Graduate Courses given by Tamer Ölmez
Data Acquisition with
Embedded Linux System
(This course is given in Turkish as "Gömülü
Linuks Sistemleriyle Veri Toplama")
Basics of data acquisition processes. Embedded Linux development kit (BeagleBone-Black): Installing, terminal commands, scripts, devices on the kit, and C programming. Programming environments (Qt and Python IDE) for the embedded Linux development kit. Device tree, power management and device control for the embedded Linux development kit. Introduction to device driver design for the embedded Linux development kit: Kernel setting, compiling, loading, and controlling kernel modules. Character device implementation steps; designing, compiling, inserting a character device into the kernel as a module, and character device controlling. Controlling of the general purpose IO ports, interrupts, timer, ADC, PWM, UART/SPI/I2C devices in a kernel module. Data acquisition applications with the Python running on the BeagleBone-Black. Data transmission applications on the network via wireless communication.
Machine
Learning and Genetic Algorithms
(This course is given in Turkish as
"Makina Ögrenmesi ve Genetik Algoritmalar")
Basic concepts in machine learning: Knowledge representation methods. Transforms in knowledge representation. Feature extraction methods for patterns in 2 and 3 dimension. Classifiers: Bayesian classifier, c-means, K-nearest neighbor classifier. Artificial neural networks: Perceptron, multi layer perceptron, Kohonen network, LVQ, GAL, RCE, Hopfield networks. Concepts and procedures learning. Learning by classification and discovery. Evolution algorithms. Genetic algorithms: Reproduction, crossover and mutation. Genetic pool, fitness function, coding, scaling. Genetic learning. Training of artificial neural networks by the genetic algorithms. Basic concepts in fuzzy logic. Fuzzy classifiers.
Basics of
Biomedical Informatics
An introduction to the fundamental principles of medical informatics.
Computer-based tools in health care, human computer interfaces. An introduction
to computer applications in medicine. Medical records, database, data
representation, data acquisition and presentation. Biological signal
processing. Knowledge-based systems. Medical artificial intelligence. Medical
decision and analysis. Introduction to health information systems:
communication and networks. Telemedicine and Internet applications. Advance
topics in biomedical informatics.
Medical Imaging
(This course is given in Turkish as
"Medikal Görüntüleme")
Imaging methods in 2D: X-ray, ultrasound, magnetic resonance imaging (MRI), computer tomography (CT). Reconstruction algorithms in medicine. Image formation methods in 3D. Görüntü dizileri. Classification of biomedical images (MR and CT). Volumetric image representation, interpolation. Boundary and object labelling in 3D. Feature extraction in 2-D. Basic concepts in image processing. Image enhancement: Histogram equalization, low-pass and high-pass filters, median filter. Image transforms: DFT, DCT, Cosine, Hough and Gabor filter. Image compression: Lossy and lossless compression techniques. Image segmentation: Edge detection, region growing. Rotation, translation and scaling in 3D. Projections. Surface rendering. Shading. Virtual reality in medicine.
Undergraduate Courses
Computer Based Systems in Medicine
(This course is given in Turkish as "Tıp
Alanında Kullanılan Bilgisayar Destekli Düzenler")
Origins and properties of the biological signals: Biological signals,
Biological sensors. Basic information about the computer systems: Linux
installation, Linux terminal commands, Beaglebone Black (BBB) embedded system
hardware and software installation, Shell scripting, C programming on
Beaglebone Black, Python scripting. Biological signal acquisition on Beaglebone
Black: Controlling Beaglebone Black peripheral devices (GPIOs, Timer, ADC,
UART/I2C/SPI, PWM, FTDI-USB) by using Python Libraries. Sample programs on data
acquisition using BBB. Biological signal and image processing: Filter design
for one dimensional signals, Fourier transform,
Data visualization by using Web Server on BBB. Compression and
transmission of the biological signals: Biological signal compression methods,
serial communication on BBB, Wifi communication on BBB, Bluetooth communication
on BBB, and data communication over network by using BBB..
Real-Time System Design by Digital Signal Processors
(This course is given in Turkish as "Sayısal İşaret İşlemciler ile Gerçek
Zamanda Sistem Tasarımı" )
Fundamental concepts of real-time signal processing. Architecture of
real-time signal processors. Hardware interface implemented by peripheral
units. DSP programming techniques. Software development tools. Analog/digital
and digital/analog converter, sampling. Real-time signal processing techniques.
Real time implementation of signal processing algorithms, and frequecy domain
processing. Data compressing. Learning process and classifiers in real-time.
Introduction to Medical Electronics
(This course is given in Turkish as
"Tıp Elektroniğine Giriş" )
Human instrumentation systems. Transducers, amplifiers, filters, patient isolation and care devices. Biological signals formation. Measurement of electroneurogram, electromiyogram, electrocardiogram, electroensefalogram, electroretinogram, electrookulogram signals, evoked potentials, blood pressure and blood flow. Analysis and processing of biological signals. Problems encountered in using medical devices. Noise reduction techniques.
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