Terahertz (T-rays) spectroscopy has recently emerged as a powerful method to access a heretofore barely explored region of the electromagnetic spectrum where fundamental molecular resonances occur. Besides their importance for fundamental research, these resonances could be used as signatures in the identification of molecular species and as sensitive probes in a wide variety of molecular processes.
In this paper we consider the potential of THz spectroscopy in the application to relevant biomedical and homeland security problems such as the analysis of normal and diseased tissues and the detection of toxic biomolecules.
As examples, we present preliminary experimental data which suggest that THz spectroscopy: 1) can discriminate between cancerous and normal tissue, and 2) can reveal the presence of foreign substances hidden in an envelope and even allow their specific identification. This capability is of particular relevance as a straightforward homeland security tool for the detection of anthrax and other biotoxic molecules.
We discuss the role of evolutionary adaptive algorithms in shaping femtosecond pulses with an eye toward their use in the quantum control of optical properties. In particular, we report preliminary results from an ongoing attempt to implement the recently proposed FAST CARS technique for the detection and identification of bacterial spores. In the initail phase of this project, we are studying the CARS signal from a deuterated water (D2O) solution of Dipicolinic Acid (DPA), which is an important constituent of the spores. enhancement of the CARS intensity associated with the DPA vibrational resonance at ~ 3000cm-1. This effect is weak, but significant. It is premature to ascribe it to any particular mechanism, but its detection encourages its optimization by searching the space of all possible pulse shapes via an evolutionary feedback
algorithm.
Optical techniques are very promising for detecting and identifying bacterial spores. They are potentially superior to the existing “wet chemistry” approaches regarding several important features of an effective alarm system, such as speed, in-field use, continuous monitoring, and reliability. In this paper we discuss the role that computational intelligence (CI) can play in the control and optimization of optical experiments, and in the analysis and interpretation of the large amount of data they provide. After a brief discussion of the use of CI in the classification of optical spectra, we introduce the recently proposed FAST CARS (Femtosecond Adaptive Spectroscopic Techniques for Coherent Anti-Stokes Raman Scattering) technique. Here the role of CI is essential: using an adaptive feedback approach based on genetic algorithms, the hardware system evolves and organizes itself to optimize the intensity of the CARS signal.
We discuss a successful application of evolutionary algorithms and femtosecond pulse-shaping technology to the coherent control of quantum phenomena. After a brief review of the field of quantum control, we show how evolutionary algorithms provide an effective and, so far, the only general solution to the problem of managing the complex interplay of interference effects which characterize quantum phenomena. A representative list of experimental results is presented, and some directions for future developments are discussed. The success of evolutionary algorithms in quantum control is seen as a significant step in the evolution of computational intelligence, from evolutionary algorithms, to evolutionary programming, to evolutionary engineering, whereby a hardware system organizes itself and evolves on line to achieve a desired result.
The methodologies of soft computing (fuzzy logic, neural networks, evolutionary computation, etc.), represent a new computational paradigm which may usefully complement the conventional digital computing approaches in the application to real life problems. This paper considers the potential role of soft computing (SC) in electronic product engineering. The problem is first treated on general grounds, using electronic design as example. Then a more specific discussion is presented, concerning the use of SC methodologies (fuzzy logic and neural nets) in a representative problem of testing, the analysis and interpretation of infrared thermal maps.
KEYWORDS: Reliability, Very large scale integration, Manufacturing, Fuzzy logic, Microelectronics, Process control, Control systems, Design for manufacturability, Semiconductors, Tolerancing
This paper discusses the application of fuzzy logic to quality and reliability issues in microelectronics. After a general introduction, the potential role of fuzzy logic is reviewed at various stages of the production process: testing, process control, and design for reliability and quality.
This paper discusses the potential of fuzzy logic for manufacturing science. After a general introduction of manufacturing science as a complex systems to which Zadeh's Incompatibitlity Principle applies, the paper presents a bird's eye view of fuzzy logic applications to operational and engineering aspects of manufacturing science, and, in particular, to reliability studies.
This paper presents a discussion of the potential of Fuzzy Logic Technology (FLT) for the IVHS (Intelligent Vehicle/Highway System) program. After a review of the IVHS program, some relevant roles of FLT are highlighted and illustrated with examples from recent works on the subject.
We review and discuss the papers presented at the Conference on Fuzzy and Neural Systems, and Vehicle Applications '91 (Intelligent Vehicles '91). This conference, organized by IEEE/IES Intelligent Vehicle Subcommittee, in collaboration with the Japanese Society for Fuzzy Theory and Systems and other related societies, was held in Tokyo, Japan, in November 1991.
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