Multi-start iterated local search metaheuristic for the multi-mode resource-constrained project scheduling problem

In this paper a multi-start iterated local search (MS-ILS) algorithm is presented as a new and effective approach to solve the multi-mode resource-constrained project scheduling problem (MRCPSP). The MRCPSP is a well-known project scheduling NP-Hard optimization problem, in which there is a trade-off between the duration of each project activity and the amount of resources they require to be completed. The proposed algorithm generates an initial solution, performs a local search to obtain a local optimum, subsequently, for a certain number of iterations, makes a perturbation to that local optimum and performs a new local search on the perturbed solution. This whole process then restarts with a different initial solution for a certain number of restarts. The algorithm was tested on benchmark instances of projects with 30, 50 and 100 activities from well-known libraries. The obtained results were compared to recent benchmark results from the literature. The proposed algorithm outperforms other solution methods found in related literature for the largest tested instances (100 activities), while for smaller instances it shows to be quite competitive, in terms of the average deviation against known lower bounds.     

Model-driven development for early aspects

Currently, non-functional requirements (NFRs) consume a considerable part of the software development effort. The good news is that most of them appear time and again during system development and, luckily, their solutions can be often described as a pattern independently from any specific application or domain. A proof of this are the current application servers and middleware platforms that can provide configurable prebuilt services for managing some of these crosscutting concerns, or aspects. Nevertheless, these reusable pattern solutions presents two shortcomings, among others: (1) they need to be applied manually; and (2) most of these pattern solutions do not use aspect-orientation, and, since NFRs are often crosscutting concerns, this leads to scattered and tangled representations of these concerns. Our approach aims to overcome these limitations by: (1) using model-driven techniques to reduce the development effort associated to systematically apply reusable solutions for satisfying NFRs; and (2) using aspect-orientation to improve the modularization of these crosscutting concerns. Regarding the first contribution, since the portion of a system related to NFRs is usually significant, the reduction on the development effort associated to these NFRs is also significant. Regarding the second contribution, the use aspect-orientation improves maintenance and evolution of the non-functional requirements that are managed as aspects. An additional contribution of our work is to define a mapping and transition from aspectual requirements to aspect-oriented software architectures, which, in turn, contributes to improve the general issue of systematically relating requirements to architecture. Our approach is illustrated by applying it to a Toll Gate case study.     

An Axiomatic System for Conditional Attribute Implications in Triadic Concept Analysis

In this paper, we define a sound and complete inference system for triadic implications generated from a formal triadic context , where G, M, and B are object, attribute, and condition sets, respectively, and I is a ternary relation . The inference system is expressed as a set of axioms “à la Armstrong.” The type of triadic implications we are considering in this paper is called conditional attribute implication (CAI) and has the following form: , where X and Y are subsets of M, and is a subset of B. Such implication states that Ximplies Y under all conditions in and any subset of it. Moreover, we propose a method to compute CAIs from Biedermann's implications. We also introduce an algorithm to compute the closure of an attribute set X w.r.t. a set Σ of CAIs given a set of conditions.     

Model-based energy-aware data movement optimization in the storage I/O stack

The increasing data demands of applications from various domains and the decreasing relative power cost of CPU computation have gradually exposed data movement cost as the prominent factor of energy consumption in computing systems. The traditional organization of the computer system software into a layered stack, while providing a straightforward modularity, poses a significant challenge for the global optimization of data movement in particular and, thus, the energy efficiency in general. Optimizing the energy efficiency of data movement in large-scale systems is a difficult tasks because it depends on a complex interplay of various factors at different system layers. In this work, we address the challenge of optimizing the data movement of the storage I/O stack in a holistic manner. Our approach consists of a model-based system driver that obtains the current I/O power regime and adapts the CPU frequency level according to this information. On the one hand, for simplifying the understanding of the relation between data movement and energy efficiency, this paper proposes novel energy prediction models for data movement based on series of runtime metrics from several I/O stack layers. We provide an in-depth study of the energy consumption in the data path, including the identification and analysis of power and performance regimes that synthesize the energy consumption patterns in a cross-layer approach. On the other hand, we propose and prototype a kernel driver that exploits data movement awareness for improving the current CPU-centric energy management.     

Proxy-based sliding mode control on platform of 3 degree of freedom (3-DOF)

Proxy-based sliding mode control, created by Ryo Kikuuwe and Hideo Fujimoto, combines the advantages of sliding mode control and proportional integral derivative controller. This paper implements this control algorithm on a platform of 3 degrees of freedom (3-DOF) driven by electropneumatic actuators with proportional flow valves. This paper presents an extension of proxy-based sliding mode control. This time it is implemented on a parallel robot. Despite the robot being a coupled system, is reached a perfect decoupled control. The simulations in MSC-ADAMS and experimental results demonstrate good tracking.     

The role of the environment in agreement technologies

The notion of Multi-Agent System environment is currently considered as a mediating entity, functioning as enabler but possibly also as a manager and constrainer of agent actions, perceptions, and interactions. In this paper, we analyze how the environment could be a first class abstraction to support the building, the development and the management of Agreements in decentralized and open systems between autonomous agents. To this aim we analyze the synergies between the environment and the foundational dimensions of agreement technologies such as semantics, norms, organizations, argumentation & negotiation, trust.     

EMOTAG: AN APPROACH TO AUTOMATED MARKUP OF EMOTIONS IN TEXTS

This paper presents an approach to the automated markup of texts with emotional labels. The approach considers two possible representations of emotions in parallel: emotional categories (emotional tags used to refer to emotions) and emotional dimensions (measures that try to model the essential aspects of emotions numerically). For each representation, a corpus of example texts previously annotated by human evaluators is mined for an initial assignment of emotional features to words. This results in a list of emotional words (LEW) which becomes a useful resource for later automated markup. The algorithm proposed for the automated markup of text closely mirrors the steps taken during feature extraction, employing a combination of the LEW resource and the ANEW word list for the actual assignment of emotional features, and WordNet for knowledge‐based expansion of words not occurring in either and an ontology of emotional categories. The algorithm for automated markup is tested and the results are discussed with respect to three main issues: the relative adequacy of each of the representations used, correctness and coverage of the proposed algorithm, and additional techniques and solutions that may be employed to improve the results. The average percentage of success obtained by our approach when it marks up with emotional dimensions is around 80% and when it marks up with emotional categories is around 50%. The main contribution of the approach presented in this paper is that it allows dimensions and categories at different levels of abstraction to operate simultaneously during markup.     

Analyzing scalability of parallel systems with unbalanced workload

This paper presents a new formulation of the isoefficiency function which can be applied to parallel systems executing balanced or unbalanced workloads. This new formulation allows analyzing the scalability of parallel systems under either balanced or unbalanced workloads. Finally, the validity of this new metric is evaluated using some synthetic benchmarks. The experimental results allow assessing the importance of considering the unbalanced workloads while analyzing the scalability of parallel systems.     

Scalable shot boundary detection

In a Content-based Video Retrieval system, the shot boundary detection is an unavoidable stage. Such a high demanding task needs a deep study from a computational point of view to allow finding suitable optimization strategies. This paper presents different strategies implemented on both a shared-memory symmetric multiprocessor and a Beowulf cluster, and the evaluation of two different programming paradigms: shared-memory and message passing. Several approaches for video segmentation as well as data access are tested in the experiments that also consider load balancing issues.