esa-sceva/satcom-chunk-collection huggingface dataset:
# An Adaptive Delay-Tolerant Routing Algorithm for Data Transmission in Opportunistic Social Networks
## 2 Related Works  
### The State of the Art of the Routing Algorithm Based on Cache  
Recently, cache-aware opportunistic network routing algorithms have attracted increasing attention from researchers. Various routing approaches have been proposed for various application scenarios. These routing algorithms usually leverage two different strategies to improve network performance: one is cache management, and the other deletes unnecessary messages. Typical representatives for cache management are references [7; 25; 31]. In [25], the author proposes an information cache management and data transmission algorithm and [31] introduces an information transmission probability and cache management method. With the support of the cache management, the two routing algorithms increase the delivery ratio by storing data information in idle nodes that have enough cache spaces. However, because of the ignorance of the remaining energy, the two cache-aware routing algorithms only slightly increase the delivery ratio and cannot decrease the network delay. To this end, reference [7] recommended an energy-efficient method that is utilized to minimize the cache management cost in wireless body area networks (WBANs) [3]. A network cost minimization approach has been proposed to improve the quality of service and synchronously minimizing the network throughput [11] in each communication link of WBANs. The simulation results show a slightly enhancement of network delay because of the lack of an adaptive approach for energy and cache.  
To tackle the issue of limited cache space of nodes, routing algorithms that use the mechanism of deleting unnecessary messages are another important strategy. [PERSON] et al. [10] proposed a Prophet-based routing algorithm [32], which establishes a communication link through the information associated with data duplicate routing policy in opportunistic networks. Combined with the Prophet routing protocol [33], this buffer management mechanism comprehensively considers the cache spaces of nodes, the link-state of nodes, the transmission probability of nodes, and the number of message copied, and then deletes unnecessary nodes cache packet. The biggest problem in this algorithm is that this buffer management mechanism does not improve the average end-to-end delay in opportunistic networks. [PERSON] et al. [34] propose a new data fragmenting algorithm that is used to limit the communication duration and delete invalid data information, and it is suitable for short-duration contact between nodes. The disadvantage of this algorithm is that it does not make good use of the characteristics of cache cooperation between each relay nodes in opportunistic networks.
## 4 Results and Discussion
### Fundamental Period and Relative Modal Mass  
Fundamental periods and relative modal masses for the case study buildings were calculated using Eigen Victor method [13]. Results are focusing on the \(Y\) and \(Z\) directions as they are the directions of interest for translation and rotation response. Also, for the sake of brevity; selected results for one building in each group of the buildings under study are tabulated in this section. The selected modal analysis results are related to building of frequency ratios \(\Omega=1.0\), \(\Omega<1.0\), and \(\Omega>1.0\), in order to demonstrate the differences in torsional response.  
The results show that stiff buildings of torsional to translation frequency ratio \(\Omega\geq 1.0\) exhibit high relative modal mass in \(Y\) direction and little or zero in rotation around the \(Z\)-axis in the first and second fundamental modes. The third mode, representing floor twisting, is characterized by high mass torsional participation ratios around the \(Z\)-axis, along with zero participation in translation modes in \(X\) and \(Y\) directions, as seen in Tables 2-6. On the other hand, flexible buildings with \(\Omega<1.0\) exhibit high relative modal mass in rotation around the \(Z\)-axis (floor twisting) in the first fundamental period. The second and third modes in flexible buildings are characterized with high relative modal mass in \(Y\) direction (or \(X\) direction) translation and nearly zero for rotation around the \(Z\)-axis, as shown in Tables 4, 7 and 8. These results are consistent as buildings with \(\Omega<1.0\) are torsionally flexible, and hence, have high torsional participation in first mode, which is consistent with published literature [8]. Tables 9 and 10 show a consistent response where mass model participation is associated with the otherwise translation modes (1 and 2), for buildings that are torsionally stiff
## 4 Communication Technologies for WSANs Applied to the SG
### From Home Area Network to Wide Area Network  
As it has been pointed out previously in this paper, SGs present a decentralized infrastructure (contrary to classical power grids) that allows the delivery of energy from generation units to the consumers and the integration of renewable energy sources. In this frame, WSANs are a suitable solution that can be deployed over the whole grid (power generation, power delivery and power consumers), to guaranty its reliability in an intelligent way. However, communication technologies are imperative to the correct operation of a WSAN, assuring the transmission of the data measured by sensors and the commands to the actuators [69; 70].  
The objective now is to study the different communication protocols that can be employed in a WSAN that operates in a SG scenario, including MGs whose operation must be managed. As the first step of this analysis, a SG can be generally subdivided in three network levels, as it is shown in Figure 6.  
The main characteristics of each level will delimit the candidate communication protocols:  
* Home Area Network (HAN), dedicated to connect different kinds of devices in the home such as displays, computers and electricity or gas meters. Home automation applications are also placed at the HAN level. In the context of SGs, HANs represent the lowest level of the overall infrastructure  
Figure 6: The three different communication network levels of a SG.  
and permit, for example, to connect smart meters and control devices for distributed renewable sources and Plug-in Hybrid Electric Vehicles, and to implement DR applications. The coverage range of a HAN is usually limited to ten meters.
* Neighborhood Area Network (NAN), which plays the role of gateway between HANs and the upper level. Very frequently, NANs transmit the data information between customer locations, issued from different HANs, and data aggregation points. Therefore, NAN must guarantee a range of around thousands of meters. Besides, the coverage of a NAN is particularly well adapted to the dimensions of medium-size electrical MGs; that is, a MG comprising some buildings (techno poles, residential areas or little villages) or installed in large buildings such as hospitals.
* Wide Area Network (WAN), which constitutes the backbone of SG communication network. The main task of a WAN is to transfer the overall collected data to grid operators, and command messages to the consumers. Thus, WAN must be able to carry large amount of data on wide range. Nowadays, the Internet is the most important WAN, allowing the transmission of high data volumes worldwide.  
Taking into account these three network levels, the next sections will describe the generalities of different communication protocols that can be potentially employed to support the communication needs at each stage.
###### Abstract  
The electrocardiogram (ECG) is relatively easy to acquire and has been used for reliable biometric authentication. Despite growing interest in ECG authentication, there are still two main problems that need to be tackled, i.e., the accuracy and processing speed. Therefore, this paper proposed a fast and accurate ECG authentication utilizing only two stages, i.e., ECG beat detection and classification. By minimizing time-consuming ECG signal pre-processing and feature extraction, our proposed two-stage algorithm can authenticate the ECG signal around 660 us. [PERSON]'s method was used for ECG beat detection, while the Residual Depthwise Separable Convolutional Neural Network (RDSCNN) algorithm was used for classification. It was found that between six and eight ECG beats were required for authentication of different databases. Results showed that our proposed algorithm achieved 100% accuracy when evaluated with 48 patients in the MIT-BIH database and 90 people in the ECG ID database. These results showed that our proposed algorithm outperformed other state-of-the-art methods.  
Keywords: electrocardiogram (ECG); biometric authentication; beat detection; depthwise separable convolution (DSC); ECG ID database; MIT-BIH database +
Footnote †: journal: Applied Sciences
## 2 Metrological Study of the Regulatory Framework on the Occupational Exposure to Vibrations
### CEN/TR 15350:2013 on Estimation Method
#### 3.1.1 Uncertainty  
Estimation methods have several disadvantages both from a practical and a metrological point of view. The main drawback would be the truly high associated uncertainty for such methodology, especially when compared to uncertainties obtained when direct measurements are carried out. The CEN/TR 15350:2013 provides a number of multiplication factors that are to be applied to the declared value of vibrations provided by the manufacturers, which are to be applied in those cases where necessary, as in those equipment analyzed through uniaxial tests rather than triaxial tests, the latter being more commonly employed since 2005. The authors of [28] studied the instruction manuals of 1822 tools from two of the most representative manufacturers in the market. As of 2005, more than 70% of the manuals analyzed provided triaxial information, thus complying with the stipulations of the ISO 20643:2005 standard [29]. With respect to the requirements of the European Directive 2006/42/CE, for the commercialization and commissioning of machinery, as of 2006, more than 80% of the manuals analyzed included all the required information.  
When estimating uncertainty by means of such multiplication factors, uncertainty might dramatically increase. As it is concluded in [27], in general the results obtained in several investigations conclude that the actual values suffered by final operators of the machinery where overestimated when multiplication factors where applied. From a metrological perspective, a vibrations risk assessment based on this method might be affected by high uncertainty values, and, as a result, real level of vibrations might strongly differ from the values employed in the risk assessment, creating a NER as this could overestimate the level of exposure to this risk.  
To this respect, a new version of this document, the FprCEN/TR 15350:2020 [30], will supersede CEN/TR 15350:2013. FprCEN/TR 15350:2020 has been submitted to the vote on TR. Among the main changes related to this work, it stands out that Annex C is now based on harmonized standardspublished after 2007, without the need of multiplying factors; in addition, prior to 2005, the declared emission values for tools based on single-axis should not be used for estimating the daily vibration exposure. The new version of this document is very recent, and as it suggests employing independent harmonized standards, its application and suitability are to be evaluated after it is fully established and applied in actual cases. In any case, this new version does also assume that the daily exposure values have a high level of uncertainty.
# The Evolution and Optimization Strategies of a PBFT Consensus Algorithm for Consortium Blockchains
## 3 An Introduction to Mainstream Consensus Algorithms
### The Mainstream Consensus Algorithms Used in Consortium Blockchains  
The mainstream consensus algorithms in consortium blockchains include DPoS, Kafka, and PBFT, with PBFT being the most widely adopted. This is due to its participation of multiple nodes in jointly validating transaction consistency and its ability to tolerate up to one-third of Byzantine nodes, which has contributed to its widespread recognition.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Author** & **Year** & **Improvement Method** & **Core Mechanism** & **Limitations** \\ \hline [PERSON] [52] & 2021 & Real-time adversarial environment optimization & Dynamic leader reconfiguration to enhance fault tolerance and real-time performance. & Frequent leader reconfiguration may introduce instability and additional overhead. \\ \hline [PERSON] [53] & 2021 & Hyperledger integration & Log replication optimization to improve blockchain throughput. & Log replication efficiency depends on network conditions and node synchronization speed. \\ \hline [PERSON] [54] & 2021 & Halal supply chain blockchain & Multi-channel Raft to enhance transaction traceability. & Multi-channel implementation increases system complexity and may require additional infrastructure. \\ \hline [PERSON] [57] & 2021 & IoT transaction migration framework & MEC integration to reduce latency while maintaining Byzantine fault tolerance. & MEC-based architecture may have scalability limitations due to edge device constraints. \\ \hline [PERSON] [55] & 2021 & IoT weighted Raft & Gateway-based weighted election to prevent Sybil attacks. & Requires an effective weighting mechanism, which could introduce centralization risks. \\ \hline [PERSON] [61] & 2021 & Medical data management & Privacy standard adaptation and optimization of log storage efficiency. & Privacy adaptations may introduce trade-offs between security and accessibility. \\ \hline [PERSON] [56] & 2022 & Supply chain finance Multi-Raft & Weighted node election to balance consortium blockchain load. & Weighted election may favor certain nodes, leading to potential centralization. \\ \hline [PERSON] [58] & 2023 & 6G wireless Raft performance analysis & Quantifying the impact of channel loss on consensus delay. & Performance analysis does not provide solutions to mitigate channel loss effects. \\ \hline [PERSON] [59] & 2023 & Wireless network reliability model & Probability model analysis of node mobility and connection disruption. & Theoretical model; real-world validation is required to confirm reliability predictions. \\ \hline \hline \end{tabular}
\end{table}
Table 6: A comparison of Raft consensus improvements.
## 3 Research Methodology
### Testing Stage II  
After analyzing the results from the first stage, we selected six standout configurations for more extensive testing. These tests primarily focused on measuring latency under simultaneous uplink load generated by the LiDAR. This time, however, two sensor configurations were used: one whose entire traffic could be transmitted without loss across all base  
Figure 3: Visualization of raw LiDAR sensor data. The image shows a point cloud representation of the surrounding environment generated by the sensor’s laser scanning mechanism.  
station configurations, and another whose traffic could only be transmitted without loss by selected configurations. The tests also considered mobility aspects by introducing various levels of additional attenuation, which affected the SNR and consequently influenced the automatic selection of the Modulation and Coding Scheme (MCS). Additionally, different packet sizes were evaluated with respect to their latency.
# Private and Secure Distribution of Targeted Advertisements to Mobile Phones
## 5 Detailed System Description
### Two Users Meet
#### 5.2.2 User Authentication and Logging  
When two registered Contacts meet, their encounter is logged by both clients after the users have authenticated each other with a challenge-response password handshake.  
As shown in Figure 2, the procedure begins with the two users A and B exchanging their User-IDs (\(U_{A}\) and \(U_{B}\)) and two random nonce challenges \(R1\) and \(R2\). User A hashes \(R2\) concatenated with his/her password \(P_{A}\) and sends the result \(H_{A}=h(P_{A},R2)\) to User B. Similarly, User B produces \(H_{B}=h(P_{B},R1)\) and sends it to A.  
Once \(H_{A}\) and \(H_{B}\) have been delivered, User A generates \(H_{B}^{\prime}=h(P_{B}^{\prime},R1)\) where \(P_{B}\)' is his/her originally stored copy of the password that [PERSON] sent when they became Contacts, while User B performs the same operation to calculate \(H_{A}^{\prime}=h(P_{A}^{\prime},R2)\). The two users can now authenticate each other by simply comparing the hash digests \(H_{A}\) with \(H_{A}\)' and \(H_{B}\) with \(H_{B}\)'.
## 5 Conclusions  
A novel approach based on the ion-implantation was implemented for pixel diode isolation for MWIR SLS-based heterostructure photodetectors. The different steps in the simulation and performance of ion-implantation were addressed, and the performance of the planar \(nBn\) and \(pBn\) heterostructure InAs/InAsSb SLS photodetectors were compared with each other and with reference mesa-isolated diodes. The planar fabrication method suggests that, instead of using ion-implantation for diffusion or doping the substrate, it should be used to perform ion-bombardment on substrates to selectively form highly-resistive regions and isolate the pixels from each other. Both devices revealed similar performances, not very far from their mesa-isolated counterpart devices. Overall, the method may have merits to pursue with promising results. There are some relevant concerns about electrical or optical cross talk between the pixels, which might drastically affect the modulation transfer function (MTF) performance of FPAs fabricated by the method, which has to be investigated in further studies. Another appealing subject of the study is to focus on scaling the pixel size down to the level of present interest in FPA applications (around 10 \(\upmu\)m). Changing the design of the devices to suppress the dark current, such as a different form of heterojunction structure with multiple or higher barriers, or using thinner barrier/top contact to allow more effective diode isolation can be another consideration. By optimizing and developing the structure design of the SLS device and ion-implanting process, it is possible to surpass the mesa-isolated device performance for SLS planar devices.  
The research that was reviewed in this paper was performed at Northwestern University and NOUR, LLC. This work was supported through SBIR program by the US Army under Contract No. W909 MY-19-P-0027.  
Not applicable.  
The data that support the findings of this study are available from the corresponding author upon reasonable request.  
**Acknowledgments:** The author would like to acknowledge great help and support from [PERSON] and [PERSON]. The author is also grateful for the support from [PERSON], the director of the Center for Quantum Devices. The author is now with Leonardo DRS.  
**Conflicts of Interest:** The author declares no conflict of interest.
## 4 Simulation Results
### Applications of RTC France PV
#### 4.1.2 Case 2: DD Model of RTC France PV
Figure 8a,b illustrate that the simulated and measured current absolute errors range from 7.69197 \(\times\) 10\({}^{-9}\) to 6.28712 \(\times\) 10\({}^{-6}\), while the simulated and measured power absolute errors range from 1.97225 \(\times\) 10\({}^{-6}\) to 1.4626 \(\times\) 10\({}^{-3}\).
# A New LoRa-like Transceiver Suited for LEO Satellite Communications +
## 3 Proposed Transceiver
### Proposed Synchronization Algorithm
#### 3.3.4 Step 4--Fractional CFO Estimation  
The compensation of the fractional CFO \(\
u\) is mandatory to avoid off-by-one demodulation errors and the degradation of the SNR after the dechriping process. One method to estimate \(\
u\) was described in [27] using a variant of the well-known Schmidl-Cox estimator [30]. This estimator averages the phase differences between samples with the same index from two consecutive chirps carrying the same symbol. Given that the transmittedsignal starts with \(N_{p}\) unmodulated up-chirps of the preamble, an estimate \(\hat{v}\) of \(\
u\) is obtained, after compensating the DR, as follows:  
\[\hat{v}=\frac{1}{N_{p}-1}\sum_{p=1}^{N_{p}-1}\frac{1}{2\pi}\arg\left(\sum_{n=0}^{ M-1}r_{c_{d}}(n,p)r_{c_{d}}^{*}(n,p+1)\right) \tag{31}\]  
where \(r_{c_{d}}(n,p)=r(n+(p-1)M)e^{-j\pi c_{d}n^{2}T_{s}^{2}}\), \(\forall n\in[0,M-1]\). Here, we note that the compensation of the time varying Doppler is mandatory to prevent the changing of the fractional CFO from one symbol to another.
## 3 Optimization Model and Evaluation Indexes  
### Back Propagation Neural Network  
The back propagation neural network (BPNN) is a multi-layer forward and feedback neural network [33; 34], which is composed of the input layer, hidden layers, and output layer. BPNN has unique advantages in dealing with complex nonlinear relationships under the influence of multiple factors with its multi-layer neuron connection and activation function. It continuously trains the samples through the back propagation algorithm to determine the deviation between the predicted output and the actual value. Once the deviation exceeds the expectation, the deviation signal will be propagated backward along the neural network to each network layer, the weight and bias of the neuron nodes will be updated according to the prediction error, and the iteration will be repeated until the expected goal is achieved. Figure 3 is the BPNN topology structure with multiple hidden layers. Although the nonlinear generalization ability of BPNN is strong, it takes a long time to search for the optimal solution by multiple iterative training, the convergence is poor, it is not easy to escape from the local extremum, and the prediction error is relatively large [35; 36]. As such, the traditional BPNN prediction has great limitations in some fields.  
Figure 2: Primary factors and measured height of WCFZ.
## 3 Materials and Methods
### Optical Evaluation
#### 3.2.2 Measuring Equipment and Methods  
Rheological properties were measured with a rotational rheometer (Kinexus lab+, Netzsch, Germany). A 40 mm plate-plate geometry with a sample gap of 0.1 mm was employed in conjunction with a passive solvent trap. Each sample was equilibriated  
\begin{table}
\begin{tabular}{c c c c} \hline
**Variables**Indicators** & **Agglomerates** & **Sedimentation** & **Reported by** \\ \hline Viscosity & High viscosity values (same composition and preparation), high standard deviation & Decreasing viscosity at a constant shear rate & [34; 36; 37] \\ \hline Zeta potential & Low absolute values & - & [1; 38; 39] \\ \hline Particle size distribution & Higher than particle size of single nanoparticles & - & [26; 29] \\ \hline Gray value from optical & Isolated particles & Formation of a sediment, decreasing contrast of the dispersion & [40] \\ \hline \end{tabular}
\end{table}
Table 1: Quantities determining the stability of dispersions.  
at 25 \({}^{\circ}\)C prior to the measurement. A single viscosity measurement was conducted at 80 1/s for 5 min, capturing 61 single point measurements. Zeta-potential measurements were conducted with a zeta potential analyzer (Zetasizer Nano ZSP, Malvern Panalytical, Malvern, UK). To enable this, the dispersions were diluted in deionized water at a ratio of 1:250. The pH value was determined with a pH measuring instrument (PH-100 ATC, Voltcraft, Switzerland) with an absolute accuracy of 0.2 pH. The particle size distribution was determined while using a static laser diffraction analyzer (SALD-2201, Shimadzu, Japan). The as-prepared dispersions were diluted in deionized water at a ratio of 1:500. The prepared dispersions were poured into transparent test vessels to enable optical assessment. Camera images (D60, Canon, Japan) of the samples were taken at regular intervals. The images were inverted using GIMP image processing software. The average gray value was calculated from a histrogram analysis. The minimum gray value was 0 and the maximum average gray value 255, with 0 being assigned to black and 255 to white. A low average gray value thus denotes that the dispersion is comparably dark in color. This occurs when the particles are homogeneously distributed in the solution and they have not yet settled down to the bottom of the vessel.