esa-sceva/satcom-chunk-collection huggingface dataset:
# EXPRESS: Exploiting Energy-Accuracy Tradeoffs in 3D NAND Flash Memory for Energy-Efficient Storage
## 2 Background
### Fundamentals of 3D NAND Array
Any flash cell that is set to a logic '0' by a page program operation can only be set to a logic '1' by erasing the entire block. A page read operation in the NAND array involves applying a read reference voltage (\(V_{REF}\)) on the selected page's WL, and then sensing the threshold voltage of the cells connected to that WL. WLs of all the other pages in the selected block are set to a high voltage (\(V_{PASS}\)), which turns on all of the flash cells from the nonselected pages. In this way,  
Figure 1: 3D NAND Flash Memory: (**a**) 3D flash memory cell; (**b**) physical structure of a 3D NAND flash array; (**c**) transistor-level schematic of a NAND flash memory block, which consists of 34 pages in this example. the state of the selected page can be sensed through the bit lines. An erased cell conducts the current, and that is sensed as a logic '1', whereas a programmed cell does not conduct the current, and that is sensed as a logic '0'. The read reference voltage is set in between the erased state and the programmed state distributions to correctly identify the cell states. Traditional flash memory cells that store one bit of information are known as \"single-level cells\", or SLCs. The recent advances in controlling and sensing different levels of the charge on the floating gate have enabled modern flash memory cells that can store two bits of information (multilevel cell, or MLC), three bits (triple-level cell, or TLC), or even four bits (quad-level cell, or QLC).
# Sub-Band Backdoor Attack in Remote Sensing Imagery
## 8 Results of Sub-Band Backdoor Attack
### Results of Defense Mechanisms against Sub-band BadNets
#### 8.2.3 GangSweep  
We applied the Gangsweep defense approach to defend the all-bands, important-bands and less-important-bands BadNets attack on the DCNN model with the Eurosat dataset, and the results are shown in Table 5. We observed that it failed to detect the backdoor for most scenarios, especially for the important-bands BadNets attack, it failed all nine cases.
## 3 Methodology
### Latency Using Control Tests over the Wired University Network  
The initial tests performed were baseline and validation tests of controlling the robot over the same local University network to validate the correct operation of the control and visual feedback loops. This network scenario, shown in Figure 3, also allowed us to ensure the accuracy of the precision timers within each script, as packets were captured on both the client's and host server's Ethernet interfaces.  
Once the measurement methods were confirmed to be accurate, the results were collected from the control script. This script initiated a connection between the client and the host server and issued control commands. This network configuration was also utilized to test the effective movement command rate that can be sent from the client to the [PERSON] robot. While the [PERSON] robot accepts packets at much faster rate, even a 100 ms delay between command packets still resulted in smooth robot movement within our control scheme.
## 4 Bit-Error-Rate Analysis
When the index position is wrong, the constellation symbol bits must be recovered by the data of the inactive antenna, leading to \(\log_{2}L/2\) error bits. Traverse all antenna index positions to obtain the error bit number of index position:  
\[m_{e10}=\frac{1}{10^{6}}\sum\limits_{u=1}^{10^{6}}\sum\limits_{\hat{u}\
eq u =1}^{10^{6}}P(x_{u}\rightarrow\hat{x}_{u})\frac{\log_{2}L}{2} \tag{24}\]  
When the index position is correct, its probability upper bound position can be expressed as follows:  
\[1-\sum\limits_{\hat{u}\
eq u=1}^{10^{6}}P(x_{u}\rightarrow\hat{x}_{u}) \tag{25}\]  
Let \(P(y_{u})\) denote the BER used to activate antenna detection when the index position is correct; i.e., the BER of \(L\)-PAM, and, for 2-PAM, it can be expressed as \(P(y_{u})=Q\bigg{(}\sqrt{2\left|HA_{u}\right|^{2}/N_{0}}\bigg{)}\); hence, we can obtain  
\[m_{c}\leq\sum_{u}\sum_{\hat{u}}P(x_{u}\rightarrow\hat{x}_{u}|H)\frac{1}{10^{6 }}\hat{m}_{e}(u,\hat{u}) \tag{17}\]0The total BER expression can be obtained from Equations (23), (24) and (26):  
\[ \begin{split} P_{b}&=\frac{1}{10^{6}}\sum\limits_{u=1}^ {10^{6}}\sum\limits_{d\
eq u=1}^{10^{6}}P(x_{u}\rightarrow\hat{x}_{u})e(u,\hat{ u})\\ &+\frac{1}{10}\sum\limits_{u=1}^{10^{6}}\sum\limits_{d\
eq u=1}^ {10^{6}}P(x_{u}\rightarrow\hat{x}_{u})\frac{\log_{2}L}{2}\\ &+\frac{1}{10^{6}}\sum\limits_{u=1}^{10^{6}}\left(1-\prod\limits _{i\
eq u=1}^{10^{6}}P(x_{u}\rightarrow\hat{x}_{u})\right)\log_{2}LP(y_{u}) \end{split}  \tag{27}\]
###### Abstract  
The rising demand for dental and orthopedic implants and their frequent aseptic loosening failure mode necessitate the drive to continue modifying implant surfaces to improve osseointegration outcomes. Plasma-sprayed hydroxyapatite coatings are widely used but are prone to delamination. This study involves a single-step anodization process utilizing a novel electrolyte to produce Mg-doped carbonated hydroxyapatite and tricalcium phosphate-containing coatings on four titanium alloy surfaces. XRD confirmed hydroxyapatite and tricalcium phosphate formation, with FTIR examination revealing carbonate substitutions indicative of bone-like apatite formation in each oxide. SEM analyses revealed micro- and nano-scaled surface features on each oxide. SEM and EDS analyses of the oxide coating cross-sections showed each group to be bi-layered with an inner titanium dioxide-rich layer and an outer hydroxyapatite/tricalcium phosphate-rich layer. The oxide layer adhesion quality was shown to be good on CPTi, TAV, and TiMo \(\alpha+\beta\) implant alloy surfaces. Unfortunately, the anodization process also resulted in an undesirable and embrittling omega phase at the substrate-oxide interface due to the migration of molybdenum into the inner oxide. Nonetheless, the anodized coatings on the CPTi and TAV alloy substrates, which are the most widely used titanium alloys for implant applications, show much potential for improving future patient outcomes.  
hydroxyapatite; anodization; osseointegration; titanium implant Article
## 3 Model of the Eszterhaza Opera House for Geometrical Acoustic Simulations
### Assumptions and Acoustic Simulations
The value of absorption coefficients of the chairs has been replaced with tissue's coefficient, as done in the previous study, that achieved excellent results [26]. The presence of the audience in the stalls, galleries, and Royal box is important to understand whether it can negatively affect the overall acoustics of the theatre and if it involves variations of the room's acoustics parameters. The sound absorption of the spectators depends on posture, clothing, and also occupation density [27; 28; 29] and its value was chosen accordingly with the literature [23]. From the analysis of historical references [11; 12; 13; 14; 15; 16], it is possible to state that Eszterhaza Opera House had many capacities in its historical evolution, and it was not normally used in full capacity, and indeed, the chairs were not always placed in the galleries. Therefore, the simulations were performed placing about 200 chairs in the main hall. Figure 8: The 3D model of the Eszterháza Opera House in Scenarios 1 and 2 (**a**), and the 3D model of the Eszterháza Opera House in Scenario 3 (**b**). Figure 7: Plan of sound source positions (red points) and 106 receiver positions (blue points). In the last simulation, Eszterhaza Opera House 3D model was reconstructed according to the plan dated 1784 (Figure 8b), adding two dressing rooms (6.50 m high, 7.40 m wide, and 5.80 m long) covered with lime plaster at the back of the stage without the presence of the audience in the main hall (Scenario 3). Acoustic simulations were carried out in the octave bands from 250 to 4 kHz, setting the relative humidity at 50% and temperature at 20 Celsius. The IR definition was set 1 ms with the length of 5 s. The main acoustic parameters defined in ISO 3382-1:2009 [30] were calculated, and the results of the simulations are discussed. The reverberation was evaluated through reverberation time (T10 and T30), while the perceived reverberation was obtained with Early Decay Time (EDT). The clarity perceived for music was related to the parameter C80, whereas the clarity perceived for the speech was related to the parameter C50. Moreover, the center time, strength, and STI (Speech transmission index) were calculated.
# Fiber-Based Sensors and Energy Systems for Wearable Electronics
## 3 Fiber-Based Sensors
### Tactile Sensing Fibers
However, this fiber showed very stable electrical characteristics after 10,000 cycles of 15% strain and the ability to be weaved into the fabric. The researchers were able to use this fabric to detect pressure below 200 kPa. These fiber-based capacitive sensors require binding two fibers to fabricate one sensor. On the other hand, all-in-one fiber capacitive sensors were reported [68; 81]. A strip was cut from a silicone rubber film to create a fiber with a square cross-section with 2 mm thickness and 2 mm width [81]. On two opposing sides of the fiber, MWCNT sheets were attached and acted as two electrodes that were separated by the fiber core (silicone rubber). Although this fiber sensor was thick, it was capable of sensing strain up to 200% with 0.6 GF. In another study, [PERSON] et al. utilized multi-shell printing to fabricate a fiber whose inside was composed of two ionic conductive layers separated and encapsulated by the silicone elastomer dielectric layer (Figure 2c) [68]. The multi-shell printed fiber strain sensor with a diameter of 1.5 mm showed a strain detection range up to 700% with a GF of 0.35. In summary, resistive, piezoelectric, and capacitive types of fiber-based tactile sensors were explored. Active materials, such as metals, carbon-based materials, and conductive polymers have been utilized along with natural fabrics or polymer fibers to fabricate flexible, stretchable, and durable fiber-based tactile sensors. Applications of these sensors in physiological monitoring have been introduced, such as pulse and joint motion detection. The physiological monitoring capability has been suggested to be useful in sports and rehabilitation settings [3; 4; 80]. However, none of the fiber-based wearable tactile sensors has yet been commercialized to our knowledge, probably due to the limited durability and the resistance to various environmental factors of these fibers, which should be addressed in the future.
## 2 Materials and Methods
### Satellite Data  
For satellite data, we opted to use Sentinel-2, Sentinel-1, and a DEM (Digital Elevation Model) layer. The data were acquired through GEE, and all subsequent analyses were processed using the GeeMap package ([PERSON] et al., 2016). The choice of these satellites is primarily driven by the optimal compromise between spatial, spectral, and temporal resolutions, making them ideal for crop-monitoring applications. Additionally, their availability in GEE further contributes to their suitability and accessibility.  
Sentinel-2 is a constellation comprising two passive optical satellites that operate in a sun-synchronous orbit, capturing data every 3-5 days at medium latitudes. It offers a spatial resolution of 10 m/pixel for RGB and Near Infrared (NIR) bands ([PERSON] et al., 2016). This satellite excels in discriminating surface spectral responses, utilizing specific bands targeted at vegetation, such as Red-Edge, NIR, and Short Wave Infrared (SWIR), with a great potential for estimation of the biophysical variables of canopies ([PERSON] et al., 2016).  
Figure 2: Representation of classes based on high-resolution satellite images gathered from Google Earth-Maxar WMS services.  
In the present study, the following bands were exploited:  
* 4 \(\times\) 10 m Bands: the three classical RGB bands (B2, B3, B4) and a Near Infra-Red (B8\(\sim\)833 nm) band.
* 6 \(\times\) 20 m Bands: 4 narrow bands in the VNIR vegetation Red-Edge spectral domain (B5\(\sim\)704 nm, B6\(\sim\)740 nm, B7\(\sim\)783 nm and B8a\(\sim\)865 nm) and 2 wider SWIR bands (B11\(\sim\)1610 nm and B12\(\sim\)2190 nm) for applications such as vegetation moisture stress assessment.  
Sentinel-1 is a C-band synthetic-aperture radar (SAR) satellite system that comprises two active satellites, Sentinel-1A and Sentinel-1B. These satellites acquire data in all weather conditions, both during the day and night, with a revisit time of 6-12 days. They employ various modes and polarizations [64], enabling sensitivity to the dielectric constants of materials, including the water content and phenological stage of vegetation [65]. Additionally, the cross-polarization capability allows for the characterization of volumetric scattering, providing insights into the volume of biomass present in the observed area. These features make it highly suitable for crop identification and characterization [66; 67; 68].  
The supplementary selection of the Digital Elevation Model (DEM) is employed to justify the temporal shift that can occur between bands at different altitudes, especially when observing the same type of vegetation cover. This is attributed to the variations in phenological phases that may affect the spectral-temporal response of the vegetation over different elevations [69].
# Energy-Efficient Hardware Implementation of an LR-Aided K-Best MIMO Decoder for 5G Networks
## 1 Introduction
Therefore, for green wireless communications there is a need for MIMO decoding schemes, which have low-power hardware implementation and minimal transmission power requirements. Lattice reduction (LR) techniques [15] have received increasing attention for MIMO detection because of their potential to attain near-ML performance, while having a significantly lower complexity than the maximum likelihood detection (MLD), especially in large-scale MIMO systems [16]. In comparison with the conventional K-best detectors, the LR-aided K-best algorithm assumes no boundary information about the symbols in the lattice-reduced domain, which means possible children for each layer can be infinite. Therefore, to find the K-best partial candidates from the infinite children set, LR-aided K-best algorithms typically replace the infinite set with a finite subset of the children. The complexity of generating the subset may be reduced by using an on-demand child expansion based on the Schnorr-Euchner (SE) strategy [17]. This paper presents an energy-efficient LR-aided K-best detector targeting a \(2\times 2\) MIMO system with quadrature amplitude modulation (QAM) spatial multiplexing. We developed a new hardware architecture, which was implemented in 32 nm technology for verification and energy cost evaluation. Our results indicate that the proposed decoder reduces the overall power costs by four-fold, on average, compared to existing schemes, thanks to its better bit error rate BER performance. The throughput of the proposed decoder is comparable with existing approaches. This paper is organised as follows: Section 2 outlines the main principles of sphere decoding and K-best algorithms; Section 3 explains how LR techniques can be combined with K-best decoding to enhance performance; Section 4 describes the proposed hardware architecture of the LR-aided K-best detection; Section 5 presents a framework to evaluate the overall power costs of a MIMO scheme, which takes into consideration its transmission power requirements; Section 6 explains the VLSI implementation details and compares the proposed design with recently-published energy efficient MIMO decoders; and, finally, conclusions are drawn in Section 7.
# Precise Channel Estimation Approach for a mmWave MIMO System
## 3 mmWave Channel Estimation Problem Formulation  
In this section, a channel estimation problem for a mmWave MIMO system is formulated. Without loss of generality, matrix decomposition methods are used for the completion of a low-rank matrix with the help of partially observed data [35, 36]. By following the given conditions, Equation (6) can be written in decomposed form as \(\rm{H}=A_{R}DA_{T}^{H}\), where \(\rm{D}\) is the submatrix of \(\rm{Z}\). The optimization problem for the joint recovery of channel state information (CSI) matrix H and the decomposed beamspace for the unknown sparse matrix D thereof can be described as  
\[\begin{split}\underset{\text{H,D}}{\text{minimize}}\ \Gamma_{\text{H}}\| \text{H}\|_{\star}+\Gamma_{\text{D}}\|\text{D}\|_{1}\\ \text{Subject to}\ \Psi\circ\text{H}=\text{H}_{\Psi}\ \text{and}\ \text{H}= \text{A}_{\text{R}}\text{DA}_{\text{T}}^{\text{H}}\end{split} \tag{7}\]  
Here, the side information of \(\text{A}_{\text{T}}\) and \(\text{A}_{\text{R}}\) is used to find the missing values of matrix H. Originally, \(\text{H}=\text{A}_{\text{R}}\text{DA}_{\text{T}}^{\text{H}}\) is the decomposed form of Equation (6). Here, the sum of the singular values of a matrix is obtained by imposing a nuclear norm, which also represents the tightest convex lower bound for any matrix. In this way, the low rank property of matrix H is exhibited by the nuclear norm, however, \(\text{l}_{1}\) - norm bounds D to enforce the sparsity. In contrast, the weighting factors \(\Gamma_{\text{H}}\) and \(\Gamma_{\text{D}}\), which depend upon the number of propagation paths, are always considered as positive integers [35].  
The positions of non-zero-unit values, which are distributed uniformly, such that \(\Psi=\{1,2,3,\ldots\text{N}_{\text{R}}\text{N}_{\text{T}}\}\)[28; 37] in matrix \(\Psi\) of Equation (7), are chosen in a random fashion. In this way, one can say that the matrix \(\Psi\) has M ones and \((\text{N}_{\text{R}}\text{N}_{\text{T}}-\text{M})\) zeros. The position of non-zero values in \(\text{H}_{\Psi}\) is the same as the position of non-zero values in matrix \(\Psi\), where matrix \(\text{H}_{\Psi}\) is the subsampled estimated matrix, followed by matrix \(\Psi\). The estimation error of H depends upon the estimation accuracy of \(\text{H}_{\Psi}\)'s elements and the M non-zero values of \(\text{H}_{\Psi}\).
# Study of Urban Unmanned Aerial Vehicle Separation in Free Flight Based on Track Prediction
## 2 Separation Formulation Method
### Separation Formulation Based on Position Error
#### 2.2.1 Flight Path Structure  
Considering the rapid development of urban logistics UAV delivery services, the air traffic volume in low-altitude airspace will increase rapidly, becoming increasingly congested. To fully leverage the lightweight, agile advantages of urban logistics UAVs, free flight can reduce flight path constraints, alleviate flight route pressure, and effectively address future low-altitude airspace congestion issues. However, it is worth noting that in free flight, airspace operation becomes more complex, conflict increases, and safety risk rises. Therefore, it is necessary to analyze and assess the air collision risk of urban logistics UAVs in free flight.
# Physical Layer Definition for a Long-Haul HF Antarctica to Spain Radio Link
## 4 Physical Layer Tests Analysis  
In this section, the details of the concluding analysis for the physical layer definition are explained. A short review of the previous sounding and modulations work done over the same channel for previous campaigns will be summarized in the first section. Afterwards, the channel symbol error  
Figure 7: (**a**) Gain fidelity _vs._ frequency for a given power and (**b**) Gain _vs._ input power for a given frequency. Note that, in both examples, 60 dB must be added to the vertical axis to compensate the attenuator and get the measured gain.  
performance is analyzed, as well as the PN sequence comparison for the best synchronization performance and, finally, all the modulation tests, with both spread spectrum techniques [8] and multi-carrier modulations [18]. The tests presented in this paper were performed over the long-haul channel during several Antarctic campaigns. Table 1 provides the time intervals when the tests were carried out in detail.
# Location-Aware Point-to-Point RPL in Indoor IR-UWB Networks
## 4 Location-Aware P2P-RPL for Indoor IR-UWB Based Network with Self Localization
If a route is not discovered within a timeout period, LA P2P-RPL initiate a new route discovery with the P2P-RPL algorithm. Note that the probability of finding a path (in the first attempt) can be increased by enlarging the size of the initial route forwarding request area. However, the route discovery overhead  
Figure 5: The flow chart of Forwarding Zone based point-to-point (P2P) route discovery. also increases with the size of the request area. There is a trade-off between the latency of route determination and the message overhead.
## 3 Results
### Comparisons of the Average Monthly SD Differences Recorded by Manual and Automatic Devices
The positive differences could be attributed to the fact that the compared pair is located at a distance of about 35 km, where the weather conditions, with respect to the cloud cover, would be probably differ. The lowest negative value was observed in November (\(-6.8\%\)), while during the rest of the months it was around 1%. Positive differences were also observed between the pair Gl and CS for Larnaca during the summer ranging from 2% to 4.5%. The lowest negative difference was recorded in December reaching the value of \(-12.5\%\). In particular, high differences between the selected pairs occurred in the winter period (November to February). The lowest monthly mean daily difference for Gl and CS at Larnaca is \(-0.4\) h/d which is observed in November, while the highest positive mean daily difference is \(0.5\) h/d which was recorded in September (Table 3). At Pafos, for the same pair of instruments, the mean daily difference ranged between \(0.0\) and \(-0.8\) h/d with the lowest occurring in December. Regarding the differences between CSD3 at Mennogia and CS at Larnaca, the monthly mean daily values are negative throughout the year with the lowest average difference of \(-0.6\) h/d which occurred in May and November. Finally, the respective monthly mean daily differences between the pyrhelimetric method (Pr) and CS are again negative, with the lowest average of \(-0.7\) h/d occurring in February  
Figure 7: Percentage difference in daily sunshine duration measured using automatic devices (Gl, CSD3 and Pr) and CS recorders for each of the three study locations. Positive values indicate that the automatic devices measure higher SD than CS, whereas negative values indicate that the automatic devices measure lower values than CS. at Athalassa in the period 2012-2015. The main reason for the larger values of manual sunshine duration is the 'overburning effect' [18; 20]. The burnt area on the card of the CS sunshine recorder does not cease immediately at the moment when a cloud disturbs the sunshine. Furthermore, the types of clouds play important roles. [PERSON] [9] found that, under an overcast sky, higher sunshine durations were observed if the cloud type was Cirrus and Cirrostratus (i.e., relatively thin and high cloud) compared to Stratocumulus and Stratus (i.e., relatively thick and low cloud). The effect of cloud amount and type has to be explored under local conditions.