Frequency Domain Characterization Of Sliding Mode Control Of An Inverter Used In DSTATCOM Application

In this paper, the commonly used switching schemes for sliding mode control of power converters is analyzed and designed in the frequency domain. Particular application of a distribution static compensator (DSTATCOM) in voltage control mode is investigated in a power distribution system. Tsypkin's method and describing function is used to obtain the switching conditions for the two-level and three-level voltage source inverters. Magnitude conditions of carrier signals are developed for robust switching of the inverter under carrier-based modulation scheme of sliding mode control. The existence of border collision bifurcation is identified to avoid the complex switching states of the inverter. The load bus voltage of an unbalanced three-phase nonstiff radial distribution system is controlled using the proposed carrier-based design. The results are validated using PSCAD/EMTDC simulation studies and through a scaled laboratory model of DSTATCOM that is developed for experimental verification

Contribution of transmembrane domain V amino acids to β1l-adrenoceptor activity and affinity

Introduction. There are two binding sites on the β1-adrenoceptor (AR), β1H and β1L corresponding to high and low affinity binding sites respectively, which can be activated to cause cardiostimulation. Some β-blockers that block β1AR and β2ARs can activate β1LARs at higher concentrations than those required to cause blockade. The β2AR does not form a corresponding low affinity binding site and therefore we postulated that heterologous amino acids are responsible for the formation of β1LAR. Aim. To investigate whether heterologous amino acids of transmembrane domain V (TMDV) of β1AR and β2ARs contribute to β1LAR. Methods. β1ARs, β2ARs and mutant β1ARs containing all (β1(β2TMDV)AR) or single amino acids of TMDV of the β2AR were prepared and stably expressed in Chinese Hamster Ovary cells. Concentration-effect curves for cyclicAMP accumulation were carried out for (-)-CGP12177 in the absence or presence of (-)-bupranolol. Results. The potencies (pEC50) of (-)-CGP12177 were β2AR (9.24 ± 0.14, n = 5), β1(V230I)AR (9.07 ± 0.07, n = 10), β1(β2TMDV)AR (8.86 ± 0.10, n = 15), β1(R222Q)AR (8.09 ± 0.29, n = 6), β1AR (8.00 ± 0.11, n = 11). The affinities (pKB) of (-)-bupranolol were β2AR (9.82 ± 0.52, n = 5), β1(V230I)AR (7.64 ± 0.12, n = 8), β1(β2TMV)AR (8.06 ± 0.17, n = 8), β1(R222Q)AR (7.33 ± 0.23, n = 5), β1AR (7.23 ± 0.23, n = 5). Discussion. The potency of (-)-CGP12177 was higher at β2AR than at β1AR consistent with activation through a low affinity site at the β1AR (β1LAR). The presence of V230 in β1AR accounted for the lower potency of (-)-CGP 12177. The affinity of (-)-bupranolol was lower at β1AR compared to β2AR. The presence of V230 in β1AR accounted in part for the lower affinity. In conclusion TMDV of the β1AR contributes in part to the low affinity binding site of β1AR.

Contribution of transmembrane domain V amino acids to β1l-adrenoceptor activity and affinity

There are two binding sites on the β1-adrenoceptor (AR), β1H and β1L corresponding to high and low affinity binding sites respectively, which can be activated to cause cardiostimulation (reviewed Kaumann and Molenaar, 2008). Some β-blockers that block β1AR and β2ARs can activate β1LARs at higher concentrations than those required to cause blockade. The β2AR does not form a corresponding low affinity binding site (Baker et al 2002) and therefore we postulated that heterologous amino acids are responsible for the formation of β1LAR. Our aim was to investigate whether heterologous amino acids of transmembrane domain V (TMDV) of β1AR and β2ARs contribute to β1LAR. β1ARs, β2ARs and mutant β1ARs containing all (β1(β2TMDV)AR) or single amino acids of TMDV of the β2AR were prepared and stably expressed in Chinese Hamster Ovary cells. Concentration-effect curves for cyclicAMP accumulation were carried out for (-)-CGP12177 or (-)-isoprenaline in the absence or presence of (-)-bupranolol. _______________________________________________________________________ (-)-CGP 12177 (-)-Bupranolol affinity (pKB) pEC50 vs (-)-CGP 12177 vs (-)-isoprenaline _______________________________________________________________________ β1AR 8.00 ± 0.11 (11) 7.23 ± 0.23 (5) 9.52 ± 0.28 (5) β2AR (high density) 9.24 ± 0.14 (5) 9.82 ± 0.52 (8) xPaulxxxxxxx β2AR (low density) no effect β1(β2TMV)AR 8.86 ± 0.10 (15) 8.06 ± 0.17 (8) 9.08 ± 0.22 (6) β1(V230I)AR 9.07 ± 0.07 (10) 7.64 ± 0.12 (8) 9.36 ± 0.28 (9) β1(R222Q)AR 8.09 ± 0.29 (6) 7.33 ± 0.23 (5) 9.36 ± 0.08 (6) β1(V230A)AR 7.59 ± 0.09 (6) 7.32 ± 0.24 (4) 8.62 ± 0.18 (5) _______________________________________________________________________ The potency of (-)-CGP12177 was higher at β2AR than at β1AR consistent with activation through a low affinity site at the β1AR (β1LAR) but not β2AR. The presence of V230 in β1AR accounted for the lower potency of (-)-CGP 12177. The affinity of (-)-bupranolol at β1AR and mutants was higher when determined with (-)-isoprenaline than with (-)-CGP 12177. The affinity of (-)-bupranolol determined against (-)-CGP 12177 was lower at β1AR compared to β2AR. The presence of V230 in β1AR accounted in part for the lower affinity. In conclusion V230 of the β1AR contributes in part to the low affinity binding site of β1AR. Baker JG, Hall IP, Hill SJ (2002). Pharmacological characterization of CGP12177 at the human β2-adrenoceptor. Br J Pharmacol 137, 400−408 Kaumann AJ, Molenaar P (2008) The low-affinity site of the β1-adrenoceptor and its relevance to cardiovascular pharmacology. Pharmacol Ther 118, 303-336

Noise robust voice activity detection using normal probability testing and time-domain histogram analysis

This paper presents a method of voice activity detection (VAD) suitable for high noise scenarios, based on the fusion of two complementary systems. The first system uses a proposed non-Gaussianity score (NGS) feature based on normal probability testing. The second system employs a histogram distance score (HDS) feature that detects changes in the signal through conducting a template-based similarity measure between adjacent frames. The decision outputs by the two systems are then merged using an open-by-reconstruction fusion stage. Accuracy of the proposed method was compared to several baseline VAD methods on a database created using real recordings of a variety of high-noise environments.

Par4 is a coactivator for a splice isoform-specific transcriptional activation domain in WT1

The Wilms’ tumor suppressor protein WT1 is a transcriptional regulator involved in differentiation and the regulation of cell growth. WT1 is subject to alternative splicing, one isoform including a 17–amino acid region that is specific to mammals. The function of this 17–amino acid insertion is not clear, however. Here, we describe a transcriptional activation domain in WT1 that is specific to the WT1 splice isoform that contains the 17–amino acid insertion. We show that the function of this domain in transcriptional activation is dependent on a specific interaction with the prostate apoptosis response factor par4. A mutation in WT1 found in Wilms’ tumor disturbs the interaction with par4 and disrupts the function of the activation domain. Analysis of WT1 derivatives in cells treated to induce par4 expression showed a strong correlation between the transcription function of the WT1 17–amino acid insertion and the ability of WT1 to regulate cell survival and proliferation. Our results provide a molecular mechanism by which alternative splicing of WT1 can regulate cell growth in development and disease.

Noise robust voice activity detection using features extracted from the time-domain autocorrelation function

This paper presents a method of voice activity detection (VAD) for high noise scenarios, using a noise robust voiced speech detection feature. The developed method is based on the fusion of two systems. The first system utilises the maximum peak of the normalised time-domain autocorrelation function (MaxPeak). The second zone system uses a novel combination of cross-correlation and zero-crossing rate of the normalised autocorrelation to approximate a measure of signal pitch and periodicity (CrossCorr) that is hypothesised to be noise robust. The score outputs by the two systems are then merged using weighted sum fusion to create the proposed autocorrelation zero-crossing rate (AZR) VAD. Accuracy of AZR was compared to state of the art and standardised VAD methods and was shown to outperform the best performing system with an average relative improvement of 24.8% in half-total error rate (HTER) on the QUT-NOISE-TIMIT database created using real recordings from high-noise environments.

Mum, why are the potholes 8 feet apart? Repetitive wheel loads from heavy vehicles in the spatial domain

This paper presents the results of testing to determine pavement forces from three heavy vehicles (HVs). The HVs were instrumented to measure their wheel forces. A “novel roughness” value of the roads during testing is also derived. The various dynamic pavement forces are presented according to the range of novel roughness of pavement surfacings encountered during testing. The paper then examines the relationship between the two derived wavelengths predominant within the HV suspensions; those of axle hop and body-bounce. How these may be considered as contributing to spatial repetition of pavement forces from HVs is discussed. The paper concludes that pavement models need to be revised since dynamic forces from HVs in particular are not generally considered in current pavement design.

Robust suspicious behaviour detection for smart surveillance systems

Video surveillance technology, based on Closed Circuit Television (CCTV) cameras, is one of the fastest growing markets in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. To overcome this limitation, it is necessary to have “intelligent” processes which are able to highlight the salient data and filter out normal conditions that do not pose a threat to security. In order to create such intelligent systems, an understanding of human behaviour, specifically, suspicious behaviour is required. One of the challenges in achieving this is that human behaviour can only be understood correctly in the context in which it appears. Although context has been exploited in the general computer vision domain, it has not been widely used in the automatic suspicious behaviour detection domain. So, it is essential that context has to be formulated, stored and used by the system in order to understand human behaviour. Finally, since surveillance systems could be modeled as largescale data stream systems, it is difficult to have a complete knowledge base. In this case, the systems need to not only continuously update their knowledge but also be able to retrieve the extracted information which is related to the given context. To address these issues, a context-based approach for detecting suspicious behaviour is proposed. In this approach, contextual information is exploited in order to make a better detection. The proposed approach utilises a data stream clustering algorithm in order to discover the behaviour classes and their frequency of occurrences from the incoming behaviour instances. Contextual information is then used in addition to the above information to detect suspicious behaviour. The proposed approach is able to detect observed, unobserved and contextual suspicious behaviour. Two case studies using video feeds taken from CAVIAR dataset and Z-block building, Queensland University of Technology are presented in order to test the proposed approach. From these experiments, it is shown that by using information about context, the proposed system is able to make a more accurate detection, especially those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information give critical feedback to the system designers to refine the system. Finally, the proposed modified Clustream algorithm enables the system to both continuously update the system’s knowledge and to effectively retrieve the information learned in a given context. The outcomes from this research are: (a) A context-based framework for automatic detecting suspicious behaviour which can be used by an intelligent video surveillance in making decisions; (b) A modified Clustream data stream clustering algorithm which continuously updates the system knowledge and is able to retrieve contextually related information effectively; and (c) An update-describe approach which extends the capability of the existing human local motion features called interest points based features to the data stream environment.

Encyclopedia contributions : entries S-Z in Oxford Companion to Australian Gardens

Shelton, E.M. (p.548); Sherwood Arboretum (p.550); Soutter, William (pp.563-4); Styles (pp.575-6); Summer-House (579-580); Trapnell, W.G. (p.602); Tropical Gardens (pp.604-5);Verandah Gardening (p.614); Wickham Park (p.642); Wijaya, Made (p.642); Williams, George (p.644); Williams Keith A (p.644).

Feature-domain super-resolution for IRIS recognition

Uncooperative iris identification systems at a distance suffer from poor resolution of the captured iris images, which significantly degrades iris recognition performance. Superresolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, all existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values. This paper considers transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. This is the first paper to investigate the possibility of feature domain super-resolution for iris recognition, and experiments confirm the validity of the proposed approach.

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.