Adaptive design of delta sigma modulators

In this thesis, a genetic algorithm based on differential evolution (DE) is used to generate delta sigma modulator (DSM) noise transfer functions (NTFs). These NTFs outperform those generated by an iterative approach described by Schreier and implemented in the delsig Matlab toolbox. Several lowpass and bandpass DSMs, as well as DSM\u27s designed specifically for and very low intermediate frequency (VLIF) receivers are designed using the algorithm developed in this thesis and compared to designs made using the delsig toolbox. The NTFs designed using the DE algorithm always have a higher dynamic range and signal to noise ratio than those designed using the delsig toolbox

Understanding and Design of an Arduino-based PID Controller

This thesis presents research and design of a Proportional, Integral, and Derivative (PID) controller that uses a microcontroller (Arduino) platform. The research part discusses the structure of a PID algorithm with some motivating work already performed with the Arduino-based PID controller from various fields. An inexpensive Arduino-based PID controller designed in the laboratory to control the temperature, consists of hardware parts: Arduino UNO, thermoelectric cooler, and electronic components while the software portion includes C/C++ programming. The PID parameters for a particular controller are found manually. The role of different PID parameters is discussed with the subsequent comparison between different modes of PID controllers. The designed system can effectively measure the temperature with an error of ± 0.6℃ while a stable temperature control with only slight deviation from the desired value (setpoint) is achieved. The designed system and concepts learned from the control system serve in pursuing inexpensive and precise ways to control physical parameters within a desired range in our laboratory

DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma : a preliminary report

Purpose: Neoadjuvant chemotherapy is recommended in patients with locally advanced breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables evaluation of the tumour neovasculature that occurs prior to any volume change, which helps identify early treatment failures and allows prompt implementation of second-line therapy. Material and methods: We conducted a prospective study in 14 patients with histopathologically proven breast cancer. DCE-MRI data were acquired using multisection, T1-weighted, 3D vibe sequences with fat suppression before, during, and after IV bolus injection (0.1 mmol/kg body weight, Gadoversetamide, Optimark). Post-processing of dynamic contrast perfusion data was done with the vendor's Tissue 4D software to generate various dynamic contrast parameters, i.e. Ktrans, Kep, Ve, initial area under the time signal curve (IAUC), apparent diffusion coefficient (ADC), and enhancement curve. Patients underwent MRI examinations at baseline, and then after two cycles, and finally at completion of chemotherapy. Results: Based on Sataloff criteria for pathological responses, four patients out of 14 were responders, and 10 were non-responders. At the 2nd MRI examination, IAUC was significantly smaller in responders than in non-responders (p = 0.023). When the results of the first and second MRI examinations were compared, Kep decreased from baseline to the second MRI (p = 0.03) in non-responders and in responders (p = 0.04). This change was statistically significant in both groups. The ADC values increased significantly in responders from baseline to the third MRI (p = 0.012). Conclusions: In our study, IAUC and ADC were the only parameters that reliably differentiated responders from non-responders after two and three cycles of chemotherapy