Kenan Danisman

A different approach for the computation of refractive index change in quantum-well diode lasers for different injection levels

A model is developed for the carrier induced refractive-index change in Quantum-well (QW) lasers which affects different mechanisms. The model is based on Artificial Neural Network (ANN) which provides a powerful approach for setting up a complex non-linear model. Different algorithms are tried and tested for different injection current levels. Both the training and the test results for refractive-index change are in very good agreement with the experimental findings reported elsewhere.

Measurement of temperature-dependent reflectivity of Cu and Al in the range 30-1000 degrees C

In the CO2 laser cutting process it is important to predict the absorption mechanism during laser-workpiece interaction, since the form of the dependence of absorption on temperature greatly affects the form of the resulting temperature profile in the material. In order to be able to use any of the theoretical models for absorption with any degree of confidence, it appears necessary to obtain experimental data on the subject. Consequently an experiment to determine the variation of absorption with temperature is necessary. A reflectivity method is employed to measure the temperature-dependent reflection coefficient experimentally. The results obtained from the experiment for aluminium and copper samples are then compared with the theoretical results. In the analysis, high-temperature surface oxidation is also included.

Closed-loop control of blood glucose level in type-1 diabetics: A simulation study

Survey on diabetes is one of the popular fields of biomedical signal processing. In this paper, a closed-loop system which utilizes modified Stolwijk-Hardy glucose insulin interaction model is considered. The modified model was derived by adding an exogenous insulin infusion term. Two control algorithms are used for exogenous insulin infusion: a Mamdani type fuzzy logic controller (FLC), and a fuzzy-PID controller. Simulations are performed to assess control function in terms of keeping desired steady state plasma glucose level (0.81 mg/ml) against to exogenous glucose input. Simulation results are notable and significant in terms of controlling blood glucose level (BGL). The control algorithms that applied to the model are firstly proposed, therefore this study is made a contribution to the literature.

Optimization of affecting parameters in relation to pulsed CO2 laser design

In the present study, the optimal design of CO2 laser was investigated and a mathematical model developed for this purpose. The mathematical model covers energy levels, transitions of molecules between these levels and molecular collisional decay mechanism. The effect of gas mixture ratios on molecular population at excited states and on efficiency are interpreted as results.

An embedded fingerprint authentication system integrated with a hardware-based truly random number generator

Recent advances in information security requires randomly selected strong keys. Most of these keys are generated by software-based random number generators. However, implementing a Truly Random Number Generator (TRNG) without using a hardware-supported platform is not reliable. In this paper, a fingerprint authentication system using a hardware-based TRNG to produce a private key that encrypts the fingerprint template of a person is presented. The designed hardware can easily be mounted on a standard or embedded PC via its PCI interface to produce random number keys. Random numbers forming the private key is guaranteed to be true because it passes a two-level randomness test evaluated first on the FPGA then on the PC by applying the full NIST test suite. The whole system implements an AES-based encryption scheme to store the persons secret stored on a smart or glossary card safely. The main contribution of the work is the use of new-generation hardware-based TRNGs to enhance the security of a fingerprint authentication system.

Design of a high precision temperature measurement system

An experimental method is designed and proposed in order to estimate the non-linearity, test and the calibration of a thermocouple using artificial neural network (ANN) based algorithms integrated in a virtual instrument (VI). An ANN and a data acquisition board with signal conditioning unit designed are used for data optimization and to collect experimental data respectively. In both training and testing phases of the ANN, Wavetek 9100 calibration unit is used to obtain the experimental data. After the successful training completion of the ANN, it is used as a neural linearizer to calculate the temperature from the thermocouple’s output voltage.

A multi-layer perseptron network model for a quantum-well laser diode

This study presents a different approach to compute the modal peak gain, differential modal refractive index change, and the linewidth enhancement factor (alpha parameter) of an InGaAs deep quantum-well laser sample from a single model. Each of these optical quantities requires many calculations with the use of different theories, assumptions, and estimations in addition to strong background knowledge. The approach is based on artificial neural networks (ANNs) which are capable of representing complex input/output relationship. The model results agree well with the measured data from an InGaAs quantum-well (QW) laser sample.

Neural computation of alpha parameter with the use of differential gain, wavelength, and number of quantum wells

A different method to determine α (Alpha) parameter for different number of Quantum-wells is presented. The Levenberg-Marquardt algorithm is used to train the Artificial Neural Networks (ANNs) which has a quadratic speed of convergence. Both the computed and the test results are in very good agreement with the experimental results reported elsewhere.

Determination of amplitude-phase relationship in laser diodes using linear system approximation

In this study, amplitude-phase relationship of laser diodes is analyzed under modulation with the help of the transfer functions. The dynamic behavior of laser diodes is observed as functions of both damping and relaxation resonance frequencies. Within the linear system approach, the amplitude-phase relationship is harmonious up to some extent and both of them have dependence on each other. Phase changes occurring within the system are not stable and cause oscillations which prevent the system from stable working. These oscillations have some threshold value and the system may be driven in to chaos after this point.

Prediction of Dynamics of Chaotic Chua's Circuit with Artificial Neural Network

In this paper prediction of dynamics of chaotic Chuas circuit is made using artificial neural networks (ANN). The required data set to train and test the ANN were obtained with numerical analyzes of state equations of Chuas circuit. It is obviously seen that the predicted dynamics at the out of the ANN are similar with circuit dynamics. Without any necessity to system parameters and initial states which are required for Chuas circuit that presents chaotic behavior, an ANN based chaotic signal generator can be designed using this paper.