Optimized deep learning model with integrated spectrum focus transformer for pavement distress recognition and classification by Wenlin Wu, Fenghua Zhu, Zheng Li, Xue Li, Xiaowei Li, Jinwen Wang

“…Experiments conducted on the road pavement distress dataset revealed through heatmap analysis that distress regions received increased attention, achieving an accuracy of 97.73%. …”
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Impact of land prices on corporate carbon emission intensity by Lin Guo, Ying Liu, Zeqing Jiang, Xiaoping Yuan, Qi Jing

“…Abstract This study examines the impact of micro-level land prices on corporate carbon emission intensity and identifies the underlying mechanisms. Using a unique dataset of Chinese industrial enterprises from 2000 to 2014, we employ a two-way fixed effects econometric model, alongside instrumental variable and Difference-in-Differences (DID) techniques, to address endogeneity concerns. …”
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Anatomy of Complex System Research by Yang Wang, Xinyue Wang

“…In this work, we present an anatomy of complex system research by leveraging a large-scale dataset that contains more than 100 million digitalized publications. …”
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Writer identification and writer retrieval based on NetVLAD with Re‐ranking by Shervin Rasoulzadeh, Bagher BabaAli

“…Experimental evaluation has been done on the three publicly available datasets: the ICDAR 2013, CVL, and KHATT datasets. …”
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A Single-Layer Dual-Band Reflectarray Cell for 5G Communication Systems by Sandra Costanzo, Francesca Venneri, Antonio Borgia, Giuseppe Di Massa

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Efficient Synthesis of Large Finite Patch Arrays for Scanning Wide-Angle Anomalous Reflectors by Sravan Kumar Reddy Vuyyuru, Risto Valkonen, Sergei A. Tretyakov, do-Hoon Kwon

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Patch Testing in Suspected Allergic Contact Dermatitis to Cosmetics by Pramod Kumar, Rekha Paulose

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Lion Algorithm-Optimized Long Short-Term Memory Network for Groundwater Level Forecasting in Udupi District, India by B. S. Supreetha, Narayan Shenoy, Prabhakar Nayak

“…The hybrid LSTM-LA-based forecasting model is promising for a larger dataset.…”
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Modeling Spatiotemporal Precipitation: Effects of Density, Interpolation, and Land Use Distribution by Christopher L. Shope, Ganga Ram Maharjan

“…We develop a weighted, distributed approach for gap-filling the observed meteorological dataset. We analyze five interpolation methods (Thiessen, IDW, nearest neighbor, spline, and ordinary Kriging) at five gauge densities. …”
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Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm by G. Ayappan, S. Anila

“…Audio data from the COUGHVID dataset undergo preprocessing through fuzzy gray level difference histogram equalization, followed by segmentation with a U-Net model. …”
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Harnessing artificial intelligence for predicting breast cancer recurrence: a systematic review of clinical and imaging data by Jaqueline Alvarenga Silveira, Alexandre Ray da Silva, Mariana Zuliani Theodoro de Lima

“…Despite these advancements, limitations such as dataset diversity, sample size, and evaluation standardization persist, emphasizing the need for further research. …”
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Trade-Off between Sampling Frequency and Duration and Their Influences on the Estimation of Space Use of Japanese Macaques by Kana Terayama, Hiroshi Ebihara, Hironori Seino, Masaaki Takiguchi, Motomi Genkai-Kato

“…In this study, we assessed how different combinations of sampling frequency and duration would affect estimates for home-range size and maximum utilization area (MUA) of Japanese macaques, using datasets subsampled by reducing frequency and/or duration from the original dataset. …”
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A Dynamic Intrusion Detection System Based on Multivariate Hotelling’s T2 Statistics Approach for Network Environments by Aneetha Avalappampatty Sivasamy, Bose Sundan

“…Performance of the model, as evaluated through validation and testing using KDD Cup’99 dataset, has shown very high detection rates for all classes with low false alarm rates. …”
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Accuracy of the Photometric Redshifts of Brightest Cluster Galaxies Identified in the CFHTLS-W1 by Sinan Aliş

“…Cross-matching of 3283 BCGs with this large spectroscopic dataset yielded 1215 BCGs with high-quality spectroscopic redshift. …”
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The Draft Genome and Transcriptome of the Atlantic Horseshoe Crab, Limulus polyphemus by Stephen D. Simpson, Jordan S. Ramsdell, Winsor H. Watson III, Christopher C. Chabot

“…Overall, these assemblies provide a resource to investigate the Limulus clock systems and provide a large dataset for further exploration into the taxonomy and biology of the Atlantic horseshoe crab.…”
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Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression by Mayumi Kamada, Yusuke Sakuma, Morihiro Hayashida, Tatsuya Akutsu

“…Moreover, we perform computational experiments employing two machine learning methods, support vector regression (SVR) and relevance vector machine (RVM), for dataset obtained from biological experiments. The prediction results showed that both SVR and RVM with our proposed features outperformed the best existing method.…”
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Challenges in Management of Ovotesticular Differences in Sex Development in Resource-Limited Settings by Serwah Bonsu Asafo-Agyei, Emmanuel Ameyaw, Boateng Nimako, Michael Amoah

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CoMFA and CoMSIA Studies on Inhibitors of HIV-1 Integrase - Bicyclic Pyrimidinones by V. Radhika, S. Sree Kanth, M. Vijjulatha

“…To understand the structural requirements of HIV-1 integrase inhibitors and to design new ligands against human HIV-1 integrase with enhanced inhibitory potency, a 3D QSAR (quantitative structure-activity relationship) study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a dataset of 35 bicyclic pyrimidinones which are inhibitors of human HIV-1 integrase was performed. …”
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VARAT: Variable Annotation Tool for Documents on Manufacturing Processes by Shota Kato, Manabu Kano

“…VARAT was subsequently employed to create a dataset containing 1,988 variable symbols from the 47 papers. …”
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Real-Time Forestry Pest Detection Method Based on Enhanced Feature Fusion with Deep Learning by Rui Li, Tong Liu, Yalu Ren

“…Finally, data augmentation is performed on a relatively small number of samples in the dataset, the accuracy of the model is improved by 1.94%, the FPS is improved to 1.6 times of the original one, and the training time is slightly increased compared with the preinnovation model. …”
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