esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparison of Water Pretreatment Devices for the Measurement of Polar Odorous Compounds
## 3 Results and Discussion
### Odorous Compound Recovery of Water Pretreatment Device
#### 3.3.2 Reproducibility  
The analytical reproducibility of recovery rates for odorous compounds was also measured to investigate the performance of water pretreatment devices. The reproducibility of the compounds was evaluated as the relative standard deviation (RSD) of triplicated experiments. Experimental results are demonstrated in Figure 4. A high RSD value indicates that the concentration of the odorous compound recovered after water vapor removal was not consistent.  
As shown in Figure 4, the Desolvator-K denoted stable reproducibility because RSD was \(\leq\)5.95% for all compounds under all conditions. The Cooler-G showed consistent reproducibility for MEK, MIBK, and BuAc (i.e., RSD \(\leq\) 3.08%), but very unstable reproducibility for i-BuAl (i.e., RSD = 4.44-31.2%). This pattern was similar to that of the Cooler-K. The Cooler-K showed stable reproducibility of less than 5.66% RSD for all compounds except i-BuAl, but the RSD for i-BuAl indicated the fluctuation reproducibility (i.e., RSD = 2.92-8.14%). These phenomena occurred due to the inner shape of the Cooler-G's impinger and the characteristics of i-BuAl, as mentioned in Sections 3.2 and 3.3.1.  
The Desolvator-K consists of a short and straight tube with which water vapor is removed. In contrast, the cooler has an impinger in which a vortex occurs due to flow direction from downward to upward. Therefore, the cooler showed high RSD values because the gas flow was not uniform.  
In the present test method, it was recommended to use the Nafion(r) dryer as a water pretreatment device for the target compounds concerned in this study [6; 8]. Therefore, [PERSON] et al. [31] analyzed the removal of the MEK, i-BuAl, MIBK, and BuAc compounds when using a Nafion(r) dryer as a water pretreatment device. It was reported that recoveries of the four compounds were less than 20% when the Nafion(r) dryer was installed. For more accurate and reliable analysis, the water pretreatment device should be able to selectively remove water vapor that affects sample analysis without influencing analytes. However, the Nafion(r) dryer was not appropriate as a water pretreatment device for the  
Figure 4: Reproducibility of odorous compounds after removing water vapor: (**a**) Desolvator-K; (**b**) Cooler-G; (**c**) Cooler-K.  
MEK, i-BuAl, MIBK and BuAc compounds. Consequently, it was very important to select a suitable water pretreatment device according to the target analyte.
# Network Structure and Synergy Characteristics in the Guangdong-Hong Kong-Macao Greater Bay Area
## 3 Research Data and Methods  
### Overview of the Research Area  
Logistics and capital flows are closely interconnected in modern economies. Efficient logistics accelerates cargo and service turnover, enhances market responsiveness, and reduces transaction costs, thereby attracting capital inflows and fostering regional investment and economic growth [29]. Conversely, robust capital flows support the development and upgrading of logistics infrastructure, providing essential financial backing for the logistics sector. Additionally, the efficiency and security of capital flows are critical for expanding logistics networks and improving accessibility. In the context of deepening globalization and regional integration, the Guangdong-Hong Kong-Macao Greater Bay Area serves as a dynamic economic growth hub, characterized by a complex transportation network and diverse economic connections [30]. Major cities such as Guangzhou, Shenzhen, Hong Kong, and Macau form an integrated system through efficient transport and strong economic ties [31]. The region's logistics system thrives on a highly liquid and innovative capital market, with Hong Kong acting as an international capital center that enables rapid access to global markets for cargo and services [32]. The synergy between logistics and financial technology innovation in the Greater Bay Area enhances the efficiency of both logistics and capital flows, driving industrial upgrading and economic transformation. This interplay allows the Greater Bay Area to maintain its competitive edge and economic vitality in the global landscape.  
The Greater Bay Area, situated along the southern coast of China, is one of the country's most economically developed and open regions. It includes the special administrative regions of Hong Kong and Macao, along with nine cities in the Pearl River Delta of Guangdong Province: Guangzhou, Shenzhen, Zhuhai, Foshan, Huizhou, Dongguan, Zhongshan, Jiangmen, and Zhaoqing, covering approximately 56,000 square kilometers (as shown in Figure 1). Geographically positioned near Southeast Asia and supported by the extensive mainland Chinese market, the Greater Bay Area serves as a crucial hub linking the mainland to international markets. It acts as a vital window for China's global engagement and a frontline for international economic competition. With a diversified industrial structure, well-developed infrastructure, and significant economic influence, the Greater Bay Area holds a prominent position in the global economy [33].
## 3 The Proposed SensorAnt Protocol
### The Energy Model  
Energy consumption in WSN is mainly attributed to the radio system being in active mode. In fact, the energy consumed in the sleep and idle modes are very small compared to the transmit and receive modes. Let sensor node \(x\) have \(N\) bits of packets to transmit or receive during active mode (per unit time). Accordingly, the total energy consumption for \(x\) can be calculated as:  
\[ToEnC(x)=EnC^{Tx}(x)+EnC^{Rx}(x) \tag{1}\]  
where the \(EnC^{Tx}(x)\) and \(EnC^{Rx}(x)\) are the circuit energy consumption for the node \(x\) during the transmission and receiving states respectively. The energy consumed due to transmission \(EnC^{Tx}(x)\) is given by:\[EnC^{Tx}(x)=EnC^{elect}+EnC^{amp} \tag{2}\]  
where \(EnC^{elect}\) is the electronic circuit energy consumed due to the transmitter, which is calculated as:  
\[EnC^{elect^{T}}=EnC^{mx}+EnC^{syn}+EnC^{filt}+EnC^{dac} \tag{3}\]  
where \(EnC^{mx},EnC^{Syn},EnC^{filt}\)_and_\(EnC^{dac}\) are the energy consumption of the mixer, frequency synthesizer, filter and digital to analog converter respectively, and \(EnC^{amp}\), the energy consumed by the power amplifier.  
In the same manner, the energy consumption in the receiving state \(EnC^{Rx}(x)\) is given by:  
\[EnC^{Rx}(x)=EnC^{electR} \tag{4}\]  
where \(EnC^{electR}\) is the electronic circuit energy consumption at receiver and calculated as:  
\[EnC^{electR}=EnC^{mx}+EnC^{syn}+EnC^{filt}+EnC^{lna}+EnC^{ifa}+EnC^{dac} \tag{5}\]  
where \(EnC^{lna},EnC^{ifa}\)and \(EnC^{dac}\) are the energy consumption of the low noise amplifier, the intermediate frequency amplifier and the analog to digital converter respectively.  
Based on Equations (1), (2) and (4), the energy consumption per packet bits \(EnC_{Pkt}(x)\) is given by:  
\[EnC_{Pkt}(x)=ToEnC(x)/N \tag{6}\]
###### Abstract  
In aero engines, noise absorption is realised by acoustic liners, e.g., Helmholtz resonator (HR) liners, which often absorb sound only in a narrow frequency range. Due to developments of new engine generations, an improvement of overall acoustic damping performance and in particular more broadband noise absorption is required. In this paper, a new approach to increase the bandwidth of noise absorption for HR liners is presented. By replacing rigid cell walls in the liner's honeycomb core structure by flexible polymer films, additional acoustic energy is dissipated. A manufacturing technology for square honeycomb cores with partially flexible walls is described. Samples with different flexible wall materials were fabricated and tested. The acoustic measurements show more broadband sound absorption compared to a reference liner with rigid walls due to acoustic-structural interaction. Manufacturing-related parameters are found to have a strong influence on the resulting vibration behaviour of the polymer films, and therefore on the acoustic performance. For future use, detailed investigations to ensure the liner segments compliance with technical, environmental, and life-cycle requirements are needed. However, the results of this study show the potential of this novel liner concept for noise reduction in future aero-engines.  
acoustic liner; broadband noise; Helmholtz resonator; honeycomb sandwich panel +
Footnote †: journal: Applied Physics Letters
## 4 Conclusions, Limitations, and Future Research
Conceptualization, N.C., J.J. and A.Z.-M.; methodology, J.J., N.C. and A.Z.-M.; software, J.J.; validation, J.J., N.C. and A.Z.-M.; formal analysis, J.J.; investigation, [PERSON]; resources, A.Z.-M. and N.C.; data curation, [PERSON]; writing--original draft preparation, [PERSON]; writing--review and editing, J.J., N.C. and A.Z.-M.; visualization, [PERSON]; supervision, N.C. and A.Z.-M.; project administration, J.J., N.C. and A.Z.-M.; funding acquisition, N.C. and A.Z.-M. All authors have read and agreed to the published version of the manuscript. [PERSON] was supported by a University Postgraduate Award from the University of Wollongong, Australia. N.C. was supported by Australian Research Council Discovery Project DP190100180. A.Z.-M was supported by an Australian Research Council Discovery Early Career Research Award (DECRA) DE180100203 and by Discovery Project DP190100180. All authors were additionally supported by NASA ROSES grant 20-OCOST. The coSIF data product for February, April, July, and October 2021 is openly available from Zenodo at: [[https://doi.org/10.5281/zenodo.8078592](https://doi.org/10.5281/zenodo.8078592)]([https://doi.org/10.5281/zenodo.8078592](https://doi.org/10.5281/zenodo.8078592)). The supplementary dataset of fitted model parameters is openly available from Zenodo at: [[https://doi.org/10.5281/zenodo.8078560](https://doi.org/10.5281/zenodo.8078560)]([https://doi.org/10.5281/zenodo.8078560](https://doi.org/10.5281/zenodo.8078560)). The input data presented in this study are collected in a compressed file that is openly available from Zenodo at: [[https://doi.org/10.5281/zenodo.8078476](https://doi.org/10.5281/zenodo.8078476)]([https://doi.org/10.5281/zenodo.8078476](https://doi.org/10.5281/zenodo.8078476)). These input data are a subset of the openly available data in [35; 36; 37]. The code repository can be found at: [[https://github.com/joshhjacobson/coSIF](https://github.com/joshhjacobson/coSIF)]([https://github.com/joshhjacobson/coSIF](https://github.com/joshhjacobson/coSIF)). We are grateful for helpful comments from two referees and the Academic Editor. We thank [PERSON] for his assistance with maintaining the high-performance computing architecture on which the results in this article were produced. We would also like to acknowledge [PERSON] for developing the Scientific Colour Maps package [54], which was used for Figures 3, 6, and A2. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. The following abbreviations are used in this manuscript:  
BIAS  
Average Prediction Error  
CMG  
Climate Modeling Grid  
CO2  
Carbon Dioxide  
DSS  
Dawid-Sebastiani Score  
GES DISC  
Goddard Earth Sciences Data and Information Services Center  
GPP  
Gross Primary Production  
IGBP  
International Geosphere-Biosphere Programme
# _k_-Labelsets Method for Multi-Label ECG Signal Classification Based on SE-ResNet
## 2 Materials and Methods  
### Dataset  
The PTB-XL ECG dataset [19] is composed of open data that can be obtained from the Physionet [32] site managed by the MIT Laboratory for Computational Physiology. The dataset included waveform data collected from October 1989 to June 1996 with a Schiller AG device and was created so that individual patients could not be identified. Waveform data are provided in waveform database (WFDB) format in 100 Hz and 500 Hz, and 100 Hz data were used in this study. The structured data consisted of 21,837 clinical 12-lead ECGs of 18,885 patients. In total, 71 ECG descriptions conforming to SCP-ECG standards, prepared by two cardiologists, have been documented, along with demographic items, such as age, gender, and height. One ECG datum was excluded because the measurement was interrupted in the middle, and a total of 21,836 data were used. Therefore, the format of the input data we used is equal to 21,386 \(\times\) 12 \(\times\) 1000. Diagnosis of ECG data is classified into five superclasses: normal ECG (NORM), myocardial infarction (MI), ST/T change (STTC), conduction disturbance (CD), and Hypertrophy (HYP). This superclass is further subclassed into subclasses, and the description of each class can be found in Table 1[19]. The entire dataset was split into 60:20:20 ratio and used as training (13,101), validation (4367), and test sets (4368), respectively.
# Underwater Accompanying Robot Based on SSDLite Gesture Recognition
## 3 Framework and Methodology
### Image Enhancement  
Due to the effects of absorption and scattering, underwater images have very serious color distortion. Especially when the camera is far away from the target, the longer the path of light propagation, the more serious the color distortion. The attenuation effects are subject to the wavelength of light and usually the images collected in deep water are blue-green, which is due to the red and purple light being completely attenuated. Therefore, it is very important to perform color correction and image restoration for underwater images, which can restore the real scene information.  
Figure 1: Gesture-based control framework.  
The scattering model for the underwater image [32] can be simplified and equated to the following Equation (1):  
\[I_{c}=J_{c}T_{c}^{D}+B_{c}^{\infty}\Big{(}1-T_{c}^{B}\Big{)} \tag{1}\]  
where \(J_{c}\) denotes the recovered image, and \(T_{c}^{D}\) correspond to the direct light transmission map (DLTM), \(B_{c}^{\infty}\) is called the veiling light, which is the background light at infinity under underwater imaging conditions, and \(T_{c}^{B}\) represents the back scattered light transmission map (BLTM). The recovered image can thus be calculated using Equation (2).  
\[J_{c}=\frac{I_{c}-B_{c}^{\infty}\big{(}1-T_{c}^{B}\big{)}}{T_{c}^{D}} \tag{2}\]  
In our project, to obtain the recovery image \(J_{c}\), we need to know \(T_{c}^{D}\), \(T_{c}^{B}\) and \(B_{c}^{\infty}\), but it is difficult to obtain these parameters from a single image. For this purpose, we propose a neural network structure estimation network, as shown in Figure 2, consisting mainly of an encoder and four decoders to estimate the parameters \(J_{c}\), \(T_{c}^{D}\), \(T_{c}^{B}\), and \(B_{c}^{\infty}\) in the scattering model. The encoder is improved based on DenseNet [33], which aims to extract multiple scale features of the underwater images as input to the decoder. The four decoders have roughly the same structure and are responsible for estimating different imaging parameters. Among them, \(DecoderT_{c}^{D}\) is responsible for estimating DLTM, \(DecoderT_{c}^{B}\) is responsible for estimating BLTM, and \(DecoderB_{c}^{\infty}\) is responsible for estimating veiling light. \(DecoderJ_{c}\) is a bootstrap decoder that we designed to guide the network training to improve the performance. When an underwater image is input, the parameters \(T_{c}^{D}\), \(T_{c}^{B}\), and \(B_{c}^{\infty}\) in the scattering model are estimated by the network, and then the underwater recovery image \(J_{c}\) can be obtained by Equation (2).
## 4 Verification
### Simulation Validation Utilizing Authentic PMU Data  
To conclusively assess the effectiveness of the fitting-based ERA method in identifying various parameters of synchrophasors under SSO, simulation analysis was conducted, leveraging authentic PMU recordings gathered during a real SSO event within the North China Power Grid's operational environment [17].  
The real-time current signal and the magnitudes of the synchrophasor quantities, as derived from the authentic PMU measurements, are illustrated in Figure 2.  
As depicted in Figure 2, the targeted 6 s data window, functioning as the cornerstone of our simulation and grounded in authentic PMU recordings, revealed exceptionally swift fluctuations in SSO activity. This rapid fluctuation reflects the complexity of the dynamic behavior in relation to the energy grid, posing challenges for monitoring and analyzing system stability.  
Figure 2: Instantaneous current signal and synchrophasor amplitudes for authentic PMU data. (**a**) Instantaneous currents. (**b**) Amplitudes of synchrophasors.  
In this paper, the presented fitting-based ERA approach identified a 200 ms data segment for analysis. Additionally, a DFT algorithm utilizing interpolation and employing a 2 s data frame for processing was implemented, theoretically offering higher accuracy in its identification results. Therefore, the identification results from a DFT algorithm utilizing interpolation and employing a 2 s data frame were used as a reference benchmark for assessing the identification accuracy of other algorithms. Furthermore, the identification results of the SSO parameters using the existing ERA method with a data window length of 1 s were also compared.  
Using the three approaches, the recognition outcomes of the synchrophasor parameters under SSO are presented in Figure 3. Gradient fill points resulted from the introduced algorithm, with blue and rose red representing the start and end times, respectively. Given that the subsynchronous and supersynchronous elements formed a coupled pair, the precision of identifying the supersynchronous element could be roughly mirrored by the outcomes of recognizing the subsynchronous counterpart. Consequently, the results pertaining to the supersynchronous element's identification are excluded from further discussion.
# Individuals Identification Based on Palm Vein Matching under a Parallel Environment
## 2 Related Works
### Palm Vein Recognition
The image quality is usually solved using visual improvement techniques such as histogram equalization [38; 53]. Regarding the vein image deformations, the work of [45] should be highlighted, which introduces a new perspective to deal with the problem of deformations for finger-vein recognition. Their contribution is different from other works that try to reduce the influence of deformations by implementing a more precise segmentation of ROI [53], or using a more robust feature extraction [27; 30], among others. The features obtained at the pixel level in [45] are based on the observation that the displacement of pixels generated in the matching process, due to the deformations of vein images, are convenient as discriminatory information. Understanding the ideas introduced by [PERSON] et al. [45], the information that allows for distinguishing a correspondence of images between genuine and imposter matching is based on two principles--see Figure 3: (1) the displacement of a pixel and its neighbors are similar because the pixels in a local region tend to be similar in deformations; (2) the number of pixels that have the same displacement tends to be larger in genuine matching because two similar images share the same vein structure. For these reasons, the displacement at the pixel level is obtained by treating the correspondence process as an optimization problem based on the proposal of [48]. Thus, the displacement matrices are generated from the dense correspondences of SIFT descriptors [54], from which the feature of uniformity texture [47] is extracted being the final degree of similarity. This new perspective solves the problem of deformations and avoids the segmentation of blood vessel structures for finger-vein recognition. In addition, the recognition method used is more robust and much more discriminatory than traditional approaches. Our proposal aims to prove these principles are also met for palm vein recognition, but we use a sparse matching algorithm which is more efficient than dense correspondences using SIFT proposed in [45]. To the best of our knowledge, the method we present is the first that aims to reduce the influence of deformations by using it as discriminative information for palm vein recognition. At the same time, our approach reduces the execution time of the matching process of palm vein images being able to use in individual massive identification. Our experimental results show that a higher speed-up is obtained by combining the effectiveness and efficiency of a sparse matching algorithm with a multi-core parallel implementation. Figure 3: Comparison of displacements for genuine and imposter matching, image from [45]. (**a**) genuine matching: the displacements tend to be similar in length and direction for matched pixels; (**b**) imposter matching: the displacements vary in distance and in various directions for matched pixels.
# Research Progress Regarding the Precision of Dosing and Distribution Devices for Fertilizers
## 2 Current Status of Research on Precision Fertilizer Dischargers  
In recent years, there has been continuous research on precision fertilizer dischargers around the world. There are four main types of fertilizer discharges: spiral fertilizer dischargers, groove wheel fertilizer dischargers, disc fertilizer dischargers, and air-feed fertilizer dischargers. In order to achieve precise fertilizer dosing and distribution, researchers conducted in-depth research.
# Optimized Architecture for Efficient OFDMA Network Design
## 4 Validation and Robustness Study of the Analytical Model
### System Parameters  
* A single WiMAX cell will be considered, with a focus on studying the downlink.
* The number of slots is determined by factors such as the system's bandwidth, frame duration, downlink/uplink ratio, subcarrier permutation (PUSC, FUSC, AMC), and protocol overhead (including preamble, FCH, and maps).
* The system's bandwidth is set at _10 MHz_.
* The frame duration for the TDD WiMAX network is assumed to be _5 ms_, with a downlink/uplink ratio of _2/3_.
* For simplicity, the protocol overhead is assumed to have a fixed length of two symbols, although, in practice, it varies depending on the number of users.
* Based on these parameters, the total number of data slots available per downlink amounts to _450_.