esa-sceva/satcom-chunk-collection huggingface dataset:
# Design of External Rotor Ferrite-Assisted Synchronous
## 3 Design of Fe-PMaSynRM for High Power Density
### Multi-Physics Analysis
#### 3.5.3 The Decision on Rotor Configuration Based on Electromagnetic Analysis  
The multi-physics analysis results have been considered. The flux barriers create the rotor saliency as well as house the Fe-PM. As discussed before, the flux barrier thickness and their numbers in each pole influence the average torque and the demagnetization characteristics. The thickness of the flux barriers (\(t_{m}\)), angular span (\(\theta_{m1}\)), and magnet span (\(\theta_{m2}\)) have been optimized using the LPM and DE, as shown in Table 3 Initially, several design variables such as flux barrier number, shape, and dimensions are considered during the optimization. The DE algorithm and multi-physics analysis combined helped narrow the flux barrier number to two, which is subjected to the constraints and multi-objective cost function. The FEA simulation is then conducted on the optimal model to ensure proper saturation in the core and robustness against demagnetization. Based on the FEA results, specified torque were obtained, however, the demagnetization characteristics were not satisfied as the magnets were getting partially demagnetized at 2.5 times rated RMS current flow through the q-axis circuit. Therefore, the LPM model was modified for two flux-barrier-based design and DE optimization has been conducted to find the optimal model. The single flux barrier design met the demagnetization criteria of withstanding 2.5 times of rated current flow through the q-axis circuit. The LPM model has been modified for the single flux barrier design and optimized. The multi-physics simulation of the single flux barrier design shows that it can withstand the maximum demagnetizing field of 2.5 times the rated current.  
Figure 10: Flux density in magnets under 2.5 times of rated current for (a) two-flux barrier design, (b) single flux barrier design.
# Detection of Quasi-Static Trapped Human Being Using Mono-Static UWB Life-Detection Radar
###### Abstract  
In practical situations such as hostage rescue, earthquake and other similar events, the ultra-wideband (UWB) life-detection radar echo response from the respiration motion of the trapped person is always quasi-/non-periodic in respiration frequency or very weak in respiration amplitude, which can be called quasi-static vital sign. Although it is an extremely difficult task, considering the economic cost, the detection ability of the traditional UWB life-detection radars with only a pair of transceiver antennas is desired to be enhanced for locating the quasi-static trapped human being. This article proposes two different detection methods for quasi-static trapped human beings through the single/multiple observation points, which corresponds to the single-/multi-station radar operating mode, respectively. Proof-of-principle experiments were carried out by our designed radar prototypes, validating the effectiveness of the proposed methods.  
UWB radar; UWB life-detection radar; trapped persons; quasi-static +
Footnote †: journal: Applied Physics Letters  
Article  
Detection of Quasi-Static trapped human being using Mono-Static UWB Life-Detection Radar
# Adsorption of Cadmium and Methylene Blue Using Highly Porous Carbon from Hemp Seeds
###### Abstract  
Toxins in water, such as metal ions and dyes, have become a global challenge to humanity by causing several serious illnesses. Removal of these toxins from water is needed for human health and environmental concerns. This work investigated the use of hemp seeds as an environmentally friendly adsorbent for applications in water treatment. Pristine hemp seeds (PHSs) were carbonized at 500 and 700 \({}^{\circ}\)C to obtain carbon-based hemp seeds (CHS-500 and CHS-700 for the removal of cadmium and methylene blue. The morphological and functional groups of the carbonized adsorbents and pristine hemp seeds were determined by SEM and FTIR. Isotherm studies showed that the Langmuir model best described the adsorption process based on homogenous surfaces. The maximum adsorption capacities were obtained with CHS-700 with a 36.88 and 52.61 mg/g uptake of cadmium and methylene blue, respectively. The effect of contact time showed that the sorption process rate was rapid initially, followed by a slower increment due to the saturation of active sites. \(\Delta\)S\({}^{\circ}\) values were positive, demonstrating the increased randomness and degree of freedom of cadmium and methylene blue in water. The adsorption trends for cadmium and methylene blue by CHS-500 and CHS-700 increased as the temperature rose; a decrease was observed for adsorption by PHSs. This result suggests that the adsorption was endothermic for CHS-500 and CHS-700 and exothermic for PHSs. The pseudo-second-order model better described the uptake of both pollutants by the adsorbents. This research illustrates the great potential of carbon-based hemp seeds in removing cadmium and methylene blue dye from water.  
adsorption; cadmium; carbon; hemp seeds; methylene blue 20231039699137969 Article
# Social Media Analytics for Disaster Response: Classification and Geospatial Visualization Framework
## 3 Methods
### Dataset and Data Cleaning
#### 3.1.1 Dataset
For instance, in the case of the 2016 Ecuador Earthquake, the class \"Displaced people and evacuations\" included only three tweets, rendering it insufficient for meaningful classification and model training. Removing these underrepresented categories aimed to enhance the model's ability to learn effectively by minimizing noise and reducing class imbalance. As a result of this refinement, the dataset size was reduced from 77,196 to 76,484 tweets. This adjustment was intended to improve the overall performance of the classification model by focusing on categories with sufficient representation, allowing for more balanced and accurate learning across different disaster-related classes [4]. Figure 2 illustrates the word frequency of all disasters using a word cloud, highlighting the most frequently occurring terms in the dataset. This visualization offers insights into the dominant themes and concerns expressed by users during the disaster, providing valuable context for understanding the dataset's content and the relevance of specific terms to disaster response efforts. Figure 2: World cloud of HumAID dataset. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Event Name** & **Caution and** & \begin{tabular}{c} **Displaced** \\ **Advice** \\ \end{tabular}  & \begin{tabular}{c} **Infrastructure** \\ **Fooled and** \\ **Features** \\ \end{tabular}  & \begin{tabular}{c} **Induced or** \\ **Dead People** \\ **and** \\ **Unity** \\ \end{tabular}  & \ \begin{tabular}{c} **Missing or** \\ **Fooled People** \\ **toilet** \\ **Fooling** \\ **toilet** \\ **forums** \\ \end{tabular}  &
\begin{tabular}{c} **Not** \\ **Hunian-  
For the experiments, the dataset was split into three subsets: 70% for training, 10% for validation, and 20% for testing. This distribution ensures there is sufficient data for each stage of model development. Training ensured the model learned from a substantial portion of the data, validation was used for hyperparameter tuning and monitoring overfitting, and testing provided an unbiased evaluation of the model's final performance. This division facilitates an assessment of the model's effectiveness and generalization capabilities.
# A Local Information Perception Enhancement-Based Method for Chinese NER
## 4 Experimental Results and Comparison
### Ablation Study  
To further validate the benefit of the GAT layer and short-sequence CNNs in terms of their respective gains on the model, the outcomes of Weibo, E-commerce, and OntoNotes-based ablation experiments are recorded in Table 6.  
The ablation studies were designed as follows:  
* w/o SSCNN: without short-sequence CNN module;
* w/o GAT: no GAT layer module;
* w/o SSCNN and GAT: there is no short-sequence CNN and GAT layer module.  
Removing any module leads to significant performance degradation. Specifically, the performance difference between \"w/o GAT\" and \"Complete model\" on Weibo and E-commerce is enormous, especially in the Weibo dataset, where F1 decreases the most (1.12%). This indicates that without the GAT module, the model cannot capture the semantic interaction information between characters and their neighbors. Since dialectal slang and irregular phrases are prevalent in social domains, we must rely on GAT to more accurately capture data correlations to utilize more local information for complex contexts. Similarly, model performance deteriorates when the SSCNN module is removed. The local details captured by the SSCNN module can provide a balanced view of the global sequence details from Bi-LSTM. It is shown that SSCNN can better capture the local semantics of the text, which is crucial for capturing character-based nuances in Chinese text. On the OntoNotes dataset, removing the performance gap between the modules similarly validates the usefulness of the GAT layer and SSCNN for capturing local information. The ablation study demonstrates that the GAT layer and SSCNN are crucial for enhancing the perception of local information in the model. Both character and word neighborhood information helps to enhance the performance of NER, while the combination of the two gives the best results.
## 5 Discussion
### Towards the Acceleration Process
#### 5.1.1. Estimation Based on Software Level Optimization  
The work presented by [PERSON] et al. [17] reported a software-based parallelization of the VVC decoder, which was analysed for software-level estimation analysis. To the best of our knowledge, this was the unique published work proposing software-based optimizations with the new VVC standard. Here, the VTM5.0 decoder was redesigned using load balancing task parallelization (LBTP) and CTU-based data parallelization (CDP). The LBTP was applied to the CABAC and slice decoding task, whereas CDP was applied to each sub-module of the slice decoding task. This implementation achieved an average processing time reduction of 70.2% for motion vector component derivation, 88.2% for inter-reconstruction, 68.9% for intra-CU reconstruction, 86.8% for the inverse re-shaper, 90.2% for the DBF, 72.3% for the SAO, and 88.2% for the ALF using 4k sequences of A-class resolution, similar to those stated in Section 4.1. The aforementioned ratio improvements of different VVC decoder blocks were used to calculate the performance of the corresponding decoder block over HGPP- and EGPP-based implementations.
## 2 Materials and Methods
### Line Passing through Two Centroids in the Data Particle Geometrical Divide Approaches
In accordance with the above-described state of the art concerning data particle geometrical divide approaches, their idea can be briefly presented as the sequence of three steps, which was illustrated in Figure 3.  
Figure 1: A line passing through two points: the geometric centre (blue diamond) and the centre of mass (green diamond), dividing the current data particle into two new data particles. Figure 3: The sequence of tasks leading to the geometrical divide of data particle belonging to the two-dimensional feature space. Figure 2: Atomic data particles belonging to two newly created data particles. The main contribution to the state of the art on the data particle geometric divide methods, following the development of the new Unequal Geometrical Divide method, results from the new selection strategy of data particle to be divided. As aforementioned, the GD method in a single iteration performs the divide of all data particles. It is an effective approach in the classification process of balanced data sets [1]. The idea accompanying the genesis of the Unequal Geometrical Divide was to enable the divide of larger particles regardless of the size of those referring to the minority class samples, which in the base algorithm significantly limited the possibility of divide. Therefore, the UGD method is the data particle geometrical divide approach dedicated to applications in the classification process of imbalanced data sets. The effectiveness of the new approach in this problem is determined by the fact that the UGD method in a single iteration divides only the data particle consisting of the largest number of atomic data particles. By making the synthesis of the above-introduced lemma and the above-placed description of works concerning the development of the Unequal Geometrical Divide approach, the extended idea of the geometrical divide methods can be visualised in the form of the schema presented in Figure 4.  
In Figure 4, the orange elements refer to Lemma 1, and the blue element presents the new selection strategy of data particle, which will be divided. According to the schema, the idea of improved geometrical divide starts from determining the centre of mass and the geometric centre. Next, the comparison of vectors expressing these centres is conducted in consonance with the introduced lemma. If they are different, the divide of data particle can be realised. Otherwise, the divide of data particle is not possible. In the last step, the selection of data particle/-s is conducted. At this stage, two strategies can be applied. Pursuant to the first one, all existing data particles, whose centre of mass and geometric centre are different, will be divided. However, the second strategy, which was developed in this article, can be used as well and in accordance to its idea only the largest data particle will be divided. The described sequence of tasks can be repeated until the established number of data particles is reached.
###### Abstract
Moreover, CFD simulations are considered prior to cardiovascular operations in order to enhance the surgical strategy in coronary artery bypass surgery and heart transplant cases [8]. One of the most promising technologies that have been employed in recent years in the inspection of cardiovascular diseases is the AM process, which is used to create a highly detailed and accurate physical replica of a human heart [9; 10]. AM procedures utilize a layer-by-layer approach to construct objects from digital designs; hence, a 3D model of the heart can be fabricated in order to accurately represent its shape, size, and structure. It must be noted that certain AM technologies can provide the ability to construct 3D models with tissue-like materials [11; 12]. These physical 3D-printed models could be a valuable educational tool for medical students and healthcare professionals, allowing them to examine the heart in greater detail and gain a better understanding of its anatomy and function [13]. However, certain challenges such as the quality of the medical imaging data derived from MRI or CT scanning procedures, as well as the duration and the expertise that is necessary for the 3D modeling of patient-specific hearts, need to be addressed. The objective of the present study is the development of novel technological tools based on cutting-edge applied sciences such as 3D modeling, VR, numerical simulation, and the additive manufacturing of complex cardiac models. In particular, the novelty of the present research can be summarized in the next remarks:  
* The 3D modeling of patient-specific human hearts using a robust and fast 3D reconstruction and segmentation tool that does not require the purchase of dedicated software packages or special training on its operation;
* The development of a sophisticated virtual reality environment that provides the necessary technological assets in order to inspect a human heart, providing a unique and valuable learning experience for healthcare professionals, medical students, and patients;
* The visualization of complex simulations for professional clinicians, which can be a valuable tool in studying the hemodynamics of the human heart, designing medical devices, or even planning surgical procedures in the developed VR environment;
* The fabrication of additively manufactured human hearts utilizing heart-like materials in order to produce a detailed replica of the real one, highlighting potential heart defects or allowing scientists and doctors to study the structure as well as the function of the heart in greater detail.
## 3 Confounding Adjustment Methods
### Doubly Robust Estimator  
Doubly robust estimators combine models for the treatment and outcome in such a way that they provide unbiased estimates for the treatment effect as long as one of the models is correctly specified. Augmented Inverse Probability Weighting (AIPW) is a commonly used doubly robust estimator. The AIPW is built by combing an inverse probability weighting approach with g-computation [45]. For each treatment group, a separate model for the outcome variable is fitted by using a set of covariates, and the potential outcomes that correspond to each treatment assignment are predicted for all the subjects as follows:  
\[\hat{Y}_{i}(0)=g^{-1}\Big{(}X_{i}\hat{\mathbf{\beta}}_{c}\Big{)},\ \hat{Y}_{i}(1)=g^{-1} \Big{(}X_{i}\hat{\mathbf{\beta}}_{t}\Big{)}\]  
where \(g^{-1}\) is the inverse link function used in the generalized linear model for the outcome variable, \(\hat{\mathbf{\beta}}_{c}\) is the regression coefficient estimate for the outcome regression model in the control group, and \(\hat{\mathbf{\beta}}_{t}\) is the coefficient estimate for the outcome regression model in the treatment group. The AIPW estimates are given by [46]  
\[\hat{\mu}_{0}=\frac{1}{n}\sum_{i=1}^{n}\frac{(1-A_{i})Y_{i}}{1-\hat{e}_{i}}+ \frac{(A_{i}-\hat{e}_{i})}{1-\hat{e}_{i}}\hat{Y}_{i}(0),\]  
\[\hat{\mu}_{1}=\frac{1}{n}\sum_{i=1}^{n}\frac{A_{i}Y_{i}}{\hat{e}_{i}}-\frac{(A _{i}-\hat{e}_{i})}{\hat{e}_{i}}\hat{Y}_{i}(1),\]  
where \(\hat{e}_{i}\) is the predicted PS for a subject from the treatment model.  
A targeted maximum likelihood estimator (TMLE) is another doubly robust estimator that is based on a targeting step to optimize the bias-variance tradeoff for the parameters of interest [47]. Like the g-computation, TMLE estimates the predicted probabilities of potential outcomes for each subject. Then, g-computation calculates the difference in those two predicted probabilities over all levels of the covariates, whereas TMLE involves an extra targeting step incorporating the inverse probability weights prior to calculation of treatment difference.
# DDPG-MPCC: An Experience Driven Multipath Performance Oriented Congestion Control
## 2 Experience Driven MPCC Design
### DDPG-MPCC Implementation  
Our implementation is tailored so that DDPG-MPCC retains the sound characteristics of MPCC while the DDPG plugin module accelerates the learning and bandwidth exploration process. MPCC starts with the slow start phase, multiplicatively increasing its sending rate until the utility decreases. When the utility decreases, it will go to the probing phase, exploring a network with a higher and lower sending rate. This probing mechanism helps congestion control to decide the direction in which the rate should be changed. In the moving phase, DDPG-MPCC will determine how much the rate must change to increase the utility. When utility decreases, it falls back to the probing phase. Our project page is available at github [[https://github.com/MPTCP-FreeBSD](https://github.com/MPTCP-FreeBSD)]([https://github.com/MPTCP-FreeBSD](https://github.com/MPTCP-FreeBSD)) (accessed on 1 January 2024), and the implementation of this paper will be publicly available at DDPG-MPCC repository [[https://github.com/MPTCP-FreeBSD/DDPG-MPCC-SRC](https://github.com/MPTCP-FreeBSD/DDPG-MPCC-SRC)]([https://github.com/MPTCP-FreeBSD/DDPG-MPCC-SRC](https://github.com/MPTCP-FreeBSD/DDPG-MPCC-SRC)) (accessed on 1 January 2024). The implementation and experiment of DDPG-MPCC have been fully conducted by the author, [PERSON], as a part of his honors thesis for SIT723, School of IT, Deakin University.  
The initial data were collected through the kernel logs while setting up the network scenario over CloudLab. The CloudLab clusters consist of nearly one thousand machines distributed across three sites in the United States: Utah, Wisconsin, and South Carolina. These machines are interoperable with existing testbeds, such as GENI and Emulab, allowing us to utilize hardware at dozens of sites around the world. See [[https://www.cloudlab.us/](https://www.cloudlab.us/)]([https://www.cloudlab.us/](https://www.cloudlab.us/)) for details.  
Figure 1: Abstract view of the interrelationship between DDPG-MPCC Modules.  
We train the DDPG model offline using the collected logs. We can also change the utility function to prioritize lower latency and loss rather than high utilization or vice versa. In our experiments, each episode starts by resetting the whole environment, and the training session always begins with a new data point whose utility is between 40% and 70%. Each episode trains the underlying agent to capture the interrelationship between action, states, and reward. We execute 1000 actions or steps, improving the entire episode's reward. This is the training of the model based on the data-networking dynamics collected over the MPCC environment data for 1000 episodes. In actual deployment, the model will be used at specific intervals to receive data from the kernel space and calculate the best action given the current state of the network.
###### Abstract  
The clearance of a kinematic pair will lead to the contact collision between the joints of the mechanism, which will have a great influence on the dynamic characteristics of a mechanical system with clearance. In order to study the influence of a rotating motion pair with clearance on the dynamic characteristics of a tool changing robot, a contact wear dynamics model of a modular tool changing robot was established based on the three-state model of \"free-contact-collision\". Different from analysis of a light linkage structure, this paper takes a solid structure with large mass as the analysis object. Based on the impact contact force model and the improved Coulomb friction model, the effects of clearance size, rotational speed and friction coefficient on the dynamic characteristics of the tool changing robot were analyzed. The Archard wear model was used to predict the wear between the motion pairs with clearance. The analysis results show that, with the increase of clearance size and actuating speed, the fluctuation range of velocity and acceleration increases, and the fluctuation frequency decreases. Under the action of friction, the contact force between components will be reduced due to energy loss so that the kinematic reliability of the mechanism is improved. The wear of the moving pair with clearance is non-uniform. Through the research of this paper, the motion characteristics of the tool-changing robot at low speed and heavy load are clarified. The results show that the established method can realize the dynamic characteristics analysis of low-speed heavy-duty mechanisms with joint gaps, which can be used to guide the design of tool-changing robots, and also has important reference significance for the design of mechanisms containing joint gaps in general.  
tool-changing robot; joint clearance; contact force; wear and tear; dynamic characteristics analysis +
Footnote †: journal: Applied Sciences