177,425 research outputs found
Evolutionary Optimization
No full textThe emergence of different metaheuristics and their new variants in recent years has made the definition of the term Evolutionary Algorithms unclear. Originally, it was coined to put a group of stochastic search algorithms that mimic natural evolution together. While some people would still see it as a specific term devoted to this group of algorithms, including Genetic Algorithms, Genetic Programming, Evolution Strategies, Evolutionary Programming, and to a lesser extent Differential Evolution and Estimation of Distribution Algorithms, many others would regard “Evolutionary Algorithms” as a general term describing population-based search methods that involve some form of randomness and selection. In this chapter, we re-visit the fundamental question of “what is an Evolutionary Algorithm?” not only from the traditional viewpoint but also the wider, more modern perspectives relating it to other areas of Evolutionary Computation. To do so, apart from discussing the main characteristics of this family of algorithms we also look at Memetic Algorithms and the Swarm Intelligence algorithms. From our discussion, we see that establishing semantic borders between these algorithm families is not always easy, nor necessarily useful. It is anticipated that they will further converge as the research from these areas cross-fertilizes each other.Christian Blum, Raymond Chiong, Maurice Clerc, Kenneth De Jong, Zbigniew Michalewicz, Ferrante Neri and Thomas Weis
Variants of Evolutionary Algorithms for Real-World Applications
No full textEvolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation
ALICE: adaptive learning via interactive, collaborative and emotional approaches
No full textGrid technologies are rising as the next generation of Internet by defining a powerful computing paradigm by analogy with the electric Power Grid. A Grid user is able to use his private workplace to invoke any application from a remote system, use the system best suited for executing that application, access data securely and consistently from remote sites, exploit multiple systems to complete economically complex tasks or to solve large problems that exceed the capacity of a single system. Grid could be used as a technology “glue” providing users with a uniform way to access resources by means of several devices. These technologies can provide, in a natural way, a support for Technology Enhanced Learning (TEL) by enabling new learning environments based on collaboration, social interaction, experience, realism, personalisation, ubiquity, accessibility and contextualisation. Nevertheless, to be effectively used in TEL, Grid must be complemented with other elements like semantics and educational modelling so bringing to the concept of “Grid for Learning” whose description is the object of this paper
Estimation of graphical models using the L1,2 norm
No full textFull text access from Treasures at UT Dallas is restricted to current UTD affiliates.Supplementary material available at publisher's website.Gaussian graphical models are recently used in economics to obtain networks of dependence among agents. A widely used estimator is the graphical least absolute shrinkage and selection operator (GLASSO), which amounts to a maximum likelihood estimation regularized using the (Formula presented.) matrix norm on the precision matrix Ω. The (Formula presented.) norm is a LASSO penalty that controls for sparsity, or the number of zeros in Ω. We propose a new estimator called structured GLASSO (SGLASSO) that uses the (Formula presented.) mixed norm. The use of the (Formula presented.) penalty controls for the structure of the sparsity in Ω. We show that when the network size is fixed, SGLASSO is asymptotically equivalent to an infeasible GLASSO problem which prioritizes the sparsity-recovery of high-degree nodes. Monte Carlo simulation shows that SGLASSO outperforms GLASSO in terms of estimating the overall precision matrix and in terms of estimating the structure of the graphical model. In an empirical illustration using a classic firms' investment data set, we obtain a network of firms' dependence that exhibits the core–periphery structure, with General Motors, General Electric and US Steel forming the core group of firms.Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF‐2017S1A5A2A01023679).Naveen Jindal School of Managemen
A comparative study of the performance of seven- and 63-chip optical code-division multiple-access encoders and decoders based on superstructured fiber Bragg gratings
No full textWe report a range of elementary optical coding and decoding experiments employing superstructured fiber Bragg grating (SSFBG) components: first, we perform a comparative study of the relative merits of bipolar and unipolar coding: decoding schemes and show that the SSFBG approach allows high-quality unipolar and bipolar coding. A performance close to that-theoretically predicted for seven-chip, 160-Gchip/s M-sequence codes is obtained. Second, we report the fabrication and performance of 63-chip, 160-Gchip/s, bipolar Gold sequence grating pairs. These codes are at least eight times longer than those generated by any other scheme based on fiber grating technology so far reported. Last, we describe a range of transmission system experiments for both the seven- and 63-bit bipolar grating pairs. Error-free performance is obtained over transmission distances of ~25 km of standard fiber. In addition, we have demonstrated error-free performance under multiuser operation (two simultaneous users). Our results highlight the precision and flexibility of our particular grating writing process and show that SSFBG technology represents a promising technology not just for optical code division multiple access (OCDMA) but also for an extended range of other pulse-shaping optical processing applications
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Clinical utility of tolvaptan in the management of hyponatremia in heart failure patients.
No full textVariants of Evolutionary Algorithms for Real-World Applications
No full textEvolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book "Variants of Evolutionary Algorithms for Real-World Applications" aims to promote the practitioner's view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.Raymond Chiong, Thomas Weise and Zbigniew Michalewiczhttp://trove.nla.gov.au/work/16340961
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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