Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470583
J. Bhuvana, Megha Pandeya, Deepak Kumar
This study's paper examines using a generative opposed network as an excellent way to predict the malignancy of tumors in a clinically applicable manner. The examination outcomes imply that the DCGAN-based total version can make surprisingly dependable predictions of tumor malignancy compared to other machine-mastering strategies. Furthermore, the authors additionally propose that the DCGAN-based total version may be hired in scientific applications with promising effects.
{"title":"Examining the Use of Generative Adversarial Network for Predicting Tumor Malignancy","authors":"J. Bhuvana, Megha Pandeya, Deepak Kumar","doi":"10.1109/ICOCWC60930.2024.10470583","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470583","url":null,"abstract":"This study's paper examines using a generative opposed network as an excellent way to predict the malignancy of tumors in a clinically applicable manner. The examination outcomes imply that the DCGAN-based total version can make surprisingly dependable predictions of tumor malignancy compared to other machine-mastering strategies. Furthermore, the authors additionally propose that the DCGAN-based total version may be hired in scientific applications with promising effects.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"3 4","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470512
Sunil Kumar, Bhuvana J, Rakhi Gupta
This study affords a help vector system-based totally (SVMB) technique to beautify the accuracy of endmember estimation from hyperspectral snapshots. The research applies the SVMB method to the hyperspectral photograph band selection and endmember extraction using the guide vector regression (SVR) method to extract endmembers correctly from hyperspectral pix. The proposed model is examined with an artificial dataset composed of four substances and a real-international dataset of 4 forms of soil to illustrate the model's effectiveness as it should be estimating endmembers from the pix. The version is located to have significant improvement in phrases of accuracy compared with existing techniques. The proposed technique merges the characteristic extraction procedure, the selection of suitable bands, and the endmember extraction system into an unmarried level to decorate accuracy and reduce the time needed for hyperspectral photograph evaluation. The studies also propose a method to select appropriate bands with the assistance of SVR to sharpen the spectral data. The proposed version's outcomes show the proposed method's effectiveness for correctly estimating end members from hyperspectral snapshots.
{"title":"A Support Vector Machine Based Approach for Accuracy Enhancement in End Member Estimation from Hyper Spectral Images","authors":"Sunil Kumar, Bhuvana J, Rakhi Gupta","doi":"10.1109/ICOCWC60930.2024.10470512","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470512","url":null,"abstract":"This study affords a help vector system-based totally (SVMB) technique to beautify the accuracy of endmember estimation from hyperspectral snapshots. The research applies the SVMB method to the hyperspectral photograph band selection and endmember extraction using the guide vector regression (SVR) method to extract endmembers correctly from hyperspectral pix. The proposed model is examined with an artificial dataset composed of four substances and a real-international dataset of 4 forms of soil to illustrate the model's effectiveness as it should be estimating endmembers from the pix. The version is located to have significant improvement in phrases of accuracy compared with existing techniques. The proposed technique merges the characteristic extraction procedure, the selection of suitable bands, and the endmember extraction system into an unmarried level to decorate accuracy and reduce the time needed for hyperspectral photograph evaluation. The studies also propose a method to select appropriate bands with the assistance of SVR to sharpen the spectral data. The proposed version's outcomes show the proposed method's effectiveness for correctly estimating end members from hyperspectral snapshots.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"65 45","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470863
A. Kannagi, Dr. Savita, Pankaj Kumar Goswami
Reinforcement getting to know (RL) has emerged as an ability method to deal with electricity green supply chains and improve the sustainability of operations. This paper critiques the software of RL in supply chain management, exploring the primary programs, methodologies, and approaches of incorporating RL in power structures. We overview recent advances in RL that would be implemented to supply chain power modeling, in addition to the benefits and demanding situations that can stand up from using RL for superior management of delivery chains. Further, we provide a conclusion on the blessings of RL as a tool for managing power green supply chains and advise capacity programs for research that explores how RL can be used to enhance the sustainability of operations.
{"title":"Reinforcement Learning to Manage Energy Efficient Supply Chains","authors":"A. Kannagi, Dr. Savita, Pankaj Kumar Goswami","doi":"10.1109/ICOCWC60930.2024.10470863","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470863","url":null,"abstract":"Reinforcement getting to know (RL) has emerged as an ability method to deal with electricity green supply chains and improve the sustainability of operations. This paper critiques the software of RL in supply chain management, exploring the primary programs, methodologies, and approaches of incorporating RL in power structures. We overview recent advances in RL that would be implemented to supply chain power modeling, in addition to the benefits and demanding situations that can stand up from using RL for superior management of delivery chains. Further, we provide a conclusion on the blessings of RL as a tool for managing power green supply chains and advise capacity programs for research that explores how RL can be used to enhance the sustainability of operations.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"57 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470703
Ananta Ojha, D. Yadav, Manish Kumar Goyal
Deep gaining knowledge of is a place of artificial intelligence that is becoming increasingly famous inside the scientific area. This paper provides an improved optimization of computerized detection of cardiac abnormalities the use of deep learning. particularly, the authors recommend using a convolutional neural community (CNN) to stumble on abnormalities from ECG records. They use an ensemble of models to further improve accuracy and reduce false superb quotes. moreover, they apply transfer learning techniques to higher generalize the mastering from the EEG facts. The authors take a look at their optimized set of rules on two datasets of ECG recordings and file an normal accuracy of 88.9%. This demonstrates the potential for deep getting to know techniques to end up an increasing number of reliable and sturdy for detecting cardiac abnormalities. The authors also talk the feasible directions of future studies and the potentials of deep learning for clinical safety and diagnostics in phrases of fee and efficiency.
{"title":"An Enhanced Optimization of Automated Detection of Cardiac Abnormalities Using Deep Learning","authors":"Ananta Ojha, D. Yadav, Manish Kumar Goyal","doi":"10.1109/ICOCWC60930.2024.10470703","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470703","url":null,"abstract":"Deep gaining knowledge of is a place of artificial intelligence that is becoming increasingly famous inside the scientific area. This paper provides an improved optimization of computerized detection of cardiac abnormalities the use of deep learning. particularly, the authors recommend using a convolutional neural community (CNN) to stumble on abnormalities from ECG records. They use an ensemble of models to further improve accuracy and reduce false superb quotes. moreover, they apply transfer learning techniques to higher generalize the mastering from the EEG facts. The authors take a look at their optimized set of rules on two datasets of ECG recordings and file an normal accuracy of 88.9%. This demonstrates the potential for deep getting to know techniques to end up an increasing number of reliable and sturdy for detecting cardiac abnormalities. The authors also talk the feasible directions of future studies and the potentials of deep learning for clinical safety and diagnostics in phrases of fee and efficiency.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"41 12","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/icocwc60930.2024.10470826
{"title":"Copyright and Reprint Permission","authors":"","doi":"10.1109/icocwc60930.2024.10470826","DOIUrl":"https://doi.org/10.1109/icocwc60930.2024.10470826","url":null,"abstract":"","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"37 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470765
Arun Kumar Pipersenia, M.S. Nidhya, Sandeep Kumar Jain
Hybrid network protection algorithms represent a critical vicinity in facts safety techniques. Inside the computation of networking environments, such algorithms provide a cozy and dependable mechanism for site visitor management, records storage, entry to manipulation, and so on. The security of this mechanism is, but suffering from the presence of certain safety vulnerabilities within the gadget. To ensure the powerful operation of modern-day networks, these vulnerabilities need to be identified and addressed. This paper explores some of the procedures to be had for the identification and addressing of the safety vulnerabilities in hybrid community security algorithms: The security goals the ones want to be worked on, consisting of authentication, authorization, records integrity, and confidentiality, are mentioned. Several assault fashions, consisting of insider attacks, man-in-the-center assaults, and brute-pressure assaults, are also stated to detail the vulnerabilities in hybrid protection algorithms. Modern practices for figuring out and addressing safety vulnerabilities in hybrid community security algorithms are supplied. Those consist of techniques which include reading network site visitors, assessing the trustworthiness of customers, enforcing encryption techniques, and applying community entry to controls. Several protection models, in addition to protocols for reaching secure verbal exchange in hybrid networks, are examined.
{"title":"Identifying and Addressing Security Vulnerabilities in Hybrid Network Security Algorithms","authors":"Arun Kumar Pipersenia, M.S. Nidhya, Sandeep Kumar Jain","doi":"10.1109/ICOCWC60930.2024.10470765","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470765","url":null,"abstract":"Hybrid network protection algorithms represent a critical vicinity in facts safety techniques. Inside the computation of networking environments, such algorithms provide a cozy and dependable mechanism for site visitor management, records storage, entry to manipulation, and so on. The security of this mechanism is, but suffering from the presence of certain safety vulnerabilities within the gadget. To ensure the powerful operation of modern-day networks, these vulnerabilities need to be identified and addressed. This paper explores some of the procedures to be had for the identification and addressing of the safety vulnerabilities in hybrid community security algorithms: The security goals the ones want to be worked on, consisting of authentication, authorization, records integrity, and confidentiality, are mentioned. Several assault fashions, consisting of insider attacks, man-in-the-center assaults, and brute-pressure assaults, are also stated to detail the vulnerabilities in hybrid protection algorithms. Modern practices for figuring out and addressing safety vulnerabilities in hybrid community security algorithms are supplied. Those consist of techniques which include reading network site visitors, assessing the trustworthiness of customers, enforcing encryption techniques, and applying community entry to controls. Several protection models, in addition to protocols for reaching secure verbal exchange in hybrid networks, are examined.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"30 4","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470750
Chandra Kant Gautam, Amit Kumar, Bhuvana J
this text surveys the usage of fuzzy logic for constructing self-organized underwater communication networks. Fuzzy common sense is a type of computing logic where approximate in place of particular values are applied. Fuzzy common sense is utilized in several underwater communique network designs due to its potential of making choices primarily based on records that is inconsistent, approximate, and with out clear parameters. The emphasis of this text is on Hierarchical Fuzzy logic (HFL) and its use inside the production of underwater communique networks. HFL allows self-agency thru the use of fuzzy rulebased structures that make use of fuzzy common sense to make choices at each step. thru HFL, a gadget can create an prepared, dependable conversation network based totally on its surroundings and the statistics available. using statistics which includes noise stages, speed/distance of moving objectives, and verbal exchange variety, HFL permits underwater communique networks to create dynamic clusters that could adapt to the surroundings and carefully hyperlink all nodes inside the machine. in addition, HFL provides the ability to detect performance degradation resulting from nodes departing from the network, and restoration techniques to conquer those changes. eventually, the object discusses how HFL can reduce the complexity of the machine, and outlines future research possibilities in its application.
{"title":"Applying Fuzzy Logic for Constructing Self-Organized Underwater Communication Networks","authors":"Chandra Kant Gautam, Amit Kumar, Bhuvana J","doi":"10.1109/ICOCWC60930.2024.10470750","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470750","url":null,"abstract":"this text surveys the usage of fuzzy logic for constructing self-organized underwater communication networks. Fuzzy common sense is a type of computing logic where approximate in place of particular values are applied. Fuzzy common sense is utilized in several underwater communique network designs due to its potential of making choices primarily based on records that is inconsistent, approximate, and with out clear parameters. The emphasis of this text is on Hierarchical Fuzzy logic (HFL) and its use inside the production of underwater communique networks. HFL allows self-agency thru the use of fuzzy rulebased structures that make use of fuzzy common sense to make choices at each step. thru HFL, a gadget can create an prepared, dependable conversation network based totally on its surroundings and the statistics available. using statistics which includes noise stages, speed/distance of moving objectives, and verbal exchange variety, HFL permits underwater communique networks to create dynamic clusters that could adapt to the surroundings and carefully hyperlink all nodes inside the machine. in addition, HFL provides the ability to detect performance degradation resulting from nodes departing from the network, and restoration techniques to conquer those changes. eventually, the object discusses how HFL can reduce the complexity of the machine, and outlines future research possibilities in its application.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"22 9","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470594
M. N. Nachappa, D. Yadav, Surjeet Yadav
It has a look at examines revolutionary neural network modeling of lengthy-time period cardiac arrest hazard forecasting. We generated a comprehensive dataset of cardiac arrest sufferers and used a bidirectional lengthy brief-term memory (Bi-LSTM) version to evaluate the risk. Our effects tested that the Bi-LSTM version outperformed conventional machine-studying techniques such as logistic regression and boosted trees in phrases of accuracy and sensitivity. We also used a visualization approach to interpret version predictions, which indicated that our model became capable of appropriately picking out affected person traits associated with cardiac arrest hazards. We concluded that our model could provide practical long-time period chance estimation for cardiac arrest sufferers and may be used for manual scientific interventions and prevent cardiac arrests in clinical contexts.
{"title":"Neural Network Modeling of Long-Term Cardiac Arrest Risk Forecasting","authors":"M. N. Nachappa, D. Yadav, Surjeet Yadav","doi":"10.1109/ICOCWC60930.2024.10470594","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470594","url":null,"abstract":"It has a look at examines revolutionary neural network modeling of lengthy-time period cardiac arrest hazard forecasting. We generated a comprehensive dataset of cardiac arrest sufferers and used a bidirectional lengthy brief-term memory (Bi-LSTM) version to evaluate the risk. Our effects tested that the Bi-LSTM version outperformed conventional machine-studying techniques such as logistic regression and boosted trees in phrases of accuracy and sensitivity. We also used a visualization approach to interpret version predictions, which indicated that our model became capable of appropriately picking out affected person traits associated with cardiac arrest hazards. We concluded that our model could provide practical long-time period chance estimation for cardiac arrest sufferers and may be used for manual scientific interventions and prevent cardiac arrests in clinical contexts.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"228 7","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Go-layer design (CLD) provides a promising approach for optimizing overall performance in multi-hop wi-fi networks. CLD enables coherent optimization of various layers of protocol stacks (e.g. MAC, community, delivery, and alertness) via data trade between layers. with the aid of leveraging a multi-layer angle for community optimization, CLD can achieve significant overall performance development in phrases of throughput, put off, and energy efficiency in comparison to conventional tactics. The CLD method enables closely coupled model thru coordination of MAC, network, delivery, and application layers. the combination of various layers permits the optimization of stop-to-stop overall performance by leveraging various move-layer interactions for adapting to varying channel situations. moreover, CLD can permit the incorporation of topology awareness for optimization of network overall performance. To gain a success CLD optimization, various elements, which includes network modeling, channel estimation, scheduling, congestion manage, and routing, ought to be taken into consideration. To enable CLD optimization, new protocols need to be proposed and new wireless architectures must be designed. moreover, most appropriate CLD techniques should be developed such that the design criteria of numerous layers may be efficiently taken into consideration. moreover, exclusive optimization algorithms need to be studied to optimize the CLD manner.
{"title":"Optimizing Cross-Layer Design for Multi-Hop Wireless Networks","authors":"Manju Bargavi, Girija Shankar Sahoo, Khushboo Sharma","doi":"10.1109/ICOCWC60930.2024.10470800","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470800","url":null,"abstract":"Go-layer design (CLD) provides a promising approach for optimizing overall performance in multi-hop wi-fi networks. CLD enables coherent optimization of various layers of protocol stacks (e.g. MAC, community, delivery, and alertness) via data trade between layers. with the aid of leveraging a multi-layer angle for community optimization, CLD can achieve significant overall performance development in phrases of throughput, put off, and energy efficiency in comparison to conventional tactics. The CLD method enables closely coupled model thru coordination of MAC, network, delivery, and application layers. the combination of various layers permits the optimization of stop-to-stop overall performance by leveraging various move-layer interactions for adapting to varying channel situations. moreover, CLD can permit the incorporation of topology awareness for optimization of network overall performance. To gain a success CLD optimization, various elements, which includes network modeling, channel estimation, scheduling, congestion manage, and routing, ought to be taken into consideration. To enable CLD optimization, new protocols need to be proposed and new wireless architectures must be designed. moreover, most appropriate CLD techniques should be developed such that the design criteria of numerous layers may be efficiently taken into consideration. moreover, exclusive optimization algorithms need to be studied to optimize the CLD manner.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"133 1-4","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470691
Satendra Singh, Shri Bhagwan, C. Menaka
This paper examines video transmission, compression, and supply coding modeling and optimization. The middle challenge of this paper is to investigate the impact of diverse compression and source coding strategies on video overall performance. The paper will analyze the impact of compression and source coding techniques on video transmission bit rate, latency, blunders price, and exceptional provider. Distinctive methods and strategies are discussed for enhancing video performance, including superior supply coding strategies, perceptual metrics, and using a few codecs for high-quality warranty and playback. Furthermore, a comprehensive implementation of a video transmission gadget that contains information compression strategies, channel coding, supply coding, and buffering design is considered. ultimately, an optimization hassle version is formulated to optimize the video's overall performance concerning the compressing and supply coding strategies. Modeling and optimizing video transmission in records compression and supply coding is a crucial research topic for multimedia community communications. It includes transmitting motion video statistics over dispensed networks and the networks themselves. As technological advancements in hardware and software programs preserve to enhance, the layout and improvement of efficient video transmission algorithms grow to be even extra significant. Exclusive coding fashions and optimization strategies have been explored to improve the excellent of virtual video if you want to maximize the perceived excellent and decrease the transmission costs in various eventualities. Researchers have evaluated various techniques for deciding on the most desirable bitrates; finding methods for body charge conversion; improving the coding efficiency in textures, motion vectors, and features; block and remodel coding; and increasing video throughput in diverse network situations. These techniques are critical to enabling dependable, low-latency video transmission. There was growing interest in optimizing video transmission in various use cases, including streaming media, stay broadcasts, and digital fact packages. Standard, optimizing video transmission in statistics compression and supply coding stays a vital topic of exploration to ensure reliable and cost-powerful multimedia communications..
{"title":"Modeling and Optimization of Video Transmission in Data Compression & Source Coding","authors":"Satendra Singh, Shri Bhagwan, C. Menaka","doi":"10.1109/ICOCWC60930.2024.10470691","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470691","url":null,"abstract":"This paper examines video transmission, compression, and supply coding modeling and optimization. The middle challenge of this paper is to investigate the impact of diverse compression and source coding strategies on video overall performance. The paper will analyze the impact of compression and source coding techniques on video transmission bit rate, latency, blunders price, and exceptional provider. Distinctive methods and strategies are discussed for enhancing video performance, including superior supply coding strategies, perceptual metrics, and using a few codecs for high-quality warranty and playback. Furthermore, a comprehensive implementation of a video transmission gadget that contains information compression strategies, channel coding, supply coding, and buffering design is considered. ultimately, an optimization hassle version is formulated to optimize the video's overall performance concerning the compressing and supply coding strategies. Modeling and optimizing video transmission in records compression and supply coding is a crucial research topic for multimedia community communications. It includes transmitting motion video statistics over dispensed networks and the networks themselves. As technological advancements in hardware and software programs preserve to enhance, the layout and improvement of efficient video transmission algorithms grow to be even extra significant. Exclusive coding fashions and optimization strategies have been explored to improve the excellent of virtual video if you want to maximize the perceived excellent and decrease the transmission costs in various eventualities. Researchers have evaluated various techniques for deciding on the most desirable bitrates; finding methods for body charge conversion; improving the coding efficiency in textures, motion vectors, and features; block and remodel coding; and increasing video throughput in diverse network situations. These techniques are critical to enabling dependable, low-latency video transmission. There was growing interest in optimizing video transmission in various use cases, including streaming media, stay broadcasts, and digital fact packages. Standard, optimizing video transmission in statistics compression and supply coding stays a vital topic of exploration to ensure reliable and cost-powerful multimedia communications..","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"12 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：