CMOS and TTL compliance

There was a time, when all IC’s were only TTL type. They were marked as 74LS or 74ALS. But then there came CMOS types of semiconductor. They are usually marked CDxx. And lately there appeared combined semiconductors who are compliant to both types. They usually are marked as 74HC or 74HCT. TTL are faster than CMOS, but they sink more power. They are powered from 5V source. To diminish the power consumption, the CMOS were developed. They can work with supplied voltages in range 3 to 15V. The main disadvantage is that they are static sensitive. So you always have to be grounded when working with CMOS. Now both types of semiconductors are widely used. Sometimes there is as dilemma to connect TTL to CMOS. You cannot connect directly TTL to CMOS as there are different supply voltages. So you need some compliance circuit. The simplest can be bipolar transistor…

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Skin lession boundary tracing algorithm

I found on Matlab very handy tool which allows easily to trace boundaries of objects in a picture. So I adopted it to skin lesions. This can be used for automatic detection of skin irregularities and used to calculate lesion properties like asymmetry of shape, or border irregularities, who can help in detecting melanoma. There are numerous of investigations done, so I only put few examples on how it looks like. I will give you my source code, so you can try it by your own. Look at my results: 1) And it also finds center of mass:

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ABCD method for screening skin cancer

To improve diagnostic accuracy the  ABCD rule of lesion screening is widely used based on  asymmetry (A), border (B), color (C), and differential structure (D) measuring. •         A total dermatoscopic value (TDV) results from the calculation TDV = A·1,3 + B·0,1 + C·0,5 + D·0,5 •         This score contributes to the differentiation between benign and malignant lesions:                                            1,00  –  4,75 – benign skin lesion                                            4,75  –  5,45 – suspicious                                            More than 5,45 – melanoma Asymmetry A – Asymmetry of Shape, Structure and Color. The lesion is divided in four regions and there is symmetry inspected across x or y axis. If asymmetry is only by one axis it gives 1 point and if on both axis there are 2 points calculated. So for shape, structure and color, there can be 6 points maximum.

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Skin imaging methods for melanoma diagnosis

    There are many skin image capture methodologies developed and used. Here are short review of them: Dermatoscopic photography The deepest layer of skin can be reached – Papillary dermis Resolution – depends on optical system View of skin – Horizontal The main disadvantage is reflections of light from skin surface – stratum cornea.   Dermatoscopic oil immersion photography The deepest layer of skin can be reached – Papillary dermis Resolution – depends on optical system View of skin – Horizontal Reflections of light from skin surface are smaller because of oil used between camera optics and skin.

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Polarizer test

I used simple lamp directed to glossy table surface. One polarizer is in front of lamp and other is in front of lens of digital camera. Both polarizes are perpendicularly oriented to each other. How does this work? There is a theory about an angle on which the incident polarized electromagnetic waves turn reflects from surface with polarization plane turned in 90 degrees. When light going through polarizer towards the surface, the light is polarized in one direction and when it reflects from surface it is turned by 90 degrees and those waves are filtered by another perpendicular polarizer in front of lens.

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Removing 60Hz from ECG using digital band stop filter

Let’s make a filter, which filters off the 60Hz frequency from ECG signal. As we know American power supply is 60Hz. This is common noise in biomedical signals, while they are powered from industrial power supply. This type of noise can be defined easily and can be filtered as parameters of noise are known. Here is one example of how to implement FIR filter using mathematical tools, like Matlab. This can be done by using microcontroller, like ARM or even ARM, because the frequencies are up to 1 KHz. Initial conditions: f0=60Hz – pover supply frequency; fs=500Hz – sampling rate; frequencies who define complex zeros: we get w0=0.754; Positions of complex zeros: Zeros and poles in z plane System Function From it we can calculate filter coefficients: And filter coefficients:         Also we know that: And here we get filter characteristics: We have band stop filter at 60Hz and…

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