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

Current Issue Vol. 15 Issue 1

Most Cited

Volume 9 Issue 2 December - February 2019

Research Paper

A Comparison of CNTFET Models through a Simulation Study of Digital Circuits

Roberto Marani* , Anna Gina Perri**

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

**Full Professor and Head of Electronic Devices Laboratory, Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy.

Marani,R.,Perri,A.G.(2019).A Comparison of CNTFET Models through a Simulation Study of Digital Circuits.i-manager’s Journal on Electronics Engineering,9(2),1-7. https://doi.org/10.26634/jele.9.2.15180

Abstract

In this paper, the authors present a simulation study in order to carry out static and dynamic analysis of CNTFET-based digital circuits, in the semi-empirical compact model for CNTFETs, which was already proposed with, both the quantum capacitance effects and the sub-threshold currents. To verify the validity of the obtained results, they are compared with those of the Stanford-Source Virtual Carbon Nanotube Field-Effect Transistor (VS-CNFET) model. This comparison is made through some simulations of digital circuits. In particular they have considered XOR gate, but emphasizing that the proposed procedure can be applied to any logic gate based on CNTFET. As regards the static conditions, the two models behave in a manner virtually identical, while, as regards the dynamic analysis, there is a remarkable differences between two models in terms of propagation delays and rise and fall times.

References

[1]. Datta, S. (1995). Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, New York: Cambridge University Press.

[2]. Deng, J., & Wong, H-S P. (2007a). A compact SPICE model for carbon-nanotube field-effect transistors including nonidealities and its application—Part I: Model of the intrinsic channel region. IEEE Transactions on Electron Devices, 54(12), 3186-3194.

[3]. Deng, J., & Wong, H-S P. (2007b). A compact SPICE model for carbon-nanotube field-effect transistors including nonidealities and its application—Part II: Full device model and circuit performance benchmarking., IEEE Transactions on Electron Devices, 54(12), 3195-3205.

[4]. Gelao, G., Marani, R., Diana, R., & Perri, A. G. (2011). A semi-empirical SPICE model for n-type conventional CNTFETS. IEEE Trans. on Nanotechnology,10(3), 506-512.

[5]. Gelao, G., Marani, R., Pizzulli, L., & Perri, A. G. (2015a). A model to improve analysis of CNTFET logic gates in Verilog-A - Part I: static analysis. Current Nanoscience, 11(4), 515-526.

[6]. Gelao, G., Marani, R., Pizzulli, L., & Perri, A. G. (2015b). A model to improve analysis of CNTFET logic gates in Verilog-A - Part II: dynamic analysis. Current Nanoscience, 11, (6), 770-783.

[7]. Javey, A., Guo, J., Wang, Q., Lundstrom, M., & Dai (2003). Ballistic carbon nanotube field-effect transistors. Nature, 424, 654.

[8]. Javey, A., Kim, H., Brink, M., Wang, Q., Ural, A., Guo, J...., & Dai, M. (2002). High–K dielectrics for advanced carbon nanotube transistors and logic gates. Nature Materials, 1, 241-246.

[9]. Lee, C-S., Pop, E., Franklin, A D., Haensch, W., & Wong, H-S. P. (2015a). A compact virtual-source model for carbon nanotube field-effect transistors in the sub-10-nm regime-Part I: Intrinsic elements. IEEE Transactions on Electron Devices, 62(9), 3061-3069.

[10]. Lee, C-S., Pop, E., Franklin, A. D., Haensch, W., & Wong, H-S P. (2015b). A compact virtual-source model for carbon nanotube field-effect transistors in the sub-10-nm regime-Part II: Extrinsic elements, per formance assessment, and design optimization. IEEE Transactions on Electron Devices, 62(9), 3070-3078.

[11]. Marani, R., Gelao, G., & Perri, A. G. (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). Modeling of carbon nanotube field effect transistors oriented to SPICE software for A/D circuit design. Microelectronics Journal, 44(1),33-39.

[13]. 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.

[14]. Marani, R., & Perri, A. G. (2012). A DC model of carbon nanotube field effect transistor for CAD applications. International Journal of Electronics, 99(3), 427-444.

[15]. Marani, R., & Perri, A. G. (2016a). Analysis of CNTFETs operating in subthreshold region for low power digital applications. ECS Journal of Solid State Science and Technology, 5(2), M1-M4.

[16]. Marani, R., & Perri, A G. (2016b). A de-embedding procedure to determine the equivalent circuit parameters of RF CNTFETs. ECS Journal of Solid State Science and Technology, 5(5), M31-M34.

[17]. Marani R., & Perri A. G. (2016c). A simulation study of analogue and logic circuits with CNTFETs. ECS Journal of Solid State Science and Technology, 5(6), M38-M43.

[18]. Marani R., & Perri A. G. (2017). A simulation study of basic digital circuits using Molecular Diodes. i-manager's Journal on Electronics Engineering, 7(3), 1-10.

[19]. Naderi, A., Noorbakhsh, S. M., & Elahipanah, H. (2012). Temperature dependence of electrical characteristic of carbon nanotube field effect transistors: A quantum simulation study. Journal of Nanomaterials, 1- 7.

[20]. Perri, A. G. (2009). Fondamenti di Elettronica, Progedit editor, Bari, Italy.

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

[22]. 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.

[23]. Verilog-AMS Language Reference Manual. (2014). Version 2.2.

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Research Paper

IoT Based Smart Health Monitoring System

Udigala Basavaraju Mahadevaswamy * , Zaibabuktiyar Durgad**

*Professor, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India.

**PG Scholar, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India.

Mahadevaswamy,U.B., Durgad,Z.,(2019).IoT Based Smart Health Monitoring System.i-manager’s Journal on Electronics Engineering,9(2),8-23. https://doi.org/10.26634/jele.9.2.14867

Abstract

Globalization around the world has led to a number of spontaneous technologies. Among them artificial intelligence is one such technique which can be implemented through IoT. The aim of this work is to design and develop a system which performs the tasks of measurement of vital parameters, such as temperature, blood pressure, and heart rate. The measured values are continuously updated on ThingSpeak server using Wi-Fi module and in case of abnormalities, the information is conveyed to the concerned doctor through SMS using GSM module. An alert call is also initiated to the doctor after a couple of minutes. The system also has an inbuilt pill tracker unit, which alerts the patient at right time to take the prescribed tablet and it also warns the patient in case of wrong tablet selection. Simultaneously, the message regarding wrong tablet selection is sent to the caretaker. The system is also programmed to measure and categorize the nature of blood pressure. The performance of the system with respect to the measurement of blood pressure, heart rate, and temperature is evaluated under the supervision of a qualified physician. The readings recorded by the system are compared with the observations recorded by the physician using conventional methods. The application of the system as pill tracker is studied by considering a patient with multiple ailments.

References

[1]. Al-Aubidy, K. M., Derbas, A. M., & Al-Mutairi, A. W. (2016). Real-time patient health monitoring and alarming using wireless-sensor-network. In 2016 13^th International Multi-Conference on Systems, Signals & Devices (SSD) (pp. 416-423). IEEE.

[2]. Amendola, S., Lodato, R., Manzari, S., Occhiuzzi, C., & Marrocco, G. (2014). RFID technology for IoT-based personal healthcare in smart spaces. IEEE Internet of Things Journal, 1(2), 144-152.

[3]. Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., & Tarricone, L. (2015). An IoTaware architecture for smart healthcare systems. IEEE Internet of Things Journal, 2(6), 515-526.

[4]. Gope, P., & Hwang, T. (2016). BSN-Care: A secure IoT-based modern healthcare system using body sensor network. IEEE Sensors Journal, 16(5), 1368-1376.

[5]. Gupta, P., Agrawal, D., Chhabra, J., & Dhir, P. K. (2016). IoT based smart healthcare kit. In 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT) (pp. 237-242). IEEE.

[6]. Kumar, M. A., & Sekhar, Y. R. (2015). Android based health care monitoring system. In 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS) (pp. 1-5). IEEE.

[7]. Lakshmanachari, S., Srihari, C., Sudhakar, A., & Nalajala, P. (2017). Design and implementation of cloud based patient health care monitoring systems using IoT. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) (pp. 3713-3717). IEEE.

[8]. Mahadevaswamy, U. B. (2018). Wireless Wearable Smart Healthcare Monitoring using Android, I. J. Computer Networkand Information Security.2,12-19.

[9]. Pasluosta, C. F., Gassner, H., Winkler, J., Klucken, J., & Eskofier, B. M. (2015). An emerging era in the management of Parkinson's disease: Wearable technologies and the Internet of Things. IEEE Journal of Biomedical and Health Informatics, 19(6), 1873-1881.

[10]. Patil, N., & Iyer, B. (2017). Health monitoring and tracking system for soldiers using Internet of Things (IoT). In 2017 International Conference on Computing, Communication and Automation (ICCCA) (pp. 1347- 1352). IEEE.

[11]. Saha, J., Saha, A. K., Chatterjee, A., Agrawal, S., Saha, A., Kar, A., & Saha, H. N. (2018). Advanced IoT based combined remote health monitoring, home automation and alarm system. In 2018 IEEE 8^th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 602-606). IEEE.

[12]. Sali, S., & Parvathi, C. S. (2017). Integrated wireless instrument for heart rate and body temperature measurement. In 2017 2^nd International Conference for Convergence in Technology (I2CT) (pp. 457-463). IEEE.

[13]. Staessen, J. A., Li, Y., Hara, A., Asayama, K., Dolan, E., & O'Brien, E. (2017). Blood pressure measurement anno 2016. American Journal of Hypertension, 30(5), 453-463.

[14]. Vinod, K. P., & Mahadevaswamy, U. B. (2018). Unilateral vital signs monitoring systems on IoT. International Journal of Engineering and Manufacturing, 8(1), 53-62.

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Research Paper

Low Power Design for Testability Implementation for Asynchronous FIFO

Madhu Kumar Patnala* , R. Nagendra**

*_** Assistant Professor (SL), Center for VLSI & Embedded Systems, Department of Electronics and Communication Engineering, SreeVidyanikethan Engineering College, (Autonomous) Tirupati, Andhra Pradesh, India.

Patnala,M.K.,Nagendra,R.(2019).Low Power Design for Testability Implementation for Asynchronous FIFO.i-manager’s Journal on Electronics Engineering,9(2),24-28. https://doi.org/10.26634/jele.9.2.15142

Abstract

A First in First out (FIFO) is used as a memory buffer between two asynchronous systems with simultaneous write and read access to and from the FIFO, where these accesses being independent of one another. Sequential operation of FIFO is particularly useful for implementing system level functions like Packet Buffering, Frequency Coupling, and Bus Matching. Asynchronous FIFO is a memory file, which uses synchronization for reading and writing with different clocks, by performing the conditions of over-run and under-run. In essence, the transfer of data from read domain to write domain with different frequencies. To generate overrun and under-run status flags, the synchronization takes place with the help of “preceding operation”of both the write and read pointers. In this design, the gray code converters are used to reduce switching activity and the low power Design for Testability (DFT) technique was applied by considering the two phases that is scan insertion and ATPG Simulations. This design is executed by using synthesizable VERILOG (Register Transfer Level) RTL Code and verified with Xilinx ISE simulator.

References

[1]. Anumothu, M., Kishore, K. H., & Reddy, D. V. (2016). Integrating FPGAs with trigger circuitry coresystem insertions for observability in debugging process. Journal of Engineering and Applied Sciences, 11(12), 2643-2650.

[2]. Charan, N. S., Kishore, K. H. (2016). Recognization of delay faults in cluster based FPGA using BIST. Indian Journal of Science and Technology, 9(28), 1-7. DOI: 10.17485/ijst/2016/v9i28/92389

[3]. Dastagiri, B. N., Kishore, K. H. (2016a). Analysis of Low Power Low Kickback Noise in Dynamic Comparators in Pacemakers. Indian Journal of Science and Technology, 9(44), 1-4.

[4]. Dastagiri, B. N., & Kishore, K. H. (2016b). Reduction of Kickback Noise in Latched Comparators for Cardiac IMDs. Indian Journal of Science and Technology, 9(43), 1-6.

[5]. Gopal, P. B., & Kishore, K. H. (2016). An FPGA Implementation of on Chip UART testing with BIST Techniques. International Journal of Reconfigurable and Embedded Systems, 5(3), 176-182.

[6]. Hussain, S. N., & Kishore, K. H. (2016). Computational Optimization of Placement and Routing using Genetic Algorithm. Indian Journal of Science and Technology, 9(47), 1-4.

[7]. Kishore, K. H., Akhil, K., Viswanath, G., Kumar, N. P. (2016). Design and Implement of 8x8 Multiplier using 4-2 Compressor and 5-2 Compressor. International Journal of Reconfigurable and Embedded Systems, 5(3), 131-135.

[8]. Mudavath, M., & Kishore, K. H. (2016). Design of CMOS RF Front-End of Low Noise Amplifier for LTE System Applications. Asian Journal of Information Technology, Medwell Journal, (15), 4040-4047.

[9]. Ramesh, G., Kumar, V., & Reddy, K. (2012). Asynchronous FIFO design with gray code pointer for high speed AMBA AHB compliant memory controller. IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), 1, 32- 37.

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Research Paper

Contemplation on Smart Toll Collection Strategies and Enhancement

Mohil Kumar Verma* , Rakesh Anand, Amit Kumar Barnwal*, Surekha Bhusnur****

_UG Scholar, Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India.

**Professor,Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India.

Verma,M.,Anand,R.,Barnwal,A.,Bhusnur,S.(2019).Contemplation on Smart Toll Collection Strategies and Enhancement.i-manager’s Journal on Electronics Engineering,9(2),29-35. https://doi.org/10.26634/jele.9.2.15112

Abstract

The problem of managing smart toll lanes is one of the crucial topics of researchers and transportation industry. This paper provides an insight to various strategies involved in Smart Toll Collection System (STCS). One of the most widely used techniques for STCS is the Radio Frequency Identification (RFID) technique. A small prototype hardware realization of STCS is delineated to make the basics discernible. This paper describes the toll collection system based on distance travelled by the vehicle using RFID technology. The vehicle will hold a unique identification number assigned to the vehicle by traffic governing authority. All basic information as well as prepaid account details to ensure payment against toll tax incurred, is stored in the data base of the STCS. The unique tag number is read by the RFID reader at both entry and exit of the toll road and gate number will be stored in data base. At the time of exit, the distance will be calculated by the microcontroller. The billing amount is then displayed, balance is deducted from the prepaid balance, and new balance is updated. This paper is a short communication to enable a novice to decipher the details involved in STCS in a facile manner.

References

[1]. Arduino Mega 2560. (2018). Datasheet. http://www.mantech.co.za/datasheets/products/ A000047.pdf.

[2]. Electronic toll collection on Highways: NHAI Signs Pact (2014). Indian Tollways. Retrieved from http://www.indiantollways.com/category/- etc/

[3]. Khali, H., Araar, A., Abdulla, A. (2014). Suitability of passive RFID technology for fast moving vehicle identification. Journal of Emerging Trends in Computing and Information Sciences, 5(1), 44-51.

[4]. Khan, A. A., Yakzan, A. I. E., & Ali, M. (2011). Radio Frequency Identification (RFID) based toll collection system. In 2011 Third International Conference on Computational Intelligence, Communication Systems and Networks (pp. 103-107). IEEE

[5]. Laghari, A. A., Memon, M. S., & Pathan, A. S. (2012). RFID based toll deduction system. IJ Information Technology and Computer Science, 4, 40-46.

[6]. Landt, J. (2005). The history of RFID. IEEE Potentials. 24(4), 8–11.

[7] Michael, K., & McCathie, L. (2005, July). The pros and cons of RFID in supply chain management. In International Conference on Mobile Business (ICMB'05) (pp. 623-629). IEEE.

[8]. Rosencranz, A. (2017). High- occupancy toll lanes will combat air pollution and foster a more disciplined driving culture. In The Hindu. Retrieved from http://www.jgls.edu. in/article/high-occupancy-toll-lanes-will-combat-airpollution- and-foster-more-disciplined-driving

[9]. Satyasrikanth, P., Penna, M., & Bolla, D. R. (2016). Automatic toll collection system using RFID. International Journal of Computer Science and Mobile Computing, 5(8), 247-253.

[10]. SkyRFID Inc. (2019). RFID Range Overview. Retrieved from https://skyrfid.com/RFID_Range.php

[11]. Sreekumar, A., Meena, A., & Shahabudeen, S. (2014). Telematics and potential in indian market. SAE International Journal of Passenger Cars-Electronic and Electrical Systems, 7(2), 399-405.

[12]. TCI. (2016). Operational Efficiency of Freight Transportation by Road in India. Calcutta: TCI Leaders in Logistics.

[13]. Tentzeris, X. Z. (2011). Applications of Fast-Moving RFID tags in high-speed railway systems. International Journal of Engineering Business Management, 3(1), 27- 31.

[14]. Ting, S., Tsang, A. H., & Tse, Y. (2013). A framework for the implementation of RFID systems. International Journal of Engineering Business Management, 5, 5-9.

[15]. WSTC. (2006). Washington state comprehensive tolling study final report :toll technology considerations, opportunities, and risks (Vol. 2). Washington State Transportation Commission. Retrieved from http://www.wstc.wa.gov/Rates/Tolling/FR1_WS_TollStudy_V ol2_Paper08.pdf

[16]. Win, A., M., Nwe, C. M., & Latt, K.Z. (2014). RFID based automated toll plaza system. International Journal of Scientific and Research Publications, 4(6), 1-7.

[17]. Yang, L., Saigal, R., & Zhou, H. (2012). Distancebased dynamic pricing strategy for managed toll lanes. Transportation Research Record: Journal of the Transportation Research Board, 2283, 90-99.

[18]. Yoon, W., Chung, S., & Lee, S. (2008). Implementation and performance evaluation of an active RFID system for fast tag collection. Computer Communications, 31(17), 4107-4116.

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Research Paper

Energy Efficiency and Enhancement in Cognitive Radio Cellular Set-Up

G. Karpagarajesh* , S. Narmatha , A. V. Niranjana , M. Ramya , P. Sivagami

*Assitant Professor, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India.

_*** Undergraduate, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India.

Karpagarajesh,G.,Narmatha,S.,Niranjana,A.V.,Ramya,M.,Sivagami,P.(2019). Energy Efficiency and Enhancement in Cognitive Radio Cellular Set-Up.i-manager’s Journal on Electronics Engineering,9(2),36-44. https://doi.org/10.26634/jele.9.2.15397

Abstract

As the quantity of mobile clients increments exponentially, improving the pectrum effectiveness was more important by keeping in mind the end goal to suit more clients. In this paper, by abusing the collaboration between Principle Base Stations (PBS) and Minor Base Stations (MBS), another vitality range exchanging model was proposed to upgrade the vitality and also range proficiency of cell systems. By utilizing cognitive radio, PBS shares some part of their authorized range with MBS. MBS in return to give information administration to the rule clients under their scope. Efficient power Energy Attentive Request (GEAR) and Adaptive Request Allocation (ARA) calculations are the calculations to accomplish a decent estimation of the ideal arrangement in less time.

References

[1]. Ansari, N., & Han, T. (2017). Green Mobile Networks: A Networking Perspective. John Wiley & Sons.

[2]. Deruyck, M., Vereecken, W., Tanghe, E., Joseph, W., Pickavet, M., Martens, L., & Demeester, P. (2010). Power consumption in wireless access network. In 2010 European Wireless Conference (EW) (pp. 924-931). IEEE.

[3]. Cordeiro, C., Challapali, K., Birru, D. (2006). An introduction to the first wireless standard based on cognitive radios. Journal of Communications, 1(1), 38-47.

[4]. Cormio, C., & Chowdhury, K. R. (2009). A survey on MAC protocols for cognitive radio networks. Ad Hoc Networks, 7(7), 1315-1329.

[5]. Ehsan, S., & Hamdaoui, B. (2012). A survey on energy-efficient routing techniques with QoS assurances for wireless multimedia sensor networks. IEEE Communications Surveys & Tutorials, 14(2), 265-278.

[6]. Etoh, M., Ohya, T., & Nakayama, Y. (2008). Energy consumption issues on mobile network systems. In 2008 International Symposium on Applications and the Internet (365-368). IEEE.

[7]. 3GPP. (2010). 3GPP r3-100162: Overview to LTE energy saving solutions to cell switch OFF/ON: In 3GPP RAN3 Meeting.

[8]. Han,T., & Ansari, N. (2011). Energy efficient wireless multicasting. IEEE Commun. Letters, 15 (6), 620-622.

[9]. Hasan, Z., Boostanimehr, H., & Bhargava, V. K. (2011). Green cellular networks: A survey, some research issues and challenges. IEEE Communications Surveys & Tutorials, 13 (4), 524-540.

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[14]. Oh,E., & Krishnamachari, B. (2010). Energy savings through dynamic base station switching in cellular wireless access networks. In 2010 IEEE Globecom (pp.1-5).

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

Current Issue Vol. 15 Issue 1

Most Read

Most Cited

Volume 9 Issue 2 December - February 2019

A Comparison of CNTFET Models through a Simulation Study of Digital Circuits

Roberto Marani* , Anna Gina Perri**

Marani,R.,Perri,A.G.(2019).A Comparison of CNTFET Models through a Simulation Study of Digital Circuits.i-manager’s Journal on Electronics Engineering,9(2),1-7. https://doi.org/10.26634/jele.9.2.15180

Abstract

References

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IoT Based Smart Health Monitoring System

Udigala Basavaraju Mahadevaswamy * , Zaibabuktiyar Durgad**

*Professor, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India. **PG Scholar, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India.

Mahadevaswamy,U.B., Durgad,Z.,(2019).IoT Based Smart Health Monitoring System.i-manager’s Journal on Electronics Engineering,9(2),8-23. https://doi.org/10.26634/jele.9.2.14867

Abstract

References

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Low Power Design for Testability Implementation for Asynchronous FIFO

Madhu Kumar Patnala* , R. Nagendra**

*_** Assistant Professor (SL), Center for VLSI & Embedded Systems, Department of Electronics and Communication Engineering, SreeVidyanikethan Engineering College, (Autonomous) Tirupati, Andhra Pradesh, India.

Patnala,M.K.,Nagendra,R.(2019).Low Power Design for Testability Implementation for Asynchronous FIFO.i-manager’s Journal on Electronics Engineering,9(2),24-28. https://doi.org/10.26634/jele.9.2.15142

Abstract

References

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Contemplation on Smart Toll Collection Strategies and Enhancement

Mohil Kumar Verma* , Rakesh Anand**, Amit Kumar Barnwal***, Surekha Bhusnur****

*_***UG Scholar, Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India. ****Professor,Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India.

Verma,M.,Anand,R.,Barnwal,A.,Bhusnur,S.(2019).Contemplation on Smart Toll Collection Strategies and Enhancement.i-manager’s Journal on Electronics Engineering,9(2),29-35. https://doi.org/10.26634/jele.9.2.15112

Abstract

References

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Energy Efficiency and Enhancement in Cognitive Radio Cellular Set-Up

G. Karpagarajesh* , S. Narmatha **, A. V. Niranjana ***, M. Ramya ****, P. Sivagami*****

*Assitant Professor, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India. **_***** Undergraduate, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India.

Karpagarajesh,G.,Narmatha,S.,Niranjana,A.V.,Ramya,M.,Sivagami,P.(2019). Energy Efficiency and Enhancement in Cognitive Radio Cellular Set-Up.i-manager’s Journal on Electronics Engineering,9(2),36-44. https://doi.org/10.26634/jele.9.2.15397

Abstract

References

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*Professor, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India.

**PG Scholar, Department of Electronics and Communication, JSSS&TU, Mysuru, Karnataka, India.

Mohil Kumar Verma* , Rakesh Anand, Amit Kumar Barnwal*, Surekha Bhusnur****

_UG Scholar, Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India.

**Professor,Department of Electrical and Electronics Engineering, Bhilai Institute of Technology, Durg, (C.G), India.

G. Karpagarajesh* , S. Narmatha , A. V. Niranjana , M. Ramya , P. Sivagami

*Assitant Professor, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India.

_*** Undergraduate, Department of Electronics and Communication Engineering, Government College of Engineering, Tamilnadu, India.