A statistical pattern recognition approach for the classification of cooking stages. The boiling water case

Tabacchi, Marco Elio; Asensio, C.; Pavón, Ignacio; Recuero, M.; Mir, Junaid; Artal, M.C.

doi:10.1016/j.apacoust.2013.03.001

Cited by 13 publications

(8 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Clustering or cluster analysis is the process of grouping a set of objects into classes of similar objects. This form of analysis has been extensively studied in many areas, including statistics (Tabacchi et al, 2013), machine learning (Zhao et al, 2013), pattern recognition (Nguyen et al, 2013;Tao et al, 2012), and image processing (Bayro-Corrochano and Eklundh, 2011), but their application in environment area was very limited. Objects in any one cluster share some similarity.…”

Section: Classification Methodsmentioning

confidence: 99%

A real time method of contaminant classification using conventional water quality sensors

Liu

Han

Smith

et al. 2015

Journal of Environmental Management

View full text Add to dashboard Cite

Section: Classification Methodsmentioning

confidence: 99%

A real time method of contaminant classification using conventional water quality sensors

Liu

Han

Smith

et al. 2015

Journal of Environmental Management

View full text Add to dashboard Cite

“…Meanwhile, the second method used for event detection is based on signal processing and data-driven technique. Many studies have focused on the development of data-driven estimation model detection algorithm such as statistical, pattern-based recognition, machine learning approach, and image processing to detect contaminants based on real-time water quality measurements [402][403][404][405]. Contamination event detection in WDS has become a challenging research topic, in accordance with improved water system analysis.…”

Section: Algorithmic Model-based Event Detectionmentioning

confidence: 99%

Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications

Zulkifli

Rahim

Lau

2018

Sensors and Actuators B: Chemical

232

View full text Add to dashboard Cite

a b s t r a c tWater monitoring technologies are widely used for contaminants detection in wide variety of water ecology applications such as water treatment plant and water distribution system. A tremendous amount of research has been conducted over the past decades to develop robust and efficient techniques of contaminants detection with minimum operating cost and energy. Recent developments in spectroscopic techniques and biosensor approach have improved the detection sensitivities, quantitatively and qualitatively. The availability of in-situ measurements and multiple detection analyses has expanded the water monitoring applications in various advanced techniques including successful establishment in hand-held sensing devices which improves portability in real-time basis for the detection of contaminant, such as microorganisms, pesticides, heavy metal ions, inorganic and organic components. This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations. Particularly, this review focuses on the most recently developed techniques for water contaminant detection applications. Several recommendations and prospective views on the developments in water quality assessments will also be included.

show abstract

“…A feature extraction process is carried out for both events, describing the dynamic and frequency characteristics of the sounds, and also the position of the aircraft for each of the events. Mel frequency cepstral coefficients (MFCC) have shown a good performance in sound recognition applications [11][12][13][14][15], so the first 20 coefficients were selected. Two new features were selected to describe the evolution of the time delay between microphones during EV1 and EV2, which is highly correlated to the location and movement of the aircraft during both events.…”

Section: Events Classificationmentioning

confidence: 99%

A novel intelligent instrument for the detection and monitoring of thrust reverse noise at airports

et al. 2015

Self Cite

View full text Add to dashboard Cite

Many airports all over the world have established restrictions for the use of thrust reverse for slowing down aircraft after landings, especially during the night period, as a way of reducing noise impact and the number of complaints in the vicinity of airports. This is the case of Madrid airport, where the Universidad PolitÃ©cnica de Madrid, in collaboration with AENA, and the Politecnico di Milano have been researching, and developing intelligent instruments to improve the detection and classification of thrust reverse noise among other noise sources present in the airport. Based on a traditional approach, the thrust reverse noise detection tool detects two consecutive sound events, and applies pattern recognition techniques for the classification of each of them (such as landing and thrust reverse). A second improvement refers to the use of a microphone array linked to a noise- monitoring unit, which enables tracking the direction of arrival of the sound, thus improving the classification rates. By taking the latter, it is also possible to track the aircraft location along the runway, which enables sound pressure measurements to be transformed into sound power level estimations. Although the novel instrument can still be optimized and customized, the results have shown quite good classification rates (over 90%).

show abstract

A statistical pattern recognition approach for the classification of cooking stages. The boiling water case

Cited by 13 publications

References 14 publications

A real time method of contaminant classification using conventional water quality sensors

A real time method of contaminant classification using conventional water quality sensors

Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications

A novel intelligent instrument for the detection and monitoring of thrust reverse noise at airports

Contact Info

Product

Resources

About