检索结果-内蒙古大学图书馆

A BERT-encoded ensembled CNN model for suicide risk identification in social media posts

Neural Computing and Applications 2024年第18期36卷 10955-10970页

作者： Gorai, Joy Shaw, Dilip Kumar Department of Computer Science and Engineering National Institute of Technology Jamshedpur India

Suicide is a significant public health issue that devastates individuals and society. Early warning systems are crucial in preventing suicide. The purpose of this research is to create a deep learning model to identify suicide risk using a combination of bidirectional encoder representations from transformers (BERT) and an ensemble of multiple convolutional neural networks (CNN). BERT is used to encode the text data into numerical representations that capture the context-aware meaning of words and phrases, while ensemble CNN is used to analyze the encoded text data to identify patterns and relationships relevant to suicide risk. The model is trained on a large corpus of text data from social media and suicide notes and evaluated on a validation set of labeled data. The results of the proposed model perform better than the recent approaches in detecting suicide risk and can potentially be a valuable tool for suicide prevention efforts. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Security experimental framework of trajectory planning for autonomous vehicles

引用

International Journal of Intelligent Networks 2024年第1期5卷 315-324页

作者： Al-sheyab, Sujoud Al-shara, Zakarea Al-khaleel, Osama Department of Computer Engineering Jordan University of Science and Technology Irbid Jordan Department of Software Engineering Jordan University of Science and Technology Irbid Jordan

In the contemporary landscape, autonomous vehicles (AVs) have emerged as a prominent technological advancement globally. Despite their widespread adoption, significant hurdles remain, with security standing out as a critical concern. The potential for attacks within AV networks, exemplified by the Trajectory Privacy Attack on Autonomous Driving (T-PAAD), underscores the urgency for robust security measures. Unfortunately, existing simulations for preemptively assessing the T-PAAD attack's impact are scarce. This paper introduces the Security Experimental Framework for Autonomous Vehicles (SEFAV), designed to address this gap by providing a versatile platform for simulating security scenarios in AV environments. SEFAV is cross-platform and compatible with different operating systems such as Windows and Linux, enhancing accessibility for researchers and practitioners. Our primary focus lies in showcasing the T-PAAD attack within our framework, highlighting its efficacy in evaluating and fortifying AV security. © 2024 The Authors

关键词： Vehicle routing

来源：评论

学校读者我要写书评

暂无评论

Revolutionising facility layout: a case study of dynamic facility layout in cable production

引用

International Journal of Web engineering and Technology 2024年第3期19卷 267-309页

作者： Vineetha, G.R. Rasheedali, Shiyas Chekkot Division of Computer Science and Engineering Department of Mechanical Engineering Cochin University College of Engineering CUSAT Kuttanadu Kerala Alappuzha India

In the competitive landscape of globalised markets, businesses must prioritise cost reduction for sustained competitiveness. This study delves into the dynamic facility layout problem (DFLP) within a cable production company in Kerala, emphasising adaptability to changing production demands. Addressing material handling costs and rearrangement expenses, the research evaluates the efficacy of the current static layout and explores the benefits of transitioning to a dynamic layout. The case study reveals potential cost savings through the strategic restructuring of machine arrangements. The innovative machine learning-based genetic algorithm (ML-GA) integrates machine learning algorithms, genetic algorithms, and a local search method, offering a cutting-edge solution to dynamic facility layout challenges. By considering demand variability and relocation costs, the study provides insights for informed decision-making, emphasising the significance of material flow patterns. This research contributes to enhancing efficiency and profitability, providing practical implications for businesses navigating the complexities of modern manufacturing. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Plant layout

来源：评论

学校读者我要写书评

暂无评论

A Voting Approach for Heart Sounds Classification Using Discrete Wavelet Transform and CNN Architecture

引用

SN computer science 2024年第2期5卷 251页

作者： Das, Sunanda Ahsan, Sk. Md. Masudul Rahman, Mahfujur Karim, Md. Shahriar Department of Computer Science and Engineering Khulna University of Engineering & amp

Cardiovascular diseases (CVDs) are a group of diseases that affect the heart or blood vessels and are the leading cause of mortality around the world. The main focus of this work is to classify heart sounds accurately before the condition of the heart worsens. Over the past few decades, audio-based classifications of medical data have received high consideration among various researchers. However, there are mainly two drawbacks while working with audio data. (1) variable length of the audio data and, (2) an inadequate number of class quintessential audio samples. In this work, reflection operation and the sliding window approach are employed to generate fixed-sized audio data. The proposed method applied Discrete Wavelet Transform (DWT) and Mel-Spectrogram for feature extraction. Furthermore, different augmentation techniques such as time-stretching and pitch-shifting are utilized in the method so that the proposed deep learning-based CNN architecture can be trained on a large amount of data. The proposed method is verified using two datasets provided by the ‘PASCAL Heart Sounds Challenge’, each of which contains a small number of heart sound samples of various lengths. In comparison, the experimental outcomes exhibit that the proposed approach outperforms many state-of-the-art methods with respect to sensitivity, specificity, precision, Youden index, etc. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Augmentation Convolutional neural network (CNN) Discrete wavelet transform (DWT) Sliding window Spectrogram

来源：评论

学校读者我要写书评

暂无评论

Cocoa-Net: Performance Analysis on Classification of Cocoa Beans Using Structural Image Feature

Informatica (Slovenia)

引用

Informatica (Slovenia) 2024年第12期48卷 41-54页

作者： Pal, Chandrajit Das, Samikshan Akuli, Amitava Adhikari, Sudip Kumar Dey, Aniruddha Department of Electrical Engineering IIT Hyderabad India Capgemini India Centre for Development of Advanced Computing Kolkata India Department of Computer Science & Engineering CGEC Cooch Behar India Department of Computer Science & Engineering MSIT Kolkata India

The process of cocoa hybridization produces new types that have unique chemical properties impacting the manufacturing of chocolate yet are resistant to a number of plant illnesses. Image analysis is a valuable tool for visually differentiating cocoa beans where deep neural networks (DNN) play a pivotal role in implementing them. In this manuscript, we compare machine learning and deep learning models because it takes into consideration multiple images covering a wide range of agricultural products. Specifically, we extract features from images using a series of image processing techniques, following which we use both traditional machine learning methods (KNN, Decision tree, SVM, and Random Forest) and Convolutional Neural Networks (proposed Cocoa-Net and RESNET 50) to classify the cocoa beans into four categories: large, medium, small, and rejected. Since each methodology offers strong classification performance and has potential for use in the classification of food, they were all chosen. To test these methods, a dataset including 200 samples of fragmented images was utilized. Studies that compare various similar approaches are also carried out. Two optimization techniques: Univariate Selection and Feature Importance have been leveraged to optimize the retrieved features before the learning models are trained. The Adam optimizer is used to optimize the proposed Cocoa-Net model. K-fold cross validation is utilized to assess trained models, and mean cross validation scores are then computed for performance analysis. The empirical result shows that, the proposed Cocoa-Net model predicts with the highest classification accuracy score of 0.85. © 2024 Slovene Society Informatika. All rights reserved.

关键词： cocoa beans Cocoa-Net decision tree KNN random Forest SVM

来源：评论

学校读者我要写书评

暂无评论

Hybrid two-level protection system for preserving pre-trained DNN models ownership

引用

Neural Computing and Applications 2024年第34期36卷 21415-21449页

作者： Fkirin, Alaa Moursi, Ahmed Samy Attiya, Gamal El-Sayed, Ayman Shouman, Marwa A. Department of Electrical Engineering Faculty of Engineering Fayoum University Fayoum Egypt Computer Science and Engineering Department Faculty of Electronic Engineering Menoufia Governorate Menouf32952 Egypt

Recent advancements in deep neural networks (DNNs) have made them indispensable for numerous commercial applications. These include healthcare systems and self-driving cars. Training DNN models typically demands substantial time, vast datasets and high computational costs. However, these valuable models face significant risks. Attackers can steal and sell pre-trained DNN models for profit. Unauthorised sharing of these models poses a serious threat. Once sold, they can be easily copied and redistributed. Therefore, a well-built pre-trained DNN model is a valuable asset that requires protection. This paper introduces a robust hybrid two-level protection system for safeguarding the ownership of pre-trained DNN models. The first-level employs zero-bit watermarking. The second-level incorporates an adversarial attack as a watermark by using a perturbation technique to embed the watermark. The robustness of the proposed system is evaluated against seven types of attacks. These are Fast Gradient Method Attack, Auto Projected Gradient Descent Attack, Auto Conjugate Gradient Attack, Basic Iterative Method Attack, Momentum Iterative Method Attack, Square Attack and Auto Attack. The proposed two-level protection system withstands all seven attack types. It maintains accuracy and surpasses current state-of-the-art methods. © The Author(s) 2024.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Genetic-Based Keyword Matching DBSCAN in IoT for Discovering Adjacent Clusters

引用

computer Modeling in engineering & sciences 2023年第5期135卷 1275-1294页

作者： Byoungwook Kim Hong-Jun Jang Department of Computer Engineering Dongshin UniversityNaju58245Korea Department of Computer Science and Engineering Jeonju UniversityJeonju55069Korea

As location information of numerous Internet of Thing(IoT)devices can be recognized through IoT sensor technology,the need for technology to efficiently analyze spatial data is *** of the famous algorithms for classifying dense data into one cluster is Density-Based Spatial Clustering of Applications with Noise(DBSCAN).Existing DBSCAN research focuses on efficiently finding clusters in numeric data or categorical *** this paper,we propose the novel problem of discovering a set of adjacent clusters among the cluster results derived for each keyword in the keyword-based DBSCAN *** existing DBSCAN algorithm has a problem in that it is necessary to calculate the number of all cases in order to find adjacent clusters among clusters derived as a result of the *** solve this problem,we developed the Genetic algorithm-based Keyword Matching DBSCAN(GKM-DBSCAN)algorithm to which the genetic algorithm was applied to discover the set of adjacent clusters among the cluster results derived for each *** order to improve the performance of GKM-DBSCAN,we improved the general genetic algorithm by performing a genetic operation in *** conducted extensive experiments on both real and synthetic datasets to show the effectiveness of GKM-DBSCAN than the brute-force *** experimental results show that GKM-DBSCAN outperforms the brute-force method by up to 21 ***-DBSCAN with the index number binarization(INB)is 1.8 times faster than GKM-DBSCAN with the cluster number binarization(CNB).

关键词： Spatial clustering DBSCAN algorithm genetic algorithm textual information

来源：评论

学校读者我要写书评

暂无评论

Distribution,enrichment mechanism and risk assessment for fluoride in groundwater:a case study of Mihe-Weihe River Basin,China

引用

Frontiers of Environmental science & engineering 2023年第6期17卷 63-83页

作者： Xingyue Qu Peihe Zhai Longqing Shi Xingwei Qu Ahmer Bilal Jin Han Xiaoge Yu College of Earth Science and Engineering Shandong University of Science and TechnologyQingdao 266590China College of Safety and Environmental Engineering Shandong University of Science and TechnologyQingdao 266590China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China Department of Resource and Civil Engineering Shandong University of Science and TechnologyTai'an 271019China

Due to the unclear distribution characteristics and causes of fluoride in groundwater of Mihe-Weihe River Basin(China),there is a higher risk for the future development and utilization of ***,based on the systematic sampling and analysis,the distribution features and enrichment mechanism for fluoride in groundwater were studied by the graphic method,hydrogeochemical modeling,the proportionality factor between conventional ions and factor *** results show that the fluorine content in groundwater is generally on the high side,with a large area of medium-fluorine water(0.5–1.0 mg/L),and high-fluorine water is chiefly in the interfluvial lowlands and alluvial-marine plain,which mainly contains HCO_(3)·Cl-Na-and HCO_(3)^(-)Na-type *** vertical zonation characteristics of the fluorine content decrease with increasing depth to the water *** high flouride groundwater during the wet season is chiefly controlled by the weathering and dissolution of fluorine-containing minerals,as well as the influence of rock weathering,evaporation and *** weak alkaline environment that is rich in sodium and poor in calcium during the dry season is the main reason for the enrichment of ***,an integrated assessment model is established using rough set theory and an improved matter element extension model,and the level of groundwater pollution caused by fluoride in the Mihe-Weihe River Basin during the wet and dry seasons in the Shandong Peninsula is defined to show the necessity for local management measures to reduce the potential risks caused by groundwater quality.

关键词： Groundwater in the Mihe-Weihe River Basin Distribution characteristics of fluorine Factors influencing fluoride Enrichment mechanism of fluorine Hydrogeochemical modeling Pollution and risk assessment

来源：评论

学校读者我要写书评

暂无评论

Development of IoT-Based Smart Bin System for Effective Garbage Management 14

Development of IoT-Based Smart Bin System for Effective Garb...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Chobhare, Prachi Bagul, Gayatri Soyam, Harshad Pardeshi, Rahulkumar Pujari, Siddharaj Patane, Atul Walchand College of Engineering Computer Science and Engineering Sangli India Walchand College of Engineering Department of Computer Science and Engineering Department of Civil Engineering Sangli India

The cleanliness situation related to garbage management is rapidly declining, and it is essential to implement proper garbage management techniques to address the widespread garbage crisis, particularly in the Urban Environment. In order to address this problem, we developed a Smart Bin System for efficient waste management utilizing IoT technology. The system involves the use of sensors to detect garbage levels and Android applications for monitoring purposes. The integration of wireless technologies, micro-electromechanical systems, microservices, and the internet has given rise to IoT technology. This innovative development of an IoT-Based smart bin System for effective Garbage Management, also known as the Smart Bin, aims to keep cities clean and free from pollution. © Grenze Scientific Society, 2023.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Low-error Fixed-Width Booth Multiplier Using Approximation Of Carry Function

Journal of Applied Science and Engineering

引用

Journal of Applied science and engineering 2024年第10期28卷 1951-1961页

作者： Kumar, Ganjikunta Ganesh Khan, Sibghatullah Inyatullah Acharya, G. Prasad Kumar, Shravan S.M. Department of Electronics and Communication Engineering Sreenidhi Institute of Science and Technology Hyderabad India Department of Civil Engineering Sreenidhi Institute of Science and Technology Hyderabad India

This paper introduces an innovative solution for increasing precision of fixed-width radix-4 Booth multipliers through variable error compensation functions that leverage Approximation of Carry Function (ACF). Error compensation mechanisms typically comprise two carries-ideal and base carry functions–strategically chosen to minimize mean error. We present three distinct methods-ACF-1, ACF-2, and ACF-3—each employing fixed base values with varying column information (w) and bit lengths (N). Comparative analyses against recent studies demonstrate that our proposed fixed-width Booth multiplier using ACF-1 stands out in terms of accuracy and efficiency tradeoffs. © The Author(’s).

关键词： Error compensation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：