esa-sceva/satcom-chunk-collection huggingface dataset:
# Theoretical Study of SOF\({}_{2}\) Adsorption on Pd/Pt-Ni(111) Bimetallic Surfaces
## 3 Results and Discussion
### Adsorption of SOF\({}_{2}\) on Pd-Ni(111) and Ni-Pd-Ni(111) Surfaces
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Surface** & **Structure** & **\(E_{\text{ads}}\) (eV)** & **\(Q_{\text{T}}\) (e)** & **Distance (Å)** & **Comparison** \\ \hline Ni(111) & 3 thf & \(-\)1.550 & \(-\)0.182 & 1.820 & [PERSON] et al. [21] \\ \hline Pd-Ni(111) & M1 & \(-\)1.964 & 0.068 & 2.183 & \\  & M2 & \(-\)1.880 & 0.079 & 2.200 & This Work \\ \hline Ni-Pd-Ni(111) & M3 & \(-\)0.413 & \(-\)0.016 & 3.793 & \\  & M4 & \(-\)0.372 & \(-\)0.009 & 3.555 & \\ \hline \end{tabular}
\end{table} 
Table 1: The adsorption parameters of SOF\({}_{2}\) adsorbed by Ni(111), Pd-Ni(111), and Ni-Pd-Ni(111) surfaces. Figure 4 shows the electron density difference of SOF\({}_{2}\) adsorption on Pd-Ni(111) and Ni-Pd-Ni(111) surfaces. Since the electron distribution of M4 is similar to M3, M3 was selected for comparison with M1 and M2. The red region represents an increase of the electron density, while the blue region represents a decrease of the electron density. For the M1 structure in Figure 4a, it is shown that electrons transfer from the bonding Pd atom to O atom and F atom. The density of electrons between the S atom and bonding Pd atom indicates the formation of chemical bonds. As shown in Figure 4b, the electron density near the O atom and S atom increased, while the Pd atoms had varying degrees of charge transfer. In Figure 4c, a small amount  
Figure 4: Electron density difference of SOF\({}_{2}\) adsorption on the (**a**) M1:Pd-Ni(111), (**b**) M2:Pd-Ni(111), and (**c**) M3:Ni-Pd-Ni(111) surfaces. Figure 3: (**a,c**) Total density of states (TDOS), (**b,d**) partial density of states (PDOS) for the structure of M1 and M3. of electrons transferred from the Pd atoms to the O atom and F atom, indicating a weak chemical interaction between them. According to the results from the analysis of adsorption energy, DOS, and electron density difference, it is concluded that the Pd-Ni(111) surface shows a stronger ability of adsorbing the SOF\({}_{2}\) molecule than the Ni-Pd-Ni(111) surface.
# QoS-Guaranteed Radio Resource Management in LTE-A Co-Channel Networks with Dual Connectivity
## 2 System Model
### Optimal Resource Allocation
\begin{table}
\begin{tabular}{c c c c} \hline
**CQI Index** & **Modulation** & **Code Rate \(\times\) 1024** & **Efficiency** \\ \hline
5 & QPSK & 449 & 0.8770 \\
6 & QPSK & 602 & 1.1758 \\
7 & 16 QAM & 378 & 1.4766 \\
8 & 16 QAM & 490 & 1.9141 \\
9 & 16 QAM & 616 & 2.4063 \\
10 & 64 QAM & 466 & 2.7305 \\
11 & 64 QAM & 567 & 3.3223 \\
12 & 64 QAM & 666 & 3.9023 \\
13 & 64 QAM & 772 & 4.5234 \\
14 & 64 QAM & 873 & 5.1152 \\
15 & 64 QAM & 948 As aforementioned, we will propose a max-min RB allocation method which will be described in detail in the next section. In the following, we performed experiments to compare the performance of three RB allocation methods, namely, the max method, the random method, and the max-min method. We compared three performance metrics: The similarity between the optimal solution (of the 0-1 integer programming) and that of these methods, the difference of objective function (1) and (2) of the optimal solution, and that of these methods. The similarity was defined as the pair-wise comparison of each variable of the optimal solution, and that of the three methods. For example, if the system had 50 RBs, and allocation of 40 RBs were the same between two methods, we would define the similarity as 80%. For the objective function, we compared the degradation of the objective function of one method as compared to the optimal solution. For example, 10% means the objective function obtained by one approximate method only achieves 90% of that of the optimal solution. The system parameters of the experiments are shown in Table 2, in which the system has seven Macro BSs, each Macro BS contains three sectors, and each sector deploys five user equipments. We simulate 500 TTIs, and for each TTI, the optimal solution as well as the solutions of the three methods were calculated for each sector (i.e., 21 sectors). Table 3 shows the experimental results. As can be observed, random method did not perform well, neither yielded good similarity to the optimal solution nor achieved good objective value. The max method yielded the closest solution to the optimal solution. On the other hand, the max-min method also yielded a very competitive solution to the max method, in particular, both methods yielded very high objective value with less than 1% degradation. However, the max-min method had much less computation complexity as compared to the other methods which need to solve 0-1 integer linear programming or linear programming problem. In summary, the max-min method is a good candidate mechanism for RB allocation.
## 7 Conclusions  
In this work, we present a DMPF scheduler that uses multi-path TCP (MPTCP) to transmit different Scalable Video Coding (SVC) layers, over Moving Picture Experts Group (MPEG) Dynamic Adaptive Streaming over HTTP (DASH) standard in software defined network (SDN). The DMPF scheduler has advanced forwarding and processing modes. The processing modes are categorized into _allLayer_ and _layerWise_. The forwarding mode consists of _singlePath_ or _multiPath_.  
We compare the combination of different DMPF scheduler processing and forwarding modes of the DMPF scheduler and dive deep into identifying which mode combination yields the acceptance of the maximum number of client streaming requests and identify the trade-offs associated with the combination. We find that _allLayers-multiPath_ mode results in accepting the maximum number of SVC layers after _allLayers-singlePath_ mode. However, both of these modes do not accommodate the maximum number of clients. Therefore, both modes focus more on providing the maximum number of enhancement layers to each client request. Therefore, the quality of experience of the client is improved. Moreover, _layerWise-multiPath_ and _layerWise-singlePath_ modes accept the maximum number of client requests as they do not reject base layers. However, they reject enhancement layers therefore providing each client with a basic representation of the video. We see that _layerWise_ processing mode is slower and more time consuming as compared to _allLayer_ processing mode. Moreover, we also conclude that it is wise to use eighty percent of the capacity of the paths connected to the DASH server to accept client requests. The remaining twenty percent of the capacity can be used for network diagnostics, forwarding and switching and so forth.  
Conceptualization, A.G. and S.L.; methodology, A.G. and S.L.; software, A.G.; formal analysis, A.G. and S.L.; investigation, A.G. and S.L.; resources, S.L.; data curation, A.G.; writing-original draft preparation, A.G.; writing-review and editing, A.G. and S.L.; visualization, A.G.; supervision, S.L.; project administration, S.L.; funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript. This research was supported by Global Scholarship Program for Foreign Graduate Students at Kookmin University in Korea and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1 FIA1061136). The authors declare no conflict of interest.  
Figure 12: Number of paths found to accept requests.
## 2 Mathematical and Physical Formulation
### Cascaded Lattice Boltzmann Method (CLBM)  
* The choice of the model The Cascaded Lattice Boltzmann Method (CLBM) was chosen for this project because it is very good at accurately describing complicated heat flow and transport processes, especially when there is a mix of convection and conduction. Compared to more common methods like finite volume or finite element approaches, CLBM offers better numerical stability, less vulnerability to non-physical oscillations, and an easier way to deal with complex boundary conditions. These features make CLBM perfect for modeling turbulent and transitional flows, like those found in medium- and large-scale heat sinks. Furthermore, CLBM can easily simulate problems on high scales because it is naturally scalable. It does this by using parallel computing to handle the higher computational needs. This advantage makes it an ideal choice for studying the thermal management challenges posed by heat sinks operating under high heat flux conditions.  
The D2Q9 lattice model discretizes the dynamic (fluid flow) field, while the D2Q5 lattice model discretizes the thermal field. The D2Q9 model is flexible enough to accurately show the speed distribution and multicellular flow structures that are common in these types of convection. The D2Q5 model is also the best for thermal transport, providing computational economy without sacrificing the precision required for heat transfer computations. This dual-lattice method is a good choice for this study because it makes sure that both the hydrodynamic and thermal fields are resolved correctly and quickly.
* Problem Description and Governing Parameters In this study, the selected ranges of Rayleigh number (\(5\times 10^{7}<Ra<5\times 10^{8}\)) and Reynolds numbers (\(10^{3}<Re<3\times 10^{3}\)) were chosen to reflect thermal and flow conditions typically encountered in practical applications such as data centers and high-power electronic systems. The Rayleigh numbers correspond to realistic temperature differences (around 20 \({}^{\circ}\)C to 50 \({}^{\circ}\)C) across air-filled enclosures of decimeter-scale dimensions, which are commonly found in heat-generating equipment.  
The Reynolds numbers, on the other hand, represent airflow velocities in the range of approximately 0.5 to 2.5 m/s, consistent with forced convection produced by fans or ducted ventilation systems in such environments. These parameter ranges were selected to ensure that the simulated configurations are representative of real-world mixed convection scenarios and can help identify key behaviors relevant to the design of efficient thermal management systems.
# Effect of Fiber Wave Structure in Printed Circuit Boards on Signal Transmission Characteristics
## 4 Conclusions  
The dielectric constant fluctuation of different types of fiber weaves were inconsistent: 1080, 3313, and 2116 are much larger than 1035 and 1078 (1080 is 0.44 and 1078 is 0.18). This fluctuation characteristic fed back to the effect on impedance and signal propagation delay. Here, 1035 and 1078 had relatively lower impedance fluctuations, which were below 1.0 \(\Omega\) for 50 \(\Omega\) designed traces (1080, 3313, and 2116 could reach 2.0-2.5 \(\Omega\)), and lower differential skews with various differential transmission lines (1078 was 2 ps/in. and 1080 could reach 4.0 ps/in.).  
For methods to improve the fiber weave effect, we advise high-speed digital designers to use flattened fiber weaves (such as 1078 and 1035) and NE-glass fiber weaves (such as 2116 NE). We also suggest designing long signal lines parallel to the weft direction or rotating the image with a proper angle (if the fiber weave pitch is not known, 5 degree is recommended).  
[PERSON] makes substantial contributions to conception and design, acquisition of data, analysis and interpretation of data; [PERSON] gives final approval of the version to be submitted and any revised version; [PERSON] participates in drafting the article or revising it critically for important intellectual content; [PERSON] participates in drafting the article or revising it critically for important intellectual content; [PERSON] submit this article. This work was supported by the Science and Technology Project of Guangdong (2014B090901017) and the Science and Technology Project of Guangzhou (201604010086).  
The authors declare no conflicts of interest.  
Figure 16: Calculation of the rotation angle.  
Figure 15: \(\Delta\)Phase before and after rotating.
# High-Performance Garbage Collection Scheme with Low Data Transfer Overhead for NoC-Based SSDC
## 3 Proposed Garbage Collection Scheme
### Efficient Data Handling Through Task Queue Architecture  
The proposed GC scheme intelligently governs the flow of data to be copied back, requiring a precise hardware mechanism for its implementation. A defining characteristic  
Figure 4: Copy-back data path selection by the proposed GC scheme.  
of multi-channel SSDs is their capacity to perform multiple tasks simultaneously--such as processing host-oriented read and write requests while executing GC tasks--thereby maximizing overall SSD throughput. In prior work, we introduced an efficient method for managing multiple tasks in bus-based SSD controllers using a task queue [10].  
To effectively support parallelism in NoC-based SSD controllers, each flash memory channel is paired with a dedicated task queue that organizes all requests for that channel, as illustrated in Figure 5. Each channel is associated with four distinct task queues: read requests from the host (R\({}_{\text{host}}\)), read requests for GC (R\({}_{\text{gc}}\)), write requests from the host (W\({}_{\text{host}}\)), and write requests for GC (W\({}_{\text{gc}}\)). Tasks in these queues are processed sequentially by dedicated hardware that operates independently for each channel.  
The criteria for enqueueing tasks in the W\({}_{\text{gc}}\) (write requests for GC) queue are determined by the analysis results from the ECC unit. If the ECC unit detects errors in the page data, the corrected data will be stored in an empty page of flash memory, and the corresponding request will be added to the W\({}_{\text{gc}}\) queue. Conversely, if the ECC unit confirms that the page data are error-free, the data temporarily held in the FMC buffer will be written back to an available page in the flash memory, and no new task will be enqueued in the W\({}_{\text{gc}}\) queue.  
Key innovations include the following:  
1. Efficient Task Queue Integration: The approach integrates with task queue architectures in NoC-based SSD controllers, enabling smooth implementation alongside host read and write operations.
2. Integration with ECC Analysis: The task queue enqueues GC write requests (W\({}_{\text{gc}}\)) only if errors are detected and corrected. Otherwise, error-free data from the FMC buffer are directly written back without generating additional W\({}_{\text{gc}}\) tasks.
## 4 Encryption Process
### Ciphertext Splitting
#### 4.3.2 Take Out the Sharing Code  
Calculate the mid-length of the ciphertext FinalSTR.  
Figure 3: Sharing code insertion process.  
Figure 2: Combination of MD5 values.  
Calculate \(\frac{(midLength-2-K)}{2}\) and round down to nums, extract the sharing code and the length of the sharing code from the ciphertext FinalSTR so that only the final scrambled encrypted data string and the combination of two MD5s are left in FinalSTR.  
If \(nums>K\), all sharing codes can be inserted at intervals of two bits, and the sharing codes are extracted from the third bit of the data transmission string FinalSTR at intervals of two bits to restore the original sharing code FinalKey, as shown in Figure 4.  
If \(nums\leq K\), we cannot insert all the sharing codes in two intervals, and some of the sharing codes are placed at the end of the FinalSTR. Firstly, the sharing code is extracted from the 3 rd bit of the FinalSTR, and then the sharing code is combined into a left party with an interval of 2 bits. The number of extraction is \(K-\frac{(midLength-2-K)}{2}\), and then the value of \(K-nums\) is calculated as the right party. Finally, the original sharing code is the sequential combination of the left party and the right party. The operation flow is shown in Figure 5.
# Can Livestock Farming Benefit from Industry 4.0 Technology? Evidence from Recent Study
## 4 Results
### Poultry  
The German egg production of approx. 14.3 million eggs p.a. (2020) covers only 72% of the national consumption. About 10 million eggs p.a. must be imported; about 75% of the imported eggs originate from the Netherlands [36]. There are about 47,100 registered egg producing farms, but 84% of these producers have less than 100 laying hens. Only about 2000 farms have more than 3000 laying hens with a total of 43 million hens in 2020. Farms with 10,000 to 30,000 hens are the most common size; about 30 farms have more than 200,000 laying hens.  
The German sector of broiler fattening counts only 3828 farms (2020). In total, 99% of the broilers are produced in 1378 farms with more than 10,000 broilers per farm, and the production is strongly concentrated, with more than half of the broilers being produced in Lower Saxony [37].
## 2 Penetration Experiments  
### UHPC Targets  
In the present tests, two cuboid UHPC targets are cast for the projectile impact under different striking velocities, as shown in Figure 1. The plain sizes of the two targets are both 2.0 m \(\times\) 2.0 m, while the thicknesses are 0.9 m and 1.5 m, respectively. Each target is wrapped by 1 cm thick steel plates except for the front and back to weaken the lateral boundary effects. Straight copper-coated steel fibers with 0.2 mm diameter and 13 mm long, as shown in Figure 2, are incorporated into the matrix at a volume content (\(V\)) of 2%. The yield strength of the steel fiber is 2100 MPa, and the density is 7830 kg/m\({}^{3}\).  
Quasi-static uniaxial compression tests are carried out on prismatic specimens with dimensions of 100 mm \(\times\) 100 mm \(\times\) 300 mm using an electro-hydraulic servo testing  
Figure 1: Cuboid UHPC target.  
Figure 2: Straight copper-coated steel fibers.  
machine with a capacity of 300 tons to determine the uniaxial compressive strength of UHPC used for targets and corresponding matrixes without steel fibers, as shown in Figure 3. A total of six specimens are tested, three of which are made of UHPC with steel fibers, and the other three are made of UHPC without steel fibers (which can be named as matrix), complying with the test procedure in Chinese Standard GB/T 50081-2019 [19]. Before the compression tests, all prismatic specimens are steam cured using an automatic control system [20]. The experimental uniaxial compressive strengths of UHPC specimens with steel fibers are 144.1 MPa, 152.3 MPa, and 148.6 MPa, respectively, and the results of matrix specimens are 139.8 MPa, 134.5 MPa, and 145.3 MPa, respectively. In the subsequent discussion, the uniaxial compressive strength of UHPC and matrix are taken as the average values of the corresponding three specimens, i.e., 148.3 MPa and 139.9 MPa, respectively. At the same time, the density of UHPC specimens with steel fibers and matrix specimens is also measured, and the average values are 2430 kg/m\({}^{3}\) and 2237 kg/m\({}^{3}\), respectively.
# A Survey on Intrusion Detection Systems for Fog and Cloud Computing
## 4 Intrusion Detection and Prevention Systems
### Host-Based vs. Network-Based Intrusion Detection and Prevention Systems  
There are two main types of intrusion detection and prevention systems (IDPS): host-based (HIDS) and network-based (NIDS). It is also possible to build hybrid solutions combining the strengths of both technologies to create a more efficient and effective solution.  
The HIDS system operates by using functions to protect an endpoint. The technology can monitor the network traffic that moves towards the inside and sends off the device, progressions in succession on the system, and adjustments to files.  
The NIDS technology operates by monitoring the traffic on the network. It consists of a packet sniffer to collate the packets from the network or sniff wireless traffic. This traffic is then assessed for any sign of malicious activity, which can signify the common types of attacks (namely, scanning and DDoS attacks).
# A Survey on the Application of WirelessHART for Industrial Process Monitoring and Control
## 2 Background of Process Automation
### Process Control Automation
#### 2.1.3 Monitoring and Control  
In this classification of control systems, latency is not considered an essential factor in taking control actions and there is a maximum allowed latency of 1000 ms. Here, field device data are commonly utilized to perform maintenance operations for calibration and repair. However, in some cases, data transfer consistency is needed to continue the process operations.
# Infrared and Visible Image Fusion: Methods, Datasets, Applications, and Prospects
## 2 Infrared and Visible Image Fusion Methods
### Methods Based on Multi-Scale Transformation
#### 2.1.3 Non-subsampled Contourlet Transform  
The wavelet transform has been widely applied in various signal processing domains as a quick and efficient way to encode one-dimensional piecewise smooth signals. To separate the discontinuity of edge points, the one-dimensional signal wavelet transform is extended to the two-dimensional image wavelet transform. However, the two-dimensional wavelet transform is unable to capture the rich directional information of the image. [PERSON] et al.'s [34] efficient contour transform approach for multi-directional, multi-resolution image representation was offered as a solution to this issue. This model can accurately represent the geometry of picture edges since it is based on the Laplacian pyramid and directional filter banks. However, there are shift variance issues brought on by up- and down-sampling, as well as redundancy issues brought on by the pyramid filter bank topology.  
The non-subsampled contourlet transform (NSCT) is a model that has been presented to address the drawbacks of the contour transform [35]. It is quick, flexible, and translation-invariant. The non-subsampling pyramid and non-subsampling direction filter banks are the foundation of the NSCT model. To achieve multi-resolution decomposition, the non-subsampled pyramid filter banks divide each source picture into a collection of high- and low-frequency sub-images. To achieve multi-direction decomposition, the non-subsampled direction filter banks divide these high-frequency sub-images. By doing away with the down-sampling and up-sampling steps of contour transformations, NSCT achieves strong frequency selectivity and regularity and is shift-invariant.