esa-sceva/satcom-chunk-collection huggingface dataset:
# A 32-GHz Eight-Way Power Amplifier MMIC in 150 nm GaN HEMT Technology
## 2 32 GHz High-Power Amplifier Design
### Impedance Matching Network Design  
In designing the HPA, an ADS momentum simulator was used to optimize the transmission lines for accurate impedance matching higher frequencies. The design procedure involves careful EM simulation with backside via formed through a thick SiC substrate to avoid frequency shift and impedance mismatch. In this work, an additional backside via inductance of 32 pH was included in series with the via model from the process design kit (PDK). Since GaN HEMT has relatively large transconductance, it is crucial to guarantee the amplifier stability at the low-frequency region. Thus, the matching network was carefully designed to suppress undesired low-frequency signals below the target frequency. The out-of-band gain should be less than 0 dB to eliminate the possibility of instability at low frequencies. Due to the difficulty of accurately implementing the required inductance with lumped inductors from the PDK and layout restrictions, all the matching networks comprised the transmission lines with lumped capacitors by trading off the area occupancy and matching performance. Compared with a spiral lumped inductor, a transmission line is more promising at the Ka-band considering the SRF and the layout inconvenience of the spiral inductors. Moreover, a more accurate impedance-matching circuitry can be implemented with transmission lines throughout the momentum simulation in the ADS. Different from the series inductance, a lumped capacitor was used for the shunt capacitance in the matching networks since it has a relatively higher SRF than a lumped inductor, with more compact area occupancy compared with its distributed counterpart. The output matching network determines the power delivered to the load and the power-added efficiency (PAE). Load-pull simulations were used to determine the optimum output-matching impedance. A load-pull simulation of the 8 \(\times\) 50 \(\upmu\)m OSV HEMT is presented in Figure 5. The load-pull simulation was performed with the parallel RC network at the gate with a power contour step size of 0.8 dB and a PAE contour step size of 5%. The maximum  
Figure 4: Implemented stabilization circuits for the parallel HEMT networks.  
power delivery was 27.2 dBm at optimum impedance \(Z_{pout\_opt}\) = 9.2 + j35.8 \(\Omega\), and the maximum PAE was 38% at optimum impedance \(Z_{\text{P}AE\_opt}\) = 4.8 + j37.5 \(\Omega\). The input impedance of the output matching network from 28 GHz to 32 GHz is also shown in Figure 5. To achieve a high-outpower level, the output matching network has an input impedance of \(Z_{in}\) = 12.7 + j36 \(\Omega\), which is close to \(Z_{pout\_opt}\) at 32 GHz. The output matching network combines the output power amplified by each HEMT device. There are losses due to the structures combining the output power, which will inevitably occur, and consideration is required. The loss of the designed combiner (output matching network) at 32 GHz is 1.47 dB, which is an acceptable value for the eight-way combiner.
## 1 Introduction
[35] introduced a fixed relaxation factor to transform equality constraints into inequality constraints and increased the feasible region in the CO solution process. [PERSON] et al. [36] obtained faster and better outcomes by changing the static relaxation factor to the dynamic relaxation factor. The methods described by the authors of [37; 38; 39; 40; 41; 42] will also be developed to choose the relaxation factor value according to the inconsistent information dynamic states between different subjects. [PERSON] et al. [43] proposed a relaxation factor based on the different information between discipline levels and system levels. The methods above do not consider the motion trend of the function in the iterative process and are not able to adjust the number of relaxation factors in time. Additionally, these methods did not solve the problem of CO having too many iterations. Many improvements have been applied to CO other than the relaxation factor, and the application of intelligence algorithms is one of these. [PERSON] et al. [44] proposed an adaptive intelligent CO method based on inconsistent information. [PERSON] [45] established a method based on collaborative optimization and an artificial bee colony algorithm and designed a distributed optimization framework for solving the difficult problem of consistency. These methods can be more effective in finding the global optimal solution in some ways, but they increase the number of iterations and computational complexity. This means that much time may be consumed by computation. Additionally, these methods may be sensitive to initial points, which means that lots of work needs to be done for the purpose of choosing the initial points. In order to overcome the mentioned problems in the above improvement methods, this paper proposed an improved CO based on the Manhattan Distance and Chameleon Swarm Algorithm (CSA) by constructing a new relaxation factor and using the Manhattan Distance formula and CSA to improve the model of the inconsistency constraints of the system level, as well as to updates the rules for determining the optimal value during the process of iteration. The algorithm will be used to solve the problem of beer production scheduling, and the simulation results will be provided.
###### Abstract  
This paper describes the application of cryptography and steganography in the protection of cardiac databases. The original cardiac data studied were transformed using a Daubechies wavelet transform. The next step is to conduct Energy Packing Efficiency-based compression. A watermark is added to the received data to protect against unauthorized access, before hybrid cryptography is performed using a suitably selected encryption algorithm. The presented and analyzed algorithm includes protection using public and symmetric key cryptography. The proposed software algorithm is performed on real electrocardiographic, photoplethysmographic, and Holter cardio data. We have evaluated the effectiveness of the applied approach and concluded that a sufficient level of protection of the studied data has been achieved, with methods of authentication and accuracy applied to the users.  
c 2022 2021 23 January 2022 27 January 2022  
Questions about the use of encryption remain on the agenda. In December 2020, the European Commission and the High Representative of the Union for Foreign Affairs and Security Policy identified encryption as a key method of protecting individual rights and ensuring the security of individuals [2].  
The application of cryptographic algorithms regardless of the specific method of implementation (public key, secret key, or hybrid algorithms) is very important for the security of transmitted information. The use of key exchange protocols, digital signatures, and watermark embedding are effective tools for the protection of data, signals, and images.  
The choice of the most appropriate encryption algorithm has an essential role in the process of designing the scheme of protection of transmitted information. The choice of the key used is extremely important, as in practice almost every key can be broken (including from a brute-force attack) by using a rough attack [3] if high computing power is used and enough time is allocated to search for the key.
# Green Macrolgae Biomass Upcycling as a Sustainable Resource for Value-Added Applications
## 3 Results and Discussion  
### Physicochemical Analysis  
#### 3.1.1 Chemical Composition  
Understanding the chemical composition of _Ulva_ sp. (Table 1) is essential for evaluating its biological and nutritional properties and identifying specific industrial applications for it [1]. This analysis guides the efficient use of natural resources for food, health, and biotechnology applications [41; 42].  
Results highlight high crude fiber and total ash concentrations in the dried green macroalgae. The high fiber content reveals an abundance of polysaccharide compounds, while ash content reflects a significant concentration of minerals. Similar findings were reported by [PERSON] et al. [43], who observed 40% of insoluble carbohydrates in _Ulva_ sp., while [PERSON] et al. [33] showed 22.1% for the green algae _Codium isthmocladum_ collected in Brazil. Moreover, the total ash content of 30% is consistent with previous reports [1; 34; 44].  
Our findings agree with the low fat content previously reported for green algae [44]. Comparable results were shown for the ether extract of _Caulerpa racemosa_ (1.8%) by [PERSON] et al. [1] and for _Ulva_ sp. (3%) by [PERSON] et al. [43]. Indeed, fat content levels, including fatty acid profiles, vary with species, season, geography, and growth conditions [33].  
The protein content of UODP (3.39%) is higher than the 2.46% reported by [PERSON] et al. [45] for _Ulva lactuca_ (formally _Ulva fascita_). However, literature values for protein content in _Ulva_ sp. vary widely, with results reaching up to 47% [34]. Such variations in protein content can be attributed to nitrogen availability at the cultivation site. Studies  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Compounds** & **Results (\% DW)** \\ \hline Moisture & 14.77 \(\pm\) 0.20 \\ Crude protein & 3.39 \(\pm\) 0.31 \\ Crude fiber & 37.63 \(\pm\) 6.84 \\ Fat & 1.74 \(\pm\) 0.11 \\ Ash & 30.45 \(\pm\) 1.19 \\ \hline \hline \end{tabular} Values are expressed as mean \(\pm\) standard deviation. DW: dry weight.  
\end{table}
Table 1: Chemical composition (%) of oven-dried green algae _Ulva_ sp. (UODP).  
comparing land-based and sea-based cultivation have reported green algae with protein content ranging from 5% to 20% [33; 43], as it can reach up to 47% in red seaweeds [33].  
Overall, environmental conditions (water temperature, salinity, depth, and pollution) and processing methods (collection, cleaning, drying, and analytical techniques) play a significant role in the variations in chemical composition of macroalgae species [33; 43; 45].
# Rangeland Productivity Partitioned to Sub-Pixel Plant Functional Types
## 2 Materials and Methods
### GPP/NPP Partitioning  
The disaggregated NDVI values by PFT were incorporated into the MOD17 model adapted for Landsat as per the methods in [16]. For each pixel in every 16-day composite, however, rather than a single NDVI value, the disaggregated NDVI values for each PFT represented within the pixel were used. GPP and NPP were then calculated individually for each PFT using the set of biome specific parameters for the given PFT. This results are given in rate of GPP (g C m-2 16-day-1) for each 16-day period and NPP (g C m-2 year-1) annually, for each PFT of each pixel. To calculate actual production per PFT per pixel, the rates of GPP and NPP were combined with the fractional cover estimates (Figure 3).  
Figure 3: Flow chart of the methodological steps to calculate partitioned gross primary production (GPP) and net primary production (NPP) by integrating the Landsat NDVI composite product and the annual plant functional type (PFT) percent cover dataset for perennial forbs and grasses (PFG), annual forbs and grasses (AFG) and shrubs.
# Rapidly Deployable IoT Architecture with Data Security: Implementation and Experimental Evaluation
## 2 Related Works
### Encryption Algorithms
In other works, SIMON is shown to be promising in terms of area and throughput through simulations [23], but not much published literature exists to demonstrate its implementation in commodity hardware like microcontrollers manufactured by popular companies such as TI, Microchip, ST, etc. KATAN is a lightweight block cipher, but requires a large area to be implemented for IoT devices [20]. Light Encryption Device (LED) has an adjustable security level, but the performance is not on par with other algorithms such as PRESENT [15; 21; 22]. Although newer block ciphers like PRESENT and CLEFIA require less area and smaller memory, it comes at a cost of reduced security levels and low throughput and as a result, are not yet adopted in new IoT proposals. Moreover, software implementation of PRESENT is not as effective and is complex [23]. In [31], authors propose optimization strategies for AES 32-b architecture to maximize throughput, reduce area, power, and energy. Their proposed AES implementation consumes almost the same amount of energy as PRESENT, making it a suitable candidate for future ultra-low power IoT applications. Other lightweight algorithms such as SEA and TEA have similar performance, but TEA requires less code-space [23]. Among the lightweight algorithms, TEA matches the speed and conciseness of hardware accelerated AES more than any other encryption algorithm [15; 22; 23]. XTEA was developed to address the vulnerabilities that existed in TEA [35]. Overall, AES was found to be the most widely used, optimized for constrained hardware, and the byte-oriented operations work efficiently on 8-bit, 16-bit and 32-bit architectures. AES and XTEA lightweight encryption algorithms are employed to provide security to edge node devices in IoT applications. The modularity of these algorithms and compatibility with low resource hardware make them ideal candidates for research to find the feasibility of using them in applications where developers have to tune the trade-off between cost, light weight devices, and security. In this paper, we address the security issues in IoT edge nodes. Although blockchain technology has been considered to provide security in IoT systems, it is more targeted at higher levels of the IoT architecture as it requires significant energy, introduces time delay and computational overhead [36; 37]. While there are attempts to use blockchain technology for security at IoT edge nodes in simulation, this is currently beyond the scope of the current work, and will be addressed in the future [38].
## 3 Results, Analysis, and Simulations
### Simulation Planning Results Based on Link Budget, Coverage, and Capacity Calculations
#### 3.3.3 Scenario 1-2: O2O Downlink--Data Rate Throughput  
In Figure 6, the average throughput data rate obtained from the prediction using X sites of groodeB is 50 Mbps. Meanwhile, this research shows a throughput data rate with a minimum value of 30 Mbps and a maximum value of 100 Mbps. By comparing the above findings with those results between scenario one and scenario two, the simulation outcomes are very similar to the calculation results.  
Figure 4: SS-RSRP coverage plot with ACP: 3.5 GHz (**left**) and 28 GHz (**right**).  
Figure 5: SS-SINR quality plot with ACP: 3.5 GHz (**left**) and 28 GHz (**right**).
# Iterative Learning Control for Vibration Suppression of a Robotic Arm
## 4 Experimental Results  
Two experiments were conducted to validate the proposed VH-ILC-EJ controller, the first of which analyzed the effect of the vibration of each joint on the end-effector and the second of which implemented the proposed VH-ILC-EJ controller on the laboratory-developed 6-DOF robotic arm.
## 3 Simulation and Experimental Setups
### Image Quality Metrics  
The lateral resolution was measured by the lateral full-width at half-maximum (FWHM, \(-6\) dB beam width) of a point target. The contrast ratio (CR) was calculated as  
\[\text{CR}=20\text{log}_{10}(\frac{\mu_{\text{cyst}}}{\mu_{\text{bck}}}), \tag{21}\]  
where \(\mu_{\text{cyst}}\) and \(\mu_{\text{bck}}\) are mean values of pixel values before log-compression in selected cyst and background speckle regions, respectively.  
The generalized contrast-to-noise ratio (gCNR) [49], which can evaluate the lesion detectability, is defined as  
\[\text{gCNR}=1-\int min\{p_{\text{cyst}}(x),p_{\text{bck}}(x)\}\,dx, \tag{22}\]  
where \(p_{\text{cyst}}(x)\) and \(p_{\text{bck}}(x)\) are the probability density functions of pixel intensity inside cyst and speckle regions, respectively.  
The speckle signal-to-noise ratio (sSNR), which can evaluate the speckle quality, is estimated as  
\[\text{sSNR}=\frac{\mu_{\text{bck}}}{\sigma_{\text{bck}}}. \tag{23}\]  
where \(\sigma_{\text{bck}}\) is the standard deviation of pixel values in the selected background speckle region.
###### Abstract  
In this study, detailed finite element analysis was conducted to examine the seismic performance of square and circular hollow steel braces under axial cyclic loading. Finite element models of braces were constructed using ABAQUS finite element analysis (FEA) software and validated with experimental results from previous papers to expand the specimen's matrix. The influences of cross-section shape, slenderness ratio, and width/diameter-to-thickness ratio on hysteretic behavior and compressive-tensile strength degradation were studied. Simulation results of parametric studies show that both square and circular hollow braces have a better cyclic performance with smaller slenderness and width/diameter-to-thickness ratios, and their compressive-tensile resistances ratio significantly decreases from cycle to cycle after the occurrence of the global buckling of braces.  
seismic performance; braces; axial cyclic loading; finite element models; compressive-tensile strength degradation +
Footnote †: journal: Applied Sciences  
sections [11; 12; 13; 14; 15; 16]. These previous studies have provided significant data to understand the key parameters of steel braces under cyclic loadings, such as energy dissipation capacity, ductility, lateral deflection at mid-span, and post-buckling compressive resistance. Contrary to other important parameters, asymmetric compressive-tensile resistance ratios, which influence the seismic performance of braced structures, have not been previously investigated. Thus, examination of these parameters is required.  
Hollow square and circular braces are preferred due to their easier connection specifications and applicability to a wide range of sections; the corresponding dimensions (width, diameter, and thickness) of both square and circular specimens are shown in Figure 1. To examine seismic performance, a comprehensive finite element study was conducted on a broad range of slenderness values and width/diameter-to-thickness ratios of square and circular hollow braces using ABAQUS v.6.10 finite element (FE) software [17]. First, finite element models of braces were developed based on experimental tests conducted by [1; 15] to replicate the axial load hysteretic response for parametric study of braces under axial cyclic loading. Then, following the FE models validated against experimental results, a series of parametric studies were carried out on a wide array of specimens to assess hysteretic performance, energy dissipation capability, and asymmetric compressive-tensile resistance.
# Novel Approach in Vegetation Detection Using Multi-Scale Convolutional Neural Network
## 2 Materials and Methods
### Proposed Architecture
#### 2.1.3 Max Pooling  
Max pooling layers are used to downsample the feature maps, reducing spatial dimensions while retaining the most significant features. This operation helps in achieving translational invariance and also reduces computational complexity. By progressively reducing the spatial size of the feature maps, the model focuses on the most salient features.
## 3 Case Analysis
### Prediction Accuracy with Factor Ablation  
In Section 3.1, the effects of vegetation type and distance between the flux sites on GPP prediction accuracy were then investigated. The training data included temperature (Ta), photosynthetically active radiation (PAR), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface water index (LSWI). In this analysis, a feature ablation experiment was conducted to explore the influence of each factor on GPP prediction accuracy.
## 3 Phenomenological Model of Gearbox with Broken Sun Gear Fault
### Phenomenological Model of Planetary Gearbox under Fault Condition  
When a broken fault occurs on the sun gear, it can lead to a remarkable decrease in the mesh stiffness, increase the vibration amplitude, and intensify the impact effects. Replacing \(k_{total}\) in Equation (12) with \(k_{total,fault}\), the meshing shock \(R(t)\) under fault condition is expressed as follows:  
\[R(t)=\frac{F}{\sqrt{k_{total,fault}(t)}}\bigg{(}\frac{1}{m_{c1}}+\frac{1}{m_{c2 }}\bigg{)}e^{-\zeta wt}\sin(\omega t). \tag{22}\]  
The vibration of the sun-planet gear pair can be expressed as follows [25]:  
\[v_{spi}(t)=\sum_{k=-K}^{K}\sum_{q=-Q}^{Q}\overline{c_{k}}V_{q}^{sp}e^{i\varphi q }e^{j2\pi(qf_{m}+kf_{c})t}, \tag{23}\]  
where \(V_{q}^{sp}\) is the Fourier coefficients of \(v_{q}^{sp}\), \(v_{q}^{sp}\) is the amplitude of the \(q^{th}\) harmonic of \(v^{spi}(t)|_{n=1,...,N}\), and \(\overline{c_{k}}\) is a coefficients of Fourier series.  
According to the meshing stiffness under fault conditions, other parameters are kept constant, and the phenomenological model with broken sun gear fault vibration signal can be represented as follows:  
\[x(t)=\sum_{i=1}^{N}\big{(}\
u_{rpi}(t)+\
u_{spi}(t)\big{)}\cdot\Phi_{f}\cdot W _{pi}(t), \tag{24}\]  
where \(\Phi_{f}\) is the meshing impact effect under broken fault condition.  
Based on Equation (24), Figure 12 depicts the simulated vibration signal and its spectrum caused by the faulty sun gear. Similarly, three equally spaced envelopes of the planet carrier exist in a revolution period. However, the impact due to the tooth fault will emerge three times after the planet gear rotates for one cycle. The obvious impacts with an interval of \(1/f_{rs}\) caused by the sun gear fault emerge in the time-domain waveform, as shown in Figure 12a. Figure 12b shows that the same meshing frequency \(f_{m}\), \(2f_{m}\), \(3f_{m}\) also exist. Moreover, the vibration signal appears as sidebands with \(f_{rs}\) interval under the fault condition.  
To further analyze the variation of vibration characteristics under different degrees of broken tooth, Figure 13 shows the frequency spectrum of the gearbox vibration signal with different fault sizes. In Figure 13, the fault frequency of sun gear \(f_{rs}\) can be observed clearly, and there is a symmetric sideband spaced by the rotational frequency of planet carrier \(f_{c}\), which indicates the necessity of considering the time-varying transfer path modulation and shows that the proposed phenomenological model can effectively simulate the sun gear broken fault. The amplification near the peak of fault frequency \(f_{rs}\) shows that the amplitude of the frequencies related to the fault increase gradually with the increase in the fault size, which verifies the validity of the signal model from the perspective of frequency  
Figure 11: A simulated vibration signal of conventional phenomenological models constructed by cosine functions: (**a**) waveform; (**b**) frequency spectrum.