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Determining Level of Cognitive Impairment via Computing Fractals using a ComputerSiriyala, Kodhanda Karthik 26 June 2018 (has links)
Mild Cognitive Impairment is a condition that affects an individual's thinking and decision making capabilities. Specifically, it is one where an individual's capabilities of memorizing, thinking and decision making are less efficient when compared to others. In order to diagnose this condition, a conventional method is to provide the subject with a small challenge they should be completed using pen and paper. This thesis focuses on how this method can be converted to a computer based test. A data visualization tool named Processing has been used to develop a system that runs a game-like test, which is completed by individuals using a mouse. The system then saves the individual's mouse movements in the form of a CSV file. This files are used for further analyzed using JMP Pro on how this data can be used for determining cognitive abilities via computing a metric called Fractal, and what conclusions can be drawn. In order to achieve comparable results, readings from two diverse age groups have been collected. The results using a total of 12 subjects are convincing in that the tool can be used to as a marker for detecting cognitive impairment.
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OPTIMIZING COBALT CARBIDE BASED NANOMATERIALS BY USING NUCLEATING AGENTS AND STATISTICAL ROUTESAlmugaiteeb, Turki I. 01 January 2016 (has links)
The continuous high demand on permanent magnets in industries opened new research plateau to develop alternative magnetic material. The current used permanent magnet materials in the market still suffer from high cost and insufficient magnetic or thermal properties. The central focus of this dissertation work is the optimization of cobalt carbide based nanomaterial by means of modifying polyol synthesis assisted by nucleation agent and systematic statistics using JMP software tool. In most existing literatures, producing cobalt carbide (Co2C or Co3C) lack reproducibility and consistency resulting in nonsolid magnetic properties results. The practical requirements for cobalt carbide to be used as permanent magnet are high coercivity (Hc), high magnetization (Ms), resulting in a high-energy product (HcxMs). Previous literatures have shown coercivities of 1.5 to 2.5 kOe for cobalt carbides under aggressive temperatures conditions (300oC) or after aligning the particles under magnetic field.
A statistical guided method performed a sequence of experiments toward producing high coercivities using surface response design. Primarily, the statistical study to optimize cobalt carbide was made by analyzing experimental condition to fulfill high magnetic properties with tuned conditions as much as possible. Therefore, having the advantage for superior control on process variable when shifting cobalt carbide for scale up production in flow chemistry set up using microreaction system (MMRS). The optimization is based upon selecting the most important conditions in polyol reaction to produce cobalt carbide (Co2C or Co3C) and feed JMP software model e.g. reaction temperature, reaction time, and or precursor concentration…etc. These factors called (effects) used to design experiments and generate tables to run minimum experiments. Points of each effect (levels) are selected based on previous knowledge and experience with the synthesis. The output called (response) can be any of the magnetic properties of our interest e.g. magnetization (Ms), coercivity (Hc), or energy magnetic product (HcxMs). In the first model fit of cobalt carbide magnetic was studied in a polyol reaction to increase its magnetic energy product and optimize the experimental conditions. The results disclosed increase in magnetic energy product (6.2 MGOe) when validating the prediction model conditions suggested by JMP: shorter reaction time, and lower precursor concentration conditions at maximum reaction temperature.
Finally, to my knowledge studying the effect of the nucleating agent to alter cobalt carbide growth have not been studied so far. Therefore, statistical study design using central composite design (CCD) to investigate the nucleating agent effect of silver nitrite on cobalt carbide coercivity was made. The importance of nucleating agent on coercivity is vigorous to attain and control the growth direction of cobalt carbide nanoparticles. This is due to the shape anisotropy contribution to enhance coercivity unlike weak shape anisotropy attributed to agglomeration of nanoparticles demonstrated in previous studies. Enhancement of coercivity reached 3 kOe with aspect ratio control as a function of silver nitrite concentration under lower reaction temperature.
The continuous high demand on permanent magnets in industries opened new research plateau to develop alternative magnetic material. The current used permanent magnet materials in the market still suffer from high cost and insufficient magnetic or thermal properties. The central focus of this dissertation work is the optimization of cobalt carbide based nanomaterial by means of modifying polyol synthesis assisted by nucleation agent and systematic statistics using JMP software tool. In most existing literatures, producing cobalt carbide (Co2C or Co3C) lack reproducibility and consistency resulting in nonsolid magnetic properties results. The practical requirements for cobalt carbide to be used as permanent magnet are high coercivity (Hc), high magnetization (Ms), resulting in a high-energy product (HcxMs). Previous literatures have shown coercivities of 1.5 to 2.5 kOe for cobalt carbides under aggressive temperatures conditions (300oC) or after aligning the particles under magnetic field.
A statistical guided method performed a sequence of experiments toward producing high coercivities using surface response design. Primarily, the statistical study to optimize cobalt carbide was made by analyzing experimental condition to fulfill high magnetic properties with tuned conditions as much as possible. Therefore, having the advantage for superior control on process variable when shifting cobalt carbide for scale up production in flow chemistry set up using microreaction system (MMRS). The optimization is based upon selecting the most important conditions in polyol reaction to produce cobalt carbide (Co2C or Co3C) and feed JMP software model e.g. reaction temperature, reaction time, and or precursor concentration…etc. These factors called (effects) used to design experiments and generate tables to run minimum experiments. Points of each effect (levels) are selected based on previous knowledge and experience with the synthesis. The output called (response) can be any of the magnetic properties of our interest e.g. magnetization (Ms), coercivity (Hc), or energy magnetic product (HcxMs). In the first model fit of cobalt carbide magnetic was studied in a polyol reaction to increase its magnetic energy product and optimize the experimental conditions. The results disclosed increase in magnetic energy product (6.2 MGOe) when validating the prediction model conditions suggested by JMP: shorter reaction time, and lower precursor concentration conditions at maximum reaction temperature.
Finally, to my knowledge studying the effect of the nucleating agent to alter cobalt carbide growth have not been studied so far. Therefore, statistical study design using central composite design (CCD) to investigate the nucleating agent effect of silver nitrite on cobalt carbide coercivity was made. The importance of nucleating agent on coercivity is vigorous to attain and control the growth direction of cobalt carbide nanoparticles. This is due to the shape anisotropy contribution to enhance coercivity unlike weak shape anisotropy attributed to agglomeration of nanoparticles demonstrated in previous studies. Enhancement of coercivity reached 3 kOe with aspect ratio control as a function of silver nitrite concentration under lower reaction temperature.
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