esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Discussion
This makes the process more scalable and reusable compared to traditional ontology development methodologies that focus on narrower domains. The focus on mapping real-world data during the early stages ensures that the ontology is scalable and can accommodate large datasets from different sources. This is particularly important for domains like asset concealment, where the volume and variety of data are significant. Traditional methodologies provide more generalized steps for ontology development but often lack the detailed focus on domain-specific data integration that the proposed process emphasizes. This makes the proposed process more practical for large-scale, data-intensive applications. Another key innovation in this process is the reference ontology alignment technique. This step is designed to integrate and harmonize existing upper-level and domain-specific ontologies. Many traditional methodologies overlook this alignment or treat it as a superficial task. In contrast, this process offers a structured way of aligning multiple ontologies, which ensures consistency and interoperability across different systems. This technique allows the ontology to reuse existing ontologies meaningfully, thus improving its scope and reducing redundancy. It ensures that any overlaps or inconsistencies between existing concepts are resolved through structured alignment, making the ontology more robust. Lastly, it is important to highlight that the construction of the ontology itself does not solve the data integration problem regarding asset concealment. Developing processes to populate the ontology with information from different data sources is necessary. Although this activity is beyond the scope of this work, due to the large volume and variety of data typically involved, it is recommended to build automated data import routines and to use appropriate ETL (Extract, Transform, and Load) tools.
## 5 Simulation Results and Analysis
### Velocity Field  
Figure 12 shows the distribution of velocity vector diagrams at different rotational angles after the working fluid in the working chamber stabilizes. It can be observed that in the various working chambers of the vortex compressor, the flow of the working fluid is smooth, with a flow rate slightly higher than that in the back pressure chamber. During operation, vortex compressors experience pressure differences, and the speed of the gas brought by tangential leakage flow might exceed the surrounding gas speed, leading to an uneven distribution in the velocity vector field. Tangential leakage occurs at the radial gap between the dynamic and static vortex teeth, where the velocity reaches its peak. The maximum velocity in the combined profile vortex compressor is 570 m/s, while in the uniform wall thickness vortex compressor, it is 492 m/s. The higher maximum leakage velocity in the combined profile is due to the larger pressure difference between adjacent compression chambers in this design. Vortices appear near the back pressure chamber in the intake area and at the radial gaps between adjacent compression chambers, caused by abrupt changes in the velocity and direction of the working fluid. The areas where vortices occur also exhibit localized high temperatures, making vortices one of the causes of uneven temperature distribution in the compression chamber.  
Figure 12: Distribution of velocity vector diagram at different corner positions. (**a**) Velocity vector diagram of combined profile; (**b**) velocity vector diagram of uniform wall thickness.
# Tensile Properties and Tensile Failure Criteria of Layered Rocks
## 3 Numerical Study of Layered Rocks
### Discussion  
#### 3.4.1 Failure Modes of Layered Rock Specimens under Direct Tension Test  
The main failure modes of layered rocks under the direct tension test are analyzed in Section 3.2; however, the failure modes of layered rocks highly depends on the anisotropic coefficient (\(\text{k }=\frac{\text{T}_{\text{qq}}}{\text{T}_{\text{q}}}\)). If the anisotropic coefficient is less than 1 (\(\text{k }<1\)), that is to say, the tensile strength of the bedding plane is stronger than the tensile strength of the rock material, it can be hypothesized that the bedding plane is the strong binding material, therefore, as the layered rock specimen is subjected to the uniaxial tensile load, the rock material will be fractured first, whatever the layer orientation is. If the anisotropic coefficient is equal to 1 (\(\text{k }=1\)), which means the tensile strength of the bedding plane is the same as the tensile strength of the rock material, the tensile strength of the layered rocks may present isotropic characteristics. However, layered rocks may not only fracture along the bedding plane or the rock material due to the different elastic parameters between the bedding plane and the rock material. If the anisotropic coefficient is greater than 1 (\(\text{k }>1\)), the failure modes may present as the three main patterns. In conclusion, the failure modes of layered rock specimens subjected to a direct tensile load may be greatly influenced by the anisotropic coefficient.
# A Review of Progress and Hydrodynamic Design of Integrated Motor Pump-Jet Propulsion
## 5 Discussion
### Hydrodynamic Performance of IMP Thrusters  
When predicting the propulsion performance of an IMP thruster, the CFD method considering the viscous effect can accurately simulate the complex flow of the IMP thruster's wakefield and the slight vortex structure of the blade. At the same time, it can accurately simulate the flow near the wall through the boundary layer grid, and the effect of turbulent flow is fully considered on the propulsion performance of IMP thrusters. With the development of high-performance computers, the viscous-flow CFD method strongly supports the prediction of the hydrodynamic performance of IMP thrusters. At present, it seems to be the most mainstream method for the numerical simulation of IMP thrusters' flow fields.  
In terms of CFD preprocessing for IMP thrusters, the CFD grid discrete method is relatively mature. The main research work is focused on comparing different grid types and corresponding grid layout methods to automatically generate grids for specific calculation conditions and to investigate the combined use of different grid discretization methods.  
In terms of the IMP thruster CFD calculation method, the aim is to evaluate the applicability of different turbulence models in the calculation of an IMP thruster's hydrodynamic performance. At present, it seems that different turbulence models have certain differences when measuring the hydrodynamic performance of IMP thrusters. These works also provide a reliable reference for the reasonable selection of turbulence models that are suitable for specific research topics. For the flow field of rotating machinery such as IMP thrusters, numerical methods such as multireference system models, sliding grids, overlapping grids, moving grids, and periodic boundaries also have corresponding suitable application scenarios.  
In terms of CFD calculations for IMP thrusters, the current research work is mainly focused on the open-water performance of IMP thrusters, the numerical prediction of unsteady forces, the fluid-structure interaction, the performance in a nonuniform flow field, and the cavitation of IMP thrusters. Regarding the open-water performance, the research content includes the impact analysis of IMP thruster parameters, such as side slope and pitch, and the geometric parameters of duct IMP thrusters, such as blade tip clearance. For the application of different turbulence models in the calculation of the unsteady force of IMP thrusters, more extensive research has been carried out at home and abroad, mainly comparing the calculation accuracy of different turbulence models. According to the research results, the DES method and the LES method deal with nonstationary forces and are most widely used for steady problems. There are also related studies on the influence of calculation settings on unsteady calculations and the calculation of the unsteady performance of new types of thrusters.
## 1 Introduction
### Existing Polynomial Multiplier Architectures and Their Limitations
A bit-parallel systolic multiplication design is described in [23] over \(GF(2^{m})\). The performance results are given for FPGA and ASIC platforms. An efficient and high-speed overlap-free Karatsuba polynomial multiplier is described in [24] over \(GF(2^{m})\) on an Artix-7 FQPA. **Digit-serial multiplier designs. ** A digit-based serial-in and serial-out semisystolic multiplication architecture is presented in [25] over \(GF(2^{m})\). Their architecture can execute both polynomial multiplication and square operations together with the shared hardware resources. It results in a decrease in execution time. Additionally, due to shared hardware resources, their semisystolic architecture reduces the hardware area and as well the power/energy consumption. An efficient implementation of a full-word Montgomery multiplication is presented in [26]. This incorporates the Karatsuba multiplication algorithm to reduce the computational complexity. The Karatsuba algorithm allows one to split the input operands into smaller segments. Two approaches of operand splitting were used: (i) four-part splitting and (ii) deep four-part (DFP) splitting. The implementation results are reported for Virtex-5, Virtex-6 and Virtex-7 FPGA devices over 192 to 521 prime fields. For various \(GF(2^{m})\) fields, an optimized m-term polynomial multiplier similar to the Karatsuba multiplication method is proposed in [27]. The implementation results are reported for a Spartan-7 device. **Digit-parallel multiplier architectures. ** To accelerate the point multiplication operation of ECC, digitparallel multipliers with digit sizes of 32 and 41 bits are utilized in [28; 29], respectively. To perform digit multiplications, a simple least-significant approach is used. Their multiplication designs are more suitable for the applications that demand a reasonable throughput with minimum hardware area, where throughput is the ratio of one over computation time. Although there are different polynomial multiplication architectures in the literature [14; 15; 16; 17; 25; 28; 29], these designs are specific to cryptographic applications having specific operand lengths. Concerning [13], scalability/flexibility is one of the critical requirements for 5G architecture development to incorporate enhanced mobile broadband, machine type communication (MTC) and ultra-reliable MTC. Rather than this, various high-speed cryptographic applications (e.g., internet servers), implementing cryptographic algorithms for different security levels, require scalable polynomial multiplication architectures. Therefore, there is a real demand for scalable multiplication designs.
## 2 Background and Related Work
### Anchoring Systems  
Methods of anchoring vessels have existed for thousands of years [1]. Typically, anchors either dig into the seabed (such as hook anchors, bruce anchors, etc.), have sufficient mass to stay in one place on the seabed (such as those used with moorings for larger vessels and anchors for very small vessels), or screw into or are otherwise affixed to the seabed [8]. In most cases, rode made of chain, rope, cable, or a combination of materials attaches the anchor to the vessel [9]. In many cases, the anchor uses a length of rode at least the length of the vessel, made of chain that lays on the ocean floor to increase the anchor's ability to hold fast [10]. All of the above techniques can be used by AUVs, but the implementation depends upon a variety of factors, such as the carrying capacity of the AUV.  
Recent concepts and implementations of anchoring systems for underwater vehicles include the use of a bottom crawler, which is carried on the bottom of an AUV and delivered to the seabed by the AUV [11]. Once on the seabed, the AUV detaches from the bottom crawler but remains connected by a cable. Upon completion of the mission, the AUV is winched back to the crawler, re-attaches itself, and proceeds to a new location. Another recent prototype, described as a self-mooring AUV, uses compressed gas to jettison an anchor, in the form of a nosecone, attached to a torpedo-shaped AUV by a vacuum seal [12]. The weight of the anchor drags the AUV down vertically by a mooring line until the anchor rests on the seabed. The AUV later detaches from the mooring line via galvanic release and continues its mission. Other recent works [13; 14; 15; 16] have described potential uses, such as harvesting the energy of currents using an organic kite-based generator, for AUVs that can anchor temporarily to the seabed. Another design describes a vehicle that uses jet pumps to cause an AUV to penetrate the seabed for seismic sensing [17].
## 1 Introduction  
The Digital Twin (DT) represents a concept that emerges from Product Lifecycle Management and has a primary role in the development of current trends related to customer requirements, design constraints, complexity, data security, and integrity. The basic idea of this technology is to examine the use of the digital replica of a physical object. A Digital Twin has been defined as a digitization platform with a role in improving, processing, and managing information at the level of physical and virtual companies. Initially, DTs were capable of monitoring and could be improved in terms of control, optimization, and autonomy capability [1]. They also enable the integration and sharing of acquired data throughout the lifecycle, resulting from a continuous learning process, and include various aspects of digital representation. By combining the notions of artificial intelligence, data analysis, the Internet of Things (IoT), virtual reality, and the foundations of modern engineering are laid, characterized by innovation and performance.  
The field of application of DTs is vast; thus, DT applications are being developed for smart cities, construction, medical systems, manufacturing, agriculture, and the automotive industry. Based on the specialized literature consulted, the advantages identified following the use of DT applications are the urban planning of cities, services, increased reliability, reduced operational costs, improved performance, optimization of implemented strategies, reduction of discrepancies between projected and realized requirements, and increasing efficiency and quality control [1].  
In Section 2, a literature review methology is realized, serving as a foundation for understanding the context and research directions. Section 3 explores the evolution of the Digital Twin concept, providing a detailed analysis of its transition into a functional architectural model. In Section 4, the applicability and impact of Digital Twin models in various domains are examined, highlighting both the advantages and challenges associated with their use. Section 5 presents the results obtained in the study, providing a clear perspective on its contribution. In Section 6, discussions focus on the interpretation and detailed analysis of the results, addressing relevant aspects and their implications. Finally, Section 7 gathers the key conclusions of the work.
# Study on Thermal Radiation Characteristics and the Multi-Point Source Model of Hydrogen Jet Fire
## 4 Results and Discussion
### Numerical Simulation
#### 4.4.2 Effect of Leakage Diameter  
Jet fires were simulated at the leakage pressure of 4 MPa and leakage diameters of 10 mm, 20 mm, and 40 mm. The thermal radiation data along the flame axis in the \(y\)-direction and \(x\)-direction (\(y\) = 2 m plane) were extracted and plotted as shown in Figure 11. The temperature distribution along the flame axis in the \(y\)-direction is depicted in Figure 12. Figure 11a shows that as the leakage diameter increases, the thermal radiation intensity in the \(x\)-direction also significantly increases. However, at the position far from the flame axis, the thermal radiation release is decreased. Similar behavior is observed under the conditions of the three leakage diameters. Hydrogen jet fire with a large leakage diameter significantly expands the impact range of thermal radiation. Figure 11b shows that as the leakage diameter increases, the thermal radiation intensity in the \(y\)-direction significantly increases, and the flame height at which the maximum thermal radiation occurs also increases. Additionally, comparing the thermal radiation data under different leakage diameters, it is found that the thermal radiation intensity increases more rapidly  
Figure 10: Flame temperature variations in \(y\)-direction under various leakage pressures.  
Figure 9: Thermal radiation distributions in \(x\)- and \(y\)-directions for various leakage pressures.  
with the increasing leakage diameter, which is consistent with the experimental findings discussed earlier.  
Figure 12 shows the temperature distribution along the flame axis in the \(y\)-direction. The maximum temperature of the hydrogen jet flame does not significantly change with the increase in the leakage diameter, while its corresponding height obviously moves upward. Comparing the results of the thermal radiation and temperature distributions, it is found that regions with high temperatures have higher thermal radiation intensities. The above analysis indicates that temperature is a critical factor affecting thermal radiation release.
# UAV Formation Shape Control via Decentralized Markov Decision Processes
## 2 Problem Formulation
Let \(d^{i}\) be the destination location UAV \(i\) must reach, and \(d_{\text{coll,thresh}}\) is the distance between the UAVs below which the UAVs are considered to be at the risk of collision. We now define the local cost function for UAV \(i\), as follows:  
\[ \begin{split} c(b_{k}^{i},a_{k}^{i},a_{k}^{nn})&=w_ {1}\Big{[}\text{dist}(\dot{s}_{k}^{i,\text{pos}},d^{i})+\text{dist}(\dot{s}_{k }^{\text{nn,pos}},d^{\text{nn}})\Big{]}\\ &+w_{2}\Big{[}\text{dist}(\dot{s}_{k}^{i},s_{k}^{nn})^{-1}\mathbb{ I}\Big{(}\text{dist}(\dot{s}_{k}^{i},s_{k}^{nn})<d_{\text{coll,thresh}} \Big{)}\Big{]}\end{split}  \tag{1}\]  
where \(\dot{s}_{k}^{i,\text{pos}}\) represents the location of the \(i\)th UAV, \(w_{1}\) and \(w_{2}\) are weighting parameters, \(\text{dist}(a,b)\) represents the distance between locations \(a\) and \(b\), and \(\mathbb{I}(a)\) is the indicator function, i.e., \(\mathbb{I}(a)=1\) if the argument \(a\) is true and \(0\) otherwise. By minimizing the above cost function, each UAV optimizes its own control commands and that of its neighbor, but only implement its own local control commands and discards the commands optimized for its neighbor. The first part of the cost function lets the UAV reach its destination, while the second part minimizes the risk of collisions between UAVs. The Dec-MDP starts at an initial random state \(s_{0}\) and the state of the system evolves according to the state-transition law and the control commands applied at each UAV. The overall objective is to optimize the control commands at each UAV \(i\) such that the expected cumulative local cost over a horizon \(H\) (shown below) is minimized. where \(b_{0}^{i}\) is the initial local state at UAV \(i\), and the expectation \(E[\cdot]\) is over the stochastic evolution of the local state over time (due to the random variables present in the UAV dynamic equations). \[\min_{\{a_{k}^{i},a_{k}^{m}\},k=0,\ldots,H-1}\mathrm{E}\left[\sum_{k=0}^{H-1}c( b_{k}^{i},a_{k}^{i},a_{k}^{m})\middle|b_{0}^{i}\right] \tag{2}\]
# MLRNet: A Meta-Loss Reweighting Network for Biased Data on Text Classification
## 2 Related Work
### Corrupted Labels  
To tackle label noise, refs. [5; 8; 24] assume the underlying causes of label noise and employ label correction processes to transform corrupted labels into cleaner ones. These methods require estimating a label corruption matrix, which is independent of the model training process. However, such estimations do not consider data-related noise, which is common in real-world label noise scenarios [25]. Ref. [26] expanded label correction by incorporating an additional meta-update process during normal training. They used a small amount of unbiased data to introduce meta-labels representing the reliability of each label. Through a meta-learning network, they dynamically adjusted the weights of each meta-label, enabling adaptive label noise correction during the training process.  
Figure 1: The variation in average training loss for biased samples in the AG News. In the figure, it is evident that different types of biased samples exhibit distinct trends in their loss value variations (with an imbalance factor of 20 and noise label level of 0.4). Firstly, concerning the class imbalance issue, head class samples consistently display lower loss values compared to tail class samples. Secondly, for samples with noisy labels, their loss values are higher than those with undistorted labels. For head class samples, the loss values for clean label samples steadily decrease, while the loss values for samples with noisy labels initially decrease and then sharply increase before slowly decreasing again. Conversely, for tail class samples, the loss values for clean label samples initially experience an increase, which is followed by a significant decrease. In contrast, the loss values for samples with noisy labels first increase and then decrease.  
Another approach is reweighting the loss values of each sample, where samples with higher loss values are considered more likely to be noisy, and the model tends to focus on those high-confidence samples with clean labels. This is often achieved through methods like the SPL series [10].
## 3 Results  
In this section, we will conduct research and analysis on the relationship between the radiation characteristics of nonlinear Thomson scattering resulting from the cross-impact of a linearly polarized Gaussian laser pulse and an electron in a tightly focused state and the laser amplitude. The linearly polarized laser pulse with varying laser amplitudes will exert distinct effects on the electrons in the cross-collision, and the resulting radiation characteristics will each have their unique characteristics. Consequently, to investigate the influence of the parameter of laser amplitude, it is necessary to effectively and reasonably set the other parameters of the linearly polarized laser and the high-energy electron. We can set the parameters of the laser pulse as follows: the normalized beam waist radius \(b0=6\ \mu m\), the pulse width \(L=3\lambda\), the wavelength \(\lambda=1\ \mu m\) and the initial phase \(\varphi_{0}=0\). The normalized initial energy of the electron is \(\gamma=10\). The numerical simulation approach adopted in this paper is applicable within the realm of classical electrodynamics, and the parameter settings comply with its requirements [22,23]. When the intensity of the laser amplitude reaches a certain threshold (where the laser amplitude \(a_{0}\) is 20 or even higher), the transition from Thomson scattering to Compton scattering requires the consideration of the recoil correction in quantum mechanics. Nevertheless, the range of the laser amplitude \(a_{0}\) investigated in this paper is from 1 to 9, and therefore, the recoil correction need not be taken into account. In the Cartesian coordinate system, the interaction point of the laser and the electron in the cross-collision is set at the origin of the coordinate system, which renders the description more explicit. The delay time of laser emission determines the part of the laser where the electron collides, which will have a certain influence on various characteristics. Therefore, in this paper, the position where the electron collides with the laser is set at the center of the linearly polarized laser pulse, namely the position where the maximum radiation power is generated. After testing, the delay time of laser emission at this point is \(5 fs\).