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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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Applying ant colony optimization algorithm to solve flying probe inspection problem

Applying ant colony optimization algorithm to solve flying p...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Chen, Chih-Yung Chang, Yu-Ming National Pingtung University of Science and Technology Program in Artificial Intelligence and Mechatronics Pingtung Taiwan Shu-Te University Department of Computer Science and Information Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350324174

This paper applies ant colony optimization (ACO) algorithm for the dual-pin flying probe circuit board inspection optimal path searching problem. First, the proposed approach creates a representation for circuit inspection path, which groups and encodes the measurement endpoints into a sequence. Moreover, the ant colony algorithm with the sequence can be used to solve the complex circuit optimal problem. The experimental results show that the best solutions of ACO are performed better than other algorithms. © 2023 IEEE.

关键词： Inspection

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Retinal Blood Vessel Tracking and Diameter Estimation via Gaussian Process With Rider Optimization Algorithm

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IEEE Journal of Biomedical and Health Informatics 2024年第3期28卷 1173-1184页

作者： Ahmad, Nehal Lai, Kuan-Ting Tanveer, M. Indian Institute of Technology Indore Simrol Department of Mathematics Indore453552 India National Taipei University of Technology Department of International Program of Electrical Engineering and Computer Science Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan

Retinal blood vessels structure analysis is an important step in the detection of ocular diseases such as diabetic retinopathy and retinopathy of prematurity. Accurate tracking and estimation of retinal blood vessels in terms of their diameter remains a major challenge in retinal structure analysis. In this research, we develop a rider-based Gaussian approach for accurate tracking and diameter estimation of retinal blood vessels. The diameter and curvature of the blood vessel are assumed as the Gaussian processes. The features are determined for training the Gaussian process using Radon transform. The kernel hyperparameter of Gaussian processes is optimized using Rider Optimization Algorithm for evaluating the direction of the vessel. Multiple Gaussian processes are used for detecting the bifurcations and the difference in the prediction direction is quantified. The performance of the proposed Rider-based Gaussian process is evaluated with mean and standard deviation. Our method achieved high performance with the standard deviation of 0.2499 and mean average of 0.0147, which outperformed the state-of-the-art method by 6.32%. Although the proposed model outperformed the state-of-the-art method in normal blood vessels, in future research, one can include tortuous blood vessels of different retinopathy patients, which would be more challenging due to large angle variations. We used Rider-based Gaussian process for tracking blood vessels to obtain the diameter of retinal blood vessels, and the method performed well on the 'STrutred Analysis of the REtina (STARE) Database' accessed on Oct. 2020 (https://***/~ahoover/stare/). To the best of our knowledge, this experiment is one of the most recent analysis using this type of algorithm. © 2013 IEEE.

关键词： Blood vessels

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DeAFusion: Detail-Aware Image Fusion for Whitematter Hyperintensity Segmentation

DeAFusion: Detail-Aware Image Fusion for Whitematter Hyperin...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jo, Gyeongdeok Kim, Jonghun Park, Bo-Yong Park, Hyunjin Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Institute for Basic Science Center for Neuroscience Imaging Research Suwon Korea Republic of Korea University Department of Brain and Cognitive Engineering Seoul Korea Republic of

ISBN: (纸本)9798350386226

White matter hyperintensities (WMHs) are critical indicators of cerebral small vessel disease and are linked to stroke and cognitive decline. Accurate WHM segmentation is challenging due to limited contrast and small size, particularly for deep WMHs where T1-weighted and FLAIR MRI are routinely used. Image fusion offers a method to combine two modalities into one fused modality useful for WHM segmentation. We propose DeAFusion: Detail-Aware Image Fusion, a novel image fusion framework. This framework introduces a Pixel-wise Information Preservation Degree map to enable detailed control of fusion at the pixel level and incorporates segmentation loss to embed semantic information. Our model outperforms existing fusion methods in enhancing lesion visibility and preserving structural details, as demonstrated on both public and in-house datasets. DeAFusion shows promise for improving clinical assessments of WMHs. Our code is available at https://***/Gyeongdeok-Jo/DeAFusion. © 2024 IEEE.

关键词： Image fusion

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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What does functional connectivity tell us about the behaviorally-functional connectivity of a multifunctional neural circuit?

What does functional connectivity tell us about the behavior...

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2022 Conference on Artificial Life, ALIFE 2022

作者： Izquierdo, Eduardo J. Candadai, Madhavun Cognitive Science Program Indiana University Luddy School of Informatics Computing and Engineering Indiana University United States

What insights can statistical analysis of the time series recordings of neurons and brain regions during behavior give about the neural basis of behavior? With the increasing amount of whole-brain imaging data becoming available, the importance of addressing this unanswered theoretical challenge has become increasingly urgent. We propose a computational neuroethology approach to begin to address this challenge. We evolve dynamical recurrent neural networks to be capable of performing multiple tasks. We then analyze the neural activity using popular network neuroscience tools, specifically functional connectivity using Pearson’s correlation, mutual information, and transfer entropy. We compare the results from these tools against a series of informational lesions, as a way to reveal their degree of approximation to the ground-truth. Our initial analysis reveals an overwhelming large gap between the insights gained from statistical inference of the functionality of the circuits based on neural activity and the actual functionality of the circuits as revealed by mechanistic interventions. © Artificial Life Conference Proceedings 2022.

关键词： Recurrent neural networks

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Stress detection system for social media users 7

Stress detection system for social media users

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Febriansyah, Mochamad Rizky Nicholas Yunanda, Rezki Suhartono, Derwin Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Software Engineering Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Stress detection is a growing topic in the field of natural language processing. The study of stress detection for mental health prediction has been proven to benefit the development of recommender systems and automated mental health assessments in previous studies. Additionally, the widespread usage of social media has served as a potential data source for developing such models. Our research tried to detect whether the users of social media were under stress or not. We used a dataset from Dreaddit consisting of posts from one of the popular social media platforms, Reddit. We propose a machine learning model consisting of Support Vector Machine (SVM), Naïve Bayes, Decision Tree, Random Forest, Bag of Words, and Term Frequency - inverse document frequency (TF-IDF) for stress detection. The final evaluation of the model achieved an 80.00% F-1 Score and 75.00% accuracy, and both were scored by SVM. © 2022 Elsevier B.V.. All rights reserved.

关键词： Support vector machines

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An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network 7

An Improved Particle Swarm Approach for Energy-Aware Locatio...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Kumar, Sandeep Sharma, Khemraj Ashok Kumar, P.M. Jain, Arpit Bhagat, Sukesh Kumar Singh, Pranita Tula's institute U.K Dehradun India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science Engineering AP Vaddeswaram522502 India Uttaranchal University Department of Computer Science & Engineering Uttarakhand Dehradun India Roorkee Institute of Technology Department of Computer Science and Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350350067

A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MANETs, routing procedures enhance the overall appearance of the network by ensuring Quality of Service (QoS). A routing protocol may use a composite routing measure to determine the best path for transferring data. Optimal location-based routing for MANETs based on energy-awareness is presented in this paper. Optimal routes are selected using this fast algorithm. Particle swarm optimization (PSO) is used instead of location-aided routing to select the normal data transmission route. Last but not least, the network is tested by simulating its packet delivery ratio, its energy level, its delay, and its overhead. © 2024 IEEE.

关键词： Adversarial machine learning

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A Multi-trace Surface Integral Equation Solver to Analyze Electromagnetic Field Interactions on Graphene-based Devices

A Multi-trace Surface Integral Equation Solver to Analyze El...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2022

作者： Zhao, Ran Chen, Liang Hu, Jun Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955 Saudi Arabia School of Electronic Science and Engineering Chengdu610056 China

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A multi-trace surface integral equation (MT-SIE) solver is proposed to analyze electromagnetic field interactions on graphene-based devices. This solver decomposes the computation domain into an exterior subdomain (the background medium where the device resides in) and an interior subdomain that represents the device's dielectric substrate. The infinitesimally thin graphene sheet partially covers the interface between these two subdomains. On the graphene surface and the rest of this interface, resistive Robin transmission conditions (formulated for the first time in this work) and the traditional Robin transmission conditions are used to "connect"these two subdomains, respectively. In each subdomain, the electric and magnetic field equations are used as the governing equations. Various numerical examples are presented to demonstrate the accuracy and the applicability of the proposed MT-SIE solver. © 2022 IEEE.

关键词： Graphene

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Migratable AI Systems for Tailoring User Experience through Multimodal Affective-cognitive State Analysis

Migratable AI Systems for Tailoring User Experience through ...

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2023 International Conference of the Italian Association for Artificial Intelligence Doctoral Consortium, AIxIA-DC 2023

作者： La Monica, Ludovica Institute of Cognitive Science and Technology National Research Council Rome00185 Italy Unit of Computer Systems and Bioinformatics Department of Engineering Università Campus Bio-Medico di Roma Rome00128 Italy

In the era of digital technologies permeating numerous aspects of society, the development of intelligent artificial agents endowed with autonomy, social capabilities, reactivity, and proactivity has become a pivotal innovation. Traditionally, these agents were confined to singular forms, known as embodiments, which dictated their capabilities and the environments in which they operated. To transcend these limitations and enable agents to expand their capabilities, the concept of agent migration has emerged, allowing them to seamlessly transition between different embodiments. My research program delves into the realm of agent migration, uncovering its challenges and potential opportunities. The central objective is to leverage this technology to deepen our understanding of human affective and cognitive states across various contexts. Specifically, my aim is to develop a migratory agent architecture capable of recognizing and characterizing individuals’ emotional experiences using different sets of capabilities tied to distinct embodiments. In summary, the intent of this research is to harness migratable AI to promote the technical advantages brought about by agent migration and gain insights into how to utilize the acquisition of additional capabilities resulting from migration to craft a more comprehensive and potentially enduring architecture, to be applied in the realm of affective computing. © 2022 Copyright for this paper by its authors.

关键词： Autonomous agents

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