esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
As a result, the generation of the forward-kinematic region hadrons at superhigh energies can only be studied in experiments using cosmic rays. However, this requires a large amount of Monte Carlo simulations. In order to implement the project discussed below, calculations of the development of extensive air showers containing a huge number of hadrons, electrons, positrons, \(\gamma\)-rays and muons, as well as the calculation of the observed EAS characteristics, have been started using the standard CORSIKA modeling software package, which is widely used in the international practice for experiments with cosmic particles at different levels of observation. While using the CORSIKA package, it is possible to choose from several models concerning the interaction of hadrons with oxygen and nitrogen nuclei in the atmosphere. At the first stage of our calculations, we used the QGSJet II-04 model based on the ideologies of quark-gluon strings (QGS) and quantum chromo dynamics (QCD), which describe the generation of hard hadron jets with large transverse momenta. QGSJet II-04 is one of the most popular models in international EAS experiments. The development of showers from the atmospheric boundary to the level of the location of the Tien Shan High-mountain Scientific Station (3340 m a.s.l.) initiated by various nuclei (from protons to iron nuclei) with energies of 1, 10, 30, 100 PeV (1 PeV = 10\({}^{15}\) eV) was simulated. The lateral and energy characteristics of hadrons, electrons, and muons have been obtained at various threshold values of E\({}_{\rm thr}\). The preliminary results are not unexpected and can be formulated as follows:  
1. Electrons are the most intense EAS component at the considered energies at distances of less than 1 km from the axis. 2. The PDF of hadrons, electrons, and muons strongly depends on their energies. The higher the energy of the particles, the narrower their PDF becomes. 3. The intensity of hadrons in EASs initiated by protons near the shower axis is approximately one order of magnitude higher than the corresponding intensity in iron-initiated EASs at \(E_{0}\) = 1 PeV, but the difference rapidly decreases with increasing \(E_{0}\). 4. Similar behavior is shown by muons. 5. Differences in the behavior of correlations between the average hadron energy and the distance to the axis in vertical EASs initiated by primary protons and iron nuclei are not very significant.
The deployment and utilization of underwater sensors, data acquisition through observational activities, and equipment retrieval constitute integral aspects of underwater operations. However, this approach suffers from several drawbacks, notably the absence of real-time monitoring, the inability to configure operating systems, the absence of fault detection, extended propagation delays, and limited bandwidth availability [12; 13]. In UWSNs, energy efficiency remains among the myriad of complexities encountered, and addressing this facet proves to be a formidable endeavor. Numerous researchers have investigated the most efficient ways to reduce the energy consumption of nodes. Cooperative underwater wireless sensor network co-operative (Co-UWSN) and Co-operative energy-efficient routing (CEER) protocols are two of these methods. Co-UWSNs and CEER are selected because they can enhance network performance while also serving as potential destinations and relays. However, the disadvantage of Co-UWSN and CEER is that  
Figure 1: Framework for neighbor-based energy-efficient routing protocol. collaboration occurs at the node level, which increases energy consumption and sensor node separation [14]. The primary contributions of this study include the following:  
* Energy consumption and latency reduction: The proposed routing technique introduces a novel routing scheme aimed at minimizing energy consumption and addressing latency issues. This is achieved through the utilization of neighbor node data cooperation, enabling efficient data transfer to the base station. * Neighbor node cooperation: The proposed method incorporates neighbor node cooperation to optimize energy consumption. By selecting neighbor nodes with high residual energy as neighbor head nodes (NHNs), data can be efficiently transmitted to the sink node located on the water surface. * Enhancing data reliability: Recognizing that direct data transmission does not guarantee reliability, the proposed approach employs neighbor node cooperative data forwarding. This technique effectively reduces end-to-end delay and enhances the network's overall lifetime. * Performance evaluation: The research evaluates the performance of the routing scheme using the MATLAB simulation tool. The results demonstrate improvements in energy consumption, end-to-end delay, packet delivery ratio (PDR), transmission loss, and the number of packets received. This article is structured as follows. The first section provides a concise introduction to the research topic, the research questions or objectives, and context for the study. In Section 2, a literature review is presented. Section 3 provides a thorough explanation of the research methodology. In Section 4, the simulation results are discussed. Section 5 provides a comprehensive conclusion.
## 4 Background
### Software Defined Network  
SDN is a network architecture that separates control logic from forwarding logic in a network in order to provide high flexibility and programmability [58]. The control plane is logically centralized and mainly perform control functionalities of routers in traditional IP networks, as well as providing Application Programming Interfaces (APIs) to support different services offered at the application layer [59]. SDN can support new control functions by creating software-based logic that maps the entire network with various services and applications running at the control plane [60]. The data plane consists of a network of passive switches where each switch mainly perform packet forwarding tasks. Figure 3 depicts the architecture of an SDN. This architecture consists of three main layers namely, application layer, control layer, and data layer. These layers are interconnected by the northbound interface and the southbound interface.  
The application layer has a number of programs that can perform network operations. An SDN may consist of more than one controller. The northbound interface allows communications between different controllers.  
In an SDN, the controller is the network's primary processing unit. It collects and processes all network's state data. The control layer provides services to the data layer through the southbound interface, which transmits or receives control packets regarding network events such as topology changes of data plane and addition or deletion of forwarding or security rules in the switches.  
The Open Networking Foundation (ONF) [61] created the first and most well-known southbound interface, OpenFlow, to describe how the SDN controller should communicate with the data plane. According to OpenFlow [62], rules are called \"flows\" and are stored in \"flow tables\" of switches. Various messages are defined by OpenFlow to enable communication between the switches and the controller, including connection setup messages, configuration messages, getting status, lifetime, asynchronous event, and error and experimenter messages [63].
## 1 Introduction
[25] used the concept of carpet cloaks with a metamaterial comprising a structure of perforated plates for the fabrication of a pyramidal device as an acoustic carpet cloak operating at 3 kHz. The pyramidal cloaking device comprised four perforated plate components to enable 3D cloaking. Theoretical and practical guidelines have been developed for the design of acoustic cloaks in water; however, little work has been completed on the development of cloak shells working in air. Enabling cloaking by the transformation of spatial coordinates (transformation acoustic) requires spatially anisotropic material properties along three coordinate axes. Furthermore, a cloak shell working in air requires a density or bulk modulus of less than unity in some areas of the shell; this, however, is not easy to realize physically. The metamaterials designed for use in water are inapplicable in air. Previous attempts to develop metamaterials aimed at hiding objects submerged in water were unable to provide the anisotropic material density that would be required in air. Even the scattering cancellation techniques proposed by [PERSON] et al. [23] are difficult to implement, and the resulting cloak fails when the hidden object is replaced with another object of a different shape. This failure can be attributed to the scattering interaction caused by the incongruuity between the new object and the design of the ring structure within the cloak shell. The present study focused on the design, fabrication, and evaluation of acoustic cloak shells in air. This research involved the physical realization of the acoustic cloak in air by means of the proposed cloak shell designed to spatially vary the impedance values of the cloak shell. In addition to the cloak design, we have also presented a new meta-composite structure material for practical applications. Finally, a real cloak shell was produced by 3D printing and subjected to both numerical and experimental analyses.
# Surface Subsidence Modelling Induced by Formation of Cavities in Underground Coal Gasification
## 4 Discussions  
### Numerical Simulation Discussion  
In this study, the modelling was carried out under the elasticity regime, and no rock failure was considered. In reality, due to stress concentrations around cavities and significant cavity roof deformations as modelled, as shown in the simulation results given above, parts of the cavity roof or walls would fail. In other words, the cavities are not expected to stay stable after they are created. Under the action of the vertical stress, saving of the cavity will develop upwards. However, this caring development is limited due to two reasons: (1). from the stress re-distribution perspectives, the caving eventually stops after it forms a stable arch which is strong enough to support the redistributed stresses; (2). there is a volume swelling factor that needs to be considered after the roof caves. The cavity voids are eventually filled by caved rocks, which help prevent further caving development. From the subsidence perspectives, cavity caving, if it happens, may actually reduce the surface subsidence. This is due to the caving possibly causing a more favorite stress redistribution around the cavity. Since no failure parameter data of rock and coal were obtained, the subsidence analysis was not conducted with an elastoplastic model. However, the subsidence calculation would be more adequate using a rock failure model, such as Drucker-Prager or Mohr-Coulomb models.  
This study also shows that the final stress and subsidence distribution profiles are identical between two gasification scenarios after all four cavities are formed. This is only true under the elasticity regime. If rock failure and cavity caving are considered, due to significant stress redistributions and alteration of cavity geometries after stage 1 gasification, very different initial conditions are expected for stage 2 operation and therefore, the final stress and subsidence distribution profiles of the two scenarios are also expected to be very different. A detailed modelling considering these issues should be conducted in next work. Also, the order of the gasification of cavities can affect intermediate subsidence and stress distribution, which provides guideline for the order of gasification.  
It is noted that massive gas (such as carbon monoxide, methane) would be produced and form cavities by internal pressure during gasification process. This pressure keeps the cavities in the tension condition, which affects the stability of cavities. This need to be considered in a 3D model. However, temperature, internal pressure distribution, and value need to be obtained based on field monitoring. This work will be conducted in the future.
## 4 Results
### Museum Questionnaire
\begin{table}
\begin{tabular}{l c c} \hline \hline  & **SLDs** & **Not SLDs** \\ \hline
**2.5 In which ways would you like the contents and information to be offered to you?** & & \\ \hline Paper guide * & 21.4\% & 25.7\% \\ Totem near the museum work * & 32.1\% & 42.9\% \\ Audio guide * & 46.4\% & 45.7\% \\ Maxi-screen near the museum work * & 39.3\% & 20.0\% \\ Personal smartphone/tablet * & 32.1\% & 45.7\% \\ Museum guide * & 0\% & 2.90\% \\ \hline
**2.9 Would you like to be involved in some activities while visiting a museum?** & & \\ No. & 32.1\% & 14.3\% \\ Yes, with an educational workshop * & 57.1\% & 57.1\% \\ Yes, by playing games * & 17.9\% & 54.3\% \\ Other * & 0\% & 5.71\% \\ \hline
**2.13 Do you believe that these new technologies (i.e., XR) can be useful within a museum?** & & \\ No & 3.57\% & 0\% \\ Yes & 75.0\% & 88.6\% \\ I do not know & 21.4\% & 11.4\% \\ \hline
**3.3 Do you think it would be interesting to interact with holographic objects/characters?** & & \\ No, I prefer a static reproduction with only language & 3.57\% & 2.86\% \\ Yes, that would be much more interesting & 96.4\% & 97.1\% \\ \hline
**3.5 How would you like to interact?** & & \\ Touch screen/keyboard/mouse & 25.0\% & 28.6\% \\ Requests made by voice & 28.6\% & 54.3\% \\ Limb movement (hand/arm/legs) & 21.4\% & 14.3\% \\ By facial expression recognition & 25.0\% & 2.86\% \\ \hline
**3.7 What kind of background would you like behind the holographic character?** & & \\ Monocolor & 0\% & 2.86\% \\ Virtual & 7.14\% & 5.71\% \\ Realistic & 32.1\% & 28.6\% \\ The same as the environment in which the museum works & 60.7\% & 62.9\% \\ \hline
**3.8 Where would you like the holographic character to be displayed?** & & \\ Personal smartphone/tablet & & \\ Big screen near the museum artwork & 17.9\% & 2.86\% \\ Totem near the museum artwork & 7.1\% & 20.0\% \\ Moving around the room without physical supports & 42.9\% & 48.6\% \\ Tablet near the museum artwork & 14.3\% & 11.4\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Questionnaire excerpt focus on technologies and tools that can be implemented within the museum, and then, opinions and preferences regarding immersive realities going on to subdivided by people with and without SLDs.
# A Survey of Photoplethysmography and Imaging Photoplethysmography Quality Assessment Methods
## 3 Introduction to Signal Quality Index for Photoplethysmographic Signals
### Definition of Quality
#### 3.1.2 Physiological Quality  
The notion of physiological quality is specific to the nature of the PPG signal. The measurement of PPG is done on living tissues. Consequently, the obtained signal is affected by physiological factors. For example, let us consider a PPG signal measured in optimal conditions with a perfect sensor and a proper processing algorithm, giving a signal whose variations are only due to blood volume changes in tissues, supposing also that we want to use this signal to measure the pulse rate. Then, the signal retrieved may still not be suitable for this application if the patient suffers from arrhythmia. Here, we want to highlight that, given some applications built upon the PPG signal (e.g., estimation of pulse rate, blood oxygenation, or pulse rate variability), the quality of the signal can be independent of metrological factors. Physiological factors can affect the PPG signal with different intensities. For example, an arteria can be more or less stiff or the respiration intensity of the patient can vary. Consequently, we also decided to represent physiological quality with a continuous scale (Figure 3). This notion of physiological quality is dependent on the application of the PPG signal and the algorithms implemented to achieve it (including the signal extraction process).  
Figure 2: Non-exhaustive example of perturbation factors influencing the metrological quality. For each perturbation, the color bar represents the metrological quality of the signal. Signals tending to the red color have low metrological quality and will have high metrological quality when tending to the green color. Depending on the intensity of the perturbation factor, it has an influence on how well the signal retrieved from the sensor reflects the variation in blood volume in tissues.
# Creation, Analysis and Evaluation of AnnoMI, a Dataset of Expert-Annotated Counselling Dialogues +
## 6 Dataset Analysis
### Utterance Embedding Distribution  
To further investigate the semantic-level differences between utterances of different types, we probe the clustering of utterance embeddings. Specifically, we obtain the utterance embeddings using a language model [35] that is lightweight and performs well on sentence embedding tasks ([[https://www.sbert.net/docs/pretrained_models.html](https://www.sbert.net/docs/pretrained_models.html)]([https://www.sbert.net/docs/pretrained_models.html](https://www.sbert.net/docs/pretrained_models.html)), accessed on 10 March 2023) as a sequence-level encoder. Through t-SNE (maximum 1000 iterations, perplexity = 30) [36]--an unsupervised, non-linear technique for visualising high-dimensional data--Figures 10 and 11 show that there is no obvious clustering of utterances of the same therapist (Main) Behaviour or client Talk Type, which is evidence that more advanced machine-learning-based methods are needed to distinguish between utterances of different types.
## 5 Results and Discussion
### Comparison with Arabic and Turkish Respondents  
To compare the results on the same basis, we conducted the same survey and performed the same analysis that we conducted for the Turkish respondents [13]. When we compared the Arabic and Turkish populations, we obtained similar results (Table 9). For Arabic respondents, one item, ANX7, was deleted from ANX, and one item, HAP7, was deleted from HAP to construct the final model. Three ANX (ANX2, ANX6, and ANX8) items, as well as one DEJ (DEJ3) item, were eliminated from the final model for the Turkish respondents, owing to low indicator loadings. Table 9 displays the \(p\)-values between the latent variables. Except for H1, the study's findings verified most of the hypotheses for both populations.
## 4 System Performance Analysis
### The Analysis of HHT Protocol  
#### 4.2.1 Packet Timeout Probability Analysis of Single Node  
Analogously, we need to derive the CDF of the packet transmission time for the HHT protocol. Combining (6) with (11) and (12), the CDF of time \(T_{k}^{(v)}\) in the HHT protocol can be rewritten as follows:  
\[F_{T_{k}^{(v)}}(t)=\Pr\Big{\{}G_{k1}^{(v)}G_{k3}\leq\Psi(t)\mathcal{K}_{k2} \Big{\}}, \tag{27}\]where \(\mathcal{H}_{l2}=\frac{d_{k}^{-2\lambda}(1-\alpha)_{k}}{\alpha_{k}\gamma_{0}\eta_{ k}\mu_{k}}\). Similarly, using (27), in combination with Lemma 1, we can easily deduce the expression of the CDF in the HHT protocol for the MRC and SC theories as follows:  
\[F_{T_{k}^{(\text{MRC})}}\left(t\right)=\frac{2}{\Gamma(M)}\bigg{(}\frac{\Psi(t) \mathcal{H}_{l2}}{\omega_{k}\Phi_{k}}\bigg{)}^{\frac{M}{2}}K_{M}\bigg{(}2\sqrt {\frac{\Psi(t)\mathcal{H}_{l2}}{\omega_{k}\Phi_{k}}}\bigg{)}, \tag{28}\]  
\[F_{T_{k}^{(\text{SC})}}(t) =2M\sum_{m=0}^{M-1}\binom{M-1}{m}(-1)^{m} \tag{29}\] \[\times\sqrt{\frac{\Psi(t)\mathcal{H}_{l2}}{(m+1)\omega_{k}\Phi_{ k}}}K_{1}\bigg{(}2\sqrt{\frac{(m+1)\Psi(t)\mathcal{H}_{k}}{\omega_{k}\Phi_{ k}}}\bigg{)}.\]  
The packet outage probability of single sensor node for the HHT protocol can be derived by combining (28) with (29) and using (15) as  
\[\mathcal{O}_{k}^{(MRC)}=1-F_{T_{k}^{(\text{MRC})}}(t_{out}), \tag{30}\]  
\[\mathcal{O}_{k}^{(SC)}=1-F_{T_{k}^{(\text{SC})}}(t_{out}). \tag{31}\]
# Kinematics and Statics of the Gough-Stewart Platform
## 3 Kinematics of a Multi-Rigid System
### Kinematics of an Open Kinematic Chain  
For an open serial kinematic chain, based on the linear combination, the angular velocity and linear velocity of the terminal joint \(J_{i}\) can be expressed as follows:  
\[\left\{\begin{array}{c}{}_{0}\mathbf{\omega}_{i}={}_{0}\mathbf{\omega}_{1}+{}_{1}\bm {\omega}_{2}+{}_{2}\mathbf{\omega}_{3}+\cdots+{}_{i-2}\mathbf{\omega}_{i-1}+{}_{i-1} \mathbf{\omega}_{i}\\ {}_{0}\mathbf{v}_{i}={}_{0}\mathbf{v}_{1}+{}_{1}\mathbf{v}_{2}+{}_{2}\mathbf{v}_{3}+\cdots+{}_ {i-2}\mathbf{v}_{i-1}+{}_{i-1}\mathbf{v}_{i}\end{array}\right. \tag{5}\]  
where \({}_{0}\mathbf{\omega}_{i}\) is the absolute angular velocity of the end joint \(J_{i}\) with respect to the absolute coordinate system, and \({}_{0}\mathbf{v}_{i}\) is the absolute linear velocity of the end joint \(J_{i}\) with respect to the absolute coordinate frame.  
With the definition of velocity screw in Equations (4) and (5), the forward kinematics of an open kinematics chain would be obtained such that  
\[{}_{0}\mathbf{\xi}_{i}=\sum_{i=1}^{n}{}_{i-1}\mathbf{\xi}_{i}=\mathbf{S}\mathbf{\omega} \tag{6}\]  
where  
\[\mathbf{S}=\begin{bmatrix}\mathbf{\xi}_{1u}&\mathbf{\xi}_{2u}&\cdots&\mathbf{\xi}_{ii} \end{bmatrix} \tag{7}\]  
which presents the unit screw matrix of the serial linkage and  
\[\mathbf{\omega}=\begin{bmatrix}{}_{0}\mathbf{\omega}_{1}&{}_{1}\mathbf{\omega}_{2}&\cdots &{}_{i-1}\mathbf{\omega}_{i}\end{bmatrix}^{T} \tag{8}\]  
with \(\mathbf{\omega}\) representing the angular velocity vector, which contains all the velocity information of all joints in the kinematic chain.  
With Equation (6), if the kinematics of the end link \(J_{i}\) is given, the inverse kinematics of the open kinematic chain could be derived through:  
\[\textbf{S}^{T}\textbf{S}\boldsymbol{\omega}=\textbf{S}^{T}_{\ 0}\textbf{ \Large$\boldsymbol{\xi}$}_{i} \tag{9}\]  
When \(\left|\textbf{S}^{T}\textbf{S}\right|=0\), the kinematic chain is a redundantly actuated mechanism, or it is in a singular configuration. Otherwise, the inverse kinematics of an open serial chain can be solved from Equation (9):  
\[\boldsymbol{\omega}=\left[\textbf{S}^{T}\textbf{S}\right]^{-1}\textbf{S}^{T}_{ \ 0}\textbf{ \Large$\boldsymbol{\xi}$}_{i} \tag{10}\]