esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Cost, Energy, and Throughput Analysis  
4.5.1. Material and Labor Costs  
Table 5 summarizes the per-part costs for FDM and SLA, including material, labor, energy, and depreciation.  
FDM is significantly more cost-effective, with per-part costs approximately 60% lower than SLA. This cost advantage is driven by lower material prices and faster production times.
# Retransmission Avoidance for Reliable Data Delivery in Underwater WSNs
## 2 Related Work
### Summary of Related Work  
In aforesaid state of the art, the major focus of the research community is on the energy savings through multi-hop based routing. However, the features of the existing work differs from each other as per the requirements of the scenario. Such as, depth routing algorithms with single path focus on energy efficiency by ignoring the inevitable threat of void holes results in discontinuity in the network operations.  
In multipath depth based routing schemes, source node looks for the reliability of the data packet. The scarcity of the energy is not taken into the consideration and packets are transmitted from various paths towards the destination resulting in high throughput at the cost of minimal lifetime.  
Void avoidance depth based algorithms consider both parameters; energy and reliability. However, there exists tradeoff in the form of high latency and high energy consumption because when void hole occurs, an alternative route is discovered by broadcasting the beacon messages among the network nodes. In addition, if the alternative route is not discovered then depth of the source node is adjusted and again the configuration is performed which leads to unnecessary energy consumption and degrades the network performance.
# Towards Autonomous Bridge Inspection: Sensor Mounting Using Aerial Manipulators
## Appendix A  
Here, we show detailed proof that the adaptation law (17) is stable. Assuming that THE referent force \(f_{r}(t)\) is constant, \(f_{r}(t)=F_{r}\), the time derivatives of Equation (16) are:  
\[\dot{x}_{r}(t) =\dot{\kappa}(t)F_{r}+\dot{x}_{e}(t), \tag{18}\] \[\dot{x}_{r}(t) =\dot{\kappa}(t)F_{r}+\dot{x}_{e}(t),\]  
while the derivatives of Equation (13) yield:  
\[\dot{x}(t) =\frac{-\dot{\kappa}(t)}{k_{e}}+\dot{x}_{e}(t), \tag{19}\] \[\dot{x}(t) =\frac{-\dot{\kappa}(t)}{k_{e}}+\dot{x}_{e}(t).\]  
By susbstituting Equations (18) and (19) into Equation (10), the dynamics of the contact force error can be obtained as  
\[m\ddot{e}(t)+b\dot{e}(t)+(k+k_{e})e(t)=g(t), \tag{20}\]  
where:  
\[g(t)=F_{r}[k(1-k_{e}\kappa(t))-k_{e}(b\dot{\kappa}(t)+mk(t))], \tag{21}\]  
and \(x=x_{c}\). The adaptation law thus determines the dynamics of the adaptation parameter \(\kappa(t)\) and defines the dynamics of the contact force error. Formally, the adaptation law should enforce \(g(t)\to g^{*}\) such that \(e(t)\to 0\) and \(\kappa(t)\to 1/k_{e}\).  
For the [PERSON] candidate:  
\[V(t)=\frac{1}{2}\Big{[}p_{1}e(t)^{2}+p_{2}\dot{e}^{2}(t)\Big{]}+\frac{1}{2 \gamma}\big{[}g(t)-g^{*}\big{]}^{2}, \tag{22}\]  
with \(p_{1},p_{2}\) and \(\gamma\) as positive parameters, the condition \(\dot{V}(t)\leq 0\) yields:  
\[\frac{2}{\gamma}g(t)\dot{g}(t)+2g(t)[p_{1}e(t)+p_{2}\dot{e}(t)]-\frac{2}{ \gamma}\dot{g}(t)g^{*}\leq 0. \tag{23}\]After reordering, we obtain:  
\[\dot{g}(t)[g(t)-g^{*}]\leq-\gamma\sigma(t)g(t), \tag{10}\]  
where \(\sigma(t)=[p_{1}e(t)+p_{2}\dot{e}(t)]\). By choosing:  
\[\dot{g}(t)=-\gamma\sigma(t)+\gamma_{d}\dot{\sigma}(t), \tag{11}\]  
where \(\gamma_{d}\) is a positive constant, Lyapunov condition Equation (10) becomes:  
\[g(t)\leq g^{*}, \tag{12}\]  
i.e., for the adaptation law to be stable, \(g(t)\) should be bounded. Since \(x_{r},\dot{x}_{r}\) and \(\ddot{x}_{r}\) are bounded, so are \(e,\dot{e}\) and \(\ddot{e}\). Therefore, \(g(t)\) is also bounded, i.e., the condition in Equation (12) is satisfied. The adaptation law is finally obtained by taking the derivative of Equation (11), and substituting \(\dot{g}(t)\) with Equation (11), yields the (17). Parameters \(\gamma\) and \(\gamma_{d}\) dictate the adaptation dynamics. Based on the measured contact force, the error adaptation law Equation (17) estimates the adaptation parameter \(\kappa\) (reciprocal value of the environment stiffness), which is then used in Equation (16) for calculating the referent position \(x_{r}\).
# An Improved Blind Recognition Algorithm of Frame Parameters Based on Self-Correlation
###### Abstract  
The blind recognition of the frame parameter plays a crucial role in frame synchronization in the background of a non-cooperation communication system. This paper proposes an algorithm based on self-correlation on the foundation of existed cumulative filtering algorithm. To overcome high BER, the peak-to-average ratio (PAR) is calculated to improve the algorithm. The simulation results proved that the performance of the algorithm has been improved.  
frame parameters; blind recognition; cumulative filtering; self-correlation; peak-to-average ratio
# Tracking Dynamic Northern Surface Water Changes with High-Frequency Planet CubeSat Imagery
## 6 Conclusions  
By providing near-daily high resolution imagery of large swaths of the world, Planet CubeSat imagery has the potential to transform many aspects of hydrologic remote sensing. The presented water fraction classification and object-based tracking approach performs well in both RapidEye and PlanetScope imagery, enabling tracking of sub-seasonal surface area changes in lakes and rivers, and identification of river-floodplain connections in a complex wetland environment. Other potential hydrological applications for near-daily, near real-time Planet data are numerous and include assimilation of inundation changes into hydrologic models, improvement of flood prediction models, estimation of river discharge from space, and studies of river ice breakup and flood hazards. To encourage scientific use of Planet CubeSat data, we recommend addressing the described limitations of automated cloud masking of Planet imagery, cross-sensor calibration and geolocation accuracy. With Planet imagery now available at sub-daily to weekly intervals globally, once these limitations are addressed, CubeSat imagery will be a valuable resource for studying dynamic water processes from space.  
This research was funded by the NASA Terrestrial Ecology Program Arctic-Boreal Vulnerability Experiment (ABoVE) grant #NNX17 AC60A. [PERSON] is also funded by a National Science Foundation Graduate Research Fellowship. Geospatial support for the WorldView data was provided by the Polar Geospatial Center under NSF OPP awards 1043681 & 1559691. We thank three anonymous reviewers for their constructive comments on this paper.  
[PERSON] and [PERSON] conceived the project. [PERSON] developed the method, performed the analysis and interpreted the results. [PERSON] wrote the paper with assistance from [PERSON] and [PERSON]. [PERSON] and [PERSON] provided technical guidance and [PERSON] performed the analysis projected imaging frequency.  
The authors declare no conflict of interest.
## 2 Miniaturized X-ray/Gamma-ray Imaging Payload  
The instrument is deployed in LEO as technology demonstrator payload (shown in Figure 1) onboard VZLUSAT-2 and is designed for the observation and high-resolution imaging of the hard X-ray and Gamma-ray component (5.0 keV-500 keV) in the cosmic ray field in open space.  
The device consists of two components: the integrated optical collimator in the form of a wide-angle metal element and the focal-plane X-ray imager provided by the high-resolution semiconductor pixel detector Timepix. The assembled instrument has an overall size below 9 cm, power consumption 2 W, and mass below 100 g, including casing and holders (see Figure 1). The payload was designed and built by the Czech company RigakuInnovative Technologies Europe s.r.o. (RITE) including the optical-collimating wide-angle metal unit. The pixel detector in the customized configuration was manufactured and provided by Advacam, Prague, including its equalization and per-pixel energy calibration. The novel architecture of the developed device is given by the unique design of the segmented array of optical-collimators and wide-angle metal element (RITE) and the high-sensitivity and spectral imaging response of the customized high-Z sensor MiniPIX-TPX detector (Advacam).
# Backscatter Communications: Inception of the Battery-Free Era--A Comprehensive Survey
## 3 BackCom: An Effective Solution
### Understanding BackCom
\begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**S.No** & **Period** & **Ref.** & **Main Work** & **Details of Work** \\ \hline
1 & World War II & [48] & Transponder used to identify Foe or Friend (IFF). & Passive radar reflectors were introduced. \\ \hline
2 & October 1948 & [40] & Reflected signals use continuous time modulation. & A gadget was designed that can modulate human voices on reflected light signals. \\ \hline
3 & The Late 1960’s & [9] & Commercialization of RFID. & The first commercial application using RFID-based electronic article surveillance. \\ \hline
4 & July 1963 & [9] & Developed and patented passive RFID transponder. & This device can couple and rectify energy from the electromagnetic field of an interrogator and can transmit signals at the harmonic of the received frequency. \\ \hline
5 & January 1967 & [9] & US patent: inductive coupling based simple and inexpensive interrogator-transponder system. & Repetitive tuning was utilized to load an antenna circuit at the rate of the specific transponder. \\ \hline
6 & August 1975 & [9] & Transponder antenna load modulation. & A novel idea of the transponder antenna load modulation was made known as a simple and effective method of backscatter modulation. \\ \hline
7 & October 1987 & [43] & RFID-based toll collection system came to existence. & An RFID-based toll collection system was created in Alesund, Norway. \\ \hline
8 & The 1990s & [9] & Many standardization activities by different organizations. & The International Standards Organization (ISO), working in 157 countries, started making standards for BackCom. Moreover, the International Electrotechnical Commission (IEC) started to establish BackCom standards for electrical devices, electronics, and other related technologies. \\ \hline
9 & The 1990s & [9] & Used in supply chain management. & The Electronics Product Code (EPC) was used. \\ \hline
10 & 2005 & [49] & EPC Global Standards introduced. & Using silicon technology, cheap and reliable tags became common and global standards were made for EPC. \\ \hline
11 & 2013 & [12] & Ambient  BackCom introduced. & Ambient BackCom was used for surrounding signals for communication. \\ \hline
12 & 2014 & [50] & Bistatic Scatter (BiS). & Architecture was proposed for bistatic scatter type of BackCom. \\ \hline
13 & 2014 & [37] & WiFi BackCom proposed. & Connecting tags with off-the-shelf WiFi devices were conceived. \\ \hline
14 & 2015 & [37] & Full-duplex WiFi backscatter used. & Full-duplex BackCom with a WiFi access point was used to maximize data throughput. \\ \hline
15 & 2015 & [51] & Utilizing Bluetooth signal in BackCom. & Utilizing Bluetooth signals in WiFi BackCom was conceived. \\ \hline
16 & 2017 & [52] & Hybrid BackCom. & Hybrid technologies in BackCom were proposed. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Evolution of BackCom.
# Scheduling Sparse LEO Satellite Transmissions for Remote Water Level Monitoring
### Connectivity for Internet of Remote Things  
This paper addresses the problem of providing inexpensive and energy-efficient satellite IoT links in the context of GNSS-IR monitoring. Such a water-level sensor must be affordable and widely deployable. Wide geographic reach imposes the challenge of data uplink from remote locations to where that data is needed [3]. This limitation of IoT has spawned a subdomain dedicated to solving the issues of bringing IoT to the remote corners of the globe, the IoRT [7].  
There is an abundance of connectivity options for IoT around populated areas. Several standard IoT connectivity options range from cellular technologies to LoRa. Connectivity options for IoRT range from low-power wide area networks (LPWANs) to low-power cellular network standards to geostationary and LEO satellites [8]. Additionally, there have been efforts into unmanned aerial vehicles supporting IoRT [8; 9]. Satellite options are the only proven connectivity options for truly global coverage [8; 10; 11], but only if the cost and energy consumption are kept low enough. Traditional geostationary satellites are always overhead for a fixed earth location, but they are costly, require higher transmission power, and incur around 70 times longer latency than LEO satellites [7; 12].
# Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review
## 3 Results
### A Taxonomy of Hashtag Recommendation Methods  
This subsection addresses RQ2 and RQ3 research questions. There is a lack of a clear taxonomy in the literature that classifies hashtag recommendation methods for tweets. From our literature search, we notice that most of the research papers were focused on the textual content of tweets instead of other data. Moreover, although collaborative filtering methods are the most popular category in the traditional/social recommendation systems, they are seldom used solely in hashtag recommendation. Taking this perspective, we propose an alternative way of classifying hashtag recommendation methods. Figure 3 shows the distributions of the eligible hashtag recommendation papers from 2010 to 2020 with respect to the methods classified under our taxonomy, which comprises three main categories (see Figure 4):  
* text-based methods,
* hybrid user-based methods; and
Text-based methods mainly depend on the textual content of the tweets, such as words, hashtags, URLs, and mentions of all users. This category is further classified into tweet similarity methods, probabilistic methods, classification based methods, graph-based methods and matrix factorization based methods. Hybrid user-based methods involve those that group related users either by their behavioral similarity or social relations to recommend hashtags. Hybrid miscellaneous methods include methods that integrate multiple modalities and factors. The included papers are listed in Table 1. Some methods incorporate more than a feature and so they have more than one * symbol in the table.
# Physical Layer Definition for a Long-Haul HF Antarctica to Spain Radio Link
## 3 System Description
### Hardware of the Receiver  
The receiver hardware is located in Cambrils, a village located 100 km southwest of Barcelona, in a quiet electromagnetic environment. The block diagram of the receiver is shown in Figure 4b.  
The system is able to receive simultaneously from three different antennas. The monopole and the inverted V are both HF antennas with vertical and horizontal polarization, respectively. The third antenna is a Yagi tuned to 14 MHz. This allows performing polarization diversity tests in the whole HF band.  
As the monopole is not a wideband antenna, an antenna tuner is needed, even in reception. For the tuning process, a low-power signal (around 10 W) is injected to the antenna during an interval larger than 10 s. This is the reason why a 30 W amplifier is connected to the DAC which generates the tone at the required frequency. The RF (Radio Frequency) relay switches either the adaptation tone (Tx) or the received signal (Rx). The signals from the three antennas are properly filtered, to avoid aliasing and non-desired signals, and amplified to improve the dynamic range of the system.
_applied sciences_  
_Article_  
**Improved Brain Tumor Segmentation in MR Images with a Modified U-Net**  
**[PERSON] \({}^{1,*}\)\({}^{\copyright}\), [PERSON] \({}^{2}\)\({}^{\copyright}\), [PERSON] \({}^{2,3}\)\({}^{\copyright}\) and [PERSON] \({}^{4,5}\)\({}^{\copyright}\)**  
\({}^{1}\) Department of Biomedical Systems and Informatics Engineering, Yarmouk University, Irbid 21163, Jordan  
\({}^{2}\) King Hussein Medical Center, The Jordanian Royal Medical Services, Amman 11885, Jordan;  
[EMAIL_ADDRESS] (M.A.); [EMAIL_ADDRESS] (A.R.)  
\({}^{3}\) The Institute of Biomedical Technology, AI-Balqa Applied University, Al-Salt 19117, Jordan  
\({}^{4}\) Faculty of Electrical Engineering & Technology, Pauh Putra Campus, Universiti Malaysia Perlis (UniMAP),  
\({}^{5}\) Centre of Excellence for Advanced Computing, Pauh Putra Campus, Universiti Malaysia Perlis (UniMAP),  
Arau (02600), Perlis, Malaysia  
\({}^{*}\) Correspondence: [EMAIL_ADDRESS]  
**Abstract: Detecting brain tumors is crucial in medical diagnostics due to the serious health risks these abnormalities present to patients. Deep learning approaches can significantly improve localization in various medical issues, particularly brain tumors. This paper emphasizes the use of deep learning models to segment brain tumors using a large dataset. The study involves comparing modifications to U-Net structures, including kernel size, number of channels, dropout ratio, and changing the activation function from ReLU to Leaky ReLU. Optimizing these parameters has notably enhanced brain tumor segmentation in MR images, achieving a Global Accuracy of 99.4% and a dice similarity coefficient of 90.2%. The model was trained, validated, and tested on many magnetic resonance images, with a training time not exceeding 19 min on a powerful GPU. This approach can be extended in medical care and hospitals to assist radiologists in identifying tumor locations and suspicious regions, thereby improving diagnosis and treatment effectiveness. The software could also be integrated into MR equipment protocols.**  
**Keywords: brain tumors; deep learning; U-Net; segmentation; MRI**
## 3 Results and Discussion
### DSR test  
The asphalt rutting factor (G*/sin (\(\delta\))) was developed by the SHRP in the 1990s and was mainly used as an index in performance evaluation at high temperatures. A criterion specified by Superpave was G*/sin (\(\delta\)) was higher than 1 kPa for fresh asphalt binders. The asphalt rutting factor (G*/sin (\(\delta\))) of different types of asphalt binder at different temperatures is shown in Figure 9. It could be noticed that the asphalt rubber experienced higher G*/sin (\(\delta\)) than the virgin asphalt. When the temperature was greater than 65 \({}^{\circ}\)C, virgin asphalt did not meet the criterion, and high temperature performance was not satisfactory. Meanwhile, the asphalt rutting factor (G*/sin (\(\delta\))) of asphalt rubber remained higher than 1 kPa and satisfied the requirement, showing a better high temperature performance. Therefore, the addition of crumb rubber could significantly improve the rutting resistance of the asphalt and make positive improvement to its high temperature performance.
## 3 Method
### Algorithmic Process  
The algorithm optimizes the model fusion process using Q-learning. The base models, parameters, and Q-table are initialized. In each iteration, the models are fused using TIES/Slerp, evaluated using a SOTA LLM module, and rewards are calculated. Actions are selected, and Q-values are updated to refine the parameters. The best-performing model is tracked and returned after all iterations are completed. The flow of the algorithm is illustrated in Algorithm 1.  
```
0: Base models BaseModels = \(\{M_{1},M_{2},\dots,M_{n}\}\)
0: Number of epochs for training: epochs
0: Best_Model and Best_Performance
1: Initialize model parameters and metrics \(\text{E}(\text{P})\) (The base model before fusion was obtained using SOTA LLM evaluation).
2: Initialize Q-table Q for reinforcement learning.
3: Set Best_Model = \(\text{E}(\text{P})\), Best_Performance = \(-\infty\)
0: Training and Optimization:
4: for episode = 1 to epochs:
5: Fuse BaseModels using TIES/Slerp method, adjust model weights.
6: Evaluate the fusion model using SOTA LLM evaluation module for current parameter configuration \(\text{E}(\text{P})\) Calculated from Equation (5).
7: Calculate r using Equation (10)
8: Select action a using Equation (11)
9: Update Q-value using Equation (12)
10: Update Q-value for selected action a in state s.
11: if \(\text{E}(\text{P})>\text{BestPerformance}\):
12: BestModel = current model configuration
13: BestPerformance = \(\text{E}(\text{P})\)
```  
**Algorithm 1**Model Fusion and Optimization with Q-Learning
## 2 AHRS Principles of Operation
Signal \(\dot{X}\) is an angular rate measured by angular rate sensors and transformed to the frame \(F_{v}\). Similarly, the \(X_{\text{COR}}\) signal is the correction signal calculated in the TC correction angle calculation block shown in Figure 1.  
It should be noted that correction is improper in dynamic states; therefore, other correction signals should be considered, or correction should be turned off [11; 14; 33]. If a correction switching system has not been implemented, it would be impossible to use the AHRS on board an aircraft. An important task for ensuring correction quality is the analysis of static conditions. The presented form of the complementary filter is easy to implement in low-cost systems and is sufficient for ensuring the proper behavior of the system as a whole. The proper value of the complementary filter determines the quality of the estimated signal, and the methodology for its tuning will be shown below. The required accuracy of AHRS signals depends on several factors, such as the type of aircraft, its mission, and the control scenario. In [34], the required attitude measurement error is defined as 0.5% of the measurement range.
# TrustShare: Secure and Trusted Blockchain Framework for Threat Intelligence Sharing
## 4 Evaluation and Performance Analysis
### Discussion and Roadmap  
The evaluation confirms TrustShare's effectiveness in delivering scalable, secure, and policy-aware CTI sharing. Future enhancements aim to improve usability, automation, and resilience:  
* Integration with live CTI feeds and real-time analytics pipelines.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Metric** & **TrustShare (DLT)** & **Centralized Baseline** \\ \hline Average Latency (ms) & 70–175 (steady growth) & 40–310 (non-linear spike) \\ Throughput (tx/sec) & 150–540 (scalable) & 300–110 (declines with load) \\ Fault Tolerance & Byzantine Fault Tolerance & Single Point of Failure \\ Trust Assumptions & Distributed validation & Full trust in coordinator \\ Scalability & High (until consensus limit) & Low (coordinator bottleneck) \\ Auditability & Immutable ledger & No native audit support \\ Deployment Complexity & Moderate–High & Low \\ \hline \hline \end{tabular}
\end{table}
Table 8: Comparison between TrustShare and centralized baseline.  
Figure 10: Summary of TrustShare vs. centralized baseline performance.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Security Layer** & **Mechanism Implemented** \\ \hline Identity Management & MSP via X.509 Certificates issued by Hyperledger CA \\ Data Encryption & Ciphertext-Policy Attribute-Based Encryption (CP-ABE) \\ Data Storage Security & IPFS-based encrypted off-chain storage \\ Access Control & Smart contract-enforced policy-based access \\ Anonymity & Optional ring signatures (FCsLRS) for contributor privacy \\ \hline \hline \end{tabular}
\end{table}
Table 9: Key security features in the TrustShare framework.  
* Graphical policy management interface.
* Automated certificate renewal workflows.
* Enhanced auditing and threat simulation modules.
* Extended testing under adversarial network conditions.  
These improvements will further strengthen TrustShare's readiness for operational deployment in collaborative cybersecurity environments.