We investigated the relationship between the intracranial pulse pressure (ICP/sub PP/) and the mean intracranial pressure (ICP/sub M/). In adult patients, several research groups have described a linear relationship b...
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We investigated the relationship between the intracranial pulse pressure (ICP/sub PP/) and the mean intracranial pressure (ICP/sub M/). In adult patients, several research groups have described a linear relationship between ICP/sub PP/ and ICP/sub M/ within the range of cerebral autoregulation. Current monitoring and therapy are mainly based on the mean ICP/sub M/, since it is believed that the ICP/sub M/ contains most of the information provided by the other pulse morphology metrics. In this paper we attempt to answer whether there is further information within the ICP morphology not explained by ICP/sub M/ that might be of prognostic significance. We screened ICP records of 42 patients admitted to the Pediatric Intensive Care Unit at Doernbecher Children's Hospital for segments in which the ICP/sub M/ varied at least 5 mmHg during a 1-hour period. We found 54 segments in 9 different pediatric TBI patients (ages 0.2-17.8 years, mean=9.9 years). ICP/sub PP/ and ICP/sub M/ were calculated for each pulse using an automatic pressure detection algorithm. The coefficient of linear correlation r was > 0.70 in 43/54 segments (p < 0.001), which indicates that there exists a linear relationship between ICP/sub PP/ and ICP/sub M/. However, we found r > 0.90 only in 16/54 segments (p=NS) . This result and visual inspection of ICP/sub PP/ vs. ICP/sub M/ density plots suggest that ICP pulse pressure is not fully explained by the ICP M.
We describe a computer model of intracranial pressure (ICP) dynamics that evaluates clinical treatment options for elevated ICP during traumatic brain injury (TBI). The model uses fluid volumes as primary state variab...
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We describe a computer model of intracranial pressure (ICP) dynamics that evaluates clinical treatment options for elevated ICP during traumatic brain injury (TBI). The model uses fluid volumes as primary state variables and explicitly models fluid flows as well as the resistance, compliance, and pressure associated with each intra- and extracranial compartment (arteries and arterioles, capillary bed, veins, venous sinus, ventricles, and brain parenchyma). The model evaluates clinical events and therapies such as intraand extra-parenchymal hemorrhage, cerebral edema, cerebrospinal fluid drainage, mannitol administration, head elevation, and mild hyperventilation. The model is able to replicate observed clinical behavior in many cases, including elevated ICP associated with severe cerebral edema following subdural, epidural, or intraparenchymal hematoma. The model also mimics cerebrovascular regulatory mechanisms that are activated during TBI.
The Level 1 Muon Trigger subsystem for BTeV will be implemented using the same architectural building blocks as the BTeV Level 1 Pixel Trigger: pipelined field programmable gate arrays feeding a farm of dedicated proc...
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The Level 1 Muon Trigger subsystem for BTeV will be implemented using the same architectural building blocks as the BTeV Level 1 Pixel Trigger: pipelined field programmable gate arrays feeding a farm of dedicated processing elements. The muon trigger algorithm identifies candidate tracks, and is sensitive to the muon charge (sign);candidate dimuon events are identified by complementary charge track-pairs. To insure that the trigger is operating effectively, the trigger development team is actively collaborating in an independent multi-university research program for reliable, self-aware, fault adaptive behavior in real-time embedded systems (RTES). Key elements of the architecture, algorithm, performance, and engineered reliability are presented.
Aboard current ships, such as the DDG 51, engineering control and damage control activities are manpower intensive. It is anticipated that, for future combatants, the workload demand arising from operation of systems ...
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Aboard current ships, such as the DDG 51, engineering control and damage control activities are manpower intensive. It is anticipated that, for future combatants, the workload demand arising from operation of systems under conditions of normal steaming and during casualty response will need to be markedly reduced via automated monitoring, autonomous control, and other technology initiatives. Current DDG 51 class ships can be considered as a manpower baseline and under Condition III typical engineering control involves seven to eight watchstanders at manned stations in the Central Control Station, the engine rooms and other machinery spaces. In contrast to this manning level, initiatives such as DD 21 and the integrated engineering plant (IEP) envision a partnership between the operator and the automation system, with more and more of the operator's functions being shifted to the automation system as manning levels decrease. This paper describes some human systems integration studies of workload demand reduction and, consequently, manning reduction that can be achieved due to application of several advanced technology concepts. Advanced system concept studies in relation to workload demand are described and reviewed including. Piecemeal applications of diverse automation and remote control technology concepts to selected high driver tasks in current DDG 51 activities. Development of the reduced ship's crew by virtual presence system that will provide automated monitoring and display to operators of machinery health, compartment conditions, and personnel health. The IEP envisions the machinery control system as a provider of resources that are used by various consumers around the ship. Resource needs and consumer priorities are at all times dependent upon the ship's current mission and the availability of equipment pawnbrokers.
We present the fuzzy Markov predictor (FMP), a hybrid system that is applied to the task of monthly electric load forecasting. The FMP is a modification we introduce in the hidden Markov model in order to enable it to...
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We present the fuzzy Markov predictor (FMP), a hybrid system that is applied to the task of monthly electric load forecasting. The FMP is a modification we introduce in the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor (FBP) that was modified from the naive Bayes classifier. For verifying the efficiency of the FMP's prediction, we compare it with the FBP, one fuzzy system and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.
In this paper we present a new, adaptive spatial-derivative circuit for CMOS image sensors. The circuit removes its offset as a natural part of its operation using a combination of electron tunneling and hot-electron ...
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In this paper we present a new, adaptive spatial-derivative circuit for CMOS image sensors. The circuit removes its offset as a natural part of its operation using a combination of electron tunneling and hot-electron injection to add or remove charge on a floating-gate of an auto-zeroing amplifier. We designed, fabricated and successfully tested a chip with the circuit. Test results show that the circuit reduces the offsets by more than an order of magnitude.
The design of wholesale electricity markets through deregulation has focused almost exclusively on the development of competitive supply (generation). The demand side of the market has been virtually ignored. Mostly, ...
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ISBN:
(纸本)0780373227
The design of wholesale electricity markets through deregulation has focused almost exclusively on the development of competitive supply (generation). The demand side of the market has been virtually ignored. Mostly, this is due to the assumption that electricity demand is almost completely inelastic. As a result, deregulated wholesale markets universally fail to pass price signals down to the end-users. This paper challenges the assumption of inelastic demand by exploring the potential benefits of implementing a simple load control scheme. This load control scheme allows consumers to shift demand from high priced hours to low priced hours during the day. The benefits to the individual consumer are explored through an example applied to residential air conditioning using price and demand data from California. This example shows that "smart" use of air conditioning can lead to great savings for residential consumers, without sacrificing comfort. The potential for multiple consumers implementing load control to reduce wholesale prices is also examined.
A soft expert system is defined to be one that is qualitatively fuzzy. In this paper, we present such a system known as "KASER" which stands for 'Knowledge Amplification by Structural Expert Randomizatio...
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A soft expert system is defined to be one that is qualitatively fuzzy. In this paper, we present such a system known as "KASER" which stands for 'Knowledge Amplification by Structural Expert Randomization". KASER facilitates reasoning using domain specific expert and commonsense knowledge. It accomplishes this through object-classed predicates and an associated novel inference engine. It addresses the high cost associated with the knowledge acquisition bottleneck. It also enables the entry of a basis of rules and provides for the automatic extension of that basis through domain symmetries. We demonstrate an application for KASER in the design of an intelligent tutoring system that teaches the basic science of crystal-laser design. It enables the student to experiment with various design concepts and receive feedback on the functionality of the proposed design. This is possible without a need to preprogram all possible scenarios.
Adaptive critics have shown much promise for designing optimal nonlinear controllers in an off-line context. Still, their greatest potential exists in the context Of reconfigurable control, that is, real time controll...
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Adaptive critics have shown much promise for designing optimal nonlinear controllers in an off-line context. Still, their greatest potential exists in the context Of reconfigurable control, that is, real time controller redesign in response to (substantial) changes in plant dynamics. To accomplish this, a framework is proposed for the application of adaptive critics in real-time control (for those critic methods requiring a model of the plant). The framework is presented in the context of work being done in reconfigurable flight control by the NW Computational Intelligence Lab (NWCIL) at Portland State University. The proposal incorporates recent work (by others) in fast and efficient on-line plant identification, considerations for bounding the computational costs of converging neural networks, and a novel approach (by us) toward the task of assuring system stability during the adaptation process. The potential and limitations of the proposed framework are discussed. It is suggested that with the recent rapid reduction in computational barriers, only certain theoretical issues remain as the central barriers to successful on-line application of the methods.
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