Electrical and Electronic Engineering
141 theses under this subject heading
Image Super Resolution using Fast Converging Iterative Interpolation and Back Projection
Super resolution (SR) is one of the techniques to enhance image resolution in terms of the number of pixels and noise reduction. In SR techniques, a sequence of low resolution (LR) images captured by moderate camera is used to generate a high resolution (HR) image. In this thesis a new Iterative Back Projection (IBP) based SR technique is proposed. In the proposed techniques, IBP technique is improved by using interpolation. This SR technique is achieved by adding an up-sampling and down sampling in each iteration. First of all, four observed LR images are generated by an observation LR model. One of these LR images is considered as a reference image, then interpolation techniques are used to increase the size of the reference image to the size of the ground truth image. This image is considered as an initial guess image. Then the size of initial image is increased and decreased respectively by using interpolation techniques. The interpolated image is decimated to four LR images. The LR images are registered to generate an HR image, then the HR image is sent back to the first step. This process is repeated iteratively until an error criterion is met. The proposed technique is called Iterative Interpolation and Back Projection (IIBP), since an interpolation (up-sampling followed by down-sampling) module is embedded in each iteration. The embedded interpolation module speeds up the convergence of the standard IBP and generates faster results than the standard IBP. The proposed techniques are tested on various well-known benchmark images. The quantitative Peak Signal-to-Noise Ratio (PSNR) results as well as the visual results show the superiority of the proposed techniques over the standard IBP whenever limited numbers of iterations are allowed. As the number of iterations approach to infinity, generally standard IBP gives better results. Keywords: Super Resolution, Iterative Back Projection, Image Registration
The Radiation Pattern and Phase Center of Two-Dimensional Apertures
Two matching techniques namely linearly tapered and multistep transition were used to design two dimensional radiators between parallel plate regions and 50 microstrip feed line. Transitions for different aperture widths were designed at 2.45GHz, by using a full wave simulation software. As these radiators are not point radiators, they may cause phase errors. In this study, a simple method is suggested to estimate the phase center of the radiating apertures and reduce the phase errors. The suggested method is based on the phase equally in the broadside direction and at another constant angle. The study has been carried out by using a full wave simulation software. The results show that there is almost no phase error over the range of angles of interest for the estimated phase center at the design frequency. The position of the phase does not vary with the distance from the radiator, which means that there are no phase errors as the distance from the radiator varies. Although there is some phase errors as the frequency is decreased or increased, these errors are not significant over a wide band of frequencies. For the multistep transition it is observed that the position of the phase center is closer to the center of the radiator aperture, for the wide apertures. Keyword: Phase center, parallel plate, two dimensional radiation, far field region
Multi-Beam Near Field Focusing Characteristics of Microstrip Patch Antenna Array
Several modern-day antenna applications require the radiated fields to be focused at a predetermined point away from the antenna to perform different tasks, such as sensing, testing, charging, diagnosing, and treatment of different medical conditions. In this thesis, a thorough study has been made to investigate the characteristics of near-field focusing. In many applications, along with focusing the radiated fields at a focal point, it is also required to move that focused beam to scan a specific region i.e., usually carried out either electronically or physically by changing the position of the antenna array. The thesis proposes a robust mechanism to move the focused beam at single and dual focal points to improve the scanning properties of the antenna array. The proposed mechanism does not depend upon any external phase shifter circuit or changing the position of the array for focusing and scanning the focused beam. The movement of the focused beam is achieved as a result of introducing extra transmission lines to the scanning axis of the array. Antenna designs for single-focal and dual-focal points are analyzed using MATLAB and CST simulation software. The simulation results show that the proposed designs work efficiently as the movement of the beam is controlled by the change in frequency. Furthermore, in the case of dual focal point near field focused antenna array, there is a significant increase in the scanning distance as compared to the single focal point. The proposed mechanism results in an increment in scanning distance of around 53%. The proposed designs can be used in applications such as RFID, Non-destructive industrial inspection and testing, and wireless power transfer, where the focused beam is to be directed at a point in the near-field and the scanning of the focused beam is required as well. Keywords: microstrip patch antenna array, near-field focusing, parasitic patch, hyperthermia, beam scanning.
Novel Robust Adaptive Beamforming Algorithms with Improved Estimation of Array Covariance Matrix and Signal Steering Vector
Robust adaptive beamforming has long been an attractive research topic over several decades due to wide applications in vast fields of signal processing such as, radar, sonar, wireless communications, medical imaging, microphone array speech processing and other areas. Adaptive beamforming improves the reception of desired signals in the presence of interference signals automatically by sensing the presence of interferences and suppressing them while simultaneously enhancing desired signal reception without prior knowledge of the signal and interference environment. However, under certain circumstances, adaptive beamformers suffer performance degradation due to several reasons which include small sample size, the presence of the desired signal in the training data, the presence of nonstationary interference, or imprecise knowledge of the steering vector of the desired signal. Moreover, conventional approaches are very sensitive to these types of mismatches, do not provide sufficient robustness and may suffer from severe performance degradation in such situations. In this thesis, we propose three different types of novel adaptive beamforming techniques to resolve the effects caused by some of the aforementioned difficulties. A general goal in adaptive beamforming is to adaptively steer a beam towards a desired signal, while placing nulls at interference directions. The well-known minimum variance distortionless response (MVDR) adaptive beamformer is designed to linearly combine the outputs of the sensors in order to minimize the array output power, while maintaining a fixed response towards the desired signal. However, it is well known that the MVDR beamformer is quiet sensitive to the mismatch between the actual steering vector and the assumed one, which could be caused by any array imperfection. In the first approach, a robust adaptive beamforming technique based on a modification of the robust Capon beamforming approach is introduced which estimates the steering vector using eigenspace projection-based approximation. The steering vector is estimated as a reasonable approximation for the orthogonal projection of the presumed steering vector of the desired signal onto the signal-plus-interference subspace. In this approach, the optimal diagonal loading factor corresponds to the minimum of the estimated beamformer output power. Also, estimation of the desired signal’s direction-of-arrival is utilized to update the presumed steering vector. On the other hand, during the past decade, many approaches based on the processing of the sample covariance matrix have been proposed. However, since the desired signal component is usually included in this matrix, the beamformer is sensitive to slight mismatches. Although, some techniques have been proposed to remove the signal-of-interest (SOI) component from the signal covariance matrix using the reconstruction of the interference-plus-noise covariance (IPNC) matrix, these have a number of drawbacks. In the second approach, we introduce a low complexity procedure for IPNC matrix construction. The main motivation of this algorithm is to simplify the estimation of the IPNC matrix using its theoretical expression which is based on projection processing for covariance matrix construction and desired-signal steering vector estimation. In this accordance, the optimal minimum variance distortion-less response beamformer is closely achieved through approximating the interference-plus-noise covariance matrix by utilizing the eigenvalue decomposition of the received signal’s covariance matrix. Moreover, the direction-of-arrival (DOA) of the desired signal is estimated by maximizing the beamformer output power in a certain angular sector. In particular, the proposed beamformer utilizes the aforementioned DOA in order to estimate the desired-signal’s steering vector for general steering vector mismatches. In addition, adaptive beamforming methods are sensitive to underlying assumptions on the environment, sources, or sensor array violation, especially when interferences are moving fast. In recent years, research efforts have been devoted to the development of beamforming using covariance matrix taper (CMT) or additional constraints in the optimization programming for suppression of pre-defined angular ranges. This research presents an innovative beamforming approach in which the nonstationary interference source is estimated during the period in which snapshots are taken. Then, a new interference-plus-noise covariance matrix reconstruction is introduced which is derived from a simplified power spectral density function that can be used to shape the directional response of the beamformer. Finally, the beamformer is designed to impose nulls toward the regions of the moving interference based on the reconstructed covariance matrix. The essence of the proposed method is to express the inverse of the reconstructed covariance matrix in such a way that significantly reduces computational complexity. Theoretical analysis and simulation results indicate the superior performance of the introduced proposed approaches in the presence of mismatches relative to other some existing methods.
Sliding Mode Control Applied To UPS Inverter Using Norm of the State Error
ABSTRACT: In dynamical system it is impossible to avoid dealing with uncertain conditions such as disturbances; that case is applicable on the UPS Inverter. There are many approaches to control inverters; here we are going to introduce a new approach of sliding mode control applied to UPS inverters. We reduce the sliding time of the state trajectory, by defining a function with respect to the error norm. This function gives the system a value of the sliding line at each instance, such that the performance is improved. The function is defined as the norm of both voltage error and its derivative multiplied by a factor. The norm value is saturated for small and large value of λ, which represents the slope of the sliding line. Another parameter (β) is also introduced, which is a gain multiplying the result of the saturated function. When the state is far from the origin, small value of λ is used in the reaching mode, while large value of λ is used when the state reaches the sliding line and start to “slide” on the sliding line. From the definition of the norm error, a function is derived which is used to minimize the reaching time. The results of simulation are compared to Three level hysteresis and rotating sliding mode approaches. The new approach shows a fast response with very small value of the voltage error. Keywords: uninterruptible power supply, inverters, sliding mode control, rotating sliding line. ……………………………………………………………………………………………………………………………………………………………………………………………………………………
Modeling, Analysis and Control of quasi-Z-Source Inverters
This thesis aims to develop new control methods for the single-phase quasi-Z-source inverters (qZSIs). The key challenge lies in the design of suitable control method for the qZSI which is a nonlinear multi-input-multi-output (MIMO) system. Hence, from the control point of view, developing an integrated control technique is a challenging issue. Although the conventional control methods attain reasonable responses, suppression of double frequency ripple (DFR), robustness against parameter variations and simplification issues are still open issues. Thus, the proposed new control methods target to achieve these objectives. A novel approach which is created based on the model of the system while tuning the current of the system (MBCC) with DFR mitigation, virtual time constant and active damping to damp the resonances of the LCL filter is presented for a grid-tied qZSI as the first control method in this thesis. The second control method proposed in this thesis is a MIMO sliding mode control (SMC) which aims to control all variables of qZSI concurrently. This control approach not only synchronizes the control of all state variables at the same time, but also offers simplification in the implementation without using proportional-integral (PI) controllers in the dc-side, robustness to parameter variations, DFR mitigation when the sliding constant in the dc-side is selected appropriately and fixed switching frequency by introducing boundary layer technique. The boundary layer smooths the sliding functions and makes them appropriate for the PWMprocess. The applicability of the MIMO SMC method is also investigated for a single-phase high gain Z-source inverter which is called switched Z-source inverter (SZSI) in the literature. The effectiveness and validity of the proposed control methods are supported by simulation results in MATLAB/Simulink environment and the experimental results. The results show that the DFR mitigation approach can remove the DFR in the inductor current successfully and the MBCC method is also an efficient approach with fast dynamic response, zero steady state error and active damping of the resonance. Moreover, MIMO SMC can also achieve the goals with zero steady state error, robustness against parameter variation and fast dynamic response while attaining fixed switching frequency. Keywords: Active damping, double frequency ripple, quasi-Z-source inverter, LCL filter, proportional-resonant control, boundary layer, sliding mode control, switched Z-source inverter
Robust Color Image Watermarking Techniques Based on DWT, DCT and SVD in Different Color Spaces
Within the last decade, with the development of communication technologies and the increasing growth in the internet has become insecure, so it created different techniques to solve this problem. One of these techniques is the digital watermark, which provides the protection of property rights. In this thesis, we suggest new techniques of watermarking image aim to increase the degree of robustness of the watermark against various attacks and to increase the imperceptibility of the watermark image. Also these techniques aim to ensure the watermark image using Arnold transform where the watermark is available only to a legitimate user. The proposed approaches of watermarking image based on DWT, DCT and SVD have been applied on gray and color images in different color spaces like RGB, YIQ and YCbCr. Therefore, we have seven proposed algorithms namely: a gray image watermarking technique, an image watermarking technique in RGB color space (using a gray watermark image), an image watermarking technique in RGB color space (using a color watermark image), an image watermarking technique in YIG color space (using a gray watermark image), an image watermarking technique in YIQ color space (using a color watermark image), an image watermarking technique in YCbCr color space (using a gray watermark image) and an image watermarking technique in YCbCr color space (using a color watermark image). The difference between these algorithms is the type of watermark and the colorspace used (gray or color image: RGB, YIQ or YCbCr). To test the performance of proposed approaches, we calculated the PSNR and the SSIM. The best proposed approach which gives high robustness and imperceptibility of the watermark image against different attacks is an image watermarking technique in YIQ colour space (using a gray watermark image). And, the worst proposed approach which gives low robustness and low imperceptibility of the watermark image against different attacks is an image watermarking technique in YCbCr color space (using a color watermark image). In addition, our proposed approaches give high imperceptibility and high robustness of the watermark image when compared with other techniques [17][22][23]. Through the results, it has been verified superiority of our proposed approaches on many techniques. Our proposed approaches have high robustness of the watermark against various attacks with high quality for the watermarked image and security of the watermark image. Keywords: Watermarking Image, robustness, imperceptibility, PSNR, SSIM.
3D Modelling of Buildings and Environments using Laser Scanning and Surface Reconstruction
ABSTRACT: 3D models of environments and buildings are widely used in Geographical Information Systems (GIS), building information models, constructional management, environmental planning, city guides, path finding and Robotic applications, where the accuracy of data collection and resolution of the 3D model have been the main concern. 3D models of buildings and other objects can be constructed by following three main steps, namely, data acquisition, alignment and surface reconstruction. This project aims at introducing the process of forming a 3-D model from 3-D scan data and describing the data acquisition, alignment and surface reconstruction sequences in detail. Hardware and software design and implementation has been made for each stage of the 3D modelling process and a full grasp of the system is achieved. However, due to the complexity of the system, and also due to time limitation, it was not possible to achieve sufficient performance from the designed system. Instead, a commercial 3D laser scanner was used for the sake of completing the requirements of the 3D Modelling process with a reasonable performance. Current data acquisition systems have been reviewed and compared to discuss their advantages and drawbacks, as a result of which, 3D laser scanner has been chosen to be the most accurate and fast data acquisition system appropriate for scanning indoor and outdoor environments. Due to some limitations of the available 3D laser scanners, a commercial 1D-laser scanner has been converted into a 3D laser scanner, by designing and constructing a pan-tilt mechanism for the 3 axis control of the 1D laser scanner. The new 3D laser scanner is a simple and light in weight, which is easily adopted to a remote operating and monitoring Vehicle (ROMV) which has been designed in this project to add an indoor and outdoor mobility feature to the device. Although the new 3D Laser scanner operates properly, the accuracy and resolution of the scan results are not as expected yet. In order to complete the 3D modelling process with a reasonable accuracy and resolution, data acquisition is achieved by using the 3D laser scanner provided form the Stevens Institute of technology (CAD eye Scanner). This system is not only able to scan indoor and outdoor environments with acceptable resolution, but also it is able to collect RGB data corresponding to each scanned point in the scanned environment. For the Alignment or Registration of the acquired coordinate data obtained by the 3D Laser scanner, this research has used the semi- automatic method produced by an academic software tool called Mesh-lab. Point cloud model of the Techno park building was obtained by using professional software called Pointools. Surface reconstruction methods are investigated to obtain models with seamless and smooth surfaces from the point cloud model. It is realized that the existing methods fail to produce realistic surfaces under noisy data and a new method based on implicit surface reconstruction using isotropic basis functions has been developed to represent the sharp features more close to their real appearance. Some initial simple results of this method are presented in the thesis. A further work is needed to apply this method to reconstruct the surfaces of a complete 3D building model. Keywords: 3D Laser scanner, surface reconstruction, registration, radial basis functions, generalization..........
Experimental Performance Analysis of Multipath TCP
Multiple wireless interfaces in modern devices today have given great promise in enhancing multimedia service delivery over wireless networks. However, the IP coupled nature of the conventional TCP/IP protocol inhibits the simultaneous use of these interfaces. Multipath TCP (MPTCP), a protocol undergoing IETF standardization has been developed to simultaneously use multiple interfaces for delivery of services over the Internet. Unlike other earlier studies that use simulations, stationary scenario, and Advanced Video Codec-Dynamic Adaptive Streaming over HTTP (AVC-DASH) to study MPTCP, this thesis uses mobile scenario, real measurements, and Ultra High Definition, High Efficiency Video Codec (UHD HEVC-DASH) to evaluate the performance of MPTCP. The findings show that MPTCP gives a higher performance in terms of throughput, shorter download time, and increased bandwidth compared to Single Path TCP (SPTCP). The results from delivery of multimedia services using UHD HEVC- DASH streaming, though specific instead of general, reveal that under balanced and unbalanced network paths, MPTCP offers good Quality of Experience (QoE) compared to SPTCP. However, with variability in latency, and packet loss between paths, MPTCP underperforms compared to SPTCP in terms of video buffering in the unbalanced network case, and high packet retransmission rate in either balanced or unbalanced network paths.
Video Transmission Using Scalable Video Coding For 4G Wireless Communications Systems
The technology foundation preferred by 4G wireless broadband networks is Long Term Evolution (LTE). This is because of its speed, robustness and lots of significant technological and business advantages. In recent years, applications based on video streaming have turned out to be immensely important. Due to the data-intensive nature of videos, alternatives for the delivery process have been investigated. In order to maximize throughput and video quality, Scalable Video Coding (SVC), combined with adaptive modulation and coding schemes and wireless multicast provides an excellent solution for streaming video to heterogeneous wireless devices. By choosing different modulation and coding schemes for different video layers, SVC can provide good video quality to users in good channel conditions while maintaining basic video quality for users in bad channel conditions. SVC provides three sorts of scalability, i.e. the spatial, temporal and quality scalability. Quality scalability in particular, plays an important role on the Quality of Experience. In view of the above, the research in the thesis addresses the specific problem of the performance assessment of video traffic over a wireless communication link with varying channel conditions. The objective of the research is to mainly involve re-definition of system quality measures and parameters to adjust (such as modulation and video quality) for improvement of these quality measures and implement a successful SVC scenario where optimization of performance over varying channel conditions and scaling rate for the SVC is obtained. Keywords: LTE, SVC, modulation and coding schemes, quality scalability.
Contour optimization of a pin insulator using neural network
ABSTRACT: Insulator geometry strongly affects the distribution of electric field along the surface of the insulator. If the field distribution is not uniform, that stresses the insulator unevenly which most often may lead to unnecessary loss of energy, flashover and eventual breakdown of the power network system. As the desire to have a more efficient, effective and reliable system devoid of losses increases; the need for a well optimized insulator arises. In this study, neural network is used to obtain an optimized form of a pin insulator. Neural network is trained by using geometric information of the pin insulator and field intensities in order to provide a field distribution as uniform and minimum as possible along the insulator surface. Electric field intensities along the surface for different insulator profiles are obtained numerically by using finite element method. Finally, the result obtained such as the mean absolute error of less than 0.1 at optimum, shows that the network has successfully been used to optimize the contour geometry of the pin insulator. Keywords: High voltage, insulator, contour optimization, neural network, electric field distribution. …………………………………………………………………………………………………………………………
Energy Yield Optimization of a Large-Scale PV Power Plant in Self-Consumption Mechanism
The objective of this thesis is to optimize the design parameters of a large scale photovoltaic power plant in order to find its optimal size having the lowest payback period. A methodology is proposed to guide the investors and technical staff in the design of such a system, with core emphasis on self-consumption policy. A flowchart of the process, that uses site survey, system components, associated costs, meteorological data, load analysis, is created. A three-step algorithm is developed in order to solve the optimization problem that searches for the PV plant size having the lowest payback period. The first phase of the algorithm is to minimize the energy fed into the grid for free of charge. In other words the self-consumption is maximized. The decision variables such as the tilt angle of the PV modules, number of PV modules connected in series across a string, number of strings connected to an inverter and the number of inverters are calculated in this phase. The second phase involves maximizing the occupied land area and determining layout of the PV plant. The layout is based on consecutive PV blocks in the installation area. Number of rows and columns in a PV block are obtained in this phase. Last phase is based on the calculation of the optimal size of the PV plant, which has the lowest payback period, by using an iterative approach. Net present value analysis is used as a supplementary tool in order to allow the investor to make better judgment on the project. A case study is carried out in Cyprus International University campus in order to support the proposed methodology. The lowest payback period is achieved at 6.18 years with the total installed capacity of 712 kWp. The payback period results iv calculated by the proposed algorithm and PV*SOL Premium, which is one of the most commonly used PV planning software in the PV market, for each increment in the PV plant size are compared. The difference between the payback periods obtained from the proposed algorithm and PV*SOL Premium is 1.79% on average and 0.34% at the optimum PV plant capacity. According to the case study, a 712 kWp self-consumption PV plant can be installed on 9055 m2 of land area. The initial investment cost is calculated as € 1,063,700. The system can consume 97.92% of its own annual production while only 2.08% of the annual PV energy generation is exported to the grid. The system reaches a self-sufficiency ratio of 25.02%. The net present value is calculated as € 7,091,000. Keywords: Solar energy, large-scale PV power plant, non-incentivized self-consumption, design optimization.
Experimental Analysis on Concentrated Photovoltaic Solar Panel
In recent years, renewable energy such as solar and wind energy is being used abundantly. Concentrated photovoltaic (CPV) modules ensure a more effective and greater power output than the conventional photovoltaic (PV) solar panel. The motivation of this research project was to design and construct a dual axis solar tracker to compare the power output of a conventional PV panel to a two-stage CPV panel. CPV solar panel is studied to achieve the maximum output and performance compared to the traditional PV panel. This work is centered on the investigation CPV and PV output energy. A dual axis solar tracker was designed to implement a two-stage CPV solar panel and a PV panel on it at the same time. A two-stage CPV solar panel consists of one linear Fresnel lens as a primary lens and a solar prism as a secondary lens, in order to concentrate the solar irradiance to gain more power output. The designed dual axis tracker includes a dc motor, a dual axis solar tracker controller, and a linear actuator, to track the plate regarding the elevation angle and azimuth angle. 6 months of data has been collected since January 2018. In this study, we were collecting global solar radiation, direct solar radiation, diffuse solar radiation, CPV produced energy, PV produced energy, elevation angle, and azimuth angle on an hourly basis. The data shows that the output power of the CPV panel is mostly related to the direct solar radiation. Therefore, when direct solar radiation is more than diffuse solar radiation, the output power of the CPV panel is more than the conventional PV panel. In contrast, when diffuse solar radiation is more than direct solar radiation, the output power of the PV panel is more than CPV panel. In contrast, since the diffuse radiation effects on PV panels more than CPV panels, when diffuse solar radiation is more than direct solar radiation, the output power of the PV panel is more than CPV panel.
3D Tumor Segmentation in MR images using Tumor Characteristics
3D segmentation is an important pre-processing phase that dictates the performance of the possible post processing applications in 3D biomedical image analysis. 3D reconstruction of the segmented tumor from 2D MRI plays an essential role in 3D encapsulation of the segmented tumor. Fuzzy C-mean clustering is widely used in 2D segmentation of the brain tumor. In this thesis 2D tumor projections in each slice of the MRI are segmented using FCM. 2D slices extracted through FCM are used to generate the 3D reconstruction of the tumor. However, the possible low number of slices limits the quality of such 3D reconstruction. This thesis proposes to minimize this problem by generating predicted slices (P) between intra slices (I) and generating bi-predictive slices (B) between predictive slices and intra slices by using bilinear interpolation. 3D reconstruction of the brain tumor is performed by using the real slices and the predicted slices. Limitations of the FCM clustering in deciding which cluster is to be segmented is overcome by employing 2D/3D characteristics such as intensity, circularity and 3D Compactness in T2 -weighted MR Images for reliable segmentation of the 3D brain tumors. The proposed approach leads to detect the 3D tumor automatically with improved accuracy compared to alternative methods in the literature. Keywords: 3D Segmentation; MRI; FCM clustering; Labeling; Thresholding; 3D reconstruction; 3D compactness; Circularity; Tumor; Brain.
Investigation of Wide Band Modified Bowtie Antenna
The wide band width is one of the most demanding characteristic of patch antennas in the current advanced technology and research studies. Several studies on improving the bandwidth of patch antennas have been reported in the literature. Spiral patch antenna, fractal patch antenna and bowtie patch antenna are among the major configurations that are investigated primarily for improving the bandwidth of patch antennas. Bowtie patch antenna has the simplest layout that is used for its wide bandwidth and significant antenna for improving bandwidth and gain. Perfect Electric Conductor (PEC) with a Taconic TLY-5 as a substrate with 0.79 mm thickness are used in the simulations in this thesis. Three different modifications are used in the simulations to improve the bandwidth and gain of a simple 2x2 bowtie array. 1st modification which involves a slot with different lengths increase the bandwidth from 5.09 % to 8.62 % and gain from 13.4 dB to 13.7 dB. 2nd modification is applied to the feed network to make the antenna radiation symmetrical which increased the bandwidth from 5.09 % to 5.91 % but decreased the gain to 12 dB. 3rd modification involves a combination of the first two modifications that would make the antenna radiation symmetrical, increase bandwidth from 5.09 % to 9.51 % and increase the gain from 13.4 to 13.7 dB. The simulations cover the X-band region.
K-means clustering based angiographic image analysis to measure coronary stenosis
ABSTRACT: Medical imaging uses techniques or processes which use human body images for clinical or medical science. Medical imaging has a wide range of applications in the field of radiology, angiography and angiogram imaging. Nowadays, angiography and computerized tomography (CT) scans are two common methods that are used by doctors for the detection of coronary artery stenosis (artery blockage) in medical imaging. Most of the detection processes in medical imaging are performed by analyzing digital images generated through angiography and CT scan processes. Currently most of the diagnoses are performed by doctors after manual inspection of real time frames of the video generated by the respective medical imaging systems. In this thesis we propose to use digital image processing techniques in detection and categorization of the clogs in the arteries (stenosis/blockage) by using the frames generated from the X-ray angiography. Utilized image pre-processing methods includes selecting a line of Interest (LOI) on blocked vessel and further selection of the region of interest (ROI) on that area, then automatically cropping the region of interest followed by Gaussian filtering for smoothing. In the post processing, three alternative methods are proposed to measure the stenosis in the vessel. The first method applies thresholding to extract the vessel of interest. The extracted vessel is analyzed for the calculation of the stenosis in percentage. The second method utilizes segmentation of the vessel tissue over the extracted pixels of ROI. The final method uses K-means clustering to differentiate between the vessel regions and non-vessel regions. Among the proposed methods K-means clustering based method outperforms the thresholding and segmentation methods. The performance of the proposed methods is compared with the manually measured objective results and doctor’s opinion which can be considered a subjective score. The results indicate that the proposed methods are reliable alternatives to aid the doctors in deciding reliable stenosis scores. K-means based method produces the best average performance on the evaluated vessels with stenosis. A new metric, Maximum Percentage Error Ratio (MPER), in decibels is proposed to indicate the quality of the decisions regarding the generated stenosis (%) using different methods. K-means based method generates the highest performance in terms of MPER. Keywords: Medical image processing, X-ray angiography, angiography imaging, segmentation, thresholding, K-means clustering, stenosis in heart vessels. …………………………………………………………………………………………………………………………………………………………………………………………………………
Nonbinary Convolutional Coding For Multimedia Data Transmission
ABSTRACT: In this thesis, the performance of nonbinary convolutional coding technique is investigated and new nonbinary codes with better performance are proposed. Nonbinary convolutional coding technique is a coding technique which is similar to the binary convolutional codes with the same decoding strategy but they are designed for general nonbinary sources. The nonbinary convolutional coding technique is described and simulated under various channel conditions. Synthetic nonbinary source sequences are produced by using Markov processes. The channels used in the experimental simulations include additive white Gaussian noise (AWGN) and flat fading channel models. Coded image and video sequences are transmitted over the channels by using binary phase shift keying (BPSK) modulation technique. The Viterbi decoding algorithm is used for decoding the encoded sequences. Viterbi decoding employs hard and soft decision metrics. The soft metric is updated to include the source statistics. This enables the decoder to use the source redundancy for improved decoding performance. Results show that nonbinary convolutional coding which uses the source statistic is effective in reducing bit error rate (BER). New nonbinary convolutional coding is optimized to increase the code distance (). The optimized codes are shown to perform better at low BER.freedv. Keywords: Error Control coding, Convolutional codes, Source metric. ……………………………………………………………………………………………………………………………………………………………………………………………………………………
Size Reduction of Square Microstrip Patch Antenna by Using Metamaterials Structure
The focus of this study is to investigate size reduction of Conventional Microstrip Patch Antenna (CMPA), using metamaterial structure. Metamaterial is a Complementary Split Ring Resonator (CSRR) unit cell which has negative permittivity (ε <0) and positive permeability (μ >0). The CSRR response is verified in simulation based on scattering parameters by using Nicolson-Ross-Weir (NRW) method. Results show that the relative permittivity is negative at the resonant frequency of CSRR. This study also presents the design and simulation of the CMPA and Miniaturized Microstrip Patch Antennas (MMPA) at 5.15 GHz resonant frequency. The reduction ratio reaches to 80.7 % by applying metamaterial structure via CSRR in the substrate. Those antennas were simulated using Computer Simulation Technology Microwave Studio (CST MWS).
Analysis of different structures of patch antennas
ABSTRACT: In this thesis, Method of Moment (MoM) based FEKO software version 5.5 was used to simulate patch antennas in different structures. For patch antennas, some of the fields are in the substrate and some of them in air. Due to this reason, it is necessary to calculate the effective dielectric constant which affects the resonant frequency and the wavelength of the wave in the substrate. Simulations were carried out to compute the value of effective dielectric constant of a single substrate layer which has a relative permittivity equal to 2.2 by making use of the standing wave pattern (SWP) generated by FEKO. After that, microstrip patch antennas were simulated based on multi-substrate layers instead of a single layer. Square, circular and triangular patches were simulated by FEKO and the resonant frequencies obtained were compared with other published (experimental, analytical, simulations by other methods) works. The results are close (from 1 to 3GHz difference) for different modes of the circular patch, while they were equal at 4.02 GHz and 7.03 GHz for the triangular and square patches respectively. Slot antennas are used to enhance the bandwidths, but slots may affect the relative permittivity. i.e. the effective permittivity. Triangular and square shape slot antennas were simulated by FEKO and the results were compared among themselves and with the published result for the triangular slot. The results very close. Slots on the patch are widely used. Here a triangular slot for various heights was simulated by FEKO for the rectangular patch. If has been observed that the resonance frequency reduces by the increase of the height. The optimum height for the given design was recorded. Also, circular slots were applied inside the circular patch to improve the return loss, voltage standing wave ratio and the bandwidth. Defected ground structures (DGS) in different shapes (rectangular, phi-shape, c-shape and plus-shape) were used to solve the surface wave problem which is a drawback for patch antennas. The use of this method resulted in gain enhancement. Gain was enhanced by using patch antenna array topology. In this thesis, a 4 element array antenna was designed at 2 GHz and simulated by FEKO. A maximum gain of 13.1dB dB was achieved. Keywords: Effective Dielectric Constant, Gain, return loss, Patch Antenna, Patch Array Antenna. …………………………………………………………………………………………………………………………………………………………………………………………………………
Distributed Generation Placement Based on Voltage Stability Using Genetic Algorithm
In this thesis, a genetic algorithm (GA) based optimization is used to improve the voltage stability of a power network using Distributed Generation (DG) Units. GA determines the best places of DG Units in the power network. Also, the number and sizes of DGs used are calculated by the proposed algorithm. First, we have solved the problem without using GA. In this step, just one DG with constant size is considered. The main reason of using GA to solve the problem is that finding the best places of DGs could be very complicated and time consuming, considering the number and size of DGs. To evaluate and compare the possible solutions, an index called Voltage Index (VI), is proposed which shows the voltage stability of the power network. A Forward/Backward load flow is used to determine the bus voltages, and consequently the VI of the network. The results show that by using DGs the voltage stability of the network is improved. In addition, GA, as an optimization algorithm, can find the best solution for the problem considering number, size and place of DGs after a specific number of iterations. The best solution for the problem and the results of the load flow for best state are shown as the results of the thesis. Keywords: Power Systems, Distributed Systems, Distributed Generation, Renewable Energy Systems
Microstrip Patch Antenna Design and Performance Study for Biomedical Application
Early stage of tumor detection is important due to increased chance for recovery and saving patient's lives, therefore, many types of researches are going out to find more techniques or methods to be used for breast cancer detection in early stages. The aim of this thesis is to investigate the tumor location after designing a UWB antipodal Vivaldi antenna. In this thesis, an antipodal Vivaldi antenna has been designed using copper for patch and ground layers and FR4 for the substrate layer. The antenna is operating over a band from 3.38 to 10GHz. Also the antenna parameters which are reflection coefficient (S11), directivity and radiation pattern are included in this study. Moreover, to optimize the antenna radiation direction and reduce the sidelobe leve, a Tapered Slot Edge (TSE) technique is applied and shows -18.8 dB and 6.58 dBi for side lobe level and directivity respectively at 5 GHz. The Specific Absorption Rate (SAR) is the tool used to indicate the tumor location in the coordinate system (x, y, z) in this research. Tests have been done with CST microwave studio using a breast model built with a radius of 50mm. For simulation tumor radius was changed from 10mm, 7mm and 5mm respectively. Also the antenna location changed to 3 different places for reliability. The tumor location is approximated to the same coordinates of the maximum specific absorption rate (SAR) which is examined at 5GHz, 6GHz, 7GHz and 8GHz. Simulations successfully show the correct tumor location while the antenna is facing the tumor. Keywords: Antipodal Vivaldi Antenna, Tapered Slot Edges (TSE), Specific Absorption Rate (SAR), Tumor Detection and Coordinates.
Cancer Detection Using Printed Antenna Placed on Human Breast Model
In this study electromagnetic properties of female human breast were used for cancer tissue detection. Deviation of the malignant cells’ properties from those of healthy cells’ directly affect the performance of an antenna placed on the breast. Return loss, gain and directivity of an antenna designed on an FR4 substrate were used as parameters for studying the effects of the normal and cancerous tissues. Planar and hemispherical shaped, multilayer breast models, composed of skin, fat and part of the connected lymph nodes were modeled and designed. The antenna was designed, fabricated, and return loss measurements were taken by a network analyzer (Rohde & Schwarz ZWB20). Separate measurements were taken in free space and when placed on a healthy human breast. Simulations of normal breast models carried out by CST Microwave Studio were in a good agreement with the measured results. Tumors in breast and lymph nodes with different sizes and numbers defined according to American Joint Committee on Cancer (AJCC) were used to model the first and second stages of cancer. The presented work is shown to be a promising method for breast cancer studies, thereby reducing the need for invasive surgical operations. Keywords: Breast cancer, Microstrip antenna, Biomedical.
Channel Estimation for Millimeter Wave Cellular Systems
The imagination of our future on wireless base networks is beyond science fiction. By emerging 2020, most of the wireless communication systems are going to suffer by the vast increase in the number of traffic in their network which leads to the lower data rate and higher latency. The current cellular network provides the stable connection for the demanding users, but in near future this technology will need a drastic improvement as it crosses its capabilities when users want more data. Therefore, 4G is going to be replaced by 5G. 5G technology, which is currently under development, is going to achieve a couple of objectives such as higher spectral efficiency, preferable battery life for handsets, higher capacity, improvement in the coverage area and lower latency. For this technology, to be realistic and operative as it is promised, some upcoming technologies such as massive MIMO, millimeter wave, beamforming and small cells are going to aid 5G system. Millimeter wave along with massive MIMO provides a high data rate within a large coverage area. Additionally, beamforming manages the massive transmission of data to all over the medium and directs the data to a specific user. In every wireless network, there are losses due to the propagation of medium, also known as channel. The channel is usually estimated by the signal processing module to assist the receiver in order to eliminate channel’s severe domination. For each generation of wireless cellular networks, a model by all the factors that have an impact on the signal will be presented as a fixed modeled and then channel is estimated and compared to the modeled version to have constancy. 5G network channel should be carefully estimated due to the use of high frequency band and the massive number of antennas. In this thesis, our focus is on estimation of channel through some training procedures. We try to pre-code the incoming input signal with some code words to reach as close as possible to the actual channel. Accordingly, BER, MSE and spectral efficiency will be illustrated to provide the channel performance and stability of the mm-wave systems. Keywords: 5G, Beamforming, Channel estimation, Precoding, Massive MIMO, Millimeter Wave and Small Cells.
Recursive Inverse Adaptive Filtering for Fading Communication Channels
Adaptive filtering is an important and rapidly developing discipline in the signal processing and communications field. Many different algorithms were developed throughout the years. LMS and RLS being the most well-known and studied of the algorithms. Like in many disciplines in engineering there exists many disadvantages in these algorithms and so variations were proposed. The main parameters sought after in a new algorithm were convergence speed, stability, and computational complexity. LMS suffers in the former as it has generally low convergence speed. Meanwhile, RLS main disadvantage is the computational complexity it introduces, in addition to being unstable in varying channel settings. RI adaptive filtering algorithm proposed in 2009 provides some solutions to the aforementioned issues. In this thesis, the use of the RI algorithm in common communication channel setting is simulated. The performance of the algorithm is studied and compared to some other adaptive filtering algorithms in terms of BER. Both channel estimation and channel equalization performances are investigated and commented upon. The conclusions reached will be that RI outperforms RLS in terms of convergence speed and computational complexity in all cases studied while giving similar results to NLMS in frequency selective channels but outperforming it in flat fading channels. Keywords: Adaptive filter, recursive inverse, RLS, communication channel