A semi-partitioning technique is presented for efficient scheduling of sporadic task systems on multiprocessors. The presented technique performs in the same manner as the traditional partitioning, as long as tasks are successfully partitioned, but a task is allowed to be shared among multiple processors for its execution, if a spare capacity of every individual processor is not enough to accep...

In this paper, we present an on-line semi-supervised algorithm for real-time separation of speech and background noise. The proposed system is based on Nonnegative Matrix Factorization (NMF), where fixed speech bases are learned from training data whereas the noise components are estimated in real-time on the recent past. Experiments with spontaneous conversational speech and real-life nonstati...

In order to improve the detection of malicious tampering of images, it is necessary to decrease the fragility of hidden watermarks, even for digital images which have been distorted incidentally. In this paper, we propose a new semi-fragile digital watermarking technique based on eigenvalues and eigenvectors of real symmetric matrix generated by the pair of four pixels. A signature bit for dete...

In this work, the design of a low-cost, field programmable gate array (FPGA)-based digital hardware platform that implements image processing algorithms for real-time distance measurement is presented. Using embedded development kit (EDK) tools from Xilinx, the system is developed on a spartan3 / xc3s400, one of the common and low cost field programmable gate arrays from the Xilinx Spartan fami...

This research proposed a pedestrian detection system in an outdoor scene by a pin-hole camera with field-programmable gate array. We used two different feature descriptors included histograms of oriented gradients and local weighted pattern which were descripted the shape and textural information for the image feature of pedestrians. Semi-supervised learning with linear support vector machine w...

We address two critical issues involved in applying semi-supervised learning (SSL) to a real-world task: parameter tuning and choosing which (if any) SSL algorithm is best suited for the task at hand. To gain a better understanding of these issues, we carry out a medium-scale empirical study comparing supervised learning (SL) to two popular SSL algorithms on eight natural language processing ta...

In order to improve the detection of malicious tampering images, it is necessary to decrease the fragility of hidden watermarks, even for digital images which have been incidentally distorted. In this paper, we propose a new invariant semi-fragile digital watermarking technique based on eigenvalues and eigenvectors of real symmetric matrix generated by the four pixel pairs. A signature bit for ...

Most real-time multiprocessor scheduling algorithms for achieving optimal processor utilization, adhere to the fairness rule. Accordingly, tasks are executed in proportion to their utilizations at each time quantum or at the end of each time slice in a fluid schedule model. Obeying the fairness rule results in a large number of scheduling overheads, which affect the practicality of the algorith...

In this preliminary work, left and right conjugate direction vectors are defined for nonsymmetric, nonsingular matrices A and some properties of these vectors are studied. A left conjugate direction (LCD) method for solving general systems of ∗The work of the first author was partially supported by CNPq, CAPES, Fundação Araucária, Brazil. The work of the second author was partially supported by...

We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the points by minimizing a certain energy function, which corresponds to a minimal k-way cut solution. In contrast to these methods, we estimate the distribution of classifications, instead of the sole minimal k-way cut, which ...