Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).

DiCER: A distributed consumer experience research method for use in public spaces

Date of Acceptance: 06/03/2015 Acknowledgement: This research was funded by NCR and the Northern Research Partnership

Patterns of weight change after the diagnosis of type 2 diabetes in Scotland and their relationship with glycaemic control, mortality and cardiovascular outcomes: a retrospective cohort study

Acknowledgements The authors would like to thank the Scottish Diabetes Research Network Epidemiology Group for granting permission to use this database. They also thank the data management team in the University of Aberdeen who were the initial conduit for access to these data and also provided validation to the various data cleaning criteria applied. Jeremy J Walker, University of Edinburgh, was invaluable for the original funding application and initial exploration of data. HSRU is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Funding Chief Scientist Office (CSO) reference number: CZG/2/571.

Control and prediction for blackouts caused by frequency collapse in smart grids

C.-W.W. is supported by a studentship funded by the College of Physical Sciences, University of Aberdeen. M.S.B. acknowledges EPSRC grant NO. EP/I032606/1.

The object binary interface: C++ objects for evolvable shared class libraries

Object-oriented design and object-oriented languages support the development of independent software components such as class libraries. When using such components, versioning becomes a key issue. While various ad-hoc techniques and coding idioms have been used to provide versioning, all of these techniques have deficiencies - ambiguity, the necessity of recompilation or re-coding, or the loss of binary compatibility of programs. Components from different software vendors are versioned at different times. Maintaining compatibility between versions must be consciously engineered. New technologies such as distributed objects further complicate libraries by requiring multiple implementations of a type simultaneously in a program. This paper describes a new C++ object model called the Shared Object Model for C++ users and a new implementation model called the Object Binary Interface for C++ implementors. These techniques provide a mechanism for allowing multiple implementations of an object in a program. Early analysis of this approach has shown it to have performance broadly comparable to conventional implementations.

IMPROVING THE PERFORMANCE OF DATABASE-CENTRIC APPLICATIONS THROUGH PROGRAM ANALYSIS

Modern software applications are becoming more dependent on database management systems (DBMSs). DBMSs are usually used as black boxes by software developers. For example, Object-Relational Mapping (ORM) is one of the most popular database abstraction approaches that developers use nowadays. Using ORM, objects in Object-Oriented languages are mapped to records in the database, and object manipulations are automatically translated to SQL queries. As a result of such conceptual abstraction, developers do not need deep knowledge of databases; however, all too often this abstraction leads to inefficient and incorrect database access code. Thus, this thesis proposes a series of approaches to improve the performance of database-centric software applications that are implemented using ORM. Our approaches focus on troubleshooting and detecting inefficient (i.e., performance problems) database accesses in the source code, and we rank the detected problems based on their severity. We first conduct an empirical study on the maintenance of ORM code in both open source and industrial applications. We find that ORM performance-related configurations are rarely tuned in practice, and there is a need for tools that can help improve/tune the performance of ORM-based applications. Thus, we propose approaches along two dimensions to help developers improve the performance of ORM-based applications: 1) helping developers write more performant ORM code; and 2) helping developers configure ORM configurations. To provide tooling support to developers, we first propose static analysis approaches to detect performance anti-patterns in the source code. We automatically rank the detected anti-pattern instances according to their performance impacts. Our study finds that by resolving the detected anti-patterns, the application performance can be improved by 34% on average. We then discuss our experience and lessons learned when integrating our anti-pattern detection tool into industrial practice. We hope our experience can help improve the industrial adoption of future research tools. However, as static analysis approaches are prone to false positives and lack runtime information, we also propose dynamic analysis approaches to further help developers improve the performance of their database access code. We propose automated approaches to detect redundant data access anti-patterns in the database access code, and our study finds that resolving such redundant data access anti-patterns can improve application performance by an average of 17%. Finally, we propose an automated approach to tune performance-related ORM configurations using both static and dynamic analysis. Our study shows that our approach can help improve application throughput by 27--138%. Through our case studies on real-world applications, we show that all of our proposed approaches can provide valuable support to developers and help improve application performance significantly.

Jigsaw Java: Intelligent, Automated Marking

The popularity of Computing degrees in the UK has been increasing significantly over the past number of years. In Northern Ireland, from 2007 to 2015, there has been a 40% increase in acceptances to Computer Science degrees with England seeing a 60% increase over the same period (UCAS, 2016). However, this is tainted as Computer Science degrees also continue to maintain the highest dropout rates.
In Queen’s University Belfast we currently have a Level 1 intake of over 400 students across a number of computing pathways. Our drive as staff is to empower and motivate the students to fully engage with the course content. All students take a Java programming module the aim of which is to provide an understanding of the basic principles of object-oriented design. In order to assess these skills, we have developed Jigsaw Java as an innovative assessment tool offering intelligent, semi-supervised automated marking of code.
Jigsaw Java allows students to answer programming questions using a drag-and-drop interface to place code fragments into position. Their answer is compared to the sample solution and if it matches, marks are allocated accordingly. However, if a match is not found then the corresponding code is executed using sample data to determine if its logic is acceptable. If it is, the solution is flagged to be checked by staff and if satisfactory is saved as an alternative solution. This means that appropriate marks can be allocated and should another student have submitted the same placement of code fragments this does not need to be executed or checked again. Rather the system now knows how to assess it.
Jigsaw Java is also able to consider partial marks dependent on code placement and will “learn” over time. Given the number of students, Jigsaw Java will improve the consistency and timeliness of marking.

A survey of control architectures for autonomous mobile robots

MEDEIROS, Adelardo A. D.A survey of control architectures for autonomous mobile robots. J. Braz. Comp. Soc., Campinas, v. 4, n. 3, abr. 1998 .Disponível em: Acesso: 27 set. 2010.

High-performance parallel systems for data-intensive computing

Thesis (Ph.D.)--University of Washington, 2016-08

Type-Aware Programming Models for Distributed Applications

Thesis (Ph.D.)--University of Washington, 2016-08

Synergistic nisin-polymyxin combinations for the control of Pseudomonas biofilm formation

The emergence and dissemination of multi-drug resistant pathogens is a global concern. Moreover, even greater levels of resistance are conferred on bacteria when in the form of biofilms (i.e., complex, sessile communities of bacteria embedded in an organic polymer matrix). For decades, antimicrobial peptides have been hailed as a potential solution to the paucity of novel antibiotics, either as natural inhibitors that can be used alone or in formulations with synergistically acting antibiotics. Here, we evaluate the potential of the antimicrobial peptide nisin to increase the efficacy of the antibiotics polymyxin and colistin, with a particular focus on their application to prevent biofilm formation of Pseudomonas aeruginosa. The results reveal that the concentrations of polymyxins that are required to effectively inhibit biofilm formation can be dramatically reduced when combined with nisin, thereby enhancing efficacy, and ultimately, restoring sensitivity. Such combination therapy may yield added benefits by virtue of reducing polymyxin toxicity through the administration of significantly lower levels of polymyxin antibiotics.

A survey of control architectures for autonomous mobile robots

MEDEIROS, Adelardo A. D.A survey of control architectures for autonomous mobile robots. J. Braz. Comp. Soc., Campinas, v. 4, n. 3, abr. 1998 .Disponível em: Acesso: 27 set. 2010.

A LOFAR mini-survey for low-frequency radio emission from the nearest brown dwarfs

We have conducted a mini-survey for low-frequency radio emission from some of the closest brown dwarfs to the Sun with rapid rotation rates: SIMP J013656.5 +093347, WISEPC 150649.97+702736.0, and WISEPA J174124.26+255319.5.We have placed robust 3s upper limits on the flux density in the 111 – 169 MHz frequency range for these targets: WISE 1506: < 0:72 mJy; WISE 1741: < 0:87 mJy; SIMP 0136: < 0:66 mJy. At 8 hours of integration per target to achieve these limits, we find that systematic and detailed study of this class of object at LOFAR frequencies will require a substantial dedication of resources.

User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user's session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to "continuously authenticate users" while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from "normal behavior" can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user's actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic.