Leveraging social network data for analytical CRM strategies : the introduction of social BI

The skyrocketing trend for social media on the Internet greatly alters analytical Customer Relationship Management (CRM). Against this backdrop, the purpose of this paper is to advance the conceptual design of Business Intelligence (BI) systems with data identified from social networks. We develop an integrated social network data model, based on an in-depth analysis of Facebook. The data model can inform the design of data warehouses in order to offer new opportunities for CRM analyses, leading to a more consistent and richer picture of customers? characteristics, needs, wants, and demands. Four major contributions are offered. First, Social CRM and Social BI are introduced as emerging fields of research. Second, we develop a conceptual data model to identify and systematize the data available on online social networks. Third, based on the identified data, we design a multidimensional data model as an early contribution to the conceptual design of Social BI systems and demonstrate its application by developing management reports in a retail scenario. Fourth, intellectual challenges for advancing Social CRM and Social BI are discussed.

Semi-parametric forecasting of realized volatility

Forecasts generated by time series models traditionally place greater weight on more recent observations. This paper develops an alternative semi-parametric method for forecasting that does not rely on this convention and applies it to the problem of forecasting asset return volatility. In this approach, a forecast is a weighted average of historical volatility, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in volatility across time (as a measure of market conditions) by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are significantly more accurate than a number of competing approaches at both short and long forecast horizons.

Bi-objective bundle adjustment: towards large-scale visual sea-floor mapping with a minimal sensor suite

Visual sea-floor mapping is a rapidly growing application for Autonomous Underwater Vehicles (AUVs). AUVs are well-suited to the task as they remove humans from a potentially dangerous environment, can reach depths human divers cannot, and are capable of long-term operation in adverse conditions. The output of sea-floor maps generated by AUVs has a number of applications in scientific monitoring: from classifying coral in high biological value sites to surveying sea sponges to evaluate marine environment health.

Semi-parametric modelling of ultrafine particle number concentration

Quantifying spatial and/or temporal trends in environmental modelling data requires that measurements be taken at multiple sites. The number of sites and duration of measurement at each site must be balanced against costs of equipment and availability of trained staff. The split panel design comprises short measurement campaigns at multiple locations and continuous monitoring at reference sites [2]. Here we present a modelling approach for a spatio-temporal model of ultrafine particle number concentration (PNC) recorded according to a split panel design. The model describes the temporal trends and background levels at each site. The data were measured as part of the “Ultrafine Particles from Transport Emissions and Child Health” (UPTECH) project which aims to link air quality measurements, child health outcomes and a questionnaire on the child’s history and demographics. The UPTECH project involves measuring aerosol and particle counts and local meteorology at each of 25 primary schools for two weeks and at three long term monitoring stations, and health outcomes for a cohort of students at each school [3].

Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion

In most visual mapping applications suited to Autonomous Underwater Vehicles (AUVs), stereo visual odometry (VO) is rarely utilised as a pose estimator as imagery is typically of very low framerate due to energy conservation and data storage requirements. This adversely affects the robustness of a vision-based pose estimator and its ability to generate a smooth trajectory. This paper presents a novel VO pipeline for low-overlap imagery from an AUV that utilises constrained motion and integrates magnetometer data in a bi-objective bundle adjustment stage to achieve low-drift pose estimates over large trajectories. We analyse the performance of a standard stereo VO algorithm and compare the results to the modified vo algorithm. Results are demonstrated in a virtual environment in addition to low-overlap imagery gathered from an AUV. The modified VO algorithm shows significantly improved pose accuracy and performance over trajectories of more than 300m. In addition, dense 3D meshes generated from the visual odometry pipeline are presented as a qualitative output of the solution.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Re-melting of Bi-2212/Ag laminated tapes by partial melting process

Bi-2212 tapes are prepared by a combination of dip-coating and partial melt processing. We investigate the effect of re-melting of those tapes by partial melting followed by slow cooling on the structure and superconducting properties. Microstructural studies of re-melted samples show that they have the same overall composition as partially melted tapes. However, the fractional volumes of the secondary phases differ and the amounts and distribution of the secondary phases have a significant effect on the critical current. Critical current of Bi-2212/Ag tapes strongly depends on the maximum processing temperature. Initial J(c)'s of the tapes, which are partially melted, then slowly solidified at optimum conditions and finally post-annealed in an inert atmosphere, are up to 10.4 x 10(3) A/cm(2). It is found that the maximum processing temperature at initial partial melting has an influence on the optimum re-heat treatment conditions for the tapes. Re-melted tapes processed at optimum conditions recover superconducting properties after post-annealing in an inert atmosphere: the J(c) values of the tapes are about 80-110% of initial J(c)'s of those tapes.

Bi-2212/Ag laminated tapes: Bending and joining effects

Superconducting composite Bi-2212/Ag tapes and their joints are fabricated by a combination of dip-coating and partial melt processing. The heat treated tapes have a critical current (Ic) between 8 and 26A, depending on tape thickness and the number of Bi-2212 layers. Current transmissions between 80% and 100% have been achieved through the joints of tapes. Different types of HTS joints of Bi-2212/Ag laminated tapes are made and their transport properties during winding operations are investigated. Irreversible strain values (ε irrev) for laminated tapes and their joints are determined and it is found that the degradation of Ic during tape bending depends on the type of joint.

Superconducting joints of Bi-2212/Ag tapes and laminates

Different types of HTS joints of Bi-2212/Ag tapes and laminates, which are fabricated by dip-coating and partial-melt processes, have been investigated. All joints are prepared using green single and laminated tapes and according to the scheme: coating-joining-processing. The heat treated tapes have critical current (Ic) between 7 and 27 A, depending on tape thickness and the number of Bi-2212 ceramic layers in laminated tapes. It is found that the current transport properties of joints depend on the type of laminate, joint configuration and joint treatment, Ic losses in joints of Bi-2212 tapes and laminates are attributed to defects in their structure, such as pores, secondary phases and misalignment of Bi-2212 grains near the Ag edges. By optimizing joint configuration, current transmission up to 100% is achieved for both single tapes and laminated tapes.

Bi-2212/Ag tapes and laminates : effects of bending

Superconducting Bi-2212 tapes and laminates are fabricated by a combination of dip-coating and partial melt processing. The heat treated tapes have critical current densities (Jc) up to 11 kAcm -2. We investigate the degradation of critical current (Ic) during bending experiments for both single tapes and tapes with laminate structure. Although degradation of Ic is observed in both forms, the characteristics of the degradation differ. It is determined that laminated tapes perform better than single tapes when critical current is measured against bending radius, and laminated tapes tolerate a higher strain for a given reduction in critical current. It is found that increasing the number of Bi-2212 layers increases the total Ic of the laminated tape, but degradation of critical current is more pronounced during bending because of the increased total thickness of the laminate structure. It is also found that addition of silver to the Bi-2212 layers reduces critical current degradation during bending for both tapes and laminates.

Partial melt processing and electrical properties of Bi-Sr-Ca-Cu-o superconducting thick films on (100) MgO substrates

Superconducting thick films of Bi2Sr2CaCu2Oy (Bi-2212) on single-crystalline (100) MgO substrates have been prepared using a doctor-blade technique and a partial-melt process. It is found that the phase composition and the amount of Ag addition to the paste affect the structure and superconducting properties of the partially melted thick films. The optimum heat treatment schedule for obtaining high Jc has been determined for each paste. The heat treatment ensures attainment of high purity for the crystalline Bi-2212 phase and high orientation of Bi-2212 crystals, in which the c-axis is perpendicular to the substrate. The highest Tc, obtained by resistivity measurement, is 92.2 K. The best value for Jct (transport) of these thick films, measured at 77 K in self-field, is 8 × 10 3 Acm -2.

Reaction products between Bi-Sr-Ca-Cu-oxide thick films and alumina substrates

The structure and composition of reaction products between Bi-Sr-Ca-Cu-oxide (BSCCO) thick films and alumina substrates have been characterized using a combination of electron diffraction, scanning electron microscopy and energy dispersive X-ray spectrometry (EDX). Sr and Ca are found to be the most reactive cations with alumina. Sr4Al6O12SO4 is formed between the alumina substrates and BSCCO thick films prepared from paste with composition close to Bi-2212 (and Bi-2212 + 10 wt.% Ag). For paste with composition close to Bi(Pb)-2223 + 20 wt.% Ag, a new phase with f.c.c. structure, lattice parameter about a = 24.5 A and approximate composition Al3Sr2CaBi2CuOx has been identified in the interface region. Understanding and control of these reactions is essential for growth of high quality BSCCO thick films on alumina. (C) 1997 Elsevier Science S.A.

Microstructural investigation of Bi-Sr-Ca-Cu-oxide thick films on alumina substrates

The microstructure of Bi-Sr-Ca-Cu-oxide (BSCCO) thick films on alumina substrates has been characterized using a combination of X-ray diffractometry, scanning electron microscopy, transmission electron microscopy of sections across the film/substrate interface and energy-dispersive X-ray spectrometry. A reaction layer formed between the BSCCO films and the alumina substrates. This chemical interaction is largely responsible for off-stoichiometry of the films and is more significant after partial melting of the films. A new phase with fee structure, lattice parameter a = 2.45 nm and approximate composition Al3Sr2CaBi2CuOx has been identified as reaction product between BSCCO and Al2O3.