esa-sceva/satcom-chunk-collection huggingface dataset:
# Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection
## 4 Robust Estimation via the Genetic Algorithm
### Genetic Operators
In Equation (10), \(\mathbf{\tau}_{i}=(\tau_{i_{1}},\tau_{i_{2}}):=\dfrac{\mathbf{x}_{i}^{o}-1}{\xi-1}\), \(\mathbf{u}=(u_{1},u_{2})\) includes two random uniformly-distributed numbers between zero and one; \(\mathbf{s}=(s_{1},s_{2}):=\pi\circ\pi\) follows a power distribution with \(\pi\) having random values between zero and one. At any iteration, a random exploration is also performed by generating a fixed number of individuals based on the proposed guided sampling strategy in Section 4.2. Generating random solutions as a fixed portion of the population reduces the chance of converging to local optima. The replacement strategy applied in this study can be considered as a combination of steady-state and elitist replacement methods. It helps to keep the best solutions from older generations and to maintain the population diversity to avoid premature convergence. Assume that \(\mathbf{P}^{-}\) is the population of the last generation, \(\mathbf{P}^{+}\) is the population of the selected parents from \(\mathbf{P}^{-}\) and \(\mathbf{P}^{++}\) is the population of the reproduced offspring using \(\mathbf{P}^{+}\). Accordingly, \(q^{-}\) demonstrates the least fitness value among the best third quartile of individuals in \(\mathbf{P}^{-}\). Therefore, the new population \(\mathbf{P}\) starts forming by the fittest individuals of \(\mathbf{P}^{-}\) (elites). Among the elite individuals with similar fitness, those who are formed by correspondences coming from more distinct regions of the overlapping rectangle have priority in replacement. This way, the chance of ending with the local optima is highly reduced. In fact, this factor is used to distinguish models with similar fitness values. The rest of the spots available at \(\mathbf{P}\) are occupied by the following replacement condition:  
\[\mathbf{P}_{i}= \begin{cases}\mathbf{P}_{i}^{++}&\text{if fitness}(\mathbf{P}_{i}^{++})>q^{ -}\\ \mathbf{P}_{i}^{+}&\text{if fitness}(\mathbf{P}_{i}^{++})<q^{-}\end{cases} , \tag{11}\]  
where \(\mathbf{P}_{i}\) means the \(i\)-th individual in the population, \(i=\{1,\ldots,\text{population size}\}\). Equation (11) implies that an offspring whose quality is worse than 75% of the previous solutions is not qualified enough to replace its parents. The genetic algorithm iterates the procedures mentioned above until there is no improvement in the average of the elites' fitness values during a specified number of generations.
# Mental Workload Classification Method Based on EEG Independent Component Features
## 5 Conclusions  
In this study, we propose a mental workload classification method based on EEG IC features for vision and operation tasks. This method, named Method 1, contains four steps: filtering the measured EEG signals; using ICA to obtain EEG ICs; extracting their energy features; and classifying them. The energy features of EEG ICs are implemented to overcome the problem of low accuracy. The proposed method can realize fast, accurate, and automatic mental workload classification. Based on the comparison results of four classification methods, some conclusions can be drawn as follows:  
* Compared with Method 2 based on EEG signal features, the classification accuracy of our presented method is improved from 55.9% to 79.8%. The classification accuracies of Method 3 and Method 4 are compared, and their average difference is 22.2%. Therefore, the classification method based on EEG ICs features proposed in this paper is superior to the classification method based on EEG signal features.
* The different numbers of ICs are adopted to extract the energy features and classify the mental workloads. The results reveal that the classification accuracy can be improved with the increase of the numbers of ICs.  
Conceptualization: H.Q.; methodology: Y.S.; software: Y.L.; validation: Y.L., Y.S., and H.Q.; formal analysis: H.Q.; investigation: Z.F.; resources: L.P. and J.Z.; data curation: Y.S.; writing--original draft preparation: Y.S.; writing--review and editing: Y.S. and L.P.; visualization: Y.L.; supervision: X.W.; project administration: H.Q.; funding acquisition: L.P. All authors have read and agreed to the published version of the manuscript.  
The research is supported by Liao Ning Revitalization Talents Program (XLYC1802092), and the jointly program of National Natural Science Foundation of China and Civil Aviation Administration of China (No.U1733118).  
The authors are grateful to the anonymous reviewers for their critical and constructive review of the manuscript. Their comments helped to increase the quality and readability of the manuscript. We also want to thank the subjects for their contributions to the experiment and would like to thank [PERSON] and [PERSON] for conducting the experiments in the laboratory.  
The authors declare no conflicts of interest.
## 2 Materials and Methods
### Numerical Simulation Setup  
#### 2.2.1 Designing CAD Files  
Based on the international standard ASTM F2033-12 [43] of hip implant design, a hip implant was designed using SpaceClaim, ANSYS software version 2020 R2. The traditional standard hip implant comprises three parts: the head, the neck, and the stem. The dimensions of the implant are defined when the head diameter, the neck's length and diameter, and the length of the intramedullary implant (the stem) are all known [16]. In this study, as shown in Figure 3, the stem was divided into two bodies: the middle stem and the lower stem. This was so we could apply a lattice structure to the middle stem to optimize the design and enhance the bone ingrowth into the holes of the latticed part, thus increasing the fixture of the implant and prolonging the life span of the implant without loosening.  
Figure 4 also shows the setup for the compression test following the hip implant testing standard ISO 7206-4:2010 [43], where the compression template compressed the implant and a resin base played the role of the fixed support in the numerical simulation.  
Table 4 shows a list of properties of all parts contributing to the numerical simulation of the material.
# A Jamming-Resilient and Scalable Broadcasting Algorithm for Multiple Access Channel Networks
## 7 Evaluation
In addition, when no jamming occurs, the QB and the KTFW algorithms exhibit almost identical performance in terms of average packet latency. In contrast, the QB algorithm has a slightly lower average packet latency for larger networks in certain traffic scenarios (e.g., the RIM). Nevertheless, the KTFW algorithm performs better than the QB algorithm when considering networks with jamming attacks. Figure 12: Comparing the average packet latency for the BEB and KTFW algorithms for all jamming rates and \(n\in[10,50,100]\).
# A Random Forest-Based Precipitation Detection Algorithm for FY-3C/3D MWTS2 over Oceanic Regions
## 1 Introduction
proposed an RF-based downscaling-calibration method that outperformed classical approaches like geographically weighted regression and artificial neural networks in generating high-resolution precipitation datasets [13]. [PERSON] et al. further validated RF's superiority over traditional statistical fusion methods through multi-source satellite precipitation integration in South Korea [14]. [PERSON] et al. [15] applied the random forest algorithm to precipitation prediction, which improved the accuracy of the precipitation rate determined by optical satellite sensors. To enable more accurate and efficient precipitation detection for MWTS2 and provide a novel precipitation detection approach for future MWTS2 data assimilation, this paper proposes a new precipitation detection method (denoted as _RF_SI_) by using fused FY-2F VISSR and NOAA-19 AMSU-A data as a training dataset in combination with the random forest model employed in machine learning approaches. Compared with conventional imager-matched MWTS2 precipitation algorithms, the _RF_SI_ method, which uses more cloud parameters (the relative humidity, cloud classification, cloud-top temperature, and water vapor values in the middle and upper levels of the troposphere), can accurately simulate the nonlinear relationships between cloud parameters and microwave precipitation signals with a higher spatiotemporal resolution. _RF_SI_ information can be matched with MWTS2 pixels to assist MWTS2 in performing precipitation detection. This paper focuses on the precipitation detection principle of _RF_SI_ and evaluates its precipitation detection effect. In the future work, we plan to implement the _RF_SI_ method in MWTS2 data assimilation systems to further validate and operationalize this approach. The remainder of this paper is organized as follows. Section 2 introduces the satellite data, the GEO-LEO satellite pixel fusion algorithm, and the multispectral microwave precipitation identification method developed based on the random forest approach. The preprocessing method applied to the given machine learning datasets and the model training process are described in Section 3. Section 4 presents the experimental and analysis results obtained for a single case and a long-term series case by using the FY-2F satellite cloud products. Finally, a summary and a conclusion are given in Section 5.
## 3 Results and Discussion
### Impact of Ageing Time  
The aging process enhances the kinetics of zeolite nucleation and crystal growth (via increasing the dissolution of aluminosilicate species). According to Table S7, the synthesized membrane without ageing showed high N\({}_{2}\) permeance. According to Figure 2g, as the aging time increased from 2 to 24 h, the ideal CO\({}_{2}\)/CH\({}_{4}\), CO\({}_{2}\)/N\({}_{2}\) and H\({}_{2}\)/SF\({}_{6}\) permselectivity also improved from 15 to 110, 11 to 14, and 20 to 56, individually. Nevertheless, maximum CO\({}_{2}\) and minimum SF\({}_{6}\) permeances were correlated to the samples aged 16 and 8 h (\(\sim\)2.97 \(\times\) 10\({}^{-6}\) [mol/(m\({}^{2}\)sPa)] for CO\({}_{2}\) and \(\sim\)8.06 \(\times\) 10\({}^{-9}\) [mol/(m\({}^{2}\)sPa)] for SF\({}_{6}\), separately). The obtained results display that with the increase of ageing time, because of higher nucleation rate as well as shorter induction and crystallization period, the number of crystals on the surface of the support increased, while their size decreased. Moreover, the formation rate of aluminosilicate hydrogel is enhanced by the ageing process and hence, it is probable that by increasing the ageing time from 8 and 16 to 24 h, a denser membrane layer was formed, and this led to a decrease in CO\({}_{2}\) permeance.
# Analyzing Port State Control Data to Explore Future Improvements to GMDSS Training
## 4 Discussion
### Radio Deficiencies Linked to a Lack of Competencies in Maritime Communications of OOWs
The common deficiencies in the category \"training\" have to do with a lack of knowledge and familiarity with the operation of communications equipment and procedures, especially distress, false distress alert procedures, lack of maintenance routines, and not having correctly carried out radio-electronic watchkeeping tasks, especially when negligence is shown in not warning about distress messages at radio logs. When examining the time evolution of radio deficiency codes (Figure 4), the radio log (5115) leads the ranking practically from the beginning of the record, which is represented by the red bars in Figure 4b. Figure 3: Time series showing the time variability in the 18 years of records of the year-over-year of the 3 types of deficiencies once re-coded as “equipment”, “training”, and “others” (Table 5). On the left (**a**), the time evolution of the frequency distribution of the 3 categories is shown. On the left (**b**) is the same, but comparing the relative distribution (percentages). In article [58], a survey of 112 OOWs presents the perceptions of these professionals regarding future trends in radio logs. It is worth noting that 56% of the deck officers are in favor of automating the recording and storage of the radio log. However, it should be noted that out of the 32 respondents who provided additional commentary and expressed their personal opinions on this specific topic, 13 were against the automatic filling of the radio log. It is important to keep in mind that the radio log must contain a record of both sea and radio incidents that are relevant to the radio communications service during watchkeeping. Some incidents may not be automatically registered, such as (i) breakdowns or malfunctions of GMDSS equipment; (ii) communication interruptions with coast stations, earth stations, or satellites; (iii) poor propagation and atmospheric interference causing message reception issues; (iv) significant violations of radio procedures by other ship stations; (v) any occurrence related to radio service, such as false distress alerts; and (vi) distress, urgency, and safety voice traffic. The shortcomings of radio logs may appear to be of minor importance, but they raise the question of whether implementing new technologies alone would be sufficient to address these deficiencies.
# Reduction Potential of Gaseous Emissions in European Ports Using Cold Ironing
## 3 Cold Ironing Concept  
The cold ironing concept is a consolidated concept based on electricity supply onboard ships through a connection to a main fixed electrical grid instead of the use of the ship's generators [7]. Nonetheless, the technological solutions are various and suffer from poor standardization [8]. The power supply is provided through a high-voltage line and a main substation to reduce the voltage. Afterward, the current is distributed via underground cables to various quays, where a further conversion into the voltage and frequency required for the specific ship is normally necessary. The frequency conversion is an important aspect because the majority of ships' grids use 60 Hz frequency, while the fixed electricity network normally provides 50 Hz standard frequency.  
The last step of the process is the connection, through the cables, of the dock's station with sockets placed onboard. Furthermore, depending on the onboard voltage, an additional transformer inside the ship may be required for the end use of electricity. Normally, during navigation, the main engine, supported by the auxiliary ones, generate the power for the motion and all other services of the ship. However, in ports, the main engine is switched off, and the energy need is normally satisfied by the auxiliary engines alone. Nevertheless, some big and modern cruise ships use diesel-electric propulsion during navigation and are not equipped with auxiliary engines.  
Therefore, cold ironing allows engines to be turned off in ports and emissions to be drastically reduced because internal combustion engines are not working during berthing, and the emission of CO\({}_{2}\) in the atmosphere is prevented, as are local emissions of pollutant matter, noise, and vibrations.  
The phases of the processes are the following:  
1. The ship enters a port and docks at a berth or pier,
2. The port provides an electrical connection point,
3. The electrical system of the ship is connected to the electrical connection point using a cable and a plug,
4. The electrical system of the ship is powered by the onshore electrical connection point,
5. The engines and the generators of the ship are switched off, and the zero-emission phase starts,
6. The electrical system of the ship powers all necessary onboard systems during the time spent at berth,
7. The ship is declared ready to depart,
8. The main engines and the auxiliary generators of the ship are switched on, and the zero-emission phase ends,
9. The onshore electrical connection is interrupted.
## 3 System Model and Description
### Network Configuration and Data Transmission
#### 3.4.1 SPF-Three  
SPF-Three forwards the data packets after ensuring the information of next 3-hop neighbors from the current node to avoid the void regions. The shortest path is obtained from the proposed protocol based on 'Dijkstra' algorithm. It selects the best route for the underwater communication. Algorithm 1 demonstrates the selection and transmission of SPF-Three.
# Blockchain Secured Dynamic Machine Learning Pipeline for Manufacturing
## 4 Security Challenge of ML Models and ML Pipelines
### Attacks against Confidentiality  
Attacks against confidentiality may happen on sensitive data and model information while honestly executing ML training and inference without altering the computation outcomes. Because the data and models are accessible by several stakeholders, these attack vectors often occur in the pipeline phases of model training, model deployment or inference, or model upgrades [37].  
In federated ML, the host that orchestrates all clients' local training may access their updated models and use these models to infer private information about their local data [38]. Among the most common attacks are: data reconstruction attacks [39], which aim to reconstruct original input data based on the observed model or its gradients; attribute inference attacks [40], which aim to infer the value of users' private properties in the training data, and membership inference attacks [41], which aim to learn whether specific data instances are present in the training dataset.
# Remote Image Capture System to Improve Aerial Supervision for Precision Irrigation in Agriculture
## 3 Results and Discussion
### Experiments on the Data Transmission Speed  
In order to achieve a reliable wireless link with the minimum data loss, the remote and local nodes have been tested by transferring images at different speeds. Therefore, XBee and A20/A6C modules were configured with the available transfer rates (in bit per second, bps), and tested with the goal of obtaining the fastest communication speed without data loss. As an example, Figure 10 shows some of the in-lab images received in these tests. In this case, the files transmitted are VGA images of 640 \(\times\) 480 pixels.  
Figure 9: Global view of a remote capture node in the field. (**a**) Location of the node on a crop of lettuce. (**b**) Sample image captured by the system.  
In general, it was observed that higher speed rates produce more errors in the transmission, being unacceptable for values above 38,400 bps. A bandwidth of 28,800 bps was acceptable in some cases, but produced errors in other tests, as in Figure 10c. The maximum speed allowed for a robust transmission was 19,200 bps. In consequence, as the result of this experiment, the remote and local nodes are set to 19,200 bps to ensure a high reliability in error-free data transmission at the target distances between local and remote nodes. For this speed, the estimated time to transmit an image between 35 and 50 Kbytes (which is the typical size at VGA resolution) is 15-22 s; hence, the system can capture a maximum of 163 images per hour.
# Application of Thermal Image Data to Detect Rebar Corrosion in Concrete Structures
## 2 Research Methodology  
### Theoretical Considerations  
#### 2.1.1 Rebar Corrosion Mechanism  
When chlorides infiltrate a reinforced concrete structure, a potential difference occurs because the chlorides do not enter all the parts of the rebar in a uniform manner [7; 20; 28]. The potential difference causes the electrons to flow in the rebar and, simultaneously, electrochemical reactions on the rebar surface [29]. Electron creation and consumption occur at the positive and negative poles, respectively. When the corrosion reaction occurs, the negative charges created at the positive pole maintain electrical neutrality by moving through the electrolyte and the positive charges move toward the negative pole. Thus, an electrical circuit is formed. This electrochemical reaction occurs continuously and destroys the rebar's passive film, which promotes corrosion. The corrosion pressure that occurs at this point reaches 4700 psi, and hence, the concrete structure gets damaged [30].  
When moisture and oxygen infiltrate into a reinforced concrete structure, the ferric hydroxide goes through the process represented by Figure 1 and changes into black rust. The resultant changes in volume are shown in Figure 1. The corrosion products that create rust are oxides or hydroxides, and their volume is significantly larger as compared to the volume of the original steel. Calculations have been performed to determine the multiplication factor of the volumetric expansion that occurs when steel changes to oxides or hydroxides. This is done because the specific gravity of steel (7.86) changes to the specific gravity of the oxides or hydroxides. Calculations show that there is a volume expansion factor of 2 when steel changes into oxides and 3 when steel changes into hydroxides.  
The pressure that increases as the corrosion progresses can cause cracks and delamination in the concrete. These cracks readily supply more oxygen and further promote the corrosion process, leading to a continuous cycle of corrosion.
## 2 Materials and Methods
### Analytical Methods and Calculations  
The determination of oxygen \(\mathrm{K}_{\mathrm{L}}\alpha\): Dissolved oxygen depends on the power of the diaphragm pump and the amount of filling material used. The diaphragm pump (QBY6-15 SSF, KAIZON, Shanghai, China) sprays the fermentation broth through a spray nozzle into the gas-liquid exchanger. The rate of oxygen transfer depends on the volume mass transfer coefficient \(\mathrm{K}_{\mathrm{L}}\alpha\) and the driving force [44]. The filler material increases the surface area of the gas-liquid mixture, which increases the amount of dissolved oxygen. Under ambient conditions (open to air), a dynamic method is used to measure the oxygen \(\mathrm{K}_{\mathrm{L}}\alpha\) of a bioreactor [44]. \(\mathrm{K}_{\mathrm{L}}\alpha\) is calculated as follows (Equation (8)):  
\[\mathrm{Ln}\left(\frac{\mathrm{C}_{\mathrm{L}0}-\mathrm{C}_{\mathrm{L}}}{ \mathrm{C}_{\mathrm{L}0}-\mathrm{C}_{\mathrm{S}}}\right)=-\mathrm{k}_{\mathrm{L }}\alpha(\mathrm{t}-\mathrm{ts}) \tag{8}\]  
where \(\mathrm{C}_{\mathrm{L}0}\) is the solubility of oxygen in the gas mixture; \(\mathrm{C}_{\mathrm{S}}\) is the instantaneous oxygen concentration dissolved in the fermentation broth at time t; \(\mathrm{C}_{\mathrm{L}}\) is the initial oxygen concentration at the time of recording the measurement; t is the start time; and ts is the time at which the gas flow restarts to any subsequent time. The probe's response time is a crucial parameter of the dynamic method. It is defined as the time it takes for the probe to reach 63.2% of the final value recorded when the dissolved oxygen concentration changes step by step [45].  
A Full 2D GCMS (QP2010 PLUS, Shimadzu, Kyoto, Japan) can determine the composition of a gas mixture. The method of determination used refers to Yu [30] and requires a 1D Column DB-WAX (36.4 m \(\times\) 0.25 mm, 0.25 m) and 2D Column DB-17 MS (1.3 m \(\times\) 0.18 mm, 0.18 m). The Full 2D GCMS gas phase adopts a solid-state thermal modulator and HV modulation column (1.2 m \(\times\) 0.25 mm); the modulation time is 4 s and the resolution time is 1 s. The Kang [32] method was calibrated using a gas standard.  
The optical density of the culture sample at OD\({}_{620}\) was determined [46]. The mineral medium was used as a blank reading, and the sample could be diluted if necessary, so that the absorbance coefficient was between 0.2 and 0.8. The instrument used is the full-wavelength microplate analyzer (HBS-ScanX, Detie, Shanghai, China). The dry mass of the cells is determined by the volumetric method, drying the biomass at 105 \({}^{\circ}\)C as previously described [47]. The fermentation broth supernatant was appropriately diluted, 10 \(\mu\)L was used to coat a heterotrophic medium with 2% agar, and, after 48 h of incubation, the number of colonies on the culture was recorded. The data used were sampled three times, averaged, and error bars were made.