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.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Effects of memory load and distraction on performance and event-related slow potentials in a visuospatial working memory task

Brain electrical activity related to working memory was recorded at 15 scalp electrodes during a visuospatial delayed response task. Participants (N = 18) touched the remembered position of a target on a computer screen after either a 1 or 8 sec delay. These memory trials were compared to sensory trials in which the target remained present throughout the delay and response periods. Distracter stimuli identical to the target were briefly presented during the delay on 30% of trials. Responses were less accurate in memory than sensory trials, especially after the long delay. During the delay slow potentials developed that were significantly more negative in memory than sensory trials. The difference between memory and sensory trials was greater at anterior than posterior electrodes. On trials with distracters, the slow potentials generated by memory trials showed further enhancement of negativity whereas there were minimal effects on accuracy of performance. The results provide evidence that engagement of visuospatial working memory generates slow wave negativity with a timing and distribution consistent with frontal activation. Enhanced brain activity associated with working memory is required to maintain performance in the presence of distraction. © 1997 by the Massachusetts Institute of Technology

Effect of load distance on self-selected manual lifting technique

The aim of this research is to determine the effects of constraining the horizontal distance of the feet from the load on the posture adopted at the start of the lift. Kinematic data were collected while each of 24 subjects lifted 3, 6, and 9 kg loads from a starting height 18 cm above the ground. The position of the feet was controlled relative to the load such that the horizontal distance from the hand to the ankle at the start of extension was either 20, 40, or 60 cm. Subjects performed 20 trials in each of six combinations of load and ankle-load distance chosen to provide three sets of equivilent load moment pairs. The initial horizontal distance from the load to the ankle had a large influence on the posture adopted to lift the load. Ankle and knee flexion, in particular, were reduced when the ankle-load distance was smaller, and particularly so when the distance was reduced to 20 cm. Hip flexion was reduced to a smaller extent, while lumbar vertebral flexion remained relatively unchanged. The inclination of the trunk at the start of the lift was unchanged when the ankle-load distance was 60 or 40 cm, but was 10 degrees greater when the load was 20 cm from the ankles, indicating that subjects adopted a posture closer to a stoop when the ankle-load distance was small. Comparison of conditions of equal load moment (but different load mass and ankle-load distance) revealed differences which mirrored the effects of ankle-load distance alone, suggesting that the effects of ankle-load distance on the posture adopted at the start of extension were largely independent of the load moment. While the forces and torques required to lift a load must be to some extent dependent on the load moment, rather than load or ankle-load distance per se, the posture adopted to lift the load is not.

Effects of egg load on the host-selection behaviour of Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

We examined the effect of age-specific fecundity, mated status, and egg load on host-plant selection, by Helicoverpa armigera under laboratory conditions. The physiological state of a female moth (number of mature eggs produced) greatly influences her host-plant specificity and propensity to oviposit (oviposition motivation). Female moths were less discriminating against cowpea (a low-ranked host) relative to maize (a high-ranked host) as egg load increased. Similarly, increased egg load led to a greater propensity to oviposit on both cowpea and maize. Distribution of oviposition with age of mated females peaked shortly after mating and declined steadily thereafter until death. Most mated females (88%) carried only a single spermatophore, a few females (12%) contained two. The significance of these findings in relation to host-plant selection by H. armigera, and its management, are discussed.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Asymptomatic primary Epstein-Barr virus infection occurs in the absence of blood T-cell repertoire perturbations despite high levels of systemic viral load

Primary infection with the human herpesvirus, Epstein-Barr virus (EBV), may result in subclinical seroconversion or may appear as infectious mononucleosis (IM), a lymphoproliferative disease of variable severity. Why primary infection manifests differently between patients is unknown, and, given the difficulties in identifying donors undergoing silent seroconversion, little information has been reported. However, a longstanding assumption has been held that IM represents an exaggerated form of the virologic and immunologic events of asymptomatic infection. T-cell receptor (TCR) repertoires of a unique cohort of subclinically infected patients undergoing silent infection were studied, and the results highlight a fundamental difference between the 2 forms of infection. In contrast to the massive T-cell expansions mobilized during the acute symptomatic phase of IM, asymptomatic donors largely maintain homeostatic T-cell control and peripheral blood repertoire diversity. This disparity cannot simply be linked to severity or spread of the infection because high levels of EBV DNA were found in the blood from both types of acute infection. The results suggest that large expansions of T cells within the blood during IM may not always be associated with the control of primary EBV infection and that they may represent an overreaction that exacerbates disease. (C) 2001 by The American Society of Hematology.

Proteomics of breast cancer for marker discovery and signal pathway profiling

Breast cancer is the most common form of cancer among women and the identification of markers to discriminate tumorigenic from normal cells, as well as the different stages of this pathology, is of critical importance. Two-dimensional electrophoresis has been used before for studying breast cancer, but the progressive completion of human genomic sequencing and the introduction of mass spectrometry, combined with advanced bioinformatics for protein identification, have considerably increased the possibilities for characterizing new markers and therapeutic targets. Breast cancer proteomics has already identified markers of potential clinical interest (such as the molecular chaperone 14-3-3 sigma) and technological innovations such as large scale and high throughput analysis are now driving the field. Methods in functional proteomics have also been developed to study the intracellular signaling pathways that underlie the development of breast cancer. As illustrated with fibroblast growth factor-2, a mitogen and motogen factor for breast cancer cells, proteomics is a powerful approach to identify signaling proteins and to decipher the complex signaling circuitry involved in tumor growth. Together with genomics, proteomics is well on the way to molecularly characterizing the different types of breast tumor, and thus defining new therapeutic targets for future treatment.

A portable load cell for in-situ ore impact breakage testing

This paper discusses the design and characterisation of a short, and hence portable impact load cell for in-situ quantification of ore breakage properties under impact loading conditions. Much literature has been published in the past two decades about impact load cells for ore breakage testing. It has been conclusively shown that such machines yield significant quantitative energy-fragmentation information about industrial ores. However, documented load cells are all laboratory systems that are not adapted for in-situ testing due to their dimensions and operating requirements. The authors report on a new portable impact load cell designed specifically for in-situ testing. The load cell is 1.5 m in height and weighs 30 kg. Its physical and operating characteristics are detailed in the paper. This includes physical dimensions, calibration and signal deconvolution. Emphasis is placed on the deconvolution issue, which is significant for such a short load cell. Finally, it is conclusively shown that the short load cell is quantitatively as accurate as its larger laboratory analogues. (C) 2062 Elsevier Science B.V. All rights reserved.

Profiling the Senior Traveler: An Australia Perspective

Recently, the behavior of senior travelers has become an important area of interest because of its market size and potential for growth. This study describes a study profiling senior travelers according to their demographic and psychographic characteristics. Six market segments were used to highlight the differences that exist in terms of holiday attractions, travel motivations, and information sources used among senior travelers when planning and choosing a holiday. Seniors are shown not to be a uniform conservative market, which has implications for marketing and product development.

Simulation of the load-unload response ratio and critical sensitivity in the lattice solid model

The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.

Load-unload response ratio and accelerating moment/energy release critical region scaling and earthquake prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.