We investigate the relation between codimension two smooth complete intersections in a projective space and some naturally associated graded algebras. We give some examples of log-concave polynomials and we propose two conjectures for these algebras.
We construct gradient-orthonormal bases of momentum-entire wavelets in dimension n in the case where n is odd. The scale factor is 3√2 and the coherence on a given scale is based on the propagator exp .This propagator can be described in terms of two one-variable functions. One of them is the Airy function, while the other satisfies an ordinary differential equation less familiar than the Airy equation. This construction is part of our on-going quest for compactly supported, gradient-orthonormal wavelets that have some kind of coherence on a given scale.
In this paper we present some properties for projective hypersurfaces, smooth and singular, to be criteria for identication. To make the decision with these criteria, we have included procedures written in Singular language.
Aims: To extract characters from skewed images without image rotation. Study Design: This study is designed to be implemented at the gates of Customs, Port Authorities, Terminal Operators and it can also be implemented for vehicles traffic management. Place and Duration of Study: Lebanon, between September and November 2013. Methodology: The proposed method consists of sorting the segmented characters according to the X axis, then assigning a Program Line Number to each character based on the skew angle and finally sorting the Program Line Numbers according to their intersection with the Y axis. Results: Our approach is capable of handling any font and size of characters and it is robust and efficient; regarding its complexity for an image having N lines and M characters, the worst CPU time usage and the worst memory usage is equal to O (NxM) while the network usage and disk usage for one image is O (1) which led to a 0.11 milliseconds response time to extract all container number digits. Conclusion: Acceleration of segments’ extraction from skewed images by avoiding image rotation in order to acquire a faster and more accurate OCR process.
Parameter estimation is an important part of computational systems biology – especially in studies on biological networks. Numerous stochastic search methods have been applied in parameter estimation in biological networks. In this paper, a constrained stochastic space search (CSSS) method for parameter estimation is proposed and evaluated for estimating the parameters of a genetic network described by differential equations. Both linear and nonlinear model formalisms were used for the data evaluation. The performance of the CSSS method was compared to the Integrated Controlled Random Search for Dynamic Systems (ICRS/DS) stochastic optimization algorithm. Compared to the ICRS/DS, the CSSS algorithm is faster with at least a 7-fold shorter convergence time. Independent replicates were run and identification performed. For the same initialization conditions prior to optimization, the CSSS had on average smaller relative mean errors than the ICRS/DS.
We use the SIR model Kermack and Mckendrickand for hepatitis B with vaccination. The main goal is to use existing clinical hepatitis B data from the biostatistics Department of the Tano North District Health Directorate to formulate a mathematical model to understand the dynamics in the Tano North District and assist decision makers to formulate the best ideas to prevent, control and eradicate the disease. Analyses is made of the existence and stability of the disease free and endemic equilibria. It is proven that the disease free equilibrium is locally asymptotically stable if the basic reproductive ratio, R0< 1 and when R0 > 1 we have the endemic equilibrium. MATLAB was used for the programming and simulations.
Aims: This paper presents a design for a custom Application-Specific-Integrated-Circuit (ASIC) VLSI continuous time recurrent neural network computer suitable for use in Evolvable Hardware (EH) applications. Study Design: Extensive testing of a fabricated device will be used to demonstrate that the designed and fabricated neural chip possesses excellent behavioral congruence to the differential equation and ASIC hardware forms of neural networks programmed into the chip. Place and Duration of Study: Department of Computer Science and Engineering, Wright State University, between 2009 and 2012. Methodology: The presented ASIC neural chip has been designed with specific concentration on the CMOS sub-threshold design concepts. This CMOS sub-threshold design forms the basis for underlying neural computation and also the current-mode Digital-to-Analog Converter (DAC) that can be used to program neuron configurations. The proposed designed has been developed to be immune to any faults introduced thru fabrication, at least to the extent that is non-detrimental to underlying neural behavior. Results: Ten separate intrinsic CTRNN learning runs were conducted on the fabricated chips. Each test was conducted on a separate fabricated chip to assess intrinsic to extrinsic transferability across individual instantiations of the device. Further, as mentioned earlier, a secondary set of tests were conducted that involved performing intrinsic match analysis for 15 (separate) extrinsically learnt CTRNN configurations to test extrinsic to intrinsic transferability. Based on the comparison metrics computed between the simulated and the fabricated chip, it has been demonstrated that the observed worst case average mismatch across all computed outputs of the four neuron CTRNNs is about seven percent on amplitude with near perfect matching for slope and frequency. Conclusion: Extensive testing of a fabricated device has been used to demonstrate that the analog computer possesses excellent behavioral congruence to the differential equation and ASIC hardware forms of neural networks are programmed into the chip. The major advantage of choosing the proposed CTRNNs chip for EH applications is that one can easily transition between model and circuit form no matter how the circuit was evolved. In this paper, we demonstrated quite clearly that the barrier is either non-existent or very slight by having designed, fabricated, and tested an actual VLSI chip in the application that one would expect to be most difficult -- evolution in hardware and modeling in differential equation form.
A numerical computer model based on the dual reciprocity boundary element method (DRBEM) is extended to study the generalized thermo elastic responses of functionally graded anisotropic rotating plates. In the case of plane deformation, a predictor-corrector implicit-explicit time integration algorithm was developed and implemented for use with the DRBEM to obtain the solution for the displacement and temperature fields in the context of the Green and Lindsay theory. Numerical results that demonstrate the validity of the proposed method are also presented in the tables.