Presenting a Quantum Leadership Model to Establish Organizational Civilization in the Iranian Higher Education System by reza heydari, hamidreza rezaeekelidbari, musa chaman zamin

“…If the source of developments and changes does not base its priority on order, politeness, ethics, and social justice, it will certainly deviate from its main path and goal; and achieving predetermined perspectives will be out of reach. Therefore, in this research, we seek to answer the question: what is the quantum leadership model for establishing organizational civilization in the Iranian higher education system? …”
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Deep Learning Classification of Systemic Sclerosis Skin Using the MobileNetV2 Model by Metin Akay, Yong Du, Cheryl L. Sershen, Minghua Wu, Ting Y. Chen, Shervin Assassi, Chandra Mohan, Yasemin M. Akay

“…Machine learning algorithms, especially deep learning, have been found to be greatly useful in biology, medicine, healthcare, and biomedical applications, in the areas of medical image processing and speech recognition. However, the need for a large training data set and the requirement for a graphics processing unit (GPU) have hindered the wide application of machine learning algorithms as a diagnostic tool in resource-constrained environments (e.g., clinics). …”
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DETERMINATION OF HYDRODYNAMIC CHARACTERISTICS OF A RADIO-CONTROLLED AIRPLANE MODEL WITH AIR CUSHION LANDING GEAR by Yu. Yu. Merzlikin

“…The experimental data of the real aircraft Dingo, LMS, An-26, C-130 Hercules (size, weight, thrust) parameters were processed. Tests were carried out, using the standard testbed, utiliz- ing the dynamically-corresponding models in the water tank. …”
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A complex roadside object detection model based on multi-scale feature pyramid network by Zhihao Zheng, Jianguang Zhao, Jingjing Fan, Ruirui Bai, Jiana Zhao, Jianan Liu

“…Additionally, a novel C3FB structure (Efficient Fusion of C3 modules and FocalNextBlock structure) is introduced to replace the C2f module in the neck network of YOLOv8, aiming to reduce the parameter count while enhancing model accuracy. Combining the weighted Bi-directional Feature Pyramid Network (BCFPN) for feature fusion incorporates deep, shallow, and original features, reinforces feature integration, minimizes information loss during convolution processes, and enhances target detection accuracy. …”
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Computational Modeling of Ganglion Cell Bicolor Opponent Receptive Fields and FPGA Adaptation for Parallel Arrays by Hui Wei, Wenbo Yao

“…The Artix-7 family of xc7a200tsbv484-1 FPGAs can reach a maximum frequency of 200 MHz and a maximum parallelism of 600, and a single receptive field model consumes only 0.142 W of power. …”
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Hybrid GRU–Random Forest Model for Accurate Atmospheric Duct Detection with Incomplete Sounding Data by Yi Yan, Linjing Guo, Jiangting Li, Zhouxiang Yu, Shuji Sun, Tong Xu, Haisheng Zhao, Lixin Guo

“…Atmospheric data forecasting traditionally relies on physical models, which simulate atmospheric motion and change by solving atmospheric dynamics, thermodynamics, and radiative transfer processes. …”
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A geospatial modelling approach integrating archaeobotany and genetics to trace the origin and dispersal of domesticated plants. by Jacob van Etten, Robert J Hijmans

“…The consilience reached by the model is the extent to which it converges around solutions optimal for both archaeobotanical and genetic data. …”
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Lightweight pose estimation spatial-temporal enhanced graph convolutional model for miner behavior recognition by WANG Jianfang, DUAN Siyuan, PAN Hongguang, JING Ningbo

“…Experimental results showed that: ① The parameter count of MEST-GCN was reduced to 1.87 Mib. ② On the public NTU60 dataset, evaluated using cross subject and cross view standards, the accuracy of the miner behavior recognition model based on Lite-HRNet and MEST-GCN reached 88.0% and 92.6%, respectively, with Lite-HRNet extracting 2D human keypoint coordinates. ③ On a custom-built miner behavior dataset, the model based on Lite-HRNet and MEST-GCN achieved an accuracy of 88.5% and a video processing speed of 18.26 frames per second, accurately and quickly identifying miner action categories.…”
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Modelling the mitigation of anti-vaccine opinion propagation to suppress epidemic spread: A computational approach. by Sarah Alahmadi, Rebecca Hoyle, Michael Head, Markus Brede

“…In a coupled agent-based model that consists of opinion and disease diffusion processes, we explore and compare different heuristics to design positive campaigns based on the network structure and local presence of negative vaccine attitudes. …”
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Fitting nonlinear double sigmoid models to macauba fruit growth data using Bayesian inference by Edilene Cristina Pedroso Azarias, Natiele de Almeida Gonzaga, Édipo Menezes da Silva, Edilson Marcelino Silva, Tales Jesus Fernandes, Joel Augusto Muniz

“…We used Bayesian inference to estimate the parameters of the nonlinear double logistic and double Gompertz regression models to find the model that best describes the data. …”
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Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. by Jörn Diedrichsen, Nikolaus Kriegeskorte

“…Representational models specify how activity patterns in populations of neurons (or, more generally, in multivariate brain-activity measurements) relate to sensory stimuli, motor responses, or cognitive processes. …”
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Predictive Modeling of Credit Card Rejection Using Machine Learning Algorithms: A Comparative Study by Shengyu Gu

“…The results of the training phase depict that the RFPO model reached an accuracy of 0.971, proving to be a vital model in predictive skills. …”
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Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease by Hanyu Luo, Benlong Wang, Rui Cao, Jun Feng

“…Additionally, decision curve analysis highlighted that both decision trees and XGBoost models achieved higher net benefits within the majority of threshold ranges, emphasizing their significant potential in clinical decision-making processes. …”
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Embedded Systems Technologies Using IoT and Wireless Sensor Networks in Semi-Real-Time Modeling by T.A. Samoliuk

“…A description of the semi-real-life modeling of the healthcare system for chronically ill patients using embedded IoT systems technologies is provided. …”
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Streamflow Prediction in Human‐Regulated Catchments Using Multiscale Deep Learning Modeling With Anthropogenic Similarities by Arken Tursun, Xianhong Xie, Yibing Wang, Dawei Peng, Yao Liu, Buyun Zheng, Xinran Wu, Cong Nie

“…Abstract Accurate streamflow prediction in human‐regulated catchments remains a formidable challenge due to the complex disturbance of hydrological processes. To consider human disturbance in hydrological modeling, this study introduces a novel static attribute collection that combines river‐reach attributes with catchment attributes, referred to as multiscale attributes. …”
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GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling by Xin Wang, Changchun Li, Chenyi Zhao, Yinghua Jiao, Hengmao Xiang, Xifang Wu, Huabin Chai

“…Ablation experiments validate the effectiveness of the proposed methods.Compared with classic models such as Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, the GrainNet model achieves better detection performance and computational efficiency in various scenarios and adhesion levels. …”
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A Radiomic-based model to predict the depth of myometrial invasion in endometrial cancer on ultrasound images by Francesca Arezzo, Annarita Fanizzi, Rosanna Mancari, Emiliano Cocco, Samantha Bove, Maria Colomba Comes, Mariangela Gianciotta, Giorgia Lanza, Salvatore Lopez, Gerardo Cazzato, Erica Silvestris, Elsa Vitale, Enrico Vizza, Gennaro Cormio, Raffaella Massafra, Vera Loizzi

“…The binary and multiclass model reached optimal classification performances with a mean AUC value equals to 90.76 (88.63–92.89 IC95%). …”
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REPRESENTATION OF KNOWLEDGE IN LEARNING SYSTEMS BASED ON THE THEORY OF FUZZY SETS by Y. B. Popova, A. I. Burakovski

“…The main advantage of the mathematical model is the accuracy, abstraction processing, communication logically uniform way. …”
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A Rotated Object Detection Model With Feature Redundancy Optimization for Coronary Athero-Sclerotic Plaque Detection by Xue Hao, Haza Nuzly Abdull Hamed, Qichen Su, Xin Dai, Linqiang Deng

“…Experimental results demonstrate that YOLO-Plaque performs better than existing plaque detection models while remaining lightweight. The vital metric mAP50 has increased by 3.59% reaching 91.23%, while GFLOPs and parameters decreased to 7.2 and 2.55M, respectively.…”
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DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions by Zhiyong Jing, Zhaobing Chen, Yucheng Shi, Lei Shi, Lin Wei, Yufei Gao

“…First, DSNet utilizes the dehaze fusion network (DFN) to learn dehazing features, applying differentiated processing weights to regions with light and dense fog. …”
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