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检索条件"任意字段=Proceedings of the 7th International Conference on Algorithms, Computing and Systems"

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7th international conference on Swarm, Evolutionary, and Memetic computing, SEMCCO 2019, and 5th international conference on Fuzzy and Neural computing, FANCCO 2019

7th International Conference on Swarm, Evolutionary, and Mem...

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7th international conference on Swarm, Evolutionary, and Memetic computing, SEMCCO 2019, and 5th international conference on Fuzzy and Neural computing, FANCCO 2019

ISBN: (纸本)9783030378370

the proceedings contain 18 papers. the special focus in this conference is on Swarm, Evolutionary, and Memetic computing. the topics include: Competition of Strategies in jSO Algorithm;neural Swarm Virus;wrapper-Based Feature Selection Using Self-adaptive Differential Evolution;SOMA T3A for Solving the 100-Digit Challenge;tracking the Exploration and Exploitation in Stochastic Population-Based Nature-Inspired algorithms Using Recurrence Plots;insight into Adaptive Differential Evolution Variants with Unconventional Randomization Schemes;virtual Measurement of the Backlash Gap in Industrial Manipulators;hybrid Elephant Herding Optimization Approach for Cloud computing Load Scheduling;pareto-Based Self-organizing Migrating Algorithm Solving 100-Digit Challenge;population Size in Differential Evolution;channel Assignment with Ant Colony Optimization;self-organizing Migrating Algorithm with Non-binary Perturbation;Boundary Strategies for Self-organizing Migrating Algorithm Analyzed Using CEC’17 Benchmark;MOEA with Approximate Nondominated Sorting Based on Sum of Normalized Objectives;evolutionary Bi-objective Optimization and Knowledge Extraction for Electronic and Automotive Cooling;classification of Stock Market Trends with Confidence-Based Selective Predictions.

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Ensemble Framework for Bankruptcy Prediction 9

Ensemble Framework for Bankruptcy Prediction

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Joint 9th international conference on Digital Arts, Media and Technology with 7th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI DAMT and NCON 2024

作者： Chaising, Supansa Srimaharaj, Wanus School of Management Chiang Rai57100 Thailand Payap University The International College Chiang Mai50000 Thailand

ISBN: (纸本)9798350318241

When a company faces bankruptcy, it refers to a there is insufficient cash available to pay bills, or the total value of its assets is less than its overall liabilities, including potential future obligations. It is significant to recognize or predict business bankruptcy promptly when companies face financial difficulties. this research introduces an ensemble framework for bankruptcy prediction, which integrates different predictive models to enhance overall prediction performance. the proposed framework is represented as an ensemble learning method that combines a neural network model and a logistic regression model, leveraging the unique strengths of each technique to provide accurate bankruptcy predictions. the experiment involved a dataset comprising 78,682 samples. the prediction outcomes of the proposed ensemble learning method were compared with those of general neural network, deep neural network, and logistic regression models, utilizing various metrics such as accuracy, ROC curve, AUC, precision, recall, and F1-score. the comparative result highlighted that the proposed method achieved the highest accuracy (93.54%), demonstrating high performance in the domain of bankruptcy prediction compared to the other models. © 2024 IEEE.

关键词： Learning systems

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international conference on Man Machine systems, ICoMMS 2021

International Conference on Man Machine Systems, ICoMMS 2021

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7th international conference on Man Machine systems, ICoMMS 2021

the proceedings contain 71 papers. the topics discussed include: design and development of IoT based garbage monitoring and management system;performance analysis of different classifiers in segmenting point cloud data;design of a mechatronic interface with compliant manipulator for robot assisted echocardiography;visual tracking using multi-layer appearance approach;defects detection algorithm of Harumanis mango for quality assessment using color features extraction;analysis of human object lifting operation force using power assist device;development of aquaculture water quality real-time monitoring using multi-sensory system and Internet of things;research on effects and influence by presenting information on priority order and oncoming vehicle to operators for teleoperation of multiple autonomous vehicles;and a study of extreme learning machine on small sample-sized classification problems.

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7th international Symposium on Intelligent Informatics, ISI 2022

7th International Symposium on Intelligent Informatics, ISI ...

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7th international Symposium on Intelligent Informatics, ISI 2022

ISBN: (纸本)9789811980930

the proceedings contain 37 papers. the special focus in this conference is on Intelligent Informatics. the topics include: Segmentation Approach for Nucleus Cytoplasm of Ewing Sarcoma;Deep Neuroevolution Squeezes More Out of Small Neural Networks and Small Training Sets: Sample Application to MRI Brain Sequence Classification;abstractive Text Summarization of Hindi Corpus Using Transformer Encoder-Decoder Model;automatic Text Classification for Web-Based Malayalam Documents;question and Answer Generation from Text Using Transformers;A Comparative Study of Spam SMS Detection Techniques for English Content Using Supervised Machine Learning algorithms;Evaluation of Tweet Sentiments Using NLP;cascaded Feature Vector Assisted Blood Vessel Segmentation from Retinal Images;Unsupervised Deep Clustering and Reinforcement Learning Can Accurately Segment MRI Brain Tumors with Very Small Training Sets;towards Frugal Artificial Intelligence: Exploring Neural Network Pruning and Binarization;EEG-Based Emotion Recognition Using an Ensemble Learning Algorithm;imaging and Vision Development Platform with Algorithm Library for Intelligent Vision systems;pulse Decomposition Analysis Based Non-invasive Diabetes Detection System;noise Classification and Removal in Compressively Sensed Surveillance Videos Using Statistical Measures;DNA and Improved Sine Map Based Video Encryption;the Analysis of Srgb Color Space Based Density for Brain Tumor Segmentation;improved Kapur Entropy-Based Lung Nodule Segmentation in X-ray Images;comparative Analysis of Various Standards for Medical Image Compression;Repetitive Filtering-Based Intra Prediction Scheme for HEVC;identification and Counting of Blood Cells Using Machine Learning and Image Processing;practical Implications of Dequantization on Machine Learning algorithms: A Survey;EDGE-Based ML in W-Band Target Micro-Doppler Feature Extraction;emotion Detection Using Speech Analysis;FED6G: Chameleon Learning for Network Slice Management in Beyond 5G

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2021 international conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2021

2021 International Conference on Cyber Situational Awareness...

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7th international conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2021

ISBN: (纸本)9781665425292

the proceedings contain 34 papers. the topics discussed include: navigation anomaly detection: an added value for maritime cyber situational awareness;file slack handling tool;feature vulnerability and robustness assessment against adversarial machine learning attacks;intelligent intrusion detection system for smart grid applications;secure (S)hell: introducing an SSH deception proxy framework;energy efficiency in low power and lossy networks;the cybersecurity (CSEC) questionnaire: individual differences in unintentional insider threat behaviors;evaluating threat modeling tools: Microsoft TMT versus OWASP threat dragon;and revolution and stability in the study of the human factor in the security of information systems field. a systematic literature review over 30 years of publication.

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Machine Learning Applications in Azure for Enhanced E-commerce Customer Sentiment Analysis 7

Machine Learning Applications in Azure for Enhanced E-commer...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： De, Tanmoy Dankan Gowda, V. thirani, Pooja Prasad, K.D.V. Srinivas, Ved Gireesh, Namineni Symbiosis Institute of Business Management Hyderabad Symbiosis International University Faculty of Management Pune India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Symbiosis Institute of Business Management Hyderabad Symbiosis International University Department of Management Pune India Symbiosis Institute of Business Management Hyderabad Pune India Thiagarajar School of Management Department of Human Resources Tamil Nadu Madurai India Mohan Babu University School of Engineering Department of Electronics and Communications Engineering Tirupati India

ISBN: (纸本)9798350372816

this study performs both qualitative and quantitative examination of sentiment analysis applied to the E-Commerce platforms with machine learning technologies being the main component which are run on Microsoft Azure cloud through a high focus on customers' emotional targets and feedback, it is assumed that this study will follow the effects of sentiment analysis on e-commerce businesses in general. According to our analysis from the leading e-commerce A-to-Z and grocery companies in India for the past three years through the power of machine learning on Azure we are able to weave intelligence into your solutions. the work describes the final research that globalizes sentiment analysis in the process of preceding customers' interaction. Moreover, another point of discussion revolves around possibility of the advantages, including weaknesses, that come from conducting reviews of online customers. the research which encompasses this provides the significant contribution on exploiting machine learning for doing the improvement of e-commerce experience with the in depth analysis of sentiment. © 2024 IEEE.

关键词： Cloud platforms

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ADL-VTON: Advanced Deep Learning Virtual Try-On Technique 7

ADL-VTON: Advanced Deep Learning Virtual Try-On Technique

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7th international conference on Image Information Processing, ICIIP 2023

作者： Tajinder Sharma, Sahil International Institute of Information Technology Bangalore India Ulster University School of Computing Engineering And Intelligent Systems Londonderry United Kingdom

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371406

the objective of Image-based Virtual Try-On (VTO) is to effectively superimpose retail clothing items onto a specific individual, creating a seamless integration between the garments and the person. Despite significant advancements in VTO (Virtual Try-On) technology, numerous techniques struggle to maintain semantic integrity, particularly when faced with difficult inputs like complicated human poses and complex clothing designs. the presence of these discrepancies undermines the overall quality of the final visual outputs, hence reducing both the user experience and the effectiveness of the Virtual Try-On (VTO) system. this study provides an in-depth investigation into the enduring problem by utilizing advanced deep learning techniques. In addition to just recognizing the obstacles, this study emphasizes a thorough comprehension derived from extensive literature reviews and practical code experiments. We aim to tackle the significant issue of preserving semantic detail in VTO applications by implementing cutting-edge techniques. this article adopts a future-oriented approach to not only illuminate current constraints but also provide a trajectory for forthcoming initiatives that seek to enhance the virtual retail domain and fully actualize the capabilities of AI-driven fashion technology. © 2023 IEEE.

关键词： Computer vision

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Using Data Analysis Methods for Predicting the Concentration of Toxic Elements in Soil 12

Using Data Analysis Methods for Predicting the Concentration...

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12th IEEE international conference on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications, IDAACS 2023

作者： Naizabayeva, Lyazat Zakirova, Gulnara International Information Technology University Almaty050000 Kazakhstan

ISBN: (纸本)9798350358056

this article is aimed at the selection of machine learning algorithms for the perception of elements in the composition of the soil. In our study, machine learning aims to track changes in the toxicity of contaminated soils in order to predict the level of human health hazard of a contaminated soil condition. For this, the following tasks were set: 1) collection and analysis of data on the types of soil toxicity;2) study of a mathematical model of toxicity to assess the level of resistance;3) testing the concentration of toxic elements in soils using four machine learning algorithms. Four machine learning algorithms were tested in the article to predict the content of heavy metals in the soil. the results show that the use of machine learning algorithms allows achieving a high degree of prediction of harmful elements concentrations in soils, which can be useful for making decisions on managing pollution sites. Further improvement of data accuracy and selection of the model and algorithm can also increase the accuracy of prediction. As a result of forecasting using the K-Nearest Neighbors algorithm, the accuracy of the model was achieved at the level of 68%, and using the Decision Tree - 69%. the results of the experiment make it possible to predict the measures of danger to human health from the state of contaminated soil. this will help reduce the risks of the relationship between soil pollution and human health. the obtained results can be useful for specialists in environmental protection, land resource management, and decision-making. © 2023 IEEE.

关键词： data structure intellectual analysis predicting soil toxic elements

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8th international Ergonomics conference, ERGONOMICS 2020

8th International Ergonomics Conference, ERGONOMICS 2020

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8th international Ergonomics conference, ERGONOMICS 2020

ISBN: (纸本)9783030669362

the proceedings contain 27 papers. the special focus in this conference is on Ergonomics. the topics include: New Proposals for Improvement of Train Driving Support systems Performances;3D Printing Technologies for Clothing Industry: A Review;Research of Working Postures in the Technological Sewing Process Using the REBA Method;analysis of Working Conditions and Modeling of Activity algorithms for Contact-Center Operators;Prometheus (PN-2003016) Digital Medical Device Collaborative E-Training and Cognitive Ergonomics to Integrate AI and Robotics in Organ Transplantations;Prometheus I (PN 1008239) Digital Medical Device Integrated with AI and Robotics Cognitive Ergonomics in Breast Cancer Prevention;portuguese Firefighters’ Anthropometrics: Pilot Study Results;Embedding Function Icons into QR Codes;suitability of School Furniture and Correlation with Pain Prevalence Among Slovenian 6th to 9th Graders;functional and Subjective Assessment of Spinal Exoskeletons: From Development of Battery of Tests to Experiments with Low Back Pain Patients;hammer Design Using Ergonomic Knowledge-Based Guidelines;functional Networks for Modeling and Optimization Human-Machine systems;burnout and Workload Among Health Care Workers in Bulgaria;the Advantages of Woven Wraps as Baby Carriers;the Moisture Management Properties of Laundered Hospital Textiles;research Methodology Used to Investigate the Effects of Noise on Overhead Crane Operator’s Performances;mobile App Authentication systems: Usability Issues for Cyrillic Alphabet Users (Pilot Study);proposal of an Ergonomic Interface for Supervision and Control of an Automated Shunting Device;skidder Operator Vibration Exposure;a Preliminary Study of the Possible Impact of Non-related Driving Tasks on the Car Driver’s Performance Using Glance-Based Measures.

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proceedings of the 7th international conference on Movement and computing, MOCO 2020

Proceedings of the 7th International Conference on Movement ...

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7th international conference on Movement and computing, MOCO 2020

ISBN: (纸本)9781450375054

the proceedings contain 40 papers. the topics discussed include: MotionHub: middleware for unification of multiple body tracking systems;sonification of heart rate variability can entrain bodies in motion;person identification based on sign language motion: insights from human perception and computational modeling;feasible stylized motion: robotic manipulator imitation of a human demonstration with collision avoidance and style parameters in increasingly cluttered environments;let's resonate! how to elicit improvisation and letting go in interactive digital art;designing glitch procedures and visualisation workflows for markerless live motion capture of contemporary dance;somatic sonification in dance performances. from the artistic to the perceptual and back;recognition of Laban effort qualities from hand motion;and portable interactive explorations of motion data for choreographers.

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