Designing Internet-Based Payment Systems: Guidelines and Empirical Basis

ABSTRACT

This article describes research into online electronic payment systems, focusing on the aspects of payment systems that are critical for their acceptance by end users. Based on our earlier research and a diary study of payments with an online payment system and with online banking systems of a reputable bank, we proposed a set of 12 interaction design guidelines. The guidelines have been applied during the implementation and redesign of a new payment system. An extensive experimental comparison of the original version of the system with the one designed according to the design guidelines has provided confirmation of the relevance and adequacy of these guidelines for designing online payment systems.     

Improving the Hybrid Data Dissemination Model of Web Documents

One of the major problems in the Internet today is the scalable delivery of data. With more and more people joining the Internet community, web servers and services are being forced to deal with workloads beyond their original data dissemination design capacity. One solution that has arisen to address scalability is to use multicasting, or push-based data dissemination, to send out data to many clients at once. More recently, the idea of using multicasting as part of a hybrid system with unicasting has shown positive results in increasing server scalability. In this paper we focus on solving problems associated with the hybrid dissemination model. In particular, we address the issues of document popularity and document division while arguing for the use of a third channel, called the multicast pull channel, in the hybrid system model. This channel improves performance in terms of response time while improving the robustness of the hybrid system. We show through extensive simulation using our working hybrid server the usefulness of this additional channel and its improving effects in creating a more scalable and more efficient web server.     

On the parameterized complexity of d-dimensional point set pattern matching

Deciding whether two n-point sets A,B∈Rd are congruent is a fundamental problem in geometric pattern matching. When the dimension d is unbounded, the problem is equivalent to graph isomorphism and is conjectured to be in FPT.When |A|=m<|B|=n, the problem becomes that of deciding whether A is congruent to a subset of B and is known to be NP-complete. We show that point subset congruence, with d as a parameter, is W[1]-hard, and that it cannot be solved in O(mno(d))-time, unless SNP⊂DTIME(²o(n)). This shows that, unless FPT=W[1], the problem of finding an isometry of A that minimizes its directed Hausdorff distance, or its Earth Mover's Distance, to B, is not in FPT.     

Exact algorithms for a scheduling problem with unrelated parallel machines and sequence and machine-dependent setup times

A scheduling problem with unrelated parallel machines, sequence and machine-dependent setup times, due dates and weighted jobs is considered in this work. A branch-and-bound algorithm (B&B) is developed and a solution provided by the metaheuristic GRASP is used as an upper bound. We also propose a set of instances for this type of problem. The results are compared to the solutions provided by two mixed integer programming models (MIP) with the solver CPLEX 9.0. We carry out computational experiments and the algorithm performs extremely well on instances with up to 30 jobs.     

A parallel multistart algorithm for the closest string problem

In this paper we describe and implement a parallel algorithm to find approximate solutions for the Closest String Problem (CSP). The CSP, also known as Motif Finding problem, has applications in Coding Theory and Computational Biology. The CSP is NP-hard which motivates us to think about heuristics to solve large instances. Several approximation algorithms have been designed for the CSP, but all of them have a poor performance guarantee. Recently some researchers have shown empirically that integer programming techniques can be successfully used to solve moderate-size instances (10–30 strings each of which is 300–800 characters long) of the CSP. However, real-world instances are larger than those tested. In this paper we show how a simple heuristic can be used to find near-optimal solutions to that problem. We implemented a parallel version of this heuristic and report computational experiments on large-scale instances. These results show the effectiveness of our approach.     

Optimal control of switched systems via non-linear optimization based on direct differentiations of value functions

This paper presents an approach for solving optimal control problems of switched systems. In general, in such problems one needs to find both optimal continuous inputs and optimal switching sequences, since the system dynamics vary before and after every switching instant. After formulating a general optimal control problem, we propose a two stage optimization methodology. Since many practical problems only concern optimization where the number of switchings and the sequence of active subsystems are given, we concentrate on such problems and propose a method which uses nonlinear optimization and is based on direct differentiations of value functions. The method is then applied to general switched linear quadratic (GSLQ) problems. Examples illustrate the results.     

Parameter estimation in time-triggered and event-triggered model-based control of uncertain systems

In this article on-line parameter estimation of dynamical systems is addressed in the context of model-based networked control systems (MB-NCSs). Stability conditions that are robust to parameter uncertainties and lack of feedback for extended intervals of time are presented. The updated model is used to control the real system the next time feedback information is unavailable. Additionally, new estimation models are proposed that offer better convergence properties than typical state-space parameter estimation methods; common assumptions such as availability of persistently exciting inputs and estimation of only a canonical form of the system are relaxed. The implementation of upgraded models in MB-NCSs results in better usage of the network by allowing longer intervals without the need for measurement updates.     

Design of stabilizing switching control laws for discrete- and continuous-time linear systems using piecewise-linear Lyapunov functions

In this paper, the stability of switched linear systems is investigated using piecewise linear Lyapunov functions. In particular, we identify classes of switching sequences that result in stable trajectories. Given a switched linear system, we present a systematic methodology for computing switching laws that guarantee stability based on the matrices of the system. In the proposed approach, we assume that each individual subsystem is stable and admits a piecewise linear Lyapunov function. Based on these Lyapunov functions, we compose 'global' Lyapunov functions that guarantee stability of the switched linear system. A large class of stabilizing switching sequences for switched linear systems is characterized by computing conic partitions of the state space. The approach is applied to both discrete-time and continuous-time switched linear systems.     

Evaluation of a pervasive awareness system designed for busy parents

Does pervasive technology have a role to play in supporting the communication of busy couples? Especially when they are already living together and already have a high degree of awareness of each other’s rhythms of daily life, their whereabouts and needs? A two week long field study of an awareness system allowed eight working couples to automatically exchange place, activity and calendar information as well as messages and photos. Data analysis provides both qualitative and quantitative evidence which suggest strongly that such a system can provide support for availability, coordination, reassurance and affection for this group. Findings which inform the design of such systems are: the need for transitions in places instead of location information to support coordination, the two tracks of daily communication of busy parents (reassurance and emergency) and usability barriers in current mobile applications which prevent this group from engaging in photo sharing. The contexts and unexpected uses that participants found in the system are described in detail.     

hGA: Hybrid genetic algorithm in fuzzy rule-based classification systems for high-dimensional problems

The aim of this work is to propose a hybrid heuristic approach (called hGA) based on genetic algorithm (GA) and integer-programming formulation (IPF) to solve high dimensional classification problems in linguistic fuzzy rule-based classification systems. In this algorithm, each chromosome represents a rule for specified class, GA is used for producing several rules for each class, and finally IPF is used for selection of rules from a pool of rules, which are obtained by GA. The proposed algorithm is experimentally evaluated by the use of non-parametric statistical tests on seventeen classification benchmark data sets. Results of the comparative study show that hGA is able to discover accurate and concise classification rules.