An Introduction to the MISD Technology

The growth of data volume, velocity, and variety will be the global IT challenges in the next decade. To overcome performance limits, the most effective innovations such as cognitive computing, GPU, FPGA acceleration, and heterogeneous computing have to be integrated with the traditional microprocessor technology. As the fundamental part of most computational challenges, the discrete mathematics should be supported both by the computer hardware and software. But for now, the optimization methods on graphs and big data sets are generally based on software technology, while hardware support is promising to give a better result. \ \ In this paper, the new computing technology with direct hardware support of discrete mathematic functions is presented. The new non-Von Neumann microprocessor named Structure Processing Unit (SPU) to perform operations over large data sets, data structures, and graphs was developed and verified in Bauman Moscow State Technical University. The basic principles of SPU implementation in the computer system with multiple instruction and single data stream (MISD) are presented. We then introduce the programming techniques for such a system with CPU and SPU included. The experimental results and performance tests for the universal MISD computer are shown

An approach to a pseudo real-time image processing engine for hyperspectral imaging

Hyperspectral imaging provides an alternative way of increasing the accuracy by adding another dimension: the wavelength. Recently, hyperspectral imaging is also finding its way into many more applications, ranging from medical imaging in endoscopy for cancer detection to quality control in the sorting of fruit and vegetables. But effective use of hyperspectral imaging requires an understanding of the nature and limitations of the data and of various strategies for processing and interpreting it. Also, the breakthrough of this technology is limited by its cost, speed and complicated image interpretation. We have therefore initiated work on designing real-time hyperspectral image processing to tackle these problems by using a combination of smart system design, and pseudo-real time image processing software. The main focus of this paper is the development of a camera-based hyperspectral imaging system for stationary remote sensing applications. The system consists of a high performance digital CCD camera, an intelligent processing unit, an imaging spectrograph, an optional focal plane scanner and a laptop computer equipped with a frame grabbing card. In addition, special software has been developed to synchronize between the frame grabber (video capture card), and the digital camera with different image processing techniques for both digital and hyperspectral data

Computer Supported Interprofessional Education for Improving Health Profession Students’ Attitudes Toward Teamwork and Team Performance

This presentation will present results from a study that investigated the effect computer supported interprofessional education (CSIE) had on healthcare profession students’ attitudes toward healthcare teamwork and to what extent computer supported group processing impacted student perceptions of team performance. A hybrid approach to interprofessional education, CSIE, was used to provide students with an educational experience that combined the benefits of traditional face-to-face communication with a computer-mediated platform. JeffersonCenterfor InterProfessional Education has successfully been providing IPE to healthcare students for over 5 years. A long term strategic goal was identified to “create innovative learning environments that support interprofessional education including state-of-the-art technologies”. In actualizing this goal, the curriculum was enhanced with an online discussion forum to assist in student group processing and reflection. A pretest-posttest design was used to answer: (a) Does computer supported interprofessional education affects the attitudes toward healthcare teamwork? And (b) To what extent are perceptions of team performance affected by a computer supported interprofessional education component on enhancing group processing and teamwork? Student attitudes and perceptions were measured before and after participating in CSIE. Results from the Team Performance Scale showed a significant increase in student’s perceptions pre to post CSIE signifying students perceived their team to be functioning better after participating in CSIE. Results of the Attitudes Toward Healthcare Teams survey did not show a statistical significance increase, however the data showed an upward trend in attitude scores. The findings support the importance of utilizing reflection for team processing and further endorses the need for integration of computer supported interprofessional education within healthcare curriculums. Curriculum planners can utilize these results to integrate effective interprofessional strategies that incorporate CSIE to positively impact student attitudes of teamwork. Learning Objectives: At the end of this session, participants will: 1. Discuss one way to enhance IPE communication using technology. 2. Identify one computer supported strategy to encourage reflection after an IPE experience