Venkatesan G (67 results)

Condition: New. pp. 187.

Condition: New. pp. 187 1st Published.

Condition: New. pp. 187.

Condition: As New. Unread book in perfect condition.

Condition: New.

Paperback. Condition: New.

N.A. Condition: New. ISBN:9788184874273,190pp N.A.

N.A. Condition: New. ISBN:9788184873498,248pp N.A.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9781842658819.…

Hardcover. Condition: New. 1st Edition. Contents: 1. Current status of insecticide resistance in arthropods. 2. Insect physiology with reference to action of insecticides. 3. Neurotoxide insecticides and their mode of action. 4. Insecticides resistance: a micro evolutionary phenomena. 5. Entomopathogens: mode of action and mechanism of resistance. 6. Overview of pesticide resistance mechanisms. 7. Reduced cuticular penetration and metabolic resistance. 8. Target site resistance. 9. Conventional methods of detection of insecticide resistance. 10. Biochemical and molecular methods of detections of insecticides. 11. Fitness cost associated with insecticides resistance. 12. Functional significance of insect endosymbionts. 13. Insect endosymbionts: metagenomic perspective. 14. Do insects show resistant to EPN? Role of insect immunity. 15. Insecticide resistance management in insect pests. 16. Bt crops and insects pests susceptibility: current status. 17. Pesticide induced hormesis and resurgence. 18. Practical aspects of resistance detection: bioassay methods. 19. Practical aspects of resistance detection: biochemical methods. 20. Clean laboratory practices for rearing and bioassay of insects. …

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Neuware.

Hardcover. Condition: Good. 2000 CRC Press hardcover edition. Light reading wear, a little wear to edge else very good condition. Heteropterans regularly cause a wide variety and large number of problems for humans - at times on a catastrophic scale. The 37,000 described species of this suborder include many pests, disease transmitters, and nuisances that exist worldwide. They inflict damage on crops, forests, orchards, and humans. Inspired by the widespread economic impact of this activity, Heteroptera of Economic Importance presents the most thorough, detailed account of true bugs to date. From the bloodsucking bed bug to the dreaded assassin bug, Heteroptera of Economic Importance integrates the best of insect-focused and crop-oriented references, synthesizing the biology, behavior, and ecology of the true bugs. Each entry includes a detailed life history, that helps you evaluate the impact of harmful and useful Heteroptera. The thorough, comprehensive bibliographies support further research. Separate indices to insects and plants allow you to adapt the book to your use. It covers the physiology of plant damage and predation by this cosmopolitan group. This coverage, along with information on control measures and natural enemies, helps you evaluate and compare the best methods of management. Contents: INTRODUCTION 1 Economic Importance of Heteroptera: A General View by Carl W. Schaefer and Antonio R. Panizzi HARMFUL BUGS 2 Possible Causes of Disease Symptoms Resulting from the Feeding of Phytophagous Heteroptera by Koji Hori 3 Plant Bugs (Miridae) as Plant Pests by A. G. Wheeler, Jr. 4 Lace Bugs (Tingidae) by John W. Neal, Jr. and Carl W. Schaefer 5 Palm Bugs (Thaumastocoridae) by Lionel Hill and Carl W. Schaefer 6 Seed and Chinch Bugs (Lygaeoidea) by Merrill H. Sweet II 7 Ash-Gray Leaf Bugs (Piesmatidae) by Narisu 8 Cotton Stainers and Their Relatives (Pyrrhocoroidea: Pyrrhocoridae and Largidae) by Carl W. Schaefer and Imtiaz Ahmad 9 Scentless Plant Bugs (Rhopalidae) by Carl W. Schaefer and Jill Kotulski 10 Broad-Headed Bugs (Alydidae) by Antonio R. Panizzi, Carl W. Schaefer, and Yoshiro Natuha 11 Leaf-Footed Bugs (Coreidae) by Paula Levin Mitchell 12 Burrower Bugs (Cydnidae) by Jerzy A. Lis, Miriam Becker, and Carl W. Schaefer 13 Stink Bugs (Pentatomidae) by Antonio R. Panizzi, J. E. McPherson, David G. James, M. Javahery, and Robert M. McPherson 14 Shield Bugs (Scutelleridae) by M. Javahery, Carl W. Schaefer, and John D. Lattin 15 Several Small Pentatomoid Families (Cyrtocoridae, Dinidoridae, Eurostylidae, Plataspidae, and Tessaratomidae) by Carl W. Schaefer, Antonio R. Panizzi, and David G. James 16 Flat Bugs (Aradidae) by Kari Heliovaara 17 Bed Bugs (Cimicidae) by Carl W. Schaefer 18 Triatominae (Reduviidae) by Eloi S. Garcia, Patricia de Azambuja, and Joao C. P. Dias 19 Adventitious Biters — "Nuisance" Bugs by Carl W. Schaefer USEFUL BUGS 20 How Carnivorous Bugs Feed by Allen Carson Cohen 21 Creeping Water Bugs (Naucoridae) by Robert W. Sites 22 Giant Water Bugs (Belostomatidae) by P. Venkatesan 23 Waterscorpions (Nepidae) by Steven L. Keffer 24 Small Aquatic Bugs (Nepomorpha) with Slight or Underestimated Economic Importance by Miroslav Papacek 25 Semiaquatic Bugs (Gerromorpha) by John R. Spence and Nils Moller Andersen 26 Minute Pirate Bugs (Anthocoridae) by John D. Lattin 27 Damsel Bugs (Nabidae) by S. Kristine Braman 28 Predacious Plant Bugs (Miridae) by A. G. Wheeler, Jr. 29 Assassin Bugs (Reduviidae excluding Triatominae) by Dunston P. Ambrose 30 Economic Importance of Predation by Big-Eyed Bugs (Geocoridae) by Merrill H. Sweet II 31 Stilt Bugs (Berytidae) by Thomas J. Henry 32 Predaceous Stinkbugs (Pentatomidae: Asopinae) by Patrick De Clercq.…

Paperback. Condition: New.

Hardcover. Condition: new. Hardcover. BRAIN-COMPUTER INTERFACE It covers all the research prospects and recent advancements in the brain-computer interface using deep learning. The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved. Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN). Audience Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New.

Hardcover. Condition: new. Hardcover. BRAIN-COMPUTER INTERFACE It covers all the research prospects and recent advancements in the brain-computer interface using deep learning. The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved. Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN). Audience Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condition: new. Hardcover. BRAIN-COMPUTER INTERFACE It covers all the research prospects and recent advancements in the brain-computer interface using deep learning. The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real world, however, some problems remain to be solved. Research focusing on deep learning is anticipated to bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN). Audience Researchers and industrialists working in brain-computer interface, deep learning, machine learning, medical image processing, data scientists and analysts, machine learning engineers, electrical engineering, and information technologists. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: new.