A mathematical model for transient analysis of computer systems

The study of computer system dynamic behavior is a prerequisite for the design and implementation of automatic mechanisms for performance control. An analytic technique for modelling the transient behavior of computer systems is presented and a suitable method for modelling job dynamics is given.

The system model is discussed from the viewpoint of transient analysis with particular reference to bottleneck identification and to bottleneck migration analysis.

A mathematical study is given together with a numerical algorithm. The model is validated on the basis of suitable experimental results.     

A mathematical model and computer program for adriamycin distribution and elimination

A mathematical physiological flow model is described for the distribution and elimination of adriamycin in the rat. The model includes the volume or mass of, and blood flow to the following tissues: heart, plasma, muscle, skin, kidney, bone marrow, gut, liver and bile. A compartment is also included for tight or almost irreversible binding which occurs with this drug. The program was written in FORTRAN to compute the concentration of drug in each tissue as a function of time after bolus injection or short term infusion. The computed data is printed on a line printer and recorded on disk for use in a SAS program GPLOT to obtain precision plots.     

A mathematical model and image analysis technique for calculating regional cerebral blood flow

This paper discusses the theory and implementation of a modular data analysis system for the calculation and imaging of regional cerebral blood flow. The program may be generalized to any system requiring instantaneous and controllable visual data display, and we have set it up for compartmental analysis as described by the Fick equation with certain correction factors. We have included flow charts of the program source code and data paths for the various modules. We also describe the functional hardware components necessary for the execution of these algorithms. Finally, analyzed data are represented from a set of experiments employing differential visual stimulation. The results obtained using our methods are comparable to those in the existing literature; they are more accurately and easily obtained, and have the added power of manipulable digitization of the original image without loss of data.     

A mathematical model for spirometry

A model originally designed to fit population growth data was investigated to determine whether it could fit spirometric traces as a function of time in normal and ill humans and in normal rats, obtained, respectively, by spirometer and whole-body plethysmography. The model showed great accuracy when applied to a simple spirometer coupled with an analog-to-digital converter interfaced with a personal computer. It also proved to be a good alternative for the more expensive and less accurate electronic devices, as derivative systems, and may be an attractive method for research and/or diagnostic centers.     

A mathematical model for integrated diagnostics

The authors expand on the form of the information flow model they introduced previously, (see ibid., vol.8, no.3, p.16-30 (1991)). Compiling the model requires three algorithms for determining higher-order relationships. One of these, the algorithm for computing logical closure, helps to simplify the modeling task. The authors also introduce a hypothetical antitank missile launcher to illustrate concepts and computations presented previously     

A mathematical model and a computer tool for the Tower of Hanoi and Tower of London puzzles

We propose a mathematical model for the Towers of Hanoi and London based on state graphs. The analysis of this model allows to address questions like equivalence of puzzles, difficulty of tasks and optimality of solutions using topological, metric and symmetry properties of the corresponding graphs.The mathematical model serves as a base for a computer program to administer tower puzzles in a variety of psychological test situations. It is suitable for bedside use and is equipped with numerous devices for post-processing of recorded data. Among these features is the graphical representation of the projection of the path taken by a test person onto the state graph.     

A real-time mathematical computer method for potato inspection using machine vision

Detection of external defects on potatoes is the most important technology in the realization of automatic potato sorting stations. This paper presents a hierarchical grading method applied to the potatoes. In this work a potato defect detection combining with size sorting system using the machine vision will be proposed. This work also will focus on the mathematics methods used in automation with a particular emphasis on the issues associated with designing, implementing and using classification algorithms to solve equations. In the first step, a simple size sorting based on mathematical binarization is described, and the second step is to segment the defects; to do this, color based classifiers are used. All the detection standards for this work are referenced from the United States Agriculture Department, and Canadian Food Industries. Results show that we have a high accuracy in both size sorting and classification. Experimental results show that support vector machines have very high accuracy and speed between classifiers for defect detection.     

A graphical model for audiovisual object tracking

We present a new approach to modeling and processing multimedia data. This approach is based on graphical models that combine audio and video variables. We demonstrate it by developing a new algorithm for tracking a moving object in a cluttered, noisy scene using two microphones and a camera. Our model uses unobserved variables to describe the data in terms of the process that generates them. It is therefore able to capture and exploit the statistical structure of the audio and video data separately, as well as their mutual dependencies. Model parameters are learned from data via an EM algorithm, and automatic calibration is performed as part of this procedure. Tracking is done by Bayesian inference of the object location from data. We demonstrate successful performance on multimedia clips captured in real world scenarios using off-the-shelf equipment.     

A local-motion-based probabilistic model for visual tracking

Color-based tracking is prone to failure in situations where visually similar targets are moving in a close proximity or occlude each other. To deal with the ambiguities in the visual information, we propose an additional color-independent visual model based on the target's local motion. This model is calculated from the optical flow induced by the target in consecutive images. By modifying a color-based particle filter to account for the target's local motion, the combined color/local-motion-based tracker is constructed. We compare the combined tracker to a purely color-based tracker on a challenging dataset from hand tracking, surveillance and sports. The experiments show that the proposed local-motion model largely resolves situations when the target is occluded by, or moves in front of, a visually similar object.     

Centroid Iteration algorithm for image tracking

A simple and elegant tracking algorithm called Centroid Iteration algorithm is proposed. It employs a new Background-Weighted similarity measure which can greatly reduce the influence from the pixels shared by the target template and background on localization. Experiments demonstrated the Background-Weighted measure performs much better than the other similarity measures like Kullback–Leibler divergence, Bhattacharyya coefficient and so on. It has been proved that this measure can compute the similarity value contribution of each pixel in the target candidate, based on which, a new target search method called Centroid Iteration is constructed. The convergence of the method has been demonstrated. Theory analysis and visual experiments both validated the new algorithm.     

A realistic lighting model for computer animators

Because of the problems inherent in modeling the physics of light transmission, all lighting models used in computer graphics are approximations. Each model provides a different balance between image realism, model complexity, and runtime efficiency. A model that balances these factors and is easier than its predecessors for inexperienced animators to use is presented     

A computer model for power system control

A forward dynamic programming formulation of the optimal commitment of units for economic power generation is proposed, and it is shown how advantage is taken of the characteristics of the formulation as well as the structure of the problem itself to impose limiting conditions which reduce the size and complexity of the solution, while still ensuring that the generating schedules determined are costefficient. By employing a number of strategies which control the multiplicity of states, the proposed method eliminates the necessity for large computer storage—a drawback in the early dynamic programming methods. Operating constraints like non-linearities in the cost characteristics of units, deterministic spinning reserve, time-dependent start-up costs are incorporated in the model and operating schedules are produced over a 24-h horizon. Computational experience with the technique indicates its potentiality for on-line computer implementation.     

A programmable systolic device for image processing based on mathematical morphology

Systolic array architectures are favourable for special purpose systems as they are simple and offer a high degree of concurrency. A programmable systolic device is designed to cater for all tasks of image processing based on mathematical morphology. The design consists of a systolic memory matrix accessible via a rotation operation by a linear systolic array of simple processing elements. The instruction set consists of 1-bit assignmments, logical and and or and shift operations on the memory. Thus extremely short clock cycles and a high degree of parallelism can be achieved.     

Fuzzy mathematical morphology for biological image segmentation

Due to the imaging devices, real-world images such as biological images may have poor contrast and be corrupted by noise, so that regions in the images present soft edges and their segmentation turns out to be quite difficult. Fuzzy mathematical morphology can be successfully applied to segment biological images having such characteristics of vagueness and imprecision. In this work we introduce an approach based on fuzzy mathematical morphology to segment images of human oocytes in order to extract the oocyte region from the entire image. The approach applies fuzzy morphological operators to detect soft edges in the oocyte images, followed by morphological reconstruction operators to isolate the oocyte region. The main concepts from fuzzy mathematical morphology are briefly introduced and the results of applying fuzzy morphological operators are reported in low-contrast images of human oocytes.