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Go to Editorial ManagerTechnically, medical imaging modalities are quantitative, qualitative, and semi-quantitative. Such modalities can generate meaningful and valuable quantitative and qualitative data. Correlating predictive outcomes with quantitative and qualitative data is a difficult process. Thanks to modern computational hardware and advanced machine learning algorithms, it is not a demanding job to perform predictive analysis by cultivating quantitative and qualitative data. Radiomics is a popular topic that studies quantitative data from medical images in order to obtain biologically meaningful information for diagnosis, prognosis, theragnosis, and decision support. Handcrafted radiomics is a process including features based on shape, pixel, and texture-related knowledge from medical scans. In the pursuit of advancing the field of radiomics, we have developed a cutting-edge radiomics training simulator, powered by MATLAB. This tool has been designed for those familiar with MATLAB, making it easy for them to transition into the fascinating world of radiomics. MATLAB's user-friendly interface and strong support in the engineering community provide an ideal platform for this simulator, ensuring aspiring radiomics learners have access to the resources they need for success. Throughout the paper, purpose, design details and methodology of the simulator are described.
The aim of this work is to use Fiber Bragg Grating (FBG) to detect the breast cancer at its earliest stages based on the Photoacoustic (PA) hybrid technique. The fiber Bragg gratings sensitivity to acoustic wave, effect of grating length, effect of grating refractive index modification, and ultrasonic frequency on the wavelength sensitivity and intensity sensitivity of the ultrasonic sensor (FBG) for ultrasonic waves were investigated using a simulation programs. A wavelength for the photoacoustic (PA) excitation laser was chosen with respect to a high absorption by the tumor and with low absorption to the surrounding tissue (normal tissue); for higher contrast absorption between them. Fiber Bragg can be used as a sensor to detect the acoustic wave emitted from the tumor (depending on the photoacoustic principle). In this study, k-wave a MATLAB toolbox was used to simulate photoacoustic wave which is detected with fiber Bragg grating simulation, using Optisystem program. The acoustic wave was transferred to FBG by using Optisystem-MTLAB communication programs to detect tumors.
The main purpose of this paper is to design a robust second order sliding mode controller that can deal with uncertain nonlinear systems. This controller can keep the main advantages of the first order sliding mode controller, such as the ability to make the system asymptotically stable by forcing the error and its derivatives to have a zero value, the simplicity in the operation, and the robustness in the existence of perturbations. In spite of the features that characterize the first order sliding mode controller (1 SMC), it still suffers from the unwanted phenomenon “chattering”, which originates from a discontinuous control part (sign function). In this context, saturation function can be used instead of sign function to reduce this problematic chattering. Different from the saturation function method, the second order sliding mode controller can be used to overcome the chattering; suffered by the first order sliding mode controller and to retain the stability and performance of the system. In this paper, the twisting and the super twisting second-order algorithms of the sliding mode controller were used, and their results were compared with the first order sliding mode controller. So, this subject focused on the chattering problem who suffers from it the 1 SMC and try to reduce it by using the 2 SMC, the uncertain pendulum system was adopted in this work for the purpose of checking the three controllers. The simulations results showed that the second order sliding mode controller has the ability to reduce both the chattering magnitude and the steady state error and achieve an asymptotically stable system. The results were obtained by using MATLAB programming.
The effect of defect on structures and machines has negative consequences on them and it always takes researchers concern and attention in order to find feasible solutions to trace and detect the location of the defect accurately.In this research, the effect of a hole with different diameters on a square composite plate is studied as well as the effects of both the boundary condition and the plate thickness, furthermore, Vibration analysis of composite plate has been studied numerically and experimentally. The Numerical analysis has been carried out by using FEM by building MATLAB program as well as (ANSYS 15). The experimental part of this research is done by using vibration measuring instruments. The rate of error among the experimental tests and the numerical solution is less than 15%. These results have been used an inputs to the Genetic Algorithm model that the defect is located by, with a high percentage of success.
The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. This paper presents the effect of installing the UPFC on the Iraqi (400 kV) grid transmission system to control the active and reactive power flow by choosing the optimal location and parameters of Unified Power Flow Controllers (UPFCs), which were specified based on the Genetic Algorithm (GA) optimization method. The objectives are improving voltage profile, reducing power losses, treating power flow in overloaded transmission lines, and reducing power generation. The steady state model of UPFC has been adopted on (400 kV) Iraq transmission lines and simulated using the MATLAB programming language. The Newton-Raphson (NR) numerical analysis method has been used for solving the load flow of the system. The practical part has been solved through Power System Simulation for Engineers (PSS\E) software Version 32.0. The Comparative results between the experimental and practical parts obtained from adopting the UPFC were too close and almost the same under different loading conditions, which are (5%, 10%, 15% and 20%) of the total load.
This paper proposes the design and simulation of Interval Type-2 Fuzzy Logic Control using MATLAB/Simulink to control the position of the bucket of the backhoe excavator robot during digging operations. In order to reach accurate position responses with minimum overshoot and minimum steady state error, Ant Colony Optimization (ACO) algorithm is used to tune the gains of the position and force parts for the force-position controllers to obtain the best position responses. The joints are actuated by the electro-hydraulic actuators. The force-position control incorporating two-Mamdani type-Proportional-Derivative-Interval Type-2 Fuzzy Logic Controllers for position control and 3-Proportional-Derivative Controllers for force control. The nonlinearity and uncertainty in the model that inherit in the electro hydraulic actuator system are also studied. The nonlinearity includes oil leakage and frictions in the joints. The friction model is represented as a Modified LuGre friction model in actuators. The excavator robot joints are subjected to Coulomb, viscous and stribeck friction. The uncertainty is represented by the variation of bulk modulus. It can be shown from the results that the ACO obtain the best gains of the controllers which enhances the position responses within the range of (19, 23 %) compared with the controllers tuned manually.
A proposed modern technique for determination the blood group typing by monitoring the agglutination of red blood cells using acousto-optical technique and digital camera. The method based on analysis the digital image of the agglutination process by MATLAB software._x000D_ We present an overview of two acousto-optic sensing approaches; the first demonstrates the cuvette approach while the second is the microscope slide approach. The cuvette approach digital image analyzing depends on the green channel distribution of the original image and count the brighten pixels, while the microscope slide approach passes through series of algorithms started with grayscale filter and end with edge detection it counts the different color pixels._x000D_ The experimental result shown that it is possible to enhance the determination of blood group typing by using acousto-optical technique in both cases of using isohemagglutinating sera as well as the crossmatch test in a short time and high efficiency compared with the traditional methods.
Dynamic modeling of a robot manipulator is a central problem in an accurate robot control. In this paper; the dynamic equations of motion were derived by using Eular-Lagrange method for a six degree of freedom articulated robot manipulator based on the geometrical jacobian construction for each link and actuator. In addition, friction effects beside the end effector forces that act the environment are considered. A Matlab Simulink plant is developed to embrace the theoretical work and simulate the dynamic response for a designed nonlinear controller Proportional Derivative plus Gravity (PD+G), also a modified controller is applied to reject the disturbances and the internal friction effect where the settling errors were 3.57E-6, 2.09E-7, -3.63E-6, 8.84E-6, -5.39E-8 and -4.39E-5 (deg) for joints one to six respectively. The presented approach can be applicable to solve the dynamic problem of other n-link robot manipulators and achieve a suitable solution for tracking trajectories.
Mobile robots use simultaneous localization and mapping (SLAM) techniques for generating maps of unknown environments through navigating its. In this work, firstly SLAM technique was considered based on extended Kalman filter (EKF) which it was implemented and evaluated at unknown environments with different number of landmarks to estimate mobile robot’s position and build a map for navigated environment at the same time. Then, the detectable landmarks will play an important role in controlling the overall navigation process as well EKF-SLAM technique’s performance. After that, three intelligent optimization algorithms are proposed to enhance the performance of the EKF-SLAM trajectory for the mobile robot, these algorithms are: particle swarm optimization (PSO), chaotic particle swarm optimization (CPSO) and genetic optimization (GA). MATLAB simulation results show that CPSO algorithm outperforms PSO and GA algorithms in terms of minimizing the mean square error (MSE1) with increasing the number of landmarks, where MSE1 is the mean square error of EKF-SLAM according to the actual trajectory. The simulation results show also the performance of EKF-SLAM trajectory is better than the performance of the Odometry trajectory and becomes best with using intelligent optimization algorithms.
In the present work, theoretical and experimental Study of vibration of a drum type of Horizontal Washing Machine. The effect of the Isolators stiffness, damping coefficient and the drum mass for specific laundry capacity also has been studied. The work in this research has been carried out analytically by using MATLAB, and Study experimentally the effect of different speed and unbalance force during the spinning cycle of the washing machine at four sides of it. This analysis aims to reducing the excited vibration. This was achieved theoretically by investigate the effect of various parameters in order to assign property values to increase the isolation efficiency to reach optimum design. The results is show that drum vibration amplitude reduced to 42 % at spinning speed 1000 rpm and 41% at 1200, 1400 rpm when the applied selected parameters.
In the last two decades, underwater acoustic sensor networks have begun to be used for commercial and non-commercial purposes. In this paper, the focus will be on improving the monitoring performance system of oil pipelines. Linear wireless sensor networks are a model of underwater applications for which many solutions have been developed through several research studies in previous years for data collection research. In underwater environments, there are certain inherent limitations, like large propagation delays, high error rate, limited bandwidth capacity, and communication with short-range. Many deployment algorithms and routing algorithms have been used in this field. In this work a new hierarchical network model proposed with improvement to Smart Redirect or Jump algorithm (SRJ). This improved algorithm is used in an underwater linear wireless sensor network for data transfer to reduce the complexity in routing algorithm for relay nodes which boost delay in communication. This work is implemented using OMNeT++ and MATLAB based on their integration. The results obtained based on throughput, energy consumption, and end to the end delay.
Total hip replacement (THR) is an elective surgical procedure with the primary indication being pain relief. The aim of this study is to analyze gait dynamics for patients after they underwent a unilateral THR surgery and compare it with normal parameters. To investigate the gait dynamics a gait analysis was performed on five patients after they underwent a unilateral THR surgery; only two of them were examined before the surgery. The gait analysis was performed using a digital video camera with two force plates. Kinematics data were obtained from 2D trajectories of seven passive markers using SkillSpector software. MATLAB software has been used for inverse dynamics computation. General gait parameters, Harris Hip Score, joints’ angles, forces, moments and powers were obtained during gait cycle. It was found that the average of improvement in Harris Hip Score (for four patients who were examined 1.5, 2.5, 3 and 9 months after surgery) is 61.8 points, which is an indication of pain relief. In the other hand, the general gait parameters were found slightly lower than normal after THR surgery. The average hip reaction force was found to be 2.988 N/BW, which is within normal range. Also, the average of maximum hip extension and maximum hip flexion angles were found to be 25.69 and -13.524 degree respectively, which both are within normal ranges. Furthermore, hip, knee and ankle moments and powers results showed some abnormality. Therefore as a conclusion, patient satisfaction and functional improvement are not related to general gait parameter. And it is not unusual that gait mechanics improvement would not reach normal after months of recovery. Also, the results of gait dynamics which are from the engineer’s perspective are compatible with Harris Hip Score, which is from the physician’s perspective, in quantifying surgical results and subsequent recovery progress.
The present work demonstrates the optimization process of Micro- hole of Electrical Discharge Machining (EDM) by Adaptive Neuro Fuzzy Inference System (ANFIS). The workpiece material was copper alloy. The current, gap distance and pulse on time were the control parameters of EDM. The process has been successfully modeled using ANFIS model constructs a fuzzy inference system in MATLAB 7.2 Software Gaussian type for optimization of micro diameter, were adopted during the training and testing process of ANFIS model in order to compare the prediction accuracy of micro diameter by one membership function. Finally, the comparison of ANFIS results with experimental data indicates that adoption of Gaussian membership function in proposed system achieved satisfactory accuracy. Prediction using ANFIS model compared with experimental values of micro holes at correspond ratio 98.37%.
This paper discusses the development of a seven-band coherent wavelength-division multiplexing (WDM) system covering the T to U systems, aiming to enhance the capacity and system efficiency. Seven multiband systems (C+L, S+C+L, S+C+L+U, E+S+C+L, E+S+C+L+U, O+E+S+C+L+U, and T+O+E+S+C+L+U) are designed with 40 GBaud symbol rate, 50 GHz channel spacing, and dual-polarization (DP)-16QAM signaling. The analysis adopted the enhanced Gaussian noise model, considering the amplified spontaneous emission of inline optical amplifiers and nonlinear interference (NLI) from fiber nonlinear optics, including Kerr effect and stimulated Raman scattering (SRS) which it implemented using Matlab (Ver. 2020b) program. The results show that the optimal powers are -4, -5, -5, -4.5, -3.5, -6, and -4.5 dBm for the seven WDM systems, respectively. Further, with a fiber span length of 100 km, the C+L system has the longest transmission reach of 20 span. However, using S+C+L+U system gives the highest bit rate-distance product of 1619 Tbps.km. The O+E+S+C+L+U and T+O+E+S+C+L+U systems are designed with 50 km-span length to reduce the effect of NLI caused by the large numbers of channels (1060 and 1200, respectively).
In this paper, a hiding encrypted message using pseudo random number generator and sequential encoding is proposed. This algorithm can provide better security of hiding information in image. The main emphasis in mine results will be on visual image quality and also the peak signal to noise ratio (PSNR) value which is a measure of quality of embedding. The results of statistical analyses like average difference, PSNR and MSE indicate high security and suitability of the proposed scheme. The obtained result shows the peak signal to noise ratio is 79dB. The programming language MATLAB is used for implementing the proposed algorithm.
Computed tomography (CT) imaging is an important diagnostic tool. CT imaging facilitates the internal rendering of a scanned object by measuring the attenuation of beams of X-ray radiation. CT employs a mathematical technique of image reconstruction; those techniques are classified as; analytical and iterative. The iterative reconstruction (IR) methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time, those methods are excluded from routine use in clinical applications. In this paper the reconstruction time of an IR algorithm is minimized through the employment of an adaptive region growing segmentation method that focuses the image reconstruction process on a specified region, thus ignoring unwanted pixels that increase the computation time. This method is tested on the iterative algebraic reconstruction technique (ART) algorithm. Some phantom images are used in this paper to demonstrate the effects of the segmentation process. The simulation results are executed using MATLAB (version R2018b) programming language, and a computer system with the following specifications: CPU core i7 (2.40 GHz) for processing. Simulation results indicate that this method will reduce the reconstruction time of the iterative algorithms, and will enhance the quality of the reconstructed image.
Diabetes is one of the most critical diseases in the world which requires measuring the concentration of glucose also the injection of insulin to control the glucose rate in the body. The proposed controller is applied to the Bergman’s three-state minimal patient model, where the model is considered certain but with unknown meal. In the present work, a nonlinear controller is designed to control the concentration of glucose based on the Backstepping approached with a sliding mode for observing the disturbance meal. So will have estimated the meal and have canceled the effect that the glucose concentration has regulating to the basal level._x000D_ The effectiveness of the proposed controller, which represent the insulin dose, is proved via simulating the Bergman’s model with designed controller via MATLAB Simulink software. The result clarify the ability and the robustness of the proposed controller.
The goal of this paper is to present a study of tuning the Proportional-Integral-Derivative (PID) controller for control the position of a DC motor by using the Particle Swarm Optimization (PSO) technique as well as the Ziegler & Nichols (ZN) technique. The conventional Ziegler & Nichols (ZN) method for tuning the PID controller gives a big overshoot and large settling time, so for this reason a modern control approach such as particle swarm optimization (PSO) is used to overcome this disadvantage. In this work, a third order system is considered to be the model of a DC motor. Four types of performance indices are used when using the particle swarm optimization technique. These indices are ISE, IAE, ITAE and ITSE. Also study the effect of each one of these performance indices by obtaining the percentage overshoot and settling time when a unit step input is applied to a DC motor. A comparison is made between the two methods for tuning the parameters of PID controller for control the position of a DC motor is considered. The first one is tuning the controller by using the Particle Swarm Optimization technique where the second is tuning by using the Ziegler & Nichols method. The proposed PID parameters adjustment by the Particle Swarm Optimization technique showed better results than the Ziegler & Nichols’ method. The obtained simulation results showed good validity of the proposed method. MATLAB programming and Simulink were adopted in this work.
Reverse Engineering is a process of re-producing existing parts by obtaining digital models using a special data taken from the original parts using specific techniques. It can be used to redesign existing parts either due to lost data or the parts are no longer available. In this paper, surface modelling technique using special data taken from CMM (Coordinate Measuring Machine) was employed to redesign a candle holder. Specific MATLAB code was generated to model the data taken from the surface of a candle holder made of glass. Bezier curve technique was implemented in this research to model the curve of the outer surface of the candle holder. Various orders of Bezier curves were discussed and used to give better approximation of the original data curve with error percentage monitoring each time. The thickness of the candle holder was reduced from 5mm to 3mm and the volume reduction was calculated. The amount of reduction in the glass volume when reducing the thickness was found to be 210mm3. In addition, the amount of increase in the area of glass section was calculated to be 138.5mm2. This reduction gives a better vision of the amount of glass saved using this procedure. Two different shapes were found and plotted by varying the control points coordinates.
This paper proposes robust control for three models of the linear inverted pendulum (one mass linear inverted pendulum model, two masses linear inverted pendulum model and three masses linear inverted pendulum model) which represents the upper, middle and lower body of a bipedal walking robot. The bipedal walking robot is built of light-weight and hard Aluminum sheets with 2 mm thickness. The minimum phase system and non-minimum phase system are studied and investigated for inverted pendulum models. The bipedal walking robot is programmed by Arduino microcontroller UNO. A MATLAB Simulink system is built to embrace the theoretical work. The results showed that one linear inverted pendulum is the worst performance, worst noise rejection and the worst set point tracking to the zero moment point. But two masses linear inverted pendulum models and three masses linear inverted pendulum model have a better performance, a better high-frequency noise rejection characteristic and better set-point tracking to the zero moment point.
The daily peak load forecasting for the next day is the basic operation of generation scheduling. The approach of using ANN methodology alone is limited which has generated interest to explore hybrid system. In this paper a search of genetic programming to a short term load forecasting is presented. A genetic architecture with the fitness normalization has been used to find as optimum data peak load of Baghdad city. The optimize data applied to the ANN to be trained and tested to estimate the daily peak load of Baghdad city. Different cases for load forecasting are considered with the aid of MATLAB 7 package to get the estimation of the next day. So an improvement method of genetic optimization is proposed to get a better solution for the load estimation rather than artificial neural network.
Optical methods are widely used for medical diagnostic and therapeutic purposes. The use of laser source as non-ionized radiation in the imaging is considered safe, and has advantages more than the other radiological methods The laser application in imaging is based upon the detection and measuring the laser light parameters after passing through the turbid media of the tissue layers and the tumor mass to differentiate them precisely according to their different optical properties._x000D_ In this experimental study, the tumor masses were implanted in the legs of ex-vivo mice. Then each leg was non-invasively scanned by NIR 785nm diode laser. The penetrated laser light power through the leg was measured. The results were tabulated and treated by using the Matlab program version R2013a (8.1.0.609) to create 2D image for the scanned tissue. The resulted images were clear. They showed precisely the imbedded tumor, its dimensions, and its location inside the tissue.
Kids carrying heavy loads as a part of everyday activity may be related to bend their trunks forward to maintain body posture and balance while walking. This study was to determine a correlation between the weight of a child's backpack, their body weight, and certain features of their body posture. The study group consisted of 6 children, in age of primary school. The anthropometry (age, length, weight) were taken for each volunteers. A school backpack was specially built for the present study. Walking gait was filmed in three cases: (zero kg, 3 kg and 6 kg) backpack.Posture was analyzed by using (Kenova and MATLAB) computer programs.The results show that the forward inclination of the trunk increases when the load and the walking distance are increased, this forward inclination segment may impose greater stress over the vertebral column (ligaments and intervertebral disks) and increase the risk of back problems.Spine and back health may be adversely affected by load carriage and it may be important to use spinal curvature as a measure of posture for load carriage. This study shows that the backpack load cause a lumbar asymmetry by 10 to 20 degree according to the load which has a significant amount of back pain in kids.
Cone-beam computed tomography (CBCT) is an indispensable method that reconstructs three dimensional (3D) images. CBCT employs a mathematical technique of reconstruction, which reveals the anatomy of the patient’s body through the measurements of projections. The mathematical techniques employed in the reconstruction process are classified as; analytical, and iterative. The iterative reconstruction methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time those methods are excluded from routine use in clinical applications. The aim of this research is to accelerate the iterative methods by performing the reconstruction process using a graphical processing unit (GPU). This method is tested on two iterative-reconstruction algorithms (IR), the algebraic reconstruction technique (ART), and the multiplicative algebraic reconstruction technique (MART). The results are compared against the traditional ART, and MART. A 3D test head phantom image is used in this research to demonstrate results of the proposed method on the reconstruction algorithms. The simulation results are executed using MATLAB (version R2018b) programming language and computer system with the following specifications: CPU core i7 (2.40 GHz) for the processing, with a NIVDIA GEFORCE GPU. Experimental results indicate, that this method reduces the reconstruction time for the iterative algorithms.
Transfer function characteristics of a DC machine are used in this paper to estimate speed and torque in four quadrant operation modes. Estimation speed and torque control based on a DC machine transfer function is implemented by measuring the DC chopper instantaneous average output voltage and current. MATLAB\SIMULINK is used to implement the DC drive circuit in the forward and reverse motoring and regenerative modes, respectively. The DC drive system is simulated at different speed and load torque values in steady state and dynamic operating conditions. Simulation results demonstrate success of the sensorless and PI controller systems, which gives satisfactory agreements between the estimated, actual and reference speed and torque values.
Facial expressions are a form of non-verbal communication, they appear as changes on the surface of the facial skin according to one's inner emotional states, aims, or social communications. Classification of these expressions is a normal process for humans, but it is a challenging task for machines.Lately, interest in facial expression recognition has grown, and many systems have been developed to classify expressions from facial images. Any expression recognition system is comprised of three steps. The first one is face acquisition, then feature extraction, and finally classification. The classification accuracy depends primarily on the feature extraction step. Therefore, in this research we study many texture feature extraction descriptors and compare their results under the same preprocessing circumstances; moreover, we propose two improvements for one of these descriptors, which give better results than the original one. We validate the results on two commonly used databases for expression recognition using Matlab programming language, wishing all of that to be an interesting point for researchers in this field.
The modern development in prosthetics field demand the evaluation of the dynamical behavior and automatic control .The key process in the design and implement of these devices is the determination of the model parameters inherited with the transfer function .In such complicated structures it is so difficult to evaluate transfer function analytically ,however experimental approaches can serve as a simple and effective tool for estimating transfer function and model parameters .In this regard computer software such as Matlab is used .System Identification SID refers to the method for estimating the system transfer function from experimental tests by using computer .In the present paper; SID method is employed for analyzing below-knee prosthesis leg .In order to simulate with the practical requirement for design and evaluation ,two phases of human gait are considered ,namely; swing phase and single support of stance phase .The validity of this method is firstly checked by applying it on clamped-clamped beam model where the required parameters are evaluated and compared theoretically (via modal analysis) and experimentally (via System identification) .It is found that ; the error in estimating the transfer function parameter of beam is not exceeded 6% . Then the transfer function of the prosthesis are estimated for two phases of gait cycle .It is found that; the estimated transfer function of the prosthesis leg is highly affected by the phase type of gait cycle , where ;the natural frequency highly increases, the static gain decrease for support phase as compared with the swing phase ,however the damping ratio does not affected .
Millimeter Wave (mmWave) Massive Multiple Input Multiple Out (MIMO) system is a key technology for future wireless transmission. The system's architecture can differ based on the type of Analog-to-Digital Converters (ADCs) used at the receiver, whether they are all low-resolution or a mix of different resolutions (Mixed-ADCs). Mixed-ADCs is a promising solution to achieve better performance than low-resolution ADC-only architectures by leveraging high-resolution ADCs to capture critical signal components while maintaining energy efficiency through low-resolution ADCs. In this paper, the problem of channel estimation for this system architecture is taken into consideration. A novel compressive-sensing based algorithm, that is called Approximate Conjugate Gradient Pursuit (ACGP), is proposed to estimate the channel coefficients. The performance of the proposed algorithm is investigated under varying system parameters, including different Signal-to-Noise Ratios (SNR), Radio Frequency (RF) chains, ADC resolutions, and numbers of observation frames. Matlab software was used to perform numerical simulations. The results demonstrated that mixed-ADCs architecture outperforms low resolutions only in performance. It was found that ACGP achieves lower Minimum Mean Squared Error (MMSE) compared to Orthogonal Matching Pursuit (OMP) and Least Square (LS), particularly in low SNR conditions showcasing its robustness and efficiency in signal reconstruction, achieving an average enhancement of 30% to 50% at moderate SNR levels. While OMP exhibited faster computation times under various number of observation frames, ACGP maintained stable computational performance, with a slight increase in computation time. For applications where accurate channel estimation is required under noisy environment, the proposed algorithm is an effective choice to meet such requirements.
The free vibration analysis of rotating multi-layered cylindrical shell is investigated based on the first order shear deformation theory (FSDT) of shell. Cylindrical shell consists of three layers; outer and inner layers are isotropic material and the middle layer is a functionally graded material (FGM). The material properties for middle layer are assumed to be graded in the thickness direction. Based on Hamilton’s principle, the equilibrium equations and the equations of motion are derived and then solved by using the differential quadrature method (DQM) as a numerical tool. MATLAB software was adopted for programming the equations and the related boundary condition. The effect of (FGM) layer thickness, angular speed, index power law, circumferential wave number on the natural frequency of the clamped-clamped rotating cylindrical shell were examined. The numerical results showed that a reasonable agreement between the present study and analytical data available in the literature.