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Upadhyaya, Gopal
- Fuzzy Logic Based Monitoring System for Detecting the Concentration of Hydrogen Cyanide
Abstract Views :367 |
PDF Views:84
Authors
Affiliations
1 Dept. of Physics, B.M. Engg. College, Indore-452012, IN
2 School of Studies in Physics, Vikram University, Ujjain, IN
1 Dept. of Physics, B.M. Engg. College, Indore-452012, IN
2 School of Studies in Physics, Vikram University, Ujjain, IN
Source
Indian Journal of Science and Technology, Vol 3, No 3 (2010), Pagination: 293-295Abstract
This paper describes a fuzzy logic based monitoring system able to detect, measure the concentration of hydrogen cyanide released into the environment from the exhaust of vehicles, burning nitrogen-containing plastics or from any other source. We applied our suggested model to sensor network. The mobile sensor network is composed of a collection of distributed nodes each of which has limited sensing, intelligence and communication capabilities. An ad hoc wireless network is established among all nodes and each node considers other node as extended sensor.Keywords
Hydrogen Cyanide Monitoring System, Fuzzy Logic Control SystemReferences
- Baum MM, John A. Moss, Stephen H. Pastel and Gregory A. Poskrebyshev (2007) Hydrogen cyanide exhaust emissions from in-use motor vehicles. Environ. Sci. Technol. 41 (3), 857–862.
- Cui X, Hardin T, Ragade RK and Elmaghraby AS (2004) A swarm-based fuzzy logic control mobile sensor network for hazardous contaminants localization. In: IEEE Int. Conf. on Mobile Ad Hoc & Sensor Systems. Oct. 25-27, Univ. of Louisville, KY 40292. pp: 194–203.
- Dashore Pankaj and Jain Suresh (2009) Fuzzy Rule-based system andmetagraph for risk management in electronic banking activities.IJET Singapore vol1No.2,101-107
- El Ghawabi SH, Gaafar MA, El-Saharti AA, Ahmed SH, Malash KK and Fares R (1975) Chronic cyanide exposure: a clinical, radioisotope, and laboratory study. Br. J. Ind. Med. 32, 215-219.
- Fiskel J, Cooper C, and Eschenroeder A (1981) Exposure and risk assessment for cyanide. EPA/440/4-85/008. NTIS PB85-220572
- Fungal Genetics & Biol. 28 (2), 126-134.
- amalu BP (1995) The adverse effects of long-term cassava (Manihot esculenta Crantz) consumption. Int. J. Food Sci. Nutr. 46(1), 65-93.
- Lewis FL (2005) Wireless Sensor Network. The University of Texas, Arlington.
- Mohammad AA and Abbas J (2006) "Optimized Forwarding for Wireless Sensor Networks by Fuzzy Inference System” The University of Sydney, NSW, Australia.
- Nilesh Dashore and Gopal Upadhyay (2009) Fuzzy logic based monitoring system for detecting radon concentration. 2 (5), 29-30.
- Ping Wang, Robert W. Sandrock and Hans D. VanEtten (1999) Disruption of the cyanide hydratase gene in Gloeocercospora sorghi increases its sensitivity to the phytoanticipin cyanide but does not affect its pathogenicity on the cyanogenic plant sorghum. Pradyot Patnaik (2002) Handbook of Inorganic Chemicals. McGraw-Hill, ISBN 0070494398.
- SP Technical Research Institute of Sweden (2010) Formation of Hydrogen Cyanide in Fires. http://www.sp.se/en/index/research/hydrogen_formation/Sidor/default.aspx. Extracted on 20th April 2010.
- Fuzzy Logic Based Model for Predicting Volcanic Activity
Abstract Views :496 |
PDF Views:125
Authors
Affiliations
1 Dept. of Physics, B.M. College of Technology, Indore-452012, IN
2 School of Studies in Physics, Vikram University, Ujjain, IN
3 Dept. of Computer Science B.M. College of Technology, Indore 452012, IN
1 Dept. of Physics, B.M. College of Technology, Indore-452012, IN
2 School of Studies in Physics, Vikram University, Ujjain, IN
3 Dept. of Computer Science B.M. College of Technology, Indore 452012, IN
Source
Indian Journal of Science and Technology, Vol 3, No 7 (2010), Pagination: 759-763Abstract
This paper describes a fuzzy logic based system to predict volcanic eruption. Meaningful prediction requires careful monitoring of a volcano's vital signs. Seismometers can be used to pinpoint earthquakes which track the rise of magma and its movement along fissures. Measurements of the tilt of the entire mountain provide additional information about the 'breathing' of the volcano as magma moves inside it. Instruments that sniff SO2, CO2 and other gases also can signal changes in the volcano. At some volcanoes the seismic information seems most reliable; at others the tilt tells the story. But the best predictions come from the combination of all of these methods into a volcano monitoring and prediction system.Keywords
Fuzzy Logic Control SystemReferences
- Anderson JG, Bodin P, Brune JN, Prince J, Singh SK, Quaas R and Onate M (1986) Strong ground motion from the Michoacan, Maxico earthquake. Science. 233, 1043-1049.
- Bralower, Timothy J, Charles K. Paull and Mark Leckie R (1998) The cretaceous- Tertiary boundary cocktail: Chicxulub impact triggers margin collapse and extensive sediment gravity flows. Geology. 26, 331-334. doi: 10.1130/0091-7613(1998)026; ISSN 0091-7613.
- John Yen and Reza Langari (2007) Fuzzy Logic Intelligence, control, and Information. Pearson Education, Texas. 68-70.
- Mohammad Abdul Azim and Abbas Jamlipour (2006) Optimized forwarding for wireless sensor networks by fuzzy inference system. The Univ. of Sydney, NSW 2006, Australia.
- Murck, Barbara W, Brian J. Skinner and Stephen C. Porter (1997) Dangerous Earth, an introduction to geologic hazards. Oxford University Press. pp: 299
- Nilesh Dashore and Gopal Upadhyay (2009) Fuzzy logic based monitoring system for detecting radon concentration. Indian J. Sci.Technol. 2 (5), 29-30. Domain site: http://www.indjst.org.
- Patrick L. Abbott (1996) Natural Disaster. Wm.c. Brown Publishing Co. pp:438.
- Zhong Lu, Timothy Masterlark, Daniel Dzurisin , Russell Rykhus and Charles Wicks (2003) Magma Supply dynamics at Westdahl volcano, Alaska, modeled from satellite radar interferometry. J. Geophysical Res., 108 (B 7), 2354, ETG 9-1. 2003doi:10.1029/2002JB002311.
- Fuzzy Logic Based Model for Monitoring Air Quality Index
Abstract Views :422 |
PDF Views:125
Authors
Affiliations
1 School of Studies in Physics, Vikram University, Ujjain
1 School of Studies in Physics, Vikram University, Ujjain
Source
Indian Journal of Science and Technology, Vol 4, No 3 (2011), Pagination: 215-218Abstract
Environment is the sum of all social, physical, chemical, biological or economical factors which constitute the surroundings of man to both his creator and moulders of environment. This paper discusses on global warming and green house effect and suggests the way to control global warming and the steps to be taken to reduce the temperature of the earth. The produced CO2 from industries and from several other sources is to be sent through separate pipe lines to glass chambers kept in open atmosphere and sunlight is to be supplied to it. When chlorophyll pigments are supplied through plant sources or through algae that survive in anaerobic conditions to the glass chamber, the incoming CO2 will get converted into oxygen due to photosynthesis. The outgoing oxygen can be collected through outlets and can be used in hospitals and several other places. In this way we can control the level of CO2 in atmosphere and thus reducing global warming.Keywords
Global Warming, Environment, Green-house GasReferences
- Air Pollution Index”. Environmental Protection Department. 2004. http://www.epd-asg.gov.hk.
- John Yen, Reza Langari Second Impresion, (2007) Fuzzy Logic Intelligence, control, and Information Teexas,page 68-70.
- Mohammad Abdul Azim and Abbas Jamlipour (2006) Optimized forwarding for wireless sensor networks byfuzzy inference system. The University of Sydney, NSW 2006, Australia.
- Nilesh Dashore and Gopal Upadhyay (2009) Fuzzy logic based monitoring system for detecting radon concentration. 2 (5), 29-30.
- Pollution index based on index set 20 years ago, p5, South China Morning Post taken from http://en.wikipedia.org/wiki/ Air_Pollution_Index dated 22/08/2010.
- USEPA (1998). Federal Register, Vol. 63 No. 236 / Wednesday, December 9, 1998.
- www.sepa.gov.cn/quality/air.php3?offset=60 taken from http://en.wikipedia.org/wiki/ Air_Pollution_Index dated 22/08/2010.