esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Aeroacoustic Model
### Propagation Model
#### 3.2.3 Ground Propagation Noise Model  
ACO-ENV is an ENvironmental ACOustic tool developed by CIRA's department of computational acoustics that allows analyzing the environmental acoustic impact of novel configurations once their acoustic behavior is characterized at source level.  
The code, based on the Quasi-Static Acoustic approach [27; 28], considers an acoustic database (ADB) as input and propagates the acoustic field on the ground through a ray tracing technique. The ADB is made up of far-field acoustic hemispheres, computed by the above-mentioned propagation model, able to reproduce the acoustic source in terms of three-dimensional directivity pattern and covering the whole trimming conditions needed during the flight trajectory. The code also accounts for sound propagation in compliance with UNI-ISO 9613-2:2006, atmospheric absorption according to SAE ARP866B [29], several acoustic metrics (e.g., Sound Exposure Level, L'Amax, and EPNL) and it is also able to compute multiple events analyses.  
The code needs of the following input:  
* Ambient conditions.
* Segmentation of the aircraft flight trajectory in terms of global cartesian coordinates of the center, velocity, and flight path angle.
* Acoustic database of hemispheres covering the trajectory conditions in terms of velocity and flight path angle and reporting the Sound Pressure Level (SPL) in narrow- or third-octave bands.
* A carpet of observation points for the acoustic footprint generation.  
For each flight segment in terms of velocity and flight path, the corresponding source hemisphere is carried out by a bilinear interpolation over the acoustic database. The selected hemisphere is moved to the aircraft center position and a ray is projected to connect each observation point with the hemisphere center. The intersection of the ray with the hemisphere allows selecting the discretized hemisphere panel that includes the intersection point, as shown in Figure 5. The SPL values for each narrow or third-octave band are interpolated from the panel nodes, through an Inverse-distance interpolation algorithm, and propagated according to UNI-ISO 9613-2:2006 and SAE ARP866B.  
The integration over the whole frequency spectrum provides the Overall Sound Pressure Level (OASPL) for each carpet microphone. The process is iterated for each trajectory segment providing, for each microphone, the time history of SPL values and of the (OASPL) in A-weighted scale is used to finally compute the acoustic metrics.  
In this work, the Sound Exposure Level (SEL) and the Single Event Level \((LAeq,T)\) in the period T is finally computed for each microphone as  
\[LAeq,T=SEL-10 log(T/T_{0}) \tag{19}\]  
\[SEL=10 log\left(\sum_{i=1}^{N}dt_{i}*10^{SPLAi/10}\right) \tag{20}\]  
where \(T\) is the event duration time, \(dt_{i}\) is the acoustic observation period of the trajectory segment i, N are the number of observation periods that corresponds to the trajectory segments, and \(T_{0}\) is a reference time of 1 s. A sketch of the method is available in Figure 6.  
Figure 5: ACO-ENV approach for ray tracing Sound Pressure Level propagation.
[18] studied the influence of source characteristics on the site effects in the Valley of Mexico from 36 interplate and inslab Mexican earthquakes and 12 teleseismic events originated in South America. Their results agree with those obtained by [16] and concluded that observed site effects were independent of the characteristics and location of the source. [PERSON] et al. [19] presented the first study of site effects in the TMVB outside the Valley of Mexico, based on local shallow seismicity. They analyzed HVSR curves obtained from 22 earthquakes recorded by 25 seismological stations located in the study zone. The events studied have depths H \(<\) 10 km, and magnitudes between 3.6 and 4.3. Average values for the fundamental frequency \(f_{0}\) and amplification factors obtained from the HVSR curves were reported. Their results were compared with previous studies and they attributed the differences found to the location of the source. However, due to the limited amount of data employed, some of their conclusions were supported only with one or two records. Furthermore, it should be considered that HVSR curves do not unequivocally represent the actual site amplification. Considering the low density of permanent seismological stations in the TMVB [20], the number of records that can be analyzed with the SSR technique is very limited. So, the use of ambient noise records represents a feasible option to include additional data for the analysis of site response in terms of \(f_{0}\). In this paper, we analyze HVSR curves obtained from ambient noise and regional instrumental records related to 121 crustal and inslab events with an epicenter inside the TMVB. Data considered were recorded by 90 seismological stations belonging to seven seismic networks. The results of our study may be useful in disaster prevention and in estimating the behavior of future buildings in the study area. The information presented may also be used to complement studies examining the damage observed to existing infrastructure after the occurrence of a seismic event [21; 22]. However, it is important to consider that a more accurate and reliable analysis can be carried out throughout microzonation studies, so our results only give a general overview.
###### Abstract  
Microalgae are unicellular and photosynthetic microorganisms which grow thanks to inorganic salts, CO\({}_{2}\) and light, and find applications in several fields thanks to their variety. The industrial application of microalgae has not often been fully exploited because of a lack of information about how microalgae respond to inputs and to different growth environments. In the present work a model able to predict the microalgae growth in reactors with different geometries was developed. We combined a Monod-like model for the specific growth rate with the Lambert-Beer law of homogeneous light distribution in thick photobioreactors. Kinetic parameters related to the cultivation of the microcalga _Nanochloropsis gaditana_ were obtained, for the first time through batch cultivation under different photon flux densities inside a quasi-isocentric photobioreactor, in order to obtain a practically homogeneous light distribution. The maximum specific growth rate and saturation constant resulted, respectively as \(\mu_{max}=0.0256\) h\({}^{-1}\) and \(l_{\rm{R}}=15.28\)\(\mu\)E s\({}^{-1}\)m\({}^{-2}\). These parameters were applied to the model to obtain data on microalgae growth in different geometries. Model simulation results are presented and discussed. Furthermore, biochemical analysis was performed on the biomass obtained at the end of each batch cultivation, grown both under different light intensities and in reactors with different configurations. Results indicated that lipid content increases with increasing average photon flux density. The fatty acid and carotenoids profiles markedly shift when the average light intensity varies: the PUFA content decreases and the SFA content increases when the average light intensity rises, and an accumulation of carotenoids at lower photon flux densities is observed. In conclusion, the model resulted in a useful tool, able to predict the growth of the microcalga _Nanochloropsis gaditana_ in reactors with different configurations.  
Naturechioropsis gaditana; photobioreactor modelling; growth model; lipids; kinetic parameters +
Footnote †: journal: Applied Sciences
# Robot Delay-Tolerant Sensor Network for Overhead Transmission Line Monitoring
###### Abstract  
The rapid development of the smart grid has led to higher maintenance cost and greater scalability of transmission lines. An effective and secure monitoring system for power lines has become a bottleneck restricting the intellectualization of power grids. To address this problem, a novel method is proposed for the intelligent monitoring of power grids (Robot Delay-Tolerant Sensor Network, RDTSN) based on an inspection robot, Wireless Sensor Network (WSN) and Delay-Tolerant Sensor Network (DTSN) to achieve low-cost, energy-efficient, elastic and remote monitoring of power grids. With RDTSN, a smart grid can detect the fault of transmission lines and evaluate the operational state of power grids. To build an effective monitoring system for a smart grid, this research focuses on designing a methodology that achieves efficient and secure delivery of the data inspected on transmission lines. Multiple RDTSN scenarios are performed, in which different routing algorithms are explored to determine the optimal parameters, with a balance in network performance and financial cost. Furthermore, a data delivery strategy is introduced to ensure communication security.  
delay-tolerant; disruption-tolerant; WSN; inspection robot; opportunistic forwarding; transmission line monitoring; smart grid +
Footnote †: journal: Applied Sciences
# Research on Wellbore Trajectory Prediction Based on a Pi-GRU Model
## 3 Experiments and Analysis
### Additional Applications  
To further evaluate the generalization of the model, this study conducted cross-scenario validation based on the actual drilling data of one main shaft and two branch shafts in the Dehong Coal Mine. The test data cover the trajectories of three main and branch boreholes. Among them, the section from 114 m to 550 m is the training set (including complex formation crossing and conventional correction operations), and the target section from 550 m to 630 m is the independent test set (simulating the unknown geological conditions of the new mining area). As shown in Figures 16 and 17, the model has a good ballistic prediction ability in the test section: the MSE for azimuth prediction is 0.13\({}^{\circ}\) (R\({}^{2}\) = 0.86), and the MSE for tilt prediction is 0.13\({}^{\circ}\) (R\({}^{2}\) = 0.95). The coefficient of determination between the dip angle prediction curve and the measured value is greater than 0.95, and the measurement accuracy reaches the sub-degree level (<0.5\({}^{\circ}\), with an error ratio of 82%). The experimental results show that the Pi-GRU model can still maintain sub-degree measurement accuracy and stable generalization performance in the trajectory prediction task under unknown geological conditions, verifying its practical engineering value.  
Figure 15: Ablation experiment.
# A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots
## 2 Motivating Scenario: Autonomous Factory Service Robot  
Our proposed emitter-based localisation and navigation approach can be applied to many real-world applications such as indoor delivery and industrial automation. In this research, we target a factory automation application as our motivating scenario. The main feature of this application is the requirement to navigate within a dynamically changing environment with minimal infrastructure deployment due to physical and/or financial reasons. Figure 1 shows a typical factory setting where items such as raw materials and final products need to be fetched from or delivered to different locations in a dynamic setting, depending on production schedules and logistics flow. In the vision of Industry 4.0 and the Industrial Internet of Things (IIoT), it is critical to be able to track the source materials and final products through technologies such as active RFID. In this context, it is not uncommon to assume that an RF emitter could be attached to a target object. Robots will need to have the ability to map and manoeuvre in a complex environment with multiple mobile and non-mobile obstacles. However, typically in a warehouse or production facility, the environment is structured in such a way that robots only need to travel in straight lines with 90\({}^{\circ}\) turns. It is also likely that there may be dead-ends in the environment, such as when rows of shelves are positioned against a wall. This means that there are cases where a robot could be in close physical proximity to a target object, but due to the presence of shelves or other obstacles, the robot cannot take a straight-line path and must move between different corridors or lanes in order to reach the target. This is beyond the ability of basic motion planning and manoeuvring, requiring long-term path planning. These requirements will be used to guide the design of our navigation system as well as the set of tests and experiments that are conducted for evaluating the system performance in Section 7.
## 2 Materials and Methods
### Industrial Trial
#### 2.2.2 Experimental Design and Sampling  
The particle size of the plastic materials used in the industrial trials was less than 10 mm, which is much larger than the coal particle size, which was smaller than 38 \(\upmu\)m. Thus, the plastic materials were introduced to the furnace through a different injection system than coal. Two sets of trials were performed, one with only coal injection as reference, and one set of trials with co-injection of coal and each plastic material. The main difference during the trials with injection of plastic material was that the coal injection rate was reduced and the plastic material was substituted for it. The initial idea of the industrial trial was to reduce the amount of injected coal and substitute it with plastic material, in such a way that the total amount of carbon entering the process remained the same. However, the amount of plastic material injected was dictated by the injection system due to technical difficulties. The trials included 11 batches with only coal injection, two trials with the co-injection of coal and PE, four trials with coal and PUR, and six trials with coal and SRM. Table 2 summarizes the conditions during the trial; a more detailed description of the trial has been published elsewhere [21].  
The most important data from these batches were the changes in zinc concentration in the slag compositions. A slag sample was taken from the start of the batch with an interval of 10 min until tapping. Sample collection was conducted by inserting a steel rod through a tuyere on the opposite side of the plastic-injection zone. A chemical analysis of the slag samples was performed by the Central Laboratory of the Boliden Ronnskar smelter using X-ray emission spectroscopy. Furthermore, the steam generation and heat lost through water cooling panel were measured.
###### Abstract  
Fog is a meteorological/environmental phenomenon which happens across the Indo-Gangetic Plains (IGP) and leads to significant social and economic problems, especially posing significant threats to public health and causing disruptions in air and road traffic. Meteorological stations in Pakistan provide limited information regarding fog episodes as these provide only point observations. Continuous monitoring, as well as a spatially coherent picture of fog distribution, is possible through the use of satellite observations. This study focuses on the 2012-2015 winter fog episodes over the Pakistan region using the Moderate Resolution Image Spectrometer (MODIS), the Ozone Monitoring Instrument and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) products. The main objective of the study was to map the spatial distribution of aerosols, their types, and to identify the aerosol origins during special weather conditions like fog in Pakistan. The study also included ground monitoring of particulate matter (PM) concentrations, which were conducted during the 2014-2015 winter period only. Overall, this study is part of a multi-country project supported by the International Centre for Integrated Mountain Development (ICIMOD), started in 2014-2015 winter period, whereby scientists from Bangladesh, India and Nepal have also conducted measurements at their respective sites. A significant correlation between MODIS (AOD) and AERONET Station (AOD) data from Lahore was identified. Mass concentration of PM\({}_{10}\) at all sampling sites within Lahore city exceeded the National Environmental Quality Standards (NEQS) levels on most of the occasions. Smoke and absorbing aerosol were found to be major constituents of winter fog in Pakistan. Furthermore, an extended span of winter fog was also observed in Lahore city during the winter of 2014-2015. The Vertical Feature Mask (VFM) provided by CALIPSO satellite confirmed the low-lying aerosol layers, instead of clouds for the vertical profiles of selected case studies.  
AOD; MODIS; AERONET; HYSPLIT; IGP; Pakistan +
Footnote †: journal:  
Academic Editors: [PERSON] and [PERSON]  
Received: 29 February 2016; Accepted: 22 April 2016; Published: 16 May 2016
## 1 Introduction  
Wireless sensor networks (WSNs) are small inexpensive devices with finite energy, limited sensing/processing capability, small memory and transmission capacity [1, 2]. They may perform self-organization in ad hoc mode [1, 2, 3] and have the ability to work autonomously. It makes them front line ally with human beings for executing various critical tasks such as elderly people health-care [4, 5], structural examination [6, 7], habitat monitoring [8] and near-shore environmental inspection [9]. WSNs have an indispensable role in metropolitan planning and development such as traffic handling [10; 11; 12; 13], tunnel monitoring [14], parking lot management [15; 16], water pipeline monitoring [17], water consumption examining [18], solid waste management [19], gas pipeline monitoring [20] and power grids applications [21]. In addition to that, they have a key role in security and help in intrusion detection [22], surveillance [23] and reconnaissance activities [24]. Besides that, their role in catastrophes administration is admirable such as tsunami detection and countermeasure [25], building fire monitoring [26] and disaster management [27]. The acronyms used in this survey are defined in Table 1.  
Due to unique nature of WSNs, the related techniques devised for the other wireless networks were discovered unsuitable for WSNs. Eventually, new methodologies and approaches were researched and developed for WSNs keeping in view their underlying constraints, so that they may perform the assigned duties in an appropriate manner. At the inception of WSNs related research, the primary focus was energy efficiency [1; 28] while throughput, delay and fairness were given secondary importance [1; 28; 29]. Such sensor networks were mainly employed for environmental monitoring in terms of temperature, pressure and humidity, etc. As technology flourished, the capabilities of sensor networks were further enhanced and they became able to support high data rate applications e.g., structural health monitoring requires sensor nodes to send more than 500 samples/s for recognizing any structural distortion [30]. It has also motivated the researchers to devise Wireless Multimedia Sensor Networks (WMSNs) oriented applications that may sense the delay and loss-sensitive multimedia data and relay it with high data rate to sink node using one or more routing path(s). Furthermore thanks to Wireless Power Transfer (WPT) technology that has handled the longstanding energy depletion issue in WSNs and gave birth to Wireless Rechargeable Sensor Networks (WRSNs). Such WRSNs has the ability to harvest energy and to operate in a long-lasting manner [31; 32; 33; 34].
# Numerical Simulation and Optimization of the Airflow Field of a Forage Drum Mower
## 3 Material and Method
### Numerical Simulation
#### 3.1.2 Simulation Parameters  
The relevant simulation parameters include geometric parameters, meshing parameters, physical models, and solving parameters. As for the geometric model, the disc diameter was set to 223 mm. The conical drum was set to have a top diameter of 110 mm, a bottom diameter of 157 mm, and a height of 157 mm. As a convex rib with an isosceles triangle cross-section, the guide plate was mounted on the surface of the conical drum, with a width of 23 mm and a height of 14 mm. The blade was 60 mm long, 26 mm wide, and 4 mm thick, with 45\({}^{\circ}\) cutting edge on both sides. In accordance with the requirementsof subsequent orthogonal experiments, the blade twist angle \(\alpha\), disc tilt angle \(\beta\), and the number of guide plates were set, respectively. In addition to the solid domain of the cutter, it is also necessary to establish the geometric model of the fluid domain. The fluid domain model was constructed as a cuboid with a length of 800 mm, a width of 800 mm, and a height of 400 mm. The solid domain of the double-drum cutter was positioned in the middle of this cuboid region, with the distance between the tip of the blade and the bottom surface (used to simulate the ground) of the fluid domain cuboid set to 50 mm.  
For the meshing, the mesh type was chosen to be Tera/Mixed, and the Robust (Octree) method was adopted to create the tetrahedral mesh. The Scale factor of 1 and the Max element of 3 were defined to control the size of the global mesh when the solid domain mesh was created, i.e., the maximum size of mesh in the solid domain was set to 3 mm. The Scale factor of 1 and the Max element of 15 were defined to control the size of the global mesh when the fluid domain mesh was created, i.e., the maximum size of mesh in the fluid domain was set to 15 mm.  
For physical models and solving settings, the type of fluid was chosen to be air at 25 \({}^{\circ}\)C, and the k-epsilon turbulence model was treated as the computational solving model. The boundary condition for the bottom surface of the cuboid fluid domain was set to rough WALL with sand grain roughness of 20 mm for simulation of the ground, while the other five surfaces were set to OPENING for simulation of the free-flow air around the cutter. The solid domain was chosen to be immersed solid, the rotating motion was selected, and the parameters of the rotating speed were set according to the orthogonal test. The transient simulation was taken as the analysis type of solving, and the output variables include air-flow velocity and velocity components in each direction. The total simulation time was set to 2 s, and the simulation step size was set to 0.05 s when the cutter speed was 1500 r/min. To maintain the blades in the same position at the moment of 2 s at different disc speeds, the simulation step was adjusted accordingly when the rotating speed of the disc changed.
# Unexpected-Behavior Detection Using TopK Rankings for Cybersecurity
## 2 Intrusion Detection Systems
### Stateful Protocol Analysis  
Stateful protocol analysis or deep packet inspection is the process of comparing predefined accepted protocol activity against the observed events to identify deviations. Unlike anomaly-based detection, which uses network profiles, stateful protocol analysis relies on vendor specifications of how the protocol should and should not be used [7]. In Figure 4 we can observe a generic diagram of this type of detection methodology.  
Usually, the vendor specifications include: rules for individual commands, sequence of commands, minimum and maximum lengths for arguments, argument data types, etc.  
This methodology produces a low false-positive rate similar to signature-based detection because it is based on legitimate behaviors. In addition, it is able to detect unexpected behaviors [10]. The big  
Figure 4: Diagram of a generic stateful-protocol IDS.  
Figure 3: Diagram of a generic anomaly-based IDS.  
challenge of this methodology is to design secure protocol specifications strong enough to detect illegitimate behaviors.