An environment for knowledge discovery in biology

This paper describes a data mining environment for knowledge discovery in bioinformatics applications. The system has a generic kernel that implements the mining functions to be applied to input primary databases, with a warehouse architecture, of biomedical information. Both supervised and unsupervised classification can be implemented within the kernel and applied to data extracted from the primary database, with the results being suitably stored in a complex object database for knowledge discovery. The kernel also includes a specific high-performance library that allows designing and applying the mining functions in parallel machines. The experimental results obtained by the application of the kernel functions are reported. © 2003 Elsevier Ltd. All rights reserved.

Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: A comparison study

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

Limitantes inferiores par ao problema de dimensionamento de lotes em máquinas paralelas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sequenciamento de lotes em prensas de alta capacidade com tempo de setup dependente da sequência

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relaxação Lagrangiana Aplicada ao Problema de Dimensionamento de Lotes em Máquinas Paralelas: Limitantes Inferiores

This paper addresses the single stage lot-sizing problem in parallel machines. Each item can be produced on any machine, and incurs a setup time before to start the production. The objective of this paper is to obtain lower bounds of good quality for this problem. A solution method is developed based on a reformulation of the problem and the Lagrangian relaxation of a set of constraints. Some computational results are presented comparing the proposed method with a method from the literature and with a computational package.

Modelo de concurrencia de ADA: implementación y sus implicaciones en el interfaz con el entorno

El principal problema que impide actualmente una mayor utilización de las máquinas paralelas es la falta de herramientas de programación que permitan generar programas transportables a máquinas con diferentes prestaciones. En este trabajo se ha estudiado si los lenguajes con paralelismo explícito cumplen este requisito y son, por lo tanto, adecuados para programar este tipo de máquinas. El exceso de paralelismo, esto es, el uso de mayor paralelismo en el programa que el proporcionado por la máquina para esconder la latencia en la comunicación, se presenta en este trabajo como una solución a los problemas de eficiencia de los programas con paralelismo explícito cuando se ejecutan en máquinas que no tienen una granularidad adecuada. Con esta técnica, por lo tanto, los programas escritos con estos lenguajes pueden transportarse con eficiencia a diferentes máquinas. Para llevar a cabo el estudio de los lenguajes con paralelismo explícito, se ha desarrollado un modelo abstracto de paralelismo, en el cual un sistema está formado por una jerarquía de máquinas virtuales paralelas. Este modelo permite realizar un análisis genérico de la implementación de este tipo de lenguajes, ya sea sobre una máquina con sistema operativo o directamente sobre la máquina física. Este análisis genérico se ha aplicado a un lenguaje de este tipo, el lenguaje Ada. Se han estudiado las características específicas de Ada que pueden influir en la implementación eficiente del lenguaje, analizando también la propuesta de modificación del lenguaje correspondiente al proceso de revisión Ada 9X. Dentro del marco del modelo de paralelismo, se analiza también la problemática específica de las implementaciones del lenguaje sobre el sistema operativo. En este tipo de implementaciones, las interacciones de un programa con el entorno externo pueden causar ciertos problemas, como el bloqueo del proceso correspondiente del sistema operativo, que disminuyen el rendimiento del programa. Se analizan estos problemas y se proponen soluciones a los mismos. Se desarrolla en profundidad un ejemplo de este tipo de problemas: El acceso al estándar gráfico GKS desde Ada.---ABSTRACT---The major obstacle to the widespread utilization of the parallel machines is the lack of programming tools allowing the development of software portable between machines with different performance. This dissertation analyzes whether languages with explicit parallelism fulfil this requirement. The approach of using programs with more parallelism than available on the machine (parallel slackness) is presented. This technique can solve the efficiency problems appearing in the execution of programs with explicit parallelism over machines with a too coarse granularity. Therefore, with this approach programs can run efficiently on different machines. A new abstract model of parallelism allowing the generic study of the implementation of languages with explicit parallelism is developed. In this model, a parallel system is described by a hierarchy of parallel virtual machines. This generic analysis is applied to Ada language. Ada specific features with problematic implementation are identified and analyzed. The change proposals to Ada language in the frame of Ada 9X revisión process are also analyzed. The specific problematic of the language implementation on top of the operating system is studied under the scope of the parallelism model. With this kind of implementation, program interactions with extemal environments can lead to problems, like the blocking of the corresponding operating system process, decreasing the program execution performance. A practical example of this kind of problems, the access to GKS (Graphic Kernel System) from Ada programs, is analyzed and the implemented solution is described.

Evaluation of the JOSTLE mesh partitioning code for practical multiphysics applications

The use of unstructured mesh codes on parallel machines is one of the most effective ways to solve large computational mechanics problems. Completely general geometries and complex behaviour can be modelled and, in principle, the inherent sparsity of many such problems can be exploited to obtain excellent parallel efficiencies. However, unlike their structured counterparts, the problem of distributing the mesh across the memory of the machine, whilst minimising the amount of interprocessor communication, must be carefully addressed. This process is an overhead that is not incurred by a serial code, but is shown to rapidly computable at turn time and tailored for the machine being used.

A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem

Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

An algorithm for solving linear recurrence systems on parallel and pipelined machines /

"UILU-ENG 78 1745."

Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

The antipyretic effect of dipyrone is unrelated to inhibition of PGE(2) synthesis in the hypothalamus

BACKGROUND AND PURPOSE Bacterial lipopolysaccharide (LPS) induces fever through two parallel pathways; one, prostaglandin (PG)-dependent and the other, PG-independent and involving endothelin-1 (ET-1). For a better understanding of the mechanisms by which dipyrone exerts antipyresis, we have investigated its effects on fever and changes in PGE(2) content in plasma, CSF and hypothalamus induced by either LPS or ET-1. EXPERIMENTAL APPROACH Rats were given (i.p.) dipyrone (120 mg center dot kg-1) or indomethacin (2 mg center dot kg-1) 30 min before injection of LPS (5 mu g center dot kg-1, i.v.) or ET-1 (1 pmol, i.c.v.). Rectal temperature was measured by tele-thermometry. PGE(2) levels were determined in the plasma, CSF and hypothalamus by elisa. KEY RESULTS LPS or ET-1 induced fever and increased CSF and hypothalamic PGE(2) levels. Two hours after LPS, indomethacin reduced CSF and hypothalamic PGE(2) but did not inhibit fever, while at 3 h it reduced all three parameters. Three hours after ET-1, indomethacin inhibited the increase in CSF and hypothalamic PGE(2) levels but did not affect fever. Dipyrone abolished both the fever and the increased CSF PGE(2) levels induced by LPS or ET-1 but did not affect the increased hypothalamic PGE(2) levels. Dipyrone also reduced the increase in the venous plasma PGE(2) concentration induced by LPS. CONCLUSIONS AND IMPLICATIONS These findings confirm that PGE(2) does not play a relevant role in ET-1-induced fever. They also demonstrate for the first time that the antipyretic effect of dipyrone was not mechanistically linked to the inhibition of hypothalamic PGE(2) synthesis.