esa-sceva/satcom-chunk-collection huggingface dataset:
# An Overview of GIS-Based Assessment and Mapping of Mining-Induced Subsidence
## 5 Discussion
### Why Is Subsidence Risk Mapping Difficult?  
Clearly, the number of case studies on subsidence risk investigated in this study is small compared with that of subsidence susceptibility/hazard mapping studies. A prediction of the geohazard (including subsidence) risk is still a highly difficult task. This difficulty can be ascribed to several reasons.  
The first is because of difficulties associated with the analysis of the temporal probability of a subsidence event. As mentioned in Section 5.1, the probability of subsidence occurrence caused by underground cavities varies depending on the elapsed time after creation, and it is difficult to accurately determine the time of subsidence in rural areas. The second is because of the difficulties associated with the evaluation of subsidence vulnerability at risk. The vulnerability of an element at risk can be affected by the element's own characteristics (e.g., strength of the buildings) as well as the subsidence hazard. Hence, it is difficult to determine whether the degree of vulnerability is caused by a subsidence event or its own characteristics if a full investigation is not conducted. These aspects are similar to the difficulty of mapping landslide risk [52]. Third, the damaged area of mine subsidence may not be sufficiently wide. Compared with other geological disasters such as landslides, floods, and earthquakes, the influential ground area affected by mining activities is relatively small. For these reasons, the number of studies on subsidence risk mapping is considerably smaller than that of studies based on risk from other geological disasters.
# Coverage and Rate Analysis for Location-Aware Cross-Tier Cooperation in Two-Tier HetNets
## 4 Numerical Results
### Validation of Analysis  
In Figure 2, the overall coverage probability for the LA-CTC scheme was validated by Monte Carlo simulations via MATLAB on a square window of \(10\)\(\times\)\(10\) km\({}^{2}\). Each simulation result was averaged over \(10^{6}\) iterations. For each realization, the locations of both the BSs and the users were generated by independent PPPs, while the FBSs within the inner region of each MBS were removed or deactivated. Then, the specific serving BS set was selected for each user on the basis of the LA-CTC scheme in Equation (1). The performance (i.e., coverage probability) of each user at each BS (which can be seen for a typical user at the origin) was evaluated. Finally, the mean value of the coverage probability was calculated. The details of the simulation procedure in [42] can be referred to as a pedagogical treatment to enable reproducibility. It can be seen that the analytical results match reasonably well with the simulation results. Hence, the performance trend of the LA-CTC scheme could be well captured by the analytical results. The small gaps were mainly due to the approximation of assuming that the density of the FBSs in the vicinity of the outer region was not changed.
Future Internet_**2014**, \(6\), 155-170; doi:10.3390/fi6010155  
_future internet_  
**ISSN 1999-5903**  
www.mdpi.com/journal/futureinternet  
_Article_  
**A Novel DOA Estimation Algorithm Using Array**  
**Rotation Technique**  
**[PERSON] 1,*, [PERSON] 2, [PERSON] 3 and [PERSON] 4**  
Electronics and Information Engineering College, Shenyang Aerospace University, NO.137 Daoyi South Avenue, Daoyi Development District, Shenyang 110136, Liaoning, China  
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, China; E-Mail: [EMAIL_ADDRESS]  
Department of Information and Communication Systems, Hohai University, Changzhou 213022, Jiangsu, China; E-Mail: [EMAIL_ADDRESS]  
Instituto de Telecomunicacoes, University of Beira Interior, Covilha 6201-001, Portugal; E-Mail: [EMAIL_ADDRESS]  
Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-180-4003-3201; Fax: +86-24-8972-3750.  
_Received: 2 December 2013; in revised form: 10 February 2014 / Accepted: 26 February 2014 / Published: 17 March 2014_  
**Abstract:** The performance of traditional direction of arrival (DOA) estimation algorithm based on uniform circular array (UCA) is constrained by the array aperture. Furthermore, the array requires more antenna elements than targets, which will increase the size and weight of the device and cause higher energy loss. In order to solve these issues, a novel low energy algorithm utilizing array base-line rotation for multiple targets estimation is proposed. By rotating two elements and setting a fixed time delay, even the number of elements is selected to form a virtual UCA. Then, the received data of signals will be sampled at multiple positions, which improves the array elements utilization greatly. 2D-DOA estimation of the rotation array is accomplished via multiple signal classification (MUSIC) algorithms. Finally, the Cramer-Rao bound (CRB) is derived and simulation results verified the effectiveness of the proposed algorithm with high resolution and estimation accuracy performance. Besides, because of the significant reduction of array elements number, the array antennas system is much simpler and less complex than traditional array.  
keywords: direction of arrival (DOA) estimation; spatial spectrum estimation; multiple signal classification (MUSIC); array rotation +
Footnote †: journal: Journal of the American Statistical Association
## 4 Results and Analysis
### Climate Change since 1990 in the TRH Region
Precipitation declines occurred in the northern part of Xinghai, Maduo, Qumalai counties; Yushu, Nangqian counties in central TRH, and Banma, Dari, Juzhi counties in the southeastern TRH. During 2004-2012, the precipitation increase trend was more obvious than that in previous time periods, especially the precipitation increased most significantly in Chengduo-Qumalai-Zhiduo, with an average growth rate of 9-15 mm/year. Precipitation changes of each river basin showed that the precipitation tendency in the Yangtze River basin increased most significantly, with an of average 3.48 mm/year during 1990-2004 and 9.8 mm/year during 2004-2012. By contrast, the precipitation in the Yellow River basin raised slowly, merely 4.4 mm/year during 2004-2012. The change of temperature and precipitation directly resulted in the change of humidity conditions in the THR region. The humidity conditions were divided by the Tanggulashanxiang-Zhiduo-Qumalai-Maduo-Xinghai line, showing a semi-arid zone to the north of the line and a semi-humid zone to the south of the line. The _HI_ decreased gradually from southeast to northwest and reached the lowest value (lower than 0.3) in the northwest of Zhiduo. The average _HI_ was 0.5 in 1990-2004 and it increased to 0.6 in 2004-2012, increased by 0.06 and showed an upward trend and a shift of the dividing line towards the northwest in both the semi-humid and semi-arid zone areas (Figure 9). Figure 8: Spatial distribution of annual average precipitation trend rate in the TRH region. Figure 7: Spatial distribution of annual average temperature tendency rate in the TRH region. The spatial pattern of annual _HI_ change rate showed that during 1990-2004, the humidity tendency was slow, and the average change rate of annual _HI_ was only 0.025/10 years in the TRH region. Especially, the change rate was only \(-\)0.05/10 years to \(-\)0.05/10 years in most areas, and only Tanggulashanxiang, Zhiduo and parts of Zaduo in the southwest areas were higher than 0.05/10 years. During 2004-2012, the average annual _HI_ change rate was 0.121/10 years, showing a significant increase of humidification compared to the former period. However, the change of _HI_ showed great spatial heterogeneity. It presented a _HI_ that was higher than 0.1/10 years in Tanggulashanxiang, Zhiduo, Qumalai, Yushu and Chengduo but an obviously lower rate of \(-\)0.1/10 years in the eastern TRH regions (Figure 10).
## 4 Simulation Results
### Scenario One: Immediate Charging EVs  
In immediate charging, EVs start charging directly upon arrival without any attempt to schedule or organize their needs. Figure 6 shows the result of the uncoordinated charging scheme where 100 EVs were charged immediately after arriving at the parking lot. The peak power consumption was about 208 kW at 11.00 a.m. The charging load of the EVs coincided with the building's daily peak demand hours. Both the PV system and the ESS were not configured in this scenario. The result showed that the impact of EV charging on the building power consumption was very severe.
# Polarization-Discriminated RSOA-EAM for Colorless Transmitter in WDM-PON
## 1 Introduction
The upstream signal will be linearly amplified on its returning path in the same SOA, but with its gain greatly suppressed due to the polarization mismatch. This paper is organized as follows: In the next section, we present the proposed structure and explain its working principle. The influence of the polarization state is shown and the approach to obtain the optimum rotation angle is given in Section 3. We summarize this work in Section 4.
###### Abstract  
Agricultural activity has always been threatened by the presence of pests and diseases that prevent the proper development of crops and negatively affect the economy of farmers. One of these pests is Coffee Leaf Rust (CLR), which is a fungal epidemic disease that affects coffee trees and causes massive defoliation. As an example, this disease has been affecting coffee trees in Colombia (the third largest producer of coffee worldwide) since the 1980s, leading to devastating losses between 70% and 80% of the harvest. Failure to detect pathogens at an early stage can result in infestations that cause massive destruction of plantations and significantly damage the commercial value of the products. The most common way to detect this disease is by walking through the crop and performing a human visual inspection. As a result of this problem, different research studies have proven that technological methods can help to identify these pathogens. Our contribution is an experiment that includes a CLR development stage diagnostic model in the _Coffea arabica_, Caturra variety,scale crop through the technological integration of remote sensing (through drone capable multispectral cameras), wireless sensor networks (multisensor approach), and Deep Learning (DL) techniques. Our diagnostic model achieved an \(F_{1}\)-score of 0.775. The analysis of the results revealed a \(p\)-value of 0.231, which indicated that the difference between the disease diagnosis made employing a visual inspection and through the proposed technological integration was not statistically significant. The above shows that both methods were significantly similar to diagnose the disease.  
c cdfee leaf rust; machine learning; deep learning; remote sensing; Fourth Industrial Revolution; Agriculture 4.0 +
Footnote †: journal: Applied Sciences
## 1 Introduction
In this work, we go one step ahead on employing the CYGNSS coherent component for deriving reflectivity estimates, and correct from BSR and VOD effects. Then, we employ the converted Fresnel linear reflectivity coefficients from GYGNSS reflectivity estimates to derive SMC. This is possible for low incidence angles as it has been pointed out by [31; 45]. Under these conditions, our results show the potential capability of the inversion procedure and highlight the conditions for a correct assessment of SMC. In order to validate this approach, specific geographical areas are tested by means of existing SMAP SMC datasets. This manuscript is organized as follows: In Section 2, we firstly describe the different datasets involved in the SMC retrieving process and the geographical extent for the validation test. Then, our proposed reflectivity conversion method of CYGNSS DDMs to SMC is shown. In Section 3, the experiments and results are presented, and Sections 4 and 5 show the discussion, and conclusions and recommendations for future research.
# SDN-Based Congestion Control and Bandwidth Allocation Scheme in 5G Networks
## 3 System Design
### SDN-Based Congestion Detection  
We use the open source OpenDaylight controller as the controller of the OpenFlow protocol. The southbound interface of the OpenFlow protocol is connected to the OpenFlow switch, and the controller can obtain real-time network status, such as latency, packet loss rate, and available bandwidth. In the OpenDaylight controller, we integrated a congestion detection module to detect whether the link is congested. The architecture diagram of the SDN-based congestion detection module is shown in Figure 2.  
The congestion detection module acquires the bandwidth (BW), number of queued packets (P), and length of each queue (Qi, 0! i! < n) to determine if congestion is present by calculating the network adapter utilization and queuing rate. The network adapter utilization can be expressed as follows:  
\[\mathrm{NetcardRate}_{\mathrm{t}}=\frac{(\mathrm{S}^{\mathrm{t}}-\mathrm{S}^{ \mathrm{t}-\mathrm{At}})*\mathrm{MSS}*8}{\mathrm{BW}*\mathrm{At}} \tag{5}\]  
Figure 1: Deployment site of the BRF protocol.  
Figure 2: Architecture diagram of the SDN-based congestion detection module.  
The variable S represents the count of transmitted packets, MSS denotes the maximum length of a packet, and \(\Delta\)t signifies the duration of time elapsed.  
The queue rate can be expressed as  
\[\text{Qutilization}_{\text{t}}=\frac{\text{P}_{\text{t}}}{\sum_{i=0}^{n}\text{Q} _{i}} \tag{6}\]  
When either \(\text{NectcardRate}_{\text{t}}>\alpha\) or \(\text{Qutilization}_{\text{t}}>\beta\), the queue is deemed congested. Typically, the values of \(\alpha\) and \(\beta\) are 0.98 and 0.1, respectively. The congestion detection module is a very important module in the congestion control algorithm. Even if the most reasonable CC algorithm and bandwidth allocation scheme are set in the network, it is difficult to avoid the emergence of congestion because the network state is constantly changing, and there are constantly new flows joining the network. It is difficult to avoid short-term bursts of large traffic. The congestion detection module is responsible for discovering the network route congestion quickly, reducing the congestion degree, ensuring fairness between flows, and improving the service quality.  
The congestion detection module obtains the network status in real time through the network service module in the OpenDaylight controller. When a router is found to be congested, the congestion signal will be sent to the corresponding router to make the router enter the congestion reduction state. The corresponding congestion reduction algorithm will be introduced in detail in Section 3.3.
# A Component-Based Approach to Early Warning Systems: A Theoretical Model
## 3 Results
### Components of Early Warning Systems
The goal of the third component is to warn the public of an imminent threat with clear instructions for protection and appropriate action. At this stage, warnings and notifications should be communicated through sirens as well as SMS messages. Crisis event information should be conveyed as clearly and concisely as possible. Public messages must meet certain quality criteria--they must be truthful, timely, and comprehensive [47]. The information should precisely indicate the type of crisis event, the extent of the threat, the severity level, and the necessary actions to be taken. EWSs must be comprehensive. All three components should be integrated into a single system within the crisis management structure, ensuring access to up-to-date and relevant information required for decision-making and response. Real-time data sources, particularly sensors and remote sensing technologies, play a crucial role. While a significant amount of data infrastructure already exists, further development is necessary--especially in establishing measuring stations equipped with sensors to monitor parameters that trigger crisis events, as well as to measure their actual manifestations. Figure 1 presents a model of an EWS based on three components. For crisis management, receiving, analysing, and modelling these data are critical. Emphasis should be placed on a unified information system that not only displays all relevant information but also evaluates all the data using machine learning methods or artificial intelligence, with direct capabilities for issuing alerts and warnings.
# Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM +
Footnote †: The results of this paper have been presented in part at the Workshop on Smart Antennas (WSA) 2018.  
[PERSON]  
1 Optical and Quantum Laboratory, Huawei Munich Research Center, 80992 Munich, Germany;  
[EMAIL_ADDRESS]  
[PERSON]  
2 Institute for Communications Engineering, Technical University of Munich (TUM), 80333 Munich, Germany;  
[EMAIL_ADDRESS]  
[PERSON]  
2 The results of this paper have been presented in part at the Workshop on Smart Antennas (WSA) 2018.2018.  
Most works consider discrete alphabet signaling. Perhaps the simplest approach, called quantized linear precoding (QLP), applies a linear precoder followed by one low-resolution quantizer per antenna [8; 9; 10; 11; 12; 13; 14; 15]. Our focus is on zero forcing (ZF), and we use the acronyms LP-ZF and QLP-ZF, respectively, for unquantized ZF and the QLP version of ZF.  
More sophisticated approaches use optimization tools as in [3; 4]. For example, the papers [16; 17; 18] use convex relaxation methods; Refs. [19; 20; 21; 22; 23; 24; 25] apply coordinate-wise optimization; Refs. [26; 27; 28] develops a symbol-wise Maximum Safety Margin (MSM) precoder; Refs. [29; 30; 31; 32] use a branch-and-bound (BB) algorithm; Ref. [33] uses a majorization-minimization algorithm; Ref. [34] uses integer programming; and [35; 36] use neural networks (NNs). These references are collected in Table 1 together with the papers listed below on orthogonal frequency-division multiplexing (OFDM). As the table shows, most papers focus on single-carrier and flat fading channels.
## 4 Discussion
Linear mixed model analysis showed that conventional impressions resulted in more accurate absolute trueness than intraoral digital scans, even though intraoral digital scans showed more accurate trueness at several tooth positions using an independent two sample \(t\)-test. In addition, conventional impressions showed more accurate precision at every x, y, z coordinate except the x coordinate of #15C and z coordinate of #22C (\(p>0.05\)). Based on the results above, the second null hypothesis was also rejected. This finding is in agreement with that of the other studies evaluating the accuracy of complete-arch digital scans compared with conventional impressions. [PERSON] et al. evaluated the complete-arch impression accuracy of intraoral digital scans, and reported that the intraoral digital scan was less accurate than conventional impressions and showed a different pattern of deviations [27]. [PERSON] et al. evaluated the trueness and precision of complete-arch digital impressions using various intraoral scanners and reported that the conventional impression method was significantly more accurate than intraoral scanners [24]. A recent study also reported that digital scans using an intraoral scanner were less accurate than the conventional impression method on partial or full arches [22]. Previous studies have reported that digital impressions using intraoral scanners showed comparable accuracy with conventional impression methods on quadrant impressions [17; 18]. Group CI and ISO showed similar \(\Delta\)x, \(\Delta\)y and \(\Delta\)z raw data distributions in Figures 7 and 8, however, Group ISO resulted in a greater dispersion than Group CI. Therefore, it can be concluded that the accuracy of intraoral digital scans was still less accurate than conventional impressions for complete-arch impressions. The present study has some limitations. Coordinate measurements can be only applied to basic geometric shapes; therefore, it is not possible to apply this method to real dentitions. Further, it was difficult to find a general trend of each centroid's deviation direction, and this is due to the use of absolute values for trueness and precision. Instead of raw values, absolute values were chosen to prevent dilution of the amount of deviation. The current study used only one commercial intraoral scanner; different intraoral scanners could lead to different results. Even with the limitations above, this new method is very useful to compare the statistical significance of trueness and precision between impression methods, but not to measure the amount of trueness and precision. Simply, this new method favors qualitative rather than quantitative comparisons. Quantitative, as well as qualitative analyses, will be included in future studies.
## 2 Results and Discussion
### Immobilization Process  
The cell immobilization procedure is divided into two phases. Firstly, _P. acidilactici_ cells were collected by centrifuging the seed broth at 4 \({}^{\circ}\)C and distributed in a PBS buffer (20 mM, pH = 7.4), which aimed to remove the culture medium and limit further cellular growth and proliferation. Then 1 g of sterilized polyHIPE scaffold was placed in the above PBS dispersion of _P. acidilactici_, and shaken at 150 rpm at room temperature for cell immobilization, in which the cells were attached to the carrier of the porous scaffold. During this process, due to the high reactivity and plasticity of the epoxy group, which on GMA provided anchoring points for cells on the void wall and reacted directly with the -NH\({}_{2}\) group on the cell surface for covalent immobilization [45].  
The immobilized _P. acidilactici_ was characterized via SEM-EDS images. Before observation, the immobilized cells were treated using 2.5 wt.% glutaraldehyde as a fixative to freeze the cell morphology. The cells were subsequently dehydrated using an ethanol gradient before the cell-immobilized polyHIPE was freeze-dried. SEM-EDS images of the distribution of cells within the voids are shown in Figure 4a,d. Figure 4a shows that the cells were located on the void walls, which demonstrated that the _P. acidilactici_ was successfully  
Figure 3: Water wettability of PHI-1090 scaffold.  
Figure 2: Stress–strain curves (**a**) and Young’s modulus (**b**) of the varied polyHIPE scaffolds under compressive load.  
immobilized on the polyHIPE support. The successful immobilization of _P. acidilactici_ was further confirmed by the sulfur element EDS mapping as the sulfur element in sulfhydryl1 groups is only present in cells in this system (Figure 4d).  
The quantitative analysis of the immobilized _P. acidilactici_ was investigated by determining nitrogen contents with elemental analysis; the nitrogen mass fraction in the _P. acidilactici_ was maintained at 11.4 wt.%, which can be used as a reference standard to figure out the content of immobilized bacteria, which was calculated to 0.04 g/g (the immobilized efficiency was 75.3 wt.% compared to the cells wight before immobilization), which demonstrated the excellent characteristics of the polyHIPE on the immobilized cells. Since the cells are covalently immobilized on the PHI, the cells are firmly bound to the scaffold and not easily dislodged. In contrast to the cells adsorbed on the carrier [46], the initial cell amount on PHI can be kept constant. Moreover, as cells were immobilized on the carrier, the material's hydrophilicity rose, resulting in an increase in water wettability and permeability (Figure S3).