esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Cement Content on the Deformation Properties of Cemented Sand and Gravel Material
###### Abstract
performed triaxial tests to study the mechanical properties of polyurethane foam adhesive reinforced rockfill materials; [PERSON] et al. conducted an experimental study on the effect of aggregate gradation on dilatancy behavior and acoustic characteristics of cemented rockfill; the effect of fines on the mechanical properties of composite soil-stabilizer-stabilized gravel soil was analyzed by [PERSON] et al. ; [PERSON] et al. analyzed the effects of morphological parameters of natural sand on the mechanical properties of engineered cementitious composites; [PERSON] et al. performed a series of test studies to evaluate the potential impact of basalt fibers on the mechanical performance (compressive strength, flexural strength), fracture energy, and anti-shrinkage properties of cement-stabilized macadam; [PERSON] et al. conducted a comparative analysis between the conventional models in terms of evaluating mechanical properties of self-compacting and conventional concrete and developed new modulus of elasticity models, tensile strength models, and compressive stress-strain models for those materials; in addition, [PERSON] et al. investigated the compressive and splitting tensile strengths, modulus of elasticity and rupture, compressive stress-strain curve, and energy dissipated under compression at different curing ages for a control self-compacting concrete (SCC) mixture and three fiber-reinforced SCC containing steel, polypropylene, and hybrid (steel + polypropylene) fibers, and established their corresponding prediction models considering the effect of curing age. In these studies, only [PERSON] et al. and [PERSON] et al. qualitatively analyzed the effects of cement content and confining pressure on the deformation properties of cemented poorly graded sand-gravel mixtures, and polyurethane foam adhesive reinforced rockfill materials; however, they did not establish the quantitative expressions for quantitative indexes of these deformation properties [15; 16]. Therefore, in this study, triaxial shear tests on CSG material with cement contents of 20, 40, 60, 80, and 100 kg/m\({}^{3}\) are designed and conducted. According to the test results, some expressions are derived for the deformation characteristics for different cement contents, which can reveal the variation of deformation characteristics such as initial modulus, failure strains, peak volumetric strains, and their corresponding axial strains, based on the amount of cement content. The experimental study provides a theoretical basis for improving the accuracy of the strain-stress forecasting results of CSG material for applications in the CSG dam and other projects.
## 1 Introduction
In the same study, single-Doppler analysis wind retrievals were utilized to demonstrates the complementary role of space- and ground-based radar systems to obtain more accurate representation of the wind fields, as the latter depict wind features at a higher altitude than the scatterometer as a function of distance from the center of the radar. This study explores the degree to which scatterometer wind retrievals can detect outflow boundaries at varying spatial resolutions taking into account the trade-off between wind vectors at finer spatial scales and noise levels with increasing spatial resolution. Section 2 describes the satellite and ground-based data used, Section 3 describes the methods, Section 4 describes the results obtained from a case study and Section 5 presents a summary and discussion.
# Intelligent Total Transportation Management System for Future Smart Cities
## 3 Results--Examples of Sub-Model Developments
### Intelligent Total Transportation Managing System in Smart Cities
#### 3.3.1 Management of Non-Cooperating Vehicles  
The system collects available and measured data on the traffic conditions, vehicles, and weather conditions; such data are used as the primary input for surveillance. The non-cooperating vehicles are identified by sensors such as optical, infrared, ultrasonic, and radar built in the traffic infrastructure. These vehicles are then classified depending on their size and mass predicted performances and predictable goal trips. This information is used in a short time forecast of the traffic intensity and complexity, together with the information provided by the cooperating vehicles. Accordingly, the system evaluates and monitors where/which direction traffic will increase and where a traffic jam might appear, which supports even the drivers of the non-cooperating vehicles.
## 4 Discussion  
This study aimed to develop an individual-level prediction model for the wearing-off of anti-PD medicine using a readily available fitness tracker in a real-world environment. Our first goal was to collect and combine the related datasets needed for this study. Second, prediction models were built to predict the wearing-off period. Lastly, we analyzed the produced results to assess our primary goal. In response to our first research question, there were two main challenges in data collection and processing. First, various datasets from different tools were collected in different time intervals. There were some significant gaps without available data. Before re-sampling, the datasets were filled with values of \"\(-\)1\", based on Garmin's data handling protocol for stress scores. After re-sampling the datasets, the last known values were copied to missing values. It would be convenient to have a uniform interval rather than to re-sample the data for future studies. The use of smartwatches can also be beneficial to read and record raw sensor data, without sacrificing the comfort of the participants. Second, there were few wearing-off reports for participant 2. The sparsity and the low number of reports affected the performance of the prediction models. Participant 1 had sufficient reports, while participant 2 did not have very many reports. In this study, we have shown the feasibility of using a fitness tracker to predict the wearing-off phenomenon. Based on the feature importance from the models, the elapsed time since the last drug intake affected both participants' models regardless of the sampling interval. For participant 1, the stress score and heart rate were indicators of the wearing-off phenomenon. For both participants, the 15 min time frame produced better results than the 15 s time frame. The difference in the time frame affected the prediction model due to the presence of large amounts of missing data. In the future, the sampling interval can be optimized since the differences between the two time frames were substantial. In response to the second research question, our case study showed the possibility of utilizing the fitness tracker dataset to estimate wearing-off. The individual-level prediction models were built to personalize the estimation based on the participants' experiences of PD. It was highlighted in a previous study that each PD patient had varying degrees of symptoms [20]. In this study's analysis, the participants' heart rate, number of steps, and stress score were also shown have significant differences. Thus, this study was able to produce a prediction model with an accuracy of 70.0-71.7% for participant 1 and 76.1-76.9% for participant 2 with the use of a non-motor dataset, i.e., in contrast with the accelerometer and gyroscope datasets, which were based on motor functions (Table 17).
## 2 Sparse Representation  
Sparse representation, as an important means of signal analysis and processing, was first proposed by [PERSON] and Filed in 1996 [PERSON] in 1996 [PERSON] (1996). It was summarized from the strategy research of biological neural sensing systems and then gradually applied to the fields of signal processing, image analysis, and speech recognition. Its basic idea is to choose a library of redundant basis functions to construct an overcomplete dictionary, whose atoms are the basis functions of choice, according to the signal features. Then, the sparse decomposition algorithm is used to represent the original signal by linear combinations of as few atoms as possible, resulting in the most sparsely expressed form of the original signal, which makes it easier to obtain the features contained in the signal. The specific mathematical model is as follows:  
\[y=D\alpha+r \tag{1}\]  
where \(y\) represents the original signal, \(D\) is the over complete dictionary, \(\alpha\) is the sparse coefficient and \(r\) is the residual.  
Expand the dictionary \(D\) in the above formula according to the column, and each column is regarded as an atom. Suppose there are \(n\) atoms, and the atoms are represented by \(d\); then, Formula (1) can be equivalent to:  
\[y=\sum_{k=1}^{n}\alpha_{k}d_{k}+r \tag{2}\]  
where \(d_{k}\) represents the \(k\) atom in the dictionary.  
According to Formula (2), in order to obtain the most sparse expression of the signal, the number of atoms should be minimized, that is, the non-zero term of the coefficient \(\alpha_{k}\) in the formula should be minimized. Therefore, the above formula can be regarded as an optimization problem based on \(l_{0}\) norm [PERSON] (1996):  
\[(l_{0}):\ min=\|\alpha\|_{0}. \tag{3}\]
## 4 Technologies and Devices
### ZigBee  
ZigBee is a standard for wireless communication based on the IEEE 802.15.4 protocol. It is used to connect several devices together creating a mesh network with no central powerful device, but with distributed nodes able to transfer data throughout intermediate motes. Table 1 shows a comparison between the most famous technologies used as wireless communication. As the table shows, both Wi-Fi and the Bluetooth have higher bit rates than ZigBee, but the higher power consumption and the  
Figure 1: Block scheme of the system architecture.  
lower number of devices making up the network suggest that the ZigBee technology is the best candidate to create sensor networks for applications where the power consumption must be as low as possible. Furthermore, studies proved that the ZigBee is more affordable in terms of power consumption and costs than competitive technologies [3,18-20].  
The communication between the lamp posts in the isle has been achieved using the ZigBee standard. This uses a mesh topology with a coordinator, routers (also called primary) and end device nodes (also called secondary); the first controls the formation and security of networks, the second extend the range of networks while the last perform specific sensing or control functions. Each lamp post has a Tx/Rx to get or send information and control commands. Furthermore, the lamp posts closer to the roads, used to approach the intersection, are also connected to a presence sensor card. The secondary nodes will send their status to the coordinator lamp post throughout the mesh network and receive back commands. Thus, the power consumption is limited to short time frames, since there is no continuous communication between nodes.  
The networked communication is realized using the XBee radio modules by MaxStream which are already equipped with on-chip antenna [21-23]. These modules have been chosen because they have a good operational range for the application reaching tens of meters indoors and hundreds of meters outdoors. Thanks to its high radio sensitivity the XBee module has a low probability to receive corrupted packets (less than 1%). Furthermore the reported tests demonstrated that these performances are achieved without sacrificing power consumption. In fact, the current necessary to operate the two-way radio transmissio, is approximately 50 mA with a 3 V DC source. To ensure further power reduction, the sleep mode ensures a current draw of less than 10.
# Drivers, Barriers and Benefits of the EU Ecolabel in European Companies' Perception
## 2 EU Ecolabel Drivers, Benefits and Barriers: A Literature Review
### Drivers  
Ecolabelling schemes, whose primary function is that of being communication tools, aim to close the information gap between operators providing environmentally friendly products/services and consumers making purchasing choices on the market. Therefore, Ecolabels have a specific role in contributing to the overall awareness of the environmental impacts of products and services. The EVER study (2006) found that companies apply for the EU Ecolabel to take advantage of business opportunities offered by consumers' increased awareness of environmental issues, and to satisfy customers' specific requests for products and services with high environmental quality. Indeed, in a quantitative analysis carried out by [PERSON] et al. [2] to assess whether the EU Ecolabel can stimulate eco-friendly behavior, the authors show that Ecolabels in general play a significant role of \"guarantee\" for consumers and, consequently, are able to guide consumers' choices toward products and services with a higher environmental quality. Considering these initial considerations, it can be argued that one of the most powerful drivers for companies to choose the EU Ecolabel is the need to respond to external pressures coming from the \"demand side\", i.e., final consumers and  
Figure 1: Numbers of EU Ecolabel products and services.  
Figure 2: Numbers of EU Ecolabel Licences.  
intermediate customers, who ask for reliable and clear information on the products and services that are presented as \"green\". This argument is in line with most of the existing studies, which basically agree with the assumption that societal pressures and market requirements affect the decision of companies to invest in eco-innovation [3; 4; 5]. Ecolabels, in particular, aim at establishing a reliable and trustworthy information system on products' environmental qualities [6] and are used by companies as a marketing and communication tool targeting customers and consumers in order to increase market share. [PERSON] et al. [7] hold that companies introduce eco-innovative products and services into the market only when it is rewarding. Even considering that environmental product innovations might be costlier than non-environmental ones, companies may decide to accept lower short run profits in order to reach higher mid-term and long-term business goals. In fact, [PERSON] [8] refers to Ecolabels as market-based instruments aimed at internalizing environmental externalities through prices. In other words, the decision to use Ecolabels by the business sector is driven by the aspiration to extract a premium price on Ecolabelled products/services and to gain greater access to markets, including the opportunities offered by green public procurement policies.
## 2 Results and Discussion
### Sensory Evaluation  
The preliminary sensory evaluation was performed by non-trained testers (consumers) to evaluate the produced NFP and FP in terms of the juices' fruity, sour, astringent, bitter, alcoholic, sweet, and fresh qualities, and overall acceptability in comparison with commercial pomegranate juice. In general, all pomegranate beverages were accepted by the consumers as illustrated in Figure 2. It is noteworthy that the commercial pomegranate juice received higher scores for sourness, bitterness, and astringency compared to NFP and FP. Pomegranate juice is usually characterized by an astringent mouthfeel as well as earthy notes, which can lead to a sour and bitter essence [31]. As a result, these attributes can hinder consumer acceptance. On the other hand, both non-fermented (NFP) and fermented (FP) pomegranate beverages were characterized as sweeter with a slight alcoholic sense while FP retrieved the lowest scores for bitterness, sourness, and astringency. In addition, panelists scored the FP significantly better compared to NFP regarding overall acceptance. These results are in accordance with previous studies that had correlated the volatile compound composition of fermented and non-fermented pomegranate juices and found that the fermented juice provided an enhanced volatile composition and received higher evaluation scores compared to non-fermented juices [13]. As a result, it is highlighted that lactic acid fermentation promotes flavour attributes in fermented pomegranate beverages.  
Figure 1: Total phenolics content (mg GAE/100 mL) and antioxidant activity (mg TE/100 mL) of non-fermented (NFP) and fermented with _Lactobacillus puncasei_ K5 (FP) pomegranate beverages during the first 24 h (30 \({}^{\circ}\)C) and during refrigerated storage (4 \({}^{\circ}\)C) for 4 weeks.
## 2 Literature Review
### Sentiment Analysis  
Sentiment analysis, also known as opinion mining, aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text [32]. It encompasses the methodologies of collecting, processing, analyzing, summarizing, and interpreting texts laden with subjective and emotional content. As a vital subset of data mining, sentiment analysis is extensively utilized in various domains, notably in analyzing public opinion [33].  
Sentiment analysis techniques have been successfully applied across various disciplines, proving effective in capturing public sentiments. For instance, text mining has been employed to analyze Twitter data, enhancing public services by gaining insights into the attitudes and sentiments towards public sector enterprises in Bogota [34].  
Sentiment analysis methodologies vary significantly and can be categorized according to the techniques employed. These include sentiment dictionary-based approaches [31], traditional machine learning-based methods [35], and deep learning-based sentiment analysis techniques [36].  
Since the Weibo posts we are studying are related to the theme of common prosperity, and the keywords used in posts under this theme are mainly words used in daily life, the sentiment analysis method based on sentiment dictionary can meet our research needs.
# Delay-Tolerance-Based Mobile Data Offloading Using Deep Reinforcement Learning
## 3 Evaluation and Discussion
### Performance Comparison
In reinforcement learning, the reward function is an important factor for evaluating the action. In this paper, we applied only suppression of eNB load within \(L_{iall}\) as the reward function. We can expect that the performance will be further improved on examining the reward function.
## 3 Results and Discussion
### Discussion
#### 3.3.1 Focus on an Area Where the Camera Aiding Algorithm Improves the PVT  
Figure 7 evidences the HPE improvement around time stamp 850. In this area, the mean error without the camera is around 8 m while it is less than 4 m when the camera is used.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Camera Module**} & \multicolumn{3}{c}{**HPE**} & \multicolumn{3}{c}{**HPL**} \\ \cline{2-7}  & **67\%** & **95\%** & **99\%** & **67\%** & **95\%** & **99\%** & **MI** \\ \hline OFF & 4.27 & 8.79 & 12.17 & 31.71 & 41.56 & 58.45 & 0 \\ \hline ON & 3.85 & 6.59 & 10.14 & 36.64 & 47.62 & 78.28 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: HPE, HPL and MI with a Kalman filter and proposed camera-based aiding algorithm.  
Figure 6: HPE for the whole track—1800s.  
The proposed experimental setting (shown in Figure 5) enables us to correlate the HPE with HPL, HDOP and the number of satellites used in the PVT. It can be observed on the upper panel in Figure 8 that the HPE improvement is associated with the HPL increase. The PL increase is due to satellite exclusions and HDOP increases.  
Figure 8: HPL (**a**) and HDOP (**b**) around timestamp 850.  
Figure 7: HPE zoomed around timestamp 850.  
However, due to the Kalman filtering effect, the HDOP fluctuations are neither totally nor instantaneously reported on the HPL fluctuations. On the contrary, it can be checked that satellite exclusions do instantaneously impact the HDOP. At timestamp 861, only one satellite is excluded, as can be observed in Figure 9. Compared to the case in which the camera was not used, this leads to an increase of HDOP and consequently to an increase of HPL (see Figure 8). However, this also leads to an improvement in accuracy (see Figure 7) by more than 8.5 m.  
Figure 9 represents the physical context at timestamp 861. On one side of the road, a high building can be seen, and on the other side, trees are observed. Figure 9 confirms that only one satellite (ID 228, i.e., GPS 28) is to be excluded as it is masked by the building. Finally, Figure 10 illustrates the pseudorange residuals, the Carrier to Noise ratio (C/N\({}_{0}\)) and pLoS for the GPS PRN 28. Focusing around timestamp 861, it can be confirmed that the C/N\({}_{0}\) is strong enough to track the satellite; however, the measurements are biased by around 32 m. In this case, the camera exclusion significantly improves the HPE and the DOP degradation is weak.  
Figure 10: Pseudorange residuals, C/N\({}_{0}\) and LoS probability on SVID GPS 28.  
Figure 9: LoS MAP and video at timestamp 861.  
A few seconds later, a street lamp pole \"hides\" the satellite 213 and thus it is declared as NLoS and is excluded from the PVT. Nevertheless, although not illustrated here, the GNSS data were perfectly valid for this timestamp (pseudorange are not biased and C/N\({}_{0}\) very good). This corresponds to a typical case where the camera exclusion should not be trusted.
# A Vision-Based Bolt Looseness Detection Method for a Multi-Bolt Connection
## 3 Experimental Section  
### Experiment Setup  
The lab-test experiment was conducted to evidence the effectiveness and performance of the method. As shown in Figure 4, the laser emitted from the semiconductor lasers passed through the beam lifter and was expanded by the spatial filter; then, it irradiated the disk surface to form laser speckles. After being reflected on the surface of the disk, the laser speckle passed through polarizer 1, the Rochon prism, and polarizer 2; was captured by the CCD; and was finally transmitted to the computer.  
The aluminum disk, with a diameter of 20 mm and a thickness of 2 mm, was assembled using four M6 bolts on the bracket. In Figure 5a, the front view of the disk and bolts is depicted, and these bolts are labeled as B1, B2, B3, and B4, respectively. It is worth noting that the shooting area of the CCD is outlined by the red square in Figure 5a. This illustrates that the method can even detect unseen bolts in the multi-bolt connections, making it applicable for connections in complex structures in which occlusion often occurs.  
The reciprocating actuator applies a load (pressure) at the center of the back of the disk, causing it to wrap, as shown in Figure 5b. The varying amount of deformation results in a series of distinct speckle fringe patterns.  
For the rigid multi-bolt connection in this experiment, we simplify each bolt to have one of two states: fully tightened and fully loosened. As a result, there are 16 (24) looseness cases in total, as illustrated in Table 1 (where \"\(\bigcirc\)\" represents \"Loose\" and \"\(\times\)\" represents \"Tight\"). For example, case 9 indicates that bolts B2 and B3 are loose, but B1 and B4 are tight.  
Figure 4: Optical path diagram of the DSSPI system.