Reliability of vegetation community information derived using decorana ordination and fuzzy c-means clustering

Descriptions of vegetation communities are often based on vague semantic terms describing species presence and dominance. For this reason, some researchers advocate the use of fuzzy sets in the statistical classification of plant species data into communities. In this study, spatially referenced vegetation abundance values collected from Greek phrygana were analysed by ordination (DECORANA), and classified on the resulting axes using fuzzy c-means to yield a point data-set representing local memberships in characteristic plant communities. The fuzzy clusters matched vegetation communities noted in the field, which tended to grade into one another, rather than occupying discrete patches. The fuzzy set representation of the community exploited the strengths of detrended correspondence analysis while retaining richer information than a TWINSPAN classification of the same data. Thus, in the absence of phytosociological benchmarks, meaningful and manageable habitat information could be derived from complex, multivariate species data. We also analysed the influence of the reliability of different surveyors' field observations by multiple sampling at a selected sample location. We show that the impact of surveyor error was more severe in the Boolean than the fuzzy classification. © 2007 Springer.

"Belonging” in the gentrified Golden Horn/Halic neighbourhoods of Istanbul

Mainstream gentrification research predominantly examines experiences and motivations of the middle-class gentrifier groups, while overlooking experiences of non-gentrifying groups including the impact of in situ local processes on gentrification itself. In this paper, I discuss gentrification, neighbourhood belonging and spatial distribution of class in Istanbul by examining patterns of belonging both of gentrifiers and non-gentrifying groups in historic neighbourhoods of the Golden Horn/Halic. I use multiple correspondence analysis (MCA), a methodology rarely used in gentrification research, to explore social and symbolic borders between these two groups. I show how gentrification leads to spatial clustering by creating exclusionary practices and eroding social cohesion, and illuminate divisions that are inscribed into the physical space of the neighbourhood.

Discovering knowledge structures in mind maps of mental health risks

This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

Midterm to long-term longitudinal outcome of autologous chondrocyte implantation in the knee joint:a multilevel analysis

Background Autologous chondrocyte implantation is a cell therapeutic approach for the treatment of chondral and osteochondral defects in the knee joint. The authors previously reported on the histologic and radiologic outcome of autologous chondrocyte implantation in the short- to midterm, which yields mixed results. Purpose The objective is to report on the clinical outcome of autologous chondrocyte implantation for the knee in the midterm to long term. Study Design Cohort study; Level of evidence, 3. Methods Eighty patients who had undergone autologous chondrocyte implantation of the knee with mid- to long-term follow-up were analyzed. The mean patient age was 34.6 years (standard deviation, 9.1 years), with 63 men and 17 women. Seventy-one patients presented with a focal chondral defect, with a median defect area of 4.1 cm2 and a maximum defect area of 20 cm2. The modified Lysholm score was used as a self-reporting clinical outcome measure to determine the following: (1) What is the typical pattern over time of clinical outcome after autologous chondrocyte implantation; and (2) Which patient-related predictors for the clinical outcome pattern can be used to improve patient selection for autologous chondrocyte implantation? Results The average follow-up time was 5 years (range, 2.7–9.3). Improvement in clinical outcome was found in 65 patients (81%), while 15 patients (19%) showed a decline in outcome. The median preoperative Lysholm score of 54 increased to a median of 78 points. The most rapid improvement in Lysholm score was over the 15-month period after operation, after which the Lysholm score remained constant for up to 9 years. The authors were unable to identify any patient-specific factors (ie, age, gender, defect size, defect location, number of previous operations, preoperative Lysholm score) that could predict the change in clinical outcome in the first 15 months. Conclusion Autologous chondrocyte implantation seems to provide a durable clinical outcome in those patients demonstrating success at 15 months after operation. Comparisons between other outcome measures of autologous chondrocyte implantation should be focused on the clinical status at 15 months after surgery. The patient-reported clinical outcome at 15 months is a major predictor of the mid- to long-term success of autologous chondrocyte implantation.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Statistical mechanics analysis of LDPC coding in MIMO Gaussian channels

Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases. © 2007 IOP Publishing Ltd.

Institutional shifts in inter-municipal service delivery:an analysis of developments in eight Western European countries

Comparative research on inter-municipal cooperation in eight European countries shows that there is a great variety of institutional arrangements for cooperation across the different countries. Also, these arrangements tend to change over time in terms of the scope of cooperation among partners, their composition and the degree of organizational integration. This article describes and analyzes the variety of and shifts in institutional arrangements for a specific class of inter-municipal cooperation arrangements: those that are set up to provide for the joint delivery of public services. It is argued that specific arrangements are typically the outcomes of interaction between national institutional contexts,?environmental factors and local preferences.

Exploiting sensitivity of nonorthogonal joint diagonalisation as a security mechanism in steganography

We have recently proposed the framework of independent blind source separation as an advantageous approach to steganography. Amongst the several characteristics noted was a sensitivity to message reconstruction due to small perturbations in the sources. This characteristic is not common in most other approaches to steganography. In this paper we discuss how this sensitivity relates the joint diagonalisation inside the independent component approach, and reliance on exact knowledge of secret information, and how it can be used as an additional and inherent security mechanism against malicious attack to discovery of the hidden messages. The paper therefore provides an enhanced mechanism that can be used for e-document forensic analysis and can be applied to different dimensionality digital data media. In this paper we use a low dimensional example of biomedical time series as might occur in the electronic patient health record, where protection of the private patient information is paramount.

Industrial relations in the road passenger transport industry-a political-economic analysis.

This thesis examines the British Bus and Tram Industry from 1889 to 1988. The first determinant of the pattern of industrial relations is the development of the labour-process. The labour process changes with the introduction of new technology (electrified trams and mechanised buses), the concentration and centralisation of ownership, the decline of competition, changing market position, municipal and state regulation, ownership and control. The tram industry, as a consequence of electrification, is almost wholly municipally owned and the history of the labour process from horse-trams to the decline of the industry is examined. The bus industry has a less unified structure and is examined by sector; London, Municipal, and Territorial/Provincial. The small independent sector is largely ignored. The labour process is examined from the horse-bus to the present day. The development of resistance in the labour process is discussed both as a theoretical problematic (the `Braverman Debate') and through the process of unionisation, the centralisation and bureaucratisation of the unions, the development of national bargaining structures (National Joint Industrial Council and the National Council for the Omnibus Industry), and the development of resistance to those processes. This resistance takes either a syndicalist form, or under Communist Party leadership the form of rank and file movements, or simply unofficial organisations of branch officials. The process of centralisation of the unions, bureaucratisation and the institutionalisation of bargaining and the relationship between this process and the role of the Unions in the Labour Party is examined. Neo-corporatism, that is the increasing integration of the leadership of the main Union, the T.G.W.U.with the Labour Party and with the State is discussed. In theoretical terms, this thesis considers the debate around the notion of `labour process', the relationship between labour process and labour politics and between labour process and labour history. These relationships are placed within a discussion of class consciousness.

Weakly supervised joint sentiment-topic detection from text

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JST model called Reverse-JST, obtained by reversing the sequence of sentiment and topic generation in the modeling process, is also studied. Although JST is equivalent to Reverse-JST without a hierarchical prior, extensive experiments show that when sentiment priors are added, JST performs consistently better than Reverse-JST. Besides, unlike supervised approaches to sentiment classification which often fail to produce satisfactory performance when shifting to other domains, the weakly supervised nature of JST makes it highly portable to other domains. This is verified by the experimental results on data sets from five different domains where the JST model even outperforms existing semi-supervised approaches in some of the data sets despite using no labeled documents. Moreover, the topics and topic sentiment detected by JST are indeed coherent and informative. We hypothesize that the JST model can readily meet the demand of large-scale sentiment analysis from the web in an open-ended fashion.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Living together with age related macular degeneration:an interpretative phenomenological analysis of sense-making within a dyadic relationship

In this article, we present an idiographic analysis of a couple's experience of living and coming to terms with age-related macular degeneration. Interpretative phenomenological analysis was used to explore three joint interviews, conducted over an 18-month period, with a married couple (aged 82 and 77 years) both living with age-related macular degeneration. Three themes are discussed: the disruption of vision impairment, managing mutual deterioration and resilience through togetherness. We discuss the existential challenges of vision impairment and consider the applicability of Galvin and Todres' typology of well-being as a means of understanding well-being in older adults.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Dynamic joint sentiment-topic model

Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different ways of accounting for such dependency information: (1) Sliding window where the current sentiment-topic word distributions are dependent on the previous sentiment-topic-specific word distributions in the last S epochs; (2) skip model where history sentiment topic word distributions are considered by skipping some epochs in between; and (3) multiscale model where previous long- and shorttimescale distributions are taken into consideration. We derive efficient online inference procedures to sequentially update the model with newly arrived data and show the effectiveness of our proposed model on the Mozilla add-on reviews crawled between 2007 and 2011. © 2013 ACM 2157-6904/2013/12-ART5 $ 15.00.