurable, all having default values. A node is considered inoperative when more than 50% (default parameterization) of its neighbors fail to report it in their neighborhood lists. In the default parameterization, the deterioration of link quality is considered relevant when a 100% increase in the ETX metric occurs in relation to the last notification sent, and the improvement is considered relevant when a 50% reduction of ETX is reported. The format adopted for response and notification messages is JSON (JavaScript Object Notation) [28]. This format is largely used and has the advantage of a simple structure, with the delimitation of the fields formed by unique characters, like keys and brackets. SD6 WSNP defines four messages: node-mod, info-get, flow-mod and packet-in. Messages are classified according to the process to which they are associated. Node-mod and info-get are used for topology discovery and maintenance, while flow-mod and packet-in are used for flow control. Node-mod is the first message sent by SD6 WSNP, from the controller to the border router (6 LBR), requesting a notification every time a new node is identified by RPL. Just after receiving a notification, the controller sends info-get to obtain the neighbors of the discovered node and the quality of respective wireless links. A networking application can also ask the controller to send an info-get, whenever it needs information from a node. After registering the node information in its database, the controller sends a packet-in message instructing the node to send back a notification when it receives data plane packets that do not match any entry in its flow table. Flow-mod is used to insert and remove entries in flow tables, allowing the networking applications to install flows according to their traffic needs. Table 3 summarizes SD6 WSNP messages, and more details are provided in [9]. \begin{table}
\begin{tabular}{c c l} \hline \hline
**Action** & **Length (Bits)** & **Description** \\ \hline \multirow{3}{*}{type} & \multirow{3}{*}{8} & 0, Forward the packet to the next-hop through the data plane \\  & & 1, Drop the packet \\  & & 2, Forward the packet to the controller through the control plane \\ \cline{1-1} nhipaddr & 128 & Next-hop IPv6 address (required parameter for Type 0) \\ \cline{1-1} rfpwr & 8 & Transmission power (optional parameter for Type 0) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Action field of the SD6 WSN flow table entry. Figure 3: Flow table entry format.
## 2 Background
However, artificial visual landmarks are still required to be properly recognized by the AV's computer-vision-based system in extreme environmental conditions. [PERSON] [28] proposed a system for navigating AVs in a winter terrain by extracting the vector of the visual navigation marker. This approach might be effectively employed when the visual conditions are more or less stable,without significant environmental condition degradation. [PERSON] and [PERSON] [PERSON] and [PERSON] [29] developed a system for navigation in a 3D space, including open terrain areas. The disadvantage of the solution is that it also does not consider the AV's operating conditions, which makes it unsuitable for complex environments. In this paper, we focus on rather complex, dynamic, and weather-dependent environmental conditions that affect the quality of the obtained visual information in various ways. Specifically, we developed a computer-vision-based AV localization system and enhanced its robustness regarding the on-board camera image quality degradation caused by harsh environmental conditions. One of the significant challenges we addressed is the low informative features visibility caused by the unstable environment. The extreme weather can cause camera lenses to freeze or fog, which can further degrade the image quality and affect the computer-vision-based localization performance. Additionally, the reflective properties of snow and ice can create glare and distortions in the images captured by the system, thereby further degrading the DQ. We present a solution capable of adapting to those complex weather conditions by employing an ML model for a computer-vision-based localization system. As the visual information extractor, we employed a convolutional neural network (CNN), as it demonstrated the highest performance in our empirical investigation. To enhance the robustness of our ML-based model, we produced images affected by various complex environmental conditions and employed them to re-train the model. To further assure the ML model performance on the low quality data, we expanded the training dataset by modifying it using affine transformations. Below, we describe the architecture and major components of the developed AV computer-vision-based localization system and how it might be integrated in the overall navigation process.
# A Novel Multi-Objective Five-Elements Cycle Optimization Algorithm
## 5 Simulation Experiment and Result Analysis
### Parameter Analysis and Comparison Experiments of MOFECO
#### 5.3.4 Comparison of Mutation Methods
(The best result is bolded for each function). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Functions** & **Combined Mutation** & **Cauchy Mutation** \\ \hline ZDT1 & \(\mathbf{1.40\times 10^{-4}}\) & \(1.50\times 10^{-4}\) \\ ZDT2 & \(\mathbf{4.02\times 10^{-6}}\) & \(\mathbf{2.46\times 10^{-6}}\) \\ ZDT4 & \(\mathbf{2.39\times 10^{-5}}\) & \(1.50\times 10^{-3}\) \\ ZDT6 & \(\mathbf{3.50\times 10^{-7}}\) & \(1.80\times 10^{-3}\) \\ DTLZ2 & \(\mathbf{7.43\times 10^{-4}}\) & \(1.10\times 10^{-3}\) \\ DTLZ4 & \(1.43\times 10^{-3}\) & \(\mathbf{7.65\times 10^{-4}}\) \\ DTLZ5 & \(3.56\times 10^{-5}\) & \(\mathbf{3.36\times 10^{-5}}\) \\ DTLZ6 & \(\mathbf{4.82\times 10^{-7}}\) & \(4.89\times 10^{-7}\) \\ DTLZ7 & \(9.60\times 10^{-3}\) & \(\mathbf{7.30\times 10^{-3}}\) \\ WFG2 & \(\mathbf{6.25\times 10^{-2}}\) & \(7.82\times 10^{-2}\) \\ WFG3 & \(\mathbf{5.29\times 10^{-2}}\) & \(1.87\times 10^{-1}\) \\ WFG4 & \(\mathbf{1.57\times 10^{-2}}\) & \(2.03\times 10^{-2}\) \\ MaF1 & \(\mathbf{7.10\times 10^{-3}}\) & \(7.40\times 10^{-3}\) \\ MaF2 & \(3.67\times 10^{-3}\) & \(\mathbf{2.60\times 10^{-3}}\) \\ MaF12 & \(\mathbf{1.88\times 10^{-2}}\) & \(2.01\times 10^{-2}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 13: \(IGD\) result of the mutation methods of MOFECO algorithms on test functions. (The best result is bolded for each function). From the experimental results of Tables 12-14, we can see that the Pareto solution set obtained by MOFECO using combinatorial mutation has smaller \(GD\), \(IGD\) and \(SP\) values than with using only Cauchy mutation. The reason may be that combinatorial optimization takes full account of the characteristics of Pre-iteration and late iteration, which can better adapt to the changes in the population. Thence, we choose the combined mutation in MOFECO. In summary, through the above experiment, the MOFECO parameters are configured as follows. Equation (11) is adopted for the update condition, the variation of local-global update probability \(P_{\text{s}}\) is nonlinear, and the mutation operator uses the combined mutation method.
## 4 XUV Wave Mixing and Coherent Control
### Coherent Control  
In order to manipulate molecular processes, coherent control could be the technique of choice. In this kind of experiment Phase coherent light of one or more colours interacts with a target. The outcome of the interaction is determined by the phase and amplitude of the light. Ion yield, direction of emission of ions and electrons, and so on, can be controlled. In the XUV to X-ray range, the times of the duration of an optical cycle periods are from hundreds to a few attoseconds thus increasing the temporal resolution of orders of magnitude when comparing to optical lasers. Recently FERMI has been employed to carry out the first XUV coherent control experiment where the first and the second harmonics were ionizing Neon on the \(2p^{5}4s\) resonance [13]. While the second harmonic was producing a single photon ionization process, the first was exiting two photon ionization processes (see Figure 10a).  
The possibility offered by FERMI to change the phase among the two harmonics (see Figure 10b) allowed the first experimental demonstration that coherent control experiments can be carried out in the XUV X-ray region.  
Much effort is being invested to develop ever shorter pulses at FELs. The arrival of phase control of multi-color pulses now means that they can be designed to produce trains of very short pulses, since  
Figure 10: (**a**) Scheme of the experiment. Left: a \(2p\) electron is excited to \(4s\) by one photon and then emitted as a \(p\)-wave by a second photon. Right: a \(2p\) electron process is emitted as an (\(s+d\))-wave by a one-photon process. (**b**) Asymmetry parameter \(A_{LR}\) as a function of \(\Delta\phi\) (black curve), and \(\beta_{1}\) (green), \(\beta_{3}\) (blue) and \(\beta_{2}\) (red) parameters as a function of \(\Delta\phi\). Experimental data are shown as markers with error bars. The lines are sinusoidal or straight line fits for \(\beta_{1}\), \(\beta_{3}\), and \(\beta_{2}\) respectively.  
a train of attosecond pulses can be constructed from a coherent superposition of coherent femtosecond pulses with commensurate wavelengths. This ability to tailor pulses may eventually lead to \"design\" single pulses of attosecond duration.
## 3 Case Study  
Before presenting our approach, a brief introduction of the case study that was used to evaluate the approach is given. In this research, the data from the VAST (Visual Analytics Science and Technology) dataset 2008 [37] was used. This is a synthetic dataset that was generated for the VAST challenge contest. This dataset contains a set of mobile phone call records from over a ten-day period that was narrowed down to about 400 unique mobile phones during this period. The dataset contains 9834 different calls and the values stored per call are presented in Section 3.1.  
It is important to remark that the proposed dataset was created in 2008 but, nowadays, it is still used in many different research works because it is very suitable for evaluating different tasks.  
Very recent examples (2016-2017) of the use of this dataset include voice calls interaction [38], communication network anomaly detection [39], tracking based on call log analysis [30; 31], interactive visual analytics [40], and so on. In this research, the VAST data set has been chosen because it has been used widely in this field and, in our case, the extraction of calling patterns is proposed solely from CDR data.  
In addition, one of the specifications in this research is that the extracted callers and calling patterns are related with a pre-defined time interval. The reason for this is that the obtained patterns (in relation with these time intervals) need to be clearly understood. For this reason, two different methods for pre-processing this dataset were applied. One of them is related with the calls done per hour and the other is related with a typical time division: morning, afternoon, evening and night. Both processed datasets are presented in Section 3.2.
# Review of Professionally Applied Fluorides for Preventing Dental Caries in Children and Adolescents
###### Abstract  
This review aims to evaluate the effectiveness of professional topical fluoride application on the prevention of dental caries in primary and permanent dentition. A web search was conducted for English papers published from 2000 to 2020, using various digital resources (Pubmed, Google Scholar, Cochrane Library, and ResearchGate). The keywords were \"professionally applied fluoride\", \"fluoride gel\", \"fluoride varnish\", \"fluoride foam\", \"fluoride mouthrinses\", and \"non-cavitated caries lesions\". Inclusion criteria: (a) participants: children and adolescents, treated in a dental care setting; (b) intervention: professionally applied fluorides (gel, varnish, foam, mouthrinse); (c) comparator: no professional treatment or other preventive treatments; (d) outcomes: clinical effectiveness (e.g., caries reduction, tooth remineralization); (e) study design: randomized controlled trials, systematic reviews, meta-analyses; (f) publication period: 1 January 2000-31 December 2021. Clinical studies about home-use fluoride products, discussion papers, in-vitro studies, case reports, non-English articles, and studies with unclear methodology were excluded. Topical fluoride applications are indicated for patients with active smooth surface caries and for patients in high caries risk groups. Both APF gel and fluoride varnish are effective and can be recommended for caries prevention in primary and permanent teeth. For children under the age of 6, only 2.26% fluoride varnish is recommended.  
Keywords:fluorides; professional application; caries prevention; children; dentistry; pedodontics; review +
Footnote †: journal: _Sciences_
## 3 Results and Discussion
### Chlorophyls and Carotenoids Contents  
Chlorophyls and carotenoids are the only pigments that are responsible for the characteristic yellowish-green color of the virgin olive oil. Chlorophyll is considered a basic attribute related to the quality of olive oil. The total chlorophyll content in the WOF sample was 148.41 mg/kg dw of olive fruit, whereas the total carotenoids was 85.90 mg/kg dw of olive fruit (Table 2). The chlorophyll fraction is mainly composed of chlorophyll a (86.61 mg/kg dw of olive fruit) and chlorophyll b (61.80 mg/kg dw of olive fruit). The concentrations of both chlorophyls and carotenoids decrease progressively during olive fruit ripening [50].  
As presented in Table 2, \(\alpha\)-tocopherol was the predominant tocopherol fraction of the WOF sample, whereas (\(\beta\)+\(\gamma\))-tocopherol and \(\delta\)-tocopherol were minor isomers. It is known that \(\alpha\)-tocopherol plays a protective role against oil stability and shelf life, preserving its quality [51]. The total tocopherol content quantified in the present study (107.05 mg/kg dw of WOF or 497.07 mg/kg of oil) was within the range reported for seven populations of Tunisian oleaster oils (309.5-781.8 mg/kg of oil) [52], and slightly higher for those of three Portuguese oleaster oils (392.5-467.6 mg/kg oil) [29]. However, Algerian wild oils had much lower total tocopherol content (87-182 mg/kg oil) compared to our results [7]. These differences could be associated with genetic factors or other factors involved during the transportation, storage, and processing of the fruit [53]. The (\(\beta\)+\(\gamma\))- and \(\delta\)-isomers were minor constituents, accounting for less than 3% of the total tocopherols, which was slightly lower than those found in virgin olive oils (approximately 10%). Their contents differ among cultivars and modify during fruit ripening, while environmental factors can affect their contents [54]. According to [PERSON] et al. [55], olive oils with total tocopherol contents within the range of 100 and 300 mg/kg are characterized by a good quality.
# PDTR: Probabilistic and Deterministic Tree-based Routing for Wireless Sensor Networks
## 6 Simulation Results
### Importance of Implementing the Control-Parameters Sets on PDTR
#### 6.3.2 On the Energy Consumption  
Minimizing both the transmission distance and the number of hops leads to minimizing energy consumption. To achieve this goal, the control parameters of both the transmission distance and the hop-count have to be greater than the control parameter of the residual energy distribution. For this, we consider three scenarios.  
The first scenario selected 14 parameters set such that the value of \(\alpha=3\), \(\beta=1\), while \(\gamma=\{0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.4,2.6\}\). Each source node sends one packet every 0.1 s, and the simulation time is 100 s, for the parameter values defined in Table 1 and given by Table 2, and the communication radius R = 25 m. The results show that to achieve the minimum energy consumption, the control parameter of the residual energy should be \(\gamma=0\), (see Figure 6, first scenario).  
The second scenario selected 14 parameters set such that the value of \(\alpha=3\), \(\beta=2\), while \(\gamma=\{0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.4,2.6\}\). Each source node sends one packet every 0.1 s, while the simulation time is 100 s, for the parameter values given by Table 2, and the communication range R = 50 m. The results show that to achieve the minimum energy consumption, the control parameter of the residual energy should be \(\gamma=0\), (see Figure 6, second scenario).  
The third scenario selected 14 parameters set such that the value of \(\alpha=3\), \(\beta=3\), while \(\gamma=\{0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.4,2.6\}\). Each source node sends one packet every 0.1 s, and the simulation time is 100 s, for the parameter values given by Table 2, and the communication range R = 50 m. The results show that to achieve the minimum energy consumption, the control parameter of the residual energy should be \(\gamma=0\), (see Figure 6, third scenario).  
From the above three scenarios, we can conclude that; first, the minimum energy consumption in the proposed PDTR protocol is reached when \(\gamma=0\). Second, for better results in term of energy consumption, the control parameter of the transmission distance should be set such that: \(\beta>\frac{\alpha}{2}\). Third, for better results in term of energy consumption, the control parameter of the transmission distance should be less  
Figure 5: Impact of control parameters sets on the average hops/path and the average delay/path.  
than the control parameter of the hops-count \(\beta<\alpha\).To minimize the energy consumption in the PDTR routing protocol, the values of the control parameters should be set such that \(\gamma=0,\ \alpha>\beta>\frac{\alpha}{2}\).This conclusion is maintained under the condition: \(\alpha+\gamma+\beta\leq U_{b}\) (Experimental view).
# Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment
## 3 Results  
This study examined the performance of RC and FIR filters in suppressing noise in partial-discharge signals under the fixed conditions of a sampling rate of 20 Msps, a filter order of 20, and a cutoff frequency of 1.6 MHz. The analysis results are as follows:  
The waveform of the original signal, shown in Figure 11, displays the typical characteristics of a partial-discharge signal, where the voltage changes show rapid pulse variations accompanied by a significant amount of high-frequency noise. The signal-to-noise ratio (SNR) at this stage was only 3.617 dB, indicating poor signal quality with a high level of noise, which poses challenges for subsequent signal analysis and identification.  
Figure 10: Simulation waveform noise suppression results using FIR.  
After the application of the RC filter, as shown in Figure 12, the SNR improved to 9.223 dB. This indicates that the RC filter can effectively reduce high-frequency noise, although it may affect the shape and phase of the pulses to a certain extent. However, due to its analog nature, the RC filter may have difficulties in precisely controlling the cutoff frequency, and its performance can change over time with the variability of component tolerances.  
With the use of the FIR filter, as shown in Figure 13, the SNR further increased to 9.968 dB, the highest among the three. As a digital filter, the FIR filter offers a superior noise-suppression effect and maintains the integrity and characteristics of the signal. The pulse shapes are clearer and smoother, which highlights the advantage of the FIR filter in maintaining a linear phase response, which is essential for preserving the authenticity of the signal.  
Figure 11: Partial discharge waveform acquisition using self-develop hardware.  
Figure 12: Partial discharge waveform after RC filter.  
The FIR filter demonstrates superior performance in the noise suppression of partial-discharge signals due to its inherent stability and consistent performance. Although FIR filters may require more computational resources, which should be considered when selecting a filter, they provide higher-quality signals for precise signal analysis. Conversely, if system resources are limited, the RC filter may be a more economical and practical choice. However, for the best signal quality, the FIR filter is the more appropriate option.
# An ADS-Based Sparse Optimization Method for Sonar Imaging Sensor Arrays
## 4 Analysis of ADS Thinned Array
### Frequency Performance  
It is essential to investigate the frequency performance of the sparse array obtained via the ADS method, so that this sparse optimization method can be applied to future practical projects. Therefore,  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**ArrayItems** & **Transmit** & **Receive** & **Aperture** & **Azimuth** & **Azimuth** \\  & **Elements** & **Elements** & **Size** & **Average** & **Deviations** \\ \hline Thinned by ADS & 20 & 20 & 19.5\(\AA\) & 5.25\({}^{\circ}\) & 0.31\({}^{\circ}\) \\ Thinned by CDS & 21 & 21 & 18.5\(\AA\) & 5.62\({}^{\circ}\) & 0.28\({}^{\circ}\) \\ Mills Cross & 40 & 40 & 19.5\(\AA\) & 5.00\({}^{\circ}\) & 0.16\({}^{\circ}\) \\ Mills Cross & 20 & 20 & 9.5\(\AA\) & 10.21\({}^{\circ}\) & 0.12\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Average values and standard deviations of azimuth resolutions of the arrays.  
Figure 10: Azimuth resolution of four different arrays. (**a**) Sparse array after ADS implementation (40,20,9,10); (**b**) Sparse array after CDS implementation (40,21,1); (**a**) Sparse array after ADS implementation (40,20,9,10); (**d**) Mills Cross array with \(20\times 20\) elements.  
the above obtained sparse array using the (40,20,9,10)-ADS sequence structure is used to produce some frequency examinations, and the results are compared with those of the original Mills Cross array with \(40\times 40\) elements. The relevant parameters are set as follows: center frequency (design frequency) \(f_{0}\) = 300 kHz, signal frequency range \(f_{\rm min}\) = 20 kHz, \(f_{\rm max}\) = 400 kHz, frequency step 40 kHz. Main lobe width (MLW) and \(PSLL\) are adopted as performance indices. The experimental results are shown in Figure 11. The size of array aperture is specified as \((k-1)\cdot\lambda/2\) in the simulation experiments. Otherwise, the grating lobes must appear when the wave frequency increases to a certain extent if using the fixed size of array aperture.  
As shown in Figure 11, the \(PSLL\) values of the two arrays are different in the given frequency range, except for 60 kHz below, while their MLW have consistent values. The \(PSLL\) deviations are always 1.5 dB at the different frequencies. The deviations are caused by the aforementioned overlarge thinned ratio resulting from the spatial undersampling of the array sensor. This illustrates that the trends of \(PSLL\) and MLW of the sparse array after the ADS method are in line with the original Mills Cross array in the given frequency range.