AndroMedia - Towards a Context-aware Mobile Music Recommender

Portable music players have made it possible to listen to a personal collection of music in almost every situation, and they are often used during some activity to provide a stimulating audio environment. Studies have demonstrated the effects of music on the human body and mind, indicating that selecting music according to situation can, besides making the situation more enjoyable, also make humans perform better. For example, music can boost performance during physical exercises, alleviate stress and positively affect learning. We believe that people intuitively select different types of music for different situations. Based on this hypothesis, we propose a portable music player, AndroMedia, designed to provide personalised music recommendations using the user’s current context and listening habits together with other user’s situational listening patterns. We have developed a prototype that consists of a central server and a PDA client. The client uses Bluetooth sensors to acquire context information and logs user interaction to infer implicit user feedback. The user interface also allows the user to give explicit feedback. Large user interface elements facilitate touch-based usage in busy environments. The prototype provides the necessary framework for using the collected information together with other user’s listening history in a context- enhanced collaborative filtering algorithm to generate context-sensitive recommendations. The current implementation is limited to using traditional collaborative filtering algorithms. We outline the techniques required to create context-aware recommendations and present a survey on mobile context-aware music recommenders found in literature. As opposed to the explored systems, AndroMedia utilises other users’ listening habits when suggesting tunes, and does not require any laborious set up processes.

Field Flow Sensitive Pointer and Escape Analysis for Java Using Heap Array SSA

Context sensitive pointer analyses based on Whaley and Lam’s bddbddb system have been shown to scale to large Java programs. We provide a technique to incorporate flow sensitivity for Java fields into one such analysis and obtain an escape analysis based on it. First, we express an intraprocedural field flow sensitive analysis, using Fink et al.’s Heap Array SSA form in Datalog. We then extend this analysis interprocedurally by introducing two new φ functions for Heap Array SSA Form and adding deduction rules corresponding to them. Adding a few more rules gives us an escape analysis. We describe two types of field flow sensitivity: partial (PFFS) and full (FFFS), the former without strong updates to fields and the latter with strong updates. We compare these analyses with two different (field flow insensitive) versions of Whaley-Lam analysis: one of which is flow sensitive for locals (FS) and the other, flow insensitive for locals (FIS). We have implemented this analysis on the bddbddb system while using the SOOT open source framework as a front end. We have run our analysis on a set of 15 Java programs. Our experimental results show that the time taken by our field flow sensitive analyses is comparable to that of the field flow insensitive versions while doing much better in some cases. Our PFFS analysis achieves average reductions of about 23% and 30% in the size of the points-to sets at load and store statements respectively and discovers 71% more “caller-captured” objects than FIS.

practical type checking of functions defined on context-free languages

A type checking method for the functional language LFC is presented. A distinct feature of LFC is that it uses Context-Free (CF) languages as data types to represent compound data structures. This makes LFC a dynamically typed language. To improve efficiency, a practical type checking method is presented, which consists of both static and dynamic type checking. Although the inclusion relation of CF.languages is not decidable,a special subset of the relation is decidable, i.e., the sentential form relation, which can be statically checked.Moreover, most of the expressions in actual LFC programs appear to satisfy this relation according to the statistic data of experiments. So, despite that the static type checking is not complete, it undertakes most of the type checking task. Consequently the run-time efficiency is effectively improved. Another feature of the type checking is that it converts the expressions with implicit structures to structured representation. Structure reconstruction technique is presented.

pattern matching compilation of functions defined in context-free languages

LFC is a functional language based on recursive functions defined in context-free languages. In this paper, a new pattern matching algorithm for LFC is presented, which can represent a sequence of patterns as an integer by an encoding method. It is a rather simple method and produces efficient case-expressions for pattern matching definitions of LFC. The algorithm can also be used for other functional languages, but for nested patterns it may become complicated and further studies are needed.

function definition language fdl and its implementation

A Function Definition Language (FDL) is presented. Though designed for describing specifications, FDL is also a general-purpose functional programming language. It uses context-free language as data type, supports pattern matching definition of functions, offers several function definition forms, and is executable. It is shown that FDL has strong expressiveness, is easy to use and describes algorithms concisely and naturally. An interpreter of FDL is introduced. Experiments and discussion are included.

yet another meta-language for programming language processing

The formal specification language LFC was designed to support formal specification acquisition. However, it is yet suited to be used as a meta-language for specifying programming language processing. This paper introduces LFC as a meta-language, and compares it with ASF+SDF, an algebraic specification formalism that can also be used to programming languages.

facilitating formal specification acquisition by using recursive functions on context-free languages

Although formal specification techniques are very useful in software development, the acquisition of formal specifications is a difficult task. This paper presents the formal specification language LFC, which is designed to facilitate the acquisition and validation of formal specifications. LFC uses context-free languages for syntactic aspect and relies on a new kind of recursive functions, i.e. recursive functions on context-free languages, for semantic aspect of specifications. Construction and validation of LFC specifications are machine-aided. The basic ideas behind LFC, the main aspects of LFC, and the use of LFC and illustrative examples are described.

Deconstructing 'Mono'-Lingualism: considerations of value for 'English' 'language' education in a global setting.

Traditionally, language speakers are categorised as mono-lingual, bilingual, or multilingual. It is traditionally assumed in English language education that the ‘lingual’ is something that can be ‘fixed’ in form, written down to be learnt, and taught. Accordingly, the ‘mono’-lingual will have a ‘fixed’ linguistic form. Such a ‘form’ differs according to a number of criteria or influences including region or ‘type’ of English (for example, World Englishes) but is nevertheless assumed to be a ‘form’. ‘Mono-lingualism’ is defined and believed, traditionally, to be ‘speaking one language’; wherever that language is; or whatever that language may be. In this chapter, grounded in an individual subjective philosophy of language, we question this traditional definition. Viewing language from the philosophical perspectives such as those of Bakhtin and Voloshinov, we argue that the prominence of ‘context’ and ‘consciousness’ in language means that to ‘fix’ the form of a language goes against the very spirit of how it is formed and used. We thus challenge the categorisation of ‘mono’-lingualism; proposing that such a categorisation is actually a category error, or a case ‘in which a property is ascribed to a thing that could not possibly have that property’ (Restivo, 2013, p. 175), in this case the property of ‘mono’. Using this proposition as a starting point, we suggest that more time be devoted to language in its context and as per its genuine use as a vehicle for consciousness. We theorise this can be done through a ‘literacy’ based approach which fronts the context of language use rather than the language itself. We outline how we envision this working for teachers, students and materials developers of English Language Education materials in a global setting. To do this we consider Scotland’s Curriculum for Excellence as an exemplar to promote conscious language use in context.

Language Teacher Education in Ireland, North and South

The European Union considers modern languages among the basic skills or key competencies required by all its citizens and is concerned to promote excellence in the teaching and learning of languages as well as greater diversity in the range of languages available to learners in the Member States, as witnessed by the recent European Commission Action Plan, Promoting Language Learning and Linguistic Diversity: An Action Plan 2004-2006. This consideration, the changing socio-cultural demography of Ireland, the need for more joined-up thinking in the context of language teaching in schools, and in the context of language teacher education in particular, form the back-drop to the paper. Among the challenges facing modern/world languages’ education in Ireland identified in the paper are, lack of a languages’ policy, lack of a languages’ strategy, and lack of an integrated language curriculum and by implication, a whole school approach to language teaching and learning. The paper refers to positive signs that are occurring in this context as well, e.g. official recognition to Irish as a working language in the European Union and in the Official Languages Act in Ireland (2003). The paper reports on the recent first ever all Ireland cross-border conference in the context of language teacher education. It outlines the background, aims, and content of the conference that includes findings from a study about the impact of autonomous language teaching and learning supported by the European Language Portfolio in the context of post-primary language teacher education in Ireland. The paper shows data from the first ever survey on language teacher education provision, policy and practice across colleges in Ireland, North and South. Initial teacher education is on the cusp of change. This paper highlights several key issues facing language teacher education. This paper has implications for Irish as well as international readers, and is aimed at supporting all those who want to bring about improvement in this important area.

The effect of context on the acquisition of vocabulary in good and poor readers

This study examined the effectiveness of context on the acquisition of new vocabulary for good and poor readers. Twentyeight Grade Three children, fourteen good readers and fourteen poor readers, took part in a word-learning task within three conditions: (1) strong sentence context, (2) weak sentence context, and (3) list condition. The primary hypothesis was that poor readers would show less learning in the list condition than good readers and that there would be no difference in the amount of learning in the sentence conditions. Results revealed that: (a) Words are read faster in sentence contexts than in 1 ist contexts; (b) more learning or greater improvement in performance occurs in list contexts and weak sentence contexts as opposed to strong sentence contexts; and (c) that most of these differences can be attributed to the build-up of meaning in sentences. Results indicated that good and poor readers learned more about words in all three condi tions. More learning and greater performance occurred in the list condition as opposed to the two sentence conditions for both subject groups. However, the poor readers learned significantly more about words in both the list condition and the weak sentence condition than the good readers.

Systems of Parallel Communicating Restarting Automata

In der vorliegenden Dissertation werden Systeme von parallel arbeitenden und miteinander kommunizierenden Restart-Automaten (engl.: systems of parallel communicating restarting automata; abgekürzt PCRA-Systeme) vorgestellt und untersucht. Dabei werden zwei bekannte Konzepte aus den Bereichen Formale Sprachen und Automatentheorie miteinander vescrknüpft: das Modell der Restart-Automaten und die sogenannten PC-Systeme (systems of parallel communicating components). Ein PCRA-System besteht aus endlich vielen Restart-Automaten, welche einerseits parallel und unabhängig voneinander lokale Berechnungen durchführen und andererseits miteinander kommunizieren dürfen. Die Kommunikation erfolgt dabei durch ein festgelegtes Kommunikationsprotokoll, das mithilfe von speziellen Kommunikationszuständen realisiert wird. Ein wesentliches Merkmal hinsichtlich der Kommunikationsstruktur in Systemen von miteinander kooperierenden Komponenten ist, ob die Kommunikation zentralisiert oder nichtzentralisiert erfolgt. Während in einer nichtzentralisierten Kommunikationsstruktur jede Komponente mit jeder anderen Komponente kommunizieren darf, findet jegliche Kommunikation innerhalb einer zentralisierten Kommunikationsstruktur ausschließlich mit einer ausgewählten Master-Komponente statt. Eines der wichtigsten Resultate dieser Arbeit zeigt, dass zentralisierte Systeme und nichtzentralisierte Systeme die gleiche Berechnungsstärke besitzen (das ist im Allgemeinen bei PC-Systemen nicht so). Darüber hinaus bewirkt auch die Verwendung von Multicast- oder Broadcast-Kommunikationsansätzen neben Punkt-zu-Punkt-Kommunikationen keine Erhöhung der Berechnungsstärke. Desweiteren wird die Ausdrucksstärke von PCRA-Systemen untersucht und mit der von PC-Systemen von endlichen Automaten und mit der von Mehrkopfautomaten verglichen. PC-Systeme von endlichen Automaten besitzen bekanntermaßen die gleiche Ausdrucksstärke wie Einwegmehrkopfautomaten und bilden eine untere Schranke für die Ausdrucksstärke von PCRA-Systemen mit Einwegkomponenten. Tatsächlich sind PCRA-Systeme auch dann stärker als PC-Systeme von endlichen Automaten, wenn die Komponenten für sich genommen die gleiche Ausdrucksstärke besitzen, also die regulären Sprachen charakterisieren. Für PCRA-Systeme mit Zweiwegekomponenten werden als untere Schranke die Sprachklassen der Zweiwegemehrkopfautomaten im deterministischen und im nichtdeterministischen Fall gezeigt, welche wiederum den bekannten Komplexitätsklassen L (deterministisch logarithmischer Platz) und NL (nichtdeterministisch logarithmischer Platz) entsprechen. Als obere Schranke wird die Klasse der kontextsensitiven Sprachen gezeigt. Außerdem werden Erweiterungen von Restart-Automaten betrachtet (nonforgetting-Eigenschaft, shrinking-Eigenschaft), welche bei einzelnen Komponenten eine Erhöhung der Berechnungsstärke bewirken, in Systemen jedoch deren Stärke nicht erhöhen. Die von PCRA-Systemen charakterisierten Sprachklassen sind unter diversen Sprachoperationen abgeschlossen und einige Sprachklassen sind sogar abstrakte Sprachfamilien (sogenannte AFL's). Abschließend werden für PCRA-Systeme spezifische Probleme auf ihre Entscheidbarkeit hin untersucht. Es wird gezeigt, dass Leerheit, Universalität, Inklusion, Gleichheit und Endlichkeit bereits für Systeme mit zwei Restart-Automaten des schwächsten Typs nicht semientscheidbar sind. Für das Wortproblem wird gezeigt, dass es im deterministischen Fall in quadratischer Zeit und im nichtdeterministischen Fall in exponentieller Zeit entscheidbar ist.

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.

Young learners : teachers' questions and prompts as opportunities for children's language development

One highly regarded context for language learning is book reading, as teachers engage children in discussions around texts read. However, there is considerable variation in teachers’ patterns of talk that mediate this learning with preschool children’s oral language development dependent on the opportunities for engagement in language use provided by teachers. To explore the affordances of talk interactions within book reading a systematic analysis of teachers’ questions and children’s responses was undertaken. Results of this analysis show that the highest proportion of questions asked by this group of 18 preschool teachers were closed questions with a small proportion of open teaching questions asked. However, while open questions provided the most substantial opportunities for children’s extended talk, the range of questions asked provided opportunities for preschool teachers to extend children’s responses, support children’s understanding of the text, develop vocabulary and world knowledge, and to model more complex language structures.

A shadow-like task migration model based on context semantics for mobile and pervasive environments

Pervasive computing is a user-centric mobile computing paradigm, in which tasks should be migrated over different platforms in a shadow-like way when users move around. In this paper, we propose a context-sensitive task migration model that recovers program states and rebinds resources for task migrations based on context semantics through inserting resource description and state description sections in source programs. Based on our model, we design and develop a task migration framework xMozart which extends the Mozart platform in terms of context awareness. Our approach can recover task states and rebind resources in the context-aware way, as well as support multi- modality I/O interactions. The extensive experiments demonstrate that our approach can migrate tasks by resuming them from the last broken points like shadows moving along with the users.

The contours of employee voice in SMEs: the importance of context

This article develops a context-sensitive approach to analyse how and why voice operates in small- to medium-sized enterprises (SMEs), an area that remains under-theorised and under-researched. By building on a priori frameworks with proven ability to unpack complexity and take account of the wider context of SMEs, this article explores how resources (human and social capital) and constraints (product market, labour market and strategic orientation) interact to shape voice practices. The article finds significant differences between 'reported' compared with 'actual' practices in situ, and identifies different types of firms ('strategic market regulation', 'strategic market-led' and 'non-strategic market-led') along with the factors that influence the form and practice of voice. Overall, the article argues that researchers should further pursue research that appreciates the layered nature of ontology and the role played by firm context to explain complex organisational phenomena, if we are to advance our understanding of voice practices in SMEs and beyond.