Search results for: generalized weighted composition operators

Authors: Hisham Mughrabi

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Osteoporosis is one of the most common diseases in the world and, its seriousness lies in the lack of clear symptoms. The researcher aims to identify the impact of sports activities on osteoporosis and the body component of those with mild intellectual disabilities of students in the schools in Saudi Arabia -Medina. The research sample was selected in an intentional manner and consisted of 45 students and they were divided into two groups. The first group consisted of 23 individuals participate in sports and the second group consisted of 22 individuals does not participate in sports. The researcher used the descriptive method and collected the data by measuring osteoporosis using and ultrasound osteoporosis screening device (OSTEO PRO B.M. Tech) and measured the body composition by using a Tanita devise (Body Composition Analyzer TBF- 300 Tanita). The results indicated that there was a statistical significant difference between the two comparing groups in osteoporosis measurement and body composition for the benefit of the group of sport participants. The researcher recommended the need to involve individuals with mild intellectual disabilities in physical activities to improve their rate of osteoporosis and body composition as well as to develop sports programs for individuals with mild intellectual disabilities.

Keywords: body composition, mild intellectual disabilities, osteoporosis, physical activities

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Authors: Youngji Lee, Yonghyeon Jeon, Sunyoung Bu, Philsu Kim

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The aim of this paper is to construct an algorithm of time step control for the error correction method most recently developed by one of the authors for solving stiff initial value problems. It is achieved with the generalized Chebyshev polynomial and the corresponding error correction method. The main idea of the proposed scheme is in the usage of the duplicated node points in the generalized Chebyshev polynomials of two different degrees by adding necessary sample points instead of re-sampling all points. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. Two stiff problems are numerically solved to assess the effectiveness of the proposed scheme.

Keywords: stiff initial value problem, error correction method, generalized Chebyshev polynomial, node points

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Authors: Sara Kanzi, Izzet Sakalli

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The effect of Lorentz symmetry breaking (LSB) on the Hawking radiation of Schwarzschild-like black hole found in the bumblebee gravity model (SBHBGM) is studied in the framework of quantum gravity. To this end, we consider Hawking radiation spin-0 (bosons) and spin-12particles (fermions), which go in and out through the event horizon of the SBHBGM. We use the modified Klein-Gordon and Dirac equations, which are obtained from the generalized uncertainty principle (GUP) to show how Hawking radiation is affected by the GUP and LSB. In particular, we reveal that independent of the spin of the emitted particles, GUP causes a change in the Hawking temperature of the SBHBGM. Furthermore, we compute the semi-analytic greybody factors (for both bosons and fermions) of the SBHBGM. Thus, we reveal that LSB is effective on the greybody factor of the SBHBGM such that its redundancy decreases the value of the greybody factor. Our findings are graphically depicted.

Keywords: bumblebee gravity model, Hawking radiation, generalized uncertainty principle, Lorentz symmetry breaking

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Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

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Authors: Manoel Pereira, Alvaro Veiga, Camila Epprecht, Renato Costa

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This paper introduces an empirical version of the Esscher transform for risk-neutral option pricing. Traditional parametric methods require the formulation of an explicit risk-neutral model and are operational only for a few probability distributions for the returns of the underlying. In our proposal, we make only mild assumptions on the pricing kernel and there is no need for the formulation of the risk-neutral model for the returns. First, we simulate sample paths for the returns under the physical distribution. Then, based on the empirical Esscher transform, the sample is reweighted, giving rise to a risk-neutralized sample from which derivative prices can be obtained by a weighted sum of the options pay-offs in each path. We compare our proposal with some traditional parametric pricing methods in four experiments with artificial and real data.

Keywords: esscher transform, generalized autoregressive Conditional Heteroscedastic (GARCH), nonparametric option pricing

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Authors: Meetty Tomy, Arxhana G Thosar

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This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

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Authors: Safeer Hussain Khan

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In this paper, we introduce a two-step iterative algorithm to prove a strong convergence result for approximating common fixed points of three contractive-like operators. Our algorithm basically generalizes an existing algorithm..Our iterative algorithm also contains two famous iterative algorithms: Mann iterative algorithm and Ishikawa iterative algorithm. Thus our result generalizes the corresponding results proved for the above three iterative algorithms to a class of more general operators. At the end, we remark that nothing prevents us to extend our result to the case of the iterative algorithm with error terms.

Keywords: contractive-like operator, iterative algorithm, fixed point, strong convergence

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Authors: Sakhon Woothipatanapan, Surasit Prakobkit

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This paper presents a model for analysis the induced voltage of transmission lines (energized) acting on neighboring distribution lines (de-energized). From environmental restrictions, 22 kV distribution lines need to be installed under 115 kV transmission lines. With the installation of the two parallel circuits like this, they make the induced voltage which can cause harm to operators. This work was performed with the ATP-EMTP modeling to analyze such phenomenon before field testing. Simulation results are used to find solutions to prevent danger to operators who are on the pole.

Keywords: transmission system, distribution system, induced voltage, off-line operation

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Authors: Mustofa Ahda, Fiqri Rozi, Gina Noor Habibah, Mas Ulfah Lestari, Tomy Hardianto, Yuni Andriani

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The development of natural antioxidants in the Centella asiatica and Majapahit is a great potential. This research has been optimizing the composition of ethanol extract of Centella asiatica and leaves Majapahit as an antioxidants source using measure the free radical scavenging activity of DPPH. The results of the research showed that both the ethanol extract of Centella asiatica and leaves Majapahit has a total content of phenol. It is shown with the ability to reduce reagent Folin Ciocalteu become blue colour. The composition optimization of extract Centella asiatica leaves Majapahit = 30:70 has free radical scavenging activity of DPPH most well compared ethanol extract of Centella asiatica and leaves Majapahit. IC50 values for the composition of ethanol extract of Centella asiatica : leaves Majapahit = 30:70 is 0,103 mg/mL.

Keywords: antioxidant activity, Centella asiatica, Cresentia cujete, composition extract

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: H. R. Fazlollahi

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Dark Energy origin is unknown and so describing this mysterious component in large scale structure needs to manipulate our theories in general relativity. Although in most models, dark energy arises from extra terms through modifying Einstein-Hilbert action, maybe its origin traces back to fundamental aspects of ground energy of space-time given in quantum mechanics. Hence, diluting space-time in general relativity with quantum mechanics properties leads to the Karolyhazy relation corresponding energy density of quantum fluctuations of space-time. Through generalized uncertainty principle and an eye to Karolyhazy approach in this study we extend energy density of quantum fluctuations of space-time. Also, the application of this idea is considered in late time evolution and we have shown how extra term in generalized uncertainty principle plays as a plausible interaction term role in suggested model.

Keywords: generalized uncertainty principle, karolyhazy approach, agegraphic dark energy, cosmology

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: Anton G. Kalmykov, Andrew Yu. Bychkov, Georgy A. Kalmykov

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Nowadays, most oil reserves in Russia and all over the world are hard to recover. That is the reason oil companies are searching for new sources for hydrocarbon production. One of the sources might be high-carbon formations with unconventional reservoirs. Bazhenov formation is a huge source rock formation located in West Siberia, which contains unconventional reservoirs on some of the areas. These reservoirs are formed by secondary processes with low predicting ratio. Only one of five wells is drilled through unconventional reservoirs, in others kerogen has low thermal maturity, and they are of low petroliferous. Therefore, there was a request for tertiary methods for in-situ cracking of kerogen and production of oil. Laboratory experiments of Bazhenov formation rock hydrous pyrolysis were used to investigate features of the oil generation process. Experiments on Bazhenov rocks with a different mineral composition (silica concentration from 15 to 90 wt.%, clays – 5-50 wt.%, carbonates – 0-30 wt.%, kerogen – 1-25 wt.%) and thermal maturity (from immature to late oil window kerogen) were performed in a retort under reservoir conditions. Rock samples of 50 g weight were placed in retort, covered with water and heated to the different temperature varied from 250 to 400°C with the durability of the experiments from several hours to one week. After the experiments, the retort was cooled to room temperature; generated hydrocarbons were extracted with hexane, then separated from the solvent and weighted. The molecular composition of this synthesized oil was then investigated via GC-MS chromatography Characteristics of rock samples after the heating was measured via the Rock-Eval method. It was found, that the amount of synthesized oil and its composition depending on the experimental conditions and composition of rocks. The highest amount of oil was produced at a temperature of 350°C after 12 hours of heating and was up to 12 wt.% of initial organic matter content in the rocks. At the higher temperatures and within longer heating time secondary cracking of generated hydrocarbons occurs, the mass of produced oil is lowering, and the composition contains more hydrocarbons that need to be recovered by catalytical processes. If the temperature is lower than 300°C, the amount of produced oil is too low for the process to be economically effective. It was also found that silica and clay minerals work as catalysts. Selection of heating conditions allows producing synthesized oil with specified composition. Kerogen investigations after heating have shown that thermal maturity increases, but the yield is only up to 35% of the maximum amount of synthetic oil. This yield is the result of gaseous hydrocarbons formation due to secondary cracking and aromatization and coaling of kerogen. Future investigations will allow the increase in the yield of synthetic oil. The results are in a good agreement with theoretical data on kerogen maturation during oil production. Evaluated trends could be tooled up for in-situ oil generation by shale rocks thermal action.

Keywords: Bazhenov formation, fossil fuels, hydropyrolysis, synthetic oil

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Authors: Guesh Simretab Gebremedhin, Saumya Rajan Jena

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In this work, a septic B-spline scheme has been used to simplify the process of solving an approximate solution of the generalized Rosenau-regularized long-wave equation (GR-RLWE) with initial boundary conditions. The resulting system of first-order ODEs has dealt with Butcher’s fifth order Runge-Kutta (BFRK) approach without using finite difference techniques for discretizing the time-dependent variables at each time level. Here, no transformation or any kind of linearization technique is employed to tackle the nonlinearity of the equation. Two test problems have been selected for numerical justifications and comparisons with other researchers on the basis of efficiency, accuracy, and results of the two invariants Mᵢ (mass) and Eᵢ (energy) of some motion that has been used to test the conservative properties of the proposed scheme.

Keywords: septic B-spline scheme, Butcher's fifth order Runge-Kutta approach, error norms, generalized Rosenau-RLW equation

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Suleiman Ahmed Badayi

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Corporate governance literature is very wide and involves several empirical studies conducted on the relationship between board structure, composition and firm performance. The separation of ownership and control in organizations were aimed at reducing the losses suffered by the investors in the event of financial scandals. This paper reviewed the theoretical and empirical literature on the relationship between board composition and its impact on firm performance. The findings from the studies provide different results while some are of the view that board structure is related to firm performance, many empirical studies indicates no relationship. However, others found a U-shape relationship between firm performance and board structure. Therefore, this study argued that board structure is not much significant to determine the financial performance of a firm.

Keywords: board structure, composition, firm performance, corporate governance

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Authors: Mawarni Mohamed, Sharifah Shahira A. Hamid

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Leisure time is an important component to offset the sedentary lifestyle of the people. Women tend to benefit from leisure activities not only to reduce stress but also to provide opportunities for well-being and self-satisfaction. This study was conducted to investigate body composition and leisure time use among women in Selangor from the influences of community settlement. A total of 419 women aged 18-65 years were selected to participate in this study. Descriptive statistics, t-test and ANOVA were used to analyze the level of physical activity and the relationship between leisure-time use and body composition were made to analyze the physical lifestyles. The results showed that women with normal body composition seem to be involved in more passive activities than women with less weight gain and obesity. Thus, the study recommended that the government and other health and recreational agencies should develop more places and activities suitable for leisure preference for women in their community settlement so they become more interested to engage in more active recreational and physical activities.

Keywords: body composition, community settlement, leisure time, physical lifestyles

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Authors: M. Priscila Ramos, Omar O. Chisari, Juan Pablo Vila Martínez

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Current literature about trade liberalization of environmental goods and services (EGS) raises doubts about the extent of the triple win-win situation for trade, development and the environment. However, much of this literature does not consider the possibility that this agreement carries technological transmissions, either through trade or foreign direct investment. This paper presents a computable general equilibrium model calibrated for Argentina, where there are alternative technologies (one dirty and one clean according to carbon emissions) to produce the same goods. In this context, the trade liberalization of EGS allows to increase GDP, trade, reduce unemployment and improve the households welfare. However, the capital mobility appears as the key assumption to jointly reach the environmental target, when the positive scale effect generated by the increase in trade is offset by the change in the composition of production (composition and technical effects by the use of the clean alternative technology) and of consumption (composition effect by substitution of relatively lesspolluting imported goods).

Keywords: CGE modeling, CO2 emissions, composition effect, scale effect, technique effect, trade liberalization of EGS

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Authors: Tanju Teker, Yener Tekeli̇, Esra Karpuz

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Salvia species are known as medicinal plant and often used in public. The antimicrobial effects and essential oil composition of Salvia verticillata L. subsp. amasiaca were determined. The antimicrobial activity is determined by using disk diffusion method against two Gram-positive bacteria, two Gram-negative bacteria and one kind of yeast and essential oil composition was determined by GC - MS. As a result of antimicrobial analysis while sample has shown very strong antimicrobial activity against Staphylococcus aureus, moderately effective against Pseudomonas aeruginosa and low effective against Enterococcus faecalis, it has not shown antimicrobial activity against Escherichia coli and C. albicans. Trans-caryophyllene (% 35.07), germacrene-d (% 10.98) and caryopyllene oxide (% 5.81) are the main components of essential oil composition.

Keywords: salvia, medicinal plant, antimicrobial activity, essential oil

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Authors: Samia Sadouki Chibani, Abdelkamel Tari

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Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: bio-inspired algorithms, elephant herding optimization, QoS optimization, web service composition

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Authors: Jose Francisco Ferreira Ribeiro, Alexandre Bevilacqua Leoneti, Andre Lucirton Costa

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This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil.

Keywords: generalized assignment problem, logistics, optimization, scheduling

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Authors: V. Hakimzadeh, M. Noori, M. maleki

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The aim of this study was to determine the composition and antimicrobial effect of Mentha piperita essential oil in "in-vitro" condition. The chemical composition of the essential oil obtained by hydro-distillation was examined by GC/MS and the antimicrobial effect was studied on the growth of seven microbial species including Bacillus cereus, Pseudomonas aeruginosa and Proteus vulgaris using micro-dilution method. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined. Chemical composition analysis identified a total of 28 compounds in which the main components were menthol (32%), mentone (13.4), menthyl acetate (12%), 1,8-cineole (8.2%) and neomenthol (4%) representing 69.6 % of the total oil. Other separated components accounted for less than 30.4% of the oil. Results of antimicrobial analysis showed that the MIC values for Bacillus cereus, Pseudomonas aeruginosa and Proteus vulgaris was respectively 50, 200 and 100 µg/ml and the MBC was determined at 200, 400 and 200 µg/ml respectively. The results of the present study indicated that Mentha piperita essential oil had significant antimicrobial activity.

Keywords: antimicrobial activity, essential oil composition, Mentha piperita

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Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

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Authors: Ehsan Vaziri Goodarzi, Mahmood Houshmand, Omid Fatahi Valilai, Vahidreza Ghezavati, Shahrooz Bamdad

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One important paradigm of industry 4.0 is Cloud Manufacturing (CM). In CM everything is considered as a service, therefore, the CM platform should consider all service provider's capabilities and tries to integrate services in an equilibrium state. This research develops a framework for implementing manufacturing cloud service composition in the equilibrium state. The developed framework using well-known tools called axiomatic design (AD) and game theory. The research has investigated the factors for forming equilibrium for measures of the manufacturing cloud service composition. Functional requirements (FRs) represent the measures of manufacturing cloud service composition in the equilibrium state. These FRs satisfied by related Design Parameters (DPs). The FRs and DPs are defined by considering the game theory, QoS, consumer needs, parallel and cooperative services. Ultimately, four FRs and DPs represent the framework. To insure the validity of the framework, the authors have used the first AD’s independent axiom.

Keywords: axiomatic design, manufacturing cloud service composition, cloud manufacturing, industry 4.0

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Authors: Farrukh Javed, Krzysztof Podgórski

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We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: M. O. Olayiwola

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Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems.

Keywords: burger-fisher, modified variational iteration method, lagrange multiplier, Taylor’s series, partial differential equation

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Authors: Snehalata Tembhurne

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Introduction: A healthy menstrual cycle is a sign of women’s sound health.Various variables may influence the length and regularity of menstrual cycle.Studies have revealed that menstrual cycle abnormalities may be associated with psychological stress,lack of physical exercise, alteration in body composition,endocrine disturbances,higher estrogen levels as seen in obese females.Hence there is an urgent need to find out the relationship between variations in body mass composition(BMI & body fat%) with menstrual abnormalities like primary dysmenorrhoea. Aim: To find out the relationship between body mass composition and primary dysmenorrhea. Objectives: 1.To check whether there is any association between body mass index and primary dysmenorrhoea.2.To check whether there is any association between body fat percentage and primary dysmenorrhoea. NULL HYPOTHESES-There is no relationship between body mass composition and primary dysmenorrhea. Hypothesis: There exists a relationship between body mass composition and primary dysmenorrhea. Materials and Methods: The study was conducted over a period of 6 months with 90 samples selected on random basis. The procedure was explained to the participant and a written consent was taken thereafter. The participant was made to stand on the BODY COMPOSITION SCANNING MONITOR, which scanned the physical profile of the participant (height, weight, BMI, body fat percentage and visceral fat).Thereafter, the candidate was asked about her menstrual irregularities and was asked to grade her level of dysmenorrhoea (if present) using the Verbal Dimensional Dysmenorrhea Scale. Results: Chi square test of association was used to find out the association between body mass composition(body mass index,body fat percentage) and primary dysmenorrhea.The chi-square value for association between body mass index and primary dysmenorrhea was 38.63 p<0.001 which was statistically significant.The chi-square value for the association of body fat % & primary dysmenorrhea was 30.09,p<0.001which was statistically significant. Conclusion: Study shows that there exists a significant relationship between body mass composition and primary dysmenorrhea and as the value of Body mass index and body fat percentages goes on increasing in females, the severity of primary dysmenorrhea also increases.

Keywords: body mass index, body composition screening monitor, primary dysmenorrhea, verbal dimensional dysmenorrhea scale

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Authors: Fuad Al Sarari

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The purpose of the present paper is to study subclasses of analytic functions which generalize the classes of Janowski functions introduced by Polatoglu. We study certain convolution conditions. This leads to a study of the sufficient condition and the neighborhood results related to the functions in the class S (T; H; F ): and a study of new subclasses of analytic functions that are defined using notions of the generalized Janowski classes and -symmetrical functions. In the quotient of analytical representations of starlikeness and convexity with respect to symmetric points, certain inherent properties are pointed out.

Keywords: convolution conditions, subordination, Janowski functions, starlike functions, convex functions

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Authors: Howard Gomwe, Eunice Seekoe

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There is arguably dearth of literature regarding body physical fitness and body composition amongst primary schools in South Africa. For this reason, the study is aimed at investigating and accessing how body composition relates to physical fitness amongst learners between 9 – 14 years of age in the Eastern Cape Province of South Africa. In order to achieve this, a school-based cross-sectional survey was carried out among 876 primary school learners aged 9 to14 years. Body composition indicators were measured and/or calculated, whilst physical fitness was evaluated by a 20 m shuttle run, push-ups, sit and reach as well as sit-ups, according to the EUROFIT fitness standards. Out of 876 participants, a total of 870 were retained. Of these, 351 (40.34%) were boys and 519 (59.66%) were girls. The average age of learners was 11.04 ± 1.50 years, with boys having a importantly (p = 0.002) higher average age (M = 11.24; SD = 1.51 years) as compared to that of girls (M = 10.91; SD = 1.48 years). The non-parametric Spearman Rho correlation coefficients revealed several significant and negative relationships between body composition measurements with physical fitness characteristics, which were stronger in girls than in boys. The findings advocate for policy makers and responsible authorities to initiate the development of policies and interventions targeted at encouraging physical activity and healthy promotion among primary school learners in South Africa, especially in girls.

Keywords: BMI, body composition, physical fitness, children

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Authors: M. Mohemmed Sha Mohamed Kunju, Abdalla A. Al-Ameen Abdurahman, T. Manesh Thankappan, A. Mohamed Mustaq Ahmed Hameed

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Web service composition is an effective approach to complete the web based tasks with desired quality. A single web service with limited functionality is inadequate to execute a specific task with series of action. So, it is very much required to combine multiple web services with different functionalities to reach the target. Also, it will become more and more challenging, when these services are from different providers with identical functionalities and varying QoS, so while composing the web services, the overall QoS is considered to be the major factor. Also, it is not true that the expected QoS is always attained when the task is completed. A single web service in the composed chain may affect the overall performance of the task. So care should be taken in different aspects such as functionality of the service, while composition. Dynamic and automatic service composition is one of the main option available. But to achieve the actual functionality of the task, quality of the individual web services are also important. Normally the QoS of the individual service can be evaluated by using the non-functional parameters such as response time, throughput, reliability, availability, etc. At the same time, the QoS is not needed to be at the same level for all the composed services. So this paper proposes a framework that allows composing the services in terms of QoS by setting the appropriate weight to the non-functional parameters of each individual web service involved in the task. Experimental results show that the importance given to the non-functional parameter while composition will definitely improve the performance of the web services.

Keywords: composition, non-functional parameters, quality of service, web service

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