Leonid Reznik

Soft computing in measurement and information acquisition

Uncertainty in Measurement: Some Thoughts about its Expressing and Processing.- Why Two Sigma? A Theoretical Justification for an Empirical Measurement Practice.- Fuzzy Linguistic Scales: Definition, Properties and Applications.- A Fuzzy Shape Specification System to Support Design for Aesthetics.- Generating Membership Functions for a Noise Annoyance Model from Experimental Data.- An Exegesis of Data Fusion.- Possibilistic Logic: A Theoretical Framework for Multiple Source Information Fusion.- Automated Adaptive Situation Assessment.- Soft Computing, Real-time Measurement and Information Processing in a Modern Brewery.- The Aggregation of Industrial Performance Information by the Choquet Fuzzy Integral.- Computing Image with an Analog Circuit Inspired by the Outer Retinal Network.- Extending the Decision Accuracy of a Bioinformatics System.- On Fuzzy Controllers Having Radial Basis Transfer Functions.- Evolutionary Scene Recognition and Simultaneous Position/Orientation Detection.- Evolutionary Dynamics Identification of Multi-Link Manipulators Using Runge - Kutta - Gill RBF Networks.- Towards Reliable Sub-Division of Geological Areas: Interval Approach.- A Fuzzy Classifier with Pyramidal Membership Functions.- A Comparison of Soft Computing and Traditional Approaches for Risk Classification and Claim Cost Prediction in the Automobile Insurance Industry.- Evolutionary Rule Generation and its Application to Credit Scoring.- Social Fuzziology in Action: Acquisition and Making Sense of Social Information.

Secure communication and signal processing in inertial navigation systems

This paper focuses on secure communication, data-analytic signal processing and robust algorithms for inertial navigation systems (INSs). Middleware, software, data processing and algorithms are studied. We examine and report high-impact technology developments as applied to current and next generations of INSs. We research advanced microelectronic, processing and software solutions. New architectures, algorithms and protocols for robustly reconfigurable networked inertial systems are studied. Examining advanced-technology inertial measurement units with application-specific integrated circuits, long-standing problems are solved. The INSs impediments are minimized by using intelligent processing schemes, consistent algorithms and software. Precision, accuracy, resolution, stability, bandwidth and dynamic range are improved by attenuating noise, reducing static error and minimizing dynamic error. We present results on secure communication for transmitting mission critical data over heterogeneous networks.

Fuzzy Prediction Models in Measurement

The paper investigates the feasibility of fuzzy models application in measurement procedures. It considers the problem of measurement information fusion from different sources, when one of the sources provides predictions regarding approximate values of the measured variables or their combinations. Typically, this information is given by an expert but may be mined from available data also. This information is formalized as fuzzy prediction models and is used in combination with the measurement results to improve the measurement accuracy. The properties of the modified estimates are studied in comparison with the conventional ones. The conditions when fuzzy models application can achieve a significant accuracy gain are derived, the gain value is evaluated, and the recommendations on fuzzy prediction model production and formalization in practical applications are given.

Fuzzy Intervals Application for Software Metrological Certification in Measurement and Information Systems

This paper analyzes the advantages and disadvantages of two types of self-validating software that may run on into measurements devices: programs, which realize interval computations, and programs, which process inaccurate initial data that are expressed in terms of fuzzy intervals. The proposed analysis is presented from the viewpoint of metrology requirements. It is demonstrated that expressing measurement uncertainties in the form of fuzzy intervals results in the software that is better suited for its application in measurement systems.

Estimates and measures of data communication and processing in nanoscaled classical and quantum physical systems

This paper studies fundamentals of classical, classical-quantum and quantum information technologies to advance sensing, data acquisition and computing. The overall goal is to define, analyze and evaluate classical and quantum-mechanical information measures pertained to data processing by low-power nanoelectronic devices, nanoICs, nano-waveguides, CMOS nanophotonics, etc. Electronic, optoelectronic and photonic systems operate on the electron- and photon-induced transductions. There are fundamental differences in physics, arithmetics, device- and system-level solutions as electrostatic and quantum phenomena are utilized. This paper analyzes multi-physics quantum↔classical processing. We enable a knowledge base in cognizant areas across computer science and engineering. Our findings enable existing and future communication, sensing, information fusion, computing and processing platforms. Consistent tools and practical schemes facilitate developments of novel engineering solutions, technical readiness, technological capabilities and commercialization capacities.

Improving Measurement Accuracy in Sensor Networks by an Object Model Generation and Application

The paper describes a novel method of calculating measurement results in sensor networks, which includes modifying the conventional measurement estimates based on the object under measurement model mined from the data collected by the sensor network itself previously and other information made available by domain experts. It is shown that the model application might produce a significant gain in measurement accuracy if the model is correct. The gain value is estimated and its dependence on various factors is studied by computer simulation and experimentation with real sensor networks built from Crossbow Telos ver. B motes. The conditions of achieving the gain versus suffering the loss are derived and the recommendations of how to shape the object model in order to achieve and maximize the gain value are provided.