esa-sceva/satcom-chunk-collection huggingface dataset:
# Detection of Volatile Organic Compounds (VOCs) in Livestock Houses Based on Electronic Nose
## 3 Results and Discuss
### Response Analysis of Electronic Nose Sensor Array  
The electronic nose can obtain the overall information of the sample smells, and the subtle differences in volatile compounds affect the response of the sensor array. From the collected gas samples, we conducted a total of 244 electronic nose tests for the pig houses and 110 electronic nose tests for the chicken houses, as shown in Tables 2 and 3. Figure 4 shows the sensor's response to six odor sources. The bar graph amplitude is the average and standard deviation of the maximum voltage (Vmax) calculated from the electronic nose test for all odor samples test at each sampling location. The TGS2602 sensor was used to detect ammonia, hydrogen sulfide, and volatile organic compounds. It can be seen from Figure 4 that TGS2602 had a high average in response to samples; this is because there is  
Figure 2: The response curve of electronic nose sensors.  
more hydrogen sulfide and ammonia in the pig house and chicken house. The response of TGS2602 in the chicken house was larger than that in the pig house, which indicated that the ammonia and hydrogen sulfide content in the chicken house was larger than that in the pig house. The results of this study were consistent with that of _[PERSON]_[27]. The TGS2603 sensor was the second most sensitive sensor in the pregnant pig house, while the TGS2602 sensor was the second most sensitive sensor in the nursery pig house. Among them, TGS2603 was highly sensitive to amine series and sulfur-containing odors, while TGS2602 was more sensitive to organic solvents, which indicated that there were differences in odor components between the two houses, and the main VOCs were different, which is related to the pig age and feeding methods.  
Figure 3: Types and relative percentage of volatile organic compounds determined by gas chromatography–mass spectrometry (GC–MS): (**a**) nursery-middle-morning; (**b**) nursery-middle-afternoon; (**c**) nursery-window-afternoon; (**d**) chicken-middle-morning; (**e**) chicken-middle-afternoon; (**f**) chicken-window-afternoon.
# Real-Time Communication Aid System for Korean Dysarthrie Speech
## 3 Proposed Real-Time Communication Aid System for Korean Dysarthric Speech  
In order to overcome the shortcomings of [10], which lacks real-time processing of various speech, this study proposes a system that can recognize the user's speech as a whole sentence and process it in real-time. By doing so, we aim to expand the communication range of dysarthria and create an environment where natural dialogue is possible in real-time. In addition, to overcome the low computational efficiency of the model structure used in [27] and the processing problem for long sequences, we use the conformer structure. The conformer is optimized for processing temporal sequences such as speech data, and it improves computational efficiency and enhances the learning of local (short-range) patterns in the input speech data. By doing so, we aim to improve the performance of the improved model on the same dataset compared to the existing model.  
Figure 2 illustrates the overall architecture of the real-time communication aid system proposed in this study. The core components of the proposed system include the following:  
1. ASR model for Korean dysarthric speech recognition: this model processes speech input from individuals with dysarthria, identifying and converting it into textual information.
2. TTS model for normal speech synthesis: based on the recognized text, this model generates high-quality non-dysarthric speech, making the output more natural and intelligible for effective communication.  
The developed ASR and TTS models are integrated through a web server to ensure seamless operation. The system processes a single speech input and produces a single speech output in real-time, aiming to provide a practical and efficient solution for assisting individuals with dysarthria in various communication scenarios.  
The flow of the entire system starts with the dysarthric speech input captured via a microphone. To process the input speech signal, the ASR and TTS models are modularized by loading the weights and parameters of each model, enabling them to make predictions for a single input on the web server. The ASR and TTS modules are integrated into the web server using the Flask framework of Python3.9. The ASR model processes the captured speech to generate a text output, which is then immediately passed as input to the TTS model. Through this integration, the input dysarthric speech is directly transformed into clear non-dysarthric speech on the web server. As a result, users can inter  
Figure 1: Flowchart of the existing state-of-the-art Korean dysarthric ASR model.  
act more smoothly with others in social communication situations using the synthesized non-dysarthic normal speech.
## 1 Introduction
As shown in Figure 1, the capsule can be expanded through injecting the cement paste into it, and the resulting displacement of the soil will act on the deformed pile foundation, thereby reducing the pile deformation. Figure 1: Schematic of capsule grouting expansion technology controlling pile deformation. Capsule grouting expansion technology has been used in some engineering applications, with several field tests conducted to investigate its working mechanism [25]. However, there is a lack of theoretical research on capsule grouting expansion technology, warranting further investigation. The theoretical calculation method offers the advantages of a clear force mechanism and requires less time for calculation. Therefore, it is essential to analyze the control effect of capsule grouting expansion technology on the deformation of piles through theoretical research. In the theoretical calculations, the \"two-stage\" method is typically adopted [26; 27; 28]. Initially, the displacement field or stress field of soil is determined, disregarding the existence of pile foundations. Subsequently, the displacement field or stress field is applied to the neighboring pile foundation to obtain the force response of the pile foundation.
# Analytical Solution for the Problem of Point Location in Arbitrary Planar Domains
## 2 Related Work
### Background and Scope of This Paper  
This paper demonstrates and gives implementations of a unified approach that covers the traditional solutions based on ray-crossing or winding numbers, solves the cases where those algorithms may find limitations or ambiguities, and extends and demonstrates a practical, viable solution for generic contours that can be expressed in a parametric form, which is its major novelty.  
In the early 1990's, information was not so easy to obtain or track, and faced with the need, the author proposed, during his Ph.D. Thesis [25], an approach for the problem of point location in polygons based on the Cauchy and Residue theorems, which is closely related to the winding number approach, although unfamiliar at the time.  
The algorithm operates by explicitly evaluating contour integrals in the complex plane of a specially chosen function. The solution, found by accidental simplification (it was not fully demonstrated then), proved to work well with a very simple and elegant mathematical formulation. Only later, when formal full mathematical demonstrations were needed, was the current solution developed, as presented in this paper. Hence, it can be said that the solution came to be after the usage of the Cauchy and Residue theorems, but it later became as it it now in its present state. The next sections describe in detail the foundations of the technique, including algorithmic implementations, followed by illustrative results and conclusions.  
Code for this research and demonstrations of the algorithms described in the remainder of this paper are publicly available in a GitHub repository ([[https://github.com/vitoruapt/PointInclusion](https://github.com/vitoruapt/PointInclusion)]([https://github.com/vitoruapt/PointInclusion](https://github.com/vitoruapt/PointInclusion)) (accessed on 2 October 2024)).
## 3 Results and Discussion
### THz Absorption Spectroscopy Measurements
So, although single measurements performed with the pyroelectric receiver have an SNR that is worse by approximately a factor of 10 compared to the SNR of single measurements performed with the bolometer, the SNRs of absorption spectra recorded with the same measurement time differ by only a factor of 2. We note here that purging can additionally improve the SNR by a factor of 3 to 4, depending on the humidity level. Also a low-pass filter with a cut-off frequency of 10 kHz or smoothing filters could be used to digitally remove noise from the signal. Based on the standard deviation of the noise given in Figure 7, the lowest detectable density of NH\({}_{3}\) can be calculated as the density that would correspond to an absorption profile with a peak value of three times the standard deviation of the noise. For example, for a total measurement time of 10 s, the resulting detection limits are \(4\times 10^{14}\) cm\({}^{-3}\) and \(2\times 10^{14}\) cm\({}^{-3}\), corresponding to a pressure of 0.016 mbar and 0.008 mbar for the pyroelectric receiver and the bolometer, respectively. These values are valid for the used configuration only (see Figure 2a) and should be considered as rough estimates of the detection limits as the exact values depend on the humidity level, optical alignment, and other factors with an influence on the signal intensity.
## 5 Conclusions  
The essence of remote sensing time series reconstruction is to repair missing values by exploring and using relevant time series data. Traditional time series reconstruction methods commonly have over-smoothing and under-fitting deficiencies, and traditional reconstruction function-based models are too simple to reflect complex time series variations. Certainly, a complex model with many more parameters definitely fits data better than a simple model, but simply increasing the number of parameters is not effective. The CCTM model with 6 parameters is constructed based on the second-order derivative theorem and this is why its reconstruction precision is higher than the Harmonic model with 8 parameters. In general, the CCTM model can comprehensively reflect the complex characteristics of time series variation and embody seasonal characteristics.  
Compared to the Exp, Ln, and harmonic models, the CCTM model has lower fitting errors. In the reconstruction of GPP and MSR time series with a smoothing process, >95% of time series points (except the EBF type) had \(R^{2}\)-values >0.9 and RMSEs < 2 g C m\({}^{-2}\) and 0.025, respectively by using the CCTM model. For NDVI reconstruction after smoothing, >95% of time series points had \(R^{2}\)-values >0.9 and RMSEs < 0.01 (except for the ENF and MF types) using the CCTM model. The CCTM model had the fewest extreme fitting errors but also has its limitations. Because the TP and LST time-series datasets contain too many frequent fluctuations, none of the models is suitable for their reconstruction.  
Developing high-precision models can improve the precision of time series reconstruction and be beneficial in obtaining accurate knowledge of the variations in the time series dataset. Besides, the CCTM model is supposed to be applied to time series change detection, trend analysis, extraction of phenology and seasonal characteristics, time-series image compression, and land cover classification.  
Methodology, Y.Z., and L.W. ([PERSON]); software, Y.Z., Y.H. and F.T.; validation, Y.Z.; formal analysis, Y.Z., F.T. and Q.Z.; investigation, Y.Z.; resources, Y.Z. and L.W. ([PERSON]); data curation, Y.Z.; writing--original draft preparation, Y.Z.; writing--review and editing, Y.Z., L.W. ([PERSON]), Y.H., N.H., W.L., S.X., Q.Z., W.S., W.D., X.W., S.M., B.N., L.Z., F.T., H.D., L.W. ([PERSON]) and Z.N.; supervision, L.W. ([PERSON]); project administration, L.W. ([PERSON]); funding acquisition, L.W. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDA19030404 to [PERSON]), the National Natural Science Foundation of China (grant 41871347 to [PERSON]), and the Youth Innovation Promotion Association Chinese Academy of Sciences (grant 2018084 to [PERSON]).  
All the time series data are available from the Earth Engine Data Catalog.  
Thanks to people who have also contributed to this article.  
The authors declare no conflict of interest.
## 8 Implementation and Discussion
### Discussion
#### 8.1.2 Anticipated Data Throughput and Query Frequency  
Hypothesized data throughput and the frequency of queries in a BFS system are expected to be high, particularly for real-time financial reporting and auditing purposes. These can be anticipated based on typical usage patterns observed in blockchain implementations:  
* Transaction processing throughput in comparative blockchain systems can range from a few transactions per second (TPS) to tens of TPS depending on the underlying blockchain technology and network configuration. Advanced platforms such as Corda, designed for high throughput and low latency, are known for high TPS.
* The frequency of queries for accounting data and reports may be frequent, especially during peak periods such as financial audits, regulatory reporting deadlines, and end-of-quarter financial reviews. The frequency of queries can range from a few per day for small businesses to several hundred per day for larger enterprises, and the BFS system's capabilities should be optimised in future research efforts to accommodate these demands.
* The BFS architecture prioritises overall performance, ensuring that querying is not hindered. By leveraging off-ledger storage for accounting ledgers, the most frequently accessed data, the BFS system maintains high performance by supporting the frequent implementation of the \"funds verification consensus\" model.
# Human Pose Detection for Robotic-Assisted and Rehabilitation Environments
## 3 Materials and Methods
#### Cameras Calibration  
In order to compare the different pose estimation methods, all 3 cameras need to be calibrated in a common coordinate system. Calibration of the cameras was performed using the OpenCV multiple cameras calibration package [35]. A checkerboard pattern with known dimensions is shown so that at least two cameras can identify it at the same time. To obtain the ground truth, information of the extrinsic parameters of the cameras (translation and rotation matrix) is required, then a 3D-to-2D projection must be made in the image plane to be able to compare with the information provided from OpenPose or Detectron 2 (see Equations (1) and (2)). The acquisition and processing scheme of the data is shown in Figure 2.  
\[\left[\begin{array}{c}X_{\text{{C}K1}}\\ Y_{\text{{C}K1}}\\ Z_{\text{{C}K1}}\end{array}\right]=R\left[\begin{array}{c}X_{\text{{C}K1}}\\ Y_{\text{{C}K1}}\\ Z_{\text{{K}1}}\end{array}\right]+\ T \tag{1}\]  
\[u=\left(\frac{x}{z}\right)*f_{x}+c_{x}v=\left(\frac{y}{z}\right)*f_{y}+c_{y} \tag{2}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Server-Client** & **Client 2** & **Client 3** \\ \hline OS & Ubuntu 18.04.03 Desktop (64 bit), (Canonical, London, UK) & Windows 10 Pro (64 bit), (Microsoft, Albuquerque, NM, USA) & Windows 10 Pro (64 bit) \\ Processor & Intel® CoreTM i7-9750, (Intel, Santa Clara, CA, USA) & Intel® CoreTM i5-8250U & Intel® CoreTM i7-4700 MQ \\ Memory & 16 GB & 16 GB & 16 GB \\ GPU & NVIDIA GeForce GTX 1650 GDDR5 @4 GB (128 bits), (NVIDIA, Santa Clara, CA, USA) & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Hardware setup of our system.  
Figure 1: An overview of the proposed system.  
where (\(X_{\text{K1}}\), \(Y_{\text{K1}}\), \(Z_{\text{K1}}\)) are the coordinates of a 3D point in the coordinate system of the Kinect 1 (IR camera), (\(X_{\text{c}K1}\), \(Y_{\text{c}K1}\), \(Z_{\text{c}K1}\)) are the coordinates of a 3D point calculated from the Kinect 1, \(T\) is the transfer vector, \(R\) is the rotation matrix, (\(u\), \(v\)) are the coordinates of the projection point in pixels, (\(cx\), \(cy\)) is the image center (IR camera), and (\(fx\), \(fy\)) are the focal lengths expressed in pixel units (IR camera).
# A Shearlets-Based Method for Rain Removal from Single Images
###### Abstract  
This work focuses on the problem of rain removal from a single image. The directional multilevel system, Shearlets, is used to describe the intrinsic directional and structure sparse priors of rain streaks and the background layer. In this paper, a Shearlets-based convex rain removal model is proposed, which involves three sparse regularizers: including the sparse regularizer of rain streaks and two sparse regularizers of the Shearlets transform of background layer in the rain drops' direction and the Shearlets transform of rain streaks in the perpendicular direction. The split Bregman algorithm is utilized to solve the proposed convex optimization model, which ensures the global optimal solution. Comparison tests with three state-of-the-art methods are implemented on synthetic and real rainy images, which suggests that the proposed method is efficient both in rain removal and details preservation of the background layer.  
Keywords:rain removal; shearlets; split Bregman algorithm +
Footnote †: journal: Applied Sciences
###### Abstract  
This study starts from the physical perspective of electromagnetic wave propagation in ionosphere media, and the skywave OTH (over-the-horizon) ionosphere channel model is established for hypersonic vehicles based on the ray-tracing method, and this study identifies the key parameters influencing channel characteristics. Secondly, using the re-entry trajectory of the RAM C-II flight experiment as an example, dynamic multipath channel characteristic parameters--such as loss, delay, and Doppler shift--are analyzed in multiple seasons during the noon and midnight periods at a communication frequency of 14 MHz. The results indicate that the settling effect of the ionosphere at midnight makes the changes in the channel more complex, with the irregular sudden appearance and disappearance of multipath numbers. In addition, channel loss is greater in low-elevation propagation mode than in high-elevation propagation mode, indicating that the channel multipath exhibits high loss and low delay characteristics. The skywave communication channel model for hypersonic vehicles, and the dynamic multipath channel characteristic parameters presented in this study offer valuable support for the design, development, and evaluation of long-distance TT&C (Tracking, Telemetering, and Command) communication systems.  
Keywords:skywave; OTH; electromagnetic propagation; hypersonic vehicle; channel characteristics +
Footnote †: journal: remote sensing
## 3 Challenges for Routing Protocols in FANETs
### Energy Efficiency  
Battery-powered UAVs have limited energy to retransmit packets in the event of a route failure, and to execute routing tasks such as route discovery, updates, and mainte  
Figure 19: Challenges for FANETs routing protocol.  
nance. Furthermore, because of the relatively high distance between UAVs, UAV energy is normally utilized to support a long transmission range, which can quickly drain the limited battery capacity. As a consequence, UAVs consume a lot of energy [84]. UAVs must preserve energy to support lengthy flight times because energy availability influences route lifetime [85]. The number of UAVs required to meet network performance criteria, such as throughput and packet delivery ratio, is also considered to minimize energy consumption.
# Tokens Shuffling Approach for Privacy, Security, and Reliability in IoHT under a Pandemic
## 3 Proposed Approach (TSA)
### Algorithm of TSA
In Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 9-12 December 2019; pp. 4017-4024. * (27) [PERSON]; [PERSON]; [PERSON]; [PERSON] Privacy-preserving federated learning based on multi-key homomorphic encryption. _Int. J. Intell. Syst._**2022**, _37_, 5880-5901. [CrossRef]* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] Security and privacy on blockchain. _ACM Comput. Surv. CSUR_**2019**, _52_, 1-34. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Data query mechanism based on hash computing power of blockchain in internet of things. _Sensors_**2019**, _20_, 207. [CrossRef] [PubMed]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A double obfuscation approach for protecting the privacy of IoT location based applications. _IEEE Access_**2020**, \(8\), 129415-129431. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Enhancing privacy through caching in location-based services. In Proceedings of the 2015 IEEE Conference on Computer Communications (INFOCOM), Hong Kong, China, 26 April-1 May 2015; pp. 1017-1025. * [PERSON] et al. (2020) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] Pseudonym change-based privacy-preserving schemes in vehicular ad-hoc networks: A survey. _J. Inf. Secur. Appl._**2020**, _55_, 102618. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] An innovative method for preserving privacy in Internet of Things. _Sensors_**2019**, _19_, 3355. [CrossRef]
* [PERSON] (2022) [PERSON] Anonymous Trajectory Method for Indoor Users for Privacy Protection. In _International Conference on Computational Science and Its Applications_; Springer: Cham, Switzerland, 2022; pp. 104-112. * [PERSON] et al. (2021) [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] PAPIR: Privacy-aware personalized information retrieval. _J. Ambient. Intell. Humaniz. Comput._**2021**, _12_, 9891-9907. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON] Security and Privacy of Blockchain-Based Single-Bit Cache Memory Architecture for IoT Systems. _IEEE Access_**2022**, _10_, 35273-35286. [CrossRef]
* [PERSON] and [PERSON] (2020) [PERSON]; [PERSON] A new method with swapping of peers and fogs to protect user privacy in IoT applications. _IEEE Access_**2020**, \(8\), 210206-210224. [CrossRef]
* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] A survey on differential privacy for unstructured data content. _ACM Comput. Surv. CSUR_**2022**, _54_, 1-28. [CrossRef]

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.