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Looks at Harrah’s casino business and how it is run, with the aid of analytics: accessing; aggregating; and analysing large amounts of data from many sources. States Harrah’s converts data into knowledge to enhance its ability to make effective business decisions. Lists out five “rules of the road” with descriptions of them in full. Concludes that advances in analytics are breathing new life into companies’ efforts in creating new businesses and line extensions.

The presence of random noise as well as narrow band coherent noise makes the structural health monitoring a really challenging issue and to achieve efficient structural health assessment methodology, very good extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities.

Filtration of time-frequency information of multimode Lamb waves through the noisy signal is investigated in the present analysis using matched filtering technique and wavelet denoising methods. Using Shannon’s entropy criterion, the optimal wavelet function is selected and verification is made via the analysis of root mean square error of filtered signal.

The authors propose wavelet matched filter method, a combination of the wavelet transform and matched filtering method, which can significantly improve the accuracy of the filtered signal and identify relatively small damage, especially in enormously noisy data. Correlation coefficient and root mean square error are additionally computed for performance evaluation of the filters.

The present study provides detailed information about various noise filtering methods and a first attempt to apply the combination of the different techniques in signal processing for the structural health monitoring application. A comparative study is performed using the statistical tool to know whether filtered signals obtained through three different methods are acceptable and practicable for guided wave application or not.

The real challenge in the solution of contact problems is the lack of an optimal adaptive scheme. As the contact zone is a priori unknown, successive refinement and iterative method are necessary to obtain a high-accuracy solution. The purpose of this paper is to provide an optimal adaptive scheme based on second-generation finite element wavelets for the solution of non-linear variational inequality of the contact problem.

To generate an elementary multi-resolution mesh, the authors used hierarchical bases (HB) composed of Lagrange finite element interpolation functions. These HB functions are customized using second-generation wavelet techniques for a fast convergence rate. At each step of the algorithm, the active set method along with mesh adaptation is used for solving the constrained minimization problem of contact case. Wavelet coefficients-based error indicators are used, and computation is focused on mesh zones with a high error indication. The authors take advantage of the wavelet transform to develop a parameter-free adaptive scheme to generate an appropriate and optimal mesh.

Adaptive wavelet Galerkin scheme (AWGS), a newly developed method for multi-scale mesh adaptivity in this work, is a combination of the second-generation wavelet transform and finite element method and significantly improves the accuracy of the results without approximating an additional problem of error estimation equations. A comparative study is performed taking a solution on a highly refined mesh and results are generated using AWGS.

The proposed adaptive technique can be utilized in the simulation of mechanical and biomechanical structures where multiple bodies come into contact with each other. The algorithm of the method is easy to implement and found to be successful in producing a sufficiently accurate solution with relatively less number of mesh nodes.

Although many error estimation techniques have been developed over the past several years to solve contact problems adaptively, because of boundary non-linearity development, a reliable error estimator needs further investigation. The present study attempts to resolve this problem without having to recompute the entire solution on a new mesh.

The real challenges in online crack detection testing based on guided waves are random noise as well as narrow-band coherent noise; and to achieve efficient structural health assessment methodology, magnificent extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities.

Filtration of time-frequency information of guided elastic waves through the noisy signal is investigated in the present analysis using matched filtering technique which “sniffs” the signal buried in noise and most favorable mother wavelet based denoising methods. The optimal wavelet function is selected using Shannon’s entropy criterion and verified by the analysis of root mean square error of the filtered signal.

Wavelet matched filter method, a newly developed filtering technique in this work and which is a combination of the wavelet transform and matched filtering method, significantly improves the accuracy of the filtered signal and identifies relatively small damage, especially in enormously noisy data. A comparative study is also performed using the statistical tool to know acceptability and practicability of filtered signals for guided wave application.

The proposed filtering techniques can be utilized in online monitoring of civil and mechanical structures. The algorithm of the method is easy to implement and found to be successful in accurately detecting damage.

Although many techniques have been developed over the past several years to suppress random noise in Lamb wave signal but filtration of interferences of wave modes and boundary reflection is not in a much matured stage and thus needs further investigation. The present study contains detailed information about various noise filtering methods, newly developed filtration technique and their efficacy in handling the above mentioned issues.

The purpose of this research paper is to identify the sources of job stress and their impact on health of employees.

A total of 650 employees of power sector in Punjab (India) responded to the survey. Exploratory factor analysis and ANOVA were performed. Further, post hoc was conducted to find out which variable differs significantly.

The findings indicates that five parameters, namely workload, working environment, concentration, positivity and future perspective are the factors that are responsible to create stress in employees. There is great impact on health as “frequency of visit to a doctor” and “numbers of diseases” they have are high and “employee's time spared for exercise” is less.

Since the survey was conducted only in power sector, it is difficult to generalize the results. However, the findings from this study will provide the factors that cause job stress and how they impact on health of employees.

The result indicates the impact of job stress on health of employees in power sector. Current research suggests that job stressors should be treated timely to minimize the impact of job stress.

While previous research has focused on the effect of stress on health, the present study provides evidence of the relationship between the sources of job stress and health, particularly in power sector in Punjab. This study would be contributing to the existing literature in Indian context.

The purpose of this paper is to determine the relative efficiencies of public sector hospitals in Uttarakhand, India.

The study use data of public hospitals collected from Directorate of Medical Health and Family Welfare, Government of Uttarakhand, Dehradun, India for the year 2011. The cross-sectional data analyses are carried out by applying data envelopment analysis (DEA) based slack based model.

The analysis found that out of total 36 hospitals only ten hospitals are relatively overall technical efficient. The average overall technical efficiency 54.10 per cent indicates that an average hospital has the scope of producing the outputs with the inputs 45.90 per cent lesser than their existing levels. The slack analysis results show that on average 12.57 per cent of beds, 13.16 per cent of doctors, 14.04 per cent of paramedical staff can be reduced and 17.53 per cent of out-door patients, 66.55 per cent of in-door patients, 208.23 per cent of major surgeries, 110.73 per cent of minor surgeries can be expanded if all the inefficient hospitals operate at the level of efficient hospitals.

The present study is undertaken to measure the relative efficiencies of public sector hospitals in Uttarakhand. There is dearth of studies being done on Indian healthcare sector and this study will help to utilize healthcare resources efficiently for formulating policy implications for public hospitals in Uttarakhand. For the robustness of DEA results, Jackknifing analysis is also conducted.

Introduction: Amidst Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), turbulence is a vital component of an entrepreneurial landscape. VUCA world has set a new dynamic in the business environment and organisation’s settings. In such an environment, it is pertinent for entrepreneurs to exhibit creativity, innovative service behaviour, and performance.

Purpose: The study investigates whether creativity, innovative service behaviour, and performance of entrepreneurs are fostered through employee engagement practices in a highly volatile, uncertain, complex, and ambiguous environment.

Methodology: The methodology involves a systematic review and meta-synthesis. By identifying the major topics, a systematic literature review helped critically analyse and synthesise the literature.

Findings: According to the study, corporate entrepreneurial factors like (management reinforcement, reward/reinforcement, job autonomy/discretion, time attainability, and organisational boundaries) entrepreneurial potential, entrepreneurial orientation, human capital, self-efficacy beliefs lead to employee engagement, which, in turn, fosters creativity, innovative service behaviour, and performance among entrepreneurs in the VUCA world.