Search

Our long-term project involves performing general-purpose computation on 2D amorphous computing media, which consist of arbitrary many, small, identical processing elements that are homogeneously spread in 2D Euclidian space, and that communicate locally in space. While the minimal assumptions on hardware provide the fascinating perspective of arbitrary large computing power, they also make programming notoriously difficult. Furthermore, our project involves simulating objects extended in 2D-space, called "blobs". Maintaining the connectedness of blobs while they move in space adds another layer of difficulty since it demands to process the topology of 2D space. This paper describes a new parallel data structure that can simplify the programming task, in this context. In computer graphics, processing related to 2D topology is performed by using triangle meshes. We consider synchronous media whose underlying network is also a triangle mesh. Our data structure, derived from computer graphics, is anchored on that mesh so that its operations can be compiled on the medium. More precisely, our compiler produces a circuit of logic gates, which enables a high-performance simulation, in the case of crystalline media (Cellular Automata). We demonstrate the expressiveness of the data structure's operation by using an incremental and modular programming style. We program, first small, then larger building-block functions, and re-use them. Blobs are implemented and re-used to compute the Voronoï diagram. What is the scope of the data-structure? This poses the question of whether there exists a universal set of primitives able to program any processing specified only in terms of 2D-geometry. [ABSTRACT FROM AUTHOR]

To improve the algorithmic dimension, critical thinking, and problem-solving ability of computational thinking (CT) in students' programming courses, first, a programming teaching model is constructed based on the scratch modular programming course. Secondly, the design process of the teaching model and the problem-solving model of visual programming are studied. Finally, a deep learning (DL) evaluation model is constructed, and the effectiveness of the designed teaching model is analyzed and evaluated. The T-test result of paired samples of CT is t = −2.08, P < 0.05. There are significant differences in the results of the two tests, and the designed teaching model can cause changes in students' CT abilities. The results reveal that the effectiveness of the teaching model based on scratch modular programming has been verified on the basis of experiments. The post-test values of the dimensions of algorithmic thinking, critical thinking, collaborative thinking, and problem-solving thinking are all higher than the pretest values, and there are individual differences. The P values are all less than 0.05, which testifies that the CT training of the designed teaching model has the algorithm dimension, critical thinking, collaborative thinking, and problem-solving ability of students' CT. The post-test values of cognitive load are all lower than the pretest values, indicating that the model has a certain positive effect on reducing cognitive load, and there is a significant difference between the pretest and post-test. In the dimension of creative thinking, the P value is 0.218, and there is no obvious difference in the dimensions of creativity and self-efficacy. It can be found from the DL evaluation that the average value of the DL knowledge and skills dimensions is greater than 3.5, and college students can reach a certain standard level in terms of knowledge and skills. The mean value of the process and method dimensions is about 3.1, and the mean value of the emotional attitudes and values is 2.77. The process and method, as well as emotional attitude and values, need to be strengthened. The DL level of college students is relatively low, and it is necessary to improve their DL level from the perspective of knowledge and skills, processes and methods, emotional attitudes and values. This research makes up for the shortcomings of traditional programming and design software to a certain extent. It has a certain reference value for researchers and teachers to carry out programming teaching practice. [ABSTRACT FROM AUTHOR]

A highly interactive programming system is presented which supports hierarchical and modular program development with abstraction mechanisms. By taking advantage of abstraction mechanisms, the system provides a "truly modular" environment, in which modules are constructed, debugged, verified, and compiled in a module-by-module fashion. Such an environment naturally requires system management of the information concerning ongoing program development, in the form of module databases. As a result, further problems arise as to how to modify the information in efficient and consistent ways. This paper discusses design objectives for modular programming systems by focusing on such issues as information management, interactive construction and modification of modules, separate processing, specification and verification, and supports for cooperative program development. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain.Results: We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application.Conclusions: The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB. [ABSTRACT FROM AUTHOR]

Plotkin and Pretnar's effect handlers offer a versatile abstraction for modular programming with user-defined effects. This paper focuses on foundations for implementing effect handlers, for the three different kinds of effect handlers that have been proposed in the literature: deep, shallow, and parameterised. Traditional deep handlers are defined by folds over computation trees and are the original construct proposed by Plotkin and Pretnar. Shallow handlers are defined by case splits (rather than folds) over computation trees. Parameterised handlers are deep handlers extended with a state value that is threaded through the folds over computation trees. We formulate the extensions both directly and via encodings in terms of deep handlers and illustrate how the direct implementations avoid the generation of unnecessary closures. We give two distinct foundational implementations of all the kinds of handlers we consider: a continuation-passing style (CPS) transformation and a CEK-style abstract machine. In both cases, the key ingredient is a generalisation of the notion of continuation to accommodate stacks of effect handlers. We obtain our CPS translation through a series of refinements as follows. We begin with a first-order CPS translation into untyped lambda calculus which manages a stack of continuations and handlers as a curried sequence of arguments. We then refine the initial CPS translation by uncurrying it to yield a properly tail-recursive translation and then moving towards more and more intensional representations of continuations in order to support different kinds of effect handlers. Finally, we make the translation higher order in order to contract administrative redexes at translation time. Our abstract machine design then uses the same generalised continuation representation as the CPS translation. We have implemented both the abstract machine and the CPS transformation (plus extensions) as backends for the Links web programming language. [ABSTRACT FROM AUTHOR]

Modular multiplication forms the basis of many cryptographic functions such as RSA, Diffie-Hellman key exchange, and ElGamal encryption. For large RSA moduli, combining the fast Fourier transform (FFT) with McLaughlin's Montgomery modular multiplication (MLM) has been validated to offer cost-effective implementation results. However, the conditional selections in McLaughlin's algorithm are considered to be inefficient and vulnerable to timing attacks, since extra long additions or subtractions may take place and the running time of MLM varies. In this work, we restrict the parameters of MLM by a set of new bounds and present a modified MLM algorithm involving no conditional selection. Compared to the original MLM algorithm, we inhibit extra operations caused by the conditional selections and accomplish constant running time for modular multiplications with different inputs. As a result, we improve both area-time efficiency and security against timing attacks. Based on the proposed algorithm, efficient FFT-based modular multiplication and exponentiation are derived. Exponentiation architectures with dual FFT-based multipliers are designed obtaining area-latency efficient solutions. The results show that our work offers a better efficiency compared to the state-of-the-art works from and above 2048-bit operand sizes. For single FFT-based modular multiplication, we have achieved constant running time and obtained area-latency efficiency improvements up to 24.3 percent for 1,024-bit and 35.5 percent for 4,096-bit operands, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the stability of a modular multi-level converter (MMC) based HVDC system connected to a weak ac grid. Impedance analysis is used to study the interactions between the weak ac grid and the converter. For this, the impedance of the MMC is first derived considering various outer- and inner-loop controllers. The Nyquist-stability criterion is then used to analyze the stability of the MMC connected to the weak ac grid for various case studies. The impact of circulating current controller on the stability of the MMC connected to the weak ac grid is also validated for two different types of outer-loop controllers. Finally, time-domain simulations are carried out using MATLAB/Simscape Power System toolbox to validate the analytical results. [ABSTRACT FROM AUTHOR]

This paper presents a genetic algorithm (GA) based approach for solving a multi-objective credibilistic model (MOCM) for commercial-off-the-shelf (COTS) product selection problem subject to many realistic constraints by using an exponential membership function. To solve this problem, a fuzzy technique is utilized to handle each uncertain parameter by a credibility-based model and finds a different efficient solution by taking various shape parameters in the exponential membership function subject to all resource constraints and for each objective function, aspiration level is specified by the decision maker (DM). A real-world example is provided to represent the importance of the proposed approach with data set from the realistic situation. [ABSTRACT FROM AUTHOR]

This research work evaluates the performance of a Fluid–Structure Interaction (FSI) solver, which is created using a generic interface to couple two independent software packages. The basic idea is to combine the advantages of the two independent codes to create a powerful FSI solver for two and three dimensional FSI analysis using the concept of modular programming. A detailed description about the implementation of an interface to couple a three-field system involved in the analysis is given, and this developed interface can be generalized to others codes. Since solving complex FSI problems is very time consuming, the focus of this work is placed on the performance of the coupled solver, for which a FSI benchmark will be solved on a computer cluster in order to measure speed up and efficiency. [ABSTRACT FROM AUTHOR]

Explores the parameter-related conceptions of two college students enrolled in introductory programming course in the U.S. Adjustments to formal parameter lists; Fundamental misconception of the parameter process; Improvement of student success on programming.

Although known to be very powerful, the widespread application of model-based techniques is still significantly hampered in the area of bio-processes. Reasons for this situation can be found along the whole chain to set up and implement such approaches. In a time-consuming step, models are typically hand-crafted. Whether alternatives of better models exist to actually fulfill the final goals is undocumented, most often even unknown. In a next step, model-based process control methods are hand-coded in an error-prone procedure. For many of these methods given in the literature, only simulation studies are shown, leaving the interested reader with the unanswered question whether the implementation of a specific method in a real process is viable. As the potentially time-consuming implementation of such a method presents a risk for a rapid process development, promising candidates may be overlooked. To remediate this unsatisfactory situation, a combination of theoretical methods and information technology is proposed here. By an exemplarily realized software tool, it is shown how such an environment helps to promote model-based optimization, supervision, and control of bio-processes and allows for an inexpensive test of new ideas as well in real-life experiments. The contribution concentrates on an overview of a possible software architecture with respect to necessary methods and a meaningful information strategy, highlighting some of the more crucial building blocks. Experimental results exploiting parts of the proposed methods are given for a yeast strain synthesizing a product of industrial interest. [ABSTRACT FROM AUTHOR]

Reuse in programming language development is an open research problem. Many authors have proposed frameworks for modular language development. These frameworks focus on maximizing code reuse, providing primitives for componentizing language implementations. There is also an open debate on combining feature-orientation with modular language development. Feature-oriented programming is a vision of computer programming in which features can be implemented separately, and then combined to build a variety of software products. However, even though feature-orientation and modular programming are strongly connected, modular language development frameworks are not usually meant primarily for feature-oriented language definition. In this paper we present a model of language development that puts feature implementation at the center, and describe its implementation in the Neverlang framework. The model has been evaluated through several languages implementations: in this paper, a state machine language is used as a means of comparison with other frameworks, and a JavaScript interpreter implementation is used to further illustrate the benefits that our model provides. [ABSTRACT FROM AUTHOR]

In this paper we define a formal refinement theory for a variant of Abstract State Machines (ASMs) with submachines and power cuts. The theory is motivated by the development of a verified flash file system. Different components of the system are modeled as submachines and refined individually. We define a non-atomic semantics that is suitable for considering power cuts in the middle of operations. We prove that refinement is compositional with respect to submachines and crashes. We give a criterion “crash-neutrality” and corresponding proof obligations that are sufficient to reduce non-atomic reasoning to standard pre/post verification in the context of power failures in file systems. [ABSTRACT FROM AUTHOR]

Background: Adjustment disorder is one of the most common mental health diagnoses. Still it receives relatively little attention from researchers trying to establish best interventions to treat it. With high prevalence of stressful life events, which might be leading to adjustment disorder, and limited resources of mental health service providers, online interventions could be a very practical way of helping people who have these disorders or are in the risk to develop them. The proposed study protocol is aimed to describe a randomized controlled trial of an internet-based modular intervention for adjustment disorder as it is defined in a proposal for the ICD-11. Methods/design: This study is a two-armed Randomized Controlled Trial (RCT) to examine the effectiveness of a web-based intervention BADI (Brief Adjustment Disorder Intervention) for adjustment disorder symptoms. BADI has four modules: Relaxation, Time management, Mindfulness and Strengthening relationships. It is based on stress and coping research and integrates evidence-based treatment approaches such as Cognitive Behavioural therapy (CBT), mindfulness and body-mind practices, as well as exercises for enhancing social support. Primary outcome of the study are symptoms of adjustment disorder and well-being. Engagement into the program and motivation for change is a secondary outcome. All participants after completing the baseline assessment are randomly assigned to one of the two groups: either to the one in which participant will instantly gain access to the BADI intervention or a group in which participants will be given access to the BADI program after waiting one month. Participants of BADI can choose exercises of the program flexibly. There is no particular order in which the exercises should be completed. Discussion: Study will provide new insights of modular internet-based interventions efficacy for adjustment disorders. The study will also provide information about the role of motivation and expectancies on engagement in modular internet-based interventions. In case this RCT supports effectiveness of fully automated version of BADI, it could be used very broadly. It could become a cost-effective and accessible intervention for adjustment disorder. [ABSTRACT FROM AUTHOR]

Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience, and computational benefits. We introduce the concepts of abstract inference modules and abstract modular inference systems to study general principles behind the design and analysis of model generating programs, or solvers , for integrated multi-logic systems. We show how modules and modular systems give rise to transition graphs , which are a natural and convenient representation of solvers, an idea pioneered by the SAT community. These graphs lend themselves well to extensions that capture such important solver design features as learning. In the paper, we consider two flavors of learning for modular formalisms, local and global. We illustrate our approach by showing how it applies to answer set programming, propositional logic, multi-logic systems based on these two formalisms and, more generally, to satisfiability modulo theories. [ABSTRACT FROM AUTHOR]

Reliability is a major concern in the process of software development because unreliable software can cause failure in the computer system that can be hazardous. A way to enhance the reliability of software is to detect and remove the faults during the testing phase, which begins with module testing wherein modules are tested independently to remove a substantial number of faults within a limited resource. Therefore, the available resource must be allocated among the modules in such a way that the number of faults is removed as much as possible from each of the modules to achieve higher software reliability. In this article, we discuss the problem of optimal resource allocation of the testing resource for a modular software system, which maximizes the number of faults removed subject to the conditions that the amount of testing-effort is fixed, a certain percentage of faults is to be removed and a desired level of reliability is to be achieved. The problem is formulated as a non linear programming problem (NLPP), which is modeled by the inflection S-shaped software reliability growth models (SRGM) based on a non homogeneous Poisson process (NHPP) which incorporates the exponentiated Weibull (EW) testing-effort functions. A solution procedure is then developed using a dynamic programming technique to solve the NLPP. Furthermore, three special cases of optimum resource allocations are also discussed. Finally, numerical examples using three sets of software failure data are presented to illustrate the procedure developed and to validate the performance of the strategies proposed in this article. Experimental results indicate that the proposed strategies may be helpful to software project managers for making the best decisions in allocating the testing resource. In addition, the results are compared with those of Kapur et al. (2004), Huang and Lyu (2005), and Jha et al. (2010) that are available in the literature to deal the similar problems addressed in this article. It reveals that the proposed dynamic programming method for the testing-resource allocation problem yields a gain in efficiency over other methods. [ABSTRACT FROM AUTHOR]

The paper investigates the relationships between two well-known approaches to the modelling of concurrent and distributed systems, process calculi and Petri nets. A framework for the modular encoding of process calculi into Petri nets is proposed, which is based on a reactive variant of Petri nets. In particular, two exemplary calculi are considered: (asynchronous) CCS and CSP, representing alternative interaction paradigms, namely asynchronous and (broadcast) synchronous communication. The encoding is proved to preserve as well as to reflect the operational semantics. As a consequence, it is well-behaved with respect to the standard behavioural equivalences, a fact that is exploited to perform a “technology transfer” between the two formalisms, in terms of un/decidability results for classical properties such as reachability and deadlock-freedom. The encoding highlights the expressiveness of the proposed reactive variant of nets, as well as paving the way for a fruitful integration of tools and techniques between the visual formalism of nets and the algebraic framework of processes. [ABSTRACT FROM AUTHOR]

In this paper we propose a software architecture that allows for processing of large geospatial data sets in the cloud. Our system is modular and flexible and supports multiple algorithm design paradigms such as MapReduce, in-memory computing or agent-based programming. It contains a web-based user interface where domain experts (e.g. GIS analysts or urban planners) can define high-level processing workflows using a domain-specific language (DSL). The workflows are passed through a number of components including a parser, interpreter, and a service called job manager. These components use declarative and procedural knowledge encoded in rules to generate a processing chain specifying the execution of the workflows on a given cloud infrastructure according to the constraints defined by the user. The job manager evaluates this chain, spawns processing services in the cloud and monitors them. The services communicate with each other through a distributed file system that is scalable and fault-tolerant. Compared to previous work describing cloud infrastructures and architectures we focus on the processing of big heterogeneous geospatial data. In addition to that, we do not rely on only one specific programming model or a certain cloud infrastructure but support several ones. Combined with the possibility to control the processing through DSL-based workflows, this makes our architecture very flexible and configurable. We do not only see the cloud as a means to store and distribute large data sets but also as a way to harness the processing power of distributed computing environments for large-volume geospatial data sets. The proposed architecture design has been developed for the IQmulus research project funded by the European Commission. The paper concludes with the evaluation results from applying our solution to two example workflows from this project. [ABSTRACT FROM AUTHOR]

Background The importance of digital signal processing in clinical neurophysiology is growing steadily, involving clinical researchers and methodologists. There is a need for crossing the gap between these communities by providing efficient delivery of newly designed algorithms to end users. We have developed such a tool which both visualizes and processes data and, additionally, acts as a software development platform. New method AnyWave was designed to run on all common operating systems. It provides access to a variety of data formats and it employs high fidelity visualization techniques. It also allows using external tools as plug-ins, which can be developed in languages including C++, MATLAB and Python. Results In the current version, plug-ins allow computation of connectivity graphs (non-linear correlation h2) and time-frequency representation (Morlet wavelets). The software is freely available under the LGPL3 license. Comparison with existing methods AnyWave is designed as an open, highly extensible solution, with an architecture that permits rapid delivery of new techniques to end users. Conclusions We have developed AnyWave software as an efficient neurophysiological data visualizer able to integrate state of the art techniques. AnyWave offers an interface well suited to the needs of clinical research and an architecture designed for integrating new tools. We expect this software to strengthen the collaboration between clinical neurophysiologists and researchers in biomedical engineering and signal processing. [ABSTRACT FROM AUTHOR]

Abstract: The paper considers the modular programming with hierarchically structured multi-processor tasks on top of SPMD tasks for distributed memory machines. The parallel execution requires a corresponding decomposition of the set of processors into a hierarchical group structure onto which the tasks are mapped. The result is a multi-level group SPMD computation model with varying processor group structures. The advantage of this kind of mixed task and data parallelism is a potential to reduce the communication overhead and to increase scalability. We present a runtime library to support the coordination of hierarchically structured multi-processor tasks. The library exploits an extended parallel group SPMD programming model and manages the entire task execution including the dynamic hierarchy of processor groups. The library is built on top of MPI, has an easy-to-use interface, and leads to only a marginal overhead while allowing static planning and dynamic restructuring. [Copyright &y& Elsevier]

Distributed systems are complex, being usually composed of several subsystems running in parallel. Concurrent execution and inter-process communication in these systems are prone to errors that are difficult to detect by traditional testing, which does not cover every possible program execution. Unlike testing, model checking can detect such faults in a concurrent system by exploring every possible state of the system. However, most model-checking techniques require that a system be described in a modeling language. Although this simplifies verification, faults may be introduced in the implementation. Recently, some model checkers verify program code at runtime but tend to be limited to stand-alone programs. This paper proposes cache-based model checking, which relaxes this limitation to some extent by verifying one process at a time and running other processes in another execution environment. This approach has been implemented as an extension of Java PathFinder, a Java model checker. It is a scalable and promising technique to handle distributed systems. To support a larger class of distributed systems, a checkpointing tool is also integrated into the verification system. Experimental results on various distributed systems show the capability and scalability of cache-based model checking. [ABSTRACT FROM PUBLISHER]

Abstract: Generalization, also called anti-unification, is the dual of unification. Given terms t and , a generalizer is a term of which t and are substitution instances. The dual of a most general unifier (mgu) is that of least general generalizer (lgg). In this work, we extend the known untyped generalization algorithm to, first, an order-sorted typed setting with sorts, subsorts, and subtype polymorphism; second, we extend it to work modulo equational theories, where function symbols can obey any combination of associativity, commutativity, and identity axioms (including the empty set of such axioms); and third, to the combination of both, which results in a modular, order-sorted equational generalization algorithm. Unlike the untyped case, there is in general no single lgg in our framework, due to order-sortedness or to the equational axioms. Instead, there is a finite, minimal and complete set of lggs, so that any other generalizer has at least one of them as an instance. Our generalization algorithms are expressed by means of inference systems for which we give proofs of correctness. This opens up new applications to partial evaluation, program synthesis, and theorem proving for typed equational reasoning systems and typed rule-based languages such as ASF+SDF, Elan, OBJ, Cafe-OBJ, and Maude. [Copyright &y& Elsevier]

This paper proposes implementations for both, software and hardware on Xilinx FPGAs of the Montgomery multiplication algorithm using the Separated Operand Scanning (SOS) method, which is an efficient way to compute modular multiplications. The software solution has been developed on the MicroBlaze processing platform and the hardware was carried out directly in logic and dedicated resources of the FPGA. The results are presented with a comparison between the two cases based on their performance and use of resources. [ABSTRACT FROM AUTHOR]

We consider totally unimodular (TU) stochastic programs, that is, two-stage stochastic programs whose extensive-form constraint matrix is TU. We generalize the notion of total unimodularity to apply to sets of matrices and provide properties of such sets. We provide several sufficient conditions on stochastic programs to be TU. When solving TU stochastic problems using the L-shaped method, it is not clear whether the integrality restrictions should be imposed on the master problem. Such restrictions will make each master problem more difficult to solve. On the other hand, solving the linear relaxation of the master typically means sending fractional (and unlikely optimal) solutions to the subproblems, perhaps leading to more iterations. Our computational results investigate this trade-off and provide insight into which strategy is preferable. [ABSTRACT FROM AUTHOR]

Technological artifacts such as software often comprise a large number of modules; more than twenty thousand in the case of the Java software Eclipse. While on the micro-level this system is modular, how should the building blocks be arranged on the macro-level? In the literature this question has mainly been addressed with the same arguments already used to advocate modularity on the micro-level: Dependencies should be minimized as they impede optimization and flexibility of the system. In contrast to this I argue that along with a change from the micro view to the macro view also the argumentation has to change. In this paper, I analyze the theoretical ramifications of dependency between modules on the macro-level. In particular, I argue that macro-level dependencies are first weak dependencies, and second, foster flexibility and change efficiency. This argumentation is supported by an empirical analysis of 35 software architectures. Data show that dependency relations seldom cause change propagation. Furthermore, high dependency in the architecture negatively correlates with the occurrence of large change events. Thus, higher interdependency is associated with higher evolvability and more efficient change. [ABSTRACT FROM AUTHOR]

In this paper, we discuss modular software system for Software Reliability Growth Models using testing effort and study the optimal testing effort intensity for each module. The main goal is to minimize the cost of software development when budget constraint on testing expenditure is given. We discuss the evolution of faults removal dynamics in incorporating the idea of leading /independent and dependent faults in modular software system under the assumption that testing of each of the modulus is done independently. The problem is formulated as an optimal control problem and the solution to the proposed problem has been obtained by using Pontryagin Maximum Principle. [ABSTRACT FROM AUTHOR]

There is a discription of the problems of minimization of supermodular functions on the different types of lattices: Boolean lattices, lattices with relative supplements (division lattices, lattices of vector subspaces of finite-dimensional vector space, geometrical lattices), lattices equal to Cartesian product of chains. The previously obtained theoretical results, on the basis of which the problems of minimization of supermodular functions on these lattices have been solved, are shown. A new type of lattices, lattice of Cubes, is defined and described. The problems of minimization and maximization of supermodular functions are considered on it. Particular examples of such functions are given. Optimization algorithms and the possibilities of setting and solving a new class of problems on the lattices of Cubes are discussed. [ABSTRACT FROM AUTHOR]

A logic circuit of the adaptable unit intended for controlling the processes of measurements and experimental data acquisition is presented. The adaptation to the particular measurement type is attained by combining all base components of the unit and its software in separate interchangeable program and electronic assemblies. The prototype of the unit is designed as an example of the automatic setup intended for measuring spectral dependences of physical quantities. A possibility of the adaptation is shown using the example of modifying the implemented circuit for measuring volt-ampere characteristics. [ABSTRACT FROM AUTHOR]

Abstract: A classification method of self-dual codes over is given. If with relatively prime integers r and s, then the classification can be accomplished by double coset decompositions of by automorphism groups of self-dual codes over and . We classify self-dual codes of length 4 over for all primes p in terms of their automorphism groups and then apply our method to classify self-dual codes over for arbitrary integer m. Self-dual codes of length 8 are also classified over for . [Copyright &y& Elsevier]

Abstract: Management, allocation and scheduling of heterogeneous resources for complex distributed real-time applications is a challenging problem. Timing constraints of applications may be fulfilled by the proper use of real-time scheduling policies, admission control and enforcement of timing constraints. However, it is not easy to design basic infrastructure services that allow for easy access to the allocation of multiple heterogeneous resources in a distributed environment. In this paper, we present a middleware for providing distributed soft real-time applications with a uniform API for reserving heterogeneous resources with real-time scheduling capabilities in a distributed environment. The architecture relies on standard POSIX OS facilities, such as time management and standard TCP/IP networking services, and it is designed around CORBA, in order to facilitate modularity, flexibility and portability of the applications using it. However, real-time scheduling is supported by proper extensions at the kernel-level, plugged within the framework by means of dedicated resource managers. Our current implementation on Linux supports the reservation of the CPU, disk and network bandwidth. However, additional resource managers supporting alternative real-time schedulers for these resources, as well as additional types of resources, may be easily added. We present experimental results gathered on both synthetic applications and a real multimedia video streaming case study, showing the advantages deriving from the use of the proposed middleware. Finally, overhead figures are reported, showing the sustainability of the approach for a wide class of complex, distributed, soft real-time applications. [Copyright &y& Elsevier]

The article offers information on a research that presents a method for the optimization of modularity detection algorithm for the protein-protein interaction networks. It is mentioned that Newman and Girvan (NG) algorithm is used in the domain of modularity detection. Also, the algorithm was used on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and the modules obtained were comparable with those obtained through NG algorithm, both qualitatively and quantitatively. Additionally, the proposed modules helped in reducing computational time and cost savings.

Abstract: We study the feasibility and the performance of modular design concept as applied to pattern profiling problems using artificial neural network. By decomposing the given pattern profiling problem into smaller modules, it is shown that comparable performance can be achieved with improvement on computation and design complexity. A survey of typical modular neural networks shows that large-scale nonlinear problems can alleviate its dimensionality curse with modular technique. Overview of modular neural networks based on how the problem is modularized through various decomposition and subsequent aggregation is given. A pattern recognition problem for aircraft trajectory prediction using NeuroFuzzy learning with a two stage modular learning design is presented. Decoupled data are used to train respective neural network modules. A genetic algorithm is used to aggregate all the learned modules so that it is ready for online pattern recognition purpose. As compared with the non-modular approach, the modular approach offers comparable prediction performance with significantly lower overall computation time. This study validates that modular design is a promising solution for large-scale soft computing problems. [Copyright &y& Elsevier]

The OpenAD/F tool allows the evaluation of derivatives of functions defined by a Fortran program. The derivative evaluation is performed by a Fortran code resulting from the analysis and transformation of the original program that defines the function of interest. OpenAD/F has been designed with a particular emphasis on modularity, flexibility, and the use of open source components. While the code transformation follows the basic principles of automatic differentiation, the tool implements new algorithmic approaches at various levels, for example, for basic block preaccumulation and call graph reversal. Unlike most other automatic differentiation tools, OpenAD/F uses components provided by the OpenAD framework, which supports a comparatively easy extension of the code transformations in a language-independent fashion. It uses code analysis results implemented in the OpenAnalysis component. The interface to the language-independent transformation engine is an XML-based format, specified through an XML schema. The implemented transformation algorithms allow efficient derivative computations using locally optimized cross-country sequences of vertex, edge, and face elimination steps. Specifically, for the generation of adjoint codes, OpenAD/F supports various code reversal schemes with hierarchical checkpointing at the subroutine level. As an example from geophysical fluid dynamics, a nonlinear time-dependent scalable, yet simple, barotropic ocean model is considered. OpenAD/F's reverse mode is applied to compute sensitivities of some of the model's transport properties with respect to gridded fields such as bottom topography as independent (control) variables. [ABSTRACT FROM AUTHOR]

Abstract: Aspect-Oriented Programming (AOP) is a programming paradigm that supports the modular implementation of crosscutting concerns. Thereby, AOP improves the maintainability, reusability, and configurability of software in general. Although already popular in the Java domain, AOP is still not commonly used in conjunction with C/C++. For a broad adoption of AOP by the software industry, it is crucial to provide solid language and tool support. However, research and tool development for C++ is known to be an extremely hard and tedious task, as the language is overwhelmed with interacting features and hard to analyze. Getting AOP into the C++ domain is not just technical challenge. It is also the question of integrating AOP concepts with the philosophy of the C++ language, which is very different from Java. This paper describes the design and development of the AspectC++ language and weaver, which brings fully-fledged AOP support into the C++ domain. [Copyright &y& Elsevier]

In 1999, Solinas introduced families of moduli called the generalized Mersenne numbers (GMN5), which are expressed in low-weight polynomial form, p = f(t), where is limited to a power of 2. GMNs are very useful in elliptic curve cryptosystems over prime fields since modular reduction by a GMN requires only integer additions and subtractions. However, since there are not many GMNs and each GMN requires a dedicated implementation, GMNs are hardly useful for other cryptosystems. Here, we modify GMN by removing restriction on the choice oft. and restricting the coefficients of f(t) to 0 and ±1. We call such families of moduli low-weight polynomial form integers (LWPFIs). We show an efficient modular multiplication method using LWPFI moduli. LWPFI5 allow general implementation and there exist many LWPFI moduli. One may consider LWPFIs as a trade-oft between general integers and GMNs. [ABSTRACT FROM AUTHOR]

A mixed radix-4/2 algorithm for modular multiplication/division suitable for VLSI implementation is proposed. The algorithm is based on Montgomery method for modular multiplication and on the extended Binary GCD algorithm for modular division. Both algorithms are modified and combined into the proposed algorithm so that almost all the hardware components are shared. The new algorithm carries out both calculations using simple operations such as shifts, additions, and subtractions. The radix-2 signed-digit representation is used to avoid carry propagation in all additions and subtractions. A modular multiplier/divider based on the algorithm performs an n-bit modular multiplication/division in O(n) clock cycles where the length of the clock cycle is constant and independent of n. The modular multiplier/divider has a linear array structure with a bit-slice feature and can be implemented with much smaller hardware than that necessary to implement both multiplier and divider separately. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new unified architecture that utilizes the Montgomery Multiplication algorithm to perform a modular multiplication for both integers and binary polynomials and NTRU's polynomial multiplications. The unified design is capable of supporting a majority of public-key cryptosystems such as NTRU, RSA, Diffie-Hellman key exchange, and Elliptic Curve schemes, among others. Furthermore, the architecture is highly efficient in terms of area and speed. [ABSTRACT FROM AUTHOR]

A modular mapping consists of a linear transformation followed by modulo operations. It is characterized by a transformation matrix and a vector of moduli, called the modulus vector. Modular mappings are useful to derive parallel versions of algorithms with commutative operations and algorithms intended for execution on processor arrays with toroidal networks. In order to preserve algorithm correctness, modular mappings must be injective. Results of previous work characterize injective modular mappings of rectangular index sets. This paper provides a technique to generate modular appings that satisfy these injective conditions and extends the results to general index sets. For an n-dimensional rectangular index set, the technique has O(n²n!) complexity. To facilitate generation of efficient code, modular mappings must also be reversible (i.e., have easily described inverses). An O(n²) method is provided to generate reversible modular mappings. This method reduces the search space by fixing entries of the modulus vector while attempting to minimize the number of entries to exclude few solutions. For general index sets defined by linear inequalities, injectivity can be checked by formulating and solving a set of linear inequalities. A modified Fourier-Motzkin elimination is proposed to solve these inequalities. To generate an injective modular mapping of an index set defined by linear inequalities, this paper proposes a technique that attempts to minimize the values of the entries of the modulus vector. Several examples are provided to illustrate the application of the above mentioned methods, including the case of BLAS routines. [ABSTRACT FROM AUTHOR]

FBF is a series of modular programs coded in ANSI C++ to simulate thrust and normal faulting in cross-section. The employed deformation function preserves area and therefore balanced cross-sections can be obtained with these programs. The programs run in text mode and the source code can be ported to and compiled on most computer platforms.The package consists of a preprocessor, a processor, and a postprocessor. The preprocessor generates meshes that represent stratigraphic units in their undeformed state. Units in the initial state can have tabular geometries, thin laterally, or a composite geometry. The processor carries out a forward simulation to obtain the dislocated state of the units induced by a fault of known shape and displacement. Finally, the postprocessor converts the processor output to a format suitable for plotting.The structural models obtained with the package are in good agreement with structures observed in fold-and-thrust belts and in extensional areas. Moreover, FBF can be used to test activity sequences of faults, to calculate potential fields associated with subsurface structures, and to simulate more complex geological systems and processes such as the stratigraphic response to synsedimentary brittle deformation. [Copyright &y& Elsevier]

This paper discusses an electronic course survey system designed to support evaluation of a modular programme in management taught through distance education. The scale and communication issues raised by distance education, when compounded by a complex rolling modular programme, make conventional evaluation complicated, slow and expensive. To overcome these problems, an automated evaluation process was introduced, partly based on web-based surveying, but significantly emphasising the reporting process and allowing performance indicators and complex analyses to be embedded in high quality word-processed reports, that can be quickly and easily generated after each presentation of a module. The paper discusses the system and the impact that it has had on the evaluation process, before looking to future opportunities for developments in this field, and discussing some of the implications - both expected and unanticipated - that have come out of using automation in the evaluation process. [ABSTRACT FROM AUTHOR]

Comments on an article by William Frawley which compares implicit and explicit representation and intra-modula and inter-modular processing in computer science. Illustration of predication implicitness-explicitness; Factual explicitness in inter-modular communication; Discussion of language processing.

Presents a study which investigated the generalization ability of modular architectures that implement the parity function. Significance of the design of optimal architectures to neural networks; Methods used; Findings and discussion.

Provides information on a study which presented a portable and flexible system for three-dimensional scanning. Methodology of the study; Results and discussion on the study; Conclusion.