Applied Mechanics and Materials Vols. 764-765

Abstract: In this paper, we propose a three-dimensional (3D) image encryption method using the computer-generated integral imaging and random phase mask encoding. The advantages of this proposed method can not only increase the resolution of the reconstructed plane images, but also greatly improve the robustness compared with conventional methods. We present the experimental results to verify the performance of our proposed encryption method.

Abstract: The stochastic Markov model is combined with fuzzy set concept and grey system for improving forecasting performance. The data for model test is obtained from ACI including Hong Kong, Beijing, Taoyuan, Incheon and Narita international airport. The empirical results show that fuzzy Markov model has better predictive performance with the data with trend and intercept. For the data with random walk, grey Markov model performs better. The paper also examines the effects of transition state and length of interval on the forecasting performance with the result. Keywords: Markov model, Grey Markov model, Air cargo flow, ARIMA, MAPE.

Abstract: Many software reliability growth models (SRGMs) have been developed to estimate some useful measures such as the mean value function, number of remaining faults, and failure detection rate. Most of these models have focused on the failure detection process and not given equal priority to modeling the fault correction process. But, most latent software errors may remain uncorrected for a long time even after they are detected, which increases their impact. The remaining software faults are often one of the most unreliable reasons for software quality. Therefore, we develop a general framework of the modeling of the failure detection and fault correction processes. Furthermore, it is assumed that a detected fault is immediately removed and is perfectly repaired with no new faults being introduced for the traditional SRGMs. In reality, it is impossible to remove all faults from the fault correction process and have a fault-free effect on the software development environment. In order to relax this perfect debugging assumption, we introduce the possibility of imperfect debugging phenomenon. Finally, numerical examples are shown to illustrate the results of the unified approach for integration of the detection and correction process under imperfect debugging.

Abstract: Information systems are being used for more and more applications are becoming more complicated and expensive, while at the same hand today’s software systems demand increasing tremendously for sophisticated software engineering processes. There are many ways to solve a single problem in software development. Sometimes, in Structural engineering, developer is not able to decide which process will suit to that particular problem or in other words we can say that selecting a good process is a big issue in Structural Process Software engineering. The solution of such kind of problem can be found in the work to be done, and the task to be performed by the Operational process rather than structure of a process. This paper introduces the notion of process operationality and proposes ‘process architecture’ to represent this operationality. Thus, Structural Process Engineering (SPE) becomes Operational Process Engineering (OPE).

Abstract: An intrusion is a series of relevant actions that occur to a victim in some sequence through the Internet. In this paper, a serial episode mining is first applied to find all possible sophisticated Internet attacks, and then an episode pruning skill is applied to cut unnecessary ones to reduce administrator’s further effort. Input data, log files from a honeypot system, is regarded as a sequence of events, where each event has an associated time of occurrence. The method proposed in this paper can be used to detect abnormal Internet episodes including unknown attacks. Some experiments had been conducted to show the effectiveness of the proposed method.

Abstract: In this paper, we propose a video image encryption approach by using maximum length cellular automata (MLCA) methods. First, the plane images of video of the encryption method are obtained by dividing frame units. Then the XOR operation and Arnold transform are applied to each of RGB plane images. Lastly, the encryption image is encrypted by the basis image of MLCA. To demonstrate the usefulness of the proposed method, we carry out preliminary experiments and present the experimental results. The experimental results show that the proposed method provides high security.

Abstract: In this paper, we represent approaches for detecting users’ POIs and identifying personal routes based on temporal smartphone sensor data, including GPS. POIs and routes of users are factors that affect prediction of a traveling route. However, recording user destinations and the routes of training data is almost impossible when building a route model. Thus, we propose algorithms that automatically extract the points of destinations and routes using GPS.

Abstract: This paper describes a method for inferring user destinations and routes based on logs collected by smartphones. A challenging problem is coping with the uncertainty of smartphone sensor data. In this study, we represent a user transportation model with probabilistic models based on temporal smartphone sensor data, including GPS and accelerometer data. In our model, the travel behavior and spatio-temporal information of users are factors that affect route decisions. We propose hierarchical particle filters to enhance the performance and efficiency by sampling the route model based on hierarchical and semantic relationships.

Abstract: Instrumentation technology has been widely used in debugging interactive applications, such as interactive games and virtual reality. Debug codes are instrumented into a target program in order to collect run-time information. Although instrumentation provides detail information of the target program behavior, it can significantly prolong execution time, change program behavior and lead to incorrect debugging results, especially for time dependent and real-time applications. This paper aims to design a scalable parallel debugging mechanism to reduce instrumentation overhead while collecting detail run-time information. We design a new synchronization mechanism of instrumentation, named MDM, which uses multiple buffers to process debug messages. Also, a binding mechanism is used to specify the relationship between the target program, helper threads and cores. We conduct a case study of augmented reality interactive games on an Intel Core i7-2600 processor with Linux 2.6.38. Compared to existing methods, MDM can reduce instrumentation overhead by up to 19%.

Abstract: A new method using an incomplete measurement set to locate and identify structural damage is proposed. The method is iterative yet computationally efficient and requires no sensitivity calculations. Mass and stiffness matrices, established by finite element method, are partitioned and measured partial eigenvectors are expanded to full modes. Stiffness reduction coefficients for structural elements are defined and then solved by a nonnegative least-squares solution scheme. With much less measured degrees of freedom and even less measured modes than the finite element analysis degrees of freedom, the proposed approach can still identify the damaged locations and extent of the damage in a structure. The effectiveness of the method is demonstrated by solving a numerically simulated example on the GARTEUR SM-AG19 structure.