Darrin M. Hanna

Best Practices Involving Teamwork in the Classroom: Results From a Survey of 6435 Engineering Student Respondents

A teamwork survey was conducted at Oakland University, Rochester, MI, in 533 engineering and computer science courses over a two-year period. Of the 6435 student respondents, 4349 (68%) reported working in teams. Relative to the students who only worked individually, the students who worked in teams were significantly more likely to agree that the course had achieved its stated learning objectives (p < 0.001). Regression analysis showed that roughly one-quarter of the variance in belief about whether the objectives were met could be explained by four factors: 1) student satisfaction with the team experience; 2) the presence of instructor guidance related to teamwork; 3) the presence of slackers on teams; and 4) team size. Pearson product-moment correlations revealed statistically significant associations between agreement that the course objectives had been fulfilled and the use of student teams and between satisfaction with teams and the occurrences of instructor guidance on teamwork skills. These and other results suggest that assigning work to student teams can lead to learning benefits and student satisfaction, provided that the instructor pays attention to how the teams and the assignments are set up.

Using a system-on-a-chip implantable device to filter circulating infected cells in blood or lymph

This paper describes a system on a chip (SoC) that makes use of nanoscale cellular adhesion mechanisms in an integrated electronic microsystem to filter infected cells from blood or lymph. An example of a human immunodeficiency virus-specific SoC is explored in depth. Such systems work in vivo, and blood and lymph are filtered on a continuous basis. With the intelligence on the chip, captured cells can be identified and lyzed, expelled, or otherwise acted upon. These types of systems transfer the burden of research from traditional chemotherapy to bioengineering and system design.

Ultrasonic Parameters as a Function of Absolute Hydrostatic Pressure. I. A Review of the Data for Organic Liquids

This review provides an overview of experimental results involving ultrasonic parameters as a function of absolute hydrostatic pressure in organic liquids. Major topics of discussion include the pioneering work of Litovitz and Carnevale involving deduction of the chemical and structural properties of liquids from acoustical properties as a function of pressure; modern general ultrasonic studies of a broad range of organic liquids; work accomplished by Russians and others from the former Soviet block countries, particularly the work headed by Otpuschennikov at the Kursk Pedagogical Institute; the studies involving refrigerants published by Takagi at the Kyoto Institute of Technology; tribological and petroleum industry studies related to oils; Brillouin scattering experiments; and thermodynamic methods of B/A measurement. The importance of ultrasonic parameters as a function of pressure to the understanding of a variety of processes is highlighted. A table of 325 liquids and liquid mixtures with a total of...

Accelerating the performance of particle swarm optimization for embedded applications

The ever increasing popularity of particle swarm optimization (PSO) algorithm is recently attracting attention to the embedded computing world. Although PSO is in general considered to be computationally efficient algorithm, its direct software implementation on complex problems, targeted on low capacity embedded processors could however suffer from poor execution performance. This paper first evaluates the performance of the standard PSO algorithm on a typical embedded platform (using a 16-bit microcontroller). Then, a modular, flexible and reusable architecture for a hardware PSO engine, for accelerating the algorithms performance, will be presented. Finally, implementation test results of the proposed architecture targeted on Field Programmable Gate Array (FPGA) technology will be presented and its performance compared against software executions on benchmark test functions.

Enhancing performance of PSO with automatic parameter tuning technique

Particle Swarm Optimization (PSO) has gained growing popularity in the recent years and is finding a wide range of important applications. Like other population based, stochastic meta-heuristics, PSO has a few algorithm parameters that need to be carefully set to achieve best execution results. This paper develops an automatic parameter tuning technique for enhancing its performance. The effectiveness of the proposed method is demonstrated on mathematical benchmark functions as well as on a real world application problem.

Ultrasonic Parameters as a Function of Absolute Hydrostatic Pressure. II. Mathematical Models of the Speed of Sound in Organic Liquids

Polynomial expressions for the speed of sound as a function of pressure for 68 different organic liquids are presented in tabular form. (The liquids form a subset of those discussed in the companion paper: Ultrasonic parameters as a function of absolute hydrostatic pressure. I. A review of the data for organic liquids.) The polynomial expressions are based upon the experimental results reported by many different researchers. For some common liquids, such as benzene, hexane, ethanol, and carbon tetrachloride, the results of as many as five different researchers are reported. These results sometimes vary widely—far more than would be expected from calculated experimental uncertainties. An analysis is presented of how well pressure-dependent polynomials fit the experimental data when the number of coefficients is increased. The error in the polynomial fit is also explored when both pressure and temperature dependencies are present. Finally, differences between ultrasonic and Brillouin scattering experimental...

Particle Swarm Optimization for classification of breast cancer data using single and multisurface methods of data separation

This paper exploits the simplicity, efficiency and flexibility of the particle swarm optimization (PSO) method to propose a single and multisurface based data separation methods for classification of Breast Cancer Data. Like most artificial intelligence based techniques the first step of the proposed approaches involve the training of the PSO-based classifiers according to pre-defined data separation methods, using part of the dataset for training. The performances of the classifiers are then tested on the remaining dataset to measure the classification accuracy. The training and testing datasets are derived from the Breast Cancer database obtained from the UCI machine learning repository. Both separation methods produce good classification performance; however, the method based on multiple separating surfaces achieves the best result of 100% classification accuracy on both the training and testing datasets.

Multi-swarm parallel PSO: Hardware implementation

The ever increasing popularity of the particle swarm optimization (PSO) algorithm is recently attracting attention to the embedded computing world. Although PSO is considered efficient compared to other contemporary population based optimization techniques, for many continuous multimodal and multidimensional problems, it still suffers from performance loss when it is targeted onto embedded application platforms. Examples of such target applications include small mobile robots and distributed sensor nodes in sensor network applications. In a previous work we presented a novel, modular, efficient and portable hardware architecture to accelerate the performance of the PSO for embedded applications. This paper extends the work by presenting a parallelization technique for further speedup of the PSO algorithm by dividing the swarm into a set of subswarms that are executing in parallel. The underlying communication topology and messaging protocols are described. Finally, the performance of the proposed system is evaluated on mathematical and real-world benchmark functions.

A VHDL Forth Core for FPGAs

Abstract The Forth programming language is typically implemented to run on some particular microprocessor. Several Forth engines have been designed that execute Forth instructions directly, typically in a single clock cycle. With the advent of high density FPGAs it has become feasible to implement a high-performance Forth core in an FPGA. This paper describes the design of a Forth core using VHDL that has been implemented on a Xilinx Spartan II FPGA. Examples are presented of high-level Forth programs that are compiled to VHDL code that implements a ROM embedded in the FPGA. The use of a Forth core in an FPGA allows for rapid prototyping of digital systems. Experiments show that an identical Forth program for the Sieve of Eratosthenes executes nearly 30 times faster on the FPGA Forth core than on a 68HC12 microcontroller at the same clock speed. This same program executes over six times faster on the FPGA Forth core than an equivalent compiled C program run on the same 68HC12. The Forth core is available as an EDIF file at www.tigs.com/fc16 , which can be included in a VHDL project and uses approximately 30% of a Spartan II FPGA.

Hardware PSO for sensor network applications

This paper addresses the problem of emission source localization in an environment monitored by a distributed wireless sensor network. Typical application scenarios of interest include emergency response and military surveillance. A nonlinear least squares method is employed to model the problem of estimation of the emission source location and the intensity at the source. A particle swam optimization (PSO) approach to solve this problem produces solution qualities that compete well with other best known traditional approaches. Moreover, the PSO solution achieves the best runtime performance compared to the other methods investigated. However, when it is targeted on to low capacity embedded processors PSO itself suffers from poor execution performance. To address this problem a direct, flexible and efficient hardware implementation of the PSO algorithm is developed, resulting in tremendous speedup over software solutions on embedded processors.