esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Training Model
#### 2.4.2 YOLOv8 Model  
YOLOv8 is an advanced SOTA (state-of-art) model developed by Ultralytics which supports image classification, instance segmentation, object detection and tracking, etc. [22]. It was built on the YOLO series with an improved backbone which extracts image features and a detection head which predicts object locations and categories to further improve performance and flexibility.  
YOLOv8 selects the decoupling head, which removes the previous Objectness branch and only has decoupled classification, which is responsible for predicting the class of the object, and the regression branch, which is responsible for predicting the location of the object. Moreover, YOLOv8 abandons the anchor bases of the previous YOLO series and uses Anchor Free, which means that YOLOv8 no longer relies on preset anchor frames to predict object position but instead directly predicts the center point, width, and height of the target by simplifying the complexity of the model and improving the inference velocity. The improvement of the backbone is that YOLOv8 replaces the C3 module in YOLOv5 with the C2f module, which further lightens the model and obtains rich gradient flow information. In addition, YOLOv8 continues to use the SPPF module used in models such as YOLOv5, which is a spatial pyramid pooling layer and can integrate features of different scales. The main purpose is to achieve the effective fusion of global features, thereby enriching the feature information of the model.  
In this paper, the key points in the scatter plots of the key cross-section of the cleaning chamber needed to be identified by trying different pre-trained models. Five models were trained in the same batch, i.e., YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x. The scatter plots of the key cross-section obtained in 2.3.1 were used as the dataset and were randomly divided into the training dataset and the validation dataset in a ratio of 8:2 to prevent overfitting during model training.  
Figure 5: Key-cross-section scatter and key-point position diagram. (**a**) Slice thickness of 100 mm, (**b**) slice thickness of 20 mm, (**c**) slice thickness of 10 mm, (**d**) slice thickness of 2 mm, and (**e**) example diagram of key-point location, where 1 is the front endpoint of the upper-sieve surface, 2 is the rear endpoint of the upper-sieve surface, 3 is the front endpoint of the lower-sieve surface, and 4 is the rear endpoint of the lower-sieve surface.
## 3 Test Results
### Excess Support Pressure
#### 3.1.4 Measurement of Soil Deformation with PIV  
Particle Image Velocimetry (PIV) was adopted to monitor subsurface soil displacement on the vertical plane of symmetry in the test, which can enable displacement measurement at potentially thousands of points of the model with high accuracy by tracking the soil texture within a digital image and through successive images to monitor subsurface soil displacement on the vertical plane of symmetry. The PIV results are presented in the experimental type scale.  
The ground movement when the support pressure reaches the maximum value, that is, when the faceplate advances to the maximum value under different buried depths are shown in Figure 9. As it can be seen, the disturbance range of the ground induced by the excavation face advancement is roughly shaped \"fishtail\", which will be discussed in Section 4.1. It should be pointed that there exists a settlement area above the face. This phenomenon is attributed to the soil particles slide induced by the advancement of the faceplate, which imposes a squeezing effect on the soil at the face and accelerated the soil particles in front of the excavation to tend to squeeze forward and upward as a whole. As a result, the soil above the excavation surface is also disturbed and tends to slide forward and downward, which in turn causes the surface settlement directly above the excavation surface. In addition, the PIV analysis shows that the soil deformation characteristics are consistent with the results monitored by the laser displacement sensor that the ground movement can extend to the surface at both burial depths of 0.5 D and 1.0 D while it is difficult for the tunnel located at C/D ratio equals to 1.5 to extend to the surface. For the case where the ground movements propagate to the surface, the settlement area and the heaved area will be specifically discussed in Section 4.1.  
Figure 8: Curves of the heaving and face support pressure.
## 3 Implementation of Dynamic Balance Method
### Adaptive Notch Filter  
In this paper, an amplitude and phase solution method based on improved ANF is adopted. The method has a simple structure and good tracking performance.  
The input signal, as shown in Equation (11), is a single sinusoidal signal and contains a DC component, where \(A_{0}\) is the DC component, \(A\) is the amplitude of the sinusoidal signal, \(\omega\) is the frequency and \(\varphi\) is the initial phase.  
\[u(t)=A_{0}+A\sin(\omega t+\varphi) \tag{11}\]  
The differential equation of the improved ANF is shown in Equation (12) [20,21].  
\[\left\{\begin{array}{l}\ddot{x}+\theta^{2}x=2\xi\theta e(t)\\ \dot{\theta}=-\gamma x\theta e(t)\\ e(t)+\dot{x}+\beta\int e(t)=u(t)\\ \gamma=\frac{\lambda}{\left(1+N\frac{A^{2}}{4\xi^{2}}\right)(1+\mu \theta^{2})}\end{array}\right. \tag{12}\]  
where \(\theta\) is the estimated frequency of \(u(t)\), which is equal to the actual frequency \(\omega\). \(\dot{x}\) is the instantaneous value of \(u(t)\). \(\xi\) and \(\gamma\) are ANF parameters, which determine the steady  
Figure 2: Schematic diagram of correction method.  
state accuracy and convergence rate of ANF, respectively. \(N\), \(\mu\) and \(\lambda\) are positive real numbers that can be adjusted according to the signal frequency.\(\beta\)\(\int e(t)\) is the calculated DC component.  
Equation (13) is the solution to the above equations.  
\[\begin{bmatrix}\theta\\ \dot{x}\\ x\\ \beta\int e(t)\end{bmatrix}=\begin{bmatrix}\omega\\ A\sin(\omega t+\varphi)\\ -\dfrac{A}{\omega}\cos(\omega t+\varphi)\\ A_{0}\end{bmatrix} \tag{13}\]  
From Equation (13), it can be known that \(-\theta x\) is the orthogonal component of the input signal. According to the input signal and the orthogonal components of the input signal, the amplitude and phase information of the input signal can be obtained. The calculation formula is shown in Equations (14) and (15).  
\[A=\sqrt{\left(\dot{x}\right)^{2}+\left(-\theta x\right)^{2}} \tag{14}\]  
\[\varphi=\arctan\left(\dfrac{\dot{x}}{-\theta x}\right) \tag{15}\]  
The schematic diagram of calculating amplitude and phase based on the improved ANF is shown in Figure 3.  
Figure 4 shows the substructure of the ANF. Figure 5 shows the amplitude and phase calculation substructure.  
Figure 4: ANF substructure.  
Figure 5: Amplitude and phase calculation substructure.  
Figure 3: Schematic diagram of improved ANF.  
Set the ANF parameters according to Table 2 to track the displacement signal.  
The tracking effect of the improved ANF algorithm on the collected signal is shown in Figure 6. It can be seen from the figure that the algorithm can accurately track the displacement signal of the same frequency as the rotor speed.
## 3 Reducing Transmission Overhead without Compromising Throughput
### Overview of LARep
The following assumptions are made in the design of LARep: (i) each node is a smart mobile device and is equipped with a Global Positioning System (GPS); (ii) nodes are collaborative and willing to participate in routing; and (iii) source nodes have the necessary information for destinations, which are node ID and location-based information in this case. Figure 11: Functional block diagram of Locality Aware Replication (LARep).
## 4 IoMT-Related Technologies
### RFID Technology  
The RFID technology allows, via radio frequencies, the automatic remote identification of objects equipped with RFID tags. An RFID system is mainly composed of two entities, which communicate between them, the reader (also called interrogator) and the label (also called \"tag\"). In its passive version, the reader will interrogate the tag via radio waves and the tag will then use the electromagnetic energy carried by the received signal to power itself and, at the end of the processing, to send its data in response to the reader [26, 33, 34].  
RFID remains a promising technology for the implementation of smart health systems. Moreover, in addition to being a founding technology of the IoMT, it is an effective way to uniquely identify and manage objects. The use of RFID technology in the healthcare sector allows healthcare providers to facilitate decision-making and the accomplishment of tasks that are usually difficult in a complex clinical environment.
## 3 Results
### Application to Sentinel-5 Precursor and GEMS Validation
As discussed in Section 3.3, NO\({}_{2}\) and HCHO data from the GMAP21 and SIJAQ22 campaigns were processed using the FRM4 DOAS centralised facility. These datasets have been used for the validation of GEMS together with data from stationary instruments operated in Xianghe, Mohali, Yokosuka, Chiba and Kasuga, the latter stations being processed using their own non-harmonised retrievals [61; 62; 63]. This allowed for expansion of the validation of GEMS HCHO data, which until then was relying on a limited number of ground-based data [64]. More detailed comparisons during the GMAP 2021 and SIJAQ 2022 campaigns can be found in [54] and in [55] for HCHO and NO\({}_{2}\), respectively, using both (FRM4 DOAS) MAX-DOAS and Pandora instruments and focusing on GEMS and TROPOMI satellite data.
## 1 Introduction  
\(\beta\)-blockers have been used as drugs for more than 50 years in the therapy of several diseases of the cardiovascular system [1] as well as in other disorders connected with an increase in sympathetic tone, such as glaucoma [2, 3], anxiety [4], thyrotoxicosis [5], osteoporosis [6], and migraine prophylaxis [7]. The study of this drug group is substantiated by high incidence rate of cardiovascular diseases [8], such as ischemic heart disease, hypertension [9, 10, 11, 12], heart arrhythmia, hypertrophic cardiomyopathy [13], and heart failure [8, 14], all of which have been brought into connection with \(\beta\)-adrenergic receptors. These disorders are among the main mortality causes and at present affect increasingly younger fractions of population.  
The particular \(\beta\)-blockers differ in the extent of preferential binding to \(\beta_{1}\)-adrenergic receptors, that is, in their cardiorespiratory, the extent of antagonist activity toward \(\beta\)-receptors, pharmacokinetic properties, and the presence or absence of intrinsic sympathomimetic activity (ISA). These properties further determine the differences in side effects and potential contraindications. \(\beta\)-blockers may be classified according to their pharmacodynamics, pharmacokinetics or duration of action [15]. They are usually categorized into following groups:  
1. Cardioselective \(\beta\)-adenolytics without ISA.  
They affect mainly \(\beta_{1}\)-receptors, while \(\beta_{2}\)-receptors are blocked only at higher doses. The examples include atenol, betaxolol, bisoprolol, esmolol, metoprolol, and nebivolol.
2. Cardioselective \(\beta\)-adenolytics with ISA.  
Because of their agonist activity they are sometimes called \(\beta\)-adenolytics with vasodiliant effect. Typical members of this group are acebutolol and celiprol
## 5 Numerical Examples
### Parameter Tuning
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Distance** & **Depot** & & & & & & & & & & & **Charging** \\  & \(d\) & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & \(c\) \\ \(d\) & 0 & 100 & 150 & 110 & 100 & 120 & 110 & 110 & 120 & 100 & 110 & 150 & 100 & 0 \\ \(1\) & 100 & 0 & 120 & 80 & 110 & 100 & 90 & 90 & 100 & 110 & 80 & 120 & 0 & 100 \\ \(2\) & 150 & 120 & 0 & 80 The optimal solution obtained by CPLEX is: two AMRs are needed to run three routes, where the first AMR runs two routes \(d\to 1\to 3\to 6\to 7\to d\), \(d\to 9\to 11\to 10\to d\) ; the second AMR runs the route \(d\to\)4\(\to\)2\(\to\)5\(\to\)8\(\to\)12\(\to d\). The total cost is \(f(x)=\xi_{1}\cdot m+\xi_{2}\cdot\sum d_{ij}=30\times 2+0.01\times 1190=71.9\). For the VNS algorithm, let the maximum number of iterations be \(N=800,\ 1000,\ 2000\), \(4000,\ 5000\). We run ten times for any fixed \(N\) and get the total number of AMRs participating in service \(m\), the total travel distance \(\sum d_{ij}\), and the total cost \(f(x)\). The optimal solution of the VNS algorithm for any fixed \(N\) is the one with the least cost among the ten experiments, and the results are shown in Table 6. As \(N\) increases, \(f(x)\) approaches the optimal value \(71.9\), which is the same as the result of CPLEX. It can be found from Table 6 that when the number of iterations is \(N=800\), the total travel distance \(\sum d_{ij}\) is the shortest, but the number of AMRs participating in service is more than the others. The cost \(f(x)\) with three AMRs participating in service is much more than the cost with two AMRs participating in the service, even though the travel distance is short. It is a better choice to adopt fewer AMRs to provide service. The optimal solution is described in detail with a route diagram, as shown in Figure 8, where 1 represents request \(i\), and the three elements in vector \((l_{i}\;level,\ \gamma_{i}\;\%,\ u_{i}\;kg)\) represent the floor, the remaining electricity, and the remaining load at the request point \(i\), respectively, \(i=1,\cdots,12\).
# Recent Progress on Aberration Compensation and Coherent Noise Suppression in Digital Holography
###### Abstract  
Digital holographic microscopy (DHM) is a topographic measurement technique that permits full-field, nondestructive, dynamic, quantitative amplitude, and phase-contrast imaging. The technique may realize the lateral resolution with submicron scale and the longitudinal resolution with subnanometer scale, respectively. Improving imaging quality has always been the research focus in DHM since it has a direct effect on the precise topographic measurement. In this paper, the recent progress on phase aberration compensation and coherent noise suppression is reviewed. Included in this review are the hologram spectrum's centering judgment methods of side band in tilt phase error compensation, the physical and numerical compensation methods in phase aberration compensation, and the single-shot digital process methods in coherent noise suppression. The summaries and analyses for these approaches can contribute to improving the imaging quality and reducing the measurement error of DHM, which will further promote the wider applications of DHM in the topographic measurement fields, such as biology and micro-electro mechanical systems.  
digital holographic microscopy; imaging quality improvement; tilt phase error compensation; phase aberration compensation; coherent noise suppression +
Footnote †: journal: Applied Physics Letters
## 3 Review of WBASN MAC Protocols for IEEE 802.15.4 and IEEE 802.15.6  
The interest in WBASNs for remote patient monitoring has increased considerably. It is evidenced that the medium access method used in WBASNs plays a vital role in fulfilling the specific set of QoS requirements for biomedical devices. These QoS requirements are a specified set of time-bound data transmission, data rates, reliability and energy consumption, etc. In the last few years, many MAC protocols for WBASNs have been proposed for medical applications. The WBASN MAC protocols are classified into three broader categories based on channel access mechanisms, i.e., contention, scheduled and hybrid access mechanisms. MAC protocols play a critical part in providing QoS for WBASNs by extending network lifetimes, avoiding packet collisions, reducing overhearing and idle listening, etc. Generally, WBASN MAC protocol characteristics include energy efficiency, scalability, low latency, fairness in terms of channel access, throughput and jitter, etc. Based on channel access mechanisms, the MAC protocols are categorised into three types, i.e., schedule, contention and hybrid-based access mechanisms. For WBASNs, mostly hybrid-based mechanisms are used, due to their flexibility, to adjust light and heavy data traffic. The hybrid MAC protocols combine the benefits of both access mechanisms, i.e., contention-based MAC and schedule-based MAC. The IEEE 802.15.4 and IEEE 802.15.6 MAC protocols have evolved from the idea of an adaptive MAC protocol that combines slotted ALOHA and TDMA, presented in the 1970s [68; 69], to attain maximum throughput. Therefore, several optimisation mechanisms for the IEEE 802.15.4/IEEE 802.15.6 MAC protocols have been proposed. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Standard** & **Provided Data Rate** & **Power Requirement** & **Battery Lifetime** \\ \hline WiFi & 100 Mbps & 100–1000 mW & Hours–days \\ Bluetooth & 1–10 Mbps & 4–100 mW & Days–weeks \\ Wibree & 600 Kbps maximum & 2–10 mW & Weeks–months \\ ZigBee & 250 Kbps & 3–10 mW & Weeks–months \\
802.15.4 & 250 Kbps maximum & 3–10 mW & Weeks–months \\
802.15.6 & 1 Kbps–10 Mbps & 0.1–2 mW & Months–years \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of WBASN standards with other wireless standards [1].
## 4 Security Threat Landscape in 5G Networks
### Attack Methods and Techniques  
As 5G networks become increasingly sophisticated, so do the methods and techniques used by potential attackers to exploit vulnerabilities. A few of the anticipated attack methods and techniques are outlined in this section. The DDoS attacks are anticipated to be a significant threat to 5G networks. As 5G networks offer significantly higher bandwidth, they could potentially be leveraged to launch larger-scale DDoS attacks than those seen on previous generations of mobile networks [89; 93]. Another anticipated method is the MitM attack, where an attacker intercepts communication between two parties to steal data or inject malicious content. The increased reliance on edge computing and IoT devices, which often have weaker security measures, makes 5G networks potentially more vulnerable to MitM attacks [96]. The APTs are another anticipated attack method in 5G networks. These sophisticated attacks are often state-sponsored and involve a prolonged and targeted effort to compromise a network. APTs often employ a mix of attack techniques, including social engineering, zero-day exploits, and rootkits to gain access and maintain a foothold in the target network [97]. Finally, the exploitation of software vulnerabilities is an anticipated attack method in 5G networks. The shift towards SDN and NFV in 5G introduces a new attack surface, as attackers may seek to exploit vulnerabilities in the software layers [89; 90; 91]. Understanding these attack methods and techniques is crucial for developing effective countermeasures and securing 5G networks.
# Smart Irrigation Systems from Cyber-Physical Perspective: State of Art and Future Directions
## 4 Challenges and Future Directions
* _Security_: It is an essential issue in irrigation systems, because any damage to the irrigation system will influence crops' growth rate or cause water contamination. Blockchain technology has been widely used in the farming industry. However, if we apply blockchain to our irrigation system, its lack of scalability and high energy consumption will burden the irrigation system. In addition, the massive volume ofdata collected by the sensors must be passed to the cloud server for further analysis. Physical device protection also needs to be considered, such as adding lockers to protect sensors. We can design mechanisms on the server to collect data only sent from trusted sensors. The continuous adaptation of security methodologies is essential to meet the evolving needs of these systems. These challenges underline the multifaceted nature of implementing smart irrigation systems. Solutions will likely involve interdisciplinary collaborations, technological advancements, and a deep understanding of local agricultural contexts. The path forward lies in continuous research and innovation to overcome these challenges and create sustainable, efficient, and reliable irrigation systems.
###### Abstract  
An adaptive digital phase-locked loop (DPLL) continually adjusts the noise bandwidth of the loop filter in global navigation satellite system (GNSS) receivers to track signals by measuring the signal-to-noise ratio and/or dynamic stress. Such DPLLs have a relatively large amount of computational complexity compared with the conventional DPLL. A table-based adaptive DPLL is proposed that adjusts the noise bandwidth value by extracting it from the pre-generated table without additional calculations. The values of the noise bandwidth table are computed in an optimal manner in consideration of the thermal noise, oscillator phase noise, and dynamic stress error. The calculation method of the proper integration time to maintain the stability of the loop filter is presented. Additionally, the simulation is configured using the trajectory analysis results from the Moon exploration mission and shows that the proposed algorithm operates stably in harsh environments, while a conventional fixed bandwidth loop cannot. The proposed algorithm has a similar phase jitter performance to the existing adaptive DPLL algorithms and has an execution time that is approximately 2.4-5.4 times faster. It is verified that the proposed algorithm is computationally efficient while maintaining jitter performance.  
GNSS receiver; adaptive digital phase-locked loop; look-up table; Moon exploration mission +
Footnote †: journal: Physics Letters A  
1
Footnote 1: institutetext: Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea  
22, 10001. [[https://doi.org/10.3390/s222410001](https://doi.org/10.3390/s222410001)]([https://doi.org/10.3390/s222410001](https://doi.org/10.3390/s222410001))
# Helicopter Takeoff and Landing Point Location in Cities for Emergency Services
## 3 Data Processing Using ArcGIS and Methods
### Data Processing
#### 3.2.2 Building of Terrain Obstacle Buffer Zone  
Considering the existence of road networks, rivers and other factors that may affect the safe operation of aircraft, this paper selects the main traffic lines in Nanjing and the banks of the Yangtze River to establish a buffer zone with a width of 50 m to prevent helicopter take-off and landing points from falling into the buffer zone. In this part, the buffer is set linearly. The road network and river information are downloaded from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences and can be directly applied to the software, as shown in Figure 3.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Time** & **Rainfall/mm** & **Visibility/m** & **Cloudage/\%** &
\begin{tabular}{c} **Wind Speed/** \\ **m/s** \\ \end{tabular} & **Ceiling/m** \\ \hline
0200 & 4.0 & 2100 & 100 & 9 & 600–1000 \\
0500 & 3.0 & 1900 & 100 & 9 & 1000–1500 \\
0800 & 3.0 & 1700 & 100 & 8 & 600–1000 \\
1100 & 1.0 & 1500 & 100 & 8 & 600–1000 \\
1400 & 0.2 & 1300 & 100 & 8 & 1000–1500 \\
1700 & 0.1 & 1100 & 100 & 8 & 600–1000 \\
2000 & 0 & 1700 & 100 & 6 & 1000–1500 \\
2300 & 0 & 3400 & 100 & 6 & 9999 \\ \hline \hline \end{tabular}
\end{table}
Table 3: 24-h observation data of Nanjing Weather Station.  
Figure 2: Slope grading layer and terrain undulation grading layer.