Efficient Memory-Enhanced Transformer for Long-Document Summarization in Low-Resource Regimes

Long document summarization poses obstacles to current generative transformer-based models because of the broad context to process and understand. Indeed, detecting long-range dependencies is still challenging for today’s state-of-the-art solutions, usually requiring model expansion at the cost of an unsustainable demand for computing and memory capacities. This paper introduces Emma, a novel efficient memory-enhanced transformer-based architecture. By segmenting a lengthy input into multiple text fragments, our model stores and compares the current chunk with previous ones, gaining the capability to read and comprehend the entire context over the whole document with a fixed amount of GPU memory. This method enables the model to deal with theoretically infinitely long documents, using less than 18 and 13 GB of memory for training and inference, respectively. We conducted extensive performance analyses and demonstrate that Emma achieved competitive results on two datasets of different domains while consuming significantly less GPU memory than competitors do, even in low-resource settings

The XFM view adaptation mechanism: An essential component for XML data warehouses

In the past few years, with many organisations providing web services for business and communication purposes, large volumes of XML transactions take place on a daily basis. In many cases, organisations maintain these transactions in their native XML format due to its flexibility for xchanging data between heterogeneous systems. This XML data provides an important resource for decision support systems. As a consequence, XML technology has slowly been included within decision support systems of data warehouse systems. The problem encountered is that existing native XML database systems suffer from poor performance in terms of managing data volume and response time for complex analytical queries. Although materialised XML views can be used to improve the performance for XML data warehouses, update problems then become the bottleneck of using materialised views. Specifically, synchronising materialised views in the face of changing view definitions, remains a significant issue. In this dissertation, we provide a method for XML-based data warehouses to manage updates caused by the change of view definitions (view redefinitions), which is referred to as the view adaptation problem. In our approach, views are defined using XPath and then modelled using a set of novel algebraic operators and fragments. XPath views are integrated into a single view graph called the XML Fragment Materialisation (XFM) View Graph, where common parts between different views are shared and appear only once in the graph. Fragments within the view graph can be selected for materialisation to facilitate the view adaptation process. While changes are applied, our view adaptation algorithms can quickly determine what part of the XFM view graph is affected. The adaptation algorithms then perform a structural adaptation to update the view graph, followed by data adaptation to update materialised fragments

Student Expectations: The effect of student background and experience

CONTEXT The perspectives and previous experiences that students bring to their programs of study can affect their approaches to study and the depth of learning that they achieve Prosser & Trigwell, 1999; Ramsden, 2003). Graduate outcomes assume the attainment of welldeveloped independent learning skills which can be transferred to the work-place. PURPOSE This 5-year longitudinal study investigates factors influencing students’ approaches to learning in the fields of Engineering, Software Engineering, and Computer Science, at two higher education institutes delivering programs of various levels in Australia and New Zealand. The study aims to track the development of student approaches to learning as they progress through their program. Through increased understanding of students’ approaches, faculty will be better able to design teaching and learning strategies to meet the needs of an increasingly diverse student body. This paper reports on the first stage of the project. APPROACH In August 2017, we ran a pilot of our survey using the Revised Study Process Questionnaire(Biggs, Kember, & Leung, 2001) and including some additional questions related to student demographics and motivation for undertaking their current program of study. Data were analysed to evaluate the usefulness of data collected and to understand the demographics of the student cohort. Over the period of the research, data will be collected using the questionnaire and through focus groups and interviews. RESULTS Participants provided a representative sample, and the data collected was reasonable, allowing the questionnaire design to be confirmed. CONCLUSIONS At this preliminary stage, the study has provided insight into the student demographics at both institutes and identified aspects of students’ modes of engagement with learning. Some areas for improvement of the questionnaire have been identified, which will be implemented for the main body of the study

Personalizing the web: A tool for empowering end-users to customize the web through browser-side modification

167 p.Web applications delegate to the browser the final rendering of their pages. Thispermits browser-based transcoding (a.k.a. Web Augmentation) that can be ultimately singularized for eachbrowser installation. This creates an opportunity for Web consumers to customize their Web experiences.This vision requires provisioning adequate tooling that makes Web Augmentation affordable to laymen.We consider this a special class of End-User Development, integrating Web Augmentation paradigms.The dominant paradigm in End-User Development is scripting languages through visual languages.This thesis advocates for a Google Chrome browser extension for Web Augmentation. This is carried outthrough WebMakeup, a visual DSL programming tool for end-users to customize their own websites.WebMakeup removes, moves and adds web nodes from different web pages in order to avoid tabswitching, scrolling, the number of clicks and cutting and pasting. Moreover, Web Augmentationextensions has difficulties in finding web elements after a website updating. As a consequence, browserextensions give up working and users might stop using these extensions. This is why two differentlocators have been implemented with the aim of improving web locator robustness

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together

Moderating effects of government support on the relationship between organizational innovativeness, culture and sustainable construction among Malaysian contractors

Drawing upon organizational readiness for change and resource-based view theories, this study examined the role of government support in moderating the effects of organizational innovativeness and organizational culture on sustainable construction among Malaysian large contractors (the G7 contractors). A total of 172 contractors from the eleven states in peninsula Malaysia participated in the survey. The data collected were initially screened using SPSS (version 21), while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesized paths in this study. Specifically, the results indicated that the extent of sustainable construction among Malaysian large contractors is high (mean score: 3.95). The empirical evidence also supported the hypothesized direct effects of organizational innovativeness and organizational culture on sustainable construction. However, government support was found to be negatively but significantly related to sustainable construction. There also was a stronger positive relationship between organizational innovativeness and sustainable construction, to such an extent that this relationship becomes stronger (i.e. more positive) for contractors that are being aided by the government than it is for those that are disadvantaged in that regard. Similarly, the result regarding the moderating effect of government support on the relationship between organizational culture and sustainable construction was supported. Generally, these findings supported the view that government support has a strong contingent effect on the influence of contractors’ innovativeness and culture on sustainability adoption in construction project execution. Therefore, to enhance sustainable construction adoption, more efforts are suggested to be applied to developing and utilising organizational innovativeness and organizational cultural dimensions, while more government support is also encouraged. Some limitations of the study are indicated, suggesting opportunities for future research