The 10th IEEE International Symposium on Signal Processing and Information Technology

Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

As more flexible and self-adaptive network connections are expected between cloud users and service vendors, the requests for more sophisticated bandwidth scheduling schemes are emerging. In this paper, we conduct a thorough study on the a specific type of bandwidth reservation: First-Slot scheduling in this scenario. We introduce a model for the optical networks with sparse wavelength conversion,... View full abstract»

Computer networks are the core of the cyberinfrastucture and are endangered by malicious activities and natural disasters. These threats stress the need for a resilient computer networks to ensure business operational continuity and optimum performance. Several aspects affect computer network resilience level such as network topology, routing protocols, and others. This paper demonstrates Redundan... View full abstract»

This paper address the problem of static task clustering and scheduling of a parallel program given as a Directed Acyclic Graph(DAG) with duplication. Scheduling of task graphs onto multiprocessors is known to be an NP-complete in most cases leading to solutions based on heuristics. In this paper, a novel task-duplication scheduling heuristic is presented. Our approach differs from other heuristic... View full abstract»

What we know is less important than our capacity to continue to learn more until e-learning appeared. While e-learning technology has matured considerably since its inception, there are still many problems that practitioners find when come to implementing e-learning. Today's knowledge society of the 21st century requires a flexible learning environment which is capable to adapt according to teachi... View full abstract»

This paper deals with how to adapt the context architecture defined in [1] to a context-aware application called Simulated Context-Aware Meeting Room Application (SCAMRA). The main goal is to test and experiment the CFM and the proposed architecture done in [1]. SCAMRA can be used to manage any holding meeting on offices, universities, organizations or any other location by managing sessions, atte... View full abstract»

Theoretical analyses on generalization error of a model space for kernel regressors with respect to training samples are given in this paper. In general, the distance between an unknown true function and a model space tends to be small with a larger set of training samples. However, it is not clarified that a larger set of training samples achieves a smaller difference at each point of the unknown... View full abstract»

Song and music discrimination play a significant role in multimedia applications such as genre classification and singer identification. Song and music discrimination play a significant role in multimedia applications such as genre classification and singer identification. The problem of identifying sections of singer voice and instrument signals is addressed in this paper. It must therefore be ab... View full abstract»

This paper presents an optical watermarking technique that is robust against geometrical distortion in images by using spatially modulated illumination. It can protect “analog” objects like pictures painted by artists from having photographs taken of them illegally in museums. Illegally captured images in practical situations may contain various distortions, and embedded watermarks m... View full abstract»

Shoulder-surfing, phishing and keylogging are widely used by attackers to obtain users' sensitive credentials. In this paper, we propose a framework to strengthen password authentication using mobile devices and browser extensions. This approach provides a relatively high resilience against shoulder-surfing, phishing and keylogging attacks while requires no change on the server side. A prototype i... View full abstract»

Temporal invariant shape moments intuitively seem to provide an important visual cue to human activity recognition in video sequences. In this paper, an SVM based method for human activity recognition is introduced. With this method, the feature extraction is carried out based on a small number of computationally-cheap invariant shape moments. When tested on the popular KTH action dataset, the obt... View full abstract»

One of the challenging problems in Networks-on-Chip (NoC) design is optimizing the architectural structure of the on-chip network in order to maximize the network performance while minimizing corresponding costs. In this paper, a methodology for multi-objective optimization of NoC standard architectures using Genetic Algorithms is presented. The methodology considers two cost metrics, power and ar... View full abstract»

Filter-based fading channel simulators universally use White Gaussian Noise (WGN) to generate complex tap coefficients. In this work, we will show that replacing WGN source by Uniform Random Number Generator (URNG) results in improved simulation speed in case of software simulator; and reduced area/power in case of hardware simulator. We will verify, both analytically and through extensive simulat... View full abstract»

A novel approach for an efficient extraction of rectangular boundaries from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is utilized for connecting low-level linear structures or grouping similar objects. The proposed an approach, called hierarchical clustering method, utilizes the fact that rooftops of a building are... View full abstract»

A classification scheme for content-based audio signal retrieval is proposed in this paper. The proposed scheme uses the Centroid Neural Networks (CNN) with a Divergence Measure called Divergence-based Centroid Neural Network (DCNN) to perform clustering of Gaussian Probability Density Function (GPDF) data. In comparison with other conventional algorithms, the DCNN designed for probability data ha... View full abstract»

Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. Inverse dynamics control is a well-known conventional motion control strategy for manipulators which ensures global asymptotic stability for fixed symmetric positive definite (proportional and derivative) gain matrices. In this paper, a superviso... View full abstract»

Recent developments of generalized forms of signal processing transforms with a large number of independent parameters, such as the Multiple Parameter Fractional Fourier Transform and the Discrete Fractional Cosine Transform, have encouraged many researchers to propose image encryption algorithms based on a single or multiple applications of these transforms. In order to claim a high level of secu... View full abstract»

With advances in intelligent technologies, e.g. ambient intelligence, context-aware, and pervasive systems, much research is now devoted to a computational paradigm that senses and perceives changes in human emotion. This paper presents a context-aware architecture for adaptive emotional sensibility analysis called CAF-ESA (a Context-Aware Framework based Emotional Sensibility Analysis) with adapt... View full abstract»