Primitive Constraints Research Articles

Performance Analysis of Multipliers Using Modified Gate Diffused Input Technology

The primitive constraints in any VLSI system design are power, delay and area. Systems based on CMOS logic consume more power and area. Higher power dissipation will have a direct effect on the lifetime and performance of digital systems. Adders and multipliers form the core of almost all the digital systems like Microprocessor, Digital Signal Processors (DSPs), etc., so the adders and multipliers need to be optimized in terms of power, area and delay for an efficient and cost-effective processor design. This paper presents an approach for implementing 8-bit Array multiplier, Wallace Tree multiplier and Vedic multiplier using modified Gate Diffusion Input (m-GDI) technology and comparative analysis against area, power and delay. From the analysis, it is found that multipliers, which are built on m-GDI logic, occupy less area, dissipate less power and experience less delay than the multipliers based on CMOS logic, GDI logic and Booth multiplier. Also among the three m-GDI-based multipliers, Vedic multiplier performs better in terms of area, speed and power than array multiplier and Wallace tree multiplier.

Study on intelligent collision avoidance and recovery path planning system for the waterjet-propelled unmanned surface vehicle

To avoid collision accidents and achieve independent recovery in the cluttered marine environment, this work proposes an intelligent path planning system for a waterjet-propelled unmanned surface vehicle (USV). Unlike the existing works on USV navigation systems, our study focuses on the real-time, smoothness and seaworthiness properties of the path in practical clutter environments. A hybrid A* algorithm with motion primitive constraints is proposed to generate an initial reference path. According to different types of dynamic obstacles, the International Regulations for Preventing Collisions at Sea (COLREGs) rules are used, and a local threat map based on the Apollonius circle is constructed to avoid these obstacles. Together with the motion characteristics of the waterjet-propelled USV, the Reeds-Shepp curve is used to calculate the autonomous recovery path. The performance of the proposed intelligent navigation system is verified in a practical marine environment. The experimental results show that our hybrid A* algorithm outperforms the conventional A* algorithm, and it is easy for the waterjet-propelled USV to follow the final continuous curvature path. It was demonstrated that our method can effectively avoid various static and dynamic obstacles in real time and thus help achieve autonomous recovery.

Hybrid uncertainty model for multi-state systems and linear programming-based approximations for reliability assessment

This article studies reliability assessment for Multi-State Systems (MSSs) with components states that are uncertain in both probability and performance realizations. First, we propose a model of (discrete) Hybrid Uncertainty Variable (HUV) for modeling the hybrid uncertainty of the MSS, in which both state performance levels and associated probability level are described by uncertain values. The HUV can be regarded as a generalization of random variable whose realizations and corresponding probabilities are both uncertain values. Especially the uncertain probabilities are controlled by the probability law. Leveraging the HUV-based hybrid uncertainty model, the primitive probability law is considered throughout the whole process from modeling component state probabilities, through the resulting system state probabilities, to the final reliability computations. Therefore, the information loss is reduced to a minimum. Furthermore, we develop a framework for assessing the reliability of the MSS with hybrid uncertainty. In particular, due to hybrid uncertainty considered together with the primitive probability law constraints, the reliability bound computations essentially require solving a pair of multi-linear optimization problems, which in general are non-convex and non-concave and therefore belong to a class of difficult optimization problems. Therefore, we develop a linear programming‐based cut-generation approach for solving the reliability bound assessment problem which achieves a computationally attractive approximation. Finally, the effectiveness of our approaches is validated in the case study with the comparisons to the published results.

Centralization or Decentralization in Multi-Agency Contracting Games?

We explore the strategic equivalence of the delegated menu contracting procedure in pure-strategy multi-agency games under ex post equilibrium. Our model setup permits full-blown interdependence, including information externality, contract externality, correlated types, and primitive constraints across the contracts for different agents. Our delegation principle identifies that (optimal) ex post menu design is strategically equivalent to (optimal) bilateral ex post mechanism design, which simplifies collective ex post mechanism design by ignoring relative information evaluation. Moreover, one can restrict attention to product menu design problems out of general menu design problems if the contract constraint sets have product structures. Our results still hold if we include individual rationality or any degenerated form of full-blown interdependence.

Pixel Art: Estética de la necesidad o elogio del medio

Este texto pretende exponer cómo el proceso de evolución tecnológica de la imagen digital, desde sus limitaciones primigenias hasta el momento en que pudo reproducir los recursos gráficos de los medios anteriores –principalmente la fotografía– junto a la incorporación de la tecnología 3D, ha permitido, por oposición, magnificar las características gráficas que son específicas de esta tecnología para finalmente configurar lo que podemos denominar una estética propiamente digital.<br />Vamos a centrarnos en particular en el ámbito del ocio electrónico con el objetivo de comprobar si el reciente auge de videojuegos diseñados con la estética conocida como pixel art puede deberse a las carencias técnicas de los soportes a los que va destinado –tabletas, dispositivos portátiles y teléfonos móviles, principalmente- y a la aparición de equipos de programación independientes que no cuentan con los recursos de las grandes compañías del entretenimiento, o si por el contrario, se trata de decisiones conscientes de diseño cuyas motivaciones intentaremos esclarecer aquí.

Adding partial functions to Constraint Logic Programming with sets

AbstractPartial functions are common abstractions in formal specification notations such as Z, B and Alloy. Conversely, executable programming languages usually provide little or no support for them. In this paper we propose to add partial functions as a primitive feature to a Constraint Logic Programming (CLP) language, namely {log}. Although partial functions could be programmed on top of {log}, providing them as first-class citizens adds valuable flexibility and generality to the form of set-theoretic formulas that the language can safely deal with. In particular, the paper shows how the {log} constraint solver is naturally extended in order to accommodate for the new primitive constraints dealing with partial functions. Efficiency of the new version is empirically assessed by running a number of non-trivial set-theoretical goals involving partial functions, obtained from specifications written in Z.

Deformation of objects with non-linear constraints

There are various techniques for deforming three-dimensional objects in existing computer-aided design (CAD) systems. To maintain user-specified constraints in the deformation of a parametric and feature-based model is a new challenge in deformation modelling. This article presents a constraint-based deformation technique. Firstly, a deformed object is obtained with common deformation techniques such as free-form deformation (FFD) and axial deformation. Secondly, features defined with parametric are grouped into systems of primitive constraints based on user specification. Finally, features are reconstructed by the use of optimisation technique. The optimisation is to minimise the changes in the deformed model subjected to all the provided constraints. This method allows deformations like FFD and axial deformation to be performed without destroying the constraints in the model. This method combines the advantage of free-form modelling with feature-based modelling and allows engineering design to be performed in a free-form manner.

Decentralizability of Multi-Agency Contracting with Bayesian Implementation

We modelize and investigate the analytical rationale of employing bilateral mechanism design, which simplifies collective mechanism design by ignoring relative information evaluation, in generalized multi-agency contracting games under Bayesian Nash equilibrium. We permit interdependent valuations, contract externalities, correlated types, and heterogeneous or different message sets of different agents. The delegation principle under Bayesian Nash equilibrium identifies that bilateral Bayesian mechanism design can be translated to delegated Bayesian menu design without loss of generality. We take advantage of interim-payoff-equivalence to provide economically interesting conditions on the primitives for the full equivalence in which bilateral mechanism design can be substituted for collective mechanism design. Our analysis can also incorporate individual rationality constraints. Moreover, we discuss the approximation of full equivalence and the case allowing primitive constraints across the contracts for different agents.

Delegation principle for multi-agency games under ex post equilibrium

We explore the strategic equivalence between the delegated menu contracting procedure and the centralized mechanism contracting procedure in general pure strategy multi-agency games under ex post equilibrium. We allow information externalities, contract externality, correlated types, and primitive constraints across the contracts for different agents. Our delegation principle identifies that even under this general setting ex post menu design is strategically equivalent to bilateral ex post mechanism design, which simplifies collective ex post mechanism design by ignoring relative information reference. Moreover, one can restrict attention to product menu design problems out of general menu design problems if the contract constraint sets have product structures. We provide conditions for when the principal can do strictly better by using the collective mechanism. Our results still hold if we include individual rationality or any degenerated form of our general model.

Closed and noise-tolerant patterns in n-ary relations

Binary relation mining has been extensively studied. Nevertheless, many interesting 0/1 data naturally appear as n-ary relations with n ? 3. A timely challenge is to extend local pattern extraction, eg, closed pattern mining, to such contexts. When considering higher arities, faint noise affects more and more the quality of the extracted patterns. We study a declarative specification of error-tolerant patterns by means of new primitive constraints and the design of an efficient algorithm to extract every solution pattern. It exploits the enumeration principles of the state-of-the-art Data-Peeler algorithm for n-ary relation mining. Efficiently enforcing error-tolerance crucially depends on innovative strategies to incrementally compute partial information on the data. Our prototype is tested on both synthetic and real datasets. It returns relevant collections of patterns even in the case of noisy ternary or 4-ary relations, eg, in the context of pattern discovery from dynamic networks.

Propagation algorithms for lexicographic ordering constraints

Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constraint programming to a problem, it is modelled by a set of constraints on a set of decision variables. A common modelling pattern is the use of matrices of decision variables. The rows and/or columns of these matrices are often symmetric, leading to redundancy in a systematic search for solutions. An effective method of breaking this symmetry is to constrain the assignments of the affected rows and columns to be ordered lexicographically. This paper develops an incremental propagation algorithm, GACLexLeq, that establishes generalised arc consistency on this constraint in O ( n ) operations, where n is the length of the vectors. Furthermore, this paper shows that decomposing GACLexLeq into primitive constraints available in current finite-domain constraint toolkits reduces the strength or increases the cost of constraint propagation. Also presented are extensions and modifications to the algorithm to handle strict lexicographic ordering, detection of entailment, and vectors of unequal length. Experimental results on a number of domains demonstrate the value of GACLexLeq.

When do bounds and domain propagation lead to the same search space?

This article explores the question of when two propagation-based constraint systems have the same behavior, in terms of search space. We categorize the behavior of domain and bounds propagators for primitive constraints, and provide theorems that allow us to determine propagation behaviors for conjunctions of constraints. We then show how we can use this to analyze CLP(FD) programs to determine when we can safely replace domain propagators by more efficient bounds propagators without increasing search space. Empirical evaluation shows that programs optimized by the analysis' results are considerably more efficient.

Contracting Optimally an Interval Matrix without Loosing Any Positive Semi-Definite Matrix Is a Tractable Problem

In this paper, we show that the problem of computing the smallest interval submatrix of a given interval matrix [A] which contains all symmetric positive semi-definite (PSD) matrices of [A], is a linear matrix inequality (LMI) problem, a convex optimization problem over the cone of positive semidefinite matrices, that can be solved in polynomial time. From a constraint viewpoint, this problem corresponds to projecting the global constraint PSD (A) over its domain [A]. Projecting such a global constraint, in a constraint propagation process, makes it possible to avoid the decomposition of the PSD constraint into primitive constraints and thus increases the efficiency and the accuracy of the resolution.

Extending HCLP with partially ordered hierarchies and composite constraints

. Hierarchical constraint logic programming (HCLP) extends the expressive power of constraint logic programming (CLP) by allowing both required and nonrequired constraints, making the framework suitable for resolving and relaxing overconstrained problems. Each non-required constraint in HCLP is associated with a strength and constraint strengths are totally ordered. This artificial restriction is incompatible with a sizeable class of real-life problems, in which some constraints cannot be classified as stronger or weaker than one another. Formulating this class of problems in HCLP in an ad hoc fashion would result in some valid solutions being discarded. To cope with this problem, the HCLP framework is enhanced with a theory of partially ordered constraint hierarchy, resulting in PO-HCLP. Another anomaly of HCLP is due to the frequent need to model a complex constraint using a group of primitive constraints, which is a standard practice in the constraint programming community. It is said that the primitive constraints are related. The lack of language facilities in HCLP to enforce the simultaneous satisfaction or relaxation of a group of related primitive constraints would result in nonsensical as well as valid solutions. To resolve this problem, composite constraints are introduced into (PO-)HCLP. The formal syntax and semantics of PO-HCLP are presented and the soundness and completeness of the results established. A prototype of PO-HCLP(R,W S P W) is constructed using CLP(R).

A Permutation-Based Approach for Solving the Job-ShopProblem

In this paper, we deal with the famous job-shop scheduling problem, which has been being a constant subject of study for many years due to its high computational complexity (NP-hard in the strong sense). We present a permutation-based scheme for solving the problem, which in the abstraction level differs from the classical one of Jacques Carlier and Eric Pinson. In particular, we specify the differences both in the fashion of stating the constraints (the use of the generalized sorting constraint) and in the search strategy (splitting intervals of task orders). We will first give a constraint program for solving the problem, which involves only primitive constraints and which is clean and simple to understand. We then study some special techniques based on testing variable bounds that allow us to solve two hard instances la21 and la38. These two instances have been open problems recommended in a paper of David Applegate and William Cook in 1991.

Constructive Negation of Arithmetic Constraints Using DataflowGraphs

A system which extracts a dataflow graph from sets of arithmetic constraints is described. This information is used to simplify constraints and to extract positive information from negations of constraints. The context for this work is a Prolog implementation where intervals are used to represent the underlying arithmetic variables. The system uses simple information about the existence of solutions of primitive constraints to derive the dataflow graph. This makes the system easily extensible to new primitives and domains. A practical implementation over both real and integer arithmetic is described and an extended example of its application given.

An integrated scheduling/planning environment for petrochemical production processes

Production planning/scheduling is a very difficult task because it has to deal with many conflicting constraints. Some attempts have been made to obtain an optimal solution that satisfies all constraints, but this approach is not practical, because the scheduling problem is NP-complete. This paper proposes a practical approach to actual scheduling and planning problems and describes its application to creating monthly schedules for synthetic rubber production, a typical petrochemical process. Cooperative scheduling is a new approach in which procedures, rules, and the user cooperate to make feasible schedules efficiently. The procedures, collectively called a “scheduling engine,” work as a local constraint satisfier to solve general primitive constraints. Rules that represent domain-dependent knowledge then solve domain-specific constraints by means of a pattern-matching function. Finally, the user evaluates the schedule and modifies it via a user-friendly interface with direct-manipulation functions. The user interaction is therefore included in the system architecture as a global constraint satisfier. The integrated planning and scheduling environment described here was designed within this cooperative framework. The system produces a production plan that satisfies a due date limitation, taking account of stock shortages; the plan is checked concurrently to determine whether it leads to a realizable schedule. The prototype system has been transferred to one of the major petrochemical companies in Japan, and is being tested and evaluated in an actual environment for operational use.

Introducing global constraints in CHIP

The purpose of this paper is to show how the introduction of new primitive constraints (e.g., among, diffn, cycle) over finite domains in the constraint logic programming system CHIP result in finding very rapidly good solutions for a large class of difficult sequencing, scheduling, geometrical placement and vehicle routing problems. The among constraint allows us to specify sequencing constraints in a very concise way. For the first time, the diffn constraint allows us to express and to solve directly multi-dimensional placement problems, where one has to consider nonoverlapping constraints between n-dimensional objects (e.g., rectangles, parallelepipeds). The cycle constraint makes it possible to specify a wide range of graph partitioning problems that could not yet be expressed by using current constraint logic programming languages. One of the main advantages of all these new primitives is to take into account more globally a set of elementary constraints. Finally, we point out that all the previous primitive constraints enhance the power of the CHIP system significantly, allowing us to solve real life problems that were not within reach of constraint technology before.

Cooperative scheduling and its application to steelmaking processes

A cooperative approach to scheduling problems is proposed, and its application to creating daily schedules for steelmaking processes is described. In cooperative scheduling, procedures, rules, and the user cooperate to make a feasible schedule efficiently. The procedures, collectively called a scheduling engine, work as a local constraint satisfier to solve general primitive constraints. Rules that represent domain-dependent knowledge then solve the domain-specific constraints by means of a pattern-matching function. The user evaluates the schedule and modifies it by means of a user-friendly interface with direct-manipulation functions. The user interaction is therefore included in the system architecture as a global constraint satisfier. The iteration of this cycle improves the schedule until it becomes feasible. Experimental results obtained with Scheplan, the scheduling environment that applies this approach to scheduling steelmaking processes, show that the daily scheduling time is much less than in manual scheduling and the quality of the schedule is much improved. >