Lightweight deep learning models are increasingly required in resource-constrained environments such as mobile devices and the Internet of Medical Things(IoMT).Multi-head convolution with channel attention can facilit...Lightweight deep learning models are increasingly required in resource-constrained environments such as mobile devices and the Internet of Medical Things(IoMT).Multi-head convolution with channel attention can facilitate learning activations relevant to different kernel sizes within a multi-head convolutional layer.Therefore,this study investigates the capability of novel lightweight models incorporating residual multi-head convolution with channel attention(ResMHCNN)blocks to classify medical images.We introduced three novel lightweight deep learning models(BT-Net,LCC-Net,and BC-Net)utilizing the ResMHCNN block as their backbone.These models were crossvalidated and tested on three publicly available medical image datasets:a brain tumor dataset from Figshare consisting of T1-weighted magnetic resonance imaging slices of meningioma,glioma,and pituitary tumors;the LC25000 dataset,which includes microscopic images of lung and colon cancers;and the BreaKHis dataset,containing benign and malignant breast microscopic images.The lightweight models achieved accuracies of 96.9%for 3-class brain tumor classification using BT-Net,and 99.7%for 5-class lung and colon cancer classification using LCC-Net.For 2-class breast cancer classification,BC-Net achieved an accuracy of 96.7%.The parameter counts for the proposed lightweight models—LCC-Net,BC-Net,and BT-Net—are 0.528,0.226,and 1.154 million,respectively.The presented lightweight models,featuring ResMHCNN blocks,may be effectively employed for accurate medical image classification.In the future,these models might be tested for viability in resource-constrained systems such as mobile devices and IoMT platforms.展开更多
The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigatio...The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigation.AUV dynamics are highly nonlinear and time-varying,facing unpredictable disturbances due to AUVs operating in deep,hazardous oceanic environments.Consequently,navigation guidance and control systems for AUVs must learn and adapt to the time-varying dynamics of the nonlinear fully coupled vehicle model in the presence of highly unstructured underwater operating conditions.Many control engineers focus on the application of robust model-free adaptive control techniques in AUV maneuvers.Hence,the main goal is to design a novel salp swarm optimization of super twisting algorithm-based secondorder sliding mode controller for the planar path-following control of an AUV through regulation of the heading angle parameter.The finite time for tracking error convergence in the horizontal plane is provided through the control structure architecture,particularly for lateral deviations from the desired path.The proposed control law is designed such that it steers a robotic vehicle to track a predefined planar path at a constant speed determined by an end-user,without any temporal specification.Finally,the efficacy and tracking accuracy are evaluated through comparative analysis based on simulation and experimental hardware-in-loop assessment without violating the input constraints.Moreover,the proposed control law can handle parametric uncertainties and unpredictable disturbances such as ocean currents,wind,and measurement noise.展开更多
Deep learning(DL),derived from the domain of Artificial Neural Networks(ANN),forms one of the most essential components of modern deep learning algorithms.DL segmentation models rely on layer-by-layer convolution-base...Deep learning(DL),derived from the domain of Artificial Neural Networks(ANN),forms one of the most essential components of modern deep learning algorithms.DL segmentation models rely on layer-by-layer convolution-based feature representation,guided by forward and backward propagation.Acritical aspect of this process is the selection of an appropriate activation function(AF)to ensure robustmodel learning.However,existing activation functions often fail to effectively address the vanishing gradient problem or are complicated by the need for manual parameter tuning.Most current research on activation function design focuses on classification tasks using natural image datasets such asMNIST,CIFAR-10,and CIFAR-100.To address this gap,this study proposesMed-ReLU,a novel activation function specifically designed for medical image segmentation.Med-ReLU prevents deep learning models fromsuffering dead neurons or vanishing gradient issues.It is a hybrid activation function that combines the properties of ReLU and Softsign.For positive inputs,Med-ReLU adopts the linear behavior of ReLU to avoid vanishing gradients,while for negative inputs,it exhibits the Softsign’s polynomial convergence,ensuring robust training and avoiding inactive neurons across the training set.The training performance and segmentation accuracy ofMed-ReLU have been thoroughly evaluated,demonstrating stable learning behavior and resistance to overfitting.It consistently outperforms state-of-the-art activation functions inmedical image segmentation tasks.Designed as a parameter-free function,Med-ReLU is simple to implement in complex deep learning architectures,and its effectiveness spans various neural network models and anomaly detection scenarios.展开更多
The crystal structure of L-glutamine is stabilized by a three-dimensional network of intermolecular hydrogen bonds.We utilize plane-wave density functional theory lattice-dynamics calculations within the generalized-g...The crystal structure of L-glutamine is stabilized by a three-dimensional network of intermolecular hydrogen bonds.We utilize plane-wave density functional theory lattice-dynamics calculations within the generalized-gradient approximation（GGA）, Perdew–Burke–Ernzerhof（PBE）, PBE for solids（PBEsol）, PBE with Wu–Cohen exchange（WC）, and dispersion-corrected PBE, to investigate the effect of these intermolecular contacts on the absorption spectra of glutamine in the terahertz frequency range. Among these calculations, the solid-state simulated results obtained using the WC method exhibit a good agreement with the measured absorption spectra, and the absorption features are assigned with the help of WC. This indicates that the vibrational modes of glutamine were related to the combination of intramolecular and intermolecular motions, the intramolecular modes were dominated by rocking or torsion involving functional groups; the intermolecular modes mainly result from the translational motions of individual molecules, and the rocking of the hydrogenbonded functional groups.展开更多
3C-SiC is a promising structural material for piezoresistive sensors used in high-temperature applications. For sensor development, the preparation of sensor materials and study of its electrical properties, such as r...3C-SiC is a promising structural material for piezoresistive sensors used in high-temperature applications. For sensor development, the preparation of sensor materials and study of its electrical properties, such as resistivity, barrier height of grain boundaries, and temperature coefficient of resistivity, are important in addition to structural properties and these have to be optimized. In the present work, 3C-SiC thin film with in situ doping of nitrogen is prepared through low- pressure chemical vapor deposition by using methyl trichloro silane, ammonia, and hydrogen as precursors. Electrical properties of deposited 3C-SiC thin films with varying nitrogen doping concentration through four probe technique are studied. Atomic force microscopy investigations are carried out to study the grain size on and average root-mean-squared roughness 3C-SiC thin films. A decrease in the degree of crystallinity is observed in nitrogen-doped 3C-SiC thin films. The sheet resistivity of nitrogen-doped 3C-SiC thin film is found to decrease with increase in temperature in the range from 303 to 823 K. The sheet resistivity, average temperature coefficient of resistance, and barrier height of the grain boundaries of film doped with 17 at.% of nitrogen are 0.14 cm, -1.0 x 10-n/K, and 0.01 eV, respectively. Comparing all the nitrogen-doped 3C-SiC thin films, the film doped with 17 at.% of nitrogen exhibits an improved structural and electrical properties and it can be used as sensing material for high-temperature applications.展开更多
TiO2thin films with 0.2 wt%, 0.4 wt%, 0.6wt%, and 0.8 wt% Fe were prepared on glass and silicon substrates using sol–gel spin coating technique. The optical cut-off points are increasingly red-shifted and the absorpt...TiO2thin films with 0.2 wt%, 0.4 wt%, 0.6wt%, and 0.8 wt% Fe were prepared on glass and silicon substrates using sol–gel spin coating technique. The optical cut-off points are increasingly red-shifted and the absorption edge is shifted over the higher wavelength region with Fe content increasing. As Fe content increases, the optical band gap decreases from 3.03 to 2.48 eV whereas the tail width increases from 0.26 to 1.43 eV. The X-ray diffraction（XRD） patterns for doped films at 0.2 wt% and0.8 wt% Fe reveal no characteristic peaks, indicating that the film is amorphous whereas undoped TiO2exhibits（101） orientation with anatase phase. Thin films of higher Fe content exhibit a homogeneous, uniform, and nanostructured highly porous shell morphology.展开更多
Chlorophenols, typically 4-chlorophenols are highly toxic and non-biodegradable organic contaminants which pose serious threat to the environment, particularly when released into aqueous medium. The removal of these p...Chlorophenols, typically 4-chlorophenols are highly toxic and non-biodegradable organic contaminants which pose serious threat to the environment, particularly when released into aqueous medium. The removal of these pollutants by efficient method has received worldwide concern in recent past. A new Fe3O4–Cr2O3 magnetic nanocomposite was synthesized by wet chemical method under ultrasonic irradiation. Microstructure and morphology of the nanocomposite were characterized by powder X-ray diffraction（XRD）,Fourier transform infrared（FT-IR）, and a transmission electron microscope（TEM）. Magnetic and optical properties were studied by a vibrating sample magnetometer（VSM） and an ultraviolet–visible（UV–Vis） spectrophotometer respectively. The magnetic nanocomposite（MNC） was used as photocatalyst for effective decomposition of 4-chlorophenol in water under ultraviolet（UV） irradiation.展开更多
The effect of substrate and annealing temperatures on mechanical properties of Ti-rich NiTi films deposited on Si （100） substrates by DC magnetron sputtering was studied by nanoindentation.NiTi films were deposited ...The effect of substrate and annealing temperatures on mechanical properties of Ti-rich NiTi films deposited on Si （100） substrates by DC magnetron sputtering was studied by nanoindentation.NiTi films were deposited at two substrate temperatures viz.300 and 400 ℃.NiTi films deposited at 300 ℃ were annealed for 4 h at four different temperatures,i.e.300,400,500 and 600 C whereas films deposited at 400 ℃ were annealed for 4 h at three different temperatures,i.e.400,500 and 600 ℃.The elastic modulus and hardness of the films were found to be the same in the as-deposited as well as annealed conditions for both substrate temperatures.For a given substrate temperature,the hardness and elastic modulus were found to remain unchanged as long as the films were amorphous.However,both elastic modulus and hardness showed an increase with increasing annealing temperature as the films become crystalline.The results were explained on the basis of the change in microstructure of the film with change in annealing temperature.展开更多
A mathematical model based on the computational fluid dynamics method,heat and mass transfer in porous media and the unreacted shrinking core model for the oxidation reaction of an individual magnetite pellet during p...A mathematical model based on the computational fluid dynamics method,heat and mass transfer in porous media and the unreacted shrinking core model for the oxidation reaction of an individual magnetite pellet during preheating was established.The commercial software COMSOL Multiphysics was used to simulate the change in the oxidation degree of the pellet at different temperatures and oxygen concentrations,and the simulated results were compared with the exper-imental results.The model considered the influence of the exothermic heat of the reaction,and the enthalpy change was added to calculate the heat released by the oxidation.The results show that the oxidation rate on the surface of the pellet is much faster than that of the inside of the pellet.Temperature and oxygen concentration have great influence on the pellet oxidation model.Meanwhile,the exothermic calculation results show that there is a non-isothermal phenomenon inside the pellet,which leads to an increase in temperature inside the single pellet.Under the preheating condition of 873-1273 K(20%oxygen content),the heat released by the pellet oxidation reaction in a chain grate is 7.8×10^(6)-10.8×10^(6) kJ/h,which is very large and needs to be considered in the magnetite pellet oxidation modelling.展开更多
The design and development of a timer based revolution per minute(RPM)measurement system were described in this paper.The rotating shaft of a dc motor was used to measure the RPM and timer integrated circuit(IC)555 wa...The design and development of a timer based revolution per minute(RPM)measurement system were described in this paper.The rotating shaft of a dc motor was used to measure the RPM and timer integrated circuit(IC)555 was used in astable mode.The frequency of timer output waveform measured by a digital storage oscilloscope(DSO)is almost linearly proportional to the RPM of rotating shaft,and the RPM also linearly varies with the change of the external input voltage level.Hence the linear relationship between the frequency of timer output waveform and the RPM can be obtained.The main advantages of this developed system are linear input-output relationship,small size,easy to carry and cost effective.展开更多
Commercial off-the-shelf(COTS) ADCs(analog-to-digital converters) that are radiation-tolerant, high speed,high density and low power will be used in upgrading the LAr(liquid argon) calorimeter front end(FE) trigger re...Commercial off-the-shelf(COTS) ADCs(analog-to-digital converters) that are radiation-tolerant, high speed,high density and low power will be used in upgrading the LAr(liquid argon) calorimeter front end(FE) trigger readout electronics. Total ionization dose(TID) and single event effect(SEE) of the COTS ADCs should be characterized. In our initial TID test, 17 COTS ADCs from different manufacturers with dynamic range and sampling rate meeting requirements of the FE electronics were checked, and the ADS5272 of Texas Instruments(TI) was the best performer of all. Another interesting feature of ADS5272 is its 6.5 clock cycles latency, which is the shortest of all the 17 candidates. Based on the TID performance, we designed an SEE evaluation system for ADS5272, which allows us to further assess its radiation tolerance. In this paper, we present a detailed design of ADS5272 SEE evaluation system and show the effectiveness of this system while evaluating ADS5272 SEE characteristics in multiple irradiation tests. According to TID and SEE test results, ADS5272 was chosen to be implemented in the full-size LAr Trigger Digitizer Board(LTDB) demonstrator, which will be installed on ATLAS calorimeter during the 2014 Long Shutdown 1(LS1).展开更多
This article first generalizes the basic engineering phases of modern rapid prototyping processes, and then describes the techniques of data capture for data modeling and model making. The article also provides a brie...This article first generalizes the basic engineering phases of modern rapid prototyping processes, and then describes the techniques of data capture for data modeling and model making. The article also provides a brief overview of the photogrametric techniques of restitution of 3D objects, and highlights the difficulties and limitations of existing methods. It therefore presents a novel approach to photo-modeling for acquiring 3D model data from single 2D photorealistic images. Implementation of the approach is then described against a effectiveness of photo-modeling practice. background of rapid prototyping processes to demonstrate the展开更多
The present investigation attempts to quantify the temporal variation of Solar Flare Index(SFI)with other activity indices during solar cycles 21-24 by using different techniques such as linear regression,correlation,...The present investigation attempts to quantify the temporal variation of Solar Flare Index(SFI)with other activity indices during solar cycles 21-24 by using different techniques such as linear regression,correlation,cross-correlation with phase lag-lead,etc.Different Solar Activity Indices(SAI)considered in this present study are Sunspot Number(SSN),10.7 cm Solar Radio Flux(F10.7),Coronal Index(CI)and MgⅡCore-to-Wing Ratio(MgⅡ).The maximum cycle amplitude of SFI and considered SAI has a decreasing trend from solar cycle 22,and cycle 24 is the weakest solar cycle among all other cycles.The SFI with SSN,F10.7,CI and MgⅡshows hysteresis during all cycles except for solar cycle 22 where both paths for ascending and descending phases are intercepting each other,thereby representing a phase reversal.A positive hysteresis circulation exists between SFI and considered SAI during solar cycles 22 and 23,whereas a negative circulation exists in cycles 21 and 24.SFI has a high positive correlation with coefficient values of 0.92,0.94,0.84 and 0.81 for SSN,F10.7,CI and MgⅡrespectively.According to crosscorrelation analysis,SFI has a phase lag with considered SAI during an odd-number solar cycle(solar cycles21 and 23)but no phase lag/lead during an even-numbered solar cycle(solar cycles 22 and 24).However,the entire smoothed monthly average SFI data indicate an in-phase relationship with SSN,F10.7 and MgⅡ,and a one-month phase lag with CI.The presence of those above characteristics strongly confirms the outcomes of different research work with various solar indices and the highest correlation exists between SFI and SSN as well as F10.7 which establishes that SFI may be considered as one of the prime activity indices to interpret the characteristics of the Sun’s active region as well as for more accurate short-range or long-range forecasting of solar events.展开更多
In this paper, it is shown that for low-order uncertain systems, there is no need to calculate all the minimum and maximum values of the coefficients for a perturbed system which is expressed in terms of polynomials a...In this paper, it is shown that for low-order uncertain systems, there is no need to calculate all the minimum and maximum values of the coefficients for a perturbed system which is expressed in terms of polynomials and hence no need to formulate and test all the four Kharitonov＇s polynomials. Furthermore, for higher-order systems such as n ≥ 5, the usual four Kharitonov＇s polynomials need not be tested initially for sufficient condition of perturbed systems; rather, the necessary condition can be checked before going for sufficient condition. In order to show the effectiveness of the proposed method, numerical examples are shown and computational efficiency is highlighted.展开更多
The COVID-19 outbreak initiated from the Chinese city of Wuhanand eventually affected almost every nation around the globe. From China,the disease started spreading to the rest of the world. After China, Italybecame t...The COVID-19 outbreak initiated from the Chinese city of Wuhanand eventually affected almost every nation around the globe. From China,the disease started spreading to the rest of the world. After China, Italybecame the next epicentre of the virus and witnessed a very high death toll.Soon nations like the USA became severely hit by SARS-CoV-2 virus. TheWorld Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the worldhas instituted various policies like physical distancing, isolation of infectedpopulation and researching on the potential vaccine of SARS-CoV-2. Toidentify the impact of various policies implemented by the affected countrieson the pandemic spread, a myriad of AI-based models have been presented toanalyse and predict the epidemiological trends of COVID-19. In this work, theauthors present a detailed study of different articial intelligence frameworksapplied for predictive analysis of COVID-19 patient record. The forecastingmodels acquire information from records to detect the pandemic spreadingand thus enabling an opportunity to take immediate actions to reduce thespread of the virus. This paper addresses the research issues and correspondingsolutions associated with the prediction and detection of infectious diseaseslike COVID-19. It further focuses on the study of vaccinations to cope withthe pandemic. Finally, the research challenges in terms of data availability,reliability, the accuracy of the existing prediction models and other open issuesare discussed to outline the future course of this study.展开更多
Fuel is a very important factor and has considerable influence on the air quality in the environment,which is the heart of the world.The increase of vehi-cles in lived-in areas results in greater emission of carbon par...Fuel is a very important factor and has considerable influence on the air quality in the environment,which is the heart of the world.The increase of vehi-cles in lived-in areas results in greater emission of carbon particles in the envir-onment.Adulterated fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous pollution.Adulteration is the mixing of foreign substances in fuel,which damages vehicles and causes more health problems in living beings such as humans,birds,aquatic life,and even water resources by emitting high levels of hydrocarbons,nitrogen oxides,and carbon monoxide.Most frequent blending liquids are lubricants and kerosene in the petrol,and its adulteration is a considerable problem that adds to environ-mental pollution.This study focuses on detecting the adulteration in petrol using sensors and machine learning algorithms.A modified evanescent wave opticalfiber sensor with discrete wavelet transform is proposed for classification of adult-erated data from the samples.Furthermore,support vector machine classifier is used for accurate categorization.The sensor isfirst tested with fuel and numerical data is classified based on machine learning algorithms.Finally,the result is eval-uated with less error and high accuracy of 99.9%,which is higher than all existing techniques.展开更多
Unmanned Aerial Vehicles(UAVs)or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance,due to their ability to perform repetitive and tedi...Unmanned Aerial Vehicles(UAVs)or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance,due to their ability to perform repetitive and tedious tasks in hazardous environments.Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional(3D)flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature.However,not a single optimization algorithms can solve all kind of optimization problem effectively.Therefore,there is dire need to integrate metaheuristic for general acceptability.To address this issue,in this paper,a novel reinforcement learning controlled Grey Wolf Optimisation-Archimedes Optimisation Algorithm(QGA)has been exhaustively introduced and exhaustively validated firstly on 22 benchmark functions and then,utilized to obtain the optimum flyable path without collision for UAVs in three dimensional environment.The performance of the developed QGA has been compared against the various metaheuristics.The simulation experimental results reveal that the QGA algorithm acquire a feasible and effective flyable path more efficiently in complicated environment.展开更多
In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheel...In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.展开更多
Simulation of stress intensity factor as function of rolling contact fatigue cracks of railway tracks and the vehicle load is made with the help of COMSOL Multiphysics software. It is found that the critical stress in...Simulation of stress intensity factor as function of rolling contact fatigue cracks of railway tracks and the vehicle load is made with the help of COMSOL Multiphysics software. It is found that the critical stress intensity factor i.e. 41.6 MPa. m1/2 is reached at a stress level of 32 MPa and at the crack size 11.5 × 10-2 m.Noting the power law variation of acoustic emission count with increase in crack size (analogous to Paris Law), the simulation was further carried out to model the dependence of measured AE count with the stress intensity factor ahead of a growing RCF crack tip. It is demonstrated that AE measurement can be effective to trigger a control loop for avoidance of fatigue failure of railway track. In view of potential difference in the intensity of back scattered light from surface irregularities, a model is developed to find out the threshold intensity of scattered light that insures safety in the railway system against fatigue failure.展开更多
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)-Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2023-00259678)by INHA UNIVERSITY Research Grant.
文摘Lightweight deep learning models are increasingly required in resource-constrained environments such as mobile devices and the Internet of Medical Things(IoMT).Multi-head convolution with channel attention can facilitate learning activations relevant to different kernel sizes within a multi-head convolutional layer.Therefore,this study investigates the capability of novel lightweight models incorporating residual multi-head convolution with channel attention(ResMHCNN)blocks to classify medical images.We introduced three novel lightweight deep learning models(BT-Net,LCC-Net,and BC-Net)utilizing the ResMHCNN block as their backbone.These models were crossvalidated and tested on three publicly available medical image datasets:a brain tumor dataset from Figshare consisting of T1-weighted magnetic resonance imaging slices of meningioma,glioma,and pituitary tumors;the LC25000 dataset,which includes microscopic images of lung and colon cancers;and the BreaKHis dataset,containing benign and malignant breast microscopic images.The lightweight models achieved accuracies of 96.9%for 3-class brain tumor classification using BT-Net,and 99.7%for 5-class lung and colon cancer classification using LCC-Net.For 2-class breast cancer classification,BC-Net achieved an accuracy of 96.7%.The parameter counts for the proposed lightweight models—LCC-Net,BC-Net,and BT-Net—are 0.528,0.226,and 1.154 million,respectively.The presented lightweight models,featuring ResMHCNN blocks,may be effectively employed for accurate medical image classification.In the future,these models might be tested for viability in resource-constrained systems such as mobile devices and IoMT platforms.
文摘The path-following control design for an autonomous underwater vehicle(AUV)requires prior full or partial knowledge about the mathematical model defined through Newton’s second law based on a geometrical investigation.AUV dynamics are highly nonlinear and time-varying,facing unpredictable disturbances due to AUVs operating in deep,hazardous oceanic environments.Consequently,navigation guidance and control systems for AUVs must learn and adapt to the time-varying dynamics of the nonlinear fully coupled vehicle model in the presence of highly unstructured underwater operating conditions.Many control engineers focus on the application of robust model-free adaptive control techniques in AUV maneuvers.Hence,the main goal is to design a novel salp swarm optimization of super twisting algorithm-based secondorder sliding mode controller for the planar path-following control of an AUV through regulation of the heading angle parameter.The finite time for tracking error convergence in the horizontal plane is provided through the control structure architecture,particularly for lateral deviations from the desired path.The proposed control law is designed such that it steers a robotic vehicle to track a predefined planar path at a constant speed determined by an end-user,without any temporal specification.Finally,the efficacy and tracking accuracy are evaluated through comparative analysis based on simulation and experimental hardware-in-loop assessment without violating the input constraints.Moreover,the proposed control law can handle parametric uncertainties and unpredictable disturbances such as ocean currents,wind,and measurement noise.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘Deep learning(DL),derived from the domain of Artificial Neural Networks(ANN),forms one of the most essential components of modern deep learning algorithms.DL segmentation models rely on layer-by-layer convolution-based feature representation,guided by forward and backward propagation.Acritical aspect of this process is the selection of an appropriate activation function(AF)to ensure robustmodel learning.However,existing activation functions often fail to effectively address the vanishing gradient problem or are complicated by the need for manual parameter tuning.Most current research on activation function design focuses on classification tasks using natural image datasets such asMNIST,CIFAR-10,and CIFAR-100.To address this gap,this study proposesMed-ReLU,a novel activation function specifically designed for medical image segmentation.Med-ReLU prevents deep learning models fromsuffering dead neurons or vanishing gradient issues.It is a hybrid activation function that combines the properties of ReLU and Softsign.For positive inputs,Med-ReLU adopts the linear behavior of ReLU to avoid vanishing gradients,while for negative inputs,it exhibits the Softsign’s polynomial convergence,ensuring robust training and avoiding inactive neurons across the training set.The training performance and segmentation accuracy ofMed-ReLU have been thoroughly evaluated,demonstrating stable learning behavior and resistance to overfitting.It consistently outperforms state-of-the-art activation functions inmedical image segmentation tasks.Designed as a parameter-free function,Med-ReLU is simple to implement in complex deep learning architectures,and its effectiveness spans various neural network models and anomaly detection scenarios.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61302007 and 60977065)the Fundamental Research Funds for the Central Universities of China(Grant No.FRF-SD-12-016A)the Engineering Research Center of Industrial Spectrum Imaging of Beijing,China
文摘The crystal structure of L-glutamine is stabilized by a three-dimensional network of intermolecular hydrogen bonds.We utilize plane-wave density functional theory lattice-dynamics calculations within the generalized-gradient approximation（GGA）, Perdew–Burke–Ernzerhof（PBE）, PBE for solids（PBEsol）, PBE with Wu–Cohen exchange（WC）, and dispersion-corrected PBE, to investigate the effect of these intermolecular contacts on the absorption spectra of glutamine in the terahertz frequency range. Among these calculations, the solid-state simulated results obtained using the WC method exhibit a good agreement with the measured absorption spectra, and the absorption features are assigned with the help of WC. This indicates that the vibrational modes of glutamine were related to the combination of intramolecular and intermolecular motions, the intramolecular modes were dominated by rocking or torsion involving functional groups; the intermolecular modes mainly result from the translational motions of individual molecules, and the rocking of the hydrogenbonded functional groups.
文摘3C-SiC is a promising structural material for piezoresistive sensors used in high-temperature applications. For sensor development, the preparation of sensor materials and study of its electrical properties, such as resistivity, barrier height of grain boundaries, and temperature coefficient of resistivity, are important in addition to structural properties and these have to be optimized. In the present work, 3C-SiC thin film with in situ doping of nitrogen is prepared through low- pressure chemical vapor deposition by using methyl trichloro silane, ammonia, and hydrogen as precursors. Electrical properties of deposited 3C-SiC thin films with varying nitrogen doping concentration through four probe technique are studied. Atomic force microscopy investigations are carried out to study the grain size on and average root-mean-squared roughness 3C-SiC thin films. A decrease in the degree of crystallinity is observed in nitrogen-doped 3C-SiC thin films. The sheet resistivity of nitrogen-doped 3C-SiC thin film is found to decrease with increase in temperature in the range from 303 to 823 K. The sheet resistivity, average temperature coefficient of resistance, and barrier height of the grain boundaries of film doped with 17 at.% of nitrogen are 0.14 cm, -1.0 x 10-n/K, and 0.01 eV, respectively. Comparing all the nitrogen-doped 3C-SiC thin films, the film doped with 17 at.% of nitrogen exhibits an improved structural and electrical properties and it can be used as sensing material for high-temperature applications.
文摘TiO2thin films with 0.2 wt%, 0.4 wt%, 0.6wt%, and 0.8 wt% Fe were prepared on glass and silicon substrates using sol–gel spin coating technique. The optical cut-off points are increasingly red-shifted and the absorption edge is shifted over the higher wavelength region with Fe content increasing. As Fe content increases, the optical band gap decreases from 3.03 to 2.48 eV whereas the tail width increases from 0.26 to 1.43 eV. The X-ray diffraction（XRD） patterns for doped films at 0.2 wt% and0.8 wt% Fe reveal no characteristic peaks, indicating that the film is amorphous whereas undoped TiO2exhibits（101） orientation with anatase phase. Thin films of higher Fe content exhibit a homogeneous, uniform, and nanostructured highly porous shell morphology.
基金support from Central Instruments Facility and Department of Chemistry of Indian Institute of Technology Guwahati for extending various analytical facilities during the course of investigation
文摘Chlorophenols, typically 4-chlorophenols are highly toxic and non-biodegradable organic contaminants which pose serious threat to the environment, particularly when released into aqueous medium. The removal of these pollutants by efficient method has received worldwide concern in recent past. A new Fe3O4–Cr2O3 magnetic nanocomposite was synthesized by wet chemical method under ultrasonic irradiation. Microstructure and morphology of the nanocomposite were characterized by powder X-ray diffraction（XRD）,Fourier transform infrared（FT-IR）, and a transmission electron microscope（TEM）. Magnetic and optical properties were studied by a vibrating sample magnetometer（VSM） and an ultraviolet–visible（UV–Vis） spectrophotometer respectively. The magnetic nanocomposite（MNC） was used as photocatalyst for effective decomposition of 4-chlorophenol in water under ultraviolet（UV） irradiation.
基金the support of Defence Research Development Organization under Project DMR-275the support of the National Program on Smart Materials (NPSM)
文摘The effect of substrate and annealing temperatures on mechanical properties of Ti-rich NiTi films deposited on Si （100） substrates by DC magnetron sputtering was studied by nanoindentation.NiTi films were deposited at two substrate temperatures viz.300 and 400 ℃.NiTi films deposited at 300 ℃ were annealed for 4 h at four different temperatures,i.e.300,400,500 and 600 C whereas films deposited at 400 ℃ were annealed for 4 h at three different temperatures,i.e.400,500 and 600 ℃.The elastic modulus and hardness of the films were found to be the same in the as-deposited as well as annealed conditions for both substrate temperatures.For a given substrate temperature,the hardness and elastic modulus were found to remain unchanged as long as the films were amorphous.However,both elastic modulus and hardness showed an increase with increasing annealing temperature as the films become crystalline.The results were explained on the basis of the change in microstructure of the film with change in annealing temperature.
基金the National Natural Science Foundation of China(51675245).
文摘A mathematical model based on the computational fluid dynamics method,heat and mass transfer in porous media and the unreacted shrinking core model for the oxidation reaction of an individual magnetite pellet during preheating was established.The commercial software COMSOL Multiphysics was used to simulate the change in the oxidation degree of the pellet at different temperatures and oxygen concentrations,and the simulated results were compared with the exper-imental results.The model considered the influence of the exothermic heat of the reaction,and the enthalpy change was added to calculate the heat released by the oxidation.The results show that the oxidation rate on the surface of the pellet is much faster than that of the inside of the pellet.Temperature and oxygen concentration have great influence on the pellet oxidation model.Meanwhile,the exothermic calculation results show that there is a non-isothermal phenomenon inside the pellet,which leads to an increase in temperature inside the single pellet.Under the preheating condition of 873-1273 K(20%oxygen content),the heat released by the pellet oxidation reaction in a chain grate is 7.8×10^(6)-10.8×10^(6) kJ/h,which is very large and needs to be considered in the magnetite pellet oxidation modelling.
文摘The design and development of a timer based revolution per minute(RPM)measurement system were described in this paper.The rotating shaft of a dc motor was used to measure the RPM and timer integrated circuit(IC)555 was used in astable mode.The frequency of timer output waveform measured by a digital storage oscilloscope(DSO)is almost linearly proportional to the RPM of rotating shaft,and the RPM also linearly varies with the change of the external input voltage level.Hence the linear relationship between the frequency of timer output waveform and the RPM can be obtained.The main advantages of this developed system are linear input-output relationship,small size,easy to carry and cost effective.
基金Supported by the Unites States Department of Energy(No.DE-AC0298CH10886)
文摘Commercial off-the-shelf(COTS) ADCs(analog-to-digital converters) that are radiation-tolerant, high speed,high density and low power will be used in upgrading the LAr(liquid argon) calorimeter front end(FE) trigger readout electronics. Total ionization dose(TID) and single event effect(SEE) of the COTS ADCs should be characterized. In our initial TID test, 17 COTS ADCs from different manufacturers with dynamic range and sampling rate meeting requirements of the FE electronics were checked, and the ADS5272 of Texas Instruments(TI) was the best performer of all. Another interesting feature of ADS5272 is its 6.5 clock cycles latency, which is the shortest of all the 17 candidates. Based on the TID performance, we designed an SEE evaluation system for ADS5272, which allows us to further assess its radiation tolerance. In this paper, we present a detailed design of ADS5272 SEE evaluation system and show the effectiveness of this system while evaluating ADS5272 SEE characteristics in multiple irradiation tests. According to TID and SEE test results, ADS5272 was chosen to be implemented in the full-size LAr Trigger Digitizer Board(LTDB) demonstrator, which will be installed on ATLAS calorimeter during the 2014 Long Shutdown 1(LS1).
基金This work is supported by Cheung Kong Scholars Program of the People's Republic of China, in association with Southeast University, Nanjing, PRC. (No.seuzx042001)
文摘This article first generalizes the basic engineering phases of modern rapid prototyping processes, and then describes the techniques of data capture for data modeling and model making. The article also provides a brief overview of the photogrametric techniques of restitution of 3D objects, and highlights the difficulties and limitations of existing methods. It therefore presents a novel approach to photo-modeling for acquiring 3D model data from single 2D photorealistic images. Implementation of the approach is then described against a effectiveness of photo-modeling practice. background of rapid prototyping processes to demonstrate the
基金the support extended by Jadavpur University,West Bengal Indiaa part of the RUSA 2.0 faculty major research project under Jadavpur University。
文摘The present investigation attempts to quantify the temporal variation of Solar Flare Index(SFI)with other activity indices during solar cycles 21-24 by using different techniques such as linear regression,correlation,cross-correlation with phase lag-lead,etc.Different Solar Activity Indices(SAI)considered in this present study are Sunspot Number(SSN),10.7 cm Solar Radio Flux(F10.7),Coronal Index(CI)and MgⅡCore-to-Wing Ratio(MgⅡ).The maximum cycle amplitude of SFI and considered SAI has a decreasing trend from solar cycle 22,and cycle 24 is the weakest solar cycle among all other cycles.The SFI with SSN,F10.7,CI and MgⅡshows hysteresis during all cycles except for solar cycle 22 where both paths for ascending and descending phases are intercepting each other,thereby representing a phase reversal.A positive hysteresis circulation exists between SFI and considered SAI during solar cycles 22 and 23,whereas a negative circulation exists in cycles 21 and 24.SFI has a high positive correlation with coefficient values of 0.92,0.94,0.84 and 0.81 for SSN,F10.7,CI and MgⅡrespectively.According to crosscorrelation analysis,SFI has a phase lag with considered SAI during an odd-number solar cycle(solar cycles21 and 23)but no phase lag/lead during an even-numbered solar cycle(solar cycles 22 and 24).However,the entire smoothed monthly average SFI data indicate an in-phase relationship with SSN,F10.7 and MgⅡ,and a one-month phase lag with CI.The presence of those above characteristics strongly confirms the outcomes of different research work with various solar indices and the highest correlation exists between SFI and SSN as well as F10.7 which establishes that SFI may be considered as one of the prime activity indices to interpret the characteristics of the Sun’s active region as well as for more accurate short-range or long-range forecasting of solar events.
文摘In this paper, it is shown that for low-order uncertain systems, there is no need to calculate all the minimum and maximum values of the coefficients for a perturbed system which is expressed in terms of polynomials and hence no need to formulate and test all the four Kharitonov＇s polynomials. Furthermore, for higher-order systems such as n ≥ 5, the usual four Kharitonov＇s polynomials need not be tested initially for sufficient condition of perturbed systems; rather, the necessary condition can be checked before going for sufficient condition. In order to show the effectiveness of the proposed method, numerical examples are shown and computational efficiency is highlighted.
文摘The COVID-19 outbreak initiated from the Chinese city of Wuhanand eventually affected almost every nation around the globe. From China,the disease started spreading to the rest of the world. After China, Italybecame the next epicentre of the virus and witnessed a very high death toll.Soon nations like the USA became severely hit by SARS-CoV-2 virus. TheWorld Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the worldhas instituted various policies like physical distancing, isolation of infectedpopulation and researching on the potential vaccine of SARS-CoV-2. Toidentify the impact of various policies implemented by the affected countrieson the pandemic spread, a myriad of AI-based models have been presented toanalyse and predict the epidemiological trends of COVID-19. In this work, theauthors present a detailed study of different articial intelligence frameworksapplied for predictive analysis of COVID-19 patient record. The forecastingmodels acquire information from records to detect the pandemic spreadingand thus enabling an opportunity to take immediate actions to reduce thespread of the virus. This paper addresses the research issues and correspondingsolutions associated with the prediction and detection of infectious diseaseslike COVID-19. It further focuses on the study of vaccinations to cope withthe pandemic. Finally, the research challenges in terms of data availability,reliability, the accuracy of the existing prediction models and other open issuesare discussed to outline the future course of this study.
文摘Fuel is a very important factor and has considerable influence on the air quality in the environment,which is the heart of the world.The increase of vehi-cles in lived-in areas results in greater emission of carbon particles in the envir-onment.Adulterated fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous pollution.Adulteration is the mixing of foreign substances in fuel,which damages vehicles and causes more health problems in living beings such as humans,birds,aquatic life,and even water resources by emitting high levels of hydrocarbons,nitrogen oxides,and carbon monoxide.Most frequent blending liquids are lubricants and kerosene in the petrol,and its adulteration is a considerable problem that adds to environ-mental pollution.This study focuses on detecting the adulteration in petrol using sensors and machine learning algorithms.A modified evanescent wave opticalfiber sensor with discrete wavelet transform is proposed for classification of adult-erated data from the samples.Furthermore,support vector machine classifier is used for accurate categorization.The sensor isfirst tested with fuel and numerical data is classified based on machine learning algorithms.Finally,the result is eval-uated with less error and high accuracy of 99.9%,which is higher than all existing techniques.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R66),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Unmanned Aerial Vehicles(UAVs)or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance,due to their ability to perform repetitive and tedious tasks in hazardous environments.Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional(3D)flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature.However,not a single optimization algorithms can solve all kind of optimization problem effectively.Therefore,there is dire need to integrate metaheuristic for general acceptability.To address this issue,in this paper,a novel reinforcement learning controlled Grey Wolf Optimisation-Archimedes Optimisation Algorithm(QGA)has been exhaustively introduced and exhaustively validated firstly on 22 benchmark functions and then,utilized to obtain the optimum flyable path without collision for UAVs in three dimensional environment.The performance of the developed QGA has been compared against the various metaheuristics.The simulation experimental results reveal that the QGA algorithm acquire a feasible and effective flyable path more efficiently in complicated environment.
文摘In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.
文摘Simulation of stress intensity factor as function of rolling contact fatigue cracks of railway tracks and the vehicle load is made with the help of COMSOL Multiphysics software. It is found that the critical stress intensity factor i.e. 41.6 MPa. m1/2 is reached at a stress level of 32 MPa and at the crack size 11.5 × 10-2 m.Noting the power law variation of acoustic emission count with increase in crack size (analogous to Paris Law), the simulation was further carried out to model the dependence of measured AE count with the stress intensity factor ahead of a growing RCF crack tip. It is demonstrated that AE measurement can be effective to trigger a control loop for avoidance of fatigue failure of railway track. In view of potential difference in the intensity of back scattered light from surface irregularities, a model is developed to find out the threshold intensity of scattered light that insures safety in the railway system against fatigue failure.
