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Framework to analyze customer's feedback in smartphone industry using opinion mining
In the present age cellular phones are the largest selling products in the world. Big Data Analytics is a method used for examining large and varied data, which we know as big data. Big data analytics is very useful for understanding the world of cellphone business. It is important to understand the requirements, demands, and opinions of the customer. Opinion Mining is getting more important than ever before, for performing analysis and forecasting customer behavior and preferences. This study proposes a framework about the key features of cellphones based on which, customers buy them and rate them accordingly. This research work also provides balanced and well researched reasons as to why few companies enjoy dominance in the market, while others do not make as much of an impact 2018 Institute of Advanced Engineering and Science. All rights resented. -
Analysis of secure cloud storage provisioning for medical image management system
Medical images are considered to be the most sensitive images as it contains various health related sensitive information of an individual and it is necessary for the health care organization to maintain the sensitivity of these images without anybody misusing these data. When these images are transferred digitally through a network in order to store it in cloud for easy access for the authorities of the health care system, it is important to compress and encrypt these images to reduce the size and safeguard the information before storing and make sure that these images are transferred securely. In this paper, we use Huffman Coding technique in order to compress the image for easy transmission and to consume less storage space in cloud. To maintain the confidentiality of these images Blowfish encryption methodology is used. Once the image undergoes compression and encryption, the encrypted image is transferred and stored in a cloud storage. IAEME Publication. -
Scrutinization of thermal radiation, viscous dissipation and Joule heating effects on Marangoni convective two-phase flow of Casson fluid with fluid-particle suspension
The impact of Marangoni convection on dusty Casson fluid boundary layer flow with Joule heating and viscous dissipation aspects is addressed. The surface tension is assumed to vary linearly with temperature. Physical aspects of magnetohydrodynamics and thermal radiation are also accounted. The governing problem is modelled under boundary layer approximations for fluid phase and dust particle phase and then Runge-Kutta-Fehlberg method based numeric solutions are established. The momentum and heat transport mechanisms are focused on the result of distinct governing parameters. The Nusselt number is also calculated. It is established that the rate of heat transfer can be enhanced by suspending dust particles in the base fluid. The temperature field of fluid phase and temperature of dust phase are quite reverse for thermal dust parameter. The radiative heat, viscous dissipation and Joule heating aspects are constructive for thermal fields of fluid and dust phases. The velocity of dusty Casson fluid dominates the velocity of dusty fluid while this trend is opposite in the case of temperature. Moreover qualitative behaviour of fluid phase and dust phase temperature/velocity are similar. 2018 -
Workflow Scheduling Using Heuristic Scheduling in Hadoop
In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud. The Korea Institute of Information and Communication Engineering. -
Pendant number of graphs
A decomposition of a graph G is a collection of its edge disjoint sub-graphs such that their union is G. A path decomposition of a graph is a decomposition of it into paths. In this paper, we define the pendant number ?p as the minimum number of end vertices of paths in a path decomposition of G and determine this parameter for certain fundamental graph classes. 2018 Academic Publications. -
Scrutinization of joule heating and viscous dissipation on MHD flow and melting heat transfer over a stretching sheet
The present paper deals with an analysis of the combined effect of Joule heating and viscous dissipation on an MHD boundary layer flow and melting heat transfer of a micro polar fluid over a stretching surface. Governing equations of the problem are transformed into a set of coupled nonlinear ordinary differential equations by applying proper transformations and then they are solved numerically using the RKF-45 method. The method is verified by a comparison with the established results with limiting solution. The influence of the various interesting parameters on the flow and heat transfer is analyzed in detail through plotted graphs. 2018 K.G. Kumar et al., published by Sciendo. -
Analysis of multimode oscillations caused by subsynchronous resonance on generator shaft
Series capacitors are installed in high voltage alternating current transmission lines to counteract the inductive reactance of the line. The resonance caused by series capacitors between electric system and mechanical system at frequencies less than the synchronous speed, leads to torsional oscillations. Undamped oscillations ma y cause a severe fatigue in the turbine generator shaft system. Rotating component undergoes various modes of oscillations when it is subjected to resonance. Rotor oscillate in different modes such as swing mode, super synchronous mode, electromechanical mode and torsional mode. Rotor dynamics of rotating structure depends on several factors like Coriolis Effect, moment of inertia and stiffness coefficient. Modal analysis using finite element method gives the natural frequency and mode shapes of any rotating structures. In this paper, a two mass rotating system which is analogous to turbine generator is subjected to resonance by adding series capacitors and its dynamic behavior is studied using finite element method. 2018 Lavoisier. -
A novel congestion-aware approach for ECC based secured WSN multicasting
--Multicasting in Wireless Sensor Networks greatly reduces the communication complexity between The Base station and set of sensor nodes deployed in a given region. It reduces the number of packets to be sent thus minimizing the chance of congestion. Still the existence of congestion appears due to improper channel utilization resulting in low throughput. In this paper, we have addressed the issue of congestion with reference to WSN multicasting. The Simulation results have shown that our approach is better in terms of throughput and delay compared with existing approaches. 2018, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Suicidal behavior prediction using data mining techniques
Background: Suicide is one of the most serious public health problem that has affected many people. After being recognized as a public health priority by the WHO (World Health Organization) various studies have been going out for its prevention. It is one of a serious health problem and it is preventable and can be controlled by proper interventions and study in the field. The objective of the study is to create a prediction model for individuals who are at higher risk of suicide by studying the different predictors of suicide such as depression, anxiety, hopelessness, stress etc. by using data mining techniques for the prediction. Study Design: Systematic review and predictive analysis for suicidal behavior. Methods: The research applies data mining process to analyze the data and on the basis of analysis create the model to predict suicidal behaviors present in the individual. Prediction is done on the basis of analysis of risk factors which are Depression, anxiety, hopelessness, stress, or substance misuse which is calculated by using various psychological measures such as Beck hopelessness scale,suicidal ideation subscale,hospital anxiety and depression scale.Various data mining algorithms for classification are compared for the purpose of prediction. Results: Six different data mining classification algorithms which are namely Classification Via Regression, Logistic Regression. Random Forest, Decision Table, SMO are compared and Classification Via Regression was found to the highest accuracy in prediction. Conclusions: Data required for the development of such a model requires continuous monitoring and needs to be updated on a periodic basis to increase the accuracy of prediction. IAEME Publication. -
Causal relationship between leverage and performance: Exploring Dhaka Stock Exchange
To magnify shareholders' returns, managers employ the use of debt in the firms' capital structure. However, excessive debt financing can often cause financial distress for the firms. In fact, various debt equity ratio levels may lead to different financial performance when compared for high levered and low levered firms. Thus, the aim of this paper is to examine the cause and effect relationship between financial leverage and financial performance of firms. To pursue the purpose, a purposive sample of 163 non-financial firms listed on the Dhaka Stock Exchange (DSE) was selected to conduct this study. Findings indicate that there was no significant difference in the financial performance between high levered and low levered firms, neither in terms of their size nor growth rates. A negative relationship therefore persists between leverage and performance of such firms. Implications of these findings can provide policy guidelines for managers and directions for any further work in this context. Copyright 2018 Inderscience Enterprises Ltd. -
DFT, spectroscopic studies, NBO, NLO and Fukui functional analysis of 1-(1-(2,4-difluorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethylidene) thiosemicarbazide
A novel triazole derivative 1-(1-(2,4-difluorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethylidene) thiosemicarbazide was synthesized and subjected to density functional theory (DFT) studies employing B3LYP/6-31+G(d,p) basis set. Characterization was done by FT-IR, Raman, mass, 1H NMR and 13C NMR spectroscopic analyses. The stability of the molecule was evaluated from NBO studies. Delocalization of electron charge density and hyper-conjugative interactions were accountable for the stability of the molecule. The dipole moment (?), mean polarizabilty (??) and first order hyperpolarizability (?) of the molecule were calculated. Molecular electrostatic potential studies, HOMO-LUMO and thermodynamic properties were also determined. HOMO and LUMO energies were experimentally determined by Cyclic Voltammetry. 2018 Elsevier B.V. -
Provably secure quantum key distribution By applying quantum gate
The need for Quantum Key Distribution (QKD) is strengthening due to its inalienable principles of quantum mechanics. QKD commences when sender transforms bits into qubits or quantum states by applying photon polarization and sends to the receiver. The qubits are altered when measured in incorrect polarization and cannot be reproduced according to quantum mechanics principles. BB84 protocol is the primary QKD protocol announced in 1984. This paper introduces a new regime of secure QKD using Hadamard quantum gate named as PVK16 QKD protocol. Applying quantum gate to QKD makes tangle to the eavesdroppers to measure the qubits. For a given length of key, it is shown that the error rate is negligible. Also, the authentication procedure using digital certificates prior to QKD is being performed which confers assurance that the communicating entities are legitimate users. It is used as a defensive mechanism on man in the middle attack. The Japan Society for Analytical Chemistry. -
Significance of buoyancy, velocity index and thickness of an upper horizontal surface of a paraboloid of revolution: The case of non-Newtonian carreau fluid
The problem of fluid flow on air-jet weaving machine (i.e. mechanical engineering and chemical engineering) is deliberated upon in this report using the case of non-Newtonian Carreau fluid flow. In this report, the boundary layer flow of the fluid over an upper horizontal surface of a paraboloid of revolution is presented. The dimensional governing equations were nondimensionalized, parameterized, solved numerically and discussed. Maximum horizontal velocity is ascertained at smaller values of thickness parameter, a larger value of buoyancy related parameter and the flow is characterized as shear-thickening. Local skin friction coefficient is an increasing and a decreasing property of Deborah number for Shear thinning and Shear-thickening cases of the flow respectively. The velocity of the flow parallel to the surface (uhspr) is a decreasing property of thickness parameter and increasing function of velocity index parameter. 2018 Trans Tech Publications, Switzerland. -
UVIT observations of the star-forming ring in NGC 7252: Evidence of possible AGN feedback suppressing central star formation
Context. Some post-merger galaxies are known to undergo a starburst phase that quickly depletes the gas reservoir and turns it into a red-sequence galaxy, though the details are still unclear. Aims. Here we explore the pattern of recent star formation in the central region of the post-merger galaxy NGC 7252 using high-resolution ultraviolet (UV) images from the UVIT on ASTROSAT. Methods. The UVIT images with 1.2 and 1.4 arcsec resolution in the FUV and NUV are used to construct a FUV-NUV colour map of the central region. Results. The FUV-NUV pixel colour map for this canonical post-merger galaxy reveals a blue circumnuclear ring of diameter ?10?? (3.2 kpc) with bluer patches located over the ring. Based on a comparison to single stellar population models, we show that the ring is comprised of stellar populations with ages ? 300 Myr, with embedded star-forming clumps of younger age (? 150Myr). Conclusions. The suppressed star formation in the central region, along with the recent finding of a large amount of ionised gas, leads us to speculate that this ring may be connected to past feedback from a central super-massive black hole that has ionised the hydrogen gas in the central ?4?? ?1.3 kpc. ESO 2018. -
A hybrid algorithm for face recognition using PCA, LDA and ANN
Face recognition is an evolving technique in the field of digital device security. The two procedures Principal Component Analysis and Linear Discriminant Analysis (LDA) are standard methodologies commonly used for feature extraction and dimension reduction techniques extensively used in the recognition of face system. This paper discourse, PCA trailed through a feed forward neural network (FFNN) called PCA-neural network and LDA trailed through feed forward neural network as LDA-neural network are considered for development of hybrid face recognition algorithm. In the current research work, a hybrid model of face recognition is presented with the integration of PCA, LDA, and FFNN. The proposed system experimental results indicate better performance compared to the state of the art literature methods. IAEME Publication. -
Smart songs selection in playlists using parallel k-means clustering
Most songs today are of different tempo, pitch and time signature. In a music player application, the typical shuffle picks the succeeding song or preceding song at random with no parameters to choose the songs. Different songs from different genres can have a tempo range anywhere between forty beats per minute and three hundred beats per minute. In this paper, the quick and efficient parallel k means clustering algorithm is implemented in Hadoop on the million-song dataset subset to form clusters for the songs based on tempo and pitch. The aim of this paper is to reduce the variation that occurs when a typical shuffle picks the succeeding song at random. This variation can be in the form of tempo or other parameters. The formation of clusters and intern the reduction in the variation of tempo can be used in a new 'smart shuffle'. After the clusters have been formed, the smart shuffle picks the songs within that specific cluster. This paper aims at reducing the variation by 50%. This would have many musical benefits and would also be more pleasing to the listener. 2018 IAEME Publication. -
Potential flow simulation through Lagrangian interpolation meshless method coding
From the past many decades, mesh generation posed many challenges in the field of computational sciences for many researches. High rise in computational power has enabled many researches to tackle the problems of complex geometries. Due to the high need of computational power, computational cost also increased abruptly. In today's world, many academic and industry researches are willing to increase the use of present simulation technology; mesh generation plays a vital role in this aspect. we can say that many real-world simulation problems are dependent on mesh generation which has more chances in giving an inaccurate simulation results. In order to make the simulation process simpler, Meshless methods are introduced to the field of Computational Fluid Dynamics. This technique requires a less computational power compared to the computational power needed for generating the mesh. In the present dissertation, our main objective is to develop a scheme for Meshless method for the field of Computational Fluid Dynamics for flow over a blunt body. The performance of the present scheme is evaluated by comparing the simulation results with existing experimental data and also compared with the results obtained by generation of mesh using commercial CFD software. 2018 Isfahan University of Technology. -
Microscale screen printing of large-area arrays of microparticles for the fabrication of photonic structures and for optical sorting
There are a limited number of methods applicable to the large-scale fabrication of arrays of discrete microparticles; however, such methods can be applied to the fabrication of structures applicable to photonics, barcoding, and optoelectronics. This manuscript describes a universal method, "microparticle screen printing" (?SP), for the rational patterning of micron-scale particles onto a variety of 2D substrates with diverse mechanical and chemical properties. Specifically, an array of microparticles of different sizes and compositions were patterned onto an array of materials of varying chemistry and stiffness using ?SP yielding a diversity of homo/heterogeneous microparticle-based structures. Further, this manuscript reports how the Young's moduli of the substrate can be used to calculate contact area and thus interaction energies (quantified using Hamaker constants) between the particle/substrate during ?SP. Generally, ?SP is most effective for substrates with low Young's moduli and large Hamaker constants (A132) with the target particles, as confirmed by the performance (quantified using yield and accuracy metrics) of ?SP for the different empirically investigated particle/substrate combinations. These understandings allow for the design of optimal surface/particle pairing for ?SP and were applied to the fabrication of a diversity of heterogeneous structures, including those with periodic vacancies in HCP (hexagonally closed packed) 2D photonic crystal useful to structural optics, optical particle screening useful to chemical assays, and the fabrication of structural barcodes useful for labeling and anticounterfeiting. 2018 The Royal Society of Chemistry. -
Implementation of digital signature using hybrid cryptosystem
Security is a major concern when it comes to electronic data transfer. Digital signature uses hash function and asymmetric algorithms to uniquely identify the sender of the data and it also ensures integrity of the data transferred. Hybrid encryption uses both symmetric and asymmetric cryptography to enhance the security of the data. Digital Signature is used to identify the owner of the document but it does not hide the information while transferring the document. Anyone can read the message. To avoid this, data sent along with the signature should be secured. In this paper, Digital signature is combined with hybrid encryption to enhance the security level. Security of the data or the document sent is achieved by using hybrid encryption technique along with digital signature. 2018 Authors. -
Dual solutions for unsteady stagnation-point flow of prandtl nanofluid past a stretching/shrinking plate
Dual solutions for the time-dependent flow of a Prandtl fluid containing nanoparticles along a stretching/shrinking surface are presented. The nano Prandtl fluid fills the porous stretching/shrinking surface. The Buongiorno model is employed by accounting Brownian motion and thermophoresis slip mechanisms in the analysis. The relevant nonlinear problem is treated numerically via Runge-Kutta-Fehlberg scheme. The flow profiles are scrutinized with respect to the different governing parameters. Results of this study indicate that the temperature boundary layer thickness increased due to the influence of nanoparticles. 2018 Trans Tech Publications, Switzerland.