Search results for: measure of divergence

Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Neda Lovričević, Đilda Pečarić, Josip Pečarić

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The Jensen functional in its discrete form is brought in relation to the Csiszar divergence functional, this time via its monotonicity property. This approach presents a generalization of the previously obtained results that made use of interpolating Jensen-type inequalities. Thus the monotonicity property is integrated with the Zipf-Mandelbrot law and applied to f-divergences for probability distributions that originate from the Csiszar divergence functional: Kullback-Leibler divergence, Hellinger distance, Bhattacharyya distance, chi-square divergence, total variation distance. The Zipf-Mandelbrot and the Zipf law are widely used in various scientific fields and interdisciplinary and here the focus is on the aspect of the mathematical inequalities.

Keywords: Jensen functional, monotonicity, Csiszar divergence functional, f-divergences, Zipf-Mandelbrot law

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Authors: Vishal Jaunky, Jonas Grafström

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The development of the European Union’s (EU) single economic market and rapid technological change has resulted in major structural changes in EU’s member states economies. The general liberalization process that the countries has undergone together has convinced the governments of the member states of need to upgrade their economic and training systems in order to be able to face the economic globalization. Several signs of economic convergence have been found but less is known about the knowledge production. This paper addresses the convergence pattern of technological innovation in 13 European Union (EU) states over the time period 1990-2011 by means of parametric and non-parametric techniques. Parametric approaches revolve around the neoclassical convergence theories. This paper reveals divergence of both the β and σ types. Further, we found evidence of stochastic divergence and non-parametric convergence approach such as distribution dynamics shows a tendency towards divergence. This result is supported with the occurrence of γ-divergence. The policies of the EU to reduce technological gap among its member states seem to be missing its target, something that can have negative long run consequences for the market.

Keywords: convergence, patents, panel data, European union

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Benedict Barnes, Anthony Y. Aidoo

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A Divergence Regularization Method (DRM) is used to regularize the ill-posed Helmholtz equation where the boundary deflection is inhomogeneous in a Hilbert space H. The DRM incorporates a positive integer scaler which homogenizes the inhomogeneous boundary deflection in Cauchy problem of the Helmholtz equation. This ensures the existence, as well as, uniqueness of solution for the equation. The DRM restores all the three conditions of well-posedness in the sense of Hadamard.

Keywords: divergence regularization method, Helmholtz equation, ill-posed inhomogeneous Cauchy boundary conditions

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Authors: M. V. Belubekyan, S. R. Martirosyan

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On the example of an elastic rectangular plate streamlined by a supersonic gas flow, we have investigated the phenomenon of divergence and of panel flatter of the overrunning of the gas flow at a free edge under assumption of the presence of concentrated inertial masses and moments at the free edge. We applied a new approach of finding of solution of these problems, which was developed based on the algorithm for an analytical solution finding. This algorithm is easy to use for theoretical studies for the wides circle of nonconservative problems of linear elastic stability. We have established the relation between the characteristics of natural vibrations of the plate and velocity of the streamlining gas flow, which enables one to draw some conclusions on the stability of disturbed motion of the plate depending on the parameters of the system plate-flow. Its solution shows that either the divergence or the localized divergence and the flutter instability are possible. The regions of the stability and instability in space of parameters of the problem are identified. We have investigated the dynamic behavior of the disturbed motion of the panel near the boundaries of region of the stability. The safe and dangerous boundaries of region of the stability are found. The transition through safe boundary of the region of the stability leads to the divergence or localized divergence arising in the vicinity of free edge of the rectangular plate. The transition through dangerous boundary of the region of the stability leads to the panel flutter. The deformations arising at the flutter are more dangerous to the skin of the modern aircrafts and rockets resulting to the loss of the strength and appearance of the fatigue cracks.

Keywords: stability, elastic plate, divergence, localized divergence, supersonic panels flutter

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Philippe Gugler

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This contribution reflects some important questions regarding inter alia the economic development occurring in the light of the ASEAN’s goal of creating the ASEAN Economic Community (AEC) by 2015. We observe a continuing economic growth of GDP per capita over recent years despite the negative effects of the world economic crisis. IMF forecasts indicate that this trend will continue. The paper focuses on the analysis and comparison of economic growth trends of ASEAN countries.

Keywords: ASEAN, convergence, divergence, economic growth, globalization, integration

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Authors: Heidar Jafarizadeh, Hossein Keshtkar, Ahmad Sohankar

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Heat transfer and turbulent flow structure have been studied in a divergent ribbed duct with a varying duct geometry with Reynolds numbers of 7000 to 90000 using numerical methods. In this study, we confirmed our numerical results of a ribbed duct with an Initial slope of zero to 3 degree by comparing them to experimental data we had and investigated the impact of the ducts divergence on heat transfer and flow pattern in the 2-dimensional flow. Then we investigated the effect of tilting the ribs, on heat transfer and flow behavior. We achieved this by changing the ribs angles from a range of 40 to 75 degrees in a divergent duct and simulated the flow in 3-dimensions. Our results show that with an increase in duct divergence, heat transfer increases linearly and the coefficient of friction increases exponentially. As the results show, a duct with a divergence angle of 1.5 degree presents better thermal performance in comparison with all the angle range’s we studied. Besides, a ribbed duct with 40 degree rib orientation had the best thermal performance considering the simultaneous effects of pressure drop and heat transfer which were imposed on it.

Keywords: divergent ribbed duct, heat transfer, thermal performance, turbulent flow structure

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Authors: Dzmitry M. Kabanau, Vladimir V. Kabanov, Yahor V. Lebiadok, Denis V. Shabrov, Pavel V. Shpak, Gevork T. Mikaelyan, Alexandr P. Bunichev

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This article is deal with the experimental investigations of the laser diode matrixes (LDM) based on the AlGaAs/GaAs heterostructures (lasing wavelength 790-880 nm) to find optimal LDM parameters for active vision systems. In particular, the dependence of LDM radiation pulse power on the pulse duration and LDA active layer heating as well as the LDM radiation divergence are discussed.

Keywords: active vision systems, laser diode matrixes, thermal properties, radiation divergence

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Niloofar Fariborzi, Hamzeh Alipour, Kourosh Azizi, Neda Eskandarzade, Abozar Ghorbani

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The family Parvoviridae consists of a large diversity of single-stranded DNA viruses, which cause mild to severe diseases in both vertebrates and invertebrates. The Parvoviridae are classified into three subfamilies: Parvovirinae infect vertebrates, Densovirinae infects invertebrates, while Hamaparovirinae infects both vertebrates and invertebrates. Except for the NS1 region, which is the prime criterion for phylogeny analysis, other parts of the parvoviruses genome, such as UTRs, are diverse even among closely related viruses or within the same genus. It is believed that host switching in parvoviruses may be related to genetic changes in regions other than NS1; therefore, whole-genome screening is valuable for studying parvoviruses' host-virus interactions. The aim of this study was to analyze genome organization and phylogeny of the complete genome sequence of the 132 Paroviridae family members, focusing on viruses that infect invertebrates. The maximum and minimum divergence within each subfamily belonged to Densovirinae and Parvovirinae, respectively. The greatest evolutionary divergence was between Hamaparovirinae and Parvovirinae. Unclassified viruses were mostly from Parovirinae and had the highest divergence to densoviruses and the lowest divergence to Parovirinae viruses. In a phylogenetic tree, all hamparoviruses were found in the center of densoviruses, with the exception of Syngnathid Ichthamaparvovirus 1 (NC_055527), which was positioned between two Parvovirinae members (NC _022089 and NC_038544). The proximity of hamparoviruses members to some densoviruses strengthens the possibility that densoviruses may be the ancestors of hamaparoviruses or vice versa. Therefore, examination and phylogeny analysis of the whole genome is necessary to understand Parvoviridae family host selection.

Keywords: densoviruses, parvoviridae, bioinformatics, phylogeny

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Authors: Yu-Chen Wei

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The relationship between organizational human capital and organizational effectiveness have been a common topic of interest to organization researchers. Much of this research has concluded that higher human capital can predict greater organizational outcomes. Whereas human capital research has traditionally focused on organizations, the current study turns to the team level human capital. In addition, there are no known empirical studies assessing the effect of human capital divergence on team performance. Team human capital refers to the sum of knowledge, ability, and experience embedded in team members. Team human capital divergence is defined as the variation of human capital within a team. This study is among the first to assess the role of human capital divergence as a moderator of the effect of team human capital on team performance. From the traditional perspective, team human capital represents the collective ability to solve problems and reducing operational risk of all team members. Hence, the higher team human capital, the higher the team performance. This study further employs social learning theory to explain the relationship between team human capital and team performance. According to this theory, the individuals will look for progress by way of learning from teammates in their teams. They expect to have upper human capital, in turn, to achieve high productivity, obtain great rewards and career success eventually. Therefore, the individual can have more chances to improve his or her capability by learning from peers of the team if the team members have higher average human capital. As a consequence, all team members can develop a quick and effective learning path in their work environment, and in turn enhance their knowledge, skill, and experience, leads to higher team performance. This is the first argument of this study. Furthermore, the current study argues that human capital divergence is negative to a team development. For the individuals with lower human capital in the team, they always feel the pressure from their outstanding colleagues. Under the pressure, they cannot give full play to their own jobs and lose more and more confidence. For the smart guys in the team, they are reluctant to be colleagues with the teammates who are not as intelligent as them. Besides, they may have lower motivation to move forward because they are prominent enough compared with their teammates. Therefore, human capital divergence will moderate the relationship between team human capital and team performance. These two arguments were tested in 510 team-seasons drawn from major league baseball (1998–2014). Results demonstrate that there is a positive relationship between team human capital and team performance which is consistent with previous research. In addition, the variation of human capital within a team weakens the above relationships. That is to say, an individual working with teammates who are comparable to them can produce better performance than working with people who are either too smart or too stupid to them.

Keywords: human capital divergence, team human capital, team performance, team level research

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Authors: Omenogor, Happy Dumbi

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This paper examines the areas of convergence and divergence between English and Ųkwųanį (a language in Nigeria) vowel systems with particular emphasis on the front vowels. It specifies areas of difficulty for the average Ųkwųanį users of English and Ųkwųanį L1 users of English as a second language. The paper explains the nature of contrastive analysis, the geographical locations where Ųkwųanį is spoken as mother tongue as well as English and Ųkwųanį front vowels. The principles of establishing phonemes, minimal pairs in Ųkwųanį as well as the vowel charts in both languages are among the issues highlighted in this paper.

Keywords: convergence, divergence, English, Ukwųanį

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Authors: Ana Barbir, S. Ivelic Bradanovic, D. Pecaric, J. Pecaric

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We proved a converse to Sherman's inequality. Using the concept of f-divergence we obtained some inequalities for the well-known entropies, such as Shannon entropies that have many applications in many applied sciences, for example, in information theory, biology and economics Zipf-Mandelbrot law gave improvement in account for the low-rankwords in corpus. Applications of Zipf-Mandelbrot law can be found in linguistics, information sciences and also mostly applicable in ecological eld studies. We also introduced an entropy by applying the Zipf-Mandelbrot law and derived some related inequalities.

Keywords: f-divergence, majorization inequality, Sherman inequality, Zipf-Mandelbrot entropy

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Authors: Jyh-Yang Wu, Sheng-Gwo Chen

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In this paper, we present a simple effective numerical geometric method to estimate the divergence of a vector field over a curved surface. The conservation law is an important principle in physics and mathematics. However, many well-known numerical methods for solving diffusion equations do not obey conservation laws. Our presented method in this paper combines the divergence theorem with a generalized finite difference method and obeys the conservation law on discrete closed surfaces. We use the similar method to solve the Cahn-Hilliard equations on evolving spherical surfaces and observe stability results in our numerical simulations.

Keywords: conservation laws, diffusion equations, Cahn-Hilliard equations, evolving surfaces

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Authors: Mandy Tao Benec

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Propaganda, understood as a ‘deliberate attempt to persuade people to think and behave in a desired way’, contributes to the fabric of mass media discourse as an important component, albeit often under various alternative expressions except ‘propaganda’. When the word ‘propaganda’ does appear in the mainstream media of the West, it is often selectively applied upon undesiring parties such as China, the North Korea, Russia’s Putin, or terrorists, etc.. This attitude reveals an ‘us verse them’ mentality; and a presupposition that propaganda is something only ‘they’ do whilst ‘we’ do not. This phenomenon not only runs in danger of generating political naivety, but also calls for the necessity of re-examining propaganda which will benefit from analysing it in contrasting social and political environments. Therefore, this paper aims to compare how propaganda has been understood and put in practice both in the Anglo-American context and by the Chinese Communist Party (CCP). By revealing the convergence and divergence of the propaganda discourses between China and the West, it will help clarify the misconception and misunderstanding of the term. Historical narrative analysis and critical discourse analysis are the main methodologies. By carefully examining data from academic research on propaganda in both English and Chinese, the landscape of how propaganda is defined throughout different eras is mapped, with special attention paid to analysing the parallelism and/or correspondence between China and the West when applicable. Meanwhile, critically analysing the official documents such as speeches and guidelines for propaganda administration given by top-rank CCP leaders will help reveal that in contrast to the West’s ‘us-them’ mentality, China sees oneself in no difference with the Western democracies when propaganda is concerned. Major findings of this study will identify a series of convergence and divergence between Chinese and Western propaganda discourses, and the relationship between propaganda the ‘signified’ (its essence) and propaganda the ‘signifier’ (the term itself), including (yet not limited to): 1) convergence in China catching up with the West, acknowledging the perceived pejorative connotation of the term 2) divergence in propaganda activities disassociated from the term in the West; and convergence in adopting such practice when China following suit in its external propaganda towards the West 3) convergence in utilising alternative notions to replace ‘propaganda’, first by the West, then imported and incorporated enthusiastically by China into its propaganda discourse 4) divergence between China’s internal and external propaganda and the subsequent differentiation between in which contexts the CCP sees fit to utilise the concept 5) convergence between China and the West in their English language propaganda discourses, whilst simultaneous divergence in their presuppositions: ‘usthem’ by the West and ‘we are the same’ by China. To conclude, this paper will contribute to the study of propaganda and its discourse by analysing how propaganda is understood and utilised in both worlds, and hence to uncover the discourse power struggle between the two, which contributes to the propaganda discourse itself. Hence, to untie the misconception of propaganda.

Keywords: China, discourse, power, propaganda

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Authors: Manvender Singh

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Temperature is one of the most important climatic parameter for explaining the geographic distribution of ectothermic species. Empirical investigations on norms of the reaction according to developmental temperatures are helpful in analyzing the adapture capacity of a species which may be related to its ecological niche. In the present investigation, we have compared the effects of developmental temperatures on fecundity, hatchability, viability, and duration of development in five natural populations of Drosophila bipectinata along the latitudinal range. The clinal patterns for fecundity, as well as ovariole number, were observed which showed significant positive correlation (r=0.97). Similarly, hatchability and duration of development also revealed a positive correlation with latitude. Hence, suggesting the role of natural selection in maintaining the genetic divergence for life history traits along the north-south transect of the Indian Subcontinent.

Keywords: growth temperature, fecundity, hatchability, viability, duration of development, Drosophila

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

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Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Chawarat Rotejanaprasert, Andrew Lawson

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Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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Authors: K. P. Sandesh, M. H. Suman

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Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

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Authors: I. Arockiarani

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The focus of the paper is to furnish the entropy measure for a neutrosophic set and neutrosophic soft set which is a measure of uncertainty and it permeates discourse and system. Various characterization of entropy measures are derived. Further we exemplify this concept by applying entropy in various real time decision making problems.

Keywords: entropy measure, Hausdorff distance, neutrosophic set, soft set

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Authors: M. Fowsia, Dominic Xavier Fernando, Vinojitha, Rahamath Juliyana

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Aerofoil is a primary element to be designed during the initial phase of creating any new aircraft. It is the component that forms the cross-section of the wing. The wing is used to produce lift force that balances the weight which is acting downwards. The lift force is created due to pressure difference over the top and bottom surface which is caused due to velocity variation. At sub-sonic velocities, for a real fluid, we obtain a smooth flow of air over both the surfaces. In this era of high speed travel, commercial aircraft that can travel faster than speed of sound barrier is required. However transonic velocities cause the formation of shock waves which can cause flow separation over the top and bottom surfaces. In the transonic range, shock waves move across the top and bottom surfaces of the aerofoil, until both the shock waves merge into a single shock wave that is formed near the leading edge of theaerofoil. In this paper, a transonic aerofoil is designed and its aerodynamic properties at different velocities in the Transonic range (M = 0.8; 0.9; 1; 1.1; 1.2) are studied with the help of CFD. The Pressure and Velocity distributions over the top and bottom surfaces of aerofoil are studied and the variations of shock patterns, at different velocities, are analyzed. The analysis can be used to determine the effect of drag divergence on the lift created by the aerofoil.

Keywords: transonic aerofoil, cfd, drag divergence, shock formation, viscous flow

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: David Glassmeyer

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Quantitative reasoning is necessary to robustly understand mathematical concepts ranging from elementary to university levels. Quantitative reasoning involves identifying and representing quantities and the relationships between these quantities. Without reasoning quantitatively, students often resort to memorizing formulas and procedures, which have negative impacts when they encounter mathematical topics in the future. This study investigated how high school students’ quantitative reasoning could be fostered within a unit on arc measure and angle relationships. Arc measure, or the measure of a central angle that cuts off a portion of a circle’s circumference, is often confused with arclength. In this study, the researcher redesigned an activity to clearly distinguish arc measure and arc length by using a quantitative reasoning framework. Data were collected from high school students to determine if this approach impacted their understanding of these concepts. Initial data indicates the approach was successful in supporting students’ quantitative reasoning of these topics. Implications for the work are that teachers themselves may also benefit from considering mathematical definitions from a quantitative reasoning framework and can use this activity in their own classrooms.

Keywords: arc length, arc measure, quantitative reasoning, student content knowledge

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Authors: Ved Vrat Verma, Rani Gupta, Manisha Goel

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γ-glutamyltranspeptidase (GGT: EC 2.3.2.2) is an N-terminal nucleophile hydrolase conserved in all three domains of life. GGT plays a key role in glutathione metabolism where it catalyzes the breakage of the γ-glutamyl bonds and transfer of γ-glutamyl group to water (hydrolytic activity) or amino acids or short peptides (transpeptidase activity). GGTs from bacteria, archaea, and eukaryotes (human, rat and mouse) are homologous proteins sharing >50% sequence similarity and conserved four layered αββα sandwich like three dimensional structural fold. These proteins though similar in their structure to each other, are quite diverse in their enzyme activity: some GGTs are better at hydrolysis reactions but poor in transpeptidase activity, whereas many others may show opposite behaviour. GGT is known to be involved in various diseases like asthma, parkinson, arthritis, and gastric cancer. Its inhibition prior to chemotherapy treatments has been shown to sensitize tumours to the treatment. Microbial GGT is known to be a virulence factor too, important for the colonization of bacteria in host. However, all known inhibitors (mimics of its native substrate, glutamate) are highly toxic because they interfere with other enzyme pathways. However, a few successful efforts have been reported previously in designing species specific inhibitors. We aim to leverage the diversity seen in GGT family (pathogen vs. eukaryotes) for designing specific inhibitors. Thus, in the present study, we have used DIVERGE software to identify sites in GGT proteins, which are crucial for the functional and structural divergence of these proteins. Since, type II divergence sites vary in clade specific manner, so type II divergent sites were our focus of interest throughout the study. Type II divergent sites were identified for pathogen vs. eukaryotes clusters and sites were marked on clade specific representative structures HpGGT (2QM6) and HmGGT (4ZCG) of pathogen and eukaryotes clade respectively. The crucial divergent sites within 15 A radii of the binding cavity were highlighted, and in-silico mutations were performed on these sites to delineate the role of these sites on the mechanism of catalysis and protein folding. Further, the amino acid network (AAN) analysis was also performed by Cytoscape to delineate assortative mixing for cavity divergent sites which could strengthen our hypothesis. Additionally, molecular dynamics simulations were performed for wild complexes and mutant complexes close to physiological conditions (pH 7.0, 0.1 M ionic strength and 1 atm pressure) and the role of putative divergence sites and structural integrities of the homologous proteins have been analysed. The dynamics data were scrutinized in terms of RMSD, RMSF, non-native H-bonds and salt bridges. The RMSD, RMSF fluctuations of proteins complexes are compared, and the changes at protein ligand binding sites were highlighted. The outcomes of our study highlighted some crucial divergent sites which could be used for novel inhibitors designing in a species-specific manner. Since, for drug development, it is challenging to design novel drug by targeting similar protein which exists in eukaryotes, so this study could set up an initial platform to overcome this challenge and help to deduce the more effective targets for novel drug discovery.

Keywords: γ-glutamyltranspeptidase, divergence, species-specific, drug design

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Authors: Abdulrahman Fahim M. Alsulami

Abstract:

The current research seeks to explore the regulation of vaccine-related IP rights in light of the areas of divergence between the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement and investment treaties. The study is conducted in the context of the COVID-19 pandemic; therefore, it seems natural that a specific chapter is devoted to the examination of vaccine arrangements related to vaccine supplies. The chapter starts with the examination of a typical vaccine from the perspective of IP rights. It presents the distinctive features of vaccines as pharmaceutical products and investments, reviews the basics of their patent protection, reviews vaccines’ components, and discusses IPR protection of different components of vaccines. The subsection that focuses on vaccine development and licensing reviews vaccine development stages investigates differences between vaccine licensing in different countries and presents barriers to vaccine licensing. The third subsection, at the same time, introduces the existing arrangements related to COVID-19 vaccine supplies, including COVAX arrangements, international organizations’ assistance, and direct negotiations between governments and vaccine manufacturers.

Keywords: bilateral investment treaties, COVID-19 vaccine, IP rights, TRIPs agreement

Procedia PDF Downloads 183

Authors: Prittesh Patel, Ramar Krishnamurthy

Abstract:

In the present study, nine strains of C. falcatum obtained from different places and cultivars were characterized for sporulation, growth rate, and 18S rRNA gene sequence. All isolates had characteristic fast-growing sparse and fleecy aerial mycelia on potato dextrose agar with sickle shape conidia (length x width: varied from 20.0 X 3.89 to 25.52 X 5.34 μm) and blackish to orange acervuli with setae (length x width: varied from 112.37X 2.78 to 167.66 X 6.73 μm). They could be divided into two groups on the base of morphology; P1, dense mycelia with concentric growth and P2, sparse mycelia with uneven growth. Genomic DNA isolation followed by PCR amplification with ITS1 and ITS4 primer produced ~550bp amplicons for all isolates. Phylogeny generated by 18S rRNA gene sequence confirmed the variation in isolates and mainly grouped into two clusters; cluster 1 contained CoC671 isolates (cfNAV and cfPAR) and Co86002 isolate (cfTIM). Other isolates cfMAD, cfKAM, and cfMAR were grouped into cluster 2. Remaining isolates did not fall into any cluster. Isolate cfGAN, collected from Co86032 was found highly diverse of all the nine isolates. In a nutshell, we found considerable genetic divergence and morphological variation within C. falcatum accessions collected from different areas of south Gujarat, India and these can be used for the breeding program.

Keywords: Colletotrichum falcatum, ITS, morphology, red rot, sugarcane

Procedia PDF Downloads 127

Authors: K. Umbleja, M. Ichino

Abstract:

Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

Procedia PDF Downloads 162