esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments
### Natural Frequency Experiment  
The natural frequency of the optical platform is measured to validate the effectiveness of the proposed EANSG method in the frequency domain. Two comparative experiments were performed using a rubber hammer to produce an impact vibration excitation on the top of the optical platform. In the first experiment, the natural frequency of the optical platform supported only by pneumatic springs is tested. Then, natural frequency of the optical platform supported by four LFPEIs was measured for comparison in the second experiment. Theoretically, the natural frequency of the optical platform can be derived from its displacement impact response, or velocity impact response, or acceleration impact response [32]. The velocity impact response at the center of the optical platform was measured  
Figure 16: Experimental setup for the EANSG method validation: (**a**) sketch of the experimental setup and (**b**) a photo of the experimental setup.  
by a low-frequency velocity-type vibration sensor and sampled by a multi-channel signal acquisition system. The experimental results are shown in Figure 17.  
Figure 18 shows the spectrum analysis of the measured velocity impact responses. It can be seen that the natural frequency of the optical platform supported by four pneumatic springs was 2.00 Hz, while that of the optical platform supported by four developed LFPEIs was reduced to 1.37 Hz, decreased by 31.50%, which proved that the proposed EANSG method is effective in counteracting the positive stiffness of pneumatic springs and enhancing the low frequency vibration isolation performance of the optical platform.
## 4 Security Attacks
### Network Layer
#### 4.2.4 BGP Hijacking Attack  
BGP hijacking attacks [18; 30; 42] exploit vulnerabilities in the border gateway protocol (BGP) to manipulate network-level traffic. In such an attack, an adversary alters the routing information so that network traffic is rerouted through malicious channels. This can delay the propagation of messages, adversely affecting mining operations, or even enable the theft of cryptocurrency. To mitigate BGP hijacking, network operators can implement BGP monitoring, route origin validation, and encrypted communication channels to safeguour routing information.
## 2 Fundamental Theories
Secondly, the effective mode index of the bending fiber, which is denoted as \(n_{\text{eff1-bend}}\), is obtained by numerically solving Maxwell equations under \(n_{eq}(x,y)\). Finally, the bending loss of the fiber can be computed using Equation (4), provided that the \(n_{\text{eff1-bend}}\) instead of \(n_{\text{eff1}}\) is used in the calculation. The performances of DWDM systems are deteriorated due to various nonlinear effects in optical fibers. From the nonlinear fiber optical theory, it is known that fibers with larger effective mode areas \(A_{\text{eff}}\) are less susceptible to nonlinear effects. Thus, the \(A_{\text{eff}}\) also needs to be considered during fiber design. According to its definition, \(A_{\text{eff}}\) can be expressed as  
\[A_{\text{eff}}=\frac{\left(\iint_{\text{s}}|\mathbf{E}_{t}|^{2}dxdy\right)^{2}}{ \iint_{\text{s}}|\mathbf{E}_{t}|^{4}dxdy}, \tag{6}\]  
where \(\mathbf{E}_{t}\) represents transverse component of the electric field. In addition to the value of \(A_{\text{eff}}\), the two-dimensional distribution of optical intensity \(I\) of the mode field also plays an important role in nonlinear effect generation. Here, \(I\) is also known as the optical energy flux. It is the average of the instantaneous Poynting vector \(\mathbf{S}\) over time and has a unit of \(\text{W}/\text{m}^{2}\). To better evaluate our proposed TA-MCF's susceptibility to nonlinear effects, the detailed distribution of \(I\) was studied by a parameter called optical intensity ratio (\(IR\)). It is defined as  
\[IR=\frac{I_{0}}{I}, \tag{7}\]  
where \(I_{0}\) and \(I\) denote the optical intensity at the center of the MCF and in the six individual cores, respectively. Based on the definition of \(IR\), we can conclude that the \(IR\) value approaching unity stands for a flatter mode field-intensity distribution for the six-core MCF. For a fiber with a flatter intensity profile, the optical power is distributed more uniformly in its cross-section. This further means a lower peak intensity under the same \(A_{\text{eff}}\) and input power, which is favorable for the prevention of nonlinear effects.
## 5 Experimental Results
### Performance Evaluation for MIMO Wi-Fi Backscatter System
The other existing power-level algorithm [12] needed a higher SNR condition by 15 dB for having the same throughput as the proposed backscatter method. The BER performance in the proposed backscatter method when increasing the number of antennas of the reader from one to eight are shown in Figure 6. Without regarding both the method in the proposed system and the distance between the reader and the tag sensor, the BER performance increased in proportion to the number of antennas employed in the reader. As given in Equation (12), the final Euclidean distance value was calculated from the distance obtained in each antenna and can be obtained from more CSI data with increasing the number of antennas. By increasing the number of antennas in the reader, the reader can gather more information about the channel affected by the tag sensor and can see the difference easily between the tag's backscatter (reflecting RF waves) and  
Figure 4: BER (bit error rate) performance for the existing and the proposed backscatter method. (**a**) Proposed MIMO (multiple-input multiple-output) encoding/decoding algorithm for increasing the data rate (the first method); (**b**) proposed MIMO encoding/decoding algorithm for improving the reliability (the second method). silent (observing RF waves) operations. Since the backscatter system loads the information on the variation of a Wi-Fi communication channel between the helper (AP) and the reader (device), it is very important on the performance to collect the channel information through multiple antennas.
## 3 Materials and Methods  
In this study, we have incorporated the novel approach of forward error correction while crypto-encoding videos before transmission using the H.264/AVC encoder to recover the errors encountered during transmission, resulting in improved objective video quality. Additionally, the proposed work enhances transmission security by selectively encrypting videos using specific syntax elements to protect against unauthorized access. The details are described in subsequent subsections.
# Evaluating the Energy-Saving Potential of Solar Dedicated Ventilation Systems Based on ADRC
## 6 Evaluation of Actual System  
The proposed solar dedicated ventilation system has been used in actual operation as the cooling system of a laboratory (the previous study was conducted for a laboratory), and the evaluation will be shown in this part. A lot of calculations and analyses for the operation of the proposed system were conducted, and the energy-saving potential, initial investment, and payback period are compared with the former systems in this paper.  
The cooling area of this laboratory is nearly 300 m\({}^{2}\). One year's operation of the laboratory has been recorded and the data have been collected. For 8760 h of one year's operation, about 2752 h of cooling system use is needed under outdoor and indoor conditions, which is proposed in the experimental part of this paper. There are almost no extreme cases in the 2752 cooling hours.  
Comparison between the proposed solar dedicated ventilation system and the conventional system system is 58.43 W/m\({}^{2}\). This indicates the energy-saving potential of the proposed system relative to the conventional system based on the operation data and calculations. Standard coal consumption and CO\({}_{2}\) emissions could be reduced by 64.31 kg/m\({}^{2}\) and 160.32 kg/m\({}^{2}\), respectively, according to the energy-saving potential compared with the traditional system.  
Comparison between the proposed solar dedicated ventilation system and heat pipe heat exchanger combined with dedicated ventilation system  
The energy-saving potential of the heat pipe heat exchanger combined with a dedicated ventilation system compared to the conventional system was proposed in previous research [14]. Compared with the heat pipe heat exchanger combined with a dedicated ventilation system, the energy-saving potential of the proposed system is 55.8 W/m\({}^{2}\). The corresponding reduction of standard coal consumption and CO\({}_{2}\) emissions is 61.42 kg/m\({}^{2}\) and 153.11 kg/m\({}^{2}\), respectively.  
Three different systems (conventional system, heat pipe heat exchanger combined with dedicated ventilation system, and the proposed solar dedicated ventilation system) were compared from different aspects under the same conditions in this laboratory. The results are shown in Table 4.  
It can be seen in Table 4 that the proposed solar dedicated ventilation system will provide benefit by the sixth year, leaving 19 years of net income according to a 25-year system life.
## 3 Topological Path Planning (TPP)
### Proposed Method  
Consider the Euclidean space represented by an \(N_{1}\times N_{2}\) grid \(G\) of connected points. The manipulator workspace \(W\in G\) contains only the points reachable by the robot arm and a known map of obstacles represented by a grid \(M\in G\) containing only the points inside the obstacles. We define the free space \(F=\{p\mid p\
eq q,p\in W,q\in M\}\) as the set of points belonging to the workspace \(W\) and not belonging to the obstacles map \(M\). The shapes numbered 1, 2, and 3 in Figure 3a represent the obstacles. The free space, illustrated in Figure 3b, represents our topological-constrained space of connected points. \(F\) can be seen as a finite set of paths between \(q_{start}\) and \(q_{goal}\).  
Using a controlled thinning, where relaxed influence zone criteria allow non-maximum circles to be present, the TPP algorithm shrinks the free space \(F\) until the resulting area is a roadmap \(R\in F\) surrounding the obstacles, including larger regions, as shown in Figure 3c. In this paper, the thinning procedure is modulated by distance and a number of obstacles nearby. As a result, our proposal preserves more points between obstacles, as shown in Figure 4. This behavior allows the next step to find shorter paths between \(q_{start}\) and \(q_{goal}\).  
The resulting roadmap \(R=h1\cup h2\cup\dots\) is composed by sets of collision-free homotopic paths \(h\), shown in Figure 3c. Finally, a shortest path algor  
Figure 4: Disk size is modulated by zones of influence driven by distance and obstacle population. Both maximum (blue) and smaller (magenta) disks are allowed in specific regions.  
Figure 3: Topological path planning model. (**a**) The environment shows the obstacles (1, 2, and 3), start (green), goal (red), and the optimum path. Blue marks represent critical positions. (**b**) The free space \(F\). (**c**) The subsets of homotopic roadmaps \(R=h1\cup h2\) are achieved by controlled thinning. (**d**) The topological path \(P\) is depicted in purple.  
points \(P\subset R\) that represent the best possible topological path inside \(R\). The final path \(P\) is smoother and minimizes the unnecessary detours when compared to TPP* as illustrated in Figure 3d. Notice that, by using different functions or transformations to compute \(R\), one can find different paths that meet the same objectives. The topological path planning (TPP) method, shown in Figure 3, is presented in Algorithm 1.  
```
0: start point \(q_{start}\), goal point \(q_{goal}\), obstacles map \(M\), manipulator workspace \(W\).
1: Initialize a grid \(G\) of \(N_{1}\times N_{2}\) points containing the workspace of the robot and obstacles.
2: Compute the free space \(F\).
3: Compute the topological-constrained set of paths \(R\) using a controlled thinning on \(F\), modulated by the influence of obstacles.
4: Connect the \(q_{start}\) and \(q_{goal}\) points to the TPP.
5: Find the shortest path \(P\) between \(q_{start}\) and \(q_{goal}\) on \(R\).
6: a topological-constrained path \(P\) of between \(q_{start}\), goal point \(q_{goal}\).
```  
**Algorithm 1** Topological Path Planning (TPP)
## 3 Methodology
Since in such cases, this report must be compared to all the existing clusters prior to being labelled as a breaking event, as more news reports are clustered and new clusters are created, the clustering procedure will become more computationally expensive. Therefore, a system where the number of clusters is continuously growing is not scalable. To resolve this issue, the concept of \"freezing\" old clusters. This means that clusters that have not had new members for some time are \"frozen\", and incoming documents are not compared to them at all. They are assumed to be describing events whose \"influence\" has now passed and are not any more of \"interest\" within the world of news reporting. Apart from aiding the system efficiency, \"cluster freezing\" is also preventing new news reports to be clustered with obsolete events. The identification of \"frozen\" clusters is performed by the system, which traverses the list of active (unfrozen) clusters periodically. Reverting back to the case of our operational setup, the typical number of \"active\" clusters at any one time is around 135. Considering that in our current system setup, a news report is clustered in slightly less than 1 second, if there is no \"freezing\" of old clusters, the clustering of a single news report will start to take round 10 s after 1 month of system operation, and nearly 100 s after 6 months of system operation. Such delays may render the clustering system not feasible especially if it is just a small of part of a larger and considerably more complex operational cycle.
# CvAMoS--Event Abstraction Using Contextual Information
## 5 Evaluation  
To evaluate the approach introduced in this paper, we decided to opt for a two-fold validation. The first one is based on synthetic data and well-defined configurations, while the second one is based on the application on a real data set. The objective of the evaluation is to be able to reply to the research questions introduced in Section 1. Using synthetic data for the first evaluation allows us to verify the functioning of the approach, as well as manipulate the different parameters, such as the attributes, the motif length, the distancesand the cost. On the other hand, using a real dataset for the second evaluation allows us to assess the performance of the approach in a more realistic scenario, and to measure its ability to recognize motifs in a real dataset as well as to verify the computation time required by the algorithm. All the evaluations are made by comparing our solution against another approach in the literature, the event abstraction using LPMs [15] (referred to as LPM).
# A Novel Non-Coherent \(Q\)-Ary TH-PPM Transceiver
## 5 Discussion  
We would like to use the new TH-PPM as a technical for secure communication due to the pseudo-random characteristics of its time-hopping sequence. TH-PPM is well known as a technology for UWB which leads to a variety of literature, a brief discussion compared to the BER performance of known work in the field of UWB is proposed in this section. To the best of our knowledge, there are several ways to improve the BER performance of the UWB.  
The first way is to overcome the jitter by designing the waveform of pulse [29; 30; 31], which was a focus of attention a decade ago. The second way is to improve the accuracy of timing synchronization [32; 33; 34], which has been a concern in recent years. The third way is about weighted receivers [26; 27; 28], which can achieve good performance by overcoming the change in the shape of the pulse.  
In our work, we proposed a new method different from the known work. We introduce a new structure of the TH-PPM signal model without changing the waveform of the pulse. So, it can be combined with the method of designing a good waveform of pulse to achieve better performance. Furthermore, the receiver in our work, which consists of matched filters, can combine with the method of weighted receivers by changing the filter coefficients with weighted. Then the new TH-PPM can achieve better performance over the change in the shape of the pulse. So, our work is not a replacement for other methods, but a new way which can combine with the other methods to improve the BER performance of TH-PPM.
## 8 Discussion
### Limitations  
The proposed model was designed for a densely deployed network, assuming that the area includes a sufficient amount of sensor nodes. In case there is an insignificant number of sensor nodes, the inputs of the fuzzy system might be affected (especially the number of neighbours), thus, affects the optimization of the path planning. On the other hand, most of the model operations exist in the MA's side. Assuming that the MA is not energy-constrained and is able to complete the assigned movement distance, we did not consider the computation load or energy consumption in this model. In a special scenario where the MA has a trivial source of energy, it might be unable to even complete its limited distance. Although our proposed model shows a significant improvement of localization ratio in comparison to other models, it is very difficult to guarantee that all UNs will be able to receive the localization information. Two reasons behind that namely the limited movement distance of the MA, and the nature of the dynamic models of forming the mobility movement based on the information received from the deployement area.
## 6 Experimental Results
### Response Time Analysis  
This experiment considers 10 sets of callbacks. A set contains 100 callbacks randomly generated with a CPU utilization factor of 60%.  
For each deadline interval \([a,b]\), we run all algorithms on 10 sets of callbacks and determine the maximum average response time. Figure 8 shows the average response time versus the deadline. The proposed algorithm finds a mapping of callbacks to executors that gives better response times than those obtained by other algorithms. This is due to the tuning of the callback sequencing and activation. However, the LL algorithm underperforms compared with the RMS and GBFS algorithms by causing the highest response times. Furthermore, we note that when the deadlines tighten after the interval [0.2, 1], both the LL and the proposed algorithm continue to be schedulable with a gradual increase in response time up to the interval [0, 0.5].
# Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review
## 2 The Definition of Digital Twins
### DTs in Agriculture
AI technologies facilitate the recognition of cattle states, empowering animal caregivers and ethologists to understand animal behavior and optimize their well-being and productivity. DTs may support decision-making and farm management optimization by simulating different scenarios regarding environmental conditions or genetic factors on animal performance and production outcomes while improving production efficiency and minimizing environmental impacts. Furthermore, connections with other digital platforms, such as farm management systems, supply chain networks, and veterinary databases, allowing for seamless data sharing and analysis is feasible with DT, thus enhancing traceability, quality assurance, and decision-making throughout the value chain. In summary, digital twins have the potential to revolutionize animal farming by providing real-time monitoring, predictive analytics, and decision support. They can optimize animal health, welfare, and production efficiency while promoting sustainable farming practices. Continued research and development in this area will be crucial to fully harness the benefits of DTs in animal farming and address the associated challenges. An Aquaculture 4.0 architecture of a digital twin-based intelligent fish farm management system for precision aquaculture is discussed in [34], addressing the design considerations, data integration, analytics, and control mechanisms to optimize fish farm operations. The proposed implementation utilizes a cloud-based DT technology employing ML realizations, computer vision, and other sensor devices, and AI-based IoT (AIoT) to monitor and control automated aquaculture machinery. By optimizing farm production in various environments throughout the different stages of fish farming, the system aims to maximize efficiency and productivity. Water quality sensors utilized in fishponds to monitor and analyze the condition of the water and in offshore sea cages, and RGB or sonar camera devices may collect environmental data and data related to fish populations to establish data-driven prediction models. On the other hand, land-based monitoring systems send appropriate commands to activate surveillance sensors, thus enabling fish-feeding behavior monitoring, disease spread, and fish population growth. Furthermore, DTs address optimization solutions regarding water flow and treatment processes related to water quality reduction following floods and stormwater within transboundary water security projects due to urban expansion [17]. DT models are employed to monitor the quality of urban water by integrating physical entities and utilizing sensors in urban drainage systems. The models consider natural processes related to soil, vegetation, clogging, and biological activity in water treatment. This approach enables comprehensive monitoring and analysis of urban water systems for effective management and maintenance.