In this thesis, an improved genetic algorithm (GA) for multi-user detectors is investigated in synchronous and asynchronous DS-CDMA systems. Although the embedded GA and multistage detector (E-GA/MSD) can also improve the conventional GA performance for multiuser detection, the MSD incurs high computational consumption when the users are growing. To eliminate the MSD operation at each generation, an improved GA with adjustable parent size and enlarged sampling space is developed. The proposed GA with much less complexity can achieve almost the same BER performance as the E-GA/MSD. Simulation results demonstrate that the proposed GA is near to an optimum detector. Additionally, we apply the proposed GA to a spatial diversity reception assisted multiuser detector over uncorrelated flat Rayleigh fading channels in synchronous CDMA systems. As expected, computer simulations also show that the proposed GA can achieve the lower BER performance than conventional GA.

Nowadays, manufactures are under tremendous pressure to dispose product in an environmentally responsible way to pursue a sustainable development. Disassembly operations are required in the product recycling and maintenance period. An optimal disassembly sequence can reduce the disassembly cost and time. This thesis proposes an efficient method for selective disassembly sequence planning (DSP). The proposed method includes two main aspects: product representation and sequence searching. Multi-level constraint matrices based on product’s bill of material (BOM) are constructed. This representation approach can identify the product’s hierarchical structure to reduce the searching size of the sequence plans. Traversal algorithm and genetic algorithm are used to search the desired disassembly sequence. A disassembly feasibility check is integrated in the genetic algorithm to generate a better disassembly sequence with a less searching time. Several case studies are used to verify the proposed algorithms. In addition, destructive disassembly operations are considered to remove those constraints that cannot be removed by the non-destructive disassembly. / May 2016

Thesis (M.S.)--University of Tennessee, Knoxville, 2002. / Title from title page screen (viewed Sept. 6, 2002). Thesis advisor: Robert D. Hatcher. Document formatted into pages (xii, 148 p. : ill. (some col.), map). Vita. Includes bibliographical references (p. 114-118).

No description available.

No description available.

Thesis (Ed. D.)--Florida State University. / Includes bibliographical references (p. 243-251). Also issued in print.

Published also as Thesis (PH. D)--Columbia University, 1922.

Thesis (Ed. D.)--Florida State University. / Includes bibliographical references (p. 243-251).

Thesis (M.A.)--Georgia State University, 2006. / Title from title screen. Robert Adelman, committee chair; Charles Jaret, Dawn Baunach, committee members. Electronic text (92 p. : ill., col. maps) : digital, PDF file. Description based on contents viewed July 25, 2007. Includes bibliographical references (p. 86-92).

The turbine is one of the key components in gas turbine engines. To prevent the turbine blades from being badly damaged by their harsh working environment, it is necessary to keep them cool. This can be achieved by enhancement of the heat transfer performance through internal cooling passages. However, the large quantity of flow within this internal cycle inevitably results in mass flow loss, which is a major source of loss in turbomachinery. Therefore labyrinth seals are also investigated in this study, attempting to reduce the flow leakage and further increase the turbine efficiency. Large Eddy Simulation ( LES ) is used for its capability to capture the complex unsteady flow features in this study. Different rib shapes in a fully developed ribbed channel are investigated, aiming to improve the heat transfer performance. An immersed boundary method ( IBM ) is used with LES to generate complex geometries. With the use of IBM , the range of geometries can be represented on a background Cartesian grid. To obtain the best sealing performance, an investigation is undertaken into the possibility of optimising labyrinth seal planforms using a genetic algorithm ( GA ). By making use of the large number of populations, a much faster calculation can be achieved toward the objective function. Three hundred LES calculations are carried out, and an optimised design is generated that maximises the sealing effectiveness. The optimised design shows a leakage reduction of about 27.6% compared to the baseline geometry. The optimisation process employing a GA will be continued. It is expected that automated optimisation as presented will become increasingly important in the design process of future turbomachines, particularly for flows with strong parameter interactions, with an aim to further improve the overall efficiency of gas turbines.