Data envelopment analysis with imprecise data: Fuzzy and interval modeling approaches by Hassan Mishmast Nehi, Faranak Hosseinzadeh Saljooghi, Amir Rahimi, Laxmi Rathour, Lakshmi Narayan Mishra, Vishnu Narayan Mishra

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Neurotechnology for enhancing human operation of robotic and semi-autonomous systems by William J. Tyler, William J. Tyler, Anusha Adavikottu, Christian Lopez Blanco, Archana Mysore, Archana Mysore, Christopher Blais, Marco Santello, Avinash Unnikrishnan

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New Approaches for the Use of Extended Mock-Ups for the Development of Air Traffic Controller Working Positions by Lennard Nöhren, Lukas Tyburzy, Marco-Michael Temme, Kathleen Muth, Thomas Hofmann, Deike Heßler, Felix Tenberg, Eilert Viet, Michael Wimmer

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Experimental and Numerical Investigation of Jute Fibre-Reinforced Composite, a Sustainable Material for Green Energy by Kirubakaran Covallane, Daryl Johan, Rakesh Kumar Singh, Rahul Sinha, Digvijay Boodala, Krishna Kumar Jaiswal, Karthik Selva Kumar

“…This study demonstrates the efficacy of using computational tools to predict the behaviour of natural fibre composites. …”
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MM-3D Unet: development of a lightweight breast cancer tumor segmentation network utilizing multi-task and depthwise separable convolution by Xian Wang, Wenzhi Zeng, Junzeng Xu, Senhao Zhang, Yuexing Gu, Benhui Li, Xueyang Wang

“…The network architecture features a contracting path for downsampling and an expanding path for precise localization, enhanced by skip connections that integrate multi-level semantic information.ResultsThe network was evaluated using a dataset of Dynamic Contrast Enhanced MRI (DCE-MRI) breast cancer images, and the results show that compared to the classical 3DU-Net, MM-3DUNet could significantly reduce model parameters by 63.16% and computational demands by 80.90%, while increasing segmentation accuracy by 1.30% in IoU (Intersection over Union).ConclusionsMM-3DUNet offers a substantial reduction in computational requirements of breast cancer mass segmentation network. …”
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An end-to-end covert channel via packet dropout for mobile networks by Yu-an Tan, Xinting Xu, Chen Liang, Xiaosong Zhang, Quanxin Zhang, Yuanzhang Li

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Unusual Presentation of Hydatid Cyst in Breast with Magnetic Resonance Imaging Findings by Ali Koc, Inanc Samil Sarici, Umit Erkan Vurdem, Ozgur Karabiyik, Ummugulsum Ozgul Gumus

“…We report a case of 59-year-old woman with a painful left breast mass, compatible with types II-III hydatid cyst. Lesion was evaluated with mammography, ultrasound, computed tomography, and magnetic resonance imaging modalities. …”
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Bandwidth Estimation in Wireless Lans for Multimedia Streaming Services by Heung Ki Lee, Varrian Hall, Ki Hwan Yum, Kyoung Ill Kim, Eun Jung Kim

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Building an Intelligent Laboratory Environment via a Cyber-Physical System by Chi-Un Lei, Ka Lok Man, Hai-Ning Liang, Eng Gee Lim, Kaiyu Wan

“…Evaluations of an on-site deployment verify the functionality of the proposed CPS. …”
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Combining Convolutional Neural Network (CNN) and Grad-CAM for Parkinson’s Disease Prediction and Visual Explanation by Reyhaneh Dehghan, Marjan Naderan, Seyed Enayatallah Alavi

“…In this study, a Convolutional Neural Network (CNN) namely ConvNet, is used to discriminate Parkinson's patients based on Single Photon Emission Computed Tomography (SPECT) images acquired from the PPMI database. …”
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Intelligent Modelling Techniques for Enhanced Thermal Comfort and Energy Optimisation in Residential Buildings by Shamaila Iram, Hafiz Muhammad Athar Farid, Abduljelil Adeola Akande, Hafiz Muhammad Shakeel

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Improving Causality Induction with Category Learning by Yi Guo, Zhihong Wang, Zhiqing Shao

“…CL-CIS considers cause-effect relations in both explicit and implicit forms and especially practices the relation between category and causality in computation. In elaborately designed experiments, CL-CIS is evaluated together with general causality analysis system (GCAS) and general causality analysis system with learning (GCAS-L), and it testified to its own capability and performance in construction of cause-effect relations. …”
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Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm by Amna Bamaqa, Waleed M. Bahgat, Yousry AbdulAzeem, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

“…When PCR tests are unavailable, computational lesion detection offers a promising option. …”
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Seismic risk assessment of typical bridges in Northeastern Brazil through the application of Machine Learning methods by Lucas Filipe Da Ronch, Gustavo Henrique Ferreira Cavalcante, Eduardo Marques Vieira Pereira, Isabela Durci Rodrigues, Thiago Dias dos Santos, Gustavo Henrique Siqueira

“…Traditional approaches to evaluating fragility curves are time-consuming, mainly because of the relatively high computational cost of running several finite element-based models. …”
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Artificial Intelligence and Algorithmic Approaches of Health Security Systems: A Review by Savina Mariettou, Constantinos Koutsojannis, Vassilios Triantafillou

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On First-Principle Robot Building in Undergraduate Robotics Education in the Robotic System Levels Model by Bryan Van Scoy, Peter Jamieson, Veena Chidurala

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Intelligent Renewable Energy Agent-Based Distributed Control Design for Frequency Regulation and Economic Dispatch by Amjad Khan, Amjad Ullah Khattak, Bilal Khan, Sahibzada Muhammad Ali, Zahid Ullah, Faisal Mehmood

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Analyzing the Impact of Data Augmentation on the Explainability of Deep Learning-Based Medical Image Classification by Xinyu (Freddie) Liu, Gizem Karagoz, Nirvana Meratnia

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Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads by Shu Yang, Ruiyu Chen, Laizhong Cui, Xiaolei Chang

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Secure data transmission through fractal-based cryptosystem: a Noor iteration approach by Deepak Negi, Rajiv Kumar, Vijay Kumar, Arvind Dhaka

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