Reconciling Function- and Affordance-Based Design

Traditional engineering design methods are based on Simon's (1969) use of the concept function, and as such collectively suffer from both theoretical and practical shortcomings. Researchers in the field of affordance-based design have borrowed from ecological psychology in an attempt to address the blind spots of function-based design, developing alternative ontologies and design processes. This dissertation presents function and affordance theory as both compatible and complimentary. We first present a hybrid approach to design for technology change, followed by a reconciliation and integration of function and affordance ontologies for use in design. We explore the integration of a standard function-based design method with an affordance-based design method, and demonstrate how affordance theory can guide the early application of function-based design. Finally, we discuss the practical and philosophical ramifications of embracing affordance theory's roots in ecology and ecological psychology, and explore the insights and opportunities made possible by an ecological approach to engineering design. The primary contribution of this research is the development of an integrated ontology for describing and designing technological systems using both function- and affordance-based methods.

ENVISIONING QUEER THROUGH DIGITAL MEDIA: DEVELOPING A COMMUNITY-BASED WORKSHOP IN MEDIA ANALYSIS FOR LGBTQIA+ YOUTH

This project consists of a proposed curriculum for a semester-long, community-based workshop for LGBTQIA+ (lesbian, gay, bisexual, trans*, queer or questioning, intersex, asexual or ally, "+" indicating other identifications that deviate from heterosexual) youth ages 16-18. The workshop focuses on an exploration of LGBTQIA+ identity and community through discussion and collaborative rhetorical analysis of visual and social media. Informed by queer theory and history, studies on youth work, and visual media studies and incorporating rhetorical criticism as well as liberatory pedagogy and community literacy practices, the participation-based design of the workshop seeks to involve participants in selection of media texts, active analytical viewership, and multimodal response. The workshop is designed to engage participants in reflection on questions of individual and collective responsibility and agency as members and allies of various communities. The goal of the workshop is to strengthen participants' abilities to analyze the complex ways in which television, film, and social media influence their own and others’ perceptions of issues surrounding queer identities. As part of the reflective process, participants are challenged to consider how they can in turn actively and collaboratively respond to and potentially help to shape these perceptions. My project report details the theoretical framework, pedagogical rationale, methods of text selection and critical analysis, and guidelines for conduct that inform and structure the workshop.

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

Orbits design for Leo space based solar power satellite system

Space Based Solar Power satellites use solar arrays to generate clean, green, and renewable electricity in space and transmit it to earth via microwave, radiowave or laser beams to corresponding receivers (ground stations). These traditionally are large structures orbiting around earth at the geo-synchronous altitude. This thesis introduces a new architecture for a Space Based Solar Power satellite constellation. The proposed concept reduces the high cost involved in the construction of the space satellite and in the multiple launches to the geo-synchronous altitude. The proposed concept is a constellation of Low Earth Orbit satellites that are smaller in size than the conventional system. For this application a Repeated Sun-Synchronous Track Circular Orbit is considered (RSSTO). In these orbits, the spacecraft re-visits the same locations on earth periodically every given desired number of days with the line of nodes of the spacecraft’s orbit fixed relative to the Sun. A wide range of solutions are studied, and, in this thesis, a two-orbit constellation design is chosen and simulated. The number of satellites is chosen based on the electric power demands in a given set of global cities. The orbits of the satellites are designed such that their ground tracks visit a maximum number of ground stations during the revisit period. In the simulation, the locations of the ground stations are chosen close to big cities, in USA and worldwide, so that the space power constellation beams down power directly to locations of high electric power demands. The j2 perturbations are included in the mathematical model used in orbit design. The Coverage time of each spacecraft over a ground site and the gap time between two consecutive spacecrafts visiting a ground site are simulated in order to evaluate the coverage continuity of the proposed solar power constellation. It has been observed from simulations that there always periods in which s spacecraft does not communicate with any ground station. For this reason, it is suggested that each satellite in the constellation be equipped with power storage components so that it can store power for later transmission. This thesis presents a method for designing the solar power constellation orbits such that the number of ground stations visited during the given revisit period is maximized. This leads to maximizing the power transmission to ground stations.

DESIGN AND DEVELOPMENT OF BODIPY-BASED FLUORESCENT PROBES FOR SENSING AND IMAGING OF CYANIDE, Zn (II) IONS, LYSOSOMAL pH AND CANCER CELLS

BODIPY (4,4-Difluoro-3a,4a-diaza-s-indacene) dyes have gained lots of attention in application of fluorescence sensing and imaging in recent years because they possess many distinctive and desirable properties such as high extinction coefficient, narrow absorption and emission bands, high quantum yield and low photobleaching effect. However, most of BODIPY-based fluorescent probes have very poor solubilities in aqueous solution, emit less than 650 nm fluorescence that can cause cell and tissue photodamages compared with bio-desirable near infrared (650-900 nm) light. These undesirable properties extremely limit the applications of BODIPY-based fluorescent probes in sensing and imaging applications. In order to overcome these drawbacks, we have developed a very effective strategy to prepare a series of neutral highly water- soluble BODIPY dyes by enhancing the water solubilities of BODIPY dyes via incorporation of tri(ethylene glycol)methyl ether (TEG) and branched oligo(ethylene glycol)methyl ether (BEG) residues onto BODIPY dyes at 1,7-, 2,6-, 3,5-, 4- and meso- positions. We also have effectively tuned absorptions and emissions of BOIDPY dyes to red, deep red and near infrared regions via significant extension of π-conjugation of BODIPY dyes by condensation reactions of aromatic aldehydes with 2,6-diformyl BODIPY dyes at 1,3,5,7-positions. Based on the foundation that we built for enhancing water solubility and tuning wavelength, we have designed and developed a series of water-soluble, BODIPY-based fluorescent probes for sensitive and selective sensing and imaging of cyanide, Zn (II) ions, lysosomal pH and cancer cells. We have developed three BODIPY-based fluorescent probes for sensing of cyanide ions by incorporating indolium moieties onto the 6-position of TEG- or BEG-modified BOIDPY dyes. Two of them are highly water-soluble. These fluorescent probes showed selective and fast ratiometric fluorescent responses to cyanide ions with a dramatic fluorescence color change from red to green accompanying a significant increase in fluorescent intensity. The detection limit was measured as 0.5 mM of cyanide ions. We also have prepared three highly water-soluble fluorescent probes for sensing of Zn (II) ions by introducing dipicoylamine (DPA, Zn ion chelator) onto 2- and/or 6-positions of BEG-modified BODIPY dyes. These probes showed selective and sensitive responses to Zn (II) ion in the range from 0.5 mM to 24 mM in aqueous solution at pH 7.0. Particularly, one of the probes displayed ratiometric responses to Zn (II) ions with fluorescence quenching at 661 nm and fluorescence enhancement at 521 nm. This probe has been successfully applied to the detection of intracellular Zn (II) ions inside the living cells. Then, we have further developed three acidotropic, near infrared emissive BODIPY- based fluorescent probes for detection of lysosomal pH by incorporating piperazine moiety at 3,5-positions of TEG- or BEG-modified BODIPY dyes as parts of conjugation. The probes have low auto-fluorescence at physiological neutral condition while their fluorescence intensities will significant increase at 715 nm when pH shift to acidic condition. These three probes have been successfully applied to the in vitro imaging of lysosomes inside two types of living cells. At the end, we have synthesized one water- soluble, near infrared emissive cancer cell targetable BODIPY-based fluorescent polymer bearing cancer homing peptide (cRGD) residues for cancer cell imaging applications. This polymer exhibited excellent water-solubility, near infrared emission (712 nm), good biocompatibility. It also showed low nonspecific interactions to normal endothelial cells and can effectively detect breast tumor cells.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.