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12 results on '"Nguyen, Duc-Hoai"'

1. Brand Authenticity and Social Identity Theory as Drivers of Purchase Intention Towards the Sustainable Development of Vietnamese Weasel Coffee with the Mediating Role of Vietnamese Law Context

Author

Vi, Tran Thi Tuong, Quang, Ho Nhut, Anh, Nguyen Duc Hoai, Nam, Vu Hai, Vi, Tran Thi Tuong, Quang, Ho Nhut, Anh, Nguyen Duc Hoai, and Nam, Vu Hai

Abstract

Objective: This article aims to test the effect of cues signaling authenticity on purchase intention and overall brand equity, mediated by the consumer preference for authentic fruits. It also presents Brand Authenticity and Social Identity Theory as drivers of Purchase Intention towards the sustainable development of Vietnamese Weasel coffee with the mediating role of Vietnamese law context. Method: Authors has used SPSS, AMOS and SEM method with reference on Planned Behavior concept/theory. Result: Our findings indicate that First, creating more products is better to affect intention to buy (consumers/consumer intention). Second, social identity /value affect people and consumer intention to buy. Third, three elements (Brand Authenticity, Brand Equity, Consumer Preference) affecting intention to buy fruits of consumers Conclusion: This study assists marketers in examining how Vietnamese customers perceive their authentic brands and their competitors, as well as what policymakers of these authentic fruit brands can do to increase customer purchase intention.&nbsp

Published
2023

2. Heterogeneous Centroid Neural Networks

Author

Park, Dong-Chul, Nguyen, Duc-Hoai, Lee, Song-Jae, Lee, Yunsik, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Jun, editor, Yi, Zhang, editor, Zurada, Jacek M., editor, Lu, Bao-Liang, editor, and Yin, Hujun, editor

Published
2006
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3. Classification of Audio Signals Using Gradient-Based Fuzzy c-Means Algorithm with Divergence Measure

Author

Park, Dong-Chul, Nguyen, Duc-Hoai, Beack, Seung-Hwa, Park, Sancho, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ho, Yo-Sung, editor, and Kim, Hyoung Joong, editor

Published
2005
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4. Equalization of a Wireless ATM Channel with Simplified Complex Bilinear Recurrent Neural Network

Author

Chul-Park, Dong, Nguyen, Duc-Hoai, Hong, Sang Jeen, Lee, Yunsik, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Lipo, editor, Chen, Ke, editor, and Ong, Yew Soon, editor

Published
2005
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5. Extending UTAUT2 in Mobile money adoption and actual use behavior: An empirical research in Vietnam during the Covid-19

Author

null Duc Dang Thi Viet, null Luan Nguyen Thanh, and null Anh Nguyen Duc Hoai

Abstract

The goal of this article is to examine the antecedents of behavioral intention toward mobile money, as well as the mediating role of trust on behavioral intention and financial inclusion in Vietnam during the COVID-19 period, using an expanded unified theory of technology acceptance and use (UTAUT2). The data were collected by an online self-administered questionnaire and analyzed using SmartPLS 3.3.3. To determine the exogenous constructs’ relevance and performance, a matrix analysis of importanceperformancewas used. The findings indicate that behavioral desire to use mobile money is primarily driven by awareness, structural assurance, habit, and performance expectation. The behavioral intention of mobile money will substantially influence its adoption, and trust will not act as a mediator between behavioral intention and financial inclusion. The extended UTAUT2 was used for the first time to analyze mobile money in Vietnam. Additionally, the new research provides a more comprehensive explanation for users’ financial inclusion than past research provided.

Published
2022

9. Model-based testing of multiple GUI variants using the GUI test generator.

Author

Nguyen, Duc Hoai, Strooper, Paul, and Suess, Jorn Guy

Abstract

Many modern application development frameworks separate presentation logic and business logic into layers. However, current model-based GUI testing tools do not model and test presentation logic and business logic separately. This paper proposes to separate business logic from the GUI behaviour model. The business logic is modelled using traditional modelbased testing tools like Spec Explorer while the presentation logic is recorded by a capture/replay tool. The two parts are connected via a mapping model. This paper proposes a new approach to test multiple GUI variants of an application in a reusable manner and introduces the GUI Test Generator (GTG). GTG is a tool which allows testers to define a mapping from business logic to presentation logic. Based on the mapping, GTG converts business logic test cases into presentation logic test cases. GTG is particularly useful for testing applications with a single business logic core and multiple variants of the user interface. This paper introduces the architecture of GTG and presents a case study for testing two different front-ends of an email client. [ABSTRACT FROM AUTHOR]

Published
2010
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10. Heterogeneous Centroid Neural Networks.

Author

Wang, Jun, Yi, Zhang, Zurada, Jacek M., Lu, Bao-Liang, Yin, Hujun, Park, Dong-Chul, Nguyen, Duc-Hoai, Lee, Song-Jae, and Lee, Yunsik

Abstract

The Tied Mixture Hidden Markov Model (TMHMM) is an important approach to reduce the number of free parameters in speech recognition. However, this model suffers from degradation in recognition accuracy due to its Gaussian Probability Density Function (GPDF) clustering error. This paper proposes a clustering algorithm called a Heterogeneous Centroid Neural Network (HCNN) for use in TMHMMs. The algorithm utilizes a Centroid Neural Network (CNN) to cluster acoustic feature vectors in the TMHMM. The HCNN uses a heterogeneous distance measure to allocate more code vectors in the heterogeneous areas where probability densities of different states overlap each other. When applied to an isolated Korean digit word recognition problem, the HCNN reduces the error rate by 9.39% over CNN clustering, and 14.63% over the traditional K-means clustering. Keywords: speech recognition, tied mixture, unsupervised clustering, Hidden Markov Model. [ABSTRACT FROM AUTHOR]

Published
2006
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11. Equalization of a Wireless ATM Channel with Simplified Complex Bilinear Recurrent Neural Network.

Author

Wang, Lipo, Chen, Ke, Ong, Yew, Chul-Park, Dong, Nguyen, Duc-Hoai, Hong, Sang Jeen, and Lee, Yunsik

Abstract

A new equalization method for a wireless ATM communication channel using a simplified version of the complex bilinear recurrent neural network (S-CBLRNN) is proposed in this paper. The S-BLRNN is then applied to the equalization of a wireless ATM channel for 8PSK and 16QAM. The results show that the proposed S-CBLRNN converges about 40 % faster than the CBLRNN and gives very favorable results in both of the MSE and SER criteria over the other equalizers. [ABSTRACT FROM AUTHOR]

Published
2005
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12. Classification of Audio Signals Using Gradient-Based Fuzzy c-Means Algorithm with Divergence Measure.

Author

Ho, Yo-Sung, Kim, Hyoung Joong, Park, Dong-Chul, Nguyen, Duc-Hoai, Beack, Seung-Hwa, and Park, Sancho

Abstract

Multimedia databases usually store thousands of audio files such as music, speech and other sounds. One of the challenges in modern multimedia system is to classify and retrieve certain kinds of audio from the database. This paper proposes a novel classification algorithm for a content-based audio retrieval. The algorithm, called Gradient-Based Fuzzy c-Means Algorithm with Divergence Measure (GBFCM(DM)), is a neural network-based algorithm which utilizes the Divergence Measure to exploit the statistical nature of the audio data to improve the classification accuracy. Experiment results confirm that the proposed algorithm outperforms 3.025%-5.05% in accuracy in comparison with conventional algorithms such as the k-Means or the Self-Organizing Map. [ABSTRACT FROM AUTHOR]

Published
2005
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