esa-sceva/satcom-chunk-collection huggingface dataset:
# Self-Tuning Lam Annealing: Learning Hyperparameters While Problem Solving
## 2 Methods
### Self-Tuning Lam
#### 2.3.2 Tuning the Acceptance Rate EMA Hyperparameters  
There are two hyperparameters, \(\alpha\) and \(\text{AcceptRate}(0)\), that are related to the estimation of the acceptance rate that occurs throughout the run. The Modified Lam defined a constant \(\text{AcceptRate}(0)=0.5\), independent of run length and cost function scale, essentially assuming that at the start it is equally likely to accept a neighbor as it is to reject it. For an approach like the Modified Lam, which does not rely on any knowledge of the problem instance, this is a reasonable assumption considering that an EMA should eventually settle in upon an accurate estimation independent of its initial value.  
The Self-Tuning Lam initializes \(\text{AcceptRate}(0)\) more accurately, to enhance the accuracy of the EMA of the acceptance rate earlier in the search. Although the 0 seems to imply the beginning of the run, we actually mean when the adaptive portion of the run commences, once the \(M\) tuning iterations have ended. Prior to that point, the Self-Tuning Lam does not need \(\text{AcceptRate}(0)\). Because it accepts all neighbors during the tuning phase, it would not be unreasonable to define \(\text{AcceptRate}(0)=1.0\). However, we can be more accurate. We will see in the next section that the temperature is initialized based on samples of the cost function derived from the tuning iterations so as to cause the expected value of the acceptance rate to equal the target acceptance rate. Therefore, we can initialize \(\text{AcceptRate}(0)\) to the target:  
\[\text{AcceptRate}(0)=\begin{cases}\lambda_{0.001}&\text{if $N\geq 10,000$}\\ \lambda_{0.01}&\text{if $N<10,000$}.\end{cases} \tag{9}\]  
The original Modified Lam defines \(\alpha=0.002\), independent of run length. This is equivalent to what the finance industry refers to as a 999-day EMA, where an \(N\)-day EMA is defined by \(\alpha=2/\left(N+1\right)\). We obviously are not dealing with statistics of investments over time. However, this definition of an \(N\)-day EMA is useful to us as a way to define \(\alpha\) in terms of run length. The problem with using a constant for \(\alpha\) is that for short runs of SA, the ongoing estimation of AcceptRate may not adapt quickly enough as the true acceptance rate varies throughout the run.  
In the Self-Tuning Lam, we define \(\alpha\) in terms of the run length \(N\). Specifically, we set \(\alpha\) for a \(0.01N\)-day EMA, but we do not allow an \(\alpha>0.2\) to avoid basing the running estimate of the acceptance rate on too few samples. Thus, \(\alpha\) is defined as follows:  
\[\alpha=\min(2/(0.01N+1),0.2). \tag{10}\]
# Two-Dimensional Full-Waveform Joint Inversion of Surface Waves Using Phases and Z/H Ratios
## 1 Introduction
Currently, an increasing number of dense linear arrays have been deployed around the world, which facilitates the high-resolution imaging of the 2D structures beneath the linear array. In global-scale tomography, [PERSON] et al. [32] presented a 2D ambient-noise adjoint tomography technique for a linear array with a significant reduction in computational cost, and applied it to an array in northern China. [PERSON] et al. [33] developed 2D teleseismic body-wave adjoint tomography by an FK-SEM hybrid method. [PERSON] et al. [34] proposed a strategy of joint inversion for ambient-noise surface waves and teleseismic body waves recorded by linear arrays based on the adjoint-state method, which can be used to yield a fine S-wave velocity model and Moho topography. Small-scale tomography has been fully developed by the oil industry in the past three decades (well known as FWI), while 2D elastic FWI has recently been applied to shallow surface waves [35; 36; 37; 38]. In particular, [PERSON] et al. [39], [PERSON] et al. [40], and [PERSON] et al. [41] proposed a stable workflow for the 2D FWI of shallow-seismic Rayleigh waves not only for synthetic data, but also for real field-recorded data. However, including surface waves in FWI is a challenging issue, especially the cycle-skipping problems that occur due to these waves' higher amplitudes and different physical behaviors with respect to body waves. Benefiting from the fact that the sensitivity to the S-wave velocity is only concentrated near stations, the \(Z/\mathrm{H}\) ratio information can constrain the shallow S-wave velocity structure in the near surface, which helps mitigate the cycle-skipping problem. However, there is a lack of research about FWI using the \(Z/\mathrm{H}\) ratio or the joint inversion of both data sets. In this paper, we present a systematic investigation of the 2D Rayleigh wave travel-time (phase) sensitivity kernel and the \(Z/\mathrm{H}\)-ratio kernel via an adjoint-state method [19]. In addition, a full-waveform joint-inversion scheme for surface waves with phases and \(Z/\mathrm{H}\) ratios is proposed to take advantage of their complementary sensitivities to the S-wave velocity structure. Finally, synthetic-imaging experiments are described to demonstrate the potential of the proposed method to yield a better complementary S-wave velocity model with a high-resolution.
## 3 Proposed Joint Decoding (JD) Framework for Video
### Joint Decoding Framework  
This subsection discusses in detail the decoding process of the proposed JD scheme. The proposed JD consists of three significant steps, as presented in Figure 3.  
The descriptions of each step are provided in the following sections.
# Fault-Tolerant Control of Multi-Joint Robot Based on Fractional-Order Sliding Mode
## 5 Conclusions  
In this paper, the problem of actuator fault-tolerant control of multi-joint robots is studied; in particular, the fault-tolerant control of actuators under constant gain fault and constant deviation fault. The novel FSMC is designed to reduce the steady-state error under sinusoidal references. Additionally, the response speed is improved under step reference compared with SM. The following conclusions can be made from the experiment results.  
(1) The output voltage of the FSMC is smooth and there is no fluctuation compared with regular SMC method. There are two reasons to interpret this: the first reason is the introduction of tanh function, while the other reason is the fractional differential operator in the FSMC controller.  
(2) The response time under step reference is reduced and the control accuracy under sinusoidal reference are greatly improved, where the response time under CDF is improved by three times and the maximum error under CGF is improved by ten times.  
(3) The FSMC is robust under different actuator CDF and CGF, and it can achieve smooth tracking at steady state, which is superior to regular SMC.  
The comparative experiments show the superiority of FSMC in terms of rapidity and steady error characteristics. Future research work could be focused on the control problem of mixed faults, so the mathematic model of the multi-joint robot needs to be simplified and tested. New control theories research applied to robots is also worth its way.  
Conceptualization, J.P.; methodology, J.P., L.Q. and K.P.; software, L.Q.; validation, J.P.; formal analysis, K.P.; investigation, J.P. and K.P.; resources, L.Q. and K.P.; data curation, J.P. and L.Q.; writing--original draft preparation, J.P.; writing--review and editing, J.P. and K.P.; visualization, K.P. and L.Q.; supervision, L.Q.; project administration, L.Q.; funding acquisition, L.Q. and K.P. All authors have read and agreed to the published version of the manuscript.  
Figure 7: Output voltage of FSMC and SMC control under constant deviation fault (300 N-m).  
Funding: This research was funded by the National Key R&D Program of China, grant number 2019 YFB2005804.
###### Abstract  
Solar air heaters play a crucial role in distributing heated air at low to medium temperatures. The heart of these systems lies in the absorber plate, which directly absorbs solar heat energy and then efficiently transfers it to the flowing air. However, the challenge lies in achieving optimal thermal efficiency by modifying the absorber plate roughness. Traditional smooth absorber plates have a limited contact area for heat transfer, leading to suboptimal performance. Using passive techniques, such as corrugation on the absorber plate, may increase thermal efficiency by creating turbulence in the laminar sublayer. In this study, corrugated solar air heaters are considered, with the absorber plates roughened into square, semicircular, and triangular ribs. The flow characteristics of heat due to the roughness of the absorber plate is simulated using the computational fluid dynamic (CFD) technique. The ANSYS Fluent 2019R3 is used to investigate the turbulent air flow in the absorber plate. The simulation analyses are performed over a Reynolds number range of 4000-18,000 using three different pitches. As the main contribution, two different model equations, namely M1 and M2, for the correlation model of the solar heat transfer were proposed to predict the Nusselt number, where M2 is an original model and M1 is newly established with the fine-tuned coefficients. Also, for the first time in the literature, the recent swarm optimization algorithm, namely Honey Formation Optimization with Single Component (HFO-1), is used to optimize the solar air heater and a comparison study with a popular non-swarm optimization, namely the Generalized Reduced Gradient (GRG) optimization, is provided. The Nusselt number was obtained using HFO-1 with a percentage error (MAPE) of 2.15% and 0.86% for the models M1 and M2, respectively. Moreover, the average achievement of HFO-1 on the proposed correlation models is 50% better than that of the GRG optimization, with respect to the RMSE.  
CFD; solar air heater; heat transfer; HFO-1; metaheuristic; optimization
## 3 Opportunities, Challenges and Suitability  
The next generation of high-performance networks exploiting RDMA are giving rise to extremely important opportunities and challenges for these new protocols. These issues as well as suitability of RDMA-enabled networks are described in the following.
# Performance Evaluation of a Full-Duplex Relaying-Enabled Satellite Sensor Network
## 3 Performance Evaluation
### Ergodic Capacity
It is shown that the outage performance can be improved with low values of off-boresight angle and high values of elevation angles. This is because when the ES nodes are located closer to the satellite beam center, an enhanced beam gain factor would be obtained. Moreover, the satellite links with higher elevation angles experience weaker shadowing severities, thus leading to an improved propagation quality. Figure 4 shows the performance comparison between FD and HD modes versus residual error level \(p\). The Monte Carlo simulations are consistent with the theoretical derivation in the presence of different residual loop interference levels, which justifies the correctness of derived analytical expression. Further, the analysis can also serve as benchmark on interference cancellation performance with respect to their residual error levels. As can be seen, although the SI is inevitable, the ergodic capacity of FD mode is apparently superior to the HD modes, which is obtained due to time multiplexing gain by achieving simultaneously data transmission and reception. Besides, the ergodic capacity of the FD-based satellite relaying system is superior than that of the HD-based mode. This is due to the fact that the residual loop interference at the satellite relaying poses a detrimental effect on the system performance. Bedsides, with the increase of \(p\), the system performance becomes degraded, which justifies the importance of integrity and accuracy in SI cancellation for FD mode. Overall, from the theoretical derivations, the allowable SI error levels for which the considered FD operation in satellite relaying provides performance gains over the traditional HD relaying is warranted. Figure 5 depicts the ergodic capacity comparison between FD and HD satellite relaying systems for different off-boresight beam angles. It is shown that the system performance for both FD and HD modes can be improved with a smaller off-boresight angles \(\varphi_{1}\) and \(\varphi_{2}\) for both uplink and downlink. This is because when the ES nodes are located closer to the satellite beam center, an enhanced beam gain factor would be obtained. However, it is worth noticing that the off-boresight angle \(\varphi_{2}\) for downlink exhibits a more notable impact of the system capacity than that of \(\varphi_{1}\) for uplink in FD mode. This phenomenon is because the residual loop interference would be corresponding enhanced with a higher channel gain of uplink transmission. Figure 6 illustrates the ergodic capacity comparison between FD and HD satellite relaying systems for elevation angles \(\theta_{1}\) and \(\theta_{2}\). As can be observed, the increasing values
## 3 The Radiative Transfer Equation
### RTE Solution Considerations  
#### 3.2.1 Modelling Intrinsic Optical Property Set  
We need to incorporate the absorption and scattering coefficients into the RTE to account for light's attenuation as it travels through the water. Then, we use appropriate models or measurements to determine the absorption and scattering coefficients based on water properties and environmental conditions.
# A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection
## 4 Case Study  
The COVID-19 pandemic has brought a far-reaching global impact upon SC logistics, suppliers, and workforces especially in the manufacturing industries. As a result, there was a combination of typical and painful remedies against financial insolvency such as employee layoffs and budget cuts which finally ended up with bankruptcy [35]. However, Food and Agriculture Organization (FAO) [36] stated that the food manufacturing industry is slightly different from others because it works on the daily essential needs. In this case, factory closures have ramifications for the food manufacturing supply chain. If one of the factories closes, those who work there might lost their jobs and go hungry, whereas if the suppliers and manufacturers become infected, more people are at risk [37]. This demonstrates that the food manufacturing industry faces a variety of challenges, hence resilience is vital to be incorporated in the SC. Previously, the case company focused less on the element of resilience, resulting in the post-pandemic impact on its SC. Currently, the management level is shifting its main focus towards resilience in selecting suppliers to cope with the economic challenges. The proposed criteria and the new technique were applied in the case company to verify their effectiveness. This study presents a list of 7 resilience criteria to assess 10 suppliers' performances in improving the SC performance of the company. The most common criteria from previous supplier selection studies [3; 10; 11; 12; 13] were combined to form a new set of resilience criteria. In this case, six common resilience criteria have been discovered based on previous research. However, there was a lack of financial consideration which was experienced by the case company. Financial concern tends to be one of the important factors in selecting suppliers since financial issues are often the root cause of deteriorating supplier performance, and suppliers often try to hide it from customers and buyers. Therefore, financial stability was proposed as one of the resilience criteria for this case study.  
Table 5 shows the set of resilience criteria with their respective definitions to assess the suppliers.
# Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions
## 3 Results and Discussions
### Evaluation of Performance Metrics
#### 3.2.3 Regression for (ANN)  
Figure (a)a presents a series of scatterplots comparing the predicted outputs to the actual target values across training, validation, and test datasets, as well as the combined data collected from Lucia, Spain. Each scatterplot includes a best-fit line representing the predicted versus actual values, with the R correlation coefficient indicates the strength and direction of the linear relationship. For the training dataset, the correlation coefficient is R = 0.9744, demonstrating a strong correlation and indicating good model performance. The validation and test datasets have R values of 0.9712 and 0.9698, respectively, reflecting a slight decrease in prediction accuracy but still maintaining high performance. This minor decline could suggest some overfitting, where the model captures the training data very well but may not generalize perfectly to unseen data. The combined dataset yields an overall R value of 0.9733, confirming that the model performs reliably across different data subsets and supports its practical applicability. These results highlight the model's effectiveness in generalizing various locations and datasets.  
Figure (b)b illustrates the performance of the predictive model across different FUMEM datasets: training, validation, test, and the combined set (all data). The training plot shows a regression line aligned with the identity line (Y = T), with an R\({}^{2}\) of 1, indicating perfect agreement between predicted and actual values. The validation plot, shown in green, also has an R\({}^{2}\) of 1, demonstrating the model's high accuracy on validation data. Similarly, the test plot, depicted in red, exhibits an R\({}^{2}\) of 1, confirming that the model can accurately predict outcomes on unseen data. Overall, these plots underscore the model's exceptional predictive capability across all datasets.
# Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System
## 3 PM-DQPSK System and Simulation Results
### Simulation Results
\begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Value** \\ \hline Coding lengths & 576/1152/2304 \\ Coding rate & 1/2 \\ Number of encodings & 800/400/200 \\ Maximum number of iterations & 5/10/15/20 \\ \hline \end{tabular}
\end{table} 
Table 2: LDPC parameter settings. The constellation changes in the polarization states of the PM-DQPSK signal during the distortion compensation process are illustrated in Figure 4. Specifically, Figure 4a,b illustrate the constellation diagrams of the X and Y polarizations, respectively, without any digital signal processing applied at the receiving end of the system. Subsequently, after undergoing damage compensation treatment, although some improvements in the constellation diagrams of the X and Y polarizations can be observed in Figure 4c,d, the constellation diagrams still have a certain degree of distortion, indicating that further optimization may be required to achieve satisfactory performance. Figure 4: The constellations of X and Y polarization when OSNR = 15 dB: (**a,b**) receiver-received signal; (**c,d**) compensated but without LDPC. Figure 3: BER curve of the system with different maximum number of iterations. By comparing the BER of the PM-DQPSK signal with and without the implementation of LDPC, the effectiveness of LDPC in reducing errors and enhancing the quality of the received signal can be evaluated. This comparative analysis provides valuable, significant results regarding the impact of LDPC on error reduction and signal quality improvement in the PM-DQPSK communication system. Figure 5 demonstrates the BER plotted against different OSNR for a code rate of 1/2 and code lengths of 576, 1152, and 2304, each with 20 iterations. The results illustrate that incorporating LDPC significantly enhances the performance of the PM-DQPSK system across different OSNR values and code lengths. The LDPC coding gain is observed to approach approximately 4.3 dB, 5.1 dB, and 6 dB when the OSNR is 15 dB for code lengths of 576, 1152, and 2304. This indicates the improvement in signal quality achieved by LDPC coding under these conditions. Respectively, the BER is reduced by nearly three orders of magnitude when the OSNR is 17.2 dB. These findings underscore the remarkable effectiveness of LDPC in improving the reliability of the PM-DQPSK system, particularly in scenarios with challenging noise conditions.
## 3 Results and Discussion  
### Performance of a Series Samples  
Figure 2 shows the performance of the adsorbents at different Co/Fe mass ratios in O\({}_{2}\)-containing flue gas at a temperature ranging between 60 and 180 \({}^{\circ}\)C. The pure ZSM-5 sample exhibited a relatively low level of efficiency in Hg\({}^{0}\) removal. Given the modification to CoO\({}_{x}\) or FeO\({}_{x}\), there was an obvious improvement detected in the efficiency of Hg\({}^{0}\) removal. The mercury removal efficiency of Co\({}_{x}\)Fe\({}_{1}\)-ZSM-5 sorbents was enhanced with the increase of Co mass ratio. Compared with other samples, Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 and Co-ZSM-5 achieved a satisfactory performance in mercury removal. Hg\({}^{0}\) removal efficiency reached up to around 96%. In order to identify the variation in performance between Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 and Co-ZSM-5, the theoretical capacity of Hg\({}^{0}\) adsorption by these samples was calculated (Figure S1). It was found out that Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 performed better in Hg\({}^{0}\) removal, as evidenced by the higher theoretical capacity of Hg\({}^{0}\) adsorption. According to these results, there must be a significant synergistic effect at play between cobalt oxides and iron oxide, thus promoting mercury removal. Moreover, Co\({}_{4}\)Fe\({}_{1}\)-ZSM-5 is applicable as an optimal sample for further experimentation. The theoretical capacity of Hg\({}^{0}\) capture by Fe-ZSM-5 is extremely low, which is consistent with the result of Hg\({}^{0}\) removal efficiency, as shown in Figure 2a. Additionally, it is worth noting that the Hg\({}^{0}\) removal efficiency profiles of Co\({}_{x}\)Fe\({}_{1}\)-ZSM-5 resemble a volcano, which is attributable to the increasingly active reactant with the rise of temperature and the desorption of mercury species from the adsorbent  
surfaces at an excessively high reaction temperature [33; 35]. Compared with the reported adsorbents (Table S1), it seems that Co\({}_{4}\)Fe\({}_{1}\)ZSM-5 can be a potential adsorbent for the practical application.
###### Abstract  
An array antenna for millimeter-wave communication and an array antenna for millimeter-wave sensing are designed and put together into one structure. Because millimeter-wave signals become weaker fast with the increasing distance and any kind of error in the required functions of the antenna has to be minimized, pointing error from the target direction should be prevented. The device is a millimeter-wave sensing antenna with high directivity to check the straight link between the TX and RX sides of wireless communication. A 24 GHz 8-by-16 array antenna which generates stronger signals for sensing resolves the drawback of a 28 GHz 1-by-4 array antenna that is commonly seen in 5G wireless terminals. The sensing and communication antennas are integrated as a planar structure mountable on platforms, which is investigated with regard to forming wireless links over a distance of several meters with an input power of less than 0 dBm. Additionally, in the event of a reflecting surface disturbing the straight path and worsening the pointing error in RF signal transfer, the dual-capability of the combination is presented on the basis of intuitive electromagnetic experiments.  
array antenna; millimeter-wave; signal strength; radio sensor; reflecting surface; transmission and reflection +
Footnote †: journal: Sensors  
0000-0001-5891-5800][PERSON]  
1 Department of Information & Telecommunication Engineering, Incheon National University, Incheon 20212, Republic of Korea; [EMAIL_ADDRESS] (J.K.); p0306 [EMAIL_ADDRESS] (H.P.); [EMAIL_ADDRESS] (W.K.); [EMAIL_ADDRESS] (S.S)