A random forest system combination approach for error detection in digital dictionaries

When digitizing a print bilingual dictionary, whether via optical character recognition or manual entry, it is inevitable that errors are introduced into the electronic version that is created. We investigate automating the process of detecting errors in an XML representation of a digitized print dictionary using a hybrid approach that combines rule-based, feature-based, and language model-based methods. We investigate combining methods and show that using random forests is a promising approach. We find that in isolation, unsupervised methods rival the performance of supervised methods. Random forests typically require training data so we investigate how we can apply random forests to combine individual base methods that are themselves unsupervised without requiring large amounts of training data. Experiments reveal empirically that a relatively small amount of data is sufficient and can potentially be further reduced through specific selection criteria.Comment: 9 pages, 7 figures, 10 tables; appeared in Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data, April 201

Numerical investigation of novel microwave applicators based on zero-order mode resonance for hyperthermia treatment of cancer

This paper characterizes three novel microwave applicators based on zero-order mode resonators for use in hyperthermia treatment of cancer. The radiation patterns are studied with numerical simulations in muscle tissue-equivalent model at 434 MHz. The relative performance of the applicators is compared in terms of reflection coefficient, current distribution, power deposition (SAR) pattern, effective field size in 2D and 3D tissue volumes, and penetration depth. One particular configuration generated the most uniform SAR pattern, with 25% SAR covering 84 % of the treatment volume extending to 1 cm depth under the aperture, while remaining above 58% coverage as deep as 3 cm under the aperture. Recommendations are made to further optimize this structure

Big Data, Digitization, and Social Change (Ubiquity Symposium)

The term “big data” is something of a misnomer. Every generation of computers since the 1950s has been confronted with problems where data was way too large for the memory and processing power available. This seemed like an inconvenience of the technology that would someday be resolved when the next generation of computers came along. So what is different about big data today? The revolution is happening at the convergence of two trends: the expansion of the internet into billions of computing devices, and the digitization of almost everything. The internet gives us access to vast amounts of data. Digitization creates digital representations for many things once thought to be beyond the reach of computing technology. The result is an explosion of innovation of network-based big data applications and the automation of cognitive tasks. This revolution is introducing what Brynjolfsson and McAfee call the “Second Machine Age.” This symposium will examine this revolution from a number of angles

Establishing microbial baselines to identify indicators of coral reef health

Microorganisms make a significant contribution to reef ecosystem health and resilience via their critical role in mediating nutrient transformations, their interactions with macro-organisms and their provision of chemical cues that underpin the recruitment of diverse reef taxa. However, environmental changes often cause compositional and functional shifts in microbial communities that can have flow-on consequences for microbial-mediated processes. These microbial alterations may impact the health of specific host organisms and can have repercussions for the functioning of entire coral ecosystems. Assessing changes in reef microbial communities should therefore provide an early indicator of ecosystem impacts and would underpin the development of diagnostic tools that could help forecast shifts in coral reef health under different environmental states. Monitoring, management and active restoration efforts have recently intensified and diversified in response to global declines in coral reef health. Here we propose that regular monitoring of coral reef microorganisms could provide a rapid and sensitive platform for identifying declining ecosystem health that can complement existing management frameworks. By summarising the most common threats to coral reefs, with a particular focus on the Great Barrier Reef, and elaborating on the role of microbes in coral reef health and ecosystem stability, we highlight the diagnostic applicability of microbes in reef management programs. Fundamental to this objective is the establishment of microbial baselines for Australia's coral reefs.AIMS@JCU PhD Scholarship; GBRMPA Science Management Research Award; Advance Queensland PhD Scholarship; Portuguese Science and Technology Foundation (FCT) [SFRH/BPD/110285/2015

Q-analysis based clustering of online news

With online publication and social media taking the main role in dissemination of news, and with the decline of traditional printed media, it has become necessary to devise ways to automatically extract meaningful information from the plethora of sources available and to make that information readily available to interested parties. In this paper we present a method of automated analysis of the underlying structure of online newspapers based on Q-analysis and modularity optimisation. We show how the combination of the two strategies allows for the identification of well defined news clusters that are free of noise (unrelated stories) and provide automated clustering of information on trending topics on news published online

Differences and reasons in IASB accounting standards between small and large companies

This paper studies the main differences in accounting standards of the International Accounting Standards Board (IASB) between small and large companies, materialised in the dissimilarities between the International Financial Reporting Standard for Small and Medium-sized Entities and the full International Financial Reporting Standards, as of 2010. Another element of this project is the analysis of the reasons behind the differences between the two aforementioned frameworks, which intends to expose the rationale and the mindset that led to an adaptation of the full standards in a stand-alone document designed for small companies

IT governance enablers for an efficient IoT implementation

IoT is considered to be one of the focal points for the 4.0 industry revolution because of the way it is changing the business models of each organization. IT governance is now an increasingly important tool for organizations to align their IT infrastructure with the organization's business objectives. IT governance has been used to help implement new technologies using the best practices such as COBIT, which defines a number of enablers that facilitate the implementation, identification and management of IT. This research aims to explore and define the most suitable enablers for an IoT implementation. These objectives will be achieved through the Design Science Research methodology, which incorporates two literature reviews, a Delphi method and, finally, a semi-structured interview. With a first systematic review of the literature, it was possible to identify the main enablers to implement IoT. Next, the list was improved using the Delphi method, gathering expert opinion. In the Delphi method, the level of agreement was verified to create exclusion criteria and a level of efficiency in each recommendation. Finally, a specialist was interviewed to demonstrate the applicability and validation of the proposed artifact in the various IoT projects implemented by his organization. At the end, a final list of enablers for IoT implementation is provided. The results indicate that data privacy, data protection, and data analysis are currently the best recommendations to be considered in an IoT implementation because they increase the efficiency of the solution and increase the credibility of the data obtained. Future work and limitations are detailed in the end.A IoT é considerada como um dos pontos fulcrais para a revolução da indústria 4.0, devido à maneira como está a alterar os modelos de negócio das organizações. A governação das TI é atualmente uma ferramenta cada vez mais importante para as organizações alinharem a sua infraestrutura tecnológica com os objetivos de negócio da organização. A governação de TI tem sido utilizada para ajudar na implementação de novas tecnologias recorrendo à utilização de boas práticas como por exemplo o COBIT, que define vários enablers que facilitam a implementação, identificação e gestão das TI. Esta investigação visa explorar e definir os enablers mais adequados para uma implementação de IoT. Estes objetivos vão ser alcançados através da metodologia Design Science Research, que incorpora duas revisões de literatura, um método Delphi e por fim uma entrevista semiestruturada. Com uma primeira revisão sistemática da literatura, foi possível identificar os principais enablers para implementar IoT. De seguida, a lista foi melhorada utilizando o método Delphi, recolhendo a opinião de especialistas. No método Delphi, verificou-se o nível de concordância para criar critérios de exclusão e um nível de eficiência em cada recomendação. Finalmente, um especialista foi entrevistado para demonstrar a aplicabilidade e validar o artefacto proposto nos diversos projetos de IoT implementados pela sua organização. No final a lista de enablers para implementar IoT é fornecida. Os resultados indicam que atualmente, a privacidade de dados, a proteção de dados e a análise de dados são as melhores recomendações a serem consideradas numa implementação de IoT, porque aumentam a eficiência da solução e aumentam a credibilidade dos dados obtidos. Trabalho futuro e limitações são detalhadas no final

A comparison of substance use stigma and health stigma in a population of veterans with co-occurring mental health and substance use disorders

OBJECTIVE: This pilot study examined whether substance use or mental illness was more stigmatizing among individuals with co-occurring mental health and substance abuse problems. METHODS: This study included 48 individuals with co-occurring substance use and mental health problems enrolled in a Substance Abuse and Mental Health Services funded treatment program. Subjects received a baseline assessment that included addiction, mental health, and stigma measures. RESULTS: The sample consisted primarily of White males with an average age of 38 years. Substance abuse was found to be more stigmatizing than mental illness, F(1, 47) = 14.213, p < .001, and stigma varied across four different levels of stigma (Aware, Agree, Apply, and Harm), F(2.099, 98.675) = 117.883, p < .001. The interaction between type and level of stigma was also significant, F(2.41, 113.284) = 20.250, p < .001, indicating that differences in reported stigma between types varied across levels of stigma. Post hoc tests found a significant difference between all levels of stigma except for the comparison between Apply and Harm. Reported stigma was significantly higher for substance abuse than mental illness at the Aware and Agree levels. In addition, pairwise comparisons found significant differences between all levels of stigma with the exception of the comparison between Apply and Harm, indicating a pattern whereby reported stigma generally decreased from the first level (Aware stage) to subsequent levels. CONCLUSIONS: These results have important implications for treatment, suggesting the need to incorporate anti-stigma interventions for individuals with co-occurring disorders with a greater focus on substance abuse