Los emigrantes en las áreas mineras y las ciudades de Hispania: religión, identidades y difusión cultural

En el presente artículo analizamos los desplazamientos de cultos indígenas hispanos desde distintas áreas de la Península Ibérica hacia los principales lugares de inmigración en Hispania: las áreas mineras y las ciudades. Proponemos que estos grupos de emigrantes rendían culto en su nueva residencia a las deidades que veneraban en sus regiones de procedencia como un medio de preservar su cohesión social y su identidad cultural. La dureza de la vida laboral en las áreas mineras reforzaba la necesidad de fortalecer los lazos culturales.

Contextual text mining

With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

As Minas Barrojeiras das Alcanadas: um estudo para a sua valorização patrimonial

O património industrial mineiro assume cada vez mais, uma importância crescente em Portugal. As estruturas abandonadas deste período industrial que tanto marcou o nosso país estão a ser cada vez mais desprotegidas, sofrendo uma degradação crescente à medida que o tempo passa. É, portanto, relevante recuperá-las e elaborar projetos de valorização que visem dinamizar essas áreas preservando a memória coletiva. É neste panorama que se inserem as Minas das Barrojeiras das Alcanadas, concelho da Batalha. Pertencentes ao Couto Mineiro do Lena, laborando entre 1854 e 1956, estas minas foram abandonadas e entretanto despidas das estruturas que a compunham. Tendo isto em conta, foi proposta a realização de um circuito de valorização que complementa a exposição presente no MCCB, e que irá dinamizar aquele local; ABSTRACT: The industrial mining heritage, has nowadays an increasing importance in Portugal. The abandoned structures of this industrial time that defined so intensely our country are being forsaken more and more, suffering a growing degradation though out the time. Is therefore imperative to recover them and produce valuation projects that aim on enhancing the sites. Is in this perspective that the Minas of Barrojeiras of Alcanadas (in Batalha) are inserted. Belonging in the Couto Mineiro do Lena, and being active from 1854 till 1956, these mines were forsaken and later on, stripped from the structures that followed the activities of exploring the mineral. With this in mind, was proposed a valorization circuit that will enhance the location of the mine´s and will be a complement to the exhibition in Batalha´s MCCB.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

A University Support Model for eResearch

Queensland University of Technology (QUT) is faced with a rapidly growing research agenda built upon a strategic research capacity-building program. This presentation will outline the results of a project that has recently investigated QUT’s research support requirements and which has developed a model for the support of eResearch across the university. QUT’s research building strategy has produced growth at the faculty level and within its research institutes. This increased research activity is pushing the need for university-wide eResearch platforms capable of providing infrastructure and support in areas such as collaboration, data, networking, authentication and authorisation, workflows and the grid. One of the driving forces behind the investigation is data-centric nature of modern research. It is now critical that researchers have access to supported infrastructure that allows the collection, analysis, aggregation and sharing of large data volumes for exploration and mining in order to gain new insights and to generate new knowledge. However, recent surveys into current research data management practices by the Australian Partnership for Sustainable Repositories (APSR) and by QUT itself, has revealed serious shortcomings in areas such as research data management, especially its long term maintenance for reuse and authoritative evidence of research findings. While these internal university pressures are building, at the same time there are external pressures that are magnifying them. For example, recent compliance guidelines from bodies such as the ARC, and NHMRC and Universities Australia indicate that institutions need to provide facilities for the safe and secure storage of research data along with a surrounding set of policies, on its retention, ownership and accessibility. The newly formed Australian National Data Service (ANDS) is developing strategies and guidelines for research data management and research institutions are a central focus, responsible for managing and storing institutional data on platforms that can be federated nationally and internationally for wider use. For some time QUT has recognised the importance of eResearch and has been active in a number of related areas: ePrints to digitally publish research papers, grid computing portals and workflows, institutional-wide provisioning and authentication systems, and legal protocols for copyright management. QUT also has two widely recognised centres focused on fundamental research into eResearch itself: The OAK LAW project (Open Access to Knowledge) which focuses upon legal issues relating eResearch and the Microsoft QUT eResearch Centre whose goal is to accelerate scientific research discovery, through new smart software. In order to better harness all of these resources and improve research outcomes, the university recently established a project to investigate how it might better organise the support of eResearch. This presentation will outline the project outcomes, which include a flexible and sustainable eResearch support service model addressing short and longer term research needs, identification of resource requirements required to establish and sustain the service, and the development of research data management policies and implementation plans.

Characterisation of Coal Seam Gas Waters in New Zealand

Coal seam gas (CSG) exploration and development requires the abstraction of significant amounts of water. This is so because gas desorbtion in coal seams takes place only after aquifer pressure has been reduced by prolonged pumping of aquifer water. CSG waters have a specific geochemical signature which is a product of their formation process. These waters have high bicarbonate, high sodium, low calcium, low magnesium, and very low sulphate concentrations. Additionally, chloride concentrations may be high depending on the coal depositional environment. This particular signature is not only useful for exploration purposes, but it also highlights potential environmental issues that can arise as a consequence of CSG water disposal. Since 2002 L&M Coal Seam Gas Ltd and CRL Energy Ltd, have been involved in exploration and development of CSG in New Zealand. Anticipating disposal of CSG waters as a key issue in CSG development, they have been assessing CSG water quality along with exploration work. Coal seam gas water samples from an exploration well in Maramarua closely follow the geochemical signature associated with CSG waters. This has helped to identify CSG potential, while at the same time assessing the chemical characteristics and water generation processes in the aquifer. Neutral pH and high alkalinity suggest that these waters could be easily managed once the sodium and chloride concentrations are reduced to acceptable levels.

Dealing with unique interests in Crown Land : a Queensland perspective

Security of tenure is the cornerstone of the land management system in Australia. Freehold title is protected throug indefeasibility of title entrenched in legislation and protection of registrable interests in land is offered through the Statutory Assurance Fund. For those with interests pertaining to Crown Land no such protection is offered, although this position is not uniform across Australia. Notably those with Crown leasehold interests or a profit a prendre on Crown Land in Queensland are not protected through registration on the freehold land register and do not have the benefit of indefeasibility of title. The issue of management of interests pertaining to Crown Land has become increasingly relevant due to the complexities associated with balancing public interests including native title with more commercial interests in land generated through carbon sequestration, forestry and mining. This paper considers the framework for the management of Crown Land in Queensland and the adequacy of this framework for commercial interests that pertain to Crown Land.

Learning domain ontology for tag recommendation

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging and represent those in a form of ontology, but the application of the learned ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

Conformance checking of service behavior

A service-oriented system is composed of independent software units, namely services, that interact with one another exclusively through message exchanges. The proper functioning of such system depends on whether or not each individual service behaves as the other services expect it to behave. Since services may be developed and operated independently, it is unrealistic to assume that this is always the case. This article addresses the problem of checking and quantifying how much the actual behavior of a service, as recorded in message logs, conforms to the expected behavior as specified in a process model.We consider the case where the expected behavior is defined using the BPEL industry standard (Business Process Execution Language for Web Services). BPEL process definitions are translated into Petri nets and Petri net-based conformance checking techniques are applied to derive two complementary indicators of conformance: fitness and appropriateness. The approach has been implemented in a toolset for business process analysis and mining, namely ProM, and has been tested in an environment comprising multiple Oracle BPEL servers.

Flotation process response of Ok Tedi fluorine bearing minerals

Orebodies at Ok Tedi contain a number of different fluorine bearing minerals. Some of these minerals report to concentrate and are responsible for the presence of the penalty element, fluorine, within the concentrate. Previous analytical work has tended to examine geological samples for content, rather than determine the metallurgical behaviour of the different mineralogical species. This investigation utilised X-Ray Diffraction combined with Scanning Electron Microscope/Electron Microprobe to identify the fluorine bearing minerals in flotation test products. Seven fluorine bearing minerals were identified, viz., talc, phlogopite, amphibole (tremolite and actinolite), sphene, apatite, biotite and clay. Talc was found exclusively in the skarn ore type. Phlogopite and amphiboles (tremolite and actinolite) were found to occur in both skarn and porphyry ores, while sphene, apatite, biotite and clay were found only in the porphyry ores. Of the fluorine bearing minerals observed, only talc exhibited natural hydrophobicity to any significant degree. Phlogopite and the amphibole minerals were found to be hydrophillic, whilst the remaining minerals occurred in insufficient quantities to determine the flotation behaviour. Ok Tedi copper concentrate fluorine content prior to skarn ore treatment in the mill (typically 350ppm) was previously identified as deriving from phlogopite, while talc was believed to be the source of intermittent high concentrate fluorine contents when skarn ores were treated. This paper provides supporting evidence for this belief, and reports the nature of fluorine bearing mineral flotation behaviour.

Reputation modelling in Citizen Science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Data reliability issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. Participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data reliability has become an urgent demand. This study aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we propose to design a reputation framework to enhance data reliability and also investigate some critical elements that should be aware of during developing and designing new reputation systems.

Linking Karumba : Creating Sustainable Connections

Linking Karumba: Creating Sustainable Connections This exhibition showcases the work of 3rd -4th year undergraduate landscape architecture, architecture, Industrial Design, Environmental Engineering, Civil Engineering students in response to issues of sustainability in the Gulf of Carpentaria town of Karumba. It presented the work to the Karumba and Carpentaria Shire community. 16 students and four staff set off on a 2488km journey to undertake the first half of the Carpentaria Project: a fortnight-long strategic planning project entitled Linking Karumba to encourage social, economic, environmental and cultural linkages across the town. Karumba, along with the nearby town of Normanton, is one of Queensland’s most remote settlements. Its economy is based on fishing, tourism, and mining. It has two centres, 2.5km apart by river, or 9km by road. This physical disconnect was identified by Carpentaria Shire Council (CSC) and the Karumba Progress Association (KPA) as a source of socio-cultural disconnection, which formed the basis of our project brief. Student designs were highly responsive to the character of Karumba’s culture and environment, indicating remarkable levels of immersion, and attracting $830 000 in Qld. state government funding for implementation. The Exhibition Four groups of four students produced four strategic planning and design options toward this future: Make the Switch: Alice Anonuevo, Michael Marriott, Carla Priestley & Grant Harvey Realigning the Systems: Claudia Bergs, Rebecca Stephens, Anna Coulson & Lois Kerrigan Diversification of Experience: Rebecca North, Kyle Bush, Debra Sullivan & Jenna Green The River is the Main Street: Ashley Nicholson, Monica Kuiken, Dean Bowen & Bill Schild

QUT Linking Karumba Project

QUT Linking Karumba Project This exhibition showcases the work of 3rd -4th year undergraduate landscape architecture, architecture, Industrial Design, Environmental Engineering, Civil Engineering students in response to issues of sustainability in the Gulf of Carpentaria town of Karumba. It presented the final, polished set of work to the Karumba and Carpentaria Shire community, following revisions in line with feedback from the 2008 exhibition. 16 students and four staff set off on a 2488km journey to undertake the first half of the Carpentaria Project: a fortnight-long strategic planning project entitled Linking Karumba to encourage social, economic, environmental and cultural linkages across the town. Karumba, along with the nearby town of Normanton, is one of Queensland’s most remote settlements. Its economy is based on fishing, tourism, and mining. It has two centres, 2.5km apart by river, or 9km by road. This physical disconnect was identified by Carpentaria Shire Council (CSC) and the Karumba Progress Association (KPA) as a source of socio-cultural disconnection, which formed the basis of our project brief. Student designs were highly responsive to the character of Karumba’s culture and environment, indicating remarkable levels of immersion, and attracting $830 000 in Qld. state government funding for implementation. The Exhibition Four groups of four students produced four strategic planning and design options toward this future: Make the Switch: Alice Anonuevo, Michael Marriott, Carla Priestley & Grant Harvey Realigning the Systems: Claudia Bergs, Rebecca Stephens, Anna Coulson & Lois Kerrigan Diversification of Experience: Rebecca North, Kyle Bush, Debra Sullivan & Jenna Green The River is the Main Street: Ashley Nicholson, Monica Kuiken, Dean Bowen & Bill Schild

Learning routines used by firms during construction of infrastructure projects using the alliance procurement method

Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.