Generating natural language texts from business process models

Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

The role of metacognition in the development of EFL learners’ listening skill

This study investigated the impact of metacognitive instruction on the listening skill, and metacognitive knowledge of a group of male students (N = 30) who were learning English as a Foreign Language (EFL) in Iran. The study participants spoke Persian as a first language and were high-intermediate EFL learners. The participants received a guided lesson plan in metacognition (planning, monitoring, and evaluation) through a pedagogical cycle approach over a semester (eight weeks). International English Language Testing System listening tests (practice) were used to track the participants’ listening performance. Participants also completed a Metacognitive Awareness Listening Questionnaire, which examined their use of metacognitive awareness when engaged in listening tasks. Results indicated that the students improved their listening skill after being taught about metacognition; however, no significant use of metacognitive awareness was reported. This study concludes with a discussion of some potential implications, and provides scope for future research.

Broken gates and leaky graves : spectral language and Australia's ghost stories

Ghost stories are unusual amongst supernatural literatures in their modelling of a recognisable, mimetic reality interrupted or infiltrated by immaterial forces. In its discussion of Australian ghost stories, this thesis advances a new approach to ghost narratives which seeks to model and articulate the mechanics of ghosts and hauntings as something reliant on and engaged with the material and the mundane.

Understanding the information literacy experiences of EFL (English as a Foreign Language) students

This thesis investigated the information literacy experiences of EFL (English as a Foreign Language) students in a higher education institution in the United Arab Emirates (UAE). Phenomenography was used to investigate how EFL students' 'used information to learn' (ie. information literacy). The study revealed that EFL students' experienced information literacy across four categories and had varying experiences of information and learning. The research also showed that EFL students' faced a number of challenges and barriers due to language that impacted on their experiences of reading, understanding, accessing and translating information.

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Design of a garment for data collection of toddler language and physical activity

Design process phases of development, evaluation and implementation were used to create a garment to simultaneously collect reliable data of speech production and intensity of movement of toddlers (18-36 months). A series of prototypes were developed and evaluated that housed accelerometer-based motion sensors and a digital transmitter with microphone. The approved test garment was a top constructed from loop-faced fabric with interior pockets to house devices. Extended side panels allowed for sizing. In total, 56 toddlers (28 male; 28 female; 16-36 months of age) participated in the study providing pilot and baseline data. The test garment was effective in collecting data as evaluated for accuracy and reliability using ANOVA for accelerometer data, transcription of video for type of movement, and number and length of utterances for speech production. The data collection garment has been implemented in various studies across disciplines.

Educational paradox : the hidden obstacles to the integration of mobile phones in the language classroom

This paper reports on the findings of an international telecollaboration study using Facebook, in which teachers studying in M. Ed programs in Australia and Greece, discussed the use of mobile phones in language classrooms. Results suggest that invisible barriers exist in the use of mobile phones in the classroom, including bans on use in schools, lack of familiarity with educational uses for mobile phones, and negative perceptions about mobile phones specifically in terms of classroom management.

An attack-localizing watermarking scheme for natural language documents

We present a text watermarking scheme that embeds a bitstream watermark Wi in a text document P preserving the meaning, context, and flow of the document. The document is viewed as a set of paragraphs, each paragraph being a set of sentences. The sequence of paragraphs and sentences used to embed watermark bits is permuted using a secret key. Then, English language sentence transformations are used to modify sentence lengths, thus embedding watermarking bits in the Least Significant Bits (LSB) of the sentences’ cardinalities. The embedding and extracting algorithms are public, while the secrecy and security of the watermark depends on a secret key K. The probability of False Positives is extremely small, hence avoiding incidental occurrences of our watermark in random text documents. Majority voting provides security against text addition, deletion, and swapping attacks, further reducing the probability of False Positives. The scheme is secure against the general attacks on text watermarks such as reproduction (photocopying, FAX), reformatting, synonym substitution, text addition, text deletion, text swapping, paragraph shuffling and collusion attacks.