Cognitive Load Detection For Advanced Driver Assistance Systems

In this thesis, we investigate cognitive load detection and classification based on minimally invasive methods. Cognitive load detection is crucial for many emerging applications such as advanced driver assistance systems (ADAS) and industrial automation. Numerous studies in the past have reported several psychological measures, such as eye-tracking, electrocardiogram (ECG), electroencephalogram (EEG), as indicators of cognitive load. However, existing physiological features are invasive in nature. Consequently, the objective of this study is to determine the feasibility of non-invasive features such as pupil dilation measurements low-cost eye-tracker with minimal constraints on the subject for cognitive load detection. In this study, data from 33 participants were collected while they underwent tasks that are designed to permeate three different cognitive difficulty levels with and without cognitive maskers and the following measurements were recorded: eye-tracking measures (pupil dilation, eye-gaze, and eye-blinks), and the response time from the detection response task (DRT). We also demonstrate the classification of cognitive load experienced by humans under different task conditions with the help of pupil dilation and reaction time. Developing a model that can accurately classify cognitive load can be used in various sectors such as semi-autonomous vehicles and aviation. we have used a data fusion approach by combining pupil dilation and DRT reaction time to determine if the classification accuracy increases. Further, we have compared the classifier with the highest classification accuracy using data fusion against the accuracy of the same classifier with only one feature (pupil dilation; reaction time) at a time

Mechanistic Understanding of Catalytic Processes for Sustainable Chemical Transformations

The current field of catalysis is notably advanced in terms of both conceptual and technical innovation. There is a constant need to design new catalysts and develop catalytic processes to improve the scope, efficiency, and selectivity of various chemical transformations. It is also imperative to design catalytic systems which are effective, truly-recyclable and energy efficient for a sustainable future. This can be done through comprehensive knowledge and understanding of catalyst behavior, reaction kinetics and process designing. For most industrial processes, the preferred catalysts are heterogeneous because these solid catalysts can be easily separated from the final product. However, they often lack selectivity and produce waste due to unwanted side reactions. Traditional homogeneous molecular catalysts are highly selective but lack practical industrial utility due to challenges in catalyst separation, final product separation and catalyst degradation in aqueous medium and thus face manufacturing scale-up complexities. To address these challenges and build an active, robust and highly selective catalytic system, designing a hybrid catalyst by immobilizing these molecular catalysts onto a solid support is a viable solution for sustainable catalysis. This could transform the practical utility of molecular catalysts, increase the reaction selectivity with simplified catalyst separation and product recovery, and prevent catalyst decomposition by impeding any bimolecular catalyst interactions. Thus, Chapter 2 details this study based on the well-studied Suzuki carbon– carbon cross-coupling reaction, to demonstrate the ability to achieve catalytic performance using a non-noble nickel-based molecular catalyst in high aqueous content solvents. Furthermore, this study demonstrates a new paradigm in the design of hybrid catalysts in which Atomic Layer Deposition (ALD) is used to improve the attachment and stability of molecular catalysts on solid metal oxide supports. This research has helped achieve a combination of ligand first surface attachment with molecular design and ALD application for new approaches in catalyst discovery. Encouraged by the results from this study, further study on synthesizing nickel bipyridine based hybrid catalysts anchored onto the silica oxide support via carboxylic acid and silatrane linking group was undertaken to analyze if covalent binding of the silatrane linker promotes stronger immobilization of the molecular catalyst onto the oxide support. Comparative analysis on synthesis and characterization of molecular and hybrid versions of carboxylic acid and silatrane linker is discussed in Chapter 3. Another foremost area which has gained increased momentum is developing hydrocarbon-free, green energy technologies and exploring promising solutions for utilizing and producing sustainable energy to meet our current and future energy needs. In this regard, the aims for Chapter 4, are to study energyefficient photocatalytic hydrogen production and investigate the catalytic pathway as part of the solution to the green energy transition. Natural photosynthesis uses an elaborate array of chemical structures to absorb multiple photons of light and convert that energy into chemical bonds in a “Z-scheme” process. Extensive research has been performed in the field of artificial photosynthesis to mimic this natural Z-scheme. To date, however, an artificial Z-scheme composed only of molecular components has yet to be realized.Here, we have developed a novel Z-scheme based molecular photocatalytic system by utilizing the light absorbing properties of aryl-alcohol photocatalysts for hydrogen production at significantly lower reaction overpotentials (≤40meV). Chemical, electrochemical, and spectroscopic data studies supports a Z-scheme based pathway and provides mechanistic insights into hydrogen production via dual photoexcitation. This research can open new avenues for further study of molecular photocatalytic hydrogen production

Response time and eye tracking datasets for activities demanding varying cognitive load

The dataset contains the following three measures that are widely used to determine cognitive load in humans: Detection Response Task - response time, pupil diameter, and eye gaze. These measures were recorded from 28 participants while they underwent tasks that are designed to permeate three different cognitive difficulty levels. The dataset will be useful to those researchers who seek to employ low cost, non-invasive sensors to detect cognitive load in humans and to develop algorithms for human-system automation. One such application is found in Advanced Driver Assistance Systems where eye-trackers are employed to monitor the alertness of the drivers. The dataset would also be helpful to researchers who are interested in employing machine learning algorithms to develop predictive models of humans for applications in human-machine system automation. The data is collected by the authors at the Department of Electrical & Computer Engineering in collaboration with the Faculty of Human Kinetics at the University of Windsor under the guidance of their Research Ethics Board

Fatigue and Structural Analysis of Azimuth Thruster Assembly

Composite is stated as constituent of two or more materials which retain their own physical and chemical property during the time of application, but produce a component which inherent the properties of its constituent materials and makes it better for the real time USAge. There are varieties of processing techniques for fabricating composite parts or structures such as: (1) Resin Transfer Moulding, (2) Pultrusion, (3) Filament Winding, (4) Autoclave Moulding. Among all these technique of exercising composite materials, the filament winding technique is the most appropriate because it avails the user with the ease of USAge, as well as gives wide range of degree of freedom for fabricating or manufacturing objects. In the paper we basically reveal the maximum approach made to study basic theory related to the filament winding technique or method, which provides initial platform for the new learner

Tracking Multiple Objects without Indexes

Computational models of multiple object tracking (MOT) presuppose the existence of non-conceptual indexes in visual perception, and as a result predict that ID (identification) performance on MOT tasks should be no worse than tracking performance for the same stimuli. However, empirical evidence suggests that ID performance is worse than tracking performance in MOT. We propose a computational model of MOT that is able to account for several empirical results related to tracking performance without the use of indexes and thus avoids yoking tracking performance to ID performance. We also test our model empirically, contrasting it with an existing index-based model, and show that an assumption that avoids indexes and instead incorporates an explicit (rather than an implicit) mechanism for identity maintenance accounts well for the variation in ID performance with increasing number of targets in MOT with visually identical objects

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Not AvailableEffect of plant spacing, irrigation and fertilizerlevels on growth and yield of brinjal (solanum melongena L.) under drip irrigation system in lateritic soils of Konkan region of MaharashtraNot Availabl

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Organism descriptor(s) : Brassica oleracea var. botrytis Descriptor(s) : cauliflowers, crop yield, irrigation, mulching, soil depth, soil temperature, soil water, trickle irrigation Identifier(s) : heading broccoli, soil moisture, watering Geographical Location(s) : India, Maharashtra Broader term(s) : Brassica oleracea, Brassica, Brassicaceae, Brassicales, eudicots, angiosperms, Spermatophyta, plants, eukaryotes, India, Commonwealth of Nations, Developing Countries, South Asia, AsiaField experiment was conducted at Instructional Farm of Department of Irrigation and Drainage Engineering, College of Agricultural Engineering and Technology, Dr.BSKKV, Dapoii (India), during rabi season in 2014-2015. The main objective of the study was to investigate the effect of mulching and irrigation levels on soil temperature, soil moisture, and yield of drip irrigated cauliflower. The field experiment was laid out in Split Plot Design (SPD) with three irrigation levels in the main plots and four mulching levels in the sub plots. Treatments were replicated four times. Soil temperature was measured at 5 cm and 15 cm soil depth. The morning soil temperature was found maximum (20.38°C) at 15 cm depth under black plastic mulch. The afternoon soil temperature was found maximum (25°C) at 5 cm depth under black plastic mulch. Silver mulch had minimum temperature variation (0.75°C) and maintained the soil temperature within the optimum temperature range for cauliflower (15-22°C). The soil moisture content was maintained close to field capacity (26.01 per cent) throughout the growing period under a combination of 0.8 ETc and silver plastic mulch. The same treatment combination had maximum yield (29.69 t ha-1), water use efficiency (12.92 q ha-1 cm-1), net income (Rs. 5,57,159.35 ha-1) and B:C ratio (2.67). It was concluded that, in order to obtain higher marketable yield, water use efficiency and net return of cauliflower during rabi season, use of 80 percent of crop water requirement through drip irrigation with silver mulch could be the best option under agroclimatic conditions of Dapoli in Konkan region of Maharashtra, India.Not Availabl