esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
In relation to the oral processing of the bars, the results showed significant differences in the chewing duration and number of chews required, with the EX bar taking longer to chew and requiring more chews than the AP bar (\(p\) = 0.013, ES \(>0.8\) and \(p\) = 0.009, ES = 0.7, respectively). However, the mean and minimum jaw opening width was lower for the EX bar (\(p\) = 0.014, ES = 0.4; and \(p\) = 0.013, ES = 0.4, respectively). Likewise, the mean jaw closure distance was significantly lower with the EX bar compared to the AP bar (\(p\) = 0.009, ES = 0.4). The remaining variables showed no significant differences (\(p>0.05\)) between the two bars (Table 3).  
Regarding the effect of eating the bar on the performance variables analysed, no significant differences (\(p>0.05\)) were observed for any parameter (Table 4). Likewise, no differences were found in the perception of effort required (AP vs. EX: 6.1 \(\pm\) 0.6 vs.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Variable**} & **AP Bar** & **EX Bar** & \multirow{2}{*}{**\(p\) (ES)**} \\  & **Mean \(\pm\) SD** & **Mean \(\pm\) SD** & \\ \hline Duration (s) & 32.71 \(\pm\) 6.06 * & 39.79 \(\pm\) 10.57 & \(p\) = 0.013 (\(>\)0.8) \\ Number of chews (n) & 43.30 \(\pm\) 10.01 ** & 51.80 \(\pm\) 12.21 & \(p\) = 0.009 (0.7) \\ Mean time (cs) & 76.50 \(\pm\) 6.50 & 76.81 \(\pm\) 6.90 & \(p\) \(>0.05\) \\ Minimum time (cs) & 54.02 \(\pm\) 6.01 & 51.50 \(\pm\) 3.60 & \(p\) \(>0.05\) \\ Maximum time (cs) & 139.25 \(\pm\) 28.28 & 151.75 \(\pm\) 24.89 & \(p\) \(>0.05\) \\ Average opening (mm) & 13.54 \(\pm\) 2.66 * & 12.41 \(\pm\) 2.76 & \(p\) = 0.014 (0.4) \\ Minimum opening (mm) & 5.55 \(\pm\) 2.26 * & 4.64 \(\pm\) 1.92 & \(p\) = 0.013 (0.4) \\ Maximum opening (mm) & 21.48 \(\pm\) 2.81 & 21.56 \(\pm\) 3.76 & \(p\) \(>0.05\) \\ Average closing (mm) & 13.73 \(\pm\) 2.64 ** & 12.51 \(\pm\) 2.77 & \(p\) = 0.009 (0.4) \\ Minimum closing (mm) & 5.35 \(\pm\) 2.47 & 4.77 \(\pm\) 1.62 & \(p\) \(>0.05\) \\ Maximum closing (mm) & 22.08 \(\pm\) 3.18 & 21.82 \(\pm\) 3.34 & \(p\) \(>0.05\) \\ Speed (mm/s) & 17.90 \(\pm\) 3.74 & 16.54 \(\pm\) 5.06 & \(p\) \(>0.05\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of oral processing of the Aptonia (AP) and Etixx (EX) bars. The data are expressed as mean values with their standard deviations (\(SD\)s), significances (\(p\)), and Cohen effect sizes (ES).  
5.7 \(\pm\) 0.5 points; \(p\) > 0.05) or heart rate (AP vs. EX: 126.1 \(\pm\) 4.4 vs. 124.9 \(\pm\) 5.8 points, \(p\) > 0.05) when the 15 min sections for each bar were compared.  
The results in terms of the perception of satisfaction while consuming each bar were similar overall (3.22 \(\pm\) 0.97 points), with no significant differences (\(p\) > 0.05) in any of the items analysed (Figure 3). The three most identified textures in the AP bar were pastiness (90%), stickiness (90%), and softness (80%), while for the EX bar, they were lumpiness (90%), hardness (80%), and stickiness (70%).
## 3 Materials and Methods
### Rule Extraction from Neural Network Ensembles  
Particular MLPs, such as those shown in Figure 4, were reported in [29]. Their precise name is _Interpretable Multi-Layer Perceptrons_ (IMLPs). IMLPs often include two hidden layers, with the feature that any neuron in the first hidden layer receives only one connection from an input neuron and the bias neuron. Furthermore, the activation function in the first hidden layer is a step function. Above the first hidden layer, neurons are fully connected.  
Figure 5: An MLP with two hidden layers that represents a propositional rule with a unique antecedent (\(x_{1}\leq t_{1}\)). The activation function of the output layer is the identity, with coefficient \(w\) representing the rule weight.  
With IMLPs, the training process was performed with a simulated annealing algorithm, while rule extraction was carried out with the ESPRESSO logic minimizer [30]. More precisely, the binary activations of the first hidden layer put into play a Boolean minimization problem with respect to the IMLP network responses. Later, the step activation function in the first hidden layer was generalized by the staircase activation function with the DIMLP architecture [6]. The staircase function approximates the sigmoid function; thus, it provides quantized values of the sigmoid. With DIMLPs, the training algorithm is a modified back-propagation algorithm [6; 12].  
The rule extraction algorithm for a single DIMLP is briefly described here; it includes three main steps, the details of which are reported in [6; 12]. In the first step, the relevance of axis-parallel hyperplanes is calculated. Specifically, this relevance measure corresponds to the number of samples viewing a hyperplane as the transition to a different class. In the second step, a decision tree is built with all of the training samples. The class represented at the leaves is the one provided by the neural model. In the third step, all of the paths between the root and the leaves are represented as propositional rules. At this point, rules are disjointed, and generally, their number is large, as is their number of antecedents. Then, a pruning strategy is applied; it removes as many antecedents and as many rules as possible.  
Rule extraction from ensembles of DIMLPs is achieved with the rule extraction algorithm that was briefly described above, as it can be applied to any DIMLP with any number of hidden layers. It is worth noting that an ensemble of DIMLP networks can be viewed as a single DIMLP with an additional hidden layer [12]. Hence, rule extraction can also be performed for a DIMLP ensemble.
## 6 Evaluation Metrics  
There are two different types of performance evaluation metrics often used. The first one evaluates the model performance (Table 13) and the second one is used for portfolio performance (Table 14). The confusion matrix is used to evaluate the classification models' performance for a given set of test data. Figure 11 shows the confusion matrix of binary classification and has only two conditions positive and negative.  
The confusion matrix is a matrix that is used to assess the performance of classification models for a certain set of test data by comparing those models against one another. The following cases are included in the table above.  
* **True Positive (TP):** YES, as predicted by the model, and YES, as measured by the actual value.
* **True Negative (TN):** The model predicted NO, and the actual value was also NO.
* **False Positive (FP):** YES was predicted by the model, but the actual value was NO.
* **False Negative (FN):** When the model predicted NO but the actual value was YES.
## 6 MANTIS
### Communication Protocol Support  
MOS implements the network stack in two parts. The first part of the network protocol stack is implemented in user space, as shown in Figure 4. That part contains the implementation of layer 3 (and above) protocols. A second part contains the implementation of the MAC and PHY layer operations. The rationale behind implementing the layer 3 and above functionality in user space is to provide flexibility. If an application wants to use its own data-driven routing protocol, then it can implement its routing protocol in user space. The downside of the approach is performance _i.e._, the network protocol stack has to use APIs provided by MANTIS instead of communicating directly with the device driver and hardware. This results in many context switches, resulting in computational and memory overheads.  
The second part of the networking protocol stack is implemented in a COMM layer. The COMM layer primarily implements synchronization and MAC layer functionalities. The COMM layer provides a unified interface for communication with device drivers, for interfaces such as serial connections, USB, and radio devices. The COMM layer also performs packet buffering. It is possible that packets arrive from the network for a thread that is not currently scheduled. In such scenarios the COMM layer will buffer packets. Once the thread gets scheduled, the COMM layer passes a pointer to the data to the concerned thread.  
MANTIS OS does not provide support for multicast applications, furthermore it does not provide an implementation for group management protocols. MANTIS also does not provide support for real-time multimedia applications in its communication protocol stack. On the other hand MANTIS does provide a facility to implement custom routing and transport layer protocols on top of the MAC layer. Hence, one can implement real-time transport and routing protocols for multimedia sensor networks in MANTIS.
# Post-Quantum Digital Signature: Verkle-Based HORST
###### Abstract  
The security of commonly used cryptographic systems like RSA and ECC might be threatened by the future development of quantum computing. Verkle-based HORST decreases the size of signatures by 75% (from 12.8 KB to 3.2 KB) and enables O(1)-sized proofs by replacing Merkle trees with Verkle trees. Because verification shifts from O(log t) to constant time, it is ideal for blockchain and IoT applications that require short signatures and fast validation. In order to increase efficiency, this study introduces Verkle-based HORST, a hash-based signature method that uses Verkle trees. Our primary contributions are the following: a formal security analysis proving maintained protection levels under standard assumptions; a thorough performance evaluation demonstrating significant improvements in signature size and verification complexity in comparison to conventional Merkle tree approaches; and a novel signature construction employing polynomial commitments to achieve compact proofs. The proposed approach has a lot of benefits for real-world implementation, especially when dealing with situations that call for a large number of signatures or settings with limited resources. We offer comprehensive implementation instructions and parameter choices to promote uptake while preserving hash-based cryptography's quantum-resistant security features. Our findings suggest that this method is a good fit for post-quantum cryptography systems' standardization.  
Keywords:quantum cryptography; Merkle tree; HORS; HORST; hash-based digital signatures; Verkle tree; Verkle-based HORST; cryptographical application +
Footnote †: journal: Cybersecurity and Privacy
## 3 Bearing Estimation Methods
### Rotation Method of Maximum Radial Power  
The rotational method of maximum radial power is based on measuring ice seismic waves for which the direction of particle motion is oriented radially outward from the source [23]. Therefore, the maximum radial signal power as a function of the horizontal look angle is built. By continuously rotating the horizontal azimuth from \(0^{\circ}\) to \(360^{\circ}\), the maximum value is obtained. The angle of maximum power provides the optimal estimate of the source bearing. The maximum radial power function [23] is  
\[\psi(\theta)=\sum_{t=1}^{T}r_{t}^{2}(\theta)=\cos^{2}\theta{\sum x_{t}^{2}+\sin ^{2}\theta{\sum y_{t}^{2}+2\cos\theta\sin\theta{\sum x_{t}y_{t}}}} \tag{1}\]  
In Equation (1), \(\theta\) is the incident angle in the horizontal plane, \(t\) stands for a certain time, and \(x_{t}\) and \(y_{t}\) denote the discrete time series of particle displacement recorded in the \(x\)- and \(y\)-directions of a geophone, respectively. \(r_{t}\) is the horizontal (radial) particle motion at the time. By calculating the derivative of the maximum radial power function, the maximum value is obtained when the derivative is zero. The angle \(\theta\) of maximum power, as shown in Equation (2), is the estimated bearing [23].  
\[\theta_{\max}=1/2\tan^{-1}\left[\frac{2{\sum x_{t}y_{t}}}{{\sum x_{t}^{2}-\sum y _{t}^{2}}}\right] \tag{2}\]  
Figure 2: Field trial geometry. (D is the depth of the acoustic source, R is the horizontal distance between the source and the geophone).
# How to Adopt BIM in the Building Construction Sector across Greece?
## 3 European Strategy on BIM--What's Happening in Greece?  
### European Strategy about BIM  
As noted, the exploitation of BIM was established in Europe with Directive 2014/24/EU. According to this directive [7], the European Parliament established a working group (EUBIM Task Group) aiming at the treatment of two pilot applications: (a) an application aiming to the construction of new buildings and (b) an application aimed at the maintenance of existing buildings. After the completion of the group's work (June 2018), the European Parliament advanced the pilot application of BIM to three parliamentary buildings for the total of the parliament buildings to be included in the application within qo years.  
Through the above pilot application, it is shown that the public authorities play an important role in the promotion of the BIM use. This conclusion was reached by [PERSON] and [PERSON] [26], whose research has focused on the role of public sector for BIM adoption, and [PERSON], [PERSON] and [PERSON] [27], who studied case studies across Europe on the role of the various stakeholders in BIM procedures. The EUBIM Task Group, as a leading European public authority group, which represents the authorities' interest regarding the digitization of the EU construction sector, is expected to play an important role in the future. The EUBIM Task Group's vision is to encourage the common use of BIM as \"digital construction\" in public, not just private, works with a common goal the improvement of public value for money, the quality of public real estate and the viable competitiveness of the industry. Indeed, as [PERSON], [PERSON] and [PERSON] [28] underline, BIM should be firstly used in the public sector in order to promote its use in the private sector, later, through publishing specific guidelines.  
The above working group compiled 4 documents--protocols that describe the BIM application procedure as follows:  
* Creation Protocol: determines the creation method of a BIM for an existing building, as well as the test method for the delivered BIM.
* Project Protocol: for how the BIM is applied during the construction phase of a building.
* Maintenance Protocol: determines the way of creation of a BIM during the maintenance phase of a building.
* Charter: a management protocol that determines which information is included in the model depending on the phase of the building's life (construction or maintenance).  
These documents are public European documents and, therefore, available for consultation. The EUBIM Task Group has also created the \"Handbook for the introduction of building information modelling by the European Public Sector\" [29], in which the basic guidelines and the experience and the relative action of other countries (United Kingdom, France, Germany, Sweden, etc.) are given.  
Finally, it should also be underlined that in some countries, not only in Europe but also elsewhere, many organizations recognize BIM's value-adding potential and thus guidelines and reports dedicated to define and explore the requirements and deliverables of BIM (Table 1).
## 1 Introduction
As [PERSON] and [PERSON] depicted in the conclusion section of their article, in which they collated roughly 70 different studies, they inferred that several data sets are necessary for the field of software fault prediction [6]. This study developed three separate software, including Accounting, Staffing, and Inventory software, using both the eXtreme Programming (XP) [7] software development methodology and the test-driven development (TDD) [8] approach to contribute to the resolution of this problem. These applications were developed by a development group consisting of seven people in the information technology department of a university. The software in question were used for over one year and their faults were recorded by a developed software management tool. A data set named SFP XP-TDD was created in order to make machine learning (ML) and deep learning (DL)-based software fault predictions. Data regarding some Chidamber and Kemerer (CK) metrics and other well- known metrics such as Cyclomatic Complexity, Comment Rate, Average Depth, Max Depth, Line Count, Statement Count, and Error Count [9] were obtained from these software. The primary motivation of this work is twofold: Initially, a novel software fault prediction data set named SFP XP-TDD was introduced to the literature and made publicly available for further studies in the field. Secondly, the study also provides the experimental outcomes of a model with a layer of recurrent neural networks (RNN). The study further used the SFP XP-TDD, Eclipse data sets [10], and the Apache Active MQ datasets [11] in addition to the data set developed to test the performance of the proposed deep learning method. Experimental results demonstrated that an RNN-based approach model is more accurate than many other machine learning and deep learning algorithms in software fault prediction. The study also provides the effectiveness of the Rotation Forest classifier ensemble in software fault prediction analyzed empirically. The rest of the paper is organized as follows: The Related Work section presents a comprehensive literature survey on software fault detection. In the Materials and Methods section, applied methods and algorithms in this study from machine learning and deep learning scope are introduced with their details. Then, the Experimental Results and Discussion section presents the experimental settings and results, and discusses the experimental results obtained, threads to validity. Finally, the paper is concluded with the Conclusions and Future Work section.
###### Abstract  
This paper addresses the escalating threat of malicious jamming in next-generation communication systems, propelled by their continuous advancement in speed, latency, and connectivity. Recognizing the imperative for communication security, we propose an efficient jamming detection method with distinct innovations and contributions. Motivated by the growing sophistication of jamming techniques, we advocate the adoption of the error vector magnitude (EVM) metric, measured in IQ symbols, deviating from traditional received signal strength and bit error rate-based measurements. Our method achieves enhanced jamming detection sensitivity, surpassing existing approaches. Furthermore, it introduces low complexity, ensuring resource-effective detection. Crucially, our approach provides vital jammer frequency information, enhancing counteraction capabilities against jamming attacks. It demonstrates stable results against varying system parameters, such as modulation type and code rate, thereby contributing to adaptability. Emphasizing practicality, the method seamlessly integrates into 5G and LTE systems without imposing additional overhead. Versatility is demonstrated through successful operations in diverse scenarios that are run by extended simulation conditions. Theoretical analysis substantiates these advantages, reinforcing the validity of our methodology. The study's success is further validated through laboratory experiments, providing empirical evidence of its effectiveness. The proposed method represents a significant step toward fortifying next-generation communication systems against evolving jamming threats.  
jamming detection; EVM; 5G; resource block +
Footnote †: journal: _electronics_
## 3 Results  
Figure 3 shows the spectral RIAs of the _high_- (a), _medium_- (b), and _low_-OH (c) samples in the visible/near-IR domain during the irradiation and up to 60 min after its end. In addition, the insets show the RIA growth and recovery kinetics at 450 nm and 650 nm. For all cases, a monotonic increase of the spectral RIA is observed, except for the red wavelength range of the _medium_-OH fiber. Indeed, the 450 nm kinetics increase rapidly at 1 dB/m up to \(\sim\)10 kGy for both the _high_- and _medium_-OH samples and at 4 dB/m up to \(\sim\)30 kGy for the _low_-OH. Instead, the kinetics at 650 nm follow different trends. For the _high_-OH, it continuously grows with no saturation trend. The _medium_-OH sample presents an unexpected non-monotonical behavior, reaching a local maximum RIA value (0.5 dB/m) at \(\sim\)5 kGy, after which the RIA decreases before increasing again with a constant slope at higher doses. Finally, the RIA of the _low_-OH fiber follows the trend of the kinetic at 450 nm, since the tendency is dominated by the tail of the UV bands, reaching a very low saturation value (0.02 dB/m) at \(\sim\)0.1 kGy. The most resolved features in the spectral measurements are the presence of the \(\sim\)620 nm centered absorption band (_high_- and _medium_-OH content samples) overlapped by the tail of a UV absorption related to point defects absorbing at higher energies. The above-mentioned band is not observed in the _low_-OH sample for which the UV band is very intense. It is interesting to note how the amplitude of the 620 nm  
Figure 2: Attenuation spectra of the pristine _medium_-OH sample before and after the H\({}_{2}\) loading and thermal treatment (TT).  
band is coherent with the OH concentration increase in the fibers and in countertendency with the UV tail.  
Figure 3: Radiation-induced attenuation (RIA) spectral growth during the irradiation (left) and spectral decrease during the recovery (right) in the _high_-OH (**a**), the _medium_-OH (**b**), and the _low_-OH (**c**) sample. Both insets show their respective RIA kinetics at the wavelengths of 450 nm and 650 nm.  
Another spectral characteristic observed in the _medium_-OH content fiber is an unstable wide band centered between 650 and 770 nm, which explains the local maximum at ~5 kGy observed in the RIA kinetic and disappears at higher doses. Regarding the RIA recovery kinetics, two types of decays are eVident: one representing the contribution of the UV tail, which recovers almost all the transmission properties in one hour from the irradiation end, while the defects responsible for the 620 nm peaked band seem more stable in the same time frame at room temperature.  
Figure 4 reports the RIA spectra during and up to one hour after the irradiation end for the treated _medium_-OH sample. The two most significant differences with respect to the non-treated counterpart, Figure 3b, are: a greater attenuation due to the tail of the band peaked in the UV region and the disappearance of the local maximum in the 650 nm kinetic.
# Commercially Biochar Applied for Tartrazine Removal from Aqueous Solutions
## 3 Results and Discussion
### Testing the Biochar Efficiency as Tartrazine Adsorbent from Synthetic Aqueous Solutions
#### 3.2.3 The Influence of the Adsorption Dose on the Adsorption Process  
In order to characterize the adsorption process as a function of the adsorbent dose, the degree of tartrazine removal was monitored while the adsorbent dose was increased from 0.2 mg L\({}^{-1}\) to 1.0 mg L\({}^{-1}\). The measurements were conducted at 30 \({}^{\circ}\)C temperature, stirring the mixture of 5 mL tartrazine solution of 5 mg L\({}^{-1}\) concentration and the corresponding amount of adsorbent at 400 rpm for 20 min for each sample. In Figure 5, which shows the removal efficiency with the adsorbent dose, can be observed a rather oscillatory trend in the removal degree.  
In order to obtain a good removal efficiency using the smallest possible amount of adsorbent, further studies were carried out using 0.9 mg L\({}^{-1}\) adsorbent dose.