i-manager Publications

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

Current Issue Vol. 15 Issue 1

Most Cited

Volume 12 Issue 1 September - November 2021

Research Paper

Low Redundancy Matrix Code with Efficient PPA

Bujjibabu Penumutchi* , Sarvani Voruganti**

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

Penumutchi, B., and Voruganti, S. (2021). Low Redundancy Matrix Code with Efficient PPA. i-manager's Journal on Electronics Engineering, 12(1), 1-9. https://doi.org/10.26634/jele.12.1.15085

Abstract

Memory is one of the key elements in any of the electronic systems. But, Multiple Cell Upsets (MCU's) are becoming serious reliability problems to the memories when they are operated in radiation environment. So to protect memories, complex Error Correcting Codes (ECC) are proposed to overcome data corruption but the issue with them is that they need higher delay overheads., Decimal Matrix Code (DMC) has been proposed for the protection of memories which uses a decimal algorithm to enhance memory reliability. In DMC, the area of the circuit is minimized by using Encoder Reuse Technique (ERT) (i.e. encoder is reused in the decoder). But it requires a higher number of redundancy bits. So, to reduce redundancy bits and to improve error correcting capability, another technique called Parity Matrix Code (PMC) is used with the same algorithm as that of DMC with reduced redundancy bits and performance overheads. The drawback of existing DMC algorithm is that it requires more number of redundancy bits. This drawback was rectified in the modified PMC technique thus reducing the number of redundancy bits used for detecting and correcting the data. Thus modified PMC technique is more advantageous than an existing DMC technique because it has less number of redundancy bits with maximum error correction capability and Efficient Power, Performance and Area (PPA).

References

[1]. Aishwarya, S., & Mahendran, G. (2016, May). Multiple bit upset correction in SRAM based FPGA using Mutation and Erasure codes. In 2016, International Conference on Advanced Communication Control and Computing Technologies (ICACCCT) (pp. 202-206). IEEE. https://doi. org/10.1109/ICACCCT.2016.7831630

[2]. Baeg, S., Wen, S., & Wong, R. (2009). Minimizing soft errors in TCAM devices: A probabilistic approach to determining scrubbing intervals. IEEE Transactions on Circuits and Systems I: Regular Papers, 57(4), 814-822. https://doi.org/10.1109/TCSI.2009.2025856

[3]. David, S., & Gayathree, K. (2014). A Comparative Study of Various Error Correction Codes. International Journal of Computer Science and Mobile Computing (IJCSMC), 3(8), 196-200.

[4]. Guo, J., Xiao, L., Mao, Z., & Zhao, Q. (2013). Enhanced memory reliability against multiple cell upsets using decimal matrix code. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 22(1), 127-135. https://doi.org/ 10.1109/TVLSI.2013.2238565

[5]. Hsiao, M. Y. (1970). A class of optimal minimum oddweight- column SEC-DED codes. IBM Journal of Research and Development, 14(4), 395-401. https://doi.org/10.1147/ rd.144.0395

[6]. Kamalakannan, S., Karthikeyan, S., & Sathyamoorthy, K. (2015). Implementation of error correction technique based on decimal matrix code. International Journal of Advanced Research Trends in Engineering and Technology (IJARTET), 2(4), 1-6.

[7]. Madhuri, K., & Thrimurthulu, V. (2014). Implementation of Decimal Matrix Code for correcting Cell Upsets in Static Random Access Memories. International Journal of Electrical, Electronics and Data Communication (IJEEDC), 2(10), 72-76.

[8]. Pagiamtzis, K., & Sheikholeslami, A. (2006). Contentaddressable memory (CAM) circuits and architectures: A tutorial and survey. IEEE Journal of Solid-State Circuits, 41(3), 712-727. https://doi.org/10.1109/JSSC.2005.864128

[9]. Sanchez-Macian, A., Reviriego, P., & Maestro, J. A. (2012). Hamming SEC-DAED and extended hamming SECDED- TAED codes through selective shortening and bit placement. IEEE Transactions on Device and Materials Reliability, 14(1), 574-576. https://doi.org/10.1109/TDMR. 2012.2204753

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Research Paper

Design of Frequency Efficient CMOS Difference Amplifier Circuit for Sigma Delta ADC for Aerospace Applications

Suneetha Telidevulapalli* , Srinivasa Rao Talla**

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

Telidevulapalli, S., and Talla, S. R. (2021). Design of Frequency Efficient CMOS Difference Amplifier Circuit for Sigma Delta ADC for Aerospace Applications. i-manager's Journal on Electronics Engineering, 12(1), 10-15. https://doi.org/10.26634/jele.12.1.15084

Abstract

Nowadays, Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) has found its usage in each and every field. Researchers are always trying to redesign the circuit by using Complementary Metal-oxide Semiconductor (CMOS) technology which gives the efficient circuit of MOSFET. To design sensor for aerospace application, that it uses sigma delta Analog to Digital Converter (ADC). To design difference amplifier, high gain operational amplifier plays a key role. The proposed work modifies the differential amplifier design using R-2R technique and also uses reduced operational amplifier. Thus it outcomes the consumption of energy and frequency reduced due to optimized op-amp design.

References

[1]. Abo, A. M., & Gray, P. R. (1999). A 1.5-V, 10-bit, 14.3-MS/s CMOS pipeline analog-to-digital converter. IEEE Journal of Solid-State Circuits, 34(5), 599-606. https://doi.org/10.110 9/4.760369

[2]. Koh, H. Y., Sequin, C. H., & Gray, P. R. (1990). OPASYN: A compiler for CMOS operational amplifiers. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 9(2), 113-125. https://doi.org/10.1109/43.46777

[3]. Li, Y., Zeng, T., & Chen, D. (2013, May). A high resolution and high accuracy R-2R DAC based on ordered element matching. In 2013, IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1974-1977). IEEE. https:// doi.org/10.1109/ISCAS.2013.6572256

[4]. Razavi, B. (1997). Design considerations for directconversion receivers. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 44(6), 428- 435. https://doi.org/10.1109/82.592569

[5]. Yu, J., & Mao, Z. (2009). A design method in CMOS operational amplifier optimization based on adaptive genetic algorithm. WSEAS Transactions on Circuits and Systems, 8(7), 548-558.

[6]. Zeng, T., & Chen, D. (2013). An order-statistics based matching strategy for circuit components in data converters. IEEE Transactions on Circuits and Systems I: Regular Papers, 60(1), 11-24. https://doi.org/10.1109/TCSI.2012.2232991

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Research Paper

Fast Integrating of Kinect V2 Data for Recognition of Hand Gesture

S. Chandra Sekhar* , Nitiket N Mhala**

*-** Department of Electronics Engineering, Bapurao Deshmukh College of Engineering Seagram Wardha, Maharashtra, India.

Sekhar, S. C., and Mhala, N. N. (2021). Fast Integrating of Kinect V2 Data for Recognition of Hand Gesture. i-manager's Journal on Electronics Engineering, 12(1), 16-22. https://doi.org/10.26634/jele.12.1.15413

Abstract

Hand gesture recognition is critical to human-computer interaction. This paper proposes a revolutionary permanent method for hand gestures and presents a framework for detecting rapid gestures using information combination techniques and a direct indicator of hand development. The foundation subtraction approach in this system removes the arm area from the foundation. This structure is currently adopted by the procedures for implementing the Kinect V2 application. The required time is confirmed quickly compared to other ongoing minutes. The time analysis is compared and using the data pooling approach, the average time is 63ms. The average time is 45 milliseconds when using Rapid Data Integration. The time it takes to recognize hand movement has been reduced. MATLAB is used to analyze the results of experiments.

References

[1]. Celebi, S., Aydin, A. S., Temiz, T. T., & Arici, T. (2013, February). Gesture recognition using skeleton data with weighted dynamic time warping. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) (pp. 620-625). https://doi.org/10.522 0/0004217606 200625

[2]. El-Baz, A. H., & Tolba, A. S. (2013). An efficient algorithm for 3D hand gesture recognition using combined neural classifiers. Neural Computing and Applications, 22(7), 1477-1484. https://doi.org/10.1007/s00521-012-0844-2

[3]. Jacob, M. G., & Wachs, J. P. (2014). Context-based hand gesture recognition for the operating room. Pattern Recognition Letters, 36, 196-203. https://doi.org/10.1016/j.patrec.2013.05.024

[4]. Lan, Y., Li, J., & Ju, Z. (2016, July). Data fusion-based real-time hand gesture recognition with Kinect V2. In 2016, 9^th International Conference on Human System Interactions (HSI) (pp. 307-310). IEEE. https://doi.org/10.1109/HSI.2016.7529649

[5]. Livingston, M. A., Sebastian, J., Ai, Z., & Decker, J. W. (2012, March). Performance measurements for the Microsoft Kinect skeleton. In 2012, IEEE Virtual Reality Workshops (VRW) (pp. 119-120). IEEE. https://doi.org/10.1109/VR.2012.6180911

[6]. Mahbub, U., Imtiaz, H., Roy, T., Rahman, M. S., & Ahad, M. A. R. (2013). A template matching approach of oneshot- learning gesture recognition. Pattern Recognition Letters, 34(15), 1780-1788. https://doi.org/10.1016/j.patrec.2012.09.014

[7]. Ohn-Bar, E., & Trivedi, M. M. (2014). Hand gesture recognition in real time for automotive interfaces: A multimodal vision-based approach and evaluations. IEEE Transactions on Intelligent Transportation Systems, 15(6), 2368-2377. https://doi.org/10.1109/TITS.2014.2337331

[8]. Pisharady, P. K., & Saerbeck, M. (2015). Recent methods and databases in vision-based hand gesture recognition: A review. Computer Vision and Image Understanding, 141, 152-165. https://doi.org/10.1016/j.cviu.2015.08.004

[9]. Ren, Z., Yuan, J., Meng, J., & Zhang, Z. (2013). Robust part-based hand gesture recognition using kinect sensor. IEEE Transactions on Multimedia, 15(5), 1110-1120. https://doi.org/10.1109/TMM.2013.2246148

[10]. Trail, S., Dean, M., Odowichuk, G., Tavares, T. F., Driessen, P. F., Schloss, W. A., & Tzanetakis, G. (2012, May). Non-invasive sensing and gesture control for pitched percussion hyper-instruments using the Kinect. In New Interfaces for Musical Expression (NIME).

[11]. Yoon, H. S., Soh, J., Bae, Y. J., & Yang, H. S. (2001). Hand gesture recognition using combined features of location, angle and velocity. Pattern Recognition, 34(7), 1491-1501. https://doi.org/10.1016/S0031-3203(00)00096-0

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Research Paper

The use of Arduino UNO Microcontroller Sensor to Control Light Bulb

Alcayaga P.* , Condez J., Dalluay N., De Guzman C., Mesina C.

*-***** De La Salle University-Dasmarinas, Philippines.

Alcayaga, P., Condez, J., Dalluay, N., Guzman, C. D., and Mesina, C. (2021). The use of Arduino UNO Microcontroller Sensor to Control Light Bulb. i-manager's Journal on Electronics Engineering, 12(1), 23-28. https://doi.org/10.26634/jele.12.1.16004

Abstract

Electricity is widely consumed in the everyday life of an individual, especially when used for light bulbs. Excessive consumption of electricity greatly affects the ecosystem. Nonetheless, Arduino Uno is used by the researchers as a microcontroller to control a light bulb with the use of a Passive Infrared (PIR) motion sensor in order to enable a user to program their specified schedule for when it will only turn on. The researchers use a Descriptive - Evaluative Design in order to measure the accuracy and efficiency of this device. The device acquired good results and functioned as of how the researchers programmed it to be. Based on the study conducted, the Arduino Uno device made by the researchers consumed fewer kilowatts per hour, calculated in a span of five days.

References

[1]. Castaneda, C. J. S. (2018). Electricity Consumption across Regions up By Nearly 4% in 2017. Retrieved from https://www.bworldonline.com/infographics/2018/07/07/1 71081/electricity-consumption-up-by-nearly-4-in-2017/

[2]. Eriksson, L. (2018). Effects of policy measures and moderating factors on climate change adaptation among private forest owners in Sweden. Society & Natural Resources, 31(4), 409-423. https://doi.org/10.1080/08941920.2017.1382629

[3]. Martirano, L. (2011, May). Lighting systems to save energy in educational classrooms. In 2011, 10^th International Conference on Environment and Electrical Engineering (pp. 1-5). IEEE. https://doi.org/10.1109/EEEIC.2011.5874691

[4]. Maslekar, A., Aparna, K., Mamatha, K., & Shivakumara, T. (2015). Smart lighting system using raspberry PI. International Journal of Innovative Research in Science and Technology, 4(7), 5113-5121.

[5]. Patel, K. K., & Patel, S. M. (2016). Internet of things-IOT: definition, characteristics, architecture, enabling technologies, application & future challenges. International Journal of Engineering Science and Computing, 6(5), 6122-6131. https://doi.org/10.4010/2016.1482

[6]. Shuttleworth, M. (2008). Descriptive Research Design. Retrieved from https://explorable.com/descriptiveresearch-design

[7]. Suresh, S., Anusha, H. N. S., Rajath, T., Soundarya, P., & Vudatha, S. P. (2016, November). Automatic lighting and control system for classroom. In 2016, International Conference on ICT in Business Industry & Government (ICTBIG) (pp. 1-6). IEEE.

[8]. Trochim, W. M. K. (2007). Research Methods Knowledge Base. Retrieved from https://conjointly.com/kb/

[9]. Urrutia, J., Meneses, J., & Antonio, G. (2019). Predicting future monthly electricity consumption in the philippines using markov-chain grey model. Indian Journal of Science and Technology, 12(33), 1-44. https://doi.org/10.17485/ijst/2019/v12i33/145762

[10]. Williams, A., Atkinson, B., Garbesi, K., Page, E., & Rubinstein, F. (2012). Lighting controls in commercial buildings. Leukos, 8(3), 161-180. https://doi.org/10.1582/leukos.2012.08.03.001

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Research Paper

Numerical Simulation of Set using TCAD

Tarun Singhal* , Vijay K. Lamba, Javed Ashraf*

* Department of Electronics & Communication Engineering, AFSET-Al Falah School of Engineering and Technology, Faridabad, Haryana, India.

Department of Electronics & Communication Engineering, Global College of Engineering and Technology, Kahanpur, Punjab, India.

* Department of Electronics & Communication Engineering, Al-Falah University, Faridabad, Haryana, India.

Singhal, T., Lamba, V. K., and Ashraf, J. (2021). Numerical Simulation of Set using TCAD. i-manager's Journal on Electronics Engineering, 12(1), 29-34. https://doi.org/10.26634/jele.12.1.15128

Abstract

The ability to control the electron flow of a Metal-Oxide-Semiconductor Field-Effect Transistor MOSFET decreases due to a quantum mechanical effect as the size decreases below 50 nm. To meet this challenge, a new area of device research is needed. One such area is devices based on tunneling phenomena, called single-electron devices. In this paper, the most fundamental single-electron device, the Single Electron Transistor (SET), is designed using visual Technical Computer Aided Design (TCAD) with a gate length of 2 nm and a gate width of 2 nm. The channel is ultra-thin with a length of 2 nm and a width of 0.005 nm, and the thickness of the channel is 0.3 nm. Then, a Si quantum dot with a size of 0.5 * 1.6 nm² is used between the island and the gate. Both devices are successfully simulated using Genius Simulator. It has been established that a device with a silicon dot is more promising at room temperature. A device with a silicon dot has a lower capacity and higher charging energy than a device without a quantum dot.

References

[1]. Fulton, T. A., & Dolan, G. J. (1987). Observation of singleelectron charging effects in small tunnel junctions. Physical review letters, 59(1), 109-112. https://doi.org/10.1103/Phys RevLett.59.109

[2]. Hashim, U., & Rasmi, A. (2006). Single-electron transistor (SET) process and device simulation using SYSNOPSYS TCAD tools. American Journal of Applied Sciences, 3(7), 1933- 1938.

[3]. Kanjanachuchai, S., & Panyakeow, S. (2002, December). Beyond CMOS: single-electron transistors. In 2002, IEEE International Conference on Industrial Technology, 2002. IEEE ICIT'02. (Vol. 2, pp. 1219-1222). IEEE. https://doi.org/10.1109/ICIT.2002.1189348

[4]. Kastner, M. A. (1992). The single-electron transistor. Reviews of Modern Physics, 64(3), 849-858.

[5]. Kastner, M. A. (2000). The single electron transistor and artificial atoms. Annalen Der Physik, 9(11‐12), 885-894. https://doi.org/10.1002/1521-3889(200011)9:11/12<885: :AID-ANDP885>3.0.CO;2-8

[6]. Sheela, L., Balamurugan, N. B.,& Ananth, J, T. (2014). TCAD simulation of single-electron transistor with recessed channel. International Journal of Applied Engineering Research, 9(24), 23781-23788.

[7]. Talbo, V., Galdin-Retailleau, S., Valentin, A., & Dollfus, P. (2011). Physical simulation of silicon-nanocrystal-based single-electron transistors. IEEE transactions on electron devices, 58(10), 3286-3293. https://doi.org/10.1109/TED. 2011.2161611

[8]. Tilke, A. T., Simmel, F. C., Blick, R. H., Lorenz, H., & Kotthaus, J. P. (2001). Coulomb blockade in silicon nanostructures. Progress in Quantum Electronics, 25(3), 97- 138. https://doi.org/10.1016/S0079-6727(01)00005-2

[9]. Touati, A., Chatbouri, S., Sghaier, N., & Kalboussi, A. (2012). New model for drain and gate current of singleelectron transistor at high temperature. World Journal of Nano Science and Engineering, 2(4), 171-175. https://doi. org/10.4236/wjnse.2012.24022

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

Current Issue Vol. 15 Issue 1

Most Read

Most Cited

Volume 12 Issue 1 September - November 2021

Low Redundancy Matrix Code with Efficient PPA

Bujjibabu Penumutchi* , Sarvani Voruganti**

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

Penumutchi, B., and Voruganti, S. (2021). Low Redundancy Matrix Code with Efficient PPA. i-manager's Journal on Electronics Engineering, 12(1), 1-9. https://doi.org/10.26634/jele.12.1.15085

Abstract

References

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Design of Frequency Efficient CMOS Difference Amplifier Circuit for Sigma Delta ADC for Aerospace Applications

Suneetha Telidevulapalli* , Srinivasa Rao Talla**

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

Telidevulapalli, S., and Talla, S. R. (2021). Design of Frequency Efficient CMOS Difference Amplifier Circuit for Sigma Delta ADC for Aerospace Applications. i-manager's Journal on Electronics Engineering, 12(1), 10-15. https://doi.org/10.26634/jele.12.1.15084

Abstract

References

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Fast Integrating of Kinect V2 Data for Recognition of Hand Gesture

S. Chandra Sekhar* , Nitiket N Mhala**

*-** Department of Electronics Engineering, Bapurao Deshmukh College of Engineering Seagram Wardha, Maharashtra, India.

Sekhar, S. C., and Mhala, N. N. (2021). Fast Integrating of Kinect V2 Data for Recognition of Hand Gesture. i-manager's Journal on Electronics Engineering, 12(1), 16-22. https://doi.org/10.26634/jele.12.1.15413

Abstract

References

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The use of Arduino UNO Microcontroller Sensor to Control Light Bulb

Alcayaga P.* , Condez J.**, Dalluay N.***, De Guzman C.****, Mesina C.*****

*-***** De La Salle University-Dasmarinas, Philippines.

Alcayaga, P., Condez, J., Dalluay, N., Guzman, C. D., and Mesina, C. (2021). The use of Arduino UNO Microcontroller Sensor to Control Light Bulb. i-manager's Journal on Electronics Engineering, 12(1), 23-28. https://doi.org/10.26634/jele.12.1.16004

Abstract

References

Full Article (HTML)

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Numerical Simulation of Set using TCAD

Tarun Singhal* , Vijay K. Lamba**, Javed Ashraf***

Singhal, T., Lamba, V. K., and Ashraf, J. (2021). Numerical Simulation of Set using TCAD. i-manager's Journal on Electronics Engineering, 12(1), 29-34. https://doi.org/10.26634/jele.12.1.15128

Abstract

References

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Alcayaga P.* , Condez J., Dalluay N., De Guzman C., Mesina C.

Tarun Singhal* , Vijay K. Lamba, Javed Ashraf*