Signal Extraction from the Components of the Philippine National Accounts Statistics Using ARIMA Model-Based Methodology

The state-of-the-art in signal extraction gradually evolved from the use of mechanical form of moving average filters to the present sophisticated model-based techniques capable of performing automatic modeling and signal extraction involving hundreds or even thousands of time series in one production run. The leading edge of technology is being shared by two ARIMA model-based systems – ARIMA X12 of the US Bureau of Census and the twin programs TRAMO-SEATS developed at the Bank of Spain. These specialized expert systems have been adopted by most statistical agencies of advanced OECD countries and the European community. The Philippines on the other hand is still using the ARIMA X11 system modified by the Bank of Canada in its routine seasonal adjustment and time series decomposition tasks. This study is an attempt to implement the ARIMA model-based (AMB) approach of extracting unobserved signals from 194 quarterly national accounts statistics of the Philippines using the TRAMO-SEATS system in a fully automatic modeling mode. The successful result of the application adequately demonstrates the feasibility of adopting a system being used routinely by countries in more advanced economies

Nowcasting Philippine Economic Growth using MIDAS Regression Modeling

Among the most anticipated data releases of the Philippine statistical system is the quarterly real gross domestic product. This all-important variable provides the basis for deriving the economic growth performance of the country on a year-on-year basis. Official publication of this statistics, however, comes at a significant delay of up to two months, upsetting the planning function of various economic stakeholders. Under this backdrop, data scientists coined the term “nowcasting,” which refers to the prediction of the present, the very near future, and the very recent past, based on information provided by available data that are sampled at higher frequencies (monthly, weekly, daily, etc.). Nowcasting, however, opens up the “mixed frequency” problem in forecasting, which is the data frequency asymmetry between the dependent and independent variables of regression models that will be used in forecasting. The central objective of this study is to demonstrate the viability of using a state-of-the-art technique called MIDAS (Mixed Data Sampling) Regression to solve the mixed frequency problem in implementing the “nowcasting” of the country’s economic growth. Different variants of the MIDAS model are estimated using quarterly Real GDP data and monthly data Inflation, Industrial Production, and Philippine Stock Exchange Index. These models are empirically compared against each other and against the models traditionally used by forecasters in the context of mixed frequency. The results indicate the feasibility of adopting the MIDAS framework in accurately predicting future growth of the economy using information from high-frequency economic indicators. Certain MIDAS models considered in the study performed better than traditional forecasting models in both in-sample and out-of-sample forecasting performance

Towards precise recognition of pollen bearing bees by convolutional neural networks

Automatic recognition of pollen bearing bees can provide important information both for pollination monitoring and for assessing the health and strength of bee colonies, with the consequent impact on people's lives, due to the role of bees in the pollination of many plant species. In this paper, we analyse some of the Convolutional Neural Networks (CNN) methods for detection of pollen bearing bees in images obtained at hive entrance. In order to show the in uence of colour we preprocessed the dataset images. Studying the results of nine state-of-the-art CNNs, we provide a baseline for pollen bearing bees recognition based in deep learning. For some CNNs the best results were achieved with the original images. However, our experiments showed evidence that DarkNet53 and VGG16 have superior performance against the other CNNs tested, with unsharp masking preprocessed images, achieving accuracy results of 99:1% and 98:6%, respectively.info:eu-repo/semantics/publishedVersio

Workshop report: Farm-household modelling with a focus on food security, climate change adaptation, risk management and mitigation: a way forward

Related working paper at http://hdl.handle.net/10568/21112The workshop entitled: ‘Farm-household modelling with a focus on food security, climate change adaptation, risk management and mitigation: a way forward’ focused on identifying the current strengths and weaknesses of farm and household-level models, and laying out practical pathways to improve these models. This activity followed a recent review on farm household modelling commissioned by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). The workshop took place in Amsterdam, The Netherlands on 23–25 April 2012. The most important conclusions of the workshop were: 1. It is possible to analyse household-level questions related to climate change in a reasonable short (6 months to 1 year) time span with existing tools and the expertise present in the group of participants. 2. Availability of component tools can be an issue; the tools are there but free usability of code and parameters is not always possible. 3. Activities to develop repositories of models and data are urgently needed to increase further development of household models and make better use of existing knowledge. A set of activities will be developed to move the work forward in three CCAFS target regions (West Africa, East Africa and South Asia). The expectation is that the workshop will serve as a springboard for a multi-year initiative that will eventually involve a wide range of participants both within and outside the CGIAR. The challenges associated with climate change, agriculture and food security are considerable, and household modelling has a key role to play in designing and evaluating adaptation, risk management and mitigation options that can help lead to the positive outcomes that CCAFS and research-for-development partners are seeking

Using analog ensembles with alternative metrics for hindcasting with multistations

This study concerns making weather predictions for a location where no data is available, using meteorological datasets from nearby stations. The hindcast with multiple stations is performed with different variants of the Analog Ensemble (AnEn) method. In addition to the traditional Monache metric used to identify analogs in datasets from one or two stations, several new metrics are explored, namely cosine similarity, normalization, and k-means clustering. These were analyzed and benchmarked to find the ones that bring improvements. The best results were obtained with the k-means metric, yielding between 3% and 30% of lower quadratic error when compared against the Monache metric. Also, by making the predictors to include two stations, the performance of the hindcast improved, decreasing the error up to 16%, depending on the correlation between the predictor stations.info:eu-repo/semantics/publishedVersio

Regional and temporal changes in bivalve diversity off the south coast of Portugal

12 pages, 8 figures.-- Printed version published Dec 10, 2008.From 2000 to 2006, a total of 75 bivalve species were identified, varying from 29 (spring 2001) to 54 species (spring 2005) per year. Seasonal tendencies in diversity varied according the year, thus the interpretation of long-term and regional scales is essential before drawing any conclusions in other studies. Richness and diversity consistently decreased with depth and increased with sediment grain size (from low in very coarse sand to high in coarse silt). Diversity decreased progressively from 3 to 16 m depth, thus the harsher shallower environments (due to waves and tidal air exposure) showed greater diversity than the most stable areas. Communities in finer sediments were more diverse than those in coarser sand. Evenness showed patterns opposite to diversity, overall.Diversity and evenness maps (produced with multivariate universal kriging), showed that most geographic areas with greater diversity were farer from river outflows and wastewater treatment plants. Two types of geographic pattern were observed: areas with persistently greater bivalve diversity through time and areas that changed locally from year to year. This spatial analysis can be used to establish priority conservation areas for management purposes, and to analyse the persistency of regional diversity patterns. The area with most habitat heterogeneity (Sotavento) corresponded to greatest diversity.There was a positive relationship between Spisula solida and Chamelea gallina landings and bivalve diversity 2 years and 1 year later, respectively. Possibly, local fisheries, by selectively withdrawing the commercial numerically dominant species from the ecosystem, increased diversity 1 to 2 years later, as the ecological niches of the dominants are quickly filled by several other species thereby creating a more even community. On regional scales, no significant impact was found on long-term bivalve diversity in local fisheries.This work was part of an MMR Post-doc program financed by Fundação para a Ciência e a Tecnologia BPD /14935/ 2004.Peer reviewe

Avaliação da viabilidade do pólen e receptvidade do estigma de genitores do Programa de Hibridação do Amendoim Forrageiro.

Este trabalho teve como objetivo estabelecer um meio de cultura e temperatura de incubação adequados para a germinação in vitro de grãos de pólen de Arachis pintoi, bem como determinar a condição térmica de armazenamento dos mesmos para prolongar sua viabilidade. Para a germinação in vitro dos pólens, foram testadas diferentes concentrações de H3BO3 (0,25, 50, 75 e 100 mg.L-1) e de sacarose (0, 100, 200, 300, 400 g.L-1) suplementados ao meio de cultura Niles & Quesenverry. Após definida a composição do meio de cultura, foram testadas as seguintes temperaturas 25, 30, 35 e 40 °C para a germinação dos pólens in vitro. A avaliação das condições térmicas para o armazenamento, pólens frescos foram mantidos a -22, 10, 20 e 33 ºC durante um período de 11 semanas. A cada sete dias, foi avaliada a germinação utilizando-se o meio de cultura e temperatura de incubação definidos nos experimentos anteriores. Verificou-se que a interação da sacarose com o ácido bórico suplementados ao meio de cultura, foi significativa para a germinação in vitro dos pólens de A. pintoi. O meio suplementado com 200 g.L-1 de sacarose suplementado com 25 mg.L-1 de ácido bórico foi o mais adequado para a germinação in vitro de pólens de A. pintoi (21,7% de germinação). Apesar de ocorrer germinação no meio sem ácido bórico, nesta condição os tubos polínicos apresentaram parede celular delgada, rompendo-se facilmente. Constatou-se que a temperatura que resultou na maior porcentagem de germinação in vitro 30 °C, resultando em 21% de germinação. O armazenamento dos pólens a -22ºC é a condição mais adequada para prolongar a viabilidade do pólen, sendo observada a ocorrência de germinação até os 32 dias

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps

Abstract Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved