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Vector-evaluated particle swarm optimization (VEPSO) is a particle swarm optimization (PSO) variant which employs multiple swarms to solve multi-objective optimization problems (MOPs). Each swarm optimizes a single objective and information is passed between swarms using a knowledge transfer strategy (KTS). The recently proposed co-operative VEPSO (CVEPSO) algorithm has been shown to improve the performance...
The notion of cluster ability is often used to determine how strong the cluster structure within a set of data is, as well as to assess the quality of a clustering model. In multivariate applications, however, the cluster ability of a data set can be obscured by irrelevant or noisy features. We study the problem of finding low dimensional projections which maximise the cluster ability of a data set...
Traffic forwarding is a fundamental function in network operations. And forwarding traffic dynamically according to the current situation is attractive to network providers. With its programmability, Software-Defined Networks (SDN) provide network providers dynamic traffic forwarding ability. But SDN only provides trivial flow table to control traffic forwarding that is not an effective way for applications...
As researchers got interested in the vehicular ad hoc networks (VANET), several approaches and uses have been given. One of the most interesting is the network congestion control in an ad hoc environment. Our work consists of introducing a new approach in congestion control of Vehicular Ad Hoc Networks (VANET), using a new model. Our model is based on the hop by hop congestion control methods. This...
Multi-tiered storage, where each tier comprises one type of storage device, e.g., SSD, HDD, is a commonly used approach to achieve both high performance and cost efficiency in large-scale systems that need to store data with vastly different access characteristics. By aligning the access characteristics of the data to the characteristics of the storage devices, higher performance can be achieved for...
Efficient and flexible server provisioning is one of the most important criteria in measuring quality of cloud service. In order to save time and mitigate risk, images are set up as templates. And to provision a server, the cloud service provider replicates a selected image and then customize it to fulfill the server request. Therefore image set-up is vital to the efficiency and flexibility of cloud...
In this paper, we consider the effect of different order relations on the solutions of Multi-Objective Constraint Optimization Problems (MOCOP) with tradeoffs, where the tradeoffs are given in the form of elicited or observed preferences over alternatives. In MOCOP, alternatives are evaluated on a number of objectives (utility scales) and thus correspond to utility vectors, the set of optimal solutions...
We introduce the notion of Optimal Patterns (OPs), defined as the best patterns according to a given user preference, and show that OPs encompass many data mining problems. Then, we propose a generic method based on a Dynamic Constraint Satisfaction Problem to mine OPs, and we show that any OP is characterized by a basic constraint and a set of constraints to be dynamically added. Finally, we perform...
Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear programming (MILP) approaches, especially given the size of data centres. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP or MILP to obtain good results in this context. As a result, the first approaches to address this problem...
In this paper, the use of evolutionary metaheuristic for the management of emergency rescue operations applied to real-word scenarios is analyzed. The problem of selecting the best candidate assets for a given emergency event is addressed. While the problem of deploying one single resource is trivial, its complexity grows when considering more assets to be deployed at the same time. Two objective...
The Minimum Satisfiability Problem (MinSAT) consists in finding the minimum number of satisfied clauses of a CNF formula. This NP-hard problem is an extension of the famous SAT problem and has received less attention than its dual problem MaxSAT (Maximum Satisfiability). One of the MinSAT variants is the Partial MinSAT Problem where some clauses are hard and the others are soft. This variant is used...
Interactions in many real-world phenomena can be explained by a stronghierarchical structure. Typically, this structure or ranking is not known, instead we only have observed outcomes of the interactions, and the goal is toinfer the hierarchy from these observations. Discovering a hierarchy in the context of directed networks can be formulated asfollows: given a graph, partition vertices into levels...
We consider the problem of learning distributed representations for documents from their content and associated tags, and of distributed representations of users from documents and tags provided by users. The documents, words, and tags are represented as low-dimensional vectors and are jointly learned with a multi-layered neural language model. We propose a two stage method where in the first stage...
Constraint Programming (CP) allows to solve constraint satisfaction and optimization problems by building and then exploring a search tree of potential solutions. Potential solutions are generated by firstly selecting a variable and then a value from the given problem, phase known as enumeration. In this context, Autonomous Search (AS) that is a particular case of adaptive systems, enables the problem...
This paper presents the key optimization techniques for an efficient accelerator implementation in an image decoder IP core design for real-time Joint Photographic Experts Group Lossless (JPEG-LS) decoding. Pipeline architecture, frequency multiplication technique and accelerator elements have been utilized to enhance the throughput capability. Improved parameters mapping schemes have been adopted...
In this proposal, we study the problem of understandinghuman sentiments from large scale collection ofInternet images based on both image features and contextualsocial network information (such as friend comments anduser description). Despite the great strides in analyzing usersentiment based on text information, the analysis of sentimentbehind the image content has largely been ignored. Thus, we...
Cascading pull-down menus are common interface elements in many modern graphical interactive applications. Navigation of standard cascading pull-down menus is governed by a combination of Fitts' and Acott-Zhai steering laws, however, recent research has shown that the constraints imposed by the two laws can be overcome by reducing the target distance by either reducing the target distance or increasing...
Machine-Part Cell Formation consists on organizing a plant as a set of cells, each one of them processing machines containing different part types. In recent years, different techniques have been used to solve this problem ranging from exact to approximate methods. This paper focuses on solving new instances of this problem for which no optimal value exists by using the classic Boctor�s mathematical...
In this publication a two-step approach for resourceoptimal sensor scheduling in intelligence is presented. This approach has been developed in close cooperation with subjectmatter experts from the Intelligence, Surveillance, and Reconnaissance (ISR) domain. It constitutes the fundamental basis of a computer-aided assistance system for ISR management personal.
We investigate metric learning in the context of dynamic time warping (DTW), the by far most popular dissimilarity measure used for the comparison and analysis of motion capture data. While metric learning enables a problem-adapted representation of data, the majority of methods has been proposed for vectorial data only. In this contribution, we extend the popular principle offered by the large margin...
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