In the last decade Support Vector Machines (SVMs) have emerged as an important learning technique for solving classification and regression problems in various fields, most notably in computational biology, finance and text categorization. This is due in part to built-in mechanisms to ensure good generalization which leads to accurate prediction, the use of kernel functions to model non-linear distributions, the ability to train relatively quickly on large data sets using novel mathematical optimization techniques and most significantly the possibility of theoretical analysis using computational learning theory. In this thesis, we discuss the theoretical basis and computational approaches to Support Vector Machines.

This Ph.D. thesis presents the design and implementation of a biologically inspired four-phase walking strategy using behaviours for a four legged walking robot. In particular, the walking strategy addresses the balance issue, including both static and dynamic balance that were triggered non-deterministically based on the robot’s realtime interaction with the environment. Four parallel Subsumption Architectures (SA) and a simple Central Pattern Producer (CPP) are employed in the physical implementation of the walking strategy. An implementation framework for such a parallel Subsumption Architecture is also proposed to facilitate the reusability of the system. A Reinforcement Learning (RL) method was integrated into the CPP to allow the robot to learn the optimal walking cycle interval (OWCI), appropriate for the robot walking on various terrain conditions. Experimental results demonstrate that the robot employs the proposed walking strategy and can successfully carry out its walking behaviours under various experimental terrain conditions, such as flat ground, incline, decline and uneven ground. Interactions of all the behaviours of the robot enable it to exhibit a combination of both preset and emergent walking behaviours.

Thesis (M. Phil.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 156-165). Also available in print.

Thesis (Ph.D.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Aug. 19, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Computing Science, University of Alberta." Includes bibliographical references.

abstract: In order for assistive mobile robots to operate in the same environment as humans, they must be able to navigate the same obstacles as humans do. Many elements are required to do this: a powerful controller which can understand the obstacle, and power-dense actuators which will be able to achieve the necessary limb accelerations and output energies. Rapid growth in information technology has made complex controllers, and the devices which run them considerably light and cheap. The energy density of batteries, motors, and engines has not grown nearly as fast. This is problematic because biological systems are more agile, and more efficient than robotic systems. This dissertation introduces design methods which may be used optimize a multiactuator robotic limb's natural dynamics in an effort to reduce energy waste. These energy savings decrease the robot's cost of transport, and the weight of the required fuel storage system. To achieve this, an optimal design method, which allows the specialization of robot geometry, is introduced. In addition to optimal geometry design, a gearing optimization is presented which selects a gear ratio which minimizes the electrical power at the motor while considering the constraints of the motor. Furthermore, an efficient algorithm for the optimization of parallel stiffness elements in the robot is introduced. In addition to the optimal design tools introduced, the KiTy SP robotic limb structure is also presented. Which is a novel hybrid parallel-serial actuation method. This novel leg structure has many desirable attributes such as: three dimensional end-effector positioning, low mobile mass, compact form-factor, and a large workspace. We also show that the KiTy SP structure outperforms the classical, biologically-inspired serial limb structure. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2017

A interação de várias substancias bioativas com monocamadas de fosfolipídios foi investigada usando isotermas de pressão e potencial de superfície, incluindo as drogas farmacológicas dipiridamol (DIP), clopromazina (CPZ) e trifluoperazina (TFP), além da melatonina (MEL) e o colesterol (COL). Os fosfolipídios empregados foram o zwiteriônico dipalmitoil fosfatidil colina (DPPC) e o aniônico dipalmitoil fosfatidil glicerol (DPPG) espalhados na superfície de água ultrapura, sendo que as monocamadas servem como modelo simples de membranas. A cooperatividade na interação entre fosfolipídios e moléculas com atividade biológica foi essencial para entender os acentuados efeitos na expansão (ou condensação) das monocamadas e as mudanças no momento de dipolo (até 10% de aumento na expansão em relação à monocamada do fosfolipídio puro para as misturas DIP/DPPC) que ocorreram a concentrações molares muito baixas entre 0,2-0,4% do DIP. Tais efeitos foram observados para todas as cinco substâncias investigadas, em todos os regimes de pressão. Nas altas concentrações, o comportamento da interação depende do tipo de mólecula e também de se a monocamada é de DPPC ou DPPG. Para o DPPC, as drogas farmacológicas foram expelidas da interface em vários graus a altas pressões, e existia um máximo de concentração da droga acima do qual ocorria a saturação, provavelmente porque as moléculas em excesso foram para a subfase. Essas concentrações críticas foram de 2% em mol para o DIP e a CPZ e de 5% em mol para a TFP. Para o DIP, em particular, os resultados das isotermas foram correlacionados com experimentos de espectroscopia de FTIR e microscopia de fluorescência \"in situ\", realizados por colaboradores, os quais permitiram a determinação de uma localização precisa da droga estudada. Não existe inserção do DIP na região da cauda hidrofóbica da monocamada do DPPC, com a interação ocorrendo com o grupo fosfato no zwiteríon, cujas pequenas mudanças na orientação induzidas pelo DIP levam a grandes mudanças no momento de dipolo. Como o DPPG está carregado negativamente sobre a superfície da água pura, não existe saturação nos efeitos de expansão com o aumento da concentração das drogas. O aumento do momento de dipolo efetivo na monocamada mista é atribuído a alterações na densidade de carga superficial pela adsorção da droga catiônica, que reduz a contribuição negativa do potencial da dupla camada, quando comparado com o da monocamada de DPPG puro. Os resultados do COL e a MEL devem ser considerados separadamente devido a sua natureza distinta, embora um comportamento cooperativo também tenha observado com grandes efeitos nas baixas concentrações. Tanto o COL como o MEL induzem mudanças na expansão das monocamadas de DPPC até a máxima concentração empregada, 20% molar. Para o COL foi observado um efeito de condensação a baixas concentrações, o qual foi seguido por uma expansão a altas concentrações, confirmando assim resultados prévios da literatura. Todas as monocamadas mistas COL/DPPG apresentavam-se expandidas, também confirmando alguns resultados da literatura para lipídios (diferentes do DPPC) quando misturados com o COL. A interação da MEL com o DPPC foi essencialmente similar à do COL, apesar do fato de a MEL pura não formar monocamadas estáveis. Sua interação com o DPPG foi peculiar já que o efeito que esta induz satura a 5% em mol. Isto também difere do comportamento das drogas farmacológicas. A MEL é neutra em todos os pHs, portanto, sua intenção com as membranas modelo de DPPG e DPPC só pode ocorrer via dipolo. O mesmo se aplica ao colesterol, o que justifica as diferenças no comportameto destas duas moléculas quando comparadas com as drogas (DIP, CPZ, TFP), que são carregadas sobre a água pura, nas misturas com os dois fosfolipídios (DPPG e DPPC). / The interaction of various bioactive substances with phospholipids monolayers has been investigated using surface pressure and surface potential isotherms, which include the pharmaceutical drugs dipyridamole (DIP), chlorpromazine (CPZ) and trifluoperazine (TFP), in addition to melatonin (MEL) and cholesterol (COL). The phospholipids employed were the zwitterionic dipalmitoyl phosphatidyl choline (DPPC) and the anionic dipalmitoyl phosphatidyl glycerol (DPPG) spread onto ultra pure water surfaces, where the monolayers served as simple model membrane systems. Cooperativity in the interaction between phospholipid and bioactive molecules was essential to account for the large effects of expansion (up to 10% increase in area in relation to the pure phospholipid monolayer for the DIP/DPPC mixture) of the monolayers and changes in dipole moment, which occurred at very low concentrations, e.g. 0.2 - 0.4 mol% of the substance. Such large effects were observed for all 5 substances investigated, at all surface pressure regimes. At higher concentrations, the interaction behavior depended on the type of molecule and also on whether the host monolayer was DPPC or DPPG. For DPPC, the pharmaceutical drugs were expelled at varying degrees from the interface at high surface pressures, and there was a maximum drug concentration above which the effects saturated, probably because the molecules in excess were lost to the subphase. These critical concentrations were 2mol% for DIP and CPZ and 5mol% for TFP. For DIP, in particular, the results from isotherm were correlated with in situ FTIR spectroscopy and fluorescent microscopy experiments, carried out by collaborators, which allowed the precise location of the drug to be determined. There is no insertion of DIP into the hydrophobic tail region of the DPPC monolayer, with interaction taking place with the phosphate group in the zwitterion, whose small changes in orientation induced by DIP lead to the large changes in dipole moment. Because DPPG is negatively charged on a pure water surface monolayer, there is no saturation of the expansion effects with the increase in drug concentration. The increase in the effective dipole moment of the mixed monolayers are attributed to alterations in the surface charge density by adsorption of the cationic drugs, which then reduces the negative contribution of the double-layer potential as compared to the pure DPPG monolayer. The results for COL and MEL must be considered separately owing to their distinct nature, even though a cooperative behavior was also observed with large effects at low concentrations. Both COL and MEL induce changes in the DPPC monolayers up to the highest concentration employed, viz. 20mol%. For COL, a condensation effect was observed at low concentrations, which was followed by monolayer expansion at high concentrations, thus confirming previous results in the literature. All COL/DPPG monolayers were more expanded than pure DPPG, also confirming previous results from the literature. While the interaction of MEL with DPPC was essentially similar to that of COL, in spite of the fact that MEL does not form stable monolayers on its own, its interaction with DPPG was somewhat peculiar in that the effects it induced saturate at 5mol%. This also differs from the behavior of the pharmaceutical drugs. MEL is neutral over a wide range of pHs, and therefore its interaction with DPPC and DPPG monolayers must occur via dipole interaction. The same applies to COL, and this explains why the behavior of these two substances is different from the drugs (DIP, CPZ and TFP) that are charged on the water surface, in the interaction with DPPC and DPPG.

This thesis describes development and optimalization of method for identification of polyphenols compounds present in hops (Humulus lupulus L.) that have potential antimicrobial activity. Within extraction of compounds from hop, minced hop cones were applied in a growth medium, where compounds diffused into the medium and created an inhibition zone after inoculated with Streptococcus aureus. The method combining extraction with acetone a salting out using QuEChERS principles was optimized for extraction of compounds from solid growth medium. The analysis was carried out using LC/HR-MS with a quadrupole-orbitrap hybrid mass analyzer. The MS method was developed as a screening method with a subsequent fragmentation of compound of interest on the base of inclusion mass list. The compounds extracted from inhibition zone were identified either by searching against a database or their structures have been elucidated on the basis of their fragmentation spectra.

No description available.

Continuum robots mimic the principle of a special biological structure known as the muscular hydrostat. These robots have an ability to bend at any location on along its backbone and have potential applications in disaster relief, medical surgeries and nuclear waste disposal. This thesis presents the modeling and verification of a multi-section continuum robot by applying the Cosserat theory of rods. Next, 2D verification is performed on a continuum robot based on a backbone composed of a nickel titanium alloy. In addition, the thesis develops the theoretical foundations for a cable-driven continuum robot by studying the effects of cable guide mass which cause additional deformation of the robot The results of this thesis show that the multi-section model is accurate within 3.4% in predicting the Cartesian tip coordinates, and the model with the cable guides accurate within 1.26% error in predicted versus the observed Cartesian tip coordinates of the backbone.

Current and emerging large-scale networks, for example the current Internet and the future Internet of Things, target supporting billions of networked entities to provide a wide variety of services and resources. Such complexity results in network-data from different sources with special characteristics, such as widely diverse users and services, multiple media (e.g., text, audio, video, etc.), high-dimensionality (i.e., large sets of attributes) and various dynamic concerns (e.g., time-sensitive data). With huge amounts of network data with such characteristics, there are significant challenges to a) recognize emergent and anomalous behavior in network traffic and b) make intelligent decisions for efficient and effective network operations. Fortunately, numerous analyses of Internet traffic have demonstrated that network traffic data exhibit multi-dimensional patterns that can be learned in order to enable discovery of data semantics. We claim that extracting and managing network semantics from traffic patterns and building conceptual models to be accessed on-demand would help in mitigating the aforementioned challenges. The current Internet, contemporary networking architectures and current tools for managing large network-data largely lack capabilities to 1) represent, manage and utilize the wealth of multi-dimensional traffic data patterns; 2) extract network semantics to support Internet intelligence through efficiently building conceptual models of Internet entities at different levels of granularity; and 3) predict future events (e.g., attacks) and behaviors (e.g., QoS of unfamiliar services) based on learned semantics. We depict the limited utilization of traffic semantics in networking operations as the “Internet Semantics Gap (ISG)”. We hypothesize that endowing the Internet and next generation networks with a “memory” system that provides data and semantics management would help resolve the ISG and enable “Internet Intelligence”. We seek to enable networked entities, at runtime and on-demand, to systematically: 1) learn and retrieve network semantics at different levels of granularity related to various Internet elements (e.g., services, protocols, resources, etc.); and 2) utilize extracted semantics to improve network operations and services in various aspects ranging from performance, to quality of service, to security and resilience. In this dissertation, we propose a distributed network memory management system, termed NetMem, for Internet intelligence. NetMem design is inspired by the functionalities of human memory to efficiently store Internet data and extract and utilize traffic data semantics in matching and prediction processes, and building dynamic network-concept ontology (DNCO) at different levels of granularity. The DNCO provides dynamic behavior models for various Internet elements. Analogous to human memory functionalities, NetMem has a memory system structure comprising short-term memory (StM) and long-term memory (LtM). StM maintains highly dynamic network data or data semantics with lower levels of abstraction for short time, while LtM keeps for long time slower varying semantics with higher levels of abstraction. Maintained data in NetMem can be accessed and learned at runtime and on-demand. From a system’s perspective, NetMem can be viewed as an overlay network of distributed “memory” agents, called NMemAgents, located at multiple levels targeting different levels of data abstraction and scalable operation. Our main contributions are as follows: • Biologically-inspired customizable application-agnostic distributed network memory management system with efficient processes for extracting and classifying high-level features and reasoning about rich semantics in order to resolve the ISG and target Internet intelligence. • Systematic methodology using monolithic and hybrid intelligence techniques for efficiently managing data semantics and building runtime-accessible dynamic ontology of correlated concept classes related to various Internet elements and at different levels of abstraction and granularity that would facilitate: ▪ Predicting future events and learning about new services; ▪ Recognizing and detecting of normal/abnormal and dynamic/emergent behavior of various Internet elements; ▪ Satisfying QoS requirements with better utilization of resources. We have evaluated the NetMem’s efficiency and effectiveness employing different semantics reasoning algorithms. We have evaluated NetMem operations over real Internet traffic data with and without using data dimensionality reduction techniques. We have demonstrated the scalability and efficiency of NetMem as a distributed multi-agent system using an analytical model. The effectiveness of NetMem has been evaluated through simulation using real offline data sets and also via the implementation of a small practical test-bed. Our results show the success of NetMem in learning and using data semantics for anomaly detection and enhancement of QoS satisfaction of running services. / Ph. D.