Beyond bronchial thermoplasty – where to now? by Peter B. Noble, David Langton, Chuan T. Foo, Bruce R. Thompson, Alvenia Cairncross, Michael J. Hackmann, Francis Thien, Graham M. Donovan

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Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks by A.V. Dobshik, S.K. Verbitskiy, I.A. Pestunov, K.M. Sherman, Yu.N. Sinyavskiy, A.A. Tulupov, V.B. Berikov

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Apriori algorithm based prediction of students’ mental health risks in the context of artificial intelligence by You Fu, Fang Ren, Jiantao Lin

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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

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An efficient Cucconi based feature extraction with random decision forest classification for improved sentiment analysis by Anuradha K., Mallik Banitamani, Krishna Vamsi M.

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Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble by Mona Ahamd Alghamdi, Abdullah S. AL-Malaise AL-Ghamdi, Mahmoud Ragab

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Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning by Binay Kumar Pandey, Digvijay Pandey, S. K. Sahani

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A comparative study of statistical and intelligent classification models for predicting airlines passenger management satisfaction by Mohammed Alharithi, Ehab M. Almetwally, Omar Alotaibi, Marwa M. Eid, El-Sayed M. El-kenawy, Alaa A. Elnazer

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Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer by Sandeep Dwarkanth Pande, Pala Kalyani, S Nagendram, Ala Saleh Alluhaidan, G Harish Babu, Sk Hasane Ahammad, Vivek Kumar Pandey, G Sridevi, Abhinav Kumar, Ebenezer Bonyah

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A Comparative Study between Time Series and Machine Learning Technique to Predict Dengue Fever in Dhaka City by Tanzina Akter, Md. Tanvirul Islam, Md. Farhad Hossain, Mohammad Safi Ullah

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Numerical assessment of solar panel with utilizing ferrofluid flow within wavy duct equipped with V-shaped fins by Mohammed A. Tashkandi, Ali Basem, Hussein A.Z. AL-bonsrulah, Lioua Kolsi, Mahmood Shaker Albdeiri, Lotfi Ben Said, Amira M. Hussin

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Milk Composition Is Predictive of Low Milk Supply Using Machine Learning Approaches by Xuehua Jin, Ching Tat Lai, Sharon L. Perrella, Xiaojie Zhou, Ghulam Mubashar Hassan, Jacki L. McEachran, Zoya Gridneva, Nicolas L. Taylor, Mary E. Wlodek, Donna T. Geddes

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Advancing terrestrial snow depth monitoring with machine learning and L-band InSAR data: a case study using NASA’s SnowEx 2017 data by Ibrahim Olalekan Alabi, Ibrahim Olalekan Alabi, Hans-Peter Marshall, Jodi Mead, Ernesto Trujillo

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Gene content of seawater microbes is a strong predictor of water chemistry across the Great Barrier Reef by Marko Terzin, Steven J. Robbins, Sara C. Bell, Kim-Anh Lê Cao, Renee K. Gruber, Pedro R. Frade, Nicole S. Webster, Yun Kit Yeoh, David G. Bourne, Patrick W. Laffy

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Exploring SLEEPINESS through home monitoring with ultra-long-term subcutaneous EEG and ecological momentary assessment in sleepy treatment naïve obstructive sleep apnea patients st... by Mathias Sarkez-Knudsen, Martin Ballegaard, Martin Ballegaard, Henning Piilgaard, Esben Ahrens, Martin Christian Hemmsen, Tobias Søren Andersen, Jakob Eyvind Bradram, Preben Homøe, Preben Homøe

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Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios by Aminjon Gulakhmadov, Xi Chen, Nekruz Gulahmadov, Muhammmad Rizwan, Manuchekhr Gulakhmadov, Muhammad Umar Nadeem, Moldir Rakhimova, Tie Liu

“…The research aimed to identify differences in historical simulations and future predictions of rainfall and temperature, examining the accuracy of eight General Circulation Models (GCMs) used in both CMIP5 (RCP4.5 and 8.5) and CMIP6 (SSP2–4.5 and 5–8.5). The evaluation metrics demonstrated that the GCMs have a high level of accuracy in reproducing maximum temperature (Tmax) with a correlation coefficient of 0.96. …”
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Environmental Supply Chain Performance Mapping of an Enterprise by Exploring a Novel Vague-Intellectual Approach by Juan Wang, M. Prabhu, Abatihun Alehegn Sewagegn, Anoop Kumar Sahu

“…To fulfill the first RG, the authors first of all proposed the two GTFN set-based mathematical models, which are executed to compute the priority weights and appropriateness ratings (PWsaARs) for 1st level measures from 2nd level PWsaARs of metrics (discarded the requirement of PWsaARs data for 1st level measures from experts). …”
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A Distribution Agnostic Rank-Based Measure for Proximity Search by Mayur Garg, Ashutosh Nayak, Rajasekhara Reddy Duvvuru Muni

“…Extant algorithms depend on distance-based metrics to find the closest data points. However, these metrics are limited by their dependency on the distribution of data along different dimensions, making them sensitive to scaling and translation. …”
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Low-Complexity User Selection for Rate Maximization in MIMO Broadcast Channels with Downlink Beamforming by Eduardo Castañeda, Adão Silva, Ramiro Samano-Robles, Atílio Gameiro

“…Based on the derived metrics we present a mathematical model that describes the dynamics of the user selection process which renders the user selection problem into an integer linear program. …”
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Long Memory of Pathfinding Aesthetics by Ron Coleman

“…Secondly, those investigators who have studied aesthetics in pathfinding have relied largely on anecdotal arguments rather than metrics. Finally, in those cases where metrics have been used in the past, they show only that aesthetic paths are different. …”
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