esa-sceva/satcom-chunk-collection huggingface dataset:
# GreenLab, an IoT-Based Small-Scale Smart Greenhouse
## 3 GreenLab Project
### System Design  
As a solution, we propose an IoT-based small-scale smart greenhouse called GreenLab, powered by a photovoltaic panel and a mobile application for monitoring the environmental  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Solution** & **IOT** & **Mobile/Web** & **Green** & **Irigation** & **Low Cost** & **Reference** \\  & **Connectivity** & **Application** & **Energy** & **System** & **Low Cost** & **Reference** \\ \hline Realization of wireless charging in an intelligent greenhouse field & ✓ & X & X & X & X & [13] \\ \hline Wireless power supply technology for the uniform magnetic field of intelligent greenhouse sensors & ✓ & X & ✓ & X & X & [14] \\ \hline Fuzzy Maximum Power Point Tracking (MPPT) controller for photovoltaic system on mini greenhouse & ✓ & X & ✓ & X & X & [15] \\ \hline An Automated Greenhouse Monitoring and Controlling System using Sensors and Solar Power & ✓ & ✓ & ✓ & X & ✓ & [16] \\ \hline A Smart Photovoltaic System with the Internet of Things: A Case Study of the Smart Agricultural Greenhouse & ✓ & ✓ & ✓ & ✓ & X & [17] \\ \hline Personal Food Computer: A new device for controlled-environment agriculture & ✓ & ✓ & X & ✓ & ✓ & [18] \\ \hline “Food Computer”—A Demo Platform for the Internet of Things Education & ✓ & ✓ & X & ✓ & ✓ & [19] \\ \hline GreenLab & ✓ & ✓ & ✓ & ✓ & ✓ & \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._parameters. The solution respects the IoT layered architecture approach and includes layers for perception, communication, and the application. Figure 1 presents the block diagram of the perception layer of GreenLab. The diagram consists of the Arduino MEGA 2560 R3 development board with an ATmega2560 microcontroller, an 8-channel relay module, an ultrasonic distance sensor to measure the water level in the container, a capacitive soil moisture sensor, a gas sensor, a light sensor, an air temperature and humidity sensor, an Ethernet module connected to a phpMyAdmin database, a solar panel, a battery (with its charger), a submersible water pump, an auto heater, two fans, LED matrices and the greenhouse itself.  
GreenLab is powered mainly by the energy obtained from the solar panel. Taking into account the cloudy days or that there is a day-night cycle, a buffer battery has been connected to provide the energy to supply all the components of the mini-greenhouse which is charged mainly from the solar panel. Secondary/alternatively, a charger is connected to the main battery, only in case of need. The functional block diagram with the supply of the component blocks from the renewable energy source (solar panel) and alternatively from the network is presented in Figure 2.  
Figure 1: Block diagram of the perception layer of GreenLab.
## 3 Numerical Simulation Results on Flow Characteristics
### The Flow Characteristics with 30% and 50% Concentration of Ethylene Glycol  
To explore the influence of ethylene glycol solution concentration on flow characteristics, based on the method described in Section 3.1, a comparative simulation of ethylene glycol aqueous solutions with three volume concentrations of 30%, 50%, and 60% was carried out under the condition of keeping the total inlet flow constant. The flow distribution uniformity of the cold plate was verified and the most unfavorable conditions were identified. The results show significant differences in the hydrodynamic characteristics of solutions with different concentrations. Compared with the 60% concentration solution, the 30% and 50% concentration solutions showed non-uniform flow distribution characteristics in the cooling pipe. The lowest flow area was located in the ninth and tenth rows of the cold plate, and the branch flow showed a non-linear trend of decreasing first and then rising. This phenomenon indicates that the change in solution concentration will significantly affect the flow stability of the system, and it is necessary to consider the influence of concentration gradient on the distribution uniformity in the thermal management design. Here, the flow distribution data of the cold plate with a volume concentration of 30% are shown in Table 4.
# Design of A Parallel Decoding Method for LDPC Code Generated via Primitive Polynomial
## 1 Introduction
Therefore, the outputted extrinsic information will not be affected by short cycles. Then the cascaded decoding module output candidate codeword with the help of extrinsic information. At last, all outputted codewords of sub-decoders are sent into the same LMS and the final codeword is selected by MAP rule. In this paper, the m sequence codes with code length 3000, 1100 are constructed by primitive polynomial \(f(x)=x^{89}+x^{38}+1\) and \(f(x)=x^{33}+x^{13}+1\), respectively. Then the bit error rate simulation experiments of these codes are carried out. In the experiment, 6 and 4 parity-check matrices are constructed by the proposed construction method, respectively. In addition, when the numbers of sub-decoders are 5 and 4, the bit error rate (BER) curves have converged. Simulation results show that the proposed parallel decoding method is about 0.4 dB better than the single decoder method in [1]. This paper is organized as follows. Section 2 gives a brief introduction of LDPC code generated via primitive polynomial and presents the problem statement. The construction method of parity-check matrices and new parallel decoding method are specified in Section 3. Section 4 shows and analyzes the numerical results. Finally, some conclusions are drawn in Section 5.
# A High Efficiency Multistage Coder for Lossless Audio Compression using OLS+ and CDCCR Method
## 4 Complex Prediction Method with Backward Adaptation
### Alcm+  
In the proposed solution, the complexity of the main prediction block can be significantly reduced by replacing the RLS block with the rapid ALCM+ method. In the ALCM+ method, the prediction coefficients adaptation procedure has a linear complexity relative to the order of prediction and does not require any square matrix to be adapted.
# Performance of Automated Oral Cancer Screening Algorithm in Tobacco Users vs. Non-Tobacco Users
## 2 Materials and Methods
### Overview  
A total of 2198 images of healthy oral mucosa and oral lesions suspicious for OPML or OC were collected from 318 subjects, together with a full documentation of any clinical signs and symptoms as well as an evaluation of all individual risk factors and behaviors. Images and data were recorded using a prototype intraoral camera system and algorithm specifically designed for non-specialists working in a low resource community setting. The accuracy of OC risk status as determined by the screening platform was compared in tobacco smokers vs non-smokers. Specialist screening outcome served as gold standard for evaluating the platform's screening accuracy.
# Computation of the Hausdorff Distance between Two Compact Convex Sets
## 2 Materials and Methods
### Support Functions and Supporting Sets  
The set of supporting points \(\operatorname{supp}_{S}(\mathbf{v})=\operatorname{argmax}_{\mathbf{x}\in S}\mathbf{v}^{ \top}\mathbf{x}\) determines the support function \(\sigma_{S}(\mathbf{v})\). For instance, the \(\ell_{1}\) unit ball has \(\operatorname{supp}_{S}(\mathbf{v})\) equal to the convex hull of the vertices \(\pm\mathbf{e}_{i}\) where \(|v_{i}|\) is largest. For the unit simplex, \(\operatorname{supp}_{S}(\mathbf{v})\) equals the convex hull of the vertices \(\mathbf{e}_{i}\) where \(v_{i}\) is largest. For a Minkowski sum \(A+B\), \(\operatorname{supp}_{A+B}(\mathbf{v})=\operatorname{supp}_{A}(\mathbf{v})+ \operatorname{supp}_{B}(\mathbf{v})\). If \(S\) is either a convex cone or a compact convex set that is symmetric about the origin with a non-empty interior, then its support function \(\sigma_{S}(\mathbf{y})\) has a special form. In the former case, \(\sigma_{S}(\mathbf{y})\) is the indicator of the dual cone, and in the latter case, \(\sigma_{S}(\mathbf{y})\) is a norm. The support function of a Cartesian product is the Cartesian product of the separate support functions. For instance, the support function of rectangle \([\mathbf{a},\mathbf{b}]\) reduces to the one-dimensional case, where \(\operatorname{supp}_{[a,b]}(\mathbf{v})\) is \(a\) when \(v_{i}<0\), \(b\) when \(v_{i}>0\), and all of \([a,b]\) when \(v_{i}=0\). There are many other known support functions. For instance, one-sided penalties such as \(c\max\{y,0\}\) and asymmetric penalties such as \(\sigma_{[-a,b]}(y)\) are covered by the current theory. Indeed, the former is the support function generated by the interval \([0,c]\). The latter is the tilted absolute value equal to \(by\) for \(y\geq 0\) and to \(-ay\) for \(y<0\). The support function of a singleton \(\{\mathbf{a}\}\) is the linear function \(\mathbf{a}^{\top}\mathbf{y}\). More generally, the support function of the convex hull of the set \(\{\mathbf{a}_{1},\ldots,\mathbf{a}_{d}\}\) is \(\max_{1\leq i\leq d}\mathbf{a}_{i}^{\top}\mathbf{y}\). The support function of the line segment from \(-\mathbf{a}\) to \(\mathbf{a}\) is the absolute value \(|\mathbf{a}^{\top}\mathbf{y}|\). Adding a constant vector \(\mathbf{a}\) to a set \(S\) produces the support function \(\sigma_{S}(\mathbf{y})+\mathbf{a}^{\top}\mathbf{y}\). It is trivial to project onto \(S+\mathbf{a}\) if one can project onto \(S\). For any non-negative scalar \(c\), the set \(cS\) has support function \(c\sigma_{S}(\mathbf{y})\). Again, it is trivial to project onto \(cS\) if one can project onto \(S\).
# Surface Defect Detection of Preform Based on Improved YOLOv5
## 3 YOLOv5 Network and Improvement  
In this article, the surface image of preform is obtained by the machine visual platform, and the image is annotated by the online annotation tool Make Sense. After the annotation is completed, it is saved as a txt file in YOLO format, and a dataset is created. Based on the idea of transfer learning, the YOLOv5 model is introduced to properly train the dataset and identify defects. A total of 427 images with defects were collected, and the original image resolution was 8192 \(\times\) 13,000 pixels. Each image may contain multiple defects, with a total of 2157 marks. Among them, 162 overall dislocation of prepreg, 168 overall non dislocation of prepreg, 158 dislocation of stiffeners, 162 normal stiffeners, 855 wrinkles, and 652 bubbles are marked. That is, the proportion of wrinkle defects is about 40%, the proportion of bubble defects is about 30%, the proportion of reinforcement dislocation defects is about 7.5%, and the overall dislocation defects of prepreg are about 7.5%. There are differences in the number of different defect types. Compared to other open data sets, the data set established in this article has very few samples, and there are various cases of uneven samples between classes, which poses a great challenge to defect identification.
# Method to Measure Light Spot Position in Beacon-Less Inter-Satellite Communication System
## 2 The Beacon-Less Is-OWC System Description  
Beacon-less Is-OWC system requires small size, low power cost and flexible network, in which transmitted and received light use the same wavelength and pass through the same optical path [2]. Because of some factors in the transmission channel, such as the back surface reflection of the polarizer and the installation errors of the optical devices, etc., part of the transmitted light will be reflected in the transmission. As Figure 1 shows, some reflected light will be mixed within the received light. We could consider separate the mixed light beams by polarization splitting [11; 12]. However, in practice, polarizing splitter cannot separate the two light completely.
# Towards Deep Integration of Electronics and Photonics
## 1 Introduction
It is remarkable that most of the required components can be improved using plasmonics. The discussion of building blocks of hybrid circuits in Section 3 of this paper is preceded by the discussion of perspective plasmonic materials in Section 2. Key experiments and achievements in the field of quantum plasmonics are presented in the Section 4. A brief discussion of other quasiparticles capable of light-matter hybridization as well as their interaction with plasmons is presented in Section 5. The conclusion follows in Section 6. Figure 1: Various types of plasmonic excitations: (**a**) Bulk plasmon in a metallic sample, electronic gas oscillates as a whole with a plasmonic frequency \(\omega_{p}\). (**b**) Propagating surface plasmon polariton excited by the external electromagnetic wave. (**c**) Localized surface plasmon excited by the external field in a small metallic nanoparticle. Displacement of the electron gas is shown with light grey.
## 3 Result and Discussion
### Strain Mapping
#### 3.3.2 Multi-Cell Panels with Infill  
Double-Cell Panels with Infill  
The strain mapping of the double-cell panels is shown in Figure 12. All the panels show that with an increase in loading, the mid-span of the bottom skin remained in compression, and the top skin remained in tension. In double-cell panels without fibres, a deviation in the curves was noticed when the panels underwent local buckling or tearing of sheets, which resulted in a drop in the strain value. The strain in the bottom skin of the double-cell panel with chopped basalt fibres was less than in the panels without them. It showed fewer variations due to the SCGC concrete combined with the chopped basalt fibres making the panels more ductile. No sudden or brittle failure was reported for the panels containing chopped basalt fibres in the infill. The strain mapping data of double cells with fibre indicates that the tensile properties of the deck were not completely utilised since the steel sheeting failed before the yield values of strain. However, double cells without fibre sufficiently utilised the full tensile capacity of the deck panels to attain the ultimate load.  
Triple-Cell Panels with Infill  
The two triple-cell panels tested without chopped basalt fibres showed similar behaviours, as presented in Figure 13. The top skin was in tension, and the bottom in compression. However, close to the ultimate load, when the cracks in concrete began widening, and the steel and concrete interface began to slip, a variation in the strain data on  
Figure 12: Strain mapping of double-cell panels.  
the bottom skin was noticed. The strain reduced and moved away from compression until the panel failed at the ultimate load. This also indicates that the neutral axis moved into the steel sheeting and part of the steel resisted the compression. The top skin yielded first and did not take any more load, whereas the bottom skin continued taking a steady amount of load after reaching the ultimate load until complete failure occurred. The strain mapping data depict that the strain values in tension reported lower values than those of the yield strength of steel sheets, indicating that the full capacity of the steel deck was not utilised.
## 4 Primary and Secondary Paths
### Secondary Paths Analysis
The paths are compared in the same manner as before. In Figures 11 and 12, the selected actuators are mounted to the back and right casing panel, respectively. Once again, the magnitude increases for decreasing distance \(d_{i}\) in a frequency range up to approximately 200 Hz. These paths also confirm, that placing the casing in a corner increases the magnitude of paths in the low frequency range (these frequencies are better excited in the enclosure). However, it is also noteworthy that both primary and secondary paths' magnitudes increase in a similar manner, hence the balance between them should be sustained and the noise reduction capabilities should not be impeded. Figure 10: The amplitude functions of the frequency functions of the impulse response estimates for the secondary paths between top casing panel’s selected actuator and the error microphone adjacent to the top casing panel, at all distances, in both setups. Figure 9: The amplitude functions of the frequency functions of the impulse response estimates for the secondary paths between back casing panel’s selected actuator and the error microphone adjacent to the back casing panel, at all distances, in both setups.
## 1 Introduction
According to a review of a large number of FAO references, the existing control methods do not consider the complexity of the control or optimization algorithm structure, and they mostly use feedback to construct the control law, generating the control input through the deviation of the train operation status information. However, when the deviation of the train operating state from tracking the desired curve is large, the controller will generate a large fluctuating control input, which will affect the control accuracy of the train operation and the comfort of passengers. Therefore, this paper starts from a new perspective; based on the output-constrained adaptive control theory, while ensuring the minimum structural complexity of the algorithm, the upper and lower bounds of the output value of the train position are directly restricted, so as to ensure that the error of the train operation position is within the allowable error, the desired position curve is tracked with small position error or 0 error, and the control accuracy of the FAO is improved. Due to the influence of factors such as parameter uncertainty and external disturbance in the FAO, this paper introduces the additional resistance and unknown disturbances that cannot be accurately modeled in the train dynamics model into the position output-constrained adaptive controller in the form of disturbance by RBFNN, so as to enhance the ability of the system to deal with disturbances such as ramps and curves, as well as realize accurate tracking control of the urban rail train operation curve. This is of great significance for guaranteeing the safety of multi-train tracking operations and station fixed-point parking. The main elements of this paper are summarized below. * A position output-constrained robust adaptive control algorithm based on RBFNN (RBFNN-POCRAC) is proposed. The algorithm combines position output constraints, RBFNN, and adaptive control, explicitly considers the complexity of the algorithm structure, the initial tracking, and approximation errors of the system, and gives the error boundary that can be adjusted to any small value by selecting appropriate parameters. Considering the unknown and time-varying coefficients of the basic resistance Davis equation, the adaptive control law is designed to estimate the basic resistance of the train and enhance the engineering practicability of the control algorithm. * The additional resistance and unknown disturbance are introduced into the position output-constrained adaptive controller in the form of disturbance by RBFNN, which can usefully decrease the acquisition of data such as route slopes, curves, and turnouts, as well as have a strong inhibitory effect on the disturbance caused by train operation in open routes or tunnels. * In order to test and verify the availability of the designed FAO controller, complex route conditions are selected for MATLAB simulation. The results show that the FAO control algorithm proposed in this paper can track the desired curve with higher control accuracy in a shorter time and has good control performance.
# Interconnecting Haptic Interfaces with High Update Rates through the Internet +
## 4 Simulation Scenarioof Existing Protocols  
In order to monitor the performance metrics of Table 1 and evaluate the transport protocols, simulations are undertaken. The network simulator that is used is the Network Simulator 2 (NS2) [51]. It is a widely used open source simulator. A lot of common protocols have already been implemented and tested in the NS2. Unfortunately, not many haptic protocols have been applied in NS2 so far.  
One transport protocol for haptic applications that havebeen implemented in NS2 is the ETP. Apart from that, a lot of real-time protocols that could be used for haptic applications have been applied in the NS2. Some of them are the RTP, SCTP, DCCP and UDP.  
All the above protocols were attached to different nodes in the NS2, as shown in Figure 1. The protocol TCP was mainly applied to the simulation scenario as a traffic generator. All the other protocols try to send a stream of packets with a packet rate of 1000 packets per sec. Most of them have a congestion control algorithm and minimize their sending rate in case of congestion. The haptic packet size that every protocol sends is 64 bytes of data payload [12] plus the overhead of the protocol.  
The sample video for the HEVC encoding was the mobile_cif YUV series [52] with 352 \(\times\) 288 resolution at 24 Hz. The data rate of this video sample after the HEVC encoding with Quantization Parameter QP = 27 and Low-Delay inter-prediction is 642 kbps [53]. This data stream sent over the RTP protocol with a packet size of 1500 bytes.  
The audio stream was sent over the RTP protocol with 128 kbps bit rate, packet size 320 bytes and sending rate 50 packets per second.
## 4 Applications of Fe\({}_{3}\)O\({}_{4}\) Nanoparticles
### Biomedical Applications (Therapeutic and Diagnostic Technologies)
#### 4.1.1 Contrast Agents for Magnetic Resonance Imaging (MRI)
These functionalized NPs were highly dispersible in water and exhibited a high spin-lattice relaxivity r\({}_{1}\) of 17 s\({}^{-1}\) mM\({}^{-1}\) and low r\({}_{2}\)/r\({}_{1}\) ratios ranging from 3.3 to 3.8, which are good characteristics for T\({}_{1}\) positive contrast agents. [PERSON] and coworkers synthesized ultrasmall superparamagnetic Fe\({}_{3}\)O\({}_{4}\) NPs modified with bull serum albumin and investigated these NPs as T\({}_{1}\)-T\({}_{2}\) dual-modal MRI contrast agents in rabbit hepatic tumors [109]. In vivo experiments showed a rapid T\({}_{2}\)-weighted effect after 5 min, and T\({}_{1}\) contrast enhancement appeared 90 min after intravenous administration. An Fe\({}_{3}\)O\({}_{4}\)-based dual-mode contrast agent for MRI and computed topography (CT) imaging was developed by [PERSON] et al. [110]. In this study, Fe\({}_{3}\)O\({}_{4}\)@Au core-shell nanoparticles with a size of approximately 21 nm were prepared using a simple sonochemical method. The obtained core-shell NPs showed transverse relaxivity values of 222.28 mM\({}^{-1}\) s\({}^{-1}\) and have good potential for applications in MRI and CT imaging.