Search results for: generalized random graphs

Authors: Rongli Gai, Zhiyuan Chang

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At this stage, in view of various situations in the interpolation process, most researchers use self-adaptation to adjust the interpolation process, which is also one of the current and future research hotspots in the field of CNC machining. In the interpolation process, according to the overview of the spline curve interpolation algorithm, the adaptive analysis is carried out from the factors affecting the interpolation process. The adaptive operation is reflected in various aspects, such as speed, parameters, errors, nodes, feed rates, random Period, sensitive point, step size, curvature, adaptive segmentation, adaptive optimization, etc. This paper will analyze and summarize the research of adaptive imputation in the direction of the above factors affecting imputation.

Keywords: adaptive algorithm, CNC machining, interpolation constraints, spline curve interpolation

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Authors: Khizar Hayat Bhatti, Fiza Javed, Misbah Zafar

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Oat (Avena sativa L.) is a major cereal plant belonging to the family Poaceae. It is a very important source of carbohydrates, starch, minerals, vitamins and proteins that are beneficial for general health. Plants grow in the heavy metals contaminated soils that results in decline in growth. Glycine betaine application may improve plant growth, survival and resistance to metabolic disturbances due to stresses. Heavy metals, like nickels, have been accumulated for a long time in the soil because of industrial waste and sewage. The experiment was intended to alleviate the detrimental effects of heavy metal nickel stress on two oat varieties ‘Sgd-2011 and Hay’ using Glycine betain. Nickel was induced through soil application while GB was applied as foliar spray. After 10 days of nickel treatment, an exogenous spray of glycine betaine on the intact plant leaves. Data analysis was carried out using a Completely Randomized Design (CRD) with three replications in this study. For the analysis of all the data of the current research, Mini-Tab 19 software was used to compare the mean value of all treatments and Microsoft Excel software for generating the bars graphs. Significant accelerated plant growth was recorded when Ni exposed plants were treated with GB. Based on data findings, 3mM GB caused significant recovery from Ni stress doses. Overall results also demonstrated that the sgd-2011 variety of oats had the greatest outcomes for all parameters.

Keywords: CRD, foliar spray method, glycine betaine, heavy metals, nickel, ROS

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Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

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Authors: Usman Yakubu, Muktar Haruna

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The paper examines the impact of the audit committee on the earning quality of the listed consumer goods sector in Nigeria. The study used data collected from annual reports and accounts of the 13 sampled companies for the periods 2007 to 2018. Data were analyzed by means of descriptive statistics to provide summary statistics for the variables; also, correlation analysis was carried out using the Pearson correlation technique for the correlation between the dependent and independent variables. Regression was employed using the Generalized Least Square technique since the data has both time series and cross sectional attributes (panel data). It was found out that the audit committee had a positive and significant influence on the earning quality in the listed consumer goods companies in Nigeria. Thus, the study recommends that competency and personal integrity should be the worthwhile attributes to be considered while constituting the committee; this could enhance the quality of accounting information. In addition to that majority of the committee members should be independent directors in order to allow a high level of independency to be exercised.

Keywords: earning quality, corporate governance, audit committee, financial reporting

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Authors: Geetika Sahu, Chanchal Chakraborty, Subhadeep Roy, Souri Banerjee

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We aim to investigate the growth mechanism of molybdenum disulfide quantum dots (MoS₂ QDs) under hydrothermal reaction conditions by exploring two important parameters that control the growth process – (i) reaction time and (ii) precursor concentration. This fundamental study will focus on tuning the particle size, which eventually alters the optical and electronic properties of the QDs due to the quantum confinement effect, as well as monitoring the spatial growth of quantum dot sheets prepared through the aggregation of individual quantum dots. Among the mentioned two parameters, the former dictates the duration of aggregation while the latter controls the aggregation rate. The hydrothermally synthesized QDs have been analyzed through morphological and optical tools, and we used fractal analysis to understand the growth process. With increasing reaction time T (at a constant precursor concentration ≈ 73mM), the growth process shows a crossover from a bottom-up to a top-down process at T= 14 hours. A non-monotonic behavior of average QD size ( d ) is observed on the other side of it ( d=7nm at T= 7 hours; d=16nm at T=14 hours; d=2nm at T=30 hours), which is supported by morphological studies like TEM and STEM, as well as optical studies like UV visible and PL spectra. Higher (lower) QD sizes correspond to lower (higher) bandgap and significant redshift (blueshift) in the PL spectra. The fractal dimension ( f) of the QD clusters shows a sudden drop from 1.92 at this particular time T=14 to 1.82 and saturates at this value afterward. This signifies the onset of the fragmentation of the clusters due to the unavailability of active precursors. To validate the role of the precursors that have been claimed, we have carried out photophysical and statistical studies at a constant reaction time (14 hours ) and have varied the precursor concentration instead. We observe a similar non-monotonic behavior in QD size (maximum size at ≈ 73mM) supported by the morphological and optical studies as the precursor concentration varies from 22mM ( d=10nm) to 125mM (d=7nm ). This is in agreement with fractal analysis, where the maximum df of 1.97 is observed at 73 mM which decreases at both higher ( df = 1.67 at 125mM ) and lower concentration ( df = 1.75 at 22mM). This impact of precursor concentration is consistent for all reaction times. The fractal dimension of the QD sheets formed during the seeding and growth process is replicated for different reaction times as well as precursor concentration values through numerical simulations of random walk process on a 2D square lattice.

Keywords: aggregation and fragmentation, fractal analysis, optical studies, random walk

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Authors: Apedzan Emmanuel Kighir

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This research investigates dividends smoothing among non-financial companies trading on the Nigerian Stock Exchange in an era of unclaimed dividends from 2004 to 2013. There has been a raging controversy among Regulatory Authorities, Company Executives, Registrars of Companies, Shareholders and the general public regarding the increasing incidence of unclaimed dividends in Nigeria. The objective of this study is to find out if corporate earnings management through dividends smoothing is implicated in unclaimed dividends among Nigerian non-financial firms. The research used panel data and employed Generalized Method of Moment as method of analysis. The research finds evidence of dividends-smoothing in this era of unclaimed dividends in Nigeria. The research concludes that dividends-smoothing is a trigger and red flag for unclaimed dividends, an output of earnings management. If earnings management and hence unclaimed dividends in Nigeria is allowed to continue, it will lead to great consequences to the investors and corporate policy of government. It is believed that the research will assist investors and government in making informed decisions regarding dividends policy in Nigeria.

Keywords: dividends smoothing, non financial companies, Nigerian stock exchange, unclaimed dividends, corporate earnings management

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Aminul Islam

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The issue of aging is now an emerging aspect of all over the world. Both the rural and urban societies of our country are not immune from this problem. This study mainly explored the influence of wealth on the enjoyment of role and status of the elderly in rural Bangladesh. It is based on empirical findings from the four villages of Gopalnagar union of Dhunat upazila of Bogra district. The study depicted that wealth has much influence regarding the enjoyment of role and status. Mixed approach has been given priority in this study. Survey, observation, case study and life history methods and focus group discussion technique have also been used in this study. Data have been collected from both primary and secondary sources. Simple random sampling procedure has also been followed in this study.

Keywords: wealth, role status, elderly

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Authors: Latif Adnane, C. E. Ait Zaouiat, M. Eddabbah

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In Wireless Body Area Networks, the issue of systems lifetime is a big challenge to complete. In this paper, we have tackled this subject to suggest some solutions. For this aim, we have studied some batteries characteristics related to human body temperature. Moreover, we have analyzed a mathematical model which defines sensors lifetime (battery lifetime). Based on this model, we note that the random access increases the energy consumption, because nodes are waking up during the whole superframe period. Results show that using scheduled mode access of IEEE 802.15.6 maximizes the lifetime function, by setting nodes in the sleep mode in the inactive period of transmission.

Keywords: battery, energy consumption, IEEE 802.15.6, lifetime, polling

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Rahul Saini, Roshan Lal

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The present paper deals with the free axisymmetric vibrations of bi-directional functionally graded circular plates using Mindlin’s plate theory and physical neutral surface. The temperature-dependent, as well as temperature-independent mechanical properties of the plate material, varies in radial and transverse directions. Also, temperature profile for one- and two-dimensional temperature variations has been obtained from the heat conduction equation. A simple computational formulation for the governing differential equation of motion for such a plate model has been derived using Hamilton's principle for the clamped and simply supported plates at the periphery. Employing the generalized differential quadrature method, the corresponding frequency equations have been obtained and solved numerically to retain their lowest three roots as the natural frequencies for the first three modes. The effect of various other parameters such as temperature profile, functionally graded indices, and boundary conditions on the vibration characteristics has been presented. In order to validate the accuracy and efficiency of the method, the results have been compared with those available in the literature.

Keywords: bi-directionally FG, GDQM, Mindlin’s circular plate, neutral axis, vibrations

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Authors: R. B. Ogunrinde, C. C. Jibunoh

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In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t.

Keywords: spectral decomposition, linear RHS, homogeneous linear systems, eigenvalues of the Jacobian

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Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

Keywords: counter-cyclical policy, fiscal rules, government efficiency, procyclical policy

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Authors: Shahadut Hossain

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Measurement errors in continuous covariates and/or misclassifications in categorical covariates are common in epidemiological studies. Regression analysis ignoring such mismeasurements seriously biases the estimated main and interaction effects of covariates on the outcome of interest. Thus, adjustments for such mismeasurements are necessary. In this research, we propose a Bayesian parametric framework for eliminating deleterious impacts of covariate mismeasurements in logistic regression. The proposed adjustment method is unified and thus can be applied to any generalized linear and non-linear regression models. Furthermore, adjustment for covariate mismeasurements requires validation data usually in the form of either gold standard measurements or replicates of the mismeasured covariates on a subset of the study population. Initial investigation shows that adequacy of such adjustment depends on the sizes of main and validation samples, especially when prevalences of the categorical covariates are low. Thus, we investigate the impact of main and validation sample sizes on the adjusted estimates, and provide a general guideline about these sample sizes based on simulation studies.

Keywords: measurement errors, misclassification, mismeasurement, validation sample, Bayesian adjustment

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Authors: Lukman Oyelami

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Studies have identified trade as a veritable tool for inclusive economic growth and poverty reduction in developing countries. However, contrary to the overwhelming pieces of evidence of the Asian tiger as a success story of beneficial trade, many African countries still experience poverty unabatedly despite active engagement in trade. Consequently, this study seeks to investigate the contributory effect of technological innovation on total export performance and specifically manufacturing exports of African countries. This is with a view to exploring manufacturing exports as a viable option for diversification. To achieve the empirical investigation this study, require Systems Generalized Method of Moments (sys-GMM) estimation technique was adopted based on the econometric realities inherent in the data utilized. However, the static technique of panel estimation of the Fixed Effects (FE) model was utilized for baseline analysis and robustness check. The conclusion from this study is that innovation generally impacts export performance of African countries positively, however, manufacturing export shows more sensitivity to innovation than total export. And, this provides a clear pathway for export diversification for many African countries that run a resource-based economy.

Keywords: innovation, export, GMM, Africa

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Authors: Veronica Sri Lestari, Sitti Nurani Sirajuddin, Kasmiyati Kasim

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The purpose of this research was to know the attitude of beef cattle farmers toward bio security practices. This research was conducted in Barru regency, South Sulawesi province, Indonesia, in 2014. Thirty beef cattle farmers were selected through random sampling. Primary and secondary data were collected through report, observation and deep interview by using questionnaire. Bio security practices consisted of 35 questions. Every answer of the question was scored based on three categories: score 1 (not important), score 2 (important) and 3 (very important). The results of this research showed that the attitude of beef cattle farmers toward bio security practices was categorized as important.

Keywords: attitude, beef cattle, biosecurity, farmers

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Authors: J. Bernasovska, I. Boronova, J. Poracova, M. Mydlarova Blascakova, V. Szabadosova, P. Ruzbarsky, E. Petrejcikova, I. Bernasovsky

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The paper presents the results of the molecular genetics analysis in sports research, with special emphasis to use genetic information in diagnosing of motoric predispositions in Roma boys from East Slovakia. The ability and move are the basic characteristics of all living organisms. The phenotypes are influenced by a combination of genetic and environmental factors. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. The aim of the presented study was to examine motion abilities and to determine the frequency of ACTN3 (R577X) gene in Roma children. Genotype data were obtained from 138 Roma and 155 Slovak boys from 7 to 15 years old. Children were investigated on physical performance level in association with their genotype. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor-Gene 6000 Corbett and Light Cycler 480 Roche). The software allows creating reports of any analysis, where information of the specific analysis, normalized and differential graphs and many information of the samples are shown. Roma children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in Roma children was different from controls. The frequency of XX genotype was 9.26%, RX 46.33% and RR was 44.41%. The frequency of XX genotype was 9.26% which is comparable to a frequency of an Indian population. Data were analyzed with the ANOVA test.

Keywords: ACTN3 gene, R577X polymorphism, Roma children, sport performance, Slovakia

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Authors: T. Padma, Jayashree S. Pillai

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Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.

Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis

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Authors: Chi-Yan Chu, Kai-Chi Chuang, Huang-Chung Cheng

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In this study, the RRAM devices with the TiN/Ti/HfO_x/TiN structure were fabricated, then the electrical characteristics of the devices without annealing and after 400 °C and 500 °C of the furnace annealing (FA) temperature processes were compared. The RRAM devices after the FA’s 400 °C showed the lower forming, set and reset voltages than the other devices without annealing. However, the RRAM devices after the FA’s 500 °C did not show any electrical characteristics because the TiN/Ti/HfO_x/TiN device was oxidized, as shown in the XPS analysis. From these results, the RRAM devices after the FA’s 400 °C showed the best electrical characteristics.

Keywords: RRAM, furnace annealing (FA), forming, set and reset voltages, XPS

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Authors: Mballa Abanda Luc Aurelien Serge, Henda Gnakate Biba, Kuate Guemo Romaric, Akono Rufine Nicole, Zabotom Yaya Fadel Biba, Petfiang Sidonie, Bella Suzane Jenifer

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original, and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological, and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation, and the question of modeling in the human sciences: mathematics, computer science, translation automation, and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal, and random music. The experimentation confirming the theorization, I designed a semi-digital, semi-analog application that translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music, and deterministic and random music). To test this application, I use music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). The translation is done (from writing to writing, from writing to speech, and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz, and world music or variety, etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: language, music, sciences, quantum entenglement

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Authors: Flaurence Benjamain, Michel Casperance

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We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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Authors: Barenten Suciu

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Classical matrix calculus and Routh-Hurwitz stability conditions, applied to the snake-like motion of the conical wheel axle, lead to the conclusion that the hunting mode is inherently unstable, and its natural frequency is a complex number. In order to analytically solve such a complicated vibration model, either the inertia terms were neglected, in the model designated as geometrical, or restrictions on the creep coefficients and yawing diameter were imposed, in the so-called dynamical model. Here, an alternative solution is proposed to solve the hunting mode, based on the observation that the bullet train wheel axle is equipped with cylindrical wheels. One argues that for such wheel treads, the geometrical hunting is irrelevant, since its natural frequency becomes nil, but the dynamical hunting is significant since its natural frequency reduces to a real number. Moreover, one illustrates that the geometrical simplification of the wheel causes the stabilization of the hunting mode, since the characteristic quartic equation, derived for conical wheels, reduces to a quadratic equation of positive coefficients, for cylindrical wheels. Quite simple analytical expressions for the damping ratio and natural frequency are obtained, without applying restrictions into the model of contact. Graphs of the time-depending hunting lateral perturbation, including the maximal and inflexion points, are presented both for the critically-damped and the over-damped wheel axles.

Keywords: bullet train, creep, cylindrical wheels, damping, dynamical hunting, stability, vibration analysis

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Authors: Adrian W. Egger, Savvas P. Triantafyllou, Eleni N. Chatzi

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The scaled boundary finite element method (SBFEM) is a semi-analytical numerical method, which introduces a scaling center in each element’s domain, thus transitioning from a Cartesian reference frame to one resembling polar coordinates. Consequently, an analytical solution is achieved in radial direction, implying that only the boundary need be discretized. The only limitation imposed on the resulting polygonal elements is that they remain star-convex. Further arbitrary p- or h-refinement may be applied locally in a mesh. The polygonal nature of SBFEM elements has been exploited in quadtree meshes to alleviate all issues conventionally associated with hanging nodes. Furthermore, since in 2D this results in only 16 possible cell configurations, these are precomputed in order to accelerate the forward analysis significantly. Any cells, which are clipped to accommodate the domain geometry, must be computed conventionally. However, since SBFEM permits polygonal elements, significantly coarser meshes at comparable accuracy levels are obtained when compared with conventional quadtree analysis, further increasing the computational efficiency of this scheme. The generalized stress intensity factors (gSIFs) are computed by exploiting the semi-analytical solution in radial direction. This is initiated by placing the scaling center of the element containing the crack at the crack tip. Taking an analytical limit of this element’s stress field as it approaches the crack tip, delivers an expression for the singular stress field. By applying the problem specific boundary conditions, the geometry correction factor is obtained, and the gSIFs are then evaluated based on their formal definition. Since the SBFEM solution is constructed as a power series, not unlike mode superposition in FEM, the two modes contributing to the singular response of the element can be easily identified in post-processing. Compared to the extended finite element method (XFEM) this approach is highly convenient, since neither enrichment terms nor a priori knowledge of the singularity is required. Computation of the gSIFs by SBFEM permits exceptional accuracy, however, when combined with hybrid quadtrees employing linear elements, this does not always hold. Nevertheless, it has been shown that crack propagation schemes are highly effective even given very coarse discretization since they only rely on the ratio of mode one to mode two gSIFs. The absolute values of the gSIFs may still be subject to large errors. Hence, we propose a post-processing scheme, which minimizes the error resulting from the approximation space of the cracked element, thus limiting the error in the gSIFs to the discretization error of the quadtree mesh. This is achieved by h- and/or p-refinement of the cracked element, which elevates the amount of modes present in the solution. The resulting numerical description of the element is highly accurate, with the main error source now stemming from its boundary displacement solution. Numerical examples show that this post-processing procedure can significantly improve the accuracy of the computed gSIFs with negligible computational cost even on coarse meshes resulting from hybrid quadtrees.

Keywords: linear elastic fracture mechanics, generalized stress intensity factors, scaled finite element method, hybrid quadtrees

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Authors: Rajasekhar Mamilla, G. Janardhana, G. Anjan Babu

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The present research studies analyses the students’ satisfaction with university performance regarding the reliability dimension, ability of professors and staff to perform the promised services with quality to students in the post-graduate courses offered by Sri Venkateswara University in India. The research is done with the notion that the student compares the perceived performance with prior expectations. Customer satisfaction is seen as the outcome of this comparison. The sample respondents were administered with the schedule based on the stratified random technique for this study. Statistical techniques such as factor analysis, t-test and correlation analysis were used to accomplish the respective objectives of the study.

Keywords: satisfaction, reliability, service quality, customer

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Authors: Niesha Douglas, Lisa Merriweather, Cathy Howell, Anna Sancyzk

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Many studies explain that mentoring in an academic setting contributes to student success and retention. However, in the United States, where the population is diverse and filled with multiple ethnic groups, mentoring has become too generalized and fails to offer a unique individualized experience for underrepresented minorities (URM). The purpose of this paper is to describe the findings of an ongoing qualitative study that investigates the relationships among STEM doctoral faculty and URM students. Several faculty from three different predominately white institutions (PWI) in the Southeastern region of the United States were interviewed and engaged in open dialogue about their experiences with mentoring. The data collection included semi-structured interviews that took place in the classroom (pre-COVID-19) as well as virtually. The theoretical framework draws on the idea of Critical Race Theory and how cultural, social constructs interfere with effective mentoring for URM Doctoral STEM students. The findings in this study suggest that though the faculty and several years of experience mentoring students, there were some gaps in understanding the needs of URM students and how mentoring is a unique relationship that should be specialized for each student and should not fit into one mold.

Keywords: culture, critical race theory, mentoring, STEM

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

Abstract:

In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

Procedia PDF Downloads 406

Authors: Moneesh Thakur, Hridayesh Prasad, Nikitasha Bora, Parimal Roy Choudhary, A. K. Samanta, Sanjeev Kumar

Abstract:

Canine demodicosis is a common parasitic condition which involves dog skin. Demodicosis in dogs is due the prominent growth of Demodex. Out of various canine Demodex spp., Demodex canis is the most often involved species. Canine demodicosis can occur as either a localized or generalized form of demodicosis severely affect the dogs and in non-treated dogs may cause death. This study was planned with the aim to screen and characterize the 18S rRNA gene of isolated Demodex canis. A total of 1200 dogs were screened during this study period. The skin scrapings of all the suspected dogs were examined under a microscope at 100X magnification for the presence of Demodex canis. The skin scrapings positive for Demodex canis were examined using PCR for confirmation. A total of 35 dogs were confirmed a positive result for D. canis based on 18S rRNA gene amplification by PCR. Further, the 18S rRNA gene of isolated Demodex canis was cloned and sequenced for genome analysis. On the sequence analysis, it was found that isolated sequence (GenBank Accession No. MK177513) had close similarity (99.7%) to that of D. canis genotype of China (Accession No. MG372254).

Keywords: PCR, phylogenetic analysis, cloning and sequening, Demodex canis

Procedia PDF Downloads 93

Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

Abstract:

Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

Procedia PDF Downloads 525

Authors: A. Bilek, M. Beldi, T. Cherfi, S. Djebali, S. Larbi

Abstract:

Finite elements analysis and photoelasticity are used to determine the stress field developed in a double edge notched specimen loaded in tension. The specimen is cut in a birefringent plate. Experimental isochromatic fringes are obtained with circularly polarized light on the analyzer of a regular polariscope. The fringes represent the loci of points of equal maximum shear stress. In order to obtain the stress values corresponding to the fringe orders recorded in the notched specimen, particularly in the neighborhood of the notches, a calibrating disc made of the same material is loaded in compression along its diameter in order to determine the photoelastic fringe value. This fringe value is also used in the finite elements solution in order to obtain the simulated photoelastic fringes, the isochromatics as well as the isoclinics. A color scale is used by the software to represent the simulated fringes on the whole model. The stress concentration factor can be readily obtained at the notches. Good agreements are obtained between the experimental and the simulated fringe patterns and between the graphs of the shear stress particularly in the neighborhood of the notches. The purpose in this paper is to show that one can obtain rapidly and accurately, by the finite element analysis, the isochromatic and the isoclinic fringe patterns in a stressed model as the experimental procedure can be time consuming. Stress fields can therefore be analyzed in three dimensional models as long as the meshing and the limit conditions are properly set in the program.

Keywords: isochromatic fringe, isoclinic fringe, photoelasticity, stress concentration factor

Procedia PDF Downloads 229