From a historical perspective, we are at a stage in science comparable to the post-Newtonian developments of physics, engineering and technology-with the key difference that now we are trying to create a solid quantit...
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From a historical perspective, we are at a stage in science comparable to the post-Newtonian developments of physics, engineering and technology-with the key difference that now we are trying to create a solid quantitative mathematical basis for biology, physiology and the study of disease. The enormous complexity of living systems means that understanding their behaviour in a quantitative mathematical way is very difficult. However, a large element of the difficulty is associated with the complexity of the dynamical properties of biologicalsystems. This means that the tools of control, feedback theory and dynamical systems analysis should be central to a systems approach to biology. It is of inestimable importance that today's generation of control systems engineers recognise this and respond, in the Spirit of Tustin, to the opportunities that it presents.
In microwave induced thermo-acoustic tomography (TAT), circular scanning sensor array is the general signal acquiring mode. For higher sensitivity, large aperture detectors are widely preferred in the real TAT imaging...
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In microwave induced thermo-acoustic tomography (TAT), circular scanning sensor array is the general signal acquiring mode. For higher sensitivity, large aperture detectors are widely preferred in the real TAT imaging system. However, large aperture of detector usually results in the limited spatial sampling points. Meanwhile, for considering the safety and comfort, the microwave radiation power is also limited. Due to these limitations, the signal to noise ratio (SNR) of TA signals may not be ideal to reconstruct an image with satisfactory quality. In addition, the TA image often suffers the artifacts resulted by sparsely sampling data. Herein, we propose a deep learning-based scheme to process the TA images which are reconstructed with time reversal (TR) method. Since the obvious artifacts removing performance in photoacoustic tomography (PAT), fully dense U-Net (FD U-Net) is employed to be the base deep learning architecture. Due to the amount limitation of real experimental TA data, the network is mainly trained by synthetic data which are generated in TAT simulating scheme. Furthermore, in order to ensuring the trained network could correctly detect the targets in the TA image, we propose a scheme termed data augmentation FD U-Net (DAFD U-Net) in which a few experimental TA images are added to the training procedure and perform data *** performance of DAFD U-Net is verified by an experimental image. Results show that the proposed scheme could significantly improve the quality of TAT image.
Recently, attention has been focused on the class of bilinear systems, both for its applicative interest and intrinsic simplicity. In fact, it appears that many important processes, not only in engineering, but also i...
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Recently, attention has been focused on the class of bilinear systems, both for its applicative interest and intrinsic simplicity. In fact, it appears that many important processes, not only in engineering, but also in biology, socio-economics, and ecology, may be modeled by bilinear systems. Moreover, since their nonlinearity is due to products between input and state variables, this class frequently may be studied by techniques similar to those employed for linear systems. This work is intended to motivate the interest of bilinear systems and to present the current state of research in its various aspects. After an introductory section, in which theoretical and applicative aspects of bilinear systems are enlightened, four other sections follow, respectively, devoted to structural properties, mathematical models, identification and optimization. In a final section, some concluding remarks are made on still open problems and possible trends for future research.
Sonar echo analysis that is not affected by relative motion between target, transmitter, and receiver is discussed. Motion-tolerant measurement and recognition of range-distributed targets involves: 1) a determination...
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Sonar echo analysis that is not affected by relative motion between target, transmitter, and receiver is discussed. Motion-tolerant measurement and recognition of range-distributed targets involves: 1) a determination of the effects of range rate upon echoes from non-planar reflectors and 2) the derivation of a signal, filter bank, and target parameterization scheme that is insensitive to those effects. The appropriate system is derived, simulated with a computer, and tested with actual echoes from various targets. The system's signals and filters are very similar to those found in biological sonars.
This paper presents dipole modeling techniques which are useful for calculations of far-fields from vertically-or horizontally-polarized electromagnetic pulse (EMP) simulators. Vertically-polarized simulators are mode...
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This paper presents dipole modeling techniques which are useful for calculations of far-fields from vertically-or horizontally-polarized electromagnetic pulse (EMP) simulators. Vertically-polarized simulators are modeled with a single dipole above a finitely conducting half-space. Three dipoles were used in the case of a horizontally-polarized simulator. Effects of soil models with both frequency-dependent and frequency-independent values for soil conductivity and dielectric constant are included in the study. Calculations with dipole models compare reasonably well with measurements conducted at the AESOP facility and finite-difference calculations of free fields near the VEMPS II simulator. Integrals of the Poynting vector are used to obtain an upper limit for whole body specific absorption in a prolate spheroidal human model. The results suggest that EMP simulator thermal effects at the cellular level are small in comparison to random thermal agitation.
Block models of man which consist of a limited number of cubical cells are commonly used to predict the internal electromagnetic (EM) fields and specific absorption rate (SAR) distributions inside the human body. Nume...
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Block models of man which consist of a limited number of cubical cells are commonly used to predict the internal electromagnetic (EM) fields and specific absorption rate (SAR) distributions inside the human body. Numerical results, for these models, are obtained based on moment-method solutions of the electric-field integral equation (EFIE) with a pulse function being used as the basis for expanding the unknown internal field. In this paper, we first examine the adequacy of the moment-method procedure, with pulse basis functions, to determine SAR distributions in homogeneous models. Calculated results for the SAR distributions in some block models are presented, and the stability of the solutions is discussed. It is shown that, while the moment-method, using pulse basis functions, gives good values for whole-body average SAR, the convergence of the solutions for SAR distributions is questionable. A new technique for improving the spatial resolution of SAR distribution calculations using a different EFIE and Galerkin's method with linear basis functions and polyhedral mathematical cells is also described.
Temporal gradient estimation is a pervasive phenomenon in natural biologicalsystems and holds great promise for synthetic counterparts with broad-reaching applications. Here, we advance the concept of BioSD (Biomolec...
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Temporal gradient estimation is a pervasive phenomenon in natural biologicalsystems and holds great promise for synthetic counterparts with broad-reaching applications. Here, we advance the concept of BioSD (Biomolecular Signal Differentiators) by introducing a novel biomolecular topology, termed Autocatalytic-BioSD or AC-BioSD. Its structure allows for insensitivity to input signal changes and high precision in terms of signal differentiation, even when operating far from nominal conditions. Concurrently, disruptive high-frequency signal components are effectively attenuated. In addition, the usefulness of our topology in biological regulation is highlighted via a PID (Proportional-Integral-Derivative) bio-control scheme with set point weighting and filtered derivative action in both the deterministic and stochastic domains.
Theoretical dosimetry, i.e., calculation of the electromagnetic (EM) energy absorbed by humans in radiation fields, has become increasingly important as the use of EM devices in our society has increased. Since such c...
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Theoretical dosimetry, i.e., calculation of the electromagnetic (EM) energy absorbed by humans in radiation fields, has become increasingly important as the use of EM devices in our society has increased. Since such calculations are difficult and complicated, a number of EM analysis techniques have been used by researchers in the field to obtain dosimetric data and understanding of absorption characteristics. Both analytical and numerical EM techniques have been applied extensively. In this paper, important techniques are reviewed and significant dosimetric data are summarized. Some important areas of future research in EM dosimetry are discussed.
A new type of visual feature extracting network has been synthesized, and the response of the network has been simulated on a digital computer. This research has been done as a first step towards the realization of a ...
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A new type of visual feature extracting network has been synthesized, and the response of the network has been simulated on a digital computer. This research has been done as a first step towards the realization of a recognizer of handwritten characters. The design of the network was suggested by biologicalsystems, especially, the visual systems of cat and monkey. The network is composed of analog threshold elements connected in layers. Each analog threshold element receives inputs from a large number of elements in the neighbouring layers and performs its own special functions. It takes care of one restricted part of the photoreceptor layer, on which an input pattem is presented, and it responds to one particular feature of the input pattem, such as brightness contrast, a dot in the pattern, a line segment of a particular orientation, or an end of the line. This means that the network performs parallel processing of the information. With the propagation of the information through the layered network, the input pattern is successively decomposed into dots, groups of line segments of the same orientation, and the ends of these line segments.
A statistical screening test has been developed for processing washout data to choose the best model for these data. A choice is made between a linear single-compartment model and nonlinear multi-compartment model. Th...
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A statistical screening test has been developed for processing washout data to choose the best model for these data. A choice is made between a linear single-compartment model and nonlinear multi-compartment model. The screen is expressed as a test of a null hypothesis Ho, using a likelihood ratio test.
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