esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Test Results
### Effects of Chord Face Stiffener  
For N00-150, the stiffness and strength began to degrade early as out-of-plane deformations of the connecting chord face and longitudinal plate occurred at the unstiffened connection. In particular, inappropriate lateral supporting increased such premature strength and stiffness degradation. On the other hand, for S15-150 and S25-200 with the plate-to-RHS K-connection stiffened by chord face stiffener, the deformations of the connective chord face and longitudinal plate were greatly reduced, and consequently, the lateral resistance of the trusses, such as strength and stiffness, was greatly improved. Note that such stiffening effects were achieved even in the state where the design parameters  
Figure 8: Test results of stiffened plate-to-RHS connection: S25-200: (**a**) Lateral load-displacement relationship; (**b**) Failure mode.  
were beyond the limits of applicability specified in current design codes. For example, the steel yield strength of the chord member (\(F_{y}\) =405 MPa) exceeded the specified limit (=360 MPa) by 13%; for S15-150, the thickness of the chord face stiffener (\(t_{s}\) =15 mm) was only 77% of the minimum thickness specified in the CIDECT Design Guide 3; and for S25-200, the wall width-to-thickness ratio of the connecting chord face (\(b/t\) = 44.4) exceeded the specified limit (=40) by 11%.  
For the stiffened specimens S15-150 and S25-200, chord face plastification was delayed, and instead, the slip and subsequent hole bearing at the bolted joint of branch members became the governing limit states. In general, slip may limit or delay strength development in the slip-critical bolted connection; however, the connection slip that occurs while maintaining the frictional resistance can have positive effects of increasing ductility and energy dissipation, particularly under seismic loading. In this study, as shown in Figures 6-8, S15-150 and S25-200 with the stiffened truss K-connections displayed a hardening behavior dissipating considerable energy after the slip at the bolted joint of branch members. This indicates that, if the post-slip bearing resistance of the bolted joint of branch members is large enough to achieve stable cyclic behavior, the seismic performance of stiffened plate-to-RHS connections can be greatly improved by allowing slip at the slip-critical bolted joint.
# Remote Servo Tuning System for Multi-Axis CNC Machine Tools Using a Virtual Machine Tool Approach
## 2 Preliminaries
### Specifications of the Machine Tool System  
In this study, the proposed approach was applied in the Microcut-MCU-5X five-axis machine tool (shown in Figure 3) at National Chung Hsing University, Taiwan. Its major specifications are shown in Table 1. The CNC controller of the machine tool is TNC640, published by Heidenhain Co. (Schaumburg, IL, USA) [22]. By using TNC640, we could obtain table position by linear scales, spindle speed, speed or acceleration of each axis, etc.  
Figure 3: Five-axis machine tool MCU-5X in National Chung Hsing University (NCHU).  
Figure 2: Block diagram of feed drive system; (**a**) Servo motor system; (**b**) Mechanical system; and (**c**) Closed-loop systems.
## 3 Current Applications
### Retina
#### 3.2.2 Diabetic Retinopathy  
Diabetic retinopathy (DR) is a common microvascular complication that occurs in individuals with diabetes mellitus [48]. Worldwide, over 100 million individuals are dealing with DR, and it stands out as a primary cause of vision loss and blindness, particularly in the working-age adult group [49; 50]. Multiple studies explored the potential of PBM in the setting of DR. In 2022, [PERSON] and co-authors [51] guided a pivotal transition from animal studies to human application in cases of diabetic macular edema that did not involve the fovea. Despite promising results in reducing macular thickness, the small sample size raised caution in drawing definitive conclusions. The potential benefits underscore the need for larger investigations to establish optimal treatment parameters and address safety concerns, particularly in patients with pre-existing risk factors. [PERSON] and colleagues explored different energy levels of 670 nm light, adding valuable insights, and emphasizing the importance of dose optimization. The observed maximal reduction in central macular thickness at a specific energy level of 100 mW/cm\({}^{2}\) suggests the need for precise dosing in PBM treatment [52]. Another research by [PERSON] and co-workers supported the safety and efficacy of PBM in treating diabetic macular edema. The authors observed improvements in visual acuity, retinal findings and thickness suggesting positive outcomes and encouraging additional exploration of PBM's potential in this field [53]. [PERSON] and co-authors reported the same improvements in visual acuity and retinal findings of patients with diabetic macular edema using the Valeda multiwavelength PBM approach [54]. On the contrary, it is crucial to highlight the clear contrast between these results and those obtained in the study conducted by DCRC, in the AE protocol. The phase 2 randomized controlled trial currently stands as the largest randomized controlled trial investigating the efficacy of PBM on DME. A total of 135 adults were enrolled, 69 were assigned to receive PBM treatment, and 66 received placebo. The results, while confirming the safety of PBM, distinctly underscore the lack of scientific evidence regarding its efficacy in terms of anatomical and functional improvement. During the 4-month study period, no statistically significant improvements were observed in the central subfield thickness of optical coherence tomography (OCT CST). The OCT CST increased by approximately 13 \(\upmu\)m in the PBM group and 15 \(\upmu\)m in the placebo group. Additionally, central-involved diabetic macular edema (CI-DME) was found in 90% of eyes treated with PBM and 86% of eyes treated with placebo at the 4-month mark, with no significant differences between the two groups. Furthermore, there was a slight decrease in visual acuity (VA) in both groups, with an average of \(-0.2\) letters in the PBM group and \(-0.6\) letters in the placebo group [55].
## 4 The Experiments and Results
### Experimental Results
#### 4.5.3 Failure Detection Efficiency
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Tested Program**} & \multirow{2}{*}{**No. of Faults**} & \multicolumn{2}{c}{**Failure Detection Efficiency**} \\ \cline{3-4}  & & **2 nd-Order Mutation** & **Du-Pairs** \\ \hline Triangle & 2459 & 98\% & 91\% \\ \hline Sort & 2333 & 96\% & 84\% \\ \hline Stack & 354 & 89\% & 72\% \\ \hline Reversed & 956 & 100\% & 82\% \\ \hline Clock & 109 & 100\% & 75\% \\ \hline Quotient & 2597 & 100\% & 92\% \\ \hline Product & 759 & 100\% & 93\% \\ \hline Area & 405 & 100\% & 86\% \\ \hline Dist & 274 & 100\% & 89\% \\ \hline Middle & 319 & 100\% & 92\% \\ \hline \multicolumn{4}{c}{Total = 10,565} & Average = 98\% & Average = 86\% \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Failure detection ratio of second-order mutation and all du-pairs test suites.
# A Novel Piezoelectric Ceramic Actuator with Scissoring Composite Vibration for Medical Applications
## 3 Finite Element Modeling
### Harmonic Analysis  
Owing to the variable boundary conditions and working environments, the real scissoring vibration mode is vulnerable to excitation under resonant frequencies. Therefore, harmonic analysis is performed to further confirm the effective excitation of the vibration mode. An excitation voltage of 50 V is applied to the piezoelectric stack, with a sweeping frequency around the corresponding resonant frequency, under scissoring mode. The range of sweep frequency was set from 3480-3560 Hz and 2190-2260 Hz for an actuator with a beam tip length of 7 and 9 mm, respectively. Since the effective operation mode is the bending vibration at the beam tip, the displacement amplitude of the beam tip (point A) in the transverse direction is measured and compared with the amplitude at the beam point before the groove structure (point B). During the harmonic simulations, the left end of the back mass is clamped as a fixed boundary condition.  
The measured displacement amplitudes of an actuator with the beam tip of 7 and 9 mm are shown in Figures 4 and 5 respectively. Figure 4 shows that, at the resonance frequency of 3518.8 Hz, the transverse amplitude of beam tip (Point A) is 3.060 \(\upmu\)m, whereas a negligible amplitude of 0.0632 \(\upmu\)m is observed at the beam point (Point B). Figure 5 shows that the transverse amplitude of beam tip (Point A) and beam point (Point B) are 2.230 and 0.042 \(\upmu\)m under the resonance frequency of 2223.7 Hz,  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Parameter** & **Value** & **Unit** \\ \hline [PERSON]’s modulus (E) & 193 & GPa \\ Density (\(\rho\)) & 8000 & kg/m\({}^{3}\) \\ Poisson’s ratio (\(\
u\)) & 0.29 & - \\ Length of beam & 20 & mm \\ Length of beam tip & 7/9 & mm \\ Length of groove & 2 & mm \\ Width of beam & 3 & mm \\ Thickness of beam & 0.5 & mm \\ Groove angle & 80 & degree \\ \hline \hline \end{tabular}
\end{table}
Table 1: Physical parameters of the actuator beam and material constants.  
respectively. It should be noted that both models exhibit large transverse amplitude at the beam tip (Point A) and a negligible transverse amplitude at the beam point (Point B). Obviously, the bending vibration concentrates on the beam tip and the deflection on other part of beam is restricted successfully. Therefore, based on the harmonic analysis, the proposed design exhibited excellent performance for scissoring mode excitation.
## 4 Segmentation Performance Evaluation  
Several evaluation measures are computed to quantify segmentation performances by comparing masks--obtained from analyzed unsupervised methods--and the ground-truth--provided by a radiologist, with more than 5-year experience on breast MRI, in consensus with a consultant breast radiologist (with more than 30-year experience on breast imaging). To obtain an accurate and detailed quantification, both area-based and distance-based metrics were used. The reason behind this choice is that area-based metrics strongly depend on region size and are not always able to evaluate the precision of a segmentation approach. On the other hand, distance-based metrics take into account the distance between the boundaries of the two segmentations to be compared, ignoring the actual volume difference between the two masks.
## 2 Privacy and Security Issues
**Phishing attacks:** With the widespread adoption of the Internet of Things, where each user has a unique identity and utilizes the network interface to access or manage smart devices, hackers may attempt to obtain critical information about savvy users or devices by sending a fake message or email. Users exchange personal information with the network as an IoT-based application to monitor and manage the environment in real time. Therefore, trust management concerns will arise among the network's nodes if a node in the network behaves maliciously. **Authentication:** Intelligent devices, sensors, actuators, and some smart devices make up an IoT application, which monitors and computes. Smart devices collect data or information, which is then transferred to the next layer for processing and computation. The network node triggers the related event once the calculation is complete. **Malicious attack:** Smart devices used in IoT applications are exposed to the outside world due to unprotected wireless connections and communication pathways. An attacker might compromise the device by injecting malicious code into the device via the software. **Unauthorized attack:** Because most IoT devices are connected through a separate router, the attacker uses several techniques to obtain authorization credentials. After obtaining personal credentials, the attacker has access to the network data. Policy enforcement: One of the most critical security issues in IoT applications is policy, which allows users to utilize smart devices. Adequate rules must be defined by the application's needs to ensure user privacy.
## 6 Conclusions  
This paper introduces an integrated path controller consisting of an upper-level controller and a lower-level controller. The upper-level controller is the NMPC with a terminal-cost state tracking controller, which provides the upcoming longitudinal velocity and steering rate for path tracking. To meet the requirements of the upper-level controller, a lower-level controller is proposed, which includes a steering controller and a driving controller.  
Verification experiments were conducted to validate the lower-level controller. The results demonstrate that the lower-level controller can accurately and rapidly achieve the desired longitudinal velocity and steering rate.  
Path tracking experiments on a single shift line were performed using the integrated controller. The results indicate that the vehicles can precisely follow the reference path at different reference velocities. However, the controller with the terminal cost is more accurate and stable. The controllers' solution times are all guaranteed to be less than the control time interval. However, as the reference velocity increases, both the peak lateral error and the peak heading angle error increase, and the solution time of the controller also increases.  
This paper presents several significant contributions in the field of vehicle path tracking control.  
(1) A novel method for controlling the articulated angular speed of the vehicle is proposed. Specifically, a stepper-motor-controlled fully hydraulic steering gear is employed to achieve wire control. Compared with the traditional solenoid-proportional directional valve, this control method exhibits no dead zone of steering speed, thus enabling the controller to achieve smaller steering speed. Furthermore, the coupling relationship between the engine, hydraulic oil pump, and solenoid proportional directional valve is decoupled, leading to simpler and more accurate steering control.  
(2) A driving controller is developed using a BP neural network approach. The proposed controller is capable of ensuring that the vehicle can meet desired speeds for different loadings, surpassing other drive control algorithms in terms of performance.  
(3) A terminal penalty cost is introduced into the NMPC controller, which significantly enhances the stability of the controller and reduces path tracking errors. Building upon this study, future research will focus on improving the stability and robustness of the NMPC. Additionally, machine learning algorithms will be utilized to enhance the prediction model's accuracy and adaptability.  
Methodology, N.S.; software, N.S.; validation, N.S.; writing--original draft preparation, N.S.; writing--review and editing, J.Y. and W.Z.; visualization, N.S.; project administration, J.Y.; funding acquisition, J.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key Research and Development Program of China, grant number 2018 YFC0604402.  
Not applicable.  
The authors would like to thank the National Key Research and Development Program of China for funding this research.  
The authors declare no conflict of interest.
# Traffic Signal Control with State-Optimizing Deep Reinforcement Learning and Fuzzy Logic
## 6 Experimental Results
### Ambulance Prioritization System  
The experimental results are presented in Table 14. Data for the duration of safety at 3 s and 5 s, as well as the detection distances of 150 m, 200 m, 250 m, and 300 m are shown.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{4}{c}{**Average Total Waiting Time(s)**} \\ \hline \multirow{2}{*}{**Lane**} & \multicolumn{4}{c}{**Method**} \\ \cline{2-4}  & **Traditional** & \begin{tabular}{c} **Original DQN** \\ **with Fuzzy Logic**[29] \\ \end{tabular} & \begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} \\ \hline E-3 S-3 W-3 & 122.02 & 22.48 & 17.37 \\ \hline E-3 S-3 N-3 & 95.74 & 21.09 & 17.86 \\ \hline E-3 N-3 W-3 & 118.49 & 22.38 & 16.90 \\ \hline S-3 N-3 W-3 & 113.16 & 21.20 & 17.51 \\ \hline \multicolumn{4}{c}{**Average total waiting time for vehicles to make a left turn(s)**} \\ \hline \multirow{2}{*}{**Lane**} & \multicolumn{4}{c}{**Method**} \\ \cline{2-4}  & **Traditional** & \begin{tabular}{c} **Original DQN** \\ **with Fuzzy logic**[29] \\ \end{tabular} & \begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} \\ \hline E-3 S-3 W-3 & 5.06 & 9.63 & 4.80 \\ \hline E-3 S-3 N-3 & 5.05 & 8.70 & 4.69 \\ \hline E-3 N-3 W-3 & 5.02 & 9.11 & 4.71 \\ \hline S-3 N-3 W-3 & 5.00 & 9.21 & 4.67 \\ \hline \multicolumn{4}{c}{**Average total waiting time per car(s)**} \\ \hline \multirow{2}{*}{**Lane**} & \multicolumn{4}{c}{**Method**} \\ \cline{2-4}  & **Traditional** & \
\begin{tabular}{c} **Original DQN** \\ **with Fuzzy logic**[29] \\ \end{tabular} &
\begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} \\ \hline E-3 S-3 W-3 & 13.39 & 5.40 & 4.25 \\ \hline E-3 S-3 N-3 & 12.41 & 5.28 & 4.28 \\ \hline E-3 N-3 W-3 & 13.46 & 5.38 & 4.17 \\ \hline S-3 N-3 W-3 & 12.94 & 5.27 & 4.22 \\ \hline \end{tabular}
\end{table}
Table 13: The experimental results in three-lane and three-arm environments.  
A few variables were considered when selecting the appropriate safety duration and detection distance for the ambulance prioritization system, which consists of two metrics: the average total waiting time and total ambulance waiting time. When analyzing the average total waiting time, it was observed that using a detection distance of 300 m results in the highest value. Consequently, they were deemed to be inappropriate for use. When analyzing the total ambulance waiting time, the pair with a safety duration of 3 s and detection distance of 250 m provided the optimal value, indicating no waiting time for the ambulance. Therefore, a safety duration of 3 s and a detection distance of 250 m were selected for the ambulance prioritization system.  
Based on the experimental results shown in Table 15, using a safety duration of 3 s and a detection distance of 250 m, it was found that the average total waiting time is similar for the proposed method. However, the original DQN with the fuzzy logic method had an approximately 5.39% higher average total waiting time. Overall, the proposed method provided better results.
# The Big Picture: An Improved Method for Mapping Shipping Activities
## 4 Improving AIS Data  
In this section, two methods for improving the trajectories given by the AIS data are provided. First, we propose a grid-based reconstruction technique for filling large temporal gaps on the AIS data. After that, we describe a pipeline for generating additional vessel  
Figure 6: Density map for the cleaned SAT-AIS messages from the month of October 2021 from central European waters, depicting the total time vessels spent in each grid cell in hours (according to the color caption).  
Figure 7: Density maps for four different resolutions (in terms of grid cell length in km, top: left 200 \(\times\) 200 and right 100 \(\times\) 100, bottom: left 10 \(\times\) 10 and right 1 \(\times\) 1) for SAT-AIS data from the month of October 2021 from central European waters (depicting the total time vessels spent in each grid cell in hours).  
positions using satellite images. The following methods can be applied to any AIS dataset in order to improve its quality and in turn lead to more accurate depictions of vessel traffic. The presented techniques are suitable for different types of vessels. Most precisely, the trajectory reconstruction can be applied to all vessel types that follow repetitive patterns. On the contrary, results have shown that most vessels that often diverge such patterns, like pleasure crafts or small fishing boats, do not benefit from such techniques. Regarding satellite imagery, due to the specifications of the images used, vessels of small dimensions are more difficult to be identified. More specifically, since the maximum pixel resolution is of 10 m length, vessels whose size is smaller than a few pixels may not be recognized by the CNN.
## 4 HSI in Fresh-Cut Product Quality Assessment
### Fresh-Cut Vegetables  
#### 4.4.1 Celery  
Fresh-cut celeries, one of the most widely consumed vegetables, are very rich in fibers. [PERSON] et al. (2017) applied an HSI device (380-1000 nm) to quantify the soluble and insoluble dietary fiber in celery, and their spatial distribution was visualized at 0, 7, 14, 21, and 28 days of storage (Figure 12). Celeries showed interesting spectral variability values in the shortwave near-infrared region (from 780 to 1008 nm). Different PLS prediction models were developed using a variant of the PLS method (the genetic synergy interval partial least square, GA-Si-PLS) to select the optimal wavelengths with minimal redundant information. The obtained models showed high prediction performance for both (R\({}^{2}\) equal to 0.96 and 0.97 and RMSE of 1.18 g/100 g and 0.34 g/100 g, respectively) insoluble and soluble fiber [42].  
Figure 11: Distribution of total sugar content (TSC) in apple slices predicted by the PLS models proposed by [PERSON] et al. (2021). Reprinted with permission from Ref. [54]. 2021, Elsevier.
# Towards an Efficient Chipless RFID System for Modern Applications in IoT Networks
## 1 Introduction  
In recent years, the diffusion of various wireless technologies has shown natural binding affinity towards the Internet of Things (IoT). Under the framework of the IoT, the heterogeneous devices are networked together to share or transfer data wirelessly or in wired mode. With the addition of new sensors, devices, and subnetworks, the volume of the IoT is growing, and therefore an improvement in the pervasiveness of the IoT is in high demand. Low power or ideal self-powered devices having low cost with compact size can enhance the pervasiveness of IoT networks. Therefore, for such scenarios, chipless radio-frequency identification (RFID) tags and sensors are the most suitable devices to be widely deployed in IoT networks where tagging and sensing is required [1, 2, 3].  
Chipless RFID tags and sensors are passive in nature, have miniaturized dimensions and low cost which can be deployed in a variety of applications such as defense and logistics, food processing, healthcare, agriculture and environment, retail industries, and banking, in addition to other applications that operate under the umbrella of the IoT framework [4, 5, 6, 7, 8].  
Robust operation of IoT networks requires low latency, low powered miniaturized nodes and tags, appropriate communication range between nodes to prevent complex multi-hop transmissions, reduction of data packets collision and drops, and increased data throughput. These can be achieved by using pattern reconfigurability of the RFID readers, adopting multi-resonator RFID chipless tags, adopting more directive RFID antennas, and exploiting spatial reuse of the nodes [9].  
With the bulk deployment of RFID tags in IoT networks, the integrity of the data generated must be maintained at every level. Therefore, data from the working nodes, RFID tags, sensors, and devices operating in IoT networks can be processed as Big Data, which incorporates methods and techniques related to data management, storage, and analysis [10, 11]. To ensure the accuracy of data is preserved, the specificity of the RFIDtags should be confirmed at deployment stages. Therefore, validation of devices such as chipless RFID tags working as a standalone system is inevitable.  
Therefore, the presented research is an attempt to validate the specificity of a novel chipless RFID tag while operating as a standalone unit prior to its deployment in an IoT network. The proposed validation system is comprised of a chipless RFID tag that exhibits a high bit encoding capacity suitable to be adopted for IoT networks [12; 13], and a high gain ultra-wideband antenna module [14; 15; 16]. The modeling and simulation of tag and antennas were performed in Computer Simulation Technology Microwave Studio while RT Duroid 5880 substrate (\(\epsilon_{\rm r}=2.2\), tan \(\sigma=0.0009\), and h = 0.79 mm) was used for fabrication.