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Non-destructive Detection of Moldy Camellia Oleifera Seeds Based on Deep Learning and Hyperspectral Imaging 7

Non-destructive Detection of Moldy Camellia Oleifera Seeds B...

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7th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Han, Zhenyu Zhang, Yongli Zhu, Guangfei Liu, Xuan Tang, Hao Han, Tailin Changchun University of Science and Technology School of Electronic and Information Engineering Changchun China Academy of Agricultural Planning and Engineering Key Laboratory of Agro-Products Primary Processing Ministry of Agriculture and Rural Affairs Beijing China Hainan University School of Information and Communication Engineering Haikou China

ISBN: (纸本)9798350350890

Camellia oleifera, a woody oil plant of high economic value, faces potential mold growth during storage and transportation, which could significantly impact its sales and processing. therefore, it is crucial to identify and select moldy camellia oleifera seeds. Due to the fact that the mold growth of camellia oleifera seeds typically originates from the inside of the seeds, the mold is not visibly apparent on the surface of the shells in the early stages of mold growth. the existing chemical methods are time-consuming, labor-intensive, and result in sample damage. To address this challenge, this study introduces a non-destructive detection method for assessing the extent of mold growth in camellia oleifera seeds efficiently and effectively. the method is based on deep learning and hyperspectral imaging (HSI) technology. A hyperspectral imaging system was utilized to capture hyperspectral images of camellia oleifera seeds at three degrees of mold. In response to the limitations of traditional machine learning methods in hyperspectral classification, which only focus on learning spectral features and yield unsatisfactory results, this study introduces a deep learning approach based on three-dimensional convolution. this algorithm is capable of extracting features from both spatial and spectral information. the classification performance of the proposed model is compared with machine learning methods that rely solely on spectral information and deep learning methods that use only spatial information from visual images. Based on the dataset constructed in this study, experimental results demonstrate that the proposed method achieves an accuracy of 88.99%, surpassing other methods by at least 18.6%. © 2024 IEEE.

关键词： Petroleum transportation

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Remote Sensing Image Ship Detection Based on Improved YOLOv3 7

Remote Sensing Image Ship Detection Based on Improved YOLOv3

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Da, Yifan Gao, Xing Li, Mengfei Beijing University of Chemical Technology School of Information and Communication Technology Beijing China Yanshan University Liren College Qinhuangdao China Beijing University of Posts and Telecommunications Computer Science and Technology Beijing China

ISBN: (纸本)9781665478571

With the improvement of remote sensing image resolution, remote sensing target detection has become a research hotspot, and it plays an important role in military reconnaissance, disaster rescue, urban traffic management, and other scenarios. However, remote sensing target detection still has problems such as a large amount of data and specific differences in shooting by different sensors. In order to meet these challenges and improve the speed and accuracy of remote sensing target detection, this paper proposes a target detection algorithm based on an attention mechanism. Based on the YOLOv3 network, the SE-YOLOv3 network is designed using an attention mechanism to increase expressiveness, focus on essential features, and suppress unnecessary features. the experimental results show that: on the DOTA data set, compared with the YOLOv3 network, adding the squeeze and excitation (SE) model to the bottleneck has the best effect and can better improve the performance of the model. Experiments show that the proposed SE-YOLOv3 network is more efficient and accurate than YOLOv3, so it is more suitable for target detection tasks in complex remote sensing scenes. © 2022 IEEE.

关键词： Object detection

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MMSFD: Multi-grained and Multi-modal Fusion for Short Video Fake News Detection 7

MMSFD: Multi-grained and Multi-modal Fusion for Short Video ...

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7th international conference on Data Science and information technology, DSIT 2024

作者： Ren, Shuai Liu, Yahui Zhu, Yaping Bing, Wanlong Ma, Hongliang Wang, Wei Shihezi University School of Information Science and Technology Shihezi China Xinjiang Production and Construction Corps Key Laboratory of Computing Intelligence and Network Information Security Shihezi China Beijing Jiaotong University School of Computer Science and Information Technology Beijing China

ISBN: (纸本)9798350384093

Short video platforms have become an essential part of people's daily lives, while also facing the challenge of the rapid spread of fake news. therefore, the detection of fake news in short videos has attracted increasing attention. Existing works mostly focus on the integration of textual and visual content, but fail to fully exploit multi-modal information at both fine-grained and coarse-grained levels. Moreover, multi-modal fake news detection is vulnerable to modality ambiguity due to potential conflicts or weak correlations between different modalities. In this paper, we propose a Multi-grained and Multi-modal fusion for Short video Fake news Detection (MMSFD). We encode textual and visual content using pre-trained models at both fine-grained and coarse-grained levels and fuse them through distinct branches. To tackle the ambiguity issue, we design a multi-modal fusion branch based on similarity weighting, as well as separate single-modal branches. Additionally, this paper presents a cross-modal attention mechanism for adaptively aggregating and reweighting features. the experimental results on a real-world short video dataset demonstrate that the proposed method outperforms state-of-the-art short video fake news detection methods. © 2024 IEEE.

关键词： Fake detection

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Hidden Markov Model for Improving Resource Utilization of Dehydration Rice Paddy Service in Community Cooperatives 7

Hidden Markov Model for Improving Resource Utilization of De...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： thanavanich, thanawut Kantawong, Krittika Yaibuates, Mayoon Duangtang, Pumipong Sriwanna, Kittakorn Siri, Atikhom Chiangrai Rajabhat University School of Computer and Information Technology Mueang Chiangrai57100 Thailand University of Phayao School of Information and Communication Technology Phayao Phayao56000 Thailand

ISBN: (纸本)9781665495103

the moisture content of paddy is an important indicator of the price of paddy. therefore, reducing humidity is necessary and costly to invest by farmers themselves. the dehydration of rice paddy is currently available as a community cooperative service such as hot air blowing and natural drying methods. the operation problems of cooperative services encountered are resource management of blowing machines and management of paddy drying area effectively. In this paper, we present a Hidden Markov Model of a decision in more efficient use of those services. the experimental results of discrete event simulations show that the proposed model can efficiently improve resource utilization and can achieve the needs of farmers as well. © 2022 IEEE.

关键词： Hidden Markov models

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An Improved Privacy Control Scheme for Contract Algorithm Based on Structure Entropy 24

An Improved Privacy Control Scheme for Contract Algorithm Ba...

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7th international conference on Signal processing and Machine Learning, SPML 2024

作者： Wang, Diao Hu, Zhifei School of Computer Science Liupanshui Normal University China

ISBN: (纸本)9798400717192

In response to the limitations of current contract algorithms that rely on random selection during the clustering process, resulting in excessively random clustering outcomes and high computational costs for subsequent privacy validation, this research introduced a privacy control framework for contract algorithms based on structural entropy. the framework proposed two strategies: the maximum probability information flow priority strategy and the "acquaintance"priority strategy to minimize result uncertainty. Furthermore, drawing from the concept of resistance of graphs, an algorithm utility evaluation mechanism based on graph resistance was established to evaluate changes in the network's resistance to privacy breaches caused by privacy protection algorithms. through comparative experimental analysis, it is demonstrated that this framework improves the efficiency of algorithm iterations and reduces computational costs while ensuring security. © 2024 ACM.

关键词： Differential privacy

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Research on Overlapping Community Detection Based on Density Peak Clustering in Heterogeneous Networks 7

Research on Overlapping Community Detection Based on Density...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Yue, Sun Yuhong, Zhao Inner Mongolia University of Science and Technology School of Information Engineering Baotou China

ISBN: (纸本)9781665478571

To solve the problem of finding overlapping communities in heterogeneous networks, this paper proposes a model for finding overlapping communities in heterogeneous networks based on density peak clustering. the model improves the heterogeneous graph attention network, which fully mines for the important information of nodes and meta-paths in information representation from the node level and the semantic level attention mechanisms and performs hierarchical aggregation to obtain heterogeneous graph embedding vectors. It combines the heterogeneous graph attention network with density peak clustering and calculates node density and relative distance through the heterogeneous graph embedding vector to divide community center nodes. then it also uses the weight information of the node-level attention mechanism to generate a community membership matrix. the experimental results on real datasets show that the model can utilize the diversity of heterogeneous network node information to discover overlapping communities with good stability and accuracy. © 2022 IEEE.

关键词： Heterogeneous networks

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Intelligent-Based Extraction of Business Capabilities from Company Descriptions 7

Intelligent-Based Extraction of Business Capabilities from C...

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7th international conference on information technology, information Systems and Electrical Engineering, ICITISEE 2023

作者： Fahmi, Faisal Hamid, Siti Hafizah Ab Yuadi, Imam Airlangga University Faculty of Political and Social Science Department of Library and Information Science Indonesia Universiti Malaya Faculty of Computer Science & Information Technology Department of Software Engineering Malaysia

ISBN: (纸本)9798350382266

In the era of Big Data, information can be generated, extracted, and utilized in diverse ways. In business, information about business capabilities can be a crucial aspect in understanding the strengths and competencies of organizations. this information can empower stakeholders to make informed decisions regarding partnerships, acquisitions, and market positioning. Additionally, by comparing capabilities across companies and industries, organizations can identify their competitive advantages, industry trends, potential disruptions, and effective resource allocations, leading to improved strategies and better market opportunities. Traditional methods for extracting business capabilities primarily rely on keyword matching or rule-based techniques, which often fail to capture the complex relationships between words in a sentence. this paper presents a comprehensive study on extracting business capabilities using dependency parsing techniques in natural language processing (NLP) to overcome limitations of the traditional methods and improve the accuracy of business capability extraction. Dependency parsing utilizes pre-trained language models to analyze the grammatical structure of sentences, identifying the dependencies between words and capturing their relationships. the feasibility and effectiveness of the proposed approach is demonstrated through experiments conducted on more than 40K real-world company descriptions crawled from Wikipedia. © 2023 IEEE.

关键词： Competition

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A Hybrid SARIMAX Model in Conjunction with Neural Networks for the Forecasting of Life Insurance Industry Growth in thailand 9

A Hybrid SARIMAX Model in Conjunction with Neural Networks f...

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Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, ECTI DAMT and NCON 2024

作者： Huadsri, Supika Mekruksavanich, Sakorn Jitpattanakul, Anuchit Phaphan, Wikanda King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Applied Statistics Bangkok10800 Thailand University of Phayao School of Information and Communication Technology Department of Computer Engineering Phayao56000 Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Mathematics Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Thailand Research Group in Statistical Learning and Inference Thailand

ISBN: (纸本)9798350318241

this article is conducted with the primary aim of comparing various forecasting models to identify the optimal model for forecasting the growth of the life insurance industry in thailand. the models under consideration include the SARIMAX model, the Recurrent Neural Network (RNN), and a hybrid model introduced as RNN-SARIMAX. the dataset utilized for this investigation is extensive, consisting of monthly direct premium data from the thai life insurance sector spanning January 2003 to December 2022. the dataset is segregated into two distinct segments. Initially, data from January 2003 to December 2021 is employed for constructing the forecasting model. Subsequently, data from January 2022 to December 2022 is utilized for a comparative analysis of the forecasting models, to determine the most suitable and accurate model for predicting the growth of the life insurance industry in thailand. the evaluation criteria for comparing models include the Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R-squared). the consistent findings from our analysis indicate that the SARIMAX model consistently outperforms both the RNN and RNN-SARIMAX models. © 2024 IEEE.

关键词： Recurrent neural networks

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the Surveillance Systems to Prevent Pressure Bedsores and Clinical Guidelines for Bedridden Patients and Caregivers 7

The Surveillance Systems to Prevent Pressure Bedsores and Cl...

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作者： Siramungklanon, Napatrapee Yaibuates, Mayoon Pravesjit, Sakkayaphop Kantawong, Krittika Learning Subject Group Science and Technology Samsenwittayalai School Bangkok Thailand School of Computer and Information Technology Chiang Rai Rajabhat University Chiang Rai Thailand School of Information and Communication technology University of Phayao Phayao Thailand

ISBN: (纸本)9781665495103

this work proposed the development of surveillance systems to prevent bedridden patients from pressure sores. the system can notify caregivers and patients when pressure, humidity, and pH exceed its limitation. In addition, caregivers and bedridden patients can study clinical guidelines in the system to avoid pressure ulcers. the real-time information sensing from the sensor of the system can notify caregivers to change the posture of patients or clean up when the humidity or pH value is higher than the normal standard. the testing found that the system can give satisfying results. © 2022 IEEE.

关键词： Security systems

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Enhancing Negotiation Flexibility of Smart Contract in Hyperledger Framework 7th

Enhancing Negotiation Flexibility of Smart Contract in Hyp...

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7th international conference on Advanced Computing and Intelligent Engineering, ICACIE 2022

作者： Samanta, Ashis Kumar Chaki, Nabendu Department of Computer Science and Engineering University of Calcutta Kolkata India

ISBN: (纸本)9789819950140

Blockchain technology has changed the security level of usage potential of soft data in the digital world. Users depend on blockchain and follow business procedures similar to legacy systems. the smart contract applications, built on blockchain technology, are utilized in diverse application areas, including educational domain, service domain, economic data processing, financial services, healthcare, etc. the advantage of a smart contract is that without any trusted third party, a digital negotiation between two or more anonymous parties is built using self-executed blockchain computer code. the technology still has some issues in the context of its flexibility in respect of the negotiation between two participants involved in the smart contract. Hyperledger is one of the most extensive and popular existing blockchain frameworks that support the private blockchain and smart contract. this paper aims to enhance the flexibility of the bargaining process of smart contracts by adding more options in negotiation in the Hyperledger framework for future dealings. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart contract

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