Brain-wave passwords are a highly efficient method of safeguarding sensitive data. Even though biometric identification tools like fingerprints, face recognition and voice detection are commonly used, they can be repl...
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Quality of training data is a major issue in machine learning. In some domains, data samples may be hard to obtain, and detection of problematic samples becomes essential. This work proposes to use explainable AI to e...
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In recommender systems, click-through rate (CTR) prediction is an important task. Previous approaches model users' preference based on their historical behaviors, but users' interests change over time, so it&#...
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The rapid growth of electric vehicles (EVs) has led to significant challenges in providing efficient and sustainable charging solutions. This paper addresses the battery swapping station (BSS) recommendation problem b...
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Cervical Cancer(CC)is a rapidly growing disease among women throughout the world,especially in developed and developing *** this many women have ***,it is curable if it can be diagnosed and detected at an early stage ...
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Cervical Cancer(CC)is a rapidly growing disease among women throughout the world,especially in developed and developing *** this many women have ***,it is curable if it can be diagnosed and detected at an early stage and taken proper *** the high cost,awareness,highly equipped diagnosis environment,and availability of screening tests is a major barrier to participating in screening or clinical test diagnoses to detect CC at an early *** solve this issue,the study focuses on building a deep learning-based automated system to diagnose CC in the early stage using cervix cell *** system is designed using the YOLOv5(You Only Look Once Version 5)model,which is a deep learning *** build the model,cervical cancer pap-smear test image datasets were collected from an open-source repository and these were labeled and *** the YOLOv5 models were applied to the labeled dataset to train the *** versions of the YOLOv5 model were applied in this study to find the best fit model for building the automated system to diagnose CC at an early *** of the model’s variations performed *** model can effectively detect cervical cancerous cell,according to the findings of the *** the medical field,our study will be quite *** can be a good option for radiologists and help them make the best selections possible.
At present, the prediction effect of using deep learning to predict futures prices is usually not good. A Multi Contract LSTM model (MC-LSTM) was designed and implemented to predict futures prices by utilizing actual ...
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作者：
Zhang, ZiyiYan, RongYuan, WeiCollege of Computer Science
Inner Mongolia University Inner Mongolia Key Laboratory of Mongolian Information Processing Technology National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot010021 China
Identifying influential spreaders is a hot topic in complex network research. While centrality-based algorithms are easy to implement, they often have lower accuracy. Topology-based algorithms are effective for identi...
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Nowadays different corporate sectors in the world want all digital works done by human to be automated and done very quickly. Here comes Robotic Process Automation (RPA) technology which helps in building software rob...
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Hadoop, as an open-source implementation of the MapReduce paradigm, is increasingly being used in both industry and academia for large-scale data processing. Yarn, one of the core components of the second-generation H...
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ISBN:
(纸本)9798350349184;9798350349191
Hadoop, as an open-source implementation of the MapReduce paradigm, is increasingly being used in both industry and academia for large-scale data processing. Yarn, one of the core components of the second-generation Hadoop, manages cluster resources and job scheduling. Minimizing the total completion time of a set of MapReduce jobs is a point worth exploring in terms of Yarn's performance. Hadoop's default schedulers, including first-in-first-out (FIFO), Fair, and Capacity, do not consider the characteristics and preferences of job resource demand, resulting in insufficient resource utilization. Therefore, in this paper, a new job scheduler named Q-scheduler is proposed. It uses reinforcement learning (RL) to accumulate scheduling experience autonomously based on the Fair scheduler. Specifically, the proposed scheduler consists of a Classifier and a Decider. The Classifier classifies jobs through similarity measurement, and the Decider, as an agent with a Q-Table, considers the execution order of different job classes and updates the stateaction values of the Q-Table to learn optimal scheduling. The experimental results show that Q-scheduler can reduce the total completion time of the job set and improve resource utilization.
Among the spectrum of dermatological conditions, melanoma stands as the most lethal, emanating from melanocytes-cells responsible for producing melanin, the skin's pigment. Distinctively more aggressive than its c...
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