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At least 883 records · Page 49Linked to original sources

Musical inventiveness of five idiots-savants.

Accounts of musical ability in idiots-savants have up till now been confined to stressing the astounding musical memory which such persons may possess. The present study investigates compositional and improvisational skills in five idiots-savants. The findings interpreted as indicating that a representational system of musical rules and structures is accessible to persons of low general intelligence, and that such a system may underlie reproductive as well as generative musical capacity.

Adolescent↗

Consistent integration of non-reliable heterogeneous information resources applied to the annotation of transmembrane proteins.

Information agents integrate multiple distributed heterogeneous information sources. The challenging yet unsolved problem that remains, is to ensure the semantic consistency of the integrated data. In this paper we set out to develop a general approach to inconsistency management for information agents. It is implemented as part of the EDITtoTrEMBL system and applied on a large real-world problem in the domain of bioinformatics.

Amino Acid Sequence↗

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↗

Low-cost, high reliability voice control unit (VCU).

A dedicated microcomputer system has been developed to provide voice control over a wide variety of motorized devices. Employing a 8051 microprocessor with 16 kilobytes of ROM and 16 kilobytes of non-volatile RAM, the system potentially realizes an OEM cost of under $100. Other features include: a simplified user interface, a failsafe stop and voice programmable capabilities. This system has the potential to bring voice control into the marketplace in a wide variety of applications. Currently, the system has been adapted to surgical microscopes and is used in controlling several types of hospital beds.

Algorithms↗

Induction of medical expert system rules based on rough sets and resampling methods.

Automated knowledge acquisition is an important research issue in improving the efficiency of medical expert systems. Rules for medical expert systems consists of two parts: one is a proposition part, which represent a if-then rule, and the other is probabilistic measures, which represents reliability of that rule. Therefore, acquisition of both knowledge is very important for application of machine learning methods to medical domains. Extending concepts of rough set theory to probabilistic domain, we introduce a new approach to knowledge acquisition, which induces probabilistic rules based on rough set theory (PRIMEROSE) and develop a program that extracts rules for an expert system from clinical database, using this method. The results show that the derived rules almost correspond to those of medical experts.

Artificial Intelligence↗

On the soundness and safety of expert systems.

The problems of developing sound and safe expert systems are discussed, with particular reference to medicine. The concepts, notations, methods, results and technologies which have emerged from the study of mathematical logic as a computational paradigm offer many benefits for improving the quality of expert systems. Logic programming offers a better discipline for design, specification and implementation than ad hoc development methodologies. When logic programming is combined with software engineering methods, such as a software development life-cycle, the probability of routinely developing large-scale yet efficient and sound applications will be increased. However, although soundness is a necessary property of any technology it is not sufficient for assuring safety. Established methods for improved software safety are discussed, and a number of approaches to improving the safety of medical expert systems is identified. The possibility of introducing an appropriately extended life-cycle, and the potential benefits of a formal theory of safety are discussed.

Artificial Intelligence↗

Application of the SCADA system in wastewater treatment plants.

The implementation of the SCADA system has a positive impact on the operations, maintenance, process improvement and savings for the City of Houston's Wastewater Operations branch. This paper will discuss the system's evolvement, the external/internal architecture, and the human-machine-interface graphical design. Finally, it will demonstrate the system's successes in monitoring the City's sewage and sludge collection/distribution systems, wet-weather facilities and wastewater treatment plants, complying with the USEPA requirements on the discharge, and effectively reducing the operations and maintenance costs.

Artificial Intelligence↗

Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring.

The real-time monitoring of human movement can provide valuable information regarding an individual's degree of functional ability and general level of activity. This paper presents the implementation of a real-time classification system for the types of human movement associated with the data acquired from a single, waist-mounted triaxial accelerometer unit. The major advance proposed by the system is to perform the vast majority of signal processing onboard the wearable unit using embedded intelligence. In this way, the system distinguishes between periods of activity and rest, recognizes the postural orientation of the wearer, detects events such as walking and falls, and provides an estimation of metabolic energy expenditure. A laboratory-based trial involving six subjects was undertaken, with results indicating an overall accuracy of 90.8% across a series of 12 tasks (283 tests) involving a variety of movements related to normal daily activities. Distinction between activity and rest was performed without error; recognition of postural orientation was carried out with 94.1% accuracy, classification of walking was achieved with less certainty (83.3% accuracy), and detection of possible falls was made with 95.6% accuracy. Results demonstrate the feasibility of implementing an accelerometry-based, real-time movement classifier using embedded intelligence.

Acceleration↗

Design aspects for novel, telemedical unattended diagnosis and therapy control systems for sleep disorders.

Medical research confirmed the relevance of diagnosis and therapy of sleep-related breathing disorders, revealing prevalence and patho-physiological mechanisms [1-10]. Reliable sleep assessment currently demands examinations in the sleep-lab, which is very technical and time-consuming. Thus, expanding the conventional procedure to meet capacity demands does not seem realistic regarding cost aspects. As a solution, the authors present telemetric system concepts for the unattended assessment of a patient's sleep profile and cardio-respiratory parameters. Taking initial experience with home polysomnography into consideration, the presented research work focuses on easily applicable sensors, the corresponding sleep profile assessment rules, wireless data recording, intelligent signal processing algorithms and telemedical information logistics to include sleep-labs in the diagnosis and treatment process as competence centers.

Algorithms↗

Overcoming deficiencies of the rule-based medical expert system.

One of the current deficiencies of the rule-based expert system is its static nature. As these systems are applied to medicine, this shortcoming becomes accentuated by: the rapid speed at which new knowledge is generated, the regional differences associated with the expression of many diseases, and the rate at which patient demographics and disease incidence change over time. This research presents a solution to the static nature of the rule-based expert system by proposing a hybrid system. This system consists of an expert system and a statistical analysis system linked to a patient database. The additional feature of a rule base manager which initiates automatic database analysis to refresh the statistical correlation of each rule ensures a dynamic, current, statistically accurate rule base. The philosophical differences between data and knowledge are also addressed as they apply to this type of hybrid system. The system is then used to generate four rule bases from different knowledge sources. These rule bases are then compared.

Artificial Intelligence↗

An integrated approach for a knowledge-based clinical workstation: architecture and experience.

Today, the demand for medical decision support to improve the quality of patient care and to reduce costs in health services is generally recognized. Nevertheless, decision support is not yet established in daily routine within hospital information systems which often show a heterogeneous architecture but offer possibilities of interoperability. Currently, the integration of decision support functions into clinical workstations is the most promising way. Therefore, we first discuss aspects of integrating decision support into clinical workstations including clinical needs, integration of database and knowledge base, knowledge sharing and reuse and the role of standardized terminology. In addition, we draw up functional requirements to support the physician dealing with patient care, medical research and administrative tasks. As a consequence, we propose a general architecture of an integrated knowledge-based clinical workstation. Based on an example application we discuss our experiences concerning clinical applicability and relevance. We show that, although our approach promotes the integration of decision support into hospital information systems, the success of decision support depends above all on an adequate transformation of clinical needs.

Artificial Intelligence↗

EICO-1: an orthodontist-maintained expert system in clinical orthodontics.

Expert systems are increasingly being used to provide comprehensive interpretative services for diagnosis and treatment planning. Some of these systems are constrained by the complexities of rule-based strategies and a need for knowledge engineers throughout the maintenance phase. A new approach to knowledge acquisition known as Ripple-Down-Rules was used in the development of EICO-1 (Expert Interpretation in Clinical Orthodontics). This expert-maintained system for automating orthodontic reports has a knowledge base of six hundred and eighty rules, and is maintained by an expert trained only in Orthodontics and without the help of knowledge engineers. EICO-1 is the first expert system in Dentistry to use Ripple-Down-Rules. It has potential as an interactive advisory tool and is applicable in a clinical situation.

Artificial Intelligence↗

Neural [correction of Neutral] networks for control, identification and diagnosis.

Advances in the theory and technology of artificial neural networks provide the potential for new approaches to the problems of control, identification, and diagnosis for large, complex systems. However, these approaches must be validated for specific applications before they can be exploited effectively. Because of the unique capabilities they offer, neural networks should play an important role in space exploration systems operations. After a brief introduction to neural networks is presented, some applications of neural networks to identification and control of space systems are described and discussed. They span the spectrum of relatively straightforward to rather complex applications. An explanation of how neural networks can be applied to such important tasks as fault diagnosis and accommodation is presented. Neural networks are shown to be part of the hierarchy of intelligent control where a higher order decision element monitors and supervises lower order elements for sensing and actuation.

Algorithms↗

From semi-conductors to the rhythms of sensitive plants: the research of J.C. Bose.

J.C. Bose (1858-1937) was one of the world's first biophysicists. He was the first person to use a semi conducting crystal to detect radio waves, and the ingenious inventor of a portable apparatus for generating and detecting microwaves (approximately 1 cm to 5 mm radio waves, frequency 12-60 GHz), as well as inventing many instruments now routinely used in microwave technology. Bose extended his specialist knowledge of the physics of electromagnetic radiation into insightful experiments on the life-processes of plants. He became a controversial figure in the west. He invented unique, delicate instruments for simultaneously measuring bioelectric potentials and for quantifying very small movements in plants. He worked with touch-sensitive plants, including Mimosa pudica, with plants that perform spontaneous movements, including the Indian telegraph plant Desmodium, and with plants and trees that did not make obvious rapid movements. Bose concluded that plants and animals have essentially the same fundamental physiological mechanisms. All plants co-ordinate their movements and responses to the environment through electrical signalling. All plants are sensitive explorers of their world, responding to it through a fundamental, pulsatile, motif involving coupled oscillations in electric potential, turgor pressure, contractility, and growth. His overall conclusion that plants have an electromechanical pulse, a nervous system, a form of intelligence, and are capable of remembering and learning, was not well received in its time. A hundred years later, concepts of plant intelligence, learning, and long-distance electrical signalling in plants have entered the mainstream literature.

Biomechanical Phenomena↗

Multirobot systems: a classification focused on coordination.

Multirobot systems (MRS) are, nowadays, an important research area within robotics and artificial intelligence and a growing number of systems have recently been presented in the literature. Since application domains and tasks that are faced by MRS are of increasing complexity, the ability of the robots to cooperate can be regarded as a fundamental feature. In this paper, we present a survey of the recent work in the area by specifically examining the forms of cooperation and coordination realized in the MRS. In particular, we propose a new taxonomy for classification of the approaches to coordination in MRS and we describe some systems, which we consider representative in our taxonomy. We finally discuss the outcomes of our analysis and try to highlight future trends of the research on MRS.

Algorithms↗