Bengali handwritten character recognition using modified syntactic method

Several approaches have been proposed to recognize handwritten Bengali characters using different curve fitting algorithms and curvature analysis. In this paper, a new algorithm (Curve-fitting Algorithm) to identify various strokes of a handwritten character is developed. The curve-fitting algorithm helps recognizing various strokes of different patterns (line, quadratic curve) precisely. This reduces the error elimination burden heavily. Implementation of this Modified Syntactic Method demonstrates significant improvement in the recognition of Bengali handwritten characters.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Fixed argument pairings

A common scenario in many pairing-based cryptographic protocols is that one argument in the pairing is fixed as a long term secret key or a constant parameter in the system. In these situations, the runtime of Miller's algorithm can be significantly reduced by storing precomputed values that depend on the fixed argument, prior to the input or existence of the second argument. In light of recent developments in pairing computation, we show that the computation of the Miller loop can be sped up by up to 37 if precomputation is employed, with our method being up to 19.5 faster than the previous precomputation techniques.

secFleck: A Public Key Technology Platform for Wireless Sensor Networks

We describe the design and implementation of a public-key platform, secFleck, based on a commodity Trusted Platform Module (TPM) chip that extends the capability of a standard node. Unlike previous software public-key implementations this approach provides E- Commerce grade security; is computationally fast, energy efficient; and has low financial cost — all essential attributes for secure large-scale sen- sor networks. We describe the secFleck message security services such as confidentiality, authenticity and integrity, and present performance re- sults including computation time, energy consumption and cost. This is followed by examples, built on secFleck, of symmetric key management, secure RPC and secure software update.

Towards trusted wireless sensor networks

This article presents the design and implementation of a trusted sensor node that provides Internet-grade security at low system cost. We describe trustedFleck, which uses a commodity Trusted Platform Module (TPM) chip to extend the capabilities of a standard wireless sensor node to provide security services such as message integrity, confidentiality, authenticity, and system integrity based on RSA public-key and XTEA-based symmetric-key cryptography. In addition trustedFleck provides secure storage of private keys and provides platform configuration registers (PCRs) to store system configurations and detect code tampering. We analyze system performance using metrics that are important for WSN applications such as computation time, memory size, energy consumption and cost. Our results show that trustedFleck significantly outperforms previous approaches (e.g., TinyECC) in terms of these metrics while providing stronger security levels. Finally, we describe a number of examples, built on trustedFleck, of symmetric key management, secure RPC, secure software update, and remote attestation.

Wide-angle visual feature matching for outdoor localization

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.

Poster Abstract : A public key technology platform for wireless sensor networks

Communication security for wireless sensor networks (WSN) is a challenge due to the limited computation and energy resources available at nodes. We describe the design and implementation of a public-key (PK) platform based on a standard Trusted Platform Module (TPM) chip that extends the capability of a standard node. The result facilitates message security services such as confidentiality, authenticity and integrity. We present results including computation time, energy consumption and cost.

Tracking road edges in the panospheric image plane

This paper presents a technique for tracking road edges in a panoramic image sequence. The major contribution is that instead of unwarping the image to find parallel lines representing the road edges, we choose to warp the parallel groundplane lines into the image plane of the equiangular panospheric camera. Updating the parameters of the line thus involves searching a very small number of pixels in the panoramic image, requiring considerably less computation than unwarping. Results using real-world images, including shadows, intersections and curves, are presented.

Standardization and omics science : technical and social dimensions are inseparable and demand symmetrical study

Standardization is critical to scientists and regulators to ensure the quality and interoperability of research processes, as well as the safety and efficacy of the attendant research products. This is perhaps most evident in the case of “omics science,” which is enabled by a host of diverse high-throughput technologies such as genomics, proteomics, and metabolomics. But standards are of interest to (and shaped by) others far beyond the immediate realm of individual scientists, laboratories, scientific consortia, or governments that develop, apply, and regulate them. Indeed, scientific standards have consequences for the social, ethical, and legal environment in which innovative technologies are regulated, and thereby command the attention of policy makers and citizens. This article argues that standardization of omics science is both technical and social. A critical synthesis of the social science literature indicates that: (1) standardization requires a degree of flexibility to be practical at the level of scientific practice in disparate sites; (2) the manner in which standards are created, and by whom, will impact their perceived legitimacy and therefore their potential to be used; and (3) the process of standardization itself is important to establishing the legitimacy of an area of scientific research.

Design Optimisation of UAVs Systems achieved on a Framework Environment via Evolution and Game Theory

Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

Avoiding full extension field arithmetic in pairing computations

The most costly operations encountered in pairing computations are those that take place in the full extension field Fpk . At high levels of security, the complexity of operations in Fpk dominates the complexity of the operations that occur in the lower degree subfields. Consequently, full extension field operations have the greatest effect on the runtime of Miller’s algorithm. Many recent optimizations in the literature have focussed on improving the overall operation count by presenting new explicit formulas that reduce the number of subfield operations encountered throughout an iteration of Miller’s algorithm. Unfortunately, almost all of these improvements tend to suffer for larger embedding degrees where the expensive extension field operations far outweigh the operations in the smaller subfields. In this paper, we propose a new way of carrying out Miller’s algorithm that involves new explicit formulas which reduce the number of full extension field operations that occur in an iteration of the Miller loop, resulting in significant speed ups in most practical situations of between 5 and 30 percent.

Faster pairing computations on curves with high-degree twists

Research on efficient pairing implementation has focussed on reducing the loop length and on using high-degree twists. Existence of twists of degree larger than 2 is a very restrictive criterion but luckily constructions for pairing-friendly elliptic curves with such twists exist. In fact, Freeman, Scott and Teske showed in their overview paper that often the best known methods of constructing pairing-friendly elliptic curves over fields of large prime characteristic produce curves that admit twists of degree 3, 4 or 6. A few papers have presented explicit formulas for the doubling and the addition step in Miller’s algorithm, but the optimizations were all done for the Tate pairing with degree-2 twists, so the main usage of the high- degree twists remained incompatible with more efficient formulas. In this paper we present efficient formulas for curves with twists of degree 2, 3, 4 or 6. These formulas are significantly faster than their predecessors. We show how these faster formulas can be applied to Tate and ate pairing variants, thereby speeding up all practical suggestions for efficient pairing implementations over fields of large characteristic.

Delaying mismatched field multiplications in pairing computations

Miller’s algorithm for computing pairings involves perform- ing multiplications between elements that belong to different finite fields. Namely, elements in the full extension field Fpk are multiplied by elements contained in proper subfields F pk/d , and by elements in the base field Fp . We show that significant speedups in pairing computations can be achieved by delaying these “mismatched” multiplications for an optimal number of iterations. Importantly, we show that our technique can be easily integrated into traditional pairing algorithms; implementers can exploit the computational savings herein by applying only minor changes to existing pairing code.

An analysis of the RC4 family of stream ciphers against algebraic attacks

To date, most applications of algebraic analysis and attacks on stream ciphers are on those based on lin- ear feedback shift registers (LFSRs). In this paper, we extend algebraic analysis to non-LFSR based stream ciphers. Specifically, we perform an algebraic analysis on the RC4 family of stream ciphers, an example of stream ciphers based on dynamic tables, and inves- tigate its implications to potential algebraic attacks on the cipher. This is, to our knowledge, the first pa- per that evaluates the security of RC4 against alge- braic attacks through providing a full set of equations that describe the complex word manipulations in the system. For an arbitrary word size, we derive alge- braic representations for the three main operations used in RC4, namely state extraction, word addition and state permutation. Equations relating the inter- nal states and keystream of RC4 are then obtained from each component of the cipher based on these al- gebraic representations, and analysed in terms of their contributions to the security of RC4 against algebraic attacks. Interestingly, it is shown that each of the three main operations contained in the components has its own unique algebraic properties, and when their respective equations are combined, the resulting system becomes infeasible to solve. This results in a high level of security being achieved by RC4 against algebraic attacks. On the other hand, the removal of an operation from the cipher could compromise this security. Experiments on reduced versions of RC4 have been performed, which confirms the validity of our algebraic analysis and the conclusion that the full RC4 stream cipher seems to be immune to algebraic attacks at present.