esa-sceva/satcom-chunk-collection huggingface dataset:
# Improved Smart Pillow for Remote Health Care System
## 2 Materials and Methods
### Key Roles in the System Implementation  
As temperature, humidity and position are determined, all the data are stored in the BT host first, then transferred to cloud server for eventual analysis. All parties of the system and their connections are shown in Figure 8. The upper row is server side, and the lower row is user end, and they are all connected through to the Internet.  
Figure 8: The connection of all parties in the Remote Healthcare System.  
There are three key actors in the system being the monitor, daemon, and agent. The former two are pure software implementations and installed in the cloud server. The agent is a user end software device, which is equipped with BT and Wi-Fi for communication. It takes the initiative to connect to the pillow and obtain the raw data, then it contacts the daemon in the cloud server by Wi-Fi, with final permission given to upload the raw data to the daemon in the cloud server.  
In the cloud side, the daemon and monitor share two significant flags, \"Order\" and \"Data\", which are stored in the database. Their values are \"True\" or \"False\", where \"True\" means new order or new data, while \"False\" is the opposite case. The interaction between the monitor and daemon is shown in Figure 9.  
The daemon saves the received data in the cloud server's database and updates the shared flag \"Data\" to \"True\" in the database, then checks the \"Order\" flag, so if it is \"True\", then order the agent accordingly. The monitor is a program attached to a monitoring webpage, so when the page is open, the monitor is active, it checks the shared flags, analyzes raw data, and presents the results to the administrator visually, as well as providing a UI for the administrator to control the devices. If some options in the page are triggered by administrator, it updates the corresponding flags in database. For \"Data\", the daemon is publisher, and the monitor is subscriber, but for \"Order\", the roles are exchanged.  
Raw data from the pillow travels via the agent and router and are saved to the cloud database by the daemon process. They are encrypted by a proprietary algorithm in the BT host, not just for security purposes but also to reduce bandwidth. On the Internet they are transferred via HTTPS (Secure Hypertext Transfer Transport Protocol), and they are finally decrypted by the monitor applying the proprietary algorithm. Therefore, the security of the raw data is ensured for best industry practice.  
The \"Order\" flag is designed for proactive monitoring mode, typically, this mode is only applied in the laboratory with the DC power supply connected to the pillow as it drains the battery due to the data refresh rate.
# Automatic Feature Construction-Based Genetic Programming for Degraded Image Classification
## 1 Introduction
To confront the challenges previously mentioned, this research introduces a new program structure based on information transmission and develops a novel function set and terminal set for it. The design of the structure enables nodes in specific layers to transmit the key information they learn to nodes in subsequent layers. This promotes the construction of more effective new features by GP individuals, thereby enhancing their performance as solutions for classification tasks. Furthermore, this research devises an accompanying evolution strategy that enhances population diversity by replacing redundant individuals after stagnation, thereby facilitating the search for superior GP individuals. Moreover, the proposed multi-generational individual ensemble strategy aims to combine several efficient GP individuals to construct an ensemble of GP individuals with enhanced generalization capabilities, serving as an effective solution for classification tasks. The proposed new method is abbreviated as ITACIE-GP. The contributions of this paper lie in the following aspects. 1. Due to the limitations in program structure and node design in existing GP methods, the performance of GP individuals is restricted. To address this, the study develops a new program structure based on information transmission, which is centered on allowing nodes in specific layers to transmit effective information to subsequent layers. Such a design aids GP individuals in constructing distinctive features, thereby enhancing their performance as solutions for classification tasks. 2. To solve the problem of stagnation in fitness growth of the best GP individuals during the iterative process, this study proposes an accompanying evolution strategy. When stagnation in the fitness growth of the best GP individuals is detected, this strategy will guide the population toward exploring in the direction of more optimized GP individuals. 3. To address the potential overfitting issue when using a single GP individual as the solution, this study proposes a multi-generational individual ensemble strategy. This strategy, by combining several efficient GP individuals, constructs an ensemble GP individual with stronger generalization capabilities, effectively reducing the overfitting phenomenon. 4. ITACIE-GP is an effective method suitable for degraded image classification tasks. This method evaluates its performance in original, blurry, low contrast, noisy, and occlusion scenarios for six different types of datasets. It has been compared with several benchmark methods. Moreover, through detailed program examples, this paper delves into the reasons behind the high performance demonstrated by this method. The remainder of this paper is structured as follows. Section 2 introduces the related work. Section 3 presents the proposed ITACIE-GP method. Section 4 details the design of the experiments. Section 5 discusses and analyzes the experimental results, and Section 6 concludes the work.
# Analysis of Recent Deep Learning Techniques for Arabic Handwritten-Text OCR and Post-OCR Correction
## 7 Discussion
### OCR Deep-Learning Works
#### 7.1.3 GANs-Based Works [57; 58; 59; 60]
Therefore, even the accuracy, which is currently not particularly high, could be a case of overfitting, precluding generalization. Lastly, the amount used for fine-tuning the mixture of sets is unknown. Nevertheless, [PERSON] et al. 's work is still notable, as it showed generally good competency in both Arabic and English degraded sets. From the works analyzed above, that the following conclusions can be drawn:  
* GANs works are sensitive to balanced/unbalanced datasets. This is due to the fact that GANs are usually devised as a way to augment data before they are classified using another classifier. The use of GANs is a method to combat the limitations of Arabic datasets. However, the overall performance becomes dependent on the application of another model for classification. In essence, this adds layers of complexity to the model and does not guarantee that it can achieve high accuracy on challenging sets;
* GANs suffer when generating letters with dots, as they can be considered noise;
* GANs works accuracy is mostly inappropriately reported. Overall, the analysis, performance, and drawbacks of deep-learning OCR works are summarized in Table 2. We can conclude from the table and the discussion above that:  
* LSTM-CNN-CTC is the current preferred architecture for Arabic OCR. This is due to the fact that this combination allows the handling of spatial relations, long text dependencies, and their alignments, and it does not require as many data as Transformer and GANs;
* Transformer is the most promising architecture for future works when more annotated and domain-specific data are made available;GANs are usually used to augment datasets, but they are sensitive to the dataset's state of balance. In addition, GANs must be combined with a classifier, which contributes to enhancing the accuracy on one hand and the model's complexity on the other; There is a crucial need for more public handwritten Arabic OCR datasets in terms of quantity, quality, scope, and font diversity in order for OCR research to progress. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
## 2 Method  
### Classical Statistical Techniques  
Classical statistical techniques involve analyzing the statistical properties of the signal to detect changes. One common approach is based on monitoring changes in the mean and  
Figure 1: Change detection in biomedical signals. This figure illustrates the performance of different change detection methods on a synthetic signal. The original signal contains a known anomaly between time points 100 and 150. The classical statistical method uses mean and standard deviation thresholding to identify changes. The Continuous Wavelet Transform (CWT) method analyzes the signal in both time and frequency domains to detect anomalies. The Support Vector Machine (SVM) classifier is trained on the signal to identify changes based on learned patterns. The figure highlights the detected anomalies by each method, demonstrating their effectiveness in identifying different types of changes in biomedical signals.  
variance of the signal. Let \(x(t)\) represent the signal at time \(t\). The mean \(\mu\) and standard deviation \(\sigma\) of the signal can be calculated as follows:  
\[\mu=\frac{1}{N}\sum_{t=1}^{N}x(t) \tag{1}\]  
\[\sigma=\sqrt{\frac{1}{N}\sum_{t=1}^{N}(x(t)-\mu)^{2}} \tag{2}\]  
Once the mean and standard deviation are computed, a change can be detected if the absolute deviation of a data point from the mean exceeds a certain threshold \((\alpha\times\sigma)\), where \(\alpha\) is a user-defined parameter.
## 3 System Model
### Minimum Hop Region (MHR)  
The concept of MHR was originally proposed in [14] as a region defining a set of paths with minimal hops between the source and destination to restrict request messages. Given  
Figure 1: LEO satellite polar constellation.  
the network topology \(G=(V,E)\), MHR is defined by the generated sub-graph \(G^{\prime}=(W,E^{\prime})\). Let us assume that the source satellite ID is \(v_{s_{1},s_{2}}\) and the virtual coordinates are \((s_{1},s_{2})\). The destination satellite ID is \(v_{d_{1},d_{2}}\) and the virtual coordinates are \((d_{1},d_{2})\). In other words, the minimum hop region for packet \(k\) is \(MHR^{k}=\{(v_{s_{1},s_{2}},v_{d_{1},d_{2}})|(v_{s_{1},s_{2}},v_{d_{1},d_{2}}) \in W,v_{s_{1},d_{1}}\in M_{x},v_{s_{2},d_{2}}\in M_{y}\}\), where \(M_{x}\) and \(M_{y}\) denoted the MHR edge. The \(x\)-axis of the MHR edge is \(M_{x}=[x_{\min},x_{\max}]\) with \(x_{\min}=\min\{s_{1},d_{1}\}\) and \(x_{\max}=\max\{s_{1},d_{1}\}\). The \(y\)-axis of the MHR edge is the same as that of the \(x\)-axis. Subsequently, MHR is defined as shown in Figure 2.  
MHR always does not always have a rectangular shape. If the coordinates of either the \(x\)-axis or \(y\)-axis of the source \(v_{s_{1},s_{2}}\) or destination \(v_{d_{1},d_{2}}\) in the graph are the same, then the shape of MHR is a line. If \(s_{1}\) and \(d_{1}\) have the same coordinates, then MHR is along a vertical line in the same orbit. Conversely, if \(s_{2}\) and \(d_{2}\) have the same coordinates, then the MHR is a horizontal line. For the routing path to have the minimum number of hops, a packet must be transmitted within the MHR. But, if MHR has a line shape, no detour paths exist within MHR. In the proposed scheme, to determine the optimal detour point in case of a link failure, the MHR must be of a rectangular shape.  
Therefore, we extend the linear MHR to form a rectangular shape. When the MHR has a vertical line shape in the same orbit, it is extended in the seam-away direction. When the MHR has a horizontal line shape, it is extended toward the pole. Inter-ISL is shorter at high latitudes and the MHR is extended toward the poles. However, if the extended area crosses the polar boundary, the MHR is extended in the opposite direction to maintain the polar boundary.
# Proxy-Based Adaptive Transmission of MP-QUIC in Internet-of-Things Environment
## 4 Performance Analysis by Experimentations
### Analysis of Response Delays  
Figure 3 shows the comparison of response delays from the server to the client of the three candidate schemes for different link delays. The link delays for each path are changed from 10 ms to 50 ms. From the figure, we see that the proposed scheme provides smaller response delays than the two existing schemes. As the link delay gets larger, the response delay tends to increase. The two existing schemes, SP-QUIC (using single path) and MP-QUIC (Round Robin), provide similar and larger response delays than the proposed scheme. This is because the proposed adaptive MP-QUIC scheme can utilize the available link for data transmission adaptively the network conditions. Using the proposed scheme can keep the response delay remains lowest, this can happen when link delayincrease, proxy system migrate the connection using path manager. While another scheme is not concerned with adaptive path changing, the proposed scheme can provide the best path for the proposed MP-QUIC.  
Figure 4 shows the response delays of the three candidate schemes for different packet loss rates in the network, which are ranged from 0% to 15%. In the figure, the response delays tend to increase as the packet loss rate gets larger. We see that the proposed adaptive MP-QUIC transmission scheme provides smaller response delays than the existing SP-QUIC and MP-QUIC schemes. This is because the proposed adaptive scheme can transmit the data packets over the best path among the multiple paths by considering the network conditions, including the packet loss rate. In the figure, we can also see that the performance gaps between the proposed scheme and the existing schemes tend to increase as the packet loss rate gets larger.  
Figure 5 compares the response delays of the candidate scheme for the different sizes of data files transmitted, which are ranged from 128 KB to 1024 KB. From the figure, we see that the proposed scheme provides the best performance among the three candidate schemes for all test instances.  
Figure 4: Comparison of response delays for different packet loss rates.  
Figure 3: Comparison of response delays for different link delays.
# Mechanical Structure Design and Experimental Study of Gamma-ray Monitor for Small Satellite Payload
## 2 Materials and Methods
### Comparison of Traditional and Novel GRM  
The traditional gamma-ray detector with PMT is shown in Figure 1b. Its size and weight are about \(\Phi\)190 mm \(\times\) 300 mm and more than 4 kg, respectively. Comparing with the traditional gamma-ray detector, the novel GRM has the advantages of: compact  
Figure 1: Comparison of the traditional and novel GRM: (**a**) Novel GRM. (**b**) Traditional gamma-ray detector.  
structure, vibration resistance, small size, light weight and no need for high pressure, thus the cost of manufacturing and loading orbit can be reduced.
## 2 Materials and Method
### Procedure  
Prior to the intervention phase, all 18 SLPs received 3 h of training on location at the special daycare centers. They were trained in delivering the vocabulary intervention using the tablet game as well as the real objects. Two SLPs were not able to attend these meetings; therefore, they received the training online via Skype. All SLPs had a tablet with the tablet game used in the intervention pre-installed. During the training, the following topics were addressed: the aim of the study and the study protocol, the test and intervention intervals, the target words chosen for the intervention (Appendix A), and the scripts for the sessions to be used in both conditions (Appendix B). Furthermore, they were instructed how to fill in and return the weekly logbooks and the importance of monitoring treatment fidelity this way. During the training, the SLPs practiced the intervention scripts in both the tablet game and real objects condition during role-play. Much emphasis was given to the prerequisite that the treatments in both conditions had to be as comparable as possible. Naturally, all SLPs are familiar with working with real objects during therapy. In addition, the best practices to deliver vocabulary therapy with tablet games were presented and practiced. The SLPs also received printed material containing the scripts, a list of target words, a roadmap for the treatment sessions, a logbook template, and a hand-out with tips and tricks on how to use tablet games during therapy. These tips and tricks were based on a study investigating the verbal and nonverbal strategies of SLPs working with tablet games in speech and language therapy. A key outcome of this study was that social interaction is crucial, and therefore, a key element of our intervention was that the child and therapist always played the game together [18].
# Advancements in Flame-Retardant Systems for Rigid Polyurethane Foam
## 2 Reactive-Type Flame Retardants
### Incorporation of Sulfur-Containing Groups  
Sulfur-based flame retardants represent an alternative category of reactive flame retardants employed in the manufacture of polyurethane foam. These compounds have the advantages of having a low cost, being effective, and having a low impact on the mechanical properties of the foam. A sulfur-containing polyol was synthesized by [PERSON] et al. [49] to create flame-retardant polyurethane foams with improved compressive strength without affecting the foam morphology or closed cell content. The modified RPUF exhibited a self-extinguishing time that was decreased from 94.0 s to 1.7 s when the phosphorus content reached 1.5 wt.% in contrast to the pristine RPUF.
# Multi-Relational Graph Convolution Network for Service Recommendation in Mashup Development
## 4 Experiments
### Implementation Details  
The details of training and the settings of hyper-parameters are listed as follows:  
* In learning the vector representations of textual descriptions of mashups and services, we aggregate the textual descriptions of all 6300 mashups and 21,474 services into one big corpus, and perform a series of pre-processing steps: (1) Tokenization, which splits sentences into words; (2) Stop-words removal, which remove the insignificant words and infrequent words that appear less than 5 times; (3) Lemmatization, which transform words to their root forms. All pre-processing is done using the _NLTK_ library. After pre-processing, we feed the dataset to the LDA and doc2 vec model in the _gensim_ library. The number of topics \(NK\) in LDA model and the vector size \(ND\) in doc2 vec model are both set to 64. The other parameters are set as the default value of the gensim API. In building the functional and tagging relations, \(\tau_{1}\) is set to 30, and \(\tau_{2}\) is set to 15.
* For each positive mashup-service pair, we sample \(t=3\) negative pairs. In training the GCN model, the initial node features are set as the document representations learned with the doc2 vec model, and the parameters in GCN are initialized from a Gaussian distribution \(\mathcal{N}(0,0.01)\). The batch size is set to 256, the learning rate is set to 0.005, and the \(L_{2}\) regularization term \(\lambda\) is set to \(10^{-4}\). The number of GCN layers \(L\) is set to 2, and in each layer, the feature dimension \(d_{l}\) is set to 64. We stop the training process when NDCG@20 on the test set does not increase for 10 successive epochs.
## 3 Results and Discussion
### Influence of Different Propagation Directions
In addition, the wake for the \"Corotating-Counterclockwise\" traveling wave induces an overall upward vortex street, which is opposite to that in Figure 9. For both clockwise and counterclockwise propagation directions, the TWW is activated at the same time (\(t=1.8\) s), and the initial state of the flow field controlled by the TWW propagating in the two directions is exactly the same. If the clockwise and counterclockwise TWWs are activated at opposite phases of the lift coefficient oscillations, it is expected to obtain a mirror-symmetrical flow field and exactly equal aerodynamic results. The choice of TWW activating phase is an important reason for the slight difference in the aerodynamic statistic values of the circular cylinder with the two different propagation directions of TWW, as shown in Figure 6.
# Biochar for Wastewater Treatment--Conversion Technologies and Applications
## 2 Conventional Thermal Methods for the Conversion of Feedstock into Carbonaceous Materials
### Gasification  
Gasification is a thermochemical process performed by the conversion of biomass or other organic matter, into a gas mixture \"syngas\" (85%) containing H\({}_{2}\), CO, CO\({}_{2}\), and probably small hydrocarbons such as CH\({}_{4}\), a solid char (10%), and a liquid phase \"tar\" (5%) [72]. Tar and char are the undesirable byproducts of the gasification process. The properties of char generated from biomass gasification processes vary widely based on the nature of feedstock, reactor design, gasifying agent, and gasification temperature. In a study performed by [PERSON] et al. [73], the authors reported a low specific surface area (60 g/m\({}^{2}\)) of char produced from gasification of dealcoholized marc of grape at 1200 \({}^{\circ}\)C under air flow, which discourages their application as activated carbon without further activation. However, [PERSON] et al. [74] previously concluded that gasification of pine wood at 800 \({}^{\circ}\)C during 4 h under steam flow enabled the production of good quality activated carbon with a micropore volume of 0.263 cm\({}^{3}\)/g and a surface area of 603 m\({}^{2}\)/g. Equally, [PERSON] et al. [75] tested the capacity of chars produced from gasification of coal and pine and activated with potassium carbonate to adsorb acetaminophen and caffeine from aqueous solutions. The authors reported that the highest porosity development was obtained with the char derived from pine after gasification at 850 \({}^{\circ}\)C under air flow  
Figure 1: The microspheres core-shell structure of hydrochar. Reproduced from reference [61], Copyright (2009), with permission from John Wiley and Sons.  
and activated with potassium carbonate at 800 \({}^{\circ}\)C during 2 h. The produced carbon material exhibited a mass yield of about 35% along with a high surface area of 1500 m\({}^{2}\)/g and adsorption capacities of 434.8 mg/g and 476.2 mg/g toward acetaminophen and caffeine, respectively. Contrary to biochar prepared by pyrolysis that have been extensively explored, fewer studies evaluated the characteristics of char from biomass gasification. Nevertheless, a thorough knowledge of the char properties and its correlation with the gasification technology are crucial in the view of its potential valorization in water and wastewater decontamination.