esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions
#### Limitations and Future Research  
There are several limitations that have been identified in this research, such as the fact that this article considers self-reports of the perspectives that students have without presenting a validation of academic performance and thus results of how efficient the proposed system is cannot be presented [138; 139]. Another limitation that should be mentioned is that the system has not been tested in a real learning mode with users who would actually use this solution in the learning process [140].  
Although it has been shown that generative artificial intelligence tools are useful for rapid learning, there are still drawbacks when it comes to acquiring long-term knowledge. The article [134] demonstrated how students performed worse with ChatGPT compared to those who used a traditional learning method.  
Although this paper proposes a conceptual architecture that takes into account students' impressions of using an LLM, for future work this system can be validated in terms of its efficiency. This stage is foreseen as a direction in future research. Therefore, the evaluation plan takes into account significant and specific metrics of these solutions, such as the gains that students have in terms of learning, the effectiveness in completing tasks, the shortest time interval in which the learning assistant responds, and the degree of customization of the content for each user in relation to their needs [122]. Another way to test the proposed system would be to carry out a comparative analysis between experimental groups in order to see the real impact of generative artificial intelligence. It is also intended to explore intercultural differences in the perspective on AI tools [138].  
This article contributes to research on information systems/software engineering and adaptive learning solutions in education by presenting a concrete architectural approach to incorporate AI and generative AI into learning, based on concrete results gathered from students who are generative artificial intelligence users, as well as on a rigorous analysis of existing platform architectures.  
Conceptualization, C.-M.M., R.B. and A.T.; methodology, R.B.; validation, C.-M.M., R.B., A.B., A.T. and D.-D.P.; investigation, C.-M.M., R.B., A.C., A.T. and A.B.; resources, C.-M.M., A.C. and D.-D.P.; writing--original draft preparation, C.-M.M., A.C. and A.B.; writing--review and editing, C.-M.M.; visualization, C.-M.M., A.B. and D.-D.P.; supervision, C.-M.M.; and project administration, C.-M.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The dataset is available at the following address: [[https://data.mendeley.com/datasets/ymg9](https://data.mendeley.com/datasets/ymg9) ns6 kn]([https://data.mendeley.com/datasets/ymg9](https://data.mendeley.com/datasets/ymg9) ns6 kn) (accessed on 30 December 2024).  
The authors declare no conflicts of interest.
## 3 Results and Discussion
### Irradiation Intensity Dependence  
In addition to the solvent dependence of the laser-induced absorbance change spectra, we investigated the irradiation intensity dependence of the absorbance change for newly prepared water and ethanol samples (Figures 4 and 5).  
Figure 4a shows the absorbance change spectra in the water sample for the irradiation intensity, from 3.7 to 25.7 W/cm\({}^{2}\). Figure 4b displays the absorbance change vs. irradiation intensity at the absorbance increase peak (444 nm) and absorbance decrease peak (413 nm). Both the increase and decrease depended nonlinearly on the irradiation power and converged as the irradiation intensity increased. The observed curves could be fitted to \(y=\mathrm{A}(1-\mathrm{exp}(-\mathrm{B}x))\) with the fitting parameters in Table 4.  
Figure 4: (**a**) The laser irradiation intensity dependence of the absorbance change spectra for the water sample (colored solid lines) and sample absorption spectrum (dashed line). (**b**) Absorbance increase peak values (green circle) and decrease peak values (blue square).  
For the absorbance decrease, the fitting parameter A was \(-0.0101\), which indicated the maximum attainable change in the F monomer peak absorbance in the limit of the infinite irradiation intensity. This maximum change (decrease) in the absorbance was 70 times smaller than the sample absorbance considering the cell thickness, indicating that only a part of TPPS molecules within the laser irradiation spot can change its aggregation states.  
Figure 5 shows the absorbance change spectra in the ethanol solution for the same irradiation intensity as that in Figure 4. The absorbance change spectra in ethanol were similar to those in water, observed as the increase in the broad spectral range and decrease at the monomer absorption peak. However, this sample's dependence on the irradiation intensity was linear over the whole intensity range, differing from that for the water solution sample.  
In the water solution sample, the absorbance change was large and seemed to be saturated. The maximum change estimated from the saturation behavior was smaller by two orders of magnitude than the original sample absorbance. In contrast, in the ethanol sample, the absorbance change was smaller and depended linearly on the irradiation intensity. These features could be explained qualitatively as follows: There was an upper limit to the ratio of aggregated molecules to monomer molecules in the laser-irradiated volume because only those molecules that were located statistically as closely as they could interact were aggregated. The capability of the formation of J-aggregate depends on the solvent species, resulting in the different intensity dependence in different solvents observed here.
# Compatibility of Different Automotive Elastomers in Paraffinic Diesel Fuel
## 3 Results and Discussion  
### Properties of Rubbers  
A natural phenomenon occurring in the course of a fuel interacting with rubber compounds is their swelling, which causes the formation of a tight connection between fuel supply system elements. The change in the volume of conventional fuels depends, among others, on the aromatic hydrocarbon content in the fuel composition. With the regard to the use of synthetic hydrocarbons as fuel (without blending with a petroleum component), such fuels are free from aromatic compounds, indicating that rubber seals will not ensure sufficient tightness, leading to fuel leakage. The EN 590 standard only limits the content of polycyclic aromatic hydrocarbons to 8% (m/m), when the standard defining jet fuel properties [48] stipulate the aromatic hydrocarbon content range at 8-25% (\(v/v\)). However, the lower value is determined only to ensure adequate rubber swelling in order to avoid potential leakage from fuel and distribution systems.  
Figure 1 shows the change in the volume of O-rings made from two types of rubber. The impact of NBR rubber used in the automotive industry on diesel fuel leads to a volume change of approx. 5%. Adding methyl esters slightly increases elastomer volume relative to diesel fuel. The GTL synthetic component (which does not contain aromatic hydrocarbons) causes virtually no changes to the rubber ester volume. Furthermore, it can be concluded that KFM rubber is less susceptible to volume changes resulting from contact with fuel.  
The impact of petroleum fuels on rubber compounds also leads to their increased mass (Figure 2), however, this occurs at a lower rate than the volume change. Synthetic components free of aromatic hydrocarbons virtually do not react with rubber compounds. Generally speaking, the increase in the mass and volume is associated with elastomer swelling, which is induced by absorbing fuel and polymer chain relaxation and is related to the affinity between the fuel and the elastomer.  
The interaction of all fuel samples with elastomers resulted in a decrease in elastomer hardness (Figure 3). This phenomenon is caused by the fact that hardening agents are added to elastomers in order to improve elastomer properties. This leads to cross-linking between their chains. After immersion in fuel, these agents dissolve, which results in decreased seal hardness.
# Pitfalls in the Detection of Hearing Loss via Otoacoustic Emissions
## 1 Introduction
Over the years, evidence about similar occurrences has circulated unofficially at audiology and ear, nose, and throat (ENT) specialist meetings, but these anomalies have never been properly assessed or evaluated. One might expect that the data in the literature regarding the performance of OAE devices would help lessen the doubts about these difficult to interpret cases, but over the last 24 years very few papers have presented rigorous data comparing different OAE systems [15; 16; 17; 18; 19]. OAEs are clinically very popular and are also chosen as the ideal tool to study the basic mechanisms of hearing [20; 21]. The need of being able to compare data across different OAE devices is an important issue, particularly when one considers recent reports of OAE issues caused by erroneous OAE calibration procedures [13]. The issue of OAE screening criteria becomes even more involved when one takes note of the data in the literature suggesting that, across different devices, there is considerable variability in OAE measurements and in the OAE detection criteria [22]. The present study is designed to answer questions about the OAE data the authors have encountered and to document the variability of the OAE data between different devices. The Accuscreen device, with its statistical OAE evaluation algorithms, is considered in many countries of Europe and elsewhere as the device of choice for infant and children hearing assessment, and it is also used for clinical assessment of adult subjects. The objective of this study is to compare the data acquired from the new touchscreen Accuscreen device with the outcomes from the previous Accuscreen model, using the ILO-292 equipment as the gold standard. To identify the factors that might be contributing to different performances between the tested devices, very high-quality OAE data are required. To minimize issues related to OAE recording variability, which are often observed in neonates, the data for this study are recorded from adult subjects. This provided important advantages: (i) The software and hardware for the OAE data collection of all these devices is the same for neonates, children, and adults, and so the conclusions from an adult group can be easily extended to another population of interest; (ii) the adult OAE responses present significantly lower levels of noise, and so effects related to the recording device are more easily identified; (iii) for every subject it is possible to have supporting audiometric data on hearing thresholds, i.e., data that are not easily available for neonates or young children.
# Structural Evolution of Polyimide-Derived Carbon during Phosphoric Acid Activation
## 3 Results and Discussion  
### Porous Structure  
Nitrogen adsorption-desorption isotherm for parent BM-DVB copolymer belongs to type II of IUPAC classification [57] characteristic to adsorption on nonporous or macroporous adsorbents (Figure 2a). On the contrary, the isotherms for carbons obtained bycarbonization of BM-DVB copolymer can be attributed to a combination of type I and IVa of IUPAC classification. A steep rise of nitrogen uptake at very low p/p\({}^{0}\) is due to adsorption in narrow micropores with enhanced potential while the gradual increase in nitrogen adsorption at medium to high relative pressures corresponds to monolayer-multilayer adsorption in mesopores followed by capillary condensation accompanied by small hysteresis of type H4. The isotherms are typical of micro-mesoporous carbons.  
The pore size distribution in the porous polymer BM-DVB reveals a developed mesoporous structure in the range of pores from 12 to 44 nm, with a maximum at 34 nm and the absence of micropores (Figure 2b). Carbonization of a porous polymer in the presence of phosphoric acid results in a complete restructuring of the porous structure, with well-developed porosity appearing in the range of micropores and small mesopores (0.5-5 nm) and the polymer's developed mesoporous structure transforming into small rudimentary residues. Carbonization of a porous polymer without phosphoric acid, on the other hand, produces an increase in the size of mesopores and the emergence of a microporous structure. It should be noted that the microporous structure of carbon obtained without phosphoric acid is represented by pores in the range of 0.5-1.2 nm, while carbon obtained in the presence of phosphoric acid has additional pores in the range of 1.2-5 nm.  
Carbons produced in the presence of phosphoric acid have a more developed porous structure than carbons formed in the absence of acid (Table 1). Phosphoric acid enhances the formation of a microporous structure during carbonation.
# An Efficient Scalable Scheduling MAC Protocol for Underwater Sensor Networks +
## 3 Challenges and Requirements
### Impact of Long and Variable Propagation Delays  
Long propagation delays in underwater acoustic channels mean that choosing the right MAC protocol design is critical [43]. Traditional mechanisms for collision detection, such as carrier sense, are no longer effective. The fundamental approach of using Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), for instance, is to avoid sending data in a busy channel, i.e., a node first listens to the channel before transmitting data. If the channel is idle, the data packet can be transmitted [44]. In underwater acoustic networks, however, due to long propagation delays, even when a node overhears a signal, it does not mean that its neighbours are experiencing the same thing at the same moment. The whole idea of detecting collision by listening to the channel is therefore not valid in this scenario. The performance of some advanced collision detection mechanisms for terrestrial wireless networks, however, such as the RTS/CTS handshake-based approach, is very low in underwater acoustic networks. Figure 1 shows the basic workflow of the classic RTS/CTS approach.  
When node A wants to communicate with its neighbouring node B, it first transmits an RTS message (denoted as RTS in the diagram). Once B receives the message, it responses with a CTS message to confirm to the sender and triggers data transmission. The CTS message also informs other neighbours to avoid any potential collisions. After node A receives the CTS message, it starts delivering its data packet. After receiving the DATA packet, node B sends an ACK to node A to conclude the communication process.  
Assuming the time spent on RTS/CTS/DATA/ACK are denoted as \(T_{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}{ \_}{\_}{\_}{\_}{\_}{\_}{\_}{\_}
# Electrospinning of Chitosan for Antibacterial Applications--Current Trends
## 7 Application Fields of Electrospun Chitosan Nanofibers and Chitosan Derivatives
### Food Storage
#### 7.3.1 Fruit Freshness
Regarding the fruit covered with the composite membrane, the water retention and appearance were mostly maintained, without any traces of bacteria (Figure 9). These results validate the plausible prolonged freshness of transported fruits through the optimistic application of the biocompatible CMCS/PEO electrospun nanofibers, due to their breathable structure and antibacterial effects [187]. Variations in the electrospinning and solution parameters (concentration and ratio of chitosan and PEO) resulted in optimized nanofiber properties, which were adjustable for different requirements [187].
# A Novel Covert Channel for IEEE 802.11 Networks Utilizing MAC Address Randomization
## 1 Introduction
This approach enhances the covert channel's functionality and provides a unique perspective on covert communication. * Focus on reliability--Unlike many existing covert channel implementations, we emphasize the importance of reliability. Our study addresses the need for robust message transmission and reception to ensure the covert channel's successful operation. This aspect fills a crucial gap in current covert channel research. * Novel approach to optimize the performance of IEEE 802.11 covert channel--We present a concept and implementation of the modified Selective Repeat ARQ protocol within the covert channel to prevent network congestion generated by the covert channel traffic and maintain QoS metrics at the appropriate level. * Scenario-based evaluation--We examine the results of three distinct scenarios and provide an evaluation of each. We identify and recommend the most appropriate approach for effective covert communication by considering various network conditions. This study offers a comprehensive analysis of an IEEE 802.11 covert channel, introduces transmission techniques for dense environments, and bridges gaps in existing covert channel implementations. The findings contribute to the broader understanding of covert communication and provide practical insights for enhancing covert channel performance in real-world scenarios. The article is structured into nine sections, each addressing specific aspects of the research topic. Section 2 highlights the existing IEEE 802.11 covert channels. Section 3 explores the MAC address randomization technique in detail, including emergence, current status, and plans. The proposed covert channel, presenting the underlying concept and providing in-depth details about its implementation, is introduced in Section 4. Section 5 evaluates the performance of the covert channel in two distinct scenarios, assessing metrics such as throughput, efficiency, delay, and jitter. Section 6 describes the modified Selective Repeat ARQ protocol, its adaptation and integration into the covert channel, discussing the benefits and implications of this implementation. The results of Selective Repeat ARQ protocol integration, showcasing the performance improvements achieved and analyzing the findings, are presented in Section 7. Section 8 discusses the overall results and the uniqueness of the covert channel. Finally, Section 9 concludes the work by summarizing the key findings, highlighting the significance of the research, and outlining potential directions for future research and advancements in the field.
# Feasibility Study on Grouting Compactness Detection in Sleeves Using Piezoelectric Transducers
## 2 Detection Method of Piezoceramic Transducer
### Hilbert-Huang Transform Method  
The HHT is a signal time-frequency processing method [19]. In the HHT, the intrinsic mode function (IMF) obtained via empirical mode decomposition (EMD) reflects the inherent physical characteristics of the original data. Compared with the wavelet packet energy method, a basis function is not required. However, each IMF must meet the following conditions: (1) the sum of the positive and negative values of the function must be the same as the zero-crossing point, or at most, they differ by one; (2) the upper and lower envelopes formed by the extreme values have an average value of zero [28]. The HHT can adaptively localize the signal from the characteristic time scale of the non-stationary signal. The acquired piezoelectric signal is transformed to depict its Hilbert energy spectrum, where the energy accumulated by each frequency is expressed over the entire length of time [29; 30]. In addition, the Hilbert energy is more concentrated than the wavelet energy.  
The Hilbert amplitude spectrum \(H(\omega,t)\) is obtained by applying the Hilbert transform to each IMF component after EMD, as follows:  
\[H(\omega,t)=\text{Re}\sum_{j}^{n}a_{j}(t)e^{j\int a_{j}(t)dt} \tag{5}\]  
where Re is the real part of the complex number, and \(a_{j}(t)\) and \(\omega_{j}(t)\) are the instantaneous amplitude and instantaneous frequency, respectively, of the \(j\)th IMF component.  
The Hilbert energy \(ES(\omega)\) is defined by the following equation, in terms of the square of the amplitude-versus-time integral, which expresses the energy accumulated for each frequency over the entire length of time.  
\[ES(\omega)=\int_{0}^{T}H^{2}(\omega,t)dt \tag{6}\]  
Here, \(T\) is the length of time of the signal.
## 4 Efficient FFT Algorithms
### T-Transform  
[PERSON] _et al_. [77] proposed a multicarrier system using low computational complexity transform called T-Transform that combines WHT and DFT into a single fast orthonormal unitary transform. The proposed algorithm offers a significant improvement in BER and reasonable reduction in the PAPR. Through the proposed algorithm, OFDM systems can achieve high frequency diversity gain by combining all the data samples resulting in the transmission over many subcarriers. The frequency diversity of the proposed T-OFDM system results in increased resilience over multipath fading channels. The proposed transform reduces PAPR by reducing the high peak power, while preserving the average transmitted power and data rate.  
T-transform is based on the factorization of the DFT and WHT matrices using the Kronecker product technique. Advantages of the T-transform include simple structure and low computational complexity. For example in radix-2, 16-point FFT butterfly diagram the number of stages will be four. However, the proposed T-transform butterfly diagram has only three stages and in each stage many of the butterflies are zero and do not need to be calculated. Unlike FWFT, the T-transform can be scaled up or down to any transform length.