Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Analysis of the Respiratory Dynamics During Normal Breathing by Means of Pseudophase Plots and Pressure–Volume Loops

This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure-volume curves and the pseudophase-plane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

Innovation through virtual communities of Practice: motivation and constraints in the knowledge-creation process

Communities of Practice are places which provide a sound basis for organizational learning, enabling knowledge creation and acquisition thus improving organizational performance, leveraging innovation and consequently increasing competitively. Virtual Communities of Practice (VCoP‟s) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. The ongoing case study, described here, aims to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of the VCoP‟s to which they belong. Based on a literature review, we have identified several factors that influence such processes; they will be used to analyse the results of interviews carried out with the leaders of VCoP‟s in four multinationals. As future work, a questionnaire will be developed and administered to the other members of these VCoP‟s

Virtual communities of practice: investigating motivations and constraints in the processes of knowledge creation and transfer

With accelerated market volatility, faster response times and increased globalization, business environments are going through a major transformation and firms have intensified their search for strategies which can give them competitive advantage. This requires that companies continuously innovate, to think of new ideas that can be transformed or implemented as products, processes or services, generating value for the firm. Innovative solutions and processes are usually developed by a group of people, working together. A grouping of people that share and create new knowledge can be considered as a Community of Practice (CoP). CoP’s are places which provide a sound basis for organizational learning and encourage knowledge creation and acquisition. Virtual Communities of Practice (VCoP's) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. Nevertheless, it is known that not all CoP's and VCoP's share the same levels of performance or produce the same results. This means that there are factors that enable or constrain the process of knowledge creation. With this in mind, we developed a case study in order to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of VCoP's. Results show that organizational culture and professional and personal development play an important role in these processes. No interviewee referred to direct financial rewards as a motivation factor for participation in VCoPs. Most identified the difficulty in aligning objectives established by the management with justification for the time spent in the VCoP. The interviewees also said that technology is not a constraint.

Histogram-based DNA analysis for the visualization of chromosome, genome and species information

We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

Analysis of six fungicides and one acaricide in still and fortified wines using solid-phase microextraction-gas chromatography/tandem mass spectrometry

A multiresidue gas chromatographic method for the determination of six fungicides (captan, chlorthalonil, folpet, iprodione, procymidone and vinclozolin) and one acaricide (dicofol) in still and fortified wines was developed. Solid-phase microextraction (SPME) was chosen for the extraction of the compounds from the studied matrices and tandem mass spectrometry (MS/MS) detection was used. The extraction consists in a solvent free and automated procedure and the detection is highly sensitive and selective. Good linearity was obtained with correlation coefficients of regression (R2) > 0.99 for all the compounds. Satisfactory results of repeatability and intermediate precision were obtained for most of the analytes (RSD < 20%). Recoveries from spiked wine ranged from 80.1% to 112.0%. Limits of quantification (LOQs) were considerably below the proposedmaximumresidue limits (MRLs) for these compounds in grapes and below the suggested limits for wine (MRLs/10), with the exception of captan.

Biofiltration of Air/Styrene and Air/Styrene/Acetone mixtures in a bubble column reactor

The goal of this work was the treatment of polluted waste gases in a bubble column reactor (BCR), in order to determinate the maximum value of reactor’s efficiency (RE), varying the inlet concentration (C in) of the pollutants. The gaseous mixtures studied were: (i) air with styrene and (ii) air with styrene and acetone. The liquid phase used to contain the biomass in the reactor was a basal salt medium (BSM), fundamental for the microorganisms’ development. The reactor used in this project consists of a glass column of 620mm height and inside diameter 75mm. In all essays there were continually measured: pH, dissolved oxygen and liquid’s temperature. Temperature and pH were controlled (T=24ºC, 7.0 ≤ pH ≤ 7.7). In all experiments the liquid volume (including the biomass) used in the reactor was kept constant (1.5L) as well as the total gas flowrate (1 L/min). Concerning the goal of the work, some parameters were calculated: the organic load (OL), removal efficiency (RE), elimination capacity (EC), biomass concentration (xf) and dry biomass concentration (Xdw). In a first series of experiments, the gas mixture used was air with styrene, varying its concentration from 191 mg.m-3 to 6500 mg.m-3.It was concluded that the RE maximum value (97%) was obtained for C in Sty = 4200 mg.m-3. For the maximum tested value of C in Sty, RE obtained was 20%. In a second step, the gaseous mixture included acetone, varying C in Sty between 225 mg.m-3 and 2659 mg.m-3 and C in Ac between 153mg.m-3 and 1389 mg.m-3. The aim of these tests was the determination of C in Ac for which RE was maximum, obtaining C in Ac = 750 mg.m-3. A third series of experiments was performed, in which C in Ac was maintained equal to that value and C in Sty was varied until higher values (5422 mg.m-3). RE maximum values obtained in this last series were 100% for styrene and 40% for acetone. One important conclusion is the fact that the microorganisms available degrade better styrene than acetone. On the ambit of this study, it was possible to identify the species available in biomass: Xanthobacter antotrophicus py2, Enterobacter aerogenes, Nocardia, Corynebacterium Spp., Rhodococcus rhodochrous e Pseudomonas Sp.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

Virtual Communities of Practice: Design and Development of Support Platforms and Participation Fostering

Mestrado em Engenharia Informática - Área de Especialização em Sistemas Gráficos e Multimédia