esa-sceva/satcom-chunk-collection huggingface dataset:
# DQN-Based Shaped Reward Function Mold for UAV Emergency Communication
###### Abstract  
Unmanned aerial vehicles (UAVs) have emerged as pivotal tools in emergency communication scenarios. In the aftermath of disasters, UAVs can be communication nodes to provide communication services for users in the area. In this paper, we establish a meticulously crafted virtual simulation environment and leverage advanced deep reinforcement learning algorithms to train UAVs agents. Notwithstanding, the development of reinforcement learning algorithms is beset with challenges such as sparse rewards and protracted training durations. To mitigate these issues, we devise an enhanced reward function aimed at bolstering training efficiency. Initially, we delineate a specific mountainous emergency communication scenario and integrate it with the particularized application of UAVs to undertake virtual simulations, constructing a realistic virtual environment. Furthermore, we introduce a supplementary shaped reward function tailored to alleviate the problem of sparse rewards. By refining the DQN algorithm and devising a reward structure grounded on potential functions, we observe marked improvements in the final evaluation metrics, substantiating the efficacy of our approach. The experimental outcomes underscore the prowes of our methodology in effectively curtailing training time while augmenting convergence rates. In summary, our work underscores the potential of leveraging sophisticated virtual environments and refined reinforcement learning techniques to optimize UAVs deployment in emergency communication contexts.  
umanned aerial vehicle UAV; deep Q-learning network DQN; reward shaping +
Footnote †: journal: applied sciences
## 3 Results and Discussion
### Characteristics of the Quartz Crystal Microbalance Sensor
#### 3.1.2 Linear Range and Selectivity of the Sensor
It is well known that the water solubility of the hydrophobic compounds with an ionized functional group is generally higher than the solubility of the neutral species and the potential to partition from 1-octanol to water significantly increases by several orders of magnitude. Therefore palmitate in triolein phase can easily transfer to aqueous solution even if palmitate and triolein coexist together. Additionally the low response to acetate is likely due to its hydrophilic nature. These results indicate that pH adjustment and dissociation of fatty acids can contribute to the selectivity of the QCM sensor.
## 3 Results and Analyses  
### Illumination Analysis  
#### 3.1.1 Winter Illumination Analysis  
A photovoltaic module has obvious effects on the illumination in a greenhouse, especially in winter when the light is weakest. Tropical areas have relatively rich light resources. However, the deployment of photovoltaic modules may reduce the light intensity to a large extent. If the light in the greenhouse during winter rainy days in tropical areas can satisfy the growth requirement of crops, theoretically this kind of photovoltaic greenhouse can meet the growth requirement for light throughout the year.  
The winter test time was 5 January 2016. The weather was limited rain. The light intensity of each collection site in the photovoltaic greenhouse is shown in Figure 3.  
As shown, the change trends of light intensity at different points in the photovoltaic greenhouse were basically the same, and the light intensity reached a peak value at about 14:30. According to the comparison between site A (shading area), site B (photic area) and site C (transition area) with the shading area in descending order of C > B > A, the shading has impact on the daylighting of the area under photovoltaic panels. According to the comparison of the light intensities between site D (photic belt) and site E (photic area) with the shading area in descending order of E > D, the shading also has influence on the daylighting of the area under the photic belt.  
Figure 3: Changes of the light intensity in the photovoltaic greenhouse during limited rain winter.  
For the quantitative analysis of the indoor light transmittance, we averaged the light intensity during 10:00-16:00 and compared them with the outdoor light intensity (Table 1).  
As shown in Table 1, the average outdoor light intensity between 10:00 and 16:00 was 27.23 kLux, and the average indoor light intensities at different sites were between 6.48 and 7.99 kLux. According to the weighted calculation of the roof cover transmittance area and the photovoltaic area in proportion to their area, the compound average transmittance was 25.77%, and the compound average light intensity was 7.02 kLux.  
According to the comparison of the average winter indoor light intensity of the best site (C) and the poorest site (A) of daylighting, the light intensity of site A was 81.1% of site C (1.51 kLux difference). This means that although the winter light intensity in the photovoltaic greenhouse was not even, the difference between the areas was limited and the distribution of light was relatively even.
# Extensive Experiments on Opportunistic Routing in Wireless Sensor Networks
## Appendix A Flowchart of ODYSSE
# Conceptual Framework of an Intelligent Decision Support System for Smart City Disaster Management
###### Abstract  
In order to protect human lives and infrastructure, as well as to minimize the risk of damage, it is important to predict and respond to natural disasters in advance. However, currently, the standardized disaster response system in South Korea still needs further advancement, and the response phase systems need to be improved to ensure that they are properly equipped to cope with natural disasters. Existing studies on intelligent disaster management systems (IDSSs) in South Korea have focused only on storms, floods, and earthquakes, and they have not used past data. This research proposes a new conceptual framework of an IDSS for disaster management, with particular attention paid to wildfires and cold/heat waves. The IDSS uses big data collected from open application programming interface (API) and artificial intelligence (AI) algorithms to help decision-makers make faster and more accurate decisions. In addition, a simple example of the use of a convolutional neural network (CNN) to detect fire in surveillance video has been developed, which can be used for automatic fire detection and provide an appropriate response. The system will also consider connecting to open source intelligence (OSINT) to identify vulnerabilities, mitigate risks, and develop more robust security policies than those currently in place to prevent cyber-attacks.  
decision support system; big data; artificial intelligence; Internet of Things; disaster management +
Footnote †: journal: Applied Sciences
# Polarization Imaging Method for Underwater Low-Visibility Metal Target Using Focus Dividing Plane
## 5 Discussion  
Based on the split-focus plane imaging system, underwater polarization imaging experiments are carried out for metal targets of different materials and low-visibility scenes. The results show that the degree of polarization of metal objects is higher than that of nonmetals. Polarization imaging can effectively distinguish underwater metal and nonmetal targets. Under the condition of low underwater visibility, the brightness and  
Figure 14: Image quality evaluation results of different milk concentrations: (**a**) EME; (**b**) information entropy; (**c**) average gradient.  
Figure 13: Image I and DOP at different turbidities: (**a**) 0.3 mL/L; (**b**) 0.6 mL/L; (**c**) 0.9 mL/L; (**d**) 1.2 mL/L; (**e**) 1.5 mL/L; (**f**) 1.8 mL/L.  
contrast of the light intensity image drop sharply, but the contrast of the polarization image is high due to the great difference in the polarization characteristics of different objects. Therefore, polarization imaging can effectively detect metal targets in harsh underwater environments. It has certain application prospects in underwater environment monitoring, military reconnaissance and other fields.  
[PERSON] and [PERSON] proposed the idea of the paper. [PERSON] and [PERSON] helped manage the annotation group and helped clean the raw annotation. [PERSON] conducted all experiments and wrote the manuscript. [PERSON], [PERSON] and [PERSON] revised and improved the text. [PERSON] and [PERSON] are the people in charge of this project. All authors have read and agreed to the published version of the manuscript.  
This research was funded by [Science and Technology Foundation of State Key Laboratory] grant number [2022-JCJQ-L8-015-0201], [Liaoning Provincial Department of Education Scientific research funding project] grant number [LJKZ0475] and [Dalian High-Level Talent Innovation Support Program] grant number [2022 RJ03].  
Not applicable.  
Data Availability StatementData that support the findings of this study are available from the corresponding author upon reasonable request.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Preprocessing
#### 2.1.2 Phase Correction  
MR spectra are not always in absorption mode, due to the misadjustment of the reference phase relative to the receiver phase detector, amplifier dead time, and phase shift from the digital filter employed to reduce noise [26]. The phase correction operation is automatically performed through application of reference [27], which combines \"coarse tuning\" and \"fine tuning\". In the former procedure, the position of the tail ends of each peak is determined with a baseline, and then the preliminary phase spectra are obtained by minimizing the height difference between tail ends. After the coarse tuning, peaks are classified as: positive, negative, or distorted. A custom negative penalty function is generated to neglect the negative and distorted peaks. Ultimately, the phase spectra are obtained by minimizing the generated negative penalty function.
# Reducing Dynamic Power Consumption in Mixed-Critical Real-Time Systems
## System Model
### Power Model  
In this paper, we assume the DVFS-enabled CPU system where the CPU frequency is adjusted dynamically during run-time. The number of discrete frequency levels is given by \(m\) while the frequency levels are defined as a set \(F\).  
Let us assume that a task requires \(t\) execution time on the CPU at its maximum frequency level. For a given frequency level \(f\) of the CPU, the relative speed level \(s\) is defined by \(f/f_{\max}\), where \(f_{\max}\) is the maximum frequency level. Then, the task execution time is defined by \(t/s\).  
Since the dynamic power consumption is a major issue in the power consumption of systems, we take dynamic power consumption into account in the paper. Generally, the dynamic power is in proportion to \(f^{3}\) or \(f^{4}\) for a frequency level \(f\), we use Equation (1) for the execution time model of a task with \(t\) execution time on the relative speed level \(s\)[31].  
\[E=\alpha\cdot\frac{t}{s}\cdot s^{3}=\alpha\cdot t\cdot s^{2}, \tag{1}\]  
where \(\alpha\) is a coefficient. In this paper we assume \(\alpha=1\) for the sake of simplicity.  
Figure 2 shows an DVFS scheme for real-time task scheduling. For example, a real-time task requires 3 time unit for its execution, while its result requires 10 time units (Figure 1(a)). If there is no other task, the system has 7 time-unit slack time to the task deadline. Thus, the task can be executed on the relative speed level of 0.3, as shown in Figure 1(b). In the reduced CPU speed level, the system can reduce the power consumption without violating the task deadline.  
Figure 1: An example of mixed-criticality scheduling.
## 1 Introduction
### Research Gap and Objectives  
Many educational institutions and hospitals are developing tools utilizing VR and AR for surgical training, planning, and assistance in various medical fields. However, research on VR or AR-based simulators specifically for maxillofacial reconstruction surgery remains relatively scarce. Maxillofacial reconstruction is a surgical procedure that restores the bones or skeletal structure of the mouth, jaw, and face using materials such as the iliac crest or fibula, requiring a high level of difficulty and precision. Inaccurate surgeries can lead to various side effects and complications, including speech disorders, sleep apnea, facial asymmetry, and nerve damage. Safe reconstruction surgery requires accurate patient diagnosis, skilled medical professionals, and precise surgical planning. To achieve this, practical and clinical training in maxillofacial procedures, as well as tools to assist in precise surgical planning, are essential. However, similar to other medical practical and clinical training programs and 3D CAD tools, it faces challenges such as high costs for creating the environment, a lack of equipment and educators, and limited practice opportunities. Additionally, difficulties in analyzing the details of 3D models due to the 2D UI and variations in functionality utilization based on user proficiency can make precise surgical planning challenging. To mitigate these challenges, research on applying VR technology, which has proven effective in educational and planning aids, is necessary. In this context, we propose the development and validation of a VR simulator for the education and planning of maxillofacial reconstruction surgery.  
The goal of this study is to develop a simulator for the education and planning of maxillofacial reconstruction surgery using the iliac bone by leveraging VR and interactive technologies and to validate the simulator's effectiveness and potential feasibility through various evaluations. The paper describes the methods for loading 3D models of the iliac bone and maxillofacial regions based on medical data, as well as the development of functionalities such as exploration, translation, rotation, and resection of the models using interactive devices. Additionally, it outlines the performance, usability, and accuracy evaluation methods for the simulator. Finally, the study conducts validation according to these methods, summarizes and analyzes the results, and confirms the simulator's validity and potential feasibility.
# Integrating a Path Planner and an Adaptive Motion Controller for Navigation in Dynamic Environments
## 3 The Methodology
### Problem Description  
In this paper, the problem of navigation can be stated as follows: on an initially known map, the mobile tracked robot that is only equipped with local laser sensors autonomously navigate without colliding with moving obstacles via continuous control. Since environments with moving obstacles are dynamic and uncertain, this navigation task is difficult to be dealt with, and is an non-deterministic polynomial-hard problem [27].  
In this paper, we adopt the Cartesian coordinate system. The structure of the tracked robot is shown in Figure 1. The position state of the tracked robot is defined as \(s=(x_{r},y_{r},\theta_{r})\) by the global coordinate of the map, where \(x_{r}\) and \(y_{r}\) are the tracked robot's horizontal and vertical coordinates, respectively, and \(\theta_{r}\) is the angle between the forward orientation of the tracked robot and the abscissa axis. Twelve laser sensors equipped at the front of the tracked robot can sense the nearby surroundings 360 degrees. The detection angle of each laser sensor is 30 degrees. The max detection distance is \(D_{max}\). The robot is controlled by the left and right tracks. The kinematic equations were as follows:  
\[\left(\begin{array}{c}\dot{x}_{r}\\ \dot{y}_{r}\\ \dot{\theta}_{r}\end{array}\right)=R\left[\begin{array}{cc}\frac{cos\theta _{r}}{2}&\frac{cos\theta_{r}}{2}\\ \frac{sin\theta_{r}}{2}&\frac{sin\theta_{r}}{2}\\ \frac{\dot{\Gamma}}{\dot{\Gamma}_{B}}&-\frac{\dot{\Gamma}}{\dot{\Gamma}_{B}} \end{array}\right]\left(\begin{array}{c}\omega_{l}\\ \omega_{r}\end{array}\right), \tag{1}\]  
\[\left(\begin{array}{c}\dot{\omega}_{l}\\ \dot{\omega}_{r}\end{array}\right)=\left(\begin{array}{c}\frac{\partial\omega _{l}}{\partial l}\\ \frac{\partial\omega_{r}}{\partial l}\end{array}\right), \tag{2}\]  
where R is the radius of the driving wheels in the tracks; \(\omega_{l}\) and \(\omega_{r}\) denote the angular velocity (rad\(\cdot\)s\({}^{-1}\)) of left tracks and right tracks; \(\dot{\omega}_{l}\) and \(\dot{\omega}_{r}\) respectively denote the angular acceleration of left tracks and right tracks (rad\(\cdot\)s\({}^{-2}\)), and \(l_{B}\) denotes the distance between the left and right tracks.
# Improving User Experience with Recommender Systems by
## 2 Theorical Background
### Hypotheses Development
#### 2.3.3 System and Recommendation Outcomes  
For an RS to be successful with respect to its adoption, users should have confidence in the system-generated recommendations and trust the system [5]. Transparency plays an important role in users' confidence in recommendations as it may encourage or deter users' trust in a system [42; 43], where recommendations perceived as transparent by users increase their confidence [44]. User perceptions of ease of use and usefulness are positively related to each other [45; 46; 47; 12] and to system attitudes, such as those toward the system's use and system satisfaction [46; 47; 12; 40; 48]. Moreover, explanations contribute to user trust in RSs [49; 50; 30]. Confidence in the system positively influences trust in the system [51] and the user's behavioral intentions with the system, including their intention to accept a system-generated recommendation [40]; in addition, the degree of trust users put in the system plays an important role in the acceptance of a recommendation [52]. In the context of I.S. use, trust has been shown to positively affect satisfaction [53], which in turn has been shown to encourage use of the system [54; 55]. Hence, the following hypotheses were proposed:  
**Hypothesis 15 (H15).**_Information transparency positively impacts recommendation confidence._  
**Hypothesis 16 (H16).**_RS ease of use positively impacts its usefulness._  
**Hypothesis 17 (H17).**_RS ease of use positively impacts user satisfaction._  
**Hypothesis 18 (H18).**_RS usefulness positively impacts user satisfaction._  
**Hypothesis 19 (H19).**: _RS usefulness positively impacts RS trust._
**Hypothesis 20 (H20).**: _RS usefulness positively impacts RS confidence._
**Hypothesis 21 (H21).**: _Recommendation confidence positively impacts recommendation acceptance intentions._
**Hypothesis 22 (H22).**: _Recommendation confidence positively impacts RS confidence._
**Hypothesis 23 (H23).**: _RS confidence positively impacts RS trust._
**Hypothesis 24 (H24).**: _RS confidence positively impacts recommendation acceptance intentions._
**Hypothesis 25 (H25).**: _RS trust positively impacts RS satisfaction._
**Hypothesis 26 (H26).**: _RS satisfaction positively impacts RS use intentions._
## 6 Conclusions  
In this paper, a dedicated multi-channel oblique backscatter sounder with a miniaturized L-shaped receiving antenna array was developed. Relaying on the high pulse compression gain of m-sequence, a transmission power of 500 W can guarantee the sounding performance. The simulation analysis and experimental results verify that the L-shaped antenna array can achieve a good 2-D beam pointing at elevation and azimuth simultaneously. By using the adaptive beamforming technique, the directional reception of the signal is more optimized, which not only weakens the influence of the two-hop ionospheric vertical echoes on the low-frequency band, but also suppressing the other RF interferences. Thus, on the ionograms, the oblique backscatter echo signals are enhanced and the contrast of the whole ionogram is remarkably improved. Through the analysis of some frequency signal sequences, it can be found that the adaptive beamformers makes the trace leading edge easier to be identified and extracted in the inversion process. Finally, by comparing the results of CFAR and de-noising, it can be concluded that SMI beamformer is more suitable for the low power system and the miniaturized L-shaped antenna array described in this paper.  
From the practice of this paper, it can be seen that employing 2-D antenna array to conduct the ionospheric oblique backscatter sounding has considerable research and application value. Typical arrays and processing algorithms are used in the current work. Naturally, how to further combine the characteristics of the ionosphere to study and design the optimal array structure and processing method should be the research goal of the next stage. Some existing related theories may be used for reference. But this still requires further experiments and analysis of the observational data.  
Data curation, T.L. Investigation, G.Y.; Methodology, T.L.; Project administration, Z.Z.; Software, C.J.; Validation, Y.H.; Writing-original draft, T.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (42327002/41304127/41727804/41604133).  
The authors declare no conflict of interest.
## 3 Results
### Nematicidal and Antifungal Activities of 3-Carene  
To measure nematicidal and antifungal activities of 3-carene, test solutions containing various concentrations of 3-carene were treated to PWNs for two days. No significant difference was found in PWNs with treatment from 0.01 to 1 mg/mL 3-caren concentration, but 35.25% of PWNs were immobilized at a 2 mg/mL concentration of 3-carene, and 45.98% of PWNs were immobilized at a 10 mg/mL concentration of 3-carene (Figure 8a).  
Figure 6: Construction of transgenic tobacco plants overexpressing _Pd3-car_ gene and RT-PCR analysis: **(a)** Schematic diagram of the _Pd3-car_ gene overexpression vector plasmid under the control of the _Cauliflower mosaic virus_ (CaMV) 35S promoter. LB represents the left border and RB represents the right border of the T-DNA. NPT, kanamycin resistance gene; P35S, CaMV 35S promoter; 3′35S, CaMV 35S terminator. **(b)** Genomic PCR of wild-type and transgenic lines overexpressing the _Pd3-car_ gene. PCR products of genomic DNA extracted from the wild-type tobacco and three transgenic lines followed by screening with _Pd3-car_ and _nptII_ gene primers. **(c)** Expression of the introduced _Pd3-car_ gene and attB1-attB2 vector region by RT-PCR. \(\beta\)-actin was used as a loading control. M = marker (1 kb), Wt = wild type, Tr = selected transgenic tobacco lines.  
Figure 8: Nematicidal and antifungal activities of 3-carene: (**a**) Nematicidal activity of 3-carene against _Bursaphelenchus xylophilus_, (**b**) photograph of _Botrytis cinerea_ on potato dextrose agar (PDA) medium with 3-carene test solution, and (**c**) antifungal activity of 3-carene against _B. cinerea_.  
Figure 7: Production of 3-carene from wild-type and transgenic tobacco leaves expressing the _Pd3-car_ gene: (**a**) SPME/GC-MS chromatography of tobacco leaf volatile compound from wild-type and transgenic plants. (**b**) Mass fraction of the peak in the transgenic plant (line Tr-8) overexpressing the _Pd3-car_ gene and authentic standard. (**c**) Content of 3-carene in the transgenic line. The data are shown as the means \(\pm\) standard error obtained from three independent plants.  
The antifungal activity of 3-carene was measured in _Botrytis cinerea_, commonly used for propagation of PWN as a feed in the laboratory. Mycelial of _B. cinerea_ in control was fully grown in Petri dish after seven days, whereas growth of the fungus in 3-carene treatment was restricted (Figure 8b). The treatment of 1.5 mg/mL 3-carene concentration inhibited 91% of the fungal growth compared with the control (Figure 8c). In the lowest concentration (0.05 mg/mL), the compound restricted the mycelial growth of _B. cinerea_ at 36% compared with the control.