Journal of Integrated Design and Process Science - Volume 11, issue 3

Article Type: Other

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 1-3, 2007

Authors: von Buelow, Peter

Article Type: Research Article

Abstract: In early phases of design a wide exploration of the design space is crucial to the development of creative solutions. In this regard, Evolutionary Computation (EC), and in particular Genetic Algorithms, contain several qualities that can enhance exploration by opening the search process beyond the focus of finding a single "best" solution. Over the years many researchers in the area of creative thinking including Gordon, de Bono, Parnes, Osborn and others, have suggested design strategies that …have interesting parallels in EC processes. For instance, a well known inhibitor of creative thinking is design fixation, where the suggestion of a particular solution makes it difficult to imagine other good solutions. Unlike many other computational search algorithms, EC methods work with populations of "fairly good" solutions. Therefore, there is less danger that creativity will be harmed by design fixation on one "best" solution. This paper shows through a specific example of a truss bridge how an EC based design exploration program can aid the designer by providing a selection of "pretty good" solutions rather than a single optimal solution. Other aspects of the EC program are also discussed including drawbacks to the method such as computational intensity as well as directions of future development. Show more

Keywords: genetic, evolutionary, truss, topology, exploration, optimization, morphogogy

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 5-18, 2007

Authors: Samsonovich, Alexei V.

Article Type: Research Article

Abstract: This paper focuses on three connected to each other fundamental beliefs that appear to be unconsciously taken for granted at the basis of modern cognitive neuroscience: (i) the attractor hypothesis, (ii) the neural code hypothesis, and (iii) the supervenience hypothesis about human subjective experience. Their precise understanding and experimental verification is an important challenge that calls for a scientific paradigm change and needs to be addressed for future progress in cognitive neuroscience. The work presents a …theoretical analysis and preliminary experimental and modeling results that suggest a roadmap to solving the challenge. Show more

Keywords: semantic cognitive mapping, attractor dynamics, computational consciousness

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 19-30, 2007

Authors: Ingber, Lester

Article Type: Research Article

Abstract: Ideas by Statistical Mechanics (ISM) is a generic program to model evolution and propagation of ideas/patterns throughout populations subjected to endogenous and exogenous interactions. The program is based on the author's work in Statistical Mechanics of Neocortical Interactions (SMNI), and uses the author's Adaptive Simulated Annealing (ASA) code for optimizations of training sets, as well as for importance-sampling to apply the author's copula financial riskmanagement codes, Trading in Risk Dimensions (TRD), for assessments of risk …and uncertainty. This product can be used for decision support for projects ranging from diplomatic, information, military, and economic (DIME) factors of propagation/evolution of ideas, to commercial sales, trading indicators across sectors of financial markets, advertising and political campaigns, etc. It seems appropriate to base an approach for propagation of ideas on the only system so far demonstrated to develop and nurture ideas, i.e., the neocortical brain. A statistical mechanical model of neocortical interactions, developed by the author and tested successfully in describing short-term memory and EEG indicators, is the proposed model. ISM develops subsets of macrocolumnar activity of multivariate stochastic descriptions of defined populations, with macrocolumns defined by their local parameters within specific regions and with parameterized endogenous inter-regional and exogenous external connectivities. Parameters of subsets of macrocolumns will be fit using ASA to patterns representing ideas. Parameters of external and inter-regional interactions will be determined that promote or inhibit the spread of these ideas. Tools of financial risk management, developed by the author to process correlated multivariate systems with differing non-Gaussian distributions using modern copula analysis, importancesampled using ASA, will enable bona fide correlations and uncertainties of success and failure to be calculated. Marginal distributions will be evolved to determine their expected duration and stability using algorithms developed by the author, i.e., PATHTREE and PATHINT codes. Show more

Keywords: statistical mechanics, neocortical interactions, simulated annealing, risk management

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 31-54, 2007

Authors: Madni, Azad M. | Andrecut, Mircea

Article Type: Research Article

Abstract: In this paper, the authors describe a gene network reverse engineering method, which employs mutual information to infer the connections between the genes. Given the expression profile of the genes, determined for different conditions, the method calculates the similarity matrix corresponding to the mutual information between each pair of genes. The approximated matrix can be subsequently refined by using a data processing inequality and an analytically estimated threshold for the statistical significance of mutual …information. The authors have used the proposed method to reconstruct a network of 2041 gene transcription factors, measured over 79 human tissues. The numerical results show that the connectivity of the transcription factors network is characterized by a scale free distribution, with an exponent of the power law between 1.5 and 2. The power law for the connectivity distribution implies that the network is extremely heterogeneous; i.e., its topology is dominated by a few highly connected genes, which link the rest of the loosely-connected genes to the system. Show more

Keywords: mutual information, gene networks, reverse engineering, similarity matrix, gene transcription factors, power law

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 55-68, 2007

Authors: Khalid, Sabah | Grazio, Daniela | Wang, Ping | Liu, Xiaohui | Li, Su-Ling

Article Type: Research Article

Abstract: The declaration "DNA microarrays serve as powerful tools for the global characterization of gene expression" is widely accepted by the scientific community exploiting microarray technology. With the inherent ability to distinguish between the expression levels of genes, microarrays have the power to provide the researcher with a direction for further exploration. However, the immediate results from microarray experiments require further mining to determine the genes, which have been differentially expressed. This narrows …down the dataset to those genes that are of most interest to the researcher. In turn, hypotheses regarding the significance of these genes within the molecular mechanism being investigated can be generated. This would result in a more in-depth investigation within the researcher's area of expertise and further microarray experiments. The purpose of these experiments would be to answer more detailed biological questions arising from the analysis of the initial microarray. As a result of the enhanced focus within the investigative area, it would be ideal to use more specialised microarrays facilitating the gain of further knowledge into the biological aspect under scrutiny. Although commercially available, microarrays may be of limited use if they fail to represent the targeted pathways and biological processes to the extent required. Hence, customised microarrays become extremely advantageous, benefiting researchers with particular requirements. Furthermore, due to the sheer cost of DNA gene chips it is impractical to purchase microarrays for every biological need, and thus, it becomes imperative for biologists to maximise the use of existing gene sets. In order to achieve this, bioinformatics tools are necessary to extract meaningful data from the gene set according to a biologist's requirements. To this end, the authors have developed the first software, called Gene Chip Design, which can extract meaningful data from a given gene set according to a biologist's needs. This unique information retrieval software is a powerful, flexible and user-friendly tool aimed at researchers needing to generate personalised custom in-house arrays that represent the genes from specialised biological pathways of interest. With the inbuilt functionality to generate a novel gene chip specific to a researcher's interest from any given generalised gene set, this software can be applied within any biological field. An ontology to allow the global functional characterization of any given gene set, has also been created, together with the unique ability to categorize genes in a more structured and informative manner within numerous functional groups. Furthermore, this software identifies biological pathways pertaining to genes of interest. These aspects also provide researchers with the control to identify further genes with biological functions of interest to extract from their gene set and incorporate into their unique gene chip. Using their NIA 15K Mouse cDNA Clone Gene Set, the authors have designed several gene chips including an oncology gene chip. Furthermore, combined with their previous microarray experimental results, the researchers have developed a novel immuno-tolerance gene chip that can be used for further studies investigating the molecular mechanisms underlying autoimmune disease. Show more

Keywords: oncology, immune tolerance, microarrays, gene chip design, functional annotation, biological pathways

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 69-83, 2007

Authors: Esat, I. I.

Article Type: Research Article

Abstract: This paper presents some studies in biologically inspired computing. The case studies are grouped under two sections, in the first section case studies involving more fundamental aspects of networks and in the second section application oriented studies are presented. The first section involves geometrical interpretation of back propagation networks and a scheme for generating network structure from the decision space was offered. The second study presents a new encoding scheme and also studies how the encoding …scheme and performance are related. The third study is specific to Hopfield neural networks and shows that a stiffness matrix has properties which allow it being mapped to the Hopfileld transition matrix. The last study presents the particle swarming algorithm and a new concept of quantum inspired computing. The second section involves cases relating to some engineering applications or bench marks of some biologically inspired computing. The case studies as many of them based on manipulation of engineering structures, this section presents a stiffness matrix of a simple spring attached on a 3D body. The following study involves manipulation of matrix elements in order to achieve vibration decoupling (of modes). This is studied in three different ways; firstly an analytical solution is obtained. This way, the equations were proved to be ill conditioned. The second study involves using these equations with GA algorithm which showed that GA is robust in dealing with ill conditioned problems and finally it was assumed no prior knowledge of the matrix formulation. In this case GA operated directly with the mode shapes obtained from the eigenvector analysis. The final approach appears to be the most unreliable in convergence. The matrix formulation was also used with Hopfield networks. The other examples included gearbox fault detection which as well as identifying the faults the study demonstrated the importance of preprocessing and information filtering or refinement. Furthermore the studies on gear box faults showed that even the type of preprocessing influences the performance of identification. The study of fault identification in gas cylinders led recognition of various loopholes in manually selection of features for fault identification. The study involved manual feature extraction which in this case led to endless experiments, however the use of the frequency response function (FRF) proved to be the most effective in this case and probably it is likely to be the same for similar cases where the system disturbance levels cannot be repeated. The last case study involved bench mark based comparative study among GA, PSO and quantum inspired computing. This study showed that all three are similar in their effectiveness but quantum inspired computing algorithm showed an incredibly fast convergence during the first few cycles of optimization. A series of less detailed cases such as cellular automata for breast cancer growth modeling, the use of GA in real time control, were also included in the paper. The paper, finally weighs findings against the No Free Lunch (NLF) theorem, although conclusions are complimentary. The work presented illustrates the reliance of biologically inspired computing to representation and encoding schemes both for architecture and data for its effective execution. Show more

Keywords: ANN design, GA, PSO, biologically inspired, quantum inspired, stochastic search

Citation: Journal of Integrated Design & Process Science, vol. 11, no. 3, pp. 85-104, 2007