Data mining and mall users profile

Marketing scholars have suggested a need for more empirical research on consumer response to malls, in order to have a better understanding of the variables that explain the behavior of the consumers. The segmentation methodology CHAID (Chi-square automatic interaction detection) was used in order to identify the profiles of consumers with regard to their activities at malls, on the basis of socio-demographic variables and behavioral variables (how and with whom they go to the malls). A sample of 790 subjects answered an online questionnaire. The CHAID analysis of the results was used to identify the profiles of consumers with regard to their activities at malls. In the set of variables analyzed the transport used in order to go shopping and the frequency of visits to centers are the main predictors of behavior in malls. The results provide guidelines for the development of effective strategies to attract consumers to malls and retain them there.

Biogeochemistry in acid sulphate soil landscapes and small urban centres in Western Finland

The overall purpose of this thesis was to increase the knowledge on the biogeochemistry of rural acid sulphate (AS) soil environments and urban forest ecosystems near small towns in Western Finland. In addition, the potential causal relationship between the distribution of AS soils and geographical occurence of multiple sclerosis (MS) disease was assessed based on a review of existing literature and data. Acid sulphate soils, which occupy an area of approximately 17–24 million hectare worldwide, are regarded as the nastiest soils in the world. Independent of the geographical locality of these soils, they pose a great threat to their surrounding environment if disturbed. The abundant metal-rich acid drainage from Finnish AS soils, which is a result of sulphide oxidation due to artificial farmland drainage, has significant but spatially and temporally variable ecotoxicological impacts on biodiversity and community structure of fish, benthic invertebrates and macrophytes. This has resulted in mass fish kills and even eradication of sensitive fish species in affected waters. Moreover, previous investigations demonstrated significantly enriched concentrations of Co, Ni, Mn and Al, metals which are abundantly mobilised in AS soils, in agricultural crops (timothy grass and oats) and approximately 50 times higher concentrations of Al in cow milk originating from AS soils in Western Finland. Nevertheless, the results presented here demonstrate, in general, relatively moderate metal concentrations in oats and cabbage grown on AS soils in Western Finland, although some of the studied fields showed anomalous values of metals (e.g. Co and Ni) in both the soil and target plants (especially oats), similar to that of the previous investigations. The results indicated that the concentrations of Co, Ni, Mn and Zn in oats and Co and Zn in cabbage were governed by soil geochemistry as these metals were correlated with corresponding concentrations extracted from the soil by NH4Ac-EDTA and NH4Ac, respectively. The concentrations of Cu and Fe in oats and cabbage were uncorrelated to that of the easily soluble concentrations in the soils, suggesting that biological processes (e.g. plant-root processes) overshadow geochemical variation. The concentrations of K and Mg in cabbage, which showed a low spread and were strongly correlated to the NH4Ac extractable contents in the soil, were governed by both the bioavailable fractions in the topsoil and plant-uptake mechanisms. The plant´s ability to regulate its uptake of Ca and P (e.g. through root exudates) seemed to be more important than the influence of soil geochemistry. The distribution of P, K, Ca, Mg, Mn and S within humus, moss and needles in and around small towns was to a high degree controlled by biological cycling, which was indicated by the low correlation coefficients for P, K, Ca, Mg and S between humus and moss, and the low spread of these nutrients in moss and needles. The concentration variations of elements in till are mainly due to natural processes (e.g. intrusions, weathering, mineralogical variations in the bedrock). There was a strong spatial pattern for B in humus, moss and needles, which was suggested to be associated with anthropogenic emissions from nearby town centres. Geogenic dust affected the spatial distribution of Fe and Cr in moss, while natural processes governed the Fe anomaly found in the needles. The spatial accumulation patterns of Zn, Cd, Cu, Ni and Pb in humus and moss were strong and diverse, and related to current industry, the former steel industry, coal combustion, and natural geochemical processes. An intriguing Cu anomaly was found in moss. Since it was located close to a main railway line and because the railway line´s electric cables are made of Cu, it was suggested that the reason for the Cu anomaly is corrosion of these cables. In Western Finland, where AS soils are particularly abundant and enrich the metal concentrations of stream waters, cow milk and to some extent crops, an environmental risk assessment would be motivated to elucidate if the metal dispersion affect human health. Within this context, a topic of concern is the distribution of multiple sclerosis as high MS prevalence rates are found in the main area of AS soils. Regionally, the AS soil type in the Seinäjoki area has been demonstrated to be very severe in terms of metal leaching, this area also shows one of the highest MS rates reported worldwide. On a local scale, these severe AS soil types coincide well with the corresponding MS clustering along the Kyrönjoki River in Seinäjoki. There are reasons to suspect that these spatial correlations are causal, as multiple sclerosis has been suggested to result from a combination of genetic and environmental factors.

Innovation in a Non-Formal Adult Education Organisation – Multi-Case Study in Four Adult Education Centres

More than ever, education organisations are experiencing the need to develop new services and processes to satisfy expanding and changing customer needs and to adapt to the environmental changes and continually tightening economic situation. Innovation has been found in many studies to have a crucial role in the success of an organisation, both in the private and public sectors, in formal education and in manufacturing and services alike. However, studies concerning innovation in non-formal adult education organisations, such as adult education centres (AECs) in Finland, are still lacking. This study investigates innovation in the non-formal adult education organisation context from the perspective of organisational culture types and social networks. The objective is to determine the significant characteristics of an innovative non-formal adult education organisation. The analysis is based on data from interviews with the principals and fulltime staff of four case AECs. Before the case study, a pre-study phase is accomplished in order to obtain a preliminary understanding of innovation at AECs. The research found strong support for the need of innovation in AECs. Innovation is basically needed to accomplish the AEC system’s primary mission mentioned in the ACT on Liberal Adult Education. In addition, innovation is regarded vital to institutes and may prevent their decline. It helps the institutes to be more attractive, to enter new market, to increase customer satisfaction and to be on the cutting edge. Innovation is also seen as a solution to the shortage of resources. Innovative AECs search actively for additional resources for development work through project funding and subsidies, cooperation networks and creating a conversational and joyful atmosphere in the institute. The findings also suggest that the culture type that supports innovation at AECs is multidimensional, with an emphasis on the clan and adhocratic culture types and such values as: dynamism, future orientation, acquiring new resources, mistake tolerance, openness, flexibility, customer orientation, a risk-taking attitude, and community spirit. Active and creative internal and external cooperation also promote innovation at AECs. This study also suggests that the behaviour of a principal is crucial. The way he or she shows appreciation the staff, encouragement and support to the staff and his or her approachability and concrete participation in innovation activities have a strong effect on innovation attitudes and activities in AECs.

BIOCHEMICAL GENETIC STUDIES ON THE OIL SARDINE, Sardinella longiceps (CUVIER AND VALENCIENNES, 1847) FROM SELECTED CENTRES OF THE WEST COAST OF INDIA

The main objective of the present investigation was to study the biochemical genetic variability within the species and genetic structure of its regional populations from west coast. Realising the recent report of occurrence of oil sardine fishery in east coast of India, population samples from Mandapam and Madras were also included in the present investigation. The original data gathered on the population genetics of the species have helped to interpret and evaluate the results objectively. The important conclusions drawn from a detailed discussions on the subject would throw some light on the probable process of problematic fluctuations in the abundance of oil sardine fishery of India. The academic and applied values of present discoveries need not be emphasised. The data used for the doctoral thesis were generated during the ICAR ad-hoc project on the "Population genetic studies on oil sardine, sardinella longiceps to identity distinct genetic stocks", carried out at CMFRI, Cochin during the years, 1988-1991

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Use of Online Information Resources for Knowledge Organisation in Library and Information Centres: A Case Study of CUSAT

The paper discusses the use of online information resources for organising knowledge in library and information centres in Cochin University of Science and Technology (CUSAT). The paper discusses the status and extent of automation in CUSAT library. The use of different online resources and the purposes for which these resources are being used, is explained in detail. Structured interview method was applied for collecting data. It was observed that 67 per cent users consult online resources for assisting knowledge organisation. Library of Congress catalogue is the widely used (100 per cent) online resource followed by OPAC of CUSAT and catalogue of British Library. The main purposes for using these resources are class number building and subject indexing

Compositional data analysis in archaeometry

We shall call an n × p data matrix fully-compositional if the rows sum to a constant, and sub-compositional if the variables are a subset of a fully-compositional data set1. Such data occur widely in archaeometry, where it is common to determine the chemical composition of ceramic, glass, metal or other artefacts using techniques such as neutron activation analysis (NAA), inductively coupled plasma spectroscopy (ICPS), X-ray fluorescence analysis (XRF) etc. Interest often centres on whether there are distinct chemical groups within the data and whether, for example, these can be associated with different origins or manufacturing technologies

Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering of compositional data in situations where observations are constituted by trajectories of compositional data, that is, by sequences of composition measurements along a domain. Observed trajectories are known as “functional data” and several methods have been proposed for their analysis. In particular, methods for clustering functional data, known as Functional Cluster Analysis (FCA), have been applied by practitioners and scientists in many fields. To our knowledge, FCA techniques have not been extended to cope with the problem of clustering compositional data trajectories. In order to extend FCA techniques to the analysis of compositional data, FCA clustering techniques have to be adapted by using a suitable compositional algebra. The present work centres on the following question: given a sample of compositional data trajectories, how can we formulate a segmentation procedure giving homogeneous classes? To address this problem we follow the steps described below. First of all we adapt the well-known spline smoothing techniques in order to cope with the smoothing of compositional data trajectories. In fact, an observed curve can be thought of as the sum of a smooth part plus some noise due to measurement errors. Spline smoothing techniques are used to isolate the smooth part of the trajectory: clustering algorithms are then applied to these smooth curves. The second step consists in building suitable metrics for measuring the dissimilarity between trajectories: we propose a metric that accounts for difference in both shape and level, and a metric accounting for differences in shape only. A simulation study is performed in order to evaluate the proposed methodologies, using both hierarchical and partitional clustering algorithm. The quality of the obtained results is assessed by means of several indices

Effect of the human papillomavirus (HPV) quadrivalent vaccine in a subgroup of women with cervical and vulvar disease: Retrospective pooled analysis of trial data

Objectives To determine the effect of human papillomavirus (HPV) quadrivalent vaccine on the risk of developing subsequent disease after an excisional procedure for cervical intraepithelial neoplasia or diagnosis of genital warts, vulvar intraepithelial neoplasia, or vaginal intraepithelial neoplasia. Design Retrospective analysis of data from two international, double blind, placebo controlled, randomised efficacy trials of quadrivalent HPV vaccine (protocol 013 (FUTURE I) and protocol 015 (FUTURE II)). Setting Primary care centres and university or hospital associated health centres in 24 countries and territories around the world. Participants Among 17 622 women aged 15–26 years who underwent 1:1 randomisation to vaccine or placebo, 2054 received cervical surgery or were diagnosed with genital warts, vulvar intraepithelial neoplasia, or vaginal intraepithelial neoplasia. Intervention Three doses of quadrivalent HPV vaccine or placebo at day 1, month 2, and month 6. Main outcome measures Incidence of HPV related disease from 60 days after treatment or diagnosis, expressed as the number of women with an end point per 100 person years at risk. Results A total of 587 vaccine and 763 placebo recipients underwent cervical surgery. The incidence of any subsequent HPV related disease was 6.6 and 12.2 in vaccine and placebo recipients respectively (46.2% reduction (95% confidence interval 22.5% to 63.2%) with vaccination). Vaccination was associated with a significant reduction in risk of any subsequent high grade disease of the cervix by 64.9% (20.1% to 86.3%). A total of 229 vaccine recipients and 475 placebo recipients were diagnosed with genital warts, vulvar intraepithelial neoplasia, or vaginal intraepithelial neoplasia, and the incidence of any subsequent HPV related disease was 20.1 and 31.0 in vaccine and placebo recipients respectively (35.2% reduction (13.8% to 51.8%)). Conclusions Previous vaccination with quadrivalent HPV vaccine among women who had surgical treatment for HPV related disease significantly reduced the incidence of subsequent HPV related disease, including high grade disease.

La superdotació als centres d'educació infantil i primària dels Serveis Territorials d'Educació de Girona: creences dels professionals de l'educació, mestres i Equips d'Assessorament i Orientació Psicopedagògica (EAP), sobre la detecció d'aquests alumnes i les mesures d'intervenció educativa

En aquesta tesi es fa una valoració dels elements que incideixen en les creences dels mestres d'educació infantil i primària i dels professionals dels EAP respecte la detecció dels alumnes amb altes capacitats i les principals mesures d'intervenció educativa. Els instruments utilitzats són els propis de les metodologies naturalistes i quasi experimentals. L'anàlisi de resultats obtinguts llarg de tres cursos escolars recull les creences dels mestres i EAP a partir de diferents fonts d'informació: entrevistes, descripció de casos, anàlisi de dades, valoració de normativa i dos qüestionaris, un per a mestres i l'altre per a EAP. Els resultats posen en evidència una molt baixa detecció, insuficiència de regulació legal, eines de diagnòstic febles, dispersió documental i falta de formació. Es detecten contradiccions entre les creences i les pràctiques. Finalment es proposa una redefinició del concepte Altes Capacitats-superdotació des dels àmbits de l'eficàcia, del perfil i del rendiment escolar.

Evaluation of the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data

Simulations of the top-of-atmosphere radiative-energy budget from the Met Office global numerical weather-prediction model are evaluated using new data from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat-8 satellite. Systematic discrepancies between the model simulations and GERB measurements greater than 20 Wm-2 in outgoing long-wave radiation (OLR) and greater than 60 Wm-2 in reflected short-wave radiation (RSR) are identified over the period April-September 2006 using 12 UTC data. Convective cloud over equatorial Africa is spatially less organized and less reflective than in the GERB data. This bias depends strongly on convective-cloud cover, which is highly sensitive to changes in the model convective parametrization. Underestimates in model OLR over the Gulf of Guinea coincide with unrealistic southerly cloud outflow from convective centres to the north. Large overestimates in model RSR over the subtropical ocean, greater than 50 Wm-2 at 12 UTC, are explained by unrealistic radiative properties of low-level cloud relating to overestimation of cloud liquid water compared with independent satellite measurements. The results of this analysis contribute to the development and improvement of parametrizations in the global forecast model.

Data dilemmas in forecasting European office market rents

This paper uses data provided by three major real estate advisory firms to investigate the level and pattern of variation in the measurement of historic real estate rental values for the main European office centres. The paper assesses the extent to which the data providing organizations agree on historic market performance in terms of returns, risk and timing and examines the relationship between market maturity and agreement. The analysis suggests that at the aggregate level and for many markets, there is substantial agreement on direction, quantity and timing of market change. However, there is substantial variability in the level of agreement among cities. The paper also assesses whether the different data sets produce different explanatory models and market forecast. It is concluded that, although disagreement on the direction of market change is high for many market, the different data sets often produce similar explanatory models and predict similar relative performance.

The management of positive inter-store externalities in shopping centres: some empirical evidence

In enclosed shopping centres, stores benefit from the positive externalities of other stores in the centre. Some stores provide greater benefits to their neighbours than others – for example anchor tenants and brand leading stores. In managing shopping centres, these positive externalities might be captured through rental variations. This paper explores the determinants of rent – including externalities – for UK regional shopping centres. Two linked databases were utilised in the research. One contains characteristics of 148 shopping centres; the other has some 1,930 individual tenant records including rent level. These data were analysed to provide information on the characteristics of centres and retailers that help determine rent. Factors influencing tenant rents include market potential factors derived from urban and regional economic theory and shopping centre characteristics identified in prior retail research. The model also includes variables that proxy for the interaction between tenants and the impact of positive in-centre externalities. We find that store size is significantly and negatively related to tenant with both anchor and other larger tenants, perhaps as a result of the positive effects generated by their presence, paying relatively lower rents while smaller stores, benefiting from the generation of demand, pay relatively higher rents. Brand leader tenants pay lower rents than other tenants within individual retail categories.

Tenant mix variety in regional shopping centres: some UK empirical analyses

The variety and quality of the tenant mix within a shopping centre is a key concern in shopping centre management. Tenant mix determines the extent of externalities between outlets in the centre, helps establish the image of the centre and, as a result, determines the attractiveness of the centre for consumers. This then translates into sales and rents. However, the management of tenant mix has largely been based on perceived “optimum” arrangements and industry rules of thumb. This paper attempts to model the impact of tenant mix on the rent paid by retailers in larger UK shopping centres and, hence, the returns made by shopping centre landlords. It extends work on shopping centre rent determination (see Working Paper 10/03) utilising a database of 148 regional shopping centres in the UK, with detailed data for over 1900 tenants. Econometric models test the relationship between rental levels and the levels of retail concentration and diversity, while controlling for a range of continuous and qualitative characteristics of each tenant, each retail product, and each shopping centre. Factor analysis is then used to extract the core retail and service categories from the tenant lists of the 148 shopping centres. The factor scores from these core retailer factors are then tested against rent payable. The results from the empirical analysis allow us to generate some clear analytical and empirical implications for optimal retail management.

Conditioning and preconditioning of the variational data assimilation problem

Numerical weather prediction (NWP) centres use numerical models of the atmospheric flow to forecast future weather states from an estimate of the current state. Variational data assimilation (VAR) is used commonly to determine an optimal state estimate that miminizes the errors between observations of the dynamical system and model predictions of the flow. The rate of convergence of the VAR scheme and the sensitivity of the solution to errors in the data are dependent on the condition number of the Hessian of the variational least-squares objective function. The traditional formulation of VAR is ill-conditioned and hence leads to slow convergence and an inaccurate solution. In practice, operational NWP centres precondition the system via a control variable transform to reduce the condition number of the Hessian. In this paper we investigate the conditioning of VAR for a single, periodic, spatially-distributed state variable. We present theoretical bounds on the condition number of the original and preconditioned Hessians and hence demonstrate the improvement produced by the preconditioning. We also investigate theoretically the effect of observation position and error variance on the preconditioned system and show that the problem becomes more ill-conditioned with increasingly dense and accurate observations. Finally, we confirm the theoretical results in an operational setting by giving experimental results from the Met Office variational system.