esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion and Future Research Direction
It is currently difficult to identify radiologist experts in the area where most of the authors reside. We claim that the proposed CovidDetNet approach can be used as a replacement for expert radiologists to timely identify COVID-19 and help stop the spread of the virus. Furthermore, to perfectly know the time gained comparing chest radiography with the proposed CovidDetNet approach, we need to experiment with the domain experts diagnosing COVID-19 from X-rays and compare the results and time taken with the proposed CovidDetNet approach. Additionally, to generalize the proposed CovidDetNet approach, we aim to test and validate the proposed approach with the emerging new variants of COVID-19 and record its performance and accuracy to identify the new types of COVID-19 virus. Additionally, we are interested to identify the performance of proposed approach on detecting & removing mask [70] and heart disease predication [71; 72]. Furthermore, healthcare institutions in many countries are incorporating a large number of smart devices for combating the disease and obtaining information about its growth. In addition, blockchain and IoT are also assisting medical professionals in gaining valuable insights about behavior and symptoms. At the same time, physicians are using various IoT-enabled devices for remote monitoring of patients, considering that COVID-19 spreads faster than the average communicable disease. In particular, the Internet of Medical Things (IoMT) applications involve tracking medication orders, monitoring COVID-19 patients remotely, and incorporating wearables for transmitting healthcare information to the respective healthcare professionals. The healthcare sector is banking on the potential of IoMT technologies to collect, evaluate, and transmit healthcare information efficiently. IoT devices can pacify the diagnosis process of infectious diseases, which is essential in the case of COVID-19. IoT-enabled devices can capture body temperatures, collect samples from possible cases, and eliminate human intervention. Even during the quarantine period, IoT devices can remotely monitor patients, preventing further infection. Even IoT-based drones are being used for thermal imaging, disinfecting, medical purposes, surveillance, and announcements to draw the line of defense against COVID-19. Therefore, there is a rising demand to develop deep learning models based on IoT and blockchain technologies--since both have significantly leveraged the global healthcare industry--to detect COVID-19 infection early from the data gathered from IoT-enabled devices.
# Webcam Eye Tracking for Monitoring Visual Attention in Hypothetical Online Shopping Tasks
## 4 Results
### Visual Attention Paid to the Product Depictions  
Figure 3 gives an overview on the proportion of AOIs (i.e., the product depictions) that received visual attention. The boxplots show that there were considerable differences between the participants. In addition, in online shop B, which contained almost twice as many product depictions compared with shop A, a smaller proportion of product depictions received visual attention than in online shop A. In online shop A, the lower quartile was 26.6%, the median was 44.8%, and the upper quartile was 64.6%. In online shop B, the lower quartile amounted to 18.2%, the median to 33.3% and the upper quartile to 40.8%. This means that in online shop A, half of the people looked at less than 50% of the product depictions. In online shop B, even three quarters of the people looked at less than 50% of the product depictions.  
Figure 2: Assessment of visual aesthetics of the two online shops.  
Factors that could explain differences in the visual attention the product depictions received were included in linear regression analyses. Table 1 presents the results of the linear regression analyses for both online shops. Both models were significant (\(p<0.001\)). The independent variables explained more than 80% of the variance of the dependent variable, i.e., the percentage of participants visiting an AOI consisting of a product depiction.  
The independent variables affected the dependent variable in a similar way in both models. With an increasing number of the row (i.e., the further down on the website the product depiction was located), the percentage of participants who looked at the product decreased. In online shop A, an increase in one row was associated with a decrease of 4%, and in online shop B with a decrease of 2%. In other words, with 16 rows in online shop A, the model indicated that 64% less participants looked at the product depictions in the last row compared with the first row; in shop B with 28 rows, the decrease amounted to 56%.  
A product depiction in the middle of the three columns was associated with 16% (online shop A) and 10% (online shop B) more participants looking at the product depiction compared with the left column. In online shop A, significantly more participants also looked at product depictions in the right column compared with the left column. In online shop B, however, no differences were found between the right and left columns. A human model in the product depiction was associated with an increase of 8% (online shop A) and 4% (online shop B) participants who looked at the product depiction.
## 4 Conclusions  
We researched the suppression effects of thermoacoustic oscillation variation under different parameter settings, which brings significant challenges to the design of active control systems. In this study, the influence of three different types of parameters on lean-premixed combustion thermoacoustic oscillation was theoretically investigated. The effects among three parameters were investigated: the burner length, the inlet air temperature and the thermal power.  
The research results indicate that an elongated combustor length or improved gas temperature could alleviate the oscillation intensity. However, improved thermal combustion power cannot effectively suppress thermoacoustic instability. The oscillation frequency not only fluctuated with the parameter settings but also altered the process of thermoacoustic coupling. Meanwhile, some unreasonable designs, such as excessively short burner designs, can lead to stronger thermoacoustic oscillations.  
The triggering time and climb rate were key factors that must be considered when designing an active control system for thermoacoustic oscillations. The triggering time and climb rate fluctuated extensively among different conditions, and the above two factors are interrelated and contradictory to each other when a thermoacoustic oscillation is excited. It is necessary to optimize the triggering time and climb rate of thermoacoustic oscillations in future research to achieve better active control effects in gas turbine combustors. Based on the research results in this article, the design of active control systems for thermal acoustic oscillations can be improved. For thermal acoustic oscillations with short triggering times and fast climb rates, it is necessary to adopt active control algorithms with fast response actions and small delay times and to use high-frequency actuators as much as possible.  
Conceptualization, C.T.; data curation, L.Z. and J.Y.; formal analysis, S.L.; methodology, Y.W.; supervision, C.T. and R.S.; visualization, C.T.; writing--original draft, C.T. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Jiangsu Province (No. BK20230699), the China Postdoctoral Science Foundation (No. 2023M731492), Scientific Research Start-up Foundation funding of High-level Introduction Talents of Nanjing Institute of Technology (No. YKJ202107) and the Natural Science Research Project in Colleges and Universities in Jiangsu Province of China (No. 23 KJB470010).  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
We thank [PERSON] in MayAir Technology (China) Co., Ltd., for her support of this study.  
[PERSON] was employed by the company MayAir Technology (China) Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 4 Conclusions  
Against a background of anti-lightning-strike aircraft carbon fiber/epoxy composites, a lightning strike experiment was carried out, and full digital ultrasonic C-scanning was used to investigate the damage behavior of composite-reinforced panel and its protection structures after lightning strikes. The following main conclusions can be drawn.  
1. Lightning impulse electrical currents are conducted mainly along the fiber direction of the unprotected carbon fiber/epoxy composite-reinforced panel that has maximum electrical conductivity. The protected specimens in favor of lightning current conduction show improved anti-lightning damage performance compared with the unprotected specimen.
2. Delamination damage occurred in protected and unprotected specimens, and might have extended to the stiffener. Overall, the specimen with full-sprayed aluminum protection was more effective than those with local-sprayed aluminum and full copper mesh filling protection in terms of anti-lightning delamination damage, although the deterioration damage depth was almost the same.  
At present, the above study has been applied to the anti-lightning-strike design of carbon fiber/epoxy composite panels in civil aircraft. However, it should be noted that ultrasonic C-scanning is more effective for detecting composite delamination damage. In further investigations, other non-destructive testing auxiliary systems should be further investigated to deeply detect composite damage behavior due to lightning strikes, such as fiber breakage and matrix cracking.  
Material testing and formal analysis: F.W., X.M., Y.Z. and S.J.; Formal analysis and writing--original draft preparation: F.W.  
This study was supported by the National Natural Science Foundation of China (No.: 51475369), the Natural Science Basic Research Plan in Shaanxi Province of China (No.: 2018 JM1001), and the Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University (No.: ZZ2018107). The authors declare no conflict of interest.
# Anomaly Detection for IOT Systems Using Active Learning
## 4 Proposed Methodology  
The approach that is suggested in our research focuses on an active learning framework for an IoT anomaly detection system. A machine learning technique called active learning reduces the need for labeled data while increasing model accuracy. It operates by actively choosing particular data points for labeling, decreasing the cost of annotation, and improving accuracy by emphasizing instructive samples. To more accurately discover anomalies with fewer labeled data points, active learning quickly locates and categorizes anomalous data inside complex IoT datasets. Figure 9 shows our active learning system, which blends supervised and unsupervised techniques to improve anomaly detection. While the unsupervised portion locates potential anomaly clusters, the supervised portion categorizes the data as normal or anomalous. Active learning adapts to different IoT data types and applications by iteratively classifying data based on uncertainty. Entropy and information theory constitute the basis of active learning, particularly uncertainty sampling. A probability distribution's entropy measures its degree of randomness, and active learning chooses which data to label by maximizing information gain. Entropy-based uncertainty sampling, which concentrates on data points close to the decision border or those where the model is uncertain, is the fundamental basis of active learning. Entropy, margin, and variance are three metrics that help it choose data points. Our model uses the modAL package for autonomous active learning and a random forest classifier. The model finds ambiguous instances in the test set, labels them, and adds them to the training set at the end of each iteration. It is especially helpful in situations when there is little or expensive labeled data since it minimizes labeled data while optimizing accuracy. This procedure continues until a performance threshold is reached.
###### Abstract  
In recent decades, the construction industry has advanced in its use of natural green resources, such as vegetable fibers (e.g., flax, hemp, jute, etc.) added in concrete mixtures, to create building materials that are both economically and environmentally sustainable. The pricing, low energy cost, and environmental sustainability of these natural fibers are driving this interest. The quantity of fibers and the ratio of fiber length to its transverse diameter (aspect ratio) are critical characteristics that have a decisive impact on concrete's mechanical qualities. The influence of the aspect ratio of _Arundo donax_ fibers on the tensile characteristics of concrete blocks was specifically investigated in this study. These fibers were collected from the outer section of the stem of this plant, which grows commonly in Mediterranean locations, but that is also found all over the world. Experiments were carried out on cylindrical concrete blocks with a constant amount of fiber (1 percent by weight) and different aspect ratios: 30, 50, and 70 (mm/mm) respectively, to assess their tensile strength, even when compared with concrete blocks without any fiber addition. Tensile tests on _Arundo donax_ fibers were also conducted, with the aim to contribute to the analysis of their interaction with cementitious matrices, and to assess differences between the various compositions. The results showed a direct impact of the aspect ratio on the final tensile strength of concrete blocks, with higher aspect ratios producing superior tensile properties.  
Bioarchitecture; concrete blocks; natural fibers; _Arundo donax_; aspect ratio; splitting tensile strength; Brazilian test
# Trajectory Planning of Shape-Following Laser Cleaning Robot for the Aircraft Radar Radome Coating
## 3 Results
Prior to the execution of the cleaning trials, it was imperative to fine-tune the laser cleaning parameters on a test piece composed of identical material to guarantee the attainment of thorough cleanliness in a solitary scan. The parameters for laser cleaning are delineated in Table 1. The system employs a pulsed fiber laser, characterized by a central wavelength of 1064 nm, a circular core diameter of 400 um, and a maximum output power of 1000 W. Figure 15 provides a clear demonstration of the effectiveness of laser cleaning. The efficiency of this robotic laser cleaning system was determined by calculating the ratio of cleaning duration to the area cleaned, yielding a cleaning efficiency of 2.94 m\({}^{2}\)/h. This represents a significant improvement over the efficiency of 0.396 m\({}^{2}\)/h reported in [29], thereby highlighting a marked enhancement in performance metrics. The trajectory planning method mentioned successfully removed the coating from the test section, meeting the experimental requirements. \begin{table}
\begin{tabular}{c c} \hline
**Designation** & **Parameters** \\ \hline Pulse width & 100 ns \\ Beam diameter & 340 um \\ Repetition rate & 20–50 kHz (continuously adjustable) \\ Maximum single pulse energy & 50 mJ \\ \hline \end{tabular}
\end{table} 
Table 1: Laser cleaning parameters. Figure 14: Estimation of normal vector for cleaning point location: (**a**) normal vector for cleaning execution point and (**b**) local enlarged display.
# Shared eHMI: Bridging Human-Machine Understanding in Autonomous Wheelchair Navigation
## 4 Results and Discussion
### Discussion
#### 4.3.4 The Novelty and Adaptability of Projection Interface Information  
On-ground projection interaction, as an implementation of the proposed shared eHMI, employs a kind of augmented reality for immersive navigation. It enriches wheelchair-human interaction design by blending virtual navigation elements with real-time scenarios, ensuring practical visibility. In the user interface design, we balanced cognitive load against interface complexity, tailoring the display of information for user-system and system-pedestrian interactions to avoid information overload. Control over the display and hiding of interface components ensures information is provided when needed, eliminating unnecessary cues.  
Participants' feedback indicates that a continuous moving navigation path provides seamless guidance, the display of global compass and speed modulation, and the destination proximity, which meets users' needs for precise navigation. In terms of interface visual design, the color scheme of the interface is selected to enhance the visibility of projections, ensuring clarity across various ground colors. We observed that the relative motion of the ground during wheelchair movement, which causes ground blur, still allows projected content to maintain a degree of clarity even in variegated ground conditions. This aspect somewhat improves the ground adaptability of the projections.  
Most participants found the projection interface design intuitive, innovative, practical, and engaging. However, a minority reported high information density and difficulty in understanding, leading to cumbersome and inefficient use. Beyond the visual feedback design, we believe the main reasons for these issues are the participants' short adaptation time to the interface and varying receptiveness to new elements. For older wheelchair users, interface designs that are more age-appropriate need to be considered.
# On the Use of FOPID Controllers for Maintenance Phase of General Anesthesia
## 4 Discussion  
The results presented in Section 3 show that, with a fractional-order PID controller, it is possible to achieve a satisfactory performance (all the clinical requirements are met) in the maintenance phase of anesthesia during surgical procedures. From the presented results, it appears that tuning a FOPID controller by minimizing the IAE provides a slightly better performance compared to that obtained when the isodamping condition is imposed. All the analyzed controllers are able to handle both inter- and intra-patient variabilities, providing adequate robustness. From the performed simulations, it appears in any case that the performance obtained with a FOPID controller is very similar to that obtained with a PID controller. Therefore, it can be concluded that a FOPID closed-loop control system can be used to titrate propofol to achieve the required Depth of Hypons, but a traditional PID controller seems to still be the best option in terms of the trade-off between performance and the complexity of implementation. Given the encouraging results obtained from this simulation study, it would be interesting to test the FOPID-based control structure in a real clinical scenario. Since the Oustaloup approximation [29] was exploited during the design phase of the fractional-order controller, the controller transfer function turns out to be of high order. Anyway, it is still possible to perform controller discretization in order to implement it in control software that was used for clinical investigation [8; 32]. Moreover, since the proposed control solution does not take into account the analgesic drug infusion, this variable will be manually regulated by the anesthesiologist, and it will be seen as a disturbance from the controller. In future works, a fractional-order PID controller will be designed for both components of anesthesia (i.e., hyponsis and analgesia) by exploiting a MISO system that considers both the propofol and remifentanil flow rates as control actions and the BIS as the only process variable.
## 5 Simulation Results and Analysis
### Performance Evaluation of DOIDS under Different Routing Attacks  
In this section, we simulate and analyze the defense effects of DOIDS under different types of attacks. As shown in Table 3, we tested the impact of five different types of routing attacks on the average hop count of delivered packets, packet delivery ratio, and energy tax respectively. Refer to Section 3 for detailed descriptions of these types of routing attacks.  
We compared the network performance of UWSNs with 10% of malicious nodes before and after the DOIDS response. Refer to Figure 10 in Section 5.3, when no malicious nodes exist on the network, the average packet hop count is 3.37, packet delivery ratio is 96.16%, and energy tax is 6.48 J. Obviously, several types of attacks have different degrees of negative impact on network performance. This is because the Sybil attack can use its multiple identities to repeatedly forward the same packet that falls into the routing loop. The simulation in this paper sets Time to Live as 15 hops; that is, the packet is automatically discarded when the forwarding times exceed 15. Therefore, Sybil attacks can significantly reduce the packet delivery ratio. In addition, the average packet hop count is slightly affected because the discarded packets cannot reach the sink node. The generation of routing loop will increase the forwarding behavior of nodes in the network; so for each packet, the energy tax to reach the sink node will also increase. Thus, we can conclude that Sybil attacks can seriously disrupt normal routing planning. However, under the detection and response of DOIDS, the performance of the network with Sybil nodes is improved. Because of the isolation response in this paper, network performance cannot be restored to a situation without malicious nodes.  
Packets forwarded by the sinkhole node are not easy to fall into the routing loop, but they will disturb the routing because of their routing attraction. Therefore, the existence of sinkhole nodes results in a slightly lower delivery ratio and increases the average hop count and energy tax of delivered packets. A hybrid attack is the alternation of the above two kinds of attacks, with an impact on the network somewhere in between. An on-off attack is a periodic attack that starts and stops at an equal time. They will obviously have less impact on the network than a persistent attack.  
At last, according to Table 3, when 10% of malicious nodes exist in UWSNs, DOIDS has similar response effects on these types of routing attacks, indicating that DOIDS is effective in defending against them. DOIDS can improve network performance after routing attacks.
## 4 Results and Discussion
### The Results of the ADI Mitigation Models
#### 4.2.7 Discussion: Comparative Analysis of the Six ADI Mitigation Models  
In comparing the six ADI mitigation models--GB, LSTM, CNN, ODGB, SGD, and HGB as in Table 31--it becomes evident that LSTM, the CNN, and HGB stand out for their balanced performance across classification and signal quality metrics. LSTM achieved the highest F1 score (0.60) and one of the lowest BER values (0.002), showcasing its effectiveness in both detecting and mitigating interference. The CNN followed closely, excelling particularly in signal clarity, with the highest SNR (\(-13.7\) dB), and HGB offered the best overall classification accuracy (0.70), alongside an F1 score equal to that of LSTM, indicating robustness in diverse deployment scenarios. These three models demonstrate a clear advantage in handling complex, interference-heavy environments typical of TD-LTE networks.  
In contrast, while GB, ODGB, and SGD showed comparatively modest classification capabilities--with lower F1 scores and a slightly higher BER--their performance notably improved with extended configurations and model ensembles. SGD, despite lower classification metrics, achieved a strong SNR (\(-13.2\) dB) and a low BER (0.002), suggesting its suitability for scenarios prioritizing signal recovery over detection precision. Across all models, extended configurations consistently improved the BER and SNR, highlighting the importance of leveraging broader data inputs and ensemble strategies. Ultimately, deep learning models like LSTM and the CNN are best suited for environments where accuracy and adaptability are paramount, while Gradient Boosting and SGD models offer efficient alternatives for more interpretable or lightweight implementations.