Investigation and evaluation of optical fiber bio-sensor for identification of biological materials

Number of pages: 71 File Format: word File Code: 32159
Year: Not Specified University Degree: Associate degree Category: Electronic Engineering
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  • Summary of Investigation and evaluation of optical fiber bio-sensor for identification of biological materials

    Master's thesis field: Electricity

    Trend: Electronics

    First chapter

    Fundamentals and generalities

    Introduction

    Today in various fields including Biosensors are used in medicine, chemical industry, food industry, environment and the production of pharmaceutical-health products [1]. In clinical and medical environments, it is very necessary to have tools to diagnose diseases. The development of systems that have a complete database of all types of diseases and provide an easy and favorable environment for their users is a topic that has attracted researchers of various sciences such as medicine and related scientific branches. One of the common methods of disease diagnosis is sampling, which is mainly done through blood or urine. This method also has several problems. The limitations of moment-to-moment access to the patient, the long duration of the diagnosis of the disease from the samples, the change of the concentration of the samples with the passage of time and the significant volume of the samples are among these problems. The use of rapid diagnosis methods or a combination of these methods that require the least amount of samples reduces time, cost and the possibility of errors in disease diagnosis. One of the ways to achieve this goal is to use biosensors.

    Sensors are a kind of disguise. Some sensors can be used alone and do not need other peripheral devices to read them, such as a mercury thermometer. The other group must be used with other devices, such as a thermocouple. Most of the sensors are electric or electronic, and the electric types have lower accuracy. Of course, there are other types. Sensors are widely used in our daily life, including automobiles, industrial machines, aerospace equipment, and even pharmaceuticals. Technical progress has led to the production of various types of sensors with MEMS technology. In most cases, this has resulted in high sensitivity.

    With the emergence of different ways to display the effect of energies, sensors are classified based on the energy under test, which the sensor receives.

    Temperature sensors

    Thermometer

    thermocouple

    thermistors and resistance temperature detectors

    bolometer

    calorimeter

    electrical resistance sensors

    electroscope

    voltmeter

    But why do we use sensors? As mentioned at the beginning of this speech, the sensors find the required information and convert the desired physical or chemical parameters into electrical signals. The advantages of electrical signals can be categorized as follows: - Easier and cheaper processing - Easy transmission - High accuracy

               –         High speed

                –         and.

    Biological sensors

    Sensors have many applications in medicine and health, chemical industry, defense industry and automobile industry. In the previous section, we discussed nano sensors. In this part, we introduce biosensors.

    The important features of nanosensors are higher selectivity, higher sensitivity, smaller dimensions and more efficient. Nanosensors are inherently smaller and more sensitive than other sensors. And as we said, they have the capacity to make their cost less than the cost of sensors in the market.

    In the military and national security sector, there is a need for very sensitive sensors that can be widely distributed so that radiation and biological biomes can be investigated with their help. In the medical field, there is a need for very sensitive sensors in the form of labs on a chip that can detect the smallest signs of cancer. In the aerospace industry, there is a need for nanosensors to be placed in the body of airplanes as a fixed warning system and to determine when the airplane needs repairs.

    In the automobile industry, nanosensors can be used for optimal fuel consumption. Also, in expensive cars, these nanosensors can be used to improve the state of the seat and the state of existing controls to suit different body postures. Next, it can be used in information technology to encourage the spread of always-on mobile computing systems. It can also be used as a mass of sensors in smartphones that are used for fixed communication between other smartphones and mobile computers!

    Principles and applications of biosensors

    Biosensor or biosensor is the name of a group of sensors. These sensors are designed to react with only one specific substance. The result of this reaction is in the form of messages that a microprocessor can analyze. These sensors consist of three parts.

    Biological acceptor or bioreceptor: a biological element (antibodies, nucleic acids, enzymes, cells and other biological substances) that can selectively react only with a specific substance.

    Bioreceptors used in biosensors are They are as follows:

    1. Enzyme

    2. Antibody

    3. Cell receptors

    4. DNA or RNA nucleic acids

    5. Microorganism or complete cell

    6. Texture

    7. Synthetic receptors

    Detector and converter: which come into action after the reaction of a specific substance with biological receptors and can send the type and amount of the reaction with different physical-chemical methods (for example, by examining electrochemical, optical, mass or thermal changes before and after the reaction) and by means of suitable signals to the processor.

    Common types of transducers used in biosensors include:

    Electrochemical sensors

    Electrochemical transducers are divided into three potentiometric categories (this method is based on measuring the potential of a battery at zero current). This potential is proportional to the logarithm of the concentration of the measured substance. (Voltammetry) a potential is applied to the cell to cause the oxidation (or reduction) of the measured substance and an increase or decrease in the current of the cell is created. This method is known as amperometry and conductometry of solutions containing ions are electron conductors. The magnitude of this conductivity changes due to the chemical reaction. The relationship between conductivity and concentration depends on the nature of the reaction. Optical sensors (luminescence, absorption and surface plasmon resonance) The methods used in optical biosensors include absorption spectroscopy, fluorescence spectroscopy, internal reflection spectroscopy, light diffraction. style="direction: rtl;">These sensors have two types sensitive to mass and thermal changes.

    All chemical processes are associated with the production or absorption of energy. This heat can be measured with a sensitive thermistor and attributed to the reaction rate.

    Signal processors that are mainly responsible for displaying the results and performing sensor calculations.

    Biological sensors have been the focus of many research centers in recent years. Biosensors or sensors based on biological materials now have a wide range of applications such as pharmaceutical industries, food industries, environmental sciences, military industries, especially the Biowar branch. includes

  • Contents & References of Investigation and evaluation of optical fiber bio-sensor for identification of biological materials

    List:

    1 Chapter 1 Introduction. 1

    1.1 Separability as an inverse problem. 7

    1.2 Thesis chapters. 10

    2 The second chapter review of past works. 13

    2.1 Shooting system model. 14

    2.2 Dissociability in the frequency domain. 16

    2.3 Spatial domain methods. 18

    2.3.1 Interpolation-reconstruction: non-repetitive methods. 19

    2.3.2 Statistical methods. 21

    2.3.2.1 Maximum probability. 23

    2.3.2.2 maximum posterior probability. 25

    2.3.2.3 Reset - MAP with you. 27

    2.3.3 Projection approach on convex sets. 28

    2.3.4 ML-POCS hybrid approach. 30

    3 The third chapter of improving the resolution of gray images. 31

    3.1 Composition of low-resolution images based on estimation- M. 32

    3.1.1 The estimation framework of M. 32

    3.1.2 Composition of images based on Half-Quadratic estimation. 40

    3.1.2.1 Calculation of parameter a according to the accuracy of each frame. 42

    3.1.3 Adjusters 45

    3.2 Suggested method to improve resolution. 49

    3.3 Tests 50

    3.3.1 Investigation of different reconstruction methods and the effect of regulators 51

    3.3.2 Performance evaluation of the proposed algorithm against registration error. 52

    3.3.3 Evaluation of the robustness of the proposed method against artifacts 54

    3.3.4 Implementation of the proposed method on real images. 55

    4 The fourth chapter of improving the resolution of color images. 65

    4.1 An overview of meta-resolvability issues in color images and image de-mosaicing. 66

    4.1.1 Meta-resolvability in color images. 66

    4.1.2 De-mosaicing of the image. 67

    4.1.3 Integrating meta-resolvability and de-mosaicing in one process. 73

    4.2 Mathematical model and problem solving. 75

    4.2.1 Mathematical model of the photography system. 75

    4.3 Proposed method for multi-frame de-mosaicing. 78

    4.3.1 The sentence of loyalty. 80

    4.3.2 Penalty sentence for lighting. 80

    4.3.3 Color penalty sentence. 81

    4.3.4 Penalty sentence for color dependencies. 82

    4.4 Total cost function. 83

    4.5 Tests 84

    4.5.1 Checking the performance of the proposed algorithm against registration errors. 86

    4.5.2 Checking the performance of the proposed algorithm against the bugs 87

    5 Chapter 5 summary and conclusion. 95

    5.1 Conclusion. 96

    5.2 Suggestions for future works. 97

    Resources and references. 101

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Investigation and evaluation of optical fiber bio-sensor for identification of biological materials