esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The combined effect of non-thermal plasma (NTP) and hydropriming on the germination performance and seedling characteristics of specific varieties of cucumber (_Cucumis sativus_ L.) and broccoli (_Brassica oleracea_ var. _italica_ [PERSON]) seeds after short-term storage is reported. Seeds were treated with NTP for 10 and 15 min, followed by hydropriming in distilled water for 24 h, and then stored for six months in the dark before evaluation. The treated cucumber seeds demonstrated a statistically significant enhancement in seed germination and seedling vitality indices. In contrast, broccoli seeds showed no significant improvement. The stimulatory effects observed in cucumber may be attributed to reactive oxygen and nitrogen species, which act as signaling molecules to promote stress tolerance and early growth. This study also highlights the potential of combined NTP treatment and hydropriming as a pre-sowing treatment for select crops, underscoring the need for species-specific optimization. The used, portable, and relatively inexpensive NTP device offers practical advantages for agricultural applications.  
non-thermal plasma; hydropriming; aging; germination; seedling characteristics Article
# Using Deep Learning for Collecting Data about Museum Visitor Behavior
## 2 State of the Art  
Nowadays, technology is increasingly exploited to improve users' quality of life anywhere and anytime, when they use local transport services [9] or visit points of interest [10]. In particular, the possibility of providing museum curators and staff members with a system to track visitor behavior for improving the service offered is a widely investigated topic. In [11], the authors propose a computer vision algorithm based on Kinect and RGB-D camera. They track groups of visitors at the National Museum of Emerging Science and Innovation (Miraikan) in Tokyo, Japan, to identify the leader and study their dynamics. In [12], the authors present an IoT- (Internet of Things) based system to measure and understand visitor dynamics at the Galleria Borghese museum in Rome, Italy. A similar approach is described in [5], in which the authors report the results of a case study conducted at the CoBrA Museum of Modern Art in Amstelveen, the Netherlands. Tracking can be also used to understand how the flow of visitors inside a museum is oriented. In [13], the authors propose a method based on LIDAR to identify human beings and track their positions, body orientation, and movement trajectories in any public space. The system can accurately track the position of the visitor inside the museum. It has been tested at the Ohara Museum of Modern Arts in the Kurashiki area of Okayama Prefecture, Japan. In [3], [PERSON] et al.  
propose a visual guide for museum curators and staff. Their system can show routes of interest and hotspots, and analyze visitor behavior. It has been tested at the Hecht Museum, University of Haifa, Israel. There are already numerous thorough and exhaustive works that review the main indoor localization technologies (e.g., see [14; 15; 16; 17; 18; 19]). On the other hand, fewer works are focused on analyzing the technologies for the localization of museum visitors. The goal of our study is to propose a tracking system easy to use by museum curators and staff. Moreover, it has to capture as much information as possible about visitor behavior in real time. Finally, it should be ready to accommodate several further developments like visitors' micro-expressions recognition when looking at an artwork and subsequent recommendation. For this reason, we now analyze the hardware most commonly used for this aim by examining the strengths and weaknesses of the principal indoor localization technologies.
## 6 Conclusions  
In this paper, the time frequency distributions of various communication signals are first analyzed via Choi-Williams analysis. The distributions of the baseband and binary modulated pulse shaping signals are time-varying and regular, which facilitates the pass region generation procedure. Then, the equivalence of the time frequency distributions of the baseband and RF signals is discussed, and two methods are proposed to guarantee the consistence by adjusting the window length and zero padding. In addition, the masking threshold constrained time-varying filter is applied to suppress the co-channel interferences, of which the pass region is generated according to the energy distribution of the desired signal. According to the simulation evaluations, the proposed time-varying filter can suppress the co-channel interference efficiently, especially when the interference power is strong.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the paper; [PERSON] revised the paper.  
This work was supported in part by Heilongjiang provincial Internet of things perception layer and sensor network technology innovation service platform, and in part by the Basic scientific research project of Heilongjiang Province under Grant No. KJCXZD201704. This work was also partly supported by the National Natural Science Foundation of China (61602127).  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
4-QAM 4 th order Quadrature Amplitude Modulation BER Bit Error Rate BPSK Binary Phase Shift Keying BT Bandwidth Time product CWD Choi-Williams Distribution D2D Device-to-Device communications \(E_{b}/N_{0}\) Bit energy to noise spectral density ratio GNSS Global Navigation Satellite System GWS General Weyl Symbol LPF Low Pass Filter LTV Linear Time Varying M-QAM Mth order Quadrature Amplitude Modulation QPSK Quadrature Phase Shift Keying SC-FDMA Single Carrier-Frequency Division Multiple Access SIR Signal to Interference Ratio SINR Signal to Interference and Noise Ratio SNR Signal to Noise Ratio STFT Short Time Fourier Transform WVD Wigner-Ville Distribution
# Underwater Acoustic Target Tracking: A Review
## 6 Discussion, Challenges, Countermeasures, and Lessons Learned
### Countermeasures
Base on the relationship, the tracking algorithm can automatically adjust the number of sensors transmitting information to meet the requirement of specific application scene.
However, each study found different NDRAs due to varying participants, research methods, contexts, and other factors, and the evolution of NDRAs across Levels 3, 4, and 5 automation remains fuzzy as well. A better understanding of NDRAs and their evolution across Levels 3, 4, and 5 is crucial for car interior design, as interiors will need to be adapted to align with these user activities [14]. For instance, the current car seat is optimized for driving [15], but as automation increases, new interior designs will be required to accommodate a broader range of activities. [PERSON] et al. [16] found that people adopt different postures in automated cars compared to traditional driving situations, highlighting the need for these adaptations. This review examines the prioritization of NDRAs in which consumers wish to engage within self-driving vehicles at Levels 3, 4, and 5. Evidence from existing research was synthesized into a meta-analysis highlighting the importance of different NDRAs and the transition from L3 to L5. Potential changes needed in car interior design are also emphasized. The prioritized list aims to provide clear guidance for car manufacturers and designers, helping them create vehicle interiors that enhance user comfort and optimize the in-car experience in future AVs.
# Contrast-Invariant Edge Detection: A Methodological Advance in Medical Image Analysis
## 1 Introduction
This substitution aimed to diminish the impact of speckle noise on edge detection and enhance the accuracy of edge detection. To further remove the interference of Salt-and-Pepper noise as well as random noise in the image, [PERSON] et al. [20] put forward an edge detection approach based on median filtering, which better retains the edge information and does not destroy the detail information, can effectively detect the edges in medical, natural or industrial images, and has strong versatility. [PERSON] et al. [21] proposed an edge detection method founded on the matching tracking algorithm for multiple application scenarios. The algorithm transforms the edge detection issue into a signal processing matter. It holds the merits of being noise-insensitive and capable of detecting weak edge pixels. It shows potential for application in the diagnosis and treatment of medical image-related diseases. [PERSON] et al. [22] proposed a quasi-high-pass filtering operator for medical images, which calculates the local grayscale mean value and local signal energy variations within a 3 \(\times\) 3 neighborhood. The operator has good adaptivity and isotropic symmetry, and it can accurately locate the edges and reduce the blurring of the edges. However, owing to the intricacy and particularity of medical images, these methods may not be able to accurately recognize the edges of the lesions when the medical image contrast is low, resulting in incomplete or inaccurate edge information being extracted. To overcome these problems, we propose the Contrast-Invariant Edge Detection (CIED) method, which does not directly rely on the change of grayscale but combines the information of three Most Significant Bit (MSB) planes to obtain the final edge detection result. The CIED is capable of efficiently extracting the image edges and is insensitive to different contrasts. The contributions of this paper are summarized and listed below:  
* A new Contrast-Invariant Edge Detection (CIED) algorithm is proposed. It performs better in terms of visualization and applicability. * Experimental results are presented to confirm the effectiveness of CIED. This includes visualization, as well as contrast-invariant robustness and comparison with other methods. * A new edge detection test dataset based on medical images is created. It contains different kinds of medical images that can be efficiently employed to assess the performance of edge detection methods. This paper's primary structure is as follows. Section 2 introduces the concepts of Most Significant Bit (MSB), Least Significant Bit (LSB), and bit plane. Section 3 describes the CIED method. Section 4 shows the detailed experimental results and comparisons. Section 5 further analyzes the experimental results and discusses the CIED method. Section 6 summarizes our findings.
# Accurate Collaborative Globally-Referenced Digital Mapping with Standard GNSS
## 5 Empirical Results
### Rover and Reference Platforms  
The rover GNSS receiver is one among several sensors housed in an integrated perception platform called the University of Texas Sensorium [6]. Designed for connected and automated vehicle research, the Sensorium is a self-contained sensor housing that can be mounted atop any standard passenger vehicle. Two Antcom G8 Ant-3A4 TNB1 triple-frequency patch antennas are flush-mounted in the cross-track direction on the Sensorium's upper plate, separated by just over one meter. The antennas' signals are routed to a unified radio frequency (RF) front end whose output intermediate frequency (IF) samples are processed in real-time (to within less than 10 ms latency) by the Sensorium's onboard computer  
Figure 10: GEOSLAM trajectories after joint BA of current and prior keyframes (in green), overlaid on the corresponding (black and red) trajectories from Figure 8. (**a**) Top view of the trajectories. Note that both the current and prior keyframes (and map points, not shown) have been adjusted to optimally minimize the BA cost function over \(N_{m}\) levels of covisibility. (**b**) View from \(5^{\circ}\) elevation.  
The samples are also stored to disk for post-processing. The experimental setup also includes a surveyed GNSS reference station that aids in the generation of the ground truth trajectory.  
The GNSS data were processed by a software-defined GNSS receiver tracking signals from GPS L1 C/A, GPS L2 CLM, Galileo E1, and SBAS. Data from both the primary (passenger's side) and secondary (driver's side) antennas were used to reconstruct a sub-dm-accurate CDGNSS-based ground truth trajectory, as described in [6]. Enhanced code-phase positioning was performed on the data from the primary antenna, incorporating precise orbit and clock products from IGS, ionospheric corrections from WAAS satellites, and the Saastamoinen model for tropospheric corrections, in addition to NIS-based exclusion of multipath signals. Double-differenced pseudorange-based positioning was also performed with the data from the primary antenna, as discussed later in this section. The code-phase-based position estimates were (i) compared against the ground truth from the primary antenna to study the code-phase positioning error statistics, and (ii) fed to GEOSLAM for vision-GNSS sensor fusion. The primary antenna feed was also input to a ublox M8T receiver for comparison against the enhanced code-phase software receiver.  
The Sensorium features a front-facing stereo camera rig composed of two Basler acA2040-35 gm cameras that capture synchronous stereo image pairs when triggered by a signal tied to the GNSS front-end's sampling clock. The images are captured in grayscale at 10 frames per second and timestamped by the Sensorium's computer. The cameras are configured to automatically adjust the exposure time based on lighting, while the focal length, focus, and aperture are held fixed, having been adjusted physically prior to capture.
# Battery-Free Pork Freshness Estimation Based on Colorimetric Sensors and Machine Learning
## 3 Material and Method
### Calculation of PI Matching Network via Smith Chart  
RF energy harvesting approaches are utilized to power the proposed smart-sensor tag. Impedance matching circuits are necessary to increase the efficiency of receiving energy in the form of electromagnetic fields generated by resonance at the signal source of RF in the 915 MHz band. This method allows for maximum power to be transferred to the antenna-connected load. Impedance matching circuits are placed where the receiving antenna and sensor tag are connected.  
The Smith chart is used to match impedance by showing the relationship between the reflection coefficient and impedance on the transmission line [22; 23]. The equation relating the reflection coefficient and impedance expresses the impedance value on the complex plane where the reflection coefficient is expressed. The equation makes the load impedance equal to the complex conjugate of the impedance derived from the signal source.  
\[Z_{\mathrm{s}}=Z_{\mathrm{L}}^{*}=(R_{L}+jX_{L})^{*}=R_{L}-jX_{L} \tag{10}\]  
The proposed collinear antenna in this study uses a PI-type circuit for impedance matching.
# A Petri Net Approach for Business Process Modeling and Simulation
## 3 Related Work
### Disco  
DISCO (DISCOver your process) is a process mining software used to analyze and visualize business process data. Its characteristics include [34; 35]:  
* **Intuitive User Interface:** DISCO has a friendly and easy-to-use user interface, making it easy to load data, perform analysis, and view results.
* **Process Analysis:** DISCO offers a variety of tools to analyze business processes, including workflow visualization, pattern identification, and deviation detection.
* **Model Discovery:** DISCO can generate process models from event data, allowing users to understand how activities in a process unfold.
* **Conformance Analysis:** DISCO can be used to compare event records with a previously defined process model to identify discrepancies and deviations.
* **Process Visualization:** DISCO offers different types of visualization, such as flow charts, Gantt charts, and process maps, to help understand and communicate the flow of activities.
* **Performance Analysis:** DISCO can help to identify bottlenecks, wait times, and other areas for process improvement.  
* **Large Data Set Support**: DISCO can handle large event datasets, which is essential for analyzing complex processes.
* **Complex Events Support**: DISCO provides event handling with attributes and properties, allowing for more detailed analysis. While DISCO is a widely used and appreciated tool, it has features that might be considered disadvantages as well, for example [33]:
* **Cost**: DISCO is a commercial tool, which means that it may have costs associated with its acquisition and licensing. This may be a limitation for individual users or small organizations with limited financial resources.
* **Learning Curve:** as with any specialized tool, DISCO can have a steep learning curve for those who are new to process mining or to the tool itself. Understanding advanced functionality can require considerable time and effort.
* **Hardware Requirements**: DISCO may require significant hardware resources to handle large event datasets and perform complex analysis, which could limit its use on systems with insufficient capabilities.
* **Quality Data Dependency:** as with any process mining tool, the results are highly dependent on the quality of the input data. If the data are incomplete, inconsistent, or poorly recorded, the results could be less accurate or useful.
* **Data Format Support:** as with many tools, support for specific data formats could be a challenge. Users may need to adjust or transform their data before use.
# Performance Analysis of a Novel TCP Protocol Algorithm Adapted to Wireless Networks
## 3 Results
### Wireless Link Emulation  
In this experiment, we evaluated TCP-NACK performance by the Network Emulator (Netem) software, which is an utility available within the Linux kernel from the 2.6.7 version, and allows emulating the link properties by specifying bandwidth parameters, \(\delta\), losses, and traffic control using statistical probability [20].  
This experiment required a computer with the Ubuntu Operating System and with two network interfaces configured in bridge mode to emulate the wireless link. As user equipment, we employed two computers with the modified TCP-NACK Ubuntu Operating System, which acted as a client and a server, respectively. In each user equipment, we used the \"Iperf\" and \"Tcpprobe\" tools, available within the Linux repositories, those tools allowed to obtain the CWND and \(\overline{\theta}\) values.  
The scenario consisted of two computers interconnected by an emulated wireless link, which was managed in an intermediate computer by the Netem software, as showed in Figure 4. The link emulation was required to maintain a fixed error rate for multiple traffic injections.  
Netem is a utility available within the Linux kernel, it allows to emulate a communication link by the specification of its parameters [20]. Table 1 shows the parameters used for a 25-second emulation of the wireless link, with high packet errors probability, greater than 0.5% (\(P_{\mathit{seg.TCP}}\geq 5\times 10^{-3}\)). The commands used to define Netem parameters in the Linux terminal were:  
1. [noitemsep,topsep=0 pt]
2. [noitemsep,topsep=0 pt]
3. sudo tc qdisc add dev ethX root handle 1:0 tbf rate Bandwidthkbit
4. sudo tc qdisc add dev ethX parent 1:1 handle 10: netem corrupt Y% delay Z  
where ethX is the network interface name, Bandwidth is the link bandwidth in kb/s, Y is the error probability in percent, and Z is the \(\delta\) in milliseconds.
## 2 Materials and Methods
### Substrates, Water, and Seed Characteristics
#### 2.2.4 Irrigation Water  
The water that supplies the entire La Molina Experimental Center at the INIA headquarters had an almost constant pH of 7.7 and EC of 0.619 dS m\({}^{-1}\).
# Wide-Band Interference Mitigation in GNSS Receivers Using Sub-Band Automatic Gain Control +
## 4 Test Setup  
### Physical Setup  
Figure 3 shows the experimental setup. The setup has two signal sources. First, a stationary geodetic-grade antenna placed on the roof provides GNSS signals for the test setup. The signal is also adequately amplified to accommodate for losses expected by the setup and the connection to the roof. Second, interference signals are generated in the laboratory with an Agilent MXG-series vector signal generator. The output power is varied over time to analyze different interference-to-noise ratios (INRs).  
COTS GNSS receivers are used for analysis, as this focuses the test setup on the IM capabilities and does not limit it to the differences in GNSS processing. Two types of COTS receivers are evaluated to provide a broader range of analyses.  
Figure 3: Experimental setup.  
cost (LC) receiver (blue blocks in Figure 3) with limited built-in IM is used. This receiver is configured to use GPS L1 CA and Galileo E1 BC. Second, a high-end (HE) geodetic grade receiver (green blocks in Figure 3) with built-in IM is used. Receivers HE #2, #3, and #4 are configured to only use GPS L1 CA and Galileo E1 BC, but receiver HE #1 is configured to be multi-band and multi-system to provide maximum precision. A radio-frequency (RF) network connects the two signal sources to various receivers. These fall into four categories:  
1. [label=0., ref=0]
2. Roof Antenna: Receivers HE #1 and LC #1 are connected to the roof antenna without interference. These provide the interference-free ground truth signals.
3. HDDM-AGC: Receivers HE #2 and LC #2 get GNSS and interference signals. The signals are received with an radio-frequency front-end (RFFE), where the HDDM-AGC mitigation is implemented in firmware as described in Section 3. Unfortunately, this platform does not have an onboard DAC. Therefore, the most significant bit of the I and Q components of the signal after mitigation is up-converted back to the L1 band using a Rohde&Schwarz signal generator. The mitigated signal is then passed to the two receivers. Note that as this process only uses a 1-bit DAC, significant quantization loss is introduced [25].
4. No IM: Receivers HE #3 and LC #3 both have GNSS signals and interference signals, but no mitigation is enabled. The HE #3 receiver is explicitly configured to bypass all IM.
5. With IM: In the HE #4 receiver wide-band IM capabilities are enabled. It allows a direct comparison of the HDDM-AGC to the state-of-the-art IM.
## 3 Case Study  
The semantic rules for ship graph data are constructed with reference to the business rules of maritime supervision and maritime security, and the ternary processed ship ontology data are combined with the semantic rules to form a standard ship graph knowledge representation. A case study was carried out on river-sea direct ships.