Assessing a Bayesian Approach for Detecting Exotic Hybrids between Plantation and Native Eucalypts by Matthew J. Larcombe, René E. Vaillancourt, Rebecca C. Jones, Brad M. Potts

“…A six-way analysis (all species in the model together) showed that as the number of species increases the accuracy of hybrid identification decreases. …”
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DEVELOPMENT OF NON-DESTRUCTIVE ROBOT FOR EGGPLANTS (SOLANUM MELONGENA) PEST DETECTION AND CLASSIFICATION by Mark Jayson Y. Sutayco, Eidref Simon Dela Cruz, Harold Aranza, Gian Fernan Collado, Kyle Benedict Lui

“…Deep learning techniques, such as convolutional neural networks, enable accurate pest identification and decision-making based on insect images. …”
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The Data Artifacts Glossary: a community-based repository for bias on health datasets by Rodrigo R. Gameiro, Naira Link Woite, Christopher M. Sauer, Sicheng Hao, Chrystinne Oliveira Fernandes, Anna E. Premo, Alice Rangel Teixeira, Isabelle Resli, An-Kwok Ian Wong, Leo Anthony Celi

“…Results The Data Artifacts Glossary adopts a collaborative approach modeled on successful open-source projects like Linux and Python. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…This study presents a semi-automated approach for assessing water quality in the Sundarbans, a critical and vulnerable ecosystem, using machine learning (ML) models integrated with field and remotely-sensed data. …”
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Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset by Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui

“…It not only showed excellent results for evaluation parameters but also proved highly efficient in terms of time and space complexity. Moreover, the concept of the profiling technique makes our model highly transparent and explainable. …”
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Predicting ROS1 and ALK fusions in NSCLC from H&E slides with a two-step vision transformer approach by Eghbal Amidi, Mohammadreza Ramzanpour, Ming Chen, Tommy Boucher, Mukund Varma, Timothy Samec, Brian Lamon, Nicolas Stransky, Mark R. Miglarese, Matthew Oberley, David Spetzler, George W. Sledge

“…A vision transformer model (MoCo-V3) was trained as a feature extractor, followed by training transformer-based models to predict the presence of ROS1 and ALK fusions. …”
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Enhancing Crack Segmentation Network with Multiple Selective Fusion Mechanisms by Yang Chen, Tao Yang, Shuai Dong, Like Wang, Bida Pei, Yunlong Wang

“…Accurate crack detection allows for the timely identification and repair of cracks, reducing safety risks and extending the service life of structures. …”
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Design optimization of Bakelite support for LNG ISO tank 40 ft using finite element analysis by Tuswan Tuswan, Taufiq Rafif Naufal, Mursid Ocid, Sari Dian Purnama, Rizal Nandiko, Yuniati Yuniati, Sasmito Agus, Machfudin Andik, Sandjaja Irfan Eko, Utina Muhammad Ridwan, Harmadi Rudias, Muttaqie Teguh

“…This approach enables the identification of efficient material distributions under critical loading conditions, enhancing safety, compliance with ISO 1496 standards, and overall transport efficiency without compromising strength. …”
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The contribution of remote sensing for the development of a Green-Holistic IoT Platform for Forest Management and Monitoring: Reforestation and Deforestation Modules by M. Prodromou, M. Tzouvaras, C. Mettas, A. Konstantinidis, A. Pamboris, I. Iasonos, D. Hadjimitsis

“…The Green-HIT project focuses on effective and efficient forest monitoring and management, which holds the promise for climate change mitigation, ecosystem conservation, and biodiversity loss reduction. …”
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BirdRecon: A free open source tool for image based bird species recognition by Hari Kishan Kondaveeti, Nabin Kumar Upadhaya, Dheeraj Sai Tukkugudam, Rahul Panigrahi, Sirivella Madhan Chandra Mouli, Valli Kumari Vatsavayi, Nagendra Panini Challa

“…The system leverages a soft voting ensemble of four pretrained deep learning models—DenseNet201, EfficientNetB7, InceptionV3, and ResNet50V2—to improve classification accuracy and robustness. …”
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Partial discharge defect recognition method of switchgear based on cloud-edge collaborative deep learning by Zhijie Jia, Songhai Fan, Zhichuan Wang, Shuai Shao, Dameng He

“…The results indicate that the DBN proposed in this paper can recognize PDs in switchgear with an accuracy of 88.03%, and under the edge computing architecture, the training time of the switchgear PD defect type classifier can be reduced by 44.28%, overcoming the challenges associated with traditional diagnostic models, which are characterized by long training durations, low identification efficiency, and weak collaborative analysis capabilities.…”
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Research of WLAN authentication in roaming environment with the trend of network integration by Zhang-zhe LIU, Hua-ying SHU

“…In the tendency of network convergence,the method of WLAN network client authentication based on telecommunications network will be the main way of WLAN authentication in the future.In order to make WLAN authentication efficiency and security under roaming condition,WLAN authentication requirements were analyzed,the authentication mode,the process and the existing problems were discussed.An application model and design scheme of WLAN network client authentication based on EAP SIM/AKA protocol with the trend of network integration were proposed and verified.Experimental results show that this application model can complete the EAP SIM/AKA protocol identification of a WLAN client in roaming process,reduce the investment of networks,keep the safety grades of the nodes in the visited WLAN with the initial safety grades,and realize the real-time charging.…”
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Lung Segmentation with Lightweight Convolutional Attention Residual U-Net by Meftahul Jannat, Shaikh Afnan Birahim, Mohammad Asif Hasan, Tonmoy Roy, Lubna Sultana, Hasan Sarker, Samia Fairuz, Hanaa A. Abdallah

“…<b>Conclusions:</b> Using the capabilities of DL and cutting-edge attention processes, the proposed model improves current efforts to enhance lung segmentation for the early identification of many serious lung diseases.…”
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“Image-Spectral” fusion monitoring of peanut leaf spot disease level based on deep learning by Yongda Lin, Jiangtao Tan, Hong Li, Xi Li, Jianguo Wang, Tingting Chen, Lei Zhang

“…The model simultaneously processes RGB and spectral data as inputs, both of which are efficiently loaded through a unified dataloader. …”
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The unintended outcome: a retrospective cross‐sectional study using a urine lateral flow assay to detect ART use reveals non‐disclosure of taking ART in South Africa's public healt... by Nsika Sithole, Indira Govender, Matthew Spinelli, Theresa Smit, Siyabonga Cibane, Mlungisi Zwane, Njabulo Phakathi, Meighan Krows, Busisiwe Nkosi, Janet Seeley, Ruanne V. Barnabas, Mark J. Siedner, Mosa Moshabela, Connie Celum, Alison Grant, Monica Gandhi, Adrienne E. Shapiro

“…Abstract Introduction Differentiated service delivery (DSD) models for HIV and tuberculosis (TB) care prioritize efficient resource allocation and targeted interventions, and benefit from accurate assessment of patients’ antiretroviral therapy (ART) pill‐taking status. …”
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Study on Discriminant Analysis of Photosensitive Ink by Xingyu Duan, Fushi Chen, Xingzhou Han, Da Qin

“…Conventional methods often lack the efficiency or precision required to differentiate inks from varying manufacturers and models. …”
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Systematic Literature Review: Identifying Key Variables and Measuring Maximum Loan Limits by Algies Rifkha Fadillah, Mohamad Nurkamal Fauzan

“…This study identifies key variables and measurement methods, including Machine Learning techniques, Neural Networks, and traditional statistical approaches. Machine Learning models, such as Random Forest and Gradient Boosting, often surpass traditional methods in handling large, unstructured datasets due to their capacity for modeling complex, non-linear relationships. …”
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Online Estimation and Control Method of Optimal Slip Ratio for Vehicle With an Electric Power-Assisted Brake System by Lei Chen, Yuchao He, Tangtang Ma, Shengshi Zhong

“…Then a tire model parameter identification algorithm based on road surface similarity and Adam gradient descent is developed. …”
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Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods by Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan

“…On the decision curve analysis (DCA), the threshold probability of the nomogram ranged from 1 to 99% (training cohort) and 1 to 75% (validation cohort).Conclusion We successfully developed an ML model for predicting AHD in patients undergoing cervical spine surgery, showcasing its potential to support clinicians in AHD identification and enhance perioperative treatment strategies.…”
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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…We evaluated five computational models: EfficientNet, MobileNet v3, RegNet, ResNet, and ShuffleNet v2. …”
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