A Preemptive Algorithm for Maximizing Disjoint Paths on Trees

We consider the on-line version of the maximum vertex disjoint path problem when the underlying network is a tree. In this problem, a sequence of requests arrives in an on-line fashion, where every request is a path in the tree. The on-line algorithm may accept a request only if it does not share a vertex with a previously accepted request. The goal is to maximize the number of accepted requests. It is known that no on-line algorithm can have a competitive ratio better than Ω(log n) for this problem, even if the algorithm is randomized and the tree is simply a line. Obviously, it is desirable to beat the logarithmic lower bound. Adler and Azar (Proc. of the 10th ACM-SIAM Symposium on Discrete Algorithm, pp. 1–10, 1999) showed that if preemption is allowed (namely, previously accepted requests may be discarded, but once a request is discarded it can no longer be accepted), then there is a randomized on-line algorithm that achieves constant competitive ratio on the line. In the current work we present a randomized on-line algorithm with preemption that has constant competitive ratio on any tree. Our results carry over to the related problem of maximizing the number of accepted paths subject to a capacity constraint on vertices (in the disjoint path problem this capacity is 1). Moreover, if the available capacity is at least 4, randomization is not needed and our on-line algorithm becomes deterministic.     

Podcasting in education: Are students as ready and eager as we think they are?

Instructors in higher education are disseminating instructional content via podcasting, as many rally behind the technology’s potential benefits. Others have expressed concern about the risks of deleterious effects that might accompany the adoption of podcasting, such as lower class attendance. Yet, relatively few studies have investigated students’ perceptions of podcasting for educational purposes, especially in relation to different podcasting forms: repetitive and supplemental. The present study explored students’ readiness and attitudes towards these two forms of podcasting to provide fundamental information for future researchers and educators. The results indicated that students may not be as ready or eager to use podcasting for repetitive or supplemental educational purposes as much as we think they are, but they could be persuaded.     

Performance analysis of available bandwidth estimation tools for grid networks

Modern large-scale grid computing systems for processing advanced science and engineering applications rely on geographically distributed clusters. In such highly distributed environments, estimating the available bandwidth between clusters is a key issue for efficient task scheduling. We analyze the performance of two well known available bandwidth estimation tools, pathload and abget, with the aim of using them in grid environments. Differently than previous investigations (Jain et al., ; Shriram et al., in Passive and active network measurement: 6th international workshop, PAM 2005. Springer, Berlin, 2005), our experiments consider a series of relevant metrics such as accuracy of the estimation, convergence time, degree of intrusion in the grid links, and ability to handle multiple simultaneous estimations. No previous work has analyzed the use of available bandwidth tools for the derivation of efficient grid scheduling.     

Fuzzy grey relational analysis for software effort estimation

Accurate and credible software effort estimation is a challenge for academic research and software industry. From many software effort estimation models in existence, Estimation by Analogy (EA) is still one of the preferred techniques by software engineering practitioners because it mimics the human problem solving approach. Accuracy of such a model depends on the characteristics of the dataset, which is subject to considerable uncertainty. The inherent uncertainty in software attribute measurement has significant impact on estimation accuracy because these attributes are measured based on human judgment and are often vague and imprecise. To overcome this challenge we propose a new formal EA model based on the integration of Fuzzy set theory with Grey Relational Analysis (GRA). Fuzzy set theory is employed to reduce uncertainty in distance measure between two tuples at the k ^th continuous feature ( | ( x_o(k) - x_i(k) | ) \left( {\left| {\left( {{x_o}(k) - {x_i}(k)} \right.} \right|} \right) .GRA is a problem solving method that is used to assess the similarity between two tuples with M features. Since some of these features are not necessary to be continuous and may have nominal and ordinal scale type, aggregating different forms of similarity measures will increase uncertainty in the similarity degree. Thus the GRA is mainly used to reduce uncertainty in the distance measure between two software projects for both continuous and categorical features. Both techniques are suitable when relationship between effort and other effort drivers is complex. Experimental results showed that using integration of GRA with FL produced credible estimates when compared with the results obtained using Case-Based Reasoning, Multiple Linear Regression and Artificial Neural Networks methods.     

The challenge of conceptual modeling for product–service systems: status-quo and perspectives for reference models and modeling languages

Confronted with decreasing margins and a rising customer demand for integrated solutions, manufacturing companies integrate complementary services into their portfolio. Offering value bundles (consisting of services and physical goods) takes place in integrated product–service systems, spanning the coordinated design and delivery of services and physical goods for customers. Conceptual Modeling is an established approach to support and guide such efforts. Using a framework for the design and delivery of value bundles as an analytical lens, this study evaluates the current support of reference models and modeling languages for setting up conceptual models for an integrated design and delivery of value bundles. Consecutively, designing modeling languages and reference models to fit the requirements of conceptual models in product–service systems are presented as upcoming challenges in Service Research. To guide further research, first steps are proposed by exemplarily integrating reference models and modeling languages stemming from the service and manufacturing domains.     

Shrinkage estimation in general linear models

We propose a James-Stein-type shrinkage estimator for the parameter vector in a general linear model when it is suspected that some of the parameters may be restricted to a subspace. The James-Stein estimator is shown to demonstrate asymptotically superior risk performance relative to the conventional least squares estimator under quadratic loss. An extensive simulation study based on a multiple linear regression model and a logistic regression model further demonstrates the improved performance of this James-Stein estimator in finite samples. The application of this new estimator is illustrated using Ontario newborn infants data spanning four fiscal years.     

Learning a color distance metric for region-based image segmentation

In this paper we describe an experiment where we studied empirically the application of a learned distance metric to be used as discrimination function for an established color image segmentation algorithm. For this purpose we chose the Mumford–Shah energy functional and the Mahalanobis distance metric. The objective was to test our approach in an objective and quantifiable way on this specific algorithm employing this particular distance model, without making generalization claims. The empirical validation of the results was performed in two experiments: one applying the resulting segmentation method on a subset of the Berkeley Image Database, an exemplar image set possessing ground-truths and validating the results against the ground-truths using two well-known inter-cluster validation methods, namely, the Rand and BGM indexes, and another experiment using images of the same context divided into training and testing set, where the distance metric is learned from the training set and then applied to segment all the images. The obtained results suggest that the use of the specified learned distance metric provides better and more robust segmentations, even if no other modification of the segmentation algorithm is performed.     

Tactical combat movements: inter-individual variation in performance due to the effects of load carriage

An examination into the effects of carried military equipment on the performance of two tactical combat movement simulations was conducted. Nineteen Airfield Defence Guards performed a break contact (five 30-m sprints) and a fire and movement simulation (16 6-m bounds) in five load conditions (10–30 kg). Heavier loads significantly increased movement duration on the break contact (0.8%/kg load) and fire and movement (1.1%/kg). Performance deterioration was observed from the beginning to the end of the series of movements (bounds or sprints) with deterioration becoming significantly greater in heavier load conditions. Inter-individual variation between slower and faster participants showed a range in load effects; 0.6, 0.8%/kg for fast and 1.0, 1.4%/kg for slow (break contact, fire and movement, respectively). Velocity profiles revealed that the initial acceleration and peak velocity were the primary determinants of performance. As the duration of these tactical combat movements reflects periods of heightened vulnerability, these findings highlight important implications for commanders.

Practitioner Summary: Increasing amounts of carried military equipment impairs the performance of tactical combat movements. Examination of inter-individual variation in velocity profiles identified that the initial acceleration and the peak velocity achieved during sprints and bounds are key determinants of overall performance.     

Resilient overlay network for real-time interactive multimedia sessions in corporate networks

Real-time interactive multimedia communications are becoming increasingly useful for education, business, e-commerce and e-government, providing an enriched user experience in teleconferencing, e-meetings, distance training and product demonstrations. Large corporations are usually located at several sites, so real-time multipoint sessions within corporations are especially difficult. IP multicast is available or feasible within each site of an organization. Thus, corporate networks can be considered as various multicast-capable networks interconnected through a wide area network without multicast connectivity. This paper proposes a resilient self-managed overlay network to support real-time multipoint interactive sessions within corporate networks. The proposed overlay takes advantage of the configuration of corporate networks to self-organize and provide an efficient media delivery service, making use of multicast communications wherever available. Various self-healing techniques are implemented allowing for the continuity of ongoing sessions in spite of network disruptions and entity failures. Extensive simulations and tests have been carried out to assess the performance and resilience of the overlay facing several types of disruptions.