Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…This study is highly significant as it implements a deep learning model using the CNN algorithm optimized with the ResNet50 architecture. …”
Get full text

An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…Crow Search Optimization (CSO) and fractional calculus are used to create an optimal solution in the proposed crow search fractional calculus optimization (CSFCO) algorithm for deep learning. CSO is inspired by the intelligent foraging behavior of crows, and when combined with fractional calculus, it provides a robust optimization framework that improves the accuracy and efficiency of the AI model. …”
Get full text

DVCW-YOLO for Printed Circuit Board Surface Defect Detection by Pei Shi, Yuyang Zhang, Yunqin Cao, Jiadong Sun, Deji Chen, Liang Kuang

“…To address these challenges, this paper proposes a novel PCB surface defect detection algorithm, named DVCW-YOLO. First, all standard convolutions in the backbone and neck networks of YOLOv8n are replaced with lightweight DWConv convolutions. …”
Get full text

Revisiting microgenderome: detecting and cataloguing sexually unique and enriched species in human microbiomes by Zhanshan Sam Ma

“…Results Here, we fill the gap by taking advantages of a recently developed computational algorithm, species specificity, and specificity diversity (SSD) framework (refer to the companion article) to reanalyze the HMP and complementary seminovaginal microbiome datasets. …”
Get full text

The role of multispiral computed tomography in detecting and the assessment of the degree of damage of esophago-gastric junction cancer by V. N. Diomidova, A. N. Dmitrieva

“…The results of the work showed that the inclusion of MSCT with intravenous bolus contrast in the algorithm of the study of patients with suspected tumor pathology of the EGJ will improve the diagnosis of cancer of the EGJ.…”
Get full text

Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data by Bo Lu, Bo Lu, Qingyun Liu, Hao Liu, Tianxiang Long, Tianxiang Long

“…By applying the XGBoost algorithm and SHAP (SHapley Additive exPlanations), an explainable machine learning framework was established to evaluate the importance of various factors, explore the nonlinear relationships between variables and walking activity, and analyze the interaction effects among these variables.ResultsThe findings underscore the significant impact of several key factors, including the proportion of sports land, proximity to water bodies, and Normalized Difference Vegetation Index NDVI, alongside the notable influence of six distinct campus area types. …”
Get full text

Cowpea genetic diversity, population structure and genome-wide association studies in Malawi: insights for breeding programs by Michael M. Chipeta, John Kafwambira, Esnart Yohane

“…The Fixed and Random Model Circulating Probability Unification (FarmCPU) algorithm was used to identify significant MTAs.ResultsThe morphological traits showed significant genotype, location, and interaction effects. …”
Get full text

Genetic analysis of scab disease resistance in common bean (Phaseolus vulgaris) varieties using GWAS and functional genomics approaches by Shadrack Odikara Oriama, Benard W. Kulohoma, Evans Nyaboga, Y. O. Masheti, Reuben Otsyula

“…Annotation of genes proteins with significant association values was conducted using a machine learning algorithm of support vector machine on prPred using python3 on Linux Ubuntu 18.04 computing platform with an accuracy of 0.935. …”
Get full text

Mapping forest-agroforest frontiers in the Peruvian Amazon with deep learning and PlanetScope satellite data by Wanting Yang, Daniel Ortiz-Gonzalo, Xiaoye Tong, Dimitri Gominski, Rasmus Fensholt

“…To achieve this, we combine deep learning and remote sensing data, including 3-m PlanetScope satellite imagery, a Digital Elevation Model (DEM), and temporal data from the Landtrendr change detection algorithm. We conducted a sequence of modeling experiments involving different complexity of the data inputs and output classes, with overall accuracies ranging from 28.6 % to 82.9 %. …”
Get full text

An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique by Yongjun Qi, Shaohua Yang, Zhengzheng Jia, Yuanmeng Song, Jie Zhu, Xin Liu, Hongxing Zheng

“…Some experiments on datasets such as infrared small object detection (IR-SOD) and infrared small target detection 1K(IRSTD-1K), etc. have been executed to verify the proposed algorithm; and the mean average precision of 94.0% and 69% under the condition of threshold at 0.5 and over a range from 0.5 to 0.95 is obtained, respectively. …”
Get full text

Estimation of Anthocyanins in Apple Leaves Based on Ground Hyperspectral Imaging and Machine Learning Models by Yu Zhang, Mi Zou, Yanjun Li, Qingrui Chang, Xing Chen, Zhiyong Dai, Weihao Yuan

“…This study utilizes ground hyperspectral imaging to estimate anthocyanins in Fuji apple leaves in the Loess Plateau through spectral transformation, feature extraction (including band selection and spectral indices construction), and regression algorithm selection, establishing models for three growth stages. …”
Get full text

On the Twistability of Partially Coherent, Schell-Model Sources by Riccardo Borghi

“…As a nontrivial application of the algorithm developed here, the analytical determination of the spectrum of saturated twisted astigmatic Gaussian Schell-model sources is also presented.…”
Get full text

Experimental and Theoretical Study on the Failure of Sandwich Specimens with Tabs under Four-Point Bending by V. N. Paimushin, S. A. Kholmogorov, M. V. Makarov, N. V. Levshonkova

“…This method involved reducing the original boundary value problem to integro-algebraic equations with Volterra-type operators of the second kind and additional relations for determining the unknown integration constants. The algorithm of the developed method was implemented as an application software, which facilitated a series of computational experiments. …”
Get full text

Vehicle-Mounted Photovoltaic System Energy Management in Intelligent Transportation Systems: A Maximum Power Point Tracking Control by Jingao Wang, Qifei Liu, Silan Jing

“…To improve the situation, a micro-scale inverter is proposed to provide MPPT control of photovoltaic modules, which can effectively improve the output power of each photovoltaic panel. Moreover, our MPPT algorithm is applicable to cloud shadow, building shadow, and shade, and it is more suitable for the car roof. …”
Get full text

Peripheral nerve injury induces dystonia-like movements and dysregulation in the energy metabolism: A multi-omics descriptive study in Thap1+/− mice by Colette Reinhold, Susanne Knorr, Rhonda L. McFleder, Lisa Harder-Rauschenberger, Tom Gräfenhan, Andreas Schlosser, Michael Sendtner, Jens Volkmann, Chi Wang Ip

“…Phenotypic analysis using an unbiased deep learning algorithm revealed that nerve-injured Thap1+/− mice exhibited significantly more dystonia like movements (DLM) over the course of the 12-week experiment compared to naive Thap1+/− mice. …”
Get full text

Evaluating Radio Occultation (RO) Constellation Designs Using Observing System Simulation Experiments (OSSEs) for Ionospheric Specification by Nicholas Dietrich, Tomoko Matsuo, Chi‐Yen Lin, Brandon diLorenzo, Charles Chien‐Hung Lin, Tzu‐Wei Fang

“…Errors from models and EDP retrieval are realistically accounted for in this study through distinct I‐T models and by retrieving synthetic EDPs through an extension Abel inversion algorithm. OSSE assessment, using multiple metrics, finds that greater EDP spatial coverage leading to improved specification at altitudes 300 km and above, with the 520 km altitude constellations performing best due to yielding the highest observation counts. …”
Get full text

Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study by abbas Rezaianzadeh, Samane Nematolahi, maryam jalali, Shayan Rezaeianzadeh, Masoumeh Ghoddusi Johari, Seyed Vahid Hosseini

“… Background: Hypertension is a serious chronic disease and an important risk factor for many health problems. this study aimed to investigate the factors associated with hypertension using a decision-tree algorithm. Methods: this cross-sectional study was conducted in Kharameh city between 2014-2017 through census. …”
Get full text

Nonlinear association between depressive symptoms and homeostasis model assessment of insulin resistance: a cross-sectional analysis in the American population by Chunqi Jiang, Bo Wang, Yinuo Qu, Jun Wang, Xin Zhang

“…Then, we constructed a two-piece linear regression model and performed a recursive algorithm to calculate the inflection point.ResultsThe study included 20,282 participants in the United States. …”
Get full text

Predicting the infecting dengue serotype from antibody titre data using machine learning. by Bethan Cracknell Daniels, Darunee Buddhari, Taweewun Hunsawong, Sopon Iamsirithaworn, Aaron R Farmer, Derek A T Cummings, Kathryn B Anderson, Ilaria Dorigatti

“…Despite these challenges, the best performing machine learning algorithm achieved 76.3% (95% CI 57.9-89.5%) accuracy on the out-of-sample test set in predicting the infecting serotype from PRNT data. …”
Get full text

Sustainable synthesis and advanced optimization of Prosopis juliflora biomass catalyst for efficient biodiesel production and environmental impact assessment by Thota S S Bhaskara Rao, Manikandaraja Gnanaprakasam, Rajayokkiam Manimaran, Dhinesh Balasubramanian, Utku Kale, Artūras Kilikevičius

“…Abstract The present research focuses on developing an innovative biochar-based heterogeneous catalyst from Prosopis Juliflora biomass waste using response surface methodology and genetic algorithm (GA) to optimize pyrolysis parameters, achieving a 46.31% PJBC yield from 60 mg of biomass at 790 °C for 60 min. …”
Get full text