2,052 research outputs found

    An enhanced classifier system for autonomous robot navigation in dynamic environments

    Get PDF
    In many cases, a real robot application requires the navigation in dynamic environments. The navigation problem involves two main tasks: to avoid obstacles and to reach a goal. Generally, this problem could be faced considering reactions and sequences of actions. For solving the navigation problem a complete controller, including actions and reactions, is needed. Machine learning techniques has been applied to learn these controllers. Classifier Systems (CS) have proven their ability of continuos learning in these domains. However, CS have some problems in reactive systems. In this paper, a modified CS is proposed to overcome these problems. Two special mechanisms are included in the developed CS to allow the learning of both reactions and sequences of actions. The learning process has been divided in two main tasks: first, the discrimination between a predefined set of rules and second, the discovery of new rules to obtain a successful operation in dynamic environments. Different experiments have been carried out using a mini-robot Khepera to find a generalised solution. The results show the ability of the system to continuous learning and adaptation to new situations.Publicad

    Data-driven Soft Sensors in the Process Industry

    Get PDF
    In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

    Assembly Line

    Get PDF
    An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

    Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

    Get PDF
    While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

    Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

    Get PDF
    While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

    Insights into Genome Functional Organisation through the Analysis of Interaction Networks

    Get PDF
    Using computational techniques to identify orthology and operon structure, it is possible to find functional interactions between genes, which, together, define the genetic interactome. These large networks contain information about the relationships between phenotypes in organisms as genes responsible for related abilities are often co-regulated and reasserting of these genes can be detected in the operon structure. However, these networks are too large to analyse by hand In order to practically analyse the networks, a computational tool, gisql, was developed and, using this tool, the connectivity patterns in the genetic interactome can be analysed to understand high-level organisation of the genome and to narrow the list of candidate genes for wet lab analysis. The many strains of Escherichia coli are interesting subjects as there are many sequenced strains and they show highly variable pathogenic abilities. Analysis shows that the pathogenic genes have a strong tendency to connect to genes ubiquitous in the E. coli pan-genome. The Rhizobiales, including Sinorhizobium meliloti and Ochrobactrum anthropi, are multi-chromosomal eukaryote-associated bacteria and a significant history of horizontal transfer. Regions of the pSymB megaplasmid of S. meliloti which cannot be deleted via transposon-targeted homologous recombination were shown to be significantly more connected to the main chromosome. Targets for functional complementation of deletions in pSymB in S. meliloti using genes from O. anthropi were identified and unusual connectivity patterns of orthologs were identified. Finally, a putative cytokinin receptor in the Rhizobiaceæ, likely involved in symbiosis with plant hosts, was identified. Thanks to the flexibility of gisql, these analyses were straight-forward and fast to develop
    corecore