Hybridisation of Neural Networks and Genetic Algorithms in an Application of Time-Optimal Control

This paper presents the use of neural network and genetic algorithms in the time-optimal control of a closed loop robotics system. Radial basis function networks are used in conjunction with PID controllers in an independent joint position control to reduce tracking error. Genetic algorithm is then used to solve a multi-objective optimisation problem where decision variables are torque limits on each joint and the objective variables are trajectory time and position tracking error. This represents a task hybridisation between neural network and genetic algorithm. Two approaches with genetic algorithms are used to solve this optimisation problem: Multi-objective Genetic Algorithm (MOGA) and genetic algorithm with weighted-sum approach

Myoelectric Signals Pattern Recognition for Intelligent Functional Operation of Upper-Limb Prosthesis

This paper represents a comparative study of the classification accuracy of myoelectic signals using multi-layer perceptron with back-propagation algorithm and radial basis functions networks. The myoelectric signals considered are used to classify four upper-limb movements which are elbow bending, elbow extension, wrist pronation and wrist supination. The network structure for multi-layer perceptron is a fully connected one, while the structures used in radial basis functions network are both fully connected and partially connected. Two learning strategies are used for training radial basis networks, namely supervised selection of centres and fixed centres selected at random. The results suggest that radial-basis function network with fixed centres can generalise better than the others without enquiring extra computational effort

Runtime analysis of evolutionary multi-objective algorithms optimising the degree and diameter of spanning trees

Motivated by the telecommunication network design, we study the problem of finding diverse set of minimum spanning trees of a certain complete graph based on the two features which are maximum degree and diameter. In this study, we examine a simple multi-objective EA, GSEMO, in solving the two problems where we maximise or minimise the two features at the same time.With a rigorous runtime analysis, we provide understanding of how GSEMO optimize the set of minimum spanning trees in these two different feature spaces.Wanru Gao, Mojgan Pourhassan, Vahid Roostapour, and Frank Neuman

Comparison of the diagnostic accuracy of commercial NS1-based diagnostic tests for early dengue infection

<p>Abstract</p> <p>Background</p> <p>We compared the diagnostic accuracy and reproducibility of commercially available NS1-based dengue tests and explored factors influencing their sensitivities.</p> <p>Methods</p> <p>Paired analysis of 310 samples previously characterized as positive (n = 218) and negative (n = 92) for viral isolation and/or RT-PCR and/or IgM seroconversion. Masked samples were tested by two observers with Platelia™ Dengue NS1 Ag, second generation Pan-E™ Dengue Early ELISA, SD Dengue NS1 Ag ELISA, Dengue NS1 Ag STRIP™, and SD BIOLINE™ Dengue Duo (NS1/IgM/IgG).</p> <p>Results</p> <p>SD BIOLINE™ NS1/IgM/IgG had the highest sensitivity (80.7% 95%CI 75-85.7) with likelihood ratios of 7.4 (95%CI 4.1-13.8) and 0.21 (95%CI 0.16-0.28). The ELISA-format tests showed comparable sensitivities; all below 75%. STRIP™ and SD NS1 had even lower sensitivities (<65%). The sensitivities significantly decreased in samples taken after 3 days of fever onset, in secondary infections, viral serotypes 2 and 4, and severe dengue. Adding IgM or IgG to SD NS1 increased its sensitivity in all these situations.</p> <p>Conclusions</p> <p>The simultaneous detection of NS1/IgM/IgG would be potentially useful for dengue diagnosis in both endemic and non endemic areas. A negative result does not rule out dengue. Further studies are required to assess the performance and impact of early laboratory diagnosis of dengue in the routine clinical setting.</p

Recent Developments in the Evolution Strategies of Genetic Algorithms: Theory and Applications

This paper provides a review on current developments in genetic algorithms. The discussion includes theoretical aspects of genetic algorithms and genetic algorithm applications. Theoretical topics under review include genetic algorithm techniques, genetic operator techniques, niching techniques, genetic drift,, method of benchmarking genetic algorithm performances, measurement of difficulty level of a test-bed function,population genetics and developmental mechanism in genetic algorithms. Examples of genetic algorithm application in this review are pattern recognition, robotics, artificial life, expert system, electronic circuit design, cellular automata and biological applications.While the paper covers many works on the theory and application of genetic algorithms, not much details are reported on genetic programming, parallel genetic algorithms, in addition to more advanced techniques e.g. micro genetic algorithms and multiobjective optimisation

A Novel Model Extraction Algorithm for Reconstruction of Coupled Transmission Lines in High-speed Digital System

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A variant in the CD209 promoter is associated with severity of dengue disease

Dengue fever and dengue hemorrhagic fever are mosquitoborne viral diseases. Dendritic cell-specific ICAM-3 grabbing nonintegrin (DC-SIGN1, encoded by CD209), an attachment receptor of dengue virus, is essential for productive infection of dendritic cells. Here, we report strong association between a promoter variant of CD209, DCSIGN1-336, and risk of dengue fever compared with dengue hemorrhagic fever or population controls. The G allele of the variant DCSIGN1-336 was associated with strong protection against dengue fever in three independent cohorts from Thailand, with a carrier frequency of 4.7% in individuals with dengue fever compared with 22.4% in individuals with dengue hemorrhagic fever (odds ratio for risk of dengue hemorrhagic fever versus dengue fever: 5.84, P = 1.4 × 10-7) and 19.5% in controls (odds ratio for protection: 4.90, P = 2 × 10-6). This variant affects an Sp1-like binding site and transcriptional activity in vitro. These results indicate that CD209 has a crucial role in dengue pathogenesis, which discriminates between severe dengue fever and dengue hemorrhagic fever. This may have consequences for therapeutic and preventive strategies