A generic optimising feature extraction method using multiobjective genetic programming

In this paper, we present a generic, optimising feature extraction method using multiobjective genetic programming. We re-examine the feature extraction problem and show that effective feature extraction can significantly enhance the performance of pattern recognition systems with simple classifiers. A framework is presented to evolve optimised feature extractors that transform an input pattern space into a decision space in which maximal class separability is obtained. We have applied this method to real world datasets from the UCI Machine Learning and StatLog databases to verify our approach and compare our proposed method with other reported results. We conclude that our algorithm is able to produce classifiers of superior (or equivalent) performance to the conventional classifiers examined, suggesting removal of the need to exhaustively evaluate a large family of conventional classifiers on any new problem. (C) 2010 Elsevier B.V. All rights reserved

Data mining in soft computing framework: a survey

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included

Combining machine learning and metaheuristics algorithms for classification method PROAFTN

© Crown 2019. The supervised learning classification algorithms are one of the most well known successful techniques for ambient assisted living environments. However the usual supervised learning classification approaches face issues that limit their application especially in dealing with the knowledge interpretation and with very large unbalanced labeled data set. To address these issues fuzzy classification method PROAFTN was proposed. PROAFTN is part of learning algorithms and enables to determine the fuzzy resemblance measures by generalizing the concordance and discordance indexes used in outranking methods. The main goal of this chapter is to show how the combined meta-heuristics with inductive learning techniques can improve performances of the PROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems

MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation

BACKGROUND: The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polymorphisms in DNA and genome-wide analysis of mRNA concentrations. Local array data management solutions are instrumental for efficient processing of the results and for subsequent uploading of data and annotations to a global certified data repository at the EBI (ArrayExpress) or the NCBI (GeneOmnibus). DESCRIPTION: To facilitate and accelerate annotation of high-throughput expression profiling experiments, the Microarray Information Management and Annotation System (MIMAS) was developed. The system is fully compliant with the Minimal Information About a Microarray Experiment (MIAME) convention. MIMAS provides life scientists with a highly flexible and focused GeneChip data storage and annotation platform essential for subsequent analysis and interpretation of experimental results with clustering and mining tools. The system software can be downloaded for academic use upon request. CONCLUSION: MIMAS implements a novel concept for nation-wide GeneChip data management whereby a network of facilities is centered on one data node directly connected to the European certified public microarray data repository located at the EBI. The solution proposed may serve as a prototype approach to array data management between research institutes organized in a consortium

Water filtration by using apple and banana peels as activated carbon

Water filter is an important devices for reducing the contaminants in raw water. Activated from charcoal is used to absorb the contaminants. Fruit peels are some of the suitable alternative carbon to substitute the charcoal. Determining the role of fruit peels which were apple and banana peels powder as activated carbon in water filter is the main goal. Drying and blending the peels till they become powder is the way to allow them to absorb the contaminants. Comparing the results for raw water before and after filtering is the observation. After filtering the raw water, the reading for pH was 6.8 which is in normal pH and turbidity reading recorded was 658 NTU. As for the colour, the water becomes more clear compared to the raw water. This study has found that fruit peels such as banana and apple are an effective substitute to charcoal as natural absorbent

Negotiating Tradition - The pragmatics of international deliberations on Cultural Property

Communicative interactions in international negotiations on cultural property not only provide information about the emergence and proliferation of arguments, rhetorics, and registers, but also permit valuable insights into actors’ positions, strategies and alliances. They significantly influence local and national practices and views related to cultural property debates. What can be gained from a deep analysis of the communicative patterns and strategies that actors engage in – the entailing text and talk of negotiations – is a better understanding of the process itself: how do different actors argue, what kind of strategies and rhetorics do they use, to which instruments and institutions do they refer, and in what way do actors react to each other? An analysis of communicative interactions contributes to the question of how international negotiations work. The analytic inclusion of sociolinguistic practices allows insights into positions, strategies, and perspectives pertaining to cultural property. By looking at not only what actors say, but also at how and in what contexts they do so, it is possible to make more accurate statements about their positions and perceptions in cultural property debates. As these communicative interactions influence outcomes considerably, an approach from linguistic anthropology is not only beneficial for an understanding of specific negotiations, but also for the analysis of broader cultural property issues.Communicative interactions in international negotiations on cultural property not only provide information about the emergence and proliferation of arguments, rhetorics, and registers, but also permit valuable insights into actors’ positions, strategies and alliances. They significantly influence local and national practices and views related to cultural property debates. What can be gained from a deep analysis of the communicative patterns and strategies that actors engage in – the entailing text and talk of negotiations – is a better understanding of the process itself: how do different actors argue, what kind of strategies and rhetorics do they use, to which instruments and institutions do they refer, and in what way do actors react to each other? An analysis of communicative interactions contributes to the question of how international negotiations work. The analytic inclusion of sociolinguistic practices allows insights into positions, strategies, and perspectives pertaining to cultural property. By looking at not only what actors say, but also at how and in what contexts they do so, it is possible to make more accurate statements about their positions and perceptions in cultural property debates. As these communicative interactions influence outcomes considerably, an approach from linguistic anthropology is not only beneficial for an understanding of specific negotiations, but also for the analysis of broader cultural property issues