esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Antenna Designing and Operation Mechanism
### Design of Band Notch Elements
#### 2.2.1 WiMax Band Notch Element Design  
The notch for the WiMax is introduced in the UWB characteristic by etching the patch with an inverted L-shape element. The notching formula determines the length of the \(L_{u}\)-shaped slit:  
\[f_{WiMax}=\frac{c}{4L_{u}\sqrt{\epsilon_{ref}}} \tag{1}\]  
\[L_{u}=L_{2}+W_{2} \tag{2}\]  
where \(L_{u}\) is the total length inverted L-shaped slit on the radiating patch, \(f_{WiMax}\) is the center of notching frequency at the WiMax band, \(\epsilon_{ref}\) is the dielectric constant of the FR-4 substrate, and \(c\) is the speed of light. The length is calculated from the formula, which gives \(L_{u}=11\) mm for the resonance center frequency of 3.2 GHz. However, the width of the \(L_{u}\) slit = 0.2 mm. The analysis shows that the resonance frequency for the notch will be 3.06 GHz a decrease of 4.3% whilst the length increase by 15% (i.e., \(L_{u}\) increases from 11 mm to 13 mm). Figure 3 shows that placing an inverted L-shaped slit on the patch introduces a WiMax notch band characteristic.  
Figure 3: (a) Geometry of \(L_{u}\) shaped slit at the radiating patch; (b) \(S_{11}\) parameter for different lengths of an inverted L-shaped slit (i.e., \(L_{u}\) = 11 mm, 13 mm) for WiMax band rejection.  
Figure 2: \(S_{11}\) parameter with and without the loading of semi-circles to show the impedance matching improvement for semi-circle loading. The inclusion of a smooth curve or level shape technique is used to improve impedance matching.
## 6 Evaluation  
The testbed and workload specifications are described in this section. We also present the results of our experiments and discuss their implications. We evaluate the impact of CRBF- based integrity verification system on overall performance of data transfer. We then assess the effectiveness of the CRBF-based data integrity verification system by analyzing factors such as memory overhead, recovery overhead, and false positive error probability. All experiments employed a large, fixed dynamic random-access memory (DRAM) as random-access memory (RMA) buffers at both the source and sink ends, with a maximum utilization of 256 MB at each end. The results were obtained through multiple iterations and presented as average bar graphs. Additionally, 99% confidence intervals are displayed in the error bar wherever needed.
Specifically, only a single pass of the surface loads, isotropic hardening, thermal stresses and possibly temperature-dependent constitutive parameters are usually considered as opposed to the focus on multiple loading cycles, kinematic hardening, and isothermal problems prevalent in rolling contact research. However, systematic and thorough analysis of the adequacy of the mentioned approximate algorithms on more theoretical grounds seems to be mostly limited to these latter circumstances of rolling contact; see e.g., the works of [PERSON] et al. [18; 19] and [PERSON] and [PERSON] [20] as well as [7; 8]. The present paper aims to close this knowledge gap by analyzing the applicability of the approximate algorithms [6; 7; 8] under conditions more relevant to manufacturing applications. Specifically, we consider single-pass thermomechanical surface loads and isotropic hardening (according to a Johnson-Cook-type yield stress model)--while investigating the quality of the predicted residual stresses using reference solutions from appropriate FE models. This enables an in-depth discussion of the approximate algorithms' accuracy in conjunction with their underlying additional simplifications regarding certain transient stress and strain components. Furthermore, we generalize and reformulate the algorithms to account for thermal softening in a consistent way, which is necessary in case of temperature-dependent yield strength but has not been done previously. In doing so, we cast the algorithms' treatment of elastoplastic increments into a proper predictor-corrector form and provide detailed implementation-ready numerical schemes for both explicit and implicit solutions of the corrector step. The implicit scheme is deemed particularly useful when the evaluation of the elastic input solution on very fine grids comes at a computational cost that is non-negligible to the application, e.g., when real-time predictions are needed [4]. In such cases, larger step sizes might be preferable over the additional effort introduced by an implicit integration method. The structure of the paper is as follows: In Section 2, the thermomechanical half-space problem under consideration is stated, the residual stress approximation algorithms [6; 7; 8] are reformulated, and their numerical solution is detailed. Next, we describe the FE models, which we later on use to validate and benchmark our implementations of said algorithms, in Section 4, where we also discuss their properties and assumptions in the context of our numerical studies. A boarder discussion follows in Section 5, where we shift the focus toward applications and the corresponding literature. Finally, conclusions on the applicability of the considered approximate methods are drawn in Section 6.
## 3 Materials and Methods
### Experiment Setup  
The path selection process and the MOCell algorithm implementation were developed in the MATLAB programming language. We used the OpenDayLight (ODL) controller with the RESTCONF module. The distributed data topology was designed using the Mininet simulator [20]. Mininet is one of the most used platforms in the literature for SDN emulation due to its compatibility and flexibility with other applications and controllers. For the simulation environment, we configured a virtual machine with a Linux Debian 9 operating system with 12 CPUs, 16 RAM, and 100 GB of disk space (NLSAS disks). Below is a list of the software specifications and tools used:  
* Linux Debian 9;
* Mininet 2.3;
* OpenDayLight (ODL) SDN Controller;
* MATLAB 2021 for MOCell-based code;
* Python 3 for REST API communication scripts;
* Iperf for data stream transfers performance.  
The ODL controllers for Domains A, B, and C were configured according to the simulated network topology (Figure 6) and the link parameters (bandwidth, packet loss, and delay) corresponding to the values in Appendix A. We simulated each domain along with its SDN controller, and they were configured to connect with the Mininet simulator.  
The network topology was divided into three domains. Controllers A, B, and C managed the domains, respectively. Since the domains were separate, each controller had its own domain status and network information. Therefore, it was necessary to implement an application that coordinates the controllers to establish the routing process that allows communication among them.  
Figure 6: Experimental topology.
## 3 Experimental Verification  
### Data Acquisition and Preprocessing  
#### 3.1.1 Data Acquisition  
To validate the feasibility of the proposed climbing formwork state monitoring method, Building 3 of Phase B, China Overseas City Plaza, Tianjin (2024) was selected as the monitoring object. The main office tower is designed to reach a height of approximately 339.9 m and is located in the city center, where the construction environment is highly complex. During construction, an attached climbing scaffolding system is utilized for enclosure and safety. The monitoring items are shown in Figure 3.  
There are a total of four monitoring stations, each installed at one of the four corners of the climbing scaffold, with two reference monitoring stations set up on the building's exterior. The monitoring instruments are mounted on pre-welded brackets, positioned approximately half a meter away from the building's exterior surface. The distribution of monitoring stations is illustrated in Figure 4.
## 3 Solution to the Problem of Comparing OFN/vOFNs
### Summary  
This study introduces a novel approach to the problem of comparing fuzzy numbers. As discussed earlier, many existing methods either directly or indirectly lead to comparisons in the domain of real numbers, moving beyond the boundaries of fuzzy numbers. In contrast, the objective of this research was to devise a comparison operator that stays entirely within the fuzzy number domain.  
The proposed operator functions intuitively on fuzzy numbers, similar to how relational operators operate in other number systems. To validate the JC metric, the authors employed examples previously used by other researchers to verify their comparison operators. The experimental section involved calculations on positively ordered numbers expressed in vOFN notation. The properties of vOFNs show that they behave identically to traditional (crisp) numbers.  
The results of the fuzzy number comparisons confirm the effectiveness of the proposed operator. No anomalies were observed, and the relationships between numbers determined by the JC metric were consistent with those identified by other researchers. Therefore, it can be concluded that the JC comparison operator provides a robust and consistent method for comparing fuzzy numbers within the fuzzy number framework.  
Moreover, the computational demands of the operator are modest, making it suitable for repeated application. Preliminary experiments further suggest that the proposed approach performs well across various fuzzy number notations, although the comprehensive confirmation of this observation is left for future research. Future work should involve testing the JC metric across the full spectrum of OFNs. However, based on the examples presented and the preliminary findings, no significant challenges are anticipated.  
Additionally, based on the extended comparison framework and the incorporation of benchmark examples, we observed that the JC metric not only preserves the structure and semantics of ordered fuzzy numbers but also provides results that align closely with or improve upon existing methods. In contrast to traditional OFN-based operators, the JC metric demonstrates better handling of symmetry, reversed order, and division-by-zero sensitivity. Therefore, the findings support the conclusion that vectorial OFNs (vOFNs) in combination with the JC metric offer a more flexible and robust approach to fuzzy number comparison.
## 4 Experimental Results and Analysis
### Mechanism of Water Drive Oil and Gas  
(1)Replenishing formation energy  
In depletion and water injection development, the injected water can occupy the volume of the crude oil that is produced, and replenish the formation energy consumed by  
Figure 30: Remaining oil types in pore model and fracture pore model. (**a**) Pore type model remaining oil type; (**b**) Residual oil type of fracture pore model.  
Figure 29: Segmentation of threshold value of remaining oil in water injection after exhaustion in fracture pore model.  
depletion development and raise the formation pressure to maintenance level, as shown in Figure 31.  
It can be seen from Figure 31 that water injection development after depletion development can improve the formation pressure maintenance level, and the formation pressure level gradually rises from below the saturation pressure to above the saturation pressure.  
(2) Protection of reservoir and fluid properties  
The water injection development after depletion development can improve the formation pressure level, and the weak volatile oil reservoir especially showed the mechanism of protecting the reservoir and fluid properties. Water injection can make the dissolved gas dissolve again and protect the fluid properties, as shown in Figure 32. The process of redistribution can be seen in Figure 32, which is the inverse process of nucleation, enlargement and coalescence. In addition, water injection can alleviate reservoir damage caused by the Jamin effect and expand the effective mobilization range, as shown in Figure 33.  
Figure 31: Water injection to replenish formation energy. (**a**) The pressure drops below saturation at the end of depletion development; (**b**) Rising above saturation pressure at the end of waterflood development.  
Figure 32: Injected water protects fluid properties. 1 Before replenishing formation energy; 3 Early stage of water injection; 3 Meddle stage of water injection; 4 Late stage of water injection.  
3. Improve the degree of crude oil recovery Similar to the oil-displacement mechanism of higher-than-saturation pressure, after the depletion development, the injection water can provide the oil-displacement power to drive the crude oil in the large pore throat forward. In hydrophilic-weak hydrophilic reservoirs, the oil is removed from the rock surface along the rock particle surface (pore throat wall), and the oil is transported forward in the form of a continuous water film to drive the oil and improve the degree of crude oil recovery. Figures 34 and 35 show the change of the oil displacement efficiency of the porous and fractured porous carbonate reservoirs, respectively. After waterflooding, the displacement efficiency of the porous and fractured porous carbonate reservoirs increases by 51.02% and 27.61%, respectively.
## 5 Results
### Configuration II SVM Classifiers Performance  
The results of concatenating each DL feature set with the combined handcrafted features are shown in Table 2. The results in Table 2 indicate that merging the DL features of each CNN with the combined handcrafted features enhanced the diagnostic performance. This is clear as the accuracies attained after integrating both feature types were 99.1%, 99.2%, 99.2%, and 98.8% for linear, quadratic, cubic, and gaussian SVMs, respectively, (trained with the DL features of MobileNet and the combined handcrafted features) which are better than those attained before fusion. Similarly, when fusing the DL features of DarkNet-19 and the combined handcrafted features, the accuracies reached 99.2%, 99.6%, 99.6%, and 97.9 % for the same classifiers. Additionally, when incorporating the DL features of ResNet-18 and the combined handcrafted features, both the quadric and cubic SVMs have higher accuracies than that obtained by using either group of features. Note these accuracies are attained with 85 features. As indicated in studies [65,66,67], fusing DL features of an individual CNN  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Features** & **Linear** & **Quadratic** & **Cubic** & **Gaussian** \\ \hline Statistical & 85.7 & 92.8 & 93.3 & 90.2 \\ \hline GLCM & 73.7 & 85.0 & 87.7 & 72.6 \\ \hline GW & 63.6 & 62.2 & 57.1 & 63.6 \\ \hline DWT \(-\) GLCM & 69.8 & 74.8 & 76.6 & 70.8 \\ \hline GLCM + Statistical + GW + & 87.8 & 94.2 & 95.1 & 91.3 \\ DWT \(-\) GLCM & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: The diagnostic accuracy (%) of the SVM classifiers trained with individuals and combined handcrafted features set from multiple domains.  
with multiple handcrafted features improved classification accuracy. For this reason, the results in Table 2 confirm this statement of combining deep features obtained from one CNN with ensemble handcrafted features boosts classification performance.
### Types of Antenna Systems Used in Underground Mining
#### 1.2.3 Millimeter-Wave Antennas  
Millimeter-wave antennas are specialized antennas that work at frequencies ranging from 30 GHz to 300 GHz. These frequencies are substantially higher than those utilized in standard wireless communication systems, which operate at frequencies below 6 GHz [34]. The usage of millimeter-wave frequencies provides various advantages, including greater data speeds, less interference, and reduced antenna diameters [35]. [PERSON] et al. [36] proposed a compact, high-gain, and wideband CP antenna using millimeter (mm) waves for underground communication. A multilayer pyramidal dielectric resonator antenna was responsible for the CP mechanism. The impedance bandwidth of the antenna covers the Industrial, Scientific, and Medical (ISM) band from 58 GHz to 68 GHz with a gain of 11.2 dBi and an axial ratio bandwidth of 37% in the operating band. Using substrate-integrated waveguide technology, the horn antenna was optimized for a satellite broadcast signal in the tunnel at 27 GHz [37]. The beam width was reduced by 32 degrees, and the antenna's gain was increased by 8.78 dBi [38]. [PERSON] et al. [39] designed a coplanar waveguide-fed staked dielectric resonator antenna (DRA) for millimeter waves at 62.16 GHz for underground ISM communications. The major limitation of the proposed antenna was the degradation in radiation patterns at higher frequencies. Similarly, [PERSON] et al. [40] presented a broadband and high-gain DRA at 59.55 GHz for underground communication systems. The proposed antenna structure comprises a microstrip feed, a cylindrical resonator, and multiple metallic strips on a superstrate. The simulated results provided a gain of 15.40 dBi over the bandwidths from 57 GHz to 59.55 GHz and a maximum gain of 16.71 dBi at 58 GHz. In another study, [PERSON] et al. [41] designed a cylindrical DRA two-element array at 60 GHz mounted on a conformal ground plane substrate for millimeter-wave underground communications [42].
# Damage Imaging in Lamb Wave-Based Inspection of Adhesive Joints
## Materials and Methods
### Weighted Root Mean Square Damage Imaging  
The guided wave field that was acquired with the use of SLDV can be further processed to more accurately identify the position and shape of defects. This processing technique depends on the  
Figure 4: Experimental setup: (**a**) instrumentation for generation and acquisition of Lamb waves; and, (**b**) detail showing the piezo actuator attached to the specimen.  
Figure 5: Investigated specimen with indicated scanning points.  
calculation of the weighted root mean square for each registered time signal and the creation of a damage map. The WRMS for a time signal \(s(t)\) can be defined as follows [25; 26; 30; 33; 36]  
\[WRMS=\sqrt{\frac{1}{t_{2}-t_{1}}\int_{t_{1}}^{t_{2}}\left(w(t)s(t)^{2}\right)dt} \tag{1}\]  
where \(w(t)\) denotes a weighting factor and \((t_{2}-t_{1})\) is length of the time window with \(t_{1}\) denoting the beginning of the time window and \(t_{2}\) denoting the end of the time window. For a discrete signal \(s_{r}=s(t_{r})\) sampled with \(\Delta t\) interval and calculated from the interval \(T=(N-1)\Delta t=t_{2}-t_{1}\), the WRMS can be approximated by  
\[WRMS=\sqrt{\frac{1}{N}\sum_{r=1}^{N}(w_{r}s_{r}^{2})} \tag{2}\]  
where \(N\) is the number of samples in the signal used for RMS calculation and \(w_{r}\) is the weighting factor defined based on the number of consecutive sample \(r\)  
\[w_{r}=r^{m},\ m\geq 0,\ r=1,2,\ldots,N \tag{3}\]  
where \(m\) is a power of the weighting factor. The weighting factor with parameter \(m>0\) enables the decrease of importance of the samples at the moment of excitation. The interpretation of WRMS maps allows for the determination of the shape and location of the existing defects. In general, the areas with higher WRMS values can indicate the possible locations of damage that are related to the reduction of material stiffness and may be in the form of cracks, corrosion, or delamination [26].
###### Abstract
A literature review showed that most of the previous studies on the capture and purification of cooking fume mainly focused on certain parts of the kitchen fume exhaust system. For example, studies on the capture of cooking fumes mainly considered the kitchen and hood part and investigated the kitchen indoor air environment or the capture efficiency of the hood, while studies on the purification of cooking fume considered the purifier module and explored the factors affecting purification efficiency. This kind of research was helpful in optimizing the design parameters of local structures. However, in practical application, the Chinese commercial kitchen fume exhaust (CCKEF) system encompasses the kitchen, exhaust hood, air duct and purifier. Compared with simplified local kitchen exhaust hood or purifier modules, the airflow characteristics in a complete CCKEF system are more complicated, which may result in capture and purification performance that is inconsistent with the design requirements of each module. Therefore, the operation performance of the CCKEF system should be examined. However, there have been few related studies. A previous survey study conducted by [PERSON] et al. [22] showed that the proportions of wall-mounted canopy hood, rectangular air duct and terminal electrostatic purifier used to capture, transport and purify the cooking fume in Chinese commercial kitchens were 94.12%, 100% and 98.04%, respectively. That is to say, most of the CCKEF systems were composed of wall-mounted canopy hoods, rectangular air ducts and terminal electrostatic purifiers. In order to study the actual operating performance of such systems, this study developed a simulation method. First, a geometric model of a representative CCKEF system, including kitchen stoves, personnel, exhaust hood, air duct, terminal electrostatic purifier and make-up air, was established and discretized with an unstructured grid using CFD software. The types of boundary conditions were determined based on the literature and actual measurement. The MHD potential model with generalized convection diffusion equation was coupled with the RNG k-\(\epsilon\) turbulence model and species transport model to calculate the steady-state continuous-phase flow, temperature, pollutants and electric fields. After calculation convergence, the DPM model in the Lagrange frame was introduced to track the particles entrained in the gas phase and calculate the purification efficiency of the purifier. In order to verify the accuracy of the model, the temperature, air velocity and purification efficiency of the CCKEF system were measured at several measurement points. The validated model was used to predict the indoor air environment and purification efficiency of the CCKEF system under different working conditions (simultaneous coefficient of stove, surface temperature of stoves, replacement air parameters and exhaust air volume) to understand the actual operation of the case system and offer suggestions for improvement.