esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion  
The path accuracy of the robot is important in applications where it is necessary to follow the curve exactly. Currently, this parameter cannot be found in the robot parameters. The accuracy of this parameter depends not only on the mechanical accuracy of the robot but also on the control system, specifically, how exactly and with what frequency it determines individual positions.  
The overall analysis of all the data measured and calculated has shown that a change in the nominal speed, namely from 10% to 50% or 100%, does not affect the overall path accuracy of the collaborative Fanuc robot. The ISO standard prescribes these measurements to be performed under a full nominal load, which, in our case, means 10 kg. The path-accuracy values remained at the same levels at changed speeds, or deviations were very small. Repeated measurements have manifested no abrupt deviations in the robot. As has been shown in the plotted overall path accuracy, it is clear that throughout its travel, the robot maintained a very stable path, and neither an increase nor a decrease in speed resulted in any errors.  
Figure 23: Overall path accuracy plotted under a 100% load and at 100%, 50%, and 10% speed, respectively, for points P10 to P1.  
Figure 22: Overall path accuracy plotted under a 100% load and at 100%, 50%, and 10% speed, respectively, for points P1 to P10.  
The main advantage of the proposed experimental method is that the measuring system it has used, i.e., GEPARD, is highly precise. The uncertainty of measurement can be assessed from several points of view. The certainty of measurement is influenced by the measuring device, especially the PSD sensor, and the repeatability of aiming the center of the laser rays' beam at the PSD sensor. The manufacturer states the repeatability of measurement of the device itself is \(\pm 1\) um. Another effect influencing accuracy may be the situation of the receiver in the direction of the \(z\)-axis and the effect of the angle of the incident laser beam on the PSD sensor. This inaccuracy may be in the order of microns, yet precise positioning and aiming are capable of mostly eliminating it. The most important effect is the environment traversed by the laser beam. This impacts all measurements where the beam passes through the inhomogeneous environment, even those where measurement is performed using an autocollimator.  
In addition, another advantage of this device compared to laser tracker technology is that it is several times cheaper. This experimental method is of a specific type, the main benefit of which is the lower price of the measuring chain, starting with the measuring system all the way up to making a flange with the weight. Further modification might yield automated data harvesting and rendering of the required charts that could serve the purpose of error detection, i.e., searching for significant deviations in the robot's operation. The predictive power of these data should lead to the prevention of costly maintenance.
# A Blockchain-Based Secure Inter-Hospital EMR Sharing System
## 2 Preliminary and Security Requirements
### Preliminary
#### 2.1.2 Elliptic Curve Group  
Digital network systems are essential technologies in our daily life, with large amounts of documents and information being transmitted and exchanged over them. Thus, it is very important to guarantee the security of these transmitted and exchanged messages. To ensure the security of these important documents and messages, several digital encryption systems have therefore been proposed by researchers. The elliptic curve cryptography [48] was proposed in 1985, and the length of its message is shorter than that of the Rivest-Shamir-Adleman (RSA) encryption system. A brief introduction to the elliptic curve group technology and its corresponding difficultly mathematical problems as follows:  
Allowing \(F_{q}\) to be a prime finite field, \(E/F_{q}\) is an elliptic curve defined over the prime finite field \(F_{q}\), and \(P\) is a generator for a cyclic additive group of the composite order \(q\). The point on \(E/F_{q}\) is together with an extra point \(\Theta\), which is called the point at infinity, and it forms a group \(G=\left\{(x,y):x,y\in F_{q};(x,y)\in E/F_{q}\right\}\cup\left\{\Theta\right\}\). \(G\) is a cyclic additive group of composite order \(q\). Scalar multiplication over \(E/F_{q}\) can be computed as \(tP=P+P+\ldots+P\), which is added \(\mathrm{t}\) times.  
The following problems exist for the elliptic curve Diffie-Hellman (ECDH) method:  
**Computational Diffie-Hellman (CDH) Problem**: \(aP\) and \(bP\) are given first, and where \(a,b\in R\). \({Z_{q}}^{*}\) and \(P\) are the generators of \(G\), the value \(abP\) is computed.  
**Decisional Diffie-Hellman (DDH) Problem**: \(aP\), \(bP\) and \(cP\) are given first, and where \(a,b,c\in R\). \({Z_{q}}^{*}\) and \(P\) are the generators of \(G\), then whether \(cP=abP\) or not is confirmed, and this is equal to confirming whether \(c=ab\mathrm{mod}q\) or not.
## 3 Results and Discussion
### Cases Design
#### 3.1.2 Design of Thermal Damage Conditions  
In order to analyze the effects of thermal damage caused by time-varying and extreme thermal loads on satellite health during orbit operation, we designed four conditions as shown in Table 3. In these cases, case I serves as a reference case. By comparing the Cases II, III, IV and the reference case I, respectively, the effects of the magnitude, duty cycle and period of different thermal loads on satellite health can be analyzed. The pulse rectangular wave is used in the time-varying heat load. Where duty ratio refers to the proportion of thermal load time relative to the total time in an impulse cycle. For example, in Case I, the duty ratio is 1/6, indicating that the thermal load of 10 s is 2 W/cm\({}^{2}\) in an impulse cycle, and the remaining heat load of 50 s is 0 W/cm\({}^{2}\).  
The target of thermal damage is the temperature controller in the thermal control subsystem. The temperature controller as a thermal control component guarantees the normal operation of other satellite core components, but it cannot withstand large thermal loads because it does not have good cooling. So, the final simulation selects 2 W/cm\({}^{2}\) and 4 W/cm\({}^{2}\). In the initial moment of simulation, the target temperature controller is loaded with extreme thermal loads and the satellite thermal health response is solved by using the THIEM.
## 4 Algorithm Description
### Static Configuration in Clustered Networking
When one node reaches the transmission boundary of the other node after t seconds, the link will be disconnected. At this point, \(D(t)=R\), where \(R\) is the communication radius and \(t\) represents the connection time of the two nodes. Following the above equation, the calculation result \(t\) of the function is defined as the residual link lifetime (\(RLL\)); it can be obtained that \(RLL\) is  
\[RLL=\frac{-B+\sqrt{B^{2}-4 AC}}{2A}, \tag{5}\]  
\[\left\{ \begin{array}{c}A={u_{ij}}^{2}+{v_{ij}}^{2}\\ B=2(x_{ij}u_{ij}+y_{ij}v_{ij})\\ C={x_{ij}}^{2}+{y_{ij}}^{2}-R^{2}\end{array} \right.. \tag{6}\]  
Calculate the residual link lifetime of all nodes in the cluster when the train nodes run into the cluster, and select the node in the cluster with the longest residual link lifetime as the node communicating with the train. At this time, the segment of the link has good stability. Next, statically configure the fixed source node using an improved routing discovery algorithm. After static configuration, perform the following dynamic addressing algorithm.
## 3 Experiment and Analysis
### Sensitivity Analysis of the Voronoi Model's Parameters
#### 3.1.2 Sensitivity Analysis of the Defect's Position Uncertainty Threshold  
The impact of the defect's position uncertainty threshold \(\delta\) on the Voronoi model is analyzed using \(\alpha=0.080\) and \(\tau=0.001\). As shown in Figure 18, the highest recall of 84.4% is observed for \(\delta\) values of 0.020, 0.060, 0.070, 0.080, 0.100, and 0.110 m, aligning with the estimation driven from the tool specifications.  
When \(\delta=0.0\) m, the model achieves a recall of 81.5%. Under this configuration, mixed nearest neighbors are not identified, which causes the model to bypass ICP optimization and rely solely on linear optimization using linear programming, as shown in Equation (2), where now \(\mathrm{T}^{\prime}\left(\widetilde{\mathrm{P}_{i}}\right)=\widetilde{ \mathrm{P}_{i}}\). These findings suggest that the proposed linear optimization approach can provide moderate accurate results without requiring prior transformations, making it suitable for scenarios where preprocessing is impractical or unnecessary.
## 3 Sampling and Reconstruction  
We reviewed the ideal sampling having as base the comb. In practice, we cannot implement the ideal Dirac impulses, but we can approximate them by narrow high rectangular pulses, \(r(t)\), with area equal to 1. Nonetheless, we are interested in having the values \(x(t_{n})\), rather than \(x(t_{n})\delta(t-t_{n})\) or its realistic version \(x(t_{n})r(t-t_{n}).\) Therefore, we need to adopt a system that keeps, i.e.'memorizes', the value \(x(t_{n})\) during a sufficient time for the computer system to be able to read the value.  
The standard sampling is performed by a zero order hold. This scheme transforms the signal \(x(t)\) in a sequence of rectangles with height equal to \(x(t_{n})\) and width less or equal to the sampling interval. This procedure, called pulse amplitude modulation (usually abbreviated as PAM) in telecommunications [18], introduces an amplitude distortion and increases of the bandwidth that are corrected by a lowpass equalizer filter. However, there are several distinct ways of implementing the reconstruction and we review a few in the sequel.
# Resource Allocation in 5G Cellular IoT Systems with Early Transmissions at the Random Access Phase
## 3 System Model
### Service Process in Uplink and Downlink  
EDs are associated with traffic in both the uplink and downlink directions. The service of a packet in the uplink direction requires the successful passing of RA only or RA and DT phase depending on the packet size; see Figure 2. If the packet size \(S\) is smaller than a certain threshold \(T_{S}\), an early transmission mode is utilized, where the information is transmitted as part of the preamble. Otherwise, data are transmitted during the DT phase. It should be noted that uplink transmissions require one RU during the DT phase.  
Traffic in the downlink direction proceeds directly to the DT phase, as the identifier of the ED to whom traffic needs to be sent is available at the BS. Both downlink and uplink traffic is multiplexed in the DT phase. At the RA phase, there are \(n_{1}\) RUs, each having \(l\) preambles for the RA for uplink EDs. We denote \(L=ln_{1}\). The packets in the DT phase are served by using the first come first served (FCFS) service discipline.  
We consider and compare two access schemes: one that utilizes EDT and one that does not. In contrast to the four-step RA scheme specified in 3 GPP Release 17 [31], in which each ED must initially transmit Msg1 to secure an uplink grant for the transmission of Msg3, the two-step RA scheme enables each ED to convey both Msg1 and Msg3 in a single message, designated as MsgA, without the necessity of an uplink grant. Consequently, the two-step RA scheme aligns with grant-free random access, whereas the four-step RA-SDT scheme corresponds to grant-based random access. As Figure 3[15] illustrates, each node transmits its data payload along with the preamble in MsgA. If the random access response (RAR) message and the radio resource control (RRC) release message are received within the MsgB response window, then the node knows that its MsgA transmission has been successful.
# Blind Compensation of \(I/q\) Impairments in Wireless Transceivers
## 3 Simulation Results
### BER Performance in the Presence of Multi-Path Channel  
#### 3.2.1 Parameter Estimation under Known Channel  
Another important factor in the evaluation of the proposed methodology is the effect of the wireless channel on the system performance. The problem of connection between transceiver impairments and channel estimation has been explained in [15; 28; 29]. In order to understand the effects of channel on the proposed mitigation strategy, an OFDM signal was generated to evaluate the performance of the proposed technique under the influence of wireless channel. Random data bits were generated and modulated using 16-Quadrature Amplitude Modulation (QAM). A 1024-point inverse Fourier transform was applied to this modulated signal. Modulator imbalance was applied to the signal and the signal was passed through a multi-path channel with the channel taps [\(0.866+0.5j\) \(0.0643+0.0766j\) \(0.0098-0.0017j\)] [15]. At the receiver, the demodulator imbalance parameters were applied; and, the signal was then fed to the post-compensation algorithm. The performance of the proposed mitigation methodology was tested after channel equalization, assuming that the channel state was known. The corrected signal was demodulated after application of Fast Fourier Transform (FFT); and the BER was computed. The BER performance vs. SNR is shown in Figure 8. It can be seen that the proposed method can reasonably estimate and correct for the joint modulator and demodulator impairments in the presence of multi-path channel and AWGN noise. The achieved BER using the proposed methodology is very close to the AWGN bound for all values of SNR.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Signal** & **Image Suppression before** & **Image Suppression after** \\  & **Compensation (dB)** & **Compensation (dB)** \\ \hline S1 (WCDMA 1101 with \(f_{c}\) around 10 MHz) & \(-16.2\) & \(-28.7\) \\ S2 (WCDMA 1101 with \(f_{c}\) around 5 MHz) & \(-15.5\) & \(-28.7\) \\ S3 (WCDMA 1101 with \(f_{c}\) around DC) & \(-15.4\) & \(-28.8\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: IMGsup using proposed Methodology for \(g\) = 0.92 dB, \(g^{\prime}\) = 0.5 dB and \(\theta=-6\) degrees, \(\theta^{\prime}=-2\) degrees under 20 dB SNR.  
Figure 8: Bit error rate (BER) vs. SNR for the proposed model for 16 QAM orthogonal frequency division multiplexing (OFDM) signal with 1024 subcarriers for \(g=g^{\prime}=0.92\) dB and \(\theta=\theta^{\prime}=-6\) degrees.
# Relevancy Between Objects Based on Common Sense for Semantic Segmentation
###### Abstract
ViT [19] is the first work built with a pure transformer for the image classification task and outperforms other CNN-based architectures. Following the method used in the image classification task, the semantic segmentation task is also regarded as a sequence-to-sequence prediction task. The transformer is proficient in modeling long-range dependencies in the data, SETR [20], Swin transformer [21] and BEiT [22] took full advantage of it and significantly surpassed the FCN-based models. State-of-the-art models are computationally expensive. Many works focus on speeding up the inference of their models. ERFNet [23] reduced the resolution of the input image. BiSeNet [24] introduced a fast downsampling context path to extract semantic information and a simple spatial path to preserve spatial information. FastFCN [25] proposed the joint pyramid upsampling module to extract high-resolution feature maps. In this paper, we aim to provide a post-processing method for the semantic segmentation task. It is an attempt and exploration of a new idea. First, we count the frequency of paired occurrences of adjacent connected components in the training set and build a relevancy matrix. The class of the central connected component is highly correlated with the category of the surrounding area. We get prior probabilities from the relevancy matrix. Then, we propose two post-processing methods for the semantic image segmentation task. Based on the average confidence of the central connected component, we apply the appropriate post-processing method for it. Recently, popular methods based on deep learning have focused on how to improve the performance of prediction models. We propose two new post-processing methods to improve the original results of the prediction model, which is different from the prediction methods, and also our innovation. Our proposed post-processing method improves the mean IoU of UperNet50 [26], OCRNet [27] and SETR-MLA on the ADE20K [28] validation set with single-scale inference from 40.7%, 43% and 48.64% to 42.07%, 44.09% and 49.09%, and the mean IoU of PSPNet, DeepLabV3 and OCRNet on the COCO-Stuff dataset [29] validation set with single-scale inference from 37.26%, 37.3% and 39.5% to 38.93%, 38.95% and 40.63%. In practical applications, in most cases of autonomous driving, it is a street view image that has fewer categories, and the post-processing proposed does not have much effect. For application scenarios, such as unmanned aerial vehicle navigation, due to many objective factors, such as light, shooting angle and weather, the images taken will be partially blurred or include a number of categories. For processing these complex images, the post-processing method will be very useful.
# Methodology for Conceptual Navigational 3D Chart Assessment Based on Eye Tracking Measures
## 3 Results  
### Visual Assessment  
In both the 2D and 3D scenarios, testers focused their attention on similar locations, while in the 2D maps, the areas of focus were more dispersed. On 2D maps, testers focused their attention much more on the legend than they did with the 3D maps. When comparing inexperienced testers with experienced testers, it was noted that the heatmaps for inexperienced testers were more spread out, meaning that these testers performed tasks more chaotically; inexperienced testers sometimes focused on unusual objects that were not part of the task. Furthermore, the experienced testers looked at the legend less often, leading to the conclusion that they relied mainly on their knowledge when performing the test. A comparison between men and women, on the other hand, showed that men focused on fewer objects than women. The two genders also analysed the legend differently, with women focusing more on descriptions and men on symbols of objects. As a result, women were more likely to correctly identify objects than men. Some test scenarios proved to be very problematic for the testers (this was evidenced by the heatmap generated over almost the entire test scenario, indicating high uncertainty), leading to the conclusion that analysing only heatmaps is insufficient. Table 3 provides a summary of differences in visual attention patterns between experienced and inexperienced testers, while Table 4 includes differences between male and female testers.  
We noted that the visual assessment method was problematic for drawing final conclusions about whether the 3D map was more effective than the 2D map. We found this method ineffective for the unambiguous choice of an effective map. This method could be more useful in the assessment of one-map scenarios but is less useful during the testing of multiple maps. The strengths of this method are its identification of problematic cases and the collection of preliminary insights related to the interpretation of map content or the behaviour of tester groups. This method could also be subjective because it depends on the experience of the assessor and is time-consuming.
# State-of-the-Art Review of Structural Vibration Control: Overview and Research Gaps
## 6 Optimized Control System Designed to Tackle Practical Implementation Challenges
### Control Systems for Optimal Placement and Number of Control Devices  
Strategically positioning dampers optimally enhances control performance and reduces the system's reliance on external power sources, thus lowering the overall cost of the control system and creating additional available space. Furthermore, an optimally placed, compact set of dampers can deliver the same level of performance as a complete set, typically requiring less energy to generate control forces. Ideal locations for these dampers may include the lower floors and other vulnerable areas of civil structures, where seismic excitations often induce significant nonlinear deformations [51; 194; 195; 196].  
An overview of the optimal damper distribution as a passive energy dissipation system for retrofitting structures against earthquakes is presented in [44]. [PERSON] and [PERSON] [197] introduced an algorithm for determining damper locations based on their maximum contribution to total seismic energy dissipation. [PERSON] et al. [4; 198] proposed a multi-objective genetic algorithm to optimize the placement of control devices and sensors, considering cost and seismic control performance when designing structural control systems. To study the optimal placement of devices, the linear quadratic Gaussian (LQG) algorithm emerges as the most employed in the studies reviewed, as seen in the works of [4; 197; 198; 199] and [44].
# Optimization Design of Lattice Structures in Internal Cooling Channel of Turbine Blade
## 4 Results and Analysis
### Sensitivity Analysis
#### 4.1.4 Optimization Results Comparison  
Table 8 shows the comparison between the initial model and the optimized model. In order to reveal the performance improvement of the optimized structure compared with the original structure, a representative Pareto solution set of Op-I or Op-II was selected. As can be found from Table 8, for Op-I, when the \(Nu\) reached 150, it was about 24.1% higher than that of the initial model. At the same time, the relative density decreased by 31%. For Op-II, when the \(Nu\) reached 160, it was 28.8% higher than that of the initial model, and the relative density was basically the same as the initial model. Therefore, the optimization results were very effective.