esa-sceva/satcom-chunk-collection huggingface dataset:
# Energy Saving in Wireless Sensor Networks via LEACH-Based, Energy-Efficient Routing Protocols
## 3 LEACH-Based Energy-Efficient Routing Protocols
In the second scheme, sensor nodes lying in an uncovered area of the network compose a subcluster and choose a cluster head based on the shortest distance from the gateways. The orphan node that is located closer to the gateway is selected to be the cluster head. O-LEACH is evinced to outperform LEACH in terms of energy efficiency, scalability, connectivity, and convergence. However, it suffers because of the rapid energy drainage of the nodes that are positioned far away from the base station, as a consequence of single-hop routing. In quadrature LEACH (Q-LEACH) [52] the field of interest is divided into four quadrants based on information location of networks nodes, so that cluster balancing is achieved. Every node randomly picks a number between 0 and 1, while in each one of the four quadrants, a threshold between 0 and 1 is set. If both the random number picked by a node is less than the threshold of the network quadrant it belongs to and the predefined number of cluster heads for this quadrant has not been filled, then this node turns into a cluster head and broadcasts the corresponding pieces of information to the network. Based on the received signal strength indicator (RSSI) of these broadcast messages, each one of the rest network nodes decides the cluster head within their quadrant to be associated with and communicates with this cluster head during its own TDMA slot. In Q-LEACH, cluster head election is energy-efficient, and the overall network lifetime is extended comparatively to LEACH. Nevertheless, it is associated with a higher probability of energy hole creation. In multi-hop routing LEACH (MR-LEACH) [53], the field of interest is divided into different levels, according to the number of hops needed to reach the base station. Each one of these levels includes its own clusters, while all clusters have the same size. In each one of these layers, the cluster heads collaborate with cluster heads of their adjacent layer. Specifically, the data that are aggregated from the more distant clusters are transmitted to the base station by multi-hop routes via the cluster heads of layers being located nearer to the base station. Nodes having greater energy residues are selected to be cluster heads, while the rest nodes choose their own cluster head based on RSSI. The communication among the base station and the cluster heads is performed by using an appropriate TDMA schedule. The use of multi-hop paths in MR-LEACH achieves high energy efficiency. On the other hand, the rapid energy drainage of the nodes close to the base station is the main disadvantage of this protocol.
# Experimental Study on Cooling Performance of a Hybrid Microchannel and Jet Impingement Heat Sink
## 4 Results and Discussion
### Cooling Performance of the Hybrid Microchannel Heat Sink
The hybrid heat sink with a highly-dense micro-jet array (\(\sim\)100 jets per cm\({}^{2}\) with jet width of 0.5 mm) has a lower thermal resistance with a larger pressure drop. Figure 13 shows the pressure drops at different heat fluxes. The pressure drops at 350 W/cm\({}^{2}\) are 5.85, 7.75 and 13.24 kPa at 0.86, 1.30 and 1.90 L/min, respectively. The heat sink has a larger pressure drop with a high volumetric flow rate. The two-phase flow occurs at a large heat flux. Two-phase flow is more complicated at high heat flux where the pressure drop rises in an obvious way. The maximum pressure drop in the experiment is 13.46 kPa at 1.90 L/min and 400 W/cm\({}^{2}\). The range of pressure drop is 1.54-13.46 kPa in the experiment. Figure 11: The thermal resistances of the heat sink. Figure 10: The outlet vapor quality at different heat fluxes. Published studies [13; 14; 16; 37; 38; 39] (experimental and numerical) on microchannel heat sinks for cooling high-power devices are compared with this work. Several important parameters including flow rate, pressure drop, thermal resistance, heat flux and heating area are compared. In the published studies with a heat flux of 200-600 W/cm\({}^{2}\), the thermal resistance ranges from 0.23 to 0.71 K/W with a heating area of 10-30 mm\({}^{2}\) and a pressure drop of 17-400 kPa. The heat sink in this work has a thermal resistance of 0.11 K/W, a 52% reduction compared to existing solutions. The maximum pressure drop is 13.5 kPa. It can be seen that the present hybrid scheme has a smaller pressure drop and thermal resistance. In addition to the pursuit of low thermal resistance at high heat flux, the heating area is also a very important evaluation parameter. The presented solution has a larger heating area of 210 mm\({}^{2}\), which is 6 times larger than the existing schemes. The microjet array designed by [PERSON] et al. [40] has a cooling capacity of 1100 W/cm\({}^{2}\), which is 2.75 times higher than this work. However, its area of the heater is 1 mm\({}^{2}\), which is much smaller than the presented scheme in the heating area. The microchannel heat sink has great cooling performance owing to the combination of a microchannel and jet impingement. A large aspect ratio microchannel can be fabricated by the superposition of the heat sink and the heat sink. The heat sink is  
of microchannel plates. The jet impingement with a size of 0.2 mm \(\times\) 0.5 mm \(\times\) 10 mm has a great cooling capacity and reduces the risk of dryout. The large heating area with low thermal resistance and pressure drop is implemented by heat sinks combining a microchannel and jet impingement.
## 1 Introduction
Most examples in the literature are focused on the analytical/numerical solutions of simple Navier-type or Levy-type square plates. The numerical examples reported for the C\({}^{1}\) rectangular finite element using Lagrange interpolation and Hermite interpolation proposed by [PERSON] [25] and the C\({}^{0}\) continuous isoparametric Lagrangian finite element with 63 Degrees Of Freedom (DOFs) per element proposed by [PERSON] et al. [44] are also limited to the rectangular plate or skew plate. Owing to the striking feature of capturing the high-order continuity well, the Meshless Methods (MM) and IsoGeometric Analysis methods (IGA) appear to be suitable potential methods to construct the numerical formulations for the plate based on HSDTs. The successful implementation of MM [45; 46; 47; 48] and IGA [19; 23; 49; 50; 51; 52; 53; 54] in a number of thick-thin plates with arbitrary geometries can be found in the literature. From the above literature review, it is observed that, due to the mathematical complexity raised by the high continuity requirement, developing simple/efficient standard finite elements with general polynomial approximations applicable for arbitrary HSDTs seems to be a difficult and unreachable task at the present theoretical level. In [PERSON] and [PERSON] [55], a locking-free MTP9 (Mindlin type Triangular Plate element with nine degrees of freedom) using incompatible polynomial approximation is proposed. It also provides a new way and methodology to develop simple and efficient plate/shell elements based on HSDTs. In this work, with a similar procedure as the MTP9, a series of simple High-order Shear Deformation Triangular Plate Elements (HSDTPEs) using incompatible polynomial approximation are developed for the analysis of isotropic thick-thin plates and through-thickness functionally graded plates. In the HSDTPEs, different orders of general polynomials can be easily employed as element approximation functions, the displacement continuity among the adjacent plate elements can be equivalently enforced by a fictitious thin layer which has a definite physical meaning, and consequently, there are no extra continuity requirements under the theoretical framework of the present HSDTPEs. The HSDTPEs avoid the shear-locking problem and the use of a shear correction factor, and have a good convergence rate and high accuracy for both thick and thin plates. Several representative numerical examples are solved and compared to validate the performance of the present HSDTPEs.
# Context-Aware Enhanced Application-Specific Handover in 5G V2X Networks
## 3 Connection-Aware Policy Mechanism (CAP)
### Network Connection Quality Parameters  
The following crucial parameters are used by the proposed mechanism to evaluate the SC performance:  
* Received Signal Strength Indicator (RSSI): This device calculates the power of the radio signal ratio that is received.
* Signal to Interference and Noise Ratio (SINR): The signal quality is measured by comparing the strength of the desired signal to noise and undesired interference.
* Bit Error Rate (BER): This indicates the number of incorrect bits received during the transmission.
* Data Transmission Rate: This represents the rate at which information is sent.
* Delay: The amount of time it takes for data to move from one location to another is calculated.
* Packet Loss: This represents the quantity of packets dropped during the transfer.
* Each of these factors is essential in determining the overall performance of an SC.
# Exploiting Stacked Autoencoders for Improved Sentiment Analysis
## 5 Experimental Results and Evaluation
### Discussion
#### 5.6.3 Learning Rate  
Hyperparameters are interconnected in such a way that a change in the value of one parameter leads to changes in the values of other hyperparameters, which leads to an improvement in performance. Additionally, an optimal value of some hyperparameters depends on the values of other hyperparameters. For example, the learning rate is correlated with momentum, batch size, and L2 regularization. If the momentum decreases from 0.9 to 0.0, the learning rate increases 10-fold. In our research, GA optimized the learning  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Study** & **Model** & **Dataset** & **Accuracy** \\ \hline [PERSON] et al. [78] & FK-SVM & Sentiment140 & 87.2 \\ [PERSON] et al. [89] & LSTM-CNN & Sentiment140 & 84.1 \\ Proposed & GA(SAE)-SVM & Sentiment140 & 83.9 \\ [PERSON] et al. [86] & SVM and Naive Bayes & Tweets Airline & 80.0 \\ [PERSON] et al. [89] & LSTM-SVM & Tweets Airline & 92.9 \\ Proposed & GA(SAE)-SVM & Tweets Airline & 93.0 \\ [PERSON] et al. [90] & Bi-LSTM + attention & Tweets SemEval & 67.7 (F1) \\ Clich’e [91] & LSTM-CNN & Tweets SemEval & 68.5 (F1) \\ [PERSON] et al. [89] & CNN-LSTM & Tweets SemEval & 91.9 (F1) \\ Proposed & GA(SAE)-SVM & Tweets SemEval & 91.8(F1) \\ [PERSON] et al. [92] & Char + CoVe-LSTM & IMDb & 92.1 \\ [PERSON] et al. [88] & XLNET & IMDb & 96.21 \\ [PERSON] et al. [87] & BERT & IMDb & 92.28 \\ [PERSON] et al. [89] & CNN-LSTM & IMDb & 93.4 \\ Proposed & GA(SAE)-SVM & IMDb & 93.6 \\ [PERSON] et al. [93] & SVM-IG & Cornell movie reviews & 85.65 \\ [PERSON] et al. [89] & LCNN-SVM & Cornell movie reviews & 87.0 \\ Proposed & GA(SAE)-SVM & Cornell movie reviews & 87.4 \\ [PERSON] [94] & SVM & Book reviews & 89.0 \\ [PERSON] et al. [89] & LC-S & Book reviews & 89.5 \\ Proposed & GA(SAE)-SVM & Book reviews & 91.0 \\ [PERSON] [94] & Logistic & Music reviews & 87.0 \\ [PERSON] et al. [89] & LSTM-CNN & Music reviews & 91.1 \\ Proposed & GA(SAE)-SVM & Music reviews & 91.3 \\ \hline \hline \end{tabular}
\end{table}
Table 11: A comparison of the proposed model and state-of-the-art approaches based on specified datasets.  
rate for the SAE. We found that in each dataset, as the learning rate decreases, the accuracy increases. We established that 0.001 is the optimal learning rate. Figure 6 shows the effect of learning rate on accuracy.
## 5 Conclusions  
A brief review of the IIoT applications, architecture design, and cloud computing has been presented. The review is followed by the preliminary application of AML for the indirect monitoring of the surface finishing process. The scope of the research work is the chamfer length prediction of a boss-hole replica in the deburring process using AWS Machine Learning (AML). Overall, our indirect monitoring system performed well in terms of the model performance and the time taken to generate the predictions. Additionally, AML was an effective solution in creating a machine learning model for our infrastructure. This results in a system that is relatively easy to set up. Additionally, this system offers a scalability for the prediction requests as the machine learning model on AML is capable of handling 200 prediction requests every second [13]. Additionally, this computing capability can be increased by the AWS team upon request. However, this method is dependent on the accuracy of the machine learning model. Hence, it is important to train and evaluate the machine learning model with large datasets to ensure the accuracy of the model before the system is implemented. The proposed approach in this report is also not limited to the aerospace deburring process, but to any processes which can utilize the regression or logistic regression algorithms provided by the AML client. From the results attained, it was observed that the algorithms have the potential to improve the efficiency of an aerospace deburring process and that this model can be extended to other processes where machine learning can be adopted.  
Figure 20: The AML prediction speed of the Python script.  
The limitation of this approach is in the available machine learning methods in AML. Since the AML only provides logistic regression methods, an advanced machine learning method such as an artificial neural network (ANN), a support vector machine (SVM), or an adaptive neuro-fuzzy inference system (ANFIS) need to be developed and embedded in the AML platform in order to increase the prediction accuracy for more advanced applications such as the prediction of surface roughness and material removal rates. Logistic regression methods have a low performance when handling huge datasets. The development of some machine learning methods can be programmed in tensorflow.  
Conceptualization, W.C. and D.L.; Methodology, W.C. and D.L.; Software, W.C. and D.L.; Validation, W.C. and D.L.; Formal Analysis, W.C. and D.L.; Investigation, W.C. and D.L.; Resources, B.K.P. and T.W.; Data Curation, B.K.P. and T.W.; Writing-Original Draft Preparation, W.C., B.K.P., T.W. and D.L.; Writing-Review & Editing, W.C. and T.T.; Visualization, W.C., B.K.P., T.W. and D.L.; Supervision, T.T. and D.T.; Project Administration, T.W. and O.M.M.; Funding Acquisition, T.T. and D.T.  
This work was conducted within the Rolls-Royce@NTU Corporate Lab with support from the National Research Foundation (NRF) Singapore under the Corp Lab@University Scheme.  
The authors declare no conflict of interest.
## 1 Introduction
The proposed approach is based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to simulate and analyze the layout (the physical location of the elements) and to determine whether robots and other components are suitable. The results in this virtual testbed will easily permit modifications in the original design before the physical implementation, presenting a far more cost-efficient solution. In addition, once the new process has been implemented, the digital twin can be efficiently used for operator training, real-time process monitoring, and feasibility study of future optimizations, resulting in a novel and intelligent mirror with high potential benefits. As it is not a simple replica, it is able to process and understand data, and automatically react to changes according to them. The innovation of the proposed approach is that it combines design, feasibility studies, virtual and real commissioning, training, and monitoring of multi-robot cells in a unique application, which implies a cost-effective and affordable solution for manufacturing industries of all types. The theoretical outcome is the proposed methodology for robot-based automation, while the practical is the digital twin framework with an immersive virtual reality interface which is used as a testbed environment. The proposed approach is validated in a real-life case study that provides a solution for the assembly of parts, demonstrating that the use of the digital twin-based methodology is feasible. Not only is the result of the proposed approach more visual, thanks to the integration of virtual reality, it also reduces costs and increases the productivity, as proven with real operations. Therefore, it is very likely to find potential applications in a number of different areas and multiple industries to create flexible and easily reconfigurable production lines. The rest of the paper is organized as follows: Section 2 reviews the state of the art and previous work, Section 3 presents the proposed approach, Section 4 contains the use case, and main conclusions are found in Section 5.
## 3 Results and Discussion
### Potentialor Polarization Measurements  
The polarization curves of bronze exposed to 3.5% NaCl and simulated acid rain solutions, without and with different concentrations of NAC, are shown in Figure 4.  
Electrochemical corrosion parameters, including corrosion current densities (i\({}_{\text{corr}}\)), corrosion potentials (E\({}_{\text{corr}}\)), and cathodic (\(\beta_{\text{c}}\)) and anodic (\(\beta_{\text{a}}\)) Tafel slopes were estimated by Tafel extrapolation and are listed in Table 3. The i\({}_{\text{corr}}\) values were further used to calculate the inhibition efficiency, \(\eta_{\text{pol}}\), using Equation (2), and the obtained values are also included in Table 3.  
As expected, the corrosion current density estimated for the uninhibited saline environment was almost ten times higher compared to the i\({}_{\text{corr}}\) value of the uninhibited simulated acid rain of a pH = 3.4. The greater corrosive aggressiveness of the saline environment was associated with the presence of chloride ions, which promote the preferential dissolution of the Cu-rich phase in bronze exposed to high-oxygen saline conditions [73], leading to the formation of loosely adherent corrosion products [74]. Patina flaking, commonly observed on Cu-alloys after immersion in marine environments, was associated with the gradual transformation of nantokite (CuCl) into paratacamite (Cu\({}_{2}\)(OH)\({}_{3}\)Cl) of a larger volume [75] that induced internal stress within the patina [76].  
As illustrated in Table 3, some important shifts in E\({}_{\text{corr}}\) towards more negative values were noticed in the presence of increasing concentrations of NAC in both tested electrolytes. The utmost changes in the E\({}_{\text{corr}}\) due to the addition of NAC exceeded \(-\)85 mV, allowing us to suppose that NAC acted mainly as a cathodic-type inhibitor for the bronze corrosion in the two electrolytes.  
Figure 4: Tafel polarization curves of bronze exposed to 3.5% NaCl (**a**) and 0.2 g L\({}^{-1}\) Na\({}_{2}\)SO\({}_{4}\) + 0.2 g L\({}^{-1}\) NaHCO\({}_{3}\) + 02 g L\({}^{-1}\) NaNO\({}_{3}\) (pH = 3.4) (**b**) solutions, without and with different concentrations of NAC, at 298 K.  
The \(\rm{i_{corr}}\) values decreased considerably in the presence of the drug in both tested electrolytes, and this decreasing trend was more pronounced as the concentration of NAC increased up to 36 mM in the 3.5% NaCl solution and 6 mM in the simulated acid rain, respectively. At these concentrations, the inhibiting efficiencies of NAC on bronze corrosion reached the highest values of 83.2% in the 3.5% NaCl solution and 90.1% in the simulated acid rain of \(\rm{pH}=3.4\) (Table 3). The inhibited efficiency values obtained from the potentiodynamic polarization curves and the EIS measurements were in reasonable agreement.  
The changes in the cathodic (\(\rm{\beta_{c}}\)) and anodic (\(\rm{\beta_{a}}\)) Tafel slopes observed in the presence of the drug suggest that the oxygen reduction and the bronze dissolution were affected by the inhibitor addition in both corrosive solutions, but no clear trend was observed.
# Encryption of 3D or Higher-Dimensional Images: A Review
## 2 Plenoptic Images  
Despite advancements in acquisition and display methods for models based on two-dimensional frames, significant limitations remain regarding their fidelity in replicating the real world [21]. One reason is the fact that real-world scenes, which are inherently three-dimensional, are displayed using devices capable of presenting only two-dimensional shapes. Consequently, three-dimensional experiences have gained popularity in recent years across various application domains and need appropriate solutions for data acquisition, encoding, representation, display, and security. In this regard, notable progress has been made in the development of sensors and displays that, instead of relying on the traditional two-dimensional-frame model, employ acquisition and/or display techniques based on directional information, thereby facilitating more immersive visual experiences characterized by multiple views and diverse perspectives.  
In this context, the so-called plenoptic function plays a fundamental role in representing the intensity of light captured from any viewpoint or spatial position in three dimensions, as well as the angular direction, for each wavelength and over time [22; 23]. This model opens new possibilities for visual representation, leading to a more comprehensive and realistic experience, while encompassing the simplest forms of current representations [21]. Conversely, the additional information that enables more faithful representations of real scenes comes at the cost of increased data volume, thereby introducing new challenges in representation. In practical situations, it is necessary to reduce the dimensionality of these data to ensure that the information is represented in a manner suitable for its intended use. Therefore, new modalities of imaging have emerged as simplified representations of light, inspired by the plenoptic function, such as light field images and 3D point clouds [21; 24]. Each of these representations is derived from distinct acquisition models.
# DDS: A Delay-Constrained Duty-Cycle Scheduling Algorithm in Wireless Sensor Networks
## 3 Network Model and Problem Definition
### Network Model  
This work considers a network of \((N-1)\) static sensor nodes and a sink node. Sensor nodes have the same transmission range, within which they can communicate with other nodes. The node deployment strategy can be varied based on specific user demands, i.e., sensors can be placed inside buildings or outdoors, following deterministic or nondeterministic node deployment layouts.  
In order to reduce power consumption, the duty cycling mechanism is used. Nodes can turn off the radio and be dormant during the duty cycle interval except for the sink, which is always active. Nodes only transmit and receive data packets when they are in the active state. In addition, when a node in the sleep state detects an event, the node's radio is turned on to transmit packets. Let \(T\) denote the duty cycle interval, and let \(\tau\) denote the active period of nodes in a duty cycle interval. For each duty cycle interval, sensor nodes independently select a random time to wake up.
# Sillcom: A Communication-Efficient Privacy-Preserving Scheme for Indoor Localization
## 8 Evaluation Results  
### Experiment Setup  
We employed a cloud server equipped with an AMD EPYC 7663 3.5 GHz processor (30 cores) to simulate three computing servers through three terminal instances. To main tain consistency with FAPRIL's experimental setups, we simulated a 16 ms round-trip time (RTT) for user connections via WiFi. Based on Microsoft's EzPC project [61], we implemented our two schemes in C++ and conducted a large number of tests to illustrate the performance of our design. In addition, we compared the theoretical and experimental results with those of FAPRIL in detail.  
For the experimental dataset, we similarly generated the RSS data of RPs through simulation, based on the range of values for \(n\) and \(m\) discussed in Section 4.2.1. Additionally, a single RSS value represented by 4 bits was expanded to  
\[l=2\cdot l_{\text{RSS}}+\lceil\sqrt{n}\rceil\]  
after the distance calculation. Therefore, the value of \(l\) was selected from the range [14; 16] based on the range of \(n\) in [50; 250].