A Heuristic Algorithm for Optimal Hamiltonian Cycles in Weighted Graphs

Abstract. The paper focuses on finding of the optimal Hamiltonian cycle, when it is regarded with respect to cost, time, distance or difficulty level of the route. The problem is strictly related to the traveling salesman problem proved to be NP-complete for general graphs. The paper gives a heuristic algorithm for finding the optimal spanning cycle in a weighted graph. Its idea is based on optimization of weight losses and reduction the complexity of a problem by reduction the dimension of the graph payoff matrix.&nbsp

Desafios para a implantação de soluções de integração de aplicações empresariais em provedores de computação em nuvem

Nos últimos anos o campo de estudos conhecido como Integração de Aplicações Empresariais tem desempenhado um importante papel ao proporcionar metodologias, técnicas e ferramentas para que as empresas possam desenvolver soluções de integração, visando reutilizar suas aplicações e dar suporte às novas demandas que surgem com a evolução dos seus processos de negócio. A Computação em Nuvem é parte de uma nova realidade, na qual tanto pequenas como grandes empresas têm a sua disposição uma infraestrutura de TI de alta capacidade, a um baixo custo, na qual podem implantar e executar suas soluções de integração. O modelo de cobrança adotado pelos provedores de Computação em Nuvem se baseia na quantidade de recursos computacionais consumidos por uma solução de integração. Tais recursos podem ser conhecidos, basicamente, de duas formas distintas: a partir da execução real de uma solução de integração em um motor de orquestração, ou a partir da simulação do modelo conceitual que descreve a solução sem que a mesma tenha que ser previamente implementada. Ainda, é desejável que os provedores proporcionem modelos conceituais que descrevam detalhadamente a variabilidade de serviços e as restrições entre eles. A revisão da literatura técnica e científica evidencia que não existem metodologias, técnicas e ferramentas para estimar a demanda de recursos computacionais consumidos por soluções de integração, a partir de seus modelos conceituais. Além disso, os provedores de Computação em Nuvem não possuem ou disponibilizam os modelos conceituais dos serviços que possam ser contratados. Tais questões constituem a base para que se possa estabelecer um processo e desenvolver ferramentas de apoio a tomada de decisão para a implantação de soluções de integração de aplicações empresariais em provedores de Computação em Nuvem

Purposeful selection of variables in logistic regression

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Time-Optimal Trajectory Generation and Way-Point Sequencing for 5-Axis Laser Drilling

Laser drilling provides a highly productive method for producing arrays of holes on planar and freeform shaped components. Industrial applications include fuel injection nozzles, printed circuit boards (PCB’s), inkjet printer heads, pinholes and slits for scientific instrumentation, high-resolution circuitry, sensors, fiber-optic interconnects, medical devices, and gas turbine combustion chamber panels. This thesis deals with time-optimal trajectory planning for two mainstream laser drilling methods: on-the-fly drilling and percussion drilling, which are used in the aerospace industry. The research has been conducted in collaboration with the Canadian aero-engine producer, Pratt & Whitney Canada (P&WC). The algorithms developed have been tested in a target application involving the laser drilling of cooling hole arrays on gas turbine engine combustion chamber panels. On-the-fly drilling is an operation in which each hole receives one low powered shot at a time while the workpiece is in motion, and the beam focal point is continuously proceeding to the next hole location. The positioning sequence repeats itself until all holes are gradually opened up in small increments. Each hole location has ample time to cool down before the next shot is received. Thus, this process can yield favorable material properties in terms of preserving the desired crystal structure, and also hole quality in terms of dimensional (size) and form (shape) accuracy, due to the reduction of local thermal loading. However, there is no existing trajectory planner, in industry, or in literature, capable of generating time-optimized positioning trajectories for on-the-fly laser drilling. This thesis studies this problem and presents a new algorithm, capable of handling 5 degree-of-freedom (axis) positioning capability. The ability to generate spline-based smooth trajectories is integrated within a Traveling Salesman Problem (TSP) type sequencing algorithm. The sequencing algorithm optimizes both the order of the waypoints (i.e., hole locations) and also the timing levels in between, which affect the temporal (time-dependent) nature of the motions commanded to the laser drilling machine’s actuators. Furthermore, the duration between consecutive holes has to be an integer multiple of the laser pulsing period, considering a machine configuration in which the laser is firing at a constant frequency, and unused pulses are diverted away using a quick shutter. It is shown that the proposed algorithm is capable of generating 17-25% reduction in the beam positioning time spent during a manufacturing cycle, compared to some of the contemporary practices in industry. 17% reduction in the vibrations induced onto the laser optics is also observed, which helps prevent downtime due to the optics hardware gradually losing alignment. The second type of laser drilling operation for which optimized 5-axis trajectory planning has been developed is percussion drilling. In this process, a series of pulses are sent to each hole while the part is stationary. Once the hole is completely opened up, then positioning to the next hole proceeds. While percussion drilling is less advantageous in terms of local thermal loading and achievable part quality, it is used extensively in industry; due to its simplicity of automation compared to on-the-fly drilling. Thus, a TSP-style trajectory planning algorithm has also been developed for percussion laser drilling. The novelty, in this case, is concurrent planning of 5-axis time-optimal point-to-point movements within the sequencing algorithm, and direct minimization of the total travel time, rather than just distance (in two Cartesian axes); as is the method for which significant portion of TSP solvers and trajectory planners in literature have been developed. Compared to currently applied methods at P&WC, 32-36% reduction in the beam positioning time has been achieved. Also, 39-45% reduction in the peak magnitude of vibration has been realized. Limited benchmarking with state-of-the-art TSP solvers from combinatorial mathematics, considering only 2-axis Euclidean distance as the objective function, indicate that the proposed sequencing algorithm for percussion drilling is sub-optimal by 9-12%. Thus, it can still use further improvement in future research. Nevertheless, the two trajectory planners that have been developed in this thesis for on-the-fly drilling and percussion drilling have experimentally demonstrated very promising improvements in terms of motion time and smoothness. As more advanced Computer Numerical Control (CNC) systems and laser control electronics with deterministic execution and rapid synchronization capability become available, such algorithms are expected to facilitate significant production gains in laser drilling processes used in different industries

The design and implementation of a system for the automatic generation of narrative debriefs for AUV Missions

Increased autonomy allows autonomous underwater vehicles to act without direct support or supervision. This requires increased complexity, however, and a deficit of trust may form between operators and these complex machines, though previous research has shown this can be reduced through repeated experience with the system in question. Regardless of whether a mission is performed with real vehicles or their simulated counterparts, effective debrief represents the most efficient method for performing an analysis of the mission. A novel system is presented to maximise the effectiveness of a debrief by ordering the mission events using a narrative structure, which has been shown to be the quickest and most effective way of communicating information and building a situation model inside a person’s mind. Mission logs are de-constructed and analysed, then optimisation algorithms used to generate a coherent discourse based on the events of the missions with any required exposition. This is then combined with a timed mission playback and additional visual information to form an automated mission debrief. This approach was contrasted with two alternative techniques: a simpler chronological ordering; and a facsimile of the current state of the art. Results show that participant recall accuracy was higher and the need for redundant delivery of information was lower when compared to either of the baselines. Also apparent is a need for debriefs to be adapted to individual users and scenarios. Results are discussed in full, along with suggestions for future avenues of research