esa-sceva/satcom-chunk-collection huggingface dataset:
# Toughened Vinyl Ester Resin Reinforced with Natural Flax Fabrics
## 2 Materials and Methods  
### Materials  
* DION(r) IMPACT 9400 provided by Polynt spa, Bergamo, Italy  
Specifically modified for improved processing properties, this is a high-performance epoxy novolac vinyl ester resin. This high-crosslink-density resin offers excellent resistance to solvents, chemicals, and acidic, alkaline, and oxidizing environments and provides excellent retention of mechanical properties at elevated temperatures (viscosity: 500 cps).
* DION(r) IMPACT 9500 provided by Polynt spa, Bergamo, Italy  
DION(r) 9500 is a non-accelerated, rubber-modified epoxy-based vinyl ester resin. This resin has a unique combination of properties such as high tensile elongation, good impact resistance, low shrink, low exothermic peak, excellent adhesion, and good chemical resistance. Due to these properties, this vinyl ester is well suited for use as a primer and for constructions exposed to dynamic loads.
* Butanox LPT  
Butanox(r) LPT-IN is a methyl ethyl ketone peroxide (MEKP) (provided by Polynt spa, Bergamo, Italy)for the curing of unsaturated polyester resins at room temperature and higher temperatures. Specially designed for filament winding, it is very suitable for extra slow gelling and marine applications.
* Co 6%  
Cobalt Naphthalene (6% Co) (from Merck, Darmstadt, Germany) is an effective additive that acts as a catalyst to accelerate curing times and improve overall performance in polyesters and epoxies.
* Flax fiber: FLAX DRY BL300, twill (from FiberTech, Varese, Italy)  
It is suitable for use as a surface or backing because of its relatively smooth surface texture but slightly heavier weight. The roll width is 1000 mm, and the thickness is 0.3 mm (basis weight: 300 g/m\({}^{2}\)). As described in its datasheet, the density of the fiber is 1.29 g/cm\({}^{3}\), and the mechanical properties are the same for both the warp and the wert directions, as this type of woven fabric is balanced. Elastic modulus, stress at break, flexural modulus, and flexural strength are 11.2 GPa, 113 MPa, 8.9 GPa, and 126 MPa, respectively.  
Going into detail, this study considered an initial selection and characterization of different curing and post-curing protocols for Dion 9500 with 2% of MEKP, as indicated by the datasheet. Furthermore, the analysis and characterization of Dion 9500 with 1% of MEKP was done in order to increase the gel time to facilitate the vacuum bagging process. In addition, the characterization of Dion 9400 as an unmodified reference was studied to understand the mechanism and the extent of the rubber toughening mechanism. Different curing cycles were analyzed, and the best one was chosen based on the results of the characterizations of the resins; woven flax and glass were tested as reinforcing materials. Finally, composites were realized via the vacuum bagging process, and the mechanical properties were studied to detect if flax composites can substitute for glass composites in high-performance applications; the properties' differences were evaluated.
## 5 Results of Comparing Algorithms
### Effectiveness Comparison
As can be seen in Figure 6, the AMOSA, MSPSO, and NSGA-II show more evenly and smoothly distributed solutions along the Pareto front compared to MOABC. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multicolumn{2}{c}{**Fcapacity**} & \multicolumn{2}{c}{**Fdistance**} \\ \cline{2-5}  & **t-Statistic** & \(p\)**-Value** & **t-Statistic** & \(p\)**-Value** \\ \hline AMOSA-MOABC & \(-\)3.223 & 0.001 * & \(-\)0.393 & 0.852 \\ AMOSA-MSPSO & \(-\)17.183 & 0.000 * & \(-\)19.693 & 0.000 * \\ MOABC-MSPSO & \(-\)13.960 & 0.000 * & \(-\)19.300 & 0.000 * \\ AMOSA-NSGA-II & \(-\)9.043 & 0.000 * & \(-\)11.549 & 0.000 * \\ MOABC-NSGA-II & \(-\)5.820 & 0.000 * & \(-\)11.156 & 0.000 * \\ MSPSO-NSGA-II & 8.141 & 0.000 * & 8.144 & 0.000 * \\ \hline \hline \end{tabular}
\end{table} 
Table 3: \(p\)-value of pairwise comparison of algorithms vs. t-statistic value of capacity and distance function. Figure 5: Box plot of the average of the cost of four algorithms. (**a**) displays the full range of variation of the fitness values of capacity function, (**b**) displays the full range of variation of the fitness values of distance function. The outlier symbols (\(\Box\), *) represent extreme values in data set of each method.
# Margin and Shared Proxies: Advanced Proxy Anchor Loss for Out-of-Domain Intent Classification
###### Abstract  
Out-of-Domain (OOD) intent classification is an important task for a dialog system, as it allows for appropriate responses to be generated. Previous studies aiming to solve the OOD intent classification task have generally adopted metric learning methods to generate decision boundaries in the embedding space. However, these existing methods struggle to capture the high-dimensional semantic features of data, as they learn decision boundary using scalar distances. They also use generated OOD samples for learning. However, such OOD samples are biased, and they cannot include all real-world OOD intents, thus representing a limitation. In the current paper, we attempt to overcome these challenges by using Advanced Proxy-Anchor loss, which introduces a margin proxy and shared proxy. First, to generate a decision boundary that has the high-dimensional semantic features of training data, we use a margin proxy for learnable embedding vectors. Next, the shared proxy, which is shared by all In-Domain (IND) samples, is introduced to make it possible to learn the discriminative feature between IND intents and OOD intent, ultimately leading to the improved classification of OOD samples. We conduct evaluations of the proposed method using three benchmark datasets. The experimental results demonstrate that our method achieved an improved performance compared to the methods described in previous studies.  
deep learning; dialog system; metric learning; natural language processing; out-of-domain intent classification; text classification +
Footnote †: journal: Applied Sciences
# A Simple Estimation Method of Weibull Modulus and Verification with Strength Data
## 4 Material Strength Data
### Fibers  
Table 5 lists the data of fibers, which constitute the largest group in this Weibull modulus survey. Datasets for over 90 types of fibers have been collected. About half of them are for carbon fibers, reflecting the high interest in their properties. For these datasets, the average of m\({}_{\rm obs}\)/m\({}_{\rm est}\) is 1.007, and the standard deviation is 0.072. The value of m\({}_{\rm obs}\)/m\({}_{\rm est}\) is close to unity. Data trends on Figure 7 show less data scatters than other similar plots. This trend is better seen in Figure 7b, and less than 20% of the data points showed a deviation higher than \(\pm\) 0.1. The m values are confined to a range of 2 to 11, implying more brittle behavior even compared to ceramics, and reflecting the higher strength levels of fibers. Only four datasets exceeded m \(\approx\) 10 [70; 71; 72]. Natural fibers included showed mostly low m values below 5, while those above 8 were either carbon or ceramic fibers made in recent years. Data for glass fibers became scarce after the 1970s, while early data lacked some of the parameters that were needed here, and only 10 datasets were found. Again, reported Weibull modulus studies often omitted \(<\)\(\alpha\)\(>\) and S data. Figure 6: (**a**) Plots of m\({}_{\rm obs}\) (red + symbol) and m\({}_{\rm est}\) (blue dot) vs. \(<\)\(\alpha\)\(>\)/S for the data of ceramics and glasses. (**b**) Plot of m\({}_{\rm obs}\)/m\({}_{\rm est}\) (blue dot) vs. \(<\)\(\alpha\)\(>\)/S for the same.
## 4 Results and Discussion
### Discussion about Strictly LoRaWAN, LoRaMESH or Hybrid Networks  
As seen in the results obtained, the LoRaWAN protocol obtained better distances and greater range, however it was more affected as the distance increases and obstacles become more and more important variables for the effectiveness of communication or not. While in the LoRaMESH protocol implemented by Radioenge, it obtained a shorter distance, but was able to maintain communication significantly affecting the efficiency of communication. Thus, LoRaWAN becomes a better option to be used in cases where gateways will be spread throughout the city to promote coverage for SMs with LoRaWAN modules as well as hybrid DAPs that will play the role of connecting to a mesh network present in certain places. Meanwhile the LoRaWAN protocol becomes more suitable to promote a more controlled infrastructure in terms of distances between consumers, such as condomiums, public buildings and industries, as well as sets of houses that are clustered in quantity but in a specific region. However, this protocol will not be possible to use, with the configurations and results obtained, without the presence of LoRaWAN, in this case, hybridizing the network, unlike LoRaWAN.  
In the case of the hybrid network, the main contribution is in the implementation of the DAP, because it will mediate between the mesh network and the LoRaWAN network. Furthermore, the results of a hybrid network are directly linked to the results of each network strictly, that is, if a network composed of LoRaMESH is operating efficiently and with connectivity capable of promoting communication, when hybridizing this network, the devices will operate in the same way, since the only difference is that the coordinator will no longer be alone, but with the final LoRaWAN device. In this case, the hybrid network has limitations, and the main ones are related to Radioende's LoRaMESH protocol, such as not having access to the routing algorithm, distance limitations, as well as this causes more complexity for any extra implementation that has to change something in the main source code. Another important factor about the hybrid network is the implementation of the communication processing between the LoRaMESH coordinator and the LoRaWAN end device, even though it is a serial communication, via cables, the implementation of the packet queue, as well as the processing and temporary storage of this large amount of data, In this study this problem did not arise because the tests were performed with only five SMs, but it is worth analyzing the DAP with a larger amount and verify if it can really operate efficiently, or if it will not support such a large amount of processing and information flow.  
However, the hybrid network allows AMI scalability, a wider coverage range as well as other advantages such as the possibility of using two different topologies to deploy in a real scenario, and this is a relevant contribution, since there are different scenarios and environments that possibly a strictly LoRaWAN or LoRaMESH network will not be able to reach efficiently.
# A Review of Transformer-Based Approaches for Image Captioning
## 5 Vision-Language Pre-Training in Captioning
### VLP in Image Captioning
#### 5.2.11 Universal Captioner  
[PERSON] et al. [112] propose a model that can generate in- and out-of-domain captions characterized by the natural descriptive style and fluency of human captions. Their model trains well on datasets with different descriptive styles and semantic concepts, i.e., non-uniform or heterogeneous sources, and manages to separate the content from the descriptive style. The non-uniform sources are made up of curated datasets as well as weakly labeled or noisy web-scale datasets. A chief goal of the work is to foster the ability to describe more real-world concepts with a high level of caption quality.  
The architecture entails a transformer-based encoder-decoder. The encoding of the images is based on a self-attentive visual encoder [99] and is, therefore, carried out without the need for an object detector. They use a large-scale multi-modal model based on CLIP [53] to extract _pivotal keywords_, which then help to train in a style-aware manner that enables the transfer of semantic concepts between sources. The pivotal keywords are similar in concept to the object tags used in OSCAR [38]; however, they take the style into account. The decoder then jointly takes in the CLIP-based keywords, style and other text to generate the caption in an autoregressive manner. In terms of the objective loss function for training, they only use unidirectional language modeling coupled with a prompting strategy, which highlights the simplicity of their approach. During inference, predictions are conditioned on a dataset indicator parameter, which is chosen according to the desired generation style. Their training is on a dataset of 35.7 million images.
# LoRa Mobile-To-Base-Station Channel Characterization in the Antarctic
## 2 Materials and Methods
### Environmental Factors  
We now discuss the potential effect of environmental factors on our experiments. The full weather report during the measurements is listed below:  
Weather Information from Princess Elisabeth station  
Date : 13/01/2017 Time : 10,00 UTC  
Wind Direction : 84 degrees Wind Speed : 11.2 kt Wind Speed(Max) : - kt  
Visibility : 60 km  
1 st Cloud Layer Clouds amount : Ci Sct type : - Ceiling : - ft  
2d Cloud Layer Clouds amount : - type : - Ceiling : - ft  
Figure 7: Calibration of the receiver’s signal-to-noise ratio (SNR) measurement.  
Humidity : 52.4 % Temperature : -6.2 C Pressure (QFF) : 1004.6 hPa Horizon : VERY GOOD Contrast : VERY GOOD Present Weather : NSW Remarks : -  
Status of Skiway/Runway: VERY GOOD -Last grooming: 10-01-2016 -Surface condition: Compacted snow on firm base (L 1200M) -Visual inspection: 10-01-2016 09:00 UTC [PERSON] Antarctica Usteinen - S71 57' E23 21' Antarctica www.antarcticstation.org  
We have observed that environmental factors did not impact the communication in our measurements. Extreme temperatures do not have an effect on the radiowave propagation from antenna to antenna. Receiver performance may be affected by extremely low temperatures, but these were not present at the time of the measurement. The receiving PC and LoRa receiver were mounted in an unheated metal closet, at a temperature slightly above the outdoor temperature, which was \(-6\ ^{\circ}\)C. However, the receiver is specified to operate correctly at temperatures down to \(-40\ ^{\circ}\)C. Care should be taken that the PC and the microcontroller--which provide the data to the transmitter--are also specified for operation at these low temperatures. The PC that controls the LoRa transmitter was mounted inside the vehicle, where the temperature is \(20\ ^{\circ}\)C. The LoRa transmitter itself was mounted on top of the vehicle, at a temperature of \(-6\ ^{\circ}\)C. According to the specifications, the transmitter also operates correctly down to \(-40\ ^{\circ}\)C.
# A Service-Caching Strategy Assisted by Double DQN in LEO Satellite Networks
## 5 Conclusions  
This paper has addressed the issue of the content-caching strategy in the context of cloud-fog-edge collaboration scenarios in satellite internet services. We proposed a caching prediction scheme that considers the mobility characteristics of LEO satellites to enhance the cache hit rate of fog satellite nodes. Initially, we analyzed the characteristics of LEO constellations and edge users, establishing a network model. Subsequently, we introduced  
Figure 8: Content transmission delay compared to CAFR.  
Figure 7: Content transmission delay with different cache capacities.  
a caching prediction method based on Double DQN to improve the cache hit rate. The simulation results demonstrate that our proposed method can enhance the cache hit rate by 13% compared to baseline schemes. Based on the analysis, it can be concluded that, with the assistance of the Double DQN algorithm, the cache hit rate of edge-user cache requests can be effectively improved, thereby efficiently saving satellite networks' bandwidth resources and reducing content-transmission latency.  
Conceptualization, Y.L. and F.S.; methodology, Y.L. and F.S.; software, Y.L. and F.S.; validation, J.Z., Y.L. and F.S.; formal analysis, J.Z., Y.L. and F.S.; investigation, J.Z., Y.L. and F.S.; resources, J.Z., Y.L. and F.S.; data curation, J.Z., Y.L. and F.S.; writing--original draft preparation, Y.L. and F.S.; writing--review and editing, J.Z., Y.L. and F.S.; visualization, J.Z., Y.L. and F.S.; supervision, Y.L. and F.S.; project administration, J.Z.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are contained within the article.  
The authors acknowledge the contributions of the Aerospace Information Research Institute at the Chinese Academy of Sciences and School of Information and Communication Engineering of Beijing University of Posts and Telecommunications for supporting this work with research facilities and resources.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} SFC & Satellite fog computing \\ Double DQN & Double Deep Q-Network \\ LEO & low Earth orbit \\ IoT & Internet of Things \\ VNI & Visual Networking Index \\ NDN & Named data networking \\ QoE & Quality of experience \\ AP & Access point \\ RL & Reinforcement learning \\ TD & Time difference \\ \end{tabular}
# Analysis of Student Academic Performance Using Human-in-the-Loop Cyber-Physical Systems
## 2 ISABELA Platform
### Data Acquisition System  
In order to achieve and infer the students' behavior, we collected data related to their physical activity, location, sleep, emotions, and sociability. Data acquisition was carried on using three different types of sources:  
1. Mobile phone sensors: We obtained the physical activity of students from the accelerometer and the gyroscope, and the location by using information from WiFi scans and GPS. For the sleep state, we employed the light and the proximity sensors, the alarm information, the phone lock, and the microphone. Finally, for sociability, (a) we used information on the number of SMSs sent and received, calls made, received, and lost; (b) the duration of these calls, the number of different destinations of the calls/SMSs were also collected; and (c) proximity of other devices, via Bluetooth, was also obtained;
2. Questionnaire: The students entered daily information about their sociability state, quality of sleep, amount of study, and emotional state via a questionnaire integrated into the application;
3. Social networks: To infer their emotional status, we used what they post on Facebook and Twitter, including reactions and the number of retweets.
## 4 Conclusions  
In this article, a small-sized four-port UWB MIMO antenna with dual-band rejection features is presented. The proposed design contains four matching octagonal-shaped resonators arranged orthogonally, and the diagonal elements are arranged anti-parallellly. The antenna showed an isolation \(>\)18 dB for the entire operational range. An HCSRR was implanted in the radiating element for notching the interfering Wi-MAX and WLAN frequencies (3.5 and 5.5 GHz, respectively). The simulated and experimental results for gain, S-parameters, isolation, ECC, and radiation patterns were studied. The results validated that the decoupling metal strips used to reduce the inter-element coupling is a simple and efficient approach, and a good diversity response was achieved. The obtained results illustrate that the proposed MIMO antenna could be useful for UWB applications. It can serve as a potential candidate for base station terminals and other wireless communication systems.  
Conceptualization, P.K. and S.U.; methodology, P.K.; software, P.K.; validation, P.K., S.U., and F.A.; formal analysis, P.K.; investigation, P.K.; resources, S.U.; data curation, P.K.; writing--Original draft preparation, P.K.; writing--Review and editing, S.U.; visualization, P.K.; supervision, S.U.; project administration, S.U.; funding acquisition, S.U. and F.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia, through the Fast-Track Research Funding Program.  
The authors declare no conflicts of interest.
## 4 Experimental Setup  
Based on the proposed analytical model, except for the operating condition \(V_{DD}\), \(I_{DD}\), \(V_{GG}\), and \(V_{SS}\), the parameters needed in the calculation are the junction capacitances \(C_{gs}\), \(C_{gd}\), \(C_{gs}\) and \(C_{f}\), the stray inductances of the PCB traces \(L_{bus}\), \(L_{line}\), the parasitic inductances of the terminal \(L_{g}\), \(L_{d}\), \(L_{s}\), \(L_{a}\) and \(L_{c}\), and the static characteristic of power devices: the trans-conductance \(g_{f}\), the internal resistance \(R_{g\_int}\) and \(R_{f}\), the threshold voltage \(V_{th}\), the forward voltage \(V_{f}\), and on-state resistance \(R_{on}\). Apart from the junction capacitances and the parasitic, stray inductances, all the other parameters are temperature dependent. Therefore, it is necessary to build a test platform for the measurement. The approaches to obtain these parameters can be divided into three categories.
# Assessing Cyber Challenges of Maritime Navigation
## 3 Findings
### Regulatory Framework  
_Global_  
The maritime cybersecurity legal issues are complex [40]. In 2017, the International Maritime Organization (IMO) adopted resolution MSC.428(98) on Maritime Cyber Risk Management in Safety Management System (SMS) [47]. The resolution stated that an approved SMS should take into account cyber risk management following the objectives and functional requirements of the International Safety Management Code (ISM Code) [48]. It further encourages administrations to ensure that cyber risks are appropriately addressed in safety management systems no later than the first annual verification of the company's Document of Compliance after 1 January 2021. IMO also developed guidelines on maritime cyber risk management that provide high-level recommendations on maritime cyber risk management to safeguard shipping from current and emerging cyber threats and vulnerabilities. These guidelines highlighted that effective cyber risk management should start at the senior management level [49]. Aligned with both IMO documents, the Guidelines on Cyber Security Onboard Ships were made to provide practical recommendations on maritime cyber risk management covering both cybersecurity and cyber safety [50]. In addition, IMO is preparing, in collaboration with the International Electrotechnical Commission (IEC), a new standard for maritime navigation and radio-communication equipment and systems: IEC 63,154 \"Cybersecurity--General Requirements, Methods of Testing and Required Test Results\" [3, 51].