Ontologies establish a common and unambiguous terminology for knowledge formal representation and (semi-) automatic reasoning, being gradually applied in Semantic Web services. OntoClean, on the other hand, is a metho...
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ISBN:
(纸本)9781467396189
Ontologies establish a common and unambiguous terminology for knowledge formal representation and (semi-) automatic reasoning, being gradually applied in Semantic Web services. OntoClean, on the other hand, is a methodology that addresses the creation of clean ontologies, i.e. the creation of taxonomic hierarchies to model properly the concepts in the domain of discourse. Due the lack of stable implementations in the literature, this paper presents an OntoClean implementation in constraint Handling Rules (CHR), a constraint programming Prolog extension. Furthermore, it is proposed in an unprecedented way an evaluation for a Legal Ontology, highlighting the meta properties tagging for some domain concepts.
We present a new declarative compilation of logic programs with constraints into variable-free relational theories which are then executed by rewriting. This translation provides an algebraic formulation of the abstra...
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ISBN:
(纸本)9783319178226;9783319178219
We present a new declarative compilation of logic programs with constraints into variable-free relational theories which are then executed by rewriting. This translation provides an algebraic formulation of the abstract syntax of logic programs. Management of logic variables, unification, and renaming apart is completely elided in favor of algebraic manipulation of variable-free relation expressions. We prove the translation is sound, and the rewriting system complete with respect to traditional SLD semantics.
The problem studied in this paper is to schedule elective surgeries (in contrast to urgent surgeries) to multiple operating rooms (ORs) in ambulatory surgical settings. We focus on three aspects of the daily schedulin...
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The problem studied in this paper is to schedule elective surgeries (in contrast to urgent surgeries) to multiple operating rooms (ORs) in ambulatory surgical settings. We focus on three aspects of the daily scheduling decisions, including the number of ORs to open, the allocation of surgery-to-OR, and the sequence of surgeries in each OR. All the surgeries to be scheduled are known in advance, which is a common assumption for elective surgery scheduling problems. The surgeries belong to different types, and each OR can only allow certain types of surgeries to be performed. Before a surgery starts, some setup work needs to be done, such as sterilization and preparing required equipment. The setup times are assumed sequence-dependent, and both setup times and surgery durations are deterministic. The fixed costs of running the ORs are high;while sometimes overtime costs, which are even higher than the fixed costs, may occur when the surgeries cannot be done within the normal operating period of the ORs. We build a Mixed Integer Nonlinear programming (MINLP) model and a constraint programming (CP) model to solve this problem. The performance of these two models is tested on numerical examples, and the results show that the CP model is more efficient than the MINLP model in terms of the computational time and solution quality. We also examine the sensitivity of the solutions to the variation of surgery durations, and the analysis shows that the total costs do not change much when the variations of surgery durations are small. (C) 2014 Elsevier Ltd. All rights reserved.
Contemporary motor vehicles have increasing numbers of automated functions to augment the safety and comfort of a car. The automotive industry has to incorporate increasing numbers of processing units in the structure...
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Contemporary motor vehicles have increasing numbers of automated functions to augment the safety and comfort of a car. The automotive industry has to incorporate increasing numbers of processing units in the structure of cars to run the software that provides these functionalities. The software components often need access to sensors or mechanical devices which they are designed to operate. The result is a network of hardware units which can accommodate a limited number of software programs, each of which has to be assigned to a hardware unit. A prime goal of this deployment problem is to find software-to-hardware assignments that maximise the reliability of the system. In doing so, the assignments have to observe a number of constraints to be viable. This includes limited memory of a hardware unit, collocation of software components on the same hardware units, and communication between software components. Since the problem consists of many constraints with a significantly large search space, we investigate an ACO and constraint programming (CP) hybrid for this problem. We find that despite the large number of constraints, ACO on its own is the most effective method providing good solutions by also exploring infeasible regions.
Given a graph G = (S, E), the problem dealt with in this paper consists in partitioning S into a disjoint union of cliques by adding or removing a minimum number z(G) of edges. The problem, which is refered to by the ...
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ISBN:
(纸本)9783319075938;9783319075921
Given a graph G = (S, E), the problem dealt with in this paper consists in partitioning S into a disjoint union of cliques by adding or removing a minimum number z(G) of edges. The problem, which is refered to by the Zahn Problem (ZP), is NP-hard in general. This paper presents a constraint programming approach to ZP. The problem is formulated in terms of a Weighted constraint Satisfaction Problem (WCSP), a widely used framework for solving hard combinatorial problems. As a seach strategy, we applied a Limited Discrepancy Search coupled with a branch-and-bound algorithm, a combination which has proved to be very advantageous. We compared our approach to a fixed-parameter tractability algorithm, one of the most used algorithms for solving ZP. The comparison clearly show that our approach is very competitive, especially on large ZP instances.
Uncertain data due to imprecise measurements is commonly specified as bounded interval parameters in a constraint problem. For tractability reasons, existing approaches assume independence of the parameters. This assu...
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ISBN:
(纸本)9783319088556;9783319088549
Uncertain data due to imprecise measurements is commonly specified as bounded interval parameters in a constraint problem. For tractability reasons, existing approaches assume independence of the parameters. This assumption is safe, but can lead to large solution spaces, and a loss of the problem structure. In this paper we propose to combine the strengths of two frameworks to tackle parameter dependency effectively, namely constraint programming and regression analysis. Our methodology is an iterative process. The core intuitive idea is to account for data dependency by solving a set of constraint models such that each model uses data parameter instances that satisfy the dependency constraints. Then we apply a regression between the parameter instances and the corresponding solutions found to yield a possible relationship function. Our findings show that this methodology exploits the strengths of both paradigms effectively, and provides valuable insights to the decision maker by accounting for parameter dependencies.
This article presents a case study of using a constraint programming solver in a system level synthesis framework called SYLVA. The solver is used to find the repetition vector of a synchronous data flow graph and ser...
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ISBN:
(纸本)9783319104287;9783319104270
This article presents a case study of using a constraint programming solver in a system level synthesis framework called SYLVA. The solver is used to find the repetition vector of a synchronous data flow graph and serving as the design space exploration engine, which rapidly finds qualified system implementations by solving a constraint satisfaction optimization problem. Each system implementation is a combination of a number of function implementation instances and their cycle accurate execution schedules. The problem to be solved is automatically generated based on the user inputs: 1) a system model to be synthesized, 2) a library containing all the usable function implementations, 3) the performance/cost constraints, and 4) the optimization objectives. Use of constraints programming technique enabled a low cost development of design space exploration engine in addition to gaining ease of use.
Although the Steel Mill Slab problem (prob 38 of CSPLib) has already been studied by the CP community, this approach is unfortunately not used anymore by steel producers since last century. Continuous casting is prefe...
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ISBN:
(纸本)9783319104287;9783319104270
Although the Steel Mill Slab problem (prob 38 of CSPLib) has already been studied by the CP community, this approach is unfortunately not used anymore by steel producers since last century. Continuous casting is preferred instead, allowing higher throughput and better steel quality. This paper presents a CP model related to scheduling of operations for steel making with continuous casting. Activities considered range from the extraction of iron in the furnace to its casting in continuous casters. We describe the problem, detail a CP scheduling model that is finally used to solve real-life instances of some of the PSI Metals' customers.
Run-time reconfiguration has the potential to allow reuse of resources and the reduce cost of field programmable gate array (FPGA)-based systems. To compute feasible placement locations for partially reconfigurable (P...
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ISBN:
(纸本)9781479941162
Run-time reconfiguration has the potential to allow reuse of resources and the reduce cost of field programmable gate array (FPGA)-based systems. To compute feasible placement locations for partially reconfigurable (PR) modules in such systems, multiple constraints have to be evaluated. This includes unused area, placement of heterogeneous resources and communication requirements of the PR module. To improve resource utilization, both polyomino shaped PR modules and PR modules with layout variants have been suggested. In order to compute placement locations for relocatable PR modules, the embedded system has to perform more computation. In this paper, our main target is to demonstrate a constraint solver which computes placement positions at run-time. We have measured the performance of the constraint solver when executed on a MicroBlaze soft CPU. Our experiments show execution times within 30ms when executing the constraint solver on a MicroBlaze soft CPU. The results show that it is indeed feasible to compute placement positions at run time for relocatable PR modules using a constraint solver.
Background: The new biotechnologies are producing a huge amount of biological data at an accelerated speed, e.g.400Gb nucleotide sequences may be generated by one sequencing machine in one *** biomedical research lite...
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Background: The new biotechnologies are producing a huge amount of biological data at an accelerated speed, e.g.400Gb nucleotide sequences may be generated by one sequencing machine in one *** biomedical research literature is also expanding rapidly, and massive biomedical knowledge is also accumulated *** the majority of the existing machine learning algorithms only focus on the model optimization of the complete dataset, and have not interface to integrate the biological knowledge into the modeling process.
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