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检索条件"任意字段=3rd International Conference on Signal Processing and Machine Learning, SPML 2020"

共 732 条记录，以下是391-400 订阅

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Information processing in Extended Hodgkin-Huxley Neuron Model 3

Information Processing in Extended Hodgkin-Huxley Neuron Mod...

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3rd international conference on Emerging Technologies in Computer Engineering: machine learning and Internet of Things, ICETCE 2020

作者： Devi, M. Choudhary, Durga Garg, Akhil Ranjan J.N.V.U. Department of Electrical Engineering Jodhpur India

ISBN: (纸本)9781728116839

Models of a variety of neurons share the same form as the Hodgkin-Huxley (HH) neuron and evidence suggests that single-compartment models can capture the key properties of in vivo and in vitro neurons. In this paper we are going to discuss about how the conductance of the excitatory and inhibitory synapse vary when the pre synaptic action potential arrived at the synapse and how this synaptic conductance affects the information transfer in the single neuron. In our model the injected current is replaced with the synaptic current in the HH model. In order to validate the impact of excitatory and inhibitory synapse in the generation of action potential, the extended HH model is examined with various synaptic inputs. © 2020 IEEE.

关键词： Neurons

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

8th EAI International Conference on Advancement of Science a...

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

ISBN: (纸本)9783030806170

The proceedings contain 74 papers. The special focus in this conference is on Advancement of Science and Technology. The topics include: Earliest-Arrival Route: A Global Optimized Communication for Networked Control Systems;Impulsive Noise Mitigation Using Hybrid Nonlinear Preprocessor and Turbo Code in OFDM-PLC System;comparative Analysis of Kalman Filtering and machine learning Based Cardiovascular signal processing Algorithms;modeling and Analysis of Three-Phase Inverter for Induction Motor Drive for Three-Wheel Electric Vehicle Application;performance Analysis of Multicarrier Modulation Techniques for Next Generation Networks;synchronous Generator Excitation Loss Detection Based on Reactive Power Flow Limit;estimation of Synchrophasor Parameters in the Presence of 3rd & 5th Harmonics and White Gaussian Noise;Performance Analysis of Vertical Sectorization in Sub-6-GHz Frequency Bands for 4G Mobile Network Under Realistic Deployment Scenario;power Loss Reduction and Voltage Profile Improvement of Radial Distribution System Through Simultaneous Network Reconfiguration and Distributed Generation Integration;A Comprehensive Review and Evaluation of Classical MPPT Techniques for a Photovoltaic System;antiviral Activity of Aloe pirottae A. Berger Root Extracts Against Influenza A and B Viruses, Picornaviruses and Dengue Virus: An Endemic Plant Species of Ethiopia;dynamic Performance Evaluation of Type-3 Compensator for Switch-Mode Dc-Dc Converter;inset-Feed Rectangular Microstrip Patch Antenna Array Performance Enhancement for 5G Mobile Applications;blockchain Based Green Coffee Supply Chain Management to Improve Traceability and Transparency (Case Study on Sidama Coffee);wireless Local Area Network Intrusion Detection System Using Deep Belief Networks;Direct Adaptive Fuzzy PI Strategy for a Smooth MPPT of Variable Speed Wind Turbines.

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

8th EAI International Conference on Advancement of Science a...

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8th EAI international conference on Advancement of Science and Technology, ICAST 2020

ISBN: (纸本)9783030806200

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Comparing Different Pre-processing Techniques and machine learning Models to Predict PM10 and PM2.5 Concentration in Malaysia 3rd

Comparing Different Pre-processing Techniques and Machine Le...

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3rd international conference on Separation Technology, ICoST 2020

作者： Djarum, Danny Hartanto Ahmad, Zainal Zhang, Jie School of Chemical Engineering Universiti Sains Malaysia Engineering Campus Nibong Tebal Penang14300 Malaysia School of Engineering Merz Court Newcastle University Newcastle upon TyneN1 7RU United Kingdom

ISBN: (纸本)9789811607417

A recent report from world health organization (WHO) showed that there are in total of 3.7 million deaths that were attributed with outdoor ambient pollution. Particulate matter (PM) has been considered by many as the major contributor of air pollution, it poses serious health risks towards human that are mostly associated with cardiovascular and respiratory disease. Even though various studies have been carried out to predict the concentration of PM10 and PM2.5, there are only a handful of papers that focused on the pre-processing aspect of the prediction. In this study, the importance of data pre-processing steps were assessed for PM10 and PM2.5 prediction in Malaysia, these cover: Data cleaning (handling missing values), data transformation (standardization, normalization, robust scaling, and min–max scaling), features selection (univariate linear regression and mutual info regression), and dimensionality reduction (principle component analysis) techniques. Four different machine learning models were utilized for the predictions: Multiple linear regression (MLR), random forest regression (RFR), extra tree regression (ETR), and Decision tree regression with AdaBoost (BTR). The result showed that the best PM10 and PM2.5 prediction accuracy (R2 = 0.97, 0.92) were achieved by using BTR model coupled with normalization and PCA techniques, in which the missing data were imputed with median values. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision tree regression with AdaBoost Extra tree regression Pre-processing Principle component analysis

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Inferring SQL Queries Using Interactivity 2020

Inferring SQL Queries Using Interactivity

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3rd international conference on Networking, Information System and Security (NISS)

作者： Ahkouk, Karamwh Machkour, Mustapha antari, Jilali Ibn Zohr Univ Agadir Morocco

ISBN: (纸本)9781450376341

Interactivity in language processing plays a pivotal role to allow models to better understand how to build the appropriate output. In the task of Natural Language to SQL, the fact of including the users' interactivity can be one of the practical solutions that haven't been studied deeply in the existing works published in the last decade. Using databases by users with limited familiarity in SQL will create an additional obstacle for these users to better exploit the content stored in the database systems. In this paper we present the already published studies and we discuss the utility of using the interactivity to definitely improve the query generation process in order to construct a model that generalize for unseen and complex sentences and to automatically generate the appropriate outputs.

关键词： Natural language Database languages machine translation deep learning

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Detection of Ventricular Late Potentials in Electrocardiograms Using machine learning 3rd

Detection of Ventricular Late Potentials in Electrocardiogra...

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3rd international conference on Computer Science, Engineering and Education Applications, ICCSEEA 2020

作者： Fagan, Xavier Ivanko, Kateryna Ivanushkina, Nataliia Ecole Centrale de Lyon Lyon France Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9783030555054

The first signs of myocardial electrical instability reflect the depletion of regulatory systems at the cellular level. These changes at the first stage may not manifest themselves clinically as functional and anatomical changes. The development of methods for detecting early signs of cardiac abnormalities makes it possible to prevent life threatening pathological processes. Such a task includes eliciting a violation of the electrical homogeneity of the myocardium based on the registration of ventricular late potentials (VLP) by high resolution electrocardiography. The goal of this paper is to evaluate the performance of the Simson method, widely accepted as the standard method for detecting VLP and to compare it to other methods based on time-frequency analysis. The simulation of VLP with different signal-to-noise ratio conducted in this study allows us to generate a variety of VLP of different shapes, which correspond to the states of norm and pathology. Comparison of Simson method, acknowledged as the standard method for VLP detection, time-frequency and wavelet analysis as well as combinations of their features is performed in order to determine whether VLP presence in ECG. machine learning approach is used to find the efficiency of each set of features. A new method for VLP detection based on wavelet analysis is proposed as a suitable replacement for the Simson method. Using the proposed features made it possible to separate healthy and sick patients with an overall accuracy of 99%, wherein 98% of the cases with VLP were correctly identified outperforming the Simson method. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electrocardiograms

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Proceedings of the 3rd international conference on Smart Systems and Inventive Technology, ICSSIT 2020

Proceedings of the 3rd International Conference on Smart Sys...

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3rd international conference on Smart Systems and Inventive Technology, ICSSIT 2020

ISBN: (纸本)9781728158211

The proceedings contain 224 papers. The topics discussed include: jollity chatbot- a contextual AI assistant;machine learning based cardiac arrhythmia detection from ECG signal;test-driven development of automotive software functionality;security facets of cyber physical system;cardiac MR images segmentation for identification of cardiac diseases using fuzzy based approach;design and development of Arduino based multipurpose wheelchair for disabled patients;study and analysis of PD-NOMA in downlink land mobile satellite systems;and cloud load balancing: blockchain deployment at integrated Dopcloud synthesis on healthcare data.

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machine learning based diabetes prediction using decision tree J48 3

Machine learning based diabetes prediction using decision tr...

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3rd international conference on Intelligent Sustainable Systems, ICISS 2020

作者： Posonia, A. Mary Vigneshwari, S. Rani, D. Jamuna Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781728170893

Gestational diabetes is found among majority of the Indian pregnant women, when un-attended may give birth defects to child. Diabetes, which is caused by the rise in level of glucose in blood, has many latest devices to identify from blood samples. Diabetes, when unnoticed may bring many serious diseases like heart attack, kidney disease. In this way there is a requirement for solid research and learning models enhancement in the field of gestational diabetes finding and analysis. This research work has proposed a machine learning knowledge, for example, Decision Tree J48 calculation for diabetes forecast. Decision Tree is one of the powerful classification models. The dataset considered of 768 patients data with major 8 features and a target column with result "Positive"or "Negative". Experiment is done with weka, outcome of our demonstration shows that Decision Tree J48 calculation gives more efficiency with less processing time. © 2020 IEEE.

关键词： Decision trees

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machine learning Based Detection and Classification of Power System Events 3

Machine Learning Based Detection and Classification of Power...

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3rd IEEE international conference on Power, Instrumentation, Control and Computing, PICC 2020

作者： Thomas, Annmy Koshy, Subin Sunitha, R. National Institute of Technology Calicut Department of Electrical Engineering Calicut India

ISBN: (纸本)9781728175904

Rapid rise in energy demand has put a huge pressure on the electrical grid and presented major difficulties for device operators in providing stable and safe power supply. Real-time monitoring of power systems enables timely and effective post-event control actions. Phasor Measurement Units (PMU) may be used to obtain time-synchronized measurement data at very large reporting speeds, mitigating the SCADA technology drawback. This enables PMU to monitor the power system dynamically. The real-time Synchrophasor data is further processed to detect and classify the events in the power system whenever it arises. This paper presents a robust machine learning based event detection and classification technique using PMU data. Wavelet analysis is an important signal processing method for detecting events from PMU data with non-stationary characteristics. machine learning algorithms are used to classify the observed power system events. Significant characteristics are extracted and the classifier is trained using the PMU samples. The features of the machine learning algorithms are optimized to minimize the classification errors. The proposed algorithm to detect and classify the events using wavelet analysis and machine learning algorithms is validated on a WSCC 9-bus system. © 2020 IEEE.

关键词： Wavelet transforms

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Detecting, Contextualizing and Computing Basic Mathematical Equations from Noisy Images using machine learning 3

Detecting, Contextualizing and Computing Basic Mathematical ...

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3rd international conference on Computational Intelligence and Intelligent Systems, CIIS 2020

作者： Ogwok, Daniel Marie Ehlers, Elizabeth University of Johannesburg South Africa

ISBN: (纸本)9781450388085

Various machine learning architectures including neural networks have been designed, developed and used to classify data. These networks have been used for Computer Vision, Speech Recognition and Natural Language processing, to mention but a few and provide near accurate results. One of the major challenges faced in the area of mathematical equational recognition has been background information and noise. This paper presents a system that makes use of image processing and an artificial neural network to recognize, contextualize and compute mathematical equations from noisy images. The system attempts to overcome the challenges faced at segmentation and recognition stages. © 2020 ACM.

关键词： Computer vision

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