esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Multi-Physical Data Approaches
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Database Name** & **Description** & **Advantages** & **Limitation** \\ \hline \hline MELD (Multimodal Emotion Lines Dataset) [14] & Focuses on emotion recognition in movie dialogues. It contains transcriptions of dialogues and their corresponding audio and video tracks. Emotions are labeled at the sentence and speaker levels. & Large amount of data, multimodal (text, audio, video). & Emotions induced by movies. Manually labeled. \\ IEMOCAP (Interactive Emotional Dyadic Motion Capture), 2005 & Focuses on emotional interactions between two individuals during acting sessions. It contains video and audio recordings of actors performing emotional scenes. & Realistic data, emotional interactions, a wide range of emotions. & Not real induced emotions (acting). \\ CMU-MOSI (Multimodal Corpus of Sentiment Intensity. 2014, 2017 [56] & Focuses on sentiment intensity in speeches and interviews. Updated in the 2017 CMU-MOSEI. & Emotions are derived from real speeches and interviews. & Relatively small size. \\ AVEC (Affective Behavior in the Context of E-Learning with Social Signals 2007–2016 [57] & Audio and video database that focuses on emotion recognition in speech and song. It includes performances by actors expressing various emotions. & Context-specific data, enables emotion assessment in e-learning settings. \\ RAVEDESS (The Ryerson Audio-Visual Database of Emotional Speech and Song) 2016 [58] & Focuses on emotion recognition in speech. & Diverse data in terms of emotions, modalities, and contexts. & Does not contain natural dialogues. \\ SAVEE (Surrey Audio-Visual Expressed Emotion) 2010 [59] & Focuses on emotion recognition in speech. It contains recordings of speakers expressing emotions through phrases and words. & Clean audio data. \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Databases most commonly utilized in the multi-physical classified studies incorporated into this review. Figure 5: Quantity of articles classified to the multi-physical category published from 2018 to 2023.
# Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed
###### Abstract  
The capacity to update firmware is a vital component in the lifecycle of Internet of Things (IoT) devices, even those with restricted hardware resources. This paper explores the best way to wirelessly (Over The Air, OTA) update low-end IoT nodes with difficult access, combining the use of unicast and broadcast communications. The devices under consideration correspond to a recent industrial IoT project that focuses on the installation of intelligent lighting systems within ATEX (potentially explosive atmospheres) zones, connected via LoRa to a gateway. As energy consumption is not limited in this use case, the main figure of merit is the total time required for updating a project. Therefore, the objective is to deliver all the fragments of the firmware to each and all the nodes in a safe way, in the least amount of time. Three different methods, combining unicast and broadcast transmissions in different ways, are explored analytically, with the aim of obtaining the expected update time. The methods are also tested via extensive simulations, modifying different parameters such as the size of the scenario, the number of bytes of each firmware chunk, the number of nodes, and the number of initial broadcast rounds. The simulations show that the update time of a project can be significant, considering the limitations posed by regulations, in terms of the percentage of airtime consumption. However, significant time reductions can be achieved by using the proper method: in some cases, when the number of nodes is high, the update time can be reduced by two orders of magnitude if the correct method is chosen. Moreover, one of the proposed methods is implemented using actual hardware. This real implementation is used to perform firmware update experiments in a lab environment. Overall, the article illustrates the advantage of broadcast approaches in this kind of technology, in which the transmission rate is constant despite the distance between the gateway and the node. However, the advantage of these broadcast methods with respect to the unicast one could be mitigated if the nodes do not run exactly the same firmware version, since the control of the broadcast update would be more difficult and the total update time would increase.  
IoT; IIoT; LoRa; cybersecurity; over the air update; FUOTA; ATEX; firmware update +
Footnote †: journal: _Sensors_
## 2 Study Area and Data  
### Background of the Study Area  
The 2017 Mw7.3 Iran-Iraq earthquake stuck the Iraq-Iran border region on November 12, 2017 with an epicentral of [45.9\({}^{\circ}\)E, 34.93\({}^{\circ}\)N], 50 km north east of Sarpol Zahab city based on the earthquake report from the USGS (the United States Geological Survey). Figure 1 shows the tectonic in this region, the continental collision between Arabia and Eurasian plate is the driving force. The oblique convergence between the Arabia and Eurasia plates activate through a combination of strike-slip (\(\sim\)5 mm/y in the central part of the Talesh Mountains) and thrust faulting (\(\sim\)2 mm/y-6 mm/y in the northern and southern parts of the mountains), respectively [28; 29]. Geologically, the earthquake's epicenter was located near the Zagros Mountain Front Fault (ZMFF) where the Zagros Mountains have been uplifting since the Late Eocene by the driving force. As a result, this earthquake was triggered and characterized by thrust motion.  
This earthquake event has already been studied several times by using different data sets, resulting in different fault models [1; 2; 3; 4; 5; 6; 7]. These studies indicate that this earthquake was a shallow-slip thrusting event with a small amount of right-lateral strike slip. The major fault parameters including strike, dip, and rake are similar. But the maximum slip is quite different. Based on the deformation fields obtained by the data sets of ALOS-2, [PERSON] and [PERSON] indicated that the maximum slip is approximately 5 m [1; 5]. [PERSON] [2] indicated that the maximum slip is approximately 6.9 m based on Sentinel-1A interferometric pairs and teleseismic P- and SH- body-waveforms data. [PERSON] indicated that the maximum slip is about 7 m while [PERSON] indicated the maximum slip is 6 m (3,7).
# Electromagnetic Induction Imaging with Atomic Magnetometers: Progress and Perspectives
## 4 Electromagnetic Induction Imaging with Atomic Magnetometers
### First Proof-Of-Concept of EMI with Atomic Magnetometers  
The demonstration of magnetic induction measurements with an atomic magnetometer [24] was followed by the first proof-of-concept demonstration of EMI with the same atomic sensor [26]. In those works, a self-oscillating atomic magnetometer [27; 28] was used. The core of the magnetometer was a vapor cell, filled with the naturally occurring mixture of rubidium, heated to 70 \({}^{\circ}\)C to increase the vapor density, and buffer gas. Images of a square, triangle and disk of 2 mm aluminium were successfully generated by position resolved measurement, obtained by moving the object with respect to the sensor. The original images are reproduced in Figure 2. These were the very first images produced via electromagnetic induction imaging using an atomic magnetometer as the sensor.  
Figure 2: Proof-of-concept of EMI with atomic magnetometers. Images refer to (**a**) a square, (**b**) a triangle and (**c**) a disk of 2 mm aluminium. The first row shows the position resolved normalized amplitude of the ac magnetic field signal. The second row shows the corresponding normalized phase data. Adapted from [26].  
The proof-of-concept demonstration reported in [26] opened up new prospects for EMI as atomic magnetometers have the potential to reach the sensitivity at low frequency required for essentially all EMI applications. This required further development to fully exploit the exquisite sensitivity of atomic magnetometers, as described below.
## 3 Results
### Far-Distance VA  
The results showed no statistical differences in distance vision for VA between PPLs and gaze direction (Table 1). However, statistically significant differences in eye movements were found for the three factors analyzed: eye chart size, gaze direction, and PPL design. No statistically significant interactions were found between the analyzed factors. For the eye chart size, it was expected that when the letter became smaller, the task difficulty increased, thus affecting the eye movements. The results confirmed that with a smaller optotype size, there was a statistically significant longer test duration, longer fixation time, and higher fixation count. Regarding the gaze directions, as the participant is forced to look through the lateral areas of the lens with blur, we would expect the increased recognition effort to affect eye movement. Statistically significant differences in longer test duration, longer complete fixation time, and a greater number of fixations were found for off-axis gaze directions relative to the central one. Finally, it was observed an effect of PPL design on eye movements. When the participants were using the PPL optimized for distance vision, statistically lower test durations, lower duration of fixations, and a lower number of fixations were found. (Figure 4 and Table 2). \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**PPL-Balance** & **PPL-Distance** & **PPL-Near** & **SS** & **MS** & **Df** & **F-Ratio** & **_p-Value_ \\
**VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **SS** & **MS** & **Df** & **F-Ratio** & **_p-Value_ \\ \hline \(-0.06\pm 0.06\) & \(-0.06\pm 0.06\) & \(-0.05\pm 0.07\) & 0.005 & 0.002 & 2 & 2.205 & 0.120 \\ \hline
**Centered** & **Dominant eye** & **Non Dominant Eye** & **VS (Mean \(\pm\) SD)** & **SS** & **MS** & **Df** & **F-Ratio** & **_p-Value_ \\
**VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **VA (Mean \(\pm\) SD)** & **SS** & **MS** & **Df** & **F-Ratio** & **_p-Value_ \\ \hline \(-0.06\pm 0.06\) & \(-0.06\pm 0.06\) & \(-0.05\pm 0.07\) & 0.004 & 0.002 & 2 & 1.833 & 0.170 \\ \hline \end{tabular}
\end{table} 
Table 1: Detailed statistics for visual acuity (VA) analysis at distance vision. Two-way repeated measures ANOVA. Figure 3: Flowchart for participant enrollment and data analysis. Figure 4: Variations in test duration, complete fixation time, and fixation count depend on the interactions of eye chart size and gaze direction (**A**), the gaze directions and PPL (**B**), and PPL and eye chart (**C**) for far-distance VA tasks. * Shows significance at the 0.05 level.
# A Convolutional Neural Network as a Potential Tool for Camouflage Assessment
## 3 Experiment 2: YOLO vs. Human Camouflaged Person Detection on Photosimulations
### Results
The main effect of pattern and the two-way interaction failed to reach significance: F-values \(\leq\) 0.117, _p_-values \(\geq\) 0.746. Figure 8: (**a**) Bush/desert (left) and urban (right) backgrounds. (**b**) Detection probability (according to YOLO) for each background condition. (**c**) Human performance. Mean search time and mean object identification conspicuity as a function of ROI (bush/desert versus urban) and pattern (average versus 1/f) for each background condition. Error bars represent the standard error of the mean. The results are clear. As expected from the literature, camouflage efficiency was better when the color of the camouflage suit matched the colors of the background than when it did not [29; 43]. This was revealed by both the mean search times as well as the mean object identification conspicuity. Furthermore, the identification conspicuity was smaller for the 1/f pattern than for the average color pattern. However, this effect was only significant for the object identification conspicuity measure but failed to reach significance for the search time, probably due to the low number of observations in this study (given the large inherent variation that is typical for search times, reliable estimates of mean search time require many observers and a large number of repetitions [48]). To summarize, the results of Experiment 2 show that YOLO predicted the human detection of a camouflaged person quite well, with detection probability correlating negatively with mean search time and positively with mean identification conspicuity. An exception is the high 1/f (bush) pattern that was found to be difficult to detect by YOLO in both environments, whereas human camouflage effectiveness was found to be higher for the patterns matched to the urban environment when measured in that environment.
# From Google Earth Studio to Hologram: A Pipeline for Architectural Visualization
## 1 Introduction
Despite the growing interest in 3D visualization, no studies have explored how publicly available photogrammetric data sources, such as Google Earth Studio, could be directly integrated into holographic imaging workflows. Traditional holographic pipelines rely heavily on light detection and ranging (LiDAR) photogrammetry from on-site captures and computer-aided design (CAD)-based modeling, all of which are resource-intensive and often inaccessible to broader communities. The CHIMERA digital holographic printer [23] offers a powerful means of translating dense viewpoint data into high-resolution full-color holographic stereograms. However, traditional workflows for generating the necessary perspective images often require extensive photogrammetry [24], LiDAR [25; 26], or other time- and resource-intensive 3D modeling techniques [27; 28]. To address this gap, this study proposes a streamlined, scalable, and cost-effective method for directly producing architectural holograms from cinematic 3D imagery rendered using Google Earth Studio. This approach minimizes the technical barriers, prevents the need for physical site access, and enables high-fidelity holographic reconstruction using existing datasets. Moreover, our methodology presents a new visualization pipeline and democratizes access to digital holography by leveraging free and readily available tools. The proposed method enables the transformation of large-scale 3D content into immersive holographic experiences, with applications spanning architecture, geospatial communication, public exhibitions, and cultural heritage. In our research work, two case studies were selected--Barcelona's Baslica de la Sagrada Familia and Paris's Arc de Triomphe--based on their complexity, scale, and visual richness. These examplesdemonstrated the potential for creating rich holograms from Earth Studio's photorealistic 3D imagery, bypassing the technical limitations of conventional 3D scanning.
## 2 The Development of Typical Rotating Motion Mechanisms
### Chain Drive  
#### 2.3.1 Single-Row Chain Drive  
The chain drive transmits the motor's driving force to the rotating actuator. The basic structure of modern chains was first designed and proposed by the great scientist and artist [PERSON] during the European Renaissance. The sleeve roller chain adds sleeves and rollers, reduces wear, and dramatically extends the chain's service life [72]. As shown in Figure 27[73], the chain consists of alternating inner and outer rings. The chain pitch is the distance between two consecutive sleeve shafts.  
Figure 28[73] shows the typical chain drive. The drive wheel is on the right side, and the drive wheel is on the left. The drive wheel drives the gear to rotate clockwise. Therefore, the tight chain is used as a rising chain to transfer the load, and the bottom is relaxed. The end of the chain represents the transition between the chain teeth and the sprocket.  
Figure 27: Modern roller chain structure.  
Multi-row chain drive  
[PERSON] et al. [74] mentioned multi-row sprockets with flanges, as shown in Figure 29. The core of this article is the cold semi-precision forging process of 5052 aluminium alloy multi-row sprockets. By designing a new type of sprocket tooth profile and using a circular arc transition instead of traditional sharp tooth tips, stress concentration and crack risk in the mould cavity have been reduced. Propose a three-step forging process, pre-forming teeth, machining flange grooves, and final forging, to simplify operations and improve mould filling efficiency. Cold forging technology reduces material waste and heat treatment requirements, lowering production costs. The new tooth profile and segmented forging have improved dimensional accuracy.  
3. Silent chain drive  
The silent chain transmissions in the specific automotive engine shown in Figure 30 [75] have the advantages of low noise, high transmission accuracy, high transmission efficiency, and good durability. They are widely used in automotive engines, transmissions, machine tools, and other high speed transmission devices.  
Figure 28: Schematic diagram of chain drive.  
Figure 30: Partial silent chain transmission system in a specific automobile engine.  
Bidirectional chain drive  
[PERSON] et al. [76] proposed a novel dual-phase single-toothed chain plate bidirectional chain transmission system. Based on the dynamic model shown in Figure 31. Adopting dual chain and dual phase sprockets, the polygonal effect is suppressed by phase difference, vibration is reduced, and transmission stability is improved. The dual-chain design enhances wear resistance and load capacity. The chain plate only has a single-tooth meshing, breaking through the limitations of traditional double tooth design, simplifying the structure and reducing weight, and verifying transmission stability through dynamic simulation. Optimising the shape of the chain plate and pin shaft reduces system weight (by 23.3%) and meets lightweight requirements.
# An Improved Energy-Efficient Routing Protocol for Wireless Sensor Networks
## 3 Proposed Scheme
### Improved Energy-Efficient LEACH Protocol
#### 3.2.2 Cluster Head Selection Algorithm of the IEE-LEACH Protocol  
Although there are advantages of using the LEACH protocol, it cannot guarantee the current residual energy of the CH. The selection of the threshold \(T(n)\) used by conventional LEACH-based protocols only consider whether the nodes will be selected to be the CH, without considering the node's energy. Therefore, the CHs are randomly selected, and, if a node with less energy is chosen as CH, then they will quickly die. To balance the energy consumption and prolong the network lifetime, we propose a new threshold \(T(s_{i})\), which is defined by  
\[T(s_{i})=\begin{cases}\frac{p_{i}}{1-p_{i}(r\bmod(1/p_{i}))},&s_{i}\in G,\\ 0,&\text{otherwise},\end{cases} \tag{17}\]  
where \(s_{i}\) is the node and \(i\in[1,N]\). The energy adjustment parameter \(p_{i}\) is given by  
\[p_{i}=\frac{p*s_{i}*E_{r}^{i}*E_{i}}{E_{t}*E_{a}}, \tag{18}\]  
where \(p\) is the proportion of selecting the optimal CH, \(E_{r}^{i}\) is the current residual energy of the \(i\)th node, \(E_{i}\) is the initial energy of the \(i\)th node, \(E_{t}\) is the total energy of the whole network, and \(E_{a}\) is the average energy of all SNs in the WSN. It can be seen from Equation (18) that the initial energy of nodes, residual energy of the network and average energy of all nodes are all used to calculate the energy adjustment parameter. This improvement can ensure that each node dies at approximately the same time. Thus, the proposed protocol can balance the distribution of the energy load among nodes and prolong the network lifetime. If the residual energy of the nodes is more than \(E_{a}\), then an improved threshold value \(T(s_{i})\) can increase the possibility of selecting them as the CH. After IEE-LEACH operates \(r\) rounds, the average energy \(E_{a}\) of all nodes is obtained  
\[E_{a}=\frac{E_{t}(1-\frac{r}{r_{\max}})}{s_{i}}. \tag{19}\]  
Initially, the nodes are randomly distributed in the WSN when the process of selecting the CH begins to be executed. Each node generates a random number, which is compared with \(T(s_{i})\). If the result is less than or equal to \(T(s_{i})\), then the node will become the CH.  
The newly proposed algorithm can increase the probability that the node whose residual energy is higher than the energy of the neighboring node or the average energy of the whole network becomes the CH node in the current round. Notably, all nodes have different energies with the IEE-LEACH protocol when selecting the CH. This process can ensure that each node dies at approximately the same time by more frequently selecting nodes with more residual energy than nodes with less residual energy as the CHs. Therefore, the IEE-LEACH protocol can lead to an increase in the lifetime of the overall network.
###### Abstract  
Water scarcity significantly challenges agricultural systems worldwide, especially in tropical areas such as the Dominican Republic. This study explores integrating satellite-based remote sensing technologies and field-based soil moisture sensors to assess water stress and optimize irrigation management in avocado orchards in Puerto Escondido, Dominican Republic. Using multispectral imagery from the Landsat 8 and 9 satellites, key vegetation indices (NDVI and SAVI) and NDWI, a water-related index that specifically indicates changes in crop water contents, rather than vegetation vigor, were derived to monitor vegetation health, growth stages, and soil water contents. Crop coefficient (Kc) values were calculated from these vegetation indices and combined with reference evapotranspiration (ETo) estimates derived from three meteorological models (Hargreaves-Samani, Priestley-Taylor, and Blaney-Criddle) to assess crop water requirements. The results revealed that soil moisture data from sensors at 30 cm depth strongly correlated with satellite-derived estimates, reflecting avocado trees' critical root zone dynamics. Additionally, seasonal patterns in the vegetation indices showed that NDVI and SAVI effectively tracked vegetative growth stages, while NDWI indicated changes in the canopy water content, particularly during periods of water stress. Integrating these satellite-derived indices with field measurements allowed a comprehensive assessment of crop water requirements and stress, providing valuable insights for improving irrigation practices. Finally, this study demonstrates the potential of remote sensing technologies for large-scale water stress assessment, offering a scalable and cost-effective solution for optimizing irrigation practices in water-limited regions. These findings advance precision agriculture, especially in tropical environments, and provide a foundation for future research aimed at enhancing data accuracy and optimizing water management practices.  
biosystem engineering; crop water stress; satellite data; agricultural sustainability; precision agriculture