DU Undergraduate Showcase: Research, Scholarship, and Creative Works: Abstracts

Abstracts from the DU Undergraduate Showcase

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Understanding Mechanisms of Metastasis of Aggressive Breast Cancers via Microfluidic Means

The spread of cancer from its site of origin to other organs is called metastasis, and it is this stage of the disease that is responsible for over 90% of cancer deaths. Tumors are comprised of a heterogeneous population and not every cell in a primary tumor has the intrinsic capability to metastasize. Understanding what gives certain metastatically enabled cells this potential will ultimately provide insight into how to target and prevent metastases. In order to form a metastasis, a cancer cell must: move, invade through often stiff supporting tissue, enter the vasculature via small intercellular spaces, survive the hydrodynamic forces of circulation, squeeze through vessel endothelium once again, and finally proliferate. Imbued with the knowledge of this metastatic journey of a cancer cell, it is understandable how very physical and mechanical in nature the process is. Therefore, to study the steps of metastasis effectively requires the ability to precisely control physical attributes of a cell’s surroundings. The engineering field of microfluidics affords this opportunity and in this work I advanced our present knowledge of the metastatic process by using microfluidic techniques in four fundament studies of critical steps required for metastases. In one study, cancer cells are challenged with a geometrically confining migration space which mimics the constraints of a lymphatic capillary and the early necessary intravasation metastatic step. After migration, motile and non-motile cells are recaptured and analyzed for genetic differences which allow for intravasation. In another study, the effects of secreted factors from normal immune cells in the tumor microenvironment are tested for their stimulation of cancer cell migration – the first required step of metastasis – in the most aggressive form of breast cancer that is considered metastatic at its inception. A third study leveraged the adhesive properties of cancer cells as a novel paradigm for circulating tumor cell capture and analysis independent of dynamic cell surface markers. Lastly, specifically designed microfluidic assays were used to determine a multiparametric cellular phenotype of the most aggressive subpopulation of cancer cells’ biomechanical properties, which may confer the capability to effectively traverse the inefficient steps of metastasis.PHDCellular & Molec Biology PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143962/1/allensg_1.pd

An intelligent pedestrian device: social, psychological and other issues of feasibility

An Intelligent Pedestrian Device (IPD) is a new concept in pedestrian safety. It is defined as a microprocessor based information device which detects the approach of oncoming vehicles and informs the pedestrian whether or not it is safe to cross. IPDs could be portable or fixed to a roadside station. They could help reduce pedestrian accidents, which cost £2681 million in the UK in 1994. This study aims to assess whether the concept is socially acceptable and what the design criteria might be. A study of social acceptance involved group interviews of 5-10 participants with 84 pedestrians in five categories: adults aged 18-60, elderly aged 65+, visually restricted, parents of children aged 5-9 and children aged 10-14. The results suggest that vulnerable pedestrians are more positive about the device than the more able-bodied. Theories that may help explain this are discussed and it is concluded that, with education and marketing, the IPD could gain a degree of social acceptance. Observation of more than 900 pedestrian crossing movements at four different sites showed a range of behaviours, and that people often take risks in order to reduce delay. IPDs will require pedestrians to change some of their behaviours, especially those that are risky. Legal acceptance will demand high levels of costly product research and development, and a portable device will not be technologically feasible until well into the next century. However, the wider social benefits of IPDs may be worth the costs. An outline of design criteria for basic and sophisticated portable IPDs is given, and alternative functions are suggested. It is recommended that further work concentrate on developing software and hardware for fixed modes of IPD. It is concluded that, ultimately, acceptance will probably depend on whether Government decides that the IPD has a place in the road environment of the future

Vehicle trajectory prediction for safe navigation of autonomous vehicles

Trajectory prediction of the other road users in the vicinity of an autonomous vehicle is important for safe navigation in dense traffic. Once an autonomous vehicle anticipates how the other road actors will react in the near future, path planning is a lot more simpler and safer. Moreover, the knowledge of future movement of other road actors allows control of sudden jerks in the planned ego vehicle’s path and thus makes travel smoother. This trajectory prediction stage can be used at any level, from restricted driver assistance to full vehicle autonomy. In this thesis two novel trajectory prediction models have been developed. In the first model, the spatio-temporal features that form the basis of behaviour prediction were captured using a Convolutional Long Short Term Memory (Conv-LSTM) neural network architecture consisting of three modules: 1) Interaction Learning to capture the motion of and interaction with surrounding cars, 2) Temporal Learning to identify the dependency on past movements and 3) Motion Learning to convert the extracted features from these two modules into future positions. In addition, a novel feedback scheme was introduced in which the current predicted positions of each car are leveraged to update future motion, encapsulating the effect of the surrounding cars. In the second model a conventional Long Short Term Memory (LSTM) cell based encoder-decoder architecture was developed which uses not only the historical observations but also the associated map features. Moreover, unlike existing architectures, the proposed method incorporates and updates the surrounding vehicle information in both the encoder and decoder, making use of dynamically predicted new data for accurate prediction in longer time horizons. This seamlessly performs four tasks: first, it encodes a feature given the past observations, second, it estimates future maneuvers given the encoded state, third, it predicts the future motion given the estimated maneuvers and the initially encoded states, and fourth, it estimates future trajectory given the encoded state and the predicted maneuvers and motions. Both the developed models were evaluated extensively on two publicly available datasets which include both multi-lane highway and signalled intersections, to benchmark the prediction accuracy with the state-of-the-art models. Later, the conventional encoder-decoder model was also evaluated with a newly collected “Radiate” dataset which includes two intersections, the Kingussie T-junction and the Edinburgh four-way junction, both without traffic signals. The accuracy of the predicted trajectories on the benchmark datasets are comparable with state-of-the-art methods. Moreover, evaluation on the latter dataset (“Radiate”) made it possible to understand better the effect of inter-vehicle interactions on future motion without any influence from mandatory traffic signals.Engineering and Physical Sciences Research Council (EPSRC) funding

The conceptual design of 3D miniaturised / integrated products as examined through the development of a novel red blood cell / plasma separation device

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe aim of this research is to examine the conceptual design issues concerned with integrating product capabilities that can only be generated at the micro- scale (through feature sizes generally of the order of 100nm to 100μm) directly into 3-dimensional products at the macro-scale. Such macro-scale products could accordingly contain internal devices that are too small to be seen or touched by unaided human designers, which begs the question as to how to enable designers to work with objects which are beyond direct human experience, and how can the necessary collective discussion take place within teams of designers, and between these teams and those responsible for product manufacture? This thesis examines and tests a concept that theoretical 2-dimensional diagrams of function may be transformed into 3-dimensional working structures using procedures allied to those used by graphic designers to create solid objects from 2-dimensional prototype geometries through, for example, extrusion or rotation. Applying such procedures to theoretical diagrams in order to transform them into scalable 3-dimensional devices is not yet in general use at the macro-scale, but with increasing recognition of the unique capabilities of the micro- scale the idea may grow in appeal to alleviate the difficulties of conceiving of functional structures that, when built, will be too small to experience directly. Furthermore this design method, through its basis upon a common currency of functional diagrams, may overcome many of the problems of describing and discussing the design and manufacture of normally intangible objects in 3 dimensions. Finally, it is shown through the example of a novel Red Blood Cell / Plasma Separation Device that the geometric transformation process can lead to the design of functional structures which would not readily be arrived at intuitively, and that may be effectively and efficiently integrated into host products

NASA Tech Briefs, October 1991

Topics: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Development and evaluation of a calibration free exhaustive coulometric detection system for remote sensing.

Most quantitative analytical measurement techniques require calibration to correlate signal with the quantity of analyte. The purpose of this study was to employ exhaustive coulometry, an implementation of coulometric analysis in a stopped-flow, fixed-volume, thin-layer cell, to attain calibration-free measurements that would directly benefit intervention-free analysis systems designed for remote deployment. This technique capitalizes on the short diffusion lengths (\u3c 100 µm) to dramatically reduce the time for analysis (\u3c 30 sec). For this work, a thin-layer fluidic cell was designed in software, fabricated via CNC machining, and evaluated using Ferri/Ferrocyanide {Fe(CN)63-/4-} as a model analyte. The 2 µL fixed volume incorporated an oval, 8mm by 4 mm, thin-film gold electrode sensor with an integrated Ag|AgCl pseudo-reference electrode. The flow cell area matched the shape of the sensor, with a volume set by the thickness of a laser-cut silicone rubber gasket (~80 µm). A semi-permeable membrane isolated the working electrode and counter electrode chambers to prevent analyte diffusion. A miniaturized custom potentiostat was designed and built to measure reaction currents ranging from 10 mA to 0.1 nA. Software was developed to perform step voltammetry as well as cyclic voltammetry analysis for verifying electrode condition and optimal redox potential levels. Experimentally determined oxidation/reduction potentials of -100 mV and 400 mV, respectively, were applied to the working electrode for sample concentrations ranging from 50 µM to 10,000 µM. The current generated during the reactions was recorded and the total charge captured at each concentration was obtained by integrating the amperograms. When compared to the expected charge for a 2 µL sample, the total charge vs. concentration plots displayed a near perfect linearity over the full concentration range, and the expected charge (100 % converted) was reached within 20 seconds. The reaction currents ideally should have decayed to background levels, but exhibited constant offset values slightly larger than the background signal, a phenomenon assumed to be lingering residual flow from sample injection. After adding rigid tubing and external valves, the thin-layer cell was shown to remain within 6% of the theoretical charge after 200 seconds. Continued development of this system will offer the possibility of remote, calibration-free determinations of real-world analytes such mercury and lead

Biocompatible low-cost CMOS electrodes for neuronal interfaces, cell impedance and other biosensors

The adaptation of standard integrated circuit (IC) technology for biosensors in drug discovery pharmacology, neural interface systems, environmental sensors and electrophysiology requires electrodes to be electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous IC technology, complementary metal oxide semiconductor (CMOS), does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanroom facilities has been achieved by others. However, to enable adoption of CMOS as a basis for commercial biosensors, the economies of scale of CMOS fabrication must be maintained by using only low-cost post-processing techniques. The scope of this work was to develop post-processing methods that meet the electrochemical and biocompatibility requirements but within the low-cost constraint. Several approaches were appraised with the two most promising designs taken forward for further investigation. Firstly, a process was developed whereby the corrodible aluminium is anodised to form nanoporous alumina and further processed to optimise its impedance. A second design included a noble metal in the alumina pores to enhance further the electrical characteristics of the electrode. Experiments demonstrated for the first time the ability to anodise CMOS metallisation to form the desired electrodes. Tests showed the electrode addressed the problems of corrosion and presented a surface that was biocompatible with the NG108-15 neuronal cell line. Difficulties in assessing the influence of alumina porosity led to the development of a novel cell adhesion assay that showed for the first time neuronal cells adhere preferentially to large pores rather than small pores or planar aluminium. It was also demonstrated that porosity can be manipulated at room temperature by modifying the anodising electrolyte with polyethylene glycol. CMOS ICs were designed as multiple electrode arrays and optimised for neuronal recordings. This utilised the design incorporating a noble metal deposited into the porous alumina. Deposition of platinum was only partially successful, with better results using gold. This provided an electrode surface suitable for electric cell-substrate impedance sensors (ECIS) and many other sensor applications. Further processing deposited platinum black to improve signal-to-noise ratio for neuronal recordings. The developed processes require no specialised semiconductor fabrication equipment and can process CMOS ICs on laboratory or factory bench tops in less than one hour. During the course of electrode development, new methods for biosensor packaging were assessed: firstly, a biocompatible polyethylene glycol mould process was developed for improved prototype assembly. Secondly, a commercial ‘partial encapsulation’ process (Quik-Pak, U.S.) was assessed for biocompatibility. Cell vitality tests showed both methods were biocompatible and therefore suitable for use in cell-based biosensors. The post-processed CMOS electrode arrays were demonstrated by successfully recording neuronal cell electrical activity (action potentials) and by ECIS with a human epithelial cell line (Caco2). It is evident that these developments may provide a missing link that can enable commercialisation of CMOS biosensors. Further work is being planned to demonstrate the technology in context for specific markets.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Estimation du contexte par vision embarquée et schémas de commande pour l'automobile

Les systèmes dotés d autonomie doivent continument évaluer leur environnement, via des capteurs embarqués, afin de prendre des décisions pertinentes au regard de leur mission, mais aussi de l endosystème et de l exosystème. Dans le cas de véhicules dits intelligents , l attention quant au contexte environnant se porte principalement d une part sur des objets parfaitement normalisés, comme la signalisation routière verticale ou horizontale, et d autre part sur des objets difficilement modélisables de par leur nombre et leur variété (piétons, cyclistes, autres véhicules, animaux, ballons, obstacles quelconques sur la chaussée, etc ). La décision a contrario offre un cadre formel, adapté à ce problème de détection d objets variables, car modélisant le bruit plutôt qu énumérant les objets à détecter. La contribution principale de cette thèse est d adapter des mesures probabilistes de type NFA (Nombre de Fausses Alarmes) au problème de la détection d objets soit ayant un mouvement propre, soit saillants par rapport au plan de la route. Un point fort des algorithmes développés est qu ils s affranchissent de tout seuil de détection. Une première mesure NFA permet d identifier le sous-domaine de l'image (pixels non nécessairement connexes) dont les valeurs de niveau de gris sont les plus étonnantes, sous hypothèse de bruit gaussien (modèle naïf). Une seconde mesure NFA permet ensuite d identifier le sous-ensemble des fenêtres de significativité maximale, sous hypothèse de loi binômiale (modèle naïf). Nous montrons que ces mesures NFA peuvent également servir de critères d optimisation de paramètres, qu il s agisse du mouvement 6D de la caméra embarquée, ou d un seuil de binarisation sur les niveaux de gris. Enfin, nous montrons que les algorithmes proposés sont génériques au sens où ils s appliquent à différents types d images en entrée, radiométriques ou de disparité.A l opposé de l approche a contrario, les modèles markoviens permettent d injecter des connaissances a priori sur les objets recherchés. Nous les exploitons dans le cas de la classification de marquages routiers.A partir de l estimation du contexte (signalisation, détection d objets inconnus ), la partie commande comporte premièrement une spécification des trajectoires possibles et deuxièmement des lois en boucle fermée assurant le suivi de la trajectoire sélectionnée. Les diverses trajectoires possibles sont regroupées en un faisceau, soit un ensemble de fonctions du temps où divers paramètres permettent de régler les invariants géométriques locaux (pente, courbure). Ces paramètres seront globalement fonction du contexte extérieur au véhicule (présence de vulnérables, d'obstacles fixes, de limitations de vitesse, etc.) et permettent de déterminer l'élément du faisceau choisi. Le suivi de la trajectoire choisie s'effectue alors en utilisant des techniques de type platitude différentielle, qui s'avèrent particulièrement bien adaptées aux problèmes de suivi de trajectoire. Un système différentiellement plat est en effet entièrement paramétré par ses sorties plates et leurs dérivées. Une autre propriété caractéristique de ce type de systèmes est d'être linéarisable de manière exacte (et donc globale) par bouclage dynamique endogène et transformation de coordonnées. Le suivi stabilisant est alors trivialement obtenu sur le système linéarisé.To take relevant decisions, autonomous systems have to continuously estimate their environment via embedded sensors. In the case of 'intelligent' vehicles, the estimation of the context focuses both on objects perfectly known such as road signs (vertical or horizontal), and on objects unknown or difficult to describe due to their number and variety (pedestrians, cyclists, other vehicles, animals, any obstacles on the road, etc.). Now, the a contrario modelling provides a formal framework adapted to the problem of detection of variable objects, by modeling the noise rather than the objects to detect. Our main contribution in this PhD work was to adapt the probabilistic NFA (Number of False Alarms) measurements to the problem of detection of objects simply defined either as having an own motion, or salient to the road plane. A highlight of the proposed algorithms is that they are free from any detection parameter, in particular threshold. A first NFA criterion allows the identification of the sub-domain of the image (not necessarily connected pixels) whose gray level values are the most amazing under Gaussian noise assumption (naive model). A second NFA criterion allows then identifying the subset of maximum significant windows under binomial hypothesis (naive model). We prove that these measurements (NFA) can also be used for the estimation of intrinsec parameters, for instance either the 6D movement of the onboard camera, or a binarisation threshold. Finally, we prove that the proposed algorithms are generic and can be applied to different kinds of input images, for instance either radiometric images or disparity maps. Conversely to the a contrario approach, the Markov models allow to inject a priori knowledge about the objects sought. We use it in the case of the road marking classification. From the context estimation (road signs, detected objects), the control part includes firstly a specification of the possible trajectories and secondly the laws to achieve the selected path. The possible trajectories are grouped into a bundle, and various parameters are used to set the local geometric invariants (slope, curvature). These parameters depend on the vehicle context (presence of vulnerables, fixed obstacles, speed limits, etc ... ), and allows determining the selected the trajectory from the bundle. Differentially flat system is indeed fully parameterized by its flat outputs and their derivatives. Another feature of this kind of systems is to be accurately linearized by endogenous dynamics feed-back and coordinate transformation. Tracking stabilizer is then trivially obtained from the linearized system.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF