A scalable hybrid decision system (HDS) for Roman word recognition using ANN SVM: study case on Malay word recognition

An off-line handwriting recognition (OFHR) system is a computerized system that is capable of intelligently converting human handwritten data extracted from scanned paper documents into an equivalent text format. This paper studies a proposed OFHR for Malaysian bank cheques written in the Malay language. The proposed system comprised of three components, namely a character recognition system (CRS), a hybrid decision system and lexical word classification system. Two types of feature extraction techniques have been used in the system, namely statistical and geometrical. Experiments show that the statistical feature is reliable, accessible and offers results that are more accurate. The CRS in this system was implemented using two individual classifiers, namely an adaptive multilayer feed-forward back-propagation neural network and support vector machine. The results of this study are very promising and could generalize to the entire Malay lexical dictionary in future work toward scaled-up applications.     

A secure image encryption scheme based on chaotic maps and affine transformation

Due to the interesting nonlinear dynamic properties of chaotic maps, recently chaos-based encryption algorithms have gained much attention in cryptographic communities. However, many encryption schemes do not fulfil the minimum key space requirement, which is an essential concern in many secure data applications. In this paper, an efficient chaos-based image encryption scheme with higher key space is presented. Even with a single round of encryption, a significantly larger key space can be achieved. The proposed scheme removes correlation among image pixels via random chaotic sequences, simply by XOR and addition operations. In order to resist against numerous attacks, we apply the affine transformation to get the final ciphertext image. The security of the proposed scheme is proved through histogram, contrast, PSNR, entropy, correlation, key space, key sensitivity and differential attack analysis. Many significant properties of chaotic maps, sensitivity to initial condition and control parameters, structure and attack complexity, make the anticipated scheme very reliable, practical and robust in various secure communication applications.     

A cross-layer approach for partition detection at overlay layer for structured P2P in MANETs

Due to limited radio range and mobility of nodes in mobile ad hoc networks (MANETs), the network partitioning and merging could occur frequently. When structured peer-to-peer (P2P) overlays are running over MANETs, then network partition in the physical network can also cause network partition at the overlay layer. Existing approaches for structured P2P overlay over MANETs do not detect network partition at the overlay layer. This paper proposes a cross-layer approach to detect network partition at the overlay layer for structured P2P overlay over MANETs. Simulation results show that the proposed approach is highly effective and efficient in terms of routing overhead, success ratio and false-negative ratio.     

FPGA-based IP cores implementation for face recognition using dynamic partial reconfiguration

This paper presents a combination of novel feature vectors construction approach for face recognition using discrete wavelet transform (DWT) and field programmable gate array (FPGA)-based intellectual property (IP) core implementation of transform block in face recognition systems. Initially, four experiments have been conducted including the DWT feature selection and filter choice, features optimisation by coefficient selections and feature threshold. To examine the most suitable method of feature extraction, different wavelet quadrant and scales have been evaluated, and it is followed with an evaluation of different wavelet filter choices and their impact on recognition accuracy. In this study, an approach for face recognition based on coefficient selection for DWT is presented, and the significant of DWT coefficient threshold selection is also analysed. For the hardware implementation, two architectures for two-dimensional (2-D) Haar wavelet transform (HWT) IP core with transpose-based computation and dynamic partial reconfiguration (DPR) have been synthesised using VHDL and implemented on Xilinx Virtex-5 FPGAs. Experimental results and comparisons between different configurations using partial and non-partial reconfiguration processes and a detailed performance analysis of the area, power consumption and maximum frequency are also discussed in this paper.     

Evolving Takagi–Sugeno fuzzy model based on switching to neighboring models

In this paper, we propose a new online identification approach for evolving Takagi–Sugeno (TS) fuzzy models. Here, for a TS model, a certain number of models as neighboring models are defined and then the TS model switches to one of them at each stage of evolving. We define neighboring models for an in-progress (current) TS model as its fairly evolved versions, which are different with it just in two fuzzy rules. To generate neighboring models for the current model, we apply specially designed split and merge operations. By each split operation, a fuzzy rule is replaced with two rules; while by each merge operation, two fuzzy rules combine to one rule. Among neighboring models, the one with the minimum sum of squared errors – on certain time intervals – replaces the current model.To reduce the computational load of the proposed evolving TS model, straightforward relations between outputs of neighboring models and that of current model are established. Also, to reduce the number of rules, we define and use first-order TS fuzzy models whose generated local linear models can be localized in flexible fuzzy subspaces. To demonstrate the improved performance of the proposed identification approach, the efficiency of the evolving TS model is studied in prediction of monthly sunspot number and forecast of daily electrical power consumption. The prediction and modeling results are compared with that of some important existing evolving fuzzy systems.     

Performance analysis of multimedia based web traffic with QoS constraints

During the recent years, there has been a tremendous growth in the development and deployment of multimedia based networked applications such as video streaming, IP telephony, interactive games, among others. These applications, in contrast to elastic applications such as email and data sharing, are delay and delay jitter sensitive but can tolerate certain level of packet loss. A vital element of end-to-end delay and delay jitter is the random queueing delays in network switches and routers. Analysis of robust mechanisms for buffer management at network routers needs to be carried out in order to reduce end-to-end delay for traffic generated by multimedia applications. In this context, a threshold based buffer management scheme for accommodating multiple class multimedia traffic in network routers has been analysed. This technique effectively controls the allocation of buffer to various traffic classes according to their delay constraints. The forms of the joint state probabilities, as well as basic performance measures such as blocking probabilities are analytically established at equilibrium. Typical numerical experiments are included to illustrate the credibility of the proposed mechanism in the context of different quality of service (QoS) grades for various network traffic classes. This model, therefore, can be used as a powerful tool to provide a required grade of service to a particular class of multimedia based web traffic in any heterogeneous network.     

Techniques for pipelined broadcast on ethernet switched clusters

By splitting a large broadcast message into segments and broadcasting the segments in a pipelined fashion, pipelined broadcast can achieve high performance in many systems. In this paper, we investigate techniques for efficient pipelined broadcast on clusters connected by multiple Ethernet switches. Specifically, we develop algorithms for computing various contention-free broadcast trees that are suitable for pipelined broadcast on Ethernet switched clusters, extend the parametrized LogP model for predicting appropriate segment sizes for pipelined broadcast, show that the segment sizes computed based on the model yield high performance, and evaluate various pipelined broadcast schemes through experimentation on Ethernet switched clusters with various topologies. The results demonstrate that our techniques are practical and efficient for contemporary fast Ethernet and Giga-bit Ethernet clusters.     

Bandwidth Efficient All-to-All Broadcast on Switched Clusters

Clusters of workstations employ flexible topologies: regular, irregular, and hierarchical topologies have been used in such systems. The flexibility poses challenges for developing efficient collective communication algorithms since the network topology can potentially have a strong impact on the communication performance. In this paper, we consider the all-to-all broadcast operation on clusters with cut-through and store-and-forward switches. We show that near-optimal all-to-all broadcast on a cluster with any topology can be achieved by only using the links in a spanning tree of the topology when the message size is sufficiently large. The result implies that increasing network connectivity beyond the minimum tree connectivity does not improve the performance of the all-to-all broadcast operation when the most efficient topology specific algorithm is used. All-to-all broadcast algorithms that achieve near-optimal performance are developed for clusters with cut-through and clusters with store-and-forward switches. We evaluate the algorithms through experiments and simulations. The empirical results confirm our theoretical finding.     

Potentiometric urea biosensor based on BSA embedded surface modified polypyrrole film

A potentiometric biosensor based on bovine serum albumin (BSA) embedded surface modified polypyrrole has been developed for the quantitative estimation of urea in aqueous solution. The enzyme, urease (Urs), was covalently linked to free amino groups present over the BSA embedded modified surface of the conducting polypyrrole film electrochemically deposited onto an indium–tin-oxide (ITO) coated glass plate. The biosensor has been characterized by UV–visible, infrared spectroscopy and SEM. Potentiometric and spectrophotometric response of the enzyme electrode (Urs/BSA-PPy/ITO) were measured as a function of urea concentration in Tris–HCl buffer (pH 7.0). It has been found that the electrode responds to low urea concentration with wider range of detection. The electrode showed a linear response range of 6.6 × 10⁻⁶ to 7.5 × 10⁻⁴ M urea. The response time is about 70–90 s reaching to a 95% steady-state potential value and 75% of the enzyme activity is retained for about 2 months. These results indicate an efficient covalent linkage of enzyme to free amino groups of the BSA molecules over the surface of polypyrrole film, which leads to high enzyme loading, an increased lifetime stability of the electrode and an improved wide range of detection of low urea concentration in aqueous solution.     

A Cooperative Game Theoretical Technique for Joint Optimization of Energy Consumption and Response Time in Computational Grids

With the explosive growth in computers and the growing scarcity in electric supply, reduction of energy consumption in large-scale computing systems has become a research issue of paramount importance. In this paper, we study the problem of allocation of tasks onto a computational grid, with the aim to simultaneously minimize the energy consumption and the makespan subject to the constraints of deadlines and tasks' architectural requirements. We propose a solution from cooperative game theory based on the concept of Nash Bargaining Solution. In this cooperative game, machines collectively arrive at a decision that describes the task allocation that is collectively best for the system, ensuring that the allocations are both energy and makespan optimized. Through rigorous mathematical proofs we show that the proposed cooperative game in mere O(n mlog(m)) time (where n is the number of tasks and m is the number of machines in the system) produces a Nash Bargaining Solution that guarantees Pareto-optimally. The simulation results show that the proposed technique achieves superior performance compared to the Greedy and Linear Relaxation (LR) heuristics, and with competitive performance relative to the optimal solution implemented in LINDO for small-scale problems.