esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Synthetic Data Generation for Network-Based Analyses
### Pseudocode of the Data Generation  
Algorithm 1 summarizes the synthetic data generation steps for local and exponential consensus cases, explicitly detailing graph construction, edge orientation, Laplacian calculations, iterative consensus procedures, and data storage considerations.  
```
0: Number of nodes \(n\); random graph model \(\mathcal{M}\in\{\text{BA},\text{WS},\text{ER}\}\); case type \(\in\{\text{base},\text{exponential}\}\); bidirectional probability \(p_{b}\); tolerance \(\tau\); maximum iterations \(\text{iter}_{\text{max}}\); decay parameter \(\alpha\) (for multi-hop); record length \(T=10\)
0: Time-series states \(\{\phi(0),\dots,\phi(T-1)\}\); final consensus value \(\frac{1}{n}\sum_{i=1}^{n}\phi_{i}(\infty)\)
1: Generate random undirected graph \(G\) (BA, WS, or ER).
2: Create directed graph \(G\) from \(G\), orienting edges and adding reverse edges with probability \(p_{b}\).
3: Compute adjacency matrix \(A\) and out-degree diagonal matrix \(D^{\text{out}}\) from \(G\).
4: Form directed Laplacian \(L=D^{\text{out}}-A\); set \(K=L+A\), \(e=1/(100\cdot\max(K))\).
5:if case type = base then
6: Set \(P=I-\epsilon\,L\).
7:else
8: Compute \(d_{\text{max}}=\text{diameter}(\xi)\).
9: Calculate matrices \(A^{k}\) and Laplacians \(L_{k}\) for \(1\leq k\leq d_{\text{max}}\).
10: Set \(P=I-\epsilon\sum_{k=1}^{d_{\text{max}}}e^{-\alpha k}L_{k}\).
11:endif
12: Initialize \(\phi(0)=\text{diag}(K)\).
13:for\(t=0\) to \(\text{iter}_{\text{max}}-1\)do
14:\(\phi(t+1)=P\,\phi(t)\)
15:if\(\|\phi(t+1)-\phi(t)\|_{\infty}\leq\tau\)then
16:break
17:endif
18:endfor
19: Record \(\{\phi(0),\dots,\phi(\min(T-1,t))\}\) and \(\frac{1}{n}\sum_{i}\phi_{i}(t)\).
```  
**Algorithm 1** Synthetic data generation with base (one-hop) and exponential (multi-hop) consensus
## 4 Conclusions  
In this paper, the influences of random cumulative pitch deviations on mesh excitations and vibration responses of HGRS are studied. The LPMS, STE, and CMS of helical gear pairs are determined using an enhanced LTCA model. A dynamic model with multi DOF is employed to predict the vibration responses of HGRS. The effect of random cumulative pitch deviations on vibration responses of modified HGRS in time and frequency domain are also investigated in detail. The main findings are summarized as follows:  
1. considering random cumulative pitch deviations, the curve shapes of STE and CMS become irregular. When the load torque is relatively low, the LPMS in some mesh cycles will decrease due to partial contact loss. As the load torque increases, the actual contact region will become larger. When the contact patterns in each mesh cycle extend to full tooth surface, the curve shape of LPMS will become regular;  
Figure 17: DTEs versus input speeds under different random cumulative pitch deviations conditions.  
* 2) vibration modulation phenomenon can be observed in dynamic responses of HGRS with random cumulative pitch deviation, and the random characteristic of cumulative pitch deviations makes the vibration frequency spectrum complex. When HGRS is under light load conditions, the amplitudes of some sideband frequencies are larger than that of MFIHs because of relatively high contact ratio. With the increase of load torque, the amplitudes of MFIHs will increase and become larger than that of sideband frequencies;
* 3) profile modification can reduce the amplitudes of MFIHs in DTEs and bear vibration acceleration. However, with the increase of the amplitude of cumulative pitch deviations, the effectiveness of profile modification in reducing system vibration will become weaker. In some working conditions, profile modification will lead to stronger system vibration for HGRS, owing to the increased amplitudes of sideband frequencies.  
Conceptualization, methodology, writing--original draft preparation, B.Y.; writing--review and editing, L.L.; funding acquisition, B.Y., G.L., and L.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (51535009), Natural Science Basic Research Program of Shaanxi (2020-JQS007), Scientific Research Program Funded by Shaanxi Provincial Education Department (20 JK0677) and National Key R&D Program of China (2018 YFB2001501).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Modification of BC with Low-Pressure Argon Plasma (LPArP)  
LPArP treatment of the BC membranes was performed using an HPT-100 Benchtop Plasma Treater (Henniker Scientific, Runcorn, UK). The process was carried out with argon as the process gas in the gas chamber, at a power of 100 W and flow rate of 10 standard cubic centimeters per minute (SCCM) that was constant in all experiments. To determine the optimal time for BC modification, the samples were treated with LPArP for various durations of 120, 240, 480, and 960 s from both sides.
## 5 Experimentation  
The controller-driven OppNet, which uses a quota-based multi-copy forwarding with a dynamic message replication limit, is named the control configuration (Control). The control configuration is compared with two _No-Control_ multi-copy baseline forwarding algorithms: epidemic (EP) and a quota-based algorithm (Static), both presented in Section 2.2. In epidemic routing, nodes forward messages to every encountered node to achieve maximum network coverage. Static routing sets a static upper bound of the number of message replicas in the network. It distributes half of these copies to each contact (provided the contact does not carry copies of the message yet) until the node has only one copy left, which will carry up to the destination. Both no-control approaches are multi-copy baseline forwarding algorithms considered for benchmarking in opportunistic networking research [30].  
This section describes how the control configuration performs. The experimentation methodology follows the guidelines pointed out by [PERSON] et al. [31], and [PERSON] et al. [32]: (1) appropriate mobility models to favour different congestion degree situations are designed; (2) our proposal is compared with benchmark multi-copy forwarding algorithms; (3) several performance metrics, listed in Section 5.1, are evaluated over the Control and No-Control configurations; moreover, the network performance is also evaluated for the Control configuration for different values of its configuration settings listed in Section 5.4.2; (4) the experimentation setup is detailed and well documented to be reproduced for benchmark purposes; and (5) the simulator provides the link model and the physical aspects are not considered.
## 2 Hybrid System and Techno-Economic Analysis Method
### The Design of Hybrid System Components
#### Inverter  
DC provided from a PV-FC based hybrid power system needs to be converted into AC to be served as AC load. The DC-AC converter is used, and the inverter's optimized sizing is performed by Homer optimization process based on power flow from PV-FC section. The inverter efficiency is considered as 90%, technical and economic data come from the manufacturer [68], where 250 $/kW capital cost, 150 $/kW replacement cost, and 10 $/year O and M cost. The life cycle is considered as 15 years.
# Si Photonics for Practical LiDAR Solutions
## 5 Other Si Photonics Use Cases for LiDAR
### Narrow Linewidth Tunable Laser  
A FMCW LiDAR demands a narrow linewidth laser because the temporal coherence length \(L_{coh}\) of a laser is inverse proportionally to its linewidth \(\Delta\
u\). For a laser with a Lorenztian optical spectrum, this relation can be described by [84]  
\[L_{coh}=\frac{2\ln 2}{\pi}\frac{c}{\Delta\
u}, \tag{8}\]  
where \(c\) is the speed of light. The maximum linewidth for a 400 m coherent length, the round trip of 200 m range, is about 300 kHz which is narrower than that of a typical DFB diode laser (several to tens of MHz). External cavity lasers or fiber lasers can achieve very narrow linewidth but their cost is usually quite high. Ranging beyond coherent length is possible through advanced digital signal processing [85] or using a referencing calibration system [86] at the expense of compute power or system complexity respectively. In addition, as shown earlier, Si photonics LiDAR often desire a wide band tunable laser to steer the optical beam in the FOV direction that a 1D phased array cannot steer. The adoption of such narrow linewidth and tunable lasers is greatly hampered by high cost as discussed in Section 4.1.3.  
A narrow linewidth laser and wide band tunable laser may potentially be addressed by using a Si photonics high Q and tunable cavity chip. There has been ongoing research on this topic in the past decade [87; 88; 89] and some companies are currently bringing it to telecom applications. The schematic design and the experimental results of an early work of such Si photonics external cavity tunable laser are shown in Figure 9. Such lasers can be made to achieve 100 kHz linewidth corresponding to around 1 km coherent length. The wavelength tuning range is as wide as 100 nm, mainly constrained by the gain spectrum of a gain chip. The 100 nm wavelength range, corresponding to 15-30\({}^{\circ}\) steering range, may be sufficient for certain applications. Many challenges still exist to bring this solution to automotive applications due to the stringent requirement on performance and reliability. Nevertheless, it presents the potential to bring down the cost of future wavelength scanning FMCW LiDAR.  
Figure 8: (**a**) Concept of FMCW with triangle chirped optical frequency modulation; (**b**) A simplified typical FMCW LiDAR system diagram. Adapted with permission from [64] © The Optical Society.
## 2 Methodology
### Data and Data Quality Requirements (Sources and Geography)  
As a standard practice in the LCA study, secondary data were extrapolated from international databases of scientific importance and reliability. In particular, the processes used for representing the resources, materials, and energies consumed (fuels included), and the road and transportation means utilized, were extrapolated from databases (Ecoinvent 3, Agri-footprint and US Life Cycle Inventory database (USLCI) available in the SimaPro software.
# Potato Leaf Disease Segmentation Method Based on Improved UNet
## 1 Introduction
It employs ResNet50 as the feature extraction front-end and incorporates the SE attention mechanism, resulting in SE-ResNet, which serves the purpose of feature extraction, to highlight potato leaf disease spot information while suppressing redundant information. Simultaneously, UNet is employed as the back-end network. The experimental results demonstrate that the proposed model meets the requirements in terms of metrics such as Dice and MIoU, achieving favorable segmentation outcomes for potato leaf disease spots.
# Free Space Optical Communication: An Enabling Backhaul Technology for 6G Non-Terrestrial Networks
### Airborne Nodes
Secondary batteries are charged in daylight to power overnight flights. Aquila was a highly ambitious and experimental Facebook project initiated in 2014. Facebook Aquila had a wingspan roughly the same as a Boeing 737 and weighed only around 400 kg. In order to power its four electric motors, solar cells were placed on the upper surface of the wing. Batteries were used for energy storage during night flights, accounting for half the aircraft's weight. The goal was to achieve continuous flight in the stratosphere for up to 90 days, providing internet access to an 80 km radius area below its flight path. In June 2018, Facebook halted the internal development of Aquila, despite successful test flights, and decided to focus instead on broadband connectivity projects in collaboration with Airbus. Aquila's legacy continued through partnerships and test flights with Airbus's Zephyr. In 2022, the Airbus Zephyr S successfully completed a test flight lasting an impressive 64 days, covering various states and countries [59]. Table 2 gives an overview of various space-borne and airborne communication systems, including GEO, MEO, LEO, HAPSs, and UAVs. The table outlines key factors such as altitude, latency, Earth coverage, number of required satellites/airborne nodes for coverage, advantages, disadvantages, and other characteristics. It highlights the varying degrees of deployment complexity, mobility and flexibility, coverage duration, payload capacity, and applications of these communication platforms.
###### Abstract  
A spillway is a structure used to regulate the discharge flowing from hydraulic structures such as a dam. It also helps to dissipate the excess energy of water through the still basins. Therefore, it has a significant effect on the safety of the dam. One of the most serious problems that may be happening below the spillway is bed scouring, which leads to soil erosion and spillway failure. This will happen due to the high flow velocity on the spillway. In this study, an alternative to the conventional methods was employed to predict scour depth (SD) downstream of the ski-jump spillway. A novel optimization algorithm, namely, Harris hawks optimization (HHO), was proposed to enhance the performance of an artificial neural network (ANN) to predict the SD. The performance of the new hybrid ANN-HHO model was compared with two hybrid models, namely, the particle swarm optimization with ANN (ANN-PSO) model and the genetic algorithm with ANN (ANN-GA) model to illustrate the efficiency of ANN-HHO. Additionally, the results of the three hybrid models were compared with the traditional ANN and the empirical Wu model (WM) through performance metrics, viz., mean absolute error (MAE), root mean square error (RMSE), coefficient of correlation (CC), Willmott index (WI), mean absolute percentage error (MAPE), and through graphical interpretation (line, scatter, and box plots, and Taylor diagram). Results of the analysis revealed that the ANN-HHO model (MAE = 0.1760 m, RMSE = 0.2538 m) outperformed ANN-PSO (MAE = 0.2094 m, RMSE = 0.2891 m), ANN-GA (MAE = 0.2178 m, RMSE = 0.2981 m), ANN (MAE = 0.2494 m, RMSE = 0.3152 m) and WM (MAE = 0.1868 m, RMSE = 0.2701 m) models in the testing period. Besides, graphical inspection displays better accuracy of the ANN-HHO model than ANN-PSO, ANN-GA, ANN, and WM models for prediction of SD around the ski-jump spillway.  
**Keywords:** artificial neural networks; genetic algorithm; particle swarm optimization; harris hawks optimization; scour depth; ski-jump spillway
## 3 Literature Review
### Identified Research Gaps and Agent-Based Perspective  
The existing body of literature demonstrates significant progress in the development of autonomous maritime systems, the application of artificial intelligence to maritime safety, and the technical foundations of real-time data processing. However, most reviewed studies treat these dimensions in isolation, focusing on specific technologies or functionalities rather  
Figure 1: Data flow in real-time AI processing for autonomous vessels (own elaboration).  
than on how they interact within fully autonomous systems under real-world operational and legal constraints.  
One critical gap lies in the lack of integrative models that capture how AI-based components operate collectively to ensure safety, efficiency, and regulatory compliance. While machine learning, computer vision, and sensor fusion are extensively studied, there is a paucity of research on agent-based architectures that embed these technologies within intelligent, real-time, and context-aware decision systems.  
Moreover, there is limited exploration of how such AI agents can perform the following tasks:  
1. Reason and act under uncertainty (e.g., degraded sensor input);
2. Negotiate legal constraints dynamically (e.g., SOLAS or MARPOL compliance);
3. Interact with humans and external systems (e.g., VTS, port infrastructure);
4. Adapt to evolving mission objectives or operational modes.  
Another key limitation in the current literature is the scarcity of scenario-based evaluations or case studies that illustrate how AI agents respond in realistic maritime situations. The absence of concrete examples hampers the ability to assess the maturity and limitations of proposed systems [68; 69; 70; 71; 72; 73; 74; 75; 76].  
In response to these gaps, this paper proposes a structured, agent-based perspective on autonomous maritime safety systems. In the sections that follow, we present a conceptual architecture for real-time AI agents, outline core functionalities, and explore illustrative operational scenarios to demonstrate their potential role in enhancing maritime safety.
## 3 Performance Analysis
### Channel Fading
#### 3.4.3 Rayleigh Fading Channel  
Communication is only feasible when signals are reflected, refracted, and scattered as they go from the source to the destination node when there is no LoS between them. A channel whose components are zero-averaged random variables with the same variances has the most detrimental impacts on the error performance of a system; in this case, the envelope of the signal will be distributed according to the Rayleigh distribution. It is possible to determine the receiver's PDF of SNR using a Rayleigh fading channel [41]  
\[f(\gamma)=\frac{1}{\overline{\gamma}}e^{(-\frac{\gamma}{\overline{\gamma}})}. \tag{19}\]  
Outage probability can be expressed as  
\[\begin{array}{ll}P_{out}&=P(\gamma<\gamma_{th})=\int_{0}^{\gamma_{th}}f_{ \gamma}(\gamma)d\gamma=\int_{0}^{\gamma_{th}}\frac{e^{(-\frac{\gamma}{\overline {\gamma}})}}{\overline{\gamma}}d\gamma\\ &\cong 1-e^{(-\frac{\gamma_{th}}{\gamma})}=1-e^{(-\frac{\gamma_{th}N_{0}(4\pi )^{2}d}{C_{R}G_{T}\lambda^{2}P_{T}})}.\end{array} \tag{20}\]
## 1 Introduction
Although SAC labels have been widely employed, fewer previous studies investigated WDM/SAC labels for packet switching in GMPLS networks. The existing WDM code switched networks are mostly based on time-spreading codes [19], which have completely different properties from SAC. Time-spreading OCDMA requires strict synchronization between the transmitter and receiver. The decoder has to be operated at the high chip rate to detect the short pulses. In this paper, we present a scheme of extended SAC labels for packet switching in GMPLS networks. This approach combines the advantages of WDM and OCDMA techniques. WDM networks have low network complexity, while OCDMA networks benefit from the high efficiency of bandwidth utilization. The extended SAC labels preserve the orthogonal property so that the effect of MAI shown at the decoder can be neglected. The extended SAC labels have lower cross-correlation values than the conventional labels for a given code length. Thus, the proposed labels have a good performance against PIIN. The node architecture to achieve simple processes of label generation/recognition is also investigated. We select a maximal length sequence (MLS) codes [20] with the cyclic-shift property to implement the optical labels. By combining MLS codes with the wavelength-routed property of arrayed waveguide grating (AWG), the node structure can be simplified. We employ numerical simulations to show the effectiveness of the proposed labeling scheme. To quantify the system performance, the power spectral density (PSD) of the stacked labels is analyzed to calculate the bit-error rate (BER). The rest of this paper is organized as follows. Section 2 outlines the construction processes of extended SAC labels and investigates their correlation properties. Section 3 illustrates the packet switching strategy and label distribution scenarios. Section 4 describes the node architecture for generating/recognizing the extended SAC labels. Section 5 analyzes network performance by calculating BER. Finally, Section 6 presents a conclusion.
# Proactive Scheduling and Routing of MRP-Based Production with Constrained Resources
## 1 Introduction  
In modern manufacturing environments, effective planning and scheduling remain critical challenges, especially in systems based on traditional Material Requirements Planning (MRP) or its successors such as Manufacturing Resource Planning (MRP II) and Enterprise Resource Planning (ERP). Although widely used, these systems often fall short when confronted with dynamic production demands, limited resources, and the need for rapid adaptation to order changes. Key limitations include the lack of real-time integration with actual production execution, the inability to account for machine and labor availability,and limited support for cost or time optimization. Moreover, the rigidity and high implementation costs of conventional ERP/MRP II solutions often make them unsuitable for agile production contexts.  
To address these shortcomings, we introduce a novel approach based on mathematical modeling--specifically, mixed-integer linear programming (MILP)--designed to enhance production planning by integrating proactive routing and scheduling capabilities. Unlike traditional MRP systems, our method incorporates additional constraints and decision variables that reflect the partial and time-dependent use of diverse resources, including tools, software, and human labor. It also dynamically traces the origin of demand for each component, minimizes idle time between operations, and supports adaptive routing under real-time conditions.  
Our contribution further includes an innovative model-size reduction technique that enables the computationally efficient generation of feasible and near-optimal production schedules. This framework facilitates both cost and time minimization and supports comprehensive feasibility assessments under various operational scenarios, such as resource downtimes or machine failures. By automating data exchange between MRP/ERP systems and the optimization engine, the proposed method offers a scalable and cost-effective alternative to expensive Advanced Planning and Scheduling (APS) systems, ensuring traceability and strategic flexibility in production.  
This paper proceeds as follows: Section 2 reviews the relevant literature to contextualize our contribution. Section 3 presents the optimization model and methodological details. Section 4 discusses implementation and computational results. Section 5 concludes with implications and future research directions.