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检索条件"任意字段=2023 International Conference on Cognitive Computing and Complex Data, ICCD 2023"

共 718 条记录，以下是601-610 订阅

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Multivariate Statistical Analysis in Marketing Management

Multivariate Statistical Analysis in Marketing Management

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Advance computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： K. K. Ramachandran Karthick K K Rajesh Deorari Srinivas D Ali Hussein Malik Bader Alazzam Management/Commerce/International Business DR. G. R. D. College of Science India Department of Management Science Dr G R Damodaran College of Science Coimbatore Uttaranchal Institute of Technology Uttaranchal University School of Business SR University Warangal Telangana India Medical Technical College Al-Farahidi University Baghdad Iraq Information Technology College Ajloun National University Jordan

Marketing management is an essential function of any business, and it is critical to understand the various factors that influence consumer behavior. Multivariate statistical analysis is a powerful tool that can be used to analyze and understand the complex relationships between various marketing variables. This research paper explores the use of multivariate statistical analysis in marketing management, with a focus on the use of principal component analysis (PCA) and cluster analysis. The study is based on a dataset of consumer purchasing behavior and demographic data. The results of the study indicate that multivariate statistical analysis can provide valuable insights for businesses in terms of understanding consumer behavior and identifying key market segments.

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Empirical Assessment of the MAFIS Mobile App's Usability Based on the People at the Center of Mobile Application Development (PACMAD) Model

Empirical Assessment of the MAFIS Mobile App's Usability Bas...

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computing and Big data (ICCBD), international conference on

作者： William P. Rey Kieth Wilhelm Jan D. Rey School of Information Technology Mapua University Makati City Philippines

ISBN: (数字)9798350317008

ISBN: (纸本)9798350317015

The primary objective of this research was to evaluate the usability aspects of the MAFIS mobile app among Philippine National Police (PNP) personnel. The study assessed effectiveness, efficiency, learnability, memorability, error handling, and cognitive load. The research employed a surveybased methodology aligned with the PACMAD usability model. The findings indicated that the app consistently demonstrated high efficiency, surpassing expectations regarding task completion time, page duration, and interaction requirements. The evaluated effectiveness categories performed highly satisfactorily, signifying the app's successful achievement of its intended goals. Learnability was deemed high, as users perceived the app as easy to learn and quickly acquired the necessary skills. Moreover, the app exhibited a relatively high level of memorability, enabling users to reuse it without external assistance. The study also highlighted the app's strong error handling and recovery performance, providing effective support and informative error messages. Users experienced a manageable cognitive load, enabling them to complete tasks within allocated time frames. Overall, the research concluded that the current usability of the MAFIS mobile app was acceptable while recognizing the subjective nature of usability influenced by individual user factors. This research contributes to the existing literature on evaluating the usability of mobile applications in Philippine government institutions, offering valuable insights for developers and designers. Future studies could expand the sample to include other government agencies and explore novel methodologies for assessing usability.

关键词： Law enforcement Government cognitive load Mobile communication data models Mobile applications Personnel

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13th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2023

13th International Conference on High-Performance Computing ...

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13th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2023

ISBN: (纸本)9783031510564

The proceedings contain 21 papers. The special focus in this conference is on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production. The topics include: Adaptive Methods for the Structural Optimization of Neural Networks and Their Ensemble for data Analysis;self-adaptation Method for Evolutionary Algorithms Based on the Selection Operator;application of U-Net Architecture Neural Network for Segmentation of Brain Cell Images Stained with Trypan Blue;language Model Architecture Based on the Syntactic Graph of Analyzed Text;classic and Modern Methods of Automatic Parking Control of Self-driving Cars;application of Smoothing Technique to Model Predictive Traffic Signal Control;design Features of the Frequency-Controlled Electric Drive for Positioning Mechanisms;Development of a Mathematical Model to Study the Energy Indicators of Electric Drives Using the DFC-IM System;intelligent data Analysis for Materials Obtained Using Selective Laser Melting Technology;speech Enhancement Based on Two-Stage Neural Network with Structured State Space for Sequence Transformation;fourier Chromagrams for Fingerprinting, Verification and Authentication of Digital Audio Recordings;methodology of Expert-Agent cognitive Modeling for Preventing Impact on Critical Information Infrastructure;designing a Graphics Accelerator with Heterogeneous Architecture;spectrophotometer for Field Studies;comparative Study of Practical Implementation of Time Delay Estimation Methods on Single Board Computer;study of the Functional Characteristics of TiNi Coatings by the Computer-Aided Simulation Using Parallel computing;on Hierarchical Convergence of the Heterogeneous Multiscale Finite Element Method Using Polyhedral Supports;parallelization of Finite-Volume Numerical Methods of Computational Fluid Dynamics by Means of Shared Memory computing Systems.

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In-Vehicle Sensing and data Analysis for Older Drivers with Mild cognitive Impairment

In-Vehicle Sensing and Data Analysis for Older Drivers with ...

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international Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Sonia Moshfeghi Muhammad Tanveer Jan Joshua Conniff Seyedeh Gol Ara Ghoreishi Jinwoo Jang Borko Furht Kwangsoo Yang Monica Rosselli David Newman Ruth Tappen Dana Smith College of Engg and Computer Science Florida Atlantic University Boca Raton USA Charles E. Schmidt College of Science Florida Atlantic University Boca Raton USA Christine E. Lynn College of Nursing Florida Atlantic University Boca Raton USA

Driving is a complex daily activity indicating age-and disease-related cognitive declines. Therefore, deficits in driving performance compared with ones without mild cognitive impairment (MCI) can reflect changes in cognitive functioning. There is increasing evidence that unobtrusive monitoring of older adults' driving performance in a daily-life setting may allow us to detect subtle early changes in cognition. The objectives of this paper include designing low-cost in-vehicle sensing hardware capable of obtaining high-precision positioning and telematics data, identifying important indicators for early changes in cognition, and detecting early-warning signs of cognitive impairment in a truly normal, day-to-day driving condition with machine learning approaches. Our statistical analysis comparing drivers with (MCI) to those without reveals that those with (MCI) exhibit smoother and safer driving patterns. This suggests that drivers with (MCI) are cognizant of their condition and tend to avoid erratic driving behaviors. Furthermore, our Random Forest models identified the number of night trips, number of trips, and education as the most influential factors in our data evaluation.

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cognitive Ability Classification using On-body Sensors

Cognitive Ability Classification using On-body Sensors

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Adjunct Proceedings of the 2022 ACM international Joint conference on Pervasive and Ubiquitous computing and the 2022 ACM international Symposium on Wearable Computers

作者： Junaid Younas Paul Lukowicz Computer Science Technical University Kaiserslautern Germany and Embedded Intelligence DFKI Germany DFKI Germany and TU Kaiserslautern Germany

ISBN: (纸本)9781450394239

This work presents an on-body sensor setup to keep track of the learning progress while performing cognitive activities in formal education. The proposed approach uses the sensor collected data for cognitive ability classification, i.e., confidence score, cognitive load, and expertise, while attempting to solve physics-related problems. data is collected using a combination of instruction material, an eye-tracker, and a sensor pen to capture the cognition progress. The collected data is processed and transformed to feature representation using a novel feature-set presented in this paper for learning analytics. The used features help to highlight the difference in learner’s cognitive abilities and enable teachers to cater to individual needs and requirements, an essential aspect of need-based learning.

关键词： on-body sensors gaze detection learning analytics formal education need-based learning cognitive ability classification

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'Real Worlds Illusion!’ Consumer Response to Metaverse Technology Applying Flow Theory

'Real Worlds Illusion!’ Consumer Response to Metaverse Tech...

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international conference on computing Communication Control and Automation (ICCUBEA)

作者： Kanchan Pranay Patil Dhanya Pramod Symbiosis Centre for Information Technology Symbiosis International (Deemed University) Pune India

Metaverse technology will revolutionize the way the hospitality and tourism industry operate and is all set to co-create transformational experiences and value addition to customers. This study explores the impact of metaverse technology application characteristics and affective/cognitive consumer characteristics on the destination visit intentions of customers through the lens of flow theory. The data collected from 371 participants were tested on a conceptual model using SEM (structural equation modelling). The study reveals that metaverse technology application features, including interactivity, informativeness, and telepresence, impacted the metaverse flow experience, however, vividness was found to be insignificant. Also, Consumers' metaverse skills and challenge levels favourably impacted metaverse flow experience, but value-add search and perceived control were found to be insignificant. Metaverse flow experience significantly influenced tourist destination visit intentions. The study's unique contribution is the blend of constructs from consumer behaviour, flow, and environmental psychology in an integrated model of metaverse tourism consumer behaviour. The study concludes with theoretical and practical implications that can benefit tourist consumers, and metaverse tourism app designers, and marketing strategies in the tourism sector. The outcome of the study will help organizations to invest in metaverse tourism to convert prospective customers and improve revenue. Policymakers and government can refer to this study for devising a strategy to promote metaverse tourism to attract tourists

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Comparative Analysis of Functional and Effective Connectivity in Mental Disorders

Comparative Analysis of Functional and Effective Connectivit...

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IEEE/ICME international conference on complex Medical Engineering, CME

作者： Yanru Li University of Warwick Coventry United Kingdom

ISBN: (数字)9798350316117

ISBN: (纸本)9798350316124

This study investigates functional and effective connectivity differences in patients with schizophrenia and depression compared to healthy controls. Functional connectivity (FC) and effective connectivity (EC) were analyzed using fMRI data. FC, reflecting inter-regional correlations, was assessed through correlation analysis, while EC, indicating directional influence, was evaluated using Granger Causality Analysis (GCA). Results revealed significant FC and EC differences between patient groups and controls. FC analysis unveiled brain regions with altered correlations, while EC analysis identified directional information flow changes. Our findings contribute to understanding brain connectivity alterations in mental disorders. document.

关键词： Correlation Sensitivity cognitive processes Mental disorders Cause effect analysis Functional magnetic resonance imaging Depression

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Recognition of Masked Facial Expressions Based on Transfer Learning and data Augmentation

Recognition of Masked Facial Expressions Based on Transfer L...

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complex Systems and Intelligent Science (CSIS-IAC), international Annual conference on

作者： Yonggang Liu Ke Zhao Xiaolan Fu Department of Psychology State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

Facial expression recognition is currently one of the research hotspots in the field of artificial intelligence. In addition to normal natural expressions, people sometimes intentionally change their facial expressions to mask their real emotions. Masked expressions are more complex than ordinary expressions, and the number of masked expression datasets that can be used for model training is limited. The automatic recognition of masked expressions will be a new challenge. Traditional machine learning requires the manual design of feature extraction algorithms, resulting in low expression recognition rates. Deep learning requires a large amount of labeled data and has poor model performance on small sample datasets. This paper proposes a method based on transfer learning, which transfers the pre-trained weights to the model, reconstructs the classifier to complete new tasks, and combines data augmentation and regularization to improve the robustness and generalization ability of the model. It has achieved good results on the Masked Facial Expression database (MFED). Using leave-one-subject-out cross-validation, the recognition accuracy is 64.78% for required expressions (6R), 42.16% for experienced emotions evoked by video clips (6E), and 21.21% for 36 mixed expressions (6Ex6R), which is improved by 35.61%, 57.14%, and 88.52% compared to traditional methods, respectively. The experiment deepens the research on the recognition of masked expressions, providing a possible method for the recognition of deception and lies.

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Evaluating the Performance of Era5 Reanalysis datasets in Analysing Escs ‘Mocha’ Over the Bay of Bengal

Evaluating the Performance of Era5 Reanalysis Datasets in An...

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cognitive computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Arun Kumar Reena Nupur Sushil Kumar Nagendra Kumar Department of Mathematics M.M.H. College Ghaziabad India Symbiosis Centre for Management Studies (SCMS) Noida Symbiosis International (Deemed University) Pune India Department of Applied Mathematics Gautam Buddha University Greater Noida India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Extremely severe cyclonic storm (ESCS) 'Mocha' (2023), formed over the Bay of Bengal, has been analyzed using the ERA5 reanalysis datasets. The track, mean sea level pressure (MSLP) and maximum sustained wind (MSW) datasets were arranged from India meteorological department (IMD) observational datasets during the life cycle of ESCS 'Mocha'. The available IMD observations along Bay of Bengal (BoB), and the GPM rainfall observations are used to compare ERA5 reanalysis datasets. The parameters, viz. track, MSLP, MSW have been analyzed and compared with IMD observed datasets. It is seen that up to $\mathbf{1 6 8} \mathbf{- h}$ ERA5 reanalysis datasets of track and intensities have significantly improved during intense stages and the MSLP and MSW parameters analysis is reliable for up to 48 h. The ERA5 reanalysis datasets showed that the low value of MSLP in the range 961.1807-1004.849 $\mathbf{h P a}$ along the track of the TC, MSW range of 21.88056183-64.25743103 kt. Intense rainfall along vertical direction of the quadrant of the system favored the rapid intensification of ESCS 'Mocha'. The MSW variation during the intense and system's landfall is also captured, and ERA5 agree with the observed data before ESCS stage and around the time of landfall.

关键词： Rain Satellites Accuracy Tropical cyclones Computational modeling Biological system modeling Predictive models data models Sea level Reliability

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Benchmarking the Variational Quantum Eigensolver using different quantum hardware

Benchmarking the Variational Quantum Eigensolver using diffe...

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Quantum computing and Engineering (QCE), IEEE international conference on

作者： Amine Bentellis Andrea Matic-Flierl Christian B. Mendl Jeanette Miriam Lorenz Fraunhofer Institute for Cognitive Systems IKS Munich Germany Department of Computer Science CIT Technical University of Munich Garching Germany Technical University of Munich Institute for Advanced Study Garching Germany

The Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a quantum computer to simulate electronic structures with high accuracy would have a profound impact on material and biochemical science with potential applications e.g., to the development of new drugs. However, considering the variety of quantum hardware architectures, it is still uncertain which hardware concept is most suited to execute the VQE for e.g., the simulation of molecules. Aspects to consider here are the required connectivity of the quantum circuit used, the size and the depth and thus the susceptibility to noise effects. Besides theo-retical considerations, empirical studies using available quantum hardware may help to clarify the question of which hardware technology might be better suited for a certain given application and algorithm. Going one step into this direction, within this work, we present results using the VQE for the simulation of the hydrogen molecule, comparing superconducting and ion trap quantum computers. The experiments are carried out with a standardized setup of ansatz and optimizer, selected to reduce the number of required iterations. The findings are analyzed considering different quantum processor types, calibration data as well as the depth and gate counts of the circuits required for the different hardware concepts after transpilation.

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