JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Supply Chain Management practices in the electro-electronics sector in Brazil: Evolutionary approach, information technology adoption and management actions

This paper examines the current level of adoption of Supply Chain Management (SCM) practices in the electro-electronic sector in Brazil and aims to identify the management and Information Technology (IT) actions that have been implemented to support the adoption of those practices. An e-mail survey was conducted. Descriptive statistics techniques were employed for data analysis. This study makes contributions to the electro-electronics sector and to the topics related to SCM, such as identifi cation and level of adoption of SCM practices. Another contribution of this research is the investigation of whether approaches such as Enterprise Resources Planning (ERP), Workshop with Customers, Electronic Data Interchange (EDI), Workshop with Suppliers and electronic Kanban are commonly used to support SCM practices. So far, this is the fi rst research on SCM practices in the electro-electronics sector in Brazil. Copyright © 2012 Inderscience Enterprises Ltd.

Is the environmental policies procedures a barrier to development of inland navigation and port management? A case of study in Brazil

The main objective of this article is to discuss the Brazilian environmental legislation and policies towards the development of navigation and port management. The research illustrated some difficulties faced by the country and make suggestions to overcome it. The construction of the environmental legal framework began in the early 1960s and resulted in a very complex system, as a consequence of policies adopted by the country. Nowadays Brazilian environmental policies are developed in democratic and participative way, although with elevated degree of bureaucracy and lack of integration among the several governmental agencies, which makes the approval of environmental certifications demand several years for new port projects or improvements, which delays the economic development of the country. Efforts have been made to simplify the licensing process. As result of this research two flowchart for environmental licenses of ports installation are shown: The first shows the process until 2009 and the second shows the process nowadays. This become an important issue due the fact that inland navigation is one of the less pollutant modes of transportation, and although, the process of environmental certification was simplified, if compare with 2009, it is still complex and time-consuming, delaying the development of the infrastructure. © 2012 Elsevier Ltd.

Analysing green supply chain management practices in Brazil's electrical/electronics industry using interpretive structural modelling

Industries need to adopt the environmental management concepts in the traditional supply chain management. The green supply chain management (GSCM) is an established concept to ensure environment-friendly activities in industry. This paper identifies the relationship of driving and dependence that exists between GSCM practices with regard to their adoption within Brazilian electrical/electronic industry with the help of interpretive structural modelling (ISM). From the results, we infer that cooperation with customers for eco-design practice is driving other practices, and this practice acts as a vital role among other practices. Commitment to GSCM from senior managers and cooperation with customers for cleaner production occupy the highest level. © 2013 Copyright Taylor and Francis Group, LLC.

Relationships between company size, types of production system and supply chain management: evidence from electro-electronics sector in Brazil

Purpose – The purpose of this paper is to investigate how company size and the type of production system affect the adoption of supply chain management (SCM) practices in companies in the electro‐electronics sector in Brazil. Design/methodology/approach – An e‐mail survey of 107 companies associated with the Brazilian Electrical and Electronics Industry Association (ABINEE) was conducted. Statistical techniques were employed to verify the adoption of SCM practices according to the size of the company and its production system. Findings – The major results indicate that the larger the size of the company, the higher the level of adoption of SCM practices, and that the choice of SCM practices depends upon the type of production system implemented. Practical implications – The implications of this study are useful to top management leaders of small and medium‐sized enterprises since the findings enable them to identify the most common practices adopted by either large‐, medium‐ or small‐sized companies in order to benchmark the level of adoption of SCM practices. Production managers can also benefit from this study by identifying the SCM practices that may support certain production systems.