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Excitation Mechanism of Oi Lines in Herbig Ae/Be Stars
We have investigated the role of a few prominent excitation mechanisms viz. collisional excitation, recombination, continuum fluorescence, and Lyman beta fluorescence on the O i line spectra in Herbig Ae/Be stars. The aim is to understand which of them is the central mechanism that explains the observed O i line strengths. The study is based on an analysis of the observed optical spectra of 62 Herbig Ae/Be stars and near-infrared spectra of 17 Herbig Ae/Be stars. The strong correlation observed between the line fluxes of O i ?8446 and O i ?11287, as well as a high positive correlation between the line strengths of O i ?8446 and H? suggest that Lyman beta fluorescence is the dominant excitation mechanism for the formation of O i emission lines in Herbig Ae/Be stars. Furthermore, from an analysis of the emission line fluxes of O i ??7774, 8446, and comparing the line ratios with those predicted by theoretical models, we assessed the contribution of collisional excitation in the formation of O i emission lines. 2018 The American Astronomical Society. All rights reserved.. -
The facile and efficient organocatalytic platform for accessing 1,2,4-selenadiazoles and thiadiazoles under aerobic conditions
The first organocatalytic approach towards synthesis of rarely explored 1,2,4-selenadiazole and thiadiazole scaffolds have been devised using corresponding carboxamides as substrates. The transformations were realized using two distinct conditions in the presence of catalytic vitamin B3 or thiourea under aerobic conditions. Developed methods overcome the associated limitations of previous reported approaches and the desired products were obtained in high yields and selectivity without the formation of toxic side-products. 2018 Elsevier Ltd -
Semantic image annotation using convolutional neural network and WordNet ontology
Images are a major source of content on the web. The increase in mobile phones and digital cameras have led to huge amount of non-textual data being generated which is mostly images. Accurate annotation is critical for efficient image search and retrieval. Semantic image annotation refers to adding meaningful meta-data to an image which can be used to infer additional knowledge from an image. It enables users to perform complex queries and retrieve accurate image results. This paper proposes an image annotation technique that uses deep learning and semantic labeling. A convolutional neural network is used to classify images and the predicted class labels are mapped to semantic concepts. The results shows that combining semantic class labeling with image classification can help in polishing the results and finding common concepts and themes. 2018 Jaison Saji Chacko, Tulasi B. -
De novo synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazolin-4(1H)-one compounds
A new versatile and efficient strategy for the synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazoline-4(1H)-one compounds has been developed by one-pot multicomponent reaction with isatoic anhydride, amines followed by in situ-generated Vilsmeier reagent. The reaction has also been studied with different amines and solvents. 2017 Taylor & Francis. -
Short term effects of brief need based psychoeducation on knowledge, self-stigma, and burden among siblings of persons with schizophrenia: A prospective controlled trial
Siblings of persons with schizophrenia are important in providing long-term social support to the patients. Interventions addressing their needs are very sparse. Hence, this study aimed at testing the short-term effects of brief need based psychoeducation on knowledge, self-stigma, and burden among siblings of persons with schizophrenia. In this prospective controlled open label trial, 80 siblings of persons with schizophrenia were allocated in equal numbers to the brief need based psychoeducation group and the treatment-as-usual group. The outcomes were measured at baseline, and after the first and third month post-intervention. RM-ANCOVA was conducted to test the effect of the brief psychoeducation on outcome scores. The groups were similar with respect to socio-demographic, clinical, and outcome scores at the baseline. There was a significant group time interaction effect on knowledge (F = 8.71; p < 0.01; ?p 2 = 0.14) and self-stigma scores (F = 14.47; p < 0.001; ?p 2 = 0.21), wherein the brief psychoeducation group showed a significant increase in knowledge and reduction in self-stigma with medium effect size through baseline to the third month follow-up as compared to the treatment as usual group. We also observed a significant main effect of time; irrespective of the group allocation, there was a significant increase in the knowledge through baseline to third month follow-up (F = 5.69; p = 0.02; ?p 2 = 0.09). No main or interaction effects of group and time were observed on burden. The findings suggest that brief need based psychoeducation may increase knowledge about the illness and reduce self-stigma. Further systematic studies are warranted to test this intervention for long-term effects. 2017 Elsevier B.V. -
Riding the waves of culture: An empirical study on acclimatization of expatriates in IT industry
The forces of globalization and subsequent trade across the borders have necessitated the firms to have their presence across the globe to meet the needs of their customers. The employees or expatriates will be sent on assignment to different countries for a period of time ranging from few weeks, months to years. This sudden exposure to the different environment not only makes these expatriates vulnerable to cultural shocks, but also may significantly affect their job performance. Their failure to acclimatize to the foreign conditions will not only hurt the confidence, career and life of the expatriate, but it will also cost a lot to the company. The present paper aims to understand of the process of expatriate adjustment in the Indian Information Technology (IT) industry by examining demographic variables and few organizational variables of expatriate's adjustment process. A structured questionnaire was distributed to the expatriate employees working in 50 IT companies in the Silicon city, Bengaluru. The study uses Chi-square test and linear regression for testing the hypotheses and found that there is a significant influence of demographic variables like gender, work experience and length of assignment on acclimatization of expatriates to their host country culture. The findings of the study proved that there is a significant relationship between demographic variables and the cultural acceptance of the expatriates. Hence, it is suggested that multinational companies should create an enabling environment within the organizations to make international assignees compatible and comfortable with different cultural values and inculcate cultural acceptance to make them successful in their international assignments. Raghavendra A. N., A. Shivakanth Shetty, 2018. -
Data analysis in road accidents using ann and decision tree
Road accidents have become some of the main causes for fatal death globally. A report tells that road accident is the major cause for high death rate other than wars and diseases. A study by World Health Organization (WHO), Global status report on road safety 2015 says over 1.24 million people die every year due to road accidents worldwide and it even predicts by 2020 this number can even increase by 20-50%. This can affect the GDP of the Country, for developing countries this can affect adversely. This paper shows the use of data analytics techniques to build a prediction model for road accidents, so that these models can be used in real time scenario to make some policies and avoid accidents. This paper has identified the attributes which has high impact on accident severity class label. IAEME Publication. -
Phishfort - Anti-phishing framework
Phishing attack is one of the most common form of attack used to get unauthorized access to users' credentials or any other sensitive information. It is classified under social engineering attack, which means it is not a technical vulnerability. The attacker exploits the human nature to make mistake by fooling the user to think that a given web page is genuine and submitting confidential data into an embedded form, which is harvested by the attacker. A phishing page is often an exact replica of the legitimate page, the only noticeable difference is the URL. Normal users do not pay close attention to the URL every time, hence they are exploited by the attacker. This paper suggests a login framework which can be used independently or along with a browser extension which will act as a line of defense against such phishing attacks. The semi-automated login mechanism suggested in this paper eliminates the need for the user to be alert at all time, and it also provides a personalized login screen so that the user can to distinguish between a genuine and fake login page quite easily. 2018 Authors. -
Taguchi-based ANN predictions to analyze the tensile strength of adhesive-bonded single lap joints
The adhesive bonding method is commonly used in various industries to join different materials because of its benefits, which include a high strength-to-weight ratio, low cost, and high efficiency properties. Automotive, aerospace, marine, and construction industries are increasingly using adhesively bonded joints because the hand layup techniques involve simpler fabrication methodologies, maintenance procedures, and controllable stress distribution parameters in the overlap region, which ultimately lead to easier production of automobile, aircraft, and ship components. The objective of the present work is primarily to assess the overlap length in conjunction with the adhesive strength of glass-epoxy adherends bonded with epoxy resin. In this article, the experiments are performed on single lap-bonded joints. The parameters considered for the current work involve the length of overlap, which is maintained at 15, 25, and 35 mm, and adhesive bonding thickness that is maintained at 0.2, 0.3, and 0.5 mm, respectively. The strength of the adhesively bonded lap joint is determined using a Universal Testing Machine (Lloyd Instruments Ltd., West Sussex, United Kingdom) with a 1-20 kN capacity. The investigational outcome reveals that, as the overlap length of the adhesively bonded single lap joint increases, a substantial increase in the joint strength is observed; additionally, it is noted that, with the increase in adhesive thickness, the joint strength decreases. It was observed that the artificial neural network-predicted values from the analysis were extremely close to the experimental values, and the difference between the experimental and predicted values was very small. Copyright 2018 by ASTM International. -
Effects of hall current on transient flow of dusty fluid with nonlinear radiation past a convectively heated stretching plate
Influence of Hall current on flow and heat transfer of dusty fluid over a convectively heated stretching plate in the presence of nonlinear thermal radiation is explored in this paper. The unsteadiness in the flow and temperature fields is because of the time-dependent stretching velocity and surface temperature. Suitable similarity transformations are used to convert the governing partial differential equations of momentum and thermal energy to a system of nonlinear ordinary differential equations. Consequent equations are solved by using shooting method. The details of the velocities, temperatures, local Nusselt number as well as local skin friction for various parameters such as unsteadiness parameter, thermal radiation, Hall effects, Biot number, Eckert number, Prandtl number and magnetic parameter are presented graphically and discussed in detail. 2018 Trans Tech Publications, Switzerland. -
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.