A generic grouping algorithm and its quantitative analysis

This paper presents a generic method for perceptual grouping and an analysis of its expected grouping quality. The grouping method is fairly general: It may be used for the grouping of various types of data features, and to incorporate different grouping cues operating over feature sets of different sizes. The proposed method is divided into two parts: constructing a graph representation of the available perceptual grouping evidence, and then finding the “best” partition of the graph into groups. The first stage includes a cue enhancement procedure, which integrates the information available from multifeature cues into very reliable bifeature cues. Both stages are implemented using known statistical tools such as Wald's SPRT algorithm (1952) and the maximum likelihood criterion. The accompanying theoretical analysis of this grouping criterion quantifies intuitive expectations and predicts that the expected grouping quality increases with cue reliability. It also shows that investing more computational effort in the grouping algorithm leads to better grouping results. This analysis, which quantifies the grouping power of the maximum likelihood criterion, is independent of the grouping domain. To our best knowledge, such an analysis of a grouping process is given here for the first time. Three grouping algorithms, in three different domains, are synthesized as instances of the generic method. They demonstrate the applicability and generality of this grouping method     

Multi-objective reliability optimization for dissimilar-unit cold-standby systems using a genetic algorithm

A genetic algorithm approach is used to solve a multi-objective discrete reliability optimization problem in a k dissimilar-unit non-repairable cold-standby redundant system. Each unit is composed of a number of independent components with generalized Erlang distributions arranged in a series–parallel configuration. There are multiple component choices with different distribution parameters available for being replaced with each component of the system. The objective of the reliability optimization problem is to select the best components, from the set of available components, to be placed in the standby system in order to minimize the initial purchase cost of the system, maximize the system MTTF (mean time to failure), minimize the system VTTF (variance of time to failure) and also maximize the system reliability at the mission time. Finally, we apply a genetic algorithm with double strings using continuous relaxation based on reference solution updating (GADSCRRSU) to solve this multi-objective problem, using goal attainment formulation. The results are also compared against the results of a discrete-time approximation technique to show the efficiency of the proposed GA approach.     

Why Johnny can't surf (safely)? Attacks and defenses for web users

In their seminal article “Why Johnny Can't Encrypt” [Whitten A, Tygar JD. Why Johnny can't encrypt: a usability case study of PGP 5.0. In: Proceedings of the eighth USENIX security symposium; August 1999.], Whitten and Tygar showed that usability weaknesses of encryption software may result in failure to protect users, in spite of good cryptography. A similar situation happens, on a huge scale, on the Web: the widely deployed SSL/TLS protocols provide good cryptography, yet there is a growing amount of successful attacks on web users, causing massive damages. In this article, we focus on password theft via fake websites, to which we refer as phishing. We believe that phishing is currently the most severe threat facing web users.We begin with a brief review of SSL/TLS. Many sensitive sites do not use SSL/TLS, or use it incorrectly (e.g. to encrypt password, filled into an unprotected login form); we explain why.Even if sites use SSL/TLS (correctly), this may not be enough to prevent phishing – at least, using the basic security and identification indicators of most browsers (URL, padlock and HTTPS). We discuss basic and advanced indicators, and their usability problems. We review recent usability studies, whose results are rather alarming, and put in question the ability of users to avoid phishing sites based on security and identification indicators.     

Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam principles)

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (i) an evolving list of comprehensive quality metrics and (ii) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in Proteomics, Proteomics Clinical Applications, Journal of Proteome Research, and Molecular and Cellular Proteomics, as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.     

The Complexity of Boolean Functions in Different Characteristics

Every Boolean function on n variables can be expressed as a unique multivariate polynomial modulo p for every prime p. In this work, we study how the degree of a function in one characteristic affects its complexity in other characteristics. We establish the following general principle: functions with low degree modulo p must have high complexity in every other characteristic q. More precisely, we show the following results about Boolean functions f : {0, 1}ⁿ → {0, 1} which depend on all n variables, and distinct primes p, q:

FLAR: AN ADAPTIVE FUZZY ROUTING ALGORITHM FOR COMMUNICATIONS NETWORKS USING MOBILE ANTS

Swarm intelligence, as demonstrated by a natural biological swarm, such as an ant colony, has many powerful properties that are desirable for effective routing in communications networks. In this paper, we propose an intelligent routing algorithm that we are calling Fuzzy Logic Ant-based Routing (FLAR), which is inspired by ant colonies and enhanced by fuzzy logic techniques. Using a fuzzy system as an intelligent and expert mechanism allows multiple constraints to be considered in a simple and intuitive way. Simulation results and a comparison of the proposed method with two state-of-the-art routing algorithms show better performance and a higher fault tolerance for our approach, particularly in regard to link failures.     

Hidden Markov model for human to computer interaction: a study on human hand gesture recognition

Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object consisting of many connected parts and joints. Therefore, for applications that involve HCI one can find many challenges to establish a system with high detection and recognition accuracy for hand posture and/or gesture. Hand posture is defined as a static hand configuration without any movement involved. Meanwhile, hand gesture is a sequence of hand postures connected by continuous motions. During the past decades, many approaches have been presented for hand posture and/or gesture recognition. In this paper, we provide a survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications.     

Position,Jacobian and workspace analysis of a 3-PSP spatial parallel manipulator

This paper investigates the problems of kinematics, Jacobian, singularity and workspace analysis of a spatial type of 3-PSP parallel manipulator. First, structure and motion variables of the robot are addressed. Two operational modes, non-pure translational and coupled mixed-type are considered. Two inverse kinematics solutions, an analytical and a numerical, for the two operational modes are presented. The direct kinematics of the robot is also solved utilizing a new geometrical approach. It is shown, unlike most parallel robots, the direct kinematics problem of this robot has a unique solution. Next, analytical expressions for the velocity and acceleration relations are derived in invariant form. Auxiliary vectors are introduced to eliminate passive velocity and acceleration vectors. The three types of conventional singularities are analyzed. The notion of non-pure rotational and non-pure translational Jacobian matrices is introduced. The non-pure rotational and non-pure translational Jacobian matrices are combined to form the Jacobian of constraint matrix which is then used to obtain the constraint singularity. Finally, two methods, a discretization method and one based on direct kinematics are presented and robot non-pure translation and coupled mixed-type reachable workspaces are obtained. The influence of tool length on workspace is also studied.