In this paper, we introduce the class of k-partite episodes, which are time-series patterns of the form 〈A1, . . . , Ak〉 for sets Ai (1 ≤ i ≤ k) of events meaning that, in an input event sequence, every event of Ai is followed by every event of Ai+1 for every 1 ≤ i < k. Then, we present a backtracking algorithm Kpar and its modification Kpar2 that find all of the frequent k-partite episodes fro...

This paper proposes a modification to the traditional binary search algorithm in which it checks the presence of the input element with the middle element of the given set of elements at each iteration. Modified binary search algorithm optimizes the worst case of the binary search algorithm by comparing the input element with the first & last element of the data set along with the middle elemen...

We propose a computational model of neuron, called firing cell (FC), properties of which cover such phenomena as attenuation of receptors for external stimuli, delay and decay of postsynaptic potentials, modification of internal weights due to propagation of postsynaptic potentials through the dendrite, modification of properties of the analog memory for each input due to a pattern of short-tim...

This paper utilizes artificial neural networks based image processing techniques for low capacity and resource constrained devices like mobile phones for camera applications. The system is trained to develop the operating matrix, called the function matrix, by using artificial neural network theory, from a sample input and output image matrix. This is done when the system is in idle mode. After...

This paper presents a significant modification to the Random Demodulator (RD) of Tropp et al. for sub-Nyquist sampling of frequency-sparse signals. The modification, termed constrained random demodulator, involves replacing the random waveform integral to the operation of the RD with a constrained random waveform that has limits on its switching rate because fast switching waveforms may be hard...

This paper suggests a method of finding super-efficiency scores and modification of input-oriented models for sensitivity analysis of decision making units. First, by using DEA-R (ratiobased DEA) models in the input orientation, the models of superefficiency and also models of super-efficiency modification are suggested. Second, the worst-case scenarios are considered where the efficiency of th...

This paper examines the issue of handling outputs in DEA that occur at different stages in time. In some situations, the output set occur at the different period of time, meaning that the produced outputs at the first period of time impact on the production of outputs of next time . This problem setting gives rise to the phenomenon of time-staged outputs. Specifically, the two outputs occur at ...

This paper presents a new approach to fuzzy rulebased modeling of nonlinear systems from numerical data. The novelty of the approach lies in the way of input partitioning and in the syntax of the rules. This paper introduces interpretable relational antecedents that incorporate local linear interactions between the input variables into the inference process. This modification improves the appro...

A novel active feedback frequency compensation scheme is presented in this work. Based on the proposed technique, an amplifier with two main poles in its frequency bandwidth can be easily compensated by introducing a pole-zero pair in a local feedback. The proposed method is mathematically analyzed and then based on the derived formulations, a design procedure is established. The capability of ...

In the present paper, electrical energy harvesting from random vibrations of an Euler-Bernoulli nano-beam with two piezoelectric layers is investigated. The beam is composed of an aluminum layer together with two piezoelectric ceramic layers (PZT 5A) serving as energy harvesting sensors. In the proposed method, the equations governing the bimorph nano-beam will be analytically derived using cla...