Noise-robust method for image segmentation

Segmentation of noisy images is one of the most challenging problems in image analysis and any improvement of segmentation methods can highly influence the performance of many image processing applications. In automated image segmentation, the fuzzy c-means (FCM) clustering has been widely used because of its ability to model uncertainty within the data, applicability to multi-modal data and fairly robust behaviour. However, the standard FCM algorithm does not consider any information about the spatial linage context and is highly sensitive to noise and other imaging artefacts. Considering above mentioned problems, we developed a new FCM-based approach for the noise-robust fuzzy clustering and we present it in this paper. In this new iterative algorithm we incorporated both spatial and feature space information into the similarity measure and the membership function. We considered that spatial information depends on the relative location and features of the neighbouring pixels. The performance of the proposed algorithm is tested on synthetic image with different noise levels and real images. Experimental quantitative and qualitative segmentation results show that our method efficiently preserves the homogeneity of the regions and is more robust to noise than other FCM-based methods

An improved fuzzy clustering approach for image segmentation

Fuzzy clustering techniques have been widely used in automated image segmentation. However, since the standard fuzzy c-means (FCM) clustering algorithm does not consider any spatial information, it is highly sensitive to noise. In this paper, we present an extension of the FCM algorithm to overcome this drawback, by incorporating spatial neighborhood information into a new similarity measure. We consider that spatial information depends on the relative location and features of the neighboring pixels. The performance of the proposed algorithm is tested on synthetic and real images with different noise levels. Experimental quantitative and qualitative segmentation results show that the proposed method is effective, more robust to noise and preserves the homogeneity of the regions better than other FCM-based methods

Multinuclear NMR spectroscopy and isotopomer distribution analysis applied to metabolic phenotype characterization of complex systems

In the present work, the complex metabolic effects of a rag8 genetic mutation performed on Kluyveromyces lactis yeast cells is investigated with a specific, ‘information-rich’ analytical approach: differential NMR metabolomics. The use of such NMR-based metabolite profiling techniques form the basis for intelligent screening strategies to exploit the biotechnological potentials of yeasts because the rational improvement of K. lactis strains for the production of primary and secondary metabolites requires, first of all, a quantitative understanding of their metabolism, allowing the development of more efficient cell factories through metabolic engineering. Wild-type and mutant cell lines metabolomes are compared each other: through the application of multivariate statistical models a metabolic network is built on statistical basis, describing the metabolite phenotype of the rag8 mutant K. lactis strain. However, the measurement and interpretation of such in vivo metabolite dynamics at a systems level is inherently difficult. Indeed, decipher the intricate web of metabolic networks of a complex system and, particularly, infer something about gene functions only based on metabolite profiling, is one of the greatest challenges in molecular biology which cannot be resolved fully by any metabolomic tool. To resolve and improve the metabolic network description, an extension of the 13C labeling protocol for investigating eukaryotic cellular systems is applied in this work. The resulting labeling pattern of each metabolite reflects the relative importance of the alternative pathways within the metabolic network. This observation underscores the need for acquiring 13C-isotopomer data, instead of just steady-state concentrations, to deduce meaningful relationships between metabolites in related pathways. It was displayed that differential 13C-labeled isotopomer profiles and abundance can serve as a fingerprint of the metabolic networks activity and could reflects both qualitative and quantitative differences in the metabolic pathways that lead to the synthesis of each metabolite. In this way, the role of several metabolic processes could be defined, allowing the exploration of metabolic pathways, leading to qualitative information on the links between labeled precursors and their products and quantitative information on metabolic fluxes. It was demonstrated that in yeasts it has been possible to make significant progress in the analysis of carbon metabolism by using 13C NMR to measure metabolic fluxes in genetically modified cells. This approach, so, can be used for functional genomic analysis of yeast mutants providing detailed quantitative information for the understanding of a biological network useful to identify the key genes for strain improvement. Moreover, an intelligent screening of the large unexploited fungal biodiversity opens the possibility to the development and use of directed genetic modifications of cell factories for the production of novel compounds, that are otherwise difficult to produce by chemical synthesis, and also of new, efficient and environmentally friendly bioprocesses. These possibilities open the way to many comparative functional studies and will certainly change the respective importance of the different yeasts, building up new model yeasts for specific studies

Measuring specialization in species interaction networks

BACKGROUND: Network analyses of plant-animal interactions hold valuable biological information. They are often used to quantify the degree of specialization between partners, but usually based on qualitative indices such as 'connectance' or number of links. These measures ignore interaction frequencies or sampling intensity, and strongly depend on network size. RESULTS: Here we introduce two quantitative indices using interaction frequencies to describe the degree of specialization, based on information theory. The first measure (d') describes the degree of interaction specialization at the species level, while the second measure (H(2)') characterizes the degree of specialization or partitioning among two parties in the entire network. Both indices are mathematically related and derived from Shannon entropy. The species-level index d' can be used to analyze variation within networks, while H(2)' as a network-level index is useful for comparisons across different interaction webs. Analyses of two published pollinator networks identified differences and features that have not been detected with previous approaches. For instance, plants and pollinators within a network differed in their average degree of specialization (weighted mean d'), and the correlation between specialization of pollinators and their relative abundance also differed between the webs. Rarefied sampling effort in both networks and null model simulations suggest that H(2)' is not affected by network size or sampling intensity. CONCLUSION: Quantitative analyses reflect properties of interaction networks more appropriately than previous qualitative attempts, and are robust against variation in sampling intensity, network size and symmetry. These measures will improve our understanding of patterns of specialization within and across networks from a broad spectrum of biological interactions

Mass transfer coefficient for drying of moist particulate in a bubbling fluidized bed

Experiments on drying of moist particles by ambient air were carried out to measure the mass transfer coefficient in a bubbling fluidized bed. Fine glass beads of mean diameter 125?µm were used as the bed material. Throughout the drying process, the dynamic material distribution was recorded by electrical capacitance tomography (ECT) and the exit air condition was recorded by a temperature/humidity probe. The ECT data were used to obtain qualitative and quantitative information on the bubble characteristics. The exit air moisture content was used to determine the water content in the bed. The measured overall mass transfer coefficient was in the range of 0.0145–0.021?m/s. A simple model based on the available correlations for bubble-cloud and cloud-dense interchange (two-region model) was used to predict the overall mass transfer coefficient. Comparison between the measured and predicted mass transfer coefficient have shown reasonable agreement. The results were also used to determine the relative importance of the two transfer regions

The culture of market oriented organisations

This paper investigates the relationship between corporate culture and market orientation using a different methodology to those usually found done in empirical studies on this topic. Conventionally, one or two key informants provide information on the firm’s marketing practices in large scale quantitative cross-sectional studies; these few respondents provide their opinion on the firm’s actual marketing practices which are then considered as a reliable representation of both the (whole) firm’s culture and its market orientation. We have taken a different approach. Firstly, we chose to do multiple case studies in stead of cross sectional research. These case studies were small scale and qualitative; next a large(r) scale quantitative study was done within those organisations. Secondly, all employees in an organisation were invited to participate in the study: only then is it possible to measure culture as the shared beliefs in the company. Corporate culture itself as well as the marketing practices have been investigated as two separate constructs in our case studies. Both are measured via employee perceptions. Thirdly, we are looking at the possible configuration of market orientation and corporate culture. Almost all of the propositions generated are supported. The degree of openness appeared to be crucial to an organisation’s market orientation. Moreover, such a culture is also resultsoriented, employee-oriented and professional. It also has a balanced position on the two other dimensions: pragmatic/normative and loose/tight control. From the marketing perspective, the essential building blocks of a market oriented culture include: the internal cooperation, internal communication, drive to be the best, lack of pursuing self interest, learning from mistakes and from experiences in the market place, clarity about customer needs and better relative quality than competitors’. Because market orientation and corporate culture were measured as two distinct constructs, this study offers new insights in both domains as to what organisations should change to be(come) market oriented.Strategy;

An improved fuzzy clustering approach for image segmentation

Fuzzy clustering techniques have been widely used in automated image segmentation. However, since the standard fuzzy c-means (FCM) clustering algorithm does not consider any spatial information, it is highly sensitive to noise. In this paper, we present an extension of the FCM algorithm to overcome this drawback, by incorporating spatial neighborhood information into a new similarity measure. We consider that spatial information depends on the relative location and features of the neighboring pixels. The performance of the proposed algorithm is tested on synthetic and real images with different noise levels. Experimental quantitative and qualitative segmentation results show that the proposed method is effective, more robust to noise and preserves the homogeneity of the regions better than other FCM-based methods

Quantity versus Quality: The Impact of Environmental Disclosures on the reputations of UK plcs

The theoretical framework of this paper integrates quality-signalling theory and the resource based view of the firm to test the differential effects of the quantity and quality of environmental disclosures on the firm’s environmental reputation. Uniquely, the study uses a quality-adjusted method of content analysis, so that sentences are not merely counted but also weighted to reflect their likely significance. Investments in research and development and diversification, as potential methods of enhancing of environmental reputation, are also considered. In doing so the paper complements and extends the work of Toms (2002). The results confirm the framework and models tested in the original paper on more recent data and also suggest that quality of environmental disclosure rather than mere quantity has a stronger effect on the creation of environmental reputation amongst executive and investor stakeholder groups. Research and development expenditure, and under certain circumstances, diversification, also add to reputation

Bank Networks from Text: Interrelations, Centrality and Determinants

In the wake of the still ongoing global financial crisis, bank interdependencies have come into focus in trying to assess linkages among banks and systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discourse. We present a text-to-network process, which has its basis in co-occurrences of bank names and can be analyzed quantitatively and visualized. To quantify bank importance, we propose an information centrality measure to rank and assess trends of bank centrality in discussion. For qualitative assessment of bank networks, we put forward a visual, interactive interface for better illustrating network structures. We illustrate the text-based approach on European Large and Complex Banking Groups (LCBGs) during the ongoing financial crisis by quantifying bank interrelations and centrality from discussion in 3M news articles, spanning 2007Q1 to 2014Q3.Comment: Quantitative Finance, forthcoming in 201

The sweet spot in sustainability: a framework for corporate assessment in sugar manufacturing

The assessment of corporate sustainability has become an increasingly important topic, both within academia and in industry. For manufacturing companies to conform to their commitments to sustainable development, a standard and reliable measurement framework is required. There is, however, a lack of sector-specific and empirical research in many areas, including the sugar industry. This paper presents an empirically developed framework for the assessment of corporate sustainability within the Thai sugar industry. Multiple case studies were conducted, and a survey using questionnaires was also employed to enhance the power of generalisation. The developed framework is an accurate and reliable measurement instrument of corporate sustainability, and guidelines to assess qualitative criteria are put forward. The proposed framework can be used for a company’s self-assessment and for guiding practitioners in performance improvement and policy decision-maki