esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Test Results for Density Matching Approach
Previous research [8; 9] shows the significant temperature dependency of the performance of the Coriolis mass flowmeters in the wide temperature range of \(-\)40 \({}^{\circ}\)C to 20 \({}^{\circ}\)C. In Korea, the Coriolis mass flowmeters in hydrogen refueling stations are installed near the upstream of the pre-cooler, which means that the operating conditions of the flowmeter are not as cold as the conditions after the pre-cooler. Nevertheless, the temperature dependency of the Coriolis mass flowmeters should be addressed in the density-matching approach. If  
Figure 6: Measurement results of the Coriolis mass flowmeter with different pressure and flowrate conditions. temperature dependency of the operating condition of the Coriolis mass flowmeters is verified later, the density-matching approach can represent a potential method by which to perform calibration tests of Coriolis mass flowmeters at hydrogen refueling stations that do not have calibration facilities for hydrogen gas at 700 bar and \(-40\)\({}^{\circ}\)C.
# Assessing the Security and Privacy of Baby Monitor Apps
## 3 Materials and Methods
### Reviewing the Confidentiality of Monitoring Video Streams
#### 3.2.1 Threat Model  
Based on user feedback on the Google Play Store, baby monitor apps are used in potentially insecure networks, such as wireless networks in hotels during vacations. As such, we assume a threat model where a potential attacker can eavesdrop and intercept network traffic between the two cell phones in use, which is similar to the attack scenarios described in related work [11, 23]. These attacks are also known as MitM (machine-in-the-middle) [26] attacks. In the case of baby monitoring apps, MitM-attacks become easily possible if the phone monitoring the child uses a Wi-Fi network and the parental device communicates over the Internet via cellular or other Wi-Fi networks. In such a scenario, the confidentiality of protected data is usually ensured by encryption as a network security measure.
# Parallel Complex Quadrature Spatial Modulation
###### Abstract  
In this paper, we propose a new multiple-input multiple-output (MIMO) transmission scheme, called parallel complex quadrature spatial modulation (PCQSM). The proposed technique is based on the complex quadrature spatial modulation (CQSM) to further increase the spectral efficiency of the communication system. CQSM transmits two different complex symbols at each channel use. In contrast with CQSM, the new transmission scheme splits the transmit antennas into groups, and modulates the two signal symbols using the conventional CQSM before transmission. Based on the selected modulation order and the number of possible groups that can be realized, the incoming bits modulate the two signal symbols and the indices of the transmit antennas in each group. We demonstrated that while the complexity and performance of the proposed scheme is the same as that of CQSM, the number of required transmit antennas is significantly reduced. The proposed PCQSM achieves such a benefit without requiring any additional radio frequency (RF) chains. The results obtained from Monte Carlo simulation showed that at a Bit Error Rate (BER) of \(10^{-4}\), the performance of the PCQSM with two antenna groups closely matches that of CQSM, and outperformed quadrature spatial modulation (QSM) and parallel quadrature spatial modulation (PQSM) by over 0.7 dB. As the number of antenna groups increased to 4, the BER performance of PCQSM with reduced number of transmit antenna and modulation order matches that of QSM. The BER of the proposed scheme using maximum likelihood (ML) receiver is also analyzed theoretically and compared with the BER obtained via simulations.  
spatial modulation; complex quadrature spatial modulation; quadrature spatial modulation; parallel quadrature spatial modulation; multiple-input multiple-output
# Two Interval Upper-Bound \(Q\)-Function Approximations with Applications
## 2 Related Work and Motivation
Although it has been highlighted in [11; 16; 17; 27] that the bounds for the \(Q\)-function could have complex mathematical forms, nevertheless, an upper-bound approximation on the \(Q\)-function that was very accurate for small argument values and less accurate for higher argument values was proposed in ([13] Equation (12)) as:  
\[Q^{[13]}(x)=\frac{1}{50}\exp\Bigl{\{}-x^{2}\Bigr{\}}+\frac{1}{2(x+1)}\exp \biggl{\{}-\frac{x^{2}}{2}\biggr{\}}. \tag{6}\]  
Another useful and practical \(Q\)-function approximation that we took into consideration in this paper was given in ([14], Equation (9)):  
\[Q^{[14]}(x)=\frac{1}{\sqrt{2\pi}}\frac{1}{\sqrt{x^{2}+1}}\exp\biggl{\{}-\frac {x^{2}}{2}\biggr{\}}. \tag{7}\]  
As already mentioned, we chose two upper-bound approximations of the \(Q\)-function from [7]:  
\[Q_{1}^{[7]}(x)=\frac{1}{\sqrt{2\pi}}\frac{\pi}{2x+\sqrt{(\pi-2)^{2}x^{2}+2\pi }}\exp\biggl{\{}-\frac{x^{2}}{2}\biggr{\}}, \tag{8}\]  
and  
\[Q_{2}^{[7]}(x)=\frac{1}{\sqrt{2\pi}}\frac{4}{3x+\sqrt{x^{2}+8}}\exp\biggl{\{} -\frac{x^{2}}{2}\biggr{\}}, \tag{9}\]  
and analytically determined the disjoint intervals of the value of the argument \(x\) in which it was convenient to apply these approximations so that the accuracy due to the approximation of the \(Q\)-function by the considered upper-bound approximations was the highest possible.
# Quality Assessment by Region and Land Cover of Sharpening Approaches Applied to GF-2 Imagery
## 2 Materials and Methods
### Study Area and Data
\begin{table}
\begin{tabular}{c c c} \hline
**Region** & **Land Cover** & **Area Percentage (\%)** \\ \hline Region 1 & Impervious surface & 65.2 \\  & vegetation & 28.6 \\ Region 2 & Impervious surface & 28.3 \\  & forest & 71.7 \\ Region 3 & Shrub and grassland & 47.8 \\  & Bare soil & 52.2 \\ Region 4 & Unsown farmland & 57.1 \\  & Winter wheat & 30.5 \\ Region 5 & Salt water & 57.1 \\  & Salt-affected soil & 35.6 \\ Region 6 & Shrub and grassland & 7.1 \\  & Bare soil & 92.9 \\ Region 7 & Unsown farmland & 80.7 \\  & Canal water & 17.6 \\ Region 8 & Unsown farmland & 23.5 \\  & Winter wheat & 71.3 \\  & Canal water & 5.2 \\ Region 9 & Salt water & 85.3 \\  & Salt-affected soil & 24.7 \\ Region 10 & Salt water & 62.9 \\  & Salt-affected soil & 12.3 \\ Region 11 & Aquaculture water & 79.3 \\  & Ridge & 18.5 \\ Region 12 & Reservoir water & 100.0 \\ Region 13 & Canal water & 100.0 \\ Region 14 & Sea water & 100.0 \\ \hline \end{tabular}
\end{table} 
Table 2: The land-cover percentages for each region. Figure 1: (**a**) Multispectral image 6112 \(\times\) 5453 pixels false color near infra-red, red and green composition); (**b**) panchromatic image (24,448 \(\times\) 21,812 pixels), and the red square areas are the employed regions. Figure 2: Image Region 1-Urban area. (**a**) Multispectral image \(100\times 100\) pixels false color NIR, red and green composition); (**b**) panchromatic image (\(400\times 400\) pixels); (**c**) [PERSON] pansharpened image (\(400\times 400\) pixels); (**d**) color normalized algorithm pansharpened image (\(400\times 400\) pixels); (**e**) principal component analysis pansharpened image (\(400\times 400\) pixels); (**f**) modified intensity-hue-saturation pansharpened image (\(400\times 400\) pixels). The upper left corner of the image is placed at 662868 E and 4199959 N (UTM geographic coordinates, zone 50, WGS-84).
# The Value of Fractal Analysis in Ultrasound Imaging: Exploring Intricate Patterns
## 3 Results
### Breast Cancer Detection  
The integration of fractal analysis into computer-aided diagnosis (CAD) systems has significantly enhanced the detection and classification of breast lesions in ultrasound images [14; 15; 16; 17]. CAD systems employ techniques such as fractal Brownian motion and k-means clustering, which, when combined with preprocessing methods like histogram equalization, improve the accuracy of distinguishing between benign and malignant tumors. The use of these techniques allows for detailed texture analysis, thus increasing the precision of cancer detection. Studies have demonstrated that CAD systems incorporating fractal analysis achieve high accuracy rates, validating the efficacy of these methods in breast cancer diagnostics. Specifically, deep learning approaches, such as transferable texture convolutional neural networks (TTCNNs), have been shown to outperform traditional methods, achieving accuracies as high as 97.49% in classifying mammograms [18]. Recent advancements in high-definition microvasculature imaging (HDMI) have introduced novel quantitative biomarkers that significantly enhance breast cancer detection. These biomarkers include microvessel fractal dimension (mvFD), Murray's deviation, bifurcation angle and spatial vascularity pattern. The detailed analyses of tumor microvessel structures provided by these biomarkers have increased the sensitivity and specificity of diagnostic models [14; 15; 16; 17]. Studies [14; 15; 16; 17] have indicated that the inclusion of mvFD and other biomarkers in diagnostic frameworks improves the accuracy of differentiation between benign and malignant breast lesions. This precise characterization of tumor vasculature is crucial for early detection and effective treatment planning [14; 15; 16; 17]. mvFD is particularly useful in identifying the structural complexity of tumor vasculature. Malignant tumors often exhibit higher mvFD due to the irregular and chaotic nature of cancerous blood vessel growth compared to the more orderly vessel structures found in benign tumors. This differentiation is vital for accurate diagnosis and treatment planning. The higher mvFD in malignant tumors reflects their aggressive nature and helps predict tumor behavior and potential metastasis. By incorporating mvFD into imaging analyses, clinicians can achieve more accurate and detailed assessments of tumor pathology, thus enhancing the overall effectiveness of breast cancer management [14; 15; 16; 17].  
The integration of fractal analysis and advanced imaging techniques such as HDMI in CAD systems has revolutionized breast cancer diagnostics. These methods enhance the accuracy of detecting and classifying breast lesions and provide detailed insights into tumor structure and behavior. The high precision and reliability of these techniques underscore their importance in clinical practice, improving early detection, treatment planning and ultimately patient outcomes (Figure 2).
# Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks
## 5 Conclusions and Future Work  
In this paper, we have proposed a transmission strategy that is able to alleviate hole in order to maximize the network lifetime. The deployment of heterogeneous nodes in each region proved to be successful in term of balanced data transmissions over an intermediate node. In addition, the division of the network field contributed enough in balancing the energy among the network nodes. Due to the election of the optimal forwarder at each hop, even energy dissipation is achieved. The existing technique ODTS is based on ACO which computes two functions for finding the optimal energy efficient route and minimal distance between source and destination. However, the estimation of data load at each hop in proposed algorithm proved to be very effective in selecting route to the destination. Through linear optimization, we have computed a feasible region which shows that energy consumption within that region always helps the network nodes to operate for the maximal time. Moreover, after the death of an intermediate node, transmission range is adjusted in order to transmit data packets directly to the destination. This also increased the network lifetime and allows the node to utilize its energy resources completely. The effectiveness and validity of the proposed work are shown through simulations. The results are portrayed in which it is evident that proposed work outperformed selected existing counterpart scheme in terms of network lifetime and energy consumption.  
In future, we will extend our work in different ways. Firstly we will do random deployment of heterogeneous nodes in the network, i.e., they can be placed anywhere in a sector. Secondly, we will find out an optimal number of nodes that are capable of delivering data to intermediate nodes.  
This work was supported by the Deanship of Scientific Research, King Saud University, under Grant RG-1435-0037. All authors together proposed, discussed and finalized the main idea of this work. [PERSON], [PERSON], and [PERSON] proposed implemented the protocols. [PERSON], [PERSON] and [PERSON] calculated and plotted the feasible regions. The authors declare no conflict of interest.
# Minimizing Interference-to-Signal Ratios in Multi-Cell Telecommunication Networks
## 3 Dot-Product Clustering Algorithm for Total Interference Minimization Problem
### Engineering Complexity (Revisited)  
In this subsection, we discuss, in short, some practical considerations in real-life applications. One of the most important ones is that the clusters cannot be arbitrarily complex (from an engineering point of view) because of the computational overhead of the synchronization of too many base stations. Therefore, it may be necessary to consider an upper bound \(T\) on the possible numbers of the BSs in any cluster.  
The number of clusters is part of the input of the clustering method. One can ask whether there is a way to optimize \(M\). A heuristic attempt is given in [3], using a binary search wrapper over the spectral clustering method to determine an optimal \(M\). The idea is based on a theorem of [PERSON] that the optimal solution is monotone increasing in \(M\); however, no such guarantee is given for the approximate solution found by the heuristic algorithms constructing the \(M\)-part clusters. For this reason, we do not consider this alternate optimization problem.
# Design Approach and Mechanism Analysis for Cavitation-Tolerant Torque Converter Blades
## 2 Cavitation Simulation and Verification of HTC
### CFD Model and Validation
The simulation results show that cavitation degrades the performance of both \(K\) and \(T_{\text{bg}}\) under low-speed-ratio operating conditions (\(SR\leq 0.3\)). At high \(SR\)s (\(SR>0.3\)), the noncavitation CFD result is consistent with the cavitation CFD findings. The reason is that cavitation only occurs at low \(SR\)s. Both the incidence angle and mass flow rate of the stator are large under low \(SR\)s, which is conducive to the generation of cavitation.
## 2 Case Study, EPBM of Isfahan Metro  
The first line of the Isfahan metro starts in the northwest and finishes south of Isfahan. As seen in Figure 1, about 5 km of this line have been excavated by EPBM. The tunnels were two directional, with an excavation diameter of 6.9 m and a finished diameter of 6 m. The geology along the route comprises river sediments mainly consisting of sand, gravel, and clay, with some cemented lenses in the southern parts of the route. The general specifications of the utilized EPBM are shown in Table 1.  
From the point of view of maintenance, EPBMs can generally be divided into three subsystems: electrical, mechanical, and cutterhead. The electrical subsystem includes the electronic circuits, electrical power, PLC, and communication; the mechanical subsystem consists of hydraulics, mechanical, pneumatic, and water; and the cutterhead subsystem includes the cutting tools and foam lines. These three subsystems, which include other internal subsystems, are considered for a RAM analysis of EPBMs.
# Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications
## 2 Antenna Design Methodology
### Bending Analysis of the Proposed Antenna
#### 2.5.1 Bending along \(X\)-Axis  
When it comes to studying \(S_{1I}\) behavior when the antenna is in bent condition, the antenna's bending radius along the \(x\)-axis (Bx = 30 mm to 90 mm) is chosen. As shown in Figure 5, when the antenna is bent along the \(x\)-axis, the simulated \(S_{1I}\) results are compared over different radii. It is realized that the antenna has stable \(S_{1I}\), even if it bent at the radius of 30 mm, 60 mm, and 90 mm.  
\begin{table}
\begin{tabular}{|c|c|c|c|} \hline
**Parameters** & **Values (mm)** & **Parameters** & **Values (mm)** \\ \hline \(Ls\) & _4.0_ & _Ws_ & _3.0_ \\ \hline \(Lg\) & _1.45_ & _wg_ & _1.34_ \\ \hline \(Lf\) & _1.5_ & _wf_ & _0.26_ \\ \hline \(L1\) & _0.56_ & _w1_ & _1.4_ \\ \hline \(L
# Reutilization of Recycled CDW Sand in Mortars, Paving Blocks, and Structural Concrete
## 3 Results and Discussion
### Properties of Aggregates
#### 3.1.1 Morphology and Chemical and Mineralogical Composition of Aggregates
The diffractogram of the CDW aggregate, shown in Figure 8, reveals the presence of quartz (Q, SiO\({}_{2}\), PDFcard 46-1045), limestone (L, CaCO\({}_{3}\), PDFcard 83-578), and magnesium carbonate dolomite (D, CaMg(CO\({}_{3}\))\({}_{2}\), PDFcard 75-1760). This suggests that the CDW aggregate is composed of natural limestone and ceramic products. Traces of sodium feldspar albite (A, NaAlSi\({}_{3}\)O\({}_{8}\), PDFcard 9-466), a phase commonly found in ceramic products, were also identified. However, mulitte, a crystalline compound typically found in ceramics sintered at high temperatures, was not detected. This indicates that there was a small amount of ceramic products in the CDW recycled aggregate. Consistent with the thermogravimetric analyses, no peaks attributed to portlandite, a typical compound of hydrated cement, were identified, confirming that the RA used did not contain significant amounts of concrete. Additionally, neither aggregate type showed deviation from the baseline within the 15-30 degrees 20 range, which confirms a minimal presence of amorphous phases that could react with portlandite during PC hydration. As a result, the CDW aggregate was expected to have limited pozzolanic activity. Although it may be suitable as an RA, its low reactivity when used as a partial PC replacement would likely reduce binder strength. Consistently with the XRF and TG results, no crystalline phases associated with sulfur compounds were detected. The morphology and chemical and mineralogical composition of both the natural and CDW aggregates analyzed were similar. Therefore, the CDW sand characterized in this study has the potential to be effectively reused in the production of sustainable construction materials. This reuse would help reduce environmental impact and enhance resource efficiency.
# Blind Deconvolution with Scale Ambiguity
###### Abstract  
Recent years have witnessed significant advances in single image deblurring due to the increasing popularity of electronic imaging equipment. Most existing blind image deblurring algorithms focus on designing distinctive image priors for blur kernel estimation, which usually play regularization roles in deconvolution formulation. However, little research effort has been devoted to the relative scale ambiguity between the latent image and the blur kernel. The well-known \(L^{1}\) normalization constraint, i.e., fixing the sum of all the kernel weights to be one, is commonly selected to remove this ambiguity. In contrast to this arbitrary choice, we in this paper introduce the \(L^{p}\)-norm normalization constraint on the blur kernel associated with a hyper-Laplacian prior. We show that the employed hyper-Laplacian regularizer can be transformed into a joint regularized prior based on a scale factor. We quantitatively show that the proper choice of \(p\) makes the joint prior sufficient to favor the sharp solutions over the trivial solutions (the blurred input and the delta kernel). This facilitates the kernel estimation within the conventional maximum a posterior (MAP) framework. We carry out numerical experiments on several synthesized datasets and find that the proposed method with \(p=2\) generates the highest average kernel similarity, the highest average PSNR and the lowest average error ratio. Based on these numerical results, we set \(p=2\) in our experiments. The evaluation on some real blurred images demonstrate that the results by the proposed methods are visually better than the state-of-the-art deblurring methods.  
image deblurring; kernel estimation; maximum a posterior (MAP); iterative reweighed least squares (IRLS); hyper-Laplacian; scale ambiguity; joint prior +
Footnote †: journal: Applied Sciences  
_Article_  
Blind Deconvolution with Scale Ambiguity
# Extensible Hook System for Rendezvous and Docking of a CubeSat Swarm +
## 3 Guidance, Navigation, and Control  
To perform CubeSat RVD using the EHS, the GNC subsystem needs to be defined for this purpose. The main requirement of it is to ensure that the CubeSats can locate each other with low to high accuracy depending on their distance. Conversely, the guidance component must develop a motion plan for the CubeSat swarm to integrate their trajectories so they can establish connectivity via the EHS. Subsequently, all CubeSat actuators need to be controlled to follow the defined motion plan by the guidance component.  
Figure 4 illustrates the proposed GNC subsystem. Firstly, the navigation component has been split into three stages, each of which requires lower or higher accuracy. When the CubeSats are far (\(>\)5 m), low accuracy is required (\(<\)1 m). This precision can be reached using Global Navigation Satellite Services (GNSS), which, in the case of relative localization in LEO, can reach 0.5 m and below [13]. Once the CubeSats are approaching, the navigation component will require a higher accuracy (\(<\)5 cm). For this purpose, our proposal would be to include a vision-based navigation system, which would be made up of LED patterns and cameras. Using this information, the localization of the CubeSat swarm could be completed with an accuracy on the order of 1 cm [14]. Finally, when the CubeSats are about to dock using the EHS, high-resolution localization is needed. In this case, localization is replaced by electromagnetic fields on the EHS end effector that will generate the corresponding forces to attract both end effectors by hooking them.  
Regarding the guidance component, it requires the performance of motion planning for the CubeSat swarm, including the EHS. Our proposal would be to use a motion planner that allows the swarm to plan the CubeSat motion, taking into consideration nonlinearities and constraints. Multi-staged warm-started motion planners arise as a solution to be evaluated. The main advantage of this method is that it allows one to compute an optimal plan faster with an increased success calculation [15], i.e., these planners sometimes are not able to find a solution.  
Finally, control requires commanding the CubeSat to follow the predefined motion plan by the guidance component, as well as controlling all of the actuators, including those that belong to the EHS. According to Equation (1), the extensible joint (joint 3 in Figure 2a) is non-linear; therefore, a classical PID controller cannot be used for that purpose. Our proposal would be to evaluate the use of model predictive control (MPC) and gain scheduling. The first one has the advantage of allowing control of the actuator, taking into consideration a realistic model and predicting its behavior; however, it requires more computation. Alternatively, gain scheduling does not require a lot of computation, but the control is simpler.  
Figure 4: Proposed guidance, navigation, and control architecture.