119 resultados para BIOSPECIFIC INTERACTION ANALYSIS


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Condition monitoring of diesel engines can prevent unpredicted engine failures and the associated consequence. This paper presents an experimental study of the signal characteristics of a 4-cylinder diesel engine under various loading conditions. Acoustic emission, vibration and in-cylinder pressure signals were employed to study the effectiveness of these techniques for condition monitoring and identifying symptoms of incipient failures. An event driven synchronous averaging technique was employed to average the quasi-periodic diesel engine signal in the time domain to eliminate or minimize the effect of engine speed and amplitude variations on the analysis of condition monitoring signal. It was shown that acoustic emission (AE) is a better technique than vibration method for condition monitor of diesel engines due to its ability to produce high quality signals (i.e., excellent signal to noise ratio) in a noisy diesel engine environment. It was found that the peak amplitude of AE RMS signals correlating to the impact-like combustion related events decreases in general due to a more stable mechanical process of the engine as the loading increases. A small shift in the exhaust valve closing time was observed as the engine load increases which indicates a prolong combustion process in the cylinder (to produce more power). On the contrary, peak amplitudes of the AE RMS attributing to fuel injection increase as the loading increases. This can be explained by the increase fuel friction caused by the increase volume flow rate during the injection. Multiple AE pulses during the combustion process were identified in the study, which were generated by the piston rocking motion and the interaction between the piston and the cylinder wall. The piston rocking motion is caused by the non-uniform pressure distribution acting on the piston head as a result of the non-linear combustion process of the engine. The rocking motion ceased when the pressure in the cylinder chamber stabilized.

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The inclusion of carbon nanotubes in polymer matrix has been proposed to enhance the polymer’s physical and electrical properties. In this study, microscopic and spectroscopic techniques are used to investigate the interaction between poly(3-hexylthiophene) (P3HT) and nanotubes and the reciprocal modification of physical properties. The presence of P3HT-covered nanotubes dispersed in the polymer matrix has been observed by atomic force microscopy and transmission electron microscopy. Then, the modification of P3HT optical properties due to nanotube inclusion has been evidenced with spectroscopic techniques like absorption and Raman spectroscopy. The study is completed with detailed nanoscale analysis by scanning probe techniques. The ordered self assembly of polymer adhering on the nanotube is unveiled by showing an example of helical wrapping of P3HT. Scanning tunneling spectroscopy study provides information on the electronic structure of nanotube-polymer assembly, revealing the charge transfer from P3HT to the nanotube.

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This study investigates facework (communicative) strategies of Sri Lankans working in Australia and compares them with strategies used by Australians of European origin working in Australia. The study also explores the values of those Sri Lankans as a reflection of their facework, and how Sri Lankans have adjusted their facework to the Australian culture. The study used a survey questionnaire and interviewed Sri Lankans working in Australia for this investigation. The survey questionnaire was used to understand the facework similarities and difference between the Sri Lankans and Australians as explained in Oetzel and Ting-Toomey’s Face Negotiation Model. The survey revealed that Sri Lankans are higher in interdependent self construal, self face concern and other face concern than the Australians. Nonetheless, Sri Lankans are similar to the Australians in other facework strategies. The interviews clarified that Sri Lankans do not change their values by living in Australia, yet they make some changes to how they do things.

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Intuitive interaction is based on past experience and is fast and often non conscious. We have conducted ten studies into this issue over the past ten years, involving more than 400 participants. Data collection methods have included questionnaires, interviews, observations, concurrent and retrospective protocols, and cognitive measures. Coding schemes have been developed to suit each study and involve robust, literature based heuristics. Some other researchers have investigated this issue and their methods are also examined. The paper traces the development of the methods and compares the various approaches used over the years.

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There is a growing need for parametric design software that communicates building performance feedback in early architectural exploration to support decision-making. This paper examines how the circuit of design and analysis process can be closed to provide active and concurrent feedback between architecture and services engineering domains. It presents the structure for an openly customisable design system that couples parametric modelling and energy analysis software to allow designers to assess the performance of early design iterations quickly. Finally, it discusses how user interactions with the system foster information exchanges that facilitate the sharing of design intelligence across disciplines.

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The Making Design and Analysing Interaction track at the Participatory Innovation Conference calls for submissions from ‘Makers’ who will contribute examples of participatory innovation activities documented in video and ‘Analysts’ who will analyse those examples of participatory innovation activity. The aim of this paper is to open up for a discussion within the format of the track of the roles that designers could play in analysing the participatory innovation activities of others and to provide a starting point for this discussion through a concrete example of such ‘designerly analysis’. Designerly analysis opens new analytic frames for understanding participatory innovation and contributes to our understanding of design activities.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

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Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

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This article continues the critical analysis of ‘meaningful relationships’ in the context of the operation of the ‘twin pillars’ which underpin the parenting provisions. It will be argued that the attitude of judicial officers to three key questions influence how they interpret this concept and consequently apply the best interest considerations. Relevant to this discussion is an examination of the Full Court’s approach to the key parenting sections, particularly the interaction of the primary and additional considerations. Against this backdrop, a current proposal to amend the ‘twin pillars’ will be examined.

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Transcending traditional national borders, the Internet is an evolving technology that has opened up many new international market opportunities. However, ambiguity remains, with limited research and understanding of how the Internet influences the firm’s internationalisation process components. As a consequence, there has been a call for further investigation of the phenomenon. Thus, the purpose of this study was to investigate the Internet’s impact on the internationalisation process components, specifically, information availability, information usage, interactive communication and international market growth. Analysis was undertaken using structural equation modelling. Findings highlight the mediating impact of the Internet on information and knowledge transference in the internationalisation process. Contributions of the study test conceptualisations and give statistical validation of interrelationships, while illuminating the Internet’s impact on firm internationalisation.

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The Social Web is a torrent of real-time information and an emerging discipline is now focussed on harnessing this information flow for analysis of themes, opinions and sentiment. This short paper reports on early work on designing better user interfaces for end users in manipulating the outcomes from these analysis engines.

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Interactive effects of genotypes with callus induction and regeneration media combinations on green plantlet regeneration response were studied for three indica rice (Oryza sativa L.) cultivars, IR-72, IR-54 and Karnal Local. Isolated mature-embryoswere used to derive scutellar callus and fifteen media combinations involvingMS, N6, R2, SK1 and some modifications were tested. Regeneration percentage as well as the shoot-bud induction frequency were influenced by genotype, callus induction medium, regeneration medium, interaction between genotype and the two media (callus induction and regeneration) as well the interaction between the callus induction medium and regeneration medium. Basal media combination of SK1m (callusing) and MS (regeneration) was found to be the best for cv. Karnal Local in which regeneration frequency of 88% and shoot-bud induction of 233% was observed. In IR-72, the highest regeneration frequency of 47.5% and shoot-bud induction frequency of 77% was obtained on MS-MS combination. In IR-54, highest regeneration frequency (25%) was recorded on MMS(N)-MMS(N) combination, whereas, highest frequency of shoot-bud induction (50%) was observed on MMS(S)-MS combination. Although genotype and the composition of the callus induction basal medium were the major determinants of regeneration response, an overall analysis of variation also revealed a significant interaction between the media used for de-differentiation (callusing) and re-differentiation (plantlet regeneration)

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We report and reflect upon the early stages of a research project that endeavours to establish a culture of critical design thinking in a tertiary game design course. We first discuss the current state of the Australian game industry and consider some perceived issues in game design courses and graduate outcomes. The second sec-tion presents our response to these issues: a project in progress which uses techniques originally exploited by Augusto Boal in his work, Theatre of the Oppressed. We appropriate Boal’s method to promote critical design thinking in a games design class. Finally, we reflect on the project and the ontology of design thinking from the perspective of Bruce Archer’s call to reframe design as a ‘third academic art’.

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Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

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This paper discusses users’ query reformulation behaviour while searching information on the Web. Query reformulations have emerged as an important component of Web search behaviour and human-computer interaction (HCI) because a user’s success of information retrieval (IR) depends on how he or she formulates queries. There are various factors, such as cognitive styles, that influence users’ query reformulation behaviour. Understanding how users with different cognitive styles formulate their queries while performing Web searches can help HCI researchers and information systems (IS) developers to provide assistance to the users. This paper aims to examine the effects of users’ cognitive styles on their query reformation behaviour. To achieve the goal of the study, a user study was conducted in which a total of 3613 search terms and 872 search queries were submitted by 50 users who engaged in 150 scenario-based search tasks. Riding’s (1991) Cognitive Style Analysis (CSA) test was used to assess users’ cognitive style as wholist or analytic, and verbaliser or imager. The study findings show that users’ query reformulation behaviour is affected by their cognitive styles. The results reveal that analytic users tended to prefer Add queries while all other users preferred New queries. A significant difference was found among wholists and analytics in the manner they performed Remove query reformulations. Future HCI researchers and IS developers can utilize the study results to develop interactive and user-cantered search model, and to provide context-based query suggestions for users.