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The notion of a computation graph is introduced. A computation graph is a rooted, directed graph whose nodes are labelled by statements (instructions) to be executed. The motivation for developing computation graphs comes from a desire to represent programs by well‐defined, manipulable structures and to permit search (especially backtracking) to be a natural part of the execution of such programs. This initial work considers very simple computation graphs where the only statements that can be executed are assignment statements and tests. Procedure calls, parameter passing, etc. are not considered. The execution rule for computation graphs is based upon search procedures. The computation rule presented permits a computation graph to be executed depth first, breadth first or using a combination of both. This is done by defining functions, which are arguments to the computation rule, to control the traversal of the graph. The use of the rule is illustrated by describing functions to permit the rule to execute the same graph depth first and breadth first.

Anonymous distributed computing systems consist of potentially millions of heterogeneous processing nodes connected by the global Internet. These nodes can be administered by thousands of organizations and individuals, with no direct knowledge of each other. This work defines anonymous distributed computing systems in general then focuses on the specifics of an applet‐based approach for large‐scale, anonymous, distributed computing on the Internet. A user wishing to participate in a computation connects to a distribution server, which provides information about available computations, and then connects to a computation server with a computation to distribute. A Java class is downloaded, which communicates with the computation server to obtain data, performs the computation, and returns the result. Since any computer on the Internet can participate in these computations, potentially a large number of computers can participate in a single computation.

This paper aims to compare the rebate computation in Islamic sale-based financing contracts as proposed by Bank Negara Malaysia (BNM) in its guidelines on ibrāʾ (rebate) – with the rebate computation in conventional finance that is applicable to conventional loans, thus examining if there is a significant difference between the two approaches.

The paper employs the qualitative analysis method, involving review and discussion of relevant literature. Subsequently, a quantitative analysis is utilized to compare both rebate computations: the one proposed by BNM for Islamic sale-based financing contracts and the conventional finance computation that is utilized in conventional loans.

BNM's rebate computation for debts resulting from sale-based financing contracts does not differ from the conventional finance rebate computation applied to conventional loans; such similarity may raise the usury concerns that the conventional finance rebate computation raises.

The paper focuses only on the fixed profit rate rebate computation proposed by BNM guidelines.

The results highlight the need for seeking another rebate computation to be applied in Islamic financial institutions in the case of mandatory bilateral rebate for sale-based financing contracts – a computation that differs from the practice utilized in conventional loans in order to avoid any usury implications associated with conventional finance computation.

The paper examines the rebate practice proposed by BNM for sale-based financing contracts. Forcing a predetermined rebate computation in sale-based financing contracts could be plausible as BNM requires; however, the suggested computation might be questionable because it resembles conventional finance computation.

The purpose of this study is to propose an approach to avoid having to trust a single entity in cloud-based applications. In cloud computing, data processing is delegated to a remote party for efficiency and flexibility reasons. A practical user requirement usually is data privacy; hence, the confidentiality and integrity of data processing needs to be protected. In the common scenarios of cloud computing today, this can only be achieved by assuming that the remote party does not in any form act maliciously.

An approach that avoids having to trust a single entity is proposed. This approach is based on two concepts: the technical abstraction of sealed computation, i.e. a technical mechanism to confine a privacy-aware processing of data within a tamper-proof hardware container, and the role of an auditing party that itself cannot add functionality to the system but is able to check whether the system (including the mechanism for sealed computation) works as expected.

Discussion and analysis of the abstract, technical and procedural requirements of these concepts and how they can be applied in practice are explained.

A preliminary version of this paper was published in the proceedings of the second International Workshop on SECurity and Privacy Requirements Engineering (SECPRE, 2018).

Describes a system for using the World Wide Web to distribute computational tasks to multiple hosts on the Web. A programmer with a computation to distribute registers it with a Web server. An idle host uses this server to identify available computations and downloads a Java class to perform the computation ‐ we call this class a distriblet. The paper describes the programs written to carry out the load distribution, the structure of a distriblet class, and our experience in using this system.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination.

The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined.

A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency.

The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

To present a new parallel method for solving differential equations that describe transient states in physical systems.

The proposed speculative method first solves a differential equation with a large integration step to determine initial data for parallel computations in sub‐intervals of time, then speculatively computes in parallel solutions in all the sub‐intervals with a smaller integration step and finally composes the final solution from the speculatively computed ones. The basic numerical method applied is the well‐known Runge‐Kutta algorithm.

The speculative method allows important reduction of the computation time of sequential algorithms. The speed‐up of the speculative method that we propose, as compared to the sequential execution, depends on the number of sub‐intervals that are defined inside the total analysed time interval. The speed‐up increases almost linearly with the number of sub‐intervals. The good accuracy of computations in the presented example was obtained.

The proposed method can be applied to non‐linear systems without discontinuity points and to stable systems (i.e. systems insensitive to the selection of initial conditions).

The method can be especially applied for long‐lasting computations with a slow convergence of state variables values along with the decrease of integration steps.

The paper presents an original parallel method for solving differential equations, which significantly speeds up transient states analysis in physical systems.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

This paper aims to propose an Islamic compliant approach that deals with the prepayment rebate on debts resulting from cost-plus sales and their accompanied sale-based financing contracts. The proposed approach uses the time value of money concept without charging excessive fees from the debtor in the early settlement of debts.

The paper uses a qualitative analysis via analyzing and reviewing relevant literature. A quantitative analysis is subsequently used with a proposed computation that addresses prepayment rebate accompanied by debts resulting from cost-plus sales.

The proposed approach results in a rebate amount for the debtor greater than those rebate amounts resulting from either conventional finance techniques or current Islamic finance practices.

The application of the descending rebate proposed computation in this paper is restricted to cost-plus sale and their accompanied sale-based financing contracts only. The computation does not address any agreement or deal that may involve a rebate without a selling transaction.

The paper criticizes the prevailing practices for computing rebates in the case of debt prepayment, whether those nominated by conventional finance or others currently employed by most Islamic financial institutions. The paper also introduces a new rebate computation aimed to comply with Islamic finance's real context.