A schedule for a parallel program is said to be 1-fault-secure if a system that uses the schedule can either produce correct output for the program or detect the presence of any faults in a single processor. Although several fault-secure scheduling algorithms have been proposed, they can all only be applied to a class of tree-structured task graphs with a uniform computation cost. Besides, they assume a stringent error model, called the redeemable error model, that considers extremely unlikely cases. In this paper, we first propose two new plausible error models which restrict the manner of error propagation. Then we present three fault-secure scheduling algorithms, one for each of the three models. Unlike previous algorithms, the proposed algorithms can deal with any task graphs with arbitrary computation and communication costs. Through experiments, we evaluate these algorithms and study the impact of the error models on the lengths of fault-secure schedules.

Many experimentally and theoretically based models have been proposed to predict, quantitatively evaluate, and combat the fading phenomenon in mobile communication systems. However, to the best of the authors' knowledge, up to now there is no objective method to determine which is the most suitable distribution to model the fading phenomenon based on experimental data. In this work, the Minimum Description Length (MDL) criterion for model selection is proposed for that purpose. Furthermore, the MDL analysis is performed for some of the most widely used fading models based on measurements taken in a sub-urban environment.

This paper proposes a statistical method to estimate the optimal software release time which minimizes the expected total software cost incurred in both testing and operation phases. It is shown that the underlying cost minimization problem can be reduced to a graphical one. This implies that the software release problem under consideration is essentially equivalent to a time series forecasting for the software fault-occurrence time data. In order to predict the future fault-occurrence time, we apply three extraordinary auto-regressive models by Singpurwalla and Soyer (1985) as the prediction devices as well as the well-known AR and ARIMA models. Numerical examples are devoted to illustrate the predictive performance for the proposed method. We compare it with the classical exponential software reliability growth model based on the non-homogeneous Poisson process, using actual software fault-occurrence time data.

The maximum likelihood estimate of a mixture model is usually found by using the EM algorithm. However, the EM algorithm suffers from a local optima problem and therefore we cannot obtain the potential performance of mixture models in practice. In the case of mixture models, local maxima often have too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations we proposed a new variant of the EM algorithm in which simultaneous split and merge operations are repeatedly performed by using a new criterion for efficiently selecting the split and merge candidates. We apply the proposed algorithm to the training of Gaussian mixtures and the dimensionality reduction based on a mixture of factor analyzers using synthetic and real data and show that the proposed algorithm can markedly improve the ML estimates.

This paper considers two simulation models for simple unreliable file systems with checkpointing and rollback recovery. In Model 1, the checkpoint is generated at a pre-specified time and the information on the main memory since the last checkpoint is back-uped in a secondary medium. On the other hand, in Model 2, the checkpointing is executed at the time when the number of transactions completed for processing is achieved at a pre-determined level. However, it is difficult to treat such models analytically without employing any approximation method, if queueing effects related with arrival and processing of transactions can not be ignored. We apply the generalized stochastic Petri net (GSPN) to represent the stochastic behaviour of systems under two checkpointing schemes. Throughout GSPN simulation, we evaluate quantitatively the maintainability of checkpoint models under consideration and examine the dependence of model parameters in the optimal checkpoint policies and their associated system availabilities.

Predicting the performance of high speed wide area ATM networks (WANs) is a difficult task. Evaluating the performance of these systems by means of mathematical models is not yet feasible. As a result, the creation of simulation models is usually the only means of predicting and evaluating the performance of such systems. In this paper, we use measurements to validate simulation models of TCP/IP over high speed ATM wide area networks. Validation of simulations with measurements is not common; however, it is needed so that simulation models can be used with confidence to accurately characterize the performance of ATM WANs. In addition, the appropriate level of complexity of the simulation models needs to be determined. The results show that under appropriate conditions simulation models can accurately predict the performance of complex high speed ATM wide area networks. This work also shows that the user perceived performance is dependent on host processing demands.

Modern database systems have to support complex data objects, which appear in advanced data models such as object-oriented data models and nested relational data models. Set-valued objects are basic constructs to build complex structures in those models. Therefore, efficient processing of set-valued object retrieval (simply, set retrieval) is an important feature required of advanced database systems. Our previous work proposed a basic scheme to apply superimposed coded signature files to set retrieval and showed its potential advantages over the B-tree index based approach using a performance analysis model. Retrieval with signature files is always accompanied by mismatches called false drops, and proper control of the false drops is indispensable in the signature file design. This study intensively analyzes the false drops in set retrieval with signature files. First, schemes to use signature files are presented to process set retrieval involving "has-subset," "is-subset," "has-intersection," and "is-equal" predicates, and generic formulas estimating the false drops are derived. Then, three sets of concrete formulas are derived in three ways to estimate the false drops in the four types of set retrieval. Finally, their estimates are validated with computer simulations, and advantages and disadvantages of each set of the false drop estimation formulas are discussed. The analysis shows that proper choice of estimation formulas gives quite accurate estimates of the false drops in set retrieval with signature files.

Physical models for fully depleted (FD) and non-fully depleted (NFD) SOI MOSFETs are overviewed, and recent applications of them (in SOISPICE) are described, stressing the need for good physics-based accounting for the inherently coupled bipolar and MOS device features in reliable circuit design. The applications suggest that asymmetrical double-gate FD/SOI CMOS technology can be scaled below 0.1 µm, whereas the single-gate counterpart seemingly cannot be, and that the floating-body charge dynamics and the associated transient leakage current in NFD/SOI (and FD/SOI) pass transistors in memory (DRAM and SRAM) circuits can be effectively controlled by optimal device design.

For two decades, our colleagues and we have been developing our multiple learning environments in mathematical education for upper secondary school learners, and have been reporting our learner-centered system in the latest four WCCE Conferences (WCCE/1981/1985/1990/1995). In our latest learning multimedia system, individual learners have to meet a complex network structure in which objectives are arranged in the form of non-linear linking and to proceed actively to their own goals. In order to support their exploring learning, we developed several instructional navigation tools from an instructional view point. This paper presents our instructional navigation technology and its tools. The feature of our present system is to provide a supportive environment where individual learners can set up their own goals, create their own paths for their goals through instructional materials, and construct their own instructional structure based on instructional strategies. This feature is remarkably different from a traditional CAI system in which learners are only directed through the courseware via a linear selection of menus. Also this feature fundamentally differs from general navigation technologies by which a user is able to traverse a series of nodes among non-linear network structure, because our navigation must present individual learners with some easily learnable sequences of objectives based on their object and interest. For this purpose, this system has three chracteristic technologies, i.e. focusing, sequencing and clustering ones. These are very useful for them to make their decisions in order to reach their own goals. This paper consists of (1) ideas of instructional navigation, (2) map technology and (3) navigation technology.

The Virtual Path (VP) concept is one of the versatile features of ATM/B-ISDN. Using the VP concept, a bundle of virtual circuits can be grouped together between any two switching nodes in the network. Further, the VP bandwidth and routing can be dynamic. Building on this idea, a dynamically reconfigurable, dynamic call routing wide area (backbone) broadband network concept is proposed. Specifically, this provides dynamism at two levels: at the VP level and at the connection level. For an incoming connection request, at most two logical virtual path connections (VPCs) are allowed between the origin and the destination; these logical VPCs are defined by setting virtual paths links (VPLs) which are, in turn, physically mapped to the transmission network. Based on the traffic pattern during the day, the bandwidth of such VPCs and their routing, as well as call routing, changes so that the maximum number of connection requests can be granted while maintaining acceptable quality of service (QoS) for various services. Within this framework, we present a mathematical model for network design (dimensioning) taking into account the variation of traffic during the day in a heterogeneous multi-service environment. We present computational results for various cost parameter values to show the effectiveness of such networks compared to static-VP based networks in terms of network cost.

For two devices whose quality is described by non-negative one-dimensional time-homogeneous diffusion processes of the Wiener and Ornstein-Uhlenbeck types sufficient conditions are given such that their failure times, modeled as first-passage times through the zero state, are ordered according to the likelihood ratio ordering.

We develop a simulation environment for designing and examining a neural network model at the network level. The aim of our research is to enable researchers investigating neural network connective models to save time by being equipped with a graphical user interface and database of the network models. This environment consists of three parts: (1) the kernel of the simulation system, (2) NNDBMS (Neural Networks DataBase Management System), and (3) a system for displaying simulation results in various ways.

This paper proposes a hierarchical parallel processing system for the multipass rendering method. The multipass rendering method based on the integration of radiosity and ray-tracing can synthesize photo-realistic images. However, the method is also computationally expensive. To accelerate the multipass rendering method, the system, called (Mπ)2, employs two kinds of parallel processing schemes. As a coarse-grain parallel processing, object-space parallel processing with multiple processing elements based on the object-space subdivision is adapted, and each processing element (PE) is equipped with multiple pipelined units for a fine-grain parallel processing. To balance load among the system, static load balancing at the PE level and dynamic load balancing at the pipelined unit level within the PE are introduced. Especially, we propose a novel static load allocation scheme, skewed-distributed allocation, which can effectively distribute a three-dimensional object space to one- or two-dimensional processor configuration of the (Mπ)2 system. Simulation experiments show that the two-dimensional (Mπ)2 systems with the skewed-distributed allocation outperform the three-dimensional systems with the non-skewed distributed allocation. Since lower dimensional systems can be built at a lower cost than higher dimensional systems, the skewed-distributed allocation will be meritorious. Besides, by the combination of static load balancing by the skewed-distributed allocation and the dynamic load balancing by dynamic ray allocation within each PE, the system performance can be further boosted. We also propose a cached frame buffer system to relieve access collision on a frame buffer.

Our objective is to resolve three types of heterogeneity - data model,database system, and semantic - in heterogeneous databases. The basic framework which we propose for this objective is realized in an autonomous decentralized database system (i.e., an interoperable database system), called Jasmine/M. Users describe their relational or object-oriented data models and schemas locally using the model primitives which Jasmine/M provides as a scripting language. Description using such primitives or scripts constitutes viewports, which have a role to resolve heterogeneity in data models and database systems at local sites. At relational viewports, both relational and object-oriented schemas defined at other sites are translated via scripts and are viewed as relational schemas. Similarly at object-oriented viewports, any schema defined at other sites is viewed object-oriented schemas. Relational and object-oriented views are used to resolve semantic heterogeneity within viewports. This paper describes a step wise approach to resolving the three types of heterogeneity, using scripts, viewports, and views, and its implementation using active objects.

New multimedia applications have emerged on top of information infrastructures, such as on-demand services, digital libraries and museums, online shopping, information Q & A, concurrent engineering, document management, and desktop program production, which require new databases. That is, next-generation database systems must enable users to efficiently and flexibly develop and execute such advanced multimedia applications. Moreover, in some applications, there is no existent data; in others, there are databases or files to be integrated. This requires both top-down and bottom-up database development. To this end, we focus on development of a database system which enables flexible and efficient acquisition, storage, access and retrieval, and distribution and presentation of large amounts of heterogeneous media data. In particular, we propose a multimedia data model as an integration of structural, temporal, spatial, and control functionality. That is, we take an approach based on an object-oriented database, which is more suitable for description of media structures and operations than a traditional relational database. And we extend the object-oriented approach by providing temporal and spatial operators, and control of distributing computing and QOS (quality of service). In this paper, we describe a multimedia data model and its efficient implementation.

In this paper, a new off-line handwritten word recognition method based on the explicit modeling of character junctures is presented. A handwritten word is regarded as a sequence of characters and junctures of four types. Hence both characters and junctures are explicitly modeled. A handwriting system employing hidden Markov models as the main statistical framework has been developed based on this scheme. An interconnection network of character and ligature models is constructed to model words of indefinite length. This model can ideally describe any form of hamdwritten words including discretely spaced words, pure cursive words, and unconstrained words of mixed styles. Also presented are efficient encoding and decoding schemes suitable for this model. The system has shown encouraging performance with a standard USPS database.

In this paper we introduce the Piecewise Linear Radial Basis Function Model (PWL-RBFM), a new nonlinear model that uses the well known RBF framework to build a PWL functional approximation by combining an l1 norm with a linear RBF function. A smooth generalization of the PWL-RBF is proposed: it is obtained by substituting the modulus function with the logistic function. These models are applied to several time series prediction tasks.

An unsupervised segmentation technique is presented that is based on a layered statistical model for both region shapes and the region internal texture signals. While the image partition is modelled as a sample of a Gibbs/Markov random field, the texture inside each image segment is described using functional approximation. The segmentation and the unknown parameters are estimated through iterative optimization of an MAP objective function. The obtained tesults are subjectively agreeable and well suited for the requirements of region-oriented transform image coding.

The structural necessary and sufficient condition for "the transition-liveness means the place-liveness and vice-versa" of a subclass NII of general Petri nets is given as "the place and transition live Petri net, or PTL net, ÑII". Furthermore, "the one-token-condition Petri net, or OTC net, II" which means that every MSDL (minimal structural deadlock) is "transition and place live" under at least one initial token, i.e., II is "transition and place live" under the above initial marking. These subclasses NII, ÑII( NII), and II(ÑII) are almost the general Petri nets except at least one MSTR(minimal structural trap) and at least one pair of "a virtual MSTR or a virtual STR" and "a virtual MSDL" of an MBTR (minimal behavioral trap) in connection with making an MSDL transition-live.

The student model component of intelligent tutoring systems (ITSs) used to be considered central: it was the means by which the ITS could individually adapt the learning experience to suit the learner's perceived needs. However, the practical difficulty of building reliable student models, the evolution away from the knowledge communication style of ITSs towards a more constructivist philosophy, and the development of new media to support learning interactions have all combined to question the role (if any) for student models in current interactive learning environments (ILEs). In this paper we will explore the new role of student models by considering the lessons learned from five Lancaster projects (SAFE, EPIC, PEOPLEPOWER, CLORIS and SMILE). The main issues revolve (as usual) around the questions of control and learning objectives.