esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Research Methodology
### CFD Analysis  
#### 2.2.1 Computational Model  
Computation fluid dynamics (CFD) software ANSYS Fluent (version 13.0) was used in this study to simulate the root pass GTAW process of the spherical shell ring structure, and the fluid flow characteristics of molten metal in weld pools were investigated for the climbing and the flat welding positions shown in Figure 2.  
Considering the diameter of the shell structure (about 5 m) is much larger than its thickness (9.5 mm), the welding processes at both start and finish ends of the panel sheets were simplified as butt welding of flat sheets, i.e., the curvature of sheets was neglected in modeling. Moreover, the top and bottom surfaces of the weld pools were assumed to be flat and not deformable in simulations, as the existing studies showed that such a simplified model could still be used effectively to reveal the correlations between the weld formation and the fluid flow [6].  
A tungsten arc is fixed at a position above the top surface of a workpiece, while the workpiece moves at the welding speed being used, as shown in Figure 3. In addition, as the workpiece and heat source (welding arc) are symmetrical about the central plane of a butt joint, only one half of the weld joint was included in the numerical model. The dimensions of the computation domain are 50 \(\times\) 25 \(\times\) 9.5 mm\({}^{3}\), and the minimum cell in the model is 1.0 \(\times\) 1.0 \(\times\) 0.95 mm\({}^{3}\). A mesh-independency study was performed, in which a one-half smaller mesh (0.5 \(\times\) 0.5 \(\times\) 0.475 mm\({}^{3}\)) was also used. The differences in the results from two meshes were within 1.5%, indicating the mesh used in the study was fine enough.
# Chaotic Orthogonal Composite Sequence for 5G NR Time Service Signal Capture Algorithm
## 5 Conclusions  
With the further improvement of the integrated PNT system and the accelerated deployment of 5G macro and small cell base stations, the limitation of user signal reception will be greatly reduced due to the wide signal coverage capabilities. Therefore, the further exploration of timing modes based on 5G is crucial. This paper proposes a 5G NR time service signal that utilizes spread spectrum modulation, transmitting a low-power signal shared in the 5G communication frequency band. Its signal power is much lower than that of the 5G signal, appearing to be \"submerged\" under the 5G signal and without occupying the bandwidth of the 5G communication signal. Compared to traditional spreading sequences, the proposed chaotic orthogonal combination sequence offers improved security over m-sequences, better auto-correlation than Walsh sequences, and an effective suppression of the short-period characteristics that may arise when Skew Tent-Map chaotic sequences take specific values.  
In the simulation, the capture of the 5G NR time service signal was conducted in a 10 dB signal-to-noise ratio environment using the chaotic orthogonal combination sequence as the spreading code and the parallel code phase search algorithm based on FFT. This approach significantly reduced the capture time compared to traditional linear search methods, successfully acquiring the 5G NR time service signal. As a limitation of this study, it focused on the simulation of capturing the 5G NR time service signal and did not cover tracking and other aspects. Future research will continue to explore other parts of the 5G NR time service signal receiver to enhance its reception performance and further improve the timing performance of the 5G NR time service signal.  
Figure 13: Acquisition probability under different SNR conditions.  
**Author Contributions:** Writing-original draft preparation, Z.M.; methodology, Z.M.; formal analysis: Z.M.; data curation: H.W.; resources: H.W.; conceptualization, D.Z.; writing-review and editing, D.Z.; investigation, X.J.; visualization, X.J. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Youth Innovation Promotion Association CAS (Grant Nos. Y2023109).  
**Data Availability Statement:** Informed consent was obtained from all subjects involved in the study.  
**Acknowledgments:** The data presented in this study are available upon request from the corresponding author.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Literature Survey
### Contributions Made in This Article  
Energy-efficient routing is one of the approaches for optimizing energy usage in the Internet of Things. This methodology recognizes that the needed amount of energy can be decreased by selecting a more advantageous path. This approach sends data to their destination by routing it through nodes that have adequate energy resources. Additionally, it excludes the participation of any nodes that have energy resources which are lower than a predetermined threshold value. Additionally, removing redundancy lowers the amount of energy required to transmit data, which in turn enhances the lifespan of the network.  
An energy-efficient approach to Internet of Things (IoT) routing is proposed in this paper. In order to achieve energy efficiency through efficient routing and communication, this research has been proposed to provide an effective method for selecting CHs. To accomplish this goal, numerous QoS parameters, such as energy and mobility, are taken into consideration. In order to provide the most accurate assessment of fitness that is feasible, the GSO method is combined with the most optimal CH. The technique for clustering is carried out on the cluster head that has been selected. The data aggregation of individual sensor nodes and the aggregation of data from their cluster nodes through this model results in a reduction in the bandwidth that is used. Following the completion of the aggregation phase, the data are transmitted to the sink or base station. To determine the effectiveness of the suggested technique, the remaining energy, network life, and coverage rate are evaluated. The proposed approach can be utilized as a dependable method for data routing and transfer in the Internet of Things, since it consistently outperforms the basic designs in all scenarios and assessment criteria, according to an analysis of the results in two distinct case study simulations.
# Optimal Clustering in Stable Instances Using Combinations of Exact and Noisy Ordinal Queries
## 3 Clustering in Stable Instances
### Dynamic Programming
#### 3.4.2 The Actual Algorithm
Having determined the optimal couple \((l,j_{1}^{*},c_{1}^{*})+(r,j_{2}^{*},c_{2}^{*})\) for the key \((u,j,c)\), we set the corresponding content of data structures \(Cost\) and \(Centroid\) as follows:  
\[E(u,j,c)= E((l,j_{1}^{*},c_{1}^{*})+(r,j_{2}^{*},c_{2}^{*}))\cup\{(u,c)\}\] \[s(u,j,c)= s((l,j_{1}^{*},c_{1}^{*})+(r,j_{2}^{*},c_{2}^{*}))+f_{c,c}\] \[Centroid(u,j,c)= Centroid(l,j_{1}^{*},c_{1}^{*})\cup Centroid(r,j_{2}^{*},c_{2}^{*}) \cup\{c_{1}^{*},c_{2}^{*}\}\.\]  
After we have filled all possible keys \((u,j,c)\), we simply have to find the best value of \(c^{*}\) among all keys \((root,k,c)\) using the same method, and return the set associated with \(Centroid(root,k,c^{*})\). Analysis of High-Low Cost  
The total running time is given by the central part of the algorithm. Let \(\ell_{u,j,c}\) be the length of the list that contains the candidate couples associated with the key \((u,j,c)\). We have to extract the minimum every time, which can be done using \(O\langle\log\ell,\ell\log\ell\rangle\) the high-low cost, for \(\ell=\ell_{u,j,c}\) (Lemma 4). Since the length \(\ell_{u,j,c}\) is \(O(j|B_{u_{1}}||B_{u_{r}}|)=O(kn^{2})\), and the overall high-low cost is  
\[\sum_{j=1}^{k}\sum_{u\in S^{\prime}}\sum_{c\in S}O\langle\log \ell_{u,j,c},\ell_{u,j,c}\log\ell_{u,j,c}\rangle=\] \[\sum_{j=1}^{k}\sum_{u\in S^{\prime}}\sum_{c\in S}O\langle\log(kn^ {2}),kn^{2}\log(kn^{2})\rangle=\] \[O\langle kn^{2}\log n,k^{2}n^{4}\log n\rangle\.\]  
Though the high-cost is worse than the previous result, for \(k\) large, this bound is exponentially better in terms of low-cost. Finally, observe that we can invoke Lemma 4 with parameter \(\Delta=\Theta(\log n)\) so that each of these operations fails with a probability of at most \(n^{-a}\) for sufficiently large \(a\), so that the overall procedure succeeds with high probability (union bound), and the overall complexity is as above (again using \(\ell_{u,j,c}=O(kn^{2})\)).
# Two-Way Transmission for Low-Latency and High-Reliability 5G Cellular V2X Communications
## 3 Analysis of Outage Probability and Throughput of NOMA-V2X System
### Throughput  
The throughput of the system indicates how much NOMA-V2X is able to enable transmission in the context of vehicles. The outage throughput of vehicles \(\mathrm{D}_{1}\) and \(\mathrm{D}_{2}\) is defined with the fixed transmission rates \(R_{1}\) and \(R_{2}\), respectively, as  
\[\tau_{\star}^{\theta}=\left(1-\mathcal{P}_{\star}^{\theta}\right)R_{\star}, \begin{cases}\star\in\left\{1,2\right\}\\ \theta\in\left\{pSIC,ipSIC\right\}.\end{cases}. \tag{18}\]
# Hybrid-Based Analysis Impact on Ransomware Detection for Android Systems
## 3 The Proposed Hybrid-Based Analysis for Ransomware Detection
### Dynamic Analysis Phase  
Unlike static analysis, dynamic analysis is the process of inspecting the behavior of malicious software in a segregated run-time environment [45]. It is accomplished by instrumenting the application's code itself or by running it virtually in an isolated environment, such as a sandbox [46]. The main advantage of dynamic analysis is that all relevant information, such as the behavior, system interaction, and the effects on the host system of the analyzed application, are monitored during the execution time [47]. However, dynamic analysis suffers from some limitations, such as dormant code, where partial parts of the program code go unnoticed because they are not executed during the runtime [48]. Furthermore, dynamic analysis consumes more time and resources, which is why it is not commonly used in commercial antivirus [49].  
In the dynamic analysis phase, MobSF was utilized to implement ransomware analysis. The analysis method involves decompiling the mobile application's source code, then running the ransomware application dynamically in an isolated device or an emulator virtual machine. The emulator executes the application, gathers the information and reports it back to MobSF. The purpose is to keep the original device safe from being infected. Figure 3 illustrates the high-level architecture of the MobSF dynamic analyzer. The dynamic analyzer initiates an HTTPS web proxy connection in parallel to the web traffic capturing. Additionally, it generates an Android virtual machine (VM) configured with its own agent and automatically installs the Android APK app. Furthermore, the Android VM agent records all the application data and security analysis in the background.  
Once the analysis is completed, all the recorded information in the VM is sent back to the dynamic analyzer for further analysis. As a final step, a report is generated. Some of the significant features included in the MobSF dynamic analyzer are the ability to take screenshots, capture web traffic, export activities, and monitor the dynamic API calls made by the application during the runtime along with the dynamic URL and email monitoring modules.
## 5 Conclusions  
OTFTs with an electret have demonstrated potential in radiation dosimetry applications. These devices in a wireless configuration possess excellent linearity over doses between 1 to 30 Gy at both kilovoltage and megavoltage X-ray energies, with sensitivities of 60-80 nA/Gy as the change in drain current at V\({}_{\text{g}}\) = \(-\)15 V. For wired real-time readout, the sensitivity of the devices was around 8.1 nA/s at a dose rate of 600 cGy/min and electric  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Dose Rates** & **Sensitivity (n/s) at** \\  & **V\({}_{\text{ds}}\) = \(-\)15 V; V\({}_{\text{gs}}\) = \(-\)15 V** \\ \hline
600 cGy/min & 8.1 \\ \hline
400 cGy/min & 5.7 \\ \hline
300 cGy/min & 4.2 \\ \hline
200 cGy/min & 2.8 \\ \hline
60 cGy/min & 1.0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The sensitivity of the pentacene OTFTs with PS electret during real-time readout in a wired configuration irradiated with a 6 MV photon beam.  
field at V\({}_{\rm d}\) = \(-\)15 V and V\({}_{\rm g}\) = \(-\)15 V. The devices are well-suited to in vivo dosimetry applications in radiation therapy. Advantages of the design include: options for both wireless and wired readout configurations, repeated readout due to signal storage, and repeated use due to the ability to reprogram the device. Moreover, these organic devices can be fabricated on flexible substrates with an organic dielectric to contain a tissue-equivalent composition. A similar atomic number between the dosimeter and human tissue will enhance precision and facilitate high quality measurement of patient doses. Future work will include the quantification of signal fade post-exposure, lifespan of the devices, and sensitivity improvement. For example, the sensitivity of the dosimeters can potentially be improved by increasing the trap carrier density in organic semiconductor or dielectric layer. Similar to organic memory devices, the dielectric layer can be complex or with a floating gate to store more charges and thus show the improved response to ionizing radiation.  
Conceptualization I.V., I.G.H. and A.S.; methodology: I.V., A.M. and M.A.H.; formal analysis: I.V. and A.M.; investigation: I.V. and A.M.; writing--original draft: I.V. and A.M.; writing--review and editing: M.A.H., I.G.H. and A.S.; project administration: I.G.H. and A.S.; funding acquisition: A.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by a grant from the Natural Sciences and Engineering Research Council of Canada (Grant # RGPIN-2021-03715).  
Data Availability Statement: Data is available from the authors upon reasonable request.  
The authors declare no conflict of interest.
# Exploiting Concurrent Wake-Up Transmissions Using Beat Frequencies
## 4 Concurrent Wake-Up Protocol Design
### Integration into Existing Routing Protocols  
Depicted in Figure 15 is a protocol design to demonstrate the feasibility of concurrent wake-up calls and to provide a means to integrate concurrent wake-up calls into existing solutions. To begin a concurrent wake-up, Node-1 sends a single wake-up call (WUC) to Node-2 that acknowledges (ACK) the successful reception. Node-1 then transmits a request (REQ) for a concurrent wake-up message to Node-2 embedding the address of Node-3. Upon reception of this dedicated request, indicated by a special bit in the radio packet, Node-2 changes its carrier frequency for the transmission period of the concurrent wake-up packet. Based on the timing of this handshaking, Nodes-1 and 2 send the concurrent wake-up call (CWUC) to Node-3. After Node-3 detects the valid wake-up call, it is ready to receive data from Node-1. Finally, Node-3 acknowledges the data reception.  
In this example, we assumed a scenario similar to that visualized in Figure 1, where Node-3 is out of wake-up range. Alternatively, this scheme could also be used when wake-up messages reach Node-3 with low reliability, only. Both cases could be detected by Node-1, for example, by comparing the number of send wake-up calls to the number of successfully-received wake-up calls. In the case of low wake-up reliability, Node-1 could request Node-2 to transmit a concurrent wake-up message to increase its reliability.  
A thorough performance analysis of this approach, including comparisons to existing direct transmission-based approaches, is clearly out of the scope of this work, the goal of which is to demonstrate the feasibility of concurrent wake-up calls based on beat signals. However, we expect beat transmissions to be more effective as the occupied bandwidth is reduced by removing the high data-rate on-off keying modulation. Furthermore, the approach increases the probability of successful wake-up transmissions, which directly leads to a performance gain, especially in fast-fading or noisy environments. This basic concurrent wake-up scheme can be integrated into existing routing protocols, like CTP-WUR (Collection Tree Protocol - Wake-up Receiver) [28], T-ROME [6], ALBA-WUR (Adaptive Load-Balancing Algorithm - Wake-up Receiver) [29] or others, such as [4, 30, 31].  
Figure 15: Overview of the concurrent wake-up protocol. Here, we use the abbreviation WUC for a wake-up call, CWUC for a concurrent wake-up call, ACK for the wake-up acknowledgment and REQ for the concurrent transmission request.
## 3 Method
### Clarification of Exploration Policy and Mask Design  
In the deep reinforcement learning framework adopted in this study, the exploration strategy utilizes the maximum Q value to determine the optimal action. During the initial exploration phase, the selected position may be far from the desired object, often appearing near the edge of the image. To address this, a grasp mask and a push mask are used, as illustrated in Figure 4.  
The grasp mask is a binary mask designed to guide the grasper toward the center of the target object. To generate this mask, image processing techniques are used to detect the center of the object. The pixel corresponding to this center is assigned a value of 1, while all other pixels are set to 0. This configuration ensures that each grasp action is executed exactly around the center of the object, maximizing the probability of a successful grasp.  
The push mask is also a binary mask, specifically designed to facilitate a stable and safe pushing action. This mask is created by performing image post-processing, which involves subtracting a dilated image that takes the size of the clamp into account from  
Figure 4: Grasp mask and push mask. This figure shows two heightmaps for grip_mask and push_mask. In the grip_mask_heightmap (left), the bright green dots indicate the target area for the grasping action, where the highest Q value is found, indicating the optimal place to grasp the object. In the push_mask_heightmap (right), the yellow lines indicate the exploration area limited by the masking technique for the pushing action. The dark purple background in both heightmaps indicates areas outside the exploration region or areas that are irrelevant for the robot’s actions, ensuring that the robot only focuses on areas with objects present.  
another dilated image that does not. This process creates a defined area of interest around the target object, ensuring enough space for the clamp to approach and interact with the object without collision or instability.
## 4 Discussion
### Challenges
#### 4.1.3 Water Management  
Managing and distributing drinking water and water supplies properly in urban areas is an extremely challenging task. The current distribution of water systems contribute to reducing the quality of drinking water due to pipes' erosion, pipes' breakdown, and interaction with pipe materials [33; 49]. The procedure of distributing drinking water and water supply in urban areas is causing water supply tainting; whether incidental or intentional, which contributes to being a medium of transmitting microbes and bacteria and may cause serious health problems [44]. Also, with this procedure, drinking water is lavished in various ways such as wasteful use and poor water distribution [36]. Further, poor water management makes it challenging to keep up a water consumption record [36]. Moreover, the current irrigation process causes a large amount of water to be wasted due to the automated schedule of irrigation at a certain time, which is not considering the moisture in the soil and irrespective of the weather condition [35].
## 1 Introduction
The magnetic flux method can also be used to measure the cable force, but this method requires on-site checking of the relationship between the magnetic flux and the cable force and on-site calibration with the same cable to determine the relationship between permeability and strain of the cable [2]. Some researchers use optical fiber Bragg grating (OFBG) embedded inside the cable to detect the cable force, but it is only suitable for the cable of the newly built bridge [25]. In fact, the damage of the hanger causes the redistribution of the tension force and the changes of loads on the tie-beam. Thus, the deterioration of the hanger can be identified from the changes in the loads on the tie-beam and the deflection change of the tie-beam. In fact, static deflection has been a fundamental parameter in the SHM of many important structures including bridges [26]. Many scholars have studied cable damage identification based on deflection, e.g., [PERSON] et al. [7] identified the damage of the hanger by the measuring point deflection difference. [PERSON] et al. [2] detected the tension loss in cables by distributed deck strains. The bridge displacement testing technology is relatively mature, so using displacement to identify the damage of the hanger has certain advantages. Motivated from recent advances in deflection measurement technology, a new method that does not rely on an optimization algorithm is proposed to locate damaged hangers in through-arch bridges using the static deflection changes of the tie-beam. The purpose of this method is to solve the early damage, so it belongs to the linear damage category, in which the state of the structure before and after the hanger's damage is assumed to be linear. A two-dimensional FEM verifies the correctness of this method. Twenty-four hypothetical damage cases are designated in the model. Then, based on a test model of through-arch bridge, the hanger's damage is simulated to verify the method's effectiveness. Numerical and laboratory investigations demonstrate that the proposed method can always reliably detect the damaged hangers regardless of damage locations. This method can locate the damaged hanger only based on the FEM under the completed status of the bridge and the deflection difference of the tie-beam in the damaged condition and is suitable for real bridges.
###### Abstract  
The purpose of this retrospective study was to evaluate changes in the temporomandibularbular joint spaces (TMSJs) in skeletal Class III adult patients with orthognathic surgery using cone-beam computed tomography (CBCT). CBCT images taken from 26 orthognathic surgery adult patients (15 females, 11 males, average 19.6 \(\pm\) 2.8 years at pretreatment, range 15.8-26.8 years) with skeletal Class III malocclusion (ANB \(<\) 1\({}^{\circ}\)) were used for this study. TMJSs (AS, anterior space; SS, superior space; PS, posterior space; MS, medial space; CS, central space; LS, lateral space) were measured at each stage of treatment (T0, pretreatment; T1, presurgery; T2, postsurgery; T3, posttreatment, and T4, retention) and were compared according to gender, side, vertical skeletal pattern, number of surgery sites, and amount of mandibular setback. At T0, TMJSs were significantly greater in SS than in AS and PS. The ratio of AS to SS to PS was 1.0 to 1.5 to 1.1. TMJSs were significantly greater in MS and CS than in LS. The ratio of MS to CS to LS was 1.0 to 1.0 to 0.8. All TMJSs in males were significantly greater than in females except in PS. TMJSs on the left side were significantly greater than on the right side only in PS. TMJSs were not significantly different depending on the SN-MP, number of surgery sites, and amount of setback. From T0 to T4, there were no significant changes in TMJSs or their ratios according to gender, side, sella to nasion (SN), mandibular plane (MP), number of surgery sites, and amount of setback. Exceptionally, at T4, SS and CS were significantly greater in the small amount of setback group than in the large amount of setback group. There were no statistical changes in TMJSs throughout all stages when skeletal Class III patients were treated with surgery.  
class III malocclusion; cone-beam computed tomography; orthognathic surgery; temporomandibularbular joint space