A propositional probabilistic logic with discrete linear time for reasoning about evidence

The aim of the paper is to present a sound, strongly complete and decidable probabilistic temporal logic that can model reasoning about evidence. The formal system developed here is actually a solution of a problem proposed by Halpern and Pucella (J Artif Intell Res 26:1–34, 2006).     

Using column generation to solve parallel machine scheduling problems with minmax objective functions

In this paper we consider the parallel machine scheduling problem of minimizing an objective function of the minmax type, like maximum lateness, subject to release dates, deadlines, and/or generalized precedence constraints. We use a destructive strategy to compute a lower bound. Here we test the feasibility of a decision problem by applying column generation to compute a bound on the number of machines that we need to feasibly accommodate all jobs. After having derived the lower bound, we try to find a matching upper bound by identifying a feasible schedule with objective function value equal to this lower bound. Our computational results show that our lower bound is so strong that this is almost always possible. We are able to solve problems with up to 160 jobs and 10 machines in 10 minutes on average.     

A dynamic-programming-based exact algorithm for general single-machine scheduling with machine idle time

This paper proposes an efficient exact algorithm for the general single-machine scheduling problem where machine idle time is permitted. The algorithm is an extension of the authors’ previous algorithm for the problem without machine idle time, which is based on the SSDP (Successive Sublimation Dynamic Programming) method. We first extend our previous algorithm to the problem with machine idle time and next propose several improvements. Then, the proposed algorithm is applied to four types of single-machine scheduling problems: the total weighted earliness-tardiness problem with equal (zero) release dates, that with distinct release dates, the total weighted completion time problem with distinct release dates, and the total weighted tardiness problem with distinct release dates. Computational experiments demonstrate that our algorithm outperforms existing exact algorithms and can solve instances of the first three problems with up to 200 jobs and those of the last problem with up to 80 jobs.     

Finding a robust assignment of flights to gates at Amsterdam Airport Schiphol

In this paper we investigate the gate assignment problem as it appears at Amsterdam Airport Schiphol (AAS). Currently, the gate planners spend many hours on adjusting the automatically generated planning during the day of operation to make it proof against small deviations from the schedule. To alleviate this problem, we aim at finding a robust solution, given the planned arrivals and departures for the next day. We present a completely new integer linear programming formulation that is based on so-called gate plans. Each gate plan consists of a subset of the flights that can be assigned to a single gate of the corresponding type; gates with identical characteristics are aggregated in gate types. The gate assignment problem then boils down to selecting the best subset of gate plans such that each flight belongs to one selected gate plan, and such that the number of selected gate plans for a certain type of gate is equal to the number of gates of this type. In the first phase, we solve the LP-relaxation through column generation, and we describe specific features to find a very good solution to the ILP quickly. This solution is then handed to the planners at AAS in order to assign gate plans to physical gates. This consists of a number of relatively small problems that can be solved by hand and in which additional operational constraints can be incorporated. We also present the possibility of directly assigning flights to physical gates using the column generation formulation, where we then take into account other criteria as well. Computational results with real-life data provided by AAS are promising and indicate that the algorithm is able to solve real-life instances within rather small running times.     

Extracting trust information from security system of a service

The issue of trust is a research problem in emerging open environments, such as ubiquitous networks. Such environments are highly dynamic and they contain diverse number of services and autonomous entities. Entities in open environments have different security needs from services. Trust computations related to the security systems of services necessitate information that meets needs of each entity. Obtaining such information is a challenging issue for entities. In this paper, we propose a model for extracting trust information from the security system of a service based on the needs of an entity. We formally represent security policies and security systems to extract trust information according to needs of an entity. The formal representation ensures an entity to extract trust information about a security property of a service and trust information about whole security system of the service. The proposed model is applied to Dental Clinic Patient Service as a case study with two scenarios. The scenarios are analyzed experimentally with simulations. The experimental evaluation shows that the proposed model provides trust information related to the security system of a service based on the needs of an entity and it is applicable in emerging open environments.     

Ambiguity-free edge-bundling for interactive graph visualization

Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational data sets (e.g., transportation networks, citation networks, or social networks). Graphs with dense edges, however, are difficult to visualize because fast layout and good clarity are not always easily achieved. When the number of edges is large, edge bundling can be used to improve the clarity, but in many cases, the edges could be still too cluttered to permit correct interpretation of the relations between nodes. In this paper, we present an ambiguity-free edge-bundling method especially for improving local detailed view of a complex graph. Our method makes more efficient use of display space and supports detail-on-demand viewing through an interactive interface. We demonstrate the effectiveness of our method with public coauthorship network data.     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.     

Retrospective adaptive prefetching for interactive Web GIS applications

A major task of a Web GIS (Geographic Information Systems) system is to transfer map data to client applications over the Internet, which may be too costly. To improve this inefficient process, various solutions are available. Caching the responses of the requests on the client side is the most commonly implemented solution. However, this method may not be adequate by itself. Besides caching the responses, predicting the next possible requests from a client and updating the cache with responses for those requests together provide a remarkable performance improvement. This procedure is called “prefetching” and makes caching mechanisms more effective and efficient. This paper proposes an efficient prefetching algorithm called Retrospective Adaptive Prefetch (RAP), which is constructed over a heuristic method that considers the former actions of a given user. The algorithm reduces the user-perceived response time and improves user navigation efficiency. Additionally, it adjusts the cache size automatically, based on the memory size of the client’s machine. RAP is compared with four other prefetching algorithms. The experiments show that RAP provides better performance enhancements than the other methods.     

Provably correct and complete transaction rules for updating 3D city models

The shapes of our cities change very frequently. These changes have to be reflected in data sets representing urban objects. However, it must be assured that frequent updates do not affect geometric-topological consistency. This important aspect of spatial data quality guarantees essential assumptions on which users and applications of 3D city models rely: viz. that objects do not intersect, overlap or penetrate mutually, or completely cover one another. This raises the question how to guarantee that geometric-topological consistency is preserved when data sets are updated. Hence, there is a certain risk that plans and decisions which are based on these data sets are erroneous and that the tremendous efforts spent for data acquisition and updates become vain. In this paper, we solve this problem by presenting efficient transaction rules for updating 3D city models. These rules guarantee that geometric-topological consistency is preserved (Safety) and allow for the generation of arbitrary consistent 3D city models (Completeness). Safety as well as completeness is proven with mathematical rigor, guaranteeing the reliability of our method. Our method is applicable to 3D city models, which define—besides the terrain surface—complex spatial objects like buildings with rooms and storeys as interior structures, as well as bridges and tunnels. Those objects are represented as aggregations of solids, and their surfaces are complex from a topology point of view. 3D GIS models like CityGML, which are widely used to represent cities, provide the means to define semantics, geometry and topology, but do not address the problem of maintaining consistency. Hence, our approach complements CityGML.     

Identifying the criterion spontaneously minimized during the take-off phase of a sub-maximal long jump through optimal synthesis

Optimal synthesis of human movement or the prediction of the kinematics of a new movement require not only that the multi-body system be modeled but also that a performance criterion is specified. For sub-maximal movements the selection of a suitable performance criterion, able to generate realistic dynamic behavior is difficult. A two-dimensional simulation model of the take-off phase of a sub-maximal long jump was developed to study the effect of criterion choice on the realism of simulated movements. A parametric optimization technique was employed to obtain solutions to the constrained equations of motion. Seven different criteria were evaluated, by comparing simulated movements with an actual performance, to identify the criterion which most closely approximated that spontaneously minimized by the athlete. Synthesis of the take-off phase of a sub-maximal long jump was found to be sensitive to the chosen criterion, with a criterion based on minimizing joint intersegmental forces found to perform well.