Covariance Matrix Reconstruction to Improve DoA Estimation Using Subspace Method in Low SNR Regime by Sunita Khichar, Wiroonsak Santipach, Lunchakorn Wuttisittikulkij

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Smart forest monitoring: A novel Internet of Things framework with shortest path routing for sustainable environmental management by Alireza Etaati, Mostafa Bastam, Ehsan Ataie

“…Three distinct topologies are proposed in this research study: direct transmission from nodes to gateways, cluster formation with multi‐step data transmission, and clustering with data relayed by cluster heads. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…The results demonstrate that ensemble machine learning models not only enhance the accuracy of identification but also significantly improve the prediction of pulse periods, achieving an accuracy of 93.4% for classification and a mean absolute error of 1.52 seconds for regression. This research contributes to the field of earthquake engineering by providing a more reliable and computationally efficient tool for the analysis of near-fault pulse-like ground motions, ultimately aiding in the development of better earthquake-resistant structures.…”
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Comparison of longitudinal PSQI and actigraphy-assessed sleep from pregnancy to postpartum. by Ryan L Brown, Chloe M Beverly Hery, Aric A Prather, Lisa M Christian

“…Despite the importance of sleep for perinatal health, there is limited research examining whether different measurement modalities may yield inconsistent data from pregnancy through postpartum. …”
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Comparative Analysis of Neural Network Models for Predicting Battery Pack Safety in Frontal Collisions by Jun Wang, Ouyang Chen, Zhenfei Zhan, Zhiwei Zhao, Huanhuan Bao

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Revolutionizing Cytology and Cytopathology with Natural Language Processing and Chatbot Technologies: A Narrative Review on Current Trends and Future Directions by Andrea Lastrucci, Enrico Giarnieri, Elisabetta Carico, Daniele Giansanti

“…By automating the extraction and classification of medical information, these technologies can reduce human error and increase precision. They also promise to make patient information more accessible and facilitate complex decision-making processes, thereby fostering greater patient involvement in healthcare. …”
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The Revolving Door Flap: Revisiting an Elegant but Forgotten Flap for Ear Defect Reconstruction by Anupam Golash, Sudipta Bera, Aditya V. Kanoi, Abhijit Golash

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An Automated Framework for Lane Closure Detection on Highway Using Connected Vehicle Data and Machine Learning Models by Ashutosh Dumka, Raghupathi Kandiboina, Aparna Joshi, Skylar Knickerbocker, Neal Hawkins, Anuj Sharma

“…The traditional methods, which use primarily manual reporting or sensor-based methods, can be error-prone, inefficient, and costly. This study introduces an innovative real-time lane closure detection approach using connected vehicle (CV) data and machine learning techniques. …”
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Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors by Ana González-Castro, José Alberto Benítez-Andrades, Rubén González-González, Camino Prada-García, Raquel Leirós-Rodríguez

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Multi-classification of breast cancer histopathological image using enhanced shallow convolutional neural network by Musa Yusuf, Armand Florentin Donfack Kana, Mustapha Aminu Bagiwa, Mohammed Abdullahi

“…However, the clinical examination and diagnosis of BC histology images are subject to human error. Consequently, several computer-aided diagnoses (CAD) solutions have been presented to aid histopathologists with the automated classification of cancerous tumor cells on histological images. …”
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Image-based machine learning and cluster analysis for urban road network: employing Orange for codeless visual programming by Zuo Zhang, Mengwei Zhang, Xiangxiang Song, Zhi Li

“…As attributes increase and model learning improves, both the Area Under Curve (AUC) and F-1 scores exhibit continuous enhancements, ultimately achieving error-free predictions. The study’s findings offer valuable insights into urban spatial structures and systems, supporting urban decision-makers in addressing challenges associated with urban growth.…”
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Building flux capacity: Citizen scientists increase resolution of soil greenhouse gas fluxes. by Cody C Reed, Julianne M Winters, Stephen C Hart, Rachel Hutchinson, Mark Chandler, Gitte Venicx, Benjamin W Sullivan

“…This collaboration with citizen scientists increased our sampling intensity by over 700% while only doubling the sampling error relative to that of full-time researchers. …”
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Assessing the Effectiveness of Estimating the Construction Years of Cambodia Road Bridges Using an Improved Satellite-Based Method by Bennie Hamunzala, Hiroto Goto, Koji Matsumoto

“…A total of 423 road bridges were analyzed, with the accuracy of the method assessed using the Mean Absolute Error (MAE). The improved method demonstrated considerable accuracy, with 64.3% of bridges classified as high-accuracy (MAE of 0–5), 20.8% as moderate-accuracy (MAE of 6–10), and 14.9% as low-accuracy (MAE of 11–30). …”
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Models of early stages of design of trunk-route passenger airplanes with taking families into account by P. V. Zhuravlev, V. N. Zhuravlev

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Cancer Patients Missing Pain Score Information:- Application with Imputation Techniques by Gajendra Vishwakarma, Atanu Bhattacharjee, Jesna Jose, Ramesh V

“…Background: Methods for handling missing data in clinical research have been getting more attentions over last few years. …”
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Development of a Fire Risk Assessment Program for Submerged Tunnels by Suk-Min Kong, Hyo-Gyu Kim, Ho-Hyeong Lee, Seong-Won Lee

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Experimental and simulation study on fracture conductivity of acid-fracturing in Dengying Formation of Sichuan Basin by CHEN Xiang, WANG Guan, LIU Pingli, DU Juan, WANG Ming, CHEN Weihua, LI Jinlong, LIU Jinming, LIU Fei

“…Furthermore, specific acid combinations have been identified that enhance the conductivity of fractures under extreme conditions of temperature and pressure. The average error between the conductivity values calculated by the model and those obtained from experimental results is relatively low, about 10.6%, indicating that the model can effectively characterize the distribution and magnitude of conductivity across different points within the fracture. …”
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De Plantis Toxicariis e mundo novo tropicale Commentationes – XXXVIII: Ethnopharmacological and alkaloidal notes on plants of the northwest Amazon De Plantis Toxicariis e mundo nov... by Schultes Richard Evans, Raffauf Robert F.

“…</span></p><p class="MsoNormal" style="margin-bottom: 0.0001pt; line-height: normal;"><span style="font-size: 11.818181991577148px;">This series has continued to note the uses of plants as medicines, poisons </span><span style="font-size: 11.818181991577148px;">or narcotics that the Indians of the northwest Amazon have, through millennia </span><span style="font-size: 11.818181991577148px;">of trial and error, discovered to possess some activity on the human or animal </span><span style="font-size: 11.818181991577148px;">body. …”
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An ensemble prediction approach to weekly Dengue cases forecasting based on climatic and terrain conditions by Sougata Deb, Cleta Milagros Libre Acebedo, Gomathypriya Dhanapal, Chua Matthew Chin Heng

“…Results: The proposed ensemble prediction achieved a mean absolute error of 21.55, 4.26 points lower than the 25.81 obtained by a standard negative binomial model. …”
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Road Pothole Recognition and Size Measurement Based on the Fusion of Camera and LiDAR by Yongxiang Cai, Mingxing Deng, Xin Xu, Wei Wang, Xiaowei Xu

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