Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

Genetic improvement of giant freshwater prawn in Vietnam

The giant freshwater prawn (Macrobrachium rosenbergii) or GFP is one of the most important freshwater crustacean species in the inland aquaculture sector of many tropical and subtropical countries. Since the 1990’s, there has been rapid global expansion of freshwater prawn farming, especially in Asian countries, with an average annual rate of increase of 48% between 1999 and 2001 (New, 2005). In Vietnam, GFP is cultured in a variety of culture systems, typically in integrated or rotational rice-prawn culture (Phuong et al., 2006) and has become one of the most common farmed aquatic species in the country, due to its ability to grow rapidly and to attract high market price and high demand. Despite potential for expanded production, sustainability of freshwater prawn farming in the region is currently threatened by low production efficiency and vulnerability of farmed stocks to disease. Commercial large scale and small scale GFP farms in Vietnam have experienced relatively low stock productivity, large size and weight variation, a low proportion of edible meat (large head to body ratio), scarcity of good quality seed stock. The current situation highlights the need for a systematic stock improvement program for GFP in Vietnam aimed at improving economically important traits in this species. This study reports on the breeding program for fast growth employing combined (between and within) family selection in giant freshwater prawn in Vietnam. The base population was synthesized using a complete diallel cross including 9 crosses from two local stocks (DN and MK strains) and a third exotic stock (Malaysian strain - MY). In the next three selection generations, matings were conducted between genetically unrelated brood stock to produce full-sib and (paternal) half-sib families. All families were produced and reared separately until juveniles in each family were tagged as a batch using visible implant elastomer (VIE) at a body size of approximately 2 g. After tags were verified, 60 to 120 juveniles chosen randomly from each family were released into two common earthen ponds of 3,500 m2 pond for a grow-out period of 16 to 18 weeks. Selection applied at harvest on body weight was a combined (between and within) family selection approach. 81, 89, 96 and 114 families were produced for the Selection line in the F0, F1, F2 and F3 generations, respectively. In addition to the Selection line, 17 to 42 families were produced for the Control group in each generation. Results reported here are based on a data set consisting of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Experiments assessed performance of VIE tags in juvenile GFP of different size classes and individuals tagged with different numbers of tags showed that juvenile GFP at 2 g were of suitable size for VIE tags with no negative effects evident on growth or survival. Tag retention rates were above 97.8% and tag readability rates were 100% with a correct assignment rate of 95% through to mature animal size of up to 170 g. Across generations, estimates of heritability for body traits (body weight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) and carcass weight traits (abdominal weight, skeleton-off weight and telson-off weight) were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P > 0.05). Maternal and common environmental effects for body traits accounted for 4 to 5% of the total variance and were greater in females (7 to 10%) than in males (4 to 5%). Genetic correlations among body traits were generally high in both sexes. Genetic correlations between body and carcass weight traits were also high in the mixed sexes. Average selection response (% per generation) for body weight (transformed to square root) estimated as the difference between the Selection and the Control group was 7.4% calculated from least squares means (LSMs), 7.0% from estimated breeding values (EBVs) and 4.4% calculated from EBVs between two consecutive generations. Favourable correlated selection responses (estimated from LSMs) were detected for other body traits (12.1%, 14.5%, 10.4%, 15.5% and 13.3% for body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width, respectively) over three selection generations. Data in the second selection generation showed positive correlated responses for carcass weight traits (8.8%, 8.6% and 8.8% for abdominal weight, skeleton-off weight and telson-off weight, respectively). Data in the third selection generation showed that heritability for body traits were moderate and ranged from 0.06 to 0.11 and 0.11 to 0.22 at weeks 10 and 18, respectively. Body trait heritabilities estimated at week 10 were not significantly lower than at week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Overall our results suggest that growth rate responds well to the application of family selection and carcass weight traits can also be improved in parallel, using this approach. Moreover, selection for high growth rate in GFP can be undertaken successfully before full market size has been reached. The outcome of this study was production of an improved culture strain of GFP for the Vietnamese culture industry that will be trialed in real farm production environments to confirm the genetic gains identified in the experimental stock improvement program.

Fractional models for the migration of biological cells in complex spatial domains

Travelling wave phenomena are observed in many biological applications. Mathematical theory of standard reaction-diffusion problems shows that simple partial differential equations exhibit travelling wave solutions with constant wavespeed and such models are used to describe, for example, waves of chemical concentrations, electrical signals, cell migration, waves of epidemics and population dynamics. However, as in the study of cell motion in complex spatial geometries, experimental data are often not consistent with constant wavespeed. Non-local spatial models have successfully been used to model anomalous diffusion and spatial heterogeneity in different physical contexts. In this paper, we develop a fractional model based on the Fisher-Kolmogoroff equation and analyse it for its wavespeed properties, attempting to relate the numerical results obtained from our simulations to experimental data describing enteric neural crest-derived cells migrating along the intact gut of mouse embryos. The model proposed essentially combines fractional and standard diffusion in different regions of the spatial domain and qualitatively reproduces the behaviour of neural crest-derived cells observed in the caecum and the hindgut of mouse embryos during in vivo experiments.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

Business model experimentation : what is the role of deign-led prototyping in developing novel business models?

This book presents readers with the opportunity to fundamentally re-evaluate the processes of innovation and entrepreneurship, and to rethink how they might best be stimulated and fostered within our organizations and communities. The fundamental thesis of the book is that the entrepreneurial process is not a linear progression from novel idea to successful innovation, but is an iterative series of experiments, where progress depends on the persistence and resilience of the individuals involved, and their ability and to learn from failure as well as success. From this premise, the authors argue that the ideal environment for new venture creation is a form of “experimental laboratory,” a community of innovators where ideas are generated, shared, and refined; experiments are encouraged; and which in itself serves as a test environment for those ideas and experiments. This environment is quite different from the traditional “incubator,” which may impose the disciplines of the established firm too early in the development of the new venture.