49 resultados para Content Based Image Retrieval (CBIR)
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The concept of Learning Object (LO) is crucial for the standardization on eLearning. The latest LO standard from IMS Global Learning Consortium is the IMS Common Cartridge (IMS CC) that organizes and distributes digital learning content. By analyzing this new specification we considered two interoperability levels: content and communication. A common content format is the backbone of interoperability and is the basis for content exchange among eLearning systems. Communication is more than just exchanging content; it includes also accessing to specialized systems and services and reporting on content usage. This is particularly important when LOs are used for evaluation. In this paper we analyze the Common Cartridge profile based on the two interoperability levels we proposed. We detail its data model that comprises a set of derived schemata referenced on the CC schema and we explore the use of the IMS Learning Tools Interoperability (LTI) to allow remote tools and content to be integrated into a Learning Management System (LMS). In order to test the applicability of IMS CC for automatic evaluation we define a representation of programming exercises using this standard. This representation is intended to be the cornerstone of a network of eLearning systems where students can solve computer programming exercises and obtain feedback automatically. The CC learning object is automatically generated based on a XML dialect called PExIL that aims to consolidate all the data need to describe resources within the programming exercise life-cycle. Finally, we test the generated cartridge on the IMS CC online validator to verify its conformance with the IMS CC specification.
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XSLT is a powerful and widely used language for transforming XML documents. However, its power and complexity can be overwhelming for novice or infrequent users, many of whom simply give up on using this language. On the other hand, many XSLT programs of practical use are simple enough to be automatically inferred from examples of source and target documents. An inferred XSLT program is seldom adequate for production usage but can be used as a skeleton of the final program, or at least as scaffolding in the process of coding it. It should be noted that the authors do not claim that XSLT programs, in general, can be inferred from examples. The aim of Vishnu—the XSLT generator engine described in this chapter—is to produce XSLT programs for processing documents similar to the given examples and with enough readability to be easily understood by a programmer not familiar with the language. The architecture of Vishnu is composed by a graphical editor and a programming engine. In this chapter, the authors focus on the editor as a GWT Web application where the programmer loads and edits document examples and pairs their content using graphical primitives. The programming engine receives the data collected by the editor and produces an XSLT program.
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eLearning has been evolved in a gradual and consistent way. Along with this evolution several specialized and disparate systems appeared to fulfill the needs of teachers and students such as repositories of learning objects, intelligent tutors, or automatic evaluators. This heterogeneity poses issues that are necessary to address in order to promote interoperability among systems. Based on this fact, the standardization of content takes a leading role in the eLearning realm. This article presents a survey on current eLearning content standards. It gathers information on the most emergent standards and categorizes them according three distinct facets: metadata, content packaging and educational design.
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In this study, a new waste management solution for thermoset glass fibre reinforced polymer (GFRP) based products was assessed. Mechanical recycling approach, with reduction of GFRP waste to powdered and fibrous materials was applied, and the prospective added-value of obtained recyclates was experimentally investigated as raw material for polyester based mortars. Different GFRP waste admixed mortar formulations were analyzed varying the content, between 4% up to 12% in weight, of GFRP powder and fibre mix waste. The effect of incorporation of a silane coupling agent was also assessed. Design of experiments and data treatment was accomplished through implementation of full factorial design and analysis of variance ANOVA. Added value of potential recycling solution was assessed by means of flexural and compressive loading capacity of GFRP waste admixed mortars with regard to unmodified polymer mortars. The key findings of this study showed a viable technological option for improving the quality of polyester based mortars and highlight a potential cost-effective waste management solution for thermoset composite materials in the production of sustainable concrete-polymer based products.
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The development and applications of thermoset polymeric composites, namely fibre reinforced plastics (FRP), have shifted in the last decades more and more into the mass market [1]. Despite of all advantages associated to FRP based products, the increasing production and consume also lead to an increasing amount of FRP wastes, either end-of-lifecycle products, or scrap and by-products generated by the manufacturing process itself. Whereas thermoplastic FRPs can be easily recycled, by remelting and remoulding, recyclability of thermosetting FRPs constitutes a more difficult task due to cross-linked nature of resin matrix. To date, most of the thermoset based FRP waste is being incinerated or landfilled, leading to negative environmental impacts and supplementary added costs to FRP producers and suppliers. This actual framework is putting increasing pressure on the industry to address the options available for FRP waste management, being an important driver for applied research undertaken cost efficient recycling methods. [1-2]. In spite of this, research on recycling solutions for thermoset composites is still at an elementary stage. Thermal and/or chemical recycling processes, with partial fibre recovering, have been investigated mostly for carbon fibre reinforced plastics (CFRP) due to inherent value of carbon fibre reinforcement; whereas for glass fibre reinforced plastics (GFRP), mechanical recycling, by means of milling and grinding processes, has been considered a more viable recycling method [1-2]. Though, at the moment, few solutions in the reuse of mechanically-recycled GFRP composites into valueadded products are being explored. Aiming filling this gap, in this study, a new waste management solution for thermoset GFRP based products was assessed. The mechanical recycling approach, with reduction of GFRP waste to powdered and fibrous materials was applied, and the potential added value of obtained recyclates was experimentally investigated as raw material for polyester based mortars. The use of a cementless concrete as host material for GFRP recyclates, instead of a conventional Portland cement based concrete, presents an important asset in avoiding the eventual incompatibility problems arisen from alkalis silica reaction between glass fibres and cementious binder matrix. Additionally, due to hermetic nature of resin binder, polymer based concretes present greater ability for incorporating recycled waste products [3]. Under this scope, different GFRP waste admixed polymer mortar (PM) formulations were analyzed varying the size grading and content of GFRP powder and fibre mix waste. Added value of potential recycling solution was assessed by means of flexural and compressive loading capacities of modified mortars with regard to waste-free polymer mortars.
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This paper reports on the design and development of an Android-based context-aware system to support Erasmus students during their mobility in Porto. It enables: (i) guest users to create, rate and store personal points of interest (POI) in a private, local on board database; and (ii) authenticated users to upload and share POI as well as get and rate recommended POI from the shared central database. The system is a distributed client / server application. The server interacts with a central database that maintains the user profiles and the shared POI organized by category and rating. The Android GUI application works both as a standalone application and as a client module. In standalone mode, guest users have access to generic info, a map-based interface and a local database to store and retrieve personal POI. Upon successful authentication, users can, additionally, share POI as well as get and rate recommendations sorted by category, rating and distance-to-user.
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The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.
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Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.
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Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão
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Media content personalisation is a major challenge involving viewers as well as media content producer and distributor businesses. The goal is to provide viewers with media items aligned with their interests. Producers and distributors engage in item negotiations to establish the corresponding service level agreements (SLA). In order to address automated partner lookup and item SLA negotiation, this paper proposes the MultiMedia Brokerage (MMB) platform, which is a multiagent system that negotiates SLA regarding media items on behalf of media content producer and distributor businesses. The MMB platform is structured in four service layers: interface, agreement management, business modelling and market. In this context, there are: (i) brokerage SLA (bSLA), which are established between individual businesses and the platform regarding the provision of brokerage services; and (ii) item SLA (iSLA), which are established between producer and distributor businesses about the provision of media items. In particular, this paper describes the negotiation, establishment and enforcement of bSLA and iSLA, which occurs at the agreement and negotiation layers, respectively. The platform adopts a pay-per-use business model where the bSLA define the general conditions that apply to the related iSLA. To illustrate this process, we present a case study describing the negotiation of a bSLA instance and several related iSLA instances. The latter correspond to the negotiation of the Electronic Program Guide (EPG) for a specific end viewer.
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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.
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The current economic crisis has rushed even more the economists’ concerns to identify new directions for the sustainable development of the society. In this context, the human capital is crystallised as the key variable of the creative economy and of the knowledge-based society. As such, we have directed the research underlying this paper to identifying the most eloquent indicators of human capital to meet the demands of the knowledge-based society and sustainable development as well as towards achieving a comprehensive analysis of the human capital in the EU countries, respectively of a comparative analysis: Romania - Portugal. To carry out this paper, the methodology used is based on the interdisciplinary triangulation involving approaches from the perspective of human resource management, economy and economic statistics. The research techniques used consist of the content analysis and investigation of secondary data of international organisations accredited in the field of this research, such as: the United Nation Development Programme - Human Development Reports, World Bank - World Development Reports, International Labour Organisation, Eurostat, European Commission’s Eurobarometer surveys and reports on human capital. The research results emphasise both similarities and differences between the two countries under the comparative analysis and the main directions in which one has to invest for the development of human capital.
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Aim of the paper: The purpose of this paper is to examine human resources management practices (HRM practices) in small firms and to improve the understanding of the relationship between this kind of practices and business growth. This exploratory study is based on the resource-based view of the firm and empirical work carried out in two small firms by relating HRM practices with the firms’ results. Contribution to the literature: This is an in-depth study of HRM practices and its impact on performance growth in micro firms, isolating and controlling for most of the contextual and internal variables considered in the literature that relate HRM to growth. Firm growth analysis was broadened by the use of several dependent variables: employment growth and operational and financial performance growth. Some hypotheses for further research in identifying HRM practices in small business and its relation with firm growth are suggested. Methodology: Case study methodology was used to study two firms. The techniques used to collect data were semi-structured interviews to the owner and all the employees, unstructured observation at the firms’ facilities (during two days), entrepreneur profile definition (survey answer) and document data collection (on demographic characterization and performance results). Data was analyzed through content analysis methodology, and categories derived from the interviews’ protocols and literature. Results and implications: Results revealed that despite the firms’ organizational characteristics similarities, they differ significantly in owners’ motivation to grow, HRM practices and organizational performance and growth. Future studies should pay special attention to owner willingness to grow, to firms’ years of experience in business, to staff’s years of experience in their field of work and turnover. HRM practices in micro/small firms should be better defined and characterized. The external image of management posture relating to longitudinal financial results and growth should also be explored.
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Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.