Information society and public ICT policies in the Caribbean: a review of advances and challenges, policy instruments and country experiences

Includes bibliography

E-business innovation and customs renovation for secure supply chain management

Includes bibliography

The urban female labour market in Latin America: the myth and the reality

Includes bibliography

Optimization of query results in peer-to-peer database supported by semantics

The development of new technologies that use peer-to-peer networks grows every day, with the object to supply the need of sharing information, resources and services of databases around the world. Among them are the peer-to-peer databases that take advantage of peer-to-peer networks to manage distributed knowledge bases, allowing the sharing of information semantically related but syntactically heterogeneous. However, it is a challenge to ensure the efficient search for information without compromising the autonomy of each node and network flexibility, given the structural characteristics of these networks. On the other hand, some studies propose the use of ontology semantics by assigning standardized categorization of information. The main original contribution of this work is the approach of this problem with a proposal for optimization of queries supported by the Ant Colony algorithm and classification though ontologies. The results show that this strategy enables the semantic support to the searches in peer-to-peer databases, aiming to expand the results without compromising network performance. © 2011 IEEE.

Mume clonal rootstocks for 'Aurora-1' peach in São Paulo State, Brazil

In spite of significant results achieved with scion genetic improvement in stone fruits, the peach culture in Brazil still needs studies and new technologies regarding the use of rootstocks. A wide research project has being developed at the Faculdade de Ciências Agrárias e Veterinárias (FCAV/UNESP), Jaboticabal, Brazil, dealing with the use of mume clones (Prunus mume) as rootstocks for peach trees, which has produced promising results. In this research, two mume genotypes propagated by herbaceous cuttings were tested as rootstocks for peach cultivar Aurora-1. Three different tree spacing were used: 6 x 2 m, 6 x 3 m and 6 x 4 m. The experiment was carried out at Vista Alegre do Alto (21°10'14 S, 48°37'45 W, 700 m of altitude), São Paulo State, Brazil. Growing field conditions included Hapludalfs soil with medium sandy texture and using micro sprinkler irrigation. The region has an average chilling accumulation 17.9 hours per year. The evaluations were taken in 2005 and 2006 (2nd and 3rd year after planting, respectively). The trunk diameter was evaluated every three months, from the 24th to the 41st month after planting, totalizing seven evaluations. Plants on 'Rigitano' had higher trunk diameter on the 33rd, 39th and 41st month after planting (May/06, November/06 and February/07, respectively). No significant differences were observed in the other evaluations. The diameter at 5 cm above to the graft point was larger than below, but no incompatibility symptoms were observed between rootstocks and scion. Spacing tested did not influence trunk diameter, phenology and flower bud production in 'Aurora-1' scion. In conclusion, 'Rigitano' and 'Clone 15' are recommended for high density plantings of peach 'Aurora-1' in Brazil, and the 6 x 2 m spacing can be recommended, with productivity advantages for peach under low air relative humidity and mild winter conditions. © ISHS 2012.

Remote phenology: Applying machine learning to detect phenological patterns in a cerrado savanna

Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. Digital cameras have been successfully used as multi-channel imaging sensors, providing measures of leaf color change information (RGB channels), or leafing phenological changes in plants. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract RGB channels from digital images and correlated with phenological changes. Our first goals were: (1) to test if the color change information is able to characterize the phenological pattern of a group of species; and (2) to test if individuals from the same functional group may be automatically identified using digital images. In this paper, we present a machine learning approach to detect phenological patterns in the digital images. Our preliminary results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; and (2) different plant species present a different behavior with respect to the color change information. Based on those results, we suggest that individuals from the same functional group might be identified using digital images, and introduce a new tool to help phenology experts in the species identification and location on-the-ground. ©2012 IEEE.

Some aspects of chicken behavior and welfare

Brazil is the world leader in broiler production and export. It achieved this position mainly to its excellent supply chain structure and climate, which favor poultry and grain production throughout its territory. Although Brazilian egg production is not as important as broiler production, this segment presents great potential of increasing its share in the global market. However, as elsewhere in the world, Brazilian poultry production faces the challenge to balance two elements within its supply chain: cruelty and productivity. The consumers of the European Union (EU) are very concerned with animal welfare issues. In order to increase its share in the European market, and eventually in the world market, Brazilian poultry producers must understand the effects of production systems on poultry welfare, and try to develop systems that are suited for its climate and other production conditions. There is a consensus that the natural behaviors performed by poultry in intensive production systems allow better welfare. This objective of this review is to present scientific research studies that relate different behaviors to chicken welfare. Poultry behavior is a reflex of their welfare status at a particular moment, and it is related to internal (physiological) and external (environmental) factors. Several natural behaviors that favor welfare, as well as undesirable behaviors, may be stimulated by environmental enrichment. The correct interpretation of the behaviors expressed by poultry, including their frequency, duration, and sequence, may be used to estimate their welfare. Animal production is an import sector of Brazilian economy. It significantly contributes to the Gross Domestic Product (GDP), in terms of products destined both to domestic consumption and exports. New technologies applied to products and management practices have been developed for field application, aiming at improving producers' productivity and profitability. In order to comply with the European Union's (EU) guidelines for animal protein production, Brazilian poultry production needs to undergo a process of adaptation. In May, 2007, the EU Commission established its new guidelines for animal welfare in poultry production, pressured by consumer demand. In the EU, there is a growing concern among consumers as to how poultry are reared and slaughtered. European consumers are in the fore front of the demand of high quality products produced with under better welfare conditions, and have spread this concern throughout the world. Beaumont et al. (2010) mentioned that European consumers frequently perceive that standard commercial poultry production has poor animal welfare practices. According to Nääs et al. (2008), Brazilian poultry production today needs to find a balance between cruelty and productivity. In fact, ensuring animal welfare may provide better financial results, as it increases the producer's profit margins and allows maintaining Brazilian chicken export quotas to the EU. França (2008) noted that biological studies that define ethical limits and guidelines for poultry production foster the development of new production practices that may ensure good product quality and productivity without putting bird welfare at risk. Gonyou (1994) states that, when animal welfare started to be studied, the only behavioral factors considered were those related to feeding and reproduction. These first studies used as indicators of animal welfare reduced life expectancy, impaired growth, impaired reproduction, body damage, disease, immunosuppression, adrenal activity, behavior anomalies, and self-narcotization (Broom, 1991). However, current studies evaluate additional indicators, such as natural behaviors, behavioral needs, preferences, behavioral problems, emotional state, cognitive abilities, etc. In the field of ethology, the expression of natural behavior is a frequently used tool used to estimate the welfare of poultry destined to human consumption. According to Bracke & Hopster (2006), natural behavior can be defined as the behavior the animal normaly presents when exposed to conditions similar to its natural habitat. Natural behaviors are pleasurable and promote biological functions that are meaningful to the animal's welfare. The definition of natural behavior, though, does not include the bird's behavior when sick, in flight or during aggression, since these are not considered pleasurable situations. Considering layer behavioral needs in the design of housing facilities optimize their welfare. Mishra et al. (2005) verified that ISA Brown layers spent, during 24 hours, around 97% of the time in the nest, feeding, walking, resting, or dust bathing, and that 57% of these behaviors did not depend on environmental enrichment. It was also observed that hens had preferred behavioral sequences, which included foraging and comfort behaviors, such as wing-stretching and preening. The present review aims at discussing, albeit not exhaustively, scientific research studies on the behavior of Gallusgallus domesticus and its relationship to welfare. The following behaviors are reviewed: feather pecking, scratching, dust bathing, nesting, locomotion activities, and aggressive behaviors. These behaviors are the most frequently observed in commercial broiler, broiler breeder, and layer farming, and therefore, monitoring their incidence may contribute to measure poultry welfare.

Market failure and technological policy

Includes bibliography

Creating capabilities in local environments and production networks

Includes bibliography

Risk management in software projects through Knowledge Management techniques: Cases in Brazilian Incubated Technology-Based Firms

In businesses such as the software industry, which uses knowledge as a resource, activities are knowledge intensive, requiring constant adoption of new technologies and practices. Another feature of this environment is that the industry is particularly susceptible to failure; with this in mind, the objective of this research is to analyze the integration of Knowledge Management techniques into the activity of risk management as it applies to software development projects of micro and small Brazilian incubated technology-based firms. Research methods chosen were the Multiple Case Study. The main risk factor for managers and developers is that scope or goals are often unclear or misinterpreted. For risk management, firms have found that Knowledge Management techniques of conversion combination would be the most applicable for use; however, those most commonly used refer to the conversion mode as internalization.. © 2013 Elsevier Ltd. APM and IPMA.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Modelagem de distorções entre realizações de referenciais geodésicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Infografia impressa: a aplicação de tecnologias digitais na construção de estampas artísticas

Pós-graduação em Artes - IA

Artemidia e ambientes expositivos

Pós-graduação em Artes - IA

Utilização de redes neurais recorrentes na caracterização de cargas não lineares em sistemas elétricos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)