iosr-JVSP   Volume-10 ~ Issue-4 ~ Jul. - Aug. 2020

ABSTRACT: In this paper, IDDQ and IDDT testing methods are analyzed for bridging and stuck-open (SOP) faults in complementary metal-oxide semiconductor (CMOS) circuits. Two test circuits (one digital and one analog) are chosen and faults are injected at particular locations. Simulation is carried out in 90 nm technology using the Cadence Virtuoso platform to observe the current waveforms and detect faults. With reference to the test circuits, simulation results show that the IDDQ testing method is effective in detecting bridging fault for both digital and analog circuits, and SOP fault in analog circuits. On the other hand, the IDDT testing method successfully detects only SOP faults in digital circuits.

Keywords: IDDQ; IDDT; bridging fault; stuck-open; CMOS

[1]. International Technology Roadmap for Semiconductors, 2009 Edition, available at the following URL http://www.itrs.netiLinks/2009ITRS/Home2009.html
[2]. Hamieh L, Mehdi N, Omeirat G, ChehabA,Kayssi A. The Effectiveness of Delay and IDDT Tests in Detecting Resistive Open Defects for Nanometer CMOS Adder Circuits. IEEE 6th International Design and Test Workshop (IDT). 2011:53-57
[3]. Guibane B, Hamdi B,MtibaaA,Bensalem B. Fault tolerant system based on IDDQ testing. International journal of electronics. 2018; 105(6):1025-1035
[4]. Nuernbergk DM, Lang C.Fast and precise on-chip IDDQ current sensor. ANALOG 2016; 15. ITG/GMM-Symposium. 2016:1-6
[5]. Levi M. CMOS is Most Testable. International Test Conference. 1981:217–220

ABSTRACT: In the growing information era, information distribution and transferal has amplified exponentially. Images extremely donate to communication during this age of the multimedia. Safety, integrity, privacy, and verification services are the most significant factors in information security. Encryption is a method used to preserve image privacy. This paper presents a comprehensive study of various techniques for image encryption. The existing technology is analyzed with respect to algorithm, type of implementation, memory management, and mathematical computations. The main aim of this paper is to obtain a hybrid solution for the existing drawbacks and develop an enhanced system for image encryption and decryption. Many researchers' developments on improvingalgorithm's performance are reviewed in this paper. The proposed system in this paper focuses on design of hardware accelerator by using Cadence tools.

Keywords: Algorithm, Cryptography, Decryption, Encryption, Image, Information Security, Public key, Simulation

[1]. AnkitaAgarwal, ―Secret Key Encryption Algorithm Using Genetic Algorithm‖, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 4, April 2012
[2]. Mustafa Emad Hameed1,2, Masrullizam Mat Ibrahim1 , NurulfajarAbdManap1, ―Review on Improvement of Advanced Encryption Standard (AES) Algorithm based on Time Execution, Differential Cryptanalysis and Level of Security‖, Journal of Telecommunication, Electronic and Computer Engineering, Jan 2018
[3]. AmitChatterjee, JitendraDhanotia, Vimal Bhatia, SantoshRana, ShashiPrakash, ―Optical Image Encryption using Fringe Projection Profilometry, Fourier Fringe Analysis, and RSA Algorithm‖, 978-1-5386-4318-1/17/$31.00 ©2017 IEEE.
[4]. Shankha Mukherjee, Shankha Mukherjee, SouvikSinha, TamalMukhopadhyay, ―A meticulous implementation of RSA Algorithm using MATLAB for Image Encryption‖, 978-1-5386-1703-8/17/$31.00 ©2017 IEEE.
[5]. SandeepSrivastava, Sanjay Kumar, ―Image Encryption using Simplified Data Encryption Standard (S-DES)‖, International Journal of Computer Applications (0975 – 8887) Volume 104 – No.2, October 2014.

ABSTRACT:Analyzing the characteristics of an ECG signal plays a vital role in the detection of various Cardiovascular Diseases (CVDs). However the analysis of ECG signal is not a simple task. In this paper a broad survey is carried out over various approaches focused to analyze the characteristics of ECG signal to perform automatic Cardiac Arrhythmia detection. Initially, the details of ECG acquisition, Characteristics of ECG and the possible arrhythmias based on the abnormalities in the ECG signal are discussed. Based on the step by step execution of the system model, all the approaches are classified as preprocessing approaches, feature extraction approaches and classification approaches. These approaches are further classified in different ways based on the methodology used for accomplishment. This paper also discussed about various standard databases which are used for the implementation of developed approaches..

Keywords: ECG, Cardiovascular Diseases, Cardiac Arrhythmia, Feature Extraction, MIT-BIH.

[1]. Harikrishnan S, Leeder S, Huffman M, Jeemon P, Prabhakaran D, A Race against Time: The Challenge of Cardiovascular Disease in Developing Economies. 2nd ed. New Delhi, India: New Delhi Centre for Chronic Disease Control; 2014.
[2]. Xavier D, Pais P, Devereaux PJ, Xie C, Prabhakaran D, Reddy KS, Gupta R, Joshi P, Kerkar P, Thanikachalam S, Haridas KK, Jaison TM, Naik S, Maity AK, Yusuf S; CREATE registry investigators. Treatment and outcomes of acute coronary syndromes in India (CREATE): a prospective analysis of registry data. Lancet., 371, 2008, pp: 1435–1442.
[3]. A.S. Adabag, G. Peterson, F.S. Apple, J. Titus, R. King, R.V. Luepker, "Etiology of sudden death in the community: results of anatomic, metabolic, and genetic evaluation", Am. Heart. J. 159, 2010, pp: 33–39.
[4]. J.J. Goldberger, A.E. Buxton, M. Cain, O. Costantini, D.V. Exner, B.P. Knight, D.Lloyd-Jones, A.H. Kadish, B. Lee, A. Moss, R. Myerburg, J. Olgin, R. Passman, D.Rosenbaum, W. Stevenson, W. Zareba, D.P. Zipes, "Risk stratification for arrhythmic sudden cardiac death: identifying the roadblocks", Circulation, 123, 2011, pp: 2423–2430.
[5]. M. Velic, I. Padavic, S. Car, "Computer aided ECG Analysis – State of the Art and Upcoming Challenges", 2013,

ABSTRACT: Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. The paper focuses on techniques for image enhancement.

Keywords: Digital, Image Processing, Image Enhancement

[1]. Bhabatosh Chanda and Dwijest Dutta Majumder, 2012, Digital Image Processing and Analysis.
[2]. R.W.Jr. Weeks,(2012). Fundamental of Electronic Image Processing . Bellingham: SPIE Press
[3]. A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice Hall, 2013.
[4]. R.M. Haralick, and L.G. Shapiro, Computer and Robot Vision, Vol-1, Addison Wesley, Reading, MA, 2012.
[5]. R. Jain, R. Kasturi and B.G. Schunck, Machine Vision, McGraw-Hill International Edition, 1995..

ABSTRACT: Increasing complexity of VLSI designs makes it hard to follow fine details within a large design. Especially in variability studies it is important to be able to determine for example, edge lengths in the x and y direction of mask shapes, within a device or a circuit. The line-edge roughness variation vs. length scales within the circuit is valuable information for the effects of variability of circuit performance. In the current article a simulation flow is presented to help circuit designer, gain more understanding of the fabricated features of their circuits. Is starts from mask files in CIF format and decomposes them into their corresponding layers in order to be used in electron-beam-lithography simulations, stochastic-lithography simulation and line width roughness metrology studies. The code is integrated in a complete software suite

Keywords: Matlab, VLSI, layout, CIF, electron-beam lithography, stochastic-lithography, roughness, metrology.

[1]. https://en.wikipedia.org/wiki/Common_Intermediate_Format
[2]. G.P. Patsis, Ν. Glezos, Electron-beam lithography simulation for EUV mask applications, Journal of Physics: Conference Series, 10
(1), 2005, 385-388.
[3]. G. P. Patsis, N. Tsikrikas, I. Raptis, N. Glezos, Electron-beam lithography simulation for the fabrication of EUV masks,
Microelectronic Engineering, 83 (4-9 SPEC. ISS.), 2006, 1148-1151.
[4]. G. P. Patsis, M. D. Nijkerk, L. H. A. Leunissen, E. Gogolides, Simultation of material and processing effects on photoresist lineedge
roughness, International Journal of Computational Science and Engineering, 2 (3-4), 2006, 134-143.
[5]. G. P. Patsis, V. Constantoudis, A. Tserepi, E. Gogolides, Quantification of line-edge roughness of photoresists. I. A comparison
between off-line and on-line analysis of top-down scanning electron microscopy images, Journal of Vacuum Science and
Technology B: Microelectronics and Nanometer Structures, 21 (3), 2003, 1008-1018..

ABSTRACT:The integrated circuit/system designers are faced with problems that involves nano-scale devices with far less than ideal characteristics, very high integration densities (i.e. giga-scale complexity), very high operation speeds and data transmission rates, and system-level integration of analog and digital functions. The single-electron tunnelling (SET) devices might be scaled down almost to the molecular level. Gate length variability due to intra or inter die variations can lead to considerable mismatch between devices even inside the same chip. This variability has to be considered in detail and new device models should be developed, aiming in modelling its effects on the electrical characteristics of the devices. In the current article, a simple mosfet model is extended to incorporate gate length variability. The model is coded in VHDL-AMS in order to be used for simulation of circuit behavior within the framework of suitable system simulation software. Also first results of VHDL-AMS macro-modelling techniques for the compact simulation of single-electron circuits are presented. The macromodel of the SET, which is much more efficient than the corresponding Monte-Carlo calculations, is developed and can become a reasonably accurate tool for the simulation of complicated single-electron circuits.

Keywords: mosfet, line-width-roughness, vhdl-ams, digital-gates, single-electron-transistor, coulombblockage, compact-device-modelling

[1]. Y. S. Yu, H. S. Lee, and S. W. Hwang, SPICE Macro-Modelling for the Compact Simulation of Single Electron Circuits, J.
Korean Phys. Soc. 33, 1998, 269.
[2]. G. P. Patsis, Modelling MOSFET gate length variability for future technology node, Phys. Stat. Sol. (a) 205 (11), 2008, 2541-2543.
Ansys site: http://www.ansys.com.

ABSTRACT: Analyzing the characteristics of an ECG signal plays a vital role in the detection of various Cardiovascular Diseases (CVDs). However the analysis of ECG signal is not a simple task. In this paper a broad survey is carried out over various approaches focused to analyze the characteristics of ECG signal to perform automatic Cardiac Arrhythmia detection. Initially, the details of ECG acquisition, Characteristics of ECG and the possible arrhythmias based on the abnormalities in the ECG signal are discussed. Based on the step by step execution of the system model, all the approaches are classified as preprocessing approaches, feature extraction approaches.

Keywords: ECG, Cardiovascular Diseases, Cardiac Arrhythmia, Feature Extraction, MIT-BIH

[1]. Harikrishnan S, Leeder S, Huffman M, Jeemon P, Prabhakaran D, A Race against Time: The Challenge of Cardiovascular Disease in Developing Economies. 2nd ed. New Delhi, India: New Delhi Centre for Chronic Disease Control; 2014.
[2]. Xavier D, Pais P, Devereaux PJ, Xie C, Prabhakaran D, Reddy KS, Gupta R, Joshi P, Kerkar P, Thanikachalam S, Haridas KK, Jaison TM, Naik S, Maity AK, Yusuf S; CREATE registry investigators. Treatment and outcomes of acute coronary syndromes in India (CREATE): a prospective analysis of registry data. Lancet., 371, 2008, pp: 1435–1442.
[3]. A.S. Adabag, G. Peterson, F.S. Apple, J. Titus, R. King, R.V. Luepker, "Etiology of sudden death in the community: results of anatomic, metabolic, and genetic evaluation", Am. Heart. J. 159, 2010, pp: 33–39.
[4]. J.J. Goldberger, A.E. Buxton, M. Cain, O. Costantini, D.V. Exner, B.P. Knight, D.Lloyd-Jones, A.H. Kadish, B. Lee, A. Moss, R. Myerburg, J. Olgin, R. Passman, D.Rosenbaum, W. Stevenson, W. Zareba, D.P. Zipes, "Risk stratification for arrhythmic sudden cardiac death: identifying the roadblocks", Circulation, 123, 2011, pp: 2423–2430.
[5]. M. Velic, I. Padavic, S. Car, "Computer aided ECG Analysis – State of the Art and Upcoming Challenges", 2013