Deep convolutional neural network model for classifying common bean leaf diseases by Dagne Walle Girmaw, Tsehay Wasihun Muluneh

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How does the mode of evolutionary divergence affect reproductive isolation? by De Sanctis, Bianca, Schneemann, Hilde, Welch, John J.

“…It follows from our results that identical patterns of RI can arise in different ways, since different evolutionary histories can lead to the same total amount and net effect of change. Nevertheless, we show how these estimable quantities do contain some information about the history of divergence, and that — thanks to Haldane's Sieve — the dominance and additive effects contain complementary information. …”
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Comprehensive Income and Stock Price: The Case of tfihe Energy Industry by Przemysław Poniatowski

“…Financial results are the main source of information for investors on the stock market. The International Accounting Standards Board has been changing the basic rules regarding a shift from net income to comprehensive income as the main picture of the financial performance of a business. …”
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EUROPEAN STRUCTURAL FUNDS IN ROMANIA: ABSORPTION AND IMPACT ON THE AGRICULTURAL SECTOR by Beatrice-Simona MANOLACHE, Constantin MANOLACHE, Silvius STANCIU

“…The results of the research show a strong correlation between the effective absorption rate of the European Structural Funds and the total net investments in the agricultural sector at the national level. …”
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Detection of selfish nodes based on credit mechanism in opportunistic networks by Zuo-yong TANG, Yi-jia YUAN, Yong-qiang DONG, Guo-xin WU

“…The existence of selfish nodes seriously affects the routing performance of opportunistic networks(OppNet).To protect the OppNet against the nodes’ selfish behavior,a credit-based selfish nodes detection mechanism was proposed to make it possible to keep away from such nodes during the process of message forwarding.The mechanism leverages 2-ACK messages to observe the nodes’behavior.Then the credit value was calculated based on the observation information and accordingly acts as the metric to distinguish the selfish nodes.Simulation results show that,when coupled with various routing algorithms,the mechanism could detect selfish nodes out accurately,and improve network performance effectively in terms of delivery rate and traffic load.…”
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Knowledge Transfer between Oscillators and Real Vibrating Structures to Enrich Dynamic Monitoring Datasets by Valeria Cavanni, Rosario Ceravolo, Gaetano Miraglia

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Assessments of non-timber forest products status in the Guraferda district of Ethiopia by Belay Gessese

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Vibration Signal Processing for Transmission System based on Quantum-inspired Mathematical Morphology by Yang Le

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TCSRNet: a lightweight tobacco leaf curing stage recognition network model by Panzhen Zhao, Panzhen Zhao, Songfeng Wang, Shijiang Duan, Aihua Wang, Lingfeng Meng, Yichong Hu

“…Compared to models such as ResNet34, GhostNet, ShuffleNetV2×1.5, EfficientNet-b0, MobileViT-xs, MobileNetV2, MobileNetV3-large, and MobileNetV3-small, TCSRNet demonstrates superior performance in terms of accuracy, FLOPs, and parameter count. …”
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Aquaculture Areas Extraction Model Using Semantic Segmentation from Remote Sensing Images at the Maowei Sea of Beibu Gulf by Weirong Qin, Mohd Hasmadi Ismail, Yangyang Luo, Yifeng Yuan, Junlin Deng, Mohammad Firuz Ramli, Ning Wu

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DECISION SUPPORT SYSTEM SUCCESS AND OPERATIONS SUSTAINABILITY: MODERATING ROLE OF SUPPLY CHAIN RESILIENCE by Khaled Mohammed Ahmed Alqasa, Veera Pandiyan Kaliani Sundram

“…The regression analysis revealed that both operational information systems and operational system quality have a positive and significant impact on net benefits, mediated by product quality and decision support satisfaction. …”
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Integrating Shallow and Deep Features for Precision Evaluation of Corn Grain Quality: A Novel Fusion Approach by Kunal Mishra, Santi Kumari Behera, A. Geetha Devi, Prabira Kumar Sethy, Aziz Nanthaamornphong

“…We evaluated 13 pre-trained CNN models, including AlexNet, VGG19, and ResNet, with AlexNet emerging as the top performer, achieving 71% accuracy validated through statistical analysis using Duncan’s multiple range test. …”
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Integration of pre-trained protein language models with equivariant graph neural networks for peptide toxicity prediction by Shihu Jiao, Xiucai Ye, Tetsuya Sakurai, Quan Zou, Wu Han, Chao Zhan

“…However, these methods mainly rely on the primary sequence and often ignore critical structural information, which limits their predictive accuracy. …”
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Effective Algorithm for Biomedical Image Segmentation by Zhao Di, Tang Yi, A. B. Gourinovitch

“…Objects in medical images have different scales, types, complex backgrounds, and similar tissue appearances, making information extraction challenging. To solve this problem, a module is proposed that takes into account the features of images, which will improve the biomedical image segmentation network FE-Net. …”
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Joint Design of Antenna Selection and Resource Allocation in Massive MIMO-Based Ultra Dense Heterogeneous Networks by Malini Balachandran, Noor Mohammed Vali Mohamad

“…The massive MIMO and heterogeneous network (HetNet) has evolved as a promising technology to address the aforementioned challenges. …”
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Estudio de alternativas de sistemas fotovoltaicos para la Aeronáutica Civil en el Aeropuerto Camilo Daza by Sebastián Loaiza Elejalde, Sergio Basilio Sepúlveda Mora

“…Finally, the benefits and costs were evaluated for each case through net present value and return on investment analysis. …”
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A Lightweight Model Enhancing Facial Expression Recognition with Spatial Bias and Cosine-Harmony Loss by Xuefeng Chen, Liangyu Huang

“…Experimental results on the AffectNet and RAF-DB datasets demonstrate that the LFNSB model achieves competitive recognition accuracy, with 63.12% accuracy on AffectNet-8, 66.57% accuracy on AffectNet-7, and 91.07% accuracy on RAF-DB, while significantly reducing the model complexity.…”
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Object representations drive emotion schemas across a large and diverse set of daily-life scenes by Chuanji Gao, Susan Ajith, Marius V. Peelen

“…To explore this, we collected emotion ratings for 4913 daily-life scenes from 300 participants, and predicted these ratings from representations in deep neural networks and functional magnetic resonance imaging (fMRI) activity patterns in visual cortex. AlexNet, an object-based model, outperformed EmoNet, an emotion-based model, in predicting emotion ratings for daily-life scenes, while EmoNet excelled for explicitly evocative scenes. …”
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Optimization of Decision Support Technology for Offshore Oil Condition Monitoring with Carbon Neutrality as the Goal in the Enterprise Development Process. by Shiya Gao, Xin Guan, Xiaojing Cao, Zhili Bai, Caimeng Wang, Yun Zhan, Haiyang Yu

“…The experiment develops a marine oil condition monitoring and classification model based on the fusion of MobileNet v2 and Faster R-CNN algorithms. This model utilizes the MobileNet v2 network to extract rich feature information from input images and combines the Faster R-CNN algorithm to rapidly and accurately generate candidate regions for oil condition monitoring, followed by detailed feature fusion and classification of these regions. …”
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Advanced deep learning models based on neutrosophic logic for the analysis of brain tumor medical images by Dina Atef, Doaa El Shaha

“…To assess the methodology, four advanced deep learning models MobileNet, VGG16, DenseNet121 and InceptionV3 were employed, and their efficacy was analyzed on brain tumor medical image datasets. …”
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