esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Dual-Wavelength Method for Evaluating Temperature Effect in Fiber-Optic SPR Sensors
## 4 Experimental Results and Discussion
Compared to the traditional multimode fiber SPR sensor, our proposed detecting method using two fixed wavelengths can improve the resolution and signal-to-noise ratio of measurements. Figure 9: The output signal of the dual wavelengths versus RI.
## 2 Materials and Methods
### Nanoparticle Synthesis  
The undoped and Eu\({}^{3+}\)-, Gd\({}^{3+}\)- and Y\({}^{3+}\)-doped CeO\({}_{2}\) nanoparticles were synthetized via a green hybrid sol-gel combustion method developed by [PERSON] et al. [44] using sucrose as a poly-condensation agent and pectin as a chelation agent. Briefly, the corresponding amounts of metal salts--for the doped systems 5 at% of Eu\({}^{3+}\), Gd\({}^{3+}\) and Y\({}^{3+}\) ions relative to CeO\({}_{2}\)--were dissolved in MiliQ water (0.05 M) at 60 \({}^{\circ}\)C for an hour under vigorous magnetic stirring. Similarly, a sucrose solution (0.1 M) was prepared using milli-Q water, at 60 \({}^{\circ}\)C, under magnetic stirring. The two solutions were mixed in the presence of the pectin (the sucrose to pectin weight ratio was 1:5). The pH value was monitored during the synthesis and no correction was necessary to maintain an acidic medium in the solution. The pH value of the final solutions was determined to be in the range of 1.5-2. The as-obtained mixture was dried in air, on the sand bath. At 215 \({}^{\circ}\)C, a spontaneous combustion of the synthesis mixture was observed and a dispersed yellow powder was obtained. The evolved gases were captured and absorbed in a soda lime aqueous solution. The following chemical reaction can be considered in the formation of ceria nanoparticles:  
\[(1-x)\text{Ce}^{3+}+x\text{RE}^{3+}+2\text{NH}_{4}^{+}+6\text{NO}_{3}{}^{-}+2 \text{C}_{12}\text{H}_{22}\text{O}_{11}+26\text{O}_{2}\text{$\rightarrow$} \text{Ce}_{(1-x)}\text{RE}_{x}\text{O}_{2}+24\text{CO}_{2}\text{$\uparrow$}+26 \text{H}_{2}\text{O}+8\text{NO}_{2}\text{$\uparrow$}\]  
The use of non-toxic reagents such as sucrose and pectin give the process a green synthesis approach, but the reaction is not an environmentally friendly reaction due to the production of nitrogen dioxide.
## 3 Concept, Classification, and Data Sources of Digital Service Trade  
### Digital Service Trade  
With the continuous deepening of academic research on digital trade, digital service trade has gradually been mentioned by more and more scholars, but there is no unified standard for the concept of digital service trade internationally. In 2017, the OECD (Organization for Economic Cooperation and Development) defined digital service trade as the trade of cross-border delivery of services through information and communication. In 2018, the Ministry of Commerce emphasized that digital service trade is mainly based on digitization. The 2019 China Digital Service Trade Development Report believes that the focus of digital service trade is on digital products, and the trade mode is digital delivery. In 2019, the Ministry of Commerce issued the Notice on Organizing the Declaration of National Digital Service Trade Export Base, which defined digital services as the use of digital technology for research and development, design, production, and delivery of products and services to users via the Internet. In the same year, OECD redefined digital service trade, believing that digital service trade refers to the trade of remote delivery of goods and services relying on digital technologies such as the Internet.  
On this basis, in line with the OECD and UNCTAD standards, and in conjunction with the Chinese Academy of Information and Communications (2020), this study defines the connotation of digital service trade as international trade in online delivery based on digital elements and content, relying on digital technologies such as the Internet. For the industry classification of digital service trade, refer to the classification of service trade in the Expanded Balance of Payments Service Classification 2010 and the statistical caliber of digital delivery trade in the OECD IMF WTO (2020), including insurance and pension services, financial service, communication, computer and information (ICT) services, intellectual property services, personal entertainment services, and other commercial services.
# Efficient Transmit Antenna Subset Selection for Multiuser Space-Time Line Code Systems
## 5 Simulation Results
It is also seen in Figure 5 that the performance gap between the proposed decremental selection algorithms and the greedy algorithm is bigger as the number of selected antennas is smaller. It is observed in Figure 6 that when the diversity gain is high, all the greedy, the proposed incremental, and the proposed MMSE decremental algorithms offer similar BER performance. In Figure 5, the SNR penalties are approximately given as 1 dB and 3.8 dB, respectively, for \(N_{S}=6\) and \(N_{S}=4\). In Figure 6, they are approximated by 2.5 dB and 6.75 dB, respectively, for \(N_{S}=8\) and \(N_{S}=4\). They are well agreed with analytical results in Figure 7, which is obtained from (50). Thus, we can evaluate the received SNR penalty owing to TAS selection by using (50) for massive MU-STLC MIMO systems. Figure 8 exhibits the asymptotic received SINR penalty as a function of \(N_{S}\) for the MU-STLC system with \(N_{T}=32\) and \(K=8\). It is found that as the number of selected transmit antennas increases, the SINR penalty decreases. Furthermore, we can expect from the received SINR penalty analysis that without BER simulations, the BER results of the proposed MMSE decremental and conventional greedy algorithms are similar for the \((32,N_{S},8)\) MU-STLC system. Figure 4: BER the proposed TAS selection algorithms for \((8,N_{S},K)\) MU-STLC system with \(N_{S}=K\). Figure 5: BER the proposed TAS selection algorithms for \((8,N_{S},4)\) MU–STLC system. Figure 6: BER the proposed TAS selection algorithms for \((16,N_{S},4)\) MU–STLC system. Finally, Figures 9 and 10 illustrate the BER results of the proposed TAS selection algorithms as a function of \(K\) for the \((8,N_{S},K)\) MU-STLC system with \(N_{S}=K\) when \(SNR=12\) dB and \(SNR=16\) dB, respectively, are given. The BER performance worsens for all TAS selection algorithms as \(N_{S}(=K)\) increases. It is due to the increased multiuser interference. Particularly, the proposed ZF decremental TAS selection algorithm for large \(K\) achieves poor performance owing to large multiuser interference. On the other hand, it is seen that the proposed MMSE decremental TAS selection algorithm achieves the BER performance close to the optimal algorithm and outperforms the other TAS selection schemes for \(N_{S}<N_{T}\). This implies that the proposed MMSE decremental selection algorithm is able to effectively suppress the multiuser interference. For this scenario, the comparison of computational complexity has been given in Figure 1. Recall that the proposed MMSE decremental TAS selection algorithm has the lowest complexity for \(N_{S}=\{5,6,7\}\). Figure 8: Received SINR loss for MU–STLC system with TAS selection for \((32,N_{S},8)\)  
Figure 7: Received signal-to-interference-plus-noise ratio (SINR) loss for MU–STLC system with TAS selection for \((8,N_{S},4)\) and \((16,N_{S},4)\).
# Thermal Evaluation of a Hybrid Dryer with Solar and Geothermal Energy for Agroindustry Application
## 3 Results
### Evaluation of the Dryer and Solar Collector in Outdoor Conditions  
The first tests were performed only in the drying chamber, with a continuous flow of air inlet. The analysis evaluated the incident solar radiation and its influence on the warming of the internal air, heat supply, ambient temperature, air speed, and humidity, among other climatic conditions of interest, reaching an increase in temperature of 35 \({}^{\circ}\)C on sunny days and an increase of 10 \({}^{\circ}\)C on low irradiation days. The chamber response to the variation in solar radiation occurred with a delay of 10 min, with the temperature loss and gain of less than 1 \({}^{\circ}\)C.  
Figure 4 shows the results obtained with the dryer chamber at different days under environmental conditions. The colors in the graph represent different measurement days. We can see that the solar dryer started at an ambient temperature between 25 \({}^{\circ}\)C to 30 \({}^{\circ}\)C and reached the design temperature of 50 \({}^{\circ}\)C with 450 W/m\({}^{2}\).  
It is necessary to indicate that the experimental tests were carried out for four months (March to June) where the maximum ambient temperature of the locality ranges between 29 \({}^{\circ}\)C and 36 \({}^{\circ}\)C on the day.  
Figure 5 analyses the influence of the solar collector on the drying chamber in real outdoor conditions. The stabilization intervals of the solar dryer were analyzed, especially at the global solar irradiation intervals of 300 to 800 W/m\({}^{2}\), where the air intake temperature in the solar collector (Te) was ambient temperature in a range of 27 \({}^{\circ}\)C and an air velocity of 1.5 m/s. The temperature of the collector reached 50 \({}^{\circ}\)C from 500 W/m\({}^{2}\).  
Figure 4: Measurements performed under environmental conditions for the solar dryer.
## 3 Results and Discussion
### Scanning Electron Microscope (SEM) Analysis  
SEM images showed that the microstructure of pangasius gels changed with varying salt concentrations and processing conditions (Figure 7), corresponding to the mechanical properties.  
The HIG sample exhibited a relatively loose and irregular structure, with visible gaps and pores. In contrast, gels treated with high pressure (especially at 400-500 MPa) showed a denser, more homogeneous, and compact structure as compared to HIGs. This indicates that HPP treatment facilitates the formation of a well-developed gel network in pangasius gels. PG with 2% salt treated with high pressure formed a more compact  
Figure 7: Scanning electron microscopy (SEM) images of pangasius gel at different salt concentrations and high-pressure processing conditions. HIGs: conventional heat-induced gels; PG300/1%: salt concentration 1% and 300 MPa/10 \({}^{\circ}\)C/10 min; PG300/2%: salt concentration 1% and 300 MPa/10 \({}^{\circ}\)C/10 min; PG400/1%: salt concen-tration 1% and 400 MPa/10 \({}^{\circ}\)C/10 min; PG400/2%: salt concentration 1% and 400 MPa/10 \({}^{\circ}\)C/10 min; PG500/1%: salt concentration 1% and 500 MPa/10 \({}^{\circ}\)C/10 min; PG500/2%: salt concen-tration 1% and 500 MPa/10 \({}^{\circ}\)C/10 min.  
microstructure with fewer voids and a smoother surface compared to PG with 1% salt, exhibiting characteristics typical of pressure-treated gels [3]. In contrast, PG with 1% salt displayed a spongier structure compared to PG with 2% salt due to the lower salt content, which limited protein solubility and resulted in a weaker gel. However, HPP still facilitated the formation of a relatively compact gel with fewer voids and a smoother surface than heat-treated gels. SEM observations also confirm the correspondence between microstructure and the mechanical properties of pangasius gels, in which HPP-treated samples exhibit improved hardness, gel strength, and WHC compared to HIGs. Similar observations in fish gels and surimi treated with HPP have been reported in previous studies, showing that pressure-induced gelation can produce finer and more stable networks compared to heat-only treatments [4; 5].
# Evaluation and Improvement of Lidar Performance Based on Temporal and Spatial Variance Calculation
###### Abstract  
Poisson distributions have the characteristic of equality between their variance and mean values. By constructing a calculation model of the temporal variance and spatial variance, the relationship between the variance and mean values of lidar analog data and photon-counting data can be analyzed. The calculation results show that the photon-counting data from far field have the distribution property of equality between the variances and the corresponding mean values, while the analog data for the whole probing traces do not. In this paper, by analyzing the distribution properties of the spatial variance and temporal variance of lidar data, the dead time of photon-counting data was estimated, and the threshold voltage of the photon-counting system and the linear working range of photomultiplier tube were evaluated. The results show that the linear working range of the high voltage for the photomultiplier tube in the ultraviolet elastic scanning lidar is between \(-500\) V and \(-1000\) V, and the dead time and threshold voltage of the photon-counting system in the Licel transient recorder are 3.488 ns and 1.20 mV, respectively. Meanwhile, a novel gluing method between analog data and photon-counting data is presented, based on the calculation results of the variance distribution of lidar data. The linear transfer coefficients were determined by minimizing the differences between the variance and mean of the transformed photon-counting data in the near filed with high signal to noise ratio. The glued data were distributed to express the atmospheric conditions uniformly.  
Keywords:spatial variance; temporal variance; analog data; photon-counting data; dead time; threshold voltage; linear working range; data gluing +
Footnote †: journal: Applied Sciences
# IW-NeRF: Using Implicit Watermarks to Protect the Copyright of Neural Radiation Fields
## 4 Proposed Method  
### Framework  
Our study centers on INR watermarking, utilizing the implicit representation of a NeRF as a case study to elucidate our approach, as depicted in Figure 3.  
In our methodology, we denote the initial network conveying watermark information as \(F_{\sigma}(\cdot)\), the augmented model network with the watermark as \(G_{\theta}(\cdot)\), the watermark information dataset as \(H_{i},i\in[1,k]\), and the carrier model's training dataset as \(Q_{i},i\in[1,k]\). The overall framework of our approach, delineated in Figure 4, is partitioned into three sequential stages. Initially, the content owner trains \(H_{i}\) using \(F_{\sigma}(\cdot)\) to derive the watermark information network \(\hat{F}_{\sigma}(\cdot)\) and integrates the model parameters of \(\hat{F}_{\sigma}(\cdot)\) into \(G_{\theta}(\cdot)\) via the key K. Subsequently, the content owner trains \(G_{\theta}(\cdot)\) with the carrier dataset to construct a NeRF model \(\hat{G}_{\theta}(\cdot)\) encompassing watermarks. In the final phase, during a copyright dispute, the content owner leverages the key K to extract the original parameters of \(\hat{F}_{\sigma}(\cdot)\) from \(\hat{G}_{\theta}(\cdot)\) for watermark information recovery. The embedding and extraction processes of the watermark information described above can be expressed through Equations (1) and (2):  
\[G_{\theta}(\cdot) = Emb(\hat{F}_{\sigma}(\cdot),K) \tag{1}\] \[\hat{F}_{\sigma}(\cdot) = Ext(\hat{G}_{\theta}(\cdot),K) \tag{2}\]
# Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model
## 2 Model Description
### UAV Robot Imaging Configuration Based on the Satellite Communication Systems  
A UAV robot imaging system based on the satellite communication is one with the transmitter and receiver loaded on satellite and UAV platforms, respectively, as shown in Figure 2. In this simulation, the flight tracks of the transmitter and receiver are set to be parallel, and both transmitter and receiver operate in strip mode. Furthermore, it is assumed that both transmitter and receiver work in \"work-stop-work\" mode based on the fact that the motion velocity of this UAV and satellite is very small compared with the signal transmitting velocity. Therefore, the satellite can transmit and the UAV robot can receive the signals at a series of discrete positions. In this study, the orbit altitude of the transmitter remains unchanged, while the heights of the receivers loaded on UAV networking are considered to obtain scattering signals at different zenith angles, which contribute to analyze the multi-path scattering mechanisms of vegetation based on UAV networking using a satellite communication system.  
The working frequency is chosen at C band, and proper bandwidth is selected according to the system, as listed in Table 1. The altitude of the transmitter is 800 km, while the height of receiver is 8 km. The incident angle of the transmitting signal is 45\({}^{\circ}\), and it can be demonstrated that the horizontal distance between the transmitter and the target vegetation is approximately 800 km. For the receiver, six typical zenith angles: 26\({}^{\circ}\), 36\({}^{\circ}\), 46\({}^{\circ}\), 56\({}^{\circ}\), 66\({}^{\circ}\) and 76\({}^{\circ}\) are chosen to study how the zenith angle affects the multi-path scattering imaging results. The horizontal distance between the receiver and the target vegetationin can be calculated according to the zenith angle and flight height. Other parameters in this simulation are listed in Table 1.  
Figure 2: UAV robot observation configuration.
# An Operational Image-Based Digital Twin for Large-Scale Structures
###### Abstract  
This study presents a novel methodology to create an operational Digital Twin for large-scale structures based on drone inspection images. The Digital Twin is primarily used as a virtualized representation of the structure, which will be updated according to physical changes during the life cycle of the structure. The methodology is demonstrated on a wind turbine transition piece. A three-dimensional geometry reconstruction of a transition piece as manufactured is created using a large number (>500) of RGB images collected from a drone and/or several LiDAR scans. Comparing the reconstruction to the original design will locate and quantify geometric deviations and production tolerances. An artificial intelligence algorithm is used to detect and classify paint defects/damages from images. The detected and classified paint defects/damages are subsequently digitalized and mapped to the three-dimensional geometric reconstruction of the structure. These developed functionalities allow the Digital Twin of the structure to be updated with manufacturing-induced geometric deviations and paint defects/damages using inspection images at regular time intervals. The key enabling technologies to realize the Digital Twin are presented in this study. The proposed methodology can be used in different industrial sectors, such as the wind energy, oil, and gas industries, aerospace, the marine and transport sector, and other large infrastructures.  
Digital Twin; drone; machine learning; 3D reconstruction; damage inspection; artificial intelligence
## 4 Experiments and Results
### Analysis Results for the Urban Area
#### 4.3.3 Weekend Urban Analysis  
The same results were obtained when comparing the results of the appropriate number of clusters between the weekend and the weekday in the urban acoustic environment: \(Q=2\) was the suboptimal lower number of clusters for all the metrics, despite the Gap one, which also attained this value for \(Q=3\) clusters (see Figures 12 and 15).  
However, regarding the distribution of sensors within the obtained clusters with the agglomerative hierarchical clustering method, some small differences can be found when comparing weekend with weekday STPs. As can be seen in the dendrogram depicted in Figure 16, sensor locations of hb106 and hb127 were grouped together with another set of sensors, as well as hb135 and hb137. Figure 17 shows the corresponding similarity matrix of the urban weekend STPs. hb106 and hb127 seem to have behaved similarly to other  
Figure 14: Similarity matrix (**S**) for the urban environment on the weekday. White dashed lines separate three clusters of the \(Q=3\) clustering solution (marked as green rhomboids at bottom), and the \(Q=2\) one (also marked on the left-side as red rectangles). Inter (\(i=j\)) and intra-cluster (\(i\
eq j\)) distances are highlighted in white and denoted as \(D_{ij}\).  
Figure 15: Clustering validity indices obtained for the acoustic urban environment at the weekend, resulting from the agglomerative hierarchical clustering algorithm for the considered number of clusters sweep \(2\leq Q\leq 18\). The suboptimal number of clusters are marked as red asterisks, being the local maxima in all clustering indices despite the Davies–Bouldin index, which is a local minimum.  
sensors of cluster C1 in the \(Q=3\) solution and also other sensors from cluster C3, while the sensor location of hb135 behaved clearly closer to those from cluster C2. This pattern can also be discerned in Figure 14, but in the weekend analysis it is clearer. In contrast, the acoustic environment sensed by hb137 seems to be closer to those acoustic environments grouped in cluster C3, despite it being assigned to cluster C2.
## 1 Introduction
The proposed algorithm incorporates the dynamic values of harmony memory considering rate (HMCR) and pitch adjustment rate (PAR) with the local optimization techniques from a HS, to hybridize with the idea of probabilistic acceptance rule from the SA to deal with premature convergence. Computational experiments on the popular benchmark dataset of Perl, Gaskell, and Christofides show that the proposed algorithm outperformed a standard HS and an improved HS for all cases. This study is the extension of the research from [6,7]. The idea of solving the vehicle routing problem (VRP) using a standard HS algorithm is first proposed in [6]. The problem is further extended into the LRP in [7]. The HS in [6] solved the VRP using four local search techniques with fixed values of HMCR and PAR. In [7], they introduced the dynamic values of HMCR and PAR to solve the LRP. In this paper, we extended the methodology in [7] to solve the LIRP by adding two popular local search methods: 2-opt and 3-opt, as the local optimization techniques. The proposed HS is further enhanced by hybridizing it with SA with the implementation of probabilistic acceptance rule during the improvisation procedure of the HS. The remainders of the paper are organized as follows: the literature review of supply chain network design is presented in Section 2. The mathematical formulation of the LIRP with EPQ model is given in Section 3. Section 4 describes the framework and procedures of the proposed hybrid HS-SA algorithm. The computational experiments on three sets of popular benchmark datasets are performed, and the results are discussed in Section 5. Lastly, the conclusions and future direction are given in Section 6.
# Enhanced QoS Routing Protocol for an Unmanned Ground Vehicle, Based on the ACO Approach
## 2 Method
### ACO-Based Optimization  
The ant colony optimization method, utilized to solve multi-object problems with a high computing complexity, was inspired by the food-foraging activities of actual ants [9; 10; 11].  
Figure 1: ACO scenario of the VANET for the firefighting UGVs, which depends on the throughput parameter to select the optimal route.  
The ACO may also be appropriate for the VANET routing issues for the following reasons [12; 13]:  
1. The number of ACO nodes, namely scalability, vary depending on the size of networks, which is enhanced by the interactions between various ant colonies. The ant can be portrayed as a firefighting UGV.
2. Adaptation: As the network evolves, the number of ant colonies can be increased or decreased.
3. The strategy of the parallelism for the ant colony: this technique aids in the acceleration of the processes.
4. Fault tolerance: Because the ACO is an uncentralized control mechanism, several connections that are lost will have no effect on the overall system.  
Depending on the previous considerations, the ACO flexibility and the nature of decentralization, together are essential to address the obstacles of tracking the routing optimization. The ACO is employed in the development of a multi-objective heuristic algorithm that determines the optimum path, based on the shortest distance and the lowest chance of disconnection [14]. It is a hybrid routing system that combines the reactive route construction with the proactive route management. Nonetheless, each node (firefighting UGV) is required to keep all traffic from the visited routes, which observes the network of remote routers [15].