D6.1 – Ecosystem Software Platform with Underlying Software Repository, Digital Library and Media Archive

The objective of D6.1 is to make the Ecosystem software platform with underlying Software Repository, Digital Library and Media Archive available to the degree, that the RAGE project can start collecting content in the form of software assets, and documents of various media types. This paper describes the current state of the Ecosystem as of month 12 of the project, and documents the structure of the Ecosystem, individual components, integration strategies, and overall approach. The deliverable itself is the deployment of the described components, which is now available to collect and curate content. Whilst this version is not yet feature complete, full realization is expected within the next few months. Following this development, WP6 will continue to add features driven by the business models to be defined by WP7 later on in the project.

Classifying Written Texts Through Rhythmic Features

Rhythm analysis of written texts focuses on literary analysis and it mainly considers poetry. In this paper we investigate the relevance of rhythmic features for categorizing texts in prosaic form pertaining to different genres. Our contribution is threefold. First, we define a set of rhythmic features for written texts. Second, we extract these features from three corpora, of speeches, essays, and newspaper articles. Third, we perform feature selection by means of statistical analyses, and determine a subset of features which efficiently discriminates between the three genres. We find that using as little as eight rhythmic features, documents can be adequately assigned to a given genre with an accuracy of around 80 %, significantly higher than the 33 % baseline which results from random assignment.

Feature recognition & tool path generation for 5 axis step-nc machining of free form / irregular contoured surfaces

This research paper presents a five step algorithm to generate tool paths for machining Free form / Irregular Contoured Surface(s) (FICS) by adopting STEP-NC (AP-238) format. In the first step, a parametrized CAD model with FICS is created or imported in UG-NX6.0 CAD package. The second step recognizes the features and calculates a Closeness Index (CI) by comparing them with the B-Splines / Bezier surfaces. The third step utilizes the CI and extracts the necessary data to formulate the blending functions for identified features. In the fourth step Z-level 5 axis tool paths are generated by adopting flat and ball end mill cutters. Finally, in the fifth step, tool paths are integrated with STEP-NC format and validated. All these steps are discussed and explained through a validated industrial component.

Feature Study on a Programmable Network Traffic Classifier

Monitoring and tracking of IP traffic flows are essential for network services (i.e. packet forwarding). Packet header lookup is the main part of flow identification by determining the predefined matching action for each incoming flow. In this paper, an improved header lookup and flow rule update solution is investigated. A detailed study of several well-known lookup algorithms reveals that searching individual packet header field and combining the results achieve high lookup speed and flexibility. The proposed hybrid lookup architecture is comprised of various lookup algorithms, which are selected based on the user applications and system requirements.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Feature Selection for Anomaly Detection Using Optical Emission Spectroscopy

To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.

Synthesis and characterization of eco-friendly inorganic yellow pigments for coloring applications

Research in the fields of ceramic pigments is oriented towards the enlargement of the chromatic set of colors together with a replacement for more expensive and less stable organic pigments. Novel non-toxic inorganic pigments have been required to answer environmental laws to remove elements like lead, chromium, cobalt entering in the composition of usual pigments widely used in paints and plastics. Yellow is particularly an important color in the pigment industry and consumption of yellow exceeds that of any other colored pigments. Apart from this, high infrared reflective pigments are now in great demand for usage in coatings, cement pavements, automotives and camouflage applications. They not only impart color to an object, but also reflect the invisible heat from the object to minimize heat build–up, when exposed to solar radiation. With this in view, the present work aims at developing new functional yellow pigments for these applications. A series of IR reflecting yellow pigments have been synthesized and analyzed for their crystalline structure, morphological, composition and optical characteristics, coloring and energy saving applications

The signalling effect of eco-labels in modern coastal tourism

As the demand for environmentally sustainable tourism grows, eco-labels are becoming increasingly popular as a signal of environmental quality. However, the existence of a causal link between awarding a seaside eco-label and the increase in tourism flows is still under discussion in the literature. In this article, we gauge the signalling impact of a specific eco-label, the Blue Flag award, using detailed data on tourism flows to seaside Italian destinations during the period 2008-2012. We adopt a recent econometric modelling strategy - the synthetic control method - in shaping estimation results and testing the sensitivity and robustness of our results. We find that being awarded the Blue Flag increases the flow of domestic tourists for up to three seasons after assignment. However, we find no effect for the flow of international tourists. Investigating the mechanisms driving the results, we find that the award of a Blue Flag only positively affects the flow of domestic tourists when it is used as a driver of organisation, coordination and integrated management of the tourism supply.

Danças Circulares e o Eco-humanismo nas Organizações

A presente dissertação pretende avaliar como os membros das organizações relacionam a prática das danças circulares com elementos do comportamento organizacional. A pertinência desta investigação consiste no fato de estudos e intervenções direcionadas ao comportamento organizacional poderem impactar positivamente o desempenho tanto dos servidores quanto da organização como um todo. As organizações estão enfrentando desafios que demandam teorias e práticas que as fortaleçam, buscando-se atender às necessidades de todos que a compõe. A profundidade dessas mudanças faz com que seja necessário alinhar-se o esforço individual ao grupal. Necessita-se o aprendizado em grupo, o pensamento sistêmico. As danças circulares parecem proporcionar efeitos de bem-estar, segurança, solicitude, cooperação, abertura ao diálogo e eles são extremamente importantes em relação a diversos aspectos da organização, como liderança, hierarquia, motivação, poder, clima organizacional, cultura, comunicação, etc. Seus efeitos, por conseguinte, podem fazê-las importante instrumento que melhore os ambientes de trabalho, além de proporcionarem uma conscientização quanto à importância de levar às organizações o tema da sustentabilidade. A sustentabilidade insere-se no paradigma eco-humanista, alinhado, por sua vez, ao resgate da inteireza do homem. As danças circulares, podem expressar e materializar tal paradigma, de modo a favorecer o comprometimento, a motivação e a participação nas organizações. / This dissertation aims evaluate how the members of organizations relate the practice of circle dances with elements of organizational behavior. Its importance derives in the fact that studies and interventions addressed to the organizational behavior may impact positively both the performance of the workers as well of the organization as a whole. The organizations are facing challenges that need theories and practices to strengthen them, in order to fill the needs of all its members. The depth of the changes makes it necessary to encompass the individual and the grupal efforts. It is necessary the group learning and the systemic thinking. The circle dances seems to provide effects such as well being, security, solicitude, cooperation, openness to dialogue and they are extremely important related to various aspects of organization, as leadership, hierarchy, motivation, power, organizational climate, culture, communication, etc. Its effects, thus, may make them important tool to the betterment of the work environment, besides allow the awareness of the importance to bring to organizations the theme of sustainability. The sustainability is a part of the eco-humanistic paradigm, related to the integrity of man. The circle dance may express and materialize this paradigm, helping commitment, motivation and participation in the organizations.

How Can Villages Become Eco-villages?

The authors investigated (a) the relationship between feeling connected to nature and pro-environmental behaviours; and (b) the relationship between environmental values and environmental behaviours. Seventy-six students completed an online survey that measured connectedness to nature, egoistic, altruistic and biospheric values, and pro-environmental behaviours. This study suggests that finding ways to increase community feelings of connectedness to nature, and developing altruistic and biospheric values may lead to increased pro-environmental behaviours in the short term and positively address climate change issues in the longer term.