esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Finite Element Modeling of Interconnection Metamaterial
### Frequency Response Analysis for Multi-Celled Interconnected Metamaterial  
The frequency response analysis for the multi-celled metamaterial is implemented to verify the vibration-reduction performance in the frequency range of the stopband [23] in this subsection. Considering the computational cost, the size of the unit cell used to analyze the frequency response analysis of the multi-celled structure was determined to be 5 \(\times\) 5 and 5 \(\times\) 10. The multi-celled interconnected metamaterials of sizes 5 \(\times\) 5 and 5 \(\times\) 10 were attached to a plate of 800 mm \(\times\) 200 mm, and each vibration response was compared. As shown in Figure 5, point excitation was performed at the center point of one edge along the z-direction, and the mobility response along the normal direction was calculated at the center point of the opposite direction.  
Figure 4: Dispersion diagram of the interconnected metamaterial: (**a**) stopband plot with host structure dominant (black star line) and resonator dominant (red circle line) bands; (**b**,**c**) are host structure dominant Bloch modes; (**d**,**e**) are resonator dominant Bloch modes.  
Figure 6 shows the transfer function of the z-directional mobility calculated at each measuring point, as shown in Figure 5. As shown in Figure 4, the stopband of the interconnected metamaterial proposed in this study ranges from 763.48 to 1613.9 Hz. In this frequency range, the mobility of the bare plate decreases 17.5, 22.6 dB on average by attaching the multi-celled metamaterial of sizes 5 \(\times\) 5 and 5 \(\times\) 10. As shown in Figure 6, the flexural vibration-reduction performance of the 5 \(\times\) 10 multi-celled structure is better than that of the 5 \(\times\) 5 structure. Thus, as the size of the array increases, the vibration transmission of the structure decreases.  
Figure 5: Frequency response analysis of plates (**a**) without and with interconnected metamaterials of sizes (**b**) 5 \(\times\) 10 and (**c**) 10 \(\times\) 10.  
Figure 6: Frequency response of z-directional mobility of the bare plate and plate with interconnected 5 \(\times\) 10 and 10 \(\times\) 10 metamaterials for (**a**) 0–2000 Hz and (**b**) the stopband (764–1613 Hz).  
Figure 7 is the z-directional displacement response at 1188 and 2000 Hz calculated from the frequency response analysis model shown in Figure 5. In Figure 7a,b, the vibration generated in the excitation point of the bare plate is propagated on the whole structure regardless of the stopband. As shown in Figure 7c,e, the flexural vibration at the excitation point cannot be propagated because of the effect of the interconnected metamaterial. It is also not transmitted to the measurement point. In contrast, as shown in Figure 7d,f, the vibration of the excitation point is propagated to the entire host structure in the frequency range out of the stopband. Each resonator in the stopband locally resonates and dissipates the vibration energy, and vibration cannot be propagated.
# A Data-Driven Situational Awareness System for Enhanced Air Cargo Operations Emergency Control
## 6 Proof of Concept Testing
### Software (SW) Module Testing
#### 6.2.4 Data Validation  
These tests involve the comparison of characteristic obtained results with the same data obtained by visual inspection of the tester. This test involves (a) calculation of data packages loss and time shift, and (b) collection and transfer of data in periodic intervals between several Smart Collector devices and a remote server. All data integrity tests were performed via the HMI application. Testing proved that all values were successfully transferred to the end destination without loss or duplication and on the correct sampling rate. Deviation from the precise sample timing intervals occurred. This deviation was of the order of one (1) second, which is assumed to happen due to noise in the link budget.
# Application of Convolutional Neural Networks in Visual Feedback of Movable Camera Mounting Control
## 2 Materials and Methods
### Hardware  
The 2 DOF movable camera mounting was built from two separate servomechanisms and an ESP32-CAM board, which has an embedded processing unit, WiFi module, and micro camera that work as a surveillance camera in this project. The overall view of the system is depicted in Figure 5.  
In this study, TowerPro MG995 servomechanisms [30] were used for both degrees of freedom. Their operating speed is equal to 0.2 s for 60\({}^{\circ}\) of position displacement. The velocity was saturated in the software architecture; that is, if a control action was required, every 1 ms, a command was sent to alter the angular position of the servomechanism by 1\({}^{\circ}\).  
Both servomechanisms considered in this study have a controlled movement range of 180\({}^{\circ}\). The first drive, which was attached to the base, does not have an extra limit in the moving range. Therefore, movement is limited to 90\({}^{\circ}\) in the left direction and 90\({}^{\circ}\) in the right direction. The second servomechanism is attached to the output of the first servomechanism. The movement of the second servomechanism was restricted to 30\({}^{\circ}\) sagittal flexion down and 60\({}^{\circ}\) sagittal flexion up. The limits are directly connected with the CCTV camera image. This solution avoids pointing the camera at unimportant areas of the building (e.g., ceiling, floor). The ESP32-CAM was connected to the second servo rotor to ensure two degrees of freedom of moving mount.  
Both sides of the system are energy independent; therefore, the operator can be separated from the CCTV camera as long as they are within range of the same network.  
Figure 5: The 2 DOF mounting system of CCTV with ESP32-CAM board. (**a**) Front view. (**b**) Side view.
###### Abstract  
The effective monitoring of methane (CH\({}_{4}\)) point sources is important for climate change research. Satellite-based observations have demonstrated significant potential for emission estimation. In this study, the methane plumes with different emission rates are modelled and pseudo-observations with diverse spatial resolution, spectral resolution, and signal-to-noise ratios (SNR) are simulated by the radiative transfer model. The iterative maximum a posteriori-differential optical absorption spectroscopy (IMAP-DOAS) algorithm is applied to retrieve the column-averaged methane dry air mole fraction (XCH\({}_{4}\)), a three-dimensional matrix of estimated plume emission rates is then constructed. The results indicate that an optimal plume estimation requires high spatial and spectral resolution alongside an adequate SNR. While a spatial resolution degradation within 120 m has little impact on quantification, a high spatial resolution is important for detecting low-emission plumes. Additionally, a fine spectral resolution (<5 nm) is more beneficial than a higher SNR for precise plume retrieval. Scientific SNR settings can also help to accurately quantify methane plumes, but there is no need to pursue an overly extreme SNR. Finally, miniaturized spectroscopic systems, such as dispersive spectrometers or Fabry-Perot interferometers, meet current detection needs, offering a faster and resource-efficient deployment pathway. The results can provide a reference for the development of current detection instruments for methane plumes.  
instrument parameters; IMAP-DOAS retrieval; methane plume; emission rate estimation 1
Footnote 1: [[https://doi.org/10.3390/rs17040634](https://doi.org/10.3390/rs17040634)]([https://doi.org/10.3390/rs17040634](https://doi.org/10.3390/rs17040634))
## 5 Performance Analysis  
This section describes the performance analysis of the DSP-based approach compared with that of the standard HSR protocol. We evaluated a sample HSR network as shown in Figure 5. In this paper, the network traffic is used to analyze and evaluate the traffic performance. When unicast frames are sent from a source to a destination in a network, the network traffic is the total number of the frames' copies that are delivered and received in the network.
## 6 Experimental Results and Discussion
### Results Obtained Using LPQ  
Table 3 presents the accuracies found using SVM, k-NN and Logistic Regression classifiers, fed by the LPQ feature vector. Window sizes 3, 5, 7 and 9 were experimented. The best results were achieved using the SVM classifier with features vectors built using window sizes 5, 7 and 9.  
As we can see, an accuracy of 91.67% was achieved with \(LPQ_{5}\), \(LPQ_{7}\) and \(LPQ_{9}\); with these results, we can now confirm our first research question (**RQ1**), that it is possible to perform cancer identification exploring a spectral-based texture descriptor on microphotographs of rat liver.
# Ad-BBR: Enhancing Round-Trip Time Fairness and Transmission Stability in TCP-BBR
## 4 The Optimization Algorithm: Ad-BBR
### Adaptive Sending Rate Adjustment Mechanism
#### 4.1.1 Minimum RTT Determination Logic  
In high-speed wireless network links, rapid fluctuations in the network state can occur, making it difficult for the RTprop to reflect real-time dynamic changes. Additionally, the BBR congestion control algorithm may fail to update the RTprop correctly during the ProbeBw phase due to continuous packet over-injection. To address this, this paper introduces an adaptive dynamic regulation mechanism with a new RTT (_uRTT_) to replace the old RTprop value for link state determination. By tracking the current RTT in real time and comparing it with the smallest RTT, the _nRTT_ is determined. This value is then used to assess the current link state and adjust the transmission state, enabling the algorithm to better handle dynamic links and maintain robust link state determination. The _nRTT_ update rule is presented in Algorithm 1.  
```
1:ifmeasured_rtt \(\leq\) self.\(\alpha^{*}\)RTpropthen
2:\(nRTT\)\(\leftarrow\) RTprop
3:\(over\_\)a_duration = 0.0
4:else
5:\(over\_\)a_duration \(\leftarrow\) over_a_duration \(+\) dt
6:ifover_a_duration \(\geq\) 0.3 then
7:\(nRTT\)\(\leftarrow\) RTprop
8:\(over\_\)a_duration \(\leftarrow\) 0.0
9:endif
10:endif
```  
**Algorithm 1**Ad-BBR, minimum RTT determination logic.
# Networked Microgrids: A Review on Configuration, Operation, and Control Strategies
## 3 Networked Microgrids' Control  
Effective monitoring and control techniques play a crucial role in optimizing performance and bolstering the overall resilience of networked microgrids. These techniques aid in the efficient distribution of energy, reducing power losses, and enabling adaptive operation. They ensure that networked microgrids can swiftly adjust to changing conditions and optimize their functioning in response to disruptions. To implement advanced and real-time control techniques, a robust and reliable communication structure is necessary. Therefore, in the upcoming sections, we will initially review various communication techniques and then delve into the control approaches and aspects of NMGs in depth.
## 3 Results and Discussion
Figure 2a shows the N\({}_{2}\) adsorption isotherms of raw materials. The materials are distinguished by their adsorbed volume intensity. The following ranking was observed in increasing order: adsorbed volume of GGBS\(<\)Cement\(<\)WSA. The adsorption capacity of cement seems to be two times higher than GGBS while that of WSA is eight times higher than GGBS. The hysteresis phenomenon starts to appear from 0.8 P/P\({}^{\circ}\). The difference in adsorption capacity between the different materials demonstrates the hydration affinity. That is, the water attractiveness of the material. In terms of pore distribution, Figure 2b shows a similar trend: the measured pore families are relatively close. The results show that all the tested materials show more pronounced peaks around 0.03 micron, 0.09 micron and 0.12 micron. The difference between the different materials can be observed from the pore intensity. The same rankings as the isotherms are confirmed. The difference in adsorption capacity between the different materials demonstrates the hydration affinity. That is, the water attractiveness of the material.  
Table 5 shows the volume of adsorption and desorption of the pores calculated from related isotherms for the three raw materials. The volume adsorbed by the pores of WSA is higher than that of GGBS and cement. This is confirmed by Figure 2, which has a higher area below the curve compared to that of the GGBS and the cement. The hysteresis in Figure 2 shows a very low adsorption/desorption volume; these low values are very close to zero.  
Figure 2: (**a**) Adsorption/desorption isotherms and (**b**) pore size distribution of raw materials.
## 2 Results  
### Antibacterial Activity of the Peptides  
The antimicrobial activity of the peptides was initially tested with a microdilution broth assay to determine the minimal inhibitory concentration (MIC). Esc(1-21) showed the strongest inhibitory effect on both the _E.coli_ K12 and _E.coli_ O157:H7 EDL933 strains with MICs of 2 and 4 \(\upmu\)M compared to the higher values of 16 and 32 \(\upmu\)M found for Esc(1-18), respectively (Table 1).  
The antimicrobial activity of Esc(1-21) was also stronger than that of kanamycin, which was included as a reference antibiotic and showed a MIC of 16 \(\upmu\)M against both strains [23]. We then evaluated the minimal bactericidal concentration (MBC) and found that it was equivalent to 2 \(\times\) Mic for either the peptides or kanamycin.  
The rate of bactericidal activity of Esc(1-21) and Esc(1-18) on the EDL933 strain was then investigated with a time-kill assay (Figure 2).  
A 99% killing rate (corresponding to a 2-log reduction of viable bacterial cells (dotted line in Figure 2) was obtained within the first 30 min of treatment with Esc(1-21) at 4 \(\times\) Mic or within the first 45 min of incubation with 4 \(\times\) Mic of Esc(1-18). In comparison, a longer time (75 min) was needed for kanamycin at 4 \(\times\) Mic.
# Volatile Freight Rates in Maritime Container Industry in Times of Crises
## 3 Maritime Container Market and the Freight Rates in Times of Crises  
This section outlines the importance of maritime transport for the normal functioning of the economy and supply chains. It shows how, in previous crises, companies with great handling capacities dealt with the resource challenge of large container ships. The impact of the pandemic and the war in Ukraine on trade and longer trade routes was compared, which should lead to an optimization of resource use.  
Life and economy on global scale would not be the same without the activities performed via seas and oceans, which is best supported by the challenging events over the last two years that have undermined the stability of the maritime trade [16]. Maritime transport plays an important role in global transportation activities, and its key segment is container traffic. Logistically, as with all other economy sectors, they have experienced unseen challenges in these critical times. First and foremost, when talking about the COVID-19 pandemic, it is necessary to highlight four significant differences between this crisis and the previous crises the world had faced [22]:  
1. Pre-existing unfavorable conditions. The scope of trade has been growing at considerably lower rates than in the period before the crisis of 2008.
2. This crisis is global and has been affecting almost every world economy. Earlier crises were more regional.
3. The worst effects of the crisis that had begun in the middle of 2008, followed months after it had started, while the crisis of 2020 immediately shook the global market.
4. The effects of the pandemic caused by the coronavirus represent the greatest drop in international trade since World War II.  
If the growth rates of the world trade after the financial crisis of 2008 and 2009 are observed, it is evident that the global market has not yet recovered from it. The average growth rate in the period from 2012 to 2019 was 2.3%, while it went up to 6.2% in the period from 1990 to 2012 [39; 40]. Although it can be said that during the second half of 2020 and during 2021, world trade was on the path to recovery, it is obvious that the supply was less flexible and limited by delays and congestions occurring due to the COVID-19 pandemic, which prompted the increase in the freight rates on the maritime container market [12]. During the first quarter of 2022, the value of the total global trade grew to a record USD 7.7 trillion, which is an increase of USD 1 trillion in relation to the first quarter of 2021. However, it is expected that the growth rate will slow down due to slower economic growth as a consequence of the rising interest rates, inflationary pressures and concerns regarding the debt viability in many world economies that have arisen due to the Russian invasion of Ukraine [41].
# The Power System and Microgrid Protection--A Review
## 3 Protection Scheme of Microgrid
### Differential-Based Protection Method  
Differential protection is another common method to protect transmission lines and transformers in power systems [74; 95; 96]. The principle of differential relay operation is based on using the imbalance current flow into and out of a specific protected zone. The differential-based protection method is mainly utilized to detect low short circuit current in the islanded microgrid. The method cannot be used as a complete protection scheme and is more suited to detect downstream earth faults, while some other techniques have to be taken into account to identify further faults like upstream ground faults, line-to-line (L-L) faults, and symmetrical faults. The method also utilizes communication links for differential operation [40]. Figure 13 depicts the differential-based protection scheme of a microgrid with a communication channel.  
Figure 12: Impedance-based protection scheme.  
Normally, this scheme has the best selectivity since it depends on the communication between the beginning and the end of the protected line segment [74]. The authors of Reference [97] investigated an adaptive wide-area current differential protection system. The method divides the power system into different protection zones that are dynamically online. The protection system adaptively changes with the topological variations of the power system. References [42; 44] proposed the protection of a microgrid with a communication network using digital relays. These methods use differential protection for low fault currents, such as in an HIF and inverter-based-microgrid. In Reference [98], a communication-assisted OC protection scheme was proposed for PV in DC microgrids. This method is based on differential protection, which is used as the backup protection. The protection scheme in grid-connected and islanded operation mode of a DC microgrid uses OC relays. Otherwise, a protection scheme has been suggested based on differential protection. Reference [99] has presented a protection scheme in the loop distribution system in the presence of DGs. This method is based on the equivalent circuit of the distribution system and uses a control center with high-speed communication as the centralized protection scheme.
## 4 Data Mining
### Data Mining Requirements within MoDisNet
#### 4.1.2 P2P Based Distributed Data Mining  
Historical data is well-suited to large-scale analysis over multiple dimensions, but for dynamic queries over real-time sensor data streams, the data has to be taken directly from the sensors. These data points have little value for warehousing and also the real time mining querying cannot afford a \"store and mining\" model. A typical analytical work would involve the statistics at a certain location and about certain properties in that location. The sensor may not be able to offer this information on its own, due to its movement from the location, or due to inability to capture all relevant information pertaining to the query. The dynamically composed sensor network with P2P communication model can support such information exchange and distributed streaming mining algorithms to provide real time analytical querying model.  
The P2P in-networks data mining is based on the data collected and stored by each sensor in real time. Mining these real-time data, the system can give a quick judgment on the pollution status. And the result may reflect some change of the traffic situations. The convergence time of the distributed mining algorithms must be as quick as possible. At the same time, the results may be very simple and not accurate as the centralized one.
## 4 Applications
### Human Pulse Monitoring  
Human pulse was monitored to test the ability of the strain sensor to measure small strains. The radial artery sitting on the thumb side of the wrist is commonly used to clinically measure heart rate in traditional Chinese medicine. Therefore, to mimic the actual application, we attached the strain sensor to the radial artery of the wrist via transparent tape. The wave-form signal of the strain sensor in 3 s is shown in Figure 7b. As can be seen, although the relative change in resistance is very small with its maximum at 1.2%, good measurement stability can still be achieved. Clearly, there are four stable pulse-beating cycles with each, including three local peak values, P1, P2, and P3, which respectively represent pulse beating, left ventricular systolic pressure, and lower body reflection. Based on these  
Figure 7: Applications of the fabric-based MWCNTs/rGO/rGO strain sensor in physiological signal detection.  
peak values, certain diseases can be diagnosed. For example, the ratio of P2 and P1 can be used as an evaluation criterion for the degree of arteriosclerosis which is a common disease of the elderly.
## Human-Performed Classification
### Post-Screening  
Following from above, the post-screening procedure involved the two following steps:  
1. removing the data obtained using BRIR sets 12 and 13 (as a result, the accuracy increased from 40.6% to 42.5%),
2. retaining the data obtained only from the listeners whose accuracy scores were no less than the statistical significance threshold of 53.3%, resulting in the further accuracy rise to 59.7%.  
The results obtained after the post-screening procedure are shown in Figure 4b. It can be seen that the scores markedly improved, as the mean accuracy scores increased to almost 60%. This improved score is used in the remainder of the paper as a basis for comparison with the classification accuracy obtained by the machine-listening algorithm  
Figure 4: Boxplots of the accuracy scores for stimuli synthesized using specific BRIR sets: (**a**) before post-screening; (**b**) after post-screening. Red line denotes no-information rate.  
While some variations in the scores can be seen across the BRIR sets in Figure 4b, the ANOVA model was not statistically significant. Hence, despite the visual variations seen in the figure, no inferences regarding the inter-BRIR effects could be made.  
The confusion matrix, obtained after completing the above post-screening procedure, is presented in Figure 2f. In contrast to the matrices shown in the remaining panels of that figure, distinct maxima along the diagonal line seem to emerge.
# Monitoring and Data Analysis in Small-Scale Landslide Physical Model
## 3 Review of Landslide Monitoring Equipment
### Geotechnical Monitoring System
#### 3.2.2 MEMS Accelerometers
Temperature gradient is symmetrical about the heat source, if no acceleration is applied, temperature is the same in each thermopile, and consequently, they all output the same voltage. Acceleration causes a disturbance in the temperature profile which becomes asymmetrical. Since the temperature of the four thermopiles is different, voltage output is also different. Voltage at thermopile outputs is directly proportional to the acceleration [65].