Adaptive Cuckoo Search Algorithm for Short-Term Fixed-Head Hydrothermal Scheduling Problem with Reservoir Volume Constraints

Bach Hoang Dinh,Thang Trung Nguyen,Dieu Ngoc Vo 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.5

This paper present three versions of Cuckoo Search Algorithm (CSA) including conventional Cuckoo Search Algorithm (CSA), modified CSA (MCSA) and adaptive CSA (ACSA) for solving the fixed head short-term hydrothermal scheduling (ST-HTS) problem where the reservoir volume constraints and nonconvex fuel cost function of thermal unit as well as the power losses in transmission line are taken into account. Among the applied methods, ACSA is first developed in the study by performing two modifications on second new solution generation via the action of an alien egg to be abandoned. In the ACSA, all initial solutions or all solutions at the end of the previous iteration are evaluated and sorted into two kinds of solution, good solutions with lower fitness function and bad solutions with higher fitness function. The implementation of the first new solution generation first via Lévy flights in the ACSA is carried out similarly to that in MCSA. However, at the second new solution generation the ACSA evaluates the current solutions to choose the best one and use the information of the best one with a random solution to generate the second new solutions via the action of an alien egg to be abandoned. In addition, the probability of an alien egg discovery is considered an adaptive variable, which is set to the largest value at the beginning and decreased as the iteration is increased. Due to the adaptive value of the parameter, the ACSA can search an optimal solution but the trial runs are significantly decreased compared to CSA and MCSA. The performance of the ACSA is validated by testing on two systems and comparing with CSA, MCSA and other existing methods available in the paper.

A review of anaerobic digestion systems for biodegradable waste: Configurations, operating parameters, and current trends

Dinh Pham Van,Takeshi Fujiwara,Bach Leu Tho,Pham Phu Song Toan,Giang Hoang Minh 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.1

With benefits to the human health, environment, economy, and energy, anaerobic digestion (AD) systems have attracted remarkable attention within the scientific community. Anaerobic digestion system is created from (bio)reactors to perform a series of bi-metabolism steps including hydrolysis/acidogenesis, acetogenesis, and methanogenesis. By considering the physical separation of the digestion steps above, AD systems can be classified into single-stage (all digestion steps in one reactor) and multi-stage (digestion steps in various reactors). Operation of the AD systems does not only depend on the type of digestion system but also relies on the interaction among growth factors (temperature, pH, and nutrients), the type of reactor, and operating parameters (retention time, organic loading rate). However, these interactions were often reviewed inadequately for the single-stage digestion systems. Therefore, this paper aims to provide a comprehensive review of both single-stage and multi-stage systems as well as the influence of the growth factors, operating conditions, and the type of reactor on them. From those points, the advantages, disadvantages, and application range of each system are well understood.

FGW-FER: Lightweight Facial Expression Recognition with Attention

Huy-Hoang Dinh,Hong-Quan Do,Trung-Tung Doan,Cuong Le,Ngo Xuan Bach,Tu Minh Phuong,Viet-Vu Vu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9

The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.

Modified Sliding Mode Control for Mismatched Uncertain Large-Scale Systems

Van Van Huynh,Bach Hoang Dinh 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.6

In this paper, a modified sliding mode control is proposed to stabilize a class of large-scale systems with mismatched uncertainties, unknown exogenous disturbances and without the measurements of the states. Based on the Lyapunov method, appropriate linear matrix inequality stability conditions are derived to guarantee the stability of the system. Then, a modified adaptive sliding mode control law is proposed to guarantee the finite time reachability of the system states by using output feedback only. Final, a double-inverted pendulums system connected by a spring is simulated to demonstrate the efficacy of the proposed method.

Using Online Respondent Driven Sampling for Vietnamese Youths’ Alcohol Use and Associated Risk Factors

Melvyn WB Zhang,Bach Xuan Tran,Huong Lan Thi Nguyen,Huong Thi Le,Nguyen Hoang Long,Huong Thi Le,Nguyen Duc Hinh,Tran Dinh Tho,Bao Nguyen Le,Vu Thi Minh Thuc,Chau Ngo,Nguyen Huu Tu,Carl A. Latkin,Roger 대한의료정보학회 2017 Healthcare Informatics Research Vol.23 No.2

Objectives: The average alcohol consumption per capita among Vietnamese adults has consistently increased. Although alcoholrelated disorders have been extensively studied, there is a paucity of research shedding light on this issue among Internet users. The study aimed to examine the severity of alcohol-related disorders and other associated factors that might predispose individuals towards alcohol usage in a sample of youths recruited online. Methods: An online cross-sectional study was conducted with 1,080 Vietnamese youths. A standardized questionnaire was used. Respondent-driven sampling was applied to recruit participants. Multivariate logistic and Tobit regressions were utilized to identify the associated factors. Results: About 59.5% of the males and 12.7% of the total youths declared that they were actively using alcohol. From the total sample, a cumulative total of 32.3% of the participants were drinking alcohol, with 21.8% and 25.0% of the participants being classified as drinking hazardously and binge drinkers, respectively. The majority of the participants (60.7%) were in the pre-contemplative stage. Conclusions: A high prevalence of hazardous drinking was recognized among online Vietnamese youths. In addition, we found relationships between alcohol use disorder and other addictive disorders, such as tobacco smoking and water-pipe usage. Our results highlighted that the majority of the individuals are not receptive to the idea of changing their alcohol habits, and this would imply that there ought to be more government effort towards the implementation of effective alcohol control policies.

Adaptive Cuckoo Search Algorithm for Economic Emission Load Dispatch Problem

Ly Huu Pham,Thang Trung Nguyen,Bach Hoang Dinh 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4

This paper proposes an Adaptive Cuckoo Search Algorithm (ACSA) for solving economic emission dispatch (EELD) problem with quadratic fuel function. The ACSA is developed by performing two adaptive updated step size parameters on conventional CSA in aim to enhance the convergence speed and quality solution of the conventional CSA. In addition to minimizing electricity generation fuel cost, emission released into the air from thermal plants is also another main objective needs to be minimized. In order to test the performance of the proposed ACSA two systems including a three unit system with one load case and a six unit system with three load cases are employed. The obtained result by the ACSA compared to that from other methods has revealed that the proposed ACSA is a very promising meata-heuristic algorithm for solving economic emission load dispatch problem.

Optimal Generation Coordination of Hydrothermal System

Ly Huu Pham,Thang Trung Nguyen,Dieu Ngoc Vo,Bach Hoang Dinh 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.5

This paper presents the use of an enhanced version of conventional cuckoo search algorithm (ECSA) for solving optimal generation coordination of hydrothermal system where the objective is to minimize both fuel cost and emission, and the hydro model is represented as a quadratic function of water discharge with respect to generation. The ECSA method is built for the optimal operation based on several modifications on conventional Cuckoo search algorithm (CSA). In the ECSA method, by evaluating the fitness of all initial eggs they are divided into two parts including the high quality one with lower fitness value and bad quality one with higher fitness value. The ECSA is tested on several systems and obtained results from the ECSA are compared those from other methods. The comparison reveals that the ECSA is so efficient for the considered problem.