Abstract
Data has increased in a large scale in various fields leading to the coin of the term Big Data. Big data is mainly used to describe enormous datasets that typically includes masses of unstructured data that may need real-time analysis. As human behaviour and personality can be captured through human-computer interaction a massive opportunity opens for providing wellness services. Through the use of interaction data, behavioral biometrics can be obtained. The usage of biometrics has increased due to several factors such as the rise of power and availability of computational power. One of the challenges in this kind of approaches has to do with handling the acquired data. The growing volumes, variety and velocity brings challenges in the tasks of pre-processing, storage and providing analytics. In this sense, the problem can be framed as a Big Data problem. In this work it is intended to provide an architecture that accommodates the data pipeline of data generated by human-computer interaction, providing real time data analytics on behavioral biometrics.

Abstract

Abstract
A rise in population, along with urbanization, has been causing an increase in demand for urban transportation services in the sub-Saharan Africa countries. In these countries, mobility of people is mainly ensured by bus services and a large-scale informal public transport service, which is known as paratransit (e.g., car rapides in Senegal, Tro Tros in Ghana, taxis in Uganda and Ethiopia, and Matatus in Kenya). Transport demand estimation is a challenging task, particularly in developing countries, mainly due to its expensive and time-consuming data collection requirements. Without accurate demand estimation, it is difficult for transport operators to provide their services and make other important decisions. In this paper, we present a methodology to estimate passenger demand for public transport services using cell phone data. Significant origins and destinations of inhabitants are extracted and used to build origin-destination matrices that resemble travel demand. Based on the inferred travel demand, we are able to reasonably suggest strategic locations for public transport services such as paratransit and taxi stands, as well as new transit routes. The outcome of this study can be useful for the development of policies that can potentially help fulfill the mobility needs of city inhabitants.

Abstract
Multi-layer Stream Mapping (MSM) comprehends a new framework for the performance assessment of complex systems. The MSM was developed for multi-domain analysis in an original manner to assess if resources, process and other domains are used to their full potential. The costs related with misuses/inefficiency situations are also quantified and integrated in a simplified manner. A real case study applying the MSM method is validated through application to a Medium Density Fibreboard (MDF) finishing line. For this study all the resources and materials consumed in each unit process where considered. The overall efficiency was assessed and improvements actions were evaluated. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
Assessing eco-efficiency performance of a production system is of great importance, since such assessment enables one to make an informed decision concerning economic and environmental performance of elementary systems within industrial productions systems. The framework presented in this paper is based on the eco-efficiency principles and four cornerstones i) Data inventory, ii) Environmental performance evaluation, iii) Environmental impact assessment and iv) Cost models/Value data. The Eco-Efficiency Integrated Methodology for Production Systems (ecoPROSYS) approach relies on the use of a systematized and organized set of indicators easy to understand/analyse promoting continuous improvement and a more efficient use of resources and energy. The goal is to assess eco-efficiency performance in order to support decision and enable the maximization of product/processes value creation and minimization of environmental burdens. The methodology was applied to a Medium Density Fibreboard (MDF) finishing line. The results of the study intend to validate the applicability of ecoPROSYS. The case study showed that the cutting and the feeding table have superior eco-efficiency performance while packing and sanding have lower eco-efficiency performance. The presented framework is a powerful tool that can be used to identify and quantify key variables, assess alternative scenarios, evaluate environmental aspects, environmental influence and assess unit processes and overall eco-efficiency performance. (C) 2016 The Authors. Published by Elsevier

Abstract
The aim of this research paper is to formulate a road map for implementation of lean techniques within SMEs product development (PD) teams, identifying barriers to change and explaining possible drivers for successful implementation. The research methodology necessary to develop the road map - the IPID cycle - is a combination of different approaches. It combines a literature review, an initial quantitative study with questionnaires, informal interviews and direct observation of companies' practices of five different manufacturing companies organised in a consortium. Like any other case study methodology, it suffers from generalisation issues, but we expect that the proposed road map is applicable whenever managers need to introduce changes inside their PD teams. Also, we found that a consortium arrangement can be highly positive to the implementation of the proposed road map. Finally, we found that the application of the road map to SMEs PD teams is somewhat different from big companies' implementations and discuss the observed particularities of these findings. Copyright © 2016 Inderscience Enterprises Ltd.