On the Development of a Sense and Avoid System for Small Fixed-Wing UAV by Bruno M. B. Pedro, André C. Marta

“…A collision avoidance algorithm utilizing the Vector Field Histogram method was implemented to process sensor data and generate real-time trajectory corrections. …”
Get full text

BOLT LOOSENING ANGLE DETECTION METHOD BASED ON COLOR SEGMENTATION by KANG Jingjie, ZHANG Lijun, SUN Yuandong, YANG Xiaoyu, WANG Ruolan, ZHAO Tianhao

“…Then, the orientation vector of the connected domain in the anti-loose line image was determined by computing the geometric moments. …”
Get full text

Dynamic Analysis and Scale Optimization of Prefabricated Building Wall Panel Installation by Jiang Mingyang, Zhang Lin, Liu Hongbin, Sima Mingyang, Yu Ningtao

Get full text

An association rule-based approach for frequent item mining of multi-stage access data by Silong Wu

“…Abstract The processing of large-scale datasets is complex and requires high efficiency. …”
Get full text

Biochemical and physiological characterization of Aedes aegypti midgut chymotrypsin by Abigail G. Ramirez, Jun Isoe, Mateus Sá Magalhães Serafim, Daniel Fong, My Anh Le, James T. Nguyen, Olive E. Burata, Rachael M. Lucero, Rebecca K. Spangler, Alberto A. Rascón

“…Thus, elucidating the activity and specific roles of all midgut proteases will help understand the complexity of the digestion process and help validate them as potential targets for the development of a new vector control strategy. …”
Get full text

Optimized SVR model for predicting dissolved oxygen levels using wavelet denoising and variable reduction: Taking the Minjiang River estuary as an example by Peng Zhang, Xinyang Liu, Huiru Zhang, Chengchun Shi, Gangfu Song, Lei Tang, Ruihua Li

“…The integrated WD-MIC data processing method shows promising potential in reducing model errors and lowering water monitoring costs by focusing on highly correlated variables.…”
Get full text

Hardware Implementation for Triaxial Contact-Force Estimation from Stress Tactile Sensor Arrays: An Efficient Design Approach by María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín, José A. Hidalgo-López

“…This paper presents a contribution to the state of the art in the design of tactile sensing algorithms that take advantage of the characteristics of generalized sparse matrix-vector multiplication to reduce the area, power consumption, and data storage required for real-time hardware implementation. …”
Get full text

Enhancing Brain Tumor Detection on MRI Images Using an Innovative VGG-19 Model-Based Approach by Burhan Ergen, Abdullah Şener

Get full text

Wind Turbine Blade Fault Detection Method Based on TROA-SVM by Zhuo Lei, Haijun Lin, Xudong Tang, Yong Xiong, He Wen

“…This method integrates the Tyrannosaurus Optimization Algorithm (TROA) with a support vector machine (SVM), aiming to enhance the accuracy and reliability of fault detection. …”
Get full text

A Study on Denoising Autoencoder Noise Selection for Improving the Fault Diagnosis Rate of Vibration Time Series Data by Jun-gyo Jang, Soon-sup Lee, Se-Yun Hwang, Jae-chul Lee

“…The fault diagnosis rates were calculated using One-Class Support Vector Machines (OC-SVM) for performance comparison. …”
Get full text

Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…To this purpose, the integration of advanced machine learning algorithms such as cosine similarity, support vector machine, and Naive Bayes improves recommendation systems with sentiment analysis. …”
Get full text

Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…In this paper, we introduce a novel imbalanced learning approach named Imbalanced Maximizing-Area Under the Curve (AUC) Proximal Support Vector Machine (ImAUC-PSVM), which harnesses the foundational principles of traditional PSVM for the detection of CVDs. …”
Get full text

Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…Edge computing allows to do AI processing on devices with limited resources, but the challenge remains high computational costs followed by the energy limitations of such devices making on-device machine learning inefficient, especially for Support Vector Machine (SVM) classifiers. …”
Get full text

Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

Get full text

Urban growth simulation using cellular automata model and machine learning algorithms (case study: Tabriz metropolis) by Omid Ashkriz, Babak Mirbagheri, Ali Akbar Matkan, Alireza Shakiba

“…To prevent over-fitting of algorithms to training samples and to obtain optimistic results, in the process of extracting optimal parameters of machine learning algorithms, the spatial cross-validation method was used to reduce the spatial correlation between training and test data.Results and discussion: The results showed that the random forest algorithm with the area under the ROC curve of 0.9228 compared to the support vector machine and multilayer perceptron neural network algorithms with 0.8951 and 0.8726, respectively, had a better performance in estimating the change potential of non-urban to urban areas. …”
Get full text

Using the ASTER GDEM v.2 global digital elevation model to identify areas of possible activation of karst processes in the Arkhangelsk region (Russia) by E.V. Polyakova, Y.G. Kutinov, A.L. Mineev, Z.B. Chistova, T.Ya. Belenovich

“…Hydrological correction of the digital elevation model of the Arkhangelsk region (based on ASTER GDEM v.2) was performed. A vector layer of depressions in the region was obtained. …”
Get full text

BCLH2Pro: A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Thanadol Tuntiwongwat, Sippawit Thammawiset, Thongchai Rohitatisha Srinophakun, Chawalit Ngamcharussrivichai, Somboon Sukpancharoen

“…This study optimizes biomass chemical looping processes (BCLpro), a technique for converting biomass to energy, through machine learning (ML) for sustainable energy production. …”
Get full text

Impact of a typical scanner delay processing parameter on local microstructure in metallic laser-based powder bed fusion by Brenda Leticia Valadez Mesta, Pascal Thome, Marcus C. Lam, Sammy Tin, Jorge Mireles, Ryan B. Wicker

“…In laser-based powder bed fusion of metals (PBF-LB/M), variations in laser scanner movements, particularly lesser-studied parameters like scanner delays that control laser directional changes, can influence the microstructure in a part during fabrication as each of typically millions of individual laser vectors impact part thermal history and resulting microstructure. …”
Get full text

Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses by Esra Imamoglu

“…This review examines the increasing application of artificial intelligence (AI) and/or machine learning (ML) in microalgae processes, focusing on their ability to improve production efficiency, yield, and process control. …”
Get full text

(In)acceptabilités environnementales et/ou sanitaires : dilemmes autour de la démoustication du littoral méditerranéen français by Elise Mieulet, Cécilia Claeys

“…Through a case study addressing mosquito and vector control policies in Metropolitan France, this paper stresses the need to deconstruct the normalisation and standardisation processes at work in the manufacturing of social acceptability. …”
Get full text