Understanding U.S. regional linguistic variation with Twitter data analysis

We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Survival data analysis using neural networks

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Feed-forward neural networks and topographic mappings for exploratory data analysis

A recent novel approach to the visualisation and analysis of datasets, and one which is particularly applicable to those of a high dimension, is discussed in the context of real applications. A feed-forward neural network is utilised to effect a topographic, structure-preserving, dimension-reducing transformation of the data, with an additional facility to incorporate different degrees of associated subjective information. The properties of this transformation are illustrated on synthetic and real datasets, including the 1992 UK Research Assessment Exercise for funding in higher education. The method is compared and contrasted to established techniques for feature extraction, and related to topographic mappings, the Sammon projection and the statistical field of multidimensional scaling.

Short fatigue crack growth behaviour:data analysis effects

Consideration of the influence of test technique and data analysis method is important for data comparison and design purposes. The paper highlights the effects of replication interval, crack growth rate averaging and curve-fitting procedures on crack growth rate results for a Ni-base alloy. It is shown that an upper bound crack growth rate line is not appropriate for use in fatigue design, and that the derivative of a quadratic fit to the a vs N data looks promising. However, this type of averaging, or curve fitting, is not useful in developing an understanding of microstructure/crack tip interactions. For this purpose, simple replica-to-replica growth rate calculations are preferable. © 1988.

Evaluating the evaluator:modelling systematic data analysis strategies for software selection

Developers of interactive software are confronted by an increasing variety of software tools to help engineer the interactive aspects of software applications. Not only do these tools fall into different categories in terms of functionality, but within each category there is a growing number of competing tools with similar, although not identical, features. Choice of user interface development tool (UIDT) is therefore becoming increasingly complex.

Decision theory to support evacuation in advance of catastrophic disaster including modular influence diagrams and spatial data analysis.

DUE TO INCOMPLETE PAPERWORK, ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The effects of relocation on Royal Air Force families

This doctoral research project examines the effects that geographical transience has on Royal Air Force families. The methodology employed in this exploratory and qualitative study consisted largely of open-ended interview questions but also included a series of demographic variables. In total, 29 RAF personnel without families, 33 RAF personnel with families, 33 RAF spouses, and 15 RAF children participated in this research (N = 110). All respondents volunteered to take part in the study and were based in the United Kingdom at the time of data collection. The interviews were transcribed and content coded according to six major relocation themes arising from the literature (change, tasks, support, coping, difficulty, and outcome). QSR NVIVO 2.0, a qualitative data analysis software package, was used to facilitate the process. Through the utilisations of qualitative methodology, the researcher was able to offer various novel and reoccurring variables that appear to play an important role (at least subjectively) in relocation. Additionally, frequencies associated with these factors were presented. The findings were integrated with those from the literature in order to offer an initial comparison and differentiation between civilian and military samples. The main theoretical contributions were the introduction of the concept of mobile mentality, the creation of a novel relocation model that takes familial interaction into account, and the development of a taxonomy for the classification of relocation outcomes. Finally, additional observations, recommendations for future research, and practical implications are reviewed.

An exploration of female leadership language:case studies of senior women in Bahrain

This is a multiple case study of the leadership language of three senior women working in a large corporation in Bahrain. The study’s main aim is to explore the linguistic practices the women leaders use with their colleagues and subordinates in corporate meetings. Adopting a Foucauldian (1972) notion of ‘discourses’ as social practices and a view of gender as socially constructed and discursively performed (Butler 1990), this research aims to unveil the competing discourses which may shape the leadership language of senior women in their communities of practice. The research is situated within the broader field of Sociolinguistics and the specific field of Language and Gender. To address the research aim, a case study approach incorporating multiple methods of qualitative data collection (observation, interviews, and shadowing) was utilised to gather information about the three women leaders and produce a rich description of their use of language in and out of meeting contexts. For analysis, principles of Qualitative Data Analysis (QDA) were used to organise and sort the large amount of data. Also, Feminist Post- Structuralist Discourse Analysis (FPDA) was adopted to produce a multi-faceted analysis of the subjects, their language leadership, power relations, and competing discourses in the context. It was found that the three senior women enact leadership differently making variable use of a repertoire of conventionally masculine and feminine linguistic practices. However, they all appear to have limited language resources and even more limiting subject positions; and they all have to exercise considerable linguistic expertise to police and modify their language in order to avoid the ‘double bind’. Yet, the extent of this limitation and constraints depends on the community of practice with its prevailing discourses, which appear to have their roots in Islamic and cultural practices as well as some Western influences acquired throughout the company’s history. It is concluded that it may be particularly challenging for Middle Eastern women to achieve any degree of equality with men in the workplace because discourses of Gender difference lie at the core of Islamic teaching and ideology.

The complements towards developing a new risk management framework and Its applicability to the Nigerian power sector

The availability of regular supply has been identified as one of the major stimulants for the growth and development of any nation and is thus important for the economic well-being of a nation. The problems of the Nigerian power sector stems from a lot of factors culminating in her slow developmental growth and inability to meet the power demands of her citizens regardless of the abundance of human and natural resources prevalent in the nation. The research therefore had the main aim of investigating the importance and contributions of risk management to the success of projects specific to the power sector. To achieve this aim it was pertinent to examine the efficacy of risk management process in practice and elucidate the various risks typically associated with projects (Construction, Contractual, Political, Financial, Design, Human resource and Environmental risk factors) in the power sector as well as determine the current situation of risk management practice in Nigeria. To address this factors inhibiting the proficiency of the overarching and prevailing issue which have only been subject to limited in-depth academic research, a rigorous mixed research method was adopted (quantitative and qualitative data analysis). A review of the Nigeria power sector was also carried out as a precursor to the data collection stage. Using purposive sampling technique, respondents were identified and a questionnaire survey was administered. The research hypotheses were tested using inferential statistics (Pearson correlation, Chi-square test, t-test and ANOVA technique) and the findings revealed the need for the development of a new risk management implementation Framework. The proposed Framework was tested within a company project, for interpreting the dynamism and essential benefits of risk management with the aim of improving the project performances (time), reducing the level of fragmentation (quality) and improving profitability (cost) within the Nigerian power sector in order to bridge a gap between theory and practice. It was concluded that Nigeria’s poor risk management practices have prevented it from experiencing strong growth and development. The study however, concludes that the successful implementation of the developed risk management framework may help it to attain this status by enabling it to become more prepared and flexible, to face challenges that previously led to project failures, and thus contributing to its prosperity. The research study provides an original contribution theoretically, methodologically and practically which adds to the project risk management body of knowledge and to the Nigerian power sector.

An introduction to analysis of variance (ANOVA) with special reference to data from clinical experiments in optometry

This article is aimed primarily at eye care practitioners who are undertaking advanced clinical research, and who wish to apply analysis of variance (ANOVA) to their data. ANOVA is a data analysis method of great utility and flexibility. This article describes why and how ANOVA was developed, the basic logic which underlies the method and the assumptions that the method makes for it to be validly applied to data from clinical experiments in optometry. The application of the method to the analysis of a simple data set is then described. In addition, the methods available for making planned comparisons between treatment means and for making post hoc tests are evaluated. The problem of determining the number of replicates or patients required in a given experimental situation is also discussed. Copyright (C) 2000 The College of Optometrists.

Education and self-management for people newly diagnosed with type 2 diabetes: a qualitative study of patients' views.

OObjectives: We explored the perceptions, views and experiences of diabetes education in people with type 2 diabetes who were participating in a UK randomized controlled trial of methods of education. The intervention arm of the trial was based on DESMOND, a structured programme of group education sessions aimed at enabling self-management of diabetes, while the standard arm was usual care from general practices. Methods: Individual semi-structured interviews were conducted with 36 adult patients, of whom 19 had attended DESMOND education sessions and 17 had been randomized to receive usual care. Data analysis was based on the constant comparative method. Results: Four principal orientations towards diabetes and its management were identified: `resisters', `identity resisters, consequence accepters', `identity accepters, consequence resisters' and `accepters'. Participants offered varying accounts of the degree of personal responsibility that needed to be assumed in response to the diagnosis. Preferences for different styles of education were also expressed, with many reporting that they enjoyed and benefited from group education, although some reported ambivalence or disappointment with their experiences of education. It was difficult to identify striking thematic differences between accounts of people on different arms of the trial, although there was some very tentative evidence that those who attended DESMOND were more accepting of a changed identity and its implications for their management of diabetes. Discussion: No one single approach to education is likely to suit all people newly diagnosed with diabetes, although structured group education may suit many. This paper identifies varying orientations and preferences of people with diabetes towards forms of both education and self-management, which should be taken into account when planning approaches to education.

Quantitative neuropathology:data collection and statistical analysis

The use of quantitative methods has become increasingly important in the study of neuropathology and especially in neurodegenerative disease. Disorders such as Alzheimer's disease (AD) and the frontotemporal dementias (FTD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This chapter reviews the advantages and limitations of the different methods of quantifying pathological lesions in histological sections including estimates of density, frequency, coverage, and the use of semi-quantitative scores. The sampling strategies by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are described. In addition, data analysis methods commonly used to analysis quantitative data in neuropathology, including analysis of variance (ANOVA), polynomial curve fitting, multiple regression, classification trees, and principal components analysis (PCA), are discussed. These methods are illustrated with reference to quantitative studies of a variety of neurodegenerative disorders.

Efficacy and safety of second-generation antipsychotic long-acting injections (SGA LAIs) in maintenance treatment of bipolar disorder:protocol for a systematic review and meta-analysis

INTRODUCTION: Bipolar disorder requires long-term treatment but non-adherence is a common problem. Antipsychotic long-acting injections (LAIs) have been suggested to improve adherence but none are licensed in the UK for bipolar. However, the use of second-generation antipsychotics (SGA) LAIs in bipolar is not uncommon albeit there is a lack of systematic review in this area. This study aims to systematically review safety and efficacy of SGA LAIs in the maintenance treatment of bipolar disorder. METHODS AND ANALYSIS: The protocol is based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and will include only randomised controlled trials comparing SGA LAIs in bipolar. PubMed, EMBASE, CINAHL, Cochrane Library (CENTRAL), PsychINFO, LiLACS, http://www.clinicaltrials.gov will be searched, with no language restriction, from 2000 to January 2016 as first SGA LAIs came to the market after 2000. Manufacturers of SGA LAIs will also be contacted. Primary efficacy outcome is relapse rate or delayed time to relapse or reduction in hospitalisation and primary safety outcomes are drop-out rates, all-cause discontinuation and discontinuation due to adverse events. Qualitative reporting of evidence will be based on 21 items listed on standards for reporting qualitative research (SRQR) focusing on study quality (assessed using the Jadad score, allocation concealment and data analysis), risk of bias and effect size. Publication bias will be assessed using funnel plots. If sufficient data are available meta-analysis will be performed with primary effect size as relative risk presented with 95% CI. Sensitivity analysis, conditional on number of studies and sample size, will be carried out on manic versus depressive symptoms and monotherapy versus adjunctive therapy.