Edge detection is a projection

A desirable property of any edge detector is that it be a projection in the mathematical sense, that is, that when it is applied to its own output it produces no further change. This report examines the behaviour of some conventional and some new operators when applied to line-drawings. The Marr-Hildreth and some gradient operators are among the conventional operators examined. Also a class of energy feature detectors is explored. It is shown that the energy feature detector is a true projection and does not proliferate edges when applied to a line-drawing, whereas several of the conventional operators do.

Real solutions number of the switching angles in the selective harmonic eliminated PWM

With the purpose of solving the real solutions number of the nonlinear transcendental equations in the selective harmonic eliminated PWM (SHEPWM) technology, the nonlinear transcendental equations were transformed to a set of polynomial equations with a set of inequality constraints using the multiple-angle formulas, an analytic method based on semi-algebraic systems machine proving algorithm was proposed to classify the real solution number of the switching angles. The complete classifications of the real solution number and the analytic boundary point of the single phase and three phases SHEPWM inverter with switch points of N=3 and the single phase SHEPWM inverter with switch points of N=4 are obtained. The results indicate that the relationship between the modulation ratio and the real solution number can be demonstrated theoretically by this method, which has great implications for the solution procedure of switching angles and the improvement of harmonic elimination effects of the inverter.

Medial prefrontal cortex control of the paraventricular hypothalamic nucleus response to psychological stress : possible role of the bed nucleus of the stria terminalis

The medial prefrontal cortex (mPFC) has been strongly implicated in control of the paraventricular nucleus of the hypothalamus (PVN) response to stress. Because of the paucity of direct projections from the mPFC to the PVN, we sought to investigate possible brain regions that might act as a relay between the two during psychological stress. Bilateral ibotenic acid lesions of the rat mPFC enhanced the number of Fos-immunoreactive cells seen in the PVN after exposure to the psychological stressor, air puff. Altered neuronal recruitment was seen in only one of the candidate relay populations examined, the ventral bed nucleus of the stria terminalis (vBNST). Furthermore, bilateral ibotenic acid lesions of the BNST caused a significant attenuation of the PVN response to air puff. To better characterize the structural relationships between the mPFC and PVN, retrograde tracing studies were conducted examining Fos expression in cells retrogradely labeled with cholera toxin b subunit (CTb) from the PVN and the BNST. Results obtained were consistent with an important role for both the mPFC and BNST in the mpPVN CRF cell response to air puff. We suggest a set of connections whereby a direct PVN projection from the ipsilateral vBNST is involved in the mpPVN response to air puff and this may, in turn, be modulated by an indirect projection from the mPFC to the BNST.

Exploiting side information in locality preserving projection

Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the data's local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance.

Ridge regression for two dimensional locality preserving projection

Two Dimensional Locality Preserving Projection (2D-LPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, 2D-PCA and LPP. However, the computational cost of 2D-LPP is high. This paper proposes a novel algorithm called Ridge Regression for Two Dimensional Locality Preserving Projection (RR- 2DLPP), which is an extension of 2D-LPP with the use of ridge regression. RR-2DLPP is comparable to 2DLPP in performance whilst having a lower computational cost. The experimental results on three benchmark face data sets - the ORL, Yale and FERET databases - demonstrate the effectiveness and efficiency of RR-2DLPP compared with other face recognition algorithms such as PCA, LPP, SR, 2D-PCA and 2D-LPP.

Dance therapy collections : number three

This collection of articles by keynote speakers, Australian and overseas practitioners, developed out of presentations at the third Australian Dance Movement Therapy conference, ‘Weaving The Threads’, held in Melbourne in 2007. This volume includes 22 articles from Australian and international dance movement therapists and colleagues on a wide range of topics, from dance therapy's origins and directions, research and evaluation in dance-movement therapy to therapeutic applications and skill development for therapists.

Number plate survey methodology for long-distance traffic flows

The lack of comprehensive data on transport operations is a long- standing problem in transport research. Information on road transport in particular has proved difficult to obtain. This Paper documents a study which was aimed at developing and testing a technique to estimate long-distance passenger and freight movements based on direct observation of vehicle movements.

The number of years lived with obesity and the risk of all-cause and cause-specific mortality

Background The role of the duration of obesity as an independent risk factor for mortality has not been investigated. The aim of this study was to analyse the association between the duration of obesity and the risk of mortality.

Methods A total of 5036 participants (aged 28–62 years) of the Framingham Cohort Study were followed up every 2 years from 1948 for up to 48 years. The association between obesity duration and all-cause and cause-specific mortality was analysed using time-dependent Cox models adjusted for body mass index. The role of biological intermediates and chronic diseases was also explored.

Results The adjusted hazard ratio (HR) for mortality increased as the number of years lived with obesity increased. For those who were obese for 1–4.9, 5–14.9, 15–24.9 and ≥25 years of the study follow-up period, adjusted HRs for all-cause mortality were 1.51 [95% confidence interval (CI) 1.27–1.79], 1.94 (95% CI 1.71–2.20), 2.25 (95% CI 1.89–2.67) and 2.52 (95% CI 2.08–3.06), respectively, compared with those who were never obese. A dose–response relation between years of duration of obesity was also clear for all-cause, cardiovascular, cancer and other-cause mortality. For every additional 2 years of obesity, the HRs for all-cause, cardiovascular disease, cancer and other-cause mortality were 1.06 (95% CI 1.05–1.07), 1.07 (95% CI 1.05–1.08), 1.03 (95% CI 1.01–1.05) and 1.07 (95% CI 1.05–1.11), respectively.

Conclusions The number of years lived with obesity is directly associated with the risk of mortality. This needs to be taken into account when estimating its burden on mortality.

Copy number variation and transposable elements feature in recent, ongoing adaptation at the Cyp6g1 locus

The increased transcription of the Cyp6g1 gene of Drosophila melanogaster, and consequent resistance to insecticides such as DDT, is a widely cited example of adaptation mediated by cis-regulatory change. A fragment of an Accord transposable element inserted upstream of the Cyp6g1 gene is causally associated with resistance and has spread to high frequencies in populations around the world since the 1940s. Here we report the existence of a natural allelic series at this locus of D. melanogaster, involving copy number variation of Cyp6g1, and two additional transposable element insertions (a P and an HMS-Beagle). We provide evidence that this genetic variation underpins phenotypic variation, as the more derived the allele, the greater the level of DDT resistance. Tracking the spatial and temporal patterns of allele frequency changes indicates that the multiple steps of the allelic series are adaptive. Further, a DDT association study shows that the most resistant allele, Cyp6g1-[BP], is greatly enriched in the top 5% of the phenotypic distribution and accounts for ~16% of the underlying phenotypic variation in resistance to DDT. In contrast, copy number variation for another candidate resistance gene, Cyp12d1, is not associated with resistance. Thus the Cyp6g1 locus is a major contributor to DDT resistance in field populations, and evolution at this locus features multiple adaptive steps occurring in rapid succession.

An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for
developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be
incorporated into a computerized system and, at the same time, to
preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking
process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first
employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed
approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.

Visualizing and classifying data using a hybrid intelligent system

In this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) neural network, kMER (kernel-based Maximum Entropy learning Rule), and Probabilistic Neural Network (PNN) for data visualization and classification is proposed. The rationales of this Probabilistic SOM-kMER model are explained, and its applicability is demonstrated using two benchmark data sets. The results are analyzed and compared with those from a number of existing methods. Implication of the proposed hybrid system as a useful and usable data visualization and classification tool is discussed.