esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhanced Spectral Amplitude Coding OCDMA System Utilizing a Single Photodiode Detection
## 4 Results and Discussion
### Presence of EDFA Only  
In all optical communication systems, the transmitted optical power is degraded with the transmission distance, leading to the use of optical amplifiers to overcome this degradation. EDFA is an excellent type of optical amplifier to be used. The SAC-OCDMA system using MDW codes with SPD detection technique with a PIN detector in the presence of EFDA showed improvement in BER [13]. It is shown that the system at a bit rate of 622 Mbps with EDFA can transmit over a distance of 70 km with a BER of approximately \(10^{-27}\), while the BER is about\(10^{-24}\) without EDFA at the same distance [22].  
The average BER of three users of the SAC-OCDMA system using EDW codes is displayed in Figure 7 for the APD and PIN without EDFA, and for PIN with EDFA at 622 Mbps and different transmission distances. It is clear that when the PIN is used in the presence of EDFA, and when the APD is used without EDFA, the SAC-OCDMA system has nearly the same BER until50 km. Hence, it is preferable to use the system with the APD instead of the PIN with EDFA for less complexity and lower cost. However, for distances greater than 50 km, it is preferable to use EDFA with the PIN as it provides a better BER than using the APD only.  
The comparison of the eye pattern for one user as a sample (Figure 8) with those shown in Figures 4 and 5 clearly shows that using the PIN detector in the presence of EDFA results in better performance than using PIN or APD detectors alone, with a larger eye opening at 622 Mbps and 100 km.
## 4 Analysis and Discussion
### Testing Phase
In the ILSVRC [37], there is a tendency to improve the model recognition performance by increasing the number of layers of the CNN. However, the experimental results in this paper show that the performance of the network models derived from two network architectures, VGG (VGG11, VGG13, VGG16, and VGG19) and ResNet (ResNet18, ResNet34, ResNet50, and ResNet101) on the GPR B-scan distress image dataset, exhibit different trends, i.e., the performance of the models tends to deteriorate as the number of CNN layers increases, and the best models in the test set are VGG13 and ResNet18. This phenomenon occurs because the GPR B-scan distress images have relatively few features and a small dataset. Therefore, for the dataset in this paper, a network model with relatively few layers should be selected. However, it is important to note that if the number of layers in the model is too small, it may not be able to effectively characterize the distress image features.
# Low-Cost Handheld Spectrometry for Detecting Flavescence Doree in Vineyards
## 3 Results
### Confusion Matrix  
From the confusion matrix of results of 18 test samples (Figure 9A), it can be seen that out of 11 plants suffering from the FD infestation, all are classified correctly, whereas two healthy plants are classified to the class \"Diseased\" wrongly as \"False positive\" out of the seven healthy plants. Considering the results of LOO cross-validation on the whole dataset of 60 samples (Figure 9B), 29 are correctly classified to the class \"Diseased\", whereas four diseased plants are misclassified as \"False negatives\". On the other hand, out of 27 healthy plants, 22 are identified correctly, whereas five plants are misclassified as \"False positives\".
# A Review of Ku-Band GaN HEMT Power Amplifiers Development
###### Abstract

Table 1: Comparison of the electrical properties of major semiconductor materials [8]. Figure 1: Various applications of satellite communications. Figure reproduced from [4]. In line with this trend, research on Ku-band GaN HEMT HPAs has been actively conducted by various research groups worldwide. This paper aims to summarize the current status and major issues related to Ku-band GaN HEMT HPA technology developed in recent years. The paper is organized as follows: In Section 2.1, we compare the processes used to implement Ku-band GaN HEMT HPAs; in Section 2.2, we discuss the two main approaches to implementing HPAs--monolithic microwave integrated circuits (MMICs) and internally matched power amplifier modules (IM-PAMs)--and examine their respective high-power design strategies and key issues. In Section 2.3, we review research on additional performance enhancements beyond high power, and finally, we provide conclusions.
## 3 Results
### Preliminary Structural Features of CFPS
#### 3.2.3 Macromolecular Characteristics of CFPS  
The CPFS fraction was analyzed using both HPSEC-RID and SEC-MALS. The Mw and Mn of CFPS were 1.82 \(\times\) 10\({}^{5}\) and 4.68 \(\times\) 10\({}^{4}\) g.mol\({}^{-1}\), respectively, with a significant polydispersity index value (3.89), highlighting the partial heterogeneity of CFPS (Table 2), which was consistent with the presence of pectin materials, glucuronides, and glycosides. These values were in the same range as those found for water-soluble polysaccharides extracted from Ranunculaceae such as _Aconitum coreanum_ (340 kDa) [42]. The intrinsic viscosity [n] and hydrodynamic radius (Rh) values, which are used for understanding the rheological behavior of hydrocolloids in solutions, were 165 mL/g and 21 nm, respectively, for CFPS. As described in the literature, these values depend on the molecular weight and the conformation of polymer chains in solvents [43]. The critical concentration C\({}^{*}\), defined by 1-4/[n], can be theoretically estimated as ranging from 0.61% to 2.42% (\(w/v\)).  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \(\mathbf{M_{m}}\) * (g/mol) & \(\mathbf{M_{a}}\) * (g/mol) & \(\mathbf{D^{*}}\) & \(\mathbf{Rh}\) * (nm) & [n]* (m/g) & & & & & \multicolumn{3}{c}{**Monosaccharides \({}^{\prime}\) (mol\%)**} \\  & & & & & & & & & & & \\  & & & & & & & & & & \\ \(1.82\times 10^{5}\) & 4.68 \(\times 10^{4}\) & 3.89 & 21 & 165 & 16.1 & 3.55 & 6.15 & 5.49 & 19.1 & 41.5 & 5.08 & 3.02 \\ \hline \hline \end{tabular}  
* Analyses were run in duplicate, and the relative standard deviations were less than 5%. a Mw: weight-average molecular weight was measured by HPSEC. b Mn: number-average molecular weight was measured by HPSEC. c D: polydispersity index Mw/Mn. d Ik: hydration radius was determined by SEC-MALS. e [n]: intrinsic viscosity was determined by SEC-MALS. f Monosaccharide composition was determined by GC/MS-EI. Glc: glucose, GalA: galacturonic acid, Gal: galactose, Ara: arabin, Rha: rhamnose, Me-Hexp: methyl-hexopyranose.  
\end{table}
Table 2: Characterization of CFPS fraction extracted from _Clematis flammula_.  
Figure 1: ATR-FTIR spectrum of CFPS.
## 3 Results and Discussion
### Tolerance to High-Strength Ammonium  
The capacity for high-strength ammonium removal by strain F19 was evaluated using initial ammonium concentrations of 30, 50, 100, 400, 800, 1000, and 2000 mg/L as the sole nitrogen source. As shown in Figure 5A, a significant decrease in ammonium removal was observed at 30, 50, and 100 mg/L, with corresponding removal efficiencies of 96.34%, 78.24%, and 70.96%, respectively. The corresponding maximum removal rates were 0.60, 0.81, and 1.46 mg/L/h, respectively. With higher initial NH\({}_{4}\)\({}^{+}\)-N concentrations of 400, 800, 1000, and 2000 mg/L in the media, ammonium removal efficiencies were 56.38%, 34.02%, 30.18%, and 16.87%, with average removal rates of 4.05, 5.74, 6.79, 8.27, and 7.92 mg/L/h, respectively. Notably, this ammonium removal performance was comparable to that of _Bacillus methylotrophicus_ L7 and _Bacillus_ strain N31 [30; 31], suggesting that F19 has a high ammonium tolerance and moderate removal effectively. Previously, reports speculated that a high concentration of free ammonia can be caused by increasing pH, resulting in poor removal efficiency of high-strength ammonium [38]. However, analysis of the pH effects on the ammonium removal efficiency of strain F19 showed that alkaline pH was conducive to heterotrophic nitrification with high removal efficiency. Therefore, high-strength ammonium load inhibits heterotrophic nitrification activity, resulting in low removal efficiency [38]. Accumulation of nitrate was positively correlated with the concentration of initial ammonium; as the ammonium concentration was increased from 30 to 2000 mg/L, the NO\({}_{3}\)\({}^{-}\) concentration was significantly increased from 1.91 to 12.81 mg/L (Figure 4B). Additionally, accumulation of nitrite was almost unaffected by ammonium-N concentration. Strain F19 achieved a high removal rate of 100 mg/L ammonia (>70.96%), which is of great significance to practical applications in sewage treatment, including remediation of aquaculture water, general effluents, domestic sewerage, and other wastewater containing lower levels of ammonia.
# Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms +
## 3 Hard SyDR
### Envisioned Architecture  
With Hard SyDR, we aim for an architecture resembling that shown in the PL section of Figure 4a. We model this architecture after the structure of C SyDR but introduce several changes, especially to the top-level interfaces: where C SyDR itself can read and write data files, Hard SyDR requires a PYNQ driver to handle this. It is possible to allocate buffers in main memory and pass around pointers to these for the PL to access, but interfacing the PL through Direct Memory Access (DMA)-based AXI-stream transfers is usually more efficient, especially for large, contiguous chunks of data like the RF signals used in SyDR. As such, the aforementioned channel manager uses two such stream interfaces for input and output streams. Additionally, the channel manager hosts an input buffer, which is sized to match the data needs of the acquisition stage's coherent/non-coherent integration range, and an output buffer, which stores just one response from each channel to be returned once their processing is finished.  
The channels shown are independent but identical, i.e., they track different satellites starting from the same point in the RF signal till they have acquired a signal and its offset. This renders them highly suitable for operator or function reuse to avoid unnecessary duplication, but may prevent using a single input buffer due to expectedly irregular memory accesses. The former implies a potential for design space exploration to identify the best area-latency trade-off--or receiver architecture--taking the channels' concurrency into account. For example, given its infrequent use, one acquisition stage may be sufficient for a handful of channels. The latter may require some degree of buffer duplication or, at the very least, additional control logic.  
While our initial efforts target an architecture that solely responds to incoming RF data with channel configurations given at time of design-time, we envision being able to control its functionality at run-time using a third AXI-based interface. With the relevant control registers memory-mapped and accessible over this interface, a PYNQ driver can directly write values to them. Alternatively, the interface may transfer instruction-like messages to a top-level control unit responsible for distributing them to the channels.  
Our design implements a finite-state machine behavior, unlike accelerators such as [15]. That is, the design must be able to receive Radio Frequency (RF) data a little at a time and only occasionally, when enough data have been provided, start processing and return one collective response. This differs from the streaming dataflow-oriented design style typically used in HLS flows but may be achieved with properly written code. Moreover, while using and implementing floating-point arithmetic on FPGAs is possible, its resource utilization is usually unreasonably high. As such, we plan to eventually abandon these types in favor of fixed-point alternatives available in AMD's arbitrary precision libraries [38].
# Federated Learning for Secure In-Vehicle Communication
## 4 Experimental Setup
### Evaluation Metrics  
The accuracy, recall (Rec), precision (Pre), and F1-score (F1) metrics are used to evaluate the performance of our models based on True Positive (TP), False Positives (FP), True Negatives (TN), True Negatives (TN) of the confusion matrix [49]. The metrics are presented in Equations (3)-(6) [49; 50; 51]. TP are instances of a specific attack type that were correctly predicted; FP is instances of a particular attack type that were incorrectly predicted; TN is instances of a specific attack type that were correctly identified; and FN is instances of a particular attack type that were missed [50].  
\[\text{Accuracy}=\left(\frac{TP+TN}{TP+TN+FP+FN}\right)\times 100 \tag{3}\]  
\[\text{Precision (Pre)}=\left(\frac{TP}{TP+FP}\right)\times 100 \tag{4}\]  
\[\text{Recall (Rec)}=\left(\frac{TP}{TP+FN}\right)\times 100 \tag{5}\]  
\[\text{F1\_score (F1)}=2\times\left(\frac{Pre\times Rec}{Pre+Rec}\right)\times 100 \tag{6}\]
## 3 Results
### Freeze-Drying and Storage Evaluation  
The results regarding the freeze-drying impact on the particle stability can be observed in Table 3. Comparing the NP size and charge before and after freeze-drying, it is possible to see that the process led to the increase in particle size by ca. 23% of the PDI, indicating that particle aggregation occurred and, therefore, a reduction of the particles' ZP was observed.  
Considering the particle aggregation observed, several cryoprotectants were assayed. As can be seen from Table 4, of the three cryoprotectants tested, only mannitol was a viable alternative. As for sorbitol and glucose, the freeze-drying process originated an aggregated, viscous product that was not suitable for later assays.  
\begin{table}
\begin{tabular}{c c} \hline
**Compound** & **Peaks Identified (cm\({}^{-1}\))** \\ \hline Chitosan & 3320, 1655, 1413, 1374, 1061 \\ TPP & 1210, 1130, 1090, 888 \\ Chitosan–TPP NPs & 3356–3292, 2910, 1657, 1586, 1397, 1100, 1066, 1056, 1028, 890 \\ \hline \end{tabular}
\end{table}
Table 2: Peaks identified for the tested samples in the FTIR assay.  
Analysing the results obtained for the various mannitol concentrations assayed, it is possible to see that the best performance was obtained with 10% mannitol, with the freeze-dried NPs obtained under these conditions being similar (\(p>0.05\)) to the ones obtained before freeze-drying. For the other mannitol concentrations tested, the results obtained showed that NPs lost some ZP, and some particle aggregation was observed.  
When analysing the stability of the viable formulations over 90 days, it is possible to see that in terms of particle size (Figure 3), when freeze-dried in the presence of 10% mannitol, the NPs remained stable up to the 90-day mark with no significant differences (\(p<0.05\)) being observed.  
For the remaining conditions, at 90 days, NPs appeared to be completely aggregated, with particle sizes varying between 600 and 850 nm. Interestingly, up to the 60-day mark, NPs freeze-dried with 2.5% (\(m/v\)) appeared to be stable despite a small increase in size (\(p<0.05\)) being observed immediately after freeze-drying. Regarding the evolution of the particles' charges over the storage time (Figure 4), it is possible to see that for all tested conditions, there was a significant (\(p<0.05\)) drop in ZP.  
Once again, at the 90-day mark, the best performance was obtained in the presence of 10% (_m/v_) mannitol, with a drop of ca. 9 mV being registered, whereas the worst result was observed for the unprotected particles, where a drop of ca. 28 mV was observed, and the ZP at the 90-day mark was \(-\)1.71 mV.
## 3 Methods  
We managed to download all the MODIS 8-day LST raster from the Aqua and Terra satellites, for the years from 01/01/2018 to 31/12/2022, using a custom Google Engine script. The script allows, by setting the geometry of the study area and the selected bands, to collect the MODIS georeferenced images in the timeframe of interest.  
The downloaded data resulted in 229 images from the Aqua satellite and 230 images from the Terra satellite, relating to a polygon that circumscribes the study area with coordinates: [8.998, 44.750], [9.412, 44.749], [9.415, 45.081], [8.998, 45.082], [8.998, 44.750], and with pixels of size equal to 1 km\({}^{2}\).  
For our work, we selected 4 bands:  
* Day Temperature;
* Night Temperature;
* Time day (time of acquisition of the day temperature);
* Time night (time of acquisition of the night temperature).  
Starting from the downloaded images, we developed several MATLAB version 24.2 (R2024b) scripts to harmonize the data, fill voids, and perform analyses. These scripts operated a regression on both ARPA and MODIS data, to derive raster images of air temperature from Land Surface Temperature.  
For the analysis of the data, we divided the workflow into different Tasks (see Figure 7), described as follows.  
1. Task 1--Harmonization of downloaded data;
2. Task 2--Data stack of raster images;
3. Task 3--Fill-missing of the voids in the raster images;
4. Task 4--Interpolation of MODIS LST data at the geographic coordinates of ARPA Monitoring Stations;
5. Task 5--Creation of a table containing MODIS LST data and ARPA Monitoring Stations Tair data averaged over 8-days;  
Figure 7: Workflow diagram illustrating the sequential process for the analysis of MODIS Land Surface Temperature (LST) and ARPA Monitoring Stations’ air temperature (Tair) data, to estimate Tair from satellite data.  
Task 6--Comparison of MODIS LST and Monitoring Stations Tair data;  
Task 7--Linear regression for the estimation of Tair from MODIS satellite data.
# BIM and GIS Applications in Bridge Projects: A Critical Review
## 1 Introduction
This information will be relevant to practitioners who are looking to apply BIM and GIS technologies to their bridge projects. Additionally, developers of BIM and GIS technologies can use this information to develop the next generation of BIM and GIS technologies to overcome the limitations of the current methods. Therefore, the purpose of this study was to review the application and potential capabilities of BIM/GIS technology in different aspects of bridge projects, and to determine the value and implications of these technologies for decision making and management of bridge projects. The vision of BIM/GIS applications for bridge projects would be to aid the development and optimization of new construction processes to reduce project duration, construction cost, site safety and environmental impact of the bridge construction. Additionally, BIM/GIS would seek to optimize operation and maintenance processes using emerging methods such as omnidirectional data acquisition to aid real-time remote condition inspection and data collection. To achieve these visions, there will be a need to develop BIM and GIS standards and formulate standardized bridge design modeling protocols and terms. Section 2 below describes the research methods used in this review while Section 3 presents the analysis in four aspects as follows: (1) planning and design stages, (2) the construction stage, (3) operation and maintenance stage, and (4) information exchange. Section 4 discusses the challenges associated with these four aspects and suggests possible directions for future research. This study analyzed and consolidated the current state-of-the-art on the application of BIM and GIS technologies on bridge projects. This review contributes to the literature by highlighting the limitations of the current BIM and GIS applications on bridge projects. The limitations identified in this review highlight the current research gaps and will contribute to shaping the direction of future research on BIM and GIS applications on bridge projects. Additionally, this review will guide bridge engineering industry practitioners in choosing appropriate BIM/GIS tools for relevant applications on bridge projects.
# Navigation Map Construction Based on Semantic Segmentation and Multi-Submap Integration
## 4 Methods
### Multi-Submap Fusion Mapping Method for Outdoor Environment  
When the AGV traverses a certain distance, the road surface in the actual environment may display varying slopes, making it impractical to fit the entire ground into a single ideal plane. Moreover, loop closure detection and pose graph optimization in relatively large environments can significantly alter the poses of many keyframes, necessitating extensive adjustments to the grid map, which is highly time-consuming. Operations such as reading, modifying, and updating maps for an entire scene may also fail to meet the system's real-time requirements. To address these challenges, a multi-submap approach is adopted to represent relatively large environments. Submaps are created or retrieved based on the robot's current location, while historical maps are stored for future use. Notably, our system transforms the SLAM coordinate system into the Chinese Geodetic Coordinate System 2000 (CGCS2000) [32], allowing the fusion and integration of our maps with any others constructed using CGCS2000 coordinates.
# Empirical Study on 5G NR Cochannel Coexistence
## 5 5G Performance for Industrial Control
### Interference Mitigation through Link Robustness  
We have investigated the use of a more robust link adaptation algorithm for the indoor network in order to achieve resilience against cochannel interference coming from the outdoor coexisting network. We observed that link robustness for both uplink and downlink transmissions in the indoor network helps in mitigating interference effects. Link robustness leads to the selection of lower Modulation Coding Scheme (MCS) values via the link adaptation algorithm. Figure 9 shows that instead of configuring the default Block Error Rate (BLER) target of 10% for HARQ retransmission, as used in all of the above tests, when we set a BLER target of 1% for HARQ retransmission after the initial transmission, we get significantly reduced latency compared to the respective baseline  
Figure 8: Increase in DL latency compared to the respective baseline for unsynchronized TDD pattern (indoors: DDDDUDDDUU, outdoors: DDDDDU) and different indoor/outdoor UE deployment locations. (**a**) Result for only DL interference (near–far interference). (**b**) Result for only UL interference (cross-link interference).  
Figure 7: Increase in DL latency compared to baseline for unsynchronized TDD pattern (indoors: DDDU, outdoors: DDDDUU) and different indoor/outdoor UE deployment locations. (**a**) Result for only DL interference (near–far interference). (**b**) Result for only UL interference (cross-link interference).  
results for both DL and UL transmissions. One downside of configuring a stricter BLER target for HARQ retransmissions is the use of extra radio resources. However, for small packet sizes, as often used in mission-critical traffic, it is not a big overhead and allows significant latency reduction by avoiding the need for retransmissions when encountering interference from coexisting networks. While the link robustness results for the indoor network in Figure 9 are for a synchronized TDD pattern, we have observed similar results when using unsynchronized TDD patterns indoors, as mentioned in Section 5.2.