Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…<h4>Methods</h4>Data from the 1993-94 to 2017-18 Bangladesh Demographic and Health Survey (BDHS) was analyzed using advanced machine learning algorithms. Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
Get full text

Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…To accomplish this goal, we have proposed an integrated system which encompasses the use of machine learning (ML) algorithms. This hybrid model is aimed at linking various activities to VAK model of learning and hence place students in their various class learning preferences derived from their activities and the patterns created during the learning processes. …”
Get full text

Two-Echelon Multidepot Logistics Network Design with Resource Sharing by Siyu Luo, Yong Wang, Jinjun Tang, Xiangyang Guan, Maozeng Xu

“…Integrating a customer clustering algorithm, a greedy algorithm, and an improved nondominated sorting genetic algorithm-II (Im-NSGA-II), a hybrid method is then designed to handle the 2E-CMDPDTW model. …”
Get full text

Elastic Optimization for Stragglers in Edge Federated Learning by Khadija Sultana, Khandakar Ahmed, Bruce Gu, Hua Wang

“…We customize a benchmark algorithm, FedAvg, to obtain a new elastic optimization algorithm (FedEN) which is applied in local training of edge devices. …”
Get full text

Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
Get full text

Designing and planning a bioethanol supply chain network under uncertainty using a data-driven robust optimization model under disjunctive uncertainty sets by Farzaneh MansooriMooseloo, Maghsoud Amiri, Mohammad Taghi Taghavi Fard, Mostafa Hajiaghaei-Keshteli

“…Therefore, the aim of this study is to design and optimize the biomass-to-bioethanol supply chain network using data-driven robust optimization methods and disjunctive uncertainty sets.Methodology: The methodology of this study is a multi-methodology approach based on mathematical modeling and machine learning algorithms. Initially, uncertainty sets for the non-deterministic model parameter were created using K-means and SVC methods. …”
Get full text

Multi-Criteria Assessment of Flood Risk on Railroads Using a Machine Learning Approach: A Case Study of Railroads in Minas Gerais by Fernanda Oliveira de Sousa, Victor Andre Ariza Flores, Christhian Santana Cunha, Sandra Oda, Hostilio Xavier Ratton Neto

“…This case study uses a combination of the multi-criteria analysis approach and hydrological studies that use machine learning algorithms to simulate new rainfall events in order to estimate the risk of flooding on railroads. …”
Get full text

MetaQ: fast, scalable and accurate metacell inference via single-cell quantization by Yunfan Li, Hancong Li, Yijie Lin, Dan Zhang, Dezhong Peng, Xiting Liu, Jie Xie, Peng Hu, Lu Chen, Han Luo, Xi Peng

“…Abstract To overcome the computational barriers of analyzing large-scale single-cell sequencing data, we introduce MetaQ, a metacell algorithm that scales to arbitrarily large datasets with linear runtime and constant memory usage. …”
Get full text

Monitoring Soil Salinity in Arid Areas of Northern Xinjiang Using Multi-Source Satellite Data: A Trusted Deep Learning Framework by Mengli Zhang, Xianglong Fan, Pan Gao, Li Guo, Xuanrong Huang, Xiuwen Gao, Jinpeng Pang, Fei Tan

“…The study applied four types of feature selection algorithms: Random Forest (RF), Competitive Adaptive Reweighted Sampling (CARS), Uninformative Variable Elimination (UVE), and Successive Projections Algorithm (SPA). …”
Get full text

Generative ecodesign for mechanical products: A design workflow by Amos Wei Lun Lee, Kevin Kai Wern Seah, Bing Feng Ng, Ee Teng Zhang, Wen Feng Lu, Jonathan Sze Choong Low

“…This workflow combines generative design algorithms, typically used for geometry lightweighting, with life cycle thinking. …”
Get full text

A Novel Semi-Supervised Learning Method Based on Fast Search and Density Peaks by Fei Gao, Teng Huang, Jinping Sun, Amir Hussain, Erfu Yang, Huiyu Zhou

“…Under the condition of sufficiently labeled samples, recognition algorithms can achieve good classification results. …”
Get full text

FusionScan: accurate prediction of fusion genes from RNA-Seq data by Pora Kim, Ye Eun Jang, Sanghyuk Lee

“…Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. …”
Get full text

Enhancing Chronic Disease Prediction in IoMT-Enabled Healthcare 5.0 Using Deep Machine Learning: Alzheimer&#x2019;s Disease as a Case Study by Rabia Javed, Tahir Abbas, Tariq Shahzad, Khadija Kanwal, Sadaqat Ali Ramay, Muhammad Adnan Khan, Khmaies Ouahada

“…Deep machine learning algorithms have found widespread application in the diagnosis of chronic diseases. …”
Get full text

Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…Based on these results, a hybrid mode of merging algorithms based on weather radiation conditions is proposed. …”
Get full text

Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.…”
Get full text

Microwave sea ice and ocean brightness temperature and emissivity between 22 and 243 GHz from ship-based radiometers by Janna E. Rückert, Andreas Walbröl, Nils Risse, Pavel Krobot, Rainer Haseneder-Lind, Mario Mech, Kerstin Ebell, Gunnar Spreen

“…Our results can improve the characterization of surface emissions in satellite retrieval algorithms.…”
Get full text

A Novel Active Learning Technique for Fetal Health Classification Based on XGBoost Classifier by Kaushal Bhardwaj, Niyati Goyal, Bhavika Mittal, Vandna Sharma, Shiv Naresh Shivhare

“…The application of machine learning algorithms in monitoring fetal health helps to improve the chances of timely intervention and better outcomes in the event of any possible health issues in fetuses. …”
Get full text

Energy-aware feature and classifier for behaviour recognition of laying hens in an aviary system by X. Yang, Q. Hu, L. Nie, C. Wang

“…The study might provide insights into developing onboard behaviour recognition algorithms for laying hens.…”
Get full text

Stem and Leaf Segmentation and Phenotypic Parameter Extraction of Tomato Seedlings Based on 3D Point by Xuemei Liang, Wenbo Yu, Li Qin, Jianfeng Wang, Peng Jia, Qi Liu, Xiaoyu Lei, Minglai Yang

“…The RANSAC, region-growing, and greedy projection triangulation algorithms were employed to extract phenotypic parameters such as plant height, stem thickness, leaf area, and leaf inclination angle. …”
Get full text

Monitoring Interannual Variability in Spatial Distribution of Plastic-Mulched Farmland in Black Soil Areas Using Google Earth Engine by Jingfa Zhong, Dongmei Ji, Lei Chang, Yuefen Li

“…The key features and combinations were optimized, and then the MRFPS algorithm was used to minimize the impact of cloud contamination and map the distribution of PMF. …”
Get full text