esa-sceva/satcom-chunk-collection huggingface dataset:
# Intelligent Scheduling with Reinforcement Learning
## 2 Literature Review
### Scheduling Problems
Multi-operation problems differ from the previous ones in that they have multiple parallel machines capable of performing the same operations. Parallel machines may be organized according to different approaches: they may be equal, where all the machines perform the same tasks with the same speed; similar, where the machines perform the same tasks but at a different speed; or different, where the tasks to be performed and the processing speed are different on each machine. Multi-operation problems are, due to their nature, more complex and difficult to solve. Within this type of problem there are three different categories according to the nature of the tasks to be processed [3; 12]:  
* Flow shop--All tasks are the same, making all operations have a uniform order of passage through the machines. The tasks are always executed in a specific order, requiring only the decision of the start of each operation's production. * Job Shop--Each task has its own specific operations, thus allowing the existence of different tasks. The operations of each task have a predefined order that must be respected. The order of the operations can be different from task to task. * Open Shop--There are no ordering constraints, i.e., each operation of a task can be executed on any machine at any time. In addition to these three categories, scheduling problems are also distinguished by the way tasks are received by the system [13]. If all the tasks are available from the start, then all the operations that will need to be scheduled are known, which is labeled as a static problem (as it never changes). On the other hand, if new tasks may arise when a plan is already being executed and/or the ongoing tasks may be canceled, it is considered a dynamic environment problem. The work developed in the scope of this paper supports one of the most used categories of problems [14], _Job Shop_, both in static and dynamic cases.
## 3 Proposal Architecture
### Architecture  
The mobile monitoring node receives, processes and forwards the data pertaining to tachycardia, bradycardia and falls throughout the networks. The WSN Infrastructure consists of a group of nodes placed throughout the home. These nodes are capable of establishing a hierarchical network, receiving information from the mobile nodes and routing the information to a computer with reduced computational capabilities and an 802.15.4 radio. The SINK is a computational device that picks up and stores the information it receives from the WSN infrastructure, permitting either local or remote access to the data. Finally, the Remote Monitoring and Alert Interface is an application to serve mobile devices and a standard website, both of which can receive notifications of important events and consult the patient's history and other personal information.
## 3 Results
### Wettability  
The untreated bare epoxy (C0) surface was found to be mildly hydrophilic (CA = 71) (Figure 6). In the same figure, it is evident that the incorporation of the ZnO filler caused CA to increase in higher ZnO content, namely C0.5 and especially C2, thus changing corresponding sample surfaces slightly hydrophobic, as reported in the literature [40,41]. As ZnO content increased, the surface roughness of the samples also increased. Given that wettability is largely affected by surface roughness and surface free energy [42], and that air bubbles are trapped between surface ups and downs of the material, contact with water droplets is hindered. As a result, surface energy is reduced, which leads to increasing hydrophobicity, a phenomenon most prominent for C2 samples. However, although the 2880 h AWE treatment did not actually affect the CA of C0/C0.1/C0.5 samples, it increased the CA of C2 samples; this made their surfaces even more hydrophobic (CA = 88), as seen in Figure 6, due to ZnO protective properties, namely by limiting polymer oxidation reactions and chain scissions that cause the formation of polar groups [39].
## 3 Transmit MISO Beamforming  
A MISO system with \(M\) LEDs (transmitters) and one photodetector (receiver) performing a closed-loop transmit beamforming technique is considered. As previously described, dimming can be used to control the quantity of light to fit specific tasks, moods, or situations. Likewise, dimming can be used for localization tasks by incorporating closed-loop beamforming techniques. The weight vector \(\mathbf{w}\) is a complex vector corresponding to the inverse of the phase of the channel to ensure that the signals add constructively at the receiver, _i.e._, \(w_{i}=\exp\left(-\,j\phi_{i}\right)\) with \(h_{i}\left[k\right]=\left|h_{i}\right|\exp\left(j\phi_{i}\right)\). \(h_{i}\left[k\right]\) for each LED can be written together in the form of vector as \(\mathrm{h}\left[k\right]\). The weight vector is a predetermined codebook, known to both the transmitter and receiver prior to any communication. Furthermore, the codebook is considered to be fixed throughout the communication time. Since the channel is time-varying and unknown a priori, the receiver has to estimate the channel based on training signals. The channel estimation is assumed to be perfect. The channel estimate at the receiver at time \(k\)-\(D\), where \(D\) is the feedback delay, is quantized into one of the codewords in the codebook. In theory the quantization is performed via an exhaustive search over the codewords in the Grassmannian codebook [11] as:  
\[b=\underset{\mathrm{I}\leq i\leq M}{\arg\max}\left|\hat{\mathbf{h}}\left[k-D \right]\mathbf{w}^{H}\right|^{2} \tag{10}\]  
where the index \(b\) is fedback to the transmitter and the transmitter chooses vector \(\mathbf{w}_{{}_{b}}\) for beamforming (an error-free feedback channel is assumed). In an actual implementation, the Grassmannian codebook can be obtained from a lookup table, _i.e._, an exhaustive search is not really required. \(N=2^{\mathit{B}}\) is the number of the beamforming vectors in the codebook with \(B\) bits of feedback Hence, with a feedback delay of \(D\), the beamforming weight vector used at time \(k\) is \(\mathbf{w}\left[k\right]=\mathbf{w}_{{}_{b}}\). A weight vector is matched to the corresponding PWM signals for dimming control. The output SNR of the transmit MISO beamforming system, which corresponds to the output SNR \(\gamma_{{}_{0}}\) in Equation (8) is given by:  
\[\gamma_{{}_{0}}=\gamma_{{}_{i}}\left|\mathbf{h}\mathbf{w}_{{}_{i}}\right|^{2} \tag{11}\]  
where \(\gamma_{{}_{i}}\) denotes the transmit SNR given as \(\gamma_{{}_{i}}=\frac{P_{{}_{\mathrm{T}}}}{\sigma_{{}_{w}}^{2}}\) with the total transmit power \(P_{{}_{\mathrm{T}}{{}_{i}}}\). In terms of positioning, the direction of departure (DoD), _i.e._, \(\theta\), \(\phi_{i}\), and the distance between a transmitter and the receiver \(d_{{}_{i}}\) in Figure 1 are used for calculating the position of the receiver.
# Experimental Study on Dynamic Response Characteristics of RPC and RC Micro Piles in SAJBs
## 3 Experimental Results  
### Dynamic Characteristics  
Figure 6 plots the spectrum analysis results at the top of RPC micro pile under white noise waves, where Figure 6a shows the spectrum analysis results under the first white noise wave (case 1), and Figure 6b shows the fifth white noise (case 5). As seen in Figure 6, it was found that these frequencies corresponding to peak amplitude at the top of the RPC micro pile system are closed to 5 Hz and 16 Hz, respectively, and they are more clear than that of others' frequency. It was observed that the first and second natural frequency of the RPC micro-pile system were 4.74 Hz and 16.31 Hz, respectively. In addition, it was also found from Figure 6 that the natural frequency of the RPC micro pile system increased significantly after several times of repeated white noise. The reason is that the increase of sand compactness under a shaking table test, and the increase of the pile-soil interaction is significant. Meanwhile, the natural frequencies of the RC micro pile under repeated white noises were also obtained by the spectrum analysis, and the first and second natural frequencies of the RC micro-pile system were 3.62 Hz and 15.46 Hz, respectively. It was indicated that the natural frequencies of the RPC pile are larger than that of the RC micro pile.
## 6 ML and the Security of Blockchain
### Consensus Mechanism Enhancement  
ML techniques are also applied to enhance blockchain consensus mechanisms. For example, ML models can analyze mining patterns and participant behavior to predict potential 51% attacks. Reinforcement learning has been used to develop adaptive consensus mechanisms that dynamically adjust based on real-time network conditions. This adaptability is crucial in networks utilizing Proof of Work (PoW) or Proof of Stake (PoS), where miners or validators might be incentivized to act maliciously. By integrating ML, consensus algorithms can mitigate risks such as centralization and enhance overall network resilience.
# Real-Time Flood Monitoring with Computer Vision through Edge Computing-Based Internet of Things
###### Abstract
In this paper, we make the following key contributions:  
* Propose and design a novel RGB-D sensing- based technology for real-time water level monitoring under diverse weather and lighting conditions. * Integrate edge-computing-based techniques and IoT-based system architecture for rapid image processing. * Deploy the proposed architecture as a real-world system in an actual water level monitoring facility at a rural site where flooding is a common threat to the local community. The remaining sections of this paper are organised as follows. Section 2 covers the background and work related to vision-based water level detection and edge computing in IoT applications. Section 3 presents the architecture of the proposed system as well as the details of the system implementation. Section 4 discusses the implementation and experimental setup of the proposed system. Section 5 presents the experimental results and analysis followed by conclusions and future work in Section 6.
## 3 Optimization Design
### Reliability-Based Multi-Objective NSGA-II Optimization
As seen in Figure 9, the Pareto P1 has an outlier of point A, whose displacement amplification is larger than the remaining designs of the last DO-NSGA-II population. It is clear that due to the smaller thickness of \(T_{1}\), its stiffness is decreased, which makes the mechanism easier to deform. In the meantime, the Pareto P2 curve is partially coincident and partly upward with the Pareto P1 curve. It has fewer solutions than the Pareto P1 curve, since some offspring of their last generation were converged and coincident. There is no outlier in the Pareto P2, indicating that the reliability index significantly affects the optimal results. In the set of Pareto P1 optimal solutions, some solutions satisfy the expected value of \(R_{0}>98\%\), but some do not. For the reliability concern, all of the optimal solutions of P2 meet the given \(R_{0}\) value. In a nutshell, it is possible to confirm the praiseworthy compensation of the RBDO compared to without it. The target of the RBDO is to simultaneously maximize the natural frequency \(f_{1}\) and the displacement amplification \(f_{2}\). As seen in the reliability-based Pareto diagram in Figure 9, there are many design points with different levels of reliability. Among these alternatives, the chosen optimal design (point C) with the reliability index \(\beta_{3}=3\), the safety level \(R_{0}=99.87\%\), \(f_{1}=1500\) Hz, and \(f_{2}=3.104\), fulfills the given problem with the required constraints, objective functions, and expected reliability. Table 5 reports these results.
# The Cell Membrane of _Sulfolobus_ spp.--Homeoviscous Adaption and Biotechnological Applications
###### Abstract  
The microbial cell membrane is affected by physicochemical parameters, such as temperature and pH, but also by the specific growth rate of the host organism. Homeoviscous adaption describes the process of maintaining membrane fluidity and permeability throughout these environmental changes. Archaea, and thereby, _Sulfolobus_ spp. exhibit a unique lipid composition of ether lipids, which are altered in regard to the ratio of diether to tetraether lipids, number of cyclopentane rings and type of head groups, as a coping mechanism against environmental changes. The main biotechnological application of the membrane lipids of _Sulfolobus_ spp. are so called archaeosomes. Archaeosomes are liposomes which are fully or partly generated from archaeal lipids and harbor the potential to be used as drug delivery systems for vaccines, proteins, peptides and nucleic acids. This review summarizes the influence of environmental parameters on the cell membrane of _Sulfolobus_ spp. and the biotechnological applications of their membrane lipids.  
archaea; _Sulfolobus_; homeoviscous adaption; membrane; tetraether; diether; lipids; biotechnological application
## 4 Discussion
### Limitations of This Study  
There exist certain limitations in our study. Firstly, the parameters related to plant growth were established based on the existing research literature alongside uncertainty and sensitivity tests. In the future, more refined observational data will be necessary to verify and calibrate this model. Secondly, the contribution of water nutrients from surrounding rivers to the lake was not considered in this study, potentially leading to an underestimation of water nutrient concentrations. Additionally, lake ecological interaction processes were not thoroughly explored; however, they were not the focus of this paper. Our attention was primarily directed towards the construction and application of an ecological modeling of TP lakes by aggregating observations and analyzing interannual variations in key ecological indicators of lakes. Possible factors influencing these indicators were also discussed to explore the effects of climate and hydrology on lake ecosystems on the TP.  
To thoroughly understand the lake water ecological processes on the TP as related to global climate change, obtaining long-term variations in lake ecological parameters, such as WTP, WTN, and WGPP, is crucial [29; 63; 64]. With the availability of satellite remote sensing data, some important parameters for lake water ecology, such as water clarity, can be obtained in areas with abundant observations [65; 66]. However, in regions with minimal human activity, particularly in high-altitude and high-latitude areas, actual observations are still necessary to validate remote sensing inversion datasets. Thus, establishing a long-term observation network for lake ecosystems in these regions is imperative.
## 3 Results and Discussion
### Regeneration Test  
The regeneration of adsorbent is crucial for the adsorption process because it can lower the adsorption cost by recovering its adsorption performance from aqueous solutions. Desorption and regeneration experiments were studied for five cycles (Figure S5 (Supplementary Materials)), implying that the desorption process with methanol and HCl solution was efficient, and the saturated absorption capacity can attain 95-99% of virgin CDM-HCP. The results confirmed that the CDM-HCP could be efficiently recovered and it exhibited a good regeneration property. The adsorption capacity of the CDM-HCP was higher than some commercial polymeric adsorbents, such as XAD-4, PA66, and AB-8 (Table S3 (Supplementary Materials)). It showed that the CDM-HCP is a promising adsorbent in the removal of organic pollutants.
# Current Status and Future Developments of Micromegas Detectors for Physics and Applications
## 8 Micromegas for UV Detection
### Transmissive Photocathode  
The second method of coupling a photocathode to a Micromegas is a direct coating on the transparent window. A sketch of the transmissive detection mode is given in Figure 24b. This method decouples the photocathode from the mesh, and all different Micromegas mesh technologies can be used. The photocathode can be parallel to the mesh and can generate a homogeneous drift field. Primary electrons are generated on the surface of the photocathode directly facing toward the mesh. As the drift length is the same for each photoelectron, the time resolution is better.  
The transmissive photocathode also has some drawbacks compared to the reflective one. Photons have to pass through the whole photocathode layer, thus, making the efficiency dependent on the opacity of the photocathode layer. Compared to the reflective mode, only thin photocathodes with sufficient transparency work well [109]. A second drawback is the lower robustness against ion-backflow [110]. The photocathode is parallel to the mesh and can be irradiated by ions generated in the amplification region. Moreover, the photocathode can be damaged by detector sparks, and a thin but robust photocathode material is needed for operation at higher particle flux.
# Study on Vibration Characteristics of Multi-Beam Structures with Stick and Slip at Joints
## 2 Theoretical Modeling
### Improved Fourier Series Expansion Vibration Displacement  
After separating the time and space variables, vibration displacement \(u_{i}\) can be written as follows:  
\[u_{i}=\Phi_{i}(x_{i})\cdot T_{i}(t). \tag{11}\]  
This includes the basis function \(\Phi_{i}(x_{i})\) and the time term \(T_{i}(t)\). After employing the improved Fourier series to expand the basis function \(\Phi_{i}(x_{i})\), the form is as follows:  
\[\Phi_{i}(x_{i})=\sum_{k=0}^{\infty}a_{k}cosk\pi\frac{x_{i}}{L_{i}}+a_{i1}^{f} \xi_{i1}(x_{i})+a_{i2}^{f}\xi_{2}(x_{i})+a_{i3}^{f}\xi_{i3}(x_{i})+a_{i4}^{f} \xi_{i4}(x_{i}) \tag{12}\]  
where \(\xi_{i1}(x)\), \(\xi_{i2}(x)\), \(\xi_{i3}(x)\), \(\xi_{i4}(x)\) are boundary smooth terms used to eliminate the discontinuity of multi-order derivatives of displacement function at the boundary in the following form:  
\[\left\{\begin{array}{l}\xi_{i1}(x_{i})=\frac{9L_{i}}{4\pi}\sin\Bigl{(}\frac{ \pi x_{i}}{2L_{i}}\Bigr{)}-\frac{L_{i}}{12\pi}\sin\Bigl{(}\frac{3\pi x_{i}}{2L _{i}}\Bigr{)}\\ \xi_{i2}(x_{i})=-\frac{9L_{i}}{4\pi}\cos\Bigl{(}\frac{\pi x_{i}}{2L_{i}}\Bigr{)} -\frac{L_{i}}{12\pi}\cos\Bigl{(}\frac{3\pi x_{i}}{2L_{i}}\Bigr{)}\\ \xi_{i3}(x_{i})=\frac{L_{i}^{3}}{\pi^{3}}\sin\Bigl{(}\frac{\pi x_{i}}{2L_{i}} \Bigr{)}-\frac{L_{i}^{3}}{3\pi^{3}}\sin\Bigl{(}\frac{3\pi x_{i}}{2L_{i}}\Bigr{)} \\ \xi_{i4}(x_{i})=-\frac{L_{i}^{3}}{\pi^{3}}\cos\Bigl{(}\frac{\pi x_{i}}{2L_{i}} \Bigr{)}-\frac{L_{i}^{3}}{3\pi^{3}}\cos\Bigl{(}\frac{3\pi x_{i}}{2L_{i}}\Bigr{)} \end{array}\right.. \tag{13}\]  
Therefore, transverse vibration displacement can be written in the following matrix form:  
\[u_{i}=\mathbf{U}_{i}^{\mathrm{T}}\boldsymbol{\alpha}_{i}T_{i}(t). \tag{14}\]  
where \(\mathbf{U}_{i}^{\mathrm{T}}\) is the basis function vector, which is only related to the displacement variable, and \(\boldsymbol{\alpha}_{i}\) is the response coefficient vector:  
\[\left\{\begin{array}{l}\mathbf{U}_{i}^{\mathrm{T}}=[1,cos\pi\frac{x_{i}}{L _{i}},\cdots,\cos n\pi\frac{x_{i}}{L_{i}^{\prime}},\xi_{i1}(x_{i}),\xi_{i2}(x _{i}),\xi_{i3}(x_{i}),\xi_{i4}(x_{i})]\\ \boldsymbol{\alpha}_{i}=[a_{i0},\cdots,a_{in},a_{i1}^{f},a_{i2}^{f},a_{i3}^{f},a_{i4}^{f}]^{T}\end{array}\right.. \tag{15}\]  
After utilizing the first-order harmonic expansion to extend the time term [40], the vibration displacement can be written as follows:  
\[u_{i}=\mathbf{U}_{i}^{\mathrm{T}}\boldsymbol{\alpha}_{i}(\boldsymbol{\alpha}_{ i}^{\mathrm{c}}\cos(\omega t)+\boldsymbol{\mathbf{a}}_{i}^{\mathrm{s}}\sin( \omega t))=\mathbf{U}_{i}^{\mathrm{T}}\boldsymbol{\alpha}_{i}\mathbf{p}_{i}. \tag{16}\]  
where \(\boldsymbol{\mathbf{a}}_{i}^{\mathrm{c}}\) and \(\boldsymbol{\mathbf{a}}_{i}^{\mathrm{s}}\) are the response coefficient vectors corresponding to the first-order cosine and sine wave, respectively, and \(\mathbf{p}_{i}\) is the generalized time vector.
## 2 Theory of Video SAR
### Frame Rate
Unfortunately, the increased PRF in FMCW SAR systems causes the transmission time to decrease, which leads to a reduction in detection distance. However, by using a multi-channel reconstruction algorithm, the image rate can be increased without increasing the PRF at a given azimuth resolution, by increasing the platform velocity. By using the spotlight SAR mode for the proposed MIMO ViSAR system, it is possible to generate a SAR video with a high frame rate in the circular path. In the system proposed in this paper, in order to increase the frame rate in the spotlight mode, the transmitted frequency and the radar velocity are increased using the frame rate relation shown in Equation (4). In this case, a high frame rate SAR video can be obtained without using the full aperture synthesis method (BPA), which has very high computational complexity. In particular, the Doppler bandwidth is increased due to the increase in the radar velocity, and the MCRA algorithm is used to suppress Doppler ambiguities.
# A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
## 3 An In-Depth Analysis of the mmWave Hybrid Beamforming Landscape
### Band
#### 3.3.1 Narrowband  
It offers a good compromise between the need for enough beamforming gains to compensate for propagation loss and the goal of lowering hardware costs and power usage. The performance metric used in [47] to describe the transmission's dependability is the mean square error (MSE). The hybrid transmit-and-receive beamformers are optimized alternatively using the alternating minimization approach in order to get around the challenge of solving the multi-variable design problem. In particular, an HBF algorithm based on manifold optimization is first put forth, directly addressing the analog component's constant modulus limitation.
## 1 Introduction
MP-AES is a multi-element technique that offers better detection limits over a wider analytical working range than FAAS. Unlike previous microwave-induced plasma (MIP) sources, which coupled energy from the microwave electric field, this technique uses a novel magnetically excited emission source coupled to an emission spectrometer. The resultant plasma shape allows easy entrainment of the wet sample aerosol into the core of the plasma, similar to that produced by a conventional ICP nebulizer and a spray chamber. The first commercial MP-AES instruments were introduced in 2011. In our earlier studies, this technique was utilized successfully for the generation of precise data required for geochemical investigations and mineral exploration studies of precious metals in rock and ore materials [18; 19]. In another study, an attempt was made to demonstrate the potential of MP-AES for environmental studies [20]. Several other studies have employed MP-AES for the determination of trace elements such as Cu, Fe, Mn, and Zn in animal feed and fertilizers [21], gasoline and ethanol [22], petroleum crude oil [23], diesel and biodiesel [24], and biofortified yeast analysis [25]. Different procedures have been proposed for determining the content of metallic species in biosludge samples [26]. However, due to the complexity of biosludge matrices, time-consuming sample preparation and content determination procedures are typically required. In the present study, an attempt is made to develop a rapid method for the determination of B, P, and Mo content in biosludge samples utilizing the MP-AES technique. Microwave assisted acid digestion system is utilized for sample preparation and its results are compared to those determined using conventional ICP-OES and FAAS methods. Finally, the potential for the application of MP-AES in the analyses of similar materials is discussed and compared with those of FAAS and ICP-OES.
## 2 Review of the State of the Art about Packet Analysis and Related Work
### Related Research about Deep Packet Inspection
For this purpose, [PERSON] and [PERSON] [20] have developed a DPI system whose signatures and rules are updated with machine learning techniques, in conformity with the traffic it analyzes. Their tests showed that this implementation of DPI detects signatures in the shortest possible time and reduces man hours of work in creating rules and new signatures.