The influence of cluster emission and the symmetry energy on neutron-proton spectral double ratios

Emissions of free neutrons and protons from the central collisions of 124Sn+124Sn and 112Sn+112Sn reactions are simulated using the Improved Quantum Molecular Dynamics model with two different density dependence of the symmetry energy in the nuclear equation of state. The constructed double ratios of the neutron to proton ratios of the two reaction systems are found to be sensitive to the symmetry terms in the EOS. The effect of cluster formation is examined and found to affect the double ratios mainly in the low energy region. In order to extract better information on symmetry energy with transport models, it is therefore important to have accurate data in the high energy region which also is affected minimally by sequential decays.Comment: 11 pages, 4 figure

Heavy Residue Isoscaling as a Probe of the Process of N/Z Equilibration

The isotopic and isobaric scaling behavior of the yield ratios of heavy projectile residues from the collisions of 25 MeV/nucleon 86Kr projectiles on 124Sn and 112Sn targets is investigated and shown to provide information on the process of N/Z equilibration occurring between the projectile and the target. The logarithmic slopes $\alpha$ and $\beta^{'}$ of the residue yield ratios with respect to residue neutron number N and neutron excess N--Z are obtained as a function of the atomic number Z and mass number A, respectively, whereas excitation energies are deduced from velocities. The relation of the isoscaling parameters $\alpha$ and $\beta^{'}$ with the N/Z of the primary (excited) projectile fragments is employed to gain access to the degree of N/Z equilibration prior to fragmentation as a function of excitation energy. A monotonic relation between the N/Z difference of fragmenting quasiprojectiles and their excitation energy is obtained indicating that N/Z equilibrium is approached at the highest observed excitation energies. Simulations with a deep-inelastic transfer model are in overall agreement with the isoscaling conclusions. The present residue isoscaling approach to N/Z equilibration offers an attractive tool of isospin and reaction dynamics studies in collisions involving beams of stable or rare isotopes.Comment: 15 pages, 4 figures, submitted to Phys. Lett.

Efficient Optimization of Performance Measures by Classifier Adaptation

In practical applications, machine learning algorithms are often needed to learn classifiers that optimize domain specific performance measures. Previously, the research has focused on learning the needed classifier in isolation, yet learning nonlinear classifier for nonlinear and nonsmooth performance measures is still hard. In this paper, rather than learning the needed classifier by optimizing specific performance measure directly, we circumvent this problem by proposing a novel two-step approach called as CAPO, namely to first train nonlinear auxiliary classifiers with existing learning methods, and then to adapt auxiliary classifiers for specific performance measures. In the first step, auxiliary classifiers can be obtained efficiently by taking off-the-shelf learning algorithms. For the second step, we show that the classifier adaptation problem can be reduced to a quadratic program problem, which is similar to linear SVMperf and can be efficiently solved. By exploiting nonlinear auxiliary classifiers, CAPO can generate nonlinear classifier which optimizes a large variety of performance measures including all the performance measure based on the contingency table and AUC, whilst keeping high computational efficiency. Empirical studies show that CAPO is effective and of high computational efficiency, and even it is more efficient than linear SVMperf.Comment: 30 pages, 5 figures, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence, 201

Investigation of refractory dielectric for integrated circuits Second quarterly report, Dec. 1968

Process development for chemical deposition of aluminum oxide films as refractory dielectrics for integrated circuit

Investigation of refractory dielectric for integrated circuits Third quarterly report, Feb. 1969

Research and development on refractory dielectrics for integrated circuit

Occupational Therapy in Hand Rehabilitation

Department of Rehabilitation Science

Learning to locate relative outliers

Outliers usually spread across regions of low density. However, due to the absence or scarcity of outliers, designing a robust detector to sift outliers from a given dataset is still very challenging. In this paper, we consider to identify relative outliers from the target dataset with respect to another reference dataset of normal data. Particularly, we employ Maximum Mean Discrepancy (MMD) for matching the distribution between these two datasets and present a novel learning framework to learn a relative outlier detector. The learning task is formulated as a Mixed Integer Programming (MIP) problem, which is computationally hard. To this end, we propose an effective procedure to find a largely violated labeling vector for identifying relative outliers from abundant normal patterns, and its convergence is also presented. Then, a set of largely violated labeling vectors are combined by multiple kernel learning methods to robustly locate relative outliers. Comprehensive empirical studies on real-world datasets verify that our proposed relative outlier detection outperforms existing methods. © 2011 S. Li & I.W. Tsang