Teaching Communications, Cultures, Connections, Comparisons, and Communities with Multimedia: A University-Middle School Service-Learning Project

Se describe el uso de tecnología en forma de presentaciones de multimedia para facilitar la enseñanza de las Normas para el Aprendizaje de una Lengua Extranjera del Concilio Americano para la Enseñanza de Lenguas extranjeras. Las normas abarcan las comunicaciones, las culturas, las conexiones, las comparaciones y las comunidades. El estudiantado universitario aprende a crear, con multimedia, presentaciones sobre un tema cultural en la lengua meta. El componente de aprendizaje por servicio comunitario se fundamenta en las presentaciones creadas para estudiantes de colegio, quienes tienen acceso a las presentaciones en un sitio web de la universidad.A description is provided of how the use of technology in the form of multimedia presentations enhances the teaching of the Five C Standards for Foreign Language Learning of the American Council on the Teaching of Foreign Languages: communications, cultures, connections, comparisons, and communities. University students learn to create multimedia presentations on a cultural topic in the target language. The service-learning component provides the multimedia presentations for middle-school students who access them from the university website.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Modelling and simulations of ductile iron solidification-induced variations in mechanical behaviour on component and microstructural level

The mechanical behaviour and performance of a ductile iron component is highly dependent on the local variations in solidification conditions during the casting process. Here we show a framework which combine a previously developed closed chain of simulations for cast components with a micro-scale Finite Element Method (FEM) simulation of the behaviour and performance of the microstructure. A casting process simulation, including modelling of solidification and mechanical material characterization, provides the basis for a macro-scale FEM analysis of the component. A critical region is identified to which the micro-scale FEM simulation of a representative microstructure, generated using X-ray tomography, is applied. The mechanical behaviour of the different microstructural phases are determined using a surrogate model based optimisation routine and experimental data. It is discussed that the approach enables a link between solidification- and microstructure-models and simulations of as well component as microstructural behaviour, and can contribute with new understanding regarding the behaviour and performance of different microstructural phases and morphologies in industrial ductile iron components in service.

Semantic relations: Modelling issues, proposals and possible applications

Semantic relations are an important element in the construction of ontology-based linguistic resources and models of problem domains. Nevertheless, they remain under-specified. This is a pervasive problem in both Software Engineering and Artificial Intelligence. Thus, we find semantic links that can have multiple interpretations, abstractions that are not enough to represent the relation richness of problem domains, and even poorly structured taxonomies. However, if provided with precise semantics, some of these problems can be avoided, and meaningful operations can be performed on them that can be an aid in the ontology construction process. In this paper we present some insightful issues about the representation of relations. Moreover, the initiatives aiming to provide relations with clear semantics are explained and the inclusion of their core ideas as part of a methodology for the development of ontology-based linguistic resources is proposed.

Ontologies and the Semantic Web: Problems and Perspectives for LIS Professionals

Many years have passed since Berners-Lee envi- sioned the Web as it should be (1999), but still many information professionals do not know their precise role in its development, especially con- cerning ontologies –considered one of its main elements. Why? May it still be a lack of under- standing between the different academic commu- nities involved (namely, Computer Science, Lin- guistics and Library and Information Science), as reported by Soergel (1999)? The idea behind the Semantic Web is that of several technologies working together to get optimum information re- trieval performance, which is based on proper resource description in a machine-understandable way, by means of metadata and vocabularies (Greenberg, Sutton and Campbell, 2003). This is obviously something that Library and Information Science professionals can do very well, but, are we doing enough? When computer scientists put on stage the ontology paradigm they were asking for semantically richer vocabularies that could support logical inferences in artificial intelligence as a way to improve information retrieval systems. Which direction should vocabulary development take to contribute better to that common goal? The main objective of this paper is twofold: 1) to identify main trends, issues and problems con- cerning ontology research and 2) to identify pos- sible contributions from the Library and Information Science area to the development of ontologies for the semantic web. To do so, our paper has been structured in the following manner. First, the methodology followed in the paper is reported, which is based on a thorough literature review, where main contributions are analysed. Then, the paper presents a discussion of the main trends, issues and problems concerning ontology re- search identified in the literature review. Recom- mendations of possible contributions from the Library and Information Science area to the devel- opment of ontologies for the semantic web are finally presented.

Trophic food web and ecosystem attributes of a water reservoir of the Ria Formosa (south Portugal)

Using a top-down modelling approach, a balanced trophic food web model of a water reservoir of the Ria Formosa lagoonal system was constructed. Few adjustments of input data were necessary to run the model since most of the parameters were estimated at the study site and the characteristics of the water reservoir allowed a high degree of control and precision in terms of sampling and data collection. Trophic levels of the 14 compartments included in the model varied between 1.0 for primary producers and detritus to 3.4 for carnivorous fish and the 14 groups were aggregated in a food chain with six trophic levels. The water reservoir has a detritus based food chain, with the majority of the biomass concentrated in the first two levels, the producers level and the herbivore/detritivore level (97.6%). The transfer efficiencies were low, and decreased with increasing level number, varying between 6.0 and 0.2%. The degree of "ecosystem maturity" was difficult to establish, but several parameters indicate that it could be high. The water reservoir studied, which has similar environmental and ecological characteristics as the Ria Formosa lagoon. is near its carrying capacity. (C) 2004, Elsevier B.V. All rights reserved.

Communication across cultures? An intercultural approach to customer service in the hotel industry: a study with globally branded hotels in the United Kingdom

In a professional and business-social context such as that of global hotel brands in the United Kingdom, intercultural communication, contacts and relationships are found at the heart of daily operations and of customer service. A large part of the clientele base of hotels in the United Kingdom is formed by individuals who belong to different cultural groups that travel in the country either for leisure or business. At the same time, the global workforce which is recruited in the hotel industry in the United Kingdom is a reality here to stay. Global travelling and labor work mobility are phenomena which have been generated by changes which occur on a socio-economic, cultural and political level due to the phenomenon of globalization. The hotel industry is therefore well acquainted with the essence of different cultures either to be accommodated within hotel premises, as in the case of external customers, or of diversity management where different cultures are recruited in the hotel industry, as in the case of internal customers. This thesis derives from research conducted on eight different global hotel brands in the United Kingdom in particular, with reference to three, four and five star categories. The research aimed to answer the question of how hotels are organized in order to address issues of intercultural communication during customer service and if intercultural barriers arise during the intercultural interaction of hotel staff and global customers. So as to understand how global hotel brands operate the research carried out focused in three main areas relating to each hotel: organizational culture, customer service–customer care and intercultural issues. The study utilized qualitative interviews with hotel management staff and non-management staff from different cultural backgrounds, public space observations between customers and staff during check-in and checkout in the reception area and during dining at the café-bar and restaurant. Thematic analysis was also applied to the official web page of each hotel and to job advertisements to enhance the findings from the interviews and the observations. For the process of analysis of the data interpretive (hermeneutic) phenomenology of Martin Heidegger has been applied. Generally, it was found that hotel staff quite often feel perplexed by how to deal with and how to overcome, for instance, language barriers and religious issues and how to interpret non verbal behaviors or matters on food culture relating to the intercultural aspect of customer service. In addition, it was interesting to find that attention to excellent customer service on the part of hotel staff is a top organizational value and customer care is a priority. Despite that, the participating hotel brands appear to have not yet, realized how intercultural barriers can affect the daily operation of the hotel, the job performance and the psychology of hotel staff. Employees indicated that they were keen to receive diversity training, provided by their organizations, so as to learn about different cultural needs and expand their intercultural skills. The notion of diversity training in global hotel brands is based on the sense that one of the multiple aims of diversity management as a practice and policy in the workplace of hotels is the better understanding of intercultural differences. Therefore global hotel brands can consider diversity training as a practice which will benefit their hotel staff and clientele base at the same time. This can have a distinctive organizational advantage for organizational affairs in the hotel industry, with potential to influence the effectiveness and performance of hotels.

Comparazione performance di un'applicazione enterprise basata su service mesh

Ultimamente si stanno sviluppando tecnologie per rendere più efficiente la virtualizzazione a livello di sistema operativo, tra cui si cita la suite Docker, che permette di gestire processi come se fossero macchine virtuali. Inoltre i meccanismi di clustering, come Kubernetes, permettono di collegare macchine multiple, farle comunicare tra loro e renderle assimilabili ad un server monolitico per l'utente esterno. Il connubio tra virtualizzazione a livello di sistema operativo e clustering permette di costruire server potenti quanto quelli monolitici ma più economici e possono adattarsi meglio alle richieste esterne. Data l'enorme mole di dati e di potenza di calcolo necessaria per gestire le comunicazioni e le interazioni tra utenti e servizi web, molte imprese non possono permettersi investimenti su un server proprietario e la sua manutenzione, perciò affittano le risorse necessarie che costituiscono il cosiddetto "cloud", cioè l'insieme di server che le aziende mettono a disposizione dei propri clienti. Il trasferimento dei servizi da macchina fisica a cloud ha modificato la visione che si ha dei servizi stessi, infatti non sono più visti come software monolitici ma come microservizi che interagiscono tra di loro. L'infrastruttura di comunicazione che permette ai microservizi di comunicare è chiamata service mesh e la sua suddivisione richiama la tecnologia SDN. È stato studiato il comportamento del software di service mesh Istio installato in un cluster Kubernetes. Sono state raccolte metriche su memoria occupata, CPU utilizzata, pacchetti trasmessi ed eventuali errori e infine latenza per confrontarle a quelle ottenute da un cluster su cui non è stato installato Istio. Lo studio dimostra che, in un cluster rivolto all'uso in produzione, la service mesh offerta da Istio fornisce molti strumenti per il controllo della rete a scapito di una richiesta leggermente più alta di risorse hardware.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Empirical ontology design patterns

Knowledge graphs (KGs) and ontologies have been widely adopted for modelling numerous domains. However, understanding the content of an ontology/KG is far from straightforward: existing methods partially address this issue. This thesis is based on the assumption that identifying the Ontology Design Patterns (ODPs) in an ontology or a KG contributes to address this problem. Most times, the reused ODPs are not explicitly annotated, or their reuse is unintentional. Therefore, there is a challenge to automatically identify ODPs in existing ontologies and KGs, which is the main focus of this research work. This thesis analyses the role of ODPs in ontology engineering, through experiences in actual ontology projects, placing this analysis in the context of existing ontology reuse approaches. Moreover, this thesis introduces a novel method for extracting empirical ODPs (EODPs) from ontologies, and a novel method for extracting EODPs from knowledge graphs, whose schemas are implicit. The first method groups the extracted EODPs in clusters: conceptual components. Each conceptual component represents a modelling problem, e.g. representing collections. As EODPs are fragments possibly extracted from different ontologies, some of them will fall in the same cluster, meaning that they are implemented solutions to the same modelling problem. EODPs and conceptual components enable the empirical observation and comparison of modelling solutions to common modelling problems in different ontologies. The second method extracts EODPs from a KG as sets of probabilistic axioms/constraints involving the ontological entities instantiated. These EODPs may support KG inspection and comparison, providing insights on how certain entities are described in a KG. An additional contribution of this thesis is an ontology for annotating ODPs in ontologies and KGs.

Connecting works of art within the semantic web of symbolic meanings

My doctoral research is about the modelling of symbolism in the cultural heritage domain, and on connecting artworks based on their symbolism through knowledge extraction and representation techniques. In particular, I participated in the design of two ontologies: one models the relationships between a symbol, its symbolic meaning, and the cultural context in which the symbol symbolizes the symbolic meaning; the second models artistic interpretations of a cultural heritage object from an iconographic and iconological (thus also symbolic) perspective. I also converted several sources of unstructured data, a dictionary of symbols and an encyclopaedia of symbolism, and semi-structured data, DBpedia and WordNet, to create HyperReal, the first knowledge graph dedicated to conventional cultural symbolism. By making use of HyperReal's content, I showed how linked open data about cultural symbolism could be utilized to initiate a series of quantitative studies that analyse (i) similarities between cultural contexts based on their symbologies, (ii) broad symbolic associations, (iii) specific case studies of symbolism such as the relationship between symbols, their colours, and their symbolic meanings. Moreover, I developed a system that can infer symbolic, cultural context-dependent interpretations from artworks according to what they depict, envisioning potential use cases for museum curation. I have then re-engineered the iconographic and iconological statements of Wikidata, a widely used general-domain knowledge base, creating ICONdata: an iconographic and iconological knowledge graph. ICONdata was then enriched with automatic symbolic interpretations. Subsequently, I demonstrated the significance of enhancing artwork information through alignment with linked open data related to symbolism, resulting in the discovery of novel connections between artworks. Finally, I contributed to the creation of a software application. This application leverages established connections, allowing users to investigate the symbolic expression of a concept across different cultural contexts through the generation of a three-dimensional exhibition of artefacts symbolising the chosen concept.

Ship performance modelling for least-CO2 emission routes

Decarbonization of maritime transport requires immediate action. In the short term, ship weather routing can provide greenhouse gas emission reductions, even for existing ships and without retrofitting them. Weather routing is based on making optimal use of both envi- ronmental information and knowledge about vessel seakeeping and performance. Combining them at a state-of-the-art level and making use of path planning in realistic conditions can be challenging. To address these topics in an open-source framework, this thesis led to the development of a new module called bateau , and to its combination with the ship routing model VISIR. bateau includes both hull geometry and propulsion modelling for various vessel types. It has two objectives: to predict the sustained speed in a seaway and to estimate the CO2 emission rate during the voyage. Various semi-empirical approaches were used in bateau to predict the ship hydro- and aerodynamical resistance in both head and oblique seas. Assuming that the ship sails at a constant engine load, the involuntary speed loss due to waves was estimated. This thesis also attempted to clarify the role played by the actual representation of the sea state. In particular, the influence of the wave steepness parameter was assessed. For dealing with ships with a greater superstructure, the wind added resistance was also estimated. Numerical experiments via bateau were conducted for both a medium and a large-size container ships, a bulk-carrier, and a tanker. The simulations of optimal routes were carried out for a feeder containership during voyages in the North Indian Ocean and in the South China Sea. Least-CO2 routes were compared to the least-distance ones, assessing the relative CO2 savings. Analysis fields from the Copernicus Marine Service were used in the numerical experiments.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.