esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance Analysis of UAV-IRS Relay Multi-Hop FSO/THz Link
###### Abstract  
As the era of sixth-generation (6G) communications approaches, there will be an unprecedented increase in the number of wireless internet-connected devices and a sharp rise in mobile data traffic. Faced with the scarcity of spectrum resources in traditional communication networks and challenges such as rapidly establishing communications after disasters, this study leverages unmanned aerial vehicles (UAVs) to promote an integrated multi-hop communication system combining free-space optical (FSO) communication, terahertz (THz) technology, and intelligent reflecting surface (IRS). This innovative amalgamation capitalizes on the flexibility of UAVs, the deployability of IRS, and the complementary strengths of FSO and THz communications. We have developed a comprehensive channel model that includes the effects of atmospheric turbulence, attenuation, pointing errors, and angle-of-arrival (AOA) fluctuations. Furthermore, we have derived probability density functions (PDFs) and cumulative distribution functions (CDFs) for various switching techniques. Employing advanced methods such as Gaussian-Laguerre quadrature and the central limit theorem (CLT), we have calculated key performance indicators including the average outage probability, bit error rate (BER), and channel capacity. The numerical results demonstrate that IRS significantly enhances the performance of the UAV-based hybrid FSO/THz system. The research indicates that optimizing the number of IRS elements can substantially increase throughput and reliability while minimizing switching costs. Additionally, the multi-hop approach specifically addresses the line-of-sight (LoS) dependency limitations inherent in FSO and THz systems by utilizing UAVs as dynamic relay points. This strategy effectively bridges longer distances, overcoming physical and atmospheric obstacles, and ensures stable communication links even under adverse conditions. This study underscores that the enhanced multi-hop FSO/THz link is highly effective for emergency communications after disasters, addressing the challenge of scarce spectrum resources. By strategically deploying UAVs as relay points in a multi-hop configuration, the system achieves greater flexibility and resilience, making it highly suitable for critical communication scenarios where traditional networks might fail.  
free-space optical communication (FSO); terahertz (THz); unmanned aerial vehicles (UAVs); outage probability; multi-hop FSO/THz systems; Gauss-Laguerre summation +
Footnote †: journal: Electronics Letters  
Article Performance Analysis of UAV-IRS Relay Multi-Hop FSO/THz Link
# A _uv_-Cellular Network: Design, Implementation and Experiments
## 4 Simulation Study
### Test Results of the Packet Delivery Fraction  
The purpose of the simulations presented in this section is to investigate the effects of different number of forwarding on the packet delivery fraction of these protocols. Figure 8 presents the relationship between the packet delivery fraction and forwarding hops. In this test, we do not use additional methods to guarantee the reliable transmission of data. It is clear that the metric is decreased as the number of hops grows. The packet delivery fraction of the CLA is obviously better than the VBF and MFLOOD. It is due to the fact that CLA selects the relatively most reliable path using the forwarding information which maintained locally. This forwarding strategy improves the efficiency of forwarding packets. However, VBF and MFLOOD have no ability to choose a relatively reliable path or next-hop node. That make it worse to the probability of packet loss in mobile scenarios.
# Time-Specified Adaptive Robust Control Framework for Managing Nonlinear System Uncertainties
## 4 Results and Discussion  
### Example 1: Single-Link Manipulator Model  
The first model describes the dynamics of a single-link manipulator with an uncertain parameter.  
The state equation for this system is  
\[M\ddot{q}+\omega\dot{q}+\frac{1}{2}mgl\sin(q)=\tau\]  
where \(q\), \(\dot{q}\), and \(\ddot{q}\) represent the angular position, velocity, and acceleration of the link, respectively. The parameter \(M\) is the moment of inertia, \(\omega\) is the viscous friction coefficient at the joint, \(\tau\) is the control torque, and \(m\), \(l\), and \(g\) represent the mass, the length of the link, and gravitational acceleration, respectively. The gravitational term \(mgl\cdot sin(q)\) appears because the manipulator operates in a vertical plane, where gravity exerts a moment on the link proportional to \(sin(q)\). This term creates a nonlinear effect that varies with the angular position, making control more challenging.
# High Performance Computing in Satellite SAR Interferometry: A Critical Perspective
## 3 Operational SAR Systems and Applications
### InSAR Applications and Products
Polarimetric SAR and interferometric SAR techniques are currently employed in agriculture applications, such as retrieving crop parameters from polarimetric SAR interferometry (Pol-InSAR) [150].
# 2D Phase-Based RFID Localization for On-Site Landslide Monitoring
## 3 Theoretical Model
### Localization Model
#### 3.1.2 2D Relative Displacement Approach  
Using the measurements of multiple antennas, we can expand this TD-PD method with spatial considerations. For this purpose, we need both the phase measurements and the geometrical coordinates \((x_{j},y_{j})\) of each antenna. This derivation focuses on the 2D problem; the 3D case will be briefly discussed at the end.  
We define the initial distance \(r_{0,j}\) from the antenna \(j\) to the tag:  
\[r_{0,j}=\sqrt{(x_{j}-x_{0})^{2}+(y_{j}-y_{0})^{2}}\]  
where \((x_{0},y_{0})\) are the initial coordinates of the tag and \((x_{j},y_{j})\) those of the antenna.  
Applying Equation (2), we obtain a series of radial displacements from the phase measurements of each antenna. From these radial distance measurements, a multilateration approach [48] can be applied to estimate the most probable position \((\hat{x}_{i},\hat{y}_{i})\) for the tag at the \(i\)th position. Amongst various possible methods of multilateration, we use an optimization algorithm that minimizes the following cost function \(Cf\) for the \(i\)-th measurement:  
\[Cf_{i}(x,y)=\sum_{j=1}^{N_{a}}\left|r_{i,j}-\sqrt{(x_{j}-x)^{2}+(y_{j}-y)^{2}}\right| \tag{3}\]  
\[(\hat{x}_{i},\hat{y}_{i})=\underset{(x,y)\in\mathbb{R}^{2}}{argmin}\big{(} \underset{(x,y)\in\mathbb{R}^{2}}{Cf_{i}(x,y)}\big{)}\]where \((x,y)\) are the test point coordinates, \(N_{a}\) is the number of antennas, \(r_{i,j}\) is the \(i\)-th radial distance from antenna \(j\), and \((\hat{x}_{i},\hat{y}_{i})\) is the most probable tag position. The minimization of this cost function was performed using the Trust-region optimization algorithm [49] implemented in the Scipy-optimize Python module.
## 2 Architectures
### End-to-End LF-MMI ASR  
Aiming to explore new state-of-the-art end-to-end ASR systems, we evaluated an alternative to the developed Kaldi-based hybrid ASR system. That was the new end-to-end ASR Lattice-Free Maximum Mutual Information (LF-MMI) approach [19], which is also used in Kaldi's chain models. Thus, we found it interesting to perform a reliable comparison of these two systems based on LF-MMI under IberSpeech-RTVE 2020 Challenge scenarios.  
This end-to-end ASR system is based on PyChain [18], a powerful PyTorch-based implementation, which is intended to have an easy-to-use pipeline in which the data preparation and final decoding are carried out in Kaldi for efficiency, while data loading and network training are performed in PyTorch [10]. It should be noted that no alignment was necessary, i.e., the HMM-GMM training stage is not required, unlike other systems [36; 37].  
Data preparation consisted of both feature extraction (40-dimensional MFCC) and numerator/denominator graph (FSTs) generation. By following [PERSON]'s method for LF-MMI, HMM graphs were used for supervision. Consequently, the final LF-MMI loss function can be expressed as follows:  
\[L_{MMI}=\sum_{u=1}^{U}\log\frac{P(X^{(u)}|\mathbb{G}_{num}^{(u)})}{P(X^{(u)}| \mathbb{G}_{den}^{(u)})} \tag{1}\]  
where \(X^{(u)}\) is the input frame sequences for the \(u\)-th utterance, while \(\mathbb{G}_{num}\) and \(\mathbb{G}_{den}\) are the numerator and denominator graph, respectively. These graphs are a combination of an n-gram phone Language Model (LM) with the acoustic part encoding all possible word sequences. As is widely known, \(\mathbb{G}_{den}\) is generated from any possible transcription, while \(\mathbb{G}_{num}\) makes use of the true transcription.  
The probability distribution function (pdf) is used to estimate the likelihood of an HMM emission [2]. In this case, the network output and the occupation probability are computed from a pdf-index (pdf-id) instead of an HMM state. More specific details were presented in Ref. [18].  
Once the data are loaded, the PyTorch model tries to simulate a TDNN [34] by including 1D dilated convolution in addition to batch normalization, ReLU, and dropout. This sequence is stacked in that order up to 6 layers with residual connections. At the end of the sequence, a fully connected layer is added (as described in Ref. [18]). From now on, this system is called the PyChain-based baseline system.
# Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography
###### Abstract  
Solid ink density is an important control parameter in the manufacturing process of offset prints--the size of which has a significant impact on the color performance of the prints--in which the determination of the optimal solid ink density is critical for the pre-press phase of industrial production. Compared with the traditional method of determining the optimal solid ink density, the current printing equipment used to determine the optimal solid ink density will be faster at improving industrial production efficiency and product quality. To improve the efficiency of determining the optimal solid ink density, the Random Forest algorithm was applied for the first time to the prediction task of solid ink density in offset printing. An optimal solid ink density prediction model for lithographic offset printing is established, and the L*a*b* colorimetric values of CMY three-color prints are used as inputs for training through hyperparameter optimization of the model. The experimental data show that the relevant evaluation metrics MAE, RMSE, MSE, and R\({}^{2}\) of the model are within the reliable range. A comparison between the proposed prediction model and several mainstream machine-learning algorithms indicates that the Random Forest model performs superiorly in both the coefficient of determination (R\({}^{2}\)) and the mean squared error (MSE). Specifically, the Random Forest model achieved an R\({}^{2}\) value of 0.969, reflecting improvements of 27.5%, 1.89%, 3.8%, and 34.02% compared to artificial neural network, gradient boosting, polynomial regression, and support vector regression models, respectively. In terms of MSE, the model reduced prediction error by 87.1%, 36.2%, 55.4%, and 89.2%, respectively, when compared with the same models. This approach has proven to provide both theoretical support and a practical pathway for enhancing the level of intelligence in pre-press process control, demonstrating significant practical application value.  
Keywords:random forest; print solid ink density; density detection; machine learning; print quality management +
Footnote †: journal: Applied Sciences
## 1 Introduction
### Research Objectives and Research Questions
**_How have Digital Twins contributed to sustainability and smart city initiatives based on published research over the past decade?_  
**RQ.10. **_According to recent scientometric data, how has the integration of IoT, AI, and edge computing impacted manufacturing and production systems?_  
The gaps identified in the previous systematic literature review (SLR) papers primarily revolve around the fragmented scope of research and limited integration of key emerging technologies in sustainability and the built environment (SBE). For instance, while some reviews focus on specific applications like smart cities [21] or BIM evolving into Digital Twins (DT) [26], they lack a comprehensive analysis of the integration of AI, DT, and IoT technologies and their collective potential to optimize energy management, improve sustainability, and address future challenges. Additionally, many reviews, such as those on infrared thermography [1] and blockchain with DT [6], either fail to include critical aspects like future perspectives and interdisciplinary limitations or do not explore broader sustainability contexts. The detailed research questions (RQs) in this study address these gaps by systematically exploring the scientometric trends (RQ.1), AI and automation in Industry 4.0 (RQ.2), IoT and AI's role in energy management and zero-energy buildings (RQ.3), and heritage building maintenance (RQ.4). The study also delves into emerging sustainable technologies (RQ.5), data management evolution (RQ.6), and blockchain and cybersecurity in digital ecosystems (RQ.7), ensuring a holistic analysis. By aligning these RQs with specific gaps in prior reviews, the study builds a detailed framework to explore overlooked areas, including flood resilience (RQ.8), DT's contributions to smart cities (RQ.9), and the impact of IoT, AI, and edge computing on manufacturing systems (RQ.10). This structured approach ensures the study addresses key interdisciplinary challenges, offering new insights for sustainable urban and industrial systems.
_Article_  
**Optimization Design of a 2.5 Stage Highly Loaded Axial Compressor with a Bezier Surface Modeling Method**  
**[PERSON] 1,2**(c), [PERSON] 1,2,*, [PERSON] 1,2**(c), [PERSON] 1,2**(c),  
**[PERSON] 1,2 and [PERSON] 1,2**  
Received: 27 April 2020; Accepted: 28 May 2020; Published: 1 June 2020  
**Abstract:** Due to the complexity of the internal flow field of compressors, the aerodynamic design and optimization of a highly loaded axial compressor with high performance still have three problems, which are rich engineering design experience, high dimensions, and time-consuming calculations. To overcome these three problems, this paper takes an engineering-designed 2.5-stage highly loaded axial flow compressor as an example to introduce the design process and the adopted design philosophies. Then, this paper verifies the numerical method of computational fluid dynamics. A new Bezier surface modeling method for the entire suction surface and pressure surface of blades is developed, and the multi-island genetic algorithm is directly used for further optimization. Only 32 optimization variables are used to optimize the rotors and stators of the compressor, which greatly overcome the problem of high dimensions, time-consuming calculations, and smooth blade surfaces. After optimization, compared with the original compressor, the peak efficiency is still improved by 0.12%, and the stall margin is increased by 2.69%. The increase in peak efficiency is mainly due to the rotors. Compared with the original compressor, for the second-stage rotor, the adiabatic efficiency is improved by about 0.4%, which is mainly due to the decreases of total pressure losses in the range of above 30% of the span height and 10%-30% of the chord length. Besides, for the original compressor, due to deterioration of the flow field near the tip region of the second-stage stator, the large low-speed region eventually evolves from corner separation into corner stall with three-dimensional space spiral backflow. For the optimized compressor, the main reason for the increased stall margin is that the flow field of the second-stage stator with a span height above 50% is improved, and the separation area and three-dimensional space spiral backflow are reduced.  
**Keywords:** axial compressor; aerodynamic design and optimization; computational fluid dynamics; Bezier surface modeling; multi-island genetic algorithm
## 3 Experimental Results and Discussion
### Comparison to Existing Systems
Even though the cost is slightly higher than the others, it offers extensive features. It is worth noting that the cost includes the Hawell IoT Cloud HMI device. Further, the proposed SCADA system is low cost compared to the established SCADA system.
## 3 Results and Discussion
### Antibiofilm Assay  
Of all microorganisms that were susceptible to the extract's effects, _S. aureus_ were the only ones that could establish biofilms. Thus, and considering the higher activities observed, shell extracts were screened for their capacity to inhibit the formation of these  
Figure 3: Time-death curves (drawn at MBC concentration) for each of the microorganisms for active _Q.__ilex_ extracts. The _x_-axis crosses the _y_-axis at the method’s quantification limit (log 500), with points overlapping the axis corresponding to values below it.  
Figure 2: Time-death curves (drawn at MBC concentration) for each of the microorganisms for active _Q.__ilex_ extracts. The _x_-axis crosses the _y_-axis at the method’s quantification limit (log 500), with points overlapping the axis corresponding to values below it.  
structures (Figure 4). Interestingly, MRSA appeared to be more susceptible to extract's action, with all extracts exhibiting inhibitions around 70% regardless of the heat treatment or the type of Quercus tree considered. For MSSA, while less susceptible to the extracts than MRSA, an interesting trend could be observed. For all extracts, the lower concentration was more effective (statistically significant \(p<0.05\)) than the highest one, with the only exception being for _Q. super_ HT shell extract (where no significant differences were observed between concentrations; \(p>0.05\)). As biofilms are a recognized protection structure, it has been hypothesized that high concentrations of phenolic compounds could act as a strong stimulus towards the formation of this structure, namely through the stimulation of exopolysaccharideascharides production, which could function as a barrier to protect sessile cells while also increasing the biofilm's overall biomass [39]. Overall, to the best of our knowledge, no reports have been made on acorns', and particularly acorn shells', effects on biofilm establishment by _S. aureus_, although some reports have been made regarding the effect of acorn extracts from other Quercus species. These include the work of [PERSON], [PERSON] [4], who reported that _Q. infectoria_ subps. _persica_ acorn extracts could inhibit _S. aureus_ biofilm formation at a concentration capable of inhibiting the bacteria's growth by 57%; and the work of [PERSON], [PERSON] [7], who reported that both MRSA and MSSA isolates' biofilm formation was significantly inhibited when exposed to 0.25 mg/mL of _Q. infectoria_ [PERSON]. [PERSON] extract, although these authors use nutgalls, not acorns.
# Application of Image Fusion in Diagnosis and Treatment of Liver Cancer
## 4 Imaging Fusion Algorithms
### Principal Component Analysis  
Principal component analysis (PCA) is a technique for dimensionality reduction for a large dataset. PCA is mathematically defined as an orthogonal linear transformation method that transforms data to new coordinate systems, such that the greatest variance by a scalar projection of data lies on the first coordinate, and so on [36]. In this manner, PCA [37, 38, 39] helps to reduce the noise and redundant information and highlight the key feature in the dataset. PCA is widely used in various applications, including image compression, image enhancement, image coding, random noise signal removal and image rotation. For image fusion, PCA can extract the key features of the images, which highlights the similarities and differences between the input images, while reducing the noise level at the same time. Then, based on these key features  
Then, the fused image is obtained by combination of the new high frequency and low frequency images. In the medical field, PCA has been applied in the fusion of MRI, CT, PET and US [41; 42; 43]. PCA can also combine with decomposition methods, such as IHS, the pyramid method, Discrete wavelet transform [44], the Curvelet transform, Contourlet transform [45] and Non-Subsampled Contourlet transform [31; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56].
###### Abstract  
This study extends the method of pseudo-dynamic analysis based on the Mononobe-Okabe (M-O) method by comprehensively incorporating the seismic acceleration response characteristics of backfill soil and the cohesive properties of the fill. The proposed method is adapted for backfill soils by incorporating the cohesion \(c\) and internal friction angle \(\varphi\) (including scenarios with non-horizontal backfill surfaces). Theoretical formulas for the active earth pressure coefficient and its distribution on rigid retaining walls under the most unfavorable conditions are derived. The rationality of the proposed formulas is preliminarily verified using model test data from the relevant literature. A detailed parametric sensitivity analysis reveals the following trends: The active earth pressure coefficient \(K_{\text{a}}\) increases with increases in the amplification factor \(f_{\text{a}}\), wall backface inclination angle \(\theta\), backfill slope inclination \(i\), lateral vibration period \(T\), and horizontal seismic acceleration coefficient \(k_{\text{h}}\); \(K_{\text{a}}\) decreases with an increasing internal friction angle \(\varphi\) and cohesion/unit weight ratio \(c/\gamma H\). The failure wedge angle \(\alpha_{\text{a}}\) increases with increases in \(\varphi\), \(\theta\), and \(c/\gamma H\), decreases with increases in \(f_{\text{a}}\), the soil-wall friction angle \(\delta\), \(i\), \(T\), \(k_{\text{h}}\), and the vertical seismic acceleration coefficient \(k_{\text{v}}\). Calculations are carried out to further identify the critical tensile stress depth in cohesive backfill soils using \(c\) and \(\varphi\). The proposed analysis highlights the necessity of considering the seismic acceleration amplification factor \(f_{\text{a}}\), backfill cohesion \(c\), and soil-wall adhesion \(c_{\text{w}}\) in active earth pressure calculations. This study recommends that the seismic design of retaining walls should involve appropriate evaluation of the the actual cohesion of backfill materials and fully account for the acceleration amplification effects under seismic loading.  
Keywords:retaining walls; dynamic active earth pressure; pseudo-dynamic method; acceleration amplification factor