HuddleUp Club
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HuddleUp promotes internal networking by generating warm contacts. The first step and the hardest is to approach someone you don't know. Breakdown silos and build a social culture. Connect - Catch Up - Collaborate
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Knowledge Management In The Real World
The document discusses knowledge management at HP Services. It defines knowledge management as transforming information into value through reuse, innovation, and collaboration. It outlines people, processes, and technologies used at HP to foster knowledge sharing, such as communities of practice, social networking, and knowledge repositories. The goals are to increase win rates, drive down costs, and accelerate delivery through leveraging collective expertise.
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Content strategy can be used as a major driving force for that realignment (i.e. digital transformation), introducing new ways of approaching, thinking about and working with digital publishing channels so that they’re contributing the level of value that they could and should be. I call it being “content-ready”.
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important role in the proper and accurate diagnosis of the defects of the heart. As usually with the
stethoscope, it requires highly and experienced physicians to read the phonocardiogram. A diagnostic
system based on Artificial Neural Networks (ANN) is implemented as a detector and classifier of heart
diseases. The output of the system is the classification of the sound as either normal or abnormal, if it is
abnormal what type of abnormality is present. In this paper, Based on the extracted time domain and
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The mammalian brain exists in a number of attractors. In order to characterize these attractors we have collected the time series data from the EEG recording of rat models. The time series was obtained by recording of the frontoparietal, occipital and temporal regions of the rat brain. Significant changes have
been observed in the dimensionalities of these brain attractors between the normal state, focal ischemic
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correlation dimensions and embedding dimensions. The inverse of the lyapunov exponent gave us the long
term coherence of the rat brain and was found to differ for the three states. The autocorrelation function
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A Phonocardiogram or PCG is a plot of high fidelity recording of the sounds and murmurs made by the
heart with the help of the machine called phonocardiograph. It has developed continuously to perform an
important role in the proper and accurate diagnosis of the defects of the heart. As usually with the
stethoscope, it requires highly and experienced physicians to read the phonocardiogram. A diagnostic
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The mammalian brain exists in a number of attractors. In order to characterize these attractors we have collected the time series data from the EEG recording of rat models. The time series was obtained by recording of the frontoparietal, occipital and temporal regions of the rat brain. Significant changes have
been observed in the dimensionalities of these brain attractors between the normal state, focal ischemic
state and the drug induced state. Thus, these three states were characterized by unique lyapunov exponents,
correlation dimensions and embedding dimensions. The inverse of the lyapunov exponent gave us the long
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HRV is stochastic and chaotic (stochaotic) signal. It has utmost importance in heart diseases diagnosis, and it needs a sensitive tool to analyze its variability. In early works, Rosenstein and Wolf had used the Lyapunov exponent (LE) as a quantitative measure for HRV detection sensitivity, but the Rosenstein and Wolf methods diverge in determining the main features of HRV sensitivity, while Mazhar-Eslam introduced a modification algorithm to overcome the Rosenstein and Wolf drawbacks.
The present work introduces a novel reliable method to analyze the linear and nonlinear behaviour of heart complex wave variability, and to assess the use of the HRV as a versatile tool for heart disease diagnosis. This paper introduces a declaration for the concept of the LE parameters to be used for HRV diagnosis and proposes a modified algorithm for a more sensitive parameters computation
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In this paper designing of a battery operated portable single channel electroencephalography (EEG) signal acquisition system is presented. The advancement in the field of hardware and signal processing tools made possible the utilization of brain waves for the communication between humans and computers. The work presented in this paper can be said as a part of bigger task, whose purpose is to classify EEG signals belonging to a varied set of mental activities in a real time Brain Computer Interface (BCI). Keeping in mind the end goal is to research the possibility of utilizing diverse mental tasks as a wide correspondence channel in the middle of individuals and PCs. This work deals with EEG based BCI, intent on the designing of portable EEG signal acquisition system. The EEG signal acquisition system with a cut off frequency band of 1-100 Hz is designed by the use of integrated circuits such as low power instrumentation amplifier INA128P, high gain operational amplifiers LM358P. Initially the amplified EEG signals are digitized and transmitted to a PC by a data acquisition module NI DAQ (SCXI-1302). These transmitted signals are then viewed and stored in the LAB VIEW environment. From a varied set of experimental observation it can be said that the system can be implemented in the acquisition of EEG signals and can stores the data to a PC efficiently and the system would be of advantage to the use of EEG signal acquisition or even BCI application by adapting signal processing tools.
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Fall incidents remain a major issue for workers in the construction and industrial sites. From biomechanical perspectives the majority of falls occurredwhen the body’scenter of mass (CoM) leaves the base of support (BoS). Several measuresquantify stability based on the trajectories of the CoM, such as excursion, sway length, and mean displacement velocity. Nonetheless, none of these measures evaluate stability based on the optimal location of stability, which is the center of base of support (CBoS). Therefore, the main goal of this paper is to introduce new measures that evaluate stability by determining the deviation of the CoM from the CBoSin the Anterior-Posterior and Medio-Lateral directions. A lifting experiment was conducted to comparethe new measures with the existing stability measures. Participants lifted a box with different weights and placed it on a shelf with different heights. The trajectories of the CoM were captured through motion capturing system. The statistical analysis showed that the weight, height, and the interaction had statically significant effect on body stability. While comparing the intraclass correlation (ICC) values for each stability measure, (i.e. a measure of reliability), the proposed measures proved to be more reliable (i.e. highest ICC) than the existing stabilitymeasures.The high ICC values of the proposed stability measures, as compared to the existing stability measures, are a clear indication of their superior reliability. Moreover, the data indicated that increasing the load and the height resulted in an increaseofinstability.
Modeling cell movement on a substrate
Live cells respond to the changes of their physiological environment as well as to the mechanical stimuli occurring in and out of the cell body. It is known that cell directional motion is influenced by the substrate stiffness. A finite element modelling based on the tensegrity approach is used here to describe the biomechanical behavior of cells. The effects of substrate stiffness and prestress on strain energy of a cell are investigated by defining several substrate stiffness values and prestress values. Numerical simulations reveal that the internal elastic strain energy of the cell decreases as the substrate stiffness increases. As prestress of cell increases, the strain energy increases as well. The change of prestress value does not change behavior pattern of the strain energy: strain energy of a cell will decrease when substrate stiffness increases. These findings indicate that both cell prestress and substrate stiffness influence the cell directional movement.
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HuddleUp Club
- 1. HuddleUp Connect – Catch Up - Collaborate
- 2. “If only HP knew what HP knows, we would be three times more productive” – Lou Platt, Former CEO, HP 01
- 3. “Networking internally- raise your profile, source new project opportunities, strengthen relationships with stakeholders and gather information on requirements” – Lou Platt, Former CEO, HP 02
- 4. “We’ve found that networking … is simultaneously one of the most self-evident and one of the most dreaded developmental challenges that aspiring leaders must address” – Havard Business Review 2007 03
- 5. 04 HuddleUp creates opportunities to Discover warm contacts Build offline relationships Learn and engage