IF 1.8

Algorithms Pub Date : 2024-08-08 DOI: 10.3390/a17080346

M. Al-Betar, Zaid Abdi Alkareem Alyasseri, N. Al-Qazzaz, S. Makhadmeh, Nabeel Salih Ali, Christoph Guger

{"title":"EEG Channel Selection for Stroke Patient Rehabilitation Using BAT Optimizer","authors":"M. Al-Betar, Zaid Abdi Alkareem Alyasseri, N. Al-Qazzaz, S. Makhadmeh, Nabeel Salih Ali, Christoph Guger","doi":"10.3390/a17080346","DOIUrl":"https://doi.org/10.3390/a17080346","url":null,"abstract":"Stroke is a major cause of mortality worldwide, disrupts cerebral blood flow, leading to severe brain damage. Hemiplegia, a common consequence, results in motor task loss on one side of the body. Many stroke survivors face long-term motor impairments and require great rehabilitation. Electroencephalograms (EEGs) provide a non-invasive method to monitor brain activity and have been used in brain–computer interfaces (BCIs) to help in rehabilitation. Motor imagery (MI) tasks, detected through EEG, are pivotal for developing BCIs that assist patients in regaining motor purpose. However, interpreting EEG signals for MI tasks remains challenging due to their complexity and low signal-to-noise ratio. The main aim of this study is to focus on optimizing channel selection in EEG-based BCIs specifically for stroke rehabilitation. Determining the most informative EEG channels is crucial for capturing the neural signals related to motor impairments in stroke patients. In this paper, a binary bat algorithm (BA)-based optimization method is proposed to select the most relevant channels tailored to the unique neurophysiological changes in stroke patients. This approach is able to enhance the BCI performance by improving classification accuracy and reducing data dimensionality. We use time–entropy–frequency (TEF) attributes, processed through automated independent component analysis with wavelet transform (AICA-WT) denoising, to enhance signal clarity. The selected channels and features are proved through a k-nearest neighbor (KNN) classifier using public BCI datasets, demonstrating improved classification of MI tasks and the potential for better rehabilitation outcomes.","PeriodicalId":7636,"journal":{"name":"Algorithms","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification and Regression of Pinhole Corrosions on Pipelines Based on Magnetic Flux Leakage Signals Using Convolutional Neural Networks 利用卷积神经网络对基于磁通量泄漏信号的管道针孔腐蚀进行分类和回归

IF 1.8

Algorithms Pub Date : 2024-08-08 DOI: 10.3390/a17080347

Yufei Shen, Wenxing Zhou

{"title":"Classification and Regression of Pinhole Corrosions on Pipelines Based on Magnetic Flux Leakage Signals Using Convolutional Neural Networks","authors":"Yufei Shen, Wenxing Zhou","doi":"10.3390/a17080347","DOIUrl":"https://doi.org/10.3390/a17080347","url":null,"abstract":"Pinhole corrosions on oil and gas pipelines are difficult to detect and size and, therefore, pose a significant challenge to the pipeline integrity management practice. This study develops two convolutional neural network (CNN) models to identify pinholes and predict the sizes and location of the pinhole corrosions according to the magnetic flux leakage signals generated using the magneto-static finite element analysis. Extensive three-dimensional parametric finite element analysis cases are generated to train and validate the two CNN models. Additionally, comprehensive algorithm analysis evaluates the model performance, providing insights into the practical application of CNN models in pipeline integrity management. The proposed classification CNN model is shown to be highly accurate in classifying pinholes and pinhole-in-general corrosion defects. The proposed regression CNN model is shown to be highly accurate in predicting the location of the pinhole and obtain a reasonably high accuracy in estimating the depth and diameter of the pinhole, even in the presence of measurement noises. This study indicates the effectiveness of employing deep learning algorithms to enhance the integrity management practice of corroded pipelines.","PeriodicalId":7636,"journal":{"name":"Algorithms","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Parallel Machine Scheduling Problem with Different Speeds and Release Times in the Ore Hauling Operation 矿石运输作业中不同速度和释放时间的并行机器调度问题

IF 1.8

Algorithms Pub Date : 2024-08-08 DOI: 10.3390/a17080348

Luis Tarazona-Torres, Ciro Amaya, Alvaro Paipilla, Camilo Gomez, David Álvarez-Martínez

{"title":"The Parallel Machine Scheduling Problem with Different Speeds and Release Times in the Ore Hauling Operation","authors":"Luis Tarazona-Torres, Ciro Amaya, Alvaro Paipilla, Camilo Gomez, David Álvarez-Martínez","doi":"10.3390/a17080348","DOIUrl":"https://doi.org/10.3390/a17080348","url":null,"abstract":"Ore hauling operations are crucial within the mining industry as they supply essential minerals to production plants. Conducted with sophisticated and high-cost operational equipment, these operations demand meticulous planning to ensure that production targets are met while optimizing equipment utilization. In this study, we present an algorithm to determine the minimum amount of hauling equipment required to meet the ore transport target. To achieve this, a mathematical model has been developed, considering it as a parallel machine scheduling problem with different speeds and release times, focusing on minimizing both the completion time and the costs associated with equipment use. Additionally, another algorithm was developed to allow the tactical evaluation of these two variables. These procedures and the model contribute significantly to decision-makers by providing a systematic approach to resource allocation, ensuring that loading and hauling equipment are utilized to their fullest potentials while adhering to budgetary constraints and operational schedules. This approach optimizes resource usage and improves operational efficiency, facilitating continuous improvement in mining operations.","PeriodicalId":7636,"journal":{"name":"Algorithms","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Hybrid Crow Search Arithmetic Optimization Algorithm for Solving Weighted Combined Economic Emission Dispatch with Load-Shifting Practice 解决带负荷转移实践的加权组合经济排放调度的新型混合乌鸦搜索算法优化算法

IF 1.8

Algorithms Pub Date : 2024-07-16 DOI: 10.3390/a17070313

B. Dey, Gulshan Sharma, P. Bokoro

{"title":"A Novel Hybrid Crow Search Arithmetic Optimization Algorithm for Solving Weighted Combined Economic Emission Dispatch with Load-Shifting Practice","authors":"B. Dey, Gulshan Sharma, P. Bokoro","doi":"10.3390/a17070313","DOIUrl":"https://doi.org/10.3390/a17070313","url":null,"abstract":"The crow search arithmetic optimization algorithm (CSAOA) method is introduced in this article as a novel hybrid optimization technique. This proposed strategy is a population-based metaheuristic method inspired by crows’ food-hiding techniques and merged with a recently created simple yet robust arithmetic optimization algorithm (AOA). The proposed method’s performance and superiority over other existing methods is evaluated using six benchmark functions that are unimodal and multimodal in nature, and real-time optimization problems related to power systems, such as the weighted dynamic economic emission dispatch (DEED) problem. A load-shifting mechanism is also implemented, which reduces the system’s generation cost even further. An extensive technical study is carried out to compare the weighted DEED to the penalty factor-based DEED and arrive at a superior compromise option. The effects of CO2, SO2, and NOx are studied independently to determine their impact on system emissions. In addition, the weights are modified from 0.1 to 0.9, and the effects on generating cost and emission are investigated. Nonparametric statistical analysis asserts that the proposed CSAOA is superior and robust.","PeriodicalId":7636,"journal":{"name":"Algorithms","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Normalization of Web of Science Institution Names Based on Deep Learning 基于深度学习的科学网机构名称规范化

IF 1.8

Algorithms Pub Date : 2024-07-14 DOI: 10.3390/a17070312

Zijie Jia, Zhijian Fang, Huaxiong Zhang

引用次数: 0

Generating m-Ary Gray Codes and Related Algorithms 生成 m-Ary 格雷码及相关算法

IF 1.8

Algorithms Pub Date : 2024-07-13 DOI: 10.3390/a17070311

Stefka Bouyuklieva, Iliya Bouyukliev, Valentin Bakoev, Maria Pashinska-Gadzheva

引用次数: 0

Real-Time Tracking and Detection of Cervical Cancer Precursor Cells: Leveraging SIFT Descriptors in Mobile Video Sequences for Enhanced Early Diagnosis 宫颈癌前体细胞的实时跟踪和检测：利用移动视频序列中的 SIFT 描述符加强早期诊断

IF 1.8

Algorithms Pub Date : 2024-07-12 DOI: 10.3390/a17070309

J. E. Alcaraz-Chavez, A. Téllez-Anguiano, Juan C. Olivares-Rojas, R. Martínez-Parrales

{"title":"Real-Time Tracking and Detection of Cervical Cancer Precursor Cells: Leveraging SIFT Descriptors in Mobile Video Sequences for Enhanced Early Diagnosis","authors":"J. E. Alcaraz-Chavez, A. Téllez-Anguiano, Juan C. Olivares-Rojas, R. Martínez-Parrales","doi":"10.3390/a17070309","DOIUrl":"https://doi.org/10.3390/a17070309","url":null,"abstract":"Cervical cancer ranks among the leading causes of mortality in women worldwide, underscoring the critical need for early detection to ensure patient survival. While the Pap smear test is widely used, its effectiveness is hampered by the inherent subjectivity of cytological analysis, impacting its sensitivity and specificity. This study introduces an innovative methodology for detecting and tracking precursor cervical cancer cells using SIFT descriptors in video sequences captured with mobile devices. More than one hundred digital images were analyzed from Papanicolaou smears provided by the State Public Health Laboratory of Michoacán, Mexico, along with over 1800 unique examples of cervical cancer precursor cells. SIFT descriptors enabled real-time correspondence of precursor cells, yielding results demonstrating 98.34% accuracy, 98.3% precision, 98.2% recovery rate, and an F-measure of 98.05%. These methods were meticulously optimized for real-time analysis, showcasing significant potential to enhance the accuracy and efficiency of the Pap smear test in early cervical cancer detection.","PeriodicalId":7636,"journal":{"name":"Algorithms","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Messy Broadcasting in Grid 网格中的杂乱广播

IF 1.8

Algorithms Pub Date : 2024-07-12 DOI: 10.3390/a17070310

Aria Adibi, Hovhannes A. Harutyunyan

引用次数: 0

Automatic Vertical Parking Reference Trajectory Based on Improved Immune Shark Smell Optimization 基于改进的鲨鱼嗅觉免疫优化的自动垂直停车参考轨迹

IF 1.8

Algorithms Pub Date : 2024-07-11 DOI: 10.3390/a17070308

Yan Chen, Gang Liu, Longda Wang, Bing Xia

引用次数: 0

Evaluating the Expressive Range of Super Mario Bros Level Generators 评估《超级马里奥兄弟》关卡生成器的表达范围