Development of a re-configurable ambisonic decoder for irregular loudspeaker configuration

This study reports a heuristic genetic algorithm to determine the decoding parameters in a first-order ambisonic system for reconstructing a three-dimensional sound field with an arbitrary quad speaker configuration. On this basis, a hardware prototype has been developed using a field programmable gate array (FPGA) to decode ambisonic signals that are encoded in the standard B-format. To allow direct coupling with digital audio sources, the input and output channels of the decoder are implemented with the I2S interface. Evaluations reveal that the decoding parameters derived by this method are superior to existing approaches in terms of flexibility in loudspeaker configuration and optimisation of some of the essential factors in surround sound reconstruction.     

Classifying protein sequences using hydropathy blocks

The annotation of proteins can be achieved by classifying the protein of interest into a certain known protein family to induce its functional and structural features. This paper presents a new method for classifying protein sequences based upon the hydropathy blocks occurring in protein sequences. First, a fixed-dimensional feature vector is generated for each protein sequence using the frequency of the hydropathy blocks occurring in the sequence. Then, the support vector machine (SVM) classifier is utilized to classify the protein sequences into the known protein families. The experimental results have shown that the proteins belonging to the same family or subfamily can be identified using features generated from the hydropathy blocks.     

CPE: a parallel library for financial engineering applications

The Clustertech parallel environment is an object-oriented C++ library that uses abstractions to simplify parallel programming for financial engineering applications. The message passing interface ensures CPE's portability and performance over a wide range of parallel cluster and symmetric multiprocessing machines.     

Automatic generation of artistic chinese calligraphy

Chinese calligraphy is among the finest and most important of all Chinese art forms and an inseparable part of Chinese history. Its delicate aesthetic effects are generally considered to be unique among all calligraphic arts. Its subtle power is integral to traditional Chinese painting. A novel intelligent system uses a constraint-based analogous-reasoning process to automatically generate original Chinese calligraphy that meets visually aesthetic requirements. We propose an intelligent system that can automatically create novel, aesthetically appealing Chinese calligraphy from a few training examples of existing calligraphic styles. To demonstrate the proposed methodology's feasibility, we have implemented a prototype system that automatically generates new Chinese calligraphic art from a small training set.     

Fast and Exact Warping of Time Series Using Adaptive Segmental Approximations

Similarity search is a core module of many data analysis tasks, including search by example, classification, and clustering. For time series data, Dynamic Time Warping (DTW) has been proven a very effective similarity measure, since it minimizes the effects of shifting and distortion in time. However, the quadratic cost of DTW computation to the length of the matched sequences makes its direct application on databases of long time series very expensive. We propose a technique that decomposes the sequences into a number of segments and uses cheap approximations thereof to compute fast lower bounds for their warping distances. We present several, progressively tighter bounds, relying on the existence or not of warping constraints. Finally, we develop an index and a multi-step technique that uses the proposed bounds and performs two levels of filtering to efficiently process similarity queries. A thorough experimental study suggests that our method consistently outperforms state-of-the-art methods for DTW similarity search.     

BLOSSOMS: Building Lightweight Optimized Sensor Systems on a Massive Scale

As a joint effort between the Chinese Academy of Sciences and the Hong Kong University of Science and Technology, the BLOSSOMS sensor network project aims to identify research issues at all levels from practical applications down to the design of sensor nodes. In this project, a heterogeneous sensor array including different types of application-dependent sensors as well as monitoring sensors and intruding sensors are being developed. Application-dependent power-aware communication protocols are also being studied for communications among sensor nodes. An ontology-based middleware is built to relieve the burden of application developers from collecting, classifying and processing messy sensing contexts. This project is also developing a set of tools allowing researchers to model, simulate/emulate, analyze, and monitor various functions of sensor networks.     

A topological hierarchy-based approach to toolpath planning for multi-material layered manufacturing

This paper proposes a topological hierarchy-based approach to toolpath planning for multi-material layered manufacturing (MMLM) of heterogeneous prototypes. The approach facilitates control of MMLM and increases the fabrication efficiency of complex objects by generating multi-toolpaths that avoid redundant tool movements and potential collisions. It uses a topological hierarchy-sorting algorithm to group complex multi-material slice contours into families connected by a parent-and-child relationship. Subsequently, a sequential toolpath planning algorithm generates multi-toolpaths for sequential deposition of materials without redundant tool movements. To reduce build time further, a concurrent toolpath planning algorithm generates collision-free multi-toolpaths to control the tools that deposit materials concurrently. It uses parametric polygons to construct tool envelopes for contour families of the same material property to simplify detection of tool collisions. The tightness of polygons can be controlled to suit the processing speed and the optimality of the resulting concurrent toolpaths. The proposed approach has been implemented as an integral part of a multi-material virtual prototyping (MMVP) system that can process complex slice contours for planning, stereoscopic simulation, and validation of multi-toolpaths. It may be adapted for subsequent control of MMLM processes.     

Automated test case generation for the stress testing of multimedia systems

With the advancement in network bandwidth and computing power, multimedia systems have become a popular means for information delivery. However, general principles of system testing cannot be directly applied to testing of multimedia systems on account of their stringent temporal and synchronization requirements. In particular, few studies have been made on the stress testing of multimedia systems with respect to their temporal requirements under resource saturation. Stress testing is important because erroneous behavior is most likely to occur under resource saturation. This paper presents an automatable method of test case generation for the stress testing of multimedia systems. It adapts constraint solving techniques to generate test cases that lead to potential resource saturation in a multimedia system. Coverage of the test cases is defined upon the reachability graph of a multimedia system. The proposed stress testing technique is supported by tools and has been successfully applied to a real‐life commercial multimedia system. Although our technique focuses on the stress testing of multimedia systems, the underlying issues and concepts are applicable to other types of real‐time systems. Copyright © 2002 John Wiley & Sons, Ltd.     

Effect of data skewness and workload balance in parallel datamining

To mine association rules efficiently, we have developed a new parallel mining algorithm FPM on a distributed share-nothing parallel system in which data are partitioned across the processors. FPM is an enhancement of the FDM algorithm, which we previously proposed for distributed mining of association rules (Cheung et al., 1996). FPM requires fewer rounds of message exchanges than FDM and, hence, has a better response time in a parallel environment. The algorithm has been experimentally found to outperform CD, a representative parallel algorithm for the same goal (Agrawal and Srikant, 1994). The efficiency of FPM is attributed to the incorporation of two powerful candidate sets pruning techniques: distributed and global prunings. The two techniques are sensitive to two data distribution characteristics, data skewness, and workload balance. Metrics based on entropy are proposed for these two characteristics. The prunings are very effective when both the skewness and balance are high. In order to increase the efficiency of FPM, we have developed methods to partition a database so that the resulting partitions have high balance and skewness. Experiments have shown empirically that our partitioning algorithms can achieve these aims very well, in particular, the results are consistently better than a random partitioning. Moreover, the partitioning algorithms incur little overhead. So, using our partitioning algorithms and FPM together, we can mine association rules from a database efficiently