esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
## 3 Results
### Accuracy Analysis of NmrF2  
#### 3.2.1 Comparison with Ionosonde Data  
Due to the missing nighttime data of ionosonde, only daily 00:00 to 09:00 UT is used for comparison in this paper. Figures 7 and 8 show the comparison of NmF2 observed by ionosonde and the output from IRI-2016 and upda-IRI-2016 driven by IG12 and IG-up, respectively, at the Wuhan and Beijing stations from 00:00 to 09:00 UT in 2015 and January 2019, respectively. The black dots indicate the NmF2 observed by ionosonde and the green asterisks and red plus signs indicate the NmF2 output from IRI-2016 and upda-IRI-2016 driven by IG12 and IG-up, respectively. As can be seen from Figure 7, the difference between NmF2 output by upda-IRI-2016 and NmF2 observed by ionosonde at the Wuhan station is significantly smaller in 2015 compared to IRI-2016. According to Figure 8, the performance of upda-IRI-2016 is better than that of IRI-2016 in both the Wuhan and Beijing stations in 2019. Compared with IRI-2016, the NmF2 output by upda-IRI-2016 is obviously closer to that observed by ionosonde, and this advantage is more obvious in the Wuhan station than in the Beijing station. Combining Figures 7 and 8, it can be observed that the performance of upda-IRI-2016 in calculating NmF2 is better than that of IRI-2016 using the ionosonde data as a reference, and this advantage is more significant in the low solar activity year (2019) and low-latitude stations (Wuhan station).  
improvement of the MAE of NmF2 output from upda-IRI-2016 is 15.8% and 45.3% at the Beijing and Wuhan stations, respectively. In 2019, the MAE of NmF2 output from IRI-2016 was 0.0617 \(\times\) 10\({}^{12}\) el/m\({}^{3}\) and 0.097 \(\times\) 10\({}^{12}\) el/m\({}^{3}\) at the Beijing and Wuhan stations, respectively, which corresponded to 0.438 \(\times\) 10\({}^{12}\) el/m\({}^{3}\) and 0.0487 \(\times\) 10\({}^{12}\) el/m\({}^{3}\) for upda-IRI-2016. Compared with IRI-2016, the precision improvement of the MAE of NmF2 output from upda-IRI-2016 is 29.0% and 49.0% at the Beijing and Wuhan stations, respectively.  
In Figures 7 and 8, especially for the Beijing station, there are some upda-IRI-2016 performances that are poorer compared to the ionosonde observation NmF2 used as a reference, and a small number of these occur in Figures 2 and 3, which this paper conjectures may be due to some discrepancies between the GNSS-TEC used to update IG12 and the reference data used to evaluate the electron density. Although this situation exists, the overall upda-IRI-2016 performs better than IRI-2016 in terms of accuracy statistics.
# Assessment of Interventions in Fuel Management Zones Using Remote Sensing
## 2 Materials and Methods
### Satellite Data Acquisition  
The used approach uses a combination of data extracted from two satellite constellations, Sentinel-1 and Sentinel-2, as well as some derived indices derived from the multispectral data: NDVI [23], Soil-Adjusted Vegetation Index (SAVI) [24], Simple Ratio (SR) [25], Inverted Red-Edge Chlorophyll Index (IRECI) [26] and Normalized Difference Water Index (NDWI) [27]. The data used in this study was extracted from ESA's Copernicus between 30 th of January 2018 and 28 th of December 2018, the distribution of the images throughout the year is presented in Figure 3, with a total of 20 images for Sentinel-2, and for Sentinel-1, 30 in descending orbit and 30 in ascending orbit. For Sentinel-2 data, only images with a cloud cover percentage below 10% were considered, which were then manually checked to ensure there were no clouds over the study area.  
Some Sentinel-2 satellite products only provide reflectance values at the top of the atmosphere (level 1C). This can be problematic when dealing with multi-temporal data since the composition of the atmospheric layer is not constant, and can vary depending on the time of year or even the location. This instability has an impact on the values obtained by the satellite bands and, consequently, on the vegetation indices calculated from them, especially when multi-temporal data is being used [28; 29]. The tool Sen2 Cor [30] was used to process Sentinel-2 level 1C data to the corrected level 2A.  
For Sentinel-1, images with the product type Ground Range Detected (GRD) were used, in descending and ascending orbit with intensity values converted to Gamma0. The processing pipeline, using the ESA Sentinel Application Platform (SNAP) (ESA Sentinel Application Platform (SNAP)--[[http://step.esa.int/main/toolboxes/snap/--Last](http://step.esa.int/main/toolboxes/snap/--Last)]([http://step.esa.int/main/toolboxes/snap/--Last](http://step.esa.int/main/toolboxes/snap/--Last)) visited on 6 March 2020), was as follows: (1) Apply-Orbit-File; (2) Terrain-Correction; (3) LinearToFromdB.
# Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems
## 3 Materials and Methods
### ETC Gantry Data Completion Method Based on Improved Tensor Decomposition
#### 3.2.5. Description of the ETC Gantry Data Completion Issue  
It is assumed that there exists a higher-order tensor block, \(\mathcal{X}\in\mathbb{R}^{I_{1}\times I_{2}\times I_{3}}\), with missing values and a set of observable data within \(\mathcal{X}\), which is \(\Phi\in[I_{1}]\times[I_{2}]\times[I_{3}]\). Given that \(x_{ijk}(i,j,k)\in\Phi\), the elemental values outside the observable dataset should be calculated as rapidly as possible while ensuring accuracy. Therefore, the observable dataset within \(\mathcal{X}\) is projected onto each spatial dimension of the tensor block as follows: if \((i,j,k)\in\Phi\), then the observed value of element \(P_{\Phi}(x)\) is \(x_{ijk}\); otherwise, the elemental value is zero.  
\[P_{\Phi}X=\left\{\begin{array}{ll}x_{ijk},&(i,j,k)\in\Phi\\ 0,&\text{else}\end{array}\right. \tag{21}\]  
where \(P_{\Phi}\) is the projection operator.
# Adaptive Feature Fusion for Small Object Detection
###### Abstract
In response to the above challenges, we make the following contributions and propose a small object detection algorithm combining multi-branch multi-scale feature fusion with the fusion factor and an improved attention mechanism, referred to as MMF-YOLO. 1. For the problem of large scale changes of small objects like objects, we designed a multi-scale, multi-path, and multi-flow feature fusion module, referred to as MMF-Net. Among them, the features of multi-branch fusion have unique fusion factors. 2. In order to focus the \"gaze\" of the network on the representative local object region after convolution and accurately separate the background information from the object information, a new attention mechanism (M-CBAM) was designed, which was added to the feature strengthening extraction to increase attention to the features to be extracted, so that the convolution can pay attention to the feature map with less sample information. 3. In order to improve the classification probability and regression coefficient of small objects, a shallow object detector was added for the small size of small objects. Simultaneously, in order to reduce the computational load of the network, the detection head in the deepest layer of the network was discarded. At the same time, in order to ensure the correct detection of larger-sized objects in small objects, shallower and deeper detection heads were reserved.
# Nutritional Recommendations for Breath-Hold Divers
## 5 Spearfishing
### Supplementation  
Supplementation for spearfisherman is supposed to be similar to that of dynamic apnea. Hence, it is good to take BCAA to prevent muscle catabolism and maintain energy levels during activity, beta-alanine, which helps in the tolerance of lactate accumulation and increases anaerobic endurance, and L-citrulline or L-arginine, which increase the production of nitric oxide, improve circulation, and thus supply muscles with oxygen [28]. Furthermore, due to the frequent horizontal body position, water temperature, hydrostatic pressure, and the resulting diuresis caused by ANP sweating in the diving suit and increased breathing, increased water loss occurs [38]. Dehydration of 2% of body weight can reduce aerobic capacity by 10%. Therefore, it is important to maintain hydration during diving with the possible addition of essential electrolytes. A good choice for this is isotonic drinks that contain the following: Sodium--maintains fluid balance and prevents dehydration. Potassium--key for healthy muscle function and the prevention of cramps [39]. Magnesium--supports the work of muscles and the nervous system [40]. Calcium--important for muscle contraction [41]. Optionally, isotonic drinks can also contain carbohydrates, usually in the form of glucose, fructose, maltodextrin, or sucrose, which provide a quick source of energy and help replenish depleted glycogen reserves, as well as vitamin C as an antioxidant and B-group vitamins to support energy metabolism [42].  
After spearfishing, it is necessary to replace lost fluids rich in minerals as soon as possible, for example with isotonic drinks. For rapid regeneration, it is important to first consume a carbohydrate complex, such as maltodextrin or isomaltose, or, as a healthier and more natural option, a few dates and a ripe banana to quickly restore depleted glycogen reserves. In addition, a protein shake, such as whey protein, enriched with L-glutamineis recommended for accelerated muscle regeneration, protein replacement, and reduced fatigue [35]. The post-spearfishing meal can be supplemented with Omega-3 fatty acids from fish or flaxseed oil to reduce inflammatory processes, while vitamins C and E act as powerful antioxidants that neutralize oxidative stress caused by apnea and exhausting physical activity. B vitamins additionally support energy metabolism and reduce the feeling of fatigue, while minerals such as zinc and selenium strengthen the immune system and contribute to recovery [27].  
Such supplementation enables spearfishermen to maintain a high energy capacity during spearfishing, quickly replenish glycogen reserves, protect muscles, and reduce the negative effects of oxidative stress, thereby ensuring optimal preparation for spearfishing activity and accelerated recovery.
## 2 Materials and Methods
### Data
#### 2.2.8 Trendy GPP  
We used the mean GPP simulations from the TRENDYv6 [16,67] ensemble of TBMs to calculate the correlation with SPEI and evaluate the response of GPP to drought in this study. Climate variability and the observed global CO\({}_{2}\) concentration from the CRUNCEP dataset are used to constrain the TRENDY models. Since the atmospheric CO\({}_{2}\) concentrations in the S3 simulation were based on observation, and the climate and land cover were varied over the modeling period (1980-2015), we primarily analyzed model findings from that simulation. All monthly GPP from TRENDY models were first resampled to 8\({}^{\circ}\)\(\times\) 10\({}^{\circ}\) grid in the unit of gC m\({}^{2}\) yr\({}^{-1}\).
## 5 Conclusions  
This work develops a user-authentication and key-agreement scheme that exploits the favorable characteristics and speed of Chebyshev polynomials to provide high computational efficiency and comply with HIPAA privacy/security regulations. The proposed scheme solves security problems that afflict related schemes, such as the accessing of patient information without patient authorization, the inability to perform multiple verifications simultaneously, and others. This proposed key-agreement scheme depends on a certificate-management center to enable doctors, patients and authentication servers to realize mutual authentication through certificates and thereby reduce the number of rounds of communications that are required. The proposed scheme provides all of the security functions of related schemes, while overcoming their limitations and offering greater efficiency. It is more secure and compliant with HIPAA privacy/security regulations, so it is more suitable for real-world environments.  
Since the proposed scheme needs to comply with privacy/security regulations and needs to consider more contexts, it is more complicated than other schemes applied to healthcare systems. Future work plans to simplify the process of the proposed scheme, comply with the general principles of privacy/security regulations and be applicable to practical application scenarios.  
Conceptualization, Y.-P.H. and T.-F.L.; methodology, T.-F.L. and G.-J.S.; validation, Y.-P.H. and K.-C.L.; formal analysis, T.-F.L. and K.-C.L.; investigation, Y.-P.H., T.-F.L., K.-C.L. and G.-J.S.; writing--original draft preparation, K.-C.L. and G.-J.S.; writing--review and editing, Y.-P.H. and T.-F.L.; supervision, Y.-P.H. and T.-F.L.; project administration, T.-F.L.; funding acquisition, T.-F.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Science and Technology of the Republic of China, grant number MOST 109-2221-E-320-003 and MOST 110-2221-E-320-005-MY2.  
Not applicable.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Treatment Planning and Evaluation  
Original patients' treatments were planned and calculated in the Eclipse TPS version 13.6 (Varian Medical Systems, Palo Alto, CA, USA) based on NCCT in accordance with standard departmental policies. VMAT treatment planning was carried out for all patients using 6 MV X-ray beams with the anisotropic analytical algorithm (AAA). The same plan for each patient was copied and recalculated using the corresponding CCT im  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multirow{2}{*}{**Site**} & \multicolumn{4}{c}{**No. of Patients**} \\ \cline{3-5}  & & **Male** & **Female** & **Total** \\ \hline \multirow{3}{*}{Head and Neck} & \multirow{3}{*}{Nasopharynx} & 38 & 32 & 70 \\ \cline{2-5}  & & Nasopharynx & 65 & 25 & 90 \\ \cline{2-5}  & Thyroid & 6 & 3 & 9 \\ \cline{2-5}  & & Tongue & 4 & 3 & 7 \\ \hline \multirow{3}{*}{Chest} & Lung & 6 & 1 & 7 \\ \cline{2-5}  & Mediastinum & 4 & 3 & 7 \\ \cline{2-5}  & Esophagus & 1 & 4 & 5 \\ \hline \multirow{3}{*}{Abdomen} & NHL & 9 & 2 & 11 \\ \cline{2-5}  & Pancreas & 2 & 4 & 6 \\ \cline{2-5}  & Liver & 0 & 2 & 2 \\ \hline \multirow{3}{*}{Pelvis} & Cervix & 0 & 4 & 4 \\ \cline{2-5}  & Uterus & 0 & 3 & 3 \\ \cline{1-1} \cline{2-5}  & Rectum & 3 & 0 & 3 \\ \cline{1-1} \cline{2-5}  & Prostate & 2 & 0 & 2 \\ \hline Total no of Patients & & 140 & 86 & 226 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of patients’ population and site demographics.  
age set for each patient instead of the NCCT image set. These treatment plans were neither re-optimized nor modified in any way. The dose distribution and monitor units (MU) settings were then calculated. The resulting CCT-based treatment plans were evaluated and compared to the corresponding original NCCT-based treatment plans in terms of dose distribution and HU, with emphasis on OARs and PTVs.  
In addition to the investigation of differences in absolute mean HU values for critical structures and PTV between CCT and NCCT images sets, statistical evaluation included the mean dose, maximum dose, median dose, PTV volume covered by 98% of the prescribed dose (D98%), and PTV volume covered by 2% of the prescribed dose (D2%). For critical structures, the percentage difference (D\({}_{\%}\)) between relative doses in CCT (\(D_{CCT}\))- and NCCT (\(D_{NCCT}\))-based plans was calculated using Equation (1). A difference of 2% or less is considered acceptable, and relative doses less than 10% of the prescribed dose were omitted from evaluation to elude error overestimation.  
\[\text{D}\%=100\times\frac{D_{CCT}-D_{NCCT}}{D_{NCCT}} \tag{1}\]  
Furthermore, the 3D gamma evaluation method was used to evaluate the volumetric dose difference between CCT- and NCCT-based plans. The criteria were 2.0 mm distance to agreement (DTA) and 2.0% dose difference (DD) with suppression of dose values less than 10% of the prescribed dose. The 3D gamma evaluation was carried out using Verisoft package version 5.1 (PTW, Freiburg, Germany).
# Analyzing the Corporate Business Intelligence Impact: A Case Study in the Financial Sector
## 2 Proposed Research Framework, Methodology, and Case Study
### Creating the Report Using Business Intelligence Solutions
#### 2.6.1 SAP Business Objects  
SAP Business Objects (SAP BO) has different features and capabilities, helping businesses manage, analyze, and extract information from their data more effectively. SAP BO is a platform developed by SAP that offers a wide range of business intelligence and analytics solutions. The main purpose of SAP BO is to enable businesses to analyze data, create reports, and base their business decisions on better information.  
SAP BO has the following capabilities:  
* Data integration: Gathering data from different data sources and bringing it together.
* Reporting: Creating and sharing customizable reports.
* Analytics: Discovering trends, patterns, and statistics by analyzing data.
* Visualization: Making sense of data with charts, tables, and visual elements.
* Query: Accessing and analyzing data using queries.  
In general, SAP Business Objects is a suite of powerful tools used to meet the data analysis and business intelligence needs of businesses. Businesses can use this platform to better understand their data, make business decisions, and gain a competitive advantage.
# A Cross-Layer Optimization QoS Scheme in Wireless Multimedia Sensor Networks
###### Abstract  
There are two main challenges in wireless multimedia sensors networks: energy constraints and providing DiffServ. In this paper, a joint flow control, routing, scheduling, and power control scheme based on a Lyapunov optimization framework is proposed to increase network lifetime and scheduling fairness. For an adaptive distribution of transmission opportunities, a differentiated queueing services (DQS) scheme is adopted for maintaining data queues. In the Lyapunov function, different types of queues are normalized for a unified dimension. To prolong network lifetime, control coefficients are designed according to the characteristics of the wireless sensor networks. The power control problem is proved to be a convex optimization problem and two optimal algorithms are discussed. Simulation results show that, compared with existing schemes, the proposed scheme can achieve a better trade-off between QoS performances and network lifetime. The simulation results also show that the scheme utilizing the distributed media access control scheme in scheduling performs best in the transmission of real-time services.  
Keywords:Lyapunov optimization; wireless multimedia sensor networks; cross-layer control; QoS +
Footnote †: journal:
## 4 Results and Discussion
### Microwave Frequency
#### 4.1.1 Simulation Research
The heating depth is given by Equations (5) and (6):  
\[D=\frac{c}{\pi f\sqrt{2\epsilon^{\prime}\Big{(}\sqrt{1+\tan^{2}\delta}-1\Big{)}}} \tag{8}\]  
\(D\) is an inverse function of the microwave emission frequency. Compared to the microwave emission frequency of 2.45 GHz, the heating depth decreases when the frequency is 5.8 GHz. That is, the microwave energy is mainly absorbed by the surface layer of the pavement and converted into heat energy, which can quickly transfer the thermal energy of the surface layer to the junction of the ice layer and the surface layer, and quickly melt the ice. On the contrary, when the microwave emission frequency is 2.45 GHz, the heating depth increases; that is, the microwave energy is absorbed within a relatively large depth, and the heat transfer time is correspondingly increased, so the efficiency of deicing and snow removal is correspondingly reduced. Therefore, it can be concluded that microwaves with a frequency of 5.8 GHz are more suitable for road deicing.
## 5 Open Problem and Research Challenges
### Open Challenges
#### 5.1.3 Security Attack  
Due to the harsh condition of the underseas, it is not viable to change the sensor nodes regularly, nor is it a solution to the energy constraints; this opens up the sensors to plenty of cyber threats [91]. Furthermore, if we are thinking about the uses of UWSN for military purposes, these vulnerabilities may expose more significant threats. For example, wormhole attacks are common in environments where the sensors are far apart. Here, the node further from the BS says it has a free path to the BS rather than forwarding to the node closer to the BS. Again, this may lead to attacks. However, it is hard to overcome the constraints in UWSN due to the harshness of the sea, such as environmental and temporal delay. Further research should be performed in this regard [92].
## 1 Introduction  
Civil infrastructure projects constitute the backbone of the development of urban and rural areas. The significance of civil infrastructure in improving the social quality of life cannot be overstated. Nevertheless, the implementation of such civil infrastructure projects requires managing a complex array of stakeholders and interests [1]. At the crossroads of development and conservation, civil infrastructure projects encounter an intricate web of interests. Governments advocate for stable infrastructure growth; local communities seek inclusive development; private sectors look for a return on investments; environmentalists press for sustainable practices; and heritage committees prioritize preservation [2, 3]. Although these various objectives aim toward a common good, they often have different opinions. The unique combination of diverse stakeholders, limited national budget, and societal implications makes projects a fertile ground for conflict, leading to delays in project timelines and even project cancellations [4, 5]. Social conflict among external stakeholders in civil infrastructure projects has a significant impact on project performance as well as on social governance. For sustainable development of civil infrastructure, it is essential to manage conflict preemptively.  
In the era of digitalization, people are more connected to each other than ever. The transition from traditional print and broadcast news to online news media has empowered information dissemination and communication. With the ability to reach millions of people instantly, online news platforms have democratized access to information and played a pivotal role in shaping public discourse [6]. However, these platforms have a potential drawback, as they can amplify and intensify social conflicts through the swift dissemination of information [7]. The rapid dissemination of information through news and the subsequent formation of public opinion have a significant impact on the progress of civil infrastructure projects [8; 9]. Negative public opinion and social conflicts in civil infrastructure projects may lead to cost growth, schedule delay, and even project termination. In particular, conflicts change dynamically during the project execution, and unresolved conflicts cause complex problems in conjunction with subsequent conflicts. Therefore, it is essential to detect key conflict drivers and establish appropriate response strategies in a timely manner for successful project management [4].  
Recent natural language processing (NLP) technology, coupled with cutting-edge artificial intelligence and big data, has reached a level where it can help solve real-world problems [10]. Its applicability in extracting information and identifying patterns related to social conflicts based on news content is worth exploring. Against this backdrop, this study aimed to extract conflict drivers related to civil infrastructure projects presented in news articles using ChatGPT.