Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.     

A Balanced Approach to IT Transformation

The continuous improvement strategies necessary in today's climate of random change mandate that IT organizations transform the way they relate to other business units, deploy new technology, and organize and develop their people. Crafting an individualized transformation program that balances efforts in each of these areas will help IT managers add value to the bottom line while achieving real gains in customer service and productivity.     

Simulation based alternatives for overall process improvement at the cardiac catheterization lab

Cardiac catheterization is one of the critical procedures in patient care. It is pertinent for all process related issues in this department to be handled with due priority. This research is a cross-functional effort with a leading hospital that was in its planning stage to implement an overall process improvement at its cardiac catheterization lab department. It has been determined that significant process delays exist in this department. One of the identified key factors to process improvement was to reduce patient turnaround time. Process mapping was used to study the system and identify potential sources of delays in the system. A set of qualitative recommendations were put forward. These recommendations, include the reduction of wait time of outpatients and inpatients and the reduction of non-value-added times such as transfer time of patients, were evaluated using a discrete event simulation approach. The simulation study shows that the daily operating hours at the catheterization lab could be reduced, aiding to reallocate staff for discharging other duties, as the hospital may require.     

Keeping up-to-date with information technology: Testing a model of technological knowledge renewal effectiveness for IT professionals

In a rapidly changing IT environment, IT professionals need to keep abreast of technological knowledge. We examined how well this is achieved by developing a motivational model of “technological knowledge renewal effectiveness.” We hypothesized that (1) renewal effectiveness was influenced by the IT professional's career orientation, perceived IT dynamism, tolerance of ambiguity, delegation; and (2) that this positively affected both intrinsic and extrinsic job satisfaction. Survey data from 126 IT professionals was used to test the hypotheses. The results generally supported the research model. We discussed the implications of these results in both research and practice.     

Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition

Epilepsy is one of the most common neurological disorders characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is an invaluable measurement for the purpose of assessing brain activities, containing information relating to the different physiological states of the brain. It is a very effective tool for understanding the complex dynamical behavior of the brain. This paper presents the application of empirical mode decomposition (EMD) for analysis of EEG signals. The EMD decomposes a EEG signal into a finite set of bandlimited signals termed intrinsic mode functions (IMFs). The Hilbert transformation of IMFs provides analytic signal representation of IMFs. The area measured from the trace of the analytic IMFs, which have circular form in the complex plane, has been used as a feature in order to discriminate normal EEG signals from the epileptic seizure EEG signals. It has been shown that the area measure of the IMFs has given good discrimination performance. Simulation results illustrate the effectiveness of the proposed method.     

A semantic framework for automatic generation of computational workflows using distributed data and component catalogues

Computational workflows are a powerful paradigm to represent and manage complex applications, particularly in large-scale distributed scientific data analysis. Workflows represent application components that result in individual computations as well as their interdependences in terms of dataflow. Workflow systems use these representations to manage various aspects of workflow creation and execution for users, such as the automatic assignment of execution resources. This article describes an approach to automating a new aspect of the process: the selection of application components and data sources. We present a novel approach that enables users to specify varying degrees of detail and amount of constraints in a workflow request, including the specification of constraints on input, intermediate or output data in the workflow, abstract workflow component classes rather than specific component implementations, and generic reusable workflow templates that express a pre-defined combination of components. The algorithm elaborates the user request into a set of fully ground workflows with specific choices of data sources and codes to be used so that they can be submitted for mapping and execution. The algorithm searches through the space of possible candidate workflows by creating increasingly more specialized versions of the original template and eliminating candidates that violate constraints cumulated in the candidate workflow as components and data sources are selected. A novel feature of our approach is that it assumes a distributed architecture where data and component catalogues are separate from the workflow system. The algorithm explicitly poses queries to external catalogues, and therefore any reasoning regarding data or component properties is not assumed to occur within the workflow system. We describe our implementation of this approach in the Wings workflow system. This implementation uses the W3C Web Ontology Language and associated reasoners to implement the workflow system as well as the data and component catalogues. This research demonstrates the use of artificial intelligence techniques to support the kinds of automation envisioned by the scientific community for large-scale distributed scientific data analysis.     

Forecasting the trend of international scientific collaboration

The study demonstrates an integrated method of forecasting the trend of a country’s publications. In this context the paper examines international collaboration in a country’s overall publication and forecasts its future trend. The integrated method is based on regression and scaling relationship. India is taken as a case study for this examination. The study shows some interesting features of India’s publication pattern based on time-series data. One observes exponential nature of her publication growth from 2002 onwards. International collaboration also exhibits exponential growth roughly from the same period. Also one observes the faster growth of international collaborative papers than the overall growth of research papers. The study predicts values of number of internationally collaborative papers for the years 2015 and 2020. The robustness of the method is also demonstrated.     

On Plastic Deformation Behavior of Cryorolled AA8090 Alloy

AA8090 alloy was rolled up to 50 and 75 % reductions at both liquid nitrogen (LNR) and room temperatures (RTR). Both hardness and tensile behavior were evaluated on rolled samples. Optical microscope, TEM and EBSD were used for detailed microstructural examination of rolled samples. Williamson-Hall peak broadening analysis on X-ray diffraction data was made to evaluate crystallite size, lattice strain and dislocation density. An enhanced tensile strength was evidenced in LNR samples when compared to RTR samples without sacrificing ductility, which was ascribed to the higher density of dislocations in LNR samples than RTR samples. A large number of dislocation tangled regions along with ultrafine grain structure were evidenced through TEM and EBSD. Significant fraction of special boundaries in combination with increased fraction of texture components like S, Brass, Cu and Goss would be another reason for enhanced properties in LNR conditions than that of RTR. These components were observed to be strengthened with increased rolling reduction. Work hardening behavior clearly evidenced the variation in amount of work hardening and recovery phenomenon. It showed large variation in recovery in the case of 50 % reduction than that of 75 % reduction, which was attributed to significantly higher density of dislocations in 75 % rolled samples in RTR and LNR.     

A Real-Time Application of Modified Inductor Coupled KY Converter Topology in Speed Control of E-Bikes

Abstract

Congested road network and traffic jam lead to vehicle idling and fuel wastage. An E-bike which is a solution to this is often available with Thumb Throttle Mechanism and single speed operation. A motor controller with multiple output voltage levels and Click Throttle Mechanism is presented in this paper which provides variable speed operation, better power utilization and is highly economical. Proposed modified KY converter utilizes the turns ratio of an On-Line Tap Changer (OLTC) to generate multiple output voltages for variable speed commutation. This possess a stable continuous conduction mode throughout its operation and reduced switching transients when compared to the existing topologies. Mutually independent control variables namely turns ratio and duty ratio, are used here for voltage conversion, which facilitates the flexible transition between multiple output voltage levels. A 15?W prototype of the proposed modified inductor coupled KY converter is realized using Arduino Uno Board.