國立虎尾科技大學 |

Optimization,Modeling, and Control : = Applications to Klystron Designing and Hepatitis C Virus Dynamics.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Optimization,Modeling, and Control :/
其他題名:	Applications to Klystron Designing and Hepatitis C Virus Dynamics.
作者:	Lankford, George Bernard.
面頁冊數:	1 online resource (119 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
Contained By:	Dissertation Abstracts International78-08B(E).
標題:	Applied mathematics. -
電子資源:	click for full text (PQDT)
ISBN:	9781369621297

Optimization,Modeling, and Control : = Applications to Klystron Designing and Hepatitis C Virus Dynamics.
Lankford, George Bernard.

Optimization,Modeling, and Control :Applications to Klystron Designing and Hepatitis C Virus Dynamics. - 1 online resource (119 pages)

Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369621297Subjects--Topical Terms:

1069907
Applied mathematics.
Index Terms--Genre/Form:

554714
Electronic books.

Optimization,Modeling, and Control : = Applications to Klystron Designing and Hepatitis C Virus Dynamics.
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245 1 0 $a Optimization,Modeling, and Control : $b Applications to Klystron Designing and Hepatitis C Virus Dynamics.
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300 $a 1 online resource (119 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
500 $a Adviser: Hien Tran.
502 $a Thesis (Ph.D.) $c North Carolina State University $d 2016.
504 $a Includes bibliographical references
520 $a In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python).
520 $a The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost associated with constant drug treatment.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Applied mathematics. $3 1069907
650 4 $a High energy physics. $3 1180812
650 4 $a Biomedical engineering. $3 588770
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a North Carolina State University. $3 845424
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10583450 $z click for full text (PQDT)