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Sustainable Expert Systems (ICSES), International Conference on

作者： V.S. Saranya Garimidi Subbarao Dega Balakotaiah Maloth Bhavsingh K. Suresh Babu Srinivasa Rao Dhanikonda Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chennai Department o Computer Science and Engineering (AIDS) Pace Institute of Technology and Sciences Department of Computer Science and Engineering Vignan's Founadation for Science Technology & Research (Deemed to be University) Department of Computer Science and Engineering Ashok: Womens Engineering College Kurnool Andhra Pradesh Department of Computer Science and Engineering Narasaraopeta Engineering College(Autonomous) Narasaraopet A.P Department of Artificial Intelligence and Data Science Faculty of Science and Technology (IcfaiTech) ICFAI Foundation for Higher Education (Deemed to Be University) Hyderabad Telangana India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Thisstudy introduces the DeepStreamNet model, an advanced framework for enhancing real-time traffic management in urban environments using adaptive IoT and sophisticated big data analytics. Central to our approach is the integration of convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) units, which synergize with IoT devices to facilitate dynamic adaptation to fluctuating traffic conditions. The model excels in operational performance, achieving a notable accuracy of 94.7% in congestion prediction with an exceptionally low latency of only 45 ms per decision cycle and the capability to process up to 50,000 data points per second. These technical achievements have marked significant improvements over traditional traffic management systems, enhancing traffic flow efficiency and reducing congestion effectively. The results underscore the transformative potential of the DeepStreamNet model in urban traffic management and public safety, offering actionable insights for intelligent transportation systems and setting the stage for more informed urban planning. Looking forward, we suggest extending the application of our model to areas such as logistics and broader smart city initiatives, highlighting its adaptability and broad utility in various urban contexts

关键词： Adaptation models Analytical models Accuracy Smart cities Urban planning Data models Real-time systems Internet of Things Optimization Context modeling

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Machine Learning for Asthma Prediction: Analyzing Health Data for Early Detection

Machine Learning for Asthma Prediction: Analyzing Health Dat...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： TS. Sundresan Perumal Banu Priya.S Kumutha Duraisamy Faculty of Science and Technology Universiti Sains Islam Malaysia Malaysia Department of Computer Science and Engineering Jeppiaar Institute of Technology Chennai India

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

Asthma is a persistent respiratory condition that significantly affects people worldwide, making the prediction of asthma flare-ups crucial for enhancing patient care and optimizing healthcare resources. Despite progress in the field of machine learning, current predictive models often face challenges due to their dependence on historical clinical data alone. This paper evaluates existing asthma prediction models and introduces a new approach utilizing Bernoulli distribution and logistic regression to enhance prediction accuracy. Current models fre- quently depend on clinical variables such as coexisting conditions, past exacerbations, and healthcare engagement. Widely used, methodologies include decision trees, random forests, and logistic regression; however, these models generally perform poorly when evaluated on varied real-world datasets. A notable drawback is their inability to factor in environmental influences, such as air quality, weather patterns, and pollen counts, all of which play a role in asthma exacerbations. In future research, we will further investigate and refine techniques to better integrate a variety of data sources, aiming to make asthma prediction models more robust, dependable, and suitable for diverse populations.

关键词： Logistic regression Adaptation models Accuracy Atmospheric modeling Machine learning Medical services Predictive models Real-time systems Random forests Asthma

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Automatic Clustering of Hyperspectral Images Using Quantum Reptile Search Algorithm

Automatic Clustering of Hyperspectral Images Using Quantum ...

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International Conference on Business Intelligence and Information Technology, BIIT 2022

作者： Dutta, Tulika Bhattacharyya, Siddhartha Panigrahi, Bijaya Ketan Hassanien, Aboul Ella Department of Computer Science and Engineering Presidency University Bangalore India Rajnagar Mahavidyalaya Rajnagar Birbhum India Algebra University College Zagreb Croatia Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India Faculty of Computers and Information Cairo University Giza Egypt

ISBN: (纸本)9789819934157

Hyperspectral images are rich in spectral and spatial content, along with the presence of redundant data. Ground truth images are also scarcely available. Hence, automatic cluster detection in hyperspectral images is a tough task. Qubit and qutrit versions of the Reptile Search Algorithm are proposed to automatically cluster hyperspectral images. Since the Reptile Search Algorithm contains too many parameters, the number of parameters is reduced in the modified algorithm along with a balancing factor between the exploration and exploitation phases. A new cluster validity index called the Correlation-Based Cluster Validity Index is employed as the fitness function. The quantum versions produce better-optimized results and prevent the algorithm from getting stuck in local optima. The results of the proposed algorithms are compared with the classical Reptile Search algorithm and the modified Reptile Search algorithm. Different statistical tests like the mean, standard deviation, and the One-Way ANOVA test are conducted to compare the results impartially. Different subjective scores are used to adjudge the optimality of the produced clusters. The Qutrit version of the Reptile Search Algorithm is found to outperform others in respect of performance and time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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Enhanced Speech Emotion and Gender Recognition Using Hybrid CNN-LSTM Models

Enhanced Speech Emotion and Gender Recognition Using Hybrid ...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： S Priyadharshini G. Naveen Sundar D. Narmadha Senthil Kumar Thangavel Adeyemi Abel Ajibesin Selvanayaki Kolandapalayam Shanmugam Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Computer Science and Engineering Amrita School of Computing Coimbatore India Department of Information Technology Faculty of Informatics and Design Cape Peninsula University of Technology South Africa Department of Mathematics and Computer Science Ashland University USA

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The current paper proposes a new approach for peripheral speech emotion analysis and gender estimation incorporating the best machine learning architectures such as CNNs and LSTMs. Its correct depiction of emotions and the variation of the gendered speech to indicate manifold signal-to-noise ratio make the approach accommodate the difficulty inherent in recognizing emotions from the recording of voices as well as predicting the gender of a speaker. It is then able to ally with preprocessing and collection of a vast range of different speech samples, feature extraction of pitch, tone and spectral data. These features serve as input to the CNNs and LSTMs: LSTMs work well at temporal regular features and the CNNs work well in feature extraction by location (spatio feature). The approach is tested on the RAVDESS and IEMOCAP datasets and establishes a near perfect match to prior approaches with reference to recognition accuracy of emotion analysis and gender prediction. Thus, applying the identified dual method approach, which could be described by such characteristics as highly accurate data pre-preprocessing, clear indication of the features of interest, a different CNN-LSTM model joint training, it offers a reasonably good platform to gain certain insights into such characteristics of the speech as our experiment demonstrates. This work offers satisfactory configurations on concerns such as human computer relation, customer relation and mental health surveillance to suggest that other applications could be achieved in future.

关键词： Training Emotion recognition Accuracy Computational modeling Speech recognition Speech enhancement Predictive models Feature extraction Data models Convolutional neural networks

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A comparative study on bridge road works methods for flood tide management in Agats-Suator project 2

A comparative study on bridge road works methods for flood t...

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2nd International Conference on Disaster and Management 2020, ICDM 2020

作者： Dermawan, H. Palamba, W. Sebayang, E. Civil Engineering Department Faculty of Computer Science and Engineering Universitas Kristen Krida Wacana Indonesia

Currently, flood tide affects the accessibility of Agats-Suator Bridge Road. Therefore, local governments are making efforts to improve its infrastructure, one of which is in the bridge road construction previously used wood conventionally replaced with better concrete. This study examines the Agats-Suator Bridge Road Project, Asmat, Papua that compares the precast concrete system and conventional concrete system for flood tide management, in which workers were employed and materials were purchased from Surabaya. The purpose of this research is to calculate efficient scheduling conditions with a limited workforce on conventional and precast concrete implementation systems. The research method used in this research is a non-experimental quantitative method with comparative studies. Human resource allocation makes the workers scheduling more efficient by applying the principle of limited resource allocation. The research results show that the precast concrete system reach ideal conditions at rmax = 30 people with 18 weeks duration. Meanwhile, conventional concrete systems reaches ideal conditions at rmax = 89 people with 22 weeks duration. The result of resource allocation suggests that implementing a precast concrete system is more effective than implementing a conventional concrete system. The results of this study also function as a reference in selecting the concrete construction implementation systems for flood tide management in Agats-Suator Bridge Road Project. © Published under licence by IOP Publishing Ltd.

关键词： Roads and streets

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Deterministic Networking (DetNet): Architecture, Protocols, and Advanced Applications

Deterministic Networking (DetNet): Architecture, Protocols, ...

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International Conference on Mechatronics (ICOM)

作者： Zeinab E. Ahmed Aisha A. Hashim Rashid A. Saeed Mamoon M. Saeed Department of Computer Engineering University of Gezira Sudan Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

This paper provides a thorough overview of Deterministic Networking (DetN et), focusing on establishing predictable data routes in Layer 2 and Layer 3 networks to address network issues like congestion, latency, and packet loss. It discusses DetNet's principles, architecture, and Operations, Administration, and Maintenance (OAM) protocols, crucial for fault detection and network monitoring. DetN et ensures bounded latency and minimal data loss, catering to industries' need for reliable flows over multi-hop paths. It integrates Time Sensitive Networking (TSN) and MPLS, using Resource Allocation (RA), Service Protection (SP), and Explicit Routing (ER) as core technologies, within a structured architecture of controller, application, and network planes. OAM is pivotal for efficient DetN et management, offering tools for fault detection, continuity checks, and maintenance activities to maintain Service Level Objectives (SLOs). The paper delves into advanced DetN et applications, highlighting enhanced protocols, health care frameworks, service function chain management, and industrial networking solutions, emphasizing their potential to improve reliability and network efficiency across diverse applications.

关键词： Industries Multiprotocol label switching Job shop scheduling Service function chaining Fault detection Packet loss Medical services

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Designing Avatar System and Integrate to the Metaverse

Designing Avatar System and Integrate to the Metaverse

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International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Suebphong Noisri Pisut Wisessing Kunanont Srisupakwong Halim Budi Santoso Lunchakorn Wittisittikulkij Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand Department of Electrical Engineering Chulalongkorn University Bangkok Thailand Department of Information Systems Faculty of Information Technology Universitas Kristen Duta Wacana Yogyakarta Indonesia

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

Digital representations of users in virtual environments are known as avatars in the metaverse. They serve as the main vehicle for self-expression and identification in these digital places, enabling people to connect, socialize, and travel throughout the metaverse. Avatars' physical characteristics can be altered, such as their body type, skin tone, facial features, hairstyle, attire, and accessories. Design, development, and integration activities are usually combined for the avatar system to provide a smooth and interesting user experience. However, prior studies lack on how we should be able to customize the Avatar systems and integrate them into the Metaverse systems. This research tries to highlight and propose a method that might be able to deploy the avatar creation with a more straightforward user interface and apply it to the Metaverse environment. Our study provides a practical contribution to how to create a more straightforward avatar customization system and integrate it into the Metaverse Environment.

关键词： Metaverse Avatars Scalability Clothing Systems architecture User interfaces User experience

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Design and build a head circumference measurement system for toddlers 7

Design and build a head circumference measurement system for...

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7th International Conference on engineering, Technology, and Industrial Application, ICETIA 2020

作者： Martono, Kurniawan Teguh Nurhayati, Oky Dwi Indrasto, Erwan Yudi Adhy, Satriyo Computer Engineering Department-Engineering Faculty Indonesia Informatics Department-Science and Mathematics Faculty Diponegoro University Tembalang Semarang Indonesia

Growth and development are events that every living thing will experience. These events are two events, namely growth, and development. These two events are related to one another, where growth refers to a change in the shape of the body, or cell size and effect change an organ or limb's function in its operation. Every parent must consider child development because this will significantly determine and influence how the child develops in the future. Measurement of height, weight, or head circumference is carried out at the Posyandu to aim that the development of children under five in an area can be monitored and make it easier to determine policies. The results of this measurement will later be recorded on a card called the "Kartu Menuju Sehat"(KMS). Technological developments bring about considerable changes in the world of health. This paper discusses the design of a head circumference monitoring system. The use of a rotary sensor is an option in designing a head circumference gauge. The measurement results using a rotary sensor show that the measurement accuracy is 100%. Testing the system with a black box shows that 100% of the structure built is acceptable and according to the design scenario. © Published under licence by IOP Publishing Ltd.

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Path Selection Optimization Algorithms for Mobile Agent Based on Push-All-Data Strategy

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2025年第10期19卷 112-128页

作者： Alzyoud, Faisal Tarawneh, Monther Al-Shrouf, Faiz Almaghthawi, Ahmed Alrehaili, Meaad Kanaker, Hasan Department of Computer Science Isra University Amman Jordan Department of Information Technology College of Information Technology and Communications Tafila Technical University Tafila Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman Jordan Department of Computer Science College of Science & Art at Mahayil King Khalid University Abha62529 Saudi Arabia Department of Computer Sciences and Artificial Intelligence Collège of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Information Security Faculty of Information Technology Petra University Amman Jordan

With the advent of 5G and 6G technologies and the growing ubiquity of the Internet, the Mobile Agent (MA) paradigm is increasingly seen as a promising alternative to the conventional client-server model. MAs, which are software entities capable of moving and processing data across different systems, offer potential efficiencies in data management. However, their operation in dynamic and mobile environments can lead to challenges, such as incomplete or delayed tasks. This study addresses these issues by focusing on reducing the relocation time of MAs. A numerical procedure and a streamlining strategy were developed to expedite the transfer of an agent from the source to the target hub. Utilizing the itinerary design pattern and the Ant Colony Optimization (ACO) algorithm, implemented via the Java Agent Development Framework (JADE), this study sought the most efficient path for the MA. The proposed algorithm demonstrated a significant improvement, selecting the optimal path in just 271.511 seconds. This performance represents a substantial enhancement over previous approaches using the master-slave design pattern with either the Genetic Algorithm (GA) or the Node Compression Algorithm (NCA). The implications of this improvement are far-reaching, potentially enhancing the efficiency and reliability of data management systems in a variety of applications. © 2025 by the authors of this article. Published under CC-BY.

关键词： Information management

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Centre Stage: Centricity-based Audio-Visual Temporal Action Detection

arXiv

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arXiv 2023年

作者： Wang, Hanyuan Mirmehdi, Majid Damen, Dima Perrett, Toby Department of Computer Science Faculty of Engineering University of Bristol Bristol United Kingdom

Previous one-stage action detection approaches have modelled temporal dependencies using only the visual modality. In this paper, we explore different strategies to incorporate the audio modality, using multi-scale cross-attention to fuse the two modalities. We also demonstrate the correlation between the distance from the timestep to the action centre and the accuracy of the predicted boundaries. Thus, we propose a novel network head to estimate the closeness of timesteps to the action centre, which we call the centricity score. This leads to increased confidence for proposals that exhibit more precise boundaries. Our method can be integrated with other one-stage anchor-free architectures and we demonstrate this on three recent baselines on the EPIC-Kitchens- 100 action detection benchmark where we achieve state-of-the-art performance. Detailed ablation studies showcase the benefits of fusing audio and our proposed centricity scores. Code and models for our proposed method are publicly available at https: //***/hanielwang/***. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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