IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2024-11-16 DOI: 10.1016/j.eswa.2024.125717

Abdul Karim , Maria Mansab , Mobeen Shahroz , Muhammad Faheem Mushtaq , In cheol Jeong

{"title":"Anticipating impression using textual sentiment based on ensemble LRD model","authors":"Abdul Karim , Maria Mansab , Mobeen Shahroz , Muhammad Faheem Mushtaq , In cheol Jeong","doi":"10.1016/j.eswa.2024.125717","DOIUrl":"10.1016/j.eswa.2024.125717","url":null,"abstract":"<div><div>Twitter sentiment analysis is a natural language processing that analyzes the sentiments espoused in Twitter tweets, helping users understand others’ perspectives on specific issues or trends. The research aims to improve sentiment analysis applications across industries by optimizing machine learning models for accurate sentiment prediction in diverse textual data. The goal of this study is to make the development of strong ensemble learning models by utilizing a publicly available dataset, such as Twitter sentiment analysis through Kaggle. To carefully clean the data and remove any unnecessary information, preprocessing techniques are used. The data is divided into two sections to predict impressions: training data and testing data, and seven different machine learning methods are applied such as Naive Bayes Classifiers, Logistic Regression, Decision Trees, Support Vector Machines, Multilayer Perceptron, Gradient Boosting, three classifiers that were merged into one ensemble machine learning approach. To determine each words weight value within the text of a document, the TF-IDF technique is applied. The trained model is compared to testing data to determine how much variance exists between actual and expected values. The result is evaluated using evaluation parameters such as precision, recall, and F1 score. The maximum accuracy achieved by the ensemble LRD model is approximately 90.5 %. This study aims to enhance sentiment analysis in various industries and sentiment-based recommendation systems, by analyzing diverse texts and determining people’s perspectives.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"263 ","pages":"Article 125717"},"PeriodicalIF":7.5,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fault diagnosis in electric machines and propellers for electrical propulsion aircraft: A review 用于电力推进飞机的电机和螺旋桨的故障诊断：综述

IF 7.5 2区计算机科学

Engineering Applications of Artificial Intelligence Pub Date : 2024-11-16 DOI: 10.1016/j.engappai.2024.109577

Leonardo Duarte Milfont , Gabriela Torllone de Carvalho Ferreira , Mateus Giesbrecht

{"title":"Fault diagnosis in electric machines and propellers for electrical propulsion aircraft: A review","authors":"Leonardo Duarte Milfont , Gabriela Torllone de Carvalho Ferreira , Mateus Giesbrecht","doi":"10.1016/j.engappai.2024.109577","DOIUrl":"10.1016/j.engappai.2024.109577","url":null,"abstract":"<div><div>The present work aims to conduct an extensive literature review on the fault diagnosis and classification in electric machines, especially those with permanent magnets, for aeronautical propulsion applications. The main contribution of this research is to assess how intelligent systems focused on fault detection and diagnosis in electric propulsion systems have evolved over the past five years, what are the main types of algorithms used, and how the rapid advancement of machine learning techniques has impacted this research area. Initially, an introduction to the main diagnostic methods is provided, including techniques based on mathematical models, signal analysis, as well as the use of machine learning and deep learning. Subsequently, a detailed study of the main references found in recent years for each type of fault, whether electrical, magnetic, or mechanical, is undertaken. Regarding aeronautical applications, a study of faults in rotating blades and on coupling systems between an electric motor and a set of propellers is conducted. Throughout the text, some of the main datasets found during the research are presented. These datasets include characteristics of healthy operation and fault of windings, bearings, as well as other mechanical components that can be connected to the machine’s shaft, such as gearboxes. Finally, some statistics from this research are presented showing results regarding the annual distribution of publication of all reviewed references, the proportion of faults addressed in all articles, as well as a detailed analysis of the proportion in which each type of algorithm appears in the cited references.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"139 ","pages":"Article 109577"},"PeriodicalIF":7.5,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cooperative task assignment of heterogeneous unmanned aerial vehicles for simultaneous multi-directional attack on a moving target 异构无人飞行器合作分配任务，同时多方位攻击移动目标

IF 7.5 2区计算机科学

Engineering Applications of Artificial Intelligence Pub Date : 2024-11-16 DOI: 10.1016/j.engappai.2024.109595

Sami Shahid , Ziyang Zhen , Umair Javaid

{"title":"Cooperative task assignment of heterogeneous unmanned aerial vehicles for simultaneous multi-directional attack on a moving target","authors":"Sami Shahid , Ziyang Zhen , Umair Javaid","doi":"10.1016/j.engappai.2024.109595","DOIUrl":"10.1016/j.engappai.2024.109595","url":null,"abstract":"<div><div>Multiple unmanned aerial vehicle (UAV) attacks, on moving targets with directional priorities, need careful task allocation especially when the UAVs have variable attacking power. In addition, the constraints of simultaneous attack from different directions multi-folds the complexity of the problem. In this work, an extended contract net protocol (ECNP) based autonomous and cooperative task assignment method is proposed to deal with the time-sensitive position assignment for multi-directional attack and uniform resource allocation. Initially, an optimization problem is formulated using distances between each UAV and expected attack positions (APs), arrival time, and attack power. In addition, for uniform resource allocation, a variable is introduced to monitor available resources at a given time. An agent-based model is built with UAV information, such as position and speed, along with the direction of the high-value moving target (HVMT). Each UAV identifies the possible arrival points based on its speed constraints, and current position, and the position and velocity of HVMT. Moreover, distance and expected arrival time to all APs are computed. Finally, the agents make attack point allocations using the proposed ECNP after making a consensus about simultaneous attack time. The proposed method ensures uniform resource allocation. The simulation results show the superiority of the proposed method (ECNP) in comparison with classical contract net protocol (CNP) and Genetic Algorithms (GA) in terms of uniform resource allocation and mission accomplishment.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"139 ","pages":"Article 109595"},"PeriodicalIF":7.5,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Safe, visualizable reinforcement learning for process control with a warm-started actor network based on PI-control 利用基于 PI 控制的暖启动行为网络，为过程控制提供安全、可视化的强化学习

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-16 DOI: 10.1016/j.jprocont.2024.103340

Edward H. Bras, Tobias M. Louw, Steven M. Bradshaw

{"title":"Safe, visualizable reinforcement learning for process control with a warm-started actor network based on PI-control","authors":"Edward H. Bras, Tobias M. Louw, Steven M. Bradshaw","doi":"10.1016/j.jprocont.2024.103340","DOIUrl":"10.1016/j.jprocont.2024.103340","url":null,"abstract":"<div><div>The adoption of reinforcement learning (RL) in chemical process industries is currently hindered by the use of black-box models that cannot be easily visualized or interpreted as well as the challenge of balancing safe control with exploration. Clearly illustrating the similarities between classical control- and RL theory, as well as demonstrating the possibility of maintaining process safety under RL-based control, will go a long way towards bridging the gap between academic research and industry practice. In this work, a simple approach to the dynamic online adaptation of a non-linear control policy initialised using PI control through RL is introduced. The familiar PI controller is represented as a plane in the state-action space, where the states comprise the error and integral error, and the action is the control input. The plane was recreated using a neural network and this recreated plane served as a readily visualizable initial “warm-started” policy for the RL agent. The actor-critic algorithm was applied to adapt the policy non-linearly during interaction with the controlled process, thereby leveraging the flexibility of the neural network to improve performance. Inherently safe control during training is ensured by introducing a soft active region component in the actor neural network. Finally, the use of cold connections is proposed whereby the state space can be augmented at any stage of training (e.g., through the incorporation of measurements to facilitate feedforward control) while fully preserving the agent’s training progress to date. By ensuring controller safety, the proposed methods are applicable to the dynamic adaptation of any process where stable PI control is feasible at nominal initial conditions.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103340"},"PeriodicalIF":3.3,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kruskal Szekeres generative adversarial network augmented deep autoencoder for colorectal cancer detection. 用于结直肠癌检测的 Kruskal Szekeres 生成对抗网络增强型深度自动编码器。

IF 1.1 3区计算机科学

Network-Computation in Neural Systems Pub Date : 2024-11-16 DOI: 10.1080/0954898X.2024.2426580

Suresh Kumar Krishnamoorthy, Vanitha Cn

{"title":"Kruskal Szekeres generative adversarial network augmented deep autoencoder for colorectal cancer detection.","authors":"Suresh Kumar Krishnamoorthy, Vanitha Cn","doi":"10.1080/0954898X.2024.2426580","DOIUrl":"https://doi.org/10.1080/0954898X.2024.2426580","url":null,"abstract":"<p><p>Cancer involves abnormal cell growth, with types like intestinal and oesophageal cancer often diagnosed in advanced stages, making them hard to cure. Symptoms are like burning sensations in the stomach and swallowing difficulties are specified as colorectal cancer. Deep learning significantly impacts the medical image processing and diagnosis, offering potential improvements in accuracy and efficiency. The Kruskal Szekeres Generative Adversarial Network Augmented Deep Autoencoder (KSGANA-DA) is introduced for early colorectal cancer detection and it comprises two stages; Initial stage, data augmentation uses Affine Transform via Random Horizontal Rotation and Geometric Transform via Kruskal-Szekeres that coordinates to improve the training dataset diversity, boosting detection performance. The second stage, a Deep Autoencoder Anatomical Landmark-based Image Segmentation preserves edge pixel spatial locations, improving precision and recall for early boundary detection. Experiments validate KSGANA-DA performance and different existing methods are implemented into Python. The results of KSGANA-DA are to provide higher precision by 41%, recall by 7%, and lesser training time by 46% than compared to conventional methods.</p>","PeriodicalId":54735,"journal":{"name":"Network-Computation in Neural Systems","volume":" ","pages":"1-27"},"PeriodicalIF":1.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Private and Secure Distributed Deep Learning: A Survey 私密安全的分布式深度学习：调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-11-16 DOI: 10.1145/3703452

Corinne Allaart, Saba Amiri, Henri Bal, Adam Belloum, Leon Gommans, Aart van Halteren, Sander Klous

引用次数: 0

Predicting rapid impact compaction of soil using a parallel transformer and long short-term memory architecture for sequential soil profile encoding 利用并行变压器和长短期存储器架构进行土壤剖面顺序编码，预测土壤的快速冲击压实效果

IF 7.5 2区计算机科学

Engineering Applications of Artificial Intelligence Pub Date : 2024-11-16 DOI: 10.1016/j.engappai.2024.109664

Sompote Youwai, Sirasak Detcheewa

{"title":"Predicting rapid impact compaction of soil using a parallel transformer and long short-term memory architecture for sequential soil profile encoding","authors":"Sompote Youwai, Sirasak Detcheewa","doi":"10.1016/j.engappai.2024.109664","DOIUrl":"10.1016/j.engappai.2024.109664","url":null,"abstract":"<div><div>This study presents an advanced deep learning approach for predicting the effectiveness of Rapid Impact Compaction (RIC). The model integrates the focused attention mechanisms of transformer architectures with the sequential data processing capabilities of Long Short-Term Memory (LSTM) networks. Input parameters include the initial soil profile and feature vectors representing the soil's initial state, applied compaction effort, and compaction hammer energy. Utilizing an encoder-decoder framework, the model encodes soil profile information at various depths into tokens, which are subsequently decoded to predict the resulting ground improvement. An ablation study was conducted to assess the significance of each model component. The model's predictive accuracy was validated using field test data, demonstrating a strong correlation with observed outcomes (mean absolute error of 0.42 for test data). Shapley value analysis of the trained model revealed that compaction effort exerted the highest influence on predictions, followed by fine content and fill thickness. The model architecture also demonstrated successful application to alternative RIC case studies, indicating potential generalizability. Furthermore, the model's capability to simulate hypothetical scenarios with varying compaction efforts provides valuable insights for strategic planning and optimization of RIC project designs.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"139 ","pages":"Article 109664"},"PeriodicalIF":7.5,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A systematic literature review of recent advances on context-aware recommender systems 关于情境感知推荐系统最新进展的系统性文献综述

IF 10.7 2区计算机科学

Artificial Intelligence Review Pub Date : 2024-11-16 DOI: 10.1007/s10462-024-10939-4

Pablo Mateos, Alejandro Bellogín

{"title":"A systematic literature review of recent advances on context-aware recommender systems","authors":"Pablo Mateos, Alejandro Bellogín","doi":"10.1007/s10462-024-10939-4","DOIUrl":"10.1007/s10462-024-10939-4","url":null,"abstract":"<div><p>Recommender systems are software mechanisms whose usage is to offer suggestions for different types of entities like products, services, or contacts that could be useful or interesting for a specific user. Other ways have been explored in the field to enhance the power of these systems by integrating the context as an additional attribute. This inclusion tries to extract the user preferences more accurately taking into account multiple components such as temporal, spatial, or social ones. Notwithstanding the magnitude of context-awareness in this area, the research community is in agreement with the lack of framework for context information and how to integrate it into recommender systems. Under this premise, this paper focuses on a comprehensive systematic literature review of the state-of-the-art recommendation techniques and their characteristics to benefit from contextual information. The following survey presents the following contributions as outcomes of our study: (i) determine a framework where multiple aspects are taken into account to have a clear definition of context representation, (ii) the techniques used to incorporate context, and (iii) the evaluation of these methods in terms of reproducibility and effectiveness. Our review also covers some crucial topics about context integration, classification of the contexts, application domains, and evaluation of the used datasets, metrics, and code implementations, where we observed clear shiftings in algorithmic and evaluation trends towards Neural Network approaches and ranking metrics, respectively. Just as importantly, future research opportunities and directions are exposed as final closure, standing out the exploitation of various data sources and the scalability and customization of existing solutions.</p></div>","PeriodicalId":8449,"journal":{"name":"Artificial Intelligence Review","volume":"58 1","pages":""},"PeriodicalIF":10.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10462-024-10939-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FPAA-based control of a high-speed flexure-guided AFM nanopositioner 基于 FPAA 的高速挠性制导 AFM 纳米定位器控制技术

IF 3.1 3区计算机科学

Mechatronics Pub Date : 2024-11-16 DOI: 10.1016/j.mechatronics.2024.103268

Erfan Khodabakhshi, S.O. Reza Moheimani

{"title":"FPAA-based control of a high-speed flexure-guided AFM nanopositioner","authors":"Erfan Khodabakhshi, S.O. Reza Moheimani","doi":"10.1016/j.mechatronics.2024.103268","DOIUrl":"10.1016/j.mechatronics.2024.103268","url":null,"abstract":"<div><div>This paper presents the design, characterization, and control of a novel flexure-guided piezoelectrically actuated atomic force microscope (AFM) nanopositioner. The planar scanner achieves a scan range of <span><math><mrow><mn>5</mn><mo>.</mo><mn>8</mn><mo>,</mo><mi>μ</mi><mi>m</mi></mrow></math></span> in both X- and Y-directions with a first resonance frequency above <span><math><mrow><mn>15</mn><mspace></mspace><mi>kHz</mi></mrow></math></span>. Lateral displacements are measured using an interferometer sensor. A signal-transformation-based control technique and a signal pre-shaping method are explored to enhance raster scanning. An integral resonant controller (IRC) increases closed-loop bandwidth by damping the scanner’s fast axis dominant mode. Since the high-bandwidth system requires a high sampling rate, the IRC scheme is implemented using a field-programmable analog array (FPAA). The tracking performance is improved by a double integrator. The effectiveness of the signal transformation approach (STA) with the pre-shaping method in the closed-loop system is investigated. Tracking errors at frequencies from <span><math><mrow><mn>10</mn><mspace></mspace><mi>Hz</mi></mrow></math></span> to <span><math><mrow><mn>300</mn><mspace></mspace><mi>Hz</mi></mrow></math></span> maintained RMS values below <span><math><mrow><mn>50</mn><mspace></mspace><mi>nm</mi></mrow></math></span>. Results demonstrate the technique’s success, achieving rapid time-lapse AFM imaging at 10 frames per second over a <span><math><mrow><mn>2</mn><mspace></mspace><mi>μ</mi><mi>m</mi><mo>×</mo><mn>2</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> scan area.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"104 ","pages":"Article 103268"},"PeriodicalIF":3.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CATNet: A Cross Attention and Texture-Aware Network for Polyp Segmentation CATNet：用于息肉分割的交叉注意和纹理感知网络

IF 3 4区计算机科学

International Journal of Imaging Systems and Technology Pub Date : 2024-11-16 DOI: 10.1002/ima.23220

Zhifang Deng, Yangdong Wu

{"title":"CATNet: A Cross Attention and Texture-Aware Network for Polyp Segmentation","authors":"Zhifang Deng, Yangdong Wu","doi":"10.1002/ima.23220","DOIUrl":"https://doi.org/10.1002/ima.23220","url":null,"abstract":"<div>\u0000 \u0000 <p>Polyp segmentation is a challenging task, as some polyps exhibit similar textures to surrounding tissues, making them difficult to distinguish. Therefore, we present a parallel cross-attention and texture-aware network to address this challenging task. CATNet incorporates the parallel cross-attention mechanism, Residual Feature Fusion Module, and texture-aware module. Initially, polyp images undergo processing in our backbone network to extract multi-level polyp features. Subsequently, the parallel cross-attention mechanism sequentially captures channel and spatial dependencies across multi-scale polyp features, thereby yielding enhanced representations. These enhanced representations are then input into multiple texture-aware modules, which facilitate polyp segmentation by accentuating subtle textural disparities between polyps and the background. Finally, the Residual Feature Fusion module integrates the segmentation results with the previous layer of enhanced representations. This process serves to eliminate background noise and enhance intricate details. We assess the efficacy of our proposed method across five distinct polyp datasets. On three unseen datasets, CVC-300, CVC-ColonDB, and ETIS. We achieve mDice scores of 0.916, 0.817, and 0.777, respectively. Experimental results unequivocally demonstrate the superior performance of our approach over current models. The proposed CATNet addresses the challenges posed by textural similarities, setting a benchmark for future advancements in automated polyp detection and segmentation.</p>\u0000 </div>","PeriodicalId":14027,"journal":{"name":"International Journal of Imaging Systems and Technology","volume":"34 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

计算机科学最新文献