Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…Accurate and efficient predictive disease modeling is crucial in biomedical IoT for early detection and intervention, yet existing models like LSTM and XGBoost face limitations in handling the complexity and temporal nature of health data streams. The research article addresses this gap by introducing the Temporal Adaptive Neural Evolutionary Algorithm (TANEA), a novel approach designed to enhance the predictive capabilities in biomedical IoT systems. …”
Get full text

Evaluation and Analysis of Animation Multimedia 3D Lip Synchronization considering the Comprehensive Weighted Algorithm by Zhe Xu

“…How to carry out 3D lip synchronization effectively and accurately is an important research direction in the field of multimedia. On this basis, a comprehensive weighted algorithm is introduced in this paper to sort out the related laws and the time of lip pronunciation in animation multimedia, carry out the vector weight analysis on the texts in the animation multimedia, and synthesize a matching evaluation model for 3D lip synchronization. …”
Get full text

The A3C Algorithm With Eligibility Traces of Energy Management for Plug-In Hybrid Electric Vehicles by Dingyi Guo, Guangyin Lei, Huichao Zhao, Fang Yang, Qiang Zhang

Get full text

Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…It examines the performance of a logistic regression model enhanced by Bayesian optimization for detecting TOR traffic using the UNB-CIC TOR-NonTOR datasets and a Bayesian-optimized random forest model for the CIC-Darknet2020 dataset. The research evaluates four key machine learning algorithms: Random forest, logistic regression, support vector machine (SVM), and K-nearest neighbors (K-NN). …”
Get full text

Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

“…Early detection of abnormal consumers can prevent security and financial losses. Extensive research studies have been done to detect electricity theft by analyzing customer consumption patterns. …”
Get full text

Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

Get full text

A Cluster Head Selection Algorithm for Extending Last Node Lifetime in Wireless Sensor Networks by Marcin Lewandowski, Bartłomiej Płaczek

“…Experimental results demonstrate that our method significantly extends the lifetime of the last active node compared to representative state-of-the-art algorithms. This research provides a practical and robust solution for energy-efficient WSN operation in real deployment scenarios by considering realistic and application-driven communication behavior along with hardware-level energy consumption.…”
Get full text

Electricity usage prediction using developed human evolutionary optimization algorithm and Xception neural network by Dongxian Yu, Di Wu, Chongyang Liao, Zaihui Cao, Somayeh Pouramini

“…Abstract The research paper introduces a novel technique for forecasting electricity usage by utilizing the Developed human evolutionary optimization (DHEO) algorithm and the Xception Neural Network (Xception-NN) model. …”
Get full text

Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model by Reza Tehrani, Saeed Fallahpour, Hamid Nouralidokht

“…Thoughtful and accurate manipulation techniques adopted by manipulators may not easily be detected. This research examines stock price manipulation in Tehran Stock Exchange and addresses the identification and detection of stock price manipulation by mathematical algorithm (spoof trading). …”
Get full text

Multi-Threshold Remote Sensing Image Segmentation Based on Improved Black-Winged Kite Algorithm by Yi Zhang, Xinyu Liu, Wei Sun, Tianshu You, Xin Qi

“…This paper proposes an adaptive multi-threshold image segmentation method named IBKA-OTSU to address the limitations of existing deep learning-based image segmentation methods, particularly their heavy reliance on large-scale annotated datasets and high computational complexity. The proposed algorithm significantly enhances the capability of complex remote sensing scenarios by systematic improvements to core algorithm components, including population initialization strategy, attack behavior patterns, migration mechanisms, and opposition-based learning strategy. …”
Get full text

MT-Tracker: A Phylogeny-Aware Algorithm for Quantifying Microbiome Transitions Across Scales and Habitats by Wenjie Zhu, Yangyang Sun, Weiwen Luo, Guosen Hou, Hao Gao, Xiaoquan Su

“…To address this gap, we introduce MT-tracker (microbiome transition tracker), a novel algorithm designed to capture the transitional trajectories of microbial communities. …”
Get full text

Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
Get full text

A computational framework for defining and validating reproducible phenotyping algorithms of 313 diseases in the UK Biobank by Ana Torralbo, Jonathan M. Davitte, Damien C. Croteau-Chonka, Cai Ytsma, Chris Tomlinson, Natalie K. Fitzpatrick, Sheng-Chia Chung, Ghazaleh Fatemifar, Adrian S. Cortes, Tom G. Richardson, Matthew Barclay, Julia Carrasco-Zanini, Chris Finan, Harry Hemingway, Aroon D. Hingorani, Valerie Kuan, Claudia Langenberg, Georgios Lyratzopoulos, R. Thomas Lumbers, Maik Pietzner, Anoop D. Shah, Johan H. Thygesen, Natalie Zelenka, John C. Whittaker, Margaret G. Ehm, Spiros Denaxas

Get full text

Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms by Changshou Wei, Maosheng Zhou, Zhixing Du, Lijing Han, Hao Gao

Get full text

Research on Longitudinal Intelligent Control of Autonomous-rail Rapid Tram by TANG Liang, SHEN Mengyu, XIAO Lei

Get full text

Examining the Impact of Fingerprint Vector Size on Similarity Determination and Clustering Performance of a Pattern-Based Similarity Metric by Abdulmalik Shehu Yaro, Filip Maly, Pavel Prazak

“…The correlation-based context similarity coefficient (CSC) metric is a pattern-based fingerprint similarity metric that has gained interest in fingerprint database clustering operations. …”
Get full text

Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns by Ruru Xing, ZePeng Yang, Xinghua Zhang, Yiwen Liang, Tao Yang, Fei Wang

“…Secondly, combining the Floyd-Warshall algorithm and the depth-first search algorithm, we constructed a strong connectivity effective path search algorithm to adapt to the refined traffic management situation, and identified the key road sections that have the greatest impact on the connectivity of the road network by considering the maximum acceptable level of the path and the road access constraints. …”
Get full text

PyBodyTrack: A python library for multi-algorithm motion quantification and tracking in videos by Angel Ruiz-Zafra, Janet Pigueiras-del-Real, Jose Heredia-Jimenez, Syed Taimoor Hussain Shah, Syed Adil Hussain Shah, Lionel C. Gontard

Get full text

CleanSeqU algorithm for decontamination of catheterized urine 16S rRNA sequencing data by Sung Min Yoon, Chang-Seok Ki, Ju Sun Song

“…Existing in silico decontamination algorithms face limitations in accurately identifying and removing these contaminants. …”
Get full text

Ai And Creative Research In Algerian Universities: Faculty Perspectives On Integration by Meryem Kehal

“…Qualitative content analysis was performed to identify recurring themes and patterns. The findings confirmed that AI positively impacts research creativity through advanced data analysis tools, interdisciplinary collaboration, and innovative problem-solving methodologies. …”
Get full text