esa-sceva/satcom-chunk-collection huggingface dataset:
# The Impact of Internal Insulation on Heat Transport through the Wall: Case Study
## 2 Methodology
### Measurements Using a Thermal Imaging Camera  
The measurement with a thermal imaging camera was made to identify the state of thermal protection of the external wall. The tests were carried out both from the outside and from the inside. For testing in real conditions, a thermal imaging camera was applied with the temperature measurement range of \(-20\;^{\circ}\mathrm{C}\div+1500\;^{\circ}\mathrm{C}\), resolution of 161,472 pixels, thermal sensitivity for the lens \(42^{\circ}\times 32^{\circ}<\)30 mK, IFOV spatial resolution for the lens \(42^{\circ}\times 32^{\circ}\) of 2.41 mrad/pixel and interval spectral sensitivity of 7.5-14 \(\mathrm{\SIUnitSymbolMicro m}\). In addition, a temperature logger was applied with the measuring range of \(-40\;^{\circ}\mathrm{C}\div+70\;^{\circ}\mathrm{C}\) and accuracy of \(\pm\) 0.2 \({}^{\circ}\mathrm{C}\), as well as a humidity logger with the range of 0-100% and accuracy of \(\pm\)2%.  
The tests comprised the registration of temperature distribution on wall surfaces from the inside and outside. As part of the measurements, temperatures at selected characteristic points  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of Material** & **Thermal Conductivity \(\lambda\)** & **Thickness d [m]** & **Resistance R [m\({}^{2}\)K/W]** \\ \hline Inner side of the envelope & & & 0.13 \\ Cement-line plaster & 0.820 & 0.015 & 0.020 \\ Prefabricated wall & 2.300 & 0.350 & 0.150 \\ Outer side of the envelope & & & 0.04 \\ \multicolumn{3}{c}{**Total**} & **0.340** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of thermal resistance for the longitudinal wall—the existing state.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of Material** & **Thermal Conductivity \(\lambda\)** & **Thickness d [m]** & **Resistance R [m\({}^{2}\)K/W]** \\ \hline Inner side of the envelope & - & & 0.13 \\ Gypsum plaster finish & 0.55 & 0.005 & 0.009 \\ Mineral insulation boards & 0.043 & 0.060 & 1.395 \\ Cement-line plaster & 0.820 & 0.015 & 0.018 \\ Block PGS 800 (wet conditions) & 0.480 & 0.240 & 0.500 \\ Ceramic tiles & 1.050 & 0.030 & 0.029 \\ Outer side of the envelope & & & 0.04 \\ \multicolumn{3}{c}{**Total**} & **2.121** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary of thermal resistance for the gable wall (with mosaic)—after insulation.  
were determined, and the occurring thermal bridges were defined. The measurements outside were conditioned by the absence of rainfall and the reduction of wind speed to \(v<1\) m/s.
# Shared eHMI: Bridging Human-Machine Understanding in Autonomous Wheelchair Navigation
## 4 Results and Discussion
### Discussion
#### 4.3.3 Improving Wheelchair Navigation Clarity for Pedestrian Safety  
Autonomous vehicle-pedestrian interactions often rely on eHMI, which studies show improve pedestrians' safety perception and comfort. For instance, researches indicate that pedestrian awareness of wheelchairs' navigational intentions leads to smoother movements, contrasting with scenarios lacking communication [74]. Our Experiment 2 shows that pedestrian participants found projection interaction effective in improving reaction times and reducing risk, and it was easy to learn.  
However, about 30% of participants reported anxiety when crossing roads as pedestrians, possibly attributable to the current design's insufficient visual feedback for pedestrians. In manual phases, wheelchair users traditionally use vocal, eye contact, and gestures for clear multimodal communication. However, the turning arrow projected by the wheelchair while bypassing pedestrians, overlapping with the main navigation path on the same plane, may diminish the readability of the interface for pedestrians due to inadequate perceptual directness. This lack of clarity may lead to pedestrians overlooking the interaction, subsequently reducing the confidence of certain participants. In contrast, the wheelchair's projected safety line offers clear and definite indications for pedestrians, enhancing the overall interaction quality. By refining these visual feedback mechanisms, can further aid in interpreting wheelchair behaviors for pedestrians, increasing interaction safety and efficiency.
# Exploiting Concurrent Wake-Up Transmissions Using Beat Frequencies
## 3 Concurrent Wake-Up Message  
As introduced above, one of the major challenges of ultra-low power wake-up receivers is their low sensitivity. Due to this, they are susceptible to signal outages caused by fading channels, and their input signal quickly goes below their sensitivity threshold. As shown in the previous Section 2, constructive interference can improve the reliability of transmissions.  
When two senders transmit the same message simultaneously to a common receiver, constructive or destructive interference can happen. Constructive interference helps the common receiver detect a message and improves the reliability of the transmission [14]. Considering the example given  
Figure 4: Overview of Zippy.  
Figure 5: Schematic of an on-off keying-modulated message that implements high-frequency carrier signal frequency randomization.  
in Figure 6, Node-1 and Node-2 simultaneously send a wake-up message to Node-3 to achieve constructive interference.
## 4 DA Experiments
### Experiment Characteristics  
Six different experiments were conducted to assess DA performance:  
* **Free-Run**: Model simulation without assimilation;
* **Base-Test**: The assimilation of the Eulerian velocities obtained from eight Lagrangian drifter data released within the straight section of the channel between points A and B (Figure 1). The assimilation process initiates with a sampling period \(\Delta\)t = 1 min, which corresponds to the time step of the model, so the assimilation is undertaken at each model time step. This experiment is designed to study the DA performance on the velocity estimates subject to the availability of velocity information during the drifter travel time;
* **Ensemble-Test**: To assess the impact of the number of ensemble members, five values for ensemble size were analysed: 5, 10, 25, 50 and 100. Various ensemble sizes were selected to gain the optimum size considering a trade-off between computational cost and accuracy;
* **Frequency-Test**: A series of experiments was performed maintaining the same configuration as in Base-Test, using sampling period \(\Delta\)t varied as 1, 2, 5 and 10 min.
* **Density-Test**: To examine the effect of the number of drifters deployed, two experiments, in addition to Base-Test, were performed with four and two drifters released in the straight section of the lake;
* **Validation-Test**: To validate the DA performance with a different set of data (i.e., six non-assimilated drifters).
###### Abstract  
Developing effective and eco-friendly antiparasitic drugs and insecticides is an issue of high importance nowadays. In this study, we evaluated the anthelminthic and insecticidal potential of the leaf essential oil obtained from _Origanum syriacum_ against the L3 larvae of the parasitic nematode _Anisakis simplex_ and larvae and adults of the mosquito _Culex quinquefasciatus_. Tests on _A. simplex_ were performed by standard larvicidal and penetration assays, while mosquito toxicity was assessed relying on larvicidal, tarsal contact, and fumigation tests. To shed light on the possible mode of action, we analyzed the oil impact as acetylcholinesterase (AChE) inhibitor. This oil was particularly active on L3 larvae of _A. simplex_, showing a LC\({}_{50}\) of 0.087 and 0.067 mg mL\({}^{-1}\) after 24 and 48 h treatment, respectively. _O. syriacum_ essential oil was highly effective on both larvae and adults of _C. quinquefasciatus_, showing LC\({}_{50}\) values of 32.4 mg L\({}^{-1}\) and 28.1 mg cm\({}^{-2}\), respectively. Its main constituent, carvacrol, achieved larvicidal LC\({}_{50(90)}\) of 29.5 and 39.2 mg L\({}^{-1}\), while contact toxicity assays on adults had an LC\({}_{50(90)}\) of 25.5 and 35.8 \(\mu\)g cm\({}^{-2}\), respectively. In fumigation assays, the LC\({}_{50}\) was 12.1 \(\mu\)L L\({}^{-1}\) after 1 h and decreased to 1.3 \(\mu\)L L\({}^{-1}\) in 24 h of exposure. Similarly, the fumigation LC\({}_{50}\) of carvacrol was 8.2 \(\mu\)L L\({}^{-1}\) after 1 h of exposure, strongly decreasing to 0.8 \(\mu\)L L\({}^{-1}\) after 24 h of exposure. These results support the folk usage of Lebanese oregano as an antiparasitic agent, providing new insights about its utilization for developing new effective and eco-friendly nematocidal and insecticidal products.  
anisakiasis; contact toxicity; enzyme inhibition; fumigation toxicity; larvicide; mosquito control; penetration assay 2019
## 4 Related Work
### Battery Integrity Security  
Unlike a stationary terrestrial base station, the UAV base station operates on battery energy. The battery energy introduces a unique denial-of-service (DoS) vulnerability, beyond targeting the more traditional networking and computing resources (such as those exhausting the networking bandwidth or the networking connections/states), which can be exploited by an energy-targeting DoS threat to drain the battery. Previous research includes battery-depletion DoS threat studies against drones or UAVs [11; 46; 54; 55; 56], which are especially related to our work in the hardware platform (flying base station is based on the UAV drone for mobility control and implementation). Because the mobility is constrained to the battery re-charging stations, disrupting the optimal connectivity provision, a DoS can disrupt the availability of the flying base station's operations. The battery-draining DoS has been more widely been studied in other wireless computing/networking contexts (wireless applications beyond the flying base station control), including in implantable medical/health devices [12; 57; 58], wireless charging [59; 60], and standardized protocols of WiFi and Bluetooth [59; 61; 62].
## Prototype Bridge and Evaluation Scenario
### Evaluation Scenario  
The prototype bridge was utilized for a full-scale bridge fracture test program comprised of three different experiments depending on the damage levels and loading schemes [11]. In this study, a bridge fracture test result for the ultimate load-carrying capacity was utilized to evaluate the validity of FE bridge models. In this bridge fracture test, girder fracture damage was applied to one of the two girders at the mid-span of the bridge. After applying the girder fracture damage, concrete blocks and a load base simulating multiple truck live loads were applied. As shown in Figure 2a, concrete blocks were placed on the deck and transversely biased toward the fractured girder to induce a maximum positive bending moment at the fracture location. The weight of the blocks used to form the tub shape was 365 kN (82.1 kips). To match the loading points of the concrete blocks with the axles of a standard truck live load, wooden blocks were placed under the concrete blocks. A load base comprised of gravel and dirt was placed inside the tub to apply an additional load until the bridge collapsed. The standard truck live load was comprised of three axles. The front axle load was 36 kN (8 kips) and the middle and rear loads were 142 kN (32 kips). Note that the loading configuration in the bridge fracture test was different from the standard truck live load, although the concrete blocks and load base were intended to simulate multiple standard truck live loads by placing one truck on top of the other. When the total weight of the concrete blocks and load base reached 1614 kN (363 kips), the bridge collapsed, as shown in Figure 2b. The total weight  
Figure 1: Schematic view of the prototype bridge.  
corresponds to approximately five-times the standard truck load (HS-20) specified in the AASHTO Bridge Design Specifications [1].  
As aforementioned, the loading configurations of the live loads mimicked in the bridge fracture test differed from those of the standard truck live load. Therefore, two loading scenarios were used in this study. The first loading scenario followed the simulated loading used in the bridge fracture test. This loading scenario was used to verify the FE bridge models. For this loading configuration, the concrete blocks were modeled with point loads and gravel, including dirt with distributed loads, in the FE simulation. The other scenario followed the loading configuration of a standard truck live load. This scenario was used to evaluate the effects of the external cross-frame on the ultimate behavior of the bridge. In this scenario, the truck axle loads were modeled using point loads. To apply loads until the bridge collapsed, the axle loads were increased proportionally beyond the one-truck loading. Details of the FE models are described in the following section.
# A Full-Duplex LED-to-LED Visible Light Communication System
## 1 Introduction
However, the performance dependency on the wavelengths of a transmitter and a receiver LED has not been studied in detail in the previous studies. Therefore, in this study, we investigate the performance dependency on the wavelengths of a transmitter and a receiver LED, by measuring the rise time and signal-to-noise ratio (SNR) with respect to the color of transmitter and receiver LEDs. Through the investigation, the optimal color set for a transmitter LED and a receiver LED is chosen. With the optimal LED color set, a full-duplex VLC is experimentally demonstrated with a direct-current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) modulation scheme. Furthermore, we discuss distortions and signal losses in the full-duplex LED-to-LED VLC system.
# Smart Contract-Enabled Secure Sharing of Health Data for a Mobile Cloud-Based E-Health System
###### Abstract
Second, blockchain-based access control can obtain traceability and efficaciously address the problem of information leaks that can be brought on by intrepid servers. Third, authentication and user-verifying properties can be achieved by using proof-of-stake smart contracts [10]. Smart contracts can efficiently authorize access privileges to the stockpiling of health data by implementing strict rules regarding access. They can also efficiently identify and stop perceived risks to health connections in a decentralized manner. Finally, using central servers to guarantee fair treatment within and between complex interactions is eliminated when blockchain and smart contract innovations are combined. All networked agencies on the blockchain system will have a replica of smart contracts because they are public in the system, giving them equitable authority over all contract-operational processes. We summarize our contributions in this study as follows:  
1. We propose a scalable EHR-sharing mechanism utilizing blockchain technology and the distributed storage of interplanetary file systems (IPFSs) [11] for a cloud-based Internet of Things (IoT) in e-health applications. We have developed a trustworthy access control system to enhance the protection of mutual healthcare data through smart contracts. 2. The performance of the proposed method is analyzed through a compatibility test using a cloud-based IoT configuration. The findings of the evaluation showed that the recommended tactic is applicable to dissimilar e-health situations. 3. Security assessments and several analyses using different evaluation criteria are presented to illustrate the effectiveness of the proposed system compared with existing e-health methods. The remainder of this study is organized as follows. Section 2 discusses the work related to existing approaches to authorization management used for cloud-based EHR distribution. Section 3 discusses the blockchain principles and key elements in detail. Section 4 demonstrates the proposed framework model for a health data exchange method based on blockchains and smart contracts, as well as the working model of an autonomous authentication mechanism for EHR exchange in a blockchain network. The implementation details are presented in Section 5, the performance evaluation is analyzed in Section 6, and the security evaluation is presented in Section 7. A discussion is provided in Section 8. Finally, the conclusions are presented in Section 9.
# Using Tablets to Teach Basic Literacy Skills to Kindergarten Students: A Case Study
## 5 Discussion
### Limitations and Future Work  
The study presents several limitations that need consideration. An important one is the sample size; a larger one would significantly improve the findings' reliability and robustness. The fact that the study's applications were not developed by professionals, might also had an impact on the results. Additionally, the young age of the respondents raises questions about the accuracy of their responses. The research's concentration on kindergarten students and a particular subject limits the broad applicability of the results. Furthermore, the number of sessions conducted may fall short of producing substantive conclusions. While the study compared tablets with conventional materials, it did not investigate other technologies or methods, leaving unresolved whether tablets surpass these alternatives. The analysis also accounted for a narrow range of factors influencing learning outcomes; including a broader spectrum could have enriched the understanding of critical elements affecting learning through tablets. The instructional approach employed may serve as a limiting factor; it is plausible that alternative teaching methodologies could have yielded different outcomes.  
Future investigations are strongly encouraged to address these limitations to derive more reliable insights. Expanding the demographic scope to include more diverse socioeconomic groups and educational backgrounds, alongside larger sample sizes, will enhance the understanding of shared and differing experiences with tablets. It is recommended to explore additional literacy domains and application types. Researchers should also consider integrating factors like cognitive load, application quality, and application design principles to gain a better understanding of elements critical to learning outcomes when using tablets. Incorporating qualitative data through interviews and observations will also contribute to a more comprehensive perspective. Furthermore, studies with limited session numbers are susceptible to the \"novelty effect\", potentially distorting findings; thus, longitudinal studies are crucial for a more in-depth exploration of tablets' educational potential. Although the study accounted for variables like sex and prior knowledge, limitations in the statistical procedures prevented the detailed quantification of the impact of these factors; therefore, future studies should examine the impact of such factors. Lastly, given that developmental stages significantly influence outcomes, as suggested in existing literature, future research should be specifically structured to investigate the impact of this factor.
## 3 Methodology
### Data Analysis  
The vector produced in the subsequent step served as input data to the SOM network. Table 1 shows the configuration settings of our SOM network.  
The best matching unit using the Euclidean distance is determined by finding the neuron or unit in a neural network that has the smallest Euclidean distance to a given input vector.  
The Euclidean distance between two vectors is the square root of the sum of the squared differences between their corresponding elements.  
For example, suppose we have a neural network with three output units and we want to find the best matching unit for an input vector \(x=(x_{1},x_{2},x_{3})\), we first calculate the Euclidean distance between \(x\) and the weight vectors of each output unit \(w_{1}=[w_{i_{1}},w_{i_{2}},w_{i_{3}}]\), where \(i=1,2,3\). The Euclidean distance between \(x\) and \(w_{i}\) is given by \(d_{i}=\sqrt{\sum_{j=1}^{3}(x_{j}-w_{i,j})^{2}}\) We then select the output unit with the smallest Euclidean distance as the best matching unit, that is the unit \(i\) that minimizes \(d_{i}\). \(Bestmatchingunit=argmin_{i}d_{i}\).  
The concept of the Euclidean distance is used to group the features according to the best neuron or winning neuron with the Best Matching Unit (BMU) approach.  
Once the input vectors have been produced, the training of the SOM begins and lasts until all training data have been utilized. The SOM training process is elaborated in Algorithm 2. The result of the training is a rectangular grid of nodes or neurons, where each neuron is assigned a weight vector \(W_{s}\).  
```
1:for all vectors in the training data set do
2: Provide the vector as input to the SOM
3: Find the best matching unit within the SOM
4: Find the neighbors of the best matching unit
5: Update the best matching unit and its neighbors
6:endfor
```  
**Algorithm 2** The SOM training process
## 4 Discussion  
The flooding event that occurred in Grandate in November 2014 pointed out the need to understand the hydrogeological system in this area and to conceive drainage interventions to lower and control groundwater levels.  
The mathematical model, which was calibrated in an unsteady state as well as using the levels that were registered in the piezometer that was located in the flooded area since March 2016, was used to forecast the system behavior in three different scenarios:  
Scenario 1 (Business As Usual: 2014 rainfall, no interventions are simulated)--Starting from the calibrated situation, the recharge values of 2014 were set in the model and the year was simulated. Thus, the model was used to analyze the behaviour of the system in case a very rainy year, such as the year 2014--listed among the first 10 rainiest years of the last century--should occur again. Figure 14a shows the model results at the end of the month of November in terms of flooded cells at ground level, 4.5 m depth and 8 m depth.  
Figure 14: Results of Scenarios 1 (a), 2 (b), and 3 (c); wells (circles) and flooded zones (grey cells) at different depths.  
Scenario 2 (2014 rainfall and continuous extraction)--The same situation of Scenario 1 is simulated, however now the 8 wells are implemented in the model, pumping out continuously throughout the simulation time. The result is set out in Figure 14b, which shows the flooded cells at ground level, 4.5 m depth and 8 m depth at the end of the month of November. As expected, the well pumping keeps groundwater level below the 4.5 m from ground level and the area is just partially flooded at 8 m depth. It should be recalled that a very peculiar year in terms of rainfall (and then recharge) is simulated.  
Scenario 3 (2014 rainfall and 3 months extraction)--Scenario 2 has been replicated, but here the wells do not work continuously: their activation was presumed in August, about three months before the most critical period in terms of rainfall which, in these zones, is generally November. In fact, from the perspective of the groundwater control systems, to optimize the extraction and to carry it out close to the most critical period might prove convenient in terms of energy consumption and extracted groundwater disposal. The result of this last simulation is shown in Figure 14c, setting out the model response at the end of the 11 th month of the simulation (November). It is still possible to notice the effect of the pumping, which makes it possible to maintain groundwater level below 4.5 m from ground level. The wells' effect is obviously reduced at an 8 m depth from the ground compared to Scenario 2, given that the wells were active for just three months. However, as has already been said, a very exceptional year in terms of rainfall was simulated.