esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Rotating Polarization-MPSK (RP-MPSK) Modulation
#### 2.1.2 RPW Transmission and Reception  
The baseband modulated signals are upconverted to RF carrier \((\omega_{c}=2\pi f_{c})\) of ISM band. The electromagnetic signal is mathematically described as  
\[\mathbf{E}(z;t)=\left[h_{t}(t)\mathbf{a}_{x}+v_{t}(t)\mathbf{a}_{y}\right]\cos( \omega_{c}t-\beta z). \tag{4}\]  
RP-MPSK transmitter is like RP-QPSK transmitter in Figure 1. However, the serial to parallel logic varies with higher order of modulation. A block diagram of the digital implementation of RP-MPSK receiver is shown in Figure 4.  
The signals received on the two elements of dual-polarized antenna are sufficiently degraded due to scattering, multipath regular and irregular reflections:  
\[\begin{split}& r_{h}(t)=h_{t}(t)\sum\limits_{n}a_{n}\cos\varphi_{n }\cos(\omega_{c}t+\theta_{n})+n_{h}\\ & r_{v}(t)=v_{t}(t)\sum\limits_{n}b_{n}\sin\varphi_{n}\cos(\omega _{c}t+\theta_{n})+n_{v}\end{split} \tag{5}\]  
These signals are down-converted to baseband signals \(h_{r}(t)\) and \(v_{r}(t)\), respectively.  
Figure 4: Coherent RP-MPSK Receiver with Equal Gain Combining (EGC).  
Figure 3: Block Diagram of RP-MPSK Transmitter.
## 2 Literature Review
### Data Fusion in Sensor Networks
#### 2.1.1 Definition and Function of Data Fusion  
In 1985, the Joint Directors of Laboratories' Data Fusion Subpanel (later known as the Data Fusion Group) initially proposed the data fusion model. The current model has six levels, ranging from Source Preprocessing/subject Assessment (level 0) to User/Cognitive Refinement (level 5). The model describes the process of correlating and synthesizing data and information from single or multiple sources to complete correct location and identity estimates with a complete and prompt assessment of data and physical states. The process uses continuous estimation and evaluation optimization, and the process adjusts itself to achieve better results.  
Wireless sensor networks are more focused on task completion than care for individual nodes. The network is like a server receiving a request, parsing the query language, informing the network, and returning the results. The focus on purely data-oriented communication is a basic feature of wireless sensor networks. Data processing and fusion from multiple sources is an indispensable part of the network, and brings it in line with the data needed by the user. After fusion, the network can compress data to reduce the amount of information. The main goal of data fusion in sensor networks is reduction of energy consumption, enhanced accuracy, and improved efficiency [15].
# A Survey on Energy-Aware Security Mechanisms for the Internet of Things
## 3 Security Protections in IoT Environments
### Defense at the Network Level
#### 3.4.4 Secure WiFi Standard (WPA3)  
Adopting the latest WiFi security standards, such as WPA3, helps in bolstering the security of WiFi networks. WPA3 introduces the simultaneous authentication of equals (SAE) algorithm, which replaces the pre-shared key (PSK) authentication used in WPA2 [66]. SAE enhances the password security and improves resistance to brute-force breaking attacks, especially against dictionary attacks. In addition, WPA3 utilizes a higher level of encryption and provides a 192-bit encryption key, whereas WPA2 only supports a 128-bit encryption key. WPA3 is suitable for the government, financial, and medical industries that require high data security. Additionally, WPA3 provides perfect forward secrecy, ensuring that even if a long-term key is compromised, previous communication data remain secure: an attacker cannot access past communications by decrypting captured packets.
###### Abstract  
The aim of this study was to evaluate the perception of periodontal pain in patients treated with either fixed multibrackets or removable alignment systems with a monthly follow-up over a period of twelve months. Materials and Methods: This longitudinal clinical study comprised a sample of 140 patients (72 women; 68 men) divided into two groups of 70 patients each. the bracket group (BG) with conventional fixed brackets using the MBT technique with a 0.022\" slot and the Invision group (IG) with aligners (Invisalign). The visual analog scale (VAS) was used to quantify patient-reported pain. Pain analysis was conducted monthly at 4 (T1), 8 (T2), and 24 h (T3) post-follow-up as well as at 2 (T4), 3 (T5), 4 (T6), 5 (T7), 6 (T8), and 7 days (T9) post-follow-up during the first twelve months after starting orthodontic treatment. Results: Statistically significant differences (\(p<0.05\)) were observed between both study groups in the mean pain scores on the visual analog scale (VAS) during the twelve-month follow-up period, except for during the eighth month of treatment. In the first month, the group with conventional brackets reported higher pain scores. From the second month onwards, we observed that patients with aligners described a higher level of pain compared to the group of patients with conventional brackets. In both experimental groups, though at different evaluation periods, we found that the peak of maximum pain occurred between 24 and 48 h (T3-T4) after monthly follow-up appointments; from this point, the pain decreased until reaching minimum values from the fifth day onwards (T7). Conclusions: In the first month of treatment, the patients with conventional fixed multibrackets reported the highest levels of pain compared to those with removable aligners. From the second month on, this trend changed. The patients with removable aligners reported the highest levels of pain. Therefore, the orthodontic system used influenced the perception of pain in patients.  
p pain; orthodontic; oral health; aligners; brackets; visual analog scale; tooth movement
## 4 Results and Discussion
### 4.2. ODF Results according to Viscosity Conditions  
Based on the previously set 3D printer parameter conditions, the results of the ODF extrusion were analyzed according to the viscosity ranges of the sample solution. The evaluation criteria for the results were whether the discharge shape was distorted or tailing occurred. The ODF results are shown in Table 3. For high viscosity (100,000\(\sim\)200,000 cps), the high flow rate inside the nozzle leads to internal backflow phenomena. Additionally, empty spaces are formed within the nozzle, resulting in inconsistent extrusion speed. While one side of the nozzle exhibited smooth output, the shape on the other side was distorted. For medium viscosity (40,000\(\sim\)100,000 cps), the excessive solution was extruded, leading to overall distortion of the shape. At the optimal viscosity range (25,000\(\sim\)35,000 cps), which showed the most stable output in the simulation tests, precise dimensions and shapes were observed during extrusion. However, due to the omission of the retraction function and path optimization process, there were extrusion errors at the starting point and trailing effects at the endpoint.
## 4 Numerical Results
Although the number of RSUs and the amount of harvested energy are crucial parameters to the system performance, from Figure 6, power allocation factors \(a_{1},a_{2}\) significantly change the outage performance. As in the previous figures, \(D_{2}\) shows better performance compared with that of \(D_{1}\); however, increasing \(a_{1}\) contributes to contrasting trends. For example, the outage performance of \(D_{1}\) is better than that of \(D_{2}\) as \(a_{1}>0.6\) and \(R_{1}=R_{2}=0.5\); the outage performance of \(D_{1}\) is better than that of \(D_{2}\) as \(a_{1}>0.83\) and \(R_{1}=R_{2}=1\).
## 3 Proposed C-HARQ Protocol Design
### Packet Generation  
The system consists of mainly three types of packets: data packets (main message packets), FEC packets and signalling packets. The message packet and FEC packets are generated using a convolution encoder with puncturing enabled. The punctured mother code at the output of the encoder forms the main message packet while the punctured bits form the FEC packets. The convolution encoder is configured in such a way that the punctured mother code produced is exactly the same as the original data that was fed to the input of the encoder. Thus, the main message packet contains only data bits and is, hereafter, referred to simply as the data packet. This allows the source to be exempted from the burden of going through the encoding process to generate the main message packet which is actually the data part only. The other punctured outputs of the encoder form the FEC packets.  
The convolution encoder thus used is a _systematic convolution encoder_[16]; a code is systematic if the input data bits are embedded in the output mother code. Figure 2 explains the coding and the puncturing process with an example. At first a 10-bit data is encoded into a 20-bit mother code (code rate = 1/2) with data bits (highlighted bits) and FEC bits occupying the odd and even positions, respectively. Next, the mother code is punctured using some predefined puncturing patterns to get multiple packets at the output. By using the pattern [1010101010], the redundant FEC bits are deleted from mother code (positions with \"_-_\") to get the payload of the data packet _i.e._, _Pac_-0. Thus, _Pac_-0 contains only the data bits and therefore, from hereafter, refers to the original data packet in the system. Similarly, utilising the other puncturing patterns, FEC bits are recovered from the mother code to be the payload of the FEC packets; represented by _Pac_-1, _Pac_-2..._Pac_-_N\({}_{nn}\)_. In the above example, _N\({}_{nn}\)_ is set to 2.  
To these raw packets, a four byte header and a two byte trailer are added to form the final link layer packets, shown in Figure 3. The header field consists of packet ID (1 Byte), source ID (1 Byte), destination ID (1 Byte), and packet sequence number (1 Byte). The trailer is composed of 16-bit Cyclic Redundancy Check (CRC) to facilitate error detection.
## 2 Materials and Methods
### Statistical and Bioinformatics Analysis  
The QIIME2 pipeline (version 2020.11) was utilized for sequencing data processing [22]. Demultiplexed reads were downloaded from the Illumina BaseSpace website and uploaded into Qime2-2020.11 using Casava 1.8 paired-end demultiplexed format (via Qime tools import). Demultiplexed reads were denoised and filtered in DADA2 via q2-dada2 [23]. Using mafft, the observational taxonomic units (OTUs) were aligned, and a rooted phylogenetic tree was generated with fastree2 via q2-phylogeny [24]. Punitive OTUs were identified against SILVA (Silva 138 99% OTUs full-length sequences) [3; 10; 18] using the sk-learn Bayesian algorithm (via q2-feature-classifier) [25; 26]).  
Alpha and Beta diversity were analyzed using the core metrics results in QIIME2. Alpha diversity was determined using the Shannon diversity index. Observed OTUs, Pielou's Evenness, and Faith's phylogenetic diversity were used, which included the Kruskal-Wallis tests for pairwise differences [27]. Beta diversity metrics were analyzed with qualitative and quantitative indices, Bray-Curtis, Jaccard, and Unweighted and Weighted UniFrac Distance Matrix [28; 29]. PERMANOVA, a multivariate form of ANOVA with permutations to reduce bias, was used to determine if the distribution and abundances among beta diversity metrics were different. Interactions between the organ site and treatment were identified using ANOVA via q2-longitudinal [25; 26] and ADONIS [30] for alpha and beta diversity metrics. Pairwise differences for all diversity metrics (Kruskal and PERMANOVA) were considered significant when \(p\leq 0.05\) and Q \(\leq 0.05\). The Q values were used as they include the False Discovery Rate, which accounts for the occurrence of type I errors, rejecting a true null hypothesis (false positive) when conducting multiple comparisons. Lastly, ANCOM (analysis of the composition of microbiomes) was conducted according to [PERSON] et al. (2015) [18] to determine differentially abundant taxa.
# Bit Rate Adaptation Using Linear Quadratic Optimization for Mobile Video Streaming
## 4 Approach
### Extending LQ for Improving QoE in Mobile Streaming
#### 4.2.1 Adjustment Factor in the Error Term \(e_{k}\)  
To prevent frequent bit rate switching in a short term, we redefine the error term \(e_{k}\) as:  
\[e_{k} = B_{k}-q_{0}-\sigma\times q_{0}(r_{k-2}-r_{k-1})\]  
where \(r_{k}\) is the index of bit rate selected for \(k\)th chunk (increasing order according to bit rates), e.g., with six available bit rates the index of the minimum bit rate is one and the index of the maximum is six.  
The intuition behind the adjustment factor is that a negative error drives LQ to select a lower bit rate and a positive error does LQ to select a higher bit rate. By switching to a lower bit rate, the error with the next feedback decreases (going to a positive error), thus, the client can shortly increase the bit rate, resulting in short-term bit rate fluctuation. It also occurs when LQ selects a higher bit rate. To mitigate the short-term fluctuations, the adjustment factor makes increases in the error in the negative direction than the actual error when LQE previously switches to a lower bit rate. Similarly, if the LQE observes a bit rate increase, the error increases in the positive direction, allowing LQE to continue with the selected higher bit rate for a longer time.
## 5 Understand
### _Documentation and Outputs_
#### 5.2.1 Applicative Example: The Analyze Phase in the Gwangmyeong Project  
A, B. _Data Organization; Data Analysis and Synthesis: Research Findings_ In the _Analyze_ phase, the research group analyzed the information collected during the _Inquire_ phase once the data were appropriately organized. Although not all analysis outcomes can be detailed here, some of the main findings related to the research questions are worth highlighting.  
1. Context Definition: According to the team in charge of the urban plan design [53], Gwangmyeong will feature roads with cross-sections not exceeding 20 m, unlike most modern Korean districts where streets can be up to 45 m wide [60]. These roads will be intersected by tram railways forming two types of rings: medium- and low-speed rings (Figure 4). New-model smart terms will operate on these rings for passenger transport, with some carriages dedicated to other functions (e.g., freight transport and waste disposal [54]). The remodeled terms included in this study will operate on the medium-speed ring. The rail network will conform to the world standard track gauge of 1435 mm [61].
2. Context and Project Reception: The implementation of trams in Korea aligns with current trends and sustainability goals. Several Korean cities are actively integrating tramways into their transportation networks and receiving positivepublic feedback in this respect [62]. Trams also have historical significance in Korea, with Seoul operating a tram system from 1899 to 1968 [63].
* Case Study Identification: ATMosfera in Milan was deemed particularly relevant to the project for a number of reasons. Notably, its wheelset, measuring 1445 mm [64], is compatible with the world standard track gauge set for Gwangmyeong, being only 1 cm wider but much closer than other global gauges, which range from 610 mm (India) to 2134 mm (the United Kingdom) [61]. Moreover, the Milanese vehicle is notably agile due to its compact size and space optimization, and can accommodate up to 24 customers. This is suitable for Gwangmyeong, where trams share relatively narrow roads with private vehicles.
* Case Study Adaptability: Adapting international examples such as ATMosfera to the Korean context was found to be feasible. The goal was to ensure that the spaces and functions of these trams were aligned with how Koreans use and experience them in everyday contexts (e.g., restaurants, offices). The research highlighted that Korean customs related to public activities, such as eating or meeting, are now closely aligned with global habits. Additionally, adopting non-domestic styles often makes these spaces appear \"exotic\" and appealing to Korean customers [65; 66].
## 2 Analysis and Literature Review of Clearance in Port Channels and Basins
### Steps of Research Methodology  
The following steps of research methodology were used to conduct the research (Figure 3). After conducting the literature review, the mathematical model was developed.  
Based on the presented methodology, theoretical calculations of possibilities for ships sailing in port channels and basins, energy consumption and emissions created by ship were performed. The variation of hull resistance to longitudinal movement with clearance, i.e., the ratio _T/H_ (draught to depth), was used to estimate the ship's sailing speed in ports [1; 5]. For the assessment of the ship's controllability, the methods of calculation of the ship's circulation elements and trajectory at low depths were used [3; 8; 27]. The method of calculating the ship's circulation trajectory in shallow depth was applied as given in sources [4; 5]. The method is based on the calculation of the basic ship movement parameters (ship speed, ship angular velocity and ship drift angle) and the ship's trajectory in the case of low clearance, which often occurs in port navigation channels and basins. Estimation of the ship's sailing trajectory in the presence of small clearances is necessary when navigating port approach and internal navigation channels so that the ship can safely pass through channel bends. Due to the variation of the ship's draft and the power of the main engine(s) when sailing in shallow waters (port navigation channels) and maintaining the set speed, at low depths (clearance), additional resistance forces of the ship hull are formed which are related to the change of the added water mass [4; 5].  
For the calculation of the ship's energy consumption, fuel consumption was calculated as a function of the engine power at a given speed, and for the assessment of emissions, the parameters of the ship's fuel consumption, engine power and operating time were used [15; 38]. For this calculation, the maximal distribution method was used utilizing data achieved by conducting experiments on simulators and real ships [39]. The maximal distribution method could be applied in case at least 5 measurements were carried out.  
In order to verify theoretical calculations and practical application of the presented methodology, experiments were performed with the assistance of a simulator and on real ships. Simulations were carried out using the full mission simulator \"SimFlex Navigator\" (Force Technology product) [40], which analyzed similar maneuvers as the real ships, considering the set forces acting on ships sailing in port channels and ships turning in  
Figure 3: The steps of research methodology.  
turning basins. Experiments performed on real ships covered two port areas with specific navigational conditions (port approach and internal navigational channels).  
Then, the results were analyzed, discussions initiated, conclusions were drawn and suggestions for future research were outlined.
# Optimizing Electric Vehicle Routing Efficiency Using K-Means Clustering and Genetic Algorithms
## 6 Conclusions  
The strategic selection of charging stations plays a crucial role in optimizing the EV's route by minimizing travel time and energy consumption. By carefully choosing stations based on real-time data and predictive modeling, the algorithm can ensure that the EV maintains optimal battery levels while avoiding unnecessary detours. This selection process not only enhances the efficiency of the route but also contributes to a more sustainable and practical solution for electric vehicle navigation.  
This study highlights the critical role of genetic algorithm parameters in determining efficiency, particularly as problem complexity increases. While simpler scenarios with fewer charging stations revealed minimal differences between methods, the impact of these parameters became significantly more pronounced in complex cases. Approaches incorporating tournament selection, variable crossover, and variable mutation demonstrated superior performance, especially in managing higher levels of complexity. The strategy of preserving the best route for future segments proved highly effective in complex scenarios, though its impact was less consistent in simpler cases.  
In conclusion, the integration of a genetic algorithm with dynamic route reassessment and queuing time simulation offered a robust and efficient framework for optimizing EV routes. This approach successfully balanced exploration and exploitation, adapting effectively to varying levels of complexity and providing valuable insights for real-world EV route optimization challenges.
## 3 Results and Discussion
### Thermosonication Extraction Yields  
Table 1 presents the impacts of the thermosonication process conditions on the global extraction yield of the fennel extracts. The nominal power and working temperature significantly affected the global extraction yield (\(p\)-value < 0.001). The extraction yield varied from 3.2 \(\pm\) 0.2 to 5.8 \(\pm\) 0.1 g dried extract/100 g ground fennel.  
The global extraction yield increased significantly when the temperature rose from 40 to 60 \({}^{\circ}\)C, except at 300 W and 400 W. The increase in temperature may favor the diffusion and solubility of the phytochemical compounds contained in the plant material. It can even favor the extraction of impurities. Thus, the increase in thermal energy contributes to the increase in extraction yield [8]. The nominal power rise from 100 W to 400 W also increased the extraction yield. At the nominal powers of 300 W and 400 W, the mechanical and thermal energies applied to the samples were intensified. The working temperature in these powers did not influence the extraction yield. Thus, the contribution of acoustic energy is greater for the extraction of solids by thermosonication than by external heat at high powers.  
According to Figure 2, the global yield results were consistent with the respective fennel samples' visual appearance. Figure 2 shows the visual appearance of the fennel extracts right after the thermosonication-assisted extraction. The extracts produced with higher nominal powers of 300 W and 400 W presented a darker color. In addition, the working temperature increase from 40 to 60 \({}^{\circ}\)C produced darker extracts at 100 W and 200 W. This extract's darker color may be related to the extraction of more compounds (high global yields) besides its thermal degradation.  
On the other hand, fennel contains proteins and carbohydrates [21; 22]. Acoustic cavitation may have promoted the extraction of carbohydrates and proteins from plant material. Thus, thermosonication-assisted extraction may have promoted the Maillard reaction due to high temperatures, also contributing to the dark color of the extracts.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Nominal Power (W)** & **Temperature (\({}^{\circ}\)C)** & **Global Yield (g/100 g) 1** \\ \hline \multirow{3}{*}{100} & 40 & 3.2 \(\pm\) 0.2 \\ \cline{2-3}  & 50 & 3.7 \(\pm\) 0.1 \\ \cline{2-3}  & 60 & 4.2 \(\pm\) 0.1 \\ \hline \multirow{3}{*}{200} & 40 & 3.5 \(\pm\) 0.2 \\ \cline{2-3}  & 50 & 3.7 \(\pm\) 0.2 \\ \cline{2-3}  & 60 & 4.8 \(\pm\) 0.1 \\ \hline \multirow{3}{*}{300} & 40 & 5.3 \(\pm\) 0.1 \\ \cline{2-3}  & 50 & 5.5 \(\pm\) 0.1 \\ \cline{2-3}  & 60 & 5.5 \(\pm\) 0.1 \\ \hline \multirow{3}{*}{400} & 40 & 5.85 \(\pm\) 0.01 \\ \cline{2-3}  & 50 & 5.8 \(\pm\) 0.1 \\ \cline{2-3}  & 60 & 5.8 \(\pm\) 0.1 \\ \hline \end{tabular} \({}^{1}\) Global yield: g dried extract/100 g ground fennel.  
\end{table}
Table 1: Thermosonication extraction yields.