Design of an Interface for Page Rank Calculation using Web Link Attributes Information

This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment.HITS, Page Rank, Sel-HITS, Structure Mining

Multi-Sensor Event Detection using Shape Histograms

Vehicular sensor data consists of multiple time-series arising from a number of sensors. Using such multi-sensor data we would like to detect occurrences of specific events that vehicles encounter, e.g., corresponding to particular maneuvers that a vehicle makes or conditions that it encounters. Events are characterized by similar waveform patterns re-appearing within one or more sensors. Further such patterns can be of variable duration. In this work, we propose a method for detecting such events in time-series data using a novel feature descriptor motivated by similar ideas in image processing. We define the shape histogram: a constant dimension descriptor that nevertheless captures patterns of variable duration. We demonstrate the efficacy of using shape histograms as features to detect events in an SVM-based, multi-sensor, supervised learning scenario, i.e., multiple time-series are used to detect an event. We present results on real-life vehicular sensor data and show that our technique performs better than available pattern detection implementations on our data, and that it can also be used to combine features from multiple sensors resulting in better accuracy than using any single sensor. Since previous work on pattern detection in time-series has been in the single series context, we also present results using our technique on multiple standard time-series datasets and show that it is the most versatile in terms of how it ranks compared to other published results

Exploiting multimedia content : a machine learning based approach

Advisors: Prof. M Gopal, Prof. Santanu Chaudhury. Date and location of PhD thesis defense: 10 September 2013, Indian Institute of Technology DelhiThis thesis explores use of machine learning for multimedia content management involving single/multiple features, modalities and concepts. We introduce shape based feature for binary patterns and apply it for recognition and retrieval application in single and multiple feature based architecture. The multiple feature based recognition and retrieval frameworks are based on the theory of multiple kernel learning (MKL). A binary pattern recognition framework is presented by combining the binary MKL classifiers using a decision directed acyclic graph. The evaluation is shown for Indian script character recognition, and MPEG7 shape symbol recognition. A word image based document indexing framework is presented using the distance based hashing (DBH) defined on learned pivot centres. We use a new multi-kernel learning scheme using a Genetic Algorithm for developing a kernel DBH based document image retrieval system. The experimental evaluation is presented on document collections of Devanagari, Bengali and English scripts. Next, methods for document retrieval using multi-modal information fusion are presented. Text/Graphics segmentation framework is presented for documents having a complex layout. We present a novel multi-modal document retrieval framework using the segmented regions. The approach is evaluated on English magazine pages. A document script identification framework is presented using decision level aggregation of page, paragraph and word level prediction. Latent Dirichlet Allocation based topic modelling with modified edit distance is introduced for the retrieval of documents having recognition inaccuracies. A multi-modal indexing framework for such documents is presented by a learning based combination of text and image based properties. Experimental results are shown on Devanagari script documents. Finally, we have investigated concept based approaches for multimedia analysis. A multi-modal document retrieval framework is presented by combining the generative and discriminative modelling for exploiting the cross-modal correlation between modalities. The combination is also explored for semantic concept recognition using multi-modal components of the same document, and different documents over a collection. An experimental evaluation of the framework is shown for semantic event detection in sport videos, and semantic labelling of components of multi-modal document images

E-BANKING: A CASE STUDY OF ASKARI COMMERCIAL BANK PAKISTAN

This paper has covered the operational issues related to e-banking as well as customer’s perception on usage of e-banking a case study of Askari Bank, Pakistan. 40 staff members and four customers are selected as sample for this study. Both qualitative and quantitative methods are used to present the results. Descriptive statistics is applied to describe the demographic variables while for operational problems correlation was used. Finally cross case analysis present customers’ perception about e-banking practices. Analysis shows that customer is not ready to adopt new technology that why their satisfaction level with e-banking is low. Internet speed and government policies are not supportive for e-banking in Pakistan. Due to lack of trust on technology and low computer literacy rate, customer hesitates to adopt new technology. : In order to promote IT culture in Pakistan, government has to reduce the internet rate. to promote the benefits of e-banking on media so that more user get facilitated from e-banking services.E-banking, Internet, ATM, Online transaction, E-readiness, Technology Acceptance Models

DOES BRAND EXTENSION IMPACT PARENT BRAND: A CASE OF JOHNSON, UK

Purpose of study: The main purpose of this study is to check the impact of brand extensions on brand image. For this purpose Johnson is selected as parent brand for current research. The targeted brand extensions are Johnson shampoo, Johnson’s isotonic drinks, Johnson’s sports wear and Johnson’s suntan lotion. Research Methodology: sample was selected from Bradford, UK. Sample consists of graduate students including males as well as female. Total sample size is 60 and data was collected through self administered questionnaires. For each brand 15 respondents were selected. Convenient sampling was selected as sampling technique. Results: Results show that Johnson’s have high brand awareness and perceived quality. While there is negative correlation results for brand fit on brand image for those product extensions which are not in same brand category i.e. Johnson’s sportswear and Johnson’s isotonic drinks. Conclusion: It is concluded from study results that launching new product in same parent brand category have high chance of success while in different category is risk.Brand Extension, Brand Fit, Johnson, Product extensions, marketing.

Numerical Simulation of a High Mach Number Jet Flow

The recent efforts to develop accurate numerical schemes for transition and turbulent flows are motivated, among other factors, by the need for accurate prediction of flow noise. The success of developing high speed civil transport plane (HSCT) is contingent upon our understanding and suppression of the jet exhaust noise. The radiated sound can be directly obtained by solving the full (time-dependent) compressible Navier-Stokes equations. However, this requires computational storage that is beyond currently available machines. This difficulty can be overcome by limiting the solution domain to the near field where the jet is nonlinear and then use acoustic analogy (e.g., Lighthill) to relate the far-field noise to the near-field sources. The later requires obtaining the time-dependent flow field. The other difficulty in aeroacoustics computations is that at high Reynolds numbers the turbulent flow has a large range of scales. Direct numerical simulations (DNS) cannot obtain all the scales of motion at high Reynolds number of technological interest. However, it is believed that the large scale structure is more efficient than the small-scale structure in radiating noise. Thus, one can model the small scales and calculate the acoustically active scales. The large scale structure in the noise-producing initial region of the jet can be viewed as a wavelike nature, the net radiated sound is the net cancellation after integration over space. As such, aeroacoustics computations are highly sensitive to errors in computing the sound sources. It is therefore essential to use a high-order numerical scheme to predict the flow field. The present paper presents the first step in a ongoing effort to predict jet noise. The emphasis here is in accurate prediction of the unsteady flow field. We solve the full time-dependent Navier-Stokes equations by a high order finite difference method. Time accurate spatial simulations of both plane and axisymmetric jet are presented. Jet Mach numbers of 1.5 and 2.1 are considered. Reynolds number in the simulations was about a million. Our numerical model is based on the 2-4 scheme by Gottlieb & Turkel. Bayliss et al. applied the 2-4 scheme in boundary layer computations. This scheme was also used by Ragab and Sheen to study the nonlinear development of supersonic instability waves in a mixing layer. In this study, we present two dimensional direct simulation results for both plane and axisymmetric jets. These results are compared with linear theory predictions. These computations were made for near nozzle exit region and velocity in spanwise/azimuthal direction was assumed to be zero

Anaesthesia at remote location: use of modified Bain circuit (Mapleson D) at Kunri Christian Hospital (KCH)

OBJECTIVE: To develop a safe general anaesthesia technique for remote areas with lack of facilities. METHODS: Four types of anaesthesia techniques using TIVA and modified Bain circuit were planned. Monitoring facility was limited to manual sphygmomanometer, palpation of radial pulse and monitoring of colour of skin and blood. Depth of anaesthesia was assessed using EVANs, RPST scoring system. Patients were asked in recovery room for awareness. RESULTS: Surgeries done were cesarean sections, laparotomies, gynaecological, urological, hernia and burn contractures. Six patients had RPST score of 5 or more and three patients in recovery room complained of awareness. Cost per Anaesthesia was Rs225. CONCLUSION: TIVA with modified Bain circuit provided effective anaesthesia in remote area at low cost

An empirical investigation on factors influencing choice of foreign market by media firms

This study examines a number of factors suggested in the literature as important determinants of the foreign market selection. Key strategic factors are determined as four groups: host-country characteristics, firm-specific factors, competitive situation and content adaptation. In this study, multiple regression and path analysis are used. To test the model with modeling techniques, the necessary data from 29 media firms were used. It is based on a questionnaire, which has provided several insights into market selection elements. Our findings indicate that all components of the host country, exporting companies, competitive situation and the content adaptation could influence positively the selection of foreign market. The results also indicate that the adaptation of content was the most effective in choosing a foreign market. In addition, cross-cultural adaptation is an important component in selection of foreign markets. The results also suggest that the causal relationships between the independent variables are positive and significant, while the relationship between the content adaptation and the competitive situation has not been confirmed

Design of an Interface for Page Rank Calculation using Web Link Attributes Information

This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment