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Logeshwaran, J.
- SVPA - The Segmentation Based Visual Processing Algorithm (SVPA) For Illustration Enhancements In Digital Video Processing (DVP)
Abstract Views :161 |
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, K.L.N. College of Engineering, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
3 Department of Electronics and Communication Engineering, K.L.N. College of Engineering, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 3 (2022), Pagination: 2669-2673Abstract
At the present time photographic visual processing is rapidly moving towards the next stage. In addition, a variety of visual processing technologies are evolving, such as splitting image dimensions, calibration, pixel beautification, and high-resolution images. The impact of this digital visual processing technology has now greatly enhanced the opportunities for digital video processing technology and the source of its evolution. The vast industry of converting color images from black and white enables it to present even historical videos of the earlier period in a contemporary manner. In this paper, the segmentation based visual processing algorithm is proposed. The algorithm is designed to enhance resolution and clarity to a certain extent with multi-visual enhanced pixels. It also enhances the contrast, brightness and sharpness enhancement as it is much improved over the previous methods. This algorithm works on each image frame and enhances the overall visual function.Keywords
Visual Processing, Visual Processing, Image Dimension, Calibration, Pixel, Segmentation, Resolution, Contrast, Brightness, SharpnessReferences
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- L. Barghout, “Visual Taxometric Approach to Image Segmentation using Fuzzy-Spatial Taxon Cut Yields Contextually Relevant Regions”, Proceedings of International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 163-173, 2014.
- V. Maheshwari, M.R. Mahmood and S. Sravanthi, “Nanotechnology-Based Sensitive Biosensors for COVID19 Prediction Using Fuzzy Logic Control”, Journal of Nanomaterials, Vol. 2021, pp. 1-7, 2021.
- L. Barghout, “Perceptual Information Processing System”, US Patent App, No. 10/618, pp. 543, 2003.
- H. Bay, A. Ess, T. Tuytelaars and L. Van Gool, “SpeededUp Robust Features (Surf)”, Computer Vision and Image Understanding, Vol 110, No. 3, pp. 346-359, 2008.
- J. Mohana, B. Yakkala, S. Vimalnath and P.M. Benson Mansingh, “Application of Internet of Things on the Healthcare Field Using Convolutional Neural Network Processing”, Journal of Healthcare Engineering, Vol. 2022, pp. 1-7, 2022.
- Y. Bengio “Learning Deep Architectures for Ai”, Foundations and Machine Learning, Vol. 2, No. 1, pp. 120127, 2009.
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- T. Brox, L. Bourdev and S. Maji, “Object Segmentation by Alignment of Poselet Activations to Image Contours”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp 2225–2232, 2015.
- G. Dhiman, A.V. Kumar, R. Nirmalan and S. Sujitha, “Multi-Modal Active Learning with Deep Reinforcement Learning for Target Feature Extraction in Multi-Media Image Processing Applications”, Multimedia Tools and Applications, Vol. 89, pp. 1-25, 2022.
- L.C. Chen, J.T. Barron and G. Papandreou, “Semantic Image Segmentation with Task Specific Edge Detection using CNNS and a Discriminatively Trained Domain Transform”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp 4545-4554, 2016.
- M. Ramkumar, N. Basker, D. Pradeep and R. Prajapati, “Healthcare Biclustering-Based Prediction on Gene Expression Dataset”, BioMed Research International, Vol. 2022, pp. 1-8, 2022.
- S. Hannah, A.J. Deepa, V.S. Chooralil and S. Brilly Sangeetha, “Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data”, BioMed Research International, Vol. 2022, pp. 1-9, 2022.
- L.C. Chen, Y. Yang and J. Wang, “Attention to Scale: ScaleAware Semantic Image Segmentation”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3640-3649, 2016.
- A. Cohen, E. Rivlin and I. Shimshoni, “Memory Based Active Contour Algorithm using Pixel-Level Classified Images for Colon Crypt Segmentation”, Computerized Medical Imaging and Graphics, Vol. 43, pp. 150-164, 2019.
- M. Cordts, M. Omran, S. Ramos and T. Rehfeld, “The Cityscapes Dataset for Semantic Urban Scene
- Understanding”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3213-3223, 2016.
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- The Role Of Integrated Structured Cabling System (ISCS) For Reliable Bandwidth Optimization In High-speed Communication Network
Abstract Views :217 |
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Computer Science and Engineering, HKBK College of Engineering, IN
3 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
2 Department of Computer Science and Engineering, HKBK College of Engineering, IN
3 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, IN
4 Department of Automation Control and Robotics, Sheffield Hallam University, GB
Source
ICTACT Journal on Communication Technology, Vol 13, No 1 (2022), Pagination: 2635-2639Abstract
In modern companies, the functions of divisions, departments and staff are provided by telecommunication transmitting analog and digital unit information via SCS. Such cable system refers to the use of copper or optical cable networks, passive and active switching devices. Structured cabling system or abbreviated SCS is a complex set of cable trunks and switching equipment that provide the transfer of various types of media data (audio, video, computer data) and is the basis for the operation and integration of telephone, local computer networks, security systems and other services. Many modern systems of security or communications today integrate a wide variety of interfaces into their arsenal, greatly expanding their capabilities and performance. In this paper a smart model based on high-speed communication network with the help of structured cabling system (SCS). Here the speed and bandwidth play the major role. The proposed system focused the highspeed communication between sender and receiver with some higher bandwidth optimization.Keywords
Optical Cable Network, Switching Device, Structured Cabling System, Communication Network, Security SystemReferences
- E. Hossain, D. Niyato and Z. Han, “Dynamic Spectrum Access in Cognitive Radio Networks”, Cambridge University Press, 2009.
- T.D. Lagkas, D. Klonidis and I. Tomkos, “Joint Spatial and Spectral Resource Optimization over Both Wireless and Optical Fronthaul Domains of 5G Architectures”, Proceedings of 22nd International Conference on Transparent Optical Networks, pp. 1-7, 2020.
- Yuan Ai, Gang Qiu, and Yaohua Sun, “Joint Resource Allocation and Admission Control in Sliced Fog Radio Access Networks”, China Communications, Vol. 17, No. 8, pp. 14-30, 2020
- N. Khumalo, O. Oyerinde and L. Mfupe, Luzango, “Reinforcement Learning-based Computation Resource Allocation Scheme for 5G Fog-Radio Access Network”, Proceedings of 5th International Conference on Fog and Mobile Edge Computing, pp. 353-355, 2020.
- A. Kaloxylos, “A Survey and an Analysis of Network Slicing in 5G Networks”, IEEE Communications Standards Magazine, Vol. 2, No. 1, pp. 60-65, 2018.
- S.A. Syed, K. Sheela Sobana Rani and V.P. Sundramurthy, “Design of Resources Allocation in 6G Cybertwin Technology using the Fuzzy Neuro Model in Healthcare Systems”, Journal of Healthcare Engineering, Vol. 2022, pp. 1-9, 2022.
- Y. Wang, K. Wang, H. Huang, T. Miyazaki and S. Guo, “Traffic and Computation Co-Offloading with Reinforcement Learning in Fog Computing for Industrial Applications”, IEEE Transactions on Industrial Informatics, Vol. 15, No. 2, pp. 976-986, 2019.
- G. Dhiman, A.V. Kumar, R. Nirmalan and K. Srihari, “Multi-Modal Active Learning with Deep Reinforcement Learning for Target Feature Extraction in Multi-Media Image Processing Applications”, Multimedia Tools and Applications, Vol. 2022, pp. 1-25, 2022.
- L. Huang, X. Feng, C. Zhang, L. Qian and Y. Wu, ‘Deep Reinforcement Learning-Based Joint Task Offloading and Bandwidth Allocation for Multiuser Mobile Edge Computing”, Digital Communications and Networks, Vol. 5, No. 1, pp. 10-17, 2019.
- S. Hannah, A.J. Deepa, V.S. Chooralil and S. Brilly Sangeetha, “Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data”, BioMed Research International, Vol. 2022, pp. 1-7, 2022.
- L. Ze, C. Lijie and R. Bo, “Study on the Virtual Simulation Training System for SCS Maintenance”, Proceedings of International Conference on Virtual Reality and Intelligent Systems, pp. 143-146, 2020.
- J. Logeshwaran and R.N. Shanmugasundaram, “Enhancements of Resource Management for Device to Device (D2D) Communication: A Review”, Proceedings of 3 rd International Conference on IoT in Social, Mobile, Analytics and Cloud, pp. 51-55, 2019.
- K. Praghash and T. Karthikeyan, “Data Privacy Preservation and Trade-off Balance Between Privacy and Utility using Deep Adaptive Clustering and Elliptic Curve Digital Signature Algorithm”, Wireless Personal Communications, Vol. 89, pp. 1-16, 2021.
- N. Arivazhagan, K. Somasundaram, D. Vijendra Babu and V. Prabhu Sundramurthy, “Cloud-Internet of Health Things (IOHT) Task Scheduling using Hybrid Moth Flame Optimization with Deep Neural Network Algorithm for E Healthcare Systems”, Scientific Programming, Vol. 2022, pp. 1-8, 2022.
- K. Praghash and T. Karthikeyan, “Binary Flower Pollination (BFP) Approach to Handle the Dynamic Networking Conditions to Deliver Uninterrupted Connectivity”, Wireless Personal Communications, Vol. 82, No. 4, pp. 3383-3402, 2021.
- A Smart Design Of A Multi-dimensional Antenna To Enhance The Maximum Signal Clutch To The Allowable Standards In 5g Communication Networks
Abstract Views :129 |
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Authors
Affiliations
1 Department of Electronics and Communication Technology, Sri Eshwar College of Engineering, IN
2 Wipro Technologies, Pune, IN
1 Department of Electronics and Communication Technology, Sri Eshwar College of Engineering, IN
2 Wipro Technologies, Pune, IN
Source
ICTACT Journal on Microelectronics, Vol 8, No 1 (2022), Pagination: 1269-1274Abstract
Since the operating range of 5G communication networks is the same as that of the previous generation, there are no difficulties in using these antennas on 5G communication networks. For any technology, the use of antennas makes it possible to bring data rates closer to maximum values. The new technology that uses separate receivers and transmitters on the same frequency band has further increased the speed of receiving and transmitting data. The design of the existing 4G modem provides for the use of antenna technology. The proposed model provides the construction of a multidimensional antenna. The other passive devices it has a one-way direction, which increases the received signal and reduces the amount of interference from the sides to the back. Therefore, the proposed model possible to increase the signal level to acceptable values, even at unstable reception levels thereby increasing the speed of receiving and transmitting the information. The undoubted advantage of panel antennas is their low cost and exceptional reliability. There is practically nothing in the design that can be broken even when falling from a great height. The only weak point is the high-frequency cable, which can break at the point where it enters the case. To extend the life of the device, the cable must be securely connected.Keywords
5G Communication Networks, Antenna, Data Rate, Transmitters, 4G Modem, Signal Level, Panel AntennasReferences
- S. Chen, “Vehicle-to-Everything (V2X) Services Supported by LTE-Based Systems and 5G”, IEEE Communications Standards Magazine, Vol. 1, No. 2, pp. 70-76, 2017.
- T. Saeidi, I. Ismail, W.P. Wen, A.R. Alhawari and A. Mohammadi, “Ultra-Wideband Antennas for Wireless Communication Applications”, International Journal of Antennas and Propagation, Vol. 2019, pp. 1-12, 2019.
- Y. He, Y. Chen, L. Zhang, S. Wong and Z.N. Chen, “An Overview of Terahertz Antennas”, China Communications, Vol. 17, No. 7, pp. 124-165, 2020.
- A. Karmakar, “Fractal Antennas and Arrays: A Review and Recent Developments”, International Journal of Microwave and Wireless Technologies, Vol. 13, pp. 1-25, 2020.
- W. Hong, “Solving the 5G Mobile Antenna Puzzle: Assessing Future Directions for the 5G Mobile Antenna Paradigm Shift”, IEEE Microwave Magazine, Vol. 18, No. 7, pp. 86-102, 2017.
- A.D. Boursianis, S.K. Goudos, T.V. Yioultsis, K. Siakavara and P. Rocca, “MIMO Antenna Design for 5G Communication Systems using Salp Swarm Algorithm”, Proceedings of International Workshop on Antenna Technology, pp. 1-3, 2020.
- A.D. Boursianis, S. Koulouridis, D. Georgoulas and S.K. Goudos, “Wearable 5-Gigahertz Wi-Fi Antenna Design using Whale Optimization Algorithm”, Proceedings of 14th European Conference on Antennas and Propagation, pp. 1-4, 2020.
- R. Shadid, M. Haerinia and S. Noghanian, “Study of Rotation and Bending Effects on a Flexible Hybrid Implanted Power Transfer and Wireless Antenna System”, Sensors, Vol. 20, No. 10, pp. 1-13, 2020.
- S. Yang, L. Zhang, J. Fu, Z. Zheng, X. Zhang and A. Liao, “Design and Optimization for 77 GHZ Series-Fed Patch Array Antenna based on Genetic Algorithm”, Sensors, Vol. 20, No. 11, pp. 1-12, 2020.
- H. Sun, X. Ge, W. He and L. Zhao, “A Reconfigurable Antenna with Sum-and Difference-Patterns for WLAN Access Points”, IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 7, pp. 1073-1077, 2020.
- E. Zhang, A. Michel, M. R. Pino, P. Nepa and J. Qiu, “A Dual Circularly Polarized Patch Antenna with High Isolation for MIMO WLAN Applications”, IEEE Access, Vol. 8, pp. 117833-117840, 2020.
- Q. Li, Q. Chu and Y. Chang, “Design of Compact Highisolation MIMO Antenna with Multi-objective Mixed Optimization Algorithm”, IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 8, pp. 1306-1310, 2020.
- T. Aathmanesan and G. Geetharamani, “Design of Metamaterial Antenna for 2.4 GHz WiFi Applications”, Wireless Personal Communication, Vol. 113, pp. 2289-2300, 2020.
- H. Chen, Y. Tsai, C. Sim and C. Kuo, “Broadband 8-Antenna Array Design for Sub-6GHz 5G NR Bands MetalFrame Smartphone Applications”, IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 7, pp. 1078-1082, 2020.
- G. Xie, F. Zhang, S. Liu and Y. Zhao, “A Wideband Dual Polarized Aperture-Coupled Antenna Embedded in a Small Metal Cavity”, IEEE Transactions on Antennas and Propagation, Vol. 89, pp. 1-17, 2020.
- Y. Liu, W. Zhang, Y. Jia and A. Wu, “Low RCS Antenna Array with Reconfigurable Scattering Patterns Based on Digital Antenna Units”, IEEE Transactions on Antennas and Propagation, Vol. 90, pp. 1-14, pp. 1, 2020.
- D. Perez-Quintana, A. Torres-Garcia, I. Ederra and M. Beruete, “Compact Groove Diamond Antenna in Gap Waveguide Technology with Broadband Circular Polarization at Millimeter Waves”, IEEE Transactions on Antennas and Propagation, Vol. 68, No. 8, pp. 5778-5783, 2020.
- C.A. Balanis, “Antenna Theory: Analysis and Design”, John Wiley and Sons, 2016.
- Yi. Huang and K. Boyle, “Antennas from Theory to Practice”, John Wiley and Sons, 2008.
- V. Midasala and P. Siddaiah, “Microstrip Patch Antenna Array Design to Improve Better Gains”, Procedia Computer Science, Vol. 85, pp. 401-409, 2016.
- ELIMINATE THE INTERFERENCE IN 5G ULTRA-WIDE BAND COMMUNICATION ANTENNAS IN CLOUD COMPUTING NETWORKS
Abstract Views :207 |
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Authors
Affiliations
1 Department of Information Technology, K.L.N. College of Engineering., IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 SPC Free Zone., AE
1 Department of Information Technology, K.L.N. College of Engineering., IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 SPC Free Zone., AE
Source
ICTACT Journal on Microelectronics, Vol 8, No 2 (2022), Pagination: 1338-1344Abstract
In this era of technology, every day we see a new change in new development. It is truly astonishing the impressive speed we are seeing, especially in communication technology. This is where 5G comes into play. Transmission stations carry a small amount of transmitted coded signal. Especially when setting up antennas, use them. However, classical versions are based on inductive communication via a measured oscillating circuit. In most cases their small impulses do not allow sufficient contact with antenna elements, for example, with a wire frame. As a result, the indication of the frequency of the element becomes unclear, which leads to significant measurement errors. In this paper, a smart construction of 5G ultra-wide band communication antennas is designed to eliminate the interferences in cloud computing networks. The proposed design simply solved this problem by making a simple special girder to construct its “double square” elements. In a cut-off signal level, the proposed UWBCA design achieved 97.70% of peak data rate, 96.61% of antenna latency, 94.81% of antenna capacity, 96.33% of spectral efficiency and 94.99% of connection density. This proposed design increases its constructive efficiency and contact area from the classic types and prevents interference.Keywords
Communication Technology, 5G, Transmission Stations, Coded Signal, Antennas, Inductive Communication, Oscillating Circuit, Ultra-Wide Band, Cloud ComputingReferences
- T. Saeidi, I. Ismail, W.P. Wen, A.R. Alhawari and A. Mohammadi, “Ultra-Wideband Antennas for Wireless Communication Applications”, International Journal of Antennas and Propagation, Vol. 2019, pp. 1-12, 2019.
- Y. He, Y. Chen, L. Zhang, S. Wong and Z.N. Chen, “An Overview of Terahertz Antennas”, China Communications, Vol. 17, No. 7, pp. 124-165, 2020.
- A. Karmakar, “Fractal Antennas and Arrays: A Review and Recent Developments”, International Journal of Microwave and Wireless Technologies, Vol. 13, pp. 1-25, 2020.
- H. Chen, Y. Tsai, C. Sim and C. Kuo, “Broadband 8- Antenna Array Design for Sub-6GHz 5G NR Bands MetalFrame Smartphone Applications”, IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 7, pp. 1078- 1082, 2020.
- G. Xie, F. Zhang, S. Liu and Y. Zhao, “A Wideband Dual Polarized Aperture-Coupled Antenna Embedded in a Small Metal Cavity”, IEEE Transactions on Antennas and Propagation, Vol. 89, pp. 1-17, 2020.
- Y. Liu, W. Zhang, Y. Jia and A. Wu, “Low RCS Antenna Array with Reconfigurable Scattering Patterns Based on Digital Antenna Units”, IEEE Transactions on Antennas and Propagation, Vol. 90, pp. 1-14, pp. 1, 2020.
- D. Perez-Quintana, A. Torres-Garcia, I. Ederra and M. Beruete, “Compact Groove Diamond Antenna in Gap Waveguide Technology with Broadband Circular Polarization at Millimeter Waves”, IEEE Transactions on Antennas and Propagation, Vol. 68, No. 8, pp. 5778-5783, 2020.
- C.A. Balanis, “Antenna Theory: Analysis and Design”, John Wiley and Sons, 2016.
- Yi. Huang and K. Boyle, “Antennas from Theory to Practice”, John Wiley and Sons, 2008.
- K.F. Al-Tabatabaie and M.N. Saeed, “Design and Fabricate of Miniaturized T-Shape Ultra Wideband Antenna for Wireless Application”, The Scientific Journal of Cihan University-Sulaimaniya, Vol. 6, No. 1, pp. 35-51, 2022.
- J.N. Lee and Y.K. Cho, “A Compact Ultra-Wideband Chip Antenna with Bandwidth Extension Patch and Simple Isolator for MIMO Systems for Mobile Handheld Terminals”, Journal of Electromagnetic Engineering and Science, Vol. 22, No. 3, pp. 272-282, 2022.
- R. Shadid, M. Haerinia and S. Noghanian, “Study of Rotation and Bending Effects on a Flexible Hybrid Implanted Power Transfer and Wireless Antenna System”, Sensors, Vol. 20, No. 10, pp. 1-13, 2020.
- S. Yang, L. Zhang, J. Fu, Z. Zheng, X. Zhang and A. Liao, “Design and Optimization for 77 GHZ Series-Fed Patch Array Antenna based on Genetic Algorithm”, Sensors, Vol. 20, No. 11, pp. 1-12, 2020.
- A. Adekunle, K.E. Ibe, M.E. Kpanaki, C.O. Nwafor, N. Essang and I.I. Umanah, “Evaluating the Effects of Radiation from Cell Towers and High-Tension Power Lines on Inhabitants of Buildings in Ota”, Journal for Sustainable Development, Vol. 3, No. 1, pp. 1-21, 2015.
- E. Ali and A.R. Memari, “Effects of Magnetic Field of Power Lines and Household Appliances on Human and Animals and its Mitigation”, Proceedings of IEEE Middle East Conference on Antennas and Propagation, pp. 1-7, 2010.
- M.A. Abd-Allah, “Interaction of ELF Magnetic Fields with Human Body Organs Model Underneath EHV Transmission Lines”, Proceedings of IEEE PES Power Systems Conference and Exposition, pp. 1967-1970, 2006.
- L. Yang, S. Shangguan and S. Li, “Location InformationAssisted Robust Beamforming Design for Ultra-Wideband Communication Systems”, Symmetry, Vol. 14, No. 6, pp. 1171-1178, 2022.
- N. Taher, A. Zakriti and F. Rahmani, “Circular Ring UWB Antenna with Reconfigurable Notch Band at WLAN/sub 6 G RAMESH et al.: ELIMINATE THE INTERFERENCE IN 5G ULTRA-WIDE BAND COMMUNICATION ANTENNAS IN CLOUD COMPUTING NETWORKS 1344 GHz 5G Mobile Communication”, Microsystem Technologies, Vol. 28, No. 4, pp. 965-972, 2022.
- K. Bhangale, J. Annamaraju and T. Dhamale, “Design and Simulation of UWB Antenna for 4G Applications”, Proceedings of International Conference on Sustainable Communication Networks and Application, pp. 55-66, 2022.
- I. Ahmad, W. Tan and H. Sun, “Latest Performance Improvement Strategies and Techniques Used in 5G Antenna Designing Technology, a Comprehensive Study”, Micromachines, Vol. 13, pp. 717-736, 2022
- The Fuzzy Logical Controller Based Energy Storage and Conservation Model to Achieve Maximum Energy Efficiency in Modern 5g Communication
Abstract Views :73 |
PDF Views:1
Authors
Affiliations
1 Department of Electronics and communication Engineering, Muthayam Engineering College, IN
2 Department of Information Technology, K.L.N. College of Engineering, Madurai, Tamil Nadu, IN
3 Department of Electronics and communication Engineering, Sri Eshwar College of Engineering, IN
1 Department of Electronics and communication Engineering, Muthayam Engineering College, IN
2 Department of Information Technology, K.L.N. College of Engineering, Madurai, Tamil Nadu, IN
3 Department of Electronics and communication Engineering, Sri Eshwar College of Engineering, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 3 (2022), Pagination: 2774-2779Abstract
Energy conservation and energy efficiency for smart antenna design is the reduction of energy consumption per unit of service or product in 5G Communication without reducing production quality and quantity. Efficient use of energy is important in many ways. First, fossil fuels such as oil and coal, which are important sources of energy, are depleting. Greenhouse gas emissions released into the atmosphere during energy production and consumption processes are major causes of climate change and global warming. In this paper, a smart energy storage and conservation model based on fuzzy logical controller was proposed to achieve maximum energy efficiency for smart antenna design in modern 5G Communication. For the initial level the proposed model regularly monitor the energy levels of different industrial components and then allot the energy as per the requirement of the components. If there any excess allocation required, then the proper requirement will request by the operator. Once the request is valid, the requirements will allocate to the components. The biggest factor that provides energy efficiency for smart antenna design is thermal insulation. Consuming less fuel means releasing less harmful gas into the atmosphere.Keywords
Energy, Conservation, Efficiency, Consumption, Fossil Fuels, Industry, Greenhouse, Fuzzy Logical ControllerReferences
- T.T. Teo, T. Logenthiran and K. Abidi, “Fuzzy Logic Control of Energy Storage System in Microgrid Operation”, Proceedings of International Conference on IEEE Innovative Smart Grid Technologies, pp. 65-70, 2016.
- C. Pan and X. Xu, “The Analysis of Series Hybrid Energy Storage System for Regenerative Braking based on Energy Constraint Control aimed at Deceleration”, CSEE Journal of Power and Energy Systems, Vol. 2022, pp. 1-14, 2022.
- M. Michalczuk and L.M. Grzesiak, “Fuzzy Logic based Power Management Strategy using Topographic Data for an Electric Vehicle with a Battery-Ultracapacitor Energy Storage”, The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 56, No. 2, pp. 1-14, 2015.
- S.A. Syed, K. Sheela Sobana Rani and V.P. Sundramurthy, “Design of Resources Allocation in 6G Cybertwin Technology using the Fuzzy Neuro Model in Healthcare Systems”, Journal of Healthcare Engineering, Vol. 2022, pp. 1-8,2022.
- A.S. Nandhini and P. Vivekanandan, “A Survey on Energy Efficient Routing Protocols for MANET”, International Journal of Advances in Engineering and Technology, Vol. 6, No. 1, pp. 370-387, 2013.
- N. Sockeel, B. Papari and M. Mazzola, “Virtual Inertia Emulator-Based Model Predictive Control for Grid Frequency Regulation considering High Penetration of Inverter-Based Energy Storage System”, IEEE Transactions on Sustainable Energy, Vol. 11, No. 4, pp. 2932-2939, 2020.
- J. Gowrishankar, P.S. Kumar and T. Narmadha, “A Trust Based Protocol for Manets in IoT Environment”, International Journal of Advanced Science and Technology, Vol. 29, No. 7, pp. 2770-2775, 2020.
- G. Ramesh, V. Aravindarajan and Feny Thachil, “Eliminate the Interference in 5G Ultra-Wide Band Communication Antennas in Cloud Computing Networks”, ICTACT Journal on Microelectronics, Vol. 8, No. 2, pp. 1338-1344, 2022.
- M.J. Rex, T. Kiruthiga and V.A. Rajan, “FPSMM: Fuzzy Probabilistic Based Semi Morkov Model among the Sensor Nodes for Realtime Applications”, Proceedings of International Conference on Intelligent Sustainable Systems, pp. 442-446,2017.
- S. Kannan and G. Dhiman, “Task Scheduling in Cloud using ACO”, Recent Advances in Computer Science and Communications, Vol. 15, No. 3, pp. 348-353, 2022.
- B. Gopi, J. Gowri and T. Kiruthiga, “The Moment Probability and Impacts Monitoring for Electron Cloud Behavior of Electronic Computers by using Quantum Deep Learning Model”, NeuroQuantology, Vol. 20, No. 8, pp. 6088-6100, 2022.
- T. Karthikeyan and K. Praghash, “Improved Authentication in Secured Multicast Wireless Sensor Network (MWSN) using Opposition Frog Leaping Algorithm to Resist Man-in-Middle Attack”, Wireless Personal Communications, Vol. 123, No. 2, pp. 1715-1731, 2022.
- T. Karthikeyan, “Improved Privacy Preservation Framework for Cloud-Based Internet of Things”, CRC Press, 2020.
- S.B. Sangeetha, R. Sabitha and B. Dhiyanesh, “Resource Management Framework using Deep Neural Networks in Multi-Cloud Environment”, Springer, 2022.
- The Management and Reduction of Digital Noise in Video Image Processing by Using Transmission based Noise Elimination Scheme
Abstract Views :74 |
PDF Views:1
Authors
Affiliations
1 Department of Information Technology, K.L.N. College of Engineering, IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 Department of Electronics and Communication Engineering, SNS College of Technology, IN
4 SPC Free Zone, AE
1 Department of Information Technology, K.L.N. College of Engineering, IN
2 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, IN
3 Department of Electronics and Communication Engineering, SNS College of Technology, IN
4 SPC Free Zone, AE
Source
ICTACT Journal on Image and Video Processing, Vol 13, No 1 (2022), Pagination: 2797-2801Abstract
Digital noise is an image defect that is approximately close to the pixel size and differs in brightness or color from the original image. Noise reduction plays an important role in the transmission, processing and compression of video footage and images. There are a large number of methods for removing noise from images, and they can be used not only by special processing programs, but also in some photo and video cameras. Despite this, there is still no universal filtering algorithm, because when processing an image, there is always a need to choose between preserving small details with properties such as size and noise to eliminate unwanted effects. In this paper, a management and reduction of digital noise in video image processing was discussed in the basis of transmission based noise elimination. In addition, that the proposed scheme easily overcomes the various types of noise. It will identify the spoil the image with another type of noise. Hence the noise affected part will eliminated and reduce the effects of noise.Keywords
Digital Noise, Pixel Size, Brightness, Color, Original Image, Transmission, Processing.References
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- A Novel Architecture of Intelligent Decision Model for Efficient Resource Allocation in 5G Broadband Communication Networks
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, India., IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, India., IN
3 Instituto de Investigacion para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, Spain., ES
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, India., IN
2 Department of Electronics and Communication Engineering, Vetri Vinayaha College of Engineering and Technology, India., IN
3 Instituto de Investigacion para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, Spain., ES
Source
ICTACT Journal on Soft Computing, Vol 13, No 3 (2023), Pagination: 2986-2994Abstract
Intelligent Decision Model for efficient resource allocation in 5G broadband communication networks is essential for ensuring the most efficient use of available resources. This model considers several factors, such as traffic demand, network topology, and radio access technology, to make the most efficient decisions about resource allocation. It is based on intelligent algorithms and advanced analytics, which allow the network to quickly and accurately identify the optimal resource allocation for a given situation. This model can reduce costs, improve network performance, and increase customer satisfaction. In addition, the Intelligent Decision Model can help operators reduce the complexity and cost of managing a 5G network. The intelligent decision model for efficient resource allocation in 5G broadband communication networks is based on a combination of artificial intelligence (AI) and optimization techniques. The proposed decision models can use AI to identify patterns in traffic and user behavior. In contrast, the proposed can use optimization techniques to maximize resource utilization and reduce latency in the network. This model can also leverage predictive analytics and machine learning algorithms to determine the most efficient allocation of resources. Additionally, the proposed model can use AI to detect and mitigate potential security threats and malicious activities in the network. the proposed IDM has reached 91.85% of accuracy, 90.05% of precision, 90.96% of recall and 91.33% of F1-score.Keywords
Intelligent, Decision, Efficient, Resource, Allocation, 5G, Broadband, Communication, Networks.References
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