122 research outputs found
Seasonality in sprouting and growth of black pepper rooted cuttings under sub-Himalayan Terai region
No full textNot Available
No full textNot AvailablePhytoplasma, the causal agent of coconut root disease (CRD), has been considered as a serious threat to coconut production in the Malabar coastal region of India. The disease is non lethal, but causes a considerable economic loss in India, every year. It has already been reported that species of the phytoplasma, belonging to ribosomal group 16SrXI, are primarily associated this disease. In present study, our objective is to explore more information that is already hidden within this phytoplasma protein sequence, using important statistical techniques. Therefore, we explored all important statistics with regard to the CRD phytoplasma protein sequence and further, predicted its secondary structure using Chou-Fasman algorithm. We obtained the value 8.3 of iso-electronic point of this protein, and also found that its predicted secondary structure consists of 5 helical regions, 6 beta sheet regions and 2 beta turn regions. A comparative analysis of the sequence with the sequences of phytoplasma related to other economically important crops revealed that there was no evidence of significant difference within the secondary structures of the selected sequences at 5% level of significance.Not Availabl
Feature Points Extraction of Thermal Face Using Harris Interest Point Detection
No full textAbstractFacial feature extraction has become an important issue in automatic recognition of human faces. Thermal images have the advantage over visual images because of its illumination invariant property. But locating facial feature in thermal image is a difficult task due to less important texture information. In this paper, Harris interest point detector is used to locate the thermal facial features. Harris interest point detector is based on intensity and computes the presence of interest point directly fr om the grey values. Experiment result shows that Harris operator can detect good number of interest points even in illumination variation, rotation, and scaling condition
Recent advances in the use of acoustics across the frequency spectrum in the oil and gas industry
No full textOrchestration and governance in digital platform ecosystems: a literature review and trends
No full textPurpose: Because of the attention increasingly being focused on digital transformation, interest in business models of platform-enabled ecosystems is rising rapidly. Although there are different theoretical views on the role of ecosystems, a synthesis of research, with a focus on governance and orchestration in dynamic, multi-industry eco-systems, is lacking. Design/methodology/approach: A systematic literature review was conducted by following a rigorous search protocol in the scholarly databases covering both journal articles and conference papers These papers were subsequently filtered, and finally, 48 relevant papers were selected for analysis. Findings: The review identifies five key aspects of platform governance design that need close consideration: the meta-organisation or ecosystem design, coordination mechanisms, mechanisms for value co-creation, value appropriation mechanisms and architectural principles. To achieve balance among a set of competing demands, platform leaders need to devote adequate attention to these aspects. Practical implications: Based on a literature review, the authors provide an overview of underlying theoretical views, research methods and key trends to develop a sound theoretical grounding for research on platform governance design. The paper also suggests research gaps in the existing literature and sets directions for researchers to strengthen the understanding of effective platform governance design. The paper also provides valuable information to managers in developing or leading a successful platform ecosystem. Originality/value: The paper uses existing literature published in this topic and original in nature.</p
The Theme of Betrayal in Tagore’s Home and The World
No full textRabindranath Tagore was a prolific author who earned name and fame worldwide for his contribution in literature. Tagore depicts the different shades of man’s life through the characters of his novels. Tagore touches the different issues like : the struggle for freedom, the existence of good and evil of the world. Tagore’s The Home and the World deals with the theme of betrayal and the relationship of husband and wife and how the wife realizes her mistake at the end of the novel This paper is a sincere effort to display how the betrayal of Bimala effects Nikhil’s life and how she is deceived by her idol Sandip
An approach based on Hierarchical Bayesian Graphical Models for measurement interpretation under uncertainty
No full textIt is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications.In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.</p
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