ICRP110Adult Refeerence Computationl Phantoms2Abstract

Adult Reference

Computational Phantoms

ICRP PUBLICATION 110

Approved by ICRP in October 2007and

adopted by ICRU in October 2008

Abstract –This report describes the development and intended use of the computational phan-toms of the Reference Male and Reference Female.In its 2007Recommendations,ICRP adopted these computational phantoms for forthcoming updates of organ dose coe?cients for both internal and external radiation sources (ICRP,2007).The phantoms are based on medical image data of real people,yet are consistent with the data given in Publication 89(ICRP,2002)on the reference anatomical and physiological parameters for both male and female subjects.The reference phantoms are constructed after modifying the voxel models (Golem and Laura)of two individuals whose body height and mass resembled the reference data.The organ masses of both models were adjusted to the ICRP data on the adult Reference Male and Reference Female,without compromising their anatomic realism.This report describes the methods used for this process and the characteristics of the resulting computa-tional phantoms.

Chapter 1summarises the main reasons for constructing these phantoms –voxel phan-toms being the state of the art,and the necessity for compliance with the anatomical char-acteristics of the Reference Male and Reference Female given in Publication 89(ICRP,2002).Chapter 2summarises the speci?cations of the computational phantoms with respect to external dimensions and the source and target regions that are required.Chapter 3char-acterises the previously segmented voxel models (Golem and Laura)that are the origins of the reference phantoms.Chapter 4sketches the modi?cations that had to be applied to these models to create voxel models of the Reference Male and Reference Female.Chapter 5is a description of the resulting reference computational phantoms of the Reference Male and Reference Female.Finally,Chapter 6indicates their applications and highlights their limitations.

The phantoms’technical descriptions are contained in Annexes A–H,which represent the larger part of this report.The numerical data representing the phantoms are contained on an electronic data storage medium (CD-ROM)that accompanies the printed publication.One of the aims of this report is to assist those who wish to implement the phantoms for their own calculations.

Furthermore,to illustrate the uses of these phantoms,graphical illustrations of conver-sion coe?cients for some external and internal exposures are included in Annexes I–L.

ICRP Publication

110

ICRP Publication110

A comprehensive set of recommended values will be published in separate reports.Finally, Annex M presents a description of the data?les on the CD-ROM.

ó2009ICRP.Published by Elsevier Ltd.

Keywords:Computational phantoms;Voxel models;Reference Male;Reference Female

References

ICRP,2002.Basic anatomical and physiological data for use in radiological protection:reference values.

ICRP Publication89.Ann.ICRP32(3–4).

ICRP,2007.The2007Recommendations of the International Commission on Radiological Protection.

ICRP Publication103.Ann.ICRP37(2–4).

Cloud Computing for Mobile Users Can Offloading Computation Save Energy - Summary

Cloud computing for mobile users: can offloading computation save energy? Karthik Kumar and Yung-Hsiang Lu, Purdue University Motivation: The primary constraints for mobile computing are limited energy and wireless bandwidth. So the motivation behind this paper is to test weather cloud applications a good solution to improving battery lifetime of a mobile device. Assumptions: (D = data to be transferred; B = network bandwidth; C = amount of computation) 1. D is small enough for B to handle it. 2. C is large enough that its better to be done using offloading. Features, Summary and notes: 1. Cloud computing enhances the computing capability of mobile devices (as most of it can be done on the cloud) 2. Amazon Web Services: a. Simple Storage Service (S3): Lets Users to store personal data. b. Elastic Compute Cloud (EC2): Can perform computations on the stored data. 3. long battery life most desirable feature. 4. Eliminate computation all together. The mobile system does not perform the computation; instead, computation is performed somewhere else, thereby extending the mobile system’s battery lifetime. 5. Offloading - is the concept of Sending computation to another machine. Limitations & Challenges: Limitations and challenges faced by the approach suggested in the paper are: a. Privacy and security of data (Possible Solution: data encryption) i. A bug or security loophole: this might cause the data to be open to security attacks. ii. 3rd party vendors: if the data is processed by 3rd party vendors, again the problem that, how to safeguard data at their end? iii. Tracking individual using location-based-services: What if an unauthorized person is able to track the individual using location-based-services (which often uses offloading)? b. Reliability i. Dependence on Wireless network: What if there is no network connection? The application won’t work at places like deep in a forest. What if the ISP server is down? thus service outage. c. handling real-time data i. amount of data to be transferred: what if an application, which processes real time data? one cannot predict the size of data that is to be transferred. What if the size of data is huge at some time that D is too huge for B to handle?

ICRP110Adult Refeerence Computationl Phantoms2Abstract

Adult Reference Computational Phantoms ICRP PUBLICATION 110 Approved by ICRP in October 2007and adopted by ICRU in October 2008 Abstract –This report describes the development and intended use of the computational phan-toms of the Reference Male and Reference Female.In its 2007Recommendations,ICRP adopted these computational phantoms for forthcoming updates of organ dose coe?cients for both internal and external radiation sources (ICRP,2007).The phantoms are based on medical image data of real people,yet are consistent with the data given in Publication 89(ICRP,2002)on the reference anatomical and physiological parameters for both male and female subjects.The reference phantoms are constructed after modifying the voxel models (Golem and Laura)of two individuals whose body height and mass resembled the reference data.The organ masses of both models were adjusted to the ICRP data on the adult Reference Male and Reference Female,without compromising their anatomic realism.This report describes the methods used for this process and the characteristics of the resulting computa-tional phantoms. Chapter 1summarises the main reasons for constructing these phantoms –voxel phan-toms being the state of the art,and the necessity for compliance with the anatomical char-acteristics of the Reference Male and Reference Female given in Publication 89(ICRP,2002).Chapter 2summarises the speci?cations of the computational phantoms with respect to external dimensions and the source and target regions that are required.Chapter 3char-acterises the previously segmented voxel models (Golem and Laura)that are the origins of the reference phantoms.Chapter 4sketches the modi?cations that had to be applied to these models to create voxel models of the Reference Male and Reference Female.Chapter 5is a description of the resulting reference computational phantoms of the Reference Male and Reference Female.Finally,Chapter 6indicates their applications and highlights their limitations. The phantoms’technical descriptions are contained in Annexes A–H,which represent the larger part of this report.The numerical data representing the phantoms are contained on an electronic data storage medium (CD-ROM)that accompanies the printed publication.One of the aims of this report is to assist those who wish to implement the phantoms for their own calculations. Furthermore,to illustrate the uses of these phantoms,graphical illustrations of conver-sion coe?cients for some external and internal exposures are included in Annexes I–L. ICRP Publication 110

Textbooks 1. Introduction to Automata Theory, Languages, and Computation

RAJESH P.N.RAO Curriculum Vitae June2000 Work Address: The Salk Institute,CNL 10010N.Torrey Pines Road La Jolla,CA92037 Phone:858-453-4100x1527Home Address: 9230Regents Road,Apt.H La Jolla,CA92037 E-mail:rao@https://www.wendangku.net/doc/10816155.html, WWW:https://www.wendangku.net/doc/10816155.html,/rao/ Ph.D.in Computer Science,University of Rochester,1998.Dissertation title:Dynamic EDUCATION Appearance-Based Vision.Advisor:Dr.Dana Ballard. M.S.in Computer Science,University of Rochester,1994. B.S.summa cum laude in Computer Science and Mathematics,Angelo State Univer- sity,Texas,1992.GPA:4.0 Research Associate,Sloan Center for Theoretical Neurobiology,Salk Institute,1997-POSITIONS present.Advisor:Dr.Terrence Sejnowski. Research Assistant,Department of Computer Science,University of Rochester,Sum- mer1993-1997. Assistant Administrator,Microcomputer Laboratory,Angelo State University,1989- 1992. Prepared lesson plans and delivered two lectures for an undergraduate course on Com-TEACHING EXPERIENCE putational Neurobiology(BIPN146)at University of California,San Diego,1999.Pro-fessor:T.Sejnowski.Textbook:Biophysics of Computation by Christof Koch. Teaching Assistant,Department of Computer Science,University of Rochester,Spring 1993and1994.Courses:1.Theory of Computation2.Design and Analysis of Algo- rithms.Textbooks:1.Introduction to Automata Theory,Languages,and Computation by John E.Hopcroft and Jeffrey D.Ullman.2.Introduction to Algorithms by Thomas H.Cormen,Charles E.Leiserson and Ronald L.Rivest. Teaching Assistant,Mathematics Department,Angelo State University,1989-1992.Un- dergraduate courses on calculus and analytical geometry. Teaching Assistant,Physics Department,Angelo State University,1989-1990.Under- graduate courses on fundamentals of physics.

H. B. Barlow. Unsupervised learning. Neural Computation, 1295–311, 1989.

References D.H.Ackley,G. E.Hinton,and T.J.Sejnowski.A learning algorithm for Boltzmann machines.Cognitive Science,9:147–169,1985. D.G.Amaral,N.Ishizuka,and B.Claiborne.Neurons,numbers,and the hip- pocampal network.Progress in Brain Research,83:1–11,1990. J.Atick and N.Redlich.Towards a theory of early visual processing.Neural Computation,2:308–320,1990. S.Bao,V.T.Chan,and M.M.Merzenich.Cortical remodelling induced by activity of ventral tegmental dopamine neurons.Nature,412(6842):79–83,2001. H.B.Barlow.Unsupervised learning.Neural Computation,1:295–311,1989. H.B.Barlow and P.F¨o ldi′a k.Adaptation and decorrelation in the cortex.In R.Durbin,C.Miall,and G.Mitchison,editors,The Computing Neuron,chap- ter4,pages54–72.Addison-Wesley Publishing Corp.,1989. C.A.Barnes,B.L.McNaughton,S.J.Y.Mizumori,and https://www.wendangku.net/doc/10816155.html,- parison of spatial and temporal characteristics of neuronal activity in sequential stages of hippocampal processing.Progress in Brain Research,83:287–300,1990. S.Becker.Mutual information maximization:Models of cortical self-organization. Network:Computation in Neural Systems,7:7–31,1996. S.Becker.Implicit learning in3d object recognition:The importance of temporal context.Neural Computation,1999. S.Becker.A computational principle for hippocampal learning and neurogenesis. To appear in Hippocampus,2005. S.Becker and G.E.Hinton.A self-organizing neural network that discovers surfaces in random-dot stereograms.Nature,355:161–163,1992. S.Becker and J.Lim.A computational model of prefrontal control in free recall: strategic memory use in the california verbal learning task.Journal of Cognitive Neuroscience,15(6):1–12,2003. A.J.Bell and T.J.Sejnowski.An information-maximisation approach to blind separation and blind deconvolution.Neural Computation,7(6):1129–1159,1995. A.J.Bell and T.J.Sejnowski.The independent components of natural scenes are edge?lters.Vision Research,37:3327–3338,1997. N.Brenner,W.Bialek,and R.de Ruyter van Steveninck.Adaptive rescaling Haykin,Principe,Sejnowski,and McWhirter:New Directions in Statistical Signal Processing:From Systems to Brain2005/03/0810:14

计算机英语(第二版)清华大学出版社 课后习题答案

专业英语课后习题答案 Chapter1 I. 1.Application software 2. -128 127 3. system software 4. hardware system software system 5.microcomputers, minicomputers, mainframe computers, supercomputers II. 1. false 2. false 3. false 4. true 5.true III. (2)CPU (3)bit (1)integrated circuit(IC) (4) ASCII IV. (1)编码技术(2)应用软件(3) 浮点数据(4)分时(5)存储容量 VIII．1.By using various coding techniques, groups of bits can be made to represent not only binary numbers but also other discrete symbols 通过应用多种编码技术，一组二进制数字不但可以表示二进制数据，而且还可以表示其它的离散符号 2.System software includes not only the complex programs used by technicians to create application software in the first place but also the organizational programs needed to start up the computer and govern its use of other programs. 系统软件不仅包括技术人员用于创建应用软件的复杂程序，而且还包括用于启动计算机和提供给其他程序使用的管理程序。 3.Data are numbers and other binary-code information that are operated on to achieve required computational results. 数据是数字和其他的二进制代码信息，通过处理这些数据得到所需要的计算结果。 4.Rather than arithmetically or logically manipulating characters, a computer may concatenate strings of characters, replace some characters with others, or otherwise manipulate character strings. 计算机能将若干字符连成串，用一些字符代替其他字符或另行处理字符串，而不是用算术方法或逻辑方法处理字符。 5.Software applications like word processing, electronic spreadsheets, database management programs, painting and drawing programs, desktop publishing, and so forth became commercially available, giving more people reasons to use a computer. 软件应用，像文字处理、电子表格、数据库管理程序、绘图程序及桌面印刷等进入商业市场，使更多的人去使用计算机。 Chapter2 I. 1. the I/O subsystem 2. Read Only Memory(ROM) 3. SRAM 4. I/O interface 5. interrupts II. 1. false 2. true 3. false 4. false 5.false III. (2)RAM

常用光学期刊缩写

光学与应用光学等领域常用期刊英文缩写Acta Optica Sinica Acta Photonica Sinica AIP CONFERENCE PROCEEDINGS AIP CONF PROC APPLIED OPTICS APPL. OPTICS APPLIED PHYSICS LETTERS APPL PHYS LETT Chinese Journal of Lasers Chinese J. Lasers High Power Laser and Particle Beams IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE IEEE AERO EL SYS MAG IEEE ANNALS OF THE HISTORY OF COMPUTING IEEE ANN HIST COMPUT IEEE ANTENNAS AND PROPAGATION MAGAZINE IEEE ANTENNAS PROPAG IEEE CIRCUITS & DEVICES IEEE CIRCUITS DEVICE IEEE CIRCUITS AND DEVICES MAGAZINE IEEE CIRCUIT DEVIC IEEE COMMUNICATIONS LETTERS IEEE COMMUN LETT IEEE COMMUNICATIONS MAGAZINE IEEE COMMUN MAG IEEE COMPUTATIONAL SCIENCE & ENGINEERING IEEE COMPUT SCI ENG IEEE COMPUTER APPLICATIONS IN POWER IEEE COMPUT APPL POW IEEE COMPUTER GRAPHICS AND APPLICATIONS IEEE COMPUT GRAPH IEEE COMPUTER GROUP NEWS IEEE COMPUT GROUP N IEEE CONCURRENCY IEEE CONCURR

Velocity-Position Integration Formula (II)-Application to Inertial Navigation Computation

Velocity/Position Integration Formula (II): Application to Strapdown Inertial Navigation Computation Yuanxin Wu and Xianfei Pan Abstract— Inertial navigation applications are usually referenced to a rotating frame. Consideration of the navigation reference frame rotation in the inertial navigation algorithm design is an important but so far less seriously treated issue, especially for the future ultra-precision navigation system of several meters per hour. This paper proposes a rigorous approach to tackle the issue of navigation frame rotation in velocity/position computation by use of the newly-devised velocity/position integration formulae in the Part I companion paper. The two integration formulae set a well-founded cornerstone for the velocity/position algorithms design that makes the compr ehension of the iner tial navigation computation pr inciple mor e accessible to pr actitioner s, and differ ent appr oximations to the integr als involved will give bir th to var ious velocity/position update algorithms. Two-sample velocity and position algorithms are derived to exemplify the design process. In the context of level-flight airplane examples, the derived algorithm is analytically and numerically compared to the typical algorithms existing in the literature. The results throw light on the problems in existing algorithms and the potential benefits of the derived algorithm. Index Ter ms— iner tial navigation, velocity integr ation for mula, position integr ation for mula, fr ame rotation I.I NTRODUCTION Over fifty years have seen the fruitful algorithm development for the strapdown inertial navigation system using a triad of gyroscopes and accelerometers that are strapped down to the vehicle [1]. Because the inertial sensors rotate This work was supported in part by the Fok Ying Tung Foundation (131061), National Natural Science Foundation of China (61174002), the Foundation for the Author of National Excellent Doctoral Dissertation of People’s Republic of China (FANEDD 200897) and Program for New Century Excellent Talents in University (NCET-10-0900). Authors’ address: Department of Automatic Control, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, P. R. China, 410073. Tel/Fax: 086-0731-********-8212 (e-mail: yuanx_wu@https://www.wendangku.net/doc/10816155.html,).

PhaseCenterComputationofaCorrugatedHorn

Phase Center Computation of a Corrugated Horn Phase center computations are a very sensitive subject and difficult to measure. The location of the phase center depends upon a couple of parameters such as polarization direction, scan angle direction and aperture width. The device modeled in this application is a cylindrical corrugated horn with a linear vertical polarization, depicted in Figure 1. Figure 1:The CST MWS model showing the excitation direction and the definition of H- and E-Plane Correct settings are crucial in order to obtain meaningful results. The polarization of the E-field is along the E-plane (vertically orientated). Figure 2 shows the E-phi component in a three-dimensional view. It can be seen that this field component is very Figure 2:Field and H-plane scan direction settings

Revenue Limit Computation - School Financial ：年收入极限的计算-学校财务

2005-06 FINAL REVENUE LIMIT COMPUTATION 2420 HAMILTON 05OCT06 --> LINE 1: 2004-05 BASE REVENUE (ROUNDED) = 36,427,384 1. 2004-05 BASE REVENUE (LINE 1 FROM LEFT) 36,427,384 LN 1 AMNT MAY NOT EXCEED LN 9 OF FINAL 04-05 REV LIM WORKSHEET 2. BASE SEPT MEMB AVG (LINE 2 FROM LEFT) 3,946 3. 04-05 BASE REVENUE PER MEMBER (LN1 / LN2)(CENTS) 9,231.47 04-05 GENERAL AID CERT 10-15-04 (LN 12) + 16,628,146.00 4. 05-06 PER MEMB INCREASE (A+B) 248.48 04-05 COMPUTER AID, SCR 691(04-05 LN 17) + 123,477.00 A. ALLOWED PER PUPIL INCREASE 248.48 04-05 FND 10 LEVY CERT(04-05 LINE 18) + 19,425,114.00 B. LOW REV INCR: ((8100-(3+4A))-4C) (NOT < 0) 0.00 04-05 FND 38 LEVY CERT(04-05 LINE 14B) + 250,647.00 C. VALUE OF CCDEB IN LOW REVENUE DISTRICT 0.00 04-05 FND 41 LEVY CERT(04-05 LINE 14C) + 0.00 5. 05-06 MAXIMUM REVENUE / MEMB (LN 3 + LN 4) 9,479.95 04-05 AID PENALTY OVER LEVY(04-05 BOTTOM) - 0.00 6. CURR MEMB AVG (LINE 6 FROM LEFT) 4,039 7. 05-06 REV LIMIT, NO EXEMPT (LN5 X LN6) (ROUNDED) 38,289,518 04-05 LEVY FOR NON-RECURRING EXEMPTIONS (AMOUNT USED IN 04-05) 8. TOTAL RECURRING EXEMPTIONS (A+B+C+D+E) (RND) 68,127 UNUSED 04-05 RECURRING LEVY AUTHORITY= 0 04-05 NON-RECURRING REF TO EXCEED LIMIT - 0.00 04-05 DECLINING ENROLLMENT - 0.00 A. PRIOR YR CARRYOVER(100% OF AMT ABOVE) 0 04-05 OTHER NON-RECURRING - 0.00 B. TRAN OF SERVICE 68,127 C. TRANSFER OF TERRITORY 0 SEPTEMBER & SUMMER FTE MEMBERSHIP AVERAGES D. FED IMPACT AID LOSS (03-04 TO 04-05) 0 STARTING IN 2000, RES INTER FTE COUNTS ONLY 75%.) E. RECURR REF TO EXCEED(IF 05-06 1ST YR) 0 --> LINE 2: BASE AVG((02+.4SS+03+.4SS+04+.4SS)/3) = 3,946 2002 2003 2004 9. 2005-06 LIMIT WITH RECURRING EXEMPTIONS(LN7+LN8) 38,357,645 SUMMER FTE 78 76 77 10. TOTAL 05-06 NON-RECURRING EXEMPTIONS (A+B+C) 0 40%,40%,40% SUMMER 31 30 31 A. NON-RECURR REF, TO EXCEED 05-06 LIM 0 SEPT FTE 3,819 3,924 4,003 B. DECLIN ENROLL EXEMPT 05-06(FROM LEFT) 0 ------- ------- ------- C. OTHER NON-RECURRING EXEMPTION 0 TOTAL FTE 3,850 3,954 4,034 11. 2005-06 REVENUE LIMIT WITH EXEMPT (LN9 + LN10) 38,357,645 12. OCT 15 CERTIFICATION OF 2005-06 GENERAL AID 19,119,608 --> LINE 6: CURR AVG((03+.4SS+04+.4SS+05+.4SS)/3) = 4,039 13. ALLOWABLE LIMITED REV 10,38,41 LEVY+SRC 691 19,238,037 2003 2004 2005 (LINE 11 - LINE 12) (SRC 691 IS DOR COMPUTER AID) SUMMER FTE 76 77 85 40%,40%,40% SUMMER 30 31 34 14. LIMITED REVENUE TO BE USED (A+B+C) NOT>LN 13 19,219,077 SEPT FTE 3,924 4,003 4,095 AMNTS NEEDED BY PURPOSE AND FUND: ------- ------- ------- A. GEN OPER FND 10 INC 211 & 691 18,964,980 FUND 10+COMP AID TOTAL FTE 3,954 4,034 4,129 B. NON-REF DEBT(IN LIM)FD 38 210 254,097 ACTUAL FD 38 LEVY C. CAPITAL EXP FND 41 SRC 210 0 ACTUAL FD 41 LEVY --> LINE 10B: DECLINING ENROLLMENT EXEMPT = 0 15. TOTAL REVENUE FROM OTHER LEVIES (A+B+C+D) 3,326,781 AVERAGE FTE LOSS (LN 2 - LN 6, IF > 0) 0 A. REF APRVD DEBT (FD 39 210) 3,269,327 X 0.75 = 0 B. COMM SERV FND 80 SRC 210 33,500 X (LINE 5, MAXIMUM 05-06 REVENUE PER MEMB = 9,479.95 C. PRIOR YR LEVY CHRGEBK SRC 212 23,954 NON-RECURRING EXEMPTION AMOUNT = 0 D. OTHER LEVY, MLWK & KENOSHA 0 16. TOTAL LEVY+SRC 691 (LN14+LN15) 22,545,858 --> LINE 17: STATE AID FOR EXEMPT COMPUTERS= 120,629 17. SRC 691 AID (VOUCHERED BY DOR 5/1/06) 120,629 LINE 17 = A X (LINE 16 / C) (TO 8 DECIMALS) 18. FND 10 SRC 211 (LN14A-LN17), ACTUAL FD 10 LEVY 18,844,351 ENTER TAX VALUES FROM OCT 2005 CERT (MAILED 10/15/05) LINE 18(NOT 14A)IS THE FND 10 LEVY CERTIFIED BY THE BOARD A. 2005 EXEMPT COMPUTER PROPERTY VALUATION = 12,699,600 19. TOT ALL FUND TAX LEVY (18+14B+14C+15) 22,425,229 B. 2005 TIF-OUT TAX APPORTIONMENT EQ VALUE = 2,360,895,999 USE LINE 19 TO APPORT ON DOR SD-401. LEVY RATE = 0.00949861 C. 2005 TIF-OUT VAL + EXEMPT COMPUTERS(A+B)= 2,373,595,599 20. FUND 30 SRC210(38 + NON-38) (LN 14B + LN15A) 3,523,424 COMPUTER AID REPLACES A PORTION OF PROPOSED FUND 10 LEVY ALLOWABLE LESS ACTUAL (LN13-LN14) (UNDER LIMIT) 18,960 SRC691 = COMP VAL X (PROPOSED LEVY/(TIF-OUT VAL+COMP VAL))