40 resultados para Computer generated works
Resumo:
This study was undertaken in order to determine the
effects of playing computer based text adventure games on
the reading comprehension gains of students. Forty-five
grade five students from one elementary school were
randomly assigned to experimental and control groups, and
were tested with regard to ability, achievement and reading
skills. An experimental treatment, consisting of playing
computer based interactive fiction games of the student's
choice for fifteen minutes each day over an eight-week
period, was administered. A comparison treatment engaged
the control group in sustained silent reading of materials of
the student's choice for an equal period of time. Following
the experimental period all students were post-tested with an
alternate form of the pre-test in reading skills, and gain
scores were analysed. It was found that there were no
significant differences in the gain scores of the experimental
and control groups for overall reading comprehenSion, but the
experimental group showed greater gains than the control
group in the structural analysis reading sub-skill. Extreme
variance in the data made generalization very difficult, but
the findings indicated a potential for computer based
interactive fiction as a useful tool for developing reading
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Resumo:
Generation Y is entering the workforce in large numbers and, because this generation holds different values than previous generations, accounting firms are having difficulty managing these new hires. I t is important to determine whether Generation Y is associated with meaningful, long-term trends or i f they will adapt to the given situation. Gen Y' s association with average hours worked per person and average salaries in the Canadian Accounting, Marketing, and Legal professions is examined. I find that an increasing percentage of Generation Y employees in the workforce is associated with significant decreases in average hours worked, but is not associated with any significant trend in average salary. I t is concluded that Generation Y is associated with changing trends in the workplace. These trends are contrary to wha t might be expected under traditional definitions of success, therefore it is postulated that Gen Y may view workplace success differently than previous generations.
Resumo:
Layout planning is a process of sizing and placing rooms (e.g. in a house) while a t t empt ing to optimize various criteria. Often the r e are conflicting c r i t e r i a such as construction cost, minimizing the distance between r e l a t ed activities, and meeting the area requirements for these activities. The process of layout planning ha s mostly been done by hand, wi th a handful of a t t empt s to automa t e the process. Thi s thesis explores some of these pa s t a t t empt s and describes several new techniques for automa t ing the layout planning process using evolutionary computation. These techniques a r e inspired by the existing methods, while adding some of the i r own innovations. Additional experimenLs are done to t e s t the possibility of allowing polygonal exteriors wi th rectilinear interior walls. Several multi-objective approaches are used to evaluate and compare fitness. The evolutionary r epr e s ent a t ion and requirements specification used provide great flexibility in problem scope and depth and is worthy of considering in future layout and design a t t empt s . The system outlined in thi s thesis is capable of evolving a variety of floor plans conforming to functional and geometric specifications. Many of the resulting plans look reasonable even when compared to a professional floor plan. Additionally polygonal and multi-floor buildings were also generated.
Resumo:
Relation algebras is one of the state-of-the-art means used by mathematicians and computer scientists for solving very complex problems. As a result, a computer algebra system for relation algebras called RelView has been developed at Kiel University. RelView works within the standard model of relation algebras. On the other hand, relation algebras do have other models which may have different properties. For example, in the standard model we always have L;L=L (the composition of two (heterogeneous) universal relations yields a universal relation). This is not true in some non-standard models. Therefore, any example in RelView will always satisfy this property even though it is not true in general. On the other hand, it has been shown that every relation algebra with relational sums and subobjects can be seen as matrix algebra similar to the correspondence of binary relations between sets and Boolean matrices. The aim of my research is to develop a new system that works with both standard and non-standard models for arbitrary relations using multiple-valued decision diagrams (MDDs). This system will implement relations as matrix algebras. The proposed structure is a library written in C which can be imported by other languages such as Java or Haskell.
Resumo:
Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.
Resumo:
Basic relationships between certain regions of space are formulated in natural language in everyday situations. For example, a customer specifies the outline of his future home to the architect by indicating which rooms should be close to each other. Qualitative spatial reasoning as an area of artificial intelligence tries to develop a theory of space based on similar notions. In formal ontology and in ontological computer science, mereotopology is a first-order theory, embodying mereological and topological concepts, of the relations among wholes, parts, parts of parts, and the boundaries between parts. We shall introduce abstract relation algebras and present their structural properties as well as their connection to algebras of binary relations. This will be followed by details of the expressiveness of algebras of relations for region based models. Mereotopology has been the main basis for most region based theories of space. Since its earliest inception many theories have been proposed for mereotopology in artificial intelligence among which Region Connection Calculus is most prominent. The expressiveness of the region connection calculus in relational logic is far greater than its original eight base relations might suggest. In the thesis we formulate ways to automatically generate representable relation algebras using spatial data based on region connection calculus. The generation of new algebras is a two pronged approach involving splitting of existing relations to form new algebras and refinement of such newly generated algebras. We present an implementation of a system for automating aforementioned steps and provide an effective and convenient interface to define new spatial relations and generate representable relational algebras.
Resumo:
Memoirs of the late Brigadier-General Sir Samuel Bentham, with an account of his inventions -- The Paddock Viaduct / by John Hawkshaw -- Lockwood Viaduct / by John Hawkshaw -- Denby Dale Viaduct / by John Hawkshaw -- Tithebarn Street Viaduct, Liverpool / by John Hawkshaw -- Newark Dyke Bridge on the Great Northern Railway / by Joseph Cubitt -- Mountain top track in the state of Virginia / by Charles Ellet -- Preliminaries to good building / by Edward Lacy Garbett / Suggestions for increasing the circulating medium in aid of commerce and mechanical enterprise
Resumo:
An advertisement addressed to the "celebration committees" for May 24th and July 1st. William Hand details his services for fireworks and other lighting. Price ranges are included and reviews/comments quoted from several newspapers.
Resumo:
A moving advertisement for Garden City Dye Works, reads: We have removed from No. 70, St. Paul St. to No. 125 St. Paul St. Opp. the Grand Central Hotel, where we will be pleased to see our old and many new customers. Remember the place. In our new quarters we are better able to meet the requirements of the public in our line. We are up-to-date in all branches of Cleaning and Dying Ladies' and Gent's wearing apparel. Garden City Works, J.L. Wilbur. 125 St. Paul St. Phone 54. P.S. Also agents for Parisian Laundry Co.
Resumo:
While the influence of computer technology has been widely studied in a variety of contexts, the drawing teaching studio is a particularly interesting context because of the juxtaposition of traditional medium and computer technology. For this study, 5 Canadian postsecondary teachers engaged in a 2-round Delphi interview process to discuss their responses to computer technology on their drawing pedagogy. Data sources included transcribed interviews. Findings indicated that artist teachers are both cautious to embrace and curious to explore appropriate use of computer technology on their drawing pedagogy. Artist teachers are both critical and optimistic about the influence of computer technology.
Resumo:
A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.
Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks
Resumo:
Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.
Resumo:
As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.
Resumo:
A Water Works report (1 page of newsprint which is slightly tattered and taped – this does not affect the text) by Mr. T. C. Keefer regarding proposed works for the supply of water to St. Catharines, Jan. 4, 1876.