esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Material and Method
### Transformer Attention Module  
We process the sequential data belonging to GPS traces using transformer networks. For this reason, we use the transformer encoder and decoder parts as a basic unit. ReLu is used as the activation function. For spatial-temporal input features gathering, we apply the attention mechanism. When the multi-heads finish their job, the job vector's output is added to the original positional input embedding. This is called residual connection. The residual link completes their task, producing the output. This output goes through the normalization layer. In the further processing, residual normalized production is projected towards the point-wise feed-forward network. The main advantage of the residual connections is that they train the networks directly. In other words, they allow the gradient to flow through the network instantly. The purpose of using the normalization layer is to stabilize the network. The advantage of stabilizing the network is that model training time is greatly reduced. To make the attention output richer, the point-wise feed-forward neural network is projected to the attention layer. After this task, the encoder layer ends. All operations are encoded as input; this input represents continuous attention information. This constant attention information helps the decoder; thus, the decoder focuses on the appropriate words. During the training phase, this input helps the decoder. For further information, we stack the encoder N times. The N times stack provides the opportunity for the attention layer to better learn to represent differently. This increases the predictive power of the transformer.  
The feed-forward neural network is a combination of two linear layers. The ReLu activation functions are in between two layers. Two linear layers produce the output; these layers are again added to the feed-forward neural networks and further normalized. The more structural detail of the transformer is presented in Figure 3. The purpose of the attention layer is to analyze which part is more important in the trajectory and capture it. In the end, this layer is combined with the input sequence. Thus, the transformer layers capture part of the sequence, which helps the current trajectory to trace mobility regularities.
## 3 Results
### Characterization Part
#### 3.1.3 Structural Characterization of PEMA-AMP DFMAC  
The FTIR/ATR spectra of PEMA, AMP, PEMA-AMP comparatively are given in Figure 4.  
According to the FTIR/ATR spectrum of PEMA in Figure 4, peaks at \(\
u\) = 1849 cm\({}^{-1}\) (C=O stretching-anhydride) and 1770 cm\({}^{-1}\) (C=O stretching-cyclopentanone), 1218 cm\({}^{-1}\) (-O-CH\({}_{3}\) stretching), 1094 cm\({}^{-1}\) (O=C-O-C=O stretching-anhydride) and 915 cm\({}^{-1}\) (-C-H bending) were observed.  
According to the FTIR/ATR spectrum of PEMA-AMP in Figure 4, peaks at \(\
u\) = 3287 cm\({}^{-1}\) (O-H stretching of broad carboxylic acid), alkane at \(\
u\) = 2980 cm\({}^{-1}\) (CH\({}_{3}\) (a)symmetric stretching), peaks at \(\
u\) = 1762 cm\({}^{-1}\) (C=O group of beta-lactam), a carboxylic acid peak at \(\
u\) = 1704 cm\({}^{-1}\) (C=O stretching), three substituted alkene peaks at \(\
u\) = 1649 cm\({}^{-1}\) (C=C str.), a 2\({}^{\circ}\) amide (of \(\beta\)-lactam) at \(\
u\) = 1649 cm\({}^{-1}\) (C=O stretching), and monosubstituted benzene at \(\
u\) = 1497 cm\({}^{-1}\) (C-C stretching) were observed.  
The characteristic symmetric and asymmetric C=O stretching vibration peaks of anhydride of PEMA at 1849 and 1770 cm\({}^{-1}\) disappeared. The carbonyl group peak of the beta-lactam ring of AMP shifted from 1769 cm\({}^{-1}\) to 1762 cm\({}^{-1}\). After the PEMA-AMP conjugation, new peaks at 1762 cm\({}^{-1}\) (-N-C=O) and 1649 cm\({}^{-1}\) (CO-N-H) due to amide formation were observed, as shown in Figure 4.  
According to the \({}^{1}\)H NMR spectrum of PEMA-AMP in Figure S1c, \({}^{1}\)H NMR (400 MHz, dsmso-d6) \(\lx@sectionsign\): 8.32 ppm (1H, N-H), 8.00 ppm (1H, N-H), 7.37-7.31 ppm (5H, C-H), 5.65 ppm (1H, C-H), 4.60 ppm (1H, C-H), 4.39 ppm (1H, C-H), 3.06 ppm (1H, C-H), 2.94 ppm (1H, C-H), 2.68 ppm (1H, C-H), 1.51 ppm (6H, CH\({}_{3}\)), 1.33 ppm (1H, C-H), 1.23 ppm (2H, CH\({}_{2}\)).  
Figure 3: FTIR/ATR spectra of PIBMA, AMP and PIBMA-AMP.
# Supply Systems of Non-Thermal Plasma Reactors. Construction Review with Examples of Applications
## 1 Introduction
Virucidal, fungicidal, and bactericidal properties of non-thermal plasma makes it effective in the processes of sterilization and disinfection as well as in treatment of many diseases [16; 17; 18; 19; 20; 21], like:  
* Sterilization of human and animal tissues, blood and surface wounds;
* Assisting skin cancer therapy;
* Odontology--aries therapy;
* Coating of implants, contact optical lens, dentures with biocompatible films;
* Live tissue engineering--fabrication of bioactive agents and medicines, immobilization of biological molecules, cell surface modification to control their behavior, improvement of blood adhesion;
* Sterilization of medical and surgical instruments, especially made of materials and fabrics not resistant to high temperature;
* Medical diagnostics--fabrication biosensors based on polymers and thin amorphous films for medical and bio-chemical analysis. In the agriculture and food industry the plasma treatment is used for [22; 23; 24; 25; 26; 27; 28; 29; 30]:  
* Food pasteurization, disinfection, and preservation--O\({}_{3}\) is used in common refrigerators as a deodorizing and antimicrobial agent;
* Food storage packages sterilization;
* Storing agriculture products--ozone increasing storage life, sanitizing fruit and vegetable surfaces;
* Plant growth enhancement and fruit formation processes;
* Seed germination;* Ozone-aided corn steeping process--to replace current SO\({}_{2}\) application. Research in the field of technological applications of plasma concerns two main issues:
* New solutions of plasma reactors (PRs) and electric discharges used in them, in which plasma, with the required plasma-chemical parameters and high time-space effectiveness, will be produced efficiently at atmospheric pressure [31; 32; 33; 34];
* Efficient and controllable plasma reactor's power supply systems with a wide range of changes in the properties (voltage shape and frequency, range of regulation), which are an inseparable part of the plasma-chemical installation that determines industrial implementation [35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45]. In the review basic types of systems used to supply plasma devices are presented. These are, among others, systems using special transformers and non-linearity of the magnetization characteristics of their cores, as well as systems based on semiconductor technology, operating at DC, AC and pulse voltage, with mains, increased and high frequency. Also, the selected applications of the discussed systems, which were studied and implemented by the author of the article and her research team, has been presented.
## 2 Materials and Methods
### Methodology  
AZ31 alloy matrix material reinforced with graphene nanoparticles was prepared using a powder metallurgy route to form a metal matrix composite. Initially, ultrasonication of graphene nanoparticles was performed in an acetone solution for 45 min to avoid the agglomeration of nanoparticles while mixing them with the AZ31 alloy. After ultrasonication, the AZ31 alloy was added to the slurry of nanoparticles to ensure the agglomeration-free mixing of nanoparticles in the metal matrix composite. Then, after the evaporation of acetone from the mixture (containing matrix and reinforcement powder), the powders were placed in a stainless-steel jar and 0.3 wt.% stearic acid was added to the mixture to minimize cold-welding during planetary ball milling. The powders were then ball-milled at 500 rpm for 1 h with stainless-steel ball diameter of 3 mm under an argon inert atmosphere at a flow rate of 200 mL/min. Argon gas was used as a protective atmosphere in the jar to minimize oxidation. The weight ratio of the stainless-steel milling balls to mixture powder was 20:1 [25]. Thereafter, the homogenous mixture of powders was compacted in a stainless-steel cylindrical die of diameter 20 mm at compaction pressures of 250 MPa, 300 MPa, and 350 MPa, with zinc steroid used as a lubricant to prepare the green compact. The green compact was then sintered at sintering temperatures of 500 \({}^{\circ}\)C, 550 \({}^{\circ}\)C, and 600 \({}^{\circ}\)C in a tube furnace by creating a vacuum inside the furnace. The heating rate for sintering was taken as 5 \({}^{\circ}\)C/min. The sintering times were taken as 45 min, 60 min, and 75 min for sintering. From a cooling perspective, natural cooling via opening the pump valve was incorporated into the furnace. The sintering curve for the preparation of the composites is shown in Figure 1. Argon gas was supplied in the tube furnace at a flow rate of (300 mL/min) which prevents the oxidation of magnesium material in the sintering process, allowing the proper diffusion of the material in the pores to enhance the bonding strength between the reinforcing agent and matrix material. After sintering, the final sample was obtained with \(\phi\)20 \(\times\) 20 mm dimension which was used to evaluate the mechanical properties for the optimized process parameter of composite. The schematic process of fabrication of the magnesium alloy-based metal matrix composite using the powder metallurgy route is illustrated in Figure 2.  
Figure 1: Schematic representation of the sintering curve during sintering process highlights the sintering time and temperature.
## 1 Introduction
Traditionally, image analysis and characterization of shape, texture or patterns is performed by highly trained human observers, but radiomics can provide quantitative image analysis without inter/intra observer variability. Radiomic studies have recently triggered the interest of the research community, and for PCa are mainly focused on several predictive outcomes such as staging, grading, detection, Biochemical Recurrence (BCR) or aggressiveness. Furthermore, the most used imaging modality is MRI, which is usually performed in the initial stages and is critical for volume delineation. With the predictive and phenotypic power of radiomics, other imaging modalities besides MRI may provide valuable insights. [PERSON] et al. [11] evaluated CT based radiomics to predict PCa aggressiveness with promising results. In a novel attempt, [PERSON] et al. [12] evaluated the use of CBCT radiomics to address tumour staging, GS, PSA, RG and BCR. Monitoring and classifying the outcome prognosis during treatment may help to avoid extra-invasive procedures or another MRI. This work intends to evaluate a model in borderline favourable vs. unfavourable (3+4 vs. 4+3) PCa cases, providing a tool that may trigger a more conservative approach, avoiding over-treatment and reducing the side effects of radiation exposure. Following this introductory section is a summary of some of the work done in PCa radiomics using multiple imaging modalities. The idea is to gather information on the most-used feature selection and classification techniques. Section 3 describes the dataset and the methods used to build the evaluated pipelines. Section 4 presents the obtainedresults, highlighting the six best pipelines (from 98 evaluated). Finally, Section 5 presents the main conclusions drawn.
# Development and Research of a Medium Vertical Dipole Electromagnetic Pulse Simulator
## 4 Experiments and Characteristics Research  
In an ideal dipole antenna, the electrical pulse input from the pulse source is converted into an electromagnetic wave radiated outward while maintaining all parameters as unchanged. However, in actual engineering implementation, the introduction of supporting structures, wire grid structures, and loading resistors can cause a mismatch of the antenna structure and impedance, resulting in distortion of the waveforms of the electrical pulse input to the antenna and the radiation field generated from the antenna.  
To verify whether the simulator's design meets expectations, it is necessary to measure the parameters of the radiation field and its distribution around the antenna. In order to obtain the best design, it is also necessary to measure the radiation field waveforms at different angles and distances from the antenna origin under different cable numbers of the antenna, different processing methods at the end of the antenna, and different resistive values loaded on the antenna cables. Based on the test results, the impact of the different factors on the simulator's radiation field waveform and its change rules are analyzed, and it can be used as a basis for the optimization of the simulator's design.  
The experimental setup for measuring the radiation field around the simulator is depicted in Figure 5, where the origin of the coordinate system is taken as the projection of the cone vertex of the inverted-cone antenna, and the z-axis represents the upward direction of the antenna. The x-axis points towards the north and the y-axis towards the west. The vertical polarized electric field component is measured on a radial extension line with different circumference angles. For each measurement, several points at different distances from the antenna's center in the same direction were chosen, and the field waveform was recorded three times at each point. To ensure the radiation field's symmetry around the simulator's circular direction, the number of wire-mesh antenna cables was determined to be 24 to 48 [21]. To meet the measurement requirements, a series of self-developed pulse-electric field measurement systems were used with a bandwidth of 10 kHz to 500 MHz, measuring range of 100 V/m to 1000 V/m, and a background noise of less than 20 mV [22; 23; 24].  
Figure 5: Test layout of the developed dipole EMP simulator.
# Resource Allocation in Unmanned Aerial Vehicle (UAV)-Assisted Wireless-Powered Internet of Things
## 2 Related Work  
The WPT technique, as an essential way to solve the limited energy problem in IoT, has been researched by many academics. In reference [10], an energy efficient power management approach is proposed according to the user's Quality of Services (QoS) requirements in WPCN, and the optimal power of the power stations can be obtained based on the authors' adaptation algorithm. In [11], multiple users can obtain energy from fixed power stations in WPCN, and through the combination of power control and time allocation, the problem of network energy efficiency maximization is studied. From the above references, we can view that in the conventional WPT system, the energy source is relatively fixed in position. Recently, an unmanned aerial vehicle (UAV) has been used in many applications, such as traffic monitoring [12], data transmission [13], communication enhancement [14; 15], and so on. In order to solve the fixed energy source problem in the conventional WPT system, UAV can be used due to its inherent agility and on-demand quality [16], which has attracted considerable attention in the IoT [17; 18; 19; 20].  
In order to supply removable energy, UAV is used as new kind of power source for IoT devices [21; 22; 23; 24; 25; 26]. References [21; 22] have studied the resource allocation problem of the UAV auxiliary network. Using UAV as the energy source, this network can provide energy and information collection services for the devices and maximize the transmit rate to improve the system throughput. [PERSON] et al. [23] have established an energy consumption model of the UAV system to solve the energy-efficient communication problem via optimizing the trajectory of UAV, and have improved the energy utilization rate of the UAV system. In [24], the relay function was installed on the UAV, and an approach was proposed to optimize the throughput in the UAV-based relay system. The transmit power and relay trajectory were optimized in this paper. [PERSON] et al. [25] studied a mobile relay system that supports UAV to achieve tradeoff between the maximum spectrum efficiency and bits/Joule energy efficiency by taking advantage of the new degree of freedom of UAV trajectory design.
## 5 Discussion  
In this study, the main aim was to investigate the use of a character-based model using classical and CNN machine learning algorithms to solve the problem of identifying fine-grained Arabic language dialects in the form of a written short text and without word notation.  
In general, the results of all the considered algorithms demonstrated low performance for the four-way task, indicating how difficult the problem is for the existing approach. The same result was reported in the literature for such a very fine-grained ADI problem, particularly when the dialects were from very close regions (i.e., at a province level) because the degree of similarity between them was very high.  
However, the results of the four-way ADI problem revealed that the classical machine learning algorithms based on a character model outperformed the CNN approach that was also based on a character model. This outcome indicated a need for further development in the architecture of the CNN approach to deal with such fined-grained dialects on a multiway ADI problem. By contrast, the CNN approach outperformed the other considered classical machine learning algorithms in the two-way ADI problem.  
The results of the classical machine learning algorithms revealed that the best parameter for the TF-IDF was a combination of character n-grams model ranging from unigrams to four-grams, with a max_df equal to 0.75 and a min_df equal to 1. Among the considered algorithms, the LR achieved the highest performance in the four-way and three-way ADI problems.  
The reason why most of the considered algorithms performed poorly in identifying the Janobi class was the high degree of similarity between the Janobi class and other classes, particular the Najdi and Hijazi classes. Most of the disagreements between our annotators occurred in that class as well. This situation might be due to the fact that people from the Janobi region have either lived there some time in their life or grown up in the Hijaz or Najd regions in Saudi Arabia. This indicates evidence that the text dialect of the Janobi region found on the Internet has been mingled with other dialects in Saudi Arabia.  
Overall, it is not surprising that the accuracy of all considered algorithms ranged from 33.2% to 40.9% for the four-way, and from 43.1% to 47.0% for the three-way identification problem.
# Simplified Integrity Checking for an Expressive Class of Denial Constraints
## 2 Related Work
Once illegal updates are detected, it must be decided how to restore a consistent database state. We targeted a preventive approach that avoids illegal updates completely. Other approaches, instead, prefer to restore consistency via corrective actions after an illegal update--typically a rollback--but several works compute a _repair_ that changes, adds, or deletes tuples of the database in order to satisfy the integrity constraints again. The generation of repairs is a nontrivial issue; see, e.g., [40; 41; 42; 43; 44] for surveys on the topic. In some scenarios, a temporary violation of integrity constraints may be accepted provided that consistency is quickly repaired; if, by nature of the database application, the data are particularly unreliable, inconsistencies may be even considered unavoidable. Approaches that cope with the presence of inconsistencies have been studied and gave rise to _inconsistency-tolerant integrity checking_[45; 46; 47]. Besides being checked and tolerated, inconsistency can also be measured, and numerous indicators have been studied to address this problem [48; 49; 50; 51; 52]. An orthogonal research avenue is that of allowing inconsistencies to occur in databases but to filter the data during query processing so as to provide a _consistent query answer_[40], i.e., the set of tuples that answer a query in all possible repairs (without, of course, actually having to compute all the repairs). This, however, has repercussions on the complexity of query answering. Integrity checking has been applied to a number of different contexts, including data integration [53], the presence of aggregates [54; 55], the interaction with transaction management [56], the use of symbolic constraints [57], approximate constraints [58], big data [59], and data clouds [60]. We also observe that integrity checking is also commonly included as a typical part of complex data preparation pipelines for subsequent processing based, e.g., on machine learning or clustering algorithms [61; 62; 63; 64] on data collected from various sources, such as RFID [65; 66], pattern mining [67], crowdsourcing applications [68; 69; 70], and streaming data [71]. More recent works in integrity checking have covered a wide spectrum of application contexts, including a blockchain-based data integrity checking [72], possibly to detect insider attacks in DBMSs [73], privacy-preserving integrity checking for the cloud [74], and inconsistency management through repairs for databases under universal constraints [75], a form of integrity constraints that also captures TGDs and EGDs. However, the adopted perspective is that of tolerating and repairing inconsistencies rather than preventing their onset, as is done here.