esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Molecular Identification and Phylogenetic Analysis  
For the determination of the taxonomic classification of the new isolate within the Chlorococcaceae, the family to which the genus _Chlorococcum_ belongs, molecular phylogenetic analysis was carried out. Sequences of 185 rRNA genes from several Chlorococcaceae microalgae were analyzed using Bayesian (BI) and Maximum Likelihood (ML) inference. _Chlorella vulgaris_ 18S rRNA gene was used as an outgroup. BI and ML trees topology (Figure 3) indicates that the strain isolated from a pond located at Allmicroalgae industrial facilities (accession number: MT026583) belongs to a taxonomic unit sister to _C. minutum/C. aquaticum_, with an almost maximum posterior probability (0.99) and a 93% ML bootstrap value. Interestingly, _C. ellipsoidatum_ appears to be an outgroup, branching off these taxa with maximum support. Although this isolate does present similarities to _C. infusionum_, the holotype of the genus, concerning its reproduction, phylogenetic analysis strongly suggests that belongs to the Stephanosphaerinia macrolade, rather than to the Moewusinia, the macrolade of _C. infusionum_ (Figure 3) [31]. Moreover, upon submitting our sequence to GenBank, the authors found that this  
Figure 2: Microscopic images of _Chlorococcum amblystonatis_ life stages using the differential interference contrast (DIC); (**a**) vegetative cell; (**b**) zoospore; (**c**) group of cells with indefinite form; (**d**) zoosporagium; (**e**) and (**f**) burst of zoosporagium membrane and realizing of zoospores. n = nucleus, p = pyrenoid, s = stigma, z = zoospore, zp = zoosporagium. Scale bar (**a**) and (**b**) = 2 μm, (**c**) to (**f**) = 5 μm.  
sequence is 100% identical to an _Oophila amblystomatis_ (Kingston isolate, Oophila clade A) sequence with the accession number KY091671 [32] and to other sequences that have not been classified down to the species level. This finding is quite interesting, as the phylogenetic data here presented strongly indicates that _O. amblystomatis_ does belong to the genus _Chlorococcum_. This species is often isolated as a symbiont in eggs of several amphibian species, but its proper taxonomy has remained uncertain [32]. Recently, it has been reported that this species can also occur as free-living microalgae [33]. Taken together, it is here proposed to rename _O. amblystomatis_ as _Chlorococcum amblystomatis_. This proposal is supported not only by the results of Figure 3, but also by the latest attempt at defining the taxonomy of this species [32]. Indeed, these authors hint that that sequences of the _Oophila_ clade A symbionts cluster with those of _Chlorococcum_, unlike \"Oophila\" clade B isolates, which appear to be closely related to taxa classified as _Chlamydomonas_[32].
## 4 Analysis
### Experiment Result
For example, a 32 GB SD card can store pre-computed secrets that are only enough for around 1600 AlexNet inferences and 250 ResNet-50 inferences. After that, the SD card needs to be replaced and re-initialized, which could disturb the continuous operation of the IoT system in real-world applications such as drone-based systems. Our design eliminates such a limitation because of the constant storage overheads. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Benchmark** & **Methods** & **End-to-End Time** & **Communication** \\ \hline \multirow{3}{*}{SqueezeNet} & [17]-SCI\({}_{IE}\) & 59.2 & 5.27 \\  & [17]-SCI\({}_{OT}\) & 44.3 & 26.07 \\  & Ours & 9.31 & 0.08 \\ \hline \multirow{3}{*}{ResNet-50} & [17]-SCI\({}_{IE}\) & 545.8 & 32.43 \\  & [17]-SCI\({}_{OT}\) & 619.4 & 370.84 \\ \cline{1-1}  & Ours & 25.19 & 0.09 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance comparison with CrypTFlow2 [17] for End-to-End time and communication. Time is measured in seconds and communication in GB.
# Casting Process Improvement by the Application of Artificial Intelligence
## 3 Literature Review
### Improvement of the Continuous Casting Process
On this basis, the relevant secondary dendritic arm spacing was calculated. The proposed neural network model showed significantly smaller absolute and relative errors compared to the traditional methods [47]. [PERSON] et al. investigated the effectiveness of a genetic algorithm-based backpropagation (GABP) neural network model and its application to the breakout prediction in the continuous casting process [48]. [PERSON] et al. presented an adaptive control system for continuous steel casting based on artificial neural networks (ANNs) and fuzzy logic (FL). The neural system (consisting of two distinct neural networks) for the estimation of the crack detection probability was designed, implemented, tested, and integrated into an adaptive control system, which was based on fuzzy logic [49]. [PERSON] et al., in their study, found a fuzzy method for the estimation of the heat flux distribution at the metal-mold interface in slab continuous casting. The deviations between the calculated and measured temperatures acquired with the thermocouples buried in the mold were taken as the input parameters of the fuzzy system [50]. [PERSON] et al. showcased a combined approach for the optimization of the cooling strategy and solidification process in continuous casting. The mentioned approach was based on a common application of the particle swarm optimization (PSO) algorithm, a mathematical heat transfer model and the experimental temperature to determine the heat transfer coefficient. The precise assessment of the heat transfer coefficient of the secondary cooling zone is of the utmost significance because secondary cooling control is the key factor for stabilizing and enhancing the slab quality in continuous casting [51]. [PERSON] et al. presented the application of fuzzy logic and a PSO algorithm in the design of fuzzy PID controller for the control of the mold level in the continuous casting production process. PSO algorithms are used for the optimization of fuzzy controller parameters. The developed methodology was confirmed by numerous simulation studies, and was finally implemented in real industrial conditions [52]. [PERSON] et al., in their study, considered that due to the high-temperature characteristics of SCC (steelmaking-continuous casting) production, the temperature drop deriving from the non-processing process could directly affect energy losses, and could lead to the increase of the energy consumption of each procedure, which greatly influences the overall energy consumption. Following the analyzed problem, they presented the application of the multi-objective hybrid genetic algorithm to minimize the penalty of due date deviation and the extra energy consumption measured by the temperature drop [53]. Table 3 presents a brief overview of the analyzed studies of continuous casting process improvement.
# Efficient Approximation for Restricted Biclique Cover Problems
## 3 Model I: \((f,k)\)-Biclique Cover
### \((1,k)\)-Biclique Cover  
First, we observe that the \((1,k)\)-biclique problem can be trivially solved in polynomial time.  
**Lemma 1**.: _A bipartite graph \(G=(L,R,E)\) can be covered with a \((1,k)\)-biclique cover iff it has \(\leq k\) connected components and each of them is a biclique._  
Proof.: Suppose each connected component of \(G\) is a biclique. It is easy to see that then all edges can be covered by using each connected component as the biclique in the cover. Also, each node is covered by a single biclique.  
Then, assume \(G\) is a yes-instance. Let \(B_{1},\ldots B_{t}\), be the set of bicliques covering all the edges of \(G\), in the solution. Notice that the bicliques define a partition of the nodes in \(G\) as each node can belong to a single biclique. We show that there is no edge that connects two nodes in two distinct bicliques, and hence the graph consists of \(t\leq k\) connected components, each a complete subgraph. Suppose to get a contradiction that \((u,v)\in E\) is an edge connecting the nodes in \(B_{i},B_{j}\) for \(i\
eq j\). Since \((u,v)\) does not belong to any of the two bicliques, the edge must be covered by a third biclique. However, all edges of \(u\) are covered by a single biclique.  
This condition can be easily checked in polynomial time.
# Improving Spatial Reuse of Wireless LAN Uplink Using BSS Color and Proximity Information
## 4 Performance Evaluation
### Simulation Results
#### 4.2.4 Varying Margin  
In PSC-UL as well as other methods like PSR and Dual-CST, a margin parameter is used to account for estimation errors. In the fourth experiment, we have varied the margin parameter to study its effect on protocol performance. Legacy and OBSS/PD do not use the margin parameter, so their values are constant regardless of the parameter. The margin is varied from 0 dB to 10 dB. The results are in Figure 12.  
In Figure 12a, we can observe that the total throughput is reduced as we increase the margin. Increasing the margin means that the nodes transmit more conservatively, and they take the concurrent transmission opportunity only when the expected SNR at the receiver is well above the required value. With the same margin value, PSR achieves higher throughput compared to PSC-UL, which was also reflected in other experiments. However, here we can see that the peak values for the total throughput of PSR and PSC-UL are similar, achieved with different margin values. The fairness measures are improved when the margin value increases because conservative transmissions reduce collisions from hidden terminals, which is harmful for fairness. For PSR, however, the fairness measures are still much lower than other methods even with high margin values as shown in Figure 12b-e.  
Figure 12: Cont.  
In summary, PSC-UL can improve the network performance by increasing parallel transmissions. While other methods like OBSS/PD and PSR can also increase spatial reuse, these methods do not fully consider if the concurrent transmissions will be successfully received at their receivers. Therefore, lots of collisions occur which can lead to throughput degradation and unfairness. In PSC-UL, a node decides to transmit concurrently after estimating SNR at the receiver of both the ongoing transmission and the potential concurrent transmission. To estimate SNR at the receivers, nodes maintain neighbor tables that contain RSSI of APs, and include proximity information in the preamble. The experiment results show that the proposed method can significantly improve throughput over the legacy method, and shows better performance characteristics compared to other spatial reuse methods.
# A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms
## 3 Proposed Methodology
### Fingerprint Image Preprocessing
#### 3.2.7 Gabor Filtering  
Once the ridge frequency and orientation information are determined, the even-symmetric Gabor filter is generated utilizing these parameters. The two-dimensional Gabor filter consists of a sinusoidal plane wave, modified by a Gaussian envelope of a particular orientation and frequency. Gabor filters have selective frequency and selective orientation properties. These properties allow these filters to be set to provide maximum response to ridges at a particular frequency and orientation in the image. Thus, a correctly adjusted Gabor filter can be utilized to maintain the ridge structures efficiently, while reducing noise. The Gabor even-symmetric filter is the real part of the Gabor function, produced by a cosine wave modified by a Gaussian envelope. [PERSON]'s even-symmetric filter in the special domain has the following general form:  
\[G(x,y,\theta,f)=\exp\bigg{\{}-\frac{1}{2}\bigg{[}\frac{x_{\theta}^{2}}{\delta_ {x}^{2}}+\frac{y_{\theta}^{2}}{\delta_{y}^{2}}\bigg{]}\bigg{\}}\cos(2\pi fx_{ \theta}) \tag{4}\]  
The coordinates \((x_{\theta},y_{\theta})\) are defined by  
\[x_{\theta}=x\cos\theta+y\sin\theta,\,y_{\theta}=-x\sin\theta+y\cos\theta \tag{5}\]  
where \(\theta\) is the Gabor filter orientation, f is the cosine (sinusoidal plane) wave frequency, \(\delta_{x}\) and \(\delta_{y}\) are the Gaussian envelope space constants (standard deviations) along the \(x\) and \(y\) axes, respectively, and \(x_{\theta}\) and \(y_{\theta}\) are the \(x\) and \(y\) axes of the filter coordinate frame, respectively. Gabor filter is applied to the image by convolving it with the filter. The pixel convolution \(i,j\) in the image needs the corresponding orientation value \(O(i,j)\) and ridge frequency \(F(i,j)\) of that pixel. Thus, the application of the Gabor filter G to obtain an enhanced image E is carried out as follows [19],  
\[E(i,j)=\sum\limits_{u=\frac{-\pi u}{2}}^{\frac{\pi u}{2}}\sum\limits_{v=\frac{ -\pi v}{2}}^{\frac{\pi v}{2}}G(u,v;O(i,j),F(i,j))N(i-u,j-v) \tag{6}\]  
where \(O\), \(F\), and \(N\) denote the orientation, frequency, and normalized images, respectively. The width and height of the Gabor filter mask are \(w_{x}\) and \(w_{y}\), respectively.
# Systematic Review on Human Skin-Compatible Wearable Photoplethysmography Sensors
## 4 Human Skin-Compatible PPG Sensors
### Silicon Photodiodes
Stable extraction with minimized distortion of SpO2 values was observed during movement, which is an important advantage of device miniaturization compared to the present commercial oximeter devices, as shown in Figure 5c. The long-term operation for 3 months without the risk of irritation, discomfort, and device performance degradation was effective, allowing for practical application in clinical treatment and human skin-compatible healthcare platforms. Although most Si-based PPG sensors with innovative functionalities proved to operate properly on human skin, they still inadequately conform to the skin surface owing to the intrinsic brittleness of light-responsive Si materials and the rigidity of the device structure. [PERSON] et al. proposed a thinner device architecture including LEDs and PDs [32]. The thickness of the active device components (LEDs and PD) is adjusted below 20 \(\upmu\)m using the nanodiamond thinning process. Based on the stamp-assisted transfer printing technique, LEDs and PDs are transferred onto Au interconnects. Finally, the interconnected devices are encapsulated in 500 \(\upmu\)m-thick polydimethylsiloxane (PDMS) and polyurethane (PU) film (Figure 6a). Under mechanical deformation, it is demonstrated that the external elastomers absorb all stresses, and strains are barely applied to the active device parts, resulting in stable device operation under a high tensile strain of 35%. Owing to their low flexural rigidity, epidermal optoelectronic devices were positioned on the wrist (Figure 6b) and forefinger (Figure 6c) and detected precise and accurate vital parameters during movement (Figure 6d). While stretching, a disturbing error occurs in the allowable range of 0.1% of the SpO2 level. The all-inclusive device achieved by the thinning process is universal for various types of inorganic semiconducting materials, opening possibilities to fabricate skin-like functional electronic patches that can be directly mounted on human skin. Figure 5: (**a**) Illustration of the various constituent layers of the NFC-enabled pulse oximeter device. (**b**) Photograph image of measurement setup to evaluate SpO2 level from the fingernail (up). It is possible in application of a device with a computer mouse functioning as a wireless interface. Photograph image of measurement setup to evaluate SpO2 level from the earlobe (down). (**c**) Calculated SpO2 during rest and movement on the device. The device quantified the accelerometer’s signal according to the movement in the X(red), Y(blue), and Z(green) axes. Adapted with permission from [31], [PERSON], 2016.
## Materials and Methods  
### Measurement Scenario of 5G DL  
The 5G Base Station (5G-BS) and the fixed-satellite services Earth station (FSS-ES) are using the same frequency, which is the cause of the interference between two channels. The MEASAT-3A satellite with vertical polarisation is used. Co-channel interference, the design of frequency interference, and saturation to satellite ESs are the main problems with the 5G-BS. The total interfering power, location, elevation angle, and other variables of 5G-BS play a key role in the global performance and link availability. This section explains and describes the method for analysing the interference. Part of the 5G-BS signal power component enters the satellite earth frequency band between 3.6 and 4.2 GHz generating interference. A measurement campaign starting on 12 August 2020, at MAEPS Serdang, Universiti Putra Malaysia (UPM), Selangor, Malaysia, was conducted, and data were obtained between 12 and 16 August at the locations to measure the interference caused by a 5G-BS. The experiments were tested based on the 5G-BS parameters, and higher rejection was observed on the first carrier rather than the second carrier of 5G-BS transmissions. Carrier 1 is 3.4-3.5 GHz, and Carrier 2 is 3.5-3.6 GHz. In addition, in the next section, we present the 5G-BS interference model.
## 2 Methods
### Rover IFCB Correction Method
#### 2.2.1 Correcting the Large Part  
Given a receiver to be calibrated, we can select the nearest reference station to ensure the largest number of commonly observed satellites. We can then write the between-station-differenced NL code observation and the IF code and carrier phase observation equations as  
\[\begin{split}\Delta P_{n,i}^{k}=\Delta\rho_{i}^{k}+\frac{\Delta \mu_{i}^{k}}{f_{1/2}^{k}}+\Delta F_{n,i}^{k}+\Delta e_{n,i}^{k}\\ \Delta P_{c,i}^{k}=\Delta\rho_{i}^{k}+\Delta F_{c,i}^{k}+\Delta e _{c,i}^{k}\\ \Delta L_{c,i}^{k}=\Delta\rho_{i}^{k}+\Delta N_{c,i}^{k}+\Delta e _{c,i}^{k}\end{split}, \tag{8}\]  
where \(\Delta\) represents the single difference between stations. \(\Delta F_{n,i}^{k}\) and \(\Delta F_{c,i}^{k}\) denote the NL and IF IFCB difference with respect to the reference station. In the first and second equations of (8), the IFCB parameters strongly depend on the corresponding receiver clocks, so we add a zero-mean constraint on all NL and IF IFCB estimates.  
We obtain the NL and IF IFCB corrections by daily static baseline processing using (8). Since we have used homogeneous receivers as the reference stations, one can select three or more surrounding reference stations to estimate the IFCB and use average values. With the NL and IF IFCB estimates, we can attain the P1 and P2 IFCB corrections:  
\[\begin{split}\Delta F_{1,i}^{k}&=\frac{f_{1}^{k}(f_ {1}^{k}+f_{2}^{k})\Delta F_{n,i}^{k}+(f_{1}^{k2}-f_{2}^{k2})\Delta F_{c,i}^{k} }{f_{1}^{k}+f_{1}^{k2}}\\ \Delta F_{2,i}^{k}&=\frac{f_{1}^{k}(f_{1}^{k}+f_{2 }^{k})\Delta F_{n,i}^{k}-(f_{1}^{k2}-f_{2}^{k2})\Delta F_{c,i}^{k}}{f_{1}^{k} +f_{2}^{k2}}\end{split} \tag{9}\]  
Because of the residual ionosphere delays that have not been eliminated, the estimated IFCB correction is biased and it is not possible to fix the WL ambiguities. We thus need to further refine the IFCB estimates.
# Secure and Efficient Authentication Scheme in IoT Environments
###### Abstract  
Optimization of resource consumption and decreasing the response time of authentication requests is an immense urgent requirement for supporting the scalability of resources in IoT environments. The existing research attempts to design lightweight authentication protocols to address these issues. However, the schemes proposed in the literature are lacking in the creation of a lightweight (i.e., low computing, communication, and storage cost) and secure architecture. IoT devices in existing approaches consume high electricity and computing power, despite the fact that IoT devices have limited power and computing capabilities. Furthermore, the existing approaches lead to an increase in the burden on storage memory and also create heavy traffic on a communication channel, increasing the response time of device authentication requests. To overcome these limitations, we propose a novel lightweight and secure architecture that uses crypto-modules, which optimize the usage of one-way hash functions, elliptic-curve cryptography, and an exclusive-or operation. We demonstrate the proposed scheme's security strength using informal security analysis and verified it by considering the widely used automated validation of internet security protocol application (AVISPA) and the ProVerif tool. The result shows that the proposed scheme is effective against active and passive security attacks and satisfies secure design. Moreover, we calculate the proposed scheme's working cost by implementing it using a widely accepted standard pairing-based cryptography (PBC) library on embedded devices. The implementation proves that the proposed scheme is lightweight and reduces computation time by 0.933 ms, communication cost by 1408 bits, and storage cost by 384 bits, and removes the existing gaps.  
authentication scheme; elliptic-curve cryptography (ECC); Internet of Things; cloud; pairing-based cryptography (PBC) +
Footnote †: journal: Applied Sciences
# Signal to Noise Ratio of a Coded Slit Hyperspectral Sensor
## 3 Results and Data Analysis
### Implication of the Present Results in the Context of Compressive Sensing Schemes  
It is intuitively interesting to consider how the above results could be generalised for using the multiplexed architecture but with an incomplete measurement of the signal and use of compressive sensing to recover the signal. It is known that the integrity of signal recovery under compressive sensing can be improved with increasing the number of measurements in general, and this has been validated for hyperspectral data [13] experimentally. Furthermore, any prior information, such as the expectations about the sparsity of signal, is expected to enhance the quality of reconstruction beyond what has been presented here. This principle can be exploited to improve the quality of a reconstructed measurement, for example by de-noising the reconstructed signal [22]. Improvements based on use of prior information can be achieved even when considering a non-compressive measurement system, such as that considered in this paper. Compressive sensing is often seen as a way to trade-off data fidelity for higher frame rate, such as in the case for producing a spectral video. However, it is possible that compressive sensing techniques may be able to provide higher fidelity measurements than the results presented here under certain conditions.
# Online Determination of Boron Isotope Ratio in Boron Trifluoride by Infrared Spectroscopy
###### Abstract  
Enriched boron-10 and its related compounds have great application prospects, especially in the nuclear industry. The chemical exchange rectification method is one of the most important ways to separate the \({}^{10}\)B and \({}^{11}\)B isotope. However, a real-time monitoring method is needed because this separation process is difficult to characterize. Infrared spectroscopy was applied in the separation device to realize the online determination of the boron isotope ratio in boron trifluoride (BF\({}_{3}\)). The possibility of determining the isotope ratio via the 2v\({}_{3}\) band was explored. A correction factor was introduced to eliminate the difference between the ratio of peak areas and the true value of the boron isotope ratio. It was experimentally found that the influences of pressure and temperature could be ignored. The results showed that the infrared method has enough precision and stability for real-time, in situ determination of the boron isotope ratio. The instability point of the isotope ratio can be detected with the assistance of the online determination method and provides a reference for the production of boron isotope.  
s 2018 8 2509; doi:10.3390/app8122509