Computational Astronomy: Classification of Celestial Spectra Using Machine Learning Techniques

Lightyears beyond the Planet Earth there exist plenty of unknown and unexplored stars and Galaxies that need to be studied in order to support the Big Bang Theory and also make important astronomical discoveries in quest of knowing the unknown. Sophisticated devices and high-power computational resources are now deployed to make a positive effort towards data gathering and analysis. These devices produce massive amount of data from the astronomical surveys and the data is usually in terabytes or petabytes. It is exhaustive to process this data and determine the findings in short period of time. Many details can be missed out and can lead to increased errors. Machine Learning can thus be applied for automated intelligent data analysis and recognition in the field of astronomy to gather important information and recognize or classify star types. Celestial Spectral Classification is one such problem that needs to be addressed using Machine Learning and will help astronomers to know whether the classified star has particular physical or chemical properties. Machine Learning can help astronomers to determine the class of celestial spectra which in turn can help in determining various properties of the star and will make the classification process intelligent, automated and less cumbersome

Low Finesse Extrinsic Fabry-Perot Interferometer (Efpi) Demodulation for High Temperature Gap Measurements

In continuous casting steel industries, mold flux is added to provide thermal and chemical insulation for molten steel. The mold flux absorbs detrimental inclusions from the steel and promotes uniform heat distribution to prevent sticking. To promote flux infiltration, mold oscillation is used, but this creates oscillation marks that reduce local shell growth and increase temperatures. Wide (2-3 mm) and deep (0.5-0.9 mm) oscillation marks with areas of 1.1-2.5 mm² are observed, affecting the steel quality, which results in a loss of 6% per billet to the industry. To address this challenge, we propose an extrinsic Fabry-Perot interferometer (EFPI) sensor for high-temperature gap measurements. The proposed EFPI sensor has a wide measurement range of 10 µm to 1000 µm with a measurement uncertainty of 5 to 8 nm, and for larger gaps in the range of 1000 µm to 3.5 mm, the measurement uncertainty is 0.1 to 0.3 µm. The EFPI sensors measure the gap during shrinkage due to rapid cooling of the flux material in real-time, providing a reliable and accurate measurement method for high-temperature gap sensing in a harsh environment. A smaller air gap between mold and solidified mold flux is favorable for strand lubrication and the thickness of mold flux film are crucial for production of higher-quality steel. A lower melting temperature of mold flux leads to greater liquid slag thicknesses and smaller maximum air gap thicknesses. A shortage of flux feeding into the gap can lead to air gaps, non-uniform heat flow, thinning of the shell, and longitudinal surface cracks. Thus, measuring the air gap and thickness of the mold flux aids in optimizing the melting temperature, flux feeding and mold oscillation frequency which can improve overall casting process -- Abstract, p. i

Systematic Review of Driver Distraction in the Context of Advanced Driver Assistance Systems (ADAS) & Automated Driving Systems (ADS)

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors. Therefore, this thesis aims to understand the state of knowledge on automated vehicle systems and their possible impact on drivers’ distraction behaviors. I have conducted two systematic literature reviews to examine this question. This thesis reports these reviews and examines the effects of secondary task engagement on driving behaviors such as take-over times, visual attention, trust, and workload, and discusses the implications on driver safety

Higher Education Costs and The Excelsior Scholarship: Who Pays, and Who Receives?

Senior Project submitted to The Division of Social Studies of Bard College

Strain improvement of Gluconacetobacter xylinus NCIM 2526 for bacterial cellulose production

The present investigation demonstrates the effectiveness of ultraviolet (UV) radiation and ethyl methanesulfonate (EMS) in strain improvement for enhanced cellulose production by Gluconacetobacter xylinus NCIM 2526. The mutants were compared with wild type for cellulose production. UV mutants GHUV3, GHUV4, and GHUV5 of G. xylinus showed higher cellulose yield than the wild strain. The mutant GHUV4 gave cellulose yield of 3.92 g/l which was 30% more than the wild strain in standard medium. Chemical mutants GHEM4, GHEM6 and GHEM7 of G. xylinus showed higher cellulose yield than the parent strain (GHUV4). GHEM4 gave cellulose yield of 5.96 g/l which was 50% more than the parent strain (GHUV4) and 98% more than the wild strain (NCIM 2526). The results indicated that UV and EMS were effective mutagenic agents for strain improvement.Key words: Bacterial cellulose, Gluconacetobacter xylinus, ultraviolet mutagenesis, ethyl methanesulfonate treatment

Does E-Marketing Mix Influence Brand Loyalty and Popularity of E-Commerce Websites?

E-commerce portals are increasing exponentially in terms of both business and data. Many organizations rely on their online websites to attract new customers, while still retaining their existing ones. E-commerce websites provide consumers with flexibility in terms of time, price, and space, during their purchases. The traditional marketing mix comprising of product, price, place and promotion (4Ps) identifies important factors in a purchase journey. In the online environment the concept of the marketing mix remains the same, except that the characteristics and functions of each factor are dynamic, suiting the online marketplace. The e-marketing mix, namely e-product, price intelligence (price sensitivity), delivery risk (place) and promotional intelligence, influences consumer buying-decisions in online markets. This research is an attempt to find the effect of the e-marketing mix on the loyalty and popularity of e-commerce sites. Data was collected using a structured questionnaire and was analyzed using a structural equation modeling-partial least squares method. The results showed that brand popularity was significantly influenced by the characteristics of the product and intelligent promotional techniques. Brand popularity had an influence on brand loyalty in an electronic marketing space

Stimulation of cannabinoid receptor agonist 2-arachidonylglycerol by chronic ethanol and its modulation by specific neuromodulators in cerebellar granule neurons

AbstractIn an earlier study, we reported that chronic ethanol (EtOH) stimulates the formation of anandamide in human SK-N-SH cells. In the present study, we investigated the effect of chronic EtOH on the formation of yet another cannabinoid receptor (CB1) agonist, 2-arachidonylglycerol (2-AG), in cerebellar granule neurons (CGNs). The formation of 2-[3H]AG without any stimulation was more pronounced in the older cultures than in younger cultures. Exposure of CGNs to EtOH led to a significant increase in the level of 2-[3H]AG (P<0.05). Incubation with the anandamidehydrolase inhibitor phenylmethylsulfonyl fluoride and EtOH did result in an additive increase in 2-[3H]AG, but did not with E-6-(bromomethylene)tetrahydro-3-(1-naphthelenyl)-2H-pyran-2-one. The formation of 2-[3H]AG was enhanced by ionomycin in both the control and EtOH-exposed CGNs, and the ionomycin-stimulated 2-[3H]AG synthesis was inhibited by the intracellular chelating agent 1,2-bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid. Further, glutamate increased the formation of 2-[3H]AG only in control CGNs. MK-801 inhibited the EtOH-induced 2-[3H]AG synthesis, suggesting the participation of intracellular Ca2+ in EtOH-induced 2-[3H]AG synthesis. The dopamine receptor (D2) agonist did not modify the 2-AG synthesis in either the control or EtOH-exposed CGNs. However, the D2 receptor antagonist inhibited the EtOH-induced formation of 2-[3H]AG. The EtOH-induced 2-[3H]AG formation was inhibited by SR141716A and pertussis toxin, suggesting the CB1 receptor- and Gi/o-protein-mediated regulation of 2-AG. The observed increase in 2-AG level in CGNs is possibly a mechanism for neuronal adaptation to the continuous presence of EtOH. These findings indicate that some of the pharmacological actions of EtOH may involve alterations in the endocannabinoid signaling system

Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics

Identification of liquids is essential in chemical analysis, safety, environmental protection, quality control, and research. A novel liquid identification system based on Microwave Photonics (MWP) measured time transient evaporation signals is investigated. An extrinsic Fabry-Perot Interferometer (EFPI) based optical probe using single-mode fiber (SMF) is proposed to monitor evaporation of different liquids. The MWP system is used to measure the optical path changes during liquid evaporation due to its high sensitivity, selectivity, and Signal-to-Noise Ratio (SNR). The measured S21 continuous wave (CW) time Magnitude and Phase signals were processed to extract features such as histogram and Fast Fourier Transform (FFT) peaks. Using features extracted from droplet evaporation time transient events, machine learning classification accurately identified chemicals in each liquid with an accuracy rate of over 99%, employing three algorithms: Decision Trees, Support Vector Machine (SVM), and K-nearest neighbors (KNN). The classification results demonstrate accurate liquid identification based on evaporation measurements by the MWP system

Calculations of Adsorption-Dependent Refractive Indices of Metal-Organic Frameworks for Gas Sensing Applications

Detection of Volatile Organic Compounds (VOCs) is One of the Most Challenging Tasks in Modelling Breath Analyzers Because of their Low Concentrations (Parts-Per-Billion (Ppb) to Parts-Per-Million (Ppm)) in Breath and the High Humidity Levels in Exhaled Breaths. the Refractive Index is One of the Crucial Optical Properties of Metal-Organic Frameworks (MOFs), Which is Changeable Via the Variation of Gas Species and Concentrations that Can Be Utilized as Gas Detectors. Herein, for the First Time, We Used Lorentz–Lorentz, Maxwell–Ga, and Bruggeman Effective Medium Approximation (EMA) Equations to Compute the Percentage Change in the Index of Refraction (∆n%) of ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr) and HKUST-1 Upon Exposure to Ethanol at Various Partial Pressures. We Also Determined the Enhancement Factors of the Mentioned MOFs to Assess the Storage Capability of MOFs and the Biosensors\u27 Selectivity through Guest-Host Interactions, Especially, at Low Guest Concentrations

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer

Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot Interferometer (EFPI) was installed at each of the three steps in the mold. Mold flux was melted in a graphite crucible at 1400 °C and poured into the instrumented step mold for analysis. Interferograms from the three EFPIs were acquired and processed in real-time to measure the air gap and thickness of each flux film during solidification. Measurements were performed on two different mold flux compositions. Results demonstrate that the proposed system successfully records structural features of the flux film in real-time during cooling. It has a large real-time impact on the process control of steel making and optimizing the quality of steel castings. In addition, the measurement method has potential to monitor crystal nucleation and growth in a variety of crystallizing glass systems