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Papers tagged with "Memory"
Predicting Ride Costs With Advanced Regression Models
Accurate Ride Cost Prediction Has Become Increasingly Important As Ride-hailing Businesses Continue To Grow, The Ability To Accurately Predict Rides Costs Becomes More Crucial Than Ever, As It Directly Influences Pricing Efficiency, Operati...
COMPARATIVE SEISMIC ANALYSIS OF FRAMES WITH SHAPE MEMORY ALLOY SLIP FRICTION DAMPERS
A New Hybrid Shape Memory Alloy (SMA)-based Damper Was Developed To Address Two Major Challenges For SMA-based Seismic Control Devices: (i) Insufficient Force Capacity For Real-world Application And (ii) Relatively Low Energy Dissipation Ca...
Automatic Image Captioning System Using CNN-LSTM: A Deep Learning Approach
Automatic Image Captioning Is A Challenging Task At The Intersection Of Computer Vision And Natural Language Processing That Involves Generating Semantically Meaningful Textual Descriptions From Visual Input. This Paper Presents A Deep Lear...
HYBRID MACHINE LEARNING AND DEEP LEARNING-BASED VPN NETWORK TRAFFIC ANOMALY DETECTION SYSTEM
The Rapid Growth Of Internet Usage And The Widespread Adoption Of Virtual Private Networks (VPNs) Have Significantly Enhanced Secure Communication, But Have Also Introduced New Challenges In Detecting Cyber Threats Hidden Within Encrypted T...
An Intelligent Hybrid GCN-LSTM Model For Energy Stock Price Forecasting With Temporal Dynamics And Inter-Stock Correlation
Energy Sector Stock Price Prediction Is A Critical Yet Challenging Task In Financial Forecasting, Characterized By High Volatility, Non-linearity, And Complex Interdependencies Driven By Geopolitical Events, Regulatory Shifts, And Commodity...
A Hybrid GNN-LSTM Model For Feedback-Free Adaptive Modulation And Coding In Massive MIMO
Adaptive Modulation And Coding (AMC) Is A Key Enabler For Achieving High Spectral Efficiency And Reliability In Massive Multiple-Input Multiple-Output (MIMO) Systems. Conventional AMC Techniques, However, Rely Heavily On Explicit Channel St...
AQI Index Analyzer Using Machine Learning
Air Quality Index AQI Prediction Is A Critical Public Health Task That Involves Leveraging Data-driven Methods To Forecast Pollutant Concentrations And The Resulting AQI Under Dynamic Environmental And Meteorological Conditions1. This R...
Echo AI : An AI Memory Assistant
In The Era Of Information Overload, Individuals Struggle To Manage And Retrieve Personal Memories And Knowledge Effectively. This Paper Presents ECHO AI, An Intelligent Memory Assistant That Leverages Advanced Natural Language Processing An...
Human Sentiment Sound RNN Emotional Analysis With Django interface
Human Sentiment Sound RNNs For Emotional Audio Analysis With A Django Interface" Explores The Intersection Of Deep Learning And Human-computer Interaction By Developing A Recurrent Neural Network (RNN) Model Tailored To Analyze And Classify...
RNN-Based Heartbeat Sound Analysis With Django Integration
Congenital Heart Diseases (CHDs) Are Among The Leading Causes Of Mortality Worldwide, Necessitating Early And Accurate Detection Methods.Improving Patient Outcomes And Facilitating Prompt Medical Intervention Depend Heavily On Early Diagnos...
Deep Learning Approaches For Brain State Detection Under Anesthesia: A CNN-LSTM Framework
This Research Presents An Automated Approach To Analyzing Brain States During Anesthesia Using Convolutional Neural Networks (CNNs) And Long Short-Term Memory (LSTM) Networks. By Leveraging The Spatial Feature Extraction Power Of CNNs And T...
AN AREA-EFFICIENT LOW-POWER FULLY NON-VOLATILE FULL-ADDER USING RECONFIGURABLE LOGIC
The Miniaturization Of CMOS Results In High Static Power Consumption In Traditional Computer System. Logic-in-memory (LIM) Architecture Based On Emerging Non-volatile Memory (NVM) Can Significantly Reduce Static Power Consumption By Embeddi...
DDOS DETECTION IN SOFTWARE DEFINED NETWORK USING FEDERATED LEARNING
Distributed Denial Of Service Attacks Have Become A Great Concern For Security In Software Defined Networking(SDN), As They Mostly Overload Centralized Security Mechanisms. In This Work, A Federated Learning-Based Intrusion Detection System...
A STUDY ON TYPE 2 DIABETES PREDICTION USING DEEP LEARNING TECHNIQUES
T2DM, Or Type 2 Diabetes Mellitus, Has Become A Major Global Health Concern Due To Its High Prevalence And Related Medical Expenses. With An Emphasis On Data-driven Strategies That Make Use Of Patient Health Information, Such As Blood Sugar...
URBAN STREET CLEANLINESS ASSESSMENT USING MOBILE EDGE COMPUTING AND DEEP LEARNING
Object Detection Plays A Vital Role In Computer Vision, With Numerous Applications, Including Smart City Development. City Managers Invest Significant Resources In Cleaning Street Garbage Due To Its Unpredictable Appearance. As Deep Learnin...