The impact of morphological errors in phrase-based statistical machine translation from German and English into Swedish

We have investigated the potential for improvement in target language morphology when translating into Swedish from English and German, by measuring the errors made by a state of the art phrase-based statistical machine translation system. Our results show that there is indeed a performance gap to be filled by better modelling of inflectional morphology and compounding; and that the gap is not filled by simply feeding the translation system with more training data

Computer Aided ECG Analysis - State of the Art and Upcoming Challenges

In this paper we present current achievements in computer aided ECG analysis and their applicability in real world medical diagnosis process. Most of the current work is covering problems of removing noise, detecting heartbeats and rhythm-based analysis. There are some advancements in particular ECG segments detection and beat classifications but with limited evaluations and without clinical approvals. This paper presents state of the art advancements in those areas till present day. Besides this short computer science and signal processing literature review, paper covers future challenges regarding the ECG signal morphology analysis deriving from the medical literature review. Paper is concluded with identified gaps in current advancements and testing, upcoming challenges for future research and a bullseye test is suggested for morphology analysis evaluation.Comment: 7 pages, 3 figures, IEEE EUROCON 2013 International conference on computer as a tool, 1-4 July 2013, Zagreb, Croati

Morphology and design: reconciling intellect, intuition, and ethics in the reflective practice of architecture

This paper starts by exploring models of knowledge in order to place architectural knowledgein relation to the forms of knowledge that have been developed by other academic disciplineswithin the universities. In the light of suggestions that the low esteem in which architectureis held within the universities may be due to its basis in practice and its apparent lack of acoherent body of knowledge, the proposition is made that morphology has a special place inadvancing architectural knowledge because it is able to make the link between design and itssocial consequences. Understanding this relationship is vital if architecture is to defend itsposition as an art that is of general social relevance as opposed to being the domain of thesocially privileged. Kolb?s learning cycle is introduced as a device to track the forms of knowledgethat are essential to the reflective practice of a genuinely social architecture and to relatethese to the insights into morphology and design that have been provided by space syntaxover the past two decades. ?Sheltered? housing for older people is taken as an example of howa morphological approach can offer an enlightened critique of design guidance that articulatesthe authentic experiences of the inhabitants. The creative interplay of intellect and intuition isconsidered in relation to how morphology can help to clarify strategic design choices early onin the design process. The importance of briefing and evaluation are also stressed as essentialingredients that will enable space syntax to turn Kolb?s learning cycle into a dynamic learningprocess. The paper concludes by proposing an ethical framework for design. This paper starts by exploring models of knowledge in order to place architectural knowledgein relation to the forms of knowledge that have been developed by other academic disciplineswithin the universities. In the light of suggestions that the low esteem in which architectureis held within the universities may be due to its basis in practice and its apparent lack of acoherent body of knowledge, the proposition is made that morphology has a special place inadvancing architectural knowledge because it is able to make the link between design and itssocial consequences. Understanding this relationship is vital if architecture is to defend itsposition as an art that is of general social relevance as opposed to being the domain of thesocially privileged. Kolb?s learning cycle is introduced as a device to track the forms of knowledgethat are essential to the reflective practice of a genuinely social architecture and to relatethese to the insights into morphology and design that have been provided by space syntaxover the past two decades. ?Sheltered? housing for older people is taken as an example of howa morphological approach can offer an enlightened critique of design guidance that articulatesthe authentic experiences of the inhabitants. The creative interplay of intellect and intuition isconsidered in relation to how morphology can help to clarify strategic design choices early onin the design process. The importance of briefing and evaluation are also stressed as essentialingredients that will enable space syntax to turn Kolb?s learning cycle into a dynamic learningprocess. The paper concludes by proposing an ethical framework for design

Statistical parsing of morphologically rich languages (SPMRL): what, how and whither

The term Morphologically Rich Languages (MRLs) refers to languages in which significant information concerning syntactic units and relations is expressed at word-level. There is ample evidence that the application of readily available statistical parsing models to such languages is susceptible to serious performance degradation. The first workshop on statistical parsing of MRLs hosts a variety of contributions which show that despite language-specific idiosyncrasies, the problems associated with parsing MRLs cut across languages and parsing frameworks. In this paper we review the current state-of-affairs with respect to parsing MRLs and point out central challenges. We synthesize the contributions of researchers working on parsing Arabic, Basque, French, German, Hebrew, Hindi and Korean to point out shared solutions across languages. The overarching analysis suggests itself as a source of directions for future investigations

Humanoid Theory Grounding

In this paper we consider the importance of using a humanoid physical form for a certain proposed kind of robotics, that of theory grounding. Theory grounding involves grounding the theory skills and knowledge of an embodied artificially intelligent (AI) system by developing theory skills and knowledge from the bottom up. Theory grounding can potentially occur in a variety of domains, and the particular domain considered here is that of language. Language is taken to be another “problem space” in which a system can explore and discover solutions. We argue that because theory grounding necessitates robots experiencing domain information, certain behavioral-form aspects, such as abilities to socially smile, point, follow gaze, and generate manual gestures, are necessary for robots grounding a humanoid theory of language

Teaching English Language Learners from China

This research paper attempts to provide American teachers with important background information for teaching English language learners from China. The research is presented primarily for ESL teachers, but much of it would also be useful for any teacher or professor working with students of this description. The paper proceeds by exploring similarities and differences between 1. Chinese and English, 2. Chinese and American culture, and 3. Chinese and American education or classroom culture, considering all along the way the implications for teaching and working with these students

Transforming research on morphology into teacher practice

Research suggests that the explicit teaching of morphological principles will improve children’s spelling. Despite the fact that reference is made to morphology in English policy documents, teachers make limited use of morphology when teaching spelling, relying more heavily on phonic and visual strategies. After attending a course on role of morphemes in spelling, teachers’ own awareness of morphology increased and this was reflected in their practice. This in turn caused their pupils to make significant gains in spelling, compared to a control group. This reinforces the proposition that explicit instruction about morphemes is helpful to children’s learning. It demonstrates the fact that research can be transformed into teacher practice, but it also illustrates the difficulties. Policy documentation alone is insufficient. Professional development can effect change but this may be hard to sustain. Children’s gains are contingent on teacher’s continuing to dedicate class time to focussed intervention

Transfer learning for radio galaxy classification

In the context of radio galaxy classification, most state-of-the-art neural network algorithms have been focused on single survey data. The question of whether these trained algorithms have cross-survey identification ability or can be adapted to develop classification networks for future surveys is still unclear. One possible solution to address this issue is transfer learning, which re-uses elements of existing machine learning models for different applications. Here we present radio galaxy classification based on a 13-layer Deep Convolutional Neural Network (DCNN) using transfer learning methods between different radio surveys. We find that our machine learning models trained from a random initialization achieve accuracies comparable to those found elsewhere in the literature. When using transfer learning methods, we find that inheriting model weights pre-trained on FIRST images can boost model performance when re-training on lower resolution NVSS data, but that inheriting pre-trained model weights from NVSS and re-training on FIRST data impairs the performance of the classifier. We consider the implication of these results in the context of future radio surveys planned for next-generation radio telescopes such as ASKAP, MeerKAT, and SKA1-MID

Joint Morphological and Syntactic Disambiguation

In morphologically rich languages, should morphological and syntactic disambiguation be treated sequentially or as a single problem? We describe several efficient, probabilistically interpretable ways to apply joint inference to morphological and syntactic disambiguation using lattice parsing. Joint inference is shown to compare favorably to pipeline parsing methods across a variety of component models. State-of-the-art performance on Hebrew Treebank parsing is demonstrated using the new method. The benefits of joint inference are modest with the current component models, but appear to increase as components themselves improve