esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theoretical Background
### Transfer Learning  
The minimization of loss functions in CNNs is an optimization problem which involves millions of weights. It is evident that such procedures are computationally demanding. Moreover, a large number of weights results in many degrees of freedom for the SGD algorithm. When training datasets are not sufficiently large, network weights may therefore overfit data, producing models that are unable to generalize knowledge beyond training sets. Convergence issues can be addressed when SGD is unable to find minima in the loss function. TL is one of the tools developed within the AI field to face these issues.  
Considering a source domain \(D_{s}\) and a target domain \(D_{t}\), TL techniques are able to transfer the knowledge acquired in \(D_{s}\) for carrying out a source task \(T_{s}\) to the domain \(D_{t}\) for fulfilling a target task \(T_{t}\)[5; 34; 36]. For instance, fault diagnosis tasks learned in certain machine conditions can be transferred to different working conditions [38; 39], or the diagnosis knowledge can be migrated between different machines [54].  
Practically, one way for implementing TL consists of freezing the first layers of CNNs, saving the knowledge acquired for extracting low-level features. On the other hand, the last layers are modified and further trained to fine-tune the model. Favorably, such fine-tuning procedures require limited data for updating the remaining weights. This kind of approach is known in the literature as parameter-based [5], since some of the network parameters remain unchanged. In particular, the knowledge enclosed in the frozen weights concerns the ability of the network of identifying specific features in data. The pre-acquired knowledge can thus be employed to face new tasks, in which features detection abilities can be re-used. In this sense the training time is drastically reduced, and few-data trainings are less prone to overfitting. The number of replaced layers for fine-tuning essentially depends on the degree of diversity between source and target domains [36]. Nevertheless, the development of structured transferability criteria and metrics is a challenging focus of current research [5]. Further TL approaches for machine diagnosis can be feature-based, instance-based or generative models [5].  
Existing literature has emphasized the capabilities of networks pre-trained on ImageNet to detect machine faults [36; 37]. In such cases, low-level features characterizing ImageNet are exploited to classify time-frequency images of vibrational data. This work is motivated by the idea that networks pre-trained for SED, speech and music recognition, hold enough knowledge for classifying bearings faults though spectrogram analysis. Indeed, SED frameworks are already trained for the case of spectrograms classification.  
Figure 3: Pooling operations in CNNs.  
Additionally, provided the inherent similarity between source and target domains, few layers are expected to need fine-tuning.
# Nanomaterials for Healthcare Biosensing Applications
## 3 Applications of Inorganic Nanomaterials in Healthcare Biosensing
### Gold Nanoparticles
aeruginosa_) [193]. A highly conductive gold working electrode deposited with Super P, a stable form of carbon black, and AuNPs to obtain an enhanced and stable signal. This improved the electron transfer to adequate detection sensitivity. In addition to the exceptional conductivity, AuNPs played a key role in mAb immobilisation. CV, DPV, and EIS provided a detection range of 10-10\({}^{6}\) cfu mL-1 and the LOD was found to be 2 cfu mL-1. Sabouri and co-workers established a chemiluminescence sandwich immunosensor for the detection of hepatitis B using functionalised AuNPs as capture probes [136]. The AuNPs were initially allowed to react with 11-MUA prior to conjugation with luminol and cAb. The detection probe consisted of dAb. The predominant ability exhibited by AuNPs to function as biological labels was harnessed to obtain a CL response between 0.12 and 30 ng mL-1 of Hepatitis B surface Antigen(HBsAg), with a limit of 14 pg mL-1. A study for Zika virus (ZKV) detection employed silsesquioxane polyelectrolyte (SiPy) as a stable support for AuNPs [194]. To construct the impedimetric biosensor, ssDNA was immobilised on an oxidised glassy carbon electrode (oxGCE) that was modified with AuNPs-SiPy. The sensor could measure the target in a wide concentration range (\(1.0\times 10^{-12}\)-\(1.0\times 10^{-6}\) M) with a high sensitivity (LOD: 0.82 pM).
## 3 Model Reconstruction and Finite Element Analysis
### Analytical Model and Experimental Validation  
The analytical model of the effective elastic constants of porous solids is based on numerical simulation and microstructure measurement, and it is considered to be a relatively accurate empirical equation for predicting elastic properties. In order to ensure the rationality of this simulation route and accurately quantify the microstructural damage on elastic properties of micron silver sintered joints, two analytical models were used to calculate the elastic modulus at different thermal shocks and these results were compared with simulation results. The first model corresponds to the Ramakrishnan and Arunachalam (R&A) method [25] and is conducted as Equations (15) and (16).  
\[E_{p}=E_{0}(1-p)^{2}/\Big{(}1+b_{p}p\Big{)}, \tag{15}\]  
Figure 12: Equivalent stress analysis results of micron silver sintered joints under different thermal shocks by fixing X, Y and Z planes, respectively: (**a**–**c**) 50; (**d**–**f**) 100; (**g**–**i**) 150; (**j**–**l**) 250 cycles.  
\[v=\frac{1}{4}\frac{(4v_{0}+3p-7v_{0}p)}{(1+2p-3v_{0}p)}, \tag{16}\]  
where, \(b_{p}=2\)_to \(3v\)_, \(p\) is the pore volume fraction. \(v_{0}\), \(E_{0}\) is the Poisson's ratio and elastic modulus for undamaged material, and \(E_{p}\) is the elastic modulus corresponding to a certain damage state.  
Another model, the modified value of porous materials (M) [26] in Equation (17) was used to estimate the effect of microscopic damage on elastic modulus. The parameter definition is the same as above.  
\[E_{p}=E_{0}-pE_{0}\bigg{(}\frac{9-4v_{0}-5v_{0}{}^{2}}{7-5v_{0}}\bigg{)}. \tag{17}\]  
Furthermore, nanoindentation test was used to measure the load and corresponding displacement of pressureless micron sintered joints. The geometric vertices and center point of the silver welding layer were selected as test positions, and the average value was taken as the test result. If there is a large deviation in the above positions, it is determined that the silver bonding layer of the sample is uneven during sintering, and needs to be rejected. Meanwhile, a new sample is re-selected for testing. The designed stress curve is shown in Figure 13.  
For geometries based on SCR method, normalized calculation results of FEA and theoretical models and nanoindentation tests are plotted in Figure 14. The error among simulation and test and R&A method is within 15%, which indicates that the proposed simulation route and the elastic properties of micron silver sintered joints obtained by FEA are reliable and precise.  
Figure 14: Relative comparison of FEA, analytical models and nanoindentation results.  
Figure 13: Applied nanoindentation stress curve.
## 2 Materials and Methods
### HPLC Conditions for Determination of Flavonoids  
Flavonoids in Ginkgo biloba leaf samples were separated using a Waters 2695 chromatographer (Waters Corporation, Milford, CT, USA) equipped with a Waters 996 photo diode array detector (PDA) (Waters Corporation, Milford, CT, USA). An ACE C18 column (150 \(\times\) 4.6 mm, 5 \(\upmu\)m) (Advanced Chromatography Technologies, Aberdeen, Scotland, UK) was used for analysis. The column temperature was maintained at 25 \({}^{\circ}\)C. Gradient elution was performed with a mobile phase ortho-phosphoric acid (pH 2.0) (solvent A) and methanol (solvent B). A linear gradient profile was applied with the following proportions: 0 min to 1 min with 60% A and 40% B; 1 min to 20 min from 60% to 45% A and from 40% to 55% B; 20 min to 21 min from 45% to 0% A and from 55% to 100% B; 21 min to 25 min with an isocratic elution of 100% B; 25 min to 30 min from 0% to 60% A and from 100% to 40% B. The injection volume was 10 \(\upmu\)L, and the elution flow rate was 1.0 mL/min.  
Three selected flavonoids--quercetin, kaempferol and isorhamtein were identified in G. biloba leaves. Flavonoids were identified by comparing the retention time and spectral characteristics (\(\uplambda=370\) nm) of the eluting peaks with those of reference compounds.  
The percentage content of flavonoid glycosides, was calculated using following formula:  
\[X=2\times\frac{A_{1}\times m_{1}\times 2.514\times p}{A_{2}\times m_{2}} \tag{1}\]  
where \(m_{1}\)--grams of quercetin dihydrate in the reference solution; m\({}_{2}\)--grams of the extract to prepare the test solution; \(A_{1}\)--sum of the peak areas from quercetin to the isorhamtein in the chromatogram obtained with the test solution; \(A_{2}\)--areas of the peak due to quercetin in the chromatogram obtained with the reference solution and \(p\)--percentage content of anhydrous quercetin in quercetin dihydrate.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sample Name** & **CMC * (g)** & **GFD ** (g)** & **Glycerol (g)** \\ \hline CMC—0 & 2 & 0 & 0.3 \\ FRG—12 & 2 & 0.3 & 0.3 \\ FRG—15 & 2 & 0.4 & 0.3 \\ FRG—18 & 2 & 0.5 & 0.3 \\ FRG—21 & 2 & 0.6 & 0.3 \\ \hline \hline \end{tabular}  
* 2 % of CMC solution used for sublingual film preparation. ** freeze-dried G. biloba extract.  
\end{table}
Table 1: The formulation codes, composition, weight ratio of sublingual films based on carboxymethyl cellulose (CMC) (control sample) and sublingual films based on CMC and _G. biloba_ ethanol extract.
## 4 Results and Discussion
### Analysis of App Operations Logs  
The operational logs of the main application screen are listed in Table 2. The number of route selection actions was significantly less than the number of routes searched. This suggests that participants searched for routes multiple times and checked the estimated traffic before they departed. Operational logs revealed that participants who checked sightseeing spots chose the spots by receiving information on nearby tourism spots and then confirmed their final route; these participants accounted for approximately 15% of all participants.  
Participants checked the required travel times and chose one of the four options (\"Depart now\", \"Depart after 1 hour\", \"Depart after 2 hours\", and \"Depart after 3 hours\") for their return journey. These results are shown in Figure 2. One hundred and fifty operational logs for route selection were extracted and analyzed to identify which option was chosen after the estimated travel time information was provided. As a result, 98 logs displayed \"Depart now\", and 52 logs displayed the other departure options.  
In addition, operational logs on route choice were extracted when the estimated travel time for other options was shorter than that for the \"Depart now\" option. Fifty-seven route choice logs were  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Operation Type** & **Number of Operations** & **Number of Operators** & **Average Number of Operations** \\ \hline
**Route search** & 907 & 60 & 15.12 \\
**Route choice** & 234 & 58 & 4.03 \\
**Spot check** & 341 & 57 & 5.98 \\
**Spot choice** & 144 & 14 & 10.29 \\
**Route check** & 19 & 9 & 2.11 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of application operation logs.  
Figure 5: Intention to change departure time for returning home.  
extracted; in 30 logs, \"Depart now\" was chosen, and in 27 logs, other delay departure options were chosen. The selection ratio of the \"Depart now\" option and other options is shown in Figure 6; the horizontal axis is the shortened travel time required to return home. If this time was greater more than 20 min, the ratio of selecting the options of delaying the departure was higher. The time of \"-20 min\" implies that the estimated travel time of a delayed departure trip was 20 min less than the estimated travel time of the \"Depart now\" option. Furthermore, for \"-30 min\", the selection ratio of the decision to delay the departure time was 100%. These results show that the participants were sensitive to the difference in the shortened travel time.
# Analysis of Multi-Antenna GNSS Receiver Performance under Jamming Attacks
## 2 Methodology  
This section describes GNSS and interference signal simulations, the multi-antenna signal processing method, and the methodology to characterize the code and carrier phase measurement distortions used in the sequel.
# Analysis of Elastic Nonlinearity Using Continuous Waves: Validation and Applications
## 3 Validation  
### Feasibility of the Separation of Modulus and Damping Contributions  
Understanding the functional dependence of \(c\) and \(\alpha\) on strain is a first goal of the analysis of nonlinear elasticity in complex media, since it allows observing differences for different materials. As discussed above, nonlinearities in velocity are normally associated to modulus nonlinearities, while nonlinearities in attenuation coefficient are associated to damping nonlinearities.  
However, as we have shown, some corrections must be considered and this could be important in particular cases, e.g., for strongly attenuative media. Here, we focus on validating the capability of the method to separate correctly the two kind of nonlinearities.
# Developments on Perovskite Solar Cells (PSCs): A Critical Review
## 6 Device Challenges  
### Perovskite Solar Cell Device Stability  
The development of the PSCs in the past decade has shown a massive improvement in efficiency over a short period in comparison with other existing solar cells. PSCs have already surpassed the performance of commercially available silicon-based PVs, making them the future of solar energy. However, the device's lifespan is below the required 25 years for a normal PV cell, ranging from days to months. The degradation of PSCs performance suggests that device instability stands in the way of commercialization [76]. Therefore, it is necessary to understand PSC degradation mechanics to improve the device's flaws. In the characterization of perovskite cell stability, the device is subjected to harsh environments in order to obtain superior performance under normal conditions. The degradation response results from failure of device components caused by external factors (moisture, oxygen, temperature, and UV radiation), internal factors (crystal structure, ion migration, and interfacial contact), the constituting materials, device architecture, and fabrication process. Therefore, it is important to note that PSC stability is affected by a variety of factors, suggesting that it is necessary to further study PSCs thoroughly and develop standard procedures and protocols towards building a fully functional and stable device.
# Design and Implementation of Model Predictive Control for a Gyroscopic Inverted Pendulum
## 5 Conclusions  
This study proposes a design for an active stabilizing system for a single-track vehicle. By using the gyroscopic effects of two flywheels, this system can generate control torques to stabilize the vehicle in cases with centrifugal forces during turning. In order to verify the performance when stabilizing the vehicle, a gyroscopic inverted pendulum system is developed. The mathematical model for the inverted pendulum is derived using [PERSON]'s equation and then is verified by comparing the closed loop response with a model which is constructed using the commercial software ADAMS.  
To control the flywheel's gimbals for generating stabilizing torque, a model predictive control algorithm is used to synthesize the controllers. The prediction model for MPC is obtained by linearizing the nonlinear inverted pendulum model around its upright position. Three different strategies are proposed to stabilize the vehicle under different working conditions. The performance of these control strategies were verified by applying them to control the gyroscopic inverted pendulum.  
In order to evaluate the real-time performance and the feasibility of the proposed controllers, a real-time simulator is proposed. This includes two embedded STM32F407 boards and a UART-to-RS232 converter. The two STM32F407 boards are used to embed the dynamics system and the control algorithm, respectively. The interactions between the dynamic system and the controller, such as control torques and feedback signals, are studied using the UART protocol. By using the simulator, the real-time performance and the feasibility of the control algorithm can be verified without the need for costly and time-consuming manufacturing and practical experiments. The results for the real-time implementation in this study demonstrate the feasibility of embedding the proposed controllers in common hardware.  
This work was supported by the Ministry of Science and Technology of the Republic of China, Taiwan under grant MOST 104-2221-E-027-137-MY2.  
These authors contributed equally to this work in terms of proposing the research method and paper writing. [PERSON] conducted the experiments, and [PERSON] contributed to results analysis.  
The authors declare no conflict of interest.
# Copy Number Variation: Methods and Clinical Applications
## 2 Methods of CNV Detection  
From conventional cytogenetic methods through hybridization- and PCR-based techniques, up to MPS, CNV detection methods have been through a long evolution, affecting several aspects of progress in CNV research (Figure 1). Cytogenetic techniques were the first methods for CNV detection, based on visual inspection of chromosomes. Improvements led to the gradual lowering of detection limits, from numerical anomalies of whole chromosomes to CNVs of a few Mb in size. Introduction of molecular-biology methods, especially hybridization followed by Southern-blotting, allowed detection of mid-sized CNVs in the range of several kb. Later, amplification-based PCR methods together with their modifications and a wide range of associated detection techniques brought analytical resolution to single nucleotides, with upper limits of the detection range at hundreds of kb or a few Mb. Completely new possibilities were introduced by housing molecular hybridization techniques with cytogenetic methods and with microarray-based methods, but also with the invention of MPS. The latter two allowed the analysis of the whole size range of CNVs in single runs, at least theoretically, and in scales of whole genomes.
# Study on the Deployment of Ultra-Wideband Positioning Base Stations in Pig Farms
## 4 Experimental Analyses  
To conduct a comprehensive analysis of the positioning environment in pig farms, it is generally recommended to deploy positioning base stations along the corridor or on the walls. This study proposes multiple deployment schemes for base stations and evaluates their impact on positioning results by measuring the Dilution of Precision (DOP) value through both simulation experiments and real-world tests. The height of the positioning terminal is set at 100 cm.
# Research on the UAV Sound Recognition Method Based on Frequency Band Feature Extraction
## 2 Method and Model Establishment
### Frequency Band Feature Extraction Method of UAV Sound  
The frequency band feature extraction methods of UAV mainly include sound signal pre-processing, framing, and windowing, as well as Fourier transform, frequency domain conversion, frequency domain filter bank processing, and cepstral domain conversion. The feature vectors of consecutive frames are combined with 2-D sound features. The overall process of the feature extraction method is shown in Figure 1.
## 4 Conclusions  
This study presents simulations of transitional ventilation flow in building environments with the Coanda effect predicted by six low-Reynolds number \(k\)-\(\varepsilon\) models for three different Reynolds numbers (Re = 1000, 1750, and 2500).  
The geometrical details and boundary conditions used in the simulation are as similar as possible to those in the experiment of [PERSON] et al. [27]. The flow is subjected to transition, attachment, separation, and high anisotropy because of the Coanda effect, the interaction of the jet region with the recirculation region, etc. Some of these specific conclusions are summarized below:  
* All six models predict a thinner boundary layer than that in experiments because of a seriously too-low level of \(\varepsilon\) near the wall in separated flows or flows approaching separation;
* The AB, LB, YS, AKN, and CHC models underpredict the position of separation of the wall jet, while the LS model overpredicts the position of separation of the wall jet;
* The LB and YS models cannot predict the Coanda effect well when the Reynolds number is low (Re = 1000), but when the Reynolds number increases to 1750 and 2500, the LB and YS models perform better--the CHC model is the exact opposite;
* The LB model predicts unreasonable results of turbulent kinetic energy and dissipation rate, leading to the wrong velocity profile predictions;* The LS model has a good approximation of velocity profiles, and the AB model is very suitable for predicting the Coanda effect.
* Software, X.N.; Validation, Z.C.; Data curation, Z.Z.; Writing--original draft, Z.C.; Writing--review & editing, Z.Z.; Funding acquisition, X.N. All authors have read and agreed to the published version of the manuscript.
* This research was funded by [Zhejiang Province Bellwethers Projects] grant number [2023C03126]. The APC was funded by [Zhejiang Province Bellwethers Projects].
* Not applicable.
* All data included in this study are available upon request by contact with the corresponding author.
* The authors declare no conflict of interest.
## 1 Introduction  
Recently, with the development of long-range informal communication on the web, the capacity and dissemination of interactive media content have become extremely simple. On the other hand, this simplicity has led to the need for copyright protection, blocking information theft, and data genuineness [1, 2].  
To handle the above issues, digital watermarking has emerged as an appropriate solution. Digital watermarking is a way of embedding a watermark into a significant image/media. A watermark acts as copyright data, shielding advanced information from illicit replication and conveyance [3, 4]. A watermark is a sort of marker clandestinely inserted in a signal (audio, video, or image information). A watermark embedded into media may or may not relate to it. Watermarks are utilized to check the realness or uprightness of the watermarked signal [5, 6].  
Watermarking is a strategy that is broadly utilized and ceaselessly created by utilizing different strategies and executions [7, 8]. In the proposed method, discrete wavelet transform (DWT) and singular value decomposition (SVD) techniques are combined to accomplish the vigor and imperceptibility of the watermark. The scheme is generally achievable for clients and has an oddity edge over the other existing digital watermarking methods [9]. The idea of embedding the watermark information is to prevent intruders or other members from claiming to be the rightful owner of the data [10, 11].  
The literature review is provided in Section 2. The methods used in the proposed scheme are provided in Section 3. Section 4 provides the process of embedding and extraction of the propounded method. Section 5 presents the experimental results with various images, attacks, and metrics. Finally, the conclusion is provided in Section 6.