Generation of classes of robust periodic railway timetables

In this paper we discuss the problem of randomly sampling classes of fixed-interval railway timetables from a so-called timetable structure. Using a standard model for the timetable structure, we introduce a natural partitioning of the set of feasible timetables into classes. We then define a new probability distribution where the probability of each class depends on the robustness of the timetables in that class. Due to the difficulty of sampling directly from this distribution, we propose a heuristic sampling method and illustrate using practical data that our method indeed favors classes containing robust timetables over others.     

Parallel machine scheduling to minimize the sum of quadratic completion times

We consider the parallel machine scheduling problem of minimizing the sum of quadratic job completion times. We first prove that the problem is strongly NP-hard. We then demonstrate by probabilistic analysis that the shortest processing time rule solves the problem asymptotically. The relative error of the rule converges in probability to zero under the assumption that the job processing times are independent random variables uniformly distributed in (0, 1). We finally provide some computational results, which show that the rule is effective in solving the problem in practice.     

A probabilistic spectral framework for grouping and segmentation

This paper presents an iterative spectral framework for pairwise clustering and perceptual grouping. Our model is expressed in terms of two sets of parameters. Firstly, there are cluster memberships which represent the affinity of objects to clusters. Secondly, there is a matrix of link weights for pairs of tokens. We adopt a model in which these two sets of variables are governed by a Bernoulli model. We show how the likelihood function resulting from this model may be maximised with respect to both the elements of link-weight matrix and the cluster membership variables. We establish the link between the maximisation of the log-likelihood function and the eigenvectors of the link-weight matrix. This leads us to an algorithm in which we iteratively update the link-weight matrix by repeatedly refining its modal structure. Each iteration of the algorithm is a three-step process. First, we compute a link-weight matrix for each cluster by taking the outer-product of the vectors of current cluster-membership indicators for that cluster. Second, we extract the leading eigenvector from each modal link-weight matrix. Third, we compute a revised link weight matrix by taking the sum of the outer products of the leading eigenvectors of the modal link-weight matrices.     

MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN CONTROL

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per‐unit‐time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max‐min optimal policy, which maximizes the worst‐case average per‐unit‐time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time‐varying transition rates.     

Near-optimal state feedback design for singularly perturbed systems by unified approach

A near optimal state feedback design for singularly perturbed systems by a unified approach using the delta operator is presented with an example of the aircraft longitudinal motion. The main contribution of this paper is to explore the use of the i -operator that has attracted a new attention in systems science. The i -operator system unifies the continuous system and the discrete system together without loosing any characteristics of both systems. The paper offers the following; Finite-word-length-characteristics are improved using the i -operator. Floating-point-operations are reduced by block diagonalization and by time-invariant optimal feedback gain from the algebraic Riccati equation. The results of adopting those approaches are illustrated in the simulation figures and compared with the earlier one.     

Thermal,hydrolytic, anticorrosive,and tribological properties of alkyd‐silicone hyperbranched resins with high solid content

Novel alkyd hyperbranched resins (AHBRs) modified with a Z‐6018 silicone (a polysiloxane intermediate) and with high solid content were synthesized by etherification reaction using an acid catalyst. Different molar ratios of AHBR to silicone were used. Structural, thermal, hydrolytic, anticorrosive, and tribological properties were studied using infrared (IR) analysis, nuclear magnetic resonance (NMR), vapor pressure osmometry (VPO), thermogravimetric analysis (TGA), acid value, electrochemical impedance spectroscopy (EIS), and pin‐on‐disk friction. IR and NMR provide evidence of grafting of the silicone on AHBR; the efficiency of grafting was quantified by TGA. Thermal stability was studied also by acid value analysis. Grafting increases the number average molecular mass, enhances thermal stability, and improves significantly hydrolytic stability. Corrosion resistance on steel is improved by two orders of magnitude, hence our modified materials can be used as highly effective anticorrosion coatings. Grafting lowers dynamic friction dramatically, more so at higher concentrations of silicone. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Individual Stair Ascent and Descent Walk Speeds Measured in a Korean High-Rise Building

The purpose of this study was to collect and analyze individual unimpeded stair ascent and descent walk speeds for the Korean population. To collect these data, a full-scale experiment was conducted in a 50-storey residential building in Korea involving 30 male and 30 female participants with an average age of 23.4 years. Each participant was required to ascend 50 floors and after a suitable rest period was then required to descend 50 floors using the stairs. Arrival times on each floor were recorded using video cameras, allowing floor by floor walk speeds to be determined and to assess whether fatigue affected the descent/ascent. The average descent speed for the male and female population was 0.83 m/s and 0.74 m/s, respectively, while the average ascent speed was 0.66 m/s and 0.48 m/s. However, there was no significant relationship between body mass index and stair walk speed or unimpeded horizontal walk speed and stair walk speed. During the descent, 50% of the population displayed a decrease in the walk speed over the final half of the descent with a maximum decrease of some 19%. However, some 50% of the population increased their travel speed during the final half of the descent. During the ascent, all participants decreased their speed over the first 20 floors by an average of approximately 60%. Implications of these findings for evacuation modeling/simulation are discussed.     

Effects of firm and IT characteristics on the value of e-commerce initiatives: An inductive theoretical framework

We explore the theoretical foundations on how firm and IT characteristics explain the market value variations in e-commerce initiatives by examining the announcements of 946 e-commerce initiatives in the public media. Our approach combines the Event study methodology and Decision tree induction to examine the main and interaction effects of IT and firm characteristics on Cumulative Abnormal Returns (CAR). In particular, we generate complex interaction models that can guide e-commerce investment decisions so managers can know, for example, which combination of IT and firm characteristics are more likely to be viewed positively by investors. The selected study variables as well as explanation of the proposed framework are informed by innovation, resource-based view, transaction cost economics and complementarity theories. We have inductively developed a set of propositions that can be deductively tested to assess the validity of our proposed theoretical framework. Hence our study provides an initial roadmap for theory development on e-commerce and CAR.