The current study explored consumers’ intention to buy environmentally-friendly electric vehicles (EVs) based on an extended theory of planned behavior (TPB). Additionally, the moderating role of product knowledge on the relationships between attitude, subjective norm, and perceived behavioral control and consumers’ intention to buy EVs were explored. A total of 267 valid responses were collected to test the proposed model and hypotheses. The results reported that eight out of eleven hypotheses were supported, the predictive power of the proposed model was better than TPB, and the product knowledge significantly moderates the effects of attitude, subjective norm, and perceived behavioral control on consumers’ purchase behavior. The influence of subjective norm on EV purchase intention was more obvious in the situation of low product knowledge. This study contributes to the literature from a new research perspective by exploring product knowledge as a moderating factor in the TPB concerning EV purchase intention.

This article investigates changes in power spectral density caused by vibration signals of beams having damage under the act of moving load. Based on the results, the authors have proposed a parameter to monitor the structures� deterioration conditions. The article conducted simulation of deterioration in beams by causing cracks which changed the stiffness of the structure. The features proposed in this article are made by changing shapes of power spectral density to detect the deterioration of structure through damage caused in the beams. The experiment was designed to best correspond to the simulation of realistic traffic over bridges. The power spectral density was established from vibration signals received by acceleration sensors which were installed along the beams. The results of this article show that changes in shapes of power spectral density caused by damages are much greater than changes in fundamental frequency value of the beams. In other words, the uses of shape changes in power spectral density will increase the possibility to detect damage on different beam structures.

In cellular networks the series of algorithms A5 are used to ensure the communications between the different subscribers of the network. A5/1 is the strong known encryption algorithm which protects the air interface of the mobile network. However, this algorithm sufferer for a lot off problems especially in the clocking mechanism which control the clocking of registers that composes the A5/1 stream cipher. For this raison, several attacks have been published aimed to cryptanalyzing this algorithm such as time memory trade off attacks, guess and determine attacks, biased birthday attack [1] and the random subgraph attack. [2] \nThis paper propose new security enhancements to improve A5/1 encryption algorithm based on new particle swarm optimization (PSO) control mechanism in order to make the A5/1 stream cipher robust and more resistive to some attacks and to be used in future mobile communication systems. \nThe improvements that make both attacks impractical do not change the architecture of the conventional A5/1 and aims to increase the complexity of the A5 algorithm by making its clocking mechanism more complex by the integration of a new function to be optimized by the PSO algorithm which it have been successfully used to solve a wide array of different optimization problems.