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i-manager's Journal on Electronics Engineering (JELE)

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An analytical approach to Network with IoT security using NodeMCU access point- Prevention Technique
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FEATURE EXTRACTION AND CLASSIFICATION OF DIFFERENT HAND MOVEMENTS FROM THE EMG SIGNAL USING LINEAR DISCRIMINANT ANALYSIS CLASSIFIER

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Volume 13 Issue 4 July - September 2023

Research Paper

A Procedure to Analyze Digital Circuits in CNTFET and CMOS Technology by ADS

Roberto Marani* , Anna Gina Perri**

* Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy, Milan, Italy.

** Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy.

Marani, R., and Perri, A. G. (2023). A Procedure to Analyze Digital Circuits in CNTFET and CMOS Technology by ADS. i-manager’s Journal on Electronics Engineering, 13(4), 1-9. https://doi.org/10.26634/jele.13.4.20048

Abstract

This paper proposes a procedure to analyze digital circuits in both Carbon Nanotube Field-Effect Transistors (CNTFET) and Complementary Metal-Oxide-Semiconductor (CMOS) technology for the purpose of comparison. The procedure is applied to study a NAND gate, with an emphasis on its applicability to analyze other digital circuits. To demonstrate this versatility, the procedure is also used to analyze a NOT gate in both CNTFET and CMOS technology. The paper presents the improvements achieved with CNTFET technology compared to CMOS. All simulations are conducted using the Advanced Design System (ADS) software, compatible with the Verilog-A programming language. Results from the analysis reveal that CNTFET technology exhibits superior performance, particularly at lower supply voltages. The paper also quantifies the differences in propagation delay, with CNTFET technology outperforming CMOS technology by a significant margin.

References

[1]. Dadoria, A. K., & Khare, K. (2019). Design and analysis of low-power adiabatic logic circuits by using CNTFET technology. Circuits, Systems, and Signal Processing, 38, 4338-4356.

[2]. Datta, S. (1995). Cambridge Studies in Semiconductor Physics and Microelectronic Engineering 3. Electronic Transport in Mesoscopic Systems. Cambridge University Press, New York.

[3]. Gelao, G., Marani, R., Diana, R., & Perri, A. G. (2011). A semiempirical SPICE model for n-type conventional CNTFETs. IEEE Transactions on Nanotechnology, 10(3), 506-512.

[4]. Hartmann, M., Hermann, S., Marsh, P. F., Rutherglen, C., Wang, D., Ding, L., & Schröter, M. (2021). CNTFET technology for RF applications: Review and future perspective. IEEE Journal of Microwaves, 1(1), 275-287.

[5]. Marani, R., & Perri, A. G. (2011). A Compact, Semiempirical model of carbon nanotube field effect transistors oriented to simulation software, Current Nanoscience, 7(2), 245-253.

[6]. Marani, R., & Perri, A. G. (2012). A DC model of carbon nanotube field effect transistor for CAD applications. International Journal of Electronics, 99(3), 437-444.

[7]. Marani, R., & Perri, A. G. (2015). Analysis of CNTFETs operating in subthreshold region for low power digital applications. ECS Journal of Solid State Science and Technology, 5(2), M1.

[8]. Marani, R., & Perri, A. G. (2017a). CNTFET-based design of current mirror in comparison with MOS Technology. ECS Journal of Solid State Science and Technology, 6(5), M60.

[9]. Marani, R., & Perri, A. G. (2018). Design and simulation study of full adder circuit based on CNTFET and CMOS technology by ADS. ECS Journal of Solid State Science and Technology, 7(6), M108.

[10]. Marani, R., and Perri, A.G. (2017b). A simulation study of basic digital circuits using molecular diodes. i-manager's Journal on Electronics Engineering, 7(3), 7-16.

[11]. Marani, R., Gelao, G., & Gina Perri, A. (2012). Comparison of ABM SPICE library with Verilog-A for Compact CNTFET model implementation. Current Nanoscience, 8(4), 556-565.

[12]. Marani, R., Gelao, G., & Perri, A. G. (2013). Modelling of carbon nanotube field effect transistors oriented to SPICE software for A/D circuit design. Microelectronics Journal, 44(1), 33-38.

[13]. Marulanda, J. M., & Srivastava, A. (2008). Carrier density and effective mass calculations in carbon nanotubes. Physica Status Solidi (B), 245(11), 2558-2562.

[14]. Perri, A. G. (2009). Fundamentals of Electronics. Progedit, Italy.

[15]. Perri, A.G. (2011). Advanced Electronic Devices. Progedit, Italy.

[16]. Perri, A.G., & Marani, R. (2017). CNTFET Electronics: Design Principles, Progedit Italy.

[17]. Pregaldiny, F., Lallement, C., & Kammerer, J. B. (2006, September). Design-oriented compact models for CNTFETs. In International Conference on Design and Test of Integrated Systems in Nanoscale Technology, 2006 (pp. 34-39). IEEE.

[18]. Raychowdhury, A., Mukhopadhyay, S., & Roy, K. (2004). A circuit-compatible model of ballistic carbon nanotube field-effect transistors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 23(10), 1411-1420.

[19]. Srivastava, A., Marulanda, J. M., Xu, Y., & Sharma, A. K. (2009). Current transport modeling of carbon nanotube field effect transistors. Physica Status Solidi (a), 206(7), 1569-1578.

[20]. Zarandi, A. D., Reshadinezhad, M. R., & Rubio, A. (2020). A systematic method to design efficient ternary high performance CNTFET-based logic cells. IEEE Access, 8, 58585-58593.

[21]. Zareei, Z., Bagherizadeh, M., Shafiabadi, M., & Mehrabani, Y. S. (2021). Design of efficient approximate 1-bit Full Adder cells using CNFET technology applicable in motion detector systems. Microelectronics Journal, 108, 104962.

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Research Paper

Design of Virtual Electrical Laboratories for Performing Steady State and Transient Response of R-L, R-C and R-L-C Circuit

Souptik Das* , Tirthankar Chakraborty, Abantika Choudhary*, Sayan Paramanik**, Krishna Sarker*, Koustuv Sarkar****

-,*- Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India.

Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

Das, S., Chakraborty, T., Choudhary, A., Paramanik, S., Sarker, K., and Sarkar, K. (2023). Design of Virtual Electrical Laboratories for Performing Steady State and Transient Response of R-L, R-C and R-L-C Circuit. i-manager’s Journal on Electronics Engineering, 13(4), 10-25. https://doi.org/10.26634/jele.13.4.20069

Abstract

This paper delves into the concept of virtual electrical laboratories, offering a comprehensive exploration of their design and functionality. A user-centered perspective is employed to analyze existing limitations and underscore the critical need for improved usability in virtual lab design. The study proposes practical applications aimed at swiftly enhancing the efficacy of these virtual environments, focusing on experiments involving R-L-C, R-L, and R-C circuits for both steadystate and transient responses. Using JavaScript, Hypertext Markup Language (HTML), and Cascading Style Sheets (CSS), the paper introduces a validated methodology through real-time experiments conducted in the laboratory and on the proposed virtual lab platform. The versatility of this approach positions it as a viable solution for implementation in various domains, including electric machines, power systems, and circuit theory labs. In alignment with the growing trend of long-distance education, where students seek engagement in diverse experiments from their homes, this paper contributes to the evolution of virtual electrical laboratories.

References

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[8]. Dow, C.R., Li, Y.H., & Bai, J.Y. (2006). A virtual laboratory for teaching digital signal processing. International Journal of Distance Education Technologies (IJDET), 4(2), 1-13.

[9]. Faltin, N., Böhne, A., Tuttas, J., & Wagner, B. (2002, August). Distributed team learning in an Internet-assisted laboratory. In International Conference on Engineering Education (pp. 18-22). Manchester, UK Manchester, UK.

[10]. Feisel, L. D., & Rosa, A. J. (2005). The role of the laboratory in undergraduate engineering education. Journal of Engineering Education, 94(1), 121-130.

[11]. Guo, L., Abdul, N. M. M., Vengalil, M., Wang, K., & Santuzzi, A. (2022). Engaging renewable energy education using a web-based interactive microgrid virtual laboratory. IEEE Access, 10, 60972-60984.

[12]. Guo, L., Vengalil, M., Abdul, N. M. M., & Wang, K. (2022). Design and implementation of virtual laboratory for a microgrid with renewable energy sources. Computer Applications in Engineering Education, 30(2), 349-361.

[13]. Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundations for the twenty first century. Science Education, 88(1), 28-54.

[14]. Kumar, M., Emory, J., & Choppella, V. (2018, July). Usability analysis of virtual labs. In 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), (pp. 238-240). IEEE.

[15]. Pei, X. (2021). Virtual instrument based on electronic and electrician's experiment teaching laboratory design. Procedia Computer Science, 183, 120-125.

[16]. Pereira, C. E., Paladini, S., & Schaf, F. M. (2012, March). Control and automation engineering education: Combining physical, remote and virtual labs. In International Multi-Conference on Systems, Signals & Devices (pp. 1-10). IEEE.

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[19]. Sibué, J. R., Kwimang, G., Ferrieux, J. P., Meunier, G., Roudet, J., & Périot, R. (2012). A global study of a contactless energy transfer system: Analytical design, virtual prototyping, and experimental validation. IEEE Transactions on Power Electronics, 28(10), 4690-4699.

[20]. Sivakumar, S. C., Robertson, W., Artimy, M., & Aslam, N. (2005). A web-based remote interactive laboratory for Internetworking education. IEEE Transactions on Education, 48(4), 586-598.

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[22]. Soriano, A., Ponce, P., & Molina, A. (2019, May). A novel design of virtual laboratory. In 2019 20th International Conference on Research and Education in Mechatronics (REM) (pp. 1-6). IEEE.

[23]. Sunanda, C., Hemalatha, J.N., & Trilokchandran. (2022). A Case Study with Virtual Lab on Electrical Engineering Experiments. Department of Biotechnology, RV College of Engineering (pp. 1-6).

[24]. Uran, S., & Jezernik, K. (2008). Virtual laboratory for creative control design experiments. IEEE Transactions on Education, 51(1), 69-75.

[25]. Watson, K. (1995, November). Utilization of active and cooperative learning in EE courses: Three classes and the results. In Proceedings Frontiers in Education 1995 25th Annual Conference. Engineering Education for the 21st Century, 2, 3c2-1. IEEE.

[26]. Zeng-guo, L. I. (2008). The construction of the electrics and electronics network virtual laboratory system. Journal of Baoding University, 4.

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Research Paper

Speech Enhancement for Noisy Signals using Adaptive Algorithms

Anna Rahul Kasukurthy* , Uma Sankar Chintala D.**

* Department of Electronics and Communication Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

** Department of Electrical and Electronics Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

Kasukurthy, A. R., and Chintala, D. U. S. (2023). Speech Enhancement for Noisy Signals using Adaptive Algorithms. i-manager’s Journal on Electronics Engineering, 13(4), 26-35. https://doi.org/10.26634/jele.13.4.20099

Abstract

Speech enhancement is a signal processing technique used to improve the quality and intelligibility of speech recordings that contain noise or interference. Its main goal is to eliminate unwanted background noise while preserving the clarity and naturalness of the speech signal. This paper provides a comprehensive analysis of three widely used adaptive filtering algorithms, Least Mean Square (LMS), Normalized Least Mean Square (NLMS), and Affine Projection Algorithm (APA). The limitations of LMS, such as slow convergence and sensitivity to input variations, are addressed in this study. By incorporating normalization, NLMS improves convergence speed and robustness to input power levels. The Affine Projection Algorithm (APA) is known for its exceptional performance in non-stationary environments, achieved through subspace projection to estimate optimal filter coefficients, resulting in faster convergence and improved tracking capabilities. In this paper, the algorithms are compared using Signal-to-Noise Ratio (SNR), Mean-Square Error (MSE), and Root-Mean-Square-Error (RMSE) values.

References

[1]. Anoop, V., Rao, P. V., & Nidhin, M. (2015, April). Performance analysis of speech enhancement methods using adaptive algorithms and optimization techniques. In 2015 International Conference on Communications and Signal Processing (ICCSP) (pp. 1306-1310). IEEE.

[2]. Ballanger, M. G. (2001). Adaptive Digital Filters. Marcel Dekker Inc, New York (pp.1-450).

[3]. Boroujeny, B.F. (1999). Adaptive Filters: Theory and Applications. John Wiley & Sons, New York.

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[5]. Chassaing, R. (2002). DSP Applications using C and the TMS320C6x DSK. John Wiley & Sons, New York.

[6]. Cowan, C.F.N., & Grant, P.M. (1985). Adaptive Filters. Prentice-Hall, New Jersey.

[7]. Diniz, S. R. P. (2015). Adaptive Filtering: Algorithms and Practical Implementations. Springer, New York (pp. 1-659).

[8]. Elliott, S.J. (2001). Signal Processing for Active Control. Academic Press, UK.

[9]. Gupta, D., Gupta, V. K., & Chandra, M. (2017). Performance comparison of different affine projection algorithms for noise minimization from speech signals. International Journal of Future Generation Communication and Networking, 10(1), 261-270.

[10]. Hadei, S. (2011). A family of adaptive filter algorithms in noise cancellation for speech enhancement. arXiv.

[11]. Haykin, S. S. (1996). Adaptive Filter Theory. Pearson Education, India (pp. 1-752).

[12]. Haykin, S. S. (2008). Adaptive Filter Theory. Pearson Education, India, 3, 1-936.

[13]. Ifeachor, E. C., & Jervis, B. W. (2002). Digital Signal Processing: A Practical Approach. Pearson Education, UK (pp. 542-552). (Ifeachor & Jervis, 2002; Diniz, 2015; Haykin, 1996)

[14]. Kalamani, M., Valarmathy, S., & Krishnamoorthi, M. (2014). Modified noise reduction algorithm for speech enhancement. Applied Mathematical Sciences, 8(89), 4447-4452.

[15]. Kuo, S. M., & Morgan, D. R. (1999). Active noise control: A tutorial review. Proceedings of the IEEE, 87(6), 943-973.

[16]. Mousa, A., Qados, M., & Bader, S. (2012). Speech signal enhancement using adaptive noise cancellation techniques. Canadian Journal on Electrical and Electronics Engineering, 3(7), 375-383.

[17]. Paulo, S.D., (2008). Adaptive filtering: Algorithms and practical implementation. The International Series in Engineering and Computer Science, 23-50.

[18]. Ram, R., & Mohanty, M. N. (2016). Performance analysis of adaptive algorithms for speech enhancement applications. Indian Journal of Science and Technology, 9(44), 1-9.

[19]. Sayed, A. H. (2003). Fundamentals of Adaptive Filtering. John Wiley & Sons, New Jersey.

[20]. Thakkar, V. (2017). Noise cancellation using least mean square algorithm. IOSR Journal of Electronics and Communication Engineering, 12(5), 64-75.

[21]. Widrow, B., & Hoff, M. E. (1960, August). Adaptive switching circuits. In IRE WESCON Convention Record, 4(1), 96-104.

[22]. Widrow, B., Glover, J. R., McCool, J. M., Kaunitz, J., Williams, C. S., Hearn, R. H., & Goodlin, R. C. (1975). Adaptive noise cancelling: Principles and applications. Proceedings of the IEEE, 63(12), 1692-1716.

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Research Paper

An Approach to Harmonic Optimization for 25KVA Auxiliary Converter used in Indian Railway

Shawanti Roy* , Sayan Paramanik, Krishna Sarker*

, Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India.

Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

Roy, S., Paramanik, S., and Sarker, K. (2023). An Approach to Harmonic Optimization for 25KVA Auxiliary Converter used in Indian Railway. i-manager’s Journal on Electronics Engineering, 13(4), 36-47. https://doi.org/10.26634/jele.13.4.20155

Abstract

As the Indian railway network expands, the demand for reliable and efficient power systems, especially auxiliary converters supporting various on-board systems, grows. By reducing power losses and fuel consumption, it is more crucial to design an energy-efficient and economic auxiliary converter for the railway system. This is partially accomplished by using a 25KVA auxiliary (Aux.) converter, which can accept input electrical energy from a 110V DC battery at Self-Generation (SG) coaches. Biogeography Based Optimization (BBO) method of harmonic elimination for a 25KVA converter is described in this study. The paper explores the 120-degree mode of conduction and compares the existing technique with a proposed 7-switching selective odd harmonic removal method. Results from Matlab simulations demonstrate the effectiveness of the BBO technique in reducing Total Harmonic Distortion (THD). The output voltage waveforms with and without BBO are compared, showcasing a significant improvement in harmonic suppression. The paper concludes by emphasizing the practical implementation of the optimized switching angles using an ATmega2560R3 microcontroller. The online application of stored switching angles on the microcontroller is calculated offline.

References

[1]. Duffey, C. K., & Stratford, R. P. (1989). Update of harmonic standard IEEE-519: IEEE recommended practices and requirements for harmonic control in electric power systems. IEEE Transactions on Industry Applications, 25(6), 1025-1034.

[2]. Enjeti, P. N., Ziogas, P. D., & Lindsay, J. F. (1988, October). Programmed PWM techniques to eliminate harmonics-A critical evaluation. In Conference Record of the 1988 IEEE Industry Applications Society Annual Meeting (pp. 418-430). IEEE.

[3]. Mahrous, E. A., Rahim, N. A., & Hew, W. P. (2007). Threephase three-level voltage source inverter with low switching frequency based on the two-level inverter topology. IET Electric Power Applications, 1(4), 637-641.

[4]. Hoseinpour, A., Barakati, S. M., & Ghazi, R. (2012). Harmonic reduction in wind turbine generators using a Shunt Active Filter based on the proposed modulation technique. International Journal of Electrical Power & Energy Systems, 43(1), 1401-1412.

[5]. Sun, J., & Grotstollen, H. (1992, November). Solving nonlinear equations for selective harmonic eliminated PWM using predicted initial values. In Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation (pp. 259-264). IEEE.

[6]. Wells, J. R., Nee, B. M., Chapman, P. L., & Krein, P. T. (2005). Selective harmonic control: A general problem formulation and selected solutions. IEEE Transactions on Power Electronics, 20(6), 1337-1345.

[7]. Agelidis, V. G., Balouktsis, A., Balouktsis, I., & Cossar, C. (2006). Multiple sets of solutions for harmonic elimination PWM bipolar waveforms: Analysis and experimental verification. IEEE Transactions on Power Electronics, 21(2), 415-421.

[8]. Maswood, A. I., Wei, S., & Rahman, M. A. (2001, March). A flexible way to generate PWM-SHE switching patterns using genetic algorithm. In APEC 2001. Sixteenth Annual IEEE Applied Power Electronics Conference and Exposition, 2, 1130-1134. IEEE.

[9]. Ray, R. N., Chatterjee, D., & Goswami, S. K. (2009). An application of PSO technique for harmonic elimination in a PWM inverter. Applied Soft Computing, 9(4), 1315-1320.

[10]. Acharjee, P., & Goswami, S. K. (2009). Expert algorithm based on adaptive particle swarm optimization for power flow analysis. Expert Systems with Applications, 36(3), 5151-5156.

[11]. Simon, D. (2008). Biogeography-based optimization. IEEE Transactions on Evolutionary Computation, 12(6), 702-713.

[12]. Kavitha, R., & Thottungal, R. (2016). Harmonic elimination of seven level inverter with switching pattern reconfiguration technique using hybrid BBO/MAS algorithm. International Journal of Applied Power Engineering (IJAPE), 5(2), 79-86.

[13]. Kavitha, R., & Rani, T. (2018). Reconfigurable selective harmonic elimination technique for wide range operations in asymmetric cascaded multilevel inverter. Journal of Power Electronics, 18(4), 1037-1050.

[14]. Ozpineci, B., Tolbert, L. M., & Chiasson, J. N. (2004, June). Harmonic optimization of multilevel converters using genetic algorithms. In 2004 IEEE 35th Annual Power Electronics Specialists Conference, 5, 3911-3916. IEEE.

[15]. Chen, X., Chen, B., Tian, C., Yuan, J., & Liu, Y. (2011). Modeling and harmonic optimization of a two-stage saturable magnetically controlled reactor for an arc suppression coil. IEEE Transactions on Industrial Electronics, 59(7), 2824-2831.

[16]. Aghdam, M. H., Fathi, S. H., & Gharehpetian, G. B. (2007, October). Comparison of OMTHD and OHSW harmonic optimization techniques in multi-level voltageth source inverter with non-equal DC sources. In 2007 7th Internatonal Conference on Power Electronics (pp. 587-591). IEEE.

[17]. Holmes, D. G., McGrath, B. P., Segaran, D., & Kong, W. Y. (2008, October). Dynamic control of a 20kW interleaved boost converter for traction applications. In 2008 IEEE Industry Applications Society Annual Meeting (pp. 1-8). IEEE.

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Research Paper

A Novel Wearable Biosensor for Real-Time Alcohol Detection

Ushaa Eswaran* , Vishal Eswaran, Keerthna Murali*, Vivek Eswaran****

* Principal & Professor, Department of ECE, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India.

Senior Data Engineer, CVS Health Centre, Dallas, Texas, United States.

* Site Reliability Engineer II, Dell Technologies, Austin, Texas, United States.

**** Senior Software Engineer, Tech Lead at Medallia, Austin, Texas, United States.

Eswaran, U., Eswaran, V., Murali, K., and Eswaran, V. (2023). A Novel Wearable Biosensor for Real-Time Alcohol Detection. i-manager’s Journal on Electronics Engineering, 13(4), 48-55. https://doi.org/10.26634/jele.13.4.20192

Abstract

Alcohol misuse has become a major public health concern worldwide. The development of an accurate, non-invasive, and cost-effective method for real-time alcohol detection would have important applications for monitoring and preventing alcohol misuse. This paper proposes a novel wearable biosensor for real-time alcohol detection in sweat. The biosensor uses alcohol oxidase immobilized on a screen-printed electrode to amperometrically detect ethanol in sweat samples. An artificial sweat solution was used to optimize the sensor design and evaluate its analytical performance. The optimized biosensor demonstrated a linear response to ethanol in the concentration range of 0.1–1.0 g/dL, with a limit of detection of 0.02 g/dL. On-body trials of the wearable biosensor provided rapid measurements that strongly correlated with blood alcohol content. This approach could offer a convenient solution for continuous, non-invasive alcohol monitoring to help reduce alcohol misuse and promote healthy behaviors. Further research on long-term use, alternate electrode geometries, and fully integrated wearable designs is warranted.

References

[1]. ASTM International. (2018). ASTM D1193-06: Standard Specification for Reagent Water.

[2]. Bandodkar, A. J., Jia, W., Yardımcı, C., Wang, X., Ramirez, J., & Wang, J. (2015). Tattoo-based noninvasive glucose monitoring: A proof-of-concept study. Analytical Chemistry, 87(1), 394-398.

[3]. Campbell, A. S., Kim, J., & Wang, J. (2018). Wearable electrochemical alcohol biosensors. Current Opinion in Electrochemistry, 10, 126-135.

[4]. Davis-Martin, R. E., Alessi, S. M., & Boudreaux, E. D. (2021). Alcohol use disorder in the age of technology: A review of wearable biosensors in alcohol use disorder treatment. Frontiers in Psychiatry, 12, 642813.

[5]. DiMartini, A., Behari, J., Dunn, M., Bataller, R. A., Jakicic, J. M., McNulty, M., & Dew, M. A. (2023). Challenges and solutions for monitoring alcohol use in patients with alcohol related liver disease: Pilot study of a wearable alcohol biosensor. Psychosomatic Medicine, 85(7), 596-604.

[6]. Gamella, M., Campuzano, S., Manso, J., de Rivera, G. G., López-Colino, F., Reviejo, A. J., & Pingarrón, J. M. (2014). A novel non-invasive electrochemical biosensing device for in situ determination of the alcohol content in blood by monitoring ethanol in sweat. Analytica Chimica Acta, 806, 1-7.

[7]. Kim, J., Campbell, A. S., de Ávila, B. E. F., & Wang, J. (2019). Wearable biosensors for healthcare monitoring. Nature Biotechnology, 37(4), 389-406.

[8]. Lansdorp, B., Ramsay, W., Hamid, R., & Strenk, E. (2019). Wearable enzymatic alcohol biosensor. Sensors, 19(10), 2380.

[9]. Lin, K. C., Kinnamon, D., Sankhala, D., Muthukumar, S., & Prasad, S. (2019). AWARE: A wearable awareness with real-time exposure, for monitoring alcohol consumption impact through ethyl glucuronide detection. Alcohol, 81, 93-99.

[10]. Rumbut, J., Fang, H., Carreiro, S., Smelson, D., & Boyer, E. (2022). An overview of wearable biosensor systems for real-time substance use detection. IEEE Internet of Things Journal, 9 (23), 23405-23415.

[11]. WHO. (2018). Global Status Report on Alcohol and Health 2018.

i-manager's Journal on Electronics Engineering (JELE)

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Volume 13 Issue 4 July - September 2023

A Procedure to Analyze Digital Circuits in CNTFET and CMOS Technology by ADS

Roberto Marani* , Anna Gina Perri**

* Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy, Milan, Italy. ** Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy.

Marani, R., and Perri, A. G. (2023). A Procedure to Analyze Digital Circuits in CNTFET and CMOS Technology by ADS. i-manager’s Journal on Electronics Engineering, 13(4), 1-9. https://doi.org/10.26634/jele.13.4.20048

Abstract

References

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Design of Virtual Electrical Laboratories for Performing Steady State and Transient Response of R-L, R-C and R-L-C Circuit

Souptik Das* , Tirthankar Chakraborty**, Abantika Choudhary***, Sayan Paramanik****, Krishna Sarker*****, Koustuv Sarkar******

*-***,*****-****** Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India. **** Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

Abstract

References

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Speech Enhancement for Noisy Signals using Adaptive Algorithms

Anna Rahul Kasukurthy* , Uma Sankar Chintala D.**

* Department of Electronics and Communication Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India. ** Department of Electrical and Electronics Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

Kasukurthy, A. R., and Chintala, D. U. S. (2023). Speech Enhancement for Noisy Signals using Adaptive Algorithms. i-manager’s Journal on Electronics Engineering, 13(4), 26-35. https://doi.org/10.26634/jele.13.4.20099

Abstract

References

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An Approach to Harmonic Optimization for 25KVA Auxiliary Converter used in Indian Railway

Shawanti Roy* , Sayan Paramanik**, Krishna Sarker***

*,*** Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India. ** Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

Roy, S., Paramanik, S., and Sarker, K. (2023). An Approach to Harmonic Optimization for 25KVA Auxiliary Converter used in Indian Railway. i-manager’s Journal on Electronics Engineering, 13(4), 36-47. https://doi.org/10.26634/jele.13.4.20155

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A Novel Wearable Biosensor for Real-Time Alcohol Detection

Ushaa Eswaran* , Vishal Eswaran**, Keerthna Murali***, Vivek Eswaran****

Eswaran, U., Eswaran, V., Murali, K., and Eswaran, V. (2023). A Novel Wearable Biosensor for Real-Time Alcohol Detection. i-manager’s Journal on Electronics Engineering, 13(4), 48-55. https://doi.org/10.26634/jele.13.4.20192

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* Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy, Milan, Italy.

** Department of Electrical and Information Engineering, Polytechnic University of Bari, Italy.

Souptik Das* , Tirthankar Chakraborty, Abantika Choudhary*, Sayan Paramanik**, Krishna Sarker*, Koustuv Sarkar****

-,*- Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India.

Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

* Department of Electronics and Communication Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

** Department of Electrical and Electronics Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

Shawanti Roy* , Sayan Paramanik, Krishna Sarker*

, Department of Electrical Engineering, St. Thomas' College of Engineering & Technology, West Bengal, India.

Department of Servicing, Statcon Electronics India Ltd, Uttar Pradesh, India.

Ushaa Eswaran* , Vishal Eswaran, Keerthna Murali*, Vivek Eswaran****