esa-sceva/satcom-chunk-collection huggingface dataset:
# Opportunistic and On-Demand Network Coding-Based Solutions for LPWAN Forwarding
## 7 Conclusions and Future Works  
We presented opportunistic and on-demand (OOD) and opportunistic and on-demand network coding (OODC) forwarding to extend LPWAN coverage and increase its reliability while not degrading the network capacity. From the conducted experiment, we found out that the network resources are  
Figure 11: Performance evaluations between OD and OODC.  
Figure 10: Measurement of energy consumption.  
essential in LPWAN. Therefore, it is necessary to optimize the use of the network resources efficiently for better network capacity. Our method successfully reduces unnecessary forwarding, a negative effect of typical forwarding, primarily observed in long-range transmission. Combined with the network coding approach with a header overhead compression, it effectively achieves good reliability performance. Consequently, both OOD and OODC consume less energy consumption.  
A forwarding mechanism that overcomes the hidden node problem should be considered in future work, particularly for transmission between relays. Moreover, RSSI-based priority is insufficient for facilitating improved reliability and efficiency. Without considering the workload, it can put a burden on a particular relay. The assumption of unlimited buffer size is also an issue in the current work. Lastly, a physical test for proof-of-concept validation is required.  
Conceptualization, D.T. and J.D.K.; methodology, D.T. and J.D.K.; software, D.T.; validation, D.T., J.H., D.H.K. and J.D.K.; formal analysis, D.T., S.B. and J.D.K.; investigation, S.B. and J.H.; resources, D.T.; data curation, D.T.; writing-original draft preparation, D.T.; writing-review and editing, D.T., S.B., J.H., D.H.K. and J.D.K.; visualization, D.T.; supervision, J.D.K.; project administration, D.H.K. and J.D.K.; funding acquisition, D.H.K. All authors have read and agreed to the published version of the manuscript. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2020R11 IA306594711). The authors declare no conflict of interest.
# A Real-Time BLE/PDR Integrated System by Using an Improved Robust Filter for Indoor Position
###### Abstract
To inhibit the outliers from the BLE fingerprint method, a robust filter based on EKF was proposed to compensate for the gross error in the real-time positioning procedure. Our contributions are as follows:  
1. We found that the errors of the BLE fingerprint method are not only related to the signal fluctuation but are also affected by scanning numbers of BLE beacons after statistically analyzing the real-time signal data in a harsh environment. When the scanning BLE beacon numbers are few, coarse errors will more likely occur;
2. We found that the accuracy of the heading is also affected by the motion states of the pedestrian. An improved Mahony complementary filter is introduced to keep the heading angle stable by adaptively changing the control parameters in the filter after considering the different people's motion states;
3. To meet the demand of real-time position and considering the computational load of the smartphone, we adopt the EKF method to solve the nonlinear fusion problem to combine PDR with the BLE fingerprint position method to provide the real-time position service. To cope with the gross error caused by the BLE fingerprint method in a harsh environment, a robust filter based on the EKF was proposed. The robust filter detected the gross error at different granularity by constructing a robust vector changing the observation covariance matrix of the extended Kalman filter (EKF) adaptively when the application is running. The experimental results demonstrate that the proposed method has better performance at position accuracy and stability. The remainder of this paper is organized as follows: Section 2 is about the related works of the BLE-based position, self-contained position, and fusion position algorithms in detail. Section 3 introduces the BLE fingerprint method and analyzes the error of the position method. PDR method and the heading estimation based on the motion state are also introduced in this section. Next, the fusion method EKF and a robust filter are presented as well. Finally, a diagram about the BEL/PDR integrated system localization framework is demonstrated. Section 4 describes the experiments and analyzes the results. Then the discussion of the paper and the conclusions are presented in Section 5 and Section 6.
## 3 Medium Access Control Layer
### Conclusions and Future Challenges  
There are a handful of MAC protocols proposed for the UWSN. However, each protocol tries to solve different issues or gives more importance to one characteristic over another. There are many different applications with many different parameters and requirements, and choosing one MAC protocol over another can be a difficult task. Although there has been some work done on the performance analysis of different MAC protocols for a given application [14], further research should include guidelines to choose between the different MAC alternatives depending on the target application constraints.  
In addition, MAC protocols that require synchronization or localization do not usually take into account the energy consumption of these two services. MDS-MAC [70] is a recently proposed protocol that integrates these two services into its specifications and takes into account the extra energy consumption. Newly proposed protocols that make use of these services should integrate them into their behavior for a complete evaluation.  
Finally, future challenges in the development of MAC protocols for acoustic UWSNs shall include the use of new modem features such as wake-up systems, which can greatly reduce power consumption. Only one protocol, T-Lohi [88], makes use of this new characteristic. The applicability of the wake-up system to the existing MAC protocols needs to be evaluated, and new protocols utilizing this technique shall be proposed.
# Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance
## 3 Methodology and Results
### The Markov Chain Model, the Graphs, and the Eigenvectors
#### 3.2.2 The Graphs  
A graphical representation of the state transitions within the Markov chain of this study is depicted in Figure 1. In a Markov chain, each state signifies a specific event or condition (such as Forum, Assignment, Folder, etc.) that a user can be in. Students move from one event (state) to another based on certain probabilities. These transitions adhere to the rules of the Markov process, wherein the probability of transitioning to the next event depends solely on the current event and not on the sequence of events preceding it. The visual depiction of state transitions aids in comprehending the dynamics and probabilities of transitions between different states (events) within the learning environment. Indicatively, Figure 1 provides a graph with an overview of the probabilities of the student with ID 144 transitioning between different parts of Moodle, showcasing the student's engagement in Moodle during an academic year.  
Figure 1a depicts a simple graph, clearly showing that the student with ID 144 was connected to Moodle for the strictly necessary procedures in their learning process in the specific course. They seem to be quite an inactive student based on his transition behavior. More specifically, in this graph, there is a high probability of transitioning from Assignment to Course (0.58), suggesting that after completing an assignment, users are likely to move to a Course state. Similarly, from Folder there is a high probability of transitioning to Course (0.88). Some sections have probabilities of transitioning to themselves, such as Quiz (0.44), indicating the student might frequently revisit or remain within the Quiz environment. Some transitions have zero probabilities, indicating that certain states do not lead to others. For example, there are no transitions from Assignment to any other section except Course and Quiz. Certain states have relatively high probabilities of transitioning to multiple other states. For instance, Forum has a relatively high probability of transitioning to both Course and itself. Some sections, like Other, have no defined transitions, suggesting they  
Figure 1: Visualization of the transition probabilities between different parts of Moodle: (**a**) an inactive; (**b**) an active student.  
might serve as endpoints or isolated sections within Moodle. Figure 1b corresponds to an active student who moved frequently between all the states in Moodle during the academic year. All the aforementioned knowledge on students' behavior concerning Moodle may be correlated to their successful learning progress or lack thereof, a task we aim to undertake in the following subsections through the calculation of the eigenvectors of the students' transition probability matrices and of specific metrics.
# Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks
###### Abstract
For example, in sparse code multiple access (SCMA), the receiver should know the used codebook sets for UEs that are participating in SCMA transmission and the codebooks should be distinct. However, it not easy to achieve this condition in distributed network environments. Similarly, in interleave-division multiple-access (IDMA), a different interleaver should be assigned to each UE and a receiver should know them for multi-user detection. In this paper, we propose a new peer discovery framework based on trellis tone modulation multiple-access (TTMMA), which is applicable to a synchronized OFDM physical layer of 5G networks. Unlike the conventional method, TTMMA allows several MSs to modulate and transmit their signals on the same resource segment; therefore, TTMMA is indeed a non-orthogonal spectrum-sharing scheme. This mitigates the need for strict collision avoidance and collision detection techniques, in order to simplify the discovery procedure. In addition, the receivers efficiently separate and restore the superposed TTMMA modulated signals using message-passing demodulation. This message-passing demodulation increases the discovery capacity by supporting more MS signal recovery with the same resource usage. Finally, the TTMMA generates a single-tone discovery signal to concentrate the signal energy and fundamentally solves the problem of peak-to-average power ratio (PAPR) of OFDM. It thereby increases the transmission signal power and significantly improves the discovery range compared to existing technologies [24; 25]. The remainder of this paper is structured as follows. In Section 2, we describe the operation of conventional FDMA-based discovery and investigate some of its problems. In Section 3, we show the procedure of TTMMA and then, in Section 4, the method of multi-user detection via message-passing algorithm is described. In Section 5, a performance comparison is performed between the proposed TTMMA and FDMA-based scheme. Finally, we conclude by discussing how the performance of TTMMA can be improved. In this paper, both the conventional and proposed schemes are based on OFDM systems; therefore, the proposed scheme can be specified for most wireless systems with OFDM-based physical layer including LTE, future 5G, or Wi-Fi, and so on. In the following section, our is based on the 3 GPP terms, so the BS is described as Evolved Node B (eNB) and the MS is described as User Equipment (UE).
# Analysis of the Chip Geometry in Dry Machining of Aeronautical Aluminum Alloys
## 3 Results and Discussion
### Chip Thickness (t)  
Several methods have been used to evaluate \(t\) as a function of \(f\). The results are plotted in Figure 13. First of all, \(t\) values have been calculated through the obtained experimental values of \(S\) and \(b\), Equation (6). In addition, \(t\) values can be obtained through the theoretical values of chip thickness before machining (\(t_{0}\)) and the experimental values for \(\zeta\), Equation (7). Finally, a first approximation of the chip thickness values can be obtained through the experimental measurements of \(h_{c}\) and \(h_{v}\), Equation (8) [24].  
\[t = S/b, \tag{6}\] \[t = t_{0}/\zeta = (f\cdot\sin\kappa_{r})/\zeta,\] (7) \[t = (h_{c}\;+\;h_{v})/2, \tag{8}\]  
Obviously, \(t\) values show a trend to increase with \(f\), for all of the methods used and for both alloys. The obtained results, when \(t\) is evaluated by cross-section experimental parameters (\(S\) and \(b\)), are very close to those obtained by longitudinal section experimental parameters (\(h_{c}\) and \(h_{v}\)). However, the results obtained through Equation (7) are further away from this value, when \(\zeta\) is calculated by Equation (2) (considering constant tool geometry parameters). Thus, this experimental methodology allows the production of more accurate values than analytical methods, due to the necessary simplifications used in these last methods.  
For the UNS A97075 alloy, all of the experimental methods used have shown very close results, except for the UNS A92024 alloy, these results are slightly different when the method changes, mainly in the range of higher \(f\). So, in this case, Equation (8) is recommended for calculating \(t\), because the measurement process of \(h_{c}\) and \(h_{v}\) is less difficult than the measurement of \(S\) and \(b\).  
Figure 12: Shrinkage factor (\(\zeta\)) (calculated via Equations (2) and (5)) as a function of feed.  
Figure 13: Chip thickness (\(t\)) as a function of feed (calculated by several methods).
## 5 Performance Evaluation
### Fairness Analysis  
When the number of TCP connections is three and five, the throughput comparison of each flow is given by Figure 7a,b, respectively. With the traditional TCP, the throughput of one flow is close to zero. This is the inherent fairness problem of the IEEE 802.11 MAC protocol. However, by using RECN, TCP flows occupying the channel will slow down their sending rates when they received ACKs with congestion notification. Thus, these starved flows can get the chance to compete for the channel, and then, each flow can access the channel more fairly. Therefore, RECN is able to guarantee better fairness for each flow in multi-hop ad hoc networks.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**TCP Flow Number**} & \multicolumn{2}{c}{**Total Throughput (\(k_{pps}\))**} & \multicolumn{2}{c}{**Average Value of \(R_{FTE}\)**} \\ \cline{2-5}  & **RECN** & **No ECN** & **RECN** & **No ECN** \\ \hline
1 & 244.58 & 232.39 & 0.761 & 0.645 \\
2 & 556.11 & 317.64 & 0.760 & 0.640 \\
3 & 707.89 & 323.81 & 0.758 & 0.646 \\
4 & 640.80 & 399.18 & 0.756 & 0.613 \\
5 & 727.27 & 373.71 & 0.753 & 0.624 \\ \hline \hline \end{tabular}
\end{table}
Table 3: TCP throughput analysis. Compare the two situation: RECN and No ECN.  
Figure 6: Comparison of the \(R_{FTE}\) value (TCP flow number: five).  
In addition, we also have tested the fairness among the TCP flows with different hops. As shown in Figure 8, we increase the number of nodes in the experiment scenario shown in Figure 4 to nine and then set the TCP flows with different hops. The throughput comparison of each flow is given by Figure 8(a),b, respectively. With the traditional TCP, the starved flow still exists. By using RECN, each TCP flow with different hops has the chance to compete for the channel. The experiment shows again that RECN is able to guarantee better fairness for each flow in multi-hop ad hoc networks.  
Figure 8: Simulation scenario with different hops.  
Figure 7: Comparison of fairness with three hops.
## 5 Simulation Results
### Travel Flight  
To measure the effectiveness of the ASC during travel flight, the quadrotor is subjected to a trajectory pattern that involves moving the quadrotor a step in the forward direction (x) by a distance of 3 m, then in the lateral direction (y) by a similar distance, and finally returning the vehicle to the hovering point. The ASC parameters are the same as the ones used for the hovering flight.  
The time histories of the load swing angles are shown in Figures 20 and 21 with and without the ASC. The quadrotor trajectories in the x and y directions with and without the ASC are shown in Figures 22 and 23, respectively. It is observed that the oscillations were reduced when using the ASC. The ISH values are decreased from 3.7238 to 1.8930 when the ASC is implemented amounting to a reduction of about 49.2%. Moreover, the effects on the quadrotor trajectories are very small.  
Figure 19: Time history of the quadrotor position during hover with the ASC.  
Figure 20: Time history of the load swing angle during travel maneuver without the ASC.
## 3 System Implementation
### Active Self-Interference Cancel
#### 3.2.2 Canceler Linearization  
Due to the finite output conductance of the canceler transistors (MN1-4 and MP1-4), the blocker signal at the canceler output generates cross-modulation products with the TX signal, limiting the effective receiver IIP3. To address this issue, a feedback linearization technique is introduced, as anticipated in section II. The feedback resistors (RFI and RFQ in Figure 5) were sized in such a way that a small fraction of the blocker signal appears at the AMPI and AMPQ inputs, generating intermodulation products that cancel out with the input-output cross modulation terms, improving the receiver effective IIP3. Simulation results will be reported in the next section.
## 1 Introduction
### Background and Significance  
The onset of the digital age has ushered in a plethora of technological advancements, among which web development has played a significant role. As the world becomes increasingly interconnected via the World Wide Web, the demand for more efficient, robust, and secure web applications is surging. JavaScript, while integral to web development, is showing its limitations as these applications grow more intricate and demanding. This trend has sparked the creation of WebAssembly (Wasm), an innovative binary instruction format engineered to complement JavaScript by providing a performance profile closer to machine code [1]. Wasm is designed with the purpose of allowing web pages to run high-performance applications efficiently, bringing a new level of dynamism and interactivity to the web [2; 3].  
However, the influence of Wasm extends far beyond traditional web applications [4]. A particularly promising avenue lies in the rapidly evolving field of the IoT [5,6]. IoT connects physical devices with the digital world, forming an interconnected network that allows data exchange and automated control. This technology is transforming many sectors, from home automation and healthcare to industrial systems and smart cities. As the IoT ecosystem expands it poses unique challenges, particularly concerning performance, security, and interoperability.  
The unique characteristics of Wasm make it well-suited to addressing these challenges. Its compact binary format allows for quick transmission and loading, a critical requirement in IoT systems where devices may have limited computational power and network connectivity [7]. Wasm's near-native performance ensures efficient execution, enabling real-time processing of complex tasks. Moreover, its security features help to mitigate potential risks in IoT applications, where vulnerabilities can have serious implications [8, 9, 10].  
The significance of Wasm, therefore, lies not only in its impact on web development but in its potential to revolutionize the IoT landscape. By understanding and leveraging Wasm, we can unlock new possibilities for IoT, making our interconnected world faster, safer, and more efficient.
## 5 Conclusions  
Many important parameters for ICR are measured using the heterodyne beating method. The memory within the DAC of the DSP ASIC is loaded with a sinusoidal waveform. The frequency of the sinusoidal waveform in the X polarization is different from that in the Y polarization. When the difference is more than the linewidth of a laser, a polarization-multiplexed signal is produced at the output of the ICT. The significant advantage of using polarization-multiplexed signal lies in the fact that no active SoP control is needed. An SMF cable can connect the output of ICT to the input of ICR, and one can perform the calibration of ICR using heterodyne beating.  
The raw data from the ADC snapshot is analyzed. The frequency response, 3-dB bandwidth, and gain imbalance are determined. Any imperfections can be compensated in the digital domain through the FIR filter. This simple yet accurate procedure can be carried out during deployment in the field over the lifetime of a coherent transceiver.  
Conceptualization, Q.W. and Y.Y.; methodology, Q.W. and Y.Y.; software, Q.W.; validation, Q.W.; formal analysis, Q.W. and Y.Y.; investigation, Q.W. and Y.Y.; resources, Q.W. and Y.Y.; data curation, Q.W. and Y.Y.; writing--original draft preparation, Q.W. and Y.Y.; writing--review and editing, Q.W. and Y.Y.; visualization, Q.W. and Y.Y. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors also gratefully acknowledge the vigorous encouragement and study support with innovation from [PERSON] at Juniper Networks.  
The authors declare no conflict of interest.  
Figure 15: Frequency response of the ICR integrated in a CFP2-ACO. The calibration is performed using a polarization-multiplexed signal generated by the ICT.
# Data-Aware Path Planning for Autonomous Vehicles Using Reinforcement Learning +
## 3 Problem Formulation
### Reinforcement Learning Formulation
#### 3.2.4 Reward Function (R)  
The reward function \(R\) of our reinforcement learning model is designed to align the agent's actions with the dual objectives of fast route navigation and complete data transfer. The function is defined as follows:  
\[R(s,a,s^{\prime})=\begin{cases}R_{\text{complete}}&\text{if $d^{\prime}=0$ and $x^{\prime}=x_{\text{dest}}$}\\ \alpha\;R_{\text{travel}}(x,x^{\prime})\;+\;\beta\,R_{\text{data}}(d,d^{\prime} )\;-\;\gamma\,R_{\text{punish}}(x,x^{\prime})&\text{otherwise}\end{cases}\]  
where  
* \(R_{\text{complete}}\) is a large positive reward given when the agent reaches the destination \(x_{\text{dest}}\) with no remaining data to transfer (\(d^{\prime}=0\)).
* \(R_{\text{travel}}(x,x^{\prime})\) represents the fractional reward for traveling from node \(x\) to node \(x^{\prime}\), designed to encourage faster routes. The amount of this reward inversely correlates with the travel time or distance traveled.
* \(R_{\text{data}}(d,d^{\prime})\) is the reward for data transferred during the transition from \(d\) to \(d^{\prime}\), structured to incentivize maximum data transfer throughout the journey.
* \(R_{\text{punish}}(x,x^{\prime})\) encompasses penalties for inefficiencies, such as remaining stationary (\(x=x^{\prime}\) and \(d=d^{\prime}\)), revisiting previously visited nodes, or selecting slower routes.  
The scalar weights \(\alpha,\beta,\gamma\) were chosen in two steps. We first expressed the value of a one-second travel delay and a 1 kbit data transfer in the same monetary units, which yielded \(\alpha=\beta=1\). The inefficiency term should discourage route loops but not overwhelm the primary objectives, so we set \(\gamma=0.2\) after a coarse grid check \(\gamma\in\{0.1,0.2,0.3\}\) on the validation logs. Because our return is a potential-based positive sum of atomic rewards, any common scaling of \(\alpha,\beta,\gamma\) leaves the optimal policy unchanged [83]. When \(\alpha,\beta\) were varied in \(\{0.5,1,2\}\) and \(\gamma\) in \(\{0.1,0.2,0.3\}\), the mean episode return changed by less than 4%, showing that the policy is robust to reasonable re-weightings.