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ABSTRACT: The demand for animal protein, especially fish, is growing fast, perhaps due to the rapid expansion of populations, increases in income and changes in eating habits and life styles. Capture fisheries, which supply over 70% of the fish for human consumption in Malaysia, are over-exploited or depleted. Their yields have become stagnant over the last few decades and in some cases have even declined. Nevertheless, aquaculture has the potential to meet these challenges if practised well. This study therefore aims to estimate the technical efficiency of pond culture systems using data envelopment analysis (DEA). In addition, it investigates the determinants of technical efficiency by employing an ordinary least squares (OLS) regression model. The estimated technical efficiency of pond culture was found to be 0.86, which means that the fish farmers in our sample could reach full technical efficiency through reducing their input usage by 14% with the current level of technology to produce the same output levels. The results of the OLS regression indicate that farmers’ age, experience, extension training and water management have positive and statistically significant impacts on technical efficiency. Information on water management practices could be passed on by extension agents to inefficient farms to assist them in catching up with the farms demonstrating best practice.
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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.
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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.
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