Decision supporting functionality in a virtual enterprise network

Enterprises are now facing growing global competition and the continual success in the marketplace depends very much on how efficient and effective the companies are able to respond to customer demands. The Internet has provided a powerful tool to link up manufacturers, suppliers and consumers to facilitate the bi-directional interchange of useful information. The formation of virtual enterprise network is gathering momentum to meet this challenge. The idea of virtual enterprise network is meant to establish a dynamic organization by the synergetic combination of dissimilar companies with different core competencies, thereby forming a “best of everything” consortium to perform a given business project to achieve maximum degree of customer satisfaction. In this emerging business model of virtual enterprise network, the decision support functionality, which addresses the issues such as selection of business partners, coordination in the distribution of production processes and the prediction of production problems, is an important domain to be studied. This paper attempts to introduce a Neural On-Line Analytical Processing System (NOLAPS), which is able to contribute to the creation of decision support functionality in a virtual enterprise network. NOLAPS is equipped with two main technologies for achieving various objectives, including neural network for extrapolating probable outcomes based on available pattern of events and data mining for converting complex data into useful corporate information. A case example is also covered to validate the feasibility of the adoption of NOLAPS in real industrial situations.     

Towards geometrically robust data-hiding with structured codebooks

In this paper we analyze performance of practical robust data-hiding in channels with geometrical transformations. By applying information-theoretic argument we show that performance of a system designed based on both random coding and random binning principles is bounded by the same maximal achievable rate for the cases when communication channel includes geometrical transformations or not. Targeting to provide theoretic performance limits of practical robust data-hiding we model it using a multiple access channel (MAC) with side information (SI) available at one of encoders and present the bounds on achievable rates of reliable communications to such a protocol. Finally, considering template-based and redundant-based design of geometrically robust data-hiding systems, we perform security analysis of their performance and present results in terms of number of trial efforts the attacker needs to completely remove hidden information.     

A Speech Recognition IC Using Hidden Markov Models with Continuous Observation Densities

This paper presents the design of a speech recognition IC using hidden Markov models (HMMs) with continuous observation densities. Results of offline and live recognition tests are also given. Our design employs a table look-up method to simplify the computation and hence the architecture of the circuit. Currently each state of the HMMs is represented by a double-mixture Gaussian distribution. With minor modifications, the proposed architecture can be extended to implement a recognizer in which models with higher order multi-mixture Gaussian distribution are used for more precise acoustic modeling. The test chip is fabricated with a 0.35 μm CMOS technology. The maximum operating frequency is 62.5 MHz at 3.3 V. For a 50-word vocabulary, the estimated recognition time is about 0.16 s. Using noise-corrupted utterances, the recognition accuracy is 93.8% for isolated English digits. Such a performance is comparable to the software implementation with the same algorithm. Live recognition test was also run for a vocabulary of 11 Chinese words. The accuracy is 91.8% for five male and five female speakers.

Vernier parallel delay-line based time-to-digital converter

This letter proposes a new parallel delay-line time-to-digital converter (TDC) architecture based on the Vernier principle. Two parallel delay-line stages with slightly different incremental step sizes are cascaded, resulting in a finer resolution compared to the traditional parallel delay line. A 2-bit TDC fabricated in a 0.18 μm CMOS technology demonstrates the principle with a time resolution of 2.5 ps and a differential nonlinearity of 0.13 LSB.     

Numerical analysis of optical amplification in Er/sup 3+/-Yb/sup 3+/ codoped Ti:LiNbO/sub 3/ strip waveguides

Optical amplification at 1530 nm in 980-nm pumped Er/sup 3+/-Yb/sup 3+/-diffused Ti:LiNbO/sub 3/ strip waveguides was numerically analyzed on the basis of rate equation model of Er/sup 3+/-Yb/sup 3+/ system and pump/signal power propagation equations. The model includes total eight energy levels of the Er/sup 3+/-Yb/sup 3+/ system and simultaneously takes into account the excited state absorption (ESA) and upconversion processes within the Er/sup 3+/ ions as well as possible energy transfer processes between Yb/sup 3+/ and Er/sup 3+/ ions. A comparison of numerical results from the eight-level model and highly simplified five-level model has indicated that the /sup 4/S/sub 3/2/ manifold of Er /sup 3+/ ion must be included in the rate equation model. Dependences of threshold pump power and amplification gain on pump power (for gain only), Yb/sup 3+/ surface concentration and waveguide length were calculated and discussed. The characteristics of pump power evolution along the waveguide axis and population density distribution, as well as the influences of energy transfer coefficient from Yb/sup 3+/ to Er/sup 3+/, 550-nm (Er/sup 3+/), and 1060-nm (Yb/sup 3+/) fluorescence lifetime and above-mentioned detrimental processes including ESA, upconversion, and cross-relaxation processes on numerical result were studied. The role of Yb/sup 3+/ is demonstrated. A novel design idea that Yb/sup 3+/ is only incorporated at the end of the waveguide is proposed.     

Design considerations of calibration DAC in self-calibrated SAR A/D converters

A capacitive calibration digital-to-analog converter (CDAC) is commonly used to reduce the mismatch-induced linearity errors for successive approximation register (SAR) analog-to-digital converters (ADC) employing capacitor arrays. There are complicated design considerations in determining the number of bits, the unit capacitor value and even the parasitic capacitors of the CDAC, as these factors affect or are determined by the achievable ADC resolution, the main DAC's capacitance, and the main DAC unit capacitance value, etc. This paper is the first to present a systematic analysis on these relationships. The analysis is validated by behavioral and circuit simulation results.     

A 75-dB image rejection IF-input quadrature-sampling SC /spl Sigma//spl Delta/ Modulator

Quadrature sampling of intermediate frequency (IF) signals is subject to the well-known problem of gain and phase mismatches between the in-phase (I) and quadrature (Q) channels. This paper presents an IF-input quadrature-sampling switched-capacitor (SC) /spl Sigma//spl Delta/ modulator that circumvents the I/Q mismatch problem by time-sharing between the I and Q channels the critical circuit components, namely, the sampling capacitor and the capacitor of the first-stage feedback digital-to-analog converter (DAC). In addition, a clocking scheme that is insensitive to I/Q phase imbalance is used. A third-order single-loop 1-bit low-pass modulator has been designed and fabricated in a 0.35-/spl mu/m CMOS process with an active area of 0.57mm/sup 2/. The experimental results show that the modulator achieves an image-rejection ratio (IRR) of greater than 75dB throughout a 200-kHz signal bandwidth.     

Rotation-invariant texture classification using a two-stage waveletpacket feature approach

A novel two-stage wavelet packet feature approach for classification of rotated textured images is discussed. In the first stage, a set of sorted and dominant wavelet packet features is extracted from a texture image and a Mahalanobis distance classifier is employed to output N best classes. In the second stage, another set of wavelet packet features is extracted from the polarised form of the sample texture image and the most dominant wavelet packet features are selected and passed to the radial basis function (RBF) classifier with the N best classes to output the final matched class. Experimental results, based on a large sample data set of twenty distinct natural textures selected from the Brodatz album with different orientations, show that the proposed method outperforms the similar wavelet methods and the other rotation invariant texture classification schemes, and an overall accuracy rate of 91.4% was achieved     

Design and evaluation of data allocation algorithms for distributedmultimedia database systems

A major cost in retrieving multimedia data from multiple sites is the cost incurred in transferring multimedia data objects (MDOs) from different sites to the site where the query is initiated. The objective of a data allocation algorithm is to locate the MDOs at different sites so as to minimize the total data transfer cost incurred in executing a given set of queries. The optimal allocation of MDOs depends on the query execution strategy employed by a distributed multimedia system while the query execution strategy optimizes a query based on this allocation. We fix the query execution strategy and develop a site-independent MDO dependency graph representation to model the dependencies among the MDOs accessed by a query. Given the MDO dependency graphs as well as the set of multimedia database sites, data transfer costs between the sites, the allocation limit on the number of MDOs that can be allocated at a site, and the query execution frequencies from the sites, an allocation scheme is generated. We formulate the data allocation problem as an optimization problem. We solve this problem with a number of techniques that broadly belong to three classes: max-flow min-cut, state-space search, and graph partitioning heuristics. The max-flow min-cut technique formulates the data allocation problem as a network-flow problem, and uses a hill-climbing approach to try to find the optimal solution. For the state-space search approach, the problem is solved using a best-first search algorithm. The graph partitioning approach uses two clustering heuristics, the agglomerative clustering and divisive clustering. We evaluate and compare these approaches, and assess their cost-performance trade-offs. All algorithms are also compared with optimal solutions obtained through exhaustive search. Conclusions are also made on the suitability of these approaches to different scenarios     

Information frameworks for conceptual engineering design

An information modeling approach is used to gain an understanding of the information and decision content of conceptual engineering design. Information frameworks are presented that attempt to represent the key decisions made during conceptual design. Elements of the frameworks are derived from results from design theory and methodology and decision theory. Using a number of products, the frameworks are demonstrated in simulated design situations. The models provide an explicit, generic and consistent perspective for identifying the information content of conceptual designs.