Chronic kidney disease (CKD) is a prominent disease that causes loss of functionality in the kidney. Doctors can now more easily gather patient health status data due to the growth of the Internet of Health Things (Io...
详细信息
Manufacturers must be able to figure out the most suitable technique capable of generating rapid and accurate performance when developing a precise modelling approach for the development of an efficient machining proc...
详细信息
Machine learning-based methods have emerged as a promising solution to accurate battery capacity estimation for battery management ***,they are generally developed in a supervised manner which requires a considerable ...
详细信息
Machine learning-based methods have emerged as a promising solution to accurate battery capacity estimation for battery management ***,they are generally developed in a supervised manner which requires a considerable number of input features and corresponding capacities,leading to prohibitive costs and efforts for data *** response to this issue,this study proposes a convolutional neural network(CNN)based method to perform end-to-end capacity estimation by taking only raw impedance spectra as *** importantly,an input reconstruction module is devised to effectively exploit impedance spectra without corresponding capacities in the training process,thereby significantly alleviating the cost of collecting training *** large battery degradation datasets encompassing over 4700 impedance spectra are developed to validate the proposed *** results show that accurate capacity estimation can be achieved when substantial training samples with measured capacities are ***,the estimation performance of supervised machine learning algorithms sharply deteriorates when fewer samples with measured capacities are *** this case,the proposed method outperforms supervised benchmarks and can reduce the root mean square error by up to 50.66%.A further validation under different current rates and states of charge confirms the effectiveness of the proposed *** method provides a flexible approach to take advantage of unlabelled samples for developing data-driven models and is promising to be generalised to other battery management tasks.
With the increased usage of two-wheeler vehicles, traffic accidents are being recorded at an alarming rate each year. This research paper introduces RideGuard, an innovative helmet project designed to enhance rider sa...
详细信息
The AI-Enhanced Learning Assistant Platform is a revolutionary system designed to enhance learning, with cutting-edge features like question and answer generation, answer evaluation, identification of weak areas, recu...
详细信息
Orthogonal time frequency space (OTFS) is envisioned as a highly promising modulation technique due to its superior performance in high-mobility scenarios. Meanwhile, non-orthogonal multiple access (NOMA) stands out a...
详细信息
The difficulty of successfully scanning handwritten text arises from variances in style, size, and orientation, which affect handwriting optical character recognition (OCR). This study provides a novel strategy that i...
详细信息
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health withou...
详细信息
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health without premature treatment and cause *** the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observa-tion,which has become necessary to classify the type in cancer *** research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature *** paper introduces a Maximal Region-Based Candidate Feature Selection(MRCFS)for early risk diagnosing using Soft-Max Feed Forward Neural Classification(SMF2NC)to solve the above *** predictive model is based on a different relational feature learning model,which is possessed to candidate selection to reduce the *** redundant features are processed marginal weight rates for observing similar features’variants and the absolute *** neural hidden layers are trained using the Sigmoid Activation Function(SAF)to create the logical condition for feed-forward ***,the maximal features are introduced to invite a deep neural network con-structed on the Feed Forward Recurrent Neural Network(FFRNN).The classifier produces higher classification accuracy than the previous methods and observes the cancer detection,which is recommended for early diagnosis.
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of ...
详细信息
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage *** potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data *** creates a complex nature to increase the storage consumption under *** resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based Deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud ***,preprocessing is done using the sparse augmentation ***,the preprocessed files are segmented into blocks to make *** block of the contents is compared with other files through Semantic Content Source Deduplication(SCSD),which identifies the similar content presence between the *** on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a ***,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match *** implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.
In recent years,the demand for real-time data processing has been increasing,and various stream processing systems have *** the amount of data input to the stream processing system fluctuates,the computing resources r...
详细信息
In recent years,the demand for real-time data processing has been increasing,and various stream processing systems have *** the amount of data input to the stream processing system fluctuates,the computing resources required by the stream processing job will also *** resources used by stream processing jobs need to be adjusted according to load changes,avoiding the waste of computing *** present,existing works adjust stream processing jobs based on the assumption that there is a linear relationship between the operator parallelism and operator resource consumption(e.g.,throughput),which makes a significant deviation when the operator parallelism *** paper proposes a nonlinear model to represent operator *** divide the operator performance into three stages,the Non-competition stage,the Non-full competition stage,and the Full competition *** our proposed performance model,given the parallelism of the operator,we can accurately predict the CPU utilization and operator *** with actual experiments,the prediction error of our model is below 5%.We also propose a quick accurate auto-scaling(QAAS)method that uses the operator performance model to implement the auto-scaling of the operator parallelism of the Flink *** to previous work,QAAS is able to maintain stable job performance under load changes,minimizing the number of job adjustments and reducing data backlogs by 50%.
暂无评论