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The Handbook on Experimental Statistics has been prepared as an aid to scientists and engineers engaged in Army research and development programs, and especially as a guide and ready reference for military and civilian personnel who have responsibility for the planning and interpretation of experiments and tests relating to the performance of Army equipment in the design and developmental stages of production. The present document, section 3, has to do with the planning and analysis of comparative experiments.

The Handbook on Experimental Statistics has been prepared as an aid to scientists and engineers engaged in Army research and development programs, and especially as a guide and ready reference for military and civilian personnel who have responsibility for the planning and interpretation of experiments and tests relating to the performance of Army equipment in the design and developmental stages of production. The present document, section 3, has to do with the planning and analysis of comparative experiments.

The Handbook on Experimental Statistics has been prepared as an aid to scientists and engineers engaged in Army research and development programs, and especially as a guide and ready reference for military and civilian personnel who have responsibility for the planning and interpretation of experiments and tests relating to the performance of Army equipment in the design and developmental stages of production. The present document, section 3, has to do with the planning and analysis of comparative experiments.

The Handbook on Experimental Statistics has been prepared as an aid to scientists and engineers engaged in Army research and development programs, and especially as a guide and ready reference for military and civilian personnel who have responsibility for the planning and interpretation of experiments and tests relating to the performance of Army equipment in the design and developmental stages of production. The present document, section 3, has to do with the planning and analysis of comparative experiments.

This document analyzes the ways one can design a successful experiment.

Computer experiments are often performed to allow modeling of a response surface of a physical experiment that can be too costly or difficult to run except using a simulator. Running the experiment over a dense grid can be prohibitively expensive, yet running over a sparse design chosen in advance can result in obtaining insufficient information in parts of the space, particularly when the surface calls for a nonstationary model. We propose an approach that automatically explores the space while simultaneously fitting the response surface, using predictive uncertainty to guide subsequent experimental runs. The newly developed Bayesian treed Gaussian process is used as the surrogate model, and a fully Bayesian approach allows explicit measures of uncertainty. We develop an adaptive sequential design framework to cope with an asynchronous, random, agent--based supercomputing environment, by using a hybrid approach that melds optimal strategies from the statistics literature with flexible strategies from the active learning literature. The merits of this approach are borne out in several examples, including the motivating computational fluid dynamics simulation of a rocket booster.

Computer experiments are often performed to allow modeling of a response surface of a physical experiment that can be too costly or difficult to run except using a simulator. Running the experiment over a dense grid can be prohibitively expensive, yet running over a sparse design chosen in advance can result in obtaining insufficient information in parts of the space, particularly when the surface calls for a nonstationary model. We propose an approach that automatically explores the space while simultaneously fitting the response surface, using predictive uncertainty to guide subsequent experimental runs. The newly developed Bayesian treed Gaussian process is used as the surrogate model, and a fully Bayesian approach allows explicit measures of uncertainty. We develop an adaptive sequential design framework to cope with an asynchronous, random, agent--based supercomputing environment, by using a hybrid approach that melds optimal strategies from the statistics literature with flexible strategies from the active learning literature. The merits of this approach are borne out in several examples, including the motivating computational fluid dynamics simulation of a rocket booster.

A series of propulsion experiments were performed on Model 5362, representing a Stretched PONCE DE LEON Class RO/RO ship. The model was fitted with two sets of design contrarotating propellers. The results of the propulsion experiments indicate that the ship when equipped with either set of contrarotating propellers should achieve design speed with 12-13% less power than when fitted with the design single screw propeller. The methods used in analyzing the data are discussed. (Author)

Recently two entomological field experiments were conducted at Dugway Proving Ground. The purpose of the first experiment was to compare the biting propensity of two strains of a species of insect. In each trial, four 15-foot radius circles were scribed, and 10 hosts, randomly selected, were positioned equidistantly along each circumference. The Number 1 position in each circle was oriented to true north. (See Figure 1.) At function time, 100 individuals of the appropriate strain were released at the center of each circle. In two of the circles, the A strain was used; in the other two circles, the B strain. The men were seated on the ground and remained relatively motionless throughout the trial. Sampling consisted of each man recording those bites actually received and entering the total number, for 5-minute intervals, on a data card. Sampling was conducted for 30 minutes following the release unless biting activity continued. In that event, sampling in all circles was extended for additional 5-minute periods until the biting activity had essentially ceased.

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different.

It is the purpose of this study to examine the impact of "highly efficient" Design-of-Experiments (DOE) methods for combining sets of CFD generated analysis data with smaller sets of Experimental test data in order to accurately predict performance results where experimental test data were not obtained. The study examines the impact of micro-ramp flow control on the shock wave boundary layer (SWBL) interaction where a complete paired set of data exist from both CFD analysis and Experimental measurements By combining the complete set of CFD analysis data composed of fifteen (15) cases with a smaller subset of experimental test data containing four/five (4/5) cases, compound data sets (CFD/EXP) were generated which allows the prediction of the complete set of Experimental results No statistical difference were found to exist between the combined (CFD/EXP) generated data sets and the complete Experimental data set composed of fifteen (15) cases. The same optimal micro-ramp configuration was obtained using the (CFD/EXP) generated data as obtained with the complete set of Experimental data, and the DOE response surfaces generated by the two data sets were also not statistically different.

https://gioumeh.com/product/design-and-analysis-of-experiments-10th-edition-by-douglas-c-montgomery-solutions-manual-pdf/ -------------------------------------------------   Authors:  Douglas C. Montgomery Published:  Wiley2019   Edition:  10th   Pages:  709   Type:  pdf   Size:   123MB   Content:   official resources for 10th editions and covers all chapters of the textbook (chapters 1 to 15). It includes “Solution Manual”, “lecturer’s PowerPoint slides”, “Reserved Problems”, “Image Gallery”, “Supplemental Materials”, “Data Sets”, “Image Gallery” and “Sample Student Project”. The Solution Manual is available in Word format (one Word file for each of chapters) and includes answers for reserved problems too. Solution Sample:   sample file Download After Payment

https://gioumeh.com/product/design-and-analysis-of-experiments-10th-edition-by-douglas-c-montgomery-solutions-manual-pdf/ -------------------------------------------------   Authors:  Douglas C. Montgomery Published:  Wiley2019   Edition:  10th   Pages:  709   Type:  pdf   Size:   123MB   Content:   official resources for 10th editions and covers all chapters of the textbook (chapters 1 to 15). It includes “Solution Manual”, “lecturer’s PowerPoint slides”, “Reserved Problems”, “Image Gallery”, “Supplemental Materials”, “Data Sets”, “Image Gallery” and “Sample Student Project”. The Solution Manual is available in Word format (one Word file for each of chapters) and includes answers for reserved problems too. Solution Sample:   sample file Download After Payment

https://gioumeh.com/product/design-and-analysis-of-experiments-10th-edition-by-douglas-c-montgomery-solutions-manual-pdf/ -------------------------------------------------   Authors:  Douglas C. Montgomery Published:  Wiley2019   Edition:  10th   Pages:  709   Type:  pdf   Size:   123MB   Content:   official resources for 10th editions and covers all chapters of the textbook (chapters 1 to 15). It includes “Solution Manual”, “lecturer’s PowerPoint slides”, “Reserved Problems”, “Image Gallery”, “Supplemental Materials”, “Data Sets”, “Image Gallery” and “Sample Student Project”. The Solution Manual is available in Word format (one Word file for each of chapters) and includes answers for reserved problems too. Solution Sample:   sample file Download After Payment

x, 301 pages ; 25 cm

x, 301 pages ; 25 cm

x, 301 pages ; 25 cm

x, 301 pages ; 25 cm

Book Source: Digital Library of India Item 2015.449111 dc.contributor.author: Yates F. dc.date.accessioned: 2015-09-18T19:10:14Z dc.date.available: 2015-09-18T19:10:14Z dc.date.digitalpublicationdate: 2015 dc.identifier.other: 28714 dc.identifier.barcode: 99999990906599 dc.identifier.origpath: /data58/upload/0108/316 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/449111 dc.description.scannerno: 1 dc.description.scanningcentre: Allama Iqbal Library, University of Kashmir dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 98 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher.digitalrepublisher: Digital Library Of India dc.publisher: Commonwealth Agricultural Bureaux, England dc.rights: Not Available dc.source.library: Allama Iqbal Library, University Of Kashmir dc.subject.classification: Natural Sciences dc.title: The Design And Analysis Of Factorial Experiments dc.type: Print - Paper dc.type: Book

Uploaded by zygun

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xix, 728 p. : 24 cm

xix, 728 p. : 24 cm

xix, 728 p. : 24 cm

xix, 728 p. : 24 cm

xix, 728 p. : 24 cm

xix, 728 p. : 24 cm

This book is a humble addition to many excellent books already available on design of experiments. However, the present book differs from others in certain respects. We have addressed this book primarily to the students and research workers from diversified segments of agricultural sciences and with no adequate background in mathematics, but whose main interest is to learn and acquire a working knowledge about the fundamentals of experimental designs in a manner which appeals to their intuition and commonsense. Although we hold the view that statistical concepts can be communicated in this manner, the size of the book is a great limiting factor in sparing adequate space and attention to all the con-cepts in accomplishing this objective. The present book thus endeavours to expound the essentials of the mathematical logic underlying different types of designs in a non-mathematical language. For instance, in preference to the usual rigorous mathematical approach, we prefer to employ a heuristic approach in the presentation of linear models while exposing the reader to different statistical bases of analyses for different designs. Motivation is a great requisite force in learning. In order 'to help promote this althrough the book, we have drawn practically every illustrative example from the experiments actually conducted in various Research Stations presently under the University of Agricultural Sciences, Bangalore. The authors would like to record their grateful appreciation of the concerned authorities of the University, and also of the Bureau of Economics & Statistics, Govt. of Mysore in making available to them the necessary material for this purpose. Although the present one is a book primarily on the design of experiments, three chapters—Chapter 1 on some basic concepts of statistics, Chapter 2 on elements of tests of significance and Chapter 3 on Analysis of Variance—have been included merely to facilitate the reader to acquire a working knowledge about the statistical methods necessary for understanding the remaining part of the book. The reader is however advised to supplement this by reading other books dealing with these methods. Chapters 5, 6 and 7 lay bare the three designs of fundamental importance, viz., Completely Randomized Design, Randomized Complete Block Design and Latin Square Design, respectively. The concept of confounding in experimental designs and the need for the same are presented in Chapter 9, followed by con-founding in more complex designs in subsequent chapters. The lattice designs are discussed in Chapter 12. In the presentation of the step-wise analysis for each design certain i steps in the analysis are common to all the designs. Nonetheless, even at the risk of repetition, the details, of such steps are given in all illustrative llustrative examples and we believe this prevents not only any possible annoyance in referring back and forth for required details but, more importantly, makes each analysis complete in itself. Further we hope that the reader, this way will learn the general and specifics of different designs.

This book is a humble addition to many excellent books already available on design of experiments. However, the present book differs from others in certain respects. We have addressed this book primarily to the students and research workers from diversified segments of agricultural sciences and with no adequate background in mathematics, but whose main interest is to learn and acquire a working knowledge about the fundamentals of experimental designs in a manner which appeals to their intuition and commonsense. Although we hold the view that statistical concepts can be communicated in this manner, the size of the book is a great limiting factor in sparing adequate space and attention to all the con-cepts in accomplishing this objective. The present book thus endeavours to expound the essentials of the mathematical logic underlying different types of designs in a non-mathematical language. For instance, in preference to the usual rigorous mathematical approach, we prefer to employ a heuristic approach in the presentation of linear models while exposing the reader to different statistical bases of analyses for different designs. Motivation is a great requisite force in learning. In order 'to help promote this althrough the book, we have drawn practically every illustrative example from the experiments actually conducted in various Research Stations presently under the University of Agricultural Sciences, Bangalore. The authors would like to record their grateful appreciation of the concerned authorities of the University, and also of the Bureau of Economics & Statistics, Govt. of Mysore in making available to them the necessary material for this purpose. Although the present one is a book primarily on the design of experiments, three chapters—Chapter 1 on some basic concepts of statistics, Chapter 2 on elements of tests of significance and Chapter 3 on Analysis of Variance—have been included merely to facilitate the reader to acquire a working knowledge about the statistical methods necessary for understanding the remaining part of the book. The reader is however advised to supplement this by reading other books dealing with these methods. Chapters 5, 6 and 7 lay bare the three designs of fundamental importance, viz., Completely Randomized Design, Randomized Complete Block Design and Latin Square Design, respectively. The concept of confounding in experimental designs and the need for the same are presented in Chapter 9, followed by con-founding in more complex designs in subsequent chapters. The lattice designs are discussed in Chapter 12. In the presentation of the step-wise analysis for each design certain i steps in the analysis are common to all the designs. Nonetheless, even at the risk of repetition, the details, of such steps are given in all illustrative llustrative examples and we believe this prevents not only any possible annoyance in referring back and forth for required details but, more importantly, makes each analysis complete in itself. Further we hope that the reader, this way will learn the general and specifics of different designs.

This book is a humble addition to many excellent books already available on design of experiments. However, the present book differs from others in certain respects. We have addressed this book primarily to the students and research workers from diversified segments of agricultural sciences and with no adequate background in mathematics, but whose main interest is to learn and acquire a working knowledge about the fundamentals of experimental designs in a manner which appeals to their intuition and commonsense. Although we hold the view that statistical concepts can be communicated in this manner, the size of the book is a great limiting factor in sparing adequate space and attention to all the con-cepts in accomplishing this objective. The present book thus endeavours to expound the essentials of the mathematical logic underlying different types of designs in a non-mathematical language. For instance, in preference to the usual rigorous mathematical approach, we prefer to employ a heuristic approach in the presentation of linear models while exposing the reader to different statistical bases of analyses for different designs. Motivation is a great requisite force in learning. In order 'to help promote this althrough the book, we have drawn practically every illustrative example from the experiments actually conducted in various Research Stations presently under the University of Agricultural Sciences, Bangalore. The authors would like to record their grateful appreciation of the concerned authorities of the University, and also of the Bureau of Economics & Statistics, Govt. of Mysore in making available to them the necessary material for this purpose. Although the present one is a book primarily on the design of experiments, three chapters—Chapter 1 on some basic concepts of statistics, Chapter 2 on elements of tests of significance and Chapter 3 on Analysis of Variance—have been included merely to facilitate the reader to acquire a working knowledge about the statistical methods necessary for understanding the remaining part of the book. The reader is however advised to supplement this by reading other books dealing with these methods. Chapters 5, 6 and 7 lay bare the three designs of fundamental importance, viz., Completely Randomized Design, Randomized Complete Block Design and Latin Square Design, respectively. The concept of confounding in experimental designs and the need for the same are presented in Chapter 9, followed by con-founding in more complex designs in subsequent chapters. The lattice designs are discussed in Chapter 12. In the presentation of the step-wise analysis for each design certain i steps in the analysis are common to all the designs. Nonetheless, even at the risk of repetition, the details, of such steps are given in all illustrative llustrative examples and we believe this prevents not only any possible annoyance in referring back and forth for required details but, more importantly, makes each analysis complete in itself. Further we hope that the reader, this way will learn the general and specifics of different designs.

This book is a humble addition to many excellent books already available on design of experiments. However, the present book differs from others in certain respects. We have addressed this book primarily to the students and research workers from diversified segments of agricultural sciences and with no adequate background in mathematics, but whose main interest is to learn and acquire a working knowledge about the fundamentals of experimental designs in a manner which appeals to their intuition and commonsense. Although we hold the view that statistical concepts can be communicated in this manner, the size of the book is a great limiting factor in sparing adequate space and attention to all the con-cepts in accomplishing this objective. The present book thus endeavours to expound the essentials of the mathematical logic underlying different types of designs in a non-mathematical language. For instance, in preference to the usual rigorous mathematical approach, we prefer to employ a heuristic approach in the presentation of linear models while exposing the reader to different statistical bases of analyses for different designs. Motivation is a great requisite force in learning. In order 'to help promote this althrough the book, we have drawn practically every illustrative example from the experiments actually conducted in various Research Stations presently under the University of Agricultural Sciences, Bangalore. The authors would like to record their grateful appreciation of the concerned authorities of the University, and also of the Bureau of Economics & Statistics, Govt. of Mysore in making available to them the necessary material for this purpose. Although the present one is a book primarily on the design of experiments, three chapters—Chapter 1 on some basic concepts of statistics, Chapter 2 on elements of tests of significance and Chapter 3 on Analysis of Variance—have been included merely to facilitate the reader to acquire a working knowledge about the statistical methods necessary for understanding the remaining part of the book. The reader is however advised to supplement this by reading other books dealing with these methods. Chapters 5, 6 and 7 lay bare the three designs of fundamental importance, viz., Completely Randomized Design, Randomized Complete Block Design and Latin Square Design, respectively. The concept of confounding in experimental designs and the need for the same are presented in Chapter 9, followed by con-founding in more complex designs in subsequent chapters. The lattice designs are discussed in Chapter 12. In the presentation of the step-wise analysis for each design certain i steps in the analysis are common to all the designs. Nonetheless, even at the risk of repetition, the details, of such steps are given in all illustrative llustrative examples and we believe this prevents not only any possible annoyance in referring back and forth for required details but, more importantly, makes each analysis complete in itself. Further we hope that the reader, this way will learn the general and specifics of different designs.

This book is a humble addition to many excellent books already available on design of experiments. However, the present book differs from others in certain respects. We have addressed this book primarily to the students and research workers from diversified segments of agricultural sciences and with no adequate background in mathematics, but whose main interest is to learn and acquire a working knowledge about the fundamentals of experimental designs in a manner which appeals to their intuition and commonsense. Although we hold the view that statistical concepts can be communicated in this manner, the size of the book is a great limiting factor in sparing adequate space and attention to all the con-cepts in accomplishing this objective. The present book thus endeavours to expound the essentials of the mathematical logic underlying different types of designs in a non-mathematical language. For instance, in preference to the usual rigorous mathematical approach, we prefer to employ a heuristic approach in the presentation of linear models while exposing the reader to different statistical bases of analyses for different designs. Motivation is a great requisite force in learning. In order 'to help promote this althrough the book, we have drawn practically every illustrative example from the experiments actually conducted in various Research Stations presently under the University of Agricultural Sciences, Bangalore. The authors would like to record their grateful appreciation of the concerned authorities of the University, and also of the Bureau of Economics & Statistics, Govt. of Mysore in making available to them the necessary material for this purpose. Although the present one is a book primarily on the design of experiments, three chapters—Chapter 1 on some basic concepts of statistics, Chapter 2 on elements of tests of significance and Chapter 3 on Analysis of Variance—have been included merely to facilitate the reader to acquire a working knowledge about the statistical methods necessary for understanding the remaining part of the book. The reader is however advised to supplement this by reading other books dealing with these methods. Chapters 5, 6 and 7 lay bare the three designs of fundamental importance, viz., Completely Randomized Design, Randomized Complete Block Design and Latin Square Design, respectively. The concept of confounding in experimental designs and the need for the same are presented in Chapter 9, followed by con-founding in more complex designs in subsequent chapters. The lattice designs are discussed in Chapter 12. In the presentation of the step-wise analysis for each design certain i steps in the analysis are common to all the designs. Nonetheless, even at the risk of repetition, the details, of such steps are given in all illustrative llustrative examples and we believe this prevents not only any possible annoyance in referring back and forth for required details but, more importantly, makes each analysis complete in itself. Further we hope that the reader, this way will learn the general and specifics of different designs.

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

Book Source: Digital Library of India Item 2015.198544 dc.contributor.author: S. Singh dc.date.accessioned: 2015-07-08T12:50:20Z dc.date.available: 2015-07-08T12:50:20Z dc.date.digitalpublicationdate: 0000-00-00 dc.identifier.barcode: 5990010100343 dc.identifier.origpath: /rawdataupload/upload/0100/345 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/198544 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 227 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Bishwaabhaarti Prakaashan Naagpur dc.rights: Out_of_copyright dc.source.library: I I T Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Design And Analysis Of Experiments For Model Discrimination In Uniresponse

This research concerns the design and analysis of different Side-Looking Sonar experiments in order to satisfy different operational requirements. The different designs and analysis have been done via computer simulation. Side-Looking Sonar (also known as side-scan sonar) is known for very high quality, high resolution, ocean bottom imaging. Hence, it is used for bathymetric surveys, commonly called seafloor mapping. It is able to rapidly survey large ocean areas for bottom and suspended sea-mines or other kinds of threats. Another operational aspect of these systems is that they allow autonomous underwater vehicles (AUVs) to conduct operations, mostly in shallow water and near land. Thus Side-Looking Sonar can be a very useful device in littoral warfare operations. This research has defined the basic parameters that rule the operation of a Side-Looking Sonar and, furthermore, analyzed various aspects that affect the performance of these parameters. Special focus was given to the various operational requirements and conditions that a designer or a user may encounter in realistic situations. Toward that end, many numerical examples are presented. Moreover, the research has tried to indicate the various problems that may arise when a Side-Looking Sonar operates in its near-field region and suggests certain solutions. The active sonar equation and its factors were explained and were evaluated for a realistic example of mine detection as well.

This research concerns the design and analysis of different Side-Looking Sonar experiments in order to satisfy different operational requirements. The different designs and analysis have been done via computer simulation. Side-Looking Sonar (also known as side-scan sonar) is known for very high quality, high resolution, ocean bottom imaging. Hence, it is used for bathymetric surveys, commonly called seafloor mapping. It is able to rapidly survey large ocean areas for bottom and suspended sea-mines or other kinds of threats. Another operational aspect of these systems is that they allow autonomous underwater vehicles (AUVs) to conduct operations, mostly in shallow water and near land. Thus Side-Looking Sonar can be a very useful device in littoral warfare operations. This research has defined the basic parameters that rule the operation of a Side-Looking Sonar and, furthermore, analyzed various aspects that affect the performance of these parameters. Special focus was given to the various operational requirements and conditions that a designer or a user may encounter in realistic situations. Toward that end, many numerical examples are presented. Moreover, the research has tried to indicate the various problems that may arise when a Side-Looking Sonar operates in its near-field region and suggests certain solutions. The active sonar equation and its factors were explained and were evaluated for a realistic example of mine detection as well.

The past decade has witnessed a dramatic increase in the size and scope of biological and behavioral experiments. These experiments are providing an unprecedented level of detail and depth of data. However, this increase in data presents substantial statistical and graphical hurdles to overcome, namely how to distinguish signal from noise and how to visualize multidimensional results. Here we present a series of tools designed to support a research project from inception to publication. We provide implementation of dimension reduction techniques and visualizations that function well with the types of data often seen in animal behavior studies. This package is designed to be used with experimental data but can also be used for experimental design and sample justification. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.

The past decade has witnessed a dramatic increase in the size and scope of biological and behavioral experiments. These experiments are providing an unprecedented level of detail and depth of data. However, this increase in data presents substantial statistical and graphical hurdles to overcome, namely how to distinguish signal from noise and how to visualize multidimensional results. Here we present a series of tools designed to support a research project from inception to publication. We provide implementation of dimension reduction techniques and visualizations that function well with the types of data often seen in animal behavior studies. This package is designed to be used with experimental data but can also be used for experimental design and sample justification. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.

The past decade has witnessed a dramatic increase in the size and scope of biological and behavioral experiments. These experiments are providing an unprecedented level of detail and depth of data. However, this increase in data presents substantial statistical and graphical hurdles to overcome, namely how to distinguish signal from noise and how to visualize multidimensional results. Here we present a series of tools designed to support a research project from inception to publication. We provide implementation of dimension reduction techniques and visualizations that function well with the types of data often seen in animal behavior studies. This package is designed to be used with experimental data but can also be used for experimental design and sample justification. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.

The past decade has witnessed a dramatic increase in the size and scope of biological and behavioral experiments. These experiments are providing an unprecedented level of detail and depth of data. However, this increase in data presents substantial statistical and graphical hurdles to overcome, namely how to distinguish signal from noise and how to visualize multidimensional results. Here we present a series of tools designed to support a research project from inception to publication. We provide implementation of dimension reduction techniques and visualizations that function well with the types of data often seen in animal behavior studies. This package is designed to be used with experimental data but can also be used for experimental design and sample justification. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.

The past decade has witnessed a dramatic increase in the size and scope of biological and behavioral experiments. These experiments are providing an unprecedented level of detail and depth of data. However, this increase in data presents substantial statistical and graphical hurdles to overcome, namely how to distinguish signal from noise and how to visualize multidimensional results. Here we present a series of tools designed to support a research project from inception to publication. We provide implementation of dimension reduction techniques and visualizations that function well with the types of data often seen in animal behavior studies. This package is designed to be used with experimental data but can also be used for experimental design and sample justification. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.