Classi cation of new electricity customers based on surveys and smart metering data

This paper proposes a process for the classifi cation of new residential electricity customers. The current state of the art is extended by using a combination of smart metering and survey data and by using model-based feature selection for the classifi cation task. Firstly, the normalized representative consumption profi les of the population are derived through the clustering of data from households. Secondly, new customers are classifi ed using survey data and a limited amount of smart metering data. Thirdly, regression analysis and model-based feature selection results explain the importance of the variables and which are the drivers of diff erent consumption profi les, enabling the extraction of appropriate models. The results of a case study show that the use of survey data signi ficantly increases accuracy of the classifi cation task (up to 20%). Considering four consumption groups, more than half of the customers are correctly classifi ed with only one week of metering data, with more weeks the accuracy is signifi cantly improved. The use of model-based feature selection resulted in the use of a signifi cantly lower number of features allowing an easy interpretation of the derived models.

Classification of Smoking Cessation Status Using Various Data Mining Methods

AMS Subj. Classification: 62P10, 62H30, 68T01

Arbitration under the regulations on the guarantee of new residential buildings in Quebec

Dans ma mémoire, j’ai discuté les concepts d’arbitrage comme méthode de résolution d’un litige et par après, je donne un court historique de l’acceptation d’arbitrage au Québec. Le Chapitre I étudie la structure des règlements du R.B.Q., qui est un gendre d’arbitrage obligatoire institutionnelle, et j’inclus les diverses procédures dans ce système d’arbitrage. La sécurité offert par le plan de garantie règle par le R.B.Q. est discuté dans le Chapitre II en autant qu’il est relié avec le system d’arbitrage R.B.Q., y compris la structure du plan et le contenu de la sécurité. Chapitre III parle des recours disponible aux Bénéficiares ainsi que les avantages et désavantages de l’arbitrage sous les Règlements du R.B.Q. Un court étude comparative de quatre autres juridictions est recherché en Chapitre IV, incluant notre voisin, Ontario, les Etats-Unis et on croise dans les juridictions de Royaume Unie et Allemagne. En conclusion, j’établis que notre système d’arbitrage sous le Règlement protéges notre publique plus que d’autres juridictions. Je suggère des améliorations au système, par contre, incluant l’agrandissement du plan de garantie, l’ajout des pouvoirs donnés aux arbitres américains et ensuite d’intègré un système d’arrêt semblable aux Royaumes Unis.

Voltage unbalance reduction in low voltage feeders by dynamic switching of residential customers among three phases

Low voltage distribution feeders with large numbers of single phase residential loads experience severe current unbalance that often causes voltage unbalance problems. The addition of intermittent generation and new loads in the form of roof top photovoltaic generation and electric vehicles makes these problems even more acute. In this paper, an intelligent dynamic residential load transfer scheme is proposed. Residential loads can be transferred from one phase to another phase to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch with three-phase input and single-phase output connection. The main controller, installed at the transformer will observe the power consumption in each load and determine which house(s) should be transferred from one phase to another in order to keep the voltage unbalance in the feeder at a minimum. The efficacy of the proposed load transfer scheme is verified through MATLAB and PSCAD/EMTDC simulations.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Public awareness of ‘green’ residential property – an empirical survey based on data from New Zealand and Germany

Over the last few years more stringent environmental laws (e.g. the German “Energie¬ein-sparverordnung ENEV” - Energy Performance of Buildings Directive) and soaring energy prices has increased the need for the real estate industry to react and participate in overall energy reduction through efficient house construction and design, as well as upgrading the existing housing stock to be more energy efficient. Therefore the Property Economics Group at Queensland University of Technology in Australia and Nuertingen-Geislingen University in Germany are carrying out research in relation to sustainable housing construction and public awareness of “green” residential property. Part of this research is to gain an understanding of the level of knowledge and importance of these issues to the house buyer and to determine the importance of sustainable housing to the general public. The paper compares data from two different empirical studies; one of studies analyzes the situation in New Zealand, the other is focused on Germany.

Reversible cation/anion extraction from K2La2Ti3O10: Formation of new layered titanates, KLa2Ti3O9.5 and La2Ti3O9

A new soft-chemical transformation of layered perovskite oxides is described wherein K2O is sequentially extracted from the Ruddlesden-Popper (R-P) phase, K2La2Ti3O10 (I), yielding novel anion-deficient KLa2Ti3O9.5 (II) and La2Ti3O9 (III). The transformation occurs in topochemical reactions of the R-P phase I with PPh4Br and PBu4Br (Ph = phenyl; Bu = n-butyl). The mechanism involves the elimination of KBr accompanied by decomposition of PR4+ (R = phenyl or n-butyl) that extracts oxygen from the titanate. Analysis of the organic products of decomposition reveals formation of Ph3PO, Ph3P, and Ph-Ph for R = phenyl, and Bu3PO, Bu3P along with butane, butene, and octane for R = butyl. The inorganic oxides II and III crystallize in tetragonal structures (II: P4/mmm, a = 3.8335(1) angstrom, c = 14.334(1) angstrom; III: /4/ mmm, a = 3.8565(2) angstrom, c = 24.645(2) angstrom) that are related to the parent R-P phase. II is isotypic with the Dion-Jacobson phase, RbSr2Nb3O10, while III is a unique layered oxide consisting of charge-neutral La2Ti3O9 anion-deficient perovskite sheets stacked one over the other without interlayer cations. Interestingly, both II and III convert back to the parent R-P phase in a reaction with KNO3. While transformations of the R-P phases to other related layered/three-dimensional perovskite oxides in ion-exchange/metathesis/dehydration/reduction reactions are known, the simultaneous and reversible extraction of both cations and anions in the conversions K2La2Ti3O10 reversible arrow KLa2Ti3O9.5 reversible arrow La2Ti3O9 is reported here for the first time.

Synthesis and cation binding properties of new bile acid-based crown ethers

A series of bile acid-based crown ethers (7a-c,12 and 13) were easily constructed from readily available precursors. Measurement of association constants (K-a) with alkali metal picrates in CHCl3 showed that azacrown ethers 7a-c and Chola-Cuowns 12 and 13 show greater binding towards Rb+ and K+. The presence of the aromatic moieties showed subtle changes in the binding properties. Insight II minimized structures show very different conformations of aromatic units in 7a-b and 13.

Vehicle subtype, make and model classification from side profile video

This paper addresses the challenging domain of vehicle classification from pole-mounted roadway cameras, specifically from side-profile views. A new public vehicle dataset is made available consisting of over 10000 side profile images (86 make/model and 9 sub-type classes). 5 state-of-the-art classifiers are applied to the dataset, with the best achieving high classification rates of 98.7% for sub-type and 99.7- 99.9% for make and model recognition, confirming the assertion made that single vehicle side profile images can be used for robust classification.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.

Gender and identity classification for a naive and evolving system

[EN]This paper does not propose a new technique for face representationorclassification. Insteadtheworkdescribed here investigates the evolution of an automatic system which, based on a currently common framework, and starting from an empty memory, modifies its classifiers according to experience. In the experiments we reproduce up to a certain extent the process of successive meetings. The results achieved, even when the number of different individuals is still reduced compared to off-line classifiers, are promising.