This report discusses the design of computational experiments to test heuristic methods and provides reporting guidelines for such experimentation. The goal is to promote thoughtful, well-planned, and extensive testing of heuristics, full disclosure of experimental conditions, and integrity in and reproducibility of the reported results. 1

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This paper describes the design, development, implementation, and assessment of a multimedia-based learning module focused on biomechanics. The module is comprised of three challenges and is based on a model of learning and instruction known as the How People Learn (HPL) framework. Classroom assessment of the first challenge was undertaken to test the hypothesis that the HPL approach increases adaptive expertise in movement biomechanics. Student achievement was quantified using pre-and post-test questionnaires designed to measure changes in three facets of adaptive expertise: factual and conceptual knowledge and transfer. The results showed that the HPL approach increased students' conceptual knowledge as well as their ability to transfer knowledge to new situations. These findings indicate that challenge-based instruction, when combined with an intellectually engaging curriculum and principled instructional design, can accelerate the trajectory of novice to expert development in bioengineering education.

Reviews previous research on the efficiency and performance of financial institutions and uses Siems and Barr’s (1998) data envelopment analysis (DEA) model to evaluate the relative productive efficiency of US commercial banks 1984‐1998. Explains the methodology, discusses the input and output measures used and relates bank performance measures to efficiency. Describes the CAMELS rating system used by bank examiners and regulators; and finds that banks with high efficiency scores also have strong CAMELS ratings. Summarizes the other relationship identified and recommends the use of DEA to help analysts and policy makers understand organizations in greater depth, regulators and examiners to develop monitoring tools and banks to benchmark their processes.

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This paper investigates adaptive digital notch filters for the elimination of powerline noise from biomedical signals. Since the distribution of the frequency variation of the powerline noise may or may not be centered at 60 Hz, three different adaptive digital notch filters are considered. For the first case, an adaptive FIR second-order digital notch filter is designed to track the center frequency variation. For the second case, the zeroes of an adaptive IIR second-order digital notch filter are fixed on the unit circle and the poles are adapted to find an optimum bandwidth to eliminate the noise to a pre-defined attenuation level. In the third case, both the poles and zeroes of the adaptive IIR second-order filter are adapted to track the center frequency variation within an optimum bandwidth. The adaptive process is considerably simplified by designing the notch filters by pole-zero placement on the unit circle using some suggested rules. A constrained least mean-squared (CLMS) algorithm is used for the adaptive process. To evaluate their performance, the three adaptive notch filters are applied to a powerline noise sample and to a noisy EEG as an illustration of a biomedical signal.

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