esa-sceva/satcom-chunk-collection huggingface dataset:
# MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion
## 3 Methodology
### PVWF Module
The 16-dimensional pointwise image features are derived from the 2048-dimensional features extracted from the C5 layer of the IR module, which are first reduced to 128 dimensions through two fully connected layers with batch normalization (BN) and ReLU, and subsequently down to 16 dimensions. The point features are then concatenated with the reduced pointwise image features, resulting in 128-dimensional pointwise fusion features after processing through the Stacked VFE module. The advantage of the PWF module lies in its early combination of image and point features, allowing the network to learn and aggregate local feature information from multiple modalities through the VFE layers. Therefore, PWF primarily serves to extract multi-modal local features, enhancing the perception ability of local scenes. For the VWF module, the configuration of Stacked VFE is \(VFE_{1}\)(\(7,32\)) and \(VFE_{2}\)(\(32,64\)). The input image features for the PVWF module originate from the feature map output by the C5 layer of the IR module. Initially, 2048-dimensional image features at the voxelwise projection positions are obtained through RoI align operations and subsequently reduced to 256 dimensions and then to 64 dimensions through 2 fully connected layers. These 64-dimensional voxelwise image features are then concatenated with the output of \(VFE_{2}\), yielding 128-dimensional voxelwise fusion features. By retaining more spatial information through RoI align operations when extracting voxel-wise input image features, the alignment and fusion of point cloud features and image features are facilitated. The advantage of the VWF module lies in its ability to supplement missing information from distant or sparse LiDAR point clouds using image features, thereby reducing reliance on high-resolution LiDAR data. The VWF module employs an intermediate fusion strategy at the voxelwise level to incorporate features from RGB images, extracting multi-modal global features. In our MPVF architecture, the PVWF module adopts an intermediate fusion strategy to extract and utilize fine-grained features more effectively. It is designed to fuse the local features extracted by the pointwise fusion module PWF with the global features extracted by the voxelwise fusion module VWF. Through Stacked VFE operations, the image features at the pointwise and voxelwise levels are integrated into point features, achieving fusion between pointwise and voxelwise representations. Finally, through concatenation operations, the pointwise and voxelwise fusion features are further combined to form a 256-dimensional multi-modal fusion feature, enhancing the interaction between multi-modal local and global features. This ultimately improves the model's performance in small object detection and complex scenes, enhancing the accuracy and robustness of 3D object detection.
# An Architecture for the Performance Management of Smart Healthcare Applications
## 3 Background  
Standards organizations have defined network slicing in numerous ways [5; 6; 45]. In a nutshell, it refers to all the attempts to enable the availability of the network-as-a-service approach according to user demands khan:2020. Its key enabling technologies involve Software Defined Network (SDN) and Network Function Virtualization (NFV) due to programmability and flexibility in networking resource management [10; 46]. Together, they enable dynamic resource monitoring, allocation, and isolation in the network infrastructure by a logically centralized software-based platform [47]. Thus, network slicing allocates bandwidth, spectrum, and computing capacity based on application requirements [40].  
A tenant refers to a group of users accessing the shared resources with specific access privileges and access rights. It directly serves an end-to-end communication, or a vertical network tenant to access a service, under a fully qualified set of requirements [48].  
SDN technologies simplify the networking hardware by decoupling the control from the data plane. It removes control functionality from network devices (e.g., switches). These devices become simple packets forwarders (the data plane), and the network control becomes directly programmable via an open interface (e.g., OpenFlow). This configuration enables communication compatibility and interoperability among different data and control plane devices. The SDN devices forward the packets based on a network flow abstraction. Thus, the flow tables store a programmable set of forwarding rules in the memory architecture. SDN controllers, logically centralized, customize the flow rules on the memory and accommodate network control functions [47]. Therefore, SDN enables a high-level of slice abstraction from different network forwarding rules, dynamically managing network slices, and a simple NFV development. Figure 1 presents an overview of network slicing using NFV and SDN.  
NFV defines a set of softwarized functions to enable the original network functions (NF) to share the same physical environment, i.e., dispatch a network function, such as a firewall, to a provider (cloud data center) as a software instance, i.e., Virtual Network Functions (VNFs). The detachment of software from hardware helps to reassign and to share the infrastructure resources, allowing the deployment of new network services faster over the same physical platform. Therefore, VNFs allow networks to be agile and capable of responding automatically to the needs of the services running over it. This comprises a crucial feature from network slicing once it involves multiple heterogeneous physical resources managed centrally.
# Definition and Determination of Fin Substitution Factors Accelerating Thermal Simulations
## 4 Discussion and Conclusions
The _FSF\({}_{A,h,Ai}\)_ path gave the best results with an 8% overall mean deviation and an overall standard deviation of 0.5. For this reason, this calculation path is recommended for the analytical determination of the _FSF_ for vertical rectangular finned arrays considering natural convection with air as surrounding fluid and an isothermal boundary condition. In Section 3.3.4. the _FSF\({}_{A,h,Ai}\)_ path was verified using three different fin arrays at three different temperatures. The deviation between the results of the CFD simulations and the solid-state simulations (FEA) using the _FSF\({}_{A,h,Ai}\)_ were between \(-6.47\%\) and \(13.77\%\). The average relative deviation according to the amount of overall simulations was \(6.2\%\). In light of these results, the approach presented in this work is suitable for accelerating thermal simulations and achieves sufficiently accurate results simultaneously. As an alternative to the methods presented or used in [9; 10; 11] to substitute cooling fins, our approach offers an analytical solution. Provided that the corresponding formulas and correlations are available or that existing ones can be transferred, thermal simulations of any fin geometries and orientations can be simplified under various boundary conditions. The technical benefit of the approach becomes evident when correspondingly large and complex components are considered, such as large transformers or dry storage tasks for spent fuel assemblies. The authors' future research focuses on defining different analytical calculation paths, e.g., for constant heat flow boundary conditions instead of an isothermal one or other fin shapes and orientations. In addition to natural convection, radiation-related heat transfer should also be considered to depict real problems with _FSF_ more precisely. Not applicable. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# A Graph Convolutional Network Based on Sentiment Support for Aspect-Level Sentiment Analysis
## 4 Experimental Analysis
### Comparison of Model Concatenation Methods  
We used the concatenation operation to connect the feature representations of aspect words and SSWs, sending the final feature representations to Softmax for emotional classification. To illustrate why Concat was used, we applied the _Restaurant_ dataset as an example to compare Concat with direct addition and multiplication operations. The experimental results are shown in Table 5. From this table, it can be seen that using the Concat operation yielded better results than other operations in terms of accuracy and macro F1.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{_Restaurant_} & \multicolumn{2}{c}{_Laptop_} & \multicolumn{2}{c}{_Twitter_} \\ \cline{2-7}  & **Acc** & **Macro F1** & **Acc** & **Macro F1** & **Acc** & **Macro F1** \\ \hline SSGCN & 83.47 & 75.90 & 77.53 & 74.25 & 74.74 & 72.80 \\ SSGCN & **84.00** & **76.81** & **78.27** & **75.30** & **75.48** & **74.21** \\ \hline \hline \end{tabular}
\end{table}
Table 4: Fixed randomized seed experiment results.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{_Restaurant_} & \multicolumn{2}{c}{_Laptop_} & \multicolumn{2}{c}{_Twitter_} \\ \cline{2-7}  & **Acc** & **Macro F1** & **Acc** & **Macro F1** & **Acc** & **Macro F1** \\ \hline IAN (2017) & 79.09 & 65.99 & 72.63 & 67.52 & 72.50 & 70.81 \\ MGAN (2018) & 81.15 & 71.64 & 75.17 & 70.84 & 72.54 & 70.52 \\ MAN (2020) & 83.47 & 70.91 & 77.21 & 72.55 & 75.58 & 71.15 \\ KumaGCN (2020) & 81.43 * & 73.64 * & 76.12 * & 72.42 * & 72.45 * & 70.77 * \\ DualGCN (2021) & 83.02 & 76.07 & 76.58 & 73.11 & 75.18 & 74.06 \\ CNN-BiLSTM (2022) & 81.96 * & 74.16 * & 72.26 * & 68.95 * & - & - \\ MGCN (2022) & 82.32 * & 74.31 * & 76.59 * & 72.44 * & 73.31 * & 72.12 * \\ SSEGCN (2022) & 83.82 & 76.92 & 78.01 & **75.35** & 73.31 & 72.12 \\ \hline SSGCN (textual model) & **84.36** & **77.67** & **78.96** & 75.17 & **75.88** & **74.56** \\ \hline \hline \end{tabular}
\end{table}
Table 3: The results of the different comparison models. * indicates the results are directly cited from the original paper (%).  
Through the experimental results, it can be seen that the operation of directly adding or multiplying the feature representations of aspect words and sentiment support words resulted in partially lost important information, which was inferior to the concatenation operation with regard to the accuracy and macro F1. Therefore, the concatenation operation was selected for the model in this section.
# A Modified Bearing Capacity Model for Inclined Shallow Anchor Cable with Experimental Verification
## 3 Validation by Model Experiment  
To verify the accuracy of the theoretical model, a series of pull-out tests with different anchor inclinations were developed in the laboratory.
# Persistent Homology Approach for Human Presence Detection from 60 GHz OTFS Transmissions
## 2 Orthogonal Time Frequency Space Communication
### OTFS Modulation  
The OTFS information symbols (usually QAM symbols) \(x[k,l]\), placed in the delay-Doppler domain with a delay domain index \(k=0,1,\ldots,N-1\) and a Doppler domain index \(l=0,1,\ldots,M-1\), are first spread in the time-frequency domain with symbols \(X[n,m]\) through a 2D Inverse Symplectic Finite Fourier Transform (ISFFT) according to:  
\[X[n,m]=\text{ISFFT}\{x[k,l]\}=\sum_{k=0}^{N-1}\sum_{l=0}^{M-1}x[k,l]e^{-j2\pi( \frac{m}{M}-\frac{k\pi}{N})}. \tag{1}\]  
Note that the delay-Doppler symbols \(x[k,l]\) can be either the data symbols \(x_{d}[k,l]\) or the pilot symbols \(x_{p}[k,l]\). Subsequently, the signal \(X[n,m]\) is transformed from the time-frequency to the time domain using a Heisenberg transform:  
\[x(t)=\sum_{n=0}^{N-1}\sum_{m=0}^{M-1}X[n,m]w_{TX}(t-nT_{Sym})e^{j2\pi m\Delta f \left(t-nT_{Sym}\right)}, \tag{2}\]  
where \(w_{TX}(t)\) is the transmit pulse shape, \(T_{sym}\) and \(\Delta f\) are the symbol duration and tone separation that (inversely) define a quantization step in the delay and Doppler grid.  
In general, two variants of OTFS have been studied so far. Firstly, the original one, with a single cyclic prefix (CP) before transmission of the whole \(N\times M\) data symbol matrix and, secondly, its OFDM-based alternative [24] with a cyclic prefix before each of the 'corresponding OFDM symbols'. In order not to reduce spectral efficiency, we consider the usage of a single CP.
## 5 Experimental Results
### Detection Accuracy Analysis Channel Hole Not-Open  
Figure 11 shows the experimental results for detecting channel hole Not-Open defects. This type of defect is detected by monitoring the state of the status pin after performing an erase operation to target flash blocks. When the state of the status pin is high (i.e., erase status fail), the target block is regarded as having Not-Open defects, thus being numbered as a bad block. Figure 11a shows how many bad blocks are generated after an erase operation while varying the erase voltage (\(V_{ERS}\)). The Y-axis denotes the distribution of bad blocks of our tested flash blocks. Even though \(V_{ERS}\) is raised from 20 V to 24 V, there is no significant change in detection accuracy. It means that the operating conditions for a single erase operation alone do not affect whether Not-Open defects are detected or not. To efficiently reveal the hidden Soft Not-Open defects, we re-count the number of bad blocks after performing erase cycle stress. As shown in Figure 11b, the more erase cycles, the more bad blocks occur. As the number of erase cycles increases, the joint region between the substrate and the channel hole suffers from electrical stress, so the Soft Not-Open defect can be efficiently switched into the Hard Not-Open defect that is easily detected by a simple function check. Figure 11c shows how our proposed technique can reduce the infant mortality of flash products due to channel hole Not-Open defects. In the case of 50 erase cycles, additional bad blocks are found even in the early stage of the flash lifetime. However, in the case of 200 erase cycles, no bad block was found up to 100 P/E cycles. (It is known that commercial TLC NAND flash memory can tolerate 1000 P/E cycles. In our study, 100 P/E cycles (i.e., 10% of a total lifetime) are regarded as the early stage of flash lifetime.) It indicates that the combination of erase cycles and erase function check is an effective solution to screen out hidden Not-Open defects.
## 3 Discussion
### Genome Assembly  
The _A. domesticus_ genome assembly represents a contiguous assembly for downstream applications. The assembly contains 11 large scaffolds, presumably representing most of the autosomal and X chromosomes, in 2.138 Gb, close to the flow-cytometry predicted genome size of 2.150 Gb for male _A. domesticus_. There were 29,304 predicted genes, mostly concentrated on the large chromosomes. These data will be important for the insect food industries, but also for orthopteran studies in biology and evolution.  
Immediately after obtaining the genome assembly, we looked for promoters for genes for use in our transgenic experiments but encountered genes with very long sequences that were distinctly longer than the coleopteran genomes we have studied. A quick comparison of the length of the BUSCO reference gene sequences estimated that the _A. domesticus_ genes were on average 80% longer than those in _T castaneum_. We also noticed that, in most cases, the longer genes were due to longer introns that may be due to TEs as has been observed in other Orthoptera [53; 54]. Therefore, we compared repetitive elements in the _A. domesticus_ genome assembly with those available for other orthopterans and found that the _A. domesticus_ genome assembly contains the highest content of TEs (almost half of the assembly) compared to other cricket genomes. Repetitive elements and genome size in Orthoperta were significantly correlated if we included the very large genome of _L. migratoria_ (\(p\) = 0.024). When _L. migratoria_ data was excluded, LTR elements and DNA transposon were positively correlated to the expansion of genome size in crickets (\(p\) < 0.001). As we suspected, repetitive element and median length of intron were positively correlated (\(p\) = 0.044) but only when _L. migratoria_ was included, and especially for elements LINE/CR1, LINE/L1, LINE/Penelope, LINE/RTE, DNA/hAT, DNA/Kolobok, and DNA/TcMar. Our data suggest that LINE and DNA TEs contribute to variation in genome size and corresponding intron length in Orthoptera, but this is likely found only at the suborder level. Furthermore, the TE distribution pattern of LTR transposons shows a recent or ongoing burst in the _A. domesticus_ genome and likely contribute to the high abundance of repetitive elements in the genome of this species.
## 2 Materials and Methods
### Ore Characterization and Leaching Operations  
Gibbsite bearing shale ore material was collected from Abu Thor mining area in the district of Abu Zeneima locality (South Sinai Governorate, Sinai, Egypt). Major and economic elements were analyzed according the methods reported by [PERSON] [42]. The samples were previously crushed (i.e., \(-\)200 mesh) and quartered. Calcium and Mg were determined by titration method using EDTA and Eriochrome black T as the indicator, respectively. Al\({}_{2}\)O\({}_{3}\), SiO\({}_{2}\), and Fe\({}_{2}\)O\({}_{3}\) (total) were measured using spectrometric analysis, Na\({}_{2}\)O and K\({}_{2}\)O were quantified using flame photometry. The index of rare earth elements (total REEs) was measured using UV-Visible spectrometry (Shimadzu UV-160, Shimadzu Scientific Instruments, Kyoto, Japan) [43] in the presence of arsenazo III (0.015%, \(w/w\)), at the wavelength \(\lambda\): 654 nm. Trace elements corresponding to Cu, Zn, V, and Ni were determined at wavelengths 365.4, 334.4, 271.5, and 360.1 nm, respectively, by atomic absorption spectrometry (Pye Unicam Solaar 969, Pye Unicam, Cambridge, UK). Uranium was measured using oxidometric titration method by NH\({}_{4}\)VO\({}_{3}\), in the presence of sodium salt of diphenyl amine-4-sulfonic acid as the titration indicator [44].  
The Abu Thor mining area is characterized as a sedimentary basin; local ores are characterized by high contents of silica, aluminum, iron, calcium, and magnesium, with levels of 34.15%, 19.04%, 11.43%, 7.11%, and 4.18%, respectively. The chemical constituents of this ore are reported in Table S2. In addition to these major elements, the ores are characterized by important levels of base metals (Cu, Zn, Ni, Co, Cd and V), uranium (about 419 ppm), and REEs (about 1098 ppm). This ore is relatively complex to treat for the selective recovery of valuable metals because of the diversity of metals and the relatively high metal contents.  
Several leaching agents were tested (i.e., sulfuric acid, hydrochloric acid, and nitric acid) and alkaline (carbonate and bicarbonate solutions). The optimum condition was achieved by using an agitated tank reactor, with sulfuric acid solution (100 g L\({}^{-1}\); i.e., \(\sim\)1 mol L\({}^{-1}\)), a solid/liquid ratio close to 1/3. Leaching was performed at room temperature, under agitation for 3 h. A pre-treatment was operated using DOWEX 50X8 cationic commercial resin at pH 4. The residual solution was tested for polishing treatment using synthesized sorbent. After filtration of collected pre-treated samples, the concentration of leached metal ions was analyzed. Sorption tests were carried out using the same experimental procedure as those used for sorption from synthetic solutions.
# Experimental Research on Mechanical Performance of SSRC Columns under Eccentric Compression
## 3 Experimental Results  
### Failure Modes  
The typical failure and crack development patterns caused by the eccentric loading of the columns are depicted in Figures 3 and 4. Specimens SSRC1, SSRC3, SSRC4, and SSRC7 were loaded under small-eccentricity loads. At 20% of the ultimate load, 3-4 transverse cracks appeared in the tension zone. At 30-50% of the ultimate load, the number of cracks increased gradually, and the lengths and widths of existing cracks developed slowly. At 50% of the ultimate load, longitudinal cracks appeared in the compression zone. At 90% of the ultimate load, the transverse crack extended to the neutral axis of the test column, the crack width became larger, and the lateral displacement continued to increase. When the ultimate load was reached, the test column produced a crisp noise, and many longitudinal cracks appeared in the compression zone. The load dropped rapidly when the lateral displacement increased.  
Specimens SSRC2, SSRC5, SSRC6, and SSRC8 were loaded under large eccentricities. At 20% of the ultimate load, transverse cracks appeared in the tension zone of the test column, and the increase in the load was accompanied by increments in the widths and lengths of the transverse cracks. At 50% of the ultimate load, there were almost no new cracks in the tension zone. At 90% of the ultimate load, longitudinal cracks appeared in the compression zone, and transverse cracks penetrated.  
Figure 2: Test setup.  
Figure 4: Typical crack patterns: (**a**) small eccentric and (**b**) large eccentric.  
Figure 3: Typical failure modes for specimens: (**a**) small eccentric compression, (**b**) large eccentric compression, (**c**) side view, (**d**) compression side, and (**e**) tension side.
## 2 Unit Cell Design and Proposed FPC Antenna
can be inferred that an off-broadside radiation with a high gain can be realized in the FPC configuration. The reflection/transmission characteristics of the unit cell for oblique angle incidences are shown in Figure 3, and the results are given for both TE and TM wave polarizations. All results were plotted for AP\({}_{\text{L}}\) = 5.5 mm (the center of the gradient, see Table 1). From Figure 3a,b depicting TE wave polarization, it is evident that despite the variation of the angle of incidence, low magnitudes (less than \(-\)10 dB) of reflection as well as transmission are still being obtained over a wide band (starting from about 7 GHz and beyond). For the TM case, a similar behavior is also observed, and can be witnessed from Figure 3c,d. It can be asserted that the PRS backed AFSS, as an absorber, shows good angular stability. Figure 3: Unit cell response to oblique angle incidences of TE/TM wave polarizations. (**a**) Reflection response for TE wave. (**b**) Transmission response for TE wave. (**c**) Reflection response for TM wave. (**d**) Transmission response for TM wave. (All results shown for AP\({}_{\text{L}}\) = 5 mm). A 7 \(\times\) 7 unit cell array was mounted on top of a rectangular patch antenna, as shown by the simulated model in Figure 4a, and experimental prototype in Figure 4b. Cavity height (h) is 13 mm (\(\sim\)/4). The coaxial feed offset is 3.2 mm from the patch center towards +x-axis. All dielectric laminates are of Rogers RO4003C material (\(\epsilon_{\mathrm{r}}\) = 3.55 (design), thickness 1.52 mm). Gradient implementation is along y-axis, with the AP\({}_{\mathrm{L}}\) values and the corresponding reflection phases shown in Table 1.
# Mapping a Guided Image Filter on the HARP Reconfigurable Architecture Using OpenCL
## 5 Guided Image Filtering
### OpenCL Code
#### 5.2.5 Shared Virtual Memory  
The shared memory architecture of the HARP platform can make use of SVM. In SVM, both the CPU and the FPGA have full access to a specially allocated memory region. Therefore, only one instance of the data is present in memory, and no explicit data copies to a separate memory region, only available for FPGA, are necessary. The use of SVM therefore significantly reduces the communication overhead when passing data to and from the OpenCL kernel. This is illustrated in the Section 6.4 of the experimental results. Interestingly, the kernel code for using shared virtual memory is unchanged. The modification is done in the host code, using the API functions clSVMallocAltera to allocate shared memory and clSetKernelArgSVMPointerAltera to pass the arguments to the kernel.