Dual intent view contrastive learning for knowledge aware recommender systems by Jianhua Guo, Zhixiang Yin, Shuyang Feng, Donglin Yao, Shaopeng Liu

“…Experimental results on three benchmark datasets demonstrate that DIVCL outperforms state-of-the-art models, showcasing its superior performance. …”
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MDCKE: Multimodal deep-context knowledge extractor that integrates contextual information by Hyojin Ko, Joon Yoo, Ok-Ran Jeong

“…Experimental validation on the Twitter2015 and Multimodal Neural Relation Extraction (MNRE) datasets demonstrated the novelty and accuracy of MDCKE, resulting in an improvement in the F1-score by up to 5.83% and 26.26%, respectively, compared to State-Of-The-Art (SOTA) models. MDCKE was compared with top models, case studies, and simulations in low-resource settings, proving its flexibility and efficacy. …”
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Time series predictions in unmonitored sites: a survey of machine learning techniques in water resources by Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia, Vipin Kumar

“…We review relevant state-of-the art applications of machine learning for streamflow, water quality, and other water resources prediction and discuss opportunities to improve the use of machine learning with emerging methods for incorporating watershed characteristics and process knowledge into classical, deep learning, and transfer learning methodologies. …”
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Robust sparse time‐frequency analysis for data missing scenarios by Yingpin Chen, Yuming Huang, Jianhua Song

“…Finally, several experiments are conducted to show the performance of the proposed robust STFA method under different data loss levels, and it is compared with some existing state‐of‐the‐art time‐frequency methods. The results indicate that the proposed method outperforms the compared methods in obtaining the sparse spectrum of the effective signal when data are missing. …”
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Differential Evolution-Based End-Fire Realized Gain Optimization of Active and Parasitic Arrays by Rozita Konstantinou, Ihsan Kanbaz, Okan Yurduseven, Michail Matthaiou

“…Full-wave simulations validate our theoretical results, showing that our two- and three-element parasitic arrays achieve realized gain comparable to state-of-the-art designs without relying on intricate unit elements or resource-intensive simulations, while our four- and five-element parasitic arrays yield the highest realized gain values reported in the literature. …”
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Unified Quantile Regression Deep Neural Network with Time-Cognition for Probabilistic Residential Load Forecasting by Zhuofu Deng, Binbin Wang, Heng Guo, Chengwei Chai, Yanze Wang, Zhiliang Zhu

“…With ablation experiments, the proposed model achieved the best results in the AQS, AACE, and inversion error, and especially the average of the AACE is grown by 34.71%, 75.22%, and 32.44% compared with QGBRT, QCNN, and QLSTM, respectively, indicating that our method has excellent reliability and robustness rather than the state-of-the-art models obviously. Meanwhile, great performances of efficient time response demonstrate that our proposed work has promising prospects in practical applications.…”
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BWFER-YOLOv8: An Enhanced Cascaded Framework for Concealed Object Detection by Khalid Ijaz, Ikramullah Khosa, Ejaz A. Ansari, Syed Farooq Ali, Asif Hussain, Faran Awais Butt

“…The comprehensive quantitative and qualitative analysis reveals that the proposed framework outperforms the state-of-the-art tiny YOLOv3 and YOLOv8 models by achieving 98.1% precision and recall in detecting concealed weapons. …”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…Experimental results show that our proposed framework outperforms state-of-the-art approaches, vastly improving DL model detection accuracy by 98% using CNN.…”
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Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning by Ryan Eusebi, Hui Su, Longtao Wu, Pingping Rong, Karthik Balaguru, Ruby Leung, Yong-Sang Choi, Pak Wai Chan, Jianping Gan, Mark DeMaria, Galina Chirokova

“…To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model consisting of a variety of machine learning (ML) methods. …”
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Emotion recognition in conversations based on discourse parsing and graph attention network by HAO Xiulan, WEI Shaohua, CAO Qian, ZHANG Xiongtao

“…Compared with mainstream models, the proposed model at least reaches state-of-the-art, and can be used in different language scenarios.…”
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A Hybrid Approach for Color Face Recognition Based on Image Quality Using Multiple Color Spaces by Mahdi Hosseinzadeh, Mohammad Mehdi Pazouki, Önsen Toygar

“…A comparative analysis that assesses the proposed approach with the state-of-the-art systems using Faces94, ColorFERET, and Replay Attack datasets is presented. …”
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Dual-Polarimetric SAR Measurements to Observe Liquefaction Surface Manifestations by Ferdinando Nunziata, Anna Verlanti, Nicola Angelo Famiglietti, Maurizio Migliaccio, Annamaria Vicari

“…Finally, the obtained maps are qualitatively contrasted against state-of-the-art optical and interferometric SAR methodologies. …”
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Quality monitoring of resuscitative endovascular balloon occlusion of the aorta using cumulative sum analysis in Korea: a case series by Hyunsik Choi, Joongsuck Kim, Kwanghee Yeo, Ohsang Kwon, Kyounghwan Kim, Wu Seong Kang

“…Purpose Resuscitative endovascular balloon occlusion of the aorta (REBOA) is a state-of-the-art lifesaving procedure. However, due to its high mortality and morbidity, including ischemia and reperfusion injury, well-trained medical staff and effective systems are needed. …”
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BeatNet+: Real-Time Rhythm Analysis for Diverse Music Audio by Mojtaba Heydari, Zhiyao Duan

“…We introduce BeatNet+, a two-stage approach to real-time rhythm analysis built on a previous state-of-the-art method named BeatNet. The main innovation of the proposed method is the auxiliary training strategy that helps the neural network model to learn a representation invariant to the amount of percussive components in the music. …”
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PREDICTABILITY AND ACCESSIBILITY OF THE LAW by Elena ANGHEL

“…The rule of law presupposes the obligation to respect the Constitution and the laws, as provided by the provisions of art. 1 para. (5) of the Constitution. In order for the law to be accepted and respected, it must present a certain legal security, assuming the requirements of accessibility and predictability, logical coherence and stability, features designed to capture the trust of citizens in its provisions. …”
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Vajravārāhī in Khara Khoto and Prajñāpāramitā in East Java: Connected by Pearl Ornaments by Lesley S Pullen

“…This research, situated in the geographical and historical context of the Tangut and East Java, uncovers a significant aspect of the evolution of Buddhist art styles. A thangka of the goddess Vajravārāhī found in Khara Khoto, dated to the late 12th century, shows the bodhisattva decorated with a pearl-chain girdle and upper-arm bands. …”
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Surrogate Safety Analysis of Pedestrian-Vehicle Conflict at Intersections Using Unmanned Aerial Vehicle Videos by Peng Chen, Weiliang Zeng, Guizhen Yu, Yunpeng Wang

“…Conflict analysis using surrogate safety measures (SSMs) has become an efficient approach to investigate safety issues. The state-of-the-art studies largely resort to video images taken from high buildings. …”
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La democracia y sus supuestos: una perspectiva comparativa entre los conceptos de democracia Procedimental y Estructural by Maximiliano Emanuel Korstanje

“…El presente artículo trata sobre las cuestiones que hacen la percepción de los latinoamericanos con respecto a la democracia como figura de orden político. En el estado del arte, se traen a colación los trabajos más representativos en el área de la sociología política. …”
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An Artist among the Puritans:Challenging a Cultural Image in Hawthorne’s The Scarlet Letter by Michèle BONNET

“…The text first painstakingly disproves that storytelling and art in general might run counter to the Puritan work ethic. …”
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Future increase in compound soil drought-heat extremes exacerbated by vegetation greening by Jun Li, Yao Zhang, Emanuele Bevacqua, Jakob Zscheischler, Trevor F. Keenan, Xu Lian, Sha Zhou, Hongying Zhang, Mingzhu He, Shilong Piao

“…Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12–21% of the total increment at the end of 21st century. …”
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