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An Evaluation of Interactive Communication Media Algorithms and Their Usage for Networking applications 5th

An Evaluation of Interactive Communication Media Algorithms ...

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5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Kudari, Jayashree M. Yadav, Rakesh Kumar Yadav, Surendra Kapse, Vinod Mansiram Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

This paper evaluates using interactive conversation media algorithms inside the context of networking applications. Exceptional forms of algorithms are mentioned, which includes media movement algorithms, interactive conversation protocols, recording algorithms, and video compression protocols. The overall performance of those algorithms is classified and evaluated thru a quantitative analysis that includes measurements of common latency and packet loss. Additionally, the paper investigates using interactive communication media algorithms for one of kind programs together with video conferencing, on line gaming, and voice over IP offerings. Sooner or later, a contrast of various algorithms is made, with hints for the fine answers primarily based on the evaluated performance and application necessities.. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Video conferencing

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Vision-Based Locomotion Control for Humanoid Robots: A Study on Vision-Guided Walking Strategies

Vision-Based Locomotion Control for Humanoid Robots: A Study...

引用

2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Pandey, Saroj Kumar Kumar, Lalan Kumar, Gaurav Kumar, Ankit Singh, Kamred Udham Singh, Teekam Gla University Department of Computer Engineering & Applications UP Mathura India Gl Bajaj Institute of Technology and Management Department of Master of Computer Application India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350323917

Recently, there has been a lot of research on using vision to direct humanoid robots as they walk. Focusing on the major methodologies, difficulties, and prospects, this review article presents an overview of the current state of study in the vision-guided walking of humanoid robots. In the first part of the study, we introduce vision-guided walking and go through the several methods that have been developed to execute it, such as visual serving, visual odometer, and visual simultaneous localization and mapping. The difficulties of vision-guided walking are then discussed;these include, but are not limited to, the necessity for accurate and strong computer vision algorithms, the robot's need to have a solid awareness of its own body and how it moves, and the need to maintain balance while walking. This paper provides a detailed review of the research on humanoid robots that use vision to direct their gait. Deep learning for vision-guided walking, tactile and proprioceptive sensing combined with vision, and reinforcement learning for adaptive walking are only a few of the issues covered in this overview. Future directions in vision-guided walking research are discussed in this paper. These include the development of more advanced and reliable computer vision algorithms, the incorporation of other modalities like tactile and auditory sensing, and the investigation of new applications for vision-guided walking in fields like healthcare and rehabilitation. © 2023 IEEE.

关键词： Anthropomorphic robots

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An Overview of Video Tampering Detection Techniques: State-of-the-Art and Future Directions

An Overview of Video Tampering Detection Techniques: State-o...

引用

2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

ISBN: (纸本)9798350323917

In the realm of video processing and forensics, finding video tampering is a critical challenge. The purposeful change or manipulation of video material to conceal or falsely depict the original information is referred to as 'video tampering.' A significant demand for efficient video tampering detection methods has emerged in recent years as a result of the rise in false news, cyberbullying, and other types of criminal behavior. Modern approaches for detecting video manipulation may be generally divided into two categories: passive methods and aggressive methods. Whereas active methods entail putting digital watermarks or other identifiers on the video clip to aid tampering detection, passive methods rely on evaluating the video content for inconsistencies or artifacts generated during tampering. Techniques like sensor noise analysis, splicing detection, and forgery detection based on compression artifacts are examples of passive approaches. To find any discrepancies produced by manipulation, sensor noise analysis examines the noise patterns in the video. Splicing detection entails identifying the borders between several video segments and inspecting the content of each segment for irregularities. Analyzing the compressed video stream for irregularities caused during tampering is required for detecting forgeries based on compression artifacts. Techniques like digital watermarking, digital signatures, and fingerprinting are examples of active procedures. To detect any manipulation efforts, digital watermarking entails putting a digital watermark into the video clip. To confirm the legitimacy of the video clip, a digital signature is applied to it. To do fingerprinting, special characteristics from the video footage are extracted and saved in a database. In addition to the aforementioned methods, machine learning-based systems have also demonstrated promising outcomes in the identification of video manipulation. Using these methods, any tampering attempts in fresh mov

关键词： Authentication

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Sentiment Analysis of Speeches using VADER, Sentiment Intensity Analyzer, and TextBlob

Sentiment Analysis of Speeches using VADER, Sentiment Intens...

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Advancement in Electronics & Communication engineering (AECE), International Conference on

作者： Ankush Joshi Deepika Joshi Vikash Kumar Anuj Kumar Ritik Kumar Singh Naman Chauhan Computer Science and Application COER University Roorkee India Computer Science and Engineering Amarpali University Haldwani India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

In today’s world the words of a leader are the most valuable entity for his/her followers, and when the leader is a prime minister of one of the largest democratic countries then the value of his/her words is more valuable and important. In this research paper researchers have analyzed the data in the form of sentiments of the two most popular prime ministers of India Dr. Manmohan Singh and Mr. Narendra Modi. By this analysis, researchers can check the impact of their words on the people of India. For analyzing the sentiments researchers have used tools such as TextBlob, VADER, and Sentiment Intensity Analyzer, and for checking the occurrence frequency of words word cloud is used.

关键词： Sentiment analysis Speech analysis Education Tag clouds

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Automated Anomaly Detection in Medical Imaging Using Support Vector Machines 5th

Automated Anomaly Detection in Medical Imaging Using Support...

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5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Goyal, Manish Kumar Shahid, Mohammad Karthikeyan, M.P. Kumar, Ritesh Department of Computer Science & Application Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Clinical imaging techniques such as X-ray, Magnetic Resonance Imaging (MRI), and laptop Tomography (CT) scanners are used to diagnose, compare, and deal with sufferers. Automatic Anomaly Detection is an automatic technique for identifying and diagnosing abnormalities in clinical imaging. It has been diagnosed that Support Vector Machines (SVM) can be effectively used to generate correct automatic anomaly detection for scientific imaging. SVM is an approach that uses supervised getting-to-know to create a choice boundary between classes, with the decision primarily based on the information to be had. The gain of SVM is that it plays an automatic function extracting from the medical imaging facts and uses those extracted capabilities for anomaly detection. It combines photograph segmentation and classification to classify the abnormal regions in an image. So one can enhance the accuracy of SVM;it's miles viable to use an expansion of kernel capabilities and unique parameter tuning. Moreover, introducing an automatic pipeline from training to deploying SVM reduces the efforts of manual feature extraction from photos. Consequently, aid Vector Machines is a feasible approach for automatic anomaly detection in scientific imaging. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Investigating Wireless Networks with Network Coding Algorithms 5th

Investigating Wireless Networks with Network Coding Algorith...

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5th International Conference on Data Science, Machine Learning and applications, ICDSMLA 2023

作者： Ahmed, Zahid Gupta, Anjali Preethi, D. Singh, Akhilendra Pratap Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electrical and Electronic Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Community coding algorithms had been demonstrated to have capability to improve the performance of wireless networks. This paper offers a research, assessment, and implementation of community coding algorithms for Wi-Fi networks. The paper affords an overview of community coding algorithms and discusses the related blessings, drawbacks, and tradeoffs that have to be taken into account while evaluating the performance of these algorithms. Furthermore, simulation outcomes are offered to assess the overall performance of one of a kind network coding algorithms while implemented in a wireless community surroundings. Ultimately, the paper outlines the hardware and software elements required to correctly put into effect and test those algorithms in an operational wireless community. The promising consequences of the experiments imply that these community coding algorithms can be used to efficiently improve the overall performance of Wi-Fi networks within the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

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Jyoti: An Intelligent App for Women Security 1

引用

4th International Conference on Inventive Computation and Information Technologies, ICICIT 2022

作者： Pathak, Pooja Choudhary, Parul Department of Mathematics Institute of Applied Sciences GLA University Uttar Pradesh Mathura India Department of Computer Application and Engineering GLA University Uttar Pradesh Mathura India

ISBN: (数字)9789811974021

ISBN: (纸本)9789811974014

In today’s world of rapid urbanization, a new research chapter in social relations and women’s safety has begun. With this wave of urban transformation comes a growing sense of loneliness and helplessness among certain social groups. Women’s safety is a major issue in this situation, not only for the poor but also for civilized women. Weaknesses in the situation women’s safety plans, practices, and guidelines exist to reduce violence against women and their fear of crime. While alone walking or traveling, women should be aware of their surroundings. The advancement of technology may also contribute to women’s safety. Our proposed application is "Jyoti" for women’s safety. This application helps to prevent female homicide. When a female is in a bad situation, the application will send a message to trusted people and the police will go to current location. This application has unique feature that it sends messages to trusted people at regular intervals while shaking the phone. It also calls for the first trusted contact to assist in an emergency. It will help to reduce female crime. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global positioning system

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Distributed Analytics in Smart Grids with Edge Computing and Computational Intelligence

Distributed Analytics in Smart Grids with Edge Computing and...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Joshi, Apoorva Preethi, D. Gill, Amandeep Noida Institute of Engineering & Technology Master of Computer Application Uttar Pradesh Greater Noida India Department of Computer Science Bangalore India Vivekananda Global University Department of R&d Cell Jaipur India

ISBN: (纸本)9798350357769

Conventional methods like classification or clustering have limits when it comes to handling the complex task for dispersed data mining across heterogeneous sources and divergent data formats. This is especially true in scenarios where stochastic models or mathematical formulas may not be feasible. Data centralization is a prevalent trend that exacerbates problems including communication channel congestion and privacy difficulties related to sensitive data flows. In order to overcome these obstacles, this paper presents the Distributed Academic Engine (DAE), an adaptive edge-based scattered analytic engine designed for distributed networks. The DAE routinely breaks down and divides computations that need data from multiple sources among the nodes that are already in place, enabling the sharing of partial results without disclosing the original data. To get the full expression output, the master node combines these partial results. The expression is decomposed and processing jobs are distributed among nodes using three computational intelligence techniques: genetic algorithm, genetic algorithm using evolution control, the particle swarm optimization. This method's effectiveness is illustrated with a case study on smart grid KPI identification, which shows a noteworthy (over 91%) decrease in communication messages over conventional approaches. This demonstrates how well the suggested method works to reduce the difficulties related to distributed data mining. © 2023 IEEE.

关键词： Computational Intelligence Data Integration and Heterogeneous Data Source Integration Distributed Analytics Edge Computing Genetic Algorithm Particle Swarm Optimization Smart Grid

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A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Capability Evaluation of Manufacturing Enterprises 9th

A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Cap...

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19th International Conference on Advanced Data Mining and applications, ADMA 2023

作者： Liu, Tingting Ding, Xuefeng Jiang, Yuming Hu, Dasha College of Computer Science Sichuan University Chengdu610065 China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu610065 China

ISBN: (纸本)9783031466731

In the collaborative production environment of manufacturing tasks, the evaluation of enterprise technical capability in advance has a direct impact on the high-performance collaboration between the supplier and the demander of production tasks. In order to solve the problem of efficiency and accuracy in the past evaluation methods, this paper applies the adaptive neuro fuzzy inference system (ANFIS) to the field of enterprise technical capability evaluation for the first time, and proposes an improved hybrid intelligent model SFAHP-ANFIS-PSO based on fuzzy theory. The model takes the four key indexes which have the deepest impact on enterprise technical capability evaluation as the input variables of the model, and the input data are evaluated by ANFIS with high accuracy. Spherical fuzzy analytic hierarchy process (SFAHP) calculated the weight of each evaluation index to preprocess the ANFIS model. Particle swarm optimization algorithm (PSO) continuously optimized the model parameters in the training process, shortened the model training time, improved the evaluation efficiency, and further improved the accuracy of the evaluation results. The experimental results show that the SFAHP-ANFIS-PSO model has high convergence speed and accuracy of results, and can be used to evaluate the technical capability of enterprises with high efficiency and high accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Analytic hierarchy process

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Big Five Personality Prediction Based on Pre-training Language Model and Sentiment Knowledge Base 6

Big Five Personality Prediction Based on Pre-training Langua...

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6th International Conference on computer Information Science and application Technology, CISAT 2023

作者： Lin, Hao Li, Xiaolei Tianjin University of Technology School of Computer Science and Engineering Tianjin300191 China College of Data Science and Application Inner Mongolia University of Technology Hohhot010080 China

ISBN: (纸本)9781510668546

Machine learning-based personality prediction methods have become the mainstream prediction method. But existing Big Five personality prediction methods based on user-generated text rely too much on pre-trained language models to ignore the sentiment information. To tackle these issues, we propose a novel Big Five personality prediction method based on pre-trained language models and SenticNet6, which is a new sentiment knowledge base. The correlation analysis and ablation experiment shows that SenticNet6 can be used for Big Five personality prediction tasks. The experiment results indicate that our proposed method improves the state-of-art results for each Big Five personality trait by 9.89%, 9.39%, 2.99%, 3.01%, and 4.28% on Essays dataset, respectively. © 2023 SPIE.

关键词： Forecasting

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