esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In the present work, an effective ten-element MIMO antenna system that is Pi-shaped has been designed, modeled, and tested for the upper mid-band of smartphones in the next generation. The proposed system also implants the LTE 46 (5.15-5.925 GHz), LTE 47 (5.855-5.925 GHz), and n102 (5.925-6.425) GHz, with the help of which it has a fractional bandwidth of 32.7%. Based on the isolation and averaged efficiency results of the proposed antenna system, which is better than 10 dB and ranges from 76.12 to 91.57%, it reveals that the proposed antenna system lends itself to wideband applications in modern communication systems. The overall size of antenna array is 125 mm \(\times\) 70 mm using RT/5880 as the dielectric material, which fits into current and future smartphone applications. Thus, through adopting a decoupling structure, the self-coupling between the adjacent antennas is significantly minimized, thus maintaining the operation functionality of the MIMO system. The reflection coefficients, radiation patterns, and efficiency measurements attest to the efficacy of the proposed design. For 1 g tissue, the maximum and minimum SARs  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Ref.** & **Frequency (GHz)** & **\% Bandwidth** & **Isolation (\(-\) dB)** & **ECC** & **Total Eff. (\%)** \\ \hline
[11] & 4.4–7.1 & 46.96 & \(>\)17 & \(<\)0.002 & 64–82 \\ \hline
[39] & 3.4–3.8 & 11.11 & \(>\)20 & \(<\)0.01 & 87 \\ \hline
[41] & 4.4–6.0 & 30.77 & \(>\)14.2 & \(<\)0.32 & 46.1–76.9 \\ \hline
[40] & 3.29–6.61 & 67.1 & \(>\)16.6 & \(<\)0.057 & 53–86 \\ \hline Proposed & 4.7–6.5 & 32.72 & \(>\)10 & \(<\)0.03 & 76.12–91.57 \\ \hline \end{tabular}
\end{table}
Table 2: Performance comparison of various state-of-the-art 5G antennas.  
obtained in the hand simulation are 0.118 W/kg and 0.0606 W/kg, while for 10 g tissue in the presence of head simulation, they are 18.7 W/kg and 1.72 W/kg, respectively. In this work, high-isolation, compact, and wideband design issues have been discussed for the Pi-shaped MIMO antenna as a promising solution for the design of future massive connectivity communication systems with comparatively high data rates.  
Conceptualization, M.Z.; Formal analysis, Y.A.; Methodology, M.Z.; Software, M.Z.; Validation, Y.A.; Writing--original draft, M.Z.; Writing--review and editing, Y.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
All authors declare that they have no competing interests.
# State Residualisation and Kron Reduction for Model Order Reduction of Energy Systems
## 1 Introduction
Since the method ignores all dynamics of the power lines except the ones directly connected to converters, and discards states with short time constants, the obtained fixed reduced model does not adapt to the type and location of practical events. In reference [24], a new MOR technique based on a non-projection-based state residualisation approximation technique is proposed, which computes the Hankel Singular Values and identifies the most observable and reachable states in the balanced realisation. However, to maintain the physical structure and retain the variables during the MOR, it does not truncate the system; instead, it links the most observable and reachable states in the balanced realisation's system back to the states in the original physical system by using the fact that the eigenvalues in both systems are the same. The method is straightforward, but it may not result in a much-reduced system as two participation factor analyses are performed in a row, and it is unable to take into account each simulated event separately. In reference [25], another non-projection and state residualisation approximation-based MOR technique is proposed. This technique, belonging to the family of singular perturbation methods [26], preserves the physical variables and parameters of the system, achieves a bounded approximation error, and adapts to the simulated event and the observed system variables. Since the size of the reduced model was arbitrarily chosen in [25], this paper proposes a systematic method, i.e., alignment with the phasor approximation model, which improves the accuracy of the reduced model. Guidance is also provided here regarding the choice of the criterion, \(\epsilon_{part}\), which affects the form of the reduced models in subsequent steps and may eventually affect the final result, i.e., selected according to the event type. In addition to applying a state residualisation approximation technique and indicating which differential equations should be made algebraic, Kron reduction is applied to the algebraic power network equations, leading to a reduced simulation time. The next section, Section 2, presents the modelling of grid-forming converters (GFMs) and other power components. The non-projection-based state residualisation approximation and Kron technique are then described in Section 3. Subsequently, in Section 4, the accuracy and efficiency of the approach are illustrated on a modified IEEE 39-bus system, where all generation is assumed to be renewable and connected through GFM-based converters.
# 3-D Point Cloud Registration Using Convolutional Neural Networks
## 7 Conclusions  
This paper resolves the time-consuming problem of 3-D point cloud registration. The estimation time is significantly shortened by using the proposed two-stage CNN architecture, 3-D CNN model and 2-D CNN model. To generate the training data sets, firstly, the model point cloud of a specific object is randomly rotated in the full range from \(-180^{\circ}\) to \(180^{\circ}\) and the small range from \(-15^{\circ}\) to \(15^{\circ}\) and then downsampled several times. Then, these two point cloud data sets, according to the full range and the small range of rotation angles, are passed through two descriptors, SSPD and 8 CBCP, respectively. Based on these training data sets, CNN models are independently trained for each specific object.  
Figure 16: The registration results of Armadillo data for test sample 5: (**a**) The initial state; (**b**) 3-D CNNs then 2-D CNNs, (**c**) RANSAC then ICP, (**d**) Fast Global Registration.  
Figure 14: The registration results of Dragon data for test sample 20: (**a**) The initial state; (**b**) 3-D CNNs then 2-D CNNs, (**c**) RANSAC then ICP, (**d**) Fast Global Registration.  
Figure 15: The registration results of Buddha data for test sample 7: (**a**) The initial state; (**b**) 3-D CNNs then 2-D CNNs, (**c**) RANSAC then ICP, (**d**) Fast Global Registration.  
object to update optimal weights with the aim of estimating the relative orientation between the 3-D model point cloud and a 3-D data point cloud. Specifically, to guarantee comparable accuracy with existing algorithms such as RANSAC then ICP approach, the 2-D CNN model is trained on the labeled data set created by the 8 CBCP descriptor. Hence, in the training process, this 2-D CNN model can thoroughly learn distinct characteristics of several point clouds with different orientations in the case of the small uncertainty. After training, the proposed two-stage CNN architecture can quickly estimate the transformation between the model point cloud and a data point cloud in which the translation is estimated based on the average values of these two point cloud data sets. The experimental results show that the proposed algorithm can precisely and quickly estimate the relative transformation between the model point cloud and a data point cloud in fixed time. This leads to potential significance and applicability of the proposed algorithm for the purpose of estimating the pose of an object based on 3-D point clouds in automated assembly systems. Additionally, according to the results of this research, 3-D partial point cloud registration employing CNNs appears to be an important direction of future research.  
Conceptualization, W.C.C.; methodology, W.C.C.; writing-original draft preparation, W.C.C. and V.T.P.; writing-review and editing, W.C.C. and V.T.P.  
This research was supported by Ministry of Science and Technology, Taiwan, R.O.C. under grants MOST 107-2221-E-027-112 and MOST 108-2221-E-027-109-MY2.  
The authors declare no conflict of interest.
# Investigation of THz Absorptive Signatures in Opioids
## 4 Experimental Results
### Oxycodone Samples  
Next, the oxycodone SUTs O#1, O#2, and O#3 were measured. Figure 7 shows the transmittance spectrum of SUT O#1 and O#2, respectively. The strongest water vapor lines from the ambient air are exhibited: 1.102, 1.159, and 1.676 THz [22]. The three characteristic lines--0.530, 1.205, and 1.370 THz--of lactose monohydrate are found too. Even the weakest 1.205 THz is present. This confirms that lactose monohydrate was a \"filler\" material.  
By excluding the water vapor lines, as well as the lactose lines, the 1.567 THz signature on SUT O#1 and 1.552 THz on SUT O#2 are possibly an absorption line of oxycodone because of its proximity to the MD-simulated line at 1.595 THz shown in Figure 3, which is also the strongest line, so most likely to appear experimentally. The small shift of center frequency from 1.567 to 1.552 THz may be a secondary humidity effect through the hydration level in the samples, which is known to create shifts in the center frequency of THz vibrational resonances of powder samples [23]. Figure 7 also shows \"dips\" at 0.784, 1.037, and 1.637 THz. Whether or not they are absorption lines or artifacts remains to be understood. They don't belong to acetaminophen when compared with [24].  
Figure 6: Spectra of the lactose control samples. (**Top**) Power (arbitrary unit) vs. frequency (THz); (**Bottom**) transmission vs. frequency, which is corrected with an offset frequency. The \(\sim\)1.478 THz “dip” of sample L#1 may be related to lactose hydrated by water molecules [21].  
Figure 8 shows the spectrum of SUT O#3. Again, the three lines--0.530, 1.205, and 1.370 THz--of lactose are present, the same as in the case of O#1. A \"dip\" of the signature appears at \(\sim\)1.565 THz, which may be attributable to the oxycodone alone. It is broad with its lower limit at \(\sim\)1.565 and the upper limit at \(\sim\)1.591 THz.  
Figure 8: Spectra of oxycodone O#3. (**Top**) Power (arbitrary unit) vs. frequency (THz); (**Bottom**) transmission vs. frequency, which is corrected with an offset frequency.  
Figure 7: Spectra for oxycodone O#1 and O#2. (**Top**) Power (arbitrary unit) vs. frequency (THz); (**Bottom**) transmission vs. frequency, which is corrected with an offset frequency.
# A Brief Overview of Energy Efficiency Resources in Emerging Wireless Communication Systems
## 5 Discussion  
This review categorizes the energy efficiency framework for wireless communication networks as both hardware and operations based. The hardware distribution was analyzed, including high-power generation and consumption components, including power amplifiers and energy generating sources. It was suggested that the non-linearity caused by power amplifiers might be reduced by utilizing power amplifiers with non-linear components and deployable investigated technologies. Cost-effective and reliable renewable energy resources could be used rather than relying on heavy-duty diesel generators to power transmission base stations in areas where power outages are still common. Despite the large initial capital investment in renewable resources, the long-term minimal operating cost is a significant tradeoff compared to the high operating cost of diesel generators. Solar and wind are two renewable resource options that, depending on the geographical variables, may favour one over the other in the deployment area. The energy-efficient framework's operation-based or quasi-hardware component deals with the physical topology of the wireless network, component conditioning, and transmission mechanisms. According to this review, the heterogeneous network, which must be backwards compactable with developing technologies, is an increasingly evolving component of the energy-efficient framework. The base stations might be set to run on demand by enabling the sleep mode approach. The deployment of low power consumption cells in hotspot zones is a critical component in the evolution of the heterogeneous network. With the advent of light-fidelity networks, the integration of attocells into current topologies has become critical in pursuing entirely green and sustainable technology. While the introduction of enhanced data rate low power consumption visible light technology does not imply a complete replacement, its complimentary properties in high-speed traffic backhauling guarantee a smooth implementation of the future generation of wireless communication technology. Optimized signal conditioning strategies have been proposed to improve the energy efficiency of the transmission process even more. Following the development made so far, novel techniques are still sought by investigating variants of the existing optical multicarrier techniques. An excellent optical multicarrier solution will combine spectral and energy efficiency performance features.
## 1 Introduction
### Motivation and Background
Additionally, a mixed controller, which includes a time-delay feedback controller and an FO PD controller, was designed to eliminate the chaos of the FO system. The problems of stability and stabilization of the FO power system with time delays were investigated in [31]. Based on the theory of FC and the Lyapunov functional technique, the relevant stability criteria were obtained. Meanwhile, Lyapunov functionals were constructed, and the free-weighing matrix technique was introduced to reduce the conservatism of the criteria. In [32], some novel asymptotic stability criteria were deduced for different forms of multivariable fractional-order systems (MFOSs) with FO parameters between 0 and 1 under time delays based on the M-matrix. Initially, the general asymptotic stability condition of ordinary systems was extended to MFOSs. Subsequently, the stability of linear and nonlinear MFOSs was investigated, and their asymptotic stability criterion was derived using the M-matrix method. Moreover, ref. [33] focused on the stabilization of nonlinear FO time-delay systems in the presence of faults. In this research, a general class of nonlinear FOSs was considered, where faults caused variations in the system dynamics and actuators. In summary, while significant progress has been made in understanding the stability and control of FOSs under both saturation and time delays, further research is needed to fully comprehend the interplay between these two factors. Developing a more integrated approach could yield valuable insights for creating advanced control strategies that ensure the stability of real-world FOSs operating under practical constraints.
# An Empirical Study of Cluster-Based MOEA/D Bare Bones PSO for Data Clustering +
## 3 Materials and Methods
### Data  
The algorithms are tested on 13 datasets obtained from the UCI Machine Learning Repository: Appendicitis, CMC, Dermatology, Ecoli, Glass, Iris, Seeds, Sonar, Vehicle, WDBC, Wine, WOBC and Segment [15]. Full details and t-SNE biplots of the datasets are found in [30]. These datasets have different types of characteristics, such as sizes N, dimensions n and cluster numbers c, as well as having different intensity of densities and overlapping. We are particularly interested to see the effects of CM-BBPSO on challenging datasets with highly overlapping clusters and a combination of the following characteristics: high number of classes, mixed densities, imbalanced class ratios. We choose a mixture of datasets for which most algorithms tend to produce good results as well as challenging datasets, such as Glass, Sonar, Ecoli, Segment, Vehicle and CMC. Many works tested algorithms with datasets with 2 or 3 classes, such as Iris, Wine, Appendicitis, WOBC and WDBC, which give good results.
# Access Control and Pilot Allocation for Machine-Type Communications in Crowded Massive MIMO Systems
## System Model and Preliminaries
### Access Class Barring Scheme  
A well-received method proposed by 3 GPP for alleviating the congestion of MTCDs is ACB. When congestion occurs, the ACB scheme is used to prevent the access of MTCDs and reduce overload in the network. In each slot, BS broadcasts an ACB factor and the barring time to all MTCDs. Each MTCD generates a random number \(q\)\((0\leq q\leq 1)\). If \(q\) is below the ACB factor, the MTCD passes through the ACB scheme applying the random access procedure. Otherwise, it is barred for a random period of time [26] and has to regenerate the random number. The traditional ACB scheme sets a fixed barring factor during the network access process of MTCDs. A traffic-aware ACB is proposed in [20] to relieve the access delays and increase the access success rate, where the BS changes the barring factor based on the number of device arrivals. In this paper, we propose optimizing the barring factor by maximizing the access success rate. Based on the number of arrivals in the current slot, we compute a barring factor to achieve the maximum access success rate. We then use this barring factor for the next slot.
## 5 Implementation of the Study
### Performance Evaluation
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Detection** & \begin{tabular}{c} **Accuracy** \\ **(1000** \\ **Dataset)** \\ \end{tabular} & \begin{tabular}{c} **Accuracy** \\ **(12,000** \\ **Dataset)** \\ \end{tabular} & \begin{tabular}{c} **Precision** \\ **(1000** \\ **Dataset)** \\ \end{tabular} & \begin{tabular}{c} **Precision** \\ **(12,000** \\ **Dataset)** \\ \end{tabular} & \begin{tabular}{c} **Recall** \\ **(1000** \\ **Dataset)** \\ \end{tabular} & \begin{tabular}{c} **Recall** \\ **(12,000** \\ **Dataset)** \\ \end{tabular} \\ \hline \begin{tabular}{c} Worker \\ Machine \\ Control box \\ \end{tabular} & 0.98 & 0.99 & 0.9830 & 0.9912 & 0.9734 & 0.9817 \\ \begin{tabular}{c} Mobile \\ Control box \\ \end{tabular} & 0.96 & 0.97 & 0.9719 & 0.9732 & 0.9617 & 0.9751 \\ \begin{tabular}{c} Toolbox \\ \end{tabular} & 0.95 & 0.96 & 0.9464 & 0.9621 & 0.9470 & 0.9587 \\ \begin{tabular}{c} Toolbox \\ \end{tabular} & 0.98 & 0.98 & 0.9851 & 0.9878 & 0.9722 & 0.9772 \\ \
\begin{tabular}{c} Tool \\ \end{tabular} & 0.94 & 0.95 & 0.9472 & 0.9553 & 0.9419 & 0.9454 \\
\begin{tabular}{c} Product \\ \end{tabular} & 0.93 & 0.94 & 0.9353 & 0.9425 & 0.9221 & 0.9533 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Evaluation of object detection performance. Continuing to the next point, the model was set to 100,000 iterations to avoid overfitting, and the accuracy was approximately 93% for 21 videos and 94% for 31 videos. However, analysis results presented the possibility of incorrectly classifying a frame despite successfully classifying the anomaly, which indicated low false negatives. For example, the landmarks generated by the model did not align with the landmarks of the human body (Figure 10a). The hand landmarks were not correctly identified as covered by the body landmarks (Figure 10b), thus, leading to incorrect classification. However, despite the misalignment, the model successfully labeled the anomalous behavior. Figure 8: Confusion matrix for object detection: (**a**) the result of using 1000 dataset, and (**b**) 12,000 dataset. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Pose Label**} & **Accuracy** & **Accuracy** & **Precision** & **Precision** & **Recall** & **Recall** \\  & **(21 Videos)** & **(31 Videos)** & **(21 Videos)** & **(31 Videos)** & **(21 Videos)** & **(31 Videos)** \\ \hline Standing & 0.95 & 0.96 & 0.9530 & 0.9646 & 0.9534 & 0.9644 \\ Walking & 0.94 & 0.95 & 0.9319 & 0.9534 & 0.9257 & 0.9512 \\ Touching & 0.95 & 0.96 & 0.9564 & 0.9581 & 0.9582 & 0.9634 \\ Holding & 0.95 & 0.96 & 0.9551 & 0.9614 & 0.9522 & 0.9548 \\ Bending & 0.94 & 0.94 & 0.9472 & 0.9495 & 0.9417 & 0.9432 \\ Sitting & 0.88 & 0.90 & 0.8751 & 0.8984 & 0.8619 & 0.9021 \\ Squatting & 0.89 & 0.90 & 0.8851 & 0.9058 & 0.8717 & 0.9049 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Evaluation of human pose recognition performance. Figure 9: Confusion matrix for worker pose recognition: (**a**) result of 21 videos, and (**b**) result of 31 videos.
# Field Trial and Performance Evaluation of Soybean-Based Bio-Fog Seals for Asphalt Rejuvenation
## 2 Materials and Methods
### Experimental Plan
#### 2.4.3 Permeability  
The falling head permeability test with the National Center for Asphalt Technology (NCAT) Permeameter is a valuable tool for assessing pavement drainage characteristics. In this study, it was employed to evaluate whether the sprayed rejuvenator effectively sealed the pavement surface. The test works by sealing the permeameter to the pavement, filling it with water, and monitoring the water level decrease over time. The rate of decrease reflects the pavement's permeability; higher values indicate better drainage and potentially less effective sealing by the rejuvenator. This method follows the guidelines established by the NCAT [38]. To ensure accurate results, the permeability test was conducted at multiple locations on the pavement surface to account for potential variations in permeability across the area.
## 4 Conclusions  
This work successfully demonstrated an automated graffiti-detection technique for cultural heritage buildings. Data from public sources was combined and used to detect, localize, and quantify graffiti on key buildings in a community. The required visual data can be collected by ordinary citizens periodically to enable more efficient lifecycle assessment of historical structures. The output of the method was the location and size of each graffiti marking, indicated by a bounding box provided on the orthophoto. As a part of this process, a robust graffiti detector was also trained here using images of graffiti collected from real-world structures, and the training data were shared publicly for other researchers to access [32]. The feasibility of the overall method was demonstrated with a historical structure in the European community: the Church of Agios Nikolaos, located in Kantza, Greece. Images were collected in two different time windows and in weather conditions to demonstrate the capability of the technique for the use of lifecycle assessment.  
To the authors' best knowledge, no vision-based graffiti detection and quantification technique exists in the literature or industry. A completely automated technique was fully demonstrated here through a real-world case study. Some practical challenges do still exist in the technique that should be mentioned. The method is not applicable to cases in which the entire facade is contaminated with graffiti, or cases in which a significant curvature exists in the outer walls of the building being assessed, which creates distorted orthophoto generation.
# A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic
## 3 Results and Analysis
### Visual Assessments
In conclusion, the proposed SOSG method proves effective in generating optimal seamlines for SAR images, yielding more comprehensive mosaic images of feature targets.