esa-sceva/satcom-chunk-collection huggingface dataset:
# Progressive Pruning of Light Dehaze Networks for Static Scenes
## 3 Methods
### Implementation Details  
Our fine-tuning process for static scenes involves training the model for 1000 epochs using an Adam optimizer with a learning rate of 0.00001. The model is trained on scene-specific data from fixed camera viewpoints, allowing it to optimize for particular environmental characteristics. We denote the models finetuned on 01_outdoor, 02_outdoor, and 03_outdoor as f1, f2, and f3, respectively. After applying our pruning strategy to these fine-tuned models, we refer to the resulting pruned versions as pruned f1, pruned f2, and pruned f3.  
We specifically chose layer 7 for pruning as it contains the highest number of channels (32) in our network architecture, providing the greatest potential for model compression while our preliminary experiments indicated that pruning this layer had less severe impact on performance compared to earlier layers. For the pruning process, we evaluate two pruning ratios: 10% and 60%. The 10% pruning configuration maintains 29 channels inlayer 7, representing a conservative pruning approach that preserves most of the network's capacity while achieving initial compression. The 60% pruning configuration reduces layer 7 to 13 channels, demonstrating our method's effectiveness even under aggressive compression. Channel selection for pruning is based on our importance metric (Equation (1)), which considers both PSNR and SSIM(Structural Similarity Index Measure) degradation when removing specific channels.  
While our experiments focused on layer 7, this pruning methodology can be generalized to other layers or network architectures. The importance metric and progressive pruning strategy are architecture-agnostic and can be applied to any convolutional layer where channel reduction is desired. This generalization capability makes our approach adaptable to various network structures and different degrees of compression requirements, offering flexibility in balancing computational efficiency and dehazing performance across different deployment scenarios.
# A Study of Network Intrusion Detection Systems Using Artificial Intelligence/Machine Learning
## 8 Discussion
### Future Trends
#### 8.3.3 Detecting Encrypted Traffic  
Few solutions have proposed a way to detect encrypted traffic. However, nowadays almost everything is encrypted, and hackers are also using encryption to forward attacks. Thus, there is a need to find an efficient way to detect abnormal traffic from encryptedtraffic. As discussed in Section 6, all the solutions were tested using public datasets. However, those datasets are not properly representing our networks of today where a significant amount of the data is encrypted. New solutions to extract important features from encrypted traffic are required to detect abnormal instances.
# Process-Aware Enactment of Clinical Guidelines through Multimodal Interfaces
## 6 Related Work
### Vocal Interfaces
Similarly, following the direction of tele-home health care, authors in [85] examined the use of voice as a means for obtaining patients' emotions while being monitored remotely, which is a context where even a higher level of skills, professionalism, and competence is needed with respect to an in-person visit. Here, authors pointed out that detecting patients' emotions using the voice could be even more accurate, as patients themselves find difficulties to express precisely their own state of feeling, and therefore emphasized the importance of developing such multimodal intelligent effective interface. A similar work was conducted in the field of psychopathology [86], where clinical diagnosis of major depression cases was applied using facial expressions and voice analysis to help automatic detection of depression whose assessment is usually based on classical reports (e.g., clinical interviews and questionnaires). Authors in [87] discussed the employment of robots in healthcare structures (e.g., hospitals), and proposed to apply vocal interaction with robots moving around the healthcare center, for better and efficient execution of tasks in such environments. In their work of presenting multimodal integration of continuously spoken language and continuous gesture, authors in [88] included in their prototype an example of medical informatics in which users (patients in this case) can search using speech and gesture for available healthcare providers on a map of their zone. The multimodal input in this prototype is translated into a query that is executed on the database of all healthcare providers (e.g., doctors) in the selected area, and retrieve back results that can be then showed directly on the map. In the attempt of establishing a health-aware smart home that serves as an intelligent space assisting elderly and users with special needs in their daily life activities, authors in [89] argued that voice interfaces can be helpful as they do not require to be worn or to be spatially close to any device. In the context of navigational assistance for surgical interventions, authors in [90] developed a prototype that uses virtual reality together with a multimodal interface (including vocal input) and an expert system that helps to infer context in order to provide support for surgeons, either in a process simulation or in a realistic intervention, and for both training and clinical purposes. Our work can be positioned in this research context, where the introduction of a mobile application, which supports conducting the needed related clinical guidelines while providing a multimodal interaction with a vocal interface, can lead to significant benefits for both patients and clinicians. These benefits can be easily noticed when clinicians working with these IT systems use the vocal input in a hands-free mode, which in turn allows for conducting the healthcare tasks easier and faster in such environment and helps medical staff while they physically examine their patients in order to improve the overall clinical performance.
## 3 Results and Discussion
### Fourier Transform Infrared Spectroscopy (FTIR) Analysis  
The doping of nitrogen into the titania lattice was further confirmed by the FTIR spectra. The FTIR spectra of all as-prepared samples are shown in Figure 4. The complete spectrum is shown in Figure 4a, whereas the enlarged view of regions between 750-2000 cm\({}^{-1}\), and 2000-4000 cm\({}^{-1}\) are shown in Figure 4b,c, respectively. The transmittance peaks for pure TiO\({}_{2}\) can be observed within range of 1100-1200 cm\({}^{-1}\) and is associated to the stretching vibrations of Ti-O and Ti-O-Ti bonds in the TiO\({}_{2}\) lattice (Figure 4b). The peaks observed near 1636 cm\({}^{-1}\) (Figure 4b) and 3440 cm\({}^{-1}\) (Figure 4c) corresponds to the bending and stretching vibrations of the O-H bond related to the absorbed water molecules [47; 48]. For all NT samples the transmittance peaks are observed appearing in the ranges of 1000-1100 cm\({}^{-1}\) (Figure 4b), and 2800-3000 cm\({}^{-1}\) (Figure 4c). The two peaks appearing in the first region at 1040 and 1090 cm\({}^{-1}\), can be attributed to the interstitial N-O bond and Ti-O-N bond, respectively [32; 49]. However, the peaks observed in the second region are probably due to the presence of C-H stretching vibrations because of organic species from the synthesis precursors during calcination [32].
# GNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques
## 6 Field Data Analysis
### Static Test  
A Trimble R10 GNSS receiver (Trimble Inc., Sunnyvale, CA, USA) was used to collect GPS L1, L2C and L5 measurements. Figure 4 shows the equipment, its location on a rooftop near reflective surfaces, and the available satellite geometry during the test. The antenna location was pre-surveyed and tied to the International Terrestrial Reference Frame 2013 (ITRF) to derive position error results in Section 6.1.2.  
Figure 3: Combination of monitoring techniques in two cascading approaches, (**a**) a preceding CMC-based error correction followed by a GF-based multipath detection and exclusion (or de-weighting), and stochastic weighting, (**b**) a preceding multipath detection (for exclusion or de-weighting) followed by a CMC-based error correction and stochastic weighting.
## 3 Results and Discussion  
### Characteristics of the HPS  
The synthesis of submicron s-HPS employed the bottom-up strategy as depicted in Scheme 1 and the respective FTIR spectrum was shown in Figure 1. Initially SiO\({}_{2}\)-MPS seed particles with diameters of 100-150 nm were synthesized using the Stober process [26, 27]. The FTIR absorption spectrum of the SiO\({}_{2}\)-MPS particles shows a peak at 1630 cm\({}^{-1}\) (Figure 1a), which corresponds to the double bond (vinyl groups) stretching of the MPS units attached to the SiO\({}_{2}\) microspheres. This peak shows a shoulder at about 1730 cm\({}^{-1}\) representing the carbonyl group. Vinyl groups on the surface ofSiO\({}_{2}\)-MPS microspheres then served as anchor to the radical chains produced in the solution upon polymerization, and the accompanying distillation drove the interfacial grafting to generate the SiO\({}_{2}\)-P(St-DVB) core-shell microspheres. The spectrum (Figure 1b) proves realization of this structure according to benzene ring stretching at 1500 cm\({}^{-1}\), aromatic C-H stretching at 3010 cm\({}^{-1}\) and the main chain C-H stretching at 2900 cm\({}^{-1}\). The subsequent sulfonation introduced -SO\({}_{3}\)H groups to benzene rings in the P(St-DVB) shell. The characteristic double S=O stretching peaks at about 1041 and 1180 cm\({}^{-1}\) could be observed only after silica core was removed since the broad -Si-O-Si- symmetric stretching peak appears at 1000\(\sim\)1200 cm\({}^{-1}\) (Figure 1b).  
Figure 2 shows the TEM image of the core-shell structures of the SiO\({}_{2}\)/P(St-DVB) and SO\({}_{2}\)/P(MAA-DVB) spheres. The resultant core-shell microspheres of both types had a 20-30 nm thick shell. Hollow polymer spherical structure with two types of functional groups, -SO\({}_{3}\)H (s-HPS) and -CO\({}_{2}\)H (c-HPS), were securely retained after the silica core was removed. It is noteworthy that the P(St-DVB) must be sulfonated in the presence of SiO\({}_{2}\) core in order to etch the SiO\({}_{2}\) core more readily and to avoid splintering of the P(St-DVB) shell while it is sulfonated. The hollow structures of the s-HPS and c-HPS spheres exhibited well-defined capsular structure and an integrity shell. Also, the sufficiently high DVB crosslinking extent assured a free-standing shell and prevented severe agglomeration among HPS of both types.  
Figure 1: (Fourier Transform Infrared Spectroscopy) FTIR spectra: (**a**) 3-(trimethoxysilyl) propylmethacrylate (MPS) modified SiO\({}_{2}\) seeds; (**b**) SiO\({}_{2}\)-P(styrene-divinylbenzene) (SiO\({}_{2}\)-P(St-DVB)) core-shell spheres; (**c**) the sulfonated SiO\({}_{2}\)-P(St-DVB) spheres; and (**d**) s-HPS.
## 4 Conclusions  
Molecular dynamics simulations were used to investigate crystal nucleation and growth of NaCl in membrane-assisted crystallization. The results were compared with a bulk NaCl solution at the same concentration. In parallel, membrane crystallization tests were performed utilizing the same polymeric membranes in order to compare experimental results with the computational ones. Additionally, the comparison in terms of nucleation time between the crystallization of sodium chloride using the traditional evaporation process and the membrane-assisted crystallization process was performed.  
The analysis of shape and growth of crystals indicated the formation of smaller and regularly structured face-centered cubic lattice NaCl crystals when the solution was in contact with PVDF and PP membrane surfaces in comparison with that obtained from the bulk solution, where fewer and larger crystals were visible, suggesting a more controlled nucleation and higher growth of the crystals.  
The integrated experimental-computational approach showed that both polymeric surfaces speeded up crystal nucleation in comparison with the bulk solution, confirming the experimental results and thus resulting in a reciprocal validation and in useful correlations between MD and the experimental analysis.  
These preliminary simulations provide the stimuli to investigate other mono and bivalent crystals and related mixtures in view to predict crystallization with different complex polymeric matrices [67].  
[PERSON]-[PERSON] performed the simulations and carried out the data analysis. [PERSON] contributed to data analysis. [PERSON] performed experimental tests. [PERSON], [PERSON], [PERSON], and K.-L.T. contributed to Review & Editing. [PERSON] devised the study, wrote the paper with input from all Authors. The bilateral CNR/MoST Italy/Taiwan project \"Advances in membrane contacts: from material to process\" is gratefully acknowledged.  
[PERSON] gratefully acknowledges the support given for the simulations. The authors declare no conflict of interest.  
Figure 9: Density profile along the z axis of the PVDF membrane system at (**a**) 5 and (**b**) 100 ns of simulation. At 100 ns, the region with a reduction in the water density profile and an increase in the ions’ density profile is highlighted (grey area).
## Pulse Compression of Ultrashort UV Pulses by Self-Phase Modulation in Bulk Material  
**[PERSON], [PERSON] and [PERSON] ***  
Lehrstuhl fur BioMolekulare Optik, Ludwig-Maximilians-Universitat Munchen (LMU),  
80538 Munchen, Germany; E-Mails: [EMAIL_ADDRESS] (N.K.);  
[EMAIL_ADDRESS] (I.P.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +49-89-2180-9210; Fax: +49-89-2180-9202.  
_Received: 21 December 2012; in revised form: 5 February 2013 / Accepted: 6 February 2013 / Published: 8 February 2013_  
**Abstract:** The bandwidth of ultrafast pulses in the UV is limited by the finite acceptance bandwidth of the nonlinear crystals used for their generation. For fundamental laser pulses it is well established that spectral broadening can be used to overcome intrinsic bandwidth limits. We show that self-phase modulation of UV pulses in bulk materials leads to large spectral broadening and allows for a significant reduction of the pulse duration. We find that for pulse energies in the range of a few \(\upmu\)J, a thin crystal is favorable due to the strong dispersion in the UV and the limitations set by self-focusing. In contrast to spectral broadening in gaseous media, the self-focus has to lie outside the crystal to avoid beam break up. We focus UV pulses into a 1 mm thick CaF\({}_{2}\) crystal. For moderately short input pulses, a shortening factor up to 2.4 is achieved: the 120 fs long third harmonic output of a Ti:sapphire amplifier is compressed down to 50 fs FWHM. For a central wavelength of 315 nm, we generate pulses as short as 14.9 fs after compression with an UV pulse shaper. In both cases the resulting beam shape is close to Gaussian and fully usable for spectroscopic experiments. We use the pulses in a collinear 2D-UV experiment and clearly resolve vibronic off-diagonal peaks of the S\({}_{2}\)\({}^{1}\)B\({}_{2u}\) vibronic progression of pyrene.  
**Keywords:** ultrashort optical pulses; ultraviolet; UV; self-phase modulation; pulse compression
## 3 Results and Discussions
### Wall Heat Flux and Pressure  
The wall heat fluxes for the three freestream conditions obtained by different thermochemical models and the perfect gas model are compared in Figure 7. The comparison reveals that there is a significant difference between the wall heat flux of chemical reaction gas and that of perfect gas, and the former can be greater than (\(Ma\) = 29.05), or close to (\(Ma\) = 34.34), or even less than the latter (\(Ma\) = 38.94).  
Figure 7 also shows that the differences between the wall heat fluxes predicted by different thermochemical models are small. The wall heat flux of the two-temperature model is always greater than that of the one-temperature model. The Gupta model always gives most conservative results of wall heat transfer compared to the Dunn-Kang and Park models.  
The effects of different models on the wall pressure for the three cases are compared in Figure 8. Compared to the wall heat transfers, the wall pressures of different thermochemical models are more consistent, including the result of perfect gas. According to Figures 4 and 8, it can infer that the different thermochemical models have little influence on the pressure prediction of the hypersonic shock layer. However, such small differences between the wall pressure results of different models still might be amplified by multiplying the displacement in the pitch moment calculation for the hypersonic vehicle, which requires the further investigation using a complex configuration with the angle of attack.  
Figure 8: _Cont._  
Figure 7: Wall heat fluxes for three cases calculated by different models.
## 7 Conclusions  
To investigate the features of various shallow subsurface layers, seismic refraction tomography for P- and S-wave measurements was used. The main important strategic objectives of this research were to calculate the geotechnical properties, elastic moduli, degree of competence, and petrophysical characteristics of the soils/rocks in this significant archaeological site in addition to inferring the subsurface lithology. Seventeen shallow seismic refraction profiles were implemented at the studied site. The main results of this work revealed the following:  
1. Three geoseismic layers were deduced according to the vertical and the horizontal variation in the velocities for both P- and S-waves. The lithologies of these three layers from the top to the base were (i) wadi deposits, which were made up of a mixture of gravel, sand, and silt that were distinguished by incompetent to slightly competent materials, a relatively high porosity ratio, and a larger portion of voids; (ii) sand and muddy sand deposits of reasonably to moderately competent rock quality, intermediate porosity, and greater competence than the top layer; and (iii) clay deposits of competent materials, lower void ratio, and porosity materials.
2. The thicknesses of the two successive near-surface layers varied between 1.5 and 4.8 m for the first layer and 14.7 to 35 m for the second one.
3. The site was categorized as a \"B\" site class according to NEHRP classification.
4. According to the interpretation of seismic wave velocities and the final geoseismic models, there was no fracturing or faulting in front of the Osirion site.  
This study recommends that all the deduced factors primarily serve as important inputs for all future facilities and have an impact on the seismic risk estimation, structural design, and ranking of the site competency for development and investment purposes at the site.  
Conceptualization, A.M.A. and G.Z.A.A.; methodology, N.F.A., A.M.A.G. and M.A.M.; software, N.F.A., A.M.A.G. and M.A.M.; validation, A.M.A., G.Z.A.A. and M.A.M.; formal analysis, N.F.A. and M.A.M.; investigation, A.M.A.G. and M.A.M.; data curation, N.F.A. and A.M.A.G; writing--original draft preparation, N.F.A., A.M.A.G. and M.A.M.; writing--review and editing, N.F.A., A.M.A.G. and G.Z.A.A.; visualization, A.M.A.G. and M.A.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Science, Technology, and Innovation Funding Authority (STIFA) of Egypt, grant number 37087.  
The data is available upon request from the authors.  
The authors are thankful to the Science, Technology, and Innovation Funding Authority (STIFA), Egypt, for funding this work (ID number: 37087).  
The authors declare no conflict of interest.
## 5 Results and Discussions  
### Calibration Experiment  
In the calibration experiment, the detected pulse irradiation timings were \(t_{1}=0\) ms and \(t_{2}=1.0\) ms. The calculated time delay \(t_{p}\) based on the pulse irradiation timings was determined to be \(t_{p}=t_{2}-t_{1}\)= 1.0 ms. The PA signals were extracted based on the pulse irradiation timings \(t_{1}\) and \(t_{2}\), and CC analysis was applied to the extracted signals. The peak of the CC coefficient was determined at a time shift \(t_{s}=-0.0040\) us. The relevant parameters employed in the calculations were \(\theta=30^{\circ}\) and \(c=1.5\times 10^{6}\) mm/s at 22 \({}^{\circ}\)C. Based on Equation (2), the velocity of the stationary object was evaluated as  
\[v_{0}=\frac{t_{s}c}{t_{p}\cos\theta}=\frac{1.50\times(-0.0040)}{1.0\times 10^{-3 }\times\cos 30^{\circ}}=-6.9\text{ mm/s}. \tag{7}\]  
The ensemble average of 10 samples measured for the stationary case yielded an average velocity of \(v_{\text{avg}}=-3.4\) mm/s. The standard deviation (SD) of the PA velocity measurements was calculated as \(\sigma_{v_{0}}=5.0\) mm/s. The velocity resolution was limited by the sample rate of the digitizer of the measurement instrument, i.e., the oscilloscope. Under the experimental conditions, the minimum measurable velocity \(v_{\text{lim}}\) was calculated as \(v_{\text{lim}}=\pm 3.4\) mm/s by substituting the sampling interval of the measurement instrument \(t_{s}=0.002\) us into Equation (2). Theoretically, \(v_{\text{avg}}\) is 0 mm/s in the stationary case. However, in the experiment, the velocity measured for a stationary object (\(v_{\text{avg}}=-3.4\) mm/s), was within the minimum measurable velocity (\(v_{\text{lim}}=\pm 3.4\) mm/s), indicating the reasonableness of the PA velocity measurement.
## 2 Materials and Methods
### The INFN-CHNet MA-XRF Scanner  
The INFN-CHNet instrument, thoroughly described in [32], is a lightweight (about 10 kg) and compact (60 \(\times\) 50 \(\times\) 50 cm\({}^{3}\)) instrument completely designed and built for heritage science applications within the INFN-CHNet collaboration. It allows easy transport (two middle-sized boxes are enough for the instrument and other auxiliary elements, e.g., workstation and power supplies) but at the same time provides relatively wide mapping with good spatial resolution and statistics per pixel in reasonable acquisition times (e.g.,\(30\times 15\) cm\({}^{2}\) area, 1 mm spatial resolution and 75 min). Briefly, the main parts are the measuring head mounted on 3 linear motors (Physik Instrumente(r), different length available, 200 mm travel range in the x and y directions for this version, plus a 50 mm stage along the z perpendicular direction) and a carbon-fibre case containing electronics controlling motion and acquisition, power supplies and other auxiliary elements. The measuring head is composed of an X-Ray tube (Moxtekc(r) MAGNUM, 40 kV maximum voltage, 0.1 mA maximum anode current, Mo anode--and other anodes also available) equipped with a collimator (several diameters available, ranging from 400 \(\upmu\)m to 2 mm), a silicon drift detector (Amptekc XR100 SDD, 50 mm\({}^{2}\) effective active surface, 140 eV FWHM at 5.9 keV) and a telemeter (Keyence, model IA-100); signals are collected with a multichannel analyser (model CAEN DT5780, also inside the carbon-fibre case). Furthermore, 3D-printing technology was employed to produce supports, holders and other mechanical aids, features which give wide flexibility to customise to a great degree the instrument for many different applications. The software controlling the motion, acquisition and data elaboration was developed within the collaboration and allows both online and offline analysis. It has been employed in several successful applications in the last few years [33; 34; 35; 36].  
The operating conditions of the X-ray tube for all measurements discussed here were: 35 kV anode voltage, 90 \(\upmu\)A filament current and a Mo anode with an 800 \(\upmu\)m diameter collimator. The scanning velocity was 10 mm/s and the equivalent-pixel size 1 mm. Several scans were performed for the full mapping of the painting.