The proceedings contain 11 papers. The topics discussed include: multiple ensembling techniques for monitoring the physical activities and predicting the performance of the students;a comprehensive review of influence...
The proceedings contain 11 papers. The topics discussed include: multiple ensembling techniques for monitoring the physical activities and predicting the performance of the students;a comprehensive review of influence node identification in complex networks;improving lifestyle of visually impaired people using virtual reality;algorithm for optimization in medical image processing applied in heterogeneous architecture;application of real-time operating systems in the design of medical devices;smart farming using artificial intelligence;optimized cluster centroids for segmentation of skin cancer using triangular intuitionistic fuzzy sets;analog and digital RoF spatial Mux MIMO-LTE system based A2 (arithmetic Aquila) optimization model for 5G network;comparison of state - of - art deep learningalgorithms for detecting cyberbullying in twitter;and stock market technical analysis using Japanese candlesticks and machinelearning.
Energy industry has been revolutionized rapidly over past few decades. The consumption of electricity from the renewable sources is increasing speedily due to the low maintenance and environmental friendly nature. Now...
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This project aimed to develop an automated system for extracting data from the FusionSolar monitoring platform to evaluate solar energy system performance using machinelearning. Implemented in KNIME, the system autom...
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Labeled datasets are essential for supervised machinelearning. Various data labeling tools have been built to collect labels in different usage scenarios. However, developing labeling tools is timeconsuming, costly, ...
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ISBN:
(纸本)9781450391573
Labeled datasets are essential for supervised machinelearning. Various data labeling tools have been built to collect labels in different usage scenarios. However, developing labeling tools is timeconsuming, costly, and expertise-demanding on software development. In this paper, we propose a conceptual framework for data labeling and OneLabeler based on the conceptual framework to support easy building of labeling tools for diverse usage scenarios. The framework consists of common modules and states in labeling tools summarized through coding of existing tools. OneLabeler supports confguration and composition of common software modules through visual programming to build data labeling tools. A module can be a human, machine, or mixed computation procedure in data labeling. We demonstrate the expressiveness and utility of the system through ten example labeling tools built with OneLabeler. A user study with developers provides evidence that OneLabeler supports efcient building of diverse data labeling tools.
Data mining and machinelearning are gaining popularity for fraud detection due to their effective results to cater the exponentially growing card transactions that comes with the fast-growing frauds. The aim of this ...
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The proceedings contain 22 papers. The special focus in this conference is on Distributed computing and Artificial Intelligence. The topics include: Computer Vision: A Review on 3D Object Recognition;An IoUT-Base...
ISBN:
(纸本)9783031232091
The proceedings contain 22 papers. The special focus in this conference is on Distributed computing and Artificial Intelligence. The topics include: Computer Vision: A Review on 3D Object Recognition;An IoUT-Based Platform for Managing Underwater Cultural Heritage;overview: Security in 5G Wireless Systems;a Study on the Application of Protein Language Models in the Analysis of Membrane Proteins;visualization for Infection Analysis and Decision Support in Hospitals;An Intelligent and Green E-healthcare Model for an Early Diagnosis of Medical Images as an IoMT Application;towards Highly Performant Context Awareness in the Internet of Things;adaptive System to Manage User Comfort Preferences and Conflicts at Everyday Environments;ML-Based Automation of Constraint Satisfaction Model Transformation and Solver Configuration;race Condition Error Detection in a Program Executed on a Device with Limited Memory Resources;the Impact of Covid-19 on Student Mental Health and Online learning Experience;Threat Detection in URLs by Applying machinelearningalgorithms*;an Approach to Simulate Malware Propagation in the Internet of Drones;the Use of Corporate Architecture in Planning and Automation of Production Processes;Towards Ontology-Based End-to-End Domain-Oriented KBQA System;TFEEC: Turkish Financial Event Extraction Corpus;denial of Service Attack Detection Based on Feature Extraction and Supervised Techniques;automating the Implementation of Unsupervised machinelearning Processes in Smart Cities Scenarios;Intelligent Model Hotel Energy Demand Forecasting by Means of LSTM and GRU Neural Networks;explainable Artificial Intelligence on Smart Human Mobility: A Comparative Study Approach.
The proceedings contain 89 papers. The topics discussed include: qualitative assessment of cooking oil using diffuse reflectance spectroscopy technique;emotion classification of songs using deep learning;a review on p...
ISBN:
(纸本)9781665486637
The proceedings contain 89 papers. The topics discussed include: qualitative assessment of cooking oil using diffuse reflectance spectroscopy technique;emotion classification of songs using deep learning;a review on power electronics technologies and applications for EV battery charging systems;feature selection techniques for bioinformatics data analysis;sonic waves travel-time prediction: when machinelearning meets geophysics;a computational approach for predicting the termination of covid-19;diabetic retinopathy detection: improving accuracy using multiple transfer learning features from pre-trained deep learning networks;towards energy-aware scheduling of scientific workflows;a comparative hybrid optimization analysis of load frequency control in a single area power system using metaheuristic algorithms and linear quadratic regulator;and conceptualizing the implementation of peer-to-peer (P2P) energy trading in Malaysia through stakeholder engagement.
The proceedings contain 399 papers. The topics discussed include: wavelet based speech enhancement algorithm for hearing aid application;a review of image processing applications based on Raspberry-Pi;pest detection i...
ISBN:
(纸本)9781665408165
The proceedings contain 399 papers. The topics discussed include: wavelet based speech enhancement algorithm for hearing aid application;a review of image processing applications based on Raspberry-Pi;pest detection in crops using deep neural networks;kitchen safety and security system for children;intrusion detection system for databases: a hybrid metaheuristic clustering and closed sequential pattern mining approach;diabetes prediction using machinelearningalgorithms;integration of optimization techniques to improve performance of machinelearning system;role of cloud security in big data processing for healthcare system;behavioral analysis of students by integrated radial curvature and facial action coding system using DCNN;an efficient mouse tracking system using facial gestures;automatic detection of white blood cancer from blood cells using novel machinelearning techniques;portable smart storage units for agricultural products;and smart access control system for covid safety smart access control system during covid.
The proceedings contain 99 papers. The topics discussed include: parameter analysis and introduction of new features based on LSTM stock price prediction model;research on early warning of wire icing risk level based ...
ISBN:
(纸本)9781665454704
The proceedings contain 99 papers. The topics discussed include: parameter analysis and introduction of new features based on LSTM stock price prediction model;research on early warning of wire icing risk level based on machinelearning;overload data mining method for mass data of power network DCS based on decision tree;development of mass data quality improvement system for distribution network;research on task reliability test case generation technology based on xml tag description;cement concrete strength quality evaluation by dynamic time series features;research on the selection of stock prediction model feature for long-term stock market trends based on K-nearest neighbor algorithms;comprehensive evaluation of suppliers based on analytic hierarchy process;a multi-objective (MO) optimal management model of enterprise economy based on memetic algorithm;and financial data evaluation simulation on account of machinelearning and mobile information technology.
The problem of online learning with graph feedback has been extensively studied in the literature due to its generality and potential to model various learning tasks. Existing works mainly study the adversarial and st...
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The problem of online learning with graph feedback has been extensively studied in the literature due to its generality and potential to model various learning tasks. Existing works mainly study the adversarial and stochastic feedback separately. If the prior knowledge of the feedback mechanism is unavailable or wrong, such specially designed algorithms could suffer great loss. To avoid this problem, Erez & Koren (2021) try to optimize for both environments. However, they assume the feedback graphs are undirected and each vertex has a self-loop, which compromises the generality of the framework and may not be satisfied in applications. With a general feedback graph, the observation of an arm may not be available when this arm is pulled, which makes the exploration more expensive and the algorithms more challenging to perform optimally in both environments. In this work, we overcome this difficulty by a new trade-off mechanism with a carefully-designed proportion for exploration and exploitation. We prove the proposed algorithm simultaneously achieves poly log T regret in the stochastic setting and minimax-optimal regret of (O) over tilde (T-2/3) in the adversarial setting where T is the horizon and (O) over tilde hides parameters independent of T as well as logarithmic terms. To our knowledge, this is the first best-of-both-worlds result for general feedback graphs.
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