BACKGROUND AND AIMS Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data. METHODS The predictor ...

In this paper we evaluate the performance of singlefrequency, single-point positioning processors with an emphasis on ionospheric delay handling. A number of least-squares processors with singlefrequency code-only and code-and-carrier-phase observables were developed. Processing model hierarchy is based on measurement error handling, starting with a basic code-based navigation solution and prog...

This paper extends earlier results of wave based approach for stable force re°ecting systems in the presence of the transmission delay (constant or variable). Theoretically, stability of the whole system is kept for any time delay, but degradation performance increases proportionally with a large delays. In this paper, we propose a new control scheme that is also based on wave variables, but mi...

The present article deals with a fault and delay tolerant multi-sensor control scheme. In particular, we consider a process affected by additive disturbance which is monitored by redundant sensors. The process is controlled by a digital controller which is connected with the sensors via shared network. It is assumed that sensors are subject to abrupt faults while the communication between the s...

BODINE, JILL THERESE. Exploiting Computational Locality in Global Value Histories. (Under the direction of Thomas M. Conte.) Value prediction is a speculative technique to break true data dependencies by using history to predict values before they are computed. Previous research focused on exploiting two types of value locality (computation-based and context-based) in the local value history, w...

SUMMARY: Real-time hybrid simulation (RHS) is a powerful technique to evaluate structural dynamic performance by combining physical simulation of complicated and rate-dependent portion of a structure and numerical simulation of the rest portion of the same structure. This paper shows that the stability of RHS with time delay is not only related to compensation methods but also to the integratio...

Spatio-temporal feature encoding is essential for encoding facial expression dynamics in video sequences. At test time, most spatio-temporal encoding methods assume that a temporally segmented sequence is fed to a learned model, which could require the prediction to wait until the full sequence is available to an auxiliary task that performs the temporal segmentation. This causes a delay in pre...

As a core technology of Intelligent Transportation System, traffic flow prediction has wide range applications. The fundamental challenge in is to effectively model the complex spatial-temporal dependencies data. Spatial-temporal Graph Neural Network (GNN) models have emerged as one most promising methods solve this problem. However, GNN-based three major limitations for prediction: i) Most spa...

In the current paper the decoding algorithms for motor-related BCI systems for continuous upper limb trajectory prediction are considered. Two methods for the smooth prediction, namely Sobolev and Polynomial Penalized Multi-Way Partial Least Squares (PLS) regressions, are proposed. The methods are compared to the Multi-Way Partial Least Squares and Kalman Filter approaches. The comparison demon...