Two major dilemmas for classical edge detection are; firstly the choice of appropriate threshold to segregate noise and true edges and secondly to opt for an appropriate scale for edge detection. In this paper a wavelet based edge detection paradigm is envisaged to work for diverse images. The image is decomposed according to its resolution, structural parameters and noise level by multilevel wavelet decomposition using Quadrature Mirror Filters(QMF). The property that image structural information is preserved at each decomposition level whereas noise is partially reduced within subbands, is being exploited. The lower resolution wavelet detail bands are interpolated to the original image size that partially recaptures the missing edge pixels besides facilitating matrix multiplications of the concordant wavelet bands. An innovative wavelet synthesis approach is conceived based on wavelet scale correlation of the concordant detail bands such that the reconstructed image fabricates an edge map of the image. Although this technique falls short to spot few edge pixels at contours but the results are better than the classical operators in noisy scenario and noise elimination is significant in the edge maps keeping default threshold constraint. Wavelet based scalability in edge detection has been envasiged along its closed form analytical expression.
Biofertilizer enhance organic materials availability to plant more than an ordinary organic fertilizer. This in an environmentally friendly biotechnological approach also offers as an alternative to hazardous chemical fertilizers. An experiment was carried out in the experimental field of the department of Botany, JUW, Karachi to investigate the potential of different agro-waste residues as raw organic fertilizer and microbial composted biofertilizer with reference to the growth and nutritional status of green gram. These agro-waste products viz, Wheat Bran, Mustard Oil Cake, Cicer Brown Husk, Peanut Shell, Tea Waste and FYM were composted with Aspergillus niger to form biodegradable value added product (biofertilizer). Two levels of fertilizer viz. Uncomposted raw organic fertilizer and composted biofertilizer (Set-1 & Set-2) were used as experimental variables and applied @10ton/ ha as a treatment to each pot and then examined their effects on growth and biochemical parameters of study crop. The observed data revealed that a significant increase in plant root and shoot length, fresh and dry mass of mung bean (Vigna radiate.L) were observed due to PSF composted biofertilizer inoculation. This can also be attributed to the increased uptake of nutrients in the plants leading to increase in carbohydrate and protein synthesis. All the parameters performed better with agro-waste as PSF-composted biofertilizer as compared to organic fertilizer form.
This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modeled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor. The ACSA approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modeled in Simulink and the ACSA is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
Wireless Underground Sensor Network (WUSN) can be used to monitor a variety of conditions, such as soil properties for agricultural applications and toxic substances for environmental monitoring. Unlike existing methods of monitoring underground conditions, which rely on buried sensors connected via wire to the surface, WUSN devices are deployed completely below ground and do not require any wired connections. Each device contains all necessary sensors, memory, a processor, a radio, and a power source. This makes their deployment much simpler than existing underground sensing solutions. Wireless communication within a dense substance such as soil or rock is, however, significantly more challenging than through air. This factor, combined with the necessity to conserve energy due to the difficulty of unearthing and recharging WUSN devices, requires that communication protocols be redesigned to be as efficient as possible. This work discusses an energy efficient clustered wireless underground sensor network for the soil monitoring. The results show that the proposed method reduces the energy consumption and enhances the lifetime of the wireless underground sensor network lifetime over its comparatives.
-- This study presents a speed controller design for a switched reluctance (SR) motor in order to achieve minimum torque ripple and high control performance. First of all, SR motor convertor designed for soft chopping is chosen. This converter as well as producing less torque ripple, provides more degrees of freedom for SR motor drive controller. A PID, Fuzzy PID, Neural Networks controller and a switching algorithm for turn-on and turn-off degree of each phase of motor form speed control loop of SR motor drive. The primary parameters of controller are achieved by trial and error. But eventually an optimization algorithm to reach the goals and constraints in different set points is defined and its parameters are optimized with a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant colony Optimization (ACSO). This algorithm optimized the turn-on and turn-off degrees of each phase, the parameters of PID controller in transient state, and parameters of PID controller that considered for reducing the torque ripple in steady state. An Comparative study of the all the models and best among the controllers is proposed. The proposed control algorithm was simulated using MATLAB / Simulink software package and an application example of 6/4 SRM to validate the performance of designed algorithm.