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This article investigates the colloidal study for water and ethylene glycol based nanofluids. The effects of Lorentz forces and thermal radiation are considered. The process of non-dimensionalities of governing equations is carried out successfully by means of similarity variables. Then, the resultant nonlinear nature of flow model is treated numerically via Runge-Kutta scheme. The characteristics of various pertinent flow parameters on the velocity, temperature, streamlines and isotherms are discussed graphically. It is inspected that the Lorentz forces favors the rotational velocity and rotational parameter opposes it. Intensification in the nanofluids temperature is observed for volumetric fraction and thermal radiation parameter and dominating trend is noted for γ-aluminum nanofluid. Furthermore, for higher rotational parameter, reverse flow is investigated. To provoke the validity of the present work, comparison between current and literature results is presented which shows an excellent agreement. It is examined that rotation favors the velocity of the fluid and more radiative fluid enhances the fluid temperature. Moreover, it is inspected that upturns in volumetric fraction improves the thermal and electrical conductivities.

New exact solutions of the space–time conformable Caudrey–Dodd–Gibbon (CDG) equation have been derived by implementing the conformable derivative. The generalized Riccati equation mapping method is applied to figure out twenty-seven forms of exact solutions, which are soliton, rational, and periodic ones. Also, for some suitable values of parameters, the exact solutions are found, namely dark, bell type, periodic, soliton, singular soliton, and several others, by using the conformable derivative. These types of solutions have not been proclaimed so far. 2D and 3D graphical patterns of some solutions are also given for clarification of physical features. The conformable derivative is one of the excellent choices to solve the nonlinear conformable problems arising in theory of solitons and many other areas. The results are new and very interesting for the large community of researchers working in the field of mathematics and mathematical physics.

In this paper, a unique decomposition technique is implemented along with an auxiliary function for the best implementation. Some new and efficient techniques are introduced and analyzed for nonlinear equations. These techniques are higher ordered in approaching to the root of nonlinear equations. Some existing classical methods such as the Newton method, Halley method, and Traub's approach and their various modified forms are the special cases of these newly purposed schemes. These new iterative schemes are a good addition in existing methods and are also a comprehensive and generalized form for finding the solution of nonlinear equations.

As an emerging and promising approach, crowdsourcing-based software development has become popular in many domains due to the participation of talented pool of developers in the contests, and to promote the ability of requesters (or customers) to choose the ‘wining’ solution with respect to their desired quality levels. However, due to lack of a central mechanism for team formation, continuity in the developer’s work on consecutive tasks and risk of noise in submissions of a contest, there is a gap between the requesters of a domain and their quality concerns related to the adaptation of a crowdsourcing-based software development platform. In order to address concerns and aid requesters, we describe three measures; Quality of Registrant Developers (QRD), Quality of Contest (QC) and Quality of Support (QS) to compute and predict the quality of a crowdsourcing-based platform through historical information on its completed tasks. We evaluate the capacity of the QRD, QC and QS as assessors to predict the quality. Subsequently, we implement a crawler to mine the information of completed development tasks from the TopCoder platform to inspect the proposed measures. The promising results of our QRD, QC, and QS measures suggest to use the proposed measures to the requesters and researchers of other domains such as pharmaceutical research and development, in order to investigate and predict the quality of crowdsourcing-based software development platforms.

By making use of new linear fractional differential operator, we introduce and study certain subclasses of analytic functions associated with Symmetric Conjugate Points and defined in the open unit disk 𝕌 = {z : |z| < 1}. Inclusion relationships are established and convolution properties of functions in these subclasses are discussed.

Various problems of pure and applied sciences can be studied in the unified framework of nonlinear equations. In this paper, a new family of iterative methods for solving nonlinear equations is developed by using a new decomposition technique. The convergence of the new methods is proven. For the implementation and performance of the new methods, some examples are solved and the results are compared with some existing methods.

A well representing feature set that has enough differentiated power plays an important role in the classification. The existing techniques for feature set selection are mostly statistical. They are not flexible to incorporate the human reasoning and the changing requirements and preferences of the real-life systems. They only make a decision between a feature inclusion or exclusion. The fuzziness of human reasoning and thinking are not considered at all that may improve the feature selection and hence the accuracy of the classifier. Also, the selection of overlapping features in case of Local Feature Selection (LFS) methods is an important issue that negatively impacts classification accuracy. For example, in case of Odd Ratio (OR), the selection may contain overlapping features of multiple classes. In this paper, a Fuzzy Set Theory (FST) based feature selection method has been proposed. The approach aims to tackle both above mentioned issues efficiently. The selected final feature set is used to train the well-known classification algorithms and the results are compared with Global Feature Selection (GFS) and LFS methods. The comparison shows that the proposed method has improved the accuracy of the classifiers and also extract comparatively small feature set that ultimately reduces the time complexity of the system.

Cryptocurrency is one of the emerging online currency of the modern era. Big companies are investing in this technology. However, some established companies still hesitate to use it. According to them, it is a volatile trend which will fade up eventually. There is no such authority which will provide them feasibility information. So, investors can be helped by providing them feasibility information about locations for cryptocurrency investment around the world. This paper aims to provide the aforementioned information to the investors. The proposed methodology is based on Topic modeling along with public opinion mining about cryptocurrencies, blockchain network, bitcoin, litecoin, and ethereum. The crawled data for other cryptocurrencies are much insufficient, so that are excluded from the study. In the proposed methodology, the top locations where cryptocurrency is widely used are identified, then in that particular locations' users concerns along with their sentiment analyses are investigated. Top locations are identified such as Australia, Denmark, Netherlands, and the USA etc. Almost 83.7% tweets of Sweden show positive sentiment for cryptocurrency investment which ranks as the highest having friendly environment for cryptocurrency investment. Similarly, the UK shows the least positive perception of cryptocurrency and blockchain technology usage. Some of the noteworthy terms found are legitimacy, authorization rules, volatility, profit, investment, and fluctuations. Which describe the users’ concerns/ interests’ about cryptocurrency. Investors can focus on all these areas during business. These subtopics can help business experts to evolve their businesses’ and to make them more sustainable on the basis of public perception.

The main concern is to explore an electro-magneto hydrodynamic (EMHD) squeezing flow of ( A g − F e 3 O 4 / H 2 O ) hybrid nanofluid between stretchable parallel Riga plates. The benefits of the use of hybrid nanofluids, and the parameters associated to it, have been analyzed mathematically. This particular problem has a lot of importance in several branches of engineering and industry. Heat and mass transfer along with nonlinear thermal radiation and chemical reaction effects have also been incorporated while carrying out the study. An appropriate selection of dimensionless variables have enabled us to develop a mathematical model for the present flow situation. The resulting mathematical method have been solved by a numerical scheme named as the method of moment. The accuracy of the scheme has been ensured by comparing the present result to some already existing results of the same problem, but for a limited case. To back our results further we have also obtained the solution by anther recipe known as the Runge-Kutta-Fehlberg method combined with the shooting technique. The error analysis in a tabulated form have also been presented to validate the acquired results. Furthermore, with the graphical assistance, the variation in the behavior of the velocity, temperature and concentration profile have been inspected under the action of various ingrained parameters. The expressions for skin friction coefficient, local Nusselt number and local Sherwood number, in case of ( A g − F e 3 O 4 / H 2 O ) hybrid nanofluid, have been derived and the influence of various parameters have also been discussed.

Researchers have widely used statistical and machine learning techniques to construct prediction models in several domains such as prediction of software faults, spam detection, disease diagnosis, and financial fraud identification. The prediction of patients prone to lung cancer can help doctors in their decision making regarding their treatments. In this regard, this research paper attempts to evaluate the discriminative power of several predictors in the study to increase the efficiency of lung cancer detection through their symptoms. A number of classifiers including Support Vector Machine (SVM), C4.5 Decision tree, Multi-Layer Perceptron, Neural Network, and Naive Bayes (NB) are evaluated on a benchmark dataset obtained from UCI repository. The performance is also compared with well-known ensembles such as Random Forest and Majority Voting. Based on performance evaluations, it is observed that Gradient-boosted Tree outperformed all other individual as well as ensemble classifiers and achieved 90% accuracy.

As an emerging and promising approach, crowdsourcing-based software development becomes popular in many domains due to the participation of talented pool of developers in the contests, and to promote the ability of requesters (or customers) to choose the 'wining' solution with respect to their desire quality levels. However, due to lack of a central mechanism for team formation, continuity in the developer's work on consecutive tasks and risk of noise in submissions of a contest, requesters of a domain have quality concerns to adopt a crowdsourcing-based software development platform. In order to address this concern, we proposed a measure Quality of Contest (QoC) to analyze and predict the quality of a crowdsourcing-based platform through historical information on its completed tasks. We evaluate the capacity of QoC as assessor to predict the quality. Subsequently, we implement a crawler to mine the information of completed development tasks from the TopCoder platform of Tech Platform Inc (TPI) to empirically investigate the proposed measures. The promising results of QoC measure suggest the applicability of the proposed measure across the other crowdsourcing-based platforms.

The main concern is to explore an electro-magneto hydrodynamic (EMHD) squeezing flow of ( A g − F e 3 O 4 / H 2 O ) hybrid nanofluid between stretchable parallel Riga plates. The benefits of the use of hybrid nanofluids, and the parameters associated to it, have been analyzed mathematically. This particular problem has a lot of importance in several branches of engineering and industry. Heat and mass transfer along with nonlinear thermal radiation and chemical reaction effects have also been incorporated while carrying out the study. An appropriate selection of dimensionless variables have enabled us to develop a mathematical model for the present flow situation. The resulting mathematical method have been solved by a numerical scheme named as the method of moment. The accuracy of the scheme has been ensured by comparing the present result to some already existing results of the same problem, but for a limited case. To back our results further we have also obtained the solution by anther recipe known as the Runge-Kutta-Fehlberg method combined with the shooting technique. The error analysis in a tabulated form have also been presented to validate the acquired results. Furthermore, with the graphical assistance, the variation in the behavior of the velocity, temperature and concentration profile have been inspected under the action of various ingrained parameters. The expressions for skin friction coefficient, local Nusselt number and local Sherwood number, in case of ( A g − F e 3 O 4 / H 2 O ) hybrid nanofluid, have been derived and the influence of various parameters have also been discussed.

In the present work we introduce certain new subclasses of analytic functions in the open unit disk U . Then by using a quasi-Hadamard product we discuss their applications in the space of analytic functions.

An attempt has been made to give some criteria (Criteria II) for a function defined in the space of analytic functions to be univalent. Such criteria extend those obtained earlier from Ahlfors-type univalence criteria of analytic functions. We also discuss its application in the space of analytic functions.

Let \hskip 2pt $\mathcal{A}(n)$ \hskip 2pt denote \hskip 2pt the \hskip 2pt class \hskip 2pt of \hskip 2pt analytic \hskip 2pt functions \hskip 2pt $f$ \hskip 2pt in \hskip 2pt the \hskip 2pt open \hskip 2pt unit \hskip 2pt disk \hskip 2pt $U=\{z:|z

The purpose of the present study was to investigate the lipid lowering effect of Cinnamomum zeylanicum (Cinnamon) in hyperlipidaemic albino rabbits. For this purpose, forty eight albino rabbits were randomly divided into eight equal groups; untreated control on normal routine feed, untreated control on butter and cholesterol, treated control on synthetic cholesterol lowering drug simvastatin (Tablet survive (R) 20 mg), three treated groups on three respective doses of C. zeylanicum bark powder and two treated groups on water and methanol extracts of C. zeylanicum bark powder. Butter ad lib and cholesterol powder 500 mg/kg body weight were used to induce experimental hyperlipidaemia in all groups except untreated control group. The results suggested that C. zeylanicum bark powder at the rate of 0.50 g/kg, 0.75 g/kg and methanol extract equivalent to 0.75 g/kg powder produced respective percent reductions in total lipids by 45, 49 and 64; triglycerides by 38, 53 and 60; total cholesterol by 53, 64 and 69 and LDL-cholesterol by 50, 59 and 62. However, at these dosage levels HDL-cholesterol showed respective percent increase of 42, 48 and 53. Nonetheless, C. zeylanicum bark powder at the level of 0.25g/kg and C. zeylanicum extract in water could not significantly reduce lipid profile indicators. Based on these studies, it can safely be said that C. zeylanicum bark powder methanol extract equivalent to 0.75g/kg bark powder and simvastatin (0.6 mg/kg b. wt.) were equieffective in treating hyperlipidaemia.

An attempt has been made to give a criteria to a family of functions defined in the space of analytic functions to be univalent. Such criteria extended earlier univalence criteria of Pescar's-type of analytic functions.

In this paper, we shall study on some new subclasses of meromor‐phic functions in the punctured unit disk U = {z:0