Covering Dimension of C*-Algebras and 2-Coloured Classification

Peer reviewed

Localization of quantum biequivariant D-modules and q-W algebras

Peer reviewed

Different cation-protonation patterns in mol-ecular salts of unsymmetrical dimethyhydrazine : C2H9N2·Br and C2H9N2·H2PO3

Peer reviewed

Models and empirical data for the production of referring expressions

Article Accepted Date: 29 May 2014 Acknowledgements The authors gratefully acknowledge the support of the Cognitive Science Society for the organisation of the Workshop on Production of Referring Expressions: Bridging the Gap between Cognitive and Computational Approaches to Reference, from which this special issue originated. Funding Emiel Krahmer and Albert Gatt thank The Netherlands Organisation for Scientific Research (NWO) for VICI grant Bridging the Gap between Computational Linguistics and Psycholinguistics: The Case of Referring Expressions (grant number 277-70-007).

Coupled electronic and morphologic changes in graphene oxide upon electrochemical reduction

Date of Acceptance: 13/04/2015

CO induced surface segregation as a means of improving surface composition and enhancing performance of CuPd bimetallic catalysts

Date of Acceptance: 01/06/2015 We thank the University of Aberdeen for financial support and A.I. McNab (University of Aberdeen) for discussions involving the calculation of surface sites.

MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis

Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Commiphora gileadensis sap extract induces cell cycle-dependent death in immortalized keratinocytes and human dermoid carcinoma

We would like to dedicate this article to the memory of Professor Yoram Milner, who has passed away before this study was achieved. We are immeasurably indebted to him, professionally and personally. The study was supported by grants from the ICA Foundation and the Ministry of Science, Technology and Space.

Design concept evaluation based on rough number and information entropy theory

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes.

Eyewitness Memory: Balancing the Accuracy, Precision, and Quantity of Information through Metacognitive Monitoring and Control

Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded.

Utilizing ICT to prevent loneliness and social isolation of the elderly. A literature review

Ageing of the population is a worldwide phenomenon. Numerous ICT-based solutions have been developed for elderly care but mainly connected to the physiological and nursing aspects in services for the elderly. Social work is a profession that should pay attention to the comprehensive wellbeing and social needs of the elderly. Many people experience loneliness and depression in their old age, either as a result of living alone or due to a lack of close family ties and reduced connections with their culture of origin, which results in an inability to participate actively in community activities (Singh & Misra, 2009). Participation in society would enhance the quality of life. With the development of information technology, the use of technology in social work practice has risen dramatically. The aim of this literature review is to map out the state of the art of knowledge about the usage of ICT in elderly care and to figure out research-based knowledge about the usability of ICT for the prevention of loneliness and social isolation of elderly people. The data for the current research comes from the core collection of the Web of Science and the data searching was performed using Boolean? The searching resulted in 216 published English articles. After going through the topics and abstracts, 34 articles were selected for the data analysis that is based on a multi approach framework. The analysis of the research approach is categorized according to some aspects of using ICT by older adults from the adoption of ICT to the impact of usage, and the social services for them. This literature review focused on the function of communication by excluding the applications that mainly relate to physical nursing. The results show that the so-called ‘digital divide’ still exists, but the older adults have the willingness to learn and utilise ICT in daily life, especially for communication. The data shows that the usage of ICT can prevent the loneliness and social isolation of older adults, and they are eager for technical support in using ICT. The results of data analysis on theoretical frames and concepts show that this research field applies different theoretical frames from various scientific fields, while a social work approach is lacking. However, a synergic frame of applied theories will be suggested from the perspective of social work.

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.