A novel monotonic fixed-point algorithm for l1-regularized least square vector and matrix problem

Least square problem with l₁ regularization has been proposed as a promising method for sparse signal reconstruction (e.g., basis pursuit de-noising and compressed sensing) and feature selection (e.g., the Lasso algorithm) in signal processing, statistics, and related fields. These problems can be cast as l₁-regularized least-square program (LSP). In this paper, we propose a novel monotonic fixed point method to solve large-scale l₁-regularized LSP. And we also prove the stability and convergence of the proposed method. Furthermore we generalize this method to least square matrix problem and apply it in nonnegative matrix factorization (NMF). The method is illustrated on sparse signal reconstruction, partner recognition and blind source separation problems, and the method tends to convergent faster and sparser than other l₁-regularized algorithms.

When more is less : urban remnants support high bird abundance but diversity varies

Urban remnant vegetation, especially where it occurs in public parks, allows for relatively easy access for ongoing biodiversity monitoring. However, relatively little baseline information on bird species distribution and abundance across a range of identifiable urban remnants appears in the published literature. We surveyed the relative abundance and distribution of birds across urban and suburban remnant vegetation in Melbourne, Australia. One hundred and six species were recorded, of which 98 were indigenous. Red wattlebirds had the highest mean relative abundance with 2.94 birds/ha, followed by rainbow lorikeets (2.51), noisy miners (1.93), brown thornbills (1.75) and spotted doves (0.96). There was no obvious trend between overall relative abundance and the size of the remnant, in contrast to species richness which was positively correlated with remnant size. The data revealed that some species were either totally restricted to, or more abundant in, larger remnants and generally absent from smaller remnants. Some of the more common birds (crimson rosella, superb fairy-wren, spotted pardalote and black-faced cuckoo-shrike) recorded during this study were detected at similar densities to those found in comparable vegetation to the east of Melbourne within a largely forested landscape. Other species occurred at much lower densities (e.g., white-browed scrubwren, brown thornbill, eastern yellow robin and grey fantail) or had habitat requirements or ecological characteristics that could place them at risk of further decline or local extinction in the urban area. We identify a suite of bird species of potential conservation concern within Melbourne’s urban landscape. The establishment of repeatable, fixed-point, and long-term monitoring sites will allow for repeat surveying over time and provide an early warning of population declines, or conversely an indication of population increase for other species.

Evanescent

Exhibition of original artworks created in 2013. Evanescent is a new series produced in 2013 which premiered at the Castlemaine State Festival 15-24 March 2013. The series revisits a childhood delight and fascination with the projected image and the natural world. For me then, as it is now, a magnifying glass was a wonder; its simple optics twisted light into abstract comas and sci-fi aberrations; able to compact a whole view into a luminous, paradoxically inverted phantom that could fit literally into the palm of my hand. By curling fingers and thumb around the lens and cupping both hands around the elusive rays, and by peering into the space in which I had trapped them, I fancied that I had entered into the secret workings of the eye. Chrysalis, for example, appears as a scenic projection from a hand-held lens and simultaneously as the litter of the forest floor. It is produced with a makeshift camera-obscura. The nebulous silhouettes of trees, some blurred under the passing clouds of a summer wind resolve here and there into crisp lines curled across the surface of a fallen leaf on which a moth chrysalis adheres. The leaf assumes Brobdingnagian proportions and thickness as the evanescent image shrinks and is foreshortened then dissolves in the enlarged dust and grit. It manifests the unique sight anchored at this fixed point, to reveal what we might see if we were to become vegetable or mineral. Near and far, large and small, superimpose, trigonometrically exact in their adjacency and spatial relations, presenting us with a located point of view.Why? I want to understand more intimately the interior of the natural landscape, rather than any ‘scene’ of human presence, or the context of any cultural landmark. In the steep, bush locations in which I am making these images, my means are necessarily makeshift; my camera and an old manual-aperture lens able to be carried in a backpack with a black T-shirt as a 'dark-tent'. The project is not systematic but intuitive and responsive to prevailing conditions and the effect on the projection caused by sun, shade, weather and situation. I am guided by the response of objects, textures and surfaces to the projected image and how they modulate and map it. This is landscape, but not from a human point of view.

Optimal design of traffic signal controller using neural networks and fuzzy logic systems

This paper aims at optimally adjusting a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. Neural network (NN) and fuzzy logic system (FLS) are two methods applied to develop intelligent traffic timing controller. For this purpose, an intersection is considered and simulated as an intelligent agent that learns how to set green times in each cycle based on the traffic information. The training approach and data for both these learning methods are similar. Both methods use genetic algorithm to tune their parameters during learning. Finally, The performance of the two intelligent learning methods is compared with the performance of simple fixed-time method. Simulation results indicate that both intelligent methods significantly reduce the total delay in the network compared to the fixed-time method.

Optimal fuzzy traffic signal controller for an isolated intersection

  This paper aims at optimally adjusting a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. Fuzzy logic system (FLS) is the method applied to develop the intelligent traffic timing controller. For this purpose, an intersection is considered and simulated as an intelligent agent that learns how to set green times in each cycle based on the traffic information. The FLS controller (FLC) uses genetic algorithm to tune its parameters during learning phase. Finally, The performance of the intelligent FLC is compared with the performance of a FLC with predefined parameters and three simple fixed-time controller. Simulation results indicate that intelligent FLC significantly reduces the total delay in the network compared to the fixed-time method and FLC with manual parameter setting.

A review on computational intelligence methods for controlling traffic signal timing

Urban traffic as one of the most important challenges in modern city life needs practically effective and efficient solutions. Artificial intelligence methods have gained popularity for optimal traffic light control. In this paper, a review of most important works in the field of controlling traffic signal timing, in particular studies focusing on Q-learning, neural network, and fuzzy logic system are presented. As per existing literature, the intelligent methods show a higher performance compared to traditional controlling methods. However, a study that compares the performance of different learning methods is not published yet. In this paper, the aforementioned computational intelligence methods and a fixed-time method are implemented to set signals times and minimize total delays for an isolated intersection. These methods are developed and compared on a same platform. The intersection is treated as an intelligent agent that learns to propose an appropriate green time for each phase. The appropriate green time for all the intelligent controllers are estimated based on the received traffic information. A comprehensive comparison is made between the performance of Q-learning, neural network, and fuzzy logic system controller for two different scenarios. The three intelligent learning controllers present close performances with multiple replication orders in two scenarios. On average Q-learning has 66%, neural network 71%, and fuzzy logic has 74% higher performance compared to the fixed-time controller.

A method for the visual representation of historic multivariate point data

The visual representation of multivariate spatial and temporal data is important for interpreting and analyzing historical geographic patterns that change over time. The introduction of geospatial technologies in historical scholarship has challenged the suitability of current visual representations due to the need for greater temporal emphasis and the tracking of historical events over time. This research presents a holistic multivariate approach to historical visual representation for point based historical data. The method has been developed through extending the spatial presence in information graphics and through meaningful spatial classification. This paper demonstrates the benefits gained from integrating historical, geographic, temporal, and attribute data through the development of a case study on the history of Melbourne’s cinema venues between 1946 and 1986.

Simulation and hardware implementation of new maximum power point tracking technique for partially shaded PV system using hybrid DEPSO method

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.

A hybrid simulated annealing and perturb and observe method for maximum power point tracking in PV systems under partial shading conditions

This paper presents a hybrid method for Maximum Power Point Tracking (MPPT) of a Photovoltaic (PV) system which experiences non-uniform environmental conditions or partial shading conditions. The hybrid method combines two simple techniques with complementary strengths in achieving Global MPPT. Simulated Annealing (SA) has only recently been applied to PV MPPT and is very effective at locating global maxima with limited implementation complexity. Perturb and Observe (P&O) is a very common technique which provides continuous tracking of the MPP in a simple and easy to implement manner. The P&O method is generally incapable of locating global maxima, and the SA based method is unable to perform continuous searching. By merging these techniques in a hybrid MPPT method consisting of a global searching stage and a local searching stage, the tracking performance is improved compared to what each technique could achieve independently. Simulation results are presented to demonstrate the effectiveness of the proposed hybrid technique.

Predicting spatio-temporal distribution for eastern Australian birds using birds Australia's atlas data : survey method, habitat and seasonal effects

Faunal atlases are landscape-level survey collections that can be used for describing spatial and temporal patterns of distribution and densities. They can also serve as a basis for quantitative analysis of factors that may influence the distributions of species. We used a subset of Birds Australia’s Atlas of Australian Birds data (January 1998 to December 2002) to examine the spatio-temporal distribution patterns of 280 selected species in eastern Australia (17–37°S and 136–152°E). Using geographical information systems, this dataset was converted into point coverage and overlaid with a vegetation polygon layer and a half-degree grid. The exploratory data analysis involved calculating species-specific reporting rates spatially, per grid and per vegetation unit, and also temporally, by month and year. We found high spatio-temporal variability in the sampling effort. Using generalised linear models on unaggregated point data, the influences of four factors – survey method and month, geographical location and habitat type – were analysed for each species. When counts of point data were attributed to grid-cells, the total number of species correlated with the total number of surveys, while the number of records per species was highly variable. Surveys had high interannual location fidelity. The predictive values of each of the four factors were species-dependent. Location and habitat were correlated and highly predictive for species with restricted distribution and strong habitat preference. Month was only of importance for migratory species. The proportion of incidental sightings was important for extremely common or extremely rare species. In conclusion, behaviour of species differed sufficiently to require building a customized model for each species to predict distribution. Simple models were effective for habitat specialists with restricted ranges, but for generalists with wide distributions even complex models gave poor predictions.

Second person : a point of view? The function of the second person pronoun in narrative prose fiction

This thesis looks at the functions and effects of the ‘second-person’ pronoun in narrative prose fiction, with particular focus on the fluidity and ambiguity of the mode that I will call Protean-'you.' It is a mode in which it is unclear whether the ‘you’ is a character, the narrator, a reader/narratee, or no-one in particular—or a combination of these—so that readers find ‘second-person’ utterances at once familiar and deeply strange. I regard the ‘second person’ as a special case of narrative ‘person’ that, at its most fluid, can produce an experience of reading quite unlike that of reading traditional ‘first-‘ and ‘third-person’ narrative. Essentially, this unique experience comes about because Protean-‘you’ neglects to constitute the stable modes of subjectivity that readers expect to find within narrative textuality. These stable modes of subjectivity, modelled on what I will refer to as Cartesianism’s hegemonic notion of the self, have been thoroughly formalised and naturalised within the practices of ‘first-‘ and ‘third-person’ narrative. The Protean-‘you’ form of ‘second-person’ narrative, conversely, is a mode of narrative discourse that puts readers in a place of doubt and uncertainty, its unsettling equivocations forcefully disrupting accustomed, mimetic explanations of narrative and denying us access to the foundational, authorising subject of classical Cartesian thought. Rather than founding a notion of ‘second-person’ narrative and narrative ‘person’ generally on Cartesianism's ‘self-ish’ logic of unified, privatised identity, I turn to C.S, Peirce's notion of the semiotic self and to developments in post-structuralist thought. Essentially, the conception of subjectivity underpinning my arguments is Peirce's proposition that the self is to be conceived of not as a cogito, but as a sign by which the conscious entity knows itself. It is a sign, moreover, that is constantly being re-read, reinterpreted, so that identity is never self-complete. This reconception of subjectivity is necessary because 1 will argue that the effects of Protean-‘you’ arise in some part from a tension between Cartesianism's hegemony and what philosophical pragmatism and post-structuralism glimpse as the actual condition of the human subject—the subject as dispersed and contingent rather than unified and authoritative. Most discussions of ‘second-person’ narrative conceive of the mode in terms of implicit communicative relations, in some measure instituting Cartesianism's notion of the intentionalist self at the centre of literary meaning. I contrast the paradigmatic address model that arises from this conception against a model that approaches the analysis of ‘second-person’ narrative modality in terms of a referential function, that is, in terms of the object or objects referred to deictically by the ‘second-person’ pronoun. Two principal functions of ‘second-person’ textuality are identified and discussed at length. The first is generalisation, which is rarely dissipated altogether, a situation that contributes to the ambiguities of the pronoun's reference in much ‘second-person’ fiction. The second principal function is that of address, that is, the allocutionary function. Clearly, although stories that continually refer to a ‘you’ can seem quite baffling and unnatural, not all ‘second-person’ narratives unsettle the reader. In order to make the ‘second person's’ outlandish narratives knowable and stable, we bring to bear on them in our habits of reading whatever hermeneutic frames, whatever interpretive keys, come to hand, including a large number of unexceptional forms of literary and ‘natural’ discourse that employ the ‘second-person’ pronoun. These forms include letter writing and internal dialogue (i.e., talking to one's self), the language of the courtroom, the travelogue, the maxim, and so on. In looking at the ways in which the radicalising potentials of ‘second-person’ discourse are contained or recuperated, I focus on issues of vraisemblance and mimesis. Vraisemblance can be described as the ‘system of conventions and expectations which rests on/reinforces that more general system of ‘mutual knowledge’ produced within a community for the realisation and maintenance of a whole social world’. All of the forms of the vraisemblable are already instituted within social, cultural relations, so that what vraisemblance describes is the way we fit the inscriptions we read-that is, the way in which we naturalise what we read-into those given cultural and social forms. I also look at the conventionalising and naturalising work done by notions of mimesis in explaining relations between the world, our being in it, and texts, proposing that mimesis provides a principle buttress by which the good standing of the metaphor of ‘person’ is preserved in traditional and pre-critical modes of analysis. Indeed, the critic’s recourse to ‘person’ is in some measure always an engagement with mimesis. Any discussion that maintains that mimesis is in some way productive of meaning-which this thesis in fact does-must identify mimesis as a merely conventional category within practices of reading and semiosis more generally, and at the very least remove that term from its traditional position of transparent primacy and authority. Some of the most interesting and insightful arguments about ‘second-person’ narrative propose that the ‘second person’s’ most striking effects derive from the constitution of an ‘intersubjective’ experience of reading in which the subject positions of the ‘you’-protagonist, reader-narratee and narrator are combined into a fluid and indeterminate multiple subjectivity. Notions of intersubjectivity frequently position themselves as liberating the reader from Cartesianism's fixed, authoritative modes of subjectivity, Frequently, however, they tend implicitly to reinstate Cartesianism's notion of the self at the centre of textual practice and subjectivity. I look at Daniel Gunn's novel ‘Almost You’, at length in this context, illustrating the constant overdetermination of the ‘you’ and the novel's narrating voice, and demonstrating that this overdetermination leaves the origin of the narrative discourse, the identity of the narrator, and the ontological nature of both principal protagonists utterly ambiguous. The fluidity and ambiguity of Protean-‘you’ in ‘Almost You’ is discussed in terms of ‘second-person’ intersubjectivity, but with a view to demonstrating the indebtedness by the notion of intersubjectivity to Cartesianism's hegemony of ‘person’. I then turn to a discussion of what might be a more ‘old fashioned’ if perhaps ultimately more far-reaching approach to the ‘second person’s’ often startling ambiguities. This is Keats's notion of negative capability, a capacity or quality in which a person ‘is capable of being in uncertainties, Mysteries, doubts, without any irritable reaching after fact and reason.’ I suggest that Protean-‘you’ texts will license all of the readings of ambiguity and fluidity proposed in my discussion of ‘Almost You’, but conclude that the instances of indeterminacy illustrate no more than that: the fluidity and deep ambiguity, and thus, finally, the lack of coherence, of Protean-‘you’ discourse. This has particular implications for how we are to consider readers’ experiences of narrative texts. More fundamentally, it has implications for how we are to consider readers as subjects. I suggest that unstable, ambiguous instances of ‘second-person’ narrative can tear the complex and systematic embroidery of ideological suture that unifies Cretinism’s experience or sense of subjectivity, leaving the reader in a condition of epistemological and ontological havoc. I go on to argue that much of the deeply unsettling effect of Protean-‘you’ discourse anises because its utterances explicitly gesture towards Cretinism’s notion of self. Protean-‘you’ involves a sense of address that is much more pronounced than we are accustomed to facing when reading literary narrative, alerting us to the presence of inscribed anthropomorphic subjects. At the very same time, protean-‘you’ leaves its inscribed subjects indeterminate, ambiguous. This conflict generates a tension between the anticipation of the emergence of speaking and listening selves and our inability to find them. I go on to propose that Protean-‘you’ narrative's lack of coherence is also to be understood as the condition of narrative actuality generally, but a condition that is vigorously mediated against by dominant practices of reading and writing, hocusing my discussion in this respect on the issue of narrative ‘person,’ I argue that narrative ‘person’ is constituted within texts as an apparent unity, but that it is in fact, produced as unitary solely within the practice of making sense, that is, Within our habits of reading, and so is never finally unified. I propose that this is the case for ‘first-‘ and ‘third-person’ modes no less than for the ‘second.’ Where ‘second-person’ narrative at its most radical and Protean differs from conventional ‘first-‘ and ‘third-person’ narratives is the degree to which each has been circumscribed by practices of tantalization, containment and limit, and, in particular, Cretinism’s hegemony of ‘person.’ It may be that the most significant insights ‘second-person’ narrative has to offer are to be found within its capacity to reveal to the engaged reader the underlying condition of narrative discourse, and more generally, its capacity to reveal the actual condition of the human subject-a condition in which, exactly like its textual corollary of narrative ‘person,’ the self is glimpsed as thoroughly dispersed and contingent.

Sequential fixed-width confidence bands for kernel regression estimation

We consider a random design model based on independent and identically distributed (iid) pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths.

The sample size was optimized using the purely and two-stage sequential procedure together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confidence bands based on the local linear estimator have the best performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.

Sample size determination for kernel regression estimation using sequential fixed-width confidence bands

We consider a random design model based on independent and identically distributed pairs of observations (Xi, Yi), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting the aim is to produce a reasonable approximation to the unknown function m(x) when we have no precise information about the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given point by some appropriately constructed fixed-width (2d) confidence interval with the confidence coefficient of at least 1−. Here, d(> 0) and 2 (0, 1) are two preassigned values. Fixed-width confidence intervals are developed using both Nadaraya-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths. The sample size was optimized using the purely and two-stage sequential procedures together with asymptotic properties of the Nadaraya-Watson and local linear estimators. A large scale simulation study was performed to compare their coverage accuracy. The numerical results indicate that the confi dence bands based on the local linear estimator have the better performance than those constructed by using Nadaraya-Watson estimator. However both estimators are shown to have asymptotically correct coverage properties.