Deep Learning Multi-Modal Melanoma Detection: Algorithm Development and Validation by Nithika Vivek, Karthik Ramesh

“…ResultsThe accuracy of the combined model was 88% (195/221 classified correctly) on test data from the HAM10000 dataset. Model reliability was assessed by visualizing the output activation map of each model and comparing the diagnosis patterns to that of dermatologists. …”
Get full text

Elemental Symbolism and Character Relationships in Elemental Forces of Nature: A Semiotic Approach by Erina Tri Oktaviana, Abdillah Nugroho

“…The data collection process was carried out through participant observation methods, theme notes, and symbolic analysis of visual and narrative elements. …”
Get full text

Published population pharmacokinetic models of mycophenolate sodium: a systematic review and external evaluation in a Chinese sample of renal transplant recipients by Tong Gao, Wen Xu, Xiao Li, Qie Guo, Donghua Liu, Xiaolei Zhang, Ping Leng, Jialin Sun

“…The visual prediction test results based on model simulation show that the fitting result of Model 1 was relatively good, while the distribution deviation between the observed data and the simulation data of the remaining models was large, and the fitting effect was not good.ConclusionThe published models exhibit significant variability and unsatisfactory predictive performance, indicating that therapeutic drug monitoring (TDM) remains an essential requirement for the clinical application of MPS. …”
Get full text

VPL geometry processing for open multilevel and multiscalar databases by E. Lanzara, G. Fatigati, S. Guardascione, M. T. Rapicano

“…BIM/HBIM, EM, multiplatform graphic engines): restorers and diagnosers can geolocate and annotate numerous results, observations, hypotheses or indications in geometric cells to visualize and compare heterogeneous visible and invisible structural and material data at different levels of detail. …”
Get full text

Designing an Efficient Emergency Response Airborne Mapping System with Multiple Sensors by Chaoyong Shen, Zongjian Lin, Shaoqi Zhou, Xuling Luo, Yu Zhang

“…Different types of visual and measured data, such as high-resolution orthoimages, real-time videos, accurate digital elevation models, and three-dimensional landscape maps, can enable producing effective rescue plans and aid the efficient dispatching of rescuers after disasters. …”
Get full text

Comparative evaluation of methods of monitoring of water objects, potentially dangerous for the railway track by S. Y. Zavyalov

“…For comparison purposes of the listed methods the following parameters have been chosen: efficiency of data acquisition, possibility of automatic integration into the computer, accuracy of measurements, equipment cost, the detailed assessment of the studied site according to the available data, need of presence of the specialist at measurements, data acquisition in real time, time for data updating. …”
Get full text

Identifying thermokarst lakes using deep learning and high-resolution satellite images by Kuo Zhang, Min Feng, Yijie Sui, Jinhao Xu, Dezhao Yan, Zhimin Hu, Fei Han, Earina Sthapit

“…It's the most comprehensive survey of thermokarst lakes within the region and more than 45% of these lakes were not covered by any existing lake datasets, thereby leading to a possible underestimation of the amount and effects of thermokarst lakes. Validation with visually interpreted data reported MIoU of 0.97, F1 score of 0.96, and PA of 0.97, confirming that thermokarst lakes we detected were matched very well with the reference. …”
Get full text

Le patrimoine « in silico ». Exemple de la cathédrale d’Amiens by El Mustapha Mouaddib, Guillaume Caron, Dominique Groux-Leclet, Fabio Morbidi

“…While the objective is to cover the totality of the monument, both inside and out, and to take high-resolution and photometrically-realistic measurements, each of these criteria has its own scientific pertinence and an important impact on the modus operandi and on the quantities of data to be recorded and managed. These challenges forced us to design new adapted modalities of data capture. …”
Get full text

RQdeltaCT: an open-source R package for relative quantification of gene expression using delta Ct methods by Daniel Zalewski, Anna Bogucka-Kocka

“…Furthermore, the package offers functions that cover other essential steps of analysis, including importing datasets, multistep quality control of data, numerous visualisations, and enrichment of the standard workflow with additional analyses (correlation analysis, Receiver Operating Characteristic analysis, linear and logistic regression). …”
Get full text

DEVELOPMENT OF THE CHARACTERISTICS OF THE INSTITUTIONAL ENVIRONMENT FOR THE MODELING OF SUSTAINABLE DEVELOPMENT OF REGIONS by N. A. Ivanov, I. V. Kozhushkina, M. S. Oborin, M. Yu. Sheresheva

“…The method of graphic images  is used in order to visualise the analytical data and the results.Results. …”
Get full text

A drug response prediction method for single-cell tumors combining attention networks and transfer learning by BingWei Zhou, BingWei Zhou, SiLin Sun, SiLin Sun, ShengZheng Liu, ShengZheng Liu, HaiXia Long, HaiXia Long, YuChun Li, YuChun Li

“…The model utilizes transfer learning and attention networks to predict drug responses in single-cell tumor data, after pre-training on bulk cell gene expression data. …”
Get full text

Compression of 3D Optical Encryption Using Singular Value Decomposition by Kyungtae Park, Min-Chul Lee, Myungjin Cho

“…Double random phase encryption (DRPE), which employs two distinct random phase masks, is adopted as the optical encryption technique. Since the encrypted data in DRPE have the same size as the input data and consists of complex values, a compression technique is required to improve data efficiency. …”
Get full text

A White Dwarf Catalog from LAMOST DR11 Using Deep Learning by Shengwen Zhang, Yanxia Zhang, Chao Liu

“…In recent years, the astronomical community has experienced an unprecedented influx of data from initiatives like LAMOST, the Sloan Digital Sky Survey, and Gaia. …”
Get full text

Development and Application of an Integrated Monitoring and Early Warning Platform for Land Transportation Infrastructure under Special Engineering Conditions by Liujun Zhang, Youqiang Qiu, Hui Yu, Lihua Yin, Faru Zhang, Tong Wu

“…The research results show that as the monitoring data storage analysis and early warning carrier, the integrated monitoring and early warning platform not only presents key data such as comprehensive early warning information, evaluation indicators, and monitoring elements but also realizes the intelligent, automatic, and visual presentation of monitoring data. …”
Get full text

Novel Multimodal Fusion Algorithm for Non-Intrusive Anxiety Detection by Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, M. Jamshed Alam Patwary

“…Concurrently, image data from the KDEF and CK+ datasets was processed through a Convolutional Neural Network (CNN) enhanced with a Real Gabor filter, which is particularly adept at capturing textures, edges, and complex visual patterns necessary for precise image analysis and recognition. …”
Get full text

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification by Saima Raza Zaidi, Najeed Ahmed Khan, Muhammad Abul Hasan

“…This study explores the link between the emotion “guilt” and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. …”
Get full text

Introducing multiple factor analysis (MFA) as a diagnostic taxonomic tool complementing principal component analysis (PCA) by L. Lee Grismer

“…If more than one data type is used in a PCA, the output may be biased by the data type with the largest amount of variation or statistical variance. …”
Get full text

Wear - Sediment Quantity Correlation Model for Preventive Maintenance Scheduling of a Hydroelectric Power Plant by Kleber Zhañay, Cristian Leiva, Erika Pilataxi, William Quitiaquez

“… The present research is carried out for the improvement of the availability of a hydroelectric power plant through a wear-sediment quantity correlation model for the scheduling of its preventive maintenance, the data is based on the measurement of blade thicknesses, as well as visual inspection to identify discontinuities in the water equipment, once the data has been collected, data analysis techniques can be used to evaluate the condition of the Francis turbine and determine the need for preventive maintenance under working condition. …”
Get full text

Succulent Plant Image Classification Based on Lightweight GoogLeNet with CBAM Attention Mechanism by Xingyu Tong, Zhihong Liang, Fangrong Liu

“…To further validate the model robustness, this study extends the dataset via data augmentation methods, and the experiments show that the improved model still maintains stable performance in small dataset environments, demonstrating its advantages in data-scarce scenarios. …”
Get full text

Classification of Chicken Carcass Breast Blood-Related Defects Using Hyperspectral Imaging Combined with Convolutional Neural Networks by Liukui Duan, Juanfang Bao, Hao Yang, Liuqian Gao, Xu Zhang, Shengjie Li, Huihui Wang

“…To process hyperspectral data, the Improved Firefly Band Selection Algorithm was constructed with the 1-D CNN CBD classification model as the objective function, achieving a reduction in the dimensionality of hyperspectral data. …”
Get full text