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Analysis on User's Attitude Towards Content Creation Using Artificial intelligence in Social Media 3

Analysis on User's Attitude Towards Content Creation Using A...

引用

3rd international conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Anandaputra, Gregorius Valentino Yungistira, Gianco Armando Nicholas, Oliver Mailangkay, Adele B L School of Information Systems Bina Nusantara University Information Systems Department Jakarta Indonesia

ISBN: (纸本)9798350367492

In the digital era, technology, especially Artificial intelligence (AI), has significantly transformed the creative industry, particularly in content creation. AI enhances efficiency, accelerates production processes, and diversifies creativity in multimedia content development. However, understanding the attitudes of industry practitioners and consumers towards AI adoption in content creation is crucial. This study aims to investigate these attitudes and perceptions using the technology Acceptance Model (TAM). The research focuses on key factors such as perceived usefulness, perceived ease of use, and their impact on attitudes toward AI-driven content creation. A comprehensive survey was conducted among industry practitioners and consumers to gather insights into their perspectives, concerns, and expectations regarding AI integration in creative practices. The findings indicate a generally positive perception of AI's usefulness in content creation, although concerns about authenticity and control persist. This study provides valuable insights for industry practitioners, decision-makers, and researchers, offering guidance on developing AI applications that are responsive to audience needs and expectations while addressing ethical, safety, and quality considerations. The results underscore the importance of fostering a balanced approach to AI adoption in content creation, ensuring it complements rather than replaces human creativity. © 2024 IEEE.

关键词： Content Creation Generative AI technology Acceptance Model

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Control Design of Smart Home Bookshelf 3

Control Design of Smart Home Bookshelf

引用

3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Liu, Xin Dalian Neusoft University of Information School of Intelligence & Electronic Engineering Dalian China

ISBN: (纸本)9781665490788

With the development of the Internet of Things and artificial intelligence, smart home has also entered an era of rapid development. Although many publications are widely accepted in the form of e-books and paperless office is increasingly popular, there are still many people who like to read or collect paper books. If there are a large number of books at home, most of them are easily forgotten on the shelf, and it is very inconvenient to access and search, especially for many books or materials that have not been electronic in the past, and it becomes very difficult to find them over time. This design uses OpenCV text recognition technology to realize the recognition of book information, uses the electric slide to complete the access of books at high places, uses the method of combination of bookcase to facilitate the intelligent expansion and reduction of bookshelves, and the client program carries in-depth intelligent applications, which greatly facilitates the use of users. © 2023 IEEE.

关键词： Automation

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Artificial intelligence-Powered Internet of Things for Farming and Plant Research 3

Artificial Intelligence-Powered Internet of Things for Farmi...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Padma, A. Suresh, P. Narsimlu, G. Amarnath, M. Sreedhar, B.R. Chaitanya Bharathi Institute of Technology Department of Mathematics India

ISBN: (纸本)9798331509675

The wearable fiber optic sensors for plants to monitor microenvironment and growth wearable fiber optic plant sensors for microclimate and growth monitoring. The plant agricultural sectors are facing challenges because to population expansion and climate ***-powered computer vision-based plant growth monitoring system the goal of this research project is to use computer vision to create an AI-based plant growth monitoring system. The technology will allow for automatic and real-time evaluation of plant growth and health by utilizing computer vision algorithms and artificial intelligence approaches. Conventional techniques for tracking plant growth require a lot of work and time. By employing image processing techniques to analyze plant photos and extract pertinent features leaf area, plant height, and width, the suggested solution will overcome these drawbacks. Using the collected information, machine learning methods will be used to train models that can identify patterns and forecast plant development. The system will be made to adapt to various plant species and environmental circumstances. This AI-based plant growth monitoring system will help farmers, researchers, and plant enthusiasts by offering precise and timely insights into plant health and growth. This will allow them to make well-informed decisions about plant care and optimize growth conditions. By providing an economical, scalable, and effective system with numerous applications in horticulture, agriculture, and environmental research, this research project seeks to transform plant growth monitoring. © 2025 IEEE.

关键词： Smart agriculture

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Comparative Analysis of LSTM and Random Forest Algorithms for Sentiment Classification in Movie Reviews 3

Comparative Analysis of LSTM and Random Forest Algorithms fo...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Purohit, Shardha Rajput, Aarfa Vats, Satvik Mudgal, Rusha Shah, Owais Ahmad Verma, Aditya Noida International University School of Journalism & Mass Communication Gautam Budh Nagar India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India Amity University Amity School of Communication Manesar Gurugram India K. R. Mangalam University School of Engineering & Technology Gurugram India

ISBN: (纸本)9798350375190

This study conducts sentiment analysis on 50,000 movie reviews, comparing the traditional Random Forest classifier with a Long Short-Term Memory (LSTM) network. The Random Forest achieved robust metrics across accuracy, precision, recall, and F1-score (0.85), while the LSTM excelled in capturing the complex language patterns inherent in the reviews through its sequence-based processing. This study has refined the data by removing irrelevant characters and employing tokenization and lemmatization to enhance model training. Despite its higher computational requirements, the LSTM showed potential in detailed sentiment analysis. Future directions include exploring other neural architectures, enlarging the dataset, and practical applications to improve model efficacy. The study highlights key insights into sentiment analysis methodologies and their implications for both academic and practical realms. © 2024 IEEE.

关键词： Long short-term memory

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Computer Artificial intelligence IT technology Data Transmission Center Construction System Research 3

Computer Artificial Intelligence IT Technology Data Transmis...

引用

3rd IEEE international conference on Power, Electronics and Computer applications, ICPECA 2023

作者： Rui, Yuan Chengdu Neusoft University School of Computer Science and Software Chengdu China

ISBN: (纸本)9781665472784

Based on computer artificial intelligence, this paper proposes a reliability analysis algorithm model for multi-attribute data transmission based on improved cuckoo search algorithm. In this paper, the reliability problem of multi-attribute data transmission is transformed into a multi-objective combinatorial optimization problem of multi-attribute decision making by constructing the reliability quality evaluation system of multi-attribute data transmission and the mathematical model of data transmission reliability analysis. Then we study the probability distribution of node reliability and its transmission path reliability. Finally, the experimental results show that the algorithm has the advantages of short response time, low iteration times and low error when analyzing the reliability of network multi-attribute data transmission. © 2023 IEEE.

关键词： Data transfer

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Research on Network Information Security Service Model Based on User Requirements under Artificial intelligence technology 3

Research on Network Information Security Service Model Based...

引用

3rd IEEE international conference on Power, Electronics and Computer applications, ICPECA 2023

作者： Li, Xu Sichuan Technology & Business College School of Intelligent Manufacturing and Information Engineering Chengdu China

ISBN: (纸本)9781665472784

This paper proposes a general network security framework based on artificial intelligence technology. Then the relationship between security objectives, security boundaries, security system elements, security services and security risk assessment are described. The modeling methods of security objectives, security boundaries and security system elements are given by using the power and universality of Unified Modeling language (UML). On the basis of building the network scenario, this paper sets up the association rules of network information security event detection and constructs the information security risk measurement model from the three perspectives of network database security vulnerability, data islanding risk and network security protection ability. Finally, a typical network example is given to analyze the application of the above model and algorithm in network security evaluation and optimal active defense. The analysis results show that the model and method presented in this paper are feasible and effective. © 2023 IEEE.

关键词： Network security

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Compact Microstrip-Fed Antenna with Simple Layout for 5G N79 Band applications 3

Compact Microstrip-Fed Antenna with Simple Layout for 5G N79...

引用

3rd IEEE international conference on Computer Communication and Artificial intelligence, CCAI 2023

作者： Sun, Honglei No. 36 Research Institute of Cetc Jiaxing314033 China

ISBN: (纸本)9798350335262

A novel microstrip-fed patch antenna for the fifth generation (5G) mobile communication N79 band is proposed and verified. The proposed antenna is printed on one front and back surface of the printed circuit board (PCB) for simple layout. The measured relative bandwidth reaches to 12.8% (4.4-5 GHz) and the entire size of the antenna is 30 × 26 mm2 only. The reflection sensitivities with different interfering objects are also compared. The radiation pattern is nearly omnidirectional and having a power handing capability of 43.5 dBm, which is suitable for 5G mobile base station applications. © 2023 IEEE.

关键词： Microstrip antennas

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Automatic Cooperative robot Intelligent Production Line 3

Automatic Cooperative Robot Intelligent Production Line

引用

2023 3rd international conference on Artificial intelligence and Industrial technology applications, AIITA 2023

作者： Feng, Wenxuan Xiao, Junxiang Sun, Huajie School of Automation Wuhan University of Technology Hubei430070 China

Due to the diversification of consumer demand, "fast iteration, less batch, and flexible delivery"has become an inevitable choice for enterprises to have market competitiveness. In order to survive in the market competition, it is necessary to transform the traditional manufacturing line. This paper mainly puts forward and introduces a set of reconstruction schemes. The revamp of the production line will incorporate new collaborative robots. The TM5-900 robot produced by Daming was used in the scheme. Compared with the artificial situation, the man-machine cooperative production line improves the production efficiency of products, improves the balance rate, and reduces the smoothness index, which makes resource allocation more reasonable and production more stable. In addition, the man-machine cooperative scheme can realize the rapid change of product types to meet customer needs. The robot follows the operating frequency of humans so that humans can achieve the best comfort in the operation. © Published under licence by IOP Publishing Ltd.

关键词： Production efficiency

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Behind the Scenes: An Explainable Artificial intelligence (XAI) on the Service Classification of the 5G/B5G Network 3

Behind the Scenes: An Explainable Artificial Intelligence (X...

引用

3rd international conference on Digital Transformation and applications, ICDXA 2024

作者： Allias, Noormadinah Kadir, Diyana Ab Abdullahi, Akibu Mahmoud Ismail, Shahrinaz Tunku Abdul Rahman University of Management and Technology Faculty of Computing and Information Technology Kuala Lumpur Malaysia Computer Engineering Technology Universiti Kuala Lumpur- Malaysia Institute of Information Technology Kuala Lumpur Malaysia School of Computing and Informatics Albukhary International University Kedah Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798350373424

Fifth generation and beyond (5G/B5G) is part of the next generation of mobile technology, which is expected to offer more capacity and faster speeds than the previous generation Long-Term Evolution (LTE) network. These features enable 5G/B5G to offer users a wide range of services, including smart cities, entertainment and multimedia, healthcare and mission-critical applications that benefit the entire economy and communities. However, due to growing demand, telecom service providers need to provide better Quality of service (QoS) on their networks to meet user expectations. Therefore, it is necessary to implement service classification that enables service providers to select the right network slices for each service to improve network QoS. Previous studies have predicted the classification of 5G/B5G services using traditional machine learning algorithms such as random forest and decision tree, achieving good accuracy. However, prediction based on black-box machine learning models was not transparent enough, so mobile service providers could not understand the reliability and interpretation of the results. Therefore, this article aims to model the system performance of 5G Key Performance Indicators (KPI) and extend the experiment to Explainable Artificial intelligence (XAI) by using the Explainable AI to look behind the scenes of the chosen black-box models for service classification of 5G/B5G networks, as this is crucial for telecom service providers to make critical investment decisions around customer and employee experience. The results from the experiments show that the random forest has the highest confidence towards class Label 3 with the probability of 35 percent. © 2024 IEEE.

关键词： Decision trees

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A Novel Mission Planning Method for Multi-robot Collaborative Area Coverage 17th

A Novel Mission Planning Method for Multi-robot Collaborativ...

引用

17th international conference on Intelligent robotics and applications

作者： Liu, Bei Tao, Cancan She, Wanqiang HiWing Gen Aviat Equipment Co Ltd Beijing 100074 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9789819607884;9789819607891

This article proposes a novel two-layer mission planning structure for multi-robot collaborative area coverage mission planning: (1) First, an improved co-evolving particle swarm optimization algorithm is utilized to resolve the virtual sensor configuration problem, obtaining a sensor configuration scheme that can fully cover the searchable mission area;(2) Using an improved K-means algorithm to cluster and partition the sensor configuration points, obtaining each sub-area and the search path within each sub-area. The simulation results confirm the effectiveness of the method proposed in this article.

关键词： multi-robot area coverage mission planning sensor configuration improved K-means

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