Heart rate variability characterization using a time-frequency based instantaneous frequency estimation technique

In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponen signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain of the signal. These features comprise the IF, the instantaneous bandwidth (IB) and instantaneous energy (IE) of the different TF components of the HRV. Applied to the HRV of both normal and seizure suffering newborns, this method clearly reveals the locations of the spectral peaks and their time-varying nature. The total energy of HRV components, ET and ratio of energy concentrated in the low-frequency (LF) to that in high frequency (HF) components have been shown to be significant features in identifying the HRV of newborn with seizures.

Finding negative event oriented patterns in long temporal sequences

Pattern discovery in a long temporal event sequence is of great importance in many application domains. Most of the previous work focuses on identifying positive associations among time stamped event types. In this paper, we introduce the problem of defining and discovering negative associations that, as positive rules, may also serve as a source of knowledge discovery. In general, an event-oriented pattern is a pattern that associates with a selected type of event, called a target event. As a counter-part of previous research, we identify patterns that have a negative relationship with the target events. A set of criteria is defined to evaluate the interestingness of patterns associated with such negative relationships. In the process of counting the frequency of a pattern, we propose a new approach, called unique minimal occurrence, which guarantees that the Apriori property holds for all patterns in a long sequence. Based on the interestingness measures, algorithms are proposed to discover potentially interesting patterns for this negative rule problem. Finally, the experiment is made for a real application.

Origins and early development of human body knowledge

As a knowable object, the human body is highly complex. Evidence from several converging lines of research, including psychological studies, neuroimaging and clinical neuropsychology, indicates that human body knowledge is widely distributed in the adult brain, and is instantiated in at least three partially independent levels of representation. Sensori-motor body knowledge is responsible for on-line control and movement of one's own body and may also contribute to the perception of others' moving bodies; visuo-spatial body knowledge specifies detailed structural descriptions of the spatial attributes of the human body; and lexical-semantic body knowledge contains language-based knowledge about the human body. In the first chapter of this Monograph, we outline the evidence for these three hypothesized levels of human body knowledge, then review relevant literature on infants' and young children's human body knowledge in terms of the three-level framework. In Chapters II and III, we report two complimentary series of studies that specifically investigate the emergence of visuospatial body knowledge in infancy. Our technique is to compare infants' responses to typical and scrambled human bodies, in order to evaluate when and how infants acquire knowledge about the canonical spatial layout of the human body. Data from a series of visual habituation studies indicate that infants first discriminate scrambled from typical human body pictures at 15 to 18 months of age. Data from object examination studies similarly indicate that infants are sensitive to violations of three-dimensional human body stimuli starting at 15-18 months of age. The overall pattern of data supports several conclusions about the early development of human body knowledge: (a) detailed visuo-spatial knowledge about the human body is first evident in the second year of life, (b) visuo-spatial knowledge of human faces and human bodies are at least partially independent in infancy and (c) infants' initial visuo-spatial human body representations appear to be highly schematic, becoming more detailed and specific with development. In the final chapter, we explore these conclusions and discuss how levels of body knowledge may interact in early development.

The identification and characterisation of alleles of sucrose phosphate synthase gene family III in sugarcane

Little is known about the extent of allelic diversity of genes in the complex polyploid, sugarcane. Using sucrose phosphate synthase (SPS) Gene (SPS) Family III as an example, we have amplified and sequenced a 400 nt region from this gene from two sugarcane lines that are parents of a mapping population. Ten single nucleotide polymorphisms (SNPs) were identified within the 400 nt region of which seven were present in both lines. In the elite commercial cultivar Q165(A), 10 sequence haplotypes were identified, with four haplotypes recovered at 9% or greater frequency. Based on SNP presence, two clusters of haplotypes were observed. In IJ76-514, a Saccharum officinarum accession, 8 haplotypes were identified with 4 haplotypes recovered at 13% or greater frequency. Again, two clusters of haplotypes were observed. The results suggest that there may be two SPS Gene Family III genes per genome in sugarcane, each with different numbers of different alleles. This suggestion is supported by sequencing results in an elite parental sorghum line, 403463-2-1, in which 4 haplotypes, corresponding to two broad types, were also identified. Primers were designed to the sugarcane SNPs and screened over bulked DNA from high and low Sucrose-containing progeny from a cross between Q165(A) and IJ76-514. The SNP frequency did not vary in the two bulked DNA samples, suggesting that these SNPs from this SPS gene family are not associated with variation in sucrose content. Using an ecotilling approach, two of the SPS Gene Family III haplotypes were mapped to two different linkage groups in homology group 1 in Q165(A). Both haplotypes mapped near QTLs for increased sucrose content but were not themselves associated with any sugar-related trait.

Issues in boys' education: A question of teacher threshold knowledges?

This paper explores the effects of specific teacher threshold knowledges about boys and gender on the implementation of a so-called 'boy friendly' curriculum at one junior secondary high school in Australia. Through semi-structured inter-views with selected staff at the school, it examines the normalizing assumptions and 'truth claims' about boys, as gendered subjects, which drive the pedagogical impetus for such a curriculum initiative. This research raises crucial questions about the need for the formulation of both school and governmental policy grounded in sound research-based knowledge about the social construction of gender and its impact on the lives of both boys and girls and their experiences of schooling. This is crucial, we argue, in light of the recent parliamentary report on boys' education in Australia which rejects gender theorizing and given the failure of key staff in the research school to interrogate the binary ways in which masculinity and femininity are socially constructed and institutionalized in schools through a particular 'gender regime'. While some good things are happening in the research school, the failure to acknowledge the social construction of gender means that ultimately the school's programs cannot be successful.

Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping

The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in an unsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage. The algorithms used are statistical, but they employ nonlinear dynamics and machine learning. This article is an attempt to validate the output of Leximancer, using a set of evaluation criteria taken from content analysis that are appropriate for knowledge discovery tasks.

Load profiling and data mining techniques in electricity deregulated market

This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.