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Programming Techniques (programming + techniques)
Selected AbstractsPLANNING IN REACTIVE ENVIRONMENTSCOMPUTATIONAL INTELLIGENCE, Issue 4 2007A. Milani The diffusion of domotic and ambient intelligence systems have introduced a new vision in which autonomous deliberative agents operate in environments where reactive responses of devices can be cooperatively exploited to fulfill the agent's goals. In this article a model for automated planning in reactive environments, based on numerical planning, is introduced. A planner system, based on mixed integer linear programming techniques, which implements the model, is also presented. The planner is able to reason about the dynamic features of the environment and to produce solution plans, which take into account reactive devices and their causal relations with agent's goals by exploitation and avoidance techniques, to reach a given goal state. The introduction of reactive domains in planning poses some issues concerning reasoning patterns which are briefly depicted. Experiments of planning in reactive domains are also discussed. [source] Communicating process architecture for multicores,CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 8 2010D. May Abstract Communicating process architecture can be used to build efficient multicore chips scaling to hundreds of processors. Concurrent processing, communications and input,output are supported directly by the instruction set of the cores and by the protocol used in the on-chip interconnect. Concurrent programs are compiled directly to the chip exploiting novel compiler optimizations. The architecture supports a variety of programming techniques, ranging from statically configured process networks to dynamic reconfiguration and mobile processes. Copyright © 2007 D. May. [source] Analog circuit design by nonconvex polynomial optimization: Two design examplesINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 1 2010Siu-Hong Lui Abstract We present a framework for synthesizing low-power analog circuits through global optimization over generally nonconvex multivariate polynomial objective function and constraints. Specifically, a nonconvex optimization problem is formed, which is then efficiently solved through convex programming techniques based on linear matrix inequality (LMI) relaxation. The framework allows both polynomial inequality and equality constraints, thereby facilitating more accurate device modelings and parameter tuning. Compared to traditional nonlinear programming (NLP), the proposed methodology exhibits superior computational efficiency, and guarantees convergence to a globally optimal solution. As in other physical design tasks, circuit knowledge and insight are critical for initial problem formulation, while the nonconvex optimization machinery provides a versatile tool and systematic way to locate the optimal parameters meeting design specifications. Two circuit design examples are given, namely, a nested transconductance(Gm),capacitance compensation (NGCC) amplifier and a delta,sigma (,,) analog-to-digital converter (ADC), both of them being the key components in many electronic systems. Copyright © 2008 John Wiley & Sons, Ltd. [source] Designing globally optimal delta,sigma modulator topologies via signomial programmingINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 3 2009Yuen-Hong Alvin Ho Abstract We present a design methodology for globally optimizing the topologies of delta,sigma modulators (DSMs). Previous work cast the design task into a general non-convex, nonlinear programming problem, whereas we propose to recast it as a signomial programming problem. Convexification strategies are presented for transforming the signomial programming problem into its equivalent convex counterpart, thereby enabling the solution of globally optimal design parameters. It is also possible to include circuit non-ideal effects that affect the transfer function of the modulator into the formulation without affecting the computational efficiency. The proposed framework has been applied to topology synthesis problems of single-loop and multi-loop low-pass DSMs based on discrete-time circuitry. Numerical results confirm the effectiveness of the proposed approach over conventional nonlinear programming techniques. Copyright © 2008 John Wiley & Sons, Ltd. [source] A new absolute stability test for systems with state-dependent perturbationsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2002M. C. de Oliveira Abstract In this paper, a new test for the absolute stability of nonlinear systems with state-dependent nonlinearities is developed. Scalar nonlinearities are assumed to lie in sectors. Using a Lur'e function as a Lyapunov function, a linear matrix inequalities (LMI) stability condition is derived. The new condition lets one go from a pure integral (Persidskii) to a pure quadratic Lyapunov function in an unified framework. Several results available in the literature are generated as particular cases of the new test. An example shows that the proposed condition can be much less conservative than available diagonal stability and passivity based methods, as the circle and Popov criteria. Tests for infinite as well as finite nonlinearity sectors can be easily generated, since the parameters of the nonlinearity sectors appear in the LMI condition in a very convenient way. This feature can also provide optimization of the absolute stability sector through convex programming techniques. Copyright © 2002 John Wiley & Sons, Ltd. [source] Application of SIC (simple interval calculation) for object status classification and outlier detection,comparison with regression approachJOURNAL OF CHEMOMETRICS, Issue 9 2004Oxana Ye. Abstract We introduce a novel approach termed simple interval calculation (SIC) for classification of object status in linear multivariate calibration (MVC) and other data analytical contexts. SIC is a method that directly constructs an interval estimator for the predicted response. SIC is based on the single assumption that all errors involved in MVC are limited. We present the theory of the SIC method and explain its realization by linear programming techniques. The primary SIC consequence is a radically new object classification that can be interpreted using a two-dimensional object status plot (OSP), ,SIC residual vs SIC leverage'. These two new measures of prediction quality are introduced in the traditional chemometric MVC context. Simple straight demarcations divide the OSP into areas which quantitatively discriminate all objects involved in modeling and prediction into four different types: boundary samples, which are the significant objects (for generating the entire data structure) within the training subset; insiders, which are samples that comply with the model; outsiders, which are samples that have large prediction errors; and finally outliers, which are those samples that cannot be predicted at all with respect to a given model. We also present detailed comparisons of the new SIC approach with traditional chemometric methods applied for MVC, classification and outlier detection. These comparisons employ four real-world data sets, selected for their particular complexities, which serve as showcases of SIC application on intricate training and test set data structures. Copyright © 2005 John Wiley & Sons, Ltd. [source] Price dynamics in the Bangladesh rice market: implications for public interventionAGRICULTURAL ECONOMICS, Issue 1 2003Donna Brennan Commodity price stabilisation; Food policy Abstract In this paper, the price dynamics of a rice market are examined using dynamic programming techniques. The model is parameterised to the case of Bangladesh and thus represents the situation of a very poor country which has characteristically high price elasticity (due to income effects) and high storage and interest costs. The incentives for private sector storage and its impact on price stability are examined. Various options for public intervention in the storage sector are also explored, including price ceiling schemes and subsidisation of storage costs. Results show that interventions that remove private disincentives (such as storage subsidies) are much cheaper than direct intervention by government, but the impact on the probability distribution of prices is quite different. The effect of trade on the probability distribution of prices is also examined. [source] Simulation and optimization of supercritical fluid purification of phytosterol estersAICHE JOURNAL, Issue 4 2009Tiziana Fornari Abstract Supercritical carbon dioxide extraction to separate phytosterol esters from fatty acid esters and tocopherols was simulated and optimized using the group contribution equation of state. Experimental extraction data at 328 K, pressures ranging from 200 to 280 bar and solvent-to-feed ratio around 25, was employed to verify the performance of the thermodynamic model. The raw material is the product obtained after a two-step enzymatic reaction carried out on soybean oil deodorizer distillates, and contains mainly fatty-acid ethyl esters, tocopherols and phytosterol esters. The extraction process was simulated using model substances to represent the complex multicomponent feed material. Nonlinear programming techniques were applied to find out optimal process conditions for a steady-state countercurrent process with partial reflux of the extract. The process optimization procedure predicts that a product with 94.2 wt % of phytosterol ester purity and 80% yield could be achieved. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems using chance constrained conditionsJOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 3 2002Masatoshi Sakawa Abstract Two major approaches to deal with randomness or ambiguity involved in mathematical programming problems have been developed. They are stochastic programming approaches and fuzzy programming approaches. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. Using chance constrained programming techniques, the stochastic programming problems are transformed into deterministic ones. As a fusion of stochastic approaches and fuzzy ones, after determining the fuzzy goals of the decision maker, interactive fuzzy satisficing methods to derive a satisficing solution for the decision maker by updating the reference membership levels is presented. Copyright © 2003 John Wiley & Sons, Ltd. [source] Energy optimization for the design of corn-based ethanol plantsAICHE JOURNAL, Issue 6 2008Ramkumar Karuppiah Abstract In this work, we address the problem of optimizing corn-based bioethanol plants through the use of heat integration and mathematical programming techniques. The goal is to reduce the operating costs of the plant. Capital cost, energy usage, and yields,all contribute to production cost. Yield and energy usage also influence the viability of corn-based ethanol as a sustainable fuel. We first propose a limited superstructure of alternative designs including the various process units and utility streams involved in ethanol production. Our objective is to determine the connections in the network and the flow in each stream in the network such that we minimize the energy requirement of the overall plant. This is accomplished through the formulation of a mixed-integer nonlinear programming problem involving short-cut models for mass and energy balances for all the units in the system, where the model is solved through two nonlinear programming subproblems. We then perform a heat integration study on the resulting flowsheet; the modified flowsheet includes multieffect distillation columns that further reduces energy consumption. The results indicate that it is possible to reduce the current steam consumption required in the transformation of corn into fuel grade ethanol by more than 40% compared to initial basic design. © 2008 American Institute of Chemical Engineers AIChE J, 2008 [source] Optimal operation of GaN thin film epitaxy employing control vector parametrizationAICHE JOURNAL, Issue 4 2006Amit Varshney Abstract An approach that links nonlinear model reduction techniques with control vector parametrization-based schemes is presented, to efficiently solve dynamic constraint optimization problems arising in the context of spatially-distributed processes governed by highly-dissipative nonlinear partial-differential equations (PDEs), utilizing standard nonlinear programming techniques. The method of weighted residuals with empirical eigenfunctions (obtained via Karhunen-Loève expansion) as basis functions is employed for spatial discretization together with control vector parametrization formulation for temporal discretization. The stimulus for the earlier approach is provided by the presence of low order dominant dynamics in the case of highly dissipative parabolic PDEs. Spatial discretization based on these few dominant modes (which are elegantly captured by empirical eigenfunctions) takes into account the actual spatiotemporal behavior of the PDE which cannot be captured using finite difference or finite element techniques with a small number of discretization points/elements. The proposed approach is used to compute the optimal operating profile of a metallorganic vapor-phase epitaxy process for the production of GaN thin films, with the objective to minimize the spatial nonuniformity of the deposited film across the substrate surface by adequately manipulating the spatiotemporal concentration profiles of Ga and N precursors at the reactor inlet. It is demonstrated that the reduced order optimization problem thus formulated using the proposed approach for nonlinear order reduction results in considerable savings of computational resources and is simultaneously accurate. It is demonstrated that by optimally changing the precursor concentration across the reactor inlet it is possible to reduce the thickness nonuniformity of the deposited film from a nominal 33% to 3.1%. © 2005 American Institute of Chemical Engineers AIChE J, 2006 [source] A mathematical programming approach for improving the robustness of least sum of absolute deviations regressionNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 4 2006Avi Giloni Abstract This paper discusses a novel application of mathematical programming techniques to a regression problem. While least squares regression techniques have been used for a long time, it is known that their robustness properties are not desirable. Specifically, the estimators are known to be too sensitive to data contamination. In this paper we examine regressions based on Least-sum of Absolute Deviations (LAD) and show that the robustness of the estimator can be improved significantly through a judicious choice of weights. The problem of finding optimum weights is formulated as a nonlinear mixed integer program, which is too difficult to solve exactly in general. We demonstrate that our problem is equivalent to a mathematical program with a single functional constraint resembling the knapsack problem and then solve it for a special case. We then generalize this solution to general regression designs. Furthermore, we provide an efficient algorithm to solve the general nonlinear, mixed integer programming problem when the number of predictors is small. We show the efficacy of the weighted LAD estimator using numerical examples. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006 [source] Evaluating the efficacy of tele-cognitive rehabilitation for functional performance in three case studiesOCCUPATIONAL THERAPY INTERNATIONAL, Issue 1 2003Dr Sing-Fai Tam PhD Associate Professor Abstract Traumatic brain injury (TBI) is one of the main causes of long-term disability, and its rehabilitation is a challenge to the healthcare team. Tele-rehabilitation, through using advancements in networking and tailor-made software, has been developed and applied to the cognitive rehabilitation of persons with brain injury in the present study. Tele-cognitive rehabilitation uses customized online computer software as a treatment mode. The online treatment software is operated on an interactive tele-communication platform , for example, video conferencing with screen sharing. Through implementing the tele-cognitive rehabilitation activities, therapists can help clients to practise and thus improve their cognitive skills through using the treatment software successfully. Moreover, hypermedia programming techniques allow the therapist to adjust the software to meet the client's treatment needs, so that the treatment is appropriate to his/her functional levels and living environment. Also the software can customize immediate visual, auditory and personalized feedback to motivate the client and training can be set at the right pace for the client's needs. The present study aimed to evaluate the effectiveness and perceived efficacy of the newly developed customized tele-cognitive rehabilitation programme for three subjects with traumatic brain injury through using single-case and qualitative research design. The cognitive factors investigated in this pilot study were, respectively, Chinese word recognition, prospective memory and semantic memory. The subjects had undergone a recruitment process with stipulated screening criteria. A single case experimental design (ABA reversal/withdrawal design) consisted of a no-intervention baseline phase (A), an intervention phase (B) and a no-intervention withdrawal phase (A). There were six sessions in each phase, making a total of 18 sessions. Tele-cognitive rehabilitation software was tailor-made according to each subject's cognitive functional needs. To monitor the change in cognitive functions, variables were tapped by tailor-made assessment and qualitative questionnaires through interviews, and they were then used to explore subjects' opinions of the programme and to test the treatment efficacy of the tele-cognitive rehabilitation programme. Finally, the relationships among the three phases were analysed through visual analysis and trend line analysis by means of the split-middle method. The three persons with brain injury showed improving trends and levels of specific cognitive performance during the treatment phase. Qualitative findings were analysed and confirmed the efficacy of the treatment module. The tele-cognitive rehabilitation approach was well received by subjects. The authors suggest that further replication studies of this kind should be conducted in the future and that more subjects should be recruited to improve the generalizability of the results. Copyright © 2003 Whurr Publishers Ltd. [source] Controller design for optimal tracking response in discrete-time systemsOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 5 2007O. A. Sebakhy Abstract The problem of designing a controller, which results in a closed-loop system response with optimal time-domain characteristics, is considered. In the approach presented in this paper, the controller order is fixed (higher than pole-placement order) and we seek a controller that results in closed-loop poles at certain desired and pre-specified locations; while at the same time the output tracks the reference input in an optimal way. The optimality is measured by requiring certain norms on the error sequence,between the reference and output signals,to be minimum. Several norms are used. First, l2 -norm is used and the optimal solution is computed in one step of calculations. Second, l, -norm (i.e. minimal overshot) is considered and the solution is obtained by solving a constrained affine minimax optimization problem. Third, the l1 -norm (which corresponds to the integral absolute error-(IAE)-criterion) is used and linear programming techniques are utilized to solve the problem. The important case of finite settling time (i.e. deadbeat response) is studied as a special case. Examples that illustrate the different design algorithms and demonstrate their feasibility are presented. Copyright © 2007 John Wiley & Sons, Ltd. [source] Artificial intelligence advancements applied in off-the-shelf controllersPROCESS SAFETY PROGRESS, Issue 2 2002Edward M. Marszal P.E. Since the earliest process units were built, CPI engineers have employed artificial intelligence to prevent losses. The expanding use of computer-based systems for process control has allowed the amount of intelligence applied in these expert systems to drastically increase. Standard methods for performing Expert System tasks are being formalized by numerous researchers in industry and academia. Work products from these groups include designs that present process hazards knowledge in a structured, hierarchical, and modular manner. Advancements in programmable logic controller (PLC) technology have created systems with substantial computing power that are robust and fault tolerant enough to be used in safety critical applications. In addition, IEC 1131-3 standardized the programming languages available in virtually every new controller. The function block language defined in IEC 1131-3 is particularly well suited to performing modular tasks, which makes it an ideal platform for representing knowledge. This paper begins by describing some of the advancements in knowledge-based systems for loss prevention applications. It then explores how standard IEC 1131-3 programming techniques can be used to build function blocks that represent knowledge of the hazards posed by equipment items. The paper goes on to develop a sample function block that represents the hazards of a pressure vessel, using knowledge developed in the API 14-C standard. [source] | |||||||||||||||||||