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lecture notes in computer science (including subseries lecture notes in Artificial Intelligence and lecture notes in Bioinformatics) 2014年 8559 LNCS卷 XI-XII页

作者： Biere, Armin Bloem, Roderick Johannes Kepler University Linz Altenbergerstr. 69 4040 Linz Austria IAIK Graz University of Technology Inffeldgasse 16a 8010 Graz Austria

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Citrus Plant Leaves Disease Detection Using CNN and LVQ Algorithm 1

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International Conference on Data Analytics and Management, ICDAM 2023

作者： Meena, Roop Singh Solanki, Shano Computer Science and Engineering Department NITTTR Chandigarh India

ISBN: (数字)9789819965441

ISBN: (纸本)9789819965434

This study introduces a unique method for disease identification in citrus plants by combining convolutional neural network (CNN) and learning vector quantization (LVQ) techniques. The suggested technology is meant to aid in the early identification and diagnosis of citrus plant diseases, which is important for preserving crop yields and avoiding crop loss. Features are extracted from pictures of citrus plant leaves using a convolutional neural network. Furthermore, the LVQ algorithm is used to identify the retrieved features as either healthy or unhealthy. When tested on a dataset consisting of photographs of citrus plant leaves, the suggested system achieved a high accuracy of 96.33% in disease classification. A total of 3570 pictures were used in this analysis, including both healthy and diseased citrus plants, representing different pathogens (citrus canker, citrus scab, citrus rust, other diseases, and healthy images) classes. There are 500 test photographs from each class and 1070 full-size images throughout test categories. An F1-score of 96.54%, a recall score of 96.54%, and a precision score of 96.69% were all obtained using the proposed strategy. Based on the obtained data, it appears that the proposed method achieves superior accuracy in disease identification compared to the state-of-the-art methods. The citrus industry stands to benefit greatly from this strategy, as it may be used for early disease identification and prevention in citrus plants. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Diagnosis

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Fine-Tuning Large Language Models for Answering Programming Questions with Code Snippets 23rd

Fine-Tuning Large Language Models for Answering Programming...

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23rd International Conference on Computational science, ICCS 2023

作者： Lomshakov, Vadim Kovalchuk, Sergey Omelchenko, Maxim Nikolenko, Sergey Aliev, Artem Huawei St. Petersburg Russia AI Center National University of Science and Technology MISIS Moscow Russia St. Petersburg Department of the Steklov Institute of Mathematics St. Petersburg Russia

ISBN: (纸本)9783031360206

We study the ability of pretrained large language models (LLM) to answer questions from online question answering fora such as Stack Overflow. We consider question-answer pairs where the main part of the answer consists of source code. On two benchmark datasets—CoNaLa and a newly collected dataset based on Stack Overflow—we investigate how a closed-book question answering system can be improved by fine-tuning the LLM for the downstream task, prompt engineering, and data preprocessing. We use publicly available autoregressive language models such as GPT-Neo, CodeGen, and PanGu-Coder, and after the proposed fine-tuning achieve a BLEU score of 0.4432 on the CoNaLa test set, significantly exceeding previous state of the art for this task. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational linguistics

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Classification of Helpful and Unhelpful Online Customer Reviews Using XLNet and BERT Variants 1

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International Conference on Green Energy, Computing, and Intelligent Technology, GEn-CITy 2023

作者： Bilal, Muhammad Arshad, Muhammad Haseeb Ramzan, Muhammad Department of Computing and Information Systems School of Engineering and Technology Sunway University Petaling Jaya Malaysia Department of Computer Science National University of Computer and Emerging Sciences Chiniot-Faisalabad Campus Chiniot Pakistan Department of Software Engineering University of Sargodha Sargodha Pakistan School of Electronics and Computer Science University of Southampton Malaysia Iskandar Puteri Malaysia

ISBN: (数字)9789819998333

ISBN: (纸本)9789819998326

The majority of businesses have made public appearances on various social media platforms as a result of recent advances in e-commerce and the popularity of social media websites. Customers can share their experiences in the form of online customer reviews, which can assist potential customers in determining the quality of a company and making purchasing decisions. Due to the large volume of published reviews, it becomes difficult for customers to read all of the reviews and assess the quality of the business, resulting in the problem of information overload. Several solutions have been proposed in the literature by researchers using statistical and machine learning techniques to predict the helpfulness of online customer reviews. However, most of the existing solutions are based on the use of various business, review, and reviewer features, which lead to generalizability issues. Moreover, very limited studies have examined the effectiveness of state-of-the-art pre-trained language models for the classification of helpful and unhelpful reviews. Therefore, this study aims to examine the effectiveness of XLNet, Albert, DistilBert, and Roberta for review helpfulness prediction using textual features. The models were fine-tuned using a publicly available dataset of Yelp reviews. The results showed that XLNet achieved the highest F1-score of 0.730 compared to a benchmark of 0.717 achieved by the BERT base model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sales

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CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses 26th

CORSID Enables de novo Identification of Transcription Regu...

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26th International Conference on Research in Computational Molecular Biology, RECOMB 2022

作者： Zhang, Chuanyi Sashittal, Palash El-Kebir, Mohammed Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 United States

ISBN: (纸本)9783031047480

关键词： Coronavirus

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lecture notes in computer science (including subseries lecture notes in Artificial Intelligence and lecture notes in Bioinformatics): Preface

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lecture notes in computer science (including subseries lecture notes in Artificial Intelligence and lecture notes in Bioinformatics) 2014年 8454 LNCS卷 V-VII页

作者： George, Laurent Vardanega, Tullio University of Paris-Est Champs sur Marne France University of Padua Italy

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Towards Event Timeline Generation from Vietnamese News 19th

Towards Event Timeline Generation from Vietnamese News

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19th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2018

作者： Vu, Van-Chung Ha, Thi-Thanh Nguyen, Kiem-Hieu School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Viet Nam Thai Nguyen University of Information and Communication Technology Thai Nguyen Viet Nam

ISBN: (纸本)9783031238031

Event timeline generation is an active research area in many languages. In this paper, we describes our attempts towards event timeline generation from Vietnamese newswire documents based on the work in [1]. Our main contributions are: i) To our knowledge, we are the first to tackle the problem for Vietnamese language. ii) Experiments were conducted on a large-scale corpus from 145 popular online news agents in the period from 2007 to 2017 which provides extensive redundant information on various themes. iii) We manually built a dataset of 17 timelines for evaluation (The dataset could be downloaded at http://***/~hieunk/resources/*** ). Experimental results show that the proposed method works reasonably well for Vietnamese;and using n-grams on unsegmented texts achieves comparable performance to using word segmentation. © 2023, Springer Nature Switzerland AG.

关键词： Computational linguistics

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Subfield Attacks on HSVP in Ideal Lattices 18th

Subfield Attacks on HSVP in Ideal Lattices

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18th International Conference on Information Security and Cryptology, Inscrypt 2022

作者： Dong, Zhili Tian, Shixin Wang, Kunpeng Lv, Chang State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Science Beijing100093 China

ISBN: (纸本)9783031265525

In this paper, we propose two subfield attacks on HSVP in ideal lattices in number fields (not necessarily Galois fields), both under the canonical embedding and the coefficient embedding. These two attacks use the intersection method and the norm method, respectively. In addition,the reduction steps in our attacks are all in polynomial time. By contrast, the former method reduces HSVP in ideal lattices to HSVP in ideal lattices in subfields with larger approximate factor than the latter one, while the latter method has a wider range of applications. Moreover, in Galois number fields, the intersection method performs better in attacking prime ideals with small decomposition fields, whilst the norm method works better in prime ideals with large decomposition fields. Besides, ideals with small norms are vulnerable by both of these two attacks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Embeddings

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Theoretical Framework for Blockchain Secured Predictive Maintenance Learning Model Using Digital Twin 1

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International Workshop on Advanced in Information Security Management and Applications, AISMA 2024

作者： Vinodha, D. Jenefa, J. Anita, E. A. Mary Babenko, Mikhail Departmentof Computer Science and Engineering Christ University Bangalore India North-CaucasusCenter for Mathematical Research North-Caucasus Federal University Stavropol Russia

ISBN: (数字)9783031721717

ISBN: (纸本)9783031721700

The automotive sector benefits from Digital Twins (DTs), software replicas of physical assets or processes. DTs enable engineers and data scientists to obtain deeper insights into the system and solve the most difficult problems faster and more affordably. Blockchain technology is a developing and exciting technology that has the potential to offer DTs monitoring capabilities, strengthening security and enhancing DTs’ transparency, dependability, and immutability. Intelligent behavior can be integrated into blockchain-based DTs to foresee important maintenance tasks and successfully manage machine functions. Our research involves creating a theoretical framework that leverages emerging technologies such as blockchain, artificial intelligence and DTs to facilitate resolution in the predictive maintenance of industry machines with minimised governing cost. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Predictive maintenance

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Study of Quadcopter Movement Using CFD and PID with Numerical Methods 1

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6th International Conference on Mathematical Modelling, Applied Analysis and Computation, ICMMAAC 2023

作者： Kunwar, Bharti Rajput, Ravindra Kumar Singh Mathpal, Tanuja Pandey, Sourav Dibyanshu Department of Mathematics Statistics and Computer Science G.B. Pant University of Agriculture and Technology Uttarakhand Pantnagar263145 India

ISBN: (数字)9783031563072

ISBN: (纸本)9783031563065

Quadcopters play a vital role in various industries due to their excellent maneuverability, enabling them to access hard-to-reach areas and perform tasks that traditional aircraft or vehicles cannot accomplish. The Quadcopter has 6-DoF movements that include both linear (x, y, z) and angular (roll, pitch, and yaw angles) motions. The study explores a new approach to study Quadcopter movement through the integration of Computational Fluid Dynamics, and proportional-integral-derivative with Numerical Methods. This work is useful to design a control system for the stability and maneuverability of quad-copter motion. In the present work, we developed mathematical models for quadcopter movement, simulated the models, and validated them using data from previous research. Our study is valuable for aviation system automation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Computational fluid dynamics

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