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Showing posts with label Bio-instrumentation. Show all posts
Showing posts with label Bio-instrumentation. Show all posts

DNA computing ppt

Paper presentation: DNA COMPUTING

Abstract

Silicon microprocessors have been the heart of computing world for more than forty years. Computer chip manufacturers are furiously racing to make the next microprocessor that will topple speed records and in the process are cramming more and more electronic devices onto the microprocessor. Sooner or later the physical speed and miniaturization limits of silicon microprocessors is bound to hit a wall.

Chipmakers need a new material to produce faster computing speed with fewer complexities. You won’t believe where scientists have found this new material. DNA, the material our genes are made of, is being used to build the next generation of microprocessors. Scientists are using this genetic material to create nano-computers that might take the place of silicon computers in the next decade.

A nascent technology that uses DNA molecules to build computers that are faster than the world’s most powerful human-built computers is called DNA computing. Molecular biologists are beginning to unravel the information processing tools such as enzymes, copying tools, proofreading mechanisms and so on, that evolution has spent millions of years refining. Now we are taking those tools in large numbers molecules and using them as biological computer processors.

DNA computing has a great deal of advantage over conventional silicon-based computing. DNA computers can store billions of times more data than your personal computer. DNA computers have the ability to work in a massively parallel fashion, performing many calculations simultaneously. DNA molecules that provide the input can also provide all the necessary operational energy.

DNA computing has made a remarkable progress in almost every field. It has found application in fields like biomedical, pharmaceutical, information security, cracking secret codes, etc.
Scientists and researchers believe that in the foreseeable future DNA computing could scale up to great heights!


Microcontroller based- anesthesia injector

MICROCONTROLLER BASED ANESTHESIA INJECTOR

ABSTRACT

In the hospitals when any major operation is performed, the patient must be in anesthetize condition. If the operation lasts for a long time, say for suppose for 4 or 5 hours, complete dose of anesthesia cannot be administered in a single stroke. It may lead to the patient’s death. If lower amount of anesthesia is administered, the patient may wakeup at the middle of the operation.

To avoid this, the anesthetist administers few milliliters of anesthesia per hour to the patient. If the anesthetist fails to administer the anesthesia to the patient at the particular time interval, other allied problems may arise.

To overcome such hazardous problems the design of an automatic operation of an anesthesia machine based on a micro-controller is effective. In this system a keypad is provided along with the microcontroller and syringe infusion pump. The anesthetist can set the level of anesthesia in terms of milliliters per hour to administer anesthesia to the patient with the help of keypad.

After receiving the signal from the keypad, the microcontroller controls the signal to the desire level and fed into the stepper motor to drive the infusion pump in proper manner. The anesthesia is administered to the patient according to the stepper motor rotation (the syringe will move forward or backward direction).

This particular paper will be very much useful to physicians to see the current position of anesthesia of the patients. If the level of anesthesia is decreased to lower level (set value), the alarm will be initiated to alert the physician to refill the anesthesia in the Syringe Pump to continue the process.


Robotics, Paper presentation

Bio-inspired Robotics

Introduction:

Our approach is characterized with a strong inclination for biological inspiration in which examples in nature — social insects in particular — are used as a way of designing strategies for controlling mobile robots. This approach has been successfully applied to the study of task, namely, Ant’s algorithms used in computer networks for routing data between Routers.
This phenomenon found in ants to derive the necessary behaviors for accomplishing this task. We study a species of ant known to possess this capability.

“bio-Computing” is a way “to understand how the relation of brain, body and environment produce behavior, to clarify the essential problems posed, and to devise and test hypotheses under realistic conditions” social insects were capable of successfully navigating and acting in the face of uncertain and unpredictable environments. It was reasoned that if a single robot required complex systems and techniques in order to perform in a reliable manner, then perhaps intelligent systems could be designed with many “simpler” robots using a minimalist approach to sensing and actuation; where group behavior is an emergent property and control is decentralized. Could system reliability be achieved by trading complexity for redundancy coupled with ”randomness” used to explore possible solution paths, which are often traits found in social insect colonies? May be, biology can teach us a thing or two about engineering swarms of simple interacting robots, and the theoretical foundations developed to model and explain these behaviors found in insect colonies can be used to underpin a more rigorous approach to collective robot design. Nature has already demonstrated the feasibility of this approach by way of the social insects.



Bio-instrumentation 2

paper presentation, engineering paper presentations, seminars, seminar topics, paper presentation topics, ECE, EEE, CSE, IT, MECH, AERO, AUTO, CHEM.
Some Definitions:
Measurand: the physical property being investigated Sensor: converts the measurand into an electrical signal
Analog processing: conditions the signal in the analog domain, typically amplification, electrical isolation, filtering
A/D: analog to digital conversion at a specified sampling frequency and precision
Digital processing: conditions the signal in the digital domain, typically, filtering, compression,  enhancements such as digital zoom and contrast enhancement 
Display: organizes the information in a manner understandable to the user, the user interface
Storage: e.g. disk or paper output
D/A: converts a digital signal (based on some reaction to the original analog signal) back
to the analog domain
Actuator: converts and electrical signal into a mechanical action.
Example: A treatment system that controls a laser based on tissue damage. What are the
various pieces in this system?
More definitions, based on operation of instrumentation
Direct: a measurement of the quantity of interest (e.g. measure finger length)
Indirect: a measurement of a quantity related to the quantity of interest (e.g. measurement
of an X-ray of a finger)


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Bio-instrumentation

paper presentation, engineering paper presentations, seminars, seminar topics, paper presentation topics, ECE, EEE, CSE, IT, MECH, AERO, AUTO, CHEM.
So what is the temperature resolution?
In this case, use statistical analysis, given a % confidence we want to achieve of correctly being able to distinguish two different temperatures. If the distribution is assumed to be Gaussian, we can use a multitude of test to determine the resolution (students t-test is easy).Precision- is the number of distinguishable alternatives from which the result is selected. In signals that have been A/D converted, this can be no more than 2^ # bits in the converter.

Range = resolution * precision
Ex. A digital thermometer
Range: 0 to 99.9°C
Display is 3 digits XX.X, so assume resolution is 0.1 °C
Precision is 1000, or about 10 bits
Please note: Webster has another definition of precision (the quality of obtaining the
same output from repeated measurement of the same input). The word “precision” can be
used in both cases. In this class, I am most concerned with distinguishable alternatives.
Reproducibility- is the ability to give the same output for equal inputs over some period
of time (full range or standard deviation).
Specificity- is the ability of an instrument to respond to the desired input only. Signal-tonoise
ratio is one measure. The number of false positives in a binary system is another.


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