Computing delay resistant railway timetables

In the past, much research has been dedicated to compute optimum railway timetables. A typical objective has been the minimization of passenger waiting times. But only the planned nominal waiting times have been addressed, whereas delays as they occur in daily operations have been neglected. Delays have been rather treated mainly in an online context and solved as a separate optimization problem, called delay management.We provide the first computational study which aims at computing delay resistant periodic timetables. In particular we assess the delay resistance of a timetable by evaluating it subject to several delay scenarios to which optimum delay management will be applied.We arrive at computing delay resistant timetables by selecting a new objective function which we design to be somehow in the middle of the traditional simple timetabling objective and the sophisticated delay management objective. This is a slight extension of the concept of “light robustness” (LR) as it has been proposed by Fischetti and Monaci [2006. Robust optimization through branch-and-price. In: Proceedings of AIRO]. Moreover, in our application we are able to provide accurate interpretations for the ingredients of LR. We apply this new technique to real-world data of a part of the German railway network of Deutsche Bahn AG. Our computational results suggest that a significant decrease of passenger delays can be obtained at a relatively small price of robustness, i.e. by increasing the nominal travel times of the passengers.     

Discrepancy search for the flexible job shop scheduling problem

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop problem in which each operation must be processed on a given machine chosen among a finite subset of candidate machines. The aim is to find an allocation for each operation and to define the sequence of operations on each machine, so that the resulting schedule has a minimal completion time. We propose a variant of the climbing discrepancy search approach for solving this problem. We also present various neighborhood structures related to assignment and sequencing problems. We report the results of extensive computational experiments carried out on well-known benchmarks for flexible job shop scheduling. The results demonstrate that the proposed approach outperforms the best-known algorithms for the FJSP on some types of benchmarks and remains comparable with them on other ones.     

Vehicle inductive signatures recognition using a Madaline neural network

In this paper, we report results obtained with a Madaline neural network trained to classify inductive signatures of two vehicles classes: trucks with one rear axle and trucks with double rear axle. In order to train the Madaline, the inductive signatures were pre-processed and both classes, named C2 and C3, were subdivided into four subclasses. Thus, the initial classification task was split into four smaller tasks (theoretically) easier to be performed. The heuristic adopted in the training attempts to minimize the effects of the input space non-linearity on the classifier performance by uncoupling the learning of the classes and, for this, we induce output Adalines to specialize in learning one of the classes. The percentages of correct classifications presented concern patterns which were not submitted to the neural network in the training process, and, therefore, they indicate the neural network generalization ability. The results are good and stimulate the maintenance of this research on the use of Madaline networks in vehicle classification tasks using not linearly separable inductive signatures.     

Influence of personality and individual abilities on the sense of presence experienced in anxiety triggering virtual environments

In the literature, there are few studies of the human factors involved in the engagement of presence. The present study aims to investigate the influence of five user characteristics – test anxiety, spatial intelligence, verbal intelligence, personality and computer experience – on the sense of presence. This is the first study to investigate the influence of spatial intelligence on the sense of presence, and the first to use an immersive virtual reality system to investigate the relationship between users’ personality characteristics and presence. The results show a greater sense of presence in test anxiety environments than in a neutral environment. Moreover, high test anxiety students feel more presence than their non-test anxiety counterparts. Spatial intelligence and introversion also influence the sense of presence experienced by high test anxiety students exposed to anxiety triggering virtual environments. These results may help to identify new groups of patients likely to benefit from virtual reality exposure therapy.     

Transmission power and data rate aware routing on wireless networks

Wireless networks can vary both the transmission power and modulation of links. Existing routing protocols do not take transmission power control (TPC) and modulation adaptation (also known as rate adaptation – RA) into account at the same time, even though the performance of wireless networks can be significantly improved when routing algorithms use link characteristics to build their routes. This article proposes and evaluates extensions to routing protocols to cope with TPC and RA. The enhancements can be applied to any link state or distance vector routing protocols. An evaluation considering node density, node mobility and link error show that TPC- and RA-aware routing algorithms improve the average latency and the end-to-end throughput, while consuming less energy than traditional protocols.     

A scalable organization for distributed directories

Although directory-based cache-coherence protocols are the best choice when designing chip multiprocessors with tens of cores on-chip, the memory overhead introduced by the directory structure may not scale gracefully with the number of cores. Many approaches aimed at improving the scalability of directories have been proposed. However, they do not bring perfect scalability and usually reduce the directory memory overhead by compressing coherence information, which in turn results in extra unnecessary coherence messages and, therefore, wasted energy and some performance degradation. In this work, we present a distributed directory organization based on duplicate tags for tiled CMP architectures whose size is independent on the number of tiles of the system up to a certain number of tiles. We demonstrate that this number of tiles corresponds to the number of sets in the private caches. Additionally, we show that the area overhead of the proposed directory structure is 0.56% with respect to the on-chip data caches. Moreover, the proposed directory structure keeps the same information than a non-scalable full-map directory. Finally, we propose a mechanism that takes advantage of this directory organization to remove the network traffic caused by replacements. This mechanism reduces total traffic by 15% for a 16-core configuration compared to a traditional directory-based protocol.     

Fuzzy induced generalized aggregation operators and its application in multi-person decision making

We present a wide range of fuzzy induced generalized aggregation operators such as the fuzzy induced generalized ordered weighted averaging (FIGOWA) and the fuzzy induced quasi-arithmetic OWA (Quasi-FIOWA) operator. They are aggregation operators that use the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized (or quasi-arithmetic) OWA operator. Therefore, they use uncertain information represented in the form of fuzzy numbers, generalized (or quasi-arithmetic) means and order inducing variables. The main advantage of these operators is that they include a wide range of mean operators such as the FOWA, the IOWA, the induced Quasi-OWA, the fuzzy IOWA, the fuzzy generalized mean and the fuzzy weighted quasi-arithmetic average (Quasi-FWA). We further generalize this approach by using Choquet integrals, obtaining the fuzzy induced quasi-arithmetic Choquet integral aggregation (Quasi-FICIA) operator. We also develop an application of the new approach in a strategic multi-person decision making problem.     

Combining Support Vector Machines and simulated annealing for stereovision matching with fish eye lenses in forest environments

We present a novel strategy for computing disparity maps from omni-directional stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. Two of them are identified by applying the powerful Support Vector Machines approach. At a second stage, a stereovision matching process is designed based on the application of four stereovision matching constraints: epipolarity, similarity, uniqueness and smoothness. The epipolarity guides the process. The similarity and uniqueness are mapped once again through the Support Vector Machines, but under a different way to the previous case; after this an initial disparity map is obtained. This map is later filtered by applying the Discrete Simulated Annealing framework where the smoothness constraint is conveniently mapped. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.     

Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation

Atrial Fibrillation (AF) is the most common supraventricular tachyarrhythmia. Recently, it has been suggested that AF is partially organized on its onset and termination, thus being more suitable for antiarrhythmia and to avoid unnecessary therapy. Although several invasive and non-invasive AF organization estimators have been proposed, the organization time course in the first and last minutes of AF has not been quantified yet. The aim of this work is to study non-invasively the organization variation within the first and last minutes of paroxysmal AF. The organization was evaluated making use of sample entropy, which can robustly estimate electrical atrial activity organization from surface ECG recordings. This work proves an organization decrease in the first minutes of AF onset and an increase within the last minute before spontaneous AF termination. These results are in agreement with the conclusions reported by other authors who made use of invasive recordings.