Applied Mechanics and Materials Vols. 490-491

Abstract: Based on aerodynamics, this paper discussed the shock wave traits of ultrasonic bullet and studied the methods to calculate the position coordinate and ballistic trajectory vector in free sound field. Through experiments, the signals of shock wave from firing point and ballistic trajectory were decomposed and reconstructed, making use of wavelets analysis. The characteristic parameters were extracted to position the sound source and orientate the trajectory, based on the sensors array of right tetrahedron.

Abstract: The efficiency of service of Underwater Acoustic Networks is restricted by the acoustic channel characteristic, such as the low bandwidth , high varying multipath and elevated noise levels. In addition, the lifetime of Underwater Acoustic Networks is influenced greatly by the limited battery power. This paper designs an Underwater Acoustic Networks and poses the data link layer protocols including the logical link control protocol and the media access control protocol. The simulation results have demonstrated that the protocols are of certain applicability in underwater acoustic channel environment that maximize throughput and reliability while minimizing end-to-end delay. In the event of low offered load, the protocol can satisfy the requirment of Underwater Acoustic Networks.

Abstract: Relational top-N queries with both text attributes and numeric attributes are useful in many applications, by using the ranking functions based on both semantic distances for text attributes and numeric distances for numeric attributes. In this paper, we propose an approach for processing such type of top-N queries in relational databases. The basic idea of the approach is to create an index based on WordNet to expand the tuple words semantically for text attributes and on the related information of numeric attributes, meanwhile the size of the index increases linearly with the size of the database. The results of extensive experiments show that our method is efficient and effective.

Abstract: For the traditional data cleaning algorithms mainly fill up the data based on the space-time relevance in the data level, they are not suitable for RFID application scenarios with track information based on multi-logical areas. This paper proposed a track data filling algorithm based on movement recency by studying the characteristics of RFID track data. This algorithm maintains a track event tree according to the historical data, to predict the future data and guide the data cleaning. Also it considers the effect on the movement rules from time factor and brings in the ageing factor for maintaining the track event tree, which improved the predict accuracy of the tree and raise the veracity of the filling algorithm.

Abstract: This paper is concerned with face recognition using the hidden Markov model with 2D-discrete cosine transformation observations. The first part of the paper mainly discusses the influence of sampling parameter selection on model training and recognition efficiency and proposes method to increases the model efficiency through selecting optimal combinations of input parameters. In the second part of the paper, we choose the optimal parameters as input data standard for image matching and extend Viterbi algorithm by setting thresholds, the recognition time is reduced by 12.4% on average.

Abstract: Replication in distributed database is the process of copying and maintaining database objects in multiple databases that make up a distributed database system. In this paper, we will manage fragmented database replication and transaction management for Malaysian Greater Research Network (MyGRANTS) using a new proposed algorithm called Binary Vote Assignment on Cloud Quorum (BVACQ). This technique will combine replication and fragmentation. Fragmentation in distributed database is very useful in terms of usage, efficiency, parallelism and also for security. This strategy will partition the database into disjoint fragments. The result shows that managing replication and transaction through proposed BVACQ able to preserve data consistency. It also increases the degrees of parallelism. This is because by using fragmentation, replication and transaction can be divided into several subqueries that operate on the fragments.

Abstract: Lightweight speaker-dependent (SD) automatic speech recognition (ASR) is a promising solution for the problems of possibility of disclosing personal privacy and difficulty of obtaining training material for many seldom used English words and (often non-English) names. Dynamic time warping (DTW) algorithm is the state-of-the-art algorithm for small foot-print SD ASR applications, which have limited storage space and small vocabulary. In our previous work, we have successfully developed two fast and accurate DTW variations for clean speech data. However, speech recognition in adverse conditions is still a big challenge. In order to improve recognition accuracy in noisy and bad recording conditions, such as too high or low recording volume, we introduce a novel weighted DTW method. This method defines a feature index for each time frame of training data, and then applies it to the core DTW process to tune the final alignment score. With extensive experiments on one representative SD dataset of three speakers' recordings, our method achieves better accuracy than DTW, where 0.5% relative reduction of error rate (RRER) on clean speech data and 7.5% RRER on noisy and bad recording speech data. To the best of our knowledge, our new weighted DTW is the first weighted DTW method specially designed for speech data in noisy and bad recording conditions.

Abstract: The wavelet packet transform is a new time-frequency analysis method, and is superior to the traditional wavelet transform and Fourier transform, which can finely do time-frequency dividion on seismic data. A series of simulation experiments on analog seismic signals wavelet packet decomposition and reconstruction at different scales were done by combining different noisy seismic signals, in order to achieve noise removal at optimal wavelet decomposition scale. Simulation results and real data experiments showed that the wavelet packet transform method can effectively remove the noise in seismic signals and retain the valid signals, wavelet packet transform denoising is very effective.

Abstract: With the advent of location-based social media and locationacquisition technologies, trajectory data are becoming more and more ubiquitous in the real world. A lot of data mining algorithms have been successfully applied to trajectory data sets. Trajectory pattern mining has received a lot of attention in recent years. In this paper, we review the most inuential methods as well as typical applications within the context of trajectory pattern mining.

Abstract: During the authentication process of web-based single sign-on system, it is insecure that all authentication messages are forwarded by the browser, and its integrity protection is not comprehensive. This vulnerability can be exploited by attackers to bypass the authentication systems, login any account. In this work we analyze the vulnerability threat model and its root causes in detail, and propose an authentication algorithm based on Hash-tree. This algorithm can not only improve the security of the system, but the processing efficiency of the system is also acceptable according to the simulation results.