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The DVB-H Standard: Comparative Analysis of the Results Obtained for Various Modulation Techniques and Different Code Rates

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u00a0Sneha A. Pandya, Charmy Patel, Jignesh H. Joshi,

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nJanuary 10, 2023 at 4:50 am

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DVB-H happens to be the technical specification for the transmission of digital TV to mobile telephones and PDAs—handheld receivers. Published as a formal standard, DVB-H is a physical layer specification designed to facilitate the proficient delivery of IP-encapsulated data over terrestrial networks. The making of DVB-H, which is closely associated with DVB-T, also entailed modifications of some other DVB standards dealing with data broadcasting, service Information, etc. It can be used as a bearer in concurrence with the DVB-IPDC systems layer specifications. A non- proprietary open standard, DVB-H has broad support, and services are currently on air in more than ten nations. When the possibility of a dedicated DVB specification for broadcasting to handhelds was first discussed, it was in the context of the proven mobile performance of DVB-T, the widely adopted standard for digital terrestrial TV. The key applications considered were mobile TV, video streaming in general, and file downloads, all targeted at handheld receivers that would operate with limited battery life and in difficult reception conditions. This paper mainly concentrates on the comparative analysis carried out when DVB-H has been applied to random data types and the results obtained are compared for QPSK, 16, and 64 QAM methods along with various code rates.

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Volume :u00a0u00a08 | Issue :u00a0u00a01 | Received :u00a0u00a0April 5, 2021 | Accepted :u00a0u00a0April 16, 2021 | Published :u00a0u00a0April 29, 2021n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)] [/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue The DVB-H Standard: Comparative Analysis of the Results Obtained for Various Modulation Techniques and Different Code Rates under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]
Keywords DVBH, OFDM, single frequency network, terrestrial networks, time slicing

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1. Reimers UH. DVB-The Family of International Standards for Digital Video Broadcasting. Proc. IEEE. 2006; 94(1): 173–182.
2. Polak Ladislav. Simulation of the DVBH transmission in MATLAB. [Online] Available from https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2010_sbornik/03- Doktorske_projekty/01-Elektronika_a_komunikace/06-xpolak18.pdf.
3. Sneha Pandya, Charmy Patel. The DVB-H Standard: efficient energy utilizing standard compared to DVB-T2. International Journal of Research and Analytical Reviews (IJRAR). 2019; 6(2): 2019.
4. Masood F. A study on digital video broadcasting to a handheld device (DVB-H), operating in UHF band. Computing Research Repository—CORR. 2011.
5. James Clerk, Maxwell MA. A Treatise on Electricity and Magnetism. 3rd ed. Oxford: Clarendon; 1873.
6. Mobile Digital TV (DVB-H/SH) and 2nd Generation DVB Systems (DVB-S2/C2/T2). Laboratory Exercise [Online] Available from https://docplayer.net/21792262-Mobile-digital-tv- dvb-h-sh-and-2-nd-generation-dvb-systems-dvb-s2-c2-t2.html.
7. Kornfeld Michael, May Gunther. Broadcasting to handhelds, DVB factsheet. IEEE. 2007; 53(1): 161–170.
8. Kornfeld Michael, Reimers Ulrich. DVB-H—the emerging standard for mobile data communication. IEEE International Symposium on Consumer Electronics. Reading, UK. 2004, Sept 1–3.
9. Faria G, Henriksson JA, Stare E, et al. DVB-H: Digital broadcast services to handheld devices. Proc. IEEE. 2006; 94(1): 194–209.
10. European Telecommunications Standards Institute (ETSI). ETSI EN 302 304: 2004. Digital Video Broadcasting (DVB): Transmission System for Handheld Terminals. European Standard (Telecommunications Series) Sophia Antipolis Cedex – FRANCE. ETSI.
11. Borko A, Syed A. Handbook of Mobile Broadcasting, DVB-H, DMB, ISDB-T and MEDIAFLO. Boca Raton: Auerbach Publications; April 2008.

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[if 424 not_equal=”Regular Issue”] Regular Issue[/if 424] Open Access Article

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Recent Trends in Electronics Communication Systems

ISSN: 2393-8757

Editors Overview

rtecs maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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    Sneha A. Pandya, Charmy Patel, Jignesh H. Joshi

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  1. Associate Professor, Associate Professor, Associate Professor,Department of Electronics and Communication Engineering, V.V.P. Engineering College, Rajkot, Department of Electronics and Communication Engineering, V.V.P. Engineering College, Rajkot, Department of Electronics and Communication Engineering, V.V.P. Engineering College, Rajkot,Gujarat, Gujarat, Gujarat,India, India, India

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nDVB-H happens to be the technical specification for the transmission of digital TV to mobile telephones and PDAs—handheld receivers. Published as a formal standard, DVB-H is a physical layer specification designed to facilitate the proficient delivery of IP-encapsulated data over terrestrial networks. The making of DVB-H, which is closely associated with DVB-T, also entailed modifications of some other DVB standards dealing with data broadcasting, service Information, etc. It can be used as a bearer in concurrence with the DVB-IPDC systems layer specifications. A non- proprietary open standard, DVB-H has broad support, and services are currently on air in more than ten nations. When the possibility of a dedicated DVB specification for broadcasting to handhelds was first discussed, it was in the context of the proven mobile performance of DVB-T, the widely adopted standard for digital terrestrial TV. The key applications considered were mobile TV, video streaming in general, and file downloads, all targeted at handheld receivers that would operate with limited battery life and in difficult reception conditions. This paper mainly concentrates on the comparative analysis carried out when DVB-H has been applied to random data types and the results obtained are compared for QPSK, 16, and 64 QAM methods along with various code rates.n

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Keywords: DVBH, OFDM, single frequency network, terrestrial networks, time slicing

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1. Reimers UH. DVB-The Family of International Standards for Digital Video Broadcasting. Proc. IEEE. 2006; 94(1): 173–182.
2. Polak Ladislav. Simulation of the DVBH transmission in MATLAB. [Online] Available from https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2010_sbornik/03- Doktorske_projekty/01-Elektronika_a_komunikace/06-xpolak18.pdf.
3. Sneha Pandya, Charmy Patel. The DVB-H Standard: efficient energy utilizing standard compared to DVB-T2. International Journal of Research and Analytical Reviews (IJRAR). 2019; 6(2): 2019.
4. Masood F. A study on digital video broadcasting to a handheld device (DVB-H), operating in UHF band. Computing Research Repository—CORR. 2011.
5. James Clerk, Maxwell MA. A Treatise on Electricity and Magnetism. 3rd ed. Oxford: Clarendon; 1873.
6. Mobile Digital TV (DVB-H/SH) and 2nd Generation DVB Systems (DVB-S2/C2/T2). Laboratory Exercise [Online] Available from https://docplayer.net/21792262-Mobile-digital-tv- dvb-h-sh-and-2-nd-generation-dvb-systems-dvb-s2-c2-t2.html.
7. Kornfeld Michael, May Gunther. Broadcasting to handhelds, DVB factsheet. IEEE. 2007; 53(1): 161–170.
8. Kornfeld Michael, Reimers Ulrich. DVB-H—the emerging standard for mobile data communication. IEEE International Symposium on Consumer Electronics. Reading, UK. 2004, Sept 1–3.
9. Faria G, Henriksson JA, Stare E, et al. DVB-H: Digital broadcast services to handheld devices. Proc. IEEE. 2006; 94(1): 194–209.
10. European Telecommunications Standards Institute (ETSI). ETSI EN 302 304: 2004. Digital Video Broadcasting (DVB): Transmission System for Handheld Terminals. European Standard (Telecommunications Series) Sophia Antipolis Cedex – FRANCE. ETSI.
11. Borko A, Syed A. Handbook of Mobile Broadcasting, DVB-H, DMB, ISDB-T and MEDIAFLO. Boca Raton: Auerbach Publications; April 2008.

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Recent Trends in Electronics Communication Systems

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[if 344 not_equal=””]ISSN: 2393-8757[/if 344]

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Volume 8
Issue 1
Received April 5, 2021
Accepted April 16, 2021
Published April 29, 2021

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Coverage Driven Verification of Synchronous FIFO using UVM

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u00a0Anusha Bhanu, Rajesh Odela, G.R. Padmini,

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nJanuary 9, 2023 at 8:22 am

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FIFO (first in first out) is a memory array in which the data written first into the memory will be read first with the help of the control signals read and write where the control signal write is used to write the data into the memory and the control signal read is used to read the data from the memory. To avoid the memory overflow and to know that whether there is a space in memory to write, a few status signals are asserted which are empty and full. The empty signal is high which means that all the memory location in the FIFO is empty i.e., no data written is into it and if the full signal is high then all the memory location in the FIFO is occupied with some data. The FIFO has been designed with a depth of 64 locations and the size of each location is 16-bit and verify it with the help of System Verilog-based UVM (universal verification methodology). The coverage driven verification is being used to verify the design functional accuracy. Constrained randomization has been used to attain the maximum amount of coverage (i.e., both code coverage and functional coverage). Code coverage of 99.43% and functional coverage of 100% have been achieved.

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Volume :u00a0u00a08 | Issue :u00a0u00a01 | Received :u00a0u00a0March 12, 2021 | Accepted :u00a0u00a0April 10, 2021 | Published :u00a0u00a0April 29, 2021n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)] [/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue Coverage Driven Verification of Synchronous FIFO using UVM under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]
Keywords Code coverage, design and verification, functional coverage, synchronous FIFO

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1. Akhare Mohini, Narkhede Nitin. Design and verification of generic FIFO using layered test bench and assertion technique. International Journal of Engineering and Advanced Technology (IJEAT). 2019; 8(6): 5254–5260.
2. Vinoth Nagarajan. The design and verification of a synchronous first-in-first-out (FIFO) module using system verilog based universal verification methodology (UVM). [Master’s Project]. New York: Rochester Institute of Technology. 2018.
3. Morris Mano, Emeritus, Michael D. Digital Design: with an Introduction to the Verilog HDL. 5th ed. Pearson Education: Uttar Pradesh, India: January 2013.
4. Bergeron Janick. Writing Testbenches Using System Verilog. Berlin, Germany: Springer; 2006.
5. Maurya Shilpa. Design of RTL synthesizable 32-Bit FIFO memory. International Journal of Engineering Research & Technology (IJERT). 2016; 5(11): 591–593.
6. Bergeron Janick. Writing Testbenches: Functional Verification of HDL Models. Germany: Springer; 2003.
7. Samir Palnitkar. Verilog HDL: A Guide to Digital Design and Synthesis. 2nd ed. Hoboken, New Jersey: Prentice Hall PTR; 2003.
8. Navaid Zafar Rizvi, Rajat Arora. Implementation and verification of synchronous FIFO using system verilog verification methodology. Journal of Communications Technology, Electronics and Computer Science. 2015; 2: 18.
9. Amit Kumar, Shankar, Neeraj Sharma. Verification of asynchronous FIFO using system. International Journal of Computer Applications. 2014; 86(11): 0975–8887.
10. Mehta Ashok B. System Verilog Assertions and Functional Coverage. 2nd ed. New York: Springer Verlag; 2013.

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[if 424 not_equal=”Regular Issue”] Regular Issue[/if 424] Open Access Article

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Recent Trends in Electronics Communication Systems

ISSN: 2393-8757

Editors Overview

rtecs maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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    Anusha Bhanu, Rajesh Odela, G.R. Padmini

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  1. Assistant Professor, Associate Professor, Associate Professor,Vasavi College of Engineering, Vasavi College of Engineering, Vasavi College of Engineering,Hyderabad, Telangana, Hyderabad, Telangana, Hyderabad, Telangana,India, India, India

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nFIFO (first in first out) is a memory array in which the data written first into the memory will be read first with the help of the control signals read and write where the control signal write is used to write the data into the memory and the control signal read is used to read the data from the memory. To avoid the memory overflow and to know that whether there is a space in memory to write, a few status signals are asserted which are empty and full. The empty signal is high which means that all the memory location in the FIFO is empty i.e., no data written is into it and if the full signal is high then all the memory location in the FIFO is occupied with some data. The FIFO has been designed with a depth of 64 locations and the size of each location is 16-bit and verify it with the help of System Verilog-based UVM (universal verification methodology). The coverage driven verification is being used to verify the design functional accuracy. Constrained randomization has been used to attain the maximum amount of coverage (i.e., both code coverage and functional coverage). Code coverage of 99.43% and functional coverage of 100% have been achieved.n

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Keywords: Code coverage, design and verification, functional coverage, synchronous FIFO

n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)]

n[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]

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1. Akhare Mohini, Narkhede Nitin. Design and verification of generic FIFO using layered test bench and assertion technique. International Journal of Engineering and Advanced Technology (IJEAT). 2019; 8(6): 5254–5260.
2. Vinoth Nagarajan. The design and verification of a synchronous first-in-first-out (FIFO) module using system verilog based universal verification methodology (UVM). [Master’s Project]. New York: Rochester Institute of Technology. 2018.
3. Morris Mano, Emeritus, Michael D. Digital Design: with an Introduction to the Verilog HDL. 5th ed. Pearson Education: Uttar Pradesh, India: January 2013.
4. Bergeron Janick. Writing Testbenches Using System Verilog. Berlin, Germany: Springer; 2006.
5. Maurya Shilpa. Design of RTL synthesizable 32-Bit FIFO memory. International Journal of Engineering Research & Technology (IJERT). 2016; 5(11): 591–593.
6. Bergeron Janick. Writing Testbenches: Functional Verification of HDL Models. Germany: Springer; 2003.
7. Samir Palnitkar. Verilog HDL: A Guide to Digital Design and Synthesis. 2nd ed. Hoboken, New Jersey: Prentice Hall PTR; 2003.
8. Navaid Zafar Rizvi, Rajat Arora. Implementation and verification of synchronous FIFO using system verilog verification methodology. Journal of Communications Technology, Electronics and Computer Science. 2015; 2: 18.
9. Amit Kumar, Shankar, Neeraj Sharma. Verification of asynchronous FIFO using system. International Journal of Computer Applications. 2014; 86(11): 0975–8887.
10. Mehta Ashok B. System Verilog Assertions and Functional Coverage. 2nd ed. New York: Springer Verlag; 2013.

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Recent Trends in Electronics Communication Systems

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[if 344 not_equal=””]ISSN: 2393-8757[/if 344]

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Volume 8
Issue 1
Received March 12, 2021
Accepted April 10, 2021
Published April 29, 2021

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Development of Game Theory Strategy for Estimating Mobility Variety in Approaching Wireless Networks

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u00a0Ancy.M, Vijayaprabhu A., Gopalakrishnan S,

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nJanuary 9, 2023 at 8:33 am

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Game theory designed with a set of structured tools with an evaluation tool for the tedious interaction among logical players. This theory approaches for analyzing of communication networks, which functions with autonomous structured networks and the designed network devices can take rational decisions according to network congestion. The proposed structure consists of mixture frame for channel allocation for random probability for accessing channel. The main objective of this work is to reduce the cost of wireless access while satisfying the quality-of-service requirements thereby developing a game theoretic model and also to estimate both the stable coalitional structure and the optimal channel access policy from the game model. Then the average cost of optimal and stable coalitional structure is compared with the dominant coalitional structures which achieves the lowest average cost.

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Volume :u00a0u00a08 | Issue :u00a0u00a03 | Received :u00a0u00a0January 23, 2022 | Accepted :u00a0u00a0February 15, 2022 | Published :u00a0u00a0February 21, 2021n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)] [/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue Development of Game Theory Strategy for Estimating Mobility Variety in Approaching Wireless Networks under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]
Keywords Social preparedness, Game theory, channel allocation, Quality of Service, Network congestion, Wireless access.

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1. K. Y. Islam, I. Ahmad, D. Habibi, and A. Waqar, “A survey on energy efficiency in underwater wireless communications,” J. Netw. Comput. Appl., vol. 198, p. 103295, Feb. 2022, doi: 10.1016/J.JNCA.2021.103295.
2. J. Fahad A. Rida, “Development of a remote health care wireless sensor network based on wireless spread spectrum communication networks,” Mater. Today Proc., Mar. 2021, doi: 10.1016/J.MATPR.2021.02.534.
3. M. M. Ahmed, A. Ganguly, A. Vashist, and S. M. Pudukotai Dinakarrao, “AWARe-Wi: A jamming-aware reconfigurable wireless interconnection using adversarial learning for multichip systems,” Sustain. Comput. Informatics Syst., vol. 29, p. 100470, Mar. 2021, doi: 10.1016/j.suscom.2020.100470.
4. A. Ometov et al., “A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges,” Comput. Networks, vol. 193, p. 108074, Jul. 2021, doi: 10.1016/J.COMNET.2021.108074.
5. M. Abbasi, A. Shahraki, M. Jalil Piran, and A. Taherkordi, “Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey,” Eng. Appl. Artif. Intell., vol. 102, p. 104234, Jun. 2021, doi: 10.1016/J.ENGAPPAI.2021.104234.
6. S. K. Memon, N. I. Sarkar, A. Al-Anbuky, and M. A. Hossain, “Preemptive admission control mechanism for strict QoS guarantee to life-saving emergency traffic in wireless LANs,” J. Netw.Comput. Appl., vol. 199, 2022, doi:10.1016/j.jnca.2021.103318.
7. B. Sahin, D. Yazir, A. Soylu, and T. L. Yip, “Improved fuzzy AHP based game-theoretic model for shipyard selection,” Ocean Eng., vol. 233, 2021, doi: 10.1016/j.oceaneng.2021.109060.
8. K. Abid, H. Lakhlef, and A. Bouabdallah, “A survey on recent contention-free MAC protocols for static and mobile wireless decentralized networks in IoT,” Computer Networks, vol. 201. Elsevier,p. 108583, Dec. 24, 2021, doi:10.1016/j.comnet.2021.108583.
9. S. H. Al-Sharaeh, “Dynamic rate-based borrowing scheme for QoS provisioning in high speed multimedia wireless cellular networks,” Appl. Math. Comput., vol. 179, no. 2, pp. 714–724, 2006, doi: 10.1016/j.amc.2005.11.119.
10. P. Ghasemi, F. Goodarzian, J. Muñuzuri, and A. Abraham, “A cooperative game theory approach for location-routing-inventory decisions in humanitarian relief chain incorporating stochastic planning,” Appl. Math. Model., vol. 104, pp. 750–781, Apr. 2022, doi: 10.1016/j.apm.2021.12.023.
11. M. Alizadeh Bidgoli and A. Ahmadian, “Multi-stage optimal scheduling of multi-microgrids using deep-learning artificial neural network and cooperative game approach,” Energy, vol. 239, p.122036, Jan. 2022, doi:10.1016/J.ENERGY.2021.122036.
12. B. Pourpeighambar, M. Dehghan, and M. Sabaei, “Non-cooperative reinforcement learning based routing in cognitive radio networks,” Comput. Commun., vol. 106, pp. 11–23, Jul. 2017, doi: 10.1016/J.COMCOM.2017.02.013.
13. H. Wang, C. Zhang, K. Li, and X. Ma, “Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage,” Energy, vol. 221, p. 119777, Apr. 2021, doi:10.1016/J.ENERGY.2021.119777.
14. M. Noura and R. Nordin, “A survey on interference management for Device-to-Device (D2D) communication and its challenges in 5G networks,” J. Netw. Comput. Appl., vol. 71, pp. 130–150, Aug. 2016, doi: 10.1016/j.jnca.2016.04.021.
15. F. Basso, L. J. Basso, M. Rönnqvist, and A. Weintraub, “Coalition formation in collaborative production and transportation with competing firms,” Eur. J. Oper. Res., vol. 289, no. 2, pp. 569– 581, Mar. 2021, doi:10.1016/J.EJOR.2020.07.039.
16. W. Tushar et al., “A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid,” Appl. Energy, vol. 243, pp. 10–20, Jun. 2019, doi: 10.1016/J.APENERGY.2019.03.111.
17. J. Delaram, M. Houshamand, F. Ashtiani, and O. Fatahi Valilai, “A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm,” J. Manuf. Syst., vol. 60, pp. 569–584, Jul. 2021, doi: 10.1016/J.JMSY.2021.07.012.
18. Y. Ishida and S. Ikeno, “Asymmetry of Strategies in Proposal: Gale-Shapley Algorithm on Diagrams,” Procedia Comput. Sci., vol. 96, pp. 1730–1739, Jan. 2016, doi: 10.1016/J.PROCS.2016.08.221.
19. V. Varagapriya, V. V. Singh, and A. Lisser, “Constrained Markov decision processes with uncertain costs,” Oper. Res. Lett., Feb. 2022, doi: 10.1016/J.ORL.2022.02.001.
20. D. A. Melo Moreira, K. Valdivia Delgado, L. Nunes de Barros, and D. Deratani Mauá, “Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget,” Int. J. Approx. Reason., vol. 139, pp. 143–165, Dec. 2021, doi: 10.1016/J.IJAR.2021.09.003.
21. M. Iftikhar, B. Landfeldt, S. Zeadally, and A. Zomaya, “Service level agreements (SLAs) parameter negotiation between heterogeneous 4G wireless network operators,” Pervasive Mob. Comput., vol. 7, no. 5, pp. 525–544, Oct. 2011, doi: 10.1016/J.PMCJ.2011.02.008.
22. D. Sikeridis, E. E. Tsiropoulou, M. Devetsikiotis, and S. Papavassiliou, “Wireless powered Public Safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency,” J. Netw. Comput. Appl., vol. 123, pp. 69–79, Dec. 2018, doi: 10.1016/J.JNCA.2018.09.003
23. A. Roy and N. Sarma, “A synchronous duty-cycled reservation based MAC protocol for underwater wireless sensor networks,” Digit. Commun. Networks, vol. 7, no. 3, pp. 385–398, Aug. 2021, doi: 10.1016/J.DCAN.2020.09.002.
24. D. Pianini, R. Casadei, M. Viroli, and A. Natali, “Partitioned integration and coordination via the self-organising coordination regions pattern,” Futur. Gener. Comput. Syst., vol. 114, pp. 44–68, Jan. 2021, doi:10.1016/J.FUTURE.2020.07.032.

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Recent Trends in Electronics Communication Systems

ISSN: 2393-8757

Editors Overview

rtecs maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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    Ancy.M, Vijayaprabhu A., Gopalakrishnan S

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  1. Research Scholar, Assistant Professor, Professor,Dr. M.G.R. Educational and Research institute, , Sri Venkateswara College of engineering and technology, Siddhartha Institute of Technology and Sciences,,India, India, India

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Abstract

nGame theory designed with a set of structured tools with an evaluation tool for the tedious interaction among logical players. This theory approaches for analyzing of communication networks, which functions with autonomous structured networks and the designed network devices can take rational decisions according to network congestion. The proposed structure consists of mixture frame for channel allocation for random probability for accessing channel. The main objective of this work is to reduce the cost of wireless access while satisfying the quality-of-service requirements thereby developing a game theoretic model and also to estimate both the stable coalitional structure and the optimal channel access policy from the game model. Then the average cost of optimal and stable coalitional structure is compared with the dominant coalitional structures which achieves the lowest average cost.n

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Keywords: Social preparedness, Game theory, channel allocation, Quality of Service, Network congestion, Wireless access.

n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)]

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1. K. Y. Islam, I. Ahmad, D. Habibi, and A. Waqar, “A survey on energy efficiency in underwater wireless communications,” J. Netw. Comput. Appl., vol. 198, p. 103295, Feb. 2022, doi: 10.1016/J.JNCA.2021.103295.
2. J. Fahad A. Rida, “Development of a remote health care wireless sensor network based on wireless spread spectrum communication networks,” Mater. Today Proc., Mar. 2021, doi: 10.1016/J.MATPR.2021.02.534.
3. M. M. Ahmed, A. Ganguly, A. Vashist, and S. M. Pudukotai Dinakarrao, “AWARe-Wi: A jamming-aware reconfigurable wireless interconnection using adversarial learning for multichip systems,” Sustain. Comput. Informatics Syst., vol. 29, p. 100470, Mar. 2021, doi: 10.1016/j.suscom.2020.100470.
4. A. Ometov et al., “A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges,” Comput. Networks, vol. 193, p. 108074, Jul. 2021, doi: 10.1016/J.COMNET.2021.108074.
5. M. Abbasi, A. Shahraki, M. Jalil Piran, and A. Taherkordi, “Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey,” Eng. Appl. Artif. Intell., vol. 102, p. 104234, Jun. 2021, doi: 10.1016/J.ENGAPPAI.2021.104234.
6. S. K. Memon, N. I. Sarkar, A. Al-Anbuky, and M. A. Hossain, “Preemptive admission control mechanism for strict QoS guarantee to life-saving emergency traffic in wireless LANs,” J. Netw.Comput. Appl., vol. 199, 2022, doi:10.1016/j.jnca.2021.103318.
7. B. Sahin, D. Yazir, A. Soylu, and T. L. Yip, “Improved fuzzy AHP based game-theoretic model for shipyard selection,” Ocean Eng., vol. 233, 2021, doi: 10.1016/j.oceaneng.2021.109060.
8. K. Abid, H. Lakhlef, and A. Bouabdallah, “A survey on recent contention-free MAC protocols for static and mobile wireless decentralized networks in IoT,” Computer Networks, vol. 201. Elsevier,p. 108583, Dec. 24, 2021, doi:10.1016/j.comnet.2021.108583.
9. S. H. Al-Sharaeh, “Dynamic rate-based borrowing scheme for QoS provisioning in high speed multimedia wireless cellular networks,” Appl. Math. Comput., vol. 179, no. 2, pp. 714–724, 2006, doi: 10.1016/j.amc.2005.11.119.
10. P. Ghasemi, F. Goodarzian, J. Muñuzuri, and A. Abraham, “A cooperative game theory approach for location-routing-inventory decisions in humanitarian relief chain incorporating stochastic planning,” Appl. Math. Model., vol. 104, pp. 750–781, Apr. 2022, doi: 10.1016/j.apm.2021.12.023.
11. M. Alizadeh Bidgoli and A. Ahmadian, “Multi-stage optimal scheduling of multi-microgrids using deep-learning artificial neural network and cooperative game approach,” Energy, vol. 239, p.122036, Jan. 2022, doi:10.1016/J.ENERGY.2021.122036.
12. B. Pourpeighambar, M. Dehghan, and M. Sabaei, “Non-cooperative reinforcement learning based routing in cognitive radio networks,” Comput. Commun., vol. 106, pp. 11–23, Jul. 2017, doi: 10.1016/J.COMCOM.2017.02.013.
13. H. Wang, C. Zhang, K. Li, and X. Ma, “Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage,” Energy, vol. 221, p. 119777, Apr. 2021, doi:10.1016/J.ENERGY.2021.119777.
14. M. Noura and R. Nordin, “A survey on interference management for Device-to-Device (D2D) communication and its challenges in 5G networks,” J. Netw. Comput. Appl., vol. 71, pp. 130–150, Aug. 2016, doi: 10.1016/j.jnca.2016.04.021.
15. F. Basso, L. J. Basso, M. Rönnqvist, and A. Weintraub, “Coalition formation in collaborative production and transportation with competing firms,” Eur. J. Oper. Res., vol. 289, no. 2, pp. 569– 581, Mar. 2021, doi:10.1016/J.EJOR.2020.07.039.
16. W. Tushar et al., “A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid,” Appl. Energy, vol. 243, pp. 10–20, Jun. 2019, doi: 10.1016/J.APENERGY.2019.03.111.
17. J. Delaram, M. Houshamand, F. Ashtiani, and O. Fatahi Valilai, “A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm,” J. Manuf. Syst., vol. 60, pp. 569–584, Jul. 2021, doi: 10.1016/J.JMSY.2021.07.012.
18. Y. Ishida and S. Ikeno, “Asymmetry of Strategies in Proposal: Gale-Shapley Algorithm on Diagrams,” Procedia Comput. Sci., vol. 96, pp. 1730–1739, Jan. 2016, doi: 10.1016/J.PROCS.2016.08.221.
19. V. Varagapriya, V. V. Singh, and A. Lisser, “Constrained Markov decision processes with uncertain costs,” Oper. Res. Lett., Feb. 2022, doi: 10.1016/J.ORL.2022.02.001.
20. D. A. Melo Moreira, K. Valdivia Delgado, L. Nunes de Barros, and D. Deratani Mauá, “Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget,” Int. J. Approx. Reason., vol. 139, pp. 143–165, Dec. 2021, doi: 10.1016/J.IJAR.2021.09.003.
21. M. Iftikhar, B. Landfeldt, S. Zeadally, and A. Zomaya, “Service level agreements (SLAs) parameter negotiation between heterogeneous 4G wireless network operators,” Pervasive Mob. Comput., vol. 7, no. 5, pp. 525–544, Oct. 2011, doi: 10.1016/J.PMCJ.2011.02.008.
22. D. Sikeridis, E. E. Tsiropoulou, M. Devetsikiotis, and S. Papavassiliou, “Wireless powered Public Safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency,” J. Netw. Comput. Appl., vol. 123, pp. 69–79, Dec. 2018, doi: 10.1016/J.JNCA.2018.09.003
23. A. Roy and N. Sarma, “A synchronous duty-cycled reservation based MAC protocol for underwater wireless sensor networks,” Digit. Commun. Networks, vol. 7, no. 3, pp. 385–398, Aug. 2021, doi: 10.1016/J.DCAN.2020.09.002.
24. D. Pianini, R. Casadei, M. Viroli, and A. Natali, “Partitioned integration and coordination via the self-organising coordination regions pattern,” Futur. Gener. Comput. Syst., vol. 114, pp. 44–68, Jan. 2021, doi:10.1016/J.FUTURE.2020.07.032.

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Volume 8
Issue 3
Received January 23, 2022
Accepted February 15, 2022
Published February 21, 2021

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Views: 1,280

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Blind Image Quality Assessment using NSS Approach in the DCT Domain

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u00a0Sayali S. Deshmkh1, H. K. Waghmare,

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nJanuary 9, 2023 at 6:11 am

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nAbstract

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We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are used to form features that are informed of perceptual quality. Before calculating the parameters as the bilateral filter is applied, so it gives the processing time of the bilateral filter which may vary depending upon the input provided by the user. So using this model we calculate PSNR, Mean, Standard Deviation and entropy for indication of errors if any while processing. There are many algorithms which are based on no reference picture to calculate image quality such as Visual Information Fidelity (VIF) algorithm, BRISQUE and NIQE. Consequently, if these algorithms are performed on image distortions, then these algorithms are expected to perform as per desired on the distortions they have raised during processing. It is highly required for many application to improve image quality with zero level of error. The algorithm does computation for the parameters which user expect at output. The certain extracted features to predict image quality scores approach depends on a simple Bayesian inference model

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Volume :u00a0u00a011 | Issue :u00a0u00a03 | Received :u00a0u00a0December 23, 2021 | Accepted :u00a0u00a0December 28, 2021 | Published :u00a0u00a0January 10, 2021n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)] [/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue Blind Image Quality Assessment using NSS Approach in the DCT Domain under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]
Keywords Natural scene statistics, Discrete, Cosine, Transform.

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1. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEETrans. Image Process., vol. 13, no. 4, pp. 600–612, Apr. 2004.
2. Z. Wang, E. P. Simoncelli, and A. C. Bovik, “Multiscale structural similarity image quality assessment,” in Proc. 37th Asilomar Conf. Signals Syst. Comput., Nov. 2003, pp. 1398–1402.
3. D. M. Chandler and S. S. Hemami, “VSNR: A wavelet-based visual signal-to-noise ratio for natural images,” IEEE Trans. Image Process., vol. 16, no. 9, pp. 2284–2298, Sep. 2007.
4. H. R. Sheikh, A. C. Bovik, and G. de Veciana, “Image information and visual quality,” IEEE Trans. Image Process., vol. 15, no. 2, pp. 430–444,Feb. 2006.
5. P. C. Teo and D. J. Heeger, “Perceptual image distortions,” Proc. SPIE, vol. 2179, pp. 127–141,Feb. 1994.
6. V. Laparra, J. Munoz-Mari, and J. Malo, “Divisive normalization image quality metric revisited,” J. Opt. Soc. Amer., vol. 27, no. 4, pp. 852–864, Apr. 2010.
7. E. Cohen and Y. Yitzhaky, “No-reference assessment of blur and noise impacts on image quality,” Signal Image Video Process., vol. 4, no. 3, pp. 289–302, 2010.
8. A. M. Tourapis, A. Leontaris, K. Suhring, and G. Sullivan, “H.264/14496-10 AVC reference software manual,” in Proc. 31st Meeting Joint Video Team, Jul. 2009, pp. 1–90.
9. Z. Wang, A. C. Bovik, and B. L. Evans, “Blind measurement of blocking artifacts in images,” in Proc. IEEE Int. Conf. Image Process., Sep. 2000, pp. 981–984.
10. Z. M. P. Sazzad, Y. Kawayoke, and Y. Horita, “No-reference image quality assessment for jpeg2000 based on spatial features,” Signal Process. Image Commun., vol. 23, no. 4, pp. 257–268, Apr. 2008.

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[if 424 not_equal=”Regular Issue”] Regular Issue[/if 424] Open Access Article

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Recent Trends in Electronics Communication Systems

ISSN: 2393-8757

Editors Overview

rtecs maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

n

“},{“box”:4,”content”:”

n“},{“box”:1,”content”:”

    By  [foreach 286]n

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    Sayali S. Deshmkh1, H. K. Waghmare

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    2. [/foreach]

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    [foreach 286] [if 1175 not_equal=””]n t

  1. Student, Professor,Marathwada Institute of Technology, Marathwada Institute of Technology,Aurangabad Maharashtra, Aurangabad Maharashtra,India, India

    2. n[/if 1175][/foreach]

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Abstract

nWe have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are used to form features that are informed of perceptual quality. Before calculating the parameters as the bilateral filter is applied, so it gives the processing time of the bilateral filter which may vary depending upon the input provided by the user. So using this model we calculate PSNR, Mean, Standard Deviation and entropy for indication of errors if any while processing. There are many algorithms which are based on no reference picture to calculate image quality such as Visual Information Fidelity (VIF) algorithm, BRISQUE and NIQE. Consequently, if these algorithms are performed on image distortions, then these algorithms are expected to perform as per desired on the distortions they have raised during processing. It is highly required for many application to improve image quality with zero level of error. The algorithm does computation for the parameters which user expect at output. The certain extracted features to predict image quality scores approach depends on a simple Bayesian inference modeln

n

n

Keywords: Natural scene statistics, Discrete, Cosine, Transform.

n[if 424 equals=”Regular Issue”][This article belongs to Recent Trends in Electronics Communication Systems(rtecs)]

n[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Recent Trends in Electronics Communication Systems(rtecs)] [/if 424]

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n[if 1104 equals=””]

1. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEETrans. Image Process., vol. 13, no. 4, pp. 600–612, Apr. 2004.
2. Z. Wang, E. P. Simoncelli, and A. C. Bovik, “Multiscale structural similarity image quality assessment,” in Proc. 37th Asilomar Conf. Signals Syst. Comput., Nov. 2003, pp. 1398–1402.
3. D. M. Chandler and S. S. Hemami, “VSNR: A wavelet-based visual signal-to-noise ratio for natural images,” IEEE Trans. Image Process., vol. 16, no. 9, pp. 2284–2298, Sep. 2007.
4. H. R. Sheikh, A. C. Bovik, and G. de Veciana, “Image information and visual quality,” IEEE Trans. Image Process., vol. 15, no. 2, pp. 430–444,Feb. 2006.
5. P. C. Teo and D. J. Heeger, “Perceptual image distortions,” Proc. SPIE, vol. 2179, pp. 127–141,Feb. 1994.
6. V. Laparra, J. Munoz-Mari, and J. Malo, “Divisive normalization image quality metric revisited,” J. Opt. Soc. Amer., vol. 27, no. 4, pp. 852–864, Apr. 2010.
7. E. Cohen and Y. Yitzhaky, “No-reference assessment of blur and noise impacts on image quality,” Signal Image Video Process., vol. 4, no. 3, pp. 289–302, 2010.
8. A. M. Tourapis, A. Leontaris, K. Suhring, and G. Sullivan, “H.264/14496-10 AVC reference software manual,” in Proc. 31st Meeting Joint Video Team, Jul. 2009, pp. 1–90.
9. Z. Wang, A. C. Bovik, and B. L. Evans, “Blind measurement of blocking artifacts in images,” in Proc. IEEE Int. Conf. Image Process., Sep. 2000, pp. 981–984.
10. Z. M. P. Sazzad, Y. Kawayoke, and Y. Horita, “No-reference image quality assessment for jpeg2000 based on spatial features,” Signal Process. Image Commun., vol. 23, no. 4, pp. 257–268, Apr. 2008.

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Recent Trends in Electronics Communication Systems

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[if 344 not_equal=””]ISSN: 2393-8757[/if 344]

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Volume 11
Issue 3
Received December 23, 2021
Accepted December 28, 2021
Published January 10, 2021

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Views: 1,292

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Recent Developments in the Design and Use of Fractional-Order Circuits and Systems

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Recent Trends in Electronics Communication Systems

ISSN: 2393-8757

Editors Overview

rtecs maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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Open Access

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Special Issue

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Topic

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n Recent Developments in the Design and Use of Fractional-Order Circuits and Systemsn

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Abstract Submission Deadline : November 30, 2023

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Manuscript Submission Deadline : December 25, 2023

n [if 457 equals=”Special Issue”]

[This article belongs to Special Issue Recent Developments in the Design and Use of Fractional-Order Circuits and Systems under section rtecs in Recent Trends in Electronics Communication Systems(rtecs)] [/if 457]n

n Special Issue Descriptionn

Electrical engineers are becoming more interested in the developing field of fractional-order calculus, and its deeply ingrained mathematical ideas are slowly making their way into other engineering disciplines. The fact that research on fractional-order circuits and systems is an interdisciplinary field is particularly significant. In particular, it is a region where biochemistry, medicine, and electrical engineering converge, opening up a wide range of new possible applications. The literature has described implementations of fractional-order devices, circuits, and systems. Furthermore, there are several biological uses of fractional-order circuits, Particularly in energy storage technologies like super-capacitors, fuel cells, and batteries are being investigated.

n [if 233 not_equal=””]Editor [foreach 234]n

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n [/foreach][/if 233]n Keywordsn

Fractional-Order Circuits, Capacitors, Electrical devices, Design methods, Modeling electronic

n Manuscript Submission informationn

Manuscripts should be submitted online via the manuscript Engine. Once you register on APID, click here to go to the submission form. Manuscripts can be submitted until the deadline.n All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the email address:[email protected] for announcement on this website.n Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a Double-blind peer-review process. A guide for authors and other relevant information for the submission of manuscripts is available on the Instructions for Authors page.

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