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Gia Nhu Nguyen

Bio: Gia Nhu Nguyen is an academic researcher from Duy Tan University. The author has contributed to research in topics: Feature selection & Facial recognition system. The author has an hindex of 12, co-authored 40 publications receiving 517 citations.

Papers
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Journal ArticleDOI
TL;DR: A technique for image compression using a deep wavelet autoencoder (DWA), which blends the basic feature reduction property of autoen coder along with the image decomposition property of wavelet transform is proposed and it is noted that the proposed method outshines the existing methods.
Abstract: Technology and the rapid growth in the area of brain imaging technologies have forever made for a pivotal role in analyzing and focusing the new views of brain anatomy and functions. The mechanism of image processing has widespread usage in the area of medical science for improving the early detection and treatment phases. Deep neural networks (DNN), till date, have demonstrated wonderful performance in classification and segmentation task. Carrying this idea into consideration, in this paper, a technique for image compression using a deep wavelet autoencoder (DWA), which blends the basic feature reduction property of autoencoder along with the image decomposition property of wavelet transform is proposed. The combination of both has a tremendous effect on sinking the size of the feature set for enduring further classification task by using DNN. A brain image dataset was taken and the proposed DWA-DNN image classifier was considered. The performance criterion for the DWA-DNN classifier was compared with other existing classifiers such as autoencoder-DNN or DNN, and it was noted that the proposed method outshines the existing methods.

183 citations

Journal ArticleDOI
TL;DR: A secure intrusion, detection with blockchain based data transmission with classification model for CPS in healthcare sector, which achieves privacy and security and uses a multiple share creation (MSC) model for the generation of multiple shares of the captured image.

130 citations

Journal ArticleDOI
TL;DR: A new effective training scheme for the deep neural network (DNN), called ETS-DNN model in edge computing enabled IoMT system, is presented to facilitate timely data collection and processing to identify the patterns that exist in the data.
Abstract: At present times, the real-time requirement on the multiaccess healthcare monitoring system, information mining, and efficient disease diagnosis of health conditions is a difficult process. The recent advances in information technology and the internet of medical things (IoMT) have fostered extensive utilization of the smart system. A complex, 24/7 healthcare service is needed for effective and trustworthy monitoring of patients on a daily basis. To accomplish this need, edge computing and cloud platforms are highly required to satisfy the requirements of smart healthcare systems. This paper presents a new effective training scheme for the deep neural network (DNN), called ETS-DNN model in edge computing enabled IoMT system. The proposed ETS-DNN intends to facilitate timely data collection and processing to make timely decisions using the patterns that exist in the data. Initially, the IoMT devices sense the patient’s data and transfer the captured data to edge computing, which executes the ETS-DNN model to diagnose it. The proposed ETS-DNN model incorporates a Hybrid Modified Water Wave Optimization (HMWWO) technique to tune the parameters of the DNN structure, which comprises of several autoencoder layers cascaded to a softmax (SM) layer. The SM classification layer is placed at the end of the DNN to perform the classification task. The HMWWO algorithm integrates the MWWO technique with limited memory Broyden–Fletcher-Goldfarb-Shannon (L-BFGS). Once the ETS-DNN model generates the report in edge computing, then it will be sent to the cloud server, which is then forwarded to the healthcare professionals, hospital database, and concerned patients. The proposed ETS-DNN model intends to facilitate timely data collection and processing to identify the patterns exist in the data. An extensive set of experimental analysis takes place and the results are investigated under several aspects. The simulation outcome pointed out the superior characteristics of the ETS-DNN model over the compared methods.

106 citations

Journal ArticleDOI
TL;DR: The main medical image processes that can be developed using the neutrosophic sets, including de-noising, thresholding, segmentation, clustering and classification, were highlighted and the general algorithms that could be used to include NS in each task were proposed.
Abstract: In real world applications, soft computing is an inspirational domain for encoding imprecision and uncertainty. Soft computing procedures integrated with medical applications can support the existing medical systems to allow solutions for unsolvable problems. Fuzzy techniques have extensive solutions for the medical domain applications; however incorporating a new neutrosophic approaches in the medical domain proves its superiority. The current study reported the main neutrosophic sets (NS) definitions along with different medical applications based on NS. In addition, an extensive discussion for the possibility of prolonging the abilities of the fuzzy systems using the neutrosophic systems was included. The preceding studies established that the NS has a significant role in medical images de-noising, clustering, and segmentation. As a future scope, it was suggested that the neutrosophic medical systems can be exploited for neutrosophic scores; continuous truth/indeterminate/falsity versions of conventional score schemes. The integrated methods of the NS in medical domain would lead to tabular or rule-based mapping from input to output variables. The qualitative simulation of the reported studies established that the neutrosophic model based diagnosis is promising aspirants for future research. Furthermore, the current work highlighted the main medical image processes that can be developed using the NS, including de-noising, thresholding, segmentation, clustering and classification. The general algorithms that can be used to include NS in each task were proposed.

84 citations


Cited by
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01 Jan 2007
TL;DR: In this paper, the authors provide updates to IEEE 802.16's MIB for the MAC, PHY and asso-ciated management procedures in order to accommodate recent extensions to the standard.
Abstract: This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

1,481 citations

Book ChapterDOI
01 Jan 2014
TL;DR: This chapter is devoted to a more detailed examination of game theory, and two game theoretic scenarios were examined: Simultaneous-move and multi-stage games.
Abstract: This chapter is devoted to a more detailed examination of game theory. Game theory is an important tool for analyzing strategic behavior, is concerned with how individuals make decisions when they recognize that their actions affect, and are affected by, the actions of other individuals or groups. Strategic behavior recognizes that the decision-making process is frequently mutually interdependent. Game theory is the study of the strategic behavior involving the interaction of two or more individuals, teams, or firms, usually referred to as players. Two game theoretic scenarios were examined in this chapter: Simultaneous-move and multi-stage games. In simultaneous-move games the players effectively move at the same time. A normal-form game summarizes the players, possible strategies and payoffs from alternative strategies in a simultaneous-move game. Simultaneous-move games may be either noncooperative or cooperative. In contrast to noncooperative games, players of cooperative games engage in collusive behavior. A Nash equilibrium, which is a solution to a problem in game theory, occurs when the players’ payoffs cannot be improved by changing strategies. Simultaneous-move games may be either one-shot or repeated games. One-shot games are played only once. Repeated games are games that are played more than once. Infinitely-repeated games are played over and over again without end. Finitely-repeated games are played a limited number of times. Finitely-repeated games have certain or uncertain ends.

814 citations

Posted Content
TL;DR: In this paper, the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures.
Abstract: We consider heuristic algorithms for the resource-constrained project scheduling problem. Starting with a literature survey, we summarize the basic components of heuristic approaches. We briefly describe so-called X -pass methods which are based on priority rules as well as metaheuristic algorithms. Subsequently, we present the results of our in-depth computational study. Here, we evaluate the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures. Moreover, we analyze the behavior of the heuristics with respect to their components such as priority rules and metaheuristic strategy. Finally, we examine the impact of problem characteristics such as project size and resource scarceness on the performance.

438 citations

01 Jan 2016
TL;DR: The fundamentals of light microscopy and electronic imaging can be found in this article, where the authors describe how people have looked hundreds of times for their favorite books like this fundamentals, but end up in harmful downloads, and instead they juggled with some infectious bugs inside their laptop.
Abstract: Thank you very much for reading fundamentals of light microscopy and electronic imaging. Maybe you have knowledge that, people have look hundreds times for their favorite books like this fundamentals of light microscopy and electronic imaging, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some infectious bugs inside their laptop.

249 citations