projection

Open Access Article

1 - Defect Detection using Depth Resolvable Statistical Post Processing in Non-Stationary Thermal Wave Imaging
G.V.P. Chandra Sekhar Yadav V. S. Ghali Naik R. Baloji

10.52547/jist.15690.10.38.132

Defects that are generated during various phases of manufacturing or transporting limit the future applicability and serviceability of materials. In order to detect these defects a non-destructive testing modality is required. Depth resolvable subsurface anomaly detecti More

Defects that are generated during various phases of manufacturing or transporting limit the future applicability and serviceability of materials. In order to detect these defects a non-destructive testing modality is required. Depth resolvable subsurface anomaly detection in non-stationary thermal wave imaging is a vital outcome for a reliable prominent investigation of materials due to its fast, remote and non-destructive features. The present work solves the 3-Dimensional heat diffusion equation under the stipulated boundary conditions using green’s function based analytical approach for recently introduced quadratic frequency modulated thermal wave imaging (with FLIR SC 655A as infrared sensor with spectral range of 7.5-14µm and 25 fps) to explore the subsurface details with improved sensitivity and resolution. The temperature response obtained by solving the 3-Dimensional heat diffusion equation is used along with random projection-based statistical post-processing approach to resolve the subsurface details by imposing a band of low frequencies (0.01-0.1 Hz) over a carbon fiber reinforced polymer for experimentation and extracting orthonormal projection coefficients to improve the defect detection with enhanced depth resolution. Orthonormal projection coefficients are obtained by projecting the orthonormal features of the random vectors that are extracted by using Gram-Schmidt algorithm, on the mean removed dynamic thermal data. Further, defect detectability of random projection-based post-processing approach is validated by comparing the full width at half maxima (FWHM) and signal to noise ratio (SNR) of the processed results of the conventional approaches. Random projection provides detailed visualization of defects with 31% detectability even for deeper and small defects in contrast to conventional post processing modalities. Additionally, the subsurface anomalies are compared with their sizes based on full width at half maxima (FWHM) with a maximum error of 0.99% for random projection approach. Manuscript profile

Open Access Article

2 - Mathematical Modeling of Flow Control Mechanism in Wireless Network-on-Chip
Fardad Rad Marzieh Gerami

10.52547/jist.19923.11.41.48

Network-on-chip (NoC) is an effective interconnection solution of multicore chips. In recent years, wireless interfaces (WIs) are used in NoCs to reduce the delay and power consumption between long-distance cores. This new communication structure is called wireless netw More

Network-on-chip (NoC) is an effective interconnection solution of multicore chips. In recent years, wireless interfaces (WIs) are used in NoCs to reduce the delay and power consumption between long-distance cores. This new communication structure is called wireless network-on-chip (WiNoC). Compared to the wired links, demand to use the shared wireless links leads to congestion in WiNoCs. This problem increases the average packet latency as well as the network latency. However, using an efficient control mechanism will have a great impact on the efficiency and performance of the WiNoCs. In this paper, a mathematical modeling-based flow control mechanism in WiNoCs has been investigated. At first, the flow control problem has been modeled as a utility-based optimization problem with the wireless bandwidth capacity constraints and flow rate of processing cores. Next, the initial problem has been transformed into a dual problem without limitations and the best solution of the dual problem is obtained by the gradient projection method. Finally, an iterative algorithm is proposed in a WiNoC to control the flow rate of each core. The simulation results of synthetic traffic patterns show that the proposed algorithm can control and regulate the flow rate of each core with an acceptable convergence. Hence, the network throughput will be significantly improved. Manuscript profile

Open Access Article

3 - Multi-Human Face Detection Using Gabor Filters and Neural Networks in Internet Images
R. Mohammadian M. Mahlouji

This paper presents a new method for multi human face detection from frontal view in internet images with complex background. The main goal is to reduce false acceptance error rate using feed forward back propagation multilayer perceptron neural network and Gabor energy More

This paper presents a new method for multi human face detection from frontal view in internet images with complex background. The main goal is to reduce false acceptance error rate using feed forward back propagation multilayer perceptron neural network and Gabor energy feature in the frequency domain. In the proposed method, the false acceptance error extremely decreased using a combination of three operations; introducing a new preprocessing algorithm to increase the quality of Gabor energy feature, performing two step monitoring on the input and output images, and utilizing three indexes of facial components recognition in Gabor energy output. In this paper, a new image database namely RFD is collected from internet images including 583 non repetitive face images and 9961 non face images with size of 192×168. The face detection accuracy of the proposed method on RFD images is 88.16% with false acceptance rate of 0.48% or 48 false acceptances only, while Viola-Jones algorithm has 124 false acceptances. Therefore, the false acceptance error of the proposed method has reduced by 2.5 times compared to that of Viola-Jones algorithm. Manuscript profile

Open Access Article

4 - Identification and Contribution Evaluation of Interharmonic Sources in a Power System Using Adaptive Linear Neuron and Superposition and Projection Method
P. Sarafrazi H. R. Mohammadi

In this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and proj More

In this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and projection method which needs the norton equivalent circuit of loads and supply network. Also in the proposed method, a two-stage adaptive linear neuron is used for determining the interharmonic components of a signal. The effectiveness of the proposed method has been shown through simulation studies in the MATLAB/SIMULINK software. The simulation results show the capability of the proposed method for identification and contribution evaluation of interharmonic sources in a power system. Manuscript profile

Open Access Article

5 - Identification and Contribution Evaluation of Interharmonic Sources in a Power System Using Adaptive Linear Neuron and Superposition and Projection Method
P. Sarafrazi H. R. Mohammadi

In this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and proj More

In this paper a new method for identification of interharmonic producing loads in a power system is proposed which is capable of evaluating the contribution of each individual load in the point of common coupling. This method is based on using the superposition and projection method which needs the norton equivalent circuit of loads and supply network. Also in the proposed method, a two-stage adaptive linear neuron is used for determining the interharmonic components of a signal. The effectiveness of the proposed method has been shown through simulation studies in the MATLAB/SIMULINK software. The simulation results show the capability of the proposed method for identification and contribution evaluation of interharmonic sources in a power system. Manuscript profile

Open Access Article

6 - Family of Variable Step-Size Affine Projection Adaptive Algorithms in Diffusion Distributed Networks
Mohammad S. E. Abadi E. Heydari

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diff More

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diffusion Affine Projection Algorithm (VSS-DAPA) to improve the performance of the Diffusion Affine Projection Algorithm (DAPA) in distributed networks. The variable step-size of each node is obtained by minimizing the Mean-Square Deviation (MSD) in that node. In comparison with Diffusion Affine Projection Algorithm (DAPA), the VSS-DAPA algorithm has faster convergence speed and lower steady-state error. To reduce the computational complexity of VSS-DAPA, the Variable Step-Size Selective Regressors Diffusion Affine Projection Algorithm (VSS-SR-DAPA), the Variable Step-Size Dynamic Selection of Diffusion Affine Projection Algorithm (VSS-DS-DAPA) and Variable Step-Size Selective Partial Update Diffusion Affine Projection Algorithm (VSS-SPU-DAPA) are proposed. Simulation results show the good performance of proposed algorithms in convergence speed and steady-state error. Manuscript profile

Open Access Article

7 - A study on narcissism and projection in the story of the Hunting and lion of Rumi's Masnavi
Mohammad karimi Badrieh Ghavami

10.52547/qap.32680.4.4.96

The word narcissism was first used by Freud. Of course, others, before Freud, used it in the sense of selfishness and humiliation to describe the psychological attitude in clinical psychology. This personality disorder often leads to projection. Projection is one of the More

The word narcissism was first used by Freud. Of course, others, before Freud, used it in the sense of selfishness and humiliation to describe the psychological attitude in clinical psychology. This personality disorder often leads to projection. Projection is one of the psychological mechanisms through which one can understand the conscience and inside of human beings and gain a relative knowledge of their personality. Mawlana Jalaluddin Mohammad Balkhi (Rumi) in his works, especially in Masnavi, has paid attention to the psychological aspect of human behavior. This study tries to analyze narcissism and projection as one of the new concepts of psychology in the story of the Hunting and lion of Masnavi, with a descriptive-analytical approach and using library resources. The findings show that Rumi considers narcissistic personality to be the general problem of humanity and wants to find a solution to it. The whole of Masnavi is a struggle against narcissism and pride. In the story of the lion meets himself and comes to his truth. In fact, the rabbit did not kill the lion, the lion's anger and narcissism and his lack of trust in God caused his negligence and eventual destruction. The issue of meeting in Rumi's language is sometimes expressed with interpretations and signs such as water, spring, stream, face, seeing one's reflection in water, etc., which evokes the myth of Narcissus in the world of myth. Manuscript profile

Open Access Article

8 - Data-Driven Sliding Mode Control Based on Projection Recurrent Neural Network for HIV Infection: A Singular Value Approach
Ashkan Zarghami mehdi Siahi Fereidoun Nowshiravan Rahatabad

In the present study, drug treatment of HIV infection is investigated using a Data-Driven Sliding Mode Control (DDSMC) combined with a Projection Recurrent Neural Network (PRNN). The major objective is to establish the control law that eliminates the need for HIV infect More

In the present study, drug treatment of HIV infection is investigated using a Data-Driven Sliding Mode Control (DDSMC) combined with a Projection Recurrent Neural Network (PRNN). The major objective is to establish the control law that eliminates the need for HIV infection mathematical formulae and ensures that the physical limits of the actuator are reached. This is accomplished by creating the concepts of model-free adaptive control, in which the relation between input and output is described using local dynamic linearized models based on quasi-partial derivatives. To determine the DDSMC law, a performance index is first defined based on the fulfillment of a discrete-time exponential reaching condition. By turning this index into a quadratic programming problem, the dynamics of the PRNN are extracted based on projection theory. The closed-loop system is explicitly determined using the optimizer output equation and the closed-loop stability analysis is evaluated using the singular value approach. The simulation results reveal that the proposed algorithm has robust performance in conducting the state variables of HIV infection to the healthy equilibrium point in the face of model uncertainty and external disturbances when compared to one of the newest control techniques. Manuscript profile

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