Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model by Kanti Rongali Divya, Rao Gottapu Sasibhushana, Aruna Singam

“…Therefore, the TLD classification and identification model is developed to solve the above problems. …”
Get full text

Baseline filtering and peak reconstruction for haloscope-like axion searches by A. Gallo Rosso, J. Conrad, J. Jeong

“…For haloscopes, the problem reduces to the identification of a peak above a noisy baseline. Its modeling, however, may be problematic. …”
Get full text

Fault Management in Speed Control Systems of Hydroelectric Power Plants Through Petri Nets Modeling: Case Study of the Alazán Power Plant, Ecuador by Cristian Fernando Valdez-Zumba, Luis Fernando Guerrero-Vásquez

“…Traditional diagnostic approaches often rely on manual inspection and expert intuition, and they lack formal mechanisms to model concurrent or asynchronous system behavior—leading to delays and reduced accuracy in fault identification. …”
Get full text

A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…These findings highlight the model’s adaptability and efficiency, offering a secure, scalable, and resilient solution for decentralized networks while addressing critical challenges in trust and reputation management.…”
Get full text

Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Introduction Over the past few decades, the identification of geochemical anomalies has played an important role in mineral exploration (Coates et al., 2011; Lecun et al., 2015; Bergen et al., 2019) Various methods have been used to identify geochemical anomalies in the last few decades, including statistical analysis, geostatistical approaches (Nabavi, 1976), fractal modeling (Ziaii et al., 2009; Ziaii et al., 2012) and many other methods. …”
Get full text

An Improved Model for Detecting the Presence of Pesticide Residues in Edible Parts of Tomatoes, Cabbages, Carrots, and Green Pepper Vegetables Using Batch Image Analysis by Nabaasa, Evarist, Natumanya, Deborah, Mabirizi, Vicent

“…Our results highlight the potential influence of this model on agricultural food safety practices by indicating that it can be used for the quick and extensive identification of pesticide residues. …”
Get full text

Recovery in personality disorders: the development and preliminary testing of a novel natural language processing model to identify recovery in mental health electronic records by Giouliana Kadra-Scalzo, Jaya Chaturvedi, Oliver Dale, Richard D. Hayes, Lifang Li, Shaza Mahmood, Jonathan Monk-Cunliffe, Angus Roberts, Paul Moran

“…However, the models performed less acceptably in correctly identifying all those who recovered, generally missing at least 50% of the population of those who had recovered.ConclusionIt is feasible to develop NLP models for the identification of recovery domains for individuals with a diagnosis of personality disorder. …”
Get full text

Structural Damage Detection Using an Unmanned Aerial Vehicle-Based 3D Model and Deep Learning on a Reinforced Concrete Arch Bridge by Mary C. Alfaro, Rodrigo S. Vidal, Rick M. Delgadillo, Luis Moya, Joan R. Casas

“…These networks are effective in detecting complex patterns, improving the accuracy and efficiency of damage identification based on simple visual inspection. …”
Get full text

Construction and validation of a nomogram prediction model for antiviral efficacy based on clinical characteristics and intestinal microflora distribution in patients with chronic... by Hongjie Wu, Mingqiang Yue, Tianbao Wang, Xiaoxia Wei, Yanping Wang, Changyun Si

“…In the training set, multivariate logistic regression was used to analyze the risk factors for the failure of antiviral therapy and the nomogram prediction model was constructed. The ROC curve and calibration curve were drawn to evaluate the prediction efficiency of the nomogram model and were verified in the verification set.ResultsThere was no significant difference in the incidence, clinical characteristics and distribution parameters of intestinal flora between the training set and the verification set (p > 0.05). …”
Get full text

MSKd_Net: Multi-Head Attention-Based Swin Transformer for Kidney Diseases Classification by H. Sharen, Modigari Narendra, L. Jani Anbarasi

“…The MSKd_Net architecture integrates Swin Transformer-based hierarchical learning, efficiently capturing both local and global features, along with a customized convolved model enhanced with a multi-head attention layer. …”
Get full text

A deep learning model based on self-supervised learning for identifying subtypes of proliferative hepatocellular carcinoma from dynamic contrast-enhanced MRI by Hui Qu, Shuairan Zhang, Xuedan Li, Yuan Miao, Yuxi Han, Ronghui Ju, Xiaoyu Cui, Yiling Li

“…The model analyzes temporal and spatial patterns in DCE-MRI data to identify the proliferative subtype efficiently and accurately. …”
Get full text

DeepB3P: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN by Qiang Tang, Wei Chen

“…Methods: A transformer-based deep learning model, DeepB3P, was proposed for predicting BBBP. …”
Get full text

LiSA-MobileNetV2: an extremely lightweight deep learning model with Swish activation and attention mechanism for accurate rice disease classification by Yongqi Xu, Dongcheng Li, Changcheng Li, Zheming Yuan, Zhijun Dai

“…In the context of intelligent agriculture in China, rapid and accurate identification of crop diseases is essential for ensuring food security and improving crop yield. …”
Get full text

Associations between perceived stress profiles, social connection and work engagement in clinical registered nurses: a mediation analysis and generalized additive models by Yuan Liao, Miaochun Huang, Zhimin Gu, Chun Li, Yan Yu, Qimei Zhang, Xiangyu Lai, Jialin Liu, Kang He, Huiyun Chu, Yao Zhao, Xinyu Wu, Lihua Wu, Yu Li, Sujuan Fang

“…Statistical analyses were performed utilizing latent profile examination, mediation analysis and generalized additive models. Results (1) The analysis revealed heterogeneity in stress levels among nurses, resulting in the identification of three distinct groups: low stress-high self-demand group (23.4%), high tension-low out-of-control group (57.5%), and high stress-low efficiency group (18.2%). (2) Clinical registered nurses that obtained support from their families were more inclined to be placed in the Low stress-high self-demand group. (3) Social connection significantly mediated the relationship between nurses’ work engagement and perceived stress. (4) Work engagement demonstrated a non-linear relationship with both perceived stress and social connection. …”
Get full text

Qin Seal Script Character Recognition with Fuzzy and Incomplete Information by Yun Ou, Zhen-Jie Zhou, Di-Wen Kang, Pan Zhou, Xue-Wei Liu

“… The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. …”
Get full text

Quantifying the State of the Art of Electric Powertrains in Battery Electric Vehicles: Comprehensive Analysis of the Two-Speed Transmission and 800 V Technology of the Porsche Tayc... by Nico Rosenberger, Nicolas Wagner, Alexander Fredl, Linus Riederle, Markus Lienkamp

“…In addition to providing researchers with this study’s results, all data utilized in this study will be made available as open-access, enabling individual use of test data for parameter identification and the development of simulation models.…”
Get full text

Assessment of potential for economic growth and development of regions of Siberian Federal District by A. E. Demyanenko

“…The assessment of the level of efficiency of the regional economy and identification of reserves of regional economies of the Siberian Federal District is based on determining the level of potential for socio-economic development of the regions and determining the calculated characteristics of gross regional product on the basis of economic and mathematical modeling. …”
Get full text

An experimental study on flow induced motion and energy harvesting of cylinders with different cross sections by Ronglai Song, Peng Xu, Peng Xu, Changqing Jiang, Yuan Zhang, Yuan Zhang, He Li, He Li

“…Under equivalent conditions, the Circular-T-shaped oscillator demonstrates superior energy conversion capacity compared to existing models, with the galloping branch being the most efficient for energy conversion; the peak efficiency is 24.5% (Ur = 14.5). …”
Get full text

A two-stage model for enhanced mango leaf disease detection using an innovative handcrafted spatial feature extraction method and knowledge distillation process by Mohammad Manzurul Islam, Mst. Nasrat Jahan Niva, Abdullahi Chowdhury, Saleh Masum, Rifat Ara Shams, Taskeed Jabid, Md. Sawkat Ali, Md. Mostofa Kamal Rasel, Muhammad Firoz Mridha

“…In the second stage, we introduce a Knowledge Distillation (KD) process to further enhance model performance by transferring knowledge from a larger teacher model to a smaller student model. …”
Get full text

Robotic training complex by Yu. N. Matrunchyk

“…It is proposed to solve the following problems: development of a robotic training complex (hereinafter – RTС), its simulation and mathematical model; identification and optimization of the model; development of an electrical circuit diagram of the RTС; creation of a simulation model of the manipulator; development of a training and methodological complex for training personnel in the basics of designing and programming industrial manipulators with equipment for production tasks of varying complexity. …”
Get full text