Results 31 to 40 of about 354,162 (284)
Proceedings of the AAAI Conference on Artificial Intelligence, 2011 We present a first theoretical analysis of the power of polynomial-time preprocessing for important combinatorial problems from various areas in AI. We consider problems from Constraint Satisfaction, Global Constraints, Satisfiability, Nonmonotonic and Bayesian Reasoning. We show that, subject to a complexity theoretic assumption, none
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Remote SensingImaging has been an important strategy for exploring space weather. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is a joint Chinese Academy of Sciences (CAS) and European Space Agency (ESA) mission, aiming at studying the interaction ...
Jiaqi Wang +4 more
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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients
Известия высших учебных заведений России: Радиоэлектроника, 2022 Introduction. Patients with diabetes are exposed to various cardiovascular risk factors, which lead to an increased risk of cardiac complications. Therefore, the development of a diagnostic system for diabetes and cardiovascular disease (CVD) is a ...
A. Mayya, H. Solieman
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Generalized MIMO transmit preprocessing using pilot symbol assisted rateless codes [PDF]
, 2010 In this paper, we propose a generalized multiple-input multiple-output (MIMO) transmit preprocessing system, where both the channel coding and the linear MIMO transmit precoding components exploit the knowledge of the channel. Moreover, we also propose a
Sheng Chen +8 more
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Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
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The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications
IEEE Transactions on Neural Systems and Rehabilitation EngineeringThe last decade has witnessed a notable surge in deep learning applications for electroencephalography (EEG) data analysis, showing promising improvements over conventional statistical techniques. However, deep learning models can underperform if trained
Federico Del Pup +4 more
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FEBS Letters, EarlyView.Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell +2 more
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InformationSentiment analysis is a crucial component of text mining and natural language processing (NLP), involving the evaluation and classification of text data based on its emotional tone, typically categorized as positive, negative, or neutral.
Zineb Nassr +3 more
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Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
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, 2009 In this contribution we propose and investigate a relay diversity transmission scheme for the direct-sequence code-division multiple-access (DS-CDMA) downlink, where each (destination) mobile terminal (MT) is aided by a cluster of relays for achieving ...
Yang, Lie-Liang, Fang, Wei, Hanzo, Lajos
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