esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 System Models and Assumptions
### Adversary Model  
In this paper, we consider an adversary model that is similar to the one used in [22; 40]. The model has three types of adversaries:  
1. **A passive adversary** that can observe and obtain packets by eavesdropping on a network transmission.
2. **An external adversary** who can originate and inject false data from the outside. He can also replay old packets or modify the transmitted data.
3. **An internal adversary** that can physically compromise sensor nodes or cluster heads.  
Each one of the three types of adversaries can launch a different number of attacks based on his abilities.  
An adversary of **Type 1** can obtain secret information by eavesdropping.  
1. **Eavesdropping Attack:** this attack concerns the passive adversary who aims to obtain information by listening to the message transmission in the broadcasting wireless medium [41].  
The adversary of **Type 2** can send false information by modifying the content of packets, injecting false data, or replaying old messages. Therefore, he can launch three kinds of attacks:  
1. **Injection Attack:** In this attack, an adversary injects false data into the network and compromises the trust in the communicated information.
2. **Replay Attack:** the attacker captures some packets and resends them at a future time.
3. **Modification Attack:** the adversary modifies the data without knowing the content.  
Lastly, the adversary of **Type 3** can sense and know all secret parameters. In this situation, he can launch a compromise attack.  
1. **Node Compromise Attack:** the attacker physically comprises a node or CH to obtain secret information and generate the secret parameters of the network.
# Reducing the Power Consumption of VR Displays with a Field Sequential Color LCD
###### Abstract  
To achieve 60 pixels per degree (PPD) and 100\({}^{\circ}\) field of view (FoV) while keeping a reasonably high aperture ratio for active-matrix liquid crystal displays (LCDs), field sequential color (FSC) is a promising approach. We evaluate the physical properties of a high birefringence nematic LC mixture and then use these data to simulate the performance of a fringe-field switching (FFS) LCD. Such an FFS LCD exhibits a fast average gray-to-gray response time (\(\sim\)1.5 ms) to enable FSC operation. By removing the spatial color filters, FSC operation triples the resolution density and optical efficiency, which are critical to high-resolution density and low power consumption virtual reality applications. Wide color gamut (96.2% of the DCI-P3 standard) and superior color uniformity are also demonstrated using such an FSC LCD.  
field sequential color; liquid crystal display; low power consumption +
Footnote †: journal: Applied Sciences
# Control Synthesis as Machine Learning Control by Symbolic Regression Methods
## 4 Symbolic Regression Methods
### The Genetic Programming  
Genetic programming (GP) is the first invented and the most popular method of symbolic regression [9]. GP codes the mathematical expression in the form of computational tree. Figure 1 shows the computational tree for the example mathematical expression (30).  
In the computer memory the mathematical expression is written in the form of an ordered multi-set of integer vectors with two components, the first component is the number of arguments of function, the second component is a function number.  
The code of GP for the example is  
\[C_{GP}=\bigg{(}\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 1\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 3\end{array}\bigg{]},\]  
\[\bigg{[}\begin{array}{c}1\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 1\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 4\end{array}\bigg{]},\bigg{[}\begin{array}{c}1\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 2\end{array}\bigg{]},\]  
\[\bigg{[}\begin{array}{c}1\\ 4\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 3\end{array}\bigg{]},\bigg{[}\begin{array}{c}1\\ 3\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 1\end{array}\bigg{]},\bigg{[}\begin{array}{c}1\\ 5\end{array}\bigg{]},\]  
\[\bigg{[}\begin{array}{c}2\\ 1\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 5\end{array}\bigg{]},\bigg{[}\begin{array}{c}2\\ 2\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 1\end{array}\bigg{]},\bigg{[}\begin{array}{c}0\\ 4\end{array}\bigg{]}\bigg{)}. \tag{34}\]  
Despite the popularity of the method, it has a computational weakness. The code of GP has different length for different mathematical expressions. In this regard, other methods considered below seem to us more attractive from a computational point of view.
## 3 Results and Discussion
In such modes of operation, the supercapacitor is more energy efficient. The advantage of supercapacitors is that they can have a thousand times higher energy than linear capacitors [12; 24]. In terms of specific energy, SCs are equivalent to modern lead-acid batteries [8], and the specific power of SCs is \(23\) times higher than the specific power of serial lithium-ion batteries [11]. The development and improvement of technology for the production of supercapacitors has led to the emergence of new materials for electrodes, such as three-dimensional porous carbon. This type of carbon has the properties of a supercapacitor, with a thickness of only one atom. The surface area of one gram of the material is \(3100\) square meters. Treatment of the above material with potassium hydroxide leads to the creation of a large number of tiny pores in the carbon, which, in combination with the electrolyte are able to retain a colossal electric charge. This material has ideal properties for a supercapacitor and industry is fully prepared for its production. With the advent of new serial samples of supercapacitors, it will be necessary to improve equivalent substitution schemes, taking into account the physical properties of the material of the electrodes of the SC. It will be important to take into account the dependence of the electrical parameters of the SC on frequency, voltage and ambient temperature. This substitution scheme can be refined to study longer processes that occur in the deep layers for more than \(30\) min. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**The Range of Change** & **0.25 \(\ldots\) 0.5** & **0.5 \(\ldots\) 0.75** & **0.75 \(\ldots\) 0.9** & **0.9 \(\ldots\) 0.99** \\
**Voltage, (\(U_{i}-U_{\mathrm{n}}\))/\(U_{\mathrm{n}}\), V** & & & & \\ \hline \(W_{\mathrm{SCin}}\), J & 302.93 & 680.30 & 651.00 & 493.00 \\ \hline \(W_{\mathrm{LCin}}\), J & 420.00 & 699.90 & 556.00 & 379.00 \\ \hline \(W_{\mathrm{ABin}}\), J/SC & 791.50 & 1079.00 & 787.00 & 521.00 \\ \hline \(W_{\mathrm{ABin}}\), J/LC & 1120.00 & 1120.00 & 674.00 & 401.00 \\ \hline \(W_{\mathrm{loss}}\) in J/SC & 488.57 & 398.70 & 136.00 & 28.00 \\ \hline \(W_{\mathrm{loss}}\) in J/LC & 700.00 & 420.10 & 118.00 & 22.00 \\ \hline \(\eta_{\mathrm{SCin}}\), \% & 38.3 & 63.0 & 82.7 & 95.0 \\ \hline \(\eta_{\mathrm{LCin}}\), \% & 37.5 & 62.5 & 82.5 & 95.0 \\ \hline \(\dagger_{\mathrm{SCin}}\), s & 35.62 & 83.24 & 13.320 & 37.100 \\ \hline \(t_{\mathrm{LCin}}\), s & 49.78 & 85.09 & 11.310 & 28.230 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Energy characteristics when charging a linear capacitor and a supercapacitor in different ranges of voltage change.
## 2 Proposed HEMS Framework
The findings evaluation section focuses on the outcomes of implementing the AI-powered Smart HEMS and is divided into three assessments: technical, economic, and environmental. The technical evaluation includes an energy analysis that compares the energy generation from renewable sources with the household's energy consumption. This analysis helps to identify periods of surplus and deficit energy, ensuring that the backup systems are effectively utilized to balance energy supply and demand. The economic assessment involves a financial analysis that evaluates the operating costs across various scenarios, such as high renewable energy availability versus low availability. This analysis helps to determine the most cost-effective energy management strategies. The environmental assessment includes an ecological analysis that measures the reduction in greenhouse gas emissions achieved by prioritizing renewable energy sources and the improvement in the renewable fraction, which indicates the proportion of total energy consumption met by renewable sources.
# DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)
## 4 Proposed Scheme
### Acoustic Signal Velocity in the Underwater Environment  
Different factors affect the speed of acoustic waves i.e., temperature variation, pressures at different layers of the sea and salinity of the water. Mathematically, it can be related as [36]: \(c=1446.96+4.591T-5.305\times 10^{-2}T^{2}+2.374\times 10^{-2}T^{3}+1.340(S-35)+1.63 \times 10^{-1}D+1.675\times 10^{-7}D^{2}-1.025\times 10^{-2}T(S-35)-7.139\times 10^{- 13}TD^{3}\), where \(c\) represents the velocity of the acoustic signal in m/s, \(T\) represent the temperature in degree Celsius, \(S\) is the salinity in parts per thousand and \(D\) represents the depth in meters. The sound speed increases with the increase in temperature as shown in Figure 3 and speed of sound variation with respect to salinity shown in Figure 4. The above Equation is valid for 0 \({}^{\circ}\)C \(\leq T\leq\) 30 \({}^{\circ}\)C, 30 \(\leq S\leq\) 40 PPT, 0 \(\leq D\leq\) 8000 m.  
Figure 3: Speed of sound vs. temperature.  
Figure 2: Network architecture.
## 4 Conclusions  
In summary, we fabricated a lightweight shingled-type PV module with an ETFE front sheet and an Al honeycomb structure. The ETFE film replaced the front cover glass  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**ML 2400**} & \multicolumn{2}{c}{**DH 1000**} & \multicolumn{2}{c}{**TC 200**} \\ \cline{2-7}  & **Before Test** & **After Test** & **Before Test** & **After Test** & **Before Test** & **After Test** \\ \hline V\({}_{\text{OC}}\) (V) & 21.50 & 21.49 & 21.63 & 21.59 & 21.79 & 21.76 \\ I\({}_{\text{SC}}\) (A) & 10.71 & 10.74 & 10.99 & 10.84 & 11.04 & 10.88 \\ FF & 0.717 & 0.706 & 0.748 & 0.744 & 0.753 & 0.743 \\ P\({}_{\text{M}}\) (W) & 165.09 & 162.88 & 177.78 & 174.23 & 181.14 & 175.78 \\ P\({}_{\text{M}}\) loss & 1.34\% & & 2.00\% & & 2.96\% & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Result of standard reliability tests of lightweight shingled-type PV modules under IEC 61215 viz. mechanical load 2400, damp heat 1000 and temperature cycling 200 tests.  
Figure 5: (**a**) Photograph, (**b**) electroluminescence images, and (**c**) I-V curve of the shingled-type lightweight PV module.  
to reduce the module weight, and an Al honeycomb structure was used instead of the front glass to improve the mechanical rigidity. To enhance the \(\mathrm{P_{M}}\) of the PV module, we integrated 12 string arrays with 40.8 M2-size Si solar cells. In our lightweight shingled-type PV module, 4.8 M2-size Si solar cells were more integrated compared to the optimized conventional PV module at the same area. Moreover, we adjusted the amount of dispensed ECA to optimize its performance. The lightweight shingled-type PV module had a \(\mathrm{P_{M}}\) of 195.84 W at a 1.004 m\({}^{2}\) area and weighed only 9 kg/m\({}^{2}\). Finally, we performed standard reliability tests to verify the durability of lightweight shingled-type PV modules. The conversion power reduction of the PV modules were less than five percent.  
Conceptualization, M.-J.P.; methodology, M.-J.P. and S.Y.; data curation, M.-J.P., S.H.L. and K.J. writing--original draft preparation, M.-J.P.; writing--review and editing, M.-J.P. and C.J.; supervision, C.J. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the International Energy Joint R&D Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP). The authors also acknowledge financial resources granted by the Ministry of Trade, Industry & Energy, Republic of Korea. (No. 20203030010200).  
Not applicable.  
The authors declare no conflict of interest.
# Efficient Detection of Pre-Proinsulin by Double Antibody Sandwich ELISA
## 2 Materials and Methods
### Accuracy and Sensitivity Evaluation  
In order to evaluate the accuracy of our established double antibody sandwich ELISA method, we further determined the recovery rate. First, recombinant human insulin was accurately weighed and dilutions at a concentration of 2 mg/mL were prepared. Next, PPI standards were prepared at concentrations of 82.5 pg/mL, 20.58 pg/mL and 5.16 pg/mL. Afterwards, 2 mg/mL of recombinant human insulin solution was mixed with equal volumes of different concentrations of PPI standards to prepare QC samples with final concentrations of 41.25 pg/mL, 10.31 pg/mL and 2.58 pg/mL. The samples to be tested were diluted from 2 ug/mL of recombinant human insulin solution to 1 ug/mL of solution. Finally, the standard, the sample to be tested and the QC sample were added to the coated ELISA plate, and 3 replicate wells of each sample were used as blank control with the universal dilution solution, and the assay was performed according to the ELISA method established above. The accuracy was expressed as the recovery rate. The mean value of the measured concentration of the control sample was subtracted from the mean value of the measured concentration of the sample to be tested, and the ratio of the difference to the theoretical added concentration was the recovery rate.  
The absorbance values of 12 blank samples, i. e., those of the general dilutions at 450 nm wavelength, were determined by the double-antibody sandwich ELISA method. The average absorbance value of the measured samples plus the absorbance value obtained by three times standard deviation was substituted into the quantitative equation.
# Improving Waste Management System Efficiency and Mobility with Efficient Path MANET
## 2 Related Work
#### Ga  
GA is an evolutionary optimization strategy that draws inspiration from natural processes and is used in research on routing algorithms [37; 38]. GA is a form of natural selection and evolutionary computing applied in global optimization [39; 40; 41; 42]. GA has been demonstrated in theory and through experiments to be a reliable search method. GA-based routing algorithms are used in routing algorithms to find paths through networks [43].  
As shown in Figure 3, the GA process starts by obtaining the population. In particular, it begins by randomly generating a population before evaluating individuals and finding solutions. This population is then tested using a fitness function that seeks to determine the function objective. After the evaluation, the best candidates for genetic operations, such as crossover and mutation, are selected to improve the next generation. Finally, the condition termination process is applied to see if the process should go on to the next round or be terminated.  
Crossover operation, which is based on the GA structure, is the exchange of genes between pairs of selected individuals of chromosomes at specific points to generate a new generation of offspring with modified characteristics.  
Chromosomes 1 and 2 are designated as parents or initial possible paths, whereas Chromosomes 3 and 4 are designated as new offspring, which may lead to the final solution. This process considers the suitable path, followed by the termination process or proceeding to the next iteration of the problem-solving process.  
Figure 2: WMS architecture.  
The present study presents an intersection GA-based routing algorithm via a chromosome intersection method on the selected path during genetic processing to find the efficient paths that comply with the service requirement constraints. The influence of the intersection activation values in the proposed algorithm is also examined.
## 2 Quantum Dots in Sensing Applications
### Semiconductor Quantum Dots
While QDs have great potential as fluorescent probes in the sensing of organic molecules, the affinity of their surfaces for the target molecules must be improved. Recently, a few studies on the improvement of their affinity for aromatic compounds have been reported. In 2021, [PERSON] et al. reported the synthesis of graphene oxide (GO)-modified CuInS/ZnS QDs for the sensing of PAHs. The addition of different concentrations of PAHs to the GO-modified QDs has shown enhancement of photoluminescence (PL) intensity. This enhancement was ascribed to the \(\pi\)-\(\pi\) stacking between the chemical sensor and the PAHs [33].
# UWB-Based Real-Time Indoor Positioning Systems: A Comprehensive Review
## 4 Commercial UWB Modules and Chips for IPSs
### Summary of the Commercial UWB Modules and Chips for IPSs  
In this section, we present a summary of the most prominent characteristics of some available commercial chips and units available on the market that can be used in the design and development of real-time indoor positioning systems operating with ultra-wideband technology, as shown in Table 1.
## 5 Application to Platoon Protection  
As traffic and cargo volume increase worldwide, many researchers have studied how to reduce traffic congestion and to carry cargo efficiently through truck platooning. In 2011, California PATH [35] team conducted experiments with three heavy trucks that have only an automated longitudinal control and confirmed the improvement of fuel consumption by about 10% on the average. Energy ITS [36] team performed tests with three automated heavy trucks and one light truck with the gaps of 10 m and 4.7 m at 80 km/h in 2013. Currently, there are numerous others seeking even higher efficiency goals [37]. These project teams conducted their research using vehicle sensors and vehicle-to-vehicle (V2V) communication, and they demonstrated that platooning can improve energy [38] and traffic efficiency [39]. Like this, as platooning is one of the most promising applications of V2X [9], and one of the prominent target for roadside remote attackers when V2X becomes available [5], it is imperative to explore how the proposed scheme can help mitigate attacks against platoons.
## 3 Field Trialed System
### Cyber and Network Security
#### 3.3.1 Access Control and Security Posture Management for the IoT  
We trialed a solution for identity, access and trustworthiness management. The proposed access control service authenticates and verifies IoT devices that request access to services within the network. The widely used OAuth 2.0 identity and access management framework [50] authorizes new users and devices for the information and application services in the farm. In addition to authenticating IoT devices, the solution verifies that devices with trusted execution environments are running the expected, trusted software. To support networked business models in SF, authorizations can be temporary.  
During the trial we verified the feasibility of our extensions to the OAuth 2.0 framework. The extension, which we specified in [51], allows IoT devices to prove their software integrity using device attestation as part of OAuth's delegated authorization protocol. The approach is able to detect and locate compromised devices and malware as well as verify the trustworthiness of devices requesting access to services.  
Figure 7: Standalone private LTE 2.3 base station RTT measurement to router 1.  
performance measurements [51] demonstrated the feasibility of the approach. The latency (during the security handshake phase) depends on the processing capabilities of the IoT platform. Total latency of handshake--made when a device first accesses a service and that contains authentication and attestation phases--was around 11.1 s for the ARM TrustZone-based NuvotonM2351 class micro-controller. The attestation procedure is a relatively rare operation and will not impair the feasibility of sensor applications.
# Coffee-Leaf Diseases and Pests Detection Based on YOLO Models
## 4 Experimental Results and Discussion
### Qualitative Results
Figure 8: The GT of sample 2 and YOLO results from the detection of diseases and pests on coffee leaves. (**a**) GT of sample 2. (**b**) Detection of YOLOv8s. (**c**) Detection of YOLOv9m. (**d**) Detection of YOLOv10l. (**e**) Detection of YOLOv11n. Figure 9: The GT of sample 3 and YOLO results from the detection of diseases and pests on coffee leaves. (**a**) GT of sample 3. (**b**) Detection of YOLOv8s. (**c**) Detection of YOLOv9m. (**d**) Detection of YOLOv10l. (**e**) Detection of YOLOv11n. The qualitative analysis describes the performance of the YOLO models in visually detecting diseases and pests on coffee leaves. In Figures 7-10, it can be seen that the YOLOv8s model showed consistency in the detection behavior of the four diseases, with well-defined bounding boxes and good confidence in the predictions, especially for the miner and rust classes regardless of the size of the location and the region affected. On the other hand, the YOLOv11n model showed difficulties in detecting cercospora and miner, generating predictions with low confidence and omitting some infected regions that were present in the ground truth. It was also observed that YOLOv9m had an intermediate performance, detecting instances of rust, but with low accuracy for the cercospora disease. YOLOv101 was also able to detect most instances of phoma and smaller regions of the rust class. However, the model showed some difficulty in differentiating cercospora from other diseases, as well as failing to detect larger regions of the rust class. In this scenario, the visual results reinforce the importance of a qualitative assessment complementing the quantitative analysis, highlighting the performance of YOLOv8s for detection.