esa-sceva/satcom-chunk-collection huggingface dataset:
# PVDF-TrFE Film on PDMS Substrate for Energy Harvesting Applications
## 3 Results and Discussion
The inset shows a magnified plot of charging transients up to 100 s. We found that the output voltage on the 4.7 \(\upmu\)F capacitor terminals reached 4.4 V in \(\sim\)60 s, while it took \(\sim\)145 s and \(\sim\)1085 s, respectively, to charge the 10 \(\upmu\)F and 47 \(\upmu\)F capacitors to the same voltage (4.4 V). The maximum stored energy and average power values were determined to be 113.74 \(\upmu\)J and 370 nW, respectively. Based on the active area and thickness of the sample (4 cm\({}^{2}\) and 7 \(\times\) 10\({}^{-4}\) cm), the maximum output power density can be calculated as 6.62 mW/cm\({}^{3}\), which is comparable to the state-of-the-art performance across all energy harvesting device technologies [19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38]. Although the power from the device is in the sub \(\upmu\)W range, just a single device can still provide sufficient power to operate structural health monitoring devices, such as a 100 nW temperature sensor, or a low-power 4 kB 80 nW microprocessor [39; 40; 41]. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Frequency (Hz)** & **Average Voltage (V)** & **Average Current (\(\upmu\)A)** & **Average Power (\(\upmu\)W)** \\ \hline
5 & 2.8 & 1.2 & 3.36 \\
10 & 3.3 & 1.5 & 4.95 \\
20 & 3.8 & 2.1 & 7.98 \\
30 & 5.8 & 3.2 & 18.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Average output voltage, current, and power of the device for various excitation frequencies. Figure 6: **(a)** Voltage-time charging curve of storage capacitors with different capacitances (4.7 \(\upmu\)F, 10 \(\upmu\)F, and 47 \(\upmu\)F) under application of an external force with 30 Hz frequency. The inset shows an enlarged plot of voltage-time charging curves; **(b)** Electric charging circuit for the storage capacitor, and a picture of an LED assembly that glows by drawing power from the storage capacitor after energy harvesting is done. To demonstrate a simple practical application of the energy harvester, we used it to light a set of 27 commercial LEDs connected in parallel. The overall circuit schematic, including 4 diodes, a switch, a capacitor, and 27 LEDs is shown in Figure 6b. As the capacitor reaches the threshold voltage (2.2 V), it turns on the LEDs, which then begin to glow. A picture of the lighted LEDs after the threshold voltage from the output capacitor was reached is shown in Figure 6b. This device can be used to charge many capacitors sequentially over a longer period to obtain a much higher stored energy that can be used for various applications, such as powering wireless sensors, wearable/implantable bio-electronic devices, or smart monitoring devices [42; 43; 44].
## 4 Problem Definition and Optimization Approaches
### Routing Task Results after Disconnections  
Before tasks are transmitted for offloading, a mobile node identifier value is packaged with the task for transmission. When the task arrives at an edge device, if the task is to be further offloaded, the node identifier of the edge device is also attached to the package with the task for transmission. These identifiers can be used to trace back the origin of a task in normal circumstances without disconnections.  
In an event when a mobile device disconnects from an edge device and connects to a new edge device, the mobile device puts its node identifier inside a list structure and broadcasts a package containing the list into the network. For the sake of simplicity, we call the package sent with this list structure containing the node identifiers a \"discovery package\". Each time an edge device receives a discovery package, it checks the node identifiers inside the list. If the node identifier of the edge device is already inside the list, the package is dropped. On the other hand, if the list does not contain the node identifier of the edge device, the edge device adds its node identifier to the end of the list and rebroadcasts the package. In the latter case, the edge device also stores the discovery package in memory for later use.  
When task execution is completed in an edge device, firstly the sequence of node identifiers augmented with the task are used to send back the task result to the original sender of the task. If the sequence requires transmission of the task results to a node to which the current node does not have a connection, then the current node searches its stored discovery packages to find another route to the mobile device. If no such route is found, the task result is stored in a waiting list and reattempted after each discovery package arrival. This process is repeated until the task result is delivered to the mobile device.
# Two-Dimensional Digital Beam Steering Based on Liquid Crystal Phase Gratings
## 2 Materials and Methods
### Calibration  
The LC cells were calibrated at room temperature (25\({}^{\circ}\)) to establish their relationship between driving PWM signal and induced phase delay, as previously described [34] (Figure 9).  
The phase delay as a function of the PWM duty cycle (dc) follows a pseudo exponential decreasing function:  
\[\delta=A\cdot\mathrm{e}^{-B\cdot\mathrm{dc}}+C, \tag{4}\]  
The fitted intensity curve (Equation (2)) was employed to calculate the required PWM for any desired retardation level used in the different topologies (Figure 10).  
Figure 8: The 12 bits PWM driver that controls the LC cells.  
Figure 9: Calibration set up, including 632.8 nm He-Ne laser, attenuator, LC cells, electronic driver, polarizers, and camera.
# Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach
## 3 Proposed Detection Framework
### Designing a CNN-Based Malicious Network Traffic Detection Model
The parameter update optimizer used Adaptive Moment Estimation (Adam) [86], which provides a fast learning speed by quickly converging to the global minimum. The final output layer used the _sigmoid_ function, as shown in Equation (6), for binary classification. \[\hat{y}=\sigma(z)=\frac{1}{1+e^{-z}} \tag{6}\]  
\[ \begin{cases}1&\text{if }\hat{y}\geq 0.5,\text{ (Attack)}\\ 0&\text{if }\hat{y}<0.5,\text{ (Normal)}\end{cases}  \tag{7}\]  
where \(z\) denotes the value of the input image just before it is passed to the final output layer after passing through the network. This value is processed by the _sigmoid_ function, outputting a probability value, \(\hat{y}\), between 0 and 1. As shown in Equation (7), if the value is 0.5 or higher, the packet is classified as an attack; if the value is less than 0.5, the packet is classified as normal. Binary cross-entropy is used for parameter updates, as calculated in Equation (8). During model training, weights are adjusted to minimize the difference between the ground truth value and the predicted value. \[L(y,\hat{y})=-\frac{1}{N}\sum_{i=1}^{N}y_{i}\log(\hat{y_{i}})+(1-y_{i})\log(1 -\hat{y_{i}}) \tag{8}\]  
where \(y\) denotes the ground truth, while \(\hat{y}\) signifies the predicted value.
# Efficient CORDIC Iteration Design of LiDAR Sensors' Point-Cloud Map Reconstruction Technology +
## 5 Experimental Results
### Processing Time  
The LiDAR decoding process can be divided into three parts. The first part is the classification of the input data. The second part is the CORDIC algorithm, which mainly looks for the values of SIN and COS. The third part is the calculation of the XYZ coordinates. The processing times of these three blocks are different, and the total processing time is 0.094 s (Figure 24). To increase the overall circuit processing speed, the decoding circuit was designed as a decoding chip to improve the system processing time.
# Power System State Estimation Approach Considering Transmission Line Temperature
## 7 Conclusions  
The SE considering the influence of line temperature is studied, and the ETC-SE approaches are proposed to reduce the temperature-dependent errors. An ETC-SE model integrating the HBE and WLS-SE is established. In addition, the AJ-ETC-SE approach is presented to simultaneously solve the problems of SE and temperature estimation through an augmented Jacobian matrix. For the sake of accelerating the solving process, the ITS-ETC-SE approach is proposed, in which the SE and temperature estimation are decoupled and solved via alternate iteration.  
The effectiveness, efficiency, and convergence performance of the proposed ETC-SE approaches are verified through the IEEE 14-, 39-, and 118-bus systems. Results show that the proposed ETC-SE approaches can reduce estimated errors evidently and estimate line temperature precisely. The accuracy of the AJ-ETC-SE approach is slightly higher than the ITS-ETC-SE approach. Further, the ITS-ETC-SE approach is able to accelerate the calculation process. Furthermore, the ETC-SE approaches possess good convergence performance with varying environmental circumstances and ill-conditioned branches.  
In future studies, the influence of the measurements of PMUs on the SE will be considered, and an ETC-SE approach will be provided based on hybrid measurement data.  
Conceptualization, Y.C. and H.Z.; methodology, Y.C.; software, Q.X.; writing--original draft preparation, Q.X. and Z.G.; writing--review and editing, H.Q. and Q.X.; supervision, Y.C. and H.Z. All authors have read and agreed to the published version of the manuscript.  
This paper is funded by Shandong Provincial Natural Science Foundation (No. ZR2021 QE133).  
The authors declare no conflict of interest.
## 1 Introduction
Studies like this show that functional training for prosthesis use can speed up the adaptation process and improve user performance in daily activities. However, significant problems are currently presented by conventional hand prostheses, arising from issues such as low customization, resulting in an aesthetically unappealing appearance [18; 19]. Issues such as dimensional inaccuracies, excessive weight, and discomfort during use are critical factors that directly affect the functionality of prostheses. Additionally, limitations in manipulation and overall convenience further undermine their effectiveness [18; 20]. An upper limb prosthesis considered \"ideal and comfortable\" should be recognized by the user as an extension of their natural body. It must replace and meet, within its potential and functionalities, the motor, emotional, and social capabilities of the amputated limb, promoting practical and pleasant use [15; 21]. Creating devices that take into account the anatomy and individual preferences of the patient can increase the acceptance and efficiency of prostheses [17]. This article aims to develop a parametric hand prosthesis designed to address various levels of partial or total hand amputations using additive manufacturing technologies. The proposed approach leverages advanced manufacturing methods that allow for the customization of the prosthesis according to the anatomical features and functional needs of each patient. The primary focus of this work is on the characterization of materials, design development, construction, and additive manufacturing of the prosthesis, with a particular emphasis on engineering aspects such as dimensional accuracy, optimization of manufacturing processes, and sustainability. This project aligns with recent advances in the application of additive manufacturing for prosthesis customization [6, 7, 8, 9]. Furthermore, the mechanical feasibility of the prosthesis will be assessed through finite element analysis (FEA), which will help ensure the prosthesis's structural integrity and functionality at various amputation levels. FEA serves as a critical tool for predicting the mechanical behavior of the prosthesis prior to physical manufacturing, enabling design optimization and the identification of potential weak points. While clinical testing with patients is vital for the final validation of the prosthesis, this stage is not part of the present study. However, it is planned as a future step in our multidisciplinary bioengineering laboratory, where the integration of various engineering and health disciplines will be key to the next phase of development.
## 2 Theoretical Background  
### Issues in Wildfire Management and Firebreak Construction  
Wildfire management comprises two important stages: prevention and response (firebreak construction). In the prevention stage, the risk of wildfire occurrence can be reduced, and effective responses to initial outbreaks can be provided by establishing fire prevention lines (i.e., firebreaks) [5]. These lines act as obstacles along the spread path of a wildfire, thereby delaying its propagation and facilitating efficient firefighting operations [6].  
In the response stage, firebreaks are constructed by deploying personnel and helicopters. According to Article 2 of \"Integrated Regulations for Wildfire Management\", firebreak construction with manual labor involves establishing firebreaks by utilizing natural terrain features (such as rivers and rocks) or employing methods such as clearing undergrowth, removing leaf litter, and digging trenches to create fire containment lines [7].  
However, firefighting and prevention efforts that rely on human labor have physical limitations and raise safety concerns [4]. Although the safety of firefighting personnel has been evaluated as the most crucial element of the firefighting response, its importance has been ranked the lowest [8]. The use of helicopters for constructing firebreaks is highly effective for safeguarding residential areas and critical infrastructure [9]; however, aerial firefighting using helicopters is perceived as ineffective during nighttime, and helicopter pilots have reported experiencing hazardous situations during aerial firefighting operations [10].  
The authors of this study aim to establish firebreaks for suppressing low-intensity wildfires caused by surface fires and spreading ground fires, rather than high-intensity fires. Wildfires tend to spread primarily from grass fires, and it is crucial to establish effective firebreaks to prevent and mitigate large-scale wildfires. Grass fires act as a major catalyst for high-intensity wildfires, and without proper control, wildfires are highly likely to spread expansively. Therefore, setting up appropriate firebreaks in advance is essential for effectively controlling the spread of high-intensity wildfires and preventing their occurrence.  
However, firefighting activities in areas affected by wildfires present two main challenges. First, the burning of farmland and crop residues by farmers can escalate into wildfires or large-scale fires [11]. Despite the awareness that the burning of fields is a major cause of wildfires, farmers continue this practice [12]. Second, the areas in which fires occur are typically narrow and situated between rice paddies, which constrains the entry of fire trucks. An evaluation of the road conditions within rural communities with a focus on residents revealed a need for \"increasing the road width to facilitate the passage of emergency vehicles such as firetrucks and ambulances\" [13]. This signifies the necessity of increasing road width, especially in areas that are prone to wildfires and located between rice paddies, to facilitate easier access for emergency vehicles, including firetrucks and ambulances.
# Performance Evaluation of Reinforced Recycled Aggregate Concrete Columns under Cyclic Loadings
## 1 Introduction
Thus, the main purposes of the present study are two-fold: (i) to investigate the modeling method of RRC columns under combined action of constant axial load and cyclic lateral loading, based upon a fiber-based numerical approach; (ii) to examine the effects of a range of variables (such as the replacement ratio of RCAs, the mixing method of RAC, and the yield strength and area ratio of longitudinal reinforcing bars) on the seismic performance of RRC columns. This allows an insightful seismic evaluation of those columns that has been less often addressed before. The remainder of this paper is organized as follows: a fiber-based modeling method is firstly developed to reproduce the cyclic response of RRC columns. Upon a careful benchmarking, the model is employed to perform a comprehensive parametric investigation to examine the effects of a set of potential influencing variables on the seismic performances of RRC columns. Furthermore, a grey relational model, capable of detecting the underlying, not easily discernible tendencies, is used to study the sensitivity of key variables. The research outcomes presented in this study provides valuable insights on the seismic design of RRC columns. The outcomes can be easily extended to performance-based evaluations, hence they are beneficial to the safe and rational use of those columns as lateral-load-resisting elements.
## 2 Materials and Methods
### Goal and Scope Definition
#### 2.1.1 Model Area Settings  
The authors conducted a questionnaire survey of local governments across Japan in 2019, identified the issues for cooperation between waste incineration plants and sewage treatment plants, and presented the conditions under which local governments with a high possibility of cooperation can be achieved [29]. Japan's waste incineration plants may be operated by a union that brings together multiple local governments or be operated independently by a single local government. However, in union operation, cooperation with the sewage treatment plant cannot be considered without the agreement of all participating local governments, which is a barrier to cooperation between the two facilities. In addition, there are two types of sewage treatment plants: the \"public sewage system\" operated by each local government and the \"watershed sewerage system\" operated by the prefecture. The watershed sewerage system is less likely to cooperate for similar reasons mentioned above. Japan has the most waste incineration plants in the world and has numerous subdivided organizations to manage them. This situation complicates cooperation between facilities, though cooperation is high when they are operated independently [29]. Therefore, to secure local governments' cooperation, waste incineration plants and sewage treatment plants' jurisdiction and management methods were input to QGIS 3.20 and visualized [30]. Figure 1 shows the results of visualizing the municipalities in Chiba Prefecture that operate both facilities independently.  
Figure 1: Cities in Chiba Prefecture that operate both facilities independently.  
In Chiba Prefecture, the following four cities corresponded to this: Ichihara City, Sodegaura City, Asahi City, and Tateyama City. The Keiyo Coastal Industrial Zone is near Ichihara City, and the city was set as the model area, considering the possibility of reducing the loss by using the waste energy generated industrially.
# Metallic, 3D-Printed, K-Band-Stepped, Double-Ridged Square Horn Antennas
## 3 Characterization of the Antenna  
The input impedance of the printed antennas were measured using a Rohde & Schwarz ZVA 50 VNA. The directivity and radiation patterns were measured in a far-field setup in an anechoic chamber. Figure 3a compares the simulated and measured \(|\)S\({}_{11}\)\(|\) of the 3D-printed antennas. The impedance bandwidth of the horn covers the whole K-band in simulation for \(|\)S\({}_{11}\)\(|\)\(<\)\(-\)10 dB. In the measurement, both the copper and aluminum alloy horns show an impedance bandwidth from 18 GHz to 26 GHz. Behavioral agreement is observed between simulation and measurement in the \(|\)S\({}_{11}\)\(|\). Figure 3b shows the gain of the horn. The simulated gain is \(>\)10 dBi across the K-band with a maximum gain of 13.17 dBi @ 24 GHz. In measurement, the aluminum alloy horn has \(\sim\)2 dB less in gain than in the simulation, with a maximum gain of 13.23 dBi @ 25 GHz, while the copper horn shows similar behavior as the aluminum alloy horn, with a maximum gain of 13.5 dBi @ 24 GHz. The discrepancies are caused by the conductivity difference and the surface roughness. The antennas are printed by different partners. The different surface roughness is caused by the skills of different technician in post processes. Since the conductivity of the aluminum alloy is lower than that of copper,  
Figure 2: Photographs of the 3D-printed, K-band-stepped, double-ridged square horns. The aluminium alloy horn: (**a**) outlook; (**c**) aperture view; (**e**) flange view. The copper horn: (**b**) outlook; (**d**) aperture view; (**f**) flange view.  
and the aluminum alloy antenna has a rougher surface finishing than the counterpart, a larger gain decrement is observed in the aluminum horn. Figure 3c-f reveal that both of the aluminum alloy and copper horns have very low side lobe levels in the boresight across the K-band. The measured radiation patterns agree well with the simulation. The increased cross-polarization and deteriorated front-to-back ratio in measurement are caused by diffraction due to the roughness on the inner surface and on the aperture of the horn.  
Figure 3: Measured performance of the 3D-printed, K-band-stepped, double-ridged square horns: (**a**) \(1S_{11}\) ; (**b**) gain; (**c**) radiation patterns on phi = 0° @ 18 GHz; (**d**) radiation patterns on phi = 90° @ 18 GHz; (**e**) radiaiton patterns on phi = 0° @ 26 GHz; (**f**) radiation patterns on phi = 90° @ 26 GHz.
# Registration of Urban Aerial Image and LiDAR Based on Line Vectors
###### Abstract  
In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR) data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR) in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS) test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.  
image registration; laser radar; multisensor data; urban areas; aerial image; linear feature