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检索条件"任意字段=International Conference on Advances in Information Communication Technology and Computing"

共 82280 条记录，以下是51-60 订阅

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A Novel Interdisciplinarity Model Towards Inter-domain information Pairing 24th

A Novel Interdisciplinarity Model Towards Inter-domain Infor...

引用

24th international TRIZ Future conference

作者： Douard, Nicolas Samet, Ahmed Giakos, George Cavallucci, Denis Univ Strasbourg Inst Natl Sci Appl 24 Bd Victoire F-67000 Strasbourg France Manhattan Coll Dept Elect & Comp Engn 3825 Corlear Ave New York NY 10463 USA

ISBN: (纸本)9783031759253;9783031759239;9783031759222

This study introduces an interdisciplinary prediction framework as part of a novel approach that integrates the Inventive Design Method (IDM), Topic Modeling, and Generative AI to foster innovation across academic fields. Identifying interdisciplinary connections is essential for solving complex, multi-domain problems. Our research uses a supervised machine learning classifier to identify interdisciplinary documents within the Semantic Scholar corpus, extracting latent insights. The Text Convolutional Neural Network model performed best, achieving an F1 score of 0.80. We find that approximately 25% of human knowledge is interdisciplinary. This framework helps create comprehensive knowledge maps across multiple domains, promoting innovation through effective cross-domain knowledge transfer.

关键词： Interdisciplinary mapping cross-domain transfer biomimicry literature analysis topic models language models

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advances in Big Data and Data Mining: Techniques and Applications in Data Fusion for Enhanced Insights and Decision-Making

Advances in Big Data and Data Mining: Techniques and Applica...

引用

2025 IEEE international conference on Computational, communication and information technology, ICCCIT 2025

作者： Goyal, Himanshu Rai Shrivastava, Anurag Nagpal, Amandeep Reddy, R. Akhilesh Yadav, Kanchan Revathi, R. Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Lovely Professional University Phagwara India MLR Institute of Technology Department of CSE-AI&ML Telangana Hyderabad India GLA University Department of Electrical Engineering Mathura India New Horizon College of Engineering Department of Applied Sciences Bangalore India

ISBN: (纸本)9798331512965

The advancement of big data has accelerated over the years to change how companies utilize data to drive decisions. And so, this paper aims to look at big data and data mining in different perspectives while highlighting the importance of data fusion in decision making in the current society. Many times, data fusion combines different data sources to provide better and broader results. Clustering of raw data, anomaly detection and machine learning are discussed as well as their use in healthcare, financial management and smart cities. This paper also presents such issues as data heterogeneity, data quality assurance, as well as scalability issues. Lastly, tomorrow's possibilities, such as artificial intelligence and quantum computing, are presented as possible enhancements of the data fusion effectiveness are mentioned due to the expected marked advancement in real-time and adaptive decisionmaking systems. © 2025 IEEE.

关键词： Data centers

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Job Generator for Evaluating and Comparing Scheduling Algorithms for Modern GPU Clouds

Job Generator for Evaluating and Comparing Scheduling Algori...

引用

15th international conference on Cloud computing and Services Science, CLOSER 2025

作者： Konopa, Michal Fesl, Jan Beránek, Ladislav Department of Data Science and Computing Systems Faculty of Agriculture and Technology University of South Bohemia České Budějovice Czech Republic

ISBN: (纸本)9789897587474

The steep technological and performance advances in GPU cards have led to their increasing use in data centers in the recent years, especially in machine learning jobs. However, high hardware performance alone does not guarantee (sub) optimal utilization of computing resources, especially when the cost associated with power consumption also needs to be increasingly considered. As consequence of these realities, various job scheduling algorithms have been and are being developed to optimize the power consumption in data centers with respect to defined constraints. Unfortunately, there is still no known, widely used, parametrizable dataset that serves as a de facto standard for simulating scheduling algorithms and the resulting ability to compare their performance against each other. The goal of this paper is to describe a simple job set generator designed to run on modern GPU architectures and to introduce the newly created data set suitable for evaluation the scheduling algorithms. Copyright © 2025 by SCITEPRESS - Science and technology Publications, Lda.

关键词： Scheduling algorithms

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Twin Bounded Least Squares Support Vector Regression 6th

Twin Bounded Least Squares Support Vector Regression

引用

6th IFIP TC 12 international conference on Intelligence Science, ICIS 2024

作者： Chen, Ran Liu, Muhan Ma, Jinwen Department of Information and Computational Sciences School of Mathematical Sciences Peking University Beijing100871 China Department of Applied Mathematics China Agricultural University Beijing100083 China

ISBN: (纸本)9783031712524

Support Vector Machine (SVM) has received much attention in machine learning due to its profound theoretical research and practical application results. Support Vector Regression (SVR) has become a powerful tool for solving regression problems. Least Squares Support Vector Regression (LSSVR) has advantages in computing speed but can be prone to overfitting due to its sensitivity to noise and outliers. Additionally, Twin Support Vector Regression (TSVR) shows insufficient flexibility when dealing with large-scale data, and its robustness to noise could be improved. In response to these problems, this paper proposes an innovative solution: Twin Bounded Least Squares Support Vector Regression (TBLSSVR). This model combines the advantages of LSSVR and TSVR and introduces regularization terms to mitigate their limitations effectively. The regularization term helps minimize structural risk, reflecting the advantages of statistical learning theory and ensuring the stability of the solution. Experimental results demonstrate that TBLSSVR improves regression accuracy and significantly accelerates the solution speed, providing new directions and methods for future technology development. © IFIP international Federation for information Processing 2025.

关键词： Vectors

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Research on Disruptive technology Prediction Methods Based on BERT Model and Graph Theory Analysis 24th

Research on Disruptive Technology Prediction Methods Based o...

引用

24th international TRIZ Future conference

作者： Wang, Zhongyou Zhang, Jianhui Li, Rongjian Guo, Xiangdong Hebei Univ Technol Sch Mech & Engn Tianjin Peoples R China

ISBN: (纸本)9783031759215;9783031759192;9783031759185

With the acceleration of the technological revolution, disruptive technologies have become a key factor in global technological competition. However, existing prediction methods are limited by single technology fields, semantic analysis limitations, and subjective factors, making it difficult to effectively predict these technologies. In this paper, we studied the current disruptive technology prediction methods using the ideal solution analysis and resource analysis tools of TRIZ theory and proposed a new prediction method. This method combines the BERT model and graph theory analysis for the first time, and it analyzes patent text, mines the inherent relationships between cross-domain technologies, extracts disruptive technology features, and evaluates them through expert judgments. This method fills the gap in existing research. Our method demonstrates unique innovation in cross-domain technology integration and can more accurately predict disruptive technologies. The research results show that the patent technologies selected after being fused perform excellently in terms of performance and advantages, verifying the scientificity and effectiveness of our research framework. This study provides a new and effective method for exploring and predicting disruptive technologies, which is expected to drive further development in related fields.

关键词： Disruptive technology Forecasting BERT Models Graph Theory Analysis Patent Text Analysis Cross-Domain Technologies

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Cloud computing: Innovations and Impacts on Global Data Infrastructure

Cloud Computing: Innovations and Impacts on Global Data Infr...

引用

2025 IEEE international conference on Computational, communication and information technology, ICCCIT 2025

作者： Banumathi, S. Sivajothi, E. Indumathi, G.S. Kefyalew, Enku Yosef Sivakumar, J. Priya, V. Banu Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India St Joseph's College of Engineering OMR Department of MBA Chennai India Technical and Vocational Training Institute Department of Electrical and Electronics Technology Addis Ababa Ethiopia St.Joseph's College of Engineering Department of Electronics and Communication Engineering Chennai India R.M.K. College of Engineering and Technology Department of Mathematics Thiruvallur District India

ISBN: (纸本)9798331512965

Cloud computing has transformed global data infrastructure with unparalleled scale, flexibility, and accessibility. This study examines how cloud computing innovations have changed data storage, processing, and management worldwide. By examining the progression of cloud services from simple storage and computing to sophisticated platforms and SaaS, we examine how they have transformed corporate operations, economic growth, and societal development. Virtualization, containerization, serverless architectures, and edge computing are the main cloud computing advancements, which we investigate through a literature study and case studies. Data security, privacy, and regulatory frameworks are also considered while adopting the cloud. Cloud computing promotes digital transformation in banking, healthcare, education, and government, according to study. The industry's sustainability and green computing efforts and data centers' environmental impacts are also covered. We found that cloud computing continues to spur innovation by enabling new business models, global connectivity, and data-driven application growth. Cloud technologies' integration with AI, IoT, and 5G networks is likely to change the global data infrastructure, opening new research and development options. This report covers the cloud computing landscape, its advancements, and its potential to shape global data management and digital ecosystems. © 2025 IEEE.

关键词： Cloud platforms

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Mental Stress Assessment in Working Environment for an Individual Using Wearable Sensor of EEG and Pulse Signal Measured with Help of Deep Learning Algorithm 8th

Mental Stress Assessment in Working Environment for an Indiv...

引用

8th IFIP TC 12 international conference on Computer, communication and Signal Processing, ICCCSP 2024

作者： Karthikeyan, M.V. Bhuvaneshwar, S. Nishanth, V. Department of Electronics and Communication Engineering St. Joseph’s Institute of Technology OMR Tamil Nadu Chennai60019 India

ISBN: (纸本)9783031736162

Thanks to artificial intelligence (AI), machines will eventually have the same emotional impact as humans. Deep emotions, not just words, are used by this "affective computing" to engage with humans. Bypassing societal masks, sensors like the EEG and GSR are able to sense our genuine feelings. However, creating robots that are actually sensitive to our emotions is challenging. To build genuinely emotionally intelligent machines, we need to improve the methods we use to choose, arrange, and evaluate these signals. This paper propose a method for assessing mental stress in the workplace in real-time using deep learning algorithms in conjunction with wearing EEG and GSR. The major goal is to make computers smarter emotionally so that they can change the way people interact with computers (HCI). Our proposed system can discreetly track a worker’s emotional and psychological well-being as they go about their daily tasks. By combining electroencephalogram (EEG) and pulse signal analysis, our system is able to record not only the mental but also the physiological reactions to mental stress. © IFIP international Federation for information Processing 2025.

关键词： Wearable sensors

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Building a safe and secure metaverse 2nd

Building a safe and secure metaverse

引用

2nd international conference on Next-Generation computing and information Systems, ICNGCIS 2023

作者： Gupta, Ankur Model Institute of Engineering and Technology Jammu India

ISBN: (纸本)9781032738659

The metaverse is an exciting domain representing an amalgamation of advances in computing and communications along with immersive technologies (AR/VR/XR). It is therefore intuitive for large corporations, research organizations and businesses cutting across industry verticals to adopt a metaverse-centric approach and explore diverse use-cases catering to business/individual needs. However, the transition from traditional applications to metaverse-native applications is not expected to be seamless. Privacy, safety and security concerns exist in the early versions of the metaverse with several flaws endangering individual user safety being highlighted. Plus, there is increased scrutiny on the illeffects of social media, gaming and immersive environments by Governments and regulatory agencies. Thus, it is increasingly clear that the final iteration of the metaverse will need to address the concerns of individual users while navigating a complex legal and regulatory landscape. This keynote examines the different aspects and challenges which the future metaverse will need to address. A set of "first principles" are put forth towards building an inclusive, safe and secure metaverse. © 2025 The Author(s).

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Enhancing Ground Network in UAV Assisted Wireless communication 1

Enhancing Ground Network in UAV Assisted Wireless Communicat...

引用

1st international conference on advances in Computer Science, Electrical, Electronics, and communication Technologies, CE2CT 2025

作者： Jebaraj, Solomon Yadav, Dhananjay Kumar Department of Computer Science and Information Technology Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331518578

The development of wireless technology for ground communications is being aided by the use of unmanned aerial vehicles (UAVs). It is believed that these technologies will continue to advance in the next years. Traditional methods of communication need elaborate, expensive, and laborintensive infrastructure, not to mention lengthy installation procedures. Instead of requiring expensive and time-consuming infrastructure construction, a UAV aided wireless network for communication guarantees a cheap wireless connection to devices. In comparison to High Altitude Platforms (HAPs) such as balloons with hot air or terrestrial systems, wireless communication systems that are incorporated with low level altitude UAVs provide quicker deployment, more mobility, easier re-configuration and according to expectations, improved channels for communication with a shorter line-of-sight (LOS) connectivity. However, unforeseen challenges impair the UAV to Ground system's performance and the reliability of the communication link between users and drones on the ground. Adaptive modulation and coding (AMC) are discussed in this letter as it pertains to Aerial-to-Ground (A2G) networks. Evaluating the downlink data rates and network capacity is our goal, along with reaching peak performance. Additionally, this research thoroughly evaluates the performance of terrestrial users connected to drones in different circumstances in terms of ratio of signal to noise, path loss, latency, and throughput. Furthermore, they investigated the A2G channels downlink link characteristics, which regulate the modulation and coding rate switching. © 2025 IEEE.

关键词： Drones

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Research on Routing Optimization Algorithm for Power OTN Based on DQN 24

Research on Routing Optimization Algorithm for Power OTN Bas...

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2nd international conference on advances in Artificial Intelligence and Applications, AAIA 2024

作者： Hu, Yang Yu, Yang Zhang, Qiang He, Yujun Information and Communication Company State Grid Jilin Electric Power Co. Ltd. Jilin Changchun China Department of Electronic and Communication Engineering North China Electric Power University Hebei Baoding China

ISBN: (纸本)9798400712883

Routing optimization is key to improve the performance of power OTN. To solve the unequally distributed traffic load in power OTN, this paper put forward a power OTN routing optimization algorithm based on DQN. The power OTN was logically divided into states according to the technology characteristics of DQN, with corresponding actions, rewards and DQN agent designed for its operation. It generated optimized routing strategies that produce network routing optimization after several rounds of device-level iteration. The experimental method verified good convergence and effectiveness of the algorithm through simulation experiments on a 14 nodes NSFNet network. © 2024 Copyright held by the owner/author(s).

关键词： Routing algorithms

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