esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Salinity Structure Change by the Typhoon
Surface salinity distribution at **(a)** 5:00 on 19 September in the rising period; **(b)** 7:00 on 23 September in the stable period; **(c)** and 9:00 on 25 September 2014 in the falling period of Typhoon Fongwong, and the same time-surface salinity distribution (**d–f**) without typhoon. Figure 14 is the salinity vertical distribution along the talweg of the NB at 5:00 on 19 September in the rising period and 9:00 on 25 September 2014 in the falling period of Typhoon Fongwong. Both have significant different vertical structures, the former is a typical salt wedge reflecting partial mixing, while the latter is totally mixed in the vertical direction. Moreover, compared to the salinity stratification at the two different times, it is obvious that the water movement was not only synchronized from the surface to the bottom but also from the upstream area to the mouth. Combined with the \(n_{s}\) and the simulation result, the typhoon changes the estuarine mixing type and enhances water mixing and matter exchange in the vertical direction, which means that the strong winds can create sufficient mixing energy to destroy this stratification [39]. Figure 14 also shows the isohaline of the 1 psu, 2 psu and 4 psu shift upstream at 500 m, 1000 m and 19.5 km, respectively, in the NB due to the typhoon and this result can have important implications for the water quality. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \(n_{s}\) & **Point 1** & **Point 2** & **Point 3** & **Point 4** & **Point 5** & **Point 6** & **Point 7** & **Point 8** & **Point 9** & **Point 10** & **Point 11** \\ \hline
19 September & 0.050 & 0.011 & 0 & 0.003 & 0.381 & 0.240 & 0.510 & 0.528 & 0.390 & 0.263 & 0.231 \\ \hline
25 September & \(-\)0.025 & \(-\)0.015 & \(-\)0.003 & 0.003 & \(-\)0.007 & \(-\)0.005 & \(-\)0.002 & \(-\)0.002 & \(-\)0.001 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary \(n_{s}\) values of the points along the talweg. Figure 14: Salinity vertical distribution along the talweg of the NB at (**a**) 5:00 on 19 September in the rising period; (**b**) and 9:00 on 25 September 2014 in the falling period of Typhoon Fongwong.
# Improved Sea Ice Image Segmentation Using U\({}^{2}\)-Net and Dataset Augmentation
## 2 Materials and Methods
### U\({}^{2}\)-Net Retrofit
#### 2.2.2. SCM-RSU and SC-U\({}^{2}\)-Net Network  
SC-U\({}^{2}\)-Net refers to U\({}^{2}\)-Net with Skip connect structure and CBAM improvements. The SC-U\({}^{2}\)-Net improvement was divided into two parts. First, the SCM-RSU was used instead of the RSU (Figure 4). SCM-RSU is the RSU that incorporates Skip connect structure, CBAM, multiscale dilated convolution. In the downsampling stage, SCM-RSU used the residual structure, and the output of the upper layer skipped the intermediate convolution as the input of the lower convolution directly to reduce the loss of features in the downsampling process. The U\({}^{2}\)-Net network used multiscale expansion convolution only in RSU-4F, which was located in the deep layer of the network, to extract richer features at different scales. The SCM-RSU deep perception module was changed to multiscale expansion convolution, where the input feature maps were subjected to 1 \(\times\) 1 convolution with an expansion factor (d) of 1, 3 \(\times\) 3 convolution with a d of 1, and 3 \(\times\) 3 expansion with a d of 2, respectively. Subsequently, the outputs of the three convolutions were stitched in the channel dimension, and, finally, channel fusion was performed using a 1 \(\times\) 1 convolution. In the decoding stage, the output of the same depth encoding and that of the previous decoding depth were processed by the CBAM attention mechanism and inputted.  
Secondly, in the overall framework, multiple attention mechanisms were added (Figure 5). The feature map of the encoder output feature map decoder upsampling after using CBAM processing and then input to the corresponding decoder; the decoder output feature map enables CBAM processing and then convolution operation to obtain the feature map with channel number 1; each feature map upsampled to the input image. After upsampling each feature map to the size of the input image, stitching was performed to obtain an output with a channel number of 6 and the same size as the original image, and then CBAM was used to process the output. Finally, the output with a channel number of 1 was obtained using 1 \(\times\) 1 convolution.  
Figure 4: SCM-RSU structure.
# On Connectivity and Energy Efficiency for Sleeping-Schedule-Based Wireless Sensor Networks
## 5 Conclusions  
This paper researches the connectivity of WSNs, combines the probability theory with the new network connectivity and energy efficiency algorithm, the principle of updating routing table by a router in the computer network is applied to the WSNs, which explains the information exchange between neighbor nodes, such as updating the list of neighbor information. The innovation of the paper is to choose which type of sleeping node to wake up according to the residual energy and the relative distance of the nodes. In order to maximize the network connectivity and the connectivity probability, and minimize the energy consumption of the entire network as much as possible, the algorithm wakes up as few neighbor nodes as possible, to improve the service life of the whole network. According to the random deployment of sensor nodes satisfying a Poisson distribution, the simulation results show the network reaches the maximum network connectivity and connectivity probability, and the expression and the value of the node communication radius \(R\) and the number of nodes \(N\) are given. According to the parameters provided by the strongly-connected network, under different node communication radius \(R\), the relationship between the node connectivity \(K\) and the connectivity probability \(P_{r}\) is presented. When the connectivity \(K=8\), according to the relationship between the node communication radius \(R\) and the connectivity probability \(P_{r}\), the algorithm maximizes the connectivity and minimizes the energy consumption in the WSNs.  
Figure 4: The relationship between the node communication radius and the connected probability diagram \(P_{r}\) when the K = 8.  
**Author Contributions:** Conceptualization, L.W. and J.Y.; Methodology, L.W.; Software, T.H.; Validation, L.W. and T.H.; Formal Analysis, L.W.; Investigation, L.W.; Resources, L.W.; Data Curation, L.W.; Writing-Original Draft Preparation, L.W.; Writing-Review & Editing, L.W.; Visualization, L.W.; Supervision, D.D.; Project Administration, D.D.; Funding Acquisition, D.D.  
**Funding:** The authors would like to acknowledge the support from the National Natural Science Foundation of China (NSFC) under grant 61471180, the Hong Kong Tin Ka Ping fund (1602-07-411), the Project of Hubei Province Universities outstanding youth scientific innovation team (T201431, T201633, T201735), the Hubei Provincial Science and Technology Department under grant 2013 CFB188, the Hubei Provincial Department of Education Scientific research projects (B2015188) and a grant from Wenhua College (2019T01).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Waveguide Characterization
### Conclusions  
We built and characterized air-cladded single-mode polymer optical waveguides, fabricated by means of direct laser writing, and supported by a narrow fin which has a minimal impact on optical performance. Coupling in and out of the waveguides was aided by bending both ends upwards at 45\({}^{\circ}\) from the substrate to facilitate lensed fiber alignment. Waveguides of two-micron diameter, with lengths from hundreds of microns to a couple of millimeters, were printed, all proving to be robust and functional due to the stability afforded by the nano-fin support to the substrate. This waveguide design opens new possibilities for interconnection and sensing devices for various applications. Free-standing waveguides are exposed to the surrounding area, which enhances the interaction of the evanescent field of the guided mode with the external sensing medium, offering new prospects for the design of highly sensitive sensors. TPP-based devices can also be fabricated directly on a fiber tip and can help realize single-fiber-based sensors for various applications.  
[PERSON] designed and fabricated waveguides and performed the experiments; [PERSON] discussed and gave suggestions on the design and experiments; [PERSON] wrote the paper, and [PERSON] revised and edited the paper. Both authors have read and agreed to the published version of the manuscript.  
This work is funded in part by the Pazy Foundation and by the Israel Ministry of Science.  
We thank [PERSON] (Peter Brojde Center for Innovative Engineering at the Hebrew University of Jerusalem) for her guidance on the Nanoscribe system during the waveguide fabrication process, and [PERSON] (Photonic Devices Lab, The Hebrew University of Jerusalem) for his help in designing the experimental setup for characterizing the fabricated waveguides in our laboratory.  
The authors declare no conflict of interest.
# Label-Setting Algorithm for Multi-Destination \(K\) Simple Shortest Paths Problem and Application
## 3 Methodology
### Multi-Destination \(k\) Simple Shortest Paths
#### 3.1.1 Single Destination KSSP  
Given a directed network \(G(N,A)\), an origin \(s\in N\), and a destination \(t\in N\), find the set of simple shortest paths \(\Phi_{st}\) from \(s\) to \(t\), if they exist, such that \(C(\gamma_{s,t})\leq C\big{(}\gamma_{s,t}^{\prime}\big{)}\ \forall\ \gamma_{s,t}\in\Phi_{st},\ \forall\ \gamma_{s,t}^{\prime}\
otin\Phi_{st}\). The number of paths in the shortest path set may be \(k\) or fewer. If at least \(k\) simple paths exist between \(s\) and \(t\), the set of interest \(\Phi_{st}\) contains exactly \(k\) paths, i.e., the cardinality of the set \(|\Phi_{st}|=k\). If fewer than \(k\) simple paths exist between \(s\) and \(t\), then the set of interest \(\Phi_{st}\) contains the available number of simple paths, i.e., \(|\Phi_{st}|<k\).
## Formulation of the Problem
### Investigated Structures  
Two models were investigated, and both are perfect cylindrical shells without imperfections or openings that would change their dynamic behavior [38]. The first one, MODEL1, is a cantilever tube, and its model is a thin-walled cylindrical shell with a circular cross-section. The diameter of the middle-surface of the cross-section is \(R=0.6103\) m, the thickness of the shell is \(t=0.016\) m,and the length of the cantilever is \(l=6.0\) m. The shell web consists of a varying number of layers of composite material of equal thickness but with different fiber orientations (Figure 1b shows three layers of composite material).  
The second investigated model, MODEL2, has the same overall length, \(l=6.0\) m, but it consists of three two-meter-long segments (see Figure 1c). Again, each of the segments is a thin-walled cylindrical shell with a circular cross-section. The first and the third segments have constant diameters (\(R_{1}=0.6103\) m and \(R_{3}=0.4103\) m, respectively), and the diameter of the middle section changes linearly from \(R_{1}\) to \(R_{3}\). Moreover, the axes of any segment are not parallel to any other segment axes. The shell web of each segment consists of four symmetric layers of composite material. The second model is not a cantilever; there are supports on both ends, with some parts of the outer rings free, some parts supported (no displacements are possible), and some parts fixed (neither displacement nor rotation is possible).  
The material properties of both MODEL1 and MODEL2 are based on [39]: \(E_{1}=141.9\) GPa, \(E_{2}=9.78\) GPa, \(v_{12}=0.42\), \(G_{12}=6.13\) GPa, and \(\rho=1445\) kg/m\({}^{3}\).
## 2 Materials and Methods
### Experimental Methods  
The experimental procedure involved cleaning each sample from oil, bitumen, and water-soluble salts, saturating it with a 2% NaCl solution, and maintaining it for 12 h at a temperature of 20 \({}^{\circ}\)C and a pressure of 3 MPa (reservoir conditions) [31]. Then, each sample was scanned using an X-ray microcomputed tomography General Electric V! tome! X S240 (Baker Hughes, Houston, TX, USA) at a resolution of about 18 \(\upmu\)m before injecting HCl solution.  
Flow-through experiments involving the injection of 2% sodium chloride (NaCl) and hydrochloric acid (HCl) solutions were conducted using the electronic rock testing unit Wille Geotechnik Y1000 (Wille Geotechnik, Rosdorf, Germany). This unit facilitates the measurement of sample permeability before and after dissolution with HCl solutions under reservoir conditions. The experimental setup is illustrated in Figure 1. The sample was installed in the Hassler cell, valves V3 and V4 were opened to inject a 2% NaCl solution through the sample, and the drop in pressure at the ends of the sample was measured at three constant injection rates after stabilization. Subsequently, valves V3 and V4 were closed, and valves V1 and V2 were opened for the injection of HCl solution until the breakthrough. Following the injection of the HCl solution, a 2% NaCl solution was reinjected into the sample, and the drop in pressure at the ends of the sample was measured at three constant injection rates after stabilization. All experimental data were recorded on a computer. After each experiment, the pressure was released, the sample was removed from the core holder unit, and the injection lines were flushed. Then, the sample was scanned with X-ray microcomputed tomography after dissolution with HCl solution.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Sample Name**} & \multirow{2}{*}{**Porosity, \%**} & \multirow{2}{*}{**Permeability, \(\upmu\)m\({}^{2}\)**} & \multicolumn{4}{c}{**Composition, \%**} \\ \cline{3-6}  & & & **Calcite** & **Dolomite** & **Quartz** \\ \hline \#1 & 19.0 & 0.29 & 99 & - & 1 \\ \hline \#2 & 20.6 & 0.43 & 100 & - & - \\ \hline \#3 & 20.9 & 0.71 & 99 & - & 1 \\ \hline \#4 & 20.0 & 0.45 & 100 & - & - \\ \hline \hline \end{tabular}
\end{table}
Table 1: The main characteristics of the studied samples.  
The water permeability of the samples was calculated using Darcy's law. A constant temperature of 20 \({}^{\circ}\)C and a confining pressure of 3 MPa were maintained throughout the experiment. Table 2 contains the permeability data of the samples before and after their dissolution with HCl solutions, and the data on the injection rate and mass concentration of HCl in the solution.
## 3 Results and Discussion
### Effect of Initial Concentration  
The effect of the initial Zn concentration was studied at the optimum pH value of 4. Other concentrations were also studied: 10 mg/L, 25 mg/L, 50 mg/L, 75 mg/L, 100 mg/L, 125 mg/L, 150 mg/L, 200 mg/L, and 500 mg/L. The results of the initial concentration experiments are presented in Figure 2. Biomass-based activated carbon works quite well in the concentration range of 0 mg/L-150 mg/L. The removal percentage increases as a function of the initial Zn concentration to 75 mg/L and then starts to decrease sharply. Therefore, the optimum Zn concentration, 75 mg/L, was selected for further experiments. The optimal adsorption sites are occupied first at low concentrations. When the concentration increases, there may exist some driving forces to increase the removal percentage. [34].  
Figure 1: The removal percentage as a function of pH. Experiments were done in duplicate and the range of results were at maximum 3 percentage points.  
Figure 2: Removal percentages as a function of Zn initial concentration. Experiments were done duplicated and the removal % varied in the range of 3 percentage points.  
adsorption capacity increases as a function of Zn concentration. The adsorption capacity was compared to other adsorbents used in Zn removal, shown in Table 2. The adsorption capacities presented in the literature vary between 2.21 and 52.09 mg/g. The adsorption capacity (21.44 mg/g) obtained in this study was in the same order of magnitude. The amount of Zn adsorbed as a function of Zn concentration is presented in Figure 3. [PERSON] et al. used the initial metal concentration of 320 mg/L [35] and [PERSON] and [PERSON] reported the initial metal concentration between 1-1000 mg/L [18]. The initial metal concentration used in this study was 10-500 mg/L. The initial metal concentration may have effect to the adsorption capacity.
###### Abstract  
Through offloading computing tasks to visible satellites for execution, the satellite edge computing architecture effectively issues the high-delay problem in remote grids (e.g., mountain and desert) when tasks are offloaded to the urban terrestrial cloud (TC). However, existing works are usually limited to offloading tasks in pure satellite networks and make offloading decisions based on the predefined models. Additionally, runtime consumption for offloading decisions is rather high. Furthermore, privacy information may be maliciously sniffed since computing tasks are transmitted via vulnerable satellite networks. In this paper, we study the task-offloading problem in satellite-terrestrial edge computing networks, where tasks can be executed by satellite or urban TC. A privacy leakage scenario is described, and we consider preserving privacy by sending extra random dummy tasks to confuse adversaries. Then, the offloading cost with privacy protection consideration is modeled, and the offloading decision that minimizes the offloading cost is formulated as a mixed-integer programming (MIP) problem. To speed up solving the MIP problem, we propose a deep reinforcement learning-based task-offloading (DRTO) algorithm. In this case, offloading location and bandwidth allocation only depend on the current channel states. Simulation results show that the offloading overhead is reduced by 17.5% and 23.6% compared with pure TC computing and pure SatEC computing, while the runtime consumption of DRTO is reduced by at least 42.6%. The dummy tasks are exhibited to effectively mitigate privacy leakage during offloading.  
satellite-terrestrial networks; edge computing; deep reinforcement learning; computation offloading; privacy protection; mixed-integer programming
# On the Analysis of Coverage Feedback in a Fuzzing Proprietary System
## 8 Conclusions  
This paper uncovers the details of how and when code coverage feedback is beneficial or not. Our research revealed that while coverage-guided fuzzing benefits most scenarios to some extent, its effectiveness is substantially influenced by multiple factors such as the _existence of an initial seed corpus_, type of data parser, and amount of code base (line of code). Such information is especially valuable in situations requiring substantial effort to implement coverage feedback fuzzing, such as with closed-source or embedded system firmwares. By evaluating 44 real-world bugs from OSS-Fuzz, we found detailed correlations between coverage feedback and external factors. We hope researchers can reference our findings in designing fuzzing systems for closed-source applications, such as UAV/IoT firmware.  
Conceptualization, D.J. and C.K.; methodology, J.K. ([PERSON]); software, J.K. ([PERSON]); validation, W.I., M.J. and B.C.; writing--original draft preparation, D.J.; writing--review and editing, D.J.; visualization, J.K. ([PERSON]); supervision, C.K.; project administration, D.J.; funding acquisition, B.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the Convergence Security Core Talent Training Business Support Program grant number IITP-2024-RS-2023-00266615, and the APC was funded by the KRIT (Korea Research Institute for defense Technology planning and advancement) grant funded by the Defense Acquisition Program Administration (DAPA) (KRIT-CT-22-074) and was also supported by a grant from Kyung Hee University in 2023 (KHU-2023080).  
Data Availability Statement: The original data presented in the study are openly available in oss-fuzz-lab at [[https://github.com/Jminis/oss-fuzz-lab](https://github.com/Jminis/oss-fuzz-lab)]([https://github.com/Jminis/oss-fuzz-lab](https://github.com/Jminis/oss-fuzz-lab)) (accessed on 20 March 2024).  
Conflicts of Interest: Authors [PERSON] and [PERSON] were employed by the company CW Research Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Improved ISR for IEEE 802.11 ah Nonlinearity Compensation via Adjustable Constellation Borders
###### Abstract  
Iterative subcarrier regularization (ISR) has been recently proposed as a receiver-side remedy for orthogonal frequency division multiplexing (OFDM) nonlinearity. It allows the power amplifier of OFDM transmitters to operate at a lower input back-off for more efficient uplinks. However, the compensation ability cannot align with increasing channel quality, because the standard quadrature amplitude modulation (QAM) used in ISR may eliminate compensation due to erroneous decisions. To solve this issue, an improved version of ISR was proposed to flexibly adjust the constellation borders of QAM and numerically optimize it based on IEEE 802.11 ah (hereinafter referred to as 802.11 ah) specifications. Simulations show that the proposed scheme not only improves the converged bit error rate of ISR but also accelerates its own convergence, especially in a high channel quality, thereby achieving better power efficiency for Internet of Things clients without additional computational complexity.  
IEEE 802.11 ah; orthogonal frequency division multiplexing (OFDM); nonlinearity compensation; peak-to-average power ratio (PAPR) +
Footnote †: journal: _electronics_  
**Citation:** [PERSON]; [PERSON]; [PERSON] Improved ISR for IEEE 802.11 ah Nonlinearity Compensation via Adjustable Constellation Borders.  
_Electronics_**2021**, _10_, 1573. [[https://doi.org/10.3390/electronics10131573](https://doi.org/10.3390/electronics10131573)]([https://doi.org/10.3390/electronics10131573](https://doi.org/10.3390/electronics10131573))