Efficient Compositing Methods for the Sort-Last-Sparse Parallel Volume Rendering System on Distributed Memory Multicomputers

In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, one can achieve a very good performance improvement in the rendering phase by increasing the number of processors. This is because each processor can render images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors exceeds a threshold, the image compositing time becomes a bottleneck. In this paper, we propose three compositing methods to efficiently reduce the compositing time in parallel volume rendering. They are the binary-swap with bounding rectangle (BSBR) method, the binary-swap with run-length encoding and static load-balancing (BSLC) method, and the binary-swap with bounding rectangle and run-length encoding (BSBRC) method. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the BSBRC method has the best performance among these four methods.     

Transient temperature responses of hydronic radiant floor heating system by different pipe embedding depth and water supply condition

"Ondol" is a Korean unique heating system. It is a specific radiant floor heating system using combustion heat of briquette or timber in Korea. Such traditional "Ondol" is changed to radiant heating system with pipe-coil embedded in the floor or slab. This study has contributed to the understandings of the transient behaviours of Ondol-heated floor panels and enclosure exposed to this type of heating system. The result is that the water supply temperature had a large effect on the rate of increase in floor surface and room air temperature. But, in spite of a higher water supply temperature, the heat flow rate was not increased considerably. The shallow pipe embedding depths, of course, result in a low heat flow rate.     

Effects of user age and target-expansion methods on target-acquisition tasks using a mouse

Target expansion, i.e., the increase of target size according to cursor movement, can be a practical scheme to improve the usability of target-selection tasks using a mouse. This study examined the effects of different user age groups and target-expansion methods on target-acquisition tasks with grouped icons. Twenty-eight subjects performed acquisition tasks under eight experimental conditions: combinations of four expansion areas (no, one-icon, fish-eye, and group expansion) and two expansion techniques (occlusion and push). Older users took longer to acquire targets than younger users; however, they showed no significant difference in accuracy. Target expansion did not substantially improve performance speed compared to the static condition. However, the error rate was lowest when group area was expanded with the push technique, and both age groups were most satisfied with one-icon area expansion with the occlusion technique. We suggest alternative guidelines in designing target-expansion schemes.     

A novel frequency-offset monitoring technique for direct-detection DPSK systems

We propose and demonstrate a novel technique to monitor the frequency offset between the optical source and delay interferometer (DI) for direct-detection differential phase-shift-keying (DPSK) systems. In this scheme, a phase-modulated tone is applied to DPSK signals at the transmitter and then detected after being converted into an amplitude-modulated tone at the DI to be used for the monitoring signal. Our experimental demonstration shows that the monitoring range and sensitivity of the proposed scheme are measured to be /spl plusmn/2 GHz and /spl sim/10 MHz, respectively, which we believe are good enough to be used either to generate alarm signals for the frequency offset monitoring or to control the feedback loop of the DI.     

Comments on “Quadratic stabilization of continuous timesystems with state-delay and norm-bounded time-varyinguncertainties”

In the above mentioned paper by Mahmoud-Muthairi (ibid. vol.39 (1994)) a sufficient condition for memoryless stabilization of a class of uncertain linear systems with a variable-state delay and norm-bounded time-varying uncertainties is derived in terms of an algebraic Riccati equation. This Riccati equation depends on several free matrix variables, and a subsequent result in the paper, Theorem 2, states that failure or success of the stabilization algorithm is independent of the selection of these matrix variables. In this paper, we give a counterexample to this Theorem 2 as well as providing a fix     

Parallel finding all initial palindromes and periods of a string on reconfigurable meshes

Given a string of lengthn, this short paper first presents anO(1)-time parallel algorithm for finding all initial palindromes and periods of the string on ann×n reconfigurable mesh (RM). Then, under the same cost (= time × the number of processors =O(n ²)), we provide a partitionable strategy when the RM doesn’t offer sufficient processors; this overcomes the hardware limitation and is very suitable for VLSI implementation. Prof. Chung was supported in part by the National Science Council of R. O. C. under contracts NSC87-2213-E011-001 and NSC87-2213-E011-003.     

Application of multi-layer perceptron neural networks to vision problems

This paper discusses the application of a class of feed-forward Artificial Neural Networks (ANNs) known as Multi-Layer Perceptrons(MLPs) to two vision problems: recognition and pose estimation of 3D objects from a single 2D perspective view; and handwritten digit recognition. In both cases, a multi-MLP classification scheme is developed that combines the decisions of several classifiers. These classifiers operate on the same feature set for the 3D recognition problem whereas different feature types are used for the handwritten digit recognition. The backpropagationlearning rule is used to train the MLPs. Application of the MLP architecture to other vision problems is also briefly discussed.     

A game theoretic fault detection filter

The fault detection process is approximated with a disturbance attenuation problem. The solution to this problem, for both linear time-varying and time-invariant systems, leads to a game theoretic filter which bounds the transmission of all exogenous signals except the fault to be detected. In the limit, when the disturbance attenuation bound is brought to zero, a complete transmission block is achieved by embedding the nuisance inputs into an unobservable, invariant subspace. Since this is the same invariant subspace structure seen in some types of detection filters, we can claim that the asymptotic game filter is itself a detection filter. One can also make use of this subspace structure to reduce the order of the limiting game theoretic filter by factoring this invariant subspace out of the state space. The resulting lower dimensional filter will then be sensitive only to the failure to be detected. A pair of examples given at the end of the paper demonstrate the effectiveness of the filter for time-invariant and time-varying problems in both full-order and reduced-order forms     

An evolutionary approach to pattern-based time series segmentation

Time series data, due to their numerical and continuous nature, are difficult to process, analyze, and mine. However, these tasks become easier when the data can be transformed into meaningful symbols. Most recent works on time series only address how to identify a given pattern from a time series and do not consider the problem of identifying a suitable set of time points for segmenting the time series in accordance with a given set of pattern templates (e.g., a set of technical patterns for stock analysis). However, the use of fixed-length segmentation is an oversimplified approach to this problem; hence, a dynamic approach (with high controllability) is preferable so that the time series can be segmented flexibly and effectively according to the needs of the users and the applications. In view of the fact that this segmentation problem is an optimization problem and evolutionary computation is an appropriate tool to solve it, we propose an evolutionary time series segmentation algorithm. This approach allows a sizeable set of pattern templates to be generated for mining or query. In addition, defining similarity between time series (or time series segments) is of fundamental importance in fitness computation. By identifying the perceptually important points directly from the time domain, time series segments and templates of different lengths can be compared and intuitive pattern matching can be carried out in an effective and efficient manner. Encouraging experimental results are reported from tests that segment both artificial time series generated from the combinations of pattern templates and the time series of selected Hong Kong stocks.