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Analyzing Handling Effects on Performance Parameters of Ethernet Cables using the Feature Selective Validation Method and Kolmogorov-Smirnov Test

Olusegun Ogundapo , Charles Nche, Alistair Duffy, Gang Zhang
American Journal of Electrical and Electronic Engineering. 2019, 7(3), 55-61. DOI: 10.12691/ajeee-7-3-1
Received June 24, 2019; Revised August 02, 2019; Accepted August 08, 2019

Abstract

The use of Ethernet cables is a vital, if under- discussed element of the infrastructure for the internet of things (IOT). While there are many cable types on the market, one worrying trend is the wide availability of copper clad aluminum (CCA) cables, which are widely considered unsuitable for infrastructure deployment. The availability of these copper clad aluminum (CCA) cables frequently disguised as compliant Ethernet communication cables calls for a method of assessing their performance, as this is crucial to ensuring quality of service delivery. This paper presents a method of analyzing the measured return loss and impedance profile due to handling stress. In this research, four Ethernet cables of which one of them was copper CCA cable were subjected to three rounds of coiling and uncoiling tests to represent stress from handling during installation. The Feature Selective Validation (FSV) method and Kolmogorov-Smirnov (KS) tests were used to quantify the variations between the tests. The results indicate that the CCA cable has the lowest resilience to physical stress with high potential for degradation.

1. Introduction

Ethernet cable is one of the fundamental communication channels used in internet of things infrastructure 1, 2. With the evolution of standards for Gigabit Ethernet over twisted pair, there has been a tremendous increase in its deployment as part of IOT infrastructure 3, 4.

The concept of Internet of Things (IOT) is one of the recognized directions in the evolution of the internet 5, 6. The IOT enables the combination of sensors, communication, information and energy processes to monitor and control a very large number of different objects 7. The IOT enabled information processing and communication can support objects in fast decision making, operational efficiency and improved situation awareness leading to its application in a wide range of fields such as transportation, industry, healthcare, energy, information and communication technology and networks 6.

The other motivation behind the IOT is the need to create a smart city that uses information and communication technologies (ICTs) to make services and monitoring more interactive and efficient 8, 9. The smartness of a city is enabled and driven technologically by the IOT 10.

To achieve the aforementioned advantages and applications of IOT requires the use of Ethernet cables that are of high quality and are reliable as a fundamental part of the overall physical layer. The selection or choice of Ethernet cables to meet the standards required in IOT infrastructure is a big challenge for cable professionals, contractors and installers.

The availability of counterfeit and non-standards compliant Ethernet cable coupled with copper clad aluminum (CCA) cables in the market masquerading as Ethernet cables pose a serious threat to the networking world 11, 12. The use of these substandard cables can affect network performance with potential liability to the contractor or installer 11, 13. Typically, for infrastructure deployment, the cables will be unwound off the reel, run-out where they need to go with the excess at the ends re-coiled for convenience, the ends will then be terminated. So, typically the cable could be re-coiled up to three times 14, 15. There is, therefore, the need for methods of evaluating the physical integrity of these cabling channels to ensure that they can be reused and would not degrade due to handling or installation stress. This paper presents a technique that can be used to evaluate the resilience of cables to the kind of handling stress they can be subjected. An additional benefit of this approach is that it provides the tools to undertake a more detailed analysis of partial data (magnitude only). This paper will concentrate on Category 6 cables due to their current popularity. Four Category 6 unshielded twisted pair (UTP) cables from different manufacturers are subjected to a series of coiling and uncoiling tests. The FSV and KS test are used to quantify the differences in return loss and impedance profiles between the first and the third coiling and uncoiling. The FSV and KS test are used due to the difficulty in making objective assessments visually with the human eye. The results of this analysis will be used to determine the cable that has the best, and worst, resilience to handling stress.

The paper consists of five sections. Section I is the introduction to the paper, section II deals with the background to the research, section III is the methodology used in measurements, section IV provides the results and discussions from the research and section V deals with the paper conclusion.

2. Background

2.1. Feature Selective Validation

The Feature Selective Validation (FSV) method is a validation tool that can be used to objectively quantify the similarity between data sets 17. The method has now been used to quantify data from a wide variety of sources, whether from experimental data, numerical models, computational electromagnetics etc. 17, 18. The method removes the human subjective judgement and enables objective decisions in the comparison of data 19.

The FSV method can be broken into the calculation of two components, the Amplitude Difference Measure (ADM) and the Feature Difference Measure (FDM). The combination of the ADM and FDM gives the Global Difference Measure (GDM) 20.

The ADM and FDM measure the overall differences in amplitude and characteristics or features of the data sets compared respectively 18, 20. The point by point comparison (ADMi, FDMi and GDMi) can be used to create histograms known as ADMc, FDMc and GDMc which can be classified into six quality descriptors: excellent, very good, good, fair, poor and very poor 20.

The single number quality indicators are used for quickly evaluating the average comparison between the two data sets are known as ADMtot, FDMtot and GDMtot 17. The FSV interpretation scale of these average single number indicators is shown in Table 1 21:

2.2. The Kolmogorov-Smirnov (KS) Test

The KS test was used to supplement the FSV comparison results and provide further analysis of the data sets. The KS test aims to determine if the distributions of two datasets differ significantly and have been explained in detail in 22, 23. The KS test has the advantage of making no assumption about the distribution of data 23, 24. The KS test uses the maximum vertical deviation between the two curves of the cumulative distributive functions (CDFs) as the statistic D given in 22, 23 as :

(11)

In equation (11), is the proportion of values less than or equal to x in the first data set and is the proportion of values less than or equal to x in the second data set. The critical value for different significance value is given in 23 as:

(12)

In equation (12), and is the length of the data sets compared and the value of k is given in 22, 23 for a confidence level of 95% (significance value as 1.36.

The p value determines if the difference is significant or otherwise 24. The null hypothesis means that the two data sets can be regarded as being from the same distribution 23. The null hypothesis will be rejected if the p value is smaller than the significance value or the test statistic D is greater than the critical value 23.

3. Methodology

3.1. Measurement Procedure

The impedance profile across the length of four Category 6 unshielded twisted pair (UTP) cables from different manufacturers were measured using an industrial standard DSX-5000 cable analyzer. The analyzer consists of two units: “main” and “remote”. The cable to be tested is connected through patch cord plugs to standard link interface adapters. The main and remote units have openings in which these link interface adapters are connected 25.

The DSX-5000 cable tester uses HDTDR (High-Definition Time Domain Reflectometry) to measure the impedance profile across the cables. The four Ethernet cables were tested according to International Standard ISO/IEC 11801 Class E, T568B pin connection for four pairs which allows performance of up to 250MHz 25. The four cables considered were marked as cable 1, cable 2, cable 3 and cable 4 for easy identification. Cable 2 was copper clad aluminum (CCA) cable. A 30m length of each cable was used for measurement to represent the last few meters that could be subjected to handling stress in real installation situations. The schematic diagram of the measurement set up is shown in Figure 1.

The cable measurements method was:

Measurements A: cables are used to form coils of about 30cm diameters and stretched out for measurement.

Measurements B: cables used for measurements A are reused to form coils of about 30 cm diameters and stretched out for measurement.

Measurements C: cables used for measurements B are reused to form coils of about 30cm diameters and stretched out for measurement.

4. Results and Discussions

The plots of the return loss measurements of the orange pair of the four cables, for illustration, across their length with Category 6 limits 16 are shown in Figure 2 to Figure 5. A view of the plots in Figure 2 to Figure 5 indicates that only the CCA cable 2 in Figure 3 crosses the Category 6 return loss limit. The CCA cable 2 therefore appears to be worse but needs objective confirmation. The aim of this paper is to objectively (quantitatively) compare the data. Which in this case, is to quantify the changes between the return loss measurement A (first test) which is the baseline and return loss measurement C (third test) of the four cables under examination.

The FSV return loss results of the comparison of measurement A (first test) and measurement C (third test) of the orange, green, blue and brown pairs are shown in Table 2 to Table 5 for cables 1 to 4. The FSV GDM results in Table 2 to Table 5 shows cable 1 (orange and brown pairs) and cable 4 (green and blue pairs) gave the least changes between return loss measurements A and C comparison. On the other hand, the FSV GDM results of Table 2 to Table 5 shows that the CCA gave the highest changes between return loss measurements A and C comparison for all the pairs. In summary, the FSV GDM result indicates that cable 1 and 4 showed the highest resilience to the three rounds of whole length coiling and uncoiling tests, while the CCA cable 2 showed the lowest resilience to the stress tests for all the pairs. However, all the cables show a fair comparison between return loss measurements A and C indicating the impact of the whole length coiling and uncoiling. The summary of the FSV result of the return loss measurements A and C comparison is illustrated with a chart in Figure 6.

To determine if the impact of the handling stress on the cables is significant or not, the KS test was used to compare measurement A (baseline) and measurement C (third test). Table 6 and Table 7 show the results of the KS test comparison of return loss measurements A and C using the orange, green, blue and brown pairs of cables 1 to 4. The critical value (Dcrit.) was calculated from equation (12), the value of k is 1.36 at a significance value (α) of 0.05, N1 and N2 is equal to 818 and (Dcrit) was found to be 0.067.

The KS test results in Table 6 and Table 7 shows that cable 1(orange, blue and brown pairs), cable 3 (orange and green pairs) and cable 4 (green pair) gave no significant difference between return loss measurements A and C as their P values are greater than 0.05 and D values is less than 0.067. On the other hand, the CCA cable (all pairs) showed significant difference between return loss measurements A and C as the P values are lower than 0.05 and D values greater than 0.067. The KS test D values of the comparison between return loss measurements A and C for the four cables is illustrated with a chart in Figure 7. Similarly, the KS test p values of the comparison between return loss measurements A and C is illustrated with a chart in Figure 8. In summary, the KS test result indicates that cable 1 showed the highest resilience to the three rounds of whole length coiling and uncoiling tests, while the CCA cable 2 showed the lowest resilience to the stress tests.

The graphs of the impedance profile measurements of the orange, green, blue and brown pairs of the four cables across their length are shown in Figure 9 to Figure 12. The FSV results of the comparison of impedance profile measurements A and C of the orange, green, blue and brown pairs are shown in Table 8 to Table 11 for cables 1 to 4. The FSV GDM results in Table 8 to Table 11 shows that the green, blue and brown pairs of cable 1and the orange pair of cable 3 gave the least changes between impedance profile measurements A and C comparison. On the other hand, the FSV GDM results of Table 8 to Table 11 shows that the CCA cable 2 (orange and brown pairs) and cable 4 (green and blue pairs) gave the largest changes between impedance profile measurements A and C comparison. The summary of the FSV GDM result indicates that cable 1 showed the highest resilience to the three rounds of whole length coiling and uncoiling tests, while the CCA cable 2 showed the lowest resilience to the stress tests. However, they all show a fair comparison between impedance profile measurements A and C comparison.

The results of the KS test using the orange, green, blue and brown pairs of cables 1 to 4 are shown in Table 12 and Table 13. The critical value (Dcrit.) was calculated from equation (12), the value of k is 1.36 at a significance value (α) of 0.05, N1 and N2 is equal to 233 and (Dcrit) was found to be 0.126. The KS test results in Table 12 and Table 13 shows that the test values D of all pairs of the four cables are below 0.126, while the P values of all pairs of the four cables are greater than 0.05. The D and P values in Table 12 and Table 13 show that the null hypothesis cannot be rejected or is accepted. The summary of the KS test D and P values of the comparison between impedance profile measurements A and C for the four cables are illustrated with charts in Figure 14 and Figure 15. In summary, this means the difference between the impedance profile measurements A and C is not significant to be considered as failure on the part of the cables. The KS test results obtained is true as none of the cables impedance profiles falls outside the +15/-15 of the 100Ω standard often specified for UTP cables.

5. Conclusion

This paper has presented an approach that can be used to evaluate cables resilience to handling stress and also undertake a more detailed analysis of the partial data (magnitude only). The research subjected four Category 6 UTP cables from different manufacturers to three rounds of coiling and uncoiling tests. The FSV GDM and KS test results for return loss shows that cable 1 presented the highest resilience to handling stress as it gave the lowest variations between measurements A (baseline) and C (third test) in most of it cable pairs. On the other hand, the CCA cable 2 gave the lowest resilience to handling stress as it gave the highest variations between return loss measurements A and C comparison for all pairs. Similarly, the FSV GDM for impedance profile measurements shows that cable 1 presented the highest resilience to handling stress as it gave the lowest variations in three of it pairs, while the CCA cable 2 gave the lowest resilience to handling stress as it gave the highest variations in two of it pairs. The KS test for impedance profile measurements A and C comparison indicates that they are not significant to be considered as failure on the part of all the cables pairs. The paper has therefore presented a technique that can be used by cable professionals to undertake a more detailed analysis of the partial data (magnitude only) obtained from UTP cable measurements.

References

[1]  M.Jung, C.Reinisch and W.Kastner, “Integrating Building Automation Systems and IPv6 in Internet of Things”, Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Palermo, July 2012, pp. 683-688.
In article      View Article
 
[2]  J. Randolph, “Introduction to Lightning and AC Power Fault Surge Protection for Telecom Signaling Cables”, IEEE Symposium on Product Compliance Engineering, Portland, November 2012, pp. 1-12.
In article      View Article
 
[3]  C.Spurgeon and J.Zimmerman, “Ethernet: The Definitive Guide”, Second Edition, O’Reilly Media Inc., 2014.
In article      
 
[4]  D.Law, D.Dove, J.D’Ambrosia, M.Hajduczenia, M.Laubach and S.Carlson, “Evolution of Ethernet Standards in the IEEE 802.3 Working group”, IEEE Communications Magazine,Vol.51, Issue 8, August, 2013, pp. 88-96.
In article      View Article
 
[5]  J. Stankovic, “Research Directions for the Internet of Things”, IEEE Internet of Things Journal, Vol.1, No. 1, March 2014, pp. 3-9.
In article      View Article
 
[6]  M. Sanctis, E. Cianca, G. Araniti, I. Bisio and R. Prasad, “Satellite Communications Supporting Internet of Remote Things”, IEEE Internet of Things Journal, Vol.3, No.1, February 2016, pp. 113-123.
In article      View Article
 
[7]  N.Bari, G.Mani and S.Berkorich, “Internet of Things as a Methodological Concept”, Fourth International Conference on Computing for Geospatial Research and Application, San Jose, July 2013, pp. 48-55.
In article      View Article
 
[8]  J.Jin, J.Gubbi, S.Marusic and M.Palaniswami, An Information Framework for Creating Smart City through the Internet of Things”, IEEE Internet of Things Journal, Vol. 1, No. 2, January 2014, pp. 112-121.
In article      View Article
 
[9]  R. Harmon, C. Leon and S. Bhide,“ Smart Cities and the Internet of Things”, International Conference on Management of Engineering and Technology, Portland, August 2015, pp. 485-494.
In article      View Article
 
[10]  A. Al-Faqaha, M. Guizani, M. Mohammadi, M. Aledhan and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols and Applications”,IEEE Communications Surveys and Tutorials, Vol.17, No. 4, June 2015, pp. 2347-2376.
In article      View Article
 
[11]  Fluke Networks: “Application Note: Copper Clad Aluminum (CCA) Cables”, [Online]. Available: http://www.flukenetworks.com/doc_links_pdf/en/content/application-note-copper-clad- aluminum-cables.
In article      
 
[12]  D.B.Kiddoo, “Update: Counterfeit and Non-Compliant Communications Cable”, 63rd International Wire and Cable Symposium, Rhode Island, USA, November 2014, pp.440- 475.
In article      
 
[13]  F. Peri, “Non-Compliant and Counterfeit Cable: A Risk Too Real to Ignore”, [Online]. Available:http://cccassoc.org/files/6314/0050/5728/CCCA- Article-on-Non-Compliant-Cable-in-ICT-Today-May-2014.pdf.
In article      
 
[14]  A.Oliviero and B.Woodward, Cabling: The Complete Guide to Copper and Fibre-Optic Networking,Fourth Edition, Wiley Publishing Inc., 2009.
In article      
 
[15]  J.Hayes and P.Rosenberg, Data,Voice, and Video Cabling,3rd Edition, Delmar Cengage Learning, 2009.
In article      
 
[16]  ANSI/TIA/EIA-568-B.2-1-2002: “Commercial Building Telecommunications Cabling Standard, Part 2: Balanced Twisted Pair Cabling Components - Addendum 1: Transmission Performance Specifications for 4-pair 100-ohm Category 6 Cabling", June, 2002.
In article      
 
[17]  O. Ventosa, M. Pous, F. Silva, R. Jauregui. “Application of Feature Selective Validation Method to Pattern Recognition”, IEEE Transactions on Electromagnetic Compatibility, Vol. 56, No. 4, August, 2014.
In article      View Article
 
[18]  Y. Sanchez, C. Rosi, E. Paez and M. Azpurua, “Feature Selective Validation Applied to the Comparison of Calibration Data, International Conference on Precision Electromagnetic Measurements, Rio de Janeiro, August, 2014, pp.194-195.
In article      View Article
 
[19]  M. Johnson, “FSV versus Human Subjective Data Evaluation; an Informal Survey”, IEEE International Symposium on Electromagnetic Compatibility, Pittsburgh, August, 2012, pp. 679-684.
In article      View Article  PubMed
 
[20]  B.Archambeault and J.Diepenbrock, “Quantifying the Quality of Agreement between Simulation and Validation Data for Multiple Data Sets”, IEEE International Symposium on Electromagnetic Compatibility, Florida, July, 2010, pp. 722-725.
In article      View Article
 
[21]  R. Telleria, F. Silva, A. Orlandi, H. Sasse and A. Duufy, “Factors Influencing the Successful Validation of Transient Phenomenon Modelling”, Asia-Pacific International Symposium on Electromagnetic Compatibility, Beijing, April, 2010, pp. 338-341.
In article      View Article
 
[22]  F.J. Massey, “The Kolmogorov-Smirnov Test for Goodness of Fit”, Journal of the American Statistical Association, vol. 46, No.253, March, 1951, pp.67-78.
In article      View Article
 
[23]  G. Zhang, A. Duffy, H. Sasse, W. Lixin, “The Use of Probability Density Functions to Improve the Interpretation of FSV Results”, IEEE International Symposium on Electromagnetic Compatibility, Pittsburgh, August 2012, pp. 685-689.
In article      View Article
 
[24]  T. Kirkman, “Statistics to Use”, 1996, [Online]. Available: http://www.physics.csbsju.edu/stats/KS-test.html.
In article      
 
[25]  “FLUKE networks: Versiv Cabling Certification Product Family User’s Manual”, [Online]. Available: http://download.flukenetworks.com/Download/Asset/9828877-c- en.pdf.
In article      
 

Published with license by Science and Education Publishing, Copyright © 2019 Olusegun Ogundapo, Charles Nche, Alistair Duffy and Gang Zhang

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Cite this article:

Normal Style
Olusegun Ogundapo, Charles Nche, Alistair Duffy, Gang Zhang. Analyzing Handling Effects on Performance Parameters of Ethernet Cables using the Feature Selective Validation Method and Kolmogorov-Smirnov Test. American Journal of Electrical and Electronic Engineering. Vol. 7, No. 3, 2019, pp 55-61. http://pubs.sciepub.com/ajeee/7/3/1
MLA Style
Ogundapo, Olusegun, et al. "Analyzing Handling Effects on Performance Parameters of Ethernet Cables using the Feature Selective Validation Method and Kolmogorov-Smirnov Test." American Journal of Electrical and Electronic Engineering 7.3 (2019): 55-61.
APA Style
Ogundapo, O. , Nche, C. , Duffy, A. , & Zhang, G. (2019). Analyzing Handling Effects on Performance Parameters of Ethernet Cables using the Feature Selective Validation Method and Kolmogorov-Smirnov Test. American Journal of Electrical and Electronic Engineering, 7(3), 55-61.
Chicago Style
Ogundapo, Olusegun, Charles Nche, Alistair Duffy, and Gang Zhang. "Analyzing Handling Effects on Performance Parameters of Ethernet Cables using the Feature Selective Validation Method and Kolmogorov-Smirnov Test." American Journal of Electrical and Electronic Engineering 7, no. 3 (2019): 55-61.
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  • Figure 1. Schematic diagram of the measurement set up (where, A1 and A2: Link interface adapters and patch plugs; B: Cable under test)
[1]  M.Jung, C.Reinisch and W.Kastner, “Integrating Building Automation Systems and IPv6 in Internet of Things”, Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Palermo, July 2012, pp. 683-688.
In article      View Article
 
[2]  J. Randolph, “Introduction to Lightning and AC Power Fault Surge Protection for Telecom Signaling Cables”, IEEE Symposium on Product Compliance Engineering, Portland, November 2012, pp. 1-12.
In article      View Article
 
[3]  C.Spurgeon and J.Zimmerman, “Ethernet: The Definitive Guide”, Second Edition, O’Reilly Media Inc., 2014.
In article      
 
[4]  D.Law, D.Dove, J.D’Ambrosia, M.Hajduczenia, M.Laubach and S.Carlson, “Evolution of Ethernet Standards in the IEEE 802.3 Working group”, IEEE Communications Magazine,Vol.51, Issue 8, August, 2013, pp. 88-96.
In article      View Article
 
[5]  J. Stankovic, “Research Directions for the Internet of Things”, IEEE Internet of Things Journal, Vol.1, No. 1, March 2014, pp. 3-9.
In article      View Article
 
[6]  M. Sanctis, E. Cianca, G. Araniti, I. Bisio and R. Prasad, “Satellite Communications Supporting Internet of Remote Things”, IEEE Internet of Things Journal, Vol.3, No.1, February 2016, pp. 113-123.
In article      View Article
 
[7]  N.Bari, G.Mani and S.Berkorich, “Internet of Things as a Methodological Concept”, Fourth International Conference on Computing for Geospatial Research and Application, San Jose, July 2013, pp. 48-55.
In article      View Article
 
[8]  J.Jin, J.Gubbi, S.Marusic and M.Palaniswami, An Information Framework for Creating Smart City through the Internet of Things”, IEEE Internet of Things Journal, Vol. 1, No. 2, January 2014, pp. 112-121.
In article      View Article
 
[9]  R. Harmon, C. Leon and S. Bhide,“ Smart Cities and the Internet of Things”, International Conference on Management of Engineering and Technology, Portland, August 2015, pp. 485-494.
In article      View Article
 
[10]  A. Al-Faqaha, M. Guizani, M. Mohammadi, M. Aledhan and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols and Applications”,IEEE Communications Surveys and Tutorials, Vol.17, No. 4, June 2015, pp. 2347-2376.
In article      View Article
 
[11]  Fluke Networks: “Application Note: Copper Clad Aluminum (CCA) Cables”, [Online]. Available: http://www.flukenetworks.com/doc_links_pdf/en/content/application-note-copper-clad- aluminum-cables.
In article      
 
[12]  D.B.Kiddoo, “Update: Counterfeit and Non-Compliant Communications Cable”, 63rd International Wire and Cable Symposium, Rhode Island, USA, November 2014, pp.440- 475.
In article      
 
[13]  F. Peri, “Non-Compliant and Counterfeit Cable: A Risk Too Real to Ignore”, [Online]. Available:http://cccassoc.org/files/6314/0050/5728/CCCA- Article-on-Non-Compliant-Cable-in-ICT-Today-May-2014.pdf.
In article      
 
[14]  A.Oliviero and B.Woodward, Cabling: The Complete Guide to Copper and Fibre-Optic Networking,Fourth Edition, Wiley Publishing Inc., 2009.
In article      
 
[15]  J.Hayes and P.Rosenberg, Data,Voice, and Video Cabling,3rd Edition, Delmar Cengage Learning, 2009.
In article      
 
[16]  ANSI/TIA/EIA-568-B.2-1-2002: “Commercial Building Telecommunications Cabling Standard, Part 2: Balanced Twisted Pair Cabling Components - Addendum 1: Transmission Performance Specifications for 4-pair 100-ohm Category 6 Cabling", June, 2002.
In article      
 
[17]  O. Ventosa, M. Pous, F. Silva, R. Jauregui. “Application of Feature Selective Validation Method to Pattern Recognition”, IEEE Transactions on Electromagnetic Compatibility, Vol. 56, No. 4, August, 2014.
In article      View Article
 
[18]  Y. Sanchez, C. Rosi, E. Paez and M. Azpurua, “Feature Selective Validation Applied to the Comparison of Calibration Data, International Conference on Precision Electromagnetic Measurements, Rio de Janeiro, August, 2014, pp.194-195.
In article      View Article
 
[19]  M. Johnson, “FSV versus Human Subjective Data Evaluation; an Informal Survey”, IEEE International Symposium on Electromagnetic Compatibility, Pittsburgh, August, 2012, pp. 679-684.
In article      View Article  PubMed
 
[20]  B.Archambeault and J.Diepenbrock, “Quantifying the Quality of Agreement between Simulation and Validation Data for Multiple Data Sets”, IEEE International Symposium on Electromagnetic Compatibility, Florida, July, 2010, pp. 722-725.
In article      View Article
 
[21]  R. Telleria, F. Silva, A. Orlandi, H. Sasse and A. Duufy, “Factors Influencing the Successful Validation of Transient Phenomenon Modelling”, Asia-Pacific International Symposium on Electromagnetic Compatibility, Beijing, April, 2010, pp. 338-341.
In article      View Article
 
[22]  F.J. Massey, “The Kolmogorov-Smirnov Test for Goodness of Fit”, Journal of the American Statistical Association, vol. 46, No.253, March, 1951, pp.67-78.
In article      View Article
 
[23]  G. Zhang, A. Duffy, H. Sasse, W. Lixin, “The Use of Probability Density Functions to Improve the Interpretation of FSV Results”, IEEE International Symposium on Electromagnetic Compatibility, Pittsburgh, August 2012, pp. 685-689.
In article      View Article
 
[24]  T. Kirkman, “Statistics to Use”, 1996, [Online]. Available: http://www.physics.csbsju.edu/stats/KS-test.html.
In article      
 
[25]  “FLUKE networks: Versiv Cabling Certification Product Family User’s Manual”, [Online]. Available: http://download.flukenetworks.com/Download/Asset/9828877-c- en.pdf.
In article