esa-sceva/satcom-chunk-collection huggingface dataset:
# Video Interpolation-Based Multi-Source Data Fusion Method for Laser Processing Melt Pool
###### Abstract  
In additive manufacturing processes, the metal melt pool is decisive for processing quality. A single sensor is incapable of fully capturing its physical characteristics and is prone to data inaccuracies. This study proposes a multi-sensor monitoring solution integrating an off-axis infrared thermal camera with an on-axis high-speed camera to address this issue; a multi-source data pre-processing procedure has been designed, a multi-source data fusion method based on video frame interpolation has been developed, and a self-supervised training strategy based on transfer learning has been introduced. Experimental results indicate that the proposed data fusion method can eliminate temperature anomalies caused by single emissivity and droplet splashing, generating highly credible fused data and significantly enhancing the stability of metal additive manufacturing and the quality of parts.  
additive manufacturing; laser welding; melt pool monitoring; multi-source data fusion; video frame interpolation 2025  
[PERSON]; [PERSON]; [PERSON]; [PERSON] Video Interpolation-Based Multi-Source Data Fusion Method for Laser Processing Melt Pool. _Appl. Sci._**2025**, 15, 4850. [[https://doi.org/10.3390/appl/15094850](https://doi.org/10.3390/appl/15094850)]([https://doi.org/10.3390/appl/15094850](https://doi.org/10.3390/appl/15094850))  
(c) 2025 by the authors.  
Liomasce MDPI, Basel, Switzerland.  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
# Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks
## 3 Methodology
### Simulation Setup
#### 3.1.4 Step 4: Define QoS Metrics  
* Select the specific QoS metrics you want to evaluate based on our research goals. Common QoS metrics in WSN simulations include Packet Delivery Ratio (Reliability), End-to-End Delay (Latency), Throughput, Network Lifetime and Coverage.
# Application of Virtual Reality for Learning the Material Properties of Shape Memory Alloys
###### Abstract  
A shape memory alloy (SMA) is an alloy which can eliminate deformation at lower temperatures and restore its original shape upon heating. SMAs have been receiving considerable attention in the research field of materials science, and their applications include robotics, automotive, aerospace, and biomedical industries. Observing the SMA's shaping and restoration processes is important for understanding its working principles and applications. However, the transformation of its crystal structure with temperature can only be seen using special equipment, such as a transmission electron microscope (TEM), which is an expensive apparatus and the operation requires professional skills. In this study, a teaching module is designed using virtual reality (VR) technology and research results of an SMA to show its shape memory properties, shaping and restoration processes, as well as the real-life applications in an immersive and interactive way. A teaching experiment has been conducted to analyze students' learning effectiveness using the teaching module (the experimental group) compared with that of using real SMA materials as the teaching aids (the control group). Two classes of students in the Department of Materials Science (one as the experimental group and the other as the control group) were selected as the samples by convenience sampling from a university in North Taiwan. The experimental group contained 52 students and the control group contained 70 students. A nonequivalent pretest-posttest design was adopted to explore whether the two groups had a significant difference in learning effectiveness. The experimental results reveal that the teaching module can improve the learning effectiveness significantly (\(p\) = 0.001), and the questionnaire results also show that a majority of the students had positive attitudes about the teaching module. They believed that it could increase their learning motivation and help them understand the properties and applications of the SMA.  
virtual reality (VR); shape memory alloy (SMA); transmission electron microscope (TEM); austenite; martensite +
Footnote †: journal: Applied Physics Letters  
_Article_
## 5 Performance Analysis
### Numerical Simulation
#### 5.2.5 Multipath Performance  
Multipath interference is one of the main sources of error in satellite navigation [34]. For a multipath situation with one direct path and one reflected path with a multipath-to-direct ratio of \(-6\) dB, an early-late spacing of 10.2 ns for ACE-BOC(12,1), 8.15 ns for ACE-BOC(15,10) and ACE-FHBOC(24:1:6,1), 9.8 ns for ACE-FHBOC(24:1:1,1), Figure 16 shows the simulated NELP multipath error envelopes versus the multipath delay for the example signal. When the multipath delay is less than 30 m, the most common multipath delay in urban environments [35], the error envelopes for ACE-FHBOC(24:1:1,1) is the smallest among the example signals, and the error envelopes for ACE-FHBOC(24:1:6,1) are smaller than those for ACE-BOC(15,10) and ACE-BOC(12,1).
# Analysis and Experimental Validation of Efficient Coded OFDM for an Impulsive Noise Environment
## 2 System Overview
### Description
#### 2.1.2. OFDM  
OFDM is a multi-carrier modulation largely employed in wired systems, Power-Line Communications (PLC) [22; 23] and wireless standards systems (e.g., Digital Video Broadcasting-Terrestrial (DVB-T) [24], Wimax, IEEE 802.11a/g/n/ac [25]). The high data rates and robustness to combat multi-path fading make OFDM a perfect candidate for reflective industrial environments [26]. Instead of transmitting a high-speed data stream over a single carrier, OFDM utilizes many orthogonal sub-carriers transmitted in parallel. In our case, the number of sub-carriers is \(C=64\). Each sub-carrier is modulated with a BPSK encoded matrix. An \"OFDM symbol\" is formed by each column of this matrix. The output denoted \(F\) is as follows:  
\[F=\begin{pmatrix}f_{1,1}&f_{1,2}&\cdots&f_{1,t}\\ f_{2,1}&f_{2,2}&\cdots&f_{2,t}\\ \vdots&\vdots&\vdots&\vdots\\ f_{s,1}&f_{s,2}&\cdots&f_{s,t}\end{pmatrix} \tag{4}\]  
where:  
* \(f_{ij}\) represents the tone of frequency i and time slot j,
* \(s\) corresponds to the sub-carriers used,
* \(t\) is the number of OFDM symbols sent on the channel.
## 4 Analytical Model of EMP Emission and Theoretical Results
The electric field of the generated EMP is directly dependent on the second-order time derivative of \(P\): \(S\ltimes P^{\prime\prime}\). The temporal dependence of \(Q\) appearing in Equation (2) is related to the neutralization current intensity \(I=Q^{{}^{\prime}}\) (Figure 7a (a--top plot/left)), and thus the source term is directly related to the variation rate in time of the neutralization [42] current intensity, \(S\ltimes P^{\prime\prime}=2L\dot{I}^{{}^{\prime}}\). The temporal dependence of the source term for the Ag target of 10 \(\upmu\)m thicknesses is presented in Figure 7a (a--bottom plot). The Fourier transform of S was finally calculated in MATLAB to obtain the EMP spectrum. The calculated spectra of S are presented in Figure 7b. One can note a good qualitative agreement between the numerical data and the experimental data presented in Figure 6b: the continuum EMP spectra have a maximum at 0.6 GHz and the EMP amplitude (given by the area under the spectrum curve) is higher when the EMP is emitted from the thinner targets and larger \(\rho/Z\) materials. We finally calculated and plotted in Figure 8 (bottom plot) the EMPA as a function of AEME (as measured experimentally), for all targets of different thicknesses and different materials. The experimental dependence is presented in Figure 8 (top plot). One can note a good qualitative agreement between the numerical and experimental data: the EMPA increases linearly with the AEME, regardless of the target material or target thickness, and the EMPA for the 4 \(\upmu\)m thick Ag target is approximately 5 times larger than the EMPA from the 10 \(\upmu\)m Ag target. The linear fitting curve for the experimental data presented in Figure 8 is written as:  
\[EMPA(\mathrm{kV/m})\approx 15 AEME(\mathrm{MeV})-120 \tag{3}\]  
Figure 7: (**a**) Numerical results on the EMP source. Top plot: temporal dependence of target charge \(Q\) (**right-red**) and the corresponding electronic current intensity \(I\) (**left-blue**) for the 10 \(\upmu\)m Ag film. Bottom plot: the source term \(S\ltimes P^{\prime\prime}\) of the EMP for a 10 \(\upmu\)m Ag target. (**b**) Calculated spectra of EMP radiation from targets of different materials and different thicknesses. Equation (3) indicates a linear dependence of the EMPA on AEME, with a correlation coefficient of 15 between the two quantities for the specific experimental conditions employed here. The result demonstrates a direct method to evaluate the energy of the laser-accelerated electrons: by monitoring the GHz EMP signal, which can be performed non-invasively in the reaction chamber, we can monitor in real-time the maximum energy of the laser-accelerated electrons. Of course, preliminary EMP and electron energy measurements would have to be performed and correlated in similar experimental conditions in order to calibrate the model parameters for the specific experimental system and conditions, for reasonable use of such a monitoring technique.
###### Abstract  
The generation of functional osteoblasts from human somatic cells could provide an alternative means of regenerative therapy for bone disorders such as osteoporosis. In this study, we demonstrated the direct phenotypic conversion of human dermal fibroblasts (HDFs) into osteoblasts by culturing them in osteogenic medium supplemented with valpro acid (VPA), a histone deacetylase (HDAC) inhibitor. HDFs cultured with the VPA in osteogenic medium exhibited expression of alkaline phosphatase and deposition of mineralized calcium matrices, which are phenotypical characteristics of functional osteoblasts. They also expressed osteoblast-specific genes such as alkaline phosphatase, osteepontin, and bone sialoprotein, which demonstrated their direct conversion into osteoblasts. In addition, co-treatment with VPA and a specific inhibitor for activin-like kinase 5 (ALK5i II) had a synergistic effect on direct conversion. It is considered that the inductive effect of VPA on the conversion into osteoblast-lineage is due to the opening of the nucleosome structure by HDAC inhibitor, which facilitates chromatin remodeling and cellular reprogramming. Our findings provide a novel insight into the direct conversion of human somatic cells into transgene-free osteoblasts with small chemical compounds, thus making bone regeneration using cellular reprogramming strategy more clinically feasible.  
Keywords:direct conversion; osteoblast; histone deacetylase inhibitor; valpro acid; inhibitor for activin-like kinase 5 +
Footnote †: journal: Applied Sciences
# Federated Learning for Maritime Environments: Use Cases, Experimental Results, and Open Issues
###### Abstract  
Maritime transportation is crucial for global trade and responsible for the majority of goods movement worldwide. The optimization of maritime operations is challenged by the complexity and heterogeneity of maritime nodes. This paper presents the emerging deployment of federated learning (FL) in maritime environments to address these challenges. FL enables decentralized machine learning model training, ensuring data privacy and security while overcoming issues associated with non-i.i.d. data. This paper explores various maritime use cases, including fuel consumption reduction, predictive maintenance, and just-in-time arrival. Experimental results using real datasets demonstrate the superiority of FL in predicting the fuel consumption of large cargo ships in terms of accuracy and spatiotemporal complexity over traditional collaborative machine learning approaches. The findings indicate that FL can significantly improve the performance of fuel consumption models in a collaborative way, while ensuring data privacy preservation and no data transmission during the learning process. Finally, this paper discusses open issues and future research directions necessary for the widespread adoption of FL in maritime transportation and settings.  
federated learning; machine learning; maritime communication networks; maritime industry; maritime transportation; security and privacy
## 4 Data Set Generation and Processing
### GNSS Receiver Configuration and Generated Digital Artifacts  
The experiment utilizes a Septentrio Mosaic X5 GNSS receiver for real-time data acquisition and logging, which generates the \(C/N_{0}\) time series per satellite at a frequency of 1 Hz. This metric measures the signal strength of each tracked satellite relative to the background noise level. \(C/N_{0}\) indicates a strong capability to accurately track and decode satellite data.  
An example of the impact of the interference on the GNSS \(C/N_{0}\)s artifacts is shown in Figure 5.  
The presence of spikes can be noted in Figure 5. These spikes are due to the Automatic Gain Control (AGC) algorithm employed in the Septentrio Mosaic X5 GNSS receiver. Septentrio is based in Leuven, Belgium. This algorithm dynamically adjusts the gain level to maintain a consistent signal strength, leading to temporary increases when the signal weakens corresponding to the observed \(C/N_{0}\) spikes. Other m  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Interference Type** & \(\mathbf{L_{I}}\) **= H (High)** & \(\mathbf{L_{I}}\) **= M (Medium)** & \(\mathbf{L_{I}}\) **= L (Low)** \\  & **Attenuation Value** & **Attenuation Value** & **Attenuation Value** \\ \hline Gaussian Noise & 10 dB & 20 dB & 30 dB \\ \hline Wideband Chirp & 10 dB & 20 dB & 30 dB \\ \hline Narrowband Chirp & 0 dB & 5 dB & 10 dB \\ \hline \hline \end{tabular}
\end{table}
Table 2: Definition of the power levels of interference and related attenuation level in the variable attenuator.  
Figure 4: GNU radio flow graphs for the narrow chirp generation (signal source frequency set to 1 KHz).  
the GNSS receiver, which may influence the \(C/N_{0}\) generation, are the carrier notch filters (which attenuate narrowband interference around the GNSS carrier frequency), integration time (affects smoothing of \(C/N_{0}\) plots), and GNSS selection (allows focusing on specific constellations). We use the default settings for the GNSS receiver. The selected timing source is the GPS constellation.
## 4 Application in Circular Model Selection with Significant Challenges
### Discussion  
This section illustrates the three distinct packaging scenarios to demonstrate the implications of choosing highly sustainable packaging. It highlights the crucial role of SMEs, which are currently shifting from traditional manufacturing into mass-customized manufacturing due to global competition. Additionally, to get government funding, most SMEs are also attempting mass-customized CE to produce sustainable product lifecycles. As a result, choosing a highly sustainable packaging method depends on multiple factors. Therefore, in this study, we created a \(Z\)-number-based decision-making technique to choose a highly sustainable packaging model. This approach empowers SMEs to play a significant role in the sustainable packaging shift, as they must overcome significant challenges by proactively anticipating unforeseen events, streamlining procedures, and implementing new technology. The ZF-DEMATEL-TOPSIS integrated GMCDM approach is a proposed method for identifying highly sustainable packaging models with significant challenges that significantly affect SMEs' ability to produce sustainable product lifecycles in mass-customized CE initiatives. Based on the suggested method, the recyclable packaging model is highly sustainable. The primary challenges to producing mass-customized CE in SMEs are production cost, energy efficiency, and makespan. This study provides insightful information for SMEs in India, especially for those operating in sectors like manufacturing, supply chain management, and sustainable development. The study's examination of the integration of MC and CE is highly significant to the Indian context, where a growing focus is placed on environmentally conscious manufacturing, circular economy models, and customized products.
## 3 Related Works  
### THz Radio Wave Generation and Advancements in WNoC  
Over the last decade, various experimental setups have been conducted in the THz band involving the generation, transmission, and reception of THz signals. One such experiment, as described by [25], involved generating a frequency band between 0.585 and 0.653 THz, which was upconverted from 12.2 and 13.6 GHz using a 1 mW source. This source consisted of four cascaded frequency doublers followed by a frequency tripler, all based on biased Schottky diodes, feeding into a horn antenna. Likewise, another fixed wireless link, as reported by [26], uses a 0.24 THz carrier frequency for transmitting over a distance of 850 m. This setup integrated a commercial 20 GHz signal generator with a frequency multiplier. In [27], the authors focused on THz communication channel modeling and propagation. This involved the use of an autonomous transmitter and receiver that utilized a subharmonic mixer to upconvert a 10 GHz signal to 300 GHz. The signal was then transmitted using a horn antenna. Another experiment [28] achieved the transmission of an 8K resolution video using a resonant tunneling diode (RTD) paired with a bow-tie antenna at a 0.3 THz frequency. Meanwhile, the TeraNova testbed, developed by [29], demonstrated wireless communication at a 1.02 THz frequency using a PS Keysight signal generator. The signal was upconverted to the THz band through a Schottky-diode-based frequency multiplier chain and transmitted and received using directional diagonal horn antennas. Lastly, a plasmonic nano-transceiver for the THz band proposed by [30] is based on a high electron mobility transistor (HEMT) and enhanced with graphene material.  
Research conducted by [31] utilizes multiple antennas on a single substrate carrier to analyze intra-chip wireless communication within the 10-75 GHz frequency range. Another proposed system for a wireless communication system in the THz band by [32] employs OOK modulation and standard WR-3.4 horn antennas for transmitting and receiving in chip-to-chip communication systems. A novel wireless interconnect structure, WCube, proposed in [33], incorporates a single transmitting antenna and multiple receivers within a polyimide layer. This configuration demonstrates an improvement in a channel loss of 20-30 dB compared with silicon substrates and was analyzed using Ansys HFSS software in the 0.1-0.5 THz frequency bands. Additionally, chip-scale THz propagation modeling performed by [34] uses a Hertzian dipole antenna to achieve results of 0.95 Tbps with enhanced reliability, suggesting that thinning the underfill layer could improve the path gain. Lastly, a ray-tracing multipath propagation channel model developed by [35] for WNoC within a flip-chip package indicates that intra-chip channel capacity can exceed 1 Tbps over a transmission distance of 5 mm, which then decreases to 0.382 Tbps as the distance extends to 40 mm.
## 1 Introduction  
Because of the exponential growth of cloud computing over the last 10 years, multiple corporations and business sectors have transitioned to the cloud to ensure transparency, scalability, and accessibility [1]. Most people are switching to the cloud due to cost savings and complex resource distribution. In a cloud environment, the corresponding infrastructure is managed and handled by cloud providers [2]. However, several challenges in cloud computing require resolution before the true implementation of the cloud. Among them, resource management or load balancing in cloud computing has become a big challenge. Load balancing is a technique for spreading the burden on several machine assets via network connections to achieve optimum resource efficiency and minimal data analysis time, and to prevent overloading. Load balancing implies that at any moment all processors in the system, as well as in the network, will perform almost the same amount of work [3]. Different load-balancing algorithms have been discussed in the literature.  
This study provides a performance evaluation of various load-balancing algorithms in a cloud computing environment. For this purpose, a cloud analyst has been used for the implementation. There are several analysis simulators available that can be used for testing environments and these tools support testing the output of scaling apps on the Internet [4]. This paper has added load-balancing algorithms into cloud analyst simulators and performed the analysis with different service broker policies in the cloud environment using CloudAnalyst. Load-balancing algorithms can be implemented in various sectors such as artificial neural networks, function optimization, and fuzzy control of the system. Additionally, they can be used to schedule a straightforward workflow in cloud-based virtual machines [5].  
Organization. The rest of the paper is organized as follows. In the next section, we put our work into context concerning related work, and Section 3 is based on research methodology. In Section 4, we present our experimental results, and Section 5 is based on the discussion. We conclude in Section 6.