An overview of applied robust methods

Applying robust methods to operational risk modeling

The Journal of Operational Risk ◽

10.21314/jop.2006.003 ◽

2006 ◽

Vol 1 (1) ◽

pp. 27-41 ◽

Cited By ~ 21

Author(s):

Anna Chernobai ◽

Svetlozar Rachev

Keyword(s):

Operational Risk ◽

Risk Modeling ◽

Robust Methods ◽

Operational Risk Modeling

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Robust methods in analysis of natural language data

Natural Language Engineering ◽

10.1017/s1351324902002942 ◽

2002 ◽

Vol 8 (2-3) ◽

pp. 93-96

Author(s):

AFZAL BALLIM ◽

VINCENZO PALLOTTA

Keyword(s):

Information Systems ◽

Natural Language ◽

Automated Analysis ◽

Approximate Analysis ◽

Robust Methods ◽

Analysis Techniques ◽

Intelligent Information Systems ◽

Recent Interest ◽

Language Data ◽

Intelligent Information

The automated analysis of natural language data has become a central issue in the design of intelligent information systems. Processing unconstrained natural language data is still considered as an AI-hard task. However, various analysis techniques have been proposed to address specific aspects of natural language. In particular, recent interest has been focused on providing approximate analysis techniques, assuming that when perfect analysis is not possible, partial results may be still very useful.

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Cyclodextrins as Supramolecular Recognition Systems: Applications in the Fabrication of Electrochemical Sensors

Materials ◽

10.3390/ma14071668 ◽

2021 ◽

Vol 14 (7) ◽

pp. 1668

Author(s):

Bronach Healy ◽

Tian Yu ◽

Daniele C. da Silva Alves ◽

Cynthia Okeke ◽

Carmel B. Breslin

Keyword(s):

Chiral Recognition ◽

Electrochemical Sensors ◽

Intramolecular Interactions ◽

Robust Methods ◽

Short Introduction ◽

Reduced Graphene ◽

Target Analytes ◽

Recognition Systems ◽

Covalent Interactions ◽

Target Analyte

Supramolecular chemistry, although focused mainly on noncovalent intermolecular and intramolecular interactions, which are considerably weaker than covalent interactions, can be employed to fabricate sensors with a remarkable affinity for a target analyte. In this review the development of cyclodextrin-based electrochemical sensors is described and discussed. Following a short introduction to the general properties of cyclodextrins and their ability to form inclusion complexes, the cyclodextrin-based sensors are introduced. This includes the combination of cyclodextrins with reduced graphene oxide, carbon nanotubes, conducting polymers, enzymes and aptamers, and electropolymerized cyclodextrin films. The applications of these materials as chiral recognition agents and biosensors and in the electrochemical detection of environmental contaminants, biomolecules and amino acids, drugs and flavonoids are reviewed and compared. Based on the papers reviewed, it is clear that cyclodextrins are promising molecular recognition agents in the creation of electrochemical sensors, chiral sensors, and biosensors. Moreover, they have been combined with a host of materials to enhance the detection of the target analytes. Nevertheless, challenges remain, including the development of more robust methods for the integration of cyclodextrins into the sensing unit.

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