esa-sceva/satcom-chunk-collection huggingface dataset:
# Adaptive Cruise Control for Eco-Driving Based on Model Predictive Control Algorithm
## 4 Conclusions  
In this study, an adaptive cruise control system is designed, based on the framework of model predictive control to optimize multiple objectives, including car-following, driving safety, comfortability, as well as the eco-driving. The vehicle dynamic model, the adaptive cruise control model, model predictive control framework, and instantaneous emission and fuel consumption model are proposed and analyzed. The performance of the proposed MPC-based ACC system is compared with the classic PID-based ACC system. Based on the above models, the simulation experiments are conducted in two typical and representative driving scenarios. The simulation results show that the new MPC-based ACC system performs as well as the classic PID-based ACC system, in terms of car following  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **HC(g/km)** & **CO(g/km)** & **CO\({}_{2}\)(g/km)** & **NO\({}_{\mathbf{\chi}}\)(g/km)** \\ \hline PID-based ACC & 1.41 & 4.65 & 364.83 & 3.26 \\ MPC-based ACC & 1.15 & 3.86 & 308.81 & 2.88 \\ Improvement (\%) & 18.70 & 16.99 & 15.35 & 11.65 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Emissions results in Scenario 2.  
capability and driving safety. What is noteworthy is that the MPC-based ACC system achieves an improvement of 12-13% in fuel economy, in comparison with the classic PID-based ACC system. Furthermore, the driving comfortability is optimized by the proposed new ACC system. A prospective situation is that the proposed MPC-based ACC system will encourage more users to accept the adaptive cruise control system, as a result of better driving comfortability and fuel economy, and this research can lay the groundwork for developing a more intelligent autopilot system.  
Conceptualization: Z.N. and H.F., methodology, and investigation: Z.N., Writing--review, editing, and supervising: H.F. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Kurata grant of the Hitachi Global Foundation.  
The author wishes to thank the editor and the reviewers for their contributions on the paper.  
The author declares no conflict of interest.
## 2 Methodology
### Processing Time of the Hyperspectral Cube  
The hyperspectral cube was created by processing the raw images in the Cube creator. The altitude of the sensor and image overlap percentage has the same weightage in influencing the number of raw images to be acquired by the hyperspectral imaging system. The forward overlap has an exponential impact on the processing time of the raw image and creation of hyperspectral cube. In Figure 9, a significant increase in processing time from 70% overlap is visible. While, 40 cm altitude has a higher processing time than 150 cm. The resolution of the sensor has linear influence on processing time. From the observed results it can be concluded that processing time is highly dependent on number of raw images as compared to sensor resolution.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Altitude (cm)** & **Speed (cm/s)** & **No. of Images** & **Storage (GB)** & **Flight Time (min)** \\ \hline
40 & 10.5 & 1728 & 21.25 & 26 \\
60 & 10.5 & 768 & 9.45 & 17 \\
90 & 10.5 & 285 & 3.5 & 11 \\
120 & 10.5 & 195 & 2.2 & 10 \\
150 & 10.5 & 130 & 1.6 & 8 \\ \hline \end{tabular}
\end{table}
Table 5: Determining number of images, storage and flight time at 10.5 cm/s.  
Figure 8: Minimum, suggested, and maximum speed for different altitude.  
Figure 9: (**a**) Acquisition time for different altitude at 70% image overlap; (**b**) Image processing time in minutes for different overlap percentage at 40 cm, 90 cm, 150 cm, respectively.
## 4 System Design and Goals
### Modification to Message Intervals and New Message Variables
#### 4.4.1 DSI Function  
This module retrieves the addresses of all network interfaces on a D2D communication node and saves them to the OLSRv2 Local Set. It uses the _IsD2D_ variable to determine if the address was assigned by OLSR. Nodes that responded to HELLO messages with a HI message and have not broadcasted a HELLO message can broadcast their HELLO messages once interface data are written to the Local Set--only if EH = 1. The procedure for the DSI is explained in Algorithm 1. This algorithm is designed to manage the state transitions of nodes in a D2D communication network, particularly focusing on the \"DB_SELF\" state. The goal is to optimize routing performance by ensuring that each node efficiently updates and maintains its routing information based on its interactions with neighboring nodes. The \"DB_SELF INTERVAL\" is a critical parameter that defines how frequently a node checks for incoming HELLO messages and updates its state. The interval is set based on the network's dynamics, such as node mobility and topology changes, to ensure timely updates without causing unnecessary overhead.  
```
1.\(DSIModule\) ( )
2. For \(\forall\) Address \(\in\) IPAAddress[ ] do:
3. IsD2D \(\leftarrow\)\(\left\{\begin{array}{ll}1&if\ GetType(A)\gets D2D\\ 0&otherwise\end{array}\right.\)
4. if IsD2D \(\leftarrow\)\(\left\{\begin{array}{ll}1&if\ GetType(A)\gets D2D\\ 0&otherwise\end{array}\right.\)
5. \(\text{OLSRAddr}=\text{Address}\)
6. SaveRecord(Address,IsManet, Local)
7. End For
8. DSLTimer.Enable \(\leftarrow\)\(0\)
9.\(if\ EH\gets 1\), then:
10. BroadcastMessage(\"HELLO\",OLSRAddr)
11. LI.Timer.Enable \(\leftarrow\) True
```  
**Algorithm 1**DSI Function
# Review on the Role of GNSS Meteorology in Monitoring Water Vapor for Atmospheric Physics
## 6 Conclusions
The following abbreviations are used in this manuscript:  
AIRS Atmospheric Infrared sounder  
AMSU-B Advanced Microwave Sounding Unit  
APC Antenna Phase Center  
AR atmospheric river  
BALTEX Baltic Sea Experiment  
BDS BeiDou Navigation Satellite System (Chinese GNSS)  
CORS Continuously Operating Reference Stations  
COST Cooperation in Science and Technology  
ECMWF European Centre for Medium-Range Weather Forecasts  
FTIR Fourier-transform infrared spectroscopy  
FY3-A/MERSI Fengyun-3A Medium resolution spectral imager  
GASP Atmosphere Sounding Project  
GLONASS Globalnaya navigationsnaya sputnikovaya sistema (Russian GNSS)  
GNSS Global Navigation Satellite Systems  
GOME-2 Global Ozone Monitoring Experiment 2
## 4 Results and Discussion  
### Comparison of TDM-1 and TDM-2  
Two test methods, TDM-1 and TDM-2, were used on three polymeric materials with varying acoustic impedance. These were PMMA, polycarbonate (PC), and polyvinylchloride (PVC), as these had large values of transmission coefficient, T\({}_{\rm c}\) (PMMA: 10.4 dB, PC: 12.2 dB, PVC: 10.6 dB). These tests were conducted to determine values of transmission coefficient corrections (TCC) needed to adjust  
Figure 8: (**a**) Waveforms of direct contact tests (voltage output, V\({}_{1}\)). V1030 to V111 (blue); V111 to V1030 (red); C16 to V111 (green). (**b**) Corresponding frequency spectra (R\({}_{1}\) of Equation (14a)). Color code the same as in (**a**). the attenuation coefficients from TDM-2 in-line with those from TDM-1, which are independent of transmission coefficient, T\({}_{\rm c}\). Figure 9a illustrates results of the two methods for PMMA samples with x\({}_{1}\) = 9.0 mm and x\({}_{2}\) = 45.6 mm. The thick sample was made from the same 9.0 mm plate as the thin sample, using epoxy glue measuring approximately 40 \(\upmu\)m per adhesive layer. The blue, brown, and red curves represent R\({}_{1}\), R\({}_{2}\), and R\({}_{3}\) FFT spectra, respectively, corresponding to the outputs of direct contact, and with thin and thick samples. The difference between R\({}_{1}\) and R\({}_{3}\) is given by the blue dotted curve, and the brown dotted curve shows diffraction correction D\({}_{2}\) for the thick sample. Note that these two were close to each other below 1 MHz, where attenuation was low (for some transducer pairs of larger or smaller radii, differences were larger, indicating that a = 6.35 mm is an appropriate choice.) Purple and green curves show attenuation results for TDM-1 and TDM-2 for the propagation distances of (x\({}_{2}-\)x\({}_{1}\)) for TDM-1 and of x\({}_{2}\) for TDM-2. For the TDM-2 data, a T\({}_{\rm c}\) value of 10.4 dB was included in the computation of Equation (17c). In both cases, diffraction correction was applied according to Equation (15). Linear regression fits for these curves are plotted by purple and green dotted lines. When the slopes of the linear equations are normalized by propagation distance, \(\alpha\) values are obtained with Equation (2) using C\({}_{\rm d}\), measured in dB/m/MHz, as follows (also in Table 1):  
Figure 9: **(a)** Fast Fourier transform (FFT) outputs (blue, R\({}_{1}\); brown, R\({}_{2}\); red, R\({}_{3}\)) for PMMA; x\({}_{1}\) = 9.0 mm and x\({}_{2}\) = 45.6 mm. Blue dotted curve: R\({}_{1}\)-R\({}_{2}\); brown dotted curve: D\({}_{2}\); purple curve: \(\alpha\) for transmission difference method 1 (TDM-1); green curve: \(\alpha\) for transmission difference method 2 (TDM-2). Purple and green dotted lines are linear regression fits for purple and green curves, respectively. **(b)** As in **(a)**, but using two PMMA plates stocks; x\({}_{1}\) = 9.0 mm and x\({}_{2}\) = 43.2 mm; \(\alpha\) values require normalization with thickness differences for direct comparison.
# Retrofit of Existing Reinforced Concrete (RC) Buildings: Steel vs. RC Exoskeletons
## 2 Case Study Building
### Retrofit Strategy for the Existing Building  
Generally, for the retrofit of existing RC buildings, two different intervention strategies aimed at improving structural safety indices can be efficiently developed. These strategies include (i) increasing displacement capacity or (ii) reducing displacement demand [23; 31].  
In this contribution, the retrofit strategy was focused on reducing the earthquake-induced displacement demand within the capacity limits of the existing structure through the application of two types of exoskeletons, one composed of steel and one of RC. In detail, both the steel and RC exoskeleton systems were designed to reduce the seismic demand of the existing structure to a minimum.  
It is important to point out that the two solutions compared to each other in this paper were actually proposed by the Technical Office of the University.  
The architects contemplated:  
* From an energy point of view, the elimination of thermal bridges and the renewal of outdated technological systems;
* From an architectural point of view, the conferment of a greater architectural value and a better distribution of accommodation that meets current housing standards;
* From a structural point of view, improvement in the seismic capacity of the original RC building.  
In light of these objectives, two alternative solutions of retrofitting were specifically studied, namely:  
* The construction of a steel exoskeleton to make evident and keep clear the difference between the existing RC building and the new constructional system for retrofit;
* A second option envisaging the construction of new RC frames in continuity with the existing structure, so as to minimize and possibly hide the differences between the existing RC building and the new retrofitted parts.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Push-Over** & \(F_{max}\) & \(\Gamma\) & \(F_{max}^{*}\) & \(\alpha_{u}\)/\(\alpha_{1}\) & S\({}_{e}\)(\(T^{*}\)) & \(q^{*}\) & \(C\) & \(D\
## 4 Nanostructured Materials for Uranium Removal
### Application of a Novel Graphene Oxide-Activated Carbon Felt Composite for U(VI) Removal
The adsorption of UO\({}_{2}\)\({}^{2+}\) ions depends upon the uranium species distribution in solution, which mostly depends on the respective pH value. Uranium can be hydrolyzed into different mononuclear and polynuclear hydrolysis products in the form of (UO\({}_{2}\))\({}_{\rm m}\)(OH)\({}_{\rm n}\)]\({}^{\rm[2m-n)+}\)[82]. As the pH value is lower than 4, the UO\({}_{2}\)\({}^{2+}\) ions exist predominantly in the aqueous solution as the monomeric species. However, with the increase of pH, the hydrolysis of U(VI) ions will occur. Both materials achieved their maximum sorption capacity at the pH value 5.5. Application of a Novel Graphene Oxide-Immobilized Saccharomyces Cerevisiae Gel Beads for U(VI) Removal  
According to a recent study by [PERSON] and [PERSON] (2016) [83], the waste biomass of Saccharomyces cerevisiae was immobilized using several agents, including Ca-alginate (Ca-SA), Ca-alginate plus graphene oxide (Ca-SA-GO), or in combination with polyvinyl alcohol (PVA, 5% or 10%, _w/v_), i.e., PVA-Ca-SA-GO, using a CaCl\({}_{2}\)-boric acid solution, in order to evaluate their ability to adsorb dissolved U(VI). The obtained experimental results showed that graphene oxide at 0.01% (_w/v_) could enhance the performance of immobilized cells. The yeast gel beads, prepared with 5% PVA, 1% SA, 2% yeast, 0.01% GO, 2% CaCl\({}_{2}\) and saturated boric acid, generally showed better physical-chemical properties, such as higher tolerance, when unfavorable environmental conditions were applied. Moreover, the gel beads exhibited more stable capacity for U(VI) sorption and desorption at various conditions, such as pH in the range of 3-9. The effects of initial pH at acidic (pH = 3), neutral (pH = 7) and alkaline conditions (pH = 9) on U(VI) adsorption were studied and the results suggested that the optimum pH value for U(VI) adsorption is between 2.6 and 5. The immobilized _Saccharomyces cerevisiae_ biomass, using SA, PVA and/or GO substrate materials, showed particular changes in the molecular vibration of functional groups, such as carboxyl, amide and hydroxyl groups, which may be involved in the U(VI) binding, when compared with the raw yeast biomass.
# The Influence of Interlock Loss between Rebar and Concrete on Bond Performance of RC Member
## 5 Analytical Case Study Assuming Lug Loss Due to Rebar Corrosion
### Analysis Cases
#### 5.1.1. Lug Height Loss  
As the corrosion of the rebar progresses, rebar lugs are gradually flattened. However, because the surface of the bar is uneven, the bar surface never becomes as smooth as round PC rods due to corrosion. The degree of lug interlocking is affected by the reduction of contact area between the lugs and the surrounding concrete. Thus, beams with different lug height were analyzed using the cases of 75% (LugH-75%), 50% (LugH-50%), and 25% (LugH-25%). The height of the lug in the sound case was 2.0 mm, which was the same as that of the threaded rebars used in the experiment.
# Effects of the Hybrid CRITIC-VIKOR Method on Product Aspect Ranking in Customer Reviews
## 3 Methodology  
The research design of this study is mainly based on the aspect extraction and ranking introduced in the study of [8], which is mainly based on subjective weighting of the criteria. The main contribution of this research is the deployment of objective weights on the ranking criteria in MCDM to allow the weighting process to be independent of the human weighting process. In particular, the CRITIC objective weighting method is integrated into the ranking domain of the product aspects to enhance the prioritization of extracted aspects in customer reviews.  
Figure 1 shows the complete design of the ranking method for the product aspects. The structure of the framework is categorized into aspect extraction/retrieval and aspect ranking/prioritization. In this research, the extraction approach by [46] was employed in the aspect extraction stage. In particular, sentiment analysis techniques were used to extract the candidate product aspects from customer reviews based on two main criteria. First, the candidate aspects should be opinion-driven and discussed frequently in customer reviews. Second, these aspects should be relevant to the product domain. Simultaneous with the aspect extraction stage, MCDM was utilized in the aspect ranking stage to rank the extracted aspects based on the evaluation criteria. A decision matrix \(\mathbf{D^{k}}\) was built to manage the extracted information from the customer reviews. Eventually, the decision matrix would contain the candidate product aspects that were extracted in the first stage and data on the numerical performance of these aspects according to the extraction criteria. Figure 2 presents the structure of the decision matrix. Once the decision matrix has been built, the numerical performance of the aspects should be normalized using vector normalization, as part of the VIKOR process, to be standard and comparable. After the normalization stage, the criteria weighting stage will be applied. In this research, the CRITIC method was used as part of the VIKOR approach to apply the weighting process, allowing the criteria weights to be determined mathematically, further eliminating the fuzziness of human judgments.
## 2 Materials and Methods
### Data Collection and Analysis
#### 2.2.2 Satellite Data
Since both satellites are sun-synchronous and have mid-morning overpass time, the pairs of observations are generally only minutes apart, and it can be inferred that no significant changes in land surface occur between the two observations, as demonstrated by [PERSON] (2017) [25]. The pixel values intersecting the sample point location were extracted for the blue, green, red, NIR, SWIR1, and SWIR2 bands for each platform-sensor pair. To remove any remaining undetected cloud or shadow, the blue band ratio between two sensors (MSI vs. OLI, MSI vs. ETM+, OLI vs. ETM+) was computed. Any data points exhibiting a ratio greater than 2 or less than 0.5 were excluded, on the assumption that these pixels were corresponding to areas that were cloud-free in one image but appeared brighter due to cloud presence or darker due to shadowing in the other image [25]. Following a procedure similar to that reported by [PERSON] et al. [39], all outlier values beyond four standard deviations were checked and removed (Table 3).
## 2 System Model and Conventional Precoding Schemes
### Modified Generalized Block Diagonalization
MGBD needs one more SVD operation to obtain the post-coder and the post-coder is used for forming first precoder of the MGBD. By using the effective channel matrix at the first precoder, the MGBD takes noise term into account. Therefore, the performance of the MGBD is better than the GBD. However, since the MGBD needs three SVD operations to form the final precoding matrix, the computational complexity at the base station is extremely high compared to RBD and GBD. In addition, since the residual IUI must be removed at the receiver, the computational complexity at the receiver is larger than the RBD.
# A Reinforcement Learning Approach to Speech Coding
## Appendix A DPCM and Tree Coding
### Tree Coding  
Based on the DPCM architecture, it is possible to formulate a delayed encoding approach wherein a DPCM system is used to generate current and future predictions, quantizer values, and reconstructed outputs for some lookahead number of samples, and thus, since the quantizer has a set of discrete levels, a tree structure is generated to the chosen depth. A distortion can be calculated for each path through the tree and the best path chosen, then that path is sent to the Decoder for reconstruction.  
However, the greatest impetus for tree coding came from a rate distortion theory motivation [2; 3], wherein the quantizer based tree could be replace with randomly populated trees and the number of symbols per branch, limited to one sample per branch by a scalar quantizer, could be greater than one, thus producing fractional rate trees and codes [39]. Early work in this area use time domain unweighted squared error as the fidelity criterion and nonadaptive predictors, so competitive speech coding was not achieved; however, later work incorporating adaptive algorithms, fractional rate trees, and perceptually weighted distortion measures did produce promising results [4]. While recent work on tree coding, motivated by greatly reducing complexity and achieving very low latency using simple predictive algorithms have produced good performance at higher average bit rates [6], research at much lower average rates have not achieved competitive performance compared to the block-based code excited CELP codec designs. The reinforcement learning method presented in this paper points a way forward.
# Efficient Support Vector Regression for Wideband DOA Estimation Using a Genetic Algorithm
## 3 The Proposed Method
### Optimization of SVR Parameters
#### 3.2.1 Initializing the Population  
The purpose of parameter optimization is to enhance the estimation performance by adjusting the parameter combinations of the SVR model. The first step in implementing the genetic algorithm is population initialization, which involves randomly sampling the parameter space to generate initial candidate solutions within the predefined range of values for parameters \(C\) and \(\gamma\). Each candidate solution is represented as a two-dimensional vector \([C_{i},\gamma_{i}]\), \((i\leq m)\), where \({}_{m}\) denotes the population size. The fitness of each parameter combination is evaluated via simulation experiments, and individuals meeting the criteria are added to the initial population set \(S\). The iterative process proceeds until the population size attains the predefined threshold, completing the construction of the initialization stage.
###### Abstract  
Wireless Sensor Networks (WSNs) have been widely deployed to monitor valuable objects. In these applications, the sensor node senses the existence of objects and transmitting data packets to the sink node (SN) in a multi hop fashion. The SN is a powerful node with high performance and is used to collect all the information sensed by the sensor nodes. Due to the open nature of the wireless medium, it is easy for an adversary to trace back along the routing path of the packets and get the location of the source node. Once adversaries have got the source node location, they can capture the monitored targets. Thus, it is important to protect the source node location privacy in WSNs. Many methods have been proposed to deal with this source location privacy protection problem, and most of them provide routing path diversity by using phantom node (PN) which is a fake source node used to entice the adversaries away from the actual source node. But in the existing schemes, the PN is determined by the source node via flooding, which not only consumes a lot of communication overhead, but also shortens the safety period of the source node. In view of the above problems, we propose two new grid-based source location privacy protection schemes in WSNs called grid-based single phantom node source location privacy protection scheme (SPS) and grid-based dual phantom node source location privacy protection scheme (DPS) in this paper. Different from the idea of determining the phantom node by the source node in the existing schemes, we propose to use powerful sink node to help the source node to determine the phantom node candidate set (PNCS), from which the source node randomly selects a phantom node acting as a fake source node. We evaluate our schemes through theoretical analysis and experiments. Experimental results show that compared with other schemes, our proposed schemes are more efficient and achieves higher security, as well as keeping lower total energy consumption. Our proposed schemes can protect the location privacy of the source node even in resource-constrained wireless network environments.  
wireless sensor network; privacy preservation; phantom node; random routing +
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