esa-sceva/satcom-chunk-collection huggingface dataset:
# Speaker-Independent Spectral Enhancement for Bone-Conducted Speech
## 1 Introduction
This paper discusses and studies the blind enhancement methods of BC speech for speaker-independent systems, mainly to solve the problems of dull and unclear speech caused by serious high-frequency attenuation of BC speech and consonant loss and promote the practical popularization of BC speech technology. The model adopts convolutional encoder-decoder [17] architecture. Due to the convolutional shared parameters, the model can rapidly enhance BC speech. The main contributions of this paper are summarized as follows:  
* The BSEGAN-SI method proposed in this paper does not need to align features and learns a priori knowledge from a small amount of data. By establishing the mapping relationship between BC and AC, the high-frequency components of BC speech can be recovered better without the assistance of AC speech in the enhancement phase. * We add a spectral distance (L1 regularization factor) constraint to the generator to further reduce the training error, better recover the missing components of the BC speech spectrum and improve the enhancement effect so that the enhanced BC speech signal is more similar to the clear AC speech signal. * The proposed BSEGAN-SI method only uses BC speech information in the enhancement phase and does not need AC speech features. Experimental results show that this method can better perform speaker-independent BC speech enhancement in limited data sets. The structure of subsequent papers is as follows: Section 2 introduces the blind enhancement technology of BC speech; Section 3 introduces the method of speaker-independent BC speech enhancement; Section 4 carries out the simulation experiment and presents the results from the analysis; Section 5 summarizes the whole work.
## 3 Results
### Photogrammetric Survey and Wireframe Drawing  
The monumental complex of the Duomo of Prato and the bell tower was the subject of an extensive survey using aerial photogrammetry.  
The air survey was carried out by Studio Micheloni S.R.L. (Florence, Italy) in the context of a cooperation with the DST. A Phantom 4 Pro drone ([[https://www.dji.com/it/phantom-4-pro](https://www.dji.com/it/phantom-4-pro)]([https://www.dji.com/it/phantom-4-pro](https://www.dji.com/it/phantom-4-pro)), accessed on 5 October 2022) with an RTK antenna, GPS, and a 20 Mp resolution camera was used. The drone flight, at about at 5 m distance from the walls, obtained a GSD = 0.41 cm. This type of survey was integrated with a photographic survey carried out from the ground level with a SONY \(\alpha\)6500 camera, with 24 megapixel resolution. In total, more than 3000 photos were taken.  
The planning of the survey campaign involved the execution of two types of drone survey. One was a planned flight out over the entire area of the monumental complex, while the other was a series of frontal photos in manual mode at a distance of five meters from the facades and with an overlap of about 70% between one shot and the next.  
The information obtained from the planned flight allowed the reconstruction of a 3D point cloud model and textured mesh, as well as an orthophoto of the area.  
The integrated processing of the drone photos and the photos from the ground enabled the reconstruction of high-resolution photoplanes and their subsequent two-dimensional digitization. The facades were classified and named according to a unique code in plain view and accordingly in the relative photoplanes (Figure 2).  
Starting from the photoplanes in raster format, vectorization was carried out in the CAD environment (Figure 3). The primary element is represented by the stone element digitized by means of a closed polygon. Closed geometries are essential to have correct import and identification in the GIS environment.  
In the CAD environment, layers were created through which different types of stone elements (slabs, frames, statues, among others) and architectural elements (doors, windows, grates, gutters, among others) were classified, and an initial classification of the deterioration visible above on Verde Prato elements.  
The operations carried out in this phase were essential to allow the correct setting of the geometries for the GIS database.
## 3 Results and Discussion
### Optimization Results of Laser Cladding Process Parameters  
The optimization results of the process parameters aiming at the maximum micro-hardness of coating are shown in Table 7. The optimal process parameter combination obtained using the Taguchi method was \(L_{2}D_{1}S_{1}V_{2}\), i.e., laser power 450 W, spot diameter 1 mm, overlapping ratio 20%, scanning velocity 7 mm/s, and the micro-hardness of the coating tested by the hardmeter was 1134.6 HV\({}_{0.2}\). The process parameters optimized via the BPNN model were 457.69 W, 1 mm, 21%, 7 mm/s, and the predicted micro-hardness was 1154.1 HV\({}_{0.2}\). The process parameters optimized using the BPNN-PSO model were 449.85 W, 1 mm, 20%, 6.3 mm/s, and the predicted micro-hardness was 1108.8 HV\({}_{0.2}\). The parameters optimized using the BPNN-QPSO model were 445.65 W, 1 mm, 20%, 6.33 mm/s, and the predicted micro-hardness was 1118.2 HV\({}_{0.2}\). The _fitness_ value calculated by aiming at the maximum micro-hardness value of coating is shown in Figure 13. It can be seen that BPNN-QPSO had a larger optimization range than BPNN-PSO and less iteration times were required for convergence to obtain the optimal solution than BPNN. The results showed that the probability of the BPNN-QPSO network model falling into the local optimal solution was lower than that of the BPNN-PSO network model, the convergence rate of the optimal solution was faster than that of BPNN, and the optimization result was similar to that of the Taguchi method.
# Application of Terminal Audio Mixing in Multi-Bandwidth End-to-End Encrypted Voice Conference +
## 2 Homomorphic Encryption
### Big Integer-Based Mixing Method
#### 2.2.2 Big Integer-Based Mixing  
* Unlike traditional additive mixing, where individual samples from different tracks are added pairwise, the big integer-based mixing method developed in this study involves directly adding a big integer of audio segment that is composed of a sequence of samples, with the corresponding big integers of audio segments from other tracks.
* This approach significantly reduces the implementation complexity and utilizes the carry representation provided by big integer libraries, making bitwise operations more readable and manageable.
# Smart Mobility and Aspects of Vehicle-to-Infrastructure: A Data Viewpoint
## 3 V2I Communication
### IoT  
As mentioned, wireless communication technologies are an important aspect of Smart Mobility. Using these technologies, the individual ITS elements exchange the necessary data for safer and smoother traffic. This communication is provided by IoT (Internet of Things) devices that collect and send data. IoT is the interconnection of physical objects equipped with sensors, software and other technologies that are used to exchange data with other devices over the Internet [13]. It is through the integration of IoT devices into individual elements of road traffic that we approach the interconnected and autonomous driving of vehicles. An example of IoT devices integrated into a vehicle is shown in Figure 5.  
In addition to the exchange of data between vehicles, individual vehicles also obtain other necessary information by communicating with the infrastructure. As mentioned above, many IoT devices also occur in road infrastructure and collect the necessary data. These include, for example, object recognition, parking space occupancy or light signal control. Examples are also IoT devices on the roads or on the side of roads, such as RFID, microwave radar or video image processors, which are used to collect data on current  
Figure 5: IoT devices integrated in vehicles.  
traffic density. This data is then processed in the cloud and used to predict traffic flow. By obtaining information about the predicted traffic flow via V2I communication, passengers can avoid places where there is a risk of traffic jams [26].  
The development and combination of IoT devices, artificial intelligence (AI) and communication technologies will gradually diminish the driver's driving role and the vehicle will take full control of the steering [27].
## 3 Results and Discussion
### Crushing Rate  
To adapt to the working environment, a proppant also needs to have excellent compressive strength; thus the crushing rate under 52 MPa of pressure was used as the evaluation standard. As shown in Figure 7, the crushing rate decreased at first and then increased with the increasing FA content. The crushing rate decreased to 0.92% when the content of FA was 30 wt.%. However, the crushing rate increased to about 6.98% when the content of FA was up to 50 wt.%, which reveals that the poly(St-_co_-MMA)/FA microspheres have a good crush resistance with 30 wt.% of FA. The reason for this phenomenon is the high interfacial shear strength between the poly(St-_co_-MMA) matrix and FA that forms from the bonding of cross-links which cover or screen the FA. Consequently, this prevents the expansion of the cracks inside the material, while the expansion of a crack can be transferred due to the good bonding between the poly(St-_co_-MMA) matrix and FA. Furthermore, the incorporation of the hard FA powders into the poly(St-_co_-MMA) matrix improves the stiffness of the composites by restricting the movement of the matrix molecular chain [33]. However, the polymer is not enough to encapsulate FA when the FA content exceeds  
Figure 5: The (**a**) TG and (**b**) DTG curves of (black line) pure poly(St-_co_-MMA), (red line) 10 wt.% FA, (green line) 30 wt.% FA, and (blue line) 50 wt.% FA microspheres.  
30 wt.%, which will weaken the intermolecular stress transfer of the polymer, thus reducing the compressive strength.
## 3 Network Positioning
### Cell Positioning  
Although it is not as accurate Wi-Fi positioning, the NLP in Android also utilizes cell tower localization. Cell tower localization is similar to Wi-Fi fingerprinting, since it involves determining a position using the signal strength of visible cell towers and their known location in a database. Figure 2 depicts how a mobile device may determine a location through cell tower triangulation. Using the known cell tower locations and their respective signal power levels observed by the device, it is possible to estimate the user position. Unlike the Wi-Fi routers, it may also be more convenient to estimate the transmitted power from the cell towers, as these would be centrally controlled rather than being dependent on each individual station [29].  
Another important characteristic that differentiates Wi-Fi positioning to cell positioning is the range of the signals. Cell signals have longer range, because the typical transmitted cell signal power is greater than that of Wi-Fi, and also cell signals utilize a lower frequency spectrum. Although this assists in providing better availability for cell positioning, it also reduces the need for a high-density cell tower distribution. Consequently, a receiver may often be in the range of only a few cell towers that are kilometers away. In such environments, where there is a low density of cell towers, the accuracy can range from anywhere between a few hundred meters up to multiple kilometers, which is much worse than that of Wi-Fi positioning [23]. In the near future, 5G technology may significantly improve the accuracy of cellular positioning, especially in areas with many 5G access points available. The introduction of 5G technology would allow accuracy within 10 m for scenarios, such as emergency calls, and decimeters in an indoor factory setting [30].  
Figure 2: Illustration of cell localization using cell towers. If the locations of the cell towers are known, and the distance to each cell tower can be estimated, a position solution can be computed.  
Based on what was extractable from the smartphones used in this study, the Android NLP engine is able to identify what type of network the cell signals are on, so this may help to weight all of the measurements based on their estimated qualities. For example, it is possible to differentiate between GSM, CDMA, LTE, WCDMA, 5G, and TDSCDMA. In terms of measurements, all signals provide a station ID and a power level. In the case of LTE, the bandwidth is provided, and in the case of CDMA, the station latitude and longitude are also available.
## 3 Results and Discussion
### Coverage of Mineral Requirements After Consumption of 100 g of Bread
#### 3.4.2 Macroelements  
Among macronutrients, 100 g of bread with added vegetable powders covered the daily requirement for K to the highest extent. Consumption of 100 g of bread with added CP covered the K requirement by 43.79-51.21%. Higher coverage of K requirements was recorded for bread with PP additives (45.52-59.99%). The study found that PP was richer in K than CP. [PERSON] et al. [59] report that the consumption of 100 g of PP covers the K requirement by 64%. An adequate supply of potassium in the diet is essential for maintaining normal muscle activity, maintaining water balance, osmotic pressure, and acid-base balance within the body [77].  
A portion of bread with 20% and 30% CP and PP covered more than 8% of Na requirements. In the case of Na, its consumption among Polish people is reported to be excessively high. Although Na plays an important role in the human body--it is involved in the formation of nerve impulses, muscle contractions, and regulation of blood glucose levels [59]--its excess can lead to hypertension, increased risk of cardiovascular disease, kidney dysfunction, and oxidative stress [78]. The salt content of bread can vary depending on the type of bread and the additives used during baking. [PERSON] and [PERSON] [79] report that the salt content of bread ranges from 4.28 g/kg to 12.41 g/kg, while the average Na content is 3.0 g/kg. In contrast, the contribution of bread to daily salt intake ranges from 1.3 g (12.5%) to 3.7 g (33.5%), depending on the country, which is higher than in the studies presented.  
The coverage of Mg requirements was the most variable, due to different daily requirements for this element according to sex and age. The consumption of 100 g of bread, bothwith CP and PP, covers the demand to the highest degree among women aged 19-30 years (5.47-6.76%) and 31-65 years (5.29-6.55%). Due to the higher demand for Mg among men, their Mg coverage after consuming 100 g of bread with CP and PP would be covered at 4.03-4.99% and 4.24-5.24%, respectively. Mg is involved in the transmission of neuromuscular impulses, which promote muscle relaxation; in addition, this element is an essential element of ribosomes and participates in protein synthesis [80].  
The types of bread studied covered the lowest degree of Ca requirements (up to about 6%). Commonly, bread is not considered a good source of Ca. On the other hand, considering the coverage of this element after consuming 100 g of wheat bread (2.18-2.61%), it is indicated that enriching bread with CP and PP increases the amount of this element, corresponding to a coverage of more than double (more than 5%), after consuming a 100 g serving.
## 3 Results
### Functional Verification of Overexpression of VvMIR156b/c/d and VvSPL9 in Tomatoes  
After four days of fruit injection, the overexpression of tomatoes (OE) was further observed (Figure 8A). Compared with the control plants (CK), VvmiR156b/c/d-OE fruits had a redder color, while _VvSPL9_-OE inhibited tomato coloring. The qRT-PCR results showed that in VvmiR156b/c/d-OE fruits, the expression of _SISPL9_ was inhibited to varying degrees, while in _VvSPL9_-OE fruits, the expression of _VvSPL9_ was significantly upregulated (Figure 8B). In addition, we found that in VvmiR156b/c/d-OE fruits, anthocyanin metabolism-related genes were highly expressed; in particular, the expression of _SIPAL_, _SIDFR_, _SISGT_, and _SIANS_ were significantly upregulated; while in _VvSPL9_-OE fruits, the expression levels of _SIPAL_ and _SISGT_ were inhibited (Figure 8C). These phenomena indicated that VvmiR156b/c/d could promote the expression of anthocyanin synthetics genes by negative regulatory _VvSPL9_ expression, which further led to the formation of fruit color.  
downregulated. VvmiR156b/c/d showed similar expression trends with anthocyanin structural genes, and the expression pattern of VvmiR156b/c/d was positively correlated with anthocyanin contents and anthocyanin synthesis related gene expression, and the expression pattern of _Vv5 PL9_ showed a negative correlation. These findings indicate that VvmiR156b/c/d could promote the expression of anthocyanin synthetic genes by negative regulatory _Vv5 PL9_ expression, thus promoting coloring.  
In addition, we constructed the overexpression vectors of VvmiR156 and _Vv5 PL9_ to further verify their functions. However, since grape transgenic technology is not perfect and mature, while tomato is a model transgenic plant system and is thus widely used in the verification of gene functions. Therefore, we utilized transient transformation of injecting tomato fruit for determination of gene functions in this work. Interestingly, four days after injection, all VvmiR156-OE fruits showed a redder color, but _Vv5 PL9_-OE fruits had inhibited coloring. Meanwhile, in VvmiR156-OE fruits, the expression levels of anthocyanin metabolism-related genes had a higher expression, in particular, _SIPAL_, _SIPFR_, _SI3 GT_, and _SIANS_ were significantly upregulated, but the expression of _SIPAL_ and _SI3 GT_ was inhibited in _Vv5 PL9_-OE fruits. Similarly, the regulation of anthocyanin synthesis by the miR156-_SPL_ pathway also exists in _Arabidopsis thaliana_, apple, litchi, and rice [22; 24; 25], indicating that the regulation of miR156-_SPL_ on plant-specific metabolites is highly conserved in different species, which also provides an idea for the functional study of miR156-_SPL_ in other species.
# A Universal Malicious Documents Static Detection Framework Based on Feature Generalization
## 3 Attack Forms of Malicious Documents
### Main Attack Forms of Office Documents
#### 3.2.4. DDE Commands  
In October 2017, SensePost released an article that explained how it is possible for arbitrary code to be executed from a Microsoft Word document without using any macros or scripts [39]; this technique is called dynamic data exchange (DDE). This attack is very effective, and is therefore widely used in malware campaigns and red team assessments [35]. DDE is a legitimate Microsoft Office functionality, and the DDE protocol is a set of messages and guidelines. Malicious Word documents usually include the insertion of DDE commands, which will pop up a dialog box when the program starts to ask the user whether to execute them.
# A Multi-Node Detection Algorithm Based on Serial and Threshold in Intelligent Sensor Networks
## 6 Complexity Analysis  
The complexity of MPA and its improved algorithms are mainly determined by the number of multipliers used in the algorithm. In the original MPA, the high complexity is mainly caused by the large amount of operations of the EXP algorithm in the iterative process, the large space occupied in the iterative updating process of the message, and the storage space occupied by the updating between the variable node and the function node. The number \(Q_{m}\) of multipliers used in the original MPA calculation is as Equation (15):  
\[Q_{m}=t_{\rm max}\times K\times d_{\rm f}\times M^{d_{\rm f}}\times(2\times d _{\rm f}+1)+t_{\rm max}\times J\times d_{v}\times(d_{v}-2), \tag{15}\]  
where \(d_{\rm f}\) represents the number of sensor nodes per resource block and \(d_{v}\) represents the number of resource blocks per sensor node.  
In the proposed algorithm, the user node stability and threshold are first used for decision, so the accuracy of user information decoding is increased, and the maximum number \(t^{\prime}_{\rm max}\) of user iterations is reduced, which is less than \(t_{\rm max}\). Then, the user node information updating is integrated into the resource node information updating, which reduces the storage space of the intermediate information variables. Finally, in the whole operation process, the operation of logarithmic field is used to change EXP operation into addition operation. The number \(Q^{\prime}{}_{m}\) of multipliers used in the S-T-Max-log-MPA algorithm can be calculated as Equation (16):  
\[Q^{\prime}{}_{m}=t^{\prime}{}_{max}\times K\times d_{f}^{2}\times M^{d_{f}}. \tag{16}\]  
Therefore, the number \(Q^{\prime}{}_{m}\) of multipliers of the proposed algorithm in this paper is greatly reduced, which is less than \(Q_{m}\). So the complexity of the detection algorithm will be greatly reduced.
###### Abstract  
The exponential growth of network intrusions necessitates the development of advanced artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the reliance on AI for IDSs presents several challenges, including the performance variability of different AI models and the opacity of their decision-making processes, hindering comprehension by human security analysts. In response, we propose an end-to-end explainable AI (XAI) framework tailored to enhance the interpretability of AI models in network intrusion detection tasks. Our framework commences with benchmarking seven black-box AI models across three real-world network intrusion datasets, each characterized by distinct features and challenges. Subsequently, we leverage various XAI models to generate both local and global explanations, shedding light on the underlying rationale behind the AI models' decisions. Furthermore, we employ feature extraction techniques to discern crucial model-specific and intrusion-specific features, aiding in understanding the discriminative factors influencing the detection outcomes. Additionally, our framework identifies overlapping and significant features that impact multiple AI models, providing insights into common patterns across different detection approaches. Notably, we demonstrate that the computational overhead incurred by generating XAI explanations is minimal for most AI models, ensuring practical applicability in real-time scenarios. By offering multi-faceted explanations, our framework equips security analysts with actionable insights to make informed decisions for threat detection and mitigation. To facilitate widespread adoption and further research, we have made our source code publicly available, serving as a foundational XAI framework for IDSs within the research community.  
intrusion detection systems; explainable AI; network security; Shapley additive explanations; LIME; CICIDS-2017; NSL-KDD; RoEduNet-SIMARGL2021; feature selection  
1
## 3 Results and Discussion
### Charge Carrier Mobility Characterization  
The charge carrier mobility was measured using the DI SCLC methodology which gives direct measurements of charge mobility in C\({}_{60}\). Figure 5a displays the current transient of the C\({}_{60}\) film at different voltages, where a rapid increase in the current can be observed as the applied voltage increases, reaching a point where the charge density is maximized. The well-defined maxima  
observed in Figure 5a indicates the arrival time of the fastest charge carriers to the non-injecting contact. Beyond that point, the current density decreases until it reaches the equilibrium state analogous to charge dynamic equilibrium. The observed increase in current transient with increasing voltage featuring a shift of the current peak to lower values is indicative of the formation of ohmic contact typical to DI SCLC transients. Figure 5b summarizes the electron mobilities obtained from Dark Injection Space Charge Limited Current measurements showing higher mobilities in the low voltage region and a saturation region at higher voltages, suggesting that electron mobility becomes independent of the applied voltage. These results were valuable in confirming the semiconducting behaviour of our solution-processed C\({}_{60}\) film and furthermore helped in setting an optimal voltage bias point for the reported OTFT-based sensors.