Although the technology exists for more advanced applications of automated guided vehicles in flexible manufacturing systems, the current employment of these vehicles in material handling generally subscribes to a simple mode of operation: single-load-carrying capacity for each vehicle and unidirectional traffic on each route of the system. Through a simulation programme, this study investigates the.effect of several key factors related to the automated guided vehicles on the overall performance of a flexible manufacturing system. These are the number of pallets allowed in the system, the number of vehicles used and the carrying capacity of each and the input and output queue capacities of the machining stations; finally bidirectional traffic is allowed in some routes. The results show that there is a strong interaction among these factors and reveal their combined effects on the throughput from a small flexible manufacturing system. Upon the user's request, the simulation program also provides the animated colour graphics of the system to view developments concurrently under the selected decision values through time.

The influenza A virus is a negative-stranded RNA virus composed of eight segmented RNA molecules, including polymerases (PB2, PB1, PA), hemagglutinin (HA), nucleoprotein (NP), neuraminidase (NA), matrix protein (MP), and nonstructure gene (NS). The influenza A viruses are notorious for rapid mutations, frequent reassortments, and possible recombinations. Among these evolutionary events, reassortments refer to exchanges of discrete RNA segments between co-infected influenza viruses, and they have facilitated the generation of pandemic and epidemic strains. Thus, identification of reassortments will be critical for pandemic and epidemic prevention and control. This paper presents a reassortment identification method based on distance measurement using complete composition vector (CCV) and segment clustering using a minimum spanning tree (MST) algorithm. By applying this method, we identified 34 potential reassortment clusters among 2,641 PB2 segments of influenza A viruses. Among the 83 serotypes tested, at least 56 (67.46%) exchanged their fragments with another serotype of influenza A viruses. These identified reassortments involve 1,957 H2N1 and 1,968 H3N2 influenza pandemic strains as well as H5N1 avian influenza virus isolates, which have generated the potential for a future pandemic threat. More frequent reassortments were found to occur in wild birds, especially migratory birds. This MST clustering program is written in Java and will be available upon request.

We present PEACE, a stand-alone tool for high-throughput ab initio clustering of transcript fragment sequences produced by Next Generation or Sanger Sequencing technologies. It is freely available from www.peace-tools.org. Installed and managed through a downloadable user-friendly graphical user interface (GUI), PEACE can process large data sets of transcript fragments of length 50 bases or greater, grouping the fragments by gene associations with a sensitivity comparable to leading clustering tools. Once clustered, the user can employ the GUI's analysis functions, facilitating the easy collection of statistics and allowing them to single out specific clusters for more comprehensive study or assembly. Using a novel minimum spanning tree-based clustering method, PEACE is the equal of leading tools in the literature, with an interface making it accessible to any user. It produces results of quality virtually identical to those of the WCD tool when applied to Sanger sequences, significantly improved results over WCD and TGICL when applied to the products of Next Generation Sequencing Technology and significantly improved results over Cap3 in both cases. In short, PEACE provides an intuitive GUI and a feature-rich, parallel clustering engine that proves to be a valuable addition to the leading cDNA clustering tools.

Graphical programming, which is used here to mean creation of simulation models graphically, has been used in conjunction with conventional simulation languages via block diagrams or activity networks. Its beneficial effects on model development in simulation have been generally accepted. However, none of these conventional simulation languages has reached a level of graphical programming that would impact the user's programming task substantially. Today, this is possible with the current software and hardware technology. An interactive incremental programming environment supported by a good graphical programming system that helps automatic model development, specification and verification would be greatly appreciated in modeling in general, but especially in simulation of complex real-life systems. Such a visual system could essentially be a conceptual framework for analysis of the problem at hand and become a means of communication among the people who are involved in development and management of systems. It can also be the friendly interface that forms a communication medium between the modeler and the computer for automatic programming.In this research paper, a prototype graphical programming methodology for modeling and automatic interpretation of simulation problems is developed in the object-oriented environment of the Smalltalk-80 language. The modeler uses a high-level graphical representation formalism based on the activity-cycle diagrams to define simulation models in an interactive mode. These activity-cycle diagrams can then be interpreted into the underlying programming language and executed automatically. Thus, the modeler does not have to know the underlying Smalltalk 80 language in order to use our prototype simulation system. The future expansions to this system will include a simulation object editor, a graphical output view system and a richer high-level concept base for modeling purpose.

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Reservoir operation problems are complicated by the nonlinearities in the objective functions. The dynamic programing (DP) procedure is often used to solve this problem because of the sequential nature of the decisions involved, but for simultaneous operations of multireservoir systems, other DP‐based techniques are frequently found to be more efficient in overcoming the curse of dimensionality problem caused by the interdependencies of the decisions. In this paper, another DP‐based procedure is proposed which performs better than the other well‐known techniques. The applications of this technique are presented in two different formulations for four‐reservoir operation problems. The convergence properties of the algorithm are investigated as revealed from the systematic solutions of a control problem with various dimensions.

The solution technique developed in this paper integrates the simplex search algorithm into the recursive calculations of dynamic programming in order to mitigate the "curse-of-dimensionality." Since differentiation is not required as a means of optimization procedure, it is expected that this technique will have an important impact on planning problems, such as the multiple resource allocation problems which involve nondifferentiable and/or highly nonlinear performance functions. Applications of the technique to very complex problems seem to confirm the anticipated polynomial average performance.dynamic programming, simplex search

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