DESIGN APPLIED TO FAMILY AGRICULTURE AND AQUACULTURE BASED ON SOCIAL INNOVATION

The design has gradually been considered by people as an important element for organizations, reinforcing their identities and consequently their image perceived by the society. The design assumes the compromise of intermediate the communication process producer-consumer, aggregating and highlighting the value of the products, in order to create a concept that reflects and increments their main characteristics. In this context, we listed and discussed the basic dimensions of the proposed model, identifying their influences and connections in the sector of agriculture and of aquaculture. In the case of the model of 7I’s, it is possible to identify in the same context the need of opting for actions aimed to the integration of the areas as a way to ensure more comprehensive solutions, thus bringing in it innovations at different levels (basic incremental and radical, as well as the social innovations). Additionally there is an intervention process with proactive characteristics (preferentially) which may similarly potentialize the interaction of all involved at all levels, in an intelligent and articulated form. Besides, it generates a feedback process in an integral form. All this leads to the shaping of a systemic approach of the situation. Social innovation and integration can be achieved through the implementation of actions of design. In this article we present cases occurring in sectors of agriculture and family aquaculture, in which, through of a suggestion of applied design management, it was possible to check positive results. The partnerships established between the government, university and other copartners, as well as with the producers themselves, have been resulting in concrete and evident actions of improvement on weaknesses detected in the sectors being studied. With systematic and planned procedures of management and design, it was possible to transform some actualities, by having them measured, quantitatively at points of sale, and qualitatively based on perception of consumers/users

ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in {R}

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies

Pedestrian Attribute Recognition: A Survey

Recognizing pedestrian attributes is an important task in computer vision community due to it plays an important role in video surveillance. Many algorithms has been proposed to handle this task. The goal of this paper is to review existing works using traditional methods or based on deep learning networks. Firstly, we introduce the background of pedestrian attributes recognition (PAR, for short), including the fundamental concepts of pedestrian attributes and corresponding challenges. Secondly, we introduce existing benchmarks, including popular datasets and evaluation criterion. Thirdly, we analyse the concept of multi-task learning and multi-label learning, and also explain the relations between these two learning algorithms and pedestrian attribute recognition. We also review some popular network architectures which have widely applied in the deep learning community. Fourthly, we analyse popular solutions for this task, such as attributes group, part-based, \emph{etc}. Fifthly, we shown some applications which takes pedestrian attributes into consideration and achieve better performance. Finally, we summarized this paper and give several possible research directions for pedestrian attributes recognition. The project page of this paper can be found from the following website: \url{https://sites.google.com/view/ahu-pedestrianattributes/}.Comment: Check our project page for High Resolution version of this survey: https://sites.google.com/view/ahu-pedestrianattributes

Systems Biology Graphical Notation: Activity Flow language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialized notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Descriptions, the Entity Relationships and the Activity Flows. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage ranging from textbooks and teaching in high schools to peer reviewed articles in scientific journals. The first level of the SBGN Activity Flow language has been publicly released. Shared by the communities of biochemists, genomic scientists, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signaling pathways, metabolic networks and gene regulatory maps