GERADOR DE CÓDIGOS PARA O DESENVOLVIMENTO DE APLICAÇÕES WEB A PARTIR DA MODELAGEM ENTIDADE-RELACIONAMENTO

A geração automática de código-fonte é uma prática adotada no desenvolvimento de softwares para agilizar, facilitar e padronizar a implementação dos projetos. Embora seja uma prática comum nas fábricas de software, não se conhece uma ferramenta que permita escolher o padrão de projeto a ser usado. O objetivo principal deste trabalho é apresentar um gerador de códigos para o desenvolvimento de sistemas Web a partir de uma modelagem entidade-relacionamento, uma linguagem de programação e um padrão de projeto determinados pelo usuário. Os objetivos específicos são propor uma arquitetura do sistema capaz de adequar e reaproveitar diferentes padrões de projeto, linguagens de programação e projetos cadastrados; permitir que o usuário cadastre, altere, exclua, importe e exporte um projeto; e gerar automaticamente o seu código-fonte e scripts de banco de dados. Este trabalho se justifica pela importância de reduzir erros de codificação; e evitar perca tempo ao realizar atividades rotineiras de implementação de padrões de projeto. Possibilitando assim, maior dedicação no planejamento das regras de negócios e redução de custos. A ferramenta proposta (GCER) foi desenvolvida em linguagem Java com o uso banco de dados Oracle 11g, e seguindo os padrões DAO e MVC. Os resultados foram avaliados através da geração e compilação de códigos de um projeto para cadastro de veículos. A geração com êxito evidencia a viabilidade da ferramenta proposta para a geração automática de códigos no processo de desenvolvimento de software.AbstractThe automatic generation of source code is a practice adopted in the development of software to streamline, facilitate and standardize the implementation of projects. Although it be a common practice in software factories, it is not known a tool able to choose the design pattern to be used. The main objective of this paper is to present a code generator for the development of Web systems from an entity-relationship modeling, a programming language and a design pattern determined by the user. The specific objectives are to propose a system architecture able to suit and reuse different design patterns, programming languages and saved projects; allow the user to insert, update, delete, import and export a project; and automatically generate the source code and database scripts. This work is justified by the importance to reduce errors of coding; and to avoid waste of time in the development of Web systems performing routine tasks. Allowing, then, a greater dedication in the planning of business rules and the reduction of costs. The tool proposed (GCER) was developed in Java with the database using Oracle 11g, and following the DAO and MVC patterns. The results were evaluated by generating and compiling codes of a project for vehicle registration. The successful code generation demonstrate the feasibility of the proposed tool for the automatic generation of code in the software development process

PROPOSTA DE UM FRAMEWORK BASEADO EM MINERAÇÃO DE DADOS PARA REDES 5G

Smart cities are gaining, increasingly, notoriety. Through them, the population can have better services and urban quality of life. With the future fifth generation cellular (5G) networks will be possible to collect data from various sources throughout the city, such as sensors and actuators, mobile devices, mobile and telephone networks among others. In this scenario, it will be necessary to analyze large volumes of data, in order to get knowledge and useful information for a dynamic and clever planning. This article presents a data mining based framework proposal for 5G networks, named Urban Computing Framework in 5G Networks (CoUrbF5G). Real standards of a mobile network are found and analyzed in the proposal by applying data mining techniques along with ancillary methods on the conducting of Data Science processes, such as Knowledge Discovery in Databases (KDD) and Big Data.Cidades inteligentes vêm ganhando, cada vez mais, notoriedade. Através delas, a população pode ter melhores serviços e qualidade de vida urbana. Com as futuras redes de celulares de quinta geração (5G) será possível coletar dados por meio de diversas fontes espalhadas pela cidade, tais como sensores, dispositivos móveis, redes veiculares e de telefonia, dentre outras. Nesse cenário, haverá a necessidade de análise de grandes volumes de dados, com o objetivo de extrair conhecimento e informação útil para o planejamento inteligente e dinâmico. Este artigo apresenta uma proposta de framework baseado em mineração de dados para redes 5G, denominado Urban Computing Framework in 5G Networks (CoUrbF5G). Padrões reais de uma rede de telefonia móvel são encontrados e analisados, aplicando técnicas de mineração de dados, em conjunto com métodos auxiliares na condução de processos como Knowledge Discovery in Databases (KDD) e Big Data

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

A 5G V2X Ecosystem Providing Internet of Vehicles

The Fifth Generation (5G) cellular network can be considered the way to the ubiquitous Internet and pervasive paradigm.The Internet of Vehicles (IoV) uses the network infrastructure to allow cars to be connected to new radio technologies, and can be supported by 5G networks. In this way, the Vehicle-to-Everything (V2X) integration needs 5G connections unavoidably. This paper presents a 5G V2X ecosystem to provide IoV. The proposed ecosystem is based on the Software-Defined Networking (SDN) concept. Considering vehicles as entertainment consumer points, the network infrastructure must be huge enough to guarantee delivery and quality. For this purpose, this paper evaluates vehicular Internet-based video services traffic and Vehicle-to-Vehicle (V2V) communications in urban and rural scenarios. Simulations were performed through the Network Simulator ns-3, employing millimeter Wave (mmWave) communications. Three metrics, data transfer rate, transmission delay, and Packet Delivery Ratio (PDR), were analyzed and compared for rural and urban IoV scenarios. The results have shown satisfactory performance to the IoV communications requirements when adopting the 5G network with V2X communications

Insularization drives physiological condition of Amazonian dung beetles

Abstract The fragmentation and degradation of otherwise continuous natural landscapes pose serious threats to the health of animal populations, consequently impairing their fitness and survival. While most fragmentation ecology studies focus on habitat remnants embedded withinn terrestrial matrices, the effects of true insularization remains poorly understood. Land‐bridge islands created by major dams leads to habitat loss and fragmentation, negatively affecting terrestrial biodiversity. To assess the effects of insularization, we conducted a study on the key aspects of dung beetle physiological condition and body size throughout the Balbina Hydroelectric Reservoir located in the Central Amazon. We assessed these traits at the population and assemblage levels, collecting dung beetles from both forest islands and continuous forest areas while analyzing various landscape variables. We show that landscapes with higher forest cover positively affected dung beetle body size. Interestingly, dung beetle responses to insularization were species‐dependent; larger islands tended to host larger individuals of Deltochilum aspericole, while in Canthon triangularis, smaller islands showed larger body sizes. However, individuals from the mainland were larger than those from the islands. Moreover, the proportion of closed‐canopy forest in the landscapes also impacted physiological attributes. It negatively affected the body size of Deltochilum aspericole and the lipid mass of Dichotomius boreus, but positively affected the lipid mass of Canthon triangularis. These findings contribute to a better understanding of how habitat fragmentation in aquatic matrices affects the size structure and physiology of insect assemblages. This is essential in formulating effective conservation strategies for preserving biodiversity loss in tropical forest regions and mitigating the consequences of hydropower infrastructure