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Detecting user status from smartphone sensor data
Nguyen, Thu-Trang,Nguyen, Thi-Hau,Nguyen, Ha-Nam,Nguyen, Duc-Nhan,Choi, GyooSeok The International Promotion Agency of Culture Tech 2016 International Journal of Advanced Culture Technolo Vol.4 No.1
Due to the high increment in usage and built-in advanced technology of smartphones, human activity recognition relying on smartphone sensor data has become a focused research area. In order to reduce noise of collected data, most of previous studies assume that smartphones are fixed at certain positions. This strategy is impractical for real life applications. To overcome this issue, we here investigate a framework that allows detecting the status of a traveller as idle or moving regardless the position and the direction of smartphones. The application of our work is to estimate the total energy consumption of a traveller during a trip. A number of experiments have been carried out to show the effectiveness of our framework when travellers are not only walking but also using primitive vehicles like motorbikes.
Daily wrist activity classification using a smart band
Nguyen, Nhan Duc,Truong, Phuc Huu,Jeong, Gu-Min IOP PUBLISHING 2017 PHYSIOLOGICAL MEASUREMENT Vol. No.
<P> <I>Objective:</I> In this letter, we propose a novel method for classifying daily wrist activities by using a smart band. <I>Approach:</I> Triaxial acceleration data are collected by built-in sensors of the smart band during experiments regarding five activities, i.e. texting, calling, placing a hand in a pocket, carrying a suitcase, and swinging a hand. We analyze patterns in the sensor signals during these activities based on three types of features, i.e. norm, norm-variance, and frequency-domain features. After extracting the significant features, a multi-class support vector machine algorithm is applied to classify these activities. <I>Main results:</I> We obtained recognition error rates of approximately 2.7% by applying the proposed method to the experimental dataset.</P>
Position-Based Feature Selection for Body Sensors regarding Daily Living Activity Recognition
Nguyen, Nhan Duc,Bui, Duong Trong,Truong, Phuc Huu,Jeong, Gu-Min Hindawi Limited 2018 Journal of sensors Vol.2018 No.-
<P>This paper proposes a novel approach to recognize activities based on sensor-placement feature selection. The method is designed to address a problem of multisensor fusion information of wearable sensors which are located in different positions of a human body. Precisely, the approach can extract the best feature set that characterizes each activity regarding a body-sensor location to recognize daily living activities. We firstly preprocess the raw data by utilizing a low-pass filter. After extracting various features, feature selection algorithms are applied separately on feature sets of each sensor to obtain the best feature set for each body position. Then, we investigate the correlation of the features in each set to optimize the feature set. Finally, a classifier is applied to an optimized feature set, which contains features from four body positions to classify thirteen activities. In experimental results, we obtain an overall accuracy of 99.13% by applying the proposed method to the benchmark dataset. The results show that we can reduce the computation time for the feature selection step and achieve a high accuracy rate by performing feature selection for the placement of each sensor. In addition, our proposed method can be used for a multiple-sensor configuration to classify activities of daily living. The method is also expected to deploy to an activity classification system-based big data platform since each sensor node only sends essential information characterizing itself to a cloud server.</P>
Classification of Five Ambulatory Activities Regarding Stair and Incline Walking Using Smart Shoes
Nguyen, Nhan Duc,Bui, Duong Trong,Truong, Phuc Huu,Jeong, Gu-Min IEEE 2018 IEEE SENSORS JOURNAL Vol.18 No.13
<P>In this paper, we propose a novel method to classify five ambulatory activities, i.e., level ground, incline descent, incline ascent, stair descent, and stair ascent walking using smart shoes which contain eight plantar-pressure sensors on each shoe. Pressure data are collected using an insole-based monitoring system regarding the walking activities conducted by participants at their self-imposed “normal” speed. We present three new features based on an analysis of step patterns to characterize the ambulatory activities and utilize a k-nearest neighbor algorithm to classify the activities from the created features. In experimental results, we obtain walking activity-recognition error rates of 2.16% at the sixth walking step. Furthermore, a proposed method outperforms two reference methods in terms of F1-score and overall accuracy rate.</P>
A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization
Thi-Hau Nguyen,Ha-Nam Nguyen,Dang-Nhac Lu,Duc-Nhan Nguyen International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.8
The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm which is well-known in Traveling Salesman Problem. This paper proposed a hybrid method based on genetic algorithm (GA) and ant colony system (ACS), called GACS, to solve traffic routing problem. In the GACS, we use genetic algorithm to optimize the ACS parameters that aims to attain the shortest trips and time through new functions to help the ants to update global and local pheromones. Our experiments are performed by the GACS framework which is developed from VANETsim with the ability of real map loading from open street map project, and updating traffic light in real-time. The obtained results show that our framework acquired higher performance than A-Star and classical ACS algorithms in terms of length of the best global tour and the time for trip.
Detecting user status from smartphone sensor data
Thu-Trang Nguyen,Thi-Hau Nguyen,Ha-Nam Nguyen,Duc-Nhan Nguyen,GyooSeok Choi 국제문화기술진흥원 2016 International Journal of Advanced Culture Technolo Vol.4 No.1
Due to the high increment in usage and built-in advanced technology of smartphones, human activity recognition relying on smartphone sensor data has become a focused research area. In order to reduce noise of collected data, most of previous studies assume that smartphones are fixed at certain positions. This strategy is impractical for real life applications. To overcome this issue, we here investigate a framework that allows detecting the status of a traveller as idle or moving regardless the position and the direction of smartphones. The application of our work is to estimate the total energy consumption of a traveller during a trip. A number of experiments have been carried out to show the effectiveness of our framework when travellers are not only walking but also using primitive vehicles like motorbikes.
The Impact of Human Resource Management Activities on the Compatibility and Work Results
NGUYEN, Duc Trung,HA, Van Dung,DANG, Truong Thanh Nhan Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.9
This research focuses on determining the impact of human resource management activities on the compatibility and work results of employees of Ho Chi Minh Stock Exchange (HOSE) listed companies. The paper includes five parts: introduction, literature review, research methodology, research results, and conclusion and policy implications. The data are collected from the survey of 350 listed companies in HOSE, in which 315 survey notes filled with sufficient information are used for analysis. The paper employs both qualitative method and quantitative method. Group discussion of 10 experts is for qualitative research. Quantitative method performs analysis of Statistics, Cronbach's Alpha, EFA analysis, CFA analysis and SEM model. The results of the research clearly indicate that human resource management (HRM) activities are measured through improving the ability, improving the motivation and improving the opportunity. While compatibility is measured through suitability, connection and sacrifice; whereby HRM activities of ability improvement have a positive effect on the job suitability and connection; HRM activities of motivation improvement have a positive effect on the job suitability, connection and sacrifice; and HRM activities of opportunity improvement have a positive effect on the job suitability, sacrifice and connection; Finally, the job suitability, sacrifice and connection positively affect the work results of employees.
Hoang, Van Thanh,Luu, Duc Binh,Toan Do, Le Hung,Tran, Ngoc Hai,Nguyen, Pham The Nhan,Tran, Minh Sang,Tran, Minh Thong Materials Research Society of Korea 2020 한국재료학회지 Vol.30 No.12
A combination of Polycarbonate (PC) material and Polymethylmethacrylate (PMMA), fabricated using an injection molding machine, has been investigated to determine its advantages, as studied in Ref. 1). This paper aims to investigate the optimization of PMMA/PC blend for both tensile yield strength and impact strength. Furthermore, interaction effects of process conditions on mechanical properties including tensile yield strength and impact strength of PMMA/PC blend by injection molding process are interpreted in this study. Tensile and impact specimens are designed following ASTM, type V, and are fabricated by injection molding process. The processing conditions such as melt temperature, mold temperature, packing pressure, and cooling time are applied; each factor has three levels. As a result, in comparison with optimization of separated responses, mechanical properties of PMMA/PC are found to decrease when optimizing both tensile and impact strengths simultaneously. The melt temperature is found to be the most significant interaction parameter with the mold temperature and packing pressure. In addition, there is more interaction between the mold temperature and cooling time. This investigation provides a useful understanding of the control of injection molding processing of polymer blends in optical application.