Putrajaya, Selangor Darul Ehsan, Malaysia

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    ABSTRACT: This paper presents an evaluation of a curved spring element that may be utilized in a developed variable stiffness bracing (VSB) system to confer the variable stiffness characteristic of the system.VSB system is established to protect the structure against dynamic loads induced by earthquake, wind and etc. To obtain the curved shape of the spring, mathematical modeling is conducted. Direct compression experimental tests are conducted for a variety of models with different thicknesses and materials. The results of the experiments show a nonlinear stiffness trend for the curved spring element. In addition, to observe the yielding of the curved spring, different strain gauges are installed in several positions to record the strain in the models during the application of compression load. The results reveal that the geometry and material characteristics have an important effect on the stiffness value of the spring. Furthermore, finite element simulations of models are performed, and results are compared with those of experimental tests. The results from the experiments, as well as model and finite element simulation, show the curved spring's potential to be used in the developed VSB system and can be installed as a lateral resistance system in a structure subjected to vibration excitation such as an earthquake. Finally, the efficiency of the aforementioned system is evaluated via pushover analysis in a bare frame via finite element simulation. The results from pushover analysis illustrate the efficiency of the variable stiffness bracing system in framed structures.
    Journal of Constructional Steel Research 02/2016; 117:115-125. DOI:10.1016/j.jcsr.2015.10.011
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    ABSTRACT: Human action recognition from video has several potential to apply in different real-life applications, but the most cases in this field suffer from the variation in viewpoint. Most of published methods in this area are considered the performance of each single camera, therefore the change in the viewpoints significantly decrease the recognition rate. In this paper, multiple views are considered together and a method has proposed to recognize human action depicted in multi-view image sequences. In the first step, the border of the human body's silhouette is extracted and distance signal is calculated. In the next step, the wavelet transform is applied to extract coefficients of single-view features, and then the extracted features are combined to compose multi-view features. Finally a hierarchical classifier using support vector machine and Naïve Bayes classifiers is implemented to classify the actions. The average of overall action recognition accuracy for 12 actions using 5 different angles of views on the IXMAS dataset is 88.22. The results of experiments on the popular multi-view dataset have shown the proposed method achieves high and state-of-the-art success rates. In other word, combination of single-view extracted features from the wavelet approximation coefficients and composing the multi-view features can be used as the multi-view features. Further, the hierarchical classifier can be applied to recognize actions in multi-view human action recognition area.
    Procedia Computer Science 12/2015; 62:585-592. DOI:10.1016/j.procs.2015.08.540
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    ABSTRACT: Shuffle-exchange networks (SENs) have been generally considered as a convenient interconnection systems due to the size of their switching elements (SEs) and simple configuration. Evaluation of reliability performance has been attempted by researchers in the past. This paper is a depth study of reliability evaluation in shuffle exchange network. We propose a SEN with minus one stage (SEN-) and compared with three other types of SEN. The measurement includes three parameters; terminal, broadcast and network reliability.
    Procedia Computer Science 12/2015; 59:162-170. DOI:10.1016/j.procs.2015.07.533


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Asian Pacific journal of cancer prevention: APJCP 11/2014; 15(20):8571-6. DOI:10.7314/APJCP.2014.15.20.8571
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