esa-sceva/satcom-chunk-collection huggingface dataset:
# Underwater Excavation Records Using Underwater Acoustic Survey: A Case Study in South Korea
## 5 Application Case: Method Refinement (Myeongnyang Site)
### Experimental Setup  
The Myeongnyang site is an underwater relic, where UEs have been underway since 2012. Since then, a variety of relics have been excavated and identified, including Goryeo celadon incense burners, with an openwork design and gunpowder weapons used in  
Figure 8: Survey chart of section A of the Nakwoldo underwater excavation site.  
naval battles in the Joseon Dynasty. During the sixth excavation conducted from 7 July to 27 October 2019, we carried out an SS trial excavation in section C, where the gunpowder weapons were discovered during the first excavation. The trial excavation was performed within an area of 70 m (latitudinal) \(\times\) 60 m (longitudinal). The water depth ranged from 5-13 m, and the underwater visibility was 10-20 cm with the lights on. The seafloor was covered in a silt soil with mixed-in shells, and the soil layer thickness and pebble and stone quantity increased westward. A 50 m-long rope was set up along the latitudinal axis with six 1 m wide trenches at 10 m intervals. A southward longitudinal trench was constructed over a length of 60 m, and an additional two trenches were constructed to the west of the study area in the 20-50 m section. The sediments were removed to depths of 0.1-1 m, after which the subsurface was too hard for digging.  
At the Myeongnyang site, a reflector was installed on the seafloor to achieve an accurate mosaic image of multiple sonar images. The reflector was fabricated in a hemispherical shape with a diameter of 20 cm, shaped after a radar reflector for vessels, and mounted on the handle of a probe rod used to fix it to the seafloor (Figure 9). A reflector was installed every 10 m along the probing trench at a height of 50 cm from the seafloor. The SS was operated from a barge, and the seafloor survey was repeated at every point the barge moved to as the probing operation advanced. The frequency was set to 675 kHz, and the swath was set to 25 m and 40 m (Figure 10).  
Figure 10: Scanning sonar mosaic image obtained from the trial excavation during the sixth Myeongnyang site underwater excavation (frequency: 675 kHz; swath 40 m).  
Figure 9: Reflector installed on the seafloor.
# Deterministic Propagation Modeling for Intelligent Vehicle Communication in Smart Cities
## 3 Simulation Results
### Large Scale Spatial Path Loss
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Description** & **PLE (n)** & **STD (\(\sigma\)) [dB]** \\ \hline \multicolumn{3}{c}{**(a) Along AV1 (y = 81 m)**} \\ x: (0 to AV5/AV5 to TX1/TX1 to TX2/TX2 to 400) m & (2.8/2.5/2.8/4.3) & (30.8/13.1/25.1/44.6) \\ \hline \multicolumn{3}{c}{**(b) Along AV2 (y = 70 m)**} \\ x: (0 to AV5/AV5 to TX1/TX1 to TX2/ TX2 to 400) m & (2.6/2.4/2.5/5.0) & (20.1/11.3/18.0/44.0) \\ \hline \multicolumn{3}{c}{**(c) Along ST1 (x = 161 m)**} \\ y: (AV2 to 150) m & 2.40 & 9.21 \\ \hline \multicolumn{3}{c}{**(d) Along ST2 (x = 116 m)**} \\ y: (LoS: 1 to 21/NLoS: 21 to AV1) m & (4.13/ 2.48) & (11.32/8.11) \\ \hline \multicolumn{3}{c}{**(e) Along ST3 (x = 178 m)**} \\ y: (LoS: 1 to 21/NLoS: 21 to AV1) m & (4.21/2.28) & (15.56/3.36) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Path loss exponent (n) and standard deviation (STD) for TX1. Factors such as distance, special type of street intersection (roundabout) and obstacles (trees and buildings) have significant impact on the propagated signal. The presence of a roundabout causes RSS degradation with RSS values below the RST, while a line of trees (height: 3 m) along AV1-AV2 causes Quasi-Line-of-Sight (QLoS) deriving the in signal fluctuation, which becomes evident in the reported STD values (Table 3, item a). The PLM is unable to predict the signal losses caused for the roundabout and line of trees, whose impact is greater to the extent that the TX-RX distance is increased. Figure 7b depicts the RSS along AV2 where the LoS condition and shorter distance to TX1 permit a higher RSS and lower signal dispersion values when compared with AV1-RSS. The PLE and STD values, registered in Table 3, item b, are lower than that registered in item a, due to the aforementioned aspects. The expected TX1 coverage along AV2 is already 90m and 80m for its left and right side, respectively. An additional TX1, TX2 coverage analysis is presented in the next subsection to clarify this estimation. Figure 7c depicts the RSS along ST1, ST2 and ST3 where the relative TX-RX closeness yields RSS values above the RST at ST1 (QLoS), the upper-area of ST2 (LoS) and all ST3 (LoS). The NLoS condition caused by B4 at the lower-area of ST2 and ST3, generate RSS values below the RST. Additional  
Figure 7: Spatial TX1-RSS Path Loss along: (**a**) AV1; (**b**) AV2; (**c**) ST1, ST2, ST3. simulation, when TX1 or TX2 or TX1 and TX2 are transmitting, showed areas as the roundabout, AV3, AV4, AV5, ST2 (NLoS) and ST3 (NLoS) where the V2I communications are unfeasible.
# Application of Mammalian Nudix Enzymes to Capped RNA Analysis
## 5 RNA Decapping with Mammalian Nudt2, Nudt5, Nudt12, Nudt16, and Dcp2
Interestingly, Ap\({}_{3}\)G-RNA appeared resistant to Nudt2 decapping, opposite to Gp\({}_{3}\)A-RNA [33]. Interestingly, Nudt2 hydrolase triphosphorylated pppN-RNA into monophosphorylated pN-RNA, which serves as a substrate for Xrn1 exonuclease [135] and as such could be considered as another enzymatic activity that can be used in removing uncapped pppN-RNA transcripts, similarly to the earlier-mentioned approach that utilizes commercially available 5' polyphosphatase. \begin{table}
\begin{tabular}{c c c c c} \hline  & **Dcp2** & **Nudt16** & **Nudt12** & **Nudt2** \\ \hline m\({}^{7}\)GpppN & + [105] & & & \\ m\({}^{7}\)GpppN\({}_{m}\) & + [105] & & & \\ \hline m\({}^{7}\)GpppG & + [92; 105; 120; 136] & +/ – [92; 93; 120] & + [116; 130] & + [116] \\ \hline m\({}^{7}\)GpppA & + [105] & – [120] & & \\ \hline m\({}^{7}\)GpppG\({}_{m}\) & + [105] & +/ – [120] & & \\ \hline m\({}^{7}\)GpppA\({}_{m}\) & + [105] & – [120] & & \\ \hline m\({}^{7}\)Gppp\({}^{m6}\)A\({}_{m}\) & + [105; 107] & & & \\ \(-\)[19] & (transcript dependent) & & & \\ \hline m\({}^{7}\)Gppp\({}^{m6}\)A\({}_{m}\) & + [103] & & & \\ \hline GpppG & \(-\)[14] & + [92; 93; 120] & + [116; 130] & + [33; 116] \\ \hline GpppA & & + [120] & + [33] \\ \hline ApppA & & + [33] \\ \hline ApppG & & \(-\)[33] & & \\ \hline \end{tabular}
\end{table} 
Table 2: Comparison of decapping activity of Dcp2, Nudt16, Nudt12, Nudt2 towards RNA transcripts with indicated chemically modified and natural 5’ cap structures.
# Mars to Earth Data Downloading: A Directory Synchronization Approach
## 6 Performance Analysis
### Science Data Flow (Direct Delivery)  
Now we can move on to the science data. First, we will examine the case of direct delivery using DTNperf, which is our benchmark case (Figure 9). Bundles are much more frequent (about one every 21 s) than in the previous case. Because of limited connectivity from the Lander, there are th0e same two delivery gaps as before. The main difference is that now bundles are often delivered out of order. Although this is allowed by DTN specifications [5], this is a symptom of the challenges posed by concurrent traffic. In fact, while gaps are due to lack of connectivity, disordered delivery is mainly the result of concurrent bundles of higher priority, which are always forwarded first, even if generated later, thus making delivery predictions for lower priority bundles inaccurate. In this regard, it must be stressed that CGR decides on the best route (i.e., that which should reasonably ensure fastest delivery, given the contacts in the contact plan) bundle-by-bundle, as soon as the bundle arrives at the local node [23]. CGR cannot therefore take account of the forwarding delay due to higher priority traffic that appears later. As a last positive remark, we can note that all bundles are delivered by the expected end of the experiment.
###### Abstract  
Dynamic compaction and geogrid reinforcement are two of the well-known methods used in improving the mechanical properties of fill foundations. In order to investigate their mutual restriction when used simultaneously and optimize the design parameters, model experiments and numerical simulations were conducted. First, three factors (embedded ratio of reinforced geogrid, number of reinforced layers and interval of reinforced layers) that are related to performance of reinforced geogrid were analyzed by model experiments with dynamic compaction. Then, orthogonal analysis was performed by numerical simulation (dynamic analysis in FLAC3D) to take into account five different elastic moduli and internal angle of friction along with the aforementioned three factors. Last, range analysis and variance analysis were performed on the orthogonal results to optimize the five factors by the calculated indicators. Additionally, linear regression analysis reflecting the relationships between five factors and four indicators was presented. The displacement field, compaction effect, earth pressure, and geogrid deformation of the reinforced soil under different combinations of the five factors were explored. Experiment and simulation results provide practical guides to the design of reinforced methods and a reference for the stability and deformation of other earth reinforcement projects under dynamic loads.  
model experiment; dynamic analysis; parameter optimization; range analysis; linear regression Article
# Integrated Radar and Communications Waveform Design Based on Multi-Symbol OFDM
## 3 IRC Waveform Design Objective  
In this section, we first review the PMEPR and PSLL problems of IRC waveforms. Then, the joint optimization objective function of PMEPR and PSLR in IRC waveform design is formulated.
## 4 Multihoming and Interworking
### Traffic Engineering Support  
A GLI-domain might be multihomed to two ISPs: a cheap ISP for carrying its best-effort traffic, and an expensive ISP for carrying its premium traffic from demanding applications such as games or live video. In our example in Figure 1, E may be the gateway to the cheap ISP and F may be the gateway to the expensive ISP. Thus, best-effort traffic should be exchanged through gateway E, while premium traffic should be exchanged through gateway F.
## 5 Results and Discussion
### Evaluation of Dichotomous Estimates/Forecasts  
With respect to an evaluation through contingency tables, Figure 16a-c and Table 16 reveals higher POD (0.74), lower FAR (0.40) and higher CSI (0.49) by ERA-Interim over the North of Iran, Guilan area, compared to other satellite products. High POD may have been influenced by the dominance of convective storms [(38)]. Lower POD for 3B42 and IMERG may be associated with missed precipitation over this region.  
The missed precipitation may be caused by snow cover on the ground at higher altitudes over the Alborz Mountains and by the inability to catch warm rain processes, short-lived convective storms, or maritime precipitation along the Caspian Sea.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{POD} & \multicolumn{4}{c}{FAR} & \multicolumn{4}{c}{CSI} \\ \hline  &
\begin{tabular}{c} **Number of** \\ Daily Events** \\ \end{tabular} & IMERG & **3B42** & **ERA** & IMERG & **3B42** & **ERA** & IMERG & **3B42** & **ERA** \\ \hline Guilan (GS) & 105 & 0.46 & 0.39 & **0.74** & 0.52 & 0.59 & **0.40** & 0.29 & 0.23 & **0.49** \\ \hline Bushehr (G4) & 19 & **0.70** & 0.56 & 0.39 & 0.59 & 0.55 & **0.54** & **0.35** & 0.33 & 0.28 \\ \hline Kemmanshah (GS) & 53 & 0.66 & 0.51 & 0.63 & **0.45** & 0.57 & 0.46 & **0.42** & 0.30 & **0.42** \\ \hline Tehran (G2) & 59 & 0.55 & 0.50 & 0.51 & **0.43** & 0.71 & 0.58 & **0.37** & 0.23 & 0.30 \\ \hline \hline \end{tabular}
\end{table}
Table 16: Spatially averaged POD, FAR and CSI metrics.  
Figure 16: (a–c) POD, FAR and CSI in the four study regions.  
POD value of IMERG (0.70) seems to be better than other products over Bushehr area while it is quite low for ERA-Interim (0.39). On the other hand, IMERG indicates a high FAR value (0.59) because of rare precipitation events despite high humidity. Figure 16b shows similar results for 3B42 and ERA Interim in Bushehr area as well.  
In Kermanshah area, IMERG yields a higher POD and CSI and lower FAR in comparison to 3B42. These results could be due to the inability of TRMM Microwave Imager (TMI) to measure snowfall and light rain over the ground and Zagros Mountains while the main feature of Dual-frequency Precipitation Radar (DPR) based on the GPM is to measure snowfall and light rain. Overall, the ERA-Interim product produced fewer robust results when compared to IMERG.  
As Figure 16a-c and Table 16 indicate, IMERG product performs better than others with higher POD and CSI and lower FAR in Tehran. We should note that precipitation in Tehran is stratiform and orographic.
## 4 Discussion  
For obtaining reliable results with the proposed algorithm, the value of the optimization parameter C must be decreased, and the value of the gamma parameter must be increased. The ranking of wavelength combinations together with the five-fold CV mean for white and brown eggshells are shown in Tables 9 and 10, respectively. The obtained F-score results are satisfactory. As predicted, the F-score value for the white eggshell dataset is higher than that for the brown eggshell dataset due to the broader variety of brown eggshell pigmentation, which strongly affects the spectral characteristics of the reflected light.  
The F-score being higher than 94% in the white eggshell dataset indicates the key wavelengths are A0 = 457 nm, A11 = 593 nm, A12 = 632 nm, A13 = 660 nm, A14 = 671 nm, and A15 = 690 nm, which should be accompanied at least by one (A16 = 729 nm; F-score 94.912%) or two (A16 = 729 nm and A10 = 589 nm; F-score in this case reaches 95.755%) other wavelengths. The usage of only the key wavelengths (A0 = 457 nm, A11 = 593 nm, A12 = 632 nm, A13 = 660 nm, A14 = 671 nm, and A15 = 690 nm) results in an F-score of 93.957%, and a five-fold CV SD of 2.27 with C = 107.63 and gamma = 0.25.  
For the brown eggshell dataset, to obtain an F-score higher than 83%, it was necessary to use at least five wavelengths (out of 17). Analysis of the data shown in Table 10 resulted in four key wavelengths: A4 = 532 nm, A8 = 556 nm, A14 = 671 nm, and A15 = 690 nm. The fifth wavelength necessary to reach a high F-score is A3 = 515 nm; nevertheless, the highest score (86.21%) was obtained by adding a sixth wavelength, A5 = 526 nm. Additional wavelengths that may be added to the key ones are A6 = 532 nm and A7 = 543 nm. The usage of only the key wavelengths (A4 = 532 nm, A8 = 556 nm, A14 = 671 nm, A15 = 690 nm) resulted in an F-score of 78.552%, and a five-fold CV SD of 3.35 with C = 76.1 and gamma = 0.84.
# Device-To-Device Communication in 5G Environment: Issues, Solutions, and Challenges
## 7 Challenges in D2D Communication
### Challenges in Security
#### 7.3.1 Balancing Security-Energy Trade-off  
It is impractical to utilize security techniques that use a lot of energy in a limited resource D2D devices. Therefore, to ensure the optimal device resources usage, a secure energy-efficient protocol needs to be implemented. In order to secure authentication and message integrity, a cryptographic scheme, which usually depends on the key generation complexity, is put into work. The provision of the security and privacy by using just one type of algorithm is not considered best practice in terms of the energy point of view. For that reason, future research should focus more on the hybrid protocols that work for dynamic algorithm selections depending on network conditions.
# Compressive Sensing-Based IoT Applications: A Review
## 4 CS-Based IoT Applications
### Application Layer
#### 4.3.2 CS-Based Cloud Storage  
On the other hand, receiving big data has shifted the storing paradigm from single server to multiple mega-server and it is continuously growing. The massive number of data that are collected on a daily basis requires large-scale data processing engines to analyze. However, applications are rarely interested in raw data records. Instead, only the salient features are required for deep data analytics. CS can be explored efficiently to store the cloud data by reducing the data size and discarding the non-relevant features to facilitate different types of applications. Many IoT data analytic applications are executed by sending queries to the cloud server to retrieve data. For instance, Top-\(k\), range, and keyword queries present the most popular types of queries for IoT and WSN applications. Top-\(k\) query means that the \(k\) highest (or lowest) data values are retrieved from a dataset [126]. Thus, by leveraging the fact that the CS compresses and preserves an approximate form of the data, [PERSON] et al. [127] proposed a new impression store cloud architecture based on CS that does not store all the raw data, but rather some features that can yield to provide a successful application in term of QoS. This approach saves storage capacity and bandwidth and allows for efficient and scalable parallel updates and queries. This approach consists of compressing the data to the minimum factor that allows the recovery of only the application-defined principal components. In addition, [PERSON] et al. [128] a two-stage compression scheme. First, the data are compressed at the sensor level with an \(M\) samples. Afterwards, they wait for a query from the cloud to send only the \(k\ll M\) samples that are required for a specific defined application.
# Complexity Reduction of MLSE and MAP Equalizers Using Modified Prolate Basis Expansion
## 2 Materials and Methods  
This work is intended to highlight the use of the modified version of the Prolate basis expansion [16; 17; 18], in MLSE and MAP equalization processes [13; 15; 19; 20]. The application of MPF in the time-delay domain conveys a more accurate channel representation, which leads to a reduction in the error floor. Additionally, the computation complexity is lower, compared with the MLSE and MAP algorithms found in the literature [15; 19; 20].  
The descriptive statistics of the signals related to the system model are presented in Section 2.1. Furthermore, the equalizer assumes to know the channel impulse response, which is decomposed in K basis functions to compute their relative weights. Employing a limited number of basis functions affects the variance of the modeling error. Accordingly, Monte-Carlo simulations were used in Section 3 to compare the benefits of this method, assuming perfect channel state information (CSI) and estimated channel impulse response.  
This paper does not contain studies involving human participants, data, or tissue, or animals, performed by any of the authors.
# A Novel Approach against Sun Glare to Enhance Driver Safety
## 4 Discussion  
In this paper we presented a study on the applicability and the benefits of an anti-glare system. Several test scenarios were probed using multiple MATLAB simulations in order to confirm the usability of such a system. Considering the progress registered in the HUD field in the last years, it seems only a matter of a few years until such a system will be realized at a cost of production that is low enough to bring benefits for both the driver and the manufacturer. Indeed, the classic sun visor is outdated compared to the other components of a modern vehicle and is not contributing to the safety of the driver as much as a digital sun visor.  
The presented project can be improved on different levels, starting with the hardware parts. The proposed sun tracking sensor is overqualified for a project like this since a sensor with lower precision, resolution, and accuracy would still work fine. In this manner, the costs would be reduced. An improvement from a costs point of view would be to remove the sun tracking sensor and try to obtain all the information required just by processing images.  
Another potential update is that the glare problem is approached only for direct suneams. As is known, there are some scenarios in which the suneams reflected by the road are harmful, too. In this case, we consider that the same handling shall be applied, using a HUD and creating a dark spot where the reflected suneams are producing discomfort. The analysis of this specific case and the calculation of the dark spot's position on the windshield are not presented in this paper.  
In the future, the simulation environment shall be replaced with a real prototype that can be tested in a laboratory, and then on a real-life driving test scenario.  
The merit of the project consists in the fact that a large variety of knowledge from different domains was used and combined in order to propose a working product that will increase the safety of all traffic participants. The tests done prove the value and the applicability of the ideas, algorithms, and principles implemented in the paper. The presented research represents a starting point for those who develop anti-glare systems and provides good understanding of this topic. Apart from the industrial benefits, this paper can be used in didactic activities as well, showing students how to apply theoretical knowledge in order to solve a real-life problem.  
Ideas: R.-C.M. and V.-LU.; concept, methodology, and development: V.-I.U., I.S., and R.-C.M.; software implementation: V.-I.U.; analysis of results and discussions: I.S., V.-I.U., R.-C.M., and A.K.;  
Figure 16: Test scenario 4—S and D are mobile points.  
writing scientific paper: V.-I.U.; supervision, validation, and financing: I.S. and A.K. 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.
## 1 Introduction
The proposed algorithm can provide an optimum route to react to lossy WSNs based on the radio information which reflects the current network status by using a cross-layer design. Furthermore, if RA detects the lossy situation at a target node, it can choose an alternative neighbor node as a next hop to provide reliable data transmission. Since we added the cross-layer design that utilizes radio information of existing packets, RA has the advantages of reliable communication and interoperability in lossy WSNs without burdening additional overhead on DD. In order to evaluate RA, several simulations were performed with _ns_-2 under various conditions. In accordance with the simulation results, the proposed algorithm showed better performance in various environments with different error rates. The remainder of the paper is organized as follows. In Section 2, we discuss related works and motivation. Section 3 describes the proposed radio-aware routing algorithm. In Section 4, we explain the evaluation metrics of the simulation. The simulation results are analyzed in Section 5. Section 6 concludes the paper and addresses future work.