Optimal and Suboptimal Quadriphase Sequences Derived from Maximal Length Sequences over Z _{{\bf 4}}

The paper presents families of quadriphase sequences derived from maximal length sequences over having good correlation properties. These are: (i) families of quadriphase sequences of period from maximal length sequences over ; each family consisting of sequences, (ii) families of quadriphase sequences of period from interleaved maximal length sequences over ; each family consisting of sequences. Such sequences are of interest in quadriphase modulated code division multiple access communication systems, where it is desirable to have large sets of sequences that possess low value of , the maximum magnitude of the periodic crosscorrelation and out of phase auto-correlation values. The sequences over are viewed as trace functions of appropriately chosen unit elements of Galois extension rings of . Quadriphase sequences are then obtained from sequences, by a quadriphase mapping, , from to roots of unity, given by, ; where and . Periodic correlation properties (correlation values and their distribution) of the quadriphase sequences are obtained by using an Abelian association scheme on the elements of the corresponding Galois extension ring of . The majority of the families of sequences derived are optimal with respect to the Welch lower bound on ; the rest being suboptimal with bounded by , where is the period\newpage of the sequences. However nearly half of the sequences in these families are balanced. Received July 18, 1995; revised version November 29, 1996     

An institution theory of formal meta-modelling in graphically extended BNF

Meta-modelling plays an important role in model driven software development.In this paper,a graphic extension of BNF (GEBNF) is proposed to define the abstract syntax of graphic modelling languages.Fro...     

QUICK: a tool for graphical user-interface construction by non-programmers

The last decade has placed the superiority of graphical user interfaces over traditional text-based approaches beyond dispute. In almost all contexts, users have found graphical interfaces easier to learn, faster to use, and less error-prone. However, it has been shown that the creation of powerful graphical interfaces takes up to 80% of the time required to develop an application. In our work, we seek to extend the benefits of graphical interaction to the next layer of computer user—the interface designer. Our work in this area is distinguished from other efforts by two important differences. First, while other efforts focus primarily on the design of standard user interfaces, our approach emphasizes the creation of unique and innovative interfaces by supporting, among other things, arbitrary user-designed graphical representations, direct specification of animation, and digitized sound. Second, our goal is to cater to the nonprogrammer. Thus, we address a challenging trade-off: maximizing power and flexibility in an extremely simple environment. We explore the utility of the prototype object-oriented paradigm, a high-level userinterface language, and a direct-manipulation programming environment in this context.     

Rapid software integration using structured methods

In this paper we discuss an approach to organizing the integration of 110,000 lines of C, SQL, Assembler, and microcode distributed over a network of 36 processors of four types so that it could be accomplished in six months. The software runs on a test system architecture consisting of a LAN-based workstation group and a set of VME-based embedded processors. By using structured methodology, parallelism in the integration process was achieved. The necessary stub tools were identified and developed before integration began. The principles followed and experiences of integrating the system are discussed.     

Adaptive model predictive inventory controller for multiproduct warehouse system

An inventory control system has been developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process referred to as joint replenishment. The receipt of customer orders by the warehouse proceeds in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm is developed using a periodic square wave model to represent the material flows. The adaptive concept incorporates a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The boundedness of the control output under the suggested algorithm is mathematically proven under the assumption that disturbances in the orders are bounded. The effectiveness of the scheme was demonstrated using simulations.     

Modeling time criticality of information

In this paper, we continue the research on formal treatment of attributes of information, based on the computational approach. In this scenario, the usefulness of advisory information is measured by the decrease in complexity of a problem we need to solve. We propose to model the time criticality via usefulness of a piece of information which is received during the computation. As a modeling tool, we use deterministic finite automata.     

An improved global-best harmony search algorithm for faster optimization

In this paper, an improved global-best harmony search algorithm, named IGHS, is proposed. In the IGHS algorithm, initialization based on opposition-based learning for improving the solution quality of the initial harmony memory, a new improvisation scheme based on differential evolution for enhancing the local search ability, a modified random consideration based on artificial bee colony algorithm for reducing randomness of the global-best harmony search (GHS) algorithm, as well as two perturbation schemes for avoiding premature convergence, are integrated. In addition, two parameters of IGHS, harmony memory consideration rate and pitch adjusting rate, are dynamically updated based on a composite function composed of a linear time-varying function, a periodic function and a sign function in view of approximate periodicity of evolution in nature. Experimental results tested on twenty-eight benchmark functions indicate that IGHS is far better than basic harmony search (HS) algorithm and GHS. In further study, IGHS has also been compared with other eight well known metaheuristics. The results show that IGHS is better than or at least similar to those approaches on most of test functions.     

PERIODIC CORRELATION IN STRATOSPHERIC OZONE DATA

Abstract. A 50-year time series of monthly stratospheric ozone readings from Arosa, Switzerland, is analyzed. The time series exhibits the properties of a periodically correlated (PC) random sequence with annual periodicities. Spectral properties of PC random sequences are reviewed and a test to detect periodic correlation is presented. An autoregressive moving-average (ARMA) model with periodically varying coefficients (PARMA) is fitted to the data in two stages. First, a periodic autoregressive model is fitted to the data. This fit yields residuals that are stationary but non-white. Next, a stationary ARMA model is fitted to the residuals and the two models are combined to produce a larger model for the data. The combined model is shown to be a PARMA model and yields residuals that have the correlation properties of white noise.