This paper explores the possibility of applying multi-sensor information fusion technology to the development of smart aircraft. This technology integrates information from multiple sensors and extracts tactical information to detect, track and identify time critical targets at any time, in any place and under all weather conditions. Such target information will help the war fighter avoid fratr...

This letter considers how to approximately reconstruct a cascade system from a given unstructured system estimate. Many system identification methods, including subspace methods, provide reliable but generally unstructured black-box models. The problem we consider is how to find cascade systems that are close to such black-box models. For this, we use model matching techniques and optimal weigh...

Beaudry and Portier (2006) propose an identification scheme to study the effects of news shocks about future productivity in Vector Error Correction Models (VECM). This comment shows that their methodology does not have a unique solution, when applied to their VECMs with more than two variables. The problem arises from the interplay of cointegration assumptions and long-run restrictions imposed...

Forecast DNI values in hourly resolution for one day ahead are evaluated by a comparison with pyrheliometer ground measurements. Three months of such day ahead forecasts from four different providers for a site close to Questa, NM, USA are analyzed firstly by calculating the RMSE and the mean bias error. Secondly, cumulative distributions of the DNI forecast errors are calculated as they better...

In order to increase the reliability of data transmission, using multiple antennas in radio frequency identification (RFID) systems has been investigated by researchers, mainly through measurements and simulations. The multiple-input multiple-output (MIMO) RFID backscattering channel exhibits a special type of cascaded structure rather than that of other better-studied cascaded channels such as...

In this paper, we present an approach to the automatic identification and correction of preposition and determiner errors in nonnative (L2) English writing. We show that models of use for these parts of speech can be learned with an accuracy of 70.06% and 92.15% respectively on L1 text, and present first results in an error detection task for L2 writing.

In this paper we explore the use of lexical information for language identification (LID). Our reference LID system uses language-dependent acoustic phone models and phone-based bigram language models. For each language, lexical information is introduced by augmenting the phone vocabulary with the N most frequent words in the training data. Combined phone and word bigram models are used to prov...

The high cost of model predictive control (MPC) technology has hampered its wide application in process industries beyond the refining/petrochemical industry. This work aims to increase the efficiency of MPC deployment. First a semi-automatic MPC system is introduced. It consists of three modules: an MPC control module, an online identification module and a control monitor module. The goal of t...

Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061...

The aim of the present investigation was to determine the relative extent of geometric error and errors in point identification in postero-anterior roentgenography. In one series of tests a group of dry human skulls was used, and the same cephalometric landmarks were identified twice by two orthodontists, using postero-anterior roentgenographs, first using the dry skulls as such, and then the s...