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1. Gaussian lower bounds for the density via Malliavin calculus

Author

Nguyen, Tien Dung

Subjects
Mathematics, QA1-939
Abstract

In this paper, based on a known formula, we use a simple idea to get a new representation for the density of Malliavin differentiable random variables. This new representation is particularly useful for finding lower bounds for the density.

Published
2020
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5. On Taking Advantage of Opportunistic Meta-knowledge to Reduce Configuration Spaces for Automated Machine Learning

Author

Kedziora, David Jacob, Nguyen, Tien-Dung, Musial, Katarzyna, and Gabrys, Bogdan

Subjects
Computer Science - Machine Learning
Abstract

The automated machine learning (AutoML) process can require searching through complex configuration spaces of not only machine learning (ML) components and their hyperparameters but also ways of composing them together, i.e. forming ML pipelines. Optimisation efficiency and the model accuracy attainable for a fixed time budget suffer if this pipeline configuration space is excessively large. A key research question is whether it is both possible and practical to preemptively avoid costly evaluations of poorly performing ML pipelines by leveraging their historical performance for various ML tasks, i.e. meta-knowledge. The previous experience comes in the form of classifier/regressor accuracy rankings derived from either (1) a substantial but non-exhaustive number of pipeline evaluations made during historical AutoML runs, i.e. 'opportunistic' meta-knowledge, or (2) comprehensive cross-validated evaluations of classifiers/regressors with default hyperparameters, i.e. 'systematic' meta-knowledge. Numerous experiments with the AutoWeka4MCPS package suggest that (1) opportunistic/systematic meta-knowledge can improve ML outcomes, typically in line with how relevant that meta-knowledge is, and (2) configuration-space culling is optimal when it is neither too conservative nor too radical. However, the utility and impact of meta-knowledge depend critically on numerous facets of its generation and exploitation, warranting extensive analysis; these are often overlooked/underappreciated within AutoML and meta-learning literature. In particular, we observe strong sensitivity to the `challenge' of a dataset, i.e. whether specificity in choosing a predictor leads to significantly better performance. Ultimately, identifying `difficult' datasets, thus defined, is crucial to both generating informative meta-knowledge bases and understanding optimal search-space reduction strategies., Comment: 71 pages

Published
2022

8. Applications of Big-Diameter Jet Grouting (BDJ) Method in Japan and Vietnam

Author

Nguyen, Tien Dung, Oyama, Hitoshi, Nguyen, Bao Hoang, Do, Ngoc Phong, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Duc Long, Phung, editor, and Dung, Nguyen Tien, editor

Published
2024
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9. On Preparation and Assembly of TBMs for Metro Line No. 3 Project in Hanoi

Author

Luu, Hoang Phuong, Trinh, Quoc Tuan, Nguyen, Van Quang, Nguyen, Tien Dung, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Duc Long, Phung, editor, and Dung, Nguyen Tien, editor

Published
2024
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10. Geotechnical Design of Onshore Wind Turbine Foundations: Some Applications and Lessons Learned in Vietnam

Author

Ho, Duc-An, Nguyen, Trung-Kien, Nguyen, Tien Dung, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Duc Long, Phung, editor, and Dung, Nguyen Tien, editor

Published
2024
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11. Modulus Number and Reference Tangent Modulus of Clays in the Red River Delta

Author

Nguyen, Tien Dung, Nguyen, Cong Kien, Chung, Sung Gyo, Fellenius, Bengt H., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Duc Long, Phung, editor, and Dung, Nguyen Tien, editor

Published
2024
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12. Rockfall Mitigation for Highway in Vietnam: A Case Study on the Hoang Sa Road, Da Nang City

Author

Naing, Cho Thu Thu, Nguyen, Lan Chau, Nguyen, Tien Dung, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Nguyen-Xuan, Tung, editor, Nguyen-Viet, Thanh, editor, Bui-Tien, Thanh, editor, Nguyen-Quang, Tuan, editor, and De Roeck, Guido, editor

Published
2024
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13. Remedy Solutions for a Deep-Seated Landslide on Road No. 155, Section Km 12 + 667.85–Km 12 + 711.57, Sapa Town, Lao Cai Province, Vietnam

Author

Aung, Thu Zar, Nguyen, Lan Chau, Nguyen, Tien Dung, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Nguyen-Xuan, Tung, editor, Nguyen-Viet, Thanh, editor, Bui-Tien, Thanh, editor, Nguyen-Quang, Tuan, editor, and De Roeck, Guido, editor

Published
2024
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17. An Efficient Video Streaming Architecture with QoS Control for Virtual Desktop Infrastructure in Cloud Computing

Author

Nguyen, Huu-Quoc, Nguyen, Tien-Dung, Pham, Van-Nam, Pham, Xuan-Qui, Ngo, Quang-Thai, and Huh, Eui-Nam

Subjects
Computer Science - Machine Learning
Abstract

In virtual desktop infrastructure (VDI) environments, the remote display protocol has a big responsibility to transmit video data from a data center-hosted desktop to the endpoint. The protocol must ensure a high level of client perceived end-to-end quality of service (QoS) under heavy work load conditions. Each remote display protocol works differently depending on the network and which applications are being delivered. In healthcare applications, doctors and nurses can use mobile devices directly to monitor patients. Moreover, the ability to implement tasks requiring high consumption of CPU and other resources is applicable to a variety of applications including research and cloud gaming. Such computer games and complex processes will run on powerful cloud servers and the screen contents will be transmitted to the client. TO enable such applications, remote display technology requires further enhancements to meet more stringent requirements on bandwidth and QoS, an to allow realtime operation. In this paper, we present an architecture including flexible QoS control to improve the user quality of experience (QoE). The QoS control is developed based on linear regression modeling using historical network data. Additionally, the architecture includes a novel compression algorithm of 2D images, designed to guarantee the best image quality and to reduce video delay; this algorithm is based on k-means clustering and can satisfy the requirements of realtime onboard processing. Through simulations with a real work dataset collected by the MIT Computer Science and Artificial Lab, we present experimental as well as explain the performance of the QoS system., Comment: 26 pages, Multimedia Tools and Applications Journal

Published
2022

20. Exploring Opportunistic Meta-knowledge to Reduce Search Spaces for Automated Machine Learning

Author

Nguyen, Tien-Dung, Kedziora, David Jacob, Musial, Katarzyna, and Gabrys, Bogdan

Subjects
Computer Science - Machine Learning
Abstract

Machine learning (ML) pipeline composition and optimisation have been studied to seek multi-stage ML models, i.e. preprocessor-inclusive, that are both valid and well-performing. These processes typically require the design and traversal of complex configuration spaces consisting of not just individual ML components and their hyperparameters, but also higher-level pipeline structures that link these components together. Optimisation efficiency and resulting ML-model accuracy both suffer if this pipeline search space is unwieldy and excessively large; it becomes an appealing notion to avoid costly evaluations of poorly performing ML components ahead of time. Accordingly, this paper investigates whether, based on previous experience, a pool of available classifiers/regressors can be preemptively culled ahead of initiating a pipeline composition/optimisation process for a new ML problem, i.e. dataset. The previous experience comes in the form of classifier/regressor accuracy rankings derived, with loose assumptions, from a substantial but non-exhaustive number of pipeline evaluations; this meta-knowledge is considered 'opportunistic'. Numerous experiments with the AutoWeka4MCPS package, including ones leveraging similarities between datasets via the relative landmarking method, show that, despite its seeming unreliability, opportunistic meta-knowledge can improve ML outcomes. However, results also indicate that the culling of classifiers/regressors should not be too severe either. In effect, it is better to search through a 'top tier' of recommended predictors than to pin hopes onto one previously supreme performer.

Published
2021

22. Incremental Search Space Construction for Machine Learning Pipeline Synthesis

Author

Zöller, Marc-André, Nguyen, Tien-Dung, and Huber, Marco F.

Subjects
Computer Science - Machine Learning
Abstract

Automated machine learning (AutoML) aims for constructing machine learning (ML) pipelines automatically. Many studies have investigated efficient methods for algorithm selection and hyperparameter optimization. However, methods for ML pipeline synthesis and optimization considering the impact of complex pipeline structures containing multiple preprocessing and classification algorithms have not been studied thoroughly. In this paper, we propose a data-centric approach based on meta-features for pipeline construction and hyperparameter optimization inspired by human behavior. By expanding the pipeline search space incrementally in combination with meta-features of intermediate data sets, we are able to prune the pipeline structure search space efficiently. Consequently, flexible and data set specific ML pipelines can be constructed. We prove the effectiveness and competitiveness of our approach on 28 data sets used in well-established AutoML benchmarks in comparison with state-of-the-art AutoML frameworks., Comment: Conference paper accepted at Symposium on Intelligent Data Analysis (IDA) 2021

Published
2021

25. AutoWeka4MCPS-AVATAR: Accelerating Automated Machine Learning Pipeline Composition and Optimisation

Author

Nguyen, Tien-Dung, Gabrys, Bogdan, and Musial, Katarzyna

Subjects
Computer Science - Machine Learning, Statistics - Computation
Abstract

Automated machine learning pipeline (ML) composition and optimisation aim at automating the process of finding the most promising ML pipelines within allocated resources (i.e., time, CPU and memory). Existing methods, such as Bayesian-based and genetic-based optimisation, which are implemented in Auto-Weka, Auto-sklearn and TPOT, evaluate pipelines by executing them. Therefore, the pipeline composition and optimisation of these methods frequently require a tremendous amount of time that prevents them from exploring complex pipelines to find better predictive models. To further explore this research challenge, we have conducted experiments showing that many of the generated pipelines are invalid in the first place, and attempting to execute them is a waste of time and resources. To address this issue, we propose a novel method to evaluate the validity of ML pipelines, without their execution, using a surrogate model (AVATAR). The AVATAR generates a knowledge base by automatically learning the capabilities and effects of ML algorithms on datasets' characteristics. This knowledge base is used for a simplified mapping from an original ML pipeline to a surrogate model which is a Petri net based pipeline. Instead of executing the original ML pipeline to evaluate its validity, the AVATAR evaluates its surrogate model constructed by capabilities and effects of the ML pipeline components and input/output simplified mappings. Evaluating this surrogate model is less resource-intensive than the execution of the original pipeline. As a result, the AVATAR enables the pipeline composition and optimisation methods to evaluate more pipelines by quickly rejecting invalid pipelines. We integrate the AVATAR into the sequential model-based algorithm configuration (SMAC). Our experiments show that when SMAC employs AVATAR, it finds better solutions than on its own., Comment: arXiv admin note: substantial text overlap with arXiv:2001.11158

Published
2020

26. Improving The Performance Of The K-means Algorithm

Author

Nguyen, Tien-Dung

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The Incremental K-means (IKM), an improved version of K-means (KM), was introduced to improve the clustering quality of KM significantly. However, the speed of IKM is slower than KM. My thesis proposes two algorithms to speed up IKM while remaining the quality of its clustering result approximately. The first algorithm, called Divisive K-means, improves the speed of IKM by speeding up its splitting process of clusters. Testing with UCI Machine Learning data sets, the new algorithm achieves the empirically global optimum as IKM and has lower complexity, $O(k*log_{2}k*n)$, than IKM, $O(k^{2}n)$. The second algorithm, called Parallel Two-Phase K-means (Par2PK-means), parallelizes IKM by employing the model of Two-Phase K-means. Testing with large data sets, this algorithm attains a good speedup ratio, closing to the linearly speed-up ratio., Comment: The graduation thesis submitted to the School of Computer Science and Engineering, International University - Vietnam National University HCMC in partial fulfillment of the requirements for the degree of Master of Information Technology Management

Published
2020

27. The Impact of App Experience, Livestream and Personal Coach on Customer Satisfaction: A Case Study from an English Centre

Author

Nguyen Tien, Dung, Do Ha, Anh, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Pham, Tra Lam, editor, and Pham, Quang Huy, editor

Published
2023
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28. AVATAR -- Machine Learning Pipeline Evaluation Using Surrogate Model

Author

Nguyen, Tien-Dung, Maszczyk, Tomasz, Musial, Katarzyna, Zöller, Marc-Andre, and Gabrys, Bogdan

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The evaluation of machine learning (ML) pipelines is essential during automatic ML pipeline composition and optimisation. The previous methods such as Bayesian-based and genetic-based optimisation, which are implemented in Auto-Weka, Auto-sklearn and TPOT, evaluate pipelines by executing them. Therefore, the pipeline composition and optimisation of these methods requires a tremendous amount of time that prevents them from exploring complex pipelines to find better predictive models. To further explore this research challenge, we have conducted experiments showing that many of the generated pipelines are invalid, and it is unnecessary to execute them to find out whether they are good pipelines. To address this issue, we propose a novel method to evaluate the validity of ML pipelines using a surrogate model (AVATAR). The AVATAR enables to accelerate automatic ML pipeline composition and optimisation by quickly ignoring invalid pipelines. Our experiments show that the AVATAR is more efficient in evaluating complex pipelines in comparison with the traditional evaluation approaches requiring their execution., Comment: The Eighteenth International Symposium on Intelligent Data Analysis, IDA 2020

Published
2020

31. The third Intensive Care Bundle with Blood Pressure Reduction in Acute Cerebral Haemorrhage Trial (INTERACT3): an international, stepped wedge cluster randomised controlled trial

Author

Robinson, Thompson, Miranda, J. Jaime, Anderson, Craig S., You, Chao, Song, Lili, Parry-Jones, Adrian, Sprigg, Nikola, Durrans, Sophie, Harris, Caroline, Bamford, Ann, Smith, Olivia, Herbert, Robert, Chen, Christopher, Whiteley, William, Hu, Rong, Billot, Laurent, Li, Qiang, Mysore, Jayanthi, Hu, Xin, Zhang, Yao, Liu, Feifeng, Sakamoto, Yuki, You, Shoujiang, Han, Qiao, Crutzen, Bernard, Li, Yunke, Cheung, Emily, Jan, Stephen, Liu, Hueiming, Ouyang, Menglu, Sun, Lingli, Chu, Honglin, Anjum, Anila, Gonzalez Mc Cawley, Francisca, Del Rio, Alejandra, Rimoli, Bruna, Cerantola, Rodrigo, Jeevarajah, Thanushanthan, Kannangara, Madhushani, Joseph, Andrene, Nanayakkara, Chamath, Chen, Xiaoying, Malavera, Alejandra, Zhang, Chunmiao, Yang, Zhao, Li, Brook, Meng, Zhuo, Liu, Leibo, Ning, Yi, Dong, Le, Armenis, Manuela, Lim, Joyce, Monaghan, Helen, Ma, Lu, Li, Xi, Luo, Rui, Cheng, Guojuan, Dong, Yilin, Liu, Ziqin, Wang, Shuihong, Zhang, Ying, Cheng, Jipeng, Shi, Hui, Li, Wenjing, Mou, Langming, Yi, Ping, Chen, Chen, Chen, Xue, Weerawardena, Shalomi, Ellawala, Poornima, Ranasinghe, Enalee, Rodrigo, Chrishmi, Wahab, Kolawala, Adeniyi, Sunday, Pandian, Jeyaraj, Khanna, Megha, Muñoz Venturelli, Paula, González, Francisca, Urrutia Goldsack, Francisca, Wasay, Mohammad, Begum, Dilshad, Pontes-Neto, Octavio, Camilo, Millene, Dias, Francisco, Vincenzi, Octavio, Moro, Carla, Santos, Renata, Texeira, Nara, Longo, Alexandre, Liberato, Rafaela, Martins, Sheila, Pille, Arthur, Chwal, Bruna, Silva, Isabel, Titton, Natacha, Weiss, Gustavo, Mora, Daissy, Ouriques, Magda, Carbonera, Leonardo, Bazan, Rodrigo, Modolo, Gabriel, Winckler, Fernanda, Miranda, Luana, Souza, Juli, Rojo, Alexis, Uslar, Wilhelm, Medel, Lorena, Lopez, Javiera, Herrero, Diego, Lavados, Pablo, Vargas Latorre, Barbara, Conejan, Nathalie, Esparza, Tomas, Sotomayor, Patricio, Wenger, Denisse, Gigoux, Juan Pablo, Letelier, Aldo, Acevedo, Lilian, Moya, Vivianne, Figueroa, Cristian, Vallejos, Nicol, Guerrero, Rodrigo, Velasquez, Mauricio, Vallejos, Jose, Pallauta, Kimerly, Santibanez, Tamara, Queirolo, Angelo, Lobos, Andrea, Jiang, Yongming, Li, Weimin, Huang, Wei, Luo, Ke, Liu, Gangying, Tang, Guanghai, Yang, Guang, Jiang, Hongtao, Zhang, Xu, Jing, Hongyan, Zhu, Sheng, Pu, Bo, Lv, Dong, Kang, Hui, Hu, Qiuping, She, Xiaochun, Jiang, Xiaoming, Chen, Yanli, Yang, Shenghua, He, Jianjun, Li, Zongping, Cheng, Gang, Huang, Hailin, Wang, Xiaoyi, Lin, Jianqiong, Chen, Minhui, Yang, Chenghao, Ding, Hao, Deng, Yunliang, Luo, Fei, Zhang, Rongjun, Wang, Xiaofeng, Zhang, Hongbing, Yang, Xiaoliang, Zhang, Yang, Yang, Chengyi, He, Yu, Liu, Feng, Wang, Rongjie, Zhang, Yuhui, Xin, Xiaodong, Feng, Bin, Hao, Wanru, Song, Chang, Guo, Yun, Jiang, Dehua, Chen, Jie, Tang, Changtong, Zhu, Hongliang, Li, Xin, Cui, Jin, Xu, Haidong, Li, Boyang, Tang, Fusheng, Li, Yuanbin, Gao, Min, Yang, Bo, Xu, Xuejun, Deng, Bing, Zheng, Yi, Ge, Yuanhong, Chen, Keyu, Liu, Yang, Li, Xinshen, Zhong, Tingting, Xu, Jianfeng, Zhang, Hai, Wang, Jiyue, Zhu, Jianxin, Sun, Hanyu, Yu, Fuhua, Zhang, Xueguang, Xu, Jianguo, Zhang, Mingsen, Wang, Bin, Ma, Yiming, Jiang, Donglin, Zhou, Jun, Liu, Cong, Nie, Wenhong, Li, Mingguo, Tian, Tao, Li, Yong, He, Mingfang, Tu, Xiaolong, Wu, Zhengjun, Liu, Hong, Zhong, Dongsheng, Jiang, Rongcai, Sun, Jian, Tian, Ye, Wei, Yingsheng, An, Shuo, Wei, Pingbo, Luo, Le, Lin, Bin, Liu, Gang, Wen, Yan, Cai, Qiang, Chen, Qianxue, Lei, Pan, Li, Zhiyang, Zhang, Meifang, He, Jiaquan, Chen, Yan, Liu, Jun, Liu, Xinghai, Li, Junyan, Chen, Min, Wang, Jing, Zhou, Bingzhi, Ye, Baichun, Zhang, Jiancheng, Zhang, Manyuan, Pan, Xuming, Yu, Xiaoxiang, Xu, Jian, Xiao, Qingbao, Wang, Yuefei, Tao, Liang, Shi, Lin, Zheng, Niandong, You, Guoliang, Lei, Bo, Chen, Shu, Wu, Honggang, Hu, Jin, Zhao, Jianlan, Yu, Jian, Yuan, Qiang, Du, Zhuoying, Tang, Xielin, Li, Qianke, Liu, Shenghua, Yang, Feilong, Xiao, Kui, Luo, Chao, Wang, Guang, Che, Xudong, Teng, Zhipeng, Wan, Wenwu, Li, Jun, Liu, Yu, Fan, Mingbo, Zhang, Tao, Cai, Lun, Ma, Yuan, Ma, Zhifeng, Li, Bin, He, Linlin, Li, Jinghui, Zhang, Weibing, Zhang, Shuxin, Zhang, Hongzhen, Dai, Yingguang, Lei, Jun, Mao, Lei, Huang, Yiyang, Zhou, Zhi, Chen, Ping, Chen, Fang, Wei, Pan, Li, Tiangui, Chen, Honglin, Zeng, Mengfei, Mou, Kejie, Xue, Jun, Jiang, Yong, Tang, Xiaoping, Chen, Tao, Zhang, Yalan, Xu, Yanbing, Gu, Yuchen, Chen, Lei, Zhao, Yujun, Yang, Bin, Kuai, Peng, Wang, Xi, Yang, Yuwang, Hu, Xueling, Zhang, Huitian, Yang, Yintao, Wang, Weifeng, Zhang, Junyi, Cheng, Wei, Zhang, Xiaoxue, Ma, Xiaowen, He, Qin, Zhang, Li, Gao, Rong, Liu, Huixiang, Ye, Jingwei, Xu, Ping, Wu, Xin, Yuan, Yuan, Zou, Peng, Zhang, Zhen, Cheng, Jiyong, Zhou, Zhangming, Zeng, Yijun, Liang, Zhang, Du, Deming, Yu, Shui, Cao, Yongjun, Xu, Jiaping, Huang, Zhichao, Chen, Dongqin, Xiao, Wenfeng, Zhu, Li, Yuan, Miao, Wang, Yuhai, Shi, Dongliang, Hu, Xu, Xiang, Dingchao, Shi, Like, Wang, Hongqin, Yang, Liu, Miao, Wang, Hu, Yiyi, Zhao, Yuchun, Hu, Xi, Zhou, Weiduo, Sun, Chao, Tang, Dong, Yao, Kun, You, Jin, Chen, Shishi, Yao, Jianmin, Li, Huanmei, Liu, Jinmei, Bai, Ailin, Yi, Yong, Deng, Qingshan, Luo, Peng, Wang, Han, Jiang, Jingcheng, Yang, Qingwei, He, Shunpo, Wang, Jun, Chen, Yu, He, Hua, Deng, Yuyang, Cao, Zhikai, Yi, Xuxia, Luo, Jinbiao, Luo, Shuang, Gong, Min, Liu, Li, Gao, Xuejun, Liu, Jia, Wu, Li'e, Zhang, Jia, Sun, Hongying, Li, Xinhui, Jia, Lu, Wu, Jianbing, Zhang, Jie, Zhang, Huajun, Du, Chunfu, Li, Shun, Yang, Xiaobin, He, Jie, Liao, Lei, Zhou, Gezhi, Dong, Wentao, Chen, Yunxiang, Lin, Xiaofeng, Shui, Xujian, Zhang, Peng, Zhao, Yuan, Yang, Hongli, Zhao, Wenbin, Zhang, Xiaoyi, Chen, Jincao, Wu, Qian, Dai, Xuan, Tang, Baogui, Wang, Yinjuan, Liu, Tao, Zhang, Haixia, Duan, Faliang, Luo, Ming, Jiao, Qingfang, Lei, Guoliang, Wang, Dong, Song, Chunwang, Tan, Haopeng, Ye, Feng, Qin, Xinghu, Liang, Xiaolong, Liu, Junling, Yang, Lang, Yang, Jie, Lin, Yapeng, Yang, Qian, Ma, Xuntai, Qi, Yinkuang, Pan, Baogen, Jiang, Caixia, Ye, Zhanying, Dong, Ce, Yue, Xiongfei, Yang, Xiaopeng, Maimaitiyiming, Tuoheti, Dong, Jun, Wu, Yonggang, Gao, Feng, Zhao, Deqiang, Zhang, Xinghai, Wang, PengJun, Jiang, Hongbo, Li, Jianping, Zhang, Wei, Chen, Jing, Tong, Haibo, Wang, Yonghong, Qiao, Kaipeng, Guo, Fuyou, Zhang, Mingchu, Hu, Yan, Feng, Mengzhao, Song, Dengpan, Zuo, Yi, Chen, Shangjun, Qian, Chao, Li, Baoming, Ma, Jingku, Zhang, Sunfu, Kong, Bin, Dong, Xingyu, Fang, Sheng, Lu, Bin, Li, Yang, Yang, Yongling, Yu, Hong, Sun, Huaiyu, Wang, Yue, Wang, Weimin, Li, Tong, Li, Shengli, Xu, Zhiming, Wang, Yongyi, Dong, Qiang, Tang, Yuping, Chu, Heling, Lu, Ying, Wang, Zhong, Sun, Xiaoou, Zhao, Jianhua, Yang, Shuaifeng, Qian, Xiying, Saroja, Aralikatte Onkarappa, Naik k, Ravishankar, Chindhi, Sandip, Pampaniya, Nakul, Amaresh, Kurubara, Iype, Thomas, R, Dileep, Rajan, Reeja, Panicker, Praveen, Das, Rupjyoti, Choudhury, Nupur, Gohain, Pankaja, Webster, Jemin, Pakma, Biyol, Sangi, Lalbiak, Sebastian, Ivy, Aggrawal, Gaurav, Raj, Komal, Rajoura, Deepankshi, Singh, Sulena, Aggrawal, Varun, Narang, Amit, Arauz, Antonio, Cano-Nigenda, Vanesa, López-Mena, Diego, Valdez-Ruvalcaba, Héctor, Toledo-Treviño, Roberto, Obiako, Reginald, Abubakar, Sani, Emeka, Oguike, Olayemi, Balogun, Lois, Melika, Philip, Ibinaiye, Comfort O, Olurishe, Okubadejo, Njideka, Agabi, Osigwe, Ojo, Oluwadamilola, Wahab, Kolawole, Bello, Abiodun, Ibukun, Oyinloye, Sanayaolu, Olufemi, Jimoh, Abdulraheem, Waheed, Shahid, Kamal, Dr.Ayeesha, Shoaib, Raja Farhat, Orooj, Fizza, Majid, Sadaf, Zehra, Taskeen, Khan, Abdus Salam, Shanker, Ravi, Syed, Nadir Ali, Ahmad, Nashwa, Abanto, Carlos, Valencia, Ana, Barrientos, Danny, Ramirez, Jorge, Calle, Pilar, Palliyeguruge, Dilum, Muthucumarana, Sumudu, Ratnayaka, Shiroma, Ganihiarachchi, Dilhara, Bandaranayake, Arundathi, Somaratne, S.D.B, Narayana, Saumya, Gallage, Sithara, Senanayake, Bimsara, Samarasiri, Udari, Luke, Dunya, Sivapathasundaram, Mythily, Sahadevan, Vithoosan, Rasmi, Amani, Deshaka, Yuran, Fernando, Nilukshi, Munasinghe, Aruna, Rathnapriya, Kapilanga, Nissanka, A.S, Karunathilake, Kanchana, Gayan, Isuru, Wijenayake, Kaminda, Gunasekara, Hasitha, Vidyarathne, Jagath, Keshavaraj, Ajantha, Janarthanan, Kanagasabapathy, Gerald Jeevathasan, Arhivalaky, Sivamainthan, Sivaram, John Priyanth, Mathyamuthan, John Priyanth, Abirami, Rajendiran, Thambippillai, Alwis, Sanjeewa, Gunasekare, Nushara, Liyanarachchi, Vasundara, Dissanayake, Athula, Uluwattage, Wimalasiri Mewa, Ratnayake, Gimhani, Rajinee, Charika, Jayawardana, Sakura, Peiris, Janaka, Wicramasinghe, Ranjith, Fernando, Chamila, Abbas, Jessie, Withanage, Nethmini, Bandara, Makaranda, Mai, Duy Ton, Nguyen, Van Chi, Dao, Viet Phuong, Vuong, Xuan Trung, Nguyen, Tien Dung, Dinh, Trung Hieu, Phan, Ha Quan, Bui, Quoc Viet, Phung, Dinh Tho, Pham, Quang Tho, Pham, Dinh Dai, Do, Duc Thuan, Dang, Phuc Duc, Dang, Minh Duc, Nguyen, Dang Hai, Nguyen, Thi Phuong Nga, Nguyen, Quoc Huy, Pham, Quoc Dai, Chau, Quoc Vinh, Tai, Vinh Thy Van, Le, Tran Vinh, Le, Cong Tri, Tran, Ha Mai Khuong, Nguyen, Huu Khanh, Ngyen, Hoang Minh Thao, Vo, Duc Chien, Nguyen, Thai My Phuong, Tran, Trung Thanh, Vo, Thi Hanh Vi, Cao, Hao Nhien, Nguyen, Ba Thang, Le, Thi Ngoc Suong, La, Thien Duc, Pham, Chi Duc, Thai, Huy, Muñoz-Venturelli, Paula, de Silva, Asita, Thang, Nguyen Huy, Wahab, Kolawole W, Pandian, Jeyaraj D, Pontes-Neto, Octavio M, Shi, Haiping, Wang, Xia, Zhao, Yang, Li, Hao, Liu, Yi, Jiang, Yan, Wu, Bo, Liu, Ming, and Anderson, Craig S

Published
2023
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35. Evaluate the Influence of Groynes System on the Hydraulic Regime in the Ha Thanh River, Binh Dinh Province, Vietnam

Author

Tran, Thanh-Nhan-Duc, Nguyen, Quang Binh, Le, Dinh Tam Luc, Nguyen, Tien Dung, Vo, Ngoc Duong, Gourbesville, Philippe, Kostianoy, Andrey, Series Editor, Carpenter, Angela, Editorial Board Member, Younos, Tamim, Editorial Board Member, Scozzari, Andrea, Editorial Board Member, Vignudelli, Stefano, Editorial Board Member, Kouraev, Alexei, Editorial Board Member, Gourbesville, Philippe, editor, and Caignaert, Guy, editor

Published
2022
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36. Effect of Turning Vanes on Heat Exchange Characteristics of Cooling Channel in Turbine Blade

Author

Nguyen, Tien-Dung, Do, Hai-Quang, Hoang, Cong-Hung, Nguyen, Minh-Hieu, Bui, Mai-Anh Thi, Dinh, Cong-Truong, Luu, Hong-Quan, Cavas-Martínez, Francisco, Editorial Board Member, Chaari, Fakher, Series Editor, di Mare, Francesca, Editorial Board Member, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Editorial Board Member, Ivanov, Vitalii, Series Editor, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Le, Anh-Tuan, editor, Pham, Van-Sang, editor, Le, Minh-Quy, editor, and Pham, Hoang-Luong, editor

Published
2022
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37. Design and Construction of Nearshore Wind Turbine Foundations: Some Experiences of APECO and FECON

Author

Nguyen, Tien Dung, Ho, Duc An, Bui, Nguyen Hai, Pham, Duc Huyen, Ngo, Huy Dong, Du, Van Toan, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Huynh, Dat Vu Khoa, editor, Tang, Anh Minh, editor, Doan, Dinh Hong, editor, and Watson, Phil, editor

Published
2022
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38. Geotechnical Characteristics of Seabed Deposits at Su Tu Trang Site, Cuu Long Basin, Offshore Vietnam

Author

Ngo, Huy Dong, Pham, Quy Ngoc, Nguyen, Tien Dung, Doan, Huy Hien, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Huynh, Dat Vu Khoa, editor, Tang, Anh Minh, editor, Doan, Dinh Hong, editor, and Watson, Phil, editor

Published
2022
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43. Evaluation of ride performance of PID controller in active suspension systems for an electric vehicle.

Author

Nguyen Tien Dung, Bui Van Cuong, Le Van Quynh, Ngo Van Dung, and Vu Tran Hoang

Subjects
*ELECTRIC suspension, *PID controllers, *ROOT-mean-squares, *ELECTRIC vehicles, *ACCELERATION (Mechanics)
Abstract

In order to evaluate ride performance of an electric vehicle (EV) active suspension systems (ASSs), a 8-DOF full-vehicle dynamic model of EV under random road excitation is set for control ASSs of EV to enhance ride comfort. A PID controller is proposed for control. The parameters of the PID controller are tuned using the Ziegler-Nichols method. The achieved results indicate that the root mean square (RMS) values of the vertical driver's seat, vehicle body, pitching and rolling acceleration responses with ASSs using the proposed controller respectively reduce by 31.12 %, 24.76 %, 15.00 %, and 11.59 % in comparison with passive suspension systems (PSSs) under the investigated condition. In addition, these results will be the basis for optimizing the parameters for PID controller to improve the ride performance of ASS. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Effects of Roasting on Antibacterial and Antioxidant Properties of Sophora japonica Buds—The Involvements of Rutin and Quercetin Constituents.

Author

Nguyen, Hieu Chi, Hoang, Hang Thi Thuy, Miyamoto, Atsushi, Nguyen, Tien Dung, and Nguyen, Ha Thi Thanh

Subjects
TREATMENT effectiveness, MATERIA medica, HEAT treatment, FLAVONOIDS, ENTHALPY, QUERCETIN
Abstract

Roasting is the most common thermal processing method established for Sophora japonica (SJ) buds applied as traditional medicines, and it has also been reported to alter several of their therapeutic functions. However, there have been no studies investigating the influences of roasting on the effects of these materials against bacteria. Therefore our study was performed to examine the alterations that this process would induce in SJ buds' antibacterial properties. Fresh buds were subjected to hot air drying or different roasting methods, as described in Materia Medica, including yellow-, dark yellow-, scorched-, and charred-roasting conditions. Antibacterial effects, total polyphenol and flavonoid contents, antioxidant activities, as well as rutin and quercetin concentrations in methanol extracts obtained from those materials, were then measured and compared. The results showed that dark yellow-roasted SJ buds exerted the strongest antibacterial and antioxidant activities and were also the richest in polyphenol contents. Analysis of rutin and quercetin revealed that, following the increment in heating temperatures up to 240 °C, the reduction in rutin content occurred in a parallel manner to the increment in quercetin content. However, overheating at 300 °C reduced both concentrations. Among the five tested samples, dark yellow-roasted SJ had the highest amounts of quercetin. Furthermore, the comparison of rutin and quercetin in antibacterial effects and antioxidant activities showed that the latter was significantly stronger in both of these functions, suggesting that the increment in quercetin content as a result of heat treatment was responsible, at least in part, for the potentiation of the two therapeutic effects. [ABSTRACT FROM AUTHOR]

Published
2024
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