Obesity does not reduce maximum acceptable weights of lift

The maximum acceptable weights of lift (MAWL) of obese and non-obese participants were empirically investigated. Three obesity levels were considered: non-obese (18.5 kg/m(2)< or= body mass index (BMI)or= 40 kg/m(2)). Ten male and 10 female participants were recruited for each obesity level. The participants determined their MAWL for 18 different lifting task conditions (six lifting frequencies x three lifting heights). An analysis of variance (ANOVA) was conducted to determine the effects of obesity level, gender, lifting height, lifting frequency and their interactions on MAWL. Overall, the ANOVA results indicated that obesity does not reduce MAWL, and thus, suggested that the existing MAWL data can be used to accommodate both general and obese workers. However, further studies based on the biomechanical and physiological approaches are required to provide more complete understanding of obesity effects on lifting tolerance limits.     

Multichannel direct sequence spectrum signaling using code phase shift keying

In this paper, we have designed and realized multichannel direct sequence spread spectrum (DSSS) system using code phase shift keying (CPSK). In the transmitter, taking each bit from each channel, data word is made as a symbol for selecting PN sequence, which is modulated with frequency of 100 MHz as DSSS signals. At the receiver, the correlator, integrator and decoder are used for separation of the signal of respective channel after demodulation. Oscilloscope traces show that the transmitted signals are matched with the simulated signals at the receiver. The bit error rate (BER) variation with jamming signal is estimated by our proposed simulation model, matching well with experimental values of BER measured by BER meter.     

A computational method of forecasting based on high-order fuzzy time series

This paper presents a computational method of forecasting based on high-order fuzzy time series. The developed computational method provides a better approach to overcome the drawback of existing high-order fuzzy time series models. Its simplicity lies with the use of differences in consecutive values of various orders as forecasting parameter and a w-step fuzzy predictor in place of complicated computations of fuzzy logical relations. The objective of the present study is to examine the suitability of various high-order fuzzy time series models in forecasting. The general suitability of the developed method has been tested by implementing it in the forecasting of student enrollments of the University of Alabama and in the forecasting of crop (Lahi) production, a case of high uncertainty in time series data. The results obtained have been compared in terms of average error of forecast to show superiority of the proposed model.     

Identifying and overcoming the challenges of implementing a project management office

With the ongoing challenge of successfully managing information technology (IT) projects, organizations are recognizing the need for greater project management discipline. For many organizations, this has meant ratcheting up project management skills, processes, and governance structures by implementing a project management office (PMO). While anecdotal evidence suggests that implementing a PMO can be quite difficult, few studies discuss the specific challenges involved, and how organizations can overcome them. To address this gap in existing knowledge, we conducted a Delphi study to (1) identify the challenges of implementing a PMO for managing IT projects, (2) rank these challenges in order of importance, (3) discover ways in which some organizations have overcome the top-ranked challenges, and (4) understand the role of PMO structure, metrics, and tools in the implementation of a PMO.We identified 34 unique challenges to implementing a PMO and refined this list to 13 challenges that our Delphi panelists considered most important. The top-three challenges were (1) rigid corporate culture and failure to manage organizational resistance to change, (2) lack of experienced project managers (PMs) and PMO leadership, and (3) lack of appropriate change management strategy. Through follow-up interviews with selected panelists, we identified a series of actions that can be taken to overcome these challenges including having a strong PMO champion, starting small and demonstrating the value of the PMO, obtaining support from opinion leaders, hiring an experienced program manager who understands the organization, bringing the most talented PMs into the PMO implementation team, adopting a flexible change management strategy, and standardizing processes prior to PMO implementation. The interviews were also used to better understand the role of PMO structure, metrics, and tools. In terms of PMO structure, we found that ‘light’ PMOs were more likely to be implemented successfully. Most organizations eschew formal metrics, instead relying on subjective indicators of PMO success. Lastly, it appears that PMO tools are difficult to implement unless a project management culture has been established.     

Stochastic coalitional better-response dynamics and stable equilibrium

We consider coalition formation among players in an n-player finite strategic game over infinite horizon. At each time a randomly formed coalition makes a joint deviation from a current action profile such that at new action profile all the players from the coalition are strictly benefited. Such deviations define a coalitional better-response (CBR) dynamics that is in general stochastic. The CBR dynamics either converges to a K-stable equilibrium or becomes stuck in a closed cycle. We also assume that at each time a selected coalition makes mistake in deviation with small probability that add mutations (perturbations) into CBR dynamics. We prove that all K-stable equilibria and all action profiles from closed cycles, that have minimum stochastic potential, are stochastically stable. Similar statement holds for strict K-stable equilibrium. We apply the CBR dynamics to study the dynamic formation of the networks in the presence of mutations. Under the CBR dynamics all strongly stable networks and closed cycles of networks are stochastically stable.     

A study on measuring surface deformation of the L’Aquila region using the StaMPS technique

This research compares two time-series interferometric synthetic aperture radar (InSAR) methods, namely persistent scatterer SAR interferometry (PS-InSAR) and small baseline subset (SBAS) to retrieve the deformation signal from pixels with different scattering characteristics. These approaches are used to estimate the surface deformation in the L’Aquila region in Central Italy where an earthquake of magnitude Mw 6.3 occurred on 6 April 2009. Fourteen Environmental Satellite (ENVISAT) C-band Advanced Synthetic Aperture Radar (ASAR) images, covering the pre-seismic, co-seismic, and post-seismic period, are used for the study. Both the approaches effectively extract measurement pixels and show a similar deformation pattern in which the north-west and south-east regions with respect to the earthquake epicentre show movement in opposite directions. The analysis has revealed that the PS-InSAR method extracted more number of measurement points (21,103 pixels) as compared to the SBAS method (4886 pixels). A comparison of velocity estimates shows that out of 833 common pixels in both the methods, about 62% (517 pixels) have the mean velocity difference below 3 mm year^?1 and nearly 66% pixels have difference below 5 mm year^?1. It is concluded that StaMPS-based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean line of sight (LOS) velocity as compared to SBAS method.     

Layered axial force coupled membrane based metal contact single-pole quad-throw RF MEMS switch: design,RF performance and mechanical modeling

Microsystem Technologies - RF MEMS is a perfect candidate to replace the conventional switches used for microwave frequency. Most of the RF MEMS switches developed generally concentrate on...     

SVM based robust watermarking for enhanced medical image security

Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.

     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...     

Automatic identification of cattle using muzzle point pattern: a hybrid feature extraction and classification paradigm

Multimedia Tools and Applications - Animal biometrics is an emerging research field that develops quantified methodologies for representing and detecting the visual appearances of animal based on...