esa-sceva/satcom-chunk-collection huggingface dataset:
# A Systematic Review of Ship Wake Detection Methods in Satellite Imagery
## 3 Results
### Final Overview

Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Reference** & **Type** & **Method** & **Advantages** & **Disadvantages** & **Imagery Source** \\ \hline
[55] & Traditional, SAR & Detection using two-parameter CFAR and multi-image correlation & Suitable for wide-area monitoring; high accuracy & Difficulties in complex sea backgrounds; sensitivity to sea conditions & N/A \\ \hline
[43] & Traditional, SAR & RT-based detection for identifying dark vessels & Effective in homogeneous sea clutter; reconstructs & Strugles with sharp wind transitions or surface films & Sentinel-1 \\ \hline
[56] & Traditional, SAR & Multi-ship and multi-scale wake detection using RT & High accuracy; effective on complex wakes; no large datasets needed & May miss small wakes; challenging in complex backgrounds & Gaofen-3 \\ \hline
[53] & Traditional, SAR & Anomaly detection using sea clutter dictionaries & Improves detection under varying sea states; adaptable to complex environments & Requires extensive training data; computationally intensive dictionary learning & HRSID dataset \\ \hline
[19] & Traditional, Optical & Cascaded hull and wake detection using Fourier transform; fuzzy classifier & Cascaded approach is effective; of great interest & Higher computational requirements & Gaofen-1 panchromatic and multi-spectral \\ \hline
[24] & Traditional, Synthetic SAR & Non-convex regularization with Cauchy-based penalty & High accuracy in simulated conditions; sensitive to ship parameters & Limited to simulated data; unverified in real conditions & Numerically simulated data \\ \hline
[49] & Traditional, Synthetic SAR & Pre-processing with polarimetric enhancement & Enhanced detection using PWF and PDOF filters & Complex pre-processing; mitigation of bright points needed & Synthetic data \\ \hline
[5] & & Vessel velocity estimation via azimuth offset using CNNs; RT for waking highlighting & Validated with AIS data; effective velocity estimation & Inherits RT weaknesses; issues with dark ships in AIS data & TanDEM-X Single Look Complex (SLC) images \\ \hline
[10] & DL, Optical & CNN architecture exploiting X-shaped wake patterns and RT & Combines CNN with traditional knowledge; effective detection. & Inherits weaknesses of traditional CNNs & Google Earth imagery (0.5–2.5 m resolution) \\ \hline
[61] & DL, SAR & Wake detection using Cascade Mask & Robust detection in Sentinel-1 images; generalizes to X-band data. & High false alarm rate in rough seas; limited dataset size & Sentinel-1, TerraSAR-X, COSMO-SkyMed \\ \hline
[63] & DL, Optical & Wake detection using Mask R-CNN & High accuracy in complex scenarios; effective in multiple configurations & Requires large training dataset; sensitive to weather conditions & Sentinel-2 \\ \hline
[62] & DL, SAR & Nonlinear wake detection using
## 2 MILP Model  
The mathematical problem of optimizing the synthesis, design and operation of a DG energy system has to be generally regarded as a variational calculus problem because several decision variables related to the components are time dependent. However, a realistic description of the system may be represented by a MILP formulation by properly discretizing all dynamic variables in quasi-stationary variables and approximating all non-linear relations in a set of linear functions [5; 21; 22; 23; 24]. To solve the issue of synthesizing the configuration of the energy system, a reducible structure (known also as a superstructure) which embeds several possible configurations and interconnections is defined.  
The superstructure proposed in this research is shown in Figure 1. The superstructure can be divided into two different parts: the superstructure related to each _site_; and the superstructure related to the _central unit_. The green, red and blue lines represent the physical distribution of electric, thermal and cooling energy, respectively, while the orange arrows represent the fuel inputs. Following each distribution line inside the site \(k\), the electricity can be produced by internal combustion engines (ICE), by micro gas turbines (MGT) and by photovoltaic panels (PV), can be bought from or sold to the electricity grid, used by compression chillers (CC) and by the heat pumps (HP), while the rest is sent to the user \(k\). The thermal energy can be produced by ICEs, by MGTs, by solar thermal (ST) panels, by boilers (BOI) and by HPs, can be stored in the thermal storage (TS), can be used by absorption chillers (ABS), can be send to the user \(k\) or to the DHN. The cooling energy can be produced by CCs, by ABSs and by HPs, can be stored in the cooling storage (CS), can be sent to the user \(k\) or to the district cooling network (DCN). The central unit can produce electricity by the centralized ICE, can produce thermal energy by the same ICE, by the central BOI and by the solar thermal field (ST field). The thermal energy produced in the central unit can be sent directly to the DHN and then to the users, or can be stored in a centralized TS and used later. The electricity produced in the central unit by the centralized ICE can only be sold to the electricity grid [22].  
The superstructure shown in Figure 1 has been created specifically for the problem involved in the study, but it is general and can be integrated with other components. It can be modified with different connections of the components or it can be reduced by eliminating some components considered superfluous. The number of users is not defined a priori; however, it is limited by the computational effort which is quadratic whit the overall number of decision variables.
## 3 Model Design
### BiLSTM  
Due to the complex contextual relationships in the goods text, the global dependencies of the text sequence are further captured using BiLSTM. BiLSTM is able to provide a more comprehensive contextual understanding by simultaneously considering the information before and after each word. BiLSTM consists of two LSTM models, which deal with forward and reverse sequences, respectively. For a given input \(x_{t}\) at time step \(t\), the forgetting gate \(f\), the input gate \(i\), and the output gate \(o\) are calculated as shown in Equations (7)-(11):  
\[f_{t} = \sigma(W_{f}\cdot[h_{t-1},x_{t}]+b_{f}) \tag{7}\] \[i_{t} = \sigma\Big{(}W_{i}\cdot\Big{[}h_{t-1},x_{t}\Big{]}+b_{i}\Big{)}\] (8) \[o_{t} = \sigma(W_{o}\cdot[h_{t-1},x_{t}]+b_{o})\] (9) \[C_{t} = f_{t}\odot C_{t-1}+i_{t}\odot g_{t}\] (10) \[h_{t} = o_{t}\odot\tanh(C_{t}) \tag{11}\]  
where \(\sigma\) represents the activation function, \(W\) represents the weight parameter matrix, \(b\) represents the bias term, \(g_{t}\) represents the temporary neuron state, \(C_{t}\) represents the internal state at time step \(t\), and \(h_{t}\) represents the output result at time \(t\). The symbol \(\odot\) represents element-wise multiplication [13]. Assuming that the forward LSTM hidden layer output sequence is \(\overset{\rightarrow}{h_{t}}\) and the reverse LSTM hidden layer output sequence is \(\overset{\leftarrow}{h_{t}}\), the output of BiLSTM is the output of BiLSTM after splicing the two unidirectional output sequences \(H\in\mathbb{R}^{n\times 2m}\), where m is the hidden layer dimension of the LSTM, and the structure of the model is shown in Figure 3.  
To prevent the original feature information from being lost, the original input vector is feature spliced with the BiLSTM output vector to obtain a feature vector \(F\in\mathbb{R}^{n\times h}\), where \(h\) is \(d+2m\), with the calculation formula shown in (12), which is richer in feature information:  
\[F=\left[\overrightarrow{h};\overleftarrow{h};x\right] \tag{12}\]  
\(F\) contains not only the text context feature information learned by ERNIE, but also the text context feature information captured by BILSTM, which can better represent the complex structure and relationship of text.
_Article_  
Evaluation of the bactericidal Activity of a Hyaluronic Acid-Vehicled Clarithromycin Antibiotic Mixture by Confocal Laser Scanning Microscopy  
[PERSON] 1, [PERSON] 2,*, 2 [PERSON] 1, [PERSON] 3, [PERSON] 4, 3, [PERSON] 2, [PERSON] 2, [PERSON] 5, [PERSON] 1, [PERSON] 1 and [PERSON] 2  
1 Department of Public Health and Pediatric, University of Turin, 10126 Turin, Italy:  
[PERSON] (N.M.); [PERSON]SS] (J.R.); [EMAIL_ADDRESS] (G.B.); [PERSON]A.C.)  
2 Department of Surgical Sciences, Dental School, Endododonics, University of Turin, 10126 Turin, Italy;  
[PERSON].P.); [EMAIL_ADDRESS] (E.G.); [PERSON]SS] (E.B.)  
3 S.C.Farmacia Laboratorio Galenici-Sperimentazioni Cliniche-Farmacovigilanza e Diagnostici, Azienda Ospedaliera Citta della Salute e della Scienza, 10126 Turin, Italy; [EMAIL_ADDRESS]  
4 Department of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy;  
[EMAIL_ADDRESS]  
5 Department of Drug Science and Technology, University of Torino, 10125 Turin, Italy; [EMAIL_ADDRESS]  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +39-(0)11-6331569; Fax: +39-(0)11-6708389  
Received: 13 December 2019; Accepted: 16 January 2020; Published: 13 April 2020  
**Featured Application: Thanks to the use of confocal laser scanning microscopy, it is proved that ciprofloxacin, metronidazolezo and clarithromycin (3-MIXC) mixed with hyaluronic acid (HA) is a possible alternative to root canal disinfection during regenerative endodontic procedures (REPs) in order to avoid a substantial discoloration of the teeth, mainly due to the chelating effect of the minocycline.**  
**Abstract: Confocal laser scanning microscopy (CLSM) was used to evaluate the antibacterial effect and depth of action of a novel clarithromycin-containing triple antibiotic mixture, which was proposed for root canal disinfection in dental pulp regeneration. A previous study reported that this mixture had no tooth discoloration effects in vitro. After infection with _Enterococcus faecalis_ for 3 weeks, the dental tubules in the cylindrical root specimens were exposed to different antibiotic mixtures: ciprofloxacin, metronidazolezo and minocycline (3-MIX); ciprofloxacin, metronidazolezo and clarithromycin (3-MIXC) and ciprofloxacin and metronidazolezo (2-MIX). Each antibiotic formulation was mixed with macrogl (MG) or hyaluronic acid (HA) vehicles. CLSM and viability staining were used to quantitatively analyze the mean depth of the antibacterial effect and the proportions of dead and live bacteria inside the dental tubules. The 3-MIX and 3-MIXC demonstrated a similar depth of action. The mean proportion of dead bacteria was similar in the 3-MIX and 3-MIXC groups, and both were statistically higher than that of 2-MIX (\(p=0.014\)). Each antibiotic mixture showed a higher bactericidal efficacy if conveyed with HA, compared to MG (3-MIX, \(p=0.019\); 3-MIXC, \(p=0.013\) and 2-MIX, \(p=0.0125\)). The depth of action and the antibacterial efficacy of 3-MIXC seemed comparable with 3-MIX.**  
**Keywords: confocal laser scanning microscopy; triple antibiotic paste; double antibiotic paste; regenerative endodontic procedures; hyaluronic acid**
# Adaptive Multi-Channel Clustering in IEEE 802.11s Wireless Mesh Networks +
## 2 IEEE 802.11s WLAN Mesh Networks
In proactive mode, a node announces itself every 5 s via broadcast, triggering a path discovery or update on all other nodes. Since some parameters in ALM calculation are left open to vendor implementations, Linux provides own variants for error rate estimation and overhead constants. While \(O\) is set to the constant value 1, data rate \(r\) is estimated by the rate control algorithm. The error rate \(e_{fr}\) is updated on every frame transmission and calculated by a moving average filter. Depending on the WLAN hardware and driver, this estimation is often provided by the rate control algorithm as well.
# Improved Ship Detection Algorithm from Satellite Images Using YOLOv7 and Graph Neural Network
###### Abstract  
One of the most critical issues that the marine surveillance system has to address is the accuracy of its ship detection. Since it is responsible for identifying potential pirate threats, it has to be able to perform its duties efficiently. In this paper, we present a novel deep learning approach that combines the capabilities of a Graph Neural Network (GNN) and a You Only Look Once (YOLOv7) deep learning framework. The main idea of this method is to provide a better understanding of the ship's presence in harbor areas. The three hyperparameters that are used in the development of this system are the learning rate, batch sizes, and optimization selection. The results of the experiments show that the Adam optimization achieves a 93.4% success rate when compared to the previous generation of the YOLOv7 algorithm. The High-Resolution Satellite Image Dataset (HRSID), which is a high-resolution image of a synthetic aperture radar, was used for the test. This method can be further improved by taking into account the various kinds of neural network architecture that are commonly used in deep learning.  
deep learning; GNN; object detection; HRSID dataset; high-resolution satellite images +
Footnote †: journal: _Algorithms_  
**Algorithms**  
**Algorithms**
# A Survey on Penetration Path Planning in Automated Penetration Testing
## 2 Overview
### Automated Penetration Testing
#### 2.1.2 Model-Based Automated Penetration Testing  
To enhance the intelligence of automated PT, researchers have begun exploring the integration of artificial intelligence technologies with PT techniques [15]. This exploration has led to the emergence of model-based automated PT methods. Automated PT systems can autonomously perceive and plan penetration paths in network security scenarios by using intelligent agents that model and learn from network environments, vulnerability information, and attack behaviors and then execute attack actions based on these paths [16]. This enables more effective decision-making during the testing process, making PT more autonomous and better equipped to handle complex network environments and evolving attack techniques. Figure 1 illustrates the process of model-based automated PT.
# A New GNSS Single-Epoch Ambiguity Resolution Method Based on Triple-Frequency Signals
## 1 Introduction
A geometry- and ionosphere-free distance-independent reliable TCAR method was proposed in 2010 by [PERSON] et al. [21]; it was free of both ionospheric effects and geometric terms. [PERSON] et al. [22] presented an improved CAR method that includes the advantages of both integer least-squares (ILS) and CAR. [PERSON] and [PERSON] [23] proposed a method where the incoming triple-frequency GPS signals are exploited to enable rapid convergences to ambiguity-fixed solutions in real-time precise point positioning (PPP). [PERSON] et al. [24] proposed a modified stepwise AR method based on the TCAR and evaluated its performance using real BDS data. The LAMBDA method's application to the multi-frequency AR problem has been studied extensively by a number of research groups [24; 25; 26]. LAMBDA can be applied to either multi-frequency geometry-free cases or multi-frequency geometry-based cases. The algorithms mentioned above can all be used for the AR of multi-constellation and multi-frequency signals. However, most of the AR algorithms mentioned above simply combine different systems together without bringing every single system's superiority into full play. In this paper, we focus on this issue. This paper focuses on fixing the ambiguity of GNSS carrier phase observation based on the triple-frequency signals in real time. The mathematical model applied in this study is introduced in the second section. Section three introduces the new GNSS single-epoch AR method. The performance of this method is tested based on GNSS observation; the test results are shown in Section 4. Finally, there is a conclusion.
# Intelligent Fault Diagnosis of Rolling Element Bearings Based on Modified AlexNet +
## 2 Proposed Methods and Materials
### Feature Selection  
After constructing the vibration images, features were selected by the proposed modification of the AlexNet network. At first, pre-trained models, AlexNet, GoogleNet, VGG16, and ResNet50 were used to observe the bearing fault classification performance and AlexNet provided the highest accuracy. Then, AlexNet was modified by adding and replacing layers to obtain better accuracy. Finally, features were extracted from the modified AlexNet model.
## 6 Evaluation Experiments
### Experiment 2 Navigation Task
#### 6.2.1 Experiment Setup  
The structure of the Liquid Galaxy system built based on the system in this paper is shown in Figure 11. The system uses 6 high-performance rendering nodes to drive the 60 screens. Among them, there are 3 type II rendering nodes, each driving 16 screens; 3 type III rendering nodes, each driving 4 screens. Users can use the following four methods for interactive operations:  
1. Desktop console. On the console of the display wall system, the user uses the keyboard and mouse to perform interactive operations on the Master side of Google Earth.
2. 3D mouse. On the console of the display wall system, the user uses a three-dimensional mouse to perform interactive operations on the Master side of Google Earth.  
Figure 11: System structure of Liquid Galaxy system.  
Figure 10: Proportion of each mode of double-precision pointing technology.  
3. Leap Motion Controller. The user uses the Leap Motion controller to interact with the Master side of Google Earth on the console of the display wall system.
4. Gesture interaction. Users use the human-computer interaction framework proposed in this paper to perform interactive operations using gestures, as shown in Figure 12.
# An Efficient Routing Protocol with Overload Control for Group Mobility in Delay-Tolerant Networking
## 5 Conclusions  
In this paper, we considered a group mobility environment, where both intra- and intergroup routing are carried out by using a DTN protocol. Then, we newly defined delivery predictability for group mobility and proposed an efficient DTN routing protocol for group mobility by using both individual delivery predictability and group delivery predictability for making a forwarding decision, depending on the relationship of the group of contact node \(x\), group of contact node \(y\), and group of destination node \(z\) of a considered message. To improve the performance of the proposed protocol further, we proposed proactive overload control, where if a message is delivered to any node in the same group as the destination node of the message, further message dissemination is prohibited proactively.  
Using a ONE simulator, we evaluated the performance of the proposed protocol from the aspects of delivery ratio, overhead ratio, and delivery latency by varying buffer size, message size, and TTL. Performance evaluation results show that the proposed protocol had better delivery ratios and overhead ratios than the compared protocols by efficiently forwarding messages and controlling overload proactively to delivered messages to any node in the same group as the destination node of the message, although delivery latency was increased. Since DTN is delay-tolerant basically, it is justified that the proposed protocol with a better delivery ratio and overhead ratio is more suitable for DTN than the comparable protocols, even though the proposed protocol had larger delivery latency.  
Conceptualization, M.W.K. and Y.W.C.; formal analysis, M.W.K. and Y.W.C.; funding acquisition, Y.W.C.; investigation, M.W.K. and Y.W.C.; methodology, M.W.K. and Y.W.C.; software, M.W.K.; writing--original draft, M.W.K. and Y.W.C.; writing--review and editing, M.W.K. and Y.W.C. All authors have read and agreed to the published version of the manuscript.  
This work has been supported by the Future Combat System Network Technology Research Center program of Defense Acquisition Program Administration and Agency for Defense Development (UD190033 ED).  
Figure 13: Delivery latency for varying TTL.
## 3 Study Area and Satellite Data  
### Frenchman Flat Calibration Site  
The Frenchman Flat calibration site is located in Nevada, USA, in the transition zone of the Mohave and Great Basin deserts [68] (Figure 1). The area is a dry lake bed at 940 m.a.s.l.; formed of fine-textured sedimentary deposits, mainly sand, gravel, silt and clay [69]. The site fulfills many of the requisites stated by [PERSON] [34] and [PERSON] et al. [70] and belongs to the group of calibration sites endorsed by the Working Group on Calibration and Validation (WGCV) of CEOS [31; 71]. The reflectance of the site is higher than 30% in the VIS/NIR domain, ensuring a high signal-to-noise ratio (SNR). It presents a high degree of spatial homogeneity over an area that allows the absolute calibration of sensors having a Ground Sampling Distance (GSD) smaller than 300 m [6; 31]. Another characteristic of the area is its spectral uniformity, which contributes to minimizing the influence of SRF differences on the cross-calibration of satellite sensors [21; 62; 72].
## 9 Conclusions  
Membranes for the VRB have been extensively studied. Although many membranes provide promising results, meeting all the requirements for the commercialisation of an economically viable system is still a challenge that requires further development in order to achieve the required cost structure for large-scale grid-connected applications. Membranes for the VRB must withstand the highly oxidative pentavalent vanadium ions in the case of the original VRB technology, or the oxidizing effect of bromine in the G2 V/Br system. While a large number of new membranes have been developed and successfully tested for use in the VRB, limited work has been carried out for the G2 V/Br system and for the more recently reported mixed sulphate/chloride VRB electrolyte [11]. Given that these systems promise significantly improved energy densities compared with the original VRB system, further testing of novel membranes in these electrolytes is warranted. Nafion continues to be one of the widely studied membranes in VRB systems; however its high cost, high levels of water transfer and high diffusivity values for the vanadium ions limit its use in commercial applications. New improved perfluorinated membranes possess good resistance to the oxidising V(V) and polyhalide ions, good mechanical properties and seem to be suitable for use in both VRB and G2 V/Br systems. The improved perfluorinated membranes have also demonstrated significantly reduced swelling compared with Nafion and much lower diffusivity values for the vanadium ions that significantly reduce self-discharge rates and potential thermal problems during stand-by periods when the electrolyte pumps are turned off [121]. Non fluorinated membranes which have been tested in the G2 systems so far, are not efficient because of the rapid self discharge reaction between the bromine and vanadium ions [14]. Hence, for the G2 and mixed acid flow battery systems, future work in membranes should focus on developing cost effective fluorinated membranes by experimenting with novel polymers and substances that can impart the required conductivity and chemical stability to the membrane. In the meantime however, novel membranes developed and shown to perform well in the G1 VRB electrolyte should be further evaluated in both the G2 V/Br and mixed acid electrolytes for possible short term application and scale-up towards commercialisation of these high energy density flow battery technologies.