esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
As cities are getting smarter, and as the spread of intelligent surveillance technologies is gaining popularity within developed countries, making urban transport secure and efficient plays a key role in the safety of individuals as well as in affecting traffic flow, which, in turn, may negatively impact businesses within a city [1].  
Unlike video cameras, the operation of short-range microwave radars is not much affected by the presence of adverse weather conditions. This fact makes them ideal, in addition to classical closed-circuit television (CCTV) systems [2], for operating round-the-clock automatic surveillance in an urban environment. Radars [3; 4; 5] can be used for vehicle and pedestrian classification by relying on feature extraction from the range and Doppler profiles of each target. The data collected by radar measurements can be used as input to machine learning (ML) algorithms for classification. However, the hardware should be low cost and lightweight while providing good performance. Therefore, for this application, we have chosen a Raspberry Pi [6; 7; 8], a small portable edge computing device, which is a very effective platform for real-world scenarios as well as for educational and research purposes. Raspberry Pi is ideal for edge computing applications, where the node or embedded device possesses high processing capabilities and is required to have enough storage space to avoid cloud access. With the large number of wireless sensor nodes that are used over a wide range of applications, from wearable sensors to image processing and surveillance, along with the integration of artificial intelligence and machine learning in their decision making, they are required to be as smart as possible to avoid cloud access and reduce network traffic. Urban classification may not have cloud access and requires low latency, so it is the ideal example where both training and testing need to be applied on an edge computing node.  
The main goal of the present work is the porting of the state-of-the-art machine learning package Rulex [9] onto the Raspberry Pi computational platform. The dependencies were compiled to produce output binary files that are compatible with the target platforms, the first being the Windows 32 Bit client and the second being the Raspberry Pi server, which is where the Rulex engine runs.  
The remainder of this paper is organized as follows: Section 2 presents a review on pedestrian-vehicle classification, Section 3 introduces the porting of Rulex on the Raspberry Pi, and Section 4 describes the adopted machine learning architecture. Further, forecast results obtained with the present implementation are presented in Section 5. Finally, we draw some conclusions in Section 6.
## 2 Methods
### Scattering Problem and Helmholtz Equation
To avoid these reflections, proper conditions must be imposed on it, to enable the absorption of such spurious waves. A state-of-the-art approach is the so-called, \"perfectly matched layer\" (PML), originally proposed in [13]. In the PML method, an extra layer of thickness, \(\delta\), is added to the solution domain \(B\): In this extra layer, the wave is damped according to the following law:  
\[\exp\left[j(\omega t-kr)-\frac{k}{\omega}\int_{o}^{\delta}\sigma(\mathbf{r}^{ \prime})dr\right], \tag{8}\]  
where \(\sigma(\cdot)\) is a positive function of the distance. In the PML approach, the position of the truncating boundary, \(\Sigma\), and the layer thickness, \(\delta\), are two degrees of freedom that must be adequately chosen to optimize the accuracy of the numerical solution.
# MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos
## 3 MonoMR System
### Billboard Rendering  
The MR content is synthesized by extracting the textures from image frames of a monocular video. Therefore, the camera's viewpoint is fixed, and we cannot obtain the information not captured in the original video (e.g., an information loss on the part not facing the camera), and the user notices the unnaturalness when the viewpoints of the camera and user are different (See Figure 6a).  
In order to address this problem, the system has a function that applies billboard rendering [40] to every texture, as shown in Figure 6b. Billboard rendering is a simple technique in which the textures are rotated toward the user's viewpoint, thereby reducing the unnaturalness of placing 2D textures in a 3D space. With this function, even if the user changes their viewpoint from the original camera's viewpoint, they notice less unnaturalness.
## 1 Introduction  
Lubrication plays a vital part in the efficiency of machine components. Improved lubrication can significantly increase the efficiency of machine components. For use in extreme environments, researchers are looking for other solutions rather than conventional hydrocarbon based or mineral based oils. One such example are ionic liquids (ILs). ILs have been defined as molten salts with melting points below 100 \({}^{\circ}\)C that are entirely ionic in nature, comprising both cationic and anionic species. Other descriptions include non-aqueous ionic liquid, molten salt, liquid organic salt and fused salt [1]. ILs are widely used in several industrial applications such as electrolytes in electrochemistry, solvents, extractants and catalysts in organic synthesis since they possess excellent electrochemical stability, low volatility, large charge density, tunable polarity, high temperature stability etc. [2,3]. Some of these features make them interesting as lubricants and ILs have begun to gain attention for their tribological properties since 2001 [4]. Several researchers have shown that ILs demonstrate low wear and friction in steel-steel contacts [4, 5, 6, 7, 8, 9], aluminium-steel contacts [4, 10, 11], nickel-steel contacts [12], copper-steel contacts [4] and ceramic-steel contacts [4, 13]. Aside from potential problemswith corrosion and additive compatibility most ILs are significantly more expensive to manufacture compared to more common lubricants. Several researchers have therefore explored the use of ILs as lubricant additives [14; 15; 16; 17] with promising results, although some of the interesting properties such as the low volatility of the pure liquid may be lost.  
Lubrication is usually divided into three regimes; boundary, mixed and full film lubrication [18]. Most of the research articles focus on the performance of ionic liquids in boundary and mixed lubrication. Little research is available in literature concerning the performance of ILs in full film elastohydrodynamic lubrication (EHL) [19; 20]. EHL is found in for instance gears, rolling element bearings and cam followers, and it is of interest how ILs performs in this lubrication regime. Since most of these systems consist of steel surfaces it is important that the lubricant prevents corrosion. Several types of ILs have been shown to lead to corrosion of steels [21].  
In this work, the pressure-viscosity response, film forming capacity and frictional behavior in full film elastohydrodynamic lubrication have been investigated for a protic, bio-based [choline][amino acid] IL. The study reports a pressure viscosity coefficient of below 8 GPa\({}^{-1}\) at 25 \({}^{\circ}\)C, among the lowest reported for any ionic liquid. The friction measurements show up to 70% lower friction with the ionic liquid at very similar film thickness compared to the paraffin reference oil.
## 5 Conclusions  
This work provides insights into the overall structure of the main bacterial communities and atrazine-degrading genetic potential present in the deep zones of the Petrola hypersaline lake-aquifer system. The results obtained are a first approach that shows the presence of bacteria clusters that could be related to agricultural-derived pollutant degradation. Nonetheless, subsequent detailed studies of aquifer microbial communities are necessary to further evaluate their functional biodegradation potential. Initial observations of the microbial community structure and isolated bacteria that inhabit the deep groundwater zones of the aquifer suggest that they may be undergoing a natural process of contaminant attenuation. Based on data regarding the presence of genes related to atrazine biodegradation pathways, the isolated strains from the genera _Arthrobacter_, _Pseudomonas_, and _Nocardioides_ are the best candidates to test their potential to degrade atrazine in the ecosystem.  
Knowledge about the relationship between microbial community structure and environmental conditions in hydrogeological systems is required to develop tools for the assessment and monitoring of natural attenuation processes. Further studies must be focused on the evaluation of the atrazine degrading capacity of the isolated candidates to evaluate the possibility of their use in induced bioremediation technologies.  
Conceptualization, Y.E., M.A.-O. and J.J.G.-A.; methodology, Y.E., G.A. and J.J.G.-A.; writing--original draft preparation, M.A.-O. and Y.E.; writing--review and editing, M.A.-O., Y.E. and J.J.G.-A.; funding acquisition, J.J.G.-A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by a contract (2019-CON-9523) from the Spanish Government-FSE, the CICYT-CGL2017-87216-C4-2-R project from the Spanish government FEDER--Ministerio de Ciencia e Innovacion y Universidades-Agencia Estatal de Investigacion, and the SBPLY/17/180501/000296L project from Castilla-La Mancha Regional Government. The authors declare no conflict of interest.
## 3 Methods and Data
### Data Augmentation  
#### 3.1.1 MODIS Images  
First, obtain the HDF format data of MOD02 QKM from the official website of the National Aeronautics and Space Administration (NASA) ([[https://ladsweb.modaps.eosdis.nasa.gov](https://ladsweb.modaps.eosdis.nasa.gov)]([https://ladsweb.modaps.eosdis.nasa.gov](https://ladsweb.modaps.eosdis.nasa.gov)), accessed on 1 October 2022) [17]. Research [18] shows that internal ocean waves in the South China Sea occur frequently in summer, but less frequently in other seasons. Therefore, the MODIS data collection time used in this article is from 1 June to 31 August every year, and is conducted in the northern South China Sea. In order to reflect the data enhancement work, this article only collected a total of 1217 pieces of data from 2019 to 2022. Then, use ENVI Classic 5.3 professional softwareto read the HDF format file in Earth View 250M Reflective Solar Bands Scaled Integers format into BSQ format, then save it into IMG image format, and apply histogram equalization operation to improve the brightness of the image, where the maximum resolution. The rate is 5416 \(\times\) 8120. The image is then split into smaller sub-images, each 64 \(\times\) 64 pixels in size. Finally, experts who have studied remote sensing for many years divided these sub-images into different categories, including 700 images each of internal waves, clouds, oceans, and land. Figure 3 shows some classification results. The above process finally provides data support for this study, allowing us to study the existence and characteristics of internal waves in the ocean.
## 5 WST Applications  
This section presents most relevant applications in agriculture and food industry. The development of these applications in agro-food has attracted considerable research efforts in the last years, because these technologies are very suitable for distributed data collecting and monitoring in tough environments such as greenhouses, cropland, warehouses or refrigerated trucks. However, some areas have been developed faster than others. For example, there are several applications for monitoring greenhouses or livestock and just a few in farm machinery.
# Hardware Acceleration of Tsunami Wave Propagation Modeling in the Southern Part of Japan
## 5 Conclusions  
The specific hardware configuration and corresponding modeling code we previously proposed were used to study the distribution of tsunami wave height maxima. Only the wave propagation over sufficiently large depth (10 m and more) was considered. Therefore, near-coast phenomena like dispersive effects, wave breaks, and others were not accounted for. Certainly, these are the limitations of the presented approach. A number of numerical experiments were conducted to understand the dependence on the source location of the tsunami wave maximal height distribution along the coastline. The so-called MacCormack finite difference version of the shallow water approximation of equations of hydrodynamics was applied. As observed, even a 200 km shift in artificial tsunami source position dramatically changes the distribution of tsunami wave maxima along the coast.  
A special tool we previously proposed for hardware acceleration of computer code execution on a PC was applied. The achieved performance gain was on the order of several hundred times in the case of a VC709 FPGA microchip versus the same PC without hardware acceleration. This means that one needs just a few seconds to simulate tsunami wave propagation from a source in the Nankai-Tonankai (or another) subduction zone to the coast. The mesh we used contained \(3000\times 2496\) nodes. Such high performance shows the availability of \"real-time\" tsunami danger forecast in the very near future.  
The proposed software tools and hardware code acceleration devices should be used together with the wave generation models and special approaches for inundation mapping. We note that the suggested tools should be used to study tsunami only at the regional scale, for computation areas within a few geographical degrees. For these situations, the sphericity of the Earth is not able to have a notable impact on the tsunami wave parameters. In forthcoming studies, we will present an approach to determine the initial sea surface disturbance at the tsunami source and an implementation of the code acceleration on nested grids. These two steps will contribute to overcoming the aforementioned limitations of our approach. However, even now, the proposed tool can be used as an input data generator for more precise inundation modeling.  
Conceptualization, M.L.; Formal analysis, A.M.; Investigation, M.S.; Resources, K.L.; Software, K.O. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Russian Federal Targeted Program Grant 14.574.21.0145. Unique project ID--RFMEFI574170145.  
The authors declare no conflict of interest.
## 2 System Model and Architecture  
Figure 1a shows an example of a WBAN system. There are many sensors uniformly distributed around the body to monitor the patient's health, and each sensor gathers data and sends it to the MN. In a WBAN that is based on the single-hop star topology, all the sensors send their data directly to the MN. The MN then directs the data to the monitor node, which either analyses it, or forwards it over the internet to the hospital or doctors.  
In WBANs, it should consider a number of physical environments, due to the networks are configured on/in the body. Where, the sensors attached to the body are mobile owing to numerous body movements. Therefore, the distances between the sensors and MN are varying. Some sensors may have a large distance or weak link to the MN, thus transporting data sufficiently to the MN in a single-hop is difficult.  
The CC is considered one of the best solutions to overcome the aforementioned problem, i.e., single hop transmission. Various CC modes are widely inspected in the literature. The ICC is considered in this work and it is summarized as follow: if the MN (or destination) received the data correctly from the source sensor (\(S\)) based on frame check sequence (FCS), then it sends an acknowledgment (ACK) to the \(S\) and the relay sensor (\(R\)) drop what received from \(S\). Otherwise, it sends a negative acknowledgment (NACK) that allows the \(R\) retransmit what was received from the \(S\), but MN drop what received from the \(S\), see Figure 1b. In what follow, the distance from \(S\) to MN, \(S\) to \(R\) and \(R\) to MN are denoted as \(d_{sd}\), \(d_{sr}\) and \(d_{rd}\), respectively, and we denoted link between sensor and MN as \(S-D\), link between source and relay sensor as \(S-R\) and the link between relay sensor to MN as \(R-D\).
## 9 Conclusions  
In this paper, an overview of vector tracking loop architectures has been presented. The performance of the vector-based receiver was compared to its counterpart scalar-based receiver in harsh signal conditions. The evaluation was based on several static and dynamic scenarios that included the attenuation of the signal power level by one with up to four satellites with various attenuation levels ranging from 10 to 20 dB. The advantages of VT loops were validated and verified as VT loops showed a better performance compared to ST loops, which tend to lose lock rapidly, due to sudden drops in the received signal power. Moreover, VT loops were effectively able to bridge a momentary outage of some attenuated satellites and keep their tracking at numerous attenuation levels, sustaining a superior position and velocity accuracy.  
On the other hand, ST loops failed to track satellites attenuated by 20 dB, which result in enormous errors in the positioning solution. This is intuitively understandable, as in the vector-based receiver, the prediction of weaker signals is based on more reliable signals from other satellites. However, ST loops process the measurements coming from each channel independently.  
The performance of VT and ST loops was also assessed in the presence of a jamming signal. Even though both architectures were prone to losing lock of satellites, the VT loops were able to rapidly re-track signals after the jamming signal was disabled, as contrasted with the ST loops that were unable to re-track lost signals without going into re-acquisition mode. Therefore, VT loops reduced the computational load associated with the re-acquisition of the signals. Consequently, the VT-based GNSS receiver is more suitable for augmentation with other navigation sensors for more robust and reliable positioning and navigation.  
Based on the findings and conclusions of this paper, the following recommendations are suggested for future works: the performance of vector tracking loops has been assessed for a GPS L1 C/A signal; however, it can be tested on other GNSS signals. Moreover, the performance of the vector-based receiver augmented with other navigation sensors such as inertial navigation sensors (INS) could be assessed in challenging environments. Furthermore, the integration of the vector-based receiver with a jamming mitigation module could enhance the overall system's performance in the presence of jamming.  
[PERSON] proposed the idea, conceived and designed the simulations, analyzed the data, and wrote the paper. M.T. and A.N. reviewed the paper and simulation results. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
## 6 Discussion  
The Chinese Blasting Safety Regulations (GB6722-2014) [33] stipulate that the allowable criteria for blast-induced ground vibration in traffic tunnels is 10 to 15 cm/s. The measured peak particle vibration velocities of the protected objects (i.e., vibration monitoring points) serve as the basis for safety assessment of blasting-induced vibrations. However, the safety allowable criteria for the blast-induced ground vibration in the neighborhood tunnel with small clearance are not explicitly defined. Table 5 lists some typical control criteria for blasting-induced ground vibrations in the neighborhood tunnel with small clearance in China. For the section with a 0.5 m-thick interlaid rock in the Liantang tunnel, considering the limited cases, it is more appropriate to strictly control the blasting-induced vibrations. According to the existing blasting-induced vibration control criteria, the stability of this vulnerable section with a 0.5 m thick interlaid rock cannot be adequately protected. Therefore, based on the actual conditions of the Liantang tunnel, the following blasting-induced vibration control criteria are proposed for different zones of the neighborhood tunnel.  
1. Blast-induced vibration control criteria for FT-I  
For the FT-I blasting, there is a 3 m cushioning layer to mitigate the damage of blasting vibrations on the interlaid rock. Based on the on-site monitoring conditions, the safety control criteria for the FT-I blasting are set so that the peak particle vibration velocity at a point 20 m from the blasting source within the tunnel is less than 2.0 cm/s.
2. Blast-induced vibration control criteria for FT-II  
The FT-II section, directly connected to the interlaid rock, is the core and crucial area for blasting in the neighborhood tunnels. During the blasting process, vibration monitoring points are positioned in the AT, close to the blasting source, and aligned horizontally with the source. The distance between the monitoring points and the blasting source increases with the thickness of the interlaid rock. According to the gradual variation in the thickness, when the thickness exceeds 3.5 m, the peak vibration velocity at the control monitoring point (with a minimum distance of 6 m from the blasting source) is required to be less than 8.0 cm/s. When the thickness of the interlaid rock is between 0.5 m and 3.5 m, the peak vibration velocity at a point only 3 m away from the blasting source should be less than 3.0 cm/s. These control criteria are significantly higher than that of other small clearance tunnel projects.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Section Structure** & **Site Photo** & **Marking** & **Height (m)** & **Weight (m)** & **Feature** \\ \hline  & & FT-I & 6.86 & 12.73 & Semi-circular shape \\ \hline  & & FT-II & 6.63 & 3.00 & Crescent shape \\ \end{tabular}
\end{table}
Table 4: Cross-sectional features and on-site excavation photos of the FT-I and FT-II.
## 6 Performance Evaluation
### Simulation-Based Performance Analysis
#### 6.4.2 Performance Metrics and Measurement  
The following performance metrics were measured during the simulation:  
* **Average** end-to-end latency (s): This measures the average time taken for an authentication message to travel from the operator device (via the drone relay) to the groundcontrol station. It is calculated from the time a packet is sent by the OD until it is successfully received by the GCS.
* **Packet** delivery ratio (PDR, %): This represents the percentage of successfully received authentication messages at the GCS out of the total messages sent by the ODs. A higher PDR indicates greater reliability of the authentication protocol.
* **Average** radio ON time (%): As a proxy for energy consumption, this metric indicates the percentage of time a node's radio transceiver is active (transmitting or listening). Lower radio ON time implies less energy consumption and longer battery life [17].
* **Control** traffic overhead (packets/h): This measures the total number of non-application-specific control packets exchanged within the network during the authentication process, providing insight into the protocol's efficiency in terms of network overhead.  
Data for these metrics were extracted from the Cooja simulation logs, similar to the methodology described in [16; 17]. Each data point represents an average value over multiple simulation runs to ensure statistical significance.