Advanced Materials Research Vols. 403-408

Abstract: In-flight shutdown (IFSD) of civil aviation engine can result in catastrophic accident and has been attracting more and more attention. This paper presents a new solution, which based on Bayesian Networks, to diagnose IFSD. Fleet data of china occurred in last twelve years was used to establish the network with four layers. After designating the conditional probability between two nodes which were located on the adjacent layers, it can be obtained that to what extent one factor can lead to IFSD. At last, the verification was given to prove that this solution is useful to diagnose IFSD.

Abstract: The sensing capabilities of sensor nodes are affected by various factors in the actual environment, and the ideal disk sensing model is not available in the practical sensor network. In this paper, we proposed an Energy-balance Coverage Algorithm based on Probability (ECAP). The algorithm applies to a limited target point monitoring issues, using the heuristic greedy strategy. The nodes that have a larger detecting probability and higher energy are selected to construct a coverage set. It improves energy efficiency, and extends the lifetime of sensor networks. Experiments also show that the algorithm has high stability.

Abstract: Basic carbonate monospheres of various lanthanide combinations are successfully synthesized by the urea-based homogeneous precipitation technique, which are then converted into well dispersed phosphor particles that emit diverse colours. Sequential precipitation is commonly observed for these mixed cation systems, calling for adequate annealing of the basic carbonate precursors to attain cation homogenization in the final oxide particles and thus better luminescence, through eliminating localized concentration quenching of luminescence. It is shown that, owing to their excellent dispersion and uniform size, the phosphor spheres are readily assembled into close-packed luminescent films, allowing their wide applications in white LEDs, plasma display panels (PDPs), and field emission displays (FEDs).

Abstract: This paper used multivariate analysis of variance (MANOVA) method to investigate whether changes in the independent variables such as gender, age, family location etc, have significant effects on the dependent variables. Date was collected from students in Hebei University of Technology, by using Chinese College Student Mental Health Scale (CCSMHS). Result shows that interaction from four factors such as interactions among gender, only-child, major and family location have significant influence on anxiety. Different family locations also affect some dimensions. Mental health of students grow in large cities is significantly better than those from small and medium-sized cities, small towns and rural.

Abstract: This article provides an overview about the microbes selecting, types of bioreactors, the treatment condition, etc. which influence the odors abatement effect. In the recent past, many highly efficiency microorganisms on the actual governance of malodorous gases have been selected and trained. Among different bioreactor configurations, biofilters, biotrickling filters and bioscrubbers are most common ones. The membrane bioreactor and the three phase fluidised bed bioreactor as new bioreactors have broad development prospects. Finally, this review also provides how to insights into future R&D needs in this area.

Abstract: A real-time application is proposed for Android smart phone. To achieve the best tradeoff between the complexity and the processing efficiency, Java Native Interface (JNI) is used rather than pure Java. The performance of the application is tested on an Android smart phone by dealing with various pedestrian videos. And the experimental results show that the application successfully detects and tracks certain moving object.

Abstract: Node self-positioning is one of the core technologies in wireless sensor networks and is the premise of many applications. It is significant to achieve highly efficient and reliable node localization for event observation, target tracking and efficient routing. The DV-Hop localization algorithm which is one of the Range-Free algorithms is researched deeply. Firstly, algorithmic process, error sources, and the amount of communication and computing for Traditional DV-Hop algorithm are analyzed. For low positioning accuracy in Conventional DV-Hop localization algorithm, an improved DV-Hop localization algorithm based on estimate of average hop distance, Min-Max and position correction is brought forward. The simulation results show that the improved algorithm can improve the positioning accuracy more effectively without increasing hardware consumption in nodes comparing with conventional DV-Hop algorithm. So it is a practical and effective node localization method in wireless sensor networks.

Abstract: Mobile learning is a new way of application of mobile communications technology. As a new way of learning mode and technology it must be pay much attention. It is severely affected by network technology. Cloud computing, a new computing model, is proposed based on a distributed system, grid computing, etc. It is a new way of sharing infrastructure. Cloud computing will develop a new environment of learning space, information sharing, collaboration and learning to the field of education. This article explores the impact of Cloud computing to mobile learning from several factors of the mobile learning environment.

Abstract: The paper proposes a real-time monocular vision-based algorithm that can be applied to robot tracking. Unlike the models used in other papers, the model used in this paper is suitable for the condition that the camera is looking up. There is a common deficiency existing in previous models that the target point is constrained to some areas of the camera field. To overcome the shortcomings, the camera field of view is divided into three regions which also reduces the computational complexity. The intrinsic parameters of camera can be obtained by calibration. Pitch angle rectification, together with camera calibration, improves the ranging accuracy.

Abstract: The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning sequence helps to strengthen the knowledge reserve of the classifier. This article proposes an incremental learning algorithm based on the K-Nearest Neighbor. Through calculating k maximum similar distance between test set and training set ,dividing and structuring the sequence of class number and the sequence of sum of class weight. According to the undulation degree of sequence, the instance including stronger class information is chosen to enter the learning process firstly. The experimental result indicates that the algorithm is effective and feasible.