esa-sceva/satcom-chunk-collection huggingface dataset:
# Effective Monoaural Speech Separation through Convolutional Top-Down Multi-View Network
###### Abstract  
Speech separation, sometimes known as the \"cocktail party problem\", is the process of separating individual speech signals from an audio mixture that includes ambient noises and several speakers. The goal is to extract the target speech in this complicated sound scenario and either make it easier to understand or increase its quality so that it may be used in subsequent processing. Speech separation on overlapping audio data is important for many speech-processing tasks, including natural language processing, automatic speech recognition, and intelligent personal assistants. New speech separation algorithms are often built on a deep neural network (DNN) structure, which seeks to learn the complex relationship between the speech mixture and any specific speech source of interest. DNN-based speech separation algorithms outperform conventional statistics-based methods, although they typically need a lot of processing and/or a larger model size. This study presents a new end-to-end speech separation network called ESC-MASD-Net (effective speaker separation through convolutional multi-view attention and SuDoRM-RF network), which has relatively fewer model parameters compared with the state-of-the-art speech separation architectures. The network is partly inspired by the SuDoRM-RF++ network, which uses multiple time-resolution features with downsampling and resampling for effective speech separation. ESC-MASD-Net incorporates the multi-view attention and residual conformer modules into SuDoRM-RF++. Additionally, the U-Convolutional block in ESC-MASD-Net is refined with a conformer layer. Experiments conducted on the WHAM! dataset show that ESC-MASD-Net outperforms SuDoRM-RF++ significantly in the SI-SDRi metric. Furthermore, the use of the conformer layer has also improved the performance of ESC-MASD-Net.  
speech separation; conformer; multi-view attention; residual conformer network Article
# Digital Twin in the Maritime Domain: A Review and Emerging Trends
## 5 Developing a Ship Digital Twin Architecture
### Functional Requirements of User Groups  
The DT of a fully autonomous ship will act as a complete controller of the vessel while regular manned vessels will act as a Digital Model or Digital Shadow to maintain the required data structure. A DT solution should be capable of performing the following actions to provide service to the three main stakeholders: onboard crew (if present), shore operator and researcher/engineer (Figure 6).  
Figure 5: General Functions of a Surface Ship.  
A ship DT should be able to replicate all the Smart Functions [34] of a digitalized surface ship, including the following mandatory requirements:  
* Structural Health Monitoring (SHM);
* Machinery Health Monitoring (MHM);
* Operational Performance Management (OPM);
* Asset Efficiency Monitoring (AEM);
* Crew Assistance and Augmentation (CAA).  
Apart from the above functions, a robust communication link is to be established between the ship and the shore operator to obtain real-time situational awareness with complete control during the voyage. Digital images can act as a model, shadow or twin depending on the data handshake method. DT can be utilized to monitor and maintain the autonomous control of the vessel including self-navigation and collision avoidance. The formidable internal verification system generated due to the DT architecture will enhance the existing conceptual design optimization using virtual testing and intelligent process monitoring till the finalized model is developed [90].  
Since the data handled in a fully integrated DT Process Model (DTPM) will be large and complex, therefore the model must be composed of Design Data (DD), Process Data (PD), Process Perception Data (PPD), Historical Running Data (HRD) and Simulation Data (SD) targeting the whole product life cycle [91]. Separate component schema for serialization of various components can be implemented covering the asset data, analysis and measured data of different segments of ships and can be shared among various stake holders [92] (Figure 7). The physical and control architecture of the future ships is also evolving each day with new concepts in improving the efficacy and efficiency of the vessels targeting economic and emission goals. Designing, testing, validating, and implementing a robust Digital Twin (DT) model for a surface ship will provide seamless support for the functioning of the ship/craft to its intended operation despite being an unmanned craft or a conventional crewed vessel.
# Optimized Gateway Placement for Interference Cancellation in Transmit-Only LPWA Networks
## 3 Single GW Placement for Two SNs
### Capture Circle  
The contents of this section are summarized from [8], for the convenience of the reader and to establish notation. Considering two SNs located at \(s_{1},s_{2}\in\Re^{2}\) and one GW located at \(g\in\Re^{2}\), we use \(s_{1},s_{2}\) and \(g\) as both their locations and identities for the sake of simplicity. A packet from \(s_{1}\) will be captured and successfully decoded by the GW \(g\) if  
\[\frac{P_{r}(d_{1})}{P_{r}(d_{2})+N_{0}}\geq\tau, \tag{5}\]  
where \(d_{i}\) is the distance from GW \(g\) to SN \(s_{i}\), and \(\tau\) is the capture threshold, as discussed in the previous section. We omit noise term \(N_{0}\) from the inequality in Equation (5) since it is expected to be negligible with respect to the other terms [26]. Then, we obtain that  
\[\frac{P_{r}(d_{1})}{P_{r}(d_{2})}\geq\tau\quad\Longleftrightarrow\quad\frac{1 /(d_{1})^{n}}{1/(d_{2})^{n}}\geq\tau,\]  
\[d_{1}\leq\beta d_{2}, \tag{6}\]  
where \(\beta=\tau^{-1/n}\). With \(\tau>1\), then \(0<\beta<1\). We may write \(d_{i}=\|g-s_{i}\|\), where \(\|\cdot\|\) is the Euclidian norm of a vector in \(\Re^{2}\). Substituting into Equation (6) yields  
\[\|g-s_{1}\|\leq\beta\|g-s_{2}\|. \tag{7}\]  
Squaring both sides of Equation (7) gives  
\[\|g-s_{1}\|^{2}\leq\beta^{2}\|g-s_{2}\|^{2}\]  
\[\Longleftrightarrow(1-\beta^{2})\|g^{2}\|-2g\cdot(s_{1}-\beta^{2}s_{2})\leq- \|s_{1}\|^{2}+\beta^{2}\|s_{2}\|^{2},\]  
where \(\cdot\) means the inner product of two vectors. With \(0<\beta<1\), it follows that  
\[\|g-\frac{s_{1}-\beta^{2}s_{2}}{1-\beta^{2}}\|\leq\frac{\beta}{1-\beta^{2}}\| s_{1}-s_{2}\|. \tag{8}\]  
An interpretation of Equation (8) is that \(s_{1}\) can be captured by \(g\) when \(s_{1}\) and \(s_{2}\) interfere, if \(g\) is inside a circle called the capture circle, with center \(\frac{s_{1}-\beta^{2}s_{2}}{1-\beta^{2}}\) and radius \(\frac{\beta}{1-\beta^{2}}\|s_{1}-s_{2}\|\)[8], as shown in Figure 2.  
Figure 2: The capture region defined by center and radius, based on SN pair (\(s_{1},s_{2}\)).
# Transmission Tower Re-Identification Algorithm Based on Machine Vision
## 2 The Proposed Method
### Transmission Tower matching Network
#### 2.3.5 Matching Network Training Method  
The training process of the matching network is illustrated in Figure 9. During the training process, the images first undergo data augmentation. Data augmentation techniques include random flipping, HSV color enhancement, and random bottom occlusion. Augmented images are fed into the matching network to generate corresponding feature vectors (features1 and features2). Specifically, features1 is utilized to construct triplet samples. The detailed description of online triplet generation is provided in Section 2.3.3. Furthermore, features2 is employed to compute the cross-entropy loss. The total loss, described in detail in Section 2.3.4, is optimized using the Adam optimizer during the training of the matching network.
# Slope Stability Analysis of Open-Pit Mine Considering Weathering Effects
## 5 Conclusions  
The impacts of weathering on the stability of open-pit mine slopes were rigorously examined through laboratory tests. The correlation functions between weathering time and mechanical properties were obtained, providing valuable insights into the detrimental effects of weathering on rocks. The finite element method serves as a robust tool to simulate and analyze slope stability under varying weathering conditions. The weathering processes lead to a loosening of the rock structure and a corresponding decrease in its strength and stability. The limit equilibrium methods were used for slope stability analysis, and revealed that an increase in weathering time gradually weakens the slope surface rock, ultimately resulting in a reduction in the slope safety factor. For slopes exceeding 90 m in height, it is advisable to avoid a final slope angle of 47 degrees if the intended service life exceeds one month. This study underscores the crucial importance of considering weathering effects in the design and maintenance of open-pit mine slopes which also help to ensure the long-term stability and safety of the slope structures.  
Conceptualization, W.L. and S.W.; methodology, D.L. and X.K; software, M.Y.; validation, W.L., X.K. and G.S.; formal analysis, M.Y.; resources, W.L., X.K. and G.S.; data curation, W.L., X.K. and G.S.; writing--original draft preparation, S.W. and D.L.; writing--review and editing, S.W. and D.L; project administration, S.W.; funding acquisition, W.L., X.K. and G.S. All authors have read and agreed to the published version of the manuscript.  
This paper is funded by National Natural Science Foundation of China (52474144, 52004196), the Shaanxi Innovation Capability Support Program, the Science and Technology Innovation team (2023 CX-TD-12), the Shaanxi Province Department of Education Key Projects of Scientific Research Program (23 JS036), and the Ministry of Education, \"Chunhui Plan\" (HZKY20220534).  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Author [PERSON], [PERSON] and [PERSON] were employed by the company Shaanxi Provincial Land Engineering Construction Group. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 4 Results and Discussion
### Impact of the Macro- and Micro-Deformation Behavior on the Thermal Cycling Reliability
When the macroscopic strain is \(0.4\%\) (which is equivalent to that used in thermal cycling experiment), although the stress concentration sites where the local Mises stress exceeds the tensile strength of Cu\({}_{6}\)Sn\({}_{5}\)[42] can be partially identified, it is evident that the stress is broadly distributed (Figure 11c). Further, almost no sites with local Mises stress exceeding the tensile strength of the Cu\({}_{6}\)Sn\({}_{5}\) can be found in the low strain (0.1%) condition (Figure 11b); however, many such sites can be found in the high-strain (1.0%) condition (Figure 11e). Considering the poor ductility of the IMCs, the micro-deformation behavior interestingly indicates that the high reliability of the TLPS joint is limited by this specific condition on the macroscopic strain; further evaluation of the durable strain conditions is of particular interest. It may be noted that some earlier studies have reported the deformation behavior of TLPS joints under temperature variation. [PERSON] et al. [29] experimentally and numerically identified a new failure mechanism i.e., cooling-induced formation of vertical cracks in Cu-Sn and Ni-Sn TLPS joints based on the stress concentration at the interface of the TLPS layer and DBC substrate. [PERSON] et al. [27] also numerically investigated Cu-Sn TLPS joint under thermal cycling, where they evaluated the potential failure modes corresponding to the fatigue of chip metallization and brittle fracture of IMC, components, or interfaces. These studies revealed that the brittle fracture modes mainly occurred due to the stiffness and brittleness of the IMCs; therefore, the joint reliability would strongly depend on the stress conditions; i.e., joint dimensions, operation temperature, and so on. In contrast, the proposed Cu-IMC-resin TLPS microstructure exhibited deformation behavior under low-stiffness and broad stress distribution because of its inherent \"skeleton-shape\", thereby facilitating the excellent thermal cyclic reliability of the joint. However, a comprise between low stiffness and high thermal conductivity was required for efficient operation; consequently, further optimization of the skeleton microstructure to achieve both low stiffness and high thermal conductivity is of particular interest.
## 3 Experimental Results and Discussion
### Evaluation on the Fully-Observed Video Sequences Scenario  
In this section, we evaluate the performance of the proposed approach in recognizing the four fall-related activities from fully-observed video sequences. Specifically, in this evaluation scenario, the video sequences are fully observed as described in Figure 1a. For the purpose of this evaluation scenario, we have trained a multi-class SVM classifier using the HBRs obtained from unsegmented training video sequences. In particular, for each training video \(V_{trn}\) of length \(N\) frames, we construct the HBR of the video frames with indices between one and \(N\). Using the obtained HBR from each training video sequence, we train the multi-class SVM classifier to identify the four fall-related activities in our dataset.  
In order to classify a testing video sequence \(V_{tst}\) of length \(T\), we construct the HBR of the video frames with indices between one and \(T\) in the video \(V_{tst}\), namely \(\mathbf{H}_{V_{tst}[1:T]}\). Then, using the trained multi-class SVM classifier, the class of \(V_{tst}\) can be determined by rewriting Equation (22) as follows:  
\[c^{*}=\arg\max_{c}P(\omega_{c}|\mathbf{H}_{V_{tst}[1:T]}). \tag{27}\]  
Table 3 shows the results of recognizing the four fall-related activities expressed using the precision, recall and F1-measure as an evaluation metric. The average recognition accuracy of fully-observed video sequences is 93.6%. The results demonstrate the capability of the proposed approach to detect falls from fully-observed video sequences.  
In comparison, the Kinect-based approach proposed by [PERSON] et al. [35], which was evaluated using 55 fall depth-map videos, achieved an average fall classification accuracy of 93%. Similarly, the Kinect-based system introduced by [PERSON] and [PERSON] [36] achieved fall detection accuracies between 86.1% and 89.3% based on a dataset that includes 40 falls and 32 non-falls depth-map videos. In fact, the results reported in our study for the fully-observed depth-map video sequences are comparable to the results reported in the previous approaches. It is worth noting that the main focus of our work is to detect falls form partially-observed depth-map video sequences, which has not been investigated in previous studies. The following subsections provide the performance evaluation results obtained by our approach for the partially-observed depth-map video sequences.
## 4 Discussion
### Gain Shift versus Symmetric-like Bubble  
Originally, we believed that the apex of the symmetric-like bubble might be the ideal place to gain shift due to it having greater instability. However, the data shown in Figure 14 tells a different story. The system shows an instability at a location that seems to not match with the LEs. The dip at \(Y=1.721\) does not line up exactly with the apex of the symmetric-like bubble, instead, it is slightly to the right.  
When we instead superimpose the gain shift with the LEs for \(C=3.1\) in Figure 15, we see a dip where the asymmetric bubble reaches its apex, the signatory two-zero LEs.  
This tells us that, when the parameter shifts, we must consider the stability of the attractor at _both_ the original parameter value and the shifted value. In other words, when the gain-shift method is applied, one needs to consider the attractor's stability at both gains.  
Figure 14: Schematic of LEs vs \(Y\) graphed over the domain of AIII at \(C=3.0\) and overlayed with the gain shift results. The right ordinate displays the percentage of times that AIII survives the gain shift.  
Figure 13: Comparison of the power shift without a lag in blue dots and with \(T_{\text{lag}}=15\tau\) at \(Y_{0}=1.63\) for base AIII with \(Y_{PS}=1.84\) in orange \(x\)s. The vertical axis represents the resultant attractor for a power shift.
# A Study on the Vertical Bearing Characteristics of Screw Piles in Permafrost Regions
## 5 Conclusions  
In this study, the vertical load transfer characteristics and bearing mechanisms of drilled screw piles in the permafrost regions were investigated using model tests and numerical methods, and a bearing capacity calculation method was proposed. The major conclusions drawn from this study are as follows:  
1. Approximately 90% of the bearing capacity of screw piles in permafrost regions results from the mechanical bonding between pile side's concrete and the permafrost soil. The seasonally active layer has a minimal impact on the pile's bearing capacity, and the bearing capacity of the pile's body is stable throughout the year.
2. The equivalent friction resistance of screw piles is far greater than that of conventional cast-in-place piles when used in permafrost regions. The screw pile and the soil occlude each other, resulting in a higher equivalent friction resistance of the pile's side at the beginning and the end of the thread than that of the conventional pile type,  
Province, No. 2024 QB-048; and the Research Fund of China Railway Engineering Corporation Scientific Research Institute, No. 2023-major project-01-08.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
Authors [PERSON] and [PERSON] was employed by the Power China Guiyang Engineering Corporation Limited. Author [PERSON] was employed by the Power China Engineering Corporation of Southwest Headquarters. The remaining authors declare that the re-search was con-ducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 4 Construction of the UA-FedRL Method
### Predictive Weighted Average Aggregation
It improves convergence by prioritizing high-quality model updates and reducing the variance from poorly performing devices, leading to a faster convergence rate of \(\mathcal{O}\Big{(}\frac{1}{t^{2}}\Big{)}\) compared to the traditional \(\mathcal{O}\Big{(}\frac{1}{t}\Big{)}\) in FedAvg. The heterogeneity gap \(H_{i}\), which measures the difference between local and global model updates, is also reduced, as devices with large gaps contribute less to the global model. This results in faster convergence and more accurate global models. Additionally, by assigning lower weights to outlier devices with skewed data distributions, PWA improves the robustness of the global model, making it more resilient to non-IID data. The regularization parameter \(\lambda\) helps balance high- and low-quality contributions, preventing overfitting to any one device's data. The overall architecture of the PWA and related pseudocode can be seen in Figure 4 and Algorithm 2, respectively. For further details, refer to the supplementary matters. Figure 4: The overall architecture of the PWA which employs weight quality measurement to compute the weighted average of all local models’ weight. ```
0:\(N\) devices with local datasets \(D_{i}\) and local models \(w_{i}\), quality measures \(q_{i}\)
0: Global model parameter \(w_{t+1}\)
1: Set learning rate \(\alpha\)
2:for each round \(t\)do
3:for each device \(i\)do
4: Select a random subset \(S_{i}\) of \(D_{i}\)
5: Train local model \(w_{i}\) on \(S_{i}\) for \(e_{i}\) epochs
6: Compute quality measure: \[q_{i}=\exp\Bigl{(}-\lambda*\log\Bigl{(}\Pi_{j\in D_{i}^{\prime}}L^{\prime} \Bigl{(}y_{j},f\Bigl{(}x_{j};w_{i}^{(e_{i})}\Bigr{)}\Bigr{)}\Bigr{)}\Bigr{)}\]
7:endfor
8: Compute weighted average: \[w_{(t+1)}=\frac{\sum_{i=1}^{N}q_{i}*w_{i}^{(e_{i})}}{\sum_{j=1}^{N}q_{j}}\]
9: Update global model parameter: \[w_{(t+1)}=w_{t}-\alpha*\
abla f(w_{t+1})\]
10:endfor
```  
**Algorithm 2** PWA for heterogeneous industrial IoT mitigation.
## 3 Results and Discussion
### CH/CNC and CH/CD Edible Films
#### 3.1.5 Microstructure Properties  
The understanding of the microstructure of a film or coating is very useful as it determines its mechanical, physicochemical and barrier properties, and furthermore specifies its application. The structure of edible films can be studied by: (i) scanning electron microscopy (SEM), to investigate the structure changes of the films and obtain their surface and cross-sectional topography and (ii) Fourier-transform infrared spectroscopy (FTIR) analysis, to examine the interactions between the components of the films [45; 55]. _FTIR Analysis_  
The types of bonds between (i) CH and CNC and (ii) CH and CD, were studied with FTIR measurements on the final formed edible films. Figure 1 depicts the FTIR spectra of the different final formed edible films. The FTIR spectrum of pure CH film, shows a broad absorption peak, with its center at about 3615 cm\({}^{-1}\), which was related to the stretching vibration of O\(-\)H groups and to the intermolecular and intramolecular hydrogen bonds. Two absorption peaks appeared at 2945 and 2860 cm\({}^{-1}\), which were attributed to the symmetrical and asymmetric stretching vibrations of the carboxylate group (\(-\)CH\({}_{2}\)) respectively. The absorption peaks at 1462, 1547 and 1653 cm\({}^{-1}\) were attributed to the amides III (HN-CO), II (NH) and I (\(-\)C=O). The absorption peak at 1375 cm\({}^{-1}\) was due to the bending vibrations of O\(-\)H. Finally, the absorption peak at 1032 cm\({}^{-1}\) was attributed to the C-O-C stretching vibration [61]. Results in Figure 1 indicate that no chemical reactions occurred between CH and CNC or CH and CD during the production of composite films. There were only peaks around the absorption peak of O\(-\)H (centered at 3615 cm\({}^{-1}\)), indicating the formation of intermolecular hydrogen bonds between the components. Moreover, a significant increase in the intensity of the absorption peaks at 1032 cm\({}^{-1}\) occurred by the addition of both CNC and CD to the CH samples.
## 1 Introduction
Secondly, the advantage with respect to the frequency response of the signal transmission based on the human body medium by using the proposed system has been verified by using _in-vivo_ measurements. Furthermore, in order to determine the suitable parameters, the corresponding _in-vivo_ signal transmission experiments with different carrier frequencies, baseband frequencies and multi-paths were implemented. Results indicate that the proposed method will help to achieve reliable and high speed signal BSN transmissions for healthcare and the other related fields. The rest of the paper is organized as follows. Section 2 describes the signal transmission system based on human body medium. Section 3 mainly focuses on the experiments and results discussion. Section 4 concludes the paper.