Developing Approaches for Solving a Telecommunications Feature Subscription Problem

Call control features (e.g., call-divert, voice-mail) are primitive options to which users can subscribe off-line to personalise their service. The configuration of a feature subscription involves choosing and sequencing features from a catalogue and is subject to constraints that prevent undesirable feature interactions at run-time. When the subscription requested by a user is inconsistent, one problem is to find an optimal relaxation, which is a generalisation of the feedback vertex set problem on directed graphs, and thus it is an NP-hard task. We present several constraint programming formulations of the problem. We also present formulations using partial weighted maximum Boolean satisfiability and mixed integer linear programming. We study all these formulations by experimentally comparing them on a variety of randomly generated instances of the feature subscription problem.

PROBLEM-SOLVING IN SCHIZOPHRENIA - A SPECIFIC DEFICIT IN PLANNING ABILITY

The study investigated problem solving ability in schizophrenia. Thirty DSM-IIIR schizophrenic patients and 27 matched normal controls were tested on the Three-Dimensional Computerised Tower of London Test (3-D CTL Test) (Morris et al., 1993). The patients took significantly more moves to solve a series of problems and solved significantly fewer problems in the predetermined minimum number of moves. The patients response times, as measured using a control version of the task (the 3-D CTL Control), were longer than those of the controls. However, when latencies were adjusted to take into account the slower responses overall, the patients planning times were not significantly increased. Inaccurate planning, as defined by taking more moves, did not correlate with either positive or negative symptoms, but the response times tended to be longer in patients who had more negative symptoms. The findings suggest that there is a deficit in problem solving activity in schizophrenia that may be associated with translating 'willed intentions' into action, independent of slower motor speed.

Problem-solving and spatial working memory in patients with schizophrenia and with focal frontal and temporal lobe lesions

Problem-solving ability was investigated in 25 DSM-IIIR schizophrenic (SC) patients using the Tower of Hanoi (TOH) task. Their performance was compared to that of: (1) 22 patients with neurosurgical unilateral prefrontal lesions, 11 left (LF) and 10 right hemisphere (RF); (2) 38 patients with unilateral temporal lobectomies, 19 left (LT) and 19 right (RT); and (3) 44 matched control subjects. Like the RT and LF group, the schizophrenics were significantly impaired on the TOH. The deficit shown by the schizophrenic group was equivalent whether or not the problems to be solved included goal-subgoal conflicts, unlike the LF group who were impaired specifically on these problems. The nature of the SC deficit was also distinct from that of the RT group, in that the problem-solving deficit remained after controlling for the effects of spatial memory performance. This study indicates, therefore, that neither focal frontal nor temporal lobe damage sustained in adult life is a sufficient explanation for the problem-solving deficits found in patients with schizophrenia. (C) 1999 Elsevier Science B.V. All rights reserved.

Is Early Warning Effective for the Improvement of Problem Solving and Project Performance?

Since the first launch of the new engineering contract (NEC) in 1993, early warning of problems has been widely recognized as an important approach of proactive management during a construction or engineering project. Is early warning really effective for the improvement of problem solving and project performance? This is a research question that still lacks a good answer. For this reason, an empirical investigation was made in the United Kingdom (U.K.) to answer the question. This study adopts a combination of literature review, expert interview, and questionnaire survey. Nearly 100 questionnaire responses were collected from the U.K. construction industry, based on which the use of early warning under different forms of contract is compared in this paper. Problem solving and project performance are further compared between the projects using early warning and the projects not using early warning. The comparison provides clear evidence for the significant effect of early warning on problem solving and project performance in terms of time, cost, and quality. Subsequently, an input-process-output model is developed in this paper to explore the relationship among early warning, problem solving, and project
performance. All these help construction researchers and practitioners to better understand the role of early warning in ensuring project success.

Generalized Langevin equation: An efficient approach to nonequilibrium molecular dynamics of open systems

The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e. g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

Sound Synthesis for Contact-Driven Musical Instruments via Discretisation of Hamilton's Equations

Physical modelling of musical instruments involves studying nonlinear interactions between parts of the instrument. These can pose several difficulties concerning the accuracy and stability of numerical algorithms. In particular, when the underlying forces are non-analytic functions of the phase-space variables, a stability proof can only be obtained in limited cases. An approach has been recently presented by the authors, leading to unconditionally stable simulations for lumped collision models. In that study, discretisation of Hamilton’s equations instead of the usual Newton’s equation of motion yields a numerical scheme that can be proven to be energy conserving. In this paper, the above approach is extended to collisions of distributed objects. Namely, the interaction of an ideal string with a flat barrier is considered. The problem is formulated within the Hamiltonian framework and subsequently discretised. The resulting nonlinearmatrix equation can be shown to possess a unique solution, that enables the update of the algorithm. Energy conservation and thus numerical stability follows in a way similar to the lumped collision model. The existence of an analytic description of this interaction allows the validation of the model’s accuracy. The proposed methodology can be used in sound synthesis applications involving musical instruments where collisions occur either in a confined (e.g. hammer-string interaction, mallet impact) or in a distributed region (e.g. string-bridge or reed-mouthpiece interaction).

SOLVING THE INHOMOGENEOUS SCHRODINGER-EQUATION ON A BIDIRECTIONAL PIPELINE OF TRANSPUTERS

In this paper we describe the design of a parallel solution of the inhomogeneous Schrodinger equation, which arises in the construction of continuum orbitals in the R-matrix theory of atomic continuum processes. A prototype system is described which has been programmed in occam2 and implemented on a bi-directional pipeline of transputers. Some timing results for the prototype system are presented, and the development of a full production system is discussed.

Scaling of magneto-quantum-radiative hydrodynamic equations: From laser-produced plasmas to astrophysics

We introduce the equations of magneto-quantum-radiative hydrodynamics. By rewriting them in a dimensionless form, we obtain a set of parameters that describe scale-dependent ratios of characteristic hydrodynamic quantities. We discuss how these dimensionless parameters relate to the scaling between astrophysical observations and laboratory experiments.

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies need to be to enable efficient optimal planning. Arguably, the smallest strategies one can conceive simply prescribe an action for each time step, without considering past decisions or observations. Previous work has shown that finding such optimal strategies even for polytree-shaped diagrams with ternary variables and a single value node is NP-hard, but the case of binary variables was left open. In this paper we address such a case, by first noting that optimal strategies can be obtained in polynomial time for polytree-shaped diagrams with binary variables and a single value node. We then show that the same problem is NP-hard if the diagram has multiple value nodes. These two results close the fixed-parameter complexity analysis of optimal strategy selection in influence diagrams parametrized by the shape of the diagram, the number of value nodes and the maximum variable cardinality.

Solving Decision Problems with Limited Information

We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.

Solving Limited Memory Influence Diagrams

We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that these problems are NP-hard even if the underlying graph structure of the problem has low treewidth and the variables take on a bounded number of states, and that they admit no provably good approximation if variables can take on an arbitrary number of states.

Solving Limited Memory Influence Diagrams

We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that the problem is NP-hard even if the underlying graph structure of the problem has small treewidth and the variables take on a bounded number of states, but that a fully polynomial time approximation scheme exists for these cases. Moreover, we show that the bound on the number of states is a necessary condition for any efficient approximation scheme.