7,749 research outputs found
Logic programming in the context of multiparadigm programming: the Oz experience
Oz is a multiparadigm language that supports logic programming as one of its
major paradigms. A multiparadigm language is designed to support different
programming paradigms (logic, functional, constraint, object-oriented,
sequential, concurrent, etc.) with equal ease. This article has two goals: to
give a tutorial of logic programming in Oz and to show how logic programming
fits naturally into the wider context of multiparadigm programming. Our
experience shows that there are two classes of problems, which we call
algorithmic and search problems, for which logic programming can help formulate
practical solutions. Algorithmic problems have known efficient algorithms.
Search problems do not have known efficient algorithms but can be solved with
search. The Oz support for logic programming targets these two problem classes
specifically, using the concepts needed for each. This is in contrast to the
Prolog approach, which targets both classes with one set of concepts, which
results in less than optimal support for each class. To explain the essential
difference between algorithmic and search programs, we define the Oz execution
model. This model subsumes both concurrent logic programming
(committed-choice-style) and search-based logic programming (Prolog-style).
Instead of Horn clause syntax, Oz has a simple, fully compositional,
higher-order syntax that accommodates the abilities of the language. We
conclude with lessons learned from this work, a brief history of Oz, and many
entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic
Programming
Functional Data Analysis in Electronic Commerce Research
This paper describes opportunities and challenges of using functional data
analysis (FDA) for the exploration and analysis of data originating from
electronic commerce (eCommerce). We discuss the special data structures that
arise in the online environment and why FDA is a natural approach for
representing and analyzing such data. The paper reviews several FDA methods and
motivates their usefulness in eCommerce research by providing a glimpse into
new domain insights that they allow. We argue that the wedding of eCommerce
with FDA leads to innovations both in statistical methodology, due to the
challenges and complications that arise in eCommerce data, and in online
research, by being able to ask (and subsequently answer) new research questions
that classical statistical methods are not able to address, and also by
expanding on research questions beyond the ones traditionally asked in the
offline environment. We describe several applications originating from online
transactions which are new to the statistics literature, and point out
statistical challenges accompanied by some solutions. We also discuss some
promising future directions for joint research efforts between researchers in
eCommerce and statistics.Comment: Published at http://dx.doi.org/10.1214/088342306000000132 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Teaching Concurrent Software Design: A Case Study Using Android
In this article, we explore various parallel and distributed computing topics
from a user-centric software engineering perspective. Specifically, in the
context of mobile application development, we study the basic building blocks
of interactive applications in the form of events, timers, and asynchronous
activities, along with related software modeling, architecture, and design
topics.Comment: Submitted to CDER NSF/IEEE-TCPP Curriculum Initiative on Parallel and
Distributed Computing - Core Topics for Undergraduate
Recommended from our members
A survey of simulation techniques in commerce and defence
Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches
Grid service orchestration using the Business Process Execution Language (BPEL)
Modern scientific applications often need to be distributed across grids. Increasingly
applications rely on services, such as job submission, data transfer or data
portal services. We refer to such services as grid services. While the invocation
of grid services could be hard coded in theory, scientific users want to orchestrate
service invocations more flexibly. In enterprise applications, the orchestration of
web services is achieved using emerging orchestration standards, most notably
the Business Process Execution Language (BPEL). We describe our experience
in orchestrating scientific workflows using BPEL. We have gained this experience
during an extensive case study that orchestrates grid services for the automation of
a polymorph prediction application
Engineering simulations for cancer systems biology
Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions
- …