Gait development for use in dynamic gait optimization of qudrupedrobot walking

The ability of walking robots to operate in areas that are inaccessible to wheeled robots has lead to significant research in the field of gait development and optimization for these robots. In this particular study, a catalog of gaits for use in a dynamic gait optimization system to optimize the walking speed of the quadruped Arturo robot on flat terrain is developed. This catalog of robot gaits was developed using a genetic algorithm formulation; various combinations of the selection, mutation, and crossover operators were analyzed. The Arturo robot was modified so that physical verification of the developed gaits could be carried out. The performance of several gaits was analyzed to determine both robot performance and suitability of the gait for use in a dynamic gait optimization system. The feasibility of using solely the position feedback from the joints for surface determination was examined. Piezoelectric crystals (Leybold Inficon 6 Mhz oscillators) were also examined for this application

Simulation for dynamic patients scheduling based on many objective optimization and coordinator

The Patient Admission Scheduling Problem (PASP) involves scheduling patient admissions, hospital time locations, to achieve certain quality of service and cost objectives, making it a multi-objective combinatorial optimization problem and NP-hard in nature. In addition, PASP is used in dynamic scenarios where patients are expected to arrive at the hospital sequentially, which requires dynamic optimization handling. Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. The role of multi-objective optimization deals with many soft constraints and providing a set of non-dominated solution coordinators. The role of the counter is to collect newly arrived patients and previously unconfirmed patients with the aim of passing them on to the coordinator. Finally, the role of the coordinator is to select a subset of patients from the window and pass them to the optimization algorithm. On the other hand, the coordinator is also responsible for those selected from the non-dominant solutions to activate it in the hospital and decide on unconfirmed employees to place them in the window for the next round. Simulator evaluation and comparison between several optimization algorithms show the superiority of NSGA-III in terms of set criticality and soft constraint values. Therefore, it treats PASP as a multi-objective dynamic optimization of a useful solution. NSGA-II is guaranteed 0.96 percent dominance over NSGA-II and 100 percent dominance of all other algorithms

MARKETING IN AN AUTOMOBILE DEPENDENT SOCIETY: AN ANALYSIS OF CONSUMER-ORIENTED, INDUSTRY-PRODUCED ADVERTISING MATERIAL

Despite the best intentions of public policy to cure societal ills, for the individual American consumer, the solution to the problem of automobile dependence is simple: buy an automobile. Consumers are alleviating societal pressure of not having a car rather than focusing on the negative impacts of vehicle usage after the purchase. Marketing and advertising play an important role in portraying how the public views transportation. Marketing reinforces automobile dependence and automobility by creating images and messages that say the norm of American life requires an automobile; therefore, marketing creates, controls, and reinforces values within the automobile consumer culture. Addressing automobile marketing as a part of transportation discourse is applied and applicable to a broader population, which can potentially shift the approach to automobile dependence and automobility. It offers a new approach that can expand the way planners approach automobile dependency. The objective of this research was to identify a relationship between automobility as a cultural norm and the ideology of marketed images of private vehicles. The two goals this study achieved were: 1) to characterize the message and ideology of vehicle marketing to inform a portion of the American mobility discourse and 2) to evaluate how the differences in the discourse of vehicle types interact with American values. This study examined automobile manufacturers\u27 marketing materials used to advertise vehicles of two distinct fuel-efficiency categories: passenger vehicles and light-duty trucks. A content analysis of marketing materials showed the dominant ideologies in these advertisements, such as land-use settings and values attributed to specific vehicles, while the theoretical lens of critical discourse analysis investigated the underlying power and ideology of the advertising media (Fairclough, 1989, 1995). The study found marketing has created specific links between vehicle types and land use and a connection and conflict with specific vehicles and nature; passenger vehicles were removed from rural landscapes, and messages presented to consumers conflicted with official designations in the federal Corporate Average Fuel Economy (CAFE) system. Planners often view education as the means of convincing the public to support initiatives that reduce negative impacts of human activity; however, automobile marketing inundates the consumer public with messages of the automobile as a preferred travel mode serving as a critical part of American life. As a result, vehicle marketing contributes to the automobile-dependence discourse in a significant way that requires attention

An Investigation of Supervised Learning in Genetic Programming

Centre for Intelligent Systems and their Applicationsstudentship 9314680This thesis is an investigation into Supervised Learning (SL) in Genetic Programming (GP). With its flexible tree-structured representation, GP is a type of Genetic Algorithm, using the Darwinian idea of natural selection and genetic recombination, evolving populations of solutions over many generations to solve problems. SL is a common approach in Machine Learning where the problem is presented as a set of examples. A good or fit solution is one which can successfully deal with all of the examples.In common with most Machine Learning approaches, GP has been used to solve many trivial problems. When applied to larger and more complex problems, however, several difficulties become apparent. When focusing on the basic features of GP, this thesis highlights the immense size of the GP search space, and describes an approach to measure this space. A stupendously flexible but frustratingly useless representation, Anarchically Automatically Defined Functions, is described. Some difficulties associated with the normal use of the GP operator Crossover (perhaps the most common method of combining GP trees to produce new trees) are demonstrated in the simple MAX problem. Crossover can lead to irreversible sub-optimal GP performance when used in combination with a restriction on tree size. There is a brief study of tournament selection which is a common method of selecting fit individuals from a GP population to act as parents in the construction of the next generation.The main contributions of this thesis however are two approaches for avoiding the fitness evaluation bottleneck resulting from the use of SL in GP. to establish the capability of a GP individual using SL, it must be tested or evaluated against each example in the set of training examples

Covers Uncovered: A History of the Cover Version, from Bing Crosby to the Flaming Lips

This thesis engages with the “cover version” as it has developed since the mid-1940s. This single term has survived across historical eras “so that it now indiscriminately designates any occasion of rerecording” (Coyle 2002, 134). This thesis views changing cover trends as aspects of broader cultural changes. In order to effectively illustrate the wide scope of practices to which this term has referred, the history of cover versions is separated into three broad periods: pre-rock, rock, and post-rock. This thesis explores the shifting attitudes toward, and motivations for, cover recording across these periods. It argues that it is more useful to read individual cover practices according to their distinct cultural contexts rather than to treat “covering” as a single, fixed musical technique or tradition. Specific covering techniques are differentiated and analyzed based on their apparent degrees of musical conservation and transformation. The findings of this research are used to question the appropriateness of continuing to use the same term, “cover version,” to co-categorize an historically divergent set of practices. This thesis argues that the history of the “cover version” has been intimately tied to that of rock culture, with the practice experiencing a decline in popularity when rock began to dominate in the 1960s and then a re-emergence when rock began to be residualized in the 1990s

Optimization of seasonal irrigation scheduling by genetic algorithms

In this work, we first introduce a novel approach to the long term irrigation scheduling using Genetic Algorithms (GAs). We explore the effectiveness of GAs in the context of optimizing nonlinear crop models and describe application requirements and implementation of the technique. GAs were found to converge quickly to near-optimal solutions. Second, we analyze the relationship between GA control parameters (population size, crossover rate, and mutation rate) and performance. We identify a combination of population, mutation, and crossover which searched the fitness landscape efficiently. The results suggest that smaller populations are able to provide better performance at relatively low mutation rates. More stable outcomes were generated using low mutation rates. Without crossover the quality of solutions were generally impaired, and the search process was lengthened. Aside from crossover rate zero, no other crossover rates significantly differed. The behaviors observed for best, online, offline, and average performances were sensitive to the combined influences control parameters. Interaction among control parameters was strongly indicated. Finally, several adaptive penalty techniques are presented for handling constraints in GAs, and their effectiveness is demonstrated. The constant penalty function suffered from sensitivity to settings of penalty coefficients, and was not successful in satisfying constraints. The adaptive penalty functions utilizes violation distance based metrics and search time based scaling using generation or trials number, and fitness values to penalize infeasible solutions, as the distance from the feasible region or number of generations increases so does the penalty. They were quite successful in providing solutions with minimal effort. They adapt the penalty as the search continues, encouraging feasible solutions to emerge over the time. Adaptive approaches presented here are flexible, efficient, and robust to parameter settings

The application of artificial intelligence techniques to a sequencing problem in the biological domain

SIGLEAvailable from British Library Document Supply Centre- DSC:DXN002816 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Comparison of Stochastic Global Optimization Methods: Estimating Neural Network Weights

Agricultural Economic

Application of genetic algorithm to a forced landing manoeuvre on transfer of training analysis

This study raises some issues for training pilots to fly forced landings and examines the impact that these issues may have on the design of simulators for such training. It focuses on flight trajectories that a pilot of a single-engine general aviation aircraft should fly after engine failure and how pilots can be better simulator trained for this forced landing manoeuvre. A sensitivity study on the effects of errors and an investigation on the effect of tolerances in the aerodynamic parameters as prescribed in the Manual of Criteria for the Qualification of Flight Simulators have on the performance of flight simulators used for pilot training was carried out. It uses a simplified analytical model for the Beech Bonanza model E33A aircraft and a vertical atmospheric turbulence based on the MIL-F-8785C specifications. It was found that the effect of the tolerances is highly s ensitive on the nature of the manoeuvre flown and that in some cases, negative transfer of training may be induced by the tolerances. A forced landing trajectory optimisation was carried out using Genetic Algorithm. The forced landing manoeuvre analyses with pre-selected touchdown locations and pre-selected final headings were carried out for an engine failure at 650 ft AGL for bank angles varying from banking left at 45° to banking right at 45°, and with an aircraft's speed varying from 75.6 mph to 208 mph, corresponding to 5% above airplane's stall speed and airplane's maximum speed respectively. The results show that certain pre-selected touchdown locations are more susceptible to horizontal wind. The results for the forced landing manoeuvre with a pre-selected location show minimal distance error while the quality of the results for the forced landing manoeuvre with a pre-selected location and a final heading show that the results depend on the end constraints. For certain pre-selected touchdown locations and final headings, the airplane may either touchdown very close to the pre-selected touchdown location but with greater final h eading error from the pre-selected final heading or touchdown with minimal final heading error from the pre-selected final heading but further away from the pre-selected touchdown location. Analyses for an obstacle avoidance forced landing manoeuvre were also carried out where an obstacle was intentionally placed in the flight path as found by the GA program developed for without obstacle. The methodology developed successfully found flight paths that will avoid the obstacle and touchdown near the pre-selected location. In some cases, there exist more than one ensemble grouping of flight paths. The distance error depends on both the pre-selected touchdown location and where the obstacle was placed. The distance error tends to increase with the addition of a specific final heading requirement for an obstacle avoidance forced landing manoeuvre. As with the case without specific final heading requirement, there is a trade off between touching down nearer to the pre-selected location and touching down with a smaller final heading error