i-manager Publications

Volume 14 Issue 3 April - June 2024

Article

A Comparative Exploration of Sensors and Biosensors in Analytical Detection

Atheena Milagi Pandian S.* , Rashika Murugan, Sri Manoj Kumar N.*, Aparna N.****

*-**** Atheenapandian Private Limited, Coimbatore, India.

Pandian, S. A. M., Murugan, R., Kumar, N. S. M., and Aparna, N. (2024). A Comparative Exploration of Sensors and Biosensors in Analytical Detection. i-manager’s Journal on Electronics Engineering, 14(3), 1-5. https://doi.org/10.26634/jele.14.3.20562

Abstract

This paper provides a thorough comparison of sophisticated biosensors and conventional sensors, explaining the underlying technologies, working theories, and performance measures of each in analytical detection applications. Through analyzing the essential distinctions and parallels between them, this paper brings to light the unique benefits and constraints of every technology with respect to sensitivity, specificity, reaction speed, and mobility. This paper also examines the various uses of sensors and biosensors in healthcare, environmental monitoring, and industrial processes, offering insights into the special qualities and possible collaborations of these platforms. Looking ahead, this paper explores new developments in data analytics, microfluidics, and nanotechnology that will lead to next-generation sensing technologies with improved analytical capabilities and wider practical uses.

References

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[10]. Wang, J. (2006). Electrochemical biosensors: Towards point-of-care cancer diagnostics. Biosensors and Bioelectronics, 21(10), 1887-1892.

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Research Paper

A Novel 1T-1D Single Ended SRAM Cell using FinFET Technology for Low Power Applications

T. Venkata Lakshmi* , Kamaraju M.**

*-** Department of Electronics and Communication Engineering, Gudlavalleru Engineering College, Gudlavalleru, Andhra Pradesh, India.

Lakshmi, T. V., and Kamaraju, M. (2024). A Novel 1T-1D Single Ended SRAM Cell using FinFET Technology for Low Power Applications. i-manager’s Journal on Electronics Engineering, 14(3), 6-18. https://doi.org/10.26634/jele.14.3.20286

Abstract

The increasing demand for high-density Very Large-Scale Integrated (VLSI) circuits, driven by the scaling of CMOS technology, is primarily challenged by the need for uniformity in SRAM cells. Given that most programs frequently seek dependable data, the primary cache and memory caching (MC) component in SRAM tends to be relatively steady. Resolving power and delay imbalances is the main problem with SRAM cells. The issues with CMOS-based SRAM cells include high cost, wide parameter variation, and worse dependability. CMOS devices also experience a loss of channel control by the gate. It is therefore advised to use FinFET-based SRAM cells rather than CMOS. This paper presents a design study of a 1T-1D SRAM cell using FinFET and CMOS technology. Without changing the logic state of the SRAM cell, the objective of this paper is to lessen power leakage. The cell structure's ease of design also contributes to its remarkable affordability and accessibility. A 1T-1D cell with the bare minimum of transistors has a smaller overall area. The suggested 1T-1D SRAM cell is implemented using the Tanner EDA working platform, which uses 7nm FinFET technology. With this study, low power was reached up to 99%, and delay reduction was improved to 98%.

References

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[2]. Ahmad, S., Gupta, M. K., Alam, N., & Hasan, M. (2016). Single-ended Schmitt-trigger-based robust low-power SRAM cell. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 24(8), 2634-2642.

[3]. Ashenafi, E., & Chowdhury, M. H. (2016). A new power gating circuit design approach using double-gate fdsoi. IEEE Transactions on Circuits and Systems II: Express Briefs, 65(8), 1074-1078.

[4]. Chaudhuri, D., Roy, K., & Nag, A. (2019). Comparison of different SRAM cell topologies using 180 nm technology. In Advances in Computer, Communication and Control: Proceedings of ETES 2018 (pp. 391-400). Springer Singapore.

[5]. Deepak, N., & Kumar, R. B. (2020). Certain investigations in achieving low power dissipation for SRAM cell. Microprocessors and Microsystems, 77, 103166.

[6]. Ensan, S. S., Moaiyeri, M. H., Moghaddam, M., & Hessabi, S. (2019). A low-power single-ended SRAM in FinFET technology. AEU-International Journal of Electronics and Communications, 99, 361-368.

[7]. Guler, A., & Jha, N. K. (2019). Three-dimensional monolithic FinFET-based 8T SRAM cell design for enhanced read time and low leakage. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 27(4), 899-912.

[8]. Ibe, E., Taniguchi, H., Yahagi, Y., Shimbo, K. I., & Toba, T. (2010). Impact of scaling on neutron-induced soft error in SRAMs from a 250 nm to a 22 nm design rule. IEEE Transactions on Electron Devices, 57(7), 1527-1538.

[9]. Joji, J. E., & John, A. (2018). FinFET based ultra low power SRAM. International Journal of Engineering Research & Technology (IJERT), 7(4), 226-229.

[10]. Kumar, H., & Tomar, V. K. (2021). A Low Leakage 9T SRAM Cell with Improve Stability in Sub-Threshold Region for Iot Applications. Research Square (pp. 1-26).

[11]. Kumar, T. S., & Tripathi, S. L. (2020, September). Design of low power 7T SRAM cell for portable biomedical applications. In 2020 International Conference on Smart Electronics and Communication (ICOSEC) (pp. 1175-1178). IEEE.

[12]. Lundager, K., Zeinali, B., Tohidi, M., Madsen, J., & Moradi, F. (2016). Low power design for future wearable and implantable devices. Journal of Low Power Electronics and Applications, 6(4), 20.

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[14]. Moghaddam, M., Timarchi, S., Moaiyeri, M. H., & Eshghi, M. (2016). An ultra-low-power 9T SRAM cell based on threshold voltage techniques. Circuits, Systems, and Signal Processing, 35(5), 1437-1455.

[15]. Moghaddam, M., Timarchi, S., Moaiyeri, M. H., & Eshghi, M. (2016). An ultra-low-power 9T SRAM cell based on threshold voltage techniques. Circuits, Systems, and Signal Processing, 35, 1437-1455.

[16]. Mohammed, M. U., Nizam, A., & Chowdhury, M. H. (2018a, November). Performance and reliability of asymmetrical underlapped FinFET based 6T and 8T SRAMs in sub-10nm domain. In 2018 IEEE Nanotechnology Symposium (ANTS) (pp. 1-4). IEEE.

[17]. Mohammed, M. U., Nizam, A., & Chowdhury, M. H. (2018b, October). Performance stability analysis of SRAM cells based on different FinFET devices in 7nm technology. In 2018 IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S) (pp. 1-3). IEEE.

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[20]. Song, T., Rim, W., Park, S., Kim, Y., Yang, G., Kim, H., ... & Choi, J. (2016). A 10 nm FinFET 128 Mb SRAM with assist adjustment system for power, performance, and area optimization. IEEE Journal of Solid-State Circuits, 52(1), 240-249.

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[22]. Tripathi, T., Chauhan, D. S., Singh, S. K., & Singh, S. V. (2017). Implementation of low-power 6T SRAM cell using MTCMOS technique. In Advances in Computer and Computational Sciences: Proceedings of ICCCCS 2016, 1, 475-482. Springer Singapore.

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[29]. Zhang, B., Arapostathis, A., Nassif, S., & Orshansky, M. (2006, November). Analytical modeling of SRAM dynamic stability. In Proceedings of the 2006 IEEE/ACM International Conference on Computer-Aided Design (pp. 315-322).

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Research Paper

A Method of Image Fusion using Texture Guidance Based Guided Image Filter and Image Statistics

Suneel Kumar A.* , Srikanth M. V., Nagasirisha B.*, Venkata Lakshmi T.****

- Usha Rama College of Engineering and Technology, Andhra Pradesh, India.

-**** Gudlavalleru Engineering College, Andhra Pradesh, India.

Kumar, A. S., Srikanth, M. V., Nagasirisha, B., and Lakshmi, T. V. (2024). A Method of Image Fusion using Texture Guidance Based Guided Image Filter and Image Statistics. i-manager’s Journal on Electronics Engineering, 14(3), 19-30. https://doi.org/10.26634/jele.14.3.20647

Abstract

A technique of image fusion by means of a guided image filter is proposed in this paper. It employs image smoothing with a guided filter by making use of texture information as guidance for the guided filter. Then, image statistics-based pixel weight computation is utilized for generating the weight maps of the source images from detail layer features. Finally, the source images are integrated based on the weighted average combining strategy. The efficacy of the proposed algorithm is tested and compared with several state-of-the-art image fusion methods in terms of several objective image quality assessment parameters. The experimental result suggests the efficacy of the proposed algorithm in image fusion.

References

[1]. Bavirisetti, D. P., Kollu, V., Gang, X., & Dhuli, R. (2017). Fusion of MRI and CT images using guided image filter and image statistics. International Journal of Imaging Systems and Technology, 27(3), 227-237.

[2]. Bhatnagar, G., Wu, Q. J., & Liu, Z. (2013). Directive contrast based multimodal medical image fusion in NSCT domain. IEEE Transactions on Multimedia, 15(5), 1014-1024.

[3]. Civicioglu, P., & Besdok, E. (2022). Contrast stretching based pansharpening by using weighted differential evolution algorithm. Expert Systems with Applications, 208, 118144.

[4]. De, I., Chanda, B., & Chattopadhyay, B. (2006). Enhancing effective depth-of-field by image fusion using mathematical morphology. Image and Vision Computing, 24(12), 1278-1287.

[5]. He, K., Sun, J., & Tang, X. (2012). Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1397-1409.

[6]. Jiang, Y., & Wang, M. (2014). Image fusion using multiscale edge preserving decomposition based on weighted least squares filter. IET Image Processing, 8(3), 183-190.

[7]. Kumar, B. K. S. (2015). Image fusion based on pixel significance using cross bilateral filter. Signal, Image and Video Processing, 9, 1193-1204.

[8]. Li, S., Kang, X., & Hu, J. (2013). Image fusion with guided filtering. IEEE Transactions on Image Processing, 22(7), 2864-2875.

[9]. Li, S., Kang, X., Fang, L., Hu, J., & Yin, H. (2017). Pixel-level image fusion: A survey of the state of the art. Information Fusion, 33, 100-112.

[10]. Ma, J., Ma, Y., & Li, C. (2019). Infrared and visible image fusion methods and applications: A survey. Information Fusion, 45, 153-178.

[11]. Meher, B., Agrawal, S., Panda, R., & Abraham, A. (2019). A survey on region based image fusion methods. Information Fusion, 48, 119-132.

[12]. Rahman, S. M., Ahmad, M. O., & Swamy, M. N. S. (2010). Contrast-based fusion of noisy images using discrete wavelet transform. IET Image Processing, 4(5), 374-384.

[13]. Ramac, L. C., Uner, M. K., Varshney, P. K., Alford, M. G., & Ferris Jr, D. D. (1998, March). Morphological filters and wavelet-based image fusion for concealed weapons detection. In Sensor Fusion: Architectures, Algorithms, and Applications II, 3376, 110-119. SPIE.

[14]. Rockinger, O. (1997, October). Image sequence fusion using a shift-invariant wavelet transform. In Proceedings of International Conference on Image Processing, 3, 288-291. IEEE.

[15]. Srikanth, M. V., Prasad, V. V. K. D. V., & Prasad, K. S. (2023a). Brain tumor detection through modified optimization algorithm by region-based image fusion. ECTI Transactions on Computer and Information Technology (ECTI-CIT), 17(1), 117-127.

[16]. Srikanth, M. V., Prasad, V. V. K. D. V., & Prasad, K. S. (2023b). Application of novel improved firefly algorithm for image fusion to detect brain tumor. ECTI Transactions on Computer and Information Technology (ECTI-CIT), 17(2), 292-307.

[17]. Tang, L., Yuan, J., & Ma, J. (2022). Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network. Information Fusion, 82, 28-42.

[18]. Yang, B., & Li, S. (2007). Multi-focus image fusion based on spatial frequency and morphological operators. Chinese Optics Letters, 5(8), 452-453.

[19]. Zhang, H., Xu, H., Tian, X., Jiang, J., & Ma, J. (2021). Image fusion meets deep learning: A survey and perspective. Information Fusion, 76, 323-336.

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Research Paper

Performance and Analysis of Different Adder Topologies

Rashmi B. K.* , Rohith J., Shreya Suresh Mudaladavar, Supreet Hosageri, Mahantesh P. Mattada

*-***** Department of Electronics and Communication Engineering, PES Institute of Technology and Management, Shivamogga, India.

Rashmi, B. K., Rohith, J., Mudaladavar, S. S., Hosageri, S., and Mattada, M. P. (2024). Performance and Analysis of Different Adder Topologies. i-manager’s Journal on Electronics Engineering, 14(3), 31-37. https://doi.org/10.26634/jele.14.3.20675

Abstract

This paper gives an overview of area, power, delay for four different 64-bit adders. The design metrics in VLSI are low area and delay alongside low power designs. Adder is one of the necessary components of almost every kind of digital and high- performance systems such as FIR filters, digital signal processors and microprocessors etc. Different types of adders are carry tree adder, carry save adder, carry look ahead adder and carry select adder. In this work we have designed, simulated and synthesized these adder topologies and compared the results in cadence tool.

References

[1]. Chang, T. Y., & Hsiao, M. J. (1998). Carry-select adder using single ripple-carry adder. Electronics Letters, 34(22), 2101-2103.

[2]. Devi, J. S., Sreedhar, M. B., Arulprakash, P., Kazi, K., & Radhakrishnan, R. (2022). A path towards child-centric Artificial Intelligence based Education. International Journal of Early Childhood, 14(3), 9915-9922.

[3]. Devi, P., Girdher, A., & Singh, B. (2010). Improved carry select adder with reduced area and low power consumption. International Journal of Computer Applications, 3(4), 14-18.

[4]. Hotkar, P. R., Kulkarni, V., Kamble, P., & Kazi, K. S. (2019). Implementation of Low Power and area efficient carry select Adder. International Journal of Research in Engineering, Science and Management, 2(4), 183-184.

[5]. Kumari, V. K., Chakrapani, Y. S., & Kamaraju, M. (2013). Design and characterization of koggestone sparse koggestone spanning tree and brentkung adders. International Journal of Scientific and Engineering Research, 4(10), 1502-1506.

[6]. Kwon, O., Swartzlander Jr, E. E., & Nowka, K. (2001, March). A fast hybrid carry-lookahead/carry-select adder design. In Proceedings of the 11th Great Lakes symposium on VLSI (pp. 149-152).

[7]. Liyakat, K. K. S. (2017). Lessar methodology for network intrusion detection. Scholarly Research Journal for Humanity Science & English Language, 4(24), 6853-6861.

[8]. Ramkumar, B., Kittur, H. M., & Kannan, P. M. (2010). ASIC implementation of modified faster carry save adder. European Journal of Scientific Research, 42(1), 53-58.

[9]. Samanta, J., Halder, M., & De, B. P. (2013). Performance analysis of high speed low power carry look-ahead adder using different logic styles. International Journal of Soft Computing and Engineering, 2(6), 330-336.

[10]. Shubin, V. V. (2010, June). Analysis and comparison of ripple carry full adders by speed. In 2010 11th International Conference and Seminar on Micro/Nanotechnologies and Electron Devices (pp. 132-135). IEEE.

[11]. Singh, R., Sharma, A., & Singh, R. (2013). Power efficient design of multiplexer based compressor using adiabatic logic. International Journal of Computer Applications, 81(10), 45-50.

[12]. Tejasvi, K., & Kishore, G. S. (2016). Low-Power and area-efficient N-Bit carry-select adder. International Advanced Research Journal in Science, Engineering and Technology, 3(7), 186-189.

[13]. Uma, R., Vijayan, V., Mohanapriya, M., & Paul, S. (2012). Area, delay and power comparison of adder topologies. International Journal of VLSI Design & Communication Systems, 3(1), 153.

[14]. Veeramachaneni, S., & Srinivas, M. B. (2008, May). New improved 1-bit full adder cells. In 2008 Canadian Conference on Electrical and Computer Engineering (pp. 000735-000738). IEEE.

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Research Paper

Android Guided Arduino Car

Samidha Saxena*

Department of Electronics Engineering, Institute of Engineering and Rural Technology, Uttar Pradesh, India.

Saxena, S. (2024). Android Guided Arduino Car. i-manager’s Journal on Electronics Engineering, 14(3), 38-43. https://doi.org/10.26634/jele.14.3.20815

Abstract

This paper aims to design an Android interface, an Arduino bot, and write a program on the Arduino microprocessor. Arduino cars contain Arduino microcontrollers with basic mobility features. Arduino programs contain instructions for mediating between an Android controller and an Arduino car. Android mobile controllers use different mobile sensors to supervise motion. An appropriate program in the Arduino microprocessor to interact with the Android controller has to be created. The program has been successfully compiled through the Arduino IDE on the Arduino microprocessor and loaded into it after proper checking of the logic to decrease any loss or damage to the hardware. An Android application is created that provides the user with an interface to interact with the Arduino-powered car. The interface is easy to use and provides feedback from the Arduino microprocessor through Bluetooth after giving instructions to the Arduino for various actions through the interface. The Android application is to be created with the help of Android Studio, which provides more capability and stability. After doing all of this, the application is thoroughly tested, and the maximum number of errors and wrong logic in the microprocessor program are found.

References

[1]. Aggarwal, K. K., & Singh, Y. (2013). Software Engineering. New Age International.

[2]. Arduino. (n.d.).

[3]. Burnette, E. (2010). Hello, Android Introducing Google's Mobile Development Platform. Pragamatic Publications.

[4]. Developers. (n.d.). Building with AI on Android.

[5]. DiMarzio, J. F. (2010). Android - A Programmer's Guide. Tata McGraw - Hill Education.

[6]. Fischer, G. (2002, November). The software technology of the 21st century: From software reuse to collaborative software design. In Proceedings of ISFST'2001: International Symposium on Future Software Technology (pp. 1-8).

[7]. Meier, R. (2012). Professional Android 4 Application Development. John Wiley & Sons.

[8]. Pressman, R. S. (2005). Software Engineering: A Practitioner's Approach. Palgrave Macmillan.

[9]. SCRUMstudy. (n.d.).

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Volume 14 Issue 3 April - June 2024

A Comparative Exploration of Sensors and Biosensors in Analytical Detection

Atheena Milagi Pandian S.* , Rashika Murugan**, Sri Manoj Kumar N.***, Aparna N.****

*-**** Atheenapandian Private Limited, Coimbatore, India.

Pandian, S. A. M., Murugan, R., Kumar, N. S. M., and Aparna, N. (2024). A Comparative Exploration of Sensors and Biosensors in Analytical Detection. i-manager’s Journal on Electronics Engineering, 14(3), 1-5. https://doi.org/10.26634/jele.14.3.20562

Abstract

References

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A Novel 1T-1D Single Ended SRAM Cell using FinFET Technology for Low Power Applications

T. Venkata Lakshmi* , Kamaraju M.**

*-** Department of Electronics and Communication Engineering, Gudlavalleru Engineering College, Gudlavalleru, Andhra Pradesh, India.

Lakshmi, T. V., and Kamaraju, M. (2024). A Novel 1T-1D Single Ended SRAM Cell using FinFET Technology for Low Power Applications. i-manager’s Journal on Electronics Engineering, 14(3), 6-18. https://doi.org/10.26634/jele.14.3.20286

Abstract

References

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A Method of Image Fusion using Texture Guidance Based Guided Image Filter and Image Statistics

Suneel Kumar A.* , Srikanth M. V.**, Nagasirisha B.***, Venkata Lakshmi T.****

*-** Usha Rama College of Engineering and Technology, Andhra Pradesh, India. ***-**** Gudlavalleru Engineering College, Andhra Pradesh, India.

Kumar, A. S., Srikanth, M. V., Nagasirisha, B., and Lakshmi, T. V. (2024). A Method of Image Fusion using Texture Guidance Based Guided Image Filter and Image Statistics. i-manager’s Journal on Electronics Engineering, 14(3), 19-30. https://doi.org/10.26634/jele.14.3.20647

Abstract

References

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Performance and Analysis of Different Adder Topologies

Rashmi B. K.* , Rohith J.**, Shreya Suresh Mudaladavar***, Supreet Hosageri****, Mahantesh P. Mattada*****

*-***** Department of Electronics and Communication Engineering, PES Institute of Technology and Management, Shivamogga, India.

Rashmi, B. K., Rohith, J., Mudaladavar, S. S., Hosageri, S., and Mattada, M. P. (2024). Performance and Analysis of Different Adder Topologies. i-manager’s Journal on Electronics Engineering, 14(3), 31-37. https://doi.org/10.26634/jele.14.3.20675

Abstract

References

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Android Guided Arduino Car

Samidha Saxena*

Department of Electronics Engineering, Institute of Engineering and Rural Technology, Uttar Pradesh, India.

Saxena, S. (2024). Android Guided Arduino Car. i-manager’s Journal on Electronics Engineering, 14(3), 38-43. https://doi.org/10.26634/jele.14.3.20815

Abstract

References

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Atheena Milagi Pandian S.* , Rashika Murugan, Sri Manoj Kumar N.*, Aparna N.****

Suneel Kumar A.* , Srikanth M. V., Nagasirisha B.*, Venkata Lakshmi T.****

- Usha Rama College of Engineering and Technology, Andhra Pradesh, India.

-**** Gudlavalleru Engineering College, Andhra Pradesh, India.

Rashmi B. K.* , Rohith J., Shreya Suresh Mudaladavar, Supreet Hosageri, Mahantesh P. Mattada