esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods  
The design of the urban digital twin was based on an advanced digital architecture, focused on creating an interactive virtual environment to support environmental analysis, strategic planning, and eventually accommodating forecast simulation models. The system is fully open, allowing the uploading of pre-processed data for customized forecasts. The construction of the system was articulated in several stages, starting with the selection of the most suitable technological platform and ending with the integration of data from different, highly specialized sources. For this experimental research, the Cesium Ion platform was chosen--an open-source platform that allows visualization, management, and analysis of 3D geospatial data. The following diagram (Figure 1) functionally summarizes the various steps followed in the design and development of the proposed experimental system:  
The process described is divided into several phases: The first phase involves the collection and cataloging of data useful for the planned simulations. The data collected for characterizing a process or a physical phenomenon is often of various types and comes from different sources. Therefore, efficient collection and cataloging are necessary to avoid redudancy or missing data. The second phase is mainly dedicated to the processing and integration of this heterogeneous data, which must be communicated within a single interoperable system. The third phase is focused on the creation of a physical model that not only represents the data but also allows their interaction, allowing them to evolve based on the results that need to be achieved. This allows progression to phase four, the management phase, in which it is possible to analyze the current state of the phenomena that characterize the digital twin. Phases five and six are closely interconnected. Starting from the mapped and analyzed current state, they aim to create future or hypothetical scenarios and projections that can support proactive territory management, facilitating decisions based on data and forecasts.  
Figure 1: Research flow.  
In order to apply the proposed technology, two phenomena closely linked to industrialization, global warming, and climate change were evaluated: light pollution and hydrogeological risk.  
In relation to public lighting, the aim of this work was to conduct advanced simulations to analyze different aspects of the public lighting network, specifically examining the influence of lighting on the concentration of CO\({}_{2}\) in a densely populated urban center and their close correlation. In relation to hydrogeological risk, the aim was to evaluate the effect of climate change on flood-related risks. The results show the experimental methodology and propose the creation of representative models of such phenomena, which still require in-depth studies.
# Finite-Time Tracking Control of a Flexible Link Manipulator Based on an Extended State Observer
## 4 Simulation and Experimental Verification  
In this section, in order to verify the effectiveness of the proposed adaptive ESO and the adaptive sliding mode controller based on the ESO, numerical simulation and physical experiments are carried out on the Quanser Flexible Link System, as shown in Figure 2. Then, according to the nominal parameters of [24], the state space equation of the system is calculated as follows:  
\[\left\{\begin{array}{l}\dot{x}_{1}=x_{2}\\ \dot{x}_{2}=-40.32x_{2}+623.74\alpha+61.63v+d.\end{array}\right. \tag{47}\]
###### Abstract
For a binaural recording with a conventional artificial head, on the other hand, the recording can be presented only for a fixed head orientation of the listener, namely, the orientation of the artificial head during the recording. Previous studies [12; 13] reported good perceptual performance of the VAH in dynamic scenarios for speech signals with respect to different perceptual attributes, including the perceived source position. The evaluations were based on direct comparisons between binaural VAH signals played back through headphones and signals from real sources. In those studies, non-individual binaural signals generated with binaural room impulse responses (BRIRs) of a conventional artificial head were evaluated as well. Dynamic presentation was artificially enabled by BRIRs measured for different head-above-torso orientations of the artificial head, which is quite unrealistic and different from the typical application of an artificial head in practice. The signals generated with such non-individual BRIRs also showed good perceptual performance. Since in [12; 13], the subjects could see the real sources in the room, the first open question was to which extent the visual information about the sound sources contributed to the successful performance of the VAH and the non-individual binaural signals, especially with respect to the perceived source position. The second open question concerned the possibly positive impact of head tracking on the perceptual results. This paper aims to answer both questions. The paper consists of two parts. In Part I, localizing virtual sources in the absence of visual cues is assessed. A localization experiment was performed with dynamically presented virtual sources generated with VAH technology and with a conventional artificial head (the same artificial head as evaluated in previous studies [12; 13]). Subjects were asked to localize the virtual sources while listening to dynamic headphone signals in the darkness, i.e., without being supplied with any visual information about the sources. Subjects mapped the perceived source position on a graphical user interface (GUI). The same localization test was also performed with hidden real sound sources in order to verify the GUI employed. In Part II, the impacts of dynamic presentation on the localization performances attained via virtual sources generated with VAH technology and the conventional artificial head, were assessed by two separate localization experiments, one with and one without head tracking. The paper continues in Section 2 with a review of the methods and parameters used to calculate the individual VAH spectral weights. Sections 3 and 4 present the methods, and the results and discussion of the results for both localization experiments. Finally, some general discussion is offered in Section 5.
# Advances in Fermentation Technology: A Focus on Health and Safety
## 3 The Effectiveness of Innovative Methods in Fermented Food Safety Assurance
### Smart Packaging and Sensor Technology for Supply Chain Monitoring  
Smart packaging significantly advances food supply chain management by improving safety and quality through integrated sensors, indicators, and communication systems for real-time monitoring during transit and storage [115]. Benefits include enhanced traceability, reduced food waste, and improved consumer satisfaction, which is particularly crucial for perishable items like fermented foods. Continuous monitoring helps ensure safety throughout the supply chain [116; 117; 118]. As the field continues to evolve, smart packaging is poised to revolutionise food preservation and distribution practices.  
Smart packaging equipped with time-temperature indicators and gas sensors enables ongoing feedback on product quality, facilitating early detection of spoilage or microbial growth. These materials monitor temperature, humidity, microbial growth, oxygen levels, pH, and chemical composition within packaged food, ensuring food safety throughout storage and transit. Active functions include ethylene and oxygen absorption and humidity control. In fruits and vegetables crucial for fermentation, smart technologies utilize freshness sensors and active strategies to minimize decay [119; 120; 121]. These innovations aim to minimise food losses, reduce waste in fruits and vegetables by monitoring environmental conditions in real-time, improve food quality and safety, and extend shelf life during distribution and storage, which is especially significant due to fermented foods' often limited shelf life. However, challenges remain, including cost considerations, consumer acceptance, and regulatory aspects, which need to be addressed for commercial sustainability [122].  
Incorporating agents like oxygen scavengers and moisture absorbers, these systems also employ phase change materials to maintain optimal temperatures. Smart applications enhance consumer understanding of expiration dates and inventory management [123]. Although various sensing systems based on food quality indicators are proposed, commercial application challenges remain. Future research should address safety concerns, legal regulations, and cost management to promote the broader adoption of intelligent packaging technologies specifically designed for the fermentation industry.
# ATWin: An Improved and Detailed Startup Model of TTP/C
## 2 Background Work and Literature Review  
### TTP/C  
The fundamental component of the TTA is the node that accesses a shared medium in a time division multiple access (TDMA) manner. TTP/C, standardized by AS6003, follows the basic design principles of TTA. The node of TTP/C, called the smallest replaceable unit (SRU), consists of a host, a controller network interface (CNI), and a communication controller (CC). Multiple SRUs are combined to form a fault-tolerant unit (FTU) [24]. The message descriptor list (MEDL) is responsible for setting the control signal. The bus is the primary network topology of TTP/C, with two redundant communication channels. Each channel has an optional centralized bus guardian (BG) that can be combined to form a centralized bus guardian system [25; 26].  
TDMA enables each controller to transmit and receive frames during a predetermined time interval specified by the GTB, as seen in Figure 1. For each node, the time interval specified by GTB is called a slot, whose duration is represented by \(\Delta_{slot}\). The slots periodically repeat in a TDMA round, and the periodically repeating TDMA round is called a cluster cycle. Each slot comprises multiple phases. In the pre-transmission preparation phase (PSP), the node reads the scheduling information of the slot and the attribute configuration of the node from MEDL. If a node is ready to transmit the data frame, the data transmitted or received during the upcoming transmission phase (TP) must be prepared during the PSP phase, whose duration is indicated by \(\Delta_{PSP}\). The \(\Delta_{TP}\) indicates the duration of the TP phase. During the post-receive phase (PRP), the TTP/C processes the received data, and performs corresponding protocol services. \(\Delta_{PRP}\) indicates the duration of the PRP phase in a slot. The action time (AT) denotes the moment when the node sends or receives a frame. The idle phase (IDL) may not exist, which is generally merged into the PRP phase.
## 7 Optimization of the Four-Layer Three-Segment Tube
### Pattern Generation and ANN Training
The details concerning pattern generation are summarized in Table 9. The length of time required to generate one pattern is shorter than that in the previous case of MODEL1 optimization since the sparse FE mesh was applied (the number of finite elements is four times smaller than that in the case of the dense FE mesh). The minimum and maximum values of the first ten natural frequencies (in [Hz]) that could be found in the pattern sets are \(f_{1}\in(50.25,90.31)\), \(f_{2}\in(54.31,95.91)\), \(f_{3}\in(67.97,109.47)\), \(f_{4}\in(74.77,116.65)\), \(f_{5}\in(91.03,151.66)\), \(f_{6}\in(92.87,152.67)\), \(f_{7}\in(110.16,169.93)\), \(f_{8}\in(110.41,175.39)\), \(f_{9}\in(121.12,179.44)\), and \(f_{10}\in(128.03,212.70)\). Two deep networks were trained for \(f_{1}\) maximization, and the difference between them is the number of learning patterns: ANN\({}_{1}^{1}\) was trained with 4096 patterns, while ANN\({}_{123}^{1}\) was trained with 8,921 patterns. Another two, ANN\({}_{123}^{10}\) and ANN\({}_{1234}^{10}\), were trained for the maximization of the distance between natural frequencies and a selected frequency.
# Hard-Decision Coded Modulation for High-Throughput Short-Reach Optical Interconnect
## 4 Numerical Analysis for an Optical Transmission System  
In this section, numerical results of optical fiber transmission are presented by considering the channel block in Figure 2 as a nonlinear optical channel. As shown in Figure 2, the simulated system consists of an optical link comprising either unrepeated single standard single-mode fiber (SSMF) span \(N_{sp}=1\) or multiple SSMF spans with erbium-doped fiber amplifier (EDFA). The investigated link lengths are the typical distances of data center interconnects (\(<\) 200 km), metro, and regional links (200-1000 km). To support the targeted net data rates of \(>\)600 Gbit/s and \(>\)400 Gbit/s per wavelength for these two distance ranges above, two sets of constellations are investigated. The first set uses 256 QAM and 256-GS for single span transmission, and second set uses 64 QAM, 128 QAM, 64-GS, and 128-GS for multi-span transmission. The fiber propagation is simulated through the split-step Fourier method numerical solution of the nonlinear Manakov equation, where the step size was uniformly set to 0.1 km. The maximum-reach gains are defined as the reach increase observed at fixed net data rate when switching from 64 QAM, 128 QAM, and 256 QAM constellations to 64-GS, 128-GS, and 256-GS. The QAM or GS symbols are independently modulated over the two orthogonal polarization channels via polarization multiplexing. The simulation parameters are shown in Table 1.  
Figure 6: AIRs and operational CM rates vs. SNR for post-SCC BER \(<1\times 10^{-6}\).
## 4 Simulation Results and Discussion
### Path Planning in a Dynamic  
In real working scenarios, the mobile robots are usually faced with environmental changes--one or more unknown obstacles appear. To ensure the mobile robot works well, the state-of-the-art path planning methods present solutions to respond to the unknown information and adjust the original path by considering the unknown information. In this sub-section, we employ the proposed APF-IRRT* algorithm to perform the on-line path planning in the test environment M5 where some unknown random static obstacles appear on the known path.  
To complete the experiment, we perform the path planning as the following steps: First, we perform the off-line path planning in the known test environment M5 in which information is described in Table 1. An average path length of 268.01 m from the start point to the target point is obtained. Next, when the mobile robot travels along the original path at position (120, 60), the mobile robot senses a new obstacle. It calculates the obstacle position and re-plans a new feasible path to avoid collision with the obstacle, as shown in Figure 8(b). Then, when the mobile robot travels along the new path at position (190, 85), the mobile robot senses another obstacle. Again, the mobile robot calculates the second obstacle position and re-plans another feasible path to avoid collision with the second obstacle, as shown in Figure 8(c). Finally, the mobile robot travels along the latest path to the target point, as shown in Figure 8(d). The total path length from the start point to the target point is 285.54 m.
## 3 Results and Discussion  
For the purpose of verifying the correctness and accuracy of the analytical model, experimental measurements were performed on the hydraulic system in the industrial facility. Its basic dimensional parameters are listed in Table 1.  
In the measured sections with a steady water flow, the data required for calculating the pipe coefficients were obtained. They were used to calculate the flow rates in the pipeline over a 10 h interval of operation. This facilitated comparing the measured data with the computational model. Subsequently, various simulations of water withdrawal in the industrial enterprise with subsequent regulation of the system at variable values of coefficient \(\varepsilon\) were analysed.
# Influence of Aggregate Gradation on the Engineering Properties of Lightweight Aggregate Concrete
## 1 Introduction  
Generally, normal-weight concrete (NWC) aggregate gradation should fit in with the standard code requirements. The main purpose is to enable finer concrete workability and make the aggregate collection tighter. A tighter aggregate collection indicates that the concrete contains more aggregate and less paste. Hence, the unit weight and achievable concrete strength can be higher. Lightweight aggregate concrete (LWAC) mix-proportion design criteria is established in many standard specifications, such as ACI 318 of US, DIN of Germany, JIS of Japan, CNS 12891 of Taiwan, etc. In addition to lightweight aggregate (LWA) consideration, the aggregate gradation is generally in accordance with NWC [1; 2; 3]. For example, the criteria for the structural aggregate gradation of the structural LWAC in the American Society for Testing and Materials (ASTM) C330 specification refer to the ASTM C33 specification. The gradation prescriptions for \"Lightweight aggregates for structural concrete\" from CNS 3691 in Taiwan is similar to that for \"Concrete aggregates\" in CNS 1240 for NWC. However, for LWAC, when a higher quantity or coarser aggregate particle size is used, the unit weight of the concrete could be reduced, but negative effects on the concrete strength might occur.  
Over the past decades, a number of experimental research projects have been conducted to study the properties of LWA, as well as the associated engineering properties of LWAC. They indicated that the engineering properties of LWAC are affected by several parameters, like the water-to-cement ratio,age, curing conditions, strength and elastic modulus of the aggregate, aggregate types, volume fraction of the aggregate, etc. [4; 5; 6; 7; 8]. In recent years, analytical methods of data-driven models have also been of increasing interest in evaluating the concrete compressive strength such as artificial intelligence based techniques like artificial neural network [9; 10] and adaptive network-based fuzzy inference systems (ANFIS) [11; 12]. However, these studies do not distinctly study the effect of LWA aggregate gradation. Therefore, whether the gradation prescriptions for LWAC should parallel that for NWC or not should be further investigated. This research manufactured concrete using various aggregate grades. The engineering properties were determined to investigate the effects of various aggregate grades on concrete properties.
## 4 Conclusions  
This study presented a hybrid modeling approach for predicting surface roughness (Ra) in laser cutting by combining response surface methodology (RSM) with machine learning-based residual correction. A quadratic RSM model was initially developed using a Box-Behnken design, with cutting speed, laser power, and auxiliary gas pressure as input parameters. Although the RSM model achieved a reasonable fit (R\({}^{2}\) = 0.8227), it showed limitations in capturing certain nonlinear relationships between the predicted and experimental values. To address this, a regression tree algorithm was applied to model the residuals of the RSM predictions, resulting in a significant improvement in accuracy. The final hybrid model demonstrated enhanced predictive performance, achieving an R\({}^{2}\) of 0.8889 and a reduced RMSE compared to the standalone RSM model.  
Leave-one-out cross-validation (LOOCV) further confirmed the model's generalization capability, yielding an RMSE of 0.3241 \(\upmu\)m and an R\({}^{2}\) of 0.6039. Although lower than the training performance, these results validate the model's robustness when applied to limited experimental datasets. Comparative analysis with existing approaches such as random forest (RMSE = 0.05 \(\upmu\)m, R\({}^{2}\) = 0.91) demonstrated the competitiveness of the proposed hybrid method, particularly in balancing predictive accuracy and interpretability.  
The findings underscore the benefits of integrating classical statistical techniques with machine learning for modeling complex manufacturing processes. The hybrid approach not only enhances prediction accuracy but also preserves interpretability, making it suitable for real-world applications where data availability is limited. Future research could explore the integration of alternative machine learning algorithms or extend this methodology to additional machining parameters and material types.  
Conceptualization, D.R.; Methodology, M.S.; Investigation, B.S.; Resources, M.T.; Writing--original draft, M.M.; Writing--review and editing, D.R. All authors have read and agreed to the published version of the manuscript.  
This research has been supported by the Ministry of Science, Technological Development and Innovation (Contract No. 451-03-137/2025-03/200156) and the Faculty of Technical Sciences, University of Novi Sad, through the project \"Scientific and Artistic Research Work of Researchers in Teaching and Associate Positions at the Faculty of Technical Sciences, University of Novi Sad 2025\" (No. 01-50/295).  
Not applicable.  
All data supporting the findings of this study are included in the article.  
The authors declare no conflicts of interest.
## 1 Introduction
In this paper, efficient reversible data-hiding systems are proposed by using new fluctuation functions and rate-matched RS codes. The estimated bits of the fluctuation functions are more correct since boundary pixels and average distance are used for calculation. With the help of the error-correcting capability of RS codes, the embedded message can be recovered correctly. In order to efficiently correct the errors according to weak spatial correlation, RS codes based on the BM algorithm are considered for decoding. In the bit error rate (BER) results of three different images, our proposed system showed better performances than the data-hiding systems. Peak signal to noise ratio (PSNR) performances were also shown in the experimental results. To check the performance enhancements, fundamental RDH systems are considered as referenced systems, but our fluctuation functions or coding schemes can be applied to recently-published RDH systems with modifications.