Electroclinical manifestations elicited by intracerebral electric stimulation "shocks" in temporal lobe epilepsy

In patients with severe drug-resistant partial epilepsy, undergoing Stereo-EEG investigations, spatial definition of the "epileptogenic area" is mainly based on spontaneous seizures recordings, but also on seizures induced by intracerebral electrical stimulation (ES). Only "trains" ES (TES, 50 pps) are currently used with this aim; "shocks" ES (SES, 1 pps) are principally applied to localize motor pathways. We have shown, during a prospective study concerning 10 temporal lobe epileptic patients, that SES could frequently induce seizures, especially when stimulation is applied in the anterior part of the Ammon's horn. Even if its efficacy seems lower than by TES, this kind of stimulation, in the majority of the cases, does reproduce isolated ictal subjective symptomatology, allowing the visualization of the progressive organisation of ictal electrical discharges, and avoids "unexpected" ("false positive"?) clinical responses.     

Learning extended FSA from software: An empirical assessment

A number of techniques that infer finite state automata from execution traces have been used to support test and analysis activities. Some of these techniques can produce automata that integrate information about the data-flow, that is, they also represent how data values affect the operations executed by programs.The integration of information about operation sequences and data values into a unique model is indeed conceptually useful to accurately represent the behavior of a program. However, it is still unclear whether handling heterogeneous types of information, such as operation sequences and data values, necessarily produces higher quality models or not.In this paper, we present an empirical comparative study between techniques that infer simple automata and techniques that infer automata extended with information about data-flow. We investigate the effectiveness of these techniques when applied to traces with different levels of sparseness, produced by different software systems. To the best of our knowledge this is the first work that quantifies both the effect of adding data-flow information within automata and the effectiveness of the techniques when varying sparseness of traces.     

Prediction of time-varying metrology delay for dEWMA and RLS-LT controllers

This paper investigates how to adaptively predict the time-varying metrology delay that can realistically occur in the semiconductor manufacturing practice. In the presence of metrology delays, the expected asymptotic double exponentially weighted moving average (dEWMA) control output, by using the EWMA and recursive least squares prediction methods, is derived. It has been found that the relationships between the expected control output and target in both estimation methods are equivalent, and six cases are addressed. Within the context of time-varying metrology delay, a new time update scheme to the recursive least squares-linear trend (RLS-LT) controller, combined with zone tests and the moving average (MA) control chart, is proposed. Simulated single input–single output (SISO) run-to-run processes subject to two time-varying metrology delay scenarios are used to assess the effectiveness of the proposed controller.     

A general bayes rule and its application to nonlinear estimation

This paper consists of two main results, a general Bayes rule, and a general Bucy representation theorem. The general Bayes rule is a natural generalization of the elementary Bayes rule:

$\text{P(A}\text{B)}\text{P(A)}\text{=}\text{P(B}\text{A)}\text{P(B)}$

. The general Bucy representation theorem plays a central role in nonlinear estimation theory as does the Bucy theorem in nonlinear filtering. A simple and direct proof of the general Bucy representation theorem is obtained by the application of the general Bayes rule.     

Simulation of interconnect inductive impact in the presence of process variations in 90 nm and beyond

The on-chip inductive impact on signal integrity has been a problem for designs in deep-submicrometer technologies. The inductive impact increases the clock skew, max timing, and noise of bus signals. In this letter, circuit simulations using silicon-validated macromodels show that there is a significant inductive impact on the signal max timing (/spl sim/ 10% pushout versus RC delay) and noise (/spl sim/2/spl times/RC noise). In nanometer technologies, process variations have become a concern. Results show that device and interconnect process variations add /spl sim/ 3% to the RLC max-timing impact. However, their impact on the RLC signal noise is not appreciable. Finally, inductive impact in 65- and 45-nm technologies is investigated, which indicates that the inductance impact will not diminish as technology scales.     

Recursive estimation methods for discrete systems

In system identification, the error evolution is composed of two decoupled parts: one is the identifying information on the current estimation residual, while the other is past arithmetic errors. Previous recursive algorithms only considered how to update current prediction errors. Up to now, research has mostly been based on recursive least-squares (RLS) methods. In this note, a general recursive identification method is proposed for discrete systems. Using this new algorithm, a recursive empirical frequency-domain optimal parameter (REFOP) estimate is established. The REFOP method has the advantage of resisting disturbance noise. Some simulations are included to illustrate the new method's reliability.     

Multi-Scale Spoken Document Retrieval for Cantonese Broadcast News

This paper presents the application of a multi-scale paradigm to Chinese spoken document retrieval (SDR) for improving retrieval performance. Multi-scale refers to the use of both words and subwords for retrieval. Words are basic units in a language that carry lexical meaning, and subword units (such as phonemes, syllables or characters) are building components for words. Retrieval using subword indexing units is better than retrieval using words because of the robustness of subword units to out-of-vocabulary (OOV) words during speech recognition and ambiguities in word segmentation. Experimental results have demonstrated that subword bigrams can bring improvement in retrieval performance over words (～9.56%). Application of multi-scale fusion to SDR aims at combining the lexical information of words and the robustness of subwords. This work presents the first detailed investigation for a Cantonese broadcast news retrieval task using two different multi-scale fusion approaches: pre-retrieval fusion and post-retrieval fusion. Multi-scale retrieval using both words and syllable bigrams achieves improvement in retrieval performance (～1.90%) over retrieval on the composite scales.     

Modeling the Heterogeneity in Contractors’ Mark-Up Behavior

Individual contractors exhibit different bidding behaviors when confronted with a given set of project decision environment factors, i.e., heterogeneity in the population of contractors. In examining the tenability of the bidder homogeneity assumption, a linear mixed modeling approach is applied to two data sets obtained from Hong Kong and Singapore contractors via a bidding experiment. Two linear mixed models were developed by relating the contractors’ mark-up decision to four project decision environment factors, namely, (1) market conditions; (2) number of bidders; (3) project type; and (4) project size. The results show that not only is there a significant heterogeneity between the Hong Kong and the Singapore contractors in terms of both their preferences (intercepts) and responses (slopes) to the project decision environment factors that affect their mark-up decision, but also that the individual Hong Kong and Singapore contractors have different degrees of sensitivity toward the project decision environment factors (which is reflected in the varying individual-specific intercepts and slopes). These individual-specific parameter estimates have implications for managerial action in formulating a firm’s competitive strategies.     

Dual-mode-control multiphase DC/DC converter

High-performance voltage-regulator modules for the new generation of microprocessors have many strict and challenging specifications, such as high power density, high output-current capability, low output-voltage deviation and fast transient response. A dual mode control multiphase DC/DC converter is presented, which combines voltage and hysteretic control modes and has the merits of high efficiency, simple control and fast transient response. It can also be used for single-phase and built-in integrated circuits without requiring additional cost and space. The operating principles and design considerations are analysed and discussed in detail. A 1.3 V/80 A four-phase laboratory prototype is simulated and implemented to verify the feasibility of the proposed scheme. The results prove to be satisfactory