esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this paper, a maritime communication system based on time-delay overlapping modulation with higher spectral efficiency and a higher communication rate is proposed. The system breaks through the strict orthogonality constraint of the carrier through a simple delay and through overlapping modulation at the transmitter to achieve high-spectral-efficiency non-orthogonal communication. It is shown that spectral efficiency of the TDOM system can be up to 20 times of that of a VDES in a bandwidth of less than 20 kHz, and its communication performance is comparable to that of the VDES. Meanwhile, when occupying the same bandwidth as the VDES, the peak communication rate of the TDOM system can reach up to 6.144 Mbps, which is 20 times that of the VDES. It is worth mentioning that, as a physical layer modulation technique, TDOM technology can be extended to any other communication scenario with high communication rate and spectral efficiency requirements. Future research will be conducted in the following areas. Firstly, similarly to maritime communication systems, the underwater communication also has an urgent need for high spectral efficiency and communication rates. Therefore, deploying TDOM technology in underwater communications is one of the future work directions. However, unlike the maritime multipath channels discussed in this paper, underwater communication channels are more complex. The severe Doppler effect is one of the forms of interferences in underwater communications. Therefore, it is necessary to investigate TDOM systems that can counteract the Doppler shift. In addition, future work should include reducing system complexity and combining the TDOM system with coding techniques to further enhance the communication performance and to advance the practicalization of TDOM.  
Simulation, T.M.; writing, X.D.; writing--review and editing, X.D.; supervision, X.D. and D.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the National Natural Science Foundation of China under Grant 62001077, and in part by the China Postdoctoral Science Foundation under Grant 2019M661075 and Grant 2022T150081.  
Figure 10: Performance comparison of TDOM systems with VDESs.
## 3 Methods
### Heterogeneous Training Management System (HTMS)
#### 3.2.3 Task Management Layer  
Algorithms related to training are executed in units of sub-models, and the results are received and transmitted to the managers of the Context Management Layer.  
1. Task Manager Task Manager issues one task among forward propagation, backward propagation, and optimization for one sub-model. Propagation runs on multi-GPU, and optimization runs on multi-thread. Since an execution context is required to execute a task, it is requested in the Context Management Layer. When the execution context is ready, the manager places parallelized tasks and waits until all the arranged tasks are finished. When all tasks are executed, task completion is notified via the Result Manager, the result is transmitted to the CPU, and no longer needed resources are returned.
2. Result Manager The Result Manager issues an IO task that transfers the results generated using the results of each sub-model from the GPU to the CPU. Furthermore, it operates a Result Queue that stores results asynchronously, calculates information in the Queue, and transmits it to the Context Management Layer.
3. Worker Layer In the Worker Layer, training tasks related to the assigned execution are arranged and executed. In this layer, only one propagation and optimization task can run concurrently. One task consists of several parallelized jobs running in multi-process or multi-thread. Several jobs work by forming a group, and the jobs within the group exchange or collect calculation results via MPI.
# uDMA: An Efficient User-Level DMA for NVMe SSDs +
## 4 Design of uDMA
### Statically Pinned Memory Management  
The statically pinned memory management is shown in Figure 3. It contains three memory block lists, namely (a), (b), and (c). Memory blocks (a) and (b) serve the writing requests of the NVMe SSD. We designed two memory blocks to serve writing requests because of the imbalance between the NVMe SSD's reading and writing. Because the writing speed is relatively slow, the data in the memory block take a long time to write to the NVMe SSD. As shown in the figure, when (a) is full, it is out of service, and the data in it are written to the NVMe SSD in batch. At the same time, (b) begins to serve writing requests. When (b) is full, (a) becomes free. The (c) list illustrated in Figure 3 is designed for reading requests. The principle is based on the feature of reading fast and writing slowly of the NVMe SSD. Assigning one list of memory blocks for reading requests can meet reading requirements while saving memory resources.  
This design has three points: (1) It can reduce the data transfer time, and we described the reasons in detail in the motivation section. (2) It takes up less memory space because the design is oriented toward small data requests. Thus, we only need to fix a few memory blocks to meet the requirements. (3) It fully considers the characteristics of fast reading and slow writing of NVMe SSDs, prepares enough memory space for write requests, and improves the processing efficiency of NVMe SSDs' write requests.
## 2 Hierarchical Sources
### Formal Definition of Hierarchical Source  
Let \(\mathcal{S}=\{S(\lambda):\lambda\in\Lambda(m,k)\}\) be a family of hierarchical type classes in which each class \(S(\lambda)\) belongs to the set of classes \(\mathcal{S}_{m,k}(\lambda)\). Then \(\mathcal{S}\) is defined to be a (\(\Lambda(m,k)\)-indexed) hierarchical source if the following additional condition is satisfied.  
* **Consistency Condition:** For each \(S\in\mathcal{S}\) of order \(>0\), each term in the \(k\)-tuple \((S_{1},S_{2},\cdots,S_{k})\) associated with \(S\) in Prop. 4 also belongs to \(\mathcal{S}\).  
We discuss how the Consistency Condition gives us a way to describe every possible hierarchical source. Let \(\Lambda(m,k)^{k}\) be the set of all \(k\)-tuples whose entries come from \(\Lambda(m,k)\). Let \(\Phi(m,k)\) be the set of all mappings \(\phi:\Lambda(m,k)^{+}\rightarrow\Lambda(m,k)^{k}\) such that whenever \(\phi(\lambda)=(\lambda_{1},\lambda_{2},\cdots,\lambda_{k})\), we have * \(\lambda=\sum_{i=1}^{k}\lambda_{i}\).
* If \(\lambda\) is of order \(j\), then each entry \(\lambda_{i}\) of \(\phi(\lambda)\) is of order \(j-1\).  
Each \(\phi\in\Phi(m,k)\) gives rise to a \(\Lambda(m,k)\)-indexed hierarchical source \(\mathcal{S}^{\phi}=\{S^{\phi}(\lambda):\lambda\in\Lambda(m,k)\}\), defined inductively as follows.  
* If \(\lambda\in\Lambda(m,k)\) is of order \(0\), define class \(S^{\phi}(\lambda)\) to be the set \(\{a_{i}\}\), where \(a_{i}\) is the unique letter in \(\mathcal{A}_{m}\) whose type is \(\lambda\).
* If \(\lambda\in\Lambda(m,k)^{+}\), assume class \(S^{\phi}(\lambda^{*})\) has been defined for all types \(\lambda^{*}\) of order less than the order of \(\lambda\). Letting \(\phi(\lambda)=(\lambda_{1},\lambda_{2},\cdots,\lambda_{k})\), define  
\[S^{\phi}(\lambda)\stackrel{{\Delta}}{{=}}\bigcup_{\pi\in\Pi_{k}} \left[S^{\phi}(\lambda_{\pi(1)})*S^{\phi}(\lambda_{\pi(2)})*\cdots*S^{\phi}( \lambda_{\pi(k)})\right]\]  
From the Consistency Condition, all possible hierarchical sources arise in this way, that is, given any \(\Lambda(m,k)\)-indexed hierarchical source \(\mathcal{S}\), there exists \(\phi\in\Phi(m,k)\) such that \(\mathcal{S}=\mathcal{S}^{\phi}\).  
Another advantage of the Consistency Condition is that it allows the entropies of the classes in a hierarchical source to be recursively computed. To see this, let \(\mathcal{S}=\{S(\lambda):\lambda\in\Lambda(m,k)\}\) be a \(\Lambda(m,k)\)-indexed hierarchical source and choose \(\phi\in\Phi(m,k)\) such that \(\mathcal{S}=\mathcal{S}^{\phi}\). Define \(H_{\phi}:\Lambda(m,k)\rightarrow[0,\infty)\) to be the function which takes the value zero on \(\Lambda_{0}(m,k)\), and for each \(\lambda\in\Lambda^{+}(m,k)\),  
\[H_{\phi}(\lambda)=[\sum_{i=1}^{k}H_{\phi}(\lambda_{i})]+\log_{2}N(\lambda) \tag{3}\]  
where \((\lambda_{1},\cdots,\lambda_{k})\) is the \(k\)-tuple \(\phi(\lambda)\) and \(N(\lambda)\) is the number of distinct permutations of this \(k\)-tuple. By the Consistency Condition and Lemma 1,  
\[H_{\phi}(\lambda)=H(S(\lambda)),\ \ \lambda\in\Lambda(m,k)\]
## 3 Results and Discussion
### Influence of Different Wave Velocities  
The \"Downstream\" propagation direction of TWW is selected to further study the effect of wave velocity. The wave number is set as 4, and the amplitude ratio \(\hat{A}/D\) is 0.02. Figure 14 shows the lift and drag coefficient time histories under given velocity ratios of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0. From the results of the lift coefficient fluctuation, the cylinder wake is suppressed in different degrees, but the fluctuation of lift coefficient increases slightly after \(c/U_{\infty}>2\). The mean lift coefficient decreases to negative values as \(c/U_{\infty}\) increases. With the increase in wave velocity, the mean drag coefficient decreases dramatically but the fluctuating drag coefficient increases gradually, as shown in Figure 14.  
Figure 15 shows the characteristic value analysis of lift and drag coefficients under different wave velocities, including the mean and RMS values of lift and drag coefficients. In Figure 15a, with the increase of \(c/U_{\infty}\), \(\overline{C}_{l}\) changes from a result larger than that of standard circular cylinder to a result less than that of standard circular cylinder. As for the overall time, \(\overline{C}_{l}\) has little difference with that of standard circular cylinder in the range of the whole velocity ratios. As \(c/U_{\infty}\) increases from 0.5 to 1.5, \(C_{l}^{\prime}\) decreases dramatically from 0.115 to 0.003. In addition, \(C_{l}^{\prime}\) reaches the minimum at \(c/U_{\infty}~{}=~{}1.5\), whose value decreases by 99.63% than that of standard circular cylinder. \(C_{l}^{\prime}\) increases slightly from 0.005 to 0.036 as \(c/U_{\infty}\) increases from 2.0 to 5.0. In addition, \(C_{l}^{\prime}\) equals to 0.036 at \(c/U_{\infty}~{}=~{}5.0\), which achieves 96.09% reduction from the result of standard circular cylinder. In Figure 15b, with the increase of \(c/U_{\infty}\), \(\overline{C}_{d}\) decreases from 0.761 (60.04% of standard cylinder) to \(-1.8774\), and \(C_{d}^{\prime}\) increases from 0.014 to 1.037 (almost 12.8 times the result of standard circular cylinder). From the analysis results above, it is indicated that the velocity ratio \(c/U_{\infty}~{}=~{}1.5\) is the optimal wave velocity for TWW flow control with respect to the control effect and energy input.  
Figure 14: Cont.
## 3 Results and Discussion
### QCA for Management Reasons: Combination Paths
The raw coverage of this path was 0.44, which meant that this combined path could explain 44% of accident cases. The unique coverage of this path was 0.07, which showed that the accident cases with only this combined variable path account for 7%. Based on the above two combined paths, the following measures were proposed. For training and education management, the safety awareness of operators should be strengthened, and education and training on the identification of toxic and harmful gases, the use of protective equipment and emergency response should be strengthened. For supervision and inspection management, supervisors should monitor the gas concentration in the working environment, the effectiveness of the ventilation system and the standardization of personnel operations before entering places prone to methane production. For emergency and response management, an emergency plan should be established and drills should be organized regularly to avoid casualties due to blind rescue in the event of an emergency. Robustness test. This paper conducted a stability test of QCA analysis from two aspects. First, the consistency threshold was adjusted from 0.8 to 0.7, 0.75, and 0.9, respectively. The results showed that the necessary conditions were the same when the consistency thresholds were 0.7, 0.75, and 0.9, which indicated that the obtained results were robust. Second, five cases were added, and conditional necessity analysis and truth value analysis were performed. The results are shown in Tables 5 and 6, respectively. It can be seen from Tables 5 and 6 that the necessary conditions were the same, and the consistency index of each condition variable was slightly different. In addition, the condition combination path obtained after adding five cases was consistent with the original condition combination path. In summary, the research results obtained in this paper using the QCA method were robust.
###### Abstract
Latency in telerobotic systems encompasses several components, including transmission delay, processing delay, propagation delay, sensor and actuator delay, and feedback delay. Transmission delay is influenced by network bandwidth and congestion, while processing delay depends on the computational power and software efficiency of both the operator's and robot's systems. Propagation delay is related to physical distance, while sensor and actuator delays impact how quickly the robot can respond. Feedback delay involves the time needed for the operator to receive and interpret sensory information. To reduce overall latency and improve the quality of service (QoS) and overall user experience, a comprehensive study of each factor is necessary. Our extensive literature review could not find any such study, however. Therefore, this paper aims to provide an in-depth analysis of these contributing elements. In this paper, we quantify and assess the individual latency components that make up the control feedback loop in telerobotics by performing tests measuring end-to-end and robot processing latency in varied network topologies. Specifically, we focus on two key data streams: the camera feed that provides the operator with a visual representation of the robot's environment, and the control communications from the operator to the robot. Through this analysis, we provide insights into constituent latency elements that can be used to optimize the overall end-to-end latency. The remainder of this paper is structured as follows: Section 2 reviews publications that relate to this work, and Section 3 goes into detail on the methodology of our work. Section 4 provides an overview and discussion of the results we obtained, and Section 5 presents the conclusions of this work and suggestions for future work.
# Demystifying DFT-Based Harmonic Phase Estimation, Transformation, and Synthesis
## 3 An Interpretable Time-Shift Invariant Harmonic Phase Model
It should be noted that, in this case, phase (un)wrapping is vertical, meaning that it is performed along the frequency axis, as opposed to the time axis, which is by far the most common use of phase (un)wrapping operations. As a summary, the NRD captures the vertical phase structure (i.e., along the frequency axis) of all the harmonic sinusoids, which just depends on the waveform shape of the periodic signal they define. It should be stressed that when the (vertical) harmonic magnitude and (vertical) harmonic phase structure are combined, they uniquely define the waveform shape of a given periodic signal, independently of its time shift, and its fundamental frequency. In the next three subsections, we take inspiration from [23] in order to demonstrate the practical estimation of three different NRD feature vectors that characterize three different waveforms, all of them emerging from the sawtooth wave.
## 2 Nonlinear Distributed-Parameter Model of the MSR Plant  
ORNL proposed the design of the MSR plant with a nominal power of 2250 MW, which employed molten salt composed of U-Th fluoride as the fuel and coolant [29]. This MSR plant was selected as the research subject to be modeled for the control system design in this paper. The schematic of the whole system is illustrated in Figure 1. It can be observed that the following components play a key role in the process of heat generation and energy transfer: the reactor core moderated by graphite, the tubular heat exchanger, and the supercritical steam generator. Referring to the ORNL design, two zones exist in the core: the inner zone and the outer zone; the two zones separate the molten salt flowing through the graphite into two parts [30]. By employing the online fuel processing system, fission products and high-level radioactive wastes in the molten-salt fuel are separated and removed from the reactor core. In addition, as a safety feature, the fuel salt is discharged into emergency dump tanks without any active measures when it overheads under severe accident conditions, in which the reactor could always be shut down spontaneously, and the risk of the release of radioactive material is minimized. In the primary loop, the fuel salt flows into the core from the bottom and then travels upward through the channels inside the graphite. Afterward, it leaves the core from the top and then enters the tubes of the heat exchanger. The heat released by fission is carried by the fuel salt and then transferred to the salt of the secondary circuit, which is located on the shell side of the heat exchanger. Finally, the heat is transferred to the feedwater of the tertiary circuit in the horizontal U-tube steam generator, by which the feedwater is transformed into superheated steam and then sent to the steam turbine for the generation of electricity.  
A nonlinear distributed-parameter model was established for the entire system, including the reactor core, heat exchangers, and steam generators. The schematic diagram of  
Figure 1: Overall schematic diagram of the whole MSR plant.  
the discretized system model is shown in Figure 2. The primary salt and graphite in the core region are divided into N nodes axially and 2 zones radially. In the radial direction, the mass flow rate is distributed such that 81.4% is in the central zone and 18.6% is in the outer zone [30] according to the power distribution to achieve a uniform temperature rise. The heat transfer coefficient is assumed to be a function of the mass flow rate and the temperature. The axial nodalization scheme is also applied to the fuel salt, secondary salt, and tube wall of the heat exchanger. In the steam generator, the secondary salt, the tube wall, and the feedwater/steam are also discretized into N nodes as for the core and heat exchanger. The technique of backward differentiation formulas (BDFs) is applied to solve the nonlinear time-dependent differential equations of the computer model [31].
## 4 Results
### Correlations between LOS and GSI and Their Trends
#### 4.3.2 Trends in Correlations between LOS and GSI  
Linear trends in correlations between LOS and GSI calculated from correlations between LOS and GSI for each 16-year window from 1982-1997 to 1998-2013 (Figure 7) show larger areas (39.76%) of significant increasing strength of the correlations between LOS and GSI than areas with decreasing correlations (31.14%) for the NH. It is evident that most areas in high latitudes of NA show positive trends and areas of pixels with significant positive trends in NA (46.92%) are considerably larger than those with negative trends (25.92%). Contrastingly, areas of pixels with a significant positive trend in EA (36.45%) are only a little larger than those with negative trends (33.55%) (Table 4). This suggests that EA shows more divergent pattern of trends in correlations between LOS and GSI, as compared to NA with dominating increasing trends.  
Figure 6: (**A**) Distribution of pixels with significant correlations between LOS and GSI within each major biome during 1982–2013 (only distributions within eight major biomes are shown). (**B**) Percentages of pixels with significant correlations between LOS and GSI for major biomes during 1982–2013.  
Figure 7: Trends in correlations between LOS and GSI from 1982–1997 to 1998–2013 (17 moving windows).  
Pixels with significant positive trends in correlations between LOS and GSI (Figure 8A) are mainly distributed in croplands and non-forest biomes for the NH, but are rarely found in forest biomes, except for mixed forest. Interestingly, a similar distribution pattern is observed for pixels with negative trends. Biomes having high percentages of pixels with significant positive trends in correlations between LOS and GSI (Figure 8B) are mainly observed for savannas, shrublands, evergreen needleleaf forest, and mixed forest for the NH, whereas low percentages of these trends are primarily found for deciduous broadleaf and needleleaf forest, croplands, and grasslands. Complementarily, biomes having high percentages of pixels with significant negative trends in correlations between LOS and GSI (Figure 8B) are mostly observed for deciduous broadleaf and needleleaf forest, croplands, and grasslands, while low percentages of these trends are mainly found for savannas, shrublands, evergreen needleleaf forest, and mixed forest.
# Virtualized MME Design for IoT Support in 5G Systems
## 3 System Model
### eNodeB Stations  
eNodeB (eNB) stations receive signaling messages from the UEs and forward them to the virtualized MME. Each eNB keeps a user inactivity timer, which has an expiration time \(T_{I}\), for each attached UE within its coverage area. Using this timer, the eNB detects the users' inactivity (i.e., a user does not perform any data transmission over a period of length \(T_{I}\)). If the timer expires, the eNB triggers a Service Release (SRR) procedure to release the bearer [5].
# Quad-Port Multiservice Diversity Antenna for Automotive Applications
## 1 Introduction
In [28], a MIMO antenna was designed with meandering lines and SRR for improved isolation. However, the above-mentioned antennas are relatively large, have few resonating elements, and require more installation space. This paper proposes a UWB MIMO antenna for automotive applications. The proposed antenna element has a straightforward geometry that covers a wide range of frequencies. Resonances at 1.5 GHz and 2.45 GHz are also achieved by incorporating stubs in the patch of the antenna element. The antenna elements are arranged orthogonally to develop the proposed MIMO antenna. The proposed quad-port MIMO antenna offers polarization and spatial diversity. The MIMO antenna is compact in size, covers multiple frequency bands, and offers good reliability in the automotive environment. It can be easily integrated into a vehicle using the shark fin mounting available in the market. The diversity parameters are also evaluated to understand the performance of the MIMO antenna, and the results are satisfactory.