esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Control Strategies
### The First Strategy  
The two analyzed models of the open-loop reference model tracking control system have been incorporated into the closed-loop model reference PID control system shown in Figure 3. As it can be seen, there are applied two kinds of disturbances, i.e., along the damping coefficient of load rotation \(b_{s}(t)\) (case A), as well as along the loading torque \(T_{la}(t)\), both changing almost-discontinuously with some frequency (low and high-doubled  
Figure 2: Block diagram of the open-loop model reference control system with the additional time-dependent loading disturbance \(T_{la}(t)\), while variation of the additional damping coefficient \(b_{la}(t)\) is turned off, \(G_{2}\) is the second-order dynamical operator given by Equation (9).  
with respect to the lower one). This way, we introduce the next criterion of assessment of efficiency of the investigated control strategies.  
Parameters of the classical PID are constant, being selected appropriately to achieve the best system response in both analyzed cases. Results of application of the control strategy are shown in Figures 6a,b and 10a,b.  
The control law for the actual rotational velocity of the load is defined on time intervals obtained after splitting the time by appearance of step inputs of the reference control input \(u_{s}(t)\) given by Equation (10) and the pyramid-shaped function of disturbances given by Equation (12), as it follows:  
\[\begin{split} u_{c}(t)&=\beta_{1}(\theta_{lr}(t)- \theta_{la}(t)),\\ u_{a}(t)&=K_{p}\left(u_{c}(t)+T_{d}\frac{du_{c}(t) }{dt}+\frac{1}{T_{i}}\int_{t_{j}}^{t_{j+1}}u_{c}(\tau)d\tau\right)\end{split} \tag{14}\]  
for \(j=0,1,\ldots,j_{s}+j_{u}\) and parameters \(K_{p}\), \(T_{d}\), and \(T_{i}\) of the regulator. In the numerical simulation, the parameters of the regulator for both considered types of disturbance will be valued as follows: \(K_{p}=300\), \(T_{i}=1\), \(T_{d}=2\), \(\beta_{1}=1\).
## Literature Review
### Research on the Stable Matching Mechanism  
The major research focus of the international academic community on stable matching mechanisms has been to develop economic theories that are based on matching stability and the deferred acceptance procedure. Stability is critical for the participants to make their choices while considering the choices of the others in the two-sided market. [PERSON] (2008) pointed out that, although the algorithms that are used by the centralized clearinghouse had been improved multiple times so as to meet the evolving needs of hospitals and medical students, stability remained the key to the success of the matching mechanism; the deferred acceptance procedure, in turn, is critical to matching stability and many matching mechanisms have been designed based on this procedure (13). [PERSON] (2017) found that incentive compatibility extends to many-to-one matching when the agents employ truncation strategies and capacity manipulations in a Gale-Shapley mechanism (14). [PERSON] and [PERSON] (2022) proposed a matching-updating mechanism which is a solution for the stable marriage problem with dynamic preferences (15). Research on stable matching mechanisms can be sorted into three categories: one-to-one matching, many-to-one matching, and many-to-many matching.  
A one-to-one matching mechanism is also referred to as the marriage matching mechanism because it resembles the matching that is required for monogamous heterosexual marriages: each participant on one side can only match with one participant on the other side. The one-to-one matching mechanism is the most classical matching model in two-sided matching theories and scholars have conducted considerable research on this topic.  
The many-to-one matching mechanism is also referred to as the college admission matching mechanism, another subject on which many scholars have performed in-depth studies. [PERSON] and [PERSON] (1989) compared the marriage matching mechanism with the college admission matching mechanism and pointed out that the two cannot be viewed as equivalent, as the college admission mechanism only retains the main features of the marriage matching mechanism (16).  
The many-to-many matching mechanism is also referred to as the worker-firm matching mechanism. As the depth of the research has been extended, scholars have generalized the marriage matching mechanism and the college admission matching mechanism, expanding the research to the many-to-many problem (17). Worker-firm matching is a typical many-to-many matching model. In comparison to many-to-one and one-to-one matching, there is less research devoted to many-to-many matching, but this is mainly due to the sequence of theoretical development, not because the many-to-many market is unimportant.
# Impact of Texture Information on Crop Classification with Machine Learning and UAV Images
## Materials and Methods
### Datasets  
#### 2.2.1 UAV Images  
We used six UAV image mosaics taken from June to September 2017, by considering the growth cycle of highland Kimchi cabbage (Table 1). The preprocessed UAV image mosaics provided by the National Institute of Agricultural Sciences (NAAS) were acquired from a fixed-wing unmanned aerial system (UAS; eBee, Sensefly, Swiss) equipped with a Cannon S110 camera that includes green (550 nm), red (625 nm), and near-infrared (NIR; 850 nm) spectral bands (hereafter referred to as VNIR). The UAV image mosaics with a ground sampling distance of 12 cm were upscaled to 25 cm resolution to facilitate  
Figure 1: Location of the study area and the unmanned aerial vehicle (UAV) image mosaic acquired in the study area.  
data processing without loss of information. Upscaling may result in loss of textural image information. However, a significant change in the generation of texture features and classification results was not observed in our preliminary experiment at subareas in the study area, which was attributed to the size of crop parcels in the study area. Hence, the image mosaics with a 25 cm resolution were used as inputs for classification. To examine the applicability of a single-date image with texture information, the UAV image mosaic acquired on 25 August was selected due to the peak in vitality of highland Kimchi cabbage. This selection is explained in detail in Section 3.
# Heterogeneous Wireless Networks for Smart Grid Distribution Systems: Advantages and Limitations
## 5 Performance Study
### Impact of Available Contention-Free Link Capacity  
Our proposed HWN architecture relies on MPTCP, which pushes more data on to the better link, i.e., the one with higher speed and lower packet loss. Transmission over WiFi leads to less throughput due to the medium access control (MAC) control messaging mechanism and the higher chance for packet collisions as many data sources compete for the media. On the other hand, the 3G/4G link can guarantee very low data transfer time since it is a contention-free link, but this comes at a higher cost for utility companies than WiFi networks. Here, we investigate how the available capacity of the 3G/4G link affects the data share that MPTCP allocates to each interface. Figure 3 shows the data transfer time and the percentage of WiFi share that result from delivering 500 KB data from seven substations to the primary substation. The connections are configured such that the congestion window size \(W_{M}\) equal to 55 segments for each subflow. In essence, wireless channel impairments cause packet loss. Here, we assume that both links have a packet loss ratio (PLR) of 0.005. The 3G/4G link speed is varied from 384 kbps to 5.7 Mbps. As Figure 3 depicts, increasing the 3G link speed leads to a significant decrease in the amount of data transferred over WiFi (percentage WiFi share). Apparently, MPTCP gives preference to the contention-free link over WiFi even if the link speed is comparable to the available WiFi per-substation channel capacity. This happens mainly due to packet collisions.
# Low-Profile Dual-Band Reflector Antenna for High-Frequency Applications
## 2 Antenna Configuration and Design
### Element of Lower-Band SRA
In order to decrease the influence of sharp phase variation in the SRA, the value of \(\Delta\Phi\) is designed to be 90\({}^{\circ}\). It can be clearly seen from Figure 9a that no sharp phase variation arises in the middle of the SRA. The area of unavoidable sharp phase variation is moved to the edges of the SRA, not in the middle area, due to the designed \(\Delta\Phi\). Consequently, the best radiation performance of the reflector antenna is achieved, as shown in Figure 9b. The gain of radiation patterns at \(f_{\rm{i}}\) is 31.4 dBi, corresponding to an antenna aperture efficiency of 59%. Moreover, the optimized radiation patterns show that the high sidelobes are lower than \(-\)13 dB. Table 2 summarizes the estimated aperture efficiency and gain loss reduction attribution at \(f_{\rm{i}}\). The calculated total losses at \(f_{\rm{i}}\) are 2.4 dB, with taper loss as the main loss factor. Shade loss is the shielding of the lower-band SR at \(f_{\rm{i}}\). Additionally, the simulated gain is close to the calculated gain. Figure 8: In the condition that the \(\Delta\Phi\) is 170\({}^{\circ}\): (**a**) desired compensation phase of SRA and (**b**) radiation patterns at \(f_{\rm{i}}\).
## 2 Materials and Methods  
In this work, we followed a unique design idea for transmission-based wide-band polarization-converting metasurfaces, described as follows:  
1. [PERSON] et al. used a square ring as a basic building block for a periodic structure with wide operational bandwidth without performing any polarization conversion operations [32]. Therefore, the first element in the unit cell was a square ring with a width \(w2\) in order to obtain wider operational bandwidth, as shown in Figure 1. The width of the ring controls the bandwidth, as well as the separation between the two bands of operation;
2. Multiple square patches on a unit cell can cause multiple resonances, resulting in multiple bands of operation. Therefore, placing these patches along the diagonal can result in multiple operational bands [33]. In this way, three squares, \(C_{1}\), \(C_{2}\) and \(C_{1}\), were placed diagonally;
3. According to the concept from [25; 26; 27], a split circular ring along the diagonal split can enable polarization conversion operations. Therefore, a diagonal split ring with internal diameter \(d\) and split opening \(S\) was selected as the third element in the unit cell. The width of the ring was \(w1\). The effect of each parameter on the design of the polarizer is described in the following paragraph.  
Using the above-described design idea, the unit cell of the complete metasurfaces-based structure is as shown in Figure 1. It contains a square ring with metallic width \(w2\). Three diagonal square patches were adopted for the dual-band polarization conversion operation. A circular ring with a diagonal split allows polarization conversion. In Figure 1, the periodicity of the proposed unit cell is represented with \(P\). \(w1\) represents the width of the circular ring with the split length \(S\) along the diagonal. The outer square patches have the sizes C1 \(\times\) C1, whereas the inner square patch has the size C2 \(\times\) C2. The split circular ring has the diameter \(d\). The thickness of the substrate is represented as \(h\). The parameters C1, C2, \(d\), \(S\), \(w1\), \(w2\), and \(P\) were optimized to obtain a polarization conversion operation from 11.05 to 16.75 GHz and 34.16 to 43.03 GHz. The parameter \(P\) directly controls the frequency of the operation. The dimensions of squares C1 and C2 control the separation of the two operating frequency bands. Parameters \(d\) and \(S\) control the polarization conversion due to the break in the isotropicity of the structure. The width of the square ring \(w2\) controls the performance of the conversion and the bandwidth of the bands. The final optimized parameters of the proposed structure are tabulated in Table 1.
# Resource Allocation Schemes for 5G Network: A Systematic Review
## 6 Open Research Issues and Trends in 5G
### Joint Resource Allocation Techniques  
Sophisticated and advanced allocation schemes are needed broadly due to the requirement of additional computing resources. One main challenge is to develop resourceful compression algorithms for fronthaul links. From this end, it is essential to measure and analyze the latency effect on the upper layer's performance of the fronthaul. Moreover, optimal resource allocation in contexts of constrained fronthaul requires more investigation. Fronthaul links that experience packet loss can be one more thought-provoking topic. The fronthaul network is predictably extremely diverse and has latency and various link capacities, which necessarily demand re-configuration of fronthaul so it can be altered based on traffic load and network topology.
## 5 Experimental Results
### Stochastic Volatility  
Figure 5 shows that the PF using RoSS is four to six times faster than a PF using N-R/B-R. The maximum speed-up for a PF with RoSS is approximately 125 for \(P=256\) cores. Furthermore, the gap between a PF with RoSS and a PF with any other considered redistribution also increases with \(P\), in line with the results in Section 5.1. Figure 6 describes profiling information for the three PFs with \(N=2^{24}\). In Figure 5(a), it is interesting to see that RoSS is the only redistribution variant that runs faster than IS for any \(P\leq 256\), while B-R and N-R emerge as the bottleneck for a relatively low \(P\), i.e., for \(2\leq P\leq 16\). This is mostly due to the larger volume of communication in B-R/N-R, as shown in Figure 5(b). In Figure 5(b), we have considered the average time spent on all MPI calls per core as the communication time. Since \(N\gg P\) in this experiment, the time spent on the MPI_Sendrecv calls in the redistribution step is dominant over the time spent on all the other MPI routines, such as MPI_Allreduce or MPI_Exscan, which only consists of \(\log_{2}P\) single-scalar messages and up to \(2\log_{2}P\) arithmetical operations (in this case sum). Therefore, we can state that the reported average communication is equivalent (with a good degree of confidence) to the percentage of time that the cores are not used for any computation.
# Finite Element Analysis (FEA) of Palatal Coverage on Implant Retained Maximly Overdentures
## 4 Discussion
Figure 11: Results for axial loadings on three- and four-implant models with and without palatal coverage. Figure 10: Von Mises stress (MPA) in cortical and cancellous bone for palateless three- and four-implant models with and without connecting bar. One limitation of this study is that the non-axial loading could have been applied linearly and not directly to the implants. Likewise, non-axial loading could have been applied to the locator models. Additionally, since this FEA study was conducted under the premise that implant fixtures and connecting bars were well bonded as one structure, the stresses applied to the superstructure components, like the internal joints and the connecting screws between the abutments and the implant fixtures, were not analyzed. There may be some other possible limitations resulting from the loads applied only at the surface of the implants and not at a more distal location from the implants such as what commonly occurs during food chewing and normal function. The effect of loads applied on the distal cantilever could have shown a different stress distribution at the implant/bone interface due to rotational forces posterior to the fulcrum line. Furthermore, loading the bar overdenture on one side only would be a more similar action to the natural eating process instead of the bilateral loading used in this study. Another important consideration in this study is that all the implants inserted in the FEA models are parallel to each other and present no tilt or angulation. This contrasts with what often happens with these types of rehabilitation where implants have different degrees of angulations and tilts. Also, there are inherent limitations of the FEA modeling like the bone implant contact (BIC) set at 100% due to the inability to modify the modeling. Moreover, FEA studies cannot take into consideration the so called \"Realeff Effect (resilient and like effect)\" discussed by [PERSON] [56] as well as the flexibility of the attachment housings. Therefore, the findings presented in this report are restricted to these tested conditions and should be considered transferable to clinical situations carefully. Since the results of this study are empirical, additional laboratory and clinical investigation are necessary to clarify the effect and role of palatal design, number, angulation and location of implants, superstructure design, and non-axial loading effect on maxillary implant retained overdentures. Higher quality of evidence is needed to support treatment modalities for the edentulous maxilla.
## 4 Analysis and Findings of Research Questions
#### 4.1.4. Smartphone User Activities Based on Software Modality  
According to [102], ineffective coding and the selection of ineffective programming software solutions significantly contribute to the unavailability of web application services as attackers exploit the vulnerability of input fields. This condition is accomplished by either putting the SQL query command into the input or appending the query with the desired uniform resource locator (URL). These SQL queries are converted to SQL code that an attacker inserts [102; 103].  
This vulnerability injection is the primary vector through which an attacker can compromise a web application's security. In addition, rooting and jailbreaking mobile devices are the most dangerous activities leading to smartphone intrusion [89; 90]. Moreover, research [104] has indicated that threats emerge due to insufficient validation of user input information, software designed without adhering to stringent safety requirements, and vulnerability of reusable software libraries, among other issues. Cyber attacks do not solely target mobile phones but also the Android system in modern vehicles, referred to as the Android in-vehicle infotainment (IVI) system.
## 4 Performance Evaluation  
In this section, we evaluate the performance efficiency of DAWPC-MAC (Deep adaptive with power control and collision avoidance MAC protocol) and compare its energy consumption, throughput and packet delivery rate (PDR) with other protocols. This performance assessment is conducted with respect to both benchmark techniques and the variation of design parameters. TDTSPC-MAC, which uses time synchronization and power control to reduce communication collisions and improve energy efficiency in UASNs immersed in a three-dimensional underwater environment [14]. The nodes architecture can be arranged in a cluster hierarchical structure, which can further empower the efficient segmentation and monitoring of the underwater E3D domain. Using a time synchronization mechanism and power control strategy allows unicast communications though, so there aren't any collisions. Furthermore, the periodic invocation of watching and suspension modes lets nodes enter a low-energy state throughout passive intervals, conserving strength during transient intervals. The proposed TDTSPC-MAC protocol in [14] demonstrates the stability required for its application in underwater acoustic sensor networks for tracking underwater vehicles' positions and movements. This study specifically tackles the challenges present in underwater wireless sensor networks (UWSNs), such as extended propagation delays and access conflicts arising from simultaneous competition for a shared channel by groups of nodes. In this work, we address the aforementioned issues (i.e., MAC protocol design, performance with respect to varying network conditions, etc.) by proposing a novel MAC protocol (termed DCMAC), designed based on game theory to improve performance.  
In another work [42], the DC-MAC protocol optimizes transmission scheduling by considering each node's propagation delay and cluster head (CH) degree, ensuring efficient channel access and collision-free data transmission. Another proposed framework based on reinforcement learning is UW-ALOHA-QM [37], which has an optimized MAC layer designed for UWSNs. The algorithm combines reinforcement learning to enable channel sharing by UWALOHA-QM and exhibits a high degree of flexibility in mobile network environments. Through cloud connectivity and the persistence of links, UW-ALOHA-QM achieves a channel utilization of 0.66 Erlangs under ideal conditions--a performance level comparable to that of centralized protocols developed specifically for underwater networks.  
Figure 7: Considered communication workflow in proposed DAWPC-MAC.  
This method is also appropriate for mobile underwater connections where the routes that nodes take, when moving, are unpredictable.
# High-Frame-Rate 3-D Vector Flow Imaging in the Frequency Domain
## 3 Results  
### Simulations  
Figure 5 shows the three components and the module of the velocity profiles estimated along the z-axis by using the CMUT and Vermon probes. Six probe-to-flow orientations, distributed by columns, were chosen to test the method when (a) only one velocity component was nonzero (left column), (b) two velocity components were different from zero (columns 2-4), or (c) all three velocity components contributed to the velocity module (columns 5 and 6). In particular, the azimuth angle was set to \(45^{\circ}\) in the cases shown in the three rightmost columns, which implies that the lateral and elevation velocity components should be identical.  
The differences between the profiles produced by the two probes can be appreciated in Figure 5. The velocity components (\(v_{x}\), \(v_{y}\)) were better estimated with the CMUT probe, the profiles of which more closely approached the reference. Similarly, the more pronounced underestimation of the lateral velocity components in the Vermon probe yielded a corresponding underestimation of \(v_{Module}\) (bottom panels). It is also worth noting that the estimated lateral velocity components (\(v_{x}\) and \(v_{y}\), second and third rows) obtained for \(\vartheta_{\text{A}}=45^{\circ}\) gave similar profiles, confirming their expected symmetry.  
To visualize that the method behaved correctly even outside the axis of the probe, the 3-D representations of the flow distributions are shown in Figure 6 for the CMUT probe and for \(\vartheta_{\text{D}}=90^{\circ}\), \(\vartheta_{\text{A}}=0^{\circ}\). Here, the surface view of the x-z plane for y = 0 is reported on the left and the y-z plane for x = 0 on the right.  
Figure 5: Velocity profiles reconstructed along lines crossing the probe axis with different probe-to-flow orientations. The red dotted lines refer to the CMUT probe, the blue dashed ones to the Vermon probe. The black solid line is the reference velocity profile.  
Figure 6: Example of surface diagram for the CMUT probe simulation (\(\theta_{\rm D}=90^{\circ}\), \(\theta_{\rm A}=0^{\circ}\)).  
The relative bias, \(\overline{B}_{v}\), and standard deviation, \(\overline{\sigma}_{v}\), evaluated according to Equations (1)-(3) for all simulated conditions are reported in Table 2. For the CMUT probe, \(\overline{B}_{v}\) and \(\overline{\sigma}_{v}\) were always lower than 9.6% and 11.4%, respectively. On average, \(\overline{B}_{v_{Module}}\) and \(\overline{\sigma}_{v_{Module}}\) were 6.5% \(\pm\) 8.0%, respectively. The results obtained with the Vernon probe, in general characterized by larger errors (\(\overline{B}_{v_{Module}}\) and \(\overline{\sigma}_{v_{Module}}\) resulted, on average, 14.4% \(\pm\) 8.7%), were, however, less dependent on the beam-to-flow orientation, with a relative bias ranging (for the velocity module) between 12.6% and 16.3%.