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A Framework for Mining and Applying Alarm Rules Based on LLM

A Framework for Mining and Applying Alarm Rules Based on LLM

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International conference on Vision, image and Signal processing (ICVISP)

作者： Guoqing Li Qian Zhang Haijun Su Mengyuan Zhu Mengqi Liu Haokai Zhang Development Center China Information Technology Designing & Consulting Institute Co. Ltd Beijing China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

Driven by 5G technology, network performance and management requirements are becoming increasingly sophisticated. However, massive and complex alarm information is also coming, posing severe challenges to network operation and maintenance. Accurately identifying alarm correlations and locating alarm root causes has become a core problem for operation and maintenance. In response to this challenge, this paper proposes a framework for mining and applying alarm rules based on large language models, which applies the text understanding capabilities of large language models to alarm processing and can mine uncommon alarm rules. Experimental results show that this framework significantly improves the accuracy and coverage of alarm rules, and improves the response speed and efficiency of network operation and maintenance.

关键词： Technological innovation Correlation Large language models Knowledge based systems Signal processing algorithms Signal processing Real-time systems Maintenance Communication networks Optimization

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Optimization of image Compression and Decompression Performance Based on Genetic Algorithm

Optimization of Image Compression and Decompression Performa...

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Interactive Intelligent systems and Techniques (IIST), International conference on

作者： Weishi Li Chun Yin Fujian Polytechnic of Information Technology Fuzhou China

ISBN: (数字)9798350374421

ISBN: (纸本)9798350374438

As one of the main carriers of information transmission and storage, image data need to be compressed in some application scenarios. Traditional image compression methods, although reducing the size of image files to a large extent, are still difficult to meet the performance requirements of massive, high-speed image data compression processing. In this paper, an image compression and decompression performance amelioration method based on genetic algorithm is proposed, aiming to ameliorate the efficiency and quality of image compression, while reducing the time and computational complexity of decompression. This paper first introduces the background and current status of image compression technology, and analyzes the progress of existing image compression research. Then, the basic principles of genetic algorithm and its application in image compression are introduced in detail. On this basis, an image compression algorithm based on genetic algorithm is proposed. The algorithm ameliorates the parameter settings in the image compression process through genetic algorithm to achieve efficient compression of images. At the same time, combined with the image decompression process, the decompression algorithm is ameliorated to reduce the consumption of computational resources. The research in this paper provides new ideas and methods for the performance amelioration of image compression and decompression technology, which has important theoretical and practical value.

关键词： image quality image coding Data compression Information processing image storage Intelligent systems Computational complexity Optimization Genetic algorithms Convergence

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Diabetic Retinopathy Lesion Detection Through Synergistic Analysis of Independent Components and Uncorrelated Discriminant Features 5

Diabetic Retinopathy Lesion Detection Through Synergistic An...

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5th International conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Ameerjohn, Sirajudeen Manimaran, M. Saravanan, D. Devaraju, S. Kanna, G. Prabu Aanjankumar, S. School of Computing Science Engineering and Artificial Intelligence Vit Bhopal University Indore Bhopal Highway Madhyapradesh Sehore India School of Computing Science and Engineering Vit Bhopal University Indore Bhopal Highway Madhyapradesh Sehore India

ISBN: (纸本)9798350379945

The growing incidence of blindness, specifically linked to diabetic retinopathy (DR), highlights the need for expandable retina screening programs. The purpose of this work is to determine the distinction between normal and infected retina images by applying Independent Component Analysis (ICA). Although several processing methods help in DR detection, accuracy is still a problem. The accuracy of current techniques, such as multi-scale amplitude modulation and frequency modulation (AM-FM), to differentiate normal and diseased retinal images is restricted. The proposed method seeks to improve the identification of normal retina histories, haemorrhages, exudates, neovascularization, microaneurysms and blood vessel patterns. Optic Nerve Head (ONH) identification uses established parameters from AM and FM-based extraction of features to check illness traits, relying on edge data without disguising. Type 2 diabetes, which is typified by elevated blood sugar levels, causes damage to the arteries and diabetic retinopathy (DR), an important cause of permanent loss of vision that is frequently undiagnosed till severe. In the initial phases of diabetic retinopathy (DR), non-proliferative alterations that damage the walls of retina blood vessels develop to proliferation retinal degeneration, which is marked by aberrant formation of neovascularization. A lesion diagnosis is still difficult, despite its importance in the early identification of DR. For disease identification, the intricacy of retinal anatomy necessitates the use of many images and certain segmentation algorithms. Microaneurysms, haemorrhages, exudates and neovascularization are examples of lesions markers and identifying anomalies requires accurate segment. In conclusion, precise and affordable retinal scanning devices are necessary to deal with the increasing incidence of blindness, especially that caused by DR. To improve DR identification, this investigation suggests utilizing ICA and UDA. © 2024 IEEE.

关键词： image segmentation

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Multi-Relational Hierarchical Attention for Top-k Recommendation 21st

Multi-Relational Hierarchical Attention for Top-k Recommenda...

引用

21st International conference on algorithms and Architectures for Parallel processing (ICA3PP)

作者： Yang, Shiwen Zhu, Jinghua xi, Heran Heilongjiang Univ Harbin Heilongjiang Peoples R China

ISBN: (纸本)9783030953881;9783030953874

As one of the critical application directions in the Recommendation systems domain, the top-k recommendation model is to rank all candidate items through non-explicit feedback (e.g., some implicit interact behavior, like clicking, collecting, or viewing) from users. In this ranking, the rank shows the users' satisfaction with recommended items or the relevance of the target item. Although previous methods all improve the performance of the final recommended ranking, they suffer from several limitations. To overcome these limitations, we propose a Multi-Relational Hierarchical Attention within Graph Neural Network (GNN)-attention-Deep Neural Network (DNN) architecture for the topk recommendation, named MRHA for brevity. In our proposed method, we combine the GNN's ability to learn the local item representation of graph-structure data and attention-DNN architecture's ability to learn the user's preference. For processing the multi-relational data that occurs in the real application scenarios, we propose a novel hierarchical attention mechanism based on the GNN-attention-DNN architecture. The comparative experiments conducted on two real-world representative datasets show the effectiveness of the proposed method.

关键词： Top-k recommendation Hierarchical attention Multi-relational graph

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High-Resolution Projection Network combining High-Resolution Optical Flow Compensation for Video Super-Resolution

High-Resolution Projection Network combining High-Resolution...

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image processing and Media Computing (ICIPMC), International conference on

作者： Yifei Sun Zhengxia Chen Yuying Jin xiaoyi Feng School of Electronics and Information Northwestern Polytechnical University Xi'an China Planning Department Xi'an Aerospace Propulsion Institute Xi'an China College of Information Science and Technology Northwest University Xi'an China

ISBN: (数字)9798350386660

ISBN: (纸本)9798350386677

The Super-Resolution (SR) task is to generate high-resolution (HR) images/videos using low-resolution (LR) ones. At present, the Single image Super-Resolution (SISR) methods have achieved superior performance. However, Video Super-Resolution (VSR) methods still have some disadvantages such as edge blurring, high-frequency details missing and motion artifacts. This paper proposes an end-to-end HR feature projection VSR network HOF-HRPN, which consists of a High-Resolution Optical Flow (HOF) and a High-Resolution Projection Network (HRPN). The HOF network estimates the HR optical flow and compensates it to the neighboring frames to achieve accurate frame alignment. The HRPN is composed of a multi frame feature projection channel and a single frame SR channel in parallel. HRPN takes into account the advantages that single frame SR and VSR can extract missing high-frequency details from intra-frame and inter-frame, respectively. It fuses high-frequency details obtained from multi-scale LR projection learning and single frame SR results. A large number of comparative experiments based on public datasets verify that HOF-HRPN is robust and can recover accurate pixel values, clear edges and rich textures.

关键词： Accuracy image edge detection Superresolution Streaming media Media Robustness Real-time systems

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Design and Development of an Intelligent Wireless Pond/Lake Cleaning Robot

Design and Development of an Intelligent Wireless Pond/Lake ...

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Intelligent algorithms for Computational Intelligence systems (IACIS), International conference on

作者： Premkumar M Basavaraja Desai Bhoomika Mylar Chaithanya B K Monish G Department of Electrical and Electronics Engineering Dayananda Sagar College of Engineering Bangalore India Department of Electrical and Electronics Engineering Dayananda Sagar College of Engineering Bengaluru India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

This River pollution is a major environmental problem that has serious problems for human health, aquatic life, and the overall health of ecosystems. Floating garbage is a complicated problem to address, as it can be difficult to collect and remove from rivers and other waterways. Wireless river-cleaning robots can potentially be a valuable tool for addressing this problem. These robots can be equipped with a variety of sensors and actuators to detect and collect floating garbage, without the need for human efforts. This can help to reduce the cost and environmental impact of river cleaning operations, while also improving the effectiveness of these efforts. This paper aims to design and develop a wireless river-cleaning robot that is capable of autonomously detecting and collecting floating garbage. The robot will be designed with a variety of sensors, including cameras, ultrasonic sensors, and water quality sensors. image processing will be used to identify floating garbage, as well as to avoid obstacles and navigate the river safely. The robot will also be equipped with a collection system that can collect floating garbage and other debris. The robot will be controlled wirelessly using image processing and data will be stored on the website. This paper helps to reduce the water pollution on floating bodies and saves the lives of aquatic animals.

关键词： Wireless communication Wireless sensor networks image processing Surveillance Robot vision systems Cameras Cleaning Water pollution Rivers Sensors

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Online Antenna Mode Selection for Reconfigurable MIMO via Adaptive Bandit

Online Antenna Mode Selection for Reconfigurable MIMO via Ad...

引用

International conference on Wireless Communications and Signal processing (WCSP)

作者： Boxi Zhang Ang Li School of Information and Communications Engineering Xi’an Jiaotong University Xi’an China

Reconfigurable antennas (RAs) can enhance link capacity by swiftly changing their radiation pattern to adapt to the wireless propagation environment actively. In order to exploit the property of RAs, selecting the time-varying optimal mode from candidate radiation patterns for MIMO communication is essential but however challenging in a mobile environment. In this paper, we focus on the efficient radiation mode selection for reconfigurable MIMO systems, where the transmit array consists of RAs instead of conventional antennas with fixed radiation mode. Channel prediction based on angle information is studied to obtain the channel state information (CSI) of unselected modes based on the estimated path gains. We further propose two bandit algorithms: upper confidence bound based on adaptive bandit with sliding window (UCB-AB) and Thompson sampling based on adaptive bandit with sliding window (TS-AB). UCB-AB and TS-AB exploit the useful parts of outdated CSI outside the sliding window and improve the convergence rate of bandit algorithms under mobile scenarios. Numerical results demonstrate that the introduction of adaptive bandit can enhance the convergence of bandit algorithms and improve the throughput of MIMO systems.

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DMTP: A Distributed Matchmaking Trading Platform 3

DMTP: A Distributed Matchmaking Trading Platform

引用

3rd International conference on Computer Vision, image and Deep Learning and International conference on Computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Duan, Bowen Du, Aiqing Yang, Peiyu Wang, Jiale Mou, Wenjiei Ju, Haiyu Anhui Normal University Collage of Computer AnHui China Institute of Mathematics and Computer Wuhan Polytechnic University Wuhan China ShangHai Jian Qiao University Collage of Science ShangHai China Northwest University School of Information Science and Technology Xi'an China

ISBN: (纸本)9781665459112

Matchmaking trading system has become an essential paradigm to leverage the massive buyers to obtain the certain trades in a most effective method. Trading matchmaking method is an indispensable issue in commerce platforms owing to sellers and buyers exiting in heterogeneous bidder and prices. Matchmaking method is a fundamental approach in trading platforms, while currently most researchers and systems are considered and relayed on a concentrated servers leads to ignore the server safety in assigning trading platforms and the risk of sensitive information leakage by utilizing a centralized server. In this paper, we concentrate on distributed matchmaking approach for buyers with diversity sellers in trading platforms and propose an allocation method DMTP to maximize the social welfare by utilizing the block chain trading technology with reasonable computation and communication costs. Extensively experimental results indicate that proposed mechanism can greatly enhance the successful ratio of matchmaking trades and compare proposed mechanism social welfare with exiting trading algorithms. © 2022 IEEE.

关键词： Commerce

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HOIG: End-to-End Human-Object Interactions Grounding with Transformers

HOIG: End-to-End Human-Object Interactions Grounding with Tr...

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2022 IEEE International conference on Multimedia and Expo, ICME 2022

作者： Ma, Zeyu Wei, Ping Li, Huan Zheng, Nanning Xi'an Jiaotong University Xi'an China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Visual grounding is a crucial and challenging problem in many applications. While it has been extensively investigated over the past years, human-centric grounding with multiple instances is still an open problem. In this paper, we introduce a new task of Human-Object Interactions (HOI) Grounding to localize all the referring human-object pair instances in an image with a given human, interaction, object phrase. We design an encoder-decoder architecture to model the task as a set prediction problem based on transformers. A vision-language alignment module and a grounding decoder are designed to learn accurate cross-modal contexts and interactions. Our model accomplishes alignment and prediction in an end-to-end manner without pre-trained detectors or post-processing. Experiments on two challenging datasets prove the strength of our model. © 2022 IEEE.

关键词： Decoding

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Study on Prostate image Segmentation Using Improved U-NET

Study on Prostate Image Segmentation Using Improved U-NET

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International conference on image, Vision and Intelligent systems, ICIVIS 2021

作者： Sun, Mengya Department of Mathematical Sciences University of Electronic Science and Technology of China Chengdu610000 China

ISBN: (纸本)9789811669620

Medical image plays a key role in the analysis and treatment of the patient’s condition in today’s medicine, but the clinical processing of medical image is still largely dependent on the subjective experience of doctors, and the process of manual extraction of information is time-consuming and labor-consuming. With the development of deep learning, it has become a trend to apply deep learning to medical image processing. However, due to the characteristics of medical images, many advanced segmentation algorithms fail to achieve good results in medical images. In addition, medical image data generally have the problem of insufficient or too small data sets, and there are few ways to obtain samples, mainly from some hospitals and medical institutions. Besides, the labeling work is not competent for ordinary people. So how to realize the automatic analysis and processing of medical images has always been a hot topic in the field of computer science. In this paper, we designed an experiment of prostate segmentation algorithm, built a model using a U-Net network that performs well in the field of medical image segmentation, and tried to improve its performance by combining a variety of structures, such as ASPP, ResNext, and attention module. The results show that our proposed model achieves better segmentation performance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image segmentation

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