Joyce Chapman posing by an orange tree, 1998

Joyce Chapman posing by an orange tree, West Covina, California, 1998.

Excavating a fossilized tree that is now in front of Hashinger Hall

Excavating a fossilized tree, which was later placed in front of Hashinger Hall, Chapman University, 346 N. Center Street, Orange, California. The late Dr. Edward H. Hashinger, former trustee and past chairman of the board is the man whose name has graced the walls of this building since 1969. The Hashinger Science Center (3 floors, 65,364 sq.ft.) houses all science departments including biology, natural and applied sciences, environmental and chemical sciences, food science and nutrition, kinesiology and physical therapy.

Placing a fossilized tree in front of Hashinger Hall, Chapman College, Orange, California

Placing a fossilized tree in front of Hashinger Hall, Chapman College, 346 N. Center Street, Orange, California. The late Dr. Edward H. Hashinger, former trustee and past chairman of the board is the man whose name has graced the walls of this building since 1969. The Hashinger Science Center (3 floors, 65,364 sq.ft.) houses all science departments including biology, natural and applied sciences, environmental and chemical sciences, food science and nutrition, kinesiology and physical therapy.

Decoding algorithms using side-effect machines

Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems with applications to DNA. By using side effect machines we hope to be able to provide efficient decoding algorithms for this open problem. Two ideas for decoding algorithms are presented and examined. Both decoders use Side Effect Machines(SEMs) which are generalizations of finite state automata. Single Classifier Machines(SCMs) use a single side effect machine to classify all words within a code. Locking Side Effect Machines(LSEMs) use multiple side effect machines to create a tree structure of subclassification. The goal is to examine these techniques and provide new decoders for existing codes. Presented are ideas for best practices for the creation of these two types of new edit metric decoders.

Problem children with and without communication delays : the changes in their parents' report of challenging behaviour, parental hassles and family conflict over a two -year period

The goal of this study was to examine the change, over a two year period, in mothers' reports of children's challenging behaviour and family conflict as they relate to change in parenting hassles (stress) among families who have preschool children with and without communication delays. Forty-four parent-child dyads participated in this Family Resource Project study that was funded by the Canadian Language and Literacy Research Network. Thirty-one ofthese families had preschool children with communication delays and 13 children were identified as not having communication delays. Child behaviour was evaluated using the Oppositional Subscale and ADHD Index of the Conners Parent Rating Scale (CPRS-R:S), the Conflict Subscale ofthe Family Environment Scale was used to examine family conflict, and the Parent Hassles Scale was used to examine parental stress. Results showed that change in mothers' daily hassles was influenced by change in their preschool children's ADHD behaviour and change in family conflict. Change in child oppositional behaviour did not predict change in mothers' hassles scores.

Using genetic algorithms for the single allocation hub location problem

Hub location problem is an NP-hard problem that frequently arises in the design of transportation and distribution systems, postal delivery networks, and airline passenger flow. This work focuses on the Single Allocation Hub Location Problem (SAHLP). Genetic Algorithms (GAs) for the capacitated and uncapacitated variants of the SAHLP based on new chromosome representations and crossover operators are explored. The GAs is tested on two well-known sets of real-world problems with up to 200 nodes. The obtained results are very promising. For most of the test problems the GA obtains improved or best-known solutions and the computational time remains low. The proposed GAs can easily be extended to other variants of location problems arising in network design planning in transportation systems.

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied.

Families with Children with Autism, Developmental Delay, and Typical Development: The Relationships of Parenting Self-Efficacy, Parenting Strategies, and Child Problem Behaviour

Parents of children with autism spectrum disorders (ASD) and developmental delays (DD) may experience more child problem behaviours, report lower parenting selfefficacy (PSE), and be more reactive than proactive in their parenting strategies than those who have children with typical development (TD). Differences in PSE and parenting strategies may also influence the extent to which child problem behaviours are experienced by parents who have children with ASD and DD, compared to those who have children with TD. Using a convenience sample of parents of children with ASD (n = 48), DD (n = 51), and TD (n = 72), this study examined group differences on three key variables: PSE, parenting strategies, and child problem behaviour. Results indicated that those in the DD group scored lower on PSE in preventing child problem behaviour than the ASD group. The TD group used fewer reactive strategies than the DD group, and fewer proactive strategies than both the ASD and DD groups. For the overall sample, higher reactive strategies use was found to predict higher ratings of child problem behaviour, while a greater proportion of proactive to reactive strategies use predicted lower ratings of child problem behaviour. PSE was found to moderate DD diagnosis and child problem behaviour. Implications for a behavioural (i.e., parenting strategies) or cognitive (i.e., PSE) approach to parenting are discussed.

A Needs Assessment: Language Instruction Stakeholders Engaging in Project Based Learning Outside the Classroom for Effective Strategic Problem Solving

Abstract A noted benefit of Project Based Learning (PBL) as a teaching strategy is how it engages the student and enhances learning outcomes as a result of working through challenges intended to depict dilemmas outside the classroom. PBL has seldom been applied outside the parameters of the classroom curriculum. The current needs assessment carried out in this research project examined current practices of language instruction and International Administrative Professionals of both the private and public Language Industry. Participants responded to survey questions on their current administrative practices, strategies, and program characteristics. The study investigated the usefulness of a handbook on the procedure of assisting administrative service teams in language instruction settings to an engaged approach to PBL for student service issues. The diverse opinions, beliefs, and ideas, along with institutional policy, can provide beneficial framework ideas for future tools.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Multi-Objective Genetic Algorithms for the Single Allocation Hub Location Problem

Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

New Contig Creation Algorithm for the de novo DNA Assembly Problem

DNA assembly is among the most fundamental and difficult problems in bioinformatics. Near optimal assembly solutions are available for bacterial and small genomes, however assembling large and complex genomes especially the human genome using Next-Generation-Sequencing (NGS) technologies is shown to be very difficult because of the highly repetitive and complex nature of the human genome, short read lengths, uneven data coverage and tools that are not specifically built for human genomes. Moreover, many algorithms are not even scalable to human genome datasets containing hundreds of millions of short reads. The DNA assembly problem is usually divided into several subproblems including DNA data error detection and correction, contig creation, scaffolding and contigs orientation; each can be seen as a distinct research area. This thesis specifically focuses on creating contigs from the short reads and combining them with outputs from other tools in order to obtain better results. Three different assemblers including SOAPdenovo [Li09], Velvet [ZB08] and Meraculous [CHS+11] are selected for comparative purposes in this thesis. Obtained results show that this thesis’ work produces comparable results to other assemblers and combining our contigs to outputs from other tools, produces the best results outperforming all other investigated assemblers.

Tree Fruit (peach) Nursery - Report done for the University of Guelph

A report done by Donald Ziraldo on the topic of Tree Fruit, specifically peach, in nurseries. The report was likely done while he was a student of the University of Guelph in the 1970s.