esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experiments and Results
### Mask Generator
#### 3.1.2 Experiments
\begin{table}
\begin{tabular}{c c c c c} \hline \(\mathbf{\lambda_{1}}\) & \(\mathbf{\lambda_{2}}\) & \(\mathbf{n}\) & \(\mathbf{mIoU}\) & \(\mathbf{F}\)**-Score** \\ \hline
0.1 & 0.9 & 3 & 54.5 & 0.565 \\
0.1 & 0.9 & 4 & 42.4 & 0.435 \\
0.1 & 0.9 & 5 & 41.3 & 0.364 \\
0.5 & 0.5 & 3 & 32.4 & 0.367 \\
0.9 & 0.1 & 3 & 19.2 & 0.238 \\ \hline \end{tabular}
\end{table} 
Table 2: Parameters of the mask-scoring mechanism. \begin{table}
\begin{tabular}{c c c} \hline  & \(\mathbf{mIoU}\) & \(\mathbf{F}\)**-Score** \\ \hline \(Fastsam\) & 41.7 & 0.526 \\ \(Fastsam+scoring\)\(mechanism\) & 54.5 & 0.565 \\ \(TPAVI-R50\) & 72.6 & 0.482 \\ \(SAM\)\(zero-shot\) & 51.8 & 0.626 \\ \(AV-SAM\)[14] & 40.5 & 0.568 \\ \(AL-Ref-SAM2\)[16] & 70.5 & 0.811 \\ \hline \end{tabular}
\end{table} 
Table 3: Comparison experiments. (3) Visualization and case study  
To verify the effectiveness of the proposed method, the typical segmentation results obtained during testing were plotted and compared with the labeled mask maps provided by the dataset. In Figure 5, it is evident that the mask generator effectively produces the target mask in the image based on audio prompts. Although the output accuracy is slightly lower compared to that with the real mask, the performance remains within an acceptable range. As a result, the proposed mask generator provides a concise and efficient solution for the practical implementation of audio-visual segmentation tasks, eliminating the need for additional model training and significantly reducing computational costs.
# Performance Analysis of Dual-Hop Hybrid RF-UOWC NOMA Systems
## 3 Outage Probability Analysis
### System Outage Probability \(Op_{\text{sys}}\)  
The total system outage \(OP_{\text{sys}}\) occurs if \(R\) or \(D_{2}\) fails to decode any of the two messages or \(D_{1}\) fails to decode \(x_{1}\). It is formulated as  
\[\begin{split} OP_{\text{sys}}&=1-Pr(\gamma_{R}^{1}>\gamma _{1},\gamma_{R}^{2}>\gamma_{2},\gamma_{D2}^{1}>\gamma_{1},\gamma_{D2}^{2}> \gamma_{2},\gamma_{D1}^{1}>\gamma_{1})\\ &\overset{(c)}{=}1-Pr(|h_{w}|^{2}>\frac{\tau_{1}}{\rho_{g}d^{- \eta}},|h_{w}|^{2}>\frac{\tau_{2}}{\rho_{g}d^{-\eta}})\\ &\quad\times Pr(|h_{2}|^{2}>\frac{\beta_{1}}{\rho_{R}},|h_{2}|^{2}> \frac{\beta_{2}}{\rho_{R}})\times Pr(|h_{1}|^{2}>\frac{\beta_{1}}{\rho_{R}}) \\ &=1-Pr(|h_{w}|^{2}>\frac{\tau}{\rho_{g}d^{-\eta}})\times Pr(|h_{2}|^{2}> \frac{\beta}{\rho_{R}})\times Pr(|h_{1}|^{2}>\frac{\beta_{1}}{\rho_{R}}),\end{split} \tag{8}\]  
where \((c)\) stems from the independence between \(h_{w}\), \(h_{1}\), and \(h_{2}\). With the aid of CDFs in (1) and (3), we obtain a closed-form expression of \(OP_{2}\) as in (9).  
\[\begin{split} OP_{\text{sys}}&=1-e^{\frac{-\tau}{ \rho_{g}d^{-\eta}}}\Bigg{(}1-wG_{1,2}^{1,1}\Bigg{(}\frac{1}{\lambda}(\frac{ \beta}{\rho_{R}\mu_{r}})^{\frac{1}{r}}\mid\begin{array}{c}1\\ 1,0\end{array}\Bigg{)}-\frac{1-w}{\Gamma(a)}G_{1,2}^{1,1}\Bigg{(}\frac{1}{b^{ \varepsilon}}(\frac{\beta}{\rho_{R}h_{r}})^{\frac{\varepsilon}{r}}\mid \begin{array}{c}1\\ a,0\end{array}\Bigg{)}\Bigg{)}\\ &\quad\times\Bigg{(}1-wG_{1,2}^{1,1}\Bigg{(}\frac{1}{\lambda}(\frac{ \beta_{1}}{\rho_{R}\mu_{r}})^{\frac{1}{r}}\mid\begin{array}{c}1\\ 1,0\end{array}\Bigg{)}-\frac{1-w}{\Gamma(a)}G_{1,2}^{1,1}\Bigg{(}\frac{1}{b^{ \varepsilon}}(\frac{\beta_{1}}{\rho_{R}h_{r}})^{\frac{\varepsilon}{r}}\mid \begin{array}{c}1\\ a,0\end{array}\Bigg{)}\Bigg{)}.\end{split} \tag{9}\]
## 3 Considering the ALS Workflow and Its Impact on the Efficacy of Data Products
### Planning and Data Collection  
During the survey planning phase the archaeologist should provide significant input, as the survey should be tailored to try to best answer the scientific research questions. Also the archaeologist has key local knowledge that can contribute significantly during the data collection phase. Knowledge that includes the local weather and vegetation growth patterns (which determine ideal collection time frame); and safe and secure potential sites to place GNSS (Global Navigation Satellite System) reference base stations with available infrastructure (e.g., power and Internet).
# ARMONIA: A Unified Access and Metro Network Architecture
## 5 Conclusions  
In this work, we presented a self-configured and unified access and metro network architecture, called ARMONIA. In ARMONIA, the optical and the IP equipment used in the different network segments are jointly and efficiently controlled. The control of ARMONIA's converged segments is performed through an SDN-based resource orchestration framework. Additionally, a hierarchical monitoring plane based on enhanced telemetry agents provides the required monitoring information. ARMONIA leverages dynamic optimization algorithms that adapt and optimize the unified network. We demonstrated the merits of the proposed architecture through simulation experiments of a dynamic slicing allocation scenario. ML algorithms were used to provide accurate predictions (QoT metrics and traffic volume), helping reduce the resource provisioning margins. Our simulation results indicate savings up to 15% in transponders, 11% in spectrum, and 20% in processing utilization, for the examined scenarios. Future work includes the application of the traffic prediction algorithms in different timeframes (during a day or week) to make the resource allocation even more efficient. Also, we plan to extend the ML QoT estimator, leveraging a physical layer model that takes into account the behavior of certain equipment (amplifiers, filters), providing even more accurate QoT estimation.  
All authors have contributed in all parts of this work. All authors have read and agreed to the published version of the manuscript.  
This research has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (ARMONIA, project code: T1 EDK-05061).  
The authors declare no conflict of interest.
# An Efficient Hybrid Model for Patient-Independent Seizure Prediction Using Deep Learning
## 2 Materials and Methods
### EEG Signal Segmentation Phase  
After noise removal in all channels for each patient, the following segments were extracted:  
1. Pre-ictal phase segment (with window = k), which represents the window of signal that happens just before the ictal phase and which could be used as an alarm to take precautions by caregivers.
2. Inter-ictal phase segment (with window = k), which represents the normal signal where the patient is in normal state.  
The 'k' value was tested with different values to study the effect of the segmentation of the signal. First k was equal to 8 minutes for both the pre-ictal and inter-ictal phases. Furthermore, the window extracted was segmented to equally lengthen the windows of L length, where L was chosen to be 10 s and 30 s. Both overlapping and non-overlapping windows were considered in the segmentation phase.  
Figure 5 shows the channel signal after extracting the inter-ictal phase, where k = 8 min.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Wavelet** & **SNR** & **RMSE** \\ \hline 'Daub4\({}^{\prime}\) & 55.12 & 0.0036 \\ 'Daub6\({}^{\prime}\) & 55.46 & 0.0035 \\ 'Daub8’ & 53.43 & 0.0040 \\ 'Daub12\({}^{\prime}\) & 56.189 & 0.0034 \\ 'DMeyer\({}^{\prime}\) & 55.578 & 0.0035 \\ 'Symlet9’ & 53.80 & 0.0038 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Performance comparison of different wavelet families, applied to EEG channels, in terms of signal-to-noise ratio (SNR), and root mean square error (RMSE).  
Figure 4: White Gaussian noise percentage vs. average accuracy over SVM, RF, KNN and bagging classifier.
###### Abstract
Furthermore, in the pursuit of eradicating T/O compounds from freshwater systems, it is paramount to discern the temporal and spatial patterns of variation and pinpoint the pivotal factors that contribute to the emergence of odorous manifestations. The dynamics and influencing factors of T/O compounds in aquatic systems have been extensively investigated [16; 21; 40; 41; 42; 43; 44; 45]. The occurrence of T/O compounds in water bodies has been associated with diverse biotic and abiotic parameters, encompassing the phytoplankton community, water temperature, pH, and nutrient concentrations and/or ratios, etc. [22; 28; 42; 44; 46; 47; 48; 49; 50; 51]. These studies provided valuable insights for a more nuanced comprehension of the origins and impacts of odors in aquatic environments. However, the relationships between T/O compounds and environmental factors are intricate. Moreover, numerous ambiguous ecological interactions between cyanobacteria and other organisms contribute to a substantial disparity observed among various water bodies. It would prove advantageous if the presence of odorants could be correlated with monitored environmental parameters, as such associations could potentially serve to estimate the presence of these T/O compounds in water. Chaohu Lake (30\({}^{\circ}\)25\({}^{\prime}\)-31\({}^{\circ}\)43\({}^{\prime}\) N, 117\({}^{\circ}\)16\({}^{\prime}\)-117\({}^{\circ}\)51\({}^{\prime}\) E), positioned in the central region of Anhui Province, stands as the fifth-largest freshwater lake in China. Functioning as a pivotal regional fishery and tourism resource, it simultaneously serves as a critical potable water reservoir for approximately one million residents [52]. Nonetheless, it is also a recipient of domestic sewage and industrial effluents originating from the surrounding urban and rural areas. In the late 1980s, the exchange rate with the Yangtze River decelerated due to the establishment of the Chaohu Lake Gate, leading to an upsurge in nutrient inputs resulting from rapid agricultural intensification and industrial development in the basin [53]. Consequently, Chaohu Lake has been grappling with eutrophication since the 1980s [52]. Despite its eutrophic status, Chaohu Lake retains its pivotal role as a strategic water reserve due to its substantial storage capacity. However, specific areas within Chaohu Lake accumulate a notable quantity of cyanobacteria, and the issue of distinct odors has adversely impacted water quality, necessitating further investigation. For the early detection of T/O incidents to effectively manage the drinking water sources and their respective treatment facilities in Chaohu Lake, this study aimed to (1) investigate the monthly dynamics of dissolved and particulate compounds from four typical T/O (GSM, MIB, CYC, and ION), (2) identify cyanobacteria in the eastern drinking water source of Chaohu Lake, (3) estimate the water quality variables influencing T/O contents, and (4) conduct a comprehensive comparative analysis and discussion of documented T/O incidents and their associated determinants in freshwater environments globally.
## 3 Results and Discussion
### Analysis of GC-MS
#### 3.1.1 Volatile Compounds in Different Processing Stages
However, the relative contents of terpen significantly decreased after 2 h of braising (\(p<0.05\)), compared with 1 h. Linalool and Trans-p-mentha-1(7),8-Dien-2-ol were only detected after braising for 2 h, indicating that braising for a long time is beneficial to the release of flavor compounds from spices [5]. terpen mostly provide herbal and floral fruity [28] flavors, which contribute greatly to the characteristic flavor of Daokou braised chicken due to their low odor thresholds. Additionally, 1,8-Cineole provides camphor and cool herbal notes, Limonene a pleasant lemon aroma and \(\beta\)-Fenchol a wild floral aroma of cloves and vanilla. The relative contents of 1,8-Cineole, Limonene and \(\beta\)-Fenchol were higher, indicating that they may be important contributors to the delicate flavor of Daokou braised chicken. Two heterocyclic compounds both 2-Pentyl-furan and 5-Ethenylletrahydro-2-furanmethanol were detected in the braised chicken: 2-Pentylfuran is the main flavor compound for thermally processed food, derived from linoleic acid and other n-6 fatty acids, with relatively low threshold and plant aroma [28; 29]. The content of this compound increases (\(p<0.05\)) throughout processing. Only one ester, hexyl acetate, was detected in the frying and braising stage, and its concentration did not vary (\(p>0.05\)). With the exceptions of lactone [30] and thioester, esters have high thresholds and low abundances in meat, contributing little to the flavor of meat products. Oxime-, methoxy-phenyl- and N,N-Dibutylformamide were also detected. Oxime-, methoxy-phenyl- existed throughout processing, and may have originated from the material itself [31] or from contaminants in the environment or veterinary drugs. N,N-Dibutylformamide may have originated from pesticide residue. Volatile compounds in Daokou braised chicken at different processing stages were detected by GC-MS. As shown in Figure 1, 40, 49, 57 and 63 volatile compounds were respectively detected in samples L1, L2, L3, L4. The types of volatile compounds in Daokou braised chicken increased significantly with the progress of thermal processing. A total of 75 volatile compounds (R. match and F. match were both greater than 800) were detected including 20 hydrocarbons, 16 aldehydes, 15 alcohols, 10 terpen, 9 ketones, 4 heterocyclicsand 1 ester. The quantity and proportion of volatile compounds in Daokou braised chicken during processing are shown in Figure 2. The proportion of aldehydes and alcohols remained high throughout processing. With continued processing, the number of volatile components increased significantly. Compared with L1, the number of volatile compounds increased dramatically in the other samples. Heat treatments such as frying, braising, etc. are major contributors to the formation of flavor substances in meat products [32,33].
## 4 Simulation Results and Dissections
### Residential Load
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Item**} & \multirow{2}{*}{**Position**} & \multirow{2}{*}{**PV Energy**} & \multirow{2}{*}{**E\({}_{\text{PV to grid}}\)**} & \multirow{2}{*}{**E\({}_{\text{PV to grid}}\)**} & \multirow{2}{*}{**Charging**} & \multirow{2}{*}{**Discharging**} & \multirow{2}{*}{**P\({}_{\text{loss}}\)**} \\  & & **(Size (kW))** & & **(kWh)** & & **(kWh)** & **(kWh)** & **(kW)** \\ \hline \multirow{8}{*}{Residential Load} & Without & & & & & & \\  & PV and BES & - & - & - & - & - & 1867.977 \\  & \multirow{2}{*}{1} & PV & 61 (3693.2) & 27796 & 11666 & - & - & \\  & & BES & 61 (2467.5) & - & - & 16,130 & 12,358 & 711.9071 \\  & \multirow{2}{*}{2} & PV & 61 (3466.1) & 61 (26,088) & 61 (10,971) & - & - & 613.1804 \\  & & & 17 (1163.1) & 17 (7797.1) & 17 (3279.6) & - & - & 613.1804 \\  & \multirow{2}{*}{2} & BES & 61 (2323) & & & 61 (15,116) & 61 (11,581) & \\  & & & 17 (693.992) & - & - & 17 (4517.5) & 17 (3460.9) & \\  & & & 61 (3345.6) & 61 (25,180) & 61 (10,589) & & & \\  & \multirow{2}{*}{3} & PV & 18 (745.66) & 18 (5612.2) & 18 (2361.7) & - & - & \\  & & & 11 (1012.7) & 11 (7622.3) & 11 (3202.5) & & & 594.447 \\  & & & 61 (2242.17) & & & 61 (14,591) & 61 (11,178) & \\  & \multirow{2}{*}{BES} & 18 (498.78) & - & - & 18 (3250.5) & 18 (2490.2) & \\  & & & 11 (681.1) & & 11 (4419.8) & 11 (3386) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The obtained results with and without installing PV with BES in residential system loads. Figure 12: BES output during the day by installing one PV with BES in residential system load. Figure 14: BES output during the day by installing two PV with BES in residential system load. Figure 15: PV output during the day by installing three PV with BES in residential system load.
## 2 Theoretical Model and Numerical Methods
### Analysis Scheme for Parametric Study  
In total, three series of 1-D transient analyses of the 1.2 m capillary barrier cover were carried out (Table 2). These analyses aim to provide insights into the influence of waste temperature on the transfer of LFG within the cover. The objective of the first series of analyses is to underscore the importance of considering the effects of temperature gradients, induced by waste temperature, on MAMO and evaporation. The second and third series of analyses focus on the effects of the initial moisture content and LFG generation rate, respectively. [PERSON] et al. [10] reported that a representative CH\({}_{4}\) emission flux from older landfills or sites with LFG collection systems was about 85 g m\({}^{-2}\) d\({}^{-1}\). Given that the ratio of CH\({}_{4}\) to CO\({}_{2}\) in LFG is approximately 1:1, the typical LFG influx used in this study is 10.625 mol m\({}^{-2}\) d\({}^{-1}\).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline  & \multicolumn{3}{c}{**Value**} \\ \cline{2-4}
**Parameter** & \multicolumn{1}{c}{**Loess +**} & \multicolumn{1}{c}{**Loess**} & \multicolumn{1}{c}{**Gravel**} \\ \cline{2-4}  & **Compost** & & & \\ \hline Porosity & 0.496 & 0.466 & 0.34 & \\ Soil dry bulk density (kg m\({}^{-3}\)) & 1300 & 1450 & 1716 & \\ Saturated volumetric water content & 0.496 & 0.466 & 0.34 & [PERSON] et al. [38]; \\ Residual volumetric water content & 0.08 & 0.1 & 0.04 & [PERSON] et al. [39] \\ [PERSON]’s parameter, \(a\) & 0.07 & 0.05 & 23.6 & \\ [PERSON]’s parameter, m & 0.35 & 0.34 & 0.79 & \\ [PERSON]’s parameter, n & 1.53 & 1.52 & 4.8 & [PERSON] et al. [28]; \\ Intrinsic permeability (10\({}^{-13}\) m\({}^{2}\)) & 16.6 & 4.5 & 3670 & [PERSON] et al. [15] \\ Maximum CH\({}_{4}\) oxidation rate & 3.3 & 0.6 & - & [PERSON] et al. [11] \\ (10\({}^{-7}\) mol kg\({}^{-1}\) s\({}^{-1}\)) & 0.012 & 0.012 & - & [PERSON] \\ \(K_{m}\) & 0.0066 & 0.0066 & - & et al. [40] \\ Thermal conductivity of dry soil & 0.24 & 0.27 & 0.4 & [PERSON] et al. [28]; \\ Thermal conductivity of saturated soil & 1.6 & 1.65 & 2.17 & [PERSON] et al. [41] \\ (8\({}^{-1}\) m\({}^{-1}\) K\({}^{-1}\)) & 1.6 & 1.65 & 2.17 & \\ [PERSON] constant of CH\({}_{4}\) & & 0.0316 & & \\ [PERSON] constant of CO\({}_{2}\) & & 0.8145 & & [PERSON] [42] \\ [PERSON] constant of O\({}_{2}\) & & 0.0318 & & \\ [PERSON] constant of N\({}_{2}\) & & 0.0159 & & \\ Specific heat capacity of O\({}_{2}\) (J kg\({}^{-1}\) K\({}^{-1}\)) & 1005 & & \\ Specific heat capacity of CH\({}_{4}\) (J kg\({}^{-1}\) K\({}^{-1}\)) & 2160 & & [PERSON] et al. [43] \\ Specific heat capacity of CO\({}_{2}\) (J kg\({}^{-1}\) K\({}^{-1}\)) & 816 & & \\ Specific heat capacity of N\({}_{2}\) (J kg\({}^{-1}\) K\({}^{-1}\)) & 930 & & \\ Specific heat capacity of water (J kg\({}^{-1}\) K\({}^{-1}\)) & 4185 & & \\ Specific heat capacity of soil particle & 879 & & [PERSON] and \\ (J kg\({}^{-1}\) K\({}^{-1}\)) & 1850 & & [PERSON] et al. [45] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters used in the simulation model.
# Recent Advances in the Growth and Characterizations of SILAR-Deposited Thin Films
## 2 Metal Sulfide Thin Films
### Cadmium Sulfate Films  
The depositions of CdS films took place on glass slides by using Na\({}_{2}\)S and cadmium (II) chloride (CdCl\({}_{2}\)). The immersion and rinsing times were 20 and 40 s, respectively [51]. The obtained films showed very high transmittance (visible region) and stoichiometric compositions. On the other hand, another precursor, such as cadmium acetate (Cd(CH\({}_{3}\)CO\({}_{2}\))\({}_{2}\)), was used to produce thin films (Equations (16)-(21)).  
\[\text{Na}_{2}\text{S}+\text{H}_{2}\text{O}\to 2\text{Na}^{+}+\text{ SH}^{-}+\text{OH}^{-} \tag{16}\]  
\[\text{SH}^{-}+\text{OH}^{-}\rightarrow\text{S}^{2-}+\text{H}_{2}\text{O} \tag{17}\]  
\[\text{Cd}^{2+}+2\text{OH}^{-}\rightarrow\text{Cd}\left(\text{OH}\right)_{2} \tag{18}\]  
\[\text{Cd}\left(\text{OH}\right)_{2}+4\text{NH}_{2}\text{OH}\rightarrow\left[ \text{Cd}\left(\text{NH}_{3}\right)_{4}\right]^{2+} \tag{19}\]  
\[\left[\text{Cd}\left(\text{NH}_{3}\right)_{4}\right]^{2+}\rightarrow\text{ Cd}^{2+}+4\text{NH}_{3} \tag{20}\]  
\[\text{Cd}^{2+}+\text{S}^{2-}\rightarrow\text{CdS} \tag{21}\]  
The as-deposited and annealed films (250 \({}^{\circ}\)C, under air, 30 min) showed an amorphous phase and polycrystalline nature with the hexagonal structure [52]. The glass substrate was modified by using 3-mercaptoethanolpropyltrimethoxysilane to produce good-quality films [53]. The results showed that a faster deposition rate could be observed in the modified substrates. Cadmium chloride and thiourea were used to produce thin films at 80 \({}^{\circ}\)C under different deposition cycles [54]. The results of the XRD studies confirmed that the crystallite sizes (12.44 to 14.65 nm) and absorbance edge (525 to 555 nm) increased with increasing the deposition cycles (20, 30, and 40 cycles). Cd(II) organic salt, such as cadmium 2,4-pentanedionate (C\({}_{10}\)H\({}_{14}\)CdO\({}_{4}\)), was used to produce films on glass sheets [55]. The XRD analysis revealed that these films were polycrystalline in nature with various particle sizes (20-80 nm). [PERSON] and co-workers [56] reported that homogeneous nanostructured films could be observed when the deposition cycles reached 125 cycles during the experiment. The research findings also revealed that conductivity increased when the temperature increased and the specific conductance was 10\({}^{-4}\) to 10\({}^{-2}\) (\(\Omega\cdot\)cm)\({}^{-1}\). Cadmiumacetate and ammonium sulfide ((NH4)2S) served as cationic and anionic precursors, respectively, during the formation of the films at room temperature [57]. TEM and EDX studies confirmed the average particle size was 23.5 nm and the existence of cadmium and sulfur elements. FTIR spectra showed several peaks in Figure 3, such as 653.37 cm\({}^{-1}\) (CdS stretching frequency), 1068.76 cm\({}^{-1}\) (SO\({}_{4}^{-}\) traces), 1408.43 cm\({}^{-1}\) (S=O), and 1598.51 cm\({}^{-1}\) (C-C stretching vibration).