Band Filter Research Articles

Optical Continuum Reverberation in the Dwarf Seyfert Nucleus of NGC 4395

In order to constrain the size of the optical continuum emission region in the dwarf Seyfert 1 galaxy NGC 4395 through reverberation mapping, we carried out high-cadence photometric monitoring in the griz filter bands on two consecutive nights in 2022 April using the four-channel MuSCAT3 camera on the Faulkes Telescope North at Haleakalā Observatory. Correlated variability across the griz bands is clearly detected, and the r-, i-, and z-band light curves show lags of , , and minutes with respect to the g band when measured using the full-duration light curves. When lags are measured for each night separately, the Night 2 data exhibit lower cross-correlation amplitudes and shorter lags than the Night 1 light curves. Using the full-duration lags, we find that the lag–wavelength relationship is consistent with the τ ∝ λ 4/3 dependence found for more luminous active galactic nuclei. Combining our results with continuum lags measured for other objects, the lag between g and z band scales with optical continuum luminosity as τ gz ∝ L 0.56±0.05, similar to the scaling of broad-line region size with luminosity, reinforcing recent evidence that diffuse continuum emission from the broad-line region may contribute substantially to optical continuum variability and reverberation lags.

Security Protection Mechanism in Cloud Computing Authorization Model Using Machine Learning Techniques

Because of the vast number of applications and the ambiguity in application methods, handwritten character recognition has garnered widespread recognition and increased prominence in the community of pattern recognition researchers ever since it was first developed. This is due to the fact that application methods can be quite ambiguous. Computer in the cloud, on the other hand, allows for suitable network access on demand to a shared pool of customizable computing resources and digital devices. According to those knowledgeable in the subject, the standard filtering techniques are not enough when it comes to the process of denoising images. In many different approaches to machine learning, information is lost not just during the filtering process itself but also at other points during the process. When a convolutional neural network is going through its pooling operation, the internal data representation either becomes misaligned or entirely vanishes (CNN). The reconstruction of low-intensity digital photographs, which takes place during repetitive filtering, breaks away the artefacts that remain after each filtering function, which results in an image that is more uniform. The multilayer wavelet transform, or MLWT, is a method for processing features that comprises of many filter bands and is used in cloud computing authorization that is protected securely. In this scenario, a significant quantity of information gets obliterated from digital photographs during the process of feature extraction and processing. These issues are investigated by the deep learning algorithms that make use of autoencoder, and the methods also handle the novel windowing blocks that are being introduced to the layers. In this section, the magnitude and phase information is considered in order to construct a deep learning framework that will provide good denoising of digital images. The proposed architecture is equipped with the capability of accurately identifying, in real time, the noise level and type that was employed in the training of the network. The method that we have proposed, which is centred on the distribution of noise, may be used to determine the kind of noise. In order to categorise the various types of noise, we investigated nine distinct noise distributions. Dilated convolutional filtering will be used as the method of choice in order to ascertain the specific nature of the noise that can be found in the digital images. An autoencoder-based deep learning algorithm is able to accomplish numerous experimental results in digital image denoising operations that are superior to those achieved by a typical deep learning algorithm even when the intensity of the scenario is low. The performance of the method that is produced by combining the autoencoder and the dilated convolutional filtering techniques is enhanced over the performance of the technology that is currently in use. Using the method that we have outlined in this study, it is possible to recreate the low-intensity images in their entirety. We were able to show that our proposed method beat other existing algorithms for low-density digital photos by comparing several metrics, such as the peak signal-to-noise ratio (PSNR), the structural similarity index, and others (SSIM).

Design of a Low-Power Low-Noise ECG Amplifier for Smart Wearable Devices Using 180nm CMOS Technology

Wearable biomedical devices for recording electrocardiograms (ECG) are becoming more and more popular as they provide clinicians with a comprehensive view of a patient's diagnosis. ECG signals are characterized by low amplitude and are susceptible to many kinds of noise, so high gain and high common mode rejection ratio (CMRR) are essential to suppress them, while ultra-low power low noise (AFE) is used for Analog front-end for ECG signal acquisition, based on a Drive Right Leg (DRL) circuit that combines common-mode feedback with high CMRR and a notch filter band with a cutoff frequency of 50, implemented in CMOS 180 nm technology. According to the simulation results, this front-end circuit can yield a mid-band gain of 50.75 dB at -3dB bandwidth from 100mHz to 100 Hz, a Power Supply Rejection Ratio (PSRR) of 113 dB, and a Common Mode Rejection Ratio (CMRR) of 102 dB, exhibit an input-referred noise (IRN) of 1.47 μVrms from 0.1 Hz to 1kHz，corresponding to a noise efficiency factor (NEF) of 2.74. The AFE consumes 1.08 μW from the 1.8V supply voltage.

Enhancement of single-mode optical fiber quality factor-bit error rate by using uniform fiber Bragg grating

The properties of optical fibers transmission systems based on Bragg gratings and uniform fibers, which are discussed in detail in this paper. Two - fiber optic communication channels Bragg gratings are used, along with Optisystem software for simulations. It is widely used in a variety of optical communication systems, such as, dispersion compensators, band filters, amplifiers and in - fiber sensors or fiber grating lasers, because of its versatility. In this design, the distance has been changed from 10 km up to 100 km, as well as the input power from 2 dBm to 16 dBm, and the calculation of both the bit error rate (BER) and quality (Q) f actor at the receiver could be studied by modelling the model of a communication system and employing the syste m's most suited settings, such as fiber cable length (km) and input power (dBm).

Dual-Band Design Techniques for Microwave Passive Circuits: A Review and Applications

The introduction of new technology in the wireless communication industry increases the number of frequency bands in the communication environment. Therefore, a communication system capable of functioning over several frequency bands, known as a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiband communication system</i> , is required. In addition, multiband communication systems support technology upgrades by smoothly bridging the migration from the existing technology to a newer technology. A multiband communication system can be developed with the help of two approaches. The first approach is a multiband communication system that contains multiple microwave circuits, with each circuit optimized for a single band; for example, a dual-band communication system has two low-pass filters and two power amplifiers. But this approach increases not only the size but also the cost of the system. In the second approach, rather than using a separate power amplifier and filter for each frequency band, a single power amplifier, filter, and other components are used that can support more than one frequency band. These circuits are known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiband microwave circuits</i> . Multiband circuits not only minimize size but also reduce the cost of designing the multiband communication system.

Enhanced demodulation band selection based on Operational Modal Analysis (OMA) for bearing diagnostics

Vibration time signals emitted by a defective rolling element bearing are often used to determine its health condition. For real-world measurements these fault signals may be weak compared to the remaining content in the measured signal causing increased difficulties to fault detection. One way of enhancing the fault detection is by demodulation at a filtered frequency band in which the Signal-to-Noise-Ratio (SNR) of the fault signal is high. In the present paper, we propose a method that uses the resonances obtained from Operational Modal Analysis (OMA) as center frequencies for the filter bands as it is assumed that the characteristic bearing fault frequencies modulate resonances or carrier frequencies close to them. An indicator is used to determine which of the resonances from the OMA enhance the fault signal the most and this selection is dependent on the bandwidth as well. The presented method is applied on signals from two experimental cases, an experimental test rig of a planetary gearbox and a wind turbine gearbox, and is compared to the Fast Kurtogram and Log-Cycligram to assess its performance for band selection. The results show that the presented method determines a suited band for band pass filtering which enhances the fault detection at the two complex use cases.

Dual Pass Band Filter using Quad Stub Loaded Uniform Impedance Resonator

A low loss, highly selective and miniaturized dual pass band filter for the wireless (WiMAX, WLAN) application is proposed in this paper. The filter is designed with Multimode resonators, constructed with Uniform Impedance Resonator (UIR) and multiple open stubs. Two different coupling schemes (electronic and magnetic) are observed for the said dual pass bands. A detail analysis about the dimension of the resonators, resonating conditions and frequency calculations are presented in this paper. The dual pass bands are achieved at 3.45 GHz and 5.4 GHz with minimum pass band insertion loss (|IL|) 0.1 and 0.18 dB and the pass band Fractional Band widths (FBW) 4% and 8% respectively. With proper optimizations, Transmission Zeros (TZ) are achieved on both sides of the dual pass bands and the spurious pass band are kept around -20dB level and hence good selectivity is achieved. The overall size of the filter is optimized for the best possible results in terms of Insertion Loss, Return Loss and selectivity, is found to be (24.2 x 21)mm = (0.28 x 0.24)λg = 0.06 λg2.

Localization of electro-elastic shear waves in a periodically stratified piezoelectric structure

We investigate the localization of electro-elastic shear waves travelling along a homogeneous piezoelectric superlattice waveguide with thin electrodes periodically inserted parallel to the waveguide faces. The transfer matrix between two neighbouring sub-layers is constructed based on the electrically shorted conditions on the electrodes. A relationship is established between elastic displacements of the top and bottom faces of the superlattice when these faces are traction free. When they are clamped a relationship is established between tangential stresses on the two faces. It is shown that due to the electro-mechanical coupling, waves can be localized at interfaces in the structure if the electrodes are non-uniformly distributed along the thickness of the piezoelectric waveguide. The localization of waves significantly increases with the number of non-symmetrically introduced electrodes between the layers. The results of the paper can be helpful in the design of narrow band filters or multi-channel piezoelectric filters.

THE STUDY OF THE CROSS-CORRELATION PROPERTIES OF COMPLEX SIGNALS ENSEMBLES OBTAINED BY FILTERED FREQUENCY ELEMENTS PERMUTATIONS

Context. The relevance is to study the cross-correlation properties of the developed complex signals ensembles of large volume with a low level of multiple access interference, thereby increasing the efficiency of using a limited radio frequency range. The Object of Research is a method of bandpass filtering with permutations, which allows forming complex signals ensembles of large volume. Objective. The Objective is to determine the optimal cross-correlation properties for the formation of complex signals ensembles of large volume with a low level of multiple access interference. Method. The work has the study results of cross-correlation properties of complex signals ensembles obtained by applying the filtered elements permutation method. The formation of complex signals ensembles is based on pseudo-random sequences with improved cross-correlation properties in the time domain. Bandpass filtering is applied to such sequences, and the number of filter bands is determined based on the calculation of the frequency spectrum utilization coefficient. The filter band optimal width determination is based on a comparison of the maximum emissions of the side lobes values of the of cross-correlation function of signals from the elements number in the involved sequences. The signals obtained by frequency bands allocating are characterized by a difference in form in the minimal similarity condition. In order to reduce the multiple access interference impact, the frequency components transfer obtained by spectral filtering to the common frequency range is carried out. After that, the signals are transferred using the full search method. As a result, it was obtained all possible combinations of signal pairs permutations. The use of permutations in the complex signals ensemble formation can significantly increase the ensemble volume. The signals generated by frequency filtering, to which the transfer to the common frequency band and their subsequent permutation was applied, are subjected to correlation analysis based on the calculation of the maximum emissions values of the side lobes of the cross-correlation function. Comparative characteristic of cross-correlation properties of developed signals with known signals prove that signals generated based on pseudo-random sequences with improved cross-correlation properties have a much larger ensembles volume, are formed on the basis of simple algorithms that don’t require significant computing resources and have satisfactory cross-correlation characteristics. The use of bandpass filtering method with permutation allows the formation of large-volume ensembles whose signals differ inform, and the combination of different frequency bands reduces the vulnerability to multiple access interference. Results. Due to the software implementation of the bandpass filtering method with permutations, the comparison of crosscorrelation properties of nonlinear sequences, M-sequences, multiphase signals and developed signals based on sequences with improved cross-correlation properties was performed. In estimating the levels of maximum emissions of side lobes of the cross-correlation function, it was found that the generated signals obtained by bandpass filtering with permutations deteriorate cross-correlation characteristics by increasing the pulse duration proportional to the decrease in signal frequency band, but their value satisfies the minimal similarity condition, used in cognitive telecommunications systems. Conclusions. The study of the signals cross-correlation properties proves the effectiveness of the developed bandpass filtering with permutations method. The generated signals have cross-correlated characteristics no worse than ensembles based on known signals. At this level of maximum emissions of the side lobes of the cross-correlation function of the developed signals is 7–12% less than the known signals. Thus, the method of bandpass filtering with permutations can be used to increase the efficiency of radio frequency resource use of both existing and advanced cognitive telecommunication networks of wireless access based on systems with code division multiplexing.

Research on the normal emissivity of graphite between 150 and 500 °C by an infrared camera for nuclear fusion devices

• An emissivity measurement equipment by using an infrared camera is constructed and calibrated by a blackbody furnace with a suitable emissivity model. • By using an infrared camera with no filter (band wavelength range of 7.5 μm–13 μm), a 10.2 ± 0.1 μm filter, and a 10.8 ± 0.19 μm filter, the relationship between the temperature and emissivity of graphite and the residual between data and model are obtained respectively and compared. • The emissivity of graphite at different roughness is studied, and uncertainty quantification is used to provide an error estimate for the resulting curves. Due to the advantages of high-temperature resistance, low thermal expansion coefficient, and thermal shock resistance, etc., graphite is regarded as one of the materials for the first wall of nuclear fusion devices. The real-time monitoring of temperature distribution of the first wall based on an infrared camera is widely used to guarantee the stable operation of devices. To accurately measure the temperature of the first wall, it is important to measure the normal emissivity of graphite. However, the emissivity of graphite is affected by many factors. For example, the effect of the surface layers, like carbon-hydro layers-layers, will influence the measurement of the emissivity. The ambition of this work is to study the relationship between graphite emissivity and infrared camera with filters of different wavelengths and the roughness of graphite, and then give the proposed emissivity model to improve the accuracy of graphite surface temperature measurement. The experiment is carried out with a FLIR infrared camera and calibrated by using a blackbody furnace. The emissivity at given temperatures is systematically investigated. By using an infrared camera with no filter (band wavelength range of 7.5–13 μm), a 10.2 ± 0.1 μm filter, and a 10.8 ± 0.19 μm filter, this paper studies the relationship between the temperature and emissivity of graphite from 150 °C to 500 °C and calculates the relative error of temperature measurement respectively. A suitable fitting model which fits emissivity curves is selected. The measurement results show the use of a 10.2 μm filter to measure the graphite surface temperature has the smallest relative error, the range is 0.90%∼1.17%. The emissivity of graphite with different roughness is also studied. At the same temperature, the greater the roughness of the graphite surface, the higher the emissivity value. The uncertainty of the emissivity measurement is analyzed, and its value is 0.0099–0.0211. The graphite surface temperature measurement method based on the emissivity model proposed in this paper provides useful references for the non-contact temperature measurement of the first wall in nuclear fusion devices. The research results can be used as a reference for plasma experiments in some fusion devices and other similar applications.

ПОДДЕРЖКА ПЕТЕЛЬ СЛЕЖЕНИЯ ЗА ФАЗОЙ В ПРИЕМНИКЕ СПУТНИКОВОЙ НАВИГАЦИИ С ПОМОЩЬЮ ИЗМЕРЕНИЙ ИНЕРЦИАЛЬНОЙ НАВИГАЦИОННОЙ СИСТЕМЫ

Satellite radio navigation systems make it possible to evaluate the user's state vector, usecoordinates, user speed and time relative to the system scale. The requirements for the characteristicsof these systems constantly depend on the fact that they have application features in theiralgorithms for processing radio navigation signals. One of the main characteristics of satelliteradio navigation systems is the accuracy of estimating the user's state vector. This characteristiccan be improved by the presence of estimates of the phase of the received radio navigation signals.In a satellite radio navigation system, phase estimation errors in the tracking loop have two components:dynamic and noise. To compensate for the noise error, it is necessary to reduce theequivalent noise band of the anti-aliasing filter of the phase tracking loop. However, the minimumpossible bandwidth of the smoothing filter is limited by the presence of consumer dynamics and thequality of the reference oscillator. As a result, in the presence of consumer dynamics, the sensitivityand reliability of phase tracking deteriorates. To compensate for the dynamic error in the phasetracking loop, information from an inertial navigation system can be used. The satellite radio navigationsystem and the inertial navigation system have complementary characteristics. The use ofsupport for phase tracking loops from an inertial navigation system makes it possible to increasethe sensitivity and reliability of its operation in the presence of consumer dynamics. It is assumedthat with such an implementation, the sensitivity of the phase tracking loops will be limited only bythe instability of the reference oscillator and the error of inertial measurements. To improve thecharacteristics of accuracy, sensitivity and reliability of the coherent mode of operation of the enddevice, an algorithm was developed to support phase tracking loops with measurements from aninertial navigation system. A study of the developed algorithm was carried out on a model thatuses real measurements of satellite and inertial navigation systems as input data. The developedalgorithm is implemented in the software of the NV216C-IMU inertial satellite navigation systemprototype. Experimental studies were carried out in the conditions of automobile dynamics in openareas. The research results are presented in the work.

Security and Privacy Protection of Internet of Vehicles Consensus Algorithm Based on Wireless Sensors

Due to its large network scale, open communication environment, unstable wireless network, and other characteristics, it is extremely vulnerable to attacks and causes security problems, resulting in the collapse of the Internet of Vehicles system. The application of the Internet of Vehicles is becoming more and more extensive, but there are still problems such as information security and privacy leakage in the Internet of Vehicles. Through the analysis of the security threats and privacy protection requirements faced by the Internet of Vehicles system, this paper mainly studies information security, vehicle identity privacy, and location privacy in the process of Internet of Vehicles wireless communication. Therefore, it is urgent to conduct research on the information security and privacy protection issues of the Internet of Vehicles. This paper discusses the research on the security and privacy protection of the consensus algorithm for the Internet of Vehicles based on wireless sensors, compares and analyzes the wireless sensor data privacy protection protocols based on sharding technology, Tongtai encryption technology, and perturbation technology, and selects an optimized Kalman consensus filter. The algorithm is applied to the node information exchange of the sensor network, and two filters (low pass and band pass) are used to unify the observations and covariance of the network. Estimation of the sensor network state with and without data packet loss, the effect of system estimation error under different packet loss rates, data privacy protection algorithm performance, vehicle network data communication volume, and confusion factors on algorithm efficiency and the node energy consumption was compared and analyzed. Based on the application of wireless sensors, the estimation error and inconsistency estimation error of the algorithm in this paper finally converge to about 0.5, and both can maintain good stability and have good robustness. In addition, the communication volume of the algorithm in this paper is about 30% of the SCPDA algorithm. The Kalman consensus filtering algorithm reduces the amount of confusing data sent, improves privacy protection, and also achieves lower communication overhead.

Preparation and Characterization of Orthorhombic AgMn Alloys by the Pulsed Laser Welding Technique

AbstractHerein, AgMn alloys are prepared by the pulsed laser welding technique in an argon atmosphere. The effect of the laser pulses width and stoichiometric composition of the alloys on the structural, compositional, morphological, and electrical properties are investigated. In contrast to the traditional preparation techniques which reveal cubic structure of AgMn alloys, the pulsed laser welding technique reveals the orthorhombic phase of the alloys. The lattice parameters of the orthorhombic phase of AgMn are . It is observed that pulse widths of 50 ms are the optimum from preparing these alloys. From an electrical point of view, the AgMn alloys exhibit negative dielectric constant and negative conductance effect in the microwave frequency domain. The impedance spectroscopy analyses in the frequency domain of 0.01–1.80 GHz have shown that AgMn alloys can be employed as band filters with return loss value of ≈16 dB. The features of the AgMn alloys which are achieved by the pulsed laser welding technique nominate them for use as negative capacitance and negative conductance transistors. These devices are suitable for noise reduction and parasitic capacitance cancellation.

Antarctic Survey Telescope 3-3: Overview, System Performance and Preliminary Observations at Yaoan, Yunnan

The third Antarctic Survey Telescope array instrument at Dome A in Antarctica, the AST3-3 telescope, has been in commissioning from March 2021. We deployed AST3-3 at the Yaoan astronomical station in Yunnan Province for an automatic time-domain survey and follow-up observations with an optimised observation and protection system. The telescope system of AST3-3 is similar to that of AST3-1 and AST3-2, except that it is equipped with a 14 K × 10 K QHY411 CMOS camera. AST3-3 has a field of view of 1.65∘×1.23∘ and is currently using the g band filter. During commissioning at Yaoan, AST3-3 aims to conduct an extragalactic transient survey, coupled with prompt follow-ups of opportunity targets. In this paper, we present the architecture of the AST3-3 automatic observation system. We demonstrate the data processing of observations by representatives SN 2022eyw and GRB 210420B.

Diagnosing Localized and Distributed Bearing Faults by Bearing Noise Signal Using Machine Learning and Kurstogram

Bearings are a common component and crucial to most rotating machinery. Their failures are the causes for more than half of the total machine failures, each with the potential to cause extreme damage, injury, and downtime. Therefore, fault detection through condition monitoring has a significant importance. Since the initial cost of standard condition monitoring techniques such as vibration signature analysis is high and has a long payback period, the condition monitoring via audio signal processing is proposed for both localized faults and distributed/ generalized roughness faults in the rolling bearing. It is not appropriate to analyze bearing faults using Fast Fourier Transform (FFT) of the noise signal of bearing since localized faults are Amplitude Modulated (AM) and mixed up with background noises. Localized faults are processed using Kurstogram technique for finding the appropriate filtering band because localized faulty bearings produce impulsive signals

Optical variability of quasars with 20-yr photometric light curves

ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.

New biopolymer from biomass for conditioning and dehydration of sewage sludge: application on the sludge of Bouira WWTP.

Sewage treatment plants in Algeria produce huge quantities of sludge expressed in tons annually. This sludge produced is unfortunately contaminated because of the use of synthetic polyelectrolytes. Recently several kinds of research have been carried out on natural flocculants for sludge conditioning, because of several advantages they present such as their renewable source and their non-toxicity. This work aims to evaluate the potential use of protonated pectin extracted from orange waste of N'GAOUS juice factory as an eco-friendly flocculant in the chemical conditioning of sludge. Protonated pectin effectiveness was compared with synthetic cationic anionic and ionic polyelectrolytes (SUPERFLOC 8396, AF400, NF102). In this context, raw sludge samples from Bouira WWTP were tested. Specific resistance to filtration (SRF), cakes dry solid content were analyzed to determine filterability, dewatering capacity of conditioned sludge, and the optimum dose of each conditioner. So that our goal was to obtain greater dryness, which is the case with the addition of protonated pectin and even the addition of Superfloc, which allowed us to obtain dryness of 33.01% and 29.19%, respectively, for the same doses that gave the lowest SRF. Based on the results found and the analysis of the specific resistance to filtration (SRF) and the dryness, and compared with the values observed for the dewatered sludge by the method used in the Bouira WWTP. Band filters (18-22%) and raw sludge (4.8-5.7%).

ECG classification system based on multi-domain features approach coupled with least square support vector machine (LS-SVM)

Developing a robust authentication and identification method becomes an urgent demand to protect the integrity of devices data. Although the use of passwords provides an acceptable control and authentication, it has shown much weakness in terms of speed and integrity, which make biometrics the ideal authentication solution. As a result, electrocardiogram (ECG) signals have received a great attention in most authentication systems due to the individualized nature of the ECG signals that make them difficult to counterfeit and ubiquitous. In this paper, we propose a new model for ECG verification using multi-domain features coupled with a least square support vector machine (LS-SVM). Two types of features are investigated to find the best set of features to individual from ECG signals. Time domain and frequency domain features based on optimized Triple Band filter bank are extracted from ECG signals. The extracted features are investigated to figure out the best relevant features and remove the redundant ones. The selected features are fed to three classifiers, including Least Square Support Vector Machine (LS-SVM), K-means, and K-nearest. The obtained results have shown that our ECG biometric authentication system outperforms existing methods. The proposed model obtained an average of accuracy of 88%, 95% with time and frequency features, respectively, while it recorded 99% when a combination of time and frequency features are used to classify ECG signals. A public dataset is used to assess the proposed model.

Structural, Optical and Electrical Properties of Band-Aligned CdBr2/Au/Ga2S3 Interfaces and Their Application As Band Filters Suitable for 5G Technologies

Structural, Optical and Electrical Properties of Band-Aligned CdBr2/Au/Ga2S3 Interfaces and Their Application As Band Filters Suitable for 5G Technologies

Design of single-dual channel conversion filter based on one-dimensional photonic crystal

This study proposes a quantum well photonic crystal to realize a single-dual channel conversion filter in the optical communication band, which aggregates dual-channel into single-channel by reducing the coupling strength between the air defect modes. When the photonic crystal structure with defect mode is symmetric, there is a single channel in the forbidden bandgap due to the disappearance of coupling between the two channels and the transmittance is up to 100%. The coupling coefficient α is inversely proportional to the period number M. When M is greater than the threshold-2N, the transmittance of the channel gradually decreases as M increases, correspondingly. The proposed filter can be applied in wavelength division multiplexing to increase the network capacity.