esa-sceva/satcom-chunk-collection huggingface dataset:
# Failure Assessment of Embankment Dam Elements: Case Study of the Pirot Reservoir System
## 5 Results and Discussion
### Hypothetical Scenarios Results  
#### 5.3.1 Damage of Grout Curtain (Scenario 1)  
The results of the filtration analysis in case of damage of the grout curtain for different reservoir water levels are shown in Figure 11. Grout curtain damages are, as previously noted, presented by increasing the filtration coefficient of the corresponding zone. Results shown in Figure 11 show the filtration rates through the grout curtain in case of maximum reservoir water level.  
From the presented results, it can be seen that in case of grout curtain damage, there are multiple increases in the filtration rates. This conclusion has a significant impact on the occurrence of soil erosion in the layers below the dam body, which can affect the long-term safety of the entire structure. Regarding the analysis of the total flow through the grout curtain for different reservoir water levels and in the case of individual zone damage of the grout curtain, the results are shown in Figure 12. It can be seen that the damage to some regions has a smaller impact on the change in the total flow through the grout curtain. This primarily refers to the zones of the grout curtain, which are located at higher altitudes, on the left and right side of the dam body (regions 1 and 6 in Figure 5).  
Potential damage to regions 2 and 5 (Figure 5) has the greatest impact on increasing the total flow through the grout curtain. The impact of the damage on the total flow through the grout curtain decreases with the damage to the curtain regions located in the deeper layers of the rock mass (regions 3 and 4 in Figure 5). This response can be explained by the fact that zones 1 and 6 are located at high altitudes and almost no water reaches them, i.e., they are affected by upper water with low hydrostatic pressure. Zones 3 and 4 are located in the deeper layers of the rock mass below the dam, nestled between two zones with low permeability, so such a rock mass reduced the amount of water that reaches the grout curtain. Leakage through the grout curtain ranges from \(2\times 10^{-4}\) m\({}^{3}\)/s to \(7.6\times 10^{-4}\) m\({}^{3}\)/s, which is a small quantity in relation to the average annual flow of the Visocica river. However, damage to the grout curtain increases the possibility of local erosion, which can have a progressive character and endanger the safety of the facility for a  
Figure 10: Seismic acceleration \(\mathrm{a_{y}}=0.19\) g: (**a**) total translation \(t\) (m) and (**b**) equivalent plastic strain \(e^{p}\) (\(-\)).  
longer period of time. The fact that water losses through the grout curtain represent a loss of energy, and thus a financial loss, which is not insignificant, cannot be ignored either.
# Scalp-Implanted Ultra-Wideband Circularly Polarized MIMO Antenna for Biotelemetry Systems
## 3 Results and Discussion
### Channel Parameters
As a result, this antenna is exceptionally well suited for high-data-rate biomedical IMD applications.
## 5 Conclusions  
In this paper, a mathematical model of BTMS was established, and the structure of the battery pack was optimized by adjusting parameters. The flow resistance model calculated the air velocity in the cooling channel, and the heat dissipation model calculated the temperature of battery unit. Based on these two models, the influence of five structural parameters on the maximal temperature and the maximal temperature difference under different inlet airflow rates was studied. Through sensitivity analysis, the design variables affecting the area of the battery pack were selected, and the stud GA was used to optimize the battery pack area. It can be concluded as follows:  
1. Under various inlet airflow rates, comparing the temperature of battery unit calculated by the proposed mathematical model and the CFD method, it was found that the degree of coincidence was very good. Compared to the CFD method, which requires more than a dozen hours of calculation, the flow resistance and heat dissipation model can be calculated in a few seconds, which can save a lot of time.
2. Through sensitivity analysis, it was found that the structural variable that had the greatest influence on the maximal temperature difference was \(\theta_{\text{cp}}\), followed by \(w_{\text{cp}}\), and finally \(\theta_{\text{dp}}\). These three parameters were positively correlated with the maximum temperature difference. \(d_{0}\) and \(w_{\text{dp}}\) were minimized to facilitate the heat dissipation and reduce the size of the battery pack.
3. In the case of the minimum inlet airflow rate, the minimum area of the battery pack was targeted, and the maximum temperature difference obtained by the heat dissipation model was required to be less than 5K as the constraint function. The stud GA was used to optimize \(\theta_{\text{cp}}\), \(\theta_{\text{dp}}\) and \(w_{\text{cp}}\). The final results show that compared to the original battery pack structure, the optimized battery pack meets the requirements that the maximal temperature difference be less than 5K and saves 6.24% area. The use of the heat dissipation mathematical model can greatly accelerate the design cycle of the battery industry, and at the same time increase the energy density of the battery pack to ensure that the battery works safely at a suitable temperature.  
Conceptualization, R.J.; writing--review and editing, J.C.; visualization, B.W.; supervision, R.J.; project administration, D.X.; funding acquisition, D.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Whenzhou Scientific and Technological Project, grant number 2018 ZG007.  
This study did not involve humans or animals.  
Figure 16: Comparison of air velocities in the cooling channels before and after optimization.
# A Switching Observer for State-of-Charge Estimation of Reconfigurable Supercapacitors
## 2 Modeling and Motivation
### System Modeling
#### 2.1.1 Supercapacitor Representation  
Figure 1 illustrates the adopted supercapacitor model, employing a series connection of RC circuits. This representation is widely used due to its balance of accuracy and simplicity.  
While often small in magnitude, the impact of Equivalent Series Resistance (ESR) can contribute to power dissipation within the system. In reality, ESR is a parameter that is almost impossible to measure accurately and can vary over time. We will discuss the impact of this variation in the observer design and experiment sections. State of Charge (SOC) serves as a crucial metric for supercapacitors, reflecting the available charge relative to its capacity. SOC is commonly defined as  
\[\text{SOC}=\frac{Q_{remain}(t)}{Q_{rated}}\times 100\% \tag{1}\]  
where \(Q_{remain}(t)\) represents the remaining charge at time instant t, and \(Q_{rated}\) denotes the rated charge, which remains constant.  
It is important to note that in certain cases, \(Q_{rated}\) might be replaced with the maximum available capacity, which tends to be lower than the rated capacity due to the impact of continuous charge-discharge cycles.  
Let \(v_{rated}\) represent the rated maximum voltage, \(v\) the terminal voltage of the supercapacitor cell, and \(v_{c}(t)\) the voltage across the equivalent capacitor of the cell. Based on the fundamental characteristics of a capacitor, we have  
\[Q_{remain}=C_{eq}v_{c}(t) \tag{2}\]  
Figure 1: The equivalent RC circuit of the supercapacitor.  
\[Q_{rated}=C_{eq}v_{rated} \tag{3}\]  
where \(C_{eq}\) represents the equivalent capacitance of the supercapacitor.  
Combining Equations (1)-(3), we can derive the following relationship:  
\[\text{SOC}=\frac{v_{c}(t)}{v_{rated}} \tag{4}\]  
Considering the influence of ESR, the voltage across the equivalent capacitor can be expressed as  
\[v_{c}=v-ir \tag{5}\]  
where \(i\) represents the charging current flowing through the cell, and \(r\) denotes the ESR of the cell. The voltage dynamics across the equivalent capacitor \(C_{eq}\) can be described by  
\[\hat{v}_{c}=\frac{i}{C_{eq}} \tag{6}\]  
It is crucial to observe that a higher charging current \(i\) leads to a faster rate of change in the voltage \(v_{c}\).  
Differentiating both sides of Equation (4) with respect to time, we obtain  
\[S\partial C=\frac{i}{C_{eq}v_{rated}} \tag{7}\]
## 1 Introduction
The demonstrated APDs (Device A) are fabricated using a partially depleted p-type In\({}_{0.53}\)Ga\({}_{0.47}\)As absorbing layer and thin In\({}_{0.52}\)Al\({}_{0.48}\)As dual M-layers (60, 88 nm). We obtain a wide optical-to-electrical bandwidth 18 GHz and large gain bandwidth product (459 GHz). On the other hand, after further downscaling the active diameter, in its counterpart back-illuminated device (Device A\({}^{\prime}\)) exhibits a much wider O-E bandwidth of 25 GHz and a saturation current as high as >5 mA. whereas APD (Device B) design with thick absorber and dual M-layers, there is a relaxation in the trade-off between the avalanche gain and the bandwidth. An ultra-high gain bandwidth product (460 GHz), high responsivity (1 A/W) at the unit gain and a 3-dB bandwidth of 1.25 GHz with a responsivity as high as 33 A/W at 0.9 V\({}_{\text{br}}\) can be achieved using a device with a large optical window diameter (200 \(\upmu\)m). It is worth noting that in either case (thin or thick multiplication layer), we obtain an ultra-high GBP of around 460 GHz. These promising results suggest that our proposed dual M-layer with thick absorber layer design can fundamentally overcome allow further downscaling of the M-layer and absorber layer to obtain a higher GBP, in order to meet the requirements of high-speed transmission. Nevertheless, such APDs with high GBP and high responsivity and a large optical window diameter (200 \(\upmu\)m) can be fundamentally used for FMCW Lidar applications dealing with weak reflected signals received from the objects being tested.
# Dist-YOLO: Fast Object Detection with Distance Estimation
### The Motivation and Our Idea in Brief  
Our long-term goal is to create a system capturing a scene in front of a car and providing information about the detected objects together with their _absolute_ distances. The system has to be inexpensive; therefore, it does not rely on lidar, and the object detector runs on a low-powered embedded device, Jetson Nano. The proposed system is a part of a project controlling LED segments in a car's headlamps to highlight detected objects. To set up the light beam precisely, absolute distance information is necessary, so it is not feasible to use methods providing relative distance, e.g., dense depth map [7; 9].  
We use a monocular RGB camera. The motivation to omit two cameras and compute a disparity map for distance estimation is that according to [27] \"A single-pixel error in disparity implies only a 0.1m error in depth at a depth of 5 m, but a 5.8 m error at a depth of 50 m\" on a KITTI dataset [14], and the current object detectors have a more significant pixel error. Moreover, we are restricted to a monocular camera because the usage of two cameras increases the price of the solution.  
Our intuition is that YOLO performs regression on BB coordinates, so it can be trained to solve the regression problem of absolute distance estimation as well. The assumption is that the network can use the same inner features for BB coordinates and distance estimation, leading to synergy. It motivates us to integrate the part responsible for distance estimation into the YOLO architecture and train the model in an end-to-end manner. The assumption will be confirmed when a model trained for distance estimation leads to higher BB precision than the baseline YOLO.  
Our contributions to the problem are as follows:  
1. We define a novel architecture, Dist-YOLO, where prediction vectors produced by heads are extended by information about distance and coupled with a proper distance loss function.
2. We show that Dist-YOLO detects bounding boxes more accurately than the original YOLO while having the same backbone's capacity.
3. We demonstrate that a monocular camera with Dist-YOLO can precisely estimate the distance of an object.
# Congestion Control and Traffic Differentiation for Heterogeneous 6 TiSCH Networks in IIoT
## 2 Problem Statement and Related Work
### Related Work
Moreover, the conventional Trickle timer utilized by the aforementioned approaches could fail to detect and react to congestion in a timely manner. The authors in [30] proposed CoAR, a Congestion-Aware Routing protocol, where the Trickle timer is reset to its minimum value when a congestion is detected. Although CoAR improves the network performance in congestion situations, the utilized reset strategy increases the network overhead and the energy consumption in turn. The authors in [31] proposed a heuristic algorithm that calculates the redundancy constant of the Trickle timer as a function of the number of neighbor nodes in its vicinity. However, the work overlooked the impact of the proposed algorithm on the QoS metrics of the constructed routes. The Trickle-Dalgorithm was proposed in [32], in which the redundancy constant is adapted using Jain's index to achieve fairness among nodes while keeping low overhead. According to the obtained results, Trickle-D achieves improved performance in terms of fairness and energy consumption, while other vital metrics such as packet delivery ratio and delay are not considered. Moreover, none of the above works considered the prioritized transmission of critical traffic in heterogeneous 6 TiSCH networks.
# Dynamic Behavior of Track Bridge on Serviced Long-Span Road/Railway Bridge
## 1 Introduction  
The Yeongjong Bridge is a long-span railway with various bridge types and unusual track-bridge interaction systems. Therefore, experimental and analytical studies on track-bridge interactions are needed to evaluate train safety. Recently, several experimental and analytical studies on the dynamic behavior of track bridges have been conducted to ensure the safety of train operations. [PERSON] et al. presented an experimental study on the dynamic effects of moving trains on a long-span railway consisting of continuous beam bridges [1]. [PERSON] investigated the influence of the track support stiffness on the dynamic wheel-rail forces for a ballasted track [2].  
In analytical studies, [PERSON] and [PERSON] evaluated the riding comfort and vehicle dynamic response of trains traveling over bridges, and developed an efficient, nonlinear dynamic interaction model of the train-track-bridge system [3]. [PERSON] et al. based their study on the obvious differences in flexural rigidity between rails and bridges, and presented a rail-bridge coupling element using unequal lengths [4].  
[PERSON] et al. studied how to prevent the deformation of track-integrated systems to improve safety through numerical analysis [5]. [PERSON] et al. proposed a new finite element model for the three-dimensional finite element analysis of high-speed train-bridge interactions [6]. [PERSON] et al. presented and established a numerical model to analyze the effects of car body vehicle model flexibility on the dynamic response of a train-bridge system [7]. [PERSON] et al. proposed a dynamic analysis model for a train-bridge interaction system [8].  
In this paper, dynamic analyses, including field measurements taken on the Yeongjong Bridge track-bridge, are presented with respect to train speed.  
The Yeongjong Bridge has a direct fixation track structure. Moreover, the structure supporting the rails is a simple beam structure consisting of steel plate girders. The rails fixed by the directfixation rail fastening system on the upper surface of the simple beam upper flange are directly affected by the behavior of the track girders, which causes the level of displacement of the rail to be similar to that of the track girders. A plate spring type fastener and control packing are installed through adjustable pads, in which the general nut is modified as an anti-loosening nut. To ensure secure train operation on the Yeongjong Bridge, it is necessary to predict the behavior of the track and bridge structures under the increased train speeds expected in the future to reduce semi-high-speed combined line track damage [9]. A 3D numerical analysis was performed using a full-scale bridge model to evaluate the Yeongjong Bridge track-bridge structure. The results of this model were compared with field measurements, and the track-bridge dynamic behavior was evaluated according to anticipated increases in train speed.
# A 28 nm Bulk CMOS Fully Digital BPSK Demodulator for US-Powered IMDs Downlink Communications
## 4 The Proposed Fully Digital BPSK Demodulator
It must be noted that the time delay is symmetric and equal for both the rising and falling edges of the received bit and, therefore, the time delay does not affect the demodulated data. Figure 6: Block diagram of the proposed BPSK demodulator. Concerning the data frequencies that could be achieved with such a demodulation system, they are identified starting from the timing diagram in Figure 7 and using the following equations,  
\[T_{BPSK,ON}(n)=T_{RX,ON}(n)=\frac{3}{2}T_{0}+nT_{0},\quad n\in\mathbb{N}_{0} \tag{3}\]  
\[f_{RX}(n)=\frac{1}{T_{RX}(n)}=\frac{1}{T_{0}(3+2n)}=\frac{f_{0}}{(3+2n)},\quad n \in\mathbb{N}_{0}, \tag{4}\]  
where \(T_{0}\) is the oscillation period and \(f_{0}\) is the oscillation frequency of the US-wave source, \(T_{BPSK,ON}\) is the BPSK-bit '1' duration, and \(T_{RX}=2T_{BPSK,ON}\) is the period of the received data. The maximum bit rate, \(B^{MAX}\), is established when \(n=0\) and it is equal to  
\[B^{MAX}=2\cdot f_{RX}(n=0)=2\cdot f_{RX}^{MAX}=\frac{2}{3T_{0}}=2\frac{f_{0}}{3} \tag{5}\]  
In the case under analysis, the natural index \(n\) was set as equal to zero, while \(T_{0}=500\,\mathrm{ns}\) and \(f_{0}=2\,\mathrm{MHz}\), giving as results of Equations (4) and (5), that the time of the received BPSK signal is \(T_{ON,BPSK}=750\,\mathrm{ns}\), while the bit rate is \(1.33\,\mathrm{MHz}\). Moreover, the modulation/demodulation frequency, as well as the bit rate, could be changed and reduced. Indeed, for most of the neural stimulation applications, the required bit rate goes from a few \(\mathrm{kb/s}\) up to hundreds of \(\mathrm{kb/s}\). The adopted technology is a \(28\,\mathrm{nm}\) bulk CMOS process provided by TSMC. The SVT thick-oxide transistors were used since they could work up to \(1.8\,\mathrm{V}\). The thickness of the oxide was \(C_{OX}\simeq 10\,\mathrm{fF/\upmu m^{2}}\), while the threshold voltages of NMOS and PMOS transistors were respectively \(V_{tn}\simeq 450\,\mathrm{mV}\) and \(|V_{tp}|\simeq 460\,\mathrm{mV}\), for \(L_{n,p}=4L_{min}=0.6\,\upmu\)m. The simulation environment used was Cadence Virtuoso. Figure 7: Timing diagram of the proposed demodulator circuit. The following subsections report an in-depth description of each single block that compose the system in Figure 5:0
# Flexibility Based Day-Ahead Generation-Reserve Bilevel Decision Model
###### Abstract  
With the increasing penetration rate of renewable energy like fluctuating wind and solar energy, the power system has to equip itself with a more reasonable reserve capacity. Therefore, how to quantify the reserve capacity needed for dealing with the uncertainty and fluctuation has turned out to be a new problem faced by the power system integrated with large-scale renewable energy. This paper proposes a flexibility based day-ahead generation-reserve bilevel decision model. In the upper level, the day-ahead unit commitment model is constrained by flexibility reserve, which is calculated in the lower level. In the lower level, taking into account various factors of uncertainty and fluctuation, e.g., wind power ramping, load ramping and random failure of conventional units, the ramping probability distribution of an equivalent system is obtained by the universal generating function method, then the quantified relationship between operating reserve and flexibility is established ultimately. If the unit commitment scheme gained from the upper level could not provide sufficient reserve, a feedback for the correction of the upper level is needed. The rationality and validity of the proposed model are verified through the simulation of a modified IEEE-118 bus system.  
operating reserve; flexibility evaluation; ramping; unit commitment; universal generating function +
Footnote †: journal: Applied Sciences
# A Deep Curriculum Learning Semi-Supervised Framework for Remote Sensing Scene Classification
## 3 Proposed Method
### Deep Feature Extraction  
In the past ten years, a large number of deep learning models have emerged which have evolved from AlexNet. Deep learning uses multiple hidden layers to learn, layer by layer, and conducts feature extraction from large-scale data to find the optimal abstract expression method for the data, thereby improving the accuracy of classification or recognition. However, deep network models often require abundance data for training, which is time-consuming and requires significant computational resources. Therefore, for small datasets, pretrained CNNs are usually employed.  
Due to the different structures of different networks, the capabilities of the extracted deep features for feature expression are also different, which reflects the fact that different networks will exhibit different performances in conducting the same task. In the experiment, we selected three different deep learning networks to extract features, and the extracted features are also different; see Section 4.1 for details.
## 3 Experimental Results and Analysis
### Web Detection Platform  
To facilitate farmers in easily and quickly identifying and detecting pests and diseases, the model is deployed in a web application that detects pests and diseases on maize leaves, assisting farmers in understanding the conditions of pests and diseases and obtaining expert guidance. In this application, users can detect maize leaf pests and diseases by  
Figure 11: Comparison of the visualization of the detection results of different model.  
uploading local pictures, and the test results are presented in Figure 12. Additionally, the application utilizes an embedded database, SQLite, to construct a web user service system, including registration and login functions, maize leaf pest detection functions, encyclopedia search functions, and pest control advice functions. Through the above functional design and implementation, the application provides users with convenient services and practical functions.