esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Simulation and Results
### Performance Comparisons  
Visual and quantitative evaluations were conducted to assess the performance of the proposed algorithm. Simulations were carried out using MATLAB R2020b software running on an Intel Core i7-10700 system with 2.90-GHz CPU, 16-GB RAM, and a 64-bit operating system.  
For visual evaluation, certain regions from the resulting images were enlarged as shown in Figures 6-9. The resulting images processed using WF, 2 DACS-WF, and F-MGF were not completely free of noise and were heavily affected by the AWGN. The results from the SB-ITV exhibited damages at the intersections between bright and dark regions, indicating that edge characterization was difficult compared to other methods. Conversely, the results from the proposed algorithm clearly maintained the edge components while significantly reducing the level of noise compared to other methods.  
In Table 2, the PSNR and SSIM of the proposed algorithm were superior to the conventional methods. In the case of the distorted Barbara image at AWGN \(\sigma=30\), the proposed algorithm showed a PSNR value of 27.39 [dB]. The proposed algorithm's PSNR was better than WF, 2 DACSWF, SBITV, and FMGF by 3.18 [dB], 3.72 [dB], 2.92 [dB], and 3.32 [dB], respectively.  
Concerning the proposed algorithm, the PSRN and SSIM results show high or similar values in most areas when restoring a noisy image from \(\sigma=5\) when the intensity of the AWGN is relatively weak to \(\sigma=30\), which indicates prominent noise. In particular, the proposed algorithm shows a significant performance increase compared with conventional methods when restoring images with high-frequency components, such as the Barbara images. Table 1 shows that the proposed algorithm had a PSNR of 27.39 [dB], which was  
Figure 10: PSNR graph of simulation result. (**a**) PSNR graph of Lena image. (**b**) PSNR graph of Baboon image. (**c**) PSNR graph of Barbara image. (**d**) PSNR graph of Boat image.  
higher than the PSNR values obtained using WF, SBITV, and FMGF processing by 3.18 [dB], 3.72 [dB], 2.92 [dB], and 3.32 [dB], respectively, by restoring the Barbara image damaged using an AWGN of \(\sigma=30\). In summary, the visual and quantitative results show that the proposed algorithm effectively eliminates AWGN and inhibits excessive blurring of edge components.
# Influence of Five Additives on No Loading Swelling Potential of Red Clay
###### Abstract  
In this study, cement, zeolite powder and three industrial by-products (blast furnace slag, steel slag, and fly ash) were selected as additives to study their effects on the swelling potential of red clay with different curing ages and dosages. At the same time, the mechanism of additives reducing the swelling potential of red clay was analyzed by scanning electron microscope (SEM) and X-ray fluorescence (XRF) tests. The X-ray diffraction (XRD) test was used to detect the clay mineral content of the red clay specimens before and after the modification to determine the change in the clay mineral content of the specimens. The direct shear test was used to explore the influence of additives on the strength of red clay. The results show that with 9% cement content, the no loading swelling potential of specimens can be reduced by 82.5% under 28 days of curing, and the cohesion of the specimens can be greatly increased by 82%. However, the specimens with cement have an increase in no loading swelling potential under the condition of no curing. In contrast, when steel slag is used as an additive to modify the swelling properties of red clay, the swelling potential can be reduced without curing, but the addition of steel slag will reduce the cohesive strength of specimens. XRD testing shows that the clay mineral composition in cement-modified specimens and steel slag-modified specimens experienced a relative change, the relative content of montmorillonite and illite decreased, and the relative content of kaolinite increased. Combined with SEM and XRF test results, it is concluded that cement's reduction in the swelling potential of red clay depends on pozzolanic reaction products filling the pores in specimens and bonding clay particles, so as to reduce the permeability of red clay and increase the resistance during swelling. The addition of cement can also convert hydrophilic clay minerals into nonhydrophilic clay minerals. Compared with cement, the reduction in swelling potential caused by steel slag mainly depends on the adsorption of ions to reduce the adsorption of water molecules on the surface of clay slices.  
red clay; expansive soil; cement; steel slag; modification; swelling potential +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Impact of Acoustic Transmission Characteristics on Acoustic Signal Propagation  
In the simulation section, the Euclidean distance between the base station and the user is adopted. However, the acoustic ray bending in the acoustic signal propagation path should be considered. Additionally, the acoustic transmission characteristics, such as the multipath effect caused by the acoustic signal reflected from the seabed or the sea surface, the Doppler effect caused by the motion of the acoustic source, and the transmission loss of acoustic energy, also affect acoustic signal propagation in the underwater environment. Herein, we simulated the acoustic transmission characteristics by BELLHOP [38] and studied the impact on acoustic signal propagation. The frequency of the omni-direction acoustic sonar was set to 8 kHz, and the users were randomly distributed in an underwater space of 3000 m in depth. To illustrate the impact on acoustic signal propagation, the signal service range was limited to 30 km in the horizontal, which was different from the signal positioning range in Section 2.3. Note that it is complex to simulate the real underwater environment, such as the temporal-spatial-varying ocean sound speed, sea surface wind and waves, and the seafloor topography. In the simulation, the typical deep-sea Munk model was used as the reference sound velocity profile [39], and a calm sea surface and flat seafloor were considered, as shown in Figure 6.  
Figure 5: User positioning indicators of the “4+1+1” network configuration. The geometries of the seafloor base station arrays are triangular-center-form array and square-form array. **(a,b)** Heat maps of the percentage of EPGs with the number of available base stations \(\geq\)3; **(c)** average, standard deviation, and maximum of PDOF—the box denotes the average, the black vertical line denotes the standard deviation, and the asterisk line denotes the maximum value.
# Ground Control System Based Routing for Reliable and Efficient Multi-Drone Control System
## 4 Performance Evaluation
### Simulations
#### 4.3.2 Performance Evaluation for the Mobility Scenario  
We conducted a simulation to verify that GCS-routing provided reliable routing and stable throughput even with drone movement. Similar to the experiment in Section 4.2.2, Drone 4 sending 1 Mbps UDP traffic to GCS moved along the arrow shown in Figure 14(a). GCS-routing updated routing routes based on Drone 4's geographic information, as shown in Figure 16. Simulation outcomes were strongly consistent with the drone experiment in Figure 12. GCS-routing redistributed routing tables appropriately without unnecessary redistribution, highlighting high efficiency of GCS-routing.  
Figure 13: Simulated route update time and throughput for DSDV and GCS-routing.  
Figure 13: Deployment of drones in simulation.  
GCS-routing did not significantly degrade data communication, and provided stable network throughput. In contrast, DSDV-4s was unable to respond quickly to changing network topology, hence Drone 4 frequently lost network connection, and throughput fluctuated quite sharply. DSDV with 2 s HELLO interval provided more rapid response to network changes and stable throughput. However, throughput fluctuation was very large compared to the GCS-routing result. There were unnecessary redistributions of routing tables using OLSR, causing network disconnection and large fluctuation. Table 4 shows throughput of the compared protocols, and confirms that GCS-routing provides better network performance.  
We also conducted a further mobility scenario experiment. Similar to the previous case, Drone 4 sent 1 Mbps UDP traffic to GCS. However, there was an additional 0.3 Mbps UDP transmission between Drones 1 and 2 to evaluate routing performance in the presence of background traffic in the routing path, as shown in Table 5. GCS-routing throughput decreased compared to the previous experiment due to the background traffic. However, this decrease was relatively very small compared to that of DSDV and OLSR. The standard deviation of GCS-routing was also much less than that of DSDV or OLSR despite the background traffic. Thus, this additional experiment confirmed that GCS-routing provides more stable data communications than other routing protocols even when there was background traffic in the routing path.
# On the Need for a General REST-Security Framework
## 1 Introduction
The remote application protocol data unit (APDU) call secure (RACS) [11] protocol is one example. It is an emerging REST-ful protocol for accessing smartcards. Beside transport-oriented security no further protection means have been proposed for the RACS draft standard so far. From these basic observations, the need for a general REST-security framework becomes apparent. The objective of this paper is to close this gap while providing the following contributions. First, this paper analyzes the actual security demands of REST-based systems thoroughly and emphasizes the specific REST characteristics that necessitate a dedicated REST-security, which needs to be defined at the same abstraction layer as REST itself and independent from any concrete technology in the first place. Then, a comprehensive consolidated review of the current state of the art in respect to REST-security is provided. Finally, the paper contributes a general REST-security framework alongside with a methodology on how to instantiate it for a particular REST-conformance technology stack in order to facilitate the protection of REST-based service systems of any kind by consistent and comprehensive protection means. Available as well as upcoming REST-ful technologies will benefit from the introduced methodology and the proposed general REST-security framework at its core. For this purpose, the remaining of this paper is organized as follows. The foundations in respect to the architectural style REST are laid in Section 2. The methodology for deriving the envisioned general REST-security framework is laid in Section 3. The subsequent sections follow this methodology accordingly, starting with capturing the demand in terms of required service security technologies in Section 4. Due to the lack of a widespread adoption of REST other than the Web--but without the loss of generality--the security demands and specific requirements are analyzed based on the Web Services security stack. In Section 5 the related work and current practice is presented and assessed. A general security framework that reflects the particular characteristics and properties of REST is introduced in Section 6. Based on this approach, Section 7 proposes an adoption of the framework to two prevalent concrete REST-based protocols, HTTP and CoAP. An experimental evaluation of these schemes against the related work based on prototype test-beds is given in Section 8. The paper concludes in Section 9 and provides a brief discussion on future research and development demands.
# Task-Oriented Motion Planning of a Space Manipulator under Multiple Constraints
## 5 Task Intermediate-Point Planning Modeling
### Specific Algorithm  
A* algorithm valuation function  
\[f(p)=g(p)+h(p) \tag{11}\]  
The cost is weighted summation after normalization of each resource concentration.  
Improved \(g(p)\)'s computing strategy:  
\[g(p)=\min\Bigl{\{}C\bigl{(}p_{g},p\bigr{)}+g\bigl{(}p_{g}\bigr{)},C\Bigl{(}p_{ f},p\Bigr{)}+g\Bigl{(}p_{f}\Bigr{)}\Bigr{\}} \tag{12}\]  
where \(C(p_{1},p_{2})\) is the actual cost from point \(p_{1}\) to point \(p_{2}\), \(p_{g}\) is the nominal parent node of the parent node of the current node, and \(p_{f}\) is the parent node of the current node.  
\(p_{nf}\) is defined as the nominal parent node, and the node with the lowest cost to \(p\) in \(p_{g}\) and \(p_{f}\) is taken as \(p_{nf};h(p)\) typical path planning (such as straight-line planning) from the current point to the target point without considering constraints was adopted.  
The algorithm flow is as follows in Figure 5.  
Step 1, Search in the 6-dimensional workspace of the manipulator, position search \(\Delta l\) and attitude search \(\Delta\theta\).  
Step 2, Create two empty lists: OPEN list and CLOSE list.  
Step 3, Starting from the point \"start\", add it to the open list and calculate the \(f(p)\) of the point \"start\". The nominal parent node of the starting point is itself.  
Step 4, If the close list contains the target point \"end\", go to step 9.  
Step 5, Select the \(f(p)\) smallest node in the open list and place it into the close list.  
Step 6, Find all nodes around the current node that are not in the close list and do not violate constraints \(P\).  
Step 7, Calculate the \(f(p)\) of all nodes in \(P\), record the nominal parent node \(p_{nf}\) and add it to the open list.  
Step 8, go to Step 4.  
Step 9, Starting from the target point \"end\", trace the whole path through the nominal parent node to obtain the task intermediate point.
## 2 Related Works
Each sensor determines itself to be an IBN or an OBN for constructing the Outer Boundary Area (OBA) and Inner Boundary Area (IBA) by checking its one-hop neighbors' status. The OBA and the IBA are composed of numerous boundary faces, and these faces cover the dangerous area. The area estimation is obtained simply by calculating these irregular boundary faces. This study concluded that creating the boundary faces with the YG graph can yield the highest precision. [PERSON] et al. also proposed a method that uses the planarization algorithms to locate and trace the boundary area of the continuous object with Duty-Cycled WSNs [14]. They used the Kriging algorithm to refine the boundary face area [18]. [PERSON] et al., proposed a similar novel mechanism for continuous object boundary region detection [15]. To detect a practice boundary, a set of mobile sensors traverses the predicted boundary. It uses a heuristic algorithm like ant colony optimization (ACO) to find the optimal routings for mobile sensors. Experimental results show that the proposed mechanism could get a precise boundary area. [PERSON] et al. used a gas concentration gradient to estimate and track the boundary [19]. A single moving platform with sensors constantly measures the gas concentration [20]. The proposed algorithm controls the motion of a single unmanned underwater vehicle (UUV). As in [19], the initial detection of the cloud boundary and the tracking procedures in this study are obtained according to the calculated toxic substance concentration gradient. Our previous study proposed an incremental deployment method for detecting the intangible event region, named Incremental Deployment with Gravitational Force (IDGF) [21]. IDGF applied the virtual force model to calculate subsequent sensor positions to track the boundary. Agents are continuously deployed within the region of the intangible events before the coverage area becomes stable. It can reduce the deployed sensors to cover the intangible event's region. [PERSON] 'n et al., proposed a similar method with five procedures for calculating the optimal values of these parameters [22]. The proposed method also used the virtual force to deploy the sensors. These methods use stationary sensors to figure out the continuous object. Their precision is limited once the sensors are placed in the deployed area. By involving the mobile sensors, the figured out boundary area of the continuous object can be adjusted further. Thus, this paper adopts mobile sensors to improve precision. The deployed sensors start by building a rough boundary area. Then, the proposed strategy for moving sensors is applied to improve the precision.
## 2 Results and Discussion
### Method Validation
#### 2.1.3 Linearity, Limit of Detection (LOD) and Limit of Quantification (LOQ)
The determined LOQs (0.7 \(\upmu\)g/mL for Amox and 1 \(\upmu\)g/mL for Dox (equivalent to 14 \(\upmu\)g/g for Amox and 20 \(\upmu\)g/g for Dox in tablets)) were verified using six spiked solutions at LOQ level for both targeted matrices (capsules and wastewater) (Table 2). In both cases, the RSD values were lower than 10%, and the recovery values were included in the range of 95-105%. The LOQs were accepted as valid [51; 52; 53]. Moreover, the validated method supplied recoveries in the range of 97.3 to 102% (Table 2), which supported the suitability of the HPLC technique for the envisioned application, namely the simultaneous determination of Amox and Dox in the targeted matrices. The LOQs of the optimized method were low enough to perform the quantitative determination of Amox and Dox in a variety of matrices. Our study's LOD and LOQ values are much lower than those of 0.436 and 1.32 \(\upmu\)g/mL [20], 2.14 and 7.15 \(\upmu\)g/mL [54], 1.579 and \(\upmu\)g/mL, 0.1 and 0.3 mg/mL [41], and 4.785 \(\upmu\)g/mL [17] reported for the quantitative determination of Amox, and 1.08 and 3.27 \(\upmu\)g/mL [55], and 16 and 54 \(\upmu\)g/L [6] stated for Dox in pharmaceutical formulations and wastewater samples using the HPLC method.
# A Study on Design Requirement Development and Satisfaction for Future Virtual World Systems
## 2 Trend Analysis
### Interconnectivity  
Virtual worlds can connect different people and devices to support various interactions and communication. Multiple access devices lead to various user data input to virtual worlds. One emerging category is wearable devices. Figure 4a,b (data source: [29; 30]) shows that the market value on wearable devices is growing in all categories, from both revenue and consumption perspective. Wearable devices can collect user data by tracing various user interaction patterns. For instance, Cyberith Virtualizer (cyberith.com) can track user posture in walking, running, standing, crouching, and sitting. Data are also collected from IoT devices, creating a mirrored world to telepresent real-world data in a virtual environment. For example, Eye Create Worlds [31] visualizes the data in a virtual world from sensors placed over a city to monitor and optimize the performance of a rail transportation network. Besides connecting to devices, people in virtual worlds are increasingly interconnected. Figure 4c (data source: [32]) shows that the revenue of social gaming has almost quadrupled from 2010 to 2014, and Figure 4d (data source: [33]) shows that the market value of social worlds in 2020 is expected to be twice the value in 2011. Moreover, a game industry survey in 2018 shows 54% of gamers feel video games help them connect with friends and spend time with family [34]. In summary, the above observation shows the interconnectivity trend from both hardware peripherals and social connections, leading to the growth of in-world user data collection.  
Figure 3: Trends of the virtual world market: (a) ranking of purposes of use for virtual reality in 2015; (b) investment directions of virtual/augmented reality technology worldwide in 2016 and 2018.
# Tensor Rank Regularization with Bias Compensation for Millimeter Wave Channel Estimation
###### Abstract  
This paper presents a novel method of tensor rank regularization with bias compensation for channel estimation in a hybrid millimeter wave MIMO-OFDM system. Channel estimation is challenging due to the unknown number of multipath components that determines the channel rank. In general, finding the intrinsic rank of a tensor is a non-deterministic polynomial-time (NP) hard problem. However, by leveraging the sparse characteristics of millimeter wave channels, we propose a modified CANDECOMP/PARAFAC (CF) decomposition-based method that jointly estimates the tensor rank and channel component matrices. Our approach differs from most existing works that assume the number of channel paths is known and the proposed method is able to estimate channel parameters accurately without the prior knowledge of number of multipaths. The objective of this work is to estimate the tensor rank by a novel sparsity-promoting prior that is incorporated into a standard alternating least squares (ALS) function. We introduce a weighting parameter to control the impact of the previous estimate and the tensor rank estimation bias compensation in the regularized ALS. The channel information is then extracted from the estimated component matrices. Simulation results show that the proposed scheme outperforms the baseline \(l1\) strategy in terms of accuracy and robustness. It also shows that this method significantly improves rank estimation success at the expense of slightly more iterations.  
tensor rank; sparsity; CP tensor decomposition; channel estimation; millimeter wave; hybrid-MIMO 2022 3 664-681. [[https://doi.org/10.3390/signals3040040](https://doi.org/10.3390/signals3040040)]([https://doi.org/10.3390/signals3040040](https://doi.org/10.3390/signals3040040))
## 3 Results and Discussion
### Dispersibility  
Figure 3a-f shows the dispersibility of p-MWCNT-Pd (5 mg), np-MWCNT-Pd (5 mg), and Pd/C (5 mg) in \(N\),_N_-dimethylformamide (5 mL), and toluene (5 mL). It is evident that p-MWCNT-Pd, np-MWCNT-Pd, and Pd/C were significantly more dispersible in DMF than in toluene. The particle size of the dispersed CNT-NM is presented in Table 1. It shows that there is not much difference between p-MWCNT-Pd and np-MWCNT-Pd in toluene, but there was significant difference in DMF. The particle size of CNT-NM agglomerates in toluene were higher than those in DMF. As can be seen in Figure 3, there was significant precipitation of the MWCNT-Pd in toluene, so the particle size represents what remained dispersed. The colloidal dispersion in DMF and TBA remained homogeneously suspended for several weeks without need for mechanical stirring.  
The metal nanoparticles loading in the hybrid materials were quantified using TGA as shown in Figure 4. The resulting weight above 600 \({}^{\circ}\)C was attributed to the weight of residual metal. The nanohybrids were found to contain 43.02 and 38.93 percent by weight of Pd in p-MWCNT-Pd and np-MWCNT-Pd, respectively, while Pd/C contained 5% by weight of Pd.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Samples/Solvents** & **p-MWCNT-Pd** & **np-MWCNT-Pd** \\ \hline Toluene & 240.3 nm & 234.2 nm \\ Dimethylformamide (DMF) & 168.2 nm & 126.4 nm \\ \hline \hline \end{tabular}
\end{table}
Table 1: Particle size of dispersible CNT-NM.  
Figure 4: TGA of **(a)** MWCNT, **(b)** MWCNT-COOH, **(c)** MWCNT-ODA, **(d)** p-MWCNT-Pd, and **(e)** np-MWCNT-Pd.  
Figure 3: Photographs of different dispersions: **(a)** np-MWCNT-Pd dispersed in DMF, **(b)** p-MWCNT-Pd dispersed in DMF, **(c)** np-MWCNT-Pd in Toluene, **(d)** p-MWCNT-Pd in Toluene; **(e)** Pd/C dispersed in DMF, **(f)** Pd/C dispersed in Toluene.
## 4 Experiments
### Packet Delivery Ratio  
Because Packet Delivery Ratio (PDR) directly reflects network performance of medical monitoring applications, PDR is chosen to evaluate routing reliability among the three protocols in Figure 9. While CBR data sources increase, AODV's PDR quickly drops in both topologies due to worse route maintenance capability, and thus AODV's reliability is the worst among the three protocols. In random topology, LBMR's PDR is better than AOMDV's PDR, and their PDR is quite similar in grid topology. Since network data delivery is more challenging in random topology than grid topology, LBMR is more reliable than AOMDV in the more challenging scenario. Therefore, the load balancing design of LBMR brings more reliable routing service than well-known protocols, AODV and AOMDV, for medical monitoring applications.