esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Preliminaries and Problem Setup
### Reinforcement Learning  
Reinforcement learning is an optimization-based method to solve an MDP (Markov Decision Process) [18]. An MDP is comprised of \(\{S,A,P,R,\gamma\}\) where \(S\) is a set of the state and \(A\) denotes a set of the action. Besides, \(P\) consists of \(P(s^{\prime}|s,a)\) which is the transition probability that the current state \(s\in S\) with the action \(a\in A\) becomes the next state \(s^{\prime}\in S\). \(R\) stands for the reward function and \(\gamma\in[0,1]\) is the discount factor. The agent's policy \(\pi(a|s)\) implies the distribution of the action \(a\) for the given state \(s\). In reinforcement learning, the agent takes action \(a_{t}\) according to the policy \(\pi\) at time \(t\) and state \(s_{t}\), and the environment returns the next state \(s_{t+1}\) and reward \(r_{t+1}\) by the transition \(P\) and reward function \(R\). By repeating this, the agent updates its policy so as to maximize its expected return \(E_{\pi}[\sum_{k=0}^{\infty}\gamma^{k}r_{t+k+1}]\). The resulting optimal policy is denoted by \(\pi^{*}\). In order to find the optimal policy, value-based methods like DQN (Deep Q-Network) estimate the optimal value function (i.e., estimate the maximum return) and find the corresponding policy [19]. On the other hand, policy gradient methods compute the optimal policy directly from samples. For instance, REINFORCE, actor-critic method, DPG (Deterministic Policy Gradient), DDPG (Deep DPG), A3C (Asynchronous Advantage Actor-Critic), TRPO (Trust Region Policy Optimization) are representative methods of policy gradient methods [22; 35; 36]. Training performance of reinforcement learning is heavily dependent on samples which are several sets of the state, action, and next state. Hence, in addition to the various reinforcement learning algorithms, many research efforts have been directed to study on how to use episodes efficiently for the purpose of better agent learning, for example, replay memory [19] and HER (Hindsight Experience Replay) [33]. In this paper, for the sake of designing a motion planningalgorithm, a policy gradient called TD3 (twin delayed Deep Deterministic Policy Gradient) is used for path planning.
## 5 Satellite Stabilization Problem
### Example 1. The Joint Estimation and Control Problem
#### 5.1.1 Case A  
The measuring system model is described by the following relationship:  
\[z(t)=\left(r(t),p(t)\right)^{\text{T}}\]  
The behavior of trajectories set for different mini-batch sizes is shown in Figure 1:  
Table 1 shows the results of solving the problem depending on the mini-batch size.  
Figure 1: The behavior of the satellite coordinates \(p,q,r\) (red) and estimations (blue) for different mini-batch sizes: (**a**) \(d=1\); (**b**) \(d=10\); (**c**) \(d=20\); (**d**) \(d=27\).
## The Proposed Model
### The Modified Encoder of the X-Transformer  
In the original Transformer [4], as shown in Figure 4a, each encoder is a self-attention mechanism with a point-wise feed forward layer, which is added for residual calculation and normalization. Additionally, the point-wise feed forward layer is mainly a fully connected layer with a large number of neurons through the middle layer, and it is responsible for retrieving important information in the corpus, so that the neurons can learn actively.  
Figure 4: (**a**) Encoder layer of the transformer; (**b**) modified encoder layer of the X-Transformer.  
Figure 3: Learning plateau.  
However, we found that if the feed forward layer is added for non-linear conversion at the early training stage, the NMT model is not able to capture the true hidden representation in the corpus. The reason for this is that the feed forward layer contains a non-linear transformation, Relu, which directly converts all negative values to 0. The original intention is to help the model to converge, but it may cause adverse effects in the early training step. Therefore, we experimented with several different combinations of self-attention mechanisms and feed forward layers in the encoder, with the aim of clarifying which combination does not affect the NMT model while training and that still can help to converge the model.  
Table 2 shows the impact of different combinations of self-attention mechanisms and feed forward layers in the model. In the table, the \"s\" represents a self-attention mechanism, and the \"f\" represents a feed forward layer, and the arrangement of letters represents the order of arrangement of the layers. Therefore, \"sf-sf-sf-sf-sf-sf\" is the baseline model of the original Transformer.  
In this specific translation dataset, it was found that three self-attention mechanisms are sufficient. It seems that the learning plateau phenomenon occurs again in the encoder. Finally, we chose s-sf-sf as our proposed model because it has fewer model parameters, while the BLEU score is almost the same. A similar notion was also proposed in [16]. If the self-attention mechanism appears earlier in the model and stacks more than the number of feed forward layers, the perplexity of the language model can be much lower.
## 2 Materials and Methods
### Measurement Parameters and Method
#### 2.3.3 Statistical Analysis  
The statistical differences were calculated using the SPSS Version 18.0 program, and the average difference between groups was measured by \(3\times 3\) repeated measurements of the group and the measurement time as independent variables (two-way ANOVA with the measurements). Measurements were taken three times pre-exercise, post-exercise, and post-treatment. A two-way repeated measures ANOVA was performed when the main effect and the interaction effects between the group and the measurement time were significant. The significance level of statistical analysis was set to \(\alpha=0.05\).
## 7 Passive Optical Network
### TDM-PON Application
#### 7.1.1 EPON Application  
As aforementioned, broadband solutions such as DSL and cable modem networks are widely deployed and offer relative improvements that are more than the 56 kbps dial-up lines. However, they do not have sufficient bandwidth for supporting the requirement of emerging services like interactive gaming, VoD, or video conferencing. Therefore, to support the services, access technologies that are not only simple, economical, scalable, but also capable of offering bundled data, voice, and video services are required. One of such technologies is the EPON, which is a low-cost Ethernet and optical access network (OAN) technology [396].  
In the scheme and as defined by the IEEE 802.3 standard, the data traffic is encapsulated in the Ethernet frames and then transmitted through the EPON. Like any other PON architecture, a typical EPON architecture comprises several network elements such as optical line terminal (OLT), optical network unit (ONU), and optical distribution network (ODN), which are the building blocks of the system [132]. Moreover, the scheme leverages the PON topology in offering Ethernet access. Furthermore, the combined scheme can give high bandwidth as well as relatively nice network scalability. Moreover, as the solution is well-compatible with Ethernet technology, a robust OAM can be delivered economically. Furthermore, to appreciate the relative advantage of EPON architecture regarding the lower fiber requirements, we compare different network topologies such as the PtP Ethernet and curb switched Ethernet in conjunction with the EPON. As depicted in Figure 23, PtP Ethernet can make use of either \(N\) or \(2N\) fibers, and therefore requires \(2N\) optical transceivers. Moreover, the curb-switched Ethernet employs one trunk fiber and consequently reduced the required fiber and space in the CO. However, it needs \(2N+2\) optical transceivers as well as electrical power in the field. Comparatively, EPON also employs just one trunk fiber and hence minimizes the required number of fibers and space in the CO. Besides, it demands just \(N+1\) optical transceivers, and there is no need for electrical power in the field [397]. Additionally, as shown in Figure 4 in Section 2.1.4, FTTC, FTTB, and FTTH network topologies can be effectively supported based on the ONU placements, as well as the demarcation point between the optical fiber and copper cable termination [143; 144].  
Note that apart from the IEEE 802.3 ah Ethernet that is a 1 Gbps EPON standard, there is also a 10G-EPON (IEEE 802.3 av) standard. The 10G EPON can support 10G/10G symmetric transmission in the DS and US. To further attend to the system requirements and improve the system performance, the IEEE 802.3 ca task force has been working unrelentingly over time on the 25G/50G/100G EPON standards development. Moreover, a noteworthy advantage of the standards is that they offer both backward and forward compatibility features. This helps in supporting the legacy services and advanced higher-speed services on the same ODN [143; 394; 398; 400].
## 1 Introduction  
In cervical spondylolic myelopathy (CSM), cervical disc herniation (CDH), and cervical ossification of the posterior longitudinal ligament (C-OPLL), asymptomatic patients with radiculopathy or myelopathy may be considered for surgical decompression [1]. Laminoplasty is a decompression procedure of the lamina for the spinal cord with positive surgical outcomes and improved techniques [2]. Although anterior decompression and fixation is also an important technique for decompression of the spinal cord, laminoplasty is often chosen because it allows for a wider decompression range and is relatively easy to perform [3, 4]. However, complications such as increased kyphosis and axial pain may occur more often after conducting laminoplasty compared to anterior decompression and fixation because laminoplasty invades the cervical posterior ligament complex, which can disturb the cervical sagittal balance [5]. Specifically, laminoplasty for straight or kyphotic curvatures of the cervical spine is not recommended because the laminoplasty may not create enough posterior migration or may cause impingement, stretch injury of the spinal cord, postoperative kyphotic deformity, and loss of range of motion (ROM) [6; 7].  
There are no reports that have examined the extent to which the ROM of the cervical spine, stresses on the intervertebral discs and facet joint contact biomechanics change when the laminoplasty procedure is performed for different alignments. We examined the biomechanical changes on when double-door laminoplasty [8] is performed on cervical spines with lordosis, straight, and kyphosis alignments. We hypothesized that the ROM, stress contribution of the disc, intervertebral body, and facet loads may change for the cervical alignment if the same laminoplasty was conducted. This study would provide mechanically important information for a physician performing laminoplasty and whether additional anterior decompression and fixation or posterior fixation with instrumentation is necessary, depending on the cervical spine alignment.  
In this study, a C2-C7 three-dimension (3D) FE model of a cervical spine with three alignments (lordosis, straight, and kyphosis) was created to examine how stress and mobility in the cervical spine changed for different alignments post double-door laminoplasty surgery.
## 3 Sensor Node Position Estimation
### Uncertainties in GPS Positioning
#### 3.1.1 Distance Algorithm  
In order to obtain the reference points through the distance algorithm, the sensor node calculates the distance between each pair of intersection points. For instance, consider the set of pairs \((c,e)\), \((a,d)\), and \((b,f)\) of Figure 4. When deciding between points \(c\) and \(e\), the sensor node calculates their distances to all other intersection points, which are \(a\), \(b\), \(d\), and \(f\). The point with the smallest distance (point \(c\) in the example) is set as a reference point, as can be seen in Equation (2).  
\[\forall p\in s:min(\sum(d(i,a)+d(i,b)))\ \ \forall o(a,b)\in s\ \ and\ \ o\
eq p \tag{2}\]  
where \(p\) represents the pair of intersection points, \(s\) denotes the set of pairs, \(d(x,y)\) represents the distance between intersection points \(x\) and \(y\), \(i\) represents each intersection point of the pair, \(o\) denotes the other pair of intersection points \(a\) and \(b\).
## 4 Conclusions  
For the special application of an aviation lighting system emitting green light, optical thin films made of SiO\({}_{2}\) and Nb\({}_{2}\)O\({}_{5}\) were designed using Essential Macleod. SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films were fabricated by the plasma-assisted reactive magnetron sputtering method. An XRD analysis revealed that SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films have an amorphous phase. Interfacial diffusion was not observed between the SiO\({}_{2}\) and Nb\({}_{2}\)O\({}_{5}\) layers based on cross-sectional SEM images and XPS scan spectra showing distinctive major peaks representing O1s, Si2p, Si2s, Nb3d\({}_{5/2}\), and Nb3d\({}_{3/2}\). XPS results indicated the major presence of Si\({}^{4+}\) and Nb\({}^{5+}\) in the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films, although the ratios were substoichiometric for both silicon and niobium. The most notable results were that the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films had a surface roughness of 2.32 nm \(\pm\) 0.19 nm, determined by an AFM analysis, and a transmittance of 96.14% in the range of 500 nm to 550 nm with a flat top surface and square bandwidth. The hardness of the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin film on B33 substrates measured by using a nanoindenter was 6.6 GPa. The high transmittance and hardness of the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films clearly demonstrate their feasibility for the special application of an aviation lighting system emitting green light.  
Investigation, J.-H.L, S.H.K., K.H., D.L., Y.S.H. and K.M.L.; Writing--original draft, S.K.; Writing--review & editing, J.H.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Materials and Components Technology Development Program of MOTIE/KEIT, 20018828 (Development of optical filter for wavelength control and light source module for lighting device), the Industrial Infrastructure Program for Smart Specialization of MOTIE/KIAT, P0017725 (Project of Industry supporting optical materials for camera lenses), and the Nano and Material Technology Development Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (NRF-2022M3H4A3085283).  
Not applicable.  
Data Availability Statement:Data is contained within the article.  
Conflicts of Interest:Author [PERSON] and [PERSON] were employed by the company Optrontec. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
Figure 8: Load–penetration depth curve of (**a**) SiO\({}_{2}\) and Nb\({}_{2}\)O\({}_{5}\) single-layer thin films on D263 substrates, (**b**) the SiO\({}_{2}\)/Nb\({}_{2}\)O\({}_{5}\) multilayer thin films on B33 substrates and D263 substrates.
## 2 Materials and Methods
### Data  
#### 2.2.1 The Rubber Plantations Distribution Data  
In this study, we utilized the 2000-2020 dataset of natural rubber plantation distribution changes on Hainan Island. This high-accuracy product was generated by [PERSON] et al. [40] through the integration of 1998-2022 Landsat TM/OLI imagery with field survey observations and the Third National Land Survey Report using a multi-feature random forest classifier. The resulting map achieves an overall classification accuracy of 96.93%, ensuring reliable delineation of rubber plantation extents. To align with the spatial resolution of our meteorological inputs, we overlaid a 1 km analysis grid onto Hainan Island and identified 1910 grid cells in which rubber plantation cover exceeded 90.0%, designating these as pure rubber plantation sites for subsequent analyses.
## 5 Results and Analysis
### Energy Utilization Efficiency (EUE)  
EUE of the wireless network is defined as the ratio of the energy saved in sleep mode by all small or femto BSs to the energy drained during active mode, multiplied by the number of users assisted during peak hours. Mathematically, EUE can be expressed as:  
\[\text{EUE}=\left(\begin{array}{l}\text{Energy saved during sleep mode}\\ \text{Energy consumed in Active mode}\end{array}\right)\times\left(\text{no of servered users}\right) \tag{11}\]  
Figure 9: Daily data traffic profile.  
Certainly, a higher EUE value indicates more efficient energy utilization within the network. [57]. From Figure 11, it can be observed that proposed dynamically DOSS strategies make a much better utilization of energy than other sleep strategies, mostly when the throughput requirements are high i-e when the number of mobile users per small cell increases after 20 to onwards, the EUE ratio increases with increasing number of mobile users for the proposed dynamically DOSS strategy. The rationale behind this is as follows, although LAS strategies follow static data traffic profile the actual traffic condition varies daily, therefore using static profile may reduce network performance by turning on unnecessary small BSs in active mode when the actual traffic load is low.  
Figure 11: Energy utilization of network.  
Figure 10: Small-cell BS active rate versus time.  
However, in dynamically DOSS strategies the small-cell BS adaptively update their activity status (ON/OFF) as per traffic variations so it will not only save energy but also serve a larger number of users as compared to LAS, thus it will lead towards improved EUE of the network.
# A Regional Brightness Control Method for a Beam Projector to Avoid Human Glare
## 3 Proposed System
### Transformation Profile Generation Module
#### 3.1.1 GTP Generator  
The geometric transformation matches the area of the screen observed by the camera to the area of the original image to be projected. The screen view that the camera is watching is largely distorted by the camera's angle of view and its position relative to the beam projector. To compensate for this, we applied a perspective shift operation. The features of the images for perspective translation and a transformation matrix to make those two images have similar regions should be found. Equation (1) is a matrix that converts a feature point (\(x_{1}\), \(y_{1}\)) on the camera screen to a corresponding feature point (\(x_{2}\), \(y_{2}\)) in the original image [24].  
\[\begin{bmatrix}x_{2}\\ y_{2}\\ 1\end{bmatrix}=\begin{bmatrix}a_{00}&a_{01}&b_{0}\\ a_{10}&a_{11}&b_{1}\\ a_{20}&a_{21}&1\end{bmatrix}\begin{bmatrix}x_{1}\\ y_{1}\\ 1\end{bmatrix} \tag{1}\]  
This step needs to find the eight unknowns in the matrix by finding at least four points that correspond between images \(A\) and \(B\). To perform this, various algorithms can be used for feature detection, such as corner detection, SIFT, and HOG features [25; 26; 27]. If these features are unambiguously extracted, they can be used as a reference point for calculating the transformation matrix.
## 4 Current Management Strategies for Corneal Scarring  
### Standard Terrestrial Treatments  
Corneal transplantation techniques have significantly evolved to address various extents of corneal damage. Among these, Deep Anterior Lamellar Keratoplasty (DALK) is a well-established approach for anterior corneal pathologies such as keratoconus. This technique spares the endothelium and Descemet's membrane, thereby reducing graft rejection risk [44]. Enhanced precision through femtosecond laser and \"big bubble\" techniques has further refined outcomes, minimizing complications and improving long-term graft survival [54; 55].  
Penetrating Keratoplasty (PK) remains the gold standard for full-thickness corneal damage, offering robust solutions for severe scarring caused by conditions like herpetic keratitis [56]. However, PK involves complex surgical techniques, an operating microscope, the use of anesthetic, and is associated with higher risks of immunological rejection and prolonged recovery times, necessitating extended immunosuppressive regimens to mitigate complications [56; 57]. Emerging innovations aim to address these challenges, including pre-surgical anti-inflammatory strategies to improve graft acceptance [57].  
For endothelial dysfunction, Descemet's Membrane Endothelial Keratoplasty (DMEK) and Descemet's Stripping Automated Endothelial Keratoplasty (DSAEK) are commonly performed. While DMEK ensures faster visual recovery and lower rejection rates, its steep learning curve makes it less accessible in under-resourced settings [58; 59]. DSAEK, though simpler to perform, has slower recovery rates but remains a viable alternative in resource-constrained environments [58].  
Adjunctive therapies, such as anti-scarring agents and advanced ocular bandages, complement these surgical approaches. For example, molecular therapeutics like exosomes and growth factor inhibitors are under investigation for minimizing postoperative fibrosis and enhancing corneal clarity [60].