• Steel and Composite Structures
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• v.44 no.5
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• pp.691-705
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• 2022

Shear failure in reinforced concrete (RC) structures is very hazardous. This failure is rarely predicted and may occur without any prior signs. Accurate shear strength prediction of the RC members is challenging, and traditional methods have difficulty solving it. This study develops a JAYA-GBRT model based on the JAYA algorithm and the gradient boosting regression tree (GBRT) to predict the shear strength of RC slender beams without stirrups. Firstly, 484 tests are carefully collected and divided into training and test sets. Then, the hyperparameters of the GBRT model are determined using the JAYA algorithm and 10-fold cross-validation. The performance of the JAYA-GBRT model is compared with five well-known empirical models. The comparative results show that the JAYA-GBRT model (R² = 0.982, RMSE = 9.466 kN, MAE = 6.299 kN, µ = 1.018, and Cov = 0.116) outperforms the other models. Moreover, the predictions of the JAYA-GBRT model are globally and locally explained using the Shapley Additive exPlanation (SHAP) method. The effective depth is determined as the most crucial parameter influencing the shear strength through the SHAP method. Finally, a Graphic User Interface (GUI) tool and a web application (WA) are developed to apply the JAYA-GBRT model for rapidly predicting the shear strength of RC slender beams without stirrups.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8513-8517
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• 2016

Background: GLOBOCAN12 recently reported high cancer mortality in Malaysia suggesting its cancer health services are under-performing. Cancer survival is a key index of the overall effectiveness of health services in the management of patients. This report focuses on Subang Jaya Medical Centre (SJMC) care performance as measured by patient survival outcome for up to 5 years. Materials and Methods: All women with breast cancer treated at SJMC between 2008 and 2012 were enrolled for this observational cohort study. Mortality outcome was ascertained through record linkage with national death register, linkage with hospital registration system and finally through direct contact by phone or home visits. Results: A total of 675 patients treated between 2008 and 2012 were included in the present survival analysis, 65% with early breast cancer, 20% with locally advanced breast cancer (LABC) and 4% with metastatic breast cancer (MBC). The overall relative survival (RS) at 5 years was 88%. RS for stage I was 100% and for stage II, III and IV disease was 95%, 69% and 36% respectively. Conclusions: SJMC is among the first hospitals in Malaysia to embark on routine measurement of the performance of its cancer care services and its results are comparable to any leading centers in developed countries.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1077-1082
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• 2016

Background: The three standard biomarkers used in breast cancer are the estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). The Ki-67 index, a proliferative marker, has been shown to be associated with a poorer outcome, and despite absence of standardization of pathological assessment, is widely used for therapy decision making. We aim to study the role of the Ki-67 index in a group of Asian women with breast cancer. Materials and Methods: A total of 450 women newly diagnosed with Stage 1 to 3 invasive breast cancer in a single centre from July 2013 to Dec 2014 were included in this study. Univariable and multivariable logistic regression was used to determine the association between Ki-67 (positive defined as 14% and above) and age, ethnicity, grade, mitotic index, ER, PR, HER2, lymph node status and size. All analyses were performed using SPSS Version 22. Results: In univariable analysis, Ki -67 index was associated with younger age, higher grade, ER and PR negativity, HER2 positivity, high mitotic index and positive lymph nodes. However on multivariable analysis only tumour size, grade, PR and HER2 remained significant. Out of 102 stage 1 patients who had ER positive/PR positive/HER2 negative tumours and non-grade 3, only 5 (4.9%) had a positive Ki-67 index and may have been offered chemotherapy. However, it is interesting to note that none of these patients received chemotherapy. Conclusions: Information on Ki67 would have potentially changed management in an insignificant proportion of patients with stage 1 breast cancer.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.5
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• pp.33-49
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• 2024

In this paper, a supply chain network (SCN) model with disruption risk is proposed. Either the disruption of the facilities in each stage of the SCN or the disruption of route between them is considered as the disruption risk in the SCN model. Many conventional studies have considered facility disruption and route disruption separately. However, their disruptions can be occurred simultaneously in real world. This paper proposes the SCN model with facility disruption and route disruption simultaneously. The SCN model is represented as a nonlinear 0-1 programming and solved using a hybrid meta-heuristics approach called GA-JAYA-FLC approach. In numerical experiment, the performance of the GA-JAYA-FLC approach is compared with those of some conventional single and hybrid meta-heuristic approaches using a multi-stage SCN model. Experimental result shows that the GA-JAYA-FLC approach outperforms some conventional single and hybrid meta-heuristic approaches.

• Steel and Composite Structures
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• v.30 no.1
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• pp.47-55
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• 2019

The aim of this paper is to present new and an efficient optimization algorithm called Jaya for the optimum mass of braced dome structures with natural frequency constraints. Design variables of the bar cross-section area and coordinates of the structure nodes were used for size and shape optimization, respectively. The effectiveness of Jaya algorithm is demonstrated through three benchmark braced domes (52-bar, 120-bar, and 600-bar). The algorithm applied is an effective tool for finding the optimum design of structures with frequency constraints. The Jaya algorithm has been programmed in MATLAB to optimize braced dome.

• Steel and Composite Structures
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• v.26 no.2
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• pp.163-170
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• 2018

The purpose of this paper is to present a new and efficient optimization algorithm called Jaya for optimum design of steel grillage structure. Constrained size optimization of this type of structure based on the LRFD-AISC is carried out with integer design variables by using cross-sectional area of W-shapes. The objective function of the problem is to find minimum weight of the grillage structure. The maximum stress ratio and the maximum displacement in the inner point of steel grillage structure are taken as the constraint for this optimization problem. To calculate the moment and shear force of the each member and calculate the joint displacement, the finite elements analysis is used. The developed computer program for the analysis and design of grillage structure and the optimization algorithm for Jaya are coded in MATLAB. The results obtained from this study are compared with the previous works for grillage structure. The results show that the Jaya algorithm presented in this study can be effectively used in the optimal design of grillage structures.

• Smart Structures and Systems
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• v.31 no.3
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• Steel and Composite Structures
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• v.27 no.3
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• pp.297-310
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• 2018

A simple and efficient numerical optimization approach for the lightweight optimal design of composite laminated beams is presented in this paper. The proposed procedure is a combination between the finite element method (FEM) and a global optimization algorithm developed recently, namely Jaya. In the present procedure, the advantages of FEM and Jaya are exploited, where FEM is used to analyze the behavior of beam, and Jaya is modified and applied to solve formed optimization problems. In the optimization problems, the objective aims to minimize the overall weight of beam; and fiber volume fractions, thicknesses and fiber orientation angles of layers are selected as design variables. The constraints include the restriction on the first fundamental frequency and the boundaries of design variables. Several numerical examples with different design scenarios are executed. The influence of the design variable types and the boundary conditions of beam on the optimal results is investigated. Moreover, the performance of Jaya is compared with that of the well-known methods, viz. differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO). The obtained results reveal that the proposed approach is efficient and provides better solutions than those acquired by the compared methods.

• Structural Engineering and Mechanics
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• v.73 no.4
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• pp.397-405
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• 2020

In this study size optimization of large-scale dome structures with dynamic constraints is presented. In the optimal design of these structure, the Jaya algorithm is used to find minimal size of design variables. The design variables are the cross-sectional areas of the steel truss bar elements. To take into account the constraints which are the first five natural frequencies of the structures, the finite element analysis is coded in Matlab programs using eigen values of the stiffness matrix of the dome structures. The Jaya algorithm and the finite elements codes are combined by the help of the Matlab - GUI (Graphical User Interface) programming to carry out the optimization process for the dome structures. To show the efficiency and the advances of the Jaya algorithm, 1180 bar dome structure and the 1410 bar dome structure were tested by taking into the frequency constraints. The optimal results obtained by the proposed algorithm are compared with those given in the literature to demonstrate the performance of the Jaya algorithm. At the end of the study, it is concluded that the proposed algorithm can be effectively used in the optimal design of large-scale dome structures.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2007.10a
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• pp.470-485
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• 2007