REINFORCEMENT LEARNING FOR BIT-FLIPPING DECODING OF POLAR CODES

Reinforcement Learning for Bit-Flipping Decoding of Polar Codes

A traditional successive cancellation (SC) decoding algorithm produces error propagation in the decoding process.In order to improve the Cushion SC decoding performance, it is important to solve the error propagation.In this paper, we propose a new algorithm combining reinforcement learning and SC flip (SCF) decoding of polar codes, which is called

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Sarcomatoid Carcinoma of Prostate: Report of an Unusual Tumor

Prostatic sarcomatoid carcinoma (SC) is an extremely rare type of malignant tumor of prostate.A 57 years old man presented to the outpatient department with lower urinary tract symptoms and Cups altered bowel habits.Clinical assessment revealed a stony hard prostate with normal serum prostate specific antigen (PSA).Histopathology of the prostatic b

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Detection of autism spectrum disorder using graph representation learning algorithms and deep neural network, based on fMRI signals

IntroductionCan we apply graph representation learning algorithms to identify autism spectrum disorder (ASD) patients within a large brain imaging dataset? ASD is mainly identified by brain functional connectivity patterns.Attempts to unveil the common neural patterns emerged in ASD are the essence of ASD classification.We claim that graph represen

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Pediatric oncology-hematology outreach: Evaluation of patient consultations by teleconferences between Indonesian and Dutch academic hospitals

Background: Improving the quality of care in resource limited settings through an Accessories outreach program is challenging.Teleconferencing is increasingly being used and considered a breakthrough in medical education.We evaluated adherence with childhood oncology-hematology teleconferences between two academic hospitals in Indonesia and Netherl

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