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To simultaneously cover multiple wireless services and protocols, the antenna in communication devices should operate over a wide and ultra-wide frequency band. The use of wide/ultra-wideband antennas not only lessens the number of antennas necessary to cover multiple frequency bands but also decreases the system complexity, size, and costs. To operate over the ultra-wide frequency band, in this paper a CPW-fed small antenna is reported for portable communication devices. The anticipated antenna comprises a bow-tie-shaped patch and two ground planes. One inverted L-shaped and one extended U-shaped ground plane are asymmetrically placed with the main radiator which helps the antenna prototype to realize a functional band of 3.05 – 11.25 GHz (VSWR ≤ 2). In the functional band, the studied antenna accomplished a maximum peak gain of 4.98 dBi and maximum efficiency of 94.4%. Moreover, it exhibits symmetric omnidirectional radiation patterns and good time-domain behavior. The lucrative characteristics such as simple design, very small size (24.5 × 20 mm2), ultra-wide operating band, good gain and efficiency, stable radiation characteristics, and good time-domain characteristics make it a potential candidate to be used in portable communication devices.

This article deals with a novel fractional-order active disturbance rejection control (FADRC) scheme to handle a general integer-order system. The proposed control structure enhances the robustness and performance of the classical active disturbance rejection control, especially for the open-loop gain variation. Based on the Bode's ideal transfer function, an analytical design of a state-feedback control is proposed. The integer-order model of the system to be controlled is first transformed to a noninteger-order one, where the introduced fractional order is a design parameter, which imposes the overshoot of the closed-loop step response. In addition, because the model of the system is transformed to a cascade of integer- and fractional-order integrator (the model is noncommensurate), a commensurate fractional-order extended state observer is proposed to estimate the generalized disturbance. To improve the robustness of the proposed FADRC scheme, an analytical design method of a noncommensurate state-feedback control is proposed. The proposed design method is based on the Bode's ideal transfer function cascaded with an integer-order filter. The proposed FADRC scheme is applied for a pendulum–cart test bed, and the effectiveness and robustness of the proposed control are examined by experiments.

The novelty of this work is to fabricate the double-walled (DW) TiO2 nanotube arrays (TNAs) by an anode oxidation method with NH4F-based electrolyte and Zinc counter electrode (CE, c-Zn) and to investigate the photodegradation performance of these TNAs. The structural, optical, and photodegradation performance of TNAs with c-Zn material have been compared to the properties of TNAs with the other two CEs like c-Pt (Platinum) and c-Ti (Titanium). The counter electrode has a tremendous influence on the structural properties and geometrical features of TNAs. The TNAs fabricated with c-Zn have the red-shifted absorption edge with two bandgaps such as 3.15 and 1.78 eV. Interestingly, the TNAs with c-Zn are found as the DW TNAs with outer diameter of 130 ± 3 nm, thinner outer wall thickness of 12 ± 2 nm, and thicker inner wall thickness of 30 ± 2 nm. The photodegradation performance varies with different counter electrodes during the deposition of TNAs by the anode oxidation method. The TNAs sample prepared with c-Zn has shown the highest roughness value of 305.0 nm, photodegradation efficiency of 97.0%, and the rate constant value of 0.00985 min−1 than the other TNAs with c-Pt, c-Ti, and other researcher's data. Moreover, the optical, structural, and surface morphological properties of TNAs have correlated with the photodegradation performance of TNAs prepared with various counter electrodes during deposition.

The moon is recognized as an important destination for space science and exploration. To find a satisfactory answer for the mystery of the universe and to make use of the lunar resources for the welfare of human beings, several space agencies are planning manned and unmanned missions on the moon. As a result, the concept of lunar vehicles has begun with an advanced descent scheme to execute a precise and safe landing on the surface of the moon. On the contrary, the energy budget is an important issue for any space mission. To reduce the cost of a space mission, it is necessary to design the vehicle trajectory based on optimized energy resources. Fuel is the main energy in a space mission. Therefore, a fuel-optimized energy generation technique is focused on this research. The design of an algorithm that generates a real-time trajectory for the descent and landing of a lunar probe is critical to ensuring a successful lunar landing mission. A scheme of dual-step trajectory generation for lunar descent is also investigated in this paper. In the algorithm developing process, the thrust-to-mass ratio is considered as a principle variable. Algorithm design along with mathematical modeling and simulation results are described in detail. In addition, the proposed method for generating reference trajectory profiles is also analyzed for fuel consumption and robustness.

Fractional order control (FOC) has received widespread attention in recent years due to its efficient tuning capacity, intuitive concept, and enough flexibility. Again, FOC are known to be robust with the open loop gain in particular. However, the design of FOC demands the knowledge of the model to be modified. But on the other hand, the linear active disturbance control (LADRC) technique is known to be model free controller. In order to achieve the better tracking performance even in uncertain operational conditions by responding timely against external disturbances, these two controllers (FOC and LADRC) are combined to propose a new fractional order LADRC to handle integer order system. Therefore, FOC-based LADRC for heat-flow experiment (HFE) is designed in this paper to track desired trajectories of heat flow. Bode’s ideal transfer function is considered as an orientation model to propose this new controller while using the concept of internal mode control. A better performance of fractional order linear active disturbance control (FO-LADRC) is shown for a very good disturbance rejection capability through simulation and experiments on a heat-flow system.

Recently, deep learning-based models are being extensively utilized for steganalysis. However, deep learning models suffer from overfitting and hyperparameter tuning issues. Therefore, in this paper, an efficient θ -nondominated sorting genetic algorithm- ( θ NSGA-) III based densely connected convolutional neural network (DCNN) model is proposed for image steganalysis. θ NSGA-III is utilized to tune the initial parameters of DCNN model. It can control the accuracy and f-measure of the DCNN model by utilizing them as the multiobjective fitness function. Extensive experiments are drawn on STEGRT1 dataset. Comparison of the proposed model is also drawn with the competitive steganalysis model. Performance analyses reveal that the proposed model outperforms the existing steganalysis models in terms of various performance metrics.

Novel two-dimensional (2D) PtO2/GaN van der Waals (vdW) hetero-bilayers (HBL) are studied here for photocatalytic water splitting (PWS) application under first-principles density functional theory (DFT). We proposed six HBLs due to the atomic orientational variations and two of them are found dynamically stable confirmed by phonon dispersion curves. The two stable HBLs, HBL1, and HBL6 also show negative binding energy depicted by the interlayer distance-dependent binding energy curves. Among them, HBL1 has the lowest binding energy, suggesting the exothermic practicability of the material. Electronically both materials show a visible ranged indirect bandgap of ~2.65 (2.69) eV for HBL 1 (HBL6), lowered by ~2 times compared to their intrinsic constituents (2D PtO2, 2D GaN). The bandgaps also have type-II band orientation, which is highly required for efficient spatial carrier separation in photocatalytic water splitting (PWS) applications. The optical properties of the HBLs were also calculated, and it’s found that the HBLs have $\sim 2\times 10 ^{5}{\mathrm {cm}}^{-1} $ of perovskite material-like absorption coefficient in the visible spectrum, a key requirement for efficient photocatalysis. Reflectivity is as low as ~7% in the visible spectrum, suggesting the low-loss nature of the materials. Photocatalytic band-edges with type-II band alignments show sufficient kinetic overpotential for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in both HBLs, suggesting effective water-splitting capacity. Moreover, we have explored the biaxial strain-induced tunability of the electronic bandgap, absorption coefficients, and photocatalytic band edges. They all found responsive due to homogeneous biaxial strain and show bandgap-lowering, absorption coefficient visible shifting, and band-edges tuning from compressive to tensile strains in the −6 % to +6% range. These studies suggest that the novel PtO2/GaN vdW layered material can be a probable efficient material for visible-light-driven photocatalytic water-splitting technology.

Electricity demand forecasting remains a challenging issue for power system scheduling at varying stages of energy sectors. Short Term load forecasting (STLF) plays a vital part in regulated power systems and electricity markets, which is commonly employed to predict the outcomes power failures. This paper presents an intelligent machine learning with evolutionary algorithm based STLF model, called (IMLEA-STLF) for power systems which involves different stages of operations such as data decomposition, data preprocessing, feature selection, prediction, and parameter tuning. Wavelet transform (WT) is used for the decomposition of the time series and Oppositional Artificial Fish Swarm Optimization algorithm (OAFSA) based feature selection technique to elect an optimal set of features. In order to improvise the convergence rate of AFSA, oppositional based learning (OBL) concept is integrated into it. Then, the water wave optimization (WWO) with Elman neural networks (ENN) model is employed for the predictive process. Finally, inverse WT is applied and obtained the hourly load forecasting data. To validate the effective predictive outcome of the IMLEA-STLF model, an extensive set of simulations take place on benchmark dataset. The resultant values ensured the promising results of the IMLEA-STLF model over the other compared methods.

An organic solar cell (OSC), competitive with traditional one (Si-based), draws attention to future renewable energy sources due to its low-cost and continually rising efficiency. The tandem or multijunction structure undoubtedly offers an efficient way to boost the performance of OSCs. This work has explored the optical modeling of different organic photoactive materials to identify the potential materials for efficient tandem structure. The performance of double, triple, and quadruple junction tandem OSCs with suitable bandgaps has been analyzed with photoactive materials. The absorption efficiency enhances considerably using the thickness optimization of each subcell in tandem structures. Current matching in all subcells, an essential factor for efficient device operation, is taken into account while optimizing tandem structures. The quadruple design can achieve better photovoltaic performance than double or triple junction devices. The efficiency predicted from our proposed quadruple structure is ~15.45%, with a short-circuit current density, $\text{J}_{\mathrm {SC}}$ of $\sim 9$ mA/cm2 and an open-circuit voltage, $\text{V}_{\mathrm {OC}}$ of ~2.64 V. These results are one of the high-performance in terms of organic photovoltaic (OPV). Therefore, the above findings indicate that OSCs are very potential for future photovoltaic applications.

In this paper, the performance of GaAs and GaSb based sub-10 nm double-gate junctionless metal-oxide-semiconductor field-effect transistors (DG-JLMOSFETs) have been studied for high-performance switching applications. The quantum transmitting boundary method (QTBM) has been considered for electron transport, and the band structures are accounted for sp3d5s* tight-binding modeling. The channel thickness, tch is varied from 1.7 to 4.7 nm to evaluate the device figure of merits (FOMs). The thinner channel’s device shows a lower OFF-state current, while the ticker channel device allows a higher ON-state current. The threshold voltage is approximately 0.4 V for GaAs DG-JLMOSFETs with tch = 1.7 nm, whereas it reduces to ~0.05 V for that of tch = 4.7 nm. Similar characteristics have been shown in GaSb devices. Besides, a significant impact of tch on the subthreshold swing (SS) and drain-induced barrier lowering (DIBL) is found in GaSb DG-JLMOSFETs compared with those of GaAs devices. The devices show a higher leakage-power dissipation in both channel materials and low-intrinsic delay for thicker tch due to a substantial amount of energy drop. The above results indicate that III-V-based DG-JLMOSFETs are very promising for next-generation high-performance switching technology.

Grid extension from the distribution network is being used to meet the demand for rural electricity all over the world. Due to the extra cost of extending electric lines to rural villages, it is not feasible as the installing and commissioning costs are directly related to several constraints such as distance from the main grid, the land location, utilities to be used, and the size of the approximate load. Consequently, it becomes a challenge to apply technoeconomic strategies for rural electrification. Therefore, considering the above issues of rural electrification through grid power, the renewable energy system can be an attractive solution. This research analyzes different types of loads considering domestic, industrial, and agricultural requirements for a remote village in a developing country like Bangladesh. In this paper, four types of demand scenarios are developed considering the income level of inhabitants of the village. The investigation identifies the optimal scope for renewable energy-based electrification and provides a suitable technoeconomic analysis with the help of HOMER software. The obtained results show that a combined architecture containing solar panel, diesel generator, and battery power is a viable solution and economically beneficial. The optimal configuration suggested for the primary scenario consists of 25 kW diesel generators to fulfill the basic demand. The hybrid PV-diesel-battery system becomes the optimal solution while the demand restriction is removed for secondary, tertiary, and full-option scenarios. Commercial and productive loads are considered in the load profile for these three scenarios of supply. For the primary scenario of supply, the electricity cost remains high as $0.449/kWh. On the other hand, the lowest electricity cost ($0.30/kWh) is obtained for the secondary scenario. Although the suggested optimal PV-diesel-battery might not reduce the cost of electricity (COE) and NPC significantly, it is capable to reduce dependency on diesel utilization. Hence, the emission of carbon is reduced due to less utilization of diesel that helps to minimize the greenhouse effect on the environment.

The aim of this article was to determine control strategy for balance control of rotary double inverted pendulum system, which is highly nonlinear and unstable under-actuated system. The complexities involved in rotary double inverted pendulum dynamics make this system a useful engineering test bed to test and verify newly designed controllers. In this article, a constraint-based control approach titled robust generalized dynamic inversion is designed and implemented for robust stabilization of rotary double inverted pendulum system. The robust generalized dynamic inversion control is designed in two stages; in the first stage, constraint differential equations of the controlled state variables are prescribed, which encompasses the control objectives. To enforce the constraint dynamics, the equivalent control is realized by means of Moore–Penrose generalized inversion. To enhance robustness, the switching (discontinuous) control is introduced in second stage, whose design principle is based on classical sliding mode control theory. Finally, the controllers obtained in two stages are augmented to form the resultant robust generalized dynamic inversion control law. The proposed controller ensures robustness along with improved time domain performance regardless of system nonlinearities, uncertainties, and unwanted disturbances. The stability analysis is presented for guaranteeing semi-global asymptotically stable closed loop performance via Lyapunov stability criteria. Numerical simulation and experimental investigations are carried out along with comparative analysis, to demonstrate the effectiveness of robust generalized dynamic inversion control algorithm over other conventional control methods.

The article applies the robust generalized dynamic inversion control methodology to the problem of stabilizing upright equilibrium configuration of the under-actuated rotary inverted pendulum system while tracking rotary motion of the actuated arm. The proposed robust generalized dynamic inversion control law comprised equivalent and switching control parts. The equivalent control part works to enforce a virtual constraint dynamics of the controlled state variables by means of Moore–Penrose generalized inversion. The switching control part is of the sliding mode type, and it improves robustness against unmodeled system dynamics, parametric uncertainties, and external disturbances. The robust generalized dynamic inversion control design on the linearized model of the under-actuated rotary inverted pendulum is shown to guarantee semi-global asymptotically stable tracking performance. Numerous computer simulations and experiments are conducted on the Quanser rotary inverted pendulum system, revealing that the proposed algorithm has better convergence and tracking performance than conventional sliding mode and generalized dynamic inversion control strategies when both are applied separately.

Novel GaN-based van der Walls (vdW) hetero-bilayer (HBL) is systemically studied through the first-principles density functional theory (DFT) framework to explore its optoelectronic property facilitated photocatalytic activity for hydrogen (H2) fuel production. The vdW concept of planar GaN with GeC monolayer, together making stacked hetero-bilayer, shows unique and tunable optoelectronic properties that fulfill all the photocatalysis attributes. The confirmation of chemical and dynamical stabilities is made with negative interlayer binding energy and non-negative frequency in phonon spectra, respectively. Among the dynamically stable hetero-bilayers, binding energy in HBL 2 (AB1) is the lowest and interlayer distance ~2.954A is the smallest. The HBLs are sensitive to the stacking arrangements, where HBL 2 demonstrates type-I direct bandgap and HBL 6 (AB6) is Type-II direct bandgap. The intrinsic HBLs show superior carrier mobility as their effective masses are lower from their constituent monolayers. Also, the intrinsic absorption coefficient of the HBLs increase as high as ~106 cm−1, 10 times greater than conventional perovskite materials, which show outperforming optoelectronic conversion efficiency. Additionally, the HBLs are highly tunable in both bandgap and type due to biaxial strains and cross-plane electric fields. With biaxial strains, from compressive to tensile, both HBLs show monotonous bandgap lowering with a dominant direct-indirect bandgap splitting in HBL 2. Interestingly, for all the biaxial strains within the −6% to +6% range, both HBLs have sufficient kinetic overpotential for photocatalytic water splitting and an increase in visible peak by 3.5 (2) times in the HBL 6 (HBL 2). Electric fields also increase the photocatalytic water splitting performance with a net bandgap lowering and increasing the visible absorption peak by ~1.5 times compared with intrinsic HBLs. These promising properties that we have found in the planar GaN/GeC vdW hetero-bilayer are highly suggestive for the impending use of this material in photocatalytic water splitting technology to produce H2 fuel.

The non-invasive Fetal Electrocardiogram (FECG) signal has become a significant method for monitoring the fetus's physiological conditions, extracted from the Abdominal Electrocardiogram (AECG) during pregnancy. The current techniques are limited during delivery for detecting and analyzing fECG. The non - intrusive fECG recorded from the mother's abdomen is contaminated by a variety of noise sources, can be a more challenging task for removing the maternal ECG. These contaminated noises have become a major challenge during the extraction of fetal ECG is managed by uni-modal technique. In this research, a new method based on the combination of Wavelet Transform (WT) and Fast Independent Component Analysis (FICA) algorithm approach to extract fECG from AECG recordings of the pregnant woman is proposed. Initially, preprocessing of a signal is done by applying a Fractional Order Butterworth Filter (FBWF). To select the Direct ECG signal which is characterized as a reference signal and the abdominal signal which is characterized as an input signal to the WT, the cross-correlation technique is used to find the signal with greater similarity among the available four abdominal signals. The model performance of the proposed method shows the most frequent similarity of fetal heartbeat rate present in the database can be evaluated through MAE and MAPE is 0.6 and 0.041209 respectively. Thus the proposed methodology of de-noising and separation of fECG signals will act as the predominant one and assist in understanding the nature of the delivery on further analysis.

Due to the rapid increase in the consumption of electrical energy and the instability of fossil fuel prices, renewable energy, such as wind power (WP), has become increasingly economically competitive compared to other conventional energy production methods. However, the intermittent nature of wind energy creates certain challenges to the power network operation. The combined economic environmental dispatch (CEED) including WP is one of the most fundamental challenges in power system operation. Within this context, this paper presents a new attempt to solve the probabilistic CEED problem with WP penetration. The optimal WP to be incorporated in the grid is determined in such a way that the system security is within acceptable limits. The system security is described by various fuzzy membership functions in terms of the probability that power balance cannot be met. These membership functions are formulated based on the dispatcher’s attitude. This probabilistic and non-convex CEED problem is solved using a new technique combining chaos theory and artificial bee colony (ABC) technique. In this improved version of ABC (IABC), chaotic maps are used to generate initial solutions, and the random numbers involved in the standard ABC are substituted by chaotic sequences. The effectiveness of IABC is tested on two groups of benchmark functions and practical cases. The impacts of dispatcher’s attitude and risk level are investigated in the simulation section.

Control engineers and researchers face challenges to design an efficient controller for Ball and beam system due to its nonlinear and unstable properties. This paper investigates two Degrees of Freedom fractional order control of the ball and beam system. It involves the model based method to design controllers’ parameters for the corresponding linear model. The fractional order controllers are specially tuned to have a constant phase margin of the open-loop. This characteristic ensures the robustness of the controllers to the variations of system gain. This paper presents a proper evaluation and comparison between integer and fractional order controllers. Performance of each controller is evaluated in terms of set-point tracking, disturbance rejection, and robustness. The comparison between two controllers is validated through both simulation and experimental results. Strengths and weaknesses in the real-time control are also indicated.

In this paper, a highly sensitive graphene-based multiple-layer (BK7/Au/PtSe2/Graphene) coated surface plasmon resonance (SPR) biosensor is proposed for the rapid detection of the novel Coronavirus (COVID-19). The proposed sensor was modeled on the basis of the total internal reflection (TIR) technique for real-time detection of ligand-analyte immobilization in the sensing region. The refractive index (RI) of the sensing region is changed due to the interaction of different concentrations of the ligand-analyte, thus impacting surface plasmon polaritons (SPPs) excitation of the multi-layer sensor interface. The performance of the proposed sensor was numerically investigated by using the transfer matrix method (TMM) and the finite-difference time-domain (FDTD) method. The proposed SPR biosensor provides fast and accurate early-stage diagnosis of the COVID-19 virus, which is crucial in limiting the spread of the pandemic. In addition, the performance of the proposed sensor was investigated numerically with different ligand-analytes: (i) the monoclonal antibodies (mAbs) as ligand and the COVID-19 virus spike receptor-binding domain (RBD) as analyte, (ii) the virus spike RBD as ligand and the virus anti-spike protein (IgM, IgG) as analyte and (iii) the specific probe as ligand and the COVID-19 virus single-standard ribonucleic acid (RNA) as analyte. After the investigation, the sensitivity of the proposed sensor was found to provide 183.33°/refractive index unit (RIU) in SPR angle (θSPR) and 833.33THz/RIU in SPR frequency (SPRF) for detection of the COVID-19 virus spike RBD, the sensitivity obtained 153.85°/RIU in SPR angle and 726.50THz/RIU in SPRF for detection of the anti-spike protein, and finally, the sensitivity obtained 140.35°/RIU in SPR angle and 500THz/RIU in SPRF for detection of viral RNA. It was observed that whole virus spike RBD detection sensitivity is higher than that of the other two detection processes. Highly sensitive two-dimensional (2D) materials were used to achieve significant enhancement in the Goos-Hänchen (GH) shift detection sensitivity and plasmonic properties of the conventional SPR sensor. The proposed sensor successfully senses the COVID-19 virus and offers additional (1 + 0.55) × L times sensitivity owing to the added graphene layers. Besides, the performance of the proposed sensor was analyzed based on detection accuracy (DA), the figure of merit (FOM), signal-noise ratio (SNR), and quality factor (QF). Based on its performance analysis, it is expected that the proposed sensor may reduce lengthy procedures, false positive results, and clinical costs, compared to traditional sensors. The performance of the proposed sensor model was checked using the TMM algorithm and validated by the FDTD technique.

Dynamic inverse- (DI-) based control technique has been utilized in many applications and proven to be effective. Recently, the inverse dynamic control (IDC), an expansion to the classical DI technique, has been trending with implementation in many areas. It has been proved that IDC is capable of overcoming some limitations in DI-based techniques, particularly in cancellation of useful nonlinearities. This paper extends the implementation of IDC on the positional and speed control of the linear servo cart system. Simulation results further proves that IDC is an effective and robust controller evidently when comparing it with the proportional velocity and lead compensator controller.

Performance evaluation of trajectory tracking for a rotary flexible joint system is demonstrated in this paper. The robust and converse dynamic (RCD) technique is proposed and implemented for this evaluation. This control methodology is of the left inversion type, i.e., the control inputs are obtained by means of plant output error feedback. RCD control encompasses the baseline inverse (BI) control and sliding mode control-based discontinuous control element. The baseline inverse controller enforces the prescribed servo (virtual) constraints that represent the control objectives. The control objectives of the baseline inverse controller are enclosed in the form of servo (virtual) constraints which are inverted using Moore–Penrose Generalized Inverse (MPGI) to solve for the baseline control law. To boost the robust attributes against parametric uncertainties and disturbances, a discontinuous control function is augmented with baseline controller such that semiglobal practical stability is guaranteed in the sense of Lyapunov. To exhibit the effectiveness of RCD control in terms of tracking performance, computer simulations are conducted in Simulink/Matlab environment. Furthermore, the practical implementation is also investigated through a real-time experiment on Quanser’s rotary flexible joint manipulator system. The experimental results obtained by RCD are compared to the conventional sliding mode and fractional-order control techniques.

This paper presents the application of adaptive fuzzy sliding mode control (AFSMC) for the respiratory system to assist the patients facing difficulty in breathing. The ventilator system consists of a blower-hose-patient system and patient’s lung model with nonlinear lung compliance. The AFSMC is based on two components: singleton control action and a discontinuous term. The singleton control action is based on fuzzy logic with adjustable tuning parameters to approximate the perfect feedback linearization control. The switching control law based on the sliding mode principle aims to minimize the estimation error between approximated single fuzzy control action and perfect feedback linearization control. The proposed control strategy manipulated the airway flow delivered by the ventilator such that the peak pressure will remain under critical values in presence of unknown patient-hose-leak parameters and patient breathing effort. The closed-loop stability of AFSMC will be proven in the sense of Lyapunov. For comparative analysis, classical PID and sliding mode controllers are also designed and implemented for mechanical ventilation problems. For performance analysis, numerical simulations were performed on a mechanical ventilator simulator. Simulation results reveal that the proposed controller demonstrates better tracking of targeted airway pressure compared with its counterparts in terms of faster convergence, less overshoot, and small tracking error. Hence, the proposed controller provides useful insight for its application to real-world scenarios.

The world has been facing the COVID-19 pandemic since December 2019. Timely and efficient diagnosis of COVID-19 suspected patients plays a significant role in medical treatment. The deep transfer learning-based automated COVID-19 diagnosis on chest X-ray is required to counter the COVID-19 outbreak. This work proposes a real-time Internet of Things (IoT) framework for early diagnosis of suspected COVID-19 patients by using ensemble deep transfer learning. The proposed framework offers real-time communication and diagnosis of COVID-19 suspected cases. The proposed IoT framework ensembles four deep learning models such as InceptionResNetV2, ResNet152V2, VGG16, and DenseNet201. The medical sensors are utilized to obtain the chest X-ray modalities and diagnose the infection by using the deep ensemble model stored on the cloud server. The proposed deep ensemble model is compared with six well-known transfer learning models over the chest X-ray dataset. Comparative analysis revealed that the proposed model can help radiologists to efficiently and timely diagnose the COVID-19 suspected patients.

This paper presents the implementation of a fuzzy proportional integral derivative (FPID) control design to track the airway pressure during the mechanical ventilation process. A respiratory system is modeled as a combination of a blower-hose-patient system and a single compartmental lung system with nonlinear lung compliance. For comparison purposes, the classical PID controller is also designed and simulated on the same system. According to the proposed control strategy, the ventilator will provide airway flow that maintains the peak pressure below critical levels when there are unknown parameters of the patient’s hose leak and patient breathing effort. Results show that FPID is a better controller in the sense of quicker response, lower overshoot, and smaller tracking error. This provides valuable insight for the application of the proposed controller.

Today, there is a large increase in the demand for electricity. The transmission and distribution networks, however, cannot fulfill unbound demands due to the scarcity of resources. Power lines have losses which make the situation more unfavorable for maximum power transfer. Implementing a flexible AC transmission system (FACTS) is one of the best ways to reduce line losses. This paper proposes a FACTS-based method for minimizing the fault current in the system. Switchgear and protection equipment also perform better when this is done. Moreover, due to the reduced fault current of the switched system, a larger amount of power can be transmitted. Static synchronous series compensator (SSSC), static synchronous compensator (STATCOM), and unified power flow controller (UPFC) are evaluated in this case. With STATCOM and UPFC, fault currents are significantly reduced. Furthermore, STATCOM and UPFC can also reduce the fault currents in the power system in addition to voltage regulation and power flow control. A MATLAB/Simulink model is used to evaluate the model’s feasibility.

Using electronic coordinated control of governor and blade in the wind integrated hybrid power system, this study evaluated four proposed techniques for minimizing output fluctuations owing to high wind power penetration. Four cases were investigated for simulation analysis in this study. The power system frequency and energy generation were used as indexes to evaluate the best-proposed techniques. The control of all wind turbine blade angles was demonstrated using a constant and variable reference power generating technique. In terms of wind farm output power characteristics, grid frequency fluctuations, and wind farm energy levels, case 2 performed better than other suggested systems (cases 1, 3, and 4). Frequency deviations were kept to a minimum of ±0.2 Hz. The performance of the power system with higher wind power penetration was investigated using a numerical analysis employing a multi-machine power system model. The real wind speed data were recorded on Hokkaido Island, Japan.

Recently, InGaN grown on semipolar and non-polar orientation has caused special attraction due to reduction in the built-in polarization field and increased confinement of high energy states compared to traditional polar c-plane orientation. However, any widespread-accepted report on output power and frequency response of the InGaN blue laser in non-c-plane orientation is readily unavailable. This work strives to address an exhaustive numerical investigation into the optoelectronic performance and frequency response of In0.17Ga0.83N/GaN quantum well laser in polar (0001), non-polar (101&macr, 0) and semipolar (101&macr, 2), (112&macr, 2) and (101&macr, 1) orientations by working out a 6 &times, 6 k.p Hamiltonian at the &Gamma, point using the tensor rotation technique. It is noticed that there is a considerable dependency of the piezoelectric field, energy band gap, peak optical gain, differential gain and output power on the modification in crystal orientation. Topmost optical gain of 4367 cm&minus, 1 is evaluated in the semipolar (112&macr, 2)-oriented laser system at an emission wavelength of 448 nm when the injection carrier density is 3.7 &times, 1018 cm&minus, 3. Highest lasing power and lowest threshold current are reported to be 4.08 mW and 1.45 mA in semipolar (112&macr, 2) crystal orientation. A state-space model is formed in order to achieve the frequency response which indicates the highest magnitude (dB) response in semipolar (112&macr, 2) crystal orientation.

In this article, a Quasi D-Shape dual core Photonic Crystal Fiber Surface Plasmon Resonance sensor is offered and numerically analyzed. The offered model is established comprising of circular air holes having an external sensing polishing layer coated with gold (Au) in order to ensure simple and straightforward design. The performance parameters are examined by means of modal analysis incorporated finite element method utilizing COMSOL multiphysics software. The sensor performance is analyzed with modifying the geometrical parameters like metal (Au) layer and pitch. It is observed; this model shows maximum amplitude sensitivity of 230 RIU−1 and wavelength sensitivity of 15,000 nm-RIU−1 incorporating amplitude interrogation method and wavelength interrogation method, respectively. The Figure of Merit is similarly considered and measured to 45 per RIU inbetween the refractive index ranging 1.42 RIU to 1.46 RIU. As a final point, a comparison has been given among the work explained in this paper with existing works.

In recent years, wind energy has been widely used as an alternative energy source as it is a clean energy with a low running cost. However, the high penetration of wind power (WP) in power networks has created major challenges due to their intermittency. In this study, an elitist multi-objective evolutionary algorithm called non-dominated sorting particle swarm optimization (NSPSO) is proposed to solve the dynamic economic emission dispatch (DEED) problem with WP. The proposed optimization technique referred to as NSPSO uses the non-dominated sorting principle to rank the non-dominated solutions. A crowding distance calculation is added at the end of all iterations of the algorithm. In this study, WP is represented by a chance-constraint which describes the probability that the power balance cannot be met. The uncertainty of WP is described by the Weibull distribution function. In this study, the chance constraint DEED problem is converted into a deterministic problem. Then, the NSPSO is applied to simultaneously minimize the total generation cost and emission of harmful gases. To proof the performance of the proposed method, the ten-unit and forty-unit systems&mdash, including wind farms&mdash, are used. Simulation results obtained by the NSPSO method are compared with other optimization techniques that were presented recently in the literature. Moreover, the impact of the penetration ratio of WP is investigated.

An analytical model has been developed to investigate the activation energy profile in Mg-doped p-AlxGa1−xN alloy for the entire range of Al composition. For any Al content, the calculated activation energy quantitatively shows a good agreement with experimental result which has also been confirmed by both Hydrogen atom model and effective Bohr radius model. Through this empirical analysis, a breakthrough is apparent for the hole concentration and sheet resistivity with particular Al concentration. It is found that the hole concentration is 30% in p-AlxGa1-xN. Moreover, the sheet resistivity is found to be

In the current study, a novel Zeonex based porous core photonic crystal fiber (PC-PCF) is presented for polarization-maintaining and dispersion flattened in the terahertz (THz) region. For minimizing the Effective Material Loss (EML), an array of three rectangular and six triangular air holes are surrounded by hexagonal-shaped cladding. Finite Element Method (FEM) is employed through Comsol V5.3a software to design and examine the essential features of the proposed porous core fiber which revealed that it has an extremely small EML of 0.04 cm−1 at 1.2 THz and has almost zero flattened dispersion of 0.8 ± 0.08 ps/THz/cm in 1.0–1.4 THz frequency spectrum. Moreover, the optimum designing parameters offer an extremely high value of birefringence (0.043 at 1.2 THz). Besides, other major features notably bending loss, effective area, and confinement loss are also found to be precise and relatively low. For effective, adaptable and fitting transmission characteristics, this type of design would lay the foundations for broadband THz radiation wide variety of usage in the THz regime.