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At least 541 records · Page 30Linked to original sources
PubMed2003

OligoDesign: Optimal design of LNA (locked nucleic acid) oligonucleotide capture probes for gene expression profiling.

We report the development of new software, OligoDesign, which provides optimal design of LNA (locked nucleic acid) substituted oligonucleotides for functional genomics applications. LNAs constitute a novel class of bicyclic RNA analogs having an exceptionally high affinity and specificity toward their complementary DNA and RNA target molecules. The OligoDesign software features recognition and filtering of the target sequence by genome-wide BLAST analysis in order to minimize cross-hybridization with non-target sequences. Furthermore it includes routines for prediction of melting temperature, self-annealing and secondary structure for LNA substituted oligonucleotides, as well as secondary structure prediction of the target nucleotide sequence. Individual scores for all these properties are calculated for each possible LNA oligonucleotide in the query gene and the OligoDesign program ranks the LNA capture probes according to a combined fuzzy logic score and finally returns the top scoring probes to the user in the output. We have successfully used the OligoDesign tool to design a Caenorhabditis elegans LNA oligonucleotide microarray, which allows monitoring of the expression of a set of 120 potential marker genes for a variety of stress and toxicological processes and toxicologically relevant pathways. The OligoDesign program is freely accessible at http://lnatools.com/.

Animals↗
PubMed2001

The marine food chain in relation to biodiversity.

Biodiversity provides "raw materials" for the food chain and seafood production, and also influences the capacity of ecosystems to perform these and other services. Harvested marine seafood species now exceed 100 million t y(-1) and provide about 6% of all protein and 17% of animal protein consumed by humans. These resources include representatives from about nine biologically diverse groups of plants and animals. Fish account for most of the world"s marine catches, of which only 40 species are taken in abundance. Highest primary productivity and the richest fisheries are found within Exclusive Economic Zones (EEZ). This narrow strip (200 nautical mile/370 km wide) is not only the site of coastal "food factories" but also the area associated with heaviest perturbation to the marine environment. Structural redundancy is evident in marine ecosystems, in that many species are interchangeable in the way they characterise assemblage composition. While there is probably functional redundancy within groups, the effects of species loss on ecosystem performance cannot be easily predicted. In particular, the degree to which biodiversity per se is needed for ecosystem services, including seafood/fishery production, is poorly understood. Many human activities, including unsustainable fishing and mariculture, lead to erosion of marine biodiversity. This can undermine the biophysical cornerstones of fisheries and have other undesirable environmental side effects. Of direct concern are "species effects", in particular the removal of target and non-target fishery species, as well as conservationally important fauna. Equally disrupting but less immediate are "ecosystem effects", such as fishing down the food web, following a shift from harvested species of high to low trophic level. Physical and biological disturbances from trawl nets and dynamite fishing on coral reefs can also severely impact ecosystem structure and function. "Broadscale" biological and social effects brought about by fishing carry even more far-reaching consequences. For example, fishing itself can change the age at which sexual maturity is reached, thus affecting the reproductive status of the stock. Hence, fishing may be regarded as a mediator of evolution. Social impacts include conflicts over fish prices and policies arising from heavy fishing and inadequate institutional structures. Measures to increase the sustainability of catches and of biodiversity need to be much more tightly coupled. Promising approaches include use of bio-economic indicators and fully protected marine areas. High- and local-level governance options are also examined. Use of expert systems incorporating "fuzzy logic" are providing useful environmental insights in the ASEAN countries and other parts of the world, and have applications in fishery management and biodiversity conservation.

Animals↗
PubMed2002

Comparison of Artificial Neural Network (ANN) Model Development Methods for Prediction of Macroinvertebrate Communities in the Zwalm River Basin in Flanders, Belgium.

Modelling has become an interesting tool to support decision making in water management. River ecosystem modelling methods have improved substantially during recent years. New concepts, such as artificial neural networks, fuzzy logic, evolutionary algorithms, chaos and fractals, cellular automata, etc., are being more commonly used to analyse ecosystem databases and to make predictions for river management purposes. In this context, artificial neural networks were applied to predict macroinvertebrate communities in the Zwalm River basin (Flanders, Belgium). Structural characteristics (meandering, substrate type, flow velocity) and physical and chemical variables (dissolved oxygen, pH) were used as predictive variables to predict the presence or absence of macroinvertebrate taxa in the headwaters and brooks of the Zwalm River basin. Special interest was paid to the frequency of occurrence of the taxa as well as the selection of the predictors and variables to be predicted on the prediction reliability of the developed models. Sensitivity analyses allowed us to study the impact of the predictive variables on the prediction of presence or absence of macroinvertebrate taxa and to define which variables are the most influential in determining the neural network outputs.

Amphipoda↗
PubMed1997

Method for segmenting chest CT image data using an anatomical model: preliminary results.

We present an automated, knowledge-based method for segmenting chest computed tomography (CT) datasets. Anatomical knowledge including expected volume, shape, relative position, and X-ray attenuation of organs provides feature constraints that guide the segmentation process. Knowledge is represented at a high level using an explicit anatomical model. The model is stored in a frame-based semantic network and anatomical variability is incorporated using fuzzy sets. A blackboard architecture permits the data representation and processing algorithms in the model domain to be independent of those in the image domain. Knowledge-constrained segmentation routines extract contiguous three-dimensional (3-D) sets of voxels, and their feature-space representations are posted on the blackboard. An inference engine uses fuzzy logic to match image to model objects based on the feature constraints. Strict separation of model and image domains allows for systematic extension of the knowledge base. In preliminary experiments, the method has been applied to a small number of thoracic CT datasets. Based on subjective visual assessment by experienced thoracic radiologists, basic anatomic structures such as the lungs, central tracheobronchial tree, chest wall, and mediastinum were successfully segmented. To demonstrate the extensibility of the system, knowledge was added to represent the more complex anatomy of lung lesions in contact with vessels or the chest wall. Visual inspection of these segmented lesions was also favorable. These preliminary results suggest that use of expert knowledge provides an increased level of automation compared with low-level segmentation techniques. Moreover, the knowledge-based approach may better discriminate between structures of similar attenuation and anatomic contiguity. Further validation is required.

Computer Simulation↗
PubMed2006

Fuzzy-based controller for glucose regulation in type-1 diabetic patients by subcutaneous route.

This paper presents an advisory/control algorithm for a type-1 diabetes mellitus (TIDM) patient under an intensive insulin treatment based on a multiple daily injections regimen (MDIR). The advisory/control algorithm incorporates expert knowledge about the treatment of this disease by using Mamdani-type fuzzy logic controllers to regulate the blood glucose level (BGL). The overall control strategy is based on a two-loop feedback strategy to overcome the variability in the glucose-insulin dynamics from patient to patient. An inner-loop provides the amount of both rapid/short and intermediate/long acting insulin (RSAI and ILAI) formulations that are programmed in a three-shots daily basis before meals. The combined preparation is then injected by the patient through a subcutaneous route. Meanwhile, an outer-loop adjusts the maximum amounts of insulin provided to the patient in a time-scale of days. The outer-loop controller aims to work as a supervisor of the inner-loop controller. Extensive closed-loop simulations are illustrated, using a detailed compartmental model of the insulin-glucose dynamics in a TIDM patient with meal intake.

Algorithms↗
PubMed2004

An intelligent service-based network architecture for wearable robots.

We are developing a novel robot concept called the wearable robot. Wearable robots are mobile information devices capable of supporting remote communication and intelligent interaction between networked entities. In this paper, we explore the possible functions of such a robotic network and will present a distributed network architecture based on service components. In order to support the interaction and communication between the components in the wearable robot system, we have developed an intelligent network architecture. This service-based architecture involves three major mechanisms. The first mechanism involves the use of a task coordinator service such that the execution of the services can be managed using a priority queue. The second mechanism enables the system to automatically push the required service proxy to the client intelligently based on certain system-related conditions. In the third mechanism, we allow the system to automatically deliver services based on contextual information. Using a fuzzy-logic-based decision making system, the matching service can determine whether the service should be automatically delivered utilizing the information provided by the service, client, lookup service, and context sensors. An application scenario has been implemented to demonstrate the feasibility of this distributed service-based robot architecture. The architecture is implemented as extensions to the Jini network model.

Algorithms↗
PubMed2004

Geometrical accuracy and fusion of multimodal vascular images: a phantom study.

The aim of this work was to compare the geometrical accuracy of x-ray angiography, magnetic resonance imaging (MRI), x-ray computed tomography (XCT), and ultrasound imaging (B-mode and IVUS, or intravascular ultrasound) for measuring the lumen diameters of blood vessels. An image fusion method was also developed to improve these measurements. The images were acquired from a phantom that mimic vessels of known diameters. After acquisition, the multimodal images were coregistered by manual alignment of fiducial markers, and then by maximization of mutual information. The fusion method was performed by means of a fuzzy logic modeling approach followed by a combination process based on a possibilistic theory. The results showed (i) the better geometrical accuracy of XCT and IVUS compared to the other modalities, and (ii) the better accuracy and smaller variability of fused images compared to single modalities, with respect to most diameters investigated. For XCT, the error varied from 0.4% to 5.4%, depending on the vessel diameter that ranged from 0.93 to 6.24 mm. For IVUS, the error ranged from -0.3% to 1.7% but the smallest vessel (0.93 mm) could not be investigated because of the probe size. Compared to others fusion schemes, the XCT-MRI fused images provided the best results for both accuracy (from -1.6% to 0.2% for the three largest vessels) and robustness (mean relative error of 1.9%). To conclude, this work underlined both the usefulness of the multimodality vascular phantom as a validation tool and the utility of image fusion in the vascular context.

Angiography↗
PubMed1980

Evaluation and integration of acoustic features in speech perception.

Identification of synthetic stop consonants as either /bae/, /pae/, /dae/, or /tae/ was examined in two experiments in which the stimuli varied independently on voice onset time (VOT), the consonantal second and third formant (F2-F3) transitions and, in experiment 2, the intensity of the aspiration noise during the VOT period. In both experiments, the patterns of the resulting identification probabilities were complex, but systematic, functions of each of the independent variables. Of most interest was the fact that the likelihood of identifying a stimulus to be /bae/ or /pae/, rather than /dae/ or /tae/, was strongly influenced by the VOT as well as by the F2-F3 transitions. Analogously, the likelihood of identifying a stimulus to be /bae/ or /dae/, rather than /pae/ or /tae/, depended on the F2-F3 transitions as well as on VOT. Three explanations of these results were considered within a fuzzy logical model of speech perception: (1) that there is interaction in the evaluation of acoustic features, (2) that the listener requires more extreme values of acoustic features for some speech sounds than for that of other speech sounds, and (3) that the aspiration noise during the VOT period serves as an independent acoustic feature to distinguish /pae/ and /bae/ from /tae/ and /dae/.

Adult↗
PubMed1996

Perception of asynchronous and conflicting visual and auditory speech.

Previous research has shown that perceivers naturally integrate auditory and visual information in face-to-face speech perception. Two experiments were carried out to study whether integration would be disrupted by differences in the stimulus onset asynchrony (SOA), the temporal arrival of the two sources of information. Synthetic visible and natural and synthetic auditory syllables off/ba/, /va/, [symbol: see text]a/, and /da/ were used in an expanded factorial design to present all possible combinations of the auditory and visual syllables, as well as the unimodal syllables. The fuzzy logical model of perception (FLMP), which accurately describes integration, was used to measure the degree to which integration of audible and visible speech occurred. These findings provide information about the temporal window of integration and its apparent dependence on the range of speech events in the test.

Adult↗
PubMedDate not supplied

Online practice guidelines: issues, obstacles, and future prospects.

The "guidelines movement" was formed to reduce variability in practice, control costs, and improve patient care outcomes. Yet the overall impact on practice and outcomes has been disappointing. Evidence demonstrates that the most effective method of stimulating awareness of and compliance with best practices is computer-generated reminders provided at the point of care. This paper reviews five steps along the path from the development of a guideline to its integration into practice and the subsequent evaluation of its impact on practice and outcomes. Issues arising at each step and obstacles to moving from one step to the next are described. Last, developments that could help overcome the obstacles are highlighted. These include 1) more rapid knowledge acquisition using data mining, 2) better accommodation to imprecise knowledge in clinical algorithms using fuzzy logic, 3) development of a shareable model for guideline representation and execution, and 4) more widespread availability of clinically robust information systems that support decision-making at the point of care.

Algorithms↗
PubMed1995

Predicting conditional probability distributions: a connectionist approach.

Most traditional prediction techniques deliver a single point, usually the mean of a probability distribution. For multimodal processes, instead of predicting the mean, it is important to predict the full distribution. This article presents a new connectionist method to predict the conditional probability distribution in response to an input. The main idea is to transform the problem from a regression problem to a classification problem. The conditional probability distribution network can perform both direct predictions and iterated predictions, the latter task being specific for time series problems. We compare this new method to fuzzy logic and discuss important differences, and also demonstrate the architecture on two time series. The first is the benchmark laser series used in the Santa Fe competition, a deterministic chaotic system. The second is a time series from a Markov process which exhibits structure on two time scales. The network produces multimodal predictions for this series. We compare the predictions of the network with a nearest-neighbor predictor and find that the conditional probability network is more than twice as likely a model.

Neural Networks, Computer↗
PubMed2004

Process control in municipal solid waste incinerators: survey and assessment.

As there is only rare and scattered published information about the process control in industrial incineration facilities for municipal solid waste (MSW), a survey of the literature has been supplemented by a number of waste incineration site visits in Belgium and The Netherlands, in order to make a realistic assessment of the current status of technology in the area. Owing to the commercial character, and therefore, the confidentiality restrictions imposed by plant builders and many of the operators, much of the information collected has either to be presented in a generalized manner, and in any case anonymously. The survey was focused on four major issues: process control strategy, process control systems, monitors used for process control and finally the correlation between the 850 degrees C/2 s rule in the European waste incineration directive and integrated process control. The process control strategies range from reaching good and stable emissions at the stack to stabilizing and maximizing the energy output from the process. The main indicator to be monitored, in cases in which the focus is controlling emissions, is the oxygen content in the stack. Keeping the oxygen concentration in a determined range (usually between 8 and 12 vol.%) ensures stable and tolerated concentrations of the gaseous emissions. In the case for which stabilization of energy production is the principal aim, the main controlled parameter is the steam temperature and flow-rate, which is usually related to the fuel energetic input. A lot of other parameters are used as alarm criteria, the most common of which is the carbon monoxide concentration. The process control systems used most commonly feature partially automated classical proportional integral derivative (PID) controllers. New and innovative process control systems, such as fuzzy-logic control systems, are still unknown to most plant managers while their performance is reported to be unsatisfactory in plants in which such systems have been tested or are in use. Monitoring components used in process control are still based on classical tools such as thermocouples. The use of modern and more reliable sensors is very limited due to the high initial investment cost or simply the fear of using non-standard technologies. Complying with the 850 degrees C/2 s rule in the European waste incineration directive generally is seen to be a handicap for the process control, either in terms of cost, or flexibility of reaction, or both, particularly in old incineration facilities where such restrictions were not planned in the design.

Belgium↗
PubMed1998

Expert systems in anesthesiology.

There are only a limited number of computer-based systems designed to support anesthesiologists in the operating room. This is evident from the very small number of publications on this topic. These systems may be classified by the functions they perform and include: intelligent anesthesia workstations (with current data acquisition, conditioning and analysis subsystems), systems to detect critical conditions in patients (including expert systems in smart alarm capacity), anesthesia management systems (for planning and management) and drug administration systems. Drug administration systems may be subdivided into open-loop and closed-loop systems. The techniques applied for design of such systems vary extensively. There are traditional rule-based expert systems and probability-based systems, and more recently developed artificial intelligence methods, such as neural networks and fuzzy logic. Computers are valuable tools that have the potential to assist anesthesiologists in carrying out cumbersome and monotonous processes. Future efforts may result in the development of sophisticated systems capable of assuming more responsibilities and of reducing human workload and stress.

Journal Article↗
PubMed2002

Dynamic QSAR techniques: applications in drug design and toxicology.

The basic principles of 3-D quantitative structure-activity relationships (QSARs) analysis are discussed in the light of the fuzzy logic concept. According to that concept, the traditionally one chemical - one structure - one parameter value relationship in QSAR is suggested to be modified into one chemical finite set of structures - range of parameter values principle. In this respect, two recently developed techniques accounting for conformational flexibility in 3-D QSARs are reviewed. A basic assumption underlying both methods is that chemical behavior in complex biological systems is context-dependent. A molecule can exist and interact in a variety of conformations depending on the specificity of the endpoint under investigation and reaction media. It was demonstrated that selection of active conformer(s) in QSAR studies is a task as important as the selection of relevant molecular parameters. Specifically selected active conformers, rather than the lowest-energy states of the chemicals are suggested to be used in the correlative QSARs. The method for recognition the common reactivity pattern (COREPA) of structurally heterogeneous compounds that elicit similar biological behaviour is based on all energetically reasonable conformers of chemicals. The principle assumption of the method is that biologically similar chemicals should possess a commonality in their stereoelectronic (reactivity) pattern. Originally developed algorithms for conformer generation are presented in association with the QSAR methods accounting for conformational flexibility of chemicals. Applicability of the QSAR technique for selection active conformers is illustrated by presenting QSAR models derived for Ah binding affinity of PCBs and antimicrobial activity of rifamicin derivatives. Models for predicting estrogenic activity of structurally diverse chemicals and ACE inhibition exemplified the applicability of the COREPA method. The model performance is analyzed by the 3D screening exercise of large chemical inventories with subsequent experimental validation within the EDAEP project. Besides the impact of conformational flexibility of chemicals in 3D QSAR the role of different molecular descriptors is discussed with respect to their ability to describe molecular interactions with different specificity.

Combinatorial Chemistry Techniques↗
PubMed1993

The dramatic change from empirical to scientific technology in medicine: computerized imaging, communications and holography.

Perhaps the single most important element in the rapid development of contemporary diagnostic imaging is simply its feasibility that results from the deliberate use of complicated, but powerful, mathematical formulation. Implemented with various types of computers, today mostly digital, in such applications at CT (computerized tomography), MRI (magnetic resonance imaging) and others, the underlying principles of the 3-D (three-dimensional) image recording and reconstruction can all be traced back to the principles of "holography". Further improvements in image communications and processing, for example in view of robotized "Imaging-guided Stereotactic Diagnosis and Treatment" in high-field MRI is likely to result from suitable use of "Fuzzy Logic".

Diagnostic Imaging↗
PubMed2006

Success at first insemination in Australian Angus cattle: analysis of uncertain binary responses.

Field data from Australian Angus herds were used to investigate 2 methods of analyzing uncertain binary responses for success or failure at first insemination. A linear mixed model that included herd, year, and month of mating as fixed effects; unrelated service sire, additive animal, and residual as random effects; and linear and quadratic effects of age at mating as covariates was used to analyze binary data. An average gestation length (GL) derived from artificial insemination data was used to assign an insemination date to females mated to natural service sires. Females that deviated from this average GL led to uncertain binary responses. Two analyses were carried out: 1) a threshold model fitted to uncertain binary data, ignoring uncertainty (M1); and 2) a threshold model fitted to uncertain binary data, accounting for uncertainty via fuzzy logic classification (M2). There was practically no difference between point estimates obtained from M1 and M2 for service sire and herd variance; however, when uncertain binary data were analyzed ignoring uncertainty (M1), additive variance and heritability estimates were greater than with M2. Pearson correlations indicated that no major reranking would be expected for service sire effects and animal breeding values using M1 and M2. Given the results of the current study, a threshold model contemplating uncertainty is suggested for noisy binary data to avoid bias when estimating genetic parameters.

Animals↗
PubMed1998

Automatic classification of transiently evoked otoacoustic emissions using an artificial neural network.

The increasing use of transiently evoked otoacoustic emissions (TEOAE) in large neonatal hearing screening programmes makes a standardized method of response classification desirable. Until now methods have been either subjective or based on arbitrary response characteristics. This study takes an expert system approach to standardize the subjective judgements of an experienced scorer. The method that is developed comprises three stages. First, it transforms TEOAEs from waveforms in the time domain into a simplified parameter set. Second, the parameter set is classified by an artificial neural network that has been taught on a large database TEOAE waveforms and corresponding expert scores. Third, additional fuzzy logic rules automatically detect probable artefacts in the waveforms and synchronized spontaneous emission components. In this way, the knowledge of the experienced scorer is encapsulated in the expert system software and thereafter can be accessed by non-experts. Teaching and evaluation of the neural network was based on TEOAEs from a database totalling 2190 neonatal hearing screening tests. The database was divided into learning and test groups with 820 and 1370 waveforms respectively. From each recorded waveform a set of 12 parameters was calculated, representing signal static and dynamic properties. The artifical network was taught with parameter sets of only the learning groups. Reproduction of the human scorer classification by the neural net in the learning group showed a sensitivity for detecting screen fails of 99.3% (299 from 301 failed results on subjective scoring) and a specificity for detecting screen passes of 81.1% (421 of 519 pass results). To quantify the post hoc performance of the net (generalization), the test group was then presented to the network input. Sensitivity was 99.4% (474 from 477) and specificity was 87.3% (780 from 893). To check the efficiency of the classification method, a second learning group was selected out of the previous test group, and the previous learning group was used as the test group. Repeating learning and test procedures yielded 99.3% sensitivity and 80.7% specificity for reproduction, and 99.4% sensitivity and 86.7% specificity for generalization. In all respects, performance was better than for a previously optimized method based simply on cross-correlation between replicate non-linear waveforms. It is concluded that classification methods based on neural networks show promise for application to large neonatal screening programmes utilizing TEOAEs.

Artificial Intelligence↗
PubMed2004

Mandarin speech perception by ear and eye follows a universal principle.

In this study, the nature of speech perception of native Mandarin Chinese was compared with that of American English speakers, using synthetic visual and auditory continua (from /ba/ to /da/) in an expanded factorial design. In Experiment 1, speakers identified synthetic unimodal and bimodal speech syllables as either /ba/ or /da/. In Experiment 2, Mandarin speakers were given nine possible response alternatives. Syllable identification was influenced by both visual and auditory sources of information for both Mandarin and English speakers. Performance was better described by the fuzzy logical model of perception than by an auditory dominance model or a weighted-averaging model. Overall, the results are consistent with the idea that although there may be differences in information (which reflect differences in phonemic repertoires, phonetic realizations of the syllables, and the phonotactic constraints of languages), the underlying nature of audiovisual speech processing is similar across languages.

Adolescent↗