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International conference on e-health networking, Applications and Services (HealthCom)

作者： Anne Danielle V. Malbog Ace Jhoelhee M. Irinco Regolo Jerald L. Morales Leah T. Salas Roselyn A. Maaño Rodrigo C. Belleza Joanna Fe B. Panganiban College of Computing and Multimedia Studies Manuel S. Enverga University Foundation Quezon Philippines Office of the Student Affairs and Services Manuel S. Enverga University Foundation Quezon Philippines

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350555

Eye movements provide insights into attentiveness and focus, which are crucial for determining fixation. This study develops a model for assessing attentiveness in children with autism spectrum disorder (ASD) using an eye-tracking system. The study aims to aid trained specialists in assessing attention deficiency to apply necessary mental health care to children. An eye tracker was developed to plot the gaze of thirty-four children aged 3–12 using the dlib Gaze Tracking library. Data augmentation techniques such as rotation, flipping, and filling were applied to enhance the training dataset. The model was implemented in an eye-tracker system as a proof-of-concept for the viability of early screening and intervention solution in assessing attentive behavior in children with ASD. The implemented Convolutional Neural Networks (CNN) with the K-means model resulted in 96% accuracy and 94% recall, indicating reliability in predicting attentiveness.

关键词： Training Pediatrics Visualization Autism Gaze tracking Mental health Predictive models Libraries Convolutional neural networks Reliability

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Guest Editorial: Softwarized networking for Next Generation Industrial Cyber-Physical Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第8期17卷 5506-5510页

作者： Garg, Sahil Wang, Honggang Granelli, Fabrizio Li, Hongwei Univ Quebec Ecole Technol Super Montreal PQ H3C 1K3 Canada Univ Massachusetts Dartmouth N Dartmouth MA 02747 USA Univ Trento I-38122 Trento Italy Univ Elect Sci & Technol China Chengdu 610054 Peoples R China

The papers in this special section focus on softwarized networking for next generation industrial cyber-physical systems (CPSs). With the emergence of embedded and ubiquitous cyberphysical applications, the rationale of blending the physical and the virtual worlds has become ever promising. These papers examine several topics that are recently concerned in the community, including the software defined architectures and implementations, advanced machine learning and data analytics solutions, blockchain-based network services and applications, network function allocation, dependable and trustable solutions, energy efficient networks and services, and other enabling technologies for integrating softwarized networks into CPSs.

关键词： Special issues and sections Cyber-physical systems Informatics Data analysis Deep learning Resource management Industrial Internet of Things Computer architecture Blockchain Real-time systems Cloud computing

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Comprehensive Analysis of Arabic Sentiment Analysis using Lexicon and Machine Learning based Approaches

Comprehensive Analysis of Arabic Sentiment Analysis using Le...

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Network, multimedia and Information Technology (NMITCON) International conference on

作者： M. Maheswari Ammar Hameed Shnain Ayesha Siddiqua H C Nagaraj N. Shilpa Department of Computational Intelligence School of Computing SRM Institue of Science and Technology Kattankulathur India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of ECE Nitte Meenakshi Institute of Technology Bengaluru India Department of ECE School of Engineering SR University Warangal India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

Arabic sentiment analysis (ASA) is a vital field in Natural Language Processing (NLP) that utilizes Machine Learning (ML) techniques to understand the complex emotional tones that are present in Arabic text. This survey discovers the use of ML in Arabic sentiment analysis, which aims to implement various methodologies for sentiment classification. The goal is to develop a robust model capable of translating nuanced sentiments expressed in different dialects and intricate linguistic structures. The methodology involves creating a labeled dataset, using preprocessing techniques, and utilizing machine learning algorithms such as linear classifiers and deep learning models. By extracting features, training the model, and evaluating its performance, the methodology improves the accuracy of sentiment evaluations. The results of this study highlight the effectiveness of machine learning models in accurately categorizing sentiments in Arabic text, as demonstrated by performance metrics such as precision, recall, and accuracy.

关键词： Surveys Training Support vector machines Measurement Sentiment analysis Accuracy Social networking (online) Reviews Feature extraction Standards

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Harmonizing Music Recommendation: A Unified Approach with Hybrid, Collaborative, Content-Based, and Spotipy Modules

Harmonizing Music Recommendation: A Unified Approach with Hy...

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Network, multimedia and Information Technology (NMITCON) International conference on

作者： M Asmitha C.R. Kavitha Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

Recommendation systems play a crucial role in enhancing the music streaming experience, facilitating music discovery, and fostering user loyalty on platforms like Spotify. With the exponential growth of digital music platforms like Spotify, understanding and leveraging music consumption patterns has become essential for both users and platform providers. Recommendation systems are now seen multiple platform such as movie, social media etc. This study mainly aims an in-depth analysis of preferences among Spotify users, coupled with the development of a recommendation system aimed at enhancing user experience and engagement. Furthermore the development of a robust recommendation system tailored to Spotify’s platform, leveraging the identified patterns to provide personalized music recommendations to users. The recommendation system incorporates collaborative filtering, content-based filtering, and hybrid approaches to enhance recommendation accuracy and relevance. Through extensive experimentation and evaluation using real-world Spotify data, demonstrate the effectiveness and performance of the developed recommendation system. The system performance will be assessed based on accuracy in recommending, prediction of streams and popularity using RMSE, MAE, F1-score, Precision, Recall, Accuracy.

关键词： Accuracy Filtering Social networking (online) Collaborative filtering System performance User experience Noise measurement Recommender systems Streams Optimization

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Mobile AR Streaming through Virtualized Edge Intelligence

Mobile AR Streaming through Virtualized Edge Intelligence

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IEEE conference on Standards for Communications and networking (CSCN)

作者： Fotis Foukalas Asterios Papaioannou Christos Tsakos Cognitive Innovations Athens Greece Dept. Informatics and Telecommunications University of Thessaly Lamia Greece

ISBN: (数字)9798331507428

ISBN: (纸本)9798331507435

While mobile video streaming is well specified and developed within the last decade, where 3G first appeared and then 4G and now 5G were followed, we now experience a new sort of multimedia application known as augmented reality (AR). AR is considered one of the major technology for the future mobile Internet known as metaverse. To this direction, it is important to deal with the performance of AR content transmission over mobile networks such as 5G and beyond. This paper provides an AR streaming application that is enabled at the mobile edge through Artificial Intelligence. The proposed solution consists of the streaming protocol application and the mobile edge intelligence that is provided by using reinforcement learning. We present both aspects of our solution in this work below and provide results in a real tested environment with a number of mobile users. An AR application is also used to test the performance of the streaming application that depicts 3D objects on top of Google maps. The measured latency is lower than the baseline solution and thus, the edge intelligence solution provided the expected benefit for future mobile AR applications.

关键词： Protocols Three-dimensional displays 5G mobile communication Web services Computer architecture Servers Low latency communication Standards Edge computing Testing

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Unmasking Digital Deceptions: A Comprehensive Survey of Synthetic Reality Analysis Across multimedia Domains

Unmasking Digital Deceptions: A Comprehensive Survey of Synt...

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Electronic Systems and Intelligent computing (ICESIC), International conference on

作者： Sneha Chaudhary Komal Chaurasiya Suthir Sriram Ravikumar S Nivethitha V Thangavel M Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology College of Information and Technology United Arab Emirates University

ISBN: (数字)9798331522988

ISBN: (纸本)9798331522995

The general accessibility of social networking sites like Facebook, Myspace and TikTok has transformed the way information is communicated, but it has also made it simpler to spread misleading information, thanks to cutting-edge technologies like deepfakes. The use of artificial intelligence in deepfake technology produces material that is remarkably life- like but fake, making it difficult to identify and remove fraudulent content. The evolution of deepfake technology is reviewed in this study, starting with early breakthroughs like the Video Rewrite Program and continuing with more current developments like the Synthesizing Obama and Face2Face projects. We provide a comprehensive analysis of the state-of-the-art detection strategies, namely Region-based CNNs (RCNNs), Conventional Neural Networks (CNNs), and hybrid approaches that combine various deep learning techniques. Though these methods have advanced, there are still issues with accuracy, integration complexity, and adaptability to new deepfake techniques. This paper suggests a novel approach that integrates image, video, and audio analysis into a single detection framework in order to overcome these difficulties. The new approach is directed towards improvement of detection accuracy and the lowering of the false alarm using advanced and deep learning engines along with the real time processing requirements. Early results indicate that the detection capabilities have significantly improved compared to existing solutions operating in real time environment while having less latency and higher recall and precision rates. This method is more effective for deepfake detection and at the same time helps in augmenting the comprehensiveness and efficiency of the system there by making it suitable for wider uses. The study emphasizes the presence of the need for the evolution of static approaches towards the effective defection of sophisticated false information and the justification of new possibilities in the fight a

关键词： Deep learning Surveys Deepfakes Technological innovation Accuracy Video on demand Social networking (online) Real-time systems Web sites Protection

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Analysis of inter-Mean-Opinion-Score (iMOS) and QoS metrics for 5G Voice over LTE (VoLTE) and Voice over New Radio (VoNR) services over IP-multimedia-Subsystem (IMS) in 5G mobile networks

Analysis of inter-Mean-Opinion-Score (iMOS) and QoS metrics ...

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International conference on Advanced Communication Technologies and networking (CommNet)

作者： Jussif J. Abularach Arnez Caio B. Bezerra De Souza Sidia Institute of Science and Technology Manaus Brazil

At present, mobile network operators (MNO) need to improve Quality of Service (QoS) and Quality of Experience (QoE) of voice and video services to compete with over-the-top (OTT) Voice over IP (VoIP) applications. For an MNO to be able to provide HD voice and video calls, is essential to use a dedicated IP multimedia Subsystem (IMS) network. The contribution of this paper is the analysis of measured data collected from real-time testbeds related to the fifth generation (5G) mobile network and then, computing the inter-Mean-Opinion-Score (iMOS) and QoS metrics for both 5G Voice over LTE (VoLTE) and Voice over New Radio (VoNR) services over IMS. Thus, there are evaluated QoS metrics throughout the communication stages among the User Equipment (UE) for the 5G Stand-Alone (SA) and 5G Non-Stand-Alone (NSA) networks. The obtained results show how QoS metrics like jitter and delay impact the iMOS results. The obtained results satisfy the requirement for VoNR and 5G VoLTE which show iMOS values greater than 4 out of 5 where 5 represents the best quality. The results were obtained in a controlled environment laboratory, using specialized radio test stations with non-interference outdoor propagation signals and lower path loss since can be used as a reference for upcoming research.

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MRP System to Improve the Quality of QOS Optimization System in the Field of WMSN

MRP System to Improve the Quality of QOS Optimization System...

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Advance computing and Innovative Technologies in Engineering (ICACITE), International conference on

作者： B. Nancharaiah A.S. Sai Puneeth Theja G. Santha Meena A. Pratapa Reddy Hussein Ali Kadhim Kyhoiesh Huthaifa Alani ECE Department Usha Rama College of Engineering and Technology Telaprolu Andra Pradesh Department of ECE Sri Venkateswara University College of Engineering Tirupati Andra Pradesh Department of Mathematics PSNA College of Engineering and Technology (Autonomous) Dindigul Tamil Nadu India CSE Dept SVS Group of Institutions Hanamkonda Telangana College of Health and Medical Technology National University of Science and Technology Dhi Qar Iraq Al-Farahidi university Baghdad Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

The technologies of Named Data networking (NDN) such as multipath routing protocol and Edge Cloud computing (ECC), QoS optimization are critical to the evolution of the Internet, especially when it comes to the fast information transmission required for 6 G and other next-generation networks. This paper explores the synergistic potential of integrating NDN and ECC, aiming to enhance network utility, QoS and routing in wireless multimedia sensor networks. Our proposed framework adopts an N-Tier architecture, with NDN forming Tier 1, connecting IoT devices to Tier 2 (Edge computing), and further extending to Tier 3 (Cloud computing) via Microsoft Azure Cloud servers. Through this integration, we focus on achieving expedited information response times. We deploy an NDN-based ECC system and assess its performance using simulations and testbed experiments. We analyze at metrics including round trip time (RTT), service search time, and interest aggregation with different traffic loads. Our results show how effective it is to employ NDN in conjunction with edge computing to minimize backbone network congestion, process massive amounts of data quickly in real time, and drastically cut latency-all of which contribute to smooth user experiences.

关键词： Wireless communication Cloud computing Wireless sensor networks Quality of service Telecommunication traffic Routing Time factors

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Integrating Artery and Simu5G: A Mobile Edge computing use case for Collective Perception-based V2X safety applications 45

Integrating Artery and Simu5G: A Mobile Edge Computing use c...

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45th International conference on Telecommunications and Signal Processing (TSP)

作者： Kovacs, Gergely Attila Bokor, Laszlo Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Networked Syst & Serv Muegyet Rkp 3 H-1111 Budapest Hungary ELKH BME Cloud Applicat Res Grp Magyar Tudosok Korutja 2 H-1117 Budapest Hungary

ISBN: (纸本)9781665469487

As vehicular communications (V2X) become increasingly widespread, the study of technologies capable of supporting advanced applications, like Collective Perception (CP), gains more and more significance. Architectural improvements and new features of 5G cellular networks, including Mobile Edge computing (MEC), seem to be viable to build upon, so much in general V2X use-cases as in ones based on CP. Our contribution to the study of this field is to provide an operable extension to the well-known V2X simulation framework called Artery, where implementations of 5G elements provided by the Simu5G library can be utilized in the simulations.

关键词： NR V2X C-V2X MEC Collective Perception C-ITS

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Seeing the World in Dots: A Machine Learning Adventure in Colorblind Perception

Seeing the World in Dots: A Machine Learning Adventure in Co...

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computing, Applications and Systems (COMPAS), IEEE International conference on

作者： Shah Rafatur Rahman Md Rashedul Islam Aditya Chakrabortty Department of Computer Science and Engineering Hajee Mohammad Danesh Science and Technology University Dinajpur Bangladesh School of Information Technology Deakin University Melbourne Australia

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Color is a vital communication element, conveying the message’s meaning and differentiating the contents. Nevertheless, color vision deficit (CVD), called colorblindness, affects 8% of the global population. This impairment alters color perception, making reading and understanding the message difficult. This issue becomes increasingly significant with the expanding accessibility of multimedia content in digital environments, including web browsers, digital images, entertainment media, and social media. One of the methods of identifying CVD is the Ishihara Color-blind Test. Ishihara images consist of a red-green background and a hidden number. Color-blind persons won’t recognize the number as they cannot recognize the red and green colors. Using color glasses or contact lenses this deficiency can be overcome. The main point is that there is no cure for this deficiency. This research explores machine learning's potential to overcome this challenge. We trained a neural network to detect and classify numbers from Ishihara images, successfully "passing" the test. With an impressive 96.42% accuracy, this technology offers promising hope for bridging the communication gap for colorblind individuals.

关键词： Visualization Image recognition Accuracy Image color analysis Social networking (online) Transfer learning Robustness Pattern recognition Noise measurement Vision defects

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