esa-sceva/satcom-chunk-collection huggingface dataset:
# Review of Advancement in Variable Valve Actuation of Internal Combustion Engines
## 1 Introduction
### Classification of Valve Actuation Systems  
Valve actuation systems are firstly classified into two large groups: cam-driven and camless systems. A cam-driven system utilizes cam lobes to actuate the valve lift, while a camless system does not include any cam mechanism and varies the valve lift using hydraulic, electro-magnetic, or pneumatic actuation to provide flexibility in control. Valve actuation systems are further classified based on the valve parameters being controlled.  
Camless systems generally offer more control flexibility and capability, but they are yet to be implemented in production because of technical difficulties and commercial issues. For this reason, this review covers commercialized cam-based systems and only some development work in camless systems.
# Uncertainty Propagation through a Point Model for Steady-State Two-Phase Pipe Flow
## 2 Materials and Methods
### Uncertainty Quantification
#### 2.2.1 Measurement error
\begin{table}
\begin{tabular}{c l l} \hline \hline  & & **(a) Input** \\ \hline
**Variable** & **Unit** & **Uncertainty** \\ \hline \(m_{\mathrm{g}}\) & \(\mathrm{kg}/\mathrm{s}\) & \(m_{\mathrm{g}}\cdot 0.4\%\) \\ \(m_{\mathrm{l}}\) & \(\mathrm{kg}/\mathrm{s}\) & \(m_{\mathrm{l}}\cdot 0.05\%\) \\ \(\mu_{\mathrm{g}}\) & \(\mathrm{Pa}\,\mathrm{s}\) & \(\mu_{\mathrm{g}}\cdot 2\%\) \\ \(\mu_{\mathrm{l}}\) & \(\mathrm{Pa}\) & \(\mu_{\mathrm{l}}\cdot 3\%\) \\ \(\rho_{\mathrm{g}}\) & \(\mathrm{kg}/\mathrm{m}^{3}\) & \(0.2\,\mathrm{kg}/\mathrm{m}^{3}\) \\ \(\rho_{\mathrm{l}}\) & \(\mathrm{kg}/\mathrm{m}^{3}\) & \(1\,\mathrm{kg}/\mathrm{m}^{3}\) \\ \(D\) & \(\mathrm{m}\) & \(D\cdot 1\%\) \\ \(\varepsilon\) & \(\mathrm{m}\) & \(1\cdot 10^{-6}\,\mathrm{m}\) \\ \(\sigma\) & \(\mathrm{N}/\mathrm{m}\) & \(\sigma\cdot 30\%\) \\ \(\theta\) & \(\mathrm{rad}\) & \(2\cdot 10^{-4}\,\mathrm{rad}\) \\ \hline \multicolumn{3}{c}{**(b) Output**} \\ \hline
**Variable** & **Unit** & **Uncertainty** \\ \hline \(H\) & \(-\) & 0.03 \\ \(-\partial p/\partial x\) & \(\mathrm{Pa}/\mathrm{m}\) & \(\mathrm{max}(3\,\mathrm{Pa}/\mathrm{m},-\partial p/\partial x\cdot 0.5\%)\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Uncertainty in the model variables given as one standard deviation.
## 2 Literature Review
### Flexible Job Shop Lot Streaming (FJS-LS)  
Early research in job shop lot streaming was for the classical job shop. However, in recent years, the research focus on job shop lot streaming has been in FJS-LS. [PERSON] [2] developed a parallel genetic algorithm for FJS-LS with makespan criterion considering sequence-dependent setup time, attached and detached nature of setups, machine release date, and lag-time (a delay for cooling, drying, inspection, or other ancillary operations). [PERSON] and [PERSON] [35] and [PERSON] et al. [36] implemented FJS-LS through a successive partial transfer of a job from one machine to the next to allow operation overlapping when sublots are not scheduled independently. [PERSON] and [PERSON] [37] considered FJS-LS with variable sublots in a two-stage approach.  
In the first stage, the makespan is minimized with the minimum sizes of the sublots defined for the problem (the larger number of sublots). In the second stage, the number of the sublots is reduced without affecting the makespan to minimize the transportation cost. [PERSON] and [PERSON] [38] developed a linear programming hybridized genetic algorithm where the linear programming is periodically used to enhance promising solutions during the search process. [PERSON] [39] developed a method based on constraint programming to solve flexible job shop lot streaming with makespan criterion.  
[PERSON] et al. [40] proposed an algorithm based on a variable neighborhood search to minimize the makespan for a lot streaming problem in a flexible job shop followed by a parallel assembly station. An FJS-LS problem in an Engineer to order environment was presented in [41]. The authors developed a mathematical model with variable sublot and makespan criterion and then proposed a genetic-algorithm-based heuristic to solve the model effectively. Though the above review indicates momentum in FJS-LS research, the total number of publications is minimal, and further research needs to be conducted.
# Multi-Body Dynamics Modeling and Simulation of Maglev Satellites
## 5 Conclusions  
The high-precision fast attitude pointing control method centered on the payload can achieve the control goal of \"active payload, platform follow-up\", reduce the transmission of imaging payload errors, and isolate the impact of satellite body vibration. An evaluation of the stability with a specific model mentioned earlier has been performed. The attitude accuracy of the payload subsystem is 0.00002\({}^{\circ}\) and the attitude stability is within 0.00005\({}^{\circ}\)/s, achieving ultra-high precision, ultra-high stability, and ultra-high agility attitude pointing control of imaging payloads. The payload-centered control method is also applicable to precise attitude control of other non-contact isolation systems, except for the specific model proposed in this paper.  
Writing--original draft preparation, Z.L.; writing--review and editing, W.W.; visualization, Z.L.; supervision, L.W.; project administration, W.W.; funding acquisition, W.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 52075545.  
Not applicable.  
The data presented in this study are available on request from the corresponding author due to the research project involved in the article involves relevant confidentiality agreements, and the overall project has not been completed yet.  
The authors declare no conflict of interest.
# Experimental Study on Strength of Polypropylene Fiber Reinforced Cemented Silt Soil
###### Abstract
The tensile test proved that the addition of fiber improved the tensile strength of soil. [PERSON] et al. [24] studied the effect of polypropylene fiber on the flexural strength of cement-reinforced sand and found that polypropylene fiber can improve the flexural response and failure mode of cement-reinforced sand. [PERSON] et al. [14] analyzed the interaction mode between fiber and soil particles by conducting a triaxial shear test. The test showed that the contact, bending, and weaving between soil particles and fiber provided interface shear stress for soil particles and fiber. In summary, at present, the solidification means of silt soil mainly include chemical solidification, which has the disadvantage of poor tensile and flexural properties of cement soil. The cement and polypropylene fiber improvement technology has the advantages of high strength and strong resistance to deformation and has achieved a good curing effect in the improvement of sandy soil, marine clay, light soil, concrete, and other soil. However, the strength of fiber-reinforced cement solidified sludge is affected by the cement content, fiber content, and fiber length. The current research mainly focuses on 1-2 factors, with a single focus. Therefore, this paper takes Nansha silt of Guangzhou as the research object, ordinary Portland cement as the curing agent, and polypropylene fiber as the reinforcing material, and prepares fiber-reinforced cement soil samples with different cement dosages and different fiber content and length. A series of unconfined compressive strength tests and triaxial shear tests are carried out, and the effects of fiber content, fiber length, and cement content on the shear strength of fiber-reinforced cement soil are analyzed, The microcosmic control mechanism of ordinary Portland cement and polypropylene fiber to solidify silt is explored, and the constitutive equation of fiber reinforced cement soil is derived. The expected results can provide a reference for geotechnical engineering factors such as foundation treatment, filling slope, and foundation pit support.
## 2 Materials and Testing Procedure
### PE-SHCC Mixing and Specim Preparation  
The cement and micro silica sand were first poured and mixed using a 10-L conventional mortar rotary mixer for 1 min so that the dry ingredients were well mixed. Water and liquid-type MWCNTs were then added, mixed for 3 min, followed by the SP addition and mixing for 5 min. Finally, reinforcing fibers such as PE and steel fibers were incorporated into fresh mortar and mixed for 3 min. The fresh PE-SHCC mixture were cast into oiled steel molds and vibrated to ensure good compaction. The cast specimens were kept in the molds covered with plastic sheet for 24 h before they were demolded and then stored in standard curing chamber with 95% relative humidity and temperature of 20 \({}^{\circ}\)C for 28 days.  
The flow table test was performed on fresh PE-SHCC with different contents of steel fibers to evaluate the workability of each mixture using ASTM C230, \"Standard Specification for Flow Table for Use in Tests of Hydraulic Cement.\" Average flow diameter recorded was 165 mm, 190 mm and 215 mm, respectively for PE-SHCC-SF00, PE-SHCC-SF05 and PE-SHCC-SF00.  
As shown in Figure 1a, nine dumbbell-shaped specimens were prepared for each composition. Among the nine specimens, three specimens were plain PE-SHCC specimens to examine steel fiber effect on tensile and electrical properties. The other ones were used for evaluating the steel reinforcement bar effect on the electrical property. The round steel bar with diameter of 4 or 7 mm was reinforced at the center of each dumbbell-shaped specimen.  
At three weeks after casting the specimens, four electrodes consisting of fine copper wire were wrapped at the opposing ends of wider portion of each dumbbell-shaped specimen, as shown in Figure 1b. Each copper wire was covered with several layers of silver-based conductive paint to seal any gap and improve the bonding with the tensile specimen to measure the electrical resistance.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Mix Designation** & **Cement** & **Water 1** & **Silica Sand** & **SP** & **PE 2** & **SF 2** & **MWCNT 3** \\ \hline PE-SHCC-SF00 & 1.0 & 0.3 & 0.4 & 0.02 & 0.75 & 0.0 & 1.0 \\ PE-SHCC-SF05 & 1.0 & 0.3 & 0.4 & 0.02 & 0.75 & 0.5 & 1.0 \\ PE-SHCC-SF10 & 1.0 & 0.3 & 0.4 & 0.02 & 0.75 & 1.0 & 1.0 \\ \hline \hline \end{tabular}  
* Total water, the sum of mixing water and additional water from liquid-type multi-walled carbon nanotubes (MWCNTs), 2 percentage of total mix volume, 3 percentage of weight of cement.  
\end{table}
Table 1: Mix proportion of polyethylene fiber reinforced strain-hardening cement composites (PE-SHCC).  
Figure 1: Manufacture and configuration of PE-SHCC dumbbell-shaped specimen (**a**) casting the specimen; (**b**) configuration and dimension of specimen (unit: mm).
# Quantum PSO-Based Optimization of Secured IRS-Assisted Wireless-Powered IoT Networks
## 6 Conclusions  
In this paper, we investigated the use of IRS-assisted physical layer security in a WPIN to enhance sum secrecy throughput. We employed an AO approach to jointly optimize IRS phase shift and time allocation for downlink and uplink transmissions. Specifically, we combined QPSO and the bisection method to achieve a near-optimal solution characterized by rapid convergence. Our comparative analysis revealed that the proposed QPSO and bisection method achieves substantial performance gains in secrecy throughput. For \(N=35=35\), the proposed method achieves \(19.4\)\(\mathrm{bps}/\mathrm{Hz}\), which is \(58\%\) higher than phase-optimal QPSO, \(85\%\) higher than standard PSO, and \(143\%\) higher than fixed time, random phase. Similarly, for \(P_{max}=30\) dBm, the proposed method achieves \(17.9\)\(\mathrm{bps}/\mathrm{Hz}\), outperforming phase-optimal QPSO by \(24\%\), standard PSO by \(63\%\), and fixed time, random phase by \(83\%\). These results confirm the effectiveness of the proposed approach in enhancing network security and performance. The findings demonstrate the potential of IRS technology to greatly improve wireless networks by intelligently manipulating electromagnetic waves, which will improve signal quality and reduce interference. The findings also demonstrate that intelligent time allocation and IRS phase optimization are crucial to fully leveraging the benefits of an IRS in a WPIN environment. Overall, this study provides valuable insights into the design of efficient and robust IRS-assisted wireless communications systems to achieve enhanced network security and performance. The IRS-assisted approach represents a transformative advancement in wireless communications, promising a more secure and efficient future for WPIN.  
Conceptualization, A.A. and I.K.; Methodology, A.A. and I.H.; Software, A.A.; Validation, I.H. and I.K.; Writing--original draft, A.A.; Writing--review and editing, I.H. and I.K.; Supervision, I.K. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Regional Innovation Strategy through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021 RIS-003).  
Not applicable.  
Data Availability StatementData are contained within the article.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
5G Fifth Generation  
6G Sixth Generation  
AF Amplify-and-Forward  
AI Artificial Intelligence  
AN Artificial Noise  
AO Alternating Optimization  
AP Access Point  
AWGN Additive White Gaussian Noise  
BCD Block Coordinate Descent  
DF Decode-and-Forward  
EE Energy Efficiency  
EH Energy Harvesting  
FDMA Frequency Division Multiple Access  
GB Global Best  
H-AP Hybrid Access Point  
IA Interference Alignment  
IoT Internet of Things  
IRS Intelligent Reflecting Surface  
_mbest_ Mean Best Position  
MISO Multiple-Input Single-Output
# A Performance Analysis of Internet of Things Networking Protocols: Evaluating MQTT, CoAP, OPC UA
## 3 An Overview on IoT Communication Protocols and Frameworks
### Quic  
The _Quick UDP Internet Connections (QUIC)_ protocol [20] is a flexible multiplexed and secure general-purpose transport protocol that supports multiplexed streams. Based on UDP, it has been developed to provide security protection equivalent to TLS/SSL along with reduced connection and transport latency, and bandwidth estimation in each direction to avoid congestion. Hence, QUIC relies on UDP, and integrates encryption. As with STCP, QUIC developed support for multiple sub-streams instead of using multiple transport connections.  
Originally developed by Google, today QUIC corresponds to the IETF changed version of the Google QUIC (gQUIC) [21]. It is a relevant protocol in the context of the Internet's evolution and in particular of the Web evolution from TCP to UDP.  
In the context of IoT, as it is kernel independent and can run across NATs, it is a relevant protocol in comparison to HTTP (request-response) approaches.
## 4 Conclusions  
We proposed a PnP QKD system that generates decoy pulses using optical amplification. We showed that random polarization pulses are amplified without distortion using the double amplification method and verified this through actual experiments. Signal and decoy pulses were created by the open-loop control of the OA. The key was generated through PnP QKD for 26 h. Finally, the signal and decoy pulses obtained an average key generation rate of 5.37 \(\times\) 10\({}^{-3}\) b/p and 1.037 \(\times\) 10\({}^{-3}\) b/p, respectively, and QBER obtained averages of 3.35% and 3.95%, respectively. Our results show that the proposed generation method of decoy pulses using optical amplifiers works well. In the future, a more complete system including random modulation, timing control of the single-photon detector, the generation of a secret key after post-processing, etc., will be developed.  
Conceptualization, M.-K.W. and C.-H.P.; Formal analysis, M.-K.W.; Funding acquisition, S.K. and S.-W.H.; Investigation, M.-K.W. and C.-H.P.; Methodology, M.-K.W. and C.-H.P.; Project administration, S.K. and S.-W.H.; Supervision, S.-W.H.; Validation, C.-H.P.; Visualization, M.-K.W.; Writing--original draft, M.-K.W.; Writing--review and editing, S.K. and S.-W.H. All authors have read and agreed to the published version of the manuscript.  
National Research Foundation of Korea (2019M3E4A1079777, 2021M1A2A2043892), Institute for Information and Communications Technology Promotion (2020-0-00972, 2020-0-00947), and the Korea Institute of Science and Technology (2E31531).  
Not applicable.  
Data Availability Statement: Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.  
The authors wish to thank the anonymous reviewers for their valuable suggestions.  
The authors declare no conflict of interest.
# Influence of Welding Parameters on the Weld Pool Dimensions and Shape in a TIG Configuration
## 2 Experimental Procedure
### Data Treatment  
The weld pool dimensions and shape are determined for six interaction times (1, 4, 8, 12, 16 and 20 s) using three methods [1].  
* Method 1 is based on high speed videos. During the arc interaction, images of the weld pool are recorded every one or two seconds. The diameter of the weld pool is evaluated for each sequence of images.
* Method 2 enables the estimating of the weld pool width from pictures of the top surface of the anode at the final instant.
* Method 3 consists in analysing the internal dimensions of the weld pool and the melted zone shape with metallographic investigation. After cutting and polishing the anodes, a 45 s FeCl\({}_{3}\) attack is led to reveal the grain of the welded area. Microscopy determines the width, the depth and the shape of the weld pool.  
The three methods are illustrated in a previous work [1] for Arcal.37 plasma after 8 s of interaction with a current intensity I = 100 A, a tip angle \(\theta\) = 60\({}^{\circ}\), a distance between cathode and workpiece L = 5 mm.
###### Abstract  
Accurate and precise clock synchronization is one of the fundamental requirements for various applications, such as telecommunication systems, measurement and control systems, and smart grid systems. Precision time protocol (PTP) was designed and specified in IEEE 1588 to meet that requirement. PTP provides a mechanism for synchronizing the clocks in a PTP system to a high degree of accuracy and precision based on exchange synchronization messages through a master-slave hierarchy. The best master clock (BMC) algorithm is currently used to establish the master-slave hierarchy for PTP. However, the BMC algorithm does not provide a fast recovery mechanism in case of master failures. The accuracy and precision of the PTP clocks could be deteriorated by the occurrence of failure in the network (link or node failure). These fault occurrences will affect network performance and reliability, and cause clock time drifting of the PTP nodes. In this paper, we present a novel approach, called timing fault recovery (TFR), to significantly reduce clock time drifting in PTP systems. TFR detects the fault occurrence in the network and recovers it by using a handshake mechanism with a short duration. Therefore, the TFR approach provides clock stability and constancy and increases the reliability and the availability of PTP systems. The performance of TFR has been analyzed and compared to that of the standard PTP. Various simulations were conducted to validate the performance analysis. The results show that, for our sample network, the TFR approach reduces clock drifting by 90% in comparison to the standard PTP, thus providing better clock firmness and synchronization accuracy for PTP clocks.  
IEEE 1588; precision time protocol (PTP); timing fault recovery (TFR); clock synchronization; fast recovery +
Footnote †: journal: Applied  
Article
# Mask-Aware Semi-Supervised Object Detection in Floor Plans
## 3 Method
### Mask R-CNN  
Mask R-CNN [17] is an extended version of Faster R-CNN [25] with a new branch for providing masks to the detected objects with the two already present branches for the classification and regression layer. This branch is applied on RoIs (Region of Interest) to deal with detection on the pixel level to segment each stance accurately. The basic architecture of Mask R-CNN is identical to Faster R-CNN, as it uses a similar architecture to generate object proposals. The major difference is that Mask R-CNN uses an RoI-align layer rather than an RoI-Pooling layer to reduce misalignment on the pixel level because of spatial quantization. Generally, the training of Mask R-CNN [17] and Faster R-CNN [25] is identical. For accuracy and speed, we prefer ResNet-101 [19] as a backbone with the feature Pyramid Network(FPN) [60]. We create the mask for each class for pixel-level classification to reduce interclass similarity. We created the ground truth for the mask using object width, height and bounding box coordinates. The masks of all classes are in square boxes having four corner points as (\(x_{min}y_{min}\), \(x_{max}y_{min}\), \(x_{max}y_{max}\), \(x_{min}y_{max}\)). Where (\(x_{min}\), \(y_{min}\)) is the first corner point of the mask and obtained other corner points by adding the width and height of the bounding box in the first corner point. The model learns the mask of each class separately and is defined as the average binary cross-entropy loss, as shown in the following Equation (1).  
\[L_{mask}=-\frac{1}{M^{2}}\sum_{1\in l,m\leq M}y_{lm}logy_{lm}^{n}+(1-y_{lm}) log(1-y_{lm}^{n}) \tag{1}\]  
where \(y_{lm}\) is the label of pixel (l,m) in true mask area \(M*M\) and \(y_{lm}^{n}\) is the estimated value of the same pixel for the ground-truth class n. The loss function of Mask R-CNN [17] is the combination of localization, classification and segmentation mask loss, where classification and localization loss is the same as in Faster R-CNN [25].