Statistical Measures to Determine Optimal Structure of Decision Tree: One versus One Support Vector Machine

In this paper, one versus one optimal decision tree support vector machine (OvO-ODT SVM) framework is proposed to solve multi-class problems where the optimal structure of decision tree is determined using statistical measures, i.e., information gain, gini index, and chi-square. The performance of proposed OvO-ODT SVM is evaluated in terms of classification accuracy and computation time. It is also shown that proposed OvO-ODT SVM using all the three measures is more efficient in terms of time complexity for both training and testing phases in comparison to conventional OvO and support vector machine binary decision tree (SVMBDT). Experiments on University of California, Irvine (UCI) repository dataset illustrates that ten crossvalidation accuracy of our proposed framework is comparable or better in comparison to conventional OvO and SVM-BDT for most of the datasets. However, the proposed framework outperforms the conventional OvO and SVM-BDT for all the datasets in terms of both training and testing time.Defence Science Journal, 2010, 60(4), pp.399-404, DOI:http://dx.doi.org/10.14429/dsj.60.50

Performance Evaluation of Exponential Discriminant Analysis with Feature Selection for Steganalysis

The performance of supervised learning-based seganalysis depends on the choice of both classifier and features which represent the image. Features extracted from images may contain irrelevant and redundant features which makes them inefficient for machine learning. Relevant features not only decrease the processing time to train a classifier but also provide better generalisation. Linear discriminant classifier which is commonly used for classification may not be able to classify in better way non-linearly separable data. Recently, exponential discriminant analysis, a variant of linear discriminant analysis (LDA), is proposed which transforms the scatter matrices to a new space by distance diffusion mapping. This provides exponential discriminant analysis (EDA) much more discriminant power to classify non-linearly separable data and helps in improving classification accuracy in comparison to LDA. In this paper, the performance of EDA in conjunction with feature selection methods has been investigated. For feature selection, Kullback divergence, Chernoff distance measures and linear regression measures are used to determine relevant features from higher-order statistics of images. The performance is evaluated in terms classification error and computation time. Experimental results show that exponential discriminate analysis in conjunction with linear regression significantly performs better in terms of both classification error and compilation time of training classifier.Defence Science Journal, 2012, 62(1), pp.19-24, DOI:http://dx.doi.org/10.14429/dsj.62.143

AYURVEDIC MANAGEMENT OF KOSTHASHAKHASHRITA KAMLA W.S.R TO ALCOHOLIC HEPATITIS (ALCOHOLIC LIVER DISEASE) - A CASE REPORT

Alcoholic hepatitis is an inflammatory condition of the liver. It is caused by excessive alcohol consumption over an extended period of time. Genetics, other liver disorders, and nutrition may also contribute to alcoholic Liver Disease. In Ayurveda there are so many herbs and natural remedies available for treatment of liver diseases. Herein we present a case of married male of age 36yrswho was reported in Kayachikitsa OPD, All India Institute of Ayurveda New Delhi India with chief complaints of pain in abdomen with mild distension, yellowish discolouration of eyes, skin and dark yellow urine, loss of appetite, disturbed sleep, pedal oedema, weakness, anorexia. The diagnosis alcoholic liver disease was made on clinical ground supported with Ultrasonography and blood biochemistry reports. Ayurvedic treatment given was Nitya Virechan with Trivrit Avleha (regular purgative), Bilwadi Gutika Anjana (medicated collyrium) and Shamanoushadhi (palliative drugs). During the treatment the patient was totally abstaining from alcohol. Within 45 days of starting the therapy patient showed significant improvement which were assessed by measuring liver functions through specific clinical features and laboratory parameters. Hence presenting this case is an evidence to demonstrate the effectiveness of Ayurvedic treatment in ALD which can be proved an important guideline for treating Alcoholic Liver Disease with safe and effective Ayurveda line of management

目次

Price responsive demand shifting bidding mechanism is discussed as an alternative solution to deal with intermittency in wind generation. This paper proposes a formulation of social welfare equation with price responsive demand shifting bidding and economic emission dispatch with emphasis on integration of wind power. The analysis is based on the IEEE 30 bus test system generation data, with conventional and wind generation plant over a period of 24 hours. It has been demonstrated that the proposed approach leads to reduction in emission as well deal with intermittency in wind generation

Spectrophotometric analysis of tablets of nalidixic acid using melted niacinamide as solvent

In the current attempt of research, novel method for spectrophotometric estimation of nalidixic acid in tablets using melted niacinamide as solvent was developed. The main objective behind research is to show “SOLIDS ALSO POSSESS SOLUBILIZING POWER”. The current study deals with novel spectrophotometric analytical technique for quantitative estimation of nalidixic acid in tablets using melted niacinamide as solvent. According to the theory proposed by Maheshwari, each & every substance possesses solubilising power; substance may be a gas, solid or liquid. Niacinamide imbibes large solubilizing power to nalidixic acid and having approximate solubility more than 80 mg per gm of melted niacinamide (135°C) whereas aqueous solubility of nalidixic acid is 0.21mg/ml at room temperature. Calibration curve of nalidixic acid was plotted by recording the absorbances of standard solutions of drug. The absorbances were observed at 330 nm against respective reagent blanks. The percentage label claims were found very close to 100 (100.93± 1.303 and 99.08±1.764) indicating accuracy of the proposed method. Percentage recoveries estimated by the proposed method are close to 100 (99.91±1.303 and 101.74±1.663) with significant low values of percentage deviation and standard error. Thus, it may be concluded that proposed method is simple, safe and precise and excludes use of toxic organic solvents. Keywords: Mixed Solvency, Solubilizing Power, Spectrophotometric Analysis, Niacinamide, Nalidixic Acid

Distinguishing WH and WBBbar production at the Fermilab Tevatron

The production of a Higgs boson in association with a W-boson is the most likely process for the discovery of a light Higgs at the Fermilab Tevatron. Since it decays primarily to b-quark pairs, the principal background for this associated Higgs production process is WBBbar, where the BBbar pair comes from the splitting of an off mass shell gluon. In this paper we investigate whether the spin angular correlations of the final state particles can be used to separate the Higgs signal from the WBBbar background. We develop a general numerical technique which allows one to find a spin basis optimized according to a given criterion, and also give a new algorithm for reconstructing the W longitudinal momentum which is suitable for the WH and WBBbar processes.Comment: latex, 12 pages, 19 postscript figure

On a graph related to permutability in finite groups

This paper has been published in Annali di Matematica Pura ed Applicata. Series IV, 189(4):567-570 (2010). Copyright 2010 by Springer-Verlag. The final publication is available at www.springerlink.com. http://link.springer.com/article/10.1007%2Fs10231-009-0124-7 http://dx.doi.org/10.1007/s10231-009-0124-7For a finite group G we define the graph $\Gamma(G)$ to be the graph whose vertices are the conjugacy classes of cyclic subgroups of G and two conjugacy classes $\{\mathcal {A}, \mathcal {B}\}$ are joined by an edge if for some $\{A \in \mathcal {A},\, B \in \mathcal {B}\, A\}$ and B permute. We characterise those groups G for which $\Gamma(G)$ is complete.This paper has been suported by the research grants MTM2007-68010-C03-02 from MEC (Spain) and FEDER (European Union) and GV/2007/243 from Generalitat (Valencian Community).http://dx.doi.org/10.1007/s10231-009-0124-7Ballester Bolinches, A.; Cossey, J.; Esteban Romero, R. (2010). On a graph related to permutability in finite groups. Annali di Matematica Pura ed Applicata. 4(189). doi:10.1007/s10231-009-0124-74189Abe S., Iiyori N.: A generalization of prime graphs of finite groups. Hokkaido Math. J. 29(2), 391–407 (2000)Agrawal R.K.: Finite groups whose subnormal subgroups permute with all Sylow subgroups. Proc. Am. Math. Soc. 47(1), 77–83 (1975)Alejandre M.J., Ballester-Bolinches A., Pedraza-Aguilera M.C.: Finite soluble groups with permutable subnormal subgroups. J. Algebra 240(2), 705–722 (2001)Ballester-Bolinches A., Esteban-Romero R.: Sylow permutable subnormal subgroups of finite groups. J. Algebra 251(2), 727–738 (2002)Cooper C.D.H.: Power automorphisms of a group. Math. Z. 107, 335–356 (1968)Herzog M., Longobardi P., Maj M.: On a commuting graph on conjugacy classes of groups. Commun. Algebra 37(10), 3369–3387 (2009)Huppert B.: Endliche Gruppen I, vol. 134 of Grund. Math. Wiss. Springer, Berlin (1967)Longobardi P.: Gruppi finite a fattoriali modulari. Note Math. II, 73–100 (1982)Neumann B.: A problem of Paul Erdős on groups. J. Austral. Math. Soc. Ser. A 21, 467–472 (1976)Ore O.: Contributions to the theory of groups of finite order. Duke Math. J. 5, 431–460 (1939)Schmidt R.: Subgroup lattices of groups. De Gruyter Expositions in Mathematics, vol. 14. Walter de Gruyter, Berlin (1994)Zacher G.: I gruppi risolubli finiti in cui i sottogruppi di composizione coincidono con i sottogrupi quasi-normali. Atti Accad. Naz. Lincei Rend. cl. Sci. Fis. Mat. Natur. 37(8), 150–154 (1964

Red Queen Coevolution on Fitness Landscapes

Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve ex- ploring their fitness landscapes. Coevolution involves the coupling of species fit- ness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution com- menting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.Comment: 40 pages, 12 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (H. Richter and A. Engelbrecht, eds.). Springer Series in Emergence, Complexity, and Computation, 201

MKEM: a Multi-level Knowledge Emergence Model for mining undiscovered public knowledge

<p>Abstract</p> <p>Background</p> <p>Since Swanson proposed the Undiscovered Public Knowledge (UPK) model, there have been many approaches to uncover UPK by mining the biomedical literature. These earlier works, however, required substantial manual intervention to reduce the number of possible connections and are mainly applied to disease-effect relation. With the advancement in biomedical science, it has become imperative to extract and combine information from multiple disjoint researches, studies and articles to infer new hypotheses and expand knowledge.</p> <p>Methods</p> <p>We propose MKEM, a Multi-level Knowledge Emergence Model, to discover implicit relationships using Natural Language Processing techniques such as Link Grammar and Ontologies such as Unified Medical Language System (UMLS) MetaMap. The contribution of MKEM is as follows: First, we propose a flexible knowledge emergence model to extract implicit relationships across different levels such as molecular level for gene and protein and Phenomic level for disease and treatment. Second, we employ MetaMap for tagging biological concepts. Third, we provide an empirical and systematic approach to discover novel relationships.</p> <p>Results</p> <p>We applied our system on 5000 abstracts downloaded from PubMed database. We performed the performance evaluation as a gold standard is not yet available. Our system performed with a good precision and recall and we generated 24 hypotheses.</p> <p>Conclusions</p> <p>Our experiments show that MKEM is a powerful tool to discover hidden relationships residing in extracted entities that were represented by our Substance-Effect-Process-Disease-Body Part (SEPDB) model. </p

The INCREASE project: Intelligent Collections of food‐legume genetic resources for European agrofood systems

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources