Optical-electronic monitoring system of biomedical indicators

The work is devoted to the development of medical systems for monitoring biomedical indicators. The problem of developing a universal hardware software-controlled control system for the diagnosis of biological objects is solved. The main requirements for such a system are a wide range of functionality for combining different methods of measurement transformation and compliance with modern trends in the development of microelectronic sensors. Given the requirements for modern microcircuitry, in particular for sensing devices of the Internet of Things, the signal path of the sensors is implemented on the basis of PSoC family 5LP Family Cypress. Approbation of the developed system is carried out in the course of research of the character of optical radiation in the course of measurement of biomedical indicators.

The Landscape of School Rating Systems

The rise of the accountability movement in education has resulted in the proliferation of school report cards, school ratings and rankings, and other kinds of performance reporting for public consumption and policy use. To understand the strengths and limitations of school rating systems and the role they play in shaping public perceptions and school improvement practices, this paper situates rating systems within the broader field of comparative organizational assessments and neo-institutional theory; describes school rankings and rating systems in use by states and consumer-oriented enterprises; and details four aspects of school ratings (measurement, transformation, integration, and presentation) that affect their use and interpretation.

Covariance Intersection Fusion Kalman Estimator for Multi-Sensor System with Measurements Delays

To handle the state estimation fusion problem between local estimation errors for the system with unknown cross-covariances and to avoid a large computation complexity of cross-covariances, for a multi-sensor linear discrete time-invariant stochastic system with time-delayed measurements, by the measurement transformation method, an equivalent system without measurement delays is obtained, and then using the covariance intersection (CI) fusion method, the covariance intersection fusion steady-state Kalman estimator is presented. It is proved that its accuracy is higher than that of each local estimator, and is lower than that of optimal Kalman fuser weighted by matrices with known cross-covariances. A Monte-Carlo simulation example shows the above accuracy relations, hence it has good performances.

State Estimation of Equivalent Current Measurement Transformation Based on Generalized Tellegen's Theorem

One of the most important ways to enhance the speed of state estimation is to establish the constant matrix Jacobian. This essay puts forward the state estimation method of the equivalent current transformation based on the Generalized Tellegen’s Theorem. This estimation method establishes the constant Jacobian matrix without neglecting the secondary factor making use of the Generalized Tellegen’s Theorem, solves the numerical stability problem caused by the establishment of the constant Jacobian matrix in the current state estimation, and has the advantages of a relatively rapid computing rate and an unparalleled astringency. The method put forward in this essay has been verified through IEEE-30 Node System, and the efficiency of it has been fully proved by the example results.