esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 IEEE 802.15.6: The Key-Enabling Standard for WBANs
### IEEE 802.15.6 Physical Layer
* _PSDU_: It is formed by concatenating the MAC header with the MAC frame body and Frame Check Sequence (FCS). The PSDU is then scrambled and optionally encoded by a BCH code. Figure 6: Radio Frequency Spectrum for WBAN Communications [9]. Figure 7: Physical Frame Format [9]. The PSDU shall be transmitted using any of the available data rates in the operating frequency band. More details on PSDU construction can be found in [9].
## 3 Results and Discussion  
### Fresh and Hardened Properties of Concrete  
Table 6 shows the fresh properties of the concrete. Both concrete mixes met the target slump of \(180\pm 25\) mm. In the case of the C35_O10 mix, the slump decreased by 35 mm after 60 min, which is a significant reduction. Immediately after discharge, the air content met the target of 4.5% \(\pm\) 1.5% for all concrete mixes and only slightly decreased after 60 min.  
Figure 6 shows the compressive strength of each concrete mix as a function of age. C24_O3_E5_G2 exhibited higher strength than C35_O10 from early ages, and it continuously showed higher strength even at 56 and 91 days, i.e., after long-term aging. In general, EPC is favorable for developing early strength, but it has little effect on long-term strength because of its high C3S content and high fineness [33; 34]. In the scope of this study, using EPC and GGBS as binders was found to effectively develop long-term strength. The PC-based superplasticizer was also found to contribute to the development of strength, even though the total amount of binder was smaller than that in C35_O10, because it reduced the unit water content [35].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Mix No.**} & \multicolumn{2}{c}{**Slump (mm)**} & \multicolumn{2}{c}{**Air Contents (\%)**} \\ \cline{2-5}  & **Initial** & **After 60 min** & **Initial** & **After 60 min** \\ \hline C35\_O10 & 195 & 160 & 4.6 & 4.6 \\ C24\_O3\_E5\_G2 & 190 & 180 & 4.6 & 4.5 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Fresh properties of concrete.  
Figure 7 shows the X-ray diffraction patterns of GGBS, OPC, and EPC used in this study. The results confirmed that EPC and OPC were mainly composed of C\({}_{3}\)S(3 CaO-SiO\({}_{2}\)), C\({}_{2}\)S(2 CaO-SiO\({}_{2}\)), C\({}_{3}\)A(3 CaO-Al\({}_{2}\)O\({}_{3}\)), and C4 AF(4 CaO-Al\({}_{2}\)O\({}_{3}\)-Fe\({}_{2}\)O\({}_{3}\)), as mentioned above, and that EPC contained more C\({}_{3}\)S crystals than OPC. GGBS was found to be composed of gehlenite and akermanite.  
Figure 8 shows the CaO/SO\({}_{3}\) and SO\({}_{3}\)/Al\({}_{2}\)O\({}_{3}\) ratios according to the binder type. For C24_O3_E5_G2, the CaO/SO\({}_{3}\) ratio was approximately 55.8% that of C35_O10, whereas the SO\({}_{3}\)/Al\({}_{2}\)O\({}_{3}\) ratio was 137.9% that of C35_O10. These differences arose because the SO\({}_{3}\) content was higher, while the actual CaO  
Figure 6: Compressive strength of concrete with age.  
Figure 7: X-ray diffraction patterns of GGBS, OPC, and EPC.  
content was similar. Previous studies reported that the development of early strength increased as the SO\({}_{3}\) content increased in the range of less than 5% [36; 37; 38].
# Deep Fusion Feature Based Object Detection Method for High Resolution Optical Remote Sensing Images
## 4 Size-Scalable Candidate Region Proposal Algorithm  
In the field of object detection, the traditional methods mostly employ the multi-scale sliding window method, which is an exhaustive search strategy. In order to guarantee the detection speed, only the simple feature of the candidate window can be extracted to be classified, which may lead to higher false detections. Therefore, a good region proposal algorithm plays an important role in the whole object detection process. In addition, since the size of remote sensing images is usually large, the region proposal algorithm needs to be scalable to the large image size. However, the segmentation-based selective search algorithm used in the classical deep learning-based object detection framework R-CNN needs to build a graph model: each pixel of the image acts as a node, and it includes a large number of similarity calculations and adjacent regions. This means that the algorithm needs to maintain many intermediate results, which has a heavy cost in time and in memory. Therefore, it becomes one of the bottlenecks of the whole framework. Besides, when the image size is very large, the problem is particularly critical, and memory is more likely to be insufficient in that case. The BING algorithm is based on the sliding window scoring mechanism with an accelerating optimization, and it is considered to be the fastest region proposal algorithm [25]. Furthermore, when increasing the image size, the speed and the memory usage of the algorithm increase linearly at most, and this is acceptable. In addition, because the candidate windows obtained by the BING algorithm contain probabilistic scores, we can select the appropriate number of candidate windows when necessary.
# GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation
###### Abstract  
Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks.  
GNSS; maximum likelihood estimation; spoofing detection; spoofing mitigation; navigation solution recovery +
Footnote †: journal: Sensors
Future Internet_**2014**, \(6\), 498-517; doi:10.3390/fi6030498  
_future internet_  
**ISSN 1999-5903**  
www.mdpi.com/journal/futureinternet**  
_Article_  
**Assessing Social Value in Open Data Initiatives: A Framework**  
**[PERSON] \({}^{1,\star}\), [PERSON] \({}^{2}\) and [PERSON] \({}^{2}\)**  
\({}^{1}\) Ecole polytechnique federale de Lausanne (EPFL)--CDM MTEI CSI ODY 1 16 (Odyssea) Station 5, Lausanne CH-1015, Switzerland  
\({}^{2}\) Department of Informatics Systems and Communication (DISCo)--University of Milano-Bicocca, U14 Building Viale Sarca, 336, Milano 20126, Italy;  
E-Mails: [EMAIL_ADDRESS] (M.C.); [EMAIL_ADDRESS] (C.B.)  
\({}^{\star}\) Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS] (G.V.); Tel.: + 41-216-930-018; Fax: +41-216-930-020.  
_Received: 4 March 2014; in revised form: 26 May 2014 / Accepted: 4 June 2014 / Published: 19 August 2014_  
**Abstract:** Open data initiatives are characterized, in several countries, by a great extension of the number of data sets made available for access by public administrations, constituencies, businesses and other actors, such as journalists, international institutions and academics, to mention a few. However, most of the open data sets rely on selection criteria, based on a technology-driven perspective, rather than a focus on the potential public and social value of data to be published. Several experiences and reports confirm this issue, such as those of the Open Data Census. However, there are also relevant best practices. The goal of this paper is to investigate the different dimensions of a framework suitable to support public administrations, as well as constituencies, in assessing and benchmarking the social value of open data initiatives. The framework is tested on three initiatives, referring to three different countries, Italy, the United Kingdom and Tunisia. The countries have been selected to provide a focus on European and Mediterranean countries, considering also the difference in legal frameworks (civic law _vs._ common law countries).  
**Keywords:** open data; social value; public value; assessment; classification
# Functionally Graded Plate Fracture Analysis Using the Field Boundary Element Method
## 2 Materials and Methods
### Material Properties  
The material property variation was ascribed to the Elastic Modulus only, i.e., the Poisson ratio was fixed to \(\
u=0.3\). In particular, the elastic tensor varied through a multiplicative scalar field \(\gamma(x,y)\), and fulfilled the following equation:  
\[E=\gamma(x,y)E^{0}\Leftrightarrow C_{ijk}(x)=\gamma(x,y)C^{0}_{ijk} \tag{10}\]  
In the proposed example, only the case of variability along with x and y-directions were considered. The reference of the coordinate system had the origin coincident with the center of the crack, consequently, the analyzed specimen had the origin at the leftmost side. Two variabilities were accounted for:  
1. \(XD\): Young Modulus decreasing in the x-direction with \(\gamma(x,y)=\gamma(x)\) spanning from 8 to 1: \[\gamma(x)=\gamma(0)\;e^{[(\frac{x-x_{1}+\
u}{\overline{\
u}})]nt(\frac{E_{0}}{ \overline{\
u}})]}\] (11)
2. \(X\)C: Young Modulus increasing in the x-direction with \(\gamma(x,y)=\gamma(x)\) spanning from 1 to 8: \[\gamma(x)=\gamma(0)\;e^{[(\frac{x_{1}}{\overline{\
u}})]nt(\frac{E_{0}}{ \overline{\
u}})]}\] (12)
3. \(YD\): Young Modulus decreasing in the y-direction with \(\gamma(x,y)=\gamma(y)\) spanning from 8 to 1: \[\gamma(y)=\gamma(0)\;e^{[(\frac{-x_{1}+\
u}{\overline{\
u}})]nt(\frac{E_{0}}{ \overline{\
u}})]}\] (13)
4. \(YC\): Young Modulus increasing in the y-direction with \(\gamma(x,y)=\gamma(y)\) spanning from 1 to 8: \[\gamma(y)=\gamma(0)\;e^{[(\frac{x_{1}}{\overline{\
u}})]nt(\frac{E_{0}}{ \overline{\
u}})]}\] (14)  
The numerical calculation was performed assuming a plane strain condition with reference Young Modulus equal to \(E^{0}=10^{3}\) MPa, Poisson ratio \(\
u=0.3\), and crack length variation equal to \(\frac{a}{\
u}=0.11,\;0.33,\;0.55\).  
Figures 2 and 3 show the variation of Young Modulus along the x-direction and y-direction. Furthermore, the dark blue and light blue curves indicate the decreasing Young Modulus \((XD)\) and increasing Young Modulus \((XC)\), respectively. In the same manner, dark green and light green curves indicate the increasing Young Modulus \((YC)\) and decreasing Young Modulus \((YD)\), respectively.
# Effect of Wood Densification and GFRP Reinforcement on the Embedment Strength of Poplar CLT
## 4 Conclusions  
This work evaluated the embedment strength of 3-ply poplar CLT samples reinforced with GFRP and densified wood (25% and 50%) in two loading directions (L and T). Overall, reinforcement improved the embedment strength of CLT samples. The embedment strength of CLT samples in the L loading direction (outer layers to the same fiber direction) was greater than those in the T loading direction. CLT samples made from 50% densified poplar wood showed the highest embedment strength (50L: 51.75 MPa and 50T: 47.58 MPa). However, there was no significant difference in embedment strength between CLT samples reinforced with GFRP and CLT samples made from 25% densified wood (25L: 44.8 MPa, GFRP: 44.93 MPa, 25T: 42.52 MPa, and GFRP: 42.08 MPa). Modelling using the NDS formula yielded the highest accuracy (MAPE = 10.31%), followed by the [PERSON] and [PERSON] (MAPE = 21%), [PERSON] (MAPE = 28.86%), CSA (MAPE = 32.68%), and Dong (MAPE = 40.07%) equations. Densification can be considered as an alternative to GFRP reinforcement in order to increase the embedment strength in CLT. Statistical analysis showed that in terms of main effects, densification ratio and loading direction significantly affect the embedment strength. However, in terms of interaction effects, both densification ratio and loading direction at the same time had no significant effect on the embedment strength.  
Further studies are recommended to evaluate the embedment strength of CLT reinforced with GFRP and densified wood made of more than three layers. Further studies are recommended to evaluate the embedment strength of various types of nails and screws in CLT reinforced with GFRP and densified wood. According to the results of this study, considering the cost of the products, 25% densification might be used instead of GFRP for CLT reinforcement. However, further investigations regarding the effects of densification on CLT properties, such as bending, glue line, and debonding, are required.  
Conceptualization, A.R.-H. and M.A.; methodology, A.R.-H. and M.A.; formal analysis, A.R.-H., F.A. and M.A.; resources, A.R.-H., F.A. and M.A.; writing--original draft preparation, F.A.; writing--review and editing, A.R.-H., V.N. and F.A.; visualization, F.A., supervision, A.R.-H. and M.R.; project administration, A.R.-H., V.N. and M.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**MAPE (\%)**} \\ \hline Ubel and Blab & Kennedy & Dong et al. & NDS & CSA \\ \hline
21.30 & 28.86 & 40.07 & 10.31 & 32.68 \\ \hline \hline \end{tabular}
\end{table}
Table 5: MAPE of equations for predicting embedment strength of CLT specimens.
## 4 Results and Discussion
### Complexity Analysis  
Another important issue to analyze is the complexity of the novel ELM. The complexity of the equalization process directly determines the implementation cost of the CO-OFDM scheme with respect to the power consumption and needed hardware. Following the procedure used in studies about ELMs for equalizing OFDM signals [21; 24], we develop a comparison of the complexity for the five methods (PAE, R-ELM, C-ELM, RC-ELM, and CPE compensation) in terms of the training, testing, and total times elapsed in the phase-noise correction stage, where the OFDM demodulator would expose modifications in its realization. At the same time, this complexity-evaluation form is usually adopted in standard and modified ELMs [10; 18; 19; 41]. Training and testing phases only make sense when artificial neural networks are employed. In the OFDM transmitter, the in-phase and quadrature components of the reference tones depend on the adopted equalizer as mentioned above; nevertheless, any configuration of the pilots demands the same computational time. By considering the QPSK signaling affected by a combined linewidth of \(4\) MHz without AWGN for demonstration purposes, \(100\) trials are carried out and, then, the mean results expressed in seconds are illustrated in Table 3. The CPE compensator is faster than all other techniques. It however necessitates an extra preamble for each OFDM packet for equalization purposes, which is not included in the system model. Consequently,the fully-complex ELM only formed by 2 hidden neurons consumes the minimum resources. On the contrary, the processing time of the R-ELM is the longest due to its composition: two real-valued ELMs of 10 hidden nodes each. Compared with the C-ELM, the augmentation for the benchmark PAE and introduced ELM in the CPU time is near to 1.4 and 2.8 times, respectively. The computational cost of the RC-ELM is expected by the consideration of the regularization parameter as well as the architecture characterized by 24 hidden nodes in order to the BER minimization. Regarding the ELM algorithms, the computational time for learning is higher than the testing step. It may be explained by the Moore-Penrose generalized inverse of the hidden layer output matrix that requires the training phase (see Section 3). The previous observations are obviously software/hardware dependent. A MATLAB R2018a environment running in an Intel Core i5 processor at 2.6 GHz clock speed and 4 GB RAM is used.
## 3 Data and Methods
### SPOT6/7 Satellite Data  
The SPOT6/7 satellites, launched in 2012 and 2014, offer high-resolution optical satellite imagery with a stereo and tristereo capacity. We work with a clip of a SPOT6 stereo triplet that covers an area of \(\sim\)2700 km\({}^{2}\) (Figure 2A). All images were acquired from a single pass on 13 April 2014 and come as 12-bit panchromatic (PAN) scenes with a ground resolution of 1.5 m. The scenes are corrected for radiometric and sensor distortions but have not undergone any geometric correction or orthorectification (Level 1A format). To carry out the geometric correction autonomously, the user is provided with a set of Rational Polynomial Coefficients (RPCs). These replace a physical sensor model through a mathematical model that allows mapping the image-to-ground coordinates without revealing the intrinsic parameters of the sensor [22]. However, we do note that SPOT6/7 data are delivered with a rigorous sensor model in addition to RPC data [33], but only the RPCs can be read by the ASP, and these are the most general method of geometric correction for satellite data (e.g., WorldView, GeoEye, Planet). The stereoscopic acquisition mode of the SPOT6/7 satellites collects two or three images from different viewpoints which allows us to reconstruct the terrain through stereogrammetry. The acquisitions (herein labelled as scene A, B, and C) used in this study have the following along-track angles: A = \(-\)14.96\({}^{\circ}\) (southward view); B = 0.3\({}^{\circ}\) (near-nadir view); and C = 15.8\({}^{\circ}\) (northward view). With the satellite flying at a height of 694 km, the Base/Height (B:H) ratio for the AB and BC pair is \(\sim\)0.25 and \(\sim\)0.5 for the AC pair (Figure S1). The optimum B:H ratio for generating DEMs depends on the relief of the captured area. An increased B:H ratio is beneficial for matching large flat areas with little topography. Smaller B:H ratios reduce the ability to measure parallax between two features but also reduce the risk of having hidden areas in steep terrain. Greater similarity of the images from smaller B:H ratios can furthermore aid the stereo-matching process [33].
# Wideband-Narrowband Switchable Tapered Slot Antenna for Breast Cancer Diagnosis and Treatment
## 4 Discussion  
In this paper, a frequency switchable tapered slot antenna with a meander line resonator was proposed. The wideband TSA operates in the UWB (3.1-10 GHz) for microwave imaging. A compact meander line resonator with band-pass characteristics was designed and printed on the back of the TSA to minimize the degradation of the wideband characteristic and the additional frequency response at 2.45 GHz for hyperthermia. By positioning the meander line beneath the flared slot, which was propagating the area of TSA, the maximum EM energy transfer between the flared slotline and the meander line resonator was achieved. Frequency switchable characteristics were made possible because of a PIN diode switch. Simulated and measured results demonstrated that the proposed TSA operated selectively in different modes at two different frequency bands. For hyperthermia, the designed antenna exhibited effective EM energy concentration with a thermal treatment  
Figure 16: (**a**) Comparison of normalized SAR in terms of the number of antennas along the x-axis of the breast phantom, and the (**b**) measured temperature distribution inside the breast phantom with 12 antennas.  
Figure 15: (**a**) Configuration of the temperature measurement setup, and (**b**) block diagram of the temperature measuring system.  
effect. The time-domain analysis was also conducted to demonstrate the antenna's microwave imaging capability. Consequentially, the proposed TSA was expected to be useful in the integrated biomedical system.  
Data curation and writing--original draft preparation, S.L.; writing--review and editing, S.L. and Y.J.Y.; supervision, Y.J.Y. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions.  
This paper was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1A2C1005764).  
The authors declare no conflict of interest.
# PELM: A Deep Learning Model for Early Detection of Pneumonia in Chest Radiography
## 4 Results
### Model Performance
Compared to previous studies, the proposed ensemble model PELM exhibits superior and more balanced performance in pneumonia detection using chest X-ray images. Earlier works, such as [PERSON] et al. [31] and [PERSON] et al. [33], reported high precision scores (0.98 and 0.90, respectively) and recall values reaching 0.95; however, these studies were limited by relatively small datasets and incomplete metric reporting, notably omitting specificity and AUC. [PERSON] et al. [34] achieved a strong recall of 0.96 but reported lower accuracy (0.90) and F1-score (0.92), which may impact clinical reliability. Similarly, [PERSON] et al. [35] obtained 95% accuracy using DenseNet121 and ResNet50 on a large-scale dataset, but with a notably low specificity of 0.71--reducing its effectiveness in real-world screening scenarios. More recent models proposed by [PERSON] et al. [5], [PERSON] et al. [37], and [PERSON] et al. [28] demonstrated improved balance across metrics, with F1-scores ranging from 0.93 to 0.94. In contrast, PELM outperformed all these approaches by achieving 96% accuracy, 99% precision, 91% recall, 95% F1-score, 91% specificity, and an AUC of 0.91--validated on a substantially larger and more diverse dataset comprising 44,836 CXR images. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  
These results underscore the robustness and generalizability of the PELM architecture, as well as its clinical potential for scalable, accurate, and real-time pneumonia detection in diverse healthcare environments.
## 3 Results and Discussion
### Desorption Experiments  
After adsorption, the used adsorbents can be disposed of or regenerated; in both cases, there will be secondary pollution. Metal-loaded, used adsorbents are toxic for humans and the environment. In regeneration, metals are recovered in the solution form, and secondary pollution is caused by the regeneration solution [1]. Therefore, the regeneration solution used plays an important role, and the use of non-hazardous regeneration solutions is preferred. The regeneration solutions typically used are HCl [49,50], H\({}_{2}\)SO\({}_{4}\)[36], 1 M KCl [35], 0.01 M NaNO\({}_{3}\)[51], and NaCl [52]. The regenerability of adsorbents is vital to enable cost-efficiency. In this study, Zn desorption was done using 0.1 M HCl; the results of the desorption experiments are presented in Figure 10. The desorption occurred immediately after the used adsorbent came into contact with the desorption solution. The desorption percentage was 80%, which was not related to the time. Therefore, it is possible to regenerate biomass-based carbon quickly using non-hazardous chemicals.  
Figure 10: Desorption [%] as a function of time [min].  
Figure 9: Van’t Hoff plot of zinc (Zn) sorption on the biomass based activated carbon.