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Terahertz and Mid Infrared Radiation: Detection of Explosives and CBRN (Using Terahertz) [Pehme köide]

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  • Formaat: Paperback / softback, 196 pages, kõrgus x laius: 235x155 mm, kaal: 392 g, 70 Illustrations, color; 33 Illustrations, black and white; XIII, 196 p. 103 illus., 70 illus. in color., 1 Paperback / softback
  • Sari: NATO Science for Peace and Security Series B: Physics and Biophysics
  • Ilmumisaeg: 03-Apr-2014
  • Kirjastus: Springer
  • ISBN-10: 940178583X
  • ISBN-13: 9789401785839
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Terahertz and Mid Infrared Radiation: Detection of Explosives and CBRN (Using Terahertz)Suurem pilt
  • Formaat: Paperback / softback, 196 pages, kõrgus x laius: 235x155 mm, kaal: 392 g, 70 Illustrations, color; 33 Illustrations, black and white; XIII, 196 p. 103 illus., 70 illus. in color., 1 Paperback / softback
  • Sari: NATO Science for Peace and Security Series B: Physics and Biophysics
  • Ilmumisaeg: 03-Apr-2014
  • Kirjastus: Springer
  • ISBN-10: 940178583X
  • ISBN-13: 9789401785839
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789401785839.html
Märksõnad:

The reader will find here a timely update on new THz sources and detection schemes as well as concrete applications to the detection of Explosives and CBRN. Included is a method to identify hidden RDX-based explosives (pure and plastic ones) in the frequency domain study by Fourier Transformation, which has been complemented by the demonstration of improvement of the quality of the images captured commercially available THz passive cameras. The presented examples show large potential for the detection of small hidden objects at long distances (6-10 m). Complementing the results in the short-wavelength range, laser spectroscopy with a mid-infrared, room temperature, continuous wave, DFB laser diode and high performance DFB QCL have been demonstrated to offer excellent enabling sensor technologies for environmental monitoring, medical diagnostics, industrial and security applications. From the new source point of view a number of systems have been presented - From superconductors to semiconductors, e.g. Detection of Terahertz Waves from Superconducting Bi2Sr2CaCu2O8+d Intrinsic Josephson Junctions. The quest for a compact room temperature THz source and the recent advances in high power mid-IR QCLs lead to the development of a semiconductor THz source based on intracavity difference frequency generation. Furthermore, alternative electrically pumped THz sources based on the high emission efficiency predicted for polaritonic states in the ultra-strong coupling regime led to the demonstration of electroluminescent devices. Finally, antipolaritons in dispersive media were discussed and different aspects of the interaction of THz radiation with biomatter were presented.

1 Introduction: Biostatistics and R
1(4)
1.1 Purpose of This Text
1(1)
1.2 Development of Biostatistics
2(1)
1.3 Development of R
3(1)
1.4 How R is Used in This Text
4(1)
2 Data Exploration, Descriptive Statistics, and Measures of Central Tendency
5(12)
2.1 Background on This Lesson
5(2)
2.1.1 Description of the Data
5(2)
2.1.2 Null Hypothesis (Ho)
7(1)
2.2 Data Import of a .csv Spreadsheet-Type Data File into R
7(2)
2.3 Organize the Data and Display the Code Book
9(1)
2.4 Conduct a Visual Data Check
9(1)
2.5 Descriptive Analysis of the Data
10(3)
2.6 Summary
13(1)
2.7 Addendum: Specialized External Packages and Functions
13(2)
2.8 Prepare to Exit, Save, and Later Retrieve This R Session
15(2)
3 Student's t-Test for Independent Samples
17(30)
3.1 Background on This Lesson
17(2)
3.1.1 Description of the Data
17(1)
3.1.2 Null Hypothesis (Ho)
18(1)
3.2 Data Import of a csv Spreadsheet-Type Data File into R
19(1)
3.3 Organize the Data and Display the Code Book
20(3)
3.4 Conduct a Visual Data Check
23(11)
3.5 Descriptive Analysis of the Data
34(6)
3.6 Conduct the Statistical Analysis
40(2)
3.7 Summary
42(1)
3.8 Addendum: t-Statistic v z-Statistic
43(2)
3.8.1 Create the Enumerated Dataset
44(1)
3.8.2 Calculate the t-Statistic
44(1)
3.8.3 Calculate the z-Statistic
45(1)
3.9 Prepare to Exit, Save, and Later Retrieve This R Session
45(2)
4 Student's t-Test for Matched Pairs
47(26)
4.1 Background on This Lesson
47(4)
4.1.1 Description of the Data
47(2)
4.1.2 Null Hypothesis (Ho)
49(1)
4.1.3 Unstacked Data and Stacked Data
49(2)
4.2 Data Import of a .csv Spreadsheet-Type Data File into R
51(1)
4.3 Organize the Data and Display the Code Book
52(2)
4.4 Conduct a Visual Data Check
54(6)
4.5 Descriptive Analysis of the Data
60(3)
4.6 Conduct the Statistical Analysis
63(2)
4.7 Summary
65(1)
4.8 Addendum 1: Stacked Data and Student's t-Test for Matched Pairs
66(4)
4.9 Addendum 2: The Impact of N on Student's t-Test
70(2)
4.10 Prepare to Exit, Save, and Later Retrieve This R Session
72(1)
5 Oneway Analysis of Variance (ANOVA)
73(26)
5.1 Background on This Lesson
73(2)
5.1.1 Description of the Data
73(2)
5.1.2 Null Hypothesis (Ho)
75(1)
5.2 Data Import of a csv Spreadsheet-Type Data File into R
75(2)
5.3 Organize the Data and Display the Code Book
77(5)
5.4 Conduct a Visual Data Check
82(5)
5.5 Descriptive Analysis of the Data
87(2)
5.6 Conduct the Statistical Analysis
89(4)
5.6.1 Exploratory Oneway ANOVA
90(1)
5.6.2 Oneway ANOVA Method 1: lm() and anova() Functions
91(1)
5.6.3 Oneway ANOVA Method 2: aov() and TukeyHSD() Functions
92(1)
5.7 Summary
93(3)
5.8 Addendum: Other Packages for Display of Oneway ANOVA
96(1)
5.9 Prepare to Exit, Save, and Later Retrieve This R Session
97(2)
6 Twoway Analysis of Variance (ANOVA)
99(30)
6.1 Background on This Lesson
99(1)
6.1.1 Description of the Data
99(1)
6.1.2 Null Hypothesis (Ho)
100(1)
6.2 Data Import of a csv Spreadsheet-Type Data File into R
100(1)
6.3 Organize the Data and Display the Code Book
101(3)
6.4 Conduct a Visual Data Check
104(7)
6.5 Descriptive Analysis of the Data
111(6)
6.6 Conduct the Statistical Analysis
117(5)
6.7 Summary
122(2)
6.8 Addendum: Other Packages for Display of Twoway ANOVA
124(2)
6.9 Prepare to Exit, Save, and Later Retrieve This R Session
126(3)
7 Correlation and Linear Regression
129(36)
7.1 Background on This Lesson
129(2)
7.1.1 Description of the Data
129(1)
7.1.2 Null Hypothesis (Ho)
130(1)
7.2 Data Import of a csv Spreadsheet-Type Data File into R
131(1)
7.3 Organize the Data and Display the Code Book
132(3)
7.4 Conduct a Visual Data Check
135(5)
7.5 Descriptive Analysis of the Data
140(2)
7.6 Conduct the Statistical Analysis
142(12)
7.6.1 Correlation Using Pearson's r
142(8)
7.6.2 Linear Regression
150(4)
7.7 Summary
154(1)
7.8 Addendum: Multiple Regression
155(8)
7.8.1 Hand-Calculate Multiple Regression
156(2)
7.8.2 Minimal Adequate Model (MAM) for Regression
158(2)
7.8.3 Stepwise Regression
160(3)
7.9 Prepare to Exit, Save, and Later Retrieve This R Session
163(2)
8 Future Actions and Next Steps
165
8.1 Use of This Text
165(1)
8.2 Future Use of R for Biostatistics
166(1)
8.3 External Resources
167(1)
8.4 Contact the Author
167