esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis and Optimization of HRM_CS Model
### Coherence Analysis between Measurement Matrix and Sparsity Matrix  
Coherence analysis between the measurement matrix and sparsity matrix is an important metric that affects the accuracy and stability of information recovery. The formula to compute the coherence \(\mu\)[15] is given below:  
\[\textit{Coherence }\mu=\max_{i\
eq j}<H_{i},H_{j}> \tag{8}\]  
The values of \(\mu\) depend on a column in the CS matrix, where \(H_{i}=\boldsymbol{\Phi}\Psi_{i}\), \(H_{j}=\boldsymbol{\Phi}\Psi_{j}\), and \(<H_{i},H_{j}>=\Psi_{i}^{\ T}\boldsymbol{\Phi}^{T}\boldsymbol{\Phi}\Psi_{j}\). From the large number of experiments carried out, we find two methods are able to decrease \(\mu\) and increase the stability of CS recovery: (1) Adopting the Gaussian random measurement matrix, _i.e._, the RS scheme. This is because occurrence probability of 0's and 1's in a row of the Gaussian random measurement matrix is relatively fixed so that the coherence being relatively stable; (2) Increasing the number of cluster-head nodes at some extent. This is because that the measurement matrix based on the HRM is built by setting the value of the local head node to \"1\" and that of the other nodes in this cluster to \"0\". Therefore, with an increasing number of cluster-head nodes, both the number of non cluster-head nodes within each new cluster and the total number of occurrences of the value \"1\" in a row decrease. This leads to the coherence \(\mu\) decreasing.
## 4 Experimental Analysis
### Analysis of the Impact of Image and Text Information on Liability Determination Results
#### 4.6.2 Experiment 2  
Complete image information is often unavailable in real-life scenarios. To simulate this, Experiment 2 tested the model's judgment when the key frame capturing the moment of collision was removed, as shown in Figure 14, and the vehicles were obscured, as illustrated in Figure 15. The results are presented in Table 8.  
Figure 14: Schematic diagram of the missing frame.  
Figure 15: Schematic diagram of occluded vehicles.  
As shown in Table 8, missing or obscured frames can significantly impact the model's judgment, particularly in understanding the critical details of the accident. For instance, if a key frame, such as the moment of collision, is missing, the model may struggle to accurately determine the accident's cause and the specific actions of the involved parties, potentially leading to an incorrect assignment of responsibility. However, in this experiment, even with some visual information obstructed, the model was still able to correctly determine responsibility by relying on the supplementary textual information provided. While this demonstrates the model's ability to compensate for certain visual gaps, further investigation is required to evaluate the model's performance under more complex scenarios with more significant or varied obstructions.
## 4 Simulation Studies and Performance Assessment  
To verify the effectiveness of the proposed SNN in terms of fitting performance, input data enhancement, and dynamic timing regularization, as well as to validate the scheme's effect on frequency regulation, comprehensive simulation studies will be conducted below. The specifications and key parameters of the microgrid utilized here are presented in Table 2. The performance of the aforementioned methods will be demonstrated and compared sequentially. The studies construct a microgrid for testing three DGs using the system structure shown in Figure 1. The power of common load on the common AC bus changes dynamically with time; these variations follow those shown in Figure 2.  
Figure 6: Overall control diagram.
## 5 Construction of a Simulation Environment and Evaluation Conditions
### Simulation Execution Environment Model and Simulation Conditions  
The simulation execution environment was modeled on an actual area around Shinjuku Station (\(1.8\times 2.2\) km\({}^{2}\)) in Tokyo. The map of the area was imported into _Scenargie_. The time simulated was one hour. It was assumed that victims who can walk go to the shelter on their own. Therefore, the simulation focused on those victims who did not walk to the shelter (because they walked to parks that were not designated as shelters, were confined in buildings, or were injured, _etc._). The number of victim terminals was 1000. The number of rescuers was assumed to be 300 to 350. This number was determined from the density of the members of the Self Defense Forces [2] who were actually dispatched to Miyagi Prefecture at the time of the Great East Japan Earthquake. Since it is likely that rescuers operate in a team, we assumed that 10 members made up a team and a carrier terminal was allocated to each team. Thus, we placed 30 carrier terminals. The number of shelters was 15. This number was determined from the number of actual places that can be used as shelters. Carriers start at a shelter, and walk to another shelter looking for victims. The moving speed of carriers was determined assuming that they may, from time to time, stop awhile for rescue operations. The storage capacity of a carrier terminal was 10 MB. The size of a safety confirmation message sent by a victim terminal was assumed to be 100 Bytes. The storage capacity of an information carrier terminal is much smaller than the storage capacity of an actual mobile terminal. This small capacity was selected because we took the simulation execution environment into consideration. It is not meant to restrict the propose protocol. The size of a safety confirmation message was selected assuming that it was a simple text message. In selecting these values, we intended to minimize the power needed for exchange of messages because, for a victim, the remaining battery power of his/her terminal is precious. These simulation conditions are shown in Table 3. The simulation execution environment is shown in Figure 8. The initial locations of terminals other than shelter terminals were random.
###### Abstract  
The objective of this study was to analyze the perception of visual verticality (VV) in subjects with Fibromyalgiaa Syndrome (FMS) and to correlate this with the symptoms of the disease and balance capacity. A cross-sectional study including 54 patients (51 female) was conducted. The evaluation of visual verticality was carried out with a virtual reality device by calculating the Mean Absolute Error (MAE) of degrees deviation in two tests: the Subjective Visual Vertical (SVV) test for the contribution of the vestibular system to the perception of verticality and the Rod and Frame test (RFT) for the contribution of the visual system. In total, 16 subjects (29.6%) presented good VV perception, 6 subjects (11.1%) presented an exclusive alteration of the SVV test, 19 subjects (35.2%) presented an exclusive alteration of the RFT and 13 subjects (24.1%) showed alteration in the two tests. The MAE in the SVV test showed medium correlations with several variables such as the Fibromyalgiaa Impact Questionnaire (FIQ) (Rho = 0.399, \(p\) = 0.003), the Pain Catastrophizing Scale (PCS) (Rho = 0.417, \(p\) = 0.002), the Dizziness Handicap Inventory (DHI) (Rho = 0.376, \(p\) = 0.005), and the Activities-Specific Balance Confidence Scale (ABC-16) (Rho = \(-\)0.367, \(p\) = 0.006). The MAE in the RFT showed medium correlations with the Instability Support Reduced (Rho = 0.327, \(p\) = 0.016) and Instability Gait Eyes Open (Rho = 0.312, \(p\) = 0.022) subscales of the JAEN (Joined Assessment of Equilibrium and Neuro-motor) Scale. Conclusions: Around 70% of the subjects with FMS showed some alteration in the perception of VV; 60% of these patients presented visual system dependence. The SVV test correlates with the impact and health status of FMS, and the RFT correlates with the alteration in the dynamic balance.  
Keywords:fibromyalgiaa; virtual reality; postural balance; sensation +
Footnote †: journal: Applied
# Design of a Baseband Signal for the 406 MHz Satellite Emergency Radio Transmitter Based on STM32
## 5 Conclusions  
This paper designed a method of generating the baseband signal of the COSPAS-SARSAR transmitter based on the STM32 microcontroller. The coding process of the baseband signal includes: firstly, calculating the first error correcting coding BCH (127, 106) and the second error correcting coding BCH (63, 51) by 64-bit integer data; secondly, generating the baseband signals according to GB 14391-2021 coding format; and comparing the required time for calculation of BCH check bits, respectively, based on 64-bit integer data and the string-comparison operation. The experimental results show that the BCH check bit calculation method based on the 64-bit integer data can improve the rate of the BCH check bit calculation. At present, this method has been applied to emergency position-indicating radio beacon (EPIRB) and personal locator beacon (PLB), which can run stably.  
Conceptualization, methodology and software, M.L., X.H. and J.Z.; writing-original draft preparation, M.L.; writing--review and editing, G.N.; validation, X.H. All authors have read and agreed to the published version of the manuscript.  
This study was funded by a project from the Major State Basic Research Development Programme of China (grant number:2018 YFE0206500).  
The study did not report any data.  
The authors declare no conflict of interest.
## 1 Introduction
For instance, changes in temperature and precipitation can affect the abundance and distribution of mammalian herbivores that produce dung, potentially altering the availability and quality of dungresources for the beetles. Disruptions in these intricate ecological interactions can have cascading effects on ecosystem processes, such as nutrient cycling and plant dynamics [13]. Geographical information systems (GISs) are one of the many cutting-edge scientific methods that researchers employ to assess the effects of global warming on a beetle species across its range [14]. By connecting climate change to bug dispersal, GISs offer useful insights. One such method is species distribution modeling (SDM), which forecasts the potential distribution of a species over a geographic area using environmental variables and species occurrence data [15]. Researchers can better understand how changes in temperature, precipitation, and other climatic conditions may affect insect populations and their distribution patterns by investigating the impacts of climate change on insects through SDM [16]. Scientists can determine which insect species are most vulnerable to climate change and pinpoint areas where their habitats may be in danger by combining temperature data with records of insect occurrence [15]. SDM can also be used to locate prospective refugia, or locations that may continue to be suitable for insect species in the face of a changing environment. To minimize the detrimental effects of climate change on insect biodiversity, it is essential to prioritize conservation efforts and establish effective conservation methods [17]. Therefore, the goal of this study is to evaluate the appropriateness of _Phyllogmathus excavatus_'s existing habitat across the Mediterranean region and to identify any potential effects of climate change on its spread. This study seeks to offer important insights into the vulnerability of this beetle species and contribute to the development of well-informed conservation plans by the analysis of climate data, occurrence records, and using GIS techniques. For the Mediterranean region's ecosystems to continue functioning properly and to preserve insect biodiversity, it is crucial to understand the current and projected distribution patterns of _Phyllogmathus excavatus_.
# A Hybrid Linear Quadratic Regulator Controller for Unmanned Free-Swimming Submersible
### Contributions  
The contributions of this work are given as follows:  
* We have proposed a novel and robust design of a hybrid controller, termed as HLQR, for the UFSS system. It is achieved by using two LQR controllers to efficiently tackle the hydrodynamic disturbances (see Section 5);
* The proposed HLQR controller is integrated in the UFSS system to analyze the response in terms of settling time, rise time, overshoot, and steady-state error;
* The robustness of the proposed HLQR controller is evaluated in the presence of noisy sensor data and a disturbed environment;
* The performance comparison of the proposed controller is provided with PID and lead-compensator controllers (shown in Section 6).  
The proposed controller is the integration of two LQR controllers which results in shrewd outcomes to hydrodynamic disturbances. It provides sharp rise time and settles the disturbances efficiently and quickly. Furthermore, a PID and lead-compensator are integrated to compare their response for the selection of the best controller. The robustness of the aforementioned controllers is evaluated using a specified transient response in the presence of dynamic disturbances.  
The remainder of this paper is organized as follows: Sections 2 and 3 provide the preliminaries and mathematical background of UFSS. The stability criterion to design UFSS controller is described in Section 4. Similarly, Section 5 describes the proposed HLQR controller design. Implementation results are given in Section 6. Finally, Section 7 concludes the paper.
## 4 Scenarios
### Key Performance Indicators  
In order to quantify the performance of SCHC over IP or non-IP data transport, with or without security, we use the following key performance indicators (KPIs):  
* The packet latency, i.e., the duration between the moment a message is sent by the device and the moment an acknowledgment (of the same size) is received;
* The handshake latency, i.e., the time taken for the DTLS handshake to be completed;
* The total energy consumption for transmitting a packet and receiving an acknowledgment;
* The total energy consumption for performing the DTLS handshake.  
Packet loss was not considered since we did not experience much of it (repetitions at the physical layer and the HARQ mechanism enable messages to be received correctly), except in radio condition 4. In this case, a specific explanation is given along with the test results.  
Figure 5: Variants of the application scenario.  
Figure 6: How packets are compressed using SCHC in the different variants of the application scenario.
## 1 Introduction  
Sound waves emitted from a source within a room undergo intricate interactions with the surrounding environment, influenced by factors such as the room's geometry, surface materials, and furnishings. These elements collectively determine the acoustic response of the room and contribute to the auditory experience. Considering the room as a linear time-invariant system, the sound transformations between a source and a receiver are quantitatively encapsulated as a room impulse response (RIR), uniquely describing the room's acoustic fingerprint [1].  
The RIRs can facilitate a comprehensive understanding of the room acoustics, which is pivotal in the design of performance venues [2, 3], correction of acoustic anomalies [4], and selection of acoustic treatments [5]. It is also integral in the development of speech processing algorithms [6], the design of immersive audio in extended reality (XR) environments [7], and various soundfield analysis and synthesis methods. The spatial variations captured by RIRs across the room enable accurate listener translations, providing an enriched immersive experience. Therefore, the availability of diverse and authentic RIRs can greatly benefit the research and development of numerous audio applications.  
RIRs can be obtained through two primary methods: simulation-based generation using wave-based and ray-based methods [8], or real-world measurements. While simulated RIRs are quicker to generate, they lack the authenticity of real acoustic environments due to challenges in modeling complex scattering effects and material compositions [9, 10]. Hence,algorithms validated using simulated data may malfunction when applied to real conditions. Even though resource-intensive, measured RIRs provide a realistic representation of real-world scenarios and preserve important perceptual features. Typically, a singular microphone or an array of microphones is employed to measure RIRs at spatially distributed receiver positions in a given room. Recently, higher-order ambisonic microphone arrays have been widely used to acquire directional characteristics of the acoustic field [11; 12; 13].  
Several measured RIR datasets have been collected in the past, and they are framed to meet the demands of certain applications, like acoustic analysis, room geometry estimation, speech enhancement, automatic speech recognition, and VR environment design. These datasets differ in key attributes, like the type, size, and configurations of the room measured, the number and density of source and receiver locations, and the type and configuration of loudspeakers and microphones. Some of the publicly available datasets [12; 13; 14; 15; 16; 17; 18; 19; 20] are compared in Table 1. The OpenAIR database [11] contains impulse response data from more than 50 environments, mostly collected in the Ambisonic B-format.
###### Abstract  
The aim of this study was to measure the bone mineral density of specific regions of maxilla, mandible, and first cervical verteba using the Hounsfield unit and trabecular microstructure pattern analysis and to compare the two methods. In this study, cone-beam computed tomography (CBCT) images were obtained from 58 patients. Trabecular thickness, trabecular number, trabecular separation, and bone volume fraction were measured in 484 regions for trabecular microstructure parameters and Hounsfield unit was measured for the grayscale value. There was no difference in bone mineral density between the right and left side in every site and between males and females. Trabecular thickness and trabecular number were high in the order of anterior base of the maxilla, mandibular body, first cervical verteba, and mandibular condyle. Bone volume fraction and Hounsfield unit were high in the order of anterior base of the maxilla, mandibular body, and first cervical verteba (\(p<0.05\)). Trabecular thickness, trabecular number, and bone volume fraction was positively correlated to the Hounsfield unit, and trabecular separation was negatively correlated to the Hounsfield unit (\(p<0.005\)). This study suggests that it is possible to compare the bone mineral density of trabecular bone in various sites using the Hounsfield unit and trabecular microstructure pattern analysis.  
Keywords:bone mineral density; trabecular microstructure; Hounsfield unit; cone-beam computed tomography +
Footnote †: journal:  
et al. reported that the micro structural evaluation of trabecular bone using CBCT correlated with that of micro-CT [5].  
A representative case of measuring trabecular bone density is for the diagnosis of osteoporosis, which measures the density of the lumbar spine or femur [7]. [PERSON] et al. reported that the trabecular bone density measurement using the mandible or cervical vertebra in dental CT showed a high correlation with the conventional trabecular bone density measurement through a systemic review [8]. The analysis of trabecular bone density using CBCT will be a useful reference for the diagnosis and treatment of various diseases.  
In this study, the anterior base of the maxilla, mandibular body, mandibular condyle, and the first cervical vertebra were selected to measure the trabecular bone density. The aim of this study was to evaluate the bone mineral density measurement methods in various regions of the CBCT image using the Hounsfield unit and trabecular microstructure parameters in patients undergoing an orthodontic treatment, and to compare and find out the correlation between the two methods.
# Dynamic Characteristic Master Curve and Parameters of Different Asphalt Mixtures
## 2 Acquisition of Dynamic Principal Curve  
The asphalt mixture was tested by an AMPT performance tester, and the modulus and phase angle at 20, 30, 40, and 50 \({}^{\circ}\)C under nine frequency conditions in the range of 0.1 to 25 Hz were obtained, and the modulus and phase angle at different temperatures were transformed into master curves at the same reference temperature by using the principle of time-temperature equivalence. Based on the existing research, the Sigmoid model was used to fit the dynamic modulus master curve, and the improved Gauss model was used to fit the phase angle master curve [9; 19].  
(1) Dynamic modulus master curve  
The Sigmoid model of the modulus master curve is shown in Equation (1).  
\[lg(E^{*})=E_{0}+\frac{\alpha}{1+e^{\beta+\gamma(lg\omega_{r})}} \tag{1}\]  
Among them, E* is the dynamic modulus, \(\omega_{r}\) is the load frequency at the reference temperature, E\({}_{0}\) represents the minimum value of dynamic modulus, E\({}_{0}+\alpha\) represents the maximum value of dynamic modulus, and \(\beta\) and \(\gamma\) are the shape parameters of the model curve.  
(2) Phase angle master curve  
The phase angle master curve was fitted according to the improved Gauss model with the same displacement factor as the modulus principal curve. The Gauss model is shown in Equation (2).  
\[\delta=\delta_{0}+Ae^{\frac{(lg\omega_{r}-\omega_{\rm c})^{2}}{2\omega^{2}}} \tag{2}\]  
In the formula, \(\delta\) is the phase angle, \(\omega_{r}\) is the frequency at the reference temperature, \(\omega_{\rm c}\) is the frequency corresponding to the peak of the phase angle, and \(\delta_{0}\), A is the eigenvalues of the master curves.  
Figure 1 shows the master curve of the AC-20 type mixture. Among them, the modulus master curve in Figure 1A shows a smooth S-shaped curve, which reflects the mechanical properties of the full frequency range. The asphalt mixture has the characteristics of high frequency and high elasticity, and the dynamic modulus increases and tends to have a stable value at high frequency; under the condition of low frequency, the dynamic modulus decreases and tends to a minimum.  
Figure 1B is the phase angle master curve. It can be seen that parameter \(\delta_{0}\) represents the initial phase angle, parameter A represents the variation amplitude of the phase angle, parameter \(\omega\) represents the full width at half maxima (FWHM) of the phase angle curve, and \(\omega_{c}\) represents the position of the phase peak. According to the theory of polymer physics, the FWHM parameter of the phase angle master curve covers more of the viscoelastic state of the material, the left range tends to the rubber state, and the right range tends to the glass state [10,20,21]. In this paper, the division between the amplitude of phase angle A and FWHM (A/\(\omega\)) is used to represent the significant degree of viscoelasticity of the material; the higher the A/\(\omega\) value, the greater the sensitivity of the material to frequency, and vice versa.
# A New Algorithm Model Based on Extended Kalman Filter for Predicting Inter-Well Connectivity
## 2 Construction of the SV-DC Model
### Traditional Capacitance Model
The time-lag coefficient \(\tau_{ij}\) is a dimensionless time constant representing the transfer time between wells. The TC model shows that the cumulative production of a producer is determined by the combined effect of its initial cumulative production and the historical injection activity.