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A column-shared histogramming TDC with pixel-to-pixel coincidence detection and compact analog counters for Flash LiDAR sensor
This study presents a column-shared hTDC with pixel-to-pixel coincidence detection and compact analog pulse counters. The column-shared architecture...
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End-to-End No-wait Scheduling for Time-Triggered Streams in Mixed Wired-Wireless Networks
Proprietary communication technologies for time-critical communication in industrial environments are being gradually replaced by Time-sensitive...
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Augmenting Cervical Cancer Analysis with Deep Learning Classification and Topography Selection Using Artificial Bee Colony Optimization
According to the research and study, cervical cancer has risen to develop the fourth most communal malignancy to strike women. Five different forms...
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Deep learning and embeddings-based approaches for keyphrase extraction: a literature review
Keyphrase extraction is a subtask of natural language processing referring to the automatic extraction of salient terms that semantically capture the...
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Enhancing Forecasting Accuracy with a Moving Average-Integrated Hybrid ARIMA-LSTM Model
This research provides a time series forecasting model that is hybrid which combines Long Short-Term Memory (LSTM) and Autoregressive Integrated...
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Multimedia Educational System and its Improvement Using AI Model for a Higher Education Platform
In the world of technology today, the hardware, applications, and online computing service have transformed instructional approaches and classroom...
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Taxonomy of deep learning-based intrusion detection system approaches in fog computing: a systematic review
The Internet of Things (IoT) has been used in various aspects. Fundamental security issues must be addressed to accelerate and develop the Internet...
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DQN-PACG: load regulation method based on DQN and multivariate prediction model
Demand response plays a pivotal role in modern smart grid systems, aiding in balancing energy consumption. However, the increasing energy demands of...
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Iterative missing value imputation based on feature importance
Many datasets suffer from missing values due to various reasons, which not only increases the processing difficulty of related tasks but also reduces...
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A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of...
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VAE-GNA: a variational autoencoder with Gaussian neurons in the latent space and attention mechanisms
Variational autoencoders (VAEs) are generative models known for learning compact and continuous latent representations of data. While they have...
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LightCapsGNN: light capsule graph neural network for graph classification
Graph neural networks (GNNs) have achieved excellent performances in many graph-related tasks. However, they need appropriate pooling operations to...
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Application of QPSO-BPSO in fault self-healing of distributed power distribution networks
With the widespread application of distributed power sources in distribution networks, fault self-healing technology has become the key to ensuring...
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Frequency stability of new energy power systems based on VSG adaptive energy storage coordinated control strategy
A self-adaptive energy storage coordination control strategy based on virtual synchronous machine technology was studied and designed to address the...
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Challenges to Applying Role Playing in Software Engineering Education: A Taxonomy Derived from a Rapid Literature Review
Role Playing (RP) serves as an instructional approach to enrich the learning experience for students and boost their learning by the effective...
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Early Diagnosis of COVID-19 Disease by ChestNet Convolutional Neural Network from Chest Xray Images
In the absence of a vaccine, prompt isolation and medical care are necessary to prevent and contain the COVID-19 pandemic. This requires a quick and...
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Neural Networks and the Nonlinear Feynman–Kac Theorem Applied to Financial Options Pricing
The classic financial market model proposed by Black and Scholes allows solving, under a series of simplifying assumptions, the problem of valuing...
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Cleaning ECG with Deep Learning: A Denoiser Tested in Industrial Settings
As the popularity of wearables continues to scale, a substantial portion of the population has now access to (self-)monitorization of cardiovascular...
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Diagnosing Dementia Disorder Detection Using an Improved Eliminate Particle Swarm Optimization (IEPSO) Based on Convolutional Neural Networks
Dementia is an un-repairable and continuous disease that affects a person's mental health. Symptoms of Dementia may vary from one person to another,...
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Blind Color Image Watermarking Using Deep Artificial Neural Network Using Statistical Features
With increasing digital content over the internet it is very important to secure the digital contents in such a way that the identity and integrity...
